Tuning triplet excitons and dynamic afterglow based on host-guest doping.

Designing persistent dual-band afterglow materials with thermally activated delayed fluorescence (TADF) and room temperature phosphorescence (RTP) contributed to solving the problems of homogenization and singularity in long afterglow materials. Here, six aryl acetonitrile (CBM) and aryl dicyanoaniline (AMBT) derivatives, used as host and guest materials respectively, were successfully designed and synthesized based on the isomerization effect. Among of them, 0.1 % m-CBM/p-AMBT showed the longest dual-band TADF (540 ms) and RTP lifetimes (721 ms), as well as persistent afterglow over 8 s, whose fluorescence (ΦFL), TADF (ΦT) and RTP (ΦP) quantum yields were 0.11, 0.06 and 0.22 in sequence. More interestingly, some doping systems constructed by CBM and AMBT series compounds showed persistent triple-band emissions composed of TADF, unimolecular and aggregated AMBT series compounds. What's more, ΦFL, ΦT and ΦP of 1 % o-AMBT@PMMA film were up to 0.17, 0.17, 0.23 in turn, with TADF, RTP and afterglow lifetimes of 606 ms, 727 ms, and 10 s respectively. TADF and RTP emission of CBM/AMBT series doping systems was attributed to host sensitized guest emission. Besides, the comparison displayed AMBT series compounds had bigger intensity ratios between TADF and RTP emission in PMMA films compared to in CBM series compounds. Finally, a series of data encryption were successfully constructed based on different afterglow lifetimes of the doping systems, and a dynamic anti-counterfeiting pattern was prepared by using different temperature responses of TADF and RTP emissions.

Biochemical analyses reveal new insights into RCAN1/Rcn1 inhibition of calcineurin.

Calcineurin is a serine/threonine protein phosphatase that is highly conserved from yeast to human and plays a critical role in many physiological processes. Regulators of calcineurin (RCANs) are a family of endogenous calcineurin regulators, which are capable of inhibiting the catalytic activity of calcineurin in vivo and in vitro. In this study, we first characterized the biochemical properties of yeast calcineurin and its endogenous regulator Rcn1, a yeast homolog of RCAN1. Our data show that Rcn1 inhibits yeast calcineurin toward pNPP substrate with a noncompetitive mode; and Rcn1 binds cooperatively to yeast calcineurin through multiple low-affinity interactions at several docking regions. Next, we reinvestigated the mechanism underlying the inhibition of mammalian calcineurin by RCAN1 using a combination of biochemical, biophysical, and computational methods. In contrast to previous observations, RCAN1 noncompetitively inhibits calcineurin phosphatase activity toward both pNPP and phospho-RII peptide substrates by targeting the enzyme active site in part. Re-analysis of previously reported kinetic data reveals that the RCAN1 concentrations used were too low to distinguish between the inhibition mechanisms [Chan B et al. (2005) Proc Natl Acad Sci USA 102, 13075]. The results presented in this study provide new insights into the interaction between calcineurin and RCAN1/Rcn1.

Structure Optimization of c-Jun N-terminal Kinase 1 Inhibitors for Treating Idiopathic Pulmonary Fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a progressive and lethal lung disease with an elusive etiology. Aberrant activation of c-Jun N-terminal kinase 1 (JNK1) has been implicated in its pathogenesis. Through a combination of structure-based drug design and structure-activity relationship (SAR) optimization, a series of pyrimidine-2,4-diamine scaffold derivatives have been developed as potent JNK1 inhibitors. Compound E1 was identified with low nanomolar JNK1 inhibitory potency (IC50 = 2.7 nM). The introduction of a dimethylamine side chain has significantly enhanced the ability of E1 to inhibit c-Jun phosphorylation, surpassing the clinical candidate CC-90001. Molecular dynamics simulations revealed a binding free energy of -50.46 kcal/mol for E1. Moreover, E1 displayed satisfactory pharmacokinetic properties, with a bioavailability of 69% in rats. Furthermore, compound E1 exerted significant antifibrotic effects in a bleomycin-induced IPF mouse model and prevented a TGF-ß-induced epithelial-to-mesenchymal transition in vitro. These findings position E1 as a promising lead for further drug development targeting IPF.

