Application of power-law committee machine to combine five machine learning algorithms for enhanced oil recovery screening

One of the main challenges in screening of enhanced oil recovery (EOR) techniques is the class imbalance problem, where the number of different EOR techniques is not equal. This problem hinders the generalization of the data-driven methods used to predict suitable EOR techniques for candidate reservoirs. The main purpose of this paper is to propose a novel approach to overcome the above challenge by taking advantage of the Power-Law Committee Machine (PLCM) technique optimized by Particle Swam Optimization (PSO) to combine the output of five cutting-edge machine learning methods with different types of learning algorithms. The PLCM method has not been used in previous studies for EOR screening. The machine learning models include the Artificial Neural Network (ANN), CatBoost, Random Forest (RF), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). The CatBoost is used for the first time in this work for screening of EOR methods. The role of the PSO is to find the optimal values for the coefficients and exponents of the power-law model. In this study, a bigger dataset than those in previous studies, including 2563 successful worldwide EOR experiences, was gathered. A bigger dataset improves the generalization of the data-driven methods and prevents overfitting. The hyperparameters of the individual machine-learning models were tuned using the fivefold cross-validation technique. The results showed that all the individual methods could predict the suitable EOR method for unseen cases with an average score of 0.868. Among the machine learning models, the KNN and SVM had the highest scores with a value of 0.894 and 0.892, respectively. Nonetheless, after combining the output of the models using the PLCM method, the score of the predictions improved to 0.963, which was a substantial increase. Finally, a feature importance analysis was conducted to find out the most influential parameters on the output. The novelty of this work is having shown the ability of the PLCM technique to construct an accurate model to overcome the class-imbalance issue in EOR screening by utilizing different types of data-driven models. According to feature importance analysis, oil gravity and formation porosity were recognized as the most influential parameters on EOR screening.

Architecture and Development Framework for a Web-Based Risk Assessment and Management Platform Developed on WordPress to Address Opioid Overdose

The number of overdose-related fatalities continues to reach historic levels across Canada, despite ongoing efforts by authorities. To reduce mortality, a clinical trajectory ranging from preventative measures to crisis intervention, skill training to treatment, and risk assessment to risk management needs to be supported. The web-based Risk Assessment and Management Platform (RAMP) was developed to realize this concept and to empower people who use drugs through an integrated tool that allows them to better understand and manage their risk of overdose. This paper outlines the architecture and development of RAMP, which is built on the WordPress platform. WordPress components are mapped onto a 3-tier architecture that consists of presentation, application, and database layers. The architecture facilitates the development of a modular software that includes several features that are independent in functionality but interact with each other in an integrated platform. The relatively low coupling and high coherence of the features may reduce the cost of maintenance and increase flexibility of future developments. RAMP's architecture comprises a user interface, conceptual framework, and backend layers. The RAMP front end effectively uses some of the WordPress' features such as HTML5, CSS, and JavaScript to create a mobile, friendly, and scalable user interface. The RAMP backend uses several standard and custom WordPress plug-ins to support risk assessment and monitoring, with the goal of mitigating the impacts and eliminating risks together. A rule-based decision support system has been hard-coded to suggest relevant modules and goals to complement each user's lifestyle and goals based on their risk assessment. Finally, the backend uses the MySQL database management system and communicates with the RAMP framework layer via the data access layer to facilitate a timely and secure handling of information. Overall, RAMP is a modular system developed to identify and manage the risk of opioid overdose in the population of people who use drugs. Its modular design uses the WordPress architecture to efficiently communicate between layers and provide a base for external plug-ins. There is potential for the current system to adopt and address other related fields such as suicide, anxiety, and trauma. Broader implementation will support this concept and lead to the next level of functionality.

Seeking versus receiving help: How children integrate suggestions in memory decisions

The current research examined how seeking versus receiving help affected children's memory and confidence decisions. Baseline performance, when no help was available, was compared to performance when help could be sought (Experiment 1: N = 83, 41 females) or was provided (Experiment 2: N = 84, 44 females) in a sample of predominately White 5-, 7-, and 9-year-olds from Northern California. Data collection occurred from 2018 to 2019. In Experiment 1, 5-year-olds agreed most often with sought-help, whereas 9-year-olds were the only age group reporting lower confidence for sought-help relative to baseline trials. In Experiment 2, agreement and confidence after provided help were similar across age groups. Different developmental patterns when help was sought versus provided underscore the importance of active help-seeking for memory decision-making.

An Efficient Capsule-based Network for 2D Left Ventricle Segmentation in Echocardiography Images

The segmentation of cardiac chambers is essential for the clinical diagnosis and treatment of cardiovascular diseases. It is demonstrated that in cardiac disease, the left ventricle (LV) is extensively involved. Therefore, segmentation of the LV in echocardiographic images is critical for the precise evaluation of factors that influence cardiac function such as LV volume, ejection fraction, and LV mass. Although these measurements could be obtained by manual segmentation of the LV, it would be time-consuming and inaccurate because of the poor quality and low contrast of these images. Convolutional neural networks, commonly referred to as CNNs, have emerged as a highly favored deep learning technique for medical image segmentation. Despite their popularity, the pooling layers in CNNs ignore the spatial information and do not consider the part-whole hierarchy relationships. Furthermore, they require a large training dataset and a large number of parameters. Therefore, Capsule Networks are proposed to address the CNNs limitations. In this study, for the first time, an optimized capsule-based network for object segmentation called SegCaps is proposed to achieve accurate LV segmentation on echocardiography images applied to the CAMUS dataset. The result was compared against the standard 2D-UNet. The modified SegCaps and 2D-UNet achieved an average Dice similarity coefficient (DSC) of 84.48% and 83.28% on LV segmentation, respectively. The capabilities of the CapsNet led to an improvement of 1.44% in DSC with 92.77% fewer parameters than the U-Net. The results indicate that the proposed method leads to accurate and efficient LV segmentation.Clinical Relevance- From a clinical point of view, our findings lead to more precise evaluations of critical cardiac parameters, including ejection fraction as well as left ventricle volume at end-diastole and end-systole.

Quality of life of patients treated with opium tincture or methadone: A randomized controlled trial

OBJECTIVE

Quality of life (QoL) is an increasingly recognized patient-centered treatment outcome in individuals with opioid use disorder. There is a gap in literature on the impact of opium tincture (OT) on patients' QoL compared to standard treatment options such as methadone. This study aimed to compare the QoL of participants with opioid use disorder receiving OAT using OT or methadone and identify the factors associated with their QoL during treatment.

METHODS

The opium trial was a multicenter non-inferiority randomized clinical trial in four private OAT outpatient clinics in Iran. The study assigned patients to either OT (10 mg/ml) or methadone sirup (5 mg/ml) for a follow-up of 85 days. QoL was assessed using the brief version of the World Health Organization Quality of Life instrument (WHOQOL- BREF).

