Malware Detection for Internet of Things Using One-Class Classification.

The increasing usage of interconnected devices within the Internet of Things (IoT) and Industrial IoT (IIoT) has significantly enhanced efficiency and utility in both personal and industrial settings but also heightened cybersecurity vulnerabilities, particularly through IoT malware. This paper explores the use of one-class classification, a method of unsupervised learning, which is especially suitable for unlabeled data, dynamic environments, and malware detection, which is a form of anomaly detection. We introduce the TF-IDF method for transforming nominal features into numerical formats that avoid information loss and manage dimensionality effectively, which is crucial for enhancing pattern recognition when combined with n-grams. Furthermore, we compare the performance of multi-class vs. one-class classification models, including Isolation Forest and deep autoencoder, that are trained with both benign and malicious NetFlow samples vs. trained exclusively on benign NetFlow samples. We achieve 100% recall with precision rates above 80% and 90% across various test datasets using one-class classification. These models show the adaptability of unsupervised learning, especially one-class classification, to the evolving malware threats in the IoT domain, offering insights into enhancing IoT security frameworks and suggesting directions for future research in this critical area.

Coastal dunes as drivers of genetic differentiation in the honeypot ant Myrmecocystus baja (Formicidae: Formicinae).

Coastal dunes are unique habitats, threatened by human activities. In biogeographical terms, coastal dunes are habitat islands, being discrete and distinct patches of similar habitat among themselves, separated from each other by a different type of habitat. Furthermore, coastal dunes harbor endemic species, adapted to living solely in the habitats found on specific dune systems. For example, the honeypot ant Myrmecocystus baja is endemic and restricted to coastal dunes of Mexico's Baja California Pacific coast. This ecological and biogeographical scenario led to the questions whether their geographical isolation is reflected in their genetic diversity and structuring, and how their demographic history is related with the formation of the dune system habitats. To answer these questions, population genetic, isolation-with-migration, and phylogeographical analyses were carried out, based on mitochondrial and five nuclear intronic markers. Minimal gene flow was detected only between two of the dune systems sampled; otherwise, the M. baja populations were found to be isolated and genetically structured, and their divergence generally pre-dated the modern-day dune systems. It is therefore highly likely that these ants were already present in paleodunes and that each of the populations was established from founder populations as the dunes formed. These findings highlight the importance of coastal dunes for species such as the honeypot ant from Baja California, in promoting genetic differentiation.

Inflammatory responses in Atlantic lumpfish (Cyclopterus lumpus L.) after intraperitoneal injection of a vaccine against Aeromonas salmonicida and Vibrio salmonicida at different water temperatures.

Studying inflammatory responses induced by vaccination can contribute to a more detailed understanding of underlying immune mechanisms in lumpfish (Cyclopterus lumpus). Tissue samples from lumpfish intraperitoneally immunized with a divalent oil-adjuvanted vaccine (Aeromonas salmonicida and Vibrio salmonicida) at water temperatures of 5, 10, and 15°C were collected at 630 day degrees and 18 weeks post injection. The relative amount of secretory and membrane-bound immunoglobulin M (IgM) gene transcripts in the head kidney was determined by qPCR. Vaccine-induced inflammatory lesions were assessed on histological sections of abdominal pancreatic/intestinal tissue from vaccinated fish in all three temperature groups. Inflammatory cells forming dense aggregations in lesions showed proliferative activity, many of which were identified as eosinophilic-granulocyte-like cells. IgM+ cells were scattered in inflammatory tissue dominated by connective tissue, showing no difference in numbers between lesions from fish vaccinated at 5, 10, and 15°C. Relative gene expression analysis of secretory and membrane-bound IgM revealed low overall expression in the head kidney of vaccinated fish at both 630 day-degrees and 18 weeks post injection. The results of this study indicate that the vaccine stimulated prolonged local inflammatory responses at the injection site, which were not influenced by temperature.

Role of artificial intelligence, machine learning and deep learning models in corneal disorders - A narrative review.

