Hasniza Zaman Huri

Overweight and obesity complicate insulin treatment in adults with type 2 diabetes mellitus (T2DM), requiring consideration of glycaemic control, insulin requirements, body weight, and treatment burden. This scoping review mapped insulin treatment modification (ITM) strategies, synthesised their reported outcomes, and identified evidence gaps among insulin-treated adults with T2DM and overweight or obesity. Five electronic databases were searched following Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and updated Joanna Briggs Institute methodological guidance. Thirty-three studies were classified into four ITM domains: add-on therapy to insulin, switching to advanced insulin formulations, simplifying complex insulin regimens with adjunctive therapy, and switching to fixed-ratio combinations. Intensification was generally studied in patients with higher baseline glycated haemoglobin or insulin requirements, whereas simplification was more often evaluated in those receiving complex insulin regimens. Insulin-dominant intensification generally increased total daily insulin dose, while intensification incorporating Glucagon-Like Peptide-1 Receptor Agonists (GLP-1RAs) or Sodium-Glucose Cotransporter-2 Inhibitors (SGLT2i) commonly reduced insulin requirements and body weight. Simplification generally reduced insulin requirements and/or injection burden while maintaining or improving glycaemic control, with weight reduction frequently reported. Direct comparisons and obesity-specific subgroup analyses were limited. Intensification and simplification should therefore be considered complementary rather than opposing approaches, with outcomes influenced by therapeutic components and patient characteristics.

Background: Neuromycoses, fungal infections affecting the central nervous system (CNS), cause approximately 112,000 deaths annually, representing 19% of AIDS-related deaths globally. Conventional antifungal drugs are limited by poor blood-brain barrier (BBB) penetration, systemic toxicity, and increasing drug resistance. Lipid nanoparticles (LNPs) have emerged as promising vehicles for enhancing antifungal efficacy while modulating immune responses. Thus, this comprehensive review synthesizes current knowledge on LNPs as vehicles for antifungal immune modulators, including their design principles, drug delivery mechanisms, physiological interactions, translational potential, and roadmap for next-generation precision medicine approaches to treating neuromycoses. Methods: A comprehensive narrative review of original studies on LNP-based approaches for neuromycoses was conducted. The literature was synthesized using a structured evidence table encompassing six studies published between 2019 and 2026, including one randomized clinical trial in adults, one case report, one in vitro study, two animal studies, and one study incorporating both in vitro and in vivo approaches. Original research studies were prioritized, while reviews, commentaries, and editorials were excluded. Findings: This review shows four principal findings: (1) LNP formulations achieved mean fungicidal activity of 0.402 log₁₀ CFU/mL/day, non-inferior to intravenous amphotericin B, with 18-week survival and reduced toxicity compared to intravenous formulations; (2) LNPs cross the BBB with limited or no systemic toxicity while enabling intracellular trafficking through optimization of lipid composition and surface chemistry; (3) RMT demonstrates high specificity affected by variability in receptor expression, while AMT and TMT operate through distinct mechanisms with their own potential off-target effects; and (4) encapsulation reduces nephrotoxicity and hepatotoxicity compared to free antifungal drugs, with amphotericin B-loaded NLC showing reduced nephrotoxicity in vitro compared to conventional formulations. Conclusion: These findings highlight the potential of LNP-based antifungal delivery and the need for further clinical validation before broader clinical translation.

