Circulating tumor DNA and its role in detection, prognosis and therapeutics of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is considered the fifth most prevalent cancer among all types of cancers and has the third most morbidity value. It has the most frequent duplication time and a high recurrence rate. Recently, the most unique technique used is liquid biopsies, which carry many markers; the most prominent is circulating tumor DNA (ctDNA). Varied methods are used to investigate ctDNA, including various forms of polymerase chain reaction (PCR) [emulsion PCR (ePCR), digital PCR (dPCR), and bead, emulsion, amplification, magnetic (BEAMing) PCR]. Hence ctDNA is being recognized as a potential biomarker that permits early cancer detection, treatment monitoring, and predictive data on tumor burden are subjective to therapy or surgery. Numerous ctDNA biomarkers have been investigated based on their alterations such as 1) single nucleotide variations (either insertion or deletion of a nucleotide) markers including TP53, KRAS, and CCND1; 2) copy number variations which include markers such as CDK6, EFGR, MYC and BRAF; 3) DNA methylation (RASSF1A, SEPT9, KMT2C and CCNA2); 4) homozygous mutation includes ctDNA markers as CDKN2A, AXIN1; and 5) gain or loss of function of the genes, particularly for HCC. Various researchers have conducted many studies and gotten fruitful results. Still, there are some drawbacks to ctDNA namely low quantity, fragment heterogeneity, less stability, limited mutant copies and standards, and differential sensitivity. However, plenty of investigations demonstrate ctDNA's significance as a polyvalent biomarker for cancer and can be viewed as a future diagnostic, prognostic and therapeutic agent. This article overviews many conditions in genetic changes linked to the onset and development of HCC, such as dysregulated signaling pathways, somatic mutations, single-nucleotide polymorphisms, and genomic instability. Additionally, efforts are also made to develop treatments for HCC that are molecularly targeted and to unravel some of the genetic pathways that facilitate its early identification.

Identification and prioritization of risks for new entrants in automobile sector using Monte Carlo based approach.

The automotive industry serves as a crucial support system for the economies of industrialized nations in their pursuit of international market competitiveness. Despite this industry's importance, most developing countries face the challenge of acquiring a reasonable economic position at the global level in the automotive sector for various reasons. The most salient reasons include inconsistent government policies, multiple taxes, investor insecurity, political instability, and currency devaluation. Identifying risks is crucial for a new entrant in the already-established automotive industry. The researchers have used multiple (qualitative and quantitative) techniques to identify and prioritize risks in setting up manufacturing plants. The efforts to tackle these identified risks are undertaken at the domestic and government levels to smoothen the establishment of industry. The risks are first identified, in the current study, by reviewing the previous literature and conducting interviews of the various stakeholders (automotive dealers, managers, and customers). Then this study uses Monte Carlo simulation (MCS) approach and develops a risk exposure (high, medium, or low) matrix for the automotive industry of Pakistan. The findings reveal that the depreciation of local currency against the foreign exchange, oligopoly nature of competition, and low market acceptability of new entrants due to their products' image are the most critical risks the automobile industry faces. These findings will help automotive research institutes in developing national policies that specifically aim to support new players in the automotive industry, particularly in addressing high-priority hazards. The results may also provide valuable insights for new participants seeking to identify and address the key challenges in the Pakistani automotive industry before entering it.

Congenital Anomaly Diagnosis of Typical Cardiac Chest Pain Due to Thebesian Veins Draining Into the Left Ventricular Chamber: A Case Report and Review of Literature.

Thebesian veins are microfistulae that drain the coronary arteries directly into one or more chambers of the heart. Persistence of these anomalous connections into adulthood can lead to shunting of blood away from the myocardium causing typical chest pain symptoms with electrocardiogram changes consistent with ischemia. We describe a case of a 77-year-old female who underwent ischemic evaluation for her symptoms found to have significant Thebesian veins. We also engage in a comprehensive review of the literature finding consistencies in the way these cases are presented in the literature.

Quantifying neurodegeneration of the cervical cord and brain in degenerative cervical myelopathy: A multicentre study using quantitative magnetic resonance imaging.

