ObjectiveTo analyze the incidence and spatiotemporal distribution of typhus fever in Baoshan City, Yunnan Province from 2005 to 2023, to identify high-risk populations and regions, so as to provide a scientific basis for optimizing the allocation of local prevention and control resources and developing targeted intervention measures. MethodsData of typhus fever cases in Baoshan City from 2005 to 2023 were obtained from the Infectious Disease Information Management System of the Chinese Center for Disease Control and Prevention. Descriptive epidemiological methods were used to analyze the temporal, spatial and demographic distribution of typhus fever cases. Spatial clustering was assessed using spatial dynamic window scan statistics (circular and elliptical windows), flexible spatial scan statistics, and local spatial autocorrelation methods (including local Moran’s I, local Geary’s C, and Getis-Ord G_i*). Retrospective spatiotemporal scan statistics were employed to detect spatiotemporal clusters. ResultsA total of 1 099 typhus fever cases were reported in Baoshan City from 2005 to 2023. The incidence rate peaked at 6.31/ 100 000 in 2007, followed by a decline until reaching its lowest level at 0.21/100 000 in 2015 , and subsequently rebounded during 2016‒2023. The highest proportion of cases was among children under 10 years of age (31.12%), and the top three occupations of cases were farmers, students, and children, accounting for 88.62% of all cases. Cases occurred predominantly between June and September each year. The incidence was relatively high in Jiucheng Town (62.58/100 000), Yaoguan Town (57.15/100 000), and Dianyang Town (46.81/100 000) of Shidian County. Spatial clustering analyses indicated that high-risk areas were mainly located in the southern part of Baoshan City, showing a south-to-north trend. Spatiotemporal scan analyses identified five clusters, with the most likely cluster centered around Yaoguan Town, covering ten towns (subdistricts) during the period 2007‒2010. ConclusionThe incidence of typhus fever in Baoshan City exhibits a clear seasonal and spatial clustering pattern, with peak incidence occurring in summer and autumn. Spatially, cases are primarily distributed in the southern part of Baoshan City, and high-risk clusters exhibit a south-to-north trend. Farmers, students, and children are the high-risk groups.

Objective To explore the application value of artificial intelligence in medical research assistance, and analyze the key paths to achieve precise execution of model instructions, improvement of model interpretation completeness, and control of hallucinations. Methods Taking esophageal cancer research as the scenario, five types of literature including research articles, case reports, reviews, editorials, and guidelines were selected for model interpretation tests. The model performance was systematically evaluated from five dimensions: recognition accuracy, format accuracy, instruction execution accuracy, content reliability rate, and content completeness index. The performance differences of Ruibin Agent, GPT-4o, Claude 3.7 Sonnet, DeepSeek V3, and DouBao-pro models in medical literature interpretation tasks were compared. Results A total of 15 studies were included, with 3 studies of each type. The five models collectively conducted 1 875 tests. Due to the poor recognition accuracy of the editorial type, the overall recognition accuracy of Ruibin Agent was significantly lower than other models (92.0% vs. 100.0%, P＜0.001). In terms of format accuracy, Ruibin Agent was significantly better than Claude 3.7 Sonnet (98.7% vs. 92.0%, P=0.002) and GPT-4o (98.7% vs. 78.9%, P＜0.001). In terms of instruction execution accuracy, Ruibin Agent was better than GPT-4o (97.3% vs. 80.0%, P＜0.001). In terms of content reliability rate, Ruibin Agent was significantly lower than Claude 3.7 Sonnet (84.0% vs. 92.0%, P=0.010) and DeepSeek V3 (84.0% vs. 94.7%, P＜0.001). In terms of content completeness index, the median scores of Ruibin Agent, GPT-4o, Claude 3.7 Sonnet, DeepSeek V3, and DouBao-pro were 0.71, 0.60, 0.85, 0.74, and 0.77, respectively. Conclusion Ruibin Agent has significant advantages in terms of formatted interpretation of medical literature and instruction execution accuracy. In the future, it is necessary to focus on optimizing the recognition ability of editorial types, strengthening the coverage ability of core elements of various types of literature to improve interpretation completeness, and improving content reliability through optimizing the confidence mechanism to ensure the rigor of medical literature interpretation.

