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Abstract This research study demonstrates an efficient scheme for early detection of cardiorespiratory complications in pandemics by Utilizing Wearable Electrocardiogram (ECG) sensors for pattern generation and Convolution Neural Networks (CNN) for decision analytics. In health-related outbreaks, timely and early diagnosis of such complications is conclusive in reducing mortality rates and alleviating the burden on healthcare facilities. Existing methods rely on clinical assessments, medical history reviews, and hospital-based monitoring, which are valuable but have limitations in terms of accessibility, scalability, and timeliness, particularly during pandemics. The proposed scheme commences by deploying wearable ECG sensors on the patient’s body. These sensors collect data by continuously monitoring the cardiac activity and respiratory patterns of the patient. The collected raw data is then transmitted securely in a wireless manner to a centralized server and stored in a database. Subsequently, the stored data is assessed using a preprocessing process which extracts relevant and important features like heart rate variability and respiratory rate. The preprocessed data is then used as input into the CNN model for the classification of normal and abnormal cardiorespiratory patterns. To achieve high accuracy in abnormality detection the CNN model is trained on labeled data with optimized parameters. The performance of the proposed scheme is evaluated and gauged using different scenarios, which shows a robust performance in detecting abnormal cardiorespiratory patterns with a sensitivity of 95% and specificity of 92%. Prominent observations, which highlight the potential for early interventions include subtle changes in heart rate variability and preceding respiratory distress. These findings show the significance of wearable ECG technology in improving pandemic management strategies and informing public health policies, which enhances preparedness and resilience in the face of emerging health threats.

Objective: Knee osteoarthritis (KOA) is a prevalent condition in China, necessitating effective assessment tools for treatment outcomes. This study systematically reviews and analyzes the reliability, validity, and selection of patient-reported outcome measures (PROMs) for evaluating KOA. Methods: Following PRISMA guidelines, a literature search was conducted across seven databases, including CNKI, PubMed, and Embase, covering publications from December 2012 to December 2022. The methodological quality of the studies was assessed using the COSMIN checklist. Results: Twenty-one studies met the inclusion criteria, involving eight types of KOA PROMs. The Oxford Knee Score (OKS) and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) were the most frequently utilized, appearing in nine and four studies, respectively. OKS achieved a ''strong'' rating in internal consistency, test-retest reliability, content validity, responsiveness, and measurement error, while WOMAC received a ''strong'' rating in internal consistency, test-retest reliability, and content validity, with a ''moderate'' rating in structural validity. Conclusion: Both OKS and WOMAC are effective PROMs for evaluating KOA in China. However, the choice of a specific tool should be based on the study's objectives and the practical context, considering each tool's reliability, validity, and other measurement properties.

Floods are among the world's worst natural disasters, causing significant damage to people, infrastructure, and the economy. Since synthetic aperture radar (SAR) can work in all weather and is not affected by clouds and rain, the use of SAR for flood mapping and disaster assessment has obvious advantages. However, SAR images are highly susceptible to speckle noise, shadows, and distortions, which affects the accuracy of traditional water body extraction methods. To solve this problem, we designed a new model called WaterDetectionNet (WDNet) based on SAR remote sensing images and convolutional neural network, which has a strong water extraction capability for accurate flood mapping. In order to improve the generalization ability of the model, we used a semiautomatic strategy to generate the SAR dataset S1Water containing rich semantic information with diversity. Compared with the traditional machine learning and deep learning methods, we introduced a self-attention module to increase spatial and channel attention, and adaptively update the network weights, which improved the model performance and extraction accuracy of the real case study of the Poyang Lake flood in 2020. The experimental results show that the accuracy, recall, intersection over union, and F1 score of the WDNet model were 0.986, 0.994, 0.974, and 0.987, respectively. This method is expected to provide a cost-effective alternative to global rapid flood mapping, improve the reliability of flood disaster analysis, and offer a reference for postdisaster emergency management.

