Health Data Sharing with the Goal of Value Creation; Trying to Develop a Framework Using Qualitative Content Analysis.

Introduction: Within the field of data sharing, discussions surrounding privacy concerns and big data management are extensive. This study aimed to provide a comprehensive framework for health data sharing with the objective of creating value. Methods: This study is a qualitative content analysis, which was conducted using a combination of written sources through a systematic review method, in conjunction with content derived from interviews with experts in information technology and healthcare within hospital and emergency settings. Grounded theory serves as the qualitative methodology, involving three coding phases: open, axial, and selective, facilitated by MAXQDA software. Results: Qualitative content analysis of the interviews revealed seven main (core) categories and 44 subcategories as driving factors in promoting healthcare data sharing. Simultaneously, inhibiting factors resulted in six main categories and 36 subcategories. The driving factors encompassed technology, education, patient management improvement, data utilization for various purposes, data-related considerations, legal and regulatory aspects, and health-related factors. Conversely, inhibiting factors encompassed security and privacy concerns, legal issues, external organizational influences, monitoring and control activities, financial considerations, and inter-organizational challenges. Conclusion: This study has identified key driving and inhibiting factors that influence the sharing of healthcare data. These factors contribute to a more comprehensive understanding of the dynamics surrounding data sharing within the healthcare information system.

Efficient COVID-19 testing via contextual model based compressive sensing.

The COVID-19 pandemic is threatening billions of people's life all over the world. As of March 6, 2021, covid-19 has confirmed in 115,653,459 people worldwide. It has also a devastating effect on businesses and social activities. Since there is still no definite cure for this disease, extensive testing is the most critical issue to determine the trend of illness, appropriate medical treatment, and make social distancing policies. Besides, testing more people in a shorter time helps to contain the contagion. The PCR-based methods are the most popular tests which take about an hour to make the output result. Obviously, it makes the number of tests highly limited and consequently, hurts the efficiency of pandemic control. In this paper, we propose a new approach to identify affected individuals with a considerably reduced No. of tests. Intuitively, saving time and resources is the main advantage of our approach. We use contextual information to make a graph-based model to be used in model-based compressive sensing (CS). Our proposed model makes the testing with fewer tests required compared to traditional testing methods and even group testing. We embed contextual information such as age, underlying disease, symptoms (i.e. cough, fever, fatigue, loss of consciousness), and social contacts into a graph-based model. This model is used in model-based CS to minimize the required test. We take advantage of Discrete Graph Signal Processing on Graph (DSPG) to generate the model. Our contextual model makes CS more efficient in both the number of samples and the recovery quality. Moreover, it can be applied in the case that group testing is not applicable due to its severe dependency on sparsity. Experimental results show that the overall testing speed (individuals per test ratio) increases more than 15 times compared to the individual testing with the error of less than 5% which is dramatically lower than that of traditional compressive sensing.

DNA methylation association with stage progression of head and neck squamous cell carcinoma.

Head and Neck Squamous Cell Carcinoma (HNSCC) is the sixth most common cancer worldwide, which accounts for approximately 6% of all cases and is responsible for an estimated 2% of all cancer deaths. Despite progress in the treatment of squamous cell carcinomas, survival rates remain low. It is a fact that epigenetic modifications have numerous associations with biological processes and complex diseases such as cancer. Hence, a more systematic approach is needed to provide potential screening targets and have an effective therapy method. This study developed a workflow to analyze HM450 methylation arrays with mRNA expression profiles that identified novel signatures of epigenetic regulators for tumor progression. We identified differentially expressed genes and differentially methylated regions and the correlation between associated genes to identify epigenetic modifications underlying regulation roles. We have taken the differentiation direction of expressions into account during the integration of gene expression and DNA methylation modification to detect epigenetic regulators of core genes of tumor-stage progression. Enrichment analysis of selected key genes provides better insight into their functionality. Thus, we have investigated gene copy number alteration and mutations to filter differentially expressed genes, including some members of the fibroblast growth factor family and cyclin-dependent kinase inhibitor family with other potential known regulators. Our analysis has revealed the list of 61 commercial methylation probes positively correlated with 31 differentially expressed genes, which can be associated with HNSC metastasis stages. Most of these genes have already reported potential epigenetic regulators, and their role in cancer progression was studied. We suggest these selected probes of DNA methylation as potential targets of the epigenetic regulators in revealed genes that have displayed significant genetic and epigenetic modification behavior during cancer stage progression and tumor metastasis.

Predicting brain network changes in Alzheimer's disease with link prediction algorithms.

Link prediction is a promising research area for modeling various types of networks and has mainly focused on predicting missing links. Link prediction methods may be valuable for describing brain connectivity, as it changes in Alzheimer's disease (AD) and its precursor, mild cognitive impairment (MCI). Here, we analyzed 3-tesla whole-brain diffusion-weighted images from 202 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) - 50 healthy controls, 72 with earlyMCI (eMCI) and 38 with lateMCI (lMCI) and 42 AD patients. We introduce a novel approach for Mixed Link Prediction (MLP) to test and define the percent of predictability of each heightened stage of dementia from its previous, less impaired stage, in the simplest case. Using well-known link prediction algorithms as the core of MLP, we propose a new approach that predicts stages of cognitive impairment by simultaneously adding and removing links in the brain networks of elderly individuals. We found that the optimal algorithm, called "Adamic and Adar", had the best fit and most accurately predicted the stages of AD from their previous stage. When compared to the other link prediction algorithms, that mainly only predict the added links, our proposed approach can more inclusively simulate the brain changes during disease by both adding and removing links of the network. Our results are also in line with computational neuroimaging and clinical findings and can be improved for better results.

