Optimizing vitiligo diagnosis with ResNet and Swin transformer deep learning models: a study on performance and interpretability.

Vitiligo is a hypopigmented skin disease characterized by the loss of melanin. The progressive nature and widespread incidence of vitiligo necessitate timely and accurate detection. Usually, a single diagnostic test often falls short of providing definitive confirmation of the condition, necessitating the assessment by dermatologists who specialize in vitiligo. However, the current scarcity of such specialized medical professionals presents a significant challenge. To mitigate this issue and enhance diagnostic accuracy, it is essential to build deep learning models that can support and expedite the detection process. This study endeavors to establish a deep learning framework to enhance the diagnostic accuracy of vitiligo. To this end, a comparative analysis of five models including ResNet (ResNet34, ResNet50, and ResNet101 models) and Swin Transformer series (Swin Transformer Base, and Swin Transformer Large models), were conducted under the uniform condition to identify the model with superior classification capabilities. Moreover, the study sought to augment the interpretability of these models by selecting one that not only provides accurate diagnostic outcomes but also offers visual cues highlighting the regions pertinent to vitiligo. The empirical findings reveal that the Swin Transformer Large model achieved the best performance in classification, whose AUC, accuracy, sensitivity, and specificity are 0.94, 93.82%, 94.02%, and 93.5%, respectively. In terms of interpretability, the highlighted regions in the class activation map correspond to the lesion regions of the vitiligo images, which shows that it effectively indicates the specific category regions associated with the decision-making of dermatological diagnosis. Additionally, the visualization of feature maps generated in the middle layer of the deep learning model provides insights into the internal mechanisms of the model, which is valuable for improving the interpretability of the model, tuning performance, and enhancing clinical applicability. The outcomes of this study underscore the significant potential of deep learning models to revolutionize medical diagnosis by improving diagnostic accuracy and operational efficiency. The research highlights the necessity for ongoing exploration in this domain to fully leverage the capabilities of deep learning technologies in medical diagnostics.

From mice to men: An assessment of preclinical model systems for the study of vitiligo.

Vitiligo is an autoimmune skin disease of multiple etiology, for which there is no complete cure. This chronic depigmentation is characterized by epidermal melanocyte loss, and causes disfigurement and significant psychosocial distress. Mouse models have been extensively employed to further our understanding of complex disease mechanisms in vitiligo, as well as to provide a preclinical platform for clinical interventional research on potential treatment strategies in humans. The current mouse models can be categorized into three groups: spontaneous mouse models, induced mouse models, and transgenic mice. Despite their limitations, these models allow us to understand the pathology processes of vitiligo at molecule, cell, tissue, organ, and system levels, and have been used to test prospective drugs. In this review, we comprehensively evaluate existing murine systems of vitiligo and elucidate their respective characteristics, aiming to offer a panorama for researchers to select the appropriate mouse models for their study.

Self-correction of cycle threshold values by a normal distribution-based process to improve accuracy of quantification in real-time digital PCR.

The digital polymerase chain reaction (dPCR) is a new and developing nucleic acid detection technology with high sensitivity that can realize the absolute quantitative analysis of samples. In order to improve the accuracy of quantitative results, real-time digital PCR emphasizes the kinetic information during amplification to identify prominent abnormal data. However, it is challenging to use a unified standard to accurately classify the amplification curve of each well as negative and positive, due to the interference caused by various factors in the experiment. In this work, a normal distribution-based cycle threshold value self-correcting model (NCSM) was established, which focused on the feature of the cycle threshold values in amplification curves and conducted continuous detection and correction on the whole. The cycle threshold value distribution was closer to the ideal normal distribution to avoid the influence of interference. Thus, the model achieves a more accurate classification between positive and negative results. The corrective process was applied to plasmid samples and resulted in an accuracy improvement from 92 to 99%. The coefficient of variation was below 5% when considering the quantitation of a range between 100 and 10,000 copies. At the same time, by utilizing this model, the distribution of cycle threshold values at the endpoint can be predicted with fewer thermal cycles, which can reduce the cycling time by around 25% while maintaining a consistency of more than 98%. Therefore, using the NCSM can effectively enhance the quantitative accuracy and increase the detection efficiency based on the real-time dPCR platform.

