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Abstract Background Mitochondrial dysfunction and neuronal damage are major sign of cytopathology in Huntington’s disease (HD), a neurodegenerative disease. Ubiquitin specific peptidase 11 (USP11) is a deubiquitinating enzyme involved in various physiological processes through regulating protein degradation. However, its specific role in HD is unclear. Methods To interfere with USP11 expression, adeno-associated viruses 2 containing USP11-specific shRNA were injected into the bilateral striatum of 12-week-old R6/1 and WT mice. In vitro, the inducible PC12 cell model of HD was used in which the expression of an N-terminal truncation of huntingtin, with either wild type (Q23) or expanded polyglutamine (Q74) can be induced by the doxycycline. USP11 was knocked down to study its role in HD. The protein expression patterns in Q74 cells were quantified by label-free proteomics to further explore the target protein of USP11. Detecting the association between USP11 and Phosphatase and Tensin Homolog (PTEN) through Co-IP. Results Herein, USP11 was found to be upregulated in the striatum of R6/1 mice (an HD model with gradual development of symptoms) in an age-dependent manner. The spontaneous HD was alleviated by silencing USP11, as evidenced by improved locomotor activity and spatial memory, attenuated striatal atrophy in R6/1 mice, reduced accumulation of mutant huntingtin protein, and restored mitochondrial function in vitro and in vivo. The results of label-free proteomics revealed a significant change in the protein expression profile. Through functional enrichment, we focused on PTEN, known as a negative regulator of the AKT pathway. We demonstrated that USP11 downregulation promoted ubiquitination modification of PTEN and activated the AKT pathway, and PTEN overexpression reversed the effects of USP11 knockdown. Conclusions Collectively, USP11 knockdown protects R6/1 mouse neurons from oxidative stress by alleviating mitochondrial dysfunction, thereby preventing the HD progression. This is achieved by inhibiting PTEN expression, which in turn activates the AKT pathway. This study suggests that USP11-PTEN-AKT signaling pathway may be a new attractive therapeutic target for HD.

Abstract Ferroptosis and autophagy are two main forms of regulated cell death (RCD). Ferroptosis is a newly identified RCD driven by iron accumulation and lipid peroxidation. Autophagy is a self-degradation system through membrane rearrangement. Autophagy regulates the metabolic balance between synthesis, degradation and reutilization of cellular substances to maintain intracellular homeostasis. Numerous studies have demonstrated that both ferroptosis and autophagy play important roles in cancer pathogenesis and cancer therapy. We also found that there are intricate connections between ferroptosis and autophagy. In this article, we tried to clarify how different kinds of autophagy participate in the process of ferroptosis and sort out the common regulatory pathways between ferroptosis and autophagy in cancer. By exploring the complex crosstalk between ferroptosis and autophagy, we hope to broaden horizons of cancer therapy.

Abstract Ceftazidime-avibactam (CZA) is currently one of the last resorts used to treat infections caused by carbapenem-resistant Enterobacteriaceae and Pseudomonas aeruginosa. However, KPC variants have become the main mechanism mediating CZA resistance in KPC-producing gram-negative bacteria after increasing the application of CZA. Our previous study revealed that CZA-resistant KPC-33 had emerged in carbapenem-resistant P. aeruginosa (CRPA) and had resulted in death due to hypervirulence and extensive drug resistance; however, the evolutionary path of KPC-33-producing CRPA has not been investigated. Here, we observed the emergence of bla KPC-33 in CRPA under drug pressure, leading to resistance to CZA. We further elucidated the pathway of resistance development due to bla KPC mutations in P. aeruginosa. Three KPC-producing P. aeruginosa (KPC-PA) strains (including one bla KPC-33-positive strain and two bla KPC-2-positive strains) were successively isolated from a hospitalized patient. The bla KPC-33-positive CZA-resistant strain SRPA0656 (CZA MIC >128 μg/mL, imipenem MIC = 32 μg/mL) was isolated after the bla KPC-2-positive P. aeruginosa SRP2863 (CZA MIC = 1 μg/mL, imipenem MIC >128 μg/mL) was treated with CZA. The subsequent use of carbapenems to treat the infection led to the re-emergence of the KPC-2-producing strain SRPA3703. Additionally, we collected four other KPC-33-producing P. aeruginosa strains. Antimicrobial susceptibility testing revealed that all the KPC-33-bearing P. aeruginosa strains in this study were multidrug-resistant but susceptible to colistin and amikacin. Whole-genome sequencing indicated that bla KPC-33 was located on two Tn4401-like transposons contained in the plasmids and that most of these plasmids could be transferred into P. aeruginosa PAO1Rif isolates. Growth rate determination demonstrated that the relative growth rate of P. aeruginosa harboring bla KPC-33 was faster than that of P. aeruginosa harboring bla KPC-2 in the logarithmic phase. Global phylogenetic analysis revealed that most KPC-PA strains were isolated from China and the USA. MLST revealed that the most common ST in KPC-PA was ST463, which was detected only in China, and that all the strains carried bla KPC-2 or its derivatives. These results indicated that the use of CZA for the treatment of KPC-2-producing P. aeruginosa may have contributed to the evolution of KPC-33. The widespread dissemination of KPC-PA (especially the ST463) and Tn4401 transposons may increase the spread of CRPA isolates carrying bla KPC-33. Close attention to the development of resistance to CZA during clinical treatment of CRPA infection and monitoring CZA-resistant strains is necessary to prevent further spread.

A comprehensive understanding of fine particulate matter (PM2.5) distribution is vital for addressing health concerns related to deteriorating air quality. While remotely sensed nighttime light (NTL) observations have proven effective in monitoring PM2.5 concentrations, their coarse resolution limits their ability to capture the fine-scale spatial variations within urban environments. To address this limitation, an improved simple spatial random forest model was employed to estimate PM2.5 concentrations using SDGSAT-1 Glimmer NTL data. The resultant PM2.5 concentration maps, with a resolution of 300 m, were generated for the winter of 2021 (R2 = 0.81) and cover four urban agglomerations (UAs) in China. Two population-weighted indicators were utilized to assess the nighttime population exposure to PM2.5. The findings suggest that population exposure to PM2.5 is highest in the Beijing-Tianjin-Hebei UA (66.84 μg/m3), followed by Chengdu-Chongqing (CC) (62.66 μg/m3), Yangtze River Delta (52.04 μg/m3), and Guangdong-Hong Kong-Macao Greater Bay Area (33.74 μg/m3). Notably, the CC UA exhibits the highest levels of exposure among children ($ \leq $ 5 years) and the elderly ($ \geq $ 65 years). These findings provide valuable insights for policymakers to prioritize pollution control strategies and measures.

The paper addresses the challenges of task migration and resource allocation in heterogeneous cloud–edge environments, where dynamic and stochastic conditions complicate efficient scheduling. To tackle this, the authors propose a novel scheduling algorithm combining soft actor–critic (SAC) agent with masked layer and graph convolutional network (GCN), namely MGSAC algorithm. MGSAC utilizes GCN to extract hidden structural features from the environment, enabling better adaptation to dynamic changes. Additionally, a learnable mask layer filters out ineffective actions, refining the selection of scheduling strategies and improving overall performance. By evaluating MGSAC on the real-world Bit-Brain dataset and simulating it using Cloud-Sim, experimental results demonstrate its superiority over existing algorithms in energy consumption, task response time, task migration time, and task Service-Level-Agreement violations rate, showcasing its effectiveness in real-world scenarios.

