DNA-MP: a generalized DNA modifications predictor for multiple species based on powerful sequence encoding method.

Accurate prediction of deoxyribonucleic acid (DNA) modifications is essential to explore and discern the process of cell differentiation, gene expression and epigenetic regulation. Several computational approaches have been proposed for particular type-specific DNA modification prediction. Two recent generalized computational predictors are capable of detecting three different types of DNA modifications; however, type-specific and generalized modifications predictors produce limited performance across multiple species mainly due to the use of ineffective sequence encoding methods. The paper in hand presents a generalized computational approach "DNA-MP" that is competent to more precisely predict three different DNA modifications across multiple species. Proposed DNA-MP approach makes use of a powerful encoding method "position specific nucleotides occurrence based 117 on modification and non-modification class densities normalized difference" (POCD-ND) to generate the statistical representations of DNA sequences and a deep forest classifier for modifications prediction. POCD-ND encoder generates statistical representations by extracting position specific distributional information of nucleotides in the DNA sequences. We perform a comprehensive intrinsic and extrinsic evaluation of the proposed encoder and compare its performance with 32 most widely used encoding methods on $17$ benchmark DNA modifications prediction datasets of $12$ different species using $10$ different machine learning classifiers. Overall, with all classifiers, the proposed POCD-ND encoder outperforms existing $32$ different encoders. Furthermore, combinedly over 5-fold cross validation benchmark datasets and independent test sets, proposed DNA-MP predictor outperforms state-of-the-art type-specific and generalized modifications predictors by an average accuracy of 7% across 4mc datasets, 1.35% across 5hmc datasets and 10% for 6ma datasets. To facilitate the scientific community, the DNA-MP web application is available at https://sds_genetic_analysis.opendfki.de/DNA_Modifications/.

Cholecystokinin B receptor antagonists for the treatment of depression via blocking long-term potentiation in the basolateral amygdala.

Depression is a common and severe mental disorder. Evidence suggested a substantial causal relationship between stressful life events and the onset of episodes of major depression. However, the stress-induced pathogenesis of depression and the related neural circuitry is poorly understood. Here, we investigated how cholecystokinin (CCK) and CCKBR in the basolateral amygdala (BLA) are implicated in stress-mediated depressive-like behavior. The BLA mediates emotional memories, and long-term potentiation (LTP) is widely considered a trace of memory. We identified that the cholecystokinin knockout (CCK-KO) mice impaired LTP in the BLA, while the application of CCK4 induced LTP after low-frequency stimulation (LFS). The entorhinal cortex (EC) CCK neurons project to the BLA and optogenetic activation of EC CCK afferents to BLA-promoted stress susceptibility through the release of CCK. We demonstrated that EC CCK neurons innervate CCKBR cells in the BLA and CCK-B receptor knockout (CCKBR-KO) mice impaired LTP in the BLA. Moreover, the CCKBR antagonists also blocked high-frequency stimulation (HFS) induced LTP formation in the BLA. Notably, CCKBR antagonists infusion into the BLA displayed an antidepressant-like effect in the chronic social defeat stress model. Together, these results indicate that CCKBR could be a potential target to treat depression.

Structural and thermal investigation of lignocellulosic biomass conversion for enhancing sustainable imperative in progressive organic refinery paradigm for waste-to-energy applications.

