Medical monitoring

Periodic quantification of blood glucose levels is performed using painful, invasive methods. The proposed work presents the development of a noninvasive glucose-monitoring device with two sensors, i.e., finger and wrist bands. The sensor system was designed with a near-infrared (NIR) wavelength of 940 nm emitter and a 900-1700 nm detector. This study included 101 diabetic and non-diabetic volunteers. The obtained dataset was subjected to pre-processing, exploratory data analysis (EDA), data visualization, and integration methods...

Handgrip strength is a crucial indicator to monitor the change of cognitive function over time, but its mechanism still needs to be further explored. We sampled 59 monozygotic twin pairs to explore the potential mediating effect of DNA methylation (DNAm) on the association between handgrip strength and cognitive function. The initial step was the implementation of an epigenome-wide association analysis (EWAS) in the study participants, with the aim of identifying DNAm variations that are associated with handgrip strength...

This study aimed to analyze peripheral blood lymphocyte subsets in lupus nephritis (LN) patients and use machine learning (ML) methods to establish an effective algorithm for predicting co-infection in LN. This study included 111 non-infected LN patients, 72 infected LN patients, and 206 healthy controls (HCs). Patient information, infection characteristics, medication, and laboratory indexes were recorded. Eight ML methods were compared to establish a model through a training group and verify the results in a test group...

BACKGROUND: The current state of the mental health crisis has been a topic of discussion around the nation, with those in rural communities being at a particularly higher risk. Community pharmacists are uniquely positioned to screen patients for mental health disorders as well as provide education and patient monitoring following medication changes by prescribers. OBJECTIVE: The objective of this study is to assess mental health screening outcomes provided by rural community pharmacists...

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Polymeric biomedical implants are an important clinical tool, but degradation remains difficult to determine post-implantation. Computed tomography (CT) could be a powerful tool for device monitoring, but polymers require incorporation of radiopaque contrast agents to be distinguishable from tissue. In addition, immune response to radiopaque devices must be characterized as it modulates device function. Radiopaque devices and films were produced by incorporating 0-20wt% TaOx nanoparticles into polymers: polycaprolactone (PCL) and poly(lactide-co-glycolide) (PLGA)...

STUDY QUESTION: Does linzagolix administered orally once daily for up to 3 months at a dose of 75 mg alone or 200 mg in combination with add-back therapy (ABT) (1.0 mg estradiol; 0.5 mg norethindrone acetate, also known as norethisterone acetate [NETA]) demonstrate better efficacy than placebo in the management of endometriosis-related dysmenorrhea and non-menstrual pelvic pain? SUMMARY ANSWER: Combining 200 mg linzagolix with ABT was found to significantly reduce dysmenorrhea and non-menstrual pelvic pain at 3 months of therapy, while a daily dose of 75 mg linzagolix yielded a significant decrease only in dysmenorrhea at 3 months...

This review article focuses on the recent printing technological progress in healthcare, underscoring the significant potential of implantable devices across diverse applications. Printing technologies have widespread use in developing health monitoring devices, diagnostic systems, and surgical devices. Recent years have witnessed remarkable progress in fabricating low-profile implantable devices, driven by advancements in printing technologies and nanomaterials. The importance of implantable biosensors and bioelectronics is highlighted, specifically exploring printing tools using bio-printable inks for practical applications, including a detailed examination of fabrication processes and essential parameters...

Recent advances have significantly enhanced the use of smartphone devices for medical diagnostics. This study uses high-resolution cameras in mobile devices to capture and process bioassay images, enabling the quantification of diverse biomarkers across a range of diagnostic tests conducted on 96-well microplates. The study evaluates the effectiveness of this technology through protein quantification techniques and immunoassays that generate colorimetric responses at specific wavelengths. It includes the assessment of bicinchoninic acid and Bradford protein quantification methods, alongside a conventional immunoassay for detecting mare antibodies in colostrum to monitor foal immunodeficiencies...

BACKGROUND: This study comprehensively examined the demographic and clinical characteristics of patients undergoing valproic acid therapy and explored their potential impact on plasma valproic acid concentrations. All enrolled patients were administered the extended-release formulation. An in-depth investigation of factors, including dose, age, sex, body mass index, co-administered medications, and laboratory test findings, was conducted to evaluate their potential influence on study outcomes...

BACKGROUND: Brexpiprazole is a second-generation antipsychotic approved in Japan in 2018; however, information on placental passage and breast milk transfer remains limited. In this report, the patient, a 30-year-old pregnant woman with schizophrenia, was medicated with brexpiprazole, risperidone, and quetiapine. METHODS: The study used high-performance liquid chromatography-tandem mass spectrometry to determine the concentrations of brexpiprazole, quetiapine, risperidone, and its active metabolite (paliperidone) in maternal and neonatal plasma, cord venous plasma, and breast milk...