RESULTS

A total of 83 participants, 35 (42.2%) in the OT arm and 48 (57.8%) in the methadone arm, completed the WHOQOL-BREF in full and were included in the primary analysis. The mean score of patients' QoL showed improvement compared to baseline, but differences were not statistically significant between OT and methadone arms (p = 0.786). Improvements were mainly observed within the first 30 days of receiving treatment. Being married and lower psychological distress were associated with an improved QoL. Within the social relationships domain, male gender showed significantly higher QoL compared to females.

CONCLUSION

OT shows promise as an OAT medication, comparable to methadone in improving patients' QoL. There is a need to incorporate psychosocial interventions to further sustain and improve the QoL in this population. Identifying other social determinants of health which affect QoL and the cultural adaptation of assessments for individuals from various ethnocultural backgrounds are critical areas of inquiry.

Opium tincture versus methadone for opioid agonist treatment: a randomized controlled trial

AIM

To test if opium tincture (OT) was non-inferior to methadone in retaining participants in opioid agonist treatment (OAT).

DESIGN

A Phase III, multi-centre, parallel-group, non-inferiority, double-blind randomized controlled trial with an allocation ratio of 1:1. Participants were provided treatment and followed for a period of 85 days.

SETTING

Four OAT clinics in Iran.

PARTICIPANTS

Two hundred and four participants with opioid use disorder [mean age (standard deviation) = 37.4 (9.3); female 11.3%] recruited between July 2017 and January 2018.

INTERVENTIONS

Participants were assigned to either OT (102) or methadone (102) using a patient-centred flexible dosing strategy.

MEASUREMENTS

Treatment retention over 85 days was the primary outcome. Self-reported opioid use outside treatment and occurrence of adverse events (AEs) were the secondary outcomes.

FINDINGS

Remaining in treatment at the end of the follow-up were 68.6% in the methadone arm and 59.8% in the OT arm. The relative retention rate of methadone to OT was 1.15 (0.97, 1.36) in both intent-to-treat and per-protocol analyses; non-inferiority was not supported statistically, as the upper bound of the confidence interval exceeded our pre-specified non-inferiority margin (1.25). Opioid use outside treatment was reported by 30.3% of OT (n = 152) and 49.4% of methadone (n = 168) patients, a difference in proportions of -19%: 90% confidence interval (-28%, -10%). The total count of AEs in the OT arm (22 among nine individuals) was significantly higher (P = 0.04) than that in the methadone arm (three among two individuals). Nausea was the most common side effect.

CONCLUSION

While this study could not conclude the non-inferiority of opium tincture (OT) to methadone for retaining patients in opioid agonist treatment, OT retained 60% of participants to end of follow-up (85 days) and was superior to methadone in reducing self-reported opioid use outside treatment.

Realistic three-dimensional avian vocal tract model demonstrates how shape affects sound filtering (Passer domesticus)

Despite the complex geometry of songbird's vocal system, it was typically modelled as a tube or with simple mathematical parameters to investigate sound filtering. Here, we developed an adjustable computational acoustic model of a sparrow's upper vocal tract (Passer domesticus), derived from micro-CT scans. We discovered that a 20% tracheal shortening or a 20° beak gape increase caused the vocal tract harmonic resonance to shift toward higher pitch (11.7% or 8.8%, respectively), predominantly in the mid-range frequencies (3-6 kHz). The oropharyngeal-oesophageal cavity (OEC), known for its role in sound filtering, was modelled as an adjustable three-dimensional cylinder. For a constant OEC volume, an elongated cylinder induced a higher frequency shift than a wide cylinder (70% versus 37%). We found that the OEC volume adjustments can modify the OEC first harmonic resonance at low frequencies (1.5-3 kHz) and the OEC third harmonic resonance at higher frequencies (6-8 kHz). This work demonstrates the need to consider the realistic geometry of the vocal system to accurately quantify its effect on sound filtering and show that sparrows can tune the entire range of produced sound frequencies to their vocal system resonances, by controlling the vocal tract shape, especially through complex OEC volume adjustments.

Psoriatic arthritis, axial spondyloarthritis and rheumatoid arthritis in Norway: nationwide prevalence and use of biologic agents

OBJECTIVE

To estimate the prevalence of psoriatic arthritis (PsA), axial spondyloarthritis (axSpA) and rheumatoid arthritis (RA) and the use of biologic agents in these diseases in Norway.

METHODS

From the Norwegian Patient Registry (NPR), we identified as PsA, axSpA and RA patients ≥18 years those with ≥2 recorded episodes with diagnostic coding for index disease (L40.5, M07.0-M07.3 for PsA; M45, M46.0, M46.1, M46.8 and M46.9 for axSpA; M05-M06 for RA). We calculated the point prevalence of PsA, axSpA and RA as per the 1^st of January 2017 in the Norwegian adult population (age ≥18). Dispensed disease-modifying antirheumatic drug (DMARD) prescriptions were obtained from the Norwegian Prescription Database and biologic DMARDs given in hospitals from the NPR.

RESULTS

The point prevalence of PsA, axSpA, RA, and any of these diseases in total was 0.46%, 0.41%, 0.78%, and 1.56%, respectively. Among women, the prevalence of PsA, axSpA, and RA was 0.50%, 0.37%, and 1.10%, and among men 0.43%, 0.45%, and 0.46%, respectively. In 2017, 27.3% of RA patients, 25.7% of PsA patients and 35.1% of axSpA patients used biologic DMARDs. Treatment with biologics was more frequent in younger age groups in all three diseases, and became more infrequent especially after age ≥55 years.

CONCLUSION

In Norway, the combined prevalence of PsA, axSpA, and RA was over 1.5%. Reflecting the good overall access to highly effective but costly biologic treatments, more than a fourth of these patients used biologic agents, which corresponds to over 0.4% of Norwegian adult population.

Adherence to e-health interventions for substance use and the factors influencing it: Systematic Review, meta-analysis, and meta-regression

Background

Substance use disorders affect 36 million people globally, but only a small proportion of them receive the necessary treatment. E-health interventions have been developed to address this issue by improving access to substance use treatment. However, concerns about participant engagement and adherence to these interventions remain. This review aimed to evaluate adherence to e-health interventions targeting substance use and identify hypothesized predictors of adherence.

Methods

A systematic review of literature published between 2009 and 2020 was conducted, and data on adherence measures and hypothesized predictors were extracted. Meta-analysis and meta-regression were used to analyze the data. The two adherence measures were (a) the mean proportion of modules completed across the intervention groups and (b) the proportion of participants that completed all modules. Four meta-regression models assessed each covariate including guidance, blended treatment, intervention duration and recruitment strategy.

