Immune dysregulation and autoreactivity correlate with disease severity in SARS-CoV-2-associated multisystem inflammatory syndrome in children.

Multisystem inflammatory syndrome in children (MIS-C) is a life-threatening post-infectious complication occurring unpredictably weeks after mild or asymptomatic SARS-CoV-2 infection. We profiled MIS-C, adult COVID-19, and healthy pediatric and adult individuals using single-cell RNA sequencing, flow cytometry, antigen receptor repertoire analysis, and unbiased serum proteomics, which collectively identified a signature in MIS-C patients that correlated with disease severity. Despite having no evidence of active infection, MIS-C patients had elevated S100A-family alarmins and decreased antigen presentation signatures, indicative of myeloid dysfunction. MIS-C patients showed elevated expression of cytotoxicity genes in NK and CD8+ T cells and expansion of specific IgG-expressing plasmablasts. Clinically severe MIS-C patients displayed skewed memory T cell TCR repertoires and autoimmunity characterized by endothelium-reactive IgG. The alarmin, cytotoxicity, TCR repertoire, and plasmablast signatures we defined have potential for application in the clinic to better diagnose and potentially predict disease severity early in the course of MIS-C.

The Effects of Photobiomodulation on Knee Function, Pain, and Exercise Tolerance in Older Adults: A Meta-analysis of Randomized Controlled Trials.

OBJECTIVE: To assess whether photobiomodulation therapy (PBMT) enhances the benefits of exercise in older adults. DATA SOURCES: PubMed, Scopus, Medline, and Web of Science, dated to February 2023. STUDY SELECTION: All included studies were randomized controlled trials of PBMT combined with exercise co-intervention in persons 60 years and older. OUTCOME MEASURES: Western Ontario and McMaster University Osteoarthritis Index (WOMAC-total, pain, stiffness and function), perceived pain intensity, timed Up and Go (TUG) Test, 6-min walk test (6MWT), muscle strength, and knee range of motion were included. DATA EXTRACTION: Two researchers independently performed data extraction. Article data were extracted in Excel and summarized by a third researcher. DATA SYNTHESIS: The meta-analysis included 14 of the 1864 studies searched in the database. No statistical differences were found between the treatment and control groups in terms of WOMAC-stiffness (mean difference [MD]=-0.31, 95% confidence interval [CI] -0.64 to 0.03), TUG (MD=-0.17, 95% CI -0.71 to 0.38), 6MWT (MD=32.2, 95% CI -44.62 to 109.01), or muscle strength (standardized mean difference=0.24, 95% CI -0.02 to 0.50). However, statistically significant differences were found for WOMAC-total (MD=-6.83, 95% CI -12.3 to -1.37), WOMAC-pain (MD=-2.03, 95% CI -4.06 to -0.01), WOMAC-function (MD=-5.03, 95% CI -9.11 to -0.96), visual analog scale/numeric pain rating scale (MD=-1.24, 95% CI -2.43 to -0.06), and knee range of motion (MD=1.47, 95% CI 0.07 to 2.88). CONCLUSIONS: In older adults who exercise regularly, PBMT can potentially provide additional pain relief, improve knee joint function, and increase knee joint range of motion.

Biological evaluation of novel phosphorylated pullulan-based calcium hydroxide formulations as direct pulp capping materials: An in vivo study on a rat model.

