Synergistic anticancer effects of co-delivery of linc-RoR siRNA and curcumin using polyamidoamine dendrimers against breast cancer.

Breast cancer resistance to chemotherapy necessitates novel combination therapeutic approaches. Linc-RoR is a long intergenic noncoding RNA that regulates stem cell differentiation and promotes metastasis and invasion in breast cancer. Herein, we report a dual delivery system employing polyamidoamine dendrimers to co-administer the natural compound curcumin and linc-RoR siRNA for breast cancer treatment. Polyamidoamine dendrimers efficiently encapsulated curcumin and formed complexes with linc-RoR siRNA at an optimal N/P ratio. In MCF-7 breast cancer cells, the dendriplexes were effectively internalized and the combination treatment synergistically enhanced cytotoxicity, arresting the cell cycle at the G1 phase and inducing apoptosis. Linc-RoR gene expression was also significantly downregulated. Individual treatments showed lower efficacy, indicating synergism between components. Mechanistic studies are warranted to define the molecular underpinnings of this synergistic interaction. Our findings suggest dual delivery of linc-RoR siRNA and curcumin via dendrimers merits further exploration as a personalized therapeutic approach for overcoming breast cancer resistance.

Artificial Intelligence-Based Models for Prediction of Mortality in ICU Patients: A Scoping Review.

BACKGROUND AND OBJECTIVE: Healthcare professionals may be able to anticipate more accurately a patient's timing of death and assess their possibility of recovery by implementing a real-time clinical decision support system. Using such a tool, the healthcare system can better understand a patient's condition and make more informed judgements about distributing limited resources. This scoping review aimed to analyze various death prediction AI (Artificial Intelligence) algorithms that have been used in ICU (Intensive Care Unit) patient populations. METHODS: The search strategy of this study involved keyword combinations of outcome and patient setting such as mortality, survival, ICU, terminal care. These terms were used to perform database searches in MEDLINE, Embase, and PubMed up to July 2022. The variables, characteristics, and performance of the identified predictive models were summarized. The accuracy of the models was compared using their Area Under the Curve (AUC) values. RESULTS: Databases search yielded an initial pool of 8271 articles. A two-step screening process was then applied: first, titles and abstracts were reviewed for relevance, reducing the pool to 429 articles. Next, a full-text review was conducted, further narrowing down the selection to 400 key studies. Out of 400 studies on different tools or models for prediction of mortality in ICUs, 16 papers focused on AI-based models which were ultimately included in this study that have deployed different AI-based and machine learning models to make a prediction about negative patient outcome. The accuracy and performance of the different models varied depending on the patient populations and medical conditions. It was found that AI models compared with traditional tools like SAP3 or APACHE IV score were more accurate in death prediction, with some models achieving an AUC of up to 92.9%. The overall mortality rate ranged from 5% to more than 60% in different studies. CONCLUSION: We found that AI-based models exhibit varying performance across different patient populations. To enhance the accuracy of mortality prediction, we recommend customizing models for specific patient groups and medical contexts. By doing so, healthcare professionals may more effectively assess mortality risk and tailor treatments accordingly. Additionally, incorporating additional variables-such as genetic information-into new models can further improve their accuracy.

Upregulation of the c-MYC oncogene and adjacent long noncoding RNAs PVT1 and CCAT1 in esophageal squamous cell carcinoma.

