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Abstract To analyze the causes, locations, associated injuries, and relevant factors of lower limb and pelvic fractures in hospitalized children in China to provide a theoretical basis for reducing the incidence of such fractures. A retrospective analysis of children with lower limb and pelvic fractures admitted to 27 tertiary children’s hospitals affiliated with China’s Futang Research Center of Pediatric Development between December 1, 2015, and December 31, 2019, was conducted. Inpatient cases were analyzed in the following age groups: Infants (

Abstract Radiomics offers a noninvasive avenue for predicting clinicopathological factors. However, thorough investigations into a robust breast cancer outcome-predicting model and its biological significance remain limited. This study develops a robust radiomic model for prognosis prediction, and further excavates its biological foundation and transferring prediction performance. We retrospectively collected preoperative dynamic contrast-enhanced MRI data from three distinct breast cancer patient cohorts. In FUSCC cohort (n = 466), Lasso was used to select features correlated with patient prognosis and multivariate Cox regression was utilized to integrate these features and build the radiomic risk model, while multiomic analysis was conducted to investigate the model’s biological implications. DUKE cohort (n = 619) and I-SPY1 cohort (n = 128) were used to test the performance of the radiomic signature in outcome prediction. A thirteen-feature radiomic signature was identified in the FUSCC cohort training set and validated in the FUSCC cohort testing set, DUKE cohort and I-SPY1 cohort for predicting relapse-free survival (RFS) and overall survival (OS) (RFS: p = 0.013, p = 0.024 and p = 0.035; OS: p = 0.036, p = 0.005 and p = 0.027 in the three cohorts). Multiomic analysis uncovered metabolic dysregulation underlying the radiomic signature (ATP metabolic process: NES = 1.84, p-adjust = 0.02; cholesterol biosynthesis: NES = 1.79, p-adjust = 0.01). Regarding the therapeutic implications, the radiomic signature exhibited value when combining clinical factors for predicting the pathological complete response to neoadjuvant chemotherapy (DUKE cohort, AUC = 0.72; I-SPY1 cohort, AUC = 0.73). In conclusion, our study identified a breast cancer outcome-predicting radiomic signature in a multicenter radio-multiomic study, along with its correlations with multiomic features in prognostic risk assessment, laying the groundwork for future prospective clinical trials in personalized risk stratification and precision therapy.

Abstract Background Triple-negative breast cancer (TNBC) is highly heterogeneous, resulting in different responses to neoadjuvant chemotherapy (NAC) and prognoses among patients. This study sought to characterize the heterogeneity of TNBC on MRI and develop a radiogenomic model for predicting both pathological complete response (pCR) and prognosis. Materials and methods In this retrospective study, TNBC patients who underwent neoadjuvant chemotherapy at Fudan University Shanghai Cancer Center were enrolled as the radiomic development cohort (n = 315); among these patients, those whose genetic data were available were enrolled as the radiogenomic development cohort (n = 98). The study population of the two cohorts was randomly divided into a training set and a validation set at a ratio of 7:3. The external validation cohort (n = 77) included patients from the DUKE and I-SPY 1 databases. Spatial heterogeneity was characterized using features from the intratumoral subregions and peritumoral region. Hemodynamic heterogeneity was characterized by kinetic features from the tumor body. Three radiomics models were developed by logistic regression after selecting features. Model 1 included subregional and peritumoral features, Model 2 included kinetic features, and Model 3 integrated the features of Model 1 and Model 2. Two fusion models were developed by further integrating pathological and genomic features (PRM: pathology-radiomics model; GPRM: genomics-pathology-radiomics model). Model performance was assessed with the AUC and decision curve analysis. Prognostic implications were assessed with Kaplan‒Meier curves and multivariate Cox regression. Results Among the radiomic models, the multiregional model representing multiscale heterogeneity (Model 3) exhibited better pCR prediction, with AUCs of 0.87, 0.79, and 0.78 in the training, internal validation, and external validation sets, respectively. The GPRM showed the best performance for predicting pCR in the training (AUC = 0.97, P = 0.015) and validation sets (AUC = 0.93, P = 0.019). Model 3, PRM and GPRM could stratify patients by disease-free survival, and a predicted nonpCR was associated with poor prognosis (P = 0.034, 0.001 and 0.019, respectively). Conclusion Multiscale heterogeneity characterized by DCE-MRI could effectively predict the pCR and prognosis of TNBC patients. The radiogenomic model could serve as a valuable biomarker to improve the prediction performance.

Abstract Background Breast cancer patients exhibit various response patterns to neoadjuvant chemotherapy (NAC). However, it is uncertain whether diverse tumor response patterns to NAC in breast cancer patients can predict survival outcomes. We aimed to develop and validate radiomic signatures indicative of tumor shrinkage and therapeutic response for improved survival analysis. Methods This retrospective, multicohort study included three datasets. The development dataset, consisting of preoperative and early NAC DCE-MRI data from 255 patients, was used to create an imaging signature-based multitask model for predicting tumor shrinkage patterns and pathological complete response (pCR). Patients were categorized as pCR, nonpCR with concentric shrinkage (CS), or nonpCR with non-CS, with prediction performance measured by the area under the curve (AUC). The prognostic validation dataset (n = 174) was used to assess the prognostic value of the imaging signatures for overall survival (OS) and recurrence-free survival (RFS) using a multivariate Cox model. The gene expression data (genomic validation dataset, n = 112) were analyzed to determine the biological basis of the response patterns. Results The multitask learning model, utilizing 17 radiomic signatures, achieved AUCs of 0.886 for predicting tumor shrinkage and 0.760 for predicting pCR. Patients who achieved pCR had the best survival outcomes, while nonpCR patients with a CS pattern had better survival than non-CS patients did, with significant differences in OS and RFS (p = 0.00012 and p = 0.00063, respectively). Gene expression analysis highlighted the involvement of the IL-17 and estrogen signaling pathways in response variability. Conclusions Radiomic signatures effectively predict NAC response patterns in breast cancer patients and are associated with specific survival outcomes. The CS pattern in nonpCR patients indicates better survival.

BackgroundPredicting long-term survival in intensive care unit patients with intracerebral hemorrhage (ICH) is crucial. This study aimed to develop a platelet-to-white blood cell ratio (PWR) incorporated nomogram for long-term survival prediction.MethodsA retrospective analysis was conducted on 1,728 ICH patients in the MIMIC-IV 2.2 database. The independent prognostic value of PWR for 1-year mortality was assessed. A nomogram was developed using LASSO and Cox regression to predict 1-year survival, incorporating PWR and other factors. The performance of the nomogram was evaluated through calibration curves, area under the curve, Delong test, net reclassification index, integrated discrimination improvement, and decision curve analysis.ResultsThe nomogram, which included age, weight, Glasgow Coma Scale (GCS) score, mechanical ventilation, glucose, red blood cell (RBC) count, blood urea nitrogen (BUN), and PWR, showed good predictive performance for 1-year survival. The C-index was 0.736 (95% CI = 0.716–0.756) for the training set and 0.766 (95% CI = 0.735–0.797) for the testing set. Higher age and ventilation increased mortality risk, while higher weight, GCS score, RBC count, and PWR decreased risk. The nomogram outperformed conventional scores.ConclusionsA nomogram incorporating PWR as a prognostic factor accurately predicts long-term survival in ICH patients. However, validation in large-scale multicenter studies and further exploration of biomarkers are needed.

Summary: Breast cancer is a common disease that causes great health concerns to women worldwide. During the diagnosis and treatment of breast cancer, medical imaging plays an essential role, but its interpretation relies on radiologists or clinical doctors. Radiomics can extract high-throughput quantitative imaging features from images of various modalities via traditional machine learning or deep learning methods following a series of standard processes. Hopefully, radiomic models may aid various processes in clinical practice. In this review, we summarize the current utilization of radiomics for predicting clinicopathological indices and clinical outcomes. We also focus on radio-multi-omics studies that bridge the gap between phenotypic and microscopic scale information. Acknowledging the deficiencies that currently hinder the clinical adoption of radiomic models, we discuss the underlying causes of this situation and propose future directions for advancing radiomics in breast cancer research.

