Dietary Knowledge, Attitude, Practice Survey and Nutritional Knowledge-Based Intervention: A Cross-Sectional and Randomized Controlled Trial Study among College Undergraduates in China.

BACKGROUND: Understanding undergraduates' dietary literacy, including dietary knowledge, attitude and practice (KAP), is important for future health promotion policies. Therefore, this study aimed to investigate the current status and influencing factors of dietary literacy in Chinese college undergraduates and explore whether a nutritional lecture could improve their dietary literacy. METHODS: This study included two parts: a cross-sectional study (n = 1026) conducted by a dietary literacy questionnaire, and a randomized controlled trail (RCT) that enrolled 99 college undergraduates who were randomized to a control group or a nutritional lecture group. Data from the questionnaire and 72 h food records were obtained on day 0, day 3 and day 100 before and after intervention. RESULTS: This cross-sectional study showed that the mean scores of dietary KAP were respectively 100.0 (33.3), 59.1 (13.6) and 71.7 (11.7), with an excellent rate of 36.6%, 1.9% and 3.4%. Female upper-grade undergraduates and those with medicine-related majors illustrated higher dietary knowledge scores (p < 0.001). Dietary attitude rather than dietary knowledge had a significant impact on dietary practice (p < 0.001). This finding was in line with the results in the RCT study. Compared with the control group, dietary knowledge was significantly improved in the nutritional lecture group on both day 3 (p = 0.002) and day 100 (p = 0.023) after intervention. However, dietary behavior was improved only on day 3 post nutritional lecture (p = 0.029) but decreased to the original level 100 days later (p < 0.001). CONCLUSIONS: This study discovered the unsatisfying status and discrepancy between dietary literacy among college undergraduates of different sex, majors and college years. Dietary attitude instead of dietary knowledge was discovered as a determining role in dietary practice. One nutritional lecture could improve undergraduates' dietary literacy but the effect was not long-lasting. Further studies with more reinforced and durable interventions are warranted.

An interpretable ensemble trees method with joint analysis of static and dynamic features for myocardial infarction detection.

OBJECTIVE: In recent years, artificial intelligence-based electrocardiogram (ECG) methods have been massively applied to myocardial infarction (MI). However, the joint analysis of static and dynamic features to achieve accurate and interpretable MI detection has not been comprehensively addressed. Approach. This paper proposes a simplified ensemble tree method with a joint analysis of static and dynamic features to solve this issue for MI detection. Initially, the dynamic features are extracted by modeling the intrinsic dynamics of ECG via dynamic learning in addition to extracting classical static features. Secondly, a two-stage feature selection strategy is designed to identify a few significant features, which substitute the original variables that are employed in constructing the ensemble tree. This approach enhances the discriminative ability by selecting significant static and dynamic features. Subsequently, this paper presents an interpretable classification method named StackTree by introducing a stacked ensemble scheme to modify the ensemble tree simplification algorithm. The representative rules of the raw ensemble trees are selected as the intermediate training data that is used to retrain a decision tree with performance close to that of the source ensemble model. Using this scheme, the significant precision and interpretability of MI detection are thus comprehensively addressed. Main results. The effectiveness of our method in detecting MI is evaluated using the PTB and clinical database. The findings suggest that our algorithm outperforms the traditional methods based on a single type of feature. Additionally, it is comparable to the conventional random forest, achieving 97.1% accuracy under the inter-patient framework on the PTB database. Furthermore, feature subsets trained on PTB are validated using the clinical database, resulting in an accuracy of 84.5%. The chosen important features demonstrate that both static and dynamic information have crucial roles in MI detection. Crucially, the proposed method provides clear internal workings in an easy-to-understand visual manner. .

Exposure memory and susceptibility to ambient PM2.5: A perspective from hepatic cholesterol and bile acid metabolism.