In the last decade, artificial intelligence (AI) has significantly impacted ophthalmology, particularly in managing corneal diseases, a major reversible cause of blindness. This review explores AI's transformative role in the corneal subspecialty, which has adopted advanced technology for superior clinical judgment, early diagnosis, and personalized therapy. While AI's role in anterior segment diseases is less documented compared to glaucoma and retinal pathologies, this review highlights its integration into corneal diagnostics through imaging techniques like slit-lamp biomicroscopy, anterior segment optical coherence tomography (AS-OCT), and in vivo confocal biomicroscopy. AI has been pivotal in refining decision-making and prognosis for conditions such as keratoconus, infectious keratitis, and dystrophies. Multi-disease deep learning neural networks (MDDNs) have shown diagnostic ability in classifying corneal diseases using AS-OCT images, achieving notable metrics like an AUC of 0.910. AI's progress over two decades has significantly improved the accuracy of diagnosing conditions like keratoconus and microbial keratitis. For instance, AI has achieved a 90.7% accuracy rate in classifying bacterial and fungal keratitis and an AUC of 0.910 in differentiating various corneal diseases. Convolutional neural networks (CNNs) have enhanced the analysis of color-coded corneal maps, yielding up to 99.3% diagnostic accuracy for keratoconus. Deep learning algorithms have also shown robust performance in detecting fungal hyphae on in vivo confocal microscopy, with precise quantification of hyphal density. AI models combining tomography scans and visual acuity have demonstrated up to 97% accuracy in keratoconus staging according to the Amsler-Krumeich classification. However, the review acknowledges the limitations of current AI models, including their reliance on binary classification, which may not capture the complexity of real-world clinical presentations with multiple coexisting disorders. Challenges also include dependency on data quality, diverse imaging protocols, and integrating multimodal images for a generalized AI diagnosis. The need for interpretability in AI models is emphasized to foster trust and applicability in clinical settings. Looking ahead, AI has the potential to unravel the intricate mechanisms behind corneal pathologies, reduce healthcare's carbon footprint, and revolutionize diagnostic and management paradigms. Ethical and regulatory considerations will accompany AI's clinical adoption, marking an era where AI not only assists but augments ophthalmic care.

A novel frameshift variant in BCOR causes congenital nuclear cataract.

BACKGROUND: BCL6 co-repressor (BCOR) gene variants are involved in oculofaciocardiodental (OFCD) syndrome, acute myeloid leukaemia, renal tumours, and photoreceptor degenerative diseases. Here, we describe a British family with a pathogenic heterozygous variant in the BCOR gene causing congenital nuclear cataract. METHODS: Whole-exome sequencing was conducted on an individual affected by X-linked dominant congenital cataract in a three-generation family to establish the underlying genetic basis. Bioinformatics analysis confirmed the variants with damaging pathogenicity scores. RESULTS: A novel likely pathogenic frameshift variant BCOR NM_001123385.1: c.3621del; p.Lys1207AsnfsTer31, was identified and found to co-segregate with the disease in this family. CONCLUSIONS: This is apparently the first report of a variant in BCOR causing X-linked dominant congenital cataract which is potentially isolated or presenting with a remarkably mild systemic phenotype. Our findings extend the genetic basis for congenital cataract and add to the phenotypic spectrum of BCOR variants.

Inhibition of PDIs Downregulates Core LINC Complex Proteins, Promoting the Invasiveness of MDA-MB-231 Breast Cancer Cells in Confined Spaces In Vitro.

