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Abstract With the development of ultra‐high‐voltage (UHV) and extra‐high‐voltage transmission lines in China, the transmission lines are gradually approaching the residential areas. The phenomenon of induced electric shock caused by electrostatic induction effect can cause dissatisfaction and complaints from nearby residents. In this paper, a full‐size steel‐framed residential test platform was constructed near a 1000‐kV UHV alternating current (AC) transmission line, the transient shock characteristics of human bodies and metal hangers in different scenarios was investigated, then the relationship between transient shock energy and subjective perception of the human body was discussed. In addition, the shielding effect of shielding wires for transient electric shock situations is analyzed. It was found that the worst‐case scenario occurred when the grounded human body came into contact with the insulated metal clothes hanger, even eliciting a noticeable sensation of pain. In addition, increasing metal shielding wire number has a significant effect on weakening induced electric shocks.

Abstract LC3-associated phagocytosis (LAP) is critical in host defense against invading pathogens, but the molecular mechanism for LAP activation is still unclear. Here, we find programmed cell death 6 (PDCD6) as a negative regulator of LAP. PDCD6 deficiency in mice and macrophages induces enhanced bactericidal activity and LAP formation. In parallel, lactate dehydrogenase A (LDHA) activity and lactate production is induced in macrophages challenged with bacteria, Zymosan or Pam3CSK4, while genetic ablation or pharmacological inhibition of LDHA reduces lactate levels and impairs bactericidal activity in vivo and in vitro. Mechanistically, PDCD6 interacts with LDHA to downregulate lactate metabolism, leading to reduced RUBCN lactylation at lysine33 (K33). By contrast, PDCD6-deficiency increases RUBCN lactylation, thereby promotes RUBCN interaction with VPS34, LAP formation, and protective responses. Our results thus suggest a PDCD6-LDHA-lactate-RUBCN axis of innate immunity regulation that may both contribute to protection from infectious diseases and serve as targets for therapeutic development.

Abstract Failure Modes, Effects, and Criticality Analysis (FMECA) is a commonly used method for analyzing system reliability. It is frequently applied in identifying weak points in the reliability of CNC machine tools. However, traditional FMECA has issues such as vague descriptions of risk factors, equal treatment of risk factors, and unclear directions for improving weak points. In response to the issue of vague descriptions of risk factors, this paper further expands severity (S) into machine hazard (M) and personal hazard (P), and subdivides detectability (D) into functional structural complexity (D 1) and detection cost (D 2). In addressing the issue of treating risk factors equally, this paper integrates Distance Analysis Method (DAM) and Grey Relational Analysis (GRA) to propose Distance-Grey Relational Analysis (D-GRA). Subsequently, based on the D-GRA method, the weights of each risk factor were determined by comprehensively considering expert system scores and actual economic loss indicators. In response to the issue of unclear improvement directions for weak points, this paper introduces the BCC model. It treats common failure modes of CNC machine tools as decision-making units within the BCC model, refines risk factors as input indicators, and evaluates the efficiency values of each decision-making unit based on various actual losses as output indicators. Through efficiency value analysis, it proposes improvement directions for weak points. Then, based on the weights of risk factors and the efficiency values of failure modes, a modified calculation method for the new Risk Priority Number (RPN) is proposed to amend the traditional RPN, This paper takes the electric spindle system of a certain machining center as an example, applies the proposed method to rank common failure modes with the new RPN, and compares it with other RPN calculation methods to verify the rationality of the proposed approach. Finally, it presents improvement directions for reliability enhancement.

Abstract Multi-modal image analysis using deep learning (DL) lays the foundation for neoadjuvant treatment (NAT) response monitoring. However, existing methods prioritize extracting multi-modal features to enhance predictive performance, with limited consideration on real-world clinical applicability, particularly in longitudinal NAT scenarios with multi-modal data. Here, we propose the Multi-modal Response Prediction (MRP) system, designed to mimic real-world physician assessments of NAT responses in breast cancer. To enhance feasibility, MRP integrates cross-modal knowledge mining and temporal information embedding strategy to handle missing modalities and remain less affected by different NAT settings. We validated MRP through multi-center studies and multinational reader studies. MRP exhibited comparable robustness to breast radiologists, outperforming humans in predicting pathological complete response in the Pre-NAT phase (ΔAUROC 14% and 10% on in-house and external datasets, respectively). Furthermore, we assessed MRP’s clinical utility impact on treatment decision-making. MRP may have profound implications for enrolment into NAT trials and determining surgery extensiveness.

As the proportion of renewable energy infiltrating the power grid increases, suppressing its randomness and volatility, reducing its impact on the safe operation of the power grid, and improving the level of new energy consumption are increasingly important. For these purposes, energy storage stations (ESS) are receiving increasing attention. This article discusses the structure, working principle, and control methods of grid-following and grid-forming energy-storage converters, which are currently commonly used. A simulation analysis was conducted to investigate their dynamic response characteristics. The advantages and disadvantages of two types of energy storage power stations are discussed, and a configuration strategy for hybrid ESS is proposed. This paper presents research on and a simulation analysis of grid- forming and grid-following hybrid energy storage systems considering two types of energy storage according to different capacity scenarios. Finally, a comparative analysis between the systems is presented. A simulation model was established using PSD-BPA (Power System Department-Bonneville Power Administration) to analyze the impact of the capacity ratio of grid-following and grid-forming ESS on their dynamic response characteristics in a hybrid ESS. In addition, a development direction for future ESSs is indicated.

Abstract Crustal thickening in Tibet results from the collision of India and Eurasia. The fine structure of the crust is vital information to detect the tectonic genesis of crustal growth and reworking. Here, we constructed the crustal structure of eastern Tibet and its neighboring areas using depth-domain receiver function imaging. The imaging results reveal widespread low-velocity layers in the mid-crust, alternating high- and low-velocity structures in the lower crust, and regional variations in the velocity at the bottom of the lower crust and the thickness of the entire crust. We propose that the lower crust is juvenile crust, formed by multiphase magmatism and tectonic activity during continental collision. The regional variations in crustal structure can be attributed to differences in the tectonic position of subduction-collision system and the distinct crustal-derived materials that contribute to the formation of the juvenile crust. The low-velocity layers in the mid-crust are more likely to be the product of arc magmatism during the assembly of micro-continents. Based on the constraints of the unique crustal structure, we suggest that tectonic compression and magmatism caused the juvenile and reworking of the Tibetan crust.

Abstract Background Breast cancer is the most commonly diagnosed cancer worldwide. Although major treatments represented by chemotherapy have shown effectiveness at the initial period, recurrence and metastasis still occur later after treatments. The alternation of the tumor microenvironment by chemotherapy is confirmed as a trigger of the elevated proliferation and migration of the remaining tumor cells. Methods Using bioinformatic methods, differential gene expression analysis was used to determine DEGs between post-chemotherapy and pre-chemotherapy samples of breast cancer patients, followed by survival analysis and ELISA analysis of the potential key genes. An in vitro model of 2 breast cancer cells lines was used to demonstrate the role of VWF in the evasion and migration of breast cancer cells, using cell migration, evasion and wound healing assays, PCR and molecular docking analysis. Results 19 hub genes were further identified using GO and KEGG pathway analyses and WGCNA. The 5 secreted protein-coding genes with reported carcinogenesis effects (VWF, SVEP1, DPT, ADIPOQ, and LPL) were further analyzed in breast cancer patients and VWF was identified as a potential key regulator in the anthracycline-based chemotherapy-exacerbated metastasis. It was further confirmed that anthracycline-based chemotherapeutics doxorubicin exacerbated VWF upregulation and the evasion and migration of breast cancer cells. Based on molecular docking analysis and previous study, berberine was used as an inhibitor of VWF, and showed an effective inhibition of the doxorubicin-exacerbated VWF upregulation, migration and evasion in breast cancer. Conclusions Doxorubicin-exacerbated evasion and migration through VWF upregulation. Berberine as an inhibitor of VWF was able to reversed the doxorubicin-exacerbated VWF upregulation and evasion and migration in breast cancer cells.

