DHLP 1&2: Giraph based distributed label propagation algorithms on heterogeneous drug-related networks

Background and Objective: Heterogeneous complex networks are large graphs consisting of different types of nodes and edges. The knowledge extraction from these networks is complicated. Moreover, the scale of these networks is steadily increasing. Thus, scalable methods are required. Methods: In this paper, two distributed label propagation algorithms for heterogeneous networks, namely DHLP-1 and DHLP-2 have been introduced. Biological networks are one type of the heterogeneous complex networks. As a case study, we have measured the efficiency of our proposed DHLP-1 and DHLP-2 algorithms on a biological network consisting of drugs, diseases, and targets. The subject we have studied in this network is drug repositioning but our algorithms can be used as general methods for heterogeneous networks other than the biological network. Results: We compared the proposed algorithms with similar non-distributed versions of them namely MINProp and Heter-LP. The experiments revealed the good performance of the algorithms in terms of running time and accuracy.Comment: Source code available for Apache Giraph on Hadoo

Unilateral Adrenal Hemorrhage: A Rare Complication of Anticoagulant Use

Unilateral adrenal hemorrhage is a rare but deadly complication that can occur secondary to causes such as trauma and metastasis. A 55-year-old male with a history of metastatic lung adenocarcinoma and deep vein thrombosis managed with rivaroxaban presented with acute right abdominal and flank pain. A CT angiogram of the abdomen showed a retroperitoneal hematoma around the right adrenal gland, consistent with a unilateral adrenal hemorrhage. An MRI showed no signs of adrenal metastasis and the patient had no history of trauma. The volume of the hematoma did not change in size and the patient was hemodynamically stable, which only prompted supportive management. Anticoagulant use is a known risk factor for bilateral adrenal hemorrhage. However, this case demonstrates that unilateral adrenal hemorrhage can also be a complication, one that usually appears subclinically. It can present non-specifically but may progress to a more fatal bilateral hemorrhage. Hence, it demands a high index of suspicion for patients on systemic anticoagulation

1317P Renal toxicity in black patients with non-squamous non-small cell lung cancer treated with combination platinum-pemetrexed-pembrolizumab therapy

Background: In Keynote 189, an increased incidence of renal toxicity was observed with combination platinum-pemetrexed-pembrolizumab (PPP) therapy compared to chemotherapy alone. Studies have shown that compared to White Americans, Black Americans are at higher risk of morbidity and mortality associated with chronic kidney disease (CKD). We conducted a retrospective analysis of patients treated with PPP to assess the rate of renal toxicity in Black and White patients. Methods: Data of self-identified non-hispanic (NH) Black and NH White patients with advanced NS-NSCLC who were treated with PPP between January 1, 2017, and November 1, 2020, at the Henry Ford Health System was analyzed. Serum creatinine (Cr) and calculated glomerular filtration rate (GFR) before the first cycle of PPP and over the duration of PPP therapy were assessed. Acute kidney injury (AKI) was defined as an increase in Cr 1.5 times the baseline value. Reduction in GFR of ≥ 30% was considered significant. Multiple variables and outcomes were analyzed by two-group comparisons, univariate analysis, and Cox regression. Results: A total of 134 patients were included in the analysis. The mean age was 66.5 (SD 8.6) years, and 65 (48.5%) patients were men. A total of 33 (24%) patients were NH Black and 101 (75.4%) were NH White. There were 10 (8.1%) patients who developed AKI, and the median time to development of AKI was 4.5 months. No significant association of Black (3) or White (7) ethnicity with AKI was observed (p =.57). The odds of developing AKI was not increased in patients with a history of hypertension (p =.67), diabetes mellitus (p =.33), cardiovascular disease (p =.68), or CKD (p =.33). A total of 17 out of 127 (13.4%) patients had significantly reduced GFR, and patients with CKD were more likely to have reduced GFR (OR 4.8, p =.02). At the median follow-up of 24.5 months, the median survival was 15.2 months (95% CI, 12.7-22.2). Black ethnicity (HR 1.21, p =.46) and development of AKI (HR 1.13; 95% CI, 0.45–2.86) were not associated with increased mortality. Conclusions: Black patients with NS-NSCLC treated with PPP are not at higher risk of AKI or death than White patients. Development of AKI after PPP therapy was not associated with increased mortality

Whole exome sequencing and homozygosity mapping reveals genetic defects in consanguineous Iranian families with inherited retinal dystrophies

Acknowledgements This research was funded by the Swiss National Science Foundation (Grant #176097 to CR). We would like to express gratitude to the patients and all their family members that participated in this study for their valuable cooperation and participation.Peer reviewedPublisher PD

