ObjectiveTo analyze the infection characteristics of human respiratory syncytial virus (HRSV) among children hospitalized with acute lower respiratory tract infection (ALRTI) in a specialized pediatric hospital in Shanghai, so as to provide evidence-based support for optimizing the prevention and control strategies and clinical diagnosis and treatment of respiratory tract infections in children in this region. MethodsA retrospective analysis was performed to the clinical and etiological data of 29 260 children hospitalized for ALRTI in Shanghai Children’s Hospital from January 2021 to December 2024. HRSV and 12 other common respiratory pathogens were detected with multiplex polymerase chain reaction (PCR) and capillary electrophoresis. Demographic and clinical data were collected for statistical analyses. A total of2 412 cases with positive HRSV were divided into the severe group and the non-severe group. Clinical characteristics between the two groups were compared using the Mann-Whitney U test and the chi- square (χ²) test. Additionally, the related influencing factors of severe HRSV infection were explored. ResultsThe overall positivity rate of HRSV from 2021 to 2024 was 8.24% (2 412/29 260), with statistically significant differences observed across the four years (χ²=389.42, P<0.001). The highest positivity rate was in 2021 (14.76%), with a high prevalence throughout the year. In 2022, when non-pharmaceutical interventions (NPIs) were implemented, the HRSV positivity rate was the lowest (4.93%), with a winter-dominant epidemic pattern. In 2023, after the NPIs were lifted, the HRSV positivity rate showed a slight rebound (8.14%), presenting a double-peak pattern. In 2024, the HRSV positivity rate slightly decreased compared to that in 2023 (6.29%), exhibiting a winter and spring-dominant epidemic pattern. Among the hospitalized children with ALRTI, the HRSV positivity rate in males (8.85%) was higher than that in females (7.51%), and the difference was statistically significant (χ²=17.33, P<0.001). Age distribution showed that 82.26% (1 984/2 412) of HRSV infections occurred in children aged 3 years old and below. Besides, as age increased, the infection rate of HRSV showed a gradually decreasing trend (P<0.001). Among the 2 412 children with HRSV infection, the proportion of severe cases was 22.31% (538/2 412), while the non-severe cases accounted for 77.69% (1 874/2 412). Compared with non-severe cases, severe cases were more frequently presented with high fever, longer duration of wheezing, as well as higher rates of underlying diseases or co-infection with Mycoplasma pneumoniae (P<0.001). ConclusionThe prevalence intensity of HRSV varied yearly from 2021 to 2024. After the removal of NPIs in 2023, a slight rebound with a double-peak epidemic pattern was observed. HRSV remained a common pathogen in children hospitalized for ARLTI, and children aged 3 years old and below constituted the highest proportion for infection. Compared with non-severe cases, those with severe HRSV infections were more prone to presenting with high fever and a longer duration of wheezing. Children with positive HRSV who had underlying diseases or co-infection with Mycoplasma pneumonia were more likely to develop severe conditions.

OBJECTIVE To introduce the development of an intelligent prescription review decision-support system for anti-tumor drugs and assess its clinical application outcomes. METHODS Relevant data sources， including national and local pharmaceutical administration policies， clinical practice guidelines/consensus， hospital information systems data， and genetic testing results， were integrated. Adhering to the principles of structure， standardization and dynamic updating， a knowledge base covering chemotherapeutic， targeted and immunotherapeutic agents was constructed using a dual-dimensional modeling approach that combined “drug attributes” and “clinical contexts”. This knowledge base was then embedded into the hospital’s electronic medical order system to establish the prescription review decision-support system. The application and performance of the system were evaluated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS A knowledge base containing 18 318 prescription review rules for anti-tumor drugs was constructed， and a closed-loop prescription review system was successfully established， encompassing pre-prescription real-time intervention， in-process interactive review， and post-prescription evaluation and analysis. From 2021 to 2024， the system generated a total of 57 879 alerts for prescriptions of five typical categories of anti-tumor drugs. For platinum-containing prescriptions， 22 577 alerts were generated， with Cisplatin for injection （lyophilized） being the most frequently alerted drug （13 445 alerts）， and “ototoxicity risk due to combined use” alerts remained high （7 682 alerts）. For methotrexate-containing prescriptions， 3 721 alerts were recorded， primarily related to “precaution-related issues” （76.4%， 2 843/3 721）. For doxorubicin-containing prescriptions， 17 301 alerts were triggered， primarily related to “dosage and administration” （14 315 alerts）. For human epidermal growth factor receptor 2-targeted agents-containing prescriptions， 1 007 alerts were issued， mostly related to “reimbursement restrictions” （956 alerts）. For programmed death-1/programmed death-ligand 1 inhibitors-containing prescriptions， the alerts increased year by year， totaling 13 273 alerts， primarily related to “inappropriate indication” （9 118 alerts）. Over the 4 years， the physician response rates to system alerts were 21.4%， 27.1%， 33.5% and 51.6%， respectively. CONCLUSIONS An intelligent decision-support system for anti-tumor drug prescription review， encompassing a closed-loop process of “real-time pre-event intervention， interactive in-event prescription review， post-event evaluation and analysis”， has been successfully constructed and implemented throughout the entire workflow. There is a discernible trend in this hospital， where the focus on monitoring anti-tumor drugs is shifting towards immunotherapy drugs. Additionally， the acceptance rate of physicians regarding prescription review opinions has been steadily increasing year by year.