BACKGROUND AND PURPOSE: Simultaneous assessment of neurodegeneration in both the cervical cord and brain across multiple centres can enhance the effectiveness of clinical trials. Thus, this study aims to simultaneously assess microstructural changes in the cervical cord and brain above the stenosis in degenerative cervical myelopathy (DCM) using quantitative magnetic resonance imaging (MRI) in a multicentre study. METHODS: We applied voxelwise analysis with a probabilistic brain/spinal cord template embedded in statistical parametric mappin (SPM-BSC) to process multi parametric mapping (MPM) including effective transverse relaxation rate (R2*), longitudinal relaxation rate (R1), and magnetization transfer (MT), which are indirectly sensitive to iron and myelin content. Regression analysis was conducted to establish associations between neurodegeneration and clinical impairment. Thirty-eight DCM patients (mean age ± SD = 58.45 ± 11.47 years) and 38 healthy controls (mean age ± SD = 41.18 ± 12.75 years) were recruited at University Hospital Balgrist, Switzerland and Toronto Western Hospital, Canada. RESULTS: Remote atrophy was observed in the cervical cord (p = 0.002) and in the left thalamus (0.026) of the DCM group. R1 was decreased in the periaqueductal grey matter (p = 0.014), thalamus (p = 0.001), corpus callosum (p = 0.0001), and cranial corticospinal tract (p = 0.03). R2* was increased in the primary somatosensory cortices (p = 0.008). Sensory impairments were associated with increased iron-sensitive R2* in the thalamus and periaqueductal grey matter in DCM. CONCLUSIONS: Simultaneous assessment of the spinal cord and brain revealed DCM-induced demyelination, iron deposition, and atrophy. The extent of remote neurodegeneration was associated with sensory impairment, highlighting the intricate and expansive nature of microstructural neurodegeneration in DCM, reaching beyond the stenosis level.

Evaluation of medication use and polypharmacy in postoperative cardiac patients: The clinical pharmacist's imperative in a public institute of Pakistan.

As a major concern in the healthcare sector, polypharmacy is correlated with an increased risk of potential drug-drug interactions (pDDIs), treatment costs and adverse drug reactions (ADR). To assess the prevalence of polypharmacy and its associated factors among postoperative cardiac patients admitted to the National Institute of Cardiovascular Diseases (NICVD), a hospital-based cross-sectional study was conducted between November 2021 and April 2022. Medication charts of postoperative patients were reviewed for medication utilization and polypharmacy. Data was collected using a form approved by the Ethical Review Committee (ERC) regarding patient's clinical and demographic characteristics and medications administered. Statistical analysis was performed using the SPSS software version 25.0. Patients were taking an average of 10.3±1.7 medications. The minimum number of drugs taken per patient was 5, while the maximum was 15 drugs. Only 114 (29.7%) received polypharmacy (5-9 drugs) and hyper-polypharmacy (≥10 drugs) was 270 (70.3%). The mean±SD cardiovascular drugs used were 5.45±1.18 and the mean±SD non-cardiovascular drugs were 4.83±1.18. The prevalence of hyper-polypharmacy suggests a critical need for optimized medication management strategies in this population. Incorporating clinical pharmacists within public healthcare institutions can address polypharmacy-related challenges and enhance medication safety, adherence and patient outcomes.

Prevalence of Aortic Root Pathologies in Platypnea-Orthodeoxia Syndrome Secondary to Intra-Cardiac Shunts.

Background: Atrial septal defects can allow right to left shunting of venous blood which presents clinically as platypnea-orthodeoxia syndrome. It is believed that concomitant presence of aortic root pathologies increases the likelihood of shunting. Methods: The study included a review of 510 articles listed in PubMed of patients with platypnea-orthodeoxia syndrome. Case reports of patients with extra-cardiac etiologies of platypnea-orthodeoxia were excluded. Results: We reviewed 191 case reports, and 98 cases (51.3%) had evidence of concomitant aortic root pathology. Furthermore, of the remaining 93 case reports, 69 ones excluded any mention of the nature of the aortic root altogether, further suggesting that this is an underreported number. Conclusions: There is a high prevalence of aortic root pathologies in patients with platypnea-orthodeoxia syndrome secondary to intra-cardiac shunts. In patients with unexplained hypoxemia and incidental finding of aortic root pathology, it may be worthwhile to obtain postural oxygen saturation measurements to exclude intra-cardiac shunts as the potential cause.

Occurrence of fungal microbial contamination in drinking water of megacity of Karachi (Pakistan) and their physico-chemical control.