NCI's Proteomic Data Commons: A Cloud-Based Proteomics Repository Empowering Comprehensive Cancer Analysis through Cross-Referencing with Genomic and Imaging Data.

Proteomics has emerged as a powerful tool for studying cancer biology, developing diagnostics, and therapies. With the continuous improvement and widespread availability of high-throughput proteomic technologies, the generation of large-scale proteomic data has become more common in cancer research, and there is a growing need for resources that support the sharing and integration of multi-omics datasets. Such datasets require extensive metadata including clinical, biospecimen, and experimental and workflow annotations that are crucial for data interpretation and reanalysis. The need to integrate, analyze, and share these data has led to the development of NCI's Proteomic Data Commons (PDC), accessible at https://pdc.cancer.gov. As a specialized repository within the NCI Cancer Research Data Commons (CRDC), PDC enables researchers to locate and analyze proteomic data from various cancer types and connect with genomic and imaging data available for the same samples in other CRDC nodes. Presently, PDC houses annotated data from more than 160 datasets across 19 cancer types, generated by several large-scale cancer research programs with cohort sizes exceeding 100 samples (tumor and associated normal when available). In this article, we review the current state of PDC in cancer research, discuss the opportunities and challenges associated with data sharing in proteomics, and propose future directions for the resource. SIGNIFICANCE: The Proteomic Data Commons (PDC) plays a crucial role in advancing cancer research by providing a centralized repository of high-quality cancer proteomic data, enriched with extensive clinical annotations. By integrating and cross-referencing with complementary genomic and imaging data, the PDC facilitates multi-omics analyses, driving comprehensive insights, and accelerating discoveries across various cancer types.

Identification and function characterization of NcAP2XII-4 in Neospora caninum.

BACKGROUND: Neospora caninum is a protozoan parasite in the Apicomplexa controlled by complex signaling pathways. Transcriptional control, an important way to regulate gene expression, has been almost absent in the N. caninum life process. However, to date, research on the transcriptional regulation of the AP2 family factors in N. caninum has been extremely limited. A prior study demonstrated that removing rhoptry protein 5 (ROP5), a significant virulence factor, resulted in abnormal expression levels of predicted NcAP2XII-4 in N. caninum, suggesting that the factor may regulate the function of ROP5. This study aimed to identify NcAP2XII-4 and its function in transcriptional regulation. METHODS: The NcAP2XII-4 gene was identified by analyzing the N. caninum genome. A polyclonal antibody against the protein was prepared and purified, and its expression and localization in the parasite were detected using western blot (WB) and immunofluorescence assay (IFA). The ΔNcAP2XII-4 strain was constructed from the Nc1 strain using CRISPR/Cas9 to study its effect on the growth and development of N. caninum, and DAP-Seq and electrophoretic mobility shift assay (EMSA) were used to verify the transcriptional regulatory functions of the gene. RESULTS: Bioinformatic analysis showed that NcAP2XII-4 consists of 11,976 bp and encodes 3991 amino acids, with a predicted molecular mass of 410 kDa. The protein has two AP2 domains, 1207aa-1251aa and 3453aa-3500aa, and is predicted to be located in the nucleus. The results of PCR, WB, and IFA were in accordance with the bioinformatics analysis. ΔNcAP2XII-4 was successfully constructed, but the strain could not be released and ultimately succumbed within parasitophorous vacuoles (PVs). Plaque assays demonstrated that parasites lacking this gene could not form plaques. One motif was successfully identified using DAP-Seq technique. Two prokaryotic expression vectors containing the AP2 domain of NcAP2XII-4 were successfully constructed, and two prokaryotic expression proteins, AP2-D1 and AP2-D2, and ROP5 biotinylated probes were prepared. Using EMSA, NcAP2XII-4 was shown to regulate ROP5 transcription by binding to its promoter. CONCLUSIONS: NcAP2XII-4 is an essential gene in N. caninum. This study provides a foundation for further research on transcriptional regulation in N. caninum and identifies a new candidate factor for the development of vaccines against N. caninum.

A 25-Year Retrospective of the Use of AI for Diagnosing Acute Stroke: Systematic Review.