Abstract Background Low back pain is a major disorder that causes disability and is strongly associated with intervertebral disc degeneration (IDD). Because of the limitations of contemporary interventions, stem cell transplantation (SCT) has been increasingly used to regenerate degenerative discs. Nevertheless, analyses of high-impact papers in this field are rare. This study aimed to determine and analyze the 100 highest-cited documents on SCT in IDD. Methods The 100 highest-cited documents were retrieved from the Web of Science (WoS) database. Descriptive statistics were calculated and correlation analysis was conducted to determine the relationship between WoS citations, the Altmetric Attention Score (AAS), and Dimensions citations. Results The citation counts of the top 100 most cited papers ranged from 13 to 372. These studies were conducted in 17 countries and were published in 48 journals between 2003 and 2021. The top three contributing countries were the China (31), United States (22), and Japan (14). Bone marrow-derived stem cells were the most common type of stem cells (70.00%), followed by adipose-derived stem cells (13.75%), and nucleus pulposus-derived stem cells (7.50). Rabbit was the most studied species (41.25%), followed by rat (21.25%), human (13.75%), sheep (8.75%), dog (8.75%), and pig (6.25%). Tokai University School of Medicine (11) had the largest number of documents, followed by The University of Hong Kong (8), and Southeast University (4). Sakai D (10) was the most fruitful author, followed by Cheung KMC (6), Melrose J (3), Pettine K (3), Lotz JC (3), and Murphy MB (3). We observed a very high correlation between the WoS and Dimensions citations (p

Abstract The pathogenesis of breast cancer is still unclear. Small RNAs associated with extracellular vesicles (EVs) have been found to be involved in tumor development. It is important to explore the role of EVs small RNAs in breast cancer. In this study, we established a plasma EVS-associated small RNA dataset that included 120 women who were positive for breast cancer screening and 60 women who were negative. These small RNA included 2656 miRNAs, 728 piRNAs, and 154 tsRNAs. These data provide a reference for researchers to explore molecular diagnostic biomarkers for early breast lesions.

Abstract Background The hippocampus is associated with mood disorders, and the activation of quiescent neurogenesis has been linked to anxiolytic effects. Near-infrared (NIR) light has shown potential to improve learning and memory in human and animal models. Despite the vast amount of information regarding the effect of visible light, there is a significant gap in our understanding regarding the response of neural stem cells (NSCs) to NIR stimulation, particularly in anxiety-like behavior. The present study aimed to develop a new optical manipulation approach to stimulate hippocampal neurogenesis and understand the mechanisms underlying its anxiolytic effects. Methods We used 940 nm NIR (40 Hz) light exposure to stimulate hippocampal stem cells in C57BL/6 mice. The enhanced proliferation and astrocyte differentiation of NIR-treated NSCs were assessed using 5-ethynyl-2’-deoxyuridine (EdU) incorporation and immunofluorescence assays. Additionally, we evaluated calcium activity of NIR light-treated astrocytes using GCaMP6f recording through fluorescence fiber photometry. The effects of NIR illumination of the hippocampus on anxiety-like behaviors were evaluated using elevated plus maze and open-field test. Results NIR light effectively promoted NSC proliferation and astrocyte differentiation via the OPN4 photoreceptor. Furthermore, NIR stimulation significantly enhanced neurogenesis and calcium-dependent astrocytic activity. Moreover, activating hippocampal astrocytes with 40-Hz NIR light substantially improved anxiety-like behaviors in mice. Conclusions We found that flickering NIR (940 nm/40Hz) light illumination improved neurogenesis in the hippocampus with anxiolytic effects. This innovative approach holds promise as a novel preventive treatment for depression.

Since the outbreak of the Gaza conflict in October 2023, a severe humanitarian crisis has occurred across the entire Gaza Strip. Owing to the challenges of conducting traditional ground-based surveys in the region, satellite images have become critically important as an objective source of information. In response to the demands of humanitarian relief, this study utilized VIIRS, SDGSAT-1, and Yangwang-1 nighttime light (NTL) satellite images to provide a multi-scale assessment of the spatiotemporal dynamics of power supply in the Gaza Strip during the conflict. To reduce errors in quantitatively estimating power supply based on nighttime light, the quality of daily VIIRS NTL images was enhanced and radiometric intercalibrations were conducted between SDGSAT-1 and Yangwang-1 NTL images. The result indicates a severe disruption of power supply in the Gaza Strip as a consequence of the conflict. Specifically, the overall power supply had a sharp decline shortly after the outbreak of the conflict on 7 October 2023 and persisted in a downtrend during the conflict, culminating in a reduction of around 94% as of 1 March 2024. In contrast, the power supply in areas surrounding the Gaza Strip remained relatively stable during the conflict. On 2 December 2023, 24 municipalities were found to have significant reductions in power supply exceeding 90%, and around 95% of buildings had power losses of more than 75%. Furthermore, approximately 70% of hospitals and UNRWA schools in the Gaza Strip were identified to have power outages on 1 January 2024. Among the five governorates of the Gaza Strip, Rafah was the most resilient in terms of power supply during the conflict. This study could make a positive contribution to the timely assessments of the Gaza conflict and support the implementation of humanitarian relief efforts.

Abstract Proinsulin translation and folding is crucial for glucose homeostasis. However, islet β-cell control of Proinsulin translation remains incompletely understood. Here, we identify OSGEP, an enzyme responsible for t6A37 modification of tRNANNU that tunes glucose metabolism in β-cells. Global Osgep deletion causes glucose intolerance, while β-cell-specific deletion induces hyperglycemia and glucose intolerance due to impaired insulin activity. Transcriptomics and proteomics reveal activation of the unfolded protein response (UPR) and apoptosis signaling pathways in Osgep-deficient islets, linked to an increase in misfolded Proinsulin from reduced t6A37 modification. Osgep overexpression in pancreas rescues insulin secretion and mitigates diabetes in high-fat diet mice. Osgep enhances translational fidelity and alleviates UPR signaling, highlighting its potential as a therapeutic target for diabetes. Individuals carrying the C allele at rs74512655, which promotes OSGEP transcription, may show reduced susceptibility to T2DM. These findings show OSGEP is essential for islet β-cells and a potential diabetes therapy target.

Abstract Background Exosome small RNAs are believed to be involved in the pathogenesis of cancer, but their role in breast cancer is still unclear. This study utilized machine learning models to screen for key exosome small RNAs and analyzed and validated them. Method Peripheral blood samples from breast cancer screening positive and negative people were used for small RNA sequencing of plasma exosomes. The differences in the expression of small RNAs between the two groups were compared. We used machine learning algorithms to analyze small RNAs with significant differences between the two groups, fit the model through training sets, and optimize the model through testing sets. We recruited new research subjects as validation samples and used PCR-based quantitative detection to validate the key small RNAs screened by the machine learning model. Finally, target gene prediction and functional enrichment analysis were performed on these key RNAs. Results The machine learning model incorporates six small RNAs: piR-36,340, piR-33,161, miR-484, miR-548ah-5p, miR-4282, and miR-6853-3p. The area under the ROC curve (AUC) of the machine learning model in the training set was 0.985 (95% CI = 0.948-1), while the AUC in the test set was 0.972 (95% CI = 0.882–0.995). RT-qPCR was used to detect the expression levels of these key small RNAs in the validation samples, and the results revealed that their expression levels were significantly different between the two groups (P

