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Journal of Pharmaceutical Research and Integrated Medical Sciences

📢 Latest Update: New special issue call for papers on "Pharmaceutical Research and Integrated Medical Sciences" - Submit by March 31, 2026

📢 Latest Update: New special issue call for papers on "Pharmaceutical Research and Integrated Medical Sciences" - Submit by March 31, 2026

Volume 3, Issue 5 - 2026 (JPRIMS, Vol-3, Issue-05, May-2026)

Volume 3 Issue 5 Cover

Issue Details:

Volume 3 Issue 5
Published:Invalid Date

Editorial: JPRIMS, Vol-3, Issue-05, May-2026

Welcome to the 2026 issue of Journal of Pharmaceutical Research and Integrated Medical Sciences. This issue showcases the remarkable breadth and depth of contemporary research across multiple disciplines. From cutting-edge applications of machine learning in climate science to the revolutionary potential of quantum computing in drug discovery, our featured articles demonstrate the power of interdisciplinary collaboration in addressing global challenges.

We are particularly excited to present research that bridges traditional academic boundaries, reflecting our journal's commitment to fostering innovation through cross-disciplinary dialogue. The integration of artificial intelligence with environmental science, the application of blockchain technology to supply chain management, and the convergence of urban planning with smart city technologies exemplify the transformative potential of collaborative research.

As we continue to navigate an era of rapid technological advancement and global challenges, the research presented in this issue offers both insights and solutions that will shape our future. We thank our authors, reviewers, and editorial board members for their continued dedication to advancing knowledge and promoting scientific excellence.

Dr. Arpan Kumar Tripathi
Editor-in-Chief
Journal of Pharmaceutical Research and Integrated Medical Sciences

Articles in This Issue

Showing 21 of 21 articles
Research PaperID: jprims-00000244

Ethnobotanical Perspectives on Medicinal Plants Used in the Management of Arthritis: Traditional Knowledge, Pharmacological Evidence, and Future Therapeutic Potential

Radhika Gond Gond, Mateshwari Nandan Nandan, Alok Vishwakarma Vishwakarma, Ram Sahay Sahay, Abhishek Abhishek, Abhay Kumar Gupta Gupta

Arthritis is a chronic inflammatory disorder that affects millions of people worldwide, leading to pain, stiffness, and reduced mobility. Traditional medicinal plants have long been utilized as alternative treatments, particularly in rural and indigenous communities. This ethnobotanical review aims to document and analyse the medicinal plants historically used to treat arthritis, focusing on plant identification, preparation methods, administration techniques, and associated cultural knowledge. The study systematically reviews ethnobotanical literature and field surveys involving traditional healers, herbalists, and indigenous practitioners. Data collection methods include semi-structured interviews, focus group discussions, and field observations, with plant species identified through taxonomic classification and verified using existing botanical literature. Findings indicate that numerous plant species possess significant analgesic and anti-inflammatory properties, with leaves, roots, bark, and seeds commonly used in decoctions, infusions, poultices, and topical applications. Although many of these plants have been cited in scientific literature for their therapeutic potential, further pharmacological and phytochemical investigations are necessary to validate their efficacy and safety. The study underscores the importance of preserving indigenous knowledge and integrating ethnobotanical research into contemporary healthcare systems. Future research should focus on standardization, sustainable conservation of medicinal plants, and clinical trials to establish their role in arthritis treatment.

Type 2 Diabetes MellitusDapagliflozinCanagliflozinEmpagliflozinSGLT2 inhibitorsHbA1c+5 more
15,025 views
4,422 downloads

Contributors:

 Radhika Gond Gond
,
 Mateshwari Nandan Nandan
,
 Alok Vishwakarma Vishwakarma
,
 Ram Sahay Sahay
,
 Abhishek Abhishek
,
 Abhay Kumar Gupta Gupta
Research PaperID: jprims-00000245

A Comprehensive Review of Progress and Persistence in Neglected Tropical Diseases (NTDS): Next-Generation Diagnostics Integrating Animal and Environmental Strategies for NTD Control

Yash Srivastav Srivastav, Vikash Kumar Mehta Mehta, Shivani Singh Singh, Sonakshi Raj Raj

NTDs persist in animals’ populations because of complicated interactions between livestock and wildlife reservoirs, vectors, and the environment. The present review offers the in-depth analysis of the current developments and the current issues in the control of NTDs with particular attention to the animal-based data and environmental determinants. It outlines the importance of animal reservoirs in perpetuating transmission cycles and explores how ecological factors like climate variability, land-use alterations and the dynamics of vectors affect disease persistence. The review also analyzes the progress of next-generation diagnostics, such as molecular, biosensors, and environmental DNA (eDNA), which have contributed to a considerable enhancement in the accuracy of detection and surveillance. Nevertheless, constraints connected to field applicability, expensive nature, and disjointed surveillance systems remain a barrier to successful implementation. The results highlight the need to consider the incorporation of both animal health surveillance and environmental surveillance to improve early detection and control interventions. Moreover, review indicates important gaps in research such as the underrepresentation of wildlife reservoirs and the lack of scalable and cost-effective diagnostic tools. On the whole, it highlights the need to implement interdisciplinary and combined solutions to ensure sustainable and effective management of NTDs in animals.