TRPM2-dependent autophagy inhibition exacerbates oxidative stress-induced CXCL16 secretion by keratinocytes in vitiligo.

Vitiligo is a depigmented skin disease due to the destruction of melanocytes. Under oxidative stress, keratinocyte-derived chemokine C-X-C motif ligand 16 (CXCL16) plays a critical role in recruiting CD8+ T cells, which kill melanocytes. Autophagy serves as a protective cell survival mechanism and impairment of autophagy has been linked to increased secretion of the proinflammatory cytokines. However, the role of autophagy in the secretion of CXCL16 under oxidative stress has not been investigated. Herein, we initially found that autophagy was suppressed in both keratinocytes of vitiligo lesions and keratinocytes exposed to oxidative stress in vitro. Autophagy inhibition also promoted CXCL16 secretion. Furthermore, upregulated transient receptor potential cation channel subfamily M member 2 (TRPM2) functioned as an upstream oxidative stress sensor to inhibit autophagy. Moreover, TRPM2-mediated Ca2+ influx activated calpain to shear autophagy related 5 (Atg5) and Atg12-Atg5 conjugate formation was blocked to inhibit autophagy under oxidative stress. More importantly, Atg5 downregulation enhanced the binding of interferon regulatory factor 3 (IRF3) to the CXCL16 promoter region by activating Tank-binding kinase 1 (TBK1), thus promoting CXCL16 secretion. These findings suggested that TRPM2-restrained autophagy promotes CXCL16 secretion via the Atg5-TBK1-IRF3 signaling pathway under oxidative stress. Inhibition of TRPM2 may serve as a potential target for the treatment of vitiligo. © 2024 The Pathological Society of Great Britain and Ireland.

A new prognostic model in chemotherapy-treated patients with recurrent or metastatic head and neck cancer: An analysis of ECOG-ACRIN E1305.

INTRODUCTION: For patients with recurrent or metastatic head and neck squamous cell carcinoma (R/M HNSCC) periodic reassessment of prognostic factors provides valuable information that can aid in patient stratification. PATIENTS AND METHODS: This post hoc analysis included all patients with R/M HNSCC enrolled in the ECOG-ACRIN E1305 phase III clinical trial who received first-line treatment with platinum-containing chemotherapy doublet with or without bevacizumab. Overall survival (OS) was estimated using the Kaplan-Meier method. Prognostic factors for OS were identified using univariate and multivariable analyses. A new prognostic model for OS was built retaining the prognostic factors which were significant in the final multivariable analysis (P < 0.05). RESULTS: All 403 study participants were included in the analysis. The median OS in the whole study cohort was 11.8 months (90% confidence intervals [CI], 10.6-13.2). The new prognostic model for OS comprised four risk factors (ECOG performance status [1 versus 0], primary tumor location [other versus oropharynx], presence of bone or liver metastasis, and prior radiation to the head and neck); patients with ≤ 2 (n = 249) and > 2 risk factors (n = 154) had a median OS of 15.2 and 7.6 months, respectively (Hazard ratio, 2.14; 95% CI, 1.73-2.66; P < 0.0001). CONCLUSIONS: The new proposed model includes 4 clinical prognostic factors that can be readily assessed at baseline. Similar models have the potential to improve trial design and optimize stratification of patients with R/M HNSCC.

Recent Advancements and Perspectives in the Diagnosis of Skin Diseases Using Machine Learning and Deep Learning: A Review.

