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BACKGROUND & AIMS: Chronic circadian dysfunction increases the risk of non-alcoholic fatty liver disease (NAFLD)-related hepatocellular carcinoma (HCC), but the underlying mechanisms and direct relevance to human HCC have not been established. In this study, we aimed to determine whether chronic circadian dysregulation can drive NAFLD-related carcinogenesis from human hepatocytes and human HCC progression. METHODS: Chronic jet lag of mice with humanized livers induces spontaneous NAFLD-related HCCs from human hepatocytes. The clinical relevance of this model was analysed by biomarker, pathological/histological, genetic, RNA sequencing, metabolomic, and integrated bioinformatic analyses. RESULTS: Circadian dysfunction induces glucose intolerance, NAFLD-associated human HCCs, and human HCC metastasis independent of diet in a humanized mouse model. The deregulated transcriptomes in necrotic-inflammatory humanized livers and HCCs bear a striking resemblance to those of human non-alcoholic steatohepatitis (NASH), cirrhosis, and HCC. Stable circadian entrainment of hosts rhythmically paces NASH and HCC transcriptomes to decrease HCC incidence and prevent HCC metastasis. Circadian disruption directly reprogrammes NASH and HCC transcriptomes to drive a rapid progression from hepatocarcinogenesis to HCC metastasis. Human hepatocyte and tumour transcripts are clearly distinguishable from mouse transcripts in non-parenchymal cells and tumour stroma, and display dynamic changes in metabolism, inflammation, angiogenesis, and oncogenic signalling in NASH, progressing to hepatocyte malignant transformation and immunosuppressive tumour stroma in HCCs. Metabolomic analysis defines specific bile acids as prognostic biomarkers that change dynamically during hepatocarcinogenesis and in response to circadian disruption at all disease stages. CONCLUSION: Chronic circadian dysfunction is independently carcinogenic to human hepatocytes. Mice with humanized livers provide a powerful preclinical model for studying the impact of the necrotic-inflammatory liver environment and neuroendocrine circadian dysfunction on hepatocarcinogenesis and anti-HCC therapy. IMPACT AND IMPLICATIONS: Human epidemiological studies have linked chronic circadian dysfunction to increased hepatocellular carcinoma (HCC) risk, but direct evidence that circadian dysfunction is a human carcinogen has not been established. Here we show that circadian dysfunction induces non-alcoholic steatohepatitis (NASH)-related carcinogenesis from human hepatocytes in a murine humanized liver model, following the same molecular and pathologic pathways observed in human patients. The gene expression signatures of humanized HCC transcriptomes from circadian-disrupted mice closely match those of human HCC with the poorest prognostic outcomes, while those from stably circadian entrained mice match those from human HCC with the best prognostic outcomes. Our studies establish a new model for defining the mechanism of NASH-related HCC and highlight the importance of circadian biology in HCC prevention and treatment.

The development of SARS-CoV-2 main protease (Mpro) inhibitors for the treatment of COVID-19 has mostly benefitted from X-ray structures and preexisting knowledge of inhibitors; however, an efficient method to generate Mpro inhibitors, which circumvents such information would be advantageous. As an alternative approach, we show here that DNA-encoded chemistry technology (DEC-Tec) can be used to discover inhibitors of Mpro. An affinity selection of a 4-billion-membered DNA-encoded chemical library (DECL) using Mpro as bait produces novel non-covalent and non-peptide-based small molecule inhibitors of Mpro with low nanomolar Ki values. Furthermore, these compounds demonstrate efficacy against mutant forms of Mpro that have shown resistance to the standard-of-care drug nirmatrelvir. Overall, this work demonstrates that DEC-Tec can efficiently generate novel and potent inhibitors without preliminary chemical or structural information.

Optoelectronic synaptic devices have been regarded as the key component in constructing neuromorphic computing systems. However, the optoelectronic synapses based on conventional 2D transistor are still suffering low photosensitivity and volatile retention behavior, which can affect the recognition accuracy and long-term memory. Here, a novel optoelectronic synaptic device based on surface-state-rich CdSe nanobelt photosensitized 2D MoS2 transistor is demonstrated. Benefiting from the excellent light absorption of CdSe and effective charge trapping at the hetero-interface, the device exhibits not only high photosensitivity but also long retention time (>1,500 s). In addition, typical synaptic functions including the excitatory postsynaptic current, paired-pulse facilitation, the transformation from short-term to long-term plasticity, the transformation from short-term to long-term plasticity, spike-amplitude-dependent plasticity, and learning-forgetting-relearning process are successfully simulated and modulated by light stimulation. Most importantly, an artificial neural network is simulated based on the optical potentiation and electrical habituation characteristics of the synaptic devices, with recognition accuracy rates of 89.2, 93.8, and 91.9 % for file type datasets, small digits, and large digits are achieved. This study demonstrates a simple and efficient way to fabricate highly photosensitive optoelectronic synapse for artificial neural networks by combining the merits of specific materials and device architecture.