Both epidemiological and experimental studies increasingly show that exposure to ambient fine particulate matter (PM2.5) is related to the occurrence and development of chronic diseases, such as metabolic diseases. However, whether PM2.5 has "exposure memory" and how these memories affect chronic disease development like hepatic metabolic homeostasis are unknown. Therefore, we aimed to explore the effects of exposure transition on liver cholesterol and bile acids (BAs) metabolism in mice. In this study, C57BL/6 mice were exposed to concentrated ambient PM2.5 or filtered air (FA) in a whole-body exposure facility for an initial period of 10 weeks, followed by another 8 weeks of exposure switch (PM2.5 to FA and FA to PM2.5) comparing to non-switch groups (FA to FA and PM2.5 to PM2.5), which were finally divided into four groups (FF of FA to FA, PP of PM2.5 to PM2.5, PF of PM2.5 to FA, and FP of FA to PM2.5). Our results showed no significant difference in food intake, body composition, glucose homeostasis, and lipid metabolism between FA and PM2.5 groups after the initial exposure before the exposure switch. At the end of the exposure switch, the mice switched from FA to PM2.5 exposure exhibited a high sensitivity to late-onset PM2.5 exposure, as indicated by significantly elevated hepatic cholesterol levels and disturbed BAs metabolism. However, the mice switched from PM2.5 to FA exposure retained a certain memorial effects of previous PM2.5 exposure in hepatic cholesterol levels, cholesterol metabolism, and BAs metabolism. Furthermore, 18-week PM2.5 exposure significantly increased hepatic free BAs levels, which were completely reversed by the FA exposure switch. Finally, the changes in small heterodimeric partner (SHP) and nuclear receptor subfamily 5 group A member 2 (LRH1) in response to exposure switch mechanistically explained the above alterations. Therefore, mice switching from PM2.5 exposure to FA showed only a weak memory of prior PM2.5 exposure. In contrast, the early FA caused mice to be more susceptible to subsequent PM2.5 exposure.

Drivers of associations between daytime-nighttime compound temperature extremes and mortality in China.

BACKGROUND: Temperature extremes are anticipated to become more frequent and more intense under the context of climate change. While current evidence on health effects of compound extreme temperature event is scarce. METHODS: This nationwide cross-sectional study collected daily data on weather and mortality for 161 Chinese districts/counties during 2007-2013. A quasi-Poisson generalized linear model was first applied to assess effects of daytime-only, nighttime-only and compound daytime-nighttime heat wave (and cold spell) on cause-specific mortality. Then a random-effect meta-analysis was used to produce pooled estimates at national level. Stratification analyses were performed by relative humidity, individual and regional characteristics. RESULTS: Here we show that mortality risks of compound daytime-nighttime temperature extremes are much higher than those occurring only in the daytime or nighttime. Humid weather further exaggerates the mortality risk during heat waves, while dry air enhances the risk during cold weather. People who are elderly, illiterate, and those with ischemic heart disease and respiratory disease are particularly vulnerable to extreme temperature. At the community-level, population size, urbanization rate, proportion of elderly and PM2.5 are positively associated with increased risks associated with heat waves. Temperature, humidity and normalized difference vegetation index are positively associated with the effects of cold weather, with an opposite trend for latitude and diurnal temperature range. CONCLUSIONS: This nationwide study highlights the importance of incorporating compound daytime-nighttime extreme temperature events and humid conditions into early warning systems and urban design/planning.

Ongoing climate change has exaggerated the frequency and intensity of severe climate events, leading to substantial health and socioeconomic consequences. We assessed deaths in China during periods when many extreme climate events occurred at the same or similar times. We looked at deaths occurring during periods when both daytime and nighttime temperatures were very hot or cold. We found more serious health effects were seen when temperatures remained hot or cold during the day and night compared to when it was just hot or cold during the day or night. Other factors including humidity, preexisting heart or respiratory disease and age also impacted the risk of death. Our study highlights the detrimental health effects of many extreme climate events occurring together and the need for both people and governments to consider approaches to reduce these negative effects.

N-regulated three-dimensional turf-like carbon nanosheet loaded with FeCoNi nanoalloys as bifunctional electrocatalysts for durable zinc-air batteries.