Results

The overall pooled adherence rate was 0.60 (95%-CI: 0.52-0.67) for the mean proportion of modules completed across 30 intervention arms and 0.47 (95%-CI: 0.35-0.59) for the proportion of participants that completed all modules across 9 intervention arms. Guidance, blended treatment, and recruitment were significant predictors of adherence, while treatment duration was not.

Conclusion

The study suggests that more research is needed to identify predictors of adherence, in order to determine specific aspects that contribute to better exposure to intervention content. Reporting adherence and predictors in future studies can lead to improved meta-analyses and the development of more engaging interventions. Identifying predictors can aid in designing effective interventions for substance use disorders, with important implications for e-health interventions targeting substance use.

POS0516 PLASMA CALPROTECTIN WAS ASSESSED IN MULTIPLE BIOLOGICAL TREATMENT STRATEGIES FOR EARLY RHEUMATOID ARTHRITIS

Background

Plasma calprotectin is a sensitive inflammatory marker in patients with rheumatoid arthritis (RA) and reflects activation of granulocytes and macrophages. Plasma calprotectin has not previously been studied in a head-to-head trial of multiple biological mechanisms of action versus active conventional therapy (ACT) with methotrexate and prednisolone.

Objectives

To assess the effect of treatment on plasma calprotectin levels in patients with early RA by determining the 24-week change in the four arms of the NORD-STAR Study, a large multicenter randomized head-to-head clinical trial of ACT versus tumor necrosis factor inhibition, T-cell co-stimulation inhibition, and interleukin-6 inhibition (1).

Methods

Calprotectin was analyzed in plasma samples at baseline, week 4 and week 24 from 400 treatment naïve patients with early RA in the NORD-STAR Study. Samples were analyzed using a calprotectin ELISA alkaline phosphatase (ALP) kit from CalproLab (Oslo, Norway) in a Dynex DS2 processing system (normal levels <910 µg/L). Patients were assessed by clinical (CRP, 28 SJC/TJC, physician global) and patients’ reported assessments. Crude and adjusted linear regression analyses were performed in R 4.0.3 with calprotectin levels at week 24 as the outcome. The four arms were represented by three dummy variables. The adjustment variables were age, sex, anti-CCP status and country. Both analyses were adjusted for baseline calprotectin levels.

Results

At baseline, the mean time since diagnosis was 15.7 days (SD) (22.9), mean age 53.7 (15.0) years, ACPA positive 81%, and female 66%. Mean calprotectin levels were 1931 (1495) µg/L at baseline, 866 (951) µg/L at week 4, and 629 (661) µg/L at week 24. At baseline, normal calprotectin levels (<910 µg/L) were observed in 27% of all patients (ACT 22%, certolizumab-pegol and methotrexate 30%, abatacept and methotrexate 25%, tocilizumab and methotrexate 31%). At week 24, normal calprotectin levels were observed in 82% of all patients (ACT 68%, certolizumab-pegol and methotrexate 91%, abatacept and methotrexate 80%, tocilizumab and methotrexate 90%).

Observed calprotectin levels at week 24 were significantly lower in patients treated with certolizumab-pegol and methotrexate -336µg/L (97) (p< 0.006) or tocilizumab and methotrexate -284 (99) (p < 0.004), versus ACT when adjusted for age, sex, anti-CCP status, baseline calprotectin level, and country; however, a significant difference was not observed in patients treated with abatacept and methotrexate -110 (96) (p = 0.25). The Figure 1 shows the average percentage change in calprotectin levels from baseline to week 24 for all treatment groups.

Figure 1.

Average percentage change in calprotectin levels from baseline to week 24. ACT: active conventional therapy, CZP+MTX: certolizumab-pegol and methotrexate, ABA+MTX: abatacept and methotrexate, TCZ+MTX: tocilizumab and methotrexate.

Conclusion

Calprotectin, a sensitive biomarker of inflammation, normalized in the majority of patients. The decline differed between treatment groups and was largest in patients treated with a TNF inhibitor and methotrexate, suggesting that calprotectin reflects the activity of specific inflammatory pathways rather than overall inflammation. The findings of this study should be further explored.

References

[1]Hetland ML, et. al., Active conventional treatment and three different biological treatments in early rheumatoid arthritis: phase IV investigator initiated, randomised, observer blinded clinical trial. BMJ. 2020 Dec 2;371:m4328. doi: 10.1136/bmj.m4328. PMID: 33268527; PMCID: PMC7708829.

Acknowledgements

I would like to acknowledge the NORD-STAR Study group.

Disclosure of Interests

David Stevens: None declared, Marte Heiberg: None declared, Amirhossein Kazemi: None declared, Ronald van Vollenhoven: None declared, Jon Lampa: None declared, Anna Rudin: None declared, Kristina Lend: None declared, Merete Lund Hetland: None declared, Mikkel Østergaard: None declared, Michael Nurmohamed: None declared, Kim Hørslev-Petersen: None declared, Dan Nordström Consultant of: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Björn Gudbjornsson: None declared, Till Uhlig: None declared, Espen A Haavardsholm: None declared, Hilde Berner Hammer Speakers bureau: AbbVie, Novartis, and Lilly.

A Clinical Decision Support System for Increasing Compliance with Protocols in Chemotherapy of Children with Acute Lymphoblastic Leukemia

Objective:

In this survey, a protocol-based Chemotherapy Prescription Decision Support System (CPDSS) was designed and evaluated to reduce medication errors in the chemotherapy process of children with ALL.

Methods:

The CPDSS algorithm was extracted by the software development team based on the protocol used by doctors to treat children with ALL. The ASP.Net MVC and SQL Server 2016 programming languages were used to develop the system. A 3-step evaluation (technical, retrospective, and user satisfaction) was performed on CPDSS designed at 2 children’s hospitals in Tehran. The data were analyzed using descriptive statistics. At the technical evaluation step, users provided recommendations included in the system.

Results:

In the retrospective CPDSS evaluation step, 1281 prescribed doses of the drugs related to 30 patients were entered into the system. CPDSS detected 735 cases of protocol deviations and 57 (95%, CI = 1.25-2.55) errors in prescribed chemotherapy for children with ALL. In the user satisfaction evaluation, the users approved two dimensions of the user interface and functionality of the system.

Conclusions:

With the provision of alerts, the CPDSS can help increase compliance with chemotherapy protocols and decrease the chemotherapy prescribing errors that can improve patient safety.

Substance of choice, impact of heroin or opium on treatment retention in a multicentre randomised controlled trial in Iran

INTRODUCTION

In the Middle East and Asia, illicit opioid use exists across a spectrum between heroin and opium. The impact of primary opioid of choice on opioid agonist treatment retention has not been well evaluated previously, especially for opium tincture, an increasingly popular form of opioid agonist treatment in Iran. This study investigates the relationship between primary opioid of choice, namely heroin or opium, and retention in opium tincture and methadone treatment.

