Antibody drug conjugates (ADC) have emerged as a cutting-edge technology in anti-tumor treatment, making significant strides in recent years. ADC couple a highly active small molecule toxin payload to highly specific antibodies through a linker, enabling precise targeting of tumor cells while reducing systemic toxicity, thereby expanding the therapeutic window. However, due to the complexity of ADC molecule design, its efficacy and safety are influenced by various factors. Model-informed drug development (MIDD) is a powerful tool that utilizes various mathematical models for modeling and simulation to conduct quantitative analysis, guiding drug development and decision-making. By integrating multi-faceted data and information using mathematical models, it is possible to gain insights into the complex mechanisms, pharmacokinetics, and pharmacodynamics of ADC, providing unique perspectives for optimizing ADC development processes and clinical translation decisions. This review will introduce the basic concepts of MIDD and ADC and discuss application cases of MIDD in different stages of ADC development, aiming to provide beneficial references for the advancement of ADC.

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

Objective: To analyze the incidence of statutory and keymonitored infectious diseases among school students in Beijing from 2016 to 2020, so as to provide a reference for developing the prevention and control of infectious diseases in schools. Methods: A descriptive statistical analysis was conducted on student cases aged 6-22 years in Beijing from 2016 to 2020 selected from the China Disease Surveillance Information Reporting Management System. Rate comparisons were performed using the 2 test and trend 2 test. Results: From 2016 to 2020, the overall incidence of statutory and keymonitored infectious diseases among students in Beijing showed an upward trend (χ2trend=582.42), the incidence rates of Category B and other infectious diseases exhibited a downward trend (χ2trend=82.71, 18.34), while Category C infectious diseases demonstrated a significant upward trend (χ2trend=911.75) (P<0.01). Among Category B infectious diseases, scarlet fever, bacillary dysentery, tuberculosis, and HIV/AIDS were predominant, with annual average incidence rates of 61.33/100 000, 35.38/100 000, 13.88/100 000, and 3.78/100 000, respectively. Except for HIV/AIDS, the reported incidence rates of other infectious diseases showed a declining trend. Among Category C infectious diseases, influenza, other infectious diarrhea, hand-foot-mouth disease, and mumps were predominant, with annual average incidence rates of 956.13/100 000, 114.39/100 000, 111.37/100 000, and 28.24/100 000, respectively. Influenza showed a significant upward trend (χ2trend=1 508.30), while the other infectious diarrhea, hand-foot-mouth disease, and mumps exhibited a downward trend (χ2trend=13.84, 25.78, 6.13) (P<0.05). Among other infectious diseases, varicella was predominant (χ2trend=17.47, P<0.05). Scarlet fever, influenza, hand-foot-mouth disease, and mumps had higher incidence rates among primary and middle school students; other infectious diarrhea and varicella were more prevalent among high school students; tuberculosis and bacillary dysentery were more common among high school and college students; and HIV/AIDS had higher incidence rates among college and high school students. Conclusion From 2016 to 2020, the incidence of Category B infectious diseases among students in Beijing showed a declining trend, while influenza, a Category C infectious disease, exhibited a significant upward trend.

Objective: To investigate the levels of knowledge and skills in infectious diseases among school doctors and health teachers in Beijing s primary and secondary schools in 2023, and analyze the influencing factors, so as to provide a reference basis for enhancing the professional competencies of school doctors and health teachers. Methods: From October to November 2023, a census method was used to conduct a questionnaire survey among all school doctors and health teachers in 16 districts of Beijing. Chi-square tests and multivariate Logistic regression analysis was used perform statistical analysis. Results: The awareness rate of infectious diseaserelated knowledge among school doctors and health teachers in primary and secondary schools in Beijing in 2023 ranged from 34.44 % to 98.57%, while the behavior formation rate ranged from 65.90% to 98.64%. The proportions of those with literacy in infectious disease knowledge and behavior among school doctors and health teachers were 82.76% and 85.70%, respectively. Multivariate Logistics regression analysis showed that being a full-time employee, having a bachelor s degree or above, and holding a senior professional title were positively correlated with having literacy in infectious disease knowledge ( OR =1.76, 2.57, 1.42 , P <0.01). Compared to medical professionals, those in education and other professions were negatively correlated with having literacy in infectious disease knowledge ( OR =0.37, 0.55, P <0.01). Being a full-time employee, being female, and age were positively correlated with having literacy in infectious disease behavior ( OR =1.66, 2.18, 1.02, P <0.01). Conclusions The level of health literacy for infectious diseases among school doctors in Beijing primary and secondary schools is relatively high. Targeted training on key professional knowledge and skills should be prioritized for individuals with deficiencies in infectious disease prevention and control.