Abstract Kidney tumours are among the top ten most common tumours, the automatic segmentation of medical images can help locate tumour locations. However, the segmentation of kidney tumour images still faces several challenges: firstly, there is a lack of renal tumour endoscopic datasets and no segmentation techniques for renal tumour endoscopic images; secondly, the intra‐class inconsistency of tumours caused by variations in size, location, and shape of renal tumours; thirdly, difficulty in semantic fusion during decoding; and finally, the issue of boundary blurring in the localization of lesions. To address the aforementioned issues, a new dataset called Re‐TMRS is proposed, and for this dataset, the transformer‐based boundary feedback network for kidney tumour segmentation (BFT‐Net) is proposed. This network incorporates an adaptive context extract module (ACE) to emphasize local contextual information, reduces the semantic gap through the mixed feature capture module (MFC), and ultimately improves boundary extraction capability through end‐to‐end optimization learning in the boundary assist module (BA). Through numerous experiments, it is demonstrated that the proposed model exhibits excellent segmentation ability and generalization performance. The mDice and mIoU on the Re‐TMRS dataset reach 91.1% and 91.8%, respectively.

Abstract Treatment of Mycobacterium abscessus (Mab) infections is very challenging due to its intrinsic resistance to most available drugs. Therefore, it is crucial to discover novel anti‐Mab drugs. In this study, we explored an intrinsic resistance mechanism through which Mab resists echinomycin (ECH). ECH showed activity against Mab at a minimum inhibitory concentration (MIC) of 2 µg/ml. A ΔembC strain in which the embC gene was knocked out showed hypersensitivity to ECH (MIC: 0.0078–0.0156 µg/ml). The MICs of ECH‐resistant strains screened with reference to ΔembC ranged from 0.25 to 1 µg/ml. Mutations in EmbB, including D306A, D306N, R350G, V555I, and G581S, increased the Mab's resistance to ECH when overexpressed in ΔembC individually (MIC: 0.25–0.5 µg/ml). These EmbB mutants, edited using the CRISPR/Cpf1 system, showed heightened resistance to ECH (MIC: 0.25–0.5 µg/ml). The permeability of these Mab strains with edited genes and overexpression was reduced, as evidenced by an ethidium bromide accumulation assay, but it remained significantly higher than that of the parent Mab. In summary, our study demonstrates that ECH exerts potent anti‐Mab activity and confirms that EmbB and EmbC are implicated in Mab's sensitivity to ECH. Mutation in EmbB may partially compensate for a loss of EmbC function.

Abstract Automatic segmentation of renal tumours during renal cell carcinoma surgery can help doctors accurately locate the tumour region, protect the tissues and organs around the kidneys, enhance surgical efficiency, and reduce the possibility of leakage and misdiagnosis. However, since general polyp endoscopic image segmentation models have many problems when facing the task of renal tumour segmentation, there needs to be more research on the segmentation of endoscopic images of renal tumours. This paper proposes a multi‐scale dynamic segmentation kernel network for endoscopic image segmentation of kidney tumours. First, a spatial receptive field module is proposed to augment the feature information and improve the performance of the whole network. Second, an enhanced cross‐attention module is offered to attenuate the effect of a high‐similarity segmentation background. Finally, a multi‐scale dynamic segmentation kernel module is introduced to gradually refine the segmentation results from small to large sizes to obtain more accurate tumour boundaries. Extensive experiments on the established kidney tumour endoscopic dataset and publicly available endoscopic datasets show that this method exhibits enhanced performance and generalization capabilities compared to existing techniques. On this renal tumour dataset, MDSK‐Net achieved excellent results of 94.1% and 90.1% on mDice and mIoU.

In Laser Powder Bed Fusion (L-PBF), surface roughness is pivotal for controlling the mechanical and functional performances, as well as the geometrical accuracy of the final product. This study extensively investigated the interactions of hatch and contour processing parameters, along with contour offset distance, on vertical surface roughness for 316L stainless steel in L-PBF. Melt pool morphology and surface arithmetic average roughness (Sa) were quantified using confocal microscopy, while scanning electron microscopy was employed to interpret the detailed microstructure of surface features. Under low volumetric energy density (VED) hatch conditions (e.g., 66.7 J/mm3), varying the contour offset distance has a negatable effect on the surface roughness when the contour VED is lower than 121.6 J/mm3, remaining relatively smooth surfaces dominated by bare melt tracks with sparely attached partially melted particles. Increasing the hatch or contour VED (e.g., 166.7 J/mm3), dross formation, identified by the microstructural differences and explained by the melt pool instability and migration, is inevitable, which dictates the surface roughness with higher Sa values. The larger contour offset distance further promotes the dross occurrence with irregularity and increases Sa. Employing a low contour VED with an appropriate offset distance and adopting the contour-first scan strategy was demonstrated as an effective solution to reduce the dross formation. Through the analysis of melt pool behavior, surface topography, and microstructure, this study elucidates the mechanisms governing dominant surface characteristics under the combined influence of hatch and contour parameters. It lays the foundation for precise control of surface roughness without altering hatching parameters, enabling the tailored manipulation of performance in additively manufactured structures.

A close relationship exists between the crystallographic characteristics of a bainitic matrix and formation of martensite/austenite (M/A) constituents. In this work, the isothermal transformation kinetics and crystallographic characteristics of low-carbon bainitic (LCB) steel were investigated to elucidate the formation mechanism of M/A constituents and twin-related V1/V2 variant pairs (Σ3 boundaries). The formation of M/A constituents depends on the bainitic transformation kinetics, which are influenced by the carbon concentration and isothermal temperature. An increase in the carbon concentration or transformation temperature promotes the formation of blocky M/A constituents by increasing the activation energy of the grain boundary and autocatalytic nucleation processes. In addition, increasing the carbon concentration or lowering the transformation temperature increases the strength of the austenite phase and promotes autocatalytic nucleation, thereby producing more twin-related V1/V2 variant pairs. Therefore, the increase in the carbon concentration increases the number of twin-related V1/V2 variant pairs while also causing the formation of blocky M/A constituents. To overcome this limitation, a novel heat treatment process design is proposed that can significantly eliminate blocky M/A constituents and generate high-density twin-related V1/V2 variant pairs.

