Practice Transformation

OBJECTIVE: Transcranial focused ultrasound (tFUS) is being explored for neuroscience research and clinical applications due to its ability to affect precise brain regions noninvasively. The ability to target specific brain regions and localize the beam during these procedures is important for these applications to avoid damage and minimize off-target effects. Here, we present a method to combine optical tracking with magnetic resonance (MR) acoustic radiation force imaging to achieve targeting and localizing of the tFUS beam...

Formal teaching observations not only have an essential role in the visibility of teaching and learning but also allow for constructive, critical feedback for improvement. In both nursing and teaching, there is an emphasis on the need for efficient, regular reflective practice; this not to identify negative aspects but to transform professional practice. This article provides a personal insight into formal teaching observations, and themes arising from them of motivation, the teacher's voice, the use of abbreviations and acronyms and the use of exemplars, using a critical reflective approach...

OBJECTIVE: This study aims to investigate the practical application of "Internet + technology" leveraging medical big data to enhance the development of a smart hospital platform. Specifically, the focus is on optimizing patient care processes, refining medical data management systems, and enhancing operational efficiency within the hospital setting. METHODS: With the help of traditional Internet and mobile Internet technology, we analyzed the patient behavior big data accumulated in our hospital for many years, simplified the diagnosis and treatment links, refined the service connotation, and improved patient satisfaction before, during and after diagnosis; With the help of barcode, RFID and 5G networks, the links that are easy to produce medical security incidents can be monitored to improve medical quality, such as digital operating room system, establishment of multidisciplinary consultation center (MDT), electronic medical record system based on digital signature, etc...

This study proposes a novel network modeling approach, called sliding window limited penetrable visibility graph (SLPVG), for transforming time series into networks. SLPVG takes into account the dynamic nature of time series, which is often affected by noise disturbances, and the fact that most nodes are not directly connected to distant nodes. By analyzing the degree distribution of different types of time series, SLPVG accurately captures the dynamic characteristics of time series with low computational complexity...

H+ co-intercalation chemistry of the cathode is perceived to have damaging consequences on the low-rate and long-term cycling of aqueous zinc batteries, which is a critical hindrance to their promise for stationary storage applications. Herein, the thermodynamically competitive H+ storage chemistry of an attractive high-voltage cathode LiMn2 O4 is revealed by employing operando and ex-situ analytical techniques together with density functional theory-based calculations. The H+ electrochemistry leads to the previously unforeseen voltage decay with cycling, impacting the available energy density, particularly at lower currents...

The temporary closure of the Outpatient Psychotherapy Clinic at the Sigmund Freud Private University in Vienna during the Covid-19 pandemic demanded an immediate and unexpected reaction to assure further psychotherapeutic services. Both psychotherapists and patients were forced into a rapid transition to online psychotherapy. While Covid-19 research has comprehensively described challenges of online psychotherapies, we were interested in learning specifically how early stage psychotherapists-in-training, who started their clinical work with patients exclusively in the online setting, experienced this unprecedented clinical situation...

The COVID-19 pandemic has affected millions worldwide, giving rise to long-term symptoms known as post-acute sequelae of SARS-CoV-2 (PASC) infection, colloquially referred to as long COVID. With an increasing number of people experiencing these symptoms, early intervention is crucial. In this study, we introduce a novel method to detect the likelihood of PASC or Myalgic Encephalomyelitis (ME) using a wearable four-channel headband that collects Electroencephalogram (EEG) data. The raw EEG signals are processed using Continuous Wavelet Transform (CWT) to form a spectrogram-like matrix, which serves as input for various machine learning and deep learning models...

OBJECTIVES: To assess the effect of total sleep deprivation (TSD) on spontaneous brain activity in medical staff during routine clinical practice. METHODS: A total of 36 medical staff members underwent resting-state functional MRI (rs-fMRI) scans and neuropsychological tests twice, corresponding to rested wakefulness (RW) after normal sleep and 24 h of acute TSD. The rs-fMRI features, including the mean fractional amplitude of low-frequency fluctuation (mfALFF), z-score transformed regional homogeneity (zReHo), and functional connectivity (zFC), were compared between RW and TSD...

Ophthalmology fellowship is focusing on the educational advancement, medical research progress and academic productivity by transforming general ophthalmologists into superior clinical capacities in ophthalmology. There is a vast majority of ophthalmologists who wish to undertake fellowship degrees. The fellowship programs have several benefits for ophthalmologists and medical institutions. However, the expansion of ophthalmic fellowships has resulted in a greater number of ophthalmology visits, the possibility of unnecessary subspecialty eye examinations, induced demand and increasing eye-care costs...

With the rapid growth of information and communication technologies, governments worldwide are embracing digital transformation to enhance service delivery and governance practices. In the rapidly evolving landscape of information technology (IT), secure data management stands as a cornerstone for organizations aiming to safeguard sensitive information. Robust data modeling techniques are pivotal in structuring and organizing data, ensuring its integrity, and facilitating efficient retrieval and analysis. As the world increasingly emphasizes sustainability, integrating eco-friendly practices into data management processes becomes imperative...

