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Heart failure (HF) contributes to increased hospital readmissions which results in amplified resource burden and morbidity. The conditions of readmission in HF patients have not been clarified. Objectives: To govern the relationship between heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction and correlation with readmissions ratio. Methods: This prospective cohort study was held in the Adult Cardiology department of Tabba Heart Institute, Karachi, Pakistan for 6 months from March 10, 2019 to September 9, 2019. After attaining informed consent, an interview and clinical examination were performed and subjects were divided into exposed and unexposed groups (HFpEF and HFrEF). Patients were followed for readmission within one-month of initial hospitalization. Results: A total of 162 patients with heart failure (81 patients in each group) were included in the study. The mean total age was 65.4 ± 10.4 years, and 52.5% of the patients were male. Rehospitalization on day 30 was observed in 11 (13.6%) patients from the Group A (HFpEF) and in 10 (12.3%) patients from the Group B(HFrEF). Cardiac readmission was more common in the unexposed group than in the exposed group (80.0% vs. 63.6%). Conclusions: After admission due to acute heart failure, patients with HFpEF have a statistically insignificantly higher hospitalization burden compared to patients with HFrEF. In addition, patients with HF with preserved ejection fraction were as likely to be readmitted for cardiovascular reasons as those with HF with reduced ejection fraction.

MirDIP is a well-established database that aggregates microRNA-gene human interactions from multiple databases to increase coverage, reduce bias, and improve usability by providing an integrated score proportional to the probability of the interaction occurring. In version 5.2, we removed eight outdated resources, added a new resource (miRNATIP), and ran five prediction algorithms for miRBase and mirGeneDB. In total, mirDIP 5.2 includes 46 364 047 predictions for 27 936 genes and 2734 microRNAs, making it the first database to provide interactions using data from mirGeneDB. Moreover, we curated and integrated 32 497 novel microRNAs from 14 publications to accelerate the use of these novel data. In this release, we also extend the content and functionality of mirDIP by associating contexts with microRNAs, genes, and microRNA–gene interactions. We collected and processed microRNA and gene expression data from 20 resources and acquired information on 330 tissue and disease contexts for 2657 microRNAs, 27 576 genes and 123 651 910 gene–microRNA–tissue interactions. Finally, we improved the usability of mirDIP by enabling the user to search the database using precursor IDs, and we integrated miRAnno, a network-based tool for identifying pathways linked to specific microRNAs. We also provide a mirDIP API to facilitate access to its integrated predictions. Updated mirDIP is available at https://ophid.utoronto.ca/mirDIP.

Middle-aged male known case of hypothyroidism presented with shortness of breath and hypoxia. Echo showed large RA myxoma with ASD causing right to left shunt.

Background: Type 2 diabetes mellitus is a progressive hyperglycemic ailment in which blood glucose level increases than the normal values. Eugenia jambolana has anti-hyperglycemic properties. Objective: The study aimed to evaluate the hypoglycemic effects of Eugenia jambolana in patients, suffering from type II diabetes. Study design: A control-experimental study was performed at the Department of Pharmacology, Liaquat University of Medical and Health Sciences Jamshoro for the duration of six months from February 2022 to July 2022. Material and Methods: Patients with type 2 diabetes mellitus, having fasting glucose level greater than 140mg/dl and patients having uncontrolled diabetes, despite being on the anti-diabetic drugs, were included in the study as study subjects. The control group was comprised of individuals with blood glucose levels in normal ranges and had no previous family history of diabetes mellitus. The extracts of Eungenia jambolana were administered to the study subjects as per the approved plan and after which the blood glucose levels were determined. Results: Blood glucose levels were reduced in the group of patients, who were not on any antidiabetic medication. Urinary glucose levels were also investigated and glycosuria was found to be reduced. Reduction in blood glucose was also observed in the group, which was on oral hypoglycemics and the glucose levels were dramatically reduced with high dose. Conclusion: The extract of Eungenia jambolana exhibited lowering of blood glucose levels in diabetes patients and treated diabetes mellitus. It may be used alone or in combination with other hypoglycemic drugs for the effective blood glucose reduction and treatment of the disease. Keywords: Eungenia jambolana, type 2 Diabetes Mellitus.