BACKGROUND: Stroke is a leading cause of death and disability worldwide. Rapid and accurate diagnosis is crucial for minimizing brain damage and optimizing treatment plans. OBJECTIVE: This review aims to summarize the methods of artificial intelligence (AI)-assisted stroke diagnosis over the past 25 years, providing an overview of performance metrics and algorithm development trends. It also delves into existing issues and future prospects, intending to offer a comprehensive reference for clinical practice. METHODS: A total of 50 representative articles published between 1999 and 2024 on using AI technology for stroke prevention and diagnosis were systematically selected and analyzed in detail. RESULTS: AI-assisted stroke diagnosis has made significant advances in stroke lesion segmentation and classification, stroke risk prediction, and stroke prognosis. Before 2012, research mainly focused on segmentation using traditional thresholding and heuristic techniques. From 2012 to 2016, the focus shifted to machine learning (ML)-based approaches. After 2016, the emphasis moved to deep learning (DL), which brought significant improvements in accuracy. In stroke lesion segmentation and classification as well as stroke risk prediction, DL has shown superiority over ML. In stroke prognosis, both DL and ML have shown good performance. CONCLUSIONS: Over the past 25 years, AI technology has shown promising performance in stroke diagnosis.

New species of Diaporthe (Diaporthaceae, Diaporthales) from Bauhiniavariegata in China.

Diaporthe species are known as endophytes, saprobes and pathogens infecting a wide range of plants and resulting in important crop diseases. In the present study, four strains of Diaporthe were obtained from diseased leaves of Bauhiniavariegata in Guangdong Province, China. Phylogenetic analyses were conducted to identify these strains using five gene regions: internal transcribed spacer (ITS), calmodulin (cal), histone H3 (his3), translation elongation factor 1-α (tef1) and ß-tubulin (tub2). The results combined with morphology revealed two new species of Diaporthe named D.bauhiniicola in D.arecae species complex and D.guangzhouensis in D.sojae species complex.

Human intermediate prostate cancer stem cells contribute to the initiation and development of prostate adenocarcinoma.

BACKGROUND: Intermediate cells are present in the early stages of human prostate development and adenocarcinoma. While primary cells isolated from benign human prostate tissues or tumors exhibit an intermediate phenotype in vitro, they cannot form tumors in vivo unless genetically modified. It is unclear about the stem cell properties and tumorigenicity of intermediate cells. METHODS: We developed a customized medium to culture primary human intermediate prostate cells, which were transplanted into male immunodeficient NCG mice to examine tumorigenicity in vivo. We treated the cells with different concentrations of dihydrotestosterone (DHT) and enzalutamide in vitro and surgically castrated the mice after cell transplantation in vivo. Immunostaining, qRT-PCR, RNA sequencing, and western blotting were performed to characterize the cells in tissues and 2D and 3D cultures. RESULTS: We found intermediate cells expressing AR+PSA+CK8+CK5+ in the luminal compartment of human prostate adenocarcinoma by immunostaining. We cultured the primary intermediate cells in vitro, which expressed luminal (AR+PSA+CK8+CK18+), basal (CK5+P63+), intermediate (IVL+), and stem cell (CK4+CK13+PSCA+SOX2+) markers. These cells resisted castration in vitro by upregulating the expression of AR, PSA, and proliferation markers KI67 and PCNA. The intermediate cells had high tumorigenicity in vivo, forming tumors in immunodeficient NCG mice in a month without any genetic modification or co-transplantation with embryonic urogenital sinus mesenchyme (UGSM) cells. We named these cells human castration-resistant intermediate prostate cancer stem cells or CriPCSCs and defined the xenograft model as patient primary cell-derived xenograft (PrDX). Human CriPCSCs resisted castration in vitro and in vivo by upregulating AR expression. Furthermore, human CriPCSCs differentiated into amplifying adenocarcinoma cells of luminal phenotype in PrDX tumors in vivo, which can dedifferentiate into CriPCSCs in vitro. CONCLUSIONS: Our study identified and established methods for culturing human CriPCSCs, which had high tumorigenicity in vivo without any genetic modification or UGSM co-transplantation. Human CriPCSCs differentiated into amplifying adenocarcinoma cells of luminal phenotype in the fast-growing tumors in vivo, which hold the potential to dedifferentiate into intermediate stem cells. These cells resisted castration by upregulating AR expression. The human CriPCSC and PrDX methods hold significant potential for advancing prostate cancer research and precision medicine.

