Neurophysiological features of STN LFP underlying sleep fragmentation in Parkinson's disease.

BACKGROUND: Sleep fragmentation is a persistent problem throughout the course of Parkinson's disease (PD). However, the related neurophysiological patterns and the underlying mechanisms remained unclear. METHOD: We recorded subthalamic nucleus (STN) local field potentials (LFPs) using deep brain stimulation (DBS) with real-time wireless recording capacity from 13 patients with PD undergoing a one-night polysomnography recording, 1 month after DBS surgery before initial programming and when the patients were off-medication. The STN LFP features that characterised different sleep stages, correlated with arousal and sleep fragmentation index, and preceded stage transitions during N2 and REM sleep were analysed. RESULTS: Both beta and low gamma oscillations in non-rapid eye movement (NREM) sleep increased with the severity of sleep disturbance (arousal index (ArI)-betaNREM: r=0.9, p=0.0001, sleep fragmentation index (SFI)-betaNREM: r=0.6, p=0.0301; SFI-gammaNREM: r=0.6, p=0.0324). We next examined the low-to-high power ratio (LHPR), which was the power ratio of theta oscillations to beta and low gamma oscillations, and found it to be an indicator of sleep fragmentation (ArI-LHPRNREM: r=-0.8, p=0.0053; ArI-LHPRREM: r=-0.6, p=0.0373; SFI-LHPRNREM: r=-0.7, p=0.0204; SFI-LHPRREM: r=-0.6, p=0.0428). In addition, long beta bursts (>0.25 s) during NREM stage 2 were found preceding the completion of transition to stages with more cortical activities (towards Wake/N1/REM compared with towards N3 (p<0.01)) and negatively correlated with STN spindles, which were detected in STN LFPs with peak frequency distinguishable from long beta bursts (STN spindle: 11.5 Hz, STN long beta bursts: 23.8 Hz), in occupation during NREM sleep (ß=-0.24, p<0.001). CONCLUSION: Features of STN LFPs help explain neurophysiological mechanisms underlying sleep fragmentations in PD, which can inform new intervention for sleep dysfunction. TRIAL REGISTRATION NUMBER: NCT02937727.

Perinatal outcome of emergency cesarean section under neuraxial anesthesia versus general anesthesia: a seven-year retrospective analysis.

OBJECTIVE: An emergency cesarean section (CS), which is extremely life-threatening to the mother or fetus, seems to be performed within an adequate time horizon to avoid negative fetal-maternal denouement. An effective and vigilant technique for anesthesia remains vital for emergency cesarean delivery. Therefore, this study aimed to validate the impact of various anesthesia tactics on maternal and neonatal outcomes. METHOD: This was a retrospective cohort study of parturient patients who were selected for emergency CS with the assistance of general or neuraxial anesthesia between January 2015 and July 2021 at our institution. The 5-min Apgar score was documented as the primary outcome. Secondary outcomes, including the 1 min Apgar score, decision-to-delivery interval (DDI), onset of anesthesia to incision interval (OAII), decision to incision interval (DII), duration of operation, length of hospitalization, height and weight of the newborn, use of vasopressors, blood loss, neonatal resuscitation rate, admission to neonatal intensive care unit (NICU), duration of NICU and complications, were also measured. RESULTS: Of the 539 patients included in the analysis, 337 CSs were performed under general anesthesia (GA), 137 under epidural anesthesia (EA) and 65 under combined spinal-epidural anesthesia (CSEA). The Apgar scores at 1 min and 5 min in newborns receiving GA were lower than those receiving intraspinal anesthesia, and no difference was found between those receiving EA and those receiving CSEA. The DDI of parturients under GA, EA, and CSE were 7[6,7], 6[6,7], and 14[11.5,20.5], respectively. The DDI and DII of GA and EA were shorter than those of CSE, and the DDI and DII were similar between GA and EA. Compared to that in the GA group, the OAII in the intraspinal anesthesia group was significantly greater. GA administration correlated with more frequent resuscitative interventions, increased admission rates to NICU, and a greater incidence of neonatal respiratory distress syndrome (NRDS). Nevertheless, the duration of NICU stay and the incidence rates of neonatal hypoxic ischemic encephalopathy (HIE) and pneumonia did not significantly differ based on the type of anesthesia performed. CONCLUSION: Compared with general anesthesia, epidural anesthesia may not be associated with a negative impact on neonatal or maternal outcomes and could be utilized as an alternative to general anesthesia in our selected patient population following emergency cesarean section; In addition, a comparably short DDI was achieved for emergency cesarean delivery under epidural anesthesia when compared to general anesthesia in our study. However, the possibility that selection bias related to the retrospective study design may have influenced the results cannot be excluded.

