Background Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants widely distributed in the environment. Epidemiological studies have shown that PFAS exposure is closely associated with liver dysfunction and an increased risk of liver cancer. Some animal and cell experiments have also revealed its hepatotoxicity and potential carcinogenicity; however, the related carcinogenic mechanism has not yet been fully elucidated. Objective To explore the potential molecular mechanism of PFAS-induced liver cancer, identify the key causal genes, and specifically evaluate the causal association and expression changes of KMT2C in this process, as well as the binding stability between KMT2C and PFAS, and to provid a theoretical basis for mechanistic studies and molecular target discovery in PFAS-related liver cancer. Methods Toxicity prediction was performed on six representative PFAS. Potential target genes of PFAS were identified by integrating results from SwissTargetPrediction, STITCH, and TargetNet databases. Liver cancer-related genes were retrieved from GeneCards, Online Mendelian Inheritance in Man (OMIM), and Therapeutic Target Database (TTD). The intersection of PFAS targets and liver cancer-related genes was used to obtain core genes. A compound-gene-disease regulatory network was constructed, and a protein–protein interaction network was established using STRING database. A core gene network was visualized based on node degree values. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore biological functions and enriched signaling pathways. Subsequently, two-sample Mendelian randomization was employed to assess potential causal relationships between candidate genes and hepatocellular carcinoma, enabling the identification of key genes. Molecular docking analysis using AutoDock was conducted to evaluate the binding stability between KMT2C and PFAS, and TCGA data were used to validate the differential expression of KMT2C between hepatocellular carcinoma and adjacent normal tissues. Results PFAS exhibited multisystem toxicity and posed significant risks of liver injury and carcinogenesis. A total of 266 PFAS target genes and 2923 liver cancer-related genes were identified, with 61 intersecting genes obtained. The enrichment analysis revealed that these intersecting genes were primarily involved in epigenetic regulation, nuclear receptor signaling pathways, and apoptosis-related pathways including TGF-β FoxO and Notch, suggesting their roles in diverse tumor-related biological processes. The two-sample Mendelian randomization results showed a significant negative causal association between KMT2C and hepatocellular carcinoma (OR=0.68, P <0.05). The molecular docking results demonstrated that all tested PFAS exhibited favorable binding to the KMT2C protein, with binding energies below –5.0 kcal·mol⁻¹. KMT2C was significantly upregulated in hepatocellular carcinoma tissues (unpaired P=0.025; paired P=8.38 × 10⁻⁴). Conclusion The KMT2C protein is found to stably bind with all six PFAS, exhibiting strong structural affinity. A causal relationship is identified between KMT2C and the development of hepatocellular carcinoma. TCGA data indicate that KMT2C is significantly upregulated in hepatocellular carcinoma tissues, and it may serve as a key regulatory target in PFAS-related liver cancer.

Objective To analyze the incidence and mortality of gastric cancer in countries and territories with different human development index(HDI)levels in 2022,and to understand the burden of gastric cancer globally and in China.Methods Data on gastric cancer incidence and mortality were collected from GLOBOCAN 2022 and HDI data for all countries were obtained from the Human development report 2022.Spearman correlation was applied to examine the associations between the age-standardized incidence rate(ASIR),age-standardized mortality rate(ASMR),mortality-to-incidence ratio(M/I),and HDI for gastric cancer.The Wilcoxon rank-sum test was used to assess the differences in ASIR and ASMR between males and females.Results In 2022,gastric cancer ranked the 5th in both incidence and mortality among all cancer types globally.In China,gastric cancer ranked the 5th in incidence and the 3rd in mortality among all cancer types.The ASIR and ASMR of gastric cancer showed a descending trend from high,very high,medium to low HDI countries and territories.The ASIR of gastric cancer was positively correlated with HDI(rs=0.256,P=0.001),while ASMR showed no significant correlation with HDI(rs=-0.008,P=0.918).The M/I was negatively correlated with HDI(rs=-0.831,P＜0.001).The ASIR and ASMR of gastric cancer in males were significantly higher than those in females globally,in China,and across all HDI groups(all P＜0.05).Globally,both ASIR and ASMR of gastric cancer remained relatively stable before the age of 45,but showed a consistently rising trend after the age of 45.In China,the ASIR and ASMR of gastric cancer exceeded global average level across all age groups.Conclusion The burden of gastric cancer incidence and mortality is higher in very high and high HDI countries and territories compared to medium and low HDI countries and territories.In China,the burden of gastric cancer incidence and mortality is above the global average,highlighting the need for targeted prevention and control measures.