Objective To investigate the effect of body position angle on gastric insufflation during the induction of general anesthesia in pediatric patients undergoing day surgery.Methods A total of 111 children scheduled for elective tracheal intubation under general anesthesia at the First Affiliated Hospital of Guangxi Medical University from December 2022 to March 2023 were selected as study subjects.Six children were ex-cluded due to unclear sonographic visualization of the gastric antrum,resulting in 105 children ultimately in-cluded in the study.The children were divided into three groups using a random number table method:Group D0(supine position),Group D5(5° head-up position),and Group D10(10° head-up position),with 35 children in each group.The presence of a"comet-tail artifact"on ultrasound was used as the criterion for determining gastric insufflation during anesthesia induction.The gastric antrum cross-sectional area(CSA)of the gastric antrum was measured before mask ventilation after loss of consciousness(T1)and immediately after tracheal intubation following mask ventilation(T2).The incidence of gastric insufflation,changes in CSA and their differences,and vital sign changes at T1 and T2,were compared among the three groups.Results Compared with Group D0,the incidence of gastric insufflation was significantly lower in Groups D5 and D10[25.7％(9/35)vs.20.0％(7/35)vs.54.0％(19/35)],and the difference was statistically significant(P＜0.05).Howev-er,there was no significant difference between Group D5 and Group D10(P＞0.05).No significant difference was observed in CSA at T1 among the three groups(P＞0.05).At T2,a statistically significant difference in CSA was found among the three groups(P＜0.05),with Group D10 showing a smaller CSA than Group D0(P＜0.05).The difference in CSA changes was statistically significant among the three groups(P＜0.05),with Groups D5 and D10 exhibiting smaller changes than Group D0,and Group D10 showing a smaller change than Group D5(P＜0.05).No significant differences were observed in mean artery pressure(MAP),heart rate,pulse oxygen saturation(SpO2)and pressure of end-tidal carbon dioxide(PETCO2)at T1 and T2 among the three groups(P＞0.05).A total of 6 children(5.7％)required brief adjustments in jaw support due to irregular PETCO2 waveforms or abnormal peak airway pressure.Conclusion In pediatric patients undergoing day sur-gery under general anesthesia,a 5° head-up position during induction significantly reduces the incidence of gas-tric insufflation and minimizes changes in gastric antral CSA,while a 10° head-up position does not provide ad-ditional benefits.

Protein liquid-liquid phase separation (LLPS), a pivotal phenomenon intricately linked to cellular processes, is regulated by various other proteins. However, there is still a lack of high-throughput methods for screening protein regulators of LLPS in target proteins. Here, we developed a CRISPR/Cas9-based screening method to identify protein phase separation regulators by integrating bimolecular fluorescence complementation (BiFC) and fluorescence-activated cell sorting (FACS). Using this newly developed method, we screened the RNA-binding proteins that regulate PABPN1 phase separation and identified the tumor suppressor QKI as a promoter of PABPN1 phase separation. Furthermore, QKI exhibits decreased expression levels and diminished nuclear localization in colorectal cancer cells, resulting in reduced PABPN1 phase separation, which, in turn, promotes alternative polyadenylation (APA), cell proliferation, and migration in colorectal cancer.
Humans ; Colorectal Neoplasms/genetics* ; RNA-Binding Proteins/genetics* ; Poly(A)-Binding Protein I/genetics* ; CRISPR-Cas Systems ; Flow Cytometry ; Cell Proliferation ; Cell Line, Tumor ; Cell Movement

Prostate cancer is the second most common cancer in men, accounting for 14.1% of new cancer cases in 2020. The aggressiveness of prostate cancer is highly variable, depending on its grade and stage at the time of diagnosis. Despite recent advances in prostate cancer treatment, some patients still experience recurrence or even progression after undergoing radical treatment. Accurate initial staging and monitoring for recurrence determine patient management, which in turn affect patient prognosis and survival. Classical imaging has limitations in the diagnosis and treatment of prostate cancer, but the use of novel molecular probes has improved the detection rate, specificity, and accuracy of prostate cancer detection. Molecular probe-based imaging modalities allow the visualization and quantitative measurement of biological processes at the molecular and cellular levels in living systems. An increased understanding of tumor biology of prostate cancer and the discovery of new tumor biomarkers have allowed the exploration of additional molecular probe targets. The development of novel ligands and advances in nano-based delivery technologies have accelerated the research and development of molecular probes. Here, we summarize the use of molecular probes in positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), optical imaging, and ultrasound imaging, and provide a brief overview of important target molecules in prostate cancer.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Molecular Probes ; Molecular Imaging/methods* ; Magnetic Resonance Imaging ; Positron-Emission Tomography ; Tomography, Emission-Computed, Single-Photon ; Ultrasonography ; Optical Imaging ; Biomarkers, Tumor ; Precision Medicine/methods*