Objective To identify factors affecting and key environmental factors of the Oncomelania hupensis snail density in the Yangtze River Delta region using machine learning methods. Methods Administrative village-level O. hupensis snail survey data in the Yangtze River Delta (including Shanghai Municipality, Jiangsu Province, Zhejiang Province and Anhui Province) from 2011 to 2021 were retrieved from the Information Management System for Parasitic Disease Control of Chinese Center for Disease Control and Prevention. Environmental factor data were captured from the Google Earth Engine platform, including elevation, slope, terrain, normalized difference vegetation index (NDVI), vegetation type, soil type, total petroleum hydrocarbon (TPH), ammonium nitrogen, inorganic nitrogen, dissolved oxygen, pH of water, chemical oxygen demand (COD) and inorganic phosphorus, and climatic factor data in the study region were retrieved from the Copernicus Climate Data Store, including annual precipitation, aridity index and annual mean temperature (AMT). O. hupensis snail survey data in the Yangtze River Delta region from 2011 to 2021 were randomly divided into a training set (70%) and a test set (30%), and five machine learning models were selected for machine learning model construction and comparative analysis of the O. hupensis snail density using the software R 4.3.0, including random forest (RF), eXtreme gradient boosting (XGBoost), support vector machine (SVM), gradient boosting machine (GBM) and neural network (NN). The XGBoost model was employed to construct a predictive model for the O. hupensis snail density, and the impact of each environmental factor on O. hupensis snail distribution was quantified. The SHapley Additive exPlanations (SHAPs) values were calculated to estimate the average contribution of each variable to the model prediction, and the core environmental factors affecting the O. hupensis snail population density were screened. Results Among the five machine learning models, the XGBoost model exhibited the optimal comprehensive performance, with the coefficient of determination (R²) of 0.855, mean squared error (MSE) of 0.188, root mean squared error (RMSE) of 0.434 and mean absolute error (MAE) of 0.155, respectively. Analysis of factors affecting the O. hupensis snail density with the XGBoost model showed that among the 16 environmental factors, the top four high-impact factors ranked by SHAPs values included annual precipitation, elevation, aridity index and NDVI, with cumulative SHAPs contributions of 75%, which was higher than that of other environmental factors. If NDVI was higher than 0.6, the O. hupensis snail density increased with NDVI and peaked if NDVI was 0.8 (1.60 snails/0.1 m²). The O. hupensis snail density increased with elevation if the elevation ranged from 14 to 40 m, and slowly rose if the annual precipitation ranged from 900 to 1 300 mm, and then increased rapidly to the peak (1.52 snails/0.1 m²) if the annual precipitation ranged from 1 300 to 1 500 mm. In addition, the O. hupensis snail density increased rapidly to the maximum (1.60 snails/0.1 m²) if the aridity index ranged from 0.8 to 1.1, and decreased gradually if the aridity index exceeded 1.1. Conclusions The XGBoost model shows excellent performance in prediction of the O. hupensis snail density and identification of key environmental factors in the Yangtze River Delta region. Annual precipitation, elevation, aridity index and NDVI are key environmental factors affecting the distribution and density of O. hupensis snails in the Yangtze River Delta region.

