Domestic violence and its relationship with depression, anxiety and quality of life: A hidden dilemma of Pakistani women.

OBJECTIVES: To find out the relationship of domestic violence with depression, anxiety and quality of life in married women in hospitals of Rawalpindi and Islamabad. METHODS: This co-relational study was conducted in Rawalpindi Institute of Health Sciences from January 2019 to December 2019. All the females' patients who were the victim of domestic violence were the population of the study. Consecutive non-probability sampling technique was used for selection of sampling from the target population. The inclusion criterion for this study was diagnosed case of domestic violence. DASS 21 (The Depression, Anxiety and Stress Scale) and Quality of life (WHO) scales were administered to 116 patients. RESULTS: The study's key results were that domestic abuse has positive relationship with depression, anxiety, and stress. It was also found that domestic abuse has a negative relationship with quality of life of those who have been subjected to domestic violence of this sort. CONCLUSION: It was concluded that domestic violence whether verbal, physical, emotional or sexual has strongly effects the mental health and quality of life of abused women.

Changing trends in anti-psychotic prescription pattern in Pakistan.

BACKGROUND AND OBJECTIVE: This study was designed to identify the changing trends in Anti-psychotic prescription pattern in Pakistan. It was part of the research project Research on East Asian Psychotropic Prescription Pattern (REAP) carried out to identify the prescription patterns of schizophrenic patients in different countries located in Asia.Our objective was to assess the trend and change of psychotropic drug prescriptions for patients with schizophrenia. METHODS: The design of the study was quantitative and of descriptive epidemiology. This study was carried out from 30th March 2017. Data was collected on a unified protocol by the Psychiatrists from Pakistan. Three (3) centers i.e., Lahore, Karachi and Islamabad provided the data. Indoor and outdoor cases with Schizophrenia were recruited. A web based recording system for collection of data done at Taipei Taiwan, and statistical analysis was performed and transferred to all participating centers including Pakistan. RESULTS: The main findings of the study were that majority of the patients were prescribed antipsychotic poly pharmacy drug. It was also found that Anxiolytics, anti-depressants and Anti-parkinsonian drugs were also co-prescribed. CONCLUSION: It was concluded that antipsychotic poly pharmacy along with Anxiolytics, anti-depressants and Anti-parkinsonian drugs were prescribed to patients with schizophrenia in Pakistan.

Enhancing healthcare IoT systems for diabetic patient monitoring: Integration of Harris Hawks and grasshopper optimization algorithms.

The integration of the Internet of Things (IoT) in healthcare, especially for people with diabetes, allows for constant health monitoring. This means that doctors can watch over patients' health more closely, making sure they catch any issues early on. With this technology, healthcare workers can be more accurate and effective when keeping an eye on how patients are doing. This not only helps in keeping track of patients' health in real-time but also makes the whole process more reliable and efficient.By implementing appropriate routing techniques, the transmission of diabetic patients' data to medical centers will facilitate real-time and timely responses from healthcare professionals. The grasshopper optimization algorithm is employed in the proposed approach to cluster network nodes, resulting in the formation of a network tree that facilitates the establishment of connections between the cluster head and the base station. After identifying the cluster head and establishing the clusters, the second stage of routing is implemented by employing the Harris Hawks optimization algorithm. This algorithm ensures that the data pertaining to diabetic patients is transmitted to the treatment centers and hospitals with minimal delay. For node routing, the optimal next step is selected based on the parameters such as the residual energy of the node, the ratio of delivered data packages, and the number of the neighbors of the node. To continue, first, the MATLAB software is utilized to simulate the proposed method, and then, it is compared with other similar methods. This comparison is conducted based on various parameters, including delay, energy consumption, network throughput, and network lifespan. Compared to other methods, the proposed method demonstrates a significant 33% improvement in the average point-to-point delay parameter in the subsequent iterations or rounds.

A model for skin cancer using combination of ensemble learning and deep learning.

