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/.

Peptide-based radiopharmaceuticals targeting integrin α5β1 show promise for precise tumor diagnosis and treatment. However, current peptide-based radioligands that target α5β1 demonstrate inadequate in vivo performance owing to limited tumor retention. The use of PEGylation to enhance the tumor retention of radiopharmaceuticals by prolonging blood circulation time poses a risk of increased blood toxicity. Therefore, a PEGylation strategy that boosts tumor retention while minimizing blood circulation time is urgently needed. Here, we developed a PEGylation-enabled peptide multidisplay platform (PEGibody) for PR_b, an α5β1 targeting peptide. PEGibody generation involved PEGylation and self-assembly. [⁶⁴Cu]QM-2303 PEGibodies displayed spherical nanoparticles ranging from 100 to 200 nm in diameter. Compared with non-PEGylated radioligands, [⁶⁴Cu]QM-2303 demonstrated enhanced tumor retention time due to increased binding affinity and stability. Importantly, the biodistribution analysis confirmed rapid clearance of [⁶⁴Cu]QM-2303 from the bloodstream. Administration of a single dose of [¹⁷⁷Lu]QM-2303 led to robust antitumor efficacy. Furthermore, [⁶⁴Cu]/[¹⁷⁷Lu]QM-2303 exhibited low hematological and organ toxicity in both healthy and tumor-bearing mice. Therefore, this study presents a PEGibody-based radiotheranostic approach that enhances tumor retention time and provides long-lasting antitumor effects without prolonging blood circulation lifetime. The PEGibody-based radiopharmaceutical [⁶⁴Cu]/[¹⁷⁷Lu]QM-2303 shows great potential for positron emission tomography imaging-guided targeted radionuclide therapy for α5β1-overexpressing tumors.

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/.

Aim To investigate the effect of cumulative non-high density lipoprotein cholesterol/high density lip-oprotein cholesterol(non-HDLC/HDLC)exposure on atherosclerotic cardiovascular disease(ASCVD).Methods A prospective cohort study was conducted.A total of 50 777 employees of Kailuan Group who participated in three physical examinations in 2006-2007,2008-2009 and 2010-2011 were selected as the study subjects.Groups were divided into Q1,Q2,Q3 and Q4 according to the cumulative non-HDLC/HDLC exposure quartiles.Kaplan-Meier curve was used to calculate the cumulative incidence of ASCVD in different cumulative non-HDLC/HDLC groups,and Log-rank test was used to compare the differences among groups.Cox proportional risk model was used to analyze the effect of cumulative non-HDLC/HDLC exposure on ASCVD.Results The average follow-up was(10.19±2.21)years,and 5 003 new cases of ASCVD occurred.The cumulative incidence of ASCVD in groups Q1 to Q4 was 6.49％,8.71％,10.86％and 14.85％,respectively(Log-rank P＜0.01).Multivariate Cox regression analysis showed that compared with group Q1,the HR(95％CI)of ASCVD in groups Q2,Q3 and Q4 were 1.13(1.03～1.24),1.18(1.07～1.29),1.22(1.12～1.34),respectively;the HR(95％CI)of myocardial infarction were 1.15(0.87～1.53),1.44(1.10～1.88),1.67(1.29～2.17),respectively;the HR(95％CI)of revascularization were 1.21(0.99～1.49),1.31(1.07～1.60)and 1.49(1.22～1.81),respectively;the HR(95％CI)of ischemic stroke were 1.17(1.03～1.32),1.17(1.04～1.33)and 1.21(1.06～1.37),respectively;but the above association was not found when heart failure and atrial fibrillation were used as the outcome events.The restricted cubic spline showed that cumulative non-HDLC/HDLC values were line-arly associated with the risk of ASCVD.Conclusion Cumulative non-HDLC/HDLC exposure was positively associated with the risk of ASCVD.

