Multiplex Real-Time Loop-Mediated Isothermal Amplification (LAMP) Based on the Annealing Curve Analysis: Toward an On-Site Multiplex Detection of Transgenic Sequences in Seeds and Food Products.

Monitoring of the introduction of unapproved genetically modified (GM) events is required because the approval status of a GM event may differ from country to country. The on-site methods such as loop-mediated isothermal amplification (LAMP) offer a technological answer for the rapid GM detection beyond the laboratories. Real-time LAMP assays detecting one GM target were reported earlier. To increase the efficiency of the assay, a multiplex real-time LAMP simultaneously targeting Figwort Mosaic Virus promoter (P-FMV) that constructs region between the Cauliflower Mosaic Virus 35S promoter and cry1Ac gene (p35S-cry1Ac) and neomycin phosphotransferase II (nptII) marker gene was developed. The assay could detect as low as 0.1% for each GM target within 45 min. To the best of our knowledge, multiplexing in real-time LAMP using the Genie II system with applicability in GM detection has been reported herein for the first time. The developed method provides rapid, on-site, and real-time GM detection in seeds and food products.

The interplay of co-infections in shaping COVID-19 severity: Expanding the scope beyond SARS-CoV-2.

High mortality has been reported in severe cases of COVID-19. Emerging reports suggested that the severity is not only due to SARS-CoV-2 infection, but also due to coinfections by other pathogens exhibiting symptoms like COVID-19. During the COVID-19 pandemic, simultaneous respiratory coinfections with various viral (Retroviridae, Flaviviridae, Orthomyxoviridae, and Picoviridae) and bacterial (Mycobacteriaceae, Mycoplasmataceae, Enterobacteriaceae and Helicobacteraceae) families have been observed. These pathogens intensify disease severity by potentially augmenting SARSCoV-2 replication, inflammation, and modulation of signaling pathways. Coinfection emerges as a critical determinant of COVID-19 severity, principally instigated by heightened pro-inflammatory cytokine levels, as cytokine storm. Thereby, in co-infection scenario, the severity is also driven by the modulation of inflammatory signaling pathways by both pathogens possibly associated with interleukin, interferon, and cell death exacerbating the severity. In the current review, we attempt to understand the role of co- infections by other pathogens and their involvement in the severity of COVID-19.

Multisystem Imaging Manifestations of Kidney Failure.

Kidney failure (KF) refers to a progressive decline in glomerular filtration rate to below 15 ml/min per 1.73 m2, necessitating renal replacement therapy with dialysis or renal transplant. The hemodynamic and metabolic alterations in KF combined with a proinflammatory and coagulopathic state leads to complex multisystemic complications. The imaging hallmark of systemic manifestations of KF is bone resorption caused by secondary hyperparathyroidism. Other musculoskeletal complications include brown tumor, osteosclerosis, calcinosis, soft-tissue calcification, and amyloid arthropathy. Cardiovascular complications and infections are the leading causes of death in KF. Cardiovascular complications include accelerated atherosclerosis, cardiomyopathy, pericarditis, myocardial calcinosis, and venous thromboembolism. Neurologic complications such as encephalopathy, osmotic demyelination, cerebrovascular disease, and opportunistic infections are also frequently encountered. Pulmonary complications include edema and calcifications. Radiography and CT are used in assessing musculoskeletal and thoracic complications, while MRI plays a key role in assessing neurologic and cardiovascular complications. CT iodinated contrast material is generally avoided in patients with KF except in situations where the benefit of contrast-enhanced CT outweighs the risks and in patients already undergoing maintenance dialysis. At MRI, group II gadolinium-based contrast material can be safely administered in patients with KF. The authors discuss the extrarenal systemic manifestations of KF, the choice of imaging modality in their assessment, and imaging findings of complications. ©RSNA, 2024 Supplemental material is available for this article.

Genome-scale community modelling elucidates the metabolic interaction in Indian type-2 diabetic gut microbiota.