Triple-negative breast cancer (TNBC) is the most challenging breast cancer subtype. Molecular stratification and target therapy bring clinical benefit for TNBC patients, but it is difficult to implement comprehensive molecular testing in clinical practice. Here, using our multi-omics TNBC cohort (N = 425), a deep learning-based framework was devised and validated for comprehensive predictions of molecular features, subtypes and prognosis from pathological whole slide images. The framework first incorporated a neural network to decompose the tissue on WSIs, followed by a second one which was trained based on certain tissue types for predicting different targets. Multi-omics molecular features were analyzed including somatic mutations, copy number alterations, germline mutations, biological pathway activities, metabolomics features and immunotherapy biomarkers. It was shown that the molecular features with therapeutic implications can be predicted including the somatic PIK3CA mutation, germline BRCA2 mutation and PD-L1 protein expression (area under the curve [AUC]: 0.78, 0.79 and 0.74 respectively). The molecular subtypes of TNBC can be identified (AUC: 0.84, 0.85, 0.93 and 0.73 for the basal-like immune-suppressed, immunomodulatory, luminal androgen receptor, and mesenchymal-like subtypes respectively) and their distinctive morphological patterns were revealed, which provided novel insights into the heterogeneity of TNBC. A neural network integrating image features and clinical covariates stratified patients into groups with different survival outcomes (log-rank P < 0.001). Our prediction framework and neural network models were externally validated on the TNBC cases from TCGA (N = 143) and appeared robust to the changes in patient population. For potential clinical translation, we built a novel online platform, where we modularized and deployed our framework along with the validated models. It can realize real-time one-stop prediction for new cases. In summary, using only pathological WSIs, our proposed framework can enable comprehensive stratifications of TNBC patients and provide valuable information for therapeutic decision-making. It had the potential to be clinically implemented and promote the personalized management of TNBC.

Abstract Objective Abundant neutrophils have been identified in both ruptured and unruptured intracranial aneurysm (IA) domes, with their function and clinical implication being poorly characterized. Materials and Methods We employed single‐cell RNA sequencing (scRNA‐Seq) datasets of both human and murine model, and external bulk mRNA sequencing datasets to thoroughly explore the features and functional heterogeneous of neutrophils infiltrating the IA dome. Results We found that both unruptured and ruptured IA dome contain a substantial population of neutrophils, characterized by FCGR3B, G0S2, CSF3R, and CXCR2. These cells exhibited heterogeneity in terms of function and differentiation. Despite similar transcriptional activation, neutrophils in IA dome expressed a repertoire of gene programs that mimicked transcriptomic alterations observed from bone marrow to peripheral blood, showing self‐similarity. In addition, the recruitment of neutrophils in unruptured IA was primarily mediated by monocytes/macrophages, and once ruptured, both neutrophils, and a specific subset of inflammatory smooth muscle cells (SMCs) were involved in the process. The receiver operator characteristic curve (ROC) analysis indicated that distinct neutrophil subclusters were associated with IA formation and rupture, respectively. By reviewing current studies, we found that neutrophils play a detrimental role to IA wall integrity through secreting specific ligands, ferroptosis driven by ALOX5AP and PTGS2, and the formation of neutrophil extracellular traps (NETs) mediated by PADI4. Interpretation This study delineated the biology and potential clinical implications of neutrophils in IA dome and provided a reliable basis for future researches.

Abstract Background Fractures of hands and feet are common in children, but relevant epidemiological studies are currently lacking. We aim to study the epidemiological characteristics of hand and foot fractures and growth plate injuries in children and provide a theoretical basis for their prevention, diagnosis, and treatment. Methods We retrospectively analyzed the data of children with hand and foot fractures who were hospitalized at Shenzhen Children’s Hospital between July 2015 and December 2020. Data on demographic characteristics, fracture site, treatment method, etiology of injury, and accompanying injuries were collected. The children were divided into four age groups: infants, preschool children, school children, and adolescents. The fracture sites were classified as first-level (the first–fifth finger/toe, metacarpal, metatarsal, carpal, and tarsal) and second-level (the first–fifth: proximal phalanx, middle phalanx, distal phalanx, metacarpal, and metatarsal) sites. The changing trends in fracture locations and injury causes among children in each age group were analyzed. Results Overall, 1301 children (1561 fractures; 835 boys and 466 girls) were included. The largest number of fractures occurred in preschool children (n = 549, 42.20%), with the distal phalanx of the third finger being the most common site (n = 73, 15.57%). The number of fractures in adolescents was the lowest (n = 158, 12.14%), and the most common fracture site was the proximal phalanx of the fifth finger (n = 45, 29.61%). Of the 1561 fractures, 1143 occurred in the hands and 418 in the feet. The most and least common first-level fracture sites among hand fractures were the fifth (n = 300, 26.25%) and first (n = 138, 12.07%) fingers, respectively. The most and least common first-level foot fracture locations were the first (n = 83, 19.86%) and fourth (n = 26, 6.22%) toes, respectively. The most common first-level and second level etiologies were life related injuries (n = 1128, 86.70%) and clipping injuries (n = 428, 32.90%), respectively. The incidence of sports injuries gradually increased with age, accounting for the highest proportion in adolescents (26.58%). Hand and foot fractures had many accompanying injuries, with the top three being nail bed injuries (570 cases, 36.52%), growth plate injuries (296 cases, 18.96%), and distal severed fracture (167 cases, 10.70%). Among the 296 growth plate injuries, 246 occurred on the hands and 50 on the feet. Conclusions In contrast to previous epidemiological studies on pediatric hand and foot fractures, we mapped the locations of these fractures, including proximal, shaft, distal, and epiphyseal plate injuries. We analyzed the changing trends in fracture sites and injury etiologies with age. Hand and foot fractures have many accompanying injuries that require attention during diagnosis and treatment. Doctors should formulate accident protection measures for children of different ages, strengthen safety education, and reduce the occurrence of accidental injuries.

BackgroundThe association between fibrinogen-to-albumin ratio (FAR) and in-hospital mortality in patients with spontaneous intracerebral hemorrhage (ICH) has been established. However, the association with long-term mortality in spontaneous ICH remains unclear. This study aims to investigate the association between FAR and long-term mortality in these patients.MethodsOur retrospective study involved 3,538 patients who were diagnosed with ICH at West China Hospital, Sichuan University. All serum fibrinogen and serum albumin samples were collected within 24 h of admission and participants were divided into two groups according to the FAR. We conducted a Cox proportional hazard analysis to evaluate the association between FAR and long-term mortality.ResultsOut of a total of 3,538 patients, 364 individuals (10.3%) experienced in-hospital mortality, and 750 patients (21.2%) succumbed within one year. The adjusted hazard ratios (HR) showed significant associations with in-hospital mortality (HR 1.61, 95% CI 1.31–1.99), 1-year mortality (HR 1.45, 95% CI 1.25–1.67), and long-term mortality (HR 1.45, 95% CI 1.28–1.64). Notably, the HR for long-term mortality remained statistically significant at 1.47 (95% CI, 1.15–1.88) even after excluding patients with 1-year mortality.ConclusionA high admission FAR was significantly correlated with an elevated HR for long-term mortality in patients with ICH. The combined assessment of the ICH score and FAR at admission showed higher predictive accuracy for long-term mortality than using the ICH score in isolation.

BackgroundThis cross-sectional study aims to explore the interactive effects of the Composite Dietary Antioxidant Index (CDAI) and Body Mass Index (BMI) on stroke risk among U.S. adults, utilizing data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2001 and 2018.MethodsThe analysis involved 42,042 participants from a representative sample of non-institutionalized U.S. civilians, selected through a stratified, multistage probability sampling method. Dietary intake data were collected over two 24-h periods using the Automated Multiple-Pass Method. The study calculated a modified CDAI to assess dietary antioxidant intake, excluding supplements and water sources. Statistical methods included multivariable logistic regression and Generalized Additive Models (GAM) to evaluate the interaction between CDAI scores and BMI in relation to stroke risk, adjusting for a wide range of demographic, lifestyle, and health covariates.ResultsThe research identified a significant interaction between CDAI scores and BMI categories in stroke risk assessment. While a negative correlation was observed between CDAI scores and stroke risk across the total population (OR 0.97, 95% CI 0.96–0.99), this relationship varied notably across different BMI groups. In participants with a BMI ≥25, a statistically significant negative association persisted, displaying a non-linear pattern. The study also revealed an inflection point in the CDAI score, indicating a shift in the relationship between dietary antioxidants and stroke risk.ConclusionThis study underscores the complex interaction between dietary antioxidant intake and BMI in determining stroke risk among U.S. adults. The findings suggest that individuals with higher BMI may experience more pronounced benefits from dietary antioxidants in stroke prevention. These insights could inform targeted dietary recommendations and public health strategies aimed at reducing stroke risk, particularly in populations with higher BMI. Further research is needed to fully understand these interactions and their implications for stroke prevention guidelines.