Aim To investigate the effect of cumulative non-high density lipoprotein cholesterol/high density lip-oprotein cholesterol(non-HDLC/HDLC)exposure on atherosclerotic cardiovascular disease(ASCVD).Methods A prospective cohort study was conducted.A total of 50 777 employees of Kailuan Group who participated in three physical examinations in 2006-2007,2008-2009 and 2010-2011 were selected as the study subjects.Groups were divided into Q1,Q2,Q3 and Q4 according to the cumulative non-HDLC/HDLC exposure quartiles.Kaplan-Meier curve was used to calculate the cumulative incidence of ASCVD in different cumulative non-HDLC/HDLC groups,and Log-rank test was used to compare the differences among groups.Cox proportional risk model was used to analyze the effect of cumulative non-HDLC/HDLC exposure on ASCVD.Results The average follow-up was(10.19±2.21)years,and 5 003 new cases of ASCVD occurred.The cumulative incidence of ASCVD in groups Q1 to Q4 was 6.49％,8.71％,10.86％and 14.85％,respectively(Log-rank P＜0.01).Multivariate Cox regression analysis showed that compared with group Q1,the HR(95％CI)of ASCVD in groups Q2,Q3 and Q4 were 1.13(1.03～1.24),1.18(1.07～1.29),1.22(1.12～1.34),respectively;the HR(95％CI)of myocardial infarction were 1.15(0.87～1.53),1.44(1.10～1.88),1.67(1.29～2.17),respectively;the HR(95％CI)of revascularization were 1.21(0.99～1.49),1.31(1.07～1.60)and 1.49(1.22～1.81),respectively;the HR(95％CI)of ischemic stroke were 1.17(1.03～1.32),1.17(1.04～1.33)and 1.21(1.06～1.37),respectively;but the above association was not found when heart failure and atrial fibrillation were used as the outcome events.The restricted cubic spline showed that cumulative non-HDLC/HDLC values were line-arly associated with the risk of ASCVD.Conclusion Cumulative non-HDLC/HDLC exposure was positively associated with the risk of ASCVD.

OBJECTIVE: To investigate the effects of the combined Yiqi Huoxue Jiedu formula (YHJF) on intestinal microbiota in elderly patients with pulmonary-derived sepsis and identify potential microbial targets. METHODS: A prospective randomized double-blind controlled trial was conducted. Elderly patients with pulmonary infection-induced sepsis admitted to the emergency department of Guangdong Provincial Hospital of Traditional Chinese Medicine (TCM), intensive care unit (ICU) of Fangcun Hospital, and ICU of Daxuecheng Hospital, from November 2020 to October 2021 were enrolled and randomized into two groups. Both groups received conventional Western medicine treatment. The observation group additionally received YHJF (composed of 15 g of Panax ginseng, 9 g of Panax notoginseng, and 3 g of Rheum palmatum, dissolved in 50 mL warm water) orally or via nasogastric tube twice daily for 7 days; while the control group received a placebo. Clinical data and fresh fecal samples were collected before treatment and on days 5-7 of treatment. Intestinal microbiota diversity and structure were analyzed via 16S rDNA sequencing and bioinformatics [α diversity, β diversity, and linear discriminant analysis effect size (LEfSe)]. RESULTS: Fifty-five patients were included (29 in the control group, 26 in the observation group). There were no significantly differences in gender, age, comorbidities, and baseline sequential organ failure assessment (SOFA), acute physiology and chronic health evaluation II (APACHE II), acute gastrointestinal injury (AGI) classification score, and gastrointestinal failure (GIF) score between the two groups. Compared to the control group, the observation group showed significantly lower serum procalcitonin, APACHE II score, and greater reduction in GIF score by day 7. Thirty fecal samples were collected pre-treatment (baseline group), 29 post-treatment from the control group, and 26 from the observation group. Gut microbiota α diversity analysis revealed that Simpson index in the observation group and control group were significantly decreased compared to the baseline group [0.75 (0.53, 0.91), 0.81 (0.32, 0.91) vs. 0.88 (0.87, 0.89), both P < 0.05], but there was no significantly difference between the observation group and the control group. There were no significantly differences in Chao1, Ace, and Shannon indices among three groups. β diversity analysis indicated that distinct microbiota structures among three groups (R² = 0.096, P = 0.026). Species difference analysis showed that, at the phylum level, Firmicutes (53.69%), Actinobacteria (16.23%), Proteobacteria (15.39%), and Bacteroidetes (9.57%) dominated, with no significant intergroup differences. At the genus level, 38 taxa showed significant differences. Compared to the control group, the observation group exhibited increased Erysipelatoclostridium (P = 0.014) and Faecalibacterium (P = 0.013), and decreased Bacteroides (P = 0.009), Bilophila (P = 0.005), Eggerthella (P = 0.002), and Collinsella (P = 0.043). LEfSe analysis highlighted Lactobacillus salivarius, Erysipelatoclostridium, Collinsella, Cloacibacillus, and Bacteroides as key discriminators. CONCLUSION YHJF combined with conventional therapy alters intestinal microbiota structure in patients with elderly pulmonary-derived sepsis, with Bacteroides, Erysipelatoclostridium, and Collinsella identified as potential microbial targets.
Humans ; Gastrointestinal Microbiome/drug effects* ; Drugs, Chinese Herbal/therapeutic use* ; Double-Blind Method ; Sepsis/drug therapy* ; Aged ; Prospective Studies ; RNA, Ribosomal, 16S/genetics* ; Male ; Female ; Panax notoginseng ; Rheum

