Touch enables humans to recognize the location, motion, shape, and properties of contacted objects in the real world through mechanoreceptors distributed widely across the skin. However, existing tactile displays typically stimulate only the ventral surfaces of the fingers and hands, limiting the range and richness of touch-based interactions in interactive systems. Here, we present FingerWrap, a high-density pneumatic pin-array display that wraps around the finger and activates the widely distributed mechanoreceptors. FingerWrap uses 337 pins arranged at 13pins/cm$^{2}$, which cover the ventral, dorsal, and lateral surfaces of the finger up to 45mm from the fingertip, enabling precise spatiotemporal stimulation across continuous regions of the finger skin. Across six perceptual experiments, we show that FingerWrap can provide tactile experiences that ventral-only displays cannot achieve. These include the discrimination of stimulus locations and motion trajectories across multiple regions of the finger skin, the recognition of three-dimensional shape features, and the perception of realistic resistance when the finger is immersed in virtual liquids. This display, which enables a rich and realistic touch experience, could serve as a platform for exploring novel tactile interactions and basic scientific research.

Humans achieve stable and dexterous object manipulation by coordinating grasp forces across multiple fingers and palms, facilitated by a unified tactile memory system in the somatosensory cortex. This system encodes and stores tactile experiences across skin regions, enabling the flexible reuse and transfer of touch information. Inspired by this biological capability, we present GenForce, the first framework that enables transferable force sensing across diverse tactile sensors in robotic hands. GenForce unifies tactile signals into shared marker representations, analogous to cortical sensory encoding, allowing force prediction models trained on one sensor to be transferred to others without the need for exhaustive force data collection. We demonstrate that GenForce generalizes across both homogeneous sensors with varying configurations and heterogeneous sensors with distinct sensing modalities and material properties. This transferable force sensing capability is also demonstrated in robot manipulation tasks including daily-object grasping, slip detection and compensation with multi-sensor force coordination. Our results highlight a scalable paradigm for cross-sensor robotic tactile sensing, offering new pathways toward adaptable and tactile memory-driven robot manipulation in unstructured environments.

Maternal mortality in Brazil remains a critical indicator of social and racial inequalities, reflecting structural failures in access to and quality of obstetric care. Black women, particularly those categorized as black or brown, are at a higher risk of dying during pregnancy, childbirth, or the postpartum period. This is the result of the intersection of institutional racism, poverty, and social vulnerabilities. This study aimed to analyze trends and associated factors of maternal mortality among black women in Brazil from 2000 to 2020. This is a retrospective cohort analytical study using data from the Brazilian Mortality Information System. The sample included women aged 10 to 49 years whose underlying cause of death was classified under ICD-10 codes O00-O99. Descriptive and bivariate analyses were conducted, as well as Poisson and multinomial logistic regressions to estimate adjusted risk ratios according to skin color, education, region, type, and place of death. A total of 40,907 maternal deaths were identified, with 59.2% occurring among black women. The maternal mortality ratio was 39% higher among black women compared to white women and more than double among Indigenous women. Low education, residence in the North and Northeast regions, deaths outside hospital settings, and lack of formal investigation were independently associated with increased risk. Direct obstetric causes accounted for most deaths, with hypertensive disorders and puerperal complications being the leading conditions. Maternal mortality among black women in Brazil reveals deep structural inequalities. Urgent public policies that incorporate an intersectional perspective, addressing race, gender, and class, are necessary to reduce disparities and ensure equitable and dignified maternal healthcare.

Sensory afferents in the mammary papilla are eliminated during the lactation.