AIM: Calcium hydroxide (CH) has been considered as a direct pulp capping materials (DPC) for the last decades despite having some limitations. Phosphorylate pullulan (PPL) incorporated with CH (CHPPL) is a novel biomaterial that was introduced as a promising DPC material. Thus, the aim of the study was to evaluate the inflammatory response and mineralized tissue formation (MTF) ability of PPL-based CH formulations on rat molars after DPC. METHODOLOGY: This study consisted of six groups: CH with 1% PPL (CHPPL-1); 3% PPL (CHPPL-3); 5% PPL (CHPPL-5); Dycal and NEX MTA Cement (N-MTA) as the positive control, and no capping materials (NC). One hundred twenty maxillary first molar cavities were prepared on Wistar rats. After capping, all the cavities were restored with 4-META/MMA-TBB resin and pulpal responses were evaluated at days 1, 7, and 28. Kruskal-Wallis followed by Mann-Whitney U-test was performed with a significance level of 0.05. Immunohistochemical expression of IL-6, Nestin, and DMP-1 was observed. RESULTS: At day 1, CHPPL-1, N-MTA, and Dycal exhibited no to mild inflammation, whilst CHPPL-3, CHPPL-5, and NC showed mild to moderate inflammation, and the results were significantly different (p < .05). At day 7, mild to moderate inflammation was observed in CHPPL-1, N-MTA, and Dycal, whereas CHPPL-3, CHPPL-5, and NC exhibited moderate to severe inflammation. Significant differences were observed between CHPPL-1 and N-MTA with NC (p < .05), CHPPL-1 and CHPPL-3 with CHPPL-5 and Dycal (p < .05), and CHPPL-3 with N-MTA (p < .05). A thin layer of mineralized tissue formation (MTF) was observed in all groups. At day 28, CHPPL-1, Dycal, and N-MTA showed no to mild inflammation, whilst CHPPL-3, CHPPL-5, and NC exhibited mild to severe inflammation, and statistically significant difference was detected (p < .05). CHPPL-1, Dycal, and N-MTA exhibited continuous MTF, whilst CHPPL-3, CHPPL-5, and NC had thicker and interrupted MTF. Significant differences were observed between CHPPL-1, CHPPL-3, and N-MTA with NC group (p < .05). Variable expressions of IL-6, Nestin, and DMP-1 indicated differences in the materials' impact on odontoblast-like cell formation and tissue mineralization. CONCLUSIONS: These findings suggest that CHPPL-1 has the potential to minimize pulpal inflammation and promote MTF and had similar efficacy as MTA cement.

A New Network Structure for Speech Emotion Recognition Research.

Deep learning promotes the breakthrough of emotion recognition in many fields, especially speech emotion recognition (SER). As an important part of speech emotion recognition, the most relevant acoustic feature extraction has always attracted the attention of existing researchers. Aiming at the problem that the emotional information contained in the current speech signals is distributed dispersedly and cannot comprehensively integrate local and global information, this paper presents a network model based on a gated recurrent unit (GRU) and multi-head attention. We evaluate our proposed emotion model on the IEMOCAP and Emo-DB corpora. The experimental results show that the network model based on Bi-GRU and multi-head attention is significantly better than the traditional network model at detecting multiple evaluation indicators. At the same time, we also apply the model to a speech sentiment analysis task. On the CH-SIMS and MOSI datasets, the model shows excellent generalization performance.

Cross-Modal Supervised Human Body Pose Recognition Techniques for Through-Wall Radar.

Through-wall radar human body pose recognition technology has broad applications in both military and civilian sectors. Identifying the current pose of targets behind walls and predicting subsequent pose changes are significant challenges. Conventional methods typically utilize radar information along with machine learning algorithms such as SVM and random forests to aid in recognition. However, these approaches have limitations, particularly in complex scenarios. In response to this challenge, this paper proposes a cross-modal supervised through-wall radar human body pose recognition method. By integrating information from both cameras and radar, a cross-modal dataset was constructed, and a corresponding deep learning network architecture was designed. During training, the network effectively learned the pose features of targets obscured by walls, enabling accurate pose recognition (e.g., standing, crouching) in scenarios with unknown wall obstructions. The experimental results demonstrated the superiority of the proposed method over traditional approaches, offering an effective and innovative solution for practical through-wall radar applications. The contribution of this study lies in the integration of deep learning with cross-modal supervision, providing new perspectives for enhancing the robustness and accuracy of target pose recognition.

iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects.

BACKGROUND: Single-cell RNA sequencing (scRNA-seq) technology has enabled assessment of transcriptome-wide changes at single-cell resolution. Due to the heterogeneity in environmental exposure and genetic background across subjects, subject effect contributes to the major source of variation in scRNA-seq data with multiple subjects, which severely confounds cell type specific differential expression (DE) analysis. Moreover, dropout events are prevalent in scRNA-seq data, leading to excessive number of zeroes in the data, which further aggravates the challenge in DE analysis. RESULTS: We developed iDESC to detect cell type specific DE genes between two groups of subjects in scRNA-seq data. iDESC uses a zero-inflated negative binomial mixed model to consider both subject effect and dropouts. The prevalence of dropout events (dropout rate) was demonstrated to be dependent on gene expression level, which is modeled by pooling information across genes. Subject effect is modeled as a random effect in the log-mean of the negative binomial component. We evaluated and compared the performance of iDESC with eleven existing DE analysis methods. Using simulated data, we demonstrated that iDESC had well-controlled type I error and higher power compared to the existing methods. Applications of those methods with well-controlled type I error to three real scRNA-seq datasets from the same tissue and disease showed that the results of iDESC achieved the best consistency between datasets and the best disease relevance. CONCLUSIONS: iDESC was able to achieve more accurate and robust DE analysis results by separating subject effect from disease effect with consideration of dropouts to identify DE genes, suggesting the importance of considering subject effect and dropouts in the DE analysis of scRNA-seq data with multiple subjects.

