Autoregressive Modeling and Prediction of the Activity of Antihypertensive Peptides

Naturally derived bioactive peptides with antihypertensive activities serve as promising alternatives to pharmaceutical drugs. There are few relevant reports on the mapping relationship between the EC50 value of antihypertensive peptide activity (AHTPA-EC50) and its corresponding amino acid sequence (AAS) at present. In this paper, we have constructed two group series based on sorting natural logarithm of AHTPA-EC50 or sorting its corresponding AAS encoding number. One group possesses two series, and we find that there must be a random number series in any group series. The random number series manifests fractal characteristics, and the constructed series of sorting natural logarithm of AHTPA-EC50 shows good autocorrelation characteristics. Therefore, two non-linear autoregressive models with exogenous input (NARXs) were established to describe the two series. A prediction method is further designed for AHTPA-EC50 prediction based on the proposed model. Two dynamic neural networks for NARXs (NARXNNs) are designed to verify the two series characteristics. Dipeptides and tripeptides are used to verify the proposed prediction method. The results show that the mean square error (MSE) of prediction is about 0.5589 for AHTPA-EC50 prediction when the classification of AAS is correct. The proposed method provides a solution for AHTPA-EC50 prediction.

Predicting Ruthenium Catalysed Hydrogenation of Esters using Machine Learning

Catalytic hydrogenation of esters is a sustainable approach for the production of fine chemicals, and pharmaceutical drugs. However, the efficiency and cost of catalysts are often the bottlenecks in the commercialization of such technologies. The conventional approach of catalyst discovery is based on empiricism that makes the discovery process time-consuming and expensive. There is an urgent need to develop effective approaches to discover efficient catalysts for hydrogenation reactions. We demonstrate here the approach of machine learning for the prediction of out-comes for the catalytic hydrogenation of esters. Our models can predict the reaction yields with high mean accuracies of up to 91% (test set) and suggest that the use of certain chemical descriptors selectively can result in a more accurate model. Furthermore, cata-lysts and some of their corresponding descriptors can also be pre-dicted with mean accuracies of 85%, and >90%, respectively.

Delta-8-THC: Delta-9-THC’s nicer younger sibling?

Background Products containing delta-8-THC became widely available in most of the USA following the 2018 Farm Bill and by late 2020 were core products of hemp processing companies, especially where delta-9-THC use remained illegal or required medical authorization. Research on experiences with delta-8-THC is scarce, some state governments have prohibited it because of this lack of knowledge. Objective We conducted an exploratory study addressing a broad range of issues regarding delta-8-THC to inform policy discussions and provide directions for future systematic research. Methods We developed an online survey for delta-8-THC consumers, including qualities of delta-8-THC experiences, comparisons with delta-9-THC, and open-ended feedback. The survey included quantitative and qualitative aspects to provide a rich description and content for future hypothesis testing. Invitations to participate were distributed by a manufacturer of delta-8-THC products via social media accounts, email contact list, and the Delta8 Reddit.com discussion board. Participants (N = 521) mostly identified as White/European American (90%) and male (57%). Pairwise t tests compared delta-8-THC effect rating items; one-sample t tests examined responses to delta-9-THC comparison items. Results Most delta-8-THC users experienced a lot or a great deal of relaxation (71%); euphoria (68%) and pain relief (55%); a moderate amount or a lot of cognitive distortions such as difficulty concentrating (81%), difficulties with short-term memory (80%), and alerted sense of time (74%); and did not experience anxiety (74%) or paranoia (83%). Participants generally compared delta-8-THC favorably with both delta-9-THC and pharmaceutical drugs, with most participants reporting substitution for delta-9-THC (57%) and pharmaceutical drugs (59%). Participant concerns regarding delta-8-THC were generally focused on continued legal access. Conclusions Delta-8-THC may provide much of the experiential benefits of delta-9-THC with lesser adverse effects. Future systematic research is needed to confirm participant reports, although these studies are hindered by the legal statuses of both delta-8-THC and delta-9-THC. Cross-sector collaborations among academics, government officials, and representatives from the cannabis industry may accelerate the generation of knowledge regarding delta-8-THC and other cannabinoids. A strength of this study is that it is the first large survey of delta-8 users, limitations include self-report data from a self-selected convenience sample.

Do COVID-19 Lock-Downs Affect Business Cycle? Analysis Using Energy Consumption Cycle Clock for Selected European Countries

On 11 March 2020, the WHO declared the COVID-19 epidemic to be a global pandemic. This was a consequence of the rapid increase in the number of people with positive test results, the increase in deaths due to COVID-19, and the lack of pharmaceutical drugs. Governments introduced national lockdowns, which have impacted both energy consumption and economies. The purpose of this paper is to answer the following question: do COVID-19 lockdowns affect the business cycle? We used the cycle clock approach to assess the magnitude of decrease in electricity consumption in the three waves of the epidemic, namely, April 2020, November 2021, and April 2021. Additionally, we checked the relation between energy consumption and GDP by means of spectral analysis. Results for selected 28 European countries confirm an impact of the introduced non-pharmaceutical interventions on both energy consumption and business cycle. The reduction of restrictions in subsequent pandemic waves increased electricity consumption, which suggests movement out of the economic recession.

