Microglial over-pruning of synapses during development in autism-associated SCN2A-deficient mice and human cerebral organoids.

Autism spectrum disorder (ASD) is a major neurodevelopmental disorder affecting 1 in 36 children in the United States. While neurons have been the focus of understanding ASD, an altered neuro-immune response in the brain may be closely associated with ASD, and a neuro-immune interaction could play a role in the disease progression. As the resident immune cells of the brain, microglia regulate brain development and homeostasis via core functions including phagocytosis of synapses. While ASD has been traditionally considered a polygenic disorder, recent large-scale human genetic studies have identified SCN2A deficiency as a leading monogenic cause of ASD and intellectual disability. We generated a Scn2a-deficient mouse model, which displays major behavioral and neuronal phenotypes. However, the role of microglia in this disease model is unknown. Here, we reported that Scn2a-deficient mice have impaired learning and memory, accompanied by reduced synaptic transmission and lower spine density in neurons of the hippocampus. Microglia in Scn2a-deficient mice are partially activated, exerting excessive phagocytic pruning of post-synapses related to the complement C3 cascades during selective developmental stages. The ablation of microglia using PLX3397 partially restores synaptic transmission and spine density. To extend our findings from rodents to human cells, we established a microglia-incorporated human cerebral organoid model carrying an SCN2A protein-truncating mutation identified in children with ASD. We found that human microglia display increased elimination of post-synapse in cerebral organoids carrying the SCN2A mutation. Our study establishes a key role of microglia in multi-species autism-associated models of SCN2A deficiency from mouse to human cells.

MicroRNA-431-5p inhibits angiogenesis, lymphangiogenesis, and lymph node metastasis by affecting TGF-ß1/SMAD2/3 signaling via ZEB1 in gastric cancer.

Accumulating evidence suggests that lymphangiogenesis plays a crucial role in lymphatic metastasis, leading to tumor immune tolerance. However, the specific mechanism remains unclear. In this study, miR-431-5p was markedly downregulated in both gastric cancer (GC) tissues and plasma exosomes, and its expression were correlated negatively with LN metastasis and poor prognosis. Mechanistically, miR-431-5p weakens the TGF-ß1/SMAD2/3 signaling pathway by targeting ZEB1, thereby suppressing the secretion of VEGF-A and ANG2, which in turn hinders angiogenesis, lymphangiogenesis, and lymph node (LN) metastasis in GC. Experiments using a popliteal LN metastasis model in BALB/c nude mice demonstrated that miR-431-5p significantly reduced popliteal LN metastasis. Additionally, miR-431-5p enhances the efficacy of anti-PD1 treatment, particularly when combined with galunisertib, anti-PD1 treatment showing a synergistic effect in inhibiting GC progression in C57BL/6 mice. Collectively, these findings suggest that miR-431-5p may modulate the TGF-ß1/SMAD2/3 pathways by targeting ZEB1 to impede GC progression, angiogenesis, and lymphangiogenesis, making it a promising therapeutic target for GC management.

Myosteatosis predicts postoperative complications and long-term survival in robotic gastrectomy for gastric cancer: A propensity score analysis.

BACKGROUND: Robotic gastrectomy is increasingly utilized for gastric cancer, but high morbidity remains a concern. Myosteatosis or low skeletal muscle density reflecting fatty infiltration, associates with complications after other cancer surgeries but has not been evaluated for robotic gastrectomy. METHODS: This retrospective study analysed 381 patients undergoing robotic gastrectomy for gastric cancer from September 2019 to October 2022. Myosteatosis was quantified on preoperative computed tomography (CT) images at lumbar 3 (L3). Propensity score matching addressed potential confounding between myosteatosis and non-myosteatosis groups. Outcomes were postoperative complications, 30 days mortality, 30 days readmissions and survival. RESULTS: Myosteatosis was present in 33.6% of patients. Myosteatosis associated with increased overall (47.7% vs. 26.5%, p < 0.001) and severe complications (12.4% vs. 4.9%, p < 0.001). After matching, myosteatosis remained associated with increased overall complications, major complications, intensive care unit (ICU) transfer and readmission (all p < 0.05). Myosteatosis independently predicted overall [odds ratio (OR) = 2.86, 95% confidence interval (CI): 1.57-5.20, p = 0.001] and severe complications (OR = 4.81, 95% CI: 1.51-15.27, p = 0.008). Myosteatosis also associated with reduced overall (85.0% vs. 93.2%, p = 0.015) and disease-free survival (80.3% vs. 88.4%, p=0.029). On multivariate analysis, myosteatosis independently predicted poorer survival [hazard ratio (HR) = 2.83, 95% CI: 1.32-6.08, p=0.012] and disease-free survival (HR = 1.83, 95% CI: 1.01-3.30, p=0.032). CONCLUSION: Preoperative CT-defined myosteatosis independently predicts increased postoperative complications and reduced long-term survival after robotic gastrectomy for gastric cancer. Assessing myosteatosis on staging CT could optimize preoperative risk stratification.