Abstract Background Total knee joint replacement (TKR) is an effective method for the treatment of severe knee osteoarthritis. With an increasing number of surgeries, complications such as lower limb edema, pain, and limited mobility have caused a heavy burden. Manual lymphatic drainage (MLD) may be a solution to solve the problem. The study aims to evaluate the efficacy of MLD in reducing knee edema, pain, and improving range of motion (ROM) in patients after TKR. Methods A search was conducted in PubMed, Embase, Cochrane Library, Web of Science, CNKI, VIPs, WanFang database, and Google Scholar from inception to June 2023. Only randomized controlled trials (RCTs) that compared the effects of MLD and non-MLD (or another physiotherapy) on improving knee edema, pain, and ROM after TKR were included. Stata 16.0 was used for meta-analysis. GRADE was used to assess the quality of evidence. Results In total, 7 RCTs with 285 patients were identified. There were no significant differences found in the ROM of knee flexion (standardized mean difference (SMD) = 0.03, 95% confidence interval (CI): -0.22, 0.28, P = 0.812) and the ROM of knee extension (SMD= -0.30, 95%CI: -0.64, 0.04, P = 0.084). No differences were observed in the lower extremity circumference after TKR (SMD= -0.09, 95%CI: -0.27, 0.09, P = 0.324). For postoperative pain, there was no significant advantage between the MLD and non-MLD groups (SMD= -0.33, 95%CI: -0.71, 0.04, P = 0.083). Conclusions Based on the current evidence from RCTs, manual lymphatic drainage is not recommended for the rehabilitation of patients following total knee replacement.

This study aimed to separately compare and rank the effect of various living-low and training-high (LLTH) modes on aerobic and anaerobic performances in athletes, focusing on training intensity, modality, and volume, through network meta-analysis. We systematically searched PubMed, Web of Science, Embase, EBSCO, and Cochrane from their inception date to June 30, 2023. Based on the hypoxic training modality and the intensity and duration of work intervals, LLTH was divided into intermittent hypoxic exposure, continuous hypoxic training, repeated sprint training in hypoxia (RSH; work interval: 5-10 s and rest interval: approximately 30 s), interval sprint training in hypoxia (ISH; work interval: 15-30 s), short-duration high-intensity interval training (s-IHT; short work interval: 1-2 min), long-duration high-intensity interval training (l-IHT; long work interval: > 5 min), and continuous and interval training under hypoxia. A meta-analysis was conducted to determine the standardized mean differences (SMDs) among the effects of various hypoxic interventions on aerobic and anaerobic performances. From 2,072 originally identified titles, 56 studies were included in the analysis. The pooled data from 53 studies showed that only l-IHT (SMDs: 0.78 [95% credible interval; CrI, 0.52-1.05]) and RSH (SMDs: 0.30 [95% CrI, 0.10-0.50]) compared with normoxic training effectively improved athletes' aerobic performance. Furthermore, the pooled data from 29 studies revealed that active intermittent hypoxic training compared with normoxic training can effectively improve anaerobic performance, with SMDs ranging from 0.97 (95% CrI, 0.12-1.81) for l-IHT to 0.32 (95% CrI, 0.05-0.59) for RSH. When adopting a program for LLTH, sufficient duration and work intensity intervals are key to achieving optimal improvements in athletes' overall performance, regardless of the potential improvement in aerobic or anaerobic performance. Nevertheless, it is essential to acknowledge that this study incorporated merely one study on the improvement of anaerobic performance by l-IHT, undermining the credibility of the results. Accordingly, more related studies are needed in the future to provide evidence-based support. It seems difficult to achieve beneficial adaptive changes in performance with intermittent passive hypoxic exposure and continuous low-intensity hypoxic training.

Objective: This study aimed to compare and rank the effect of hypoxic practices on maximum oxygen consumption (VO2max) in athletes and determine the hypoxic dose-response correlation using network meta-analysis.Methods: The Web of Science, PubMed, EMBASE, and EBSCO databases were systematically search for randomized controlled trials on the effect of hypoxc interventions on the VO2max of athletes published from inception until 21 February 2023. Studies that used live-high train-high (LHTH), live-high train-low (LHTL), live-high, train-high/low (HHL), intermittent hypoxic training (IHT), and intermittent hypoxic exposure (IHE) interventions were primarily included. LHTL was further defined according to the type of hypoxic environment (natural and simulated) and the altitude of the training site (low altitude and sea level). A meta-analysis was conducted to determine the standardized mean difference between the effects of various hypoxic interventions on VO2max and dose-response correlation. Furthermore, the hypoxic dosage of the different interventions were coordinated using the “kilometer hour” model.Results: From 2,072 originally identified titles, 59 studies were finally included in this study. After data pooling, LHTL, LHTH, and IHT outperformed normoxic training in improving the VO2max of athletes. According to the P-scores, LHTL combined with low altitude training was the most effective intervention for improving VO2max (natural: 0.92 and simulated: 0.86) and was better than LHTL combined with sea level training (0.56). A reasonable hypoxic dose range for LHTH (470–1,130 kmh) and HL (500–1,415 kmh) was reported with an inverted U-shaped curve relationship.Conclusion: Different types of hypoxic training compared with normoxic training serve as significant approaches for improving aerobic capacity in athletes. Regardless of the type of hypoxic training and the residential condition, LHTL with low altitude training was the most effective intervention. The characteristics of the dose-effect correlation of LHTH and LHTL may be associated with the negative effects of chronic hypoxia.

