Intelligent Internet of Medical Things for Depression: Current Advancements, Challenges, and Trends DOI Creative Commons
Md Belal Bin Heyat, Deepak Adhikari, Faijan Akhtar

et al.

International Journal of Intelligent Systems, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

We investigated the fusion of Intelligent Internet Medical Things (IIoMT) with depression management, aiming to autonomously identify, monitor, and offer accurate advice without direct professional intervention. Addressing pivotal questions regarding IIoMT’s role in identification, its correlation stress anxiety, impact machine learning (ML) deep (DL) on depressive disorders, challenges potential prospects integrating management IIoMT, this research offers significant contributions. It integrates artificial intelligence (AI) (IoT) paradigms expand studies, highlighting data science modeling’s practical application for intelligent service delivery real‐world settings, emphasizing benefits within IoT. Furthermore, it outlines an IIoMT architecture gathering, analyzing, preempting employing advanced analytics enhance intelligence. The study also identifies current challenges, future trajectories, solutions domain, contributing scientific understanding management. evaluates 168 closely related articles from various databases, including Web Science (WoS) Google Scholar, after rejection repeated books. shows that there is 48% growth articles, mainly focusing symptoms, detection, classification. Similarly, most being conducted United States America, trend increasing other countries around globe. These results suggest essence automated monitoring, suggestions handling depression.

Language: Английский

New Advances in the Pharmacology and Toxicology of Lithium: A Neurobiologically Oriented Overview DOI Creative Commons
Analı́a Bortolozzi, Giovanna Fico, Michael Berk

et al.

Pharmacological Reviews, Journal Year: 2024, Volume and Issue: 76(3), P. 323 - 357

Published: Feb. 8, 2024

Over the last six decades, lithium has been considered gold standard treatment for long-term management of bipolar disorder due to its efficacy in preventing both manic and depressive episodes as well suicidal behaviors. Nevertheless, despite numerous observed effects on various cellular pathways biologic systems, precise mechanism through which stabilizes mood remains elusive. Furthermore, there is recent support therapeutic potential other brain diseases. This review offers a comprehensive examination contemporary understanding predominant theories concerning diverse mechanisms underlying lithium's effects. These findings are based investigations utilizing animal models neurodegenerative psychiatric disorders. Recent studies have provided additional significance glycogen synthase kinase-3 (GSK3) inhibition crucial mechanism. research shed more light interconnections between GSK3-mediated neuroprotective, antioxidant, neuroplasticity processes. Moreover, advancements human valuable insights into how lithium-induced modifications at homeostatic synaptic plasticity level may play pivotal role clinical effectiveness. We focused from translational suggesting that interface with microRNA expression. Finally, we exploring repurposing beyond disorder. important clues toward developing predictive response identifying new targets.

Significance Statement

Lithium drug choice disorder, but action stabilizing presents latest evidence action. strengthened inhibition, changes plasticity, regulation expression key mechanisms, providing an intriguing perspective help bridge mechanistic gap molecular functions stabilizer.

Language: Английский

Citations

10

Relative synonymous codon usage and codon pair analysis of depression associated genes DOI Creative Commons
Rekha Khandia,

Pankaj Gurjar,

Mohammad Amjad Kamal

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Feb. 12, 2024

Abstract Depression negatively impacts mood, behavior, and mental physical health. It is the third leading cause of suicides worldwide leads to decreased quality life. We examined 18 genes available at genetic testing registry (GTR) from National Center for Biotechnological Information investigate molecular patterns present in depression-associated genes. Different genotypes differential expression are responsible ensuing depression. The study, investigated codon pattern analysis, which might play imperative roles modulating gene Of genes, seven two tended up- down-regulate, respectively, and, remaining different genotypes, an outcome SNPs were alone or combination with conditions associated Codon context analysis revealed abundance identical GTG-GTG CTG-CTG pairs, rarity methionine-initiated pairs. based on usage, preferred codons, rare, be used constructing a deliverable synthetic construct correct level human body, altered depressive state. Other signatures also role evolutionary forces shaping usage.

Language: Английский

Citations

10

Distinguishing features of depression in dementia from primary psychiatric disease DOI Creative Commons
Daniel Fisher, Jeffrey T. Dunn, Hongxin Dong

et al.

Discover Mental Health, Journal Year: 2024, Volume and Issue: 4(1)

Published: Jan. 4, 2024

Abstract Depression is a common and devastating neuropsychiatric symptom in the elderly patients with dementia. In particular, nearly 80% of Alzheimer’s Disease dementia experience depression during disease development progression. However, it unknown whether shares same molecular mechanisms as presenting primary psychiatric or occurs persists through alternative mechanisms. this review, we discuss how clinical presentation treatment differ between disease, focus on major depressive disorder. Then, hypothesize several that may be unique to such neuropathological changes, inflammation, vascular events. Finally, existing issues future directions for investigation

Language: Английский

Citations

9

Exploring molecular mechanisms, therapeutic strategies, and clinical manifestations of Huntington’s disease DOI
Alaa Shafie, Amal Adnan Ashour,

Saleha Anwar

et al.

Archives of Pharmacal Research, Journal Year: 2024, Volume and Issue: 47(6), P. 571 - 595

Published: May 19, 2024

Language: Английский

Citations

9

Intelligent Internet of Medical Things for Depression: Current Advancements, Challenges, and Trends DOI Creative Commons
Md Belal Bin Heyat, Deepak Adhikari, Faijan Akhtar

et al.

International Journal of Intelligent Systems, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

We investigated the fusion of Intelligent Internet Medical Things (IIoMT) with depression management, aiming to autonomously identify, monitor, and offer accurate advice without direct professional intervention. Addressing pivotal questions regarding IIoMT’s role in identification, its correlation stress anxiety, impact machine learning (ML) deep (DL) on depressive disorders, challenges potential prospects integrating management IIoMT, this research offers significant contributions. It integrates artificial intelligence (AI) (IoT) paradigms expand studies, highlighting data science modeling’s practical application for intelligent service delivery real‐world settings, emphasizing benefits within IoT. Furthermore, it outlines an IIoMT architecture gathering, analyzing, preempting employing advanced analytics enhance intelligence. The study also identifies current challenges, future trajectories, solutions domain, contributing scientific understanding management. evaluates 168 closely related articles from various databases, including Web Science (WoS) Google Scholar, after rejection repeated books. shows that there is 48% growth articles, mainly focusing symptoms, detection, classification. Similarly, most being conducted United States America, trend increasing other countries around globe. These results suggest essence automated monitoring, suggestions handling depression.

Language: Английский

Citations

1