Search Results (683)

Increased food production demands, labor shortages, and environmental concerns are driving the need for innovative agricultural technologies. However, effective adoption depends critically on aligning robot innovations with the needs of farmers. This paper examines the alignment between the needs of farmers and the robotic systems used in row crop farming. We review current commercial agricultural robots and research, and map these to the needs of farmers, as expressed in the literature, to identify the key issues holding back large-scale adoption. From initial pool of 184 research articles, 19 survey articles, and 82 commercial robotic solutions, we selected 38 peer-reviewed academic studies, 12 survey articles, and 18 commercially available robots for in-depth review and analysis for this study. We identify the key challenges faced by farmers and map them directly to the current and emerging capabilities of agricultural robots. We supplement the data gathered from the literature review of surveys and case studies with in-depth interviews with nine farmers to obtain deeper insights into the needs and day-to-day operations. Farmers reported mixed reactions to current technologies, acknowledging efficiency improvements but highlighting barriers such as capital costs, technical complexity, and inadequate support systems. There is a notable demand for technologies for improved plant health monitoring, soil condition assessment, and enhanced climate resilience. We then review state-of-the-art robotic solutions for row crop farming and map these technological capabilities to the farmers’ needs. Only technologies with field validation or operational deployment are included, to ensure practical relevance. These mappings generate insights that underscore the need for lightweight and modular robot technologies that can be adapted to diverse farming practices, as well as the need for farmers’ education and simpler interfaces to robotic operations and data analysis that are actionable for farmers. We conclude with recommendations for future research, emphasizing the importance of co-creation with the farming community to ensure the adoption and sustained use of agricultural robotic solutions. Full article

Background/Objectives: Neuromodulation is under investigation as a possibly effective add-on therapy in Alzheimer’s disease (AD). While transcranial pulse stimulation (TPS) has shown positive short-term effects, long-term effects have not yet been fully explored. This study aims to evaluate the long-term feasibility, safety, and potential cognitive benefits of TPS over one year in patients with Alzheimer’s disease, focusing on domains such as memory, speech, orientation, visuo-construction, and depressive symptoms. Methods: We analyzed preliminary data from the first ten out of thirty-five patients enrolled in a prospective TPS study who completed one year of follow-up and were included in a dedicated long-term database. The protocol consisted of six initial TPS sessions over two weeks, followed by monthly booster sessions delivering 6000 pulses each for twelve months. Patients underwent regular neuropsychological assessments using the Alzheimer Disease Assessment Scale (ADAS), Mini-Mental Status Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Beck Depression Inventory (BDI-II). All adverse events (AEs) were documented and monitored throughout the study. Results: Adverse events occurred in less than 1% of stimulation sessions and mainly included mild focal pain or transient unpleasant sensations, as well as some systemic behavioral or vigilance changes, particularly in patients with underlying medical conditions, with some potentially related to the device’s stimulation as adverse device reactions (ADRs). Cognitive test results showed significant improvement after the initial stimulation cycle (ADAS total improved significantly after the first stimulation cycle (M_pre = 28.44, M_post = 18.56; p = 0.001, d = 0.80, 95% CI (0.36, 1.25)), with stable scores across all domains over one year. Improvements were most notable in memory, speech, and mood. Conclusions: TPS appears to be a generally safe and feasible add-on treatment for AD, although careful patient selection and monitoring are advised. While a considerable number of participants were lost to follow-up for various reasons, adverse events and lack of treatment effect were unlikely primary causes. A multifocal stimulation approach (F-TOP2) is proposed to enhance effects across more cognitive domains. Full article

