JP7650019B2 - Method for estimating amount of nerve fibers in dermis, method for estimating skin blemish concentration and/or risk of blemish occurrence - Google Patents
Method for estimating amount of nerve fibers in dermis, method for estimating skin blemish concentration and/or risk of blemish occurrence Download PDFInfo
- Publication number
- JP7650019B2 JP7650019B2 JP2020148087A JP2020148087A JP7650019B2 JP 7650019 B2 JP7650019 B2 JP 7650019B2 JP 2020148087 A JP2020148087 A JP 2020148087A JP 2020148087 A JP2020148087 A JP 2020148087A JP 7650019 B2 JP7650019 B2 JP 7650019B2
- Authority
- JP
- Japan
- Prior art keywords
- skin
- nerve fibers
- dermis
- amount
- estimating
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 210000003491 skin Anatomy 0.000 title claims description 177
- 210000004126 nerve fiber Anatomy 0.000 title claims description 156
- 210000004207 dermis Anatomy 0.000 title claims description 106
- 238000000034 method Methods 0.000 title claims description 61
- 238000003860 storage Methods 0.000 claims description 22
- 230000002500 effect on skin Effects 0.000 claims description 18
- 210000001519 tissue Anatomy 0.000 description 48
- 210000002752 melanocyte Anatomy 0.000 description 28
- OKKJLVBELUTLKV-UHFFFAOYSA-N Methanol Chemical compound OC OKKJLVBELUTLKV-UHFFFAOYSA-N 0.000 description 24
- 210000002615 epidermis Anatomy 0.000 description 23
- 108700019745 Disks Large Homolog 4 Proteins 0.000 description 17
- 102000047174 Disks Large Homolog 4 Human genes 0.000 description 17
- IAZDPXIOMUYVGZ-UHFFFAOYSA-N Dimethylsulphoxide Chemical compound CS(C)=O IAZDPXIOMUYVGZ-UHFFFAOYSA-N 0.000 description 15
- 238000012360 testing method Methods 0.000 description 14
- 238000010586 diagram Methods 0.000 description 13
- 210000005036 nerve Anatomy 0.000 description 13
- 208000012641 Pigmentation disease Diseases 0.000 description 12
- 238000011161 development Methods 0.000 description 11
- 239000002537 cosmetic Substances 0.000 description 10
- 210000004027 cell Anatomy 0.000 description 9
- 238000005259 measurement Methods 0.000 description 9
- 239000000463 material Substances 0.000 description 8
- 230000000694 effects Effects 0.000 description 7
- 230000019612 pigmentation Effects 0.000 description 7
- 241000283074 Equus asinus Species 0.000 description 6
- XUMBMVFBXHLACL-UHFFFAOYSA-N Melanin Chemical compound O=C1C(=O)C(C2=CNC3=C(C(C(=O)C4=C32)=O)C)=C2C4=CNC2=C1C XUMBMVFBXHLACL-UHFFFAOYSA-N 0.000 description 6
- WYURNTSHIVDZCO-UHFFFAOYSA-N Tetrahydrofuran Chemical compound C1CCOC1 WYURNTSHIVDZCO-UHFFFAOYSA-N 0.000 description 6
- 238000012795 verification Methods 0.000 description 6
- 230000008859 change Effects 0.000 description 5
- 230000006870 function Effects 0.000 description 5
- 230000037311 normal skin Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 210000001044 sensory neuron Anatomy 0.000 description 5
- 238000010186 staining Methods 0.000 description 5
- 210000000225 synapse Anatomy 0.000 description 5
- 102100030310 5,6-dihydroxyindole-2-carboxylic acid oxidase Human genes 0.000 description 4
- 206010014970 Ephelides Diseases 0.000 description 4
- 101000773083 Homo sapiens 5,6-dihydroxyindole-2-carboxylic acid oxidase Proteins 0.000 description 4
- 208000003351 Melanosis Diseases 0.000 description 4
- 238000003501 co-culture Methods 0.000 description 4
- 238000007796 conventional method Methods 0.000 description 4
- 210000002966 serum Anatomy 0.000 description 4
- 230000002087 whitening effect Effects 0.000 description 4
- YMWUJEATGCHHMB-UHFFFAOYSA-N Dichloromethane Chemical compound ClCCl YMWUJEATGCHHMB-UHFFFAOYSA-N 0.000 description 3
- 239000013504 Triton X-100 Substances 0.000 description 3
- 229920004890 Triton X-100 Polymers 0.000 description 3
- 230000000903 blocking effect Effects 0.000 description 3
- 230000000052 comparative effect Effects 0.000 description 3
- 238000000491 multivariate analysis Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000000611 regression analysis Methods 0.000 description 3
- YLQBMQCUIZJEEH-UHFFFAOYSA-N tetrahydrofuran Natural products C=1C=COC=1 YLQBMQCUIZJEEH-UHFFFAOYSA-N 0.000 description 3
- HMUNWXXNJPVALC-UHFFFAOYSA-N 1-[4-[2-(2,3-dihydro-1H-inden-2-ylamino)pyrimidin-5-yl]piperazin-1-yl]-2-(2,4,6,7-tetrahydrotriazolo[4,5-c]pyridin-5-yl)ethanone Chemical compound C1C(CC2=CC=CC=C12)NC1=NC=C(C=N1)N1CCN(CC1)C(CN1CC2=C(CC1)NN=N2)=O HMUNWXXNJPVALC-UHFFFAOYSA-N 0.000 description 2
- LDXJRKWFNNFDSA-UHFFFAOYSA-N 2-(2,4,6,7-tetrahydrotriazolo[4,5-c]pyridin-5-yl)-1-[4-[2-[[3-(trifluoromethoxy)phenyl]methylamino]pyrimidin-5-yl]piperazin-1-yl]ethanone Chemical compound C1CN(CC2=NNN=C21)CC(=O)N3CCN(CC3)C4=CN=C(N=C4)NCC5=CC(=CC=C5)OC(F)(F)F LDXJRKWFNNFDSA-UHFFFAOYSA-N 0.000 description 2
- 239000012099 Alexa Fluor family Substances 0.000 description 2
- DHMQDGOQFOQNFH-UHFFFAOYSA-N Glycine Chemical compound NCC(O)=O DHMQDGOQFOQNFH-UHFFFAOYSA-N 0.000 description 2
- 241000282412 Homo Species 0.000 description 2
- 241001465754 Metazoa Species 0.000 description 2
- 102100025038 Ubiquitin carboxyl-terminal hydrolase isozyme L1 Human genes 0.000 description 2
- 101710186825 Ubiquitin carboxyl-terminal hydrolase isozyme L1 Proteins 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 239000003153 chemical reaction reagent Substances 0.000 description 2
- 238000012258 culturing Methods 0.000 description 2
- 238000005520 cutting process Methods 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- MHDVGSVTJDSBDK-UHFFFAOYSA-N dibenzyl ether Chemical compound C=1C=CC=CC=1COCC1=CC=CC=C1 MHDVGSVTJDSBDK-UHFFFAOYSA-N 0.000 description 2
- 229940079593 drug Drugs 0.000 description 2
- 239000003814 drug Substances 0.000 description 2
- 230000009977 dual effect Effects 0.000 description 2
- 210000001061 forehead Anatomy 0.000 description 2
- 238000007654 immersion Methods 0.000 description 2
- 238000012744 immunostaining Methods 0.000 description 2
- 210000002569 neuron Anatomy 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 108090000623 proteins and genes Proteins 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 230000001629 suppression Effects 0.000 description 2
- FWBHETKCLVMNFS-UHFFFAOYSA-N 4',6-Diamino-2-phenylindol Chemical compound C1=CC(C(=N)N)=CC=C1C1=CC2=CC=C(C(N)=N)C=C2N1 FWBHETKCLVMNFS-UHFFFAOYSA-N 0.000 description 1
- 239000004471 Glycine Substances 0.000 description 1
- HTTJABKRGRZYRN-UHFFFAOYSA-N Heparin Chemical compound OC1C(NC(=O)C)C(O)OC(COS(O)(=O)=O)C1OC1C(OS(O)(=O)=O)C(O)C(OC2C(C(OS(O)(=O)=O)C(OC3C(C(O)C(O)C(O3)C(O)=O)OS(O)(=O)=O)C(CO)O2)NS(O)(=O)=O)C(C(O)=O)O1 HTTJABKRGRZYRN-UHFFFAOYSA-N 0.000 description 1
- MHAJPDPJQMAIIY-UHFFFAOYSA-N Hydrogen peroxide Chemical compound OO MHAJPDPJQMAIIY-UHFFFAOYSA-N 0.000 description 1
- 239000000637 Melanocyte-Stimulating Hormone Substances 0.000 description 1
- 108010007013 Melanocyte-Stimulating Hormones Proteins 0.000 description 1
- 102100035593 POU domain, class 2, transcription factor 1 Human genes 0.000 description 1
- 101710084414 POU domain, class 2, transcription factor 1 Proteins 0.000 description 1
- 229930040373 Paraformaldehyde Natural products 0.000 description 1
- 229920001213 Polysorbate 20 Polymers 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 150000001413 amino acids Chemical group 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000005352 clarification Methods 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000009223 counseling Methods 0.000 description 1
- 238000004042 decolorization Methods 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 238000005238 degreasing Methods 0.000 description 1
- 230000018044 dehydration Effects 0.000 description 1
- 238000006297 dehydration reaction Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 239000007854 depigmenting agent Substances 0.000 description 1
- 230000029142 excretion Effects 0.000 description 1
- 229960002897 heparin Drugs 0.000 description 1
- 229920000669 heparin Polymers 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 239000002609 medium Substances 0.000 description 1
- 230000008099 melanin synthesis Effects 0.000 description 1
- 239000012528 membrane Substances 0.000 description 1
- 230000004060 metabolic process Effects 0.000 description 1
- 239000012120 mounting media Substances 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 239000002858 neurotransmitter agent Substances 0.000 description 1
- 239000002773 nucleotide Substances 0.000 description 1
- 125000003729 nucleotide group Chemical group 0.000 description 1
- 229920002866 paraformaldehyde Polymers 0.000 description 1
- 102000054765 polymorphisms of proteins Human genes 0.000 description 1
- 239000000256 polyoxyethylene sorbitan monolaurate Substances 0.000 description 1
- 235000010486 polyoxyethylene sorbitan monolaurate Nutrition 0.000 description 1
- 230000001242 postsynaptic effect Effects 0.000 description 1
- 239000000047 product Substances 0.000 description 1
- 102000004169 proteins and genes Human genes 0.000 description 1
- 238000012950 reanalysis Methods 0.000 description 1
- 230000028327 secretion Effects 0.000 description 1
- 239000002904 solvent Substances 0.000 description 1
- 238000010561 standard procedure Methods 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 208000024891 symptom Diseases 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
- 238000005406 washing Methods 0.000 description 1
Landscapes
- Investigating Or Analysing Biological Materials (AREA)
Description
特許法第３０条第２項適用 中山 和紀、佐々 祥子、錦織 秀、黒住 元紀、鈴木 民夫及び池内 与志穂が、２０１９年第７７回米国研究皮膚科学会議の予稿集、ＪＯＵＲＮＡＬ ＯＦ ＩＮＶＥＳＴＩＧＡＴＩＶＥ ＤＥＲＭＡＴＯＬＯＧＹ， Ｖｏｌｕｍｅ １３９， Ｉｓｓｕｅ ５， Ｓｕｐｐｌｅｍｅｎｔ １， Ｍａｙ ２０１９ Ｐａｇｅ Ｓ１３５にて、杉山 茉希、中山 和紀及び池内 与志穂が発明した、真皮の神線維量の推定方法、肌のシミ濃度及び／又はシミ発生リスクの推定方法について公開した。Application of Article 30, Paragraph 2 of the Patent Act Kazunori Nakayama, Sachiko Sasa, Hide Nishikori, Motoki Kurozumi, Tamio Suzuki and Yoshiho Ikeuchi have disclosed a method for estimating the amount of fibrous tissue in the dermis and a method for estimating the concentration of skin spots and/or the risk of skin spots, which were invented by Maki Sugiyama, Kazunori Nakayama and Yoshiho Ikeuchi, in the proceedings of the 77th American Society for Research Dermatology in 2019, JOURNAL OF INVESTIGATIVE DERMATOLY, Volume 139, Issue 5, Supplement 1, May 2019 Page S135.
