OBJECTIVE To confirm trigger items for adverse drug reaction （ADR） induced by bevacizumab， to identify and analyze the occurrence of related ADR， and to establish a predictive model for severe adverse reaction （SAR） caused by this drug. METHODS Based on the global trigger tool （GTT） theory， and referencing the GTT White Paper， drug package inserts and relevant literature， trigger items for bevacizumab-related ADR were confirmed using a single-round Delphi method. Utilizing these established items， electronic medical records of relevant patients at Guilin People’s Hospital from January 2020 to September 2024 were actively screened via the China Hospital Pharmacovigilance System. Pharmacists then identified and tallied the occurrence of bevacizumab-induced ADR. Data from patients with any positive trigger item served as the study subjects （divided into training and test sets at a ratio of 7∶3）， candidate feature variables were selected from 39 related variables using the Boruta algorithm， and the multivariable Logistic regression analysis was performed with the occurrence of SAR as the dependent variable. Based on these candidate features， Logistic Regression， Extreme Gradient Boosting， Light Gradient Boosting Machine， Random Forest， and Categorical Boosting models were constructed. Model performance was evaluated using metrics including the area under the curve （AUC） of receiver operating characteristic curve and recall rate. The Shapley Additive exPlanations （SHAP） method was applied to analyze and interpret the contribution of each variable. A nomogram was constructed based on the optimal model. RESULTS A total of 38 trigger items for active monitoring of bevacizumab-related ADR were determined， comprising 17 laboratory indicators， 13 clinical manifestations， and 8 intervention measures. In total， 483 patients with positive trigger items were included， and 318 patients with bevacizumab-induced ADR were identified， including 83 SARs. The positive predictive values for the trigger items and cases were 43.57% （708/1 625） and 63.84% （318/483）， respectively. Bevacizumab-induced ADR involved 7 systems/organs， with the hematological system being the most frequently involved （64.15%）. The Boruta algorithm selected 7 vari ables： serum potassium， hematocrit， albumin-to-globulin ratio， prealbumin， hypertension history， age and red blood cell count. Multivariable Logistic regression showed that elevated serum potassium levels were associated with a decreased risk of bevacizumab-induced SAR （OR＝0.234， P ＝0.002）， while a history of hypertension （OR＝2.642， P ＝0.006） and increased age （OR＝1.040， P ＝0.025） were associated with an increased risk. The Logistic Regression model demonstrated superior performance with higher AUC， F1 score and recall rate （0.761， 0.447， 0.607）， compared to other models. SHAP evaluation results indicated that variables such as serum potassium， hematocrit， and age ranked highest in importance. CONCLUSIONS Totally 38 trigger entries have been successfully identified for active screening of bevacizumab-related ADR. Elevated serum potassium levels are a protective factor against bevacizumab-induced SAR， whereas the hypertension history and increased age are risk factors. The Logistic Regression model is the optimal predictive model.

