National Forensic Sciences University

Background The β-adrenergic augmentation of cardiac contraction, by increasing the conductivity of L-type voltage-gated CaV1.2 channels, is of great physiological and pathophysiological importance. Stimulation of β-adrenergic receptors (βAR) activates protein kinase A (PKA) through separation of regulatory (PKAR) from catalytic (PKAC) subunits. Free PKAC phosphorylates the inhibitory protein Rad, leading to increased Ca²⁺ influx. In cardiomyocytes, the core subunit of CaV1.2, CaV1.2α1, exists in two forms: full-length or truncated (lacking the distal C-terminus (dCT)). Signaling efficiency is believed to emanate from protein interactions within multimolecular complexes, such as anchoring PKA (via PKAR) to CaV1.2α1 by A-kinase anchoring proteins (AKAPs). However, AKAPs are inessential for βAR regulation of CaV1.2 in heterologous models, and their role in cardiomyocytes also remains unclear. Results We show that PKAC interacts with CaV1.2α1 in heart and a heterologous model, independently of Rad, PKAR, or AKAPs. Studies with peptide array assays and purified recombinant proteins demonstrate direct binding of PKAC to two domains in CaV1.2α1-CT: the proximal and distal C-terminal regulatory domains (PCRD and DCRD), which also interact with each other. Data indicate both partial competition and possible simultaneous interaction of PCRD and DCRD with PKAC. The βAR regulation of CaV1.2α1 lacking dCT (which harbors DCRD) was preserved, but subtly altered, in a heterologous model, the Xenopus oocyte. Conclusions We discover direct interactions between PKAC and two domains in CaV1.2α1. We propose that these tripartite interactions, if present in vivo, may participate in organizing the multimolecular signaling complex and fine-tuning the βAR effect in cardiomyocytes.

This study introduces an innovative terahertz-based biosensor designed for the direct detection of dopamine. By leveraging surface plasmon resonance (SPR) principles, extensive computational electromagnetic simulations are conducted to optimize the sensor design across the 0.1–0.6 THz frequency spectrum. The proposed biosensor exhibits exceptional sensitivity to dopamine concentrations ranging from 10 to 0.001 ppm, corresponding to refractive indices between 1.256 and 1.309 RIU. The sensor’s performance is characterized by impressive metrics, including a peak sensitivity of 500 GHzRIU⁻¹, a figure of merit of 2.809 RIU⁻¹, and a detection limit of 0. 867RIU.To further enhance the sensor’s predictive capabilities, we have implemented a K-nearest neighbors (KNN) regression model. This machine learning approach is employed to forecast absorption values based on various structural parameters. The model demonstrates remarkable accuracy, achieving R² scores up to 1.0 across diverse test cases and K values. The proposed biosensor outperforms many existing sensors in terms of sensitivity and detection limit, showing significant potential for early diagnosis and monitoring of dopamine-related neurological conditions. By integrating advanced materials, innovative design, and machine learning techniques, the proposed approach represents a significant advancement in dopamine detection methodologies for clinical applications. The proposed biosensor demonstrates the potential to revolutionize the diagnosis and treatment of disorders such as Parkinson’s disease, schizophrenia, and attention deficit hyperactivity disorder (ADHD).

The growing issues with prescription drug misuse have required the development of advanced techniques like abuse-deterrent formulations (ADFs). In this abstract we have provided a comprehensive overview of these type of novel formulations and their potential impact on mitigating prescription drug misuse. ADFs is like in modifying the formulations so that it can become a challenge to misuse. Some of the examples, market products and researches are mentioned in this review like; physical and chemical barriers to prevent common abuse methods such as crushing, snorting, or injecting. By making it more tough to extract active ingredients or achieve euphoric effect, these formulations aim to deter misuse and reduce the potential for manipulation. Another innovation involves prodrugs, which require enzymatic conversion within the body to release the active drug, it will stay inactive in normal conditions which helps in prevention of misuse. We have included some combination formulations like incorporating opioid antagonists in conjunction with the API, have also increased traction. These formulations cut or block the euphoric effects of the medicine. Further advancements include specialized temper prof coating and matrix system to reduce physical manipulations. The application of ADFs has shown encouraging outcomes, including reduced abuse rates and drug diversion. However, challenges remain as determined individuals may still avoid these deterrents.

