ObjectiveTo investigate the novel post-translational modifications (PTMs) of SnRK2.6, a central component in the abscisic acid (ABA) signaling pathway, such as SUMOylation, and to establish a foundation for revealing the physiological functions and molecular mechanisms of SnRK2.6 regulated by these new modifications. MethodsThe interaction between SnRK2.6 and the SUMO E3 ligase SIZ1, as well as members of the SUMO protease family, was examined using yeast two-hybrid and in vitro pull-down assays. An in vitro SUMOylation system in Escherichia coli was utilized to determine whether SnRK2.6 undergoes SUMOylation. Mass spectrometry, combined with site-directed mutagenesis of candidate lysine residues, was employed to identify potential SUMOylation sites on SnRK2.6. In vitro de-SUMOylation assays were performed to assess whether SUMO proteases interacting with SnRK2.6 could catalyze the removal of SUMO moieties from modified SnRK2.6. The protein stability of SnRK2.6 was assessed in a cell-free degradation assay using bacterial-purified SnRK2.6 incubated with total protein extracts from Col and siz1 mutant seedlings. To dissect the genetic relationship between SnRK2.6 and SIZ1, stomatal aperture assays were performed under ABA treatment using snrk2.6, siz1, and snrk2.6 siz1 double mutant plants. ResultsSnRK2.6 physically interacts with SIZ1 and the SUMO protease ESD4, with the binding domains localized to the C-terminal region of SIZ1 and the N-terminal region of ESD4, respectively. SnRK2.6 was found to be SUMOylated, exhibiting two distinct high-molecular-mass bands ranging from 70 to 100 ku, indicative of modified forms. Bioinformatics analysis predicted four putative SUMOylation sites on lysine residues K57, K63, K142, and K190. Mass spectrometry identified three SUMOylation sites on K63, K142, and K174. However, individual or combinatorial point mutations on these sites had minimal impact on the pattern or intensity of SUMOylation signals, suggesting that these residues may not be responsible for the SUMOylation on SnRK2.6. Instead, such mutations only weaken the protein stability or accelerate the protein mobility of SnRK2.6. Therefore, the exact SUMOylation sites on SnRK2.6 remain unidentified. In de-SUMOylation experiments, incubation of GST-ESD4 with SUMOylated SnRK2.6 for 1-2 h led to the near-complete disappearance of both SUMOylated bands. In contrast, neither the GST control nor the catalytically inactive mutant GST-ESD4^C448S exhibited any de-SUMOylation activity. In protein turnover experiments, SnRK2.6 exhibited markedly enhanced half-life in siz1 compared with Col, indicating that SIZ1-dependent SUMOylation promotes SnRK2.6 turnover. Phenotypically, snrk2.6 mutants were completely insensitive to ABA-induced stomatal closure; siz1 mutants displayed pronounced hypersensitivity; and the snrk2.6 siz1 double mutant phenocopied snrk2.6—showing no significant response to ABA beyond that of the snrk2.6 mutant. These data indicate that SIZ1 acts as a negative regulator of ABA-triggered stomatal closure and SnRK2.6 functions as a positive regulator, and the inhibitory activity of SIZ1 is strictly dependent on SnRK2.6, placing SnRK2.6 genetically upstream of SIZ1 in the ABA signaling pathway. ConclusionSnRK2.6 undergoes SUMOylation, although the specific SUMOylation sites have not been defined. SnRK2.6 is dynamically regulated by reversible SUMOylation—catalyzed by SIZ1 and reversed by ESD4—which controls its protein stability. SUMOylation acts as a destabilizing signal for SnRK2.6, and SIZ1 exerts its negative effect on ABA-triggered stomatal closure probably through promoting SnRK2.6 degradation via SUMOylation. These findings uncover SUMOylation as a critical regulatory layer fine-tuning SnRK2.6 abundance in ABA signaling.

