Autoimmune liver diseases （AILD） are a group of chronic liver diseases caused by abnormal activation of the immune system， mainly including autoimmune hepatitis， primary biliary cholangitis， primary sclerosing cholangitis， IgG4-related sclerosing cholangitis， and overlap syndrome. Clinical studies have shown that patients with AILD are often comorbid with thyroid diseases， especially autoimmune thyroid diseases （AITD）， such as Graves’ disease and Hashimoto’s thyroiditis. This article systematically reviews the epidemiological association， potential shared pathogenesis， and overlapping features between AILD and thyroid diseases. A deeper understanding of the immunological links between AILD and AITD may provide a theoretical basis for precision medicine and future research.

Objective To explore the risk prediction model of major adverse cardiovascular events (MACE) in community patients with hypertension based on remote ambulatory blood pressure parameters. Methods From November 2023 to October 2024, 486 community patients with hypertension who received standardized management in Nanjing Medical University Affiliated to Suzhou Hospital were retrospectively selected. All patients wore remote ambulatory blood pressure monitor to obtain 24-hour ambulatory blood pressure data. Clinical data were collected and remote ambulatory blood pressure parameters [24-hour systolic blood pressure variability (SBPV), 24-hour diastolic blood pressure variability (DBPV), nighttime SBPV, nighttime DBPV, daytime SBPV, daytime DBPV] were extracted. The patients were followed up for 12 months, and were classified into MACE group (n=42) and non-MACE group (n=444) according to whether MACE occurred during follow-up. Multivariate Logistic regression analysis was adopted to screen the influencing factors for MACE. Based on the above factors, a risk prediction model was constructed and verified by receiver operating characteristic (ROC) curve. Results MACE occurred in 42 cases among 486 patients, with an incidence rate of 8.64%. Multivariate Logistic regression analysis suggested that nighttime DBPV (OR=1.119, 95%CI: 1.030-1.214), 24h-SBPV (OR=1.115, 95%CI: 1.007-1.235), nighttime SBPV (OR=1.116, 95%CI: 1.016-1.226) and diabetes mellitus (OR=2.762, 95%CI: 1.059-7.203) were independent factors for MACE (P<0.05). The model validation results revealed that the area under the ROC curve was 0.905 (95%CI: 0.854-0.956 ), and the model had a good discrimination degree. Conclusion Nighttime DBPV, 24h-SBPV, nighttime SBPV and diabetes mellitus are independent risk factors for MACE in community patients with hypertension. The clinical prediction model based on these variables exhibits certain predictive value on MACE risk.

Purpose: Our previous study showed that circulating tumor cell (CTC) count combined with gene mutation detection might help differentiate benign and malignant pulmonary nodules (PNs). Herein, we aimed to expand the study cohort and conduct further sequencing analysis. Materials and Methods: Patients with PNs were included, and CTCs were identified before operation. Low-coverage whole-genome sequencing (LC-WGS) and lung cancer-related targeted gene sequencing were performed on CTCs. The diagnostic efficacy was evaluated by receiver operating characteristic (ROC) curve. The differences in CTC counts among subgroups classified by demographic–clinical characteristics were analyzed. LC-WGS–based copy number variation (CNV) analysis and targeted gene mutation analysis were conducted. Results: A total of 172 patients were included. CTC count of 2.5 was identified by the ROC curves as the optimal diagnostic cutoff. The sensitivity and specificity of CTC count for differentiating benign and malignant PNs were 54.2% and 78.6%, respectively. The diagnostic sensitivity and specificity of combined CTC count, radiological nodule type, and any malignant imaging features were 84.7% and 71.4%, respectively. The CTC counts were significantly greater in patients with aggressive tumors, later stage, and spread through air spaces. CTCs from malignant cases had more CNVs than those from benign cases. Conclusion CTC count can be used in identifying malignant PNs. The diagnostic efficacy can be improved if combined with computed tomography imaging characteristics. Further CNV analysis might help differential diagnosis. Greater CTC count might suggest more aggressive tumors. CTC detection can provide important information and guidance for subsequent management of PNs.

