With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Whole-genome sequencing, serotype typing, MLST typing, population genetic structure analysis, and core-genome single nucleotide polymorphism (cgSNP) analysis were performed on 23 strains of mucoid Haemophilus influenzae collected from the Laboratory Center of Hunan Children′s Hospital from January 2021 to December 2022. Drug susceptibility tests were conducted using the automated microbial identification and susceptibility analysis system AF-600, and virulence genes and drug resistance genes were analyzed based on the whole-genome sequences. Based on the serotype typing of whole-genome sequencing, all 23 strains were Haemophilus influenzae type b (Hib). MLST analysis revealed that the 23 strains belonged to six ST types, among which 10 strains (43.5%) were ST386, 5 strains (21.7%) were ST18, and 2 strains (8.7%) were the newly discovered ST2887. Bayesian population structure analysis (BAPS) showed three distinct populations. The results of the virulence gene analysis showed that the carriage rates of genes encoding capsule-related proteins and those associated with bacterial immune regulation and inflammatory signaling pathways were all 100%. However, the ompP5 gene related to bacterial adhesion, and the hgpC and hxuA genes related to bacterial protein metabolism were all present in the newly discovered ST2887. The in vitro drug susceptibility test results of 23 strains of mucoid Hib showed that the resistance rates to ampicillin, cefuroxime, and Trimethoprim-sulfamethoxazole were 13.0%(3 strains), 13.0%(3 strains), and 87.0%(20 strains), respectively. They were sensitive to other beta-lactam drugs. All the 23 strains of mucoid Haemophilus influenzae infected children were Hib, and the main ST types were ST386 and ST18. It is very important to advocate Hib vaccination.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Whole-genome sequencing, serotype typing, MLST typing, population genetic structure analysis, and core-genome single nucleotide polymorphism (cgSNP) analysis were performed on 23 strains of mucoid Haemophilus influenzae collected from the Laboratory Center of Hunan Children′s Hospital from January 2021 to December 2022. Drug susceptibility tests were conducted using the automated microbial identification and susceptibility analysis system AF-600, and virulence genes and drug resistance genes were analyzed based on the whole-genome sequences. Based on the serotype typing of whole-genome sequencing, all 23 strains were Haemophilus influenzae type b (Hib). MLST analysis revealed that the 23 strains belonged to six ST types, among which 10 strains (43.5%) were ST386, 5 strains (21.7%) were ST18, and 2 strains (8.7%) were the newly discovered ST2887. Bayesian population structure analysis (BAPS) showed three distinct populations. The results of the virulence gene analysis showed that the carriage rates of genes encoding capsule-related proteins and those associated with bacterial immune regulation and inflammatory signaling pathways were all 100%. However, the ompP5 gene related to bacterial adhesion, and the hgpC and hxuA genes related to bacterial protein metabolism were all present in the newly discovered ST2887. The in vitro drug susceptibility test results of 23 strains of mucoid Hib showed that the resistance rates to ampicillin, cefuroxime, and Trimethoprim-sulfamethoxazole were 13.0%(3 strains), 13.0%(3 strains), and 87.0%(20 strains), respectively. They were sensitive to other beta-lactam drugs. All the 23 strains of mucoid Haemophilus influenzae infected children were Hib, and the main ST types were ST386 and ST18. It is very important to advocate Hib vaccination.

Objective: To study the effect of diurnal temperature range on the number of elderly inpatients with ischemic stroke in Hunan Province. Method: Demographic and disease data, meteorological data, air quality data, population, economic and health resource data of elderly inpatients with ischemic stroke were collected in 122 districts/counties of Hunan Province from January to December 2019. The relationships between the diurnal temperature range and the number of elderly inpatients with ischemic stroke were analyzed by using the distributed lag non-linear model, including the cumulative lag effect of the diurnal temperature range in different seasons, extremely high diurnal temperature range and extremely low diurnal temperature range. Results: In 2019, 152 875 person-times were admitted to the hospital for ischemic stroke in the elderly in Hunan Province. There was a non-linear relationship between the diurnal temperature range and the number of elderly patients with ischemic stroke, with different lag periods. In spring and winter, with the decrease in diurnal temperature range, the risk of admission of elderly patients with ischemic stroke increased (P_trend<0.001, P_trend=0.002);in summer, with the increase in diurnal temperature range, the risk of admission of elderly patients with ischemic stroke increased (P_trend=0.024);in autumn, the change in the diurnal temperature range would not cause a change in admission risk (P_trend=0.089). Except that the lag effect of the extremely low diurnal temperature range in autumn was not obvious, the lag effect occurred in other seasons under extremely low and extremely high diurnal temperature ranges. Conclusion: The high diurnal temperature range in summer and the low diurnal temperature range in spring and winter will increase the risk of admission of elderly patients with ischemic stroke, and the risk of admission of elderly patients with ischemic stroke will lag under the extremely low and extremely high diurnal temperature ranges in the above three seasons.
Humans ; Aged ; Temperature ; Ischemic Stroke ; Inpatients ; Cold Temperature ; Hot Temperature ; Seasons ; China/epidemiology*