Abstract Direct methane conversion to high-value chemicals under mild conditions is attractive yet challenging due to the inertness of methane and the high reactivity of valuable products. This work presents an efficient and selective strategy to achieve direct methane conversion through the oxidative coupling of methane over a visible-responsive Au-loaded CeO2 by photon-phonon co-driven catalysis. A record-high ethane yield of 755 μmol h−1 (15,100 μmol g−1 h−1) and selectivity of 93% are achieved under optimised reaction conditions, corresponding to an apparent quantum efficiency of 12% at 365 nm. Moreover, the high activity of the photocatalyst can be maintained for at least 120 h without noticeable decay. The pre-treatment of the catalyst at relatively high temperatures introduces oxygen vacancies, which improves oxygen adsorption and activation. Furthermore, Au, serving as a hole acceptor, facilitates charge separation, inhibits overoxidation and promotes the C-C coupling reaction. All these enhance photon efficiency and product yield.

Abstract The proliferation of renewable energy resources and the incorporation of various types of energy bring opportunities as well as new challenges to the planning and operations within integrated energy systems (IESs). To better characterize multiple uncertain variables within IES, reducing wind power curtailment and minimizing costs, this paper proposes an IES collaborative planning model with EHs, in which uncertain variables are depicted by Z-numbers. Firstly, Z-number incorporates both fuzzy and probabilistic uncertainties, allowing the representation of uncertain variables with credibility information in constraints. Secondly, simplifying Z-numbers into an engineering-applicable method reduces the complexity of model resolution. Thirdly, to fully leverage the complementary transformation characteristics among different energy sources, the optimization model includes decisions on the capacity of energy conversion and energy storage components within EHs. Moreover, outside the EHs, conventional generator dispatches, and the hardening of electric-gas grid decisions are also included. Finally, the model is verified on an IES that involves the coupling of a six-node power system and a six-node gas system, and numerical results validate that wind power output values represented by Z-numbers have a standard deviation of only 0.33 from actual values. Furthermore, different credibility information in Z-numbers significantly impacts planning outcomes; an increased DR credibility can be conducive to reducing wind curtailment with 45KW and help cost-savings with 4.05%.

Abstract The liver is the most important metabolic organ in the body. While mouse models and cell lines have further deepened our understanding of liver biology and related diseases, they are flawed in replicating key aspects of human liver tissue, particularly its complex structure and metabolic functions. The organoid model represents a major breakthrough in cell biology that revolutionized biomedical research. Organoids are in vitro three-dimensional (3D) physiological structures that recapitulate the morphological and functional characteristics of tissues in vivo, and have significant advantages over traditional cell culture methods. In this review, we discuss the generation strategies and current advances in the field focusing on their application in regenerative medicine, drug discovery and modeling diseases.

Abstract Accurate segmentation of the tumor area is crucial for the treatment and prognosis of patients with bladder cancer. Cystoscopy is the gold standard for diagnosing bladder tumors. However, The vast majority of current work uses deep learning to identify and segment tumors from CT and MRI findings, and rarely involves cystoscopy findings. Accurately segmenting bladder tumors remains a great challenge due to their diverse morphology and fuzzy boundaries. In order to solve the above problems, this paper proposes a medical image segmentation network with boundary guidance called boundary guidance network. This network combines local features extracted by CNNs and long-range dependencies between different levels inscribed by Parallel ViT, which can capture tumor features more effectively. The Boundary extracted module is designed to extract boundary features and utilize the boundary features to guide the decoding process. Foreground-background dual-channel decoding is performed by boundary integrated module. Experimental results on our proposed new cystoscopic bladder tumor dataset (BTD) show that our method can efficiently perform accurate segmentation of tumors and retain more boundary information, achieving an IoU score of 91.3%, a Hausdorff Distance of 10.43, an mAP score of 85.3%, and a F1 score of 94.8%. On BTD and three other public datasets, our model achieves the best scores compared to state-of-the-art methods, which proves the effectiveness of our model for common medical image segmentation.

Non-darcy seepage through layered porous media is common in soil-groundwater systems under the influence of human activities. The effect of average particle size and coarse-fine particle interface on the characteristics of non-Darcy porous flow through layered porous media was investigated from the relation between hydraulic gradient and flow velocity, non-Darcy seepage parameters, and critical Reynolds number. The results show that when water flows through layered porous media, the coarse-fine particle interface has an important effect on the characteristics of non-Darcy flow. The critical Reynolds number, which is used to judge the transition from Darcy flow to non-Darcy flow, decreases with the increase of the average particle size in monolayer porous media, but increases with the increase of the average particle size and the decrease of the coarse/fine particle size ratio when water flows through layered porous media. The critical Reynolds number of single-layer porous media is lower than that of the double-layer porous media with the same corresponding particle size due to the coarse-fine particle interface. By introducing the nonlinear component index E, it is found that the coarse/fine particle interface has a certain inhibitory effect on the hydrodynamic inertia force component, and the inhibitory effect degree is negatively correlated with the difference in size of the coarse and fine particles. The results in this study have a good guiding significance for studying non-Darcy seepage through layered rock and soil.

Abstract Background As a novel regional analgesic technique, ultrasound-guided pericapsular nerve group (PENG) block has some potential advantages, and we designed a randomized clinical trial (RCT) to investigate whether the ultrasound-guided PENG block combined with general anesthesia can better reduce stress response, maintain intraoperative hemodynamic stability, and reduce postoperative analgesia in elderly hip arthroplasty compared with ultrasound-guided suprainguinal fascia iliaca block (SIFIB) combined with general anesthesia. Methods Seventy-four subjects were enrolled over an 8-month period (20 April 2023 to 31 December 2023). All patients were divided into the test group (group P) and the control group (group S) using the envelope as the randomization method. The test group was treated with preoperative ultrasound-guided PENG block analgesia combined with general anesthesia and the control group was treated with preoperative ultrasound-guided SIFIB analgesia combined with general anesthesia. The primary outcome selected was the patient Visual Analogue Scale (VAS) score at 12 h postoperatively. Results After generalized estimating equations (GEE) analysis, there was a statistically significant difference in the main effect of postoperative VAS score in group P compared with group S (P = 0.009), the time effect of VAS score in each group was significantly different (P

Gravitational wave (GW) astronomy has opened new frontiers in understanding the cosmos, while the integration of artificial intelligence (AI) in science promises to revolutionize data analysis methodologies. However, a significant gap exists, as there is currently no dedicated platform that enables scientists to develop, test, and evaluate AI algorithms efficiently for GW data analysis. To address this gap, we introduce GWAI, a pioneering AI-centered software platform designed for GW data analysis. GWAI contains a three-layered architecture that emphasizes simplicity, modularity, and flexibility, covering the entire analysis pipeline. GWAI aims to accelerate scientific discoveries, bridging the gap between advanced AI techniques and astrophysical research.

Cohort studies are traditionally focused on human participants. The emergence of the “Planetary Health” and “One Health” paradigms has expanded the scope of cohort studies to include animal participants. Despite this, plants remain largely overlooked in traditional biomedical research. This gap prompts the introduction of the concept of a “plant cohort,” which involves treating plants as participants in cohort studies. By collecting comprehensive data on plant characteristics and biosamples, plant cohorts may assist in enhancing our understanding of the interactions between plants, ecosystems, and human health. However, establishing plant cohorts presents unique challenges, including interdisciplinary collaboration and data collection methods. Nonetheless, the potential contribution of plant cohorts to environmental health and human well-being may warrant further exploration and research.

