Human–Computer Interaction and Participation in Software Crowdsourcing

Improvements in communication and networking technologies have transformed people’s lives and organizations’ activities. Web 2.0 innovation has provided a variety of hybridized applications and tools that have changed enterprises’ functional and communication processes. People use numerous platforms to broaden their social contacts, select items, execute duties, and learn new things. Context: Crowdsourcing is an internet-enabled problem-solving strategy that utilizes human–computer interaction to leverage the expertise of people to achieve business goals. In crowdsourcing approaches, three main entities work in collaboration to solve various problems. These entities are requestors (job providers), platforms, and online users. Tasks are announced by requestors on crowdsourcing platforms, and online users, after passing initial screening, are allowed to work on these tasks. Crowds participate to achieve various rewards. Motivation: Crowdsourcing is gaining importance as an alternate outsourcing approach in the software engineering industry. Crowdsourcing application development involves complicated tasks that vary considerably from the micro-tasks available on platforms such as Amazon Mechanical Turk. To obtain the tangible opportunities of crowdsourcing in the realm of software development, corporations should first grasp how this technique works, what problems occur, and what factors might influence community involvement and co-creation. Online communities have become more popular recently with the rise in crowdsourcing platforms. These communities concentrate on specific problems and help people with solving and managing these problems. Objectives: We set three main goals to research crowd interaction: (1) find the appropriate characteristics of social crowd utilized for effective software crowdsourcing, (2) highlight the motivation of a crowd for virtual tasks, and (3) evaluate primary participation reasons by assessing various crowds using Fuzzy AHP and TOPSIS method. Conclusion: We developed a decision support system to examine the appropriate reasons of crowd participation in crowdsourcing. Rewards and employments were evaluated as the primary motives of crowds for accomplishing tasks on crowdsourcing platforms, knowledge sharing was evaluated as the third reason, ranking was the fourth, competency was the fifth, socialization was sixth, and source of inspiration was the seventh.Princess Nourah bint Abdulrahman University Researchers Supporting - Riyadh, Saudi Arabia. Project number (PNURSP2023TR140)

Association of methionine synthase reductase (MTRR A66G) polymorphism with susceptibility to acute lymphoblastic leukemia

Background and Objectives. The enzyme methionine synthase reductase is involved in cellular methylation reactions, DNA synthesis, and epigenetic processes. It is encoded by the MTRR gene, which garnered a lot of attention in current medical genetics research. This study was conducted to study the association between MTRR (A66G) polymorphism and the risk of developing acute lymphoblastic leukemia among Sudanese patients. Materials and Methods. This is a case-control study in which 150 patients with acute lymphoblastic leukemia (ALL) and 150 healthy participants as a control group were enrolled. DNA was extracted and analyzed for the MTRR (A66G) polymorphism using the real-time polymerase chain reaction. Results. Based on flow cytometry results, B-ALL was more common (79%) than T-ALL (21%). The comparison of hematological parameters in acute lymphoblastic leukemia subtypes showed a statistically significant high mean total white blood count (P=0.000) and mean blast percentage (P=0.050) in patients with T-ALL. The molecular analysis showed that the incidence of the MTRR homozygous genotypes AA and GG were higher in the patients (44% and 9.3%, respectively) compared to the control group (40% and 6.7%, respectively). In comparison, the heterozygous genotype AG was lower in the patients (46.7%) than in the control group (53.3%). However, the association between the polymorphism and acute lymphoblastic leukemia risk was not statistically significant (OR: 1.179, 95% CI 0.7459-1.865, P=0.445). Conclusions. This study concluded that MTRR A66G polymorphism was not associated with the risk of acute lymphoblastic leukemia among the Sudanese population

Willingness to participate in genome testing: a survey of public attitudes from Qatar

Genomics has the potential to revolutionize medical approaches to disease prevention, diagnosis, and treatment, but it does not come without challenges. The success of a national population-based genome program, like the Qatar Genome Program (QGP), depends on the willingness of citizens to donate samples and take up genomic testing services. This study explores public attitudes of the Qatari population toward genetic testing and toward participating in the QGP. A representative sample of 837 adult Qataris was surveyed in May 2016. Approximately 71% of respondents surveyed reported that they were willing to participate in the activities of the QGP. Willingness to participate was significantly associated with basic literacy in genetics, a family history of genetic diseases, and previous experience with genetic testing through premarital screening. Respondents cited the desire to know more about their health status as the principle motivation for participating, while lack of time and information were reported as the most important barriers. With QGP plans to ramp up the scale of its national operation toward more integration into clinical care settings, it is critical to understand public attitudes and their determinants. The results demonstrate public support but also identify the need for more education and individual counseling that not only provide information on the process, challenges, and benefits of genomic testing, but that also address concerns about information security