Small fiber neuropathy (SFN) is an underdiagnosed condition characterized by sensory and autonomic dysfunction due to impairment of small nerve fibers in skin, blood vessels, and internal organs. Various underlying disorders are associated with SFN, and the pathophysiology of nerve fiber damage and functional impairment is the subject of extensive research. Diagnosis of SFN is challenging as standard electrodiagnostic techniques assess large fiber function and therefore are normal in SFN patients. The current gold standard for SFN diagnosis in humans is a skin biopsy, commonly obtained from the distal leg, hairy skin region, with evaluation of intraepidermal nerve fiber density (IENFD) using protein gene product 9.5 (PGP9.5) immunolabeling. While well-established in clinical practice, equivalent standardized, reproducible methods for assessing IENFD in experimental mouse models are lacking, which limits translational research in this field. Previous work in mice has relied on diverse antibodies, variable tissue sampling, and the use of confocal microscopy to trace nerve fibers. Other approaches have used chromogenic precipitate-based staining, which limits the ability to co-label multiple proteins. Here, we present a detailed, simple, and reproducible protocol for IENFD quantification of small nerves in the distal glabrous skin of the mouse hind paw. This protocol uses the two distal footpads, ensuring consistent sampling across animals. Prior to sectioning, the tissue is fixed and cryoprotected. Serial 20-μm sections are mounted on glass slides, dried, permeabilized, blocked, and immunostained with an anti-PGP9.5 monoclonal antibody, and then detected by binding secondary fluorescent-labeled antibodies. Although murine hairy skin analysis may apparently show a higher translational value, as it better reflects human biopsy sites, it is compromised by dense hair shafts and follicles, which interrupt epidermis continuity and thus interfere with sampling consistency. Polyneuropathy sensory symptoms, in fact, begin at the most distal sensory site, which is the glabrous skin of the toes. Thus, evaluation of this anatomical location best represents the clinical realm and may have the best sensitivity for identifying early axonal changes. In this protocol, we focused on IENFD quantification as done in human samples. Mechanoreceptors such as Meissner corpuscles are detectable and quantifiable by this method, and represent additional value since pressure-evoked pain, transmitted by these, is often reported by affected individuals. This immunolabeling protocol can be completed within one day [involving a small number of animals, where all three stages can be performed during a long working day (approximately 12 h)], while the entire workflow, including fixation and cryoprotection, is completed in up to 72 h. Importantly, the dermal and epidermal small fibers can be visualized using a standard fluorescence microscope, thereby avoiding the need for confocal imaging while maintaining high reproducibility. Preliminary validation in several animal models of inflammatory neuropathy and pain demonstrated a reproducible approximately 50% reduction in IENFD compared to controls, reaching statistical significance with n = 4 per group. This method supports SFN research and preclinical evaluation of novel therapeutics.Key features• Immunostaining protocol for visualizing small epidermal nerve fibers in mouse hind paw footpads.• Use of PGP9.5 labeling, with a monoclonal antibody that is used for human diagnostics, enabling translational comparability between mouse models and clinical studies.• Fluorescence microscopy analysis, without dependence on confocal imaging.• A rapid (12–72 h) and reproducible workflow for skin processing and intraepidermal nerve fiber quantification.

ABSTRACTBackground and AimsAcupuncture is a widely used therapeutic practice that targets specific points on or beneath the skin, known as acupoints. While acupoints are thought to exhibit low electrical resistance, their underlying biophysical and molecular characteristics remain incompletely understood. This study investigates the presence and properties of high‐conductivity regions in surgically isolated human skin.MethodsHigh‐conductivity points (HCPs) were identified on human skin explants using a clinical conductivity‐based acupoint detector. Histological, transcriptomic, and metabolomic analyses were performed on HCP and control regions, with and without needle stimulation. To probe mechanistic pathways, human keratinocytes and fibroblasts were cultured under biotin‐deficient conditions, mimicking stimulation‐induced metabolic changes.ResultsNo significant structural differences were observed between HCPs and control skin. However, RNA sequencing revealed that needled HCPs activated gene programs resembling those of anatomically defined murine acupoints. Metabolomic profiling showed a stimulation‐specific decrease in biotin levels at HCPs. In vitro, biotin deficiency altered acetyl‐CoA carboxylase regulation and increased ATP production via mitochondrial respiration and glycolysis.ConclusionThese findings suggest that biotin‐dependent metabolic reprogramming occurs at electrically distinct skin regions in response to physical stimulation. While the relationship between HCPs and classical acupoints remains to be fully established, this study provides novel insights into the local biochemical responses associated with acupuncture.