Self-redox reaction driven in situ formation of Cu2O/Ti3C2Tx nanosheets boost the photocatalytic eradication of multi-drug resistant bacteria from infected wound.

BACKGROUND: MXenes with interesting optical and electrical properties have been attractive in biomedical applications such as antibacterial and anticancer agents, but their low photogeneration efficiency of reactive oxygen species (ROS) and poor stability are major concerns against microbial resistance. METHODS: Water-dispersible single layer Ti3C2Tx-based MXene through etching tightly stacked MAX phase precursor using a minimally intensive layer delamination method. After addition of Cu(II) ions, the adsorbed Cu(II) ions underwent self-redox reactions with the surface oxygenated moieties of MXene, leading to in situ formation of Cu2O species to yield Cu2O/Ti3C2Tx nanosheets (heterostructures). RESULTS: Under NIR irradiation, the Cu2O enhanced generation of electron-hole pairs, which boosted the photocatalytic production of superoxide and subsequent transformation into hydrogen peroxide. Broad-spectrum antimicrobial performance of Cu2O/Ti3C2Tx nanosheets with sharp edges is attributed to the direct contact-induced membrane disruption, localized photothermal therapy, and in situ generated cytotoxic free radicals. The minimum inhibitory concentration of Cu2O/Ti3C2Tx nanosheets reduced at least tenfold upon NIR laser irradiation compared to pristine Cu2O/Ti3C2Tx nanosheets. The Cu2O/Ti3C2Tx nanosheets were topically administrated on the methicillin-resistant Staphylococcus aureus (MRSA) infected wounds on diabetic mice. CONCLUSION: Upon NIR illumination, Cu2O/Ti3C2Tx nanosheets eradicated MRSA and their associated biofilm to promote wound healing. The Cu2O/Ti3C2Tx nanosheets with superior catalytic and photothermal properties have a great scope as an effective antimicrobial modality for the treatment of infected wounds.

Disease Progression in Patients with Parkin-Related Parkinson's Disease in a Longitudinal Cohort.

BACKGROUND: There was a paucity of follow-up studies in the disease progression of early-onset PD patients with Parkin mutations (Parkin-EOPD). Here we conducted a longitudinal study to investigate the progression of motor and cognitive features of Parkin-EOPD patients. METHODS: Genetic analysis was performed via target sequencing and multiplex ligation-dependent probe amplification. Thirty patients carrying homozygous or compound heterozygous Parkin mutations with at least 2 follow-up revisions were investigated as the Parkin-EOPD group. Fifty-two patients with at least 2 follow-up revisions, who did not have any known causative PD mutations, GBA or LRRK2 risk variants, a heterozygous Parkin mutation or 2 Parkin mutations without a segregation test, were defined as the genetically undefined EOPD (GU-EOPD) group. A linear mixed-effect model was implemented to evaluate longitudinal changes in motor symptoms and cognition. RESULTS: At baseline, the Parkin-EOPD group had a lower Unified Parkinson's Disease Rating Scale score (UPDRS-III) (off-medication) than the GU-EOPD group, without significant differences in cognition. A longitudinal study showed the estimated progression rate per year (standard error) of the UPDRS-III score (off-medication) was lower in the Parkin-EOPD group (0.203 [0.3162] points per year) than in the GU-EOPD group (1.056 [0.3001] points per year). The difference in the UPDRS-III score rate between the 2 groups was 0.853 (0.4183) (P = 0.042). The Parkin-EOPD group showed better maintenance of spatial processing ability compared with the GU-EOPD group (P = 0.027). CONCLUSION: Parkin-EOPD patients showed a slower deterioration of motor symptoms and a better spatial processing ability than GU-EOPD patients, which suggests that subtyping according to genetic features can help predict PD progression. © 2020 International Parkinson and Movement Disorder Society.

TGM6 variants in Parkinson's disease: clinical findings and functional evidence.