Eukaryotic cells tether the nucleoskeleton to the cytoskeleton via a conserved molecular bridge, called the LINC complex. The core of the LINC complex comprises SUN-domain and KASH-domain proteins that directly associate within the nuclear envelope lumen. Intra- and inter-chain disulphide bonds, along with KASH-domain protein interactions, both contribute to the tertiary and quaternary structure of vertebrate SUN-domain proteins. The significance of these bonds and the role of PDIs (protein disulphide isomerases) in LINC complex biology remains unclear. Reducing and non-reducing SDS-PAGE analyses revealed a prevalence of SUN2 homodimers in non-tumorigenic breast epithelia MCF10A cells, but not in the invasive triple-negative breast cancer MDA-MB-231 cell line. Furthermore, super-resolution microscopy revealed SUN2 staining alterations in MCF10A, but not in MDA-MB-231 nuclei, upon reducing agent exposure. While PDIA1 levels were similar in both cell lines, pharmacological inhibition of PDI activity in MDA-MB-231 cells led to SUN-domain protein down-regulation, as well as Nesprin-2 displacement from the nucleus. This inhibition also caused changes in perinuclear cytoskeletal architecture and lamin downregulation, and increased the invasiveness of PDI-inhibited MDA-MB-231 cells in space-restrictive in vitro environments, compared to untreated cells. These results emphasise the key roles of PDIs in regulating LINC complex biology, cellular architecture, biomechanics, and invasion.

Structural characterization and AlphaFold modeling of human T cell receptor recognition of NRAS cancer neoantigens.

T cell receptors (TCRs) that recognize cancer neoantigens are important for anti-cancer immune responses and immunotherapy. Understanding the structural basis of TCR recognition of neoantigens provides insights into their exquisite specificity and can enable design of optimized TCRs. We determined crystal structures of a human TCR in complex with NRAS Q61K and Q61R neoantigen peptides and HLA-A1 MHC, revealing the molecular underpinnings for dual recognition and specificity versus wild-type NRAS peptide. We then used multiple versions of AlphaFold to model the corresponding complex structures, given the challenge of immune recognition for such methods. Interestingly, one implementation of AlphaFold2 (TCRmodel2) was able to generate accurate models of the complexes, while AlphaFold3 also showed strong performance, although success was lower for other complexes. This study provides insights into TCR recognition of a shared cancer neoantigen, as well as the utility and practical considerations for using AlphaFold to model TCR-peptide-MHC complexes.

Combining phenotypic and genomic data to improve prediction of binary traits.

Plant breeders want to develop cultivars that outperform existing genotypes. Some characteristics (here 'main traits') of these cultivars are categorical and difficult to measure directly. It is important to predict the main trait of newly developed genotypes accurately. In addition to marker data, breeding programs often have information on secondary traits (or 'phenotypes') that are easy to measure. Our goal is to improve prediction of main traits with interpretable relations by combining the two data types using variable selection techniques. However, the genomic characteristics can overwhelm the set of secondary traits, so a standard technique may fail to select any phenotypic variables. We develop a new statistical technique that ensures appropriate representation from both the secondary traits and the genotypic variables for optimal prediction. When two data types (markers and secondary traits) are available, we achieve improved prediction of a binary trait by two steps that are designed to ensure that a significant intrinsic effect of a phenotype is incorporated in the relation before accounting for extra effects of genotypes. First, we sparsely regress the secondary traits on the markers and replace the secondary traits by their residuals to obtain the effects of phenotypic variables as adjusted by the genotypic variables. Then, we develop a sparse logistic classifier using the markers and residuals so that the adjusted phenotypes may be selected first to avoid being overwhelmed by the genotypic variables due to their numerical advantage. This classifier uses forward selection aided by a penalty term and can be computed effectively by a technique called the one-pass method. It compares favorably with other classifiers on simulated and real data.

Jute fibre reinforced biodegradable composites using starch as a biological macromolecule: Fabrication and performance evaluation.

The aim of this study is to develop environment friendly packaging and life style materials for replacing conventionally explored hazardous synthetic materials. The study carried out by using raw jute fibre reinforced thermoplastic corn starch (TPCS) is to develop biodegradable flexible composite materials. Flexible composites are prepared by maintaining with different fibre content (30 %, 40 % and 50 wt%). A thin coating of polyurethane based formulation is applied on one side of the developed composite to make it water resistant. Composite samples are examined in terms of their tensile properties, tear resistance, folding endurance, water absorbency, capillary action etc. The results show that flexible composites, having 50 % fibre content have tensile strength of 12.8 MPa and 12 MPa at cross and machine direction respectively compared to 3.1 MPa for the TPCS film. The Water drop test on the coated side of the developed material concluded that there is no water penetration even after 60 min of wetting. The interaction between two hydrophilic components is established with FTIR analysis. The XRD analysis was carried out to find the crystallinity of TPCS, Jute fibre and composite samples. Surface morphology and fibre/matrix interaction is observed by SEM. The detail chemical mechanism involved of fibre matrix interaction also been postulated. The scientific finding shows that the developed flexible material can be suitable for making packaging and life style items.