Prediction of occult peritoneal metastases or positive cytology using CT in gastric cancer.

OBJECTIVE: Accurate prediction of preoperative occult peritoneal metastasis (OPM) is critical to selecting appropriate therapeutic regimen for gastric cancer (GC). Considering the clinical practicability, we develop and validate a visible nomogram that integrates the CT images and clinicopathological parameters for the individual preoperative prediction of OPM in GC. METHODS: This retrospective study included 520 patients who underwent staged laparoscopic exploration or peritoneal lavage cytology (PLC) examination. Univariate and multivariate logistic regression results were used to screen model predictors and construct nomograms of OPM risk. The performance of the model was detected by using ROC, accuracy, and C-index. The bootstrap resampling method was considered internal validation of the model. The Delong test was used to evaluate the difference in AUC between the two models. RESULTS: Grade 2 mural stratification, tumor thickness, and the Lauren classification diffuse were significant predictors of OPM (p < 0.05). The nomogram of these three factors (compared with the original model) showed a higher predictive effect (p < 0.001). The area under the curve (AUC) of the model was 0.830 (95% CI 0.788-0.873), and the internally validated AUC of 1000 bootstrap samples was 0.826 (95% CI 0.756-0.870). The sensitivity, specificity, and accuracy were 76.0%, 78.8%, and 78.3%, respectively. CONCLUSIONS: CT phenotype-based nomogram demonstrates favorable discrimination and calibration, and it can be conveniently used for preoperative individual risk rating of OPM in GC. CLINICAL RELEVANCE STATEMENT: In this study, the preoperative OPM prediction model based on CT images (mural stratification, tumor thickness) combined with pathological parameters (the Lauren classification) showed excellent predictive ability in GC, and it is also suitable for clinicians to use rather than limited to professional radiologists. KEY POINTS: • Nomogram based on CT image analysis can effectively predict occult peritoneal metastasis in gastric cancer (training area under the curve (AUC) = 0.830 and bootstrap AUC = 0.826). • Nomogram model combined with CT features performed better than the original model (established using only clinicopathological parameters) in differentiating occult peritoneal metastasis of gastric cancer.

Inflammation and nutritional status indicators as prognostic indicators for patients with locally advanced gastrointestinal stromal tumors treated with neoadjuvant imatinib.

BACKGROUND: Previous studies have confirmed that preoperative nutritional-inflammatory indicators can predict prognosis in various malignancies. However, to the best of our knowledge, no study has investigated the assessment of systemic inflammatory immunity index (SII) combined with prognostic nutritional index (PNI) scores to predict prognosis after neoadjuvant treatment with imatinib in locally advanced gastrointestinal stromal tumours (LA-GIST). The aim of this study was to evaluate the predictive value of pretreatment SII-PNI scores in predicting recurrence after neoadjuvant therapy with imatinib in patients with LA-GIST. METHODS: We retrospectively analyzed 57 patients with LA-GIST who received imatinib neoadjuvant from January 2013 to March 2019. Patients were divided into recurrence and non-recurrence groups according to their follow-up status, and SII and PNI cut-offs were calculated by receiver operating characteristic. The SII-PNI score ranged from 0 to 2 and were categorized into the following: score of 2, high SII (≥ 544.6) and low PNI (≤ 47.2); score of 1, either high SII (≥ 544.6) or low PNI (≤ 47.2); score of 0, no high SII (≥ 544.6) nor low PNI (≤ 47.2). RESULTS: All patients received imatinib neoadjuvant therapy for a median treatment period of 8.5 months (ranging from 3.2 to 12.6 months), with 8 patients (14.04%) and 49 patients (85.96%) developing recurrence and non-recurrence, respectively. Patients with a high SII-PNI score had a significantly worse recurrence-free survival time than those with a low SII-PNI score (P = 0.022, 0.046), and had a poorer pathological response (P = 0.014). Multivariate analysis demonstrated that the SII-PNI score was an independent prognostic factor for prediction of recurrence-free survival (P = 0.002). CONCLUSION: The pre-treatment SII-PNI score can be used to predict the efficacy after neoadjuvant treatment with imatinib in patients with LA-GIST, which may be a promising predictor of recurrence-free survival time for patients.

