Trends and Challenges in AIoT/IIoT/IoT Implementation.

For the next coming years, metaverse, digital twin and autonomous vehicle applications are the leading technologies for many complex applications hitherto inaccessible such as health and life sciences, smart home, smart agriculture, smart city, smart car and logistics, Industry 4.0, entertainment (video game) and social media applications, due to recent tremendous developments in process modeling, supercomputing, cloud data analytics (deep learning, etc.), communication network and AIoT/IIoT/IoT technologies. AIoT/IIoT/IoT is a crucial research field because it provides the essential data to fuel metaverse, digital twin, real-time Industry 4.0 and autonomous vehicle applications. However, the science of AIoT is inherently multidisciplinary, and therefore, it is difficult for readers to understand its evolution and impacts. Our main contribution in this article is to analyze and highlight the trends and challenges of the AIoT technology ecosystem including core hardware (MCU, MEMS/NEMS sensors and wireless access medium), core software (operating system and protocol communication stack) and middleware (deep learning on a microcontroller: TinyML). Two low-powered AI technologies emerge: TinyML and neuromorphic computing, but only one AIoT/IIoT/IoT device implementation using TinyML dedicated to strawberry disease detection as a case study. So far, despite the very rapid progress of AIoT/IIoT/IoT technologies, several challenges remain to be overcome such as safety, security, latency, interoperability and reliability of sensor data, which are essential characteristics to meet the requirements of metaverse, digital twin, autonomous vehicle and Industry 4.0. applications.

Engineering of formate dehydrogenase for improving conversion potential of carbon dioxide to formate.

Formate dehydrogenase (FDH) is a D-2-hydroxy acid dehydrogenase, which can reversibly reduce CO2 to formate and thus act as non-photosynthetic CO2 reductase. In order to increase catalytic efficiency of formate dehydrogenase for CO2 reduction, two mutants V328I/F285W and V354G/F285W were obtained of which reduction activity was about two times more than the parent CbFDHM2, and the formate production from CO2 catalyzed by mutants were 2.9 and 2.7-fold higher than that of the parent CbFDHM2. The mutants had greater potential in CO2 reduction. The optimal temperature for V328I/F285W and V354G/F285W was 55 °C, and they showed increasement of relative activity under 45 °C to 55 °C compared with parent. The optimal pH for the mutants was 9.0, and they showed excellent stability in pH 4.0-11.5. The kcat/Km values of mutants were 1.75 times higher than that of the parent. Then the molecular basis for its improvement of biochemical characteristics were preliminarily elucidated by computer-aided methods. All of these results further established a solid foundation for molecular modification of formate dehydrogenase and CO2 reduction.

Prevalence of Dysphagia in China: An Epidemiological Survey of 5943 Participants.

OBJECTIVE: To determine the prevalence of dysphagia among an older population and patients with stroke, head and neck cancers (HNCs) or neurodegenerative diseases (NDDs) in China, to identify the factors associated with this condition, and to explore the relationship between dysphagia and nutritional status. METHODS: This study included participants 65 years and older living in the community or in nursing homes and patients who had sustained a stroke, HNC, or NDD also recruited in hospitals from 14 provinces of China. The presence of dysphagia was determined by use of a questionnaire, water swallowing test, and/or a videofluoroscopic swallowing study. Logistic regression analysis was used to assess the possible associated risk factors. Body mass index was assessed as an indicator of malnutrition. RESULTS: A total of 5943 persons met the inclusion criteria and 2341 (39.4%) were identified with dysphagia, including the following: 51.14% of patients with stroke, 34.4% in HNCs, 48.3% in NDDs, and 19.2% of otherwise healthy older adults. The elderly with comorbidity (OR = 2.90, p < 0.01) and stroke patients (OR = 2.27, p < 0.01) were significantly more likely to exhibit signs of dysphagia. Dysphagic participants were at significantly greater risk of malnutrition (OR = 1.91, p < 0.01) compared to those without dysphagia. CONCLUSION: Dysphagia is prevalent in China among older individuals and people who have suffered a stroke, HNCs, or NDDs. The prevalence of dysphagia increases steadily with increasing age and presence of comorbid disease. People with dysphagia are more likely to suffer from malnutrition.

