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Abstract Age-related macular degeneration (AMD), a complex neurodegenerative disease, is a leading cause of visual impairment worldwide with a strong genetic component. Genetic studies have identified several loci, but few causal genes with functional characterization. Here we highlight multiple lines of evidence which show a causal role in AMD for SLC16A8, which encodes MCT3, a retinal pigment epithelium (RPE) specific lactate transporter. First, in an unbiased, genome-wide analysis of rare coding variants we show multiple SLC16A8 rare variants are associated with AMD risk, corroborating previous borderline significant reports from AMD rare variant studies. Second, we report a novel SLC16A8 mutation in a three-generation family with early onset macular degeneration. Finally, mis-expression in multiple model organisms shows functional and anatomic retinal consequences. This study highlights the important role for SLC16A8 and lactate regulation towards outer retina/RPE health and highlights a potential new therapeutic opportunity for the treatment of AMD.

Abstract Cream cheese analogue is a soft cheese with a slightly sweet and pleasantly tangy taste. It is prepared using the substitutes of dairy fats and proteins partially or completely. Cream cheese analogue ingredients are purchased carefully keeping in mind the required specifications. For the above-mentioned research, different samples of cream cheese (T0, T1, T2 and T3) were manufactured with standardized fat and protein and the moisture was maintained at 50–55% during these trials. All ingredients were added in a large container for mixing and cooking treatment for 1–2 min at 75 °C and homogenized for 5–6 min with the help of a hand mixture until completely homogenous sample was obtained. Samples were then transferred in to another container and allowed them to attain temperature between 20 and 25 °C. After that, samples were incubated with the addition of mesophilic culture until desired pH (4.6–4.7) was achieved. Later samples were heated at 50–55 °C for 2–3 min and then placed in a muslin cloth and left overnight for whey drainage. Physicochemical, microbial analysis were performed while sensory evaluation was performed using different parameters and scales. Sample prepared using 75% dairy cream and 25% cocoa butter substitute fat (T1) showed good results. T1 had better consistency which was considered desirable characteristics of cream cheese. This research proved the cost effective as cream cheese prepared with plant-based fat which made its production possible at industrial level. Cream cheese which was made from dairy fat (75%) and cocoa butter substitute fat (25%) had more springiness, smoothness, gumminess, more pleasant taste, color, flavor and aroma than other samples. This dairy product can be used in future in Pakistan.

Abstract Strokes are a leading global cause of mortality, underscoring the need for early detection and prevention strategies. However, addressing hidden risk factors and achieving accurate prediction become particularly challenging in the presence of imbalanced and missing data. This study encompasses three imputation techniques to deal with missing data. To tackle data imbalance, it employs the synthetic minority oversampling technique (SMOTE). The study initiates with a baseline model and subsequently employs an extensive range of advanced models. This study thoroughly evaluates the performance of these models by employing k-fold cross-validation on various imbalanced and balanced datasets. The findings reveal that age, body mass index (BMI), average glucose level, heart disease, hypertension, and marital status are the most influential features in predicting strokes. Furthermore, a Dense Stacking Ensemble (DSE) model is built upon previous advanced models after fine-tuning, with the best-performing model as a meta-classifier. The DSE model demonstrated over 96% accuracy across diverse datasets, with an AUC score of 83.94% on imbalanced imputed dataset and 98.92% on balanced one. This research underscores the remarkable performance of the DSE model, compared to the previous research on the same dataset. It highlights the model's potential for early stroke detection to improve patient outcomes.

This paper examines the impact of the Monetary Policy Uncertainty (MPU) of the United States on Asian developed, emerging, and frontier stock markets using a Quantile-on-Quantile (QQR) approach by using monthly data from January 2006 to December 2022 of 14 Asian countries. The study finds that US monetary policy significantly negatively influences Asian stock markets. This is primarily due to the widespread use of the US dollar as a universal currency, resulting in substantial ripple effects on other nations through trade relationships. In Asian developed markets, MPU is negatively related to Australia and New Zealand. At the same time, it has a positive relationship with Hong Kong and Japan at the upper quantiles. Among Asian emerging markets, MPU negatively impacts Taiwan's, India's, and China's returns, increasing this negative relationship at higher MPU quantiles. Additionally, MPU has a significant negative relationship with Thailand, Indonesia, Korea, and Malaysia returns. In contrast, higher quantiles of MPU have no discernible impact on the Philippines stock returns. In Asian frontier markets, MPU negatively impacts Pakistan's and Sri Lanka's returns. The implications of these findings are twofold: for investors, this study provides valuable insights for hedging activities, allowing for more informed decisions based on the MPU of other countries to identify profitable stocks. For policymakers, this research aids in formulating effective monetary policy strategies. Furthermore, future studies can build upon these results by exploring other markets and comparing their outcomes with the findings presented in this study.

Abstract Background The integration of large language models (LLMs) like ChatGPT in diagnostic medicine, with a focus on digital pathology, has garnered significant attention. However, understanding the challenges and barriers associated with the use of LLMs in this context is crucial for their successful implementation. Methods A scoping review was conducted to explore the challenges and barriers of using LLMs, in diagnostic medicine with a focus on digital pathology. A comprehensive search was conducted using electronic databases, including PubMed and Google Scholar, for relevant articles published within the past four years. The selected articles were critically analyzed to identify and summarize the challenges and barriers reported in the literature. Results The scoping review identified several challenges and barriers associated with the use of LLMs in diagnostic medicine. These included limitations in contextual understanding and interpretability, biases in training data, ethical considerations, impact on healthcare professionals, and regulatory concerns. Contextual understanding and interpretability challenges arise due to the lack of true understanding of medical concepts and lack of these models being explicitly trained on medical records selected by trained professionals, and the black-box nature of LLMs. Biases in training data pose a risk of perpetuating disparities and inaccuracies in diagnoses. Ethical considerations include patient privacy, data security, and responsible AI use. The integration of LLMs may impact healthcare professionals’ autonomy and decision-making abilities. Regulatory concerns surround the need for guidelines and frameworks to ensure safe and ethical implementation. Conclusion The scoping review highlights the challenges and barriers of using LLMs in diagnostic medicine with a focus on digital pathology. Understanding these challenges is essential for addressing the limitations and developing strategies to overcome barriers. It is critical for health professionals to be involved in the selection of data and fine tuning of the models. Further research, validation, and collaboration between AI developers, healthcare professionals, and regulatory bodies are necessary to ensure the responsible and effective integration of LLMs in diagnostic medicine.