Engineering a potent receptor superagonist or antagonist from a novel IL-6 family cytokine ligand.

Interleukin-6 (IL-6) family cytokines signal through multimeric receptor complexes, providing unique opportunities to create novel ligand-based therapeutics. The cardiotrophin-like cytokine factor 1 (CLCF1) ligand has been shown to play a role in cancer, osteoporosis, and atherosclerosis. Once bound to ciliary neurotrophic factor receptor (CNTFR), CLCF1 mediates interactions to coreceptors glycoprotein 130 (gp130) and leukemia inhibitory factor receptor (LIFR). By increasing CNTFR-mediated binding to these coreceptors we generated a receptor superagonist which surpassed the potency of natural CNTFR ligands in neuronal signaling. Through additional mutations, we generated a receptor antagonist with increased binding to CNTFR but lack of binding to the coreceptors that inhibited tumor progression in murine xenograft models of nonsmall cell lung cancer. These studies further validate the CLCF1-CNTFR signaling axis as a therapeutic target and highlight an approach of engineering cytokine activity through a small number of mutations.

Hyperexcitability and Pharmacological Responsiveness of Cortical Neurons Derived from Human iPSCs Carrying Epilepsy-Associated Sodium Channel Nav1.2-L1342P Genetic Variant.

With the wide adoption of genomic sequencing in children having seizures, an increasing number of SCN2A genetic variants have been revealed as genetic causes of epilepsy. Voltage-gated sodium channel Nav1.2, encoded by gene SCN2A, is predominantly expressed in the pyramidal excitatory neurons and supports action potential (AP) firing. One recurrent SCN2A genetic variant is L1342P, which was identified in multiple patients with epileptic encephalopathy and intractable seizures. However, the mechanism underlying L1342P-mediated seizures and the pharmacogenetics of this variant in human neurons remain unknown. To understand the core phenotypes of the L1342P variant in human neurons, we took advantage of a reference human-induced pluripotent stem cell (hiPSC) line from a male donor, in which L1342P was introduced by CRISPR/Cas9-mediated genome editing. Using patch-clamping and microelectrode array (MEA) recordings, we revealed that cortical neurons derived from hiPSCs carrying heterozygous L1342P variant have significantly increased intrinsic excitability, higher sodium current density, and enhanced bursting and synchronous network firing, suggesting hyperexcitability phenotypes. Interestingly, L1342P neuronal culture displayed a degree of resistance to the anticonvulsant medication phenytoin, which recapitulated aspects of clinical observation of patients carrying the L1342P variant. In contrast, phrixotoxin-3 (PTx3), a Nav1.2 isoform-specific blocker, can potently alleviate spontaneous and chemically-induced hyperexcitability of neurons carrying the L1342P variant. Our results reveal a possible pathogenic underpinning of Nav1.2-L1342P mediated epileptic seizures and demonstrate the utility of genome-edited hiPSCs as an in vitro platform to advance personalized phenotyping and drug discovery.SIGNIFICANCE STATEMENT A mounting number of SCN2A genetic variants have been identified from patients with epilepsy, but how SCN2A variants affect the function of human neurons contributing to seizures is still elusive. This study investigated the functional consequences of a recurring SCN2A variant (L1342P) using human iPSC-derived neurons and revealed both intrinsic and network hyperexcitability of neurons carrying a mutant Nav1.2 channel. Importantly, this study recapitulated elements of clinical observations of drug-resistant features of the L1342P variant, and provided a platform for in vitro drug testing. Our study sheds light on cellular mechanism of seizures resulting from a recurring Nav1.2 variant, and helps to advance personalized drug discovery to treat patients carrying pathogenic SCN2A variant.

Overexpression of NaV1.6 in the rostral ventrolateral medulla in rats mediates stress-induced hypertension via glutamate regulation.

