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Applications of remote sensing using unmanned aerial vehicle (UAV) in agriculture has proved to be an effective and efficient way of obtaining field information. In this study, we validated the feasibility of utilizing multi-temporal color images acquired from a low altitude UAV-camera system to monitor real-time wheat growth status and to map within-field spatial variations of wheat yield for smallholder wheat growers, which could serve as references for site-specific operations. Firstly, eight orthomosaic images covering a small winter wheat field were generated to monitor wheat growth status from heading stage to ripening stage in Hokkaido, Japan. Multi-temporal orthomosaic images indicated straightforward sense of canopy color changes and spatial variations of tiller densities. Besides, the last two orthomosaic images taken from about two weeks prior to harvesting also notified the occurrence of lodging by visual inspection, which could be used to generate navigation maps guiding drivers or autonomous harvesting vehicles to adjust operation speed according to specific lodging situations for less harvesting loss. Subsequently orthomosaic images were geo-referenced so that further study on stepwise regression analysis among nine wheat yield samples and five color vegetation indices (CVI) could be conducted, which showed that wheat yield correlated with four accumulative CVIs of visible-band difference vegetation index (VDVI), normalized green-blue difference index (NGBDI), green-red ratio index (GRRI), and excess green vegetation index (ExG), with the coefficient of determination and RMSE as 0.94 and 0.02, respectively. The average value of sampled wheat yield was 8.6 t/ha. The regression model was also validated by using leave-one-out cross validation (LOOCV) method, of which root-mean-square error of predication (RMSEP) was 0.06. Finally, based on the stepwise regression model, a map of estimated wheat yield was generated, so that within-field spatial variations of wheat yield, which was usually seen as general information on soil fertility, water potential, tiller density, etc., could be better understood for applications of site-specific or variable-rate operations. Average yield of the studied field was also calculated according to the map of wheat yield as 7.2 t/ha.

The Photo-Fenton reaction is an advanced technology to eliminate organic pollutants in environmental chemistry. Moreover, the conversion rate of Fe 3+ /Fe 2+ and utilization rate of H 2 O 2 are significant factors in Photo-Fenton reaction. In this work, we reported three dimensional (3D) hierarchical cobalt ferrite/graphene aerogels (CoFe 2 O 4 /GAs) composites by the in situ growing CoFe 2 O 4 crystal seeds on the graphene oxide (GO) followed by the hydrothermal process. The resulting CoFe 2 O 4 /GAs composites demonstrated 3D hierarchical pore structure with mesopores (14~18 nm), macropores (50~125 nm), and a remarkable surface area (177.8 m 2 g −1 ). These properties endowed this hybrid with the high and recyclable Photo-Fenton activity for methyl orange pollutant degradation. More importantly, the CoFe 2 O 4 /GAs composites can keep high Photo-Fenton activity in a wide pH. Besides, the CoFe 2 O 4 /GAs composites also exhibited excellent cyclic performance and good rate capability. The 3D framework can not only effectively prevent the volume expansion and aggregation of CoFe 2 O 4 nanoparticles during the charge/discharge processes for Lithium-ion batteries (LIBs), but also shorten lithium ions and electron diffusion length in 3D pathways. These results indicated a broaden application prospect of 3D-graphene based hybrids in wastewater treatment and energy storage.

Primary Sjögren’s disease (SjD) is a chronic systemic autoimmune disorder whose pathogenesis remains incompletely understood. Current clinical interventions demonstrate limited efficacy, yielding suboptimal therapeutic outcomes. microRNAs (miRNAs)–critical regulators of transcriptional networks–participate in SjD pathogenesis through multifaceted mechanisms. Dysregulated miRNA expression during SjD progression directly influences disease prognosis, establishing miRNAs as promising therapeutic targets. Evidence implicates macrophage polarization, apoptosis dysregulation, Th17/Treg imbalance, T/B lymphocyte dysfunction, glandular impairment, and aberrant type I interferon responses in SjD development. Notably, miR-216a-3p, miR-31-5p, and miR-155-5p modulate key signaling pathways (NF-κB, JAK/STAT, PI3K/AKT) to optimize macrophage polarization, suppress apoptosis, restore Th17/Treg equilibrium, regulate T/B lymphocyte activity, enhance glandular function, normalize type I interferon responses,thereby exerting potent anti-SjD effects. This review synthesizes recent literature to elucidate SjD pathogenesis and miRNA-mediated therapeutic mechanisms, providing a theoretical foundation for novel SjD management strategies.

