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Over recent decades, significant advancements have been made in the treatment and imaging of gliomas. Conventional imaging techniques, such as MRI and CT, play critical roles in glioma diagnosis and treatment but often fail to distinguish between tumor pseudoprogression (Psp) and radiation necrosis (RN) versus true progression (TP). Emerging fields like radiomics and radiogenomics are addressing these challenges by extracting quantitative features from medical images and correlating them with genomic data, respectively. This article will discuss several studies that show how radiomic features (RFs) can aid in better patient stratification and prognosis. Radiogenomics, particularly in predicting biomarkers such as MGMT promoter methylation and 1p/19q codeletion, shows potential in non-invasive diagnostics. Radiomics also offers tools for predicting tumor recurrence (rBT), essential for treatment management. Further research is needed to standardize these methods and integrate them into clinical practice. This review underscores radiomics and radiogenomics’ potential to revolutionize glioma management, marking a significant shift towards precision neuro-oncology.

Automatic diagnosis of malignant prostate cancer patients from mpMRI has been studied heavily in the past years. Model interpretation and domain drift have been the main road blocks for clinical utilization. As an extension from our previous work we trained on a public cohort with 201 patients and the cropped 2.5D slices of the prostate glands were used as the input, and the optimal model were searched in the model space using autoKeras. As an innovative move, peripheral zone (PZ) and central gland (CG) were trained and tested separately, the PZ detector and CG detector were demonstrated effective in highlighting the most suspicious slices out of a sequence, hopefully to greatly ease the workload for the physicians.

With the widespread use of lithium-ion batteries in electric vehicles, energy storage systems, and portable electronic devices, concerns regarding their thermal runaway have escalated, raising significant safety issues. Despite advances in existing thermal management technologies, challenges remain in addressing the complexity and variability of battery thermal runaway. These challenges include the limited heat dissipation capability of passive thermal management, the high energy consumption of active thermal management, and the ongoing optimization of material improvement methods. This paper systematically examines the mechanisms through which three main triggers—mechanical abuse, thermal abuse, and electrical abuse—affect the thermal runaway of lithium-ion batteries. It also reviews the advantages and limitations of passive and active thermal management techniques, battery management systems, and material improvement strategies for enhancing the thermal stability of batteries. Additionally, a comparison of the principles, characteristics, and innovative examples of various thermal management technologies is provided in tabular form. The study aims to offer a theoretical foundation and practical guidance for optimizing lithium-ion battery thermal management technologies, thereby promoting their development for high-safety and high-reliability applications.

A high-fat diet (HFD) contributes to various metabolic disorders and obesity, which are major contributors to cardiovascular disease. As an essential regulator for heart homeostasis, cardiac resident macrophages may go awry and contribute to cardiac pathophysiology upon HFD. Thus, to better understand how HFD induced cardiac dysfunction, this study intends to explore the transcriptional and functional changes in cardiac resident macrophages of HFD mice. C57BL/6J female mice that were 6 weeks old were fed with HFD or normal chow diet (NCD) for 16 weeks. After an evaluation of cardiac functions by echocardiography, mouse hearts were harvested and cardiac resident CCR2 macrophages were sorted, followed by Smart sequencing. Bioinformatics analysis including GO, KEGG, and GSEA analyses were employed to elucidate transcriptional and functional changes. Hyperlipidemia and obesity were observed easily upon HFD. The mouse hearts also displayed more severe fibrosis and diastolic dysfunction in HFD mice. Smart sequencing and functional analysis revealed metabolic dysfunctions, especially lipid-related genes and pathways. Besides this, antigen-presentation-related gene such as and inflammation, particularly for NF-κB signaling and complement cascades, underwent drastic changes in cardiac resident macrophages. GO cellular compartment analysis was also performed and showed specific organelle enrichment trends of the involved genes. Dysregulated metabolism intertwines with inflammation in cardiac resident macrophages upon HFD feeding in mice, and further research on crosstalk among organelles could shed more light on potential mechanisms.

Hyperlipidemia contributes to low-grade inflammation and abnormal immune response, which is putatively involved in the development of pre-eclampsia (PE). As components of innate immune system, complements play a critical role in regulating inflammation. However, how cell-autonomous complement changes and works in PE remains elusive. In the current study, we established L-NAME-induced mice to manifest PE-like symptoms. In presence of high-fat diet (HFD) feeding, the PE-like symptoms were considerably aggravated, as well as down-regulated complement C3 in HFD/L-NAME mice trophoblasts. To explore the effect of C3 in PE development, we generated C3 overexpression and knockdown cell (Swan.71 C3 and Swan.71 ΔC3 ) based on Swan.71, a trophoblast cell line. We found that Swan.71 C3 cells display promoted proliferation, migration and invasion capability and less secretion of anti-angiogenetic cytokines, while Swan.71 ΔC3 showed highly-activated NLRP3 inflammasome and pyroptosis, which was also noted in HFD/L-NAME placentas, highlighting the contributing role of inflammation to PE. Indeed, pro-inflammatory cytokines were increased in placentas from HFD/L-NAME mice. The similar trends of C3 in trophoblast from severe PE patients supported the contribution role of C3 to PE pathogenesis. Thus, our study provides evidence that cell-autonomous complement C3 regulates NLRP3 inflammasome activation upon HFD exposure, affecting trophoblast cell function in PE development. Cell-autonomous complement C3 regulates trophoblast cell function through inflammasome activation in preeclampsia.