Brain cancer is one of the most challenging malignancies and a major contributor to worldwide morbidity and mortality. Glioblastoma, the most aggressive adult brain tumor, is associated with poor prognosis despite conventional therapies such as surgery, chemotherapy, and radiotherapy, which often result in severe toxicity and long-term side effects. Immunotherapy holds the potential to provide durable and specific anti-tumor responses; however, its success in brain cancer is hindered by obstacles such as the blood-brain barrier, immunosuppressive tumor microenvironment, and tumor heterogeneity. Nanomedicine offers a powerful approach to overcoming these barriers through targeted and efficient drug delivery. Nanotechnology-based platforms, including lipid-based, polymeric, and inorganic nanoparticles, have demonstrated superior therapeutic efficacy compared to free drugs, with several formulations advancing into clinical trials. Among these, nanotechnology-enabled vaccines represent an emerging frontier, capable of enhancing antigen presentation, stimulating strong immune responses, and overcoming tumor-induced immunosuppression. By combining the precision of nanocarriers with the long-lasting protection of vaccines, nano-vaccines hold great potential to transform brain cancer immunotherapy. Recent studies also suggest that integrating artificial intelligence (AI) with nanotechnology could further enhance the design, targeting, and effectiveness of immunotherapies. Moreover, AI is revolutionizing treatment development by enabling the prediction of immunogenicity, immune responses, and optimizing formulation design and dosing strategies. These advancements collectively accelerate the development and enhance the precision and efficiency of immunotherapy. Hence, this review discusses current nanotechnology-based immunotherapies and highlights the emerging role of integrating AI in vaccine development as next-generation strategies for improving outcomes in brain cancer treatment.

Purpose: Metabolic syndrome (MetS), characterized by central obesity, hypertension, hyperglycemia, and dyslipidemia, increases the risk of cardiovascular disease, type 2 diabetes, and cognitive decline in older adults. As the global population continues to age, elucidating the metabolic mechanisms linking MetS to cognitive decline is crucial. Patients and methods: We conducted a cross-sectional study to profile plasma metabolites of 42 MetS patients and 42 healthy controls (median age 69.0 and 68.5 years, respectively) using nuclear magnetic resonance (NMR) prior to mediation analysis. Cognitive function was assessed with the Montreal Cognitive Assessment (MoCA) and Digit Span Tests (Forward and Reverse). Results: Metabolomic analysis (PLS-DA: Q² = 0.41, R² = 0.50, accuracy 78.3%) identified 13 differentially abundant metabolites, including amino acids (isoleucine, alanine, serine), fatty acid chains, lactate, glycoprotein acetylation (GlycA), acetone, and creatine. Mediation analysis showed that fatty acid chains, GlycA, acetone, lactate, and isoleucine exhibited significant competitive mediation effects between MetS and delayed recall function. Furthermore, lactate levels fully mediated the effects between MetS and attention. Conclusion: Metabolite biomarkers associated with cognitive decline in older adults with MetS were identified, with lactate, isoleucine, GlycA, acetone, and fatty acid being associated with better delayed recall performance, whereas elevated lactate levels were associated with poorer attention. Longitudinal and interventional studies are needed to confirm these pathways and clarify their implications for cognitive health in this population. The infographic presents a study on metabolic syndrome in 84 older adults in Malaysia. The methods section shows two groups: Metabolic Syndrome group with 42 participants and Control group with 42 participants. Cognitive testing and plasma metabolomics based on Nuclear Magnetic Resonance are conducted, followed by mediation analysis. The results section includes a graph labeled ’Metabolomics results’ and identifies 13 differentially abundant metabolites. A diagram illustrates the metabolic pathways, highlighting changes in glucose, lactate and other metabolites. Eight metabolites are shown to mediate the association between metabolic syndrome and cognitive function. The conclusion states that metabolic syndrome shifts glucose metabolism toward anaerobic glycolysis, increasing lactate and reducing serine and creatine synthesis. Lactate impairs attention but supports delayed recall, while isoleucine, unsaturated fatty acids and acetone may enhance delayed recall.Infographic on metabolic syndrome study in older adults, showing methods, results and conclusions.