The water quality in Karachi (Pakistan) is uncertain due to the occurrence of fungi and other microorganisms. A total of twenty-five water samples were collected from public places, educational institutes, hospitals, water supply systems and surface water of the canal of Karachi (Pakistan). The different fungal species including Acremonium sp., Alternaria alternata, Aspergillus flavus, A. fumigatus, A. sulphureus, Cladosporium sp., Fusarium sp., Clonostachys (Gliocladium) sp., Macrophomina phaseolina, Mucor racemosus, Paecilomyces sp. Penicillium chrysogenum, P. citrinum, P. commune, P. expansum, Rhizoctonia sp. and Stachybotrys sp. were isolated from these drinking water samples. However, the bacteria, microalgae and some other microorganisms were present in low concentrations. The reason for fungi infection and production of mycotoxicity depends upon various factors and the availability of their nutrients in filtration plants. The major threats to human health are fungal mycotoxicity which is responsible for carcinogenic and other lethal diseases. Mostly, the genus Aspergillus was dominated and isolated with a maximum of 88-98% of occurrence in the different samples of drinking water by the direct plate-spread method. For the control of fungi, various Physico-chemical coagulation treatments were used, but Potassium alum, clay pot, and hot water treatment disinfected effectively 69-70% removal of the fungi and its spore or mycelia from the water. In addition, it is concluded that drinking water purifications such as chlorination, filtration and lime did not eliminate thermophilic fungal spores or mycelia including Penicillium, Paecilomyces and Mucor from the water.

Distal Versus Proximal Radial Arterial Access for Percutaneous Coronary Angiography and Intervention: Updated Meta-Analysis of Randomized Controlled Trials.

Radial artery occlusion (RAO) is a major impediment to reintervention in patients who underwent proximal transradial access (p-TRA) for coronary catheterization. Distal transradial access (d-TRA) at the level of snuffbox distal to the radial artery bifurcation is a novel alternative to p-TRA. We conducted an updated meta-analysis of all available randomized controlled trials (RCTs) to compare the incidence of RAO between p-TRA and d-TRA, along with access site-related complications. PubMed, Web of Science, and Google Scholar were searched for RCTs published since 2017 to October 2023 comparing d-TRA and p-TRA for coronary angiography and/or intervention. Risk ratios (RRs) and mean differences (MDs) with 95% confidence intervals were calculated using the random-effects model for procedural and clinical outcomes for the 2 approaches. A total of 18 RCTs with 8,205 patients (d-TRA n = 4,096, p-TRA n = 4,109) were included. The risk of RAO (RR 0.31, 0.21 to 0.46, p ≤0.001) and time to hemostasis (minutes) (MD -51.18, -70.62 to -31.73, p <0.001) was significantly lower in the d-TRA group. Crossover rates (RR 2.39, 1.71 to 3.32, p <0.001), access time (minutes) (MD 0.93, 0.50 to 1.37, p <0.001), procedural pain (MD 0.46, 0.13 to 0.79, p = 0.006), and multiple puncture attempts (RR 2.13, 1.10 to 4.11, p = 0.03) were significantly higher in the d-TRA group. The use of d-TRA for coronary angiography and/or intervention is associated with a lower risk of RAO at the forearm and may preserve p-TRA site for reintervention in selective patients by reducing the incidence of RAO.

Redox mechanisms of environmental toxicants on male reproductive function.

Humans and wildlife, including domesticated animals, are exposed to a myriad of environmental contaminants that are derived from various human activities, including agricultural, household, cosmetic, pharmaceutical, and industrial products. Excessive exposure to pesticides, heavy metals, and phthalates consequently causes the overproduction of reactive oxygen species. The equilibrium between reactive oxygen species and the antioxidant system is preserved to maintain cellular redox homeostasis. Mitochondria play a key role in cellular function and cell survival. Mitochondria are vulnerable to damage that can be provoked by environmental exposures. Once the mitochondrial metabolism is damaged, it interferes with energy metabolism and eventually causes the overproduction of free radicals. Furthermore, it also perceives inflammation signals to generate an inflammatory response, which is involved in pathophysiological mechanisms. A depleted antioxidant system provokes oxidative stress that triggers inflammation and regulates epigenetic function and apoptotic events. Apart from that, these chemicals influence steroidogenesis, deteriorate sperm quality, and damage male reproductive organs. It is strongly believed that redox signaling molecules are the key regulators that mediate reproductive toxicity. This review article aims to spotlight the redox toxicology of environmental chemicals on male reproduction function and its fertility prognosis. Furthermore, we shed light on the influence of redox signaling and metabolism in modulating the response of environmental toxins to reproductive function. Additionally, we emphasize the supporting evidence from diverse cellular and animal studies.