Background/Objectives: Norovirus is a major cause of acute gastroenteritis worldwide. Considering its highly infectious and transmissible nature, rapid and accurate diagnostic tools are of utmost importance for the effective control of outbreaks in the context of point-of-care testing (POCT). In this study, we developed a genogroup-specific multiplex reverse transcriptase loop-mediated isothermal amplification assay to detect the human norovirus genogroups I and II (GI and GII, respectively). Methods: For the comprehensive detection of clinically relevant genotypes, two sets of primers were incorporated into the assays targeting the RdRp-VP1 junction: one against GI.1 and GI.3, and the other for GII.2 and GII.4. Following optimization of the reaction variables, we standardized the reaction conditions at 65 °C with 6 mM MgSO₄, 1.4 mM dNTPs, 7.5 U WarmStart RTx Reverse Transcriptase, and Bst DNA polymerase at 8 U and 10 U for GI and GII, respectively. Amplification was monitored in real-time using a thermocycler platform to ensure precise quantification and detection. Finally, the assay was evaluated through portable isothermal detection device to test its feasibility in on-site settings. Results: Both assays detected the template down to 10²–10³ copies per reaction and showed high target selectivity, yielding no non-specific amplification across 39 enteric pathogens. These assays enabled prompt detection of GI within 10–12 min and of GII within 12–17 min after the reaction was initiated. Onsite validation reveals all template detection below 15 min, demonstrating its potential feasibility in point-of-care applications. Including the sample preparation time, test results were obtained in less than 1 h. Conclusions: This method is a rapid, reliable, and scalable solution for detecting human norovirus in POCT settings for both clinical diagnosis and public health surveillance. Full article

Sitagliptin is an orally bioavailable selective DPP4 inhibitor that reduces blood glucose levels without significant increases in hypoglycemia. The aim of this study was to design and validate an innovative, rapid, and highly sensitive LC–MS/MS assay for the precise measurement of sitagliptin concentrations in human plasma. This analytical method, utilizing sitagliptin-d4 as the internal standard, is performed using only 100 μL of plasma and a liquid–liquid extraction procedure based on methyl tert-butyl ether (MTBE). Chromatographic separation is expertly achieved with a Kinetex^® C18 column under isocratic elution, employing a perfect 1:1 blend of 5 mM ammonium acetate (with 0.04% formic acid) and acetonitrile, and maintaining an efficient flow rate of 0.2 mL/min. Detection occurs in positive ionization mode through multiple reaction monitoring, precisely targeting transitions of m/z 408.2 → 193.0 for sitagliptin and 412.2 → 239.1 for the IS. The total runtime of this assay is under 2 min. Comprehensive validation in line with MFDS and FDA criteria demonstrates outstanding linearity (5–1000 ng/mL, r² > 0.998), alongside impressive levels of accuracy, precision, recovery and sample stability. Due to its minimal sample requirement and high-throughput capability, the validated approach is highly appropriate for pharmacokinetic and bioequivalence assessments involving sitagliptin. Full article

Electro-oxidation of ammonia has emerged as a promising route for sustainable energy conversion and pollutant mitigation. In this study, we report the facile fabrication of dendritic Cu@Pt core–shell nanostructures electrodeposited on pencil graphite, forming an efficient electrocatalyst for the ammonia oxidation reaction (AOR). The designed electrocatalyst exhibited high catalytic activity towards AOR, achieving high current density at very low potentials (−0.3 V vs. Ag/AgCl), with a lower Tafel slope of 16.4 mV/dec. The catalyst also demonstrated high electrochemical stability over 1000 potential cycles with a regeneration efficiency of 78%. In addition to catalysis, Cu@Pt/PGE facilitated very sensitive and selective electrochemical detection of ammonia nitrogen by differential pulse voltammetry, providing an extensive linear range (1 μM to 1 mM) and a low detection limit of 0.78 μM. The dual functionality of Cu@Pt highlights its potential in enhancing ammonia-based fuel cells and monitoring ammonia pollution in aquatic environments, thereby contributing to the development of sustainable energy and environmental technologies. Full article

