Medical Instruments Research Articles

Long‐Term Monitoring of ApoE4 within Aqueous Humor Using Intraocular Lenses Containing Target‐Responsive Inverse Opal Hydrogel

Neurodegenerative diseases, including Alzheimer's disease (AD), pose significant challenges to global healthcare because of their irreversible postsymptomatic progression. Conventional radiographic techniques have limitations in early detection, owing to the time lapse between symptom recognition by individuals and precise inspection using medical instruments. Current research explores ophthalmic approaches to address this gap, investigating the physiological link between ocular health and brain diseases. Intraocular lenses (IOLs), widely used in cataract and refractive surgeries, provide a safe and minimally invasive platform for the continuous monitoring of neurodegenerative disease biomarkers, including those associated with AD. By integrating biomolecule‐responsive sensors with IOLs, it becomes feasible to achieve early diagnosis and long‐term, noninvasive monitoring postimplantation. Herein, a fluorescently labeled inverse opal hydrogel (FIOH) is merged with IOLs for ApoE4 detection, a key risk factor for AD. The permeability and inherent photonic properties of FIOH facilitate the cumulative enhancement of the fluorescence signal. In a simulation of the aqueous humor circulation, the detection limit for ApoE4 is determined to be 0.1 nM. Therefore, FIOH‐integrated IOLs hold promise not only for early detection but also for providing a reliable platform for the continuous, noninvasive monitoring of neurodegenerative diseases after the initial, minimally invasive implantation.

Bactericidal effect of direct and indirect plasma for medical instruments: Comparative experimental study

Bactericidal effect of direct and indirect plasma for medical instruments: Comparative experimental study

Training and education of operating room nurses in robot-assisted surgery: a systematic review.

With the introduction of robot-assisted surgery, the role and responsibility of the operating room nurses have been expanded. The surgical team for robotic-assisted surgery depends on the ability of the operating room nurses to operate and handle the robotic system before, during, and after procedures. However, operating room nurses must acquire the necessary competencies for robotic-assisted surgery. We performed a systematic review using the databases MEDLINE and EMBASE to review the evidence on educating and training operating room nurses in robot-assisted surgery. Studies describing operating room nurses' training and team-training with operating room nurses for robot-assisted surgery were included. The Medical Education Research Study Quality Instrument (MERSQI) and the Newcastle-Ottawa Scale-Education (NOS-E) were used to evaluate the quality of the included studies. We identified 3351 potential studies and included 16 in the final synthesis. Nine studies focused on team-training in robot-assisted surgery: four focused solely on training for operating room nurses, and only three on operating room nurses as first assistants in robot-assisted surgery. Most studies examined team-training in RAS, including OR nurses, focused on emergency situations and conversion to an open procedure. Only a few studies addressed other competencies relevant to OR nurses in RAS. No randomized controlled trials were identified. Only a few studies used pre- and post-testing, and only one examined clinical outcomes. The quality assessment of the included studies was moderate to low, with a median MERSQI score of 10.3 and a median NOS-E score of 2. There is sparse research on the education of operating room nurses in robot-assisted surgery, and the literature emphasizes the training of surgeons. More research is needed to develop evidence-based training for operating room nurses in robot-assisted surgery.

Impact of Skin Pigmentation on Pulse Oximetry Blood Oxygenation and Wearable Pulse Rate Accuracy: Systematic Review and Meta-Analysis.