Analyzing the impact of fintech industry and green financing on energy poverty in the European countries.

In the fourth industrial revolution, the fintech has significantly expanded during the last several years, and this has caused scholars to worry about how much electricity is being used. Because energy poverty is one of the most critical social policy concerns facing the majority of nations in the world in the modern era. This study adds to what has already been written by looking at how the fintech industry affects the environment and energy in European countries. The current study investigates how the growing awareness of the need to preserve energy and the environment has an effect on society, and analyzes the role of the fintech industry, green finance, energy efficiency, and research and development on energy poverty across European nations from 2013 to 2020. To estimate long- and short-term impacts, DOLS and FMOLS are used along with diagnostic tests. The outcomes found that there is a tight relationship between energy poverty and all the factors taken into consideration (fintech, green finance, energy efficiency, and R&D). EU governments should employ "green finance" to encourage and enable the fintech industry since fintech plays a vital role in enhancing environmental effectiveness. The financing of environmentally friendly projects is very beneficial and might help alleviate energy poverty. The findings also indicate that more financing, ecological subsidies, and social assistance programs are necessary in order to satisfy the needs for energy and put an end to energy poverty in Europe. Policymakers in the tech world may be especially interested in the results.

G-ACP: a machine learning approach to the prediction of therapeutic peptides for gastric cancer.

Conventional Gastrointestinal (GI) cancer treatments are quite expensive and have major hazards. Nowadays, a different strategy places more emphasis on creating tiny biologically active peptides that do not cause severe poisoning. Anticancer peptides (ACPs) are found through experimental screening, which is time-dependent and frequently fraught with difficulties. Gastric ACPs are emerging as a promising GI cancer treatment in the current day. It is crucial to identify novel gastric ACPs to have an improved knowledge of their functioning processes and treatment of gastric cancer. As a result of the post-genomic era's massive production of peptide sequences, rapid and effective ACPs using a computational method are essential. Several adaptive statistical techniques for distinguishing ACPs and non-ACPs have recently been developed. A variety of adapted statistically significant methods have been developed to differentiate between ACPs and non-ACPs. Despite significant progress, there is no specific model for the prediction of gastric ACPs because the specific model will predict a particular type of peptide more accurately and quickly. To overcome this, an initiative is taken for the creation of a reliable framework for the accurate identification of gastric ACPs. The current technique in particular contains four possible features along with one hybrid feature encoding mechanisms which are the target-class motif previously indicated by Amino Acid Composition, Dipeptide Composition, Tripeptide Composition (TPC), Pseudo Amino Acid Composition (PAAC), and their Hybrid. Machine Learning algorithms make high-performance and accurate prediction tools. Moreover, highly variable and ideal deep feature selection is done using an ANOVA-based F score for feature pruning. Experiments on a range of algorithms are carried out to identify the optimal operating strategy due to the diverse nature of learning. Following analysis of the empirical results, Naïve Bayes with TPC and Hybrid feature space outperforms other methods with 0.99 accuracy score on the testing dataset. To find the model generalization an external validation is carried out. In external datasets, the Extra Trees with PAAC features outperforms with the accuracy of 0.94. The comparison study shows that our suggested model will predict gastric ACPs more accurately and will be useful in drug development and gastric cancer. The predictive model can be freely accessed at https://github.com/humeraazad10/G-ACP.git.Communicated by Ramaswamy H. Sarma.

Sample size determination for time-to-event endpoints in randomized selection trials with generalized exponential distribution.

Randomized selection trials are frequently used to compare experimental treatments that have the potential to be beneficial, but they often do not include a control group. While time-to-event endpoints are commonly applied in clinical investigations, methodologies for determining the required sample size for such endpoints, except exponential distribution, are lacking. In recent times, there has been a shift in clinical trials, with a growing emphasis on progression-free survival as a primary endpoint. However, the utilization of this measure has typically been restricted to specific time points for both sample size determination and analysis. This alteration in approach could wield a substantial influence on the clinical trial process, potentially diminishing the capacity to discern variances between treatment groups. In the calculation of sample sizes for randomized trials, this investigation operates under the assumption that the time-to-event endpoint conforms to either an exponential, Weibull, or generalized exponential distribution.

3D-QSAR pharmacophore modeling, virtual screening, molecular docking, MD simulations, in vitro and in vivo studies to identify potential anti-hyperplasia drugs.

