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Abstract The recent colder winters in midlatitude Eurasia have been proposed to result from Arctic sea-ice decline. However, large uncertainties remain regarding this link in the present variable climate. Here, we present ice-rafted debris records from the eastern Arctic and geochemical data from the temperate East China Sea to reconstruct Holocene changes in sea ice and the East Asian winter monsoon. Our reconstructions and climate numerical simulations revealed enhanced Arctic sea-ice decline but warmer winters in East Asia in the mid-Holocene than in the late Holocene. In the warmer mid-Holocene, enhanced Arctic sea-ice loss transferred more heat from intensive summer solar insolation to the winter atmosphere, suppressing meridional heat transport; thus, less high-latitude cold air moved to lower latitudes in Asia due to the weakened winter monsoon. Our findings imply that the colder winters in East Asia may not change the long-term trend toward winter warming in the context of Arctic sea-ice decline.

Src homology 2 domain-containing tyrosine phosphatase 2 (SHP2) is an essential tyrosine phosphatase that is pivotal in regulating various cellular signaling pathways such as cell growth, differentiation, and survival. The activation of SHP2 has been shown to have a therapeutic effect in colitis and Parkinson's disease. Thus, the identification of SHP2 activators and a complete understanding of their mechanism is required. We used a two-step screening assay to determine a novel allosteric activator of SHP2 that stabilizes it in an open conformation. Oleanolic acid was identified as a suitable candidate. By binding to R362, K364, and K366 in the active center of the PTP domain, oleanolic acid maintained the active open state of SHP2, which facilitated the binding between SHP2 and its substrate. This oleanolic acid-activated SHP2 hindered Th17 differentiation by disturbing the interaction between STAT3 and IL-6Rα and inhibiting the activation of STAT3. Furthermore, via the activation of SHP2 and subsequent attenuation of the STAT3–Th17 axis, oleanolic acid effectively mitigated colitis in mice. This protective effect was abrogated by SHP2 knockout or administration of the SHP2 inhibitor SHP099. These findings underscore the potential of oleanolic acid as a promising therapeutic agent for treating inflammatory bowel diseases.

Abstract Background This study aims to implement a validated prediction model and application medium for postoperative pneumonia (POP) in elderly patients with hip fractures in order to facilitate individualized intervention by clinicians. Methods Employing clinical data from elderly patients with hip fractures, we derived and externally validated machine learning models for predicting POP. Model derivation utilized a registry from Nanjing First Hospital, and external validation was performed using data from patients at the Fourth Affiliated Hospital of Nanjing Medical University. The derivation cohort was divided into the training set and the testing set. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used for feature screening. We compared the performance of models to select the optimized model and introduced SHapley Additive exPlanations (SHAP) to interpret the model. Results The derivation and validation cohorts comprised 498 and 124 patients, with 14.3% and 10.5% POP rates, respectively. Among these models, Categorical boosting (Catboost) demonstrated superior discrimination ability. AUROC was 0.895 (95%CI: 0.841–0.949) and 0.835 (95%CI: 0.740–0.930) on the training and testing sets, respectively. At external validation, the AUROC amounted to 0.894 (95% CI: 0.821–0.966). The SHAP method showed that CRP, the modified five-item frailty index (mFI-5), and ASA body status were among the top three important predicators of POP. Conclusion Our model’s good early prediction ability, combined with the implementation of a network risk calculator based on the Catboost model, was anticipated to effectively distinguish high-risk POP groups, facilitating timely intervention.

Abstract The polar oceans play a vital role in regulating atmospheric CO2 concentrations (pCO2) during the Pleistocene glacial cycles. However, despite being the largest modern reservoir of respired carbon, the impact of the subarctic Pacific remains poorly understood due to limited records. Here, we present high-resolution, 230Th-normalized export productivity records from the subarctic northwestern Pacific covering the last five glacial cycles. Our records display pronounced, glacial-interglacial cyclicity superimposed with precessional-driven variability, with warm interglacial climate and high boreal summer insolation providing favorable conditions to sustain upwelling of nutrient-rich subsurface waters and hence increased export productivity. Our transient model simulations consistently show that ice sheets and to a lesser degree, precession are the main drivers that control the strength and latitudinal position of the westerlies. Enhanced upwelling of nutrient/carbon-rich water caused by the intensification and poleward migration of the northern westerlies during warmer climate intervals would have led to the release of previously sequestered CO2 from the subarctic Pacific to the atmosphere. Our results also highlight the significant role of the subarctic Pacific in modulating pCO2 changes during the Pleistocene climate cycles, especially on precession timescale ( ~ 20 kyr).

ObjectiveAmino acid (AA) metabolism plays a vital role in liver regeneration. However, its measuring utility for post-hepatectomy liver regeneration under different conditions remains unclear. We aimed to combine machine learning (ML) models with AA metabolomics to assess liver regeneration in health and non-alcoholic steatohepatitis (NASH).MethodsThe liver index (liver weight/body weight) was calculated following 70% hepatectomy in healthy and NASH mice. The serum levels of 39 amino acids were measured using ultra-high performance liquid chromatography–tandem mass spectrometry analysis. We used orthogonal partial least squares discriminant analysis to determine differential AAs and disturbed metabolic pathways during liver regeneration. The SHapley Additive exPlanations algorithm was performed to identify potential AA signatures, and five ML models including least absolute shrinkage and selection operator, random forest, K-nearest neighbor (KNN), support vector regression, and extreme gradient boosting were utilized to assess the liver index.ResultsEleven and twenty-two differential AAs were identified in the healthy and NASH groups, respectively. Among these metabolites, arginine and proline metabolism were commonly disturbed metabolic pathways related to liver regeneration in both groups. Five AA signatures were identified, including hydroxylysine, L-serine, 3-methylhistidine, L-tyrosine, and homocitrulline in healthy group, and L-arginine, 2-aminobutyric acid, sarcosine, beta-alanine, and L-cysteine in NASH group. The KNN model demonstrated the best evaluation performance with mean absolute error, root mean square error, and coefficient of determination values of 0.0037, 0.0047, 0.79 and 0.0028, 0.0034, 0.71 for the healthy and NASH groups, respectively.ConclusionThe KNN model based on five AA signatures performed best, which suggests that it may be a valuable tool for assessing post-hepatectomy liver regeneration in health and NASH.

AbstractBackground Hypoxemia often occurs in outpatients undergoing anesthesia-assisted esophagogastroduodenoscopy (EGD). However, there is a scarcity in tools to predict the hypoxemia risk. We aimed to solve this problem by developing and validating machine learning (ML) models based on preoperative and intraoperative features.Methods All data were retrospectively collected from June 2021 to February 2022. The most appropriate predictive features were selected by the least absolute shrinkage and selection operator, which were incorporated and modelled by 4 ML algorithms. The area under the precision-recall curve (AUPRC) was used as the main evaluation metric to select the best models, and the selected models were compared with the STOP-BANG score. Their predictive performance was visually interpreted by SHapley Additive exPlanations. The primary endpoint of this study was hypoxemia during the procedure, defined as at least one reading of pulse oximetry < 90% without probes misplacement from the anesthesia induction beginning to the end of EGD, while the secondary endpoint was hypoxemia during induction, from the induction beginning to the start of endoscopic intubation.Results Of 1160 patients in the derivation cohort, 112 patients (9.6%) developed intraoperative hypoxemia, of which 102 (8.8%) occurred during the induction period. In temporal and external validation, no matter whether based on preoperative variables or still based on preoperative plus intraoperative variables, our models showed excellent predictive performance for the two endpoints, significantly better than STOP-BANG score. In the model interpretation section, preoperative variables (airway assessment indicators, pulse oximeter oxygen saturation and BMI) and intraoperative variables (the induced propofol dose) made the highest contribution to the predictions.Conclusions To our knowledge, our ML models were the first to predict hypoxemia risk, which achieved excellent overall predictive ability integrating various clinical indicators. These models have the potential to become an effective tool for adjusting sedation strategies flexibly and reducing the workload of anesthesiologists.KEY MESSAGESThis study is the first model employing ML methods based on preoperative and preoperative plus intraoperative variables for predicting the risk of hypoxemia during induction and the whole EGD procedure respectively.Our four models achieved satisfactory predictive performance and outperformed STOP-BANG score in terms of AUPRC in the temporal and external validation cohorts respectively.We found that the relevant variables of airway assessment should be fully taken into account when analyzing the risk factor of hypoxemia, and the effect of patients’ age on their hypoxemia risk should be considered in conjunction with the propofol dose.

