Physical inactivity impairs health by increasing morbidity. In childhood, modifiable risk factors associated with cardiovascular pathologies and related to mitochondrial function and structure are initiated by physical inactivity. The objective of this study was to analyze the effect of high-intensity swimming interval training (HIIT-swim) on cardiac mitochondrial ultrastructure in young Sprague Dawley rats compared with a sedentary group. Five-week-old Sprague Dawley rats (n = 18) were divided into a control group (C) (n = 6), a sedentary group (S) (n = 6) and an HIIT-swim group (H-s) (n = 6), the last of which performed HIIT-swim for 4 weeks. A mitochondrial ultrastructural evaluation was performed using transmission electron microscopy. In the H-s rats, mitochondrial areas and perimeters were found to be statistically significantly different from those of the C and S rats. In addition, no predominant intramitochondrial multifragmentation was observed in the mitochondria of H-s rats, but multifragmentation was evident in the mitochondria of S rats.

Animal venoms represent an extraordinary, yet largely untapped, biochemical reservoir for oncological drug discovery. This review provides a comprehensive analysis of venom-derived enzyme inhibitors as emerging anticancer agents, emphasizing their chemical diversity, structure–activity relationships (SAR), molecular targets, and mechanistic pathways. Venom-derived peptides and proteins exhibit exceptional binding affinity and structural rigidity, characteristics frequently enforced by conserved disulfide networks. This specific architecture allows them to selectively modulate critical cancer-associated enzymes, including matrix metalloproteinases, phospholipases A₂, serine proteases, and kinases. Inhibiting these highly specific targets successfully disrupts tumour angiogenesis, extracellular matrix remodelling, and metastatic dissemination, while simultaneously inducing apoptosis through unique pathways such as reactive oxygen species generation. Modern computational approaches, encompassing deep learning algorithms, molecular docking, and molecular dynamics simulations, are substantially accelerating and transforming the discovery pipeline by rapidly mapping intricate peptide–receptor interactions and guiding rational drug design. Translating these potent molecules into clinical therapeutics remains heavily challenged by pharmacokinetic instability, rapid proteolytic degradation, and systemic toxicity. The integration of computationally optimized scaffolds with advanced targeted delivery platforms, such as nanocarriers and liposomal encapsulation, offers a highly viable strategy to overcome these barriers, ultimately paving the way for next-generation, venom-inspired cancer therapies.

Dihydromyricetin (DHM), a naturally occurring flavanonol predominantly found in medicinal plants like Ampelopsis grossedentata, has emerged as a promising source of natural antioxidants with multi-target pharmacological activities relevant to drug discovery. DHM exhibits a strong redox-modulating capacity, effectively attenuating oxidative stress and inflammation central drivers of chronic disease pathogenesis. Beyond direct radical scavenging, DHM regulates multiple redox-sensitive and kinase-mediated signalling pathways, thereby influencing key cellular processes involved in disease initiation and progression. This review synthesizes current evidence on the therapeutic potential of DHM, critically evaluating its mechanistic basis and translational prospects, with emphasis on its dual redox-driven and kinase-mediated modes of action. We detail its roles in metabolic disorders such as diabetes, obesity, and liver diseases, neuroprotection, cardio protection, and cancer prevention, focusing on the modulation of critical networks such as AMPK, PI3K/Akt, MAPK, NF-κB, and Nrf2. The interplay between these pathways underpins DHM’s efficacy across disease models. Furthermore, we highlight structure–activity relationship (SAR) analyses and molecular modelling studies that elucidate how the flavanonol scaffold, hydroxylation pattern, and stereochemistry of DHM govern its biological activities and target engagement. Key pharmacokinetic limitations, advances in extraction techniques, bioavailability challenges, and emerging formulation strategies including advanced delivery systems are discussed to address translational hurdles. Despite compelling preclinical data, the clinical translation of DHM remains constrained by limited human studies and incomplete mechanistic resolution. This review underscores the need for integrated pharmacological studies and innovative delivery approaches to translate the multifaceted promise of DHM into viable clinical interventions.

Zinc deficiency affects over 50% of agricultural soils globally and is a key constraint on crop yield and nutritional quality in tropical regions. Conventional zinc fertilizers such as ZnSO4 have limited nutrient use efficiency (< 5%) due to soil fixation and leaching. This paper examined the effectiveness of neem-mediated zinc oxide nanoparticles (NMZ) with neem leaf extract (NLe) as a sustainable bionanofertilizer for Corchorus olitorius plants (COp). Characteristic NMZ absorption peaks were verified with a UV-Visible spectrophotometer, and a crystal structure of hexagonal wurtzite with an average crystallite size of 16.8 nm was revealed by the X-ray diffraction analysis. Fourier Transform Infrared Spectra demonstrated the capping of phytochemicals in NLe. Dynamic Light Scattering results revealed progressive size reduction of highly monodisperse particles with a polydispersity index less than 0.3. Brunauer Emmet Teller analysis showed a relatively higher surface area of smaller particles. Results also revealed that the plant height of COp grew by 28% relative to the control, growing to 18.5 cm at week 7. Leaf count grew by 19%, and the chlorophyll content reached its peak of 31.8 ± 0.5 mg/g fresh weight (FW) of leaves. Soil analyses after harvests showed that NMZ treatments had maintained an optimal pH (6.15–6.26) and significantly enhanced the quantity of available zinc. Plant tissue analysis confirmed enhanced zinc uptake, with shoot zinc content reaching 0.032% in 0.05 M treated plants compared to 0.012% in controls. The results affirm that NMZ is a promising and sustainable complement to conventional zinc nutrition strategies, warranting further field-scale validation.

This study seeks to address critical gaps in household air pollution (HAP) exposure assessment in low- and middle-income settings by applying a proxy-based exposure reconstruction framework supported by machine learning to develop an exploratory proxy-based exposure index and examine associations with nonlinear health patterns in Kabale, Uganda. A quantitative cross-sectional survey ( N = 275) was conducted to capture behavioral, environmental, and socio-demographic proxies of exposure, including fuel type, cooking duration, ventilation, and cooking location. A latent exposure index was developed using Principal Component Analysis and validated with Random Forest and Gradient Boosting models, while nonlinear exposure–health relationships were analyzed using ML classifiers and household typologies identified through K -Means clustering. The findings reveal that exposure is driven primarily by behavioral factors, particularly cooking duration, rather than fuel type alone. Nonlinear modeling suggested possible threshold-like and plateauing patterns in self-reported health outcomes, with acute symptoms such as eye irritation appearing at lower proxy-based exposure levels and chronic respiratory distress showing possible plateauing at higher exposure levels. Clustering analysis identifies a large high-risk group characterized by prolonged indoor biomass use and elevated symptom burden. ML models outperform traditional regression approaches in predicting chronic symptoms but show limited performance for clinical diagnoses. These findings suggest that proxy-based HAP exposure patterns may be multidimensional and potentially nonlinear and demonstrate the value of ML in proxy-based environments, emphasizing that policy interventions must move beyond fuel switching to address behavioral practices and structural constraints shaping exposure.