Background Meteorological factors are among the key extrinsic triggers for the onset and exacerbation of cardiovascular and cerebrovascular diseases (CVD). Against the backdrop of sustained global warming, elucidating the impact of ambient temperature and atmospheric pressure on CVD, especially on pre-hospital CVD emergent events, has become imperative for evidence-based prevention and emergency preparedness. Objective To quantify the temporal trends of daily mean temperature and atmospheric pressure and their associations with pre-hospital CVD emergent events in Yantai, and to explore effect modification by demographic subgroups and geographic areas, thereby providing an empirical basis for the rational allocation of emergency medical resources. Methods Pre-hospital CVD emergency data from January 1, 2016 to December 31, 2022 were selected from the Yantai 120 Emergency Medical Command System. Synchronous meteorological factors and environmental pollutant data were obtained from the websites of the National Oceanic and Atmospheric Administration and the National Centers for Environmental Information of the United States. Time-series analysis combined with distributed lag non-linear model was used to analyze the association between daily temperature, atmospheric pressure, and pre-hospital CVD emergencies. Average annual percentage changes (AAPC) were calculated using Joinpoint (version 5.2.0.0) to reflect temporal trends. Spearman correlation analysis was employed to screen variables with low collinearity for inclusion in the multi-pollutant adjusted models. Results From 2016 to 2022, a total of 268275 pre-hospital CVD emergency cases were recorded in Yantai City, showing an increasing annual trend (AAPC=7.16%, P=0.002). Emergency volume, daily temperature, atmospheric pressure, and PM₁₀ displayed marked seasonal patterns, with summer bottoms and winter peaks for emergencies, daily temperature higher in summer and lower in winter, and the inverse for atmospheric pressure. Correlation analysis showed that both daily temperature and atmospheric pressure were positively correlated with O₃, with correlation coefficients of 0.745 and 0.723, respectively; negatively correlated with PM_2.5, with correlation coefficients of −0.246 and −0.235, respectively; and negatively correlated with PM₁₀, with correlation coefficients of −0.241 and −0.229, respectively (P < 0.05). A U-shaped correlation was revealed between daily temperature and pre-hospital CVD emergency risk. Using 24 °C as the reference, risk was elevated at both low and high daily temperatures, with the strongest cold effect at –11 ℃ (RR=1.53, 95%CI: 1.35, 1.73) and strongest heat effect at 30 ℃ (RR=1.06, 95%CI: 1.01, 1.11); cold effects were prolonged (lag0–14d) compared to heat effects. Atmospheric pressure exhibited a positive association with emergencies; using a median of 1012.2 hPa as the reference, the maximum risk occurred at 1037 hPa (RR=1.25, 95%CI: 1.03, 1.52), with a 0–5 d lag. In the subgroup analysis, the impact of low temperature was more pronounced among females (RR_{−9 ℃}=1.66), people over 60 years (RR_{−9 ℃}=1.91), and rural residents (RR_{−9 ℃}=1.76). High atmospheric pressure significantly increased the risk of pre-hospital CVD emergency among females (RR_{1035 hPa}=1.54), people under 18 years (RR_{1035 hPa}=3.62), and rural residents (RR_{1035 hPa}=1.46). The sensitivity analysis results indicated that, after excluding the impact of pandemic and the degrees of freedom for time variations, the effects of daily average temperature and atmospheric pressure on pre-hospital CVD emergency volume were consistent with the primary analysis findings. Conclusion Both non-optimal temperature and atmospheric pressure significantly increase the pre-hospital CVD emergency volume; therefore, emergency medical services should develop targeted response protocols, optimize resource allocation, and intensify public health education to mitigate the pre-hospital burden attributable to temperature and pressure fluctuations.

