DrugCLIP: Contrastive Protein-Molecule Representation Learning for Virtual Screening

Virtual screening, which identifies potential drugs from vast compound databases to bind with a particular protein pocket, is a critical step in AI-assisted drug discovery. Traditional docking methods are highly time-consuming, and can only work with a restricted search library in real-life applications. Recent supervised learning approaches using scoring functions for binding-affinity prediction, although promising, have not yet surpassed docking methods due to their strong dependency on limited data with reliable binding-affinity labels. In this paper, we propose a novel contrastive learning framework, DrugCLIP, by reformulating virtual screening as a dense retrieval task and employing contrastive learning to align representations of binding protein pockets and molecules from a large quantity of pairwise data without explicit binding-affinity scores. We also introduce a biological-knowledge inspired data augmentation strategy to learn better protein-molecule representations. Extensive experiments show that DrugCLIP significantly outperforms traditional docking and supervised learning methods on diverse virtual screening benchmarks with highly reduced computation time, especially in zero-shot setting

A systematic review and Bayesian meta-analysis of the antibiotic treatment courses in AECOPD

Background: No consensus exists on the antibiotic treatment course for patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPD). Former studies indicate that shorter courses might have the same efficacy with fewer adverse events, which is inconsistent with guidelines and general practice. Existing evidence allows us to conduct a systematic review and Bayesian analysis on this topic.Methods: Four databases were searched from their inception to January 5, 2023. All statistical estimations were performed using R. “Gemtc” was the core package of analysis. CINeMA was used to assess the grade of confidence of the results.Results: Fourteen studies were included in the Bayesian meta-analysis. No difference in the clinical success rate of antibiotic treatment was observed from a super short course (1–3 days) to a long course (≥10 days). Considering the adverse events, the short course (4–6 days) might be the safest. The majority of results were of high or moderate confidence grade.Conclusion: Short course might cause the fewest adverse events. The clinical efficacy of antibiotics might not depend on the course length. Undeniably, more systematic explorations are warranted to investigate the clinical application of a shorter course of antibiotic treatment

Adaptive Hash Retrieval with Kernel Based Similarity

Indexing methods have been widely used for fast data retrieval on large scale datasets. When the data are represented by high dimensional vectors, hashing is often used as an efficient solution for approximate similarity search. When a retrieval task does not involve supervised training data, most hashing methods aim at preserving data similarity defined by a distance metric on the feature vectors. Hash codes generated by these approaches normally maintain the Hamming distance of the data in accordance with the similarity function, but ignore the local details of the distribution of data. This objective is not suitable for k-nearest neighbor search since the similarity to the nearest neighbors can vary significantly for different data samples. In this paper, we present a novel adaptive similarity measure which is consistent with k-nearest neighbor search, and prove that it leads to a valid kernel if the original similarity function is a kernel function. Next we propose a method which calculates hash codes using the kernel function. With a low-rank approximation, our hashing framework is more effective than existing methods that preserve similarity over an arbitrary kernel. The proposed similarity function, hashing framework, and their combination demonstrate significant improvement when compared with several alternative state-of-the-art methods

Efficacy and safety of three species of Rhodiola L. in patients with chronic obstructive pulmonary disease: A systematic review and meta-analysis

Background: Chronic obstructive pulmonary disease (COPD) is characterized by chronic hypoxia, inflammation, oxidative stress, and irreversible airflow limitations. Rhodiola L. is a genus of botanical drugs used in traditional medicine that may influence COPD.Objective: A systematic review of the safety and efficacy of Rhodiola L. in patients with COPD.Material and methods: We searched the PubMed, Embase, Cochrane Library, Web of Science, Scopus, China National Knowledge Infrastructure (CNKI), Chongqing VIP, Wanfang, and SinoMed databases. The search strategy used terms including “COPD” and “Rhodiola.” Two independent reviewers conducted the literature screening, data extraction, and risk of bias assessment, with a third reviewer involved to resolve disagreements. Statistical analysis was conducted in Review Manager (version 5.4.1), following the Cochrane Handbook.Results: This review included nine studies, of which two focused on Rhodiola crenulata (Hook.f. and Thomson) H. Ohba (R. crenulata) and two on Rhodiola kirilowii (Regel) Maxim (R. kirilowii); the remaining five focused on Rhodiola wallichiana (Hook.) S.H.Fu (R. wallichiana). Compared with the placebo, patients who received Rhodiola L. presented no more adverse events (p = 0.65) but showed significant improvement in the percentage of forced expiratory volume in 1 s at prediction (FEV1%pred), forced expiratory volume in 1 s (FEV1), the ratio of forced expiratory volume in 1 s on forced vital capacity (FEV1/FVC), saturation of oxygen in arterial blood, partial pressure of oxygen in arterial blood (PaO2), partial pressure of carbon dioxide in arterial blood (PaCO2), systolic pulmonary arterial pressure, diastolic pulmonary arterial pressure, COPD assessment test, efficient rate, C-reactive protein, and N-terminal pro-B-type natriuretic peptide (all p < 0.01). Compared with ambroxol, R. kirilowii provided additional benefits to patients with COPD in FEV1%pred, FEV1, FEV1/FVC, PaO2, PaCO2, 8-iso-prostaglandin F2α, superoxide dismutase, glutathione, malondialdehyde, and total antioxidant capacity (all p < 0.01).Conclusion: Among the Rhodiola L. genus, this review included R. wallichiana, R. crenulata, and R. kirilowii, which might be safe and effective in COPD. Although this study has several limitations, further RCTs are needed.Systematic Review Registration: [https://www.crd.york.ac.uk/PROSPERO/ display_record.php?RecordID=302881], identifier [CRD42022361890]