METHODS

Participants with opioid use disorder (n = 204) were randomised to receive opium tincture or methadone. All participants were categorised as mainly using opium or heroin. Bivariate analyses between treatment retention and primary opioid of choice (P < 0.05) and logistic regression were conducted.

RESULTS

Among the 191 participants included in this analysis, heroin was the primary substance of choice for 135 participants (70.7%) and opium for 56 (29.3%). Bivariate analysis showed that the opium group was more likely to be satisfied with family situation, employed and retained in treatment than the heroin group while less likely to experience incarceration and use multiple substances. When adjusting for covariates, primary opioid of choice was not significantly associated with retention in either methadone or opium tincture treatment arm.

DISCUSSION AND CONCLUSIONS

Positive factors, such as employment, housing and family support, seem to collectively explain the higher retention in treatment among those who primarily use opium compared to those who use heroin. To optimise retention in opioid agonist treatment, biopsychosocial care models should be further evaluated to improve psychosocial functioning.

Contextual features in the developing hippocampus: A representational similarity analysis

Functional divisions of labor in support of memory have been reported along the anterior-posterior axis of the hippocampus. However, little is known about how the developing hippocampus represents associative memories along this axis. The present research employed representational similarity analysis to ask whether developmental differences exist in the extent to which the anterior versus the posterior hippocampus represent features of the context and associative memories. Functional magnetic resonance imaging data were collected during the retrieval phase of an associative recognition task from 8-year-olds, 10-year-olds, and adults (N = 58). Participants were asked to retrieve pairs of items, which were presented either in the same location as during encoding or in a flipped location. In the anterior hippocampus and only for adults, pattern similarity between the two studied pair conditions was greater than pattern similarity between studied pairs presented in the same location and novel pairs. In contrast, this difference was not significant in the posterior hippocampus. Older, but not younger, children showed a similar, albeit attenuated, similarity pattern to that of adults, but measures of patterns similarity predicted associative recognition across ages. In addition, exploratory analyses showed that similarity patterns in the adult posterior, but not anterior, hippocampus tracked the order of the runs. Overall, the results suggest functional and developmental dissociations in processing different contextual features, with the anterior hippocampus responding to salient and rapid-changing features and the posterior hippocampus responding to slower-changing features of the context.

Shedding Light on Targeting Chronic Myeloid Leukemia Stem Cells

Chronic myeloid leukemia stem cells (CML LSCs) are a rare and quiescent population that are resistant to tyrosine kinase inhibitors (TKI). When TKI therapy is discontinued in CML patients in deep, sustained and apparently stable molecular remission, these cells in approximately half of the cases restart to grow, resuming the leukemic process. The elimination of these TKI resistant leukemic stem cells is therefore an essential step in increasing the percentage of those patients who can reach a successful long-term treatment free remission (TFR). The understanding of the biology of the LSCs and the identification of the differences, phenotypic and/or metabolic, that could eventually allow them to be distinguished from the normal hematopoietic stem cells (HSCs) are therefore important steps in designing strategies to target LSCs in a rather selective way, sparing the normal counterparts.

Galvanic Vestibular Stimulation Effects on EEG Biomarkers of Motor Vigor in Parkinson's Disease

Background: Impaired motor vigor (MV) is a critical aspect of Parkinson's disease (PD) pathophysiology. While MV is predominantly encoded in the basal ganglia, deriving (cortical) EEG measures of MV may provide valuable targets for modulation via galvanic vestibular stimulation (GVS). Objective: To find EEG features predictive of MV and examine the effects of high-frequency GVS. Methods: Data were collected from 20 healthy control (HC) and 18 PD adults performing 30 trials total of a squeeze bulb task with sham or multi-sine (50-100 Hz "GVS1" or 100-150 Hz "GVS2") stimuli. For each trial, we determined the time to reach maximum force after a "Go" signal, defined MV as the inverse of this time, and used the EEG data 1-sec prior to this time for prediction. We utilized 53 standard EEG features, including relative spectral power, harmonic parameters, and amplitude and phase of bispectrum corresponding to standard EEG bands from each of 27 EEG channels. We then used LASSO regression to select a sparse set of features to predict MV. The regression weights were examined, and separate band-specific models were developed by including only band-specific features (Delta, Theta, Alpha-low, Alpha-high, Beta, Gamma). The correlation between MV prediction and measured MV was used to assess model performance. Results: Models utilizing broadband EEG features were capable of accurately predicting MV (controls: 75%, PD: 81% of the variance). In controls, all EEG bands performed roughly equally in predicting MV, while in the PD group, the model using only beta band features did not predict MV well compared to other bands. Despite having minimal effects on the EEG feature values themselves, both GVS stimuli had significant effects on MV and profound effects on MV predictability via the EEG. With the GVS1 stimulus, beta-band activity in PD subjects became more closely associated with MV compared to the sham condition. With GVS2 stimulus, MV could no longer be accurately predicted from the EEG. Conclusions: EEG features can be a proxy for MV. However, GVS stimuli have profound effects on the relationship between EEG and MV, possibly via direct vestibulo-basal ganglia connections not measurable by the EEG.

Apoptin Overexpression Efficiently Amplified Cytotoxic Effects of PI3K Inhibition Using BKM120 in Lymphoblastic Leukemia Cell Lines

Purpose: Although the complex structure of acute lymphoblastic leukemia (ALL) and involvement of diverse pathways in its pathogenesis have put an obstacle in the way of efficient treatments, identification of strategies to manipulate the genome of neoplastic cells has made the treatment prospective more optimistic.

Methods: To evaluate whether the transduction of apoptin __a gene encoding a protein that participates in the induction of apoptosis__ could reduce the survival of leukemic cells, we generated recombinant lentivirus expressing apoptin, and then, MTT assay, flow cytometric analysis of DNA content, western blotting, and quantitative reverse transcription polymerase chain reaction (qRT-PCR) were applied.

Results: Transduction of apoptin into different leukemic cells was coupled with the reduction in the viability and proliferative capacity of the cells. Among all tested cell lines, Nalm-6 and C8166 were more sensitive to the anti-leukemic property of apoptin. Moreover, we found that the transduction of apoptin in the indicated cell lines not only induced G2/M cell cycle arrest but also induced apoptotic cell death by altering the balance between pro- and anti-apoptotic target genes. The efficacy of apoptin transduction was not limited to these findings, as we reported for the first time that the overexpression of this gene could potentiate the anti-leukemic property of pan PI3K inhibitor BKM120.

Conclusion: The results of this study showed that the transduction of apoptin into lymphoblastic leukemia cell lines induced cytotoxic effects and enhanced therapeutic value of PI3K inhibition; however, further investigations are demanded to ascertain the safety and the efficacy of apoptin transduction in patients with ALL.