ObjectiveThis paper proposes a novel real-time bedside pulmonary ventilation monitoring method for the diagnosis of chronic obstructive pulmonary disease (COPD), based on electrical impedance tomography (EIT). Four indicators—center of ventilation (CoV), global inhomogeneity index (GI), regional ventilation delay inhomogeneity (RVDI), and the ratio of forced expiratory volume in one second to forced vital capacity (FEV₁/FVC)—are calculated to enable the spatiotemporal assessment of COPD. MethodsA simulation of the respiratory cycles of COPD patients was first conducted, revealing significant differences in certain indicators compared to healthy individuals. The effectiveness of these indicators was then validated through experiments. A total of 93 subjects underwent multiple pulmonary function tests (PFTs) alongside simultaneous EIT measurements. Ventilation heterogeneity under different breathing patterns—including forced exhalation, forced inhalation, and quiet tidal breathing—was compared. EIT images and related indicators were analyzed to distinguish healthy individuals across different age groups from COPD patients. ResultsSimulation results demonstrated significant differences in CoV, GI, FEV₁/FVC, and RVDI between COPD patients and healthy individuals. Experimental findings indicated that, in terms of spatial heterogeneity, the GI values of COPD patients were significantly higher than those of the other two groups, while no significant differences were observed among healthy individuals. Regarding temporal heterogeneity, COPD patients exhibited significantly higher RVDI values than the other groups during both quiet breathing and forced inhalation. Moreover, during forced exhalation, the distribution of FEV₁/FVC values further highlighted the temporal delay heterogeneity of regional lung function in COPD patients, distinguishing them from healthy individuals of various ages. ConclusionEIT technology effectively reveals the spatiotemporal heterogeneity of regional lung function, which holds great promise for the diagnosis and management of COPD.

ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza， and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter， prospective， non-randomized， parallel， controlled trial was conducted from October 2021 to May 2022 in five hospitals， including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness （ILI） cases were collected， and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention， they were assigned to the observation group （108 cases） or the control group （108 cases）. Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine （TCM） symptom score scale for influenza， influenza-related emergency （outpatient） visit rate， influenza hospitalization rate， and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled， with 108 in the observation group and 108 in the control group. Primary outcomes： （1） Incidence of ILI： The incidence was 12.0% （13/108） in the observation group and 23.1% （25/108） in the control group， with the observation group showing a significantly lower incidence （χ²=4.6， P<0.05）. （2） Influenza confirmation rate： 3.7% （4/108） in the observation group and 4.6% （5/108） in the control group， with no statistically significant difference. Secondary outcomes： （1） TCM symptom score scale： after onset， nasal congestion and runny nose scores differed significantly between the two groups （P<0.05）， while other symptoms such as fever， sore throat， and cough showed no significant differences. （2） Influenza-related emergency （outpatient） visit rate： 84.6% （11 cases） in the observation group and 96.0% （24 cases） in the control group， with no significant difference. （3） Time to onset after exposure： The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group， with a statistically significant difference （P<0.05）. ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions， Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.

ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza， and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter， prospective， non-randomized， parallel， controlled trial was conducted from October 2021 to May 2022 in five hospitals， including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness （ILI） cases were collected， and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention， they were assigned to the observation group （108 cases） or the control group （108 cases）. Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine （TCM） symptom score scale for influenza， influenza-related emergency （outpatient） visit rate， influenza hospitalization rate， and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled， with 108 in the observation group and 108 in the control group. Primary outcomes： （1） Incidence of ILI： The incidence was 12.0% （13/108） in the observation group and 23.1% （25/108） in the control group， with the observation group showing a significantly lower incidence （χ²=4.6， P<0.05）. （2） Influenza confirmation rate： 3.7% （4/108） in the observation group and 4.6% （5/108） in the control group， with no statistically significant difference. Secondary outcomes： （1） TCM symptom score scale： after onset， nasal congestion and runny nose scores differed significantly between the two groups （P<0.05）， while other symptoms such as fever， sore throat， and cough showed no significant differences. （2） Influenza-related emergency （outpatient） visit rate： 84.6% （11 cases） in the observation group and 96.0% （24 cases） in the control group， with no significant difference. （3） Time to onset after exposure： The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group， with a statistically significant difference （P<0.05）. ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions， Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.