Photoplethysmography (PPG) is a technology routinely used in clinical practice to assess blood oxygenation (SpO2) and pulse rate (PR). Skin pigmentation may influence accuracy, leading to health outcomes disparities. This systematic review and meta-analysis primarily aimed to evaluate the accuracy of PPG-derived SpO2 and PR by skin pigmentation. Secondarily, we aimed to evaluate statistical biases and the clinical relevance of PPG-derived SpO2 and PR according to skin pigmentation. We identified 23 pulse oximetry studies (n=59,684; 197,353 paired SpO2-arterial blood observations) and 4 wearable PR studies (n=176; 140,771 paired PPG-electrocardiography observations). We evaluated accuracy according to skin pigmentation group by comparing SpO2 accuracy root-mean-square values to the regulatory threshold of 3% and PR 95% limits of agreement values to +5 or -5 beats per minute (bpm), according to the standards of the American National Standards Institute, Association for the Advancement of Medical Instrumentation, and the International Electrotechnical Commission. We evaluated biases and clinical relevance using mean bias and 95% CI. For SpO2, accuracy root-mean-square values were 3.96%, 4.71%, and 4.15%, and pooled mean biases were 0.70% (95% CI 0.17%-1.22%), 0.27% (95% CI -0.64% to 1.19%), and 1.27% (95% CI 0.58%-1.95%) for light, medium, and dark pigmentation, respectively. For PR, 95% limits of agreement values were from -16.02 to 13.54, from -18.62 to 16.84, and from -33.69 to 32.54, and pooled mean biases were -1.24 (95% CI -5.31 to 2.83) bpm, -0.89 (95% CI -3.70 to 1.93) bpm, and -0.57 (95% CI -9.44 to 8.29) bpm for light, medium, and dark pigmentation, respectively. SpO2 and PR measurements may be inaccurate across all skin pigmentation groups, breaching U.S. Food and Drug Administration guidance and industry standard thresholds. Pulse oximeters significantly overestimate SpO2 for both light and dark skin pigmentation, but this overestimation may not be clinically relevant. PRs obtained from wearables exhibit no statistically or clinically significant bias based on skin pigmentation.

Materials for semiconductor nanowires in nanoscale photonic and electronic devices

Abstract Many aspects of civilization are impacted by electronic and optoelectronic equipment, including medical instruments, communications, computing, multimedia systems, and basic home appliances. the development of nanoscale devices has garnered significant attention due to the increasing demand for smaller, more powerful, and efficient systems across various industries. Nanoscale devices operate at the nanometer scale, typically involving structures and components with dimensions on the order of 1 to 100 nanometers. As a potent class of materials, semiconductor nanowires are creating a lot of new possibilities for innovative nanoscale photonic and electrical devices through carefully regulated development and organization. the exploration of electronic and optoelectronic nanodevices, along with integrated arrays, opens up a rich landscape of possibilities across various technological domains. This research not only pushes the boundaries of miniaturization but also paves the way for innovative applications in electronics, photonics, sensing, and emerging fields like quantum and neuromorphic computing that hold the potential for numerous applications in the future.

Corrosion resistance and long-term antibacterial performance of ZnO-Al2O3 nanocomposite coatings on aluminum alloy

Anodic aluminum oxide-zinc (AAO-Zn) coatings were prepared on aluminum (Al) alloy substrates through anodization and nZnO deposition. Further heat treatment at various temperature is applied to the composite coatings. Among the samples, AZ-250 sample showed lower corrosion current density (1.127 × 10−8 A/cm2) and higher charge-transfer resistance (4.65 × 105 Ω cm2) compared to the AZ-150 and AZ-350 samples. At 250 °C, a greater incorporation of nZnO into the AAO layer facilitated the fusion of ZnO with aluminum oxide, resulting in a denser and more protective coating. The antibacterial research revealed AZ-250 sample achieved a 100 % reduction of S. aureus and 97.9 % of E. coli within 2 h. Even after 40 days of air exposure, the AZ-250 sample maintained high antibacterial effectiveness due to ZnO attachment and sustained Zn2⁺ release from the nanoporous AAO structure. This nanocomposite is suitable for applications in heat exchangers, medical instrument casings, and transport structure.

Are previously validated blood pressure self-measurement devices accepted under the Universal Standard? A systematic review.

This study aimed to analyze whether oscillometric blood pressure devices validated for the general population may be considered approved under Universal Standard criteria. A systematic review was conducted, with searches in nine databases, up to September 2023, including 32 validation studies of noninvasive arm cuff devices for self-measurement. The British Hypertension Society protocol was most common (68%), followed by the Association for the Advancement of Medical Instrumentation (40%). Most devices met Universal Standard criterion 1, but only 17 (53%) met criterion 2. Few studies contained details about the choice of cuffs, the number of participants by arm circumference, or the differences between methods by cuff subgroup. Due to the considerable differences between validation protocols, 53% of the devices analyzed were approved under the Universal Standard. The study contributes to expanding the validated pool of self-measurement devices under the Universal Standard.