Population-level risks of alcohol consumption by amount, geography, age, sex, and year: a systematic analysis for the Global Burden of Disease Study 2020

Background: The health risks associated with moderate alcohol consumption continue to be debated. Small amounts of alcohol might lower the risk of some health outcomes but increase the risk of others, suggesting that the overall risk depends, in part, on background disease rates, which vary by region, age, sex, and year. Methods: For this analysis, we constructed burden-weighted dose–response relative risk curves across 22 health outcomes to estimate the theoretical minimum risk exposure level (TMREL) and non-drinker equivalence (NDE), the consumption level at which the health risk is equivalent to that of a non-drinker, using disease rates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2020 for 21 regions, including 204 countries and territories, by 5-year age group, sex, and year for individuals aged 15–95 years and older from 1990 to 2020. Based on the NDE, we quantified the population consuming harmful amounts of alcohol. Findings: The burden-weighted relative risk curves for alcohol use varied by region and age. Among individuals aged 15–39 years in 2020, the TMREL varied between 0 (95% uncertainty interval 0–0) and 0·603 (0·400–1·00) standard drinks per day, and the NDE varied between 0·002 (0–0) and 1·75 (0·698–4·30) standard drinks per day. Among individuals aged 40 years and older, the burden-weighted relative risk curve was J-shaped for all regions, with a 2020 TMREL that ranged from 0·114 (0–0·403) to 1·87 (0·500–3·30) standard drinks per day and an NDE that ranged between 0·193 (0–0·900) and 6·94 (3·40–8·30) standard drinks per day. Among individuals consuming harmful amounts of alcohol in 2020, 59·1% (54·3–65·4) were aged 15–39 years and 76·9% (73·0–81·3) were male. Interpretation: There is strong evidence to support recommendations on alcohol consumption varying by age and location. Stronger interventions, particularly those tailored towards younger individuals, are needed to reduce the substantial global health loss attributable to alcohol. Funding: Bill & Melinda Gates Foundation

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

A scalable random walk with restart on heterogeneous networks with Apache Spark for ranking disease-related genes through type-II fuzzy data fusion

One of the effective missions of biology and medical science is to find disease-related genes. Recent research uses gene/protein networks to find such genes. Due to false positive interactions in these networks, the results often are not accurate and reliable. Integrating multiple gene/protein networks could overcome this drawback, causing a network with fewer false positive interactions. The integration method plays a crucial role in the quality of the constructed network. In this paper, we integrate several sources to build a reliable heterogeneous network, i.e., a network that includes nodes of different types. Due to the different gene/protein sources, four gene-gene similarity networks are constructed first and integrated by applying the type-II fuzzy voter scheme. The resulting gene-gene network is linked to a disease-disease similarity network (as the outcome of integrating four sources) through a two-part disease-gene network. We propose a novel algorithm, namely random walk with restart on the heterogeneous network method with fuzzy fusion (RWRHN-FF). Through running RWRHN-FF over the heterogeneous network, disease-related genes are determined. Experimental results using the leave-one-out cross-validation indicate that RWRHN-FF outperforms existing methods. The proposed algorithm can be applied to find new genes for prostate, breast, gastric, and colon cancers. Since the RWRHN-FF algorithm converges slowly on large heterogeneous networks, we propose a parallel implementation of the RWRHN-FF algorithm on the Apache Spark platform for high-throughput and reliable network inference. Experiments run on heterogeneous networks of different sizes indicate faster convergence compared to other non-distributed modes of implementation

NaBH4 Hydrolysis for Hydrogen Generation over Metal-Organic Frameworks (Cu-BTC)

Hydrogen gas (H2) is widely acknowledged as a sustainable and environmentally friendly energy carrier. In this study, we examined the potential of copper-based metal-organic frameworks (MOFs); copper-benzene-1,3,5-tricarboxylate (Cu-BTC), as catalysts for the release of hydrogen through the hydrolysis of sodium borohydride (NaBH4). Cu(BTC) exhibited a hydrogen generation rate (HGR) of 4386 mLH2 gcat-1 min-1 using low catalyst loading of 1 mg. The effect of the reactant weight percentage of NaBH4 )0.2-3 wt.%) at room temperature was investigated. Thermal analysis of the hydrolysis process revealed that Cu-BTC MOF exhibits low activation energy of 41.7 kJ mol-1. The study investigated the recyclability of the catalyst and found that it could sustain catalytic hydrogen generation for up to four cycles without any noticeable decline in performance. This research demonstrated that Cu(BTC) is an inexpensive, efficient, and reusable catalyst for generating hydrogen through hydride hydrolysis