Pitch abnormalities are a common manifestation of various voice disorders, with complex pathophysiological mechanisms involving changes in vocal fold tension, mass, and neuromuscular dysfunction of the larynx. This study aims to investigate the underlying physiological mechanisms of pitch-related disorders and explore diagnostic and therapeutic approaches, providing insights for clinical management.
Humans ; Voice Disorders/therapy* ; Vocal Cords/physiopathology*

The paper presents a case of 69-year-old male with marginal zone lymphoma (MZL) manifesting as acute kidney injury (AKI) requiring emergency hemodialysis. The patient presented with fever, fatigue and rapidly progressive renal dysfunction, and serum creatinine was 1 105 μmol/L. Emergency central venous catheterization and hemodialysis were performed. Serum immunofixation electrophoresis revealed monoclonal IgM and λ light chain positivity. Autoantibody testing showed positivity for both anti-SSA and anti-SSB antibodies. Renal biopsy demonstrated interstitial infiltration by atypical B lymphocytes with λ light chain restriction. The diagnosis of MZL was confirmed by bone marrow biopsy. Following hemodialysis and chemotherapy with bendamustine plus rituximab, renal function significantly improved and remained stable during follow-up. This case highlights that AKI may serve as the initial manifestation of lymphoma, underscoring the importance of considering hematologic malignancies in the differential diagnosis of unexplained renal failure.

The paper presents a case of 69-year-old male with marginal zone lymphoma (MZL) manifesting as acute kidney injury (AKI) requiring emergency hemodialysis. The patient presented with fever, fatigue and rapidly progressive renal dysfunction, and serum creatinine was 1 105 μmol/L. Emergency central venous catheterization and hemodialysis were performed. Serum immunofixation electrophoresis revealed monoclonal IgM and λ light chain positivity. Autoantibody testing showed positivity for both anti-SSA and anti-SSB antibodies. Renal biopsy demonstrated interstitial infiltration by atypical B lymphocytes with λ light chain restriction. The diagnosis of MZL was confirmed by bone marrow biopsy. Following hemodialysis and chemotherapy with bendamustine plus rituximab, renal function significantly improved and remained stable during follow-up. This case highlights that AKI may serve as the initial manifestation of lymphoma, underscoring the importance of considering hematologic malignancies in the differential diagnosis of unexplained renal failure.

Humans ; Amyloidosis ; Amyloid ; Cardiomyopathies

Objective To evaluate the molluscicidal effect and cost of spraying molluscicides with drones against Oncomelania hupensis snails in marshland and lake areas, so as to provide new insights into field snail control in China. Methods A marshland and lake setting measuring approximately 12 000 m² was selected in Wanzhi District, Wuhu City on June 2023 as the test field, and assigned to four groups, of 3 000 m² in each group. Environmental cleaning was not conducted in groups A or B, which were given 5% niclosamide ethanolamine salt granules sprayed with knapsack-type sprayers and drones at a dose of 40 g/m², and environmental cleaning was conducted in groups C and D, which were given 5% niclosamide ethanolamine salt granules sprayed with drones and knapsack-type sprayers at a dose of 40 g/m², respectively. O. hupensis snails were surveyed before chemical treatment and 1, 3, 5, 7, 14 days post-treatment. The uniformity of chemicals was determined on the day of treatment, and the snail mortality, corrected snail mortality and density of living snails were calculated and compared among groups. The cost of molluscicides, labor fees of environmental cleaning and chemical treatment and cost of equipment were calculated, and the cost for a 1% reduction in the mean density of living snails was calculated 14 days post-treatment. Results The mean densities of living snails and mortality rates of snails were 1.82 to 2.85 snails/0.1 m² and 1.41% to 2.94% in groups A, B, C and D before chemical treatment, and the mortality and corrected mortality of snails were 55.75%, 49.32%, 85.94% and 87.50%, and 55.00%, 48.47%, 85.70% and 87.29% in groups A, B, C and D 14 days post-treatment. There was a significant difference in the mortality of snails among the four groups 14 days post-treatment (χ² = 38.735, P < 0.005), and there was a higher snail mortality in Group D than in Group A (χ² = 16.876, P < 0.005), and higher in Group C than in Group B (χ² = 20.508, P < 0.005). The density of living snails reduced by 55.00%, 43.94%, 90.43% and 87.14% 14 days post-treatment relative to pre-treatment in groups A, B, C and D, respectively. The test for uniformity of chemicals showed that the mean dose of molluscicides were 57.34, 55.21, 40.19 g/m² and 32.37 g/m² in groups A, B, C and D, respectively, and the minimal standard deviation (7.07) and coefficient of variation (0.18) of mean doses were seen in Group C. The costs for chemical treatment were 0.33 Yuan in groups A and B and 1.53 Yuan in groups C and D, respectively. The costs for a 1% reduction in the mean density of living snails were 17.82, 22.47, 50.73 Yuan and 52.56 Yuan in groups A, B, C, and D 14 days post-treatment, respectively. Conclusions The molluscicidal effect and cost of spraying 5% niclosamide ethanolamine salt granules with drones are comparable to manual spraying, and chemical treatment with drones are high in uniformity of molluscicides, time- and labor-saving, and feasible for applications in complex environments, which deserves widespread applications in the field of snail control.

