Objective: This study aimed to compare outcomes and adverse events of patients with locally advanced cervical cancer (LACC) undergoing concurrent chemoradiotherapy (CCRT) with cisplatin single-agent chemotherapy vs. CCRT with cisplatin combined with paclitaxel dualagent therapy. The primary outcomes are overall survival (OS), progression-free survival (PFS), local recurrence (LR), distant metastasis (DM) and the occurrence of adverse events. Methods: This retrospective cohort study included patients with FIGO 2009 stage IB1-IVA cervical squamous cell carcinoma undergoing radical CCRT. Patients were divided into groups A and B, treatment outcomes were compared between the two groups after 1:1 proportional propensity score matching. Results: Medical records of 1,203 patients were reviewed and 572 patients were finally included for propensity score matching. After propensity score matching, 121 pairs of patients were selected for analysis. The OS, PFS, LR and DM rates were 78.5% and 83.5% (p=0.417), 73.3% and 78.5% (p=0.312), 6.6% and 2.5% (p=0.123), 19% and 15.7% (p=0.497) for groups A and B, respectively. Further subgroup analysis according to stage and lymph node metastatic status showed no difference in survival between the two groups. The incidence of grade 3–4 acute haematological toxicities was different between the two groups (p<0.05). Conclusion Cisplatin combined with paclitaxel CCRT couldn’t improve the survival rates of patients with LACC. However, the hematological toxicity of combination chemotherapy is more severe but controllable. Cisplatin single-agent therapy remains the first choice for CCRT. Further prospective studies are indicated to provide evidence for the efficacy of cisplatin plus paclitaxel in dual-agent concurrent therapy.

Objective: This study aimed to compare outcomes and adverse events of patients with locally advanced cervical cancer (LACC) undergoing concurrent chemoradiotherapy (CCRT) with cisplatin single-agent chemotherapy vs. CCRT with cisplatin combined with paclitaxel dualagent therapy. The primary outcomes are overall survival (OS), progression-free survival (PFS), local recurrence (LR), distant metastasis (DM) and the occurrence of adverse events. Methods: This retrospective cohort study included patients with FIGO 2009 stage IB1-IVA cervical squamous cell carcinoma undergoing radical CCRT. Patients were divided into groups A and B, treatment outcomes were compared between the two groups after 1:1 proportional propensity score matching. Results: Medical records of 1,203 patients were reviewed and 572 patients were finally included for propensity score matching. After propensity score matching, 121 pairs of patients were selected for analysis. The OS, PFS, LR and DM rates were 78.5% and 83.5% (p=0.417), 73.3% and 78.5% (p=0.312), 6.6% and 2.5% (p=0.123), 19% and 15.7% (p=0.497) for groups A and B, respectively. Further subgroup analysis according to stage and lymph node metastatic status showed no difference in survival between the two groups. The incidence of grade 3–4 acute haematological toxicities was different between the two groups (p<0.05). Conclusion Cisplatin combined with paclitaxel CCRT couldn’t improve the survival rates of patients with LACC. However, the hematological toxicity of combination chemotherapy is more severe but controllable. Cisplatin single-agent therapy remains the first choice for CCRT. Further prospective studies are indicated to provide evidence for the efficacy of cisplatin plus paclitaxel in dual-agent concurrent therapy.

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

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

Direct electrical stimulation of the human cortex can produce subjective visual sensations, yet these sensations are unstable. The underlying mechanisms may stem from differences in electrophysiological activity within the distributed network outside the stimulated site. To address this problem, we recruited 69 patients who experienced visual sensations during invasive electrical stimulation while intracranial electroencephalography (iEEG) data were recorded. We found significantly flattened power spectral slopes in distributed regions involving different brain networks and decreased integrated information during elicited visual sensations compared with the non-sensation condition. Further analysis based on minimum information partitions revealed that the reconfigured network interactions primarily involved the inferior frontal cortex, posterior superior temporal sulcus, and temporoparietal junction. The flattened power spectral slope in the inferior frontal gyrus was also correlated with integrated information. Taken together, this study indicates that the altered electrophysiological signatures provide insights into the neural mechanisms underlying subjective visual sensations.
Humans ; Male ; Female ; Adult ; Visual Perception/physiology* ; Electric Stimulation ; Middle Aged ; Young Adult ; Electrocorticography ; Electroencephalography ; Brain Mapping

