bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Donepezil and Medroxyprogesterone Versus Placebo on Weaning in Adult Patients With Non-Pulmonary Etiologies Receiving Invasive Mechanical Ventilation: A triple‐blind Randomized Clinical Trial
Authors: Alizadeh Zahra , Sahebnasagh Adeleh , Hadadzadegan Navid , Mohammadi Farhad , Saghafi Fatemeh 
Published: December 2021

Background: Medroxyprogesterone and donepezil could be used as respiratory stimulants in ventilated patients. However, no randomized placebo-controlled trial is available to confirm this approach and compare these drugs. The aim of the current study was to evaluate the effects of donepezil or medroxyprogesterone compared to the placebo in improvement in respiratory status and weaning facilitation in critically ill adult patients receiving mechanical ventilation.Material and Methods: This randomized, triple-blind trial was conducted on 78 ventilated patients in intensive care units (ICU). Patients who were intubated due to pulmonary disorders were ruled out. Patients were randomized in a 1:1:1 ratio to receive 5 mg donepezil (n = 23) or 5 mg medroxyprogesterone (n = 26), or placebo (n = 24) twice a day until weaning (maximum 10 days). The primary endpoints were weaning duration, and duration of invasive mechanical ventilation. Secondary endpoints included rate of successful weaning, changes in arterial blood gas (ABG) parameters, GCS and sequential organ failure assessment (SOFA) score, hemoglobin (Hgb), ICU-mortality, and duration of ICU stay, were measured before and after the intervention and if successful weaning was recorded.Results: Of 78 studied patients who were randomized, 59 weaned successfully. 87% patients in donepezil and 88.5% patients in medroxyprogesterone groups were successfully weaned compared to 66.7% patients in the placebo group. However, this difference was not statistically significant (p-Value = 0.111). Changes in pH, mean duration of intubation, and weaning duration were statistically different in donepezil compared with the control group (p-Value &lt; 0.05). No significant difference in ABG, Hgb, GCS and SOFA score, and duration of intubation were seen in the medroxyprogesterone group, but weaning duration was significantly reduced to 1.429 days compared with the control group (p-Value = 0.038).Conclusion: The results of this clinical trial have demonstrated that the administered dose of medroxyprogesterone and donepezil can expedite the weaning process by reducing the weaning duration compared to placebo. Furthermore, the total duration of invasive ventilation was significantly lower in the donepezil group compared to the control group. Future clinical trials with a larger sample size will determine the exact role of medroxyprogesterone and donepezil in mechanically ventilated patients.Clinical Trial Registration:https://irct.ir/IRCT20190810044500N2 (April 1, 2020).
Protective Effects and Mechanisms of Polyethylene Glycol Loxenatide Against Hyperglycemia and Liver Injury in db/db diabetic Mice
Authors: Zhang Yu , Li Yufeng , Zhao Junjun , Wang Cong , Deng Bin , Zhang Qilin , Shi Chen 
Published: December 2021

Background: Type 2 diabetes mellitus (T2DM) is a metabolic disorder with insulin resistance and impaired insulin secretion that can cause complications, including liver injury. Polyethylene glycol loxenatide (PEG-Loxe), a glucagon-like peptide-1 (GLP-1) analog, is widely used to treat T2DM. However, its specific glucose-lowering and hepatoprotective mechanisms of action have not been established yet.METHODS: Using a high glucose-induced hepatocyte injury model and a type 2 diabetic db/db mouse model, we assessed PEG-Loxe’s impact on reducing blood glucose and improving liver injury in T2DM and revealed its mechanism.RESULTS: PEG-Loxe treatment significantly reduced body weight and fasting glucose, increased glucose tolerance, improved serum and liver biochemical parameters (glycated hemoglobin, serum insulin, triglycerides, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, alanine aminotransferase, and aspartate aminotransferase), and attenuated hepatic steatosis and liver and pancreatic tissue damages in db/db mice. Additionally, PEG-Loxe considerably inhibited oxidative stress, decreased pro-inflammatory factor (TNF-α, IL-6, and MCP-1) levels, and increased anti-inflammatory factor IL-10 levels. PEG-Loxe possibly inhibits hepatic lipid synthesis, oxidative stress, and inflammatory response by upregulating Sirt1, p-AMPK, and p-ACC expressions in the Sirt1/AMPK/ACC pathway of lipid metabolism, thereby improving T2DM liver injury. PEG-Loxe most likely also promotes GLP-1R expression by inhibiting β-cell apoptosis, which in turn activates the insulin PI3K/AKT pathway to promote insulin synthesis and secretion, thereby exerting hypoglycemic effects. In vitro cellular experiments further confirmed that PEG-Loxe possibly exerts hypoglycemic effects by activating the insulin PI3K/AKT pathway.Conclusion: PEG-Loxe improved liver injury in T2DM probably by activating Sirt1/AMPK/ACC lipid metabolism pathway, and exerted hypoglycemic effects through activation of insulin PI3K/AKT pathway.
Artificial Intelligence-Driven Algorithm for Drug Effect Prediction on Atrial Fibrillation: An in silico Population of Models Approach
Authors: Sanchez de la Nava Ana Maria , Arenal Ángel , Fernández-Avilés Francisco , Atienza Felipe 
Published: December 2021