The conversion of fast-twitch fibers into slow-twitch fibers within skeletal muscle plays a crucial role in improving physical stamina and safeguarding against metabolic disorders in individuals. Grape seed proanthocyanidin extract (GSPE) possesses numerous pharmacological and health advantages, effectively inhibiting the onset of chronic illnesses. However, there is a lack of research on the specific mechanisms by which GSPE influences muscle physiology and gut microbiota. This study aims to investigate the role of gut microbiota and their metabolites in GSPE regulation of skeletal muscle fiber type conversion...

The Getting It Right First Time (GIRFT) programme is a quality improvement initiative covering the National Health Service in England. The programme aims to standardise clinical practices and improve patient and system level outcomes by utilising data-driven insights and clinically-led recommendations. There are GIRFT workstreams for every medical and surgical specialty, including urology. Defining features of the GIRFT methodology are that it is clinically led by experienced clinicians, data-driven, and specialty specific...

BACKGROUND: Early blight (EB) of Tomatoes, caused by Alternaria solani, is a serious fungal disease that adversely affects tomato production. Infection is characterized by dark lesions on leaves, stems, and fruits. Several agrochemicals can be used to control infection, these chemicals may disrupt environmental equilibrium. An alternative technology is needed to address this significant fungal threat. This study was designed to control the growth of EB in tomatoes caused by A. solani, using green-fabricated silver nanoparticles (Ag-NPs)...

While dual-energy computed tomography (DECT) technology introduces energy-specific information in clinical practice, single-energy CT (SECT) is predominantly used, limiting the number of people who can benefit from DECT. This study proposed a novel method to generate synthetic low-energy virtual monochromatic images at 50 keV (sVMI50keV ) from SECT images using a transformer-based deep learning model, SwinUNETR. Data were obtained from 85 patients who underwent head and neck radiotherapy. Among these, the model was built using data from 70 patients for whom only DECT images were available...

Singlet oxygen (1O2) is an essential reactive species responsible for selective oxidation of organic matter, especially in Fenton-like processes. However, due to the great limitations in synthesizing catalysts with well-defined active sites, the controllable production and practical application of 1O2 remain challenging. Herein, guided by theoretical simulations, a series of boron nitride-based single-atom catalysts (BvBN/M, M = Co, Fe, Cu, Ni and Mn) were synthesized to regulate 1O2 generation by activating peroxymonosulfate (PMS)...

BACKGROUND: Mastitis, a pervasive and detrimental disease in dairy farming, poses a significant challenge to the global dairy industry. Monitoring the milk somatic cell count (SCC) is vital for assessing the incidence of mastitis and the quality of raw cow's milk. However, existing SCC detection methods typically require large-scale instruments and specialized operators, limiting their application in resource-constrained settings such as dairy farms and small-scale labs. To address these limitations, this study introduces a novel, smartphone-based, on-site SCC testing method that leverages smartphone capabilities for milk somatic cell identification and enumeration, offering a portable and user-friendly testing platform...

Some antibiotics are used for the treatment of various bacterial crop diseases, and there is a concern that this practice may represent a selection pressure that increases the reservoir of antibiotic resistance carried by bacteria in crop production systems. Since the 1950s the aminoglycoside antibiotic streptomycin has been widely used for the treatment of some bacterial crop diseases such as fire blight in apples and pears. Following application, the time that bacteria will be exposed to the antibiotic, and therefore the pressure for selection of resistance, will vary according to the environmental persistence of the antibiotic...

Streptococcosis outbreaks caused by Streptococcus agalactiae infection in tilapia aquaculture have been consistently reported and associated with high mortality and morbidity leading to significant economic losses. Existing vaccine candidates against Streptococcus spp. are designed for intraperitoneal injections that are not practical and labor-intensive which have prompted farmers to protect aquatic animals with antibiotics, thus encouraging the emergence of multidrug resistant bacteria. In this study, a live recombinant L...

Massive genetic compendiums such as the UK Biobank have become an invaluable resource for identifying genetic variants that are associated with complex diseases. Due to the difficulties of massive data collection, a common practice of these compendiums is to collect interval-censored data. One challenge in analyzing such data is the lack of methodology available for genetic association studies with interval-censored data. Genetic effects are difficult to detect because of their rare and weak nature, and often the time-to-event outcomes are transformed to binary phenotypes for access to more powerful signal detection approaches...

Epilepsy affects over 50 million people globally. Electroencephalography is critical for epilepsy diagnosis, but manual seizure classification is time-consuming and requires extensive expertise. This paper presents an automated multi-class seizure classification model using EEG signals from the Temple University Hospital Seizure Corpus ver. 1.5.2. 11 features including time-based correlation, time-based eigenvalues, power spectral density, frequency-based correlation, frequency-based eigenvalues, sample entropy, spectral entropy, logarithmic sum, standard deviation, absolute mean, and ratio of Daubechies D4 wavelet transformed coefficients were extracted from 10-second sliding windows across channels...