BACKGROUND: The rostral ventrolateral medulla (RVLM) plays a key role in mediating the development of stress-induced hypertension (SIH). Furthermore, enhanced glutamate transport within glutamatergic neurons in the RVLM mediates pressor responses. Data from our previous studies suggest that the voltage-gated sodium channel NaV1.6 is overexpressed in neurons in the RVLM in SIH model rats and participates in the resulting elevation of blood pressure. However, previous studies have not investigated the relationship between NaV1.6 expression and glutamatergic neurons. METHODS: Here, we constructed an SIH rat model by knocking down NaV1.6 via microinjection of clustered regularly interspaced short palindromic repeats (CRISPR) guide RNA into the RVLM. Glutamate-related markers were quantified by Western blotting and immunofluorescence, and blood pressure was measured in the rats. RESULTS: Our findings showed that vesicular glutamate transporter 1 (VGluT1) protein expression in the RVLM was higher in SIH rats than in Control rats, and GAD67 protein expression in SIH rats was lower than that in Control rats. Therefore, the number of VGluT1-positive neurons increased, while the number of GAD67-labeled neurons decreased after stress. After knocking down NaV1.6 expression in the RVLM, VGluT1 expression and the number of VGluT1-positive neurons decreased relative to those in SIH rats, while GAD67 protein expression and the number of GAD67-labeled neurons increased relative to those in SIH rats. CONCLUSIONS: These results indicate that overexpression of NaV1.6 in the RVLM may mediate the transport and transformation of glutamate in neurons, and NaV1.6 may participate in SIH.

When homologous sequences meet structural decoys: Accurate contact prediction by tFold in CASP14-(tFold for CASP14 contact prediction).

In this paper, we report our tFold framework's performance on the inter-residue contact prediction task in the 14th Critical Assessment of protein Structure Prediction (CASP14). Our tFold framework seamlessly combines both homologous sequences and structural decoys under an ultra-deep network architecture. Squeeze-excitation and axial attention mechanisms are employed to effectively capture inter-residue interactions. In CASP14, our best predictor achieves 41.78% in the averaged top-L precision for long-range contacts for all the 22 free-modeling (FM) targets, and ranked 1st among all the 60 participating teams. The tFold web server is now freely available at: https://drug.ai.tencent.com/console/en/tfold.

Neuroinflammation contributes to autophagy flux blockage in the neurons of rostral ventrolateral medulla in stress-induced hypertension rats.

BACKGROUND: Neuroinflammation plays hypertensive roles in the uninjured autonomic nuclei of the central nervous system, while its mechanisms remain unclear. The present study is to investigate the effect of neuroinflammation on autophagy in the neurons of the rostral ventrolateral medulla (RVLM), where sympathetic premotor neurons for the maintenance of vasomotor tone reside. METHODS: Stress-induced hypertension (SIH) was induced by electric foot-shock stressors with noise interventions in rats. Systolic blood pressure (SBP) and the power density of the low frequency (LF) component of the SAP spectrum were measured to reflect sympathetic vasomotor activity. Microglia activation and pro-inflammatory cytokines (PICs (IL-1ß, TNF-α)) expression in the RVLM were measured by immunoblotting and immunostaining. Autophagy and autophagic vacuoles (AVs) were examined by autophagic marker (LC3 and p62) expression and transmission electron microscopy (TEM) image, respectively. Autophagy flux was evaluated by RFP-GFP-tandem fluorescent LC3 (tf-LC3) vectors transfected into the RVLM. Tissue levels of glutamate, gamma aminobutyric acid (GABA), and plasma levels of norepinephrine (NE) were measured by using high-performance liquid chromatography (HPLC) with electrochemical detection. The effects of the cisterna magna infused minocycline, a microglia activation inhibitor, on the abovementioned parameters were analyzed. RESULTS: SIH rats showed increased SBP, plasma NE accompanied by an increase in LF component of the SBP spectrum. Microglia activation and PICs expression was increased in SIH rats. TEM demonstrated that stress led to the accumulation of AVs in the RVLM of SIH rats. In addition to the Tf-LC3 assay, the concurrent increased level of LC3-II and p62 suggested the impairment of autophagic flux in SIH rats. To the contrary, minocycline facilitated autophagic flux and induced a hypotensive effect with attenuated microglia activation and decreased PICs in the RVLM of SIH rats. Furthermore, SIH rats showed higher levels of glutamate and lower level of GABA in the RVLM, while minocycline attenuated the decrease in GABA and the increase in glutamate of SIH rats. CONCLUSIONS: Collectively, we concluded that the neuroinflammation might impair autophagic flux and induced neural excitotoxicity in the RVLM neurons following SIH, which is involved in the development of SIH.