The depletion of finite fossil fuel reserves and the severe environmental degradation resulting from human activities have compelled the expeditious development and application of sustainable waste to energy technologies. To encapsulate energy and environment in sustainability paradigm, bio waste based energy production is need to be forged in organic bio refinery setup. According to world bioenergy association, biomass can cover 50 % of the primary energy demand of the world. Therefore, the present study focuses on reforming the energy mix for a clean energy generation, where, sample composition of cotton stalk was acidified in dilute (5% wt.) hydrochloric acid (HCL) for analyzing material burnout patterns in biomass conversion systems utilized in organic bio refinery sector. Advanced thermochemical burning technique, which includes pyrolysis and combustion was applied at four different leaching times from 0 to 180 min under nitrogen environment from 0 °C to 500 °C and air from 500 °C to 900 °C, respectively. Different analyses including proximate, ultimate, gross calorific value (GCV), thermos-gravimetric, kinetic, XRD, FTIR, SEM-EDS were used for analyzing the degradation of demineralized cotton stalk at different treatment rates. Proximate study demonstrated that cotton stalk leaching for 180 min has efficiently infused HCL, leading in a significant increase in fixed carbon and higher heating value of 20.23 % and 12.48%, respectively, as well as a reduction in carbon footprint of around 54.80%. The findings of proximate was validated by GCV analysis and CHNS analysis as value of carbon and hydrogen has shown increasing behavior with the time delay in demineralization Thermo-gravimetric and derivative thermo-gravimetric data analyses shows an increasing trend of conversion efficiency, with the maximum increase of 98 % reported for sample 3H.TT.DEM. XRD characterization has reported 23° to 25° angle for all the observed peaks. Sample 3H.TT.DEM has shown maximum angle inclination along with matured crystalline peak. The latter observations has been validated by FTIR spectroscopy as sample 3H.TT.DEM has reported maximum O-H group formation. Sample 3H.TT.DEM has reported lowest activation energy of 139.51 kJ*mole-1 and lowest reactivity of 0.000293649%*min 0C, due to moderate and stable reactiveness. In SEM examination, increment in pore size and number of pores within the structural matrix of cotton stalk was observed with the enhancement in acidulation process. Furthermore, in EDS analysis, 3H.TT.DEM has shown most balanced distribution of the elements. In this research, sustainable transformation of biomass is envisioned to improve the waste bio refinery system, significantly contributing to the achievement of Sustainable Development Goals 7, 12 and 13.

Barriers and facilitators to accessing adolescents' mental health services in Karachi: users and providers perspectives.

INTRODUCTION: Adolescents' Mental Healthcare (MHC) is influenced by numerous factors, and adolescents occasionally seek professional help for mental health (MH) issues. These factors become more complex within low-middle-income countries (LMICs); therefore, this study aims to understand barriers and facilitators to access mental health services among adolescents aged 10 to 19 years old from the perspective of users (parents) and providers (Mental Healthcare Providers - MHPs). METHOD: Using a qualitative exploratory design, a semi-structured interview guide was developed using Andersen's health service utilization model. In-depth interviews were conducted with MHPs (n = 21) and parents of adolescents (n = 19) in the psychiatry department of public and private hospitals in Karachi, from October-December 2021. Data was thematically analyzed using an inductive approach. RESULT: The findings revealed a consensus of users and providers in all three categories of the Andersen model and referred the compulsion as the major driving force to MHC access and utilization rather than personal choices. Within pre-disposing, need, and enabling factors; the participants highlighted a unique perspective; users regarded frequent migration, daily wage loss, and women's societal status as barriers while the need for marriage and patient willingness were stated as facilitators. Whereas, MHPs indicated societal tolerance, the burden on the health system, and the absence of Child and Adolescent Mental Health (CAMH) services as major gaps in service delivery. CONCLUSION: Service utilization is mainly facilitated by the severity of illness rather than healthy choices and beliefs, and accessibility and affordability. It is therefore imperative to prioritize adolescent MH through promotion and prevention approaches and address service delivery gaps to prevent treatment delays via task-shifting and capacity building of the health workforce.

Various pharmacological agents in the pipeline against intractable epilepsy.

