Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis and Simulation of Glioblastoma Cell Lines-Derived Extracellular Vesicles Metabolome

Glioblastoma (GBM) is one of the most aggressive cancers of the central nervous system. Despite current advances in non-invasive imaging and the advent of novel therapeutic modalities, patient survival remains very low. There is a critical need for the development of effective biomarkers for GBM diagnosis and therapeutic monitoring. Extracellular vesicles (EVs) produced by GBM tumors have been shown to play an important role in cellular communication and modulation of the tumor microenvironment. As GBM-derived EVs contain specific “molecular signatures” of their parental cells and are able to transmigrate across the blood–brain barrier into biofluids such as the blood and cerebrospinal fluid (CSF), they are considered as a valuable source of potential diagnostic biomarkers. Given the relatively harsh extracellular environment of blood and CSF, EVs have to endure and adapt to different conditions. The ability of EVs to adjust and function depends on their lipid bilayer, metabolic content and enzymes and transport proteins. The knowledge of EVs metabolic characteristics and adaptability is essential for their utilization as diagnostic and therapeutic tools. The main aim of this study was to determine the metabolome of small EVs or exosomes derived from different GBM cells and compare to the metabolic profile of their parental cells using NMR spectroscopy. In addition, a possible flux of metabolic processes in GBM-derived EVs was simulated using constraint-based modeling from published proteomics information. Our results showed a clear difference between the metabolic profiles of GBM cells, EVs and media. Machine learning analysis of EV metabolomics, as well as flux simulation, supports the notion of active metabolism within EVs, including enzymatic reactions and the transfer of metabolites through the EV membrane. These results are discussed in the context of novel GBM diagnostics and therapeutic monitoring.
Mendelian randomisation analysis of circulating adipokines and C‐reactive protein on breast cancer risk

Circulating adipokines and C‐reactive protein (CRP) have been linked to breast cancer risk in observational epidemiological studies. The causal nature of these associations is unclear because of the susceptibility of conventional observational designs to residual confounding, reverse causation and other forms of bias. Mendelian randomisation (MR) uses genetic variants as proxies for risk factors to strengthen causal inference in observational settings. We performed a MR analysis to evaluate the causal relevance of six previously reported circulating adipokines [adiponectin, hepatocyte growth factor (HGF), interleukin‐6, leptin receptor, plasminogen activator inhibitor‐1 and resistin] and CRP in risk of overall and oestrogen receptor‐stratified breast cancer in up to 122,977 cases and 105,974 controls of European ancestry. Genetic instruments were constructed from single‐nucleotide polymorphisms robustly (p < 5 × 10−8) associated with risk factors in genome‐wide association studies. Colocalisation was performed as a sensitivity analysis to examine whether findings reflected shared causal variants or genomic confounding. In MR analyses, there was evidence for an association of HGF with oestrogen receptor‐negative cancer (odds ratio per standard deviation increase: 1.17, 95% confidence interval: 1.01–1.35; p = 0.035) but little evidence for associations of other adipokines or CRP with overall or oestrogen receptor‐stratified breast cancer. Colocalisation analysis suggested that the association of HGF with oestrogen receptor‐negative breast cancer was unlikely to reflect a causal association. Collectively, these findings do not support an important aetiological role of various adipokines or CRP in overall or oestrogen receptor‐specific breast cancer risk.
Neighborhood Walkability and Overweight/Obese Weight Status Among Latino Adults

Purpose: To examine whether aerobic physical activity mediates the association between neighborhood walkability and overweight/obesity weight status among Latino adults and whether the relative contribution of this pathway linking neighborhood walkability and aerobic activity varies by level of neighborhood social cohesion. Design: Cross-sectional. Setting: National Health Interview Survey (NHIS) 2015. Sample: NHIS adult Latino participants ≥18 years of age (n = 4303). Measures: Neighborhood walkability, neighborhood social cohesion, body mass index, and aerobic physical activity. Analysis: To determine whether physical activity mediates the relationship of walkability with overweight/obese weight status, a simple mediation analysis was conducted. Additionally, a moderated mediation analysis was conducted to test whether neighborhood social cohesion had a moderating effect on this relationship. Results: On average, the sample was 41 years old, 51% were male, 34% had less than a high school education, and 57% were foreign-born. Neighborhood walkability was statistically significantly related to overweight/obese weight status (standardized effect= −0.05, standard error [SE] = 0.02, P = .01). The interaction between walkability and neighborhood social cohesion on physical activity was not significant (standardized effect = 0.06, SE = 0.03, P = .09). Thus, the indirect effect of walkability on overweight/obesity weight status through physical activity was not shown to be modified by neighborhood social cohesion. Conclusion: Other neighborhood environment factors may play a role in the contribution of neighborhood walkability to overweight/obese weight status among Latinos.
The pharmacology course for preclinical students using team-based learning