Aims: In adults with type 2 diabetes (T2D), continuous glucose monitoring (CGM) provides insights beyond HbA1c. A comprehensive understanding of clinical benefits and patient‐reported outcomes (PROs) associated with CGM is needed to inform its integration into routine care. Methods: A systematic literature search was conducted across PubMed, Scopus, Cochrane Library and CINAHL from inception to June 2025 to identify randomised controlled trials and non‐randomised studies including quasi‐experimental and observational designs. Outcomes of interest included glycaemic measures (HbA1c, time in range, hypoglycaemia, glycaemic variability) and PROs. Given the heterogeneity in study design and outcome reporting, findings were synthesised narratively. Results: Thirty studies (N ≈ 3275) were included. CGM use was associated with improvement in HbA1c, particularly among insulin‐treated individuals and those with higher baseline HbA1c. CGM use also increased time in range by approximately 9–15 percentage points (1.5–3.6 h/day) and was generally associated with reduced hypoglycaemia risk and glycaemic variability, although effects on hypoglycaemia were not uniform. In contrast, diabetes‐specific PROs, including treatment satisfaction and diabetes‐related distress, showed more consistent improvement, whereas changes in overall quality‐of‐life measures were less pronounced. Conclusions: CGM use was associated with clinically meaningful improvements in glycaemic metrics and PROs in adults with T2D. Although evidence remains limited for long‐term outcomes and special populations, current findings support the clinical value of CGM in diabetes management.

Epicardial adipose tissue (EAT) is an emerging cardiometabolic risk factor in type 2 diabetes mellitus (T2DM). While SGLT-2 inhibitors (SGLT-2i) offer cardiovascular benefits, their specific effects on EAT and left ventricular (LV) remodeling and function in Asian populations remain understudied. This study investigated the relationship between SGLT-2i on cardiometabolic parameters, EAT thickness and LV function in Malaysian patients with T2DM and coronary artery disease (CAD). A total of 360 patients with T2DM and CAD were divided into non-SGLT-2i and SGLT-2i groups. Anthropometric, cardiometabolic, and echocardiographic measurements were analyzed at baseline and post-6 months for 302 patients who competed the study (n = 151 per group). Both groups showed improvements in glycemic control (fasting blood glucose − 1.7 vs. − 2.6 mmol/L; HbA1c − 0.3% vs. − 0.6%; all p < 0.001). Broader cardiometabolic benefits were observed predominantly among SGLT-2i group, including greater reductions in body mass index (– 0.7 vs. − 0.3 kg/m²) and serum lipid concentrations (all p < 0.001), a marked decrease in EAT thickness (–1 .5 mm vs. + 0.6 mm, p < 0.001), and concomitant improvements in left ventricular structure, with reductions in LV mass (– 20 vs. + 7.8 g) and increased LV ejection fraction (+ 4.6% vs. − 1.0%) (all p ≤ 0.01). Within the SGLT-2i group, EAT reduction was associated with lower body weight and BMI (p < 0.05) but was independent of glycemic changes. Reductions in body weight and BMI were associated with improvements in LV diameter and mass (p < 0.05) and although not directly mediated by changes in EAT. Beyond glycemic control, SGLT-2i was associated with reduced EAT thickness and improved LV remodeling and function in Malaysian T2DM patients with CAD. The reduction in EAT thickness specifically was associated with lower body weight and BMI. These findings provide Asian population–specific evidence with distinct cardiometabolic and adiposity traits.

Poor medication adherence remains a major barrier to effective hypertension control, particularly in low-resource settings. This study aimed to explore causal pathways, necessity conditions and optimization priorities of the CareAide mobile application for improving medication adherence and clinical outcomes among hypertensive patients. A prospective, randomised, open-label, two-arm trial was conducted at University Malaya Medical Centre. Adults (N = 275) with hypertension and low Morisky Medication Adherence Scale (MMAS-8) scores were randomised to CareAide plus usual care or usual care alone for six months. Primary outcome was adherence (MMAS-8) at third (F1) and sixth month (F2); secondary outcomes included systolic/diastolic blood pressure (Hypertension F1, F2) and application satisfaction via Mobile Adherence Satisfaction Scale (MASS). Structural Equation Modelling (SEM), Necessary Condition Analysis (NCA) and Combined Importance–Performance Map Analysis (cIPMA) tested hypotheses from an integrated theoretical framework. Intervention showed large positive effects on adherence at (F1 β = 0.58, F2 β = 0.79, P < 0.001 ). Six-month adherence mediated the intervention’s impact on blood pressure (indirect β = −0.16, P = 0.006 ) and together with early adherence, formed a sequential mediation chain (β = −0.05, P = 0.01 ). NCA showed the intervention (d = 0.18) and early adherence (d = 0.28) were necessary for high F2 adherence; the intervention (CE-FDH = 100%) and prior blood pressure control (CE-FDH = 48.58%) were necessary for optimal F2 blood pressure. Feature satisfaction (FS) was both sufficient (β = 0.20, P < 0.001 ) and necessary (d = 0.29) for sustained adherence. cIPMA identified the intervention, early adherence and FS as high-importance, low-performance targets. CareAide significantly improves adherence and blood pressure via a temporally sequenced behavioral pathway with early adherence gains and FS are critical, actionable factors. Trial registration: CAREAide Trial (ClinicalTrials.gov identifier: NCT06068309).

