Browsing by Author "Nitish Kumar Singh"

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Assessment of depression anxiety and stress levels among patients with epilepsy in a case control study
(Discover, 2025) Shani Vishwakarma; Abhishek Pathak; Anil Kumar Maurya; Nitish Kumar Singh; Ashish Ashish; Royana Singh
Introduction: People with epilepsy frequently experience depression, anxiety, and stress, which can significantly impact their quality of life and overall well-being. This study aimed to identify psychiatric comorbidities in individuals with epilepsy by assessing their prevalence and comparing them with a healthy control group. Methodology: This case-control study was conducted in the department of Anatomy, and patients were recruited from the Out-Patient Department of Neurology, from August 2022 to February 2024. The total number of participants was 388, including 194 Cases. 194 healthy controls were matched for age and sex, with participants under the age of 18 excluded. Psychiatric comorbidity was evaluated using standardized assessment tools and analyzed with Chi-square and one-way ANOVA. Results: The study involved 194 patients and 194 healthy controls, with a mean age of 25.11 ± 10.28 years. Among the patients, 58.2% were female and 41.8% were male. A significant difference in depression levels was found between patients on monotherapy and polytherapy (p = 0.003). However, no significant differences were found in anxiety (p = 0.214) and stress (p = 0.139). There are no significant links between depression, anxiety, stress and antiepileptic drugs. Patients with epilepsy exhibited significantly higher levels of depression, anxiety, and stress compared to healthy controls, with a statistical significance of p = 0.001. Conclusion: The study highlights the elevated levels of depression, anxiety, and stress among patients with epilepsy. Clinicians and healthcare practitioners should adopt comprehensive and holistic assessment methods to address and mitigate these psychiatric comorbidities in epilepsy patients. © The Author(s) 2025.
Assessment of genetic and environmental risk factor association with amyotrophic lateral sclerosis diseases
(Science and Engineering Research Support Society, 2020) Nitish Kumar Singh; Abhay Kumar Yadav; Manpreet Kaur; Ashish; Royana Singh
Amyotrophic lateral sclerosis (ALS) is a type of progressive neurodegenerative disease of motor neurons, resulting in a worsening weakness of voluntary muscles until death from respiratory failure occurs after about 3 to 5 years. Although highly significant mobility have been made in our understanding of the genetic causes of ALS, the contribution of environmental factors has been more challenging to assess. Extensive studies of the clinical patterns of ALS, individual family histories preceding the onset of ALS, and the rates of ALS in different populations and groups have led to improved patient care, but have not yet revealed a replicable, definitive environmental risk factor. In this review, we outline what is currently known of the environmental and genetic epidemiology of ALS, describe the current state of the art concerning the different types of ALS, and explore whether ALS should be considered a single disease or a syndrome. We examine the relationship between genetic and environmental risk factors and propose a disease model in which ALS is considered to be the result of environmental risks and time acting on a pre-existing genetic load, followed by an automatic, self-perpetuating decline to death. ⓒ 2019 SERSC.
Association between the MTHFR (rs1801133) gene variation and serum trace elements levels (Copper and Zinc) in individuals diagnosed with neural tube defects
(Elsevier B.V., 2024) Nitish Kumar Singh; Sarita Choudhary; Sangeeta Rai; Abhay Kumar Yadav; Royana Singh
Background and Aims: Neural tube defects (NTDs) occur when the neural tube fails to close within 28 days of human embryonic development. This results in central nervous system disorders like anencephaly, spina bifida, and encephalocele. Early diagnosis and treatment are crucial to minimize their impact on an individual's health and well-being. The present study aims to define the association between prenatal exposure to trace elements (Cu and Zn) and the single nucleotide polymorphism (SNP) of the MTHFR gene involved in folate metabolism pathways in neural tube defects in children and their mothers. Material and Methods: A cross-sectional study involving 331 participants (90 NTD cases, 88 healthy mothers, 85 NTD children, and 68 healthy children) from antenatal check-ups in Obstetrics and Gynaecology and Pediatric Surgery for Neural Tube Defects in the Outpatient Department (OPD) and Inpatient Department (IPD). Assessed Cu and Zn concentrations and their associations. Genomic DNA was extracted, and real-time PCR was used to determine genotypes. Atomic absorption spectrophotometry measured trace elements. Statistical analyses included Chi-Square tests, odds ratios, and Mann-Whitney U tests. Results: Significant associations were found between MTHFR C677T genotypes and NTD risk in mothers (p = 0.0491) and children (p = 0.0297). Allelic frequency analysis indicated a T allele association with NTD risk in children (p = 0.0107). Recessive models showed significant associations in mothers (p = 0.0169) and children (p = 0.1678). Cu levels differed significantly between NTD cases and controls (p < 0.0001), with MTHFR genotypes influencing Cu levels. Zinc levels also varied significantly (p < 0.0001). Conclusion: This study reveals complex associations between MTHFR C677T genotypes, trace element concentrations, and NTD risk in mothers and children. This targeted approach allows healthcare providers to identify at-risk pregnancies early, enabling personalised interventions like folic acid supplementation and counselling to moderate neural tube defect (NTD) risk in a future pregnancy. © 2024 Elsevier B.V.
