A 20-year-old male patient presented to the Department of Dermatology of Peking Union Medical College Hospital with complaints of an 8-year history of facial scarring, swelling of the lower limbs, and a 4-year history of scalp thickening. Physical examination showed thickening furrowing wrinkling of the skin on the face and behind the ears, ciliary body hirsutism, blepharoptosis, and cutis verticis gyrate. Both lower limbs were swollen, especially the knees and ankles. The skin of the palms and soles of the feet was keratinized and thickened. Laboratory examination using bone and joint X-ray showed periostosis of the proximal middle phalanges and metacarpals of both hands, distal ulna and radius, tibia and fibula, distal femurs, and metatarsals.Genetic testing revealed two variants in SLCO2A1, c.1658T > A and c.96+4A > C.Through multidisciplinary consultation, we confirmed the diagnosis of pachydermoperiostosis.

The pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.

Objective: To investigate the distribution of IgM anti-A/B titers among group O whole blood donors in Jiangsu, establish a low-titer threshold, and analyze the demographic characteristics of low-titer donors, so as to provide data for recruiting low-titer group O whole blood (LTOWB) donors. Methods: Plasma samples from 1 009 group O whole blood donors were tested for IgM anti-A and anti-B titers using the microplate technique. The distribution of antibody titers was analyzed to establish a low-titer threshold. The distribution trends of titers across different demographic groups were also analyzed. Results: The peak titer for anti-A, anti-B were 64 (31.5%), 4 (23.8%), respectively, The proportion of donors with both anti-A and anti-B titers below 64 was 97.3% (982/1 009). The mean anti-A titer was higher than anti-B titer. Anti-A titers were higher in female donors than in male donors (P<0.05). The anti-A titers differed significantly among different age groups (P<0.05). However, no significant difference in titers was observed based on the number of donations (P>0.05). Conclusion: A titer of 64 can be used as the reference threshold of LTOWB in Jiangsu. Male donors of appropriate age are more suitable than female donors for establishing an emergency panel of LTOWB mobile donors.

Radiochemotherapy-induced oral mucositis (OM) is a common oral complication in patients with tumors following head and neck radiotherapy or chemotherapy. Erosion and ulcers are the main features of OM that seriously affect the quality of life of patients and even the progress of tumor treatment. To date, differences in clinical prevention and treatment plans for OM have been noted among doctors of various specialties, which has increased the uncertainty of treatment effects. On the basis of current research evidence, this expert consensus outlines risk factors, clinical manifestations, clinical grading, ancillary examinations, diagnostic basis, prevention and treatment strategies and efficacy indicators for OM. In addition to strategies such as basic oral care, anti-inflammatory and analgesic agents, anti-infective agents, pro-healing agents, and photobiotherapy recommended in previous guidelines, we also emphasize the role of traditional Chinese medicine in OM prevention and treatment. This expert consensus aims to provide references and guidance for dental physicians and oncologists in formulating strategies for OM prevention, diagnosis, and treatment, standardizing clinical practice, reducing OM occurrence, promoting healing, and improving the quality of life of patients.
Humans ; Chemoradiotherapy/adverse effects* ; Consensus ; Risk Factors ; Stomatitis/etiology*

Human naïve pluripotent stem cells (PSCs) hold great promise for embryonic development studies. Existing induction and culture strategies for these cells, heavily dependent on MEK inhibitors, lead to widespread DNA hypomethylation, aberrant imprinting loss, and genomic instability during extended culture. Here, employing high-content analysis alongside a bifluorescence reporter system indicative of human naïve pluripotency, we screened over 1,600 chemicals and identified seven promising candidates. From these, we developed four optimized media-LAY, LADY, LUDY, and LKPY-that effectively induce and sustain PSCs in the naïve state. Notably, cells reset or cultured in these media, especially in the LAY system, demonstrate improved genome-wide DNA methylation status closely resembling that of pre-implantation counterparts, with partially restored imprinting and significantly enhanced genomic stability. Overall, our study contributes advancements to naïve pluripotency induction and long-term maintenance, providing insights for further applications of naïve PSCs.
Humans ; DNA Methylation/drug effects* ; Genomic Instability ; Pluripotent Stem Cells/metabolism* ; Cell Culture Techniques/methods* ; Cells, Cultured

