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Objective: In this paper, we review the epidemiological evidence on the relationship between ambient temperature and morbidity. We assessed the methodological issues in previous studies and proposed future research directions. Data sources and data extraction: We searched the PubMed database for epidemiological studies on ambient temperature and morbidity of noncommunicable diseases published in refereed English journals before 30 June 2010. Forty relevant studies were identified. Of these, 24 examined the relationship between ambient temperature and morbidity, 15 investigated the short-term effects of heat wave on morbidity, and 1 assessed both temperature and heat wave effects. Data synthesis: Descriptive and time-series studies were the two main research designs used to investigate the temperature-morbidity relationship. Measurements of temperature exposure and health outcomes used in these studies differed widely. The majority of studies reported a significant relationship between ambient temperature and total or cause-specific morbidities. However, there were some inconsistencies in the direction and magnitude of nonlinear lag effects. The lag effect of hot temperature on morbidity was shorter (several days) compared with that of cold temperature (up to a few weeks). The temperature-morbidity relationship may be confounded or modified by sociodemographic factors and air pollution. Conclusions: There is a significant short-term effect of ambient temperature on total and causespecific morbidities. However, further research is needed to determine an appropriate temperature measure, consider a diverse range of morbidities, and to use consistent methodology to make different studies more comparable.

As a highly productive and biologically diverse ecosystem, wetlands provide unique habitat for a wide array of plant and animal species. Owing to the strong disturbance by human activities and climate change, wetland degradation and fragmentation have become a common phenomenon across the globe. The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a typical case. The GBA has experienced explosive growth in the population and economy since the early 1980s, which has resulted in complicated transitions between wetlands and non-wetlands. However, our knowledge about the transformation paths, associated drivers, and ecological influence of the GBA’s wetlands is still very limited. Taking advantage of the land use maps generated from Landsat observations over the period of 1980–2020, here, we quantified the spatiotemporal transformation paths of the GBA’s wetlands and analyzed the associated drivers and ecological influence. We found that the dominant transformation path between wetland and non-wetland was from wetland to built-up land, which accounted for 98.4% of total wetland loss. The primary transformation path among different wetland types was from coastal shallow water and paddy land to reservoir/pond, with the strongest transformation intensity in the 1980s. The driving forces behind the wetland change were found to vary by region. Anthropogenic factors (i.e., population growth and urbanization) dominated in highly developed cities, while climate factors and aquaculture had a greater influence in underdeveloped cities. The findings presented in this study will provide a reference for wetland management and planning in the GBA.

BACKGROUND: Although interest in assessing the impacts of temperature on mortality has increased,few studies have used a case-crossover design to examine nonlinear and distributed lag effects of temperature on mortality. Additionally, little evidence is available on the temperature—mortality relationship in China or on what temperature measure is the best predictor of mortality, OBJECTIVES: Our objectives were to use a distributed lag nonlinear model (DLNM) as a part of case crossover design to examine the nonlinear and distributed lag effects of temperature on mortality in Tianjin, China and to explore which temperature measure is the best predictor of mortality. METHODS: We applied die DLNM to a case-crossover design to assess die nonlinear and delayed effects of temperatures (maximum, mean, and minimum) on deaths (nonaccidental, cardiopulmonary,cardiovascular, and respiratory). RESULTS: A U-shaped relationship was found consistently between temperature and mortality. Cold effects (i.e., significantly increased mortality associated with low temperatures) were delayed by 3 days and persisted for 10 days. Hot effects (i.e., significantly increased mortality associated with high temperatures) were acute and lasted for 3 days and were followed by mortality displacement for nonaccidental, cardiopulmonary, and cardiovascular deatiis. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. CONCLUSIONS: In Tianjin, extreme cold and hot temperatures increased the risk of mortality. The effects of cold last longer than the effects of heat. Combining the DLNM and the case-crossover design allows the case-crossover design to flexibly estimate the nonlinear and delayed effects of temperature(or air pollution) while controlling for season.