OBJECTIVE: Skin diseases constitute a widespread health concern, and the application of machine learning and deep learning algorithms has been instrumental in improving diagnostic accuracy and treatment effectiveness. This paper aims to provide a comprehensive review of the existing research on the utilization of machine learning and deep learning in the field of skin disease diagnosis, with a particular focus on recent widely used methods of deep learning. The present challenges and constraints were also analyzed and possible solutions were proposed. METHODS: We collected comprehensive works from the literature, sourced from distinguished databases including IEEE, Springer, Web of Science, and PubMed, with a particular emphasis on the most recent 5-year advancements. From the extensive corpus of available research, twenty-nine articles relevant to the segmentation of dermatological images and forty-five articles about the classification of dermatological images were incorporated into this review. These articles were systematically categorized into two classes based on the computational algorithms utilized: traditional machine learning algorithms and deep learning algorithms. An in-depth comparative analysis was carried out, based on the employed methodologies and their corresponding outcomes. CONCLUSIONS: Present outcomes of research highlight the enhanced effectiveness of deep learning methods over traditional machine learning techniques in the field of dermatological diagnosis. Nevertheless, there remains significant scope for improvement, especially in improving the accuracy of algorithms. The challenges associated with the availability of diverse datasets, the generalizability of segmentation and classification models, and the interpretability of models also continue to be pressing issues. Moreover, the focus of future research should be appropriately shifted. A significant amount of existing research is primarily focused on melanoma, and consequently there is a need to broaden the field of pigmented dermatology research in the future. These insights not only emphasize the potential of deep learning in dermatological diagnosis but also highlight directions that should be focused on.

Advanced Glycation End Products-Induced Activation of Keratinocytes: A Mechanism Underlying Cutaneous Immune Response in Psoriasis.

Psoriasis is a common inflammatory skin disease, in which epidermal keratinocytes play a vital role in its pathogenesis by acting both as the responder and as the accelerator to the cutaneous psoriatic immune response. Advanced glycation end products (AGEs) are a class of proinflammatory metabolites that are commonly accumulating in cardiometabolic disorders. Recent studies have also observed the increased level of AGEs in the serum and skin of psoriasis patients, but the role of AGEs in psoriatic inflammation has not been well investigated. In the present study, we initially detected abnormal accumulation of AGEs in epidermal keratinocytes of psoriatic lesions collected from psoriasis patients. Furthermore, AGEs promoted the proliferation of keratinocytes via upregulated Keratin 17 (K17)-mediated p27KIP1 inhibition followed by accelerated cell cycle progression. More importantly, AGEs facilitated the production of interleukin-36 alpha (IL-36α) in keratinocytes, which could enhance T helper 17 (Th17) immune response. In addition, the induction of both K17 and IL-36α by AGEs in keratinocytes was dependent on the activation of signal transducer and activator of transcription 1/3 (STAT1/3) signaling pathways. At last, the effects of AGEs on keratinocytes were mediated by the receptor for AGEs (RAGE). Taken together, these findings support that AGEs potentiate the innate immune function of keratinocytes, which contributes to the formation of psoriatic inflammation. Our study implicates AGEs as a potential pathogenic link between psoriasis and cardiometabolic comorbidities.

Revealing the Binding Events of Single Proteins on Exosomes Using Nanocavity Antennas beyond Zero-Mode Waveguides.

Exosomes (EXOs) play a crucial role in biological action mechanisms. Understanding the biological process of single-molecule interactions on the surface of the EXO membrane is essential for elucidating the precise function of the EXO receptor. However, due to dimensional incompatibility, monitoring the binding events between EXOs of tens to hundreds of nanometers and biomolecules of nanometers using existing nanostructure antennas is difficult. Unlike the typical zero-mode waveguides (ZMWs), this work presents a nanocavity antenna (λvNAs) formed by nanocavities with diameters close to the visible light wavelength dimensions. Effective excitation volumes suitable for observing single-molecule fluorescence were generated in nanocavities of larger diameters than typical ZMWs; the optimal signal-to-noise ratio obtained was 19.5 when the diameter was 300 nm and the incident angle was ∼50°. EXOs with a size of 50-150 nm were loaded into λvNAs with an optimized diameter of 300-500 nm, resulting in appreciable occupancy rates that overcame the nanocavity size limitation for large-volume biomaterial loading. Additionally, this method identified the binding events between the single transmembrane CD9 proteins on the EXO surface and their monoclonal antibody anti-CD9, demonstrating that λvNAs expanded the application range beyond subwavelength ZMWs. Furthermore, the λvNAs provide a platform for obtaining in-depth knowledge of the interactions of single molecules with biomaterials ranging in size from tens to hundreds of nanometers.

