miRNA-based electrochemical biosensors for ovarian cancer.

Ovarian cancer, a prevalent and deadly cancer among women, presents a significant challenge for early detection due to its heterogeneous nature. MicroRNAs, short non-coding regulatory RNA fragments, play a role in various cellular processes. Aberrant expression of these microRNAs has been observed in the carcinogenesis-related processes of many cancer types. Numerous studies highlight the critical role of microRNAs in the initiation and progression of ovarian cancer. Given their clinical importance and predictive value, there has been considerable interest in developing simple, prompt, and sensitive miRNA biosensor strategies. Among these, electrochemical sensors have demonstrated advantageous characteristics such as simplicity, sensitivity, low cost, and scalability. These microRNA-based electrochemical biosensors are valuable tools for early detection and point-of-care applications. This article discusses the potential role of microRNAs in ovarian cancer and recent advances in the development of electrochemical biosensors for miRNA detection in ovarian cancer samples.

A novel electrochemical sensor for rapid detection of sulfathiazole by integrating [(4,4'-bipy/P2Mo17Co)n] modified electrode.

In this study, we focused on the successful construction of [(4,4'-bipy/P2Mo17Co)6] modified electrodes using the layer-by-layer assembly method for the sensitive detection of sulfathiazole (ST). The redox reaction between ST and the metal ions in the modified layer leads to the transfer of electrons, resulting in the generation of the electrical signal. The introduction of 4,4'-bipyridine (4,4'-bipy) enhanced the molecular recognition of ST by the modified electrode. Under the combined effect of P2Mo17Co and 4,4'-bipy, the sensor exhibited good performance for ST detection (LOD: 0.5616 µM, linear ST concentration range: 0-50 µM). The spiked recoveries of the two groups were 84.4%-103.2% and 90.9%-109.4% for the determination of ST residues in large yellow croaker and South American white shrimp, respectively. In addition, the electrode showed excellent performance in terms of stability, reproducibility, and anti-interference ability.

Hemiporphycene: A pH-tunable specific probe for Zn2+ and Cu2.

Porphyrins and their isomers possess high affinity towards the formation of complexes with metal cations, but their use for the determination of metal cations is rather limited, due to low selectivity. In this study, we have investigated the unsubstituted hemiporphycene, which shows a highly irregular shape of the inner cavity, and very different reactivity with various metal cations in methanol:water solutions. It was found that hemiporphycene can act as a pH-tunable specific probe for the determination of Zn2+ at pH 8.6 and specific for Cu2+ detection at pH 5.5.

Recent advances in electrochemical approaches for detection of nitrite in food samples.

Nitrite is a common ingredient in the industry and agriculture; it is everywhere, like water, food, and surroundings. Recently, several approaches have been developed to measure the nitrite levels. So, this review was presented as a summary of many approaches utilized to detect the nitrite. Furthermore, the types of information that may be acquired using these methodologies, including optic and electrical signals, were discussed. In electrical signal methods, electrochemical sensors are usually developed using different materials, including carbon, polymers, oxides, and hydroxides. At the same time, optic signals receiving techniques involve utilizing fluorescence chromatography, absorption, and spectrometry instruments. Furthermore, these methodologies' benefits, drawbacks, and restrictions are examined. Lastly, due to the efficiency and fast means of electrochemical detectors, it was suggested that they can be used for detecting nitrite in food safety. Futuristic advancements in the techniques used for nitrite determination are subsequently outlined.

Single-Atom Catalysts in Conductive Metal-Organic Frameworks: Enabling Reversible Gas Sensing at Room Temperature.

