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Abstract Background The escalating challenge of Carbapenem-resistant Klebsiella pneumoniae (CRKP) in hospital-acquired pneumonia (HAP) is closely linked to the blaNDM-1 gene. This study explores the regulatory mechanisms of blaNDM-1 expression and aims to enhance antibacterial tactics to counteract the spread and infection of resistant bacteria. Methods KP and CRKP strains were isolated from HAP patients' blood samples. Transcriptomic sequencing (RNA-seq) identified significant upregulation of blaNDM-1 gene expression in CRKP strains. Bioinformatics analysis revealed blaNDM-1 gene involvement in beta-lactam resistance pathways. CRISPR-Cas9 was used to delete the blaNDM-1 gene, restoring sensitivity. In vitro and in vivo experiments demonstrated enhanced efficacy with Imipenem and Thanatin or Subatan combination therapy. Results KP and CRKP strains were isolated with significant upregulation of blaNDM-1 in CRKP strains identified by RNA-seq. The Beta-lactam resistance pathway was implicated in bioinformatics analysis. Knockout of blaNDM-1 reinstated sensitivity in CRKP strains. Further, co-treatment with Imipenem, Thanatin, or Subactam markedly improved antimicrobial effectiveness. Conclusion Silencing blaNDM-1 in CRKP strains from HAP patients weakens their Carbapenem resistance and optimizes antibacterial strategies. These results provide new theoretical insights and practical methods for treating resistant bacterial infections.

Abstract Histone methylation plays a crucial role in various cellular processes. We previously reported the in vitro function of histone lysine demethylase 7 A (KDM7A) in osteoblast and adipocyte differentiation. The current study was undertaken to investigate the physiological role of KDM7A in bone homeostasis and elucidate the underlying mechanisms. A conditional strategy was employed to delete the Kdm7a gene specifically in osterix-expressing osteoprogenitor cells in mice. The resulting mutant mice exhibited a significant increase in cancellous bone mass, accompanied by an increase in osteoblasts and bone formation, as well as a reduction in osteoclasts, marrow adipocytes and bone resorption. The bone marrow stromal cells (BMSCs) and calvarial pre-osteoblastic cells derived from the mutant mice exhibited enhanced osteogenic differentiation and suppressed adipogenic differentiation. Additionally, osteoclastic precursor cells from the mutant mice exhibited impaired osteoclast differentiation. Co-culturing BMSCs from the mutant mice with wild-type osteoclast precursor cells resulted in the inhibition of osteoclast differentiation. Mechanistic investigation revealed that KDM7A was able to upregulate the expression of fibroblast activation protein α (FAP) and receptor activator of nuclear factor κB ligand (RANKL) in BMSCs through removing repressive di-methylation marks of H3K9 and H3K27 from Fap and Rankl promoters. Moreover, recombinant FAP attenuated the dysregulation of osteoblast and adipocyte differentiation in BMSCs from Kdm7a deficient mice. Finally, Kdm7a deficiency prevented ovariectomy-induced bone loss in mice. This study establish the role of KDM7A in bone homeostasis through its epigenetic regulation of osteoblast and osteoclast differentiation. Consequently, inhibiting KDM7A may prove beneficial in ameliorating osteoporosis. KDM7A suppresses osteoblast differentiation and bone formation through. upregulating FAP expression and inactivating canonical Wnt signaling, and conversely promotes osteoclast differentiation and bone resorption through upregulating RANKL expression. These are based on its epigenetic removal of the repressive H3K9me2 and H3K27me2 marks from Fap and Rankl promoters. As a result, the expression of KDM7A in osteoprogenitor cells tends to negatively modulate bone mass.

Abstract Background Although epidural anaesthesia and spinal anaesthesia are currently the general choices for patients undergoing caesarean section, these two neuraxial anaesthesia methods still have drawbacks. Caudal anaesthesia has been considered to be more appropriate for gynaecological surgery. The purpose of this study was to compare epidural anaesthesia combined with caudal anaesthesia, spinal anaesthesia and single-space epidural anaesthesia for caesarean section with respect to postoperative comfort and intraoperative anaesthesia quality. Methods In this clinical trial, 150 patients undergoing elective caesarean section were recruited and randomized into three groups according to a ratio of 1:1:1to receive epidural anaesthesia only, spinal anaesthesia only or epidural anaesthesia combined with caudal anaesthesia. The primary outcome was postoperative comfort in the three groups. Secondary outcomes included intraoperative anaesthesia quality and the incidences of nausea, vomiting, postdural puncture headache, maternal bradycardia, or hypotension. Results More patients were satisfied with the intraoperative anaesthesia quality in the EAC group than in the EA group (P = 0.001). The obstetrician was more significantly satisfied with the intraoperative anaesthesia quality in the SA and EAC groups than in the EA group (P = 0.004 and 0.020, respectively). The parturients felt more comfortable after surgery in the EA and EAC groups (P = 0.007). The incidence of maternal hypotension during caesarean section was higher in the SA group than in the EA and EAC groups (P = 0.001 and 0.019, respectively). Conclusions Epidural anaesthesia combined with caudal anaesthesia may be a better choice for elective caesarean section. Compared with epidural anaesthesia and spinal anaesthesia, it has a higher quality of postoperative comfort and intraoperative anaesthesia.