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Sini Decoction (SNT) is a traditional formula recognized for its efficacy in warming the spleen and stomach and dispersing cold. However, elucidating the mechanism of action of SNT remains challenging due to its complex multiple components. This study utilized a synergistic approach combining two-dimensional fluorescence difference in gel electrophoresis (2D-DIGE)-based drug affinity responsive target stability (DARTS) with label-free quantitative proteomics techniques to identify the direct and indirect protein targets of SNT in myocardial infarction. The analysis identified 590 proteins, with 30 proteins showing significant upregulation and 51 proteins showing downregulation when comparing the SNT group with the model group. Through the integration of 2D-DIGE DARTS with proteomics data and pharmacological assessments, the findings indicate that protein disulfide-isomerase A3 (PDIA3) may serve as a potential protein target through which SNT provides protective effects on myocardial cells during myocardial infarction.
Myocardial Infarction/genetics* ; Proteomics/methods* ; Drugs, Chinese Herbal/chemistry* ; Animals ; Protein Disulfide-Isomerases/genetics* ; Male ; Two-Dimensional Difference Gel Electrophoresis/methods* ; Humans ; Rats ; Rats, Sprague-Dawley ; Electrophoresis, Gel, Two-Dimensional

BACKGROUND: Diabetic foot is a complex condition with high incidence, recurrence, mortality, and disability rates. Current treatments for diabetic foot ulcers are often insufficient. This study was conducted to identify potential therapeutic targets for diabetic foot. METHODS: Datasets related to diabetic foot and diabetic skin were retrieved from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using R software. Enrichment analysis was conducted to screen for critical gene functions and pathways. A protein interaction network was constructed to identify node genes corresponding to key proteins. The DEGs and node genes were overlapped to pinpoint target genes. Plasma and chronic ulcer samples from diabetic and non-diabetic individuals were collected. Western blotting, immunohistochemistry, and enzyme-linked immunosorbent assays were performed to verify the S100 calcium binding protein A9 (S100A9), inflammatory cytokine, and related pathway protein levels. Hematoxylin and eosin staining was used to measure epidermal layer thickness. RESULTS: In total, 283 common DEGs and 42 node genes in diabetic foot ulcers were identified. Forty-three genes were differentially expressed in the skin of diabetic and non-diabetic individuals. The overlapping of the most significant DEGs and node genes led to the identification of S100A9 as a target gene. The S100A9 level was significantly higher in diabetic than in non-diabetic plasma (178.40 ± 44.65 ng/mL vs. 40.84 ± 18.86 ng/mL) and in chronic ulcers, and the wound healing time correlated positively with the plasma S100A9 level. The levels of inflammatory cytokines (tumor necrosis factor-α, interleukin [IL]-1, and IL-6) and related pathway proteins (phospho-extracellular signal regulated kinase [ERK], phospho-p38, phospho-p65, and p-protein kinase B [Akt]) were also elevated. The epidermal layer was notably thinner in chronic diabetic ulcers than in non-diabetic skin (24.17 ± 25.60 μm vs. 412.00 ± 181.60 μm). CONCLUSIONS S100A9 was significantly upregulated in diabetic foot and was associated with prolonged wound healing. S100A9 may impair diabetic wound healing by disrupting local inflammatory responses and skin re-epithelialization.
Calgranulin B/therapeutic use* ; Diabetic Foot/metabolism* ; Humans ; Datasets as Topic ; Computational Biology ; Mice, Inbred C57BL ; Animals ; Mice ; Protein Interaction Maps ; Immunohistochemistry