In view of the characteristics of H5N6 subtype avian influenza virus(AIV)that it has both high pathogenicity and the risk of cross-species transmission,posing a serious threat to the poultry farming industry and public health security,in order to effectively prevent and control the spread of H5N6 avian influenza,a rapid,sensitive and specific detection technolo-gy was established in this study.The specific monoclonal antibodies against the neuraminidase N6 protein of avian influenza A virus subtype H5N6 were obtained through hybridoma and monoclonal antibody technology.These antibodies were coupled and labeled with carboxyl-functionalized fluorescent quantum dots,along with previously prepared specific antibodies against the hemagglutinin H5 protein.A rapid fluorescence immunochromatographic detection method for the H5N6 subtype of avian influ-enza virus was established according to the principle of double-antibody sandwich immunochromatography.This method a-chieved a detection sensitivity of 1 ng/mL for recombinant hemagglutinin H5 subtype protein and 0.1 ng/mL for recombinant neuraminidase N6 subtype protein.Moreover,the method exhibited no cross-reactivity with other influenza subtypes or patho-gens,such as Newcastle disease(ND),infectious bronchitis(IB),and infectious laryngotracheitis(ILT),thus demonstrating good specificity.The method effectively identified the highly pathogenic avian influenza virus H5 subtype and directly distin-guished the H5N6 subtype with good accuracy.The fluorescent quantum dot immunochromatographic typing detection method established herein met the sensitivity,specificity,and accuracy requirements for H5N6 subtype detection,and can be further used for rapid detection of the H5 and H5N6 subtypes of avian influenza virus.

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.

This study analyzed the demographic characteristics and clinically significant inflammatory index changes in listeriosis cases in China from 2010 to 2023.The aim was to understand Listeria monocytogenes susceptibility,to provide a reference for listeriosis prevention and control.Records in three Chinese databases—the China Knowledge Network,Wanfang Database,and VIP Database—from January 1,2010,to December 31,2023,were searched.Statistical analysis was conducted on the clinical features and epidemiological information for all identified cases.A total of 693 cases of listeriosis were included:482 occurring during the perinatal period and 211 occurring outside the perinatal period.The average mortality rate was 17.2%(119/693).The predominant clinical manifestations of listeriosis in neonatal patients during the perinatal period were sepsis(75.5%,241/319)and meningitis(41.1%,131/319).The mortality rate among neonatal patients was 27.1%(76/280).In patients in the non-perinatal period,meningitis(70.1%,148/211)and sepsis(43.6%,92/211)were the main clinical manifestations,and the average patient age was 47.2 years.Among patients of known age,the highest prevalence was observed in the 40-64 year age group,which accounted for 44.9%(44/98).Sixty-one cases had no other underlying diseases before infection.Reported cases of listeriosis occurred in 27 provinces(municipalities,and autonomous region)in China,and Beijing reported the most cases,accounting for 23.7%(164/693).L.monocytogenes was sensitive to β-lactam drug treatment but showed differing degrees of drug resistance.Among 145 cases,12 were resistant to penicillin,and 16 were resistant to oxacillin.Listeriosis is a foodborne disease with a high mortality rate,particularly among neonates.With the continuing emergence of drug-resistant strains,standardizing and strengthening prevention and treatment measures for this disease as early as possible are essential.

This study analyzed the demographic characteristics and clinically significant inflammatory index changes in listeriosis cases in China from 2010 to 2023.The aim was to understand Listeria monocytogenes susceptibility,to provide a reference for listeriosis prevention and control.Records in three Chinese databases—the China Knowledge Network,Wanfang Database,and VIP Database—from January 1,2010,to December 31,2023,were searched.Statistical analysis was conducted on the clinical features and epidemiological information for all identified cases.A total of 693 cases of listeriosis were included:482 occurring during the perinatal period and 211 occurring outside the perinatal period.The average mortality rate was 17.2%(119/693).The predominant clinical manifestations of listeriosis in neonatal patients during the perinatal period were sepsis(75.5%,241/319)and meningitis(41.1%,131/319).The mortality rate among neonatal patients was 27.1%(76/280).In patients in the non-perinatal period,meningitis(70.1%,148/211)and sepsis(43.6%,92/211)were the main clinical manifestations,and the average patient age was 47.2 years.Among patients of known age,the highest prevalence was observed in the 40-64 year age group,which accounted for 44.9%(44/98).Sixty-one cases had no other underlying diseases before infection.Reported cases of listeriosis occurred in 27 provinces(municipalities,and autonomous region)in China,and Beijing reported the most cases,accounting for 23.7%(164/693).L.monocytogenes was sensitive to β-lactam drug treatment but showed differing degrees of drug resistance.Among 145 cases,12 were resistant to penicillin,and 16 were resistant to oxacillin.Listeriosis is a foodborne disease with a high mortality rate,particularly among neonates.With the continuing emergence of drug-resistant strains,standardizing and strengthening prevention and treatment measures for this disease as early as possible are essential.

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

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.