In recent years, convolutional neural network (CNN) has achieved great success in the field of network security protection. With the popularization of smart terminals and the gradual increase of power grid informatization and digitization, the protection of power monitoring systems from various cybersecurity threads is a current scientific problem that needs to be solved urgently. To this end, this paper proposes a malware detection method based on genetic algorithm optimization of the CNN-SENet network, which firstly introduces the SENet attention mechanism into the convolutional neural network to enhance the spatial feature extraction capability of the model; then, the application programming interface (API) sequences corresponding to different software behaviors are processed by segmentation and de-duplication, which in turn leads to the sequence feature extraction through the CNN-SENet model; finally, genetic algorithm is used to optimize the hyperparameters of CNN-SENet network to reduce the computational overhead of CNN and to achieve the recognition and classification of different malware at the output layer. The examples under the public dataset containing 8 kinds of malware show that the proposed method is better than the traditional algorithmic model, and can accurately and efficiently achieve malware detection with strong generalization ability.

Underwater sonar image salient object detection (SOD) plays a crucial role in underwater rescue and marine resource discovery. Although existing SOD methods have shown some potential in sonar images, they perform poorly in terms of object localization, clear boundary detection, and local refinement. To address these issues, we propose a Reverse Feature Learning Network (RFLNet), which consists of four modules: (a) Coarse Feature Extraction Module (CFEM), (b) Reverse Feature Localization Branch Module (RFLBM), (c) Residual Channel Spatial Parallel Attention Mechanism (RCSPA), and (d) Feature Refinement Module (FRM). First, we generate a coarse prediction map using the CFEM and extract object boundary and localization information with the RFLB module. Second, we use feedback signals from the backpropagation algorithm to guide the training of the CFEM. Additionally, we introduce the RCSPA to suppress the interference of low-level non-salient information. Finally, we use the FRM to further refine the local details of the coarse prediction feature map generated by the CFEM. To demonstrate the effectiveness of the proposed RFLNet, we conducted extensive experiments on the forward-looking sonar image dataset. Experimental results show that our method achieved an enhanced contrast measurement (E-measure) of 0.9894 and a boundary displacement error of 2.9126, outperforming 20 other state-of-the-art methods. The source code and models are available at https://github.com/darkseid-arch/RFLNet-FLSSOD.

With the wide application of deep learning in image processing, salient object detection (SOD) in underwater sonar images has become an important research topic. However, due to the interference of complex underwater environments and seabed reverberation noise, the existing deep learning methods have the problem of insufficient feature representation in the SOD task for side-scan sonar (SSS) images. In the down-sampling process, these methods may lose the relationship between the global information and local information of the sonar image, which affects the detection effect for object contour structure. To address this issue, we propose a novel Global Feature Hybrid Attention Network (GFHANet) specifically designed for SOD in SSS images. Specifically, we construct a dual-encoder structure based on global feature extraction and self-attention mechanism to capture the global structure information of sonar images. The adaptive hybrid attention mechanism (AHAM) is used to realize the effective reconstruction of channel and spatial features, and a global enhancement module (GEM) is designed to fuse the global and spatial features from the dual-encoder to compensate for information loss. Comparative experiments on the underwater sonar dataset with 10 other state-of-the-art methods show that GFHANet achieves superior performance in underwater sonar salient object detection, with a mean absolute error (MAE) of 2.35%, and a structural similarity (SM) of 74.25%. The source code and models are available at https://github.com/darkseid-arch/GFHANet-4SOD.

