Diabetic kidney disease（DKD） is a chronic kidney structural and functional disorder caused by diabetes. With the global prevalence of diabetes continuing to rise， DKD has gradually become a major cause of chronic kidney disease and end-stage renal disease（ESRD）， posing a serious threat to patients' quality of life and long-term health outcomes. Studies have shown that apoptosis plays a pivotal role in the development and progression of DKD， with its mechanisms involving abnormal activation of multiple signaling pathways such as Toll-like receptor 4（TLR4）/nuclear transcription factor-κB（NF-κB）/B-cell lymphoma-2（Bcl-2）/cysteinyl aspartate-specific proteinase（Caspase）-3， protein kinase R-like endoplasmic reticulum kinase（PERK）/eukaryotic initiation factor 2α（eIF2α）/activating transcript factor 4（ATF4）/CCAAT enhancer-binding protein homologous protein（CHOP）， phosphatidylinositol 3-kinase（PI3K）/protein kinase B（Akt）/glycogen synthase kinase-3β（GSK-3β）， Janus kinase 2（JAK2）/signal transducer and activator of transcription 3（STAT3）， adenosine monophosphate-activated protein kinase（AMPK）/mammalian target of rapamycin（mTOR） and silent information regulator 1（SIRT1）/tumor suppressor protein 53（p53）， thereby accelerating renal pathological damage in DKD. Extensive evidence-based medical studies have confirmed that traditional Chinese medicine（TCM）， leveraging its unique therapeutic advantages of multi-target， multi-component and multi-pathway approaches， has demonstrated remarkable efficacy and favorable safety profiles in treating DKD. Recent studies have demonstrated that active components of TCM can specifically target and modulate key effectors in apoptotic signaling pathways. Meanwhile， traditional compound formulations exert synergistic effects through multiple approaches such as replenishing deficiency and activating blood circulation， detoxifying and dredging collaterals， tonifying kidney essence， and removing stasis and purging turbidity， thereby comprehensively regulating critical pathological processes including endoplasmic reticulum stress and mitochondrial apoptosis pathways. This combined therapeutic approach of molecular targeting and holistic regulation provides novel strategies for delaying the progression of DKD. Based on this， this paper provides an in-depth analysis of key apoptotic signaling pathways and their regulatory mechanisms， while systematically summarizing recent research advances regarding the therapeutic effects of TCM active components， compound formulations， and proprietary Chinese medicines on DKD through modulation of these pathways， with particular emphasis on their underlying molecular mechanisms. These findings not only elucidate the modern scientific connotation and theoretical basis of TCM in treating DKD but also establish a solid theoretical and practical foundation for promoting the wider clinical application and further research of TCM in the field of DKD treatment.

BACKGROUND: To evaluate the efficacy and safety of the first cohort of people in China treated with a responsive neurostimulation system (Epilcure TM , GenLight MedTech, Hangzhou, China) for focal drug-resistant epilepsy in this study. METHODS: This multicenter, before-and-after self-controlled study was conducted across 8 centers from March 2022 to June 2023, involving patients with drug-resistant epilepsy who were undergoing responsive neurostimulation (RNS). The study was based on an ongoing multi-center, single-blind, randomized controlled study. Efficacy was assessed through metrics including median seizure count, seizure frequency reduction (SFR), and response rate. Multivariable linear regression analysis was conducted to explore the relationships of basic clinical factors and intracranial electrophysiological characteristics with SFR. The postoperative quality of life, cognitive function, depression, and anxiety were evaluated as well. RESULTS: The follow-up period for the 19 participants was 10.7 ± 3.4 months. Seizure counts decreased significantly 6 months after device activation, with median SFR of 48% at the 6th month (M6) and 58% at M12 ( P  <0.05). The average response rate after 13 months of treatment was 42%, with 21% ( n  = 4) of the participants achieving seizure freedom. Patients who have previously undergone resective surgery appear to achieve better therapeutic outcomes at M11, M12 and M13 ( β  <0, P  <0.05). No statistically significant differences were observed in patients' scores of quality of life, cognition, depression and anxiety following stimulation when compared to baseline measurements. No serious adverse events related to the devices were observed. CONCLUSIONS: The preliminary findings suggest that Epilcure TM exhibits promising therapeutic potential in reducing the frequency of epileptic seizures. However, to further validate its efficacy, larger-scale randomized controlled trials are required. REGISTRATION Chinese Clinical Trial Registry (No. ChiCTR2200055247).
Humans ; Female ; Male ; Drug Resistant Epilepsy/therapy* ; Adult ; Young Adult ; Middle Aged ; China ; Adolescent ; Treatment Outcome ; Quality of Life ; Single-Blind Method ; Seizures ; Electric Stimulation Therapy/methods*

BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome

Objective:To investigate the relationship between protein tyrosine phosphatase non-receptor type 1 (PTPN1) gene polymorphism and the risk of gestational diabetes mellitus (GDM).Methods:In this case-control study, 4 835 pregnant women who delivered from March, 2012 to July, 2014 in the Department of Gynecology and Obstetrics at the First Hospital of Shanxi Medical University were consecutively enrolled. Among them, 789 cases were diagnosed with GDM. A simple random sampling method was used to select 334 pregnant women with GDM as the case group, and 334 healthy pregnant women matched by maternal age, gestation time and residence were set as control. The DNA genotyping was performed in the subjects, and those with genotyping deletions10% were excluded; and finally, 322 and 317 subjects were included in case and control group, respectively. Under the codominant, dominant, recessive, and allelic genetic models, the unconditional logistic regression model was used to check the relationship between 13 candidate single nucleotide polymorphism (snp) loci in PTPN1 gene and the risk of GDM. The Haploview was used to analyze the relationship between haplotypes and risk of GDM, and multiple comparisons were adjusted with the false discovery rate (FDR) method.Results:The age of the 639 pregnant women analyzed in this study was (30.28±4.32) years. The proportions of pre-pregnancy body mass index (BMI)≥24.0 kg/m 2 and having a family history of diabetes were significantly higher in the GDM group compared to those in the control group (29.19% vs 16.72% and 13.04% vs 6.31%, respectively, both P0.05). The rs6096644 locus was positively associated with increased risk of GDM in co-dominant (GG vs AA, OR=2.76, 95% CI: 1.18-6.44) and recessive (GG vs AA+AG, OR=2.78, 95% CI: 1.20-6.46) genetic models (all q0.2). The rs6096655 locus was positively associated with increased risk of GDM in codominant (AA vs GG, OR=5.90, 95% CI: 1.27-27.36) and recessive (AA vs GG+GA, OR=5.50, 95% CI: 1.19-25.38) and alleles (A vs G, OR=1.51, 95% CI: 1.09-2.08) genetic models (all q0.2). The rs6013317 locus was associated with an increased risk of GDM in the allele (A vs G, OR=1.74, 95% CI: 1.15-2.63) genetic model (all q0.2). The GAGG haplotype and GGAG haplotype in haplotype block 1 (rs4811262, rs6096646, rs6096655, rs6013317), and the GGGA haplotype in haplotype block 2 (rs6068018, rs6123105, rs6013324, rs2869621) of the PTPN1 gene were all positively associated with an increased risk of GDM (all P0.05). Conclusion:PTPN1 gene polymorphisms may associated with risk of GDM, moreover, complex haplotype structures within the gene influence the risk of GDM.

Objective To investigate the role of matrix GLA protein(MGP)in the pathogenesis of idiopathic calcium oxalate kidney stones(ICOS),and to find potential biomarkers for early diagnosis and disease evaluation.Methods A total of 120 patients admitted to our hospital from September 2021 to September 2023 were prospectively included,of which 60 patients with ICOS were in the calculus group and 60 patients without calculus were in the control group.Serum biochemical indexes and immunohistochemical scores of the two groups were detected,urinary MGP levels were determined by ELISA,and MGP mRNA and protein expression in renal papilla tissues were detected by qPCR and Western blot.The independent risk factors of ICOS were screened by Logistic regression analysis,and the prediction model was drawn by nomogram.Results Compared with control group,urinary MGP content in calculus group was decreased[(1 805.91±244.44)pg/ml vs.(2 014.79±252.14)pg/mnl,P＜0.05).Expression of MGP mRNA and MGP protein in renal papillae decreased(0.89±0.15 vs.1.00±0.00,P=0.001)and decreased(0.87±0.18 vs.1.00±0.00,P＜0.05).MGP immunohistochemical scores of renal tissue were decreased[4(2-6)scores vs.6(4-8)scores,P＜0.001].Multivariate analysis showed that urinary calcium(OR=1.370),urinary MGP(OR=1.127),renal papilla MGP relative expression level(OR=27.532)and renal tissue MGP immunohistochemical score(OR=1.359)were independent risk factors for ICOS.Area under ROC curve of the nomogram prediction model built based on the above factors is 0.839,indicating that the model has good differentiation ability in risk prediction.Conclusion MGP is closely related to the pathogenesis of ICOS.Urinary and renal tissue MGP levels may be potential biomarkers for early diagnosis and disease assessment of ICOS.