Radiation Detectors and Sensors in Medical Imaging.

Medical imaging instrumentation design and construction is based on radiation sources and radiation detectors/sensors. This review focuses on the detectors and sensors of medical imaging systems. These systems are subdivided into various categories depending on their structure, the type of radiation they capture, how the radiation is measured, how the images are formed, and the medical goals they serve. Related to medical goals, detectors fall into two major areas: (i) anatomical imaging, which mainly concerns the techniques of diagnostic radiology, and (ii) functional-molecular imaging, which mainly concerns nuclear medicine. An important parameter in the evaluation of the detectors is the combination of the quality of the diagnostic result they offer and the burden of the patient with radiation dose. The latter has to be minimized; thus, the input signal (radiation photon flux) must be kept at low levels. For this reason, the detective quantum efficiency (DQE), expressing signal-to-noise ratio transfer through an imaging system, is of primary importance. In diagnostic radiology, image quality is better than in nuclear medicine; however, in most cases, the dose is higher. On the other hand, nuclear medicine focuses on the detection of functional findings and not on the accurate spatial determination of anatomical data. Detectors are integrated into projection or tomographic imaging systems and are based on the use of scintillators with optical sensors, photoconductors, or semiconductors. Analysis and modeling of such systems can be performed employing theoretical models developed in the framework of cascaded linear systems analysis (LCSA), as well as within the signal detection theory (SDT) and information theory.

Fiber Bragg Grating Pulse and Systolic Blood Pressure Measurement System Based on Mach-Zehnder Interferometer.

A fiber Bragg grating (FBG) pulse and systolic blood pressure (SBP) measurement system based on the edge-filtering method is proposed. The edge filter is the Mach-Zehnder interferometer (MZI) fabricated by two fiber couplers with a linear slope of 52.45 dBm/nm. The developed system consists of a broadband light source, an edge filter, fiber Bragg gratings (FBGs), a coarse wavelength-division multiplexer (CWDM), and signal-processing circuits based on a field-programmable gate array (FPGA). It can simultaneously measure pulse pulsations of the radial artery in the wrist at three positions: Cun, Guan and Chi. The SBP can be calculated based on the pulse transit time (PTT) principle. The measurement results compared to a standard blood pressure monitor showed the mean absolute error (MAE) and standard deviation (STD) of the SBP were 0.93 ± 3.13 mmHg. The system meets the requirements of the Association for the Advancement of Medical Instrumentation (AAMI) equipment standards. The proposed system can achieve continuous real-time measurement of pulse and SBP and has the advantages of fast detection speed, stable performance, and no compression sensation for subjects. The system has important application value in the fields of human health monitoring and medical device development.

BP-Diff: a conditional diffusion model for cuffless continuous BP waveform estimation using U-Net.

Continuous monitoring of blood pressure (BP) is crucial for daily healthcare. Although invasive methods provide accurate continuous BP measurements, they are not suitable for routine use. Photoplethysmography (PPG), a non-invasive technique that detects changes in blood volume within the microcirculation using light, shows promise for BP measurement. The primary goal of this study is to develop a novel cuffless method based on PPG for accurately estimating continuous BP.
Approach. We introduce BP-Diff, an end-to-end method for cuffless continuous BP waveform estimation utilizing a conditional diffusion probability model combined with a U-Net architecture. This approach takes advantage of the stochastic properties of diffusion models and the strong feature representation capabilities of U-Net. It integrates the continuous BP waveform as the initial status and uses the PPG signal and its derivatives as conditions to guide the training and sampling process.
Main results. BP-Diff was evaluated using both uncalibrated and calibrated schemes. The results indicate that, when uncalibrated, BP-Diff can accurately track BP dynamics, including peak and valley positions, as well as timing. After calibration, BP-Diff achieved highly accurate BP estimations. The mean absolute error (MAE) of the estimated BP waveforms, along with the systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) from the calibrated BP-Diff model, were 2.99 mmHg, 2.6 mmHg, 1.4 mmHg, and 1.44 mmHg, respectively. Consistency tests, including Bland-Altman analysis and Pearson correlation, confirmed its high reliability compared to reference BP. BP-Diff meets the American Association for Medical Instrumentation (AAMI) standards and has achieved a Grade A from the British Hypertension Society (BHS).
Significance. This study utilizes PPG signals to develop a novel cuffless continuous BP measurement method, demonstrating superiority over existing approaches. The method is suitable for integration into wearable devices, providing a practical solution for continuous BP monitoring in everyday healthcare.

