Current experimental and computational methods have limitations in accurately and efficiently classifying ion channels within vast protein spaces. Here we have developed a deep learning algorithm, GPT2 Ion Channel Classifier (GPT2-ICC), which effectively distinguishing ion channels from a test set containing approximately 239 times more non-ion-channel proteins. GPT2-ICC integrates representation learning with a large language model (LLM)-based classifier, enabling highly accurate identification of potential ion channels. Several potential ion channels were predicated from the unannotated human proteome, further demonstrating GPT2-ICC's generalization ability. This study marks a significant advancement in artificial-intelligence-driven ion channel research, highlighting the adaptability and effectiveness of combining representation learning with LLMs to address the challenges of imbalanced protein sequence data. Moreover, it provides a valuable computational tool for uncovering previously uncharacterized ion channels.

Objective To collect data on imported malaria cases in Jiangsu Province from 2019 to 2023 after malaria elimination and to analyze the current epidemic situation and prevention and control measures of imported malaria, discussing future prevention and control strategies. Methods Malaria case information for Jiangsu Province from 2019 to 2023 was extracted and downloaded from the China Information System for Disease Control and Prevention (CISDCP) as well as the Jiangsu Provincial malaria epidemic database. Statistical analysis was conducted using Stata 12.0 and SPSS 16.0 software. Results From 2019 to 2023, a total of 534 cases of malaria were directly reported online in Jiangsu Province, with annual cases numbering 244, 90, 32, 36, and 132 respectively, all being laboratory-confirmed imported malaria cases from abroad. During the COVID-19 pandemic from 2020 to 2022, the number of imported malaria cases significantly decreased, with several months reporting zero cases. Among the 534 malaria cases, the vast majority were individuals who had traveled to countries in sub-Saharan Africa and Southeast Asia for work, business, international studies, or tourism. Over the five years, the median, minimum, and maximum days for patients from onset of illness to health-seeking were 1(0,12), 1(0,8), 0(0,6), 0(0,10), and 1(0,18) days, with a statistically significant difference in health-seeking time among patients (Fisher's exact test, P=0.03). Over the past three years of the COVID-19 pandemic, compared to outside centralized isolation stations, malaria cases within centralized isolation stations were diagnosed in a shorter time (Fisher exact test, P=0.007). A total of 24 severe malaria cases were reported, with no deaths, including 23 cases of P. falciparum and 1 case of P. ovale. Conclusions After the elimination of malaria, imported malaria cases in Jiangsu Province have sharply decreased due to the impact of the COVID-19 pandemic. Malaria cases in centralized isolation stations (CIS) for COVID-19 control of Jiangsu Province are more likely to be promptly diagnosed, and the timeliness from onset to health-seeking among malaria patients returning from high-malaria areas improved. As COVID-19 prevention and control policies adjusted, there has been a sharp increase in imported malaria cases in 2023. It's still necessary to strengthen measures for malaria prevention and control and maintain the capacity to prevent malaria re-transmission in Jiangsu Province.

Objective To investigate the seasonal Aedes population fluctuation and the resistance of Aedes populations to common insecticides in Jiangsu Province in 2020, so as to provide insights into vector-borne infectious diseases control.. Methods One village was randomly sampled from each of Xinbei District of Changzhou City and Zhangjiagang County of Suzhou City in southern Jiangsu Province, Hai’an County of Nantong City and Yandu District of Yancheng City in Central Jiangsu Province, and Suining County of Xuzhou City and Sihong County of Suqian City in northern Jiangsu Province during the period between May and October, 2020. A small ponding container was sampled, and larval Aedes mosquitoes were collected using straws once each in early and late stages of each month. All larvae were bred in laboratory to adults for population identification. In addition, larval breeding were observed in all small ponding containers in and out of 30 households that were randomly sampled from six surveillance sites, and the larval mosquito density was estimated using Breteau index. Larval A. albopictus mosquitoes were sampled around Cuiyuan New Village in Jintan District of Changzhou City, and bred in laboratory to the first offspring generation, and the susceptibility of adult female mosquitoes to deltamethrin, lambda-cyhalothrin, malathion, and propoxur was tested using the filter-paper bioassay recommended by WHO. Results A total of 1 165 larval Aedes mosquitoes were captured from small ponding containers in six surveillance sites of Jiangsu Province in 2020, and all were identified as A. albopictus following eclosion. The largest number of Aedes larvae captured was found in July. A total of 1 152 households were investigated in six surveillance sites, and the mean Breteau indexes were 9.58, 13.20, 13.71, 13.20, 12.18 and 5.58 from May to October, respectively, while a high Aedes transmission risk was seen in Xinbei District of Changzhou City, with a higher Breteau index than in Suining (H = 23.667, P_adjusted = 0.001) and Sihong (H = 22.500, P_adjusted = 0.003) counties. The field-captured A. albopictus from Cuiyuan New Village in Jintan District of Changzhou City remained sensitive to malathion, but was resistant to propoxur, and developed high-level resistance to deltamethrin and lambda-cyhalothrin. Conclusions A. albopictus was present in southern, central and northern Jiangsu Province in 2020, and the larval density peaked in July. A. albopictus captured from Cuiyuan New Village in Jintan District of Changzhou City has developed high-level resistance to pyrethroid pesticides.