Type 2 diabetes (T2D) is often accompanied with an induction of retinaldehyde dehydrogenase 1 (RALDH1 or ALDH1A1) expression and a consequent decrease in hepatic retinaldehyde (Rald) levels. However, the role of hepatic Rald deficiency in T2D progression remains unclear. In this study, we demonstrated that reversing T2D-mediated hepatic Rald deficiency by Rald or citral treatments, or liver-specific Raldh1 silencing substantially lowered fasting glycemia levels, inhibited hepatic glucogenesis, and downregulated phosphoenolpyruvate carboxykinase 1 (PCK1) and glucose-6-phosphatase (G6PC) expression in diabetic db/db mice. Fasting glycemia and Pck1/G6pc mRNA expression levels were strongly negatively correlated with hepatic Rald levels, indicating the involvement of hepatic Rald depletion in T2D deterioration. A similar result that liver-specific Raldh1 silencing improved glucose metabolism was also observed in high-fat diet-fed mice. In primary human hepatocytes and oleic acid-treated HepG2 cells, Rald or Rald + RALDH1 silencing resulted in decreased glucose production and downregulated PCK1/G6PC mRNA and protein expression. Mechanistically, Rald downregulated direct repeat 1-mediated PCK1 and G6PC expression by antagonizing retinoid X receptor α, as confirmed by luciferase reporter assays and molecular docking. These results highlight the link between hepatic Rald deficiency, glucose dyshomeostasis, and the progression of T2D, whilst also suggesting RALDH1 as a potential therapeutic target for T2D.

Abstract Aim Pyrotinib (an irreversible pan‐ErbB small‐molecular tyrosine kinase inhibitor) was approved in human epidermal growth factor receptor 2 (HER2)‐positive breast cancer and showed great antitumor activity in preclinical studies of gastric cancer (GC). This study was first designed to prospectively assess pyrotinib in pretreated HER2‐positive GC. Methods This multicenter, phase I study followed a standard “3 + 3” design and included two parts. In the pyrotinib part, pyrotinib was administered orally, once per day at dose levels of 240, 320, 400, and 480 mg. In the pyrotinib plus docetaxel part, patients received pyrotinib (qd, d1‐21, q3W) combined with docetaxel (60 mg/m2, d1, q3W) at dose levels of 240, 320, and 400 mg. Primary endpoints were to determine the maximum tolerated dose (MTD) and recommended phase II dose (RP2D) of pyrotinib as monotherapy or coadministered with docetaxel. Results A total of 25 patients were enrolled and received pyrotinib (n = 15) or pyrotinib plus docetaxel (n = 10). One DLT was observed in pyrotinib monotherapy part (Grade 3 uncontrolled diarrhea after supportive care) and pyrotinib plus docetaxel part (Grade 4 neutropenia and leukopenia). In the pyrotinib monotherapy part, MTD was not reached. Diarrhea, anemia, neutropenia, and leukopenia were the most common treatment‐related adverse events (TRAEs). The RP2D for pyrotinib monotherapy was recommended as 400 mg. After combining with docetaxel, the risk of leukopenia and neutropenia was increased. Grade ≥3 TRAEs were reported for four patients in the monotherapy part and for eight patients in the combination part. Mean t1/2 was approximately 20 h. Pyrotinib exposure was dose‐dependent with a nonlinear relationship versus dose. There were five patients who had confirmed partial response (monotherapy: one each at 240, 400, and 480 mg dose cohort; combination therapy: two at 240 mg dose cohort), resulting in an objective response rate of 21% and 20%, respectively. Conclusions Pyrotinib alone and combined with docetaxel showed acceptable toxicities in patients with pretreated HER2‐positive GC. Trial Registration This study was registered with ClinicalTrials.gov, NCT02378389.

AbstractObjective Low cardiac output syndrome (LCOS) is a severe complication after valve surgery, with no uniform standard for early identification. We developed interpretative machine learning (ML) models for predicting LCOS risk preoperatively and 0.5 h postoperatively for intervention in advance.Methods A total of 2218 patients undergoing valve surgery from June 2019 to Dec 2021 were finally enrolled to construct preoperative and postoperative models. Logistic regression, support vector machine (SVM), random forest classifier, extreme gradient boosting, and deep neural network were executed for model construction, and the performance of models was evaluated by area under the curve (AUC) of the receiver operating characteristic and calibration curves. Our models were interpreted through SHapley Additive exPlanations, and presented as an online tool to improve clinical operability.Results The SVM algorithm was chosen for modeling due to better AUC and calibration capability. The AUCs of the preoperative and postoperative models were 0.786 (95% CI 0.729–0.843) and 0.863 (95% CI 0.824–0.902), and the Brier scores were 0.123 and 0.107. Our models have higher timeliness and interpretability, and wider coverage than the vasoactive-inotropic score, and the AUC of the postoperative model was significantly higher. Our preoperative and postoperative models are available online at http://njfh-yxb.com.cn:2022/lcos.Conclusions The first interpretable ML tool with two prediction periods for online early prediction of LCOS risk after valve surgery was successfully built in this study, in which the SVM model has the best performance, reserving enough time for early precise intervention in critical care.

Abstract Background The evidence of mechanical thrombectomy (MT) in basilar artery occlusion (BAO) was limited. This study aimed to develop dynamic and visual nomogram models to predict the unfavorable outcome of MT in BAO online. Methods BAO patients treated with MT were screened. Preoperative and postoperative nomogram models were developed based on clinical parameters and imaging features. An independent dataset was collected to perform external validation. Web‐based calculators were constructed to provide convenient access. Results A total of 127 patients were included in the study, and 117 of them were eventually included in the analysis. The nomogram models showed robust discrimination, with an area under the receiver operating characteristic (ROC) of 0.841 (preoperative) and 0.916 (postoperative). The calibration curves showed good agreement. The preoperative predictors of an unfavorable outcome were previous stroke, the National Institutes of Health Stroke Scale (NIHSS) at admission, and the posterior circulation Alberta Stroke Program Early Computed Tomography Score (pc‐ASPECTS). The postoperative predictors were previous stroke, NIHSS at 24 h, and pc‐ASPECTS. Conclusion Dynamic and visual nomograms were constructed and validated for the first time for BAO patients treated with MT, which provided precise predictions for the risk of an unfavorable outcome. The preoperative model may assist clinicians in selecting eligible patients, and the postoperative model may facilitate individualized poststroke management.

AbstractBackground and aims Assessment of the patient’s gastric contents is the key to avoiding aspiration incidents, however, there is no effective method to determine whether elective painless gastrointestinal endoscopy (GIE) patients have a full stomach or an empty stomach. And previous studies have shown that preoperative oral carbohydrates (POCs) can improve the discomfort induced by fasting, but there are different perspectives on their safety. This study aimed to develop a convenient, accurate machine learning (ML) model to predict full stomach. And based on the model outcomes, evaluate the safety and comfort improvements of POCs in empty- and full stomach groups.Methods We enrolled 1386 painless GIE patients between October 2022 and January 2023 in Nanjing First Hospital, and 1090 patients without POCs were used to construct five different ML models to identify full stomach. The metrics of discrimination and calibration validated the robustness of the models. For the best-performance model, we further interpreted it through SHapley Additive exPlanations (SHAP) and constructed a web calculator to facilitate clinical use. We evaluated the safety and comfort improvements of POCs by propensity score matching (PSM) in the two groups, respectively.Results Random Forest (RF) model showed the greatest discrimination with the area under the receiver operating characteristic curve (AUROC) 0.837 [95% confidence interval (CI): 79.1–88.2], F1 71.5%, and best calibration with a Brier score of 15.2%. The web calculator can be visited at https://medication.shinyapps.io/RF_model/. PSM results demonstrated that POCs significantly reduced the full stomach incident in empty stomach group (p 0.05). Comfort improved in both groups and was more significant in empty stomach group.Conclusions The developed convenient RF model predicted full stomach with high accuracy and interpretability. POCs were safe and comfortably improved in both groups, with more benefit in empty stomach group. These findings may guide the patients’ gastrointestinal preparation.