Objective To explore the effects and mechanism of Jianpi Shuyi Decoction in improving pancreatic fibrosis in chronic pancreatitis(CP)based on network pharmacology and animal experiments.Methods TCMSP was used to screen the active components and targets of Jianpi Shuyi Decoction.GeneCards was used to obtain the disease targets of pancreatic fibrosis,and the intersection of drug and disease targets was used to construct the protein interaction network and the drug-component-target network,and the core target genes were screened out.GO and KEGG pathway enrichment analysis was performed on the intersecting targets.Caerulein was used to induce CP mouse model,and Jianpi Shuyi Decoction was given for gavage.HE and Sirius red staining were used to observe pancreatic tissue inflammation and collagen deposition,respectively.RT-qPCR was used to observe the mRNA expression levels of Acta2,COL1A1,PI3K and Akt1 in pancreatic tissue.Immunohistochemistry staining was used to observe the protein expression levels of α-SMA,COL-1,p-PI3K and p-Akt in pancreatic tissues.Results A total of 181 active components were screened from Jianpi Shuyi Decoction,corresponding to 284 targets,with 240 targets overlapping between drugs and disease and the core targets were PTGS2,HSP90AA1,etc.193 signaling pathways were obtained from KEGG pathway enrichment analysis,primarily involving lipids and atherosclerosis,chemical carcinogenic-receptor activation,PI3K-Akt signaling pathway and others.The results of animal experiments showed that,compared with the normal group,the model group showed a large number of inflammatory cell infiltration and collagen deposition in pancreatic tissue,the mRNA expression of Acta2,COL1A1,PI3K and Akt1 in pancreatic tissue significantly increased(P<0.01),and the protein expression of α-SMA,COL-1,p-PI3K,p-Akt significantly increased(P<0.01);Jianpi Shuyi Decoction significantly reduced the inflammation and collagen deposition in pancreas of mice,reduced the mRNA expression of Acta2,COL1A1,PI3K and Akt1(P<0.05),and attenuated the protein expression of α-SMA,COL-1,p-PI3K and p-Akt in pancreatic tissue(P<0.05).Conclusion Jianpi Shuyi Decoction may exert a therapeutic effect on CP pancreatic fibrosis by regulating the PI3K/Akt signaling pathway,attenuating inflammation and collagen deposition in the pancreas,and reducing the levels of α-SMA and COL-1.

PURPOSE: To investigate the incidence and influencing factors of bone loss in patients with spinal cord injury (SCI). METHODS: A retrospective case-control study was conducted. Patients with SCI in our hospital from January 2019 to March 2023 were collected. According to the correlation between bone mineral density (BMD) at different sites, the patients were divided into the lumbar spine group and the hip joint group. According to the BMD value, the patients were divided into the normal bone mass group (t > -1.0 standard deviation) and the osteopenia group (t ≤ -1.0 standard deviation). The influencing factors accumulated as follows: gender, age, height, weight, cause of injury, injury segment, injury degree, time after injury, start time of rehabilitation, motor score, sensory score, spasticity, serum value of alkaline phosphatase, calcium, and phosphorus. The trend chart was drawn and the influencing factors were analyzed. SPSS 26.0 was used for statistical analysis. Correlation analysis was used to test the correlation between the BMD values of the lumbar spine and bilateral hips. Binary logistic regression analysis was used to explore the influencing factors of osteoporosis after SCI. p < 0.05 was considered statistically significant. RESULTS: The incidence of bone loss in patients with SCI was 66.3%. There was a low concordance between bone loss in the lumbar spine and the hip, and the hip was particularly susceptible to bone loss after SCI, with an upward trend in incidence (36% - 82%). In this study, patients with SCI were divided into the lumbar spine group (n = 100) and the hip group (n = 185) according to the BMD values of different sites. Then, the lumbar spine group was divided into the normal bone mass group (n = 53) and the osteopenia group (n = 47); the hip joint group was divided into the normal bone mass group (n = 83) and the osteopenia group (n = 102). Of these, lumbar bone loss after SCI is correlated with gender and weight (p = 0.032 and < 0.001, respectively), and hip bone loss is correlated with gender, height, weight, and time since injury (p < 0.001, p = 0.015, 0.009, and 0.012, respectively). CONCLUSIONS The incidence of bone loss after SCI was high, especially in the hip. The incidence and influencing factors of bone loss in the lumbar spine and hip were different. Patients with SCI who are male, low height, lightweight, and long time after injury were more likely to have bone loss.
