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Phylogenetics has been foundational to SARS-CoV-2 research and public health policy, assisting in genomic surveillance, contact tracing, and assessing emergence and spread of new variants. However, phylogenetic analyses of SARS-CoV-2 have often relied on tools designed for de novo phylogenetic inference, in which all data are collected before any analysis is performed and the phylogeny is inferred once from scratch. SARS-CoV-2 data sets do not fit this mold. There are currently over 14 million sequenced SARS-CoV-2 genomes in online databases, with tens of thousands of new genomes added every day. Continuous data collection, combined with the public health relevance of SARS-CoV-2, invites an "online" approach to phylogenetics, in which new samples are added to existing phylogenetic trees every day. The extremely dense sampling of SARS-CoV-2 genomes also invites a comparison between likelihood and parsimony approaches to phylogenetic inference. Maximum likelihood (ML) and pseudo-ML methods may be more accurate when there are multiple changes at a single site on a single branch, but this accuracy comes at a large computational cost, and the dense sampling of SARS-CoV-2 genomes means that these instances will be extremely rare because each internal branch is expected to be extremely short. Therefore, it may be that approaches based on maximum parsimony (MP) are sufficiently accurate for reconstructing phylogenies of SARS-CoV-2, and their simplicity means that they can be applied to much larger data sets. Here, we evaluate the performance of de novo and online phylogenetic approaches, as well as ML, pseudo-ML, and MP frameworks for inferring large and dense SARS-CoV-2 phylogenies. Overall, we find that online phylogenetics produces similar phylogenetic trees to de novo analyses for SARS-CoV-2, and that MP optimization with UShER and matOptimize produces equivalent SARS-CoV-2 phylogenies to some of the most popular ML and pseudo-ML inference tools. MP optimization with UShER and matOptimize is thousands of times faster than presently available implementations of ML and online phylogenetics is faster than de novo inference. Our results therefore suggest that parsimony-based methods like UShER and matOptimize represent an accurate and more practical alternative to established ML implementations for large SARS-CoV-2 phylogenies and could be successfully applied to other similar data sets with particularly dense sampling and short branch lengths.

MOTIVATION: Identifying and tracking recombinant strains of SARS-CoV-2 is critical to understanding the evolution of the virus and controlling its spread. But confidently identifying SARS-CoV-2 recombinants from thousands of new genome sequences that are being shared online every day is quite challenging, causing many recombinants to be missed or suffer from weeks of delay in being formally identified while undergoing expert curation. RESULTS: We present RIVET-a software pipeline and visual platform that takes advantage of recent algorithmic advances in recombination inference to comprehensively and sensitively search for potential SARS-CoV-2 recombinants and organize the relevant information in a web interface that would help greatly accelerate the process of identifying and tracking recombinants. AVAILABILITY AND IMPLEMENTATION: RIVET-based web interface displaying the most updated analysis of potential SARS-CoV-2 recombinants is available at https://rivet.ucsd.edu/. RIVETs frontend and backend code is freely available under the MIT license at https://github.com/TurakhiaLab/rivet and the documentation for RIVET is available at https://turakhialab.github.io/rivet/. The inputs necessary for running RIVETs backend workflow for SARS-CoV-2 are available through a public database maintained and updated daily by UCSC (https://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/UShER_SARS-CoV-2/).

Abstract Hepatocellular carcinoma (HCC) is a significant global health challenge. The activation of autophagy plays an essential role in promoting the proliferation and survival of cancer cells. However, the upstream regulatory network and mechanisms governing autophagy in HCC remain unclear. This study demonstrated that histone deacetylase 2 (HDAC2) regulates autophagy in HCC. Its expression was elevated in HCC tissues, and high HDAC2 expression was strongly associated with poor prognosis in individuals with HCC. Integrated in vitro and in vivo investigations confirmed that HDAC2 promotes autophagy and autophagy-related malignant progression in HCC. Mechanistically, HDAC2 bound specifically to the lysosome-associated protein transmembrane 4-β (LAPTM4B) promoter at four distinct binding sites, enhancing its transcriptional activation and driving autophagy-related malignant progression in HCC. These findings establish LAPTM4B as a direct target gene of HDAC2. Furthermore, the selective inhibitor of HDAC2 effectively alleviated the malignant development of HCC. In addition, multivariate Cox regression analysis of 105 human HCC samples revealed that HDAC2 expression is an independent predictor of HCC prognosis. This study underscores the crucial role of the HDAC2-LAPTM4B axis in regulating autophagy in the malignant evolution of HCC and highlights the potential of targeting HDAC2 to prevent and halt the malignant progression of HCC.