N-regulated three-dimensional (3D) turf-like carbon material loaded with FeCoNi nanoalloys (F-CNS-CNT), composed of carbon nanotubes (CNT) grown in situ on carbon nanosheets(CNS), was synthesized using a low-temperature solution combustion method and organic compounds rich in pyridinic-N. This distinct structure significantly expands the effective electrochemical surface area, revealing an abundance of active sites and enhancing the mass transfer capability for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Both experimental observations and theoretical calculations corroborate that the synergy between the FeCoNi nanoalloy and the highly pyridinic N-doped carbon substrate optimizes the adsorption and desorption-free energy of oxygen intermediates, resulting in a remarkable improvement of intrinsic ORR/OER activity. Therefore, the derived F-CNS-CNT electrocatalyst can present a favorable half-wave potential of 0.85 V (ORR) and a lower overpotential of 260 mV (corresponding to a current density of 10 mA cm-2, OER) in alkaline media. Moreover, when employed in the air cathode of a flowable zinc-air battery, the electrocatalyst exhibits exceptional discharge and charge performance, including a high power density of 144.6 mW cm-2, a high specific capacity of 801 mAh g-1, and an impressive cycling stability of 600 cycles at a current density of 10 mA cm-2. Notably, these results markedly surpass those of the commercial catalyst Pt/C + IrO2.

Effects of cooking with solid fuel on hearing loss in Chinese adults-Based on two cohort studies.

The association between cooking fuel and hearing loss still needs more research to clarify, and two longitudinal cohort studies were explored to find if solid fuel use for cooking affected hearing in Chinese adults. The data from Chinese Health and Retirement Longitudinal Survey (CHARLS) and Chinese Longitudinal Healthy Longevity Survey (CLHLS) were analyzed. Participants (older than 18) without hearing loss at baseline and follow-up visits were included, which were divided into clean fuel and solid fuel groups. Hearing loss rate was from follow-up visits (both in year 2011) until the recent one (year 2018 in CHARLS and 2019 in CLHLS). Cox regressions were applied to examine the associations with adjustment for potential confounders. Fixed-effect meta-analysis was used to pool the results. A total of 9049 participants (average age 8.34 ± 9.12 [mean ± SD] years; 4247 [46.93%] males) were included in CHARLS cohort study and 2265 participants (average age, 78.75 ± 9.23 [mean ± SD] years; 1148 [49.32%] males) in CLHLS cohort study. There were 1518 (16.78%) participants in CHARLS cohort and 451 (19.91%) participants in CLHLS cohort who developed hearing loss. The group of using solid fuel for cooking had a higher risk of hearing loss (CHARLS: HR, 1.16; 95% CI 1.03-1.30; CLHLS: HR, 1.43; 95% CI 1.11-1.84) compared with the one of using clean fuel. Pooled hazard ratio showed the incidence of hearing loss in the solid fuel users was 1.17 (1.03, 1.29) times higher than that of clean fuel users. Hearing loss was associated with solid fuel use and older people were at higher risk. It is advised to replace solid fuel by clean fuel that may promote health equity.

Independent and joint associations of monocyte to high-density lipoprotein-cholesterol ratio and body mass index with cardiorenal syndrome: insights from NHANES 2003-2020.

BACKGROUND: With the development of pathophysiology, cardiorenal syndrome (CRS), a complex and severe disease, has received increasing attention. Monocyte to high-density lipoprotein-cholesterol ratio (MHR) and body mass index (BMI) are independent risk factors for cardiovascular diseases, but their association with CRS remains unexplored. This study aims to explore the independent and joint effects of MHR and BMI on CRS. METHODS: We included 42,178 NHANES participants. The determination of CRS referred to the simultaneous presence of cardiovascular disease (identified through self-report) and chronic kidney disease (eGFR < 60 mL/min per 1.73 m²). We employed multivariate weighted logistic regression to evaluate the odds ratio (OR) and 95% confidence interval (CI) for the independent and joint associations of MHR and BMI with CRS. We also conducted restricted cubic spines to explore nonlinear associations. RESULTS: The prevalence of CRS was 3.45% among all participants. An increase in both MHR and BMI is associated with a higher risk of CRS (MHR: OR = 1.799, 95% CI = 1.520-2.129, P < 0.001, P-trend < 0.001; BMI: OR = 1.037, 95% CI = 1.023-1.051, P < 0.001). Individuals who simultaneously fall into the highest quartile of MHR and have a BMI of 30 or more face the highest risk of CRS compared to those in the lowest MHR quartile with a BMI of less than 25 (OR = 3.45, 95% CI = 2.40-4.98, P < 0.001). However, there is no interactive association between MHR and BMI with CRS. CONCLUSIONS: Higher MHR and BMI are associated with higher odds of CRS. MHR and BMI can serve as tools for early prevention and intervention of CRS, respectively.

PM2.5-induced cellular senescence drives brown adipose tissue impairment in middle-aged mice.