Psoriasis is a common immune-mediated skin condition characterized by aberrant keratinocytes and cell proliferation. The purpose of this study was to explore the FDA-approved drugs by 3D-QSAR pharmacophore model and evaluate their efficiency by in-silico, in vitro, and in vivo psoriasis animal model. A 3D-QSAR pharmacophore model was developed by utilizing HypoGen algorithm using the structural features of 48 diaryl derivatives with diverse molecular patterns. The model was validated by a test set of 27 compounds, by cost analysis method, and Fischer's randomization test. The correlation coefficient of the best model (Hypo2) was 0.9601 for the training set while it was 0.805 for the test set. The selected model was taken as a 3D query for the virtual screening of over 3000 FDA-approved drugs. Compounds mapped with the pharmacophore model were further screened through molecular docking. The hits that showed the best docking results were screened through in silico skin toxicity approach. Top five hits were selected for the MD simulation studies. Based on MD simulations results, the best two hit molecules, that is, ebastine (Ebs) and mebeverine (Mbv) were selected for in vitro and in vivo antioxidant studies performed in mice. TNF-α and COX pro-inflammatory mediators, biochemical assays, histopathological analyses, and immunohistochemistry observations confirmed the anti-inflammatory response of the selected drugs. Based on these findings, it appeared that Ebs can effectively treat psoriasis-like skin lesions and down-regulate inflammatory responses which was consistent with docking predictions and could potentially be employed for further research on inflammation-related skin illnesses such as psoriasis.

Brain tumor segmentation using synthetic MR images - A comparison of GANs and diffusion models.

Large annotated datasets are required for training deep learning models, but in medical imaging data sharing is often complicated due to ethics, anonymization and data protection legislation. Generative AI models, such as generative adversarial networks (GANs) and diffusion models, can today produce very realistic synthetic images, and can potentially facilitate data sharing. However, in order to share synthetic medical images it must first be demonstrated that they can be used for training different networks with acceptable performance. Here, we therefore comprehensively evaluate four GANs (progressive GAN, StyleGAN 1-3) and a diffusion model for the task of brain tumor segmentation (using two segmentation networks, U-Net and a Swin transformer). Our results show that segmentation networks trained on synthetic images reach Dice scores that are 80%-90% of Dice scores when training with real images, but that memorization of the training images can be a problem for diffusion models if the original dataset is too small. Our conclusion is that sharing synthetic medical images is a viable option to sharing real images, but that further work is required. The trained generative models and the generated synthetic images are shared on AIDA data hub.

An Endovascular- Versus a Surgery-First Revascularization Strategy for Chronic Limb-Threatening Ischemia: A Meta-Analysis of Randomized Controlled Trials.

Timely revascularization is essential for limb salvage and to reduce mortality in patients with chronic limb-threatening ischemia (CLTI). In patients who are candidates for endovascular therapy and surgical bypass, the optimal revascularization strategy remains uncertain. Recently published randomized controlled trials (RCTs) have presented conflicting results. We conducted a trial-level meta-analysis to compare the outcomes between endovascular-first and surgery-first strategies for revascularization. PubMed, Web of Science, and the Cochrane Library were searched to identify RCTs comparing the outcomes of endovascular-first versus surgery-first strategies for revascularization in patients with CLTI. Data were pooled for major outcomes and their aggregate risk ratios (RRs) with 95% confidence intervals were calculated using a random-effects model. Kaplan-Meier curves for amputation-free survival and overall survival time were plotted using the pooled aggregated data from published curves, with their corresponding hazard ratios (HRs) and 95% confidence intervals reported for up to 5 years of follow-up. A total of 3 RCTs with 2,627 patients (1,312 endovascular-first and 1,315 surgery-first) were included in the meta-analysis. Of these, 1,864 patients (70.9%) were men and 347 (13.2%) were older than 80 years. Comparing the endovascular-first and surgery-first approaches, there was no significant difference in the overall (HR 0.92 [0.83 to 1.01], p = 0.09) or amputation-free survival (HR 0.98 [0.92 to 1.03], p = 0.42), reintervention (RR 1.24 [0.74 to 2.07], p = 0.41), major amputation, (RR 1.16 [0.87 to 1.54], p = 0.31), or therapeutic crossover (RR 0.92 [0.37 to 2.26], p = 0.85). In conclusion, data from available RCTs suggest that there is no difference in clinical outcomes between endovascular-first and surgery-first revascularization strategies for CLTI. A planned patient-level meta-analysis may provide further insight.