Epilepsy is a noncommunicable chronic neurological disorder affecting people of all ages, with the highest prevalence in low and middle-income countries. Despite the pharmacological armamentarium, the plethora of drugs in the market, and other treatment options, 30%-35% of individuals still show resistance to the current medication, termed intractable epilepsy/drug resistance epilepsy, which contributes to 50% of the mortalities due to epilepsy. Therefore, the development of new drugs and agents is needed to manage this devastating epilepsy. We reviewed the pipeline of drugs in "ClinicalTrials. gov," which is the federal registry of clinical trials to identify drugs and other treatment options in various phases against intractable epilepsy. A total of 31 clinical trials were found regarding intractable epilepsy. Among them, 48.4% (15) are about pharmacological agents, of which 26.6% are in Phase 1, 60% are in Phase 2, and 13.3% are in Phase 3. The mechanism of action or targets of the majority of these agents are different and are more diversified than those of the approved drugs. In this article, we summarized various pharmacological agents in clinical trials, their backgrounds, targets, and mechanisms of action for the treatment of intractable epilepsy. Treatment options other than pharmacological ones, such as devices for brain stimulation, ketogenic diets, gene therapy, and others, are also summarized.

Leaf senescence attributes: the novel and emerging role of sugars as signaling molecules and the overlap of sugars and hormones signaling nodes.

Sugars are the primary products of photosynthesis and play multiple roles in plants. Although sugars are usually considered to be the building blocks of energy storage and carbon transport molecules, they have also gradually come to be acknowledged as signaling molecules that can initiate senescence. Senescence is an active and essential process that occurs at the last developmental stage and corresponds to programmed degradation of: cells, tissues, organs, and entire organisms. It is a complex process involving: numerous biochemical changes, transporters, genes, and transcription factors. The process is controlled by multiple developmental signals, among which sugar signals are considered to play a vital role; however, the regulatory pathways involved are not fully understood. The dynamic mechanistic framework of sugar accumulation has an inconsistent effect on senescence through the sugar signaling pathway. Key metabolizing enzymes produce different sugar signals in response to the onset of senescence. Diverse sugar signal transduction pathways and a variety of sugar sensors are involved in controlling leaf senescence. This review highlights the processes underlying initiation of sugar signaling and crosstalk between sugars and hormones signal transduction pathways affecting leaf senescence. This summary of the state of current knowledge across different plants aids in filling knowledge gaps and raises key questions that remain to be answered with respect to regulation of leaf senescence by sugar signaling pathways.

HepFREEPak: protocol for a multi-centre, prospective observational study examining efficacy and impact of current therapies for the treatment of hepatitis C in Pakistan and reporting resistance to antiviral drugs: study protocol.

BACKGROUND: Pakistan has one of the highest burdens of Hepatitis C virus (HCV) infection globally. To achieve the World Health Organization's goals for HCV elimination, there is a need for substantial scale-up in testing, treatment, and a reduction in new infections. Data on the population impact of scaling up treatment is not available in Pakistan, nor is there reliable data on the incidence of infection/reinfection. This project will fill this gap by providing important empirical data on the incidence of infection (primary and reinfection) in Pakistan. Then, by using this data in epidemic models, the study will determine whether response rates achieved with affordable therapies (sofosbuvir plus daclatasvir) will be sufficient to eliminate HCV in Pakistan. METHODS: This prospective multi-centre cohort study will screen 25,000 individuals for HCV antibody (Ab) and RNA (if Ab-positive) at various centers in Pakistan- Karachi (Sindh) and Punjab, providing estimates of the disease prevalence. HCV positive patients will be treated with sofosbuvir and daclatasvir for 12-weeks, (extended to 24-weeks in those with cirrhosis) and the proportion responding to this first-line treatment estimated. Patients who test HCV Ab negative will be recalled 12 months later to test for new HCV infections, providing estimates of the incidence rate. Patients diagnosed with HCV (~ 4,000) will be treated and tested for Sustained Virological Response (SVR). Questionnaires to assess risk factors, productivity, health care usage and quality of life will be completed at both the initial screening and at 12-month follow-up, allowing mathematical modelling and economic analysis to assess the current treatment strategies. Viral resistance will be analysed and patients who have successfully completed treatment will be retested 12 months later to estimate the rate of re-infection. CONCLUSION: The HepFREEPak study will provide evidence on the efficacy of available and widely used treatment options in Pakistan. It will also provide data on the incidence rate of primary infections and re-infections. Data on incidence risk factors will allow us to model and incorporate heterogeneity of risk and how that affects screening and treatment strategies. These data will identify any gaps in current test-and-treat programs to achieve HCV elimination in Pakistan. STUDY REGISTRATION: This study was registered on clinicaltrials.gov (NCT04943588) on June 29, 2021.