Objective:To investigate the diagnostic efficacy of time-dependent diffusion MRI (t d-dMRI)-derived microstructural parameters for clinically significant prostate cancer (csPCa) and their associations with the pathological grade of prostate cancer(PCa) based on the International Society of Urological Pathology (ISUP) grades. Methods:This cross-sectional study prospectively enrolled 196 patients suspected of PCa from March 2023 to March 2024 at the First Affiliated Hospital, Sun Yat-Sen University. All patients underwent multiparametric MRI and t d-dMRI to obtain microstructural parameters, including cell diameter (d), intracellular volume fraction (f in), extracellular diffusion coefficient (D ex), cellularity, and apparent diffusion coefficient (ADC) value at oscillation frequencies of 33 Hz, 17 Hz, 0 Hz (ADC 33, ADC 17, and ADC 0). Pathologically, 95 cases were classified as csPCa (ISUP 2-5), and the rest 101 cases were classified as non-csPCa (benign or ISUP 1). Comparison of these microstructural metrics was made between csPCa and non-csPCa groups by independent t-tests or Mann-Whitney U tests, and multivariable logistic regression was used to identify independent predictors. A combined diagnostic model was then constructed based on the independent predictors. The receiver operating characteristic curve analysis was used to evaluate the diagnostic performance. Finally, in PCa, the correlation between microstructural parameters and ISUP grades was investigated by Spearman correlation. Results:The t d-dMRI measurements, including d, f in, cellularity, ADC 33,ADC 17 and ADC 0, were significantly different between csPCa and non-csPCa groups (All P<0.05). But D ex was not significantly different between the two groups ( Z=-1.27, P=0.204). The area under the receiver operating characteristic curve (AUC) for diagnosing csPCa were 0.701 (95% CI 0.628-0.775) for d, 0.869 (95% CI 0.819-0.920) for f in, 0.884 (95% CI 0.835-0.932) for cellularity, 0.777 (95% CI 0.712-0.842) for ADC 33, 0.852 (95% CI 0.799-0.905) for ADC 17, and 0.840 (95% CI 0.786-0.894) for ADC 0. Cellularity ( OR=6.142, 95% CI 2.920-12.929, P<0.001) and ADC 17 ( OR=0.108, 95% CI 0.027-0.429, P=0.002) were identified as the independent predictors, and their combined model achieved an AUC of 0.896 (95% CI 0.852-0.941). In PCa f in and cellularity were positively correlated with ISUP grades ( r=0.490 and 0.397, P<0.001), while ADC 33, ADC 17, and ADC 0 were negatively correlated with ISUP grades ( r=-0.198, -0.345, -0.360; P=0.041,<0.001,<0.001). d and D ex were not correlated with ISUP grades ( P>0.05). Conclusion:t d-dMRI based microstructural mapping correlates with ISUP grades of PCa and may be useful for the differential diagnosis of csPCa.

Radiation prevention and treatment drugs are a rapidly developing field.Radiation prevention and treatment drugs can be roughly divided into four categories:chemical synthetic drugs,biological products,natural plant extracts and traditional Chinese medicine compounds,which are widely used in medical,scientific research and other fields.This paper reviews the classification of radiation prevention and treatment drugs,which can be roughly divided into four categories:chemical synthetic drugs,biological products,natural plant extracts and traditional Chinese medicine compounds.At the same time,its mechanism of action and clinical application are elaborated in detail,and the risk assessment is carried out from the aspects of effectiveness,safety and drug interaction.Finally,the risk reduction strategies are summarized from the aspects of clinical medication specification and monitoring,continuous drug safety research,improvement of emergency reserve and support capacity and construction of full-cycle regulatory system,so as to provide reference for the rational application and further research of radiation prevention and treatment drugs.

Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Objective:To investigate the diagnostic efficacy of time-dependent diffusion MRI (t d-dMRI)-derived microstructural parameters for clinically significant prostate cancer (csPCa) and their associations with the pathological grade of prostate cancer(PCa) based on the International Society of Urological Pathology (ISUP) grades. Methods:This cross-sectional study prospectively enrolled 196 patients suspected of PCa from March 2023 to March 2024 at the First Affiliated Hospital, Sun Yat-Sen University. All patients underwent multiparametric MRI and t d-dMRI to obtain microstructural parameters, including cell diameter (d), intracellular volume fraction (f in), extracellular diffusion coefficient (D ex), cellularity, and apparent diffusion coefficient (ADC) value at oscillation frequencies of 33 Hz, 17 Hz, 0 Hz (ADC 33, ADC 17, and ADC 0). Pathologically, 95 cases were classified as csPCa (ISUP 2-5), and the rest 101 cases were classified as non-csPCa (benign or ISUP 1). Comparison of these microstructural metrics was made between csPCa and non-csPCa groups by independent t-tests or Mann-Whitney U tests, and multivariable logistic regression was used to identify independent predictors. A combined diagnostic model was then constructed based on the independent predictors. The receiver operating characteristic curve analysis was used to evaluate the diagnostic performance. Finally, in PCa, the correlation between microstructural parameters and ISUP grades was investigated by Spearman correlation. Results:The t d-dMRI measurements, including d, f in, cellularity, ADC 33,ADC 17 and ADC 0, were significantly different between csPCa and non-csPCa groups (All P<0.05). But D ex was not significantly different between the two groups ( Z=-1.27, P=0.204). The area under the receiver operating characteristic curve (AUC) for diagnosing csPCa were 0.701 (95% CI 0.628-0.775) for d, 0.869 (95% CI 0.819-0.920) for f in, 0.884 (95% CI 0.835-0.932) for cellularity, 0.777 (95% CI 0.712-0.842) for ADC 33, 0.852 (95% CI 0.799-0.905) for ADC 17, and 0.840 (95% CI 0.786-0.894) for ADC 0. Cellularity ( OR=6.142, 95% CI 2.920-12.929, P<0.001) and ADC 17 ( OR=0.108, 95% CI 0.027-0.429, P=0.002) were identified as the independent predictors, and their combined model achieved an AUC of 0.896 (95% CI 0.852-0.941). In PCa f in and cellularity were positively correlated with ISUP grades ( r=0.490 and 0.397, P<0.001), while ADC 33, ADC 17, and ADC 0 were negatively correlated with ISUP grades ( r=-0.198, -0.345, -0.360; P=0.041,<0.001,<0.001). d and D ex were not correlated with ISUP grades ( P>0.05). Conclusion:t d-dMRI based microstructural mapping correlates with ISUP grades of PCa and may be useful for the differential diagnosis of csPCa.

Objective To observe the value of spectral CT material separation technology for diagnosing traumatic bone marrow edema in limbs.Methods Totally 51 patients with limb traumatic bone marrow edema were retrospectively enrolled and divided into young group(n=26,18-43 years)and middle-aged group(n=25,46-74 years).Taken MRI as reference standard,the efficacy of spectral CT Water-hydroxyapatite(HAP)image for diagnosing bone marrow edema in trauma area was analyzed,and the Water-HAP density values were compared between groups.Results No significant difference of diagnosing bone marrow edema was found between spectral CT and MRI(x2=0.201,P=0.654),and the consistency was high(Kappa=0.774).Water-HAP density value in bone marrow edema area was higher than that in non bone marrow edema area(t=24.634,P＜0.05),and no significant difference of Water-HAP density values in bone marrow edema area nor non bone marrow edema area was found between young group and middle-aged group(both P＞0.05).Conclusion Spectral CT material separation technology was helpful for diagnosing traumatic bone marrow edema in limbs.

The medical mask,which is used as an important tool of preventing the spread of respiratory diseases,can effectively block the transmission of biological aerosols.The detection for the filtration efficiency of bacteria in medical mask is particular importance.The Andersen sampler,is one kind of device that samples microbial aerosols,is widely used in the inspection for the filtration efficiency for bacteria in medical masks.It mainly consists of six impactors with different pore sizes.It simulates the deposition process of the most of particles at different positions in respiratory system through the bacterial particles in biological aerosols impact respectively the surface of petri dishes with agar under different pore sizes.This paper explored the development background,structure and sampling principle,operation and counting procedures of the Andersen sampler,as well as its application and importance in the inspection for the filtration efficiency for bacteria in medical mask.

Objective:To verify the performance of MAGLUMI 4000 fully automatic chemiluminescence immunoassay analyzer in measuring special sequence of β-Collagen(β-CTx).Methods:Referring to a series of standards included WS/T 492-2016"Verification of performance for precision and trueness of quantitative measurements in clinical laboratories"and CNAS-GL037 2019"Guidance on the verification of quantitative measurement procedures used in the clinical chemistry",the precision,trueness,and linear interval of MAGLUMI 4000 fully automatic chemiluminescence immunoassay analyzer were verified in measuring β-CTx.Results:The intra batch precisions(repeatability)of MAGLUMI 4000 fully automatic chemiluminescence immunoassay analyzer were respectively 3.22%and 3.49%in measuring serum β-CTx samples with low and high values.The intermediate precisions(precision within laboratory)were respectively 4.35%and 3.29%,both of which met the requirements of laboratory.The results of trueness verification showed that the bias of samples with low concentration was-2.4%,and the bias of samples with high concentration was-2.1%.The expected values of the standards with low and high values were all between the corresponding up and low validation limits of them,which met the judgment criteria.The linear interval was 0.03-6.00 ng/mL,which was within the linear interval,and it can meet the requirements of manufacturer′s claim.Conclusion:The precision,trueness and linear interval of MAGLUMI 4000 fully automatic chemiluminescence immunoassay analyzer all passed the verification in measuring β-CTx,which indicates the performance of the project can meet the quality specifications.

