REGULATION OF REPRODUCTIVE CLONING AND INHERITABLE GENETIC MODIFICATIONS ON HUMANS - PERILS AND DEFICIENCIES

Harms arising from reproductive cloning or inheritable genetic modifications, for the time being, seem significant. This is supported by the simple fact that the first cloned monkeys were short-lived or by the fact that inheritable genetic modifications still carry a high chance of getting “off-target” results, which could result in serious health problems. Inheritable genetic modifications, in particular, have a high therapeutic potential, and it is suggested that this technology’s comprehension is shifting from an absolute ban, to concerns over safety issues. International law can prove to be facilitative when it comes to deciding which new technology should be prohibited, restricted or allowed, having in mind possible consequences and the so-called phenomenon of reproductive tourism. Legally binding regulation of both technologies has proven challenging at the universal level. However, there has been some progress in Europe on that matter. Harms arising from inheritable genetic modifications seem even higher than in the case of reproductive cloning, since they have the potential to affect the whole of humanity, including future generations. The Criminal Code of Serbia and the Constitution of the Republic of Serbia prohibit reproductive cloning. However, the prohibition of inheritable genetic modifications on humans is not regulated explicitly in the Criminal Code of Serbia, making this technology seem more acceptable or less harmful.

The Effect of Risk Communication on Public Behavior to Non-Conventional Terrorism—Randomized Control Trial

Non-conventional terrorism (NCT) incorporates an extended dimension of uncertainty that can lead to fear among the public. Health officials have an unsubstantiated assumption that thousands will seek treatment in hospitals following NCT. This study aims to examine public behavioral intentions in the case of NCT and the effect of risk communication on intents. An online randomized controlled trial was conducted among 1802 adult participants in Israel. Threat perception and behavioral intent before and after exposure to hypothetical NCT scenarios were assessed stratified to the type of media, exposure to rumors, and risk communication. The majority (~64%) of participants are aware of the NCT threat. Almost half (45%) of participants indicated a “high” or “very high” chance of seeking medical attention following an NCT incident. Regression analysis suggests that the odds of participants exposed to risk communication to report an elevated intent of seeking medical attention were 0.470 (95% CI: 0.359, 0.615) times that of participants not exposed to risk communication, χ2 = 30.366, p < 0.001. The findings demonstrate the importance of effective risk communication in reducing undesired public behavior during NCT crises. Efforts must be invested to create a robust risk communication infrastructure to allow the proper management of possible NCT incidents.

The metaethical dilemma of epistemic democracy

Epistemic democracy aims to show, often by appeal to the Condorcet Jury Theorem, that democracy has a high chance of reaching correct decisions. It has been argued that epistemic democracy is compatible with various metaethical accounts, such as moral realism, conventionalism and majoritarianism. This paper casts doubt on that thesis and reveals the following metaethical dilemma: if we adopt moral realism, it is doubtful that voters are, on average, more than 0.5 likely to track moral facts and identify the correct alternative. By contrast, if we adopt conventionalism or majoritarianism, we cannot expect that voters are both competent and sincere. Either way, the conditions for the application of Condorcet’s theorem are not met.

Frequency and Fetomaternal Outcome in COVID 19 Positive Pregnant Women

Objective: To determine the frequency and outcome in pregnant women with COVID-19 infection. Study Design: This is a observational cohort study. Setting: Study carried out at Department of Obstetrics & Gynecology, Civil Hospital, Dow University of health sciences Karachi, from July 2020 to November 2021. Materials & Methods: The study was conducted in a tertiary care hospital in Karachi. Women having COVID-19 positive status during any stage of their pregnancy having antenatal visits in our hospital were included in our study. Maternal demographics, race, maternal outcome, and neonatal complications were noted on a self-made Performa. Statistical analysis was done by SPSS version 21 and descriptive statistics with frequencies were mainly calculated. Results: During the defined time of 14 months, we had 143 women visiting antenatal outpatient department and were tested positive for COVID-19. Majority of the women were tested for COVID-19 due to symptoms like fever, flu, cough and diarrhea. The mean age of women in our study was found to be 30 ± 6.7 years. The most frequent maternal outcome with SARSCOV-2 was preterm delivery. Out of 143, 27 cases had emergency lower segment C-section.PCR testing of neonates was carried out and 8.39% (n=12) neonates tested positive for SARSCOV-2. Conclusion: Infection with Covid-19 during pregnancy is associated with adverse pregnancy outcomes. Covid-19 infection can be transmitted to the fetus during pregnancy or childbirth. Neonatal has a high chance of being admitted to the ICU, and women also faces other complications of Covid 19, such as the risk of miscarriage and premature delivery.