Background: Major Depressive Disorder (MDD) is the most severe form of depression and can be extremely debilitating for those afflicted. Treatment for MDD typically involves the use of antidepressant medications such as selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs). However, many patients do not respond adequately to these medications, leading to the use of adjunctive treatments, such as atypical antipsychotics. The combination of SSRIs and atypical antipsychotics has been found to be more effective than monotherapy with either medication alone. Aims: The Aim of this study is to compare the efficacy of two different combinations of antidepressants and atypical antipsychotics in the treatment of MDD: sertraline with aripiprazole, and paroxetine with aripiprazole. Study design and setting: Open-label trail. This study was conducted at Sir Cowasjee Jahangir Institute of Psychiatry & Behavioral Sciences, Hyderabad, Pakistan from October 2021 to October 2022. Materials and Methods: In this research trial, a total of 48 patients were randomized to receive either sertraline (100 mg/day) plus aripiprazole (5 mg/day) or paroxetine (20 mg/day) plus aripiprazole (5 mg/day) for a period of 6 weeks. The outcome measure was assessed by the change in Hamilton Depression Rating Scale (HDRS) score from baseline to 6 weeks. Data was analyzed statistically using SPSS version 26. Results: The overall mean age of patients with MDD was 36.52 ± 9.9 years; 56% female and 46% male were reported with MDD. There was a significant reduction in HDRS scores among both groups of drugs; however, no difference was found in terms of efficacy between the two groups. Conclusion: The combination therapy of aripiprazole augmentation, with the addition of either sertraline or paroxetine, was equally effective in patients with Major Depressive Disorder. Keywords: Major depressive disorder, MDD, Sertraline, Paroxetine, Aripiprazole, Augmentation therapy.

Aim: To assess the predictive features of optic neuritis in retinal loss through optic nerve lesion identification. Study design: Prospectively longitudinal study Place and duration of study: Ghulam Muhammad Mahar Medical College Sukkur and Shaheed Mohtarma Benazir Bhutto Medical University Larkana from 1st January 2021 to 30th June 2022. Methodology: One hundred and ten patients suffering from acute optic neuritis ≤8 weeks were enrolled. Retinal optical-coherence tomography was performed in all patients. Fifty five patients in the whole cohort while clinically isolated syndrome (CIS) 25 patients and relapsing remitting multiple sclerosis (RRMS) as well as neuromyelitis-optica spectrum disorders (NMOSD) and isolated optic neuritis as 20, 3 and 7 respectively. Brain optic nerve magnetic resonance imaging which included three-dimensional double inversion recovery sequence was also conducted at acute phase (M0) and then post 12 months (M12). Results: The mean age of the cases was 30.85±8.9 years. There was a higher frequency of males then females. The duration of the disease was found highest in RRMS cases with 50.31±77.45 months. The variance in estimated and standard error of the ganglion cell-inner plexiform layer volume change was significantly different in whole acute optic neuritis cases as well as the one with CIS and multiple sclerosisat cohort. Conclusion: Optic nerve-lesion length in prediction of retinal-neuroaxonal loss in cases of optic neuritis. The optic-nerve lesion length can also be considered as a biomarker for the process of retinal remodeling as well as visual impairment. Key words: Optic nerve lesion, Acute phase, Optic neuritis (ON), Retinal neuronal loss

