Pakistan Academy of Sciences

Heroin abuse poses a significant public health and law enforcement challenge globally, with concerns in Pakistan due to the prevalence of illicit street heroin and limited data on its composition. This study analyzed 706 heroin samples seized between 2017 and 2022 using gas chromatography-mass spectrometry (GC-MS) and Fourier transform infrared spectroscopy (FTIR) to determine their chemical composition. The results revealed that street heroin in Pakistan is extensively adulterated with a variety of pharmaceutical agents, including acetaminophen, caffeine, diazepam, and dextromethorphan. Pareto analysis demonstrated that a small subset of adulterants accounted for most of the street samples, with caffeine, acetaminophen, and diazepam present in nearly 90% of analyzed samples. Impurities from incomplete synthesis, particularly 6-monoacetylmorphine (97%) and acetylcodeine (95%), were also widespread. Some samples contained only adulterants, lacking heroin entirely. The widespread adulteration and presence of pharmacologically active impurities significantly increase the risk of toxicity and complicate clinical management of overdoses. These findings highlight the urgent need for drug monitoring and regulation, as well as targeted public health interventions. The comprehensive chemical characterization of street heroin provides valuable insights for forensic investigations, policy development, and epidemiological surveillance to address the evolving risks associated with illicit heroin use in Pakistan.

Artificial intelligence (AI) is transforming drug discovery by enabling the rapid identification of existing drugs with potential anti-cancer properties, a process known as drug repurposing. This approach offers a cost-effective and time-efficient alternative to traditional drug development, particularly in oncology, where the need for novel therapies is urgent. AI-driven methods, including machine learning (ML) and deep learning (DL), analyze vast datasets to uncover hidden drug-disease relationships, predict drug efficacy, and optimize therapeutic combinations. This letter highlights the transformative potential of AI in drug repurposing for cancer therapies, supported by successful examples from recent research. We also discuss the challenges and ethical considerations of integrating AI into drug repurposing efforts, emphasizing the need for robust validation and regulatory oversight to ensure patient safety and efficacy.

The novelty of this work lies in the development of a bifunctional acid-base catalyst comprising tungsten oxide (WO3) supported on mesoporous MCM-41 and impregnated with alkaline earth metal oxides (Mg, Ca, Sr, Ba), which enables simultaneous esterification and transesterification for biodiesel production. The acidic and basic properties of the catalysts were quantitatively assessed through potentiometric titration, confirming the presence of both acid and basic sites, which are essential for the concurrent esterification of free fatty acids (FFAs) and transesterification of triglycerides. This bifunctionality is particularly advantageous for feedstocks with high FFA content, such as waste cooking oil, addressing a key challenge in biodiesel synthesis. The SrO-based catalyst demonstrated exceptional performance, achieving yields of 96 % for corn oil and 93 % for waste cooking oil, with minimal yield differences of 3 % attributed to the latter's impurities and higher FFA content. The study also provides detailed optimization of reaction conditions, revealing that waste cooking oil requires slightly harsher conditions (100 °C, 6 h, 20 mg catalyst) compared to corn oil (80 °C, 5 h, 10 mg catalyst), which is consistent with its complex composition. Comprehensive characterization (PXRD, SEM-EDX, BET/BJH) and validation through 1H NMR spectroscopy (yields of 92 % and 91 % for corn and waste cooking oil, respectively) confirm the reliability of the results. Moreover, the biodiesel's physicochemical characteristics were examined thoroughly and contrasted with the ASTM biodiesel requirements. The outcomes demonstrated that the generated biodiesel's characteristics met the requirements of international standards.

Type-2 diabetes,characterized by aberrant insulin secretion orincreased hepatic glucose synthesis, accounts for approximately 90%of diabetes issues. This study explores current molecular and cellularadvances related to T2D pathogenesis. Recent research on T2D aboutintracellular signaling cascades, inflammation, autophagy, genetics,and epigenetic changes is explained discretely. The present reviewdiscusses the available antidiabetic therapeutic strategies currentlycommercialized as well as their limitations that need to be acknowledged.Specifically, the review discusses how nanotechnology-based approachesnullify conventional antidiabetic therapeutics’ inadequacyand heterogeneous nanoparticulate systems have been explored in diabetesresearch, and they’re also listed in a tabular format. Furthermore,the research offers many strategic hypotheses as a potential applicationof nanotechnology in the future to improve the management of type-2diabetes by developing a targeted nanodelivery system. In particular,attempts have been made to develop new treatment approaches basedon nanotechnology that take advantage of autophagy and inflammasometarget sites that have been previously identified. An explanationof how a smart targeted nano delivery system can inhibit the Wnt signalingpathway (inhibiting Gsk-3β), inhibit the inflammasome (inhibitingNLRP3), and activate autophagy target points (protecting the Atg3/Atg7complex from oxidative stress) is provided through graphical description,which may mitigate the severity of type-2 diabetes.

Following a bio-assay guided fractionation and chromatographic separations a known compound arborside C pentaacetate was isolated. Immunomodulatory effects of arborside C pentaacetate were revealed by inhibition of NO, pro-inflammatory mediators, IL-6, TNF-α, and NF-κB at translational level in an in vitro study. The docking results revealed that arborside C pentaacetate bind strongly to the target protein with the docking score of −10.38 kcal/mol. The compound was non-toxic on normal human fibroblast (BJ) and THP-1 cells and, could be a potential therapeutic agent in inflammation driven diseases.

The selective and efficient electrochemical transformation of carbon dioxide (CO2) into valuable chemical products remains challenging in modern catalysis. Among various electrocatalysts, silver (Ag) has emerged as a highly promising candidate for CO2-to-CO conversion under ambient conditions, attributed to its superior catalytic performance, remarkable selectivity, and thermodynamically favorable reaction pathway. In this study, we introduce a series of Ag/CuxO/C electrocatalysts derived from MOF (HKUST-1), with the optimized Ag/CuxO/C4 demonstrating exceptional performance. At −0.70 VRHE, the Ag/CuxO/C4 catalyst demonstrates a low overpotential (η) of 245 mV, a high partial current density (jCO) of 41 mA cm–2, and a Tafel slope of 49 mV dec–1, indicating efficient charge transfer and favorable reaction kinetics. These attributes collectively enabled an outstanding CO Faradaic efficiency (FECO%) of ≈95%, underscoring the catalyst’s exceptional selectivity and performance. The catalyst exhibited outstanding durability, maintaining its high FECO over 10 h of operation at various applied potentials without significant current loss. The qualitative and quantitative testing of the observed gaseous and liquid products using GC-MS, GC-TCD, and GC-FID confirmed the exceptional selectivity of Ag/CuxO/C4 for CO production. The PdCl2 strip method further validated the presence of CO, highlighting the catalyst’s specificity. This research highlights the potential of Ag/CuxO/C4 composite materials, characterized by controlled particle size and low noble metal loading, as highly efficient and durable catalysts for electrocatalytic CO2-to-CO.