Large Language Models (LLMs) have revolutionized Natural Language Processing (NLP) and have been widely adopted in various applications such as machine translation, chatbots, text summarization, and so on. However, the use of LLMs has raised concerns about their potential safety and security risks. In this survey, we explore the safety implications of LLMs, including ethical considerations, hallucination, and prompt injection. We also discuss current research efforts to mitigate these risks and identify areas for future research. Our survey provides a comprehensive overview of the safety concerns related to LLMs, which can help researchers and practitioners in the NLP community develop more safe and ethical applications of LLMs.

ObjectiveTo investigate the high-risk detection rate and aggregation of cardiovascular diseases（CVD） in 8 districts of Shanghai and influencing factors， and to provide scientific references for prevention and control of CVD.MethodsBased on the Cardiovascular Disease Screening and Management Program in Shanghai from 2016 to 2021， 104 685 participants aged 35 to 75 in 8 districts of Shanghai were selected for analysis. χ2 test and multivariate logistic regression were used for statistical analysis of the influencing factors of CVD and aggregation of CVD.ResultsThe proportion of high-risk CVD individuals in the population was 19.17%， including the high-risk individuals with hypertension （8.65%）， dyslipidemia （6.33%）， CVD history （5.58%）， and WHO assessed risk ≥20% types （2.69%）， respectively. Old age， overweight and obesity， central obesity， smoking， drinking， farmers， unmarried， and low family income were the risk factors of CVD， while high education level was the protective factor. In the participants， 16 323 people （81.34%） were classified as CVD high-risk groups； The number of aggregation of 1， 2 and ≥3 high risk types of CVD were 16 323（81.34%）， 3 236（16.13%）， 509（2.54%）， respectively. Old age， low education level， low annual family income， farmers， unmarried， smoking， drinking， overweight， obesity and central obesity were associated with the risk of aggregation of high risk types of CVD， and the correlation strength increased with the increase of aggregation types.ConclusionThe prevention and control of CVD in Shanghai should focus on the hypertension， elderly， overweight， obesity， central obesity， smoking， drinking， low educated， low family income， farmers and unmarried people， and targeted intervention measures should be taken to reduce the risk of CVD among residents.

ABSTRACTThis study examines Chinese civil servants’ attitudes toward genetically modified organisms by reviewing a national survey of 3,018 Chinese civil servants. The findings show that Chinese civil servants hold a more positive attitude to GMOs than the wider Chinese “general public”, with a similar level of genetic scientific literacy and belief in GMOs conspiracy theories and their influence mechanisms. While the Chinese civil servants’ occupational literacy plays an important role in their GMOs attitude. This study provides a new mind-set for studying some specific groups’ attitudes toward GMOs and related food policies.

The increase in new energy grid connections has reduced the supply-side regulation capability of the power system. Traditional economic dispatch methods are insufficient for addressing the flexibility limitations in the system’s balancing capabilities. Consequently, this study presents a day-ahead scheduling method for renewable energy systems that balances flexibility and economy. This approach establishes a dual-layer optimized scheduling model. The upper-layer model focuses on the economic efficiency of unit start-up and shut-down, utilizing a particle swarm algorithm to identify unit combinations that comply with minimum start-up and shut-down time constraints. In contrast, the lower-layer model addresses the dual uncertainties of generation and load. It employs the Generalized Polynomial Chaos approximation to create an opportunity-constrained model aimed at minimizing unit generation and curtailment costs while maximizing flexibility supply capability. Additionally, it calculates the probability of flexibility supply-demand insufficiency due to uncertainties in demand response resource supply and system operating costs, providing feedback to the upper-layer model. Ultimately, through iterative solutions of the upper and lower models, a day-ahead scheduling plan that effectively balances flexibility and economy is derived. The proposed method is validated using a simulation of the IEEE 30-bus system case study, demonstrating its capability to balance system flexibility and economy while effectively reducing the risk of insufficient supply-demand balance.

There are many uncertainties in the actual use of thermal protection systems (TPSs). In this paper, an interval finite element model of a TPS under transient heat transfer is established by taking the uncertainties of TPSs as interval parameters. An affine interval finite element method (AIFEM) is proposed to study the temperature response bounds of uncertain TPSs under transient heat transfer conditions. Two numerical examples are given to verify the effectiveness and accuracy of the proposed AIFEM by comparison with the Monte Carlo method. The results show that the AIFEM can provide conservative and efficient calculation results in TPS transient heat transfer design with interval parameters.

