Ion transporter cascade, reactive astrogliosis and cerebrovascular diseases.

Cerebrovascular diseases and their sequalae, such as ischemic stroke, chronic cerebral hypoperfusion, and vascular dementia are significant contributors to adult disability and cognitive impairment in the modern world. Astrocytes are an integral part of the neurovascular unit in the CNS and play a pivotal role in CNS homeostasis, including ionic and pH balance, neurotransmission, cerebral blood flow, and metabolism. Astrocytes respond to cerebral insults, inflammation, and diseases through unique molecular, morphological, and functional changes, collectively known as reactive astrogliosis. The function of reactive astrocytes has been a subject of debate. Initially, astrocytes were thought to primarily play a supportive role in maintaining the structure and function of the nervous system. However, recent studies suggest that reactive astrocytes may have both beneficial and detrimental effects. For example, in chronic cerebral hypoperfusion, reactive astrocytes can cause oligodendrocyte death and demyelination. In this review, we will summarize the (1) roles of ion transporter cascade in reactive astrogliosis, (2) role of reactive astrocytes in vascular dementia and related dementias, and (3) potential therapeutic approaches for dementing disorders targeting reactive astrocytes. Understanding the relationship between ion transporter cascade, reactive astrogliosis, and cerebrovascular diseases may reveal mechanisms and targets for the development of therapies for brain diseases associated with reactive astrogliosis.

Exploring post-COVID-19 health effects and features with advanced machine learning techniques.

COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a range of outcomes including recovery, continued health issues, and the loss of life. Among those who have recovered, many experience negative health effects, particularly influenced by demographic factors such as gender and age, as well as physiological and neurological factors like sleep patterns, emotional states, anxiety, and memory. This research aims to explore various health factors affecting different demographic profiles and establish significant correlations among physiological and neurological factors in the post-COVID-19 state. To achieve these objectives, we have identified the post-COVID-19 health factors and based on these factors survey data were collected from COVID-recovered patients in Bangladesh. Employing diverse machine learning algorithms, we utilised the best prediction model for post-COVID-19 factors. Initial findings from statistical analysis were further validated using Chi-square to demonstrate significant relationships among these elements. Additionally, Pearson's coefficient was utilized to indicate positive or negative associations among various physiological and neurological factors in the post-COVID-19 state. Finally, we determined the most effective machine learning model and identified key features using analytical methods such as the Gini Index, Feature Coefficients, Information Gain, and SHAP Value Assessment. And found that the Decision Tree model excelled in identifying crucial features while predicting the extent of post-COVID-19 impact.

SPAK inhibitor ZT-1a attenuates reactive astrogliosis and oligodendrocyte degeneration in a mouse model of vascular dementia.

BACKGROUND: Astrogliosis and white matter lesions (WML) are key characteristics of vascular contributions to cognitive impairment and dementia (VCID). However, the molecular mechanisms underlying VCID remain poorly understood. Stimulation of Na-K-Cl cotransport 1 (NKCC1) and its upstream kinases WNK (with no lysine) and SPAK (the STE20/SPS1-related proline/alanine-rich kinase) play a role in astrocytic intracellular Na+ overload, hypertrophy, and swelling. Therefore, in this study, we assessed the effect of SPAK inhibitor ZT-1a on pathogenesis and cognitive function in a mouse model of VCID induced by bilateral carotid artery stenosis (BCAS). METHODS: Following sham or BCAS surgery, mice were randomly assigned to receive either vehicle (DMSO) or SPAK inhibitor ZT-1a treatment regimen (days 14-35 post-surgery). Mice were then evaluated for cognitive functions by Morris water maze, WML by ex vivo MRI-DTI analysis, and astrogliosis/demyelination by immunofluorescence and immunoblotting. RESULTS: Compared to sham control mice, BCAS-Veh mice exhibited chronic cerebral hypoperfusion and memory impairments, accompanied by significant MRI DTI-detected WML and oligodendrocyte (OL) death. Increased activation of WNK-SPAK-NKCC1-signaling proteins was detected in white matter tissues and in C3d+ GFAP+ cytotoxic astrocytes but not in S100A10+ GFAP+ homeostatic astrocytes in BCAS-Veh mice. In contrast, ZT-1a-treated BCAS mice displayed reduced expression and phosphorylation of NKCC1, decreased astrogliosis, OL death, and WML, along with improved memory functions. CONCLUSION: BCAS-induced upregulation of WNK-SPAK-NKCC1 signaling contributes to white matter-reactive astrogliosis, OL death, and memory impairment. Pharmacological inhibition of the SPAK activity has therapeutic potential for alleviating pathogenesis and memory impairment in VCID.