Mechanisms of immune checkpoint inhibitors: insights into the regulation of circular RNAS involved in cancer hallmarks.

Current treatment strategies for cancer, especially advanced cancer, are limited and unsatisfactory. One of the most substantial advances in cancer therapy, in the last decades, was the discovery of a new layer of immunotherapy approach, immune checkpoint inhibitors (ICIs), which can specifically activate immune cells by targeting immune checkpoints. Immune checkpoints are a type of immunosuppressive molecules expressed on immune cells, which can regulate the degree of immune activation and avoid autoimmune responses. ICIs, such as anti-PD-1/PD-L1 drugs, has shown inspiring efficacy and broad applicability across various cancers. Unfortunately, not all cancer patients benefit remarkably from ICIs, and the overall response rates to ICIs remain relatively low for most cancer types. Moreover, the primary and acquired resistance to ICIs pose serious challenges to the clinical application of cancer immunotherapy. Thus, a deeper understanding of the molecular biological properties and regulatory mechanisms of immune checkpoints is urgently needed to improve clinical options for current therapies. Recently, circular RNAs (circRNAs) have attracted increasing attention, not only due to their involvement in various aspects of cancer hallmarks, but also for their impact on immune checkpoints in shaping the tumor immune microenvironment. In this review, we systematically summarize the current status of immune checkpoints in cancer and the existing regulatory roles of circRNAs on immune checkpoints. Meanwhile, we also aim to settle the issue in an evidence-oriented manner that circRNAs involved in cancer hallmarks regulate the effects and resistance of ICIs by targeting immune checkpoints.

Clinical calculator based on CT and clinicopathologic characteristics predicts short-term prognosis following resection of microsatellite-stabilized diffuse gastric cancer.

PURPOSE: Although microsatellite stability/Epithelial-mesenchymal transition (MSS/EMT) subtypes have been reported in multiple cancer prognosis studies, strong confounding factors between MSS/EMT (usually with Lauren's diffuse phenotype) and diffuse gastric cancer (GC) may obscure the independent prognostic value of diffuse GC. Additionally, recent studies suggest a strong correlation between mural stratification based on CT and diffuse GC. This study aims to investigate potential prognostic factors of MSS diffuse GC using mural stratification and to develop a risk assessment model. METHODS: This retrospective study included 131 patients with MSS diffuse GC who underwent radical surgery. Univariate and multivariate Cox proportional hazards regression analysis was used to identify model predictors and construct a nomogram for overall survival (OS) and recurrence-free survival (RFS) risks. The model's performance was evaluated using ROC, accuracy, and C-index. Internal validation of the model was conducted using the bootstrap resampling method. RESULTS: Among 131 cases, 60 cases (45.8%) exhibited grade 2 mural stratification, which correlated with a poorer tumor prognosis and a more invasive phenotype. Furthermore, a nomogram for predicting OS and RFS prognosis was established based on multivariate results (age, extranodal invasion, mural stratification, and/or P53). The nomogram demonstrated excellent performance, with an AUC of 0.859 (95% CI 0.794-0.924) for OS and 0.859 (95% CI 0.789-0.929) for RFS. Internal validation using 1000 bootstrap samples yielded AUC values of 0.845 and 0.846 for OS and RFS, respectively. CONCLUSION: Grade 2 mural stratification based on CT imaging revealed a more aggressive invasive phenotype, characterized by increased LN metastasis, higher rates of peritoneal metastasis, and a poorer short-term prognosis. Furthermore, the CT phenotype-based nomogram demonstrates favorable discrimination and calibration, enabling convenient individual short-term prognostic evaluation following resection of MSS diffuse GC.

Impact of preoperative sarcopenia on postoperative complications and prognosis in patients undergoing robotic gastric cancer surgery: A propensity score matching study.