Abstract Background Mitochondrial calcium uniporter (MCU) plays pleiotropic roles in cellular physiology and pathology that contributes to a variety of diseases, but the role and potential mechanism of MCU in the pathogenesis of metabolic dysfunction-associated steatohepatitis (MASH) remain poorly understood. Methods and results Here, hepatic knockdown of MCU in C57BL/6J mice was achieved by tail vein injection of AAV8-mediated the CRISPR/Cas9. Mice were fed a Choline-deficient, L-amino acid-defined high-fat diet (CDAHFD) for 8 weeks to induce MASH and fibrosis. We find that expression of MCU enhanced in MASH livers of humans and mice. MCU knockdown robustly limits lipid droplet accumulation, steatosis, inflammation, and hepatocyte apoptotic death during MASH development both in vivo in mice and in vitro in cellular models. MCU-deficient mice strikingly mitigate MASH-related fibrosis. Moreover, the protective effects of MCU knockdown against MASH progression are accompanied by a reduced level of mitochondrial calcium, limiting hepatic oxidative stress, and attenuating mitochondrial dysfunction. Mechanically, RNA sequencing analysis and protein immunoblotting indicate that knockdown MCU inhibited the Hippo/YAP pathway activation and restored the AMP-activated protein kinase (AMPK) activity during MASH development both in vitro and in vivo. Conclusions MCU is up-regulated in MASH livers in humans and mice; and hepatic MCU knockdown protects against diet-induced MASH and fibrosis in mice. Thus, targeting MCU may represent a novel therapeutic strategy for MASH and fibrosis. Graphical Abstract

Metamaterials with active tunability of electromagnetic response have attracted much attention due to their flexibility and applicability in a wide range of optoelectronic applications. In this study, a mid-infrared (MIR) H-shaped metamaterial absorber (HMA) with high tunability is proposed. The structure of HMA is composed of one longitudinal and two transverse metal bars, forming an H-shaped resonator. By varying structural parameters, the HMA achieves perfect triple-band absorption. The resonant intensities of first and second resonances can be modulated linearly at the wavelength of 5.3 μm, while the resonant intensity of third resonance can be kept as stable at the wavelength of 7.3 μm. By moving the transverse metal bar, the maximum tuning range of resonance is 290 nm. Due to the non-rotationally symmetric configuration of HMA, it exhibits polarization-dependence characteristic. HMA exhibits the switchable function from triple-resonance to double-resonance. These results prove that the proposed HMA can be used for applications in gas sensing, polarization controlling, and IR filtering fields.

Lithium hexafluorophosphate (LiPF6), the most commonly used lithium battery electrolyte salt, is vulnerable to heat and humidity. Quantitative and qualitative determination the variation of LiPF6 have always relied on advanced equipment. Herein, we develop a fast, convenient, high-selective fluorescence detection method based on metal–organic cages (MOC), whose emission is enhanced by nearly 20 times in the presence of LiPF6 with good stability and photobleaching resistance. The fluorescent probe can also detect moisture in battery electrolyte. We propose and verify that the luminescence enhancement is due to the presence of hydrogen bond-induced enhanced emission effect in cages. Fluorescent excitation-emission matrix spectra and variable-temperature nuclear magnetic resonance spectroscopy are employed to clarify the role of hydrogen bonds in guest-loaded cages. Density functional theory (DFT) calculation is applied to simulate the structure of host-guest complexes and estimate the adsorption energy involved in the system. The precisely matched lock-and-key model paves a new way for designing and fabricating novel host structures, enabling specific recognition of other target compounds.

Abstract Parkinson’s disease (PD) and Dementia with Lewy Bodies (DLB) are neurodegenerative disorders characterized by the accumulation of α-synuclein aggregates. α-synuclein forms droplets via liquid-liquid phase separation (LLPS), followed by liquid-solid phase separation (LSPS) to form amyloids, how this process is physiologically-regulated remains unclear. β-synuclein colocalizes with α-synuclein in presynaptic terminals. Here, we report that β-synuclein partitions into α-synuclein condensates promotes the LLPS, and slows down LSPS of α-synuclein, while disease-associated β-synuclein mutations lose these capacities. Exogenous β-synuclein improves the movement defects and prolongs the lifespan of an α-synuclein-expressing NL5901 Caenorhabditis elegans strain, while disease-associated β-synuclein mutants aggravate the symptoms. Decapeptides targeted at the α-/β-synuclein interaction sites are rationally designed, which suppress the LSPS of α-synuclein, rescue the movement defects, and prolong the lifespan of C. elegans NL5901. Together, we unveil a Yin-Yang balance between α- and β-synuclein underlying the normal and disease states of PD and DLB with therapeutical potentials.

Abstract. Background:. The association and its population heterogeneities between low-density lipoprotein cholesterol (LDL-C) and all-cause and cardiovascular mortality remain unknown. We aimed to examine the dose-dependent associations of LDL-C levels with specific types of cardiovascular disease (CVD) mortality and heterogeneities in the associations among different population subgroups. Methods:. A total of 2,968,462 participants aged 35–75 years from China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART) (2014–2019) were included. Cox proportional hazard models and Fine–Gray subdistribution hazard models were used to estimate associations between LDL-C categories (

Abstract Companion planting of white clover (Trifolium repens L.) with orchard grass (Dactylis glomerata L.), a famous hay grass, improves the forage quality of orchard grass. Microbiome profiling techniques can reveal the specific role of white clover companion planting with orchard grass. This study aimed to explore the microbiome distribution and gene functions of rhizosphere and non-rhizosphere soil via companion planting systems of white clover and orchard grass. From metagenomics sequencing analysis, we confirmed the significant role of white clover on soil environment modeling during companion planting with orchard grass. Twenty-eight biomarkers of rhizosphere soil organisms were identified during companion planting, including Proteobacteria, Betaproteobacteria, Flavobacteriia, and Caulobacterales. The number of gene functions of nitrogen and carbon fixation in companion planting was higher than that in single plants, indicating new functional flora for companion planting. We characterized specific rhizosphere effects, typical biomarker flora, and potential regulatory mechanisms for white clover-related companion planting by metagenomics analyses.

This review critically examines the integration of Virtual Reality (VR) and Augmented Reality (AR) in medical training across Low- and Middle-Income Countries (LMICs), offering a novel perspective by combining quantitative analysis with qualitative insights from medical students in Egypt and Ghana. Through a systematic review process, 17 peer-reviewed studies published between 2010 and 2023 were analysed. Altogether, these studies involved a total of 887 participants. The analysis reveals a growing interest in VR and AR applications for medical training in LMICs with a peak in published articles in 2023, indicating an expanding research landscape. A unique contribution of this review is the integration of feedback from 35 medical students assessed through questionnaires, which demonstrates the perceived effectiveness of immersive technologies over traditional 2D illustrations in understanding complex medical concepts. Key findings highlight that VR and AR technologies in medical training within LMICs predominantly focus on surgical skills. The majority of studies focus on enhancing surgical training, particularly general surgery. This emphasis reflects the technology’s strong alignment with the needs of LMICs, where surgical skills training is often a priority. Despite the promising applications and expanding interest in VR and AR, significant challenges such as accessibility and device limitations remain, demonstrating the need for ongoing research and integration with traditional methods to fully leverage these technologies for effective medical education. Therefore, this review provides a comprehensive analysis of existing VR and AR applications, their evaluation methodologies, and student perspectives to address educational challenges and enhance healthcare outcomes in LMICs.