Sex Differences in Prodromal Symptoms and Individual Responses to Acute Coronary Syndrome.

BACKGROUND: Although researchers have shown that prodromal symptoms can predict acute coronary events, the ability of patients with acute coronary syndrome (ACS) to identify these symptoms in a timely manner is limited. OBJECTIVES: We aimed to assess prodromal symptoms in Chinese patients with ACS and their responses to symptoms by sex. DESIGN: This cross-sectional, multicenter study involved 5 teaching hospitals in China and included 806 patients admitted for ACS between June 2013 and February 2014. The McSweeney Acute and Prodromal Myocardial Infarction Symptom Survey (Chinese version) was used to gather data. RESULTS: Among 806 patients (including 483 women), 688 (85.4%) experienced at least 1 prodromal symptom before ACS onset. Using adjusted logistic regression models, we determined that women were significantly more likely than men to report back pain, between- or under-shoulder blade pain/discomfort, sleep disturbances, anxiousness, or heart racing. The prevalence of generalized chest pain and loss of appetite was higher among men than women. Only 41% of patients attributed their prodromal symptoms to the heart, and women were more likely than men to attribute prodromal symptoms to a heart attack. CONCLUSIONS: More than two-thirds of patients with ACS reported at least 1 prodromal symptom, with some significant sex differences. Most patients do not attribute their symptoms to an impending ACS event.

Characterization of a Pestivirus H isolate originating from goats.

Natural Pestivirus H infections in cattle have been reported worldwide; however, only a few cases of Pestivirus H have been described in non-bovine ruminants such as goats. A new Pestivirus H HN1507 strain was isolated from an infected goat in 2015 and the genome sequence was determined. The full-length genome sequence was 12,556 nucleotides. Phylogenetic analysis, based on the complete genome and Npro fragments, revealed that the isolate belonged to Pestivirus H and was closely related to strains from Italy. Two unique amino acid substitutions were found in the C-terminal of the E2 protein. To the best of our knowledge, this is first report determining the complete genome of a Pestivirus H strain from goat.

A Scalable Context-Aware Objective Function (SCAOF) of Routing Protocol for Agricultural Low-Power and Lossy Networks (RPAL).

In recent years, IoT (Internet of Things) technologies have seen great advances, particularly, the IPv6 Routing Protocol for Low-power and Lossy Networks (RPL), which provides a powerful and flexible routing framework that can be applied in a variety of application scenarios. In this context, as an important role of IoT, Wireless Sensor Networks (WSNs) can utilize RPL to design efficient routing protocols for a specific application to increase the ubiquity of networks with resource-constrained WSN nodes that are low-cost and easy to deploy. In this article, our work starts with the description of Agricultural Low-power and Lossy Networks (A-LLNs) complying with the LLN framework, and to clarify the requirements of this application-oriented routing solution. After a brief review of existing optimization techniques for RPL, our contribution is dedicated to a Scalable Context-Aware Objective Function (SCAOF) that can adapt RPL to the environmental monitoring of A-LLNs, through combining energy-aware, reliability-aware, robustness-aware and resource-aware contexts according to the composite routing metrics approach. The correct behavior of this enhanced RPL version (RPAL) was verified by performance evaluations on both simulation and field tests. The obtained experimental results confirm that SCAOF can deliver the desired advantages on network lifetime extension, and high reliability and efficiency in different simulation scenarios and hardware testbeds.

Introduction on the fabrication technique of phosphor in glass by tape-casting and investigation on the chromaticity property.

We introduce a new fabrication technique of phosphor in glass (PiG) for light-emitting diodes (LEDs) employing the tape-casting. Through the detailed process described herein and the measurement results, it is clear that the PiG-on-glass not only share the same characteristic of those obtained from other techniques or the bulk PiG, but with more precisely controlled width from a few to hundreds micrometers. The samples are mounted on blue InGaN LED chips to test the color properties of the white light. Besides, we established an empirical model that could predict the final color properties of LEDs solely by the phosphor concentration of phosphor glass under certain conditions. This model would greatly facilitate the design of PiG-based LEDs.

MIROS: a hybrid real-time energy-efficient operating system for the resource-constrained wireless sensor nodes.