Ketamine attenuates the PTSD-like effect via regulation of glutamatergic signaling in the nucleus accumbens of mice.

Post-traumatic stress disorder (PTSD) is a devastating mental illness with high morbidity and major social and economic burden. Currently, there is no promising therapy available for the treatment of PTSD. Some clinical studies showed that ketamine could effectively alleviate PTSD symptoms. However, it is still unclear which brain region ketamine targets and how it attenuates the PTSD-like effects. In this study, we examined the effect of ketamine on fear generalization (a core symptom of PTSD) by using a mice model of fear generalization induced by fear conditioning procedure. Before retrieval, ketamine was locally infused into the nucleus accumbens (a brain region closely associated with PTSD). Fear generalization mice were subjected to behavioral testing and biochemical assessments, following ketamine infusion. The results showed that the foot shock strength-dependently induced fear generalization in mice with increased c-fos activity, and a lower level of GluR1(S845), GluR1(S831) protein, and a higher level of P-GluN2B protein in the nucleus accumbens (NAc). Local infusion of ketamine into NAc decreased the fear generalization together with an increased level of GluR1(S845), GluR1(S831) protein, and decreased level of P-GluN2B protein. Altogether, these results conclude that ketamine might affect the glutamatergic signaling in the NAc to attenuate the fear generalization in mice.

Genetic variants of CSN1S1, CSN2, CSN3, and BLG genes and their association with dairy production traits in Sahiwal cattle and Nili-Ravi buffaloes.

Milk protein genes are associated with milk yield and composition in dairy animals. The present study aimed to identify milk protein genes (CSN1S1, CSN2, CSN3, and BLG) genetic variants and their association with milk yield in Sahiwal cattle and Nili-Ravi buffaloes. One hundred animals from each species were selected to collect blood samples and milk production records. Primers were designed for these milk protein genes for PCR amplification. Sequencing of resultant PCR products revealed a higher number of SNPs (13 vs. 7, 5 vs. 1, and 6 vs. 2) in Sahiwal as compared to Nili-Ravi animals in CSN1S1, CSN2, and CSN3 genes, respectively. However, a single SNP was observed in BLG gene of both species. Association analysis revealed that one SNP in BLG gene of Nili-Ravi was associated (p < 0.05) with 305-day milk yield. Two SNPs at CSN1S1 gene in Sahiwal were associated with dry-period. Similarly, one SNP at CSN1S1 and two SNPs at CSN3 gene showed significant association (p < 0.05) with average calving-interval in Sahiwal while two SNPs in CSN1S1 gene were associated (p < 0.05) with this trait in Nili-Ravi. These SNPs could be helpful as candidate variants for marker-assisted selection in cattle and buffaloes for improvement of lactation performance.

Efficient Approach for Anomaly Detection in IoT Using System Calls.

The Internet of Things (IoT) has shown rapid growth and wide adoption in recent years. However, IoT devices are not designed to address modern security challenges. The weak security of these devices has been exploited by malicious actors and has led to several serious cyber-attacks. In this context, anomaly detection approaches are considered very effective owing to their ability to detect existing and novel attacks while requiring data only from normal execution. Because of the limited resources of IoT devices, conventional security solutions are not feasible. This emphasizes the need to develop new approaches that are specifically tailored to IoT devices. In this study, we propose a host-based anomaly detection approach that uses system call data and a Markov chain to represent normal behavior. This approach addresses the challenges that existing approaches face in this area, mainly the segmentation of the syscall trace into suitable smaller units and the use of a fixed threshold to differentiate between normal and malicious syscall sequences. Our proposed approach provides a mechanism for segmenting syscall traces into the program's execution paths and dynamically determines the threshold for anomaly detection. The proposed approach was evaluated against various attacks using two well-known public datasets provided by the University of New South Mexico (UNM) and one custom dataset (PiData) developed in the laboratory. We also compared the performance and characteristics of our proposed approach with those of recently published related work. The proposed approach has a very low false positive rate (0.86%), high accuracy (100%), and a high F1 score (100%) that is, a combined performance measure of precision and recall.