Abstract The primary impediment to the success of immunotherapy lies in the immune evasion orchestrated by tumors, contributing to the suboptimal overall response rates observed. Despite this recognition, the intricacies of the underlying mechanisms remain incompletely understood. Through preliminary detection of clinical patient tissues, we have found that ALDH1A1 was a key gene for the prognosis of cancer patients and tumor glycolysis. In vitro experiments and tumor formation in nude mice suggested that targeting ALDH1A1 could inhibit tumor growth. Through further analysis of xenograft tumor models in immune-normal mice and flow cytometry, we found that deficiency in ALDH1A1 could promote immune system suppression of tumors in vivo. Specifically, RNA-seq analysis, combined with qPCR and western blot, identified the transcription factor ZBTB7B as downstream of ALDH1A1. The binding sites of the transcription factor ZBTB7B on the LDHA promoter region, which is responsible for regulating the rate-limiting enzyme gene LDHA in glycolysis, were determined using luciferase reporter gene detection and Chip-qPCR, respectively. In addition, the increased SUMOylation of ZBTB7B stabilized its transcriptional activity. Further in vivo and in vitro experiments confirmed that the combination of targeting ALDH1A1 and ZBTB7B with immune checkpoint inhibitors could synergistically inhibit tumors in vivo. Finally, after conducting additional verification of patient tissue and clinical data, we have confirmed the potential translational value of targeting ALDH1A1 and ZBTB7B for tumor immunotherapy. These results emphasize the potential translational significance of targeting ALDH1A1 and ZBTB7B in the realm of tumor immunotherapy. The convergence of ALDH1A1 inhibition and immune checkpoint blockade, particularly with PD-L1/PD-1 mAb, presents a compelling avenue for curtailing tumor immune escape.

Abstract Cadmium (Cd) is a biologically non-essential heavy metal, a major soil pollutant, and extremely harmful to plants. The phytohormone methyl jasmonate (MeJA) plays an important role in plant heavy-metal resistance. However, the understanding of the effects of MeJA supply level on alleviating Cd toxicity in plants is limited. Here, we investigated how MeJA regulated the development of physiological processes and cell wall modification in Cosmos bipinnatus. We found that low concentrations of MeJA increased the dry weight of seedlings under 120 µM Cd stress by reducing the transport of Cd from roots to shoots. Moreover, a threshold concentration of exogenous MeJA increased the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) in plant roots, the concentration of Cd in the root cell wall, and the contents of pectin and hemicellulose 1 polysaccharides, through converting Cd into pectin-bound forms. These results suggested that MeJA mitigated Cd toxicity by modulating root cell wall polysaccharide and functional group composition, especially through pectin polysaccharides binding to Cd, with effects on Cd transport capacity, specific chemical forms of Cd, and homeostatic antioxidant systems in C. bipinnatus.

Aiming at the problem that frequently train traction starting causes wheel wear and fatigue damage, on the basis of the constant traction force, the influence of the speed at the end of the constant power section of different traction characteristic curves on wheel wear and fatigue was studied. SIMPACK and MATLAB software were used for co-simulation to establish the dynamic model of urban rail trains(URTs) under different traction characteristics and the wheel wear model based on Archard. The influence of the speed at the end of the constant power section of the traction characteristic curve on the wheel-rail creepage, wheel wear depth, wear area and fatigue index of URTs under different starting torque of traction motor was analyzed. The results show that during the train traction starting process, the larger the starting torque of the motor, the greater the wheel-rail creepage, and the wheel wear depth and wear area, while the smaller the fatigue index; For agiven starting torque of the motor, with the increase of the speed at the end of the constant power section of the train traction characteristic curve, the wheel-rail creepage, and the wheel wear depth and wear area also increase, while the fatigue index decreases.When the starting torque of the motor increases from 800 N·m to 1 400 N·m, the maximum growth rates of wheel wear depth and wear area are 6.9% and 12.6%, respectively, while the maximum decline rate of fatigue index is 7.2%; When the speed at the end of the constant power section increases from 50 km/h to 80 km/h, the maximum growth rates of wheel wear depth and wear area are 4.4% and 4.3%,respectively, and the maximum decline rate of fatigue index is 1.9%.The effects of starting torque and the speed at the end of the constant power section on wheel wear and fatigue are obtained, which provides reference for the design of vehicle traction characteristics, motor control and wheel operation and maintenance.

ObjectiveTo investigate changes of brain functional activity in patients with acute unilateral vestibulopathy (AUVP) using functional magnetic resonance imaging (fMRI).MethodsWe studied 32 AUVP patients and 30 healthy controls (HC) who received resting-state fMRI scanning. Methods of voxel-based amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC) were adopted to compare the difference in brain function between the two groups. In addition, we evaluated the associations between abnormal neuroimaging results and clinical data in AUVP patients.ResultsCompared with HC, patients with AUVP showed lower ALFF in brain regions of bilateral insular, right precentral gyrus, left inferior frontal gyrus and right middle frontal gyrus, as well as higher ALFF in left cerebellar anterior lobe. Using these abnormal brain areas as seeds, we observed decreased FC between left insular and left precuneus in AUVP patients. Furthermore, AUVP patients showed increased FC between left insular and left supplementary motor area. Results of correlation analysis indicated that ALFF value (z-value) in left insular was negatively correlated with the canal paresis value (p = 0.005, r = −0.483), and the FC (z-value) between left insular and left precuneus was negatively correlated with dizziness handicap inventory score (p = 0.012, r = −0.438) in patients with AUVP.ConclusionPatients with AUVP during acute period showed altered functional activity and connectivity in brain regions mainly involved in motor control and vestibular information processing. These changes in brain functional activity and connectivity were potentially attributed to decreased vestibular input resulting from unilateral peripheral vestibular impairment.

Interleukin enhancer binding factor 2 (ILF2), formerly called nuclear factor 45 (NF45), is widely expressed in normal human tissues. ILF2 often binds to interleukin enhancer binding factor 3 (ILF3) and regulates gene expression in several ways, participating in multiple DNA and RNA metabolism pathways. Recent studies have shown that ILF2 expression is significantly upregulated in esophageal cancer, lung cancer, gastric cancer, and other malignant tumors, which can promote tumor development and tumor cell proliferation, affect the cell cycle, and induce epithelial-mesenchymal transition. ILF2 expression is closely related to tumor cell migration and invasion, neo-angiogenesis, and patient prognosis. ILF2 is expected to become a biomarker for the early diagnosis of patients with tumors and assessing their prognosis. This article reviews the role of ILF2 in malignant tumors and its related mechanisms.

Time-restricted eating (TRE) has been shown to extent lifespans in drosophila and mouse models by affecting metabolic and anti-inflammatory activities. However, the effect of TRE on the human immune system, especially on immunosenescence, intestinal microbiome, and metabolism remains unclear. We conducted a 30-day 16:8 TRE single-arm clinical trial with 49 participants. Participants consumed daily meals from 9 a.m. to 5 p.m., provided by a nutrition canteen with a balanced, calorie-appropriate nutrition, which is designed by clinical nutritionists (ChiCTR2200058137). We monitored weight changes and weight-related parameters and focused on changes in the frequency of CD4+ senescent T cells, immune repertoire from peripheral blood, as well as serum metabolites and gut microbiota. We found that up to 95.9 % of subjects experienced sustained weight loss after TRE. The frequency of circulating senescent CD4+ T cells was decreased, while the frequency of Th1, Treg, Tfh-like, and B cells was increased. Regarding the immune repertoire, the proportions of T cell receptor alpha and beta chains were increased, whereas B cell receptor kappa and lambda chains were reduced. In addition, a reduced class switch recombination from immunoglobulin M (IgM) to immunoglobulin A (IgA) was observed. TRE upregulated the levels of anti-inflammatory and anti-aging serum metabolites named sphingosine-1-phosphate and prostaglandin-1. Additionally, several anti-inflammatory bacteria and probiotics were increased, such as Akkermansia and Rikenellaceae, and the composition of the gut microbiota tended to be “younger”. Overall, TRE showed multiple anti-aging effects, which may help humans maintain a healthy lifestyle to stay “young”. Clinical Trial Registration URL: https://www.chictr.org.cn/showproj.html?proj=159876.