The study of motor muscle control mechanisms can improve rehabilitation therapy and human-computer interaction technology. The limitations of traditional electroencephalography (EEG) limit the comprehensive understanding of motor muscle control mechanisms. Therefore, this study aims to explore the mechanism of motor muscle control based on optical EEG images, in order to expand the understanding of the process of motor control. The study selected optical EEG imaging technology as the main data acquisition tool. Optical EEG images have higher spatiotemporal resolution and can provide more detailed neural activity information. This technology combines optical imaging with EEG images to obtain spatiotemporal information of brain activity in a short period of time. The device is composed of multiple optical sensors and can measure blood oxygen concentration and neuronal activity in the cerebral cortex. Preprocess EEG image data using image processing and signal processing techniques, then use computational methods and algorithms to detect activated regions, and evaluate their relationships using correlation analysis and statistical methods. By comparing EEG image data and motor muscle activity data under different motor tasks. The research results show that optical EEG imaging technology can provide more detailed information on brain neural activity and accurately capture the activity patterns of different motor muscles. These results provide new perspectives and methods for further studying the control mechanisms of motor muscles.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has killed more than 4 million humans globally, but there is no bona fide Food and Drug Administration-approved drug-like molecule to impede the COVID-19 pandemic. The sluggish pace of traditional therapeutic discovery is poorly suited to producing targeted treatments against rapidly evolving viruses. Here, we used an affinity-based screen of 4 billion DNA-encoded molecules en masse to identify a potent class of virus-specific inhibitors of the SARS-CoV-2 main protease (Mpro) without extensive and time-consuming medicinal chemistry. CDD-1714, the initial three-building-block screening hit (molecular weight [MW] = 542.5 g/mol), was a potent inhibitor (inhibition constant [Ki] = 20 nM). CDD-1713, a smaller two-building-block analog (MW = 353.3 g/mol) of CDD-1714, is a reversible covalent inhibitor of Mpro (Ki = 45 nM) that binds in the protease pocket, has specificity over human proteases, and shows in vitro efficacy in a SARS-CoV-2 infectivity model. Subsequently, key regions of CDD-1713 that were necessary for inhibitory activity were identified and a potent (Ki = 37 nM), smaller (MW = 323.4 g/mol), and metabolically more stable analog (CDD-1976) was generated. Thus, screening of DNA-encoded chemical libraries can accelerate the discovery of efficacious drug-like inhibitors of emerging viral disease targets.

In view of the shortcomings of traditional wall defect detection methods, such as small detection range, poor accuracy, non-portable device, and so on, a wall defects detection device based on Compton backscattering technology is designed by Monte Carlo method, which is mainly used to detect the size and location information of defects in concrete walls. It mainly consists of two parts, the source container and the detection system: first, through the simulation and analysis of the parameters such as the receiving angle of the backscattered particles and the rear collimating material of the detector, the influence of the fluorescent X-ray peak of the detector collimating material on the backscattered particle counts is eliminated and the detected error is reduced; second, the ring array detector design, compared with single array detector and surface array detector, can facilitate real-time detection of defect orientation, expanding the single scan range and improving the detection efficiency. After simulation and comparative analysis, the relevant optimal parameters are obtained: the object is detected using a Cs-137 γ-ray source with an activity of 6 mCi, and a ring detector consisting of four 0.5-inch cube-shaped CsI scintillator detectors is placed at 150° to receive the backscattered photons. The simulation analysis using the Monte Carlo FLUKA program showed that the maximum depth of wall defect detection is 8 cm, the maximum error fluctuation range of defect depth and thickness is ±1 cm, the overall device weight is

BackgroundTo the authors' knowledge, information regarding whether daily bathing with chlorhexidine gluconate (CHG) reduces central line-associated bloodstream infection (CLABSI) in pediatric oncology patients and those undergoing hematopoietic stem cell transplantation (HCT) is limited.MethodsIn the current multicenter, randomized, double-blind, placebo-controlled trial, patients aged ≥2 months and

Traditional engineering risk management has been unable to adapt to the complexity and variability due to its constituent elements and dynamic nature of internal and external environments. Vulnerability, as a concept closely related to risk, has been neglected in the traditional risk management due to its hidden characteristics. This study attempts to quantify and evaluate vulnerabilities of complex engineering projects independently and explore the transmission mechanism between risk and vulnerability factors. Twenty different types of large-scale engineering projects in China were selected as case studies from the Mega Project Case Study Center (MPCSC) of Tongji University. Vulnerability and risk factors of each project were identified and analysed. A mechanism model was developed to explore the impacts of vulnerabilities and risks through ta Fuzzy Petri Net. Four main vulnerability-risk critical paths were identified through the reverse labelling method. The overall evaluation of engineering project risks considering the impacts of vulnerabilities is the highlight of this paper. This study interprets the cognition and evaluation of complex engineering risks from a new perspective, enriches the connotation of engineering risk management, and provides a reference for risk management and decisionmaking of complex engineering projects.

BackgroundTo the authors' knowledge, information regarding whether daily bathing with chlorhexidine gluconate (CHG) reduces central line-associated bloodstream infection (CLABSI) in pediatric oncology patients and those undergoing hematopoietic stem cell transplantation (HCT) is limited.MethodsIn the current multicenter, randomized, double-blind, placebo-controlled trial, patients aged ≥2 months and