Background Polypoidal choroidal vasculopathy (PCV) is a hemorrhagic fundus disease that can lead to permanent vision loss. Predicting the treatment response to anti-VEGF monotherapy in PCV is consistently challenging. We aimed to conduct a prospective multicenter study to explore and identify the imaging biomarkers for predicting the anti-VEGF treatment response in PCV patients, establish predictive model, and undergo multicenter validation.Methods This prospective multicenter study utilized clinical characteristics and images of treatment naïve PCV patients from 15 ophthalmic centers nationwide to screen biomarkers, develop model, and validate its performance. Patients from Peking Union Medical College Hospital were randomly divided into a training set and an internal validation set. A nomogram was established by univariate, LASSO regression, and multivariate regression analysis. Patients from the other 14 centers served as an external test set. Area under the curve (AUC), sensitivity, specificity, and accuracy were calculated. Decision curve analysis (DCA) and clinical impact curve (CIC) were utilized to evaluate the practical utility in clinical decision-making.Findings The eye distribution for the training set, internal validation set, and external test set were 66, 31, and 71, respectively. The ‘Good responder’ exhibited a thinner subfoveal choroidal thickness (SFCT) (230.67 ± 61.96 vs. 314.42 ± 88.00 μm, p

Sodium carbonate solvent absorbent has been widely studied for CO2 reduction to deal with global warming because of its green, low cost, and non-corrosive advantages. However, in the application of sodium carbonate as an absorbent for CO2 capture, there is no unified cognition of the mass transfer process, which leads to the lack of guidance for the industrial large-scale process. Moreover, the mechanism of mass transfer enhancement of surfactants, which can effectively improve the mass transfer performance, has not been effectively explored in the literature. Based on this, this paper firstly adopts the molecular dynamics method to analyze the solution characteristics after surfactant addition and optimize the surfactant. Subsequently, a classical dissolved oxygen test method was used to measure the gas-liquid mass transfer coefficient for CO2 absorption into sodium carbonate solution. And based on this mass transfer coefficient measurement method, the mass transfer process of sodium carbonate solution with surfactant was analyzed. The results showed that the sodium carbonate solution with 5 wt% concentration and 10 wt% concentration at 30 °C did not satisfy the pseudo first-order fast chemical reaction kinetics assumption. To improve CO2 absorption mass transfer rate, dodecyl trimethyl ammonium chloride (DTAC) surfactant was introduced, which was improved by 119 % compared with non-enhanced solvent at 5 wt% concentration solution, and the assumption of pseudo first order fast chemical reaction was satisfied. After the introduction of surfactant, the barrier effect decreased the liquid phase mass transfer coefficient, but the Marangoni effect happened in the 5 wt% concentration of sodium carbonate solution, which enhanced the liquid-phase mass-transfer coefficient. This finding reveals the mechanism of mass transfer promotion of sodium carbonate by the surfactant DTAC, which is of great engineering significance for the application in the field of decarbonization after the introduction of surfactant.

IntroductionLong-distance robot teleoperation faces high latencies that pose cognitive challenges to human operators. Latency between command, execution, and feedback in teleoperation can impair performance and affect operators’ mental state. The neural underpinnings of these effects are not well understood.MethodsThis study aims to understand the cognitive impact of latency in teleoperation and the related mitigation methods, using functional Near-Infrared Spectroscopy (fNIRS) to analyze functional connectivity. A human subject experiment (n = 41) of a simulated remote robot manipulation task was performed. Three conditions were tested: no latency, with visual and haptic latency, with visual latency and no haptic latency. fNIRS and performance data were recorded and analyzed.ResultsThe presence of latency in teleoperation significantly increased functional connectivity within and between prefrontal and motor cortexes. Maintaining visual latency while providing real-time haptic feedback reduced the average functional connectivity in all cortical networks and showed a significantly different connectivity ratio within prefrontal and motor cortical networks. The performance results showed the worst performance in the all-delayed condition and best performance in no latency condition, which echoes the neural activity patterns.ConclusionThe study provides neurological evidence that latency in teleoperation increases cognitive load, anxiety, and challenges in motion planning and control. Real-time haptic feedback, however, positively influences neural pathways related to cognition, decision-making, and sensorimotor processes. This research can inform the design of ergonomic teleoperation systems that mitigate the effects of latency.

Purpose: Radiation therapy (RT) processes require significant human resources and expertise, creating a barrier to rapid RT deployment in low- and middle-income countries (LMICs). Accurate segmentation of tumor targets and organs at risk (OARs) is crucial for optimal RT. This study assessed the impact of artificial intelligence (AI)-based autosegmentation of OARs in 2 LMICs. Methods and Materials: Ten patients, comprising 5 head and neck (HN) cancer patients and 5 prostate cancer patients, were randomly selected. Planning computed tomography images were subjected to autosegmentation using an Food and Drug Administration-approved AI software tool and manual segmentation by experienced radiation oncologists from 2 LMIC RT clinics. The control data, obtained from a large academic institution in the United States, consisted of contours obtained by an experienced radiation oncologist. The segmentation time, DICE similarity coefficient (DSC), Hausdorff distance, and mean surface distance were evaluated. Results: AI significantly reduced segmentation time, averaging 2 minutes per patient, compared with 57 to 84 minutes for manual contouring in LMICs. Compared with the control data, the AI pelvic contours provided better agreement than did the LMIC manual contours (mean DSC of 0.834 vs 0.807 in LMIC1 and 0.844 vs 0.801 in LMIC2). For HN contours, AI provided better agreement for the majority of OAR contours than manual contours in LMIC1 (mean DSC: 0.823 vs 0.821) or LMIC2 (mean DSC: 0.792 vs 0.748). Neither the AI nor LMIC manual contours had good agreement with the control data (DSC < 0.600) for the optic nerves, chiasm, and cochlea. Conclusions: AI-based autosegmentation generates OAR contours of comparable quality to manual segmentation for both pelvic and HN cancer patients in LMICs, with substantial time savings.

Objective: Non-alcoholic fatty liver disease (NAFLD) is deemed as an emerging global epidemic, whereas the underlying pathogenic mechanism remains to be clarified. We aimed to systemically analyze all the NAFLD-related gene expression datasets from published human-based studies, by which exploring potential key factors and mechanisms accounting for the pathogenesis of NAFLD. Methods: Robust rank aggregation (RRA) method was used to integrate NAFLD-related gene expression datasets. For fatty liver study, adeno-associated virus (AAV) delivery and genetic knockout mice were used to create IGFBP2 (Insulin-like growth factor binding protein 2) gain- or loss-of function models. Western blot, Co-immunoprecipitation (Co-IP), immunofluorescent (IF) staining, luciferase assay, molecular docking simulation were performed to reveal the IGFBP2-EGFR-STAT3 axis involved. Key axis protein levels in livers from healthy donors and patients with NAFLD were assessed via immunohistochemical staining. Results: By using RRA method, the present study identified IGFBP2 being the most significantly down-regulated gene in all NAFLD subjects. The decreased IGFBP2 expression was further confirmed in the liver tissues from patients and animal models of NAFLD. IGFBP2 deficiency aggravated hepatic steatosis and NASH phenotypes and promoted lipogenic gene expression both in vivo and in vitro. Mechanistically, IGFBP2 directly binds to and regulates EGFR, whereas blockage of the IGFBP2-EGFR complex by knockdown of IGFBP2 resulted in the EGFR-STAT3 pathway activation, which in turn promoted the promoter activity of Srebf1. By using molecular docking simulation and protein-protein interaction analysis, the sequence of 233-257 amino acids in IGFBP2 was characterized as a key motif responding for its specific binding to EGFR and the protective effect against hepatic steatosis. Conclusions: The current study has, for the first time, identified IGFBP2 as a novel protector against hepatosteatosis. The protective effect is mediated by its specific interaction with EGFR and thereby suppressing the EGFR-STAT3 pathway. Therefore, pharmaceutically targeting the IGFBP2-EGFR-STAT3 axis may provide a theoretical basis for for the treatment of NAFLD/NASH and the associated diseases.