BackgroundBreast cancer, despite significant advancements in treatment, remains a major cause of cancer-related deaths among women. Immunotherapy, an emerging therapeutic strategy, offers promise for better outcomes, particularly through the modulation of immune functions. Glioma-Associated Oncogene Homolog 1 (GLI1), a transcription factor implicated in cancer biology, has shown varying roles in different cancers. However, its immunoregulatory functions in breast invasive carcinoma (BRCA) remain elusive. The current study aimed to unravel the expression patterns and immune-regulatory roles of GLI1 in BRCA.MethodsUtilizing multiple bioinformatic platforms (TIMER2.0, GEPIA2, and R packages) based on The Cancer Genome Atlas (TCGA) and/or Genotype-Tissue Expression (GTEx) databases, we analyzed the expression of GLI1 in BRCA and its pan-cancer expression profiles. We further validated these findings by conducting qPCR and immunohistochemical staining on clinical BRCA samples. Kaplan-Meier analysis and Cox proportional hazards regression were performed to assess the prognostic value of GLI1. Additionally, the association between GLI1 expression and immune infiltration within the tumor immune microenvironment (TMIE) was examined.ResultsThe findings reveal dysregulated expression of GLI1 in numerous cancers, with a significant decrease observed in BRCA. High GLI1 expression indicated better survival outcomes and was correlated with the age and stage of BRCA patients. GLI1 was involved in immune status, as evidenced by its strong correlations with immune and stromal scores and the infiltration levels of multiple immune cells. Meanwhile, GLI1 was co-expressed with multiple immune-related genes, and high GLI1 expression was associated with the activation of immune-related pathways, such as binding to proteasome and mismatch repair and retinol metabolism signaling pathways. Additionally, the differential expression of GLI1 may be related to the effect of immunotherapy on CTLA-4, PD-1, and other signals, and can effectively predict the immune efficacy.ConclusionOur study underscores the critical role of GLI1 in BRCA, both as a potential tumor suppressor and an immune regulator. The association between GLI1 expression and favorable prognosis suggests its potential as a prognostic biomarker and immunotherapeutic target in BRCA.

Background: The tumor microenvironment (TME) in lung adenocarcinoma (LUAD) influences tumor progression and immunosuppressive phenotypes through cell communication. We aimed to decipher cellular communication and molecular patterns in LUAD. Methods: We analyzed scRNA-seq data from LUAD patients in multiple cohorts, revealing complex cell communication networks within the TME. Using cell chat analysis and COSmap technology, we inferred LUAD's spatial organization. Employing the NMF algorithm and survival screening, we identified a cell communication interactions (CCIs) model and validated it across various datasets. Results: We uncovered intricate cell communication interactions within the TME, identifying three LUAD patient subtypes with distinct prognosis, clinical characteristics, mutation status, expression patterns, and immune infiltration. Our CCI model exhibited robust performance in prognosis and immunotherapy response prediction. Several potential therapeutic targets and agents for high CCI score patients with immunosuppressive profiles were identified. Machine learning algorithms pinpointed the novel candidate gene ITGB1 and validated its role in LUAD tumor phenotype in vitro. Conclusion: Our study elucidates molecular patterns and cell communication interactions in LUAD as effective biomarkers and predictors of immunotherapy response. Targeting cell communication interactions offers novel avenues for LUAD immunotherapy and prognostic evaluations, with ITGB1 emerging as a promising therapeutic target.