Impact of ovalbumin allergy on oral and gut microbiome dynamics in 6-week-old BALB/c mice.

Background: The gut microbiota is known to have a significant impact on the development of food allergy, and several recent studies have suggested that both oral microbiota, which first come into contact with allergenic foods, may have a profound influence on the development of food allergy. Methods: In this study, we have established an ovalbumin-sensitive mice model by utilizing ovalbumin as a sensitizing agent. Subsequently, we performed a comprehensive analysis of the gut and oral microbiota in ovalbumin-sensitive mice and the control mice using full-length 16S rRNA sequencing analysis. Results: Interestingly, both the gut and oral microbiota of ovalbumin-sensitized mice exhibited significant dysbiosis. The relative abundance of s__Lactobacillus_intestinalis in the gut microbiota of ovalbumin-sensitive mice exhibited a significant decrease, whereas the abundance of s__Agrobacterium_radiobacter and s__Acinetobacter_sp__CIP_56_2 displayed a significant increase. Furthermore, the relative abundance of s__unclassified_g__Staphylococcus, s__Streptococcus_hyointestinalis, and s__unclassified_g__Dechloromonas in the oral microbiota of ovalbumin-sensitive mice revealed a significant decrease. In contrast, the abundance of 63 other species, including s__Proteiniclasticum_ruminis, s__Guggenheimella_bovis, and s__Romboutsia_timonensis, demonstrated a significant increase. The random forest classifier achieved the best accuracy in predicting the outcome of food allergy using three gut and three oral biomarkers, with accuracies of 94.12 and 100%, respectively. Based on the predictions of the PICRUSt2 analysis, the only consistent finding observed across multiple samples from both the groups of mice was a significant up-regulation of the nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway in the ovalbumin-sensitized mice. Conclusion: Our study demonstrates that ovalbumin-sensitized mice experience substantial alterations in both gut and oral microbial composition and structure, and specific strains identified in this study may serve as potential biomarkers for food allergy screening. Moreover, our findings highlight that the oral environment, under the same experimental conditions, exhibited greater precision in detecting a larger number of species. Additionally, it is worth noting that the NOD-like receptor signaling pathway plays a vital role in the pathogenesis of OVA (ovalbumin)-induced allergy. These findings will generate novel concepts and strategies in the realm of food allergy prevention and treatment.

Elevating water table reduces net ecosystem carbon losses from global drained wetlands.

Drained wetlands are thought to be carbon (C) source hotspots, and rewetting is advocated to restore C storage in drained wetlands for climate change mitigation. However, current assessments of wetland C balance mainly focus on vertical fluxes between the land and atmosphere, frequently neglecting lateral carbon fluxes and land-use effects. Here, we conduct a global synthesis of 893 annual net ecosystem C balance (NECB) measures that include net ecosystem exchange of CO2, along with C input via manure fertilization, and C removal through biomass harvest or hydrological exports of dissolved organic and inorganic carbon, across wetlands of different status and land uses. We find that elevating water table substantially reduces net ecosystem C losses, with the annual NECB decreasing from 2579 (95% interval: 1976 to 3214) kg C ha-1 year-1 in drained wetlands to -422 (-658 to -176) kg C ha-1 year-1 in natural wetlands, and to -934 (-1532 to -399) kg C ha-1 year-1 in rewetted wetlands globally. Climate, land-use history, and time since water table changes introduce variabilities, with drainage for (sub)tropical agriculture or forestry uses showing high annual C losses, while the net C losses from drained wetlands can continue to affect soil C pools for several decades. Rewetting all types of drained wetlands is needed, particularly for those formerly agriculture-used (sub)tropical wetlands where net ecosystem C losses can be largely reduced. Our findings suggest that elevating water table is an important initiative to reduce C losses in degraded wetlands, which could contribute to policy decisions for managing wetlands to enhance their C sequestration.

Blocking the PD-1 signal transduction by occupying the phosphorylated ITSM recognition site of SHP-2.