Objective To systematically evaluate the published models in prediction of the risk of lung infections in elderly patients with hip fracture so as to provide a guidance for medical workers in selection or development of suitable risk prediction models.Methods Relevant studies were searched from databases including CNKI,Wanfang Data,VIP,SinoMed,PubMed,Web of Science,Cochrane Library,Embase and CINAHL,from the inception to 31st January,2024.Data were extracted from the selected literature and a bias assessment tool of risk predictive model was used to evaluate the risk of bias and applicability of the included literature.Results A total of 1,035 articles were retrieved,of which seven studies involving 13 predictive models were finally included after screening.The sample sizes ranged from 305 to 2,669 cases and lung infection rates ranged from 5.40%to 20.02%.The repeatedly reported predictors included age,gender,chronic obstructive pulmonary disease,hypoproteinaemia,American Society of Anesthesiologists(ASA)Physical Status Classification and white blood cell count.In the 13 models constructed,the reported area under the curve(AUC)of subjects'job characteristics ranged from 0.667 to 0.996.Five out of seven studies had good overall applicability,but all with high risk of bias.Conclusion The predictive models for lung infections in elderly patients with hip fracture are still in the stage of development.Although the predictive models show some predictive performance,however they are still deficient,and all studies have been found with a high risk in bias.

Peptide-based therapies have attracted considerable interest in the treatment of cancer, diabetes, bacterial infections, and neurodegenerative diseases due to their promising therapeutic properties and enhanced safety profiles. This review provides a comprehensive overview of the major trends in peptide drug discovery and development, emphasizing preclinical strategies aimed at improving peptide stability, specificity, and pharmacokinetic properties. It assesses the current applications and challenges of peptide-based drugs in these diseases, illustrating the pharmaceutical areas where peptide-based drugs demonstrate significant potential. Furthermore, this review analyzes the obstacles that must be overcome in the future, aiming to provide valuable insights and references for the continued advancement of peptide-based drugs.
Humans ; Peptides/pharmacology* ; Animals ; Neoplasms/drug therapy* ; Drug Discovery ; Neurodegenerative Diseases/drug therapy* ; Diabetes Mellitus/drug therapy*

Objective To systematically evaluate the published models in prediction of the risk of lung infections in elderly patients with hip fracture so as to provide a guidance for medical workers in selection or development of suitable risk prediction models.Methods Relevant studies were searched from databases including CNKI,Wanfang Data,VIP,SinoMed,PubMed,Web of Science,Cochrane Library,Embase and CINAHL,from the inception to 31st January,2024.Data were extracted from the selected literature and a bias assessment tool of risk predictive model was used to evaluate the risk of bias and applicability of the included literature.Results A total of 1,035 articles were retrieved,of which seven studies involving 13 predictive models were finally included after screening.The sample sizes ranged from 305 to 2,669 cases and lung infection rates ranged from 5.40%to 20.02%.The repeatedly reported predictors included age,gender,chronic obstructive pulmonary disease,hypoproteinaemia,American Society of Anesthesiologists(ASA)Physical Status Classification and white blood cell count.In the 13 models constructed,the reported area under the curve(AUC)of subjects'job characteristics ranged from 0.667 to 0.996.Five out of seven studies had good overall applicability,but all with high risk of bias.Conclusion The predictive models for lung infections in elderly patients with hip fracture are still in the stage of development.Although the predictive models show some predictive performance,however they are still deficient,and all studies have been found with a high risk in bias.

Objective To explore the traditional Chinese medicine(TCM)syndrome character-istics and medication patterns of cerebral small vessel disease(CSVD)using data mining techniques.Methods Clinical research literature on TCM treatment of CSVD,published from the establishment of the database to September 1,2024,was retrieved from the China National Knowledge Infrastructure(CNKI),Wanfang,and VIP databases.Analyses were conducted on syndromes,drug frequencies,properties,flavors,and meridian tropisms.Data mining was performed using R4.4.1 software to ex-plore associations,correlations,and clustering of TCM herbs,aiming to elucidate medication patterns in CSVD treatment.Results A total of 60 prescription formulas for treating CSVD were screened,involving 142 TCM herbs with a total usage frequency of 1,312 times.The top five most frequently used herbs were Chuanxiong,Danggui,Dilong,Huangqi,and Chishao.Herb properties were pre-dominantly warm and cold;flavors were mainly pungent,bitter,and sweet;and meridian tropisms were primarily to the liver,spleen,and heart meridians.Twenty-nine strong association rules were identified,and association analysis revealed core herbal combinations centered around Chuanxiong,Chishao,and Danggui.Clustering analysis yielded five herbal combinations.Conclusion CSVD is characterized by a deficiency in essence and excess in superficiality.Treatment should focus on tonify-ing deficiencies and eliminating excesses,combining both tonification and purgation methods.Medication patterns predominantly involve herbs for promoting blood circulation and removing blood stasis,often combined with herbs for nourishing the kidney and marrow,calming the liver and suppressing wind,and awakening the mind and opening the orifices.