OBJECTIVE: To explore clinical characteristics, lesion sites and correlation differences of different types of diabetic foot gangrene, and to provide evidence-based basis for clinical classification of diabetic foot gangrene. METHODS: A retrospective analysis was conducted on 266 patients with newly diagnosed diabetic foot gangrene who were admitted from January 2018 to December 2018, including 183 males and 83 females, aged from 35 to 92 years old with an average of (69.55±10.84) years old, and they were divided into wet gangrene group and dry gangrene group according to the different natures of gangrene. There were 139 patients in wet gangrene group, including 98 males and 41 females, aged from 35 to 90 years old with an average of (68.95±10.93) years old. There were 127 patients in dry gangrene group, including 85 males and 42 females, aged from 38 to 92 years old with an average of (70.21±10.75) years old. Body mass index (BMI), waist-to-hip ratio (WHR), body temperature, skin temperature difference between the affected and healthy sides of the lower extremities, and Wagner grade between two groups were recorded to evaluate symptoms and signs. The white blood cell count (WBC), neutrophil percentage (NEUT%), and C-reactive protein (C-reactive protein), erythrocyte sedimentation rate (ESR), procalcitonin (PCT), and interleukin-6 (IL-6) in peripheral blood between two groups were detected and compared to evaluate the infection status;the severity of diabetic peripheral neuropathy (DPN) was evaluated by using Toronto Clinical Scoring System (TCSS);the degree of pain in patients with diabetic foot gangrene was evaluated by numerical rating scale (NRS); ankle-brachial index (ABI) and popliteal artery blood flow velocity were used to evaluate the degree of arterial lesions. Spearman correlation analysis was used to analyze the correlations between gangrene TCSS, ABI and age, BMI, WHR, body temperature, calf skin temperature difference, WBC, NEUT%, CRP, ESR, PCT, IL-6, NRS, and Wagner classification indicators. RESULTS: The body temperature, skin temperature difference between the affected and healthy sides of the lower extremities, Wagner grade, WBC, NEUT%, CRP, ESR, PCT, IL-6, TCSS score, ABI, and popliteal artery blood flow velocity in wet gangrene group were higher than those in dry gangrene group (P<0.01), and BMI, WHR, and NRS score in dry gangrene group were higher than those in wet gangrene group;the differences were all statistically significant (P<0.01). The results of Spearman correlation analysis showed TCSS score of gangrene patients was correlated with body temperature (r=0.214), calf skin temperature difference (r=0.364), WBC (r=0.240), NEUT% (r=0.291), CRP (r=0.347), ESR (r=0.167), PCT (r=0.241), IL-6 (r=0.316), and popliteal fossa arterial blood flow velocity (r=0.261) and Wagner grade (r=0.273) were positively correlated, and the differences were statistically significant (P<0.01). ABI was negatively correlated with age (r=-0.183), BMI (r=-0.252), WHR (r=-0.288), and NRS score (r=-0.354), and the differences were statistically significant (P<0.01). CONCLUSION Diabetic foot gangrene is an extremely difficult and critical disease. Wet gangrene has a significant synergic effect with infection and neuropathy, while dry gangrene is closely related to vascular occlusion. The main contradiction of gangrene could be revealed through blood vessels, nerves and infection, providing evidence-based basis for the selection of debridement timing, anti-infection strategies and revascularization, with the aim of reducing the risk of amputation.
Humans ; Male ; Female ; Aged ; Middle Aged ; Diabetic Foot/diagnosis* ; Aged, 80 and over ; Adult ; Retrospective Studies ; Gangrene/physiopathology* ; C-Reactive Protein