Airborne fine particulate matter (PM2.5) exposure is closely associated with metabolic disturbance, in which brown adipose tissue (BAT) is one of the main contributing organs. However, knowledge of the phenotype and mechanism of PM2.5 exposure-impaired BAT is quite limited. In the study, male C57BL/6 mice at three different life phases (young, adult, and middle-aged) were simultaneously exposed to concentrated ambient PM2.5 or filtered air for 8 weeks using a whole-body inhalational exposure system. H&E staining and high-resolution respirometry were used to assess the size of adipocytes and mitochondrial function. Transcriptomics was performed to determine the differentially expressed genes in BAT. Quantitative RT-PCR, immunohistochemistry staining, and immunoblots were performed to verify the transcriptomics and explore the mechanism for BAT mitochondrial dysfunction. Firstly, PM2.5 exposure caused altered BAT morphology and mitochondrial dysfunction in middle-aged but not young or adult mice. Furthermore, PM2.5 exposure increased cellular senescence in BAT of middle-aged mice, accompanied by cell cycle arrest, impaired DNA replication, and inhibited AKT signaling pathway. Moreover, PM2.5 exposure disrupted apoptosis and autophagy homeostasis in BAT of middle-aged mice. Therefore, BAT in middle-aged mice was more vulnerable to PM2.5 exposure, and the cellular senescence-initiated apoptosis, autophagy, and mitochondrial dysfunction may be the mechanism of PM2.5 exposure-induced BAT impairment.

Lung function benefits of traditional Chinese medicine Qiju granules against fine particulate air pollution exposure: a randomized controlled trial.

Introduction: Multiple targets are considered as the causes of ambient fine particulate matter [aerodynamic diameters of < 2.5 µm (PM2.5)] induced lung function injury. Qiju granules are derived from the traditional Chinese medicine (TCM) formula known as Qi-Ju-Di-Huang-Wan (Lycium, Chrysanthemum, and Rehmannia Formula, QJDHW), which has been traditionally used to treat symptoms such as cough with phlegm, dry mouth and throat, and liver heat. This treatment approach involves attenuating inflammation, oxidative stress, and fibrosis response. This study investigated the effects of Qiju granules on protecting lung function against PM2.5 exposure in a clinical trial. Methods: A randomized, double-blinded, and placebo-controlled trial was performed among 47 healthy college students in Hangzhou, Zhejiang Province in China. The participants were randomly assigned to the Qiju granules group or the control group based on gender. Clinical follow-ups were conducted once every 2 weeks during a total of 4 weeks of intervention. Real-time monitoring of PM2.5 concentrations in the individually exposed participants was carried out. Data on individual characteristics, heart rate (HR), blood pressure (BP), and lung function at baseline and during the follow-ups were collected. The effects of PM2.5 exposure on lung function were assessed within each group using linear mixed-effect models. Results: In total, 40 eligible participants completed the scheduled follow-ups. The average PM2.5 level was found to be 64.72 µg/m3 during the study period. A significant negative correlation of lung function with PM2.5 exposure concentrations was observed, and a 1-week lag effect was observed. Forced expiratory volume in one second (FEV1), peak expiratory flow (PEF), maximal mid-expiratory flow (MMEF), forced expiratory flow at 75% of forced vital capacity (FVC) (FEF75), forced expiratory flow at 50% of FVC (FEF50), and forced expiratory flow at 25% of FVC (FEF25) were significantly decreased due to PM2.5 exposure in the control group. Small airway function was impaired more seriously than large airway function when PM2.5 exposure concentrations were increased. In the Qiju granules group, the associations between lung function and PM2.5 exposure were much weaker, and no statistical significance was observed. Conclusion: The results of the study showed that PM2.5 exposure was associated with reduced lung function. Qiju granules could potentially be effective in protecting lung functions from the adverse effects of PM2.5 exposure. Clinical Trial Registration: identifier: ChiCTR1900021235.

Comparative genomic and transcriptome analyses of two Pectobacterium brasiliense strains revealed distinct virulence determinants and phenotypic features.