Cutting Edge: LAG3 Dimerization Is Required for TCR/CD3 Interaction and Inhibition of Antitumor Immunity.

Lymphocyte activation gene 3 (LAG3) is an inhibitory receptor that plays a critical role in controlling T cell tolerance and autoimmunity and is a major immunotherapeutic target. LAG3 is expressed on the cell surface as a homodimer but the functional relevance of this is unknown. In this study, we show that the association between the TCR/CD3 complex and a murine LAG3 mutant that cannot dimerize is perturbed in CD8+ T cells. We also show that LAG3 dimerization is required for optimal inhibitory function in a B16-gp100 tumor model. Finally, we demonstrate that a therapeutic LAG3 Ab, C9B7W, which does not block LAG3 interaction with its cognate ligand MHC class II, disrupts LAG3 dimerization and its association with the TCR/CD3 complex. These studies highlight the functional importance of LAG3 dimerization and offer additional approaches to therapeutically target LAG3.

Selective targeting of IRAK1 attenuates low molecular weight hyaluronic acid-induced stemness and non-canonical STAT3 activation in epithelial ovarian cancer.

Advanced epithelial ovarian cancer (EOC) survival rates are dishearteningly low, with ~25% surviving beyond 5 years. Evidence suggests that cancer stem cells contribute to acquired chemoresistance and tumor recurrence. Here, we show that IRAK1 is upregulated in EOC tissues, and enhanced expression correlates with poorer overall survival. Moreover, low molecular weight hyaluronic acid, which is abundant in malignant ascites from patients with advanced EOC, induced IRAK1 phosphorylation leading to STAT3 activation and enhanced spheroid formation. Knockdown of IRAK1 impaired tumor growth in peritoneal disease models, and impaired HA-induced spheroid growth and STAT3 phosphorylation. Finally, we determined that TCS2210, a known inducer of neuronal differentiation in mesenchymal stem cells, is a selective inhibitor of IRAK1. TCS2210 significantly inhibited EOC growth in vitro and in vivo both as monotherapy, and in combination with cisplatin. Collectively, these data demonstrate IRAK1 as a druggable target for EOC.

Implementation considerations for the adoption of artificial intelligence in the emergency department.

OBJECTIVE: Artificial intelligence (AI) has emerged as a potentially transformative force, particularly in the realm of emergency medicine (EM). The implementation of AI in emergency departments (ED) has the potential to improve patient care through various modalities. However, the implementation of AI in the ED presents unique challenges that influence its clinical adoption. This scoping review summarizes the current literature exploring the barriers and facilitators of the clinical implementation of AI in the ED. METHODS: We systematically searched Embase (Ovid), MEDLINE (Ovid), Web of Science, and Engineering Village. All articles were published in English through November 20th, 2023. Two reviewers screened the search results, with disagreements resolved through third-party adjudication. RESULTS: A total of 8172 studies were included in the preliminary search, with 22 selected for the final data extraction. 10 studies were reviews and the remaining 12 were primary quantitative, qualitative, and mixed-methods studies. Out of the 22, 13 studies investigated a specific AI tool or application. Common barriers to implementation included a lack of model interpretability and explainability, encroachment on physician autonomy, and medicolegal considerations. Common facilitators to implementation included educating staff on the model, efficient integration into existing workflows, and sound external validation. CONCLUSION: There is increasing literature on AI implementation in the ED. Our research suggests that the most common barrier facing AI implementation in the ED is model interpretability and explainability. More primary research investigating the implementation of specific AI tools should be undertaken to help facilitate their successful clinical adoption in the ED.

Sequential Induction of Drug Resistance and Characterization of an Initial Candida albicans Drug-Sensitive Isolate.