Health-related quality of life across disease stages in patients with amyotrophic lateral sclerosis: results from a real-world survey.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is characterized by a rapid disease course, with disease severity being associated with declining health-related quality of life (HRQoL) in persons living with ALS (pALS). The main objective of this study was to assess the impact of disease progression on HRQoL across King's, Milano-Torino Staging (MiToS), and physician-judgement clinical staging. Additionally, we evaluated the impact of the disease on the HRQoL of care partners (cALS). METHODS: Data were sourced from the Adelphi ALS Disease Specific Programme (DSP)™, a cross-sectional survey of neurologists, pALS and cALS presenting in a real-world clinical setting between July 2020 and March 2021 in Europe and the United States. RESULTS: Neurologists (n = 142) provided data for 880 pALS. There were significant negative correlations between all three clinical staging systems and EuroQol (European Quality of Life) Five Dimension Five Level Scale (EQ-5D-5L) utility scores and visual analogue scale (VAS) ratings. Although not all differences were significant, 5-item Amyotrophic Lateral Sclerosis Assessment Questionnaire (ALSAQ-5) scores showed a stepwise increase in HRQoL impairment at each stage of the disease regardless of the staging system. At later stages, high levels of fatigue and substantial activity impairment were reported. As pALS disease states progressed, cALS also experienced a decline in HRQoL and increased burden. CONCLUSIONS: Across outcomes, pALS and cALS generally reported worse outcomes at later stages of the disease, highlighting an unmet need in this population for strategies to maximise QoL despite disease progression. Recognition and treatment of symptoms such as pain and fatigue may lead to improved outcomes for pALS and cALS.

Transient ischemic stroke triggers sustained damage of the choroid plexus blood-CSF barrier.

Neuroinflammation is a pathological event associated with many neurological disorders, including dementia and stroke. The choroid plexus (ChP) is a key structure in the ventricles of the brain that secretes cerebrospinal fluid (CSF), forms a blood-CSF barrier, and responds to disease conditions by recruiting immune cells and maintaining an immune microenvironment in the brain. Despite these critical roles, the exact structural and functional changes to the ChP over post-stroke time remain to be elucidated. We induced ischemic stroke in C57BL/6J mice via transient middle cerebral artery occlusion which led to reduction of cerebral blood flow and infarct stroke. At 1-7 days post-stroke, we detected time-dependent increase in the ChP blood-CSF barrier permeability to albumin, tight-junction damage, and dynamic changes of SPAK-NKCC1 protein complex, a key ion transport regulatory system for CSF production and clearance. A transient loss of SPAK protein complex but increased phosphorylation of the SPAK-NKCC1 complex was observed in both lateral ventricle ChPs. Most interestingly, stroke also triggered elevation of proinflammatory Lcn2 mRNA and its protein as well as infiltration of anti-inflammatory myeloid cells in ChP at day 5 post-stroke. These findings demonstrate that ischemic strokes cause significant damage to the ChP blood-CSF barrier, contributing to neuroinflammation in the subacute stage.

The risk of perinatal mortality following short inter-pregnancy intervals-insights from 692 402 pregnancies in 113 Demographic and Health Surveys from 46 countries: a population-based analysis.

