Standard medical ethnobotany of Kohistan, North Pakistan.

Background: This study was exclusively focused on the documentation and cross-cultural evaluation of ethnomedicinal knowledge (EMK) within the diverse linguistic groups of Kohistan situated between the Himalayan and Hindukush Mountain ranges in the north Pakistan.

Methods: Data were gathered during the field survey (May 2022 to July 2023) through group conversations, semi-structured interviews, and on-site observation. Venn diagrams were employed to illustrate the comparative assessment of EMK, and different ethnobotanical indices were utilized to examine the data.

Crab (Charybdis natator) exoskeleton derived chitosan nanoparticles for the in vivo delivery of poorly water-soluble drug: Ibuprofen.

The study aims to extract and purify chitosan (CS) from the exoskeleton of crab (C. natator) and develop ibuprofen (IBU) encapsulated CS nanoparticles (IBU-CSNPs). Analysis of purified CS revealed characteristic functional and crystallinity peaks.

Angiotensin I-Converting Enzyme (ACE-I) Inhibition and Antioxidant Peptide from a Squilla Species.

Background: Oratosquilla woodmasoni is one of the marine squilla species, which is found in the entire Asia-Pacific region. This current study assesses the species as the main basis of both ACEi and antioxidant peptide.

Objective: To isolate the ACEi peptide derived from O.

Analysis and simulation of land cover changes and their impacts on land surface temperature in a lower Himalayan region.

Rapid urbanization is changing the existing patterns of Land Use Land Cover (LULC) globally which is consequently increasing the Land Surface Temperature (LST) in many regions. Present study was focused on estimating the current and simulating the future LULC and LST trends in the alpine environment of lower Himalayan region of Pakistan. Past patterns of LULC and LST were identified through the Support Vector Machine (SVM) and multi-spectral Landsat satellite images during 1987-2017 data period.

Content based medical image retrieval using topic and location model.

Background And Objective: Retrieval of medical images from an anatomically diverse dataset is a challenging task. Objective of our present study is to analyse the automated medical image retrieval system incorporating topic and location probabilities to enhance the performance.

Materials And Methods: In this paper, we present an automated medical image retrieval system using Topic and Location Model.

Surface modification of FeO and MgO nanoparticles with agrowastes for the treatment of chlorosis in .

Surface modification of nanoparticles for biological applications is receiving enormous interest among the research community due to the ability to alchemy the toxic nanoparticles into biocompatible compounds. In this study, the agrowastes of and were used to surface modify the magnesium oxide nanoparticles and ferric oxide nanoparticles respectively. The agrowaste amended magnesium oxide nano particles (AMNP) and agrowaste amended ferric oxide nanoparticles (AFNP) were characterized using scanning electron microscope, X-ray diffractometer, Fourier transformed-infra red spectroscope to justify the formation and surface modification of nanoparticles with the organic functional groups from the agro wastes.

DEEPAligner: Deep encoding of pathways to align epigenetic signatures.

Background And Objective: Recently, differential DNA Methylation is known to affect the regulatory mechanism of biological pathways. A pathway encompasses a set of interacting genes or gene products that altogether perform a given biological function. Pathways often encode strong methylation signatures that are capable of distinguishing biologically distinct subtypes.

An enhanced deterministic K-Means clustering algorithm for cancer subtype prediction from gene expression data.

Background: Clustering algorithms with steps involving randomness usually give different results on different executions for the same dataset. This non-deterministic nature of algorithms such as the K-Means clustering algorithm limits their applicability in areas such as cancer subtype prediction using gene expression data. It is hard to sensibly compare the results of such algorithms with those of other algorithms.

Identifying epigenetically dysregulated pathways from pathway-pathway interaction networks.

Background: Identification of pathways that show significant difference in activity between disease and control samples have been an interesting topic of research for over a decade. Pathways so identified serve as potential indicators of aberrations in phenotype or a disease condition. Recently, epigenetic mechanisms such as DNA methylation are known to play an important role in altering the regulatory mechanism of biological pathways.

A computational method for drug repositioning using publicly available gene expression data.

Motivation: The identification of new therapeutic uses of existing drugs, or drug repositioning, offers the possibility of faster drug development, reduced risk, lesser cost and shorter paths to approval. The advent of high throughput microarray technology has enabled comprehensive monitoring of transcriptional response associated with various disease states and drug treatments. This data can be used to characterize disease and drug effects and thereby give a measure of the association between a given drug and a disease.