Integrin α _v β ₃ is overexpressed in various tumor cells and angiogenesis. To date, no drug has been proven to target it for therapy. A first-in-human study was designed to investigate the safety, pharmacokinetics, and dosimetry of ¹⁷⁷Lu-AB-3PRGD2, a novel integrin α _v β ₃-targeting radionuclide drug with an albumin-binding motif to optimize the pharmacokinetics. Ten patients (3 men, 7 women; aged 45 ± 16 years) with integrin α _v β ₃-avid tumors were recruited to accept ¹⁷⁷Lu-AB-3PRGD2 injection in a dosage of 1.57 ± 0.08 GBq (42.32 ± 2.11 mCi), followed by serial scans to obtain its dynamic distribution in the body. Safety tests were performed before and every 2 weeks after the treatment for 6-8 weeks. No adverse event over grade 3 was observed. ¹⁷⁷Lu-AB-3PRGD2 was excreted mainly through the urinary system, with intense radioactivity in the kidneys and bladder. Moderate distribution was found in the liver, spleen, and intestines. The estimated blood half-life was 2.85 ± 2.17 h. The whole-body effective dose was 0.251 ± 0.047 mSv/MBq. The absorbed doses were 0.157 ± 0.032 mGy/MBq in red bone marrow and 0.684 ± 0.132 mGy/MBq in kidneys. This first-in-human study of ¹⁷⁷Lu-AB-3PRGD2 treatment indicates its promising potential for targeted radionuclide therapy of integrin α _v β ₃-avid tumors. It merits further studies in more patients with escalating doses and multiple treatment courses.

Nigella sativa L. seeds have been traditionally utilized in Chinese folk medicine for centuries to treat vitiligo. This study revealed that the ethanolic extract of Nigella sativa L. (HZC) enhances melanogenesis and mitigates oxidative stress-induced cellular senescence and dysfunction in melanocytes. In accordance with established protocols, the ethanol fraction from Nigella sativa L. seeds was extracted, concentrated, and lyophilized to evaluate its herbal effects via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays, tyrosinase activity evaluation, measurement of cellular melanin contents, scratch assays, senescence-associated β-galactosidase (SA-β-gal) staining, enzyme-linked immunosorbent assay (ELISA), and Western blot analysis for expression profiling of experimentally relevant proteins. The results indicated that HZC significantly enhanced tyrosinase activity and melanin content while notably increasing the protein expression levels of Tyr, Mitf, and gp100 in B16F10 cells. Furthermore, HZC effectively mitigated oxidative stress-induced cellular senescence, improved melanocyte condition, and rectified various functional impairments associated with melanocyte dysfunction. These findings suggest that HZC increases melanin synthesis in melanocytes through the activation of the MAPK, PKA, and Wnt signaling pathways. In addition, HZC attenuates oxidative damage induced by H₂O₂ therapy by activating the nuclear factor E2-related factor 2-antioxidant response element (Nrf2-ARE) pathway and enhancing the activity of downstream antioxidant enzymes, thus preventing premature senescence and dysfunction in melanocytes.
Oxidative Stress/drug effects* ; Melanocytes/cytology* ; Cellular Senescence/drug effects* ; Nigella sativa/chemistry* ; Plant Extracts/pharmacology* ; Seeds/chemistry* ; Mice ; Animals ; Melanins/metabolism* ; Monophenol Monooxygenase/metabolism* ; Humans

Congenital orofacial cleft, the most common birth defect in the maxillofacial region, exhibits a wide range of prognosis depending on the severity of deformity and underlying etiology. Non-syndromic congenital orofacial clefts typically present with milder deformities and more favorable treatment outcomes, whereas syndromic congenital orofacial clefts often manifest with concomitant organ abnormalities, which pose greater challenges for treatment and result in poorer prognosis. This consensus provides an elaborate classification system for varying degrees of orofacial clefts along with corresponding diagnostic and therapeutic guidelines. Results serve as a crucial resource for families to navigate prenatal screening results or make informed decisions regarding treatment options while also contributing significantly to preventing serious birth defects within the development of population.
Humans ; Cleft Lip/diagnosis* ; Cleft Palate/diagnosis* ; Consensus ; Prenatal Diagnosis ; Female

Objective To explore the mechanism of Xiakucao Xiaoliu Mixture against non-small cell lung cancer （NSCLC）. Methods The effective components of Xiakucao Xiaoliu Mixture were screened by TCMSP, BATMAN-TCM database and literature reviews. The targets of effective components were predicted. NSCLC related targets were collected by GeneCards, OMIM, PharmGKB, TTD and Drugbank, combined with the differential genes of Xiakucao Xiaoliu Mixture against Lewis lung cancer mice. The intersection targets of Xiakucao Xiaoliu Mixture against NSCLC were obtained. Cytoscape software was used to construct the network diagram of traditional Chinese medicine-active ingredients-core targets. STRING database was used to construct PPI network diagram. GO function enrichment analysis and KEGG pathway enrichment analysis of the intersection targets were performed by Metascape database to predict the key targets and active components of Xiakucao Xiaoliu Mixture against NSCLC, and Schrodinger software was used to perform molecular docking verification. Results The 32 active components and 24 intersection targets of Xiakucao Xiaoliu Mixture against NSCLC were obtained. 11 core targets such as ESR1, MAPK1 were found. The mechanism of action may be related to 30 signaling pathways such as cellular senescence, receptor activation, prolactin signaling pathway. Conclusion The active components of Xiakucao Xiaoliu Mixture act on multiple targets and signaling pathways to regulate complex biological processes. By regulating ESR1 agsinst NSCLC, it may play an important role in improving the survival rate and prognosis of female patients.