Abstract Background The biological behavior of low-grade glioma (LGG) is significantly affected by N6-methyladenosine (m6A) methylation, an essential epigenetic alteration. Therefore, it is crucial to create a prognostic model for LGG by utilizing genes that regulate m6A methylation. Methods Using TCGA and GTEx databases. We examined m6A modulator levels in LGG and normal tissues, and investigated PD-L1 and PD-1 expression, immune scores, immune cell infiltration, tumor immune microenvironment (TIME) and potential underlying mechanisms in different LGG clusters. We also performed immunohistochemistry and RT-qPCR to identify essential m6A adjustment factor. Results The results showed that m6A regulatory element expression was significantly increased in LGG tissues and was significantly associated with TMIE. A substantial increase in PD-L1 and PD-1 levels in LGG tissues and high-risk cohorts was observed. PD-L1 expression was positively correlated with FTO, ZCCHC4, and HNRNPD, whereas PD-1 expression was negatively correlated with FTO, ZC3H7B, and HNRNPD. The prognostic signature created using regulators of m6A RNA methylation was shown to be strongly associated with the overall survival of LGG patients, and FTO and ZCCHC4 were confirmed as independent prognostic markers by clinical samples. Furthermore, the results revealed different TIME characteristics between the two groups of patients, indicating disrupted signaling pathways associated with LGG. Conclusion Our results present that the m6A regulators play vital role in regulating PD-L1/PD-1 expression and the infiltration of immune cells, thereby exerting a sizable impact on the TIME of LGG. Therefore, m6A regulators have precise predictive value in the prognosis of LGG.

Abstract Background The prothrombotic state is a common abnormality in patients with coronavirus disease 2019 (COVID-19). However, there is controversy over the use of anticoagulants, especially oral anticoagulants (OAC) due to limited studies. We sought to evaluate the association between antithrombotic therapy on mortality and clinical outcomes in patients hospitalized for COVID-19 through propensity score matching (PSM) analysis. Methods A retrospective cohort study was performed to include adult patients with COVID-19 in a university hospital. The primary outcome was in-hospital mortality. Secondary outcomes included intensive care unit (ICU) admission, mechanical ventilation, and acute kidney injury (AKI) during hospitalization. PSM was used as a powerful tool for matching patients’ baseline characteristics. Adjusted odds ratios (aOR) with 95% confidence intervals (CI) were calculated from the models. Results Of 4,881 COVID-19 patients during the study period, 690 (14.1%) patients received antithrombotic therapy and 4,191 (85.9%) patients were under no antithrombotic therapy. After adjustment with multivariate regression analysis, patients receiving OAC, compared with those who did not receive any antithrombotic therapy, had significantly lower odds for in-hospital mortality (aOR: 0.46. 95% CI: 0.24 to 0.87; P= 0.017). PSM analysis observed similar results (aOR: 0.35. 95% CI: 0.19 to 0.61; P

As the amount of new energy injected into the power system increases, the system inertia decreases and the spatio-temporal characteristics become apparent. Due to the uneven distribution of inertia in the power system, the dispersion of the frequency response after disturbance is more pronounced, and the inertia estimation error has a random nature when different frequency measurement points are selected. For the above problems, a method is proposed to select the frequency measurement point based on the centre of inertia. Firstly, based on the frequency dynamic response characteristics, the main influencing factors of the frequency distribution characteristics are studied and the spatial and temporal distribution characteristics of the frequency of the new energy power system are analyzed. Secondly, the method of frequency sampling through the centre of inertia is proposed with full consideration of the electrical distance and generator inertia constants. Finally, a 10 machine 39 bus system is simulated as an example. Simulation results show that using the centre of inertia as the frequency sampling point during inertia evaluation can reduce the inertia evaluation error by up to 16.15%. The results verify the correctness of the above theoretical analysis and provide a favourable basis for further improving the accuracy of the power system inertia estimation.

Abstract Background The causal effects of gut microbiome and the development of posttraumatic stress disorder (PTSD) are still unknown. This study aimed to clarify their potential causal association using mendelian randomization (MR). Methods The summary-level statistics for gut microbiome were retrieved from a genome-wide association study (GWAS) of the MiBioGen consortium. As to PTSD, the Freeze 2 datasets were originated from the Psychiatric Genomics Consortium Posttraumatic Stress Disorder Working Group (PGC-PTSD), and the replicated datasets were obtained from FinnGen consortium. Single nucleotide polymorphisms meeting MR assumptions were selected as instrumental variables. The inverse variance weighting (IVW) method was employed as the main approach, supplemented by sensitivity analyses to evaluate potential pleiotropy and heterogeneity and ensure the robustness of the MR results. We also performed reverse MR analyses to explore PTSD’s causal effects on the relative abundances of specific features of the gut microbiome. Results In Freeze 2 datasets from PGC-PTSD, eight bacterial traits revealed a potential causal association between gut microbiome and PTSD (IVW, all P

Abstract Background and Aim The spatial distribution and interactions of cells in the tumor immune microenvironment (TIME) might be related to the different responses of triple‐negative breast cancer (TNBC) to immunomodulators. The potential of multiplex IHC (m‐IHC) in evaluating the TIME has been reported, but the efficacy is insufficient. We aimed to research whether m‐IHC results could be used to reflect the TIME, and thus to predict prognosis and complement the TNBC subtyping system. Methods The clinical, imaging, and prognosis data for 86 TNBC patients were retrospectively reviewed. CD3, CD4, CD8, Foxp3, PD‐L1, and Pan‐CK markers were stained by m‐IHC. Particular cell spatial distributions and interactions in the TIME were evaluated with the HALO multispectral analysis platform. Then, we calculated the prognostic value of components of the TIME and their correlations with TNBC transcriptomic subtypes and MRI radiomic features reflecting TNBC subtypes. Results The components of the TIME score were established by m‐IHC and demonstrated positive prognostic value for TNBC (p = 0.0047, 0.039,

Background Intracranial aneurysm (IA) is common and occasionally results in life‐threatening hemorrhagic strokes. However, the cell architecture and inflammation in the IA dome remain less understood. Methods and Results Single‐cell RNA sequencing was performed on ruptured and unruptured human IA domes for delineating the cell atlas, gene expression perturbations, and inflammation features. Two external bulk mRNA sequencing–based data sets and serological results of 126 patients were collected for validation. As a result, a total of 21 332 qualified cells were captured. Vascular cells, including endothelial cells, smooth muscle cells, fibroblasts, and pericytes, were assigned in extremely sparse numbers (4.84%), and were confirmed by immunofluorescence staining. Pericytes, characterized by ABCC9 and HIGD1B, were identified in the IA dome for the first time. Abundant immune cells were identified, with the proportion of monocytes/macrophages and neutrophils being remarkably higher in ruptured IA. The lymphocyte compartment was also thoroughly categorized. By leveraging external data sets and machine learning algorithms, macrophages were robustly associated with IA rupture, irrespective of their polarization status. The single nucleotide polymorphism rs2280543, which is identified in East Asian populations, was associated with macrophage metabolic reprogramming through regulating TALDO1 expression. Conclusions This study provides insights into the cellular architecture and inflammatory features in the IA dome and may enlighten novel therapeutics for unruptured IA.

Abstract This study aimed to examine the association of hemoglobin concentration with a 90-day mortality of young adult patients with ICH in a large retrospective cohort. A retrospective observational study was conducted between December 2013 and June 2019 in two tertiary academic medical centers in China. We defined patients with hemoglobin concentration 160 g/L as high hemoglobin. Associations of hemoglobin and outcomes were evaluated in multivariable regression analyses. The primary outcome was mortality at 90 days. We identified 4098 patients with ICH who met the inclusion criteria. After adjusting primary confounding variables, the 90-day mortality rate was significantly higher in young patients with severe anemia (OR, 39.65; 95% CI 15.42–101.97), moderate anemia (OR, 2.49; 95% CI 1.24–5.00), mild anemia (OR, 1.89; 95% CI 1.20–2.98), and high hemoglobin (OR, 2.03; 95% CI 1.26–3.26) group than in young patients of the normal group. The younger age was associated with a higher risk of death from anemia in patients with ICH (P for interaction = 0.01). In young adult patients with ICH, hemoglobin concentration was associated with 90-day mortality, and even mild to moderate anemia correlated with higher mortality. We also found that in ICH patients with anemia, younger age was associated with higher risk.