BACKGROUND: Inter-pregnancy interval has been identified as a potentially modifiable risk factor to improve perinatal outcomes. We examined the WHO recommended interval of at least 24 months after a livebirth to next pregnancy, and its recommendation of waiting for at least 6 months after a pregnancy loss to improve subsequent pregnancy outcomes. We aimed to estimate the association between inter-pregnancy interval and perinatal mortality using the Demographic and Health Survey reproductive and contraceptive calendar. METHODS: For this population-based analysis, we extracted data for pregnancies with gestational age and pregnancy outcomes from 113 publicly available Demographic and Health Surveys conducted between 2000 and 2022 in 46 countries that included a reproductive or contraceptive calendar module. The primary outcome was perinatal mortality (stillbirth and early neonatal death) while the inter-pregnancy interval was the exposure of interest, grouped into categories of less than 6 months, 6-11 months, 12-17 months, 18-23 months, and 24-59 months. The analysis was stratified by preceding pregnancy outcome (livebirths, stillbirths, or abortions). The Kaplan-Meier method and Cox proportional hazard model were used to calculate the cumulative probability of perinatal mortality and the hazard ratios (HRs). FINDINGS: The analysis sample comprised of 692 402 pregnancies contributed by 570 145 women with a mean age of 28·4 years (SD 5·96). The overall HR of perinatal death was 2·72 (95% CI 2·52-2·93) times higher for an inter-pregnancy interval of less than 6 months compared with the WHO recommended optimal waiting time of 18-23 months following a livebirth. Overall HRs followed a context-related pattern, with the highest ratio of 2·95 (95% CI 2·67-3·25) in sub-Saharan Africa and the lowest of 1·98 (1·47-2·66) in north Africa, west Asia, and Europe. Inter-pregnancy intervals of less than 3 months, 6 months, and 12 months following stillbirth or abortion (spontaneous or induced) do not pose a higher risk for perinatal death in subsequent pregnancy. INTERPRETATION: Our study reaffirms the WHO recommendation on optimal interval between the last livebirth and the next pregnancy of at least 24 months and avoiding pregnancy before 18 months. However, our analysis does not support the WHO recommendation of delaying the next pregnancy for at least 6 months after a pregnancy loss for improved perinatal survival. FUNDING: None.

A Novel Needle Mouse Model of Vascular Cognitive Impairment and Dementia.

Bilateral common carotid artery (CCA) stenosis (BCAS) is a useful model to mimic vascular cognitive impairment and dementia (VCID). However, current BCAS models have the disadvantages of high cost and incompatibility with magnetic resonance imaging (MRI) scanning because of metal implantation. We have established a new low-cost VCID model that better mimics human VCID and is compatible with live-animal MRI. The right and the left CCAs were temporarily ligated to 32- and 34-gauge needles with three ligations, respectively. After needle removal, CCA blood flow, cerebral blood flow, white matter injury (WMI) and cognitive function were measured. In male mice, needle removal led to ∼49.8% and ∼28.2% blood flow recovery in the right and left CCA, respectively. This model caused persistent and long-term cerebral hypoperfusion in both hemispheres (more severe in the left hemisphere), and WMI and cognitive dysfunction in ∼90% of mice, which is more reliable compared with other models. Importantly, these pathologic changes and cognitive impairments lasted for up to 24 weeks after surgery. The survival rate over 24 weeks was 81.6%. Female mice showed similar cognitive dysfunction, but a higher survival rate (91.6%) and relatively milder white matter injury. A novel, low-cost VCID model compatible with live-animal MRI with long-term outcomes was established.SIGNIFICANCE STATEMENT Bilateral common carotid artery (CCA) stenosis (BCAS) is an animal model mimicking carotid artery stenosis to study vascular cognitive impairment and dementia (VCID). However, current BCAS models have the disadvantages of high cost and incompatibility with magnetic resonance imaging (MRI) scanning due to metal implantation. We established a new asymmetric BCAS model by ligating the CCA to various needle gauges followed by an immediate needle removal. Needle removal led to moderate stenosis in the right CCA and severe stenosis in the left CCA. This needle model replicates the hallmarks of VCID well in ∼90% of mice, which is more reliable compared with other models, has ultra-low cost, and is compatible with MRI scanning in live animals. It will provide a new valuable tool and offer new insights for VCID research.

CovTiNet: Covid text identification network using attention-based positional embedding feature fusion.