The main aim of this study is to investigate the opportunities, challenges, and barriers in implementing generative artificial intelligence (Gen AI) in personalized patient care plans (PPCPs). This systematic review paper provides a comprehensive analysis of the current state, potential applications, and opportunities of Gen AI in patient care settings. This review aims to serve as a key resource for various stakeholders such as researchers, medical professionals, and data governance. We adopted the PRISMA review methodology and screened a total of 247 articles. After considering the eligibility and selection criteria, we selected 13 articles published between 2021 and 2024 (inclusive). The selection criteria were based on the inclusion of studies that report on the opportunities and challenges in improving PPCPs using Gen AI. We found that a holistic approach is required involving strategy, communications, integrations, and collaboration between AI developers, healthcare professionals, regulatory bodies, and patients. Developing frameworks that prioritize ethical considerations, patient privacy, and model transparency is crucial for the responsible deployment of Gen AI in healthcare. Balancing these opportunities and challenges requires collaboration between wider stakeholders to create a robust framework that maximizes the benefits of Gen AI in healthcare while addressing the key challenges and barriers such as explainability of the models, validation, regulation, and privacy integration with the existing clinical workflows.

In the current study, seven (7) aurone derivatives (ADs) were synthesized and employed to in-vitro LOX and COX-2 assays, in-vivo models of acetic acid-induced mice writhing, formalin-induced mice paw licking and tail immersion test to evaluate their analgesic potential at the doses of 10 mg and 20 mg/kg body weight. Molecular docking was performed to know the active binding site at both LOX and COX-2 as compared to standard drugs. Among the ADs, 2-(3,4-dimethoxybenzylidene)benzofuran-3(2H)-one (WE-4)possessed optimal LOX and COX-2 inhibitory strength (IC50=0.30 μM and 0.22 μM) as compared to standard (ZileutonIC50 = 0.08 μM, CelecoxibIC50 = 0.05 μM). Similarly in various pain models compound WE-4 showed significantly (p

Globally, the occurrence of skin cancers has been increasing day by day due to unprotected skin and exposure to UV radiation. This research is focused toward the evaluation of the antioxidant potential of an OH-free flavanone derivative that was synthesized by using 1,4-diazabicyclo[2.2.2]octane–polyethylene glycol (DABCO-PEG) 400. Ionic liquid was prepared via the alkylation of DABCO using 1-pentyl bromide followed by mixing with PEG 400. The structure of the synthesized molecules was characterized through single-crystal XRD. The target flavanone, viz., 2-(4-isobutylphenyl)chroman-4-one, was subjected to free radical activity. In addition, in silico studies were carried out with proteins ribonucleotide reductase and tyrosinase and isobutyl containing flavanone, viz., 2-(4-isobutylphenyl)chroman-4-one. The flavanone 2-(4-isobutylphenyl)chroman-4-one showed significant inhibition at a concentration of 25 μg/ml compared to vitamin C, which was also supported by the molecular docking studies. The flavanones exhibit binding energies of −6.45 and −6.83 kcal/mol for ribonucleotide reductase and tyrosinase, respectively. The results were further validated by molecular dynamic simulations, which recommended that further investigation of this flavanone must be carried out before using it in potent drug discovery in the field of skin cancer.

In this study we presented a novel series of NNO tridentate ligands generating imino, amido and oxo donor pocket for Pd(II) coordination. All the compounds were meticulously characterized by elemental analysis and advanced spectroscopic techniques, including FTIR, proton and carbon NMR. The synthesized compounds underwent rigorous evaluation for their potential as anti-cancer agents, utilizing the aggressive breast cancer cell lines MDA-MB (ATCC) and MCF-7 as a crucial model for assessing growth inhibition in cancer cells. Remarkably, the MTT assay unveiled the robust anti-cancer activity for all palladium complexes against MDA-MB-231 and MCF-7 cells. Particularly, complex [Pd(L1)(CH3CN)] exhibited exceptional potency with an IC50 value of 25.50 ± 0.30 µM (MDA-MB-231) and 20.76 ± 0.30 µM (MCF-7), compared to respective 27.00 ± 0.80 µM and 24.10 ± 0.80 µM for cisplatin, underscoring its promising therapeutic potential. Furthermore, to elucidate the mechanistic basis for the anti-cancer effects, molecular docking studies on tyrosine kinases, an integral target in cancer research, were carried out. The outcome of these investigations further substantiated the remarkable anticancer properties inherent to these innovative compounds. This research offers a compelling perspective on the development of potent anti-cancer agents rooted in the synergy between ligands and Pd(II) complexes and presenting a promising avenue for future cancer therapy endeavors.

Abstract Objectives To examine the hypothesis that obesity complicated by the metabolic syndrome, compared to uncomplicated obesity, has distinct molecular signatures and metabolic pathways. Methods We analyzed a cohort of 39 participants with obesity that included 21 with metabolic syndrome, age-matched to 18 without metabolic complications. We measured in whole blood samples 754 human microRNAs (miRNAs), 704 metabolites using unbiased mass spectrometry metabolomics, and 25,682 transcripts, which include both protein coding genes (PCGs) as well as non-coding transcripts. We then identified differentially expressed miRNAs, PCGs, and metabolites and integrated them using databases such as mirDIP (mapping between miRNA-PCG network), Human Metabolome Database (mapping between metabolite-PCG network) and tools like MetaboAnalyst (mapping between metabolite-metabolic pathway network) to determine dysregulated metabolic pathways in obesity with metabolic complications. Results We identified 8 significantly enriched metabolic pathways comprising 8 metabolites, 25 protein coding genes and 9 microRNAs which are each differentially expressed between the subjects with obesity and those with obesity and metabolic syndrome. By performing unsupervised hierarchical clustering on the enrichment matrix of the 8 metabolic pathways, we could approximately segregate the uncomplicated obesity strata from that of obesity with metabolic syndrome. Conclusions The data suggest that at least 8 metabolic pathways, along with their various dysregulated elements, identified via our integrative bioinformatics pipeline, can potentially differentiate those with obesity from those with obesity and metabolic complications.

Abstract The popularity of cloud and fog services has raised the number of users exponentially. Main advantage of Cloud/fog infrastructure and services are crucial specially for commercial users from diverse areas. The variety of service requests with different deadlines makes the task of a service broker challenging. The fog and cloud users always lookfor a suitable compromise between cost and quality of service in terms of response time therefore, the cost optimization is vital for the cloud/fog service providers to capture the market. In this paper an algorithm, Cost Optimization in the cloud/fog environment based on Task Deadline (COTD) is proposed that optimizes cost without compromising the response time. In this algorithm the task deadline is considered as a constraint and an appropriate data center for task processing is selected. The proposed algorithm is suitable for runtime decision making due to its low complexity. The proposed algorithm is evluated using a well-known simulation tool Cloud Analyst. Our comprehensive testbed simulations show that COTD outperforms the existing schemes, Service Proximity Based Routing and Performance-Optimized Routing. The proposed algorithm successfully minimizes the cost by 35% on average while maintaining the response time.