BACKGROUND:Osteoporosis is defined as a chronic metabolic bone disease,and a large amount of evidence has shown that gut microbiota is involved in osteoporosis.However,the causal relationship between gut microbiota and osteoporosis is yet unclear.OBJECTIVE:To evaluate the potential causal relationship between gut microbiota and osteoporosis using the two-sample Mendelian randomization.METHODS:Pooled statistics from the MiBioGen Consortium's Genome-Wide Association Analysis(GWAS)of gut microbiota and GWAS data from the UK Biometric Sample database for osteoporosis were used.Inverse variance weighting(IVW),MR-Egger regression,weighted median,weighted model and simple model were used to study the causal relationship between gut microbiota and osteoporosis.Sensitivity analysis was used to test whether the results of Mendelian randomization are reliable.RESULTS AND CONCLUSION:The inverse variance weighted method showed that there was a causal relationship between gut microbiota and osteoporosis.Among them,the R7 genus of Christensenaceae(MR Egger:β=-0.007;IVW:β=-0.004,P=0.028),Coprococus 3(MR Egger:β=-0.008;IVW:β=-0.003,P=0.046)and Trichospirillum(MR Egger:β=-0.009;IVW:β=-0.004,P=0.003)may be protective factors for osteoporosis,while Hotella(MR Egger:β=0.006;IVW:β=0.002,P=0.033)and Eubacterium oxyoxide(MR Egger:β=0.001;IVW:β=0.003,P=0.046)may be potential risk factors for osteoporosis.Eubacterium oxyoxide and Hotella can increase the risk of osteoporosis,while R7 of Christensenaceae,Coprococcus 3 and Spirillum can reduce the risk of osteoporosis.Whether this conclusion also applies to non-European populations will need to be verified in the future by large clinical trials in different groups.

Objective:To explore the distribution of Traditional Chinese Medicine constitution among patients with impaired awareness of hypoglycemia (IAH) and identify risk factors for IAH in patients with diabetes mellitus, to develop a risk prediction model. The aim is to validate the models′ predictive accuracy to facilitate early prevention and treatment of IAH.Methods:A case control study employing convenience sampling model was conducted on 1351 hospitalized patients with diabetes mellitus in the endocrinology departments of Changshu Hospital Affiliated to Nanjing University of Chinese Medicine and Affiliated Hospital of Jiangsu University, between August 2021 and December 2023. Traditional Chinese medicine constitution types were determined using the Traditional Chinese Medicine Constitution Classification and Judgment (ZYYXH/T157-2009). Data were divided into training and test sets at a ratio of 7∶3. Two prediction models were developed: Model 1, a conventional IAH prediction model for patients with diabetes mellitus, and Model 2, an IAH prediction model for patients with diabetes mellitus incorporating traditional Chinese medicine constitution. Nomograms were drawn for both models. The Hosmer-Lemeshow goodness-of-fit test, calibration curve, receiver operating characteristic (ROC) curve, and area under the curve (AUC) were calculated to evaluate the effectiveness of models 1 and 2. The improvement in prediction performance between Models 1 and 2 was assessed using Delong test, AUC, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).Results:The study included 1 283 patients with diabetes mellitus, including 578 males and 705 females, aged (59.61 ± 14.09) years. The incidence of IAH among patients with diabetes mellitus was 20.50% (263/1283), with yang deficiency constitution being the most prevalent traditional Chinese medicine constitution type, at 47.53% (125/263). Multivariate analysis revealed that age, body mass index, course of diabetes, neurological hypoglycemia symptoms, hypoglycemia symptoms and severe hypoglycemia history were the influencing factors of Model 1 (all P<0.05); age, body mass index, neurological hypoglycemic symptoms, hypoglycemic symptoms, history of severe hypoglycemia, and traditional Chinese medicine constitution were the influencing factors of Model 2 (all P<0.05). The Hosmer-Lemeshow goodness-of-fit test showed a good fit of Model 2 [training set ( χ2=8.48, P>0.05), test set ( χ2=3.92, P>0.05)]. The Delong test results showed that the AUC for Model 2 was 0.96 for both the training and test sets, significantly higher than the AUCs of the 0.90 and 0.91 for Model 1 ( Z=-7.27, -3.70, both P<0.01). Furthermore, NRI was 0.66 ( 95%CI 0.53-0.79, P<0.01) and IDI was 0.02 (95% CI 0.01-0.03, P<0.05) for Model 2. Comparative analysis of clinical utility demonstrated that the net benefit of Model 2 for predicting IAH in patients with diabetes mellitus surpassed that of Model 1 across threshold probabilities ranging from 5% to 100%. Conclusions:The study constructed a nomogram prediction model included traditional Chinese medicine constitution with good predictive performance for IAH in patients with diabetes mellitus, and is of significant clinical value for identifying high-risk IAH populations.IAH patients mainly have a biased constitution, indicating that medical staff can reduce the incidence of IAH by improving the patients′ constitution.