In order to reduce leakage flow, cavity tips are often used in high-pressure turbines, at the cost of higher thermal load compared to flat tips. To better control the leakage flow and heat transfer at the blade tip, a cavity-filling geometry is proposed in this paper, and the effects of the filling area are also investigated by numerical simulation. The results indicate that the new geometries maintain the advantages of cavity tips in terms of aerodynamic performance. With the cavity filling area increasing, the heat transfer of the new geometries shows a trend of initially increasing and then decreasing. When the front 15% of the blade tip chord length is filled, the average heat transfer of this configuration is reduced by 3.7% compared to the cavity blade tip, and the high heat transfer area is reduced by 23.3%, at the cost of more intensive hot spots. As the cavity-filling area increases from 5% to 15%, the size of the vortexes at the cavity reduces, resulting in a rise in the leakage. Similar behaviors of the tip heat transfer and leakage flow were also found when the turbine pressure ratios varied from 3 to 7, with the cavity-filling geometry.

AbstractBackground Acute kidney injury (AKI) is a common and serious complication after the repair of Type A acute aortic dissection (TA-AAD). However, previous models have failed to account for the impact of blood pressure fluctuations on predictive performance. This study aims to develop machine learning (ML) models combined with intraoperative medicine and blood pressure time-series data to improve the accuracy of early prediction for postoperative AKI risk.Methods Indicators reflecting the duration and depth of hypotension were obtained by analyzing continuous mean arterial pressure (MAP) monitored intraoperatively with multiple thresholds (

Abstract Background As a prodrug of 5-fluorouracil (5-FU), orally administrated capecitabine (CAP) undergoes preliminary conversion into active metabolites in the liver and then releases 5-FU in the gut to exert the anti-tumor activity. Since metabolic changes of CAP play a key role in its activation, a single kind of intestinal or hepatic cell can never be used in vitro to evaluate the pharmacokinetics (PK) and pharmacodynamics (PD) nature. Hence, we aimed to establish a novel in vitro system to effectively assess the PK and PD of these kinds of prodrugs. Methods Co-culture cellular models were established by simultaneously using colorectal cancer (CRC) and hepatocarcinoma cell lines in one system. Cell Counting Kit-8 (CCK-8) and flow cytometric analysis were used to evaluate cell viability and apoptosis, respectively. Apoptosis-related protein expression levels were measured using western blot analysis. A selective liquid chromatography-tandem mass spectrometry (LC–MS/MS) method was developed for cellular PK in co-culture models. Results CAP had little anti-proliferative effect on the five monolayer CRC cell lines (SW480, LoVo, HCT-8, HCT-116 and SW620) or the hepatocarcinoma cell line (HepG2). However, CAP exerted marked anti-tumor activities on each of the CRC cell lines in the co-culture models containing both CRC and hepatocarcinoma cell lines, although its effect on the five CRC cell lines varied. Moreover, after pre-incubation of CAP with HepG2 cells, the culture media containing the active metabolites of CAP also showed an anti-tumor effect on the five CRC cell lines, indicating the crucial role of hepatic cells in the activation of CAP. Conclusion The simple and cost‑effective co-culture models with both CRC and hepatocarcinoma cells could mimic the in vivo process of a prodrug dependent on metabolic conversion to active metabolites in the liver, providing a valuable strategy for evaluating the PK and PD characteristics of CAP-like prodrugs in vitro at the early stage of drug development.

Allium victorialis L. (Family: Liliaceae) is an herb with nutritional and medicinal properties. In Jilin Province, China, A. victorialis is mainly distributed in the Changbai Mountains and grows in various habitat conditions. However, the relationship between habitat factors and the nutritional quality of A. victorialis in the Changbai Mountains has not yet been examined. We assessed the nutritional quality of five A. victorialis populations growing in five different habitats in the Changbai Mountains and analyzed the relationship between nutritional quality and habitat factors. Allium victorialis populations in this region were primarily found in the undergrowth at elevations above 500 m and within specific ranges of air temperature, air relative humidity, soil temperature, and soil water content. Among the habitat factors investigated, canopy density significantly affected several nutritional components of A. victorialis; however, elevation had a significant effect only on the total flavonoid content, and the vitamin C content was not strongly associated with the main habitat factors in this study. During germplasm selection and artificial cultivation, it is important to simulate the growth conditions of the original habitat. Our results provide useful information for site selection and environmental condition optimization for the artificial cultivation of A. victorialis.

Abstract Background Pyrotinib (an irreversible pan-ErbB inhibitor) plus capecitabine has survival benefits and acceptable tolerability in patients with HER2-positive metastatic breast cancer. We further assessed addition of pyrotinib to trastuzumab and docetaxel in the neoadjuvant setting. Methods In this multicenter, double-blind, phase 3 study (PHEDRA), treatment-naive women with HER2-positive early or locally advanced breast cancer were randomly assigned (1:1) to receive four neoadjuvant cycles of oral pyrotinib or placebo (400 mg) once daily, plus intravenous trastuzumab (8 mg/kg loading dose, followed by 6 mg/kg) and docetaxel (100 mg/m2) every 3 weeks. The primary endpoint was the total pathological complete response (tpCR; ypT0/is and ypN0) rate per independent central review. Results Between Jul 23, 2018, and Jan 8, 2021, 355 patients were randomly assigned, 178 to the pyrotinib group and 177 to the placebo group. The majority of patients completed four cycles of neoadjuvant treatment as planned (92.7% and 97.7% in the pyrotinib and placebo groups, respectively). The tpCR rate was 41.0% (95% CI 34.0 to 48.4) in the pyrotinib group compared with 22.0% (95% CI 16.6 to 28.7) in the placebo group (difference, 19.0% [95% CI 9.5 to 28.4]; one-sided P < 0.0001). The objective response rate per investigator was 91.6% (95% CI 86.6 to 94.8) in the pyrotinib group and 81.9% (95% CI 75.6 to 86.9) in the placebo group after the neoadjuvant treatment, resulting in an increase of 9.7% (95% CI 2.7 to 16.6). The most common grade 3 or worse adverse events were diarrhea (79 [44.4%] in the pyrotinib group and nine [5.1%] in the placebo group), neutropenia (33 [18.5%] and 36 [20.3%]), and decreased white blood cell count (29 [16.3%] and 24 [13.6%]). No deaths were reported during neoadjuvant treatment. Conclusions The primary endpoint of the study was met. Neoadjuvant pyrotinib, trastuzumab, and docetaxel significantly improved the tpCR rate compared with placebo, trastuzumab, and docetaxel, with manageable toxicity, providing a new option for HER2-positive early or locally advanced breast cancer. Trial registration ClinicalTrials.gov, NCT03588091