Type-2 diabetes (T2D) is a rapidly growing multifactorial metabolic disorder that induces the onset of various diseases in the human body. The compositional and metabolic shift of the gut microbiota is a crucial factor behind T2D. Hence, gaining insight into the metabolic profile of the gut microbiota is essential for revealing their role in regulating the metabolism of T2D patients. Here, we have focused on the genome-scale community metabolic model reconstruction of crucial T2D-associated gut microbes. The model-based analysis of biochemical flux in T2D and healthy gut conditions showed distinct biochemical signatures and diverse metabolic interactions in the microbial community. The metabolic interactions encompass cross-feeding of short-chain fatty acids, amino acids, and vitamins among individual microbes within the community. In T2D conditions, a reduction in the metabolic flux of acetate, butyrate, vitamin B5, and bicarbonate was observed in the microbial community model, which can impact carbohydrate metabolism. The decline in butyrate levels is correlated with both insulin resistance and diminished glucose metabolism in T2D patients. Compared to the healthy gut, an overall reduction in glucose consumption and SCFA production flux was estimated in the T2D gut environment. Moreover, the decreased consumption profiles of branch chain amino acids (BCAAs) and aromatic amino acids (AAAs) in the T2D gut microbiota can be a distinct biomarker for T2D. Hence, the flux-level analysis of the microbial community model can provide insights into the metabolic reprogramming in diabetic gut microbiomes, which may be helpful in personalized therapeutics and diet design against T2D.

Amlodipine Ocular Delivery Restores Ferning Patterns and Reduces Intensity of Glycosylated Peak of Carrageenan-Induced Tear Fluid: An In-Silico Flexible Docking with IL-ß1.

BACKGROUND: The tear ferning test can be an easy clinical procedure for the evaluation and characterization of the ocular tear film. OBJECTIVE: The objective of this study was to examine the restoration of tear ferning patterns and reduction of glycosylation peak after amlodipine application in carrageenan-induced conjunctivitis. METHODS: At the rabbit's upper palpebral region, carrageenan was injected for cytokine-mediated conjunctivitis. Ferning pattern and glycosylation of the tear fluid were characterized using various instrumental analyses. The effect of amlodipine was also examined after ocular instillation and flexible docking studies. RESULTS: Optical microscopy showed a disrupted ferning of the tear collected from the inflamed eye. FTIR of the induced tear fluid exhibited peaks within 1000-1200 cm-1, which might be due to the protein glycosylation absent in the normal tear spectrogram. The glycosylation peak reduced significantly in the tear sample collected from the amlodipine-treated group. Corresponding energy dispersive analysis showed the presence of sulphur, indicating protein leakage from the lacrimal gland in the induced group. The disappearance of sulphur from the treated group indicated its remedial effect. The flexible docking studies revealed a stronger binding mode of amlodipine with Interleukin-1ß (IL-1ß). The reduction in the intensity of the glycosylated peak and the restoration offering are probably due to suppression of IL-1ß. CONCLUSION: This study may be helpful in obtaining primary information for drug discovery to be effective against IL-1ß and proving tear fluid as a novel diagnostic biomarker.

Detection of antibodies against structural proteins of foot-and-mouth disease virus in bovines of western Uttar Pradesh, India.

Foot-and-mouth disease (FMD) is considered as one of the most important contagious viral diseases affecting cloven-footed animals. For effective control of FMD, immunization along with herd immunity is essential in the field conditions. To assure and track the coverage and effectiveness of the vaccination program, the serological studies are very much required after the vaccination program. The present study was aimed to investigate the prevalence of antibodies against structural proteins of FMD virus (FMDV) serotypes of O, A and Asia-1 in seven districts of western Uttar Pradesh, India, and assure the efficacy of vaccination under National Animal Disease Control Program. A total of 308 sera samples were collected from apparent healthy vaccinated cattle and buffaloes from seven districts including Amroha, Baghpat, Bareilly, Bulandsahar, Gautam Budh Nagar, Meerut and Muzaffarnagar of western Uttar Pradesh, India. Determination of antibodies against structural proteins of FMDV was carried out using solid-phase blocking enzyme-linked immunosorbent assay. The protective level of the FMDV serotypes O, A and Asia-1 included in the inactivated trivalent vaccine was 66.55, 48.05 and 47.08% in bovines, respectively. To provide the higher level of protection against the circulating FMDV, the present study recommended the thorough investigation of the immunogenic interaction between the vaccine strains and the field strains. Further investigations should also be conducted with larger sample size and across diverse geographical regions to gain a more comprehensive understanding of herd immunity.