Humans ; Spinal Cord Injuries/complications* ; Male ; Female ; Retrospective Studies ; Incidence ; Adult ; Bone Density ; Middle Aged ; Case-Control Studies ; Osteoporosis/etiology* ; Lumbar Vertebrae ; Bone Diseases, Metabolic/etiology* ; Aged ; Risk Factors

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Objective:To carry out carrier screening among people of childbearing age, detect the pathogenic genes of monogenic genetic diseases and analyze the carrier status of pathogenic variants, so as to provide fertility guidance and intervention measures for high-risk families.Methods:From August 2022 to August 2023, 1 533 families of childbearing age who met the criteria were recruited in the Chinese PLA General Hospital, including a total of 3 044 subjects. According to the standard enrollment procedure, 223 genes (197 autosomal recessive genes and 26 X-linked genes) of the subjects were tested. According to the screening results, genetic counseling and fertility guidance were provided to the subjects. Invasive prenatal diagnosis was performed for high-risk couples (both couples being carriers of the same autosomal recessive disease gene or the woman was a carrier of X-linked disease gene), and their pregnancy pattern, outcome and offspring phenotype were followed up.Results:(1) A total of 3 044 cases from 1 511 couples and women of childbearing age from 22 families were included for carrier screening. Totally 1 503 families chose simultaneous screening and 30 families chose sequential screening out of the 1 533 families. Among the 3 044 subjects, 1 603 individuals carried at least one pathogenic or likely pathogenic variant, and the overall carrier rate was 52.66% (1 603/3 044). A total of 2 292 pathogenic or likely pathogenic variants were detected, and 0.75 variants (2 292/3 044) were detected per capita. (2) The three genes with the highest carrier rates were GJB2 (8.67%, 264/3 044), CYP21A2 (3.19%, 97/3 044) and PAH (3.09%, 94/3 044). There were 32 genes with a carrier rate ≥1/200, 17 genes with a carrier rate ≥1/100, and 7 genes with a carrier rate ≥1/50. (3) Thirty-eight high-risk families were identified. After excluding G6PD gene mutation, there were 33 high-risk families, of which 25 couples were carriers of the same autosomal recessive gene, 9 women were carriers of X-linked gene, and 1 family was double high-risk couple with both autosomal recessive and X-linked gene. After further excluding the GJB2 c.109G>A mutation, 21 high-risk families were identified. Preimplantation genetic testing for monogenic disease was performed in 12 families after genetic counseling. Prenatal diagnosis was completed in 4 out of 5 high-risk families who conceived naturally. Two fetuses carried the parental variants and terminated the pregnancy, one fetus did not carry the parental variants but was induced due to trisomy 21 syndrome, and one fetus was a carrier of congenital disorders of glycosylation type 1a.Conclusions:Carrier screening effectively identifies high-risk genetic disease families and provides reproductive guidance to prevent the birth of affected children. However, establishing multidisciplinary team is essential for managing complex cases. Implementation should prioritize prenatal institutions with genetic counseling or diagnostic expertise for monogenic disorders or established referral networks.