Covid text identification (CTI) is a crucial research concern in natural language processing (NLP). Social and electronic media are simultaneously adding a large volume of Covid-affiliated text on the World Wide Web due to the effortless access to the Internet, electronic gadgets and the Covid outbreak. Most of these texts are uninformative and contain misinformation, disinformation and malinformation that create an infodemic. Thus, Covid text identification is essential for controlling societal distrust and panic. Though very little Covid-related research (such as Covid disinformation, misinformation and fake news) has been reported in high-resource languages (e.g. English), CTI in low-resource languages (like Bengali) is in the preliminary stage to date. However, automatic CTI in Bengali text is challenging due to the deficit of benchmark corpora, complex linguistic constructs, immense verb inflexions and scarcity of NLP tools. On the other hand, the manual processing of Bengali Covid texts is arduous and costly due to their messy or unstructured forms. This research proposes a deep learning-based network (CovTiNet) to identify Covid text in Bengali. The CovTiNet incorporates an attention-based position embedding feature fusion for text-to-feature representation and attention-based CNN for Covid text identification. Experimental results show that the proposed CovTiNet achieved the highest accuracy of 96.61±.001% on the developed dataset (BCovC) compared to the other methods and baselines (i.e. BERT-M, IndicBERT, ELECTRA-Bengali, DistilBERT-M, BiLSTM, DCNN, CNN, LSTM, VDCNN and ACNN).

Integrating postpartum IUD counselling and insertion into routine maternity care in Nepal: Assessing trends over time.

To meet the postpartum family planning (PPFP) needs of women in Nepal, an intervention was launched to integrate PPFP counselling and postpartum IUD (PPIUD) insertion into maternity care. Women delivering in study hospitals over a period of 18 months were interviewed at the time of delivery and at 15 months following the end of the study enrollment period to assess if the impact of the intervention observed at the end of the study was maintained. Data were collected prior to the intervention, at the middle month of the intervention roll out, at the end of the enrollment period and 15 months after the end of the enrollment period. We compared PPFP counselling and insertion rates before, during, at the end of and after the intervention study period, using cross-tabulation and chi-square tests. Overall, PPFP counselling rates increased from 11% at the baseline month to 45% at the end of the enrollment in February 2017 and remained the same 15 months later in July 2018. PPIUD uptake, however, rose from a negligible 0.1% at the baseline to 4.3% in February 2017, but declined to 3.4% in July 2018. PPIUD uptake among women who were counselled showed a similar trend, increasing from 1.9% at the baseline to 9.6% in February 2017 and declining to 6.0% in July 2018. The intervention had an appreciable continued impact on PPIUD counselling rates and although PPIUD uptake rose during the intervention, this trend was not observed in the 15 months post-study follow up. The impact of the intervention was greater and persistent in hospitals that had a longer period of exposure to intervention. The results suggest that counselling was well integrated with the maternity care, though uptake of PPIUD dropped after intervention activities such as active monitoring, technical supervision, provision of IUDs and training were withdrawn. Trial registration: This study has been registered with Clinical Trial.gov. The registration number is NCT02718222. Details about the study design have been published by Canning et al, 2016.

Rivaroxaban and apixaban are less effective than enoxaparin for the prevention of catheter-induced clotting in vitro.

BACKGROUND: Central venous catheters are prone to clotting, particularly in patients with cancer. Although low-molecular-weight heparin and direct oral anticoagulants, such as apixaban and rivaroxaban, have been evaluated for the prevention of catheter thrombosis, their efficacy remains uncertain. OBJECTIVES: Compare apixaban and rivaroxaban with enoxaparin for the prevention of catheter-induced clotting in vitro. METHODS: To address this uncertainty, we used a well-established microplate-based assay to compare the effects of enoxaparin, apixaban, and rivaroxaban on catheter-induced thrombosis and thrombin generation in human plasma. RESULTS: Consistent with our previous findings, catheter segments shortened the clotting time and promoted thrombin generation. When compared at concentrations with similar anti-factor Xa activity as enoxaparin, apixaban and rivaroxaban were >20-fold less potent than enoxaparin for the prevention of catheter-induced clotting and thrombin generation. CONCLUSION: The prevention of catheter thrombosis in patients with cancer is challenging. Clinical trials are needed to compare the efficacy of low-molecular-weight heparin with that of direct oral anticoagulants both for the prevention and treatment of catheter thrombosis.

How Did We Get Here? Antithrombotic Therapy after Bioprosthetic Aortic Valve Replacement: A Review.