Conductive metal-organic frameworks (cMOFs) offer high porosity and electrical conductivity simultaneously, making them ideal for application in chemiresistive sensors. Recently, incorporating foreign elements such as catalytic nanoparticles into cMOFs has become a typical strategy to enhance their sensing properties. However, this approach has led to critical challenges, such as pore blockage that impedes gas diffusion, as well as limited improvement in reversibility. Herein, single-atom catalyst (SAC)-functionalized cMOF is presented as a robust solution to the current limitations. Facile functionalization of SACs in a cMOF can be achieved through electrochemical deposition of metal precursors. As a proof of concept, a Pd SAC-functionalized cMOF is synthesized. The Pd SACs are stabilized at the interplanar sites of cMOF with Pd-N4 coordination while preserving the porosity of the MOF matrix. Notably, the microenvironment created by Pd SACs prevents irreversible structural distortion of cMOFs and facilitates a reversible charge transfer with NO2. Consequently, the cMOF exhibits a fully recoverable NO2 response, which was not previously attainable with the nanoparticle functionalization. Additionally, with the combination of preserved porosity for gas diffusion, it demonstrates the fastest level of response and recovery speed compared to other 2D-cMOFs of this class.

From Friction to Function: A High-Voltage Sliding Triboelectric Nanogenerator for Highly Efficient Energy Autonomous IoTs and Self-Powered Actuation.

An advanced energy autonomous system that simultaneously harnesses and stores energy on the same platform offers exciting opportunities for the near-future self-powered miniature electronics. However, achieving optimal synchronization between the power output of an energy harvester and the storage unit or integrating it seamlessly with real-time microelectronics to build a highly efficient energy autonomous system remains challenging. Herein, a unique bimetallic layered double hydroxide (LDH) based tribo-positive layer is introduced for a high-voltage sliding triboelectric nanogenerator (S-TENG) with an output voltage of ≈1485 V and power output of 250 µW, respectively. To demonstrate the potential of a self-charging power system, S-TENG is integrated with on-chip micro-supercapacitors (MSCs) as a storage unit. The MSC array effectively self-charged up to 4.8 V (within 220s), providing ample power to support micro-sensory systems. In addition, by utilizing the high-voltage output of the S-TENG, the efficient operation of electrostatic actuators and digital microfluidic (DMF) systems driven directly by simple mechanical motion is further demonstrated. Overall, this work can provide a solid foundation for the advancement of next-generation energy-autonomous systems.

Advancements in Textile-Based sEMG Sensors for Muscle Fatigue Detection: A Journey from Material Evolution to Technological Integration.

Textile-based surface electromyography (sEMG) electrodes have emerged as a prominent tool in muscle fatigue assessment, marking a significant shift toward innovative, noninvasive methods. This review examines the transition from metallic fibers to novel conductive polymers, elastomers, and advanced material-based electrodes, reflecting on the rapid evolution of materials in sEMG sensor technology. It highlights the pivotal role of materials science in enhancing sensor adaptability, signal accuracy, and longevity, crucial for practical applications in health monitoring, while examining the balance of clinical precision with user comfort. Additionally, it maps the global sEMG research landscape of diverse regional contributors and their impact on technological progress, focusing on the integration of Eastern manufacturing prowess with Western technological innovations and exploring both the opportunities and challenges in this global synergy. The integration of such textile-based sEMG innovations with artificial intelligence, nanotechnology, energy harvesting, and IoT connectivity is also anticipated as future prospects. Such advancements are poised to revolutionize personalized preventive healthcare. As the exploration of textile-based sEMG electrodes continues, the transformative potential not only promises to revolutionize integrated wellness and preventive healthcare but also signifies a seamless transition from laboratory innovations to real-world applications in sports medicine, envisioning the future of truly wearable material technologies.

Luminescent Ln(III)-Metallopeptide Sensors for Monitoring Pseudomonas aeruginosa Elastase B Activity in Complex Biological Media.

The detection and monitoring of Pseudomonas aeruginosa and its virulence factors, such as the LasB protease, are crucial for managing bacterial infections. Traditional fluorescent sensors for this protease face limitations in bacterial cultures due to interference from pigments like pyoverdine secreted by this opportunistic pathogen. We report here a Ln(III)-metallopeptide that combines a DO3A-Ln(III) complex and a sensitizing unit via a short peptide sequence as a simple, tunable, and selective probe for detecting P. aeruginosa's LasB. The probe's luminescence switches off in the presence of P. aeruginosa's secretome due to LasB cleavage but remains stable in other bacterial environments, such as non-LasB-secreting P. aeruginosa strains or E. coli cultures. It also resists degradation by other proteases, like human leukocyte elastase and trypsin, and remains stable in the presence of bioanalytes related to P. aeruginosa infections, such as glutathione, H2O2, and pyocyanin, and in complex media like FBS. Importantly, time-gated experiments completely remove the background fluorescence of P. aeruginosa pigments, thus demonstrating the potential of the developed Ln(III)-metallopeptide for real-time monitoring of LasB activity in bacterial cultures.

