Background: Maturity-onset diabetes of the young (MODY) due to variants of hepatocyte nuclear factor 1-beta (HNF1β) (MODY5) has not been well studied in the Chinese population. This study aimed to estimate its prevalence and evaluate the application of a clinical screening method (Faguer score) in Chinese early-onset diabetes (EOD) patients. Methods: Among 679 EOD patients clinically diagnosed with type 2 diabetes mellitus (age at diagnosis ≤40 years), the exons of HNF1β were sequenced. Functional impact of rare variants was evaluated using a dual-luciferase reporter system. Faguer scores ≥8 prompted multiplex ligation-dependent probe amplification (MLPA) for large deletions. Pathogenicity of HNF1β variants was assessed following the American College of Medical Genetics and Genomics (ACMG) guidelines. Results: Two rare HNF1β missense mutations (E105K and G454R) were identified by sequencing in five patients, showing functional impact in vitro. Another patient was found to have a whole-gene deletion by MLPA in 22 patients with the Faguer score above 8. Following ACMG guidelines, six patients carrying pathogenic or likely pathogenic variant were diagnosed with MODY5. The estimated prevalence of MODY5 in Chinese EOD patients was approximately 0.9% or higher. Conclusion MODY5 is not uncommon in China. The Faguer score is helpful in deciding whether to perform MLPA analysis on patients with negative sequencing results.

Crigler-Najjar syndrome (CNS) and Gilbert syndrome (GS; OMIM: 143500) are rare autosomal recessive diseases that cause unconjugated hyperbilirubinemia due to decreased UGT1A1 enzyme activity. Crigler-Najjar syndrome type 2 (CNS2; OMIM: 606785) increases the risk of gallbladder stone formation and cholecystitis, while GS seldom causes health issues. We found a 28-year-old male patient with recurring right upper abdomen pain who experienced persistent jaundice from birth. CNS2 with gallbladder stones and cholecystitis was diagnosed after genetic testing revealed rare double homozygous mutations A(TA)₇TAA (rs3064744) and P229Q (rs35350960) in the UGT1A1 gene. After pedigree investigation, we found that the patient's parents with modestly increased bilirubin had compound heterozygous mutations A(TA)₇TAA and P229Q, which were GS. Bioinformatics analysis showed that A(TA)₇TAA is in the TATA-box region of the gene UGT1A1 promoter, affecting gene transcriptional initiation, whereas P229Q modifies protein three-dimensional structure and may be harmful. In this pedigree, double homozygous mutations have a more severe phenotype than compound heterozygous mutations. Inherited causes of hyperbilirubinemia should be suspected after ruling out biliary obstruction, and early bilirubin reduction (< 103 µmol/L (6 mg/dL)) may reduce the risk of complications like cholecystitis in CNS2 patients, though further studies with longer follow-up are needed to confirm this observation.
Humans ; Male ; Glucuronosyltransferase/genetics* ; Adult ; Crigler-Najjar Syndrome/complications* ; Cholecystitis/etiology* ; Homozygote ; Mutation ; Pedigree