Role of Social Media Promotion of Prescription Drugs on Patient Belief-system and Behaviour

In the current scenario, extremely little information exists on the uses, benefits, and limitations of social media for health communication among the patients and health professionals. Further, how it is affecting the patient belief system and behavior is even less studied, but it is emerging on the research horizon due to its growing significance in this digital age. This is a review article using a systematic approach. We performed a systematic literature search for papers that address social media–related challenges and opportunities for pharmaceutical drugs. It identifies the needs that propel patients to take recourse to SMPs; the benefits they derive from these and their limitations. This review article confirms that healthcare information provided by the social media sites has been found to be beneficial in many ways for the stakeholders and that it complements existing patient-physician interaction. However, it has limitations that need to be explored and understood to avoid ill consequences.

Development of Green Methods for the Determination of Elemental Impurities in Commercial Pharmaceutical Tablets

In this study, two methods based on the use of diluted acids were developed: microwave-assisted wet digestion (MAWD) and microwave-assisted ultraviolet digestion (MAWD-UV). These methods are evaluated for the digestion of oral pharmaceutical drugs and further determination of elemental impurities from classes 1 (As, Cd, Hg and Pb) and 2A (Co, Ni and V) by inductively coupled plasma optical emission spectrometry (ICP-OES). Commercial drugs for the treatment of type 2 diabetes are used. No prior comminution is performed. For MAWD, the optimized conditions were 2 mol L−1 or 3 mol L−1 HNO3, 1 mL of 50% H2O2 and a 45 min or 55 min irradiation program. For MAWD-UV, the condition using 1 mol L−1 HNO3, 1.6 mL of 50% H2O2 and a 55 min irradiation program enabled the digestion of all samples. In this way, efficient methods are proposed for the digestion of commercial pharmaceutical tablets for further determination of class 1 and 2A elemental impurities (ICH Q3D guidelines).

Pharmacological aspects & medicinal uses of Trigonella foenum-graecum: A Current Review

Globally a large number of people are affected by acute and chronic diseases resulting in high morbidity and mortality rate. A huge amount of pharmaceutical drugs are being manufactured on a daily basis to combat these diseases. But due to their high cost and deleterious effects, it becomes critically important to state emphasis on finding an alternative way to manage these long term conditions. Medicinal herbs could provide a good source of dietary supplement combined with existing therapies. Many scientific studies have demonstrated that medicinal plants and herbs have the potential for the treatment of many serious infections and many disorders. Out of these herbs, Fenugreek is recognized as an oldest herb with great medicinal potential. Fenugreek harbors many essential macronutrients and micronutrients along with trace elements. Numerous chemical constituents present in fenugreek highlights a variety of pharmacological activity such as anti-glycemic activity, anti-oxidant capacity, anti-inflammatory effects, hypocholesterolemic activity and many more. This article explores the diverse active compounds and potential pharmacological applications of Trigonella foenum-graecum also known as fenugreek. It also focuses on the medicinal significance and health impact of taking fenugreek in our day to day nutrition.

Glyceral Trinitrate: As Potential Corrosion Protector for Mild Steel in Acid Medium Along with Paint-coated Steel in a Saline Environment

The importance of mild steel lies in its industrial applications, and the fight against corrosion is very important from an ecological, economic, technical, and aesthetic view. The current study involves the use of pharmaceutical drugs namely GTN towards corrosion inhibiting reaction was examined by gravimetric and electrochemical approaches. From weight loss studies, maximum I.E (%) 94.04% reached for 60 mg/L concentration of GTN for 6 hrs immersion time. The Polarization measurements showed that the behaviour of GTN as mixed nature and surface assimilation of GTN at the superficial, such that water molecules are substituted at the solution-metal boundary. The corrosion resistance property of the studied inhibitor as coating was also evaluated in NaCl which shows better progress corrosion retardation property of coating in the saline medium. Theoretical calculations were employed using DFT to correlate with the experimental observations.

Manganese Catalysed Dehydrogenative Synthesis of Urea Derivatives and Polyureas

Urea derivatives are prevalent intermediates in the synthesis of resin precursors, dyes, agrochemicals, and pharmaceutical drugs. Furthermore, polyureas are useful plastics with applications in coating, adhesive, and biomedical industries and have a current annual market of USD 885 million. However, the conventional methods for the synthesis of urea derivatives and polyureas involve toxic reagents such as (di)isocyanates, phosgene, CO, and azides. We present here the synthesis of (poly)ureas using much less toxic reagents - (di)amines, and methanol via a catalytic dehydrogenative coupling process. The reaction is catalyzed by a pincer complex of an earth-abundant metal, manganese, and liberates H2 gas, valuable by itself, as the only by-product making the overall process atom-economic, and sustainable. A broad variety of symmetrical, and unsymmetrical urea derivatives and polyureas have been synthesized in moderate to quantitative yields using this catalytic protocol. Mechanistic insights have also been provided using experiments and DFT computation suggesting that the reaction proceeds via an isocyanate intermediate.