Development and application of a CNT-Ag-Cu-Al/PS-based paper electrode for detecting diverse analytes in complex matrices.

Electrochemical sensors play a crucial role in the detection of different analytes in complex matrices, and their performance is highly dependent on the electrode capacity. However, most of the available electrodes can only be used for single-component detection, so it is urgent to develop electrodes with high sensitivity and selectivity for different components. Herein, we report an amphiprotic amino-bonded carbon nanotube-Ag/Cu/Al nanoparticle/polystyrene-coated paper electrode (CNT-Ag-Cu-Al/PS electrode), which can be used for the measurement of glucose (Glc), oxytetracycline (OTC), and hydroquinone (HQ), respectively. The results showed that the analytical sensitivity and selectivity of the CNT-Ag-Cu-Al/PS electrode were comparable to those of single metal-coated paper substrate. The developed electrode also exhibited excellent linear responses for Glc, OTC, and HQ in the ranges of 1.0-1000.0 µM, 1.0 × 10-2 to 10.0 µM, and 5.0 × 10-3 to 50.0 µM, and the limits of detection (LODs) were 0.2055 µM (Glc), 0.0074 µM (OTC), and 0.0048 µM (HQ). Owing to the characteristics of good selectivity, anti-interference, stability, and reproducibility, the CNT-Ag-Cu-Al/PS paper electrode has been successfully applied to the detection of these analytes in complex human body fluids, food, and environmental waters. The paper electrode is promising for the detection of target compounds in complex matrices.

Prediction of flood sensitivity based on Logistic Regression, eXtreme Gradient Boosting, and Random Forest modeling methods.

Floods are one of the most destructive disasters that cause loss of life and property worldwide every year. In this study, the aim was to find the best-performing model in flood sensitivity assessment and analyze key characteristic factors, the spatial pattern of flood sensitivity was evaluated using three machine learning (ML) models: Logistic Regression (LR), eXtreme Gradient Boosting (XGBoost), and Random Forest (RF). Suqian City in Jiangsu Province was selected as the study area, and a random sample dataset of historical flood points was constructed. Fifteen different meteorological, hydrological, and geographical spatial variables were considered in the flood sensitivity assessment, 12 variables were selected based on the multi-collinearity study. Among the results of comparing the selected ML models, the RF method had the highest AUC value, accuracy, and comprehensive evaluation effect, and is a reliable and effective flood risk assessment model. As the main output of this study, the flood sensitivity map is divided into five categories, ranging from very low to very high sensitivity. Using the RF model (i.e., the highest accuracy of the model), the high-risk area covers about 44% of the study area, mainly concentrated in the central, eastern, and southern parts of the old city area.

Morphological variation in Schizothorax oconnori, Schizothorax waltoni (Teleostei: Cyprinidae: Schizothoracinae), and their natural hybrids from the middle Yarlung Zangbo River, Tibet.

The morphological variation in Schizothorax oconnori, Schizothorax waltoni, and their natural hybrids was examined using conventional and image-based analysis approaches. In total, 38 specimens of S. oconnori, 35 of S. waltoni, and 37 natural hybrids were collected from the Shigatse to the Lhasa section of the Yarlung Zangbo River during June and July 2021. A total of 21 morphometric, 4 meristic, and 27 truss variables were employed for the classification of S. oconnori, S. waltoni, and natural hybrids. Principal component analysis (PCA) and factor analysis (FA), as well as discriminant function analysis (DFA) and cluster analysis (CA), were conducted to identify differences based on traditional and truss measurements. Four principal components explained 75.92% of the variation among the morphometric characters, while five principal components accounted for 79.69% of the variation among the truss distances. FA results showed that factor 1 was associated with head shape, and factor 2 was associated with fins based on morphometric characters. Among the truss characters, factor 1 was related to head shape, and factor 2 was related to chest shape. In DFA, morphometric measurements achieved higher accuracy (100%) compared to truss distances (94.55%). The head morphology of hybrids exhibited intermediate traits between S. oconnori and S. waltoni. Both morphometry-based and truss-based clustering indicated that the morphology of natural hybrids leaned toward S. oconnori. In conclusion, the combination of morphometric and truss analysis is beneficial for classifying S. oconnori, S. waltoni, and their natural hybrids. The presence of natural hybrids could be considered an evolutionary response to the differentiation of nutritional and spatial niches in the middle Yarlung Zangbo River.