BACKGROUND: The pathogenic fungus Candida albicans is a leading agent of death in immunocompromised individuals with a growing trend of antifungal resistance. METHODS: The purpose is to induce resistance to drugs in a sensitive C. albicans strain followed by whole-genome sequencing to determine mechanisms of resistance. Strains will be assayed for pathogenicity attributes such as ergosterol and chitin content, growth rate, virulence, and biofilm formation. RESULTS: We observed sequential increases in ergosterol and chitin content in fluconazole-resistant isolates by 78% and 44%. Surface thickening prevents the entry of the drug, resulting in resistance. Resistance imposed a fitness trade-off that led to reduced growth rates, biofilm formation, and virulence in our isolates. Sequencing revealed mutations in genes involved in resistance and pathogenicity such as ERG11, CHS3, GSC2, CDR2, CRZ2, and MSH2. We observed an increase in the number of mutations in key genes with a sequential increase in drug-selective pressures as the organism increased its odds of adapting to inhospitable environments. In ALS4, we observed two mutations in the susceptible strain and five mutations in the resistant strain. CONCLUSION: This is the first study to induce resistance followed by genotypic and phenotypic analysis of isolates to determine mechanisms of drug resistance.

Implementation of the International Classification of Diseases 11th revision behavioural indicators for disorders of intellectual development with co-occurring autism spectrum disorder.

BACKGROUND: The classification of mental, behavioural and neurodevelopmental disorders in the World Health Organization's International Classification of Diseases 11th revision (ICD-11) includes a comprehensive set of behavioural indicators (BIs) within the neurodevelopmental disorders grouping. BIs can be used to assess the severity of disorders of intellectual development in situations in which standardised measures of intellectual functioning and adaptive behaviours are not available or feasible. This international study examines the implementation characteristics of the BIs and compares them to standardised measures for assessing the severity of intellectual impairment and adaptive behaviours in disorders of intellectual development and autism spectrum disorder (ASD). The clinical utility of the ICD-11 and the fidelity of its application in international clinical settings were also assessed. METHODS: A total of 116 children and adolescents (5-18 years old) with a suspected or established diagnosis of disorders of intellectual development were included across four sites [Italy (n = 18), Sri Lanka (n = 19) and two sites in India (n = 79)]. A principal component analysis was conducted to evaluate the application of the ICD-11 guidance for combining severity levels. RESULTS: Assessment using the BIs showed a higher proportion of individuals classified with mild severity, whereas the standardised measures indicated a higher proportion of severe ratings. Additionally, individuals with co-occurring ASD tended to have more severe impairments compared with those without ASD, as indicated by both BIs and standardised measures. Overall, the BIs were considered clinically useful, although more time and consideration were required when applying the guidelines for individuals with a co-occurring disorder of intellectual development and ASD. The principal component analysis revealed one principal component representing overall disorders of intellectual development severity levels. CONCLUSIONS: The ICD-11 BIs can be implemented as intended in international clinical settings for a broad range of presentations of individuals with neurodevelopmental disorders. Use of the BIs results in similar severity diagnoses to those made using standardised measures. The BIs are expected to improve the reliability of severity assessments in settings where appropriate standardised measures for intellectual and adaptive behaviours are not available or feasible.

Adhesive and biofilm-forming Candida glabrata Lebanese hospital isolates harbour mutations in subtelomeric silencers and adhesins.

