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Background There have been no reports regarding the molecular characteristics, virulence features, and antibiotic resistance profiles of Staphylococcus aureus ( S. aureus ) from Hainan, the southernmost province of China. Methods Two hundred twenty-seven S. aureus isolates, consisting of 76 methicillin-resistant S. aureus (MRSA) and 151 methicillin-susceptible S. aureus (MSSA), were collected in 2013–2014 and 2018–2019 in Hainan, and investigated for their molecular characteristics, virulence genes, antibiotic resistance profiles and main antibiotic resistance genes. Results Forty sequence types (STs) including three new STs (ST5489, ST5492 and ST5493), and 79 Staphylococcal protein A ( spa ) types were identified based on multilocus sequence typing (MLST) and spa typing, respectively. ST398 (14.1%, 32/227) was found to be the most prevalent, and the prevalence of ST398-MSSA increased significantly from 2013 to 2014 (5.5%, 5/91) to 2018–2019 (18.4%, 25/136). Seventy-six MRSA isolates were subject to staphylococcus chromosomal cassette mec (SCC mec ) typing. SCC mec- IVa was the predominant SCC mec type, and specifically, ST45-SCC mec IVa, an infrequent type in mainland China, was predominant in S. aureus from Hainan. The antibiotic resistance profiles and antibiotic resistance genes of S. aureus show distinctive features in Hainan. The resistant rates of the MRSA isolates to a variety of antibiotics were significantly higher than those of the MSSA isolates. The predominant erythromycin and tetracycline resistance genes were ermC (90.1%, 100/111) and tetK (91.8%, 78/85), respectively. Eleven virulence genes, including the Panton-Valentine leukocidin ( pvl ) and eta , were determined, and the frequency of eta and pvl were found to be 57.3 and 47.6%. Such high prevalence has never been seen in mainland China before. Conclusion S. aureus isolates in Hainan have unique molecular characteristics, virulence gene and antibiotic resistance profiles, and main antibiotic resistance genes which may be associated with the special geographical location of Hainan and local trends in antibiotic use.

Perovskite Solar Cells (PSCs) are regarded as a highly effective low-cost solar energy collector, which is promised to sustain considerable energy supplies for modern society. Roll-to-Roll (R2R) compatible PSCs fabrication method is promised to realized industrialized PSCs production. This paper presents an overview of recent R2R compatible methods for PSC fabrication, which covers five R2R compatible strategies towards industrialized R2R production. To further tackle technical obstacles towards the PSC industrialization, improving perovskite morphology, adopting ambient production conditions and enhancing moisture resistance, as three aspects towards a high-effective, low-cost and highly stable PSCs, are discussed and concluded. This paper also discussed the possibility of hybrid wind-solar energy collector and raises a wind-flutter-PSCs composed conceptional structure.

Vision is an important way for unmanned mobile platforms to understand surrounding environmental information. For an unmanned mobile platform, quickly and accurately obtaining environmental information is a basic requirement for its subsequent visual tasks. Based on this, a unique convolution module called Multi-Scale Depthwise Separable Convolution module is proposed for real-time semantic segmentation. This module mainly consists of concatenation pointwise convolution and multi-scale depthwise convolution. Not only does the concatenation pointwise convolution change the number of channels, but it also combines the spatial features from the multi-scale depthwise convolution operations to produce additional features. The Multi-Scale Depthwise Separable Convolution module can strengthen the non-linear relationship between input and output. Specifically, the multi-scale depthwise convolution module extracts multi-scale spatial features while remaining lightweight. This fully uses multi-scale information to describe objects despite their different sizes. Here, Mean Intersection over Union (MIoU), parameters, and inference speed were used to describe the performance of the proposed network. On the Camvid, KITTI, and Cityscapes datasets, the proposed algorithm compromised between accuracy and memory in comparison to widely used and cutting-edge algorithms. In particular, the proposed algorithm acquired 61.02 MIoU with 2.68 M parameters on the Camvid test dataset.