Convergence of novel iterative learning control methods for a class of linear discrete-time switched systems
(Springer Science and Business Media Deutschland GmbH, 2021) D.R. Sahu; Nitish Kumar Singh
In this paper, we study the convergence of different iterative learning control methods implemented to a class of linear discrete-time switched systems coupled with an arbitrary switched rules under the hypothesis that switched system operates repetitively over a finite time interval. The convergence is discussed by utilizing the super-vector approach when the system is noise-free. Here, we introduce Mann-ILC method and normal S-ILC method of switched systems and establish some theorems related to the convergence of the corresponding reference trajectory on the time interval. We present a numerical experiment to demonstrate the convergence behaviour of theoretical analysis. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.
Effect of processing on the particle size of tin oxide nano-powders
(Springer Science and Business Media, LLC, 2013) Meenakshi Choudhary; Nitish Kumar Singh; R. Dwivedi; V.N. Mishra
Nano sized tin oxide powders have been synthesized via two different chemical routes namely solid-state and sol-gel route for the fabrication of tin oxide gas/odors sensor. The synthesized powders have been characterized by simultaneous thermo gravimetric and differential thermal analysis (TG-DTA), powder X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM) and Fourier transform infrared (FTIR) spectroscopy. The effect of synthesis routes have been investigated on particle size and morphology of tin oxide powders. Powder XRD patterns show that the synthesized powders have tetragonal (rutile) crystal structure. FESEM of formed thick films reveal that powder prepared by solid-state reaction route is less agglomerated as compared to the powder prepared by sol-gel route. XRD and FESEM indicate that there is the formation of tin oxide nanoparticles in the range of 15-50 nm. FTIR spectrums of synthesized powders show Sn-O or Sn-O-Sn stretching modes and its lattice modes at 615 and 494 cm-1. © 2012 Springer Science+Business Media, LLC.
Effects of SARS-Cov-2 infection and rhino-orbital mucormycosis on concentrations of inflammatory biomarkers in Indian populations
(IP Innovative Publication Pvt. Ltd., 2022) Ajay Kumar Yadav; Shivam Tiwari; Bhupendra Kumar; Abhay Kumar Yadav; Ashish Ashish; Nitish Kumar Singh; Manpreet Kaur; Shivani Mishra; Shani Vishwakarma; Surendra Pratap Mishra; Rajendra Prakash Maurya; Nargis Khanam; Pooja Dubey; Janhavi Yadav; Royana Singh; Sayeed Mehbub Ul Kadir
Rhino-orbital mucormycosis is a rare life threatening invasive fungal infection that has recently shown a very high mortality rate in India during COVID-19 pandemic. We have designed the present study to find out associations between COVID-19 induced rhino-orbital mucormycosis and concentrations of inflammatory markers, i.e. D-dimer, Ferritin, IL-6, CRP and PCT, in blood serum of Indian population. There were four groups in the study, viz. control group with healthy subjects, treatment group-1 with patients suffering from SARS-COV-2 infection, treatment group-2 with patients suffering from both SARS-COV-2 infection and rhino-orbital mucormycosis, and treatment group-3 with patients suffering from rhino-orbital mucormycosis after SARS-COV-2 infection recovery. Inflammatory markers were quantified with standard protocols, and recorded data were subjected to statistical analyses. We found that patients suffering from SARS-COV-2 infection were more susceptible to rhino-orbital mucormycosis, as they had higher concentrations of inflammatory markers in their blood than the other subjects. Diabetes mellitus, hypertension, cardiovascular diseases and renal disorders were the associated comorbidities with the patients. We also found higher concentrations of inflammatory markers in males than the females, indicating towards their higher susceptibility in developing rhino-orbital mucormycosis than females. Present study therefore suggests that the frequent occurrence of rhino-orbital mucormycosis in India during second wave of COVID-19 was possibly due to indiscriminate use of corticosteroids by COVID-19 patients. Subjects with previous history of comorbidities like diabetes mellitus, hypertension, cardiovascular disorders and renal diseases are the most susceptible population groups for developing infection. Moreover, males are at higher risk of developing mucormycosis than the females. © 2022 Innovative Publication, All rights reserved.
