Enhancement of total antioxidants and flavonoid (quercetin) by methyl jasmonate elicitation in tissue cultures of onion (Allium cepa L.)

The onion (Allium cepa) is a vegetable used extensively all over the world both for culinary purposes as well as in medicine. Its medicinal values are due to the high levels of biologically-active compounds present within the bulb. There are various phytochemicals of therapeutic importance found in A. cepa. Quercetin, a flavonoid, is one of these phytochemicals and it is a potent antioxidant. Allium cepa is a dietary supplement and is beneficial for diverse ailments, thus justifying its status as a valuable medicinal plant. Due to its medicinal significance, elicitation of total antioxidants and quercetin levels have been attempted to enhance their production in tissue callus cultures. This study reports in vitro enhancement of total antioxidants and quercetin in A. cepa using methyl jasmonate as an elicitor. A reverse phase-high performance liquid chromatography (RP-HPLC) method was used with an isocratic system and a flow rate of 1.0 mL min−1 and a mobile phase of acetonitrile: 1% v/v acetic acid (60%:40% v/v). The detection wavelength was 362 nm and the retention time 8.79 minutes. Total antioxidant and quercetin contents were maximal with 100 µM of methyl jasmonate in leaf tissue callus cultures at 84.61 ±6.03% and 0.81 ±0.03 mg g−1 dry cell weight, respectively. They decreased with further increases of methyl jasmonate at 200 µM. The increase in total antioxidant and quercetin contents were 2.3- and 13.9-fold, respectively. The optimization of methyl jasmonate as an elicitor, as well as the determination of a suitable concentration in A. cepa in callus cultures, will be helpful for enhanced production of various other secondary metabolites of therapeutic significance. This could be beneficial for the pharmaceutical and neutraceutical industries for herbal drug formulations

Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning

Multi-agent settings in the real world often involve tasks with varying types and quantities of agents and non-agent entities; however, common patterns of behavior often emerge among these agents/entities. Our method aims to leverage these commonalities by asking the question: ``What is the expected utility of each agent when only considering a randomly selected sub-group of its observed entities?'' By posing this counterfactual question, we can recognize state-action trajectories within sub-groups of entities that we may have encountered in another task and use what we learned in that task to inform our prediction in the current one. We then reconstruct a prediction of the full returns as a combination of factors considering these disjoint groups of entities and train this ``randomly factorized" value function as an auxiliary objective for value-based multi-agent reinforcement learning. By doing so, our model can recognize and leverage similarities across tasks to improve learning efficiency in a multi-task setting. Our approach, Randomized Entity-wise Factorization for Imagined Learning (REFIL), outperforms all strong baselines by a significant margin in challenging multi-task StarCraft micromanagement settings.Comment: ICML 2021 Camera Read

Visual and treatment outcomes of tubercular uveitis: a prospective case series from a referral hospital in Pakistan

Objective: Pakistan is the fifth highest TB burden country. Tuberculous uveitis (TbU) is a form of extrapulmonary TB, that is not uncommon in high burden country but very limited data is available on its outcome. The aim of the study is to assess the outcome of TbU with anti-tuberculous treatment (ATT). Results: A prospective study was conducted at Jinnah Medical College Hospital (JMCH) Karachi, Pakistan from July to December 2017. Patients with suspected TbU were started on standard ATT chemotherapy for 12 months. Their response was assessed via slit lamp examination and visual acuity at 1, 3, 6 and 12 months of treatment. Forty patients with probable TbU were treated with ATT, mean age was 36 ± 3 years and 24 (60%) were females. Around 26 (65%) had Monteux test of 15 mm or more. History of TB contact was positive in 24 (60%) and 12 (30%) had previous history of TB. All patients complained for blurring of vision and floaters. Posterior uveitis seen in 36 (90%) of patients. Complete response achieved in 32 (80%) after ATT while 6 (14%) had changed in inflammation and 2 (6%) had no benefit

Monkeypox: A Review in Indian Context

Emerging and re-emerging zoonoses of diverse etiologies have caused significant morbidity and mortality recently. In the past two decades, several viral zoonoses, such as Bird flu, Ebola hemorrhagic fever, Hantavirus infection, Nipah virus disease, Rift Valley fever, Swine flu, West Nile fever, SARS, MERS, COVID-19 etc., have emerged from different parts of the world. The latest to the list is the “Monkey Pox”, which has recently been renamed as “Mpox” by WHO. The ongoing 2022 multi-country outbreak of monkeypox is the largest in history to occur outside of Africa. Monkeypox is an emerging zoonotic disease that for decades has been viewed as an infectious disease with significant epidemic potential because of the increasing occurrence of human outbreaks in recent years. With increasing case numbers being reported in the current outbreak, it is important for healthcare staff everywhere to update their knowledge of this zoonotic infection, including its prevention, clinical management, prophylaxis, and basics of infection control, to understand the broader implications of the current outbreak. We provide an overview of monkeypox virus infection to serve as a primer for healthcare staff who may encounter this condition in their practice

A randomized controlled behavioral intervention trial to improve medication adherence in adult stroke patients with prescription tailored Short Messaging Service (SMS)-SMS4Stroke study.