Isolated male epispadias typically presents with preputial defects and dorsal urethral dehiscence. A less common subtype, known as concealed epispadias, is distinguished by an intact prepuce. Despite its clinical relevance, there is limited literature on this variant. In this study, we retrospectively analyzed the clinical data of 86 pediatric patients with isolated male epispadias treated in Beijing Children's Hospital (Beijing, China) from May 2004 to July 2023, including 19 cases of concealed epispadias and 67 of nonconcealed epispadias. We compared clinical characteristics, preoperative diagnostics, surgical techniques, postoperative outcomes, and sexual function during follow-up between the concealed and nonconcealed groups. No significant differences were observed between the two groups regarding surgical methods, postoperative complications, or rates of urinary incontinence. However, notable distinctions were found in the age at initial diagnosis, timing of surgery, frequency of incontinence, location of the urethral meatus, and postoperative urinary incontinence scores (all P < 0.05). Given the absence of penopubic epispadias in concealed cases, we categorized glans and penile epispadias within nonconcealed epispadias as distal epispadias ( n = 40) and subsequently compared them with concealed epispadias cases. The postoperative urinary incontinence scores did not differ significantly between the concealed and distal epispadias groups. These findings suggest that concealed epispadias represents a relatively milder form of the condition, characterized by the absence of penopubic involvement, lower rates of urinary incontinence, and favorable surgical outcomes. However, the intact prepuce in concealed cases underscores the need for careful identification and early diagnosis.
Humans ; Male ; Retrospective Studies ; Epispadias/classification* ; China ; Tertiary Care Centers ; Child, Preschool ; Child ; Postoperative Complications/epidemiology* ; Urinary Incontinence/epidemiology* ; Urethra/surgery* ; Infant ; Penis/surgery* ; Adolescent ; Urologic Surgical Procedures, Male/methods* ; East Asian People

Atherosclerosis, a chronic inflammatory disease, is markedly influenced by both immune and inflammatory reactions throughout its progression. Dendritic cells, as pivotal antigen-presenting entities, play a crucial role in the initiation of immune responses and the preservation of immunological homeostasis. Accumulating data indicates that dendritic cells are present in healthy arteries and accumulate significantly in atherosclerotic plaques. Novel immunotherapeutic approaches and vaccination protocols have yielded substantial clinical advancements in managing chronic inflammatory diseases, with dendritic cell-centric modalities emerging for atherosclerotic management. In this review, we delineate the essential functions and underlying mechanisms of dendritic cells and their subsets in the modulation of atherosclerotic inflammation and immune responses. We underscore the immense promise of dendritic cell-based immunotherapeutic strategies, including vaccines and innovative combinations with nanotechnological drug delivery platforms for atherosclerosis treatment. We also discuss the challenges associated with dendritic cell immunotherapy and provide perspectives on the future direction of this field.

Accurate prediction of drug responses in cancer cell lines (CCLs) and transferable prediction of clinical drug responses using CCLs are two major tasks in personalized medicine. Despite the rapid advancements in existing computational methods for preclinical and clinical cancer drug response (CDR) prediction, challenges remain regarding the generalization of new drugs that are unseen in the training set. Herein, we propose a multimodal fusion deep learning (DL) model called drug-target and single-cell language based CDR (DTLCDR) to predict preclinical and clinical CDRs. The model integrates chemical descriptors, molecular graph representations, predicted protein target profiles of drugs, and cell line expression profiles with general knowledge from single cells. Among these features, a well-trained drug-target interaction (DTI) prediction model is used to generate target profiles of drugs, and a pretrained single-cell language model is integrated to provide general genomic knowledge. Comparison experiments on the cell line drug sensitivity dataset demonstrated that DTLCDR exhibited improved generalizability and robustness in predicting unseen drugs compared with previous state-of-the-art baseline methods. Further ablation studies verified the effectiveness of each component of our model, highlighting the significant contribution of target information to generalizability. Subsequently, the ability of DTLCDR to predict novel molecules was validated through in vitro cell experiments, demonstrating its potential for real-world applications. Moreover, DTLCDR was transferred to the clinical datasets, demonstrating satisfactory performance in the clinical data, regardless of whether the drugs were included in the cell line dataset. Overall, our results suggest that the DTLCDR is a promising tool for personalized drug discovery.