Mussel adhesive protein (MAP) is increasingly utilized in the biomedical field for the development of various bio-inspired products such as adhesives, protective films, and coatings with diverse properties, owing to its excellent biocompatibility, low immunogenicity, broad-spectrum adhesiveness, and biodegradability. The biological effects and mechanisms of MAP include adhesive film formation, cell migration and proliferation, anti-inflammatory and antioxidant activities, and inhibition of pigment formation. In dermatological applications, MAP demonstrates a significant potential in antibacterial and antipruritic effects, wound healing, barrier repair, and scar regeneration. In recent years, advances in understanding the secretion, distribution, and adhesion mechanisms of MAP, along with innovations in extraction methods, have led to the development of various natural MAP, recombinant MAP, mussel-inspired, and mussel-mimetic biomedical products. However, the biosafety, tissue compatibility, and functionality of these products remain subjects of debate. Further investigation is needed to elucidate the interactions between MAP-based products and various organ tissues and cells within complex biological systems, as well as to thoroughly evaluate their safety and efficacy. Such efforts are essential to achieve high-value utilization of MAP and to explore broader application prospects. Future research may focus on integrating MAP with emerging technologies such as nanotechnology and smart materials to further develop its multifunctional applications in the field of dermatology.

Objective:To explore the distribution of Traditional Chinese Medicine constitution among patients with impaired awareness of hypoglycemia (IAH) and identify risk factors for IAH in patients with diabetes mellitus, to develop a risk prediction model. The aim is to validate the models′ predictive accuracy to facilitate early prevention and treatment of IAH.Methods:A case control study employing convenience sampling model was conducted on 1351 hospitalized patients with diabetes mellitus in the endocrinology departments of Changshu Hospital Affiliated to Nanjing University of Chinese Medicine and Affiliated Hospital of Jiangsu University, between August 2021 and December 2023. Traditional Chinese medicine constitution types were determined using the Traditional Chinese Medicine Constitution Classification and Judgment (ZYYXH/T157-2009). Data were divided into training and test sets at a ratio of 7∶3. Two prediction models were developed: Model 1, a conventional IAH prediction model for patients with diabetes mellitus, and Model 2, an IAH prediction model for patients with diabetes mellitus incorporating traditional Chinese medicine constitution. Nomograms were drawn for both models. The Hosmer-Lemeshow goodness-of-fit test, calibration curve, receiver operating characteristic (ROC) curve, and area under the curve (AUC) were calculated to evaluate the effectiveness of models 1 and 2. The improvement in prediction performance between Models 1 and 2 was assessed using Delong test, AUC, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).Results:The study included 1 283 patients with diabetes mellitus, including 578 males and 705 females, aged (59.61 ± 14.09) years. The incidence of IAH among patients with diabetes mellitus was 20.50% (263/1283), with yang deficiency constitution being the most prevalent traditional Chinese medicine constitution type, at 47.53% (125/263). Multivariate analysis revealed that age, body mass index, course of diabetes, neurological hypoglycemia symptoms, hypoglycemia symptoms and severe hypoglycemia history were the influencing factors of Model 1 (all P<0.05); age, body mass index, neurological hypoglycemic symptoms, hypoglycemic symptoms, history of severe hypoglycemia, and traditional Chinese medicine constitution were the influencing factors of Model 2 (all P<0.05). The Hosmer-Lemeshow goodness-of-fit test showed a good fit of Model 2 [training set ( χ2=8.48, P>0.05), test set ( χ2=3.92, P>0.05)]. The Delong test results showed that the AUC for Model 2 was 0.96 for both the training and test sets, significantly higher than the AUCs of the 0.90 and 0.91 for Model 1 ( Z=-7.27, -3.70, both P<0.01). Furthermore, NRI was 0.66 ( 95%CI 0.53-0.79, P<0.01) and IDI was 0.02 (95% CI 0.01-0.03, P<0.05) for Model 2. Comparative analysis of clinical utility demonstrated that the net benefit of Model 2 for predicting IAH in patients with diabetes mellitus surpassed that of Model 1 across threshold probabilities ranging from 5% to 100%. Conclusions:The study constructed a nomogram prediction model included traditional Chinese medicine constitution with good predictive performance for IAH in patients with diabetes mellitus, and is of significant clinical value for identifying high-risk IAH populations.IAH patients mainly have a biased constitution, indicating that medical staff can reduce the incidence of IAH by improving the patients′ constitution.

Perception of recurrence risk in cardiovascular disease (CVD) patients plays a significant role in aspects such as their quality of life and treatment adherence. This paper reviews the theoretical foundations of recurrence risk perception, the conceptual origins and developmental process, measurement tools, influencing factors of recurrence risk perception in CVD patients, and research progress of recurrence risk perception in CVD management. The aim is to provide a basis for developing scientifically effective intervention measures for CVD patients in the future.