Abstract Background Although programmed cell death 1 (PD‐1) blockade plus chemotherapy can significantly prolong the progression‐free survival (PFS) and overall survival (OS) in first‐line settings in patients with driver‐negative advanced non‐small‐cell lung cancer (NSCLC), the predictive biomarkers remain undetermined. Here, we investigated the predictive value of tumor immune microenvironmental marker expression to characterize the response features to PD‐1 blockade plus chemotherapy. Methods Tumor tissue samples at baseline were prospectively collected from 144 locally advanced or metastatic NSCLC patients without driver gene alterations who received camrelizumab plus chemotherapy or chemotherapy alone. Tumor immune microenvironmental markers, including PD‐1 ligand (PD‐L1), CD8, CD68, CD4 and forkhead box P3, were assessed using multiplex immunofluorescence (mIF) assays. Kaplan‐Meier curves were used to determine treatment outcome differences according to their expression status. Mutational profiles were compared between tumors with distinct expression levels of these markers and their combinations. Results Responders had significantly higher CD8/PD‐L1 (P = 0.015) or CD68/PD‐L1 co‐expression levels (P = 0.021) than non‐responders in the camrelizumab plus chemotherapy group, while no difference was observed in the chemotherapy group. Patients with high CD8/PD‐L1 or CD68/PD‐L1 co‐expression level was associated with significantly longer PFS (P = 0.002, P = 0.024; respectively) and OS (P = 0.006, P = 0.026; respectively) than those with low co‐expression in camrelizumab plus chemotherapy group. When comparing survival in the camrelizumab plus chemotherapy with chemotherapy by CD8/PD‐L1 co‐expression stratification, significantly better PFS (P = 0.003) and OS (P = 0.032) were observed in high co‐expression subgroups. The predictive value of CD8/PD‐L1 and CD68/PD‐L1 co‐expression remained statistically significant for PFS and OS when adjusting clinicopathological features. Although the prevalence of TP53 or KRAS mutations was similar between patients with and without CD8/PD‐L1 or CD68/PD‐L1 co‐expression, the positive groups had a significantly higher proportion of TP53/KRAS co‐mutations than the negative groups (both 13.0% vs. 0.0%, P = 0.023). Notably, enriched PI3K (P = 0.012) and cell cycle pathway (P = 0.021) were found in the CD8/PD‐L1 co‐expression group. Conclusion Tumor immune microenvironmental marker expression, especially CD8/PD‐L1 or CD68/PD‐L1 co‐expression, was associated with the efficacy of PD‐1 blockade plus chemotherapy as first‐line treatment in patients with advanced NSCLC.

Abstract Background Even undergoing mechanical thrombectomy (MT), patients with acute vertebrobasilar artery occlusion (AVBAO) still have a high rate of mortality. Tirofiban is a novel antiplatelet agent which is now widely empirically used in acute ischemic stroke (AIS). In this study, we aimed to evaluate the safety and efficacy of tirofiban as adjunctive therapy for MT in AVBAO. Methods From October 2016 to July 2021, consecutive AVBAO patients receiving MT were included in the prospective stroke registry. The short-term outcomes were (1) symptomatic intracerebral hemorrhage (sICH); (2) in-hospital death; (3) National Institute of Health Stroke Scale (NIHSS) at discharge. The Long-term outcomes were: (1) modified Rankin Scale (mRS) at 3 months; (2) death at 3 months. Results A total of 130 eligible patients were included in the study, 64 (49.2%) patients received tirofiban. In multivariate regression analysis, no significant differences were observed in all outcomes between the tirofiban and non-tirofiban group [sICH (adjusted OR 0.96; 95% CI, 0.12–7.82, p = 0.97), in-hospital death (adjusted OR 0.57; 95% CI, 0.17–1.89, p = 0.36), NIHSS at discharge (95% CI, -2.14–8.63, p = 0.24), mRS (adjusted OR 1.20; 95% CI, 0.40–3.62, p = 0.75), and death at 3 months (adjusted OR 0.83; 95% CI, 0.24–2.90, p = 0.77)]. Conclusions In AVBAO, tirofiban adjunctive to MT was not associated with an increased risk of sICH. Short-term (in-hospital death, NIHSS at discharge) and long-term outcomes (mRS and death at 3 months) seem not to be influenced by tirofiban use.

ObjectiveLow awareness of hypertension and diabetes is a public health concern in Ghana. Assessing the general population’s behaviour via knowledge, attitude, and practice (KAP) will be invaluable in these diseases, where prevention and control need a lifelong commitment to a healthy lifestyle. Hence, our goal was to assess the behaviour of Akatsi South residents towards the diseases to assist health providers in implementing tailored intervention programs.MethodsThis was a population-based cross-sectional study with 150 adults (18–70 years) from November to December 2021. A semi-structured questionnaire with face-to-face interviews was used to obtain data. All variables in the model had descriptive statistics. The Chi-square (χ2) test was used to examine correlations between variables, and a value of p

Background The hypoxemia risk in adult (18–64) patients treated with esophagogastroduodenoscopy (EGD) under sedation often poses a dilemma for anesthesiologists. We aimed to establish an artificial neural network (ANN) model to solve this problem, and introduce the Shapley additive explanations (SHAP) algorithm to further improve the interpretability. Methods The relevant data of patients underwent routine anesthesia-assisted EGD were collected. Elastic network was used to filter the optimal features. Airway-ANN and Basic-ANN models were established based on all collected indicators and remaining variables excluding airway assessment indicators, respectively. The performance of Basic-ANN, Airway-ANN and STOP-BANG was evaluated by the area under the precision-recall curve (AUPRC) on temporal validation set. The SHAP was used for revealing the predictive behavior of our best model. Results 999 patients were eventually included. The AUPRC value of Airway-ANN model was significantly higher than Basic-ANN model in the temporal validation set (0.532 vs 0.429, P

Pulmonary blastoma (PB) is a rare and invasive malignancy of the lungs with a poor prognosis. Although the mainstay treatment of PB is surgery, and radiotherapy and chemotherapy have been reported, no standard therapy exists for patients inoperable in advanced stages. Moreover, little is known about driver mutation status and immunotherapy efficacy. This paper presents a male patient diagnosed with classic biphasic PB using CT-guided lung biopsy pathology and immunohistochemistry. The patient’s symptoms included cough, chest pain, shortness of breath, hemoptysis, and hypodynamia. The primary focus of this paper is to discuss the impact of anti-PD-1 immunotherapy on PB. The patient experienced progression-free survival (PFS) of over 27 months following sintilimab second-line anti-PD-1 therapy. The patient has currently survived for nearly 40 months with a satisfactory quality of life.

Drug-induced hyperglycemia/diabetes is a global issue. Some drugs induce hyperglycemia by activating the pregnane X receptor (PXR), but the mechanism is unclear. Here, we report that PXR activation induces hyperglycemia by impairing hepatic glucose metabolism due to inhibition of the hepatocyte nuclear factor 4-alpha (HNF4α)‒glucose transporter 2 (GLUT2) pathway. The PXR agonists atorvastatin and rifampicin significantly downregulated GLUT2 and HNF4α expression, and impaired glucose uptake and utilization in HepG2 cells. Overexpression of PXR downregulated GLUT2 and HNF4α expression, while silencing PXR upregulated HNF4α and GLUT2 expression. Silencing HNF4α decreased GLUT2 expression, while overexpressing HNF4α increased GLUT2 expression and glucose uptake. Silencing PXR or overexpressing HNF4α reversed the atorvastatin-induced decrease in GLUT2 expression and glucose uptake. In human primary hepatocytes, atorvastatin downregulated GLUT2 and HNF4α mRNA expression, which could be attenuated by silencing PXR. Silencing HNF4α downregulated GLUT2 mRNA expression. These findings were reproduced with mouse primary hepatocytes. Hnf4α plasmid increased Slc2a2 promoter activity. Hnf4α silencing or pregnenolone-16α-carbonitrile (PCN) suppressed the Slc2a2 promoter activity by decreasing HNF4α recruitment to the Slc2a2 promoter. Liver-specific Hnf4α deletion and PCN impaired glucose tolerance and hepatic glucose uptake, and decreased the expression of hepatic HNF4α and GLUT2. In conclusion, PXR activation impaired hepatic glucose metabolism partly by inhibiting the HNF4α‒GLUT2 pathway. These results highlight the molecular mechanisms by which PXR activators induce hyperglycemia/diabetes.