Objective To examine the impact of extreme temperature and drought stress on the survival of Bulinus globosus, so as to provide the theoretical evidence for the genomic research of Bulinus in absence of reference genes. Methods B. globosus snail samples were collected from Kiwani Shehia in Pemba Island, Zanzibar, Tanzania, and offspring snails were obtained through laboratory breeding and reproduction. A total of 120 10-week-old B. globosus snails from the same generation were selected and randomly assigned into four groups, including the high-temperature drought (HD) group, normal temperature drought (D) group, low-temperature drought (LD) group, and the control (C) group, of 30 snails in each group. Snails in HD, D, and LD groups were placed in beakers containing dry soil at the bottom and subsequently housed in climate chambers at 35, 26 ℃, and 10 ℃, respectively, while snails in Group C were maintained in 500 mL petri dishes containing dechlorinated tap water at 26 ℃. Following 3 days of breeding, living snails in each group were collected, and soft tissues were dissected and isolated. Total RNA was extracted from snail soft tissues for library construction, followed by high-throughput sequencing on the Illumina HiSeq 4000 sequencing system. De novo transcriptome assembly was performed using the Trinity software, and the longest transcripts were selected as unigenes. Gene functional annotations of unigenes were conducted using the Diamond software against Gene Ontology (GO) knowledgebase, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, NCBI non-redundant (NR) protein sequences database, Protein Family (Pfam) database, and UniProtKB/Swiss-Prot (Swiss-Prot) knowledgebase. GO and KEGG enrichment analyses of differentially expressed genes (DEGs) were performed using the topGO and clusterProfiler software, respectively. In addition, four relevant genes were selected for validation using a real-time quantitative PCR (qRT-PCR) assay to verify the reliability of transcriptome sequencing results. Results Following 3 days of breeding, there were 7, 20, 28, and 30 survival B. globosus snails in HD, LD, D, and C groups, with corresponding survival rates of 23.33% (7/30), 66.67% (20/30), 93.33% (28/30), and 100.00% (30/30), respectively (χ² = 52.72, P < 0.001). De novo transcriptome assembly generated 176 942 unigenes, with annotation rates of 0.98%, 13.49%, 26.46%, 12.48%, and 14.39% against GO knowledgebase, KEGG pathway database, NR protein sequences database, Pfam database, and Swiss-Prot knowledgebase, respectively. There were 33 up-regulated and 72 down-regulated genes in Group D, 483 up-regulated and 815 down-regulated genes in Group HD, and 245 up-regulated and 172 down-regulated genes in Group LD relative to in Group C. Following removal of overlapping genes across groups and unmatched genes, 11 candidate genes were identified. GO and KEGG analyses revealed 3 heat shock protein (HSP)-related DEGs in these 11 candidate genes, which were annotated as HSP12.2, HSP70, and HSP20 genes and were all significantly up-regulated in each treatment group. Three immune and nervous system-related DEGs were identified, and were all significantly down-regulated in each treatment group, which were involved in the neural cell adhesion molecule L1-like protein pathway, fibrinogen binding protein pathway, and leukocyte elastase inhibitor-like protein pathway. qRT-PCR assay quantified that the expression trends of four genes related to temperature and drought stress across different treatment groups were highly consistent with transcriptome sequencing data. Conclusion The survival rate of B. globosus significantly reduces under combined stresses of extreme temperature and drought, possibly due to an imbalance in its cellular homeostasis regulatory system.

Based on review of global and Chinese schistosomiasis control progress and the evolution of control strategies, this article focuses on Chinese practical experiences of schistosomiasis control and systematically summarizes five key determinants for schistosomiasis transmission risk, including source of infections, intermediate host snails, high-risk populations, natural environments, and social factors. To address these risks and challenges associated with these determinants, the article reviews the advances in techniques for assessment of schistosomiasis transmission risk and their applications, including conventional risk assessment approaches, mathematical model-based tools for prediction of schistosomiasis transmission risk, and indicator-systembased techniques for assessment of schistosomiasis transmission risk. This review underscores the essential role of interdisciplinary integration and dynamic management in precision schistosomiasis control and recommends the intensification of verification of field adaptation and dynamic updates of indicator systems to promote the widespread application of assessment tools across diverse regions and contexts, so as to provide strategic guidance and methodological support to achieve the target for elimination of schistosomiasis across China in 2030.

ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.