BACKGROUND: All cell types express long non-coding RNAs (lncRNAs), which have the potential to play a role in carcinogenesis by altering the levels of their expression. Squamous cell carcinoma of the esophagus (ESCC) is a deadly disease with a poor prognosis and a high frequency of lymphatic metastases. Understanding the functional role and signaling pathways of two neighboring lncRNAs, CCAT1 and PVT1, in this oncogene's pathogenesis may help us determine ESCC. Furthermore, it is still unclear whether these lncRNAs are linked to the clinicopathological characteristics of patients with ESCC. METHODS: For this study, we used biopsy from the Imam Khomeini Cancer Institute's tumor bank in Tehran, Iran to obtain 40 ESCC tumor samples and their normal margin counterparts. The expression levels of the CCAT1, PVT1, and c-MYC genes were assessed using quantitative Real-Time RT-PCR. Additionally, demographic data and clinical-pathologic characteristics, such as tumor grade, tumor stage, lymph node, and metastasis, were taken into consideration. Graphpad prism version 8 was used for bioinformatics analyses. RESULTS: Comparing ESCC tissues to non-tumor tissues, we found significant upregulation of PVT1, CCAT1, and c-MYC. Patients with ESCC who had increased PVT1 expression also had higher rates of advanced stage and lymph node metastasis, whereas increased CCAT1 expression was only linked to advanced stage and wasn't associated with lymph node metastasis. In predicting ESCC, CCAT1 (p < 0.05) was found to be an important factor. Overall survival was reduced by c-MYC and PVT1 overexpression (p < 0.001), according to Kaplan-Meier analysis. PVT1, CCAT1, and c-MYC were found to interact with 23 miRNAs with high and medium score classes, as shown in a bioinformatics study. We summarized the experimentally proven interactions between c-MYC, PVT1, and CCAT1 and other miRNAs, lncRNAs, and proteins. CONCLUSION: This is the first report that CCAT1, PVT1 and c-MYC have been found to be up-regulated simultaneously in ESCC. It is possible that these genes may be involved in ESCC as a result of these findings. Therefore, as consequence, more research is needed to determine whether or not these lncRNAs play an oncogenic role in ESCC development and progression, as well as the regulatory mechanisms that control them.

Fascioliasis associated with chronic cholecystitis in a woman from Sistan and Baluchestan province, a non-endemic region in Southeastern Iran.

BACKGROUND: Fascioliasis, caused by Fasciola hepatica, is a neglected zoonotic food-borne trematodiasis. The Caspian littoral in northern Iran is endemic for the disease, and human fascioliasis is well-known in that region. In the present study, we report the diagnosis, identification, and clinical management of a human case of fascioliasis associated with common bile duct (CBD) obstruction from a non-endemic remote area in southeastern Iran. CASE PRESENTATION: A 42-year-old female was admitted to Afzalipour Medical Center hepatobiliary surgery ward in Kerman with abdominal pain for the past three months. Dilated biliary tract and an ill-defined mass in CBD were reported in abdominal ultrasonography and magnetic resonance cholangiopancreatography, respectively. During distal CBD operation, nine leaf-like motile flatworms were isolated. A morphological study confirmed all the isolates as Fasciola, and further molecular investigations, identified the flukes as F. hepatica using both pepck multiplex PCR and cox1 sequencing. CONCLUSION: Molecular and morphological findings of the study indicated the presence of human fascioliasis in the southeastern province of Sistan and Baluchestan in Iran. Fascioliasis is among the etiologies of chronic cholecystitis, and physicians should consider chronic cholecystitis associated with fascioliasis in the differential diagnosis. In the present report, endoscopic ultrasound was usefully applied for the accurate diagnosis of biliary fasciolosis.

An Agent-Based Modeling and Virtual Reality Application Using Distributed Simulation: Case of a COVID-19 Intensive Care Unit.

Hospitals and other healthcare settings use various simulation methods to improve their operations, management, and training. The COVID-19 pandemic, with the resulting necessity for rapid and remote assessment, has highlighted the critical role of modeling and simulation in healthcare, particularly distributed simulation (DS). DS enables integration of heterogeneous simulations to further increase the usability and effectiveness of individual simulations. This article presents a DS system that integrates two different simulations developed for a hospital intensive care unit (ICU) ward dedicated to COVID-19 patients. AnyLogic has been used to develop a simulation model of the ICU ward using agent-based and discrete event modeling methods. This simulation depicts and measures physical contacts between healthcare providers and patients. The Unity platform has been utilized to develop a virtual reality simulation of the ICU environment and operations. The high-level architecture, an IEEE standard for DS, has been used to build a cloud-based DS system by integrating and synchronizing the two simulation platforms. While enhancing the capabilities of both simulations, the DS system can be used for training purposes and assessment of different managerial and operational decisions to minimize contacts and disease transmission in the ICU ward by enabling data exchange between the two simulations.

