The value of computed tomography angiography for evaluation of left atrial enlargement in patients with persistent atrial fibrillation.

BACKGROUND: The post-processing technology of CTA offers significant advantages in evaluating left atrial enlargement (LAE) in patients with persistent atrial fibrillation (PAF). This study aims to identify parameters for rapidly and accurately diagnosing LAE in patients with PAF using CT cross-sections. METHODS: Left atrial pulmonary venous (PV) CT was performed to 300 PAF patients with dual-source CT, and left atrial volume (LAV), left atrial anteroposterior diameter (LAD1), left atrial transverse diameter (LAD2), and left atrial area (LAA) were measured in the ventricular end systolic (ES) and middle diastolic (MD). LA index (LAI) = LA parameter/body surface area (BSA). Left atrial volume index (LAVIES) > 77.7 ml/m2 was used as the reference standard for the LAE diagnosis. RESULTS: 227 patients were enrolled in the group, 101 (44.5%) of whom had LAE. LAVES and LAVMD (r = 0.983), LAVIES and LAVIMD (r = 0.984), LAAES and LAVIES (r = 0.817), LAAMD and LAVIES (r = 0.814) had strong positive correlations. The area under curve (AUC) showed that all measured parameters were suitable for diagnosing LAE, and the diagnostic efficacy was compared as follows: LAA/LAAI> LAD> the relative value index of LAD, LAD2> LAD1. LAA and LAAI demonstrated comparable diagnostic efficacy, with LAA being more readily available than LAAI. CONCLUSIONS: The axial LAA measured by CTA can be served as a parameter for the rapid and accurate diagnosis of LAE in patients with PAF.

Asymmetric Synthesis of Chiral Cyclopropanes from Vinyl Sulfoxonium Ylides Catalyzed by a Chiral-at-Metal Rh(III) Complex.

A chiral-at-metal Rh(III) complex-mediated [2+1] cyclization of vinyl sulfoxonium ylides with α,ß-unsaturated 2,2-acylimidazoles has been demonstrated for the first time. This work provides a practical approach for assembling 1,2,3-trisubstituted chiral cyclopropane with alkyl structural units, which had advantages such as a wide range of substrates, good functional group tolerance, and mild reaction conditions. In addition, further amplification experiments and transformation of cycloaddition products were carried out to highlight the practicality of the method.

Association of single nucleotide polymorphisms and gene-environment interactions with major depressive disorder in Chinese.

We conducted a case-control study to investigate the effects of genetics and gene-environment interactions on major depressive disorders (MDD) in the Chinese population. Using targeted-exome sequencing, we included 984 patients with MDD and 508 healthy controls in our study. A logistic regression model was employed to analyze the association between single nucleotide polymorphisms (SNPs) and MDD. Additionally, a linear regression model was utilized to examine the associations between (1) gene-environment interaction and the 17-item Hamilton Depression Rating Scale, (2) SNPs and the Beck Scale for Suicide Ideation-Chinese version, and gene-environment interaction and the Beck scale for suicide ideation-Chinese version. The association analysis between SNPs and MDD revealed that the following loci reached genome-wide significance: rs2305554 of the cholinergic receptor nicotinic alpha 7 subunit, rs9459173 of synaptojanin 2, rs372369000 of beta-1,4-galactosyltransferase 6, rs866666526 of dopa decarboxylase, rs1254882194 of calcium/calmodulin dependent protein kinase ID, rs199880487 of reelin, rs1167948188 of reelin, rs1390140186 of QKI, KH domain containing RNA binding, and rs1776342 of period circadian regulator 3. The association analysis between SNPs and the Beck Scale for Suicide Ideation-Chinese version indicated that rs264272 and rs1774784888 of piezo type mechanosensitive ion channel component 2 reached genome-wide significance. These findings may enhance our understanding of MDD and contribute to the development of new potential targets for its diagnosis and treatment.

The Effect of Cosmetic Makeup on Body Imagery and Anxiety and Depression in Patients Undergoing Postoperative Chemotherapy for Breast Cancer: A Randomized Controlled Study.

