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Disease Domain	Count

Infectious Diseases	1

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Small molecule drug	1

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CLPP(caseinolytic mitochondrial matrix peptidase proteolytic subunit)	1

The vision of the investigators is to build capacity in technology-driven healthcare innovation in LMCIs. The programme will be initiated by a feasibility and proof-of-concept (POC) study to tackle the lack of awareness around immunization, which is a major health issue in developing countries. Mobile apps and social media have been shown to be effective in various programmes worldwide, but there is limited data from LMICs on the use of digital technologies in improving routine immunization (RI) coverage.

Start Date27 Feb 2020

Sponsor / Collaborator

Aga Khan University

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100 Clinical Results associated with Ned University of Engineering & Technology

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0 Patents (Medical) associated with Ned University of Engineering & Technology

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2,282

Literatures (Medical) associated with Ned University of Engineering & Technology

31 Dec 2025·Journal of Plant Interactions

Exploring the functional and regulatory mechanisms of the RBOHD gene in rice against bacterial blight disease

Author: Hussain, Sajjad ; Chen, Yinhua ; Xiao, Xiaorong ; Solangi, Kashif Ali ; Khaskhali, Shahneela ; Solangi, Farheen

01 Jul 2025·Journal of Molecular Structure

Quercetin capped Au-Ag bimetallic nanoparticles for the detection of calcium dobesilate monohydrate in biological and environmental samples

Author: Hussain, Dilshad ; Asrar, Shaz ; Qayoom, Amtul ; Ali, Saeeda Nadir

The study details the synthesis of quercetin-capped Au-Ag bimetallic nanoparticles (Qct-AuAg BMNps) in an aqueous environment.UV visible spectra showed absorbance peak of gold and bimetallic nanoparticles at 524 nm and 403 nm, resp.The SEM anal. of Qct-AuAg BMNps showed an average particle size of 67.5 nm with good uniformity (PdI: 0.386).FTIR confirmed the presence of resp. functional groups in Qct-AuAg BMNps.The Qct-AuAg BMNps were used as a colorimetric sensor for detecting calcium dobesilate monohydrate (CDM) in aqueous solutions, showing a linear spectrophotometric relationship with CDM concentration ranging from 0.000001 mM to 10 mM (R² = 0.9984).The detection and quantification limits were 1.66 x 10^-6 and 2.71 x 10^-5 mM, resp.The binding constant (K_a) was 9.8 x 10⁴ M^-1, with a 1:1 stoichiometry confirmed by Job's plot.The Qct-AuAg BMNps were successfully used to detect CDM in tap water and serum samples.The synthesis process was optimized using Box Behnken Design, with the optimal conditions found at 50°C, 2 mM quercetin, and a 5:1 silver-to-gold ratio.Therefore, the synthesized quercetin capped gold silver bimetallic nanoparticles were proved effective for the detection of CDM in liquid samples.

01 Jun 2025·Computers in Biology and Medicine

Advances in EEG-based detection of Major Depressive Disorder using shallow and deep learning techniques: A systematic review

Review

Author: Masroor, Komal ; Siddiqui, Sana Taj ; Kamran, Laiba ; Rehman, Hoorain ; Amanullah, Hafsa ; Rehman, Owais Ur ; Khan, Danish M

The contemporary diagnosis of Major Depressive Disorder (MDD) primarily relies on subjective assessments and self-reported measures, often resulting in inconsistent and imprecise evaluations. To address this issue and facilitate early intervention, there is a growing interest in utilizing objective criteria such as Electroencephalography (EEG) features analyzed through Artificial Intelligence (AI) techniques. This systematic review explores the advances in EEG-based detection of MDD using both shallow and deep learning methods, with the aim of enhancing understanding of the neural mechanisms underlying the disorder and identifying potential biomarkers for its diagnosis. Following PRISMA guidelines, a comprehensive search of the Scopus, IEEE Xplore, and ScienceDirect databases was conducted. The initial search yielded 5,603 articles; after rigorous screening and application of inclusion and exclusion criteria, 22 studies were deemed most relevant for this review. Key EEG markers, including frequency band power, EEG asymmetry, event-related potential (ERP) components, and functional and non-linear connectivity metrics, were examined. The findings affirm the utility of these measures in differentiating individuals with MDD from healthy controls. Despite these promising results, the review warrants the need for further research to enhance the interpretability of EEG metrics in the context of MDD. Future research directions are outlined to support the continued development of this emerging field.

100 Deals associated with Ned University of Engineering & Technology

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100 Translational Medicine associated with Ned University of Engineering & Technology

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Pipeline

Pipeline Snapshot as of 10 May 2025

The statistics for drugs in the Pipeline is the current organization and its subsidiaries are counted as organizations,Early Phase 1 is incorporated into Phase 1, Phase 1/2 is incorporated into phase 2, and phase 2/3 is incorporated into phase 3

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