特許法第３０条第２項適用 中山 和紀、佐々 祥子、錦織 秀、黒住 元紀、鈴木 民夫及び池内 与志穂が、第７７回米国研究皮膚科学会議にて、杉山 茉希、中山 和紀及び池内 与志穂が発明した、真皮の神経線維量の推定方法、肌のシミ濃度及び／又はシミ発生リスクの推定方法について公開した。Application of Article 30, Paragraph 2 of the Patent Act Kazunori Nakayama, Sachiko Sasa, Hide Nishikori, Motoki Kurozumi, Tamio Suzuki and Yoshiho Ikeuchi announced a method for estimating the amount of nerve fibers in the dermis, and a method for estimating the concentration of skin spots and/or the risk of spot occurrence, invented by Maki Sugiyama, Kazunori Nakayama and Yoshiho Ikeuchi, at the 77th American Congress for Dermatology Research.
特許法第３０条第２項適用 ポーラ化成工業株式会社が、ｈｔｔｐ：／／ｗｗｗ．ｐｏｌａ－ｒｍ．ｃｏ．ｊｐ／， ｈｔｔｐ：／／ｗｗｗ．ｐｏｌａ－ｒｍ．ｃｏ．ｊｐ／ｐｄｆ／ｒｅｌｅａｓｅ＿２０１９１１０５．ｐｄｆのアドレスのウェブサイトで公開されているポーラ化成工業株式会社のウェブサイトにて、杉山 茉希、中山 和紀及び池内 与志穂が発明した真皮の神経線維量の推定方法、肌のシミ濃度及び／又はシミ発生リスクの推定方法について公開した。Application of Article 30, paragraph 2 of the Patent Act POLA CHEMICAL INDUSTRIES, INC. has published a method for estimating the amount of nerve fibers in the dermis, a method for estimating the concentration of skin spots and/or the risk of spot occurrence, invented by Maki Sugiyama, Kazunori Nakayama and Yoshiho Ikeuchi, on the website of POLA CHEMICAL INDUSTRIES, INC., which is available at the addresses http://www.pola-rm.co.jp/, http://www.pola-rm.co.jp/pdf/release_20191105.pdf.
本発明は、対象者の真皮の神経線維量の推定方法、肌のシミ濃度及び／又はシミ発生リスクの推定方法に関する。 The present invention relates to a method for estimating the amount of nerve fibers in the dermis of a subject, and a method for estimating the concentration of skin spots and/or the risk of spot development.
シミやソバカス等の皮膚の色素沈着症状は、顔の見た目に大きな影響を与えるため、その予防や改善に対する関心は高い。従来、種々の作用機序による美白剤が開発されており、消費者は好みや所望の効果に応じて化粧料を選択することができる。その選択をより各人に適したものとし、適切な肌の手入れをサポートするものとして、シミやソバカス等の発生しやすさを予測することが提案されている。 Skin pigmentation conditions such as age spots and freckles have a significant impact on the appearance of the face, and so there is great interest in preventing and improving them. To date, skin whitening agents with various mechanisms of action have been developed, and consumers can select cosmetics according to their preferences and desired effects. To make this selection more suitable for each individual and to support appropriate skin care, it has been proposed to predict the likelihood of the occurrence of age spots, freckles, etc.
特許文献１には、ヒトメラノサイト刺激ホルモン１受容体に係る特定のアミノ酸配列の変異がシミやソバカスの発生確率と相関していることに基づく、シミ等の発生確率を鑑別する方法が開示されている。 Patent Document 1 discloses a method for determining the probability of developing age spots and other skin blemishes, based on the fact that mutations in a specific amino acid sequence related to the human melanocyte-stimulating hormone 1 receptor correlate with the probability of developing age spots and freckles.
また、特許文献２には、特定の遺伝子における１個以上の一塩基多型（ＳＮＰ）を検出することを特徴とする、皮膚におけるシミ又はソバカスの発生リスクを鑑別する方法が開示されている。 Patent Document 2 also discloses a method for assessing the risk of developing skin blemishes or freckles, which is characterized by detecting one or more single nucleotide polymorphisms (SNPs) in a specific gene.
上記先行技術のあるところ、本発明者らは、真皮の神経線維量と、肌のシミ濃度との間に相関関係があることを見出し、本発明を完成させた。
すなわち、本発明は、真皮の神経線維量を推定する新規技術の提供を課題とする。
また、本発明は、肌のシミ濃度及び／又はシミ発生リスクを推定する新規技術の提供を課題とする。
In spite of the above-mentioned prior art, the present inventors have found that there is a correlation between the amount of nerve fibers in the dermis and the density of skin spots, and have completed the present invention.
That is, an objective of the present invention is to provide a novel technique for estimating the amount of nerve fibers in the dermis.
Another objective of the present invention is to provide a novel technique for estimating the concentration of skin blemishes and/or the risk of developing blemishes.
すなわち、上記課題を解決する本発明は、肌のシミ濃度に基づき、神経線維量を推定することを特徴とする、真皮の神経線維量の推定方法である。 In other words, the present invention, which solves the above problem, is a method for estimating the amount of nerve fibers in the dermis, characterized by estimating the amount of nerve fibers based on the density of skin spots.
このような推定方法を用いることで、肌のシミ濃度という、取得するのが比較的容易なデータを用いて対象者の真皮の神経線維量を推定することができる。
従来の技術では、真皮の神経線維量を測定するにあたり、対象者の肌から皮膚組織を取得し解析する必要があり、少なからず対象者に負担をかけるという問題があった。また、従来の技術では、高価な実験機器や試薬を使用する必要があるため、コスト面での問題もあった。
しかしながら、本発明によれば、対象者の肌のシミ濃度に関する情報を取得するのみで真皮の神経線維量を推定することができる。そのため、真皮の神経線維量を利用した肌診断などの場面における対象者の負担を軽減することにつながる。
By using this estimation method, it is possible to estimate the amount of nerve fibers in the subject's dermis using data that is relatively easy to obtain, namely the density of skin spots.
In conventional techniques, in order to measure the amount of nerve fibers in the dermis, it was necessary to obtain and analyze skin tissue from the subject's skin, which placed a certain burden on the subject.In addition, conventional techniques required the use of expensive experimental equipment and reagents, which created a cost problem.
However, according to the present invention, it is possible to estimate the amount of nerve fibers in the dermis simply by acquiring information on the density of spots on the subject's skin, which leads to a reduction in the burden on the subject in situations such as skin diagnosis that utilizes the amount of nerve fibers in the dermis.
本発明の好ましい実施の形態では、真皮の神経線維の空間密度を推定し、該空間密度の推定結果に基づき、神経線維量を推定する。 In a preferred embodiment of the present invention, the spatial density of nerve fibers in the dermis is estimated, and the amount of nerve fibers is estimated based on the estimated spatial density.
本発明の好ましい実施の形態では、表皮のＰＳＤ９５発現量に基づき、神経線維量を推定することを含む。
ここで、本発明の好ましい実施の形態では、表皮のＰＳＤ９５発現量が少ないほど、神経線維量が少ないと推定する。
A preferred embodiment of the present invention includes estimating nerve fiber mass based on the amount of PSD95 expression in the epidermis.
Here, in a preferred embodiment of the present invention, it is presumed that the lower the expression level of PSD95 in the epidermis, the smaller the amount of nerve fibers.
本発明の好ましい実施の形態では、
対象者から肌のシミ濃度に関する情報を取得するシミ濃度取得工程と、
前記シミ濃度取得工程で取得した肌のシミ濃度に関する情報を、予め用意した、真皮の神経線維量と肌のシミ濃度との相関を示す式又はモデルに適用し、対象者の真皮の神経線維量を推定する工程と、
を有する。
In a preferred embodiment of the present invention,
A stain concentration acquisition step of acquiring information on the stain concentration of the skin from a subject;
applying the information on the skin blemish concentration acquired in the blemish concentration acquisition step to a previously prepared equation or model showing a correlation between the amount of nerve fibers in the dermis and the skin blemish concentration, thereby estimating the amount of nerve fibers in the dermis of the subject;
has.
また、本発明は、真皮の神経線維量と肌のシミ濃度との相関データを記憶する記憶手段と、
対象者から取得した肌のシミ濃度に関する情報を、前記記憶手段に記憶された前記相関データに適用し、前記対象者の真皮の神経線維量を推定する推定手段と、
を備える、真皮の神経線維量推定装置にも関する。
The present invention also provides a method for measuring the correlation between the amount of nerve fibers in the dermis and the density of skin spots, comprising:
an estimation means for applying information on the density of skin spots obtained from the subject to the correlation data stored in the storage means, and estimating a nerve fiber amount in the dermis of the subject;
The present invention also relates to a dermis nerve fiber volume estimation device comprising:
また、本発明は、コンピュータを、
真皮の神経線維量と肌のシミ濃度との相関データを記憶する記憶手段と、
対象者から取得した肌のシミ濃度に関する情報を、前記記憶手段に記憶された前記相関データに適用し、前記対象者の真皮の神経線維量を推定する推定手段と、
として機能させるための、真皮の神経線維量推定プログラムにも関する。
The present invention also provides a computer comprising:
A storage means for storing correlation data between the amount of nerve fibers in the dermis and the density of skin spots;
an estimation means for estimating a nerve fiber amount in the dermis of the subject by applying information on the density of skin spots obtained from the subject to the correlation data stored in the storage means;
The present invention also relates to a program for estimating the amount of nerve fibers in the dermis in order to function as a neural network.
また、第二の本発明は、真皮の神経線維量に基づき、肌のシミ濃度及び／又はシミ発生リスクを推定することを特徴とする、肌のシミ濃度及び／又はシミ発生リスクの推定方法である。 The second invention is a method for estimating the concentration of skin spots and/or the risk of skin spots occurring, characterized in that the concentration of skin spots and/or the risk of skin spots occurring are estimated based on the amount of nerve fibers in the dermis.
このような推定方法を用いることで、真皮の神経線維量という、肌のシミ濃度及び／又はシミ発生リスクとの相関が知られていなかったデータを用いて肌のシミ濃度及び／又はシミ発生リスクを推定することができる。 By using this estimation method, it is possible to estimate the concentration of skin blemishes and/or the risk of developing blemishes using data on the amount of nerve fibers in the dermis, which was previously unknown to have any correlation with the concentration of skin blemishes and/or the risk of developing blemishes.
また、本発明によれば、例えば、ヒト以外の動物を用いた試験研究において、真皮の神経線維量という、肌のシミ濃度及び／又はシミ発生リスクとの相関が知られていなかったデータを用い、薬剤、美容手法を適用した際の効果の推定に応用することができる。 In addition, according to the present invention, for example, in experimental studies using animals other than humans, data on the amount of nerve fibers in the dermis, which was not previously known to have a correlation with the concentration of skin spots and/or the risk of spot development, can be used to estimate the effects of applying drugs and cosmetic techniques.