indigenous knowledgephytochemical analysistraditional medicineanti-inflammatoryarthritis treatmentmedicinal plants+1 more
15,169 views
4,478 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Vikash Kumar Mehta Mehta
,
 Shivani Singh Singh
,
 Sonakshi Raj Raj
Research PaperID: jprims-00000246

Theranostic Liposomes: Dual-Function Nanocarriers for Drug Delivery and Disease Monitoring

Chetan S Dharne Dharne, Vinay Sagar Verma Verma, Aayush Yadav Yadav, Bhupendra Kumar Sahu Sahu, Govind Sharma Sharma

Theranostic liposomes represent a paradigm shift in precision nanomedicine by integrating therapeutic drug delivery with diagnostic imaging functionality into a single nanocarrier platform. These dual-function systems address long-standing limitations of conventional therapeutics and diagnostics by enabling simultaneous treatment and real-time monitoring of drug biodistribution, tissue accumulation, and therapeutic response. Structurally composed of phospholipid bilayers, liposomes can encapsulate diverse therapeutic agents—from small-molecule chemotherapeutics to macromolecules like proteins and nucleic acids—while co-loading imaging probes including fluorescent dyes, magnetic resonance imaging (MRI) contrast agents, computed tomography (CT) enhancers, and radionuclides for positron emission tomography (PET) or single-photon emission computed tomography (SPECT). Through rational design strategies including size optimization, PEGylation for prolonged circulation, ligand-mediated active targeting, and incorporation of stimuli-responsive lipids, theranostic liposomes achieve enhanced pharmacokinetics, selective tumor or tissue accumulation, and controlled release kinetics. Pharmacokinetically, these systems exploit the enhanced permeability and retention (EPR) effect for passive targeting and receptor-mediated endocytosis for active targeting, while multimodal imaging enables quantitative assessment of drug localization and therapeutic efficacy. Clinical applications span oncology, cardiovascular disease, neurological disorders, and infectious diseases—with theranostic platforms enabling personalized dosing adjustments, early prediction of therapeutic outcomes, and reduction of off-target toxicity. Despite remarkable potential, challenges including formulation stability, batch-to-batch reproducibility, cost-effective scale-up, and complex regulatory requirements demand continued innovation. Future developments emphasize smart, stimuli-responsive systems, artificial intelligence-driven optimization, biodegradable hybrid architectures, and personalized liposomal engineering. Collectively, theranostic liposomes embody the convergence of materials science, molecular pharmacology, and imaging technology—redefining precision medicine by seamlessly integrating diagnosis, therapy, and real-time disease monitoring into adaptive, patient-centric treatment paradigms.

One Health ApproachSurveillance SystemseDNAMolecular DiagnosticsVector DynamicsEnvironmental Factors+2 more
15,171 views
4,612 downloads

Contributors:

 Chetan S Dharne Dharne
,
 Vinay Sagar Verma Verma
,
 Aayush Yadav Yadav
,
 Bhupendra Kumar Sahu Sahu
,
 Govind Sharma Sharma
Research PaperID: jprims-00000247

Syphilis Infection, Clinical Synergies, Modern Diagnostic and Treatment Strategies, Epidemiological Impact: Review of Traditional and Reverse Screening Algorithms

Shivani Singh Singh, Yash Srivastav Srivastav, Saroj Kumar Kumar, Sonakshi Raj Raj

Syphilis is a chronic and multi-stage infectious disease caused by Treponema pallidum, which has a rapid spread, resistance to immune responses, and chronic infection. This review is a synthesis of animal evidence to study the pathogenesis, clinical synergies, diagnostic plans, treatment plans, and epidemiological implications of the disease. The use of animal models, especially rabbits, has been critical in understanding the interaction of the host and pathogen, development of lesions, and immunological reactions. This research indicates the relative performance of the traditional and reverse screening algorithm, which shows that reverse screening has a better sensitivity during both early and latent periods, whereas the traditional approach is useful in monitoring active infection. The development of molecular diagnostics, particularly PCR and immunoassays, has improved early diagnosis and evaluation of the disease, whereas penicillin remains the most effective treatment despite the emerging resistance issues in other treatments. Additionally, experimental epidemiological research adds to the knowledge on the dynamics and persistence of transmission. Nevertheless, animal model limitations and issues with vaccine development because of immune evasion remain a major problem. The review highlights the necessity of a better experimental model, combined diagnostic, and novel treatment and vaccine options to improve the management of the disease and future research outcomes.