Differentiation of Human Wharton Jelly Mesenchymal Stem Cells into Germ-Like Cells; emphasis on evaluation of Germ-long non-coding RNAs.

BACKGROUND: The proliferation and differentiation of stem cells into Germ-Like Cells (GLCs) is mediated by several growth factors and specific genes, of which some are related to long non-coding RNAs (lncRNAs). We have developed a modified differentiation process and identified a panel of GermlncRNAs related to GLCs. METHODS: Human Wharton Jelly Mesenchymal Stem Cells were treated with 25 ng/ml Bone Morphogenetic Protein (BMP)-4 and 10- 5 M all-trans retinoic acid to differentiate them into germ-like cells. To confirm the differentiation, changes in the expression of Oct-4, C-kit, Stella, and Vasa genes were assessed using quantitative Real-Time PCR (qPCR) and immunocytochemistry. QPCR was also used before and after differentiation to evaluate the changes in a lncRNA panel, using a 96-well array. Statistical analysis of the data was performed by SPSS 21. RESULTS: After 21 days of induction, the HWJ-MSCs derived germ-like cells were formed. Also, qPCR and immunocytochemistry showed that the pluripotent Oct4 marker was expressed in the undifferentiated HWJ-MSCs, but its expression gradually decreased in the differentiated cells. C-kit was expressed on days 7, 14, and 21 of differentiation. Both GLC markers of Stella and Vasa genes/proteins were present only in differentiated cells. Of the 44 lncRNA genes array, 36 of them showed an increase and eight genes showed a decrease. CONCLUSION: Our study showed that BMP4 and RA are effective in inducing HWJ-MSCs differentiation into GLCs. In addition, our study for the first time showed changes in the lncRNAs expression during the differentiation of HWJ-MSCs into GLCs by using BMP4 and RA.

Low expression of LncRNA-CAF attributed to the high expression of HIF1A in esophageal squamous cell carcinoma and gastric cancer patients.

PURPOSE: Cancer-associated fibroblasts (CAFs) are major components of tumor microenvironment that stimulate ESCC and GC progression. The LncRNA-CAF, FLJ22447, is located in the vicinity of HIF1A, while their association remains unclear. This study aims to assess the FLJ22447 expression in the ESCC and GC patients and evaluate its association with the HIF1A gene. METHODS: Fresh ESCC and GC tumor samples and their adjacent non-tumor tissues were collected from patients who underwent surgery in Imam Khomeini Hospital, Tehran, Iran. The expression of FLJ22447, HIF1A, and VEGF was evaluated using qRT-PCR test. The association of their expression with tumor clinicopathological features in ESCC patients was assessed. System biology tools were then applied for the possible biological subsequences of the FLJ22447. RESULTS: A significant reduction in FLJ22447 expression was observed in ESCC and GC tissues than adjacent non-tumor tissues, while, the expression of HIF1A and VEGF were increased. Low expression of FLJ22447 was significantly correlated with HIF1A (P = 2.4e-73, R = 0.63) and VEGF (P = 0.00019, R = 0.15) expression. A significant relationship was detected between the high expression of HIF1A and tumor stages (I-II) and it was related to the reduced survival of ESCC patients. Conversely, increased VEGF expression was linked to the advanced stages (III-IV) and metastasis in ESCC. The analysis of FLJ22447-interacted proteins showed that MYC, JUN, SMRCA4, PPARG, AR, FOS, and CEBPA are the hub genes. These proteins were implicated in the cancer related pathways. Among them, SPI1, E2F1, TCF7L2, and STAT1 were significantly expressed in esophageal and gastric cancers that were functionally involved in the proliferation, apoptosis, and angiogenesis pathways in cancer. CONCLUSION: The results suggested that FLJ22447 may have a regulatory function on the HIF1A expression. We identified the FLJ22447-interacted proteins and their molecular function in cancer pathogenesis. Further research emphasis is to realize the association of FLJ22447 with its protein partners in progression of cancer. These may provide an insight into the FLJ22447 activity that could introduce it as a potential value in tumor gene therapy.