TGM6 encodes transglutaminase 6, which catalyzes the covalent crosslinking of proteins through transamination reactions. Variants in TGM6 have been identified as the cause of spinocerebellar ataxia type 35. However, we found 12 TGM6 variants of low frequency among 308 patients with Parkinson's disease using next-generation sequencing technologies and multiple ligation-dependent probe amplification, including two variants TGM6 p.R111C and p.L517W, which have been reported to affect functions of transglutaminase 6 in spinocerebellar ataxia type 35 cases. The characteristics of these TGM6 carriers were summarized. To clarify the role of TGM6 variants in Parkinson's disease, we constructed the plasmids of wild-type TGM6 and TGM6 p.R111C, p.P359L, p.L517W to transfect A53T-SH-SY5Y cells and conducted transglutaminase assay, western blots, immunofluorescence, and cell viability assay. Results revealed that the distribution and expression levels of transglutaminase 6 were not affected by TGM6 variants. However, the variants showed lower transglutaminase activity than wild-type transglutaminase 6. The overexpression of wild-type TGM6 was proved to relieve the cell damage, down-regulate the level of α-synuclein and enhance autophagy. These effects were weakened in cells transfected with mutant TGM6 plasmids. Our results suggested that there may be some relationship between TGM6 and Parkinson's disease. TGM6 carriers in Parkinson's disease patients presented with typical parkinsonism but progressed slower. The high expression level of wild-type transglutaminase 6 may protect cells by decreasing α-synuclein and enhancing autophagy.

Pine Cone Detection Using Boundary Equilibrium Generative Adversarial Networks and Improved YOLOv3 Model.

The real-time detection of pine cones in Korean pine forests is not only the data basis for the mechanized picking of pine cones, but also one of the important methods for evaluating the yield of Korean pine forests. In recent years, there has been a certain number of detection accuracy for image processing of fruits in trees using deep-learning methods, but the overall performance of these methods has not been satisfactory, and they have never been used in the detection of pine cones. In this paper, a pine cone detection method based on Boundary Equilibrium Generative Adversarial Networks (BEGAN) and You Only Look Once (YOLO) v3 mode is proposed to solve the problems of insufficient data set, inaccurate detection result and slow detection speed. First, we use traditional image augmentation technology and generative adversarial network BEGAN to implement data augmentation. Second, we introduced a densely connected network (DenseNet) structure in the backbone network of YOLOv3. Third, we expanded the detection scale of YOLOv3, and optimized the loss function of YOLOv3 using the Distance-IoU (DIoU) algorithm. Finally, we conducted a comparative experiment. The experimental results show that the performance of the model can be effectively improved by using BEGAN for data augmentation. Under same conditions, the improved YOLOv3 model is better than the Single Shot MultiBox Detector (SSD), the faster-regions with convolutional neural network (Faster R-CNN) and the original YOLOv3 model. The detection accuracy reaches 95.3%, and the detection efficiency is 37.8% higher than that of the original YOLOv3.

Fusion of Hyperspectral CASI and Airborne LiDAR Data for Ground Object Classification through Residual Network.

Modern satellite and aerial imagery outcomes exhibit increasingly complex types of ground objects with continuous developments and changes in land resources. Single remote-sensing modality is not sufficient for the accurate and satisfactory extraction and classification of ground objects. Hyperspectral imaging has been widely used in the classification of ground objects because of its high resolution, multiple bands, and abundant spatial and spectral information. Moreover, the airborne light detection and ranging (LiDAR) point-cloud data contains unique high-precision three-dimensional (3D) spatial information, which can enrich ground object classifiers with height features that hyperspectral images do not have. Therefore, the fusion of hyperspectral image data with airborne LiDAR point-cloud data is an effective approach for ground object classification. In this paper, the effectiveness of such a fusion scheme is investigated and confirmed on an observation area in the middle parts of the Heihe River in China. By combining the characteristics of hyperspectral compact airborne spectrographic imager (CASI) data and airborne LiDAR data, we extracted a variety of features for data fusion and ground object classification. Firstly, we used the minimum noise fraction transform to reduce the dimensionality of hyperspectral CASI images. Then, spatio-spectral and textural features of these images were extracted based on the normalized vegetation index and the gray-level co-occurrence matrices. Further, canopy height features were extracted from airborne LiDAR data. Finally, a hierarchical fusion scheme was applied to the hyperspectral CASI and airborne LiDAR features, and the fused features were used to train a residual network for high-accuracy ground object classification. The experimental results showed that the overall classification accuracy was based on the proposed hierarchical-fusion multiscale dilated residual network (M-DRN), which reached an accuracy of 97.89%. This result was found to be 10.13% and 5.68% higher than those of the convolutional neural network (CNN) and the dilated residual network (DRN), respectively. Spatio-spectral and textural features of hyperspectral CASI images can complement the canopy height features of airborne LiDAR data. These complementary features can provide richer and more accurate information than individual features for ground object classification and can thus outperform features based on a single remote-sensing modality.