IMPORTANCE: Aortic stenosis is the most common valvular disease, and more than 90% of patients who undergo aortic valve replacement receive a bioprosthetic valve. Yet optimal antithrombotic therapy after bioprosthetic aortic valve replacement remains uncertain, and guidelines provide contradictory recommendations. OBSERVATIONS: Randomized studies of antithrombotic therapy after bioprosthetic aortic valve replacement are small and underpowered. Observational data present opposing, and likely confounded, results. Historically, changes to guidelines have not been informed by high-quality new data. Current guidelines from different professional bodies provide contradictory recommendations despite citing the same evidence. CONCLUSION: Insufficient antithrombotic therapy after bioprosthetic aortic valve replacement has serious implications: ischemic stroke, systemic arterial thromboembolism, and clinical and subclinical valve thromboses. Unnecessarily intense antithrombotic therapy, however, increases risk of bleeding and associated morbidity and mortality. Professional bodies have used the current low-quality evidence and generated incongruent recommendations. Researchers should prioritize generating high-quality, randomized evidence evaluating the risks and benefits of antiplatelet versus anticoagulant therapy after bioprosthetic aortic valve replacement.

Efficacy of novel SPAK inhibitor ZT-1a derivatives (1c, 1d, 1g & 1h) on improving post-stroke neurological outcome and brain lesion in mice.

SPAK inhibitor ZT-1a was previously shown to be neuroprotective in murine ischemic stroke models. In this study, we further examined the efficacy of four ZT-1a derivatives (ZT-1c, -1d, -1g and -1h) on reducing stroke-induced sensorimotor function impairment and brain lesions. Vehicle control (Veh) or ZT-1 derivatives were administered via osmotic pump to adult C57BL/6J mice during 3-21 h post-stroke. Neurological behavior of these mice was assessed at days 1, 3, 5, and 7 post-stroke and MRI T2WI and DTI analysis was subsequently conducted in ex vivo brains. Veh-treated stroke mice displayed sensorimotor function deficits compared to Sham mice. In contrast, mice receiving ZT-1a derivatives displayed significantly lower neurological deficits at days 3-7 post-stroke (p < 0.05), with ZT-1a, ZT-1c and ZT-1d showing greater impact than ZT-1h and ZT-1g. ZT-1a treatment was the most effective in reducing brain lesion volume on T2WI and in preserving NeuN + neurons (p < 0.01), followed by ZT-1d > -1c > -1g > -1h. The Veh-treated stroke mice displayed white matter tissue injury, reflected by reduced fractional anisotropy (FA) or axial diffusivity (AD) values in external capsule, internal capsule and hippocampus. In contrast, only ZT-1a-as well as ZT-1c-treated stroke mice exhibited significantly higher FA and AD values. These findings demonstrate that post-stroke administration of SPAK inhibitor ZT-1a and its derivatives (ZT-1c and ZT-1d) is effective in protecting gray and white matter tissues in ischemic brains, showing a potential for ischemic stroke therapy development.

Leveraging machine learning to analyze sentiment from COVID-19 tweets: A global perspective.

Since the advent of the worldwide COVID-19 pandemic, analyzing public sentiment has become one of the major concerns for policy and decision-makers. While the priority is to curb the spread of the virus, mass population (user) sentiment analysis is equally important. Though sentiment analysis using different state-of-the-art technologies has been focused on during the COVID-19 pandemic, the reasons behind the variations in public sentiment are yet to be explored. Moreover, how user sentiment varies due to the COVID-19 pandemic from a cross-country perspective has been less focused on. Therefore, the objectives of this study are: to identify the most effective machine learning (ML) technique for classifying public sentiments, to analyze the variations of public sentiment across the globe, and to find the critical contributing factors to sentiment variations. To attain the objectives, 12,000 tweets, 3000 each from the USA, UK, and Bangladesh, were rigorously annotated by three independent reviewers. Based on the labeled tweets, four different boosting ML models, namely, CatBoost, gradient boost, AdaBoost, and XGBoost, are investigated. Next, the top performed ML model predicted sentiment of 300,000 data (100,000 from each country). The public perceptions have been analyzed based on the labeled data. As an outcome, the CatBoost model showed the highest (85.8%) F1-score, followed by gradient boost (84.3%), AdaBoost (78.9%), and XGBoost (83.1%). Second, it was revealed that during the time of the COVID-19 pandemic, the sentiments of the people of the three countries mainly were negative, followed by positive and neutral. Finally, this study identified a few critical concerns that impact primarily varying public sentiment around the globe: lockdown, quarantine, hospital, mask, vaccine, and the like.

