Networks

Kidney stones form when mineral salts crystallize in the urinary tract. While most stones exit the body in the urine stream, some can block the ureteropelvic junction or ureters, leading to severe lower back pain, blood in the urine, vomiting, and painful urination. Imaging technologies, such as X-rays or ureterorenoscopy (URS), are typically used to detect kidney stones. Subsequently, these stones are fragmented into smaller pieces using shock wave lithotripsy (SWL) or laser URS. Both treatments yield subtly different patient outcomes...

The mapping of metabolite-specific data to pathways within cellular metabolism is a major data analysis step needed for biochemical interpretation. A variety of machine learning approaches, particularly deep learning approaches, have been used to predict these metabolite-to-pathway mappings, utilizing a training dataset of known metabolite-to-pathway mappings. A few such training datasets have been derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG). However, several prior published machine learning approaches utilized an erroneous KEGG-derived training dataset that used SMILES molecular representations strings (KEGG-SMILES dataset) and contained a sizable proportion (~26%) duplicate entries...

BACKGROUND: Participation in multimodal leisure activities, such as playing a musical instrument, may be protective against brain aging and dementia in older adults (OA). Potential neuroprotective correlates underlying musical activity remain unclear. OBJECTIVE: This cross-sectional study investigated the association between lifetime musical activity and resting-state functional connectivity (RSFC) in three higher-order brain networks: the Default Mode, Fronto-Parietal, and Salience networks...

This systematic review will identify and synthesize the emerging evidence on older adults with Mild Cognitive Impairment (MCI) utilizing Information and Communication Technology (ICT) to maintain, restore, or augment social networks. The systematic review will consider the evidence on contextual and personal factors of older adults with MCI and their ICT use for social connectedness. The evidence searches will be implemented in PsycINFO, Academic Search Complete, Medline, PubMed, and manual searches. We shall review articles that were published between January 2010 and October 2023 in English and on Information and Communication Technology utility in social networking among older adults with MCI...

We investigate the impact of left-behind experiences on the urban identity of new-generation migrant workers using data from the 2017 China Migrants Dynamic Survey. The results show the following: (1) The left-behind experience is an important factor undermining the urban identity of new-generation migrant workers, and the conclusion remains consistent after robustness checks, such as propensity score matching. (2) Left-behind experiences of both parents away from home had the most significant negative impact on urban identity...

Understanding risk perception and risk-taking among youth can inform targeted prevention efforts. Using a health beliefs model-informed framework, we analysed 8 semi-structured, gender-specific focus group discussions with 93 youth 15-24 years old (48% male, 52% female), drawn from the SEARCH trial in rural Kenya and Uganda in 2017-2018, coinciding with the widespread introduction of PrEP. Highly connected social networks and widespread uptake of antiretrovirals shaped youth HIV risk perception. Amid conflicting information about HIV prevention methods, youth felt exposed to multiple HIV risk factors like the high prevalence of HIV, belief that people with HIV(PWH) purposefully infect others, dislike of condoms, and doubts about PrEP efficacy...

Recognition and judgment of X-ray computed tomography (CT) images play a crucial role in medical diagnosis and disease prevention. However, the storage and calculation of the X-ray imaging system applied in the traditional CT diagnosis is separate, and the pathological judgment is based on doctors' experience, which will affect the timeliness and accuracy of decision-making. In this paper, a simple-structured reservoir computing network (RC) is proposed based on Ga2 O3 X-ray optical synaptic devices to recognize medical skeletal CT images with high accuracy...

The use of internal catalysts has emerged as a pivotal design principle to facilitate dynamic exchanges within covalent adaptable networks (CANs). Polybenzoxazines, specifically, have shown considerable potential in generating vitrimers through thermally induced transesterification reactions catalyzed internally by tertiary amines. This study aims to investigate the chemical complexities of transesterification reactions within benzoxazine vitrimers. To achieve this, model molecules using various phenolic acids and amino-alcohol derivatives were synthesized as precursors...

BACKGROUND: People with Parkinson's disease (PD) have an increased risk of dementia, yet patients and clinicians frequently avoid talking about it due to associated stigma, and the perception that "nothing can be done about it". However, open conversations about PD dementia may allow people with the condition to access treatment and support, and may increase participation in research aimed at understanding PD dementia. OBJECTIVES: To co-produce information resources for patients and healthcare professionals to improve conversations about PD dementia...

The present work describes a preclinical trial ( in silico , in vivo and in vitro ) protocol to assess the biomechanical performance and osteogenic capability of 3D-printed polymeric scaffolds implants used to repair partial defects in a sheep mandible. The protocol spans multiple steps of the medical device development pipeline, including initial concept design of the scaffold implant, digital twin in silico finite element modeling, manufacturing of the device prototype, in vivo device implantation, and in vitro laboratory mechanical testing...