Earth-abundant Zn-dipyrrin chromophores for efficient CO2 photoreduction.

The development of strong sensitizing and Earth-abundant antenna molecules is highly desirable for CO2 reduction through artificial photosynthesis. Herein, a library of Zn-dipyrrin complexes (Z-1-Z-6) are rationally designed via precisely controlling their molecular configuration to optimize strong sensitizing Earth-abundant photosensitizers. Upon visible-light excitation, their special geometry enables intramolecular charge transfer to induce a charge-transfer state, which was first demonstrated to accept electrons from electron donors. The resulting long-lived reduced photosensitizer was confirmed to trigger consecutive intermolecular electron transfers for boosting CO2-to-CO conversion. Remarkably, the Earth-abundant catalytic system with Z-6 and Fe-catalyst exhibits outstanding performance with a turnover number of >20 000 and 29.7% quantum yield, representing excellent catalytic performance among the molecular catalytic systems and highly superior to that of noble-metal photosensitizer Ir(ppy)2(bpy)+ under similar conditions. Experimental and theoretical investigations comprehensively unveil the structure-activity relationship, opening up a new horizon for the development of Earth-abundant strong sensitizing chromophores for boosting artificial photosynthesis.

Paper-in-Tip Bipolar Electrospray Mass Spectrometry for Real-Time Chemical Reaction Monitoring.

Capturing short-lived intermediates at the molecular level is key to understanding the mechanism and dynamics of chemical reactions. Here, we have developed a paper-in-tip bipolar electrolytic electrospray mass spectrometry platform, in which a piece of triangular conductive paper incorporated into a plastic pipette tip serves not only as an electrospray emitter but also as a bipolar electrode (BPE), thus triggering both electrospray and electrolysis simultaneously upon application of a high voltage. The bipolar electrolysis induces a pair of redox reactions on both sides of BPE, enabling both electro-oxidation and electro-reduction processes regardless of the positive or negative ion mode, thus facilitating access to complementary structural information for mechanism elucidation. Our method enables real-time monitoring of transient intermediates (such as N,N-dimethylaniline radical cation, dopamine o-quinone (DAQ) and sulfenic acid with half-lives ranging from microseconds to minutes) and transient processes (such as DAQ cyclization with a rate constant of 0.15 s-1). This platform also provides key insights into electrocatalytic reactions such as Fe (III)-catalyzed dopamine oxidation to quinone species at physiological pH for neuromelanin formation.

Single Dispersion of Fe(H2O)2-Based Polyoxometalate on Polymeric Carbon Nitride for Biomimetic CH4 Photooxidation.

Direct methane conversion to value-added oxygenates under mild conditions with in-depth mechanism investigation has attracted wide interest. Inspired by methane monooxygenase, the K9Na2Fe(H2O)2{[γ-SiW9O34Fe(H2O)]}2·25H2O polyoxometalate (Fe-POM) with well-defined Fe(H2O)2 sites is synthesized to clarify the key role of Fe species and their microenvironment toward CH4 photooxidation. The Fe-POM can efficiently drive the conversion of CH4 to HCOOH with a yield of 1570.0 µmol gPOM -1 and 95.8% selectivity at ambient conditions, much superior to that of [Fe(H2O)SiW11O39]5- with Fe(H2O) active site, [Fe2SiW10O38(OH)]2 14- and [P8W48O184Fe16(OH)28(H2O)4]20- with multinuclear Fe-OH-Fe active sites. Single-dispersion of Fe-POM on polymeric carbon nitride (PCN) is facilely achieved to provide single-cluster functionalized PCN with well-defined Fe(H2O)2 site, the HCOOH yield can be improved to 5981.3 µmol gPOM -1. Systemic investigations demonstrate that the (WO)4-Fe(H2O)2 can supply Fe═O active center for C-H activation via forming (WO)4-Fea-Ot···CH4 intermediate, similar to that for CH4 oxidation in the monooxygenase. This work highlights a promising and facile strategy for single dispersion of ≈1-2 Å metal center with precise coordination microenvironment by uniformly anchoring nanoscale molecular clusters, which provides a well-defined model for in-depth mechanism research.