Central Hemodynamic and Thermoregulatory Responses to Food Intake as Potential Biomarkers for Eating Detection: Systematic Review.

BACKGROUND: Diet-related diseases, such as type 2 diabetes, require strict dietary management to slow down disease progression and call for innovative management strategies. Conventional diet monitoring places a significant memory burden on patients, who may not accurately remember details of their meals and thus frequently falls short in preventing disease progression. Recent advances in sensor and computational technologies have sparked interest in developing eating detection platforms. OBJECTIVE: This review investigates central hemodynamic and thermoregulatory responses as potential biomarkers for eating detection. METHODS: We searched peer-reviewed literature indexed in PubMed, Web of Science, and Scopus on June 20, 2022, with no date limits. We also conducted manual searches in the same databases until April 21, 2024. We included English-language papers demonstrating the impact of eating on central hemodynamics and thermoregulation in healthy individuals. To evaluate the overall study quality and assess the risk of bias, we designed a customized tool inspired by the Cochrane assessment framework. This tool has 4 categories: high, medium, low, and very low. A total of 2 independent reviewers conducted title and abstract screening, full-text review, and study quality and risk of bias analysis. In instances of disagreement between the 2 reviewers, a third reviewer served as an adjudicator. RESULTS: Our search retrieved 11,450 studies, and 25 met our inclusion criteria. Among the 25 included studies, 32% (8/25) were classified as high quality, 52% (13/25) as medium quality, and 16% (4/25) as low quality. Furthermore, we found no evidence of publication bias in any of the included studies. A consistent postprandial increase in heart rate, cardiac output, and stroke volume was observed in at least 95% (heart rate: 19/19, cardiac output: 18/19, stroke volume: 11/11) of the studies that investigated these variables' responses to eating. Specifically, cardiac output increased by 9%-100%, stroke volume by 18%-41%, and heart rate by 6%-21% across these studies. These changes were statistically significant (P<.05). In contrast, the 8 studies that investigated postprandial thermoregulatory effects displayed grossly inconsistent results, showing wide variations in response with no clear patterns of change, indicating a high degree of variability among these studies. CONCLUSIONS: Our findings demonstrate that central hemodynamic responses, particularly heart rate, hold promise for wearable-based eating detection, as cardiac output and stroke volume cannot be measured by any currently available noninvasive medical or consumer-grade wearables. TRIAL REGISTRATION: PROSPERO CRD42022360600; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=360600.

Reliability of the Moover® 3D Inertial Motion Sensor in Greek Patients With Chronic Neck Pain in a Primary Care Urban Setting.

Introduction Neck pain has a high lifetime prevalence and represents a significant health issue. Reduced active cervical range of motion (ACROM) has been found in neck pain patients. Inertial sensor technology can provide objective measurements to assess the impaired ACROM. Purpose Primarily, this study investigated the inter- and intra-rater reliability of the Moover® three-dimensional (3D) inertial motion sensor (Sensor Medica, Rome, Italy) in Greek patients with non-specific chronic neck pain. Secondly, the intra-rater reliability of the Neck Disability Index (NDI) was also assessed. Methods Fifty patients (18 males and 32 females) suffering from non-specific chronic neck pain participated in this study. Two physiotherapists measured separately each participant's ACROM in three planes, within a 48-hour period. The participants' position and the sequence and direction of the three cervical movements (cervical rotation, lateral flexion, and flexion-extension) were standardized. Results The inter-rater reliability intraclass correlation coefficient (ICC) values were good to excellent ranging from 0.77 to 0.95 for the first measurement and 0.85 to 0.95 for the second (p < 0.001). The intra-rater reliability ICC values were moderate to excellent ranging from 0.74 to 0.92 for the first rater and good to excellent ranging from 0.83 to 0.94 for the secondrater (p < 0.001). Intra-rater reliability of the overall NDI was indicated as good, and ICC was 0.80 (95%CI: 0.65-0.89; p < 0.001). ICC values for all sections were significant and ranged from 0.40 to 0.88. Conclusion This study showed the reliability of the Moover 3D inertial sensor for ACROM measurement in Greek patients with chronic neck pain. The NDI scale also showed good intra-rater reliability in the same sample. Both intra- and inter-rater reliability of the Moover 3D were proven to be acceptable over a 48-hour period. The specific sensor might have a potential application in a clinical setting.