COVID-19 analytics: Towards the effect of vaccine brands through analyzing public sentiment of tweets.

The COVID-19 outbreak has created effects on everyday life worldwide. Many research teams at major pharmaceutical companies and research institutes in various countries have been producing vaccines since the beginning of the outbreak. There is an impact of gender on vaccine responses, acceptance, and outcomes. Worldwide promotion of the COVID-19 vaccine additionally generates a huge amount of discussions on social media platforms about diverse factors of vaccines including protection and efficacy. Twitter is considered one of the most well-known social media platforms which have been widely used to share a public opinion on vaccine-related problems in the COVID-19 pandemic. However, there is a lack of research work to analyze the public perception of COVID-19 vaccines systematically from a gender perspective. In this paper, we perform an in-depth analysis of the coronavirus vaccine-related tweets to understand the people's sentiment towards various vaccine brands corresponding to the gender level. The proposed method focuses on the effect of COVID-19 vaccines on gender by taking into account descriptive, diagnostic, predictive, and prescriptive analytics on the Twitter dataset. We also conduct experiments with deep learning models to determine the sentiment polarities of tweets, which are positive, neutral, and negative. The results reveal that LSTM performs better compared to other models with an accuracy rate of 85.7%.

Improving Bed Utilization in a Cohort of Bariatric Surgical Patients Using a Perioperative Obstructive Sleep Apnea Treatment and Bed Triage Protocol.

BACKGROUND: Postoperative bariatric management often includes high-intensity monitoring for respiratory complications since > 70% of patients have obstructive sleep apnea. Given the increasing number of bariatric surgeries, there is a need to determine safe and cost-effective processes for postoperative care.The objective of this study was to determine if a novel triage and perioperative management guideline reduces postoperative monitoring and costs following bariatric surgery. METHODS: Using a pre-post design, this is a retrospective analysis of 501 patients who had bariatric surgery. Half the patients were managed with usual care, and the other half received obstructive sleep apnea screening and treatment of moderate/severe obstructive sleep apnea with perioperative continuous positive airway pressure. The intervention group was triaged preoperatively to a postoperative nursing location based on risk factors. RESULTS: There were no significant differences in demographics, comorbidities, frequency, or severity of OSA between groups. In the intervention group, there were fewer admissions to the intensive care unit (2.0% vs 9.1%; p < 0.01) and high acuity unit (9.6% vs 18.3%; p < 0.01). The length of stay was shorter in the intervention group (1.3 vs 2.3 days; p < 0.01) with a 50% reduction in costs. There were no statistically significant differences in the incidence of postoperative respiratory and non-respiratory complications between the two groups. CONCLUSIONS: Most postoperative bariatric surgery patients can be safely managed on the surgical ward with monitoring of routine vitals alone if patients with moderate/severe obstructive sleep apnea receive perioperative continuous positive airway pressure.

Role of SPAK-NKCC1 signaling cascade in the choroid plexus blood-CSF barrier damage after stroke.