Qatar genome: Insights on genomics from the Middle East

Despite recent biomedical breakthroughs and large genomic studies growing momentum, the Middle Eastern population, home to over 400 million people, is underrepresented in the human genome variation databases. Here we describe insights from Phase 1 of the Qatar Genome Program with whole genome sequenced 6047 individuals from Qatar. We identified more than 88 million variants of which 24 million are novel and 23 million are singletons. Consistent with the high consanguinity and founder effects in the region, we found that several rare deleterious variants were more common in the Qatari population while others seem to provide protection against diseases and have shaped the genetic architecture of adaptive phenotypes. These results highlight the value of our data as a resource to advance genetic studies in the Arab and neighboring Middle Eastern populations and will significantly boost the current efforts to improve our understanding of global patterns of human variations, human history, and genetic contributions to health and diseases in diverse populations.The Qatar Genome Program (QGP) and Qatar Biobank (QBB) are both Research and Development entities within Qatar Foundation for Education, Science and Community Development. The authors are thankful for everyone who contributed to this endeavor including the QGP and QBB team members, in addition to our partners at Hamad Medical Corporation (HMC), Sidra Medicine and other national stakeholders. The authors would like to especially thank all participants in this study for their continuous support

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk

Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies

Chromodomain helicase DNA-binding proteins and neurodevelopmental disorders

The significance of epigenomic regulation is now established in the etiology of neurodevelopmental disorders (NDDs). Epigenomic regulatory processes include chromatin remodeling as a major regulator of gene expression in development. Chromatin remodeling is an enzymatic process carried out by large multi-unit protein complexes, of which the chromodomain helicase DNA-binding proteins comprise one of four recognized major protein families, named the chromodomain helicase DNA-binding (CHD) family. There are nine CHD proteins (CHD1-9) encoded by nine correspondingly named CHD genes. Remarkably, five of the nine CHDs are already recognized to be causative of autosomal dominant syndromic NDD. In this review, we discuss the contribution of all CHDs to NDDs. And, we specifically focus on molecular studies involving CHD8 of which several have been recently published and scarcely reviewed. The widespread nature of downstream targeting for CHD8, as well as the finding of autosomal dominant disease for the majority of CHDs in general, implicates this family of chromatin remodelers as major players in NDD causation

Interleukin-6 in systemic sclerosis and potential correlation with pulmonary involvement

Background: A progressive pulmonary involvement is frequent in systemic sclerosis and it is the leading cause of morbidity and mortality. IL-6 has been implicated in the pathogenesis of systemic sclerosis via stimulation of fibroblasts to produce excess collagen and glycosaminoglycan. Specific correlation between IL-6 and lung involvement have not been found yet. Aim: To study the possible correlation between lung involvement (assessed by spirometry and HRCT abnormalities) and the serum level of IL-6. Subjects and methods: 20 patients with scleroderma compared with 20 matched volunteers as control group. All participants underwent spirometry, HRCT scan and serum IL-6 measurements. HRCT signs were scored according to Warrick et al. score for systemic sclerosis. Results: Patients showed a statistically significant reduction in FVC%, FEF 25–75% and significantly higher ESR and IL-6 compared to control. There was a highly significant positive correlation between the total HRCT score and serum IL-6. Conclusion: Serum IL-6 could be a marker of the degree of pulmonary involvement in patients with systemic sclerosis

A QoS-Aware Data Aggregation Strategy for Resource Constrained IoT-Enabled AMI Network in Smart Grid

Emerging Internet of Things (IoT) technologies and applications have enabled the Smart Grid Utility control center to connect, monitor, control, and exchange data between the smart appliances, smart meters (SMs), data concentrators (DCs) and control center server (CCS) over the Internet. In particular, DC receives different Advanced Metering Infrastructure (AMI) applications data from multiple SMs for processing, queuing, aggregation, and forwarding onward towards the CCS over the things networking. However, DCs are expensive component of the AMI network. Recently, SMs are used as relay-devices to accomplish a cost-effective AMI network infrastructure to avoid the DC placement and bottleneck problem. However, SMs are recourse constrained (limited CPU, RAM, storage, and network capacity) intelligent devices which faces numerous communication challenges during outage conditions and summer peak hours where bulk amount of data with different traffic rates and latency are exchanged with the Utility control center. Therefore, an efficient data aggregation is required at relay-devices to deal with high volume of data exchange rates in order to optimize the constrained-resources of the AMI network. In this article, we propose a hybrid data aggregation strategy implemented on an aggregator-head (AH) in the clustering topology which performs data aggregation on the Interval Meter Reading (IMR) application data. AH induction greatly reduces the workload of the cluster-heads (CHs), and efficiently utilizes the constrained-resource of AMI devices in a cost effective-manner. The proposed strategy is evaluated for different existing approaches using the CloudSim simulation tool. Experimental and simulation results are obtained and compared which show the effectiveness of the proposed strategy such that limited resources are optimized, CH workload is minimized, and QoS of AMI applications are maintained