High-Performance Stretchable Strain Sensors Based on Auxetic Fabrics for Human Motion Detection.

Wearable strain sensors play a pivotal role in real-time human motion detection and health monitoring. Traditional fabric-based strain sensors, typically with a positive Poisson's ratio, face challenges in maintaining sensitivity and comfort during human motion due to conflicting resistance changes in different strain directions. In this work, high-performance stretchable strain sensors are developed based on graphene-modified auxetic fabrics (GMAF) for human motion detection in smart wearable devices. The proposed GMAF sensors, with a negative Poisson's ratio achieved through commercially available warp-knitting technology, exhibit an 8-fold improvement in sensitivity compared to conventional plain fabric sensors. The unique auxetic fabric structure enhances sensitivity by synchronizing resistance changes in both wale and course directions. The GMAF sensors demonstrate excellent washability, showing only slight degradation in auxeticity and an acceptable increase in resistance after 10 standard wash cycles. The GMAF sensors maintain stability under different strain levels and various motion frequencies, emphasizing their dynamic performance. The sensors exhibit superior conformability to joint movements, which effectively monitor a full range of motions, including joint bending, sports activities, and subtle actions like coughing and swallowing. The research underscores a promising approach to achieve industrial-scale production of wearable sensors with improved performance and comfort through fabric structure design.

Recent advances in moisture-induced electricity generation based on wood lignocellulose: Preparation, properties, and applications.

Moisture-induced electricity generation (MEG), which can directly harvest electricity from moisture, is considered as an effective strategy for alleviating the growing energy crisis. Recently, tremendous efforts have been devoted to developing MEG active materials from wood lignocellulose (WLC) due to its excellent properties including environmental friendliness, sustainability, and biodegradability. This review comprehensively summarizes the recent advances in MEG based on WLC (wood, cellulose, lignin, and woody biochar), covering its principles, preparation, performances, and applications. In detail, the basic working mechanisms of MEG are discussed, and the natural features of WLC and their significant advantages in the fabrication of MEG active materials are emphasized. Furthermore, the recent advances in WLC-based MEG for harvesting electrical energy from moisture are specifically discussed, together with their potential applications (sensors and power sources). Finally, the main challenges of current WLC-based MEG are presented, as well as the potential solutions or directions to develop highly efficient MEG from WLC.

Real-world gait and turning in individuals scheduled for total knee arthroplasty.

BACKGROUND: Improving mobility - specifically walking - is an important treatment goal of total knee arthroplasty. Objective indicators for mobility, however, are lacking in clinical evaluations. This study aimed to compare real-world gait and turning between individuals scheduled for total knee arthroplasty and healthy controls, using continuous monitoring with inertial measurement units. METHODS: Real-world gait and turning data were collected for 5-7 days in individuals scheduled for total knee arthroplasty (n = 34) and healthy controls (n = 32) using inertial measurement units on the feet and lower back. Gait and turning parameters were compared between groups using a linear regression model. Data was further analyzed by stratification of gait bouts based on bout length, and turns based on turning angle and turning direction. FINDINGS: Dominant real-world gait speed was 0.21 m/s lower in individuals scheduled for total knee arthroplasty compared to healthy controls. Stride time was 0.05 s higher in individuals scheduled for total knee arthroplasty. Step time asymmetry was not different between the groups. Regarding walking activity, individuals scheduled for total knee arthroplasty walked 72 strides/h less than healthy controls, and maximum bout length was 316 strides shorter. Irrespective of the size of the turn, turning velocity was lower in individuals scheduled for total knee arthroplasty. INTERPRETATION: Individuals scheduled for total knee arthroplasty showed specific walking and turning limitations in the real-world. Parameters derived from inertial measurement units reflected a rich profile of real-world mobility measures indicative of walking limitation of individuals scheduled for total knee arthroplasty, which may provide a relevant outcome dimension for future studies.