Social equity-based distribution networks design for the COVID-19 vaccine.

This study aims to investigate the role of social equity in vaccine distribution network design problems. Inspired by the current COVID-19 vaccine allocation in-country context, we capture social equity-based distribution by modeling three theories: Rawls' theory, Sadr's theory, and utilitarianism. We consider various social groups based on degree of urbanization, including inhabitants of cities, towns and suburbs, and rural areas. The distribution problem is subject to, on the one hand, demand-side uncertainty characterized by the daily contamination rate and its space-time propagation that anticipate the in-need population. On the other hand, supply-side uncertainty characterized by the stochastic arrival of vaccine doses for the supply period. To tackle this problem, we propose a novel bi-objective two-stage stochastic programming model using the sample average approximation (SAA) method. We also develop a lexicographic goal programming approach where the social equity objective is prioritized, thereafter reaching an efficiency level. Using publicly available data on COVID-19 in-country propagation and the case of two major provinces in Iran as example of middle-income country, we provide evidence of the benefits of considering social equity in a model-based decision-making approach. The findings suggest that the design solution produced by each social equity theory matches its essence in social science, differing considerably from the cost-based design solution. According to the general results, we can infer that each social equity theory has its own merits. Implementing Rawls' theory brings about a greater coverage percentage in rural areas, while utilitarianism results in a higher allocation of vaccine doses to social groups compared to the Sadr and Rawls theories. Finally, Sadr's theory outperforms Rawls' in terms of both the allocation and cost perspective. These insights would help decision-makers leverage the right equity approach in the COVID-19 vaccine context, and be better prepared for any pandemic crisis that the future may unfold.

Are individual analyses of multiple short urine collections throughout the 24 hours superior to a standard 24-hour urine collection in precipitation risk assessment of healthy subjects?

PURPOSE: The commonly used 24-hour collection technique has been the mainstay of diagnosis for supersaturation but has some certain limitations. Hence, superiority of multiple short urine collections as a new alternative in precipitation risk assessment was assessed compared to the standard 24-hour urine collection among healthy subjects. MATERIALS AND METHODS: Individual urine samples of 26 healthy subjects were acquired every 2 to 3 hours throughout the 24 hours. Urine samples were obtained and the time and volume of each sample were recorded. Urinary constituents involved in precipitation including, sodium-potassium, chloride, calcium, phosphate, citrate, magnesium, urea, creatinine and pH were measured. A simulated 24-hour collection was recalculated by the totalling of all shorter urine collections volume and urinary constituents excretions throughout the day. RESULTS: Urine pH, urine creatinine and precipitation rate had a significantly lower values in 24-hours urine collection compared to one individual value of multiple urine collections by -0.769 (P < .0001), -7.305 (P < .0001), and - 12.838 (P < .0001), respectively. However, calcium (2.697, P < .0001), citrate (3.54, P < .0001), total phosphate (19.961, P < .0001) and total creatinine (9.579, P < .0001) had statistically significantly higher values in the 24-hours urine collection compared to individual value of multiple urine collections. CONCLUSION: Based on the results, individual analysis of multiple shorter urine collections throughout the day improves the ability of identifying supersaturation points, precipitation risk zones and may potentially improve risk assessment compared to the 24-hour urine collection method.