Skin cancer has a significant impact on the lives of many individuals annually and is recognized as the most prevalent type of cancer. In the United States, an estimated annual incidence of approximately 3.5 million people receiving a diagnosis of skin cancer underscores its widespread prevalence. Furthermore, the prognosis for individuals afflicted with advancing stages of skin cancer experiences a substantial decline in survival rates. This paper is dedicated to aiding healthcare experts in distinguishing between benign and malignant skin cancer cases by employing a range of machine learning and deep learning techniques and different feature extractors and feature selectors to enhance the evaluation metrics. In this paper, different transfer learning models are employed as feature extractors, and to enhance the evaluation metrics, a feature selection layer is designed, which includes diverse techniques such as Univariate, Mutual Information, ANOVA, PCA, XGB, Lasso, Random Forest, and Variance. Among transfer models, DenseNet-201 was selected as the primary feature extractor to identify features from data. Subsequently, the Lasso method was applied for feature selection, utilizing diverse machine learning approaches such as MLP, XGB, RF, and NB. To optimize accuracy and precision, ensemble methods were employed to identify and enhance the best-performing models. The study provides accuracy and sensitivity rates of 87.72% and 92.15%, respectively.

Brain IL-6 elevation causes neuronal circuitry imbalances and mediates autism-like behaviors.

Abnormal immune responses have been reported to be associated with autism. A number of studies showed that cytokines were increased in the blood, brain, and cerebrospinal fluid of autistic subjects. Elevated IL-6 in autistic brain has been a consistent finding. However, the mechanisms by which IL-6 may be involved in the pathogenesis of autism are not well understood. Here we show that mice with elevated IL-6 in the brain display many autistic features, including impaired cognitive abilities, deficits in learning, abnormal anxiety traits and habituations, as well as decreased social interactions. IL-6 elevation caused alterations in excitatory and inhibitory synaptic formations and disrupted the balance of excitatory/inhibitory synaptic transmissions. IL-6 elevation also resulted in an abnormal change in the shape, length and distributing pattern of dendritic spines. These findings suggest that IL-6 elevation in the brain could mediate autistic-like behaviors, possibly through the imbalances of neural circuitry and impairments of synaptic plasticity.

An energy-aware routing method using firefly algorithm for flying ad hoc networks.

Flying ad-hoc networks (FANETs) include a large number of drones, which communicate with each other based on an ad hoc model. These networks provide new opportunities for various applications such as military, industrial, and civilian applications. However, FANETs have faced with many challenges like high-speed nodes, low density, and rapid changes in the topology. As a result, routing is a challenging issue in these networks. In this paper, we propose an energy-aware routing scheme in FANETs. This scheme is inspired by the optimized link state routing (OLSR). In the proposed routing scheme, we estimate the connection quality between two flying nodes using a new technique, which utilizes two parameters, including ratio of sent/received of hello packets and connection time. Also, our proposed method selects multipoint relays (MPRs) using the firefly algorithm. It chooses a node with high residual energy, high connection quality, more neighborhood degree, and higher willingness as MPR. Finally, our proposed scheme creates routes between different nodes based on energy and connection quality. Our proposed routing scheme is simulated using the network simulator version 3 (NS3). We compare its simulation results with the greedy optimized link state routing (G-OLSR) and the optimized link state routing (OLSR). These results show that our method outperforms G-OLSR and OLSR in terms of delay, packet delivery rate, throughput, and energy consumption. However, our proposed routing scheme increases slightly routing overhead compared to G-OLSR.

A secure routing approach based on league championship algorithm for wireless body sensor networks in healthcare.

Patients must always communicate with their doctor for checking their health status. In recent years, wireless body sensor networks (WBSNs) has an important contribution in Healthcare. In these applications, energy-efficient and secure routing is really critical because health data of individuals must be forwarded to the destination securely to avoid unauthorized access by malicious nodes. However, biosensors have limited resources, especially energy. Recently, energy-efficient solutions have been proposed. Nevertheless, designing lightweight security mechanisms has not been stated in many schemes. In this paper, we propose a secure routing approach based on the league championship algorithm (LCA) for wireless body sensor networks in healthcare. The purpose of this scheme is to create a tradeoff between energy consumption and security. Our approach involves two important algorithms: routing process and communication security. In the first algorithm, each cluster head node (CH) applies the league championship algorithm to choose the most suitable next-hop CH. The proposed fitness function includes parameters like distance from CHs to the sink node, remaining energy, and link quality. In the second algorithm, we employs a symmetric encryption strategy to build secure connection links within a cluster. Also, we utilize an asymmetric cryptography scheme for forming secure inter-cluster connections. Network simulator version 2 (NS2) is used to implement the proposed approach. The simulation results show that our method is efficient in terms of consumed energy and delay. In addition, our scheme has good throughput, high packet delivery rate, and low packet loss rate.