Background: The effectiveness of mobile technology to improve medication adherence via customized Short Messaging Service (SMS) reminders for stroke has not been tested in resource poor areas. We designed a randomized controlled trial to test the effectiveness of SMS on improving medication adherence in stroke survivors in Pakistan. Methods: This was a parallel group, assessor-blinded, randomized, controlled, superiority trial. Participants were centrally randomized in fixed block sizes. Adult participants on multiple medications with access to a cell phone and stroke at least 4 weeks from onset (Onset as defined by last seen normal) were eligible. The intervention group, in addition to usual care, received reminder SMS for 2 months that contained a) Personalized, prescription tailored daily medication reminder(s) b) Twice weekly health information SMS. The Health Belief Model and Social Cognitive theory were used to design the language and content of messages. Frontline SMS software was used for SMS delivery. Medication adherence was self-reported and measured on the validated Urdu version of Morisky Medication Adherence Questionnaire. Multiple linear regression was used to model the outcome against intervention and other covariates. Analysis was conducted by intention-to-treat principle. Results: Two hundred participants were enrolled. 38 participants were lost to follow-up. After 2 months, the mean medication score was 7.4 (95 % CI: 7.2–7.6) in the intervention group while 6.7 (95 % CI: 6.4–7.02) in the control group. The adjusted mean difference (Δ) was 0.54 (95 % CI: 0.22–0.85). The mean diastolic blood pressure in the intervention group was 2.6 mmHg (95 % CI; −5.5 to 0.15) lower compared to the usual care group. Conclusion: A short intervention of customized SMS can improve medication adherence and effect stroke risk factors like diastolic blood pressure in stroke survivors with complex medication regimens living in resource poor areas

Histatin peptides: Pharmacological functions and their applications in dentistry

YesThere are many human oral antimicrobial peptides responsible for playing important roles including maintenance, repairing of oral tissues (hard or soft) and defense against oral microbes. In this review we have highlighted the biochemistry, physiology and proteomics of human oral histatin peptides, secreted from parotid and submandibular salivary glands in human. The significance of these peptides includes capability for ionic binding that can kill fungal Candida albicans. They have histidine rich amino acid sequences (7–12 family members; corresponding to residues 12–24, 13–24, 12–25, 13–25, 5–11, and 5–12, respectively) for Histatin-3. However, Histatin-3 can be synthesized proteolytically from histatin 5 or 6. Due to their fungicidal response and high biocompatibility (little or no toxicity), these peptides can be considered as therapeutic agents with most probable applications for example, artificial saliva for denture wearers and salivary gland dysfunction conditions. The objectives of current article are to explore the human histatin peptides for its types, chemical and biological aspects. In addition, the potential for therapeutic bio-dental applications has been elaborated.King Saud Universit

A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems

Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks encountered by the deployed systems will not be limited to the original training context, and systems will instead need to adapt to novel distributions and tasks while deployed. This critical gap may be addressed through the development of "Lifelong Learning" systems that are capable of 1) Continuous Learning, 2) Transfer and Adaptation, and 3) Scalability. Unfortunately, efforts to improve these capabilities are typically treated as distinct areas of research that are assessed independently, without regard to the impact of each separate capability on other aspects of the system. We instead propose a holistic approach, using a suite of metrics and an evaluation framework to assess Lifelong Learning in a principled way that is agnostic to specific domains or system techniques. Through five case studies, we show that this suite of metrics can inform the development of varied and complex Lifelong Learning systems. We highlight how the proposed suite of metrics quantifies performance trade-offs present during Lifelong Learning system development - both the widely discussed Stability-Plasticity dilemma and the newly proposed relationship between Sample Efficient and Robust Learning. Further, we make recommendations for the formulation and use of metrics to guide the continuing development of Lifelong Learning systems and assess their progress in the future.Comment: To appear in Neural Network