This review focuses on thermodynamic and physical parameters, synthesis methods, and reported phases of Magnesium (Mg) containing high-entropy alloys (HEAs). Statistical data of publications concerning Mg-containing HEAs were collected and analyzed. Data on the chemical elements included in Mg-containing HEAs, their theoretical end experimental densities, thermodynamic parameters, physical parameters, fabricated techniques and reported phases were also collected and discussed. On the basis of this information, a new classification for HEAs was proposed. It is also shown that the existing thermodynamic parameters cannot accurately predict the formation of a single phase solid solution for Mg-containing HEAs. The physical parameters of Mg-containing HEAs are within a wide range, and most of the synthesized Mg-containing HEAs have a complex multiphase structure.

ObjectiveTo review our single-institution experience in the surgical management of foramen magnum tumors via a far-lateral approach using an oblique straight incision.MethodsFrom October 2023 to January 2024, four cases of tumors in the foramen magnum area treated at the Capital Medical University-affiliated XuanWu hospital neurosurgery department were involved in this study. All cases were managed with a far-lateral approach using an oblique straight incision. We retrospectively reviewed the clinical and imaging data, as well as the surgical strategies employed.ResultsThree cases of foramen magnum meningiomas and one case of glioma of the ventral medulla. All cases underwent a far-lateral approach using an oblique straight incision; all cases had a gross total resection, and the wounds healed well without cerebral fluid leakage or scalp hydrops. Except for one case of right foramen magnum meningioma, which had dysphagia and pneumothorax, the other cases were without any postoperative complications.ConclusionA far-lateral approach using an oblique straight incision can preserve muscle integrity and minimize subcutaneous exposure, allowing for complete anatomical reduction of muscles. This craniectomy method is simple and replicable, making it worthy of further clinical practice.

Accurate and timely detection of recombinant lineages is crucial for interpreting genetic variation, reconstructing epidemic spread, identifying selection and variants of interest, and accurately performing phylogenetic analyses1-4. During the SARS-CoV-2 pandemic, genomic data generation has exceeded the capacities of existing analysis platforms, thereby crippling real-time analysis of viral evolution5. Here, we use a new phylogenomic method to search a nearly comprehensive SARS-CoV-2 phylogeny for recombinant lineages. In a 1.6 million sample tree from May 2021, we identify 589 recombination events, which indicate that around 2.7% of sequenced SARS-CoV-2 genomes have detectable recombinant ancestry. Recombination breakpoints are inferred to occur disproportionately in the 3' portion of the genome that contains the spike protein. Our results highlight the need for timely analyses of recombination for pinpointing the emergence of recombinant lineages with the potential to increase transmissibility or virulence of the virus. We anticipate that this approach will empower comprehensive real-time tracking of viral recombination during the SARS-CoV-2 pandemic and beyond.

Abstract Numerous studies have proven the critical role of macrophages in the renal fibrosis process. Notably, G Protein-coupled Estrogen Receptor 1 (GPER1), a novel estrogen receptor, has been shown to play a ubiquitous role in regulating macrophage activities and proinflammatory pathways. However, the precise role of GPER1 in macrophage-mediated renal fibrosis is unknown. In this study, we aimed to investigate the function of macrophage GPER1 in the UUO-induced renal fibrosis model. Compared to vehicle-treated ovariectomized (OVX) female and male unilateral ureteral obstruction (UUO) models, we observed that G-1 (GPER1 agonist)-treated OVX female and male UUO mice had fewer renal fibrotic lesions and less M1 and M2 macrophage infiltration in the kidney tissues. Conversely, Gper1 deletion in male UUO mice accelerated renal fibrosis and increased inflammation. In vitro studies also revealed that GPER1 activation reduced M0 macrophage polarization towards M1 or M2 phenotypes. The RNA-sequencing analysis and immunoblotting indicated that GPER1 activation was primarily involved in downregulating immune pathways activation and inactivating MAPK pathways. Tubular epithelial cells co-cultured with G-1-pretreated M1 macrophages exhibited fewer injuries and immune activation. In addition, fibroblasts co-cultured with G-1-pretreated M2 macrophages showed downregulated extracellular matrix expression. Overall, this is the first study to demonstrate the effect of GPER1 on macrophage-mediated renal fibrosis via inhibition of M1 and M2 macrophage activation. These findings indicate that GPER1 may be a promising therapeutic target for treating renal fibrosis.