Developmental Differences in Subjective Recollection and Its Role in Decision Making

We examined how subjective assessments of recollection guide decision making. Subjective recollection was dissociated from accuracy during a forced-choice recognition task. Distracters were either similar to targets (match condition) or to other studied, but untested items (nonmatch condition). We assessed 223 participants (112 males) across three experiments (137 White, 37 Asian-American, 7 African-American, 4 American-Indian, 32 mixed race, 6 undisclosed). In Experiment 1, 6- to 10-year-olds and adults (N = 119) were less accurate (d = 0.70), but more likely to claim subjective recollection and make memory selections in anticipation of a reward in the nonmatch condition (ds = 0.64-0.70). This pattern was eliminated in 6- to 7-year-olds when we limited the number of selections (Experiment 2, N = 52), but was replicated when we required the selections to be counted (Experiment 3, N = 52), underscoring the effects of decision complexity on children's self-reflections.

An Intelligent Clinical Decision Support System for Predicting Acute Graft-versus-host Disease (aGvHD) following Allogeneic Hematopoietic Stem Cell Transplantation

Background:

Acute graft-versus-host disease (aGvHD) is a complex and often multisystem disease that causes morbidity and mortality in 35% of patients receiving allogeneic hematopoietic stem cell transplantation (AHSCT).

Objective:

This study aimed to implement a Clinical Decision Support System (CDSS) for predicting aGvHD following AHSCT on the transplantation day.

Material and Methods:

In this developmental study, the data of 182 patients with 31 attributes, which referred to Taleghani Hospital Tehran, Iran during 2009–2017, were analyzed by machine learning (ML) algorithms which included XGBClassifier, HistGradientBoostingClassifier, AdaBoostClassifier, and RandomForestClassifier. The criteria measurement used to evaluate these algorithms included accuracy, sensitivity, and specificity. Using the machine learning developed model, a CDSS was implemented. The performance of the CDSS was evaluated by Cohen’s Kappa coefficient.

Results:

Of the 31 included variables, albumin, uric acid, C-reactive protein, donor age, platelet, lactate Dehydrogenase, and Hemoglobin were identified as the most important predictors. The two algorithms XGBClassifier and HistGradientBoostingClassifier with an average accuracy of 90.70%, sensitivity of 92.5%, and specificity of 89.13% were selected as the most appropriate ML models for predicting aGvHD. The agreement between CDSS prediction and patient outcome was 92%.

Conclusion:

ML methods can reliably predict the likelihood of aGvHD at the time of transplantation. These methods can help us to limit the number of risk factors to those that have significant effects on the outcome. However, their performance is heavily dependent on selecting the appropriate methods and algorithms. The next generations of CDSS may use more and more machine learning approaches.

A Deep Learning Strategy for Automatic Sleep Staging Based on Two-Channel EEG Headband Data

Sleep disturbances are common in Alzheimer’s disease and other neurodegenerative disorders, and together represent a potential therapeutic target for disease modification. A major barrier for studying sleep in patients with dementia is the requirement for overnight polysomnography (PSG) to achieve formal sleep staging. This is not only costly, but also spending a night in a hospital setting is not always advisable in this patient group. As an alternative to PSG, portable electroencephalography (EEG) headbands (HB) have been developed, which reduce cost, increase patient comfort, and allow sleep recordings in a person’s home environment. However, naïve applications of current automated sleep staging systems tend to perform inadequately with HB data, due to their relatively lower quality. Here we present a deep learning (DL) model for automated sleep staging of HB EEG data to overcome these critical limitations. The solution includes a simple band-pass filtering, a data augmentation step, and a model using convolutional (CNN) and long short-term memory (LSTM) layers. With this model, we have achieved 74% (±10%) validation accuracy on low-quality two-channel EEG headband data and 77% (±10%) on gold-standard PSG. Our results suggest that DL approaches achieve robust sleep staging of both portable and in-hospital EEG recordings, and may allow for more widespread use of ambulatory sleep assessments across clinical conditions, including neurodegenerative disorders.

Opium tincture for opioid substitution treatment

Introduction

Opium tincture (OT) is widely used for opioid substitution treatment (OST) in Iran.

Objectives

To determine if OT is a safe and effective medication for OST.

Methods

Opium Trial was a multicenter, double‐blind, noninferiority randomized controlled trial, with 204 participants with opioid dependence in Iran. Participants were then randomized to OT or methadone arms with an allocation ratio of 1:1 and were followed for 12 weeks. The primary outcome was retention in treatment, compared between the two groups using both intention-To-Treat (ITT) and Per-Protocol (PP) analyses.

Results

A total of 70 participants (IT: 68.6%, PP: 69.3%) in methadone arm and 61 participants (ITT: 59.8%, PP: 60.4%) in OT arm remained in the treatment. The relative retention rate was 1.15 (0.97, 1.36) in both analyses in favour of methadone. A total of 46 out of 152 (30.3%) participants in OT arm and 83 out of 168 (49.4%) participants in methadone arm reported opioid use outside the treatment. The difference in these two proportions (OT - methadone) was 19%: (10%, 28%) in favour of OT. The proportion of patients with adverse events were not different between the two arms (P = 0.06). There was no serious AE in OT arm.

Conclusions

Opium tincture is a clinically effective and safe medication, but this study could not conclude if it was as equally effective as methadone in retaining participants in treatment, but it showed that OT was superior to methadone in reducing opioid use outside the treatment.

Disclosure

No significant relationships.

Response latencies and eye gaze provide insight on how toddlers gather evidence under uncertainty

Toddlers exhibit behaviours that suggest judicious responses to states of uncertainty (for example, turning to adults for help), but little is known about the informational basis of these behaviours. Across two experiments, of which experiment 2 was a preregistered replication, 160 toddlers (aged 25 to 32 months) identified a target from two partially occluded similar (for example, elephant versus bear) or dissimilar (for example, elephant versus broccoli) images. Accuracy was lower for the similar trials than for the dissimilar trials. By fitting drift-diffusion models to response times, we found that toddlers accumulated evidence more slowly but required less evidence for similar trials compared with dissimilar trials. By analysing eye movements, we found that toddlers took longer to settle on the selected image during inaccurate trials and switched their gaze between response options more frequently during inaccurate trials and accurately identified similar items. Exploratory analyses revealed that the evidence-accumulation parameter correlated positively with the use of uncertainty language. Overall, these findings inform theories on the emergence of evidence accumulation under uncertainty.

Machine Learning Classification Algorithms to Predict aGvHD following Allo-HSCT: A Systematic Review

BACKGROUND

 The acute graft-versus-host disease (aGvHD) is the most important cause of mortality in patients receiving allogeneic hematopoietic stem cell transplantation. Given that it occurs at the stage of severe tissue damage, its diagnosis is late. With the advancement of machine learning (ML), promising real-time models to predict aGvHD have emerged.

OBJECTIVE

 This article aims to synthesize the literature on ML classification algorithms for predicting aGvHD, highlighting algorithms and important predictor variables used.