Comparison of the ClearSight™ finger cuff monitor versus invasive arterial blood pressure measurement in elective cardiac surgery patients: a prospective observational study.

To determine the acceptability of the ClearSight™ system (Edwards Lifesciences Corp., Irvine, CA, USA) for continuous blood pressure monitoring during elective cardiac surgery compared with arterial catheterization. We enrolled 30 patients undergoing elective cardiac surgery in a prospective observational study. Blood pressure measurements were recorded every 10 sec intraoperatively. We determined agreement based on the Association for the Advancement of Medical Instrumentation (AAMI) recommendations. Statistical analysis included fixed bias (difference of measurements between methods), percentage error (accuracy between ClearSight measurement and expected measurement from arterial line), and interchangeability (ability to substitute ClearSight monitor without effecting overall outcome of analysis). We used a paired samples t test to compare the time required for placing each monitor. We found fixed bias in the differences between the ClearSight monitor and invasive arterial blood pressure measurement in systolic blood pressure (SBP; mean difference, 8.7; P < 0.001) and diastolic blood pressure (DBP; mean difference, -2.2; P < 0.001), but not in mean arterial pressure (MAP; mean difference, -0.5; P < 0.001). Bland-Altman plots showed that the means of the limits of agreement were greater than 5mm Hg for SBP, DBP, and MAP. The percentage errors for SBP, DBP, and MAP were lower than the cutoff we calculated from the invasive arterial blood pressure measurements. Average interchangeability rates were 38% for SBP, 50% for DBP, and 50% for MAP. Placement of the ClearSight finger cuff was significantly faster compared with arterial catheterization (mean [standard deviation], 1.7 [0.6] min vs 5.6 [4.1] min; P < 0.001). In this prospective observational study, we did not find the ClearSight system to be an acceptable substitute for invasive arterial blood pressure measurement in elective cardiac surgery patients according to AAMI guidelines. Nevertheless, based on statistical standards, there is evidence to suggest otherwise. ClinicalTrials.gov ( NCT05825937 ); first submitted 11 April 2023.

Design and validation of a method for evaluating medical device cleanliness by recovering and quantifying residual proteins on stainless plates

We recently reported a method for recovering and quantifying residual proteins bound to surfaces of various medical instruments via thermal coagulation under neutral pH and room temperature. The method effectively recovered and solubilised coagulated proteins at high temperatures in dry and humid conditions, with a protein recovery rate of > 90%. This study validated the previous method by comparing residual protein recovery from test samples using a conventional extraction solution (1% SDS, [pH 11.0]) and proposed solution (1% SDS, 10 mM TCEP, and 10 mM HEPES [pH 7.0]). To mimic soiled medical equipment, pseudo-blood-contaminated stainless steel plates were prepared. Residual protein was recovered using conventional and proposed solutions under varying temperature and humidity conditions. Quantitative protein recovery limits were determined at nine facilities. Compared with the conventional solution, the proposed solution recovered proteins more effectively from samples processed at temperatures > 60 °C. However, low recovery rates were observed for samples processed at 95 °C, possibly owing to differences in protein adhesion due to sample and plate-surface properties. Our findings present a method for quantifying residual proteins on medical instruments exposed to high temperatures during use or disinfection. Further studies should standardise test soiling conditions, materials, and solutions to evaluate cleaning methods.