Abstract Transdermal drug delivery (TDD) is a non-invasive approach for administering therapeutic medications through the skin. This research proposes a spine–leaf resistor–capacitor (SLRC) circuit to analyse the impedance characteristics of different skin layers during drug delivery. To optimise the SLRC circuit parameters, the Ebola Optimisation Algorithm (EOA) minimises errors and improves computational efficiency. The Poisson–Boltzmann–Nernst–Planck (PBNP) model is used to calculate input parameters such as ion concentrations and electrotransport flux, to derive the drug concentration based on input parameters. A MATLAB simulator calculates drug penetration across stratified skin regions. According to the SLRC results, the Montague, constant phase element (CPE), and Tregear models performed better in predicting drug penetration and electrotransport flux than more conventional models. Compared to the traditional Montague and Tregear models, the EOA improved performance by reducing the mean absolute percentage error ( MAPE ) to as low as 0.134. The proposed model achieved an R 2 value of 0.98 when validated against the impedance datasets, confirming high prediction accuracy. Furthermore, simulated results revealed that an optimal frequency of 4 × 10 3 Hz provides the best impedance and drug penetration, demonstrating the importance of frequency and current density in increasing drug levels. The proposed model enhances the precision and efficiency of TDD, offering significant potential for clinical and pharmaceutical applications.

Introduction: Indolent systemic mastocytosis (ISM) is a clonal mast cell (MC) disease primarily driven by D816V-mutant KIT. ISM is characterized by accumulation and hyperactivation of aberrant MCs in organs including skin, often leading to skin-related symptoms. Skin findings were characterized in patients with ISM treated with avapritinib, a potent, selective KIT D816V inhibitor, in PIONEER (NCT03731260). Methods: Long-term safety and efficacy of avapritinib 25 mg once daily plus best supportive care was evaluated in 226 patients with ISM. Skin symptoms were evaluated by the ISM-Symptom Assessment Form skin domain score (0–30) and individual skin symptoms (0–10) of spots, itching, and flushing from baseline to 48 and 144 weeks. Changes in skin lesions by photography were captured until 48 weeks. Results: Mean (standard deviation [SD]) change from baseline in the skin symptom domain was −6.89 (7.11) at Week 48 and −2.48 (2.50), –2.45 (2.82), –1.95 (2.72) for spot severity, itching, and flushing, respectively. At Week 144, the mean (SD) change in skin symptom domain was –8.14 (7.86). Patients with paired photographs (n=51) showed a median percent reduction in lesion surface area in the most affected skin region of –60% after 48 weeks; 82% had lightened skin lesion color. Long-term follow-up (up to 5 years; median 3 years) demonstrated avapritinib was generally well tolerated with no new safety concerns observed. Conclusion: Avapritinib provided sustained and durable improvements in skin manifestations of ISM and demonstrated a favorable benefit–risk profile, highlighting the ability of avapritinib to achieve long-term disease modification.

Hair gets its color from melanin produced by melanocytes in the hair matrix. The coloration patterns observed in most terrestrial mammals arise from the diverse color combinations within their fur, which depends on the distribution pattern of melanocyte-containing hair follicles. Albino rats genetically produce no melanin and their coats are thus white, but we speculated that melanocytes differentiate and localize within these rats’ hair matrix. We conducted a reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis, which revealed both the mRNA expressions of two melanocyte markers (dopachrome tautomerase and tyrosinase) in skin of male albino (SD, Wistar, and F344) rats and the differences in the markers’ expression levels among skin areas. Immunohistochemistry using anti-Dct antibody demonstrated that immunopositive cells, i.e., melanocytes, were localized in the rats’ hair matrix, and that melanocytes containing hair bulbs were distributed in head, dorsal thorax, and dorsal midline areas, which is similar to hooded rats. Our results suggest that differences in the melanocyte presence among the skin regions should be considered when the results of gene expression analyses of albino rat skin are interpreted.

Skin lesion segmentation identifies and outlines the boundaries of abnormal skin regions. Accurate segmentation may help in the early detection of skin cancer. Accurate Skin Lesion Segmentation is still challenging due to different skin color tones, variations in shape, and body hairs. Moreover, variability in the lesion appearance, quality of the images, and lack of clear skin boundaries make the problem even harder. This paper proposes a SegNet model with spatial attention mechanisms for skin lesion segmentation. Adding one component of spatial attention to SegNet allows the proposed model to focus more on specific parts across the image, eventually leading to a better segmentation of the lesion boundary. The proposed model was evaluated on the ISIC 2018 dataset. Our proposed model attained an average accuracy of 96.25%, and the average dice coefficient equals 0.9052. The model's performance indicates its possible application in automated skin disease diagnosis.