Purpose: The objective was to compare the body images of breast cancer patients undergoing postoperative chemotherapy and the varying degrees of their anxiety and depression. The comparison involved those who received four consecutive cycles of cosmetic makeup and those who did not. Patients and Methods: Seventy-four breast cancer patients receiving postoperative chemotherapy were randomly assigned to either the control group or the intervention group. The control group received usual care, while the intervention group received four consecutive cycles of chemotherapy along with cosmetic makeup intervention on top of usual care. The intervention was carried out on the first day after the completion of each chemotherapy cycle. Assessments were made before the first intervention and 1 month after the fourth intervention using the Hospital Anxiety and Depression Scale and the Scale of Body Imagery. Results: After four cycles of intervention, significant differences emerged between the intervention and control groups regarding anxiety, depression, and body imagery. Additionally, within the intervention group, notable changes in these aspects were observed over time. Conclusion: The results showed that cosmetic interventions can effectively reduce the level of anxiety and depression of breast cancer patients receiving postoperative chemotherapy and effectively improve the body imagery of patients.

Loss of OsMATE6 Function Enhances Drought Resistance Without Yield Penalty by Regulating Stomatal Closure in Rice.

Drought is one of the most severe environmental factors limiting plant growth and crop yield, necessitating the identification of genes that enhance drought resistance for crop improvement. Through screening an ethyl methyl sulfonate-mutagenized rice mutant library, we isolated the PEG tolerance mutant 97-1 (ptm97-1), which displays enhanced resistance to osmotic and drought stress, and increased yield under drought conditions. A point mutation in OsMATE6 was identified as being associated with the drought-resistant phenotype of ptm97-1. The role of OsMATE6 in conferring drought resistance was confirmed by additional OsMATE6 knockout mutants. OsMATE6 is expressed in guard cells, shoots and roots and the OsMATE6-GFP fusion protein predominantly localizes to the plasma membrane. Our ABA efflux assays suggest that OsMATE6 functions as an ABA efflux transporter; mutant protoplasts exhibited a slower ABA release rate compared to the wild type. We hypothesize that OsMATE6 regulates ABA levels in guard cells, influencing stomatal closure and enhancing drought resistance. Notably, OsMATE6 knockout mutants demonstrated greater yields under field drought conditions compared to wild-type plants, highlighting OsMATE6 as a promising candidate for improving crop drought resistance.

The impact of plan complexity on calculation and measurement-based pre-treatment verifications for sliding-window intensity-modulated radiotherapy.

Background and purpose: In sliding-window intensity-modulated radiotherapy, increased plan modulation often leads to increased plan complexities and dose uncertainties. Dose calculation and/or measurement checks are usually adopted for pre-treatment verification. This study aims to evaluate the relationship among plan complexities, calculated doses and measured doses. Materials and methods: A total of 53 plan complexity metrics (PCMs) were selected, emphasizing small field characteristics and leaf speed/acceleration. Doses were retrieved from two beam-matched treatment devices. The intended dose was computed employing the Anisotropic Analytical Algorithm and validated through Monte Carlo (MC) and Collapsed Cone Convolution (CCC) algorithms. To measure the delivered dose, 3D diode arrays of various geometries, encompassing helical, cross, and oblique cross shapes, were utilized. Their interrelation was assessed via Spearman correlation analysis and principal component linear regression (PCR). Results: The correlation coefficients between calculation-based (CQA) and measurement-based verification quality assurance (MQA) were below 0.53. Most PCMs showed higher correlation rpcm-QA with CQA (max: 0.84) than MQA (max: 0.65). The proportion of rpcm-QA  ≥ 0.5 was the largest in the pelvis compared to head-and-neck and chest-and-abdomen, and the highest rpcm-QA occurred at 1 %/1mm. Some modulation indices for the MLC speed and acceleration were significantly correlated with CQA and MQA. PCR's determination coefficients (R2 ) indicated PCMs had higher accuracy in predicting CQA (max: 0.75) than MQA (max: 0.42). Conclusions: CQA and MQA demonstrated a weak correlation. Compared to MQA, CQA exhibited a stronger correlation with PCMs. Certain PCMs related to MLC movement effectively indicated variations in both quality assurances.

Application of Lactiplantibacillus plantarum hydrogel coating in combination with ice temperature for the preservation of fresh yak meat.

Fresh yak meat is highly nutritious and prone to spoilage, so developing suitable preservation methods is crucial. In this study, hydrogel coatings composed of konjac glucomannan, Lactiplantibacillus plantarum and gallic acid (KGX) were applied to preserve fresh yak meat under ice temperature (-1 °C). After 16 days, KGX group showed lowest total viable count (5.3 ± 0.1 log cfu/g) and total volatile basic nitrogen (13.02 ± 1.40 mg/100 g), which did not exceed the relevant standards of fresh meat. Combined assessments of color, texture, pH, drip loss rate, and thiobarbituric acid reactive substances indicated that KGX coating effectively prolonged yak meat preservation. High-throughput sequencing revealed that KGX coating effectively reduced the abundance of Pseudomonas and Candida. The application of L. plantarum hydrogel coatings in conjunction with ice temperature increased the shelf life of fresh yak meat to 16-20 days, suggesting its potential as a viable preservation method for fresh meat.