BACKGROUND: Sarcopenia, defined as decreased muscle mass and function, correlates with postoperative morbidity and mortality in cancer surgery. However, sarcopenia's impact specifically following robotic gastrectomy for gastric cancer has not been clearly defined. This study aimed to determine the influence of sarcopenia on short- and long-term clinical outcomes after robotic gastrectomy for gastric cancer. METHODS: This retrospective study analyzed 381 gastric cancer patients undergoing robotic gastrectomy. Sarcopenia was diagnosed by preoperative computed tomography (CT) body composition analysis. Propensity score matching created 147 pairs of sarcopenia and nonsarcopenia patients for comparison. Outcomes included postoperative complications, survival, inflammatory markers, length of stay, intensive care unit (ICU) transfer, and readmissions. RESULTS: Sarcopenia patients exhibited significantly higher rates of overall (53.7% versus 21.1%, P < 0.001), serious (12.9% versus 4.1%, P = 0.007), and grade III-IV complications compared to nonsarcopenia pairs after matching. Sarcopenia independently predicted reduced 3-years overall (HR = 2.53, 95% CI: 1.19-5.40, P = 0.016) and disease-free survival (HR = 1.99, 95% CI: 1.09-3.66, P = 0.026). Sarcopenia patients also showed heightened postoperative leukocyte, neutrophil, platelet, platelet to lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and monocyte to lymphocyte ratio (MLR) levels alongside suppressed lymphocytes, monocytes, and neutrophil to lymphocyte ratio (NLR). CONCLUSION: Preoperative sarcopenia is correlated with increased postoperative complications and poorer long-term survival in gastric cancer patients undergoing robotic gastrectomy. Sarcopenia assessment can optimize preoperative risk stratification and perioperative management in this population.

Transcriptomics-based liquid biopsy panel for early non-invasive identification of peritoneal recurrence and micrometastasis in locally advanced gastric cancer.

BACKGROUND: This study aimed to develop a novel six-gene expression biomarker panel to enhance the early detection and risk stratification of peritoneal recurrence and micrometastasis in locally advanced gastric cancer (LAGC). METHODS: We used genome-wide transcriptome profiling and rigorous bioinformatics to identify a six-gene expression biomarker panel. This panel was validated across multiple clinical cohorts using both tissue and liquid biopsy samples to predict peritoneal recurrence and micrometastasis in patients with LAGC. RESULTS: Through genome-wide expression profiling, we identified six mRNAs and developed a risk prediction model using 196 samples from a surgical specimen training cohort. This model, incorporating a 6-mRNA panel with clinical features, demonstrated high predictive accuracy for peritoneal recurrence in gastric cancer patients, with an AUC of 0.966 (95% CI: 0.944-0.988). Transitioning from invasive surgical or endoscopic biopsy to noninvasive liquid biopsy, the model retained its predictive efficacy (AUC = 0.963; 95% CI: 0.926-1.000). Additionally, the 6-mRNA panel effectively differentiated patients with or without peritoneal metastasis in 95 peripheral blood specimens (AUC = 0.970; 95% CI: 0.936-1.000) and identified peritoneal micrometastases with a high efficiency (AUC = 0.941; 95% CI: 0.874-1.000). CONCLUSIONS: Our study provides a novel gene expression biomarker panel that significantly enhances early detection of peritoneal recurrence and micrometastasis in patients with LAGC. The RSA model's predictive capability offers a promising tool for tailored treatment strategies, underscoring the importance of integrating molecular biomarkers with clinical parameters in precision oncology.

Development and validation of nomogram models for predicting overall survival and cancer-specific survival in gastric cancer patients with liver metastases: a cohort study based on the SEER database.

OBJECTIVE: To establish nomogram models for predicting the overall survival (OS) and cancer-specific survival (CSS) of gastric cancer liver metastasis (GCLM) patients. METHODS: Data from the Surveillance, Epidemiology, and End Results (SEER) database for 5,451 GCLM patients diagnosed between 2010 and 2015 were analyzed. The cohort was divided into a training set (3,815 cases) and an internal validation set (1,636 cases). External validation included 193 patients from the Fourth Hospital of Hebei Medical University and 171 patients from the People's Hospital of Shijiazhuang City, spanning 2016-2018. Multivariable Cox regression analysis identified eight independent prognostic factors for OS and CSS in GCLM patients, including age, histological type, grade, tumor size, surgery, chemotherapy, bone metastasis, and lung metastasis. Two nomogram models were developed based on these factors and evaluated using time-dependent receiver operating characteristic curve analysis, calibration curves, and decision curve analysis. RESULTS: Internal validation showed that the nomogram models outperformed the American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system in predicting 1-year, 2-year, and 3-year OS and CSS in GCLM patients (1-year OS: 0.801 vs. 0.593, P < 0.001; 1-year CSS: 0.807 vs. 0.598, P < 0.001; 2-year OS: 0.803 vs. 0.630, P < 0.001; 2-year CSS: 0.802 vs. 0.633, P < 0.001; 3-year OS: 0.824 vs. 0.691, P < 0.001; 3-year CSS: 0.839 vs. 0.692, P < 0.001). CONCLUSION: This study developed and validated nomogram models using SEER database data to predict OS and CSS in GCLM patients. These models offer improved prognostic accuracy over traditional staging systems, aiding in clinical decision-making.