Background and Aims: Ornidazole, a nitroimidazole antibiotic, is widely used for protozoal and anaerobic infections and is generally considered safe. However, ornidazole-induced liver injury (OILI) is an underrecognized yet potentially severe adverse reaction. This multicenter study aims to characterize the clinical features, histopathology, and outcomes of OILI to improve the awareness and management of this rare entity worldwide. Methods: We conducted a retrospective analysis of 101 patients with OILI from eight tertiary centers between 2006 and 2023. Cases were included based on liver enzyme elevations temporally linked to ornidazole and the exclusion of other causes. Causality was assessed using the Roussel Uclaf Causality Assessment Method (RUCAM) score. Clinical data, laboratory parameters, autoantibody profiles, histology, treatments, and outcomes were evaluated. Results: OILI was classified as highly probable in 42.6% of cases (n = 43), probable in 51.5% of cases (n = 52), and possible in 5.9% (n = 6) of cases. The predominant pattern was acute hepatocellular injury (83.2%) (n = 84). Autoimmune-like hepatitis occurred in 5% of cases (n = 5), with ANA positivity in 16.8% of cases (n = 17). Corticosteroids were used in 24.8% of cases (n = 25) and were associated with higher ANA positivity and a 20% (n = 5) relapse rate post-discontinuation. Recovery was achieved in 87.7% of cases (n = 88), while 7.9% of cases (n = 8) required liver transplantation and 4% (n = 4) died. Conclusions: Ornidazole can cause serious idiosyncratic liver injury, including autoimmune phenotypes, and should be considered in the differential diagnosis of acute hepatitis. Given the notable risk of liver failure and death, early recognition, drug discontinuation, and close monitoring are essential. In select cases, corticosteroids and plasmapheresis may be beneficial, though the evidence remains limited. Full article

Background/Objectives: This systematic review analyzed the epidemiologic and macro/microscopic features of manifestations of hypersensitivity reactions with oral and extra-oral involvement in orthodontic patients with fixed (FAs) or removable (RAs) appliances or clear aligners (CAs), and evaluated them based on patient and treatment characteristics to provide clinical recommendations. Methods: The study protocol followed the PRISMA guidelines and was registered on PROSPERO (CRD42024517942). Results: Thirty-one studies were qualitatively assessed and synthetized, involving 858 subjects (114 males and 714 females, 9–49 years old), of whom there were 86 with a history of allergy, and 743 wearing recorded appliances (FAs = 656, FAs and RAs = 81, intra- and extra-oral RAs = 3, CAs = 3), with a mean treatment duration of 21.5 months (6 weeks–40 months). Among 75 reports, 29 (38.67%), describing burning, gingival hyperplasia, erythema, and vesicles, had oral involvement, while 46 (61.33%) had skin, eye, and systemic involvement, with erythema, papules, conjunctival hyperemia, and vertigo. Positive allergy tests concomitant with the manifestations identified nickel 451 times, cobalt 6 times, titanium 5 times, and chromium 4 times. Management included antihistamines or corticosteroids and removing the offending materials, with treatment discontinuation/appliance substitution. Conclusions: Pre-treatment evaluations, including patient histories and allergy testing, are essential to identify potential allergens and select hypoallergenic materials like titanium or ceramic brackets; regular monitoring and early intervention during treatment are crucial to prevent severe outcomes. Full article

Background: Rheumatoid arthritis (RA) is a chronic autoimmune disorder that predominantly affects synovial joints, leading to inflammation, pain, and progressive joint damage. Despite therapeutic advancements, the molecular basis of established RA remains poorly defined. Methods: In this study, we conducted an untargeted plasma proteomic analysis using two-dimensional differential gel electrophoresis (2D-DIGE) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in samples from RA patients and healthy controls in the discovery phase. Results: Significantly (ANOVA, p ≤ 0.05, fold change > 1.5) differentially abundant proteins (DAPs) were identified. Notably, upregulated proteins included mitochondrial dicarboxylate carrier, hemopexin, and 28S ribosomal protein S18c, while CCDC124, osteocalcin, apolipoproteins A-I and A-IV, and haptoglobin were downregulated. Receiver operating characteristic (ROC) analysis identified CCDC124, osteocalcin, and metallothionein-2 with high diagnostic potential (AUC = 0.98). Proteins with the highest selected frequency were quantitatively verified by multiple reaction monitoring (MRM) analysis in the validation cohort. Bioinformatic analysis using Ingenuity Pathway Analysis (IPA) revealed the underlying molecular pathways and key interaction networks involved STAT1, TNF, and CD40. These central nodes were associated with immune regulation, cell-to-cell signaling, and hematological system development. Conclusions: Our combined proteomic and bioinformatic approaches underscore the involvement of dysregulated immune pathways in RA pathogenesis and highlight potential diagnostic biomarkers. The utility of these markers needs to be evaluated in further studies and in a larger cohort of patients. Full article