Targeting the PD-1/PD-L1 axis with small-molecular inhibitors is a promising approach for immunotherapy. Here, we identify a natural pentacyclic triterpenoid, Pygenic Acid A (PA), as a PD-1 signaling inhibitor. PA exerts anti-tumor activity in hPD-1 knock-in C57BL/6 mice and enhances effector functions of T cells to promote immune responses by disrupting the PD-1 signaling transduction. Furthermore, we identify SHP-2 as the direct molecular target of PA for inhibiting the PD-1 signaling transduction. Subsequently, mechanistic studies suggest that PA binds to a new druggable site in the phosphorylated PD-1 ITSM recognition site of SHP-2, inhibiting the recruitment of SHP-2 by PD-1. Taken together, our findings demonstrate that PA has a potential application in cancer immunotherapy and occupying the phosphorylated ITSM recognition site of SHP-2 may serve as an alternative strategy to develop PD-1 signaling inhibitors. In addition, our success in target recognition provides a paradigm of target identification and confirmation for natural products.

Diosgenin derivative ML5 attenuates MPTP-induced neuronal impairment via regulating AMPK/PGC-1α-mediated mitochondrial biogenesis and fusion/fission.

OBJECTIVE: The aim of the present study was to assess the therapeutic impact of diosgenin derivative ML5 on Parkinson's disease (PD) and explore the mechanism underlying mitochondrial biogenesis and fusion/fission. METHODS: We established 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced mouse models and N-methyl-4-phenylpyridinium iodide (MPP+)-induced cell models of PD. The pole test and forced swimming test were used to detect the motor coordination and depressive symptoms in mice. The influence of ML5 on dopaminergic neuronal injury was investigated. Meanwhile, adenosine triphosphate (ATP) content, mitochondrial membrane potential (MMP), and reactive oxygen species (ROS) production were measured to evaluate mitochondrial function. Confocal and transmission electron microscopy were used to detect mitochondrial morphology of cell. The expression of mitochondrial biogenesis-related proteins was measured by Western blotting. RESULTS: The administration of ML5 showed the neuroprotection against MPTP-induced damage in vivo and in vitro. The levels of ATP, MMP, and ROS were restored after ML5 administration. In addition, we observed that ML5 preserved the mitochondrial network morphology and inhibited mitochondrial fission. Furthermore, the amelioration of mitochondrial dysfunction was mediated by enhancing 5'-monophosphate-activated protein kinase (AMPK) and peroxisome proliferators-activated receptor γ coactivator-l alpha (PGC-1α) expression, which activated its downstream modulators leading to the enhancing of mitochondrial biogenesis and the balance of mitochondrial fusion/fission. CONCLUSION: ML5 can protect the PD models against MPTP/MPP+-induced mitochondrial dysfunction and neuronal injury via promoting AMPK/PGC-1α signaling activation and be used as a therapeutic drug for PD treatment.

Factors associated with stigma in patients undergoing hemodialysis: a meta-analysis and systematic review.

BACKGROUND: Patients with hemodialysis (HD) frequently encounter stigma, which impacts their social network and adherence to treatment, increasing their risk of depression and lowering their quality of life. The factors associated with stigma among patients with HD remain poorly understood due to insufficient evidence. To fill this gap, this meta-analysis was conducted. METHODS: We carried out a thorough literature review in both Chinese and English databases like China National Knowledge Infrastructure (CNKI), Wan Fang Knowledge Data Service Platform, PubMed, Embase, PsycINFO, CINAHL (Cumulative Index to Nursing and Allied Health Literature) and Web of Science. We included literature up to May 25, 2024, focusing on the levels and factors related to stigma in HD patients. Data extraction and quality assessment of the included literature were separately carried out by two researchers, who also independently did the literature screening. Data analysis was carried out using Stata 15.1 software. The possible sources of heterogeneity were explored by sensitivity analysis and subgroup analysis, and the robustness of the results was evaluated. RESULTS: A total of 12 papers were included, and the quality of these papers was evaluated as moderate or above. The findings of the meta-analysis demonstrated that the pooled stigma mean score was 59.30 [95% (Confidence interval) CI: 55.62 to 62.97]. Per capita monthly family income [MD (Mean Deviation) =4.95, 95% CI (1.55 to 8.35), P=0.004], residence [MD=-4.66, 95% CI (-6.96 to -2.36), P<0.001], complications [MD=4.76, 95% CI (0.92 to 8.61), P=0.015], family function [Z=-0.29, 95% CI (-0.38 to -0.21), P<0.001], self-efficacy [Z=-0.37, 95% CI (-0.48 to -0.26), P<0.001], levels of social support [Z=-0.35, 95% CI (-0.45 to -0.25), P<0.001], and levels of psychological distress [Z=0.59, 95% CI (0.26 to 0.91), P<0.001] were all significant factors contributing to stigma in patients undergoing HD. CONCLUSION: Healthcare professionals should pay attention to the early assessment of stigma in patients with HD, implement personalized interventions targeting related factors, and promote effective coping strategies for managing the disease.