Complex-Valued Convolutional Gated Recurrent Neural Network for Ultrasound Beamforming.

Ultrasound detection is a potent tool for the clinical diagnosis of various diseases due to its real-time, convenient, and noninvasive qualities. Yet, existing ultrasound beamforming and related methods face a big challenge to improve both the quality and speed of imaging for the required clinical applications. The most notable characteristic of ultrasound signal data is its spatial and temporal features. Because most signals are complex-valued, directly processing them by using real-valued networks leads to phase distortion and inaccurate output. In this study, for the first time, we propose a complex-valued convolutional gated recurrent (CCGR) neural network to handle ultrasound analytic signals with the aforementioned properties. The complex-valued network operations proposed in this study improve the beamforming accuracy of complex-valued ultrasound signals over traditional real-valued methods. Further, the proposed deep integration of convolution and recurrent neural networks makes a great contribution to extracting rich and informative ultrasound signal features. Our experimental results reveal its outstanding imaging quality over existing state-of-the-art methods. More significantly, its ultrafast processing speed of only 0.07 s per image promises considerable clinical application potential. The code is available at https://github.com/zhangzm0128/CCGR.

Loss of OVOL2 in Triple-Negative Breast Cancer Promotes Fatty Acid Oxidation Fueling Stemness Characteristics.

Triple-negative breast cancer (TNBC), the most aggressive subtype of breast cancer, has a poor prognosis and lacks effective treatment strategies. Here, the study discovered that TNBC shows a decreased expression of epithelial transcription factor ovo-like 2 (OVOL2). The loss of OVOL2 promotes fatty acid oxidation (FAO), providing additional energy and NADPH to sustain stemness characteristics, including sphere-forming capacity and tumor initiation. Mechanistically, OVOL2 not only suppressed STAT3 phosphorylation by directly inhibiting JAK transcription but also recruited histone deacetylase 1 (HDAC1) to STAT3, thereby reducing the transcriptional activation of downstream genes carnitine palmitoyltransferase1 (CPT1A and CPT1B). PyVT-Ovol2 knockout mice develop a higher number of primary breast tumors with accelerated growth and increased lung-metastases. Furthermore, treatment with FAO inhibitors effectively reduces stemness characteristics of tumor cells, breast tumor initiation, and metastasis, especially in OVOL2-deficient breast tumors. The findings suggest that targeting JAK/STAT3 pathway and FAO is a promising therapeutic strategy for OVOL2-deficient TNBC.

A novel engineered IL-21 receptor arms T-cell receptor-engineered T cells (TCR-T cells) against hepatocellular carcinoma.

Strategies to improve T cell therapy efficacy in solid tumors such as hepatocellular carcinoma (HCC) are urgently needed. The common cytokine receptor γ chain (γc) family cytokines such as IL-2, IL-7, IL-15 and IL-21 play fundamental roles in T cell development, differentiation and effector phases. This study aims to determine the combination effects of IL-21 in T cell therapy against HCC and investigate optimized strategies to utilize the effect of IL-21 signal in T cell therapy. The antitumor function of AFP-specific T cell receptor-engineered T cells (TCR-T) was augmented by exogenous IL-21 in vitro and in vivo. IL-21 enhanced proliferation capacity, promoted memory differentiation, downregulated PD-1 expression and alleviated apoptosis in TCR-T after activation. A novel engineered IL-21 receptor was established, and TCR-T armed with the novel engineered IL-21 receptors (IL-21R-TCR-T) showed upregulated phosphorylated STAT3 expression without exogenous IL-21 ligand. IL-21R-TCR-T showed better proliferation upon activation and superior antitumor function in vitro and in vivo. IL-21R-TCR-T exhibited a less differentiated, exhausted and apoptotic phenotype than conventional TCR-T upon repetitive tumor antigen stimulation. The novel IL-21 receptor in our study programs powerful TCR-T and can avoid side effects induced by IL-21 systemic utilization. The novel IL-21 receptor creates new opportunities for next-generation TCR-T against HCC.