Potato soft rot caused by Pectobacterium spp. are devastating diseases of potato which cause severe economic losses worldwide. Pectobacterium brasiliense is considered as one of the most virulent species. However, the virulence mechanisms and pathogenicity factors of this strain have not been fully elucidated. Here, through pathogenicity screening, we identified two Pectobacterium brasiliense isolates, SM and DQ, with distinct pathogenicity levels. SM exhibits higher virulence compared to DQ in inducing aerial stem rot, blackleg and tuber soft rot. Our genomic and transcriptomic analyses revealed that SM encodes strain specific genes with regard to plant cell wall degradation and express higher level of genes associated with bacterial motility and secretion systems. Our plate assays verified higher pectinase, cellulase, and protease activities, as well as fast swimming and swarming motility in SM. Importantly, a unique endoglucanase S specific to SM was identified. Expression of this cellulase in DQ greatly enhances its virulence compared to wild type strain. Our study sheds light on possible determinants causing different pathogenicity of Pectobacterium brasiliense species with close evolutionary distance and provides new insight into the direction of genome evolution in response to host variation and environmental stimuli.

Dust particulate matter increases pulmonary embolism onset: A nationwide time-stratified case-crossover study in China.

BACKGROUND: Particulate matter (PM) has been found to elevate the risk of pulmonary embolism (PE) onset. Among the contributors to PM, dust PM stands as the second natural source, and its emissions are escalating due to climate change. Despite this, information on the effect of dust PM on PE onset is scarce. Hence, this study aims to investigate the impacts of dust PM10, dust PM2.5-10, and dust PM2.5 on PE onset. METHODS: A nationwide time-stratified case-crossover study was conducted between 2015 and 2020, using data from 18,616 PE onset cases across 1,921 hospitals in China. The analysis employed a conditional logistic regression model to quantify the associations between dust PM10, dust PM2.5-10, and dust PM2.5 and PE onset. Furthermore, the study explored the time-distributed lag pattern of the effect of dust PM on PE development. Stratified analyses were performed based on sex, age, region, and season. RESULTS: Dust PM10, dust PM2.5-10, and dust PM2.5 exhibited significant health effects on PE onset, particularly concerning exposure on the same day. The peak estimates were observed at lag 01 day, with the odds ratio being 1.011 [95 % confidence interval (CI): 1.003, 1.019], 1.014 (95 % CI: 1.003, 1.026), and 1.039 (95 % CI: 1.011, 1.068), for a 10 µg/m3 increase in the concentration of dust PM10, dust PM2.5-10, and dust PM2.5, respectively. In addition, the study identified a higher risk of PE onset associated with dust PM exposure during the warm season than that in cool season, particularly for dust PM2.5. CONCLUSIONS: The findings from this study suggest that short-term exposure to dust PM, particularly dust PM2.5, may trigger PE onset, posing a significant health threat. Implementing measures to mitigate dust PM emissions and protect patients with PE from dust PM exposure is imperative.

Control of positive and negative photo- and thermal-responses in a single PbI2@CH3NH3PbI3 micro/nanowire-based device for real-time sensing, nonvolatile memory, and logic operation.

CH3NH3PbI3 has shown great potential for photodetectors and photovoltaic devices due to its excellent positive response to visible light. However, its real-time response characteristics hinder its application in optical memory and logic operation; moreover, the presence of excessive PbI2 is a double-edged sword. Herein, we constructed a dual-terminal device using a single CH3NH3PbI3 micro/nanowire with two Ag electrodes, and then in situ introduced PbI2 quantum dots (QDs) as hole trap centres by thermal decomposition at 160 °C. An anomalous negative photoconductivity (NPC) effect for sub-bandgap light below the PbI2 bandgap is obtained. Importantly, an electrically erasable nonvolatile photomemory can be realized. Furthermore, the device also exhibits an abnormal positive thermal resistance (PTR)-related thermomemory effect, and the thermal-induced high-resistance state (HRS) can be erased by a large bias or an illumination of 365 nm super-bandgap UV light. Additionally, logical "OR" gate operations are achieved through a combination of 650 nm sub-bandgap light and a 70 °C temperature-induced HRS, as well as a large bias and 365 nm super-bandgap light-triggered low-resistance state. These effects are attributed to the excitation and injection of holes in QDs and structural defect traps. This multifunctional device, integrating real-time sensing, nonvolatile memory, and logical operation, holds significant potential for novel electronic and optoelectronic applications.

LRRK2 is involved in heat exposure-induced acute lung injury and alveolar type II epithelial cell dysfunction.