本発明の好ましい実施の形態では、真皮の神経線維の空間密度が高いほど、肌のシミ濃度及び／又はシミ発生リスクが高いと判定することを含む。 In a preferred embodiment of the present invention, the higher the spatial density of nerve fibers in the dermis, the higher the concentration of skin blemishes and/or the risk of developing blemishes.
本発明の好ましい実施の形態では、表皮のＰＳＤ９５発現量に基づき、肌のシミ濃度及び／又はシミ発生リスクを推定することを含む。
ここで、本発明の好ましい実施の形態では、表皮のＰＳＤ９５発現量が少ないほど、肌のシミ濃度及び／又はシミ発生リスクが低いと推定する。
A preferred embodiment of the present invention includes estimating the concentration of skin spots and/or the risk of spot development based on the amount of PSD95 expression in the epidermis.
Here, in a preferred embodiment of the present invention, it is estimated that the lower the expression level of PSD95 in the epidermis, the lower the density of skin blemishes and/or the risk of blemish development.
本発明の好ましい実施の形態では、対象者から真皮の神経線維量に関する情報を取得する神経線維量取得工程と、
前記神経線維量取得工程で取得した神経線維量に関する情報を、予め用意した、真皮の神経線維量と肌のシミ濃度及び／又はシミ発生リスクとの相関を示す式又はモデルに適用し、前記対象者の肌のシミ濃度及び／又はシミ発生リスクを推定する工程と、
を有する。
In a preferred embodiment of the present invention, a nerve fiber amount acquisition step of acquiring information on the nerve fiber amount of the dermis from a subject;
applying information on the nerve fiber amount acquired in the nerve fiber amount acquisition step to a previously prepared formula or model indicating a correlation between the nerve fiber amount in the dermis and the skin pigmentation concentration and/or pigmentation occurrence risk, thereby estimating the skin pigmentation concentration and/or pigmentation occurrence risk of the subject;
has.
また、本発明は、前述のシミ濃度及び／又はシミ発生リスクの推定方法による結果に基づいて、美白作用を有する化粧品を選択することを特徴とする、化粧品の選択方法でもある。 The present invention also provides a method for selecting cosmetics, which is characterized by selecting cosmetics having a whitening effect based on the results of the aforementioned method for estimating the concentration of spots and/or the risk of spot occurrence.
また、本発明は、真皮の神経線維量と肌のシミ濃度及び／又はシミ発生リスクとの相関データを記憶する記憶手段と、
対象者から取得した真皮の神経線維量に関する情報を、前記記憶手段に記憶された前記相関データに適用し、前記対象者の肌のシミ濃度及び／又はシミ発生リスクを推定する推定手段と、
を備える、肌のシミ濃度及び／又はシミ発生リスク推定装置でもある。
The present invention also provides a method for measuring the amount of nerve fibers in the dermis and the correlation data between the amount of skin spots and/or the risk of skin spots, comprising:
an estimation means for applying information on the amount of nerve fibers in the dermis obtained from the subject to the correlation data stored in the storage means, and estimating a concentration of spots on the skin of the subject and/or a risk of spot occurrence;
The present invention is also a skin blemish concentration and/or blemish occurrence risk estimation device comprising the above-mentioned.
また、本発明は、コンピュータを、真皮の神経線維量と肌のシミ濃度及び／又はシミ発生リスクとの相関データを記憶する記憶手段と、
対象者から取得した真皮の神経線維量に関する情報を、前記記憶手段に記憶された前記相関データに適用し、前記対象者の肌のシミ濃度及び／又はシミ発生リスクを推定する推定手段と、
として機能させるための、肌のシミ濃度及び／又はシミ発生リスク推定プログラムでもある。
The present invention also provides a computer that includes a storage means for storing correlation data between the amount of nerve fibers in the dermis and the density of skin spots and/or the risk of skin spots,
an estimation means for applying information on the amount of nerve fibers in the dermis obtained from the subject to the correlation data stored in the storage means, and estimating a concentration of spots on the skin of the subject and/or a risk of spot occurrence;
It is also a program for estimating the density of skin spots and/or the risk of spot occurrence in order to function as a skin care product.
本発明によれば、簡便に真皮の神経線維量を推定することができる。
また、本発明によれば、簡便に肌のシミ濃度及び／又はシミ発生リスクを推定することができる。
According to the present invention, the amount of nerve fibers in the dermis can be easily estimated.
Furthermore, according to the present invention, it is possible to easily estimate the concentration of skin spots and/or the risk of spot occurrence.
＜肌のシミ濃度に基づく、対象者の真皮の神経線維量の推定方法＞
本発明は、対象者の肌のシミ濃度に基づき、真皮の神経線維量を推定することを特徴とする、真皮の神経線維量の推定方法である。
<Method for estimating the amount of nerve fibers in a subject's dermis based on the density of skin spots>
The present invention provides a method for estimating a nerve fiber amount in the dermis, which is characterized by estimating a nerve fiber amount in the dermis based on a density of spots on the skin of a subject.
本発明の好ましい実施の形態では、対象者の肌のシミ濃度に基づき、肌のシミ濃度が高いほど真皮の神経線維量が多いと判定する。 In a preferred embodiment of the present invention, the amount of nerve fibers in the dermis is determined to be greater the higher the density of skin blemishes based on the density of skin blemishes on the subject.
このような推定方法を用いることで、肌のシミ濃度という、取得するのが比較的容易なデータを用いて対象者の真皮の神経線維量を推定することができる。
従来の技術では、真皮の神経線維量を測定するにあたり、対象者の肌から皮膚組織を取得し解析する必要があり、少なからず対象者に負担をかけるという問題があった。また、従来の技術では、高価な実験機器や試薬を使用する必要があるため、コスト面での問題もあった。
しかしながら、本発明によれば、対象者の肌のシミ濃度に関する情報を取得するのみで真皮の神経線維量を推定することができる。そのため、真皮の神経線維量を利用した肌診断などの場面における対象者の負担を軽減することにつながる。
By using this estimation method, it is possible to estimate the amount of nerve fibers in the subject's dermis using data that is relatively easy to obtain, namely the density of skin spots.
In conventional techniques, in order to measure the amount of nerve fibers in the dermis, it was necessary to obtain and analyze skin tissue from the subject's skin, which placed a certain burden on the subject.In addition, conventional techniques required the use of expensive experimental equipment and reagents, which created a cost problem.
However, according to the present invention, it is possible to estimate the amount of nerve fibers in the dermis simply by acquiring information on the density of spots on the subject's skin, which leads to a reduction in the burden on the subject in situations such as skin diagnosis that utilizes the amount of nerve fibers in the dermis.
対象者の肌のシミ濃度に関する情報の取得方法は特に限定されない。ここで、肌のシミ濃度に関する情報の取得方法は、非侵襲的な方法であることが好ましい。 The method of acquiring information regarding the density of blemishes on the subject's skin is not particularly limited. Here, it is preferable that the method of acquiring information regarding the density of blemishes on the skin is a non-invasive method.
シミ濃度に関する情報の非侵襲的な取得方法として、分光光度計を用い、L＊値、a＊値、b＊値を測定することにより、シミの濃度に関する情報を取得する方法を挙げることができる。
また、シミ濃度に関する情報の取得方法としては、皮膚組織を取得し、染色処理に供することにより、シミの濃度に関する情報を取得する方法も挙げることができる。
As a non-invasive method for obtaining information on the concentration of spots, there can be mentioned a method for obtaining information on the concentration of spots by measuring the L * value, a * value, and b * value using a spectrophotometer.
Another method for obtaining information about the density of blemishes is to obtain skin tissue and subject it to a staining process to obtain information about the density of blemishes.
また、後述の実施例に示すように、表皮のＰＳＤ９５発現量の多い箇所では、神経線維量が多い。
そのため、表皮のＰＳＤ９５発現量を取得し、表皮のＰＳＤ９５発現量を基に真皮の神経線維量を推定する形態とすることもできる。
Furthermore, as shown in the Examples below, areas of the epidermis where the amount of PSD95 expression is high also have a large amount of nerve fibers.
Therefore, it is also possible to obtain the expression level of PSD95 in the epidermis, and estimate the amount of nerve fibers in the dermis based on the expression level of PSD95 in the epidermis.
ここで、表皮のＰＳＤ９５発現量が少ないほど、神経線維量が少ないと推定する形態とすることが好ましい。 Here, it is preferable that the lower the amount of PSD95 expression in the epidermis, the smaller the amount of nerve fibers is estimated to be.
本発明における「真皮の神経線維量の推定」は、定量的な推定値でもよく、正常の肌状態における真皮の神経線維量を指標とした相対的かつ定性的な推定でもよい。
また、本発明における「対象者の真皮の神経線維量の推定」には、特定部位における真皮の神経線維量の推定、対象者の肌全体のうち真皮の神経線維量の多い部位の推定、の何れの概念をも含む。
In the present invention, the "estimation of the amount of nerve fibers in the dermis" may be a quantitative estimate, or a relative and qualitative estimate using the amount of nerve fibers in the dermis in a normal skin state as an index.
In addition, in the present invention, "estimating the amount of nerve fibers in the dermis of a subject" includes both concepts of estimating the amount of dermal nerve fibers in a specific area, and estimating an area of the subject's entire skin that has a large amount of dermal nerve fibers.
本発明においては、真皮の神経線維の空間密度、真皮の神経線維の分岐数、神経線維の数、神経線維の長さ、から選ばれる１以上、好ましくは２以上、より好ましくは３以上、特に好ましくは全ての項目を推定することを含む。 In the present invention, the method includes estimating one or more, preferably two or more, more preferably three or more, and particularly preferably all of the following items selected from the spatial density of dermal nerve fibers, the number of branches of dermal nerve fibers, the number of nerve fibers, and the length of nerve fibers.
本発明の特に好ましい実施の形態では、真皮の神経線維の空間密度を推定し、該空間密度の推定結果に基づき、神経線維量を推定することを含む。 A particularly preferred embodiment of the present invention includes estimating the spatial density of nerve fibers in the dermis and estimating the amount of nerve fibers based on the estimated spatial density.
真皮の神経線維量の推定方法の具体的な態様は特に限定されない。
また、真皮の神経線維量の推定方法として、上記肌のシミ濃度が高いほど、真皮の神経線維量が多いと推定するような定性的な推定手法を採用しても構わない。
この場合には、肌のシミ濃度について基準を設けておき、その基準よりシミ濃度が高い場合に「真皮の神経線維量が多い」と推定するような二元的な推定手法を採用してもよい。
The specific embodiment of the method for estimating the amount of nerve fibers in the dermis is not particularly limited.
Furthermore, as a method for estimating the amount of nerve fibers in the dermis, a qualitative estimation method may be adopted in which it is estimated that the higher the concentration of spots on the skin, the greater the amount of nerve fibers in the dermis.
In this case, a dual estimation method may be adopted in which a standard is set for the density of skin spots, and if the density of spots is higher than the standard, it is estimated that "the amount of nerve fibers in the dermis is high."
また、真皮の神経線維量の推定方法の具体的な態様として、
対象者から肌のシミ濃度に関する情報を取得するシミ濃度取得工程と、
前記シミ濃度取得工程で取得した肌のシミ濃度に関する情報を、予め用意した、真皮の神経線維量と肌のシミ濃度との相関を示す式又はモデルに適用し、対象者の真皮の神経線維量を推定する工程と、
を有する態様を挙げることができる。
In addition, as a specific embodiment of the method for estimating the amount of nerve fibers in the dermis,
A stain concentration acquisition step of acquiring information on the stain concentration of the skin from a subject;
applying the information on the skin blemish concentration acquired in the blemish concentration acquisition step to a previously prepared equation or model showing a correlation between the amount of nerve fibers in the dermis and the skin blemish concentration, thereby estimating the amount of nerve fibers in the dermis of the subject;
An embodiment having the following formula can be given.