Atg5 deficiency in macrophages protects against kidney fibrosis via the CCR6-CCL20 axis.

BACKGROUND: Autophagy is a lysosome-dependent degradation pathway that regulates macrophage activation, differentiation, and polarization. Autophagy related 5 (Atg5) is a key protein involved in phagocytic membrane elongation in autophagic vesicles that forms a complex with Atg12 and Atg16L1. Alterations in Atg5 are related to both acute and chronic kidney diseases in experimental models. However, the role of macrophage-expressed Atg5 in acute kidney injury remains unclear. METHODS: Using a myeloid cell-specific Atg5 knockout (MΦ atg5-/-) mouse, we established renal ischemia/reperfusion and unilateral ureteral obstruction models to evaluate the role of macrophage Atg5 in renal macrophage migration and fibrosis. RESULTS: Based on changes in the serum urea nitrogen and creatinine levels, Atg5 deletion had a minimal effect on renal function in the early stages after mild injury; however, MΦ atg5-/- mice had reduced renal fibrosis and reduced macrophage recruitment after 4 weeks of ischemia/reperfusion injury and 2 weeks of unilateral ureteral obstruction injury. Atg5 deficiency impaired the CCL20-CCR6 axis after severe ischemic kidneys. Chemotactic responses of bone marrow-derived monocytes (BMDMs) from MΦ atg5-/- mice to CCL20 were significantly attenuated compared with those of wild-type BMDMs, and this might be caused by the inhibition of PI3K, AKT, and ERK1/2 activation. CONCLUSIONS: Our data indicate that Atg5 deficiency decreased macrophage migration by impairing the CCL20-CCR6 axis and inhibited M2 polarization, thereby improving kidney fibrosis.

Mesenchymal Stromal Cells Increase the Natural Killer Resistance of Circulating Tumor Cells via Intercellular Signaling of cGAS-STING-IFNß-HLA.

Circulating tumor cells (CTCs) shed from primary tumors must overcome the cytotoxicity of immune cells, particularly natural killer (NK) cells, to cause metastasis. The tumor microenvironment (TME) protects tumor cells from the cytotoxicity of immune cells, which is partially executed by cancer-associated mesenchymal stromal cells (MSCs). However, the mechanisms by which MSCs influence the NK resistance of CTCs remain poorly understood. This study demonstrates that MSCs enhance the NK resistance of cancer cells in a gap junction-dependent manner, thereby promoting the survival and metastatic seeding of CTCs in immunocompromised mice. Tumor cells crosstalk with MSCs through an intercellular cGAS-cGAMP-STING signaling loop, leading to increased production of interferon-ß (IFNß) by MSCs. IFNß reversely enhances the type I IFN (IFN-I) signaling in tumor cells and hence the expression of human leukocyte antigen class I (HLA-I) on the cell surface, protecting the tumor cells from NK cytotoxicity. Disruption of this loop reverses NK sensitivity in tumor cells and decreases tumor metastasis. Moreover, there are positive correlations between IFN-I signaling, HLA-I expression, and NK tolerance in human tumor samples. Thus, the NK-resistant signaling loop between tumor cells and MSCs may serve as a novel therapeutic target.

Single-cluster Functionalized TiO2 Nanotube Array for Boosting Water Oxidation and CO2 Photoreduction to CH3OH.

Solar-driven CO2 reduction and water oxidation to liquid fuels represents a promising solution to alleviate energy crisis and climate issue, but it remains a great challenge for generating CH3OH and CH3CH2OH dominated by multi-electron transfer. Single-cluster catalysts with super electron acceptance, accurate molecular structure, customizable electronic structure and multiple adsorption sites, have led to greater potential in catalyzing various challenging reactions. However, accurately controlling the number and arrangement of clusters on functional supports still faces great challenge. Herein, we develop a facile electrosynthesis method to uniformly disperse Wells-Dawson- and Keggin-type polyoxometalates on TiO2 nanotube arrays, resulting in a series of single-cluster functionalized catalysts P2M18O62@TiO2 and PM12O40@TiO2 (M=Mo or W). The single polyoxometalate cluster can be distinctly identified and serves as electronic sponge to accept electrons from excited TiO2 for enhancing surface-hole concentration and promote water oxidation. Among these samples, P2Mo18O62@TiO2-1 exhibits the highest electron consumption rate of 1260 µmol g-1 for CO2-to-CH3OH conversion with H2O as the electron source, which is 11 times higher than that of isolated TiO2 nanotube arrays. This work supplied a simple synthesis method to realize the single-dispersion of molecular cluster to enrich surface-reaching holes on TiO2, thereby facilitating water oxidation and CO2 reduction.