Experimental recordings in hippocampal slices indicate that astrocytic dysfunction may cause neuronal hyper-excitation or seizures. Considering that astrocytes play important roles in mediating local uptake and spatial buffering of K+ in the extracellular space of the cortical circuit, we constructed a novel model of an astrocyte-neuron network module consisting of a single compartment neuron and 4 surrounding connected astrocytes and including extracellular potassium dynamics. Next, we developed a new model function for the astrocyte gap junctions, connecting two astrocyte-neuron network modules. The function form and parameters of the gap junction were based on nonlinear regression fitting of a set of experimental data published in previous studies. Moreover, we have created numerical simulations using the above single astrocyte-neuron network module and the coupled astrocyte-neuron network modules. Our model validates previous experimental observations that both Kir4.1 channels and gap junctions play important roles in regulating the concentration of extracellular potassium. In addition, we also observe that changes in Kir4.1 channel conductance and gap junction strength induce spontaneous epileptic activity in the absence of external stimuli.

Methylmalonic acidemia (MMAemia) is an inborn error of organic acid metabolism characterized by the accumulation of toxic metabolites—including methylmalonic acid (MMA), 2-methylcitric acid (2-MCA), propionic acid (PA), homocysteine (Hcy), ammonia, and lactate—due to defects in methylmalonyl-CoA mutase or impaired cobalamin metabolism. These metabolites exert profound effects on the central nervous system, contributing to neurological injury through tightly interconnected mechanisms, including mitochondrial dysfunction, neuroinflammation, and excitotoxicity. This review synthesizes current evidence on how these metabolites trigger neurological dysfunction, integrating findings from clinical studies, animal models, and cellular systems. We also highlight the increasingly recognized role of aberrant post-translational modifications (e.g., methylmalonylation, propionylation, lactylation) in disrupting metabolic network architecture and reprogramming cellular metabolism. Despite advances in supportive therapies, intracerebral metabolite accumulation remains a therapeutic challenge. We discuss emerging strategies targeting mitochondrial protection, redox homeostasis, and inflammation—including enzyme replacement, gene therapy, antioxidant regimens, and exosome-based delivery. A deeper mechanistic understanding of metabolite-driven neurotoxicity is critical to the development of targeted interventions that can improve neurological outcomes in MMAemia.

To assess the diagnostic value of the Copenhagen index for ovarian malignancy. PubMed, Web of Science, the Cochrane Library, Embase, CBM, CNKI, and WanFang databases were searched throughout June 2021. Statistical analyses were performed using Stata 12, Meta-DiSc, and RevMan 5.3. The pooled sensitivity, specificity, and diagnostic odds ratio were calculated, the summary receiver operating characteristic curve was drawn, and the area under the curve was calculated. Ten articles, including 11 studies with a total of 5266 patients, were included. The pooled sensitivity, specificity, and diagnostic odds ratio were 0.82 [95% CI (0.80-0.83)], 0.88 [95% CI (0.87-0.89)], and 57.31 [95% CI (32.84-100.02)], respectively. The area under the summary receiver operating characteristics curve and the Q index were 0.9545 and 0.8966, respectively. Our systematic review shows that the sensitivity and specificity of the Copenhagen index are high enough for it to be used in a clinical setting to provide accurate ovarian cancer diagnosis without considering menopausal status.

The agriculture industry has faced various challenges nowadays. This research is the first part of a project that presents the designing process, kinematic modelling, and parameterization of a 4-DOF SCARA-type robotic arm specifically designed for work in an agricultural field in terms of seeding, watering, fertilizing, weeding, harvesting, and transporting. The designing of parameters, such as optimum degrees of freedom and component configuration, was done. The kinematic model was calculated using the Denavit-Hartenberg method. The structure of robot was developed for inertia reduction, smooth motion, and torque minimization. The results show that the working space, maximum front access, and side access of developed robotic arm were 11.4 m , 2.9 m, and 2.4 m, respectively. The results indicate that the robot has sufficient surface coverage for defined farm work.

