Dual‐templating surface gel into thin SSZ‐13 zeolite membrane for fast selective hydrogen separation

Abstract: Highly permeable zeolite membranes are desirable for fast gas separation in the industry. Reducing the membrane's thickness is deemed to be an optimal solution for permeability improvement. Herein, we report the synthesis route of thin SSZ‐13 zeolite membranes via the conversion of template‐contained surface gels. The synthesis gel is fully crystallized into crack‐free SSZ‐13 membranes assisted with dual templates of N, N, N‐trimethyl‐1‐adamantammonium hydroxide (TMAdaOH) and tetraethylammonium hydroxide (TEAOH). The specific functions of TMAdaOH for structure directing and TEAOH for crystallization regulating are well discussed. Thin surface gel layer is impregnated onto porous alumina with subsequent crystallization into a 500 nm thick membrane. This submicron‐thick membrane exhibits high H2 permeance with 50 × 10−8 mol s−1 m−2 Pa−1 during hydrogen separation. Meanwhile, the separation factors are retained around 23.0 and 31.5 for H2/C2H6 and H2/C3H8, respectively. This approach offers a possibility for obtaining high‐quality zeolite membranes for efficient hydrogen separation

Application of Extracellular Vesicles in Gynecologic Cancer Treatment

Ovarian, cervical, and endometrial cancer are the three most common gynecological malignancies that seriously threaten women’s health. With the development of molecular biology technology, immunotherapy and targeted therapy for gynecologic tumors are being carried out in clinical treatment. Extracellular vesicles are nanosized; they exist in various body fluids and play an essential role in intercellular communication and in the regulation of various biological process. Several studies have shown that extracellular vesicles are important targets in gynecologic cancer treatment as they promote tumor growth, progression, angiogenesis, metastasis, chemoresistance, and immune system escape. This article reviews the progress of research into extracellular vesicles in common gynecologic tumors and discusses the role of extracellular vesicles in gynecologic tumor treatment

Interpretable Machine Learning Model Predicting Early Neurological Deterioration in Ischemic Stroke Patients Treated with Mechanical Thrombectomy: A Retrospective Study

Early neurologic deterioration (END) is a common and feared complication for acute ischemic stroke (AIS) patients treated with mechanical thrombectomy (MT). This study aimed to develop an interpretable machine learning (ML) model for individualized prediction to predict END in AIS patients treated with MT. The retrospective cohort of AIS patients who underwent MT was from two hospitals. ML methods applied include logistic regression (LR), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBoost). The area under the receiver operating characteristic curve (AUC) was the main evaluation metric used. We also used Shapley Additive Explanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) to interpret the result of the prediction model. A total of 985 patients were enrolled in this study, and the development of END was noted in 157 patients (15.9%). Among the used models, XGBoost had the highest prediction power (AUC = 0.826, 95% CI 0.781–0.871). The Delong test and calibration curve indicated that XGBoost significantly surpassed those of the other models in prediction. In addition, the AUC in the validating set was 0.846, which showed a good performance of the XGBoost. The SHAP method revealed that blood glucose was the most important predictor variable. The constructed interpretable ML model can be used to predict the risk probability of END after MT in AIS patients. It may help clinical decision making in the perioperative period of AIS patients treated with MT

Predicting skip metastasis in lateral lymph nodes of papillary thyroid carcinoma based on clinical and ultrasound features

BackgroundSkip metastasis in papillary thyroid cancer (PTC), defined as lateral lymph node metastasis (LLNM) without the involvement of central lymph node metastasis (CLNM), is generally unpredictable. Our study aimed to develop a model to predict skip metastasis by using clinicopathological and ultrasound factors of PTC.MethodsWe retrospectively reviewed the medical records of patients who underwent total thyroidectomy and central lymph node dissection (CLND) plus lateral lymph node dissection (LLND) between January 2019 and December 2021 at the First Affiliated Hospital of Soochow University. Furthermore, univariate and multivariate analyses assessed the clinical and ultrasound risk factors. Receiver operating characteristic (ROC) curves were used to find the optimal cut-off values for age and dominant nodule diameter. Multivariate logistic regression analysis results were used to construct a nomogram and were validated internally.ResultsIn all patients, the skip metastasis rate was 15.4% (41/267). Skip metastasis was more frequently found in patients with a tumour size ≤10 mm (OR 0.439; P = 0.033), upper tumour location (OR 3.050; P=0.006) and fewer CLNDs (OR 0.870; P = 0.005). After analysing the clinical and ultrasound characteristics of the tumour, five factors were ultimately associated with lateral lymph node skip metastasis and were used to construct the model. These factors were an age >40 years, tumour diameter <9.1 mm, upper tumour location, non-smooth margin and extrathyroidal extension. The internally evaluated calibration curves indicated an excellent correlation between the projected and actual skip metastasis probability. The nomogram performed well in discrimination, with a concordance index of 0.797 (95% CI, 0.726 to 0.867).ConclusionsThis study screened for predictors of skip metastasis in PTC and established a nomogram that effectively predicted the risk of potential skip metastasis in patients preoperatively. The method can predict and distinguish skip metastases in PTC in a simple and inexpensive manner, and it may have future therapeutic utility