Background: Antiarrhythmic drugs are the first-line treatment for atrial fibrillation (AF), but their effect is highly dependent on the characteristics of the patient. Moreover, anatomical variability, and specifically atrial size, have also a strong influence on AF recurrence.Objective: We performed a proof-of-concept study using artificial intelligence (AI) that enabled us to identify proarrhythmic profiles based on pattern identification from in silico simulations.Methods: A population of models consisting of 127 electrophysiological profiles with a variation of nine electrophysiological variables (GNa, INaK, GK1, GCaL, GKur, IKCa, [Na]ext, and [K]ext and diffusion) was simulated using the Koivumaki atrial model on square planes corresponding to a normal (16 cm2) and dilated (22.5 cm2) atrium. The simple pore channel equation was used for drug implementation including three drugs (isoproterenol, flecainide, and verapamil). We analyzed the effect of every ionic channel combination to evaluate arrhythmia induction. A Random Forest algorithm was trained using the population of models and AF inducibility as input and output, respectively. The algorithm was trained with 80% of the data (N = 832) and 20% of the data was used for testing with a k-fold cross-validation (k = 5).Results: We found two electrophysiological patterns derived from the AI algorithm that was associated with proarrhythmic behavior in most of the profiles, where GK1 was identified as the most important current for classifying the proarrhythmicity of a given profile. Additionally, we found different effects of the drugs depending on the electrophysiological profile and a higher tendency of the dilated tissue to fibrillate (Small tissue: 80 profiles vs Dilated tissue: 87 profiles).Conclusion: Artificial intelligence algorithms appear as a novel tool for electrophysiological pattern identification and analysis of the effect of antiarrhythmic drugs on a heterogeneous population of patients with AF.
The Effects of a Mindfulness Program on Mental Health in Students at an Undergraduate Program for Teacher Education: A Randomized Controlled Trial in Real-Life
Authors: Juul Lise , Brorsen Eva , Gøtzsche Katinka , Nielsen Birgitte Lund , Fjorback Lone Overby 
Published: December 2021

Background: In this study, we aimed to investigate the effects of a mindfulness program including Mindfulness-Based Stress Reduction (MBSR) on the mental health of student teachers when offered at their educational institution in a real-life context.Methods: A parallel randomized controlled trial (RCT) was conducted among self-selected student teachers at a Danish undergraduate program for teacher education in the autumns of 2019 and 2020. Participation was not recommended in case of (1) clinical depression or a diagnosis of psychosis or schizophrenia, (2) abuse of alcohol, drugs, and/or medicine. Randomization was performed by a Statistician who was blinded to the identity of the students. Data was collected using self-reported questionnaires. The primary outcome was a change in perceived stress 3 months from baseline. Secondary outcome measures were symptoms of anxiety and depression, well-being, resilience, mindfulness, and thoughts and feelings during rest. The effects were analyzed according to the intention-to-treat principle using mixed-effect linear regression models. Mediating effects of mindfulness skills on the mental health outcomes were explored using structural equation modeling.Results: The study group included 67 student teachers with 34 allocated to the intervention group (median age: 25 years; women: n = 24, 71%); and 33 students (median age: 25 years; women: n = 25, 76%) allocated to a waiting list control group. At baseline, mean Perceived Stress Scale (PSS) scores were 18.88 (SD: 5.75) in the intervention group and 17.91 (SD: 6.36) in the waiting list control group. A total of 56 students completed the questionnaire at a 3-month follow-up (28 in both the intervention- and the control group). Statistically significant effects of the intervention were found on perceived stress, symptoms of anxiety and depression, well-being, and on three of seven resting-state dimensions. No effects were found on resilience or mindfulness. Statistically significant mediated effects via resting-state dimensions were found.Conclusion The findings suggested that offering a mindfulness program at an undergraduate program for teacher education could significantly improve the mental health among self-selected students within 3 months. Results of mediation analysis supported the hypothesis that some of the effects might be explained by reduced distracting thoughts.Clinical Trial Registration: [www.ClinicalTrials.gov], identifier [NCT04558099].
Digital Interventions for Generalized Anxiety Disorder (GAD): Systematic Review and Network Meta-Analysis
Authors: Saramago Pedro , Gega Lina , Marshall David , Nikolaidis Georgios F. , Jankovic Dina , Melton Hollie , Dawson Sarah , Churchill Rachel , Bojke Laura 
Published: December 2021

