Objective This study aimed to investigate the seasonal variation of mosquitoes in Yantai, Shandong Province, and provide a scientific basis for mosquito and mosquito-borne disease control. Methods From March to November for each of the years between 2020 and 2023, adult mosquitoes were collected from different habitats, including parks, hospitals, urban residential areas, rural households and livestock sheds, in 13 counties of Yantai City using a mosquito trap lamp method, among which, female mosquitoes were separated and identified, and the numbers were counted. We used the circular distribution method to analyze the temporal distribution characteristics of mosquito density. Results The γ values obtained for mosquitoes in Yantai from 2020 to 2023, the distribution of mosquitoes in different habitats, and dominant mosquito species in different months showed strong seasonality, with values ranging from 0.7461 to 0.8531(P ＜ 0.05). The peak period of seasonal variation in mosquitoes occurred from June 28thto September 13th, with August 5thbeing identified as the peak day. The peak periods of seasonal variation in mosquitoes in residential areas, parks, hospitals, peasant households, and animals sheds were observed from June 24thto September 14th, June 25thto September 10th, June 22ndto September 12th, July 1stto September 9th, and July 2ndto September 17th, respectively, with corresponding peak days on August 4th,3rd, 2nd, 5th, and 9th, respectively. The peak periods of Culex pipiens pallens, Aedes albopictus, and Anopheles sinensis were from June 26thto September 11th, June 28thto September 17th, and July 12thto September 17th, respectively, with corresponding peak days on August 3rd,7th, and 14th, respectively. Conclusions Our findings in this study revealed that the peak of mosquito activity in Yantai was concentrated in early August, with a peak period extending from June 28thto September 13th, and there were differences between different habitats(with peak periods for rural households and livestock sheds occurring later than those in residential areas, parks, and hospitals). Moreover, with respect to the mosquito species, populations of Cx. pipiens pallens and Ae. albopictus peaked earlier than those of An. sinensis. Based on these findings, we recommend that city-wide mosquito control work should commence in late June, and include appropriate early prevention and control measures for key habitats, such as livestock sheds, and dominant mosquito species, such as Cx. pipiens pallens, to minimize the density of mosquito vectors and the risk of disease transmission.

End-stage liver disease (ESLD) covers the end-stage of acute and chronic liver diseases, mainly involving decompensated cirrhosis, various types of liver failure, and advanced liver cancer. Hepatocyte transplantation has shown promise in treating ESLD, but its clinical application is hampered by the shortage of donor hepatocytes. Cell therapy, an emerging effective treatment for ESLD, faces the same limitation due to scarce hepatocyte availability. Hepatocyte-like cells (HLCs), which are terminally differentiated cells, can be induced from both stem cells and somatic cells. As HLCs exhibit the morphology and function of primary hepatocytes, they offer a promising supplementary source of hepatocytes for cell therapy. First, we provide a background for the differentiation and maturation of primary hepatocytes. Subsequently, based on the current insights into the molecular pathways that regulate hepatocyte differentiation in vivo, we describe a strategy for establishing HLC derived from either stem cells or somatic cells. The key characteristics of these HLCs are also detailed. Furthermore, HLC offers therapeutic potential for liver failure, and HLC-based liver organoids and bioartificial liver systems have demonstrated the ability to provide liver functions, offering an innovative approach to treating various types of ESLD. Despite their promise, challenges such as efficiency in differentiation and functional maturation need to be addressed to improve the clinical application of HLCs. This review discusses these advancements and outlines the therapeutic potential and current challenges of HLC therapy for ESLD.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To establish a ultra-high performance liquid chromatography-tandem mass spectrometer(UPLC-MS/MS)method for determining the concentration of sotagliflozin in rat plasma and apply it to pharmacokinetic studies in rats.Methods Electrospray negative ion multi-reaction ion detection was used.Chromatographic column:EXT-C18(2.1 mm × 100.0 mm,2.7 μm);column temperature:45 ℃;mobile phase:5 mmol·L-1 ammonium acetate aqueous solution-acetonitrile;flow rate:0.35 mL·min-1;ion pairs:sotagliflozin m/z 483.3→315.1,dapagliflozin m/z 467.4→329.2;injection volume:6 μL,plasma samples were processed using methyl tert-butyl ether liquid-liquid extraction.Six male SD rats were administered a single oral dose of sogliflozin at 40 mg·kg-1,and detected the concentration of sogliflozin in plasma.Pharmacokinetic parameters were calculated using Drug And Statistics(DAS)2.1.1.Results Sotagliflozin showed good linearity within the range of 5-2 000 ng·mL-1,with intra-day and inter-day precision both less than 15％.The recovery rate,matrix effect,and stability were all within the specified range.Pharmacokinetic parameters:Cmax was(3 716.67±568.28)ng·mL-1,tmax was(1.00±0.32)h,t1/2 was(2.28±0.45)h,AUC0-t was(1.70 × 104±2 075.87)ng·mL-1·h.Conclusion This study established a method for determining the concentration of sotagliflozin in rat plasma,which is characterized by high sensitivity,rapid detection,and good repeatability.It is suitable for the determination of sotagliflozin concentration in plasma and pharmacokinetic studies.

