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This paper researched upon the cross-connection between social support, academic support, and well-being among a diverse sample of 190 university students, comprising 64 international and 126 Indian students. Investigating how interpersonal connections involving emotional support and educational assistance intersect, the research aims to shed light on the impact of these factors on individuals' psychological and emotional states of these vertos. It covers a crucial gap in existing literature by exploring the alliance between social support and academic success, recognizing their joint impact on well-being. Understanding the mutual linkage between these elements can provide valuable insight into how social support and academic support influence the well-being of crosscultural students to further establish the development of interventions and support mechanisms. The findings revealed a positive correlation between social support and well-being, indicating that higher levels of social support are associated with improved overall well-being for both Indian and international students. Similarly, academic support demonstrated a significant positive relationship with well-being, emphasising the crucial role of educational resources and assistance in fostering a positive mental and emotional state among students. Notably, the study unveiled minor cultural disparities highlighting the similar experiences of Indian and international students. The results of regression analysis further suggest that while social support is a significant predictor of well-being, academic support is not an efficient predictor and thus, better initiatives should be taken by the relevant organisations with respect to creating an upsurge in the social support levels.

Approximately 60–70% of individuals with diabetes experience varying degrees of damage to their nervous system, resulting in a condition known as diabetic peripheral neuropathy (DPN). DPN usually involves distal body parts and is characterised as distal symmetrical sensorimotor neuropathy which is progressive in nature and follows a "glove and stocking pattern". It has significantly contributed to neuropathic pain, decreased nerve conduction velocity (NCV), impaired proprioception, compromised balance, and postural instability. This study aimed to evaluate the effectiveness of Neuromuscular Taping (NMT) in enhancing balance, proprioception, pain relief, and nerve conduction parameters in patients with DPN. Five patients received an 8-week physiotherapy intervention that included both neuromuscular taping and transcutaneous electrical stimulation (TENS). Neuromuscular taping was applied to the bilateral tibialis anterior muscle, tibialis posterior muscle, peroneus longus muscle, and the transverse arch of the foot. TENS was administered along the distribution of the tibial and peroneal nerves with the following parameters: 80 Hz frequency, 50 Amp intensity, 0.2 ms square pulses, at 2 to 3 times the sensory threshold, on alternate days for a period of 3 weeks, with each session lasting 20 minutes. Remarkably, all patients exhibited improvements in their Berg Balance Scale scores, Leeds Assessment of Neuropathic Signs and Symptoms, proprioception, as well as nerve conduction parameters of the bilateral tibial, peroneal, and sural nerves and latency of H-reflex. NMT was found to be an effective method to treat symptoms associated with DPN. [ABSTRACT FROM AUTHOR]

Aims The immense therapeutic value of Valeriana jatamansi is attributed to the presence of bioactive secondary metabolites (valepotriates and sesquiterpenoids). Its over-exploitation in wild habitats resulted in extensive depletion, necessitating alternative approaches to produce its therapeutic metabolites. This study sought to assess the ability of endophytes of V. jatamansi to boost the biosynthesis of secondary metabolites in the leaf-cell suspension (LCS) culture of V. jatamansi. Methods and results A total of 11 fungal endophytes were isolated from the rhizomes of V. jatamansi. Isolated endophytes were found to belong to phylum Ascomycota, Basidiomycota, and Mucoromycota. Supplementation of extracts of endophyte Phaeosphaeriaceae sp. VRzFB, Mucor griseocyanus VRzFD, Penicillium raistrickii VRzFK, and Penicillium sajarovii VRzFL in the LCS culture of V. jatamansi increased the fresh cell biomass by 19.6%–39.1% and dry cell biomass by 23.4%–37.8%. Most of the endophytes' extract could increase the content of valepotriates (26.5%–76.5% valtrate and 40.5%–77.9% acevaltrate) and sesquiterpenoids (19.9%–61.1% hydroxyl valerenic acid) in LCS culture. However, only two endophytes, Irpex lacteus VRzFI and Fusarium oxysporum VRzFF, could increase the sesquiterpenoids acetoxy valerenic acid (36.9%–55.3%). In contrast, some endophytes' extracts caused negative or no significant effect on the cell biomass and targeted metabolites. Increased secondary metabolites were corroborated with increased expression of iridoid biosynthesis genes in LCS culture. Production of H2O2 and lipid peroxidation was also varied with different endophytes indicating the modulation of cellular oxidative stress due to endophyte elicitors. Conclusions The results suggest the distinct effect of different fungal endophytes-extract on LCS culture, and endophytes can serve as biotic elicitors for increasing the secondary metabolite production in plant in vitro systems. [ABSTRACT FROM AUTHOR]

Aims: The current work describes the development of mechanistic vaginal absorption and metabolism model within Simcyp Simulator to predict systemic concentrations following vaginal application of ring and gel formulations. Methods: Vaginal and cervix physiology parameters were incorporated in the model development. The study highlights the model assumptions including simulation results comparing systemic concentrations of 5 different compounds, namely, dapivirine, tenofovir, lidocaine, ethinylestradiol and etonogestrel, administered as vaginal ring or gel. Due to lack of data, the vaginal absorption parameters were calculated based on assumptions or optimized. The model uses release rate/in vitro release profiles with formulation characteristics to predict drug mass transfer across vaginal tissue into the systemic circulation. Results: For lidocaine and tenofovir vaginal gel, the predicted to observed AUC0‐t and Cmax ratios were well within 2‐fold error limits. The average fold error (AFE) and absolute AFE indicating bias and precision of predictions range from 0.62 to 1.61. For dapivirine, the pharmacokinetic parameters are under and overpredicted in some studies due to lack of formulation composition details and relevance of release rate used in ring model. The predicted to observed AUC0‐t and Cmax ratios were well within 2‐fold error limits for etonogestrel and ethinylestradiol vaginal ring (AFEs and absolute AFEs from 0.84 to 1.83). Conclusion: The current study provides first of its kind physiologically based pharmacokinetic framework integrating physiology, population and formulation data to carry out in silico mechanistic vaginal absorption studies, with the potential for virtual bioequivalence assessment in the future. [ABSTRACT FROM AUTHOR]

Code-blended online texts are increasingly prevalent due to multilingual influences. This phenomenon is commonly observed in user-generated content on social platforms, especially from multilingual users. Such content, including articles and information, possesses informal language features like non-standard abbreviations, contracted transliterations, and casual grammar. To effectively handle and analyze code-blended data for various Natural Language Processing tasks, understanding this phenomenon is crucial. As the need for translating code-blended content into standard language grows, our study focuses on short utterances gathered from Facebook, Twitter, and WhatsApp. The dataset, comprised of English and Marathi language pair from Indian web-based text, aims to provide a resource for translating code-blended content into plain English. We have tested the dataset on various machine learning classifiers, achieving good accuracy in language identification, and thereafter translation was performed through LSTM network. We scored 91% prediction accuracy while translating code mixed sentences into normal English language sentences. [ABSTRACT FROM AUTHOR]