Objective: To grasp the epidemiological characteristics of influenza outbreaks in Guangdong Province by analyzing the outbreaks of influenza-like cases reported in Guangdong Province from January 2015 to the end of August 2022. Methods: In response to the outbreak of epidemics in Guangdong Province from 2015 to 2022, information on on-site epidemic control was collected, and epidemiological analysis was conducted to describe the characteristics of the epidemics. The factors that influence the intensity and duration of the outbreak were determined through a logistic regression model. Results: A total of 1 901 influenza outbreaks were reported in Guangdong Province, with an overall incidence of 2.05%. Most outbreak reports occurred from November to January of the following year (50.24%, 955/1 901) and from April to June (29.88%, 568/1 901). A total of 59.23% (1 126/1 901) of the outbreaks were reported in the Pearl River Delta region, and primary and secondary schools were the main places where outbreaks occurred (88.01%, 1 673/1 901). Outbreaks with 10-29 cases were the most common (66.18%, 1 258/1 901), and most outbreaks lasted less than seven days (50.93%,906/1 779). The size of the outbreak was related to the nursery school (aOR=0.38, 95%CI:0.15-0.93), the Pearl River Delta region (aOR=0.60, 95%CI:0.44-0.83), the time interval between the onset of the first case and the time of report (>7 days compared with ≤3 days: aOR=3.01, 95%CI:1.84-4.90), the influenza A(H1N1) (aOR=2.02, 95%CI:1.15-3.55) and the influenza B (Yamagata) (aOR=2.94, 95%CI: 1.50-5.76). The duration of outbreaks was related to school closures (aOR=0.65, 95%CI: 0.47-0.89), the Pearl River Delta region (aOR=0.65, 95%CI: 0.50-0.83) and the time interval between the onset of the first case and the time of report (>7 days compared with ≤3 days: aOR=13.33, 95%CI: 8.80-20.19; 4-7 days compared with ≤3 days: aOR=2.56, 95%CI: 1.81-3.61). Conclusions: An influenza outbreak in Guangdong Province exhibits two peaks, one in the winter and spring seasons and the other in the summer. Primary and secondary schools are high-risk areas, and early reporting of outbreaks is critical for controlling influenza outbreaks in schools. Furthermore, comprehensive measures should be taken to prevent the spread of the epidemic.
Humans ; Influenza A Virus, H1N1 Subtype ; Influenza, Human/epidemiology* ; Disease Outbreaks ; Epidemics ; China/epidemiology*

Leukoencephalopathy with vanishing white matter (VWM) is one of the most prevalent inherited childhood white-matter disorders, and the pathogenic gene has been confirmed as EIF2B gene. VWM is characterized by chronic progressive neurological deterioration with cerebellar ataxia, usually less prominent spasticity and relatively mild mental decline. There are episodes of rapid and major neurological deterioration provoked by stresses, such as fever, minor physical trauma and acute fright, which is a characteristic clinical feature of VWM. Brain magnetic resonance imaging findings are diagnostic in almost all patients,and the disappearance of the cerebral white matter occurs in a diffuse "melting away" pattern. The onset of VWM can be at any age from fetal stage to adult stage, and the clinical phenotypes vary immensely. Gene diagnosis is the golden standard for VWM. This article reported a patient with a course of 17 years, who was misdiagnosed as Wilson′s disease because of low serum ceruloplasmin, and was finally diagnosed as VWM by reinterpretation of whole exome sequencing, which is worthy of clinicians′ vigilance and consideration.

Today, there is greater awareness on the association between oral diseases and respiration diseases after the outbreak of COVID-19. However, confusion regarding the oral health management and medical risk prevention for patients with chronic airway diseases has been remained among dental clinicians. Therefore, the dental experts of the Fifth General Dentistry Special Committee, Chinese Stomatological Association, combined with the experts of respiratory and critical care medicine, undertook the formation of consensus on the oral health management of patients with chronic airway diseases in order to help dental clinicians to evaluate medical risks and make better treatment decision in clinical practice. In the present consensus report, the relationship of oral diseases and chronic airway diseases, the oral health management and the treatment recommendations of patients with chronic airway diseases are provided.
COVID-19 ; Consensus ; Humans ; Oral Health ; Oral Medicine