Influences of vitiligo-associated characteristics on the occurrence of diabetes mellitus: Interactive analysis of a cross-sectional study.

The risk of diabetes mellitus (DM) in vitiligo patients is higher than that in non-vitiligo population. Our goal was to explore the influencing factors for DM in vitiligo patients. A matched-pair design of 107 cases with DM and 428 controls without DM was conducted among vitiligo patients in Xijing hospital from January 2010 to October 2021. The baseline characteristics of patients were analysed based on standard descriptive statistics. The vitiligo-associated characteristics were analysed by logistic regression to identify influencing factors of DM. Interaction analysis was performed to explore the additive interactions between vitiligo-associated characteristics and baseline characteristics. After adjustment for the baseline characteristics, the severity of vitiligo [odds ratio (OR) = 2.47, 95% confidence interval (CI): 1.47-4.14] and onset age of vitiligo (OR = 0.98, 95% CI: 0.97-0.99) had a significant correlation with occurrence of DM. The severity of vitiligo had additive interaction with family history of diabetes [relative excess risk due to interaction (RERI) = 132.51 (95% CI: 5.51-1100.20), attributable proportion (AP) = 0.91 (95% CI: 0.17-0.95), synergy index (S) = 11.53 (95% CI: 1.32-100.5)] and with smoking history [RERI = 6.54 (95% CI: 0.67-19.83), AP = 0.64 (95% CI: 0.04-0.80), S = 3.48 (95% CI: 1.17-10.36)]. Earlier onset age of vitiligo and greater BSA involvement might be two independent risk factors for DM in vitiligo patients. Interaction assessment identified the severity of vitiligo as additive interaction factors with diabetes family history and with smoking history for the DM occurrence.

Pharmacological inhibition of demethylzeylasteral on JAK-STAT signaling ameliorates vitiligo.

BACKGROUND: The activation of CD8+ T cells and their trafficking to the skin through JAK-STAT signaling play a central role in the development of vitiligo. Thus, targeting this key disease pathway with innovative drugs is an effective strategy for treating vitiligo. Natural products isolated from medicinal herbs are a useful source of novel therapeutics. Demethylzeylasteral (T-96), extracted from Tripterygium wilfordii Hook F, possesses immunosuppressive and anti-inflammatory properties. METHODS: The efficacy of T-96 was tested in our mouse model of vitiligo, and the numbers of CD8+ T cells infiltration and melanocytes remaining in the epidermis were quantified using whole-mount tail staining. Immune regulation of T-96 in CD8+ T cells was evaluated using flow cytometry. Pull-down assay, mass spectrum analysis, molecular docking, knockdown and overexpression approaches were utilized to identify the target proteins of T-96 in CD8+ T cells and keratinocytes. RESULTS: Here, we found that T-96 reduced CD8+ T cell infiltration in the epidermis using whole-mount tail staining and alleviated the extent of depigmentation to a comparable degree of tofacitinib (Tofa) in our vitiligo mouse model. In vitro, T-96 decreased the proliferation, CD69 membrane expression, and IFN-γ, granzyme B, (GzmB), and perforin (PRF) levels in CD8+ T cells isolated from patients with vitiligo. Pull-down assays combined with mass spectrum analysis and molecular docking showed that T-96 interacted with JAK3 in CD8+ T cell lysates. Furthermore, T-96 reduced JAK3 and STAT5 phosphorylation following IL-2 treatment. T-96 could not further reduce IFN-γ, GzmB and PRF expression following JAK3 knockdown or inhibit increased immune effectors expression upon JAK3 overexpression. Additionally, T-96 interacted with JAK2 in IFN-γ-stimulated keratinocytes, inhibiting the activation of JAK2, decreasing the total and phosphorylated protein levels of STAT1, and reducing the production and secretion of CXCL9 and CXCL10. T-96 did not significantly inhibit STAT1 and CXCL9/10 expression following JAK2 knockdown, nor did it suppress upregulated STAT1-CXCL9/10 signaling upon JAK2 overexpression. Finally, T-96 reduced the membrane expression of CXCR3, and the culture supernatants pretreated with T-96 under IFN-γ stressed keratinocytes markedly blocked the migration of CXCR3+CD8+ T cells, similarly to Tofa in vitro. CONCLUSION: Our findings demonstrated that T-96 might have positive therapeutic responses to vitiligo by pharmacologically inhibiting the effector functions and skin trafficking of CD8+ T cells through JAK-STAT signaling.