Systematic review and meta-analysis comparing Manta device and Perclose device for closure of large bore arterial access.

Data comparing MANTA device with Perclose device for large bore arterial access closure is limited. We performed meta-analysis to compare safety and efficacy of the two devices in large (⩾14 Fr sheath) arteriotomy closure post-TAVR. Relevant studies were identified via PubMed, Cochrane, and EMBASE databases until June, 2022. Data was analyzed using random effect model to calculate relative odds of VARC-2 defined access-site complications and short-term (in-hospital or 30-day) mortality. A total of 12 studies (2 RCT and 10 observational studies) comprising 2339 patients were included. The odds of major vascular complications (OR 0.99, 95% CI 0.51-1.92; p = 0.98); life threatening and major bleeding (OR 0.77, 95% CI 0.45-1.33; p = 0.35); minor vascular complications (OR 1.37, 95% CI 0.63-2.99; p = 0.43); minor bleeding (OR 0.94, 95% CI 0.57-1.56; p = 0.82); device failure (OR 0.74, 95% CI 0.49-1.11; p = 0.14); hematoma formation (OR 0.76, 95% CI 0.33-1.75; p = 0.52); dissection, stenosis, occlusion, or pseudoaneurysm (OR 1.08, 95% CI 0.71-1.62; p = 0.73) and short-term mortality (OR 1.01, 95% CI 0.55-1.84; p = 0.98) between both devices were similar. MANTA device has a similar efficacy and safety profile compared to Perclose device.

An IoT-fuzzy intelligent approach for holistic management of COVID-19 patients.

In this study, an internet of things (IoT)-enabled fuzzy intelligent system is introduced for the remote monitoring, diagnosis, and prescription of treatment for patients with COVID-19. The main objective of the present study is to develop an integrated tool that combines IoT and fuzzy logic to provide timely healthcare and diagnosis within a smart framework. This system tracks patients' health by utilizing an Arduino microcontroller, a small and affordable computer that reads data from various sensors, to gather data. Once collected, the data are processed, analyzed, and transmitted to a web page for remote access via an IoT-compatible Wi-Fi module. In cases of emergencies, such as abnormal blood pressure, cardiac issues, glucose levels, or temperature, immediate action can be taken to monitor the health of critical COVID-19 patients in isolation. The system employs fuzzy logic to recommend medical treatments for patients. Sudden changes in these medical conditions are remotely reported through a web page to healthcare providers, relatives, or friends. This intelligent system assists healthcare professionals in making informed decisions based on the patient's condition.

lGeneralized super-resolution 4D Flow MRI-using ensemble learning to extend across the cardiovascular system.

4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique capable of quantifying blood flow across the cardiovascular system. While practical use is limited by spatial resolution and image noise, incorporation of trained super-resolution (SR) networks has potential to enhance image quality post-scan. However, these efforts have predominantly been restricted to narrowly defined cardiovascular domains, with limited exploration of how SR performance extends across the cardiovascular system; a task aggravated by contrasting hemodynamic conditions apparent across the cardiovasculature. The aim of our study was to explore the generalizability of SR 4D Flow MRI using a combination of heterogeneous training sets and dedicated ensemble learning. With synthetic training data generated across three disparate domains (cardiac, aortic, cerebrovascular), varying convolutional base and ensemble learners were evaluated as a function of domain and architecture, quantifying performance on both in-silico and acquired in-vivo data from the same three domains. Results show that both bagging and stacking ensembling enhance SR performance across domains, accurately predicting high-resolution velocities from low-resolution input data in-silico. Likewise, optimized networks successfully recover native resolution velocities from downsampled in-vivo data, as well as show qualitative potential in generating denoised SR-images from clinicallevel input data. In conclusion, our work presents a viable approach for generalized SR 4D Flow MRI, with ensemble learning extending utility across various clinical areas of interest.

Risk Factors Associated With the Case Fatality Rate of Pulmonary Tuberculosis in Pregnancy: A Five-Year Retrospective Study From a Developing Country.

