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Background: With a widespread distribution throughout Africa and a plethora of traditional uses, both medicinal and non-medical, Kigelia africana is a symbol of African herbal medicine. Objective: The main aim of the study is to identified the phytoconstituents by FTIR and LCMS analysis and elaborate the antioxidant activity. Method: The extraction and fractionation processes were performed based on the polarity of the solvents. Additionally, FTIR and LCMS profiling were conducted using standard methods. The DPPH scavenging assay was employed to assess the antioxidant activity. Results: The Soxhlet extract and maceration extract were determined to have extractive values of 9% w/w and 8.4% respectively. The Total flavonoid content was found to be highest in the Soxhlet extraction, with a value of 6.4±0.173mg/QE of dry weight of extract. The presence of various functional groups in the extracts was confirmed by FTIR spectroscopy, indicating the presence of specific chemical bonds. Based on LCMS, thirty-eight compounds were identified in the maceration and soxhlet extraction. During the extraction process, it was observed that the Soxhlet process exhibited the highest antioxidant properties, with IC50 values of 14.1582 mg/mL. Conclusion: Based on the study's findings, it can be said that Kigelia africana holds promise asa herb for a number of different medical conditions.

Liquid crystal monomers (LCMs) are used widely in liquid crystal displays (LCDs), which are dramatically changing the world due to the provision of convenient communication. However, there are essentially no published reports on the fate and/or effects of LCMs in the environment. Of 362 currently produced LCMs, 87 were identified as persistent and bioaccumulative (P&B) chemicals, which indicated that these chemicals would exhibit resistance to degradation and exhibit mobility after entering the environment. Following exposure to mixtures of LCM collected from 6 LCD devices, significant modulation of 5 genes, CYP1A4, PDK4, FGF19, LBFABP, and THRSP, was observed in vitro. Modulation of expressions of mRNAs coding for these genes has frequently been reported for toxic (T) persistent organic pollutants (POPs). In LCM mixtures, 33 individual LCMs were identified by use of mass spectrometry and screened for in 53 samples of dust from indoor environments. LCMs were detectable in 47% of analyzed samples, and 17 of the 33 LCMs were detectable in at least 1 sample of dust. Based on chemical properties, including P&B&T of LCMs and their ubiquitous detection in dust samples, the initial screening information suggests a need for studies to determine status and trends in concentrations of LCMs in various environmental matrices as well as tissues of humans and wildlife. There is also a need for more comprehensive in vivo studies to determine toxic effects and potencies of LCMs during chronic, sublethal exposures.

Background The king cobra ( Ophiophagus hannah ) is widely distributed throughout many parts of Asia. This study aims to investigate the complexity of Malaysian Ophiophagus hannah (MOh) venom for a better understanding of king cobra venom variation and its envenoming pathophysiology. The venom gland transcriptome was investigated using the Illumina HiSeq™ platform, while the venom proteome was profiled by 1D-SDS-PAGE-nano-ESI-LCMS/MS. Results Transcriptomic results reveal high redundancy of toxin transcripts (3357.36 FPKM/transcript) despite small cluster numbers, implying gene duplication and diversification within restricted protein families. Among the 23 toxin families identified, three-finger toxins (3FTxs) and snake-venom metalloproteases (SVMPs) have the most diverse isoforms. These 2 toxin families are also the most abundantly transcribed, followed in descending order by phospholipases A 2 (PLA 2 s), cysteine-rich secretory proteins (CRISPs), Kunitz-type inhibitors (KUNs), and L-amino acid oxidases (LAAOs). Seventeen toxin families exhibited low mRNA expression, including hyaluronidase, DPP-IV and 5’-nucleotidase that were not previously reported in the venom-gland transcriptome of a Balinese O. hannah . On the other hand, the MOh proteome includes 3FTxs, the most abundantly expressed proteins in the venom (43 % toxin sbundance). Within this toxin family, there are 6 long-chain, 5 short-chain and 2 non-conventional 3FTx. Neurotoxins comprise the major 3FTxs in the MOh venom, consistent with rapid neuromuscular paralysis reported in systemic envenoming. The presence of toxic enzymes such as LAAOs, SVMPs and PLA 2 would explain tissue inflammation and necrotising destruction in local envenoming. Dissimilarities in the subtypes and sequences between the neurotoxins of MOh and Naja kaouthia (monocled cobra) are in agreement with the poor cross-neutralization activity of N. kaouthia antivenom used against MOh venom. Besides, the presence of cobra venom factor, nerve growth factors, phosphodiesterase, 5’-nucleotidase, and DPP-IV in the venom proteome suggests its probable hypotensive action in subduing prey. Conclusion This study reports the diversity and abundance of toxins in the venom of the Malaysian king cobra (MOh). The results correlate with the pathophysiological actions of MOh venom, and dispute the use of Naja cobra antivenoms to treat MOh envenomation. The findings also provide a deeper insight into venom variations due to geography, which is crucial for the development of a useful pan-regional antivenom.