BackgroundAneurysmal subarachnoid hemorrhage (aSAH) is a significant cause of morbidity and mortality throughout the world. Dynamic nomogram to predict the prognosis of elderly aSAH patients after endovascular coiling has not been reported. Thus, we aimed to develop a clinically useful dynamic nomogram to predict the risk of 6-month unfavorable outcome in elderly aSAH patients after endovascular coiling.MethodsWe conducted a retrospective study including 209 elderly patients admitted to the People’s Hospital of Hunan Province for aSAH from January 2016 to June 2021. The main outcome measure was 6-month unfavorable outcome (mRS ≥ 3). We used multivariable logistic regression analysis and forwarded stepwise regression to select variables to generate the nomogram. We assessed the discriminative performance using the area under the curve (AUC) of receiver-operating characteristic and the risk prediction model’s calibration using the Hosmer–Lemeshow goodness-of-fit test. The decision curve analysis (DCA) and the clinical impact curve (CIC) were used to measure the clinical utility of the nomogram.ResultsThe cohort’s median age was 70 (interquartile range: 68–74) years and 133 (36.4%) had unfavorable outcomes. Age, using a ventilator, white blood cell count, and complicated with cerebral infarction were predictors of 6-month unfavorable outcome. The AUC of the nomogram was 0.882 and the Hosmer–Lemeshow goodness-of-fit test showed good calibration of the nomogram (p = 0.3717). Besides, the excellent clinical utility and applicability of the nomogram had been indicated by DCA and CIC. The eventual value of unfavorable outcome risk could be calculated through the dynamic nomogram.ConclusionThis study is the first visual dynamic online nomogram that accurately predicts the risk of 6-month unfavorable outcome in elderly aSAH patients after endovascular coiling. Clinicians can effectively improve interventions by taking targeted interventions based on the scores of different items on the nomogram for each variable.

Abstract Background Antagonizing the androgen-receptor (AR) pathway is an effective treatment strategy for patients with metastatic castration-resistant prostate cancer (CRPC). Here, we report the results of a first-in-human phase 1/2 study which assessed the safety, pharmacokinetics, and activity of SHR3680 (a novel AR antagonist) in patients with metastatic CRPC. Methods This phase 1/2 study enrolled patients with progressive metastatic CRPC who had not been previously treated with novel AR-targeted agents. In the phase 1 dose-escalation portion, patients received oral SHR3680 at a starting daily dose of 40 mg, which was subsequently escalated to 80 mg, 160 mg, 240 mg, 360 mg, and 480 mg per day. In phase 2 dose-expansion portion, patients were randomized to receive daily dose of 80 mg, 160 mg, or 240 mg of SHR3680. The primary endpoint in phase 1 was safety and tolerability and in phase 2 was the proportion of patients with a prostate-specific antigen (PSA) response (≥ 50% decrease of PSA level) at week 12. Results A total of 197 eligible patients were enrolled and received SHR3680 treatment, including 18 patients in phase 1 and 179 patients in phase 2. No dose-limiting toxicities were reported and the maximum tolerated dose was not reached. Treatment-related adverse events (TRAEs) occurred in 116 (58.9%) patients, with the most common one being proteinuria (13.7%). TRAEs of grade ≥ 3 occurred in only 23 (11.7%) patients, and no treatment-related deaths occurred. Antitumor activities were evident at all doses, including PSA response at week 12 in 134 (68.0%; 95% CI, 61.0–74.5) patients, stabilized bone disease at week 12 in 174 (88.3%; 95% CI, 87.2–95.5) patients, and responses in soft tissue lesions in 21 (34.4%, 95% CI, 22.7–47.7) of 61 patients. Conclusion SHR3680 was well tolerated and safe, with promising anti-tumor activity across all doses tested in patients with metastatic CRPC. The dose of 240 mg daily was recommended for further phase 3 study. Trial registration Clinical trials.gov NCT02691975; registered February 25, 2016.

Abstract Background Camrelizumab plus chemotherapy significantly prolonged progression-free survival (PFS) and overall survival (OS) compared to chemotherapy alone as first-line treatment in advanced lung squamous cell carcinoma (LUSC) in the phase III trial (CameL-sq), which has become an option of standard-of-cares for Chinese patients with advanced LUSC. However, the predictive biomarkers remain unknown. Methods Tumor tissue samples at baseline, and peripheral blood samples at baseline (pretreatment) and after two cycles of treatment (on-treatment) were prospectively collected from 270 LUSC patients from the CameL-sq study. Blood tumor mutation burden (bTMB) and its dynamics were analyzed to explore their predictive values. Results Pretreatment bTMB was not associated with objective response, PFS and OS in camrelizumab or placebo plus chemotherapy groups. Low on-treatment bTMB was associated with significantly better objective response (73.8% vs 27.8%, P < 0.001), PFS (median, 9.1 vs 4.1 months; P < 0.001) and OS (median, not reached vs 8.0 months; P < 0.001) in camrelizumab plus chemotherapy group whereas it did not correlate with objective response and PFS in chemotherapy alone group. Importantly, on-treatment bTMB level could discriminate patients of initially radiological stable disease who would long-term benefit from camrelizumab plus chemotherapy (low vs high, median OS, 18.2 vs 7.8 months; P = 0.001). Combing on-treatment bTMB and its dynamics improved the ability for predicting the efficacy of camrelizumab plus chemotherapy. Conclusion On-treatment bTMB together with its dynamics could serve as a predictive biomarker for camrelizumab plus chemotherapy in patients with advanced LUSC. Trial registration ClinicalTrials.gov identifier: NCT03668496.

Abstract Background Recaticimab (SHR-1209, a humanized monoclonal antibody against PCSK9) showed robust LDL-C reduction in healthy volunteers. This study aimed to further assess the efficacy and safety of recaticimab in patients with hypercholesterolemia. Methods In this randomized, double-blind, placebo-controlled phase 1b/2 trial, patients receiving stable dose of atorvastatin with an LDL-C level of 2.6 mmol/L or higher were randomized in a ratio of 5:1 to subcutaneous injections of recaticimab or placebo at different doses and schedules. Patients were recruited in the order of 75 mg every 4 weeks (75Q4W), 150Q8W, 300Q12W, 150Q4W, 300Q8W, and 450Q12W. The primary endpoint was percentage change in LDL-C from the baseline to end of treatment (i.e., at week 16 for Q4W and Q8W schedule and at week 24 for Q12W schedule). Results A total of 91 patients were enrolled and received recaticimab and 19 received placebo. The dose of background atorvastatin in all 110 patients was 10 or 20 mg/day. The main baseline LDL-C ranged from 3.360 to 3.759 mmol/L. The least-squares mean percentage reductions in LDL-C from baseline to end of treatment relative to placebo for recaticimab groups at different doses and schedules ranged from −48.37 to −59.51%. No serious treatment-emergent adverse events (TEAEs) occurred. The most common TEAEs included upper respiratory tract infection, increased alanine aminotransferase, increased blood glucose, and increased gamma-glutamyltransferase. Conclusion Recaticimab as add-on to moderate-intensity statin therapy significantly and substantially reduced the LDL-C level with an infrequent administration schedule (even given once every 12 weeks), compared with placebo. Trial registration ClinicalTrials.gov , number NCT03944109

Background: Aneurysmal subarachnoid hemorrhage (aSAH) causes long-term functional dependence and death. Early prediction of functional outcomes in aSAH patients with appropriate intervention strategies could lower the risk of poor prognosis. Therefore, we aimed to develop pre- and post-operative dynamic visualization nomograms to predict the 1-year functional outcomes of aSAH patients undergoing coil embolization. Methods: Data were obtained from 400 aSAH patients undergoing endovascular coiling admitted to the People’s Hospital of Hunan Province in China (2015–2019). The key indicator was the modified Rankin Score (mRS), with 3–6 representing poor functional outcomes. Multivariate logistic regression (MLR)-based visual nomograms were developed to analyze baseline characteristics and post-operative complications. The evaluation of nomogram performance included discrimination (measured by C statistic), calibration (measured by the Hosmer–Lemeshow test and calibration curves), and clinical usefulness (measured by decision curve analysis). Results: Fifty-nine aSAH patients (14.8%) had poor outcomes. Both nomograms showed good discrimination, and the post-operative nomogram demonstrated superior discrimination to the pre-operative nomogram with a C statistic of 0.895 (95% CI: 0.844–0.945) vs. 0.801 (95% CI: 0.733–0.870). Each was well calibrated with a Hosmer–Lemeshow p-value of 0.498 vs. 0.276. Moreover, decision curve analysis showed that both nomograms were clinically useful, and the post-operative nomogram generated more net benefit than the pre-operative nomogram. Web-based online calculators have been developed to greatly improve the efficiency of clinical applications. Conclusions: Pre- and post-operative dynamic nomograms could support pre-operative treatment decisions and post-operative management in aSAH patients, respectively. Moreover, this study indicates that integrating post-operative variables into the nomogram enhanced prediction accuracy for the poor outcome of aSAH patients.

