The NHS Diabetes Prevention Programme (NHS-DPP) has been delivered by four commercial organizations across England, to prevent people with impaired glucose tolerance developing Type 2 diabetes. Evidence reviews underpinning the NHS-DPP design specification identified 19 Behavior Change Techniques (BCTs) that are the intervention „active ingredients.” It is important to understand the discrepancies between BCTs specified in design and BCTs actually delivered.

To compare observed fidelity of delivery of BCTs that were delivered to (a) the NHS-DPP design specification, and (b) the programme manuals of four provider organizations.

Audio-recordings were made of complete delivery of NHS-DPP courses at eight diverse sites (two courses per provider organization). The eight courses consisted of 111 group sessions, with 409 patients and 35 facilitators. BCT Taxonomy v1 was used to reliably code the contents of NHS-DPP design specification documents, programme manuals for each provider organization, and observed Nals was relatively good. Future commissioning should focus on ensuring the evidence base is more accurately translated into the programme manual contents.Coronavirus disease 2019 (COVID-19), due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan city, China in December 2019 and rapidly spread to other countries. The most common reported symptoms are fever, dry cough, myalgia and fatigue, headache, anorexia, and breathlessness. Anosmia and dysgeusia as well as gastrointestinal symptoms including nausea and diarrhea are other notable symptoms. This virus also can exhibit neurotropic properties and may also cause neurological diseases, including epileptic seizures, cerebrovascular accident, Guillian barre syndrome, acute transverse myelitis, and acute encephalitis. In this study, we discuss stroke as a complication of the new coronavirus and its possible mechanisms of damage.Climate change is an incessant global phenomenon and has turned contentious in the present century. Malaysia, a developing Asian country, has also undergone significant vicissitudes in climate, which has been projected with significant deviations in forthcoming decades. As per the available studies, climate changes may impact on the fertility, either via direct effects on the gonadal functions and neuroendocrine regulations or via several indirect effects on health, socioeconomic status, demeaning the quality of food and water. Malaysia is already observing a declining trend in the Total fertility rate (TFR) over the past few decades and is currently recorded below the replacement level of 2.1 which is insufficient to replace the present population. Moreover, climate changes reportedly play a role in the emergence and cessation of various infectious diseases. Besides its immediate effects, the long-term effects on health and fertility await to be unveiled. Despite the huge magnitude of the repercussion of climate changes in Malaysia, research that can explain the exact cause of the present reduction in fertility parameters in Malaysia or any measures to preserve the national population is surprisingly very scarce. Thus, the present review aims to elucidate the possible missing links by which climate changes are impairing fertility status in Malaysia.

Coronavirus disease 2019 (COVID-19) is an emerging viral infection without any approved treatment. Investigational therapies for COVID-19 may cause clinically important drug-drug interactions (DDIs). We aimed to study potential DDIs (pDDIs) and their risk factors in COVID-19 patients admitted to the hospital.

We conducted a cross-sectional study in a tertiary respiratory hospital dedicated to COVID-19 patients. The Lexi-Interact database was used to investigate clinically important pDDIs. The database output including interacting drug pairs, risk rating, reliability rating, mechanism, and management was evaluated. Associations between the occurrence of pDDIs and probable risk factors were assessed by logistic regression analysis.

Medical charts of 227 patients were reviewed. About 38% of the patients had at least one clinically important pDDI. More than half of the interactions were between protease inhibitors (lopinavir/ritonavir) and regularly prescribed medications for the management of comorbidities or COVID-19 symptoms (e.g., atorvastatin, alprazolam, salmeterol, and tamsulosin). Ischemic heart disease, chronic respiratory diseases, and ICU admission were significantly associated with the occurrence of pDDIs.

We recommend considering the risk factors for the emergence of clinically important DDIs in the pharmacotherapy of COVID-19 patients. Using an alternative medication or dose adjustments may be required in high-risk patients.

We recommend considering the risk factors for the emergence of clinically important DDIs in the pharmacotherapy of COVID-19 patients. Using an alternative medication or dose adjustments may be required in high-risk patients.

Raman spectroscopy has been developed for surgical guidance applications interrogating live tissue during tumor resection procedures to detect molecular contrast consistent with cancer pathophysiological changes. To date, the vibrational spectroscopy systems developed for medical applications include single-point measurement probes and intraoperative microscopes. There is a need to develop systems with larger fields of view (FOVs) for rapid intraoperative cancer margin detection during surgery.

We design a handheld macroscopic Raman imaging system for in vivo tissue margin characterization and test its performance in a model system.

The system is made of a sterilizable line scanner employing a coherent fiber bundle for relaying excitation light from a 785-nm laser to the tissue. A second coherent fiber bundle is used for hyperspectral detection of the fingerprint Raman signal over an area of 1  cm2. Machine learning classifiers were trained and validated on porcine adipose and muscle tissue.