With the aging process of population in the society, the prevalence of cardiovascular diseases (CVD) in China is increasing continuously and the number of dental patients with CVD is increasing gradually too. Due to the lack of guidelines for dental patients with CVD in our country, how to implement standardized preoperative evaluation and perioperative risk prevention remains a problem to be solved for dentists at present. The present expert consensus was reached by combining the clinical experiences of the expert group of the Fifth General Dentistry Special Committee, Chinese Stomatological Association and respiratory and cardiology experts in diagnosis and treatment for CVD patients, and by systematically summarizing the relevant international guidelines and literature regarding the relationship between CVD and oral diseases and the diagnosis and treatment of dental patients with heart failure, hypertension and antithrombotic therapy. The consensus aims to provide, for the dental clinicians, the criteria on diagnosis and treatment of CVD in dental patients in China so as to reduce the risk and complications, and finally to improve the treatment levels of dental patients with CVD in China.
Cardiovascular Diseases/prevention & control* ; China/epidemiology* ; Consensus ; Dental Care ; Humans ; Oral Medicine

Objective: To analyze the clinical epidemiological characteristics including composition of pathogens , clinical characteristics, and disease prognosis acute bacterial meningitis (ABM) in Chinese children. Methods: A retrospective analysis was performed on the clinical and laboratory data of 1 610 children <15 years of age with ABM in 33 tertiary hospitals in China from January 2019 to December 2020. Patients were divided into different groups according to age,<28 days group, 28 days to <3 months group, 3 months to <1 year group, 1-<5 years of age group, 5-<15 years of age group; etiology confirmed group and clinically diagnosed group according to etiology diagnosis. Non-numeric variables were analyzed with the Chi-square test or Fisher's exact test, while non-normal distrituction numeric variables were compared with nonparametric test. Results: Among 1 610 children with ABM, 955 were male and 650 were female (5 cases were not provided with gender information), and the age of onset was 1.5 (0.5, 5.5) months. There were 588 cases age from <28 days, 462 cases age from 28 days to <3 months, 302 cases age from 3 months to <1 year of age group, 156 cases in the 1-<5 years of age and 101 cases in the 5-<15 years of age. The detection rates were 38.8% (95/245) and 31.5% (70/222) of Escherichia coli and 27.8% (68/245) and 35.1% (78/222) of Streptococcus agalactiae in infants younger than 28 days of age and 28 days to 3 months of age; the detection rates of Streptococcus pneumonia, Escherichia coli, and Streptococcus agalactiae were 34.3% (61/178), 14.0% (25/178) and 13.5% (24/178) in the 3 months of age to <1 year of age group; the dominant pathogens were Streptococcus pneumoniae and the detection rate were 67.9% (74/109) and 44.4% (16/36) in the 1-<5 years of age and 5-<15 years of age . There were 9.7% (19/195) strains of Escherichia coli producing ultra-broad-spectrum β-lactamases. The positive rates of cerebrospinal fluid (CSF) culture and blood culture were 32.2% (515/1 598) and 25.0% (400/1 598), while 38.2% (126/330)and 25.3% (21/83) in CSF metagenomics next generation sequencing and Streptococcus pneumoniae antigen detection. There were 4.3% (32/790) cases of which CSF white blood cell counts were normal in etiology confirmed group. Among 1 610 children with ABM, main intracranial imaging complications were subdural effusion and (or) empyema in 349 cases (21.7%), hydrocephalus in 233 cases (14.5%), brain abscess in 178 cases (11.1%), and other cerebrovascular diseases, including encephalomalacia, cerebral infarction, and encephalatrophy, in 174 cases (10.8%). Among the 166 cases (10.3%) with unfavorable outcome, 32 cases (2.0%) died among whom 24 cases died before 1 year of age, and 37 cases (2.3%) had recurrence among whom 25 cases had recurrence within 3 weeks. The incidences of subdural effusion and (or) empyema, brain abscess and ependymitis in the etiology confirmed group were significantly higher than those in the clinically diagnosed group (26.2% (207/790) vs. 17.3% (142/820), 13.0% (103/790) vs. 9.1% (75/820), 4.6% (36/790) vs. 2.7% (22/820), χ²=18.71, 6.20, 4.07, all P<0.05), but there was no significant difference in the unfavorable outcomes, mortility, and recurrence between these 2 groups (all P>0.05). Conclusions: The onset age of ABM in children is usually within 1 year of age, especially <3 months. The common pathogens in infants <3 months of age are Escherichia coli and Streptococcus agalactiae, and the dominant pathogen in infant ≥3 months is Streptococcus pneumoniae. Subdural effusion and (or) empyema and hydrocephalus are common complications. ABM should not be excluded even if CSF white blood cell counts is within normal range. Standardized bacteriological examination should be paid more attention to increase the pathogenic detection rate. Non-culture CSF detection methods may facilitate the pathogenic diagnosis.
Adolescent ; Brain Abscess ; Child ; Child, Preschool ; Escherichia coli ; Female ; Humans ; Hydrocephalus ; Infant ; Infant, Newborn ; Male ; Meningitis, Bacterial/epidemiology* ; Retrospective Studies ; Streptococcus agalactiae ; Streptococcus pneumoniae ; Subdural Effusion ; beta-Lactamases