Safeguarding Public Health: Advanced Detection of Food Adulteration Using Nanoparticle-Based Sensors.

Food adulteration, whether intentional or accidental, poses a significant public health risk. Traditional detection methods often lack the precision required to detect subtle adulterants that can be harmful. Although chromatographic and spectrometric techniques are effective, their high cost and complexity have limited their widespread use. To explore and validate the application of nanoparticle-based sensors for enhancing the detection of food adulteration, focusing on their specificity, sensitivity, and practical utility in the development of resilient food safety systems. This study integrates forensic principles with advanced nanomaterials to create a robust detection framework. Techniques include the development of nanoparticle-based assays designed to improve the detection specificity and sensitivity. In addition, sensor-based technologies, including electronic noses and tongues, have been assessed for their capacity to mimic and enhance human sensory detection, offering objective and reliable results. The use of nanomaterials, including functionalized nanoparticles, has significantly improved the detection of trace amounts of adulterants. Nanoparticle-based sensors demonstrate superior performance in terms of speed, sensitivity, and selectivity compared with traditional methods. Moreover, the integration of these sensors into food safety protocols shows promise for real-time and onsite detection of adulteration. Nanoparticle-based sensors represent a cutting-edge approach for detecting food adulteration, and offer enhanced sensitivity, specificity, and scalability. By integrating forensic principles and nanotechnology, this framework advances the development of more resilient food-safety systems. Future research should focus on optimizing these technologies for widespread application and adapting them to address emerging adulteration threats.

Assessing and Enhancing Movement Quality Using Wearables and Consumer Technologies: Thematic Analysis of Expert Perspectives.

BACKGROUND: Improvements in movement quality (ie, how well an individual moves) facilitate increases in movement quantity, subsequently improving general health and quality of life. Wearable technology offers a convenient, affordable means of measuring and assessing movement quality for the general population, while technology more broadly can provide constructive feedback through various modalities. Considering the perspectives of professionals involved in the development and implementation of technology helps translate user needs into effective strategies for the optimal application of consumer technologies to enhance movement quality. OBJECTIVE: This study aimed to obtain the opinions of wearable technology experts regarding the use of wearable devices to measure movement quality and provide feedback. A secondary objective was to determine potential strategies for integrating preferred assessment and feedback characteristics into a technology-based movement quality intervention for the general, recreationally active population. METHODS: Semistructured interviews were conducted with 12 participants (age: mean 42, SD 9 years; 5 males) between August and September 2022 using a predetermined interview schedule. Participants were categorized based on their professional roles: commercial (n=4) and research and development (R&D; n=8). All participants had experience in the development or application of wearable technology for sports, exercise, and wellness. The verbatim interview transcripts were analyzed using reflexive thematic analysis in QSR NVivo (release 1.7), resulting in the identification of overarching themes and subthemes. RESULTS: Three main themes were generated as follows: (1) "Grab and Go," (2) "Adjust and Adapt," and (3) "Visualize and Feedback." Participants emphasized the importance of convenience to enhance user engagement when using wearables to collect movement data. However, it was suggested that users would tolerate minor inconveniences if the benefits were perceived as valuable. Simple, easily interpretable feedback was recommended to accommodate diverse audiences and aid understanding of their movement quality, while avoiding excessive detail was advised to prevent overload, which could deter users. Adaptability was endorsed to accommodate progressions in user movement quality, and customizable systems were advocated to offer variety, thereby increasing user interest and engagement. The findings indicate that visual feedback representative of the user (ie, an avatar) should be used, supplemented with concise text or audible instructions to form a comprehensive, multimodal feedback system. CONCLUSIONS: The study provides insights from wearable technology experts on the use of consumer technologies for enhancing movement quality. The findings recommend the prioritization of user convenience and simplistic, multimodal feedback centered around visualizations, and an adaptable system suitable for a diverse audience. Emphasizing individualized feedback and user-centric design, this study provides valuable findings around the use of wearables and other consumer technologies to enhance movement quality among the general population. These findings, in conjunction with those of future research into user perspectives, should be applied in practical settings to evaluate their effectiveness in enhancing movement quality.