Immunotherapy has rejuvenated cancer therapy, especially after anti-PD-(L)1 came onto the scene. Among the many therapeutic options, therapeutic cancer vaccines are one of the most essential players. Although great progress has been made in research on tumor antigen vaccines, few phase III trials have shown clinical benefits. One of the reasons lies in obstruction from the tumor microenvironment (TME). Meanwhile, the therapeutic cancer vaccine reshapes the TME in an ambivalent way, leading to immune stimulation or immune escape. In this review, we summarize recent progress on the interaction between therapeutic cancer vaccines and the TME. With respect to vaccine resistance, innate immunosuppressive TME components and acquired resistance caused by vaccination are both involved. Understanding the underlying mechanism of this crosstalk provides insight into the treatment of cancer by directly targeting the TME or synergizing with other therapeutics.

Abstract Objective The prognosis of aneurysmal subarachnoid hemorrhage (aSAH) survivors is concerning. The goal of this study was to investigate and demonstrate the relationship between the neutrophil-to-albumin ratio (NAR) and long-term mortality of aSAH survivors. Methods A retrospective observational cohort study was conducted at Sichuan University West China Hospital between January 2009 and June 2019. The investigation of relationship between NAR and long-term mortality was conducted using univariable and multivariable Cox regression models. To demonstrate the predictive performance of different biomarkers over time, time-dependent receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA) were created. Results In total, 3173 aSAH patients were included in this study. There was a strong and continuous relationship between NAR levels and long-term mortality (HR 3.23 95% CI 2.75–3.79, p 0.28: adjusted HR 1.74 95% CI 1.30–2.32). Results in survivors were found to be still robust. Moreover, out of all the inflammatory markers studied, NAR demonstrated the highest correlation with long-term mortality. Conclusions A high level of NAR was associated with increased long-term mortality among patients with aSAH. NAR was a promising inflammatory marker for long-term mortality of aSAH.

Due to the large terrain fluctuation and drop in Qianshuta well field, the layout of the ground large loop transient electromagnetic method detection device is limited. In order to find out the distribution range of goaf under the second Shanjing line of oil and gas pipeline in this area, numerical simulation and field test of small loop transient electromagnetic method were carried out to analyze the feasibility of ground detection, and optimized parameters were applied to the field. The results show that the numerical simulation confirms that the 3 m×3 m small loop transient electromagnetic method can effectively detect the goaf with a depth of more than 200 m and a mining height of more than 1 m, and has a more obvious effect on the water-filled goaf with low resistance; the field test adopts the small loop transient electromagnetic method with optimized parameters such as the length of the transmitting wire frame 3 m×3 m, the number of stacking times of 15, the transmitting frequency of 16 Hz, and more than 8 A transmitting current, which can achieve the purpose of effective detection and verify the correctness of the numerical simulation; a total of 5 abnormal areas were delineated and explained in the No.3 coal seam, which were inferred to be gobs or burned rock voids. The reliability of the small loop transient electromagnetic detection method is fully verified.

Abstract Background Accurately predicting the outcome of isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) remains hitherto challenging. This study aims to Construct and Validate a Robust Prognostic Model for IDH wild-type GBM (COVPRIG) for the prediction of overall survival using a novel metric, gene–gene (G × G) interaction, and explore molecular and cellular underpinnings. Methods Univariate and multivariate Cox regression of four independent trans-ethnic cohorts containing a total of 800 samples. Prediction efficacy was comprehensively evaluated and compared with previous models by a systematic literature review. The molecular underpinnings of COVPRIG were elucidated by integrated analysis of bulk-tumor and single-cell based datasets. Results Using a Cox-ph model-based method, six of the 93,961 G × G interactions were screened to form an optimal combination which, together with age, comprised the COVPRIG model. COVPRIG was designed for RNA-seq and microarray, respectively, and effectively identified patients at high risk of mortality. The predictive performance of COVPRIG was satisfactory, with area under the curve (AUC) ranging from 0.56 (CGGA693, RNA-seq, 6-month survival) to 0.79 (TCGA RNAseq, 18-month survival), which can be further validated by decision curves. Nomograms were constructed for individual risk prediction for RNA-seq and microarray-based cohorts, respectively. Besides, the prognostic significance of COVPRIG was also validated in GBM including the IDH mutant samples. Notably, COVPRIG was comprehensively evaluated and externally validated, and a systemic review disclosed that COVPRIG outperformed current validated models with an integrated discrimination improvement (IDI) of 6–16%. Moreover, integrative bioinformatics analysis predicted an essential role of METTL1+ neural-progenitor-like (NPC-like) malignant cell in driving unfavorable outcome. Conclusion This study provided a powerful tool for the outcome prediction for IDH wild-type GBM, and preliminary molecular underpinnings for future research.

Abstract Background The causal association between the gut microbiome and the development of migraine and its subtypes remains unclear. Methods The single nucleotide polymorphisms concerning gut microbiome were retrieved from the gene-wide association study (GWAS) of the MiBioGen consortium. The summary statistics datasets of migraine, migraine with aura (MA), and migraine without aura (MO) were obtained from the GWAS meta-analysis of the International Headache Genetics Consortium (IHGC) and FinnGen consortium. Inverse variance weighting (IVW) was used as the primary method, complemented by sensitivity analyses for pleiotropy and increasing robustness. Results In IHGC datasets, ten, five, and nine bacterial taxa were found to have a causal association with migraine, MA, and MO, respectively, (IVW, all P

Abstract Background N6-methyladenosine (m6A) and 5-methylcytosine (m5C) are the main RNA methylation modifications involved in the oncogenesis of cancer. However, it remains obscure whether m6A/m5C-related long non-coding RNAs (lncRNAs) affect the development and progression of low grade gliomas (LGG). Methods We summarized 926 LGG tumor samples with RNA-seq data and clinical information from The Cancer Genome Atlas and Chinese Glioma Genome Atlas. 105 normal brain samples with RNA-seq data from the Genotype Tissue Expression project were collected for control. We obtained a molecular classification cluster from the expression pattern of sreened lncRNAs. The least absolute shrinkage and selection operator Cox regression was employed to construct a m6A/m5C-related lncRNAs prognostic signature of LGG. In vitro experiments were employed to validate the biological functions of lncRNAs in our risk model. Results The expression pattern of 14 sreened highly correlated lncRNAs could cluster samples into two groups, in which various clinicopathological features and the tumor immune microenvironment were significantly distinct. The survival time of cluster 1 was significantly reduced compared with cluster 2. This prognostic signature is based on 8 m6A/m5C-related lncRNAs (GDNF-AS1, HOXA-AS3, LINC00346, LINC00664, LINC00665, MIR155HG, NEAT1, RHPN1-AS1). Patients in the high-risk group harbored shorter survival times. Immunity microenvironment analysis showed B cells, CD4 + T cells, macrophages, and myeloid-derived DC cells were significantly increased in the high-risk group. Patients in high-risk group had the worse overall survival time regardless of followed TMZ therapy or radiotherapy. All observed results from the TCGA-LGG cohort could be validated in CGGA cohort. Afterwards, LINC00664 was found to promote cell viability, invasion and migration ability of glioma cells in vitro. Conclusion Our study elucidated a prognostic prediction model of LGG by 8 m6A/m5C methylated lncRNAs and a critical lncRNA regulation function involved in LGG progression. High-risk patients have shorter survival times and a pro-tumor immune microenvironment.

Background: Although a variety of risk factors for pneumonia after spontaneous intracerebral hemorrhage have been established, an objective and easily obtainable predictor is still needed. Lactate dehydrogenase is a nonspecific inflammatory biomarker. In this study, we aimed to assess the association between lactate dehydrogenase and pneumonia in spontaneous intracerebral hemorrhage patients. Methods: Our study was a retrospective, multicenter cohort study, undertaken in 7562 patients diagnosed with spontaneous intracerebral hemorrhage from 3 hospitals. All serum Lactate dehydrogenase was collected within 7 days from admission and divided into four groups as quartile(Q). We conducted a multivariable logistic regression analysis to assess the association of Lactate dehydrogenase with pneumonia. Results: Among a total of 7562 patients, 2971 (39.3%) patients were diagnosed with pneumonia. All grades of elevated lactate dehydrogenase were associated with increased raw and risk-adjusted risk of pneumonia. Multiple logistic regression analysis showed odds ratios for Q2-Q4 compared with Q1 were 1.21 (95% CI, 1.04–1.42), 1.64(95% CI, 1.41–1.92), and 1.92 (95% CI, 1.63–2.25) respectively. The odds ratio after adjustment was 4.42 (95% CI, 2.94–6.64) when lactate dehydrogenase was a continuous variable after log-transformed. Conclusions: Elevated lactate dehydrogenase is significantly associated with an increase in the odds of pneumonia and has a predictive value for severe pneumonia in patients with pneumonia. Lactate dehydrogenase may be used to predict pneumonia events in spontaneous intracerebral hemorrhage patients as a laboratory marker.