Background: Generalized anxiety disorder is the most common mental health condition based on weekly prevalence. Digital interventions have been used as alternatives or as supplements to conventional therapies to improve access, patient choice, and clinical outcomes. Little is known about their comparative effectiveness for generalized anxiety disorder.Methods: We conducted a systematic review and network meta-analysis of randomized controlled trials comparing digital interventions with medication, non-digital interventions, non-therapeutic controls, and no intervention.Results: We included 21 randomized controlled trials with a total of 2,350 participants from generalized anxiety disorder populations. Pooled outcomes using analysis of Covariance and rankograms based on the surface under the cumulative ranking curves indicated that antidepressant medication and group therapy had a higher probability than digital interventions of being the “best” intervention. Supported digital interventions were not necessarily “better” than unsupported (pure self-help) ones.Conclusions: Due to very wide confidence intervals, network meta-analysis results were inconclusive as to whether digital interventions are better than no intervention and non-therapeutic active controls, or whether they confer an additional benefit to standard therapy. Future research needs to compare digital interventions with one-to-one therapy and with manualized non-digital self-help and to include antidepressant medication as a treatment comparator and effect modifier.
Peri-Traumatic Distress and Its Relationship to Resilience and Coping Among Medical Students in Malaysia During COVID-19 Lockdown
Authors: Mohamed Salina , Ismail Zaliha , Shuib Norley , Ali Nur Faizah 
Published: December 2021

Background: Medical students are not spared from the challenges related to the Covid-19 lockdown. The fear and uncertainties may lead to traumatic symptoms and test their resilience and sense of coping. Thus, this study aims to determine the prevalence of peri-traumatic distress symptoms and its association with the level of resilience and the coping strategies used during the lockdown among medical students.Materials and Methods: This was a cross-sectional online questionnaire survey involving medical students from a public university in Malaysia. It was conducted during the COVID-19 lockdown or Movement Control Order (MCO) where the students were asked to fill in the COVID-19 Peri-traumatic Distress Index (CPDI), Brief COPE Inventory, and Connor Davidson Resilience Scale (CDRS-25).Results: A total of 282 clinical and 172 pre-clinical medical students were involved. Peri-traumatic distress symptoms were reported by 27% out of the total students. This study found that those who were having peritraumatic distress symptoms were from the pre-clinical years, had poor internet access, as well as lower resilience levels, and used more dysfunctional coping strategies. Pre-clinical medical students with difficult internet access were eight times more likely to have peritraumatic distress symptoms.Conclusions: Given the high level of peri-traumatic distress symptoms reported by medical students during the lockdown, it is vital to identify the vulnerable students, assess their needs and risks to mental health problems during this challenging time as the pandemic is still ongoing with countries going in and out of lockdown depending on the cases at the time. The university administration for each University in Malaysia will need to have a clear academic guideline and policy as well as providing improved infrastructure to minimize the distress faced by medical students.
Perception of Law Enforcement Officers on Preventing Road Traffic Injury in Vanuatu: A Qualitative Study
Authors: Fanai Saen , Mohammadnezhad Masoud , Salusalu Mosese 
Published: December 2021