Abstract Background Glioma is one of the leading types of brain tumor, but few etiologic factors of primary glioma have been identified. Previous observational research has shown an association between viral infection and glioma risk. In this study, we used Mendelian randomization (MR) analysis to explore the direction and magnitude of the causal relationship between viral infection and glioma. Methods We conducted a two-sample bidirectional MR analysis using genome-wide association study (GWAS) data. Summary statistics data of glioma were collected from the largest meta-analysis GWAS, involving 12,488 cases and 18,169 controls. Single-nucleotide polymorphisms (SNPs) associated with exposures were used as instrumental variables to estimate the causal relationship between glioma and twelve types of viral infections from corresponding GWAS data. In addition, sensitivity analyses were performed. Results After correcting for multiple tests and sensitivity analysis, we detected that genetically predicted herpes zoster (caused by Varicella zoster virus (VZV) infection) significantly decreased risk of low-grade glioma (LGG) development (OR = 0.85, 95% CI: 0.76–0.96, P = 0.01, FDR = 0.04). No causal effects of the other eleven viral infections on glioma and reverse causality were detected. Conclusions This is one of the first and largest studies in this field. We show robust evidence supporting that genetically predicted herpes zoster caused by VZV infection reduces risk of LGG. The findings of our research advance understanding of the etiology of glioma.

Soil salinity is a major limiting factor in soybean (Glycine max (L.) Merr.) yield in Xinjiang, China. Therefore, breeding soybean to tolerate highly saline soils is crucial to improve its yield. To explore the molecular mechanisms underlying the response of soybean to salt stress, we performed a comparative transcriptome analysis of root and leaf samples collected from two local soybean cultivars. The salt-tolerant cultivar ‘Xin No. 9’ (X9) showed higher photosynthetic activity than the salt-sensitive cultivar ‘Xinzhen No. 9’ (Z9) under salt stress. In total, we identified 13,180 and 13,758 differential expression genes (DEGs) in X9 and Z9, respectively, of which the number of DEGs identified in roots was much higher than that in leaves. We constructed the co-expression gene modules and conducted Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The results suggested there were distinct differences in the mechanisms of response to salt stress between the two soybean cultivars; i.e., the salt-tolerant cultivar X9 exhibited alterations in fundamental metabolism, whereas the salt-sensitive cultivar Z9 responded to salt stress mainly through the cell cycle. The possible crosstalk among phytohormone signaling, MAPK signaling, phenylpropanoid biosynthesis, starch and sucrose metabolism, and ribosome metabolism may play crucial roles in the response to salt stress in soybean. Our results offered a comprehensive understanding of the genes and pathways involved in the response to salt stress in soybean and provided valuable molecular resources for future functional studies and the breeding of soybean varieties with enhanced tolerance to salinity.

MotivationPhylogenetic tree optimization is necessary for precise analysis of evolutionary and transmission dynamics, but existing tools are inadequate for handling the scale and pace of data produced during the coronavirus disease 2019 (COVID-19) pandemic. One transformative approach, online phylogenetics, aims to incrementally add samples to an ever-growing phylogeny, but there are no previously existing approaches that can efficiently optimize this vast phylogeny under the time constraints of the pandemic.ResultsHere, we present matOptimize, a fast and memory-efficient phylogenetic tree optimization tool based on parsimony that can be parallelized across multiple CPU threads and nodes, and provides orders of magnitude improvement in runtime and peak memory usage compared to existing state-of-the-art methods. We have developed this method particularly to address the pressing need during the COVID-19 pandemic for daily maintenance and optimization of a comprehensive SARS-CoV-2 phylogeny. matOptimize is currently helping refine on a daily basis possibly the largest-ever phylogenetic tree, containing millions of SARS-CoV-2 sequences.Availability and implementationThe matOptimize code is freely available as part of the UShER package (https://github.com/yatisht/usher) and can also be installed via bioconda (https://bioconda.github.io/recipes/usher/README.html). All scripts we used to perform the experiments in this manuscript are available at https://github.com/yceh/matOptimize-experiments.Supplementary informationSupplementary data are available at Bioinformatics online.