The NCI-MATCH trial: lessons for precision oncology.

The NCI-MATCH (Molecular Analysis for Therapy Choice) trial ( NCT02465060 ) was launched in 2015 as a genomically driven, signal-seeking precision medicine platform trial-largely for patients with treatment-refractory, malignant solid tumors. Having completed in 2023, it remains one of the largest tumor-agnostic, precision oncology trials undertaken to date. Nearly 6,000 patients underwent screening and molecular testing, with a total of 1,593 patients (inclusive of continued accrual from standard next-generation sequencing) being assigned to one of 38 substudies. Each substudy was a phase 2 trial of a therapy matched to a genomic alteration, with a primary endpoint of objective tumor response by RECIST criteria. In this Perspective, we summarize the outcomes of the initial 27 substudies in NCI-MATCH, which met its signal-seeking objective with 7/27 positive substudies (25.9%). We discuss key aspects of the design and operational conduct of the trial, highlighting important lessons for future precision medicine studies.

Wood cellulose microfibrils have a 24-chain core-shell nanostructure in seed plants.

Wood cellulose microfibril (CMF) is the most abundant organic substance on Earth but its nanostructure remains poorly understood. There are controversies regarding the glucan chain number (N) of CMFs during initial synthesis and whether they become fused afterward. Here, we combined small-angle X-ray scattering, solid-state nuclear magnetic resonance and X-ray diffraction analyses to resolve CMF nanostructures in native wood. We developed small-angle X-ray scattering measurement methods for the cross-section aspect ratio and area of the crystalline-ordered CMF core, which has a higher scattering length density than the semidisordered shell zone. The 1:1 aspect ratio suggested that CMFs remain mostly segregated, not fused. The area measurement reflected the chain number in the core zone (Ncore). To measure the ratio of ordered cellulose over total cellulose (Roc) by solid-state nuclear magnetic resonance, we developed a method termed global iterative fitting of T1ρ-edited decay (GIFTED), in addition to the conventional proton spin relaxation editing method. Using the formula N = Ncore/Roc, most wood CMFs were found to contain 24 glucan chains, conserved between gymnosperm and angiosperm trees. The average CMF has a crystalline-ordered core of ~2.2 nm diameter and a semidisordered shell of ~0.5 nm thickness. In naturally and artificially aged wood, we observed only CMF aggregation (contact without crystalline continuity) but not fusion (forming a conjoined crystalline unit). This further argued against the existence of partially fused CMFs in new wood, overturning the recently proposed 18-chain fusion hypothesis. Our findings are important for advancing wood structural knowledge and more efficient use of wood resources in sustainable bio-economies.

Trametinib in Patients With NF1-, GNAQ-, or GNA11-Mutant Tumors: Results From the NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocols S1 and S2.