Exploring the genetic architecture of powdery mildew resistance in wheat through QTL meta-analysis.

Powdery mildew (PM), caused by Blumeria graminis f. sp. tritici, poses a significant threat to wheat production, necessitating the development of genetically resistant varieties for long-term control. Therefore, exploring genetic architecture of PM in wheat to uncover important genomic regions is an important area of wheat research. In recent years, the utilization of meta-QTL (MQTL) analysis has gained prominence as an essential tool for unraveling the complex genetic architecture underlying complex quantitative traits. The aim of this research was to conduct a QTL meta-analysis to pinpoint the specific genomic regions in wheat responsible for governing PM resistance. This study integrated 222 QTLs from 33 linkage-based studies using a consensus map with 54,672 markers. The analysis revealed 39 MQTLs, refined to 9 high-confidence MQTLs (hcMQTLs) with confidence intervals of 0.49 to 12.94 cM. The MQTLs had an average physical interval of 41.00 Mb, ranging from 0.000048 Mb to 380.71 Mb per MQTL. Importantly, 18 MQTLs co-localized with known resistance genes like Pm2, Pm3, Pm8, Pm21, Pm38, and Pm41. The study identified 256 gene models within hcMQTLs, providing potential targets for marker-assisted breeding and genomic prediction programs to enhance PM resistance. These MQTLs would serve as a foundation for fine mapping, gene isolation, and functional genomics studies, facilitating a deeper understanding of molecular mechanisms. The identification of candidate genes opens up exciting possibilities for the development of PM-resistant wheat varieties after validation.

Smart e-waste management: a revolutionary incentive-driven IoT solution with LPWAN and edge-AI integration for environmental sustainability.

Managing e-waste involves collecting it, extracting valuable metals at low costs, and ensuring environmentally safe disposal. However, monitoring this process has become challenging due to e-waste expansion. With IoT technology like LoRa-LPWAN, pre-collection monitoring becomes more cost-effective. Our paper presents an e-waste collection and recovery system utilizing the LoRa-LPWAN standard, integrating intelligence at the edge and fog layers. The system incentivizes WEEE holders, encouraging participation in the innovative collection process. The city administration oversees this process using innovative trucks, GPS, LoRaWAN, RFID, and BLE technologies. Analysis of IoT performance factors and quantitative assessments (latency and collision probability on LoRa, Sigfox, and NB-IoT) demonstrate the effectiveness of our incentive-driven IoT solution, particularly with LoRa standard and Edge AI integration. Additionally, cost estimates show the advantage of LoRaWAN. Moreover, the proposed IoT-based e-waste management solution promises cost savings, stakeholder trust, and long-term effectiveness through streamlined processes and human resource training. Integration with government databases involves data standardization, API development, security measures, and functionality testing for efficient management.

Repurposing of dibucaine and niflumic acid as antimicrobial agents in combination with antibiotics against Staphylococcus aureus.

The versatile human commensal bacteria and pathogen Staphylococcus aureus cause several community and hospital-acquired illnesses associated with significant morbidity and death. Antibiotic therapy for S. aureus infections has grown increasingly difficult as the organism has developed a wide spectrum of antibiotic resistance mechanisms. This situation emphasizes the significance of developing and advocating new antimicrobials for preventative and therapeutic measures. Our study aimed to identify and evaluate new therapeutic options against S. aureus. We investigated the efficacy of two drugs, dibucaine, and niflumic acid, as potential adjuvant for anti-staphylococcal therapeutics. Dibucaine and niflumic acid found to have bactericidal activity against S. aureus. These drugs acted synergistically with antibiotics reducing the required dose of antibiotics up to 4 times. In combination with antibiotics, they were effectively and synergistically inhibited the formation of biofilms of S. aureus. The best synergistic partner of dibucaine was with kanamycin and tetracycline, whereas niflumic acid was with streptomycin and ampicillin. Both the drugs showed significant efflux inhibition in the bacteria. Moreover, the drugs are found to be safe at synergistic doses. Our findings suggest that dibucaine and niflumic acid could be potential adjuvant with antibiotics for the treatment of S. aureus infections. Their ability to significantly enhance the efficacy of antibiotics highlights their potential clinical significance as adjunct therapies.