BackgroundAmoxicillin (AMX) is among the most prescribed and the best tolerated antimicrobials worldwide. However, it can occasionally trigger severe cutaneous adverse reactions (SCAR) with a significant morbidity and mortality. The genetic factors that may be relevant to AMX-induced SCAR (AMX-SCAR) remain unclear. Identification of the genetic risk factor may prevent patients from the risk of AMX exposure and resume therapy with other falsely implicated drugs.MethodologyFour patients with AMX-SCAR, 1,000 population control and 100 AMX-tolerant individuals were enrolled in this study. Both exome-wide and HLA-based association studies were conducted. Molecular docking analysis was employed to simulate the interactions between AMX and risk HLA proteins.ResultsCompared with AMX-tolerant controls, a significant association of HLA-B*15:01 with AMX-SCAR was validated [odds ratio (OR) = 22.9, 95% confidence interval (CI): 1.68–1275.67; p = 7.34 × 10−3]. Moreover, 75% carriers of HLA-B*15:01 in four patients with AMX-SCAR, and the carrier frequency of 10.7% in 1,000 control individuals and 11.0% in 100 AMX-tolerant controls, respectively. Within HLA-B protein, the S140 present in all cases and demonstrated the strongest association with AMX-SCAR [OR = 53.5, p = 5.18 × 10−4]. Molecular docking results also confirmed the interaction between AMX and S140 of the HLA-B protein, thus eliminating the false-positive results during in association analysis.ConclusionOur findings suggest that genetic susceptibility may be involved in the development of AMX-SCAR in Han Chinese. However, whether the HLA-B variants observed in this study can be used as an effective genetic marker of AMX-induced SCAR still needs to be further explored in larger cohort studies and other ethnic populations.

Abstract The rational design of Z‐scheme heterojunction photosystems based on covalent organic frameworks (COFs) is a promising strategy for harnessing solar energy for hydrogen conversion. Herein, a direct Z‐scheme single‐atom photocatalyst based on COF and metal‐organic ring has been constructed through the supramolecular interactions of coral‐like COF (S‐COF) and photosensitized Pd2L2 type metal‐organic ring (MAC‐FA1). The MAC‐FA1/S‐COF heterojunction exhibits good light absorption, efficient charge separation and transfer, slow electron‐hole recombination, and highly dispersed Pd active sites, enabling an efficient and stable H2 evolution reaction. The optimized 4% MAC‐FA1/S‐COF achieves an H2 evolution rate of 100 mmol g−1 h−1 within 5 h and obtains a total accumulated turn‐over number relative to Pd (TONPd) of 437,685 within 20 h, far superior to S‐COF, MAC‐FA1, M‐5/S‐COF, Pd/S‐COF, and M‐5/Pd/S‐COF, which is one of the highest records among COF‐based photocatalysts for solar‐driven H2 evolution. This is the first work to incorporate photosensitized metal‐organic rings/cages into porous crystalline COFs to form a supramolecular Z‐scheme heterojunction, which has significant potential as a high‐performance photocatalyst for solar‐driven H2 production.

A redactable blockchain allows authorized individuals to remove or replace undesirable content, offering the ability to remove illegal or unwanted information. Access control is a mechanism that limits data visibility and ensures that only authorized users can decrypt and access encrypted information, playing a crucial role in addressing privacy concerns and securing the data stored on a blockchain. Redactability and access control are both essential components when implementing a regulated consortium blockchain in real-world situations to ensure the secure sharing of data while removing undesirable content. We propose a decentralized consortium blockchain system prototype that supports redactability and access control. Through the development of a prototype blockchain system, we investigate the feasibility of combining these approaches and demonstrate that it is possible to implement a redactable blockchain with access control in a consortium blockchain setting.