The problem of correlation between the Chinese green bond market and the government bond market may affect the smooth operation of the national economy. In this paper, a total of 3,181 sets of data representing the China’s green bond market and the government bond market for the period 2010–2022 are selected, and the VECM-DCC-VARMA-AGARCH model is used to analyse the spillover effects between the two in terms of information transmission and risk contagion. The results indicate that 1) The dynamic correlation between the China’s green bond market and the government bond market is significant, with obvious information transmission and risk contagion effects. 2) Compared to the government bond market, the green bond market is more sensitive to new information and the intensity of the reflection is stronger. 3) There is a long-term equilibrium relationship between the China’s green bond market and the government bond market, and the government bond market will adjust in the direction of green bonds through an error correction mechanism when deviations occur. 4) There is a significant two-way risk contagion effect between the green bond market and the government bond market, but the intensity of the effect is asymmetric. 5) The dynamic correlation between the green bond market and the government bond market has been deepening. Based on the above findings, we have put forward some rationalisation proposals.

Fiscal and taxation policy tools play an important role in promoting green and low-carbon development. Based on classical tax theory, including the Potter hypothesis and the environmental Kuznets curve, this paper explores the impact of environmental tax regulation on economic growth and carbon emission reduction. We find that resource tax reform could promote green total factor productivity; however, the ad valorem reform of resource tax does not significantly raise the level of low carbon development. This effect varies among different regions as well as different tax cuts and fee reductions. Fiscal revenue decentralization has a reverse adjustment effect on the impact of resource taxes on green total factor productivity. We conclude that it is necessary to deepen the reform of the fiscal and taxation system to achieve the carbon neutrality and emission peak goal.

Cannabidiol (CBD) is the main active ingredient in the cannabis plant used for treating epilepsy and related diseases. However, how CBD ameliorates epilepsy and its effect on the hippocampus remains unknown. Herein, we evaluated how CBD ameliorates seizure degree in pentylenetetrazol (PTZ) induced epilepsy mice after being exposed to CBD (10 mg/kg p.o). In addition, transcriptome and metabolomic analysis were performed on the hippocampus. Our results suggested that CBD could alleviate PTZ-induced seizure, of which the NPTX2, Gprc5c, Lipg, and Stc2 genes were significantly down-regulated in mice after being exposed to PTZ. Transcriptome analysis showed 97 differently expressed genes (CBD) and the PTZ groups. Metabonomic analysis revealed that compared with the PTZ group, 41 up-regulated and 67 down-regulated metabolites were identified in the hippocampus of epileptic mice exposed to CBD. The correlation analysis for transcriptome and metabolome showed that (±) 15-HETE and carnitine C6:0 were at the core of the network and were involved in the positive or negative regulation of the related genes after being treated with CBD. In conclusion, CBD ameliorates epilepsy by acting on the metabolism, calcium signaling pathway, and tuberculosis pathways in the hippocampus. Our study provided a practical basis for the therapeutic potential of treating epilepsy using CBD.

