Human Umbilical Cord Derived Mesenchymal Stem Cells in Peripheral Nerve Regeneration

BACKGROUND (100 words) Peripheral nerve injury can occur as a result of trauma or disease and carries significant morbidity including sensory and motor loss. The body has limited ability for nerve regeneration and functional recovery. Left untreated, nerve lesions can cause lifelong disability. Traditional treatment options such as neurorrhaphy and neurolysis have high failure rates. Surgical reconstruction with autograft carry donor site morbidity and often provide suboptimal results. Mesenchymal Stem Cells are known to have promising regenerative potential and have gained attention as a treatment option for nerve lesions. It is however, unclear whether it can be effectively used for nerve regeneration. AIM (20 words) To evaluate the evidence for the use of human Umbilical Cord derived Mesenchymal Stem Cells (UCMSCs) in peripheral nerve regeneration. METHOD (80 words) We carried out a systematic literature review in accordance with the PRISMA protocol. A literature search was performed from conception to September 2019 using PubMed, EmBase and Web of Science. The results of eligible studies were appraised. A risk of bias analysis was carried out using Cochrane’s RoB 2.0 tool. RESULTS (120 words) Fourteen studies were included in this review. A total of 279 subjects were treated with UCMSCs. Four studies obtained UCMSCs from a third-party source and the remainder were harvested directly from human subjects. Out of the 14 studies, ten conducted xenogenic transplantation into crushed or transected sciatic nerve injury models. All studies reported significant improvement in nerve regeneration in the UCMSC treated groups compared with the various different controls and untreated groups. CONCLUSION (30 words) The evidence summarised in this PRISMA systematic review of in vivo studies supports the notion that human UCMSC transplantation is an effective treatment option for peripheral nerve injury

Cognitive System for Objects Serving in Industry

As cognitive systems become gradually adept at performing simple jobs like moving itself, picking up and delivering the objects. In the context of building the “Cognitive System for Objects Serving in Industry” has ability to learn placement of geographical entities from environment of industries by spatial reference systems, objects identifications, human face detections and image processing. This paper presents the iterative design of a systemic system that uses a computational model for identifying and delivering objects on the basis of a range of spatial reference systems. Keywords: Cognitive System for Objects Serving in Industry (CSOSI), spatial reference systems, objects identifications

Hibernation Mechanism in Smartphone Mobile Operating Systems

Smartphone technology is advancing at a rapid pace. They are able to run more applications at a time which needs proper management of running processes especially when the processes are accidently lost due to critical battery that causes the device switch off. Therefore data loss occurs and there is no option to retrieve the lost data. In this paper, Hibernation approach for smartphones mobile operating system has been considered. Initially working of smart phones has been analyzed in order to find out their working mechanism. Hibernation approach is also discussed along with its structure. A mechanism has been proposed for smartphones based on hibernation called Hibernation Mechanism in Smartphones (HMS). HMS has been proposed for Smartphones in order to prevent application losses, thereby, giving proper management to smartphone users. Keywords:Hibernation Mechanism in Smartphones (HMS), Prevent application losses and Proper management

Identification of Associations between Cognitive Agents Using Learning Based System

The research is to pronounce the socialization with humans after identification of relationships between cognitive agents recognized with the perspective of focus, selective attention, intention and decision making. Machine learning is used to understand environment complexity, dynamic collaboration, noise, features, domain and range on different parameters. Range of view is an interesting approach for relationship identification with respect to time, distance and face direction in a settled boundary that are trying to answer socialized behavior between those multiple agents. In resultant, the system agent finds friend, best friend and stranger relationships between other agents by using top down approach. The application can play a wonderful role for security purposes, gaming, labs, and intelligence agencies etc

Development and Identification of Metrics to Predict the Impact of Dimension Reduction Techniques on Classical Machine Learning Algorithms for Still Highway Images

We are witnessing an influx of data - images, texts, video, etc. Their high dimensionality and large volume make it challenging to apply machine learning to obtain actionable insight. This thesis explores several aspects pertaining to dimensional reduction: dimension reduction methods, metrics to measure distortion, image preprocessing, etc. Faster training and inference time on reduced data and smaller models which can be deployed on commodity hardware are a critical advantage of dimension reduction. For this study, classical machine learning methods were explored owing to their solid mathematical foundation and interpretability. The dataset used is a time series of images from several camera feeds observing the traffic, weather and road conditions along highways. The time-series nature of dataset gives rise to interesting questions which are investigated in this work. For instance, can machine learning models trained on past data be used on future camera feed data? This is highly desirable and yet difficult due to the changing weather, road conditions, traffic conditions and scenery. Can dimension reduction models obtained from past data be used for reducing dimensionality of future data? This thesis also examines the difference between the performance of machine learning methods before and after application of dimension reduction. It tests some existing metrics to measure quality of dimension-reduced data set and introduces several new ones. It also examines the application of image pre-processing methods to boost the performance of classifiers. The classification performance with and without random sampling has been studied as well

Perioperative Considerations in Rheumatoid Arthritis Patients.

