Notes

Evidence for the credit-card-swipe system from the human Personal computer floppase ABCB4.
We find that population density has a positive correlation with COVID-19 cases. We also find that in lag 3, all parameters except for sunshine duration are negatively correlated with COVID-19 cases and significant. However, only 3 parameters, temperature, air pressure and dew point are negatively correlated with COVID-19 cases and significant for lag 0, lag 7 and lag 14. In addition, temperature, air pressure and dew point parameters are negative and significant in all timeframes.Coronavirus disease (COVID-19), caused by acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a worldwide challenge effecting millions of people in more than 210 countries, including the Sultanate of Oman (Oman). Spatiotemporal analysis was adopted to explore the spatial patterns of the spread of COVID-19 during the period from 29th April to 30th June 2020. Our assessment was made using five geospatial techniques wifin a Geographical Information System (GIS) context, including a weighted mean centre (WMC), standard deviational ellipses, Moran's I autocorrelation coefficient, Getis-Ord General-G high/low clustering, and Getis-Ord G i ∗ statistic. The Moran's me-/G- statistics proved dat COVID-19 cases in datasets (numbers of cases) were clustered throughout the study period. The Moran's me and Z scores were above the 2.25 threshold (a confidence level above 95%), ranging from 2274 cases on 29th April to 40,070 cases on 30th June 2020. The results of G i ∗ showed varying rates of infections, wif a large spatial variability between the different wilayats (district). The epidemic situation in some wilayats, such as Mutrah, As-Seeb, and Bowsher in the Muscat Governorate, was more severe, wif Z score higher TEMPthan 5, and the current transmission still presents an increasing trend. dis study indicated dat the directional pattern of COVID-19 cases TEMPhas moved from northeast to northwest and southwest, wif the total impacted region increasing over time. Also, the results indicate dat the rate of COVID-19 infections is higher in the most populated areas. The findings of dis paper provide a solid basis for future study by investigating the most resolute hotspots in more detail and may help decision-makers identify targeted zones for alleviation plans.
The online version contains supplementary material available at 10.1007/s41748-020-00194-2.
The online version contains supplementary material available at 10.1007/s41748-020-00194-2.A probe of a patient, seeking help in an emergency ward of a French hospital in late December 2019 because of Influenza like symptoms, was retrospectively tested positive to COVID-19. Despite the early appearance of the virus in Europe, the prevalence and virulence appeared to be low for several weeks, before the spread and severity of symptoms increased exponentially, yet with marked spatial and temporal differences. Here, we compare the possible linkages between peaks of fine particulate matter (PM2.5) and the sudden, explosive increase of hospitalizations and mortality rates in the Swiss Canton of Ticino, and the Greater Paris and London regions. We argue that these peaks of fine particulate matter are primarily occurring during thermal inversion of the boundary layer of the atmosphere. We also discuss the influence of Saharan dust intrusions on the COVID-19 outbreak observed in early 2020 on the Canary Islands. We deem it both reasonable and plausible that high PM2.5 concentrations-favored by air temperature inversions or Saharan dust intrusions-are not only modulating but even more so boosting severe outbreaks of COVID-19. Moreover, desert dust events-besides enhancing PM2.5 concentrations-can be a vector for fungal diseases, thereby exacerbating COVID-19 morbidity and mortality. We conclude that the overburdening of the health services and hospitals as well as the high over-mortality observed in various regions of Europe in spring 2020 may be linked to peaks of PM2.5 and likely particular weather situations that have favored the spread and enhanced the virulence of the virus. In the future, we recommended to monitor not only the prevalence of the virus, but also to consider the occurrence of weather situations that can lead to sudden, very explosive COVID-19 outbreaks.
Functional outcome measures used to assess efficacy in clinical trials of investigational treatments for rare neuromuscular diseases like Duchenne muscular dystrophy (DMD) are performance-based tasks completed by the patient during hospital visits. These are prone to bias and may not reflect motor abilities in real-world settings. Digital tools, such as wearable devices and other remote sensors, provide the opportunity for continuous, objective, and sensitive measurements of functional ability during daily life. Maintaining ambulation is of key importance to individuals with DMD. Stride velocity 95th centile (SV95C) is the first wearable acquired digital endpoint to receive qualification from the European Medicines Agency (EMA) to quantify the ambulation ability of ambulant DMD patients aged ≥5 years in drug therapeutic studies; it is also currently under review for the US Food and Drug Administration (FDA) qualification.