Age-related changes in adipose tissue metabolomics and inflammation, cardiolipin metabolism, and ferroptosis markers in female aged rat model.

Aging adipose tissue exhibits elevated inflammation and oxidative stress that are major sources of age-related metabolic dysfunction. However, the exact metabolic changes associated with inflammation and oxidative stress are unclear. To address this topic, we assessed variation in metabolic phenotypes of adipose tissue from 18 months adult sedentary (ASED), 26 months old sedentary (OSED), and 8 months young sedentary (YSED). The results of metabolomic analysis showed that ASED and OSED group had higher palmitic acid, elaidic acid, 1-heptadecanol, and α-tocopherol levels than YSED, but lower sarcosine levels. Furthermore, stearic acid was specifically elevated in ASED compared with YSED. Cholesterol was upregulated specifically in the OSED group compared with YSED, whereas linoleic acid was downregulated. In addition, ASED and OSED had more inflammatory cytokines, lower antioxidant capacity, and higher expression of ferroptosis-related genes than YSED. Moreover, mitochondrial dysfunction associated with abnormal cardiolipin synthesis was more pronounced in the OSED group. In conclusion, both ASED and OSED can affect the FA metabolism and increase oxidative stress in adipose tissue, leading to inflammation. In particular, linoleic acid content specifically decreases in OSED, which associated with abnormal cardiolipin synthesis and mitochondrial dysfunction in adipose tissue.

WGX50 mitigates doxorubicin-induced cardiotoxicity through inhibition of mitochondrial ROS and ferroptosis.

BACKGROUND: Doxorubicin (DOX)-induced cardiotoxicity (DIC) is a major impediment to its clinical application. It is indispensable to explore alternative treatment molecules or drugs for mitigating DIC. WGX50, an organic extract derived from Zanthoxylum bungeanum Maxim, has anti-inflammatory and antioxidant biological activity, however, its function and mechanism in DIC remain unclear. METHODS: We established DOX-induced cardiotoxicity models both in vitro and in vivo. Echocardiography and histological analyses were used to determine the severity of cardiac injury in mice. The myocardial damage markers cTnT, CK-MB, ANP, BNP, and ferroptosis associated indicators Fe2+, MDA, and GPX4 were measured using ELISA, RT-qPCR, and western blot assays. The morphology of mitochondria was investigated with a transmission electron microscope. The levels of mitochondrial membrane potential, mitochondrial ROS, and lipid ROS were detected using JC-1, MitoSOX™, and C11-BODIPY 581/591 probes. RESULTS: Our findings demonstrate that WGX50 protects DOX-induced cardiotoxicity via restraining mitochondrial ROS and ferroptosis. In vivo, WGX50 effectively relieves doxorubicin-induced cardiac dysfunction, cardiac injury, fibrosis, mitochondrial damage, and redox imbalance. In vitro, WGX50 preserves mitochondrial function by reducing the level of mitochondrial membrane potential and increasing mitochondrial ATP production. Furthermore, WGX50 reduces iron accumulation and mitochondrial ROS, increases GPX4 expression, and regulates lipid metabolism to inhibit DOX-induced ferroptosis. CONCLUSION: Taken together, WGX50 protects DOX-induced cardiotoxicity via mitochondrial ROS and the ferroptosis pathway, which provides novel insights for WGX50 as a promising drug candidate for cardioprotection.

Long-term detraining reverses the improvement of lifelong exercise on skeletal muscle ferroptosis and inflammation in aging rats: fiber-type dependence of the Keap1/Nrf2 pathway.