Objective:To investigate the reference intervals of serum uric acid levels in normal-weight children and analyze the factors influencing these levels.Methods:In this cross-sectional study, clinical data were collected from 7 910 normal-weight children, aged 1 month to 15 years, who underwent health check-ups at the Children′s Hospital of Zhejiang University School of Medicine between August 2013 and August 2023. Data included sex, age, pubertal signs, blood pressure, and serum uric acid levels. The participants were categorized into 4 age groups: 1-<12 months, 1-<6 years, 6-<11 years, and 11-<16 years, and were further analyzed by sex. The P5 and P95 percentiles of uric acid values were defined as the lower and upper limits of the reference interval, respectively. Correlation analysis and partial correlation analysis were used to assess the relationship between uric acid and other variables such as age, body mass index Z value, and Tanner stage. Multivariate linear regression was used to compare uric acid levels across gender and age groups, respectively. Results:Among the 7 910 children, the distribution across age groups was as follows: 562 (317 boys) in 1-<12 months, 4 120 (2 366 boys) in 1-<6 years, 2 357 (1 432 boys) in 6-<11 years, and 871 (536 boys) in 11-<16 years, the uric acid levels in boys were significantly higher than those in girls ( P<0.05). Uric acid levels exhibited a positive correlation with age ( r=0.47 , 0.20, both P<0.001), and a weak positive correlation with BMI Z-scores(both r=0.11, P<0.001). Among participants aged 6-<11 years and 11-<16 years, uric acid levels in boys were positively correlated with Tanner stage ( r=0.10, 0.27, both P<0.05), but no significant correlation was observed in girls (all P>0.05). The uric acid levels were significantly higher in boys than in girls in the 1-<12 months, 1-<6 years and 11-<16 years age groups (all P<0.05), but no significant gender difference was found in the 6-<11 years groups ( P>0.05). Uric acid levels exhibited statistically significant variations among age groups ( P<0.001). The reference intervals of uric acid values were as follows in 1-<12 months age group, 157-335 μmol/L for boys and 160-315 μmol/L for girls; in 1-<6 years age group, 180-359 μmol/L for boys and 180-355 μmol/L for girls; in 6-<11 years group, 190-375 μmol/L; in 11-<16 years age group, 237-480 μmol/L for boys and 218-410 μmol/L for girls. Conclusions:Reference intervals for uric acid varying significantly across different pediatric age groups. Sex, and pubertal development status are closely related to uric acid levels.

Background Psychological disturbances such as work-family conflict and depressive mood are prevalent among occupational groups and are closely related to eating behavior. Therefore, investigating the influencing factors of eating behavior is of great significance for promoting the health behaviors of occupational populations. Objective To clarify the current situation of eating behavior among the occupational populations aged 18 to 60 years in China, and to explore the relationship between work-family conflict, depressive mood, and eating behavior, and to test the mediating role of depressive mood in the relationship. Methods The study used a data set containing occupational populations aged 18 to 60 years extracted from the 2021 Psychology and Behavior Investigation of Chinese Residents. The Work-Family Conflict Scale, the Chinese version of the Sakata Eating Behavior Scale Short Form, and the Patient Health Questionnaire-Depression Scale were used. Potential influencing factors of eating behavior of the occupational populations were evaluated by multiple linear regression. Structural equation modeling was used to analyze the relationships between work-family conflict, depressive mood, and eating behavior, and the Bootstrap method was used to test the mediating effect of depressive mood on the relationship of work-family conflict and eating behavior. Results Among the occupational populations, the proportion of reporting high work-family conflict was 48.4%, and the proportion of reporting mild depression and above was 48.7%. The total score of eating behavior was (16.16±4.64), and the proportion of high abnormal eating behavior tendency was 39.1%. There were significant differences in eating behavior score among different age, educational level, marital status, number of offspring, occupation, smoking, and drinking groups (P<0.05). The partial correlation analysis showed that work-family conflict and depressive mood were positively correlated with abnormal eating behavior (r=0.367, 0.386, P<0.001); work-family conflict was positively correlated with depressive mood (r=0.466, P<0.001). The results of the multiple linear regression showed that depressive mood, work-family conflict, age, smoking, drinking, and education level were associated with eating behavior (P<0.05). The structural equation modeling indicated that work-family conflict positively associated with depressive mood (b=0.529, P<0.001), depressive mood positively associated with abnormal eating behavior (b=0.292, P<0.001), and work-family conflict positively associated with abnormal eating behavior (b=0.270, P<0.001). Depressive mood played a partial mediating role in the relationship between work-family conflict and eating behavior, and the effect value was 0.154 (95%CI: 0.132, 0.179) that accounted for 36.32% of the total effect. Conclusion Work-family conflict could directly affect the eating behavior among occupational populations, and also indirectly affect eating behavior through a mediating effect of depressive mood. Therefore, optimizing the allocation of tasks between work and family, providing psychological support in need, alleviating work-family conflict and depressive mood may improve the eating behavior and mental health of working populations.