Occupational pneumoconiosis remains the most common occupational disease in China, with occupational mineral dust exposure being its primary causative factor. Although national standards for online monitoring and early warning systems of coal mine dust concentrations have been established, national occupational health standards for rapid and online monitoring of dust concentration and particle size distribution in other industries are still limited. Among dust concentration sensor technologies, the light scattering method is the preferred choice for online dust monitoring owing to its wide measurement range and low cost. The beta-ray absorption method is mature but highly sensitive to humidity. The electrostatic induction method offers high sensitivity, simple structure, and low maintenance costs but exhibits high errors in low-concentration dust monitoring. The tapered element oscillating microbalance method is highly sensitive but costly. Multi-sensor data fusion technology can improve monitoring reliability, however, mature domestic products are not yet available. For monitoring dust particle size distribution, sieving and sedimentation methods are cumbersome. The aerodynamic method shows broad prospects in the online monitoring of respirable dust but has obvious measurement errors for larger dust particles. The use of optical measurement method is limited by dust morphology and is not suitable for monitoring coal dust particle size distribution. The electrical mobility method is primarily applicable to submicron dust. Future research should focus on promoting the application of monitoring technology for respirable dust particle size distribution in online monitoring of industrial dust. By integrating Internet of Things, data mining, and artificial intelligence technologies, along with multi-sensor data fusion and numerical simulation, dust concentration prediction models can be established to achieve accurate dust concentration monitoring and early warning of exceedances. The advancements of technologies will provide scientific support for the assessment of industrial dust hazards and the prevention and control of occupational pneumoconiosis.

Objectives:To investigate the impact of resting heart rate on the risk of all-cause mortality in ultra-high risk atherosclerotic cardiovascular disease(ASCVD)patients. Methods:A total of 3 645 patients with ultra-high risk ASCVD(as defined in the 2023 Chinese Lipid Management Guidelines)were screened from the 2006 to 2020 Kailuan Study cohort,and after excluding 602 patients with missing resting heart rate,3 043 patients were included in the final analysis.Patients were divided into＜68 beats/min group(n=744),68-74 beats/min group(n=786),75-80 beats/min group(n=760),and≥81 beats/min group(n=753)according to the resting heart rate.Cox proportional regression model was used to estimate the hazard ratios(HRs)and 95%CI for all-cause mortality associated with the different resting heart rate groups and every 10 beats/min increase of resting heart rate.The dose-effect relationship of resting heart rate level and all-cause mortality was assessed by a restricted cubic spline regression model.The Kaplan-Meier method was applied to calculate the cumulative all-cause mortality in different groups,and the differences were compared using log-rank test. Results:The median follow-up time was 5.81(3.46,9.64)years,there were 772(25.37%)all-cause deaths during follow up.After adjusting major confounding factors,the results showed that compared with＜68 beats/min group,the risk of all-cause mortality in 75-80 beats/min group and≥81 beats/min group increased by 24%(HR=1.24,95%CI:1.01-1.52,P=0.047)and 47%(HR=1.47,95%CI:1.20-1.81,P＜0.001),respectively;the risk of all-cause mortality in 68-74 beats/min group was similar(HR=1.06,95%CI:0.86-1.31,P=0.625).In addition,an increase of 10 beats/min in resting heart rate was associated with a 13%increase in the risk of all-cause mortality(HR=1.13,95%CI:1.07-1.19,P＜0.001).In stratified analyses,it was found that for every 10 beats/min increase in resting heart rate,women faced a higher risk of all-cause mortality than men,and patients＜65 years old faced a higher risk of all-cause mortality than patients≥65 years old.The restricted cubic spline analysis also showed that resting heart rate was linearly associated with the risk of all-cause mortality(Poverall＜0.001,Pnon-linear=0.933),and the risk increased significantly with resting heart rate＞70 beats/min. Conclusions:Increased resting heart rate is linearly associated with increased risk of all-cause mortality in patients with ultra-high risk ASCVD.The appropriate intervention cut-off point of resting heart rate for ultra-high risk ASCVD patients may be＞75 beats/min.