OutlierNets: Highly Compact Deep Autoencoder Network Architectures for On-Device Acoustic Anomaly Detection.

Human operators often diagnose industrial machinery via anomalous sounds. Given the new advances in the field of machine learning, automated acoustic anomaly detection can lead to reliable maintenance of machinery. However, deep learning-driven anomaly detection methods often require an extensive amount of computational resources prohibiting their deployment in factories. Here we explore a machine-driven design exploration strategy to create OutlierNets, a family of highly compact deep convolutional autoencoder network architectures featuring as few as 686 parameters, model sizes as small as 2.7 KB, and as low as 2.8 million FLOPs, with a detection accuracy matching or exceeding published architectures with as many as 4 million parameters. The architectures are deployed on an Intel Core i5 as well as a ARM Cortex A72 to assess performance on hardware that is likely to be used in industry. Experimental results on the model's latency show that the OutlierNet architectures can achieve as much as 30× lower latency than published networks.

Anticoagulation therapy in COVID-19 patients with chronic kidney disease.

Coagulopathy and derangements in the coagulation parameters are significant features of COVID-19 infection, which increases the risk of disseminated intravascular coagulation, thrombosis, and hemorrhage in these patients, resulting in increased morbidity and mortality. In times of COVID-19, special consideration should be given to patients with concurrent chronic kidney disease (CKD) and COVID-19 (CKD/COVID-19 patients) as renal dysfunction increases their risk of thrombosis and hemorrhage, and falsely affects some of the coagulation factors, which are currently utilized to assess thrombosis risk in patients with COVID-19. Hence, we believe extra attention should be given to determining the risk of thrombosis and bleeding and optimizing the timing and dosage of anticoagulant therapy in this unique population of patients. CKD/COVID-19 patients are considered a high-risk population for thrombotic events and hemorrhage. Furthermore, effects of renal function on paraclinical and clinical data should be considered during the evaluation and interpretation of thrombosis risk stratification. Individualized evaluation of clinical status and kidney function is necessary to determine the best approach and management for anticoagulant therapy, whereas there is a lack of studies about the population of CKD/COVID-19 patients who need anticoagulant therapy now.

Diagnostic and prognostic value of Sepsis-Induced coagulopathy and International Society on Thrombosis and Hemostasis scoring systems in COVID-19-associated disseminated intravascular coagulopathy.

BACKGROUND: The coronavirus disease 2019 (COVID-19) presents various phenotypes from asymptomatic involvement to death. Disseminated intravascular coagulopathy (DIC) is among the poor prognostic complications frequently observed in critical illness. To improve mortality, a timely diagnosis of DIC is essential. The International Society on Thrombosis and Hemostasis (ISTH) introduced a scoring system to detect overt DIC (score ≥5) and another category called sepsis-induced coagulopathy (SIC) to identify the initial stages of DIC (score ≥4). This study aimed to determine whether clinicians used these scoring systems while assessing COVID-19 patients and the role of relevant biomarkers in disease severity and outcome. MATERIALS AND METHODS: An exhaustive search was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses, using Medline, Embase, Cochrane, CINAHL, and PubMed until August 2020. Studies considering disease severity or outcome with at least two relevant biomarkers were included. For all studies, the definite, maximum, and minimum ISTH/SIC scores were calculated. RESULTS: A total of 37 papers and 12,463 cases were reviewed. Studies considering ISTH/SIC criteria to detect DIC suggested a higher rate of ISTH ≥5 and SIC ≥4 in severe cases and nonsurvivors compared with nonsevere cases and survivors. The calculated ISTH scores were dominantly higher in severe infections and nonsurvivors. Elevated D-dimer was the most consistent abnormality on admission. CONCLUSION: Higher ISTH and SIC scores positively correlate with disease severity and death. In addition, more patients with severe disease and nonsurvivors met the ISTH and SIC scores for DIC. Given the high prevalence of coagulopathy in COVID-19 infection, dynamic monitoring of relevant biomarkers in the form of ISTH and SIC scoring systems is of great importance to timely detect DIC in suspicious patients.