また、定量的な推定手法を採用してもよい。具体的には、真皮の神経線維量と肌のシミ濃度の相関関係に関する式又はモデルを予め作成しておき、対象者より取得した真皮の神経線維量を当該式又はモデルと照合することにより、対象者の肌のシミ濃度を推定する実施の形態を好ましく挙げることができる。このような実施の形態とすることにより推定精度を向上させることができる。 A quantitative estimation method may also be used. Specifically, a preferred embodiment is one in which an equation or model relating to the correlation between the amount of nerve fibers in the dermis and the concentration of skin spots is created in advance, and the amount of nerve fibers in the dermis obtained from the subject is compared with the equation or model to estimate the concentration of skin spots on the subject. Such an embodiment can improve the accuracy of the estimation.
ここで、式又はモデルを作成するためには、前述の真皮の神経線維量と、肌のシミ濃度を多変量解析すればよい。該多変量解析としては、目的変数（従属変数）と説明変数（独立変数）との関係を利用できるものが好ましく、判別分析、回帰分析（ＭＬＲ、ＰＬＳ、ＰＣＲ、ロジスティック）を好ましく例示することができる。これらの内、特に好ましいのは重回帰分析（ＭＬＲ）、非線形回帰分析（ＰＬＳ：Ｐａｒｔｉａｌ Ｌｅａｓｔ Ｓｑｕａｒｅｓ）である。
式又はモデルとしては、回帰式又は回帰モデルが好ましく挙げられ、さらに好ましくは重回帰式又は予測式が挙げられる。
Here, in order to create the formula or model, the amount of nerve fibers in the dermis and the skin blemish concentration may be subjected to multivariate analysis. As the multivariate analysis, it is preferable to use the relationship between the objective variable (dependent variable) and the explanatory variable (independent variable), and discriminant analysis and regression analysis (MLR, PLS, PCR, logistic) are preferable examples. Among these, multiple regression analysis (MLR) and nonlinear regression analysis (PLS: Partial Least Squares) are particularly preferable.
The formula or model is preferably a regression formula or regression model, and more preferably a multiple regression formula or a prediction formula.
上記相関関係と肌のシミ濃度との相関を示す式又はモデルを作成するため、真皮の神経線維量と肌のシミ濃度を関連付けたデータベース（ＤＢ）を作成することが好ましい。ここで、ＤＢの人数は、好ましくは５０人以上、より好ましくは１００人以上、さらに好ましくは２００人以上である。
ＤＢの構造としては、例えば行列形式（マトリックス）であれば、行に人物を、列に真皮の神経線維量及び肌のシミ濃度を入力することができる。
In order to create an equation or model showing the correlation between the above correlation and the skin pigmentation concentration, it is preferable to create a database (DB) that associates the amount of nerve fibers in the dermis with the skin pigmentation concentration, where the number of people in the DB is preferably 50 or more, more preferably 100 or more, and even more preferably 200 or more.
The DB structure may be, for example, a matrix, in which people are entered in the rows and the amount of nerve fibers in the dermis and the density of skin spots are entered in the columns.
このＤＢは、新規に取得した対象者の肌のシミ濃度を推定した後、真皮の神経線維量の推定値を追加することで、更新してもよい。必要に応じて、更新したＤＢに対し上述した多変量解析を行って、式又はモデルを更新することもできる。該更新によって推定精度が向上する所以による。 This DB may be updated by estimating the newly acquired density of skin spots on the subject and then adding an estimate of the amount of nerve fibers in the dermis. If necessary, the above-mentioned multivariate analysis may be performed on the updated DB to update the formula or model. This is because such an update improves the accuracy of the estimation.
式又はモデルの作成、又は上記ＤＢの作成にあたって必要となる肌のシミ濃度の測定及び、真皮の神経線維量の測定は、常法により行うことができる。 The measurement of skin blemish concentration and the amount of nerve fibers in the dermis required for creating the formula or model, or for creating the above DB, can be performed by standard methods.
以上で説明した肌のシミ濃度の測定及び、真皮の神経線維量の測定を、統計学的に有意な数の被験者に対して行うことで、上記式又はモデル、並びにＤＢを作成することができる。 The above-described measurements of skin blemish concentration and dermal nerve fiber volume can be performed on a statistically significant number of subjects to create the above formula or model, as well as the DB.
また、本発明は、対象者の肌のシミ濃度を推定する推定装置にも関する。
本発明の推定装置は、真皮の神経線維量と肌のシミ濃度との相関データを記憶する記憶手段と、
対象者から取得した肌のシミ濃度に関する情報を、前記記憶手段に記憶された前記相関データに適用し、前記対象者の真皮の神経線維量を推定する推定手段と、
を備える。
The present invention also relates to an estimation device for estimating the concentration of spots on the skin of a subject.
The estimation device of the present invention includes a storage means for storing correlation data between the amount of nerve fibers in the dermis and the density of skin spots,
an estimation means for applying information on the density of skin spots obtained from the subject to the correlation data stored in the storage means, and estimating a nerve fiber amount in the dermis of the subject;
Equipped with.
記憶手段は、真皮の神経線維量と肌のシミ濃度との相関データを記憶する。
相関データとしては、上述した式又はモデル、並びにこれらを作成するためのＤＢが挙げられる。
記憶手段は、例えばＲＯＭ（Ｒｅａｄ Ｏｎｌｙ Ｍｅｍｏｒｙ）により実現することができる。
The storage means stores correlation data between the amount of nerve fibers in the dermis and the density of skin spots.
The correlation data includes the above-mentioned formulas or models, as well as a DB for creating them.
The storage means can be realized by, for example, a ROM (Read Only Memory).
真皮の神経線維量の推定手段は、対象者から取得した肌のシミ濃度を、前記記憶手段に記憶された前記相関データに適用し、前記対象者の真皮の神経線維量を推定する。
当該推定手段は、ＣＰＵ（Ｃｅｎｔｒａｌ Ｐｒｏｃｅｓｓｉｎｇ Ｕｎｉｔ）により実現することができる。
ＣＰＵにおける上述した推定処理は、ＲＯＭに記憶されているプログラムに従って実行される形態とすることができる。
The dermal nerve fiber amount estimation means applies the skin blemish concentration obtained from the subject to the correlation data stored in the storage means, and estimates the dermal nerve fiber amount of the subject.
The estimation means can be realized by a CPU (Central Processing Unit).
The above-mentioned estimation process in the CPU can be executed in accordance with a program stored in the ROM.
また、記憶手段に、新規に取得した対象者の真皮の神経線維量、及び肌のシミ濃度の推定値が追加的に記憶され、相関データが逐次更新される実施の形態とすることが好ましい。
この場合、記憶手段に記憶された追加データを含むＤＢに基づき再解析を行い、更新された式又はモデルを算出し、これを記憶手段に上書き記憶する更新手段を設けることが好ましい。
更新手段は、ＲＯＭに記憶されたプログラムに従って、ＣＰＵにより実現する形態とすることができる。
In addition, it is preferable that the storage means additionally stores newly acquired estimates of the subject's dermal nerve fiber amount and skin blemish concentration, and the correlation data is successively updated.
In this case, it is preferable to provide an update means for performing a reanalysis based on the DB including the additional data stored in the storage means, calculating an updated formula or model, and overwriting and storing this in the storage means.
The update means can be realized by a CPU in accordance with a program stored in a ROM.
また、本発明の推定装置は、ＣＰＵに実行させるＯＳ（Ｏｐｅｒａｔｉｎｇ Ｓｙｓｔｅｍ）プログラムや各種アプリケーションプログラムを一時的に格納するＲＡＭ（Ｒａｎｄｏｍ Ａｃｃｅｓｓ Ｍｅｍｏｒｙ）を備えることが好ましい。 The estimation device of the present invention preferably also includes a RAM (Random Access Memory) for temporarily storing the OS (Operating System) program and various application programs executed by the CPU.
また、本発明は対象者の真皮の神経線維量推定プログラムにも関する。
本発明の推定プログラムは、コンピュータを、真皮の神経線維量と肌のシミ濃度との相関データを記憶する記憶手段と、
対象者から取得した肌のシミ濃度に関する情報を、前記記憶手段に記憶された前記相関データに適用し、前記対象者の真皮の神経線維量を推定する推定手段と、
として機能させる実施の形態とすることが好ましい。
ここで、本発明はこのようなプログラムをコンピュータ等が読み取り可能な記録媒体に記録したものでもよい。
The present invention also relates to a program for estimating the amount of nerve fibers in the dermis of a subject.
The estimation program of the present invention includes a computer, a storage means for storing correlation data between the amount of nerve fibers in the dermis and the density of skin spots,
an estimation means for estimating a nerve fiber amount in the dermis of the subject by applying information on the density of skin spots obtained from the subject to the correlation data stored in the storage means;
It is preferable to use an embodiment in which the function is as follows.
Here, the present invention may be such a program recorded on a recording medium that can be read by a computer or the like.
＜真皮の神経線維量に基づく、対象者の肌のシミ濃度及び／又はシミ発生リスクの推定方法＞
本発明は、真皮の神経線維量に基づき、対象者の肌のシミ濃度及び／又はシミ発生リスクを推定することを特徴とする、肌のシミ濃度及び／又はシミ発生リスクの推定方法である。
<Method for estimating the concentration of pigmentation on a subject's skin and/or the risk of pigmentation development based on the amount of nerve fibers in the dermis>
The present invention provides a method for estimating the concentration of spots on skin and/or the risk of spot occurrence, which is characterized by estimating the concentration of spots on a subject's skin and/or the risk of spot occurrence based on the amount of nerve fibers in the dermis.
このような推定方法を用いることで、真皮の神経線維量という、肌のシミ濃度及び／又はシミ発生リスクとの相関が知られていなかったデータを用いて肌のシミ濃度及び／又はシミ発生リスクを推定することができる。 By using this estimation method, it is possible to estimate the concentration of skin blemishes and/or the risk of developing blemishes using data on the amount of nerve fibers in the dermis, which was previously unknown to have any correlation with the concentration of skin blemishes and/or the risk of developing blemishes.
また、本発明によれば、例えば、ヒト以外の動物を用いた試験研究において、真皮の神経線維量という、肌のシミ濃度及び／又はシミ発生リスクとの相関が知られていなかったデータを用い、薬剤、美容手法を用いた際の効果の推定をすることができる。 In addition, according to the present invention, for example, in experimental studies using animals other than humans, data on the amount of nerve fibers in the dermis, which was not previously known to correlate with the concentration of skin spots and/or the risk of spot development, can be used to estimate the effects of using drugs and cosmetic techniques.
本発明の好ましい実施の形態では、対象者の真皮の神経線維量に基づき、真皮の神経線維量が多いほど肌のシミ濃度及び／又はシミ発生リスクが高いと判定する。 In a preferred embodiment of the present invention, the amount of nerve fibers in the dermis of a subject is used as a basis to determine that the greater the amount of nerve fibers in the dermis, the higher the skin blemish concentration and/or risk of blemish development.
対象者の真皮の神経線維量に関する情報の取得方法は特に限定されない。
真皮の神経線維量に関する情報の取得方法としては、皮膚組織を取得し、染色処理に供することにより、真皮の神経線維量に関する情報を取得する形態とすることが好ましい。
The method of acquiring information regarding the amount of nerve fibers in the dermis of a subject is not particularly limited.