NanomedicineDual-Function NanocarriersPrecision MedicineStimuli-Responsive SystemsBiodistributionPharmacokinetics+9 more
15,411 views
4,702 downloads

Contributors:

 Shivani Singh Singh
,
 Yash Srivastav Srivastav
,
 Saroj Kumar Kumar
,
 Sonakshi Raj Raj
Research PaperID: jprims-00000248

Advances in Nano-Immunotherapy: Pharmaceutical Formulation Strategies for Enhanced Immune Targeting

Sushmita Padhi Padhi, Vinay Sagar Verma Verma, Govind Sharma Sharma, Bhushan Lal Lal, Sanjay Gupta Gupta

Nano-immunotherapy leverages advanced nanocarrier systems to overcome limitations of conventional immunotherapies, providing precise immune modulation through targeted delivery of antigens, immunomodulators, and genetic material. Lipid-based, polymeric, inorganic, and hybrid nanocarriers enable controlled release, enhanced bioavailability, and site-specific immune activation, optimizing therapeutic efficacy while minimizing systemic toxicity. Pharmaceutical formulation strategies, including particle engineering, surface functionalization, and payload optimization, are critical to enhancing immune targeting and pharmacokinetics. Clinically, nano-immunotherapeutics have demonstrated remarkable success in vaccines, cancer immunotherapy, and genetic disease treatment, exemplified by mRNA-LNP COVID-19 vaccines and liposomal chemotherapies. Despite challenges in manufacturing, stability, and regulatory approval, emerging trends such as AI-driven design, personalized formulations, and integration with gene-editing technologies forecast a future of precision nano-immunotherapy with broad clinical impact.

Epidemiology.Antibiotic TherapyImmune EvasionPCR DiagnosticsReverse Screening AlgorithmTreponema Pallidum+1 more
15,633 views
4,691 downloads

Contributors:

 Sushmita Padhi Padhi
,
 Vinay Sagar Verma Verma
,
 Govind Sharma Sharma
,
 Bhushan Lal Lal
,
 Sanjay Gupta Gupta
Research PaperID: jprims-00000249

Biosurfactants: Classification, Production, Physicochemical Properties, and Industrial Applications

Mateshwari Nandan Nandan, Radhika Gond Gond, Raj Raj, Mohd. Yousuf Yousuf, Arshan Ahmad Ahmad

Biosurfactants are natural surfactants produced by microorganisms, such as bacteria, yeast, and fungus, which are either released into the environment or synthesized on microbial cell surfaces. These amphiphilic molecules display a variety of bioactivities and physical characteristics determined by their history, manufacturing, and purifying techniques. Glycolipids, such as rhamnolipids, mannosylerythritol lipids (MELs), sophorolipids, and trehalolipids, represent the predominant biosurfactants, including mono- or disaccharides combined with hydroxy- or long-chain aliphatic acids. They augment the solubility of hydrophobic compounds by rising their hydrophobicity and generating micelles and compartments at certain pH settings. Lipopeptides, including surfactin, lichenysin, and iturin, are produced by non-ribosomal routes by enzyme complexes such as surfactin synthetase, wherein the component SrfD is essential. Biosurfactants have remarkable surface and interfacial properties, decreasing surface tension and creating stable emulsions and foams. The combination of these qualities, together with a low critical micelle concentration (CMC), increased solubility, and greater detergency, renders biosurfactants more advantageous than conventional surfactants. Their effectiveness is contingent upon characteristics such as oil-water interfacial tension and surface tension, which range from 1 to 30 mN/m at CMC levels between 1 and 2000 mg/L. Biosurfactants has distinctive physicochemical properties, making them advantageous for drug delivery systems by enhancing solubility, stability, and effectiveness relative to traditional surfactants. They embody a sustainable and creative methodology in pharmaceutical applications.

AI-driven designCOVID-19Nano-immunotherapy
15,580 views
4,581 downloads

Contributors:

 Mateshwari Nandan Nandan
,
 Radhika Gond Gond
,
 Raj Raj
,
 Mohd. Yousuf Yousuf
,
 Arshan Ahmad Ahmad
Research PaperID: jprims-00000250

Quantifying Nature’s Novelty: Trends in HPLC and HPTLC Fingerprinting for Herbal Drug Analysis

Diyali Bairagi Bairagi, Neeraj Kumar Kumar, Devendra Singh Kushwaha Kushwaha, Shweta Jaiswal Jaiswal

The efficacy of herbal medicines in therapy, their cultural suitability, and relatively low degree of side effects have made them an inherent aspect of health care globally, yet the variability and complexity of phytochemical compositions are important concerns in quality, safety and reproducibility. Precisely, chromatographic fingerprinting techniques have emerged as an effective way of full characterization of herbal drugs particularly the High-Performance Liquid Chromatography (HPLC) and the High-Performance Thin Layer Chromatography (HPTLC). This review discusses the recent developments of these techniques using the latest state-of-the-art techniques such as Ultra-High Performance Liquid Chromatography (UHPLC), hyphenated techniques (LC-MS/MS and HPTLC-MS), densitometric analysis and combination of chemometric approaches. It covers methodological approaches, its application in the standardization of herbal drugs and a comparison of the two approaches. The findings reveal that HPLC is more sensitive and accurate in quantitative analysis, whilst HPTLC is fast, cost-effective and high-throughput screening. In addition, chemometric techniques are important to interpret the data, which enables to categorize the data correctly and detect the adulteration. Regardless of these advances, current problems such as the variability of phytochemicals and the lack of standard reference materials remain to be addressed, implying that future advances will be made with the help of hybridized chromatographic methods in the era of new technologies such as artificial intelligence and metabolomics.