OBJECTIVE: To investigate the effect of zedoarondiol on neovascularization of atherosclerotic (AS) plaque by exosomes experiment. METHODS: ApoE^-/- mice were fed with high-fat diet to establish AS model and treated with high- and low-dose (10, 5 mg/kg daily) of zedoarondiol, respectively. After 14 weeks, the expressions of anti-angiogenic protein thrombospondin 1 (THBS-1) and its receptor CD36 in plaques, as well as platelet activation rate and exosome-derived miR-let-7a were detected. Then, zedoarondiol was used to intervene in platelets in vitro, and miR-let-7a was detected in platelet-derived exosomes (Pexo). Finally, human umbilical vein endothelial cells (HUVECs) were transfected with miR-let-7a mimics and treated with Pexo to observe the effect of miR-let-7a in Pexo on tube formation. RESULTS: Animal experiments showed that after treating with zedoarondiol, the neovascularization density in plaques of AS mice was significantly reduced, THBS-1 and CD36 increased, the platelet activation rate was markedly reduced, and the miR-let-7a level in Pexo was reduced (P<0.01). In vitro experiments, the platelet activation rate and miR-let-7a levels in Pexo were significantly reduced after zedoarondiol's intervention. Cell experiments showed that after Pexo's intervention, the tube length increased, and the transfection of miR-let-7a minics further increased the tube length of cells, while reducing the expressions of THBS-1 and CD36. CONCLUSION Zedoarondiol has the effect of inhibiting neovascularization within plaque in AS mice, and its mechanism may be potentially related to inhibiting platelet activation and reducing the Pexo-derived miRNA-let-7a level.
Animals ; MicroRNAs/genetics* ; Exosomes/drug effects* ; Plaque, Atherosclerotic/genetics* ; Neovascularization, Pathologic/genetics* ; Human Umbilical Vein Endothelial Cells/metabolism* ; Humans ; Blood Platelets/drug effects* ; Apolipoproteins E/deficiency* ; Thrombospondin 1/metabolism* ; CD36 Antigens/metabolism* ; Platelet Activation/drug effects* ; Male ; Mice ; Mice, Inbred C57BL

Glutamine provides carbon and nitrogen to support the proliferation of cancer cells. However, the precise reason why cancer cells are particularly dependent on glutamine remains unclear. In this study, we report that glutamine modulates the tumor suppressor F-box and WD repeat domain-containing 7 (FBW7) to promote cancer cell proliferation and survival. Specifically, lysine 604 (K604) in the sixth of the 7 substrate-recruiting WD repeats of FBW7 undergoes glutaminylation (Gln-K604) by glutaminyl tRNA synthetase. Gln-K604 inhibits SCFFBW7-mediated degradation of c-Myc and Mcl-1, enhances glutamine utilization, and stimulates nucleotide and DNA biosynthesis through the activation of c-Myc. Additionally, Gln-K604 promotes resistance to apoptosis by activating Mcl-1. In contrast, SIRT1 deglutaminylates Gln-K604, thereby reversing its effects. Cancer cells lacking Gln-K604 exhibit overexpression of c-Myc and Mcl-1 and display resistance to chemotherapy-induced apoptosis. Silencing both c-MYC and MCL-1 in these cells sensitizes them to chemotherapy. These findings indicate that the glutamine-mediated signal via Gln-K604 is a key driver of cancer progression and suggest potential strategies for targeted cancer therapies based on varying Gln-K604 status.
Glutamine/metabolism* ; Myeloid Cell Leukemia Sequence 1 Protein/genetics* ; Humans ; Proto-Oncogene Proteins c-myc/genetics* ; Cell Proliferation ; Signal Transduction ; Neoplasms/pathology* ; F-Box-WD Repeat-Containing Protein 7/genetics* ; Cell Survival ; Cell Line, Tumor ; Apoptosis

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence