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.

The aim of this study was to understand the internal genetic diversity and population history dynamics of ticks in Inner Mongolia,to provide data for designing effective vector control programs and revealing ticks'transmission mechanisms.From 2022 to 2023,the manual collection method was used to collect samples in Inner Mongolia.The 16S rDNA and COI gene sequences of ticks were used to identify Hyalomma marginatum,Haemaphysalis concinna,and Argas persicus,and analyze the sequence characteristics and genetic diversity within the populations.Base composition analysis indicated that the average A+T content of the 16S rDNA gene and CO I gene in the three ticks was significantly higher than that of C+G.Moreover,22 haplotypes of the COI gene and 12 haplotypes of the 16S rDNA sequence were identified in Hyalomma marginatum.Eleven haplotypes were identified according to the COI gene,and nine haplotypes were identified according to the16S rDNA sequence of Haemaphysalis concinna.Two haplotypes were identified on the basis of the COI gene,and six haplotypes were identified on the basis of the 16S rDNA sequence of Ar gas persicus.The minimum 16S rDNA haplotype diversity was 0.264 for Ar gas persicus and 0.579 for the other two species.The nucleotide diversity of the three tick species was less than 0.05.Tajima's val-ue and Fu's Fs value of the neutrality test were negative.Base saturation substitution analysis indicated that neither of the two genes in the three tick species reached saturation.The phylogenetic tree revealed that Hyalomma marginatum,Haema physalis concinna,and Ar gas persicus in Inner Mongolia independently aggregated into branches.In conclusion,the base content of Hyalomma marginatum,Haemaphysalis concinna,and Argas persicus genes in Inner Mongolia was consist-ent with the characteristics of insect mitochondrial DNA content.Furthermore,the three tick populations showed rapid evolu-tionary population expansion,and the phylogeny of three tick species showed independent aggregation into clades,with no pop-ulation isolation.

Objective:To investigate the clinical effect of ultrasound bone knife bone window technique combined with viscous bone in mandibular cysts and its impact on postoperative bone defect repair.Methods:60 patients with mandibular cysts who visited our hospital from January 2024 to June 2024 were selected as the study subjects,they were randomly divided into control group(30 cases)and experimental group(30 cases).The control group underwent traditional scraping surgery(without the use of bone defect repair materials).The experimental group used ultrasound bone knife bone window technology combined with adhesive bone treatment.The surgical time,postoperative visual pain simulation(VAS)score,intraoperative blood loss,postoperative swelling degree,and incidence of postoperative complications between the two groups were observed and compared.Bone defect repair was evaluated by cone beam computed tomography(CBCT)at 3 and 6 months postoperatively.Results:There was no significant difference in surgical time,intraoperative blood loss,postoperative swelling degree,and incidence of postoperative complications between the two groups(P＞0.05).The VAS scores of both groups at 3 and 7 d postoperative were lower than those at 1 d postoperative(P＜0.05),and the VAS score at 7 d postoperative was lower than that 3 d postoperative(P＜0.05).The VAS scores in the experimental group were significantly lower than those in the control group at 1,3 and 7 d postoperative(P＜0.05).The HU values and bone repair area ratio in the experimental group at 3 and 6 months postoperative were significantly higher than those in the control group(P＜0.05),and the HU values and bone repair area ratio in the control group and experimental group at 6 months postoperative were significantly increased compared to those at 3 months postoperative(P＜0.05).Conclusion:The combination of ultrasound bone knife bone window technology and adhesive bone treatment for mandibular cysts can significantly reduce postoperative pain,accelerate bone defect repair,and improve bone density and repair quality.Compared with traditional scraping surgery,the use of sticky bone has significant advantages in postoperative bone regeneration and does not significantly increase the risk of complications,making it of high clinical application value.

Objective To investigate the efficacy and influencing factors of programmed death-1(PD-1)inhibitors in neoadjuvant chemotherapy for triple-negative breast cancer(TNBC).Methods A total of 86 patients with TNBC who received neoadjuvant therapy in The Fifth Medical Center,PLA General Hospital between Jan.1,2018,and Jan.1,2024 and met the inclusion criteria were enrolled,and their clinicopathological data were collected.Based on the neoadjuvant treatment regimens,40 patients who received TP+PD-1 inhibitor(paclitaxel+carboplatin+pembrolizumab)were assigned to TP+PD-1 inhibitor group,and 46 patients who received TP(paclitaxel+carboplatin)were assigned to TP group.The efficacy and incidence of adverse events were compared between the 2 groups after 6 cycles of neoadjuvant therapy.According to the efficacy of neoadjuvant therapy,the patients were further categorized into pathological complete response(pCR)group and non-pCR group.Multivariate logistic stepwise regression analysis was performed to identify independent factors influencing neoadjuvant treatment efficacy.Patients were followed up until Dec.31,2024,and survival analysis was conducted using Kaplan-Meier method.Results There was no significant difference in the objective response rates between the TP+PD-1 inhibitor group and TP group after neoadjuvant therapy(95.0%[38/40]vs 91.3%[42/46],P=0.351].However,the pCR rate was significantly higher in the TP+PD-1 inhibitor group compared with the TP group(65.0%[26/40]vs 43.5%[20/46],P=0.047).There were no significant differences between the 2 groups in terms of disease-free survival,overall survival,or incidence of adverse events(all P＞0.05).Multivariate logistic stepwise regression analysis revealed that the expression of Ki-67 and treatment regimen were influencing factors of pCR after neoadjuvant therapy(odds ratio[OR]=3.382,95%confidence interval[95%CI]1.290-8.868,P=0.013;OR=2.524,95%CI 1.013-6.285,P=0.047).One case of distant metastasis and death occurred in the pCR group,while 8 cases of distant metastasis and 4 deaths occurred in the non-pCR group.The disease-free survival was significantly longer in the pCR group than in the non-pCR group(P=0.031),while the overall survival was similar between the 2 groups(P=0.087).Conclusion Compared with the 6-cycle TP regimen,the 6-cycle TP combined with PD-1 inhibitor regimen can improve the pCR rate in the neoadjuvant treatment of TNBC,with manageable adverse events,suggesting it may serve as a preferred option for TNBC neoadjuvant therapy.Ki-67 expression may serve as a predictive biomarker for achieving pCR.TNBC patients who achieved pCR have better disease-free survival than those who did not.

Malonylation is an important post-translational modification of proteins.In this work,a comprehensive malonylation proteomics study on hepatocellular carcinoma(HCC)tumorous and non-tumorous tissues using antibody enrichment combined with high performance liquid chromatography-mass spectrometry for discovery of early diagnostic biomarkers or potential new drug targets of HCC was performed.A total of 1299 malonylated peptides containing 1064 malonylated sites were identified from HCC tissues,corresponding to 511 malonylated proteins.Quantitative results showed that 56 and 80 malonylated proteins were up-regulated and down-regulated in HCC tissues,including 60 and 101 malonylated sites,respectively.Kyoto encyclopedia of genes and genomes(KEGG)pathway analysis showed that these differentially modified proteins were involved in various important pathways such as metabolic pathways,fatty acid degradation,and glycolysis/gluconeogenesis.As a key enzyme in glycolysis/gluconeogenesis,phosphoenolpyruvate carboxykinase 1(PCK1)was malonylated at lysine 244(K244)and the malonylation was only detected in HCC tumorous tissues.More importantly,the K244 site served as a binding site for Mn2+and highly conserved across different species.Therefore,it could speculate that the malonylation of K244 would affect its activity and played a role in liver cancer by affecting its binding with Mn2+,which requied further verification through site mutation experiments.Western blot analysis by malonylation pan antibody showed that the malonylation level reduced markedly in HCC tumorous tissues compared with adjacent non-tumorous tissues,which was consistent with mass spectrometry data.In addition,the proliferation and invasion of PLC/PRF/5 cell was significantly inhibited and protein malonylation level was increased obviously when treated with sodium malonate.All the evidence indicated that protein malonylation played an important role in HCC pathogenesis,and its molecular mechanism deserved further investigation.Furthermore,the 136 differentially malonylated proteins provided rich source of candidate targets for further research on HCC pathogenesis.