Nomogram models for predicting overall and cancer-specific survival in early-onset gastric cancer patients: a population-based cohort study.

To develop nomogram models for predicting the overall survival (OS) and cancer-specific survival (CSS) of early-onset gastric cancer (EOGC) patients. A total of 1077 EOGC patients from the Surveillance, Epidemiology, and End Results (SEER) database were included, and an additional 512 EOGC patients were recruited from the Fourth Hospital of Hebei Medical University, serving as an external test set. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic factors. Based on these factors, two nomogram models were established, and web-based calculators were developed. These models were validated using receiver operating characteristics (ROC) curve analysis, calibration curves, and decision curve analysis (DCA). Multivariate analysis identified gender, histological type, stage, N stage, tumor size, surgery, primary site, and lung metastasis as independent prognostic factors for OS and CSS in EOGC patients. Calibration curves and DCA curves demonstrated that the two constructed nomogram models exhibited good performance. These nomogram models demonstrated superior performance compared to the 7th edition of the AJCC tumor-node-metastasis (TNM) classification (internal validation set: 1-year OS: 0.831 vs 0.793, P = 0.072; 1-year CSS: 0.842 vs 0.816, P = 0.190; 3-year OS: 0.892 vs 0.857, P = 0.039; 3-year CSS: 0.887 vs 0.848, P = 0.018; 5-year OS: 0.906 vs 0.880, P = 0.133; 5-year CSS: 0.900 vs 0.876, P = 0.109). In conclusion, this study developed two nomogram models: one for predicting OS and the other for CSS of EOGC patients, offering valuable assistance to clinicians.

A New Species of Pareas (Squamata, Pareidae) from Guangxi Province, China.

We described a new species of genus Pareas from Baise City, Guangxi Zhuang Autonomous Region, China, based on morphological and molecular evidence. Pareas baiseensis sp. nov. is distinguished from its congeners by the combination of (1) Yellowish-brown body colouration; (2) Frontal subhexagonal to diamond-shaped with its lateral sides converging posteriorly; (3) The anterior pair of chin shields is longer than it is broad; (4) Loreal not in contact with the eye, prefrontal in contact with the eye, two or three suboculars; (5) Rows of 15-15-15 dorsal scales, five rows of mid-dorsal scales keeled at the middle of the body, one vertebral scale row enlarged; (6) 187-191 ventrals, 89-97 subcaudals, all divided, cloacal plate single; (7) Two postocular stripes, the nuchal area forming a dark black four-pointed fork collar with the middle tines shorter than the outside tines. The genetic divergence (uncorrected p-distance) between the new species and other representatives of Pareas ranged from 13.9% to 24.4% for Cytochrome b (Cyt b) and 12.1% to 25.5% for NADH dehydrogenase subunit 4 (ND4). Phylogenetic analyses of mitochondrial DNA gene data recovered the new species from being the sister taxon to (P. boulengeri + P. chinensis) from China.

TUSPM-NET: A multi-task model for thyroid ultrasound standard plane recognition and detection of key anatomical structures of the thyroid.

The thyroid gland is a vital gland located in the anterior part of the neck. Ultrasound imaging of the thyroid gland is a non-invasive and widely used technique for diagnosing nodular growth, inflammation, and enlargement of the thyroid gland. In ultrasonography, the acquisition of ultrasound standard planes is crucial for disease diagnosis. However, the acquisition of standard planes in ultrasound examinations can be subjective, laborious and heavily reliant on the sonographer's clinical experience. To overcome these challenges, we design a multi-task model TUSP Multi-task Network (TUSPM-NET) that can recognize Thyroid Ultrasound Standard Plane (TUSP) and detect key anatomical structures in TUSPs in real-time. To improve TUSPM-NET's accuracy and learn prior knowledge in medical images, we proposed the plane target classes loss function and the plane targets position filter. Additionally, we collected 9778 TUSP images of 8 standard planes to train and validate the model. Experiments have shown that TUSPM-NET can accurately detect anatomical structures in TUSPs and recognize TUSP images. Compared to current models with better performance, TUSPM-NET's object detection map@0.5:0.95 improves by 9.3%; the precision and recall of plane recognition improve by 3.49% and 4.39%, respectively. Furthermore, TUSPM-NET recognizes and detects a TUSP image in just 19.9 ms, which means that the method is well suited to the needs of real-time clinical scanning.