Layer-Dependent Gas Sensing Mechanism of 2D Titanium Carbide (Ti3C2Tx) MXene.

Monolayers of Ti3C2Tx MXene and bilayer structures formed by partially overlapping monolayer flakes exhibit opposite sensing responses to a large scope of molecular analytes. When exposed to reducing analytes, monolayer MXene flakes show increased electrical conductivity, i.e., an n-type behavior, while bilayer structures become less conductive, exhibiting a p-type behavior. On the contrary, both monolayers and bilayers show unidirectional sensing responses with increased resistivity when exposed to oxidizing analytes. The sensing responses of Ti3C2Tx monolayers and bilayers are dominated by entirely different mechanisms. The sensing behavior of MXene monolayers is dictated by the charge transfer from adsorbed molecules and the response direction is consistent with the donor/acceptor properties of the analyte and the intrinsic n-type character of Ti3C2Tx. In contrast, the bilayer MXene structures always show the same response regardless of the donor/acceptor character of the analyte, and the resistivity always increases because of the intercalation of molecules between the Ti3C2Tx layers. This study explains the sensing behavior of bulk MXene sensors based on multiflake assemblies, in which this intercalation mechanism results in universal increase in resistance that for many analytes is seemingly inconsistent with the n-type character of the material. By scaling MXene sensors down from multiflake to single-flake level, we disentangled the charge transfer and intercalation effects and unraveled their contributions. In particular, we show that the charge transfer has a much faster kinetics than the intercalation process. Finally, we demonstrate that the layer-dependent gas sensing properties of MXenes can be employed for the design of sensor devices with enhanced molecular recognition.

Toward Quantitative Neurology: Sensors to Assess Motor Deficits in Dementia.

Background: Alzheimer's disease (AD) is the most common neurodegenerative disorder which primarily involves memory and cognitive functions. It is increasingly recognized that motor involvement is also a common and significant aspect of AD, contributing to functional decline and profoundly impacting quality of life. Motor impairment, either at early or later stages of cognitive disorders, can be considered as a proxy measure of cognitive impairment, and technological devices can provide objective measures for both diagnosis and prognosis purposes. However, compared to other neurodegenerative disorders, the use of technological tools in neurocognitive disorders, including AD, is still in its infancy. Objective: This report aims to evaluate the role of technological devices in assessing motor involvement across the AD spectrum and in other dementing conditions, providing an overview of the existing devices that show promise in this area and exploring their clinical applications. Methods: The evaluation involves a review of the existing literature in the PubMed, Web of Science, Scopus, and Cochrane databases on the effectiveness of these technologies. 21 studies were identified and categorized as: wearable inertial sensors/IMU, console/kinect, gait analysis, tapping device, tablet/mobile, and computer. Results: We found several parameters, such as speed and stride length, that appear promising for detecting abnormal motor function in MCI or dementia. In addition, some studies have found correlations between these motor aspects and cognitive state. Conclusions: Clinical application of technological tools to assess motor function in people with cognitive impairments of a neurodegenerative nature, such as AD, may improve early detection and stratification of patients.

Revolutionizing health monitoring: Integrating transformer models with multi-head attention for precise human activity recognition using wearable devices.