Ceftazidime-avibactam (CZA) resistance is a huge threat in the clinic; however, the underlying mechanism responsible for high-level CZA resistance in Pseudomonas aeruginosa (PA) isolates remains unknown. In this study, a total of 5,763 P. aeruginosa isolates were collected from 2010 to 2022 to investigate the ceftazidime-avibactam (CZA) high-level resistance mechanisms of Pseudomonas aeruginosa (PA) isolates in China. Fifty-six PER-producing isolates were identified, including 50 isolates carrying blaPER-1 in PA, and 6 isolates carrying blaPER-4. Of these, 82.1% (46/56) were classified as DTR-PA isolates, and 76.79% (43/56) were resistant to CZA. Importantly, blaPER-1 and blaPER-4 overexpression led to 16-fold and >1024-fold increases in the MICs of CZA, respectively. WGS revealed that the blaPER-1 gene was located in two different transferable IncP-2-type plasmids and chromosomes, whereas blaPER-4 was found only on chromosomes and was carried by a class 1 integron embedded in a Tn6485-like transposon. Overexpression of efflux pumps may be associated with high-level CZA resistance in blaPER-1-positive strains. Kinetic parameter analysis revealed that PER-4 exhibited a similar kcat/Km with ceftazidime and a high (∼3359-fold) IC50 value with avibactam compared to PER-1. Our study found that overexpression of PER-1 combined with enhanced efflux pump expression and the low affinity of PER-4 for avibactam contributes to high-level resistance to CZA. Additionally, the Tn6485-like transposon plays a significant role in disseminating blaPER. Urgent active surveillance is required to prevent the further spread of high-level CZA resistance in DTR-PA isolates.

ABSTRACTDue to the difficulty of obtaining survey data, nighttime light (NTL) imagery has emerged as valuable alternative data for asset wealth estimation. However, the nighttime light values do not differentiate between levels of asset wealth in various unlit areas, as the nighttime light values in unlit areas are all 0. Here, NTL data and World Settlement Footprint (WSF) data were combined to extract multidimensional luminous features that are also differential in unlit areas to estimate asset wealth in nighttime light-poor areas at 500 m × 500 m spatial units. A random forest model was used to estimate asset wealth, based on the shortest distance of settlements to three categories of lighted areas, along with the brightness values derived from the nearest lighted area and the settlements themselves. This model achieved an explanation of 71% for the variation in settlement asset wealth and demonstrated effectiveness in estimating the asset wealth of unlit areas. The MAE and RMSE of asset wealth estimation in the unlit clusters were 4.03 and 5.28, respectively. Asset wealth is generally low across most African settlements, with clear two-tier differentiation in Africa. In summary, the proposed method can extensively explore the luminous information in unlit areas.

Exposure to ambient fine particulate matter (PM2.5) poses a significant global health challenge. However, a major obstacle for epidemiological studies and risk assessment lies in the absence of high-resolution spatiotemporal exposure estimates. Here, we present an integrated framework to achieve accurate estimations of population exposure to PM2.5 and assess related health risks by incorporating high temporal (hourly) and high spatial (1-km) PM2.5 concentrations and population density, using Beijing, China, in 2015 as an example. Firstly, hourly PM2.5 concentrations were estimated using a functional data model by integrating the gap-filled satellite-based aerosol optical depth data at 1-km resolution with hourly in-situ PM2.5 observations. Then, we calculated the population-level exposure to PM2.5 and associated health impacts incorporating both hourly PM2.5 and population information. We also investigated the bias of exposure and health impact assessment using coarse spatial or temporal PM2.5 and population data. Our findings revealed that exposure to PM2.5 resulted in 33,830, 21388, and 5,302 premature deaths in 2015 attributable to all-cause, cardiovascular, and respiratory diseases, respectively. A sensitivity analysis conducted underscored the critical importance of considering the high spatiotemporal heterogeneity of both PM2.5 concentrations and population density when investigating population-level PM2.5 exposure and related health impacts. Insights on more accurate PM2.5 exposure assessment from this study can help policymakers better assess improvements after clean air actions and analyze exposure inequality, and thereafter develop more effective pollution mitigation strategies.

Traditional methods for measuring asset wealth face limitations due to data scarcity, making it challenging to apply them on a large scale and over long periods with fine granularity. Publicly available satellite images, such as nighttime light imagery, have become an important alternative data source for estimating asset wealth. This study thoroughly exploited the spatial neighborhood information of nighttime light, combined with other remote sensing features and the cross-national, temporally comparable International Wealth Index (IWI), to construct long-term asset wealth estimation models for African countries with and without sample data. Based on these models, it generates asset wealth estimates for African settlements at a 500 m spatial resolution from 2012 to 2022. The R2 values for the models of countries with and without sample data are 0.85 and 0.76, respectively, with mean absolute errors of 6.08 and 8.35, and root means square errors of 8.52 and 10.81, respectively. Additionally, the accuracy of the temporal variation estimates surpasses previous related studies, achieving an R2 of 0.60. From 2012 to 2022, the overall IWI increased from 28.80 to 30.80, representing an increase of 0.11 standard deviations. In addition to countries with household survey data, the proposed method can also accurately estimate asset wealth for countries without survey data and effectively track asset wealth changes over time.

Sudan has been racked by complex and volatile conflicts for decades, with a new round of civil conflict erupting in April 2023, leading to significant loss of life and property. Despite the ongoing violence, the associations between conflicts and local contextual factors remain ambiguous. In this study, we developed an event-grid dataset, consisting of 50,033 observations with 20 variables derived from nighttime light (NTL) data, OpenStreetMap data, and other geographic data. Machine learning algorithms were employed to model the outbreak of conflict in 2023. Furthermore, the SHapley Additive exPlanations method was utilized to explain the relationships between diverse explanatory variables and conflicts. The results indicate that eXtreme Gradient Boosting model outperforms other models, such as Categorical Boosting and Light Gradient Boosting Machine. Multiple factors jointly contribute to conflicts. NTL-derived variables and transportation-related variables emerge as the most influential factors, followed by climate and agricultural factors. Regions characterized by economic inequality and proximity to transportation hubs are found to be more prone to conflicts. Additionally, variables impact the outbreak of conflict not only individually but also through mutual interactions. Notably, this study enhances a comprehensive and quantitative understanding of conflicts in Sudan, providing valuable insights to support humanitarian aid efforts.

BackgroundIn medical practice, atrial fibrillation (AF) is intricately associated with heart failure (HF). Currently, ethanol infusion of vein of Marshall (EIVOM) for AF ablation in HF patients remains significantly limited.MethodThis was a non-randomized, single-center, retrospective observational study. AF patients received 4-step ablation composed of EIVOM, pulmonary vein isolation (PVI) and linear ablation. The primary composite endpoint was defined as recurrence of atrial tachycardia over 30 s. Propensity score matching (PSM) was performed to reduce selection bias.ResultsFrom April 2020 to May 2022, 362 patients were included, comprising of 182 HF patients and 180 non-HF patients. EIVOM success rate was lower in HF patients than non-HF patients (86.8% vs. 93.9%). Cardiac effusion was more common in HF patients (44.0% vs. 37.2%), and 2 cases of atrial-esophageal fistula were observed in the HF group. During a median follow-up of 12 months, no significant difference in the primary endpoint was observed between HF and non-HF group. Different HF subgroups had similar AF recurrence. After PSM, AF recurrence rate remained statistically equivalent between the HF and non-HF groups.ConclusionEVIOM combining catheter ablation can be completed with comparable success rate in AF patients with or without HF. However, peri-procedural safety is a concern for HF patients undergoing EIVOM combing AF catheter ablation. During the follow-up, HF status before ablation is not related with increased AF recurrence.