A preferred method for obtaining information regarding the amount of nerve fibers in the dermis is to obtain skin tissue and subject it to a staining process, thereby obtaining information regarding the amount of nerve fibers in the dermis.
また、後述の実施例に示すように、表皮のＰＳＤ９５発現量の多い箇所では、シミ濃度が高い。
そのため、表皮のＰＳＤ９５発現量を取得し、表皮のＰＳＤ９５発現量を基に肌のシミ濃度及び／又はシミ発生リスクを推定する形態とすることもできる。
Furthermore, as shown in the Examples below, spots with high PSD95 expression in the epidermis have a high density of spots.
Therefore, it is also possible to obtain the expression level of PSD95 in the epidermis, and estimate the concentration of skin spots and/or the risk of spot occurrence based on the expression level of PSD95 in the epidermis.
ここで、表皮のＰＳＤ９５発現量が少ないほど、肌のシミ濃度及び／又はシミ発生リスクが低いと推定する形態とすることが好ましい。 Here, it is preferable that the lower the expression level of PSD95 in the epidermis, the lower the concentration of skin blemishes and/or the risk of blemish development.
本発明における「肌のシミ濃度及び／又はシミ発生リスクの推定」は、定量的な推定値でもよく、正常の肌状態における肌の色合いを指標とした相対的かつ定性的な推定でもよい。
また、本発明における「肌のシミ濃度及び／又はシミ発生リスクの推定」には、特定部位における肌のシミ濃度及び／又はシミ発生リスク、対象者の肌全体のうち肌のシミ濃度及び／又はシミ発生リスクの高い部位の推定、の何れの概念をも含む。
In the present invention, the "estimation of skin blemish concentration and/or risk of blemish occurrence" may be a quantitative estimate, or a relative and qualitative estimate using the skin tone in a normal skin condition as an index.
In addition, in the present invention, "estimation of skin blemish concentration and/or risk of blemish occurrence" includes both concepts of estimating skin blemish concentration and/or risk of blemish occurrence in a specific area, and estimating areas of the subject's entire skin that have a high skin blemish concentration and/or risk of blemish occurrence.
なお、本発明により推定される「シミ発生リスク」は、皮膚の局所的な色素沈着症状の発生しやすさをいう。 The "risk of developing spots" estimated by the present invention refers to the likelihood of developing localized pigmentation symptoms on the skin.
肌のシミ濃度及び／又はシミ発生リスクの推定方法の具体的な態様は特に限定されない。
また、肌のシミ濃度及び／又はシミ発生リスクの推定方法として、上記真皮の神経線維量が多いほど肌のシミ濃度及び／又はシミ発生リスクが高いと推定するような定性的な推定手法を採用しても構わない。
この場合には、真皮の神経線維量について基準を設けておき、その基準より真皮の神経線維量が多い場合に「肌のシミ濃度及び／又はシミ発生リスクが高い」と推定するような二元的な推定手法を採用してもよい。
The specific embodiment of the method for estimating the skin spot concentration and/or the risk of spot occurrence is not particularly limited.
In addition, as a method for estimating the concentration of skin spots and/or the risk of spot occurrence, a qualitative estimation method may be adopted in which it is estimated that the greater the amount of nerve fibers in the dermis, the higher the concentration of skin spots and/or the risk of spot occurrence.
In this case, a dual estimation method may be adopted in which a standard is set for the amount of nerve fibers in the dermis, and if the amount of nerve fibers in the dermis is greater than that standard, it is estimated that "the skin blemish concentration and/or risk of blemish occurrence is high."
また、定量的な推定手法を採用してもよい。具体的には、真皮の神経線維量と肌のシミ濃度及び／又はシミ発生リスクの相関関係に関する式又はモデルを予め作成しておき、対象者より取得した真皮の神経線維量を当該式又はモデルと照合することにより対象者の肌のシミ濃度及び／又はシミ発生リスクを推定する実施の形態を好ましく挙げることができる。このような実施の形態とすることにより推定精度を向上させることができる。 A quantitative estimation method may also be employed. Specifically, a preferred embodiment is one in which an equation or model relating to the correlation between the amount of nerve fibers in the dermis and the concentration of skin spots and/or the risk of skin spots is created in advance, and the amount of nerve fibers in the dermis obtained from the subject is compared with the equation or model to estimate the concentration of skin spots and/or the risk of skin spots. Such an embodiment can improve the accuracy of the estimation.
また、本発明においては、真皮の神経線維の空間密度、真皮の神経線維の分岐数、神経線維の数、神経線維の長さ、から選ばれる２以上の項目に基づく神経線維量が多いほど肌のシミ濃度及び／又はシミ発生リスクが高いと判定する形態とすることが好ましい。
中でも、真皮の神経線維の空間密度が高いほど、肌のシミ濃度及び／又はシミ発生リスクが高いと判定することを含む形態とすることが好ましい。
Furthermore, in the present invention, it is preferable to determine that the greater the amount of nerve fibers based on two or more items selected from the spatial density of nerve fibers in the dermis, the number of branches of nerve fibers in the dermis, the number of nerve fibers, and the length of nerve fibers, the higher the skin blemish concentration and/or the risk of blemish development.
In particular, a preferred embodiment includes determining that the higher the spatial density of nerve fibers in the dermis, the higher the concentration of skin blemishes and/or the risk of blemish development.
本発明により推定されたシミ発生リスク（発生確率）は、化粧品を選択する際の指標として利用することができる。ここで選択される化粧品は、通常は美白作用を有する化粧品であり、より具体的には、メラニン産生抑制作用、メラニン蓄積抑制作用、メラニン排出促進作用、メラニン分解促進作用、肌代謝促進作用など、種々の美白用化粧品を含む。通常は、推定されたシミ発生リスクが高い場合に、より作用・効果が強い美白用化粧品を選択する。
また、本発明により判定されたシミ発生リスク（発生確率）の結果は、肌の手入れ（スキンケア）や化粧方法に関するカウンセリングにおいても有用な指標となり得る。
The risk (probability) of age spots estimated by the present invention can be used as an index when selecting cosmetics. The cosmetics selected here are usually cosmetics with whitening effects, and more specifically, include various whitening cosmetics that have melanin production suppression effects, melanin accumulation suppression effects, melanin excretion promotion effects, melanin decomposition promotion effects, skin metabolism promotion effects, etc. Usually, when the estimated risk of age spots is high, whitening cosmetics with stronger effects are selected.
Furthermore, the risk (probability) of spots occurring determined by the present invention can also be a useful index for counseling regarding skin care and makeup methods.
ここで、式又はモデルを作成する方法は、前述の手法を援用することができる。 Here, the method for creating the formula or model can be the same as that described above.
また、本発明は、対象者の肌のシミ濃度及び／又はシミ発生リスクを推定する推定装置にも関する。
本発明の推定装置は、真皮の神経線維量と肌のシミ濃度及び／又はシミ発生リスクとの相関データを記憶する記憶手段と、
対象者から取得した真皮の神経線維量に関する情報を、前記記憶手段に記憶された前記相関データに適用し、前記対象者の肌のシミ濃度及び／又はシミ発生リスクを推定する推定手段と、
を備える。
The present invention also relates to an estimation device for estimating the concentration of pigmentation on the skin of a subject and/or the risk of pigmentation development.
The estimation device of the present invention includes a storage means for storing correlation data between the amount of nerve fibers in the dermis and the concentration of spots on the skin and/or the risk of spot occurrence;
an estimation means for applying information on the amount of nerve fibers in the dermis obtained from the subject to the correlation data stored in the storage means, and estimating a concentration of spots on the skin of the subject and/or a risk of spot occurrence;
Equipped with.
ここで、本発明の推定装置の好ましい実施の形態は、前述の説明を援用することができる。 Here, the above description can be used as a preferred embodiment of the estimation device of the present invention.
また、本発明は対象者の肌のシミ濃度及び／又はシミ発生リスク推定プログラムにも関する。
本発明の推定プログラムは、コンピュータを、真皮の神経線維量と肌のシミ濃度及び／又はシミ発生リスクとの相関データを記憶する記憶手段と、
対象者から取得した真皮の神経線維量に関する情報を、前記記憶手段に記憶された前記相関データに適用し、前記対象者の肌のシミ濃度及び／又はシミ発生リスクを推定する推定手段と、
として機能させる実施の形態とすることが好ましい。
The present invention also relates to a program for estimating the density of spots on the skin of a subject and/or the risk of spot occurrence.
The estimation program of the present invention includes a computer, a storage means for storing correlation data between the amount of nerve fibers in the dermis and the density of skin spots and/or the risk of skin spots,
an estimation means for applying information on the amount of nerve fibers in the dermis obtained from the subject to the correlation data stored in the storage means, and estimating a concentration of spots on the skin of the subject and/or a risk of spot occurrence;
It is preferable to use an embodiment in which the function is as follows.
ここで、本発明の推定プログラムの好ましい実施の形態は、前述の説明を援用することができる。 Here, the above explanation can be used as a preferred embodiment of the estimation program of the present invention.
以下、本発明の基礎となる知見を裏付ける各種試験結果を示す。
肌のシミ濃度と真皮の神経線維量の関係性を裏付ける試験結果を示す。
Various test results supporting the findings underlying the present invention are shown below.
The following test results support the relationship between the concentration of skin blemishes and the amount of nerve fibers in the dermis.
＜実施例１＞ 肌のシミ濃度と真皮の神経線維量について <Example 1> Skin blemish density and amount of nerve fibers in the dermis
（１）試験材料及び測定部位の取得
本実施例では、表１に示すヒト皮膚を試験材料とした。
(1) Obtaining Test Materials and Measurement Sites In this example, human skin shown in Table 1 was used as the test material.
そして、本実施例では、試験材料における、シミ部位の立体皮膚組織（シミのある表皮のみを含む立体皮膚組織）と非シミ部位の立体皮膚組織（シミのない表皮のみを含む立体皮膚組織）を測定部位として選定した。そして、選定した部位の立体皮膚組織を、表１に示す大きさに切り出すことにより、取得した（図１ 参照）。 In this embodiment, three-dimensional skin tissue from the blemished area (three-dimensional skin tissue containing only the epidermis with blemishes) and three-dimensional skin tissue from the non-blemished area (three-dimensional skin tissue containing only the epidermis without blemishes) in the test material were selected as the measurement areas. The three-dimensional skin tissue from the selected areas was then obtained by cutting it to the size shown in Table 1 (see Figure 1).
（２）透明化処理工程 (2) Clarification process
まず、取得した立体皮膚組織を４℃雰囲気下、４％パラホルムアルデヒド溶液に、一晩浸漬させた。
浸漬後、立体皮膚組織をＰＢＳ溶液下、１時間×２回、振とう処理をおこなった。
その後、５０％メタノールを含むＰＢＳ溶液での振とう処理（１時間）、８０％メタノールを含むＰＢＳ溶液での振とう処理（１時間）、１００％メタノール溶液での振とう処理（１時間×２回）をおこなった。
First, the obtained three-dimensional skin tissue was immersed in a 4% paraformaldehyde solution overnight in an atmosphere at 4°C.
After immersion, the three-dimensional skin tissue was subjected to shaking treatment in the PBS solution for 1 hour twice.
Thereafter, the cells were subjected to shaking treatment in a PBS solution containing 50% methanol (1 hour), shaking treatment in a PBS solution containing 80% methanol (1 hour), and shaking treatment in a 100% methanol solution (1 hour x 2 times).
振とう処理後、５％過酸化水素溶液（溶媒 ＤＭＳＯ／メタノール）を用い、４℃雰囲気下７日間、立体皮膚組織の脱色処理を行った。 After shaking, the three-dimensional skin tissue was decolorized using a 5% hydrogen peroxide solution (solvent: DMSO/methanol) at 4°C for 7 days.