We investigated the effects of lifelong aerobic exercise and 8 months of detraining after 10 months of aerobic training on circulation, skeletal muscle oxidative stress, and inflammation in aging rats. Sprague-Dawley rats were randomly assigned to the control (CON), detraining (DET), and lifelong aerobic training (LAT) groups. The DET and LAT groups began aerobic treadmill exercise at the age of 8 months and stopped training at the 18th and 26th month, respectively; all rats were sacrificed when aged 26 months. Compared with CON, LAT remarkably decreased serum and aged skeletal muscle 4-hydroxynonenal (4-HNE) and 8-hydroxy-2-deoxyguanosine (8-OHdG) levels. Superoxide dismutase 2(SOD2) levels were higher in the LAT group than in the CON group in skeletal muscle. However, DET remarkably decreased SOD2 protein expression and content in the skeletal muscle and increased malondialdehyde (MDA) level compared with LAT. Compared with LAT, DET remarkably downregulated adiponectin and upregulated tumor necrosis factor alpha (TNF-α) expression, while phosphoinositide 3-kinase (PI3K), protein kinase B (AKT), and 70-kDa ribosomal protein S6 kinase (P70S6K) protein expression decreased, and that of FoxO1 and muscle atrophy F-box (MAFbX) proteins increased in the quadriceps femoris. Adiponectin and TNF-α expression in the soleus muscle did not change between groups, whereas that of AKT, mammalian target of rapamycin (mTOR), and P70S6K was lower in the soleus in the DET group than in that in the LAT group. Compared with that in the LAT group, sestrin1 (SES1) and nuclear factor erythroid 2-related factor 2 (Nrf2) protein expression in the DET group was lower, whereas Keap1 mRNA expression was remarkably upregulated in the quadriceps femoris. Interestingly, the protein and mRNA levels of SES1, Nrf2, and Keap1 in soleus muscle did not differ between groups. LAT remarkably upregulated ferritin heavy polypeptide 1(FTH), glutathione peroxidase 4(GPX4), and solute carrier family 7member 11 (SLC7A11) protein expression in the quadriceps femoris and soleus muscles, compared with CON. However, compared with LAT, DET downregulated FTH, GPX4, and SLC7A11 protein expression in the quadriceps femoris and soleus muscles. Long-term detraining during the aging phase reverses the improvement effect of lifelong exercise on oxidative stress, inflammation, ferroptosis, and muscle atrophy in aging skeletal muscle. The quadriceps femoris is more evident than the soleus, which may be related to the different changes in the Keap1/Nrf2 pathway in different skeletal muscles.

Ultrasound-guided pericapsular nerve group (PENG) block for early analgesia in elderly patients with hip fractures: a single-center prospective randomized controlled study.

BACKGROUND: The aim of this study was to compare the efficacy of ultrasound-guided PENG (pericapsular nerve group) block and drug therapy with intravenous flurbiprofen for early analgesia in elderly patients with hip fractures after hospitalization. METHODS: This is a single-center, observer-blinded, prospective, randomized, controlled trial. A total of 41 elderly patients (aged 60 or older) with hip fractures were enrolled in the current study. Patients were randomly assigned to two groups: Group P (ultrasound-guided PENG block, 20 mL of 0.375% ropivacaine) and Group F (intravenous flurbiprofen 50 mg). The primary outcome measure was the dynamic (passive straight leg raising 15°) NRS (numerical rating scale 0 to 10) pain scores at different time points. The secondary outcomes were the static NRS scores at different time points, the number of rescue analgesia sessions, patient satisfaction, and the incidence of complications. RESULTS: Patients in the two groups had comparable baseline characteristics. The group P had lower dynamic and static NRS scores at 15 min, 30 min, 6 h, and 12 h after intervention (P<0.05) than the group F. The highest NRS pain scores in the group P were still lower than the NRS scores in the group F at 30 min-12 h (Group F: 5.57±1.54 vs. Group P: 3.00±1.12, P<0.001), and there was no significant difference between the two groups at 12-24 h (Group F: 6.35±1.79 vs. Group P: 5.90±1.83, P>0.05). The group P had higher satisfaction scores (Group P: 9 (9,9) vs. Group F: 8 (7,8), P<0.001). There was no statistically significant difference in the number of rescue analgesics at 0-12 h or 12-24 h or the incidence of complications between the groups. CONCLUSIONS: Compared with intravenous flurbiprofen, ultrasound-guided PENG block provides better early analgesic effects in elderly patients with hip fractures, and a PENG block is safe for elderly patients with hip fractures after hospitalization. Trial registration This study was registered in the Chinese Clinical Trial Testing Center (ID: ChiCTR2200062400).