BACKGROUND: The prevalence of Candida glabrata healthcare-associated infections is on the rise worldwide and in Lebanon, Candida glabrata infections are difficult to treat as a result of their resistance to azole antifungals and their ability to form biofilms. OBJECTIVES: The first objective of this study was to quantify biofilm biomass in the most virulent C. glabrata isolates detected in a Lebanese hospital. In addition, other pathogenicity attributes were evaluated. The second objective was to identify the mechanisms of azole resistance in those isolates. METHODS: A mouse model of disseminated systemic infection was developed to evaluate the degree of virulence of 41 azole-resistant C. glabrata collected from a Lebanese hospital. The most virulent isolates were further evaluated alongside an isolate having attenuated virulence and a reference strain for comparative purposes. A DNA-sequencing approach was adopted to detect single nucleotide polymorphisms (SNPs) leading to amino acid changes in proteins involved in azole resistance and biofilm formation. This genomic approach was supported by several phenotypic assays. RESULTS: All chosen virulent isolates exhibited increased adhesion and biofilm biomass compared to the isolate having attenuated virulence. The amino acid substitutions D679E and I739N detected in the subtelomeric silencer Sir3 are potentially involved- in increased adhesion. In all isolates, amino acid substitutions were detected in the ATP-binding cassette transporters Cdr1 and Pdh1 and their transcriptional regulator Pdr1. CONCLUSIONS: In summary, increased adhesion led to stable biofilm formation since mutated Sir3 could de-repress adhesins, while decreased azole susceptibility could result from mutations in Cdr1, Pdh1 and Pdr1.

Changes in Peak Inspiratory Flow After Acute Bronchodilation: An Observational Study of Patients with Stable Chronic Obstructive Pulmonary Disease.

Introduction: Identifying factors influencing peak inspiratory flow (PIF) is essential for aerosol drug delivery in stable patients with chronic obstructive pulmonary disease. While a minimum PIF for dry powder inhalers (DPIs) is established, acute bronchodilator (BD) effects on PIF remain unknown. Materials and Methods: An inspiratory flow meter (In-Check™ DIAL) was used to measure PIF in stable patients during a 24-week observational cross-sectional study. Additionally, bronchodilator responsiveness (BDR) was determined using the In-Check DIAL device and spirometry. Patients received four puffs of albuterol, and pre- and post-BD PIF, forced expiratory volume in one second (FEV1), and forced vital capacity were measured. Sixty-three patients completed acute BDR data collection from July 31, 2019, to November 9, 2021. Primary endpoints were pre- and post-BD spirometry and PIF. Statistical analyses included PIF correlations with FEV1. BD change was assessed according to inhaler resistance and sex (subgroup analysis). Results: Median patient age was 64.8 years, 85.7% were non-Hispanic White, and 57.1% were female. The median increase in absolute PIF (In-Check DIAL) was 5.0 L/min, and the % PIF change was 8.9%. With albuterol, 57.1% experienced a PIF BD change >5.0%, whereas 49.2% experienced a change >10.0%. Similarly, 55.6% experienced an FEV1 BD change >5.0% and 28.6% had a >10.0% FEV1 BD change with albuterol. PIF was weakly correlated with FEV1 BD change (absolute; % PIF; r = 0.28 [p = 0.02]; r = 0.21 [p = 0.11]). Pre- and post-BD median PIF were 75.5 and 83.5 L/min for low-to-medium-resistance DPI and 45.0 and 52.0 L/min for high-resistance, respectively. The median increases in pre- and post-BD PIF were 9.0 L/min in males and 4.5 L/min in females. In contrast to when using the In-Check DIAL device, we observed no consistent bronchodilatory effects on PIF measured by spirometry. Conclusions: Using the In-Check DIAL device, ∼50% of patients experienced >10% PIF increase after acute BD, potentially enhancing medication lung deposition. Further research is required to understand PIF's impact on medication delivery. ClinicalTrials.gov Identifier: NCT04168775.

Physiologic oxygen responses to smoking opioids: an observational study using continuous pulse oximetry at overdose prevention services in British Columbia, Canada.

