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Abstract Controlling the temporal evolution of an electromagnetic (EM) wave’s frequency components, the so-called time-frequency (TF) distribution, in a versatile and real-time fashion remains very challenging, especially at the high speeds (> GHz regime) required in contemporary communication, imaging, and sensing applications. We propose a general framework for manipulating the TF properties of high-speed EM waves. Specifically, the TF distribution is continuously mapped along the time domain through phase-only processing, enabling its user-defined manipulation via widely-available temporal modulation techniques. The time-mapping operations can then be inverted to reconstruct the TF-processed signal. Using off-the-shelf telecommunication components, we demonstrate arbitrary control of the TF distribution of EM waves over a full bandwidth approaching 100 GHz with nanosecond-scale programmability and MHz-level frequency resolution. We further demonstrate applications for mitigating rapidly changing frequency interference terms and the direct synthesis of fast waveforms with customized TF distributions. The reported method represents a significant advancement in TF processing of EM waves and it fulfills the stringent requirements for many modern and emerging applications.

Abstract Background Subarachnoid hemorrhage (SAH) is a life -threatening cerebrovascular disease, where early brain injury (EBI) stands as a primary contributor to mortality and unfavorable patient outcomes. Neuronal ferroptosis emerges as a key pathological mechanism underlying EBI in SAH. Targeting ferroptosis for therapeutic intervention in SAH holds significant promise as a treatment strategy. Methods SAH model was induced via intravascular puncture and quantitatively assessed the presence of neuronal ferroptosis in the early phase of SAH using FJC staining, Prussian blue staining, as well as malondialdehyde (MDA) and glutathione (GSH) measurements. Hyaluronic acid-coated ursolic acid nanoparticles (HA-PEG-UA NPs) were prepared using the solvent evaporation method. We investigated the in vivo distribution of HA-PEG-UA NPs in SAH model through IVIS and fluorescence observation, and examined their impact on short-term neurological function and cortical neurological injury. Finally, we assessed the effect of UA on the Nrf-2/SLC7A11/GPX4 axis via Western Blot analysis. Results We successfully developed self-assembled UA NPs with hyaluronic acid to target the increased CD44 expression in the SAH-afflicted brain. The resulting HA-PEG-UA NPs facilitated delivery and enrichment of UA within the SAH-affected region. The targeted delivery of UA to the SAH region can effectively inhibit neuronal ferroptosis, improve neurological deficits, and prognosis in mice. Its mechanism of action is associated with the activation of the Nrf-2/SLC7A11/GPX4 signaling pathway. Conclusions Brain-targeted HA-PEG-UA NPs was successfully developed and hold the potential to enhance SAH prognosis by limiting neuronal ferroptosis via modulation of the Nrf-2/SLC7A11/GPX4 signal. Graphical Abstract

Abstract Fungal diseases are the main factors affecting the quality and production of vegetables. Rapid and accurate detection of pathogenic spores is of great practical significance for early prediction and prevention of diseases. However, there are some problems with microscopic images collected in the natural environment, such as complex backgrounds, more disturbing materials, small size of spores, and various forms. Therefore, this study proposed an improved detection method of GCS-YOLOv8 (Global context and CARFAE and Small detector-optimized YOLOv8), effectively improving the detection accuracy of small-target pathogen spores in natural scenes. Firstly, by adding a small target detection layer in the network, the network’s sensitivity to small targets is enhanced, and the problem of low detection accuracy of the small target is effectively improved. Secondly, Global Context attention is introduced in Backbone to optimize the CSPDarknet53 to 2-Stage FPN (C2F) module and model global context information. At the same time, the feature up-sampling module Content-Aware Reassembly of Features (CARAFE) was introduced into Neck to enhance the ability of the network to extract spore features in natural scenes further. Finally, we used an Explainable Artificial Intelligence (XAI) approach to interpret the model’s predictions. The experimental results showed that the improved GCS-YOLOv8 model could detect the spores of the three fungi with an accuracy of 0.926 and a model size of 22.8 MB, which was significantly superior to the existing model and showed good robustness under different brightness conditions. The test on the microscopic images of the infection structure of cucumber down mildew also proved that the model had good generalization. Therefore, this study realized the accurate detection of pathogen spores in natural scenes and provided feasible technical support for early predicting and preventing fungal diseases.

Abstract Cephalopods can change their skin color by using high‐speed electron transduction among receptors, neural networks, and pigmentary effectors. However, it remains challenging to realize a neuroelectrical transmission system like that found in cephalopods, where electrons/ions transmit on nanoscale, which is crucial for fast adaptive electrochromic tuning. Inspired by that, hereby an ideal, rapidly responsive, and multicolor electrochromic biomimetic skin is introduced. Specifically, the biomimetic skin comprises W18O49 nanowires (NWs) that are either colorless or blue, Au nanoparticles@polyaniline (Au NPs@PANI) ranging from green to pink, and a flexible conductive substrate. As the applied voltage changes from 0.4 V to ‐0.7 V and back to 0 V, the color of the biomimetic skin transforms from green to blue and ultimately to pink. This color change is attributed to the electrically induced redox reaction of Au NPs@PANI and W18O49 NWs, triggered by the transfer of electrons and ions. Furthermore, the high versatility and adaptability of electrical stimulus enable the creation of a highly interactive electrochromic biomimetic skin system through the integration of sensitive acoustic sensors, providing a perfect environment‐responsive platform. This work provides a biomimetic multicolor electrochromic skin that depends on electron/ion transfer on nanoscale, expands potential uses for camouflage skin.

PurposeTo explore the relationship between parenting styles and self-concept, emotional intelligence, and subjective well-being among primary school students.MethodsIn total, 1,683 students from 10 primary schools in Hangzhou, China, were surveyed using a simple random sampling method. Participants completed the Parenting Style Scale, the Self-Concept Scale, the Emotional Intelligence Scale, and the Subjective Well-Being Scale.Results(1) Father’s and mother’s emotional warmth was significantly positively correlated with students’ subjective well-being (r = 0.513, p

BackgroundPrevious research has indicated that engagement in social activities has proven advantageous for diminishing the likelihood of cognitive decline. However, no study has examined whether such cognitive benefits were to a similar extent for the young-old, the old–old, and the oldest-old groups. The purpose of this research was to determine whether aging would have an impact on the changes in cognitive function that would occur in older adults with varying degrees of social involvement.MethodsThe sample for this study comprised 4,481 older adults who participated in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) during the waves spanning from 2008 to 2018. At baseline, participants were classified into the young-old (60–69 years; Mage = 66.66; SD = 1.87), the old–old (70–79 years; Mage = 74.21; SD = 2.82), and the oldest-old (80 years or older; Mage = 86.46; SD = 5.71) groups.ResultsThe level of cognitive function decreased as participants aged. Importantly, compared to those lacking social activities, individuals who were got involved in social engagement at baseline had slower rates of cognitive decline over time. Furthermore, compared with the young-old group and the old–old group, the impact of social activity engagement on slowing cognitive decline was more salient for the oldest-old group.ConclusionActive engagement in social activities can slow age-related cognitive decline, particularly for the oldest-old group. To preserve cognitive function with aging, attention and resources should be allocated to encourage social activity engagement.

Summary: Maternal immune activation (MIA) is critical for imparting neuropathology and altered behaviors in offspring; however, maternal-fetal immune cell populations have not been thoroughly investigated in MIA-induced autism spectrum disorders (ASDs). Here, we report the single-cell transcriptional landscape of placental cells in both PBS- and poly(I:C)-induced MIA dams. We observed a decrease in regulatory T (Treg) cells but an increase in the M1 macrophage population at the maternal-fetal interface in MIA dams. Based on the Treg-targeting approach, we investigate an immunoregulatory protein, the helminth-derived heat shock protein 90α (Sjp90α), that induces maternal Treg cells and subsequently rescues the autism-like behaviors in adult offspring. Furthermore, in vivo depletion of maternal macrophages attenuates placental inflammatory reaction and reverses behavioral abnormalities in adult offspring. Notably, Sjp90α induces CD4+ T cell differentiation via scavenger receptor A (SR-A) on the macrophage in vitro. Our findings suggest a maternal Treg-targeted approach to alleviate MIA-induced autism-like behavior in adult offspring.

Subarachnoid hemorrhage (SAH) is a life-threatening acute hemorrhagic cerebrovascular disease, with early brain injury (EBI) being the main cause of high mortality and severe neurological dysfunction. Oxidative stress plays a crucial role in the pathogenesis of EBI. In this study, we synthesized antioxidant stress nanoparticles based on self-assembled oleanolic acid (OA) using the solvent volatilization method. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and transmission electron microscopy (TEM) techniques were employed to analyze and understand the self-assembly mechanism of oleic acid nanoparticles (OA NPs). The TUNEL assay, Nissl staining, and brain water content measurements were conducted to investigate the impact of OA NPs on cortical neuronal injury. Additionally, Western blot analysis was performed to investigate the antioxidant stress mechanism of OA NPs. The result showed that OA NPs exhibited a spherical structure with an average diameter of 168 nm. The application of OA NPs in SAH has been found to contribute to the reduction of keap1 protein levels and an increase in the nuclear level of Nrf2. As a result, the transcription of antioxidant stress proteins, including HO1 and NQO1, is triggered. The activation of the antioxidant stress pathway by OA NPs ultimately leads to a decrease in neuron damage and an improvement in neurological dysfunction. In conclusion, we successfully designed and synthesized OA NPs that can efficiently target the site of SAH. These nanoparticles have demonstrated their potential as antioxidants for the treatment of SAH, offering significant clinical applications.

IntroductionDexmedetomidine is often used as an adjunct to total intravenous anesthesia (TIVA) for procedures requiring intraoperative neurophysiologic monitoring (IONM). However, it has been reported that dexmedetomidine might mask the warning of a neurological deficit on intraoperative monitoring.MethodsWe reviewed the intraoperative neurophysiological monitoring data of 47 patients who underwent surgery and IONM from March 2019 to March 2021 at the Department of Neurosurgery, Renmin Hospital of Wuhan University. Pre- and postoperative motor function scores were recorded and analyzed. Dexmedetomidine was administered intravenously at 0.5 μg/kg/h 40 min after anesthesia and discontinued after 1 h in the dexmedetomidine group.ResultsWe found that the amplitude of transcranial motor-evoked potentials (Tce-MEPs) was significantly lower in the dexmedetomidine group than in the negative control group (P

Summary: Foodborne illness caused by consuming foods contaminated by pathogens remains threating to the public health. Despite considerable efforts of using renewable source materials, it is highly demanding to fabricate food packaging with multiple properties including eco-friendliness, bactericidal effect and biocompatibility. Here, sodium lignosulfonate (SL) and ZnO nanoparticles (ZnO NPs) were used as functional filler and structure components, respectively, on the cellulose nanofibers (CNFs)-based films, which endows the produced membrane (CNF/SL-ZnO) the UV-light blocking, antioxidant, and antimicrobial characteristics. Due to the interconnected polymeric structure, the prepared CNF/SL-ZnO films possessed considerable mechanical properties, thermal stability, and good moisture barrier capability. Moreover, the tested samples exhibited an improved shelf life in food packaging. Furthermore, metagenome analysis revealed superior biodegradability of obtained films with negligible side effect on the soil microenvironment. Therefore, the biocompatible, degradable, and antibacterial CNF/SL-ZnO film holds enormous potential for sustainable uses including food packaging.

The Three Gorges Reservoir Area (TGRA) is an important ecological barrier in the Yangtze River Basin, China. Therefore, it is of great importance to understand the spatio-temporal variation and the driving factors of production-living-ecological spaces for sustainable and high-quality development in the TGRA. This study investigated the dynamic variation of production-living-ecological spaces in the TGRA by employing land use data in 2000, 2005, 2010, 2015, and 2018, and detected the influencing factors by using the Geographic detector (GeoDetector). Results implied that the structure and dynamic trajectories of production-living-ecological spaces in the TGRA varied in both horizontal and vertical directions, and the study area was dominated by ecological space. A spatial orientation towards the northeast was detected in the evolution of production-living-ecological spaces during 2000–2018. In terms of quantity, the transition from ecological space (grassland and woodland) to agriculture land accounted for the largest proportion from 2000 to 2018. However, the reverse transition from agriculture land to ecological space has increased since 2000 with the efforts of “Grain for Green”. In terms of temporal scale, there was a fluctuating trend in production space with the continuous expansion of living space, while ecological space showed an inverted U-shaped trend during 2000–2018. The dynamic pattern of production-living-ecological spaces in the TGRA was influenced by both physical and socio-economic variables as basic determinants and dominant driving factors, respectively. Finally, the harmonization and protection of production-living-ecological spaces still require policy-makers’ efforts. This work may have potential in advancing our understanding about land use conflicts, and provide a reference for rational layout of spatial functions and the realization of sustainable development in the TGRA.

With the development of the IoT, Wireless Rechargeable Sensor Networks (WRSNs) derive more and more application scenarios with diverse performance requirements. In scenarios where the energy consumption rate of sensor nodes changes dynamically, most existing charging scheduling methods are not applicable. The incorrect estimation of node energy requirement may lead to the death of critical nodes, resulting in missing events. To address this issue, we consider both the spatial imbalance and temporal dynamics of the energy consumption of the nodes, and minimize the Event Missing Rate (EMR) as the goal. Firstly, an Energy Consumption Balanced Tree (ECBT) construction method is proposed to prolong the lifetime of each node. Then, we transform the goal into Maximizing the value of the Evaluation function of each node’s Energy Consumption Rate prediction (MEECR). Afterwards, the setting of the evaluation function is explored and the MEECR is further transformed into a variant of the knapsack problem, namely “the alternating backpack problem”, and solved by dynamic programming. After predicting the energy consumption rate of the nodes, a charging scheduling scheme that meets the Dual Constraints of Nodes’ energy requirements and MC’s capability (DCNM) is developed. Simulations demonstrate the advantages of the proposed method. Compared to the baselines, the EMR was reduced by an average of 35.2% and 26.9%.