Building Co16-N3-Based UiO-MOF to Expand Design Parameters for MOF Photosensitization.

The construction of secondary building units (SBUs) in versatile metal-organic frameworks (MOFs) represents a promising method for developing multi-functional materials, especially for improving their sensitizing ability. Herein, we developed a dual small molecules auxiliary strategy to construct a high-nuclear transition-metal-based UiO-architecture Co16-MOF-BDC with visible-light-absorbing capacity. Remarkably, the N3 - molecule in hexadecameric cobalt azide SBU offers novel modification sites to precise bonding of strong visible-light-absorbing chromophores via click reaction. The resulting Bodipy@Co16-MOF-BDC exhibits extremely high performance for oxidative coupling benzylamine (~100 % yield) via both energy and electron transfer processes, which is much superior to that of Co16-MOF-BDC (31.5 %) and Carboxyl @Co16-MOF-BDC (37.5 %). Systematic investigations reveal that the advantages of Bodipy@Co16-MOF-BDC in dual light-absorbing channels, robust bonding between Bodipy/Co16 clusters and efficient electron-hole separation can greatly boost photosynthesis. This work provides an ideal molecular platform for synergy between photosensitizing MOFs and chromophores by constructing high-nuclear transition-metal-based SBUs with surface-modifiable small molecules.

Performance evaluation and metagenomic analysis of sequencing batch reactor under transient 2,4,6-trichlorophenol shock.

The transient chlorophenol shock under some emergency conditions might directly affect the pollutant removal of bioreactor. Therefore, the recovery of bioreactor performance after transient chlorophenol shock is a noteworthy issue. In the present research, the performance, antioxidant response, microbial succession and functional genes of sequencing batch reactor (SBR) were evaluated under transient 2,4,6-trichlorophenol (2,4,6-TCP) shock. The chemical oxygen demand (COD) and ammonia nitrogen (NH4+-N) removal efficiencies decreased sharply in the first 4 days after 60 mg/L 2,4,6-TCP shock for 24 h and gradually recovered to normal in the subsequent 8 days. The nitrogen removal rates and their corresponding enzymatic activities rapidly decreased after transient 2,4,6-TCP shock and then gradually increased to normal. The increase of antioxidant enzymatic activity, Cu-Zn SOD genes and Fe-Mn SOD genes contributed to the recovery of SBR performance. The abundance of genes encoding ammonia monooxygenase and hydroxylamine dehydrogenase decreased after transient 2,4,6-TCP shock, including amoA, amoC and nxrA. Thauera, Dechloromonas and Candidatus_Competibacter played key roles in the restorative process, which provided stable abundances of narG, norB , norC and nosZ. The results will deeply understand into the effect of transient 2,4,6-TCP shock on bioreactor performance and provide theoretical basis to build promising recoveries strategy of bioreactor performance.

Evaluation of monolithic crystal detector with dual-ended readout utilizing multiplexing method.