Objectives: The aim of this study was to analyse the current use, identify challenges and barriers and propose a way forward for the use of the pager devices in the in-hospital communications. Methods: Initially, 447 studies were identified through database searching. After checking against the eligibility, 39 studies were included. Full-text records were retrieved and reviewed by two authors. After excluding unrelated studies and duplicate records, a total of 12 articles were selected for the final review. Results: The use of pagers often lacks standardisation, content, format, urgency level, and clarity within the message. Some studies reported that medical staff preferred in-person interactions with consults instead of communicating over the phone or pagers. Productive communication can reduce the turnaround time by up to 50%. The key challenges are; (1) data security and privacy, (2) timely acknowledgement of received communication, (3) lack of two-way communications causing issues in critical care situations and (4) there is no standard process for the in-hospital communications. Conclusion: We found that the clinicians’ age, experience, speciality and preferences greatly matter and influence the selection of tools and technology in healthcare. With revolutionary advances in technology, smartphones have inevitably become beneficial to healthcare, owing to multiple instant messaging applications (apps) that can streamline encrypted clinical communication between medical teams and could be safely used for in-hospital communications.

Objective: To evaluate children with Autism Spectrum Disorder (ASD) by using Common Brief Core Sets of International Classification of Functioning, Disability, and Health for Children and Youth (ICF-CY) Study Design: Cross-sectional study Place and Duration of Study: Department of Developmental-Behavioural Paediatrics, The Children’s Hospital and The Institute of Child Health, Lahore Pakistan, from Nov 2020 to Jan 2021. Methodology: This study included 48 children with Autism Spectrum Disorder aged 3-18 years. Common Brief, a Core Set of the international classification of functioning, disability, and health in children and youth (ICF-CY), was administered to assess their functional status. Strengths and weaknesses in body structure, body function, activity and participation and environmental factors were evaluated. Results: The functioning profile in all categories of body function, activities and participation showed severe impairment other than sleep, involuntary and voluntary functions, while complete impairment in complex interpersonal, recreational and leisure categories. Environmental factors were substantial facilitators 4(10%), moderate facilitators 6(15%), mild facilitators 3(7.5%), mild barriers 5(12.5%), moderate barriers 7(17.5%), severe barrier 1(2.5%) and complete barrier 5(12.5%) among children with Autism Spectrum Disorder (ASD). Conclusion: Common Brief, Core Set of ICF-CY, is a comprehensive and flexible tool which provides functional information about ASD children beyond the diagnosed criteria used for ASD. Keywords: Autism spectrum disorder (ASD), Common brief core set of the international classification of functioning, disability, and health in children and youth (ICF-CY), International classification of functioning, disability, and health in children and youth (ICF-CY).

Objective: To assess children with cerebral palsy using the Common Brief Core Set of International Classification of Functioning, Disability and Health for Children and Youth (ICF-CY). Study Design: Cross-sectional study Place and Duration of Study: Children Hospital & Institute of Child Health, Lahore Pakistan, from Nov 2020 to Jan 2021. Methodology: Fifty-nine children with cerebral palsy (CP) aged 0-18 years were included. Common Brief Core Set of International Classification of Functioning, Disability, and Health in Children and Youth (ICF-CY) was administered to children with cerebral palsy to assess their functional status. Strengths and weaknesses in body structure, body function,activity and participation and environmental factors were evaluated using the Common Brief Core Set of ICF-CY. Results: The majority of study participants were 38(64.4%), were spastic quadriplegic. Periventricular leukomalacia was noted in 36(67.9%) cases on MRI brain. Moderate to severe impairment was noted in body functions like intellectual function 46(78%). In addition, 26(44.1%) children with cerebral palsy had mild to moderate impairment in walking, while 4(6.8 %) could walk without any impairment. Social attitudes, construct, and design of buildings were the major barriers affecting the functionality of children with cerebral palsy. Conclusion: It was found that the Common Brief Core Set of ICF-CY in children with different types of cerebral palsy is a useful tool for assessing their functional level. Keywords: Cerebral Palsy, Common Brief Core Set, Disability, Health in Children and Youth (ICF-CY), International Classification of Functioning.

Objective: To see the impact of screen media usage on early childhood development. Study Design: Cross-sectional study. Place and Duration of study: Developmental Behavioural Paediatrics Department, Children’s Hospital and Institute of Child Health, Lahore Pakistan, from Oct to Dec 2020. Methodology: This study included 100 children with an age range between 15-36 months and divided into two groups. Group-1 was children with communication behaviour disorders (CBD) (n=50), and Group-2 was typically developing (TD)children (n=50). ShaMaq Developmental Screening Tool (SDST) was administered to children to screen their development.Childhood behaviours were rated on a scale of 0-10 on a Behaviour rating scale. Results: Children with CBD had poor eye contact, response to names, poor imitation, poor pointing and poor one-step command following (p

Objective: This study aimed to quantify the workload involved in patient monitoring by vital signs and early warning scores (EWS), and the time spent by a rapid response team locally known as the Patient-at-Risk (PaR) team in responding to deteriorating patients. Methods: The workload involved in the measurement and the documentation of vital signs and EWS was quantified by time and motion study using electronic stopwatch application in 167 complete sets of vital signs observations taken by nursing staff on general hospital wards at Taranaki Base Hospital, New Plymouth, New Zealand. The workload involved in responding to deteriorating patients was measured by the PaR team in real-time and recorded in an electronic logbook specifically designed for this purpose. Dependent variables were studied using analysis of variance (ANOVA), post hoc Tukey, Kruskal Wallis test, Mann-Whitney test and correlation tests. Results: The mean time to measure and record a complete set of vital signs including interruptions was 4:18 (95% CI: 4:07–4:28) minutes. After excluding interruptions, the mean time taken to measure and record a set of vital signs was 3:24 (95% CI: 3:15–3:33) minutes. We found no statistical difference between the observer, location of the patient, staff characteristics or experience and patient characteristics. PaR nurses' mean time to provide rapid response was 47:36 (95% CI: 44:57–50:15) minutes. Significantly more time was spent on patients having severe degrees of deterioration (higher EWS) < 0.001. No statistical difference was observed between ward specialty, and nursing shifts. Conclusions: Patient monitoring and response to deterioration consumed considerable time. Time spent in monitoring was not affected by independent and random factors studied; however, time spent on the response was greater when patients had higher degrees of deterioration.

Aims and objectives: This study investigated clinical staff perceptions of learning about current monitoring practices and the planned introduction of an electronic system for patient monitoring. The aim of this research was to evaluate the perceptions of clinical staff (nurses and doctors) about the perceived strengths and weaknesses of the current state of the rapid response system (RRS) and how those strengths and weakness would be affected by introducing an electronic RRS. Methods: This research applied a descriptive study methodology. Two detailed sessions on demonstration on the electronic RRS for measuring and recording vital signs and the electronic Early Warning System (EWS) were followed by two structured surveys administered through an online portal (SurveyMonkey) for nurses and doctors working at Taranaki District Health Board. The study was planned and conducted between October 2020 and May 2021 at Taranaki Base Hospital, New Plymouth, New Zealand. Results: We found that the perceptions of clinical staff were a combination of key practice issues with current manual monitoring, expectations of improved visibility of vital sign charts, better communication between staff and thus improved patient care with the introduction of an electronic system. A majority (24, 60%) of nurses reported that, when called to assess deteriorating patients, the responders arrive at bedside within 5–30 min and an additional 11 (27%) said the responders arrive within 5 min. That is a collective 87% responder arrival within 30 min Conclusion: Staff believe that an electronic RRS could improve communication, speed up decision making and have a positive impact on patient outcomes.