PURPOSE: NCI-MATCH is a precision medicine trial using genomic testing to allocate patients with advanced malignancies to targeted treatment subprotocols. This report combines two subprotocols evaluating trametinib, a MEK1/2 inhibitor, in patients with Neurofibromatosis 1 (NF1[S1] or GNA11/Q [S2]) altered tumors. METHODS: Eligible patients had tumors with deleterious inactivating NF1 or GNA11/Q mutations by the customized Oncomine AmpliSeq panel. Prior MEK inhibitor treatment was excluded. Glioblastomas (GBMs) were permitted, including malignancies associated with germline NF1 mutations (S1 only). Trametinib was administered at 2 mg once daily over 28-day cycles until toxicity or disease progression. Primary end point was objective response rate (ORR). Secondary end points included progression-free survival (PFS) at 6 months, PFS, and overall survival. Exploratory analyses included co-occurring genomic alterations and PTEN loss. RESULTS: Fifty patients were eligible and started therapy: 46 with NF1 mutations (S1) and four with GNA11 mutations (S2). In the NF1 cohort, nonsense single-nucleotide variants were identified in 29 and frameshift deletions in 17 tumors. All in S2 had nonuveal melanoma and GNA11 Q209L variant. Two partial responses (PR) were noted in S1, one patient each with advanced lung cancer and GBM for an ORR of 4.3% (90% CI, 0.8 to 13.1). One patient with melanoma in S2 had a PR (ORR, 25%; 90% CI, 1.3 to 75.1). Prolonged stable disease (SD) was also noted in five patients (four in S1 and one in S2) with additional rare histologies. Adverse events were as previously described with trametinib. Comutations in TP53 and PIK3CA were common. CONCLUSION: Although these subprotocols did not meet the primary end point for ORR, significant responses or prolonged SD noted in some disease subtypes warrants further investigation.

Multicenter Phase I Trial of Ivosidenib as Maintenance Treatment Following Allogeneic Hematopoietic Cell Transplantation for IDH1-Mutated Acute Myeloid Leukemia.

PURPOSE: Isocitrate dehydrogenase 1 (IDH1) mutations occur in 5% to 10% of patients with acute myeloid leukemia (AML). Ivosidenib is an IDH1 inhibitor, approved for use in patients with IDH1-mutated AML. PATIENTS AND METHODS: We conducted a multicenter, phase I trial of maintenance ivosidenib following allogeneic hematopoietic cell transplantation (HCT) in patients with IDH1-mutated AML. Ivosidenib was initiated between days 30 and 90 following HCT and continued for up to 12 28-day cycles. The first dose level was 500 mg daily, with level reduction to 250 mg daily, if needed, in a 3 × 3 de-escalation design. Ten additional patients would then receive the MTD or recommended phase 2 dose (RP2D). The primary endpoint was establishing the MTD or RP2D of ivosidenib. RESULTS: Eighteen patients were enrolled, of whom 16 initiated post-HCT ivosidenib. One dose-limiting toxicity, grade(g) 3 QTc prolongation, was observed. The RP2D was established at 500 mg daily. Attributable g≥3 adverse events were uncommon, with the most common being QTc prolongation in 2 patients. Eight patients discontinued maintenance, with only one due to adverse event. Six-month cumulative incidence (CI) of gII-IV aGVHD was 6.3%, and 2-year CI of all cGVHD was 63%. Two-year CI of relapse and nonrelapse mortality (NRM) were 19% and 0%, respectively. Two-year progression-free (PFS) was 81%, and 2-year overall survival (OS) was 88%. CONCLUSIONS: Ivosidenib is safe and well-tolerated as maintenance therapy following HCT. Cumulative incidence of relapse and NRM, as well as estimations of PFS and OS, were promising in this phase I study.

Improving the Encapsulation Efficiency of Lipase in Molecular Cages and Its Application.