Monitoring and biochemical characterization of beta-cypermethrin resistance in Spodoptera exigua (Lepidoptera: Noctuidae) in Sichuan Province, China.

The beet armyworm Spodoptera exigua, a major pest affecting numerous cultivated crops in China, has developed a serious resistance to many traditional chemical insecticides. The resistance levels of the field-collected populations from different districts in Sichuan Province, China, to nine insecticides were detected with a diet-incorporation bioassay. Compared to the Lab-ZN strain, five (in 2014) and three (in 2016) field populations displayed either high or extremely high levels of resistance to beta-cypermethrin. All the field populations collected in 2014 were susceptible to emamectin benzoate, hexaflumuron, methoxyfenozide, chlorantraniliprole, cyantraniliprole and indoxacarb but exhibited low or moderate levels of resistance to abamectin. The resistances of field populations collected in 2016 were significantly higher than two years earlier, especial for chlorantraniliprole and cyantraniliprole with RRs rising from 173.4- to 582.6-fold and 175.3- to 287.6-fold, respectively, even though the field populations had retained moderate or low levels of resistance to chlorpyrifos and hexaflumuron. The synergism experiment revealed that the resistance of the LS16 population to beta-cypermethrin may be mainly related to cytochrome P450 monooxygenases (P450s), which was responsible for the highest increase ratio of 37.97-fold, for piperonyl butoxide, rather than either carboxylesterase (CarE) or glutathione S-transferase (GST). The cytochrome P450 ethoxycoumarin O-deethylase activity of the LS16 population was also the strongest among the treatments (P < 0.05). Non-denaturing polyacrylamide gel electrophoresis (native PAGE) indicated that enhanced E11, E13 and E15-E16 bands in the LS16 population likely contribute to the development of resistance to beta-cypermethrin.

[Effects of Total Alkaloids of Harmaline on Learning and Memory in Vascular Dementia Rats].

OBJECTIVE: To investigate the effects of total alkaloids of harmaline on learning and memory in vascular dementia rats, and its mechanism. METHODS: The model rats of vascular dementia were established with bilateral carotid artery ligation. After 30 days, the model rats were randomly divided into six groups: sham group, model group, nicergoline tablets 7 mg/kg group, and 25, 12.5 and 6.25 mg/kg dose groups of total alkaloids of harmaline, the rats were given medicine for 30 days. Learning and memory abilities were tested by Morris water maze, histomorphology in hippocampal CA1 area were observed by HE staining, BAX and BCL-2 protein expression in hippocampal CA1 area were detected by immunohistochemistry. RESULTS: Compared with model group, 25 mg/kg group of total alkaloids of harmaline shortened the incubation period in the third and fourth day significantly, 12.5 mg/kg group of total alkaloids of harmaline shortened the incubation period in the fourth day. 25 and 12.5 mg/kg groups of total alkaloids of harmaline significantly increased the times crossing the target. Total alkaloids of harmaline improved the neurons pathological changes of rat in the hippocampus CA1 area, 25 and 12.5 mg/kg of total alkaloids of harmaline downregulated the expression of apoptosis proteins BAX, upregulated the protein expression of BCL-2. CONCLUSION: Total alkaloids of harmaline can improve the learning and memory abilities in vascular dementia rats, which probably is related to inhibiting apoptosis of hippocampus cell.

Urolithin A Inhibits Anterior Basolateral Amygdala to Ventral Hippocampal CA1 Circuit to Ameliorate Amyloid-ß-Impaired Social Ability.