A paralleled CNN and Transformer network for PPG-based cuff-less blood pressure estimation

Cuff-less blood pressure measurement plays a pivotal part in hypertension diagnosis and prevention. By employing deep learning algorithms, blood pressure estimation applying photoplethysmography (PPG) signals has achieved remarkable improvements and attracted growing attention. However, most existing methods utilize the PPG signal emphasized on localized feature learning, often neglecting the global features in the temporal data. To tackle the issue, we propose a novel architecture. It leverages a parallel processing approach by using Convolutional Neural Network for extracting local features and simultaneously employing Transformer to capture global features. The feature fusion block integrates the features using spatial and channel attention. The blood pressure values are regressed by two fully connected layers. To verify the performance of our method, we conduct evaluations on the Medical Information Mart for Intensive Care (MIMIC) database. On the MIMIC database, our algorithm demonstrates exceptional performance. For Diastolic Pressure, Mean Arterial Pressure, and Systolic Pressure, the mean absolute errors are 2.36 mmHg, 2.03 mmHg, and 4.44 mmHg, respectively. This performance aligns with the rigorous criteria required by an Association for the Advancement of Medical Instrumentation (AAMI) and receives a Grade A rating in accordance with the British Hypertension Society (BHS) standard.

Continuous blood pressure monitoring based on transformer encoders and stacked attention gated recurrent units

Continuous blood pressure monitoring (CBPM) is critical to support the accurate prevention and reliable treatment of cardiovascular diseases. To achieve efficient multi-information interaction and further improve the monitoring performance, this research proposes an intelligent model based on transformer encoders and stacked attention gated recurrent units (TE-SAGRU) for CBPM. Long-term multi-source feature sequences with rich information are initially extracted from photoplethysmography (PPG) and electrocardiography (ECG) signals. The paralleled transformer encoders are constructed for different source feature sequences to obtain high-level feature representations and preserve respective long-term independence. The multiple stacked attention gated recurrent units are cross-connected for multi-interactive feature fusion and promoting complementarity effects of multi-source features on CBPM. Comprehensive comparison experiments are carried out to validate the effectiveness of the TE-SAGRU model, using the dataset with 1000 subjects derived from the MIMIC-III database. The continuous monitoring errors of the TE-SAGRU model for systolic blood pressure (SBP) and diastolic blood pressure (DBP) are 3.91 ± 5.65 mmHg and 2.29 ± 3.01 mmHg. The monitored results pass the requirement of the Association for the Advancement of Medical Instrumentation (AAMI) standard and achieve Grade A of the British Hypertension Society (BHS) protocol.

Advances in Ultrasound-Guided Surgery and Artificial Intelligence Applications in Musculoskeletal Diseases.

Ultrasound imaging is a vital imaging tool in musculoskeletal medicine, with the number of publications on ultrasound-guided surgery increasing in recent years, especially in minimally invasive procedures of sports, foot and ankle, and hand surgery. However, ultrasound imaging has drawbacks, such as operator dependency and image obscurity. Artificial intelligence (AI) and deep learning (DL), a subset of AI, can address these issues. AI/DL can enhance screening practices for hip dysplasia and osteochondritis dissecans (OCD) of the humeral capitellum, improve diagnostic accuracy for carpal tunnel syndrome (CTS), and provide physicians with better prognostic prediction tools for patients with knee osteoarthritis. Building on these advancements, DL methods, including segmentation, detection, and localization of target tissues and medical instruments, also have the potential to allow physicians and surgeons to perform ultrasound-guided procedures more accurately and efficiently. This review summarizes recent advances in ultrasound-guided procedures for musculoskeletal diseases and provides a comprehensive overview of the utilization of AI/DL in ultrasound for musculoskeletal medicine, particularly focusing on ultrasound-guided surgery.

Improvement of executive functions and math-ematical skills through fitness/physical activity in elementary school children: a systematic review

Executive functions (EF) play a fundamental role in the acquisition of learning, especially in mathematics. The literature seems to indicate that fitness and physical activity (PA) have an important impact on cognition, including EF. Although the relationship between these variables seems evident, few studies have investigated the mediation role of EF between fitness/PA and mathematical skills (MS). The purpose of this systematic review was analysing the relationship between EF, fitness/PA and mathematical skills (MS) in children aged 6 to 12 aged. The systematic review (CRD42021237840) used information from Pubmed, WOS and ERIC published between 2010 and 2021. Eligibility criteria were: scientific articles, in English, children aged 5-16 years, assessment of EF using standardised tests and inclusion of the three variables (fitness/PA, EF and MS). For assess risk of bias was used the Medical Education Research Study Quality Instrument (MERSQI). From the selected articles were extracted the following data: country, age, type of study, characteristics of the sample, evaluation instruments, physical activity program and results. From the 387 initial records, 21 studies with a total of 8601 participants have been selected to be included in the systematic review. Only one of the studies analysed shows a clear causal relationship between the three variables, while five show a linear relationship. EF could act as a mediator between fitness and MS but not between PA and MS, although long-term randomised and controlled intervention studies are needed.