Operating system (OS) technology is significant for the proliferation of the wireless sensor network (WSN). With an outstanding OS; the constrained WSN resources (processor; memory and energy) can be utilized efficiently. Moreover; the user application development can be served soundly. In this article; a new hybrid; real-time; memory-efficient; energy-efficient; user-friendly and fault-tolerant WSN OS MIROS is designed and implemented. MIROS implements the hybrid scheduler and the dynamic memory allocator. Real-time scheduling can thus be achieved with low memory consumption. In addition; it implements a mid-layer software EMIDE (Efficient Mid-layer Software for User-Friendly Application Development Environment) to decouple the WSN application from the low-level system. The application programming process can consequently be simplified and the application reprogramming performance improved. Moreover; it combines both the software and the multi-core hardware techniques to conserve the energy resources; improve the node reliability; as well as achieve a new debugging method. To evaluate the performance of MIROS; it is compared with the other WSN OSes (TinyOS; Contiki; SOS; openWSN and mantisOS) from different OS concerns. The final evaluation results prove that MIROS is suitable to be used even on the tight resource-constrained WSN nodes. It can support the real-time WSN applications. Furthermore; it is energy efficient; user friendly and fault tolerant.

Memory and energy optimization strategies for multithreaded operating system on the resource-constrained wireless sensor node.

Memory and energy optimization strategies are essential for the resource-constrained wireless sensor network (WSN) nodes. In this article, a new memory-optimized and energy-optimized multithreaded WSN operating system (OS) LiveOS is designed and implemented. Memory cost of LiveOS is optimized by using the stack-shifting hybrid scheduling approach. Different from the traditional multithreaded OS in which thread stacks are allocated statically by the pre-reservation, thread stacks in LiveOS are allocated dynamically by using the stack-shifting technique. As a result, memory waste problems caused by the static pre-reservation can be avoided. In addition to the stack-shifting dynamic allocation approach, the hybrid scheduling mechanism which can decrease both the thread scheduling overhead and the thread stack number is also implemented in LiveOS. With these mechanisms, the stack memory cost of LiveOS can be reduced more than 50% if compared to that of a traditional multithreaded OS. Not is memory cost optimized, but also the energy cost is optimized in LiveOS, and this is achieved by using the multi-core "context aware" and multi-core "power-off/wakeup" energy conservation approaches. By using these approaches, energy cost of LiveOS can be reduced more than 30% when compared to the single-core WSN system. Memory and energy optimization strategies in LiveOS not only prolong the lifetime of WSN nodes, but also make the multithreaded OS feasible to run on the memory-constrained WSN nodes.

The role of cellular senescence-related genes in Asthma: Insights from bioinformatics and animal experiments.

BACKGROUND: Asthma is a heterogeneous chronic respiratory disease, affecting about 10% of the global population. Cellular senescence is a multifaceted phenomenon defined as the irreversible halt of the cell cycle, commonly referred to as the senescence-associated secretory phenotype. Recent studies suggest that cellular senescence may play a role in asthma. This study aims to dissect the role and biological mechanisms of CSRGs in asthma, enhancing our understanding of the progression of asthma. METHODS: The study utilized the GSE147878 dataset, employing methods like WGCNA, Differential analysis, Cibersort, GO, KEGG, unsupervised clustering, and GSVA to explore CSRGs functions and immune cell patterns in asthma. Machine learning identified key diagnostic genes, validated externally with the GSE165934 dataset and through qRT-PCR and WB experiments in animal models. RESULT: From the GSE147878 dataset, 24 CSRGs were identified, highlighting their role in immune and inflammatory processes in asthma. Differences in CD4 naive T cells and activated dendritic cells between asthma and control groups underscored CSRGs' role in immune regulation. Cluster analysis revealed two distinct asthma patient groups with unique immune microenvironments. Machine learning identified five genes, leading to a TF-miRNA-mRNA network and singling out RHOA and RBM39 as key diagnostic genes, which were experimentally validated. Finally, a nomogram was created based on these genes. CONCLUSION: This study, utilizing bioinformatics and animal experiments, identified RHOA and RBM39 as key diagnostic genes for asthma, providing new insights into the potential role and biological mechanisms of CSRGs in asthma.

Exploring the Pathogenesis and Treatment of PSD from the Perspective of Gut Microbiota.

Post-stroke depression (PSD) is a psychological disease that can occur following a stroke and is associated with serious consequences. Research on the pathogenesis and treatment of PSD is still in the infancy stage. Patients with PSD often exhibit gastrointestinal symptoms; therefore the role of gut microbiota in the pathophysiology and potential treatment effects of PSD has become a hot topic of research. In this review, describe the research on the pathogenesis and therapy of PSD. We also describe how the gut microbiota influences neurotransmitters, the endocrine system, energy metabolism, and the immune system. It was proposed that the gut microbiota is involved in the pathogenesis and treatment of PSD through the regulation of neurotransmitter levels, vagal signaling, hypothalamic-pituitary-adrenal axis activation and inhibition, hormone secretion and release, in addition to immunity and inflammation.

Combining Flexible Region Design and Automatic Design to Enhance the Thermal Stability and Catalytic Efficiency of Leucine Dehydrogenase.

Leucine dehydrogenase (LeuDH, EC 1.4.1.9) can reversibly catalyze the oxidative deamination of l-leucine and some other specific α-amino acids to form the corresponding α-ketoacids. This reaction has great significance in the field of food additives and the pharmaceutical industry. The LeuDH from Exiguobacterium sibiricum (EsLeuDH) has high catalytic efficiency but limited thermal stability, hindering its widespread industrial application. In this study, a mutant N5F/I12L/A352Y of EsLeuDH (referred to as M2) was developed with enhanced thermal stability and catalytic activity through rational modification. The M2 mutant exhibits a half-life at 60 °C (t1/2(60 °C)) of 975.7 min and a specific activity of 69.6 U mg-1, which is 5.4 and 2.1 times higher than those of EsLeuDH, respectively. This research may facilitate the utilization of EsLeuDH at elevated temperatures, enhancing its potential for industrial applications. The findings offer a practical and efficient approach for optimizing LeuDH and other industrial enzymes.

Exploration of the Binding Mechanism of Cyclic Dinucleotide Analogs to Stimulating Factor Proteins and the Implications for Subsequent Analog Drug Design.

Cyclic dinucleotides (CDNs) are cyclic molecules consisting of two nucleoside monophosphates linked by two phosphodiester bonds, which act as a second messenger and bind to the interferon gene stimulating factor (STING) to activate the downstream signaling pathway and ultimately induce interferon secretion, initiating an anti-infective immune response. Cyclic dinucleotides and their analogs are lead compounds in the immunotherapy of infectious diseases and tumors, as well as immune adjuvants with promising applications. Many agonists of pathogen recognition receptors have been developed as effective adjuvants to optimize vaccine immunogenicity and efficacy. In this work, the binding mechanism of human-derived interferon gene-stimulating protein and its isoforms with cyclic dinucleotides and their analogs was theoretically investigated using computer simulations and combined with experimental results in the hope of providing guidance for the subsequent synthesis of cyclic dinucleotide analogs.

Nanomaterial-Based Drug Delivery Systems for Ischemic Stroke.

Ischemic stroke is a leading cause of death and disability in the world. At present, reperfusion therapy and neuroprotective therapy, as guidelines for identifying effective and adjuvant treatment methods, are limited by treatment time windows, drug bioavailability, and side effects. Nanomaterial-based drug delivery systems have the characteristics of extending half-life, increasing bioavailability, targeting drug delivery, controllable drug release, and low toxicity, thus being used in the treatment of ischemic stroke to increase the therapeutic effects of drugs. Therefore, this review provides a comprehensive overview of nanomaterial-based drug delivery systems from nanocarriers, targeting ligands and stimulus factors of drug release, aiming to find the best combination of nanomaterial-based drug delivery systems for ischemic stroke. Finally, future research areas on nanomaterial-based drug delivery systems in ischemic stroke and the implications of the current knowledge for the development of novel treatment for ischemic stroke were identified.

High level expression of nicotinamide nucleoside kinase from Saccharomyces cerevisiae and its purification and immobilization by one-step method.

Nicotinamide riboside kinase (NRK) plays an important role in the synthesis of ß -nicotinamide nucleotide (NMN). NMN is a key intermediate of NAD+ synthesis, and it actually contribute to the well-being of our health. In this study, gene mining technology was used to clone nicotinamide nucleoside kinase gene fragments from S. cerevisiae, and the ScNRK1 was achieved a high level of soluble expression in E. coli BL21. Then, the reScNRK1 was immobilized by metal affinity label to optimize the enzyme performance. The results showed that the enzyme activity in the fermentation broth was 14.75 IU/mL, and the specific enzyme activity after purification was 2252.59 IU/mg. After immobilization, the optimum temperature of the immobilized enzyme was increased by 10°C compared with the free enzyme, and the temperature stability was improved with little change in pH. Moreover, the activity of the immobilized enzyme remained above 80% after four cycles of immobilized reScNRK1, which makes the enzyme more advantageous in the enzymatic synthesis of NMN.

Machine learning in the prediction of post-stroke cognitive impairment: a systematic review and meta-analysis.

Objective: Cognitive impairment is a detrimental complication of stroke that compromises the quality of life of the patients and poses a huge burden on society. Due to the lack of effective early prediction tools in clinical practice, many researchers have introduced machine learning (ML) into the prediction of post-stroke cognitive impairment (PSCI). However, the mathematical models for ML are diverse, and their accuracy remains highly contentious. Therefore, this study aimed to examine the efficiency of ML in the prediction of PSCI. Methods: Relevant articles were retrieved from Cochrane, Embase, PubMed, and Web of Science from the inception of each database to 5 December 2022. Study quality was evaluated by PROBAST, and c-index, sensitivity, specificity, and overall accuracy of the prediction models were meta-analyzed. Results: A total of 21 articles involving 7,822 stroke patients (2,876 with PSCI) were included. The main modeling variables comprised age, gender, education level, stroke history, stroke severity, lesion volume, lesion site, stroke subtype, white matter hyperintensity (WMH), and vascular risk factors. The prediction models used were prediction nomograms constructed based on logistic regression. The pooled c-index, sensitivity, and specificity were 0.82 (95% CI 0.77-0.87), 0.77 (95% CI 0.72-0.80), and 0.80 (95% CI 0.71-0.86) in the training set, and 0.82 (95% CI 0.77-0.87), 0.82 (95% CI 0.70-0.90), and 0.80 (95% CI 0.68-0.82) in the validation set, respectively. Conclusion: ML is a potential tool for predicting PSCI and may be used to develop simple clinical scoring scales for subsequent clinical use. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=383476.

Falls caused by balance disorders in the elderly with multiple systems involved: Pathogenic mechanisms and treatment strategies.

Falls are the main contributor to both fatal and nonfatal injuries in elderly individuals as well as significant sources of morbidity and mortality, which are mostly induced by impaired balance control. The ability to keep balance is a remarkably complex process that allows for rapid and precise changes to prevent falls with multiple systems involved, such as musculoskeletal system, the central nervous system and sensory system. However, the exact pathogenesis of falls caused by balance disorders in the elderly has eluded researchers to date. In consideration of aging phenomenon aggravation and fall risks in the elderly, there is an urgent need to explore the pathogenesis and treatments of falls caused by balance disorders in the elderly. The present review discusses the epidemiology of falls in the elderly, potential pathogenic mechanisms underlying multiple systems involved in falls caused by balance disorders, including musculoskeletal system, the central nervous system and sensory system. Meanwhile, some common treatment strategies, such as physical exercise, new equipment based on artificial intelligence, pharmacologic treatments and fall prevention education are also reviewed. To fully understand the pathogenesis and treatment of falls caused by balance disorders, a need remains for future large-scale multi-center randomized controlled trials and in-depth mechanism studies.

Mycobacterium tuberculosis Fatty Acyl-CoA Synthetase fadD33 Promotes Bacillus Calmette-Guérin Survival in Hostile Extracellular and Intracellular Microenvironments in the Host.

Tuberculosis, caused by Mycobacterium tuberculosis (M. tb), remains a significant global health challenge. The survival of M. tb in hostile extracellular and intracellular microenvironments is crucial for its pathogenicity. In this study, we discovered a Bacillus Calmette-Guérin (BCG) mutant B1033 that potentially affected mycobacterium pathogenicity. This mutant contained an insertion mutation gene, fadD33, which is involved in lipid metabolism; however, its direct role in regulating M. tb infection is not well understood. Here, we found that the absence of fadD33 reduced BCG adhesion and invasion into human pulmonary alveolar epithelial cells and increased the permeability of the mycobacterial cell wall, allowing M. tb to survive in the low pH and membrane pressure extracellular microenvironment of the host cells. The absence of fadD33 also inhibited the survival of BCG in macrophages by promoting the release of proinflammatory cytokines, such as interleukin (IL)-1ß, IL-6, and tumors necrosis factor-α, through the mitogen-activated protein kinase p38 signaling pathway. Overall, these findings provide new insights into M. tb mechanisms to evade host defenses and might contribute to identifying potential therapeutic and vaccine targets for tuberculosis prevention.

Regulatory Effects of Quercetin on Bone Homeostasis: Research Updates and Future Perspectives.

The imbalance of bone homeostasis has become a major public medical problem amid the background of an aging population, which is closely related to the occurrence of osteoporosis, osteoarthritis, and fractures. Presently, most drugs used in the clinical treatment of bone homeostasis imbalance are bisphosphonates, calcitonin, estrogen receptor modulators, and biological agents that inhibit bone resorption or parathyroid hormone analogs that promote bone formation. However, there are many adverse reactions. Therefore, it is necessary to explore potential drugs. Quercetin, as a flavonol compound with various biological activities, is widely distributed in plants. Studies have found that quercetin can regulate bone homeostasis through multiple pathways and targets. An in-depth exploration of the pharmacological mechanism of quercetin is of great significance for the development of new drugs. This review discusses the therapeutic mechanisms of quercetin on bone homeostasis, such as regulating the expression of long non-coding RNA, signaling pathways of bone metabolism, various types of programmed cell death, bone nutrients supply pathways, anti-oxidative stress, anti-inflammation, and activation of Sirtuins. We also summarize recent progress in improving quercetin bioavailability and propose some issues worth paying attention to, which may help guide future research efforts.

Cloning and bioinformatics analysis of an endoglucanase gene (Aucel12A) from Aspergillus usamii and its functional expression in Pichia pastoris.

Using 3' and 5' rapid amplification of cDNA ends methods, the full-length cDNA sequence encoding an endo-1,4-ß-glucanase of Aspergillus usamii E001 (abbreviated as AuCel12A) was amplified from the total RNA. The clone cDNA sequence of the gene encoding the AuCel12A, named as Aucel12A, is 1,027 bp in length harboring 5' and 3' non-coding regions, as well as a 720 bp of open reading frame that encodes a 16-aa signal peptide, and a 223-aa mature AuCel12A with a theoretical M.W. of 24,294 Da, a calculated pI of 4.15, and one putative N-glycosylation site. The complete DNA sequence of the gene Aucel12A was amplified from the genomic DNA of A. usamii E001 by using the conventional PCR and pUCm-T vector-mediated PCR initially developed in our lab. The clone DNA sequence is 1,576 bp in length, consisting of a 5' flanking regulatory region, three exons, and two introns with sizes of 50 and 66 bp. The cDNA fragment encoding the mature AuCel12A was expressed in a fully active form in Pichia pastoris. One P. pastoris transformant expressing the highest recombinant AuCel12A (rAuCel12A) activity, labeled as P. pastoris GSCel2-1, was chosen for subsequent studies. Integration of the Aucel12A into P. pastoris genome was confirmed by PCR analysis using 5'- and 3'-AOX1 primers. SDS-PAGE and enzyme activity assays demonstrated that the rAuCel12A, a glycosylated protein with an apparent M.W. of 27.0 kDa and a carbohydrate content of 4.82%, was secreted into the culture medium. The purified rAuCel12A displayed the highest activity at pH 5.0 and 60°C. It was highly stable at a pH range of 3.5-7.0, and at a temperature of 55°C or below. Its activity was not significantly affected by an array of metal ions and EDTA, but inhibited by Ag⁺, Hg²âº and Fe²âº. The K(m) and V(max) of the rAuCel12A, towards carboxymethylcellulose-Na (CMC-Na) at pH 5.0 and 50°C were 4.85 mg/ml and 160.5 U/mg, respectively.