Active and machine learning-enhanced discovery of new FGFR3 inhibitor, Rhapontin, through virtual screening of receptor structures and anti-cancer activity assessment

Introduction: This study bridges traditional remedies and modern pharmacology by exploring the synergy between natural compounds and Ceritinib in treating Non-Small Cell Lung Cancer (NSCLC), aiming to enhance efficacy and reduce toxicities.Methods: Using a combined approach of computational analysis, machine learning, and experimental procedures, we identified and analyzed PD173074, Isoquercitrin, and Rhapontin as potential inhibitors of fibroblast growth factor receptor 3 (FGFR3). Machine learning algorithms guided the initial selection, followed by Quantitative Structure-Activity Relationship (QSAR) modeling and molecular dynamics simulations to evaluate the interaction dynamics and stability of Rhapontin. Physicochemical assessments further verified its drug-like properties and specificity.Results: Our experiments demonstrate that Rhapontin, when combined with Ceritinib, significantly suppresses tumor activity in NSCLC while sparing healthy cells. The molecular simulations and physicochemical evaluations confirm Rhapontin’s stability and favorable interaction with FGFR3, highlighting its potential as an effective adjunct in NSCLC therapy.Discussion: The integration of natural compounds with established cancer therapies offers a promising avenue for enhancing treatment outcomes in NSCLC. By combining the ancient wisdom of natural remedies with the precision of modern science, this study contributes to evolving cancer treatment paradigms, potentially mitigating the side effects associated with current therapies

Whole exome sequencing identifies frequent somatic mutations in cell-cell adhesion genes in chinese patients with lung squamous cell carcinoma

Lung squamous cell carcinoma (SQCC) accounts for about 30% of all lung cancer cases. Understanding of mutational landscape for this subtype of lung cancer in Chinese patients is currently limited. We performed whole exome sequencing in samples from 100 patients with lung SQCCs to search for somatic mutations and the subsequent target capture sequencing in another 98 samples for validation. We identified 20 significantly mutated genes, including TP53, CDH10, NFE2L2 and PTEN. Pathways with frequently mutated genes included those of cell-cell adhesion/Wnt/Hippo in 76%, oxidative stress response in 21%, and phosphatidylinositol-3-OH kinase in 36% of the tested tumor samples. Mutations of Chromatin regulatory factor genes were identified at a lower frequency. In functional assays, we observed that knockdown of CDH10 promoted cell proliferation, soft-agar colony formation, cell migration and cell invasion, and overexpression of CDH10 inhibited cell proliferation. This mutational landscape of lung SQCC in Chinese patients improves our current understanding of lung carcinogenesis, early diagnosis and personalized therapy

Refined Design and Optimization of Underground Medium and Long Hole Blasting Parameters—A Case Study of the Gaofeng Mine

Previously conducted studies have established that the rationality of the parameters of medium-deep hole blasting is one of the main factors affecting the blasting effect. To solve the problem of the parameter design and optimization design of medium-deep hole blasting in underground mines, a method of parameter design and the optimization of medium-deep hole blasting based on the blasting crater tests and numerical simulation analyses has been proposed in this study. Based on the background of deep underground mining in Gaofeng Mine, a two-hole blasting model has been established, and the blasting parameters are simulated and analyzed by the damage stress variation of the two-hole model. During the study, the initial values of blasting parameters were first obtained from the field blasting crater test, then the blasting parameters were optimized and analyzed by LS-DYNA software, and finally, the optimization scheme was demonstrated by the corresponding blasting test. The results of the field test showed that the design method of integrated blast crater test and numerical simulation analysis can effectively optimize the design of medium-deep hole blasting parameters and improve the blasting effect to a large extent. This study also provides an effective design system for the design of deep hole blasting parameters in similar mines