SAR Image Ship Target Detection Adversarial Attack and Defence Generalization Research.

The synthetic aperture radar (SAR) image ship detection system needs to adapt to an increasingly complicated actual environment, and the requirements for the stability of the detection system continue to increase. Adversarial attacks deliberately add subtle interference to input samples and cause models to have high confidence in output errors. There are potential risks in a system, and input data that contain confrontation samples can be easily used by malicious people to attack the system. For a safe and stable model, attack algorithms need to be studied. The goal of traditional attack algorithms is to destroy models. When defending against attack samples, a system does not consider the generalization ability of the model. Therefore, this paper introduces an attack algorithm which can improve the generalization of models by based on the attributes of Gaussian noise, which is widespread in actual SAR systems. The attack data generated by this method have a strong effect on SAR ship detection models and can greatly reduce the accuracy of ship recognition models. While defending against attacks, filtering attack data can effectively improve the model defence capabilities. Defence training greatly improves the anti-attack capacity, and the generalization capacity of the model is improved accordingly.

Wide Temperature Range and Low Temperature Drift Eddy Current Displacement Sensor Using Digital Correlation Demodulation.

Conventional eddy-current sensors have the advantages of being contactless and having high bandwidth and high sensitivity. They are widely used in micro-displacement measurement, micro-angle measurement, and rotational speed measurement. However, they are based on the principle of impedance measurement, so the influence of temperature drift on sensor accuracy is difficult to overcome. A differential digital demodulation eddy current sensor system was designed to reduce the influence of temperature drift on the output accuracy of the eddy current sensor. The differential sensor probe was used to eliminate common-mode interference caused by temperature, and the differential analog carrier signal was digitized by a high-speed ADC. In the FPGA, the amplitude information is resolved using the double correlation demodulation method. The main sources of system errors were determined, and a test device was designed using a laser autocollimator. Tests were conducted to measure various aspects of sensor performance. Testing showed the following metrics for the differential digital demodulation eddy current sensor: nonlinearity 0.68% in the range of ±2.5 mm, resolution 760 nm, maximum bandwidth 25 kHz, and significant suppression in the temperature drift compared to analog demodulation methods. The tests show that the sensor has high precision, low temperature drift and great flexibility, and it can instead of conventional sensors in applications with large temperature variability.

Destriping of Remote Sensing Images by an Optimized Variational Model.

Satellite sensors often capture remote sensing images that contain various types of stripe noise. The presence of these stripes significantly reduces the quality of the remote images and severely affects their subsequent applications in other fields. Despite the existence of many stripe noise removal methods in the research, they often result in the loss of fine details during the destriping process, and some methods even generate artifacts. In this paper, we proposed a new unidirectional variational model to remove horizontal stripe noise. The proposed model fully considered the directional characteristics and structural sparsity of the stripe noise, as well as the prior features of the underlying image, to design different sparse constraints, and the ℓp quasinorm was introduced in these constraints to better describe these sparse characteristics, thus achieving a more excellent destriping effect. Moreover, we employed the fast alternating direction method of multipliers (ADMM) to solve the proposed non-convex model. This significantly improved the efficiency and robustness of the proposed method. The qualitative and quantitative results from simulated and real data experiments confirm that our method outperforms existing destriping approaches in terms of stripe noise removal and preservation of image details.

Improved Strong Tracking Cubature Kalman Filter for UWB Positioning.

For the problems of Non-Line-of-Sight (NLOS) observation errors and inaccurate predictive dynamics model in wireless ultra-wideband (UWB) positioning systems, an improved strong tracking cubature Kalman filter (ISTCKF) positioning algorithm is proposed in this paper. The main idea of the algorithm is as follows. First, the observations are reconstructed based on the weighted positioning results obtained from the predictive dynamics model and the least squares algorithm. Second, the difference in statistical properties between the observation noise and the NLOS errors is utilized to identify the NLOS observations by the corresponding judgment statistics obtained from the operation between the original observations and the reconstructed observations. The main positioning error of the UWB positioning system at the current moment is then judged by the NLOS identification results, and the corresponding fading factors are calculated according to the judgment results. Finally, the corresponding ISTCKF is constructed based on the fading factors to mitigate the main positioning error and obtain accurate positioning result in the UWB positioning system. In this paper, the reconstructed observations mitigate the observation noise in the original observation, and then the ISTCKF mitigates the main errors in the UWB positioning system. The experimental results show that the ISTCKF algorithm reduces the positioning error by 55.2%, 32.3% and 28.9% compared with STCKF, ACKF and RSTCKF, respectively. The proposed ISTCKF algorithm significantly improves the positioning accuracy and stability of the UWB system.