BACKGROUND: The mechanisms underlying dysfunction of choroid plexus (ChP) blood-cerebrospinal fluid (CSF) barrier and lymphocyte invasion in neuroinflammatory responses to stroke are not well understood. In this study, we investigated whether stroke damaged the blood-CSF barrier integrity due to dysregulation of major ChP ion transport system, Na+-K+-Cl- cotransporter 1 (NKCC1), and regulatory Ste20-related proline-alanine-rich kinase (SPAK). METHODS: Sham or ischemic stroke was induced in C57Bl/6J mice. Changes on the SPAK-NKCC1 complex and tight junction proteins (TJs) in the ChP were quantified by immunofluorescence staining and immunoblotting. Immune cell infiltration in the ChP was assessed by flow cytometry and immunostaining. Cultured ChP epithelium cells (CPECs) and cortical neurons were used to evaluate H2O2-mediated oxidative stress in stimulating the SPAK-NKCC1 complex and cellular damage. In vivo or in vitro pharmacological blockade of the ChP SPAK-NKCC1 cascade with SPAK inhibitor ZT-1a or NKCC1 inhibitor bumetanide were examined. RESULTS: Ischemic stroke stimulated activation of the CPECs apical membrane SPAK-NKCC1 complex, NF-κB, and MMP9, which was associated with loss of the blood-CSF barrier integrity and increased immune cell infiltration into the ChP. Oxidative stress directly activated the SPAK-NKCC1 pathway and resulted in apoptosis, neurodegeneration, and NKCC1-mediated ion influx. Pharmacological blockade of the SPAK-NKCC1 pathway protected the ChP barrier integrity, attenuated ChP immune cell infiltration or neuronal death. CONCLUSION: Stroke-induced pathological stimulation of the SPAK-NKCC1 cascade caused CPECs damage and disruption of TJs at the blood-CSF barrier. The ChP SPAK-NKCC1 complex emerged as a therapeutic target for attenuating ChP dysfunction and lymphocyte invasion after stroke.

Transfer learning with fine-tuned deep CNN ResNet50 model for classifying COVID-19 from chest X-ray images.

COVID-19 cases are putting pressure on healthcare systems all around the world. Due to the lack of available testing kits, it is impractical for screening every patient with a respiratory ailment using traditional methods (RT-PCR). In addition, the tests have a high turn-around time and low sensitivity. Detecting suspected COVID-19 infections from the chest X-ray might help isolate high-risk people before the RT-PCR test. Most healthcare systems already have X-ray equipment, and because most current X-ray systems have already been computerized, there is no need to transfer the samples. The use of a chest X-ray to prioritize the selection of patients for subsequent RT-PCR testing is the motivation of this work. Transfer learning (TL) with fine-tuning on deep convolutional neural network-based ResNet50 model has been proposed in this work to classify COVID-19 patients from the COVID-19 Radiography Database. Ten distinct pre-trained weights, trained on varieties of large-scale datasets using various approaches such as supervised learning, self-supervised learning, and others, have been utilized in this work. Our proposed i N a t 2021 _ M i n i _ S w A V _ 1 k model, pre-trained on the iNat2021 Mini dataset using the SwAV algorithm, outperforms the other ResNet50 TL models. For COVID instances in the two-class (Covid and Normal) classification, our work achieved 99.17% validation accuracy, 99.95% train accuracy, 99.31% precision, 99.03% sensitivity, and 99.17% F1-score. Some domain-adapted ( I m a g e N e t _ C h e s t X - r a y 14 ) and in-domain (ChexPert, ChestX-ray14) models looked promising in medical image classification by scoring significantly higher than other models.

New-Onset Atrial Fibrillation After Transcatheter Aortic Valve Replacement: A Systematic Review and Meta-Analysis.

OBJECTIVES: The authors aimed to identify risk factors and outcomes associated with new-onset atrial fibrillation (NOAF) after transcatheter aortic valve replacement (TAVR). BACKGROUND: NOAF is a common complication after TAVR, although estimates of the precise occurrence are variable. This study sought to quantify the occurrence of NOAF after TAVR and to explore the outcomes and predictors associated with this complication. METHODS: We searched Medline, EMBASE, and the Cochrane database from 2016 to 2020 for articles that reported NOAF after TAVR. We extracted data for studies published before 2016 from a previous systematic review. We pooled data using a random effects model. RESULTS: We identified 179 studies with 241,712 total participants (55,271 participants with pre-existing atrial fibrillation (AF) were excluded) that reported NOAF from 2008 to 2020. The pooled occurrence of NOAF after TAVR was 9.9% (95% CI: 8.1%-12%). NOAF after TAVR was associated with a longer index hospitalization (mean difference = 2.66 days; 95% CI: 1.05-4.27), a higher risk of stroke in the first 30 days (risk ratio [RR]: 2.35; 95% CI: 2.12-2.61), 30-day mortality (RR: 1.76; 95% CI: 1.12-2.76), major or life-threatening bleeding (RR: 1.60; 95% CI: 1.39-1.84), and permanent pacemaker implantation (RR: 1.12; 95% CI: 1.05-1.18). Risk factors for the development of NOAF after TAVR included higher Society of Thoracic Surgeons score, transapical access, pulmonary hypertension, chronic kidney disease, peripheral vascular disease, and severe mitral regurgitation, suggesting that the risk for NOAF is highest in more comorbid TAVR patients. CONCLUSIONS: NOAF is common after TAVR. Whether AF after TAVR is a causal factor or a marker of sicker patients remains unclear.