WHAT WAS THE EDUCATIONAL CHALLENGE?: Diminishing emphasis on pharmacology education in medical schools has resulted in a concerning lack of prescribing knowledge among physician graduates. These concerns mirror our graduates' expressed dissatisfaction with the structure and quality of pharmacology educational experiences over the past 5 years. WHAT WAS THE SOLUTION?: PharmaCORE, a web-based instructional dashboard, was developed as an interactive faculty development tool to enhance integration and instruction of pharmacology content in pre-clinical curriculum at a US medical school...

The Tennessee Bureau of Investigation (TBI) serves all 95 counties of Tennessee, but the data included in this article is primarily focused in upper east and east Tennessee (the parts of the state included in the eastern time zone). The forensic chemistry [seized drug] unit of the TBI began reporting nitazene analogues in late 2019. The primary analogues found in forensic chemistry cases were isotonitazene and metonitazene. After discussion and review of reporting statistics, the forensic toxicology unit began to monitor for these compounds in toxicology samples by using ions characteristic with the nitazene analogues...

Research on female genital cosmetic surgery usually comes from Anglophone countries. We investigated female genital cosmetic surgery in the predominantly Muslim South-East Asian country of Indonesia, aiming to identify the procedures offered by medical clinics on Instagram, how they are justified, and what they claim to achieve; and to understand what this means for women and their bodies. The 184 eligible posts from 19 clinics between 1 January to 31 March 2021 offered vaginoplasty, labiaplasty, hymenoplasty, and other procedures...

As an essential cognitive function, attention has been widely studied and various indices based on EEG have been proposed for its convenience and easy availability for real-time attention monitoring. Although existing indices based on spectral power of empirical frequency bands are able to describe the attentional state in some way, the reliability still needs to be improved. This paper proposed a subject-specific attention index based on the weighted spectral power. Unlike traditional indices, the ranges of frequency bands are not empirical but obtained from subject-specific change patterns of spectral power of electroencephalograph (EEG) to overcome the great inter-subject variance...

Seismocardiogram (SCG) signals are noninvasively obtained cardiomechanical signals containing important features for cardiovascular health monitoring. However, these signals are prone to contamination by motion noise, which can significantly impact accuracy and robustness of the measurements. A deep learning model based on the U-Net architecture is proposed to recover SCG signals contaminated by motion noise induced by walking. The model performance was evaluated through qualitative visualization, as well as quantitative analyses...

Alzheimer's disease (AD) is a neurodegenerative disorder that can cause a significant impairment in physical and cognitive functions. Gait disturbances are also reported as a symptom of AD. Previous works have used Convolutional Neural Networks (CNNs) to analyze data provided by motion sensors that monitor Alzheimer's patients. However, these works have not explored continual learning algorithms that allow the CNN to configure itself as it receives new data from these sensors. This work proposes a method aimed at enabling CNNs to learn from a continuous stream of data from motion sensors without having full access to previous data...

Accurate and robust medical image segmentation is crucial for assisting disease diagnosis, making treatment plan, and monitoring disease progression. Adaptive to different scale variations and regions of interest is essential for high accuracy in automatic segmentation methods. Existing methods based on the U-shaped architecture respectively tackling intra- and inter-scale problem with a hierarchical encoder, however, are restricted by the scope of multi-scale modeling. In addition, global attention and scaling attention in regions of interest have not been appropriately adopted, especially for the salient features...

Applying affective computing techniques to recognize fear and combining them with portable signal monitors makes it possible to create real-time detection systems that could act as bodyguards when users are in danger. With this aim, this paper presents a fear recognition method based on physiological signals obtained from wearable devices. The procedure involves creating twodimensional feature maps from the raw signals, using data augmentation and feature selection algorithms, followed by deep learning-based classification models, taking inspiration from those used in image processing...

BACKGROUND: Coronary heart disease is one of the leading causes of mortality worldwide. Secondary prevention is essential, as it reduces the risk of further coronary events. Mobile health (mHealth) technology could become a useful tool to improve lifestyles. OBJECTIVE: This study aimed to evaluate the effect of an mHealth intervention on people with coronary heart disease who received percutaneous coronary intervention. Improvements in lifestyle regarding diet, physical activity, and smoking; level of knowledge of a healthy lifestyle and the control of cardiovascular risk factors (CVRFs); and therapeutic adherence and quality of life were analyzed...