Mesenchymal stromal cells (MSCs) are promising candidates for cartilage repair therapy due to their self-renewal, chondrogenic, and immunomodulatory capacities. It is widely recognized that a shift from fetal bovine serum (FBS)-containing medium toward a fully chemically defined serum-free (SF) medium would be necessary for clinical applications of MSCs to eliminate issues such as xeno-contamination and batch-to-batch variation. However, there is a notable gap in the literature regarding the evaluation of the chondrogenic ability of SF-expanded MSCs (SF-MSCs). In this study, we compared the in vivo regeneration effect of FBS-MSCs and SF-MSCs in a rat osteochondral defect model and found poor cartilage repair outcomes for SF-MSCs. Consequently, a comparative analysis of FBS-MSCs and SF-MSCs expanded using two SF media, MesenCult™-ACF (ACF), and Custom StemPro™ MSC SFM XenoFree (XF) was conducted in vitro. Our results show that SF-expanded MSCs constitute variations in morphology, surface markers, senescence status, differentiation capacity, and senescence/apoptosis status. Highly proliferative MSCs supported by SF medium do not always correlate to their chondrogenic and cartilage repair ability. Prior determination of the SF medium’s ability to support the chondrogenic ability of expanded MSCs is therefore crucial when choosing an SF medium to manufacture MSCs for clinical application in cartilage repair.

The knowledge of the deposition fate of ambient polycyclic aromatic hydrocarbons (PAHs) on plant leaves is limited. To fill in this knowledge gap, this study strives to observe the intermolecular complex between the polycyclic aromatic hydrocarbons and epicuticular wax of plant leaves using laser scanning microscopy. Epicuticular wax refers to a type of organic mixture that covers the outermost layer of leaves. The leaves of 20 tree species were collected in Beijing in July 2023. The concentrations of 31 PAHs were quantified by gas chromatography–mass spectrometry. Furthermore, the intermolecular complexes of polycyclic aromatic hydrocarbons and epicuticular wax were found with a fluorescence spectrofluorometer and laser scanning microscopy. The levels of total PAHs across 20 tree species ranged from 12.4 ng g−1 to 68.4 ng g−1. Differences in the amounts of total PAHs across tree leaves were observed, which may be ascribed to the differences in leaf surface across tree types. The higher concentration of low-molecular-weight PAHs was found in leaves compared to high-molecular-weight PAHs. The fluorescence spectrofluorometer identified the formation of a new intermolecular complex with fluorescence emission at an excitation wavelength of 340 nm between PAHs and epicuticular wax relative to PAHs. We used laser scanning microscopy with a 405 nm laser for excitation to observe the new intermolecular complex of PAHs and epicuticular wax on the stomata and epicuticular wax of leaves. This study found the intermolecular complex of PAHs on the surface of leaves in situ, which provides important information about the deposition fate of ambient PAHs.

In this study, umami peptides were screened and characterized from bovine bone soups manufactured via atmospheric and high-pressure boiling. Peptide fractions with molecular weights less than 3 kDa were selected for peptide sequencing using LC-MS/MS, the toxicity prediction of the umami peptides was carried out by using an website, and the peptides were screened according to the binding energy, i.e., three peptides including YDAELS, TDVAHR, and ELELQ were selected. The three umami peptides were further synthesized, and their umami thresholds were determined through sensory evaluation and electronic tongue analysis, ranging from 0.375 to 0.75 mg/mL. All three peptides exhibited a significant synergistic taste enhancement effect when combined with MSG (monosodium glutamate) solution. The molecular docking of the umami peptides with the T1R1/T1R3 receptor revealed the mechanism of umami presentation, and the main interaction forces between the three umami peptides and the receptor were hydrogen bonding, electrostatic interactions, and hydrophobic interactions.

The antioxidant and immune systems of weaned piglets are not fully mature and are also subjected to serious stress challenges related to oxidative stress and inflammation. Selenium (Se) is an essential element for pigs, with documented roles encompassing antioxidative and anti-inflammatory properties via selenoproteins. Sodium selenite and Se-enriched yeast are commonly acknowledged as conventional sources of Se for piglets. In the past decade, several novel Se sources have emerged in the field of weaned piglet nutrition. In this review, we will initially outline the historical timeline of Se sources as reported in weaned piglet nutrition. Afterwards, our attention will turn towards the nutritional regulation of Se sources in relation to the antioxidant and anti-inflammatory aspects of healthy weaned piglets. Ultimately, we will provide a detailed review highlighting the potential of emerging Se sources in alleviating various adverse effects of stress challenges faced by weaned piglets. These challenges include oxidative stress, enterotoxigenic Escherichia coli infection, lipopolysaccharide-induced inflammation, heat stress, and exposure to feed mycotoxins. The output of this review will emphasize the fundamental importance of incorporating emerging Se sources in the diet of weaned piglets.