Activation of the hypoxia response in the aging cerebrovasculature protects males against cognitive impairment.

Alzheimer's disease (AD) is a neurodegenerative disorder with a distinct sex bias. Age-related vascular alterations, a hallmark of AD onset and progression, are consistently associated with sexual dimorphism. Here, we conducted an integrative meta-analysis of 335,803 single-nucleus transcriptomes and 667 bulk transcriptomes from the vascular system in AD and normal aging to address the underlying sex-dependent vascular aging in AD. All vascular cell types in male AD patients exhibited an activated hypoxia response and downstream signaling pathways including angiogenesis. The female AD vasculature is characterized by increased antigen presentation and decreased angiogenesis. We further confirmed that these sex-biased alterations in the cerebral vascular emerged and were primarily determined in the early stages of AD. Sex-stratified analysis of normal vascular aging revealed that angiogenesis and various stress-response genes were downregulated concurrently with female aging. Conversely, the hypoxia response increased steadily in males upon aging. An investigation of upstream driver transcription factors (TFs) revealed that altered communication between estrogen receptor alpha (ESR1) and hypoxia induced factors during menopause contributes to the inhibition of angiogenesis during normal female vascular aging. Additionally, inhibition of CREB1, a TF that targets estrogen, is also related to female AD. Overall, our study revealed a distinct cerebral vascular profile in females and males, and revealed novel targets for precision medicine therapy for AD.

Infrared Dim Small Target Detection Networks: A Review.

In recent years, with the rapid development of deep learning and its outstanding capabilities in target detection, innovative methods have been introduced for infrared dim small target detection. This review comprehensively summarizes public datasets, the latest networks, and evaluation metrics for infrared dim small target detection. This review mainly focuses on deep learning methods from the past three years and categorizes them based on the six key issues in this field: (1) enhancing the representation capability of small targets; (2) improving the accuracy of bounding box regression; (3) resolving the issue of target information loss in the deep network; (4) balancing missed detections and false alarms; (5) adapting for complex backgrounds; (6) lightweight design and deployment issues of the network. Additionally, this review summarizes twelve public datasets for infrared dim small targets and evaluation metrics used for detection and quantitatively compares the performance of the latest networks. Finally, this review provides insights into the future directions of this field. In conclusion, this review aims to assist researchers in gaining a comprehensive understanding of the latest developments in infrared dim small target detection networks.

Assessing parameter efficient methods for pre-trained language model in annotating scRNA-seq data.

Annotating cell types of single-cell RNA sequencing (scRNA-seq) data is crucial for studying cellular heterogeneity in the tumor microenvironment. Recently, large-scale pre-trained language models (PLMs) have achieved significant progress in cell-type annotation of scRNA-seq data. This approach effectively addresses previous methods' shortcomings in performance and generalization. However, fine-tuning PLMs for different downstream tasks demands considerable computational resources, rendering it impractical. Hence, a new research branch introduces parameter-efficient fine-tuning (PEFT). This involves optimizing a few parameters while leaving the majority unchanged, leading to substantial reductions in computational expenses. Here, we utilize scBERT, a large-scale pre-trained model, to explore the capabilities of three PEFT methods in scRNA-seq cell type annotation. Extensive benchmark studies across several datasets demonstrate the superior applicability of PEFT methods. Furthermore, downstream analysis using models obtained through PEFT showcases their utility in novel cell type discovery and model interpretability for potential marker genes. Our findings underscore the considerable potential of PEFT in PLM-based cell type annotation, presenting novel perspectives for the analysis of scRNA-seq data.

Exploring the mechanism of agarwood moxa smoke in treating sleep disorders based on GC-MS and network pharmacology.