Securing Smart Healthcare Cyber-Physical Systems against Blackhole and Greyhole Attacks Using a Blockchain-Enabled Gini Index Framework.

The increasing reliance on cyber-physical systems (CPSs) in critical domains such as healthcare, smart grids, and intelligent transportation systems necessitates robust security measures to protect against cyber threats. Among these threats, blackhole and greyhole attacks pose significant risks to the availability and integrity of CPSs. The current detection and mitigation approaches often struggle to accurately differentiate between legitimate and malicious behavior, leading to ineffective protection. This paper introduces Gini-index and blockchain-based Blackhole/Greyhole RPL (GBG-RPL), a novel technique designed for efficient detection and mitigation of blackhole and greyhole attacks in smart health monitoring CPSs. GBG-RPL leverages the analytical prowess of the Gini index and the security advantages of blockchain technology to protect these systems against sophisticated threats. This research not only focuses on identifying anomalous activities but also proposes a resilient framework that ensures the integrity and reliability of the monitored data. GBG-RPL achieves notable improvements as compared to another state-of-the-art technique referred to as BCPS-RPL, including a 7.18% reduction in packet loss ratio, an 11.97% enhancement in residual energy utilization, and a 19.27% decrease in energy consumption. Its security features are also very effective, boasting a 10.65% improvement in attack-detection rate and an 18.88% faster average attack-detection time. GBG-RPL optimizes network management by exhibiting a 21.65% reduction in message overhead and a 28.34% decrease in end-to-end delay, thus showing its potential for enhanced reliability, efficiency, and security.

Image Encryption Scheme Based on Orbital Shift Pixels Shuffling with ILM Chaotic System.

Image encryption techniques protect private images from unauthorized access while they are being transmitted. Previously used confusion and diffusion processes are risky and time-consuming. Therefore, finding a solution to this problem has become necessary. In this paper, we propose a new image encryption scheme that combines the Intertwining Logistic Map (ILM) and Orbital Shift Pixels Shuffling Method (OSPSM). The proposed encryption scheme applies a technique for confusion inspired by the rotation of planets around their orbits. We linked the technique of changing the positions of planets around their orbits with the shuffling technique of pixels and combined it with chaotic sequences to disrupt the pixel positions of the plain image. First, randomly selected pixels from the outermost orbit are rotated to shift the pixels in that orbit, causing all pixels in that orbit to change their original position. This process is repeated for each orbit until all pixels have been shifted. This way, all pixels are randomly scrambled on their orbits. Later on, the scrambled pixels are converted into a 1D long vector. The cyclic shuffling is applied using the key generated by the ILM to a 1D long vector and reshaped into a 2D matrix. Then, the scrambled pixels are converted into a 1D long vector to apply cyclic shuffle using the key generated by the ILM. After that, the 1D long vector is converted into a 2D matrix. For the diffusion process, using ILM generates a mask image, which is then XORed with the transformed 2D matrix. Finally, a highly secure and unrecognizable ciphertext image is obtained. Experimental results, simulation analysis, security evaluation, and comparison with existing image encryption schemes show that it has a strong advantage in defending against common attacks, and the operating speed of this encryption scheme also performs excellently in practical image encryption applications.

Between Life and Death: How do Muslim Terminal Patients in Pakistan cope with Hepatitis C utilizing their Beliefs and Social Support?