Background: Anxiety and social withdrawal are highly prevalent among patients with Alzheimer's disease (AD). However, the neural circuit mechanisms underlying these symptoms remain elusive, and there is a need for effective prevention strategies. Objective: This study aims to elucidate the neural circuitry mechanisms underlying social anxiety in AD. Methods: We utilized 5xFAD mice and conducted a series of experiments including optogenetic manipulation, Tandem Mass Tag-labeled proteome analysis, behavioral assessments, and immunofluorescence staining. Results: In 5xFAD mice, we observed significant amyloid-ß (Aß) accumulation in the anterior part of basolateral amygdala (aBLA). Behaviorally, 6-month-old 5xFAD mice displayed excessive social avoidance during social interaction. Concurrently, the pathway from aBLA to ventral hippocampal CA1 (vCA1) was significantly activated and exhibited a disorganized firing patterns during social interaction. By optogenetically inhibiting the aBLA-vCA1 pathway, we effectively improved the social ability of 5xFAD mice. In the presence of Aß accumulation, we identified distinct changes in the protein network within the aBLA. Following one month of administration of Urolithin A (UA), we observed significant restoration of the abnormal protein network within the aBLA. UA treatment also attenuated the disorganized firings of the aBLA-vCA1 pathway, leading to an improvement in social ability. Conclusions: The aBLA-vCA1 circuit is a vulnerable pathway in response to Aß accumulation during the progression of AD and plays a crucial role in Aß-induced social anxiety. Targeting the aBLA-vCA1 circuit and UA administration are both effective strategies for improving the Aß-impaired social ability.

Generalized sleep decoding with basal ganglia signals in multiple movement disorders.

Sleep disturbances profoundly affect the quality of life in individuals with neurological disorders. Closed-loop deep brain stimulation (DBS) holds promise for alleviating sleep symptoms, however, this technique necessitates automated sleep stage decoding from intracranial signals. We leveraged overnight data from 121 patients with movement disorders (Parkinson's disease, Essential Tremor, Dystonia, Essential Tremor, Huntington's disease, and Tourette's syndrome) in whom synchronized polysomnograms and basal ganglia local field potentials were recorded, to develop a generalized, multi-class, sleep specific decoder - BGOOSE. This generalized model achieved 85% average accuracy across patients and across disease conditions, even in the presence of recordings from different basal ganglia targets. Furthermore, we also investigated the role of electrocorticography on decoding performances and proposed an optimal decoding map, which was shown to facilitate channel selection for optimal model performances. BGOOSE emerges as a powerful tool for generalized sleep decoding, offering exciting potentials for the precision stimulation delivery of DBS and better management of sleep disturbances in movement disorders.

Targeting vulnerable microcircuits in the ventral hippocampus of male transgenic mice to rescue Alzheimer-like social memory loss.

BACKGROUND: Episodic memory loss is a prominent clinical manifestation of Alzheimer's disease (AD), which is closely related to tau pathology and hippocampal impairment. Due to the heterogeneity of brain neurons, the specific roles of different brain neurons in terms of their sensitivity to tau accumulation and their contribution to AD-like social memory loss remain unclear. Therefore, further investigation is necessary. METHODS: We investigated the effects of AD-like tau pathology by Tandem mass tag proteomic and phosphoproteomic analysis, social behavioural tests, hippocampal electrophysiology, immunofluorescence staining and in vivo optical fibre recording of GCaMP6f and iGABASnFR. Additionally, we utilized optogenetics and administered ursolic acid (UA) via oral gavage to examine the effects of these agents on social memory in mice. RESULTS: The results of proteomic and phosphoproteomic analyses revealed the characteristics of ventral hippocampal CA1 (vCA1) under both physiological conditions and AD-like tau pathology. As tau progressively accumulated, vCA1, especially its excitatory and parvalbumin (PV) neurons, were fully filled with mislocated and phosphorylated tau (p-Tau). This finding was not observed for dorsal hippocampal CA1 (dCA1). The overexpression of human tau (hTau) in excitatory and PV neurons mimicked AD-like tau accumulation, significantly inhibited neuronal excitability and suppressed distinct discrimination-associated firings of these neurons within vCA1. Photoactivating excitatory and PV neurons in vCA1 at specific rhythms and time windows efficiently ameliorated tau-impaired social memory. Notably, 1 month of UA administration efficiently decreased tau accumulation via autophagy in a transcription factor EB (TFEB)-dependent manner and restored the vCA1 microcircuit to ameliorate tau-impaired social memory. CONCLUSION: This study elucidated distinct protein and phosphoprotein networks between dCA1 and vCA1 and highlighted the susceptibility of the vCA1 microcircuit to AD-like tau accumulation. Notably, our novel findings regarding the efficacy of UA in reducing tau load and targeting the vCA1 microcircuit may provide a promising strategy for treating AD in the future.