Objective To create risk predictive models of healthcare-seeking delay among imported malaria patients in Jiangsu Province based on machine learning algorithms, so as to provide insights into early identification of imported malaria cases in Jiangsu Province. Methods Case investigation, first symptoms and time of initial diagnosis of imported malaria patients in Jiangsu Province in 2019 were captured from Infectious Disease Report Information Management System and Parasitic Disease Prevention and Control Information Management System of Chinese Center for Disease Control and Prevention. The risk predictive models of healthcare-seeking delay among imported malaria patients were created with the back propagation (BP) neural network model, logistic regression model, random forest model and Bayesian model using thirteen factors as independent variables, including occupation, species of malaria parasite, main clinical manifestations, presence of complications, severity of disease, age, duration of residing abroad, frequency of malaria parasite infections abroad, incubation period, level of institution at initial diagnosis, country of origin, number of individuals travelling with patients and way to go abroad, and time of healthcare-seeking delay as a dependent variable. Logistic regression model was visualized using a nomogram, and the nomogram was evaluated using calibration curves. In addition, the efficiency of the four models for prediction of risk of healthcare-seeking delay among imported malaria patients was evaluated using the area under curve (AUC) of receiver operating characteristic curve (ROC). The importance of each characteristic was quantified and attributed by using SHAP to examine the positive and negative effects of the value of each characteristic on the predictive efficiency. Results A total of 244 imported malaria patients were enrolled, including 100 cases (40.98%) with the duration from onset of first symptoms to time of initial diagnosis that exceeded 24 hours. Logistic regression analysis identified a history of malaria parasite infection [odds ratio (OR) = 3.075, 95% confidential interval (CI): (1.597, 5.923)], long incubation period [OR = 1.010, 95% CI: (1.001, 1.018)] and seeking healthcare in provincial or municipal medical facilities [OR = 12.550, 95% CI: (1.158, 135.963)] as risk factors for delay in seeking healthcare among imported malaria cases. BP neural network modeling showed that duration of residing abroad, incubation period and age posed great impacts on delay in healthcare-seek among imported malaria patients. Random forest modeling showed that the top five factors with the greatest impact on healthcare-seeking delay included main clinical manifestations, the way to go abroad, incubation period, duration of residing abroad and age among imported malaria patients, and Bayesian modeling revealed that the top five factors affecting healthcare-seeking delay among imported malaria patients included level of institutions at initial diagnosis, age, country of origin, history of malaria parasite infection and individuals travelling with imported malaria patients. ROC curve analysis showed higher overall performance of the BP neural network model and the logistic regression model for prediction of the risk of healthcare-seeking delay among imported malaria patients (Z = 2.700 to 4.641, all P values < 0.01), with no statistically significant difference in the AUC among four models (Z = 1.209, P > 0.05). The sensitivity (71.00%) and Youden index (43.92%) of the logistic regression model was higher than those of the BP neural network (63.00% and 36.61%, respectively), and the specificity of the BP neural network model (73.61%) was higher than that of the logistic regression model (72.92%). Conclusions Imported malaria cases with long duration of residing abroad, a history of malaria parasite infection, long incubation period, advanced age and seeking healthcare in provincial or municipal medical institutions have a high likelihood of delay in healthcare-seeking in Jiangsu Province. The models created based on the logistic regression and BP neural network show a high efficiency for prediction of the risk of healthcare-seeking among imported malaria patients in Jiangsu Province, which may provide insights into health management of imported malaria patients.