The cable-driven exoskeleton can avoid joint misalignment, and is substantial alterations in the pattern of muscle synergy coordination, which arouse more attention in recent years to facilitate exercise for older adults and improve their overall quality of life. This study leverages principles from neuroscience and biomechanical analysis to select attachment points for cable-driven soft exoskeletons. By extracting key features of human movement, the objective is to develop a subject-specific design methodology that provides precise and personalized support in the attachment points optimization of cable-driven exoskeleton to achieve natural gait, energy efficiency, and muscle coordination controllable in the domain of human mobility and rehabilitation. To achieve this, the study first analyzes human walking experimental data and extracts biomechanical features. These features are then used to generate trajectories, allowing better natural movement under complete cable-driven exoskeleton control. Next, a genetic algorithm-based method is employed to minimize energy consumption and optimize the attachment points of the cable-driven system. This process identifies connections that are better suited for the human model, leading to improved efficiency and natural movement. By comparing the calculated elderly human model driven by exoskeleton with experimental subject in terms of joint angles, joint torques and muscle forces, the human model can successfully replicate subject movement and the cable output forces can mimic human muscle coordination. The optimized cable attachment points facilitate more natural and efficient collaboration between humans and the exoskeleton, making significant contributions to the field of assisting the elderly in rehabilitation.

Wastewater treatment is a pivotal step in water resource recycling. Predicting effluent wastewater quality can help wastewater treatment plants (WWTPs) establish efficient operations so as to save resources. We propose CNN-LSTM-Attention (CLATT), an attention-based effluent wastewater quality prediction model, which uses a convolutional neural network (CNN) as an encoder and a long short-term memory network (LSTM) as a decoder. An attention mechanism is used to aggregate the information at adjacent sampling times. A sliding window method is proposed to solve the problem of the prediction performance of the model decreasing with time. We conducted the experiment using data collected from a WWTP in Fujian, China. Our results show that the accuracy of prediction is improved, with MSE decreasing by 0.25, MAPE decreasing by 5% and LER decreasing by 7%, after using the sliding window method. Compared with other methods, CLATT achieves the fastest prediction speed among all the methods based on LSTM and the most accurate prediction performance, with MSE increasing up to 0.92, MAPE up to 0.08 and LER up to 0.11. Furthermore, we performed an ablation study on the proposed method to validate the rationality of the major part of the model, and the results show that the LSTM significantly improves the predictive performance of the model, and the CNN and the attention mechanism also improve the accuracy of the prediction.

Versican has been reported to participate in carcinogenesis in several malignant tumors. However, the accurate role of VersicanV1, a predominant isoform of Versican in liver, remains an enigma in hepatocellular carcinoma (HCC). The expression of VersicanV1 in HCC tissues and adjacent tissues was detected by Reverse Transcription-Polymerase Chain Reaction (RT-PCR), Western Blot (WB) and inmumohistochemistry (IHC). Gain and loss of function assays were performed to examine the role of VersicanV1 in proliferation and metastasis of HCC. Measurement of oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) in vitro and PET-CT (positron emission tomography/computed tomography) analysis in vivo were applied to evaluate the effects of VersicanV1 on glycolysis. RNA sequencing, Co-IP (Co-immunoprecipitation) and MS (mass spectrometry) were utilized to investigate the molecular mechanisms. Our current study reveals that VersicanV1, regulated by direct interaction with Linc01225, is significantly upregulated in HCC tissues and correlates with poor prognosis. Both in vitro and in vivo experiments show that knockdown of VersicanV1 in HCC cells attenuates cancer cells malignancy. Further studies identify the positive role of VersicanV1 in aerobic glycolysis. Mechanistic investigation discovers the activation of EGFR–PI3K–AKT pathway in HCC cells expressing high VersicanV1. Moreover, EGF-like motif is indispensable for VersicanV1 to promote Warburg effect of HCC cells and subsequently, proliferation, invasion, and metastasis ability via activation of EGFR–PI3K–AKT axis. In sum, our research highlights a novel role of VersicanV1 in the progression of HCC, suggesting that VersicanV1 is an indicator for prognosis and a potential therapeutic target of HCC.

Data analysis of clinical samples suggests that higher estrogen receptor α (ERα) expression could be associated with worse overall survival in some patients with non‐small‐cell lung cancer (NSCLC). Immunofluorescence results further showed that higher ERα expression was linked to larger numbers of infiltrated macrophages in NSCLC tissues. However, the detailed mechanisms underlying this phenomenon remain unclear. Results from in vitro studies with multiple cell lines revealed that, in NSCLC cells, ERα can activate the CCL2/CCR2 axis to promote macrophage infiltration, M2 polarization, and MMP9 production, which can then increase NSCLC cell invasion. Mechanistic studies using chromatin immunoprecipitation and promoter luciferase assays demonstrated that ERα could bind to estrogen response elements (EREs) on the CCL2 promoter to increase CCL2 expression. Furthermore, ERα‐increased macrophage infiltration can induce a positive feedback mechanism to increase lung cancer cell ERα expression via the up‐regulation of the CXCL12/CXCR4 pathway. Targeting these newly identified pathways, NSCLC ERα‐increased macrophage infiltration or the macrophage‐to‐NSCLC CXCL12/CXCR4/ERα signal, with anti‐estrogens or CCR2/CXCR4 antagonists, may help in the development of new alternative therapies to better treat NSCLC. Analyses of TCGA database and our clinical samples showed that ERα correlates with worse prognosis and increased macrophage infiltration. Mechanistic study proved that ERα triggers NSCLC invasion via interaction with macrophages. Translational studies on mouse models proved that targeting ERα‐related pathways may provide benefits for NSCLC patients in the future.

