Evaluation of the BET Theory for the Characterization of Meso and Microporous MOFs

Surface area determination with the Brunauer–Emmett–Teller (BET) method is a widely used characterization technique for metal–organic frameworks (MOFs). Since these materials are highly porous, the use of the BET theory can be problematic. Several researchers have evaluated the BET method to gain insights into the usefulness of the obtained results and interestingly, their findings are not always consistent. In this review, the suitability of the BET method is discussed for MOFs that have a diverse range of pore widths below the diameters of N2 or Ar and above 20 Å. In addition, the surface area of MOFs that are obtained by implementing different approaches, such as grand canonical Monte Carlo simulations, calculations from the crystal structures or based on experimental N2, Ar, or CO2 adsorption isotherms, are compared and evaluated. Inconsistencies in the state‐of‐the‐art are also noted. Based on the current literature, an overview is provided of how the BET method can give useful estimations of the surface areas for the majority of MOFs, but there are some crucial and specific exceptions which are highlighted in this review

Prevalence and Predictors of Persistence of COVID-19 Symptoms in Older Adults: A Single-Center Study

Objectives: Symptom persistence weeks after laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) clearance is a relatively common long-term complication of Coronavirus disease 2019 (COVID-19). Little is known about this phenomenon in older adults. The present study aimed at determining the prevalence of persistent symptoms among older COVID-19 survivors and identifying symptom patterns. Design: Cross-sectional study. Setting and Participants: We analyzed data collected in people 65 years and older (n = 165) who were hospitalized for COVID-19 and then admitted to the Day Hospital Post-COVID 19 of the Fondazione Policlinico Universitario “Agostino Gemelli” IRCCS (Rome, Italy) between April and December 2020. All patients tested negative for SARS-CoV-2 and met the World Health Organization criteria for quarantine discontinuation. Measures: Patients were offered multidisciplinary individualized assessments. The persistence of symptoms was evaluated on admission using a standardized questionnaire. Results: The mean age was 73.1 ± 6.2 years (median 72, interquartile range 27), and 63 (38.4%) were women. The average time elapsed from hospital discharge was 76.8 ± 20.3 days (range 25−109 days). On admission, 137 (83%) patients reported at least 1 persistent symptom. Of these, more than one-third reported 1 or 2 symptoms and 46.3% had 3 or more symptoms. The rate of symptom persistence was not significantly different when patients were stratified according to median age. Compared with those with no persistent symptoms, patients with symptom persistence reported a greater number of symptoms during acute COVID-19 (5.3 ± 3.0 vs 3.3 ± 2.0; P < .001). The most common persistent symptoms were fatigue (53.1%), dyspnea (51.5%), joint pain (22.2%), and cough (16.7%). The likelihood of symptom persistence was higher in those who had experienced fatigue during acute COVID-19. Conclusions and Implications: Persistent symptoms are frequently experienced by older adults who have been hospitalized for COVID-19. Follow-up programs should be implemented to monitor and care for long-term COVID-19–related health issues

Gaussian Mixture Model of Heart Rate Variability

Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters

Plants and traditional knowledge: An ethnobotanical investigation on Monte Ortobene (Nuoro, Sardinia)

<p>Abstract</p> <p>Background</p> <p>Most of the traditional knowledge about plants and their uses is fast disappearing as a consequence of socio-economic and land use changes. This trend is also occurring in areas that are historically exposed to very few external influences, such as Sardinia (Italy). From 2004 to 2005, an ethnobotanical investigation was carried out in the area of Monte Ortobene, a mountain located near Nuoro, in central Sardinia.</p> <p>Methods</p> <p>Data were collected by means of semi-structured interviews. All the records – defined as 'citations', i.e. a single use reported for a single botanical species by a single informant – were filed in a data base ('analytical table'), together with additional information: i.e. local names of plants, parts used, local frequencies, and habitats of plants, etc. In processing the data, plants and uses were grouped into general ('categories') and detailed ('secondary categories') typologies of use. Some synthetic indexes have also been used, such as Relative Frequency of Citation (RFC), Cultural Importance Index (CI), the Shannon-Wiener Index (H'), and Evenness Index (J).</p> <p>Results</p> <p>Seventy-two plants were cited by the informants as being traditionally used in the area. These 72 'ethnospecies' correspond to 99 botanical taxa (species or subspecies) belonging to 34 families. Three-hundred and one citations, 50 secondary categories of use, and 191 different uses were recorded, most of them concerning alimentary and medicinal plants.</p> <p>For the alimentary plants, 126 citations, 44 species, and 13 different uses were recorded, while for the medicinal plants, there were 106 citations, 40 species, and 12 uses. Few plants and uses were recorded for the remaining categories. Plants and uses for each category of use are discussed. Analyses of results include the relative abundance of botanical families, wild vs. cultivated species, habitats, frequency, parts of plant used, types of use, knowledge distribution, and the different cultural importance of the species in question.</p> <p>Conclusion</p> <p>The study provides examples of several interesting uses of plants in the community, which would seem to show that the custom of using wild plants is still alive in the Monte Ortobene area. However, many practices are no longer in use, and survive only as memories from the past in the minds of elderly people, and often only in one or just a few informants. This rapidly vanishing cultural diversity needs to be studied and documented before it disappears definitively.</p