Exploring the multifaceted links between comorbidities and cognitive aging
(Elsevier, 2025) Ashish Ashish; Nitish Kumar Singh; Anil Kumar Maurya; Shivani Mishra; Royana Singh
Cognitive aging is a multifactorial process influenced by various physiological, psychological, pathological, and genetic factors. Comorbidities such as cardiovascular diseases, diabetes, hypertension, depression, drug addiction, family, and social environment, which are prevalent in the elderly population, have been implicated in accelerating cognitive decline. Understanding these associations is crucial for developing targeted interventions. This chapter provides a thorough review of existing literature, synthesizing data from gerontology, neurology, and psychiatry to examine the impact of comorbidities on cognitive functions. The findings highlight that cardiovascular diseases and diabetes are strongly associated with an increased risk of cognitive impairment and dementia. Hypertension contributes to vascular dementia through mechanisms involving reduced cerebral blood flow and white matter lesions. Depression, both a risk factor and a consequence of cognitive decline, is linked to shared pathophysiological pathways such as chronic inflammation and neuroendocrine dysregulation. The chapter emphasizes the bidirectional nature of these relationships, underscoring the need for holistic approaches in managing comorbidities to mitigate their impact on cognitive health. Potential mechanisms, including oxidative stress, inflammation, and vascular changes, are explored, and the role of genetic predispositions and lifestyle factors in moderating these effects is considered. Addressing comorbid conditions through integrated healthcare strategies is essential for preserving cognitive functions in aging populations. Future research should focus on personalized medicine approaches and the exploration of novel therapeutic targets to prevent or delay cognitive decline. However, the chapter’s limitations include the lack of standardized methodologies across studies and the need for further exploration into the molecular mechanisms involved. © 2026 Elsevier Inc. All rights reserved..
Genetic Analysis of Recurrent Pregnancy Loss: Role of Karyotyping in Understanding Pathogenesis and Management
(Jaypee Brothers Medical Publishers (P) Ltd, 2025) Shivani Mishra; Royana Singh; Sangeeta Rai; Ashish Ashish; Nitish Kumar Singh; Manpreet Kaur; Nargis Khanam; Janhavi Yadav; Chetan Sahni
Introduction: Recurrent pregnancy loss (RPL) is defined as two or more spontaneous pregnancy losses within 20–24 weeks of the gestational period, which typically occur in the early stages of pregnancy. Various factors can contribute to RPL, including genetic factors, hormonal imbalances, uterine abnormalities, autoimmune disorders, infections, and lifestyle factors. Materials and methods: This study involved the conventional karyotyping of women facing RPL with the G-banding method and the culture procedure of leukocytes. The statistical analysis was done by IBM SPSS 20 after the biochemical data collection and karyotyping results. Results: The total samples were collected from 160 couples, out of which only 130 were successfully done with conventional karyotyping. It was noted in this study that the genetic rearrangement in female partners was found to be 11.5%, excluding the anatomical, immunogenic, and hormonal factor dysfunctions. The advanced maternal age and primary RPL were found to be more actively causing recurrent miscarriages. Conclusion: These investigations emphasize the importance of genetic analysis in RPL cases, biochemical, and cytogenetic analysis. The karyotyping must be done to rule out any chromosomal rearrangement in male and female partners. The previous family history may indicate the likelihood of carrying chromosomal rearrangements; thus, further study needs to be done in large populations. © (2025), (Jaypee Brothers Medical Publishers (P) Ltd). All rights reserved.