In view of the characteristics of H5N6 subtype avian influenza virus(AIV)that it has both high pathogenicity and the risk of cross-species transmission,posing a serious threat to the poultry farming industry and public health security,in order to effectively prevent and control the spread of H5N6 avian influenza,a rapid,sensitive and specific detection technolo-gy was established in this study.The specific monoclonal antibodies against the neuraminidase N6 protein of avian influenza A virus subtype H5N6 were obtained through hybridoma and monoclonal antibody technology.These antibodies were coupled and labeled with carboxyl-functionalized fluorescent quantum dots,along with previously prepared specific antibodies against the hemagglutinin H5 protein.A rapid fluorescence immunochromatographic detection method for the H5N6 subtype of avian influ-enza virus was established according to the principle of double-antibody sandwich immunochromatography.This method a-chieved a detection sensitivity of 1 ng/mL for recombinant hemagglutinin H5 subtype protein and 0.1 ng/mL for recombinant neuraminidase N6 subtype protein.Moreover,the method exhibited no cross-reactivity with other influenza subtypes or patho-gens,such as Newcastle disease(ND),infectious bronchitis(IB),and infectious laryngotracheitis(ILT),thus demonstrating good specificity.The method effectively identified the highly pathogenic avian influenza virus H5 subtype and directly distin-guished the H5N6 subtype with good accuracy.The fluorescent quantum dot immunochromatographic typing detection method established herein met the sensitivity,specificity,and accuracy requirements for H5N6 subtype detection,and can be further used for rapid detection of the H5 and H5N6 subtypes of avian influenza virus.

ObjectiveTriple-negative breast cancer (TNBC) is the breast cancer subtype with the worst prognosis, and lacks effective therapeutic targets. Colony stimulating factors (CSFs) are cytokines that can regulate the production of blood cells and stimulate the growth and development of immune cells, playing an important role in the malignant progression of TNBC. This article aims to construct a novel prognostic model based on the expression of colony stimulating factors-related genes (CRGs), and analyze the sensitivity of TNBC patients to immunotherapy and drug therapy. MethodsWe downloaded CRGs from public databases and screened for differentially expressed CRGs between normal and TNBC tissues in the TCGA-BRCA database. Through LASSO Cox regression analysis, we constructed a prognostic model and stratified TNBC patients into high-risk and low-risk groups based on the colony stimulating factors-related genes risk score (CRRS). We further analyzed the correlation between CRRS and patient prognosis, clinical features, tumor microenvironment (TME) in both high-risk and low-risk groups, and evaluated the relationship between CRRS and sensitivity to immunotherapy and drug therapy. ResultsWe identified 842 differentially expressed CRGs in breast cancer tissues of TNBC patients and selected 13 CRGs for constructing the prognostic model. Kaplan-Meier survival curves, time-dependent receiver operating characteristic curves, and other analyses confirmed that TNBC patients with high CRRS had shorter overall survival, and the predictive ability of CRRS prognostic model was further validated using the GEO dataset. Nomogram combining clinical features confirmed that CRRS was an independent factor for the prognosis of TNBC patients. Moreover, patients in the high-risk group had lower levels of immune infiltration in the TME and were sensitive to chemotherapeutic drugs such as 5-fluorouracil, ipatasertib, and paclitaxel. ConclusionWe have developed a CRRS-based prognostic model composed of 13 differentially expressed CRGs, which may serve as a useful tool for predicting the prognosis of TNBC patients and guiding clinical treatment. Moreover, the key genes within this model may represent potential molecular targets for future therapies of TNBC.

This study analyzed and compared the epidemiological characteristics of foodborne listeriosis in the United States and China,to provide evidence for optimizing the listeriosis surveillance program in China.Descriptive statistical analysis was performed on the listeriosis monitoring data from 2009 to 2021 registered in the FDOSS system and the attribution estimates of Listeria monocytogenes(L.monocytogenes)from 2013 to 2021 published by IFSAC.Sporadic and outbreak data on listeriosis in China from the CNKI,Wanfang Medical,and CQVIP databases were collected.From 2009 to 2021,a total of 1 037 listeriosis cases were reported in the United States,including 902 hospitalizations and 165 deaths.The peak of cases caused by Lm con-taminated food was in July.The number of cases,hospitalizations,and deaths accounted for 18.4％(191/1 037),20.5％(185/902),and 22.4％(37/165)of the total,respectively.Most listeriosis outbreaks were attributed to three food groups:dairy products,vegetable crops,and fruits,with attribution percentages ranging from 73.8％to 89.6％.The overall incidence of list-eriosis in China was not high:619 cases were reported from 2009 to 2021,and only 177 cases were recorded in detailed inci-dence years;the maximum number of cases in 2018 was 26.A total of 220 cases were reported with detailed onset months;the highest number of cases in April was 30.Data on listeriosis cases in China are incomplete and sporadic,and only seven cases have been successfully traced to food.Listeriosis surveillance systems in the United States are relatively complete,and there are more foodborne outbreaks.Dairy products,vegetable row crops,and fruits are the most likely causes of disease outbreaks.Although only sporadic cases have been reported in China,China should take actions such as gradually improving multi-department coop-eration mechanisms,achieving data sharing and deepening data mining,and accelerating progress in the detection technology of food-borne pathogenic microorganisms,to ensure food safety and public health.