The selection of an appropriate STR allelic frequency database is the prerequisite for assessing the evidentiary value of DNA evidence. Four data sets comprising 50, 100, 200, and 500 samples were evaluated in 21 autosomal STR markers in the Indian and the Bahrain population. Allelic richness showed an increasing trend with the increase in sample size i.e., 193 and 201 (50 samples), 217 and 221 (100 samples), 255 and 238 (200 samples), and 292 and 285 (500 samples) in both the populations. TPOX and D13S317 markers did not show any increase in allele number, whereas SE33 markers showed the highest increase in both populations. With the increase in sample size, 70 (Bahrain population) and 100 (Indian population) alleles having < MAF were detected. Similarly, 37 and 47 previously undetected alleles could be detected when the sample size was increased from 50 to 500 in the Indian and Bahrain populations respectively. In the Indian population, Match probability, decreased with a 500-sample size, whereas, the PIC, PE, Heterozygosity, and PI increased with the increase in sample size. Further, database size did not show any statistical difference in the outcome of the Paternity Index value in the 50 paternity trio cases studied.

This study presents a highly sensitive sensor designed for the detection of low refractive index substances in the THz range. The sensor leverages a hybrid metasurface combined of graphene and silver nanostructures, taking advantage of the extraordinary optical properties of graphene and the plasmonic resonances of silver. By carefully engineering the geometric parameters of the sensor and optimizing the synergistic interactions between the graphene and plasmonic components, the proposed sensor achieves a sensitivity of 300 GHzRIU⁻¹, a figure of merit of 1.351 RIU⁻¹, and a detection limit of 0.608 RIU for refractive indices ranging from 1.34 to 1.39. The design features three resonator structures—Small Circular Resonator Design (SCRD), Square Split Ring Resonator Design (SSR), and Large Circular Resonator Design (LCRD)—strategically integrated to enhance performance. Additionally, the sensor demonstrates encoding capabilities, modelling a NOR gate with high transmittance efficiency. These results highlight the sensor’s potential for multifunctional applications in various fields like biomedical and environmental.

In the past two decades, targeted anti‐cancer therapeutics have achieved remarkable success due to their exceptional advantages of selectivity towards cancer cells and safety. Targeted small molecule anti‐cancer therapies persisted in many barriers; majorly poor response to drug therapy. Piperidine, a heterocyclic moiety, exceeds twenty instances of other pharmaceutical classes and natural compounds in the form of alkaloids effective in anti‐cancer treatment. The current review focuses on recent advancements, mainly from 2017–2023, of piperidine‐containing small molecule development as anti‐cancer agents. Total 10 piperidine containing anti‐cancer drugs have been approved by USFDA since 2017 to till date and around 15 small molecule anti‐cancer inhibitors containing piperidine scaffold which are in their early discovery phase have been reviewed which are classified according to their biological target. It highlights the structural contribution of piperidine ring towards the enhancement of activity or pharmacokinetic properties of diverse biological target‐specific anti‐cancer inhibitors of angiogenesis, EGFR, VEGFR, ALK, AKT1, topoisomerase, CDK2 etc. The role of the piperidine ring in enhancing potency, selectivity and bioavailability of novel molecules has been discussed. This review will be helpful to researchers, especially medicinal chemists, for the designing of piperidine‐containing potent drugs for specific biological targets for cancer.

A biological reduction method for silver nanoparticles was employed using Cassia alata extract from plant leaves, which functions as a reducing agent and the metallo‐surfactant [Co(dqn)2(C12H27N)2]³⁺ (dqn = dipyrido[3,2‐f:2′,3′‐h]‐quinoxaline; C12H27N)2 = dodecylamine) acting as both stabilizing and capping agent. The ratio of Ag nanoparticles (AgNPs) formation was adjusted to be equal to the amount of AgNO3, along with variations in the amount of plant leaf extract, the metallo‐surfactant, pH, surrounding temperature, and the length of interaction periods. High‐resolution transmission electron microscopy (HRTEM), field emission scanning electron microscopy (FE‐SEM), energy‐dispersive spectroscopy (EDS), and energy‐dispersive X‐ray analysis (EDAX) were used to confirm the formation of AgNPs. The infrared results indicate the presence of hydroxyl, amine, and carboxylate groups in the extract plays a crucial role in the reduction process. Additionally, the metallo‐surfactant acts as a capping agent for the silver nanoparticles, preventing agglomeration. By adjusting the acidity of the solution and the quantity of the additive metallo‐surface active agent utilized, the size of AgNPs can be precisely regulated. The relativistic effects observed in this metallo‐surfactant‐assisted silver nanoparticle demonstrate excellent reduction capabilities for nitro compounds, effective dye degradation, and mercury sensing applications.