BiosurfactantsSolid State FermentationHydrophilic-lipophilic Balancemannosylerythritol lipid
15,546 views
4,657 downloads

Contributors:

 Diyali Bairagi Bairagi
,
 Neeraj Kumar Kumar
,
 Devendra Singh Kushwaha Kushwaha
,
 Shweta Jaiswal Jaiswal
Research PaperID: jprims-00000251

AI-Accelerated Discovery of Novel Gero-suppressive Compounds: Quantifying the Enhancement of the Human Health span-To-Lifespan Ratio

Yash Srivastav Srivastav, Stuti Verma Verma, Vaishali Bhagwani Bhagwani, Kamini Prajapati Prajapati, Vasu Tiwari Tiwari, Neha Rawat Rawat, Shivani Singh Singh

This current study focuses on the impact of Artificial Intelligence (AI) on the rapid identification of new molecules to suppress aging processes, which increases the proportion of healthspan relative to lifespan. The research approach taken involved a quantitative method, where artificial intelligence-based machine learning, bioinformatics, and statistical analysis were used alongside computational molecular docking. Biochemical information from databases such as PubChem, DrugBank, and ChEMBL was leveraged to screen and analyze molecular data. It was observed that AI-assisted predictive models, especially Deep Learning Neural Networks, offered highly accurate predictions concerning the biological activity of anti-aging compounds. The selected molecules showed considerable decreases in oxidative stress, inflammation, and cellular senescence markers, coupled with improved mitochondrial function and cell repair. Moreover, quantitative results showed that the use of AI for predicting the efficacy of anti-aging agents led to more significant healthspan enhancements than lifespan increases.

Ultra-High Performance Liquid ChromatographyHigh-Performance Thin Layer ChromatographyHigh-Performance Liquid Chromatography (HPLC)Chromatographic fingerprintingHerbal medicines
15,883 views
4,693 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Stuti Verma Verma
,
 Vaishali Bhagwani Bhagwani
,
 Kamini Prajapati Prajapati
,
 Vasu Tiwari Tiwari
,
 Neha Rawat Rawat
,
 Shivani Singh Singh
Research PaperID: jprims-00000252

Intracytoplasmic Sperm Injection (ICSI), Embryo Transfer, Maternal BMI and Oocyte Quality: Implications for IVF Protocol Study on Live Birth Outcomes

Yash Srivastav Srivastav, Shivani Singh Singh, Kamini Prajapati Prajapati, Brijesh Kumar Pal Pal, Stuti Verma Verma, Saroj Kumar Kumar

Infertility is becoming an increasingly common reproductive health condition globally, leading to a dramatic increase in the use of assisted reproductive technologies, including intracytoplasmic sperm injection (ICSI) and in vitro fertilisation (IVF). Numerous factors, such as the mother, the embryo, and the IVF procedure, contribute to the success rate of in vitro fertilisation (IVF) and live births. Investigated here are in vitro fertilisation (IVF) success rates as a function of oocyte quality, maternal body mass index (BMI), embryo transfer methods, and ICSI. Female infertility patients undergoing in vitro fertilisation procedures at assisted reproduction centres were the subjects of the study, which used a quantitative methodology. Embryonic factors were considered alongside age, BMI, oocyte shape, fertilisation, embryo growth, embryo implantation rate, and pregnancy success rates. A chi-square test, descriptive statistics, regression models, and correlation analyses were all used to analyse the data statistically. The results show that the mother's oocyte quality and body mass index (BMI) significantly affect live birth rates, embryo growth, embryo implantation rate, and fertilisation success. There was a correlation between poor oocyte quality and high maternal BMI, lower rates of IVF success, and lower chances of live births.

Cellular SenescenceLifespanHealth spanGero suppressive CompoundsArtificial Intelligence
15,802 views
4,697 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Shivani Singh Singh
,
 Kamini Prajapati Prajapati
,
 Brijesh Kumar Pal Pal
,
 Stuti Verma Verma
,
 Saroj Kumar Kumar
Research PaperID: jprims-00000253

The "Parasitic Twin": Mimicking A Retroperitoneal Teratoma, Abdominal Mass in Neonate, Surgical Management of Fetus in Fetu (FIF)

Yash Srivastav Srivastav, Saurabh Rathaur Rathaur, Amrish Kumar Kumar, Himanshu Rathaur Rathaur, Saurabh Kumar Kumar, Divyansh Awasthi Awasthi, Shivani Singh Singh

Fetus in fetu (FIF) is a rare congenital anomaly that occurs when a malformed parasitic twin grows within the host twin (most frequently in the retroperitoneum). FIF is a rare condition, with a high diagnostic and surgical challenge for neonate and infant patients due to its similarity to retroperitoneal teratoma. The purpose of this study was to review the clinical presentation, radiological findings, surgical management and outcomes of FIF in neonates and infants by analyzing 80 cases of FIF reported between 2000 and 2025. Pediatric surgery journals, radiology reports, medical databases such as PubMed, Scopus, and Google Scholar, were used to collect data. The results indicated that the abdominal distention and palpable abdominal mass were the most common symptoms and male infants were more frequently affected. CT scan and MRI were very helpful for the identification of vertebral columns, limb buds and calcified skeletal structures, which aided in differentiating FIF from retroperitoneal teratoma. Surgical resection led to good postoperative results, with low recurrence and postoperative complications. All cases were diagnosed by histopathological examination. Prompt diagnosis and surgical intervention are still vital for favorable management and neonatal outcomes.