Background Tuberculosis is a leading cause of maternal and fetal mortality in women of reproductive age. Tuberculosis is frequently misdiagnosed and treated inadequately during pregnancy. Although the global case fatality rate of tuberculosis is decreasing annually, the trend of tuberculosis mortality in Indonesia remains relatively high. Most tuberculosis reports do not include pregnancy status because most countries do not routinely screen for tuberculosis in pregnant women and do not report pregnancy status in female cases. In Southeast Asia, there is currently insufficient data regarding the risk factors associated with maternal mortality due to tuberculosis. This study aimed to identify the risk factors associated with tuberculosis-related mortality during pregnancy. Methodology This retrospective study was conducted at Dr. Soetomo General Hospital, Surabaya. Data were collected from patients' medical records. The samples were all pulmonary tuberculosis cases in pregnancy (suspected, bacteriological, and radiologically confirmed cases) from 2014 to 2018. Data on maternal characteristics, underlying risk factors, and maternal outcomes in pregnant women with tuberculosis were collected from medical records. A total of 77 cases of pulmonary tuberculosis in pregnancy were obtained and analyzed using the chi-square test for differences between pregnant women with tuberculosis who survived and those who did not. Results In total, 77 cases of pulmonary tuberculosis out of 7,242 deliveries were found during the past five years (incidence per year was 1.07), of whom 20.8% (16/77) died. Eight patients died before the gestational age reached 28 weeks. Most of the non-surviving women were aged <35 years (93.8%; 15/16). More than 30% (5/16) of the patients had human immunodeficiency virus co-infection, and the highest risk factors were pneumonia and miliary tuberculosis. Miliary tuberculosis was significantly associated with maternal mortality in pulmonary tuberculosis (p = 0.004) with a relative risk of 3.43. Conclusions According to the findings of this study, miliary tuberculosis is a significant risk factor for maternal mortality during pregnancy.

Mesenchymal stem cell secretome ameliorates over-expression of soluble fms-like tyrosine kinase-1 (sFlt-1) and fetal growth restriction (FGR) in animal SLE model.

INTRODUCTION: In the near future, stem cell research may lead to several major therapeutic innovations in medical practice. Secretome, a "by-product" of stem cell line cultures, has many advantages. Its easiness of storage, usage, and fast direct effect are some of those to consider. Fetal growth restriction (FGR) remains one of the significant challenges in maternal-fetal and neonatal medicine. Placentation failure is one of the most profound causal and is often related to increasing sFlt-1 in early pregnancy. This study aimed to investigate hUC-MSC secretome in ameliorating sFlt-1 and how to improve outcomes in preventing FGR in an animal model. MATERIALS AND METHODS: Pristane-induced systemic lupus erythematosus (SLE) in a mouse model was used to represent placentation failure and its consequences. Twenty-one mice were randomized into three groups: (I) normal pregnancy, (II) SLE, and (III) SLE with secretome treatment. Pristane was administered in all Groups four weeks prior mating period. Secretome was derived from human umbilical cord mesenchymal stem cells (hUC-MSC) conditioned medium on the 3rd and 4th passage, around day-21 until day-28 from the start of culturing process. Mesenchymal stem cell was characterized using flow cytometry for CD105+, CD90+, and CD73+ surface antigen markers. Immunohistochemistry anlysis by using Remmele's Immunoreactive Score (IRS) was used to quantify the placental sFlt-1 expression in each group. Birth weight and length were analyzed as the secondary outcome. The number of fetuses obtained was also calculated for pregnancy loss comparison between Groups. RESULTS: The administration of secretome of hUC-MSC was found to lower the expression of the placental sFlt-1 significantly in the pristane SLE animal model (10.30 ± 1.40 vs. 4.98 ± 2.57; p < 0.001) to a level seen in normal mouse pregnancies in Group I (3.88 ± 0.49; p = 0.159). Secretome also had a significant effect on preventing fetal growth restriction in the pristane SLE mouse model (birth weight: 354.29 ± 80.76 mg vs. 550 ± 64.03 mg; p < 0.001 and birth length: 14.43 ± 1.27 mm vs. 19.00 ± 1.41 mm), comparable to the birth weight and length of the normal pregnancy in Group I (540.29 ± 75.47 mg and 18.14 ± 1.34 mm, p = 0.808 and = 0.719). Secretome administration also showed a potential action to prevent high number of pregnancy loss as the number of fetuses obtained could be similar to those of mice in the normal pregnant Group (7.71 ± 1.11 vs. 7.86 ± 1.06; p = 0.794). CONCLUSIONS: Administration of secretome lowers sFlt-1 expression in placenta, improves fetal growth, and prevents pregnancy loss in a mouse SLE model.