Observational evidence of changing cloud macro-physical properties under warming climate over the Indian summer monsoon region.

The cloud responses to global warming are captured in various global climate models with distinct inferences on changes in cloud vertical structure as function of surface warming. However, long term observational evidences are scarce to validate the model outputs. Here, we have studied the changes in radiosonde derived cloud macro-physical properties and their association with other atmospheric variables during the period 2000-2019 in response to warming climate over the Indian summer monsoon region. We have observed a statistically significant increase in the frequency of cloudy days (∼13 % decade-1), high-level clouds (HLCs ∼11 % decade-1) and simultaneous decrease in low-level clouds (LLCs ∼8 % decade-1) over the Indian region during the monsoon season. The multiple linear regression, principle component analyses and further correlation analyses suggest significant associations between cloud vertical structure variations and large-scale climate indicators, such as global warming and El Niño-Southern Oscillation. The vertical extension of the tropospheric column and the upward shift of clouds, attributed to global warming, explain the changes observed in both HLCs and LLCs. These results contribute to a deeper understanding of the dynamic interplay between global climate change and regional cloud dynamics, with implications for weather and climate modeling.

Discovering novel genomic regions explaining adaptation of bread wheat to conservation agriculture through GWAS.

To sustainably increase wheat yield to meet the growing world population's food demand in the face of climate change, Conservation Agriculture (CA) is a promising approach. Still, there is a lack of genomic studies investigating the genetic basis of crop adaptation to CA. To dissect the genetic architecture of 19 morpho-physiological traits that could be involved in the enhanced adaptation and performance of genotypes under CA, we performed GWAS to identify MTAs under four contrasting production regimes viz., conventional tillage timely sown (CTTS), conservation agriculture timely sown (CATS), conventional tillage late sown (CTLS) and conservation agriculture late sown (CALS) using an association panel of 183 advanced wheat breeding lines along with 5 checks. Traits like Phi2 (Quantum yield of photosystem II; CATS:0.37, CALS: 0.31), RC (Relative chlorophyll content; CATS:55.51, CALS: 54.47) and PS1 (Active photosystem I centers; CATS:2.45, CALS: 2.23) have higher mean values in CA compared to CT under both sowing times. GWAS identified 80 MTAs for the studied traits across four production environments. The phenotypic variation explained (PVE) by these QTNs ranged from 2.15 to 40.22%. Gene annotation provided highly informative SNPs associated with Phi2, NPQ (Quantum yield of non-photochemical quenching), PS1, and RC which were linked with genes that play crucial roles in the physiological adaptation under both CA and CT. A highly significant SNP AX94651261 (9.43% PVE) was identified to be associated with Phi2, while two SNP markers AX94730536 (30.90% PVE) and AX94683305 (16.99% PVE) were associated with NPQ. Identified QTNs upon validation can be used in marker-assisted breeding programs to develop CA adaptive genotypes.

Edema India: Executive Summary of Screening, Diagnosis, and Management of Edema.

The management of edema requires a systematic approach to screening, diagnosis, and treatment, with an essential initial assessment to differentiate between generalized and localized edema. The Association of Physicians of India (API) aimed to develop the first Indian Edema Consensus (Edema India), offering tailored recommendations for screening, diagnosing, and managing edema based on the insights from the expert panel. The panel suggested when evaluating edema symptoms, important factors to consider include the patient's current illness, medical history, risk factors, family history, and medications. Key diagnostic investigations for edema include complete blood count, cardiovascular imaging and markers, deep vein thrombosis (DVT) assessment, along with renal, hepatic, and thyroid function tests. Edema management involves a combination of pharmacologic and nonpharmacologic interventions, including limb elevation, physiotherapy, compression therapy, fluid removal, diuretics (loop diuretics: first-line therapy), and a sodium-restricted diet. The panel believed that educating patients could foster a preventive mindset, helping to prevent the worsening of edema.