脱色処理の後、１００％メタノール溶液での振とう処理（１時間×２回）をした。その後、２０％ＤＭＳＯを含むメタノール溶液での振とう処理（１時間×２回）、８０％メタノールを含むＰＢＳ溶液での振とう処理（１時間）、５０％メタノールを含むＰＢＳ溶液での振とう処理（１時間）、ＰＢＳ溶液での振とう処理（１時間×２回）をおこなった。 After the decolorization process, the cells were shaken in 100% methanol solution (1 hour x 2 times). This was followed by shaking in a methanol solution containing 20% DMSO (1 hour x 2 times), shaking in a PBS solution containing 80% methanol (1 hour), shaking in a PBS solution containing 50% methanol (1 hour), and shaking in a PBS solution (1 hour x 2 times).
振とう処理後、０．２％ Ｔｒｉｔｏｎ Ｘ－１００（ナカライテスク製）を含むＰＢＳ溶液を用い、振とう処理（１時間×２回）をおこなった。振とう処理後、立体皮膚組織を、０．２％ Ｔｒｉｔｏｎ Ｘ－１００（ナカライテスク製）／２０％ ＤＭＳＯ／０．３ Ｍ Ｇｌｙｃｉｎｅ を含むＰＢＳ溶液に、３７℃雰囲気下、一晩浸漬させた。 After the shaking treatment, a shaking treatment (1 hour x 2 times) was performed using a PBS solution containing 0.2% Triton X-100 (Nacalai Tesque). After the shaking treatment, the three-dimensional skin tissue was immersed overnight in a PBS solution containing 0.2% Triton X-100 (Nacalai Tesque) / 20% DMSO / 0.3 M Glycine at 37°C.
その後、立体皮膚組織を、０．２％ Ｔｒｉｔｏｎ Ｘ－１００（ナカライテスク製）／１０％ ＤＭＳＯ／６％ Ｄｏｎｋｅｙ Ｓｅｒｕｍ（Ｓｉｇｍａ－Ａｌｄｒｉｃｈ 社製）を含むＰＢＳ溶液に、３７℃雰囲気下、二晩浸漬させた。 Then, the three-dimensional skin tissue was immersed in a PBS solution containing 0.2% Triton X-100 (Nacalai Tesque)/10% DMSO/6% Donkey Serum (Sigma-Aldrich) at 37°C for two nights.
浸漬後、０．２％ Ｔｗｅｅｎ ２０ ｗｉｔｈ １０μg／ｍＬ Ｈｅｐａｒｉｎ（Ｗａｋｏ社製）を含むＰＢＳ溶液（以下、ＰＴｗＨと略記）を用い、立体皮膚組織の振とう処理（１時間×２回）をおこなった。 After immersion, the three-dimensional skin tissue was shaken (1 hour x 2 times) using a PBS solution containing 0.2% Tween 20 with 10 μg/mL Heparin (Wako) (hereafter abbreviated as PTwH).
振とう後、５％ ＤＭＳＯ／３％ Ｄｏｎｋｅｙ Ｓｅｒｕｍを含むＰＴｗＨ溶液を用い、一次抗体を希釈した。該希釈溶液を用い、立体皮膚組織を３晩、３７℃雰囲気下で、浸漬させた。
ここで、一次抗体には、ＰＧＰ９．５（ａｂｃａｍ）及びＴＹＲＰ１（ｂｉｏＬｅｇｅｎｄ）を用いた。
After shaking, the primary antibody was diluted with a PTwH solution containing 5% DMSO/3% Donkey Serum, and the three-dimensional skin tissue was immersed in the diluted solution for three nights in an atmosphere at 37°C.
Here, PGP9.5 (abcam) and TYRP1 (bioLegend) were used as primary antibodies.
その後、ＰＴｗＨを用い、立体皮膚組織を振とう処理（二晩）した。その後、３％ Ｄｏｎｋｅｙ Ｓｅｒｕｍを含むＰＴｗＨ溶液を用い、二次抗体を希釈した。該希釈溶液を用い、立体皮膚組織を二晩、３７℃雰囲気下で、浸漬させた。
ここで二次抗体には、Ｄｏｎｋｅｙ ａｎｔｉ－ｒａｂｂｉｔ ＩｇＧ Ａｌｅｘａ Ｆｌｏｕｒ Ｐｌｕｓ ６４７（Ｉｎｖｉｔｒｏｇｅｎ）及びＤｏｎｋｅｙ ａｎｔｉ－ｍｏｕｓｅ ＩｇＧ Ａｌｅｘａ Ｆｌｕｏｒ Ｐｌｕｓ ５５５（Ｉｎｖｉｔｒｏｇｅｎ）を用いた。
The three-dimensional skin tissue was then shaken (for two nights) using PTwH. The secondary antibody was then diluted using a PTwH solution containing 3% Donkey Serum. The three-dimensional skin tissue was immersed in the diluted solution for two nights at 37°C.
Here, Donkey anti-rabbit IgG Alexa Fluor Plus 647 (Invitrogen) and Donkey anti-mouse IgG Alexa Fluor Plus 555 (Invitrogen) were used as secondary antibodies.
その後、ＰＴｗＨを用い、立体皮膚組織を振とう処理（三晩）した。その後、立体皮膚組織を５０％（ｖ／ｖ）Ｔｅｔｒａｈｙｄｒｏｆｕｒａｎ／Ｈ２Ｏ溶液で振とう処理（一晩）した後、８０％（ｖ／ｖ）Ｔｅｔｒａｈｙｄｒｏｆｕｒａｎ／Ｈ２Ｏ溶液（１時間）で振とう処理した。 The three-dimensional skin tissue was then shaken (three nights) using PTwH, and then shaken (overnight) in a 50% (v/v) tetrahydrofuran/H 2 O solution, and then shaken (1 hour) in an 80% (v/v) tetrahydrofuran/H 2 O solution.
その後、立体皮膚組織を、Ｔｅｔｒａｈｙｄｒｏｆｕｒａｎ溶液で振とう（１時間×２回）することにより、脱水処理した。 The three-dimensional skin tissue was then dehydrated by shaking it in Tetrahydrofuran solution (1 hour x 2 times).
脱水処理の後、立体皮膚組織がＤｉｃｈｌｏｒｏｍｅｔｈａｎｅ溶液に沈むまで（半日～１日）振とうすることにより、脱脂処理した。 After dehydration, the three-dimensional skin tissue was degreased by shaking it in the dichloromethane solution until it was submerged (half a day to a day).
脱脂処理後、立体皮膚組織をジベンジルエーテル３ｍＬで透明になるまで一晩振盪させた。 After degreasing, the three-dimensional skin tissue was shaken overnight in 3 mL of dibenzyl ether until it became transparent.
（３）可視化工程、対比観察工程
共焦点レーザー顕微鏡（Ｎｉｋｏｎ社製）を用い、透明化工程後の皮膚組織の三次元画像を撮像した（図２）。
撮像した三次元画像を、画像解析ソフトウェアＩｍａｒｉｓ（ＢＩＴＰＬＡＮＥ社製）に供すことにより、神経線維の３Ｄモデルを作成した（図３）。
(3) Visualization step and comparative observation step Using a confocal laser microscope (Nikon Corporation), a three-dimensional image of the skin tissue after the clearing step was taken ( FIG. 2 ).
The captured three-dimensional images were subjected to image analysis software Imaris (BITPLANE) to create a 3D model of nerve fibers (Figure 3).
また、画像解析ソフトウェアＩｍａｒｉｓ（ＢＩＴＰＬＡＮＥ社製）に供すことにより、２値化及び細線化処理を行うことで、神経線維の空間密度、神経線維の分岐数、神経線維の数、神経線維の長さの差異を対比観察した。また、神経線維の空間密度の対比観察結果を図４に示す。 In addition, the images were subjected to binarization and thinning processing using the image analysis software Imaris (manufactured by BITPLANE), and the differences in the spatial density of nerve fibers, the number of branches of nerve fibers, the number of nerve fibers, and the length of nerve fibers were comparatively observed. The results of the comparative observation of the spatial density of nerve fibers are shown in Figure 4.
（４）考察
図４に示すとおり、シミ部位の立体皮膚組織（シミのある表皮を含む立体皮膚組織）は、非シミ部位の立体皮膚組織（シミのない表皮のみを含む立体皮膚組織）に比して、真皮の神経線維量が多いことがわかった。
(4) Discussion As shown in Figure 4, the three-dimensional skin tissue of the blemished area (three-dimensional skin tissue including epidermis with blemishes) had a greater amount of nerve fibers in the dermis than the three-dimensional skin tissue of the non-blemished area (three-dimensional skin tissue including only epidermis without blemishes).
以上の結果は、シミ濃度が高いほど真皮の神経線維量が多いことを示している。
したがって、真皮の神経線維量に基づき、対象者の肌のシミ濃度を推定できることがわかった。
また、肌のシミ濃度に基づき、真皮の神経線維量を推定できることがわかった。
These results indicate that the higher the stain concentration, the greater the amount of nerve fibers in the dermis.
Therefore, it was found that the concentration of spots on a subject's skin can be estimated based on the amount of nerve fibers in the dermis.
They also found that it is possible to estimate the amount of nerve fibers in the dermis based on the density of skin blemishes.
＜実施例２＞ 肌のシミ発生リスクと神経線維量の検証
次に、シミ発生リスクと神経線維量の検証をおこなった。
Example 2: Examination of the risk of skin blemishes and the amount of nerve fibers Next, the risk of skin blemishes and the amount of nerve fibers were examined.
（１）被験者及び測定部位
本実施例では、表１に示すヒト皮膚を試験材料とした。
そして、本実施例では、試験材料における、額領域、頬領域、顎領域を測定部位として、選定した（図５ 参照）。ここで、本実施例では正常状態の部位（シミのない表皮を含む立体皮膚組織）を測定部位とした。
(1) Subjects and Measurement Sites In this example, human skin shown in Table 1 was used as the test material.
In this embodiment, the forehead, cheek, and chin regions of the test material were selected as the measurement sites (see FIG. 5). Here, in this embodiment, the normal region (three-dimensional skin tissue including epidermis without blemishes) was selected as the measurement site.
（２）試験
実施例１と同様の方法により、立体皮膚組織を取得した。
そして、取得した立体皮膚組織に対し、実施例１と同様の処理を行うことにより、神経線維の３Ｄモデルを作成した。
(2) Test Three-dimensional skin tissue was obtained in the same manner as in Example 1.
The obtained three-dimensional skin tissue was then subjected to the same processing as in Example 1 to create a 3D model of nerve fibers.
（３）対比観察工程
可視化した各部位の３Ｄモデルを並列にし、本分野を専門とする評価者により、各領域の立体皮膚組織における、神経線維量の違いを対比観察した。
結果の代表図を図６に示す。
(3) Comparative Observation Step The visualized 3D models of each site were arranged side by side, and an evaluator with expertise in this field comparatively observed the differences in the amount of nerve fibers in the three-dimensional skin tissue of each region.
A representative diagram of the results is shown in FIG.
（４）考察
図６に示すとおり、頬領域の立体皮膚組織では、他の部位（額領域、顎領域）に比して、真皮の神経線維量が多いことがわかった。
ここで、頬領域は、シミのできやすい部位（シミ発生リスクの高い部位）である。
してみると、本実施例の結果、シミのできやすい部位（シミ発生リスクの高い部位）では、神経線維量が多いことがわかった。
(4) Discussion As shown in Figure 6, the three-dimensional skin tissue of the cheek region was found to have a greater amount of nerve fibers in the dermis than other regions (forehead region and chin region).
