Based on the theory of "sweet-flavored medicinals retaining and restoring body fluid"， this paper proposed that the core pathogenesis of hypercoagulable state in malignant tumors is qi deficiency and fluid consumption， blood stasis and vessels stagnation， which evolves dynamically according to the pattern "qi deficiency → fluid consumption → blood stasis". Accordingly， a staged treatment system is established with the general principle of "fortifying the middle jiao， restoring fluid and activating blood circulation". In the initial stage， invigorating the spleen and boosting qi to generate body fluid， targeting the onset of middle jiao deficiency and body fluid consumption； in the middle stage， nourishing yin and unblocking collaterals to facilitate body fluid circulation， addressing the disorder of body fluid transportation and collateral injury caused by internal dryness； in the late stage， consolidating yin and resolving blood stasis to retain body fluid， resolving yin impairment， fluid exhaustion， and binding of stasis and toxin. By regulating body fluid metabolism to improve the hypercoagulable state， this system is intended to provide insights for the prevention and treatment of hypercoagulable state in malignant tumors with traditional Chinese medicine.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

The rich club, as a community of highly interconnected nodes, serves as the topological center of the network. However, the similarities and differences in how the rich club supports functional integration and segregation in the brain across different species remain unknown. In this study, we first detected and validated the rich club in the structural networks of mouse, monkey, and human brains using neuronal tracing or diffusion magnetic resonance imaging data. Further, we assessed the role of rich clubs in functional integration, segregation, and balance using quantitative metrics. Our results indicate that the presence of a rich club facilitates whole-brain functional integration in all three species, with the functional networks of higher species exhibiting greater integration. These findings are expected to help to understand the relationship between brain structure and function from the perspective of brain evolution.
Animals ; Humans ; Brain/diagnostic imaging* ; Mice ; Male ; Nerve Net/diagnostic imaging* ; Macaca ; Female ; Neural Pathways/diagnostic imaging* ; Magnetic Resonance Imaging ; Biological Evolution ; Adult ; Diffusion Magnetic Resonance Imaging ; Brain Mapping ; Species Specificity ; Mice, Inbred C57BL

Bone organoids can simulate the complex structure and function of the bone tissues, which makes them a frontier technology in organoid researches. Bone organoids show a tremendous potential of applications in bone disease modeling, bone injury repair, and medicine screening. Although advancements have been made so far in constructing bone organoids with functional structures like mineralization, bone marrow, trabecular bone, callus, woven bone, etc, the researches in this field are confronted with numerous challenges such as lack of standardized construction strategies and unified evaluation criteria, which limits their further promotion and application. To standardize researches in bone organoids, the Orthopedic Expert Committee of Geriatric Branch of Chinese Association of Gerontology and Geriatrics, the Youth Osteoporosis Group of Orthopedic Branch of Chinese Medical Association, the Osteoporosis Group of Orthopedic Surgeon Branch of Chinese Medical Doctor Association, and the Osteoporosis Committee of Shanghai Association of Integrated Traditional Chinese and Western Medicine organized related experts to formulate Expert consensus on the construction, evaluation, and application of bone organoids ( version 2024) based on an evidence-based approach. A total of 17 recommendations were put forth, aiming to standardize researches and clinical applications of bone organoids and enhance their value in scientific research and clinical practice.

OBJECTIVE: To investigate the consistency and diagnostic performance of magnetic resonance imaging (MRI) for detecting microvascular invasion (MVI) of hepatocellular carcinoma (HCC) and the validity of deep learning attention mechanisms and clinical features for MVI grade prediction. METHODS: This retrospective study was conducted among 158 patients with HCC treated in Shunde Hospital Affiliated to Southern Medical University between January, 2017 and February, 2020. The imaging data and clinical data of the patients were collected to establish single sequence deep learning models and fusion models based on the EfficientNetB0 and attention modules. The imaging data included conventional MRI sequences (T₁WI, T₂WI, and DWI), enhanced MRI sequences (AP, PP, EP, and HBP) and synthesized MRI sequences (T1mapping-pre and T1mapping-20 min), and the high-risk areas of MVI were visualized using deep learning visualization techniques. RESULTS: The fusion model based on T1mapping-20min sequence and clinical features outperformed other fusion models with an accuracy of 0.8376, a sensitivity of 0.8378, a specificity of 0.8702, and an AUC of 0.8501 for detecting MVI. The deep fusion models were also capable of displaying the high-risk areas of MVI. CONCLUSION The fusion models based on multiple MRI sequences can effectively detect MVI in patients with HCC, demonstrating the validity of deep learning algorithm that combines attention mechanism and clinical features for MVI grade prediction.
Humans ; Carcinoma, Hepatocellular ; Retrospective Studies ; Liver Neoplasms ; Magnetic Resonance Imaging ; Algorithms

Type 2 diabetes (T2D) is characterized by the malfunction of pancreatic β cells. Susceptibility and pathogenesis of T2D can be affected by multiple factors, including sex differences. However, the mechanisms underlying sex differences in T2D susceptibility and pathogenesis remain unclear. Using single-cell RNA sequencing (scRNA-seq), we demonstrate the presence of sexually dimorphic transcriptomes in mouse β cells. Using a high-fat diet-induced T2D mouse model, we identified sex-dependent T2D altered genes, suggesting sex-based differences in the pathological mechanisms of T2D. Furthermore, based on islet transplantation experiments, we found that compared to mice with sex-matched islet transplants, sex-mismatched islet transplants in healthy mice showed down-regulation of genes involved in the longevity regulating pathway of β cells. Moreover, the diabetic mice with sex-mismatched islet transplants showed impaired glucose tolerance. These data suggest sexual dimorphism in T2D pathogenicity, indicating that sex should be considered when treating T2D. We hope that our findings could provide new insights for the development of precision medicine in T2D.