Objective.Monolithic crystal detectors are increasingly being applied in positron emission tomography (PET) devices owing to their excellent depth-of-interaction (DOI) resolution capabilities and high detection efficiency. In this study, we constructed and evaluated a dual-ended readout monolithic crystal detector based on a multiplexing method.Approach.We employed two 12 × 12 silicon photomultiplier (SiPM) arrays for readout, and the signals from the 12 × 12 array were merged into 12 X and 12 Y channels using channel multiplexing. In 2D reconstruction, three methods based on the centre of gravity (COG) were compared, and the concept of thresholds was introduced. Furthermore, a light convolutional neural network (CNN) was employed for testing. To enhance depth localization resolution, we proposed a method by utilizing the mutual information from both ends of the SiPMs. The source width and collimation effect were simulated using GEANT4, and the intrinsic spatial resolution was separated from the measured values.Main results.At an operational voltage of 29 V for the SiPM, an energy resolution of approximately 12.5 % was achieved. By subtracting a 0.8 % threshold from the total energy in every channel, a 2D spatial resolution of approximately 0.90 mm full width at half maximum (FWHM) can be obtained. Furthermore, a higher level of resolution, approximately 0.80 mm FWHM, was achieved using a CNN, with some alleviation of edge effects. With the proposed DOI method, a significant 1.36 mm FWHM average DOI resolution can be achieved. Additionally, it was found that polishing and black coating on the crystal surface yielded smaller edge effects compared to a rough surface with a black coating.Significance.The introduction of a threshold in COG method and a dual-ended readout scheme can lead to excellent spatial resolution for monolithic crystal detectors, which can help to develop PET systems with both high sensitivity and high spatial resolution.

Surface charge-induced electrospray for high-throughput analysis of complex samples and electrochemical reaction intermediates using mass spectrometry.

Electrospray-related ion sources are promising for direct mass spectrometric analysis of complex samples, but current protocols suffer from complicated components and low analytical sensitivity. Here, we propose a surface charge-induced electrospray ionization (SCIESI) inspired by flashover on an insulator surface under high voltage. This protocol not only effectively avoids contact between the sample solution and metal electrode, but also allows completion of the entire analytical process in less than 40 seconds and limits of detection in the pictogram per milliliter range. SCIESI coupled to mass spectrometry can also be used to monitor electro-chemical processes, and a number of oxidation and reduction reactions have been studied, demonstrating that it is a powerful tool for understanding electrochemical reaction mechanisms.

Phenome-wide causal associations between osteoarthritis and other complex traits through the latent causal variable analysis.

BACKGROUND: Individuals with osteoarthritis present with comorbidities, and the potential causal associations remain incompletely elucidated. The present study undertook a large-scale investigation about the causality between osteoarthritis and variable traits, using the summary-level data of genome-wide association studies (GWAS). METHODS: The present study included the summary-level GWS data of knee osteoarthritis, hip osteoarthritis, hip or knee osteoarthritis, hand osteoarthritis, and other 1355 traits. Genetic correlation analysis was conducted between osteoarthritis and other traits through cross-trait bivariate linkage disequilibrium score regression. Subsequently, latent causal variable analysis was performed to explore the causal association when there was a significant genetic correlation. Genetic correlation and latent causal variable analysis were conducted on the Complex Traits Genomics Virtual Lab platform ( https://vl.genoma.io/ ). RESULTS: We found 133 unique phenotypes showing causal relationships with osteoarthritis. Our results confirmed several well-established risk factors of osteoarthritis, such as obesity, weight, BMI, and meniscus derangement. Additionally, our findings suggested putative causal links between osteoarthritis and multiple factors. Socioeconomic determinants such as occupational exposure to dust and diesel exhaust, extended work hours exceeding 40 per week, and unemployment status were implicated. Furthermore, our analysis revealed causal associations with cardiovascular and metabolic disorders, including heart failure, deep venous thrombosis, type 2 diabetes mellitus, and elevated cholesterol levels. Soft tissue and musculoskeletal disorders, such as hallux valgus, internal derangement of the knee, and spondylitis, were also identified to be causally related to osteoarthritis. The study also identified the putative causal associations of osteoarthritis with digestive and respiratory diseases, such as Barrett's esophagus, esophagitis, and asthma, as well as psychiatric conditions including panic attacks and manic or hyperactive episodes. Additionally, we observed osteoarthritis causally related to pharmacological treatments, such as the use of antihypertensive medications, anti-asthmatic drugs, and antidepressants. CONCLUSION: Our study uncovered a wide range of traits causally associated with osteoarthritis. Further studies are needed to validate and illustrate the detailed mechanism of those causal associations.

Clinical practice guidelines for prevention and treatment of postoperative gastrointestinal disorder with Integrated Traditional Chinese and Western Medicine (2023).