Impact of Prolonged Fasting on the Risk of Calcium Phosphate Precipitation in the Urine: Calcium Phosphate Lithogenesis during Prolonged Fasting in a Healthy Cohort.

PURPOSE: Intermittent fasting and curtailing water intake for extended periods were likely common in Paleolithic times. Today it occurs for religious and dietary reasons. This restriction in intake should cause a decrease in the urine flow rate while raising the concentration of certain substances in urine to the point of precipitation. In this study we measured the risk of CaHPO4 precipitation following 18 hours of food and water deprivation. MATERIALS AND METHODS: Urine samples were periodically collected from 15 healthy subjects who fasted and abstained from drinking any liquid for 18 hours. The urine constituents Ca2+, HPO42- and pH involved in CaHPO4 formation were measured at various times throughout the fasting day. A comparison was made with control data, which consisted of diurnal urine collections taken throughout a separate nonfasting day prior to the fasting day. RESULTS: The mean ± SEM urine flow rate decreased significantly from 0.93 ± 0.1 ml per minute in the control group to 0.37 ± 0.05 ml per minute in the fasting group (p <0.05). Mean Na+ and Ca2+ excretion rates decreased significantly from 127 ± 12 to 54 ± 13 µmol per minute and from 3.2 ± 0.4 to 0.80 ± 0.21, respectively. Mean urinary Na+ and Ca2+ concentrations also decreased from 161 ± 11.6 to 122 ± 16.0 mmol/l and from 3.7 ± 0.5 to 2.0 ± 0.55, respectively. Urinary pH and the concentration of phosphate, citrate and magnesium were not significantly affected. CONCLUSIONS: Although the steady decrease in the urine flow rate was statistically significant during 18 hours of food and water deprivation, there was no evidence that the calculated risk of CaHPO4 precipitation in the healthy subjects had increased.

MPCaD: a multi-scale radiomics-driven framework for automated prostate cancer localization and detection.

BACKGROUND: Quantitative radiomic features provide a plethora of minable data extracted from multi-parametric magnetic resonance imaging (MP-MRI) which can be used for accurate detection and localization of prostate cancer. While most cancer detection algorithms utilize either voxel-based or region-based feature models, the complexity of prostate tumour phenotype in MP-MRI requires a more sophisticated framework to better leverage available data and exploit a priori knowledge in the field. METHODS: In this paper, we present MPCaD, a novel Multi-scale radiomics-driven framework for Prostate Cancer Detection and localization which leverages radiomic feature models at different scales as well as incorporates a priori knowledge of the field. Tumour candidate localization is first performed using a statistical texture distinctiveness strategy that leverages a voxel-resolution feature model to localize tumour candidate regions. Tumour region classification via a region-resolution feature model is then performed to identify tumour regions. Both voxel-resolution and region-resolution feature models are built upon and extracted from six different MP-MRI modalities. Finally, a conditional random field framework that is driven by voxel-resolution relative ADC features is used to further refine the localization of the tumour regions in the peripheral zone to improve the accuracy of the results. RESULTS: The proposed framework is evaluated using clinical prostate MP-MRI data from 30 patients, and results demonstrate that the proposed framework exhibits enhanced separability of cancerous and healthy tissue, as well as outperforms individual quantitative radiomics models for prostate cancer detection. CONCLUSION: Quantitative radiomic features extracted from MP-MRI of prostate can be utilized to detect and localize prostate cancer.

MicroRNA-196a as a Potential Diagnostic Biomarker for Esophageal Squamous Cell Carcinoma.