Background Aberrant expression of circular RNAs contributes to the initiation and progression of cancers, but the underlying mechanism remains elusive. Methods RNA-seq and qRT-PCR were performed to screen differential expressed circRNAs between gastric cancer tissues and adjacent normal tissues. Candidate circRNA (circMRPS35) was screened out and validated by qRT-PCR. Cell proliferation and invasion ability were determined by CCK-8 and cell invasion assays. RNA-seq, GO-pathway, RNA pull-down and ChIRP were further applied to search for detailed mechanism. Results Here, a novel circRNA named circMRPS35, was screened out by RNA-seq in gastric cancer tissues, whose expression is related to clinicopathological characteristics and prognosis in gastric cancer patients. Biologically, circMRPS35 suppresses the proliferation and invasion of gastric cancer cells in vitro and in vivo. Mechanistically, circMRPS35 acts as a modular scaffold to recruit histone acetyltransferase KAT7 to the promoters of FOXO1 and FOXO3a genes, which elicits acetylation of H4K5 in their promoters. Particularly, circMRPS35 specifically binds to FOXO1/3a promoter regions directly. Thus, it dramatically activates the transcription of FOXO1/3a and triggers subsequent response of their downstream target genes expression, including p21, p27, Twist1 and E-cadherin, resulting in the inhibition of cell proliferation and invasion. Moreover, circMRPS35 expression positively correlates with that of FOXO1/3a in gastric cancer tissues. Conclusions Our findings not only reveal the pivotal roles of circMRPS35 in governing histone modification in anticancer treatment, but also advocate for triggering circMRPS35/KAT7/FOXO1/3a pathway to combat gastric cancer.

High-complexity network models are challenging to execute on agricultural robots with limited computing capabilities in a large-scale pineapple planting environment in real time. Traditional module replacement often struggles to reduce model complexity while maintaining stable network accuracy effectively. This paper investigates a pineapple detection framework with a YOLOv7-tiny model improved via pruning and a lightweight backbone sub-network (the RGDP-YOLOv7-tiny model). The ReXNet network is designed to significantly reduce the number of parameters in the YOLOv7-tiny backbone network layer during the group-level pruning process. Meanwhile, to enhance the efficacy of the lightweight network, a GSConv network has been developed and integrated into the neck network, to further diminish the number of parameters. In addition, the detection network incorporates a decoupled head network aimed at separating the tasks of classification and localization, which can enhance the model’s convergence speed. The experimental results indicate that the network before pruning optimization achieved an improvement of 3.0% and 2.2%, in terms of mean average precision and F1 score, respectively. After pruning optimization, the RGDP-YOLOv7-tiny network was compressed to just 2.27 M in parameter count, 4.5 × 109 in computational complexity, and 5.0MB in model size, which were 37.8%, 34.1%, and 40.7% of the original YOLOv7-tiny network, respectively. Concurrently, the mean average precision and F1 score reached 87.9% and 87.4%, respectively, with increases of 0.8% and 1.3%. Ultimately, the model’s generalization performance was validated through heatmap visualization experiments. Overall, the proposed pineapple object detection framework can effectively enhance detection accuracy. In a large-scale fruit cultivation environment, especially under the constraints of hardware limitations and limited computational power in the real-time detection processes of agricultural robots, it facilitates the practical application of artificial intelligence algorithms in agricultural engineering.

Esophageal squamous cell carcinoma (ESCC), characterized by its high invasiveness and malignant potential, has long been a formidable challenge in terms of treatment. A variety of advanced analytical techniques are employed, including single-cell RNA sequencing (scRNA-seq), cell trajectory inference, transcription factor regulatory network analysis, GSVA enrichment analysis, mutation profile construction, and the inference of potential immunotherapeutic drugs. The purpose is to conduct a more comprehensive exploration of the heterogeneity among malignant squamous epithelial cell subgroups within the ESCC microenvironment and establish a model for predicting the prognosis and immunotherapy outcomes of ESCC patients. An analysis was conducted through scRNA-seq, and three Cluster of malignant epithelial cells were identified using the infer CNV method. Cluster 0 was found to exhibit high invasiveness, whereas Cluster 1 displayed prominent characteristics associated with epithelial-mesenchymal transition. Confirmation of these findings was provided through cell trajectory analysis, which positioned Cluster 0 at the initiation stage of development and Cluster 1 at the final developmental stage. The abundance of Cluster 0-2 groups in TCGA-LUAD samples was assessed using ssGSEA and subsequently categorized into high and low-expression groups. Notably, it was observed that Cluster 0-1 had a significant impact on survival (p<0.05). Furthermore, GSVA enrichment analysis demonstrated heightened activity in hallmark pathways for Cluster 0, whereas Cluster 1 exhibited notable enrichment in pathways related to cell proliferation. It is noteworthy that a prognostic model was established utilizing feature genes from Cluster 0-1, employing the Lasso and stepwise regression methods. The results revealed that in TCGA and GSE53624 cohorts, the low-risk group demonstrated significantly higher overall survival and increased levels of immune infiltration. An examination of four external immunotherapy cohorts unveiled that the low-risk group exhibited improved immunotherapeutic efficacy. Additionally, more meaningful treatment options were identified for the low-risk group. The findings revealed distinct interactions between malignant epithelial cells of ESCC and subgroups within the tumor microenvironment. Two cell clusters, strongly linked to survival, were pinpointed, and a signature was formulated. This signature is expected to play a crucial role in identifying and advancing precision medicine approaches for the treatment of ESCC.