Evaluation of effects of small-incision approach treatment on proximal tibia fracture by deep learning algorithm-based magnetic resonance imaging.

In this study, magnetic resonance imaging (MRI) based on a deep learning algorithm was used to evaluate the clinical effect of the small-incision approach in treating proximal tibial fractures. Super-resolution reconstruction (SRR) algorithm was used to reconstruct MRI images for analysis and comparison. The research objects were 40 patients with proximal tibial fractures. According to the random number method, patients were divided into a small-incision approach group (22 cases) and an ordinary approach group (18 cases). The peak signal-to-noise ratio (PSNR) and the structural similarity index (SSIM) of the MRI images before and after the reconstruction of the two groups were analyzed. The operative time, intraoperative blood loss, complete weight-bearing time, complete healing time, knee range of motion, and knee function of the two treatments were compared. The results showed that after SRR, the PSNR and SSIM of MRI images were 35.28 and 0.826 dB, respectively, so the MRI image display effect was better. The operation time in the small-incision approach group was 84.93 min, which was significantly shorter than that in the common approach group, and the intraoperative blood loss was 219.95 mL, which was significantly shorter than that in the common approach group (P < 0.05). The complete weight-bearing time and complete healing time in the small-incision approach group were 14.75 and 16.79 weeks, respectively, which were significantly shorter than those in the ordinary approach group (P < 0.05). The half-year knee range of motion and 1-year knee range of motion in the small-incision approach group were 118.27° and 128.72°, respectively, which were significantly higher than those in the conventional approach group (P < 0.05). After 6 months of treatment, the rate of good treatment was 86.36% in the small-incision approach group and 77.78% in the ordinary approach group. After 1 year of treatment, the rate of excellent and good treatment was 90.91% in the small-incision approach group and 83.33% in the ordinary approach group. The rate of good treatment for half a year and 1 year in the small incision group was significantly higher than that in the common approach group (P < 0.05). In conclusion, MRI image based on deep learning algorithm has a high resolution, good display effect, and high application value. The small-incision approach can be applied to the treatment of proximal tibial fractures, which showed good therapeutic effects and a high positive clinical application value.

Can simultaneous immobilization of arsenic and cadmium in paddy soils be achieved by liming?

Liming acidic paddy soils to near-neutral pH is the most cost-effective strategy to minimize cadmium (Cd) accumulation by rice. However, the liming-induced effect on arsenic (As) (im)mobilization remains controversial and is called upon for further investigation, particularly for the safe utilization of paddy soils co-contaminated with As and Cd. Here, we explored As and Cd dissolution along pH gradients in flooded paddy soils and extracted key factors accounting for their release discrepancy with liming. The minimum As and Cd dissolution occurred concurrently at pH 6.5-7.0 in an acidic paddy soil (LY). In contrast, As release was minimized at pH < 6 in the other two acidic soils (CZ and XX), while the minimum Cd release still appeared at pH 6.5-7.0. Such a discrepancy was determined largely by the relative availability of Fe under overwhelming competition from dissolved organic carbon (DOC). A mole ratio of porewater Fe/DOC at pH 6.5-7.0 is suggested as a key indicator of whether co-immobilization of As and Cd can occur in flooded paddy soils with liming. In general, a high mole ratio of porewater Fe/DOC (≥ 0.23 in LY) at pH 6.5-7.0 can endow co-immobilization of As and Cd, regardless of Fe supplement, whereas such a case is not in the other two soils with lower Fe/DOC mole ratios (0.01-0.03 in CZ and XX). Taking the example of LY, the introduction of ferrihydrite promoted the transformation of metastable As and Cd fractions to more stable ones in the soil during 35 days of flooded incubation, thus meeting a class I soil for safe rice production. This study demonstrates that the porewater Fe/DOC mole ratio can indicate a liming-induced effect on co-(im)mobilization of As and Cd in typical acidic paddy soils, providing new insights into the applicability of liming practice for the paddy soils.