This research presents a terahertz-based biosensor for high-precision salinity detection, employing a synergistic integration of graphene, gold, and silver in a metasurface configuration. The sensor exhibits exceptional performance characteristics within the 0.6–2 THz frequency range, demonstrating a maximum sensitivity of 571 GHzRIU⁻¹, quality factor of up to 6.107, and a figure of merit of 2.189 RIU⁻¹. Electromagnetic field distribution analysis demonstrates enhanced light-matter interactions, with peak performance observed at 1.6 THz. The investigation further explored the sensor's potential for multilevel data encoding, illustrating its versatility beyond conventional detection methods. Simulation results indicate the efficiency of the proposed sensor which surpasses some of the previous existing designs in terms of sensitivity among other performance parameters. A machine learning approach using random forest regression was employed to predict sensor responses, achieving coefficient of determination (R²) values ranging from 0.88 to 1.00 across multiple parametric studies. This research presents a promising platform for high-precision salinity sensing with potential applications in environmental monitoring, desalination processes, and aquaculture industries.

Background: Arsenic (As), a very toxic metalloid, presents significant health hazards from multiple environmental exposures, including the inhalation of arsenic-laden tobacco smoke. This pertains to the accumulation of arsenic in combustible tobacco and the related health hazards for smokers and anyone exposed to second hand smoke. Inorganic arsenic, the predominant substance in tobacco, is converted into less harmful metabolites. Nonetheless, the methylation process in smokers is suboptimal, resulting in increased concentrations of harmful arsenic compounds. Methodology: Atomic Absorption Spectroscopy with a Vapor Generator Assembly (AAS-VGA) was utilized to assess arsenic level in tobacco, owing to its superior sensitivity and cost-effectiveness. The process entailed closed vessel digestion of tobacco samples using Microwave Digestion System (MDS-10) and after that the concentration of As was analyzed. Result: The findings revealed elevated arsenic concentrations in ppm, yet no threshold for tobacco as such by WHO or any organization. This elevates the danger of developing arsenic-related health issues, such as lung cancer, cardiovascular disease, and other chronic ailments, to not only to active smokers but also to passive smokers. It is a potential cause of indoor pollution as well. Conclusion: It underscores the need for more stringent public health measures to diminish arsenic exposure from smokable tobacco, while promoting the implementation of advanced detection techniques such as AAS-VGA for efficient monitoring and reduction of contamination.

Bone age estimation (BAE) is based on skeletal maturity and degenerative process of the skeleton. The clinical importance of BAE is in understanding the pediatric and growth-related disorders; whereas medicolegally it is important in determining criminal responsibility and establishing identification. Artificial Intelligence (AI) has been used in the field of the field of medicine and specifically in diagnostics using medical images. AI can greatly benefit the BAE techniques by decreasing the intra observer and inter observer variability as well as by reducing the analytical time. The AI techniques rely on object identification, feature extraction and segregation. Bone age assessment is the classical example where the concepts of AI such as object recognition and segregation can be used effectively. The paper describes various AI based algorithms developed for the purpose of radiologic BAE and the performances of the models. In the current paper we have also carried out qualitative analysis using Strength, Weakness, Opportunities and Challenges (SWOC) to examine critical factors that contribute to the application of AI in BAE. To best of our knowledge, the SWOC analysis is being carried out for the first time to assess the applicability of AI in BAE. Based on the SWOC analysis we have provided strategies for successful implementation of AI in BAE in forensic and medicolegal context.

The development of highly sensitive sensors for detecting alcohol compounds is crucial across diverse sectors, including healthcare, automotive safety, and law enforcement. This study presents a novel graphene-based sensor integrated with gold nanostructures for the efficient detection of alcohol compounds in the terahertz frequency range. Three distinct configurations of graphene and gold were investigated to optimize sensor performance. Finite element simulations were employed to assess the sensor’s response to varying refractive indices, corresponding to different alcohol compounds. The sensor demonstrated exceptional performance, exhibiting a remarkable sensitivity of 20,400 GHzRIU⁻¹, a figure of merit of 120.71 RIU⁻¹, and a detection limit of 0.006 RIU. Electric field analysis demonstrated a strong sensor-wave interactions in the terahertz regime, while two-bit encoding capabilities were achieved through modulation of graphene’s chemical potential. Compared to existing technologies, the proposed sensor exhibits superior sensitivity, holding significant promise for rapid, accurate, and non-invasive alcohol detection. Potential applications span healthcare, law enforcement, and public safety domains.