METHODS

 A systemic review of ML classification algorithms used to predict aGvHD was performed using a search of the PubMed, Embase, Web of Science, Scopus, Springer, and IEEE Xplore databases undertaken up to April 2019 based on Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statements. The studies with a focus on using the ML classification algorithms in the process of predicting of aGvHD were considered.

RESULTS

 After applying the inclusion and exclusion criteria, 14 studies were selected for evaluation. The results of the current analysis showed that the algorithms used were Artificial Neural Network (79%), Support Vector Machine (50%), Naive Bayes (43%), k-Nearest Neighbors (29%), Regression (29%), and Decision Trees (14%), respectively. Also, many predictor variables have been used in these studies so that we have divided them into more abstract categories, including biomarkers, demographics, infections, clinical, genes, transplants, drugs, and other variables.

CONCLUSION

 Each of these ML algorithms has a particular characteristic and different proposed predictors. Therefore, it seems these ML algorithms have a high potential for predicting aGvHD if the process of modeling is performed correctly.

Cerebral palsy information system with an approach to information architecture: a systematic review

Background

Long-term complications and high costs of cerebral palsy (CP) as well as inconsistency in data related to this disease reveal the need for extensive planning to obtain accurate and complete data for the effective management of patients.

Objective

The present study reviews the information architecture of CP information system.

Method

The relevant articles published from early 1988 to 31 July 2018 were extracted through searching PubMed, Scopus, Cochran, Web of Science and Embase databases conducted independently by two researchers.

Results

A total of 39 articles on CP information system were reviewed. Hospitals, rehabilitation centres and outpatient clinics were found to be the main organisations in charge of generating CP data. Each CP database used several data sources, with hospitals serving as the most important sources of information and the main generators of data. The main CP datasets were categorised into four groups of demographic data, diagnosis, motor function and visual impairment. The majority of data standards were related to the use of the International Classification of Functioning, Disability and Health and the Gross Motor Function Classification System. Finally, accuracy, completeness and consistency were the criteria employed in data quality control.

Conclusion

Developing a robust CP information system requires deploying the principles of information architecture when developing the system, as these can improve data structure and content of CP system, as well as data quality and data sharing.

Surfactant delivery in rat lungs: Comparing 3D geometrical simulation model with experimental instillation

Surfactant Replacement Therapy (SRT), which involves instillation of a liquid-surfactant mixture directly into the lung airway tree, is a major therapeutic treatment in neonatal patients with respiratory distress syndrome (RDS). This procedure has proved to be remarkably effective in premature newborns, inducing a five-fold decrease of mortality in the past 35 years. Disappointingly, its use in adults for treating acute respiratory distress syndrome (ARDS) experienced initial success followed by failures. Our recently developed numerical model has demonstrated that transition from success to failure of SRT in adults could, in fact, have a fluid mechanical origin that is potentially reversible. Here, we present the first numerical simulations of surfactant delivery into a realistic asymmetric conducting airway tree of the rat lung and compare them with experimental results. The roles of dose volume (VD), flow rate, and multiple aliquot delivery are investigated. We find that our simulations of surfactant delivery in rat lungs are in good agreement with our experimental data. In particular, we show that the monopodial architecture of the rat airway tree plays a major role in surfactant delivery, contributing to the poor homogeneity of the end distribution of surfactant. In addition, we observe that increasing VD increases the amount of surfactant delivered to the acini after losing a portion to coating the involved airways, the coating cost volume, VCC. Finally, we quantitatively assess the improvement resulting from a multiple aliquot delivery, a method sometimes employed clinically, and find that a much larger fraction of surfactant reaches the alveolar regions in this case. This is the first direct qualitative and quantitative comparison of our numerical model with experimental studies, which enhances our previous predictions in adults and neonates while providing a tool for predicting, engineering, and optimizing patient-specific surfactant delivery in complex situations.

Bone marrow microenvironment: The guardian of leukemia stem cells

Bone marrow microenvironment (BMM) is the main sanctuary of leukemic stem cells (LSCs) and protects these cells against conventional therapies. However, it may open up an opportunity to target LSCs by breaking the close connection between LSCs and the BMM. The elimination of LSCs is of high importance, since they follow cancer stem cell theory as a part of this population. Based on cancer stem cell theory, a cell with stem cell-like features stands at the apex of the hierarchy and produces a heterogeneous population and governs the disease. Secretion of cytokines, chemokines, and extracellular vesicles, whether through autocrine or paracrine mechanisms by activation of downstream signaling pathways in LSCs, favors their persistence and makes the BMM less hospitable for normal stem cells. While all details about the interactions of the BMM and LSCs remain to be elucidated, some clinical trials have been designed to limit these reciprocal interactions to cure leukemia more effectively. In this review, we focus on chronic myeloid leukemia and acute myeloid leukemia LSCs and their milieu in the bone marrow, how to segregate them from the normal compartment, and finally the possible ways to eliminate these cells.

Effect of probiotic and prebiotic versus placebo on appetite in patients with major depressive disorder: post hoc analysis of a randomised clinical trial

BACKGROUND

Poor appetite and weight loss are common in melancholic depression. Probiotics and prebiotics have the capacity to affect host behaviour, appetite and weight change by modulating the gut microbiome. The aim of this post hoc analysis was to investigate the effect of supplementation with probiotic and prebiotic on appetite, in parallel with body mass index (BMI), weight and energy intake, in patients with major depressive disorder (MDD).

METHODS

We extracted data from a clinical trial with 81 patients. The participants were randomly assigned to receive probiotic (Lactobacillus helveticus and Bifidobacterium longum), prebiotic (galactooligosaccharide) or placebo for 8 weeks. Appetite, weight, BMI, dietary intake, serum leptin and physical activity were measured. Subjective appetite rating was evaluated every 2 weeks using visual analogue scales (VAS) to assess satiety, hunger, fullness and desire to eat. Serum leptin was measured by an enzyme-linked immunosorbent assay. Physical activity was measured using the international physical activity questionnaire. A repeated measures analysis of variance model was used to analyse VAS data and analysis of variance/analysis of covariance models for dietary intake, BMI, weight and leptin data.

RESULTS

VAS data analyses indicated no significant intervention-time interactions but did show a significant increase over time for desire to eat within the probiotic group (P = 0.025). No significant difference in either BMI or weight was seen among the groups. Energy intake and leptin were significantly increased in the probiotic group compared to the prebiotic.

CONCLUSIONS

Overall, probiotic supplementation for 8 weeks among MDD patients resulted in improvement of appetite, whereas prebiotic administration had no significant effect on appetite.

Characteristics of software used in self-management of vitamin K antagonist therapy: A systematic review

INTRODUCTION AND GOAL

Currently, 1-2% of the population in developed countries are under treatment with oral anticoagulants. An appropriate strategy to deal with this increase in demand of treatment with oral anticoagulants and to manage the costs is the transfer of part or all of the responsibility for managing treatment to the patients. The use of information technology, particularly electronic health software, can be an appropriate method to improve the quality of self-management of treatment with these drugs. Therefore, this systematic review investigated studies that discuss the characteristics of electronic health software in self-management of oral anticoagulation therapy.