Background: Rickets occurs in infants and children (aged 2 months to 3 years), compromising their skeletal development and damaging nervous, hematopoietic, immune, and other system functions. This study aimed to explore the significance of CD38 in rickets. Methods: The microarray dataset GSE22523 was analyzed to obtain differentially expressed genes in rickets patients. A total of 36 rickets patients and healthy controls were recruited for the study, and their blood samples were collected, followed by detecting mRNA levels of CD38 using quantitative real-time polymerase chain reaction (qRT-PCR). Moreover, the significance of CD38 in rickets patients was analyzed by receiver operating characteristic (ROC) analysis, while the correlation between CD38 and 25-hydroxy-vitamin D (25OHD)/parathyroid hormone (PTH) was analyzed with Pearson's correlation. Results: Results showed that CD38 mRNA levels and PTH contents were significantly increased in the rickets patients while 25OHD contents were decreased. Correlation analysis indicated that CD38 was positively correlated with PTH and negatively correlated with 25OHD in both serum and plasma samples of rickets patients. Moreover, ROC analysis showed that serum CD38 was 0.9005 (95 % CI: 0.8313–0.9696), and the AUCs of plasma CD38 was 0.7215 (95 % CI: 0.6031–0.8398) in differentiating rickets patients from healthy persons, advocating serum CD38 had better diagnostic value. Conclusion: CD38 mRNA levels were upregulated in rickets patients and closely correlated with PTH and 25OHD contents, indicating CD38 might be a diagnostic marker of rickets patients. Further research on the diagnostic utility of CD38 is necessary for the diagnosis and treatment of ricketsin rickets in the future.

BackgroundCurrent evidence linking sedentary behavior (SB), physical activity (PA), and inflammation raises questions about their causal relationships, prompting concerns about potential residual confounding or reverse causation.MethodsA bidirectional Mendelian randomization (MR) analysis was conducted. SB data (n = 408,815) from "computer use," "television watching," and "driving" were included. The PA data encompassed nine types of PA (n = 460,376) over the last four weeks and included data on the frequency of vigorous PA (n = 440,512) and moderate PA (n = 440,266) for over 10 min. Additionally, three genome-wide association study datasets (n = 64,949) on light, moderate, and vigorous exercise were included to minimize potential bias from changes in exercise intensity. Inflammation data included levels of C-reactive protein (CRP) (n = 575,531), glycoprotein acetyl (GlycA) (n = 115,082), interleukin (IL)-8, IL-6, IL-6 receptor (IL-6R), and soluble IL-6R (sIL-6R) (n = 35,278). All datasets represented participants of European ancestry.ResultsTelevision watching as an SB showed significant positive causal effects on GlycA and CRP (inverse variance weighted (IVW), odds ratios (OR): 1.34, 95% confidence intervals (CI): 1.25-1.44, p = 3.570 × 10-17; IVW, OR: 1.21, 95% CI: 1.16-1.26, p = 1.500 × 10-19, respectively), with more robust evidence for GlycA. In the direction from inflammation to PA, a negative causal relationship between CRP and"number of days/week of moderate PA 10+ minutes"was observed (IVW, OR: 0.92, 95% CI: 0.89-0.96, p = 3.260 × 10-5). Sensitivity analyses were used to verify the robustness and reliability of the results. However, other initially observed associations ceased to be significant after controlling for obesity-related confounders.ConclusionOur MR analysis suggested a potential causal relationship between television watching and chronic low-grade inflammation, with more substantial evidence for GlycA. Additionally, different types of SB may have varying effects on inflammation. Obesity-related traits could partly or entirely influence the relationship between SB, PA, and inflammatory markers. Furthermore, Our findings indicate that SB is an independent risk factor for inflammation, separate from PA, and highlight the different mechanisms by which SB and PA affect disease.

Climate varies along geographic gradients, causing spatial variations in the effects of energy and water on species richness and the explanatory power of different climatic factors. Species of the Quercus genus are important tree species in China with high ecological and socioeconomic value. To detect whether the effects of energy and water on species richness change along climatic gradients, this study built geographically weighted regression models based on species richness and climatic data. Variation partition analysis and hierarchical partitioning analysis were used to further explore the main climatic factors shaping the richness distribution pattern of Quercus in China. The results showed that Quercus species were mainly distributed in mountainous areas of southwestern China. Both energy and water were associated with species richness, with global slopes of 0.17 and 0.14, respectively. The effects of energy and water on species richness gradually increased as energy and water in the environment decreased. The interaction between energy and water altered the effect of energy, and in arid regions, the effects of energy and water were relatively stronger. Moreover, energy explained more variation in species richness in both the entire study area (11.5%) and different climate regions (up to 19.4%). The min temperature of coldest month was the main climatic variable forming the richness distribution pattern of Quercus in China. In conclusion, cold and drought are the critical climatic factors limiting the species richness of Quercus, and climate warming will have a greater impact in arid regions. These findings are important for understanding the biogeographic characteristics of Quercus and conserving biodiversity in China.

IntroductionPatients undergoing craniotomy are at high risk of perioperative morbidity and mortality due to excessive inflammatory responses. The purpose of the present study is to evaluate the prognostic utility of postoperative systemic inflammatory response syndrome (SIRS) in patients undergoing craniotomy.MethodsWe performed a retrospective cohort study of patients who underwent craniotomy between January 2011 and March 2021. SIRS was diagnosed based on two or more criteria (hypo-/hyperthermia, tachypnea, leukopenia/leukocytosis, tachycardia). We used univariate and multivariate analysis for the development of SIRS with postoperative 30-day mortality.ResultsOf 12,887 patients who underwent craniotomy, more than half of the patients (n = 6,725; 52.2%) developed SIRS within the first 7 days after surgery, and 157 (1.22%) patients died within 30 days after surgery. In multivariable analyses, SIRS (OR, 1.57; 95% CI, 1.12–2.21) was associated with 30-day mortality. Early SIRS was not predictive of 30-day mortality, whereas delayed SIRS was predictive of 30-day mortality. Abnormal white blood cell (WBC) counts contributed the most to the SIRS score, followed by abnormal body temperature, respiratory rate, and heart rate.ConclusionPostoperative SIRS commonly occurs after craniotomy and is an independent predictor of postoperative 30-day mortality. This association was seen only in delayed SIRS but not early SIRS. Moreover, increased WBC counts contributed the most to the SIRS score.

AbstractBackground Glioma is a common primary central nervous system tumor with complex pathogenesis. DNA damage and repair (DDR) is widely involved in regulating cell proliferation and tumorigenesis by correcting and repairing DNA damage mechanisms. Recent studies have reported the following properties in cancer cells in glioma, increased DNA damage and reduced DNA repair capacity. However, the relationship between glioma and DDR-related genes was unclear.Methods DDR-related risk score model was built. The validity of this model was validated in detail through the Kaplan-Meier survival analysis, tumor mutational burden (TMB) analysis, immune cell infiltration, sensitivity to treatment regimens. Moreover, the model’s adaptability was validated in different glioma data cohorts and different glioma subgroups. To further investigate the molecular mechanism of one of DDR-related gene (NUDT1) in glioma, U251 cell was used for the knockdown experiment, followed by MTT, wound healing and transwell analysis.Results Ten prognostic-related DDR-related signature genes were obtained, including EID3, MGMT, YWHAG, PMS1, SHPRH, HUS1, NUDT1, GADD45G, APEX1 and FAM175A. The RT-qPCR results suggested that the latter five genes were highly expressed in glioma patients. Interestingly, high TMB score had longer survival. In high-risk score groups, reduced immune cell infiltration in the tumor microenvironment lead to poorer patient outcomes. Sensitivity to treatment regimens analysis indicated that low-risk score groups were more sensitive to chemotherapeutics. Moreover, the risk score model had a good prediction effect on different glioma datasets and different glioma subgroups. In vitro mechanism study showed that knockdown of NUDT1 reduced tumorigenesis. Furthermore, knockdown of NUDT1 remarkably reduced the expression level of HIF-1α.Conclusion DDR-related risk score model built-in this work has good predictive performance for glioma.Key messagesTen prognostic-related DDR-related signature genes were obtained, including EID3, MGMT, YWHAG, PMS1, SHPRH, HUS1, NUDT1, GADD45G, APEX1 and FAM175A.In high-risk score groups, reduced immune cell infiltration in the tumor microenvironment leads to poorer patient outcomes.The risk score model had a good prediction effect on different glioma datasets and different glioma subgroups.Knockdown of NUDT1 reduced tumorigenesis of glioma and remarkably reduced the expression level of HIF-1α.