maternal BMI.embryo transferIVFICSIIntracytoplasmic sperm injection
15,947 views
4,821 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Saurabh Rathaur Rathaur
,
 Amrish Kumar Kumar
,
 Himanshu Rathaur Rathaur
,
 Saurabh Kumar Kumar
,
 Divyansh Awasthi Awasthi
,
 Shivani Singh Singh
Research PaperID: jprims-00000254

Biomimetic Mapping: A Comparative Analysis of Human Musculoskeletal Kinematics and High-Torque Robotic Actuation Systems

Yash Srivastav Srivastav, Satyam Verma Verma, Arun Kumar Kumar, Utkarsh Shukla Shukla, Pankaj Kumar Kumar, Anurag Verma Verma, Shivani Singh Singh

Biomimetic robotics is a cross-disciplinary area combining human biomechanics, robotics, artificial intelligence, and materials science in the development of robotic systems that can mimic human movements and functionality. The current review explores the connection between human musculoskeletal kinematics and advanced high-torque robotic actuation systems through the discussion of biomechanical theory, robotic actuator technologies, biomimetic mapping techniques, and innovative developments in the field of robotic engineering. Modern approaches such as motion capture, electromyography (EMG), inverse dynamics, biomechanical modeling, and artificial intelligence-controlled systems enable enhanced accuracy of movements, sensor fusion, and human-robot interaction in the robotic systems. Research shows that biomimetic robotics enables enhanced adaptability, efficiency, and safety during interactions with humans; nevertheless, it is still difficult to mimic the complex functionality and energy efficiency of the human musculoskeletal system. In addition, this study focuses on the innovative advancements in the field such as brain-computer interfacing and AI-enabled adaptive robotic systems.

Pediatric surgery.Congenital anomalyNeonatal abdominal massRetroperitoneal teratomaParasitic twinFetus in fetu (FIF)
15,960 views
4,782 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Satyam Verma Verma
,
 Arun Kumar Kumar
,
 Utkarsh Shukla Shukla
,
 Pankaj Kumar Kumar
,
 Anurag Verma Verma
,
 Shivani Singh Singh
Research PaperID: jprims-00000255

Biocompatible Control: The Integration of Graphene-Based Neural Interfaces and Adaptive AI Systems

Yash Srivastav Srivastav, Ankit Kumar Kumar, Vikas Kumar Kumar, Salim Salim, Ankur Bajpai Bajpai, Nitin Mishra Mishra, Shivani Singh Singh

The fusion of graphene neural interfaces with adaptive artificial intelligence (AI) systems has become a critical breakthrough in human-centred human-centred neurotechnologies and personalised healthcare. Graphene has an outstanding electrical conductivity, flexibility, transparency, light architecture and biocompatibility, making it an ideal material for wearable and implantable neural devices. At the same time, artificial intelligence systems that adapt their performance benefit the interpretation of the neural signals, learning in real time, signal recognition, and performance of rehabilitation. This review covers the structural and functional characteristics of graphene neural interfaces, adaptive AI in neural signal processing, and the synergy and application of both to brain–computer interfaces (BCIs), neuroprosthetics, assistive communication systems, and personalized neurotherapy. Humans studies show that graphene-AI systems have boosted the stability of neural signals, motor control, speech decoding and rehabilitation efficiency, as well as neural monitoring and remote healthcare. The review also covers critical issues like long-term biocompatibility, privacy of neural data, algorithmic transparency, cybersecurity, and regulatory approval. While small-scale clinical trials and the absence of standardized frameworks pose challenges, the potential applications of graphene-AI combination in neurological rehabilitation and intelligent healthcare systems are promising.

Humanoid roboticsProsthetic engineeringRehabilitation roboticsElectromyography (EMG)Artificial intelligenceHigh-torque robotic actuators+2 more
16,292 views
4,808 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Ankit Kumar Kumar
,
 Vikas Kumar Kumar
,
 Salim Salim
,
 Ankur Bajpai Bajpai
,
 Nitin Mishra Mishra
,
 Shivani Singh Singh
Research PaperID: jprims-00000256

Liquid Gold: Leveraging AI Algorithms to Decode Circulating Tumour DNA (CTDNA) for Multi-Cancer Early Detection (MCED)

Yash Srivastav Srivastav, Anoop Yadav Yadav, Mohd Danish Danish, Mohd Atif Shah Shah, Alok Yadav Yadav, Vivek Singh Singh, Shivani Singh Singh

Liquid biopsy using circulating tumor DNA (ctDNA) is gaining momentum as a powerful non-invasive tool for multi-cancer early detection (MCED) and precision medicine. The current paper highlights the role of artificial intelligence (AI), encompassing machine learning and deep learning techniques, in refining the analytical process of ctDNA to facilitate early cancer detection, diagnosis, prediction of the tissue of origin, and individualized disease management. Clinical trials in humans for various cancers, such as lung, colorectal, pancreatic, breast, and ovarian cancer, illustrate the ability of AI-enhanced ctDNA technology to detect even minute molecular changes in terms of mutations, epigenetic patterns, fragmentation features, and chromosome anomalies with higher sensitivity and specificity. In addition, the review highlights the biological relevance of ctDNA, the clinical utility of AI-based MCED systems, and the benefits of non-invasive testing, continuous surveillance, and detection of multiple cancers through a single blood sample. However, significant drawbacks, including low ctDNA concentration in early-stage tumors, false positives and negatives, non-standardization, ethical issues, and expensive technology, are substantial impediments to clinical adoption. Nonetheless, AI-powered ctDNA diagnostics hold immense promise for revolutionizing cancer screening in the future.

