KLE University

Metal ions are vital for living and environmental system. Consequently, their detection and monitoring has been considered great significance by the chemists. Scientists are developing new approaches to recognize these cations. It was successfully demonstrated that fluorescent sensors developed on organic structural framework are effective in detecting all kinds of metal ions and offer a number of benefits, including inexpensiveness, simple synthesis and high sensitivity. In present work, a novel and versatile Schiff base chemosensor 6-(2-((E)-2hydroxybenzylidene)hydrazine-1-carbonyl)-N-(2-(2-((E)-hydroxybenzylidene)hydrazine-1-carbonyl)phenyl) picolinamide (HSH) was synthesized for quick recognition of Al3+ ions through fluorescence turn-on response at lambda max. 473 nm in DMF:H2O (1:1). The HSH exhibited high fluorescence property by inhibiting ESIPT process, -C=N- isomerization and enhanced ICT character upon coordinated with Al3+ ions. The stoichiometric ratio (1:2) of the HSH towards Al3+ ions was confirmed by ESI-MS and Job's plot analysis. The obtained detection limit and binding constant value for HSH were found to be 11.93 nM and 8.69 x 106 M- 1 respectively. The HSH was utilized for bio-imaging application in HeLa cells. In addition, the sensing properties of HSH were studied on economical test along with TLC kits for the recognition of Al3+ ions. The findings of the present investigation suggest that the HSH could be serve as potent chemosensor for Al3+ ions.

Background:Reportedly, around 6.3% of individuals over the age of 30 in Asia-Pacific countries suffer from stages II and III chronic obstructive pulmonary disease (COPD). Among various rehabilitation strategies, Inspiratory Muscle Training (IMT) and Autogenic Drainage (AD) are emerging as effective interventions aimed at improving respiratory function and symptom control. This study aimed to evaluate and compare the effects of IMT and AD in hospitalized COPD patients, focusing on outcomes related to lung function, quality of life, bronchial hygiene, and respiratory muscle performance. Methods:Out of 59 screened subjects, 40 met the inclusion criteria and were enrolled. They were randomly allocated into two groups: Group A received AD and Group B underwent IMT. Both groups participated in a structured intervention protocol for two weeks. A total of 35 participants completed the study. Results:Post-intervention, both groups showed significant improvement in forced vital capacity (FVC): Group A (-0.61 ± 0.52; P = .0089) and Group B (-0.46 ± 0.67; P = .0233). Chest expansion at Point B (measured at nipple level ) increased significantly in both groups (P = .0002) and at Point A (measured at axillary level) in Group A (P = .0283). While other outcomes, namely FEV1/FVC (P = .5), St George Respiratory Questionnaire (P = .6), Maximal Inspiratory Pressure (P = .6), and 6-minute walk test (P = .9), demonstrated positive trends, although not statistically significant. Conclusion:Both the AD and IMT groups demonstrated statistically significant increases in FVC and chest expansion following the intervention, especially at the axillary level in the AD group and at the nipple level in both groups. Although not statistically significant, other variables such as the FEV1/FVC ratio, quality of life scores, inspiratory pressure, and functional exercise capacity demonstrated clinically useful trends. Keywords:chronic obstructive pulmonary disease, respiratory therapy, rehabilitation, pulmonary function tests, inspiratory muscle training, autogenic drainage.

AI and the IoT are revolutionizing drug development and discovery. By utilizing real-time data and sophisticated algorithms, researchers can rapidly identify potential drug candidates and assess their efficacy. In drug research, AI plays a vital role in predicting the pharmacological properties of lead compounds from their chemical structures, thereby improving the efficiency of medication discovery and development. It is possible to develop predictive models that estimate the key features of solubility, bioavailability, and toxicity by utilizing machine learning methods. These models provide a blueprint for designing new molecules with improved pharmacological attributes, thereby boosting the efficacy and safety of potential therapies. The integration of the IoT in the pharmaceutical industry accelerates the production of new drugs for conditions requiring treatment, reducing both time and costs. Utilizing cell-in-a-chip and organ-in-a-chip devices that replicate human physiological conditions, the early evaluation of potential formulations is significantly expedited. By analysing patient data and electronic medical records more effectively, AI enhances clinical trial design and speeds up patient recruitment. AI also helps optimise trial design by identifying which patient subgroups are more likely to respond to therapies. Real-time monitoring is enabled by AI-driven wearables, which ensure accurate data collection and the necessary modifications to trial protocols to improve patient safety. The chapter also examines how AI and IoT are used in drug research, including target identification, drug design, and clinical trials. Lastly, it addresses potential issues and constraints associated with these technologies, as well as future directions for this field's research and development. In conclusion, this chapter has shown how AI and the Internet of Things could drastically improve the development and discovery processes, leading to better and more efficient treatments for a wide range of ailments.