Alteration of astrocytes and Wnt/ß-catenin signaling in the frontal cortex of autistic subjects.

BACKGROUND: Autism is a neurodevelopmental disorder characterized by impairments in social interaction, verbal communication and repetitive behaviors. To date the etiology of this disorder is poorly understood. Studies suggest that astrocytes play critical roles in neural plasticity by detecting neuronal activity and modulating neuronal networks. Recently, a number of studies suggested that an abnormal function of glia/astrocytes may be involved in the development of autism. However, there is yet no direct evidence showing how astrocytes develop in the brain of autistic individuals. METHODS: Study subjects include brain tissue from autistic subjects, BTBR T + tfJ (BTBR) and Neuroligin (NL)-3 knock-down mice. Western blot analysis, Immunohistochemistry and confocal microscopy studies have be used to examine the density and morphology of astrocytes, as well as Wnt and ß-catenin protein expression. RESULTS: In this study, we demonstrate that the astrocytes in autisitcsubjects exhibit significantly reduced branching processes, total branching length and cell body sizes. We also detected an astrocytosis in the frontal cortex of autistic subjects. In addition, we found that the astrocytes in the brain of an NL3 knockdown mouse exhibited similar alterations to what we found in the autistic brain. Furthermore, we detected that both Wnt and ß-catenin proteins are decreased in the frontal cortex of autistic subjects. Wnt/ß-catenin pathway has been suggested to be involved in the regulation of astrocyte development. CONCLUSIONS: Our findings imply that defects in astrocytes could impair neuronal plasticity and partially contribute to the development of autistic-like behaviors in both humans and mice. The alteration of Wnt/ß-catenin pathway in the brain of autistic subjects may contribute to the changes of astrocytes.

Abnormal cell properties and down-regulated FAK-Src complex signaling in B lymphoblasts of autistic subjects.

Recent studies suggest that one of the major pathways to the pathogenesis of autism is reduced cell migration. Focal adhesion kinase (FAK) has an important role in neural migration, dendritic morphological characteristics, axonal branching, and synapse formation. The FAK-Src complex, activated by upstream reelin and integrin ß1, can initiate a cascade of phosphorylation events to trigger multiple intracellular pathways, including mitogen-activated protein kinase-extracellular signal-regulated kinase and phosphatidylinositol 3-kinase-Akt signaling. In this study, by using B lymphoblasts as a model, we tested whether integrin ß1 and FAK-Src signaling are abnormally regulated in autism and whether abnormal FAK-Src signaling leads to defects in B-lymphoblast adhesion, migration, proliferation, and IgG production. To our knowledge, for the first time, we show that protein expression levels of both integrin ß1 and FAK are significantly decreased in autistic lymphoblasts and that Src protein expression and the phosphorylation of an active site (Y416) are also significantly decreased. We also found that lymphoblasts from autistic subjects exhibit significantly decreased migration, increased adhesion properties, and an impaired capacity for IgG production. The overexpression of FAK in autistic lymphoblasts countered the adhesion and migration defects. In addition, we demonstrate that FAK mediates its effect through the activation of Src, phosphatidylinositol 3-kinase-Akt, and mitogen-activated protein kinase signaling cascades and that paxillin is also likely involved in the regulation of adhesion and migration in autistic lymphoblasts.

Mental retardation linked to mutations in the HSD17B10 gene interfering with neurosteroid and isoleucine metabolism.