A New Online Dynamic Nomogram: Construction and Validation of a Predictive Model for Distant Metastasis Risk and Prognosis in Patients with Gastrointestinal Stromal Tumors.

BACKGROUND: Gastrointestinal stromal tumor (GIST) is the most common sarcoma of the digestive tract, among which patients with distant metastases tend to have a poor prognosis. This study aimed to develop a model for predicting distant metastasis in GIST patients and to develop two models for monitoring overall survival (OS) and cancer-specific survival (CSS) in GIST patients with metastasis. This would allow us to develop an optimal, individualized treatment strategy. METHODS: We reviewed demographic and clinicopathological characteristics data from 2010 to 2017 of patients diagnosed with GIST in the Surveillance, Epidemiology, and End Results (SEER) database. The data of the external validation group was reviewed from the Forth Hospital of Hebei Medical University. Univariate and multivariate logistic regression analyses were used to confirm the independent risk factors for distant metastasis in the GIST patients, and univariate and multivariate Cox regression analyses were performed to identify the independent prognostic factors for OS and CSS in the GIST patients with distant metastasis. Subsequently, three web-based novel nomograms were developed, which were evaluated by the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS: Of the 3639 patients who met the inclusion criteria, 418 (11.4%) had distant metastases. The risk factors for distant metastasis in GIST patients included sex, primary site, grade, N stage, tumor size, and mitotic count. For OS, the independent prognosis factors for GIST patients with metastasis included age, race, marital, primary site, chemotherapy, mitotic count, and metastasis at the lung, and for CSS, age, race, marital, primary site, and metastasis at the lung were the independent prognosis factors. Three web-based nomograms were constructed based on these independent factors, respectively. The ROC curves, calibration curves, and DCA were performed in the training, testing, and validation sets which confirmed the high accuracy and strong clinical practice power for the nomograms. CONCLUSION: Population-based nomograms can help clinicians predict the occurrence and prognosis of distant metastases in patients with GIST, which may be helpful for clinicians to formulate clinical management and appropriate treatment strategies.

Thrombosis density ratio can predict the occurrence of pulmonary embolism and post-thrombotic syndrome in lower-extremity deep vein thrombosis patients.

OBJECTIVE: Deep vein thrombosis (DVT) formation of lower extremities can lead to serious complications including pulmonary embolism (PE) and chronic post-thrombotic syndrome (PTS). We aimed to explore the relationship between the ratio of thrombotic density and the occurrence of PE and PTS in patients with DVT of the lower extremities. METHODS: A retrospective analysis was conducted in patients who performed computed tomography venography, dividing into DVT with PE group (54 patients) and DVT-alone group (34 patients), The clinical data were recorded. Univariate and multivariate logistic regression analysis were used to analysis variables associated with PE. The ability of thrombosis density ratio and Wells score to diagnose PE was evaluated by using the receiver operating characteristic curve (ROC) area under the curve (AUC). According to the treatment and follow-up results, subgroup analysis was performed, and the Villata score was used to determine the presence or absence of PTS and its severity. RESULTS: Compare with the DVT-alone group, more patients had dyspnea and chest pain in the DVT with PE group. DVT with PE group had lower the percentage of neutrophils, white blood cell count and platelet count, while had higher blood cell count, D-dimer, wells score, thrombus and thrombus density ratio. Multivariate logistic analysis showed that percentage of neutrophils (OR(95% CIs)=1.15 (1.01,1.31), P = 0.040), platelets (OR(95% CIs)=0.96 (0.93,0.99), P = 0.011), and thrombus density ratio (OR(95% CIs)=5.99 (1.96,18.35), P = 0.002) are independent predictors of PE. The Wells score and thrombosis density ratio were consistent in the diagnostic efficacy of PE. In the subgroup analysis, there was a relevance between the ratio of thrombosis density and the Villalta score. CONCLUSION: Percentage of neutrophils, platelets, and thrombus density ratio are independent predictors of PE. The thrombosis density of DVT patients may be an index to predict the risk of PE and PTS in DVT patients.