Investigation of Serum Pro-Inflammatory Markers and Trace Elements Among Short Stature in Eastern Uttar Pradesh and Bihar Populations
(Dove Medical Press Ltd, 2024) Abhay Kumar Yadav; Nitish Kumar Singh; Ankur Singh; Ashish Ashish; Sachchida Nand Rai; Santosh Kumar Singh; Royana Singh; Suchitra Singh
Purpose: Short stature is prevalent among children worldwide, particularly in developing countries. Various trace elements, including zinc, magnesium, iron, copper, chromium and selenium, are crucial for proper body development. The aim of this study is to explore the relationship between trace elements and TNF-α and IL-6 to elicit and possible pathway responsible for short stature. Methods: Two hundred and twenty samples were recruited for this study, 100 short statures and 120 controls were randomly selected. Six trace elements were measured using graphite furnace atomic absorption spectrometry. The concentrations of IL-6 and TNF-α in serum were assessed utilizing the Enzyme-Linked-Immunosorbent Assay (ELISA). Superoxide dismutase was also analysed to determine the oxidative stress response. Results: The study revealed notable distinctions in serum trace element levels of short stature. They exhibited significant lower levels of zinc and magnesium, alongside higher levels of copper. The altered Cu/Zn ratio seemed to have a positive correlation with short stature. Conversely, no significant disparities were observed in iron, chromium, and selenium levels. Furthermore, a significant rise was noted in proinflammatory marker TNF-α and cytokine IL-6. Additionally, superoxide dismutase was low in the short statures In silico study shows a high affinity of Zinc with TNF alpha. It may be suggested that inflammation at any time during childhood, with the rise in TNF alpha tightly binds with zinc and may have led to a decrease in zinc serum levels, altered redox homeostasis and resulted in short stature. Conclusion: The altered Cu/Zn ratio along with high TNF alpha and IL6 may be used as a marker for short stature in the initial years of growth in children before they reach maturity at the age of 18. Thereafter, introducing zinc supplementation could potentially enhance stature by mitigating TNF-alpha level. Further experimental studies will help to establish the exact role of zinc with TNF alpha in short stature. © 2024 Yadav et al.
Ovotesticular Disorder of Sex Development in a Tertiary Care Center in North India: A Single‑center Analysis over a 5‑year Period
(Wolters Kluwer Medknow Publications, 2023) Sarita Chowdhary; Maneesha Upadhayaya; Gunjan Rai; Manpreet Kaur; Nitish Kumar Singh; Kanika Sharma; Ritesh Yadav; Bitan Naik; Shiv Prasad Sharma; Royana Singh
Background: Disorders of sexual development (DSD) encompass a group of congenital conditions characterized by diverse genotypic and phenotypic variations. Ovotesticular (OT) DSD is a distinctive subtype within this spectrum. Among the array of DSD, OT-DSD stands as one of the most infrequent anomalies, with reported prevalence rates as scarce as 1 in 83,000. This study aims to elucidate the clinical, hormonal, cytogenetic, surgical, and histopathological characteristics of OT disorder of sex development (OT-DSD) within a tertiary center in North India. Methodology: A retrospective analysis was conducted, involving a comprehensive review of records pertaining to OT-DSD patients from the years 2018 to 2022, all of whom were incorporated into the study. Results: The mean age of presentation in this study was 10 years, spanning from 6 to 15 years. Predominantly, the affected individuals were male, with a solitary patient representing the female category. Clinical manifestations displayed a spectrum encompassing genital ambiguity, inguinal swelling, and primary amenorrhea. The karyotypes observed were 46,XX in four patients and 46,XY in one patient. A holistic assessment, inclusive of clinical evaluation, hormonal assays, pelvic ultrasonography, and surgical intervention when necessary, was administered to all patients. Among these cases, three patients were reared as males, their gender assignment driven by external genital appearance and sociocultural influences. Notably, none of the patients manifested gonadal tumors during the course of the study. Conclusion: In cases of ambiguous genitalia, the consideration of OT-DSD should be integral to the differential diagnosis, underscoring the significance of heightened clinical awareness and informed decision-making. © 2023 National Journal of Clinical Anatomy | Published by Wolters Kluwer - Medknow.