Background Traditional Scarf osteotomy (TSO) is an effective procedure with a good record in moderate to severe hallux valgus (MSHV) surgery. In order to overcome shortcomings of TSO, Modified Rotary Scarf osteotomy (MRSO) was introduced in this study, which aimed to compare the clinical and radiological outcome in the patients treated with MRSO or TSO. Methods Of 175 patients (247 feet) with MSHV, 100 patients (138 feet) treated with MRSO and 75 patients (109 feet) treated with TSO were evaluated according to relevant indicators in twenty-four months follow-up. Pre-surgical and post-surgical HVA, IMA, DMAA, MTP-1 ROM, sesamoid grade and AOFAS (American Orthopaedic Foot and Ankle Society) scores and postsurgical complications were evaluated. Results Both groups manifested similar baseline characters. The mean follow-up was of 25.9 (range, 22–37) months. Significantly lower IMA, lower Sesamoid grade and higher DMAA at six months, twelve months and twenty-four months post-surgically had been showed in MRSO group compared to TSO group. There was no significant difference in HVA, MTP-1 ROM and AOFAS data at each follow-up time point post-surgically between the two groups. No major complications occurred in either group. Conclusion MRSO showed comparable results to TSO, and improved IMA and sesamoid grade to a greater extent, with a lower probability of throughing effect. Although DMAA could be increased by MRSO, MRSO could still be a reproducible, non-dangerous and efficacious alternative procedure for treating HV patients which do not have severe DMAA.

Clinical therapies for chronic pain are limited. While targeted drugs are promising therapies for chronic pain, they exhibit insufficient efficacy and poor targeting. The occurrence of chronic pain partly results from central changes caused by alterations in neurons in the rostral ventromedial medulla (RVM) in the brainstem regulatory pathway. The RVM, which plays a key role in the descending pain control pathway, greatly contributes to the development and maintenance of pain. However, the exact roles of the RVM in chronic pain remain unclear, making it difficult to develop new drugs targeting the RVM and related pathways. Here, we first discuss the roles of the RVM and related circuits in chronic pain. Then, we analyze synaptic transmission between RVM neurons and spinal cord neurons, specifically focusing on the release of neurotransmitters, to explore the cellular mechanisms by which the RVM regulates chronic pain. Finally, we propose some ideas for the development of drugs targeting the RVM.

Immunometabolism contributes to inflammation, but how activated macrophages acquire extracellular nutrients to fuel inflammation is largely unknown. Here, we show that the plasma membrane potential (V m ) of macrophages mediated by Kir2.1, an inwardly-rectifying K + channel, is an important determinant of nutrient acquisition and subsequent metabolic reprogramming promoting inflammation. In the absence of Kir2.1 activity, depolarized macrophage V m lead to a caloric restriction state by limiting nutrient uptake and concomitant adaptations in nutrient conservation inducing autophagy, AMPK (Adenosine 5‘-monophosphate-activated protein kinase), and GCN2 (General control nonderepressible 2), which subsequently depletes epigenetic substrates feeding histone methylation at loci of a cluster of metabolism-responsive inflammatory genes, thereby suppressing their transcription. Kir2.1-mediated V m supports nutrient uptake by facilitating cell-surface retention of nutrient transporters such as 4F2hc and GLUT1 by its modulation of plasma membrane phospholipid dynamics. Pharmacological targeting of Kir2.1 alleviated inflammation triggered by LPS or bacterial infection in a sepsis model and sterile inflammation in human samples. These findings identify an ionic control of macrophage activation and advance our understanding of the immunomodulatory properties of V m that links nutrient inputs to inflammatory diseases. Potassium channels and membrane potential may influence macrophage function during inflammation. Here the authors show that the Kir2.1 potassium channel affects macrophage metabolism by altering cell surface retention of nutrient transporters and subsequently regulates inflammatory disease responses.