Abstract Background Short stature homeobox 2 (SHOX2) is significant gene in the development and progression of multiple types of tumors. Nonetheless, the biological role of SHOX2 within pan-cancer datasets has not been investigated. Thus, comprehensive bioinformatics analyses of pan-cancer datasets were conducted to explore how SHOX2 regulates tumorigenesis. Methods A variety of tumor datasets and online analytical tools, including SangerBox, TIMER2, LinkedOmic, GEPIA2 and cBioPortal, were applied to explore SHOX2 expression in various tumors. To ascertain the connections between SHOX2 expression and genetic alterations, SHOX2-related genes and tumor immunity, the pan-cancer datasets were examined. In vitro assays were applied to verify the biological functions of SHOX2 in glioma cells via CCK-8, wound healing, Transwell and colony formation assays. Results Analyses found that SHOX2 was overexpressed in multiple cancer types. SHOX2 expression level was significantly correlated with isocitrate dehydrogenase (IDH), 1p/19q, O6-methylguanine DNA methyltransferase (MGMT) status and new types of glioma patients. High mRNA expression levels of SHOX2 were associated with a poor prognosis in multiple tumor patients. KEGG enrichment analysis showed that SHOX2-related genes were associated with cell cycle and DNA damage repair. Genetic alterations of SHOX2 were identified in multiple types of cancers, including duplications and deep mutations. Immune analysis showed that SHOX2 was closely correlated with the tumor mutation burden (TMB), microsatellite instability (MSI), neoantigen and neoantigens and immune checkpoint (ICP) in a variety of tumors and could influence the immunotherapy sensitivity of cancers. CCK-8, wound healing, Transwell and colony formation experiments showed that SHOX2 knockdown inhibited glioma cell proliferation, migration, invasion and colony formation abilities. Conclusion SHOX2 was overexpressed in multiple cancer types in TCGA cohort. SHOX2 knockdown inhibited glioma cell proliferation, migration and colony formation ability. Our study showed that SHOX2 may be an immunotherapeutic and promising prognostic biomarker in certain types of tumors.

ObjectiveIntracerebral hemorrhage (ICH) is a significant cause of global mortality and morbidity. This study aimed to analyze the burden of ICH and its variation trends across 204 countries and territories from 1990 to 2019.Materials and methodsThe study population comprised individuals of all ages and genders with ICH in 204 countries and regions between 1990 and 2019. Utilizing data from the Global Burden of Disease (GBD) study 2019, we collected information on age-standardized incidence rate (ASIR), age-standardized death rate (ASDR), and disability-adjusted life-years (DALYs) rate, which were compared by age, gender, and socio-demographic index (SDI).ResultsIn 2019, there were an estimated 3.4 million (3.0–3.9) incident cases, resulting in 2.8 million (2.6–3.0) deaths and 68.5 million (63.2–73.6) DALYs due to ICH. Between 1990 and 2019, the absolute number of incident cases, deaths, and DALYs increased by 43.0% (41.0–45.0), 37.0% (22.0–51.0), and 25.0% (12.0–36.0), respectively. However, the ASIR, ASDR, and DALYs showed a decreasing trend of-29.0% (−28.0 to −30.0), −36.0% (−29.0 to −43.0), and − 37.0% (−43.0 to −31.0), respectively. Countries with lower SDI tended to have higher ASIR, ASDR, and DALY rates.ConclusionWhile the ASDR and DALY rates decreased from 1990 to 2019, the decline in ASIR was less pronounced. The global burden of ICH remains high, exhibiting significant variation across different genders, age groups, and SDI levels.

Abstract Breast cancer ranks among the most prevalent malignant tumours and is the primary contributor to cancer‐related deaths in women. Breast imaging is essential for screening, diagnosis, and therapeutic surveillance. With the increasing demand for precision medicine, the heterogeneous nature of breast cancer makes it necessary to deeply mine and rationally utilize the tremendous amount of breast imaging information. With the rapid advancement of computer science, artificial intelligence (AI) has been noted to have great advantages in processing and mining of image information. Therefore, a growing number of scholars have started to focus on and research the utility of AI in breast imaging. Here, an overview of breast imaging databases and recent advances in AI research are provided, the challenges and problems in this field are discussed, and then constructive advice is further provided for ongoing scientific developments from the perspective of the National Natural Science Foundation of China.

BackgroundAbnormal hematocrit values, including anemia and polycythemia, are common in patients undergoing craniotomy, but the extent to which preoperative anemia or polycythemia independently increases the risk of mortality is unclear. This retrospective cohort study aimed to examine the association between preoperative anemia and polycythemia and postoperative mortality in patients who underwent craniotomy for brain tumor resection.MethodsWe retrospectively analyzed data from 12,170 patients diagnosed with a brain tumor who underwent cranial surgery at West China Hospital between January 2011 and March 2021. The preoperative hematocrit value was defined as the last hematocrit value within 7 days before the operation, and patients were grouped according to the severity of their anemia or polycythemia. We assessed the primary outcome of 30-day postoperative mortality using logistic regression analysis adjusted for potential confounding factors.ResultsMultivariable logistic regression analysis reported that the 30-day mortality risk was raised with increasing severity of both anemia and polycythemia. Odds ratios for mild, moderate, and severe anemia were 1.12 (95% CI: 0.79–1.60), 1.66 (95% CI: 1.06–2.58), and 2.24 (95% CI: 0.99–5.06), respectively. Odds ratios for mild, moderate, and severe polycythemia were 1.40 (95% CI: 0.95–2.07), 2.81 (95% CI: 1.32–5.99), and 14.32 (95% CI: 3.84–53.44), respectively.ConclusionsThis study demonstrated that moderate to severe anemia and polycythemia are independently associated with increased postoperative mortality in patients undergoing craniotomy for brain tumor resection. These findings underscore the importance of identifying and managing abnormal hematocrit values before craniotomy surgery.

Background: Given that limited reports have described the survival and risk factors for elderly patients with hypertensive intracerebral hemorrhage (HICH), we aimed to develop a valid but simple prediction nomogram for the survival of HICH patients. Methods: All elderly patients ≥65 years old who were diagnosed with HICH between January 2011 and December 2019 were identified. We performed the least absolute shrinkage and selection operator (Lasso) on the Cox regression model with the R package glmnet. A concordance index was performed to calculate the nomogram discrimination; and calibration curves and decision curves were graphically evaluated by depicting the observed rates against the probabilities predicted by the nomogram. Results: A total of 204 eligible patients were analyzed, and over 20 % of the population was above the age of 80 (65–79 years old, n = 161; 80+ years old, n = 43). A hematoma volume ≥13.64 cm3 was associated with higher 7-day mortality (OR = 6.773, 95 % CI = 2.622–19.481; p

Sandstorm, as a disastrous weather phenomenon, seriously threatens the ecological environment and human health. In this study, the normalized brightness temperature dust index (NBTDI) data set of sandstorms in Yellow River Basin, China during 2000–2021 was constructed. Based on this, the temporal and spatial distribution pattern of sandstorms in the Yellow River Basin in the 21st century was analyzed. The variation trend of NBTDI in the past 22 years was discussed. The results showed that the interannual variation of sandstorms in the 21st century weakened first and then intensified. From the perspective of seasonal variation, sandstorm events occurred most frequently in spring (92.4%), followed by winter (5.6%), and occasionally in summer and autumn. In space, the distribution of sandstorms in the Yellow River Basin had obvious spatial heterogeneity. The central location of the sandstorm in the Yellow River Basin moved slightly to the north, but all of them were concentrated on desert areas. This was caused by the combination of unique geographical location and meteorological factors. The natural climate was closely related to the occurrence of sandstorms. The variation trend of long time-series NBTDI indicated that there were long memories between 22 years of sandstorms. NBTDI had an increasing trend in the long time series. In the future, sandstorms will become more frequent, in line with past trends. This study provides important data support for comprehensive understanding of extreme sandstorm weather, and has important significance for large-scale and long-term monitoring of sandstorm weather.