Here, the cheek region is a region where blemishes are likely to occur (a region with a high risk of blemishes occurring).
As a result of this example, it was found that the amount of nerve fibers was greater in areas prone to blemishes (areas with a high risk of blemishes occurring).
すなわち、本実施例の結果に依れば、真皮の神経線維量に基づき、対象者のシミ発生リスクを推定できることがわかった。 In other words, the results of this example show that the risk of developing dark spots in a subject can be estimated based on the amount of nerve fibers in the dermis.
本発明は、対象者の真皮の神経線維量の推定方法に応用することができる。 The present invention can be applied to a method for estimating the amount of nerve fibers in a subject's dermis.
＜実施例３－１＞ 神経線維との接触によるメラノサイト（Ｍｃ）の表現型変化の検証
次に、神経線維との接触によるメラノサイト（Ｍｃ）の表現型変化の検証をおこなった。
Example 3-1 Verification of phenotypic change in melanocytes (Mc) due to contact with nerve fibers Next, verification was carried out on phenotypic change in melanocytes (Mc) due to contact with nerve fibers.
（１）試験
ｉＰＳ細胞より分化誘導した感覚神経細胞を２４ｗｅｌｌプレートに２００,０００ｃｅｌｌｓ／ｗｅｌｌ播種した。
感覚神経細胞を３日間培養した後、ヒトメラノサイトを１０,０００ｃｅｌｌｓ／ｗｅｌｌ播種し、２日間共培養を実施した。
共培養後、感覚神経細胞を４％ＰＦＡを用い固定し、ヒトメラノサイトを免疫染色法（ＴＹＲＰ１）にて染色した。
(1) Test Sensory neurons induced to differentiate from iPS cells were seeded onto a 24-well plate at 200,000 cells/well.
After culturing the sensory neurons for 3 days, human melanocytes were seeded at 10,000 cells/well and co-cultured for 2 days.
After co-culture, the sensory neurons were fixed using 4% PFA, and the human melanocytes were stained by immunostaining (TYRP1).
染色後、光学顕微鏡・蛍光顕微鏡にてヒトメラノサイトの明視野画像および蛍光画像を取得した。
取得した明視野画像を二値化し、神経線維との接触（共培養）によるメラノサイト（Ｍｃ）の表現型変化を観察した。
結果を、図７に示す。
After staining, bright-field and fluorescent images of human melanocytes were obtained using an optical microscope and a fluorescent microscope.
The acquired bright-field images were binarized, and the phenotypic changes of melanocytes (Mc) due to contact with nerve fibers (co-culture) were observed.
The results are shown in Figure 7.
（２）結果・考察
図７に示すとおり、神経線維とメラノサイト（Ｍｃ）の共培養により、メラノサイト（Ｍｃ）の黒色化の度合いが高くなることがわかった。
(2) Results and Discussion As shown in FIG. 7, it was found that co-culture of nerve fibers and melanocytes (Mc) increased the degree of blackening of melanocytes (Mc).
以上の結果は、シミ濃度が高いほど真皮の神経線維量が多いことを示している。
したがって、真皮の神経線維量に基づき、対象者の肌のシミ濃度を推定できることがわかった。
また、肌のシミ濃度に基づき、真皮の神経線維量を推定できることがわかった。
These results indicate that the higher the stain concentration, the greater the amount of nerve fibers in the dermis.
Therefore, it was found that the concentration of spots on a subject's skin can be estimated based on the amount of nerve fibers in the dermis.
They also found that it is possible to estimate the amount of nerve fibers in the dermis based on the density of skin blemishes.
＜実施例３－２＞ 神経線維との接触によるメラノサイト（Ｍｃ）の表現型変化の検証
次に、神経線維との接触によるメラノサイト（Ｍｃ）の表現型変化の検証をおこなった。
Example 3-2 Verification of phenotypic change in melanocytes (Mc) due to contact with nerve fibers Next, verification was carried out on phenotypic change in melanocytes (Mc) due to contact with nerve fibers.
（１）試験
ｉＰＳ細胞より分化誘導した感覚神経細胞を２４ｗｅｌｌプレートに２００,０００ｃｅｌｌｓ／ｗｅｌｌ播種した。
感覚神経細胞を３日間培養した後、ヒトメラノサイトを１０,０００ｃｅｌｌｓ／ｗｅｌｌ播種し、２日間共培養を実施した。
(1) Test Sensory neurons induced to differentiate from iPS cells were seeded onto a 24-well plate at 200,000 cells/well.
After culturing the sensory neurons for 3 days, human melanocytes were seeded at 10,000 cells/well and co-cultured for 2 days.
共培養後、細胞を、４％ＰＦＡを用い固定し、神経細胞・メラノサイトを免疫染色法（神経：ＰＧＰ９．５、Ｍｃ：ＴＹＲＰ１）にて染色した。染色後、光学顕微鏡・蛍光顕微鏡にて明視野画像および蛍光画像を取得した。 After co-culture, the cells were fixed using 4% PFA, and the neurons and melanocytes were stained by immunostaining (neurons: PGP9.5, Mc: TYRP1). After staining, bright-field and fluorescent images were obtained using an optical microscope and a fluorescent microscope.
取得した蛍光画像を基に神経とメラノサイトの接触の有無を、専門家による目視評価に供した。
また、神経とメラノサイトの接触画像（明視野）を二値化したものについて、専門家により目視にてメラノサイトの黒色程度を評価した。
結果を以下に示す。
Based on the acquired fluorescent images, experts visually evaluated whether or not there was contact between the nerves and melanocytes.
In addition, the contact images (bright field) of the nerves and melanocytes were binarized and the degree of black color of the melanocytes was visually evaluated by experts.
The results are shown below.
（２）結果・考察
表２、図８に示すとおり、神経線維とメラノサイト（Ｍｃ）の接触により、メラノサイト（Ｍｃ）の黒色化の度合いが高くなることがわかった。
(2) Results and Observations As shown in Table 2 and FIG. 8, it was found that contact between nerve fibers and melanocytes (Mc) increased the degree of blackening of melanocytes (Mc).
＜実施例４＞ シミ部位における、神経とメラノサイトの接触頻度の検証
次に、シミ部位における、神経とメラノサイトの接触頻度の検証をおこなった。
Example 4: Verification of contact frequency between nerves and melanocytes in pigmented spots Next, verification was carried out on the contact frequency between nerves and melanocytes in pigmented spots.
（１）試験材料及び測定部位の取得
本実施例では、前掲の表１に示すヒト皮膚を試験材料とした。そして、本実施例では、試験材料における、シミ部位の立体皮膚組織（シミのある表皮・真皮を含む立体皮膚組織）とシミ部位近傍の非シミ部位の立体皮膚組織（シミのない表皮・真皮を含む立体皮膚組織）を測定部位として選定した。そして、選定した部位の立体皮膚組織を、表１に示す大きさに切り出すことにより、取得した（図１ 参照）。
(1) Acquisition of Test Material and Measurement Site In this example, human skin shown in Table 1 above was used as the test material. In this example, three-dimensional skin tissue at a blemish site (three-dimensional skin tissue including epidermis and dermis with blemishes) and three-dimensional skin tissue at a non-blemish site near the blemish site (three-dimensional skin tissue including epidermis and dermis without blemishes) in the test material were selected as measurement sites. The three-dimensional skin tissue at the selected sites was then obtained by cutting it to the size shown in Table 1 (see FIG. 1).
（２）染色
実施例１と同様の方法により、シミ部位の立体皮膚組織（シミのある表皮・真皮を含む立体皮膚組織）と非シミ部位の立体皮膚組織（シミのない表皮・真皮を含む立体皮膚組織）を透明化し、染色をした。
(2) Staining Using the same method as in Example 1, the three-dimensional skin tissue of the blemished area (three-dimensional skin tissue including epidermis and dermis with blemishes) and the three-dimensional skin tissue of the non-blemished area (three-dimensional skin tissue including epidermis and dermis without blemishes) were made transparent and stained.
（３）解析
３Ｄ画像解析ソフト（Imaris）にて撮像した３Ｄ画像を開き、Ｃｏｌｏｃ機能を用いて３Ｄ空間内における神経とＭｃのシグナルが共局在する部位を検出した。
そして、検出した共局在部位の割合を定量化した。
結果を図９に示す。
(3) Analysis The captured 3D images were opened using 3D image analysis software (Imaris), and the Coloc function was used to detect areas where nerve and Mc signals co-localized in 3D space.
The proportion of colocalized sites detected was then quantified.
The results are shown in Figure 9.
（４）結果・考察
図９に示すとおり、シミ部位では神経とメラノサイトの接触頻度が有意に高いことを確認することができた。
(4) Results and Discussion As shown in Figure 9, it was confirmed that the frequency of contact between nerves and melanocytes was significantly higher in the pigmented area.
＜実施例５＞ 皮膚中における神経とメラノサイトの接触様式の同定(シナプス関連因子の発現確認)
次に、皮膚中における神経とメラノサイトの接触様式の同定をおこなった。
Example 5: Identification of the contact mode between nerves and melanocytes in the skin (Confirmation of the expression of synapse-related factors)
Next, we identified the contact pattern between nerves and melanocytes in the skin.
（１）試験
ＯＣＴ包埋済み正常皮膚組織から、クライオスタットにて１０μｍ切片を作製した。
作成した正常皮膚組織切片をＰＢＳにて洗浄（１０ｍｉｎ ｘ ３）した。
(1) Test From the OCT-embedded normal skin tissue, 10 μm sections were prepared using a cryostat.
The prepared normal skin tissue sections were washed with PBS (10 min x 3).
洗浄後、正常皮膚組織切片を１％Ｄｏｎｋｅｙ ｓｅｒｕｍ／ＰＢＳ（Ｂｌｏｃｋｉｎｇ ｓｏｌｕｔｉｏｎ）にて１ｈｒ静置（ＲＴ）し、１ｓｔ Ａｂ（シナプス関連因子：ＰＳＤ９５、メラノサイト：ＴＹＲＰ１）／Ｂｌｏｃｋｉｎｇ ｓｏｌｕｔｉｏｎにて１０／Ｎ（４℃）反応を行った。
反応後ＰＢＳにて洗浄（１０ｍｉｎ ｘ ３）し、２ｎｄ Ａｂ／Ｂｌｏｃｋｉｎｇ ｓｏｌｕｔｉｏｎにて１ｈｒ静置（ＲＴ）した。
静置後ＰＢＳにて洗浄（１０ｍｉｎ ｘ ３）し、ＤＡＰＩ入り封入剤で封入し蛍光顕微鏡にて観察した。
結果を図１０に示す。
After washing, the normal skin tissue sections were left to stand (RT) for 1 hour in 1% Donkey serum/PBS (Blocking solution) and then reacted with 1st Ab (synapse-related factor: PSD95, melanocyte: TYRP1)/Blocking solution at 10/N (4° C.).
After the reaction, the plate was washed with PBS (10 min x 3) and then allowed to stand in 2nd Ab/Blocking solution for 1 hr (RT).
After standing, the sections were washed with PBS (10 min x 3), mounted with a mounting medium containing DAPI, and observed under a fluorescent microscope.
The results are shown in Figure 10.