Abstract We present a 2D axisymmetric fluid model consistently coupled with a 0D Boltzmann-solver electron energy distribution function and a detailed Ar/O₂ chemistry set that includes electron-impact dissociation and excitation, energy-transfer (quenching) reactions of O( 1 D ), ion neutral exchange, and wall recombination. Across 3–100 mTorr and 10%–90% O₂ mixing ratio, we quantify the spatial distributions of O( 3 P ) and O( 1 D ) and the O( 1 D ) flux at the target boundary. The O( 1 D ) density and flux are primarily set by dissociative excitation of O 2 (e + O 2 ( X 3 Σ g − ) → e + O( 1 D ) + O( 3 P )), electron-impact excitation of atomic oxygen (e + O( 3 P ) → e + O( 1 D )), and energy transfer from O( 1 D ) to O 2 (O 2 + O( 1 D ) → O( 3 P ) + O 2 (b 1 Σ g + )). In addition, the O( 1 D ) density and flux are modulated by (i) pressure-driven transport limitation (reduced diffusion and shorter mean free path), (ii) composition-dependent shifts between net production and O 2 quenching, and (iii) enhanced thermal speed and thermal diffusion at low O 2 due to elevated gas temperature. Consequently, high pressure and high O 2 density confine production to the under-coil inductive skin region and suppress the target-boundary flux, whereas at low O 2 density the weaker quenching and higher gas temperature partially offset transport-limited attenuation. These results indicate that predictive control of the O( 1 D ) density and flux requires a joint treatment of transport, explicit energy-transfer quenching, and thermal-diffusion effects within a detailed reaction set.

A novel device for studying temperature and touch interactions.

The thermal properties of human skin are of great interest for understanding local and global body heat loss, various physiological responses or even skin injuries. This study presents a wearable, non-invasive skin calorimeter designed for in vivo measurement of skin heat flux, heat capacity, and thermal resistance. The device, based on the principle of non-differential heat conduction calorimetry, consists of a programmable thermostat, a heat flux sensor and a Peltier cooling system. To operate the device, we propose and calibrate a calorimetric thermal model that includes the skin. This new model approach allows to estimate the core temperature of the tissue where the measurement is performed. Experimental validation of the device was carried out on localized skin areas, both at rest and during moderate physical activity. This skin calorimeter allows determination of thermal properties in different skin regions, with an accuracy of ± 2 mW for the heat flux, ± 1 K/W for the thermal resistance, and ± 0.05 J/K for the heat capacity, for a 2 × 2 cm² skin region. The results confirm the applicability of these devices in sports medicine, thermoregulation studies, and medical diagnostics. This work also includes simulations of the calorimeter’s operation, which help to define its operating range and to study the interaction between the device and the human skin.

Accurate freckle segmentation is essential for dermatological assessments and cosmetic applications, but existing lesion detection techniques are primarily designed for well-defined skin abnormalities such as melanomas and tumors, making them less effective at capturing subtle features like freckles. In this study, we present an automated freckle segmentation framework that integrates the Gaussian Mixture Model (GMM) and the Viola-Jones algorithm for skin segmentation, coupled with an energy map-based approach for freckle detection. The process begins with image is clustered using GMM, followed by facial region detection with the Viola-Jones algorithms. A post-processing step then segments the selection of the skin region. Subsequently, an energy map is generated by combining the blue and saturation channels, while Contrast-Limited Adaptive Histogram Equalization (CLAHE) and morphological operations enhance freckle contrast. The final segmentation is achieved through binarization and additional post-processing techniques. Quantitative evaluations demonstrate that the proposed method surpasses conventional approaches in recall, Intersection over Union (IoU), and Dice coefficient, highlighting its effectiveness in accurate freckle detection and segmentation. These findings indicate that, with further refinement, the proposed framework holds significant potential for applications in both clinical dermatology and cosmetic science.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-20275-4.