Background: Agarwood moxibustion is a folk therapy developed by individuals of the Li nationality in China. There is evidence that agarwood moxa smoke (AMS) generated during agarwood moxibustion therapy can treat sleep disorders via traditional Chinese medicines' multiple target and pathway characteristics. However, the specific components and mechanisms involved have yet to be explored. Objective: GC-MS (Gas Chromatography-Mass Spectrometry) and network pharmacology were used to investigate AMS's molecular basis and mechanism in treating sleep deprivation. Method: GC-MS was used to determine the chemical composition of AMS; component target information was collected from TCMSP (Traditional Chinese Medicine Systems Pharmacology), PubChem (Public Chemical Database), GeneCards (Human Gene Database), and DisGeNet (Database of Genes and Diseases) were used to identify disease targets, and JVenn (Joint Venn) was used to identify the common targets of AMS and sleep disorders. STRING was used to construct a protein interaction network, Cytoscape 3.9.1 was used to build a multilevel network diagram of the "core components-efficacy targets-action pathways," the targets were imported into Metascape and DAVID for GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses and Autodock was used for molecular docking. This research used a network pharmacology methodology to investigate the therapeutic potential of Agarwood Moxa Smoke (AMS) in treating sleep problems. Examining the target genes and chemical constituents of AMS offers insights into the molecular processes and targets of the disease. Result: Nine active ingredients comprising anti-inflammatory substances and antioxidants, such as caryophyllene and p-cymene, found seven sleep-regulating signaling pathways and eight targets linked to sleep disorders. GC-MS was used to identify the 94 active ingredients in AMS, and the active ingredients had strong binding with the key targets. Key findings included active components with known medicinal properties, such as p-cymene, eucalyptol, and caryophyllene. An investigation of network pharmacology revealed seven signaling pathways for sleep regulation and eight targets linked to sleep disorders, shedding light on AMS's effectiveness in enhancing sleep quality. Conclusion: AMS may alleviate sleep disorders by modulating cellular and synaptic signaling, controlling hormone and neurotransmitter pathways, etc. Understanding AMS's material basis and mechanism of action provides a foundation for future research on treating sleep disorders with AMS. According to the study, Agarwood Moxa Smoke (AMS) may improve sleep quality by modifying cellular and synaptic signaling pathways for those who suffer from sleep problems. This might lead to the development of innovative therapies with fewer side effects.

Global optimization radiometric calibration method for an infrared system with a wide dynamic range.

Considering the conventional calibration restriction of the complicated calibration procedures, narrow dynamic range, and less correlation in the calibration data, a global optimization radiometric calibration method is proposed in this paper. First, a unified database is generated by integrating different gray-level images, neutral density attenuators, integration times, and target radiations under the deduced infrared physical model. Then, the calibration coefficients are automatically learned through the relative error backward propagation network. Finally, experiments are conducted on a large-aperture ground-based infrared system to evaluate the effectiveness of the proposed method. The results indicate the proposed method can solve the problem of learning imbalance with large fluctuations of infrared radiation, ensure global measurement precision with a simpler calibration procedure, and accurately measure the internal stray radiation of the optical system.

Role of an FNIP Repeat Domain-Containing Protein Encoded by Megavirus Baoshan during Viral Infection.