Creatinine serves as a crucial diagnostic biomarker for assessing kidney disease. This work developed portable non-enzymatic and multienzyme-modified electrochemical biosensors for the detection of creatinine based on commercial screen-printed carbon electrodes (SPCEs). The non-enzymatic creatinine sensor was constructed by the electrochemical deposition of AuNPs onto the surface of a pre-activated SPCE by electrochemical activation, followed by the surface modification of a Nafion membrane. The developed AuNPs/SCPE exhibited excellent reproducibility, and the proposed Nafion/AuNPs/SPCE sensor showed excellent detection sensitivity and selectivity toward creatinine. In comparison, the enzymatic creatinine biosensor was gradually established by the electrodeposition of a Prussian blue (PB) membrane on the optimal AuNPs/SCPE surface, followed by multi-enzyme cascade modification (which consisted of creatinine amidohydrolase (CA), creatine oxidase (CI) and sarcosine oxidase (SOx)) and drop-casting the Nafion membrane to stabilize the interface. The introduction of a PB interlayer acted as the redox layer to monitor the generation of hydrogen peroxide (H₂O₂) produced by the enzymatic reaction, while the Nafion membrane enhanced the detection selectivity toward creatine, and the multi-enzyme cascade modification further increased the detection specificity. Both non-enzymatic and enzymatic creatinine sensors could detect the lowest concentrations of less than or equal to 10 μM. In addition, the efficiency and reproducibility of the proposed composite biosensor were also confirmed by repetitive electrochemical measurements in human serum, which showed a positive linear calibration relation of peak currents versus the logarithm of the concentration between 10 μM and 1000 μM, namely, i_p (μA) = −7.06 lgC (μM) −5.30, R² = 0.996. This work offers a simple and feasible approach to the development of enzymatic and non-enzymatic creatinine biosensors. Full article

Acetone detection is crucial for non-invasive health monitoring and environmental safety, so there is an urgent demand to develop high-performance gas sensors. Here, platinum (Pt)-functionalized layered flower-like nickel ferrite (NiFe₂O₄) sheets were efficiently fabricated via facile hydrothermal synthesis and wet chemical reduction processes. When the Ni/Fe molar ratio is 1:1, the sensing material forms a Ni/NiO/NiFe₂O₄ composite, with performance further optimized by tuning Pt loading. At 1.5% Pt mass fraction, the sensor shows a high acetone response (R_g/R_a = 58.33 at 100 ppm), a 100 ppb detection limit, fast response/recovery times (7/245 s at 100 ppm), and excellent selectivity. The enhancement in performance originates from the synergistic effect of the structure and Pt loading: the layered flower-like morphology facilitates gas diffusion and charge transport, while Pt nanoparticles serve as active sites to lower the activation energy of acetone redox reactions. This work presents a novel strategy for designing high-performance volatile organic compound (VOC) sensors by combining hierarchical nanostructured transition metal ferrites with noble metal modifications. Full article

