Melatonin supplementation counteracts fiber loss in knee ligaments of diabetes-induced rats.

Diabetes mellitus (DM) is a prevalent metabolic disease. The clinical impact of sustained hyperglycemia on ligament healing has not been well characterized. Diabetes is a known cause of macro-, microvascular, and diabetic ulcer healing difficulties among tissues. Therefore, we aimed to investigate the healing potential occurring in injured and healthy ligaments among diabetic and healthy individuals using a rat model. We hypothesize that DM may contribute to altering the knee medial collateral ligament (MCL), thus its morphology, biochemical fitness, and functionality. The study cohort consisted of 40 rats. The animals were randomized into four equal groups. Groups I and II (20 rats) received saline subcutaneously and served as controls. Groups III and IV (20 rats) were injected with a single dose of streptozotocin (STZ). All animals underwent surgery to cut the left tibial collateral ligament in the hind limb and suture it. The access site was sutured to create inflammation and study the regenerative capacities of animals with normal carbohydrate metabolism and pharmacologically induced diabetes. Each animal then underwent sham surgery to access and suture the right tibial collateral ligament in the hind limb without ligament intervention. After the animals had undergone surgeries, groups II and IV were given melatonin supplementation for 4 weeks. Rats with DM presented with more fibrosis and calcification of the MCL and decreased healing potential. Treatment with melatonin in diabetic rats mitigated alterations and improved the antioxidant status of ligaments from the diabetic group.

Discovery of Curcuminoids as Pancreatic Lipase Inhibitors from Medicine-and-Food Homology Plants.

Researchers are increasingly interested in discovering new pancreatic lipase inhibitors as anti-obesity ingredients. Medicine-and-food homology plants contain a diverse set of natural bioactive compounds with promising development potential. This study screened and identified potent pancreatic lipase inhibitors from 20 commonly consumed medicine-and-food homology plants using affinity ultrafiltration combined with spectroscopy and docking simulations. The results showed that turmeric exhibited the highest pancreatic lipase-inhibitory activity, and curcumin, demethoxycurcumin, and bisdemethoxycurcumin were discovered to be potent pancreatic lipase inhibitors within the turmeric extract, with IC50 values of 0.52 ± 0.04, 1.12 ± 0.05, and 3.30 ± 0.08 mg/mL, respectively. In addition, the enzymatic kinetics analyses demonstrated that the inhibition type of the three curcuminoids was the reversible competitive model, and curcumin exhibited a higher binding affinity and greater impact on the secondary structure of pancreatic lipase than found with demethoxycurcumin or bisdemethoxycurcumin, as observed through fluorescence spectroscopy and circular dichroism. Furthermore, docking simulations supported the above experimental findings, and revealed that the three curcuminoids might interact with amino acid residues in the binding pocket of pancreatic lipase through non-covalent actions, such as hydrogen bonding and π-π stacking, thereby inhibiting the pancreatic lipase. Collectively, these findings suggest that the bioactive compounds of turmeric, in particular curcumin, can be promising dietary pancreatic lipase inhibitors for the prevention and management of obesity.

The Clinical Research on Ginger (Zingiber officinale): Insights from ClinicalTrials.gov analysis.

Ginger (Zingiber officinale) has a rich history of traditional medicinal use and has attracted a global interest in its health benefits. This study aims to provide insights into the clinical research landscape on ginger, focusing on its pharmacological effects and studied health-related outcomes. The study design involves systematic analysis of data from clinical trials available on ClinicalTrials.gov and discussion of findings in the context of the existing scientific knowledge. A comprehensive analysis of clinical trials registered on ClinicalTrials.gov related to ginger was first conducted, and the scientific background related to specific ginger clinical research avenues was further evaluated through PubMed searches. A variety of trial designs were identified, including treatment, prevention, and supportive care objectives. A total of 188 studies were identified on ClinicalTrials.gov, of which 89 met the inclusion criteria. Among the 89 trials, treatment objectives were predominant (47.2%), and dietary supplements (40.4%) and drugs (27%) were the most prevalent intervention types. These trials covered various health outcomes, such as antiemetic activity, analgesic function, effects on health-related quality of life, blood pressure variation, energy expenditure, and reduction in xerostomia. This study analysis provides a comprehensive overview of the clinical trials landscape on ginger, focusing on its broad spectrum of potential health benefits. While individual trials show promising results, a significant gap in the available data with a low reporting rate of final results is identified, underscoring the need for further research to establish conclusive evidence of ginger's therapeutic potentials.

