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Since the SARS-CoV-2 outbreak, pharmaceutical companies and researchers worldwide have worked hard to develop vaccines and drugs to end the SARS-CoV-2 pandemic. The potential pathogen responsible for Coronavirus Disease 2019 (COVID-19), SARS-CoV-2, belongs to a novel lineage of beta coronaviruses in the subgenus arbovirus. Antiviral drugs, convalescent plasma, monoclonal antibodies, and vaccines are effective treatments for SARS-CoV-2 and are beneficial in preventing infection. Numerous studies have already been conducted using the genome sequence of SARS-CoV-2 in comparison with that of other SARS-like viruses, and numerous treatments/prevention measures are currently undergoing or have already undergone clinical trials. We summarize these studies in depth in the hopes of highlighting some key details that will help us to better understand the viral origin, epidemiology, and treatments of the virus.

The development of new approaches to tree-level parameter extraction for forest resource inventory and management is an important area of ongoing research, which puts forward high requirements for the capabilities of single-tree segmentation and detection methods. Conventional methods implement segmenting routine with same resolution threshold for overstory and understory, ignoring that their lidar point densities are different, which leads to over-segmentation of the understory trees. To improve the segmentation accuracy of understory trees, this paper presents a multi-threshold segmentation approach for tree-level parameter extraction using small-footprint airborne LiDAR (Light Detection And Ranging) data. First, the point clouds are pre-processed and encoded to canopy layers according to the lidar return number, and multi-threshold segmentation using DSM-based (Digital Surface Model) method is implemented for each layer; tree segments are then combined across layers by merging criteria. Finally, individual trees are delineated, and tree parameters are extracted. The novelty of this method lies in its application of multi-resolution threshold segmentation strategy according to the variation of LiDAR point density in different canopy layers. We applied this approach to 271 permanent sample plots of the University of Kentucky’s Robinson Forest, a deciduous canopy-closed forest with complex terrain and vegetation conditions. Experimental results show that a combination of multi-resolution threshold segmentation based on stratification and cross-layer tree segments merging method can provide a significant performance improvement in individual tree-level forest measurement. Compared with DSM-based method, the proposed multi-threshold segmentation approach strongly improved the average detection rate (from 52.3% to 73.4%) and average overall accuracy (from 65.2% to 76.9%) for understory trees. The overall accuracy increased from 75.1% to 82.6% for all trees, with an increase of the coefficient of determination R2 by 20 percentage points. The improvement of tree detection method brings the estimation of structural parameters for single trees up to an accuracy level: For tree height, R2 increased by 5.0 percentage points from 90% to 95%; and for tree location, the mean difference decreased by 23 cm from 105 cm to 82 cm.

Carbapenem-resistant Acinetobacter baumannii (CRAB) is resistant to almost all antibiotics. Eravacycline, a newer treatment option, has the potential to treat CRAB infections, however, the mechanism by which CRAB isolates develop resistance to eravacycline has yet to be clarified. This study sought to investigate the features and mechanisms of eravacycline heteroresistance among CRAB clinical isolates. A total of 287 isolates were collected in China from 2020 to 2022. The minimum inhibitory concentration (MIC) of eravacycline and other clinically available agents against A. baumannii were determined using broth microdilution. The frequency of eravacycline heteroresistance was determined by population analysis profiling (PAP). Mutations and expression levels of resistance genes in heteroresistant isolates were determined by polymerase chain reaction (PCR) and quantitative real-time PCR (qRT-PCR), respectively. Antisense RNA silencing was used to validate the function of eravacycline heteroresistant candidate genes. Twenty-five eravacycline heteroresistant isolates (17.36%) were detected among 144 CRAB isolates with eravacycline MIC values ≤4 mg/L while no eravacycline heteroresistant strains were detected in carbapenem-susceptible A. baumannii (CSAB) isolates. All eravacycline heteroresistant strains contained OXA-23 carbapenemase and the predominant multilocus sequence typing (MLST) was ST208 (72%). Cross-resistance was observed between eravacycline, tigecycline, and levofloxacin in the resistant subpopulations. The addition of efflux pump inhibitors significantly reduced the eravacycline MIC in resistant subpopulations and weakened the formation of eravacycline heteroresistance in CRAB isolates. The expression levels of adeABC and adeRS were significantly higher in resistant subpopulations than in eravacycline heteroresistant parental strains ( P < 0.05). An IS Aba1 insertion in the adeS gene was identified in 40% (10/25) of the resistant subpopulations. Decreasing the expression of adeABC or adeRS by antisense RNA silencing significantly inhibited eravacycline heteroresistance. In conclusion, this study identified the emergence of eravacycline heteroresistance in CRAB isolates in China, which is associated with high expression of AdeABC and AdeRS.