ObjectiveTo investigate the mechanism by which Gegen Qinliantang（GQT） improves skeletal muscle insulin resistance. MethodsThe db/m mice were used as the normal group， while db/db mice were assigned to a model group， low-dose （3.12 g·kg^-1）， medium-dose （6.24 g·kg^-1）， and high-dose （12.48 g·kg^-1） GQT groups， and a Western medicine group （semaglutide， 0.045 mg·kg^-1），n=6 in each group. All groups received corresponding interventions. Intraperitoneal glucose tolerance test （IPGTT）， intraperitoneal insulin tolerance test （IPITT）， and hematoxylin-eosin （HE） staining were used to evaluate insulin resistance and therapeutic efficacy. Serum lipid levels were measured using an automatic biochemical analyzer， and apoptosis in skeletal muscle was assessed via TUNEL assay. Transcriptome sequencing combined with gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses was performed to identify differentially expressed genes （DEGs）. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to validate gene expression. Molecular docking was applied to evaluate the binding patterns between active components of GQT and key regulatory genes to elucidate pharmacological mechanisms. ResultsCompared with the model group， the medium-dose and high-dose GQT groups showed significantly reduced fasting blood glucose （FBG） levels （P<0.01）. Triglycerides （TG）， total cholesterol （TC）， and low-density lipoprotein cholesterol （LDL-C） were markedly decreased （P<0.01）， while high-density lipoprotein cholesterol （HDL-C） was significantly increased （P<0.01）. IPGTT， IPITT， and HE staining demonstrated that GQT enhanced insulin sensitivity and restored skeletal muscle morphology. GQT also alleviated apoptosis in skeletal muscle tissue. Transcriptome analysis revealed that GQT primarily affected biological processes such as oxidative phosphorylation， metabolic pathways， cellular processes， and protein binding. Real-time PCR results showed that CBR2， CDK6， F830016B08Rik， IL-1β， Rab27b， and COLEC12 were key regulatory genes. Molecular docking demonstrated that CBR2， IL-1β， Rab27b， and COLEC12 formed stable binding with the main active components of GQT. The therapeutic effects of high- and medium-dose GQT were comparable to those of the semaglutide group. ConclusionGQT improves skeletal muscle insulin resistance， potentially by regulating apoptosis as part of its underlying biological mechanism.

Objective To explore the effects of CYP2C19, CYP2C9 and CYP3A5 genotypes on the plasma concentration of voriconazole in children. Methods Collected blood samples from 50 hospitalized children with invasive fungal infections who received intravenous voriconazole from January 2020 to December 2020. High performance liquid chromatography was used to detect the blood trough concentration of voriconazole, and the time-of-flight mass spectrometry detection system was used to detect the genotypes of CYP2C19, CYP2C9 and CYP3A5, and the effects of children’s genotyping on the plasma concentration, efficacy and adverse reactions of voriconazole were analyzed. Results The total effective rate of 50 children with IFI was 84% （42/50 cases） after voriconazole treatment. The incidence of adverse reactions was 20% （10/50 cases）. The measured plasma concentration of voriconazole ranged from 0.56~7.62 μg/ml. Combined with the different mutation types of CYP2C19 gene loci, three metabolic activities were produced: fast, medium and slow, and the test results showed that there were 16 cases of fast metabolism, 27 cases of intermediate metabolism and 7 cases of slow metabolism. There was a significant difference in plasma concentrations among the three groups （F=15.359, P<0.001）, and the drug concentrations in the fast metabolic group were significantly lower than those in the intermediate metabolic and slow metabolic groups. The mutations of CYP2C9 and CYP3A5 had no significant effect on the plasma concentrations of the drugs, which were （F=2.213, P=0.086 and F=0.757, P=0.475）. Conclusion Voriconazole had significant efficacy in the treatment of invasive fungal infections in children, and the adverse reactions were mild. CYP2C19 genotype was significantly related to the rate of drug metabolism and was an important factor affecting blood drug concentration, the detection of drug concentration and genotype of voriconazole was helpful to adjust the effective drug dose clinically and would achieve more scientific and individualized treatment.