This paper investigates a cross-diffusion epidemic system in a bounded domain with no-flux boundary conditions. The local and global stability of the positive equilibrium is analyzed for this system without cross-diffusion. Sufficient conditions for the existence and nonexistence of non-constant positive steady states are derived for the cross-diffusion epidemic system, indicating whether pattern formation can occur. The results show that when the self-pressure is strong and the tendency to avoid infection is weak, non-constant positive steady states do not exist. These cases are critical in determining disease persistence. However, non-constant positive steady states arise extensively when the cross-diffusion coefficient for the removed individuals is sufficiently large and the self-diffusion coefficients d i ( i = 1 , 2 ) are relatively small under certain other conditions.

This paper is concerned with a fractional diffusion predator-prey system with Holling type-II functional response in a bounded domain with no flux boundary condition. The local and global stabilities are investigated and sufficient conditions of stabilities are obtained. The existence of the non-constant steady states is considered and the sufficient conditions of the existence for the non-constant steady states are also obtained. The results show that the predator and the prey can coexist under some suitable conditions with fractional diffusion.

Carboxylesterases (CEs) play important physiological roles in the human body and are involved in numerous cellular processes. Monitoring CEs activity has great potential for the rapid diagnosis of malignant tumors and multiple diseases. Herein, we developed a new phenazine-based “turn-on” fluorescent probe DBPpys by introducing 4-bromomethyl-phenyl acetate to DBPpy, which can selectively detect CEs with a low detection limit (9.38 × 10−5 U/mL) and a large Stokes shift (more than 250 nm) in vitro. In addition, DBPpys can also be converted into DBPpy by carboxylesterase in HeLa cells and localized in lipid droplets (LDs), emitting bright near-infrared fluorescence under the irradiation of white light. Moreover, we achieved the detection of cell health status by measuring the intensity of NIR fluorescence after co-incubation of DBPpys with H2O2-pretreated HeLa cells, indicating that DBPpys has great potential applications for assessing CEs activity and cellular health.

Background Limited data exists on the link between dietary iron intake and mortality in diabetes. Our investigation aimed to explore how dietary iron intake correlates with overall and cause-specific mortality in diabetic individuals. Methods This analysis encompassed 5970 participants with diabetes from the National Health and Nutrition Examination Survey spanning 1999 to 2014. Baseline data were collected through surveys and examinations, with mortality status tracked via National Death Index records until December 31, 2015. Cox proportional hazard models were utilized to calculate hazard ratios (HR) and 95% confidence intervals (CI) for mortality from various causes, including cardiovascular disease (CVD) and cancer. Results The average iron intake among the cohort was 14.1 ± 7.4 mg daily, with an average participant age of 61.3 and 3059 (51.3%) male adults. Over 41,425 person-years of follow-up, 1497 deaths were recorded. Following adjustments for multiple variables, an iron intake between 11.1 and 14.4 mg was associated with the lowest risk of all-cause mortality (HR 0.83 [0.70, 0.99], P  < 0.05) compared to the reference group (<8.3 mg). Analysis of dose-response curves revealed an L-shaped pattern in men and a J-shaped pattern in women concerning the relationship between iron intake and all-cause mortality. Conclusions Our findings suggest a nonlinear association between dietary iron intake and all-cause mortality in individuals with diabetes. Specifically, higher iron intake may increase all-cause mortality risk in men, while potentially exert a protective effect in women.