Graphene Neural InterfacesAdaptive Artificial IntelligenceBrain?Computer InterfacesNeuroprostheticsPersonalized NeurotherapyNeural Signal Processing+2 more
16,179 views
4,944 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Anoop Yadav Yadav
,
 Mohd Danish Danish
,
 Mohd Atif Shah Shah
,
 Alok Yadav Yadav
,
 Vivek Singh Singh
,
 Shivani Singh Singh
Research PaperID: jprims-00000257

Echofocus-CHD: Autonomous Detection and Stratification of Critical Congenital Heart Disease (CHD) in Prenatal Ultrasound

Yash Srivastav Srivastav, Rajan Yadav Yadav, Mohd Anas Ansari Ansari, Saffan Ahmad Ansari Ansari, Sartaj Alam Alam, Rinku Kashyap Kashyap, Shivani Singh Singh

Critical Congenital Heart Disease (CHD) is one of the most important causes of neonatal morbidity and mortality and early prenatal diagnosis is essential for effective treatment and better clinical outcomes. In this study, ECHOFOCUS-CHD, an AI-inspired autonomous framework for the diagnosis of Critical Congenital Heart Disease from ultrasound images of fetuses is proposed. A quantitative experimental research design was used and 200 prenatal ultrasound scans acquired from hospitals and fetal echocardiography databases are used. A Convolutional Neural Network (CNN) was created to classify fetal cardiac conditions into normal, mild, moderate and critical CHD categories. The models are enhanced by using image preprocessing methods like noise reduction, normalization, contrast enhancement, and data augmentation. An overall accuracy of 94.5%, sensitivity of 92.8%, specificity of 95.6% with an AUC value of 0.96% was obtained, which shows an excellent diagnostic capability in the proposed system. The reliability of the framework was also verified using confusion matrix and ROC curve analyses. The system was also able to automatically classify the heart defects of foals using images from their prenatal scans, aiding clinical decisions during pregnancy and early treatment planning. The results show that AI-powered prenatal ultrasound analysis has the potential to greatly improve the effectiveness of early detection of CHD and prenatal screening.

Deep LearningCancer DiagnosticsPrecision OncologyMachine LearningLiquid BiopsyMulti-Cancer Early Detection (MCED)+2 more
16,276 views
4,944 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Rajan Yadav Yadav
,
 Mohd Anas Ansari Ansari
,
 Saffan Ahmad Ansari Ansari
,
 Sartaj Alam Alam
,
 Rinku Kashyap Kashyap
,
 Shivani Singh Singh
Research PaperID: jprims-00000258

The Predictive Labor Ward: Utilizing Explainable AI (XAI) to Identify Compound Risk Factors for Sudden Stillbirth

Yash Srivastav Srivastav, Baliram Yadav Yadav, Dhiraj Chaurasiya Chaurasiya, Manish Manish, Himanshu Awasthi Awasthi, Dharm Pal Pal, Shivani Singh Singh

Sudden stillbirth still poses as one of the key challenges in maternal and fetus care, especially in developing nations where sophisticated labor ward monitoring systems cannot be afforded. It becomes very challenging to detect a pregnancy at risk early due to the combination of several risk factors related to both mother and the fetus. This paper presents the design of a Human-in-the-Loop Explainable Artificial Intelligence (XA)I-based predictive labor ward model to help detect composite risks related to sudden stillbirth. For this, the research considers clinical records on 90 pregnant mothers and then utilizes machine learning (ML) models such as Logistic Regression, Random Forest, and XGBoost for predictions. XAI algorithms are utilized to enhance transparency, interpretability, and clinician understanding of predictive results. It is found that the highest prediction accuracy can be achieved by usinsg the XGBoost-XAI method, which is superior to traditional approaches. Hypertension in mother, fetal distress, placental inefficiency, gestational diabetes, and prolonged labor are some of the most significant predictors of sudden stillbirth. The Human-in-the-Loop concept makes it more reliable.

