Yash Srivastav

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.

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.

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.

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.

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.

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.

Immunotherapy for cancer treatment has proved to be a very useful technique that helps to boost the immune responses of the host against cancer cells. In this study, the effectiveness of atezolizumab is assessed in Programmed Death-Ligand 1(PD-L1) Positive advanced cancers of Indians. This study was performed using a retrospective analysis on the clinical data of 120 patients that received atezolizumab treatment between 2021 and 2025. Patients with advanced solid malignancies such as non-small cell lung carcinoma (NSCLC), hepaticellular carcinoma (HCC), and triple-negative breast cancer (TNBC) were included in this study. The RECIST 1.1 criteria and CTCAE Version 5.0 recommendations were used to assess the response to therapy, progression-free survival, overall survival, and adverse events linked to the immune system, respectively. Kaplan-Meier survival analysis, chi-square testing, and descriptive statistics were all part of the statistical package. The results demonstrated that patients exhibiting elevated levels of PD-L1 had a substantially better chance of surviving. In total, 76.6% of people were able to keep the sickness at bay, whereas only 48.3% responded. Treatment response is strongly correlated with PD-L1 over-expression (χ² = 9.64, p = 0.002). Adverse reactions experienced by subjects in this study were mostly mild-to-moderate. It was concluded in this study that atezolizumab is an effective and safe immunotherapy drug for treating PD-L1-positive malignancies in Indians.

The mpox virus (MPXV), which is an emergent orthopoxvirus with zoonotic transmission capability, represents a growing public health threat on a global scale due to the recently reported outbreaks in multiple countries after 2022. In view of the rising prevalence of genetically heterogeneous strains, such as Clade I and Clade II, there has been a growing research focus on the molecular aspects of pathogenesis, evolution, transmission, and epidemiology of MPXV clades. The current review focuses on the genome structure, mutations, viral fitness, immune evasiveness, and human-to-human transmission rate associated with MPXV clades. The comparative pathogenicity between the Clade I and Clade II variants is also discussed, with emphasis on the increased virulence and mortality related to Clade I and increased transmissibility of Clade II variants, including Clade IIb. Recent genomic studies have shown that hypermutations caused by the APOBEC3 enzymes, single-nucleotide polymorphism, and adaptive evolution contribute to viral persistence, immune escape, and epidemic spread. Furthermore, the review explains how epidemiologic surveillance efforts, molecular diagnostic tools, genomics techniques, and public health issues related to mpox epidemic response are managed. This information highlights the crucial role of genomics surveillance, timely diagnostics, vaccines, and the One Health approach in future prevention of mpox outbreaks.

The human aging process can be characterized by progressive cellular degeneration, mitochondria malfunctioning, inflammatory responses, epigenetics modifications, and loss of tissue regenerative ability. The recent progress made in the field of longevity has revealed several promising treatment opportunities for prolonging a healthy lifespan in humans through epigenetics regulation, senolytics application, NAD+ precursors' intake, telomerase activation, and regenerative treatments. This review considers evidence from human studies about the impact of DNA methylation, cell senescence elimination, mitochondria recovery, enhanced immunity, tissue renewal, and cognitive reserve increase in human aging biology. According to findings based on human research, interventions involving senolytic compounds, Nicotinamide Riboside (NR), Nicotinamide Mononucleotide (NMN), and telomerase-linked regenerative treatment have the ability to contribute to improved metabolism, vascular functions, immunological resilience, and cognitive efficiency while reducing inflammatory processes and decreasing the number of senescent cells in a human body. In addition, comprehensive longevity approaches consisting of the mentioned interventions seem to possess combined benefits in terms of human longevity improvement. However, there are certain drawbacks that must be addressed when applying these interventions into clinical practice; namely, small sample sizes used in studies, lack of long-term safety testing, ethical issues, and inadequate biomarkers. Future directions in the research are discussed.

The investigation assessed the potential applications of LLMs, EEG neurofeedback, HRV analysis, DORAS systems, and VRH in the development of AI-powered hypnotherapy solutions for pain therapy. The results proved that AI-based hypnotherapy platforms had higher levels of customization, ability to monitor the states of trance, maintain consistency of sessions, and promote physiological adaptations compared to conventional hypnotherapy approaches based on human hypnotherapists. The quantitative analysis revealed that hypnotherapy sessions assisted by VRH delivered the most effective pain relief outcomes, whereas the EEG and HRV assessments revealed enhanced levels of autonomic relaxation and emotional control in the context of hypnotherapy. The researchers found that despite obvious strengths in terms of scalability, incorporation of neurofeedback, and responsiveness to individual conditions of patients, AI systems lack some qualities inherent to humans such as emotional empathy and rapport building. Overall, it can be concluded that future hypnotherapy systems are more likely to become hybrid human-AI solutions.