Background: Lacosamide is a relatively newer drug for treatment of chronic diabetic painful neuropathy (CDPN). Objective: To analyse the effectiveness and safety of lacosamide in patients with diabetic neuropathy. Study Design: Randomized controlled clinical trial. Duration and Place of Study: This study was conducted at department of neurology, Khairpur Medical College, Khairpur Mir’s, during from the period Oct 2021 to March 2022. Methodology: Ninety-two patients of either gender, age 20-60 years, known case of diabetes mellitus for minimally 5 years having pain intensity in the range of 4-9 on 11-point (0–10) numerical rating scale & HbA1c value 6.1%-10% were included and assigned randomly (Lacosamide = 46 & Placebo = 46) after taking a valid informed/ written consent. Lacosamide 400 mg/ day was given upto 20 weeks which initially increased from baseline at rate of 100 mg per week. The primary outcome variable was changes from baseline in average pain scores. Results: The mean age of lacosamide group was 40.26±11.33 while in placebo group was 41.30±10.46 years. The mean Pretrial Pain Score measured on NRS of lacosamide group was 6.59±1.95 which decreased to 3.39±1.94 and in placebo group was 6.71±1.89 which decreased to 6.35±1.52 by the end of maintenance phase (20 weeks; p

Improved bioassays have significantly increased the rate of identifying new protein-protein interactions (PPIs), and the number of detected human PPIs has greatly exceeded early estimates of human interactome size. These new PPIs provide a more complete view of disease mechanisms but precise understanding of how PPIs affect phenotype remains a challenge. It requires knowledge of PPI context (e.g. tissues, subcellular localizations), and functional roles, especially within pathways and protein complexes. The previous IID release focused on PPI context, providing networks with comprehensive tissue, disease, cellular localization, and druggability annotations. The current update adds developmental stages to the available contexts, and provides a way of assigning context to PPIs that could not be previously annotated due to insufficient data or incompatibility with available context categories (e.g. interactions between membrane and cytoplasmic proteins). This update also annotates PPIs with conservation across species, directionality in pathways, membership in large complexes, interaction stability (i.e. stable or transient), and mutation effects. Enrichment analysis is now available for all annotations, and includes multiple options; for example, context annotations can be analyzed with respect to PPIs or network proteins. In addition to tabular view or download, IID provides online network visualization. This update is available at http://ophid.utoronto.ca/iid.

Purpose The continual onset of natural and manmade disasters propels the humanitarian supply chain (HSC) efforts (by organizations, groups and individuals) to always be on a stand-by mode with more and more sustainable solutions. Despite all the sincere and coordinated efforts from all the humanitarian agents and bodies, the likely sustainable outputs are hampered by certain barriers (impediments) which exist at different levels of the HSCs. A better understanding of such barriers and their mutual relationship is deemed helpful in improving the outcomes of humanitarian efforts. Thus, the purpose of this paper is to explore, refine, establish and classify these barriers which thwart the sustainable efforts of the HSCs individually as well as collectively. Design/methodology/approach An extensive literature review is conducted to identify these barriers which were followed by soliciting the experts’ inputs to update, refine and retain the contextually relevant ones. The opinions about the nine identified and refined barriers are taken from eight experts based in the Northern India who are having at least five years of experience in humanitarian operations. Fuzzy interpretive structural modeling (FISM) is used to examine and establish a hierarchical relationship among these barriers, whereas fuzzy Matrice d’impacts croisés multiplication appliquée á un classment analysis is carried out to further classify these barriers into dependent, autonomous, linkage and dependent barriers. Findings The analysis led to the formation of a FISM model where the operational challenges affecting the performance occupy the topmost position in the hierarchy. The results reveal that inconsistent motives, coordination and communication and operational challenges affecting the performance are the dependent, poor strategic planning, capacity-related challenges and poor performance measurement system are the autonomous, and financial challenges, locational challenges and lack of proper awareness are the independent barriers. Research limitations/implications The focus of the researchers was to study and examine these barriers to sustainable HSCs with special reference to the epidemics and pandemics (especially COVID-19), and it sheds light particularly arising during and post disaster phases. Practical implications The structural model contributed by this study is expected to be meaningful for practitioners besides enriching the body of literature. In the context of pandemics, it distinguishes itself from the other available frameworks. Social implications As this research has been carried out in the context of the novel COVID-19, the framework is expected to assist policymakers in comprehending the issues impeding the sustainability of noble humanitarian efforts. Thus, ultimately it is expected to contribute to the ultimate cause of society at large. Originality/value This research endeavor distinguishes itself from the other accessible published resources in terms of the specific context, the methodological approach and the nature of respondents. This paper concludes with the practical implications and directions for future research.