Asia contains 58 % of the global population and approximately 39 % of the world’s cropland, making evaluation of the spatiotemporal variability patterns in cropland fire critical for understanding the interplay between crop residue burning and human activity in Asia. Although agricultural expansion and intensification have contributed to an overall decline in vegetation fires worldwide since the late 1990s, burned area by cropland fires in Asia has expanded by more than 19 % over the past two decades. India accounts for about 32 % of cropland fires in Asia, and the burned area has increased by more than two-thirds since 2003, particularly increased around 80 % during the two major cereal harvest seasons of March-May and October-November. In comparison, cropland fires have increased by

The spatial organisation of diffuse midline glioma-H3K27M mutant (DMG) and glioblastoma (GBM) remains to be investigated. Here, the authors integrate short-read and long-read spatial profiling of DMG and GBM to identify regulatory programs and cellular ecosystems in distinct glioma niches.

Brain-inspired algorithms have become a new trend in next-generation artificial intelligence. Through research on brain science, the intelligence of remote sensing algorithms can be effectively improved. This article summarizes and analyzes the essential properties of brain cognize learning and the recent advance of remote sensing interpretation. First, this article introduces the structural composition and the properties of the brain. Then, five represent brain-inspired algorithms are studied, including multiscale geometry analysis, compressed sensing, attention mechanism, reinforcement learning, and transfer learning. Next, this article summarizes the data types of remote sensing, the development of typical applications of remote sensing interpretation, and the implementations of remote sensing, including datasets, software, and hardware. Finally, the top ten open problems and the future direction of brain-inspired remote sensing interpretation are discussed. This work aims to comprehensively review the brain mechanisms and the development of remote sensing and to motivate future research on brain-inspired remote sensing interpretation.

The Tibetan Plateau (TP) is characterized by heavily local dust activities, however, the mechanism of interannual variations of winter dust frequency over the TP remain poorly understood. Previous studies showed the autumn Arctic sea ice could significantly influence the winter climate over Eurasia. Whether autumn sea ice affects winter dust activity over the TP or not? Here, we used an integrated surface database to investigate possible mechanisms for interannual variability in the frequency of winter dust events above the TP. This variability, which is thought to be mainly caused by local dust emissions, shows significant correlations with sea ice concentration (SIC) in the Barents and Kara Seas during the preceding autumn. Low Barents–Kara SIC is accompanied by reduced snow depth over northern Eurasia between autumn and winter, which can enhance the Eurasian mid-latitude westerly jet stream. This strengthening increases the cyclogenesis and occurrence of strong surface wind speeds in winter, especially over the TP. In addition, a lower SIC is closely associated with reduced precipitation and snow cover in late autumn and winter over the TP, which in turn enhances warming of the land surface and reduces the area of frozen ground. These anomalies in atmospheric circulation patterns and local surface conditions promote dust events above the TP during winter. The ensemble means of Atmospheric Model Intercomparison Project experiments from Phase 6 of the Coupled Model Inter-comparison Project and the Community Atmosphere Model version 4 can generally reproduce the atmospheric circulation anomalies associated with decreased Barents–Kara SIC. This study reveals the crucial effect that SIC anomalies in the Barents and Kara Seas have on winter dust activities over the TP.

Objectives: We sought to perform a network meta-analysis to compare the safety and efficacy of the systemic administration of corticosteroids for the treatment of COVID-19. Methods: A Bayesian network meta-analysis was performed to combine the direct and indirect evidence. The surface under the cumulative ranking curve was obtained to estimate the ranking probability of the treatment agents for each outcome. The efficacy outcome was 28-day all-cause mortality. The safety outcome was serious adverse events. Results: A total of 16 trials with 2992 patients comparing four treatments (dexamethasone, hydrocortisone, methylprednisolone, and placebo) were identified. Direct analysis showed that corticosteroids were associated with a reduced risk of 28-day mortality compared with usual care (risk ratio [RR] 0.83; 95% confidence interval [CrI] 0.70-0.99). Network analysis showed that the pooled RR was 0.63 (95% CrI 0.39-0.93) for all-cause mortality at 28 days comparing methylprednisolone with usual care or placebo (surface under the cumulative ranking curve: 91%). Our analysis demonstrated that patients who received a low dose of corticosteroids (RR 0.80; 95% CrI 0.70-0.91) and a long course of treatment (RR 0.81; 95% CrI 0.71-0.91) had higher survival rates than patients in the placebo group. Conclusion: Administration of corticosteroids was associated with a reduced all-cause mortality at 28 days compared with placebo or usual care. Our analysis also confirmed the mortality benefit associated with low-dose and long-term treatment with corticosteroids.

Abstract Objective Lactate dehydrogenase (LDH) has been reported to be associated with outcomes after surgery in patients with aneurysmal subarachnoid hemorrhage (aSAH), but it is unclear if this is independent from other biomarkers and across all aSAH treatments. This study aims to assess whether LDH is an independent predictor of mortality in patients with aSAH and test whether the inclusion of LDH in a well‐established prediction model can improve discrimination and reclassification. Methods This was a retrospective observational study at a tertiary academic medical center. This study measured baseline LDH levels taken at admission and longitudinal LDH levels (up to a month postadmission) to assess median, max, and trajectory LDH levels. The primary outcome was mortality at 90 days. Multivariable regression analyses were used to evaluate associations between LDH and outcomes. The full original Subarachnoid Hemorrhage International Trialists' (SAHIT) model was used as the reference model. Results In total, 3524 patients with aSAH were included. LDH at admission was independently associated with mortality at 90 days (quartile 4 vs. 1: odds ratio 1.60; 95% CI 1.08–2.37) and mortality at the longest follow‐up (quartile 4 vs. 1: hazard ratio1.72; 95% CI 1.34–2.20). Compared with the SAHIT model, the addition of three LDH (admission, max, and median) levels to the SAHIT model significantly improved the area under the curve and categorical net reclassification improvement for prediction mortality. Interpretation In patients with aSAH, LDH level is an independent predictor of all‐cause mortality. The incorporation of LDH into a well‐established prediction model improved the ability to predict the risk of death in patients with aSAH.

Abstract Test of different myocardial biomarkers is commonly arranged in patients with aneurysmal subarachnoid hemorrhage (aSAH). We sought to figure out whether different myocardial biomarkers' elevation is related to characteristics of ruptured aneurysms and patients' clinical outcomes. Patients with aSAH admitted in the Neurosurgery Department of West China Hospital from September 2019 to March 2020 were screened. Those who have one clear responsible aneurysm and met inclusion criteria were included. Clinical characteristics, site and size of the aneurysm, modified Fisher scale, troponin T (TPN-T), creatine kinase MB (CK-MB), and myoglobin (Myo) levels at admission, clinical outcomes (3-month mRS) were collected and compared. The study included 124 patients. After multivariate logistic regression, Hunt & Hess grade (per unit grade, OR 1.68, 95% CI 1.14–2.49), the size of ruptured aneurysm (equal to or more than 7 mm, OR 3.07, 95% CI 1.32–7.10) was highly predictive of myocardial biomarker elevation. All three biomarkers (TPN-T, CK-MB, Myo) were associated with unfavorable prognoses. Higher mortality (37.2% vs. 18.6%, P = 0.036) and a lower rate of good outcomes (41.9% vs. 71.2%, P = 0.003) were observed in patients with any positive myocardial biomarkers at admission. The clinical outcomes of patients with positive troponin T and negative creatine kinase MB were especially unfavorable. Our study demonstrates that the degree of neurological injury and size of ruptured aneurysm are strong predictors of myocardial biomarkers elevation, the site of ruptured aneurysm may not be associated with heart injury after SAH. The outcomes of patients with different combinations of abnormal biomarker levels may have significant differences and deserve further study.