Sulfamethoxazole (SMX) is an extensively applied antibacterial drug, and it is also a pollutant that poses a serious threat to human and ecosystem health. In this research, a 3D hierarchical hollow ball-flower structure catalyst (CoAl-LDHs@CoSx-rGO) was tailored for the first time to efficiently degrade SMX via visible light coupling PMS activation. A series of characterizations confirm that the target catalyst is successfully prepared and the optimized 0.1CoAl-LDHs@CoSx-rGO sample possesses superior specific surface area of 306.0 m2/g, and significantly higher photocurrent response and lower electrochemical impedance. More importantly, 0.5 g/L of the sample can degrade 98.59 % of SMX within 50 min via visible light coupling PMS activation, and after 7 degradation cycles, the degradation rate only decreased by 8.49 %. A series of parameters that affect degradation rate have been optimized in detail. Capture experiments and ESR indicate that e−, •OH and SO4•− make major contributions to degradation, and visible light coupling PMS activation generates stronger signals than alone visible-light or PMS system. LC-MS, TEST toxicity assessment and theoretical calculation were conducted to elucidate degradation route and intermediate toxicity. The research provides a new approach to design catalysts with highly exposed activity sites for efficiently removing SMX from environmental water.

The acceptance of COVID-19 mobile contact tracing apps (MCTA) is crucial to curb the spread of the virus and decrease the number of infections. However, the security and privacy concerns (SPC) of COVID-19 MCTA have been called into question. Thus this paper examines the drivers of the acceptance of the COVID-19 pandemic MCTA under the auspices of the influence of SPC from the Chinese perspective based on the modified Unified Theory of Acceptance and Usage of Technology (UTAUT) model. The data generated through a questionnaire based on the convenient sampling technique was analyzed with SPSS by performing hierarchical regression analysis. The results show that the core constructs of UTAUT such as performance expectancy (PE), facilitating conditions (FC), effort expectancy (EE), and social influence (SI) along with mobile self-efficacy (MSE) were significant predictors of individual user acceptance of COVID-19 MCTA. Additionally, the study confirmed that security and privacy concerns were significant in moderating the impact of PE, FC, EE, SI, and MSE on the acceptance of COVID-19 MCTA. The managerial and theoretical implications of these findings for policy-makers, governments, mobile app developers, and researchers are interrogated.

ObjectiveTo investigate the effects of multiple stress events in different stages of life on the incidence of metabolic syndrome (MetS).MethodsMiners from Tangshan, China, were recruited for this study. Workers of the Kailuan Mining Group were evaluated to investigate whether exposure to Tangshan earthquakes during the fetal period in 1976. Adult life events and childhood trauma were assessed separately via the Life Event Scale and Childhood Trauma Questionnaire. The subjects were physically examined and general demographic data such as waist circumference were collected. Blood samples were collected for measurement of metabolic parameters. Corticotropin releasing hormone(CRH) levels was measured by enzyme-linked immunosorbent assay (ELISA). The subjects were divided into four groups according to their exposure to traumatic events in different stages of life: no exposure group, 1-exposure group, 2-exposures group, and 3-exposures group. The incidence of MetS, metabolic parameters and CRH levels in each of the four groups was compared.ResultsIn all, 626 people were enrolled; of these, 183, 262, 150, and 31 were in the no exposure, 1-exposure, 2-exposures, and 3-exposure groups, respectively. A remarkable variation in the incidence of MetS was observed among the four groups (x2 = 16.462, P

Abstract Oligodendrocyte precursor cells (OPCs) migrate extensively using blood vessels as physical scaffolds in the developing central nervous system. Although the association of OPCs with the vasculature is critical for migration, the regulatory mechanisms important for OPCs proliferative and oligodendrocyte development are unknown. Here, a correlation is demonstrated between the developing vasculature and OPCs response during brain development. Deletion of endothelial stimulator of interferon genes (STING) disrupts angiogenesis by inhibiting farnesyl‐diphosphate farnesyltransferase 1 (FDFT1) and thereby reducing cholesterol synthesis. Furthermore, the perturbation of metabolic homeostasis in endothelial cells increases interleukin 17D production which mediates the signal transduction from endothelial cells to OPCs, which inhibits oligodendrocyte development and myelination and causes behavioral abnormalities in adult mice. Overall, these findings indicate how the endothelial STING maintains metabolic homeostasis and contributes to oligodendrocyte precursor cells response in the developing neocortex.

Alzheimer’s disease (AD) is a complex degenerative disease of the central nervous system, and elucidating its pathogenesis remains challenging. In this study, we used the inverse-variance weighted (IVW) model as the major analysis method to perform hypothesis-free Mendelian randomization (MR) analysis on the data from MRC IEU OpenGWAS (18,097 exposure traits and 16 AD outcome traits), and conducted sensitivity analysis with six models, to assess the robustness of the IVW results, to identify various classes of risk or protective factors for AD, early-onset AD, and late-onset AD. We generated 400,274 data entries in total, among which the major analysis method of the IVW model consists of 73,129 records with 4840 exposure traits, which fall into 10 categories: Disease, Medical laboratory science, Imaging, Anthropometric, Treatment, Molecular trait, Gut microbiota, Past history, Family history, and Lifestyle trait. More importantly, a freely accessed online platform called MRAD (https://gwasmrad.com/mrad/) has been developed using the Shiny package with MR analysis results. Additionally, novel potential AD therapeutic targets (CD33, TBCA, VPS29, GNAI3, PSME1) are identified, among which CD33 was positively associated with the main outcome traits of AD, as well as with both EOAD and LOAD. TBCA and VPS29 were negatively associated with the main outcome traits of AD, as well as with both EOAD and LOAD. GNAI3 and PSME1 were negatively associated with the main outcome traits of AD, as well as with LOAD, but had no significant causal association with EOAD. The findings of our research advance our understanding of the etiology of AD.