Enhancing sports image data classification in federated learning through genetic algorithm-based optimization of base architecture.

Nowadays, federated learning is one of the most prominent choices for making decisions. A significant benefit of federated learning is that, unlike deep learning, it is not necessary to share data samples with the model owner. The weight of the global model in traditional federated learning is created by averaging the weights of all clients or sites. In the proposed work, a novel method has been discussed to generate an optimized base model without hampering its performance, which is based on a genetic algorithm. Chromosome representation, crossover, and mutation-all the intermediate operations of the genetic algorithm have been illustrated with useful examples. After applying the genetic algorithm, there is a significant improvement in inference time and a huge reduction in storage space. Therefore, the model can be easily deployed on resource-constrained devices. For the experimental work, sports data has been used in balanced and unbalanced scenarios with various numbers of clients in a federated learning environment. In addition, we have used four famous deep learning architectures, such as AlexNet, VGG19, ResNet50, and EfficientNetB3, as the base model. We have achieved 92.34% accuracy with 9 clients in the balanced data set by using EfficientNetB3 as the base model using a GA-based approach. Moreover, after applying the genetic algorithm to optimize EfficientNetB3, there is an improvement in inference time and storage space by 20% and 2.35%, respectively.

Global needs for nitrogen fertilizer to improve wheat yield under climate change.

Increasing global food demand will require more food production1 without further exceeding the planetary boundaries2 while simultaneously adapting to climate change3. We used an ensemble of wheat simulation models with improved sink and source traits from the highest-yielding wheat genotypes4 to quantify potential yield gains and associated nitrogen requirements. This was explored for current and climate change scenarios across representative sites of major world wheat producing regions. The improved sink and source traits increased yield by 16% with current nitrogen fertilizer applications under both current climate and mid-century climate change scenarios. To achieve the full yield potential-a 52% increase in global average yield under a mid-century high warming climate scenario (RCP8.5), fertilizer use would need to increase fourfold over current use, which would unavoidably lead to higher environmental impacts from wheat production. Our results show the need to improve soil nitrogen availability and nitrogen use efficiency, along with yield potential.

Role of mitochondrial ribosomal protein L7/L12 (MRPL12) in diabetic ischemic heart disease.

BACKGROUND: Myocardial infarction (MI) is a significant cause of death in diabetic patients. Growing evidence suggests that mitochondrial dysfunction contributes to heart failure in diabetes. However, the molecular mechanisms of mitochondrial dysfunction mediating heart failure in diabetes are still poorly understood. METHODS: We examined MRPL12 levels in right atrial appendage tissues from diabetic patients undergoing coronary artery bypass graft (CABG) surgery. Using AC-16 cells overexpressing MRPL12 under normal and hyperglycemic conditions we performed mitochondrial functional assays OXPHOS, bioenergetics, mitochondrial membrane potential, ATP production and cell death. RESULTS: We observed elevated MRPL12 levels in heart tissue samples from diabetic patients with ischemic heart disease compared to non-diabetic patients. Overexpression of MRPL12 under hyperglycemic conditions did not affect oxidative phosphorylation (OXPHOS) levels, cellular ATP levels, or cardiomyocyte cell death. However, notable impairment in mitochondrial membrane potential (MMP) was observed under hyperglycemic conditions, along with alterations in both basal respiration oxygen consumption rate (OCR) and maximal respiratory capacity OCR. CONCLUSIONS: Overall, our results suggest that MRPL12 may have a compensatory role in the diabetic myocardium with ischemic heart disease, suggesting that MRPL12 may implicate in the pathophysiology of MI in diabetes.

The effect of blood transfusion on serum hepcidin levels in chronically transfused patients of ß-thalassemia major: An observational study in a tertiary care centre in Western Maharashtra.