Research on prediction of human oral bioavailability of drugs based on improved deep forest.

Human oral bioavailability is a crucial factor in drug discovery. In recent years, researchers have constructed a variety of different prediction models. However, given the limited size of human oral bioavailability data sets, the challenge of making accurate predictions with small sample sizes has become a critical issue in the field. The deep forest model, with its adaptively determinable number of cascade levels, can perform exceptionally well even on small-scale data. However, the original deep forest suffers unbalanced multi-grained scanning process and premature stopping of cascade forest training. In this paper, we propose a human oral bioavailability predict method based on an improved deep forest, called balanced multi-grained scanning mapping cascade forest (bgmc-forest). Firstly, the mordred descriptor method is selected to feature extraction, then enhanced features are obtained by the improved balanced multi-grained scanning, which solves the problem of missing features at both ends. And finally, the prediction results are obtained by feature mapping cascaded forests, which is based on principal component analysis and cascade forests, ensures the effectiveness of the cascade forest. The superiority of the model constructed in this paper is demonstrated through comparative experiments, while the effectiveness of the improved module is verified through ablation experiments. Finally the decision-making process of the model is explained by the shapley additive explanations interpretation algorithm.

AIM2 Deficiency Alleviates Cardiac Inflammation and Hypertrophy in HFD/STZ-Induced Diabetic Mice by Inhibiting the NLRC4/IRF1 Signaling Pathway.

Absent in melanoma 2(AIM2) exacerbates atherosclerosis by inflammasome assembly. However, AIM2-mediated inflammation in diabetic cardiomyopathy remains incompletely understood. Here we investigate the role of AIM2 in high glucose (HG)- and diabetes-induced inflammatory cardiomyopathy. By RNA-seq, we found that AIM2 were significantly upregulated in HG-induced macrophages, upregulation of AIM2 in cardiac infiltrating macrophages was confirmed in a high-fat diet (HFD)/streptozotocin (STZ)-induceddiabetic mouse model . Therefore, AIM2 knockout mice were constructed. Compared to WT mice, HFD/STZ-induced cardiac hypertrophy and dysfunction were significantly improved in AIM2-/- mice, despite no changes in blood glucose and body weight. Further, AIM2 deficiency inhibited cardiac recruitment of M1-macrophages and cytokine production. Mechanistically, AIM2-deficient macrophgaes reduced IL-1ß and TNF-α secretion, which impaired the NLRC4/IRF1 signaling in cardiomyocytes, and reduced further recruitment of macrophages, attenuated cardiac inflammation and hypertrophy, these effects were confirmed by silencing IRF1 in WT mice, and significantly reversed by overexpression of IRF1 in AIM2-/- mice. Taken together, our findings suggest that AIM2 serves as a novel target for the treatment of diabetic cardiomyopathy.

Prostate cancer subtyping and differential methylation analysis based on the ETS family of transcription factors fusion genes.