Multidrug resistance (MDR) is considered as a primary hindrance for paclitaxel failure in non-small cell lung cancer (NSCLC) patients, in which P-glycoprotein (P-gp) is overexpressed and the PI3K/Akt signaling pathway is dysregulated. Previously, we designed and synthesized DHW-221, a dual PI3K/mTOR inhibitor, which exerts a remarkable antitumor potency in NSCLC cells, but its effects and underlying mechanisms in resistant NSCLC cells remain unknown. Here, we reported for the first time that DHW-221 had favorable antiproliferative activity and suppressed cell migration and invasion in A549/Taxol cells in vitro and in vivo. Importantly, DHW-221 acted as a P-gp inhibitor via binding to P-gp, which resulted in decreased P-gp expression and function. A mechanistic study revealed that the DHW-221-induced FOXO3a nuclear translocation via Akt inhibition was involved in mitochondrial apoptosis and G0/G1 cell cycle arrest only in A549/Taxol cells and not in A549 cells. Interestingly, we observed that high-concentration DHW-221 reinforced the pro-paraptotic effect via stimulating endoplasmic reticulum (ER) stress and the mitogen-activated protein kinase (MAPK) pathway. Additionally, intragastrically administrated DHW-221 generated superior potency without obvious toxicity via FOXO3a nuclear translocation in an orthotopic A549/Taxol tumor mouse model. In conclusion, these results demonstrated that DHW-221, as a novel P-gp inhibitor, represents a prospective therapeutic candidate to overcome MDR in Taxol-resistant NSCLC treatment.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Construction of plasmids from multiple fragments often uses customised parts and leaves scars where fragments are joined. Here the authors develop a method for barcoding fragments and constructing plasmids in a scarless manner from a collection of standard parts.

Abstract Background Although anaerobic digestion for biogas production is used worldwide in treatment processes to recover energy from carbon-rich waste such as cellulosic biomass, the activities and interactions among the microbial populations that perform anaerobic digestion deserve further investigations, especially at the population genome level. To understand the cellulosic biomass-degrading potentials in two full-scale digesters, this study examined five methanogenic enrichment cultures derived from the digesters that anaerobically digested cellulose or xylan for more than 2 years under 35 or 55 °C conditions. Results Metagenomics and metatranscriptomics were used to capture the active microbial populations in each enrichment culture and reconstruct their meta-metabolic network and ecological roles. 107 population genomes were reconstructed from the five enrichment cultures using a differential coverage binning approach, of which only a subset was highly transcribed in the metatranscriptomes. Phylogenetic and functional convergence of communities by enrichment condition and phase of fermentation was observed for the highly transcribed populations in the metatranscriptomes. In the 35 °C cultures grown on cellulose, Clostridium cellulolyticum-related and Ruminococcus-related bacteria were identified as major hydrolyzers and primary fermenters in the early growth phase, while Clostridium leptum-related bacteria were major secondary fermenters and potential fatty acid scavengers in the late growth phase. While the meta-metabolism and trophic roles of the cultures were similar, the bacterial populations performing each function were distinct between the enrichment conditions. Conclusions Overall, a population genome-centric view of the meta-metabolism and functional roles of key active players in anaerobic digestion of cellulosic biomass was obtained. This study represents a major step forward towards understanding the microbial functions and interactions at population genome level during the microbial conversion of lignocellulosic biomass to methane. The knowledge of this study can facilitate development of potential biomarkers and rational design of the microbiome in anaerobic digesters.

We study a fork-join network with a single class of jobs, which are forked into a fixed number of parallel tasks upon arrival to be processed at the corresponding multi-server stations. After service completion, each task will join a buffer associated with the service station waiting for synchronization, called “unsynchronized queue”. The synchronization rule requires that all tasks from the same job must be completed, referred to as “non-exchangeable synchronization”. Once synchronized, jobs will leave the system immediately. Service times of the parallel tasks of each job can be correlated and form a sequence of i.i.d. random vectors with a general continuous joint distribution function. We study the joint dynamics of the queueing and service processes at all stations and the associated unsynchronized queueing processes. The main mathematical challenge lies in the “resequencing” of arrival orders after service completion at each station. As in Lu and Pang (2015) for the infinite-server fork-join network model, the dynamics of all the aforementioned processes can be represented via a multiparameter sequential empirical process driven by the service vectors for the parallel tasks of each job. We consider the system in the Halfin-Whitt regime, and prove a functional law of large number and a functional central limit theorem for queueing and synchronization processes. In this regime, although the delay for service at each station is asymptotically negligible, the delay for synchronization is of the same order as the service times.

