MRI-based radiomic models for the preoperative prediction of extramural venous invasion in rectal cancer: A systematic review and meta-analysis.

AIM: To estimate the diagnostic value of magnetic resonance imaging (MRI)-based radiomic models in detecting the extramural venous invasion (EMVI) of rectal cancer. MATERIALS AND METHODS: Appropriate studies in multiple electronic databases were systematically retrieved. The Quality Assessment of Diagnostic Accuracy Studies 2 and Radiomics Quality Score (RQS) were used to evaluate the eligible studies' methodology quality. Summary accuracy metrics were calculated, and the publication bias was detected using Deek's funnel plot. The sensitivity and meta-regression analysis were performed to investigate the causes of heterogeneity. RESULTS: For the seven eligible studies, which included 1175 patients, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.80 (95 % CI, 0.70-0.88), 0.89 (95 % CI, 0.84-0.92), 7.0 (95 % CI, 4.7, 10.4), 0.22 (95 % CI, 0.14, 0.34), and 32 (95 % CI, 16, 65), respectively. The area under the receiver operating characteristic curve (AUC) was 0.91 (95 % CI, 0.88, 0.93). Moderate heterogeneity was found due to I2 values of 38.63 % and 32.29 % in sensitivity and specificity, respectively. Meta-regression analysis suggested that the patient enrollment, number of patients, segmentation method, and RQS score were the source of the heterogeneity. The head-to-head analysis suggested that radiomics model had a higher sensitivity for detection of EMVI than subjective evaluation by radiologist (0.47 vs. 0.73, p ≤ 0.001). CONCLUSION: Our study suggests that MRI-based radiomic models have good diagnostic value in detecting EMVI for rectal cancer patients. Nevertheless, more prospective and high-quality studies with larger sample sizes are needed in the future to validate these results.

Serum Homer1 is a Novel Biomarker for Predicting the Clinical Outcomes of Acute Ischemic Stroke Patients.

Purpose: We aim to explore the relationship between Homer1 and the outcomes of AIS patients at 3 months. Patients and Methods: This prospective cohort study was conducted from May 2022 to March 2023. In this study, we investigated the association between serum Homer1 levels by enzyme-linked immunosorbent assay at admission and functional outcomes of patients at 3 months after AIS. Results: Overall, 89 AIS patients (48 good outcomes and 41 poor outcomes) and 83 healthy controls were included. The median serum Homer1 level of patients at admission with poor outcomes was significantly higher than that of patients with good outcomes (39.33 vs 33.15, P<0.001). Serum Homer1 levels at admission were positively correlated with the severity of AIS (r = 0.488, P<0.001). The optimal cutoff of serum Homer1 level as an indicator for an auxiliary diagnosis of 3 months functional outcomes was 35.07 pg/mL, with a sensitivity of 75.0% and a specificity of 92.7% (AUC 0.837; 95% CI [0.744-0.907]; P<0 0.001). The odds ratio of MRS > 2 predicted by the level of serum Homer1 after 3 months was 1.665 (1.306-2.122; P<0.001). Conclusion: Serum concentrations of Homer1 have a high predictive value for neurobehavioral outcomes after acute ischemic stroke. Higher serum Homer1 levels (>35.07 pg/mL) were positively associated with poor functional outcomes of patients 3 months post-stroke.

Actomyosin-II protects axons from degeneration induced by mild mechanical stress.

Whether, to what extent, and how the axons in the central nervous system (CNS) can withstand sudden mechanical impacts remain unclear. By using a microfluidic device to apply controlled transverse mechanical stress to axons, we determined the stress levels that most axons can withstand and explored their instant responses at nanoscale resolution. We found mild stress triggers a highly reversible, rapid axon beading response, driven by actomyosin-II-dependent dynamic diameter modulations. This mechanism contributes to hindering the long-range spread of stress-induced Ca2+ elevations into non-stressed neuronal regions. Through pharmacological and molecular manipulations in vitro, we found that actomyosin-II inactivation diminishes the reversible beading process, fostering progressive Ca2+ spreading and thereby increasing acute axonal degeneration in stressed axons. Conversely, upregulating actomyosin-II activity prevents the progression of initial injury, protecting stressed axons from acute degeneration both in vitro and in vivo. Our study unveils the periodic actomyosin-II in axon shafts cortex as a novel protective mechanism, shielding neurons from detrimental effects caused by mechanical stress.

Machine learning reveals neutrophil-to-lymphocyte ratio as a crucial prognostic indicator in severe Japanese encephalitis patients.

Japanese encephalitis (JE) is a severe infectious disease affecting the central nervous system (CNS). However, limited risk factors have been identified for predicting poor prognosis (PP) in adults with severe JE. In this study, we analyzed clinical data from thirty-eight severe adult JE patients and compared them to thirty-three patients without organic CNS disease. Machine learning techniques employing branch-and-bound algorithms were used to identify clinical risk factors. Based on clinical outcomes, patients were categorized into two groups: the PP group (mRs ≥ 3) and the good prognosis (GP) group (mRs ≤ 2) at three months post-discharge. We found that the neutrophil-to-lymphocyte ratio (NLR) and the percentage of neutrophilic count (N%) were significantly higher in the PP group compared to the GP group. Conversely, the percentage of lymphocyte count (L%) was significantly lower in the PP group. Additionally, elevated levels of aspartate aminotransferase (AST) and blood glucose were observed in the PP group compared to the GP group. The clinical parameters most strongly correlated with prognosis, as indicated by Pearson correlation coefficient (PCC), were NLR (PCC 0.45) and blood glucose (PCC 0.45). In summary, our findings indicate that increased serum NLR, N%, decreased L%, abnormal glucose metabolism, and liver function impairment are risk factors associated with poor prognosis in severe adult JE patients.