Porcine adipose versus muscle margin detection was validated ex vivo with an accuracy of 99% over the FOV of 95  mm2 in ∼3  min using a support vector machine.

This system is the first large FOV Raman imaging system designed to be integrated in the workflow of surgical cancer resection. It will be further improved with the aim of discriminating brain cancer in a clinically acceptable timeframe during glioma surgery.

This system is the first large FOV Raman imaging system designed to be integrated in the workflow of surgical cancer resection. It will be further improved with the aim of discriminating brain cancer in a clinically acceptable timeframe during glioma surgery.

The creation of fundamentally new approaches to storing various biomaterial and estimation parameters, without irreversible loss of any biomaterial, is a pressing challenge in clinical practice. We present a technology for studying samples of diabetic and non-diabetic human blood plasma in the terahertz (THz) frequency range.

The main idea of our study is to propose a method for diagnosis and storing the samples of diabetic and non-diabetic human blood plasma and to study these samples in the THz frequency range.

Venous blood from patients with type 2 diabetes mellitus and conditionally healthy participants was collected. To limit the impact of water in the THz spectra, lyophilization of liquid samples and their pressing into a pellet were performed. These pellets were analyzed using THz time-domain spectroscopy. The differentiation between the THz spectral data was conducted using multivariate statistics to classify non-diabetic and diabetic groups’ spectra.

We present the density-normalized absorption and refractive index for diabetic and non-diabetic pellets in the range 0.2 to 1.4THz. Over the entire THz frequency range, the normalized index of refraction of diabetes pellets exceeds this indicator of non-diabetic pellet on average by 9% to 12%. The non-diabetic and diabetic groups of the THz spectra are spatially separated in the principal component space.

We illustrate the potential ability in clinical medicine to construct a predictive rule by supervised learning algorithms after collecting enough experimental data.

We illustrate the potential ability in clinical medicine to construct a predictive rule by supervised learning algorithms after collecting enough experimental data.The ability to understand what one reads, or reading comprehension, is central to academic success. For many children with autism spectrum disorder (ASD), reading comprehension is a noted area of challenge. For children with typical development, it is well established that successful reading comprehension requires two broad skills word reading and oral language. For children with ASD, word reading is often believed to be relatively intact, even in the face of poor reading comprehension, suggesting that deficits in oral language, more than in word reading, underlie reading comprehension deficits. Yet, extant research has suggested the importance of both skills. To clarify the role of these skills in the reading comprehension of children with ASD, we conducted a meta-analysis. ERIC, PsycINFO, PubMed, and Proquest Dissertation & Theses were searched for studies of reading comprehension in children with ASD, published up to May 2019. We identified 26 relevant studies about children with ASD (aged 6-18 years) thata similar extent to both their ability to read individual words and their oral language skills. These findings suggest that both areas should be assessed in order to determine appropriate interventions to support reading comprehension for children with ASD. Autism Res 2021, 14 840-858. © 2021 International Society for Autism Research, Wiley Periodicals LLC.Metabolic syndrome (MetS) is a serious health condition triggered by hyperglycemia, dyslipidemia, and abnormal adipose deposition. Recently, circular RNAs (circRNAs) have been proposed as key molecular players in metabolic homeostasis due to their regulatory effects on genes linked to the modulation of multiple aspects of metabolism, including glucose and lipid homeostasis. Dysregulation of circRNAs can lead to metabolic disorders, indicating that circRNAs represent plausible potential targets to alleviate metabolic abnormalities. More recently, a series of circulating circRNAs have been identified to act as both essential regulatory molecules and biomarkers for the progression of metabolism-related disorders, including type 2 diabetes mellitus (T2DM or T2D) and cardiovascular disease (CVD). The findings of this study highlight the function of circRNAs in signaling pathways implicated in metabolic diseases and their potential as future therapeutics and disease biomarkers.

Anorexia of ageing is common and important in the development of sarcopenia in older individuals. Links have been proposed between the gut microbiota and sarcopenia. Disordered gut function is also recognized in anorexia of ageing, but how this may relate to resident gut microbiota is unexplored. Understanding this relationship may provide a basis for novel interventions for anorexia of ageing and sarcopenia. This study explores compositional differences of the gut microbiota between community dwelling healthy older adults with good or poor appetite, and associated differences in sarcopenia.

We assessed appetite by the Simplified Nutritional Appetite Questionnaire (SNAQ) in members of the TwinsUK cohort aged ≥65years. Using a pool of 776 individuals with existing microbiome data estimated from 16S rRNA sequencing data, we identified 102 cases (SNAQ score<14) (95% female, mean age 68years) matched to controls (SNAQ>14) on body mass index, gender, age, diet, calorie consumption, frailty, antibiotic use, socio-economic status, and technical variables to minimize confounding microbiota associations.