p-Accelerated normal S-iterative learning control algorithm for linear discrete singular time-delay systems
(Taylor and Francis Ltd., 2024) D.R. Sahu; Nitish Kumar Singh
This article addresses the issue of iterative learning control for a specific category of discrete linear singular time-delay systems. A new iterative learning control algorithm based on the p-accelerated normal S-iteration method is proposed, and convergence analysis of the corresponding learning control algorithm is studied. With certain assumptions, the proposed algorithm guarantees that the output of the system converges to the desired output trajectory within a finite time interval. The theoretical analysis is supported by numerical examples. The results indicate that the p-accelerated normal S-iterative learning control algorithm outperforms both the first-order PD-type iterative learning control and second-order PD-type iterative learning control algorithms for discrete linear singular systems theoretically and numerically. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
Prediction of antimicrobial activity using artificial intelligence
(De Gruyter, 2025) Nitish Kumar Singh; Jaikee Kumar Singh; Vivek Chandra Verma; Syed Mohammad Nasar Ata; Aprajita Singh
The fields of AI/ML (artificial intelligence/machine learning) have revolutionized the area of predicting antimicrobial activity, substantially enhancing the development of effective therapeutics for both animal and human health. These technologies have advanced the integration of multi-omics data, such as genomic, proteomic, and metabolomic datasets, and facilitated the development of a more precise and detailed forecasting framework. Modern ML methods, such as deep learning and neural networks, can now process enormous and complicated information to find new antibacterial agents and gauge their effectiveness. By simulating complex interactions between medications and microbial targets, these models can shed light on pharmacological modes of action, resistance mechanisms, and possible off-target consequences. AI-driven methods are also excellent at finding complementary medication combinations and maximizing polypharmacy tactics for difficult-to-treat illnesses. Furthermore, AI and ML facilitate the real-time processing of large extensive amounts of clinical and as well environmental data information, which helps guide the development of next-generation antimicrobial medicines and forecast the emergence of resistant strains. As AI and ML continue to advance, their role in predicting antimicrobial activity will be pivotal in combating infectious diseases, enhancing treatment efficacy, and improving global health outcomes for both humans and animals. © 2025 Walter de Gruyter GmbH, Berlin/Boston, Genthiner Straße 13, 10785 Berlin. All rights reserved.
Robust tracking of discrete-time linear switched systems with disturbance via second-order ILC with data loss
(Taylor and Francis Ltd., 2024) D.R. Sahu; Nitish Kumar Singh
The purpose of this article is to investigate the second-order P-type iterative learning control (ILC) scheme in the presence of data loss for a class of linear discrete-time switched systems with disturbances. Employing the super-vector representation technique, the discrete-time linear switched system is reformulated as an input-output transmission equation. The robustness of the resulting switched system driven by a second-order P-type ILC scheme is guaranteed through the use of the super-vector representation technique. Importantly, the article also explores cases of data loss occurring during data transmission. The proposed methodology exhibits significantly improved convergence performance compared to the P-type ILC scheme (Yang et al., 2022, Robust finite-iteration tracking of discrete-time systems in repetitive process setting via ILC scheme. International Journal of Robust and Nonlinear Control, 32(5), 2585–2602. https://doi.org/10.1002/rnc.5782). Simulation examples are provided to demonstrate the effectiveness of the proposed scheme. © 2024 Northeastern University, China.
Second-order iterative learning control for a class of switched discrete-time systems with model uncertainties, external noises and time-delay
(Taylor and Francis Ltd., 2023) D.R. Sahu; Nitish Kumar Singh
The second-order ILC algorithm is studied for a class of linear discrete-time switched systems with model uncertainties, external noises and the time-delay for tracking reference trajectory by taking advantage of super-vector representation. This study is based on the assumption that the systems operate under finite intervals. A sufficient condition for convergence of the algorithms is deduced when the model uncertainties and external noises are absent. Then the convergence is analysed, when the model uncertainties are present but the external noises are absent and the robustness against the bounded external noises is discussed. The analysis manifests that the second-order ILC algorithm is feasible and effective when it is imposed on the linear switched systems specified by the arbitrarily present switching rules when they are imposed on the system. We have presented a simulation example to illustrate effectiveness of the proposed second-order ILC algorithm in the study of robustness of the considered SISO linear discrete time-invariant time delay switched system. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
The Morphological Features of Anencephaly in North Indian Population
(Wolters Kluwer Medknow Publications, 2023) Rashmi; Nitish Kumar Singh; Ashish; Abhay Kumar Yadav; Manpreet Kaur; Royana Singh
Background: Anencephaly occurs due to the complete absence of cranial vault and subsequent disruption of the cerebral cortex with a severely damaged brain. In anencephaly, the forebrain and brain stem are exposed. Forebrain either does not develop or is destroyed, leading to the absence of cerebrum and cerebellum. Methodology: Neural tube defects were taken in the study group. During the autopsy, clinical findings, external examination, internal examination, and photography were done along with the histopathology of the specimens to confirm the anomalies at microscopic level using hematoxylin and eosin staining. Results: In our study, we observed a simian crease in 4 out of 5 (80%) cases. Furthermore, there was presence of tooth which was not seen in previous studies. Central nervous system anomalies like spina bifida, gastro intestinal tract (GIT) anomalies like cleft palate, intestinal obstruction of megacolon, and malrotation of gut were some of the common anomalies which were observed in our study. Conclusion: It may be suggested that Anencephaly shows a female predisposition and the cases seems to be associated more in the primigravida females.The classical phenotypic presentation of anencephaly having absent cranial vault, low set ears, protruding eyes were present in all subjects studied. In our study, we observed a simian crease in 4 out of 5 (80%) cases. Furthermore, there was presence of tooth which was not seen in previous studies. Central nervous system anomalies like spina bifida, GIT anomalies like cleft palate, intestinal obstruction of megacolon, and malrotation of gut were some of the common anomalies which were observed in our study. © 2023 Journal of the Anatomical Society of India.