Practical Byzantine Consensus for Internet-of-Things

Use of IoT/WSN assisted smart-systems in the current age is making our living much more easier. However, components of such systems bear a high chance of getting compromised which may result in a substantial damage or loss. Use of fault tolerant consensus protocols provides a way towards solving this problem. Existing solutions for IoT/WSN systems mostly assume simple non-Byzantine node failures which is not enough to solve the problem. To combat the presence of smart devices with malicious intention, Byzantine fault tolerance support is highly essential in building trustworthy decentralised system. Byzantine fault tolerance has not been addressed much in the context of IoT/WSN because of its inherent requirement of extensive data sharing among the nodes. In this work, we approach to bring a solution to the problem using synchronous communication. In particular, we recast the well-known \textit{Practical Byzantine Fault Tolerant} (PBFT) consensus strategy to an efficient form that is suitable for use in IoT/WSN systems. We demonstrate that our proposed design can work upto 80% faster and consume upto 82% lesser energy compared to a naive implementation of the strategy in publicly available IoT/WSN testbed having 45 nodes.<br>

Practical Byzantine Consensus for Internet-of-Things

Use of IoT/WSN assisted smart-systems in the current age is making our living much more easier. However, components of such systems bear a high chance of getting compromised which may result in a substantial damage or loss. Use of fault tolerant consensus protocols provides a way towards solving this problem. Existing solutions for IoT/WSN systems mostly assume simple non-Byzantine node failures which is not enough to solve the problem. To combat the presence of smart devices with malicious intention, Byzantine fault tolerance support is highly essential in building trustworthy decentralised system. Byzantine fault tolerance has not been addressed much in the context of IoT/WSN because of its inherent requirement of extensive data sharing among the nodes. In this work, we approach to bring a solution to the problem using synchronous communication. In particular, we recast the well-known \textit{Practical Byzantine Fault Tolerant} (PBFT) consensus strategy to an efficient form that is suitable for use in IoT/WSN systems. We demonstrate that our proposed design can work upto 80% faster and consume upto 82% lesser energy compared to a naive implementation of the strategy in publicly available IoT/WSN testbed having 45 nodes.<br>

A multiplex protein panel assay determines disease severity and is prognostic about outcome in COVID-19 patients

Global healthcare systems continue to be challenged by the COVID-19 pandemic, and there is a need for clinical assays that can both help to optimize resource allocation and accelerate the development and evaluation of new therapies. Here, we present a multiplex proteomic panel assay for the assessment of disease severity and outcome prediction in COVID-19. The assay quantifies 50 peptides derived from 30 COVID-19 severity markers in a single measurement using analytical flow rate liquid chromatography and multiple reaction monitoring (LC-MRM), on equipment that is broadly available in routine and regulated analytical laboratories. We demonstrate accurate classification of COVID-19 severity in patients from two cohorts. Furthermore, the assay outperforms established risk assessments such as SOFA and APACHE II in predicting survival in a longitudinal COVID-19 cohort. The prognostic value implies its use for support of clinical decisions in settings with overstrained healthcare resources e.g. to optimally allocate resources to severely ill individuals with high chance of survival. It can furthermore be helpful for monitoring of novel therapies in clinical trials.