Nearshore water-level prediction has a substantial impact on the daily lives of coastal residents, fishing operations, and disaster prevention and mitigation. Compared to the limitations and high costs of traditional empirical forecasts and numerical models for nearshore water-level prediction, data-driven artificial intelligence methods can more efficiently predict water levels. Attention mechanisms have recently shown great potential in natural language processing and video prediction. Convolutional long short-term memory(ConvLSTM) combines the advantages of convolutional neural networks (CNN) and long short-term Memory (LSTM), enabling more effective data feature extraction. Therefore, this study proposes a ConvLSTM nearshore water level prediction model that incorporates an attention mechanism. The ConvLSTM model extracts multiscale information from historical water levels, and the attention mechanism enhances the importance of key features, thereby improving the prediction accuracy and timeliness. The model structure was determined through experiments and relevant previous studies using five years of water level data from the Zhuhai Tide Station and the surrounding wind speed and rainfall data for training and evaluation. The results indicate that this model outperforms the four other baseline models of PCCs, RMSE, and MAE, effectively predicting future water levels at nearshore stations up to 48 h in advance. Compared to the ConvLSTM model, the model with the attention mechanism showed an average improvement of approximately 10% on the test set, with a greater error reduction in short-term forecasts than that in long-term forecasts. During Typhoon Higos, the model reduced the MAE of the best-performing baseline model by approximately 3.2 and 2.4 cm for the 6- and 24-hour forecasts, respectively, decreasing forecast errors by approximately 18% and 11%, effectively enhancing the ability of the model to forecast storm surges. This method provides a new approach for forecasting nearshore tides and storm surges.

ABSTRACT The increasing clinical significance of Mycobacterium abscessus is owed to its innate high-level, broad-spectrum resistance to antibiotics and therefore rapidly evolves as an important human pathogen. This warrants the identification of novel targets for aiding the discovery of new drugs or drug combinations to treat M. abscessus infections. This study is inspired by the drug-hypersensitive profile of a mutant M. abscessus (U14) with transposon insertion in MAB_1915. We validated the role of MAB_1915 in intrinsic drug resistance in M. abscessus by constructing a selectable marker-free in-frame deletion in MAB_1915 and complementing the mutant with the same or extended version of the gene and then followed by drug susceptibility testing. Judging by the putative function of MAB_1915, cell envelope permeability was studied by ethidium bromide accumulation assay and susceptibility testing against dyes and detergents. In this study, we established genetic evidence of the role of MAB_1915 in intrinsic resistance to rifampicin, rifabutin, linezolid, clarithromycin, vancomycin, and bedaquiline. Disruption of MAB_1915 has also been observed to cause a significant increase in cell envelope permeability in M. abscessus. Restoration of resistance is observed to depend on at least 27 base pairs upstream of the coding DNA sequence of MAB_1915. MAB_1915 could therefore be associated with cell envelope permeability, and hence its role in intrinsic resistance to multiple drugs in M. abscessus, which presents it as a novel target for future development of effective antimicrobials to overcome intrinsic drug resistance in M. abscessus.IMPORTANCEThis study reports the role of a putative fadD (MAB_1915) in innate resistance to multiple drugs by M. abscessus, hence identifying MAB_1915 as a valuable target and providing a baseline for further mechanistic studies and development of effective antimicrobials to check the high level of intrinsic resistance in this pathogen.

Nonylphenol (NP), an endocrine disruptor, has been demonstrated to be a harmful environmental contaminant and toxic to organisms. In this study, to address concerns regarding the immunotoxicity of NP, we treated clam Ruditapes philippinarum hemocytes with NP in vitro and explored the underlying mechanisms of NP-induced extracellular traps (ETs). NP could induce the formation of hemocytes ETs in a dose-dependent manner. Transcriptomics analysis revealed changes of signaling pathway involved in immunity and energy metabolism in hemocytes after NP stimulation. In this process, both reactive oxygen species (ROS) and myeloperoxidase (MPO) were up-regulated. Moreover, mitogen-activated protein kinase (MAPK) signaling pathway was proved to be activated in the formation of NP-induced ETs, manifested as enhanced phosphorylation of extracellular signal-regulated kinase (ERK) but not p38 or c-Jun N-terminal kinase (JNK). In the presence of U0126, an ERK phosphorylation inhibitor, the NP-induced expression of NADPH oxidase enzyme (NOX) was significantly decreased, which further alleviated the ROS production and ultimately limited the release of ETs. NP exposure increased glucose uptake, along with enhanced activities of glycolysis-related enzymes such as hexokinase (HK) and pyruvate kinase (PK). After inhibiting glycolysis by the inhibitor 2-DG, the formation of NP-induced ETs was significantly suppressed. ERK could regulate mTOR signaling and the PI3K/AKT pathway, potentially directing ETs formation by orchestrating the glycolysis through the activation of key transcription factors c-Myc and HIF-1α. Collectively, the results preliminary confirm that the ERK-NOX-ROS axis and glycolysis are involved in NP-induced ETs formation, contributing to the cellular immunotoxicity in clam.

Abstract Parallel acquisition-readout structured-illumination microscopy (PAR-SIM) was designed for high-speed raw data acquisition. By utilizing an xy-scan galvo mirror set, the raw data is projected onto different areas of the camera, enabling a fundamentally stupendous information spatial-temporal flux.

Abstract Cancer, a prevalent and complex disease, presents a significant challenge to the medical community. It is characterized by irregular cell differentiation, excessive proliferation, uncontrolled growth, invasion of nearby tissues, and spread to distant organs. Its progression involves a complex interplay of several elements and processes. Extracellular vesicles (EVs) serve as critical intermediaries in intercellular communication, transporting critical molecules such as lipids, RNA, membrane, and cytoplasmic proteins between cells. They significantly contribute to the progression, development, and dissemination of primary tumors by facilitating the exchange of information and transmitting signals that regulate tumor growth and metastasis. However, EVs do not have a singular impact on cancer; instead, they play a multifaceted dual role. Under specific circumstances, they can impede tumor growth and influence cancer by delivering oncogenic factors or triggering an immune response. Furthermore, EVs from different sources demonstrate distinct advantages in inhibiting cancer. This research examines the biological characteristics of EVs and their involvement in cancer development to establish a theoretical foundation for better understanding the connection between EVs and cancer. Here, we discuss the potential of EVs from various sources in cancer therapy, as well as the current status and future prospects of engineered EVs in developing more effective cancer treatments.

Abstract Azole antifungal drugs are commonly used to treat vulvovaginal candidiasis (VVC). The nephrotoxicity and developmental toxicity of azole drugs have not been systematically analyzed in the real world. We used the FDA Adverse Event Reporting System (FAERS) to investigate the adverse events (AEs) associated with imidazole therapy for VVC. FAERS data (from quarter 1 2004 to quarter 3 2022) were retrieved using OpenVigil 2.1, and AEs were retrieved and standardized according to the Medical Dictionary for Regulatory Activities (MedDRA). In the top 10 System Organ Class (SOC), all four drugs have been found to have kidney and urinary system diseases and pregnancy. We found significant signals, including clotrimazole [bladder transitional cell carcinoma, (report odds ratio, ROR = 291.66)], [fetal death, (ROR = 10.28)], ketoconazole[nephrogenic anemia (ROR = 22.1)], [premature rupture of membranes (ROR = 22.91 46.45, 11, 3)], Miconazole[hematuria (ROR = 19.03)], [neonatal sepsis (ROR = 123.71)], [spontaneous abortion (ROR = 5.98)], Econazole [acute kidney injury (ROR = 4.41)], [spontaneous abortion (ROR = 19.62)]. We also discovered new adverse reactions that were not reported. Therefore, when using imidazole drugs for treatment, it is necessary to closely monitor the patient's renal function, pay attention to the developmental toxicity of the fetus during pregnancy, and be aware of potential adverse reactions that may occur.