The pre-operative assessment is used to clarify issues prior to surgery that can change management provided by a multidisciplinary team. A high proportion of rheumatoid arthritis patients are elderly requiring orthopaedic surgery which requires further investigations, assessment of risk through functional capacity and several anaesthetic considerations. Rheumatoid arthritis patients often provide a variety of medical issues that can be found on careful and thorough pre-assessment that can be accommodated for by the surgical and anaesthetic team, however aspects of holistic management is an important considerations for efficient and effective management

Ferritin screening and Iron treatment for maternal anemia and fetal growth restriction prevention - A multicenter randomized controlled trial (FAIR Study)

Background: Non-anemic iron deficiency precedes iron deficiency anaemia and has an estimated prevalence of 1-2 billion worldwide. Few studies have comprehensively researched the idea of treating non-anemic iron deficiency (NAID) with iron to improve the outcome of the mother and the offspring. Methods and Analysis: FAIR will be a multicenter randomized controlled trial that will be conducted in multiple clinical academic obstetrics units in Lahore (including Services Institute of Medical Sciences, Lahore, Allama Iqbal Medical College, Lahore and Fatima Jinnah Medical University). Pregnant women at gestational age <20 weeks with hemoglobin 11-13 g/L and ferritin below the threshold (<30 ng/ml) will be invited to take part in the study. Randomization will be done by computer based generated random numbers. One group (usual care or oral group) will be offered routine care prophylactic dose of oral iron (30-45 mg/day) and the other group (intervention arm or IV group) will be offered therapeutic dose of IV iron (dose calculated by Ganzoni formula) in addition to usual care. All patients will be followed up till delivery. Primary maternal outcome will be hemoglobin at 36 weeks’ gestation. Secondary outcomes are fetal birthweight or small for gestational age, preterm birth, preeclampsia, multidimensional fatigue inventory, breast feeding initiation, blood transfusion, and fetal cord ferritin and hemoglobin. Discussion: The study will generate evidence as to whether screening serum ferritin in non-anemic pregnant women and replenishing their iron stores will likely reduce the rate of predelivery anemia in pregnant women, improve birthweight and preventing perinatal complications. Roles and responsibilities: Tayyiba Wasim is principal Investigator and other members of data management team are Natasha Bushra, Shamsa Humayoun, Khalid Saeed Khan, Fatima Shehbaz, Saba Rasool, Anam Riaz and Sonia Irshad. Principal investigator will assume the full responsibility of Fair trial including training of research assistants, administration of informed consent and protecting participants confidentiality. Data management team will help in the management, development and execution of trial. Khadija Irfan Khawaja is the operational lead for fair trial´s technology team comprising of Aziz Fatima and Zubia Zafar, responsible for gathering requirements from study teams and supporting the operational implementation of technology to drive the collection of high-quality study data. Protocol contributors are Gynae unit I of Services Institute of Medical Sciences/ Services hospital, Lahore, Gynae Unit II of Allama Iqbal Medical College/ Jinnah hospital, Lahore and Gynae unit 1 of Fatima Jinnah Medical College/ Sir Ganga Ram hospital, Lahore. These coordinating centres will recruit patients (sample size=600) and will discuss their progress in trial management meetings quarterly. Steering committee has an independent chair Prof Samia Malik, one expert member Prof Faiza Bashir and Ms Neelam to represent patients, public and consumers. Trial steering committee with independent chair and member with a patient representative will oversee the study. Chair of steering committee has the authority to stop the trial whenever needed in case of positive or negative results. Steering committee meetings will be held on annual basis. Independent Data monitoring committee comprises of Dr. Shehnoor Azhar as chair and Prof Ejaz Hussain and Dr. Shehla Javed Akram as members. Data monitoring committee will assess the progress, data safety and if needed critical efficacy points of the clinical study and will show their results quarterly in data interim meetings. The committee will focus on integrity of the whole process and compliance of all sites with all aspects of the protocol. It will perform confidential interim analyses quarterly, which may be used to determine if an effect` is observed and if the study should continue to its planned sample size. Data monitoring committee will report to the Chair of the steering committee