In order to understand the prevalence and genetic variation of H9N2 subtype avian influ-enza virus in Shandong,a total 492 tracheal and lung tissue samples collected from chicken farms with respiratory symptoms in partial areas in Shandong were detected by H9 subtype AIV real-time RT-PCR,and the positive samples were inoculated with chicken embryos for two generations.Whole genome sequences of the positive strains by applying Illumina Miaseq platform,and genetic evolution and mutation at positions associating with viral pathogenicity and transmissibility were analyzed.The results showed that there were 72 samples were positive for H9 subtype AIV among the 492 samples,with a positive rate of 14.63％.Thirty-four strains of H9 subtype AIV were ob-tained from the positive samples after passing through chicken embryo,meanwhile,the 34 isolates were all H9N2 subtype AIV by whole genome sequencing analysis.By analyzing the evolutionary tree of HA and NA genes,HA and NA genes of the 34 H9N2 AIV strains belonged to Y280-like branch and F/98-like branch,respectively.Meanwhile,based on above branches,there were obvious time node subbranch,which one was"isolates before 2013",another one was"isolates after 2013".The HA cleavage sites of thirty-four H9N2 strains were all 325PSRSSR↓GLF333,which met the se-quence characteristics of the lowly pathogenic avian influenza virus,and the HA receptor binding site 226 amino acid was leucine,which had the characteristics of blinding to a-2,6 mammalian sialic acid receptors.Among the internal amino acid sites that are key to mammalian adaptation,all strains had an I368V mutation in the PB1 gene that enhanced viral transmissibility in mammals and the PB2 genes of some strains were mutated to enhance the mammalian adaptation of I292 V and A588 V.The above results illustrated that the H9N2 subtype AIV gene segments in Shandong have different degrees of recombination and gene variation,so it is necessary to strengthen the monito-ring of virus variation.

Objective: To explore the value of vector angle of Lorenz plots(LPs) and the role of combining B-line slope in improving the diagnostic efficiency of arrhythmia． Methods: LPs of 119 cases with ventricular premature contraction (VPC group ) ，97 cases with supraventricular premature contraction(SPC group) ，52 cases with type II°I atrioventricular block ( Ⅱ ° Ⅰ group) and 54 cases with type Ⅱ ° Ⅱ atrioventricular / sinoatrial block ( Ⅱ ° Ⅱ group) were retrospectively analyzed．The B-line slope and vector angle were measured，and the differences between groups were compared. Receiver operating characteristic curve was used to analyze the diagnostic efficacy of B-line slope，vector angle and their combination between groups ，and MedCalc software was used for statistical comparison．The consistency of intra-observer and inter-observer measurements of B-line slope and vector angle was evaluated using Intra group correlation coefficient (ICC) and Bland-Altman plot. Results: There were significant differences between VPC group and SPC group，and between Ⅱ ° Ⅰ group and II°II group (P＜0. 05) ．The area under the curve (AUC) of B-line slope，vector angle，and the combination of the two in distinguishing ventricular and supraventricular premature contraction were 0. 81，0. 84 and 0. 87 respectively，and the AUC in distinguishing type Ⅱ ° Ⅰ and type Ⅱ ° Ⅱ atrioventricular / sinoatrial block were 0. 76，0. 78 and 0. 80 respectively．The ICC of vector angle was better than B-line slope (Intra-observer 0. 99 vs 0. 98，Inter-observer 0. 97 vs 0. 96) ． Conclusion Vector angle can be used to identify the type of arrhythmia，and has good intraobserver and interobserver consistency．Its combination with B-line slope has the highest accuracy in diagnosing arrhythmia，providing a new reference for clinical diagnosis and treatment.