Heat exposure induces excessive hyperthermia associated with systemic inflammatory response that leads to multiple organ dysfunction including acute lung injury. However, how heat impairs the lung remains elusive so far. We aimed to explore the underlying mechanism by focusing on leucine-rich repeat kinase 2 (LRRK2), which was associated with lung homeostasis. Both in vivo and in vitro models were induced by heat exposure. Firstly, heat exposure exerted core temperature (Tc) disturbance, pulmonary dysfunction, atelectasis, inflammation, impaired energy metabolism, and reduced surfactant proteins in the lung of mice. In addition, decreased LRRK2 expression and increased heat shock proteins (HSPs) 70 were observed with heat exposure in both the lung of mice and alveolar type II epithelial cells (AT2). Furthermore, LRRK2 inhibition aggravated heat exposure-initiated Tc dysregulation, injury in the lung and AT2 cells, and enhanced HSP70 expression. In conclusion, LRRK2 is involved in heat-induced acute lung injury and AT2 cell dysfunction.

Early Pulmonary Fibrosis-like Changes in the Setting of Heat Exposure: DNA Damage and Cell Senescence.

It is well known that extreme heat events happen frequently due to climate change. However, studies examining the direct health impacts of increased temperature and heat waves are lacking. Previous reports revealed that heatstroke induced acute lung injury and pulmonary dysfunction. This study aimed to investigate whether heat exposure induced lung fibrosis and to explore the underlying mechanisms. Male C57BL/6 mice were exposed to an ambient temperature of 39.5 ± 0.5 °C until their core temperature reached the maximum or heat exhaustion state. Lung fibrosis was observed in the lungs of heat-exposed mice, with extensive collagen deposition and the elevated expression of fibrosis molecules, including transforming growth factor-ß1 (TGF-ß1) and Fibronectin (Fn1) (p < 0.05). Moreover, epithelial-mesenchymal transition (EMT) occurred in response to heat exposure, evidenced by E-cadherin, an epithelial marker, which was downregulated, whereas markers of EMT, such as connective tissue growth factor (CTGF) and the zinc finger transcriptional repressor protein Slug, were upregulated in the heat-exposed lung tissues of mice (p < 0.05). Subsequently, cell senescence examination revealed that the levels of both senescence-associated ß-galactosidase (SA-ß-gal) staining and the cell cycle protein kinase inhibitor p21 were significantly elevated (p < 0.05). Mechanistically, the cGAS-STING signaling pathway evoked by DNA damage was activated in response to heat exposure (p < 0.05). In summary, we reported a new finding that heat exposure contributed to the development of early pulmonary fibrosis-like changes through the DNA damage-activated cGAS-STING pathway followed by cellular senescence.

Species diversity of Pectobacterium spp. causing potato aerial stem rot in China.

Pectobacterium spp. are the primary causative agents of aerial stem rot in potatoes in China. A nationwide survey revealed the widespread occurrence of aerial stem rot in the northern, southern, and southwestern cultivation regions, with occurrence rates ranging from 1% to 60%. In total, 36 strains were isolated and identified at the species level using multi-locus sequence analysis of six housekeeping genes (rpoS, proA, gapA, icdA, gyrA, and mdh). Genome sequencing was conducted on one representative strain for each species, and further confirmation of their identities was achieved through ANI and isDDH analysis. Five Pectobacterium species were identified, namely Pectobacterium atrosepticum, Pectobacterium brasiliense, Pectobacterium carotovorum, Pectobacterium polaris and Pectobacterium punjabense, with P. atrosepticum and P. brasiliense being the most widely distributed. Pathogenicity tests demonstrated that, among the strains isolated in this study and those obtained from other studies, P. atrosepticum and P. brasiliense are also the most virulent species. To the best of our knowledge, this is the first nationwide study describing the diversity and distribution of Pectobacterium spp. affecting potatoes in China. The information gathered will be utilized for disease diagnosis and the development of pathogen-specific integrated pest management (IPM) strategies to protect potato production.

Social-economic transitions and vulnerability to extreme temperature events from 1960 to 2020 in Chinese cities.