Postoperative gastrointestinal disorder (POGD) was a common complication after surgery under anesthesia. Strategies in combination with Traditional Chinese Medicine and Western medicine showed some distinct effects but standardized clinical practice guidelines were not available. Thus, a multidisciplinary expert team from various professional bodies including the Perioperative and Anesthesia Professional Committees of the Chinese Association of Integrative Medicine (CAIM), jointly with Gansu Province Clinical Research Center of Integrative Anesthesiology/Anesthesia and Pain Medical Center of Gansu Provincial Hospital of Traditional Chinese Medicine and WHO Collaborating Center for Guideline Implementation and Knowledge Translation/Chinese Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) Center/Gansu Provincial Center for Medical Guideline Industry Technology/Evidence-based Medicine Center of Lanzhou University, was established to develop evidence-based guidelines. Clinical questions (7 background and 12 clinical questions) were identified through literature reviews and expert consensus meetings. Based on systematic reviews/meta-analyses, evidence quality was analyzed and the advantages and disadvantages of interventional measures were weighed with input from patients' preferences. Finally, 20 recommendations were developed through the Delphi-based consensus meetings. These recommendations included disease definitions, etiologies, pathogenesis, syndrome differentiation, diagnosis, and perioperative prevention and treatment.

A Light Multi-View Stereo Method with Patch-Uncertainty Awareness.

Multi-view stereo methods utilize image sequences from different views to generate a 3D point cloud model of the scene. However, existing approaches often overlook coarse-stage features, impacting the final reconstruction accuracy. Moreover, using a fixed range for all the pixels during inverse depth sampling can adversely affect depth estimation. To address these challenges, we present a novel learning-based multi-view stereo method incorporating attention mechanisms and an adaptive depth sampling strategy. Firstly, we propose a lightweight, coarse-feature-enhanced feature pyramid network in the feature extraction stage, augmented by a coarse-feature-enhanced module. This module integrates features with channel and spatial attention, enriching the contextual features that are crucial for the initial depth estimation. Secondly, we introduce a novel patch-uncertainty-based depth sampling strategy for depth refinement, dynamically configuring depth sampling ranges within the GRU-based optimization process. Furthermore, we incorporate an edge detection operator to extract edge features from the reference image's feature map. These edge features are additionally integrated into the iterative cost volume construction, enhancing the reconstruction accuracy. Lastly, our method is rigorously evaluated on the DTU and Tanks and Temples benchmark datasets, revealing its low GPU memory consumption and competitive reconstruction quality compared to other learning-based MVS methods.

Structure-Based Discovery of the SARS-CoV-2 Main Protease Noncovalent Inhibitors from Traditional Chinese Medicine.

Traditional Chinese medicine (TCM) has been extensively employed for the treatment of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there is demand for discovering more SARS-CoV-2 Mpro inhibitors with diverse scaffolds to optimize anti-SARS-CoV-2 lead compounds. In this study, comprehensive in silico and in vitro assays were utilized to determine the potential inhibitors from TCM compounds against SARS-CoV-2 Mpro, which is an important therapeutic target for SARS-CoV-2. The ensemble docking analysis of 18263 TCM compounds against 15 SARS-CoV-2 Mpro conformations identified 19 TCM compounds as promising candidates. Further in vitro testing validated three compounds as inhibitors of SARS-CoV-2 Mpro and showed IC50 values of 4.64 ± 0.11, 7.56 ± 0.78, and 11.16 ± 0.26 µM, with EC50 values of 12.25 ± 1.68, 15.58 ± 0.77, and 29.32 ± 1.25 µM, respectively. Molecular dynamics (MD) simulations indicated that the three complexes remained stable over the last 100 ns of production run. An analysis of the binding mode revealed that the active compounds occupy different subsites (S1, S2, S3, and S4) of the active site of SARS-CoV-2 Mpro via specific poses through noncovalent interactions with key amino acids (e.g., HIS 41, ASN 142, GLY 143, MET 165, GLU 166, or GLN 189). Overall, this study provides evidence indicating that the three natural products obtained from TCM could be further used for anti-COVID-19 research, justifying the investigation of Chinese herbal medicinal ingredients as bioactive constituents for therapeutic targets.