OBJECTIVE: To investigate the association between ABO blood types and gestational diabetes mellitus (GDM) risk. METHODS: A prospective birth cohort study was conducted. ABO blood types were determined using the slide method. GDM diagnosis was based on a 75-g, 2-h oral glucose tolerance test (OGTT) according to the criteria of the International Association of Diabetes and Pregnancy Study Groups. Logistic regression was applied to calculate the odds ratios ( ORs) and 95% confidence intervals ( CIs) between ABO blood types and GDM risk. RESULTS: A total of 30,740 pregnant women with a mean age of 31.81 years were enrolled in this study. The ABO blood types distribution was: type O (30.99%), type A (26.58%), type B (32.20%), and type AB (10.23%). GDM was identified in 14.44% of participants. Using blood type O as a reference, GDM risk was not significantly higher for types A ( OR = 1.05) or B ( OR = 1.04). However, women with type AB had a 19% increased risk of GDM ( OR = 1.19, 95% CI = 1.05-1.34; P < 0.05), even after adjusting for various factors. This increased risk for type AB was consistent across subgroup and sensitivity analyses. CONCLUSION The ABO blood types may influence GDM risk, with type AB associated with a higher risk. Incorporating it-either as a single risk factor or in combination with other known factors-could help identify individuals at risk for GDM before or during early pregnancy.
Humans ; Female ; Pregnancy ; Diabetes, Gestational/etiology* ; ABO Blood-Group System ; Adult ; Prospective Studies ; Risk Factors ; Young Adult

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

Objective:To investigate the association of exposure to PM 2.5 and its constituents during pregnancy and fetal growth and to further identify critical windows of exposure for fetal growth. Methods:We included 4 089 mother-child pairs from the Jiangsu Birth Cohort Study between January 2016 and October 2019. Data of general characteristics, clinical information, daily average PM 2.5 exposure, and its constituents during pregnancy were collected. Fetal growth parameters, including head circumference (HC), abdominal circumference (AC), and femur length (FL), were measured by ultrasound after 20 weeks of gestation, and then estimated fetal weight (EFW) was calculated. Generalized linear mixed models were adopted to examine the associations of prenatal exposure to PM 2.5 and its constituents with fetal growth. Distributed lag nonlinear models were used to identify critical exposure windows for each outcome. Results:A 10 μg/m 3 increase in PM 2.5 exposure during pregnancy was associated with a decrease of 0.025 ( β=-0.025, 95% CI: -0.048- -0.001) in HC Z-score, 0.026 ( β=-0.026, 95% CI: -0.049- -0.003) in AC Z-score, and 0.028 ( β=-0.028, 95% CI:-0.052--0.004) in EFW Z-score, along with an increased risk of 8.5% ( RR=1.085, 95% CI: 1.010-1.165) and 13.5% ( RR=1.135, 95% CI: 1.016-1.268) for undergrowth of HC and EFW, respectively. Regarding PM 2.5 constituents, prenatal exposure to black carbon, organic matter, nitrate, sulfate (SO 42-) and ammonium consistently correlated with decreased HC Z-score. SO 42- exposure was also associated with decreased FL Z-scores. In addition, we found that gestational weeks 2-5 were critical windows for HC, weeks 4-13 and 19-40 for AC, weeks 4-13 and 23-37 for FL, and weeks 4-12 and 20-40 for EFW. Conclusions:Our findings demonstrated that exposure to PM 2.5 and its constituents during pregnancy could adversely affect fetal growth and the critical windows for different fetal growth parameters are not completely consistent.

Objective To analyze the medication rules of Professor HUANG Feng for the treatment of low back pain using data mining methods.Methods The information of prescriptions for the effective cases of outpatients with low back pain treated by Professor HUANG Feng were collected and screened.Microsoft Excel 2019 was used to analyze the frequency of medication and the distribution of properties,flavors and meridian tropism of the drugs in the included prescription.IBM SPSS Modeler 18.0 was used for association rule analysis,and IBM Statistics 26.0 was used for cluster analysis.Results A total of 239 prescriptions and 75 Chinese medicines were included.There were 23 high-frequency Chinese medicines with the medication frequency being or over 20 times,and the top 10 Chinese medicines were Glycyrrhizae Radix et Rhizoma,vinegar-processed Corydalis Rhizoma,Cibotii Rhizoma,Atractylodis Macrocephalae Rhizoma,Zanthoxyli Radix,salt-processed Achyranthis Bidentatae Radix,Rehmanniae Radix,Dipsaci Radix,Coicis Semen,and Salviae Miltiorrhizae Radix et Rhizoma.The medicines were mainly warm in nature,and were sweet,bitter and pungent in flavor.Most of the drugs had the meridian tropism of liver,stomach and spleen meridians.Among the drug combinations obtained from association rule analysis with the top 20 highest support,vinegar-processed Corydalis Rhizoma,Cibotii Rhizoma,Atractylodis Macrocephalae Rhizoma and Zanthoxyli Radix were the core drugs.Cluster analysis yielded 6 clustering combinations.Conclusion For the treatment of low back pain,Professor HUANG Feng follows the principle of"treatment adapting to the climate,individuality,and environment"and"treating the root cause of the disease",usually adopts the drugs for activating blood,moving qi and relieving pain,nourishing the liver and kidney,and also uses the medicines for replenishing qi and strengthening the spleen.The ideas of HUANG Feng for the treatment of low back pain can be used as a reference for the clinical treatment.