We observed significant up-regulation of miR-196a in esophageal squamous cell carcinoma (ESCC) as compared with their adjacent normal tissue (p = .002). Receiver operating characteristics curve analysis confirmed the suitability of miR-196a as a potential tumor marker for diagnosis of ESCC. Furthermore, analysis of miR-196a levels in saliva samples determined an average of 27-fold up-regulations in ESCC patients compared with healthy group. Our results suggest that salivary miR-196a may be a suitable noninvasive biomarker for diagnosis of ESCC. In addition, molecular pathway enrichment analysis of microRNA (miR)-196a determined focal adhesion, spliceosome and p53 signaling pathways as the most relevant pathways with miR-196a targetome.

Biliary reconstruction in liver transplant patients with primary sclerosing cholangitis, duct-to-duct or Roux-en-Y?

INTRODUCTION: Roux-en-Y choledochojejunostomy and duct-to-duct (D-D) anastomosis are biliary reconstruction methods for liver transplantation. However, there is a controversy over which method produces better results. We have compared the outcome of D-D anastomosis vs. Roux-en-Y hepaticojejunostomy in patients with primary sclerosing cholangitis who had undergone liver transplant in Shiraz Organ Transplant Center. MATERIALS: The medical records of 405 patients with primary sclerosing cholangitis (PSC) who had undergone liver transplant from 1996 to 2015 were reviewed. Patients were divided into two groups: Roux-en-Y group and D-D group. Morbidity, disease recurrence, and graft and patient survival rates were compared between the two groups. RESULTS: Total of 143 patients underwent a D-D biliary reconstruction, and 260 patients had a Roux-en-Y loop. Biliary complication involved 4.2% of patients from the D-D group, and 3.9% from the Roux-en-Y group (P=. 863). Actuarial 1-, 3-, and 5-year patient survival for D-D and Roux-en-Y group was 92%, 85%, and 74%; and 87%, 83%, and 79%, respectively (P=.384). The corresponding 1-, 3-, and 5-year probability of biliary complication was 97%, 95%, and 92%; and 98%, 97%, and 94%, respectively (P=.61). CONCLUSION: Duct-to-duct biliary reconstruction in liver transplantation for selected patients with PSC is a good alternative instead of Roux-en-Y biliary reconstruction.

Sparse reconstruction of compressive sensing MRI using cross-domain stochastically fully connected conditional random fields.

BACKGROUND: Magnetic Resonance Imaging (MRI) is a crucial medical imaging technology for the screening and diagnosis of frequently occurring cancers. However, image quality may suffer from long acquisition times for MRIs due to patient motion, which also leads to patient discomfort. Reducing MRI acquisition times can reduce patient discomfort leading to reduced motion artifacts from the acquisition process. Compressive sensing strategies applied to MRI have been demonstrated to be effective in decreasing acquisition times significantly by sparsely sampling the k-space during the acquisition process. However, such a strategy requires advanced reconstruction algorithms to produce high quality and reliable images from compressive sensing MRI. METHODS: This paper proposes a new reconstruction approach based on cross-domain stochastically fully connected conditional random fields (CD-SFCRF) for compressive sensing MRI. The CD-SFCRF introduces constraints in both k-space and spatial domains within a stochastically fully connected graphical model to produce improved MRI reconstruction. RESULTS: Experimental results using T2-weighted (T2w) imaging and diffusion-weighted imaging (DWI) of the prostate show strong performance in preserving fine details and tissue structures in the reconstructed images when compared to other tested methods even at low sampling rates. CONCLUSIONS: The ability to better utilize a limited amount of information to reconstruct T2w and DWI images in a short amount of time while preserving the important details in the images demonstrates the potential of the proposed CD-SFCRF framework as a viable reconstruction algorithm for compressive sensing MRI.

Two novel splice variants of SOX2OT, SOX2OT-S1, and SOX2OT-S2 are coupregulated with SOX2 and OCT4 in esophageal squamous cell carcinoma.

Long noncoding RNAs (lncRNAs) have emerged as new regulators of stem cell pluripotency and tumorigenesis. The SOX2 gene, a master regulator of pluripotency, is embedded within the third intron of a lncRNA known as SOX2 overlapping transcript (SOX2OT). SOX2OT has been suspected to participate in regulation of SOX2 expression and/or other related processes; nevertheless, its potential involvement in tumor initiation and/or progression is unclear. Here, we have evaluated a possible correlation between expression patterns of SOX2OT and those of master regulators of pluripotency, SOX2 and OCT4, in esophageal squamous cell carcinoma (ESCC) tissue samples. We have also examined its potential function in the human embryonic carcinoma stem cell line, NTERA2 (NT2), which highly expresses SOX2OT, SOX2, and OCT4. Our data revealed a significant coupregulation of SOX2OT along with SOX2 and OCT4 in tumor samples, compared to the non-tumor tissues obtained from the margin of same tumors. We also identified two novel splice variants of SOX2OT (SOX2OT-S1 and SOX2OT-S2) which coupregulated with SOX2 and OCT4 in ESCCs. Suppressing SOX2OT variants caused a profound alteration in cell cycle distribution, including a 5.9 and 6.9 time increase in sub-G1 phase of cell cycle for SOX2OT-S1 and SOX2OT-S2, respectively. The expression of all variants was significantly diminished, upon the induction of neural differentiation in NT2 cells, suggesting their potential functional links to the undifferentiated state of the cells. Our data suggest a part for SOX2OT spliced variants in tumor initiation and/or progression as well as regulating pluripotent state of stem cells.

Spontaneous rupture of uterine varicose veins: a rare cause for obstetric shock.

Spontaneous rupture of uterine surface varicose veins is rare but may result in serious complication of pregnancy, as it is associated with high perinatal and maternal mortality. We report a 24-year-old primigravida who presented with this rare condition mimicking placenta abruption, which was successfully managed. A review of reported cases was performed.

Interobserver Variability of Coronary Stenosis Characterized by Coronary Angiography: A Single-Center (Toronto General Hospital) Retrospective Chart Review by Staff Cardiologists.

Introduction: The reliability of interpretation of coronary angiography as a diagnostic tool was investigated. Furthermore, the impact of interobserver variability of coronary lesions on clinical decision-making was assessed. One of our motivations to do this research was the research gaps and our aim to have up-to-date information regarding interobserver variability among different cardiologists. Methods: Our objective was to quantify interobserver variability among cardiologists who have seen angiograms independently. Disagreement among cardiologists in the visual assessment of invasive coronary angiography of coronary artery stenosis is not uncommon in previous studies. Three cardiologists with extensive experience in coronary angiography, including the primary cardiologist of each patient, read the angiograms of 200 patients from Toronto General Hospital independently. Results: Our research showed the mean agreement among all participating observers was 77.4%; therefore, the interobserver variability of coronary angiography interpretation was 22.6%. Discussion: Coronary angiography is still the gold-standard technique for guidance regarding coronary lesions. Sometimes, coronary angiography results in underestimation or overestimation of a lesion's functional severity. Interobserver variability should also be considered when interpreting the severity of coronary stenoses via invasive coronary angiography. This research shows that interobserver variability regarding coronary angiograms is still present (22.6%).

Plain language summary: The gold-standard method for diagnosing coronary stenosis, invasive coronary angiography has some challenges too. One of these challenges has been the difference among various cardiologists regarding determination of severity of each coronary stenosis. In this study, we focused on differences in interobserver variability in coronary angiography interpretation. Three cardiologists who were experienced in coronary angiography read each patient's coronary angiogram separately. Overall, 200 patients with a history of angiography at Toronto General Hospital were selected randomly. The research showed that overall agreement among all participating cardiologists with regard to the reading of coronary angiograms was 77.4%. In other words, interobserver variability of 22.6% was seen among the readers.