Life-threatening events including terminal illness intensify the search for meaning and incite individuals to get closer to religion. Terminal patients can often find religious practices as helpful as medical therapy for bettering both physical and mental health. The present research aims to explain the interaction between religion, spirituality, and social support in coping with terminal illness among Muslim hepatitis C patients in Pakistan. A semi-structured open-ended interview guide was utilized to collect the data. Participants expressed that the deployment of religious and spiritual beliefs along with socio-emotional support during illness fostered medical therapy. Participants also revealed that belief in God provided them the strength to be steadfast during the terminal stage of the disease. Religious beliefs enabled terminal participants to accept death as an eventual reality and a normal part of their lives. Furthermore, participants put forward their longing for those kinds of religious practices that terminal diseases usually restrained them from receiving. The emotional support stemming from social relationships also improved resilience to cope with the terminal stage of illness. The study concludes that the interplay of religion, spirituality, and social support normalizes the fear of death, lessens pain, and improves resilience among Muslim hepatitis C patients in Pakistan.

Host plant resistance for fall armyworm management in maize: relevance, status and prospects in Africa and Asia.

KEY MESSAGE: Sustainable control of fall armyworm (FAW) requires implementation of effective integrated pest management (IPM) strategies, with host plant resistance as a key component. Significant opportunities exist for developing and deploying elite maize cultivars with native genetic resistance and/or transgenic resistance for FAW control in both Africa and Asia. The fall armyworm [Spodoptera frugiperda (J.E. Smith); FAW] has emerged as a serious pest since 2016 in Africa, and since 2018 in Asia, affecting the food security and livelihoods of millions of smallholder farmers, especially those growing maize. Sustainable control of FAW requires implementation of integrated pest management strategies, in which host plant resistance is one of the key components. Significant strides have been made in breeding elite maize lines and hybrids with native genetic resistance to FAW in Africa, based on the strong foundation of insect-resistant tropical germplasm developed at the International Maize and Wheat Improvement Center, Mexico. These efforts are further intensified to develop and deploy elite maize cultivars with native FAW tolerance/resistance and farmer-preferred traits suitable for diverse agro-ecologies in Africa and Asia. Independently, genetically modified Bt maize with resistance to FAW is already commercialized in South Africa, and in a few countries in Asia (Philippines and Vietnam), while efforts are being made to commercialize Bt maize events in additional countries in both Africa and Asia. In countries where Bt maize is commercialized, it is important to implement a robust insect resistance management strategy. Combinations of native genetic resistance and Bt maize also need to be explored as a path to more effective and sustainable host plant resistance options. We also highlight the critical gaps and priorities for host plant resistance research and development in maize, particularly in the context of sustainable FAW management in Africa and Asia.

Intimate partner violence against women in Southern Punjab, Pakistan: A phenomenological study.

BACKGROUND: Intimate Partner Violence (IPV) refers to behavior by an intimate partner that can cause physical, sexual, or psychological harm; is a common global public health issue requiring immediate attention. IPV is the most common form of violence in rural areas of Punjab, Pakistan. METHODS: This qualitative phenomenological study collected 46 in-depth interviews from married women who experienced IPV in the rural areas of South Punjab. A semi-structured interview guide was used for data collection. These women were selected through a snowball sampling technique from October 2018 to March 2019. Researchers accessed the study setting with the help of gatekeepers (Lady Health Workers and Village Heads). The interviews were audio-recorded in the local language (Saraiki) and were translated into English. The data were analyzed using the thematic inductive analysis technique. RESULTS: The study has presented multifaceted factors of IPV by using the socio-ecological framework in rural areas of South Punjab, Pakistan. The current study introduced culturally contextualized terminologies of "protection," "physical submissiveness," "mental delicacy," and "social security". For married women, culturally embedded terms became the primary cause of IPV. In addition, the study also highlighted some of the cultural terminologies (such as run-mureed, watta-satta, beghairat, izzat, etc.) that are ubiquitous in the local context that sometimes intensifies IPV in the family and community sphere. Furthermore, the study discussed how gender-based inequalities trigger a status quo that ultimately creates power discrimination between spouses, which perpetuates violence in the domestic context. CONCLUSIONS: Gender-prejudiced roles and expectations imposed by orthodoxy, misinterpretations of Islamic teachings, and dominant patriarchy can be contested through awareness campaigns among the public, and gender sensitization drives among public institutions of police and judiciary. Education and employment-based can lead to women's empowerment and help to challenge the orthodox anti-feminist societal norms and the role of kinship-based networks in the family and community sphere.