An efficient scRNA-seq dropout imputation method using graph attention network

Background Single-cell sequencing technology can address the amount of single-cell library data at the same time and display the heterogeneity of different cells. However, analyzing single-cell data is a computationally challenging problem. Because there are low counts in the gene expression region, it has a high chance of recognizing the non-zero entity as zero, which are called dropout events. At present, the mainstream dropout imputation methods cannot effectively recover the true expression of cells from dropout noise such as DCA, MAGIC, scVI, scImpute and SAVER. Results In this paper, we propose an autoencoder structure network, named GNNImpute. GNNImpute uses graph attention convolution to aggregate multi-level similar cell information and implements convolution operations on non-Euclidean space on scRNA-seq data. Distinct from current imputation tools, GNNImpute can accurately and effectively impute the dropout and reduce dropout noise. We use mean square error (MSE), mean absolute error (MAE), Pearson correlation coefficient (PCC) and Cosine similarity (CS) to measure the performance of different methods with GNNImpute. We analyze four real datasets, and our results show that the GNNImpute achieves 3.0130 MSE, 0.6781 MAE, 0.9073 PCC and 0.9134 CS. Furthermore, we use Adjusted rand index (ARI) and Normalized mutual information (NMI) to measure the clustering effect. The GNNImpute achieves 0.8199 (ARI) and 0.8368 (NMI), respectively. Conclusions In this investigation, we propose a single-cell dropout imputation method (GNNImpute), which effectively utilizes shared information for imputing the dropout of scRNA-seq data. We test it with different real datasets and evaluate its effectiveness in MSE, MAE, PCC and CS. The results show that graph attention convolution and autoencoder structure have great potential in single-cell dropout imputation.

Predicting neurodevelopmental outcomes in fetuses with isolated mild ventriculomegaly

BackgroundFetal ventriculomegaly is the the most common intracranial abnormality detected antenatally. When ventriculomegaly is mild and the only, isolated, abnormality detected (isolated mild ventriculomegaly (IMVM)) the prognosis is generally considered to be good. We aim to determine if there are features on in utero MRI (iuMRI) that can identify fetuses with IMVM who have lower risks of abnormal neurodevelopment outcome.MethodsWe studied cases recruited into the MRI to enhance the diagnosis of fetal developmental brain abnormalities in utero (MERIDIAN) study, specifically those with: confirmed IMVM, 3D volume imaging of the fetal brain and neurodevelopmental outcomes at 3 years. We explored the influence of sex of the fetus, laterality of the ventriculomegaly and intracranial compartmental volumes in relation to neurodevelopmental outcome.FindingsForty-two fetuses met the criteria (33 male and 9 female). There was no obvious correlation between fetal sex and the risk of poor neurodevelopmental outcome. Unilateral IMVM was present in 23 fetuses and bilateral IMVM in 19 fetuses. All fetuses with unilateral IMVM had normal neurodevelopmental outcomes, while only 12/19 with bilateral IMVM had normal neurodevelopmental outcomes. There was no obvious correlation between measure of intracranial volumes and risk of abnormal developmental outcomes.InterpretationThe most important finding is the very high chance of a good neurodevelopmental outcome observed in fetuses with unilateral IMVM, which is a potentially important finding for antenatal counselling. There does not appear to be a link between the volume of the ventricular system or brain volume and the risk of poor neurodevelopmental outcome.

Adoption of IoT Technology among Elderly NCD Patients in Malaysia: A Conceptual Study Based on the Theory of Planned Behaviour

Non-Communicable diseases (NCDs) are rising as the prime cause of death worldwide as well as in Malaysia. This is the result of evolutions occurring in social and economic factors in health. Some of these factors include a proliferation of business and promotion, improved style of living, change in socio-demographics, enhanced financial affordability, effortless travel and mobility, financial evolution, and import-export of unhealthy goods, causing high-risk behavioural deviations and spike metabolic hazards. Elderly people have a high chance of having NCDs because of poor sickness opposition, the impact of progressing lifestyle, terrible eating routine, and reduced amount of physical activities. At the end of the year 2020, individuals matured by 60 years of age and above in Malaysia are anticipated to be 9.7% of the entire populace. With the arrival of numerous wearable gadgets and smart devices, the IoT (Internet of Things) gadgets are transforming the conventional medical management system into a further customised and smart one. Therefore, the objective of this study is to identify the factors that influence the actual behaviour towards IoT adoption based on the underlying concept of the “theory of planned behaviour”. This study is expected to provide meaningful outcomes in creating awareness of the use of IoT among elderly NCD patients in Malaysia and understanding their behavioural intentions and actual behaviour that can help to maximise the utilisation of the available healthcare resources.