Prostate cancer (PCa) is a highly heterogeneous disease, encompassing various molecular and clinical pathological subtypes. Fusion genes play a facilitating role in the occurrence and progression of PCa. We categorized PCa samples into the ETS family of transcription factors fusion positive and fusion negative subtypes based on fusion genes. This subtyping method is closely related to the epigenomic DNA methylation profiles of PCa, with each sample cluster including more than 85% of the patients. We conducted an analysis of the distribution of the ETS family fusion genes on chromosomes, fusion modes within reading frames, and predictions of structural domains. Among these, the highest frequency of the ETS family related fusion genes occurred on chromosome 21. Compared to the parental genes, fusion genes exhibited new structural domains, such as IG_like, and the most common fusion mode was out-of-frame fusion. The correlation between the methylation levels of hypermethylated CpG sites and the expression levels of their corresponding mRNAs indicates that CD8A and B3GNT5 (with correlations of - 0.388 and - 0.253, respectively) could serve as potential prognostic markers for PCa.

Prioritizing test cases for deep learning-based video classifiers.

The widespread adoption of video-based applications across various fields highlights their importance in modern software systems. However, in comparison to images or text, labelling video test cases for the purpose of assessing system accuracy can lead to increased expenses due to their temporal structure and larger volume. Test prioritization has emerged as a promising approach to mitigate the labeling cost, which prioritizes potentially misclassified test inputs so that such inputs can be identified earlier with limited time and manual labeling efforts. However, applying existing prioritization techniques to video test cases faces certain limitations: they do not account for the unique temporal information present in video data. Unlike static image datasets that only contain spatial information, video inputs consist of multiple frames that capture the dynamic changes of objects over time. In this paper, we propose VRank, the first test prioritization approach designed specifically for video test inputs. The fundamental idea behind VRank is that video-type tests with a higher probability of being misclassified by the evaluated DNN classifier are considered more likely to reveal faults and will be prioritized higher. To this end, we train a ranking model with the aim of predicting the probability of a given test input being misclassified by a DNN classifier. This prediction relies on four types of generated features: temporal features (TF), video embedding features (EF), prediction features (PF), and uncertainty features (UF). We rank all test inputs in the target test set based on their misclassification probabilities. Videos with a higher likelihood of being misclassified will be prioritized higher. We conducted an empirical evaluation to assess the performance of VRank, involving 120 subjects with both natural and noisy datasets. The experimental results reveal VRank outperforms all compared test prioritization methods, with an average improvement of 5.76% ∼ 46.51% on natural datasets and 4.26% ∼ 53.56% on noisy datasets.

Ebronucimab in Chinese patients with hypercholesterolemia---A randomized double-blind placebo-controlled phase 3 trial to evaluate the efficacy and safety of ebronucimab.

Randomized clinical trials (RCTs) of PCSK9 monoclonal antibody(mAb) specifically for Chinese patients have been limited. This multi-center RCT is to clarify the efficacy and safety of a novel mAb, Ebronucimab, in Chinese patients. Patients diagnosed with primary hypercholesterolemia, including Heterozygous Familial Hypercholesterolemia, or mixed dyslipidemia, were categorized by ASCVD risk and randomly assigned at a ratio of 2:1:2:1 to receive Ebronucimab 450 mg or matching placebo every 4 weeks (Q4W), or Ebronucimab 150 mg or matching placebo every 2 weeks (Q2W). The primary outcome was the percentage change of LDL-C from baseline to week 12 for all groups. The least squares mean reduction difference (95 %CI) in LDL-C from baseline to week 12 of Ebronucimab 450 mg Q4W and Ebronucimab 150 mg Q2W groups versus the placebo group was -59.13 (-64.103, -54.153) (Adjusted p<0.0001) and -60.43 (-65.450, -55.416) (Adjusted p<0.0001), respectively. Meanwhile, the Ebronucimab group exhibited notably high rates in reaching LDL-C goals of each cardiovascular risk stratification. In addition, Ebronucimab effectively improved other lipid panel. During the double-blind treatment period, relatively frequently reported adverse events (AEs) were injection site reactions (ISR), urinary tract infection, and hyperuricemia (Incidence rate are 6.9 %, 4.8 % and 3.5 %). Among treatment-associated AEs, only injection site reactions (ISR) occurred more in the dose groups. In conclusion, Ebronucimab, with either 450 mg Q4W or 150 mg Q2W doses, demonstrated significant efficacy in lowering serum LDL-C level with a favorable safety and immunogenicity profile among hypercholesterolemic patients.