Here, lipase encapsulation is constructed by locking enzyme molecules in nanomolecular cages on the surface of SH-PEI@PVAC magnetic microspheres. To improve the encapsulation efficiency in enzyme loading, the thiol group is efficiently modified on the grafted polyethyleneimine (PEI) using 3-mercaptopropionic acid. N2 adsorption-desorption isotherms reveal the existence of mesoporous molecular cages on the microsphere surface. The robust immobilizing strength of carriers to lipase demonstrates the successful encapsulation of enzymes in nanomolecular cages. The encapsulated lipase shows high enzyme loading (52.9 mg/g) and high activity (51.4 U/mg). Different sizes of molecular cages are established, and the cage size showed important effects on lipase encapsulation. It shows that enzyme loading is low at a small size of molecular cages, which is attributed to that the nanomolecular cage is too small to house lipase. The investigation in lipase conformation suggests that the encapsulated lipase retains its active conformation. Compared with the adsorbed lipase, the encapsulated lipase shows higher thermal stability (4.9 times) and higher resistance to denaturants (5.0 times). Encouragingly, the encapsulated lipase shows high activity and reusability in lipase-catalyzed synthesis of propyl laurate, suggesting the potential application value of encapsulated lipase.

MIF inhibition alleviates vitiligo progression by suppressing CD8+ T cell activation and proliferation.

In vitiligo, autoreactive CD8+ T cells have been established as the main culprit considering its pathogenic role in mediating epidermal melanocyte-specific destruction. Macrophage migration inhibitory factor (MIF) is a pleiotropic molecule that plays a central role in various immune processes including the activation and proliferation of T cells; but whether MIF is intertwined in vitiligo development and progression and its involvement in aberrantly activated CD8+ T cells remains ill-defined. In this study, we found that MIF was overabundant in vitiligo patients and a mouse model for human vitiligo. Additionally, inhibiting MIF ameliorated the disease progression in vitiligo mice, which manifested as less infiltration of CD8+ T cells and more retention of epidermal melanocytes in the tail skin. More importantly, in vitro experiments indicated that MIF-inhibition suppressed the activation and proliferation of CD8+ T cells from the lymph nodes of vitiligo mice, and the effect extended to CD8+ T cells in peripheral blood mononuclear cells of vitiligo patients. Finally, CD8+ T cells derived from MIF-inhibited vitiligo mice also exhibited an impaired capacity for activation and proliferation. Taken together, our results show that MIF might be clinically targetable in vitiligo treatment, and its inhibition might ameliorate vitiligo progression by suppressing autoreactive CD8+ T cell activation and proliferation. © 2023 The Pathological Society of Great Britain and Ireland.

0D carbon dots intercalated Z-scheme CuO/g-C3N4 heterojunction with dual charge transfer pathways for synergetic visible-light-driven photo-Fenton-like catalysis.

Photo-Fenton-like catalysis allows development of novel advanced oxidation technology with promising application in wastewater treatment. In this work, carbon dots (CDs) were intercalated between CuO nanoparticles and coralloid flower-like graphitic carbon nitride (g-C3N4) to fabricate a ternary CuO/CDs/g-C3N4 hybrid for synergetic visible-light-driven photo-Fenton-like oxidation. The CuO/CDs/g-C3N4 hybrid showed remarkable degradation efficiency towards recalcitrant organic contamination, excellent tolerance to realistic environmental conditions, exceptional stability and wide universality, declaring great potential for practical applications. •OH and •O2- radicals were demonstrated to be the primary contributors in the photo-Fenton-like system. Mechanism studies reveal dual charge transfer pathways in the Z-scheme CuO/g-C3N4 heterojunction assisted by interfacial electron transmission bridges of CDs, which can simultaneously boost the reduction of Cu2+ to Cu+ in the Fenton-like cycle and accelerate the Z-scheme electron flow from CuO to g-C3N4, leading to synergistic enhancement of the catalytic performance. This work would afford a feasible strategy to develop reinforced solar energy-assisted photo-Fenton-like catalysis systems for water remediation.

Progress in biological activities and biosynthesis of edible fungi terpenoids.