Abstract Background Tumor-infiltrating lymphocytes (TILs) have become a promising biomarker for assessing tumor immune microenvironment and predicting immunotherapy response. However, the assessment of TILs relies on invasive pathological slides. Methods We retrospectively extracted radiomics features from magnetic resonance imaging (MRI) to develop a radiomic cohort of triple-negative breast cancer (TNBC) (n = 139), among which 116 patients underwent transcriptomic sequencing. This radiomic cohort was randomly divided into the training cohort (n = 98) and validation cohort (n = 41) to develop radiomic signatures to predict the level of TILs through a non-invasive method. Pathologically evaluated TILs in the H&E sections were set as the gold standard. Elastic net and logistic regression were utilized to perform radiomics feature selection and model training, respectively. Transcriptomics was utilized to infer the detailed composition of the tumor microenvironment and to validate the radiomic signatures. Results We selected three radiomics features to develop a TILs-predicting radiomics model, which performed well in the validation cohort (AUC 0.790, 95% confidence interval (CI) 0.638–0.943). Further investigation with transcriptomics verified that tumors with high TILs predicted by radiomics (Rad-TILs) presented activated immune-related pathways, such as antigen processing and presentation, and immune checkpoints pathways. In addition, a hot immune microenvironment, including upregulated T cell infiltration gene signatures, cytokines, costimulators and major histocompatibility complexes (MHCs), as well as more CD8+ T cells, follicular helper T cells and memory B cells, was found in high Rad-TILs tumors. Conclusions Our study demonstrated the feasibility of radiomics model in predicting TILs status and provided a method to make the features interpretable, which will pave the way toward precision medicine for TNBC.

Abstract Objective The relative effects of monoclonal antibody against calcitonin gene-related peptide (CGRP) or its receptor for adult migraine patients with prior treatment failure remains uncertain. Therefore, this study systematically assessed the comparative effectiveness of different CGRP binding monoclonal antibodies (mAbs) for these patients. Methods Several online databases including Ovid MEDILNE, Ovid EMBASE, Cochrane Library, and ClinicalTrials.gov were systematically searched from inception to June 15, 2022. We included randomized clinical trials (RCT) of adult migraine patients with previous treatment failure that assessed any CGRP monoclonal antibody. The primary efficacy outcome was change in monthly migraine days (MMDs), and the primary safety outcome was treatment-emergent adverse events (TEAEs). Results Overall, seven studies totaling 3, 052 patients were included. Three-node analysis showed that CGRP mAbs was superior to CGRP receptor mAbs in reducing MMDs (MD: -1.55, 95% CrI: − 2.43 to − 0.44) and improving at least 50% response rates (RR: 1.52, 95% CrI: 1.04 to 2.21). Nine-node analysis showed galcanezumab 240 mg ranked first in reducing MMDs (MD -4.40, 95% CrI − 7.60 to − 1.19) and improving 50% response rates (RR: 4.18, 95% CrI: 2.63 to 6.67). Moreover, treatment with fremanezumab or eptinezumab 300 mg provides a significant advantage over erenumab 140 mg regarding an improved response rate of at least 50%. The analysis did not show difference in incidences of TEAEs and serious adverse events in any of the comparisons. Conclusions It appears that CGRP mAbs, especially galcanezumab 240 mg, monthly fremanezumab, and eptinezumab 300 mg, seem to be the best choice for the treatment of migraine patients with previous treatment failures. This finding also calls for future research that examine the associations between these medications in migraine therapy among the same patient group to testify the present findings.

The increase of nitrogen (N) deposition and the diversity of its components lead to significant changes in the structure and function of temperate meadow steppe, which could affect plant nutrient uptake, nutrient resorption and litter decomposition, thus affecting the biogeochemical cycle process. The distribution and metabolism of nitrogen and phosphorus in plants determine the growth process and productivity of plants. Plant nutrient uptake, nutrient resorption and litter decomposition play an important role in the nutrient cycling process of ecosystem. This study closely combined these three processes to carry out experiments with different nitrogen dosages and types, and systematically explored the response of nitrogen and phosphorus nutrient cycling to nitrogen deposition. The results showed that nitrogen deposition can greatly affect ecosystem nutrient cycle of nitrogen and phosphorus. Firstly, Nitrogen deposition has significant effect on plant nutrient uptake. Nitrogen uptake of stems and leaves increased with the increase of nitrogen addition dosage, while phosphorus uptake of stems and leaves showed a downward trend or no significant effect. Besides, nitrogen addition type had a significant effect on nitrogen and phosphorus content of stems. Secondly, Nitrogen addition dosage had a significant effect on plant nutrient resorption, while nitrogen addition type had no significant effect on it. Thirdly, nitrogen deposition has significant effect on litter decomposition. With the increase of nitrogen addition dosage, the initial nitrogen content of litters increased and the decomposition rate of litters accelerated. Nitrogen application type had significant effect on stem litter decomposition. These results indicated that nitrogen deposition significantly affects plant nutrient cycling, and thus affects the structure and function of grassland ecosystem.

BackgroundExtrahepatic metastasis of hepatocellular carcinoma (HCC) is common. However, pituitary metastasis of HCC is extremely rare. Our case may be helpful to extend the understanding of the disease.Case presentationA 65-year-old man presented to the outpatient department for unexplained headache and ptosis for 1 month. Brain imaging showed a slight enhancement tumor in the pituitary fossa, and the endocrinological assessment showed normal results. We considered the tumor as a non-functioning pituitary adenoma before surgery. Then, the tumor was resected by an endonasal endoscopic transsphenoidal approach. The histopathological examination results revealed the pituitary metastasis of HCC. Additional abdominal imaging revealed tumors were located in the left and right liver lobes with portal vein invasion and bilateral ilium metastases. After multidisciplinary cooperation, the patient chose chemotherapy.ConclusionWe report a case of HCC metastasis to the pituitary gland that initially presented with neurological symptoms. We should consider the possibility of pituitary metastasis in HCC patients.

BackgroundDespite the widespread use of intraoperative steroids in various neurological surgeries to reduce cerebral edema and other adverse symptoms, there is sparse evidence in the literature for the optimal and safe usage of intraoperative steroid administration in patients undergoing craniotomy for brain tumors. We aimed to investigate the effects of intraoperative steroid administration on postoperative 30-day mortality in patients undergoing craniotomy for brain tumors.MethodsAdult patients who underwent craniotomy for brain tumors between January 2011 to January 2020 were included at West China Hospital, Sichuan University in this retrospective cohort study. Stratified analysis based on the type of brain tumor was conducted to explore the potential interaction.ResultsThis study included 8,663 patients undergoing craniotomy for brain tumors. In patients with benign brain tumors, intraoperative administration of steroids was associated with a higher risk of postoperative 30-day mortality (adjusted OR 1.98, 95% CI 1.09–3.57). However, in patients with malignant brain tumors, no significant association was found between intraoperative steroid administration and postoperative 30-day mortality (adjusted OR 0.86, 95% CI 0.55–1.35). Additionally, administration of intraoperative steroids was not associated with acute kidney injury (adjusted OR 1.11, 95% CI 0.71–1.73), pneumonia (adjusted OR 0.89, 95% CI 0.74–1.07), surgical site infection (adjusted OR 0.78, 95% CI 0.50–1.22) within 30 days, and stress hyperglycemia (adjusted OR 1.05, 95% CI 0.81–1.38) within 24 h after craniotomy for brain tumor.ConclusionIn patients undergoing craniotomy for benign brain tumors, intraoperative steroids were associated with 30-day mortality, but this association was not significant in patients with malignant brain tumors.

IntroductionIt is of great significance to understand the characteristics and influencing factors of vegetation coverage variation in the warm temperate zone. As a typical region of the warm temperate zone in eastern China, the mountainous and hilly region in central-south Shandong Province has fragile ecological environment and soil erosion problem. Studying on vegetation dynamics and its influencing factors in this region will help to better understand the relationship between climate change and vegetation cover change in the warm temperate zone of eastern China, and the influence of human activities on vegetation cover dynamics.MethodsBased on dendrochronology, a standard tree-ring width chronology was established in the mountainous and hilly region of central-south Shandong Province, and the vegetation coverage from 1905 to 2020 was reconstructed to reveal the dynamic change characteristics of vegetation cover in this region. Secondly, the influence of climate factors and human activities on the dynamic change of vegetation cover was discussed through correlation analysis and residual analysis.Results and discussionIn the reconstructed sequence, 23 years had high vegetation coverage and 15 years had low vegetation coverage. After low-pass filtering, the vegetation coverage of 1911–1913, 1945–1951, 1958–1962, 1994–1996, and 2007–2011 was relatively high, while the vegetation coverage of 1925–1927, 1936–1942, 2001–2003, and 2019–2020 was relatively low. Although precipitation determined the variation of vegetation coverage in this study area, the impacts of human activities on the change of vegetation coverage in the past decades cannot be ignored. With the development of social economy and the acceleration of urbanization, the vegetation coverage declined. Since the beginning of the 21st century, ecological projects such as Grain-for-Green have increased the vegetation coverage.