ObjectiveTo explore the potential mechanisms of Leigongteng （Tripterygium wilfordii Hook. f.） in treating rheumatoid arthritis （RA） using bioinformatics analysis and experimental validation. MethodsBioinformatics approaches， including the Gene Expression Omnibus （GEO）， the traditional Chinese medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， Gene Ontology （GO） enrichment analysis， Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment， protein-protein interaction （PPI） network analysis， molecular docking， receiver operating characteristic （ROC） analysis， and immune infiltration analysis， were used to predict the key active components of Leigongteng and its target genes for RA treatment. Experimental validation was conducted using human rheumatoid arthritis fibroblast-like synoviocytes （HFLS-RA） in vitro， with methotrexate as the positive control. A scratch assay was performed to assess cell migration after 24 hours of culture. Western blotting was used to detect protein expression levels， qPCR was used to measure target gene mRNA levels， and ELISA was conducted to evaluate inflammatory cytokine levels， including interleukin-1β （IL-1β）， interleukin-6 （IL-6）， interleukin-10 （IL-10）， and tumor necrosis factor-α （TNF-α）. ResultsA total of 117 target genes of Leigongteng were identified and intersected with RA-related genes， yielding 55 key genes. Further screening identified three core genes： PTGS2， CXCR4， and TIMP1. Based on the correspondence between potential drug targets and key components， triptolide and nobiletin were identified as the primary active compounds. Molecular docking results showed that both triptolide and nobiletin had binding energies lower than -5 kcal/mol with their respective target proteins， indicating strong interactions. In vitro experiments demonstrated that， compared with the blank control group， the triptolide， nobiletin， and positive control groups exhibited reduced cell migration rates after 24 hours of culture （P＜0.01）. The expression levels of PTGS2 and CXCR4 （both mRNA and protein） were significantly downregulated， while TIMP1 expression was upregulated. Levels of IL-1β， IL-6， and TNF-α decreased， whereas IL-10 levels increased （P＜0.01）. Compared with the positive control group， the triptolide and nobiletin groups showed increased cell migration rates， upregulated PTGS2 and CXCR4 expression （mRNA and protein）， downregulated TIMP1 expression （mRNA and protein）， increased IL-1β， IL-6， and TNF-α levels， and decreased IL-10 levels （P＜0.05 or P＜0.01）. ConclusionThe key active components of Leigongteng， triptolide and nobiletin， may alleviate RA by inhibiting PTGS2 and CXCR4 while promoting TIMP1 expression， thereby suppressing inflammatory responses.

Background: Maturity-onset diabetes of the young (MODY) due to variants of hepatocyte nuclear factor 1-beta (HNF1β) (MODY5) has not been well studied in the Chinese population. This study aimed to estimate its prevalence and evaluate the application of a clinical screening method (Faguer score) in Chinese early-onset diabetes (EOD) patients. Methods: Among 679 EOD patients clinically diagnosed with type 2 diabetes mellitus (age at diagnosis ≤40 years), the exons of HNF1β were sequenced. Functional impact of rare variants was evaluated using a dual-luciferase reporter system. Faguer scores ≥8 prompted multiplex ligation-dependent probe amplification (MLPA) for large deletions. Pathogenicity of HNF1β variants was assessed following the American College of Medical Genetics and Genomics (ACMG) guidelines. Results: Two rare HNF1β missense mutations (E105K and G454R) were identified by sequencing in five patients, showing functional impact in vitro. Another patient was found to have a whole-gene deletion by MLPA in 22 patients with the Faguer score above 8. Following ACMG guidelines, six patients carrying pathogenic or likely pathogenic variant were diagnosed with MODY5. The estimated prevalence of MODY5 in Chinese EOD patients was approximately 0.9% or higher. Conclusion MODY5 is not uncommon in China. The Faguer score is helpful in deciding whether to perform MLPA analysis on patients with negative sequencing results.

Background: Maturity-onset diabetes of the young (MODY) due to variants of hepatocyte nuclear factor 1-beta (HNF1β) (MODY5) has not been well studied in the Chinese population. This study aimed to estimate its prevalence and evaluate the application of a clinical screening method (Faguer score) in Chinese early-onset diabetes (EOD) patients. Methods: Among 679 EOD patients clinically diagnosed with type 2 diabetes mellitus (age at diagnosis ≤40 years), the exons of HNF1β were sequenced. Functional impact of rare variants was evaluated using a dual-luciferase reporter system. Faguer scores ≥8 prompted multiplex ligation-dependent probe amplification (MLPA) for large deletions. Pathogenicity of HNF1β variants was assessed following the American College of Medical Genetics and Genomics (ACMG) guidelines. Results: Two rare HNF1β missense mutations (E105K and G454R) were identified by sequencing in five patients, showing functional impact in vitro. Another patient was found to have a whole-gene deletion by MLPA in 22 patients with the Faguer score above 8. Following ACMG guidelines, six patients carrying pathogenic or likely pathogenic variant were diagnosed with MODY5. The estimated prevalence of MODY5 in Chinese EOD patients was approximately 0.9% or higher. Conclusion MODY5 is not uncommon in China. The Faguer score is helpful in deciding whether to perform MLPA analysis on patients with negative sequencing results.