METHOD

A systematic review based on PRISMA protocol was conducted. In this study, articles were investigated that were in English. Articles existing in Cochrane, EMBASE and PubMed databases were searched up to 14 May 2017. Then, articles searched through Google Scholar were added to this study.

FINDINGS

The common characteristics used in most software included 'encryption in exchanging information', having an 'instruction module' and 'being Android-based'. In terms of functionality, 'communication between the patient and healthcare team' existed in most of the software.

CONCLUSION

The results of the study showed that the accuracy of administration of the dose of the drug using computer to reach a target international normalized ratio level was not less than those administered with experienced medical staff. In addition, the results indicated that important characteristics of the software include encryption in exchanging information, instruction module and Android-based instruction module. The most important characteristic was the interaction between the patient and the healthcare team.

Comparing opium tincture and methadone for medication-assisted treatment of patients with opioid use disorder: Protocol for a multicenter parallel group noninferiority double-blind randomized controlled trial

OBJECTIVES

This is the first study to compare the safety and efficacy of opium tincture (OT) with methadone for treatment of opioid use disorder.

METHODS

In this multicenter, double-blind, noninferiority controlled trial, a stratified sample of 204 participants with opioid use disorder were recruited from community outreach, drop-in centers, and triangular clinics. Participants were excluded in case of active participation in another treatment program for opioid use disorder, hypersensitivity to trial medications, pregnancy, and certain serious medical conditions. They were randomized to receive either OT or methadone with an allocation ratio of 1:1 using a patient-centered flexible dosing strategy. Eligible participants were followed for a period of 12 weeks. Primary outcome is the difference in percentage of patients retained in the treatment. Secondary outcomes are craving, withdrawal symptoms, physical health, mental health, quality of life, and severity of substance use problems, cognitive function, safety profile, cost-effectiveness, and participants' satisfaction. Both intention-to-treat and per-protocol analyses will be conducted. The Ethics Board of the University of British Columbia and Tehran University of Medical Sciences approved the study. (clinicaltrials.gov; NCT02502175).

RESULTS

To be reported after final analysis.

CONCLUSIONS

If shown to be effective, OT will diversify the options for medication-assisted treatment of opioid use disorder.

Anticancer effect of pan-PI3K inhibitor on multiple myeloma cells: Shedding new light on the mechanisms involved in BKM120 resistance

The correlation between the Phosphoinositide 3-kinase (PI3K) axis and crucial mechanisms involved in the maintenance of the neoplastic nature of multiple myeloma (MM) has recently evolved a general agreement that PI3K inhibition-based therapies could construct an exciting perspective for the future treatment strategies. Our results outlined that abrogation of PI3K using pan-PI3K inhibitor BKM120 decreased survival of MM cells through induction of a caspase-3-dependent apoptosis coupled with SIRT1-mediated G2/M arrest in both KMM-1 and RPMI 8226 cell lines; however, the cell responses to the inhibitor was quite different, introducing wild-type PTEN-expressing RPMI 8226 as less sensitive cells. By investigating the sensitivity extent of a panel of hematological cell lines to BKM120, we found no significant association with respect to PTEN status. As far as we are aware, the results of the present study propose for the first time that the inhibitory effect of BKM120 was overshadowed, at least partially, through over-expression of either c-Myc or nuclear factor (NF)-κB in less sensitive MM cells. While there was no significant effect of the inhibitor on the expression of c-Myc in RPMI 8226, we found an enhanced cytotoxic effect when BKM120 was used in combination with a small molecule inhibitor of c-Myc. Noteworthy, the results of the synergistic experiments also revealed that BKM120 could produce a synergistic anti-cancer effect with carfilzomib (CFZ) and provided an enhanced therapeutic efficacy in MM cells, highlighting that PI3K inhibition might be a befitting approach in MM both in mono and combined therapy.

Long noncoding RNA PVT1: potential oncogene in the development of acute lymphoblastic leukemia

Emerging evidence shows that long noncoding RNAs (lncRNAs) participate in various cellular processes, and that plasmacytoma variant translocation 1 (PVT1), a newly described oncogene that interacts with various molecules such as p15, p16, NOP2, and c-Myc, is a major contributing factor in tumor development. However, the role of this oncogene remains unknown in the pathogenesis of acute lymphoblastic leukemia (ALL), the most prevalent form of childhood leukemia. In this study, we first measure the expression level of PVT1 in a Jurkat cell line, then small interfering (siRNA) PVT1 is applied to demonstrate the impact of PVT1 knockdown in apoptosis, proliferation, the cell cycle, and its downstream targets. Our findings show that lncRNA was significantly higher in the ALL cell line than normal lymphocytes and that PVT1 knock-down increased the rate of apoptosis, caused G0/G1 arrest in the cell cycle, reduced the proliferation rate, and, above all, reduced the stability of c-Myc protein. All findings were confirmed at the molecular level. Our results may indicate the role of PVT1 knock-down in the suppression of ALL development and might provide an option for targeted therapy for leukemic conditions.

National information system for rare diseases with an approach to data architecture: A systematic review

The study aims to systematically review literature on the rare diseases information system to identify architecture of this system from a data perspective. The search for relevant English language articles, based on keywords in title, abstract, Mesh and Emtree terms, was done in Pubmed and Embase (from 1980 to June 2017), Scopus, Science Direct and Cochran (from 1980 to July 2017). Articles were selected if they addressed data architecture of information systems with a focus on rare disease, and if at least one of their objectives dealt with design, implementation, and development of rare diseases information systems. Thirty-five studies met the inclusion criteria. The findings were categorized into six groups. This first group addressed organizations acting as data generators, data users, and data governors. The second group was related to data sources and databases. Datasets and data elements formed the third group of findings, including common datasets, specific datasets, and complementary datasets. The fourth group of findings was in relation to data standards. Data sharing and interactions among relevant bodies included the fifth group of the findings. The last group of findings was pertinent to procedures and criteria used for checking the quality of data, as cross review checking was a main procedure assessing the accuracy, consistency, and completeness of data. Design and development of an integrated information system for rare diseases considering data architecture principles in practice could help eliminating issues with management of rare diseases through facilitating sharing information and experiences.

Specifications of Computerized Provider Order Entry and Clinical Decision Support Systems for Cancer Patients Undergoing Chemotherapy: A Systematic Review

OBJECTIVE

Chemotherapy medication errors are catastrophic. The prescription phase in the chemotherapy process plays a key role in the creation of medication errors, and therefore the use of computerized physician order entry (CPOE) and clinical decision support system (CDS) systems is recommended to reduce chemotherapy medication errors. The purpose of this study was to carry out a systematic review on the specifications of the CPOE and CDS systems for chemotherapy prescription.