Objective To compare the incidence and mortality of brain and central nervous system(CNS)tumors in countries and territories with different human development index(HDI)in 2022,to make a comparison with the current epidemiological situation in China,and to assess the association between HDI and the incidence and mortality of brain and CNS tumors.Methods The data on brain and CNS tumors from GLOBOCAN 2022 were collected,and HDI data were organized based on the Human development report 2022.Generalized additive model(GAM)was used to analyze the relationships between standardized incidence ratio(SIR),standardized mortality ratio(SMR),mortality-to-incidence ratio(M/I),and HDI.Results The incidence and mortality of brain and CNS tumors increased with age in 2022,with a significant increasing trend in countries and territories with very high HDI.Countries and territories with high and very high HDI had more cases and more deaths,and countries and territories with very high HDI had the highest SIR and SMR.SIR for brain and CNS tumors in China was higher than the global average,while China's SMR was lower.M/I varied among countries and territories with different HDI,with lower M/I in countries and territories with high and very high HDI.HDI had a significant nonlinear effect on SIR(edf=1.740,P＜0.000 1)and M/I(edf=1.809,P＜0.000 1),and a significant linear effect on SMR(edf=1,P＜0.000 1).As HDI increased,SIR and SMR generally showed an increasing trend,while M/I showed a decreasing trend.Conclusion There are significant global differences in incidence and mortality of brain and CNS tumors in patients with different HDI in 2022;increasing HDI can reduce the risk of brain and CNS tumors and improve treatment outcomes,and prevention and control strategies should be made for different age groups and HDI.

Objective:To observe any effect of dual-task training on abnormal gait and fall risk among hemiplegic stroke survivors.Methods:A total of 90 stroke survivors were randomly divided into a control group, a cognitive dual-task group, and a motor dual-task group, each of 30. All 3 groups received conventional post-stroke medication and rehabilitation training, but the cognitive and motor dual-task groups received cognitive or motor dual-task training as well. Before and after 4 weeks of the training, everyone′s balance, walking and lower limb motor functioning were assessed using the Berg Balance Scale (BBS), the Timed Up and Go test (TUGT) and the Fugl-Meyer lower extremity assessment (FMA-LE). Additionally, three-dimensional gait analysis was performed to document gait speed, bilateral spatial asymmetry, bilateral temporal asymmetry, and the dual-task cost (DTC) of gait speed.Results:Significant improvement was observed in the average BBS scores, TUGT times, FMA-LE scores, gait speed, DTC of gait speed, bilateral spatial asymmetry ratios, and bilateral temporal asymmetry ratios of all 3 groups after the experiment. The averages of the cognitive dual-task group were then significantly better than the control group′s averages. The motor dual-task group′s average BBS score (42.67±7.87), TUGT time [(22.30±8.53)s], gait speed (0.58±0.2m/s), DTC of gait speed (19.02±5.99%), and bilateral spatial asymmetry ratio (19.79±10.41%) were then significantly better than the control group′s averages but not significantly different from those of the cognitive dual-task group.Conclusions:Dual-task training can significantly improve the balance, walking and lower limb motor function of stroke survivors, correcting their abnormal gait patterns and consequently reducing their fall risks.

Objective:To observe any effect of dual-task training on abnormal gait and fall risk among hemiplegic stroke survivors.Methods:A total of 90 stroke survivors were randomly divided into a control group, a cognitive dual-task group, and a motor dual-task group, each of 30. All 3 groups received conventional post-stroke medication and rehabilitation training, but the cognitive and motor dual-task groups received cognitive or motor dual-task training as well. Before and after 4 weeks of the training, everyone′s balance, walking and lower limb motor functioning were assessed using the Berg Balance Scale (BBS), the Timed Up and Go test (TUGT) and the Fugl-Meyer lower extremity assessment (FMA-LE). Additionally, three-dimensional gait analysis was performed to document gait speed, bilateral spatial asymmetry, bilateral temporal asymmetry, and the dual-task cost (DTC) of gait speed.Results:Significant improvement was observed in the average BBS scores, TUGT times, FMA-LE scores, gait speed, DTC of gait speed, bilateral spatial asymmetry ratios, and bilateral temporal asymmetry ratios of all 3 groups after the experiment. The averages of the cognitive dual-task group were then significantly better than the control group′s averages. The motor dual-task group′s average BBS score (42.67±7.87), TUGT time [(22.30±8.53)s], gait speed (0.58±0.2m/s), DTC of gait speed (19.02±5.99%), and bilateral spatial asymmetry ratio (19.79±10.41%) were then significantly better than the control group′s averages but not significantly different from those of the cognitive dual-task group.Conclusions:Dual-task training can significantly improve the balance, walking and lower limb motor function of stroke survivors, correcting their abnormal gait patterns and consequently reducing their fall risks.