Background and purposeFutile recanalization occurs when the endovascular thrombectomy (EVT) is a technical success but fails to achieve a favorable outcome. This study aimed to use machine learning (ML) algorithms to develop a pre-EVT model and a post-EVT model to predict the risk of futile recanalization and to provide meaningful insights to assess the prognostic factors associated with futile recanalization.MethodsConsecutive acute ischemic stroke patients with large vessel occlusion (LVO) undergoing EVT at the National Advanced Stroke Center of Nanjing First Hospital (China) between April 2017 and May 2021 were analyzed. The baseline characteristics and peri-interventional characteristics were assessed using four ML algorithms. The predictive performance was evaluated by the area under curve (AUC) of receiver operating characteristic and calibration curve. In addition, the SHapley Additive exPlanations (SHAP) approach and partial dependence plot were introduced to understand the relative importance and the influence of a single feature.ResultsA total of 312 patients were included in this study. Of the four ML models that include baseline characteristics, the “Early” XGBoost had a better performance {AUC, 0.790 [95% confidence intervals (CI), 0.677–0.903]; Brier, 0.191}. Subsequent inclusion of peri-interventional characteristics into the “Early” XGBoost showed that the “Late” XGBoost performed better [AUC, 0.910 (95% CI, 0.837–0.984); Brier, 0.123]. NIHSS after 24 h, age, groin to recanalization, and the number of passages were the critical prognostic factors associated with futile recanalization, and the SHAP approach shows that NIHSS after 24 h ranks first in relative importance.ConclusionsThe “Early” XGBoost and the “Late” XGBoost allowed us to predict futile recanalization before and after EVT accurately. Our study suggests that including peri-interventional characteristics may lead to superior predictive performance compared to a model based on baseline characteristics only. In addition, NIHSS after 24 h was the most important prognostic factor for futile recanalization.

Background and purposeFutile recanalization occurs in a significant proportion of patients with basilar artery occlusion (BAO) after endovascular thrombectomy (EVT). Therefore, our goal was to develop a visualized nomogram model to early identify patients with BAO who would be at high risk of futile recanalization, more importantly, to aid neurologists in selecting the most appropriate candidates for EVT.MethodsPatients with BAO with EVT and the Thrombolysis in Cerebral Infarction score of ≥2b were included in the National Advanced Stroke Center of Nanjing First Hospital (China) from October 2016 to June 2021. The exclusion criteria were lacking the 3-month Modified Rankin Scale (mRS), age 2, and unavailable baseline CT imaging. Potential predictors were selected for the construction of the nomogram model and the predictive and calibration capabilities of the model were assessed.ResultsA total of 84 patients with BAO were finally enrolled in this study, and patients with futile recanalization accounted for 50.0% (42). The area under the curve (AUC) of the nomogram model was 0.866 (95% CI, 0.786–0.946). The mean squared error, an indicator of the calibration ability of our prediction model, was 0.025. A web-based nomogram model for broader and easier access by clinicians is available online at https://trend.shinyapps.io/DynNomapp/.ConclusionWe constructed a visualized nomogram model to accurately and online predict the risk of futile recanalization for patients with BAO, as well as assist in the selection of appropriate candidates for EVT.

AbstractThe Sea of Japan (JS), a unique marginal sea without any large river influxes in the western Pacific, provides ample information about the evolution of sea level, East Asian monsoons (EAM), sea ice activity, and ocean currents in geological time. However, insufficient investigation in the western JS limits our knowledge of East Asian climate change. This study utilizes major and trace elements and Pb isotopes of fine siliciclastic components (

AbstractWildfire is an integral part of the Earth’s climate system and plays an important role in shaping terrestrial ecosystems and biodiversity, atmospheric chemistry, regional climate, and the carbon cycle in the Earth’s history. However, the lack of high-resolution records of long wildfires limits our understanding of the natural variability, long-term trends of wildfire activity, and the reasons behind the changes in wildfire on orbital timescales. Here, a 320 ka long high-resolution wildfire record from the subarctic North Pacific is reconstructed with black carbon (BC), including its two subtypes char and soot. A 7-day-long back trajectory simulation analysis reveals the higher frequency of trajectories comes from Siberia. Our data show that continuous incidence of wildfire on a continental scale over the last 320 ka was higher during glacial periods than during the interglacial periods. The increase in wildfire frequency during glacial periods is ascribed to less precipitation. Contrasting patterns of wildfire incidence between marine isotope stages 2 and 6 may be ascribed to different fuel availability, which is related to contrasting configurations of the Northern Hemisphere ice sheet between glacial periods. A significant periodicity of 23 ka of our wildfire record suggests the precession of the Earth’s orbit pace wildfire development. The tight coupling of intensified wildfire and enhanced nutrient utilization efficiency suggests a nontrivial role of fire in the climate system.

AbstractThe continental margin is one of the major depocenters for terrigenous sediments in the world ocean. Complex interactions between land and sea control the sedimentary processes along the continental margin. The Okinawa Trough (OT) receives huge amounts of terrigenous materials transported by rivers from the adjacent landmass, while the Kuroshio Current (KC) and the North Pacific Intermediate Water jointly play major roles in oceanic climate and regional deposition patterns of terrigenous sediments. Various studies have investigated the changes in terrigenous sediment provenance in the central OT only since the last glacial. Still, few studies focus on more long-term variations in terrigenous deposition over the last few glacial-interglacial cycles. Here, we report a new high-resolution sediment geochemistry record of a well-dated core MD01-2404 taken from the central OT covering a timespan of 92 kyr. Our results show dynamic glacial-interglacial changes in sediment compositions and terrigenous deposition patterns. Bulk sediments in MD01-2404 comprise relatively high biogenic components during interglacials, while higher terrigenous fractions during the last deglacial and glacial periods. We suggest that the provenance of terrigenous sediments is mainly derived from Taiwanese rivers, Yangtze River, and Yellow River with hydrothermal inputs. During the time interval of 37 to 46 kyr, a new finding of “Negative Ce Anomaly Event” in the central OT firstly reported here is attributed to a combination of suboxic conditions in deep and pore waters and the addition of depleted Ce-bearing sediments. Temporal changes of deposition patterns in the central OT are attributed to complex interactions among dynamic glacial-interglacial changes in eustatic sea level, the East Asian summer monsoon, and the KC.