Abstract Aims/Introduction The progression from prediabetes to type 2 diabetes is preventable by lifestyle intervention and/or pharmacotherapy in a large fraction of individuals with prediabetes. Our objective was to develop a risk score to screen for prediabetes in the Middle East, where diabetes prevalence is one of the highest in the world. Materials and Methods In this cross‐sectional, case–control study, we used data of 4,895 controls and 2,373 prediabetic adults obtained from the Qatar Biobank cohort. Significant risk factors were identified by logistic regression and other machine learning methods. The receiver operating characteristic was used to calculate the area under curve, cut‐off point, sensitivity, specificity, positive and negative predictive values. The prediabetes risk score was developed from data of Qatari citizens, as well as long‐term (≥15 years) residents. Results The significant risk factors for the Prediabetes Risk Score in Qatar were age, sex, body mass index, waist circumference and blood pressure. The risk score ranges from 0 to 45. The area under the curve of the score was 80% (95% confidence interval 78–83%), and the cut‐off point of 16 yielded sensitivity and specificity of 86.2% (95% confidence interval 82.7–89.2%) and 57.9% (95% confidence interval 65.5–71.4%), respectively. Prediabetes Risk Score in Qatar performed equally in Qatari nationals and long‐term residents. Conclusions Prediabetes Risk Score in Qatar is the first prediabetes screening score developed in a Middle Eastern population. It only uses risk factors measured non‐invasively, is simple, cost‐effective, and can be easily understood by the general public and health providers. Prediabetes Risk Score in Qatar is an important tool for early detection of prediabetes, and can help tremendously in curbing the diabetes epidemic in the region.

BackgroundObesity-associated dysglycemia is associated with metabolic disorders. MicroRNAs (miRNAs) are known regulators of metabolic homeostasis. We aimed to assess the relationship of circulating miRNAs with clinical features in obese Qatari individuals.MethodsWe analyzed a dataset of 39 age-matched patients that includes 18 subjects with obesity only (OBO) and 21 subjects with obesity and metabolic syndrome (OBM). We measured 754 well-characterized human microRNAs (miRNAs) and identified differentially expressed miRNAs along with their significant associations with clinical markers in these patients.ResultsA total of 64 miRNAs were differentially expressed between metabolically healthy obese (OBO) versus metabolically unhealthy obese (OBM) patients. Thirteen out of 64 miRNAs significantly correlated with at least one clinical trait of the metabolic syndrome. Six out of the thirteen demonstrated significant association with HbA1c levels; miR-331-3p, miR-452-3p, and miR-485-5p were over-expressed, whereas miR-153-3p, miR-182-5p, and miR-433-3p were under-expressed in the OBM patients with elevated HbA1c levels. We also identified, miR-106b-3p, miR-652-3p, and miR-93-5p that showed a significant association with creatinine; miR-130b-5p, miR-363-3p, and miR-636 were significantly associated with cholesterol, whereas miR-130a-3p was significantly associated with LDL. Additionally, miR-652-3p’s differential expression correlated significantly with HDL and creatinine.ConclusionsMicroRNAs associated with metabolic syndrome in obese subjects may have a pathophysiologic role and can serve as markers for obese individuals predisposed to various metabolic diseases like diabetes.

Objective: To determine the risk factors in children presenting with developmental delay coming to the tertiary care hospital. Study Design: Case control study. Place and Duration of Study: The Children’s Hospital and Institute of Child Health, Lahore, from Nov 2018 to Jan 2019. Methodology: This was a case control study that included 280 children aged 6 months to 5 years. All children were assessed on ShaMaq Developmental Inventory in four equal groups of age ranges 6-10 months, 18-24 months, 3-3.5 years and 4-4.5 years. Demographic information was gathered through specially designed questionnaire that included risk factors such as gestational age, nutritional status of child, family income and others. Different risk factors were then compared between children with developmental delay and normal development. Results: Results found that there were more delays in male children (p

This research work depicts the importance of implementing those punishment Islam prescribed against physical injury. Those punishments which involve physical injuries are mainly focused. After establishing the validity of Islamic punishments, the writer has elaborated the punishment of those who kill or cause injuries to others unintentionally. Considering the sensitivity of legal retribution Muslim jurists have set forth certain conditions which must be met before decreeing any capital punishment. According the writer Islamic punishments hold the features of all contemporary theories namely; deterrent, preventive, retributive or reformative etc. This work has addressed the following questions: How much importance does Islam give to peace and order? How for Islamic penalties play a role in keeping peace in a society? How Islam has a different perspective as compared to secular schools of punishments? What conditions Islam prescribes for implementation of any punishment? How Islam distinguishes between a deliberate killing and killing by mistake? What are the conditions of implementing legal retribution? What is the overall impact of an Islamic punishment? Relying upon quantitative method the writer attempts to elucidate on those propositions which were not clear otherwise. He relied upon those texts only which were authentic and unambiguous. Each topic is discussed in the light of different Islamic schools of thought. The researcher has added his own opinion as well where it is necessary to illuminate the subject.

Over 1,500 variants in the ABCA4 locus cause phenotypes ranging from severe, early-onset retinal degeneration to very late-onset maculopathies. The resulting ABCA4/Stargardt disease is the most prevalent Mendelian eye disorder, although its underlying clinical heterogeneity, including penetrance of many alleles, are not well-understood. We hypothesized that a share of this complexity is explained by trans-modifiers, i.e., variants in unlinked loci, which are currently unknown. We sought to identify these by performing exome sequencing in a large cohort for a rare disease of 622 cases and compared variation in seven genes known to clinically phenocopy ABCA4 disease to cohorts of ethnically matched controls. We identified a significant enrichment of variants in 2 out of the 7 genes. Moderately rare, likely functional, variants, at the minor allele frequency (MAF) 25, were enriched in ROM1, where 1.3% of 622 patients harbored a ROM1 variant compared to 0.3% of 10,865 controls (p = 2.41E04; OR 3.81 95% CI [1.77; 8.22]). More importantly, analysis of common variants (MAF>0.1) identified a frequent haplotype in PRPH2, tagged by the p.Asp338 variant with MAF = 0.21 in the matched general population that was significantly increased in the patient cohort, MAF 0.25, p = 0.0014. Significant differences were also observed between ABCA4 disease subgroups. In the late-onset subgroup, defined by the hypomorphic p.Asn1868Ile variant and including c.4253+43G>A, the allele frequency for the PRPH2 p.Asp338 variant was 0.15 vs 0.27 in the remaining cohort, p = 0.00057. Known functional data allowed suggesting a mechanism by which the PRPH2 haplotype influences the ABCA4 disease penetrance. These associations were replicated in an independent cohort of 408 patients. The association was highly statistically significant in the combined cohorts of 1,030 cases, p = 4.00E-05 for all patients and p = 0.00014 for the hypomorph subgroup, suggesting a substantial trans-modifying role in ABCA4 disease for both rare and common variants in two unlinked loci.

