ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

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/.

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/.

Objective:To extract and evaluate the relevant evidence to improve the family discharge preparation of premature infants with bronchopulmonary dysplasia, so as to provide evidence-based basis for clinical formulation of scientific and effective discharge plans.Methods:All the evidence on the family discharge readiness of premature infants with bronchopulmonary dysplasia was collected from Chinese and English databases or websites, and the quality of various studies was evaluated. JBI′s evidence grading and recommendation level system (2014 edition) was used to extract and summarize the evidence.Results:A total of 21 articles were included, and 24 pieces of evidence were summarized, which were divided into seven themes: pre-discharge planning, environmental preparedness, parent education and training, support systems, feeding and nutrition, respiratory management, and discharge follow-up.Conclusions:For preterm infants with bronchopulmonary dysplasia, discharge readiness should be improved in terms of standardizing discharge criteria and implementing a discharge plan; improving family care preparation to ensure discharge support; strengthening health management and implementing a personalized plan; and continuing high-quality follow-up to ensure long-term health.

Objective To investigate the regulatory effect of lipocalin 2(LCN2)on epidermal growth factor receptor(EGFR)phosphorylation and its impact on inflammatory damage in human fallopian tube epithelial cells.Methods Human fallopian tube epithelial cells were isolated and a lipopolysaccharide(LPS)intervention was applied to establish an in vitro cell model.The cells were randomly assigned into the following groups:a blank control group(Control),a model group(Model),experimental groups(Model+si-LCN2 or Model+oe-LCN2),and negative control groups(Model+si-NC or Model+oe-NC).Changes in cell viability,apoptosis rates,inflam-matory levels,as well as the expression of EGFR mRNA,LCN2,EGFR,p-EGFR,and the ratio of p-EGFR/EGFR proteins were evaluated.Results Compared to the Model group,the Model+si-LCN2 group exhibited enhanced cell viability,a reduced apoptosis rate,and decreased expression of inflammatory factors(P＜0.05).Immunopre-cipitation analysis confirmed a direct interaction between LCN2 and EGFR.In comparison with the Model group,the Model+oe-LCN2 group demonstrated elevated levels of p-EGFR and the p-EGFR/EGFR ratio(P＜0.05),while no significant change was observed in total EGFR expression(P＞0.05).Conclusion Inhibition of LCN2-mediated EGFR phosphorylation enhances cell viability,reduces apoptosis,and mitigates inflammatory responses,thereby ameliorating LPS-induced inflammatory injury in human fallopian tube epithelial cells.

Cardiovascular disease has become a significant cause of death in cancer patients,partly due to the cardiovascular toxicity of cancer treatments.The referral of cardio-oncology can improve the cardiovascular health of cancer patients,and develop strategies for prevention,management,and treatment of cardiovascular toxicity induced by cancer treatment.This article summarizes the strategies and status in the referral of cardio-oncology,and proposes development suggestions for the referral model of cardio-oncology,in order to improve the awareness of medical staffin implementing referral of cardio-oncology and provide a basis for promoting the development of the referral model of cardio-oncology.

Objective To investigate the regulatory effect of lipocalin 2(LCN2)on epidermal growth factor receptor(EGFR)phosphorylation and its impact on inflammatory damage in human fallopian tube epithelial cells.Methods Human fallopian tube epithelial cells were isolated and a lipopolysaccharide(LPS)intervention was applied to establish an in vitro cell model.The cells were randomly assigned into the following groups:a blank control group(Control),a model group(Model),experimental groups(Model+si-LCN2 or Model+oe-LCN2),and negative control groups(Model+si-NC or Model+oe-NC).Changes in cell viability,apoptosis rates,inflam-matory levels,as well as the expression of EGFR mRNA,LCN2,EGFR,p-EGFR,and the ratio of p-EGFR/EGFR proteins were evaluated.Results Compared to the Model group,the Model+si-LCN2 group exhibited enhanced cell viability,a reduced apoptosis rate,and decreased expression of inflammatory factors(P＜0.05).Immunopre-cipitation analysis confirmed a direct interaction between LCN2 and EGFR.In comparison with the Model group,the Model+oe-LCN2 group demonstrated elevated levels of p-EGFR and the p-EGFR/EGFR ratio(P＜0.05),while no significant change was observed in total EGFR expression(P＞0.05).Conclusion Inhibition of LCN2-mediated EGFR phosphorylation enhances cell viability,reduces apoptosis,and mitigates inflammatory responses,thereby ameliorating LPS-induced inflammatory injury in human fallopian tube epithelial cells.

Objective To survey the awareness and intended adoption of patient-based real-time quality control(PBRTQC)among medical laboratories,thereby providing a basis for subsequent research and promotion efforts.Methods An electronic questionnaire was distributed via the Questionnaire Star system to collect participants' general information,their knowledge,attitudes,and practices regarding PBRTQC,as well as their implementation willingness.Results A total of 161 valid questionnaires were collected.The sur-vey revealed that fewer than 50％of laboratory staff had basic knowledge of PBRTQC,and their confidence in establishing and applying PBRTQC in their own laboratories was low.However,they acknowledged its potential to enhance quality management.Key concerns and support needs for PBRTQC promotion include professional implementation guidelines and policy support,reliable third-party evalu-ations,software and hardware support,and user training.Conclusion The laboratory staff accepted the value of PBRTQC and gener-ally held a positive attitude toward its application.Future efforts should focus on developing standardized guidelines,refining evaluation methods,advancing software and hardware,and enhancing knowledge dissemination,technical training and other actions related to guiding the practical implementation thereby facilitating the wider adoption of PBRTQC.

Cardiovascular disease has become a significant cause of death in cancer patients,partly due to the cardiovascular toxicity of cancer treatments.The referral of cardio-oncology can improve the cardiovascular health of cancer patients,and develop strategies for prevention,management,and treatment of cardiovascular toxicity induced by cancer treatment.This article summarizes the strategies and status in the referral of cardio-oncology,and proposes development suggestions for the referral model of cardio-oncology,in order to improve the awareness of medical staffin implementing referral of cardio-oncology and provide a basis for promoting the development of the referral model of cardio-oncology.