The unspoken grief of multiple stillbirths in rural Pakistan: an interpretative phenomenological study.

BACKGROUND: Pakistan has the highest rate of stillbirth (30.6 stillbirths per 1000 total births) as compared to other South Asian countries. The psychological impact of stillbirths on bereaved women is well documented; however, there is a dearth of literature on lived experiences of women with multiple stillbirths in Pakistan. OBJECTIVE: The purpose of this research is to understand the lived experiences of women who had multiple stillbirths in Thatta, Pakistan. METHODS: An interpretative phenomenological study was conducted in district Thatta with eight women who experienced more than one stillbirth. A semi-structured in-depth interview guide was used for data collection. The data were analyzed by using thematic analysis approach. RESULTS: The results of this study show that experiencing multiple stillbirths has a devastating impact on women's mental and social wellbeing. The women who experienced multiple stillbirths are stigmatized as "child-killer" or cursed or being punished by God. They are avoided in social gatherings within the families and community, because of these social pressures these women seek spiritual and religious treatment, and struggle to conceive again to deliver a live baby. It was observed that the psycho-social and medical needs of these bereaved women remain unaddressed not only by the healthcare system but also by the society at large. CONCLUSIONS: The physical, social and mental well-being of women who experience multiple stillbirth are at stake. These women are being considered social outcast. Health care providers including physicians, lady health workers, and traditional birth attendants should be trained on provision of psychosocial support along with the routine care that they provide in communities and health facilities. The health care providers should also inform the bereaved women about the biomedical causes of stillbirths that would be helpful to mitigate the stigma associated with stillbirths. Moreover, the health care providers should also counsel family members especially in-laws of these sorrowful women about the biomedical causes of stillbirths that would also be helpful to mitigate the stigma associated with stillbirths.

What stops us from eating: a qualitative investigation of dietary barriers during pregnancy in Punjab, Pakistan.

OBJECTIVE: Adequate dietary intake during pregnancy is vital for the health and nutritional status of both mother and fetus. The nutritional status of reproductive age women in Pakistan is poor, with 14 % being underweight (BMI < 18·5) and 42 % experiencing Fe deficiency anaemia. This may stem from beliefs, practices and other barriers influencing dietary intake. This qualitative study seeks to determine which factors impact dietary intake during pregnancy in rural Punjab. DESIGN: In-depth interviews and focus group discussions were conducted and then analysed using thematic analysis. SETTING: Three purposively selected rural districts (Sahiwal, Okara and Pakpatan) with the highest prevalence of maternal and child malnutrition in the province of Punjab, Pakistan. PARTICIPANTS: Mothers with children under age two (n 29) and healthcare providers with at least 5 years of experience working in the district (n 12). RESULTS: We identified a combination of physiological, socio-cultural and structural barriers that inhibited healthful dietary intake during pregnancy. The primary physiological barriers to optimal dietary intake and dietary practices included food aversions and food cravings. Food classification, fear of a difficult childbirth, fear of high blood pressure and household food politics were the principal socio-cultural barriers. Additionally, two structural barriers, inadequate antenatal counseling and a lack of affordable food options, were identified. CONCLUSIONS: Our study demonstrates that complex barriers prevent pregnant women in the Punjab area from consuming adequate dietary intake and that antenatal health education programmes and structural interventions are needed to support healthful dietary practices during this critical period.

Multi-Mobile Agent Trust Framework for Mitigating Internal Attacks and Augmenting RPL Security.