The aim of this study was to document the university faculty members' views related to digital education during the COVID-19 pandemic and subsequently its influence on students' academic performance, encountered obstacles, and recognized prospects. A concurrent triangulation strategy by employing (QUAN+QUAL) mixed method design was used in this research. A survey was conducted to solicit perspectives of 242 university faculty members in six public sector universities selected through a stratified random sampling technique to ensure representation of geographical regions and gender. Survey focussed on ascertaining faculty members' readiness, institutional preparedness, and difficulties of online mode of delivery. Survey was followed by qualitative data collection in the form of narrations of feelings, personal experiences, challenges faced and suggestions to make online mode more effective. Data were analysed by computing descriptive statistics, mean response values of responses. The study found that faculty members expressed concerns about their readiness and satisfaction with online learning. They utilized various communication methods and assessment strategies, highlighting their adaptability. Key challenges included time management, internet connectivity, and technical issues. Achieving success in online programs necessitates reliable internet connectivity, adept time management skills, and mitigation of power disruptions Gender did not significantly affect gadget accessibility, understanding of online classes, or preferences for future online education. In conclusion, faculty members faced challenges with readiness, time management, and internet connectivity during the shift to online education but showed adaptability through diverse communication and assessment methods. To enhance digital education, institutions should improve internet infrastructure, off er time management training, and address technical issues. Gender did not significantly impact access to technology or preferences for online learning.

We performed FMEA on the existing RRS with the help of routine users of the RRS who acted as subject matter experts and evaluated the failures for their criticality using the Risk Priority Number approach based on their experience of the RRS. The FMEA found 35 potential failure modes and 101 failure mode effects across 13 process steps of the RRS. The afferent limb of RRS was found to be more prone to these failures (62, 61.4%) than the efferent limb of the RRS (39, 38.6%). Modification of calling criteria (12, 11.9%) and calculation of New Zealand Early Warning Scores (NZEWS) calculation (11, 10.9%) steps were found to potentially give rise to the highest number of these failures. Causes of these failures include human error and related factors (35, 34.7%), staff workload/staffing levels (30, 29.7%) and limitations due to paper-based charts and organisational factors (n = 30, 29.7%). The demonstrated electronic system was found to potentially eliminate or reduce the likelihood of 71 (70.2%) failures. The failures not eliminated by the electronic RRS require targeted corrective measures including scenario-based training and education, and revised calling criteria to include triggers for hypothermia and high systolic blood pressure.

BACKGROUND Outcome measures sensitive to disease progression are needed for ATP-binding cassette, sub-family A, member 4–associated (ABCA4-associated) retinopathy. We aimed to quantify ellipsoid zone (EZ) loss and photoreceptor degeneration beyond EZ-loss in ABCA4-associated retinopathy and investigate associations between photoreceptor degeneration, genotype, and age.METHODS We analyzed 132 eyes from 66 patients (of 67 enrolled) with molecularly confirmed ABCA4-associated retinopathy from a prospective natural history study with a median [IQR] follow-up of 4.2 years [3.1, 5.1]. Longitudinal spectral-domain optical coherence tomography volume scans (37 B-scans, 30° × 15°) were segmented using a deep learning (DL) approach. For genotype-phenotype analysis, a model of ABCA4 variants was applied with the age of criterion EZ-loss (6.25 mm2) as the dependent variable.RESULTS Patients exhibited an average (square-root-transformed) EZ-loss progression rate of [95% CI] 0.09 mm/y [0.06, 0.11]. Outer nuclear layer (ONL) thinning extended beyond the area of EZ-loss. The average distance from the EZ-loss boundary to normalization of ONL thickness (to ±2 z score units) was 3.20° [2.53, 3.87]. Inner segment (IS) and outer segment (OS) thinning was less pronounced, with an average distance from the EZ-loss boundary to layer thickness normalization of 1.20° [0.91, 1.48] for the IS and 0.60° [0.49, 0.72] for the OS. An additive model of allele severity explained 52.7% of variability in the age of criterion EZ-loss.CONCLUSION Patients with ABCA4-associated retinopathy exhibited significant alterations of photoreceptors outside of EZ-loss. DL-based analysis of photoreceptor laminae may help monitor disease progression and estimate the severity of ABCA4 variants.TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT01736293.FUNDING National Eye Institute Intramural Research Program and German Research Foundation grant PF950/1-1.

The present study advocates the combined experimental and computational study of metal-based aminothiazole-derived Schiff base ligands. The structure and electronic properties of ligands have been experimentally studied by spectroscopic methods (UV-Vis, FT-IR, 1H-NMR and 13C-NMR), mass spectrometry, elemental analysis and theoretically by density function theory (DFT). Computational calculations employing the B3LYP/6-31 + G(d,p) functional of DFT were executed to explore the optimized geometrical structures of ligands along with geometric parameters, molecular electrostatic potential (MEP) surfaces and frontier molecular orbital (FMO) energies. Global reactivity parameters estimated from FMO energy gaps signified the bioactive nature of ligands. The synthesized ligands were used for chelation with 3d-transition metals [VO(IV), Cr(III), Fe(II), Co(II), Ni(II), Cu(II) and Zn(II)] in 1 : 2 (metal : ligand) molar ratio. The spectral and magnetic results confirmed the formation of octahedral geometry around all the divalent and trivalent metal centres, whereas the tetravalent vanadyl centres were confirmed to have square-pyramidal geometry. All the as-synthesized compounds were investigated for in vitro antibacterial potential against two Gram-negative (Salmonella typhimurium and Escherichia coli) and two Gram-positive (Bacillus subtilis and Staphylococcus aureus) bacteria. Antibacterial assay results displayed pronounced activity, and their activity is comparable to that of a standard drug (streptomycin). The antioxidant potential of these compounds was assessed by employing diphenyl picryl hydrazide radical scavenging activity. The results displayed that all the metal chelates have exhibited more bioactivity in contrast with free ligands. The chelation was the main reason for their enhanced bioactivity. These results indicated that the thiazole metal-based compounds could be exploited as antioxidant and antimicrobial candidates.

Detection and estimation of t-wave alternans (TWA) in presence of indispensable physiological artifacts is still a challenging task, as in most of the cases, the signal of interest resides well below the noise levels. In this paper, a generalized detection theoretic framework (GDFT) is proposed for the detection and estimation of TWA from the stress test ECG signal. The analytical foundations, TWA signal modeling, and finally simulations of nine TWA detectors and estimators belonging to median match filtering, empirical mode decomposition (EMD) based match filtering, and generalized likelihood ratio test (GLRT) for GDTF are presented. GLRT schemes require noise statistics for parameter estimation and are computationally efficient. GLRT detectors outperform all the detectors including the benchmark spectral method by ≥ 2 dB for a broad spectrum of SNR ranging from -15 dB to 30 dB under Gaussian noise. EMD based strategies also outperform spectral method under Gaussian and Laplacian noise by ≥ 1 dB.