Phytohormones are critical regulators of plant growth, development, and stress responses. Despite advancements in analytical techniques, profiling multiple phytohormones across various plant matrices using a standardized approach remains underexplored. This study presents a unified LC-MS/MS analytical platform, employing consistent chromatographic and mass spectrometric conditions in combination with tailored matrix-specific extraction procedures, to profile and quantify key phytohormones. This includes abscisic acid (ABA), salicylic acid (SA), gibberellic acid (GA), and indole-3-acetic acid (IAA), across five plant matrices of significant agricultural and medicinal value. The method was validated for sensitivity, reproducibility, and matrix adaptability, demonstrating robust performance in profiling phytohormones from these diverse species. The results revealed distinct phytohormonal profiles, reflecting species-specific physiological adaptations to environmental conditions. For instance, cardamom exhibited high levels of SA and ABA, associated with stress responses in arid climates, while aloe vera showed lower phytohormone levels, indicative of its drought tolerance. Statistical analyses confirmed significant variation in hormone concentrations across the matrices, emphasizing the role of both genetic and environmental factors. This unified LC-MS/MS platform offers a comprehensive approach to understanding phytohormone distribution and dynamics, with implications for improving agricultural practices, crop resilience, and the development of functional foods and nutraceuticals. The findings contribute to the broader understanding of plant physiology and offer practical applications in sustainable agriculture, particularly in regions with significant agricultural and medicinal crop production.

Within the electronic design automation (EDA) domain, artificial intelligence (AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding, overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level (RTL) designs, circuit netlists, and physical layouts. We champion the creation of large circuit models (LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area (PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems’ capabilities.

Gut microbiota and their metabolic products are increasingly being recognized as important modulators of human health. The fecal metabolome provides a functional readout of the interactions between human metabolism and the gut microbiota in health and disease. Due to the high complexity of the fecal matrix, sample preparation often introduces technical variation, which must be minimized to accurately detect and quantify gut bacterial metabolites. Here, we tested six different representative extraction methods (single-phase and liquid–liquid extractions) and compared differences due to fecal amount, extraction solvent type and solvent pH. Our results indicate that a minimum fecal (wet) amount of 0.50 g is needed to accurately represent the complex texture of feces. The MTBE method (MTBE/methanol/water, 3.6/2.8/3.5, v/v/v) outperformed the other extraction methods, reflected by the highest extraction efficiency for 11 different classes of compounds, the highest number of extracted features (97% of the total identified features in different extracts), repeatability (CV < 35%) and extraction recovery (≥70%). Importantly, optimization of the solvent volume of each step to the initial dried fecal material (µL/mg feces) offers a major step towards standardization, which enables confident assessment of the contributions of gut bacterial metabolites to human health.

Background: Utpalashatphala ghrita (USG) is a traditional ayurvedic medicine containing piperine as its main chemical constituent responsible for the activity. Murchita is an ayurvedic process to detoxify and purify the lipids (ghee, oil). It involves heating ghee with specific ayurvedic ingredients for a specified duration and temperature. It is essential to understand the stability of piperine during and after the murchita process. Objective: The objective of this study was to develop and validate an LCMS method to assess the stability of piperine after the murchita process. Method: LCMS system with electrospray ionization and ion-trap as the analyser was used to estimate the piperine content. Analysis was carried out in the multiple reaction monitoring (MRM) mode. Chromatographic mobile phase composed of a mixture of 55 % formic acid (0.1 %) in Milli-Q water (pH 3) and 45 % methanol. The LC-MS method was validated as per ICH Q2 (R2) guidelines. Stability of ghrita was assessed at various stability conditions. Result: The developed LCMS method was accurate, precise and linear over a range of 0.5–32 μg/mL. LOQ of the method was 125 ng/mL and the run time was 10 min. Utpalashatphala ghrita (USG) and Murchita- Utpalashatphala ghrita (M-USG) were prepared as specified under Bhaishajya Ratnavali. Our study revealed that the murchita process degraded piperine by 26 %. However, the stability of piperine was found to be better in the murchita ghrita (M -USG), compared to the unprocessed USG. Conclusion: Study effectively demonstrated that the murchita process enhanced the long-term stability of piperine.

