Advancements in artificial intelligence (AI) and emerging technologies are rapidly expanding the exploration of chemical space, facilitating innovative drug discovery. However, the transformation of novel compounds into safe and effective drugs remains a lengthy, high-risk, and costly process. Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development. Despite this need, no comprehensive tool currently supports systematic evaluation and efficient screening. Here, we present druglikeFilter, a deep learning-based framework designed to assess drug-likeness across four critical dimensions: 1) physicochemical rule evaluated by systematic determination, 2) toxicity alert investigated from multiple perspectives, 3) binding affinity measured by dual-path analysis, and 4) compound synthesizability assessed by retro-route prediction. By enabling automated, multidimensional filtering of compound libraries, druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates, which can be freely accessed at https://idrblab.org/drugfilter/.

ObjectiveTo study the effect of Tanreqing injection （TRQ） on the pulmonary flora in the rat model of chronic obstructive pulmonary disease （COPD）. MethodWistar rats were randomized into control， model， and TRQ groups. The rats in other groups except the control group were treated by smoking combined with intratracheal instillation of lipopolysaccharide for the modeling of COPD. The TRQ group was intraperitoneally injected with TRQ （2 g·kg^-1）. At the end of the experiment， after blood collection from the abdominal aorta of the rats， the lung tissue was collected for hematoxylin-eosin and picric sirius red staining to reveal the pathological changes. The lung lavage fluid was collected， and the diversity and relative abundance of lung flora in different groups were analyzed by 16S rDNA amplicon sequencing. ResultThe lungs of the control group were normal， and those of the model group showed neutrophil infiltration， telangiectasia， lung hemorrhage and emphysema in individual cases， and thickening of collagen fibers in the trachea. Compared with the model group， the TRQ group showed significantly improved lungs and recovered collagen fibers. The MLI analysis showed that compared with the control group， the model group showcased increased alveolar space （P<0.01）， which was reduced in the TRQ group （P<0.05）. Compared with the control group， the model group showed increased wall thickness （P<0.01）， and the increase was attenuated in the TRQ group （P<0.01）. TRQ increased the Simpson index and altered the α diversity of pulmonary flora. The results of principal co-ordinate analysis showed that TRQ changed the β diversity and reduced the β diversity index of pulmonary flora. At the genus level， the model group showed increased relative abundance of g_Bacillus and g_Brevundimonas and decreased relative abundance of g_Pseudomonas， compared with the control group. After treatment with TRQ， the relative abundance of g_Stenotrophomonas increased， and that of g_Bacillus decreased. The LEfSe of differential taxa between groups showed that the modeling increased the relative abundance of g_Lachnospiraceae_NK4A136_group， and TRQ treatment increased the relative abundance of g_Rhodococcus and g_Stenotrophomonas. ConclusionTRQ can regulate the diversity of pulmonary flora and restore the balance of bacterial genera in the rat model of COPD， which may be one of the mechanisms of the prevention and treatment of COPD with TRQ.

Currently,human health due to corona virus disease 2019(COVID-19)pandemic has been seriously threatened.The coronavirus severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)spike(S)protein plays a crucial role in virus transmission and several S-based therapeutic approaches have been approved for the treatment of COVID-19.However,the efficacy is compromised by the SARS-CoV-2 evolvement and mutation.Here we report the SARS-CoV-2 S protein receptor-binding domain(RBD)inhibitor licorice-saponin A3(A3)could widely inhibit RBD of SARS-CoV-2 variants,including Beta,Delta,and Omicron BA.1,XBB and BQ1.1.Furthermore,A3 could potently inhibit SARS-CoV-2 Omicron virus in Vero E6 cells,with EC50 of 1.016 pM.The mechanism was related to binding with Y453 of RBD deter-mined by hydrogen-deuterium exchange mass spectrometry(HDX-MS)analysis combined with quan-tum mechanics/molecular mechanics(QM/MM)simulations.Interestingly,phosphoproteomics analysis and multi fluorescent immunohistochemistry(mIHC)respectively indicated that A3 also inhibits host inflammation by directly modulating the JNK and p38 mitogen-activated protein kinase(MAPK)path-ways and rebalancing the corresponding immune dysregulation.This work supports A3 as a promising broad-spectrum small molecule drug candidate for COVID-19.

Amyloidosis is a rare disease.This paper reports a case of localized secondary hypopharyngeal amyloidosis presenting with pulmonary tuberculosis as the initial symptom.The patient lacked specific clinical manifestations and primarily exhibited symptoms such as cough,sputum production,acid reflux,belching,and abdominal pain.Chest CT indicated bronchiectasis with infection and pulmonary tuberculosis.Digestive endoscopy revealed a white mucosal elevation at the right pyriform sinus of the hypopharynx.Pathological diagnosis confirmed amyloid deposits in the hypopharyngeal mucosal tissue.The patient tested positive for anti-amyloid A antibodies,Congo red staining(+),and periodate Schiff staining(+).Amyloidosis commonly affects the digestive system and may have various etiologies,often presenting with symptoms that overlap with other digestive system diseases,leading to frequent misdiagnosis and missed optimal treatment opportunities.The hypopharynx,a highly folded and narrow chamber that serves as a common passage for the digestive and respiratory tracts,can be effectively evaluated for amyloidosis using digestive endoscopy.