Fetal Echocardiography.Deep LearningArtificial Intelligence (AI)Prenatal UltrasoundCritical Congenital Heart Disease (CCHD)Congenital Heart Disease (CHD)
16,428 views
4,933 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Baliram Yadav Yadav
,
 Dhiraj Chaurasiya Chaurasiya
,
 Manish Manish
,
 Himanshu Awasthi Awasthi
,
 Dharm Pal Pal
,
 Shivani Singh Singh
Research PaperID: jprims-00000259

Evaluation of Transformer-Based Models in Optimizing Invasive and Non-Invasive Brain-Computer Interfaces: Recurrent Neural Networks to Enhance Communication Speed for Locked-In Syndrome Patients

Yash Srivastav Srivastav, Rajkumar Rajkumar, Rama Kant Kant, Saroj Kumar Kumar, Rupesh Raj Raj, Shivam Yadav Yadav, Shivani Singh Singh

Brain-Computer Interfaces (BCIs) have been proposed as assistive technologies for Locked-In Syndrome (LIS) patients that can facilitate communication based on decoding of neural signals. Traditional BCI systems based on recurrent neural network (RNN) models exhibit certain constraints in terms of decoding accuracy, communication speed, and response latency. The current study aims to assess the effectiveness of transformer-based frameworks in optimizing the efficiency of both invasive and non-invasive BCI systems as compared to classical RNN models. A computational-clinical study design was used which involved participation of 48 LIS or severely paralysed participants. Subjects were grouped in accordance with their involvement in invasive or non-invasive BCI groups, and assessments were conducted during a period of eight weeks of intervention. Neural activity data processing was done with the help of two different approaches, including transformer-based model application and RNN application, assessing communication speed, decoding accuracy, latency, and error rates of both systems. Results suggest that transformer-based neural decoding frameworks proved to be superior to RNNs in terms of all evaluated criteria. Invasive transformer-based BCI demonstrated the best results concerning communication speed, decoding accuracy, lowest latency, and lowest error rates. Non-invasive transformer BCIs also yielded better results than RNN-based BCIs.

Obstetric Risk FactorsPredictive AnalyticsXAIMaternal HealthcareMachine LearningLabor Ward+2 more
16,836 views
5,047 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Rajkumar Rajkumar
,
 Rama Kant Kant
,
 Saroj Kumar Kumar
,
 Rupesh Raj Raj
,
 Shivam Yadav Yadav
,
 Shivani Singh Singh
Research PaperID: jprims-00000260

Human-Robot Interaction (HRI) Focus: AI Managing The "Bonding" and Emotional/Sensory Experience of a Robot-Led Pregnancy

Yash Srivastav Srivastav, Shruti Awasthi Awasthi, Komal Singh Singh, Ajay Rathaure Rathaure, Monu Singh Singh, Neeraj Bhargav Bhargav, Shivani Singh Singh

Human-Robot Interaction (HRI) has become an essential area that combines AI, robotics, affective computing, and healthcare technologies. This study considers the application of artificial intelligence (AI) in managing emotional connections, multisensory interaction, and psychological support in robot-led pregnancy systems. This article focuses on emotional recognition systems, multisensory communication, biosensors, adaptive robotics, ethical questions, social acceptance issues, and future advancements in maternal healthcare robotics. There is existing evidence suggesting that the use of emotionally intelligent robot systems may help improve maternal mental state, minimize the negative effects of stress and anxiety, increase engagement in healthcare processes, and give individualized assistance during pregnancy. Machine learning (ML) techniques, natural language processing, affective computing, and physiological sensors play a major role in enhancing the emotional intelligence of robotic healthcare technologies. At the same time, there are some difficulties related to the authenticity of emotions, privacy issues, emotional dependence, biased algorithms, and other ethical concerns that restrict their application. Overall, robot-led pregnancy systems demonstrate great potential as maternal healthcare technology solutions.

Non-Invasive BCI.Invasive BCIDeep LearningCommunication SpeedEEGNeural Decoding+4 more
16,920 views
4,990 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Shruti Awasthi Awasthi
,
 Komal Singh Singh
,
 Ajay Rathaure Rathaure
,
 Monu Singh Singh
,
 Neeraj Bhargav Bhargav
,
 Shivani Singh Singh
Research PaperID: jprims-00000261

Cross-Infection Patterns and Urogenital Health Outcomes in Men Partnered with Women Experiencing Infectious Vaginal Discharge: Leucorrhoea Influences Male & Female Sexual Desire

Yash Srivastav Srivastav, Shivani Singh Singh, Amita Singh Singh, Kamini Prajapati Prajapati, Stuti Verma Verma, Saroj Kumar Kumar, Brijesh Kumar Pal Pal

Infectious leucorrhoea is one of the most prevalent diseases of gynecologic nature involving infection of the reproductive system by fungi, bacteria, and parasites. Recurrent vaginal infections may lead to microbial cross-infections between male sex partners, adversely affecting sexual relations and intimate connections in the couple. This paper attempted to examine the problem of cross-infection, the state of urogenital health of men involved in the research, and the effect of infectious leucorrhoea on sexual arousal in both parties. A cross-sectional observational clinical study was carried out among 80 couples undergoing gynecology and urology clinics visits due to complaints of infectious vaginal discharge. Clinical evaluation, microbial investigation, laboratory tests, and questionnaire were used in the process of information collection. The results have shown that C. albicans was the most common pathogen among women in the sample group. Dysuria, balanitis, and penile irritation were found among men involved in the research, suggesting possible cross-infection from women. Sexual desire loss and avoidance behavior were noticed as well. Analysis of statistics indicates that there were highly significant relationships between infections with leucorrhoea, urogenital problems among men, and compromised sexual wellbeing (p