Global burden of head and neck cancers from 1990 to 2019

Summary: Head and neck cancer (HNC) exerts a significant healthcare burden worldwide. Insufficient data impedes a comprehensive understanding of its global impact. Through analysis of the 2019 Global Burden of Disease (GBD) database, our secondary investigation unveiled a surging global incidence of HNC, yet a decline in associated mortality and disability-adjusted life years (DALYs) owing to enhanced prognosis. Particularly noteworthy is the higher incidence of escalation among females compared to males. Effective resource allocation, meticulous control of risk factors, and tailored interventions are imperative to curtail mortality rates among young individuals afflicted with HNC in underprivileged regions, as well as in elderly individuals grappling with thyroid cancer

Dynamic Prediction of Mechanical Thrombectomy Outcome for Acute Ischemic Stroke Patients Using Machine Learning

The unfavorable outcome of acute ischemic stroke (AIS) with large vessel occlusion (LVO) is related to clinical factors at multiple time points. However, predictive models used for dynamically predicting unfavorable outcomes using clinically relevant preoperative and postoperative time point variables have not been developed. Our goal was to develop a machine learning (ML) model for the dynamic prediction of unfavorable outcomes. We retrospectively reviewed patients with AIS who underwent a consecutive mechanical thrombectomy (MT) from three centers in China between January 2014 and December 2018. Based on the eXtreme gradient boosting (XGBoost) algorithm, we used clinical characteristics on admission (“Admission” Model) and additional variables regarding intraoperative management and the postoperative National Institute of Health stroke scale (NIHSS) score (“24-Hour” Model, “3-Day” Model and “Discharge” Model). The outcome was an unfavorable outcome at the three-month mark (modified Rankin scale, mRS 3–6: unfavorable). The area under the receiver operating characteristic curve and Brier scores were the main evaluating indexes. The unfavorable outcome at the three-month mark was observed in 156 (62.0%) of 238 patients. These four models had a high accuracy in the range of 75.0% to 87.5% and had a good discrimination with AUC in the range of 0.824 to 0.945 on the testing set. The Brier scores of the four models ranged from 0.122 to 0.083 and showed a good predictive ability on the testing set. This is the first dynamic, preoperative and postoperative predictive model constructed for AIS patients who underwent MT, which is more accurate than the previous prediction model. The preoperative model could be used to predict the clinical outcome before MT and support the decision to perform MT, and the postoperative models would further improve the predictive accuracy of the clinical outcome after MT and timely adjust therapeutic strategies

Carbon-isotope excursions in the Norian Stage (Upper Triassic) of the Baoshan terrane, western Yunnan, China

The biostratigraphy and carbon stable isotopes of the Norian Stage (Upper Triassic) are well studied in the western Tethys, but little information is available from the eastern Tethys. Therefore, we studied the Hongyan-B (HYB) section in the Baoshan terrane, western Yunnan Province, SW China, which was located in the eastern Tethys during the Late Triassic. The HYB section was investigated for conodonts, radiolarians, total organic carbon, carbonate carbon and oxygen stable isotopes (delta C-13(carb) and delta O-18(carb)), and carbon isotopes of organic matter (delta C-13(org)). The Mockina slovakensis and Mockina bidentata conodont biozones proposed in the HYB section are associated with two radiolarian zones of the Sevatian substage, the Praemesosaturnalis multidentatus and Praemesosaturnalis pseudokahleri zones (TR8A and TR8B Sugiyama zones). This biostratigraphy places the Alaunian-Sevatian substage boundary (middle-upper Norian) at meter 23 of the HYB section. Unfortunately, the delta C-13(carb) and delta O-18(carb) values suggest that they might have been influenced by diagenesis. However, the delta C-13(org) record preserves multiple carbon-isotope excursions across the Alaunian-Sevatian boundary that can be correlated with other coeval global sections. The carbon-isotope excursions registered at this middle-upper Norian boundary are perhaps related to the major outgassing of light carbon during the emplacement of Angayucham flood basalts