Objective: To investigate the current status of malaria rapid diagnostic test (RDT) strips application and malaria laboratory technicians' evaluation about them at primary healthcare provider level in Jiangsu Province. Methods: From November to December 2016, 878 medical institutions and 118 CDCs of city, county and township/community level in Jiangsu Province were selected as study samples using stratified random sampling method. Self-designed questionnaire was distributed to investigate the institution's malaria work task, RDT strips application and evaluation status in 2015. We also investigated the socio-demographic information and collected the RDT strips evaluation score from the malaria laboratory technicians selected from the institutions investigated (one technician from each institution). Rank sum test was performed to compare the RDT strips evaluation scores between medical institutions and CDCs, and among different medical institutions and CDCs. Results: In 2015, 405 cases of malaria were reported, 362 200 person-time of malaria blood testing task was conducted, and 100 000 RDT strips were procured and provided for healthcare providers in Jiangsu province for free. Of the 996 healthcare institutions investigated, 628 used RDT strips in the year 2015 and the median (P₂₅, P₇₅) of RDT strips volume used in these institutions was 10 (2, 25). The volume of RDT strips used in CDCs (15 (5, 52)) was significantly higher than that in medical institutions (10 (2, 25), (Z=3.42, P=0.001)). The investigated CDCs gave higher score on RDT strips' testing time per operation (10 (8.5, 10)) than medical institutions (9(8, 10), (Z=-2.20, P=0.028)). The employers of 614 investigated malaria laboratory technicians used RDT strips in 2015. The median of the scores given by CDC malaria laboratory technicians for RDT strips in terms of testing time per operation, testing operation and results judgement difficulties were 10 (9, 10), 10 (9, 10) and 10 (9, 10), respectively, which were significantly higher than those from technicians of medical institutions (9 (8, 10), 9 (8, 10), 9 (8, 10), (Z values were -2.55, -2.97 and -2.96, respectively; P values were all less than 0.05)). Conclusion RDT strips had been widely performed in health institutions in Jiangsu Province. The amount of RDT strips used in CDCs was significantly higher than that in medical institutions. Primary-level institutions and malaria laboratory technicians generally recognized RDT strips' advantage for application in terms of testing time and operational procedure. CDCs and malaria laboratory technicians from them gave higher regards on RDT strips in terms of testing time per operation, testing operation and results judgement difficulties compared with that of medical institutions.

Objective To understand the integrated ability of parasitic disease prevention and control of professional person-nel of Jiangsu Province through the contest. Methods Totally 56 players from the whole province were selected,and all the players participated in the contest. The theory knowledge and skill scores were collected and the statistical analyses were con-ducted. Results The average theoretical score of the participants was 88.86±15.56 and the passing rate was 91.1％. The aver-age skill operating score was 69.16 ± 16.01 and the passing rate was 67.9％. The average Plasmodium microscopy score was 16.54±8.09 and the passing rate was 50％. The average helminth egg microscopy score was 34.27±10.66 and the passing rate was 67.9％. There were statistical differences among the age groups and different levels of schistosomiasis endemic situation (F =5.10,6.39,both P<0.01). The theoretical knowledge including schistosomiasis,malaria,hydatid disease and others and the score rates were 91.07％,90.94％,85.83％and 90.93％,respectively. The hydatid disease score rate was lower(χ2=19.17, P<0.01). The radar chart displayed that the score rates of tabletting and microscopy test in Kato-Katz film production ,malaria blood film production and microscopy test were all low. Conclusion In Jiangsu Province,the participants have higher score in the theory test. However,they have lower skill test score,especially in the parasite species identification. The operational skills still need to be strengthened for center for disease control(CDC)participants.