MATERIALS AND METHODS

A systematic review on articles published in English up to September 22, 2017, using the 3 databases PubMed, Embase, and Medline was conducted. Those articles that focused on the specifications of CPOE and CDSS in chemotherapy prescription were included in this review.

FINDINGS

Of the 2,471 articles identified, 58 articles met the inclusion criteria and were included in this study. Specifications related to chemotherapy CPOE systems were categorized into the following 6 groups: automation and facilitation of the chemotherapy prescription phase, hospital workflow support, documentation and reporting, drug safety, information security, and system communications. The specifications of chemotherapy CDSS were also divided into 4 categories: embedding chemotherapy protocols, automated dose calculations and adjustment, providing alerts/reminders at the time of prescribing, and guiding or asking the user to complete the important prescription parameters. In 12 articles, the chemotherapy prescription CDSS were designed and evaluated independently of the CPOE; 45 articles provided prescription chemotherapy CDSS as part of the CPOE system, and in 1 article CPOE was introduced with no CDSS.

CONCLUSION

In complicated settings such as chemotherapy, simplification of the processes is more imperative. The use of chemotherapy CPOE, which includes specifications for helping the medical staff with their workload, encourages the professionals to use such systems and increases the likelihood for success of these systems.

Long non-coding RNA PVT1 as a novel candidate for targeted therapy in hematologic malignancies

Cancerous cells show resistance to various forms of therapy, so applying up to the minute targeted therapy is crucial. For this purpose, long non-coding RNA PVT1 as shown by recent studies is an important oncogene that interacts with vital cellular signaling pathways and different proteins such as c-Myc, NOP2 and LATS2. Due to the enormous role of long non-coding RNAs in development of leukemias, we aimed to show the role of PVT1 knock-down on fate of different hematologic cell lines. owing to this matter, various experiments such as Real-time PCR, cell cycle analysis and apoptosis assay were performed. Meanwhile, proliferation rate by CFSE, protein expression of c-Myc and hTERT by western blot and flow cytometry analysis were investigated. Our results demonstrated that PVT1 knock-down results in c-Myc degradation, proliferation down-regulation, induction of apoptosis and G0/G1 arrest. Simultaneously, for the first time, we posited the relation between this oncogene with hTERT that reduced after PVT1 knock-down. Considering these results, long non-coding RNA PVT1 may be a potential option for targeted therapy in hematologic malignancies.

Vertical Charge Transfer and Lateral Transport in Graphene/Germanium Heterostructures

Heterostructures consisting of two-dimensional (2D) materials and conventional semiconductors have attracted a lot of attention due to their application in novel device concepts. In this work, we investigated the lateral transport characteristics of graphene/germanium heterostructures and compared them with the transport properties of graphene on SiO₂. The heterostructures were fabricated by transferring a single layer of graphene (Gr) onto a lightly doped germanium (Ge) (100) substrate. The field-effect measurements revealed a shift in the Dirac voltage of Gr on the Ge substrates compared to that of the Gr on SiO₂. Transfer length model measurements show a significant difference in the sheet resistance of Gr on Ge compared to that of the Gr on SiO₂. The results from the electrical and structural characterization suggest that a charge transfer in the order of 10¹² cm^-2 occurs between Gr and Ge resulting in a doping effect in the graphene sheet. A compact electrostatic model extracted the key electronic properties of the Gr/Ge interface. This study provides valuable insights into the electronic properties of Gr on Ge, which are vital to the development of novel devices based on mixed 2D and 3D structures.

The effects of weight loss approaches on bone mineral density in adults: a systematic review and meta-analysis of randomized controlled trials

We assessed the impact of weight loss strategies including calorie restriction and exercise training on BMD in adults using a systematic review of randomized controlled trials. Weight reduction results in reduced BMD at the hip, but has less effect on the spine. Both calorie restriction and a combination of calorie restriction and exercise result in a decrease in hip bone density, whereas weight loss response to exercise training without dietary restriction leads to increased hip BMD.

INTRODUCTION

Findings are not consistent on the effect of weight loss on bone mineral density (BMD). We conducted a systematic review on the randomized controlled trials to assess the effect of weight loss strategies, including calorie restriction and exercise programs on BMD in adults.

METHODS

A structured and comprehensive search of MEDLINE and EMBASE databases was undertaken up to March 2016. Study-specific mean differences (MD) were pooled using a random-effects model. Subgroup analysis and meta-regression were used to find possible sources of between-study heterogeneity.

RESULTS

Thirty-two randomized controlled trials met predetermined inclusion criteria. The meta-analysis revealed no significant difference on total BMD (MD 0.007, 95 % CI -0.020-0.034, p = 0.608). In contrast, the pooled data of studies showed a significant effect of weight loss on hip BMD (MD -0.008, 95 % CI -0.09 to -0.006 g/cm(2), p < 0.001) and also lumbar spine BMD (MD -0.018 g/cm(2), 95 % CI -0.019 to -0.017, p < 0.001). BMD in the hip site decreased after more than 4 months, especially in those who were obese. Moreover, calorie restriction interventions longer than 13 months showed a significant decreased in lumbar spine BMD.

CONCLUSION

Weight loss led to significant decreases at the hip and lumbar spine BMD but not at the total. Weight loss response following calorie restriction resulted in a decrease in hip and lumbar spine bone density especially more than 1 year; whereas an exercise-induced weight loss did not.

Pharmacy Information Systems in Teaching Hospitals: A Multi-dimensional Evaluation Study

Objectives

In hospitals, the pharmacy information system (PIS) is usually a sub-system of the hospital information system (HIS). The PIS supports the distribution and management of drugs, shows drug and medical device inventory, and facilitates preparing needed reports. In this study, pharmacy information systems implemented in general teaching hospitals affiliated to medical universities in Tehran (Iran) were evaluated using a multi-dimensional tool.

Methods

This was an evaluation study conducted in 2015. To collect data, a checklist was developed by reviewing the relevant literature; this checklist included both general and specific criteria to evaluate pharmacy information systems. The checklist was then validated by medical informatics experts and pharmacists. The sample of the study included five PIS in general-teaching hospitals affiliated to three medical universities in Tehran (Iran). Data were collected using the checklist and through observing the systems. The findings were presented as tables.

Results

Five PIS were evaluated in the five general-teaching hospitals that had the highest bed numbers. The findings showed that the evaluated pharmacy information systems lacked some important general and specific criteria. Among the general evaluation criteria, it was found that only two of the PIS studied were capable of restricting repeated attempts made for unauthorized access to the systems. With respect to the specific evaluation criteria, no attention was paid to the patient safety aspect.

Conclusions

The PIS studied were mainly designed to support financial tasks; little attention was paid to clinical and patient safety features.