Background The aim of this study was to gain an understanding of the transcriptomic changes that occur in a wild species when infected with Toxoplasma gondii . The masked palm civet, an artifically domesticated animal, was used as the model of a wild species. Transcriptome analysis was used to study alterations in gene expression in the domesticated masked palm civet after chronic infection with T. gondii . Methods Masked palm civets were infected with 10 5  T . gondii cysts and their brain tissue collected after 4 months of infection. RNA sequencing (RNA-Seq) was used to gain insight into the spectrum of genes that were differentially expressed due to infection. Quantitative reverse-transcription PCR (qRT-PCR) was also used to validate the level of expression of a set of differentially expressed genes (DEGs) obtained by sequencing. Results DEGs were screened from the sequencing results and analyzed. A total of 2808 DEGs were detected, of which 860 were upregulated and 1948 were downregulated. RNA-Seq results were confirmed by qRT-PCR. DEGs were mainly enriched in cellular process and metabolic process based on gene ontology enrichment analysis. Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that transcriptional changes in the brain of infected masked palm civets evolved over the course of infection and that DEGs were mainly enriched in the signal transduction, immune system processes, transport and catabolic pathways. Finally, 10 essential driving genes were identified from the immune signaling pathway. Conclusions This study revealed novel host genes which may provide target genes for the development of new therapeutics and detection methods for T. gondii infection in wild animals. Graphical Abstract

Spam filtering, which refers to detecting unsolicited, unwanted, and virus-infested emails, is a significant problem because spam emails lead to unnecessary costs of Internet resources, waste of people’s time, and even loss of property. Support vector machine (SVM) is the state-of-the-art method for high accuracy spam filtering. However, SVM incurs high time complexity because of the high dimensionality of the emails. In this study, we propose a manifold learning-based approach for time-efficient spam filtering. From the experiments that most of the features are not decisive, we can obtain the viewpoint that only a minor part of the spam emails can be detected using the nondecisive features. Based on the insight, we propose to employ the Laplace feature map algorithm to obtain the geometrical information from the email text datasets and extract the decisive features. Then, the extracted features are used as the input of SVM to spam filtering. We conduct extensive experiments on three datasets, and the evaluation results indicate the high accuracy time efficiency of our proposed algorithm.

There is a great clinical need for biodegradable materials, which were used as pins of circular staplers, for gastrointestinal reconstruction in medicine. In this work we compared the effects of the Mg–6Zn and the titanium alloys on collagen metabolism in the healing of the intestinal tract in vivo . The study included Sprague-Dawley rats and their effect was compared on rat’s intestinal tract, using serum magnesium, radiology, and immunohistochemistry in vivo . Radiographic and scanning electron microscope evaluation confirmed the degradation by Mg–6Zn alloy during the implantation period. Biochemical measurements including serum magnesium, creatinine, blood urea nitrogen and glutamic–pyruvic–transaminase proved that degradation of Mg–6Zn alloy showed no impact on serum magnesium and the function of other important organs. Superior to titanium alloy, Mg–6Zn alloy enhanced the expression of collagen I/III and relatively suppressed the expression of MMP-1/-13 in the healing tissues, leading to more mature collagen formation at the site of anastomosis. In conclusion, Mg–6Zn alloy performed better than titanium alloy on collagen metabolism and promoted the healing of intestinal anastomosis. Hence, Mg-6Zn may be a promising candidate for use of stapler pins for intestinal reconstruction in the clinically.