Clinical and pathogen features of COVID-19-associated infections during an Omicron strain outbreak in Guangzhou, China.

Although the Omicron variant has been associated with greater transmissibility and tropism of the upper respiratory tract, the clinical and pathogenic features of patients infected with the Omicron variant during an outbreak in China have been unclear. Adults with COVID-19 were retrospectively enrolled from seven medical centers in Guangzhou, China, and clinical information and specimens ( BALF, sputum, and throat swabs) from participants were collected. Conventional detection methods, metagenomics next-generation sequencing (mNGS), and other methods were used to detect pathogens in lower respiratory tract samples. From December 2022 to January 2023, we enrolled 836 patients with COVID-19, among which 56.7% patients had severe/critical illness. About 91.4% of patients were infected with the Omicron strain (BA.5.2). The detection rate of possible co-infection pathogens was 53.4% by mNGS, including Klebsiella pneumoniae (16.3%), Aspergillus fumigatus (12.2%), and Pseudomonas aeruginosa (11.8%). The co-infection rate was 19.5%, with common pathogens being Streptococcus pneumoniae (11.5%), Haemophilus influenzae (9.2%), and Adenovirus (6.9%). The superinfection rate was 75.4%, with common pathogens such as Klebsiella pneumoniae (26.1%) and Pseudomonas aeruginosa (19.4%). Klebsiella pneumoniae (27.1%% vs 6.1%, P < 0.001), Aspergillus fumigatus (19.6% vs 5.3%, P = 0.001), Acinetobacter baumannii (18.7% vs 4.4%, P = 0.001), Pseudomonas aeruginosa (16.8% vs 7.0%, P = 0.024), Staphylococcus aureus (14.0% vs 5.3%, P = 0.027), and Streptococcus pneumoniae (0.9% vs 10.5%, P = 0.002) were more common in severe cases. Co-infection and superinfection of bacteria and fungi are common in patients with severe pneumonia associated with Omicron variant infection. Sequencing methods may aid in the diagnosis and differential diagnosis of pathogens. IMPORTANCE: Our study has analyzed the clinical characteristics and pathogen spectrum of the lower respiratory tract associated with co-infection or superinfection in Guangzhou during the outbreak of the Omicron strain, particularly after the relaxation of the epidemic prevention and control strategy in China. This study will likely prompt further research into the specific issue, which will benefit clinical practice.

Prevalence and correlations of schistosomiasis mansoni and schistosomiasis haematobium among humans and intermediate snail hosts: a systematic review and meta-analysis.

BACKGROUND: The control of schistosomiasis is particularly difficult in sub-Saharan Africa, which currently harbours 95% of this disease. The target population for preventive chemotherapy (PC) is expanded to all age group at risk of infection, thus increasing the demands of praziquantel (PZQ) tablets according to the new released guideline by World Health Organization. Due to the gap between available PZQ for PC and requirements, alternative approaches to assess endemicity of schistosomiasis in a community, are urgently needed for more quick and precise methods. We aimed to find out to which degree the infection status of snails can be used to guide chemotherapy against schistosomiasis. METHODS: We searched literature published from January 1991 to December 2022, that reported on the prevalence rates of Schistosoma mansoni, S. haematobium in the intermediate snails Biomphalaria spp. and Bulinus spp., respectively, and in humans. A random effect model for meta-analyses was used to calculate the pooled prevalence estimate (PPE), with heterogeneity assessed using I-squared statistic (I2), with correlation and regression analysis for the exploration of the relationship between human S. mansoni and S. haematobium infections and that in their specific intermediate hosts. RESULTS: Forty-seven publications comprising 59 field investigations were included. The pooled PPE of schistosomiasis, schistosomiasis mansoni and schistosomiasis haematobium in humans were 27.5% [95% confidence interval (CI): 24.0-31.1%], 25.6% (95% CI: 19.9-31.3%), and 28.8% (95% CI: 23.4-34.3%), respectively. The snails showed an overall infection rate of 8.6% (95% CI: 7.7-9.4%), with 12.1% (95% CI: 9.9-14.2%) in the Biomphalaria spp. snails and 6.9% (95% CI: 5.7-8.1%) in the Bulinus spp. snails. The correlation coefficient was 0.3 (95% CI: 0.01-0.5%, P < 0.05) indicating that the two variables, i.e. all intermediate host snails on the one hand and the human host on the other, were positively correlated. CONCLUSIONS: The prevalence rate of S. mansoni and S. haematobium is still high in endemic areas. Given the significant, positive correlation between the prevalence of schistosomes in humans and the intermediate snail hosts, more attention should be paid to programme integration of snail surveillance in future.