Social RoboticsHealthcare TechnologyEmotional BondingSensory InteractionAffective ComputingMaternal Healthcare Robotics+4 more
16,816 views
5,107 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Shivani Singh Singh
,
 Amita Singh Singh
,
 Kamini Prajapati Prajapati
,
 Stuti Verma Verma
,
 Saroj Kumar Kumar
,
 Brijesh Kumar Pal Pal
Research PaperID: jprims-00000262

Investigating The Rare Occurrence of Male-Female Conjoined Twinning: Incomplete Embryonic Division with Divergent Sexual Differentiation, Symmetrical Conjoined Twins Opposite Phenotypic Sex

Yash Srivastav Srivastav, Himanshu Shukla Shukla, Abhishek Raj Raj, Amit Kumar Kumar, Shivani Singh Singh, Stuti Verma Verma, Ashish Sharma Sharma

Conjoined twinning is a very rare congenital disorder that results from partial separation during the development of the embryos in cases of monozygotic twins. Male-female symmetrical conjoined twins with an opposite phenotype in relation to their biological sex are an extremely rare developmental abnormality due to the complications involved, from an embryological, genetic, hormonal, clinical, and ethical standpoint. In this review, we discuss the embryological causes of conjoined twinning, sexual differentiation processes, and the potential causes of discordant phenotypical sex development through chromosomal mosaicism, epigenetics, asymmetry of hormone distribution, or receptors. Furthermore, Disorders of Sex Development (DSD), prenatal diagnosis and molecular analyses, psychosocial impacts, surgery, and ethical issues related to sexual discordance among conjoined twins are evaluated. Our current scientific knowledge is limited since such cases are extremely rare.

Sexual WellbeingCandida albicansReproductive HealthSexual DesireMale Urogenital HealthCross-Infection+2 more
17,031 views
5,237 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Himanshu Shukla Shukla
,
 Abhishek Raj Raj
,
 Amit Kumar Kumar
,
 Shivani Singh Singh
,
 Stuti Verma Verma
,
 Ashish Sharma Sharma
Research PaperID: jprims-00000264

Systemic Physiological Reconfiguration During Sex Change Therapy: Somatic Changes in Transgender Men and Women Pre & Post Treatments

Yash Srivastav Srivastav, Abhinay Verma Verma, Monu Gupta Gupta, Mohd Rehan Rehan, Devendra Kumar Kumar, Aman Maurya Maurya, Shivani Singh Singh

The current research study explored the physiological and psychological shifts that take place in the bodies of transgender men and transgender women on undergoing hormone therapy. A quantitative comparative study design was employed involving 120 individuals – 60 transgender men on testosterone therapy and 60 transgender women on estrogen and anti-androgen therapy over a period of one year. The study involved data collection using methods such as anthropometry, hormonal profiling, laboratory testing, cardiovascular examination, and psychosocial measures. The results showed marked physiological transformations in the form of increased muscle mass and elevated hemoglobin content among transgender men, and increased body fat accumulation and breast growth and decreased muscle mass among transgender women. In addition, there were certain effects noted on the metabolism and cardiovascular system as a result of hormone therapy. The psychological effects included better emotional well-being, improved body image and self-esteem, and lower levels of anxiety and depression.

phytochemical profiling.chromatographic fingerprintingHPTLCHPLCHerbal medicines
17,152 views
5,226 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Abhinay Verma Verma
,
 Monu Gupta Gupta
,
 Mohd Rehan Rehan
,
 Devendra Kumar Kumar
,
 Aman Maurya Maurya
,
 Shivani Singh Singh
Research PaperID: jprims-00000265

New Paradigm Mechanisms of Genomic Replication in Somatic Cell Nuclear Transfer: Pathways to Human Clone Development

Yash Srivastav Srivastav, Moinuddeen, Amit Kumar Kumar, Md Putan Putan, Mohd Sameer Sameer, Piyush Verma Verma, Mohit Mishra Mishra, Deepak Bharti Bharti

Somatic Cell Nuclear Transfer (SCNT) is an essential process for cloning used in developmental and regenerative medicine. In the current investigation, there is a discussion about the mechanisms involved in genome replication, as well as the factors influencing clone development during SCNT. As a result of the analysis, it was found that cloned embryos have low developmental efficiency due to the insufficient epigenetic reprogramming, improper DNA methylation, problems with mitochondria, high oxidative stress, and insufficient activation of pluripotency genes. Comparing the SCNT embryos with the fertilized ones, there was a difference between the rate of developmental abnormalities and embryo survival. Moreover, the research suggests the possibility to use new techniques, including CRISPR-based epigenetic reprogramming, artificial intelligence-based monitoring of genomes, incorporation of stem cells, and artificial egg activation, to improve the cloning process. Despite some scientific achievements made within SCNT and related areas, many difficulties connected with ethics and biological aspects still do not allow to conduct human reproductive cloning. Therefore, the future research should concentrate only on therapeutic purposes of SCNT.

Testosterone Therapy.Physiological ChangesGender TransitionHormone TherapyTransgender Health
17,503 views
5,252 downloads

Contributors:

 Yash Srivastav Srivastav
,
 Moinuddeen
,
 Amit Kumar Kumar
,
 Md Putan Putan
,
 Mohd Sameer Sameer
,
 Piyush Verma Verma
,
 Mohit Mishra Mishra
,
 Deepak Bharti Bharti