Climate change leads to more frequent and intense extreme temperature events, causing a significant number of excess deaths. Using an epidemiological approach, we analyze all-cause deaths related to heatwaves and cold spells in 2,852 Chinese counties from 1960 to 2020. Economic losses associated with these events are determined through the value of statistical life. Findings reveal that cold-related cumulative excess deaths (1,133 thousand) are approximately 2.5 times higher than heat-related deaths, despite an increase in heat-related fatalities in recent decades. Monetized mortality due to heat-related events is estimated at 1,284 billion CNY, while cold-related economic loss is 1,510 billion CNY. Notably, cities located in colder regions experience more heat-related excess deaths, and vice versa. Economic development does not significantly reduce mortality risks to heatwaves across China. This study provides insights into the spatial-temporal heterogeneity of heatwaves and cold spells mortality, essential for policymakers ensuring long-term climate adaptation and sustainability.

An interpretable shapelets-based method for myocardial infarction detection using dynamic learning and deep learning.

Objective.Myocardial infarction (MI) is a prevalent cardiovascular disease that contributes to global mortality rates. Timely diagnosis and treatment of MI are crucial in reducing its fatality rate. Currently, electrocardiography (ECG) serves as the primary tool for clinical diagnosis. However, detecting MI accurately through ECG remains challenging due to the complex and subtle pathological ECG changes it causes. To enhance the accuracy of ECG in detecting MI, a more thorough exploration of ECG signals is necessary to extract significant features.Approach.In this paper, we propose an interpretable shapelet-based approach for MI detection using dynamic learning and deep learning. Firstly, the intrinsic dynamics of ECG signals are learned through dynamic learning. Then, a deep neural network is utilized to extract and select shapelets from ECG dynamics, which can capture locally specific ECG changes, and serve as discriminative features for identifying MI patients. Finally, the ensemble model for MI detection is built by integrating shapelets of multi-dimensional ECG dynamic signals.Main results.The performance of the proposed method is evaluated on the public PTB dataset with accuracy, sensitivity, and specificity of 94.11%, 94.97%, and 90.98%.Significance.The shapelets obtained in this study exhibit significant morphological differences between MI and healthy subjects.

Dynamic learning from adaptive neural control for full-state constrained strict-feedback nonlinear systems.

This study focuses on the learning and control issues of strict-feedback systems with full-state constraints. To achieve learning capability under constraints, transformation mapping is utilized to convert the original system with full-state constraints into a quasi-pure-feedback unconstrained system. Utilizing the system transformation technique, only a single neural network (NN) is required to identify the unknown dynamics within the transformed system. Combining the dynamic surface control design, a novel adaptive neural control scheme is developed to ensure that all closed-loop signals are uniformly bounded, and every system state remains within the predefined constraint range. In addition, the precise convergence of NN weights is further transformed into an exponential stability problem for a category of linear time-varying systems under persistent excitation conditions. Subsequently, the converged NN weights are efficiently stored and utilized to create a learning controller to achieve better control performance while abiding by the full-state constraints. The viability of this control strategy is demonstrated via simulations.

Desipramine ameliorates fine particulate matter-induced hepatic insulin resistance by modulating the ceramide metabolism in mice.

Recent research has highlighted a correlation between exposure to ambient fine particulate matter (PM2.5) and the development of systemic insulin resistance (IR) along with an elevated risk of diabetes. Ceramide has emerged as one of the pathogenic mechanisms contributing to IR. The inhibition of acid sphingomyelinase (ASMase) activity by desipramine (DES) has been shown to effectively reduce ceramide levels. In the present study, 24 female C57BL/6 N mice were randomized into one of the four groups: the filtered air exposure (FA) group, the concentrated PM2.5 exposure (PM) group, the concentrated PM2.5 treated with low-dose DES (DL) group, and the concentrated PM2.5 treated with high-dose DES (DH) group. The PM, DL and DH groups were exposed to PM2.5 for an 8-week period within a whole-body exposure system. The study encompassed extensive examinations of glucose homeostasis, liver lipid profile, ceramide pathway, and insulin signaling pathway. Our results demonstrated that PM2.5 exposure caused impaired glucose tolerance, elevated ceramide levels, increased phosphorylation PP2A, reduced Akt phosphorylation, and hindered GLUT2 expression. Remarkably, DES administration mitigated PM2.5-induced IR by effectively lowering ceramide levels. In conclusion, the reduction of ceramide levels by DES may be a promising therapeutic strategy for coping PM2.5-induced IR.