Trace elements and cognitions in elderly population: a case–control study
(Springer Science and Business Media B.V., 2025) Anil Kumar Maurya; Mona Srivastava; Ashish Ashish; Nitish Kumar Singh; Abhay Kumar Yadav; Shani Vishwakarma; Royana Singh
There have been almost no studies with trace elements and psychological battery in cognitively impaired elderly individuals. Such research is crucial to enhance diagnostic accuracy. We aim to identify significant differences in blood serum concentration levels of trace elements, Hindi Mini-Mental State Examination (HMMSE), and psychological battery as Hindi Mattis Dementia Rating Scale (HMDRS) scores between case and control groups in the elderly. A cross-sectional research design was conducted with a total of 240 subjects, comprising 120 each from the case and control groups. Trace elements were analyzed using Atomic Absorption Spectrometry. HMMSE and HMDRS tests were administered to assess cognition scores. The chi-square test, t-test, and appropriate statistics were utilized. Our findings indicate significant differences in demographic factors (age, gender, education level) and clinical levels (p <.001), while caste, habitat, and marital status were not significant (p <.05). Concentration levels of Iron (Fe) and Copper (Cu) was higher, Zinc (Zn), Chromium (Cr), and Selenium (Se) were lower, significantly different (p <.001), but Magnesium (Mg) was not (p <.05). Additionally, third HMMSE and HMDRS were significant (p <.001) between the case and control groups in the elderly. The study suggested that higher levels of Fe and Cu, while lower Zn, Cr, and Se blood serum concentrations increased the risk of cognitive impairments in the elderly population, demonstrated by the HMMSE and HMDRS test scores which were lower in the case group. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.
Unlocking cognitive vitality: the interplay of stimulation, sleep, and brain aging
(Elsevier, 2025) Nitish Kumar Singh; Ashish Ashish; Surbhi Singh; Pooja Dubey; Royana Singh
Cognitive vitality is a crucial component of healthy aging, influenced by cognitive stimulation, sleep quality, and the natural aging process of the brain. This chapter explores the interplay between these factors, integrating findings from empirical and neuroimaging studies to provide a comprehensive perspective on their impact on brain aging. Research shows that participating in cognitive activities like reading, solving problems, and engaging in social interactions boosts neural plasticity and helps slow down cognitive decline. At the same time, quality sleep, defined by sufficient duration and few interruptions, is crucial for memory consolidation, synaptic balance, and the removal of neural waste. In contrast, inadequate sleep speeds up brain aging and raises the likelihood of neurodegenerative diseases. Research indicates that the combined effects of mental stimulation and sleep may yield synergistic benefits for cognitive health. However, several limitations must be acknowledged. Despite strong empirical support, variability in study methodologies, sample sizes, and assessment tools may influence the generalizability of findings. Additionally, while neuroimaging studies provide valuable insights, they cannot fully capture the complexity of individual cognitive trajectories. The long-term impact of specific interventions remains an area requiring further exploration, particularly in diverse populations. Future research should focus on refining personalized intervention strategies and examining the bidirectional relationship between cognitive stimulation and sleep in brain aging. Addressing these gaps will enhance our understanding of cognitive resilience and inform effective approaches to maintaining cognitive function in aging populations. © 2026 Elsevier Inc. All rights reserved..