Background: Maturity-onset diabetes of the young (MODY) due to variants of hepatocyte nuclear factor 1-beta (HNF1β) (MODY5) has not been well studied in the Chinese population. This study aimed to estimate its prevalence and evaluate the application of a clinical screening method (Faguer score) in Chinese early-onset diabetes (EOD) patients. Methods: Among 679 EOD patients clinically diagnosed with type 2 diabetes mellitus (age at diagnosis ≤40 years), the exons of HNF1β were sequenced. Functional impact of rare variants was evaluated using a dual-luciferase reporter system. Faguer scores ≥8 prompted multiplex ligation-dependent probe amplification (MLPA) for large deletions. Pathogenicity of HNF1β variants was assessed following the American College of Medical Genetics and Genomics (ACMG) guidelines. Results: Two rare HNF1β missense mutations (E105K and G454R) were identified by sequencing in five patients, showing functional impact in vitro. Another patient was found to have a whole-gene deletion by MLPA in 22 patients with the Faguer score above 8. Following ACMG guidelines, six patients carrying pathogenic or likely pathogenic variant were diagnosed with MODY5. The estimated prevalence of MODY5 in Chinese EOD patients was approximately 0.9% or higher. Conclusion MODY5 is not uncommon in China. The Faguer score is helpful in deciding whether to perform MLPA analysis on patients with negative sequencing results.

Basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC), as certain forms of non-melanoma skin cancer (NMSC) or keratinocyte carcinoma, are the most common forms of malignant neoplasms worldwide (Sharp et al., 2024). BCC and cSCC have been identified as two major components of NMSC, comprising one-third of all malignancies (Burton et al., 2016). Generally speaking, patients with NMSC tend to have relatively favorable survival outcomes, while different histopathological subtypes of NMSC exhibit distinct biological behaviors (Stătescu et al., 2023). Keratinocyte carcinoma, although not considered as deadly as melanoma, tends to metastasize if left untreated (Civantos et al., 2023; Nanz et al., 2024). cSCC can evolve locally, then aggressively metastasize, invade, and even lead to fatal consequences in a subset of patients (Winge et al., 2023). A solid, pigmented, smooth plaque or a hyperkeratotic papule with or without central ulceration and hemorrhage appears to be characteristic of cSCC (Thompson et al., 2016; Zhou et al., 2023). Of note, a rare type of intraepidermal cSCC in situ often appears as a velvety, demarcated, slightly raised erythematous plaque on the genitalia of men (Yamaguchi et al., 2016). Accounting for approximately 16.0% of scalp tumors and with a rising incidence, cSCC is now the second most common NMSC in humans (Verdaguer-Faja et al., 2024). According to the latest statistics, up to 2%‒5% of cSCCs in situ may gradually progress into invasive cSCCs in the final step (Rentroia-Pacheco et al., 2023). Several risk factors for the carcinogenesis and development of cSCC have been identified, including age, accumulative exposure to ultraviolet light radiation A and B, human papillomavirus infection, arsenic ingestion, chronic scarring, xeroderma pigmentosa, a relevant history of ionizing radiation, androgenetic alopecia in males, and immunosuppression therapy (Martinez and Otley, 2001; Welsch et al., 2012; Mortaja and Demehri, 2023).
Humans ; Aminolevulinic Acid/therapeutic use* ; Skin Neoplasms/pathology* ; Photochemotherapy/methods* ; Female ; Carcinoma, Squamous Cell/pathology* ; Middle Aged ; Photosensitizing Agents/therapeutic use* ; Carcinoma, Basal Cell/drug therapy*