The mammalian epidermis forms a critical barrier against environmental insults and water loss. The formation of its outermost layer, the stratum corneum, involves a rapid terminal differentiation process that has traditionally been explained by the “bricks and mortar” model. Recent advances reveal a more dynamic mechanism governed by intracellular liquid–liquid phase separation (LLPS). This review proposes that the lifecycle of the granular layer is orchestrated by LLPS. Evidence is synthesized showing that keratohyalin granules (KGs) are biomolecular condensates formed by the phase separation of the intrinsically disordered protein filaggrin (FLG). The assembly, maturation, and pH-triggered dissolution of these condensates are essential for cytoplasmic remodeling and the programmed flattening of keratinocytes, a process known as corneoptosis. In parallel, an LLPS-based signaling pathway is described in which the kinase RIPK4 forms condensates that activate the Hippo pathway, promoting transcriptional reprogramming and differentiation. Together, these structural and signaling condensates drive skin barrier formation. This review further reinterprets atopic dermatitis, ichthyosis vulgaris, and Bartsocas-Papas syndrome as diseases of aberrant phase behavior, in which pathogenic mutations alter condensate formation or material properties. This integrative framework offers new insight into skin biology and suggests novel opportunities for therapeutic intervention through biophysics-informed biomaterial and regenerative design.

Epilepsy has been found to be modulated by the astrocyte systems in experiments, and tremendous modeling studies have unveiled the roles of astrocyte cellular functions such as the calcium and potassium channels in the epileptic seizures. However, little attention has been paid to the structure changes of astrocytes in the epileptic seizures in the scale of networks. This paper first constructs a neuron–astrocyte network model to explain the experimental observation that astrocytes mainly induce epilepsy by blocking the channels of the astrocyte gap junction in the network scale. Such model is used to discuss potential seizure induction process in the network by changing the connection intensity of the astrocyte gap junction. The simulation results show that a decrease of the gap junction intensity changes the firing pattern of the population of neurons from slow periodical firing to high-frequency epileptic seizures, featuring epileptic patterns of depolarization blocks. This further verifies that epileptic seizures are experimentally induced via the channel block of the astrocyte gap junctions. Because of the heterogeneous structure of the real neuron–astrocyte network, the effect of changing astrocyte network structures on the seizure activities is then studied in two typical network structures: the regular neighboring connection and the random connection. The results show that an increase of the number of regular connections of the regular neighboring astrocyte network could inhibit the induction and spread of the epileptic seizures. The epileptic inhibition can be achieved similarly by increasing the connection probability of the random astrocyte network. These findings further provide evidence for the experimental phenomena of the protective response of gliosis to epilepsy with increasing gap junctions. Above all, the simulation results suggest a potential pathway of epilepsy treatment by targeting the astrocyte gap junctions.

Topographic maps provide detailed information on variations in ground elevation, which is essential for precision farmland levelling. This paper reports the development and experimental study on an innovative approach of generating topographic maps at farmland-level with the advantages of high efficiency and simplicity of implementation. The experiment uses a low-altitude Unmanned Aerial Vehicle (UAV) as a platform and integrates Light Detection and Ranging (LiDAR) distance measurements with Post-Processing Kinematic Global Positioning System (PPK-GNSS) coordinates. A topographic mapping experiment was conducted over two fields in Henan Province, China, and primitive errors of the topographic surveying data were evaluated. The Root Mean Square Error (RMSE) between elevation data of the UAV-LiDAR topographic mapping system and ground truth data was calculated as 4.1 cm and 3.6 cm for Field 1 and Field 2, respectively, which proved the feasibility and high accuracy of the topographic mapping system. Furthermore, the accuracies of topographic maps generated using different geo-spatial interpolation models were also evaluated. The results showed that a TIN (Triangulated Irregular Network) interpolation model expressed the best performances for both Field 1 with sparse topographic surveying points, and Field 2 with relatively dense topographic surveying points, when compared with other interpolation models. Moreover, we concluded that as the spatial resolution of topographic surveying points is intensified from 5 m × 0.5 m to 2.5 m × 0.5 m, the accuracy of the topographic map based on the TIN model improves drastically from 7.7 cm to 4.6 cm. Cut-fill analysis was also implemented based on the topographic maps of the TIN interpolation model. The result indicated that the UAV-LiDAR topographic mapping system could be successfully used to generate topographic maps with high accuracy, which could provide instructive information for precision farmland levelling.