（２）結果・考察
図１０に示すとおり、神経とメラノサイトの接触部位では、ＰＳＤ９５の発現量が有意に高いことを確認することができた。
ここで、ＰＳＤ９５（ｐｏｓｔｓｙｎａｐｔｉｃ ｄｅｎｓｉｔｙ ｐｒｏｔｅｉｎ ９５）は、シナプス関連因子であって、シナプスの受け手側（シナプス後膜）に特異的に発現するタンパク質である（M. Hara, M. Toyoda, M. Yaar, J. Bhawan, E. M. Avila, I. R. Penner, B. A. Gilchrest, J Exp Med, Oct 1;184(4):1385-95 (1996)）。
すなわち、本試験の結果から、本試験の結果から、神経とメラノサイトの接触部位では、シナプス様接触がなされており、神経からメラノサイトへ神経伝達物質の分泌によるシグナル伝達を行っているといえる。
(2) Results and Discussion As shown in Figure 10, it was confirmed that the expression level of PSD95 was significantly higher at the contact site between nerves and melanocytes.
Here, PSD95 (postsynaptic density protein 95) is a synapse-associated factor, which is a protein that is specifically expressed on the receiving side of the synapse (postsynaptic membrane) (M. Hara, M. Toyoda, M. Yaar, J. Bhawan, EM Avila, IR Penner, BA Gilchrest, J Exp Med, Oct 1;184(4):1385-95 (1996)).
In other words, the results of this study indicate that synapse-like contact is made at the contact site between nerves and melanocytes, and signals are transmitted from nerves to melanocytes through the secretion of neurotransmitters.
また、本試験の結果から、表皮のＰＳＤ９５発現量に基づき、神経線維量を推定できることがわかった。
Furthermore, the results of this study demonstrated that the amount of nerve fibers can be estimated based on the expression level of PSD95 in the epidermis.
Claims (4)
定性的に真皮の神経線維が多いと推定する、及び／又は、対象者の肌全体のうち真皮の神経線維の多い部位であると推定する、真皮の神経線維の推定方法。 The higher the concentration of spots on your skin,
A method for estimating dermal nerve fibers, which qualitatively estimates that there are many dermal nerve fibers and/or estimates that this is an area of a subject's entire skin that has a large number of dermal nerve fibers.
定性的に真皮の神経線維が多いと推定する、及び／又は、対象者の肌全体のうち真皮の神経線維の多い部位であると推定することを含む、請求項１に記載の推定方法。 The spatial density of nerve fibers in the dermis is estimated, and the higher the spatial density, the
The method of claim 1 , further comprising qualitatively estimating that the dermis has a high number of nerve fibers and/or estimating that the area is a part of the subject's entire skin that has a high number of dermal nerve fibers.
対象者から取得した肌のシミ濃度に関する情報を、前記記憶手段に記憶された前記相関データに適用し、肌のシミ濃度が高いほど、定性的に真皮の神経線維が多いと推定する、及び／又は、対象者の肌全体のうち真皮の神経線維の多い部位であると推定する推定手段と、を備える、真皮の神経線維推定装置。 A storage means for storing correlation data between the amount of nerve fibers in the dermis and the density of spots on the skin;
A dermal nerve fiber estimation device comprising: an estimation means for applying information regarding the density of skin blemishes obtained from the subject to the correlation data stored in the memory means, and estimating that the higher the density of skin blemishes, the more dermal nerve fibers there are qualitatively, and/or estimating that the area of the subject's entire skin that has a large number of dermal nerve fibers.
対象者から取得した肌のシミ濃度に関する情報を、前記記憶手段に記憶された前記相関データに適用し、肌のシミ濃度が高いほど、定性的に真皮の神経線維が多いと推定する、及び／又は、対象者の肌全体のうち真皮の神経線維の多い部位であると推定する推定手段と、として機能させるための、真皮の神経線維推定プログラム。 A computer includes a storage means for storing correlation data between the amount of nerve fibers in the dermis and the density of skin spots,
A dermal nerve fiber estimation program for functioning as an estimation means for applying information regarding the concentration of skin blemishes obtained from a subject to the correlation data stored in the memory means, and qualitatively estimating that the higher the concentration of skin blemishes, the more dermal nerve fibers there are, and/or estimating that the area of the subject's entire skin that has a large number of dermal nerve fibers.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2020003128 | 2020-01-10 | ||
| JP2020003128 | 2020-01-10 |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JP2021110720A JP2021110720A (en) | 2021-08-02 |
| JP7650019B2 true JP7650019B2 (en) | 2025-03-24 |
Family
ID=77059800
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2020148087A Active JP7650019B2 (en) | 2020-01-10 | 2020-09-03 | Method for estimating amount of nerve fibers in dermis, method for estimating skin blemish concentration and/or risk of blemish occurrence |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JP7650019B2 (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009219491A (en) | 2008-03-17 | 2009-10-01 | L'oreal Sa | Functional pigmented skin equivalent |
| JP2013021946A (en) | 2011-07-19 | 2013-02-04 | Shiseido Co Ltd | In vitro skin model composition for evaluating skin stimulation and evaluation method using the same |
| JP2017216965A (en) | 2016-06-09 | 2017-12-14 | 株式会社ナリス化粧品 | Method for screening spot improvement ingredients |
-
2020
- 2020-09-03 JP JP2020148087A patent/JP7650019B2/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2009219491A (en) | 2008-03-17 | 2009-10-01 | L'oreal Sa | Functional pigmented skin equivalent |
| JP2013021946A (en) | 2011-07-19 | 2013-02-04 | Shiseido Co Ltd | In vitro skin model composition for evaluating skin stimulation and evaluation method using the same |
| JP2017216965A (en) | 2016-06-09 | 2017-12-14 | 株式会社ナリス化粧品 | Method for screening spot improvement ingredients |
Non-Patent Citations (7)
| Title |
|---|
| ［記者発表］皮膚の奥の神経が肌のシミ形成に影響、重要な働きを担う因子も同定，東京大学 生産技術研究所，2022年09月21日，https://www.iis.u-tokyo.ac.jp/ja/news/3977/ |
| Masahiro Hara，Innervation of Melanocytes in Human Skin，J. Exp. Med.，1996年10月，Vol.184，Page.1385-1395 |
| Nakayama, K.，The association between senile lentigo and intracutaneous nerve structure，Journal of Investigative Dermatology，2019年05月，Vol.139 No.5 Suppl.1，Page.S135 |
| Norihiko Yokoi，Identification of PSD-95 Depalmitoylating Enzymes，Journal of Neuroscience，2016年06月15日，Vol.36 No.24，Page.6431-6444 |
| コトバンク 「神経終末」，https://kotobank.jp/word/%E7%A5%9E%E7%B5%8C%E7%B5%82%E6%9C%AB-81601 |
| シミの部位には神経が集まっていたことを初めて解明，ポーラ化成工業株式会社，2019年11月05日，https://www.pola-rm.co.jp/pdf/release_20191105.pdf |
| 神経の影響によるメラノサイト活性化をヒメフウロエキスが抑制することを発見，ポーラ化成工業株式会社，2021年11月30日，https://www.pola-rm.co.jp/pdf/release_20211130_01.pdf |
Also Published As
| Publication number | Publication date |
|---|---|
| JP2021110720A (en) | 2021-08-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Quinn et al. | Optical metrics of the extracellular matrix predict compositional and mechanical changes after myocardial infarction | |
| Baugh et al. | Non-destructive two-photon excited fluorescence imaging identifies early nodules in calcific aortic-valve disease | |
| JP2025503388A (en) | Label-free virtual immunohistochemistry of tissues using deep learning | |
| Prabhu et al. | Objective assessment of endogenous collagen in vivo during tissue repair by laser induced fluorescence | |
| US11497403B2 (en) | Devices, methods, and systems for detection of collagen tissue features | |
| Eklouh-Molinier et al. | In vivo confocal Raman microspectroscopy of the human skin: highlighting of spectral markers associated to aging via a research of correlation between Raman and biometric mechanical measurements | |
| Alsamad et al. | In depth investigation of collagen non-enzymatic glycation by Raman spectroscopy | |
| Verzeaux et al. | Atopic skin: In vivo Raman identification of global molecular signature, a comparative study with healthy skin | |
| Adams et al. | Assessing the progression of systemic sclerosis by monitoring the tissue optic axis using PS-OCT | |
| Quatela et al. | In vivo Raman microspectroscopy: intra-and intersubject variability of stratum corneum spectral markers | |
| Karnachoriti et al. | Biochemical differentiation between cancerous and normal human colorectal tissues by micro-Raman spectroscopy | |
| Kiss et al. | Ex vivo nonlinear microscopy imaging of Ehlers–Danlos syndrome-affected skin | |
| Roorda | Optoretinography is coming of age | |
| Haluszka et al. | Nanomechanical and nonlinear optical properties of glycated dental collagen | |
| Kim et al. | Raman spectroscopy in cellular and tissue aging research | |
| US20150072434A1 (en) | Methods for assessing risk of bone fracture | |
| Becker et al. | Exploring the relationship between epigenetic DNA methylation and cardiac fibrosis through Raman microspectroscopy | |
| JP7650019B2 (en) | Method for estimating amount of nerve fibers in dermis, method for estimating skin blemish concentration and/or risk of blemish occurrence | |
| Chung et al. | Label‐free histological analysis of retrieved thrombi in acute ischemic stroke using optical diffraction tomography and deep learning | |
| Li et al. | Label-free assessment of collagenase digestion on bovine pericardium properties by fluorescence lifetime imaging | |
| JP7691596B2 (en) | Screening method for agents for suppressing and/or improving skin pigmentation symptoms | |
| Langton et al. | Heterogeneity of fibrillin‐rich microfibrils extracted from human skin of diverse ethnicity | |
| JP6103700B2 (en) | Discrimination method and apparatus for cardiac tissue using Raman scattering | |
| Kunchur et al. | Development of an image classification pipeline for atherosclerotic plaques assessment using supervised machine learning | |
| Zhou et al. | Label-free quantification of microscopic alignment in engineered tissue scaffolds by polarized Raman spectroscopy |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| A521 | Request for written amendment filed |
Free format text: JAPANESE INTERMEDIATE CODE: A821 Effective date: 20200903 |
|
| A621 | Written request for application examination |
Free format text: JAPANESE INTERMEDIATE CODE: A621 Effective date: 20230728 |
|
| A977 | Report on retrieval |
Free format text: JAPANESE INTERMEDIATE CODE: A971007 Effective date: 20240325 |
|
| A131 | Notification of reasons for refusal |
Free format text: JAPANESE INTERMEDIATE CODE: A131 Effective date: 20240423 |
|
| A521 | Request for written amendment filed |
Free format text: JAPANESE INTERMEDIATE CODE: A523 Effective date: 20240620 |
|
| A02 | Decision of refusal |
Free format text: JAPANESE INTERMEDIATE CODE: A02 Effective date: 20240917 |
|
| A521 | Request for written amendment filed |
Free format text: JAPANESE INTERMEDIATE CODE: A523 Effective date: 20241028 |
|
| A521 | Request for written amendment filed |
Free format text: JAPANESE INTERMEDIATE CODE: A821 Effective date: 20241028 |
|
| A911 | Transfer to examiner for re-examination before appeal (zenchi) |
Free format text: JAPANESE INTERMEDIATE CODE: A911 Effective date: 20241122 |
|
| TRDD | Decision of grant or rejection written | ||
| A01 | Written decision to grant a patent or to grant a registration (utility model) |
Free format text: JAPANESE INTERMEDIATE CODE: A01 Effective date: 20250225 |
|
| A61 | First payment of annual fees (during grant procedure) |
Free format text: JAPANESE INTERMEDIATE CODE: A61 Effective date: 20250303 |
|
| R150 | Certificate of patent or registration of utility model |
Ref document number: 7650019 Country of ref document: JP Free format text: JAPANESE INTERMEDIATE CODE: R150 |