In the era of web 2.0, online forums, blogs and Twitter are becoming primary sources for sharing views, opinions and comments about different topics. Classifying these views, opinions and comments is known as sentiment analysis which is an active research area. Sentiment analysis has vast applications in different fields of life, such as marketing, e-commerce and business. Under the umbrella of sentiment analysis, sentiment quantification that deals with estimating relative frequency of class of interest is being investigated by researchers nowadays. In sentiment quantification, exploring effect of new features and comparison of diverse types of classifiers to assess their effectiveness needs further investigation. In this paper, we explore diverse feature sets and classifiers for sentiment quantification. In addition, empirical performance analysis of conventional machine learning techniques, ensemble-based methods and state-of-the-art deep learning algorithms on basis of features set, is performed. The computed results show that the diverse features sets affect the performance of classifiers in sentiment quantification. The results also confirm that the deep learning techniques perform better than the conventional machine learning algorithms.

Objective: To assess and compare level of knowledge of doctors and allied health professionals working with cerebral palsy children at the Children‟s Hospital, Lahore regarding use of ICF-CY Study Design: Comparative - cross sectional study. Place and Duration of Study: The Children‟s Hospital and Institute of Child Health, Lahore, from Jan 2017 to Mar 2017. Methodology: Sixty two professionals, 31 doctors and 31 allied health professionals, who were primarily involved in rehabilitation of children with cerebral palsy were included. Detailed information was taken from these professionals regarding their baseline knowledge for the use of ICF-CY in children with cerebral palsy using comprehensive core set of ICF-CY. Tutorial sessions were conducted for creating awareness of ICF-CY. Same information was recorded again and level of knowledge was assessed. Post tutorial comparison was made between the knowledge of two groups by applying t-test. Results: Study showed that participants had fair knowledge of use of different constructs of ICY-CY in children with cerebral palsy after conducting tutorial sessions. There was increase in knowledge in all constructs after tutorials but marked change was observed in Activities & participation. Level of knowledge was 3.4 in both groups. It was increased up to 4.9 by doctors and 4.8 by allied health professionals. No significant difference was found among knowledge of these two groups for all constructs. Conclusion: Different professionals working with cerebral palsy children at the Children‟s Hospital, Lahore were able to use ICF-CY competently to acquire information as they gained sufficient similar level of knowledge in all subsets after getting tutorials.

Non-alcoholic fatty liver disease (NAFLD) is a common liver lesion that is untreatable with medications. Glucagon-like peptide-1 receptor (GLP-1R) agonists have recently emerged as a potential NAFLD pharmacotherapy. However, the molecular mechanisms underlying these drugs’ beneficial effects are not fully understood. Using Fourier transform infrared (FTIR) spectroscopy, we sought to investigate the biochemical changes in a steatosis cell model treated or not with the GLP-1R agonist Exendin-4 (Ex-4). HepG2 cells were made steatotic with 400 µM of oleic acid and then treated with 200 nM Ex-4 in order to reduce lipid accumulation. We quantified steatosis using the Oil Red O staining method. We investigated the biochemical alterations induced by steatosis and Ex-4 treatment using Fourier transform infrared (FTIR) spectroscopy and chemometric analyses. Analysis of the Oil Red O staining showed that Ex-4 significantly reduces steatosis. This reduction was confirmed by FTIR analysis, as the phospholipid band (C=O) at 1740 cm−1 in Ex-4 treated cells is significantly decreased compared to steatotic cells. The principal component analysis score plots for both the lipid and protein regions showed that the untreated and Ex-4-treated samples, while still separated, are clustered close to each other, far from the steatotic cells. The biochemical and structural changes induced by OA-induced lipotoxicity are at least partially reversed upon Ex-4 treatment. FTIR and chemometric analyses revealed that Ex-4 significantly reduces OA-induced lipid accumulation, and Ex-4 also restored the lipid and protein biochemical alterations caused by lipotoxicity-induced oxidative stress. In combination with chemometric analyses, FTIR spectroscopy may offer new approaches for investigating the mechanisms underpinning NAFLD.

Dark cone photoreceptors, defined as those with diminished or absent reflectivity when observed with adaptive optics (AO) ophthalmoscopy, are increasingly reported in retinal disorders. However, their structural and functional impact remain unclear. Here, we report a 3-year longitudinal study on a patient with oligocone trichromacy (OT) who presented with persistent, widespread dark cones within and near the macula. Diminished electroretinogram (ERG) cone but normal ERG rod responses together with normal color vision confirmed the OT diagnosis. In addition, the patient had normal to near normal visual acuity and retinal sensitivity. Occasional dark gaps in the photoreceptor layer were observed on optical coherence tomography, in agreement with reflectance AO scanning light ophthalmoscopy, which revealed that over 50% of the cones in the fovea were dark, increasing to 74% at 10° eccentricity. In addition, the cone density was 78% lower than normal histologic value at the fovea, and 20–40% lower at eccentricities of 5–15°. Interestingly, color vision testing was near normal at locations where cones were predominantly dark. These findings illustrate how a retina with predominant dark cones that persist over at least 3 years can support near normal central retinal function. Furthermore, this study adds to the growing evidence that cones can continue to survive under non-ideal conditions.

Schiff bases are a class of organic compounds with azomethine moiety, exhibiting a wide range of biological potentials. In this research, six chiral Schiff bases, three ‘S’ series (H1–H3) and three ‘R’ series (H4–H6), were synthesized. The reaction was neat, which means without a solvent, and occurred at room temperature with a high product yield. The synthesized compounds were evaluated for analgesic potential in vivo at doses of 12.5 and 25 mg/kg using acetic-acid-induced writhing assay, formalin test, tail immersion and hot plate models, followed by investigating the possible involvement of opioid receptors. The compounds H2 and H3 significantly (*** p < 0.001) reduced the writhing frequency, and H3 and H5 significantly (*** p < 0.001) reduced pain in both phases of the formalin test. The compounds H2 and H5 significantly (*** p < 0.001) increased latency at 90 min in tail immersion, while H2 significantly (*** p < 0.001) increased latency at 90 min in the hot plate test. The ‘S’ series Schiff bases, H1–H3, were found more potent than the ‘R’ series compounds, H4–H6. The possible involvement of opioid receptors was also surveyed utilizing naloxone in tail immersion and hot plate models, investigating the involvement of opioid receptors. The synthesized compounds could be used as alternative analgesic agents subjected to further evaluation in other animal models to confirm the observed biological potential.

The concept of the internet of things (IoT) motivates us to connect bulk isolated heterogeneous devices to automate report generation without human interaction. Energy-efficient routing algorithms help to prolong the network lifetime of these energy-restricted smart devices that are connected by means of wireless sensor networks (WSNs). Current vendor-level advancements enable algorithm-level flexibility to design protocols to concurrently collect multiple application data while enforcing the reduction of energy expenditure to gain commercial success in the industrial stage. In this paper, we propose a hybrid clustering and routing algorithm with threshold-based data collection for heterogeneous wireless sensor networks. In our proposed model, homogeneous and heterogeneous nodes are deployed within specific regions. To reduce unnecessary data transmission, threshold-based conditions are presented to prevent unnecessary transmission when minor or no change is observed in the simulated and real-world applications. We further extend our proposed multi-hop model to achieve more network stability in dense and larger network areas. Our proposed model shows enhancement in terms of load balancing and end-to-end delay as compared to the other threshold-based energy-efficient routing protocols, such as the threshold-sensitive stable election protocol (TSEP), threshold distributed energy-efficient clustering (TDEEC), low-energy adaptive clustering hierarchy (LEACH), and energy-efficient sensor network (TEEN).

