The modified model showed significant improvements in the prediction of benzofuran and dibenzofuran formation. Based on the rate of production and sensitivity analysis using the modified model, the dominant reaction pathways of benzofuran and dibenzofuran were investigated.In this study, we report a simple and economic one-pot synthesis of magnetite (Fe3O4) nanostructure and its modification with tetraethyl orthosilicate by coprecipitation method. The synthesized (Fe3O4@SiO2) nano sorbent was applied for enhanced adsorptive removal of methylene blue by ultrasonic wave driven batch experiments. After successful synthesis, the nanostructure was characterized for their physical structure by FT-IR, VSM, TEM, and XRD. For the maximum adsorptive performance of nano sorbent, various parameters were optimized, such as dose, pH, time, concentration, and temperature. The adsorption mechanism was best fitted by Langmuir isotherm with a maximum capacity of 148.69 mg/g, while kinetics best fitted by pseudo-second-order kinetic. The synthesized nano sorbent was successfully applied for enhanced adsorptive removal of toxic methylene blue from aqueous media. The proposed method is promising and effective in terms of simplicity, cost operation, green energy consumption, reproducible, excellent reusability, and magnetically separability with fast kinetic.
  The COVID-19 lockdown interrupted normal daily activities, which may have led to an increase in sedentary behavior (Castelnuovo et al., 2020). The aim of this study was to investigate the effect of the COVID-19 pandemic on the level of physical activity among Swiss office workers.
 
  Office workers from two Swiss organizations, aged 18-65 years, were included. Baseline data from January 2020 before the COVID-19 pandemic became effective in Switzerland were compared with follow-up data during the lockdown phase in April 2020. Levels of physical activity were assessed using the International Physical Activity Questionnaire. Paired sample 
  -tests or Wilcoxon signed-rank test were performed for statistical analysis.
 
  Data from 76 participants were analyzed. Fifty-four participants were female (71.1%).  https://www.selleckchem.com/products/bevacizumab.html  The mean age was 42.7 years (range from 21.8 to 62.7) at baseline. About 75% of the participants met the recommendations on minimal physical activity, both before the COVID-19 pandemic and during the lockdown. We/clinicaltrials.gov/ct2/show/NCT04169646.
 www.ClinicalTrials.gov, NCT04169646. Registered 15 November 2019 - Retrospectively registered, https//clinicaltrials.gov/ct2/show/NCT04169646.[This corrects the article DOI 10.1136/bmjno-2020-000054.].
  Heart failure (HF) together with type 2 diabetes (T2D) and chronic kidney disease (CKD) are major pandemics of the twenty first century. It is not known in people with new onset HF, what the distinct and combined associations are between T2D and CKD comorbidities and cause-specific hospital admissions and death, over the past 20 years.
 
  An observational study using the UK Clinical Practice Research Datalink linked to the Hospital Episode Statistics in England (1998-2017). Participants were people aged ≥30 years with new onset HF. Exposure groups were HF with (i) no T2D and no CKD (reference group); (ii) CKD-only (estimated glomerular filtration rate (eGFR) <60 ml/min per 1.73m
  ); (iii) T2D-only; (iv) T2D and CKD. CKD severity groups were CKD-3a (eGFR 45-59); CKD-3b (30-44); CKD-4 (15-29); CKD-5 (<15). Outcomes were cardiovascular and non-cardiovascular hospitalisations and all-cause death.
 
  In 87,709 HF patients (mean age, 78 years; 49% female), 40% had CKD-only, 12% T2D-only, and 16% both. Age-staIn a cohort of people with new onset HF, hospitalisations and deaths are high in patients with T2D or CKD, and worst in those with both comorbidities. Whilst outcomes have improved over time for patients with HF and comorbid T2D, similar trends were not seen in those with comorbid CKD. Strategies to prevent and manage CKD in people with HF are urgently needed.
 
  NIHR fellowship [reference NIHR 30011].
 NIHR fellowship [reference NIHR 30011].[This corrects the article DOI 10.1136/bmjno-2020-000054.].The water scavenger beetle genus Tobochares Short & García, 2007 currently contains ten species, including one known but formally undescribed taxon. Although Tobochares was revised in 2017, ongoing fieldwork as well as an expanded concept of the genus has led to the recognition of numerous additional species. Here a combination of morphological and molecular data is presented to review this newly found Tobochares diversity. Fifteen new species are described from South America, bringing the total number of known species to 25 Tobochares akoeriosp. nov. (Suriname), T. arawaksp. nov. (Guyana), T. anthonyaesp. nov. (Venezuela Bolívar), T. aturessp. nov., (Venezuela Amazonas), T. benettiisp. nov. (Brazil Amazonas), T. canaimasp. nov. (Venezuela Bolívar), T. communissp. nov. (Brazil Amapá and Roraima, Guyana, Suriname, Venezuela Bolívar), T. fusussp. nov. (Brazil Amapá, French Guiana), T. goiassp. nov. (Brazil Goiás), T. kappelsp. nov. (Suriname), T. kolokoesp. nov. (Suriname), T. luteomargosp. nov. (Venezuela Bolíthe genus Quadriops Hansen, 1999. High-resolution images of most species are included, as well as a key to species groups, species, and habitat photographs.
  Mental illness and substance use are prevalent among people living with HIV and often lead to poor health outcomes. Electronic medical record (EMR) data are increasingly being utilized for HIV-related clinical research and care, but mental illness and substance use are often underdocumented in structured EMR fields. Natural language processing (NLP) of unstructured text of clinical notes in the EMR may more accurately identify mental illness and substance use among people living with HIV than structured EMR fields alone.
 
  The aim of this study was to utilize NLP of clinical notes to detect mental illness and substance use among people living with HIV and to determine how often these factors are documented in structured EMR fields.
 
  We collected both structured EMR data (diagnosis codes, social history, Problem List) as well as the unstructured text of clinical HIV care notes for adults living with HIV. We developed NLP algorithms to identify words and phrases associated with mental illness and substance use in the clinical notes.