Improved Thermal Infrared Image Super-Resolution Reconstruction Method Base on Multimodal Sensor Fusion.

When traditional super-resolution reconstruction methods are applied to infrared thermal images, they often ignore the problem of poor image quality caused by the imaging mechanism, which makes it difficult to obtain high-quality reconstruction results even with the training of simulated degraded inverse processes. To address these issues, we proposed a thermal infrared image super-resolution reconstruction method based on multimodal sensor fusion, aiming to enhance the resolution of thermal infrared images and rely on multimodal sensor information to reconstruct high-frequency details in the images, thereby overcoming the limitations of imaging mechanisms. First, we designed a novel super-resolution reconstruction network, which consisted of primary feature encoding, super-resolution reconstruction, and high-frequency detail fusion subnetwork, to enhance the resolution of thermal infrared images and rely on multimodal sensor information to reconstruct high-frequency details in the images, thereby overcoming limitations of imaging mechanisms. We designed hierarchical dilated distillation modules and a cross-attention transformation module to extract and transmit image features, enhancing the network's ability to express complex patterns. Then, we proposed a hybrid loss function to guide the network in extracting salient features from thermal infrared images and reference images while maintaining accurate thermal information. Finally, we proposed a learning strategy to ensure the high-quality super-resolution reconstruction performance of the network, even in the absence of reference images. Extensive experimental results show that the proposed method exhibits superior reconstruction image quality compared to other contrastive methods, demonstrating its effectiveness.

Dual-Engine Powered Paper Photoelectrochemical Platform Based on 3D DNA Nanomachine-Mediated CRISPR/Cas12a for Detection of Multiple miRNAs.

This work proposed a novel double-engine powered paper photoelectrochemical (PEC) biosensor based on an anode-cathode cooperative amplification strategy and various signal enhancement mechanisms, which realized the monitoring of multiple miRNAs (such as miRNA-141 and miRNA-21). Specifically, C3N4 quantum dots (QDs) sensitized ZnO nanostars and BiOI nanospheres simultaneously to construct a composite photoelectric layer that amplified the original photocurrent of the photoanode and photocathode, respectively. Through the independent design and partition of a flexible paper chip to functionalize injection holes and electrode areas, the bipolar combination completed the secondary upgrade of signals, which also provided biological reaction sites for multitarget detection. With the synergistic participation of a three-dimensional (3D) DNA nanomachine and programmable CRISPR/Cas12a shearing tool, C3N4 QDs lost their attachment away from the electrode surface to quench the signal. Moreover, electrode zoning significantly reduced the spatial cross talk of related substances for multitarget detection, while the universal trans-cleavage capability of CRISPR/Cas12a simplified the operation. The designed PEC biosensor revealed excellent linear ranges for detection of miRNA-141 and miRNA-21, for which the detection limits were 5.5 and 3.4 fM, respectively. With prominent selectivity and sensitivity, the platform established an effective approach for trace multitarget monitoring in clinical applications, and its numerous pioneering attempts owned favorable reference values.

G2S3: A gene graph-based imputation method for single-cell RNA sequencing data.

Single-cell RNA sequencing technology provides an opportunity to study gene expression at single-cell resolution. However, prevalent dropout events result in high data sparsity and noise that may obscure downstream analyses in single-cell transcriptomic studies. We propose a new method, G2S3, that imputes dropouts by borrowing information from adjacent genes in a sparse gene graph learned from gene expression profiles across cells. We applied G2S3 and ten existing imputation methods to eight single-cell transcriptomic datasets and compared their performance. Our results demonstrated that G2S3 has superior overall performance in recovering gene expression, identifying cell subtypes, reconstructing cell trajectories, identifying differentially expressed genes, and recovering gene regulatory and correlation relationships. Moreover, G2S3 is computationally efficient for imputation in large-scale single-cell transcriptomic datasets.