Recently, the Internet of Things (IoT) has emerged as an important way to connect diverse physical devices to the internet. The IoT paves the way for a slew of new cutting-edge applications. Despite the prospective benefits and many security solutions offered in the literature, the security of IoT networks remains a critical concern, considering the massive amount of data generated and transmitted. The resource-constrained, mobile, and heterogeneous nature of the IoT makes it increasingly challenging to preserve security in routing protocols, such as the routing protocol for low-power and lossy networks (RPL). RPL does not offer good protection against routing attacks, such as rank, Sybil, and sinkhole attacks. Therefore, to augment the security of RPL, this article proposes the energy-efficient multi-mobile agent-based trust framework for RPL (MMTM-RPL). The goal of MMTM-RPL is to mitigate internal attacks in IoT-based wireless sensor networks using fog layer capabilities. MMTM-RPL mitigates rank, Sybil, and sinkhole attacks while minimizing energy and message overheads by 25-30% due to the use of mobile agents and dynamic itineraries. MMTM-RPL enhances the security of RPL and improves network lifetime (by 25-30% or more) and the detection rate (by 10% or more) compared to state-of-the-art approaches, namely, DCTM-RPL, RBAM-IoT, RPL-MRC, and DSH-RPL.

Location and Time Aware Multitask Allocation in Mobile Crowd-Sensing Based on Genetic Algorithm.

Mobile crowd-sensing (MCS) is a well-known paradigm used for obtaining sensed data by using sensors found in smart devices. With the rise of more sensing tasks and workers in the MCS system, it is now essential to design an efficient approach for task allocation. Moreover, to ensure the completion of the tasks, it is necessary to incentivise the workers by rewarding them for participating in performing the sensing tasks. In this paper, we aim to assist workers in selecting multiple tasks while considering the time constraint of the worker and the requirements of the task. Furthermore, a pricing mechanism is adopted to determine each task budget, which is then used to determine the payment for the workers based on their willingness factor. This paper proves that the task-allocation is a non-deterministic polynomial (NP)-complete problem, which is difficult to solve by conventional optimization techniques. A worker multitask allocation-genetic algorithm (WMTA-GA) is proposed to solve this problem to maximize the workers welfare. Finally, theoretical analysis demonstrates the effectiveness of the proposed WMTA-GA. We observed that it performs better than the state-of-the-art algorithms in terms of average performance, workers welfare, and the number of assigned tasks.

Circ-LocNet: A Computational Framework for Circular RNA Sub-Cellular Localization Prediction.

Circular ribonucleic acids (circRNAs) are novel non-coding RNAs that emanate from alternative splicing of precursor mRNA in reversed order across exons. Despite the abundant presence of circRNAs in human genes and their involvement in diverse physiological processes, the functionality of most circRNAs remains a mystery. Like other non-coding RNAs, sub-cellular localization knowledge of circRNAs has the aptitude to demystify the influence of circRNAs on protein synthesis, degradation, destination, their association with different diseases, and potential for drug development. To date, wet experimental approaches are being used to detect sub-cellular locations of circular RNAs. These approaches help to elucidate the role of circRNAs as protein scaffolds, RNA-binding protein (RBP) sponges, micro-RNA (miRNA) sponges, parental gene expression modifiers, alternative splicing regulators, and transcription regulators. To complement wet-lab experiments, considering the progress made by machine learning approaches for the determination of sub-cellular localization of other non-coding RNAs, the paper in hand develops a computational framework, Circ-LocNet, to precisely detect circRNA sub-cellular localization. Circ-LocNet performs comprehensive extrinsic evaluation of 7 residue frequency-based, residue order and frequency-based, and physio-chemical property-based sequence descriptors using the five most widely used machine learning classifiers. Further, it explores the performance impact of K-order sequence descriptor fusion where it ensembles similar as well dissimilar genres of statistical representation learning approaches to reap the combined benefits. Considering the diversity of statistical representation learning schemes, it assesses the performance of second-order, third-order, and going all the way up to seventh-order sequence descriptor fusion. A comprehensive empirical evaluation of Circ-LocNet over a newly developed benchmark dataset using different settings reveals that standalone residue frequency-based sequence descriptors and tree-based classifiers are more suitable to predict sub-cellular localization of circular RNAs. Further, K-order heterogeneous sequence descriptors fusion in combination with tree-based classifiers most accurately predict sub-cellular localization of circular RNAs. We anticipate this study will act as a rich baseline and push the development of robust computational methodologies for the accurate sub-cellular localization determination of novel circRNAs.