ObjectiveTo explore the potential mechanism of moxibustion at Guanyuan （CV 4） in delaying skin photoaging. MethodsThirty-two male Wistar rats were randomly divided into four groups， namely blank group， model group， vitamin E group， and moxibustion group， with 8 rats in each group. Except for the blank group， dorsal skin of rats were exposed to ultraviolet （UV） radiation to establish a skin photoaging model. One week after modeling， the moxibustion group received moxibustion at "Guanyuan （CV 4）" once a day， five days per week； the vitamin E group received vitamin E （25 mg/kg·d） once a day by gavage， five days per week； the blank group， model group， and moxibustion group received an equivalent volume of normal saline via gavage； the intervention lasted for 7 weeks. After 7 weeks， dorsal skin tissues were collected to analyze the following indicators， such as skin tissue moisture content， histomorphological changes using hematoxylin-eosin （HE） staining， Collagen Ⅰ and collagen Ⅲ content using ELISA. Malondialdehyde （MDA）， glutathione peroxidase （GSH-Px）， superoxide dismutase （SOD）， hydrogen peroxide （H₂O₂）， and catalase （CAT） activity in skin tissue were dectected. Western Blot was used to determin autophagy-related proteins， including microtubule-associated protein 1A/1B-light chain 3 （LC3）， polyubiquitin-binding protein （p62）， and autophagy-specific gene （Beclin-1）； LC3， p62， and Beclin-1 mRNA expression was detected via qRT-PCR， and autophagosome formation was observed using transmission electron microscopy （TEM）. ResultsHE staining showed that the epidermal structure in the blank group was orderly and evenly thick， while the model group exhibited uneven epidermal thickness. In the moxibustion group， the epidermis was well-structured， smooth， and uniform， with densely arranged dermal layers； the epidermis in the vitamin E group was thicker than that in the model group. Compared with the blank group， the model group exhibited decreased skin moisture content and reduced level of Collagen Ⅰ and collagen Ⅲ， reduced SOD， CAT， and GSH-Px activity in skin tissue， increased H₂O₂ and MDA activity， elevated p62 protein and mRNA expression， reduced LC3 and Beclin-1 protein and mRNA expression （P＜0.05 or P＜0.01）. Compared with the model group， the moxibustion group showed significant improvement in all these indicators （P＜0.05 or P＜0.01）； whereas the vitamin E group did not show a statistically significant difference in Collagen Ⅰ and collagen Ⅲ levels （P＞0.05）. TEM results showed that， compared with the blank group， the model group had atrophic skin cells， extensive mitochondrial vacuolization， and degraded cellular structures； the moxibustion group exhibited crescent- or cup-shaped autophagosomes with a significantly increased number of autophagosomes per unit area， whereas the vitamin E group showed less improvement than the moxibustion group. ConclusionMoxibustion at "Guanyuan （CV 4）" may alleviate skin photoaging by regulating oxidative stress imba-lance， modulating cellular autophagy， and promoting collagen synthesis， thereby slowing the aging process of the skin.

Numerous c-mesenchymal-epithelial transition(c-MET)inhibitors have been reported as potential anticancer agents.However,most fail to enter clinical trials owing to poor efficacy or drug resistance.To date,the scaffold-based chemical space of small-molecule c-MET inhibitors has not been analyzed.In this study,we constructed the largest c-MET dataset,which included 2,278 molecules with different struc-tures,by inhibiting the half maximal inhibitory concentration(IC50)of kinase activity.No significant differences in drug-like properties were observed between active molecules(1,228)and inactive mol-ecules(1,050),including chemical space coverage,physicochemical properties,and absorption,distri-bution,metabolism,excretion,and toxicity(ADMET)profiles.The higher chemical diversity of the active molecules was downscaled using t-distributed stochastic neighbor embedding(t-SNE)high-dimensional data.Further clustering and chemical space networks(CSNs)analyses revealed commonly used scaffolds for c-MET inhibitors,such as M5,M7,and M8.Activity cliffs and structural alerts were used to reveal"dead ends"and"safe bets"for c-MET,as well as dominant structural fragments consisting of pyr-idazinones,triazoles,and pyrazines.Finally,the decision tree model precisely indicated the key structural features required to constitute active c-MET inhibitor molecules,including at least three aromatic het-erocycles,five aromatic nitrogen atoms,and eight nitrogen-oxygen atoms.Overall,our analyses revealed potential structure-activity relationship(SAR)patterns for c-MET inhibitors,which can inform the screening of new compounds and guide future optimization efforts.