Objective:To provide a basis for the selection of antiemetic regimen by establishing an artificial intelligence model for predicting chemotherapy-induced nausea and vomiting (CINV) in cancer patients receiving platinum-based chemotherapy with high emetic risk.Methods:The clinical information on cancer patients who received cisplatin or carboplatin with area under the blood concentration-time curve (AUC) ≥4 and registered in the Department of Oncology, Tianjin Medical University General Hospital from January 2018 to December 2022 was collected, including gender, age, history of alcohol consumption, history of vomiting in pregnancy, chemotherapy cycle, patient expects to have CINV, chemotherapeutic agents, antiemetic regimen, out-of-hospital antiemetic treatment, sleep of less than 7 hours on the night before chemotherapy, occurrence of CINV in the previous cycle, and creatinine clearance (Ccr). After pre-processing, the data were randomly divided into the training set and the test set. The training set was used to construct the prediction model, and the test set was used to evaluate the prediction efficiency of the model. Three algorithms, gradient boosting decision tree (GBDT), random forest (RF), and logistic regression (LR), were used to build a prediction model and evaluate the model performance, respectively. The evaluation metrics included accuracy, sensitivity, recall, F1 value (the reconciled mean of sensitivity and recall), and area under the receiver operating characteristic curve (AUROC). Finally, Shapley Additive exPlanation (SHAP) was applied to analyze the interpretability of the clinical features with predictive significance.Results:A total of 698 patients, 439 males (62.9%) with a median age of 64 (21, 84) years, were included in this study and received a total of 1 654 cycles of chemotherapy. The chemotherapy regimen contained cisplatin in 364 cases with 864 cycles of chemotherapy, and carboplatin with AUC ≥4 in 361 cases with 790 cycles of chemotherapy. The number of treatment cycles in which neurokinin-1 receptor antagonist (NK-1 RA), 5-hydroxytryptamine-3 receptor antagonist (5-HT3 RA), and dexamethasone were selected as the antiemetic regimen was 1 347, and in those with the selection of 5-HT3 RA and dexamethasone was 307. The Spearman′s correlation analysis showed no strong correlation between the feature variables in the patients, and all of them could be used for model building. GBDT optimal hyperparameters n_estimators=500, max_depth=9; RF optimal hyperparameters max_depth=5; LR optimal hyperparameters penalty=L2. Three prediction models, GBDT, RF and LR, were established based on the optimal hyperparameter training data, respectively. The accuracy of GBDT model was 0.903, sensitivity was 0.882, recall was 0.903, F1 value was 0.883, and AUROC was 0.778±0.036 (95% CI: 0.739-0.814); the accuracy of RF model was 0.885, sensitivity was 0.861, recall was 0.885, F1 value was 0.870, and AUROC was 0.679±0.041 (95% CI: 0.636-0.720); the LR model had an accuracy of 0.817, a sensitivity of 0.851, a recall of 0.817, an F1 value of 0.832, and an AUROC of 0.682±0.042 (95% CI: 0.639-0.723). Ccr, age, chemotherapy cycle, history of alcohol consumption, and patient expects to have CINV were the main features predicted by the model. The risk of CINV was negatively associated with Ccr, age, and chemotherapy cycle. And the risk of CINV was lower in patients with no history of drinking alcohol and patient expects to have CINV. Conclusion:The GBDT, RF, and LR models could all predict the risk of CINV in patients receiving platinum-based chemotherapy with high emetic risk, with the GBDT model having the best predictive effect.