Purpose A pharmacology course in undergraduate medical education aims to enable students to cultivate the ability of applying drugs in the clinical context using basic scientific knowledge. Although team-based learning could be a useful approach, the literature on pharmacology education using team-based learning is limited. This study aims to evaluate the effectiveness of a pharmacology course using team-based learning. Methods We developed an “integrated clinical pharmacology” course for first-year medical students. All 49 students enrolled in the course. Individual and group scores were recorded for each session, and a post-course survey was conducted after the course. We compared the performance of the current class to that of a previous class based on scores in a nationwide test conducted at the end of every year. Results The reactions of the students were generally positive, with the exception of their perception of the preparatory burdens for the individual test. Throughout the team-based learning sessions, the achievement at the group level was significantly higher than at the individual level. In the nationwide test, however, when we divided students into high and low achiever groups, only the low achievers demonstrated significant improvement compared to the cohort from the previous year. Conclusion The study demonstrates that team-based learning could be an effective way of teaching pharmacology to medical students in the preclinical stage. Although most of the students were actively engaged regardless of their preparedness, low-achieving students in particular seemed to gain more benefits than high achievers regarding the acquisition of knowledge.
Optimization Method for Forecasting Confirmed Cases of COVID-19 in China

In December 2019, a novel coronavirus, called COVID-19, was discovered in Wuhan, China, and has spread to different cities in China as well as to 24 other countries. The number of confirmed cases is increasing daily and reached 34,598 on 8 February 2020. In the current study, we present a new forecasting model to estimate and forecast the number of confirmed cases of COVID-19 in the upcoming ten days based on the previously confirmed cases recorded in China. The proposed model is an improved adaptive neuro-fuzzy inference system (ANFIS) using an enhanced flower pollination algorithm (FPA) by using the salp swarm algorithm (SSA). In general, SSA is employed to improve FPA to avoid its drawbacks (i.e., getting trapped at the local optima). The main idea of the proposed model, called FPASSA-ANFIS, is to improve the performance of ANFIS by determining the parameters of ANFIS using FPASSA. The FPASSA-ANFIS model is evaluated using the World Health Organization (WHO) official data of the outbreak of the COVID-19 to forecast the confirmed cases of the upcoming ten days. More so, the FPASSA-ANFIS model is compared to several existing models, and it showed better performance in terms of Mean Absolute Percentage Error (MAPE), Root Mean Squared Relative Error (RMSRE), Root Mean Squared Relative Error (RMSRE), coefficient of determination (R2), and computing time. Furthermore, we tested the proposed model using two different datasets of weekly influenza confirmed cases in two countries, namely the USA and China. The outcomes also showed good performances.
Availability, cost and affordability of essential cardiovascular disease medicines in the south west region of Cameroon: Preliminary findings from the Cameroon science for disease study

Background More than 80% of premature deaths due to cardiovascular disease (CVD) occur in low- and middle-income countries. However, access to, and affordability of medications remain a challenge in these countries. Objective To assess the availability, cost and affordability of essential cardiovascular medicines in the South West region of Cameroon. Methods In an audit of 63 medicine outlets, twenty-six essential medicines were surveyed using the World Health Organisation (WHO) /Health Action International methodology. Availability, costs and the ratio of the median price to the international reference price were evaluated in public, confessional, private facility medicine outlets, and community pharmacies. Affordability was assessed by calculating the number of days’ wages it will cost the lowest-paid unskilled government worker to purchase a month worth of chronic treatment. Findings Availability ranged from 25.3% (public facility outlets) to 49.2% (community pharmacies) for all medicines. This was higher in urban and semi-urban compared to rural outlets. Cost of medicines was highest in community pharmacies and lowest in public facility outlets. Aspirin, digoxin, furosemide, hydrochlorothiazide and nifedipine were affordable (cost a day’s wage or less). Medicines for heart failure and dyslipidaemia (beta blockers, angiotensin converting enzyme inhibitors and statins) required 2–5 days and 6–13 days wages respectively for one month of chronic treatment. Conclusion Overall availability of CVD essential medicines was lower than WHO recommendations, and medicines were largely unaffordable. While primary prevention is pivotal, improving availability and affordability of medicines especially for public facilities would provide additional benefit in curbing the CVD burden.
Workshop on the Development and Evaluation of Digital Therapeutics for Health Behavior Change: Science, Methods, and Projects