OBJECTIVE: Huachansu injection (HCSI), a promising anti-cancer Chinese medicine injection, has been reported to have the potential for reducing the toxicity of chemotherapy and improving the quality of life for colorectal cancer (CRC) patients. The objective of this study is to explore the synergistic and detoxifying effects of HCSI when used in combination with irinotecan (CPT-11). METHODS: To investigate the effect of HCSI on anti-CRC efficacy and intestinal toxicity of CPT-11, we measured changes in the biological behavior of LoVo cells in vitro, and anti-tumor effects in LoVo cell xenograft nude mice models in vivo. Meanwhile, the effect of HCSI on intestinal toxicity and the uridine diphosphate-glucuronosyltransferase 1A1 (UGT1A1) expression was investigated in the CPT-11-induced colitis mouse model. Subsequently, we measured the effect of HCSI and its 13 constituent bufadienolides on the expression of UGT1A1 and organic anion transporting polypeptides 1B3 (OATP1B3) in HepG2 cells. RESULTS: The combination index (CI) results showed that the combination of HCSI and CPT-11 exhibited a synergistic effect (CI < 1), which significantly suppressing the LoVo cell migration, enhancing G2/M and S phase arrest, and inhibiting tumor growth in vivo. Additionally, the damage to intestinal tissues was attenuated by HCSI in CPT-11-induced colitis model, while the increased expression of UGT1A1 in HepG2 cells and in mouse was observed. CONCLUSION The co-therapy with HCSI alleviated the intestinal toxicity induced by CPT-11 and exerted an enhanced anti-CRC effect. The detoxifying mechanism may be related to the increased expression of UGT1A1 and OATP1B3 by HCSI and its bufadienolides components. The findings of this study may serve as a theoretical insights and strategies to improve CRC patient outcomes. Please cite this article as: Jiang B, Meng ZY, Hu YJ, Chen JJ, Zong L, Xu LY, Zhang XQ, Zhang JX, Han YL. Huachansu injection enhances anti-colorectal cancer efficacy of irinotecan and alleviates its induced intestinal toxicity through upregulating UGT1A1-OATP1B3 expression in vitro and in vivo. J Integr Med. 2025; 23(5):576-590.
Irinotecan/therapeutic use* ; Animals ; Glucuronosyltransferase/genetics* ; Humans ; Colorectal Neoplasms/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Mice, Nude ; Mice ; Up-Regulation/drug effects* ; Male ; Xenograft Model Antitumor Assays ; Mice, Inbred BALB C ; Hep G2 Cells ; Cell Line, Tumor ; Intestines/drug effects* ; Amphibian Venoms

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

Objective Hydroquinone(HQ),one of the phenolic metabolites of benzene,is widely recognized as an important participant in benzene-induced hematotoxicity.However,there are few relevant proteomics in HQ-induced hematotoxicity and the mechanism hasn't been fully understood yet. Methods In this study,we treated K562 cells with 40 μmol/L HQ for 72 h,examined and validated protein expression changes by Label-free proteomic analysis and Parallel reaction monitoring(PRM),and performed bioinformatics analysis to identify interaction networks. Results One hundred and eighty-seven upregulated differentially expressed proteins(DEPs)and 279 downregulated DEPs were identified in HQ-exposed K562 cells,which were involved in neutrophil-mediated immunity,blood microparticle,and other GO terms,as well as the lysosome,metabolic,cell cycle,and cellular senescence-related pathways.Focusing on the 23 DEGs and 5 DEPs in erythroid differentiation-related pathways,we constructed the network of protein interactions and determined 6 DEPs(STAT1,STAT3,CASP3,KIT,STAT5B,and VEGFA)as main hub proteins with the most interactions,among which STATs made a central impact and may be potential biomarkers of HQ-induced hematotoxicity. Conclusion Our work reinforced the use of proteomics and bioinformatic approaches to advance knowledge on molecular mechanisms of HQ-induced hematotoxicity at the protein level and provide a valuable basis for further clarification.

Objective To investigate the disease spectrum and pathogenic genes of inherited metabolic disorder(IMD)among neonates in Gansu Province of China.Methods A retrospective analysis was conducted on the tandem mass spectrometry data of 286 682 neonates who received IMD screening in Gansu Provincial Maternal and Child Health Hospital from January 2018 to December 2021.A genetic analysis was conducted on the neonates with positive results in tandem mass spectrometry during primary screening and reexamination.Results A total of 23 types of IMD caused by 28 pathogenic genes were found in the 286 682 neonates,and the overall prevalence rate of IMD was 0.63‰(1/1 593),among which phenylketonuria showed the highest prevalence rate of 0.32‰(1/3 083),followed by methylmalonic acidemia(0.11‰,1/8 959)and tetrahydrobiopterin deficiency(0.06‰,1/15 927).In this study,166 variants were identified in the 28 pathogenic genes,with 13 novel variants found in 9 genes.According to American College of Medical Genetics and Genomics guidelines,5 novel variants were classified as pathogenic variants,7 were classified as likely pathogenic variants,and 1 was classified as the variant of uncertain significance.Conclusions This study enriches the database of pathogenic gene variants for IMD and provides basic data for establishing an accurate screening and diagnosis system for IMD in this region.