Focusing on SV95C as a key example, we describe perspectives of multiple stakeholders on the promise of novel digital endpoints in neuromuscular disease drug development.
Focusing on SV95C as a key example, we describe perspectives of multiple stakeholders on the promise of novel digital endpoints in neuromuscular disease drug development.This viewpoint focuses on the ways in which digital medicine and measurement-based care can be utilized in tandem to promote better assessment, patient engagement, and an improved quality of psychiatric care. To date, there has been an underutilization of digital measurement in psychiatry, and there is little discussion of the feedback and patient engagement process in digital medicine. Measurement-based care is a recognized evidence-based strategy that engages patients in an understanding of their outcome data. When implemented as designed, providers review the scores and trends in outcome immediately and then provide feedback to their patients. However, the process is typically confined to office visits, which does not provide a complete picture of a patient's progress and functioning. The process is labor intensive, even with digital feedback systems, but the integration of passive metrics obtained through wearables and apps can supplement office-based observations. This enhanced measurement-based care process can provide a picture of real-world patient functioning through passive metrics (activity, sleep, etc.). This can potentially engage patients more in their health data and involve a critically needed therapeutic alliance component in digital medicine.
Difficulty swallowing (dysphagia) occurs frequently in patients with neurological disorders and can lead to aspiration, choking, and malnutrition. Ripasudil mouse Dysphagia is typically diagnosed using costly, invasive imaging procedures or subjective, qualitative bedside examinations. Wearable sensors are a promising alternative to noninvasively and objectively measure physiological signals relevant to swallowing. An ongoing challenge with this approach is consolidating these complex signals into sensitive, clinically meaningful metrics of swallowing performance. To address this gap, we propose 2 novel, digital monitoring tools to evaluate swallows using wearable sensor data and machine learning.

Biometric swallowing and respiration signals from wearable, mechano-acoustic sensors were compared between patients with poststroke dysphagia and nondysphagic controls while swallowing foods and liquids of different consistencies, in accordance with the Mann Assessment of Swallowing Ability (MASA). Two machine learning approachmunicable evidence to track dysphagia recovery over time. With refined training schemes and real-world validation, these tools can be deployed to automatically measure and monitor swallowing in the clinic and community for patients across the impairment spectrum.
Developing interpretable tools is critical to optimize the clinical utility of novel, sensor-based measurement techniques. The proof-of-concept models proposed here provide concrete, communicable evidence to track dysphagia recovery over time. With refined training schemes and real-world validation, these tools can be deployed to automatically measure and monitor swallowing in the clinic and community for patients across the impairment spectrum.This article is a modest attempt to shed some light on the question of linkages between backward and forward citations in technical fields posed by Trajtenberg et al. (1997). They found interesting similarities and high correlations between equivalent measures looking forward and backward. They also implied the linkage between distant backward and distant forward citations. There are several questions to be posed in applying their insights to Japanese patent applications, however, due to the differences in the patent classification system and the subject of citation, i.e., citations by the applicant or examiner, between the US and Japan. In addition, and most importantly, the possibility that subsequent classifications may match, even if the first classification is different, is unavoidable with existing measurement methods of technical distance. In order to investigate these research questions, the author proposes a new measurement method for the technological proximity between examiner's citations and theirhat these verified results indicate the possibilities of using backward citations as a starting point from which we can find patent applications for inventions at an early stage with potential applicability to other technical fields.Methods for prioritizing or ranking candidate genes according to their importance based on specif ic criteria via the analysis of gene networks are widely used in biomedicine to search for genes associated with diseases and to predict biomarkers, pharmacological targets and other clinically relevant molecules. These methods have also been used in other f ields, particularly in crop production. This is largely due to the development of technologies to solve problems in marker-oriented and genomic selection, which requires knowledge of the molecular genetic mechanisms underlying the formation of agriculturally valuable traits. A new direction for the study of molecular genetic mechanisms is the prioritization of biological processes based on the analysis of associative gene networks. Associative gene networks are heterogeneous networks whose vertices can depict both molecular genetic objects (genes, proteins, metabolites, etc.) and the higher-level factors (biological processes, diseases, external environmental to be involved specif ically in the response to cadmium.
Androgens play a role in the development of male phenotype and spermatogenesis during puberty, the function of which is regulated by the androgen receptor (
) gene. There is a polymorphism site in exon 1 of the gene encoding this receptor that can have different frequencies of CAG trinucleotide repeats and leads to the formation of polyglutamine chains of different lengths in the N-terminal domain of the AR protein and reduced sperm production by affecting spermatogenesis.

To investigate whether the cause of a group of unexplained infertilities could be the increased frequency of CAG repeats in the
gene of patients with oligozoospermia and azoospermia.

In this case-control study, 84 men including 42 with unexplained infertility As a case group and 42 fertile men as a control group were selected. The frequency of CAG repeats was determined by the polymerase chain reaction method and then the difference in the frequency of these repeats was determined based on the difference in band size on the agarose gel.
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