Microbiological evaluation of ultraviolet C light-emitting diodes for disinfection of medical instruments

BackgroundDespite the many guidelines for reprocessing of medical instruments, challenges persist such as microbial resistance to biocides, corrosive effects on materials, and time-consuming reprocessing procedures. Ultraviolet (UV) C light-emitting diode (LED) chambers might provide a solution but the integration in healthcare is still in its infancy. Here, we evaluated the efficacy of a novel ZAPARAY™ UVC LED chamber as a time and energy-efficient alternative for reprocessing of medical instruments for which current disinfection protocols exhibit limitations. MethodsWe verified the disinfection efficacy of the UVC LED chamber on a Petri dish and contaminated several medical devices with Staphylococcus aureus ATCC 25923. The bacterial reduction was assessed after 5 min of UVC LED exposure. Additionally, we investigated the impact of rinsing before UVC exposure. ResultsWe demonstrated a bacterial reduction of 9 log10 on a Petri dish. Non-rinsed dental tools exhibited varied reduction levels ranging from a 3.23 log10 to a 6.25 log10 reduction. Rinsing alone yielded an average reduction of 2.7 log10 and additional UVC exposure further reduced the bacterial load by an average of 3.65 log10. We showed an average 4.90 log10 reduction on thermistors, 2 log10 or less on orthodontic pliers, and no reduction on handpieces. ConclusionsThis study demonstrates that UVC LED chambers may be used as a standardized substitute for specific (manual) disinfection procedures of certain medical devices, offering a time-efficient and more sustainable alternative. However, its use should be preceded by efficacy testing for each specific type of instrument.

Evaluation of Attitudes Towards Safe Use of Needle-Stick and Sharp Medical Instruments of Healthcare Workers in a Public Hospital

Objective: This cross-sectional and descriptive study was conducted to evaluate the attitudes of healthcare workers towards the safe use of needle-stick and sharp medical instruments. Methods: The study was conducted cross-sectionally on 248 healthcare workers. Data were collected face-to-face using the "Healthcare Worker Identification Form" and the "Healthcare Workers' Attitude Scale Towards Safe Use of Needle-Stick and Sharp Medical Instruments". Results: The total score and cognitive and affective subscale mean scores of the Attitudes Toward Safe Use of Needle-Stick and Sharp Medical Instruments Scale were statistically significantly higher in women than in men (p&amp;lt;0.05). The mean scores of healthcare workers who were having night shift were lower than those who were not having night shift (p&amp;lt;0.05). According to the results of linear regression analysis, gender, educational status, occupation, and exposure to injury were determined as factors independently affecting attitudes towards safe use of needle-stick and sharp medical instruments (p&amp;lt;0.05). Conclusion: In this study, it was found that the attitudes of male healthcare workers, those who were having night shift, those who experienced sharps injuries, midwives and health officers towards safe use of needle-stick and sharp medical instruments were low. In line with these results, it is recommended to organize in-service training programs for the prevention of sharps injuries, to pay attention to standard prevention practices and to actively use the reporting system, taking into account the personal (gender) and professional characteristics of healthcare workers (occupation, having a needle-stick and sharp injury, postgraduate education status, having night shift, etc.).

GAN-SkipNet: A Solution for Data Imbalance in Cardiac Arrhythmia Detection Using Electrocardiogram Signals from a Benchmark Dataset