Machine Learning to Quantitate Neutrophil NETosis

We introduce machine learning (ML) to perform classifcation and quantitation of images of nuclei from human blood neutrophils. Here we assessed the use of convolutional neural networks (CNNs) using free, open source software to accurately quantitate neutrophil NETosis, a recently discovered process involved in multiple human diseases. CNNs achieved \u3e94% in performance accuracy in diferentiating NETotic from non-NETotic cells and vastly facilitated dose-response analysis and screening of the NETotic response in neutrophils from patients. Using only features learned from nuclear morphology, CNNs can distinguish between NETosis and necrosis and between distinct NETosis signaling pathways, making them a precise tool for NETosis detection. Furthermore, by using CNNs and tools to determine object dispersion, we uncovered diferences in NETotic nuclei clustering between major NETosis pathways that is useful in understanding NETosis signaling events. Our study also shows that neutrophils from patients with sickle cell disease were unresponsive to one of two major NETosis pathways. Thus, we demonstrate the design, performance, and implementation of ML tools for rapid quantitative and qualitative cell analysis in basic science

Cognitive effects of high-frequency repetitive transcranial magnetic stimulation: a systematic review

Transcranial magnetic stimulation (TMS) was introduced as a non-invasive tool for the investigation of the motor cortex. The repetitive application (rTMS), causing longer lasting effects, was used to study the influence on a variety of cerebral functions. High-frequency (>1 Hz) rTMS is known to depolarize neurons under the stimulating coil and to indirectly affect areas being connected and related to emotion and behavior. Researchers found selective cognitive improvement after high-frequency (HF) stimulation specifically over the left dorsolateral prefrontal cortex (DLPFC). This article provides a systematic review of HF-rTMS studies (1999–2009) stimulating over the prefrontal cortex of patients suffering from psychiatric/neurological diseases or healthy volunteers, where the effects on cognitive functions were measured. The cognitive effect was analyzed with regard to the impact of clinical status (patients/healthy volunteers) and stimulation type (verum/sham). RTMS at 10, 15 or 20 Hz, applied over the left DLPFC, within a range of 10–15 successive sessions and an individual motor threshold of 80–110%, is most likely to cause significant cognitive improvement. In comparison, patients tend to reach a greater improvement than healthy participants. Limitations concern the absence of healthy groups in clinical studies and partly the absence of sham groups. Thus, future investigations are needed to assess cognitive rTMS effects in different psychiatric disorders versus healthy subjects using an extended standardized neuropsychological test battery. Since the pathophysiological and neurobiological basis of cognitive improvement with rTMS remains unclear, additional studies including genetics, experimental neurophysiology and functional brain imaging are necessary to explore stimulation-related functional changes in the brain

De novo variants in CDK13 associated with syndromic ID/DD:Molecular and clinical delineation of 15 individuals and a further review

De novo variants in the gene encoding cyclin-dependent kinase 13 (CDK13) have been associated with congenital heart defects and intellectual disability (ID). Here, we present the clinical assessment of 15 individuals and report novel de novo missense variants within the kinase domain of CDK13. Furthermore, we describe 2 nonsense variants and a recurrent frame-shift variant. We demonstrate the synthesis of 2 aberrant CDK13 transcripts in lymphoblastoid cells from an individual with a splice-site variant. Clinical characteristics of the individuals include mild to severe ID, developmental delay, behavioral problems, (neonatal) hypotonia and a variety of facial dysmorphism. Congenital heart defects were present in 2 individuals of the current cohort, but in at least 42% of all known individuals. An overview of all published cases is provided and does not demonstrate an obvious genotype-phenotype correlation, although 2 individuals harboring a stop codons at the end of the kinase domain might have a milder phenotype. Overall, there seems not to be a clinically recognizable facial appearance. The variability in the phenotypes impedes an a vue diagnosis of this syndrome and therefore genome-wide or gene-panel driven genetic testing is needed. Based on this overview, we provide suggestions for clinical work-up and management of this recently described ID syndrome

Extending the evolution of the stellar mass-size relation at z < 2 to low stellar mass galaxies from HFF and CANDELS

Galaxie