FNIP repeat domain-containing protein (FNIP protein) is a little-studied atypical leucine-rich repeat domain-containing protein found in social amoebae and mimiviruses. Here, a recently reported mimivirus of lineage C, Megavirus baoshan, was analyzed for FNIP protein genes. A total of 82 FNIP protein genes were identified, each containing up to 26 copies of the FNIP repeat, and mostly having an F-box domain at the N terminus. Both nucleotide and amino acid sequences of FNIP repeat were highly conserved. Most of the FNIP protein genes clustered together tandemly in groups of two to 14 genes. Nearly all FNIP protein genes shared similar expression patterns and were expressed 4 to 9 h postinfection. A typical viral FNIP protein, Mb0983, was selected for functional analysis. Protein interactome analysis identified two small GTPases, Rap1B and Rab7A, that interacted with Mb0983 in cytoplasm. The overexpression of Mb0983 in Acanthamoeba castellanii accelerated the degradation of Rap1B and Rab7A during viral infection. Mb0983 also interacted with host SKP1 and cullin-1, which were conserved components of the SKP1-cullin-1-F-box protein (SCF)-type ubiquitin E3 ligase complex. Deletion of the F-box domain of Mb0983 not only abolished its interaction with SKP1 and cullin-1 but also returned the speed of Rap1B and Rab7A degradation to normal in infected A. castellanii. These results suggested that Mb0983 is a part of the SCF-type ubiquitin E3 ligase complex and plays a role in the degradation of Rap1B and Rab7A. They also implied that other viral F-box-containing FNIP proteins might have similar effects on various host proteins. IMPORTANCE Megavirus baoshan encodes 82 FNIP proteins, more than any other reported mimiviruses. Their genetic and transcriptional features suggest that they are important for virus infection and adaption. Since most mimiviral FNIP proteins have the F-box domain, they were predicted to be involved in protein ubiquitylation. FNIP protein Mb0983 interacted with host SKP1 and cullin-1 through the F-box domain, supporting the idea that it is a part of the SCF-type ubiquitin E3 ligase complex. The substrates of Mb0983 for degradation were identified as the host small GTPases Rap1B and Rab7A. Combining the facts of the presence of a large number of FNIP genes in megavirus genomes, the extremely high expression level of the viral ubiquitin gene, and the reported observation that 35% of megavirus-infected amoeba cells died without productive infection, it is likely that megavirus actively explores the host ubiquitin-proteasome pathway in infection and that viral FNIP proteins play roles in the process.

Hybrid Sequencing Resolved Inverted Terminal Repeats in the Genome of Megavirus Baoshan.

Mimivirus is a group of amoeba-infecting DNA viruses with linear double-strand genome. It is found to be ubiquitous in nature worldwide. Here, we reported the complete genome of a new member of Mimivirus lineage C isolated from a fresh water pond in Shanghai, China. Its 1,224,839-bp genome encoded 1,062 predicted ORFs. Combining the results of Nanopore, Illumina, and Sanger sequencing technologies, two identical 23,919 bp inverted terminal repeats (ITRs) were identified at both extremities of the viral linear genome, one of which was missing in the draft assembly based on Illumina data only. The discovery of ITRs of Mimivirus provided a new insight into Mimivirus genome structure.

Transcriptional response of Bacillus megaterium FDU301 to PEG200-mediated arid stress.

BACKGROUND: For microorganisms on a paper surface, the lack of water is one of the most important stress factors. A strain of Bacillus megaterium FDU301 was isolated from plaques on a paper surface using culture medium with polyethylene glycol 200 (PEG200) to simulate an arid condition. Global transcriptomic analysis of B. megaterium FDU301 grown under normal and simulated arid conditions was performed via RNA-seq technology to identify genes involved in arid stress adaptation. RESULTS: The transcriptome of B. megaterium FDU301 grown in LB medium under arid (15% PEG200 (w/w)) and normal conditions were compared. A total of 2941 genes were differentially expressed, including 1422 genes upregulated and 1519 genes downregulated under arid conditions. Oxidative stress-responsive regulatory genes perR, fur, and tipA were significantly upregulated, along with DNA protecting protein (dps), and catalase (katE). Genes related to Fe2+ uptake (feoB), sporulation stage II (spoIIB, spoIIE, spoIIGA), small acid-soluble spore protein (sspD), and biosynthesis of compatible solute ectoine (ectB, ectA) were also highly expressed to various degrees. Oxidative phosphorylation-related genes (atpB, atpE, atpF, atpH, atpA, atpG, atpD, atpC) and glycolysis-related genes (pgk, tpiA, frmA) were significantly downregulated. CONCLUSION: This is the first report about transcriptomic analysis of a B. megaterium to explore the mechanism of arid resistance. Major changes in transcription were seen in the arid condition simulated by PEG200 (15%), with the most important one being genes related to oxidative stress. The results showed a complex mechanism for the bacteria to adapt to arid stress.