Resistive gas sensors have attracted significant attention due to their simple architecture, low cost, and ease of integration, with widespread applications in environmental monitoring, industrial safety, and healthcare diagnostics. This review provides a comprehensive overview of recent advances in resistive gas sensors, focusing on their fundamental working mechanisms, sensing material design, device architecture optimization, and intelligent system integration. These sensors primarily operate based on changes in electrical resistance induced by interactions between gas molecules and sensing materials, including physical adsorption, charge transfer, and surface redox reactions. In terms of materials, metal oxide semiconductors, conductive polymers, carbon-based nanomaterials, and their composites have demonstrated enhanced sensitivity and selectivity through strategies such as doping, surface functionalization, and heterojunction engineering, while also enabling reduced operating temperatures. Device-level innovations—such as microheater integration, self-heated nanowires, and multi-sensor arrays—have further improved response speed and energy efficiency. Moreover, the incorporation of artificial intelligence (AI) and Internet of Things (IoT) technologies has significantly advanced signal processing, pattern recognition, and long-term operational stability. Machine learning (ML) algorithms have enabled intelligent design of novel sensing materials, optimized multi-gas identification, and enhanced data reliability in complex environments. These synergistic developments are driving resistive gas sensors toward low-power, highly integrated, and multifunctional platforms, particularly in emerging applications such as wearable electronics, breath diagnostics, and smart city infrastructure. This review concludes with a perspective on future research directions, emphasizing the importance of improving material stability, interference resistance, standardized fabrication, and intelligent system integration for large-scale practical deployment. Full article

Vertical ground reaction force (vGRF) plays an important role in the study of running-related injuries (RRIs). This study explores the synchronization method between inertial measurement unit (IMU) and vGRF data of running and develops ANN models to accurately predict vGRF. Fifteen runners participated in this study. Acceleration data and vGRF values of eight rearfoot strikers and seven forefoot strikers running at 12, 14, and 16 km/h were collected by a single IMU and an instrumented treadmill. The sliding time window synchronization (STWS) algorithm was developed to sync IMU data with vGRF data. The wavelet neural network model (WNN) and feed-forward neural network model (FFNN) were adapted to predict vGRF using three-axis or sagittal-axis acceleration data in the stance phase, respectively. One rearfoot striker and one forefoot striker were randomly selected as a test set, while the other participants formed training sets. After synchronization, mean absolute errors for stride time of the IMU and vGRF data were less than 11.2 ms. The coefficient of multiple correlations for vGRF measured curves and predicted curves was more than 0.97. The normalized root mean square errors (NRMSEs) between two curves were 4.6~9.2%, and R² was 0.93~0.99. For peak vGRF, the NRMSEs were 1.6~8.2%, except for rearfoot strike runners at 16 km/h using the FFNN model (10.7% and 11.1%). The Bland–Altman plots indicate that the errors for both the WNN and FFNN models are within acceptable limits. The STWS algorithm can effectively achieve the data synchronization between the IMU and the force plate during running. Both WNN and FFNN models demonstrated good accuracy and agreement in predicting vGRF. Using sagittal-axis acceleration data may be an ideal model with good prediction accuracy and less input data. This work provides direction for developing ANN models of personalized monitoring of lower limb load. Full article

Background/Objectives: Quantitative assessments of facial muscle function and cognitive responses can enhance the clinic evaluations in neuromuscular disorders such as Bell’s palsy and psychiatric conditions including anxiety and depression. This study explored the application of Digital Image Speckle Correlation (DISC) in detecting enervation of facial musculature and assessing reaction times in response to visual stimuli. Methods: A consistent video recording setup was used to capture facial movements of human subjects in response to visual stimuli from a calibrated database. The DISC method utilizes the displacement of naturally occurring skin pores to map the specific locus of underlying muscular movement. The technique was applied to two distinct case studies: Patient 1 had unilateral Bell’s palsy and was monitored for 1 month of recovery. Patient 2 had a comorbidity of refractory depression and anxiety disorders with ketamine treatment and was assessed over 3 consecutive weekly visits. For patient 1, facial asymmetry was calculated by comparing left-to-right displacement signals. For patient 2, visual reaction time was measured, and facial motion intensity and response rate were compared with self-reported depression and anxiety scales. Results: DISC effectively mapped biomechanical properties of facial motions, providing detailed spatial and temporal resolution of muscle activity. In a control cohort of 10 subjects, when executing a facial expression, the degree of left/right facial asymmetry was determined to be 13.2 (8)%. And showed a robust response in an average of 275 (81) milliseconds to five out of the five images shown. For patient 1, obtained an initial asymmetry of nearly 100%, which decreased steadily to 20% in one month, demonstrating a progressive recovery. Patient 2 exhibited a prolonged reaction time of 518 (93) milliseconds and reduced response rates compared with controls of 275 (81) milliseconds and a decrease in the overall rate of response relative to the control group. The data obtained before treatment in three visits correlated strongly with selected depression and anxiety scores. Conclusions: These findings highlight the utility of DISC in enhancing clinical monitoring, complementing traditional examinations and self-reported measures. Full article