Psoralea corylifolia is a well-known edible medicinal plant extensively used in traditional Chinese medicine. In this study, the methanolic extract of P. corylifolia was initially screened for its antioxidant capacity using multiple in vitro assays, including 2,2-Diphenyl-1-picrylhydrazyl (DPPH), Ferric Reducing Antioxidant Power (FRAP), 2,2′-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), and Oxygen Radical Absorbance Capacity (ORAC) assays. Additionally, Total Phenolic Content (TPC) and Total Flavonoid Content (TFC) values were calculated. To identify the key metabolites responsible for these effects, an LC-QTOF-MS/MS-based metabolite profiling approach was employed, resulting in the identification of 41 compounds. Among them, 18 compounds were selected based on drug-likeness and bioavailability scores, using multiple online databases. To explore their potential mechanisms of action, a network pharmacology approach was employed. A total of 83 of 86 genes overlapped with antioxidant-related disease genes, which were subsequently subjected to protein-protein interaction (PPI), gene ontology, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The top-ranked genes were TDP1, APEX1, TOP2A, CTSD, and KLF5. Finally, the most promising compounds and their target genes were subjected to molecular docking and simulation studies to validate the antioxidant potential of P. corylifolia .

Eleusine indica (L.) Gaertn is a perennial herb belonging to the Poaceae family. As the only species of Eleusine found abundantly in Malaysia, it is locally known as “rumput sambau” and has been traditionally used to treat various ailments including pain relief from vaginal bleeding, hastening the placenta delivery after childbirth, asthma, hemorrhoids, urinary infection, fever, and as a tonic for flu-related symptoms. A diverse array of biological activities have been reported for the plant, such as antimicrobial, cytotoxic, anticonvulsant, anti-inflammatory, analgesic, antipyretic, and hepatoprotective action. Despite many reports on its traditional uses and biological activities, limited chemical databases are available for the plant. Thus, the aims of this study were to annotate and identify the phytochemical constituents in the methanolic extract of E. indica through tandem LCMS-based analysis techniques using MZmine, GNPS, Compound Discoverer, and SIRIUS platforms. This technique managed to identify a total of 65 phytochemicals in the extract, comprising primary and secondary metabolites, and was verified by the isolation of one of the identified phytochemicals. The structural elucidation mainly using 1D and 2D NMR as well as comparison with values in the literature confirms the isolated phytochemical to be a 3-OH anomer of loliolide, a benzofuran-type of compound, which consequently increases the level of confidence in the applied technique. The research describes a useful method for the fast and simultaneous identification of phytochemicals in E. indica, contributing to the study of the chemical properties of the genus and family.

Life as we know it depends on peptide and nucleic acid polymers built from a limited set of backbone residues, yet planetary environments beyond Earth motivate consideration of alternative chemical frameworks for genetic- and protein-like polymers. In this context, we synthesize four azatide dipeptide analogs (Alaa-Glya (1), Glya-Alaa (2), Glya-Glya (3), and Alaa-Alaa (4)) as candidate backbone motifs for non-standard biologically relevant polymers. We then systematically assess their stability and reactivity in 98% w/w sulfuric acid, a solvent relevant to Venusian cloud chemistry. We assess the stability of the azatides via 1H and 13C NMR spectroscopy supported with ELSD-LCMS. We monitor the stability of the compounds over periods from hours to two weeks at room temperature and at elevated temperatures (50–80 °C). All four azatides readily dissolve in 98% w/w D2SO4 and are generally stable at room temperature. Glya-Alaa (2) shows no detectable degradation over a two-week incubation in 98% w/w sulfuric acid. The other three azatide analogs display only minor decomposition. ELSD-LCMS measurements qualitatively confirm the NMR results, revealing only minor-to-moderate loss of parent compounds after two weeks at room temperature. At higher temperatures, representative of the lower Venusian cloud deck, the stability of the azatides decreases dramatically. All four compounds undergo significant decomposition at 50 °C and completely degrade within one to two weeks at 80 °C. Our findings indicate that azatides, despite being generally stable in concentrated sulfuric acid at room temperature, lack the thermal stability that might be required to serve as viable backbone motifs for biological polymers in environments spanning the full temperature range of Venusian clouds.