Background: Road Traffic Injuries (RTIs) cause approximately 1. 35 million deaths annually, and is the leading cause of death among people between ages 5 and 29. Law Enforcement Officers (LEOs) deal with Road Traffic Collisions (RTCs) and have contact with RTI victims at a daily basis, they possess an excellent perspective on preventing RTI. This study aimed to explore LEOs perceptions on risk factors and preventive measures of RTI in Vanuatu.Methods: This study employed qualitative methods that used Focus Group Discussions (FGDs) to gather data from 25 LEOs between October 14th and November 30th, 2020. Self-identified Ni-Vanuatu LEOs who have been serving for over 6 months and residing at the study setting were included in this study. Purposive sampling was used to recruit study participants from three municipalities in Vanuatu. A semi-structured open ended questionnaire was designed to guide the FGDs. Data obtained were sorted out using thematic analysis processed with some preconceived themes based on theory, and also allowing the data to determine new themes.Results: Data saturation was reached from conducting 5 FGDs with 25 LEOs who were traffic officers and municipal wardens. Five main themes and sixteen subthemes were generated from the study. The main themes include driving and alcohol, the challenges to effective enforcement, barriers to effective care and support for RTI victims, measures for road traffic control and promoting road traffic safety. The respondents perceived that addressing resources issues and the legislations on road traffic control act and vehicle regulation act will enhance prevention of RTI.Conclusion: This study explored the risk factors of RTI and the barriers to effectively prevent RTI in Vanuatu. The study also generated suggestions of a combination of road traffic control measures that could be implemented to prevent RTI. Future research should look at effective strategies of preventing RTIs in resource deficit settings.
Lefamulin in Patients with Community-Acquired Bacterial Pneumonia Caused by Atypical Respiratory Pathogens: Pooled Results from Two Phase 3 Trials
Authors: Paukner Susanne , Mariano David , Das Anita F. , Moran Gregory J. , Sandrock Christian , Waites Ken B. , File Thomas M. 
Published: December 2021

Lefamulin was the first systemic pleuromutilin antibiotic approved for intravenous and oral use in adults with community-acquired bacterial pneumonia based on two phase 3 trials (Lefamulin Evaluation Against Pneumonia [LEAP]-1 and LEAP-2). This pooled analysis evaluated lefamulin efficacy and safety in adults with community-acquired bacterial pneumonia caused by atypical pathogens (Mycoplasma pneumoniae, Legionella pneumophila, and Chlamydia pneumoniae). In LEAP-1, participants received intravenous lefamulin 150 mg every 12 h for 5–7 days or moxifloxacin 400 mg every 24 h for 7 days, with optional intravenous-to-oral switch. In LEAP-2, participants received oral lefamulin 600 mg every 12 h for 5 days or moxifloxacin 400 mg every 24 h for 7 days. Primary outcomes were early clinical response at 96 ± 24 h after first dose and investigator assessment of clinical response at test of cure (5–10 days after last dose). Atypical pathogens were identified in 25.0% (91/364) of lefamulin-treated patients and 25.2% (87/345) of moxifloxacin-treated patients; most were identified by ≥1 standard diagnostic modality (M. pneumoniae 71.2% [52/73]; L. pneumophila 96.9% [63/65]; C. pneumoniae 79.3% [46/58]); the most common standard diagnostic modality was serology. In terms of disease severity, more than 90% of patients had CURB-65 (confusion of new onset, blood urea nitrogen > 19 mg/dL, respiratory rate ≥ 30 breaths/min, blood pressure <90 mm Hg systolic or ≤60 mm Hg diastolic, and age ≥ 65 years) scores of 0–2; approximately 50% of patients had PORT (Pneumonia Outcomes Research Team) risk class of III, and the remaining patients were more likely to have PORT risk class of II or IV versus V. In patients with atypical pathogens, early clinical response (lefamulin 84.4–96.6%; moxifloxacin 90.3–96.8%) and investigator assessment of clinical response at test of cure (lefamulin 74.1–89.7%; moxifloxacin 74.2–97.1%) were high and similar between arms. Treatment-emergent adverse event rates were similar in the lefamulin (34.1% [31/91]) and moxifloxacin (32.2% [28/87]) groups. Limitations to this analysis include its post hoc nature, the small numbers of patients infected with atypical pathogens, the possibility of PCR-based diagnostic methods to identify non-etiologically relevant pathogens, and the possibility that these findings may not be generalizable to all patients. Lefamulin as short-course empiric monotherapy, including 5-day oral therapy, was well tolerated in adults with community-acquired bacterial pneumonia and demonstrated high clinical response rates against atypical pathogens.
A New Empirical Approach for Estimating Solar Insolation Using Air Temperature in Tropical and Mountainous Environments
Authors: Hoyos-Gomez Laura Sofía , Ruiz-Mendoza Belizza Janet 
Published: December 2021