The machine tool joint is a very important factor in the overall machine tool dynamic analysis, and it has great effects on the machining performance of a machine tool. As a very important operation parameter, preload greatly influences the stiffness and the damping of a machine tool joint. This paper presents the effect of preload on the dynamic stiffness of the spindle nose of a horizontal machining center. By discussing types and distribution of machine tool joints, studies on the joints of ball screws, linear guides and bolts are carried out. The influence of preload on the axial stiffness of a ball screw is calculated based on Hertzian contact theory and the effect of pretightening moment on pressure of bolt joint is discussed, while the dynamic stiffness and the damping of a linear guide are identified by an optimum algorithm with the simulated and experimental results. A finite element model (FEM) of the whole machine tool structure considering the effects of different joints is created and verified against the test results, and then the influence of preloads on ball screws and linear guides is predicted. Results indicate that preloads on machine tool joints have significant effects on the dynamic stiffness of the spindle nose.

Highlights The review provides a brief overview of basic mechanisms, element selections, activity confirmation, and experimental protocols of photocatalytic nitrogen fixation under mild conditions. The review details strategies for scale-up photocatalysts in nitrogen fixation, emphasizing defect engineering, facet optimization, heteroatom doping, single-atom site creation, and composite synthesis. The review emphasizes the importance of environmental assessment for photocatalyst lifecycle sustainability in mild nitrogen fixation for the future. Ammonia and nitric acid, versatile industrial feedstocks, and burgeoning clean energy vectors hold immense promise for sustainable development. However, Haber–Bosch and Ostwald processes, which generates carbon dioxide as massive by-product, contribute to greenhouse effects and pose environmental challenges. Thus, the pursuit of nitrogen fixation through carbon–neutral pathways under benign conditions is a frontier of scientific topics, with the harnessing of solar energy emerging as an enticing and viable option. This review delves into the refinement strategies for scale-up mild photocatalytic nitrogen fixation, fields ripe with potential for innovation. The narrative is centered on enhancing the intrinsic capabilities of catalysts to surmount current efficiency barriers. Key focus areas include the in-depth exploration of fundamental mechanisms underpinning photocatalytic procedures, rational element selection, and functional planning, state-of-the-art experimental protocols for understanding photo-fixation processes, valid photocatalytic activity evaluation, and the rational design of catalysts. Furthermore, the review offers a suite of forward-looking recommendations aimed at propelling the advancement of mild nitrogen photo-fixation. It scrutinizes the existing challenges and prospects within this burgeoning domain, aspiring to equip researchers with insightful perspectives that can catalyze the evolution of cutting-edge nitrogen fixation methodologies and steer the development of next-generation photocatalytic systems.

Content-based image retrieval (CBIR) with deep neural networks (DNNs) on the cloud has tremendous business and technical advantages to handle large-scale image repositories. However, cloud-based CBIR service raises challenges in image data and DNN model security. Typically, users who wish to request CBIR services on the cloud require their input images remaining confidential. On the other hand, image owners may intentionally (or unintentionally) upload adversarial examples to the cloud servers, which potentially leads to the misbehavior of CBIR services. Generative Adversarial Networks (GANs) can be utilized to defense against such malicious behavior. However, the GANs model, if not well protected, can be easily abused by the cloud to reconstruct the users’ original image data. In this paper, we focus on the problem of secure generative model evaluation and secure gradient descent (GD) computation in GANs. We propose two secure generative model evaluation algorithms and two secure minimizer protocols. Furthermore, we propose and implement Sec-Defense-Gan, a secure image reconstruction framework which can keep the image data, the generative model details and corresponding outputs confidential from the cloud. Finally, We carried out a set of benchmarks over two public available image datasets to show the performance and correctness of Sec-Defense-Gan.