Background: CPUL1, a phenazine analog, has demonstrated potent antitumor properties against hepatocellular carcinoma (HCC) and indicates a promising prospect in pharmaceutical development. However, the underlying mechanisms remain largely obscure. Methods: Multiple HCC cell lines were used to investigate the in vitro effects of CPUL1. The antineoplastic properties of CPUL1 were assessed in vivo by establishing a xenograft nude mice model. After that, metabolomics, transcriptomics, and bioinformatics were integrated to elucidate the mechanisms underlying the therapeutic efficacy of CPUL1, highlighting an unanticipated involvement of autophagy dysregulation. Results: CPUL1 suppressed HCC cell proliferation in vitro and in vivo, thereby endorsing the potential as a leading agent for HCC therapy. Integrative omics characterized a deteriorating scenario of metabolic debilitation with CPUL1, presenting an issue in the autophagy contribution of autophagy. Subsequent observations indicated that CPUL1 treatment could impede autophagic flow by suppressing autophagosome degradation rather than its formation, which supposedly exacerbated cellular damage triggered by metabolic impairment. Moreover, the observed late autophagosome degradation may be attributed to lysosome dysfunction, which is essential for the final stage of autophagy and cargo disposal. Conclusions: Our study comprehensively profiled the anti-hepatoma characteristics and molecular mechanisms of CPUL1, highlighting the implications of progressive metabolic failure. This could partially be ascribed to autophagy blockage, which supposedly conveyed nutritional deprivation and intensified cellular vulnerability to stress.

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.

Background: In this single-arm phase II study (NCT03557099), we evaluated the efficacy and safety of hetrombopag, a small molecule thrombopoietin (TPO) receptor agonist, in patients with severe aplastic anemia (SAA) who were refractory to standard first-line immunosuppressive therapy (IST). Methods: SAA patients who were refractory to standard first-line IST were given hetrombopag orally at an initial dose of 7.5 mg once daily to a maximum of 15 mg once daily, for a total of 52 weeks. The primary endpoint was proportion of patients achieving hematologic responses in ⩾1 lineage at week 18. Results: A total of 55 eligible patients were enrolled and received hetrombopag treatment. This study met its primary endpoint, with 23 [41.8%, 95% confidence interval (CI) = 28.7–55.9] patients achieving hematologic response in ⩾1 lineage at week 18 after initiation of hetrombopag treatment. Twenty-four (43.6%, 95% CI = 30.3–57.7) and 27 (49.1%, 95% CI = 35.4–62.9) of the 55 patients responded in ⩾1 lineage at weeks 24 and 52, respectively. Median time to initial hematologic response was 7.9 weeks (range = 2.0–32.1). The responses were durable, with a 12-month relapse-free survival rate of 82.2% (95% CI = 62.2–92.2). Adverse events occurred in 54 (98.2%) patients, and 28 (50.9%) patients had treatment-related adverse events. Seventeen (30.9%) patients had adverse events of grade ⩾3. Serious adverse events occurred in 15 (27.3%) patients and three deaths (5.5%) were reported. Conclusion: Hetrombopag showed encouraging efficacy with durable hematologic responses in patients with SAA who were refractory to IST. Hetrombopag was well tolerant and safe for long-term use. ClinicalTrials.gov identifier: NCT03557099

Background and PurposeAbout 20.1% of intracranial aneurysms (IAs) carriers are multiple intracranial aneurysms (MIAs) patients with higher rupture risk and worse prognosis. A prediction model may bring some potential benefits. This study attempted to develop and externally validate a dynamic nomogram to assess the rupture risk of each IA among patients with MIA.MethodWe retrospectively analyzed the data of 262 patients with 611 IAs admitted to the Hunan Provincial People's Hospital between November 2015 and November 2021. Multivariable logistic regression (MLR) was applied to select the risk factors and derive a nomogram model for the assessment of IA rupture risk in MIA patients. To externally validate the nomogram, data of 35 patients with 78 IAs were collected from another independent center between December 2009 and May 2021. The performance of the nomogram was assessed in terms of discrimination, calibration, and clinical utility.ResultSize, location, irregular shape, diabetes history, and neck width were independently associated with IA rupture. The nomogram showed a good discriminative ability for ruptured and unruptured IAs in the derivation cohort (AUC = 0.81; 95% CI, 0.774–0.847) and was successfully generalized in the external validation cohort (AUC = 0.744; 95% CI, 0.627–0.862). The nomogram was calibrated well, and the decision curve analysis showed that it would generate more net benefit in identifying IA rupture than the “treat all” or “treat none” strategies at the threshold probabilities ranging from 10 to 60% both in the derivation and external validation set. The web-based dynamic nomogram calculator was accessible on https://wfs666.shinyapps.io/onlinecalculator/.ConclusionExternal validation has shown that the model was the potential to assist clinical identification of dangerous aneurysms after longitudinal data evaluation. Size, neck width, and location are the primary risk factors for ruptured IAs.

Background: Targeting factor XI (FXI) is a promising therapeutic strategy for the treatment and prevention of thrombosis without increasing the risk of bleeding. Here, we assessed the safety, pharmacokinetics (PK), and pharmacodynamics (PD) of SHR2285, a novel FXIa inhibitor, in healthy subjects.Methods: In this randomized, double-blinded, placebo-controlled, dose-ascending single-dosing trial (NCT03769831), eligible volunteer subjects receive either SHR2285 or placebo in a 3:1 ratio. Subjects assigned to the SHR2285 group received a single oral dose of SHR2285 at 50 mg, which was subsequently escalated to 100 mg, 200 mg, and 400 mg. Safety, pharmacokinetics, and pharmacodynamics parameters were assessed. All subjects were followed for 6 days.Results: SHR2285 was well tolerated. All adverse events were grade 1, and there was no evidence of bleeding events. The PK results revealed a rapid onset of action of SHR2285 (median time to maximum plasma concentration [Tmax] in different dose groups ranged 3.0–4.0 h) and the mean half-life ranged from 7.6 to 15.8 h. The metabolite SHR164471 had a slightly longer Tmax than the parent SHR2285, reaching a peak at a median of 6.0–7.0 h, and its mean half-life were 10.1–14.7 h in different dose groups. The sums of the area under the concentration–time curve from zero to time infinity of SHR2285 and SHR164471 in the 200 and 400 mg groups were similar, indicating the sum pharmacological activity of SHR2285 and SHR164471 showed a saturation trend between 200 and 400 mg. PD analysis showed that the inhibition of FXI activity was synchronized with prolonged activated partial thromboplastin time after SHR2285 administration, but the serum prothrombin time and international normalized ratio levels were not affected by SHR2285.Conclusion: SHR2285 demonstrated favorable safety, PK, and PD profiles in the dose range of 50 mg–400 mg. This first-in-human study supports the further development of SHR2285 for indications requiring anticoagulation.Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT03769831, identifier [NCT03769831].

Ferroptosis, a newly discovered form of regulatory cell death (RCD), has been demonstrated to be distinct from other types of RCD, such as apoptosis, necroptosis, and autophagy. Ferroptosis is characterized by iron-dependent lipid peroxidation and oxidative perturbation, and is inhibited by iron chelators and lipophilic antioxidants. This process is regulated by specific pathways and is implicated in diverse biological contexts, mainly including iron homeostasis, lipid metabolism, and glutathione metabolism. A large body of evidence suggests that ferroptosis is interrelated with various physiological and pathological processes, including tumor progression (neuro)degenerative diseases, and hepatic and renal failure. There is an urgent need for the discovery of novel effective ferroptosis-modulating compounds, even though some experimental reagents and approved clinical drugs have been well documented to have anti- or pro-ferroptotic properties. This review outlines recent advances in molecular mechanisms of the ferroptotic death process and discusses its multiple roles in diverse pathophysiological contexts. Furthermore, we summarize chemical compounds and natural products, that act as inducers or inhibitors of ferroptosis in the prevention and treatment of various diseases. Herein, it is particularly highlighted that natural products show promising prospects in ferroptosis-associated (adjuvant) therapy with unique advantages of having multiple components, multiple biotargets and slight side effects.