Mutations in the HSD17B10 gene were identified in two previously described mentally retarded males. A point mutation c.776G>C was found from a survivor (SV), whereas a potent mutation, c.419C>T, was identified in another deceased case (SF) with undetectable hydroxysteroid (17beta) dehydrogenase 10 (HSD10) activity. Protein levels of mutant HSD10(R130C) in patient SF and HSD10(E249Q) in patient SV were about half that of HSD10 in normal controls. The E249Q mutation appears to affect HSD10 subunit interactions, resulting in an allosteric regulatory enzyme. For catalyzing the oxidation of allopregnanolone by NAD+ the Hill coefficient of the mutant enzyme is approximately 1.3. HSD10(E249Q) was unable to catalyze the dehydrogenation of 2-methyl-3-hydroxybutyryl-CoA and the oxidation of allopregnanolone, a positive modulator of the gamma-aminobutyric acid type A receptor, at low substrate concentrations. Neurosteroid homeostasis is critical for normal cognitive development, and there is increasing evidence that a blockade of isoleucine catabolism alone does not commonly cause developmental disabilities. The results support the theory that an imbalance in neurosteroid metabolism could be a major cause of the neurological handicap associated with hydroxysteroid (17beta) dehydrogenase 10 deficiency.

SecAODV: A Secure Healthcare Routing Scheme Based on Hybrid Cryptography in Wireless Body Sensor Networks.

In recent decades, the use of sensors has dramatically grown to monitor human body activities and maintain the health status. In this application, routing and secure data transmission are very important to prevent the unauthorized access by attackers to health data. In this article, we propose a secure routing scheme called SecAODV for heterogeneous wireless body sensor networks. SecAODV has three phases: bootstrapping, routing between cluster head nodes, and communication security. In the bootstrapping phase, the base station loads system parameters and encryption functions in the memory of sensor nodes. In the routing phase, each cluster head node calculates its degree based on several parameters, including, distance, residual energy, link quality, and the number of hops, to decide for rebroadcasting the route request (RREQ) message. In the communication security phase, a symmetric cryptography method is used to protect intra-cluster communications. Also, an asymmetric cryptography method is used to secure communication links between cluster head nodes. The proposed secure routing scheme is simulated in the network simulator version 2 (NS2) simulator. The simulation results are compared with the secure multi tier energy-efficient routing scheme (SMEER) and the centralized low-energy adaptive clustering hierarchy (LEACH-C). The results show that SecAODV improves end-to-end delay, throughput, energy consumption, packet delivery rate (PDR), and packet loss rate (PLR).

An energy-aware and Q-learning-based area coverage for oil pipeline monitoring systems using sensors and Internet of Things.

Pipelines are the safest tools for transporting oil and gas. However, the environmental effects and sabotage of hostile people cause corrosion and decay of pipelines, which bring financial and environmental damages. Today, new technologies such as the Internet of Things (IoT) and wireless sensor networks (WSNs) can provide solutions to monitor and timely detect corrosion of oil pipelines. Coverage is a fundamental challenge in pipeline monitoring systems to timely detect and resolve oil leakage and pipeline corrosion. To ensure appropriate coverage on pipeline monitoring systems, one solution is to design a scheduling mechanism for nodes to reduce energy consumption. In this paper, we propose a reinforcement learning-based area coverage technique called CoWSN to intelligently monitor oil and gas pipelines. In CoWSN, the sensing range of each sensor node is converted to a digital matrix to estimate the overlap of this node with other neighboring nodes. Then, a Q-learning-based scheduling mechanism is designed to determine the activity time of sensor nodes based on their overlapping, energy, and distance to the base station. Finally, CoWSN can predict the death time of sensor nodes and replace them at the right time. This work does not allow to be disrupted the data transmission process between sensor nodes and BS. CoWSN is simulated using NS2. Then, our scheme is compared with three area coverage schemes, including the scheme of Rahmani et al., CCM-RL, and CCA according to several parameters, including the average number of active sensor nodes, coverage rate, energy consumption, and network lifetime. The simulation results show that CoWSN has a better performance than other methods.

IL-6 is increased in the cerebellum of autistic brain and alters neural cell adhesion, migration and synaptic formation.