Computer-aided diagnosis (CAD) systems play a very important role in modern medical diagnosis and treatment systems, but their performance is limited by training samples. However, the training samples are affected by factors such as imaging cost, labeling cost and involving patient privacy, resulting in insufficient diversity of training images and difficulty in data obtaining. Therefore, how to efficiently and cost-effectively augment existing medical image datasets has become a research hotspot. In this paper, the research progress on medical image dataset expansion methods is reviewed based on relevant literatures at home and abroad. First, the expansion methods based on geometric transformation and generative adversarial networks are compared and analyzed, and then improvement of the augmentation methods based on generative adversarial networks are emphasized. Finally, some urgent problems in the field of medical image dataset expansion are discussed and the future development trend is prospected.
Humans ; Diagnosis, Computer-Assisted ; Diagnostic Imaging ; Datasets as Topic

Medical image segmentation based on deep learning has become a powerful tool in the field of medical image processing. Due to the special nature of medical images, image segmentation algorithms based on deep learning face problems such as sample imbalance, edge blur, false positive, false negative, etc. In view of these problems, researchers mostly improve the network structure, but rarely improve from the unstructured aspect. The loss function is an important part of the segmentation method based on deep learning. The improvement of the loss function can improve the segmentation effect of the network from the root, and the loss function is independent of the network structure, which can be used in various network models and segmentation tasks in plug and play. Starting from the difficulties in medical image segmentation, this paper first introduces the loss function and improvement strategies to solve the problems of sample imbalance, edge blur, false positive and false negative. Then the difficulties encountered in the improvement of the current loss function are analyzed. Finally, the future research directions are prospected. This paper provides a reference for the reasonable selection, improvement or innovation of loss function, and guides the direction for the follow-up research of loss function.
Algorithms ; Image Processing, Computer-Assisted

It is an urgent demand worldwide to control the coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. The 3-chymotrypsin-like protease (3CL^pro) and papain-like protease (PL^pro) are key targets to discover SARS-CoV-2 inhibitors. After screening 12 Chinese herbal medicines and 125 compounds from licorice, we found that a popular natural product schaftoside inhibited 3CL^pro and PL^pro with IC₅₀ values of 1.73 ± 0.22 and 3.91 ± 0.19 μmol/L, respectively, and inhibited SARS-CoV-2 virus in Vero E6 cells with EC₅₀ of 11.83 ± 3.23 μmol/L. Hydrogen-deuterium exchange mass spectrometry analysis, quantum mechanics/molecular mechanics calculations, together with site-directed mutagenesis indicated the antiviral activities of schaftoside were related with non-covalent interactions with H41, G143 and R188 of 3CL^pro, and K157, E167 and A246 of PL^pro. Moreover, proteomics analysis and cytokine assay revealed that schaftoside also regulated immune response and inflammation of the host cells. The anti-inflammatory activities of schaftoside were confirmed on lipopolysaccharide-induced acute lung injury mice. Schaftoside showed good safety and pharmacokinetic property, and could be a promising drug candidate for the prevention and treatment of COVID-19.

Objective:To retrieve, evaluate and summarize the evidence of perioperative delirium prevention and care in elderly patients with fractures, and provide a basis for standardized prevention, care and management in clinical practice.Methods:The evidence was systematically retrieved from the Guidelines International Network, National Guidelines Library, Institute for Healthcare Optimization, UpToDate, BMJ Best Practice, Joanna Briggs Institute Center for Evidence Based Health Care, Cochrane Library, Yimaitong, CINAHL, Embase, BMJ, PubMed, CNKI , Wanfang, and China Biology Medicine disc (CBMdisc) , including guidelines, evidence summary, systematic reviews, best practice information, and randomized controlled trials (RCT) published up to December 1, 2019.Results:Finally, 15 articles were included, including 2 clinical decision-making, 5 guidelines, 5 systematic reviews, 2 summaries of evidence, and 1 RCT. The best evidence included 11 aspects such as delirium risk factor assessment, assessment tools, assessment timing, and qualifications of assessors, with a total of 25 pieces of evidence.Conclusions:Perioperative delirium in elderly patients with fractures has not yet gained the full attention from healthcare professionals. Medical institutions should establish standardized procedures for the evaluation, prevention, and care of elderly patients with fractures based on evidence-based evidence transformation, improve the health education system for medical staff and patients, formulate corresponding norms, improve the level of delirium care, and improve patients' outcomes.

Heat stroke is the most serious type of heat-related diseases, and the induced multiple organ dysfunction syndrome (MODS) is an important cause of death for heat stroke patients. The cardiovascular system is one of the important targets of heat injury. Studies have reported that heat stress can lead to myocardial inhibition, abnormal heart conduction and blood flow redistribution, thus changing the hemodynamic state, leading to obvious abnormalities in electrocardiogram, echocardiography, myocardial injury biological markers and hemodynamic indicators of patients with heat stroke. In this article, the pathophysiological and histological changes and clinical manifestations of heatstroke-induced myocardial injury are reviewed, aiming to provide references for further understanding and research of myocardial damage caused by hyperthermia.