This study reveals the fabrication of a gas sensor with a PEDOT:PSS/graphene ink composite as an active layer on glossy paper. The glossy paper was chosen as the substrate material due to its low cost and easy availability. PEDOT:PSS/graphene ink was synthesized by simple mixing of PEDOT:PSS and graphene solution in the presence of distilled water, ethanol, glycerol, and diethylene glycol and was then sonicated and stirred at room temperature and characterized by FTIR, UV, XRD, AFM, and SEM. The sensitivity of the gas sensors towards acetonitrile, propanol, butanol, benzene, methanol, and ammonia analytes was investigated by measuring the change in resistance using a conventional multimeter at room temperature. The results exhibited that the composite’s response to ammonia change is stable and can measure concentration were the results also indicate that the sensors show promising responses with ± 1% reading error with a high response percentage.

Clinical chemistry is a multidisciplinary field in medical sciences that concentrates on key qualitative and quantitative tests of critical analytes or markers in bodily fluids and tissues. It employs advanced analytical tools and techniques, along with specialized instruments, to carry out these tests. This interdisciplinary domain incorporates knowledge from toxicology, medicine, biology, chemistry, biomedical engineering, informatics, and other applied sciences, holding direct relevance to both plant and animal life. The hepatic system, responsible for metabolism and excretion, plays a key role in managing toxicants, substances, or chemicals that may cause harm through adverse effects or toxicity. Hepatotoxicants are chemicals or metabolites that can lead to liver injury, often resulting from biotransformation processes. Carcinogenicity, the ability to cause cancer, is a critical concern, with scientists assessing its risk through studies and regulatory bodies relying on data to guide cancer prevention and treatment. Toxicity denotes a substance’s harmful potential, affecting various organisms and cell types, leading to hepatotoxicity, nephrotoxicity, or cytotoxicity. Toxicity is dose dependent, varying with age, sex, and species. The Drug Toxicity Index (DTI) predicts clinical outcomes with insights beyond traditional dose–response. Tackling toxicity is crucial for ecosystem health and addressing environmental challenges.

Protein detection is essential across diverse biomedical and biochemical disciplines, including disease diagnostics, pharmaceutical research, and environmental monitoring. Precise and efficient detection methodologies are critical for explaining complex biological processes and identifying biomarkers associated with various health conditions. This study presents the development and evaluation of an advanced terahertz biosensor designed for protein detection, utilizing graphene metasurfaces combined with surface plasmon resonance (SPR) to achieve high sensitivity. The sensor design incorporates a circular ring resonator and rectangular resonators on a silica substrate, with a graphene layer serving as the active sensing element. Finite element simulations are conducted to optimize the sensor’s geometric and material parameters. The optimized sensor design demonstrates impressive performance characteristics, achieving an optimal sensitivity of 508 GHzRIU⁻¹ and a quality factor of 5.089. Further analysis reveals a high figure of merit (11.293 RIU⁻¹), low detection limit (0.607), and strong signal-to-noise ratio (0.022). Additionally, the sensor exhibits potential for use in 2-bit encoding applications. A locally weighted linear regression model is leveraged to analyze and predict the sensor’s performance across various parameter combinations, achieving R² scores of up to 100%. The proposed biosensor shows promise for diverse applications, including enhancing medical diagnostics, ensuring food safety, and monitoring environmental factors.

Acriflavine (Af) and Rhodamine B (RB), two laser dyes, were tested for Fluorescence Resonance Energy Transfer (FRET). It was seen that the energy transfer efficiency from Af to RB is sensitive to the presence of Lead in clay dispersion. In the presence of Pb+ 2 ions, the FRET efficiency of the dye pair decreases up to 47.2% in clay dispersion. We can build a photo-regulated molecular logic NOT gate using this characteristic. The existence of Lead in the test water can be realized by molecular logic gate.

This work presents the design and characterization of a highly sensitive biosensor based on a metasurface architecture that integrates graphene and gold nanostructures. The sensor incorporates a combination of circular, circular ring, and rectangular resonator elements. Through comprehensive numerical simulations and optimization techniques, the geometrical parameters of the sensor hare fine-tuned to achieve optimal performance. The proposed sensor demonstrates a remarkable maximum sensitivity of 200 GHz/refractive index unit (GHz/RIU) and an impressively low detection limit of 0.10285 RIU across a wide refractive index range of 1.33 to 1.4 RIU. This exceptional sensitivity enables the sensor to detect minute variations in analyte concentration with high precision, making it a promising candidate for various biosensing applications. Furthermore, the sensor exhibits an optimal quality factor of 9.09259, further enhancing its capability to resolve small changes in the refractive index. In addition to its biosensing capabilities, the transmittance characteristics observed across various frequency ranges highlight the sensor’s potential for two-bit encoding applications, expanding its utility beyond biochemical sensing. The exceptional sensitivity, low detection limits, and encoding capabilities of the proposed graphene/gold metasurface sensor position it as a highly versatile and promising tool for early disease detection, environmental monitoring, and a wide range of other applications.