The novel fluid loss additive HTF-200C for oil field cementing

The domestic fluid loss additives often have lower thermal stability and poor salt-tolerance and their comprehensive properties are not good enough. To solve the problems, a novel cement fluid loss additive HTF-200C, which can resist high temperature and high salt content, was synthesized using the monomers of 2-acrylamido-2-methyl-propane sulphonic acid (AMPS), N, N-dimethyl acrylamide (DMAA) and a new compound with double carboxyl by the method of aqueous solution polymerization. The microstructural characterization and application performance of HTF-200C show that the polymer with the structure of all the monomers has an excellent thermal stability and strong salt tolerance, and can be used in 200 °C or in saturated brine. And the problem of the normal fluid loss additive being easy to hydrolyze due to high temperature can be solved with HTF-200C. What's more, it can also deal with the bulge of thickening curve in consistency test. The cement slurry prepared mainly by HTF-200C presents good comprehensive properties such as low filtration, high thermal stability, strong salt tolerance, rapid development of strength in low temperature, without far delayed solidification, short transit time during thickening process, and so on. The cementing job quality of Well Chengu 1-3 in the Liaohe Oilfield is excellent after it is used. Key words: novel fluid loss additive, HTF-200C, salt-tolerance, temperature-resistance, cement properties, applicatio

Underground Mine Safety and Health: A Hybrid MEREC–CoCoSo System for the Selection of Best Sensor

This research addresses the paramount issue of enhancing safety and health conditions in underground mines through the selection of optimal sensor technologies. A novel hybrid MEREC-CoCoSo system is proposed, integrating the strengths of the MEREC (Method for Eliciting Relative Weights) and Combined Compromise Solution (CoCoSo) methods. The study involves a three-stage framework: criteria and sensor discernment, criteria weight determination using MEREC, and sensor prioritization through the MEREC-CoCoSo framework. Fifteen criteria and ten sensors were identified, and a comprehensive analysis, including MEREC-based weight determination, led to the prioritization of “Ease of Installation” as the most critical criterion. Proximity sensors were identified as the optimal choice, followed by biometric sensors, gas sensors, and temperature and humidity sensors. To validate the effectiveness of the proposed MEREC-CoCoSo model, a rigorous comparison was conducted with established methods, including VIKOR, TOPSIS, TODIM, ELECTRE, COPRAS, EDAS, and TRUST. The comparison encompassed relevant metrics such as accuracy, sensitivity, and specificity, providing a comprehensive understanding of the proposed model’s performance in relation to other established methodologies. The outcomes of this comparative analysis consistently demonstrated the superiority of the MEREC-CoCoSo model in accurately selecting the best sensor for ensuring safety and health in underground mining. Notably, the proposed model exhibited higher accuracy rates, increased sensitivity, and improved specificity compared to alternative methods. These results affirm the robustness and reliability of the MEREC-CoCoSo model, establishing it as a state-of-the-art decision-making framework for sensor selection in underground mine safety. The inclusion of these actual results enhances the clarity and credibility of our research, providing valuable insights into the superior performance of the proposed model compared to existing methodologies. The main objective of this research is to develop a robust decision-making framework for optimal sensor selection in underground mines, with a focus on enhancing safety and health conditions. The study seeks to identify and prioritize critical criteria for sensor selection in the context of underground mine safety. The research strives to contribute to the mining industry by offering a structured and effective approach to sensor selection, prioritizing safety and health in underground mining operations

Microstructure and mechanical properties of K438 alloy processed by selective laser melting and subsequent heat treatment

In this work, K438 nickel-based high-temperature alloy was successfully prepared and heat-treated by selected laser melting (SLM). A comparative study of the microstructure and mechanical properties of different samples was carried out to reveal the influence of SLM process parameters and heat treatment. The layer-by-layer fabrication in SLM created a special sunflower-shaped dendrites and the extremely fast cooling rate resulted in a large number of low angle grain boundaries (LAGBs) and inhomogeneous γ’ phases being found in the samples. After heat treatment, the orbital structure within the tissue disappeared and the coarse square γ’ phase (0.4 to 0.8 μm) melted and precipitated fine rounded secondary γ’ phases (0.05 μm). During recrystallisation, the LAGBs to high angle grain boundaries (HAGBs) transition occurs and many fine grain clusters appear at the grain boundaries, resulting in subcrystalline nucleation based on subcrystals and an increase in UTS