IntroductionAnxiety diagnoses have surged recently during and after the COVID-19 pandemic. Lorazepam is widely recognized for its efficacy in treatment of anxiety, as well as insomnia, etc. However, the long-term safety profile of lorazepam in extensive patient populations has not been thoroughly established.MethodsThis study aims to evaluate the potential lorazepam-associated adverse events (AEs) using data mining of the Food and Drug Administration Adverse Event Reporting System (FAERS) of the United States, seeking to provide a guidance for the future therapeutic practices.ResultsOur study revealed drug abuse, suicide attempt, sopor, delirium, and psychotic disorder were among the most prevalent AEs linked to lorazepam. In addition to common AEs, we also found that patients using lorazepam may have the risk of abnormal fat metabolism, cardiac impairment, and immunosuppression-related disorders.DiscussionIn general, our research has unveiled novel AE signals and expanded our understanding of the safety profile of lorazepam in clinical practices, providing guidance for its rational use.

In the post-pandemic era, a growing emphasis on elevating the quality of tourism consumption has been observed. This study explores how different language portfolios on product packaging can influence tourists’ perceptions and purchase intentions to promote sustainable consumption. Previous studies on tourism product strategies often addressed national identity, power perception, and stereotypes, but overlooked the fundamental role of multilingual packaging strategies for enterprises and tourists. This study focuses on sake, which combines cultural and natural attributes, as its experimental object. Sub-studies 1, 2, and 3 empirically analyzed how perceptions of competence and warmth are affected by monolingual, bilingual, and trilingual properties of language packaging, respectively, and their impact on tourists’ purchase intentions. The findings suggest that monolingual and bilingual packaging enhances tourists’ competence perception, while trilingual packaging enhances tourists’ warmth perception, thereby stimulating tourists’ positive purchase intentions. Additionally, cultural identity significantly moderates the effectiveness of multilingual packaging strategies. Understanding these dynamics can help tourism enterprises design more effective promotional activities and packaging language strategies for tourists’ preferences. It can also enhance the post-pandemic tourism industry.

Background: Clear cell renal cell carcinoma (ccRCC) is a serious threat to human life. It is very important to clarify the pathogenesis of ccRCC. In this study we evaluated the clinical value of HADH and explored its role and mechanism in the malignant progression of ccRCC. Methods: HADH expression and its relationship with prognosis were analyzed using bioinformatics database. RT-PCR, Western blot and immunohistochemistry were used to examine the expression of HADH in ccRCC tissues and tissue microarrays. To examine the cell proliferation, apoptosis, migration and invasion ability, ccRCC cells with HADH overexpressed were constructed. Xenograft experiments were performed to determine the role of HADH. Non-target metabolomics was applied to explore the potential metabolic pathway by which HADH inhibited ccRCC progression. Plasmid pcDNA3.1-NRF2 was used to confirm whether HADH inhibited the process of ccRCC cells through NRF2-related glutathione (GSH) synthesis. Results: Bioinformatics database analysis showed that HADH expression was significantly decreased in ccRCC tissues, and its low expression predicted a poor prognosis. Both ccRCC tissues and tissue microarrays exhibited a significantly decreased HADH level compared with adjacent normal renal tissues. HADH overexpression inhibited the malignant behaviors of ccRCC cells. Furthermore, HADH overexpression attenuated GSH synthesis and induced oxidative stress damage. Exogenously increased NRF2 effectively attenuated the inhibitive effect of HADH overexpression on ccRCC cells. Conclusion: Our data revealed that HADH suppressed the malignant behaviors of ccRCC cells by attenuating GSH synthesis through inhibition of NRF2 nuclear translocation, and HADH might be a novel therapeutic target for ccRCC treatment.

The cerebral vasculature plays a significant role in the development of Alzheimer’s disease (AD), however, the specific association between them remains unclear. In this paper, based on the benefits of photoacoustic imaging (PAI), including label-free, high-resolution, in vivo imaging of vessels, we investigated the structural changes of cerebral vascular in wild-type (WT) mice and AD mice at different ages, analyzed the characteristics of the vascular in different brain regions, and correlated vascular characteristics with cognitive behaviors. The results showed that vascular density and vascular branching index in the cortical and frontal regions of both WT and AD mice decreased with age. Meanwhile, vascular lacunarity increased with age, and the changes in vascular structure were more pronounced in AD mice. The trend of vascular dysfunction aligns with the worsening cognitive dysfunction as the disease progresses. Here, we utilized in vivo PAI to analyze the changes in vascular structure during the progression of AD, elucidating the spatial and temporal correlation with cognitive impairment, which will provide more intuitive data for the study of the correlation between cerebrovascular and the development of AD.

Abstract Background Detection of cancer and identification of tumor origin at an early stage improve the survival and prognosis of patients. Herein, we proposed a plasma cfDNA-based approach called TOTEM to detect and trace the cancer signal origin (CSO) through methylation markers. Methods We performed enzymatic conversion-based targeted methylation sequencing on plasma cfDNA samples collected from a clinical cohort of 500 healthy controls and 733 cancer patients with seven types of cancer (breast, colorectum, esophagus, stomach, liver, lung, and pancreas) and randomly divided these samples into a training cohort and a testing cohort. An independent validation cohort of 143 healthy controls, 79 liver cancer patients and 100 stomach cancer patients were recruited to validate the generalizability of our approach. Results A total of 57 multi-cancer diagnostic markers and 873 CSO markers were selected for model development. The binary diagnostic model achieved an area under the curve (AUC) of 0.907, 0.908 and 0.868 in the training, testing and independent validation cohorts, respectively. With a training specificity of 98%, the specificities in the testing and independent validation cohorts were 100% and 98.6%, respectively. Overall sensitivity across all cancer stages was 65.5%, 67.3% and 55.9% in the training, testing and independent validation cohorts, respectively. Early-stage (I and II) sensitivity was 50.3% and 45.7% in the training and testing cohorts, respectively. For cancer patients correctly identified by the binary classifier, the top 1 and top 2 CSO accuracies were 77.7% and 86.5% in the testing cohort (n = 148) and 76.0% and 84.0% in the independent validation cohort (n = 100). Notably, performance was maintained with only 21 diagnostic and 214 CSO markers, achieving a training AUC of 0.865, a testing AUC of 0.866, and an integrated top 2 accuracy of 83.1% in the testing cohort. Conclusions TOTEM demonstrates promising potential for accurate multi-cancer detection and localization by profiling plasma methylation markers. The real-world clinical performance of our approach needs to be investigated in a much larger prospective cohort.