Biomarkers ; Brain/diagnostic imaging* ; Brain Diseases/diagnostic imaging* ; Humans ; Machine Learning ; Magnetic Resonance Imaging ; Neuroimaging

Objective To explore the Reading man flap for the treatment of soft tissue defects in distal fin-gers. Methods From May, 2014 to June, 2017, Reading man flaps were transferred in the emergency room to repair soft tissue defects in distal fingers in 46 patients. There were 28 cases of finger pulp defects, 6 cases of dorsal defects and 12 cases of finger stump defects with the size of soft tissue defects ranged from 1.0 cm×0.9 cm to 2.2 cm×2.0 cm (average, 1.2 cm×1.3 cm).The volar, dorsal and hybrid flaps were 28, 6 and 12 cases respectively.The average size of the major flap and minor flap were 1.8 cm×1.2 cm and 1.4 cm×0.8 cm, respectively. All donor sites were sutured di-rectly.All patients were followed-up by review in the outpatient department. Results The consumed operative time was 35-48 min, with an average of 37.8 min. Prophylactic antibiotics and wound dressing were conducted postopera-tively. The tip of the minor flaps occurred inflammation and small blister in 2 cases and eased by removal of the tip sutures.Traumatic neuralgia occurred in 1 case and self-healed after 3 months.Twenty-six cases were followed-up at least 11 months, which were 16 cases of finger pulp defects, 3 of dorsal defects and 7 of finger stump defects. On an average of 10.5 (9-27) months followed-up, all flaps survived. Except 4 cases with slim hook nail deformity, the re-maining flaps were observed with satisfactory texture and appearance, the bulky deformity and scar contracture did not occur.Two points distinguishment on the major and minor flaps were 3.3-6.2 (average, 4.5)mm and 5.5-9.8(average, 7.1)mm respectively. According to the Trial Standard for Evaluation of Upper Limb Function of Chinese Society of Hand Surgery, it was excellent in 28 cases, good in 11 cases and moderate in 7 cases, with the overall excellent and good rate of 84.8%. Conclusion The Reading man flap is a good option for treatment of the small size soft tissu de-fect in distal fingers with the advantages of simple procedure, high success rate, good appearance and sensory recovery.

Objective·To analyze high-risk factors of infection of multidrug resistance Klebsiellapneumonia (MDR-Kpn) and difference of therapeutic effects for different treatments.Methods·One hundred and ten MDR-Kpn strains were collected from a hospital.K-B slip diffusion method was utilized to detect the drug susceptibility of all the strains.Based on electronic medical records system,MDR-Kpn infected group included 51 patients and control group was picked out,including 51 patients as well (byl:1 ratio basing on the infected group according to the rules of under the same department,similar basic disease and all the patients in the control group isolated with the strain of Kpn).Thirty-nine clinical information of MDR-Kpn infected and control groups are collected to make single-factor analysis of high risk factors of the infection with MDR-Kpn.Multi-factor analysis was utilized between MDR-Kpn infected and control groups.The lasting time of different antibiotics used in MDR-Kpn infected patients were made statistics between effective and inefficacy patients.Results·Drug susceptibility test showed that sulfonamide,phosphonomycin and amikacin,were the three most sensitive antibiotics for 110 MDR-Kpn strains.12 clinical information,such as blood transfusion、sputum suction、invasive ventilation were all high-risk factors for the infection of MDR-Kpn (P＜0.05).The lasting time during with carbapenems (P=0.025) was statistically different between effective (n=28)and non-effective group (n=23) of MDR-Kpn infection patients.Conclusion·Controlling and eliminating high-risk factors do help to protect and decrease the infection of MDR-Kpn.Using carbapenems correctly has great influence on prognosis.

Objective To investigate the antimicrobial resistance of clinical isolates from Renji Hospital,Shanghai Jiao Tong University School of Medicine during the period from 2005 to 2015.Methods Antimicrobial susceptibility testing was carried out according to Kirby-Bauer method.Results were analyzed according to CLSI 2015 breakpoints.Results A total of 55 155 nonduplicate clinical isolates were collected from 2005 to 2015.The top 5 most frequently isolated bacterial species were E.coli (15.0％),P.aeruginosa (14.0％),A.baumannii (11.9％),K.pneumoniae (11.8％) and S.aureus (10.2％).Gram positive cocci and gram negative organisms accounted for 35.8％ and 64.2％,respectively.The prevalence of methicillin-resistant strains in S.aureus (MRSA) and coagulase negative Staphylococcus (MRCNS) was 70.2％ (3 967/5 650) and 83.2％ (4 997/6 004).No staphylococcal strain was resistant to vancomycin,teicoplanin or linezolid.Fifteen strains of Enterococcus were found resistant to vancomycin.The average prevalence of ESBLs-producing strains was 70.4％ (5 843/8 300) in E.coli,53.5％ (3 500/6 539) in Klebsiella spp.and 44.1％ (557/1 263) in P mirabilis.A few carbapenemaseproducing K.pneumoniae strains were identified for the first time in 2012 with the prevalence of 0.6％ (4/656),and the prevalence hit high (30.1％,142/472) in 2015.The prevalence of carbapenemase-producing E.coli was 2.0％ (16/787) in 2015,and almost zero in the other years.The prevalence of extensively drug-resistant A.baumannii and P.aeruginosa was 39.1％ (2 566/6 556) and 4.0％ (308/7 704),respectively.Extensively drug-resistant strain was identified in 9 of the strains of 189 E.aerogenes isolates.Conclusions Bacterial resistance is still on the rise,which poses a major challenge to clinical antimicrobial therapy,especially the multi-drug resistant and extensively drug resistant bacteria.