Objective To understand the malaria epidemic situation and characteristics in Jiangsu Province in 2015,so as to provide the evidence for malaria elimination. Methods The data of malaria cases in Jiangsu Province in 2015 were collected from China's routine diseases surveillance information system. Results Totally 405 imported cases were reported in Jiangsu Province in 2015,and the cases increased by 14.08％compared with those in 2014. All the malaria cases were imported,and 5 cases(1.23％)were from Southeast Asia and 400(98.77％)were from 25 African countries or regions. The imported malaria cases were reported in 13 cities across Jiangsu Province,where Taizhou,Lianyungang,Nantong,Huaian and Yangzhou cities accounted for 68.64％of all the cases in the province. Jiangsu Institute of Parasitic Diseases(JIPD)reference lab checked all the cases and classified 299 falciparum malaria cases,13 vivax malaria cases,18 quartan malaria cases,71 ovale malaria cas-es,and 4 mixed Plasmodium infection cases. Conclusions In Jiangsu Province,there are no local malaria cases for 4 consecu-tive years,but the imported cases are on the rise. Compared to 2014,the imported vivax cases increased significantly in 2015. It should be the key points to strengthen the surveillance of imported malaria cases,improve malaria diagnosis and treatment abili-ties for all levels of medical institutions,and promote the abilities of Plasmodium check,and focus survey and disposal of all Center for Disease Control(CDC)staffs across Jiangsu Province.

Objective To analyze data of fails among oncology inpatients from 2014 to 2015,and to explore the effects of the continuous quality improvement on management of falls among oncology inpatients.Methods According to data of falls among oncology inpatients in 2014,continuous quality improvement was carried out in prevention of falls,including health education,risk assessment process of falls and inter-department cooperation.Results One year after applying the continuous quality improvement for management of falls,the number and the rate of falls among oncology inpatients in the year of 2015 (Number=25,Rate=0.027‰) were significantly lower than those in 2014(Number=55,Rate=0.065‰,x2=15.195,P＜0.001).Conclusion Improvement of management protocol for falls can effectively reduce the rate of falls among oncology inpatients and ensure patient safety.

Objective To understand the population,density,seasonal fluctuation and nocturnal pattern of malaria vectors in Jiangsu Province,thus to provide evidences for malaria elimination in this province. Methods Seven counties(cities,dis?tricts)were selected as the monitoring sites for malaria vectors in Jiangsu Province from 2013 to 2015. The mosquitoes were cap?tured by human bait trapping in bed nets and mosquito?lured lamp overnight,and the seasonal fluctuation and nocturnal pattern of malaria vectors were observed. Results A total of 11 041 Anopheles sinensis mosquitoes were captured by the mosquito?lured lamps in 7 counties of Jiangsu Province from 2013 to 2015,and no An. anthropophagous was found. Among all the 7 monitoring sites,the number of An. sinensis captured in Sihong County was the most(6 742 mosquitoes),while that in Xuyu County was the least(34 mosquitoes). During this period,the density peaks of An. sinensis were the first half of July,the first half of August and the second half of July. A total of 2 421 An. sinensis were collected in 7 monitoring sites from 2013 to 2015 by human bait trapping in bed nets overnight. Among all the 7 monitoring sites,the captured number of An. sinensis in Sihong County was the most(1 085 mosquitoes),while that in Ganyu County was the least(13 mosquitoes). The nocturnal peak of An. sinensis was from 19:00 to 20:00 and 525 An. sinensis mosquitoes were captured during this period of time,which accounted for 21.68%of the total. Hereafter,the captured number of An. sinensis reduced over time. Conclusion The density of An. sinensis mosquitoes is still high in individual areas in Jiangsu Province,so the epidemic and vector monitoring still should be strengthened to prevent the local transmission of imported malaria.

Objective To analyze the channels of going abroad of imported malaria patients in Jiangsu Province,so as to provide the evidence for the control of imported malaria and health intervention for high?risk population. Methods The data of imported malaria cases in Jiangsu Province in 2015 were collected and the channels of going abroad were analyzed. The Quan?tum GIS 1.7.4 software was applied to map. Results Totally 405 imported cases were reported in Jiangsu Province in 2015, and the cases increased by 14.1%compared with those in 2014. All the patients were migrant workers. The migrant workers were mostly sent abroad by construction companies[43.21%(175/405)]. The dispatching companies were mainly concentrated in Taizhou,Lianyungang,Zhenjiang and Yangzhou cities,accounting for 6.17%(25/405),3.21%(13/405),2.72%(11/405) and 2.22%(9/405),respectively. Totally 176(43.46%)patients returned to China having accompanied workers,and 1.21%(9/745)of accompanied workers were found having symptoms of malaria later. Conclusions It is difficult to monitor malaria in overseas migrant works in Jiangsu Province. The channels of going abroad of migrant workers are various and complicated ,for?mulating the main difficulty and challenge of imported malaria control.