The edible fungi have both edible and medicinal functions, in which terpenoids are one of the most important active ingredients. Terpenoids possess a wide range of biological activities and show great potential in the pharmaceutical and healthcare industries. In this review, the diverse biological activities of edible fungi terpenoids were summarized with emphasis on the mechanism of anti-cancer and anti-inflammation. Subsequently, this review focuses on advances in knowledge and understanding of the biosynthesis of terpenoids in edible fungi, especially in the generation of sesquiterpenes, diterpenes, and triterpenes. This paper is aim to provide an overview of biological functions and biosynthesis developed for utilizing the terpenoids in edible fungi.

Management of the refractory vitiligo patient: current therapeutic strategies and future options.

Vitiligo is an autoimmune disease that leads to disfiguring depigmented lesions of skin and mucosa. Although effective treatments are available for vitiligo, there are still some patients with poor responses to conventional treatment. Refractory vitiligo lesions are mostly located on exposed sites such as acral sites and lips, leading to significant life stress. Understanding the causes of refractory vitiligo and developing targeted treatments are essential to enhance vitiligo outcomes. In this review, we summarized recent treatment approaches and some potential methods for refractory vitiligo. Janus kinase inhibitors have shown efficacy in refractory vitiligo. A variety of surgical interventions and fractional carbon dioxide laser have been widely applied to combination therapies. Furthermore, melanocyte regeneration and activation therapies are potentially effective strategies. Patients with refractory vitiligo should be referred to psychological monitoring and interventions to reduce the potential pathogenic effects of chronic stress. Finally, methods for depigmentation and camouflage may be beneficial in achieving uniform skin color and improved quality of life. Our ultimate focus is to provide alternative options for refractory vitiligo and to bring inspiration to future research.

Circulatory levels of alarmins in patients with non-segmental vitiligo: Potential biomarkers for disease diagnosis and activity/severity assessment.

Background: Non-segmental vitiligo (NSV) is an autoimmune skin disorder that is difficult to determine disease activity/severity and thus to treat. Alarmins have emerged as promising biomarkers in various diseases, so further confirmation of their potential roles in NSV would be of considerable value. With the present work, we aimed to determine the serum levels of alarmins in patients with NSV, correlate these alarmins with disease activity and severity, and analyze the predictive value of the combination of these markers. Methods: 104 NSV patients and 56 healthy controls were enrolled at the Xijing Hospital of Fourth Military Medical University between September 1, 2018, and June 30, 2019. The serum levels of alarmins (including IL-33, IL-1α, S100A9, S100A12, S100B, and HMGB1) were measured with enzyme-linked immunosorbent assays. The predictive performance of these biomarkers was evaluated with the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and other representative statistics. Results: A total of 104 patients with NSV (mean [SD] age, 34.2 [13.0] years; 62 [59.6%] male) and 56 healthy controls (mean [SD] age, 34.8 [13.5] years; 34 [60.7%] male) were enrolled. For vitiligo diagnosis, S100B had the highest sensitivity (92.31%), whereas HMGB1 had the highest specificity (85.71%); the combination of IL-1α, S100B, S100A9, and HMGB1 increased the AUC value to 0.925, with a sensitivity of 87.50% and a specificity of 85.71%. Multivariate logistic regression analysis showed S100B (OR, 1.019; 95% CI, 1.002-1.038; P =0.03), S100A9 (OR, 1.002; 95% CI, 1.001-1.003; P<0.001), and HMGB1 (OR, 1.915; 95% CI, 1.186-3.091; P =0.008) were significantly associated with vitiligo activity. S100A9 had the highest accuracy in discriminating patients at the active stage from the stable stage, with an AUC value of 0.827. The combination of these alarmins had an AUC value of 0.860 to assess disease activity, with a sensitivity of 90.00% and a specificity of 72.97%. Furthermore, S100B (r=0.61, P <0.001), S100A9 (r=0.33, P <0.001), and HMGB1 (r = 0.51, P <0.001) levels were positively correlated with the affected body surface area (BSA) in NSV patients. Conclusions: Serum S100B, S100A9, and HMGB1 might be biomarkers for diagnosing and assessing the activity/severity of NSV, either used alone or in combination.