Anup Kumar Sirbaiya

These rare facial diseases, which include hemifacial microsomia, Parry–Romberg syndrome, Moebius syndrome, Treacher Collins syndrome, Apert syndrome, and Crouzon syndrome, among others, pose considerable difficulties in diagnosis and treatment due to their clinical variability, rare occurrence, and complex genetic etiology. This review highlights the increasing potential of artificial intelligence (AI) and machine learning (ML) technologies in the better diagnosis, phenotyping, genotyping, and clinical management of these rare disorders. In this review, the applications of AI to facial phenotyping, three-dimensional (3D) imaging, radiomics, multimodal learning, and explainable AI have been highlighted. It also points out some latest developments in the field of bioinformatics, genome editing, RNA therapies, patient-derived models, and digital twin technology for precision medicine and translational research. Presently, there is sufficient evidence indicating the benefits of AI in increasing the accuracy in diagnosis, objective craniofacial evaluation, and customized treatment plans, whereas computational therapy is still experimental. However, various barriers such as data limitations, variability in phenotype, bias in the algorithms, external validation, ethical issues, and regulation prevent its widespread adoption in clinical practice. Future studies need to concentrate on multicenter data sharing, multimodal explainable AI, precision genomics, and translational framework to speed up the adoption of AI in rare craniofacial medicine.

Rare appendix malignancies, such as mucinous adenocarcinoma, goblet cell adenocarcinoma, signet-ring cell carcinoma, and appendiceal neuroendocrine tumors, are rare gastrointestinal cancers with diagnostic and treatment challenges due to their histological and molecular diversity. This study presents an explainable Artificial Intelligence (AI)-based approach that integrates digital histological biopsy images, molecular markers, and patient data to enhance disease classification and prediction of response to treatment. A quantitative methodology was used, based on an anonymized dataset of 200 patients with rare appendix malignancies. The performance of machine learning algorithms, such as Logistic Regression, Random Forest, XGBoost, and LightGBM, was compared using Accuracy, Precision, Recall, F1 score, and ROC-AUC metrics, while SHAP and Grad-CAM methods increased model interpretability. LightGBM outperformed all other methods and achieved the highest accuracy (96.2%), F1-score (95.5%), and ROC-AUC (0.987). KRAS, Ki-67, and TP53 were determined to be the most significant predictors from the biomarker analysis and the overall treatment response prediction accuracy of the combined model was found to be 95.1%. These results show that combining digital histopathology, biomarkers, and explainable AI (XAI) can enhance diagnosis accuracy, treatment response predictions, and clinical decision-making in rare appendiceal malignancies.

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.

Eyelid twitching and involuntary facial muscle spasms have become common neuromuscular disorders due to stress, anxiety, sleeplessness, prolonged computer usage, exhaustion, and other external factors. The purpose of this review is to discuss various neurophysiological, psychosomatic, environmental, and medical aspects of eye twitching disorders such as eyelid myokymia, hemifacial spasm, and blepharospasm in highly stressed people. Human research demonstrates that chronic stress along with dysfunction in the autonomic nervous system plays an important role in neuromuscular hyperactivity and ocular muscle spasms. Magnesium is discussed in this review as an important nutrient for nerve signaling, muscle relaxation, and neurotransmitter function. Therefore, magnesium intake in combination with stress management methods like meditation, yoga, and sleep may help alleviate the symptoms of eyelid twitches. Neurological complications like hemifacial spasm and blepharospasm generally require the intervention of drugs, neurological procedures like botulinum toxin injection therapy, anticonvulsants, and microvascular decompression surgery. The review also touches upon the effects of prolonged muscular spasm within the eye muscles on emotions, occupation, and quality of life from a psychosocial perspective. While previous human-based studies have shed light on various clinical aspects of the subject, there remain certain issues like small sample size, variation in therapeutic protocols, and absence of longitudinal studies that underscore the need for further clinical research.

The modern repair of hernia disease has undergone tremendous transitions in the past where open surgeries are still used to repair the hernia, to sophisticated minimally invasive and robotic assisted techniques through animal-based research being very essential in the understanding of the structure of the anatomy, biomaterials functions and the healing process. This review is a systematic analysis of the existing literature performed on animal models like rodents, rabbits, pigs, and canines to indicate the efficacy of various types of mesh, surgical methods and new technologies in enhancing clinical outcomes and recurrence. The results suggest that, biologic and composite mesh stimulates tissue integration, neovascularisation and organized collagen deposition and less inflammatory response and adhesion formation in comparison with synthetic mesh. As well, less invasive and robotic-assisted surgery methods enhance surgical accuracy, less tissue trauma, and outcome reproducibility. Nevertheless, interspecies variability, absence of standardized models, and inadequate long-term data are also limitations to direct translational applicability. The review notes the significance of the incorporation of advanced technologies including bioengineered meshes, artificial intelligence, and 3D bio printing and the necessity of standardized and long-term and interdisciplinary research to enhance the safety and efficacy of hernia repair approaches

Three-dimensional (3D) printing has become a transformative technology in pharmaceutical sciences, allowing the creation of customized drug delivery systems with precise control over shape, dosage, and release profiles. This review offers a thorough overview of 3D printing methods used in pharmaceuticals, including their materials, design strategies, characterization techniques, and current clinical and regulatory environments. Applications encompass personalized medicine, polypills, controlled-release implants, and new pediatric formulations. Despite its significant potential, 3D printing faces challenges related to scalability, quality control, and regulatory approval. Recent FDA approvals, notably of the first 3D-printed drug Spritam®, represent important milestones. Future advancements depend on unified guidelines, digital manufacturing integration, and AI-driven formulation improvements.