Unveiling New Strategies Facilitating the Implementation of Artificial Intelligence in Neuroimaging for the Early Detection of Alzheimer's Disease.

Alzheimer's disease (AD) is a chronic neurodegenerative disorder with a global impact. The past few decades have witnessed significant strides in comprehending the underlying pathophysiological mechanisms and developing diagnostic methodologies for AD, such as neuroimaging approaches. Neuroimaging techniques, including positron emission tomography and magnetic resonance imaging, have revolutionized the field by providing valuable insights into the structural and functional alterations in the brains of individuals with AD. These imaging modalities enable the detection of early biomarkers such as amyloid-ß plaques and tau protein tangles, facilitating early and precise diagnosis. Furthermore, the emerging technologies encompassing blood-based biomarkers and neurochemical profiling exhibit promising results in the identification of specific molecular signatures for AD. The integration of machine learning algorithms and artificial intelligence has enhanced the predictive capacity of these diagnostic tools when analyzing complex datasets. In this review article, we will highlight not only some of the most used diagnostic imaging approaches in neurodegeneration research but focus much more on new tools like artificial intelligence, emphasizing their application in the realm of AD. These advancements hold immense potential for early detection and intervention, thereby paving the way for personalized therapeutic strategies and ultimately augmenting the quality of life for individuals affected by AD.

Digital Technology Applications in the Management of Adverse Drug Reactions: Bibliometric Analysis.

Adverse drug reactions continue to be not only one of the most urgent problems in clinical medicine, but also a social problem. The aim of this study was a bibliometric analysis of the use of digital technologies to prevent adverse drug reactions and an overview of their main applications to improve the safety of pharmacotherapy. The search was conducted using the Web of Science database for the period 1991-2023. A positive trend in publications in the field of using digital technologies in the management of adverse drug reactions was revealed. A total of 72% of all relevant publications come from the following countries: the USA, China, England, India, and Germany. Among the organizations most active in the field of drug side effect management using digital technologies, American and Chinese universities dominate. Visualization of publication keywords using VOSviewer software 1.6.18 revealed four clusters: "preclinical studies", "clinical trials", "pharmacovigilance", and "reduction of adverse drug reactions in order to improve the patient's quality of life". Molecular design technologies, virtual models for toxicity modeling, data integration, and drug repurposing are among the key digital tools used in the preclinical research phase. Integrating the application of machine learning algorithms for data analysis, monitoring of electronic databases of spontaneous messages, electronic medical records, scientific databases, social networks, and analysis of digital device data into clinical trials and pharmacovigilance systems, can significantly improve the efficiency and safety of drug development, implementation, and monitoring processes. The result of combining all these technologies is a huge synergistic provision of up-to-date and valuable information to healthcare professionals, patients, and health authorities.

Use of #NutritionFacts to promote evidence-based nutrition information: X (formerly Twitter) hashtag analysis study.

Nutrition is a key determinant of health, and the dissemination of reliable nutrition information to consumers is of great importance for public health. Especially with the rise of digital communication technologies and the wide-spread online misinformation, the provision of qualitative science-based information related to diet is of great importance. The NutritionFacts.org has been established as a prominent online source of evidence-based nutrition information. In this work we aimed to investigate the use of the associated hashtag #NutritionFacts on X (formerly Twitter) over a 5 years period, from 10th of April 2018 to 10th of April 2023. The conducted analysis with the use of Symplur Signals revealed that 18,998 tweets mentioning #NutritionFacts were posted by 6,136 X users, generating a total of 50,348,223 impressions (views). Both institutional and individual accounts were broadly participating in the dissemination of #NutritionFacts tweets, and the user location profiling indicated wide international engagement with the hashtag. This work indicates that #NutritionFacts has been established as an important hashtag utilized on X for the dissemination of evidence-based information related to nutrition.