On the impact of epidemic severity on network immunization algorithms.

There has been much recent interest in the prevention and mitigation of epidemics spreading through contact networks of host populations. Here, we investigate how the severity of epidemics, measured by its infection rate, influences the efficiency of well-known vaccination strategies. In order to assess the impact of severity, we simulate the SIR model at different infection rates on various real and model immunized networks. An extensive analysis of our simulation results reveals that immunization algorithms, which efficiently reduce the nodes' average degree, are more effective in the mitigation of weak and slow epidemics, whereas vaccination strategies that fragment networks to small components, are more successful in suppressing severe epidemics.

Thyroid dysfunction and choleduocholithiasis.

BACKGROUND: Disturbances in lipid metabolism which occur during hypothyroidism leadto the formation of gallstones. This study aims to evaluate the thyroid functionpattern in patients with common bile duct (CBD) stones. METHODS: This case-control study recruited 151 patients with preliminary diagnosesof CBD stone who underwent ERCP (cases). The control group comprisedhealthy people who met the study criteria in the same hospital. The controlgroup underwent ultrasonography to exclude any asymptomatic bile duct lithiasis.A questionnaire that included demographic and anthropometrics datawere completed by an assigned physician. Morning blood samples that followed12 hours of fasting were taken from all participants for measurements ofserum total thyroxin (T4), serum thyroid stimulating hormone (TSH), fastingblood sugar (FBS), triglycerides (TG), total cholesterol, low density lipoprotein(LDL) and high density lipoprotein (HDL). RESULTS: The mean TSH in patients (2.59 ± 4.86mg/dl) was higher than the controlgroup (2.53± 4.13 9mg/dl). In subclinical hypothyroidism, serum TSH levelshigher than 5 MU/L were found in 30.6% of cases compared with 22.5% ofcontrols [OR: 1.53; 95 % confidence interval (95% CI): 0.968-2.438). Hypothyroidismwas detected in 10.8% of the control group and in 11.3% of cases(OR: 1.87; 95% CI: 0.578-2.043). The mean total cholesterol levels in caseswas higher than the control group (p=0.61).The levels of TG (p=0.05), HDL(73.35 vs. 46.41; p<0.01) and LDL (64.81.88 vs. 111.04; p<0.01) was statisticallysignificant between both groups. CONCLUSION: There is an association between thyroid disorders and the presence of bileduct stones. Thyroid testing in patients with gallstone and bile duct stones isrecommended because hypothyroidism may be a predisposing factor for stonepassage from the gallbladder.

The effect of hibiscus sabdariffa on lipid profile, creatinine, and serum electrolytes: a randomized clinical trial.

Background. Hibiscus Sabdariffa L. (HS), a member of malvaceae family, is a medicinal plant with a worldwide fame. Its effect on reducing serum lipids is mentioned in several studies. The purpose of this study was to assess the efficacy of this plant in reducing the serum's lipids in hypertensive patients. Materials and Methods. Ninety hypertensive patients were randomly assigned to receive Hibiscus Sabdariffa (HS) tea or black tea for 15 days. The patients were asked to drink the tea within 20 minutes following its preparation. This process had to be repeated two times, daily. Patient's FBS and lipid profile were collected at the first visit day (day 0) and on the day 30. Results. There was no significant differences between pre and post experiment values within the two groups. An upward trend in total cholesterol, HDL, and LDL cholesterol was evident in both groups. The increase in total and HDL cholesterol in both groups relative to their initial values were significant. Conclusion. Hibiscus Sabdariffa is probably a safe medicinal plant. No significant harmful changes in cholesterol, triglyceride, BUN, serum creatinine, Na and K levels were observed within 15 days after the discontinuation of the medication.

Influence of nitric oxide agents in the rat amygdala on anxiogenic-like effect induced by histamine.

BACKGROUND/AIMS: Both histamine and nitric oxide (NO) may play a role in anxiety-like behavior. Within the brain, the amygdala is an important area involved in processing emotional responses such as anxiety. The aim of the present study was to assess whether the NO system in the basolateral amygdala (BLA) influences histamine-induced anxiety-like behavior in rats. METHODS: Male Wistar rats weighing 200-220g were used. Bilateral cannulae were implanted in the BLA place for microinjections of drugs and the elevated plus maze apparatus has been used to test parameters (%OAT, %OAE, locomotor activity) of anxiety-like behavior. RESULTS: Intra-BLA administration of histamine (2.5 and 5µg/rat) decreased %OAT [P<0.001]. Histamine (5µg/rat) also reduced %OAE [P<0.05] but not locomotor activity. The results obtained may indicate an anxiolytic response for histamine. Furthermore, bilateral intra-BLA microinjections of different doses of l-arginine (l-arg), an NO precursor (0.5 and 1µg/rat) increased %OAT [P<0.01], %OAE [P<0.01] and locomotor activity [P<0.001] while NG-nitro-l-arg methylester (l-NAME), a potent inhibitor of NO-synthase (NOS; 0.025, 0.05 and 0.1µg/rat) decreased %OAT [P<0.05] and locomotor activity [P<0.001] but not %OAE. The combination of l-arg (0.5µg/rat) with histamine increased %OAE [P<0.001] but had no effect on %OAT and locomotor activity. Finally, the combination of l-NAME (0.025µg/rat) with histamine decreased %OAT [P<0.001] and locomotor activity [P<0.05] but increased %OAE. CONCLUSION: The results indicate a modulatory role for NO in BLA in the anxiogenic response of histamine in rats.