Biomedical engineering

Functional agents have been verified to efficiently enhance device performance of perovskite solar cells (PSCs) through surface engineering. However, the influence of intrinsic characteristics of molecules on final device performance has been overlooked. Here, we develop a surface reconstruction strategy to enhance the efficiency of inverted PSCs by mitigating the adverse effects of lead chelation (LC) molecules. We choose bathocuproine (BCP), as the representative of LC molecules for its easy accessibility and outstanding optoelectronic properties...

Endodontic therapy, while generally successful, is primarily limited to mature teeth, hence the pressing need to explore regenerative approaches. Gelatin methacryloyl (GelMA) hydrogels have emerged as pivotal biomaterials, promising a bright future for dental pulp regeneration. Despite advancements in tissue engineering and biomaterials, achieving true pulp tissue regeneration remains a formidable task. GelMA stands out for its injectability, rapid gelation, and excellent biocompatibility, serving as the cornerstone of scaffold materials...

Functional connectivity (FC) networks, built from analyses of resting-state magnetic resonance imaging (rs-fMRI), serve as efficacious biomarkers for identifying Autism Spectrum Disorders (ASD) patients. Given the neurobiological heterogeneity across individuals and the unique presentation of ASD symptoms, the fusion of individualized information into diagnosis becomes essential. However, this aspect is overlooked in most methods. Furthermore, the existing methods typically focus on studying direct pairwise connections between brain ROIs, while disregarding interactions between indirectly connected neighbors...

Prostate cancer screening often relies on cost-intensive MRIs and invasive needle biopsies. Transrectal ultrasound imaging, as a more affordable and non-invasive alternative, faces the challenge of high inter-class similarity and intra-class variability between benign and malignant prostate cancers. This complexity requires more stringent differentiation of subtle features for accurate auxiliary diagnosis. In response, we introduce the novel Deep Augmented Metric Learning (DAML) network, specifically tailored for ultrasound-based prostate cancer classification...

Despite the dominance of unsupervised and self-supervised anomaly detection methods in the current satellite fault diagnosis domain, supervised anomaly detection offers a superior alternative for high-sensitivity detection and lightweight deployment requirements specific to subsystems or components, such as attitude control systems (ACSs). This article addresses the issues of over-design and insufficient accuracy in the CNN network design for satellite ACS fault diagnosis by introducing the modified particle swarm optimization-advanced convolution blocks-based CNN (MPSO-ACBCNN) method...

Approximation biases of value functions are considered a key problem in reinforcement learning (RL). In particular, existing RL algorithms are hindered by overestimation and underestimation biases, i.e., value mismatching between RL's actual returns and action-value approximations limits the performance of RL algorithms. In this article, we first develop a new synthesis loss function for RL's action-value estimation integrating a regularization term and a modified "clipped double Q -learning" structure for solving overestimation and underestimation biases...

The reliability of automated image interpretation of point-of-care (POC) echocardiography scans depends on the quality of the acquired ultrasound data. This work reports on the development and validation of spatiotemporal deep learning models to assess the suitability of input ultrasound cine loops collected using a handheld echocardiography device for processing by an automated quantification algorithm (e.g. ejection fraction estimation). POC echocardiograms (n=885 DICOM cine loops from 175 patients) from two sites were collected using a handheld ultrasound device and annotated for image quality at the frame-level...

OBJECTIVES: Surgery planning for liver tumour is carried out using contrast enhanced computed tomography (CECT) images to determine the optimal resection strategy and to assess the volume of liver and tumour. Current surgery planning tools interpret even the functioning liver cells present within the tumour boundary as tumour. Plain CT images provide inadequate information for treatment planning. This work attempts to address two shortcomings of existing surgery planning tools: (i) to delineate functioning liver cells from the non-functioning tumourous tissues within the tumour boundary and (ii) to provide 3D visualization and actual tumour volume from the plain CT images...

Bacterial exopolysaccharides (EPS) are an emerging class of biopolymers with extensive applications in different fields due to their versatile physico-chemical and biological properties. The role of EPS in healing of different wound types is gaining interest in the tissue engineering sector. Burn is one of the devitalizing injuries that causes greater physical harm and can be fatal. Appropriate treatment modalities have to be followed for faster healing outcomes and to minimize the risk. In this study, a bacterial EPS (EPS-H29) from the marine bacterium Halomonas malpeensis YU-PRIM-29 T was used to treat the burn wound in vivo...

This study assessed the efficacy of an Ammodaucus leucotrichus seed extract to treat rheumatoid arthritis in rat models of this disease. Rheumatoid arthritis was induced in rats using two methods: immunization with 100 µL of Complete Freund Adjuvant (CFA) and immunization with 100 µL of a 3 mg/ml solution of type II collagen (CII) from chicken cartilage. The therapeutic potential of the extract was assessed at different doses (150, 300, and 600 mg/kg/day for 21 days in the CII-induced arthritis model and for 14 days in the CFA-induced arthritis model) and compared with methotrexate (MTX; 0...