Sedimentary Rocks composing the Thar Lignite basin Pakistan are of clastic origin. These rocks have comparatively low uniaxial compressive strength (UCS) values, and hence recognized as ‘soft sedimentary rocks’ in this study. UCS is a fundamental property of rocks, used by mine design engineers in designing the surface and underground excavations. The purpose of this study is to investigate the relationship between UCS with Brazilian tensile strength (BTS), and index properties of soft sedimentary rock formations at Thar Lignite basin. Various correlations between mechanical and physical properties of rocks have been developed previously. However, no significant correlation has been developed on UCS with BTS and index properties for soft sedimentary rocks. Numerous Rock samples from Two complete geotechnical drillholes at Block-IX Thar Coalfield were selected. Standard test procedures were implemented to determine the UCS, indirect Tensile and index properties such as point load strength, and shore Scleroscope hardness. The correlations between rock properties were established using simple and multiple regression techniques, and empirical equations were obtained. These equations can be used to predict the UCS and tensile strength of soft sedimentary rocks by performing simple index tests; which are quick, economical, and easier to be performed on the site.

Objective: OsteoDIP aims to collect and provide, in a simple searchable format, curated high throughput RNA expression data related to osteoarthritis. Design: Datasets are collected annually by searching “osteoarthritis gene expression profile” in PubMed. Only publications containing patient data and a list of differentially expressed genes are considered. From 2020, the search has expanded to include non-coding RNAs. Moreover, a search in GEO for “osteoarthritis” datasets has been performed using ‘Homo sapiens' and ‘Expression profiling by array’ filters. Annotations for genes linked to osteoarthritis have been downloaded from external databases. Results: Out of 1204 curated papers, 63 have been included in OsteoDIP, while GEO curation led to the collection of 28 datasets. Literature data provides a snapshot of osteoarthritis research derived from 1924 human samples, while GEO datasets provide expression for additional 1012 patients. Similar to osteoarthritis literature, OsteoDIP data has been created mostly from studies focused on knee, and the tissue most frequently investigated is cartilage. GEO data sets were fully integrated with associated clinical data. We showcase examples and use cases applicable for translational research in osteoarthritis. Conclusions: OsteoDIP is publicly available at http://ophid.utoronto.ca/OsteoDIP. The website is easy to navigate and all the data is available for download. Data consolidation allows researchers to perform comparisons across studies and to combine data from different datasets. Our examples show how OsteoDIP can integrate with and improve osteoarthritis researchers’ pipelines.

Deep Neural Networks for object detection have become of significant interest with the substantial improvement in their efficiency and increase in their applications. However, training such a network requires a large annotated dataset, which is very expensive in term of time and human effort. In this context, several automatic image annotation solutions have been proposed which are dependent on rich visual features and thus suitable for color images only. On the other hand, recent experiments have proven that color cameras alone are not enough for pedestrian related applications and there is a need to use other visual sensors as well, such as thermal cameras. In this paper, we propose an automatic image annotation technique for pedestrian detection in thermal images using an adaptive background/foreground estimation model to train Faster-RCNN. The results presented in this paper, obtained through longterm experiments demonstrate the efficacy of our technique. The results also show that our proposed technique is be very useful to generate image annotations automatically and to train a deep neural network without having a manually annotated dataset for cameras with different modalities.