Objective:To investigate the longitudinal patterns and influencing factors of platelet counts among healthy adults in Sichuan Province from 2010 to 2021, and to inform the establishment of region-specific reference intervals for platelet counts.Methods:This study is a retrospective study. A total of 7 808 healthy adults who underwent annual physical examinations at West China Hospital, Sichuan University, between January 2010 and December 2021 were included. All participants were permanent Chengdu residents and completed consecutive complete blood count tests. Group-based trajectory modeling (GBTM) was used to identify distinct trajectories of platelet count over the ten-year period. One-way analyses were then conducted to compare baseline demographic characteristics (sex and age) among the different trajectory groups.Results:Among 7 808 participants, 4 589 (58.8%) were male and 3 219 (41.2%) were female. Four platelet count trajectories were identified by GBTM: steadily increasing group [27.4% (2 139/7 808)], early increase-plateau group [44.1% (3 445/7 808)], early decrease-subsequent increase group [5.4% (422/7 808)], and steadily decreasing group [23.1% (1 802/7 808)], with an average growth rate of 3.3%, 1.6%, 0.7%, and -0.6%, respectively. There were statistically significant differences in both sex and age distributions among the four trajectory groups. Sex-distribution differed significantly across the four trajectory groups ( χ2=73.3, P<0.001). The male proportions in the four trajectory groups were 59.6% (1 275/2 139), 62.8% (2 165/3 445), 48.1% (203/422), and 52.5% (946/1 802), respectively. The baseline ages were 45 (36, 55), 43 (35, 53), 50 (40, 60), and 47 (39, 58) years, respectively (H=121.0, P<0.001). Conclusions:Healthy adults in Sichuan Province exhibit four longitudinal trajectories of platelet counts: steadily increasing, early increase-plateau, early decrease-subsequent increase, and steadily decreasing. The two trajectories characterized by rising platelet counts (steadily increasing group and early increase-plateau group) exhibited higher male predominance and lower median ages, whereas the early decrease-subsequent increase group and the steadily decreasing group exhibited lower male proportions and higher median ages. Therefore, while establishing reference intervals and developing health management strategies for platelet counts, it is essential to account for the sex, age characteristics and the population′s dynamic changes.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Objective:To analyze the effects of shift work on the renal function of oil workers and investigate whether there is a measured response relationship between shift work and renal dysfunction.Methods:In this study, oil workers who participated in physical examinations at the North China Oilfield Downhole Hospital were selected as the study subjects, and the physical examinations as well as questionnaires of the study subjects in 2017 and 2018 were collected as the baseline data, which included blood biochemical indexes, socio-demographic characteristics, history of life behaviors, occupational exposures, and occupational histories. Three follow-up surveys were subsequently conducted in April 2019, April 2020, and January 2021. The presence of renal dysfunction in the study population was determined based on the glomerular filtration rate tested at the medical examination hospital. The exposure of the study subjects to shift work was assessed using the weighted shift index (WSI), the relationship between different levels of shift work and renal dysfunction was analyzed using Cox regression, and the measure of WSI and renal dysfunction was explored by restricted cubic spline (RCS). response relationship.Results:A total of 2292 study participants were included in this study, and the prevalence density of renal dysfunction was 87.44 k/year, of which the prevalence of renal dysfunction in females (30.31%), those with per capita monthly income <2, 000 yuan (27.00%), those who consume alcohol (27.10%), those who are hypertensive (23.05%), those who are exposed to high temperatures (27.37%), those who are exposed to organic solvents (30.42%), and those who are engaged in shift work (25.87%) were to be found had a higher prevalence of renal dysfunction ( P<0.05). After correcting for age, sex, and other risk factors, there was a nonlinear association between intensity of shift work and renal dysfunction, with a hazard ratio ( HR) of 1.29 (95% CI: 0.98-1.59) for the development of renal dysfunction in petroleum workers for shift work performed at higher intensities, and moderate intensity of exposure to shift work reduced the risk of renal dysfunction in petroleum workers ( HR=0.54 with a 95% CI: 0.39-0.75, P<0.001) . Conclusion:Prolonged shift work increases the risk of renal dysfunction in oil workers, and the occurrence of renal dysfunction in oil workers is influenced by multiple factors.

ObjectiveThis study proposes a novel single-cell protein localization method based on a class perception graph convolutional network (CP-GCN) to overcome several critical challenges in protein microscopic image analysis, including the scarcity of cell-level annotations, inadequate feature extraction, and the difficulty in achieving precise protein localization within individual cells. The methodology involves multiple innovative components designed to enhance both feature extraction and localization accuracy. MethodsFirst, a class perception module (CPM) is developed to effectively capture and distinguish semantic features across different subcellular categories, enabling more discriminative feature representation. Building upon this, the CP-GCN network is designed to explore global features of subcellular proteins in multicellular environments. This network incorporates a category feature-aware module to extract protein semantic features aligned with label dimensions and establishes a subcellular relationship mining module to model correlations between different subcellular structures. By doing so, it generates co-occurrence embedding features that encode spatial and contextual relationships among subcellular locations, thereby improving feature representation. To further refine localization, a multi-scale feature analysis approach is employed using the K-means clustering algorithm, which classifies multi-scale features within each subcellular category and generates multi-cell class activation maps (CAMs). These CAMs highlight discriminative regions associated with specific subcellular locations, facilitating more accurate protein localization. Additionally, a pseudo-label generation strategy is introduced to address the lack of annotated single-cell data. This strategy segments multicellular images into single-cell images and assigns reliable pseudo-labels based on the CAM-predicted regions, ensuring high-quality training data for single-cell analysis. Under a transfer learning framework, the model is trained to achieve precise single-cell-level protein localization, leveraging both the extracted features and pseudo-labels for robust performance. ResultsExperimental validation on multiple single-cell test datasets demonstrates that the proposed method significantly outperforms existing approaches in terms of robustness and localization accuracy. Specifically, on the Kaggle 2021 dataset, the method achieves superior mean average precision (mAP) metrics across 18 subcellular categories, highlighting its effectiveness in diverse protein localization tasks. Visualization of the generated CAM results further confirms the model’s capability to accurately localize subcellular proteins within individual cells, even in complex multicellular environments. ConclusionThe integration of the CP-GCN network with a pseudo-labeling strategy enables the proposed method to effectively capture heterogeneous cellular features in protein images and achieve precise single-cell protein localization. This advancement not only addresses key limitations in current protein image analysis but also provides a scalable and accurate solution for subcellular protein studies, with potential applications in biomedical research and diagnostic imaging. The success of this method underscores the importance of combining advanced deep learning architectures with innovative training strategies to overcome data scarcity and improve localization performance in biological image analysis. Future work could explore the extension of this framework to other types of microscopic imaging and its application in large-scale protein interaction studies.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.