Abstract Cloud environment is a virtual, online, and distributed computing environment that provides users with large-scale services. And cloud monitoring plays an integral role in protecting infrastructures in the cloud environment. Cloud monitoring systems need to closely monitor various KPIs of cloud resources, to accurately detect anomalies. However, due to the complexity and highly dynamic nature of the cloud environment, anomaly detection for these KPIs with various patterns and data quality is a huge challenge, especially those massive unlabeled data. Besides, it’s also difficult to improve the accuracy of the existing anomaly detection methods. To solve these problems, we propose a novel Dynamic Graph Transformer based Parallel Framework (DGT-PF) for efficiently detect system anomalies in cloud infrastructures, which utilizes Transformer with anomaly attention mechanism and Graph Neural Network (GNN) to learn the spatio-temporal features of KPIs to improve the accuracy and timeliness of model anomaly detection. Specifically, we propose an effective dynamic relationship embedding strategy to dynamically learn spatio-temporal features and adaptively generate adjacency matrices, and soft cluster each GNN layer through Diffpooling module. In addition, we also use nonlinear neural network model and AR-MLP model in parallel to obtain better detection accuracy and improve detection performance. The experiment shows that the DGT-PF framework have achieved the highest F1-Score on 5 public datasets, with an average improvement of 21.6% compared to 11 anomaly detection models.

Abstract Background Adverse drug events (ADEs) represent challenges affecting Africa’s healthcare systems owing to the increased healthcare expenditure and negative health outcomes of ADEs. Objectives We aimed to systematically review published studies on ADEs and synthesize the existing evidence of ADE prevalence in Africa. Methods Studies reporting on ADE occurrence in African settings and published from Jan 1, 2000 to Oct 1, 2023 were identified by searching PubMed, EBSCO, Science Direct, and Web of Science. Studies that either articulately investigated ADEs caused by clinical condition (such as HIV patients) or ADEs caused by exposure to specific drug(s) (such as antibiotics) were considered specific and the remaining were general. Grouped ADE prevalence rates were described using median and interquartile range (IQR). PROSPERO registration (CRD42022374095). Results We included 78 observational studies from 15 African countries that investigated the prevalence of ADEs leading to hospital admissions (17 studies), developed during hospitalizations (30 studies), and captured in the outpatient departments (38 studies) or communities (4 studies). Twelve studies included multiple settings. The median prevalence of ADE during hospitalization was 7.8% (IQR: 4.2–21.4%) and 74.2% (IQR: 54.1–90.7%) in general and specific patients, respectively. The ADE-related fatality rate was 0.1% and 1.3% in general and specific patients. The overall median prevalence of ADEs leading to hospital admissions was 6.0% (IQR: 1.5–9.0%); in general, patients and the median prevalence of ADEs in the outpatient and community settings were 22.9% (IQR: 14.6–56.1%) and 32.6% (IQR: 26.0–41.3%), respectively, with a median of 43.5% (IQR: 16.3–59.0%) and 12.4% (IQR: 7.1–28.1%) of ADEs being preventable in general and specific patients, respectively. Conclusions The prevalence of ADEs was significant in both hospital and community settings in Africa. A high ADE prevalence was observed in specific patients, emphasizing important areas for improvement, particularly in at-risk patient groups (e.g., pediatrics, HIV, and TB patients) in various settings. Due to limited studies conducted in the community setting, future research in this setting is encouraged.

With the incredible growth of the scale and complexity of datasets, creating proper visualizations for users becomes more and more challenging in large datasets. Though several visualization recommendation systems have been proposed, so far, the lack of practical engineering inputs is still a major concern regarding the usage of visualization recommendations in the industry. In this paper, we proposed AVA, an open-sourced web-based framework for Automated Visual Analytics. AVA contains both empiric-driven and insight-driven visualization recommendation methods to meet the demands of creating aesthetic visualizations and understanding expressible insights respectively. The code is available at https://github.com/antvis/AVA.

Abstract Background Incomplete radiofrequency ablation (iRFA) in hepatocellular carcinoma (HCC) often leads to local recurrence and distant metastasis of the residual tumor. This is closely linked to the development of a tumor immunosuppressive environment (TIME). In this study, underlying mechanisms and potential therapeutic targets involved in the formation of TIME in residual tumors following iRFA were explored. Then, TAK-981-loaded nanocomposite hydrogel was constructed, and its therapeutic effects on residual tumors were investigated. Results This study reveals that the upregulation of small ubiquitin-like modifier 2 (Sumo2) and activated SUMOylation is intricately tied to immunosuppression in residual tumors post-iRFA. Both knockdown of Sumo2 and inhibiting SUMOylation with TAK-981 activate IFN-1 signaling in HCC cells, thereby promoting dendritic cell maturation. Herein, we propose an injectable PDLLA-PEG-PDLLA (PLEL) nanocomposite hydrogel which incorporates self-assembled TAK-981 and BSA nanoparticles for complementary localized treatment of residual tumor after iRFA. The sustained release of TAK-981 from this hydrogel curbs the expansion of residual tumors and notably stimulates the dendritic cell and cytotoxic lymphocyte-mediated antitumor immune response in residual tumors while maintaining biosafety. Furthermore, the treatment with TAK-981 nanocomposite hydrogel resulted in a widespread elevation in PD-L1 levels. Combining TAK-981 nanocomposite hydrogel with PD-L1 blockade therapy synergistically eradicates residual tumors and suppresses distant tumors. Conclusions These findings underscore the potential of the TAK-981-based strategy as an effective therapy to enhance RFA therapy for HCC. Graphic Abstract

Abstract The gut microbiota plays a critical role in the progression of human diseases, especially cancer. In recent decades, there has been accumulating evidence of the connections between the gut microbiota and cancer immunotherapy. Therefore, understanding the functional role of the gut microbiota in regulating immune responses to cancer immunotherapy is crucial for developing precision medicine. In this review, we extract insights from state-of-the-art research to decipher the complicated crosstalk among the gut microbiota, the systemic immune system, and immunotherapy in the context of cancer. Additionally, as the gut microbiota can account for immune-related adverse events, we discuss potential interventions to minimize these adverse effects and discuss the clinical application of five microbiota-targeted strategies that precisely increase the efficacy of cancer immunotherapy. Finally, as the gut microbiota holds promising potential as a target for precision cancer immunotherapeutics, we summarize current challenges and provide a general outlook on future directions in this field.

Abstract Background It has been proposed that inflammation plays a role in the development of sarcopenia. This study aimed to investigate the links of complete blood cell count (CBC) parameters and CBC-derived inflammatory indicators with sarcopenia and mortality. Methods Data pertaining to sarcopenia were extracted from the 1999–2006 National Health and Nutrition Examination Survey (NHANES), and mortality events were ascertained through the National Death Index up to December 31, 2019. The CBC-derived inflammatory indicators assessed in this study included the neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), monocyte-to-lymphocyte ratio (MLR), neutrophil-monocyte to lymphocyte ratio (NMLR), systemic inflammatory response index (SIRI), and systemic immune-inflammation index (SII). The prognostic significance of these CBC-derived inflammatory indicators was evaluated using the random survival forests (RSF) analysis. Results The study encompassed a cohort of 12,689 individuals, among whom 1,725 were diagnosed with sarcopenia. Among individuals with sarcopenia, 782 experienced all-cause mortality, and 195 succumbed to cardiovascular causes. Following adjustment for confounding variables, it was observed that elevated levels of NLR, dNLR, NMLR, SIRI, and SII were associated with an increased prevalence of sarcopenia. Among participants with sarcopenia, those in the highest quartile of NLR (HR = 1.336 [1.095–1.631]), dNLR (HR = 1.274 [1.046–1.550]), MLR (HR = 1.619 [1.290–2.032]), NMLR (HR = 1.390 [1.132–1.707]), and SIRI (HR = 1.501 [1.210–1.862]) exhibited an elevated risk of all-cause mortality compared to those in the lowest quartile of these inflammation-derived indicators. These associations were similarly observed in cardiovascular mortality (HR = 1.874 [1.169–3.003] for MLR, HR = 1.838 [1.175–2.878] for SIRI). The RSF analysis indicated that MLR exhibited the highest predictive power for both all-cause and cardiovascular mortality among individuals with sarcopenia. Conclusions Our findings underscore the association between CBC-derived inflammatory indicators and mortality in adults with sarcopenia. Of note, MLR emerged as the most robust predictor of all-cause and cardiovascular mortality in this population.