The Spt-Ada-Gcn5-acetyltransferase (SAGA) is an ancillary transcription initiation complex which is highly conserved. The ADA1 (alteration/deficiency in activation 1, also called histone H2A functional interactor 1, HFI1) is a subunit in the core module of the SAGA protein complex. ADA1 plays an important role in plant growth and development as well as stress resistance. In this paper, we performed genome-wide identification of banana ADA1 gene family members based on banana genomic data, and analyzed the basic physicochemical properties, evolutionary relationships, selection pressure, promoter cis-acting elements, and its expression profiles under biotic and abiotic stresses. The results showed that there were 10, 6, and 7 family members in Musa acuminata, Musa balbisiana and Musa itinerans. The members were all unstable and hydrophilic proteins, and only contained the conservative SAGA-Tad1 domain. Both MaADA1 and MbADA1 have interactive relationship with Sgf11 (SAGA-associated factor 11) of core module in SAGA. Phylogenetic analysis revealed that banana ADA1 gene family members could be divided into 3 classes. The evolution of ADA1 gene family members was mostly influenced by purifying selection. There were large differences among the gene structure of banana ADA1 gene family members. ADA1 gene family members contained plenty of hormonal elements. MaADA1-1 may play a prominent role in the resistance of banana to cold stress, while MaADA1 may respond to the Panama disease of banana. In conclusion, this study suggested ADA1 gene family members are highly conserved in banana, and may respond to biotic and abiotic stress.
Musa/genetics* ; Phylogeny ; Fungal Proteins ; Cell Nucleus ; Histones ; Stress, Physiological/genetics*

OBJECTIVE To assess the efficacy of bioabsorbable steroid-releasing sinus stents for improving surgical outcomes and subjective symptoms when placed in the bilateral frontal sinus opening(FSO)following full functional endoscopic sinus surgery in patients with chronic rhinosinusitis with nasal polyps(CRSwNP).METHODS CRSwNP patients who had under full functional endoscopic sinus surgery with complete data of nasal endoscopy and sinus computed tomography data were identified and included in the study.The patients were divided into a control group consisting of patients receiving only full functional endoscopic sinus surgery(n=92)and a stent group consisting of patients receiving full functional endoscopic sinus surgery combined with placement of steroid implants in both FSO(n=38).The visual analogue scale(VAS)subjective symptom scores and surgical outcomes were compared preoperatively,and on postoperative day(PD30 and PD90)between the two groups.RESULTS Compared to baseline,the overall symptom VAS scores of patients after operation decreased significantly in both groups(P<0.05),and the degree of improvement of overall symptoms in the stent group was significantly better than in the control group(P<0.05).On PD30,the proportion of patients requiring postoperative interventions for bilateral FSO was reduced by 42.3%in the stent group,and was significantly lower than in the control group(P<0.05).Compared to the control group,the proportion of patients needing postoperative intervention in both ethmoid sinus on the stent group decreased by 17.7%(P>0.05).The results at PD90 were consistent with those at PD30.CONCLUSION Full functional endoscopic sinus surgery in combination with bilateral frontal sinus stent implantation is better than full functional endoscopic sinus surgery alone.

Objective To understand the distribution of ecological suitability of Scutellaria baicalensis Georgi;To screen the main ecological factors affecting its distribution;To predict its suitable planting area in China.Methods A total of 231 batches of Scutellaria baicalensis Georgi were collected through the fourth national survey of TCM resources.The environment information of sampling points were recorded,and 55 ecological factors were analyzed by MaxEnt model and GIS.Results Rainfall,vegetation type and soil types had a greater influence on the distribution of Scutellaria baicalensis Georgi.The ecological suitable areas of Scutellaria baicalensis Georgi mainly concentrated in the eastern part of Shaanxi Province,the western part of Hebei Province and most areas of Chengde,the most part of Shanxi Province,the western part of Beijing,the western part of Liaoning Province,the central and eastern part of Shandong Province,the junction of Jiangsu and Anhui Province,the northern part of Yunnan Province,and the eastern and southern part of Sichuan Province.Conclusion The ecological suitability areas of Scutellaria baicalensis Georgi were classified in this study,and the results could provide reference for the selection of cultivation areas of Scutellaria baicalensis Georgi.