The health care field has integrated advances into digital technology at an accelerating pace to improve health behavior, health care delivery, and cost-effectiveness of care. The realm of behavioral science has embraced this evolution of digital health, allowing for an exciting roadmap for advancing care by addressing the many challenges to the field via technological innovations. Digital therapeutics offer the potential to extend the reach of effective interventions at reduced cost and patient burden and to increase the potency of existing interventions. Intervention models have included the use of digital tools as supplements to standard care models, as tools that can replace a portion of treatment as usual, or as stand-alone tools accessed outside of care settings or direct to the consumer. To advance the potential public health impact of this promising line of research, multiple areas warrant further development and investigation. The Center for Technology and Behavioral Health (CTBH), a P30 Center of Excellence supported by the National Institute on Drug Abuse at the National Institutes of Health, is an interdisciplinary research center at Dartmouth College focused on the goal of harnessing existing and emerging technologies to effectively develop and deliver evidence-based interventions for substance use and co-occurring disorders. The CTBH launched a series of workshops to encourage and expand multidisciplinary collaborations among Dartmouth scientists and international CTBH affiliates engaged in research related to digital technology and behavioral health (eg, addiction science, behavioral health intervention, technology development, computer science and engineering, digital security, health economics, and implementation science). This paper summarizes a workshop conducted on the Development and Evaluation of Digital Therapeutics for Behavior Change, which addressed (1) principles of behavior change, (2) methods of identifying and testing the underlying mechanisms of behavior change, (3) conceptual frameworks for optimizing applications for mental health and addictive behavior, and (4) the diversity of experimental methods and designs that are essential to the successful development and testing of digital therapeutics. Examples were presented of ongoing CTBH projects focused on identifying and improving the measurement of health behavior change mechanisms and the development and evaluation of digital therapeutics. In summary, the workshop showcased the myriad research targets that will be instrumental in promoting and accelerating progress in the field of digital health and health behavior change and illustrated how the CTBH provides a model of multidisciplinary leadership and collaboration that can facilitate innovative, science-based efforts to address the health behavior challenges afflicting our communities.
Risk of coronary heart disease in the rural population in Xinjiang: A nested case-control study in China

Background and aim Coronary heart disease (CHD) is a chronic complex disease caused by a combination of factors such as lifestyle behaviors and environmental and genetic factors. We conducted this study to evaluate the risk factors affecting the development of CHD in Xinjiang, and to obtain valuable information for formulating appropriate local public health policies. Method We conducted a nested case-control study with 277 confirmed CHD cases and 554 matched controls. The association of the risk factors with the risk of CHD was assessed using the multivariate Cox proportional hazard model. Multiplicative interactions were evaluated by entering interaction terms in the Cox proportional hazard model. The additive interactions among the risk factors were assessed by the index of additive interaction. Results The risk of CHD increased with frequent high-fat food consumption, dyslipidemia, obesity, and family history of CHD after adjustment for drinking, smoking status, hypertension, diabetes, family history of hypertension, and family history of diabetes. We noted consistent interactions between family history of CHD and frequent high-fat food consumption, family history of CHD and obesity, frequent high-fat food consumption and obesity, frequent high-fat food consumption and dyslipidemia, and obesity and dyslipidemia. The risk of CHD events increased with the presence of the aforementioned interactions. Conclusions Frequent high-fat food consumption, family history of CHD, dyslipidemia and obesity were independent risk factors for CHD, and their interactions are important for public health interventions in patients with CHD in Xinjiang.
Maintenance therapy with ex vivo expanded lymphokine‐activated killer cells and rituximab in patients with follicular lymphoma is safe and may delay disease progression

Anti‐cluster of differentiation 20 (CD20) monoclonal antibodies (mAbs) have shown promise in follicular lymphoma (FL) as post‐induction therapy, by enhancing antibody‐dependent cellular cytotoxicity (ADCC). However, cytotoxic cells are reduced after this treatment. We hypothesised that ex vivo expanded lymphokine‐activated killer (LAK) cells administered to FL‐remission patients are safe and improve anti‐CD20 efficacy. This open, prospective, phase II, single‐arm study assessed safety and efficacy of ex vivo expanded LAK cells in 20 FL‐remission patients following rituximab maintenance. Mononuclear cells were obtained in odd rituximab cycles and stimulated with interleukin 2 (IL‐2) for 8 weeks, after which >5 × 108 LAK cells were injected. Patients were followed‐up for 5 years. At the end of maintenance, peripheral blood cells phenotype had not changed markedly. Natural killer, LAK and ADCC activities of mononuclear cells increased significantly after recombinant human IL‐2 (rhIL‐2) stimulation in all cycles. Rituximab significantly enhanced cytotoxic activity. No patients discontinued treatment. There were no treatment‐related serious adverse events. Three patients had progressed by the end of follow‐up. After a median (interquartile range) follow‐up of 59.4 (43.8–70.9) months, 85% of patients remained progression free. No deaths occurred. Quality‐of‐life improved throughout the study. Post‐induction LAK cells with rituximab seem safe in the long term. Larger studies are warranted to confirm efficacy.
Tenascin C in the Tumor-Nerve Microenvironment Enhances Perineural Invasion and Correlates With Locoregional Recurrence in Pancreatic Ductal Adenocarcinoma