We propose a data augmentation technique utilizing a Diffusion-based generative deep learning model to address the issue of data scarcity in skin disease diagnosis research. Specifically, we enhanced the Stable Diffusion model, a Latent Diffusion Model (LDM), to generate high-quality synthetic images. To mitigate detail loss in existing Diffusion models, we incorporated lesion area masks and improved the encoder and decoder structures of the LDM. Multi-level embeddings were applied using a CLIP encoder-based image encoder to capture detailed representations, ranging from textures to overall shapes. Additionally, we employed pre-trained segmentation and inpainting models to generate normal skin regions and used interpolation techniques to synthesize synthetic images with gradually varying visual characteristics, while having limitations for clinical use, this approach contributes to enhanced data diversity and can be used as reference material. To validate our method, we conducted classification experiments on seven skin diseases using datasets combining synthetic and real images. The results showed improvements in classification performance, demonstrating the effectiveness of the proposed technique in addressing medical data scarcity and enhancing diagnostic accuracy.

We propose a data augmentation technique utilizing a Diffusion-based generative deep learning model to address the issue of data scarcity in skin disease diagnosis research. Specifically, we enhanced the Stable Diffusion model, a Latent Diffusion Model (LDM), to generate high-quality synthetic images. To mitigate detail loss in existing Diffusion models, we incorporated lesion area masks and improved the encoder and decoder structures of the LDM. Multi-level embeddings were applied using a CLIP encoder-based image encoder to capture detailed representations, ranging from textures to overall shapes. Additionally, we employed pre-trained segmentation and inpainting models to generate normal skin regions and used interpolation techniques to synthesize synthetic images with gradually varying visual characteristics, while having limitations for clinical use, this approach contributes to enhanced data diversity and can be used as reference material. To validate our method, we conducted classification experiments on seven skin diseases using datasets combining synthetic and real images. The results showed improvements in classification performance, demonstrating the effectiveness of the proposed technique in addressing medical data scarcity and enhancing diagnostic accuracy.

Patient assistance protocol based on continuous dose monitoring in interventional cardiological procedures.

Organic analyses of past organisms enhance our understanding of Earth's evolutionary history, complementing the macrofossil record. Biomolecular remains are typically vulnerable to diagenetic mineralisation, but can persist in exceptional depositional settings such as Lagerstätten. Their preservation is usually linked to anoxic conditions that exclude aerobic degraders. However, we report intact skin tissue of the fossil fish Diplomystus dentatus from the Fossil Basin Lagerstätte (USA), preserved through phosphate permineralisation in an oxygen-enriched microenvironment. Notably, only the skin with scales retained tissue integrity, and this organic material was closely associated with fluorapatite absent from the surrounding matrix. Geochemical analyses revealed higher oxidation states in the skin than in vertebrae and bones, likely due to early degradation of the fatty acid-rich dermis. Redox-sensitive biomarkers and isotopic data (δ15N) indicated a less reducing environment in the skin region compared to bones and the eye, yet more reducing than the surrounding sediment. This localised oxygen enrichment fostered sulphide-oxidising bacteria, evidenced by mineral sulphates (barite) found only in the skin. Phosphatisation was likely driven by dermal breakdown and the release of H+, reducing alkalinity and enabling phosphate mineralisation over the carbonate system.

In reconstructive surgery, usage of different flaps is essential to cover tissue defects. Twisting, stretching or damaging the vascular pedicle may jeopardize the flaps’ viability. The aim of our experiment was to monitor tissue perfusion parameters of local versus rotated musculocutaneous flaps. In rats, musculus cutaneus maximus-based muscle–skin flaps were prepared bilaterally: one was sutured back to its original position, while the other flap was rotated to the ventral chest region (Flap group). In the Control group, flaps were not prepared. Tissue microcirculation was monitored intraoperatively, and on the 7th and 14th postoperative days. Blood samples were taken for testing hematological and hemorheological parameters. At the end of the observation period, biopsies were taken for biomechanical (tensile strengths) and histological investigations. We found that leukocyte and platelet counts significantly increased in the Flap group, while erythrocyte deformability decreased and aggregation increased. Although both local and rotated flaps survived and wound healing progressed well, in microcirculatory recordings, hypoperfusion and visible red blood cell aggregates were seen mostly in the rotated flaps. The rotated flaps were biomechanically weaker compared to local flaps or intact skin regions. This new model seems to be suitable for studying further flap pathophysiology focusing on tissue perfusion.

Translesion Synthesis DNA Polymerase Gene Expression Is Impacted by Age and IGF-1 in Epidermal Human Skin