Purpose We conducted a systematic review and meta-analysis to compare the clinical outcomes of percutaneous endoscopic lumbar discectomy (PELD) and microendoscopic discectomy (MED) for the treatment of lumbar disc herniation (LDH), and to clarify whether PELD is more superior to MED. Methods We performed a comprehensive search in the databases of MEDLINE, EMBASE, PubMed, Web of Science, Cochrane database, CNKI, and Wanfang Data to acquire all relevant studies up to July 2018. The searched literatures were then screened according to the strict inclusion and exclusion criteria. The critical data were extracted and analyzed utilizing Review Manager software. The pooled effects were calculated by mean difference (MD) or odds ratio (OR) with 95% confidence intervals (CI) on the basis of data attributes. Results A total of 18 studies (2161 patients, 1093 in the PELD group and 1068 in the MED group) were included in this systematic review and meta-analysis. At last follow-up, the results revealed that no significant difference was found between PELD group and MED group with respect to ODI (MD − 0.30; 95% CI − 1.02 to 0.42; P  = 0.41), VAS-leg pain (MD − 0.18; 95% CI − 0.45 to 0.09; P  = 0.19), VAS-unspecified (MD − 0.00; 95% CI − 0.05 to 0.04; P  = 0.94), excellent & good rate (OR, 1.04; 95% CI 0.68 to 1.59; P  = 0.86), total complication rate (OR, 0.96; 95% CI 0.65 to 1.43; P  = 0.85), dural tear rate (OR, 0.39; 95% CI 0.10 to 1.55; P  = 0.18), and residue or recurrence rate (OR, 2.22; 95% CI 1.02 to 4.83; P  = 0.05). When compared to MED group, the PELD group showed significantly better results with regard to shorter length of incision (MD − 1.18; 95% CI − 1.39 to − 0.97; P  < 0.00001), less blood loss (MD − 45.17; 95% CI − 64.74 to − 25.60; P  < 0.00001), shorter post-operative in-bed time (MD − 59.11; 95% CI − 71.19 to − 47.04; P  < 0.00001), shorter post-operative hospital stay (MD − 3.07; 95% CI − 4.81 to − 1.33; P  < 0.00001), shorter total hospital stay (MD − 2.29; 95% CI − 3.03 to − 1.55; P  < 0.00001), and lower VAS-back pain at last follow-up (MD − 0.77; 95% CI − 1.31 to − 0.24; P  = 0.005), but with significantly worse results such as more fluoroscopy (MD 7.63; 95% CI 5.25 to 10.01; P  < 0.00001) and higher re-operation rate (OR, 2.67; 95% CI 1.07 to 6.67; P  = 0.04). Although no significant difference was found between the two groups in terms of duration of operation (MD 6.27; 95% CI − 2.44 to 14.98; P  = 0.16) and total hospital cost (MD − 0.69; 95% CI − 12.60 to 11.23; P  = 0.91), further subgroup analysis revealed that the duration of operation was significantly longer in the PELD group compared with the MED group in “Years before 2016” (MD 24.97; 95% CI 7.07 to 42.87; P  = 0.006) and “Year 2016 to 2017” (MD 6.57; 95% CI 0.58 to 12.55; P  = 0.03) subgroups but not in the subgroup “Year 2018” (MD − 5.66; 95% CI − 18.84 to 7.53; P  = 0.40), and that the total hospital cost was significantly more in the PELD group compared with the MED group in the subgroup “Southeast of China” (MD 6.67; 95% CI 3.23 to 10.28; P  = 0.0002) but not in the subgroup “Midwest of China” (MD − 8.09; 95% CI − 17.99 to 1.80; P  = 0.11). Conclusions For the treatment of LDH, both of PELD and MED can reach excellent results and no superiority was found between the two minimally invasive procedures with regard to duration of operation, ODI, VAS-leg pain, VAS-unspecified, excellent & good rate, total complication rate, dural tear rate, and residue or recurrence rate. While PELD can achieve better outcomes with respect to the length of incision, blood loss, post-operative in-bed time, post-operative hospital stay, total hospital stay, and VAS-back pain at last follow-up, however, MED showed certain advantages of less fluoroscopic times and lower re-operation rate. More practice and development are needed to make up for the deficiencies of PELD. Besides, the economic factor should also be considered according to different regions before making the treatment strategies. Well-defined randomized controlled trials with large samples are needed to further confirm these results.