Andrographis paniculata (Burm. F.) Nees (AP) is a phytomedicinal plant traditionally used for colds, infections, and diabetes in Southeast Asia. The bioactive diterpenoids such as andrographolide, 14-deoxyandrographolide, and neoandrographolide has anti-inflammatory, antimicrobial, and glucose-lowering effects. Although widely used, clinical studies integrating AP’s drug composition with its pharmacometabolomics responses remain limited. This study integrated pharmacokinetics (PK) and pharmacometabolomics (PMx) to understand dose–response relationships and pharmacological effects of orally administered AP capsules (1000 mg and 2000 mg) to 12 healthy volunteers under fasting conditions. Three biomarkers were measured from five AP brands to determine the highest-concentration AP capsule for dosing. PK analysis used 75 plasma samples while PMx analysis involved 96 plasma and urine samples. Liquid chromatography-tandem mass spectrometry (LC–MS/MS) were used for both analyses. Statistical analysis included multivariate analyses (PCA, PLS-DA), followed by peaks-to-pathway analysis via MetaboAnalyst 5.0. Time to reach maximum plasma concentration (Tmax) for andrographolide, 14-deoxyandrographolide, and neoandrographolide was 1.5 h, with maximum plasma concentration (Cmax) of 10.15 ng mL ⁻¹ , 7.02 ng mL ⁻¹ and 58.45 ng mL ⁻¹ , respectively. At 1000 mg, AP enhanced steroid hormone biosynthesis, while 2000 mg induced broader metabolic shifts, enriching pathways such as biosynthesis of unsaturated fatty acids, alanine/aspartate/glutamate metabolism, and lysine degradation. No free bioactive compounds were detected in urine, indicating metabolism into conjugated forms. Clinical PK guided PMx revealed metabolic responses supporting AP’s potential as a therapeutic agent for inflammation and glucose lowering effect. Further clinical research could optimize dosing and advance AP as a precision medicine candidate.

Background: This study aimed to identify patient segments of acceptability to vaginal dosage forms in women with the genitourinary syndrome of menopause and to identify the most important predictors and mediators of each segment using latent segment analysis. Methods: A cross-sectional study included 351 peri- and postmenopausal women from two tertiary care hospitals in the United Arab Emirates. To select the best model, we ran a finite-mixture partial least squares segmentation (FIMIX-PLS). The number of resulting segments was used to run a partial least squares-predicted-oriented segmentation to assign cases to segments and maximize the segment-specific explained variance (R²) across all groups. Multi-group analysis was then performed to examine whether differences between segments were significant. Analyses were performed using the SmartPLS Software version 4.9, Results: A two-segment model was identified (Entropy > 0.8, Corrected-Akaike’s Information Criterion = 1977.11; Bayesian Information Criterion = 1960.11), which indicated adequate and well-separated segments. The first and second segments had 179 and 171 of the cases, respectively, which were considered substantive representations of both segments. The model resulted in a weighted average R² greater than that of the original sample, indicating better predictive relevance of the model. The multi-group analysis showed that the differences between the two segments were significant. Being on vaginal treatment was observed to be the variable that drove the partition of the segments. Perceived effectiveness for those who were not on treatment (segment 1) and those who were (segment 2) was predicted by affective attitude and intervention coherence, respectively, Conclusion: The acceptability of vaginal treatments differs between experienced and anticipated users. Considering patient-related factors and previous treatment experiences can serve as a benchmark to improve patient acceptability of treatment.

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder marked by cognitive decline, memory impairment, and neuronal loss. Xanthones, a