Integration of volatile and non-volatile metabolite profile, and in vitro digestion reveals the differences between different preparation methods on physico-chemical and biological properties of Gastrodia elata.

Gastrodia elata Blume (G. elata) is a traditional medicinal and edible plant whose quality is significantly influenced by post-harvest processing. To obtain an optimal post-harvest processing method for G. elata, this study employed sensory evaluation, scanning electron microscopy (SEM), gas chromatography-ion mobility spectrometry (GC-IMS), and non-targeted metabolomics, in conjunction with an in vitro digestion model, to assess the impact of different processing and drying methods on the quality of G. elata. The findings showed that the steam treatment followed by heat pump drying resulted in the highest levels of total phenols, total flavonoids, and polysaccharides in G. elata, and caused more pronounced damage to its microstructure. This treatment also maintained the highest antioxidant activities and optimal acetylcholinesterase (AChE) inhibition capacity throughout in vitro digestion, meanwhile, effectively eliminating the unpleasant odor and achieving the highest sensory scores. Furthermore, non-targeted metabolomic analysis revealed noteworthy alterations in the metabolite profile of G. elata, mainly related to purine metabolism and the biosynthesis of amino acids pathways. This study provides valuable insights into the post-harvest processing of G. elata.

Machine Learning-Driven discovery of immunogenic cell Death-Related biomarkers and molecular classification for diabetic ulcers.

In this study, we redefine the diagnostic landscape of diabetic ulcers (DUs), a major diabetes complication. Our research uncovers new biomarkers linked to immunogenic cell death (ICD) in DUs by utilizing RNA-sequencing data of Gene Expression Omnibus (GEO) analysis combined with a comprehensive database interrogation. Employing a random forest algorithm, we have developed a diagnostic model that demonstrates improved accuracy in distinguishing DUs from normal tissue, with satisfactory results from ROC analysis. Beyond mere diagnosis, our model categorizes DUs into novel molecular classifications, which may enhance our comprehension of their underlying pathophysiology. This study bridges the gap between molecular insights and clinical practice. It sets the stage for transformative strategies in DUs management, marking a significant step forward in personalized medicine for diabetic patients.

The impact of different postures on acute intraocular pressure and accommodation responses during reading.

INTRODUCTION: To investigate the effects of different reading postures on intraocular pressure (IOP) and near-work-induced transient myopia (NITM) in children with myopia. METHODS: Sixty myopic children were instructed to read a book text placed at 33 cm for 30 min with two different reading postures: head bowed and head upright postures. The participants' IOP and NITM were assessed using a rebound tonometer and an open-field autorefractor. The measurement of IOP was conducted prior to reading, during reading sessions (at 5, 10, 20, and 30-min intervals), and after a 5-min recovery period. RESULTS: For the head bowed posture, the mean baseline IOP was 16.13 ± 2.47 mmHg. A significant rise in IOP was observed after 5 min of reading (17.17 ± 2.97 mmHg; +1.03 ± 2.29 mmHg; p = 0.014). Subsequent measurements revealed a further increase after 20 min (17.87 ± 2.90 mmHg; +1.73 ± 2.58 mmHg; p < 0.001), which continued to persist even after 30 min of reading (17.57 ± 3.46 mmHg; +1.43 ± 2.66 mmHg; p = 0.002). The IOP at different time points measured in the head upright posture did not show any significant difference in comparison to the baseline measurement (all p = 1.000). Compared to reading with the head upright, reading with the head bowed resulted in a greater increase in IOP at each time point (p < 0.05). Furthermore, the NITM was higher for reading with the head bowed than for reading with head upright at 30 min (-0.24 ± 0.53 D vs. -0.12 ± 0.47 D, p = 0.038). CONCLUSION: Reading in a head bowed position resulted in greater increases in IOP and NITM compared to reading in a head upright posture.

An integrated machine learning model enhances delayed graft function prediction in pediatric renal transplantation from deceased donors.