Objective Electroconvulsive therapy (ECT) is an interventional psychiatric technique used primarily to address treatment resistant psychiatric disorders. There are many different stimulus electrode placements and pulse widths utilized in the administration of this therapy, but it is presently unclear which is optimal. The aim of this study is to assess the relative efficacy and side-effect profile of ultrabrief pulse width ECT (UBP ECT) and brief-pulse width ECT (BP ECT) in the treatment of major depressive disorders. Method A systematic review of the literature was performed. Studies were identified from PubMed, MEDLINE and PsycINFO between January 2013 to October 2023. The final search terms included ECT, depression, brief pulse, and ultrabrief pulse. Results The search initially included 64 studies. Forty-three of these studies were not duplicates, after applying exclusion criteria 11 studies were included. UBP ECT was found to have fewer cognitive side effects than BP ECT. Additionally, patients undergoing BP ECT were found to discontinue treatment more frequently due to inability to tolerate side effects. Despite this, BP ECT may have higher rates of symptom remission than UBP ECT. Further studies should be done to clarify the outcomes of each technique. Conclusions The current evidence slightly favors UBP ECT due to its beneficial side effect profile compared to BP ECT while it has a similar efficacy. However, there is insubstantial evidence in the current body of literature. Additional studies are required to determine which of these techniques is safer and more efficacious in the treatment of major depressive disorders. Study Design Systematic review.

Background Dolphin-assisted therapy (DAT) has gained increasing attention as a complementary intervention for children with cerebral palsy. However, the scientific literature remains poorly mapped and conceptually inconsistent, frequently conflating this pediatric neurodevelopmental condition with adult-onset neurodegenerative disorders—particularly Parkinson’s disease—thereby raising concerns about clinical relevance and theoretical coherence. Data and Methods: We conducted a comprehensive bibliometric analysis of 373 peer-reviewed articles indexed in Scopus (1993–2025). Using a systematic keyword-based search strategy, we analyzed publication trends, collaboration networks, institutional productivity, and thematic evolution. Data were processed and visualized using Bibliometrix (via Biblioshiny) and VOSviewer, employing co-occurrence analysis, overlay visualization, and strategic diagram mapping to delineate the intellectual structure and developmental trajectory of the field. Results Publications increased annually by 11.21%, peaking at 40 in 2024, with strong collaboration (6.64 co-authors/article) and 24.9% international co-authorship. Research is led by a few authors (LEE, PHIL-HYU; ZOGALA, DAVID) and institutions (Yonsei University; UC San Diego). Most papers appear in neurology journals like Movement Disorders and Parkinsonism and Related Disorders . Keyword analysis identified three clusters: clinical studies, preclinical mechanistic research, and Parkinson’s biomarker work. Temporal patterns shifted from clinical (2016–2018) to mechanistic (2019–2020) to translational (2021–2022). Thematic mapping revealed underdeveloped female- and sex-specific research compared to motor-related male-focused studies. Conclusion Despite growing output, the field is misaligned framed through adult Parkinson’s paradigms despite targeting children with a non-progressive condition. The neglect of pediatric specificity, sex differences, and experiential dimensions limits clinical relevance. Future research must prioritize developmentally appropriate, patient-centered, and methodologically rigorous inquiry to determine whether dolphin therapy offers genuine therapeutic value or remains an unproven intervention shaped more by narrative than evidence.