Background: To evaluate the safety, tolerability, and efficacy of SHR4640, a highly selective urate transporter-1 inhibitor, in combination with febuxostat, in patients with primary hyperuricemia. Methods: In this randomized, double-blind, parallel-controlled phase II study, patients whose fasting serum uric acid (sUA) levels were ⩾ 480 μmol/L at screening with gout or sUA levels were ⩾ 420 μmol/L lasting for at least 3 months without gout, either with sUA levels ⩾ 540 μmol/L at screening or sUA levels ⩾ 480 μmol/L with comorbidities at screening, were enrolled. Patients were randomized (1:1:1) to receive SHR4640 10 mg plus febuxostat 80 mg, SHR4640 10 mg plus febuxostat 40 mg, and SHR4640 5 mg plus febuxostat 20 mg orally once daily. The primary end point was the incidence of treatment-emergent adverse events (TEAEs). Results: A total of 93 patients were randomized and received treatment. TEAEs occurred in 55.9% of patients. The incidence of TEAEs was comparable among all the groups. Serious TEAEs occurred in one patient (1.1%), with no deaths observed. The proportion of patients who achieved the target sUA levels by week 4 was 79.3%, 96.6%, and 75.0% in the SHR4640 10 mg plus febuxostat 80 mg, SHR4640 10 mg plus febuxostat 40 mg, and SHR4640 5 mg plus febuxostat 20 mg groups, respectively. The mean percent reduction of sUA was 59.7%, 63.7%, and 41.8%, respectively. Conclusion: SHR4640 plus febuxostat exhibited a tolerable safety profile and substantial sUA lowering activity in patients with primary hyperuricemia. Registration: www.chinadrugtrials.org.cn ; CTR 20192429

BackgroundWith the increasing variety of drugs, the incidence of adverse drug events (ADEs) is increasing year by year. Massive numbers of ADEs are recorded in electronic medical records and adverse drug reaction (ADR) reports, which are important sources of potential ADR information. Meanwhile, it is essential to make latent ADR information automatically available for better postmarketing drug safety reevaluation and pharmacovigilance. ObjectiveThis study describes how to identify ADR-related information from Chinese ADE reports. MethodsOur study established an efficient automated tool, named BBC-Radical. BBC-Radical is a model that consists of 3 components: Bidirectional Encoder Representations from Transformers (BERT), bidirectional long short-term memory (bi-LSTM), and conditional random field (CRF). The model identifies ADR-related information from Chinese ADR reports. Token features and radical features of Chinese characters were used to represent the common meaning of a group of words. BERT and Bi-LSTM-CRF were novel models that combined these features to conduct named entity recognition (NER) tasks in the free-text section of 24,890 ADR reports from the Jiangsu Province Adverse Drug Reaction Monitoring Center from 2010 to 2016. Moreover, the man-machine comparison experiment on the ADE records from Drum Tower Hospital was designed to compare the NER performance between the BBC-Radical model and a manual method. ResultsThe NER model achieved relatively high performance, with a precision of 96.4%, recall of 96.0%, and F1 score of 96.2%. This indicates that the performance of the BBC-Radical model (precision 87.2%, recall 85.7%, and F1 score 86.4%) is much better than that of the manual method (precision 86.1%, recall 73.8%, and F1 score 79.5%) in the recognition task of each kind of entity. ConclusionsThe proposed model was competitive in extracting ADR-related information from ADE reports, and the results suggest that the application of our method to extract ADR-related information is of great significance in improving the quality of ADR reports and postmarketing drug safety evaluation.

Background and Purpose: Treatment for mild stroke remains an open question. We aim to develop a decision support tool based on machine learning (ML) algorithms, called DAMS (Disability After Mild Stroke), to identify mild stroke patients who would be at high risk of post-stroke disability (PSD) if they only received medical therapy and, more importantly, to aid neurologists in making individual clinical decisions in emergency contexts.Methods: Ischemic stroke patients were prospectively recorded in the National Advanced Stroke Center of Nanjing First Hospital (China) between July 2016 and September 2020. The exclusion criteria were patients who received thrombolytic therapy, age 5. The primary outcome was PSD, corresponding to 3-month mRS ≥ 2. We developed five ML models and assessed the area under curve (AUC) of receiver operating characteristic, calibration curve, and decision curve analysis. The optimal ML model was selected to be DAMS. In addition, SHapley Additive exPlanations (SHAP) approach was introduced to rank the feature importance. Finally, rapid-DAMS (R-DAMS) was constructed for a more urgent situation based on DAMS.Results: A total of 1,905 mild stroke patients were enrolled in this study, and patients with PSD accounted for 23.4% (447). There was no difference in AUCs between the five models (ranged from 0.691 to 0.823). Although there was similar discriminative performance between ML models, the support vector machine model exhibited higher net benefit and better calibration (Brier score, 0.159, calibration slope, 0.935, calibration intercept, 0.035). Therefore, this model was selected for DAMS. In addition, SHAP approach showed that the most crucial feature was NIHSS on admission. Finally, R-DAMS was constructed and there was similar discriminative performance between R-DAMS and DAMS, but the former performed worse on calibration.Conclusions: DAMS and R-DAMS, as prediction-driven decision support tools, were designed to aid clinical decision-making for mild stroke patients in emergency contexts. In addition, even within a narrow range of baseline scores, NIHSS on admission is the strongest feature that contributed to the prediction.

The Okhotsk Sea, which connects the high latitude Asian continent and the North Pacific, plays an important role in modern and past climate changes due to seasonal sea ice coverage and as a precursor of the North Pacific Intermediate Water. The long-term glacial-interglacial changes of sea ice coverage and its impacts on terrigenous transport and surface primary productivity in the Okhotsk Sea remain, however, not well constrained. Base on the paleomagnetic, rock magnetic, micropaleontological (diatom), and geochemical studies of the marine sediment core MD01-2414 (53°11.77′N, 149°34.80′E, water depth: 1,123 m) taken in the central Okhotsk Sea, we reconstruct the terrigenous sediment transport and paleoceanographic variations during the past 1550 thousand years (kyr). Seventeen geomagnetic excursions are identified from the paleomagnetic directional record. Close to the bottom of the core, an excursion was observed, which is proposed to be the Gilsa event ∼1550 thousand years ago (ka). During glacial intervals, our records reveal a wide extension of sea ice coverage and low marine productivity. We observed ice-rafted debris from mountain icebergs composed of coarse and high magnetic terrigenous detritus which were derived from the Kamchatka Peninsula to the central Okhotsk basin. Still during glacial intervals, the initiation (i.e., at ∼900 ka) of the Mid-Pleistocene Transition marks the changes to even lower marine productivity, suggesting that sea-ice coverage became larger during the last 900 ka. During interglacial intervals, the central Okhotsk Sea was either devoid of sea-ice or the ice was at best seasonal; resulting in high marine productivity. The weaker formation of Okhotsk Sea Intermediate Water, lower ventilation, and microbial degradation of organic matter depleted the oxygen concentration in the bottom water and created a reduced environment condition in the sea basin. The freshwater supplied by snow or glacier melting from Siberia and Kamchatka delivered fine grain sediments to the Okhotsk Sea. During the stronger interglacial intervals after the Mid-Brunhes Transition (i.e., Marine Isotope Stages 1, 5e, 9, and 11), strong freshwater discharges from Amur River drainage area are in association with intensified East Asian Summer Monsoon. This process may have enhanced the input of fine-grained terrigenous sediments to the central Okhotsk Sea.

This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1186/s13046-020-01730-8.

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.

Point cloud registration is the foundation and key step for many vital applications, such as digital city, autonomous driving, passive positioning, and navigation. The difference of spatial objects and the structure complexity of object surfaces are the main challenges for the registration problem. In this paper, we propose a graph attention capsule model (named as GACM) for the efficient registration of terrestrial laser scanning (TLS) point cloud in the urban scene, which fuses graph attention convolution and a three-dimensional (3D) capsule network to extract local point cloud features and obtain 3D feature descriptors. These descriptors can take into account the differences of spatial structure and point density in objects and make the spatial features of ground objects more prominent. During the training progress, we used both matched points and non-matched points to train the model. In the test process of the registration, the points in the neighborhood of each keypoint were sent to the trained network, in order to obtain feature descriptors and calculate the rotation and translation matrix after constructing a K-dimensional (KD) tree and random sample consensus (RANSAC) algorithm. Experiments show that the proposed method achieves more efficient registration results and higher robustness than other frontier registration methods in the pairwise registration of point clouds.