BACKGROUND: Kidney transplantation is the optimal renal replacement therapy for children with end-stage renal disease; however, delayed graft function (DGF), a common post-operative complication, may negatively impact the long-term outcomes of both the graft and the pediatric recipient. However, there is limited research on DGF in pediatric kidney transplant recipients. This study aims to develop a predictive model for the risk of DGF occurrence after pediatric kidney transplantation by integrating donor and recipient characteristics and utilizing machine learning algorithms, ultimately providing guidance for clinical decision-making. METHODS: This single-center retrospective cohort study includes all recipients under 18 years of age who underwent single-donor kidney transplantation at our hospital between 2016 and 2023, along with their corresponding donors. Demographic, clinical, and laboratory examination data were collected from both donors and recipients. Univariate logistic regression models and differential analysis were employed to identify features associated with DGF. Subsequently, a risk score for predicting DGF occurrence (DGF-RS) was constructed based on machine learning combinations. Model performance was evaluated using the receiver operating characteristic curves, decision curve analysis (DCA), and other methods. RESULTS: The study included a total of 140 pediatric kidney transplant recipients, among whom 37 (26.4%) developed DGF. Univariate analysis revealed that high-density lipoprotein cholesterol (HDLC), donor after circulatory death (DCD), warm ischemia time (WIT), cold ischemia time (CIT), gender match, and donor creatinine were significantly associated with DGF (P < 0.05). Based on these six features, the random forest model (mtry = 5, 75%p) exhibited the best predictive performance among 97 machine learning models, with the area under the curve values reaching 0.983, 1, and 0.905 for the entire cohort, training set, and validation set, respectively. This model significantly outperformed single indicators. The DCA curve confirmed the clinical utility of this model. CONCLUSIONS: In this study, we developed a machine learning-based predictive model for DGF following pediatric kidney transplantation, termed DGF-RS, which integrates both donor and recipient characteristics. The model demonstrated excellent predictive accuracy and provides essential guidance for clinical decision-making. These findings contribute to our understanding of the pathogenesis of DGF.

PDHX acetylation facilitates tumor progression by disrupting PDC assembly and activating lactylation mediated gene expression.

Deactivation of the mitochondrial pyruvate dehydrogenase complex (PDC) is important for the metabolic switching of cancer cell from oxidative phosphorylation to aerobic glycolysis. Studies examining PDC activity regulation have mainly focused on the phosphorylation of pyruvate dehydrogenase (PDH, E1), leaving other post-translational modifications (PTMs) largely unexplored. Here, we demonstrate that the acetylation of Lys 488 of pyruvate dehydrogenase complex component X (PDHX) commonly occurs in hepatocellular carcinoma (HCC), disrupting PDC assembly and contributing to lactate-driven epigenetic control of gene expression. PDHX, an E3-binding protein (E3BP) in the PDC, is acetylated by the p300 at Lys 488, impeding the interaction between PDHX and dihydrolipoyl transacetylase (DLAT, E2), thereby disrupting PDC assembly to inhibit its activation. PDC disruption results in the conversion of most glucose to lactate, contributing to the aerobic glycolysis and H3K56 lactylation-mediated gene expression, facilitating tumor progression. These findings highlight a previously unrecognized role of PDHX acetylation in regulating PDC assembly and activity, linking PDHX Lys 488 acetylation and histone lactylation during HCC progression and providing a potential biomarker and therapeutic target for further development.

Effects of undescribed iridoids in Patrinia punctiflora on insulin resistance in HepG2 cells.

Patrinia punctiflora is a medical and edible Chinese herb with high nutritional and medicinal value. The continuing study of its chemical constituents led to the isolation of six iridoids, which were previously unreported compounds, patriscabioins PU (1-6). Their structures were characterized and confirmed with NMR (1D & 2D), HRMS, IR and UV. Among them, compound 5 was screened to evaluate its insulin resistance activity on an IR-HepG-2 cell model. Compound 5 had no cytotoxicity compared with the control group and could promote glucose uptake in IR-HepG-2 cells. Through further mechanism studies, the undescribed compound 5 could increase the expression levels of PI-3 K, p-AKT, GLUT4 and p-GSK3ß proteins. Moreover, the expression of PEPCK and G6Pase proteins, which are key gluconeogenic enzymes, was also inhibited. Thus, compound 5 promotes the transfer of GLUT4 to the plasma membrane by activating the PI-3 K/AKT signaling pathway, at the same time, promotes glycogen synthesis and inhibits the onset of gluconeogenesis, which in turn ameliorates insulin resistance.