Lipopolysaccharides (LPS) are major outer membrane components of Gram-negative bacteria. Unlike most Gram-negative bacteria, Acinetobacter baumannii can still survive and acquire polymyxin resistance after complete loss of LPS. Previous studies of LPS-deficient Acinetobacter baumannii mostly focused on LPS-deficient strains induced by polymyxin, whose background was complex and unstable. To investigate LPS loss-mediated polymyxin resistant-Acinetobacter baumannii, this study constructed a stable and clear background LPS-deficient strain by knocking out lpxC gene in Acinetobacter baumannii ATCC 19606 with CIRSPR/Cas9, and then studied the phenotypic changes of the lpxC-deficient strain including morphology, growth rate, antibiotic susceptibility, virulence, membrane permeability, and membrane potential. Animal experiments were approved by the Animal Care and Welfare Committee Institute of Medicinal Biotechnology, CAMS and PUMC (approval number: IMB-20240119D₉). The results indicated that the lpxC gene of Acinetobacter baumannii ATCC 19606 was successfully knocked out. After losing the lpxC, the strain underwent the morphological change from rod-shaped to spherical. Furthermore, it leads to reduced growth rate, enhanced membrane permeability, decreased membrane potential, lower virulence, and increased antibiotic susceptibility to β-lactams, quinolones, aminoglycosides, macrolides, glycopeptides. The lpxC deletion results in significant changes in membrane homeostasis and adaptability of Acinetobacter baumannii. Understanding the phenotypic changes of colistin-resistant Acinetobacter baumannii mediated by LPS loss is useful for exploring the resistance mechanism of Acinetobacter baumannii and developing new therapeutic strategies.

People frequently struggle to juggle their work, family, and social life in today’s fast-paced environment, which can leave them exhausted and worn out. The development of technologies for detecting fatigue while driving is an important field of research since driving when fatigued poses concerns to road safety. In order to throw light on the most recent advancements in this field of research, this paper provides an extensive review of fatigue driving detection approaches based on electroencephalography (EEG) data. The process of fatigue driving detection based on EEG signals encompasses signal acquisition, preprocessing, feature extraction, and classification. Each step plays a crucial role in accurately identifying driver fatigue. In this review, we delve into the signal acquisition techniques, including the use of portable EEG devices worn on the scalp that capture brain signals in real-time. Preprocessing techniques, such as artifact removal, filtering, and segmentation, are explored to ensure that the extracted EEG signals are of high quality and suitable for subsequent analysis. A crucial stage in the fatigue driving detection process is feature extraction, which entails taking pertinent data out of the EEG signals and using it to distinguish between tired and non-fatigued states. We give a thorough rundown of several feature extraction techniques, such as topology features, frequency-domain analysis, and time-domain analysis. Techniques for frequency-domain analysis, such wavelet transform and power spectral density, allow the identification of particular frequency bands linked to weariness. Temporal patterns in the EEG signals are captured by time-domain features such autoregressive modeling and statistical moments. Furthermore, topological characteristics like brain area connection and synchronization provide light on how the brain’s functional network alters with weariness. Furthermore, the review includes an analysis of different classifiers used in fatigue driving detection, such as support vector machine (SVM), artificial neural network (ANN), and Bayesian classifier. We discuss the advantages and limitations of each classifier, along with their applications in EEG-based fatigue driving detection. Evaluation metrics and performance assessment are crucial aspects of any detection system. We discuss the commonly used evaluation criteria, including accuracy, sensitivity, specificity, and receiver operating characteristic (ROC) curves. Comparative analyses of existing models are conducted, highlighting their strengths and weaknesses. Additionally, we emphasize the need for a standardized data marking protocol and an increased number of test subjects to enhance the robustness and generalizability of fatigue driving detection models. The review also discusses the challenges and potential solutions in EEG-based fatigue driving detection. These challenges include variability in EEG signals across individuals, environmental factors, and the influence of different driving scenarios. To address these challenges, we propose solutions such as personalized models, multi-modal data fusion, and real-time implementation strategies. In conclusion, this comprehensive review provides an extensive overview of the current state of fatigue driving detection based on EEG signals. It covers various aspects, including signal acquisition, preprocessing, feature extraction, classification, performance evaluation, and challenges. The review aims to serve as a valuable resource for researchers, engineers, and practitioners in the field of driving safety, facilitating further advancements in fatigue detection technologies and ultimately enhancing road safety.