BACKGROUND: Although the cellular mechanisms responsible for the pathogenesis of autism are not understood, a growing number of studies have suggested that localized inflammation of the central nervous system (CNS) may contribute to the development of autism. Recent evidence shows that IL-6 has a crucial role in the development and plasticity of CNS. METHODS: Immunohistochemistry studies were employed to detect the IL-6 expression in the cerebellum of study subjects. In vitro adenoviral gene delivery approach was used to over-express IL-6 in cultured cerebellar granule cells. Cell adhesion and migration assays, DiI labeling, TO-PRO-3 staining and immunofluorescence were used to examine cell adhesion and migration, dendritic spine morphology, cell apoptosis and synaptic protein expression respectively. RESULTS: In this study, we found that IL-6 was significantly increased in the cerebellum of autistic subjects. We investigated how IL-6 affects neural cell development and function by transfecting cultured mouse cerebellar granule cells with an IL-6 viral expression vector. We demonstrated that IL-6 over-expression in granule cells caused impairments in granule cell adhesion and migration but had little effect on the formation of dendritic spines or granule cell apoptosis. However, IL-6 over-expression stimulated the formation of granule cell excitatory synapses, without affecting inhibitory synapses. CONCLUSIONS: Our results provide further evidence that aberrant IL-6 may be associated with autism. In addition, our results suggest that the elevated IL-6 in the autistic brain could alter neural cell adhesion, migration and also cause an imbalance of excitatory and inhibitory circuits. Thus, increased IL-6 expression may be partially responsible for the pathogenesis of autism.

A novel approach for characterization of cathepsin D protease and its effect on tau and ß-amyloid proteins.

Cathepsin D is the lysosomal protease abundantly expressed in the brain. It plays an important role in the regulation of cellular apoptosis. In addition, cathepsin D has been shown to be involved in the pathogenesis of Alzheimer disease and autism. In this study, we developed a novel approach for the preparation of highly purified cathepsin D from the calf brain. This high grade purification is achieved by using DEAE-Sephacel Chromatography before the final step of applying to the Pepstatin-Sepharose 4B column. The properties of cathepsin D have also been studied. We show that cathepsin D cleaves both tau and ß-amyloid precursor protein (APP). Both tau and APP are involved in the pathogenesis of Alzheimer's disease. Our findings strongly suggest a link between the lysosomal dysfunction of cathepsin D and the etiology of Alzheimer's disease. Our findings also indicate that cathepsin D could be a new approach to treating Alzheimer's disease.

NF-κB signaling in the brain of autistic subjects.

Autism is a neurodevelopmental disorder characterized by problems in communication, social skills, and repetitive behavior. Recent studies suggest that apoptotic and inflammatory mechanisms may contribute to the pathogenesis of this disorder. Nuclear factor-κB (NF-κB) is an important gene transcriptional factor involved in the mediation of inflammation and apoptosis. This study examined the activities of the NF-κB signaling pathway in the brain of autistic subjects and their age-matched controls. The NF-κB activation is also determined in the brain of BTBR mice, which is a promising animal model for study of pathogenic mechanisms responsible for autism. Our results showed that the level of IKKα kinase, which phosphorylates the inhibitory subunit IκBα, is significantly increased in the cerebellum of autistic subjects. However, the expression and phosphorylation of IκBα are not altered. In addition, our results demonstrated that the expression of NF-κB (p65), and the phosphorylation/activation of NF-κB (p65) at Ser536 are not significantly changed in the cerebellum and cortex of both autistic subjects and BTBR mice. Our findings suggest that the NF-κB signaling pathway is not disregulated in the brain of autistic subjects and thus may not be significantly involved in the processes of abnormal inflammatory responses suggested in autistic brain.

BDNF-Akt-Bcl2 antiapoptotic signaling pathway is compromised in the brain of autistic subjects.

Although the pathogenesis of autism is not understood, emerging evidence points to apoptotic mechanisms being involved in this disorder. However, it is not known whether apoptosis signaling is deregulated in the brain of autistic subjects. This study investigates how the apoptosis-related proteins are regulated in the autistic brain. Our studies show that Bcl2 is significantly decreased, whereas the expression of p53 is increased, in the brain of autistic subjects in comparison with age-matched controls. We also found that the expression and phosphorylation/activation of Akt kinase that regulates Bcl2 are significantly decreased in the autistic brain. The down-regulation of Akt may result from a decreased concentration of brain-derived neurotrophic factor (BDNF), the growth factor that modulates Akt activities. These results suggest that down-regulation of the BDNF-Akt-Bcl2 antiapoptotic signaling pathway in the autistic brain could be one of the underlying mechanisms responsible for the pathogenesis of autism.