AIM:To analyze the clinical value of predicting drug resistance in pulmonary tuberculo-sis patients based on improved machine learning models,and to build a visualization system for veri-fication.METHODS:Retrospectively selected 1 025 pulmonary tuberculosis patients hospitalized in Zhuhai Sixth People's Hospital from March 2019 to March 2024 with drug sensitivity test results as the research object.According to the definition of drug-resistant tuberculosis,the patients were divided in-to 631 sensitive groups(drug sensitivity test results showed no drug resistance),271 RR/MDR groups(meeting the definition of rifampicin resistant tu-berculosis or multi drug resistant tuberculosis,but no drug resistance to any kind of fluoroquino-lones),and 123 pre XDR groups(on the basis of multi drug resistant tuberculosis,and at the same time,drug resistance to any kind of fluoroquino-lones).Analyze clinical data based on the improved machine learning model,help build a drug resistant tuberculosis prediction model,synchronously com-plete feature screening,conduct value analysis on the screened features,and build a visual system for verification.RESULTS:Three groups of patients with baseline data comparison shows:Age,Body mass index(BMI),basic treatment of classification,lung diseases,haemoptysis,second-line drug use history,damage to lung,with empty in all statisti-cally significant difference between the three groups(P<0.05);Based on the modified ma-chine learning model,8 variables were screened,which were history of second-line drug use,BMI,treatment classification,destructive lung,underly-ing lung diseases,cavitation,hemoptysis,and age.The modified machine learning model had the high-est prediction accuracy compared with the tradi-tional model,with AUC values of 0.9322(RR/MDR prediction was positive class)and 0.9545(pre-XDR prediction was positive class).CONCLUSION:The application of the improved machine learning mod-el can help predict the occurrence of drug-resistant tuberculosis and assist the clinical formulation of more effective treatment plans.

Objective:To construct a predictive model for mortality in patients with multiple trauma combined with thoracic injuries and evaluate its predictive value.Methods:A retrospective cohort study was conducted to analyze the clinical data of 184 patients with multiple trauma combined with thoracic injuries admitted to the International Zhuang Medicine Hospital Affiliated to Guangxi University of Chinese Medicine from April 2019 to December 2023, including 129 males and 55 females, aged 19-85 years [(46.1±13.7)years]. According to the prognostic outcomes at 3-month follow-up after discharge, the patients were divided into survival group ( n=145) and death group ( n=39). Data were recorded in both groups at admission, including gender, age, and cause of injury, laboratory tests such as systolic blood pressure, oxygen saturation (SaO 2), hemoglobin (Hb), neutrophil-to-lymphocyte ratio (NLR), and lactate, combined injuries such as the number of combined injuries, number of rib fracture, bilateral rib fracture, first-rib fracture, sternum fracture, thoracic vertebral fracture, bilateral pulmonary contusion, bilateral pneumothorax, subarachnoid hemorrhage, subdural hematoma, epidural hematoma, skull fracture, skull base fracture, cervical vertebral fracture, brain herniation, cerebral contusion, lumbar vertebral fracture, pelvic and abdominal cavity hematoma, liver injury, kidney injury, spleen injury, clavicle fracture, scapular fracture, femoral fracture, and pelvic fracture, and injury scores such as shock index (SI), modified shock index (MSI), injury severity score (ISS), revised trauma score (RTS), Glasgow coma score (GCS), and thoracic trauma severity (TTS) score. Univariate binary logistic regression analysis was used to screen for risk factors of death in patients with multiple trauma combined with thoracic injuries. LASSO regression and multivariate logistic regression analysis were employed to identify predictive variables and independent risk factors for mortality in those patients and to construct a regression equation. A nomogram prediction model based on the regression equation was developed using R language. Receiver operating characteristic (ROC) curves were plotted to evaluate the discrimination of the model. The ROC curves were internally validated using the Bootstrap method with 1 000 resamples. The calibration of the model was assessed using the Hosmer-Lemeshow (H-L) goodness-of-fit test. The clinical application value of the model was evaluated using decision curve analysis (DCA) and clinical impact curve (CIC) analysis. Results:There were statistically significant differences between the survival group and the death group in systolic blood pressure, SaO 2, NLR, lactate, number of combined injuries, subarachnoid hemorrhage, subdural hematoma, skull fracture, skull base fracture, brain herniation, liver injury, SI, MSI, ISS, RTS, GCS, and TTS ( P<0.05 or 0.01). The results of the univariate binary logistic regression analysis showed that the above-mentioned related variables except for systolic blood pressure were all significantly associated with death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Five predictive variables, TTS, GCS, brain herniation, ISS, and lactate were obtained in LASSO regression analysis. The results of the multivariate logistic regression analysis showed that GCS ( OR=0.70, 95% CI 0.58, 0.83), brain herniation ( OR=46.18, 95% CI 4.27, 499.26), TTS ( OR=1.71, 95% CI 1.30, 2.24), and lactate ( OR=1.35, 95% CI 1.01, 1.80) were independent risk factors for death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Based on the aforementioned independent risk factors, a regression formula was constructed as follows: P=e x/(1+e x), with the x=-0.36×"GCS"+3.83×"brain herniation"+0.53×"TTS"+0.30×"lactate levels"-11.03. The area under the ROC curve (AUC) of the predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on the equation was 0.97 (95% CI 0.93, 1.00). The AUC was internally validated using the Bootstrap method with 1 000 samples, resulting in an AUC of 0.97 (95% CI 0.91, 1.00). The results of the H-L goodness-of-fit test showed that the bias-corrected calibration curve of the model was in good consistence with the actual curve and both of them were close to the ideal curve. In the evaluation of the clinical application value of the predictive model, the DCA results showed that the predictive model could achieve good clinical net benefit. The CIC results showed that when the threshold probability was greater than 0.7, the model-identified high-risk patients for death highly matched the patients who actually died. Conclusion:The predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on GCS, brain herniation, TTS, and lactate has good predictive performance and clinical application value.