Supplemental digital content is available in the text. Objectives Perineural invasion is common in pancreatic ductal adenocarcinoma (PDAC) and worsens the postoperative prognosis. Tenascin C (TNC), an extracellular matrix glycoprotein, modulates tumor progression. We evaluated the functional roles of TNC, especially in perineural invasion of PDAC. Methods We examined immunohistochemical TNC expression in 78 resected PDAC specimens. The relationships between TNC expression and clinicopathological features were retrospectively analyzed. Interactions between cancer cells and nerves with TNC supplementation were investigated using an in vitro coculture model with PDAC cell line and mouse dorsal root ganglion (DRG). Results Tenascin C expression was predominant in perineural sites at the invasive tumor front. High perineural TNC expression in 30 patients (38%) was associated with perineural invasion, pathological T stage ≥3, and postoperative locoregional recurrence. High TNC expression was independently associated with postoperative, poor recurrence-free survival by multivariate analysis. In the in vitro coculture model, a TNC-rich matrix enhanced both PDAC cell colony extensions toward nerves and DRG axonal outgrowth toward cancer cell colonies, whereas TNC did not affect axonal outgrowth or cancer cell proliferation in separately cultured DRG and PDAC cells. Conclusions Strong perineural TNC expression indicated poor prognosis with locoregional recurrence. The neurotropism of TNC-induced PDAC suggests that TNC is a potential PDAC therapeutic target.
Targeting Mitochondrial Apoptosis to Overcome Treatment Resistance in Cancer

Deregulated cellular apoptosis is a hallmark of cancer and chemotherapy resistance. The B-cell lymphoma 2 (BCL-2) protein family members are sentinel molecules that regulate the mitochondrial apoptosis machinery and arbitrate cell fate through a delicate balance between pro- and anti-apoptotic factors. The recognition of the anti-apoptotic BCL2 gene as an oncogenic driver in hematological malignancies has directed attention toward unraveling the biological significance of each of the BCL-2 superfamily members in cancer progression and garnered interest in the targeting of apoptosis in cancer therapy. Accordingly, the approval of venetoclax (ABT-199), a small molecule BCL-2 inhibitor, in patients with chronic lymphocytic leukemia and acute myeloid leukemia has become the proverbial torchbearer for novel candidate drug approaches selectively targeting the BCL-2 superfamily. Despite the inspiring advances in this field, much remains to be learned regarding the optimal therapeutic context for BCL-2 targeting. Functional assays, such as through BH3 profiling, may facilitate prediction of treatment response, development of drug resistance and shed light on rational combinations of BCL-2 inhibitors with other branches of cancer therapy. This review summarizes the pathological roles of the BCL-2 family members in cancer, discusses the current landscape of their targeting in clinical practice, and highlights the potential for future therapeutic inroads in this important area.
Dental and craniofacial defects in the Crtap−/− mouse model of osteogenesis imperfecta type VII

Inactivating mutations in the gene for cartilage‐associated protein (CRTAP) cause osteogenesis imperfecta type VII in humans, with a phenotype that can include craniofacial defects. Dental and craniofacial manifestations have not been a focus of case reports to date. We analyzed the craniofacial and dental phenotype of Crtap−/− mice by skull measurements, micro‐computed tomography (micro‐CT), histology, and immunohistochemistry.
Trends in Internet Use Among Older Adults in the United States, 2011–2016

The present study examined the trends in internet use among older adults (60+ years) in the United States from 2011 to 2016 by considering not only the entire study sample as a whole but also specific subgroups by age, gender, race/ethnicity, and education. Using data from 107,500 older adults in the California Health Interview Survey between 2011 and 2016, the significance of linear trends was tested by including the survey year as a continuous variable in the logistic regression. Findings confirm the general knowledge that an increased number of the older U.S. population used the internet over the period of 2011–2016. Furthermore, closer inspection indicates that this upward trend does not apply to all, but specifically to those with advanced age, male gender, racial/ethnic minority background, and low educational attainment. Findings provide implications for identifying and prioritizing a target group for internet technology training.
Clinical and Epidemiological Characteristics of Diabetic Ketoacidosis in Older Adults

Much of the research previously done on diabetic ketoacidosis (DKA) was based on a young population with type 1 diabetes mellitus (type 1 DM). But substantial numbers of DKA episodes occur in patients with a prior history of type 2 diabetes mellitus (type 2 DM). There is a lack of Data are lacking about DKA in older adults. The aims of this study were to analyze the clinical characteristics and outcomes of older adult patients with DKA.