Pyrolysis is an important methodology for achieving efficient and clean utilization of coal. Lump coal pyrolysis demonstrates distinct advantages over pulverized coal processing, particularly in enhanced gas yield and superior coke quality. As a critical parameter in lump coal pyrolysis, particle size significantly influences heat transfer and mass transfer during pyrolysis, yet its governing mechanisms remain insufficiently explored. This research systematically investigates pyrolysis characteristics of the low-rank coal from Ordos, Inner Mongolia, across graded particle sizes (2–5 mm, 5–10 mm, 10–20 mm, and 20–30 mm) through pyrolysis experiments. Real-time central temperature monitoring of coal bed coupled with advanced characterization techniques—including X-ray diffraction (XRD), Raman spectroscopy, Brunauer–Emmett–Teller (BET) analysis, scanning electron microscopy (SEM), gas chromatography (GC), and GC–mass spectrometry (GC-MS)—reveals particle-size-dependent pyrolysis mechanisms. Key findings demonstrate that the larger particles enhance bed-scale convective heat transfer, accelerating temperature propagation from reactor walls to the coal center. However, excessive sizes cause significant intra-particle thermal gradients, impeding core pyrolysis. The 10–20 mm group emerges as optimal—balancing these effects to achieve uniform thermal attainment, evidenced by 20.99 vol% peak hydrogen yield and maximum char graphitization. Tar yield first demonstrates a tendency to rise and then decline, peaking at 14.66 wt.% for 5–10 mm particles. This behavior reflects competing mechanisms: enlarging particle size can improve bed permeability (reducing tar residence time and secondary reactions), but it can also inhibit volatile release and intensify thermal cracking of tar in oversized coal blocks. The BET analysis result reveals elevated specific surface area and pore volume with increasing particle size, except for the 10–20 mm group, showing abrupt porosity reduction—attributed to pore collapse caused by intense polycondensation reactions. Contrasting previous studies predominantly focused on less than 2 mm pulverized coal, this research selects large-size (from 2 mm to 30 mm) lump coal to clarify the effect of particle size on coal pyrolysis, providing critical guidance for industrial-scale lump coal pyrolysis optimization. Full article

Background: Diacerein, a prodrug of Rhein, is commonly prescribed for the management of joint disorders, specifically osteoarthritis. This study aimed to develop and validate an LC-MS/MS method to quantify Rhein and its major metabolites, Rhein-G1 and Rhein-G2, in plasma samples. Method: An ACE C18 column was used for chromatographic separation with a mobile phase comprising ammonium acetate at a concentration of 1.0 mM and acetonitrile. Detection was achieved using a Sciex 4000 Q-Trap LC-MS/MS, operated in negative ion mode with multiple reaction monitoring (MRM). Results: The analytical results indicated that the lower limit of quantification (LLOQ) for Rhein and its glucuronides was 7.81 nM. Precision was consistently below 9.14%, while accuracy remained within the acceptable range of 80.1–104.2%. We also verified the method’s matrix effect recovery and stability variance, which were less than 12.60% and 10.37%, respectively. The pharmacokinetic study demonstrated that diacerein is swiftly metabolized into Rhein, and then Rhein subsequently undergoes glucuronidation, forming detectable concentrations of Rhein-G1 and Rhein-G2 in plasma. Conclusions: This new LC-MS/MS method proved to be both sensitive and selective, allowing for pharmacokinetic studies in rats. Full article