Objective To explore the application value of simultaneous multi-slice(SMS)technique in diffusion tensor imaging(DTI)for evaluating brain glioma.Methods Thirty-four brain glioma patients were prospectively enrolled,and brain conventional DTI and SMS-DTI were acquired.The subjective scores of image quality,signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were compared between SMS-DTI and conventional DTI,so were the numbers of whole brain fiber bundles,tumor relative fractional anisotropy(rFA)and relative mean diffusivity(rMD)obtained based on SMS-DTI and conventional DTI.Results Among 34 patients,there were 23 cases of high-grade glioma and 11 cases of low-grade glioma.No significant difference of subjective scores of image quality,tumor edge clarity nor magnetic susceptibility artifacts was found between SMS-DTI and conventional DTI(all P＞0.05).SNR and CNR on SMS-DTI were both lower than those on conventional DTI(both P＜0.05).No significant difference of the numbers of whole brain fiber bundles,rFA nor rMD of gliomas with different pathological grades was detected based on SMS-DTI compared with those on conventional DTI(all P＞0.05).Conclusion SMS applicated in DTI for evaluating brain gliomas was able to shorten acquisition time under the condition of ensuring image quality and quantitative analysis accuracy.

Objectives:To investigate the association of trajectories of atherogenic index of plasma(AIP)with the risk of atherosclerotic cardiovascular disease(ASCVD). Methods:A total of 51 831 employees and retirees who participated in Kailuan Group health examination for three consecutive times from 2006 to 2010 were included in this study.AIP was calculated using the log(triglycerides[TG]/high-density lipoprotein-cholesterol[HDL-C])formula.AIP trajectory models were fitted by the SAS Proc Traj program,and according to AIP trajectory,the subjects were divided into low stability group(n=11 114),low to moderate stability group(n=21 647),medium to high stability group(n=13 659),and high stability group(n=5 411).Kaplan-Meier method was used to calculate the cumulative incidence of ASCVD in different groups and compared by log-rank test.Cox proportional risk regression model was used to analyze the effects of different AIP trajectories on ASCVD risk. Results:Finally,51 831 patients were included in the analysis.During a mean follow-up of(10.19±2.22)years,5 142(9.92%)subjects developed ASCVD,4 013(7.74%)subjects died.Cox regression analysis after adjusting for confounding factors showed:compared with the low stability group,the risk of ASCVD increased by 13%(HR=1.13,95%CI:1.04-1.23,P=0.003)and 20%(HR=1.20,95%CI:1.10-1.31,P＜0.001)and 41%(HR=1.41,95%CI:1.27-1.57,P＜0.001)in the low to moderate stability group,moderate to high stability group and high stability group,respectively,and the risk increased gradually(Ptrend＜0.001).Stratified analysis showed that the risk of ASCVD in people aged＜65 years and low-density lipoprotein cholesterol(LDL-C)＜3.4 mmol/L with long-term high levels of AIP was higher than that in people aged≥65 years and LDL-C≥3.4 mmol/L(both Pinteraction＜0.01). Conclusions:In Kailuan Study cohort,those with long-term high levels of AIP had a higher risk of ASCVD,and the risk gradually increased.In addition,we found that the risk of ASCVD in people with long-term high levels of AIP was higher in＜65 years old than in≥65 years old,and the risk of ASCVD in people with LDL-C＜3.4 mmol/L was higher than that in people with LDL-C≥3.4 mmol/L.