Abstract Conjunctival melanoma (CoM) is a potentially devastating tumor that can lead to distant metastasis. Despite various therapeutic strategies for distant metastatic CoM, the clinical outcomes remain unfavorable. Herein, we performed single-cell RNA sequencing (scRNA-seq) of 47,017 cells obtained from normal conjunctival samples (n = 3) and conjunctival melanomas (n = 7). Notably, we noticed a higher abundance of cancer-associated fibroblasts (CAFs) in tumor microenvironment (TME), correlated with enhanced angiogenic capacity and increased VEGFR expression in distal metastatic CoM. Additionally, we observed a significant decrease in the proportion of total CD8+ T cells and an increase in the proportion of naive CD8+ T cells, contributing to a relatively quiescent immunological environment in distal metastatic CoM. These findings were confirmed through the analyses of 70,303 single-cell transcriptomes of 7 individual CoM samples, as well as spatially resolved proteomes of an additional 10 samples of CoMs. Due to the increase of VEGFR-mediated angiogenesis and a less active T cell environment in distal metastatic CoMs, a clinical trial (ChiCTR2100045061) has been initiated to evaluate the efficacy of VEGFR blockade in combination with anti-PD1 therapy for patients with distant metastatic CoM, showing promising tumor-inhibitory effects. In conclusion, our study uncovered the landscape and heterogeneity of the TME during CoM tumorigenesis and progression, empowering clinical decisions in the management of distal metastatic CoM. To our knowledge, this is the initial exploration to translate scRNA-seq analysis to a clinical trial dealing with cancer, providing a novel concept by accommodating scRNA-seq data in cancer therapy.

Abstract Exosomes are nanovesicles with multiple components used in several applications. Mesenchymal stem cells (MSCs) are well known for their great potential in clinical applications. MSC-derived exosomes (MSC-Exos) have been shown to mediate tissue regeneration in various diseases, including neurological, autoimmune, and inflammatory diseases, cancer, ischemic heart disease, lung injury, and liver fibrosis. They can modulate the immune response by interacting with immune effector cells in the presence of anti-inflammatory compounds and are involved in intercellular communication through various types of cargo. This review summarizes the MSC-Exos-mediated tissue regeneration in various diseases, including neurological, cardiovascular, liver, kidney, articular cartilage, and oral tissue applications. In addition, we discuss the challenges and prospects of MSC-Exos in tissue regeneration.

Abstract Background ARID1A, a subunit of the SWI/SNF chromatin remodeling complex, is thought to play a significant role both in tumor suppression and tumor initiation, which is highly dependent upon context. Previous studies have suggested that ARID1A deficiency may contribute to cancer development. The specific mechanisms of whether ARID1A loss affects tumorigenesis by RNA editing remain unclear. Results Our findings indicate that the deficiency of ARID1A leads to an increase in RNA editing levels and alterations in RNA editing categories mediated by adenosine deaminases acting on RNA 1 (ADAR1). ADAR1 edits the CDK13 gene at two previously unidentified sites, namely Q113R and K117R. Given the crucial role of CDK13 as a cyclin-dependent kinase, we further observed that ADAR1 deficiency results in changes in the cell cycle. Importantly, the sensitivity of ARID1A-deficient tumor cells to SR-4835, a CDK12/CDK13 inhibitor, suggests a promising therapeutic approach for individuals with ARID1A-mutant tumors. Knockdown of ADAR1 restored the sensitivity of ARID1A deficient cells to SR-4835 treatment. Conclusions ARID1A deficiency promotes RNA editing of CDK13 by regulating ADAR1.

China is the world’s largest CO2 emitter and coal consumer, and its coal dominated energy structure is difficult to be changed in the short term. In the context of carbon peaking and carbon neutrality, the capture and storage or conversion of carbon dioxide into renewable fuels and chemicals can reduce dependence on fossil fuels and at the same time reduce CO2 emissions, providing key technical support for the green transition of coal-fired power plants and energy chemicals. Electrocatalysis and microbial conversion are important ways to produce renewable fuels and chemicals from carbon dioxide. The reaction rate of electrocatalytic reduction of CO2 is high, but the products are mostly limited to C1 and C2 products. Microbial CO2 fixation has the advantages of high selectivity and variety of products. However, the low electron transfer and energy supply lead to a long reaction period in the microbial CO2 fixation. Integration of electrocatalysis and microbial conversion can play their advantages to efficiently produce the value-added multi-carbon products. In this paper, firstly, the reaction principles, typical products of electrocatalysis and microbial CO2 fixation under a single technical route were introduced respectively. The catalyst and reactor of electrocatalytic CO2 reduction were discussed, and the microbial species and biological metabolic pathways of microbial fixation of CO2 were summarized. Secondly, two methods of the integration of electrocatalysis and microbial conversion was reviewed, and the system structure, working principle, electrode materials and value-added products were analyzed. Finally, the technology readiness level of different coupling methods was compared, and the future prospects were highlighted from four aspects: the catalysts for electrocatalytic CO2 reduction, the engineered microbial strains, the design and integration of coupling systems and the linkage between academic research and industry.

In this paper, taking the mining of deep-buried water-covered coal seam in 4105 working face of Wenjiapo Coal Mine as an example, similar material simulation and numerical simulation methods are used to study the law of overburden failure and fracture zone development, and to explore the impact of deep-buried coal seam mining on the safety of Hongyan River. The research shows that when the working face continues to advance, the goaf area increases, and the overlying rock is bent and deformed under the action of gravity to form a separation layer. When the gravity exceeds the rock deformation limit, the overlying rock will be destroyed and deformed, and some separation layers will collapse and disappear. New separation layers are developed in the upper part of the caving body, and cracks are formed on both sides. The caving zone height of 4105 working face is stable at 164 m. With the continuous advancement of the working face, the height of the water-conducting fracture zone gradually increased and eventually stabilized at 244 m. The ground fissures extend 32 m downward from the surface. There is a 414 m rock layer above the water-conducting fracture zone as a protective layer, which is not connected to the surface and not communicated with the ground fissure. Therefore, Hongyan River will not leak, and the mining of coal seams will not affect Hongyan River.