Alleviating experimental pulmonary hypertension via co-delivering FoxO1 stimulus and apoptosis activator to hyperproliferating pulmonary arteries.

Pulmonary hypertension (PH) is an insidious pulmonary vasculopathy with high mortality and morbidity and its underlying pathogenesis is still poorly delineated. The hyperproliferation and apoptosis resistance of pulmonary artery smooth muscle cells (PASMCs) contributes to pulmonary vascular remodeling in pulmonary hypertension, which is closely linked to the downregulation of fork-head box transcriptional factor O1 (FoxO1) and apoptotic protein caspase 3 (Cas-3). Here, PA-targeted co-delivery of a FoxO1 stimulus (paclitaxel, PTX) and Cas-3 was exploited to alleviate monocrotaline-induced pulmonary hypertension. The co-delivery system is prepared by loading the active protein on paclitaxel-crystal nanoparticles, followed by a glucuronic acid coating to target the glucose transporter-1 on the PASMCs. The co-loaded system (170 nm) circulates in the blood over time, accumulates in the lung, effectively targets the PAs, and profoundly regresses the remodeling of pulmonary arteries and improves hemodynamics, leading to a decrease in pulmonary arterial pressure and Fulton's index. Our mechanistic studies suggest that the targeted co-delivery system alleviates experimental pulmonary hypertension primarily via the regression of PASMC proliferation by inhibiting cell cycle progression and promoting apoptosis. Taken together, this targeted co-delivery approach offers a promising avenue to target PAs and cure the intractable vasculopathy in pulmonary hypertension.

Lithium-plasmon-based low-powered dynamic color display.

Display and power supply have been two essential and independent cornerstones of modern electronics. Here, we report a lithium-plasmon-based low-powered dynamic color display with intrinsic dual functionality (plasmonic display and energy recycling unit) which is a result of the electric-field-driven transformation of nanostructured lithium metals. Dynamic color displays are enabled by plasmonic transformation through electrodeposition (electrostripping) of lithium metals during the charging (discharging) process, while the consumed energy for coloring can be retrieved in the inverse process respectively. Energy recycling of lithium metals brings energy consumption down to 0.390 mW cm-2 (0.105 mW cm-2) for the active (static) coloration state of a proof-of-concept display/battery device, which approaches nearly-zero-energy-consumption in the near-100%-energy-efficiency limit of commercial lithium batteries. Combining the subwavelength feature of plasmonics with effective energy recycling, the lithium-plasmon-based dynamic display offers a promising route towards next-generation integrated photonic devices, with the intriguing advantages of low energy consumption, a small footprint and high resolution.

A vegetation classification method based on improved dual-way branch feature fusion U-net.

Aiming at the problems of complex structure parameters and low feature extraction ability of U-Net used in vegetation classification, a deep network with improved U-Net and dual-way branch input is proposed. Firstly, The principal component analysis (PCA) is used to reduce the dimension of hyperspectral remote sensing images, and the effective bands are obtained. Secondly, the depthwise separable convolution and residual connections are combined to replace the common convolution layers of U-Net for depth feature extraction to ensure classification accuracy and reduce the complexity of network parameters. Finally, normalized difference vegetation index (NDVI), gray level co-occurrence matrix (GLCM) and edge features of hyperspectral remote sensing images are extracted respectively. The above three artificial features are fused as one input, and PCA dimension reduction features are used as another input. Based on the improved U-net, a dual-way vegetation classification model is generated. Taking the hyperspectral remote sensing image of Matiwan Village, Xiong'an, Beijing as the experimental object, the experimental results show that the precision and recall of the improved U-Net are significantly improved with the residual structure and depthwise separable convolution, reaching 97.13% and 92.36% respectively. In addition, in order to verify the effectiveness of artificial features and dual-way branch design, the accuracy of single channel and the dual-way branch are compared. The experimental results show that artificial features in single channel network interfere with the original hyperspectral data, resulting in reduction of the recognition accuracy. However, the accuracy of the dual-way branch network has been improved, reaching 98.67%. It shows that artificial features are effective complements of network features.

EBE-YOLOv4: A lightweight detecting model for pine cones in forest.