INTRODUCTION: Hepcidin is the key regulator of systemic iron homeostasis. In iron-loading anemias, hepcidin levels are regulated by opposite forces of erythropoiesis and iron overload. In ß-thalassemia major patients, transfusions are the predominant cause of iron overload; in such chronically transfused patients, hepcidin concentrations are significantly higher than nontransfused patients, due to both increased iron load of transfusions and the suppression of ineffective erythropoiesis. AIM: This study aims to evaluate the effect of blood transfusions on serum hepcidin levels in chronically transfused patients of ß-thalassemia major and correlate with hemoglobin and serum ferritin levels of pre- and posttransfusion. MATERIALS AND METHODS: Thirty-three ß-thalassemia major patients requiring monthly transfusions were included in the study. Blood samples, collected pretransfusion and 7 days posttransfusion, were evaluated for hemoglobin, serum ferritin, and serum hepcidin using enzyme immunoassay. STATISTICAL ANALYSIS: Data were statistically analyzed through SPSS software and P < 0.05 is considered statically significant. RESULTS: Posttransfusion levels of hemoglobin, serum ferritin, and serum hepcidin increased. Posttransfusion levels of hepcidin were near normal levels. Pre- and posttransfusion hepcidin concentrations were significantly associated with hemoglobin levels. CONCLUSION: Serum hepcidin concentrations vary depending on the degree of erythropoiesis drive and level of anemia. We found that the serum hepcidin levels decrease over the inter-transfusion interval and transfusions cause suppression of ineffective erythropoiesis by the increase in hemoglobin. Posttransfusion values of hepcidin in our study were closer to normal levels which may be due to lower erythropoietic drive posttransfusion. We suggest that the measurement of serum hepcidin in chronically transfused ß-thalassemia patients can be used as a follow-up investigation for better management of these patients.

Breaking the Cycle: Matrix Metalloproteinase Inhibitors as an Alternative Approach in Managing Tuberculosis Pathogenesis and Progression.

Mycobacterium tuberculosis (Mtb) has long posed a significant challenge to global public health, resulting in approximately 1.6 million deaths annually. Pulmonary tuberculosis (TB) instigated by Mtb is characterized by extensive lung tissue damage, leading to lesions and dissemination within the tissue matrix. Matrix metalloproteinases (MMPs) exhibit endopeptidase activity, contributing to inflammatory tissue damage and, consequently, morbidity and mortality in TB patients. MMP activities in TB are intricately regulated by various components, including cytokines, chemokines, cell receptors, and growth factors, through intracellular signaling pathways. Primarily, Mtb-infected macrophages induce MMP expression, disrupting the balance between MMPs and tissue inhibitors of metalloproteinases (TIMPs), thereby impairing extracellular matrix (ECM) deposition in the lungs. Recent research underscores the significance of immunomodulatory factors in MMP secretion and granuloma formation during Mtb pathogenesis. Several studies have investigated both the activation and inhibition of MMPs using endogenous MMP inhibitors (i.e., TIMPs) and synthetic inhibitors. However, despite their promising pharmacological potential, few MMP inhibitors have been explored for TB treatment as host-directed therapy. Scientists are exploring novel strategies to enhance TB therapeutic regimens by suppressing MMP activity to mitigate Mtb-associated matrix destruction and reduce TB induced lung inflammation. These strategies include the use of MMP inhibitor molecules alone or in combination with anti-TB drugs. Additionally, there is growing interest in developing novel formulations containing MMP inhibitors or MMP-responsive drug delivery systems to suppress MMPs and release drugs at specific target sites. This review summarizes MMPs' expression and regulation in TB, their role in immune response, and the potential of MMP inhibitors as effective therapeutic targets to alleviate TB immunopathology.

Does deteriorating antioxidant defense and impaired γ-glutamyl cycle induce oxidative stress and hemolysis in individuals with sickle cell disease?