BACKGROUND: This study aims to compare antimicrobial drug usage in our hospital to Jiangsu Province and China from 2020 to 2022 during the pandemic. The ultimate goal is to improve the rational use of antimicrobials in psychiatric hospitals. RESEARCH DESIGN AND METHODS: A detailed analysis was performed using data from the National Antimicrobial Drug Clinical Application Monitoring Network. Several parameters were studied: the rate of antimicrobial drug use, number and types of drugs used, the rate of combined use, rate of microbiological examinations, drug use intensity, and cumulative Defined Daily Doses (DDDs)...

OBJECTIVES: Diagnostic errors are the leading cause of preventable harm in clinical practice. Implementable tools to quantify and target this problem are needed. To address this gap, we aimed to generalize the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) framework by developing its computable phenotype and then demonstrated how that schema could be applied in multiple clinical contexts. METHODS: We created an information model for the SPADE processes, then mapped data fields from electronic health records (EHR) and claims data in use to that model to create the SPADE information model (intention) and the SPADE computable phenotype (extension)...

Non-small cell lung cancer (NSCLC) is the most common histopathological type, and it is purposeful for screening potential prognostic biomarkers for NSCLC. This study aims to identify the lncRNAs and mRNAs related to survival of non-small cell lung cancer (NSCLC). The expression profile data of lung adenocarcinoma and lung squamous cell carcinoma were downloaded in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset. A total of eight survival related long non-coding RNAs (lncRNAs) and 262 survival related mRNAs were filtered...

São Caetano do Sul, a city in southeastern Brazil, boasts exemplary social indicators and healthcare services, with a population of 162,763 and a density of 9,736.03 inhabitants/km². Allocating 25% of its budget to healthcare, the city's mental healthcare services adhere to the National Mental Health Policy. Structured services include a CAPS-II, CAPS-AD, outpatient teams, and teams in various locations. Initiatives since 2000 include inaugurating a CAPS-AD in 2006, a psychiatric emergency service in 2010, and a CAPS-II in 2016, relocating CAPS-AD in 2019, and establishing the Cuca Legal Project in 2022...

In the task of multiview multilabel (MVML) classification, each instance is represented by several heterogeneous features and associated with multiple semantic labels. Existing MVML methods mainly focus on leveraging the shared subspace to comprehensively explore multiview consensus information across different views, while it is still an open problem whether such shared subspace representation is effective to characterize all relevant labels when formulating a desired MVML model. In this article, we propose a novel label-driven view-specific fusion MVML method named L-VSM, which bypasses seeking for a shared subspace representation and instead directly encodes the feature representation of each individual view to contribute to the final multilabel classifier induction...

Video-based referring expression comprehension is a challenging task that requires locating the referred object in each video frame of a given video. While many existing approaches treat this task as an object-tracking problem, their performance is heavily reliant on the quality of the tracking templates. Furthermore, when there is not enough annotation data to assist in template selection, the tracking may fail. Other approaches are based on object detection, but they often use only one adjacent frame of the key frame for feature learning, which limits their ability to establish the relationship between different frames...

Advances in multisource remote sensing have allowed for the development of more comprehensive observation. The adoption of deep convolutional neural networks (CNN) naturally includes spatial-spectral information, which has achieved promising performance in multisource data classification. However, challenges are still found with the extraction of spatial distribution and spectrum relationships, which eventually limit the classification performance. To solve the issue, a spatial-spectral perception network (S2PNet) is proposed to extract the advantages of different data sources and the cross information between data sources in a targeted manner...

OBJECTIVE: We present a model-based image reconstruction approach based on unrolled neural networks which corrects for image distortion and noise in low-field ( B0  ∼  50mT) MRI. METHODS: Utilising knowledge about the underlying physics, a novel network architecture (SH-Net) is introduced which involves the estimation of spherical harmonic coefficients to guarantee a spatially smooth field map estimate. The SH-Net is integrated in an end-to-end trainable model which jointly estimates the B0 -field map as well as the image...

This review aims to provide a systematic analysis of the literature focused on the use of intelligent control systems in robotics for physical rehabilitation, identifying trends in recent research and comparing the effectiveness of intelligence used in control, with the aim of determining important factors in robot-assisted rehabilitation and how intelligent controller design can improve them. Seven electronic research databases were searched for articles published in the years 2015 - 2022 with articles selected based on relevance to the subject area of intelligent control systems in rehabilitation robotics...

To evaluate sleep quality, it is necessary to monitor overnight sleep duration. However, sleep monitoring typically requires more than 7 h, which can be inefficient in terms of data size and analysis. Therefore, we proposed to develop a deep learning-based model using a 30 sec sleep electroencephalogram (EEG) early in the sleep cycle to predict sleep onset latency (SOL) distribution and explore associations with sleep quality (SQ). We propose a deep learning model composed of a structure that decomposes and restores the signal in epoch units and a structure that predicts the SOL distribution...