Coronary heart disease (CHD) is a major cause of death in Middle Eastern (ME) populations, with current studies of the metabolic fingerprints of CHD lacking in diversity. Identification of specific biomarkers to uncover potential mechanisms for developing predictive models and targeted therapies for CHD is urgently needed for the least-studied ME populations. A case-control study was carried out in a cohort of 1001 CHD patients and 2999 controls. Untargeted metabolomics was used, generating 1159 metabolites. Univariate and pathway enrichment analyses were performed to understand functional changes in CHD. A metabolite risk score (MRS) was developed to assess the predictive performance of CHD using multivariate analysis and machine learning. A total of 511 metabolites were significantly different between the CHD patients and the controls (FDR p < 0.05). The enriched pathways (FDR p < 10−300) included D-arginine and D-ornithine metabolism, glycolysis, oxidation and degradation of branched chain fatty acids, and sphingolipid metabolism. MRS showed good discriminative power between the CHD cases and the controls (AUC = 0.99). In this first study in the Middle East, known and novel circulating metabolites and metabolic pathways associated with CHD were identified. A small panel of metabolites can efficiently discriminate CHD cases and controls and therefore can be used as a diagnostic/predictive tool.

Currently, information and communication technology (ICT) allows health institutions to reach disadvantaged groups in rural areas using sensing and artificial intelligence (AI) technologies. Applications of these technologies are even more essential for maternal and infant health, since maternal and infant health is vital for a healthy society. Over the last few years, researchers have delved into sensing and artificially intelligent healthcare systems for maternal and infant health. Sensors are exploited to gauge health parameters, and machine learning techniques are investigated to predict the health conditions of patients to assist medical practitioners. Since these healthcare systems deal with large amounts of data, significant development is also noted in the computing platforms. The relevant literature reports the potential impact of ICT-enabled systems for improving maternal and infant health. This article reviews wearable sensors and AI algorithms based on existing systems designed to predict the risk factors during and after pregnancy for both mothers and infants. This review covers sensors and AI algorithms used in these systems and analyzes each approach with its features, outcomes, and novel aspects in chronological order. It also includes discussion on datasets used and extends challenges as well as future work directions for researchers.

A series of different substituted terpyridine (tpy)-based ligands have been synthesized by Kröhnke method. Their binding behaviour was evaluated by complexing them with Co(II), Fe(II) and Zn(II) ions, which resulted in interesting coordination compounds with formulae, [Zn(tpy)2]PF6, [Co(tpy)2](PF6)2, [Fe(tpy)2](PF6)2 and interesting spectroscopic properties. Their absorption and emission behaviours in dilute solutions were investigated in order to explain structure–property associations and demonstrate the impact of different aryl substituents on the terpyridine scaffold as well as the role of the metal on the complexes. Photo-luminescence analysis of the complexes in acetonitrile solution revealed a transition from hypsochromic to bathochromic shift. All the compounds displayed remarkable photo-luminescent properties and various maximum emission peaks owing to the different nature of the functional groups. Furthermore, the anti-microbial potential of ligands and complexes was evaluated with docking analyses carried out to investigate the binding affinity of terpyridine-based ligands along with corresponding proteins (shikimate dehydrogenase and penicillin-binding protein) binding sites. To obtain further insight into molecular orbital distributions and spectroscopic properties, density functional theory calculations were performed for representative complexes. The photophysical activity and interactions between chromophore structure and properties were both investigated experimentally as well as theoretically.

Abstract Background Human tissues are invaluable resources for researchers worldwide. Biobanks are repositories of such human tissues and can have a strategic importance for genetic research, clinical care, and future discoveries and treatments. One of the aims of Qatar Biobank is to improve the understanding and treatment of common diseases afflicting Qatari population such as obesity and diabetes. Methods In this study we apply a panorama of state-of-the-art statistical methods and machine learning algorithms to investigate associations and risk factors for diabetes and obesity on a sample of 1000 Qatari population. Results Regarding diabetes, we identified pronounced associations and risk factors in Qatari population including magnesium, chloride, c-peptide of insulin, insulin, and uric acid. Similarly, for obesity, significant associations and risk factors include insulin, c-peptide of insulin, albumin, and uric acid. Moreover, our study has revealed interactions of hypomagnesemia with HDL-C, triglycerides, and free thyroxine. Conclusions Our study strongly confirms known associations and risk factors associated with diabetes and obesity in Qatari population as previously found in other population studies in different parts of the world. Moreover, interactions of hypomagnesemia with other associations and risk factors merit further investigations.

Teh ultrasound-assisted magnetic stirrer was used as an effective extraction technique for teh evaluation of total phenolic contents (TPC) and antioxidant potential of ten Pakistani brown rice cultivars. For this purpose, ultrasonic (240W frequency 50/60 Hertz) assisted magnetic stirrer coupled with three solvents methanol, ethanol, and isopropanol in pure and aqueous fractions (80:20) were used for teh extraction of brown rice material. Teh extract yields of brown rice were obtained from 1.62 g/100g to 3.67 g/100g for all teh varieties. Aqueous isopropanol preferably and methanol (80:20) showed best extraction yields on teh dry mass basis of brown rice. Teh contents of total phenolics were determined as highest (496.9 mg GAE/kg) in Basmati Pak while lowest (137.7 mg GAE /kg) in non-basmati Irri-6 variety. For antioxidant activity, brown rice extracts of Basmati Pak showed teh best potential at IC50 2.19 mg/mL against DPPH radical scavenging. Reducing teh power of Basmati Pak was found highest at 0.85. Brown rice extract of Basmati 515 showed best ferrous ion metal chelation at 5.78 Eq. EDTA mg/100g.

Directed evolution of enzymes consists of an iterative process of creating mutant libraries and choosing desired phenotypes through screening or selection until the enzymatic activity reaches a desired goal. The biggest challenge in directed enzyme evolution is identifying high-throughput screens or selections to isolate the variant(s) with the desired property. We present in this paper a computational metabolic engineering framework, Selection Finder (SelFi), to construct a selection pathway from a desired enzymatic product to a cellular host and to couple the pathway with cell survival. We applied SelFi to construct selection pathways for four enzymes and their desired enzymatic products xylitol, D-ribulose-1,5-bisphosphate, methanol, and aniline. Two of the selection pathways identified by SelFi were previously experimentally validated for engineering Xylose Reductase and RuBisCO. Importantly, SelFi advances directed evolution of enzymes as there is currently no known generalized strategies or computational techniques for identifying high-throughput selections for engineering enzymes.