Solar irradiance is an available resource that could support electrification in regions that are low on socio-economic indices. Therefore, it is increasingly important to understand the behavior of solar irradiance. and data on solar irradiance. Some locations, especially those with a low socio-economic population, do not have measured solar irradiance data, and if such information exists, it is not complete. There are different approaches for estimating solar irradiance, from learning models to empirical models. The latter has the advantage of low computational costs, allowing its wide use. Researchers estimate solar energy resources using information from other meteorological variables, such as temperature. However, there is no broad analysis of these techniques in tropical and mountainous environments. Therefore, in order to address this gap, our research analyzes the performance of three well-known empirical temperature-based models—Hargreaves and Samani, Bristol and Campbell, and Okundamiya and Nzeako—and proposes a new one for tropical and mountainous environments. The new empirical technique models daily solar irradiance in some areas better than the other three models. Statistical error comparison allows us to select the best model for each location and determines the data imputation model. Hargreaves and Samani’s model had better results in the Pacific zone with an average RMSE of 936,195 Wh/m2 day, SD of 36,01%, MAE of 748,435 Wh/m2 day, and U95 of 1.836,325 Wh/m2 day. The new proposed model showed better results in the Andean and Amazon zones with an average RMSE of 1.032,99 Wh/m2 day, SD of 34,455 Wh/m2 day, MAE of 825,46 Wh/m2 day, and U95 of 2.025,84 Wh/m2 day. Another result was the linear relationship between the new empirical model constants and the altitude of 2500 MASL (mean above sea level).
A Review of Quantifying pCO2 in Inland Waters with a Global Perspective: Challenges and Prospects of Implementing Remote Sensing Technology
Authors: Wen Zhidan , Shang Yingxin , Lyu Lili , Li Sijia , Tao Hui , Song Kaishan 
Published: December 2021

The traditional field-based measurements of carbon dioxide (pCO2) for inland waters are a snapshot of the conditions on a particular site, which might not adequately represent the pCO2 variation of the entire lake. However, these field measurements can be used in the pCO2 remote sensing modeling and verification. By focusing on inland waters (including lakes, reservoirs, rivers, and streams), this paper reviews the temporal and spatial variability of pCO2 based on published data. The results indicate the significant daily and seasonal variations in pCO2 in lakes. Rivers and streams contain higher pCO2 than lakes and reservoirs in the same climatic zone, and tropical waters typically exhibit higher pCO2 than temperate, boreal, and arctic waters. Due to the temporal and spatial variations of pCO2, it can differ in different inland water types in the same space-time. The estimation of CO2 fluxes in global inland waters showed large uncertainties with a range of 1.40–3.28 Pg C y−1. This paper also reviews existing remote sensing models/algorithms used for estimating pCO2 in sea and coastal waters and presents some perspectives and challenges of pCO2 estimation in inland waters using remote sensing for future studies. To overcome the uncertainties of pCO2 and CO2 emissions from inland waters at the global scale, more reliable and universal pCO2 remote sensing models/algorithms will be needed for mapping the long-term and large-scale pCO2 variations for inland waters. The development of inverse models based on dissolved biogeochemical processes and the machine learning algorithm based on measurement data might be more applicable over longer periods and across larger spatial scales. In addition, it should be noted that the remote sensing-retrieved pCO2/the CO2 concentration values are the instantaneous values at the satellite transit time. A major technical challenge is in the methodology to transform the retrieved pCO2 values on time scales from instant to days/months, which will need further investigations. Understanding the interrelated control and influence processes closely related to pCO2 in the inland waters (including the biological activities, physical mixing, a thermodynamic process, and the air–water gas exchange) is the key to achieving remote sensing models/algorithms of pCO2 in inland waters. This review should be useful for a general understanding of the role of inland waters in the global carbon cycle.