The placenta, a temporary but essential organ for gestational support, undergoes intricate morphological and functional transformations throughout gestation. However, the spatiotemporal patterns of gene expression underlying placentation remain poorly understood. Utilizing Stereo-seq, we constructed a Mouse Placentation Spatiotemporal Transcriptomic Atlas (MPSTA) spanning from embryonic day (E) 7.5 to E14.5, which includes the transcriptomes of large trophoblast cells that were not captured in previous single-cell atlases. We defined four distinct strata of the ectoplacental cone, an early heterogeneous trophectoderm structure, and elucidated the spatial trajectory of trophoblast differentiation during early postimplantation stages before E9.5. Focusing on the labyrinth region, the interface of nutrient exchange in the mouse placenta, our spatiotemporal ligand–receptor interaction analysis unveiled pivotal modulators essential for trophoblast development and placental angiogenesis. We also found that paternally expressed genes are exclusively enriched in the placenta rather than in the decidual regions, including a cluster of genes enriched in endothelial cells that may function in placental angiogenesis. At the invasion front, we identified interface-specific transcription factor regulons, such as Atf3 , Jun , Junb , Stat6 , Mxd1 , Maff , Fos , and Irf7 , involved in gestational maintenance. Additionally, we revealed that maternal high-fat diet exposure preferentially affects this interface, exacerbating inflammatory responses and disrupting angiogenic homeostasis. Collectively, our findings furnish a comprehensive, spatially resolved atlas that offers valuable insights and benchmarks for future explorations into placental morphogenesis and pathology.

A novel multi-dimensional scenario forecast approach which can capture the dynamic temporal-spatial interdependence relation among the outputs of multiple wind farms is proposed. In the proposed approach, support vector machine (SVM) is applied for the spot forecast of wind power generation. The probability density function (PDF) of the SVM forecast error is predicted by sparse Bayesian learning (SBL), and the spot forecast result is corrected according to the error expectation obtained. The copula function is estimated using a Gaussian copula-based dynamic conditional correlation matrix regression (DCCMR) model to describe the correlation among the errors. And the multi-dimensional scenario is generated with respect to the estimated marginal distributions and the copula function. Test results on three adjacent wind farms illustrate the effectiveness of the proposed approach.

Recent advancements have broadened the application of photon filters based on Bragg gratings within optical communication networks and optical input/output interfaces. Traditional gratings, however, suffer from a fixed refractive index modulation distribution once manufactured, constraining their adaptability and flexibility. This study introduces a reconfigurable multi-channel photon filter on a silicon nitride on insulator platform. The filter incorporates an equivalent linearly chirped four-phase-shifted sampled Bragg grating with micro-heaters to enable thermo-optic tuning, facilitating programmable control over transmission spectral features. Experimental outcomes indicate the filter’s capability to seamlessly transition among single, dual, and quad-band configurations, as well as a band-stop mode, with independent tuning of each band. Moreover, optical frequency division multiplexing experiments using a 50 GHz semiconductor mode-locked laser have affirmed the filter’s tunability. In quad-band mode, band separations of 50, 100, and 150 GHz are achievable; in dual and single-band modes, band intervals extend from 150 to 250 GHz, allowing for precise single-wavelength selection. Featuring high tunability, minimal insertion losses, and superior signal side-mode suppression ratio, this filter structure supports the integration of programmable photonic devices into space optical communications, photonic integrated networks, and elastic optical networks.

Cardiovascular diseases are an array of age-related disorders, and accumulating evidence suggests a link between cardiac resident macrophages (CRMs) and the age-related disorders. However, how does CRMs alter with aging remains elusive. In the present study, aged mice (20 months old) have been employed to check for their cardiac structural and functional alterations, and the changes in the proportion of CRM subsets as well, followed by sorting of CRMs, including C-C Motif Chemokine Receptor 2 (CCR2) + and CCR2 – CRMs, which were subjected to Smart-Seq. Integrated analysis of the Smart-Seq data with three publicly available single-cell RNA-seq datasets revealed that inflammatory genes were drastic upregulated for both CCR2 + and CCR2 – CRMs with aging, but genes germane to wound healing were downregulated for CCR2 – CRMs, suggesting the differential functions of these two subsets. More importantly, inflammatory genes involved in damage sensing, complement cascades, and phagocytosis were largely upregulated in CCR2 – CRMs, implying the imbalance of inflammatory response upon aging. Our work provides a comprehensive framework and transcriptional resource for assessing the impact of aging on CRMs with a potential for further understanding cardiac aging.

The study aimed to develop and validate a nomogram for predicting sepsis-associated encephalopathy (SAE) in elderly patients with sepsis admitted to the intensive care unit (ICU). We conducted a retrospective study at the First Affiliated Hospital of Wenzhou Medical University. The least absolute shrinkage and selection operator (LASSO) regression was employed to identify characteristic predictors for SAE, and a nomogram was subsequently developed. The nomogram's performance was evaluated using receiver operating characteristic (ROC) curves, the concordance index (C-index), calibration curves, the Brier score, and decision curve analysis (DCA) to assess discrimination, calibration, and clinical utility. Internal validation was performed using the bootstrap resampling method. A total of 231 elderly sepsis patients were included in the study, among whom 66 were diagnosed with SAE. The study identified invasive mechanical ventilation (IMV), platelet count, white blood cell (WBC) count, glucose levels, lactate levels, and calcium levels as significant risk factors for SAE. The nomogram demonstrated an area under the curve (AUC) of 0.861, outperforming other predictive factors. The corrected C-index, determined through 500 bootstrap validations, was 0.842. Additionally, the calibration curve indicated strong agreement between predicted outcomes and actual observations. The Brier score of the prediction model was 0.139. Finally, DCA revealed that the nomogram had high clinical applicability. The prediction nomogram and online website demonstrated strong predictive performance for the occurrence of SAE in elderly patients with sepsis, which made the evaluation process of SAE more convenient and efficient.