Abstract Background Colorectal cancer (CRC) commonly exhibits tolerance to cisplatin treatment, but the underlying mechanisms remain unclear. Within the tumor microenvironment, macrophages play a role in resisting the cytotoxic effects of chemotherapy by engaging in efferocytosis to clear apoptotic cells induced by chemotherapeutic agents. The involvement of extracellular vesicles (EVs), an intercellular communicator within the tumor microenvironment, in regulating the efferocytosis for the promotion of drug resistance has not been thoroughly investigated. Methods We constructed GFP fluorescent-expressing CRC cell lines (including GFP-CT26 and GFP-MC38) to detect macrophage efferocytosis through flow cytometric analysis. We isolated and purified CRC-secreted EVs using a multi-step ultracentrifugation method and identified them through electron microscopy and nanoflow cytometry. Proteomic analysis was conducted to identify the protein molecules carried by CRC-EVs. MFGE8 knockout CRC cell lines were constructed using CRISPR-Cas9, and their effects were validated through in vitro and in vivo experiments using Western blotting, immunofluorescence, and flow cytometric analysis, confirming that these EVs activate the macrophage αvβ3-Src-FAK-STAT3 signaling pathway, thereby promoting efferocytosis. Results In this study, we found that CRC-derived EVs (CRC-EVs) enhanced macrophage efferocytosis of cisplatin-induced apoptotic CRC cells. Analysis of The Cancer Genome Atlas (TCGA) database revealed a high expression of the efferocytosis-associated gene MFGE8 in CRC patients, suggesting a poorer prognosis. Additionally, mass spectrometry-based proteomic analysis identified a high abundance of MFGE8 protein in CRC-EVs. Utilizing CRISPR-Cas9 gene edition system, we generated MFGE8-knockout CRC cells, demonstrating that their EVs fail to upregulate macrophage efferocytosis in vitro and in vivo. Furthermore, we demonstrated that MFGE8 in CRC-EVs stimulated macrophage efferocytosis by increasing the expression of αvβ3 on the cell surface, thereby activating the intracellular Src-FAK-STAT3 signaling pathway. Conclusions Therefore, this study highlighted a mechanism in CRC-EVs carrying MFGE8 activated the macrophage efferocytosis. This activation promoted the clearance of cisplatin-induced apoptotic CRC cells, contributing to CRC resistance against cisplatin. These findings provide novel insights into the potential synergistic application of chemotherapy drugs, EVs inhibitors, and efferocytosis antagonists for CRC treatment.

Abstract Nowadays, immunotherapy is one of the most promising anti-tumor therapeutic strategy. Specifically, immune-related targets can be used to predict the efficacy and side effects of immunotherapy and monitor the tumor immune response. In the past few decades, increasing numbers of novel immune biomarkers have been found to participate in certain links of the tumor immunity to contribute to the formation of immunosuppression and have entered clinical trials. Here, we systematically reviewed the oncogenesis and progression of cancer in the view of anti-tumor immunity, particularly in terms of tumor antigen expression (related to tumor immunogenicity) and tumor innate immunity to complement the cancer-immune cycle. From the perspective of integrated management of chronic cancer, we also appraised emerging factors affecting tumor immunity (including metabolic, microbial, and exercise-related markers). We finally summarized the clinical studies and applications based on immune biomarkers. Overall, immune biomarkers participate in promoting the development of more precise and individualized immunotherapy by predicting, monitoring, and regulating tumor immune response. Therefore, targeting immune biomarkers may lead to the development of innovative clinical applications.

Abstract Background White Sponge Nevus (WSN) is traditionally considered a benign genetic disorder affecting the oral mucosa, primarily caused by pathogenic mutations in keratin 4 (KRT4) or keratin 13 (KRT13). Despite its benign nature, recent evidence has begun to question the malignant potential of WSN. Case presentation We report a case involving a 70-year-old man who presented with a white lesion on the right floor of his mouth. Initial diagnostic evaluations confirmed the lesion as WSN. Over a one-year follow-up, the lesion underwent malignant transformation, evolving into local epithelial moderate-to-severe dysplasia. Exome sequencing identified a novel insertion mutation in exon 1 of the KRT4 gene, resulting in a deletion-insertion amino acid mutation involving glycine. Single-cell RNA sequencing further revealed altered epithelial proliferation and differentiation dynamics within the lesion. Conclusions This case not only expands the known genetic spectrum of KRT4 mutations associated with WSN but also provides preliminary evidence suggesting the malignant potential of WSN. The novel pathogenic mutation in KRT4 is postulated to alter epithelial proliferation and differentiation, thereby raising concerns about the malignant transformation of WSN. Further studies are warranted to confirm these findings.

Abstract The cumulative number of stem cell divisions in a tissue, known as mitotic age, is thought to be a major determinant of cancer-risk. Somatic mutational and DNA methylation (DNAm) clocks are promising tools to molecularly track mitotic age, yet their relationship is underexplored and their potential for cancer risk prediction in normal tissues remains to be demonstrated. Here we build and validate an improved pan-tissue DNAm counter of total mitotic age called stemTOC. We demonstrate that stemTOC’s mitotic age proxy increases with the tumor cell-of-origin fraction in each of 15 cancer-types, in precancerous lesions, and in normal tissues exposed to major cancer risk factors. Extensive benchmarking against 6 other mitotic counters shows that stemTOC compares favorably, specially in the preinvasive and normal-tissue contexts. By cross-correlating stemTOC to two clock-like somatic mutational signatures, we confirm the mitotic-like nature of only one of these. Our data points towards DNAm as a promising molecular substrate for detecting mitotic-age increases in normal tissues and precancerous lesions, and hence for developing cancer-risk prediction strategies.

Abstract Background Mechanical spinal cord injury (SCI) is a deteriorative neurological disorder, causing secondary neuroinflammation and neuropathy. ADAM8 is thought to be an extracellular metalloproteinase, which regulates proteolysis and cell adherence, but whether its intracellular region is involved in regulating neuroinflammation in microglia after SCI is unclear. Methods Using animal tissue RNA-Seq and clinical blood sample examinations, we found that a specific up-regulation of ADAM8 in microglia was associated with inflammation after SCI. In vitro, microglia stimulated by HMGB1, the tail region of ADAM8, promoted microglial inflammation, migration and proliferation by directly interacting with ERKs and Fra-1 to promote activation, then further activated Map3k4/JNKs/p38. Using SCI mice, we used BK-1361, a specific inhibitor of ADAM8, to treat these mice. Results The results showed that administration of BK-1361 attenuated the level of neuroinflammation and reduced microglial activation and recruitment by inhibiting the ADAM8/Fra-1 axis. Furthermore, treatment with BK-1361 alleviated glial scar formation, and also preserved myelin and axonal structures. The locomotor recovery of SCI mice treated with BK-1361 was therefore better than those without treatment. Conclusions Taken together, the results showed that ADAM8 was a critical molecule, which positively regulated neuroinflammatory development and secondary pathogenesis by promoting microglial activation and migration. Mechanically, ADAM8 formed a complex with ERK and Fra-1 to further activate the Map3k4/JNK/p38 axis in microglia. Inhibition of ADAM8 by treatment with BK-1361 decreased the levels of neuroinflammation, glial formation, and neurohistological loss, leading to favorable improvement in locomotor functional recovery in SCI mice. Graphical Abstract

Abstract Comprehending the complex interplay among urban mobility, human behavior, and the COVID-19 pandemic could deliver vital perspectives to steer forthcoming public health endeavors. In late 2022, China lifted its "Zero-COVID" policy and rapidly abandoned nearly all interventions. It provides a unique opportunity to observe spontaneous mobility changes without government restriction throughout such a pandemic with high infection. Based on 148 million travel data from the public bus, subway, and taxi systems in Shenzhen, China, our analysis reveals discernible spatial discrepancies within mobility patterns. This phenomenon can be ascribed to the heterogeneous responses of mobility behavior tailored to specific purposes and travel modes in reaction to the pandemic. Considering both the physiological effects of virus infection and subjective willingness to travel, a dynamic model is proposed and capable of fitting fine-grained urban mobility. The analysis and model can interpret mobility data and underlying population behavior to inform policymakers when evaluating public health strategies against future large-scale infectious diseases.