Methylorubrum extorquens (formerly Methylobacterium extorquens) AM1 is a methylotrophic bacterium with a versatile lifestyle. Various carbon sources including acetate, succinate and methanol are utilized by M. extorquens AM1 with the latter being a promising inexpensive substrate for use in the biotechnology industry. Itaconic acid (ITA) is a high-value building block widely used in various industries. Given that no wildtype methylotrophic bacteria are able to utilize methanol to produce ITA, we tested the potential of M. extorquens AM1 as an engineered host for this purpose. In this study, we successfully engineered M. extorquens AM1 to express a heterologous codon-optimized gene encoding cis-aconitic acid decarboxylase. The engineered strain produced ITA using acetate, succinate and methanol as the carbon feedstock. The highest ITA titer in batch culture with methanol as the carbon source was 31.6 ± 5.5 mg/L, while the titer and productivity were 5.4 ± 0.2 mg/L and 0.056 ± 0.002 mg/L/h, respectively, in a scaled-up fed-batch bioreactor under 60% dissolved oxygen saturation. We attempted to enhance the carbon flux toward ITA production by impeding poly-β-hydroxybutyrate accumulation, which is used as carbon and energy storage, via mutation of the regulator gene phaR. Unexpectedly, ITA production by the phaR mutant strain was not higher even though poly-β-hydroxybutyrate concentration was lower. Genome-wide transcriptomic analysis revealed that phaR mutation in the ITA-producing strain led to complex rewiring of gene transcription, which might result in a reduced carbon flux toward ITA production. Besides poly-β-hydroxybutyrate metabolism, we found evidence that PhaR might regulate the transcription of many other genes including those encoding other regulatory proteins, methanol dehydrogenases, formate dehydrogenases, malate:quinone oxidoreductase, and those synthesizing pyrroloquinoline quinone and thiamine co-factors. Overall, M. extorquens AM1 was successfully engineered to produce ITA using acetate, succinate and methanol as feedstock, further supporting this bacterium as a feasible host for use in the biotechnology industry. This study showed that PhaR could have a broader regulatory role than previously anticipated, and increased our knowledge of this regulator and its influence on the physiology of M. extorquens AM1.

Nitrification plays a crucial role in global nitrogen cycling and treatment processes. However, the relationships between the nitrifier guilds of ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) are still poorly understood, especially in freshwater habitats. This study examined the physiological interactions between the AOB and NOB present in a freshwater aquarium biofilter by culturing them, either together or separately, in a synthetic medium. Metagenomic and 16S rRNA gene sequencing revealed the presence and the draft genomes of Nitrosomonas-like AOB as well as Nitrobacter-like NOB in the cultures, including the first draft genome of Nitrobacter vulgaris. The nitrifiers exhibited different growth rates with different ammonium (NH4+) or nitrite concentrations (50–1,500 μM) and the growth rates were elevated under a high bicarbonate (HCO3-) concentration. The half-saturation constant (Ks for NH4+), the maximum growth rate (μmax), and the lag duration indicated a strong dependence on the synergistic relationships between the two guilds. Overall, the ecophysiological and metagenomic results in this study provided insights into the phylogeny of the key nitrifying players in a freshwater biofilter and showed that interactions between the two nitrifying guilds in a microbial community enhanced nitrification.

The enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) functions in the shikimate pathway which is responsible for the production of aromatic amino acids and precursors of other essential secondary metabolites in all plant species. EPSPS is also the molecular target of the herbicide glyphosate. While some plant EPSPS variants have been characterized with reduced glyphosate sensitivity and have been used in biotechnology, the glyphosate insensitivity typically comes with a cost to catalytic efficiency. Thus, there exists a need to generate additional EPSPS variants that maintain both high catalytic efficiency and high glyphosate tolerance. Here, we create a synthetic yeast system to rapidly study and evolve heterologous EPSP synthases for these dual traits. Using known EPSPS variants, we first validate that our synthetic yeast system is capable of recapitulating growth characteristics observed in plants grown in varying levels of glyphosate. Next, we demonstrate that variants from mutagenesis libraries with distinct phenotypic traits can be isolated depending on the selection criteria applied. By applying strong dual-trait selection pressure, we identify a notable EPSPS mutant after just a single round of evolution that displays robust glyphosate tolerance (Ki of nearly 1 mM) and improved enzymatic efficiency over the starting point (~2.5 fold). Finally, we show the crystal structure of corn EPSPS and the top resulting mutants and demonstrate that certain mutants have the potential to outperform previously reported glyphosate-resistant EPSPS mutants, such as T102I and P106S (denoted as TIPS), in whole-plant testing. Altogether, this platform helps explore the trade-off between glyphosate resistance and enzymatic efficiency. [ABSTRACT FROM AUTHOR]