Sickle cell disease (SCD) affects two-thirds of African and Indian children. Understanding the molecular mechanisms contributing to oxidative stress may be useful for therapeutic development in SCD. We evaluated plasma elemental levels of Indian SCD patients, trait and healthy controls (n=10/per group) via ICP-MS. Additionally, erythrocyte metabolomics of Indian SCD and healthy (n=5/per group) was carried out using LC-MS mass-spectrometry. Followed by assessment of antioxidant defence enzymes namely glutathione reductase (GR), superoxide dismutase (SOD), and catalase (CAT) in erythrocytes and plasma of Indian SCD patients (n=31) compared to trait (n=8) and healthy (n=9). In SCD plasma an elevated plasma 24Mg, 44Ca, 66Zn, 208Pb, 39K and reduced 57Fe, 77Se, 85Rb levels indicating higher hemolysis and anemia. Erythrocyte metabolome of SCD patients clustered separately from heathy revealing 135 significantly deregulated metabolic features including trimethyllysine, pyroglutamate, glutathione, aminolevulinate, and D-glutamine indicating oxidative stress and membrane fragility. Repressed GR, SOD, and CAT activities were observed in SCD patients of which GR and CAT activities did not change under hypoxia. These findings lead to the hypothesis that SCD-associated metabolic deregulations and a shift to ATP-consuming aberrant γ-glutamyl cycle leads to anemia, dehydration, oxidative stress and hemolysis driving the biomechanical pathophysiology of erythrocyte of SCD patients.

On-Device Semi-Supervised Activity Detection: A New Privacy-Aware Personalized Health Monitoring Approach.

This paper presents an on-device semi-supervised human activity detection system that can learn and predict human activity patterns in real time. The clinical objective is to monitor and detect the unhealthy sedentary lifestyle of a user. The proposed semi-supervised learning (SSL) framework uses sparsely labelled user activity events acquired from Inertial Measurement Unit sensors installed as wearable devices. The proposed cluster-based learning model in this approach is trained with data from the same target user, thus preserving data privacy while providing personalized activity detection services. Two different cluster labelling strategies, namely, population-based and distance-based strategies, are employed to achieve the desired classification performance. The proposed system is shown to be highly accurate and computationally efficient for different algorithmic parameters, which is relevant in the context of limited computing resources on typical wearable devices. Extensive experimentation and simulation study have been conducted on multi-user human activity data from the public domain in order to analyze the trade-off between classification accuracy and computation complexity of the proposed learning paradigm with different algorithmic hyper-parameters. With 4.17 h of training time for 8000 activity episodes, the proposed SSL approach consumes at most 20 KB of CPU memory space, while providing a maximum accuracy of 90% and 100% classification rates.

MiRNA-3163 limits ovarian cancer stem-like cells via targeting SOX-2 transcription factor.

Cancer stem cells (CSCs) are pivotal in both cancer progression and the acquisition of drug resistance. MicroRNAs (miRNAs) play a crucial role in modulating CSC properties and are being explored as potential targets for therapeutic interventions. MiR-3163 is primarily known for its tumor suppressive properties in various human malignancies, with lower expression reported across different cancer types. However, its role in regulating the ovarian CSC phenotype and the underlying mechanism remain largely unknown. Here, we report a remarkable downregulation of miR-3163 in ovarian cancer stem-like cells (CSLCs). Enforced expression of miR-3163 in ovarian adherent and CSLCs, significantly disrupts the stemness phenotype. Moreover, downregulation of miR-3163 expression in ovarian cancer cells (OV2008 and OVCAR-3) inhibits the stem-like cells characterized by CD44+CD117+ expression. Sphere formation assay results reveal that overexpression of miR-3163 in ovarian cancer cells significantly inhibits spheroid formation ability, confirming the regulatory properties of miR-3163 on ovarian CSLCs. Mechanistic investigation reveals that miR-3163 depletes ovarian CSLCs via targeting SOX-2. Furthermore, we establish SOX-2 as a direct target of miR-3163 through dual-luciferase assay. Taken together, our study demonstrates that overexpression of miR-3163 could be a promising strategy for efficiently eradicating the CSC population to prevent chemoresistance and tumor relapse in ovarian cancer patients.