AIM To study the chemical constituents from Tylophora ovata(Lindl.)Hook.ex Steud.and their antibacterial activities.METHODS Ethanol extract was isolated and purified by MCI,silica gel,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by spectral data.The inhibitory activities of each compound against Phomopsis sp.were determined by mycelial growth rate method.RESULTS Twenty-six compounds were identified as paeonol(1),stigmast-4-en-3-one(2),ergosta-4,6,8(14),22-tetraen-3-one(3),2,4-methoxyphenol(4),1,2,4-trimethoxybenzene(5),3-methoxyphenol(6),3,4-dimethoxyacetophenone(7),5α,8α-epidioxy-ergosta-6,22(E)-diene-3β-ol(8),kaempferol 3-O-β-D-galactopyranoside(9),glaucogenind C(10),glaucoge-nin A 3-O-β-D-cymaropyranoside(11),dibutyl phthalate(12),cynatratoside A(13),hirundigoside C(14),sublanceoside B2(15),cynanoside A(16),dipentyl phthalate(17),5-hydroxymethyl-2-furancarboxaldehyde(18),bis-(2-ethyl)hexylphthalate(19),p-hydroxybenzoic acid(20),syringic acid(21),β-hydroxypropiovanillone(22),3-hydroxy-l-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone(23),(+)-syringare sinol(24),(-)-syringare sinol(25),(+)-medioresinol(26).IC50 value of compound 12 was 37.27 μg/mL.CONCLUSION Compounds 1-26 are isolated from this plant for the first time.Compound 12 has inhibitory activity against Phomopsis sp.

Aim To investigate the effect of linarin on improving cognitive behavior of APP/PS1 mice,and to explore the therapeutic effect of linarin on A β deposi-tion and neuroinflammation and its correlation.Meth-ods APP/PS1 transgenic mice were randomly divid-ed into the model group,high-dose group,medium-dose group,low-dose group and positive control group.C57BL/6J mice were set as the normal group.Morris water maze was used to evaluate the learning and mem-ory abilities of mice.TUNEL staining was used to de-tect the apoptosis of neurons in the CA1 region of mice.IHC was used to detect the expression levels of Aβ42 and GFAP.Western blot was used to detect the expression levels of BACE1 and PS-1.Results Com-pared with the normal group,mice of the model group showed lower NCP,shorter target quadrant travel,less target quadrant residence time percentage(all P＜0.01),higher apoptosis rate of neurons in the CA1 re-gion(P＜0.01),significantly higher protein expres-sion levels of A β42 and GFAP(all P＜0.01),and significantly higher protein expression levels of BACE1 and PS-1(all P＜0.01).Compared with the model group,the medium-dose group,high-dose group and positive control group showed higher NCP,longer tar-get quadrant travel,more target quadrant residence time percentage(all P＜0.05),lower apoptosis rate of neurons in the CA1 region(P＜0.01),significantly lower protein expression levels of A β42 and GFAP(all P＜0.01),and significantly lower protein expression levels of BACE1 and PS-1(all P＜0.01).Conclu-sions Linarin can inhibit two key enzymes to reduce the decomposition of APP and the generation of A β42,thereby inhibiting the activation of astrocytes,allevia-ting neuroinflammation,improving the core pathologi-cal features of AD,and thus significantly improving learning and memory impairment in APP/PS1 mice.