BACKGROUND: A daily activity routine is vital for overall health and well-being, supporting physical and mental fitness. Consistent physical activity is linked to a multitude of benefits for the body, mind, and emotions, playing a key role in raising a healthy lifestyle. The use of wearable devices has become essential in the realm of health and fitness, facilitating the monitoring of daily activities. While convolutional neural networks (CNN) have proven effective, challenges remain in quickly adapting to a variety of activities. OBJECTIVE: This study aimed to develop a model for precise recognition of human activities to revolutionize health monitoring by integrating transformer models with multi-head attention for precise human activity recognition using wearable devices. METHODS: The Human Activity Recognition (HAR) algorithm uses deep learning to classify human activities using spectrogram data. It uses a pretrained convolution neural network (CNN) with a MobileNetV2 model to extract features, a dense residual transformer network (DRTN), and a multi-head multi-level attention architecture (MH-MLA) to capture time-related patterns. The model then blends information from both layers through an adaptive attention mechanism and uses a SoftMax function to provide classification probabilities for various human activities. RESULTS: The integrated approach, combining pretrained CNN with transformer models to create a thorough and effective system for recognizing human activities from spectrogram data, outperformed these methods in various datasets - HARTH, KU-HAR, and HuGaDB produced accuracies of 92.81%, 97.98%, and 95.32%, respectively. This suggests that the integration of diverse methodologies yields good results in capturing nuanced human activities across different activities. The comparison analysis showed that the integrated system consistently performs better for dynamic human activity recognition datasets. CONCLUSION: In conclusion, maintaining a routine of daily activities is crucial for overall health and well-being. Regular physical activity contributes substantially to a healthy lifestyle, benefiting both the body and the mind. The integration of wearable devices has simplified the monitoring of daily routines. This research introduces an innovative approach to human activity recognition, combining the CNN model with a dense residual transformer network (DRTN) with multi-head multi-level attention (MH-MLA) within the transformer architecture to enhance its capability.

Electric-field assisted spatioselective deposition of MIL-101(Cr)PEDOT to enhance electrical conductivity and humidity sensing performance.

Precise deposition of metal-organic framework (MOF) materials is important for fabricating high-performing MOF-based devices. Electric-field assisted drop-casting of poly(3,4-ethylenedioxythiophene)-functionalized (PEDOT) MIL-101(Cr) nanoparticles onto interdigitated electrodes allowed their precise spatioselective deposition as percolating nanoparticle chains in the interelectrode gaps. The resulting aligned materials were investigated for resistive and capacitive humidity sensing and compared with unaligned samples prepared via regular drop-casting. The spatioselective deposition of MOFs resulted in up to over 500 times improved conductivity and approximately 6 times increased responsivity during resistive humidity sensing. The aligned samples also showed good capacitive humidity sensing performance, with up to 310 times capacitance gain at 10 versus 90 % relative humidity. In contrast, the resistive behavior of the unaligned samples rendered them unsuitable for capacitive sensing. This work demonstrates that applying an alternating potential during drop-casting is a simple yet effective method to control MOF deposition for greater efficiency, conductivity, and enhanced humidity sensing performance.

Gut microbiota derived short-chain fatty acids in physiology and pathology: An update.

Short-chain fatty acids (SCFAs) are essential molecules produced by gut bacteria that fuel intestinal cells and may also influence overall health. An imbalance of SCFAs can result in various acute and chronic diseases, including diabetes, obesity and colorectal cancer (CRC). This review delves into the multifaceted roles of SCFAs, including a brief discussion on their source and various gut-residing bacteria. Primary techniques used for detection of SCFAs, including gas chromatography, high-performance gas chromatography, nuclear magnetic resonance and capillary electrophoresis are also discussed through this article. This review study also compiles various synthesis pathways of SCFAs from diverse substrates such as sugar, acetone, ethanol and amino acids. The different pathways through which SCFAs enter cells for immune response regulation are also highlighted. A major emphasis is the discussion on diseases associated with SCFA dysregulation, such as anaemia, brain development, CRC, depression, obesity and diabetes. This includes exploring the relationship between SCFA levels across ethnicities and their connection with blood pressure and CRC. In conclusion, this review highlights the critical role of SCFAs in maintaining gut health and their implications in various diseases, emphasizing the need for further research on SCFA detection, synthesis and their potential as diagnostic biomarkers. Future studies of SCFAs will pave the way for the development of novel diagnostic tools and therapeutic strategies for optimizing gut health and preventing diseases associated with SCFA dysregulation.