NF-κB Signaling-Mediated Activation of WNK-SPAK-NKCC1 Cascade in Worsened Stroke Outcomes of Ang II-Hypertensive Mice.

BACKGROUND: Worsened stroke outcomes with hypertension comorbidity are insensitive to blood pressure-lowering therapies. In an experimental stroke model with comorbid hypertension, we investigated causal roles of ang II (angiotensin II)-mediated stimulation of the brain WNK (with no lysine [K] kinases)-SPAK (STE20/SPS1-related proline/alanine-rich kinase)-NKCC1 (Na-K-Cl cotransporter) complex in worsened outcomes. METHODS: Saline- or ang II-infused C57BL/6J male mice underwent stroke induced by permanent occlusion of the distal branches of the middle cerebral artery. Mice were randomly assigned to receive either vehicle dimethyl sulfoxide/PBS (2 mL/kg body weight/day, IP), a novel SPAK inhibitor, 5-chloro-N-(5-chloro-4-((4-chlorophenyl)(cyano)methyl)-2-methylphenyl)-2-hydroxybenzamide (ZT-1a' 5 mg/kg per day, IP) or a NF-κB (nuclear factor-κB) inhibitor TAT-NBD (transactivator of transcription-NEMO-binding domain' 20 mg/kg per day, IP). Activation of brain NF-κB and WNK-SPAK-NKCC1 cascade as well as ischemic stroke outcomes were examined. RESULTS: Stroke triggered a 2- to 5-fold increase of WNK (isoforms 1, 2, 4), SPAK/OSR1 (oxidative stress-responsive kinase 1), and NKCC1 protein in the ang II-infused hypertensive mouse brains at 24 hours after stroke, which was associated with increased nuclear translocation of phospho-NF-κB protein in the cortical neurons (a Pearson correlation r of 0.77, P<0.005). The upregulation of WNK-SPAK-NKCC1 cascade proteins resulted from increased NF-κB recruitment on Wnk1, Wnk2, Wnk4, Spak, and Nkcc1 gene promoters and was attenuated by NF-κB inhibitor TAT-NBD. Poststroke administration of SPAK inhibitor ZT-1a significantly reduced WNK-SPAK-NKCC1 complex activation, brain lesion size, and neurological function deficits in the ang II-hypertensive mice without affecting blood pressure and cerebral blood flow. CONCLUSIONS: The ang II-induced stimulation of NF-κB transcriptional activity upregulates brain WNK-SPAK-NKCC1 cascade and contributes to worsened ischemic stroke outcomes, illustrating the brain WNK-SPAK-NKCC1 complex as a therapeutic target for stroke with comorbid hypertension.

AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems.

Artificial intelligence (AI) is a leading technology of the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR), with the capability of incorporating human behavior and intelligence into machines or systems. Thus, AI-based modeling is the key to build automated, intelligent, and smart systems according to today's needs. To solve real-world issues, various types of AI such as analytical, functional, interactive, textual, and visual AI can be applied to enhance the intelligence and capabilities of an application. However, developing an effective AI model is a challenging task due to the dynamic nature and variation in real-world problems and data. In this paper, we present a comprehensive view on "AI-based Modeling" with the principles and capabilities of potential AI techniques that can play an important role in developing intelligent and smart systems in various real-world application areas including business, finance, healthcare, agriculture, smart cities, cybersecurity and many more. We also emphasize and highlight the research issues within the scope of our study. Overall, the goal of this paper is to provide a broad overview of AI-based modeling that can be used as a reference guide by academics and industry people as well as decision-makers in various real-world scenarios and application domains.