Objective To compare artificial intelligence-assisted diagnostic system and conventional manual CT image interpretation for detection of positive pulmonary nodules and differential diagnosis of benign and malignant pulmonary nodules, and to provide a reference for the application of artificial intelligence in clinical screening for lung cancer. Methods Patients who underwent chest CT scans for pulmonary nodules from March 2019 to December 2023 were enrolled. The CT images were subjected to artificial intelligence-based and conventional manual CT image interpretation. The pathological examination results of pulmonary lesions served as a gold standard for comparison of artificial intelligence-based and conventional manual CT image interpretation in detection rate of positive pulmonary nodules and differential diagnosis of benign and malignant pulmonary nodules. Results A total of 327 positive pulmonary nodules were identified in 207 patients. The detection rate of positive pulmonary nodules was significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation (95.72% vs. 86.85%; χ²=16.16, P < 0.01). Moreover, artificial intelligence-based CT image interpretation showed significantly higher detection rates for solid (χ²=7.71, P < 0.01) and ground-glass pulmonary nodules (χ²=5.80, P < 0.05) than conventional manual CT image interpretation. The detection rates for pulmonary nodules with < 1 cm (χ²=4.97, P < 0.05), 1 to < 2 cm (χ²=7.04, P < 0.01), and 2 to < 3 cm (χ²=4.91, P < 0.05) diameters were significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for differential diagnosis of benign and malignant pulmonary nodules were 98.08%, 91.53%, 95.33%, 96.43%, and 95.71% with artificial intelligence-based CT image interpretation and 91.34%, 77.97%, 87.96%, 32.62%, and 86.50% with conventional CT image interpretation. The sensitivity (χ²=4.70, P < 0.05), specificity (χ²=4.20, P < 0.05), negative predictive value (χ²=65.28, P < 0.01), and accuracy (χ²=8.52, P < 0.01) were significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation. However, there was no significant difference in the positive predictive value (χ²=3.80, P > 0.05). Conclusion Compared with conventional manual CT image interpretation, artificial intelligence-assisted diagnostic system for CT image interpretation can significantly increase the detection rate of positive pulmonary nodules and improve the efficiency of differential diagnosis of benign and malignant pulmonary nodules, so it deserves widespread applications in physical examination and early screening for lung cancer.

Objective To compare artificial intelligence-assisted diagnostic system and conventional manual CT image interpretation for detection of positive pulmonary nodules and differential diagnosis of benign and malignant pulmonary nodules, and to provide a reference for the application of artificial intelligence in clinical screening for lung cancer. Methods Patients who underwent chest CT scans for pulmonary nodules from March 2019 to December 2023 were enrolled. The CT images were subjected to artificial intelligence-based and conventional manual CT image interpretation. The pathological examination results of pulmonary lesions served as a gold standard for comparison of artificial intelligence-based and conventional manual CT image interpretation in detection rate of positive pulmonary nodules and differential diagnosis of benign and malignant pulmonary nodules. Results A total of 327 positive pulmonary nodules were identified in 207 patients. The detection rate of positive pulmonary nodules was significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation (95.72% vs. 86.85%; χ²=16.16, P < 0.01). Moreover, artificial intelligence-based CT image interpretation showed significantly higher detection rates for solid (χ²=7.71, P < 0.01) and ground-glass pulmonary nodules (χ²=5.80, P < 0.05) than conventional manual CT image interpretation. The detection rates for pulmonary nodules with < 1 cm (χ²=4.97, P < 0.05), 1 to < 2 cm (χ²=7.04, P < 0.01), and 2 to < 3 cm (χ²=4.91, P < 0.05) diameters were significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for differential diagnosis of benign and malignant pulmonary nodules were 98.08%, 91.53%, 95.33%, 96.43%, and 95.71% with artificial intelligence-based CT image interpretation and 91.34%, 77.97%, 87.96%, 32.62%, and 86.50% with conventional CT image interpretation. The sensitivity (χ²=4.70, P < 0.05), specificity (χ²=4.20, P < 0.05), negative predictive value (χ²=65.28, P < 0.01), and accuracy (χ²=8.52, P < 0.01) were significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation. However, there was no significant difference in the positive predictive value (χ²=3.80, P > 0.05). Conclusion Compared with conventional manual CT image interpretation, artificial intelligence-assisted diagnostic system for CT image interpretation can significantly increase the detection rate of positive pulmonary nodules and improve the efficiency of differential diagnosis of benign and malignant pulmonary nodules, so it deserves widespread applications in physical examination and early screening for lung cancer.