Elevated immune response in the brain of autistic patients.

UNLABELLED: This study determined immune activities in the brain of ASD patients and matched normal subjects by examining cytokines in the brain tissue. Our results showed that proinflammatory cytokines (TNF-alpha, IL-6 and GM-CSF), Th1 cytokine (IFN-gamma) and chemokine (IL-8) were significantly increased in the brains of ASD patients compared with the controls. However the Th2 cytokines (IL-4, IL-5 and IL-10) showed no significant difference. The Th1/Th2 ratio was also significantly increased in ASD patients. CONCLUSION: ASD patients displayed an increased innate and adaptive immune response through the Th1 pathway, suggesting that localized brain inflammation and autoimmune disorder may be involved in the pathogenesis of ASD.

Binding of trypsin to fibrillar amyloid beta-protein.

We have recently reported that fibrillar amyloid beta-protein (Abeta) inhibits the proteolytic activity of trypsin and high molecular weight bovine brain protease. We report here that trypsin binds to fibrillar Abeta (fAbeta) and the resulting complex of trypsin/fAbeta is sodium dodecyl sulfate (SDS)-stable. Electron microscopic analysis confirmed the binding of trypsin on the fibrils of both Abeta 1-40 and Abeta 1-42. SDS-polyacrylamide gel electrophoresis (PAGE) of fAbeta sample incubated in the presence of trypsin showed that major amount of trypsin was associated with fAbeta that did not enter the gel. The presence of trypsin in this protein complex was confirmed by Western blotting after its elution from the gel. Kinetic studies showed that the binding of trypsin to fibrillar Abeta was dependent on the degree of Abeta fibrillization and on the concentration of fAbeta. However, the trypsin binding to Abeta oligomers did not affect the fibril growth. The maximum binding (B(max)) of trypsin to fAbeta 1-40 and fAbeta 1-42 was 36 pmol and 40 pmol, and dissociation constant (K(d)) was 18.31 microM and 20 microM respectively. Similar to fAbeta, trypsin could also bind to fibrillar amylin. This binding was dependent on the concentration of fibrillar amylin. Under similar conditions, bovine serum albumin did not bind to fibrillar Abeta. These results suggest that fAbeta and fibrillar amylin have strong affinities for trypsin, and chelation of proteases by abnormal aggregated proteins may be a general mechanism for inflicting pathological conditions in various diseases.

Fibrillar amyloid beta-protein inhibits the activity of high molecular weight brain protease and trypsin.

The effect of soluble amyloid beta-protein (sAbeta) and fibrillar amyloid beta-protein (fAbeta) on the casein-digesting activity of high molecular weight bovine brain protease (HMW protease) and trypsin was studied. While sAbeta stimulated the casein-digesting activity of HMW protease in a concentration-dependent manner, it did not affect trypsin activity. Structure-activity relationship was studied by testing different soluble and fibrillar Abeta peptides. Various Abeta peptides affected casein-digesting activity of HMW protease differently: sAbeta 1-40 > sAbeta 22-35 = sAbeta 1-11 = sAbeta1-16 > sAbeta 1-28 = sAbeta 31-35, while sAbeta 12-28 and sAbeta 25-35 had no effect. On the other hand, among the fibrillar beta peptides, only fAbeta 1-40 significantly inhibited the casein-digesting activity of HMW protease. Tricine gel electrophoresis showed that sAbeta was digested by trypsin while it remained un-cleaved in the presence of HMW protease. However, fAbeta, a major component of amyloid plaques in Alzheimer's disease, inhibited the casein-digesting activity of both HMW protease and trypsin. fAbetawas found to be resistant to proteolysis by HMW protease and trypsin. The trypsin resistance starts in the early stage of fibrillization of Abeta, i.e., aggregated Abeta. Taken together, these results suggest that fibrillization of Abeta may affect the clearance of Abeta by inhibiting the brain proteases, thereby increasing the concentration of circulating Abeta, that may further increase the Abeta fibrillization.