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve

Objective:To investigate the prevalence of and risk factors associated with Neisseria gonorrhoeae (NG), Chlamydia trachomatis (CT) and high-risk human papillomavirus (HPV) coinfections among patients with newly diagnosed syphilis at a hospital in Nanjing. Methods:A cross-sectional study was conducted on patients with newly diagnosed syphilis at the STD Clinic, Hospital of Dermatology, Chinese Academy of Medical Sciences in Nanjing, China from May 2023 to April 2024. Urethral, cervical or rectal swabs were collected according to the gender and types of sexual behavior of the patients. Screening tests for CT, NG and HPV infections were then performed by nucleic acid amplification testing. High-risk HPV testing was performed only in female patients. Univariate analysis was carried out to investigate risk factors associated with CT infection. The chi-square test, chi-square test with continuity correction, or Fisher's exact test was chosen based on the sample size and expected values.Results:A total of 111 newly diagnosed syphilis patients with test specimens were collected, including 71 males (64%) and 40 females (36%), and their ages ranged from 16 to 87 years; there were 82 patients with early syphilis and 29 with late latent syphilis; the number of sexual partners in the past 3 months ranged from 0 to 3. Among the 60 male patients with early syphilis, 1 (1.7%) was co-infected with NG, and 12 (20%) with CT; among the 16 men who have sex with men, 7 (43.8%) were co-infected with CT, while 5 (11.4%) of the 44 heterosexual patients were co-infected with CT, showing a significant difference in CT infection rates between the two groups ( χ2 = 5.80, P = 0.016). Among the 22 female patients with early syphilis, 1 (4.5%) was co-infected with NG, and 8 (36.4%) with CT; among the 12 female patients aged < 25 years, 8 (66.7%) were infected with CT, while none of the 7 patients aged 25-44 years or the 3 patients aged ≥ 45 years were infected with CT, showing a significant difference in CT infection rates among the 3 age groups ( P = 0.005) ; among the 16 female patients with 1 sexual partner in the past 3 months, 3 were infected with CT, while 5 were infected with CT in the 6 female patients with 2-3 sexual partners in the past 3 months, with a significant difference in CT infection rates between the two groups ( P = 0.011). Out of the 40 female patients with syphilis, 16 (40%) were co-infected with high-risk HPV; the HPV infection rates did not differ among different age groups (age groups of < 25 years, 25-44 years, ≥ 45 years: 8/14, 2/9, 6/17, respectively; P = 0.265) . Conclusion:The CT infection rate was relatively high in patients with newly diagnosed early syphilis, and a relatively high infection rate of high-risk HPV was observed in female patients with syphilis aged < 25 years.

Objective:To analyze the HIV antibody positivity of new type drug users in drug abuse monitoring sites in Zhejiang Province from 2017 to 2023 and its influencing factors.Methods:From 2017 to 2023, a continuous cross-sectional survey was carried out in HIV monitoring posts among new type drug users in Zhejiang Province,the sample size was 400 people per site of 9 drug abuse surveillance sites in 7 cities. Questionnaires were conducted to investigate their social demographic information, related behavioral information, AIDS awareness, and acceptance of intervention measures, and blood was collected for HIV and syphilis antibody detection, with new type drugs users in the monitoring population as the research object. SPSS 22.0 software was used for statistical analysis.Results:A total of 13 955 new drug users were surveyed, and the number of new drug users was 2 518, 2 292, 2 526, 2 119, 2 161, 1 064 and 1 275 from 2017 to 2023, respectively, the HIV antibody positive rate of new type drugs users was 0.44%, 1.09%, 2.06%, 1.09%, 1.39%, 1.50%, 2.90%, respectively, and the HIV antibody positive standardized rate showed an increasing trend (all P<0.001). The results of multivariate logistic regression analysis showed that marital status: unmarried/divorced/widowed (a OR=3.92, 95% CI: 2.46-6.25), provincial household registration (a OR=3.54, 95% CI: 2.34-5.35), high school education or above (a OR=5.42, 95% CI: 3.68-7.98), sexual activity within the last 1 year after drug use (a OR=1.84, 95% CI: 1.19-2.84), and knowledge that the use of new drugs increases the risk of HIV infection (a OR=2.27, 95% CI: 1.17-4.39) were associated with increased HIV antibody favorable rates among new type drugs users. Conclusions:During 2017-2023, the HIV antibody-positive rate of new type drug users in Zhejiang Province showed an upward trend. It is necessary to strengthen the monitoring and intervention of this population.