Pine cones are important forest products, and the picking process is complex. Aiming at the multi-objective and dispersed characteristics of pine cones in the forest, a machine vision detection model (EBE-YOLOV4) is designed to solve the problems of many parameters and poor computing ability of the general YOLOv4, so as to realize rapid and accurate recognition of pine cones in the forest. Taking YOLOv4 as the basic framework, this method can realize a lightweight and accurate recognition model for pine cones in forest through optimized design of the backbone and the neck networks. EfficientNet-b0 (E) is chosen as the backbone network for feature extraction to reduce parameters and improve the running speed of the model. Channel transformation BiFPN structure (B), which improves the detection rate and ensures the detection accuracy of the model, is introduced to the neck network for feature fusion. The neck network also adds a lightweight channel attention ECA-Net (E) to solve the problem of accuracy decline caused by lightweight improvement. Meanwhile, the H-Swish activation function is used to optimize the model performance to further improve the model accuracy at a small computational cost. 768 images of pine cones in forest were used as experimental data, and 1536 images were obtained after data expansion, which were divided into training set and test set at the ratio of 8:2. The CPU used in the experiment was Inter Core i9-10885@2.40Ghz, and the GPU was NVIDIA Quadro RTX 5000. The performance of YOLOv4 lightweight design was observed based on the indicators of precision (P), recall (R) and detection frames per second (FPS). The results showed that the measurement accuracy (P) of the EBE-YOLOv4 was 96.25%, the recall rate (F) was 82.72% and the detection speed (FPS) was 64.09F/S. Compared with the original YOLOv4, the precision of detection had no significant change, but the speed increased by 70%, which demonstrated the effectiveness of YOLOv4 lightweight design.

Esophageal granular cell tumor: A case report.

BACKGROUND: Esophageal granular cell tumor (eGCT) is a relatively rare, usually benign neoplasm of the neuroectoderm. It is derived from Schwann cells. Clinical symptoms of this disease are non-specific. However, the most common presenting symptom is dysphagia, which is mostly misdiagnosed as esophageal polyps under gastroscopy, yet it has a 2% chance of forming cancers. We report the case of a 52-year-old woman with solitary eGCT, then analysed retrospectivelyanalyze the clinical features and elucidate on the reduction of misdiagnosis and missed diagnosis. CASE SUMMARY: A 52-year-old woman was diagnosed with "esophageal granulossoma" after esophagoscopy, which was mistaken for eGCT. CONCLUSION: eGCT diagnosis depends on characteristic pathomorphologies and detection of the S-100 protein. Endoscopic mucosal resection is the preferred therapeutic method.

Correlation between pleth variability index and ultrasonic inferior vena cava-collapsibility index in parturients with twin pregnancies undergoing cesarean section under spinal anesthesia.

BACKGROUND: To explore the correlation and consistency of non-invasive pleth variability index (PVI) combined with ultrasonic measurement of inferior vena cava-collapsibility index (IVC-CI) in parturients with twin pregnancies undergoing cesarean section under spinal anesthesia. METHODS: Forty-seven twin pregnancies women undergoing elective cesarean section were selected. The ASA score was rated as I-II, aged from 18 to 45 years. Spinal anesthesia was performed at L3-4. PVI and IVC-CI, general data (BMI, gestational weeks, operation duration, blood loss), MAP, temperature sensory block level and adverse reactions were recorded at baseline (T1) and completion of testing the level of spinal anesthesia (T2). RESULTS: The correlation coefficient analysis of baseline IVC-CI% and PVI revealed that the Pearson's coefficient was 0.927, > 0.4. Thus, pre-anesthesia IVC-CI% had a strong correlation with PVI, with R2 of 85.69%. The correlation coefficient analysis of post-anesthesia IVC-CI% and PVI revealed that the Pearson's coefficient was 0.904, > 0.4. Thus, post-anesthesia IVC-CI% had a strong correlation with PVI, with R2 of 81.26%. CONCLUSION: PVI is strongly consistent with ultrasound measurement of IVC-CI twin pregnancies, which can be used as a valuable index for predicting the volume in parturients with twin pregnancies undergoing cesarean section under spinal anesthesia. Trial registration This study was registered on ClinicalTrials.gov with clinical trial registration number of ChiCTR2200055364 (08/01/2022).