Objective To establish a ultra-high performance liquid chromatography-tandem mass spectrometer(UPLC-MS/MS)method for determining the concentration of sotagliflozin in rat plasma and apply it to pharmacokinetic studies in rats.Methods Electrospray negative ion multi-reaction ion detection was used.Chromatographic column:EXT-C18(2.1 mm × 100.0 mm,2.7 μm);column temperature:45 ℃;mobile phase:5 mmol·L-1 ammonium acetate aqueous solution-acetonitrile;flow rate:0.35 mL·min-1;ion pairs:sotagliflozin m/z 483.3→315.1,dapagliflozin m/z 467.4→329.2;injection volume:6 μL,plasma samples were processed using methyl tert-butyl ether liquid-liquid extraction.Six male SD rats were administered a single oral dose of sogliflozin at 40 mg·kg-1,and detected the concentration of sogliflozin in plasma.Pharmacokinetic parameters were calculated using Drug And Statistics(DAS)2.1.1.Results Sotagliflozin showed good linearity within the range of 5-2 000 ng·mL-1,with intra-day and inter-day precision both less than 15％.The recovery rate,matrix effect,and stability were all within the specified range.Pharmacokinetic parameters:Cmax was(3 716.67±568.28)ng·mL-1,tmax was(1.00±0.32)h,t1/2 was(2.28±0.45)h,AUC0-t was(1.70 × 104±2 075.87)ng·mL-1·h.Conclusion This study established a method for determining the concentration of sotagliflozin in rat plasma,which is characterized by high sensitivity,rapid detection,and good repeatability.It is suitable for the determination of sotagliflozin concentration in plasma and pharmacokinetic studies.

OBJECTIVE: To compare the therapeutic efficacy of portal and tail vein transplantation of bone marrow-derived mesenchymal stem cells (BMSCs) against cholestatic liver fibrosis in mice. METHODS: BMSCs were isolated and co-cultured with starvation-activated hepatic stellate cells (HSCs). HSC activation markers were identified using immunofluorescence and qRT-PCR. BMSCs were injected into the liver tissues of bile duct ligation (BDL) mice via the tail and portal veins. Histomorphology, liver function, inflammatory cytokines, and the expression of key proteins were all determined in the liver tissues. RESULTS: BMSCs inhibited HSC activation by reducing α-SMA and collagen I expression. Compared to tail vein injection, DIL-labeled BMSCs injected through the portal vein maintained a high homing rate in the liver. Moreover, BMSCs transplanted through the portal vein resulted in greater improvement in liver color, hardness, and gallbladder size than did those transplanted through the tail vein. Furthermore, BMSCs injected by portal vein, but not tail vein, markedly ameliorated liver function, reduced the secretion of inflammatory cytokines, including TNF-α, IL-6, and IL-1β, and decreased α-SMA + hepatic stellate cell (HSC) activation and collagen fiber formation. CONCLUSION The therapeutic effect of BMSCs on cholestatic liver fibrosis in mice via portal vein transplantation was superior to that of tail vein transplantation. This comparative study provides reference information for further BMSC studies focused on clinical cholestatic liver diseases.
Animals ; Mice ; Mesenchymal Stem Cell Transplantation ; Liver Cirrhosis/etiology* ; Male ; Cholestasis/therapy* ; Mice, Inbred C57BL ; Hepatic Stellate Cells ; Mesenchymal Stem Cells

Objective To explore the relationship between bedtime procrastination and fear of missing out and the intervention effect of aerobic exercise on bedtime procrastination,so as to provide a theoretical basis and practical reference for remedying bedtime procrastination.Methods Totally 988 students were selected through random sampling and then surveyed with the bedtime procrastination scale and the fear of missing out scale.Correlation and regression analyses were performed to explore the relationship between bedtime procrastination and fear of missing out.A total of 36 students were recruited from the 988 students to participate in the exercise intervention and they were assigned into an exercise group and a control group by the random number table method,with 18 students in each group.The exercise group performed aerobic exercise for 12 weeks,while the control group maintained daily activities.The participants' scores on the bedtime procrastination scale and the fear of missing out scale were recorded before and after the intervention and compared.Results The fear of missing out was positively correlated with bedtime procrastination among college students(r=0.214,P<0.001),and it was an important predictive factor for bedtime procrastination(β=0.241,P<0.001).After the intervention,the scores of bedtime procrastination scale decreased in the exercise group(t=2.277,P=0.036),while there was no significant difference in the scores of the control group before and after intervention(t=-0.787,P=0.442).Conclusions A high level of fear of missing out indicates severe bedtime procrastination.And 12-week exercise intervention could remedy bedtime procrastination.
Humans ; Fear ; Exercise ; Male ; Female ; Procrastination ; Young Adult ; Cross-Sectional Studies ; Students/psychology* ; Adult ; Surveys and Questionnaires ; Adolescent

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique