tRNA modifications and tRNA-derived small RNAs: new insights of tRNA in human disease.

tRNAs are codon decoders that convert the transcriptome into the proteome. The field of tRNA research is excited by the increasing discovery of specific tRNA modifications that are installed at specific, evolutionarily conserved positions by a set of specialized tRNA-modifying enzymes and the biogenesis of tRNA-derived regulatory fragments (tsRNAs) which exhibit copious activities through multiple mechanisms. Dysregulation of tRNA modification usually has pathological consequences, a phenomenon referred to as "tRNA modopathy". Current evidence suggests that certain tRNA-modifying enzymes and tsRNAs may serve as promising diagnostic biomarkers and therapeutic targets, particularly for chemoresistant cancers. In this review, we discuss the latest discoveries that elucidate the molecular mechanisms underlying the functions of clinically relevant tRNA modifications and tsRNAs, with a focus on malignancies. We also discuss the therapeutic potential of tRNA/tsRNA-based therapies, aiming to provide insights for the development of innovative therapeutic strategies. Further efforts to unravel the complexities inherent in tRNA biology hold the promise of yielding better biomarkers for the diagnosis and prognosis of diseases, thereby advancing the development of precision medicine for health improvement.

Future in the past: paternal reprogramming of offspring phenotype and the epigenetic mechanisms.

That certain preconceptual paternal exposures reprogram the developmental phenotypic plasticity in future generation(s) has conceptualized the "paternal programming of offspring health" hypothesis. This transgenerational effect is transmitted primarily through sperm epigenetic mechanisms-DNA methylation, non-coding RNAs (ncRNAs) and associated RNA modifications, and histone modifications-and potentially through non-sperm-specific mechanisms-seminal plasma and circulating factors-that create 'imprinted' memory of ancestral information. The epigenetic landscape in sperm is highly responsive to environmental cues, due to, in part, the soma-to-germline communication mediated by epididymosomes. While human epidemiological studies and experimental animal studies have provided solid evidences in support of transgenerational epigenetic inheritance, how ancestral information is memorized as epigenetic codes for germline transmission is poorly understood. Particular elusive is what the downstream effector pathways that decode those epigenetic codes into persistent phenotypes. In this review, we discuss the paternal reprogramming of offspring phenotype and the possible underlying epigenetic mechanisms. Cracking these epigenetic mechanisms will lead to a better appreciation of "Paternal Origins of Health and Disease" and guide innovation of intervention algorithms to achieve 'healthier' outcomes in future generations. All this will revolutionize our understanding of human disease etiology.

Effects of Active Chronic Cigarette-Smoke Exposure on Circulating Fibrocytes.

PURPOSE: This study aimed to evaluate the hypothesis that active smoking impacts upon mediators and abundance of circulating fibrocyte cells in smoking-related disease characterised by fibrosis. METHODS: Flow cytometry and enzyme-linked immunosorbent assays were used to investigate blood from five patient groups: healthy never-smokers, healthy current smokers, stable chronic obstructive pulmonary disease (COPD) active smokers, idiopathic pulmonary fibrosis (IPF) never-smokers, and IPF active smokers. RESULTS: A significant inverse dose-response relationship was observed in healthy smokers among cumulative smoking burden (pack-years) and fibrocyte abundance (p = 0.006, r = -0.86). Among serum profibrotic fibrocyte chemokines measured, CCL18 rose significantly alongside fibrocyte numbers in all five subject groups, while having an inverse dose-response relationship with pack-year burden in healthy smokers (p = 0.003, r = -0.89). In IPF, CCL2 rose in direct proportion to fibrocyte abundance irrespective of smoking status but had lower serum levels in those currently smoking (p = < 0.001). For the study population, CXCL12 was decreased in pooled current smokers versus never-smokers (p = 0.03). CONCLUSION: The suppressive effect of current, as distinct from former, chronic smoking on circulating fibrocyte abundance in healthy smokers, and modulation of regulatory chemokine levels by active smoking may have implications for future studies of fibrocytes in smoking-related lung diseases as a potential confounding variable.

Emerging Trends and Challenges of IoT in Smart Healthcare Systems, Smart Cities and Education.

Due to the rapid growth of science and technology, many modern devices are being developed to support healthcare and education systems [...].

Editing microbes to mitigate enteric methane emissions in livestock.

Livestock production significantly contributes to greenhouse gas (GHG) emissions particularly methane (CH4) emissions thereby influencing climate change. To address this issue further, it is crucial to establish strategies that simultaneously increase ruminant productivity while minimizing GHG emissions, particularly from cattle, sheep, and goats. Recent advancements have revealed the potential for modulating the rumen microbial ecosystem through genetic selection to reduce methane (CH4) production, and by microbial genome editing including CRISPR/Cas9, TALENs (Transcription Activator-Like Effector Nucleases), ZFNs (Zinc Finger Nucleases), RNA interference (RNAi), Pime editing, Base editing and double-stranded break-free (DSB-free). These technologies enable precise genetic modifications, offering opportunities to enhance traits that reduce environmental impact and optimize metabolic pathways. Additionally, various nutrition-related measures have shown promise in mitigating methane emissions to varying extents. This review aims to present a future-oriented viewpoint on reducing methane emissions from ruminants by leveraging CRISPR/Cas9 technology to engineer the microbial consortia within the rumen. The ultimate objective is to develop sustainable livestock production methods that effectively decrease methane emissions, while maintaining animal health and productivity.

Mastering tracheostomy care: Refresher programme for tracheostomy training for nurses: Comparison of two training methods based on hands-on simulation-based training alone versus additional complementary self-directed e-learning.

BACKGROUND: Effective clinical education is essential for managing tracheostomy patients safely and efficiently. Simulation-based training has shown greater efficacy than traditional methods in various clinical settings. Our internal training programme, called the Tracheostomy Refresher Program (TRP) was used to enhance nurses' skills in tracheostomy care. AIM/OBJECTIVE: The aim of this study was to evaluate the impact of the TRP on nurses' self-reported knowledge and confidence and psychomotor skills comparing hands-on simulation-based training alone (TRP-S) with both the simulation-based training and the e-learning component (TRP-S + e). METHODS: The study was conducted at a large tertiary hospital in Singapore from February 2022 to October 2022, focussing on the TRP. Participants were divided into two cohorts: those receiving TRP-S and those receiving additional complementary TRP-S + e. All participants completed theory tests and affective questionnaires before and after the training to assess knowledge and attitudes. At the same time, their psychomotor skills were evaluated during the simulation using a standardised checklist. The two cohorts were then compared based on the results of these pretests and post-tests and the psychomotor skills assessment to evaluate the effectiveness of the additional e-learning component. RESULTS: Participants reported significantly enhanced confidence, knowledge, and psychomotor skills in tracheostomy care post training (p < 0.001 for all). The TRP-S + e cohort showed significantly higher knowledge and confidence scores than the TRP-S cohort (p < 0.001 for both). CONCLUSION: Our study suggests that a TRP incorporating hands-on simulation-based training with or without e-learning significantly improved self-reported knowledge, confidence, and psychomotor skills in tracheostomy care. Future research should explore the optimal duration, engagement strategies, and cost-effectiveness of such educational techniques and whether similar approaches can be applied for other clinical skills.

The emerging era of lactate: A rising star in cellular signaling and its regulatory mechanisms.

Cellular metabolites are ancient molecules with pleiotropic implications in health and disease. Beyond their cognate roles, they have signaling functions as the ligands for specific receptors and the precursors for epigenetic or posttranslational modifications. Lactate has long been recognized as a metabolic waste and fatigue product mainly produced from glycolytic metabolism. Recent evidence however suggests lactate is an unique molecule with diverse signaling attributes in orchestration of numerous biological processes, including tumor immunity and neuronal survival. The copious metabolic and non-metabolic functions of lactate mediated by its bidirectional shuttle between cells or intracellular organelles lead to a phenotype called "lactormone." Importantly, the mechanisms of lactate signaling, via acting as a molecular sensor and a regulator of NAD+ metabolism and AMP-activated protein kinase signaling, and via the newly identified lactate-driven lactylation, have been discovered. Further, we include a brief discussion about the autocrine regulation of efferocytosis by lactate in Sertoli cells which favoraerobic glycolysis. By emphasizing a repertoire of the most recent discovered mechanisms of lactate signaling, this review will open tantalizing avenues for future investigations cracking the regulatory topology of lactate signaling covered in the veil of mystery.

Recent advances in chromosome capture techniques unraveling 3D genome architecture in germ cells, health, and disease.

In eukaryotes, the genome does not emerge in a specific shape but rather as a hierarchial bundle within the nucleus. This multifaceted genome organization consists of multiresolution cellular structures, such as chromosome territories, compartments, and topologically associating domains, which are frequently defined by architecture, design proteins including CTCF and cohesin, and chromatin loops. This review briefly discusses the advances in understanding the basic rules of control, chromatin folding, and functional areas in early embryogenesis. With the use of chromosome capture techniques, the latest advancements in technologies for visualizing chromatin interactions come close to revealing 3D genome formation frameworks with incredible detail throughout all genomic levels, including at single-cell resolution. The possibility of detecting variations in chromatin architecture might open up new opportunities for disease diagnosis and prevention, infertility treatments, therapeutic approaches, desired exploration, and many other application scenarios.

Unlocking gut microbiota potential of dairy cows in varied environmental conditions using shotgun metagenomic approach.

Food security and environmental pollution are major concerns for the expanding world population, where farm animals are the largest source of dietary proteins and are responsible for producing anthropogenic gases, including methane, especially by cows. We sampled the fecal microbiomes of cows from varying environmental regions of Pakistan to determine the better-performing microbiomes for higher yields and lower methane emissions by applying the shotgun metagenomic approach. We selected managed dairy farms in the Chakwal, Salt Range, and Patoki regions of Pakistan, and also incorporated animals from local farmers. Milk yield and milk fat, and protein contents were measured and correlated with microbiome diversity and function. The average milk protein content from the Salt Range farms was 2.68%, with an average peak milk yield of 45 litters/head/day, compared to 3.68% in Patoki farms with an average peak milk yield of 18 litters/head/day. Salt-range dairy cows prefer S-adenosyl-L-methionine (SAMe) to S-adenosyl-L-homocysteine (SAH) conversion reactions and are responsible for low milk protein content. It is linked to Bacteroides fragilles which account for 10% of the total Bacteroides, compared to 3% in the Patoki region. The solid Non-Fat in the salt range was 8.29%, whereas that in patoki was 6.34%. Moreover, Lactobacillus plantarum high abundance in Salt Range provided propionate as alternate sink to [H], and overcoming a Methanobrevibacter ruminantium high methane emissions in the Salt Range. Furthermore, our results identified ruminant fecal microbiomes that can be used as fecal microbiota transplants (FMT) to high-methane emitters and low-performing herds to increase farm output and reduce the environmental damage caused by anthropogenic gases emitted by dairy cows.

Inhaled volatile anesthetic gas for severe bronchospasm in the emergency department.

Bronchospasm is caused by reversible constriction of the smooth muscles of the bronchial tree. This causes obstruction of the lower airways, which is commonly seen at the emergency department (ED) in patients with acute exacerbation of asthma or chronic obstructive pulmonary disease. Ventilation may be difficult in mechanically intubated patients with severe bronchospasm due to airflow limitation, air trapping, and high airway resistance. The beneficial effects of volatile inhaled anesthetic gas had been reported due to its bronchodilation properties. In this case series, we would like to share our experience delivering inhaled volatile anesthetic gas via a conserving device for three patients with refractory bronchospasm at the ED. Inhaled anesthetic gas is safe, feasible and should be considered as an alternative rescue therapy for ventilated patients with severe lower airway obstruction.

The Potential of Blockchain Technology in Dental Healthcare: A Literature Review.

Blockchain technology in the healthcare industry has potential to enable enhanced privacy, increased security, and an interoperable data record. Blockchain technology is being implemented in dental care systems to store and share medical information, improve insurance claims, and provide innovative dental data ledgers. Because the healthcare sector is a large and ever-growing industry, the use of blockchain technology would have many benefits. To improve dental care delivery, researchers advocate using blockchain technology and smart contracts due to their numerous advantages. In this research, we concentrate on blockchain-based dental care systems. In particular, we examine the current research literature, pinpoint issues with existing dental care systems, and consider how blockchain technology may be used to address these issues. Finally, the limitations of the proposed blockchain-based dental care systems are discussed which may be regarded as open issues.

Historical Text Image Enhancement Using Image Scaling and Generative Adversarial Networks.

Historical documents such as newspapers, invoices, contract papers are often difficult to read due to degraded text quality. These documents may be damaged or degraded due to a variety of factors such as aging, distortion, stamps, watermarks, ink stains, and so on. Text image enhancement is essential for several document recognition and analysis tasks. In this era of technology, it is important to enhance these degraded text documents for proper use. To address these issues, a new bi-cubic interpolation of Lifting Wavelet Transform (LWT) and Stationary Wavelet Transform (SWT) is proposed to enhance image resolution. Then a generative adversarial network (GAN) is used to extract the spectral and spatial features in historical text images. The proposed method consists of two parts. In the first part, the transformation method is used to de-noise and de-blur the images, and to increase the resolution effects, whereas in the second part, the GAN architecture is used to fuse the original and the resulting image obtained from part one in order to improve the spectral and spatial features of a historical text image. Experiment results show that the proposed model outperforms the current deep learning methods.

Monkeypox Detection Using CNN with Transfer Learning.

Monkeypox disease is caused by a virus that causes lesions on the skin and has been observed on the African continent in the past years. The fatal consequences caused by virus infections after the COVID pandemic have caused fear and panic among the public. As a result of COVID reaching the pandemic dimension, the development and implementation of rapid detection methods have become important. In this context, our study aims to detect monkeypox disease in case of a possible pandemic through skin lesions with deep-learning methods in a fast and safe way. Deep-learning methods were supported with transfer learning tools and hyperparameter optimization was provided. In the CNN structure, a hybrid function learning model was developed by customizing the transfer learning model together with hyperparameters. Implemented on the custom model MobileNetV3-s, EfficientNetV2, ResNET50, Vgg19, DenseNet121, and Xception models. In our study, AUC, accuracy, recall, loss, and F1-score metrics were used for evaluation and comparison. The optimized hybrid MobileNetV3-s model achieved the best score, with an average F1-score of 0.98, AUC of 0.99, accuracy of 0.96, and recall of 0.97. In this study, convolutional neural networks were used in conjunction with optimization of hyperparameters and a customized hybrid function transfer learning model to achieve striking results when a custom CNN model was developed. The custom CNN model design we have proposed is proof of how successfully and quickly the deep learning methods can achieve results in classification and discrimination.

IoMT-Enabled Computer-Aided Diagnosis of Pulmonary Embolism from Computed Tomography Scans Using Deep Learning.

The Internet of Medical Things (IoMT) has revolutionized Ambient Assisted Living (AAL) by interconnecting smart medical devices. These devices generate a large amount of data without human intervention. Learning-based sophisticated models are required to extract meaningful information from this massive surge of data. In this context, Deep Neural Network (DNN) has been proven to be a powerful tool for disease detection. Pulmonary Embolism (PE) is considered the leading cause of death disease, with a death toll of 180,000 per year in the US alone. It appears due to a blood clot in pulmonary arteries, which blocks the blood supply to the lungs or a part of the lung. An early diagnosis and treatment of PE could reduce the mortality rate. Doctors and radiologists prefer Computed Tomography (CT) scans as a first-hand tool, which contain 200 to 300 images of a single study for diagnosis. Most of the time, it becomes difficult for a doctor and radiologist to maintain concentration going through all the scans and giving the correct diagnosis, resulting in a misdiagnosis or false diagnosis. Given this, there is a need for an automatic Computer-Aided Diagnosis (CAD) system to assist doctors and radiologists in decision-making. To develop such a system, in this paper, we proposed a deep learning framework based on DenseNet201 to classify PE into nine classes in CT scans. We utilized DenseNet201 as a feature extractor and customized fully connected decision-making layers. The model was trained on the Radiological Society of North America (RSNA)-Pulmonary Embolism Detection Challenge (2020) Kaggle dataset and achieved promising results of 88%, 88%, 89%, and 90% in terms of the accuracy, sensitivity, specificity, and Area Under the Curve (AUC), respectively.

Development of a Smart Signalization for Emergency Vehicles.

As the population increases, the number of motorized vehicles on the roads also increases. As the number of vehicles increases, traffic congestion occurs. Traffic lights are used at road junctions, intersections, pedestrian crossings, and other places where traffic needs to be controlled to avoid traffic chaos. Due to traffic lights installed in the city, queues of vehicles are formed on the streets for most of the day, and many problems arise because of this. One of the most important problems is that emergency vehicles, such as ambulances, fire engines, police cars, etc., cannot arrive on time despite traffic priorities. Emergency vehicles such as hospitals and police departments need to reach the scene in a very short time. Time loss is a problem that needs to be addressed, especially for emergency vehicles traveling in traffic. In this study, ambulances, fire brigades, police, etc., respond to emergencies. A solution and a related application have been developed so privileged vehicles can reach their target destination as soon as possible. In this study, a route is determined between the current location of an emergency vehicle and its target location in an emergency. Communication between traffic lights is provided with a mobile application developed specifically for the vehicle driver. In this process, the person controlling the lights can turn on the traffic lights during the passage of vehicles. After the vehicles with priority to pass passed, traffic signaling was normalized via the mobile application. This process was repeated until the vehicle reached its destination.

Traffic Management in IoT Backbone Networks Using GNN and MAB with SDN Orchestration.

Traffic management is a critical task in software-defined IoT networks (SDN-IoTs) to efficiently manage network resources and ensure Quality of Service (QoS) for end-users. However, traditional traffic management approaches based on queuing theory or static policies may not be effective due to the dynamic and unpredictable nature of network traffic. In this paper, we propose a novel approach that leverages Graph Neural Networks (GNNs) and multi-arm bandit algorithms to dynamically optimize traffic management policies based on real-time network traffic patterns. Specifically, our approach uses a GNN model to learn and predict network traffic patterns and a multi-arm bandit algorithm to optimize traffic management policies based on these predictions. We evaluate the proposed approach on three different datasets, including a simulated corporate network (KDD Cup 1999), a collection of network traffic traces (CAIDA), and a simulated network environment with both normal and malicious traffic (NSL-KDD). The results demonstrate that our approach outperforms other state-of-the-art traffic management methods, achieving higher throughput, lower packet loss, and lower delay, while effectively detecting anomalous traffic patterns. The proposed approach offers a promising solution to traffic management in SDNs, enabling efficient resource management and QoS assurance.

Automated rapid response system activation-Impact on nurses' attitudes and perceptions towards recognising and responding to clinical deterioration: Mixed-methods study.

AIM: To explore general ward nurses' attitudes and perceptions towards recognising and responding to clinical deterioration in a hospital with automated rapid response system activation. BACKGROUND: There is growing interest in deploying automated clinical deterioration notification systems to reduce delayed or failed recognition and response to clinical deterioration of ward patients. However, little is known about its impact on ward nurses' perspectives and work patterns. DESIGN: A mixed-methods study. METHODS: Online survey of 168 registered nurses and individual interviews with 10 registered nurses in one acute hospital in Singapore. The study adhered to the STROBE checklist for cross-sectional studies and the COREQ guidelines for qualitative studies. RESULTS: Many nurses (38.1%) rarely performed patient assessments or observations other than vital signs assessment to assess for early signs of clinical deterioration. About 30% were worried about being criticised for calling the primary team doctors. Four themes emerged from the qualitative analysis: automated rapid response system activation as a safety net, being more cautious with vital signs monitoring, the NEWS2 alone is inadequate, and ward nurses as the 'middleman' between the intensive care unit outreach nurse and primary team doctors. CONCLUSIONS: Although nurses value the automated rapid response system activation as a safety net to minimise delays in accessing urgent critical care resources, it does not address the sociocultural barriers inherent in escalation of care. Although the automated system led nurses to be more cautious with vital signs monitoring, it does not encourage them to perform comprehensive patient assessments to detect early signs of deterioration. RELEVANCE TO CLINICAL PRACTICE: Nurse education on assessing for clinical deterioration should focus on the use of broader patient assessment skills other than vital signs. Sociocultural barriers to escalation of care remain a key issue that needs to be addressed by hospital management. NO PATIENT OR PUBLIC CONTRIBUTION: No patients, service users, care-givers or members of the public were involved in the study.

Nanomechanical Sensing Using Heater-Integrated Fluidic Resonators.

Micro/nanochannel resonators have been used to measure cells, suspended nanoparticles, or liquids, primarily at or near room temperature while their high temperature operation can offer promising applications such as calorimetric measurements and thermogravimetric analysis. To date, global electrothermal or local photothermal heating mechanisms have been attempted for channel resonators, but both approaches are intrinsically limited by a narrow temperature modulation range, slow heating/cooling, less quantitative heating, or time-consuming optical alignment. Here, we introduce heater-integrated fluidic resonators (HFRs) that enable fast, quantitative, alignment-free, and wide-range temperature modulation and simultaneously offer resistive thermometry and resonant densitometry. HFRs with or without a dispensing nozzle are fabricated, thoroughly characterized, and used for high throughput thermophysical properties measurements, microchannel boiling studies, and atomized spray dispensing. The HFR, without a doubt, opens a new avenue for nanoscale thermal analysis and processing and further encourages the integration of additional functions into channel resonators.

Alternative splicing and MicroRNA: epigenetic mystique in male reproduction.

Infertility is rarely life threatening, however, it poses a serious global health issue posing far-reaching socio-economic impacts affecting 12-15% of couples worldwide where male factor accounts for 70%. Functional spermatogenesis which is the result of several concerted coordinated events to produce sperms is at the core of male fertility, Alternative splicing and microRNA (miRNA) mediated RNA silencing (RNAi) constitute two conserved post-transcriptional gene (re)programming machinery across species. The former by diversifying transcriptome signature and the latter by repressing target mRNA activity orchestrate a spectrum of testicular events, and their dysfunctions has several implications in male infertility. This review recapitulates the knowledge of these mechanistic events in regulation of spermatogenesis and testicular homoeostasis. In addition, miRNA payload in sperm, vulnerable to paternal inputs, including unhealthy diet, infection and trauma, creates epigenetic memory to initiate intergenerational phenotype. Naive zygote injection of sperm miRNAs from stressed father recapitulates phenotypes of offspring of stressed father. The epigenetic inheritance of paternal pathologies through miRNA could be a tantalizing avenue to better appreciate 'Paternal Origins of Health and Disease' and the power of tiny sperm.

Emergency physician-performed emergency bronchoscopy in cardiac arrest patient due to acute foreign body airway obstruction.

As foreign body airway obstruction (FBAO) can be life-threatening, it has to be promptly diagnosed and treated. We report a case series of three patients presenting to the emergency department with cardiac arrest due to FBAO. In each case, ventilation was difficult due to high airway resistance. As FBAO was suspected, the emergency physician did a prompt flexible bronchoscopy to confirm the diagnosis and retrieve the foreign body. Flexible bronchoscopy is an important diagnostic and therapeutic tool for emergency airway management, and is a relatively safe procedure if performed by a trained personnel. The life-saving benefits of bronchoscopy outweigh the small risks of complications such as bleeding, desaturation and pneumothorax. In the three cases, the removal of the obstructing material led to immediate improvements in oxygenation and ventilation. The patients had return of spontaneous circulation after cardiopulmonary resuscitation and definite airway control.