Surface electromyography (sEMG) signal is a kind of physiological signal reflecting muscle activity and muscle force. At present, the existing methods of recognizing human motion intention need more than two sensors to recognize more than two kinds of movements, the sensor pasting positions are special, and the hardware conditions for execution are high. In this work, a real-time motion intention recognition method based on Morse code is proposed and applied to the mechanical hand. The short-time and long-term muscle contraction signals collected by a single sEMG sensor were extracted and encoded with the Morse code method, and then the developed mapping method from Morse code to six hand movements were used to recognize hand movements...

Electroencephalogram (EEG) signals are derived from the central nervous system and inherently difficult to camouflage, leading to the recent popularity of EEG-based emotion recognition. However, due to the non-stationary nature of EEG, inter-subject variabilities become obstacles for recognition models to well adapt to different subjects. In this paper, we propose a novel approach called semi-supervised bipartite graph construction with active EEG sample selection (SBGASS) for cross-subject emotion recognition, which offers two significant advantages...

Neurodegenerative diseases often exhibit a strong link with sleep disruption, highlighting the importance of effective sleep stage monitoring. In this light, automatic sleep stage classification (ASSC) plays a pivotal role, now more streamlined than ever due to the advancements in deep learning (DL). However, the opaque nature of DL models can be a barrier in their clinical adoption, due to trust concerns among medical practitioners. To bridge this gap, we introduce SleepBoost, a transparent multi-level tree-based ensemble model specifically designed for ASSC...

We present a liquid precursor for 3D printing ultramicroporous carbons (pore width < 0.7 nm) to create a novel in-plane capacitive-analogue of semiconductor-based diodes (CAPodes). This proof-of-concept integrates functional EDLCs into microstructured iontronic devices. The working principle is based on selective ion-sieving, controlling the size of the electrolyte ions and the nanoporous sieving carbon's pore size. By blocking bulky electrolyte ions from entering the sub-nanometer pores, a unidirectional charging characteristic with controllable ion flux is achieved, leading to diodic U-I characteristics with high rectification ratio...

INTRODUCTION: Due to the increasing prevalence of immune-mediated diseases such as psoriasis, lichen planus, rheumatoid arthritis and inflammatory bowel disease, dermatologists have turned to new biologic drugs known as DMARDs (disease-modifying anti-rheumatic drugs) in recent years. AREAS COVERED: In this study, we evaluate the immune-mediated dermatological side effects of DMARDS by reviewing and analyzing previous peer-reviewed research on the effects of TNF-α inhibitors in the treatment of skin diseases, as well as adverse effects of these drugs and some of the main causes of these effects...

The tunable properties of stimuli-responsive copolymers or hydrogels enable their application in different fields such as biomedical engineering, tissue engineering, or even drug release. Here we introduce a new PNIPAM-based triblock copolymer material comprising a controlled amount of a novel hydrophobic crosslinker 2,4'-diacryloyloxy benzophenone (DABP) and acrylic acid (AAc) to achieve lower critical solution temperature (LCST) between ambient and body temperatures. The dual stimuli-responsive p(NIPAM- co -DABP- co -AAc) triblock copolymer material and hydrogel were synthesized, and their temperature and pH-responsive behaviors were systematically investigated...

Acute kidney injury (AKI) is a life-threatening disease primarily caused by renal ischemia-reperfusion (I/R) injury, which can result in renal failure. Currently, growth factor therapy is considered a promising and effective approach for AKI treatment. Basic fibroblast growth factor (bFGF), an angiogenic factor with potent activity, efficiently stimulates angiogenesis and facilitates regeneration of renal tissue. However, the unrestricted diffusion of bFGF restricts its clinical application in AKI treatment...

Microparticle rotation is an important process in biomedical engineering, such as biosensors, cell injection or cell morphology. Single particle rotation has been widely investigated, while rotation of particle chains has gained rare attention. In this paper, we utilize a noncontact manipulation method to rotate microparticle chains via electrorotation by designing an octuple-electrode array (OEA). Finite element simulations were conducted for analyzing the desired electrode field and optimizing the structure of microelectrode pairs...

This study aimed to explore the variability in nasal airflow patterns among different sexes and populations using computational fluid dynamics (CFD). We focused on evaluating the universality and applicability of dimensionless parameters R (bilateral nasal resistance) and ϕ (nasal flow asymmetry), initially established in a Caucasian Spanish cohort, across a broader spectrum of human populations to assess normal breathing function in healthy airways. In this retrospective study, CT scans from Cambodia (20 males, 20 females), Russia (20 males, 18 females), and Spain (19 males, 19 females) were analyzed...

In the field of bone tissue engineering, recently developed Zn alloy scaffolds are considered potential candidates for biodegradable implants for bone regeneration and defect reconstruction. However, the clinical success of these alloys is limited due to their insufficient surface bioactivities. Further, the higher concentration of Zn2+ produced during degradation promotes antibacterial activity, but deteriorates osteogenic properties. This study fabricated an Azadirachta indica (neem)-assisted brushite-hydroxyapatite (HAp) coating on the recently developed Zn-2Cu-0...