Objective:To analyze the distribution, drug resistance, and factors influencing pathogenic microorganisms in patients with hepatitis B virus-associated acute-on-chronic liver failure (HBV-ACLF) combined with intra-abdominal infection (IAI).Methods:A retrospective analysis was conducted on 282 cases with HBV-ACLF admitted to the Hepatobiliary Internal Medicine Department of Mengchao Hepatobiliary Hospital of Fujian Medical University from May 2019 to December 2022. Patients combined with IAI and positive pathogen culture were enrolled in the infection group (141 cases), and patients combined without IAI admitted during the same period were included in the non-infection group (141 cases). Patient's general clinical data, laboratory examination indicators, pathogen types, and drug sensitivity test results were collected. Logistic regression analysis was used for IAI occurrence risk factors in patients with HBV-ACLF.Results:A total of 204 pathogenic bacteria were detected in the infection group, including 115 strains of Gram-negative bacteria (56.37%), 74 strains of Gram-positive bacteria (36.28%), and 15 strains of fungi (7.35%). The most frequently detected bacterial genera were Escherichia coli (21.57%, 44/204), Klebsiella pneumoniae (12.25%, 25/204), Enterococcus faecium (6.37%, 13/204), Staphylococcus aureus (5.39%, 11/204), and Staphylococcus epidermidis (4.90%, 10/204). The results of drug sensitivity tests showed that the resistance rates of Escherichia coli and Klebsiella pneumoniae to levofloxacin and ciprofloxacin were over 50% (66.67%,26/39;61.54%,24/39)and 30% (34.79%,8/23;39.13%,9/23)respectively. The resistance rate of Pseudomonas aeruginosa to carbapenems ( meropenem and imipenem) was 60.00%. The resistance rates of Acinetobacter baumannii to meropenem and imipenem were 100% (4/4) and 50.00% (2/4) respectively. The resistance rates of Enterococcus faecium and Enterococcus faecalis to penicillin were 100% (13/13) and 33.33% (1/3) respectively. The resistance rates of Staphylococcus aureus to penicillin (77.78%,7/9) and oxacillin (33.33%, 3/9) were relatively high. The results of the multivariate unconditional logistic regression analysis showed that puncture and drainage ( OR=17.90, 95% CI: 7.94-43.42, P<0.001), procalcitonin ( OR=3.23, 95% CI: 1.56-8.98, P=0.012), C-reactive protein ( OR=1.05, 95% CI: 1.02-1.00, P=0.003), and age ( OR=1.06, 95% CI: 1.02-1.10, P=0.001) were independent risk factors for IAI in patients with HBV-ACLF. Conclusions:The pathogenic microorganisms were mainly enterobacteriaceae and enterococci with varying degrees of drug resistance in HBV-ACLF patients combined with IAI. Early-stage intervention is an effective measure to prevent the occurrence of increase of inflammatory indicators in patients with intra-abdominal infection with HBV-ACLF.