Objective:To provide a basis for the selection of antiemetic regimen by establishing an artificial intelligence model for predicting chemotherapy-induced nausea and vomiting (CINV) in cancer patients receiving platinum-based chemotherapy with high emetic risk.Methods:The clinical information on cancer patients who received cisplatin or carboplatin with area under the blood concentration-time curve (AUC) ≥4 and registered in the Department of Oncology, Tianjin Medical University General Hospital from January 2018 to December 2022 was collected, including gender, age, history of alcohol consumption, history of vomiting in pregnancy, chemotherapy cycle, patient expects to have CINV, chemotherapeutic agents, antiemetic regimen, out-of-hospital antiemetic treatment, sleep of less than 7 hours on the night before chemotherapy, occurrence of CINV in the previous cycle, and creatinine clearance (Ccr). After pre-processing, the data were randomly divided into the training set and the test set. The training set was used to construct the prediction model, and the test set was used to evaluate the prediction efficiency of the model. Three algorithms, gradient boosting decision tree (GBDT), random forest (RF), and logistic regression (LR), were used to build a prediction model and evaluate the model performance, respectively. The evaluation metrics included accuracy, sensitivity, recall, F1 value (the reconciled mean of sensitivity and recall), and area under the receiver operating characteristic curve (AUROC). Finally, Shapley Additive exPlanation (SHAP) was applied to analyze the interpretability of the clinical features with predictive significance.Results:A total of 698 patients, 439 males (62.9%) with a median age of 64 (21, 84) years, were included in this study and received a total of 1 654 cycles of chemotherapy. The chemotherapy regimen contained cisplatin in 364 cases with 864 cycles of chemotherapy, and carboplatin with AUC ≥4 in 361 cases with 790 cycles of chemotherapy. The number of treatment cycles in which neurokinin-1 receptor antagonist (NK-1 RA), 5-hydroxytryptamine-3 receptor antagonist (5-HT3 RA), and dexamethasone were selected as the antiemetic regimen was 1 347, and in those with the selection of 5-HT3 RA and dexamethasone was 307. The Spearman′s correlation analysis showed no strong correlation between the feature variables in the patients, and all of them could be used for model building. GBDT optimal hyperparameters n_estimators=500, max_depth=9; RF optimal hyperparameters max_depth=5; LR optimal hyperparameters penalty=L2. Three prediction models, GBDT, RF and LR, were established based on the optimal hyperparameter training data, respectively. The accuracy of GBDT model was 0.903, sensitivity was 0.882, recall was 0.903, F1 value was 0.883, and AUROC was 0.778±0.036 (95% CI: 0.739-0.814); the accuracy of RF model was 0.885, sensitivity was 0.861, recall was 0.885, F1 value was 0.870, and AUROC was 0.679±0.041 (95% CI: 0.636-0.720); the LR model had an accuracy of 0.817, a sensitivity of 0.851, a recall of 0.817, an F1 value of 0.832, and an AUROC of 0.682±0.042 (95% CI: 0.639-0.723). Ccr, age, chemotherapy cycle, history of alcohol consumption, and patient expects to have CINV were the main features predicted by the model. The risk of CINV was negatively associated with Ccr, age, and chemotherapy cycle. And the risk of CINV was lower in patients with no history of drinking alcohol and patient expects to have CINV. Conclusion:The GBDT, RF, and LR models could all predict the risk of CINV in patients receiving platinum-based chemotherapy with high emetic risk, with the GBDT model having the best predictive effect.