Hematoporphyrin monomethyl ether mediated photodynamic therapy inhibits oral squamous cell carcinoma by regulating the P53-miR-21-PDCD4 axis via singlet oxygen.

The objective of this study was to determine the mechanism and effect of hematoporphyrin monomethyl ether mediated photodynamic therapy (HMME-PDT) on oral squamous cell carcinoma (OSCC). Human OSCC CAL-27 cells were randomly divided into four groups: control group, HMME group, laser group, and HMME-PDT group. Cell viability was detected by the CCK-8 method. Cell cycle distribution was evaluated by flow cytometry. GEO database was used to screen differentially expressed microRNAs (DEMs), and TCGA database was performed to verify DEM expression in OSCC and normal tissues. The effects of HMME-PDT on DEM expression were assayed by real-time PCR, and the expressions of miRNAs target genes were measured by western blot. Fluorescence probes were used to determine the production of singlet oxygen (1O2). Compared with the other three groups, HMME-PDT dramatically inhibited CAL-27 cell proliferation and induced G0/G1 cycle arrest. The expressions of miR-21 and miR-155 were significantly upregulated in OSCC. HMME-PDT downregulated the expression of miR-21 but had no obvious effect on miR-155. HMME-PDT remarkably upregulated the levels of P53 and miR-21 target proteins, such as PDCD4, RECK, and SPRY2. 1O2 was generated during HMME-PDT, and inhibition of 1O2 production could reverse the regulation of HMME-PDT on P53, miR-21, and its target proteins, thus restoring cell viability. HMME-PDT can significantly inhibit the growth of OSCC cells, and the mechanism of this effect is related to the regulation of the P53-miR-21-PDCD4 axis via 1O2 induced by HMME-PDT.

Target Detection Based on Improved Hausdorff Distance Matching Algorithm for Millimeter-Wave Radar and Video Fusion.

The intelligent transportation system (ITS) is inseparable from people's lives, and the development of artificial intelligence has made intelligent video surveillance systems more widely used. In practical traffic scenarios, the detection and tracking of vehicle targets is an important core aspect of intelligent surveillance systems and has become a hot topic of research today. However, in practical applications, there is a wide variety of targets and often interference factors such as occlusion, while a single sensor is unable to collect a wealth of information. In this paper, we propose an improved data matching method to fuse the video information obtained from the camera with the millimetre-wave radar information for the alignment and correlation of multi-target data in the spatial dimension, in order to address the problem of poor recognition alignment caused by mutual occlusion between vehicles and external environmental disturbances in intelligent transportation systems. The spatio-temporal alignment of the two sensors is first performed to determine the conversion relationship between the radar and pixel coordinate systems, and the calibration on the timeline is performed by Lagrangian interpolation. An improved Hausdorff distance matching algorithm is proposed for the data dimension to calculate the similarity between the data collected by the two sensors, to determine whether they are state descriptions of the same target, and to match the data with high similarity to delineate the region of interest (ROI) for target vehicle detection.

Analysis and Correction of Measurement Error of Spherical Capacitive Sensor Caused by Assembly Error of the Inner Frame in the Aeronautical Optoelectronic Pod.

The ball joint is a multi-degree-of-freedom transmission pair, if it can replace the inner frame in the aviation photoelectric pod to carry the optical load, which will greatly simplify the system structure of the photoelectric pod and reduce the space occupied by the inner frame. However, installation errors in ball joint siting introduce nonlinear errors that are difficult to correct and two degree of freedom angular displacement of the ball joint is difficult to detect, which limits application in the precision control of two degrees of freedom systems. Studies of spherical capacitive sensors to date have not tested sensors for use in an inner frame stabilisation mechanism nor have they analysed the influence of installation error on sensor output. A two-axis angular experimental device was designed to measure the performance of a ball joint capacitive sensor in a frame stabilisation mechanism in an aeronautical optoelectronic pod, and a mathematical model to compensate for ball joint capacitive sensor installation error was created and tested. The experimental results show that the resolution of the capacitive sensor was 0.02° in the operating range ±4°, the repeatability factor was 0.86%, and the pulse response time was 39 µs. The designed capacitive sensor has a simple structure, high measurement accuracy, and strong robustness, and it can be integrated into ball joint applications in the frames of aeronautical photoelectric pods.