Traumatic brain injury (TBI) can be defined as a disorder in the function of the brain after a bump, blow, or jolt to the head, or penetrating head injury. Mild traumatic brain injury (mTBI) can cause devastating effects, such as the initiation of long-term neurodegeneration in brain tissue. In the current study, the effects of mTBI were investigated on rat brain regions; cortex (Co) and corpus callosum (CC) after 24 h (subacute trauma) by Fourier transform infrared (FTIR) imaging and immunohistochemistry (IHC). IHC studies showed the formation of amyloid-β (Aβ) plaques in the cortex brain region of mTBI rats. Moreover, staining of myelin basic protein presented the shearing of axons in CC region in the same group of animals. According to FTIR imaging results, total protein and lipid content significantly decreased in both Co and CC regions in mTBI group compared to the control. Due to this significant decrease in both lipid and protein content, remarkable consistency in lipid/protein band ratio in mTBI and control group, was observed. Significant decrease in methyl content and a significant increase in olefinic content were observed in Co and CC regions of mTBI rat brain tissues. Classification amongst distinguishable groups was performed using principal component analysis (PCA) and hierarchical clustering (HCA). This study established the prospective of FTIR imaging for assessing biochemical changes due to mTBI with high sensitivity, precision and high-resolution.

The impact and productivity of researchers are assessed using bibliometric parameters, such as the number of publications and citation analysis. A number of indices exist that use these parameters, but almost all of them overlook citation pattern of the researchers, which results in assigning the same index value to the two different authors with different citation patterns. In this paper, a new index called DS-index is proposed, which differentiates among the authors having even a very small change in the citation pattern of their publications. It uniquely identifies the different index values and thus the proper ranking order for authors. The index is applied to the self-developed large DBLP data set having publication data of over 50 years. The results compared with the existing indices using the standard performance evaluation measures confirm that the proposed index performs better by ranking the authors in a distinctive order.

Background: Guillian Barre Syndrome (GBS) is an acute inflammatory demyelinating polyneuropathy that is characterized by progressive symmetric ascending muscle weakness, hyporeflexia with or without sensory or autonomic symptoms and paralysis; however, variants involving the cranial nerves or pure motor involvement are not uncommon. The main characteristic features of GBS is muscles weakness or paralysis. Objective: To evaluate the frequency, type and severity of fine motor impairments in patients with Guillian Barre Syndrome. Methodology: A cross sectional survey was conducted through questionnaire and manual ability assessment tool to find out the frequency, type and severity of fine motor impairments in patients with GBS.The data was collected from Occupational Therapy Department of Pakistan Society of Rehabilitation for Disabled (PSRD), Neuro ward of Lahore General Hospital, Jinnah Hospital and Children Hospital Lahore from July 2012 to December 2012.50 patients of 5-50 years old were selected through purposive sample technique. Patients of GBS with other diseases were excluded. The data was analysis with SPSS version 17. Results: According to the present study 5 (10%) patients were positive for gross motor impairments, 27 (54%) patients for fine motor impairments and 18 (36%) patients for both fine and gross motor impairments. Among these impairments 28(56%) Grasping, 27(54%) Release, 41(82%) Pinching and 23(46%) Reach. Autonomic system was involved in 30 out of 50 patients while 34 patients also presented with signs of cranial nerve involvement. Conclusion: It is concluded that the patients with Guillain Barre Syndrome mostly have fine motor impairments that affect activities of daily living (ADL's). Key Words: Guillain Barre Syndrome, Occupational Therapy, Fine Motor Impairments, Manual Ability Assessment, Activity of Daily Livings

Objective: Stroke is the main cause of adult disability in the world, leaving more than half of the patients dependent on daily assistance. Understanding the post-stroke biochemical and molecular changes are critical for patient survival and stroke management. The aim of this work was to investigate the photo-thrombotic ischemic stroke in male rats with particular focus on biochemical and elemental changes in the primary stroke lesion in the somatosensory cortex and surrounding areas, including the corpus callosum.Materials and Methods: FT-IR imaging spectroscopy and LA-ICPMS techniques examined stroke brain samples, which were compared with standard immunohistochemistry studies.Results: The FTIR results revealed that in the lesioned gray matter the relative distribution of lipid, lipid acyl and protein contents decreased significantly. Also at this locus, there was a significant increase in aggregated protein as detected by high-levels Aβ1-42. Areas close to the stroke focus experienced decrease in the lipid and lipid acyl contents associated with an increase in lipid ester, olefin, and methyl bio-contents with a novel finding of Aβ1-42 in the PL-GM and L-WM. Elemental analyses realized major changes in the different brain structures that may underscore functionality.Conclusion: In conclusion, FTIR bio-spectroscopy is a non-destructive, rapid, and a refined technique to characterize oxidative stress markers associated with lipid degradation and protein denaturation not characterized by routine approaches. This technique may expedite research into stroke and offer new approaches for neurodegenerative disorders. The results suggest that a good therapeutic strategy should include a mechanism that provides protective effect from brain swelling (edema) and neurotoxicity by scavenging the lipid peroxidation end products.

Objective: Brain damage, long-term disability and death are the dreadful consequences of ischemic stroke. It causes imbalance in the biochemical constituents that distorts the brain dynamics. Understanding the sub-cellular alterations associated with the stroke will contribute to deeper molecular understanding of brain plasticity and recovery. Current routine approaches examining lipid and protein biochemical changes post stoke can be difficult. Fourier Transform Infrared (FTIR) imaging spectroscopy can play a vital role in detecting these molecular alterations on a sub-cellular level due to its high spatial resolution, accuracy and sensitivity. This study investigates the biochemical and molecular changes in peri-infract zone (PIZ) (contiguous area not completely damaged by stroke) and ipsi-lesional white matter (WM) (right below the stroke and PIZ regions) nine weeks post photothrombotic ischemic stroke in rats. Materials and Methods: FTIR imaging spectroscopy and transmission electron microscopy (TEM) techniques were applied to investigate brain tissue samples while hematoxylin and eosin (H&E) stained images of adjacent sections were prepared for comparison and examination the morphological changes post stroke. Results: TEM results revealed shearing of myelin sheaths and loss of cell membrane, structure and integrity after ischemic stroke. FTIR results showed that ipsi-lesional PIZ and WM experienced reduction in total protein and total lipid content compared to contra-lesional hemisphere. The lipid/protein ratio reduced in PIZ and adjacent WM indicated lipid peroxidation, which results in lipid chain fragmentation and an increase in olefinic content. Protein structural change is observed in PIZ due to the shift from random coli and α-helical structures to β-sheet conformation. Conclusion: FTIR imaging bio-spectroscopy provide novel biochemical information at sub-cellular levels that be difficult to be obtained by routine approaches. The results suggest that successful therapeutic strategy that is based on administration of anti-oxidant therapy, which could reduce and prevent neurotoxicity by scavenging the lipid peroxidation products. This approach will mitigate tissue damage in chronic ischemic period. FTIR imaging bio-spectroscopy can be used as a powerful tool and offer new approach in stroke and neurodegenerative diseases research.