BACKGROUND: In British Columbia, Canada, smoking is the most common modality of drug use among people who die of opioid toxicity. We aimed to assess oxygen saturation (SpO2) while people smoked opioids during a pilot study that introduced continuous pulse oximetry at overdose prevention services (OPS) sites. METHODS: This was an observational cohort study, using a participatory design. We implemented our monitoring protocol from March to August 2021 at four OPS. We included adults (≥ 18 years) presenting to smoke opioids. A sensor taped to participants' fingers transmitted real-time SpO2 readings to a remote monitor viewed by OPS staff. Peer researchers collected baseline data and observed the timing of participants' inhalations. We analyzed SpO2 on a per-event basis. In mixed-effects logistic regression models, drop in minimum SpO2 ≤ 90% in the current minute was our main outcome variable. Inhalation in that same minute was our main predictor. We also examined inhalation in the previous minute, cumulative inhalations, inhalation rate, demographics, co-morbidities, and substance use variables. RESULTS: We recorded 599 smoking events; 72.8% (436/599) had analyzable SpO2 data. Participants' mean age was 38.6 years (SD 11.3 years) and 73.1% were male. SpO2 was highly variable within and between individuals. Drop in SpO2 ≤ 90% was not significantly associated with inhalation in that same minute (OR: 1.2 [0.8-1.78], p = 0.261) or inhalation rate (OR 0.47 [0.20-1.10], p = 0.082). There was an association of SpO2 drop with six cumulative inhalations (OR 3.38 [1.04-11.03], p = 0.043); this was not maintained ≥ 7 inhalations. Demographics, co-morbidities, and drug use variables were non-contributory. CONCLUSIONS: Continuous pulse oximetry SpO2 monitoring is a safe adjunct to monitoring people who smoke opioids at OPS. Our data reflect challenges of real-world monitoring, indicating that greater supports are needed for frontline responders at OPS. Inconsistent association between inhalations and SpO2 suggests that complex factors (e.g., inhalation depth/duration, opioid tolerance, drug use setting) contribute to hypoxemia and overdose risk while people smoke opioids.

Positively Charged Biodegradable Polymersomes with Structure Inherent Fluorescence as Artificial Organelles.

Polymersomes, nanosized polymeric vesicles, have attracted significant interest in the areas of artificial cells and nanomedicine. Given their size, their visualization via confocal microscopy techniques is often achieved through the physical incorporation of fluorescent dyes, which however present challenges due to potential leaching. A promising alternative is the incorporation of molecules with aggregation-induced emission (AIE) behavior that are capable of fluorescing exclusively in their assembled state. Here, we report on the use of AIE polymersomes as artificial organelles, which are capable of undertaking enzymatic reactions in vitro. The ability of our polymersome-based artificial organelles to provide additional functionality to living cells was evaluated by encapsulating catalytic enzymes such as a combination of glucose oxidase/horseradish peroxidase (GOx/HRP) or ß-galactosidase (ß-gal). Via the additional incorporation of a pyridinium functionality, not only the cellular uptake is improved at low concentrations but also our platform's potential to specifically target mitochondria expands.

High Body Fat as a Predictor of Osteoporosis Risk in Postmenopausal Women: Insights From a Community-Based Cross-Sectional Study in Rural South India.

INTRODUCTION: Osteoporosis poses a significant health burden, particularly among postmenopausal women. While obesity in the form of BMI has been implicated in various health conditions, the relationship between waist-hip ratio (WHR) and osteoporosis remains debated. This study aims to estimate the prevalence of osteoporosis risk and explore the association between WHR and osteoporosis risk among postmenopausal women in rural South India. METHODS: A community-based cross-sectional study was conducted in the Chengalpattu district of Tamil Nadu. The study enrolled 435 postmenopausal women aged 45 years and above and the data were collected on socio-demographic characteristics, anthropometric measurements, and osteoporosis risk assessment using the Osteoporosis Self-assessment Tool for Asian Women (OSTA) scale. Logistic regression analysis was performed to identify factors associated with osteoporosis risk with 95%CI. RESULTS: The mean (SD) age of participants was 54.5 (8.6) years, 87% were married, 33% were illiterate with mean (SD) WHR of 0.88 (0.1). Around 80.5% of the participants were categorized as low risk, 16.1% as intermediate risk, and 3.5% as high risk based on OSTA scores. Older age, lower educational attainment, and higher waist-hip ratio were significantly associated with increased osteoporosis risk. CONCLUSION: This community-based study found a 20% osteoporosis risk among postmenopausal women using the OSTA scale, with age, lower education, and waist-hip ratio as key determinants. Early identification and interventions, particularly targeting older and obese individuals, are crucial to alleviate the burden and complications of osteoporosis.