Abstract The rapid advancement of microservice architecture in the cloud has led to the necessity of effectively detecting, classifying, and diagnosing run failures in microservice applications. Due to the high dynamics of cloud environments and the complex dependencies between microservices, it is challenging to achieve robust real-time system fault identification. This paper proposes an interpretable fault diagnosis framework tailored for microservice architecture, namely Multi-scale Learnable Transformation Graph for Fault Classification and Diagnosis(MTG_CD). Firstly, we employ multi-scale neural transformation and graph structure adjacency matrix learning to enhance data diversity while extracting temporal-structural features from system monitoring metrics Secondly, a graph convolutional network (GCN) is utilized to fuse the extracted temporal-structural features in a multi-feature modeling approach, which helps to improve the accuracy of anomaly detection. To identify the root cause of system faults, we finally conduct a coarse-grained level diagnosis and exploration after obtaining the results of classifying the fault data. We evaluate the performance of MTG_CD on the microservice benchmark SockShop, demonstrating its superiority over several baseline methods in detecting CPU usage overhead, memory leak, and network delay faults. The average macro F1 score improves by 14.05%.

Abstract Background Interferon-induced transmembrane protein 2 (IFITM2) is involved in repressing viral infection. This study aim to investigate the expression of IFITM2 in colorectal cancer (CRC) and explore its effect on cell proliferation, migration, and invasion. Methods We analyzed The Cancer Genome Atlas (TCGA) database for IFITM2 expression in colorectal cancer and used western blots to detect IFITM2 protein in specimens and cell lines of colorectal cancers. To assess the association between IFITM2 and clinical features, both univariate and multivariate cox regression analysis were conducted. Kaplan–Meier plots were used in the TCGA database to assess IFITM2 gene expression's prognostic significance. Silencing IFITM2 in SW480 and HCT116 cells was achieved by transient transfection with siRNA. Proliferation of CRCs was examined using Cell Counting Kit-8. The effect of IFITM2 on the migration and invasion of CRC cells was studied using wound healing and transwell assays. Gene set enrichment analysis (GSEA) was used to examine IFITM2-associated pathways and Western blotting was used to confirm it. Results IFITM2 was over-expressed in the CRC tissues and cells, with high IFITM2 expression related to the tumor N, M, and pathologic stages. The presence of IFITM2 significantly impacted patient survival in CRC. The proliferation of SW480 and HCT116 cells was suppressed when IFITM2 was silenced, resulting in weakened migration and invasion of CRC cells. GSEA analysis showed that IFITM2 was positively related to the phosphoinositide 3-kinase (PI3K)/AKT pathway, and western blot results confirmed that IFITM2 activated it. Conclusions IFITM2 was over-expressed in CRC and modulated the PI3K/AKT pathway to promote CRC cells proliferation and metastasis.

Abstract Although Poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi) have been approved in multiple diseases, including BRCA1/2 mutant breast cancer, responses are usually transient requiring the deployment of combination therapies for optimal efficacy. Here we thus explore mechanisms underlying sensitivity and resistance to PARPi using two intrinsically PARPi sensitive (T22) and resistant (T127) syngeneic murine breast cancer models in female mice. We demonstrate that tumor associated macrophages (TAM) potentially contribute to the differential sensitivity to PARPi. By single-cell RNA-sequencing, we identify a TAM_C3 cluster, expressing genes implicated in anti-inflammatory activity, that is enriched in PARPi resistant T127 tumors and markedly decreased by PARPi in T22 tumors. Rps19/C5aR1 signaling is selectively elevated in TAM_C3. C5aR1 inhibition or transferring C5aR1hi cells increases and decreases PARPi sensitivity, respectively. High C5aR1 levels in human breast cancers are associated with poor responses to immune checkpoint blockade. Thus, targeting C5aR1 may selectively deplete pro-tumoral macrophages and engender sensitivity to PARPi and potentially other therapies.

This study systematically introduces the development of the world’s first full-link and full-system ground demonstration and verification system for the OMEGA space solar power satellite (SSPS). First, the OMEGA 2.0 innovation design was proposed. Second, field-coupling theoretical models of sunlight concentration, photoelectric conversion, and transmitting antennas were established, and a systematic optimization design method was proposed. Third, a beam waveform optimization methodology considering both a high beam collection efficiency and a circular stepped beam shape was proposed. Fourth, a control strategy was developed to control the condenser pointing toward the sun while maintaining the transmitting antenna toward the rectenna. Fifth, a high-efficiency heat radiator design method based on bionics and topology optimization was proposed. Sixth, a method for improving the rectenna array’s reception, rectification, and direct current (DC) power synthesis efficiencies is presented. Seventh, high-precision measurement technology for high-accuracy beam-pointing control was developed. Eighth, a smart mechanical structure was designed and developed. Finally, the developed SSPS ground demonstration and verification system has the capacity for sun tracking, a high concentration ratio, photoelectric conversion, microwave conversion and emission, microwave reception, and rectification, and thus satisfactory results were obtained.

Succinate dehydrogenase inhibitor (SDHI) fungicides are widely used to control plant anthracnose caused by Colletotrichum gloeosporioides. However, C. gloeosporioides resistant to SDHI fungicides have emerged in the orchard, also carry significant environmental risks. The thifluzamide, boscalid, and fluopyram are commonly used SDHIs fungicides in plant protection. In the study, the inhibitory activity of thifluzamide, boscalid, fluopyram against 55 C. gloeosporioides strains from China were determined, including mycelial growth and conidial production. The three SDHIs fungicides could inhibit the growth of mycelia and production of conidia of C. gloeosporioides. Here, we identified SDH subunits of C. gloeosporioides and expression patterns, and obtained CgSDHB, CgSDHC, CgSDHD mutants of C. gloeosporioides using CRISPR/Cas9 gene editing system. Biochemical evidence suggests that the mutants have reduced tricarboxylic acid cycle efficiency, thereby increasing the susceptibility of SDHIs and decreasing pathogenicity to multiple hosts. These results improve our understanding of SDHIs antifungal mechanism in C. gloeosporioides and provide new insights into the pathogenesis of SDH subunits regulation.

Merging traditional Chinese medicine's (TCM) principles of medicine-food homology with modern flavor chemistry, this research unveils PungentDB (http://www.pungentdb.org.cn/home), a database documenting 205 unique pungent flavor compounds from 231 TCMs. It provides detailed insights into their chemical attributes, biological targets (including IC50/EC50 values), and molecular structures (2D/3D), enriched with visualizations of target organ distribution and protein structures, exploring the pungent flavor space with the help of a feature-rich visual interface. This collection, derived from over 3249 sources and highlighting 9129 targets, delves into the compounds' unique pungent flavors—taste, aroma, and thermal sensations—and their interaction with taste and olfactory receptors. PungentDB bridges ancient wisdom and culinary innovation, offering a nuanced exploration of pungent flavors' role in enhancing food quality, safety, and sensory experiences. This initiative propels flavor chemistry forward, serving as a pivotal resource for food science advancement and the innovative application of pungent flavors.