Radiotherapy (RT) can potentially induce systemic immune responses by initiating immunogenic cell death (ICD) of tumor cells. However, RT-induced antitumor immunologic responses are sporadic and insufficient against cancer metastases. Herein, we construct multifunctional self-sufficient nanoparticles (MARS) with dual-enzyme activity (GOx and peroxidase-like) to trigger radical storms and activate the cascade-amplified systemic immune responses to suppress both local tumors and metastatic relapse. In addition to limiting the Warburg effect to actualize starvation therapy, MARS catalyzes glucose to produce hydrogen peroxide (H₂O₂), which is then used in the Cu⁺-mediated Fenton-like reaction and RT sensitization. RT and chemodynamic therapy produce reactive oxygen species in the form of radical storms, which have a robust ICD impact on mobilizing the immune system. Thus, when MARS is combined with RT, potent systemic antitumor immunity can be generated by activating antigen-presenting cells, promoting dendritic cells maturation, increasing the infiltration of cytotoxic T lymphocytes, and reprogramming the immunosuppressive tumor microenvironment. Furthermore, the synergistic therapy of RT and MARS effectively suppresses local tumor growth, increases mouse longevity, and results in a 90% reduction in lung metastasis and postoperative recurrence. Overall, we provide a viable approach to treating cancer by inducing radical storms and activating cascade-amplified systemic immunity.

Objective:To study the clustered regularly interspaced short palindromic repeats (CRISPR) genotype of Yersinia pestis and its regional distribution characteristics in natural plague focus of Tibet Autonomous Region. Methods:A total of 125 representative Yersinia pestis strains isolated from natural plague focus in Tibet Autonomous Region at different times, regions, hosts and vectors were selected as experimental strains, and the phenol chloroform mixed extraction method was used to extract Yersinia pestis DNA. Three pairs of CRISPR primers (for YPa, YPb, YPc locus) were used to amplify the DNA of the experimental strains, and the CRISPR genotype of Yersinia pestis was determined by sequencing. Results:All 125 strains of Yersinia pestis had three CRISPR locus: YPa, YPb, and YPc. A total of 18 spacer were found, including 8 in YPa loci, 6 in YPb loci, and 4 in YPc loci. Two new types of spacers had been discovered, namely b52 and c14. CRISPR typing revealed 10 genotypes, including G1, G7, G7-b4''', G7-b52, G7-c2 -, G8, G22, G22-a4 -, G22-b4''', and G22-c14, of which 6 were newly discovered genotypes. Among the 125 experimental strains, G7 was the main genotype, accounting for 65.6% (82/125), which was distributed in 6 prefecture level citys and 1 region of Tibet Autonomous Region. Next were G22 and G7-c2 - genetypes, accounting for 14.4% (18/125) and 11.2% (14/125), respectively. G22 gene type was distributed in Nagqu, Changdu, Lhasa citys, and Ngari Prefecture, while G7-c2 - genetype was distributed in Shigatse and Shannan cities. Conclusion:The CRISPR locus of Yersinia pestis in natural plague focus of Tibet Autonomous Region is highly polymorphic, and the Yersinia pestis strains with different genotypes have obvious regional distribution characteristics.

Objective:To evaluate the diagnostic performance of radiomics model based on contrast-enhanced ultrasound(CEUS) in predicting pathological complete response(pCR) after neoadjuvant chemoradiotherapy(nCRT) in patients with locally advanced rectal cancer(LARC).Methods:One hundred and six patients with LARC who underwent total mesorectal excision after nCRT between April 2018 and April 2023 in the First Affiliated Hospital of Guangxi Medical University were retrospectively included, the patients were randomly divided into a training set of 63(14 pCR patients) and a validation set of 43(12 pCR patients) in a 6∶4 ratios. Radiomics features were extracted from the tumors′ region of interest of CEUS images based on PyRadiomics. Intra-class correlation coefficient(ICC), Mann-Whitney U test, and least absolute shrinkage and selection operator(LASSO) algorithms were used to reduce features dimension. Finally, 7 radiomics features relevanted to pCR were selected to construct an ultrasomics model using elastic network regression, based on the R language. A combined model was constructed by jointing clinical feature. The performance of the models was assessed with the area under the ROC curve(AUC). Results:The AUC of the ultrasomics model and the combined model was 0.695(95% CI=0.532-0.859) and 0.726(95% CI=0.584-0.868) respectively in the training set. The AUC of the ultrasomics model and the combined model was 0.763(95% CI=0.625-0.902) and 0.790(95% CI=0.653-0.928) respectively in the validation set. Both univariate and multivariate Logistic regression analyses showed that CA199( P<0.05) and ultrasomics score( P<0.001) could be an independent predictor of pCR after nCRT in patients with LARC. Conclusions:The CEUS-based radiomics scores has certain predictive value for whether LARC patients achieve pCR after nCRT, and may provide a non-invasive imaging biomarker for predicting LARC patients achieve pCR after nCRT.