Natriuretic peptide receptor-C perturbs mitochondrial respiration in white adipose tissue.

Natriuretic peptide receptor-C (NPR-C) is highly expressed in adipose tissues and regulates obesity-related diseases; however, the detailed mechanism remains unknown. In this research, we aimed to explore the potential role of NPR-C in cold exposure and high-fat/high-sugar (HF/HS) diet-induced metabolic changes, especially in regulating white adipose tissue (WAT) mitochondrial function. Our findings showed that NPR-C expression, especially in epididymal WAT (eWAT), was reduced after cold exposure. Global Npr3 (gene encoding NPR-C protein) deficiency led to reduced body weight, increased WAT browning, thermogenesis, and enhanced expression of genes related to mitochondrial biogenesis. RNA-sequencing of eWAT showed that Npr3 deficiency enhanced the expression of mitochondrial respiratory chain complex genes and promoted mitochondrial oxidative phosphorylation in response to cold exposure. In addition, Npr3 KO mice were able to resist obesity induced by HF/HS diet. Npr3 knockdown in stromal vascular fraction (SVF)-induced white adipocytes promoted the expression of proliferator-activated receptor gamma coactivator 1α (PGC1α), uncoupling protein one (UCP1), and mitochondrial respiratory chain complexes. Mechanistically, NPR-C inhibited cGMP and calcium signaling in an NPR-B-dependent manner but suppressed cAMP signaling in an NPR-B-independent manner. Moreover, Npr3 knockdown induced browning via AKT and p38 pathway activation, which were attenuated by Npr2 knockdown. Importantly, treatment with the NPR-C-specific antagonist, AP-811, decreased WAT mass and increased PGC-1α, UCP1, and mitochondrial complex expression. Our findings reveal that NPR-C deficiency enhances mitochondrial function and energy expenditure in white adipose tissue, contributing to improved metabolic health and resistance to obesity.

Helical polyisocyanide-based macroporous organic catalysts for asymmetric Michael addition with high efficiency and stereoselectivity.

Porous materials have attracted interest due to their high specific surface area and rich functionality. Immobilizing organocatalysts onto porous polymers not only boosts enantioselectivity but also improves the reaction rates. In this work, a series of porous polymers C-poly-3ms with rigid polyisocyanide-carrying secondary amine pendants as building blocks were successfully prepared. And the pore size and optical activity of C-poly-3ms can be controlled by the length of the polyisocyanide blocks due to their rigid and helical backbone. C-poly-3150 demonstrated a preferred left-handed helix with a θ 364 value of -8.21 × 103. The pore size and S BET of C-poly-3150 were 17.52 nm and 7.98 m2 g-1, respectively. The porous C-poly-3150 catalyzes the asymmetric Michael addition reaction efficiently and generates the target products in satisfactory yield and excellent enantioselectivity. For 6ab, an enantiomeric excess (ee) and a diastereomeric ratio (dr) up to 99% and 99/1 could be achieved, respectively. The recovered catalyst can be recycled at least 6 times in the asymmetric Michael addition reaction while maintaining activity and stereoselectivity.

Accurate Prediction of Rat Acute Oral Toxicity and Reference Dose for Thousands of Polycyclic Aromatic Hydrocarbon Derivatives Based on Chemometric QSAR and Machine Learning.

Acute oral toxicity is currently not available for most polycyclic aromatic hydrocarbons (PAHs), especially their derivatives, because it is cost-prohibitive to experimentally determine all of them. Here, quantitative structure-activity relationship (QSAR) models using machine learning (ML) for predicting the toxicity of PAH derivatives were developed, based on oral toxicity data points of 788 individual substances of rats. Both the individual ML algorithm gradient boosting regression trees (GBRT) and the stacking ML algorithm (extreme gradient boosting + GBRT + random forest regression) provided the best prediction results with satisfactory determination coefficients for both cross-validation and the test set. It was found that those PAH derivatives with fewer polar hydrogens, more large-sized atoms, more branches, and lower polarizability have higher toxicity. Software based on the optimal ML-QSAR model was successfully developed to expand the application potential of the developed model, obtaining reliable prediction of pLD50 values and reference doses for 6893 external PAH derivatives. Among these chemicals, 472 were identified as moderately or highly toxic; 10 out of them had clear environment detection or use records. The findings provide valuable insights into the toxicity of PAHs and their derivatives, offering a standard platform for effectively evaluating chemical toxicity using ML-QSAR models.