Electrocardiography (ECG) plays a pivotal role in monitoring cardiac health, yet the manual analysis of ECG signals is challenging due to the complex task of identifying and categorizing various waveforms and morphologies within the data. Additionally, ECG datasets often suffer from a significant class imbalance issue, which can lead to inaccuracies in detecting minority class samples. To address these challenges and enhance the effectiveness and efficiency of cardiac arrhythmia detection from imbalanced ECG datasets, this study proposes a novel approach. This research leverages the MIT-BIH arrhythmia dataset, encompassing a total of 109,446 ECG beats distributed across five classes following the Association for the Advancement of Medical Instrumentation (AAMI) standard. Given the dataset’s inherent class imbalance, a 1D generative adversarial network (GAN) model is introduced, incorporating the Bi-LSTM model to synthetically generate the two minority signal classes, which represent a mere 0.73% fusion (F) and 2.54% supraventricular (S) of the data. The generated signals are rigorously evaluated for similarity to real ECG data using three key metrics: mean squared error (MSE), structural similarity index (SSIM), and Pearson correlation coefficient (r). In addition to addressing data imbalance, the work presents three deep learning models tailored for ECG classification: SkipCNN (a convolutional neural network with skip connections), SkipCNN+LSTM, and SkipCNN+LSTM+Attention mechanisms. To further enhance efficiency and accuracy, the test dataset is rigorously assessed using an ensemble model, which consistently outperforms the individual models. The performance evaluation employs standard metrics such as precision, recall, and F1-score, along with their average, macro average, and weighted average counterparts. Notably, the SkipCNN+LSTM model emerges as the most promising, achieving remarkable precision, recall, and F1-scores of 99.3%, which were further elevated to an impressive 99.60% through ensemble techniques. Consequently, with this innovative combination of data balancing techniques, the GAN-SkipNet model not only resolves the challenges posed by imbalanced data but also provides a robust and reliable solution for cardiac arrhythmia detection. This model stands poised for clinical applications, offering the potential to be deployed in hospitals for real-time cardiac arrhythmia detection, thereby benefiting patients and healthcare practitioners alike.

Synthesis of Graphene@C3N4-Cu Beads Nanocomposites and their Antimicrobial Efficacy Against Drug-Resistant Bacteria and Fungi.

Increased intake of drugs worldwide and the subsequent advent of resistance to existing antibiotics have globally threatened health organizations. To combat the problem of these drug-resistant infections, as an alternative approach, graphene (GN)-related nanomaterials have attracted significant interest because of their effective anti-microbial potential. The present study shows the synthesis and characterization of nanocomposite of GN with carbon nitride viz. g- C3N4, g-C3N4-Cu, and GN@g-C3N4-Cu. Further, we investigated the anti-microbial potential of these nanocomposites against strains of Gram-negative and Gram-positive bacteria, viz., a multidrug- resistant strain of Pseudomonas aeruginosa (MDRPA), a methicillin-resistant strain of Staphylococcus aureus ATCC33593 (MRSA), and an azole-sensitive fungal strain (Candida albicans ATCC14053). The morphological characterization of GN@g-C3N4-Cu nanocomposite was executed by scanning electron microscopy, whereas the elemental analysis and their distribution were studied by energy-dispersive X-ray spectroscopy and elemental mapping methods. Furthermore, the anti-microbial and antibiofilm efficacies of g-C3N4, g-C3N4-Cu, and GN@g-C3N4-Cu nanocomposites were evaluated by disc diffusion, two-fold serial micro broth dilution, and 96 well microtiter plate methods. The ternary g-C3N4-Cu@GN, apart from the structures of g-C3N4-Cu, showed big sheets of GN. The observance of C, N, O, and Cu in the elemental analysis, as well as their uniform distribution in the mapping, indicated the successful fabrication of g-C3N4-Cu@GN. GN@g-C3N4-Cu followed by g-C3N4-Cu and (g-C3N4) exhibited significantly higher antimicrobial activity (zone of inhibition from 14.33 to 49.33 mm) against both the drug-resistant bacterial strains and azole-sensitive C. albicans. MICs of nanocomposites ranged from 32 -256 μg/ml against the tested strains. Whereas all three nanocomposites at sub-MICs (0.25 A- and 0.5 A- MICs) showed concentration- dependent inhibition of biofilm formation in MDRPA, MRSA, and C. albicans by allowing 11.35% to 32.59% biofilm formation. Our study highlights the enhanced efficiency of GN@g-C3N4-Cu nanocomposites as potential anti-microbial and antibiofilm agents to overcome the challenges of multi-drug-resistant bacteria and azole-sensitive fungi. Such kind of nanocomposites could be used to prevent nosocomial infections if coated on medical devices and food manufacturing instruments.