Objectives Systemic lupus erythematosus (SLE) is a highly heterogeneous disease, and B cell abnormalities play a central role in the pathogenesis of SLE. Long non-coding RNAs (lncRNAs) have also been implicated in the pathogenesis of SLE. The expression of lncRNAs is finely regulated and cell-type dependent, so we aimed to identify B cell-expressing lncRNAs as biomarkers for SLE, and to explore their ability to reflect the status of SLE critical pathway and disease activity.Methods Weighted gene coexpression network analysis (WGCNA) was used to cluster B cell-expressing genes of patients with SLE into different gene modules and relate them to clinical features. Based on the results of WGCNA, candidate lncRNA levels were further explored in public bulk and single-cell RNA-sequencing data. In another independent cohort, the levels of the candidate were detected by RT-qPCR and the correlation with disease activity was analysed.Results WGCNA analysis revealed one gene module significantly correlated with clinical features, which was enriched in type I interferon (IFN) pathway. Among non-coding genes in this module, lncRNA RP11-273G15.2 was differentially expressed in all five subsets of B cells from patients with SLE compared with healthy controls and other autoimmune diseases. RT-qPCR validated that RP11-273G15.2 was highly expressed in SLE B cells and positively correlated with IFN scores (r=0.7329, p

The effect of underwater noise environment generated by equipment in industrial recirculating aquaculture systems (RAS) on fish is evident. However, different equipment generate noise in various frequency ranges. Understanding the effects of different frequency ranges noise on cultured species is important for optimizing the underwater acoustic environment in RAS. Given this, the effects of underwater noise across various frequency bands in RAS on the growth, physiology, and collective behavior of juvenile largemouth bass (Micropterus salmoides) were comprehensively evaluated here. In this study, three control groups were established: low-frequency noise group (80–1000 Hz, 117 dB re 1μPa RMS), high-frequency noise group (1–19 kHz, 117 dB re 1μPa RMS), and ambient group. During a 30-day experiment, it was found that: 1) industrial RAS noise with different frequency bands all had a certain inhibitory effect on the growth of fish, which the weight gain rate and product of length and depth of caudal peduncle in the ambient group were significantly higher than those of the two noise groups, with the low-frequency noise group showing significantly lower values than the high-frequency noise group; 2) industrial RAS noise had a certain degree of adverse effect on the digestive ability of fish, with the low-frequency noise group being more affected; 3) industrial RAS noise affected the collective feeding behavior of fish, with the collective feeding signal propagation efficiency and feeding intensity of the noise groups being significantly lower than those of the ambient group, and the high-frequency noise group performing better than the low-frequency noise group as a whole therein. From the above, the underwater noise across different frequency bands generated by equipment operation in industrial RAS both had an impact on juvenile largemouth bass, with the low-frequency noise group being more severely affected.

Abstract Background Glycemic gap, as a novel index of acute glycemic excursion, is associated with poor prognosis of different diseases. This study aimed to explore the association of the glycemic gap with long‐term stroke recurrence in patients with ischemic stroke. Methods This study included patients with ischemic stroke from the Nanjing Stroke Registry Program. The glycemic gap was calculated by subtracting the estimated average blood glucose from the blood glucose at admission. Multivariable Cox proportional hazards regression analysis was performed to explore the association between the glycemic gap and the risk of stroke recurrence. The Bayesian hierarchical logistic regression model was used to estimate the effects of the glycemic gap on stroke recurrence stratified by diabetes mellitus and atrial fibrillation. Results Among 2734 enrolled patients, 381 (13.9%) patients experienced stroke recurrence during a median follow‐up of 3.02 years. In multivariate analysis, glycemic gap (high group vs. median group) was associated with significantly increased risk for stroke recurrence (adjusted hazard ratio, 1.488; 95% confidence interval, 1.140–1.942; p = .003) and had varying effects on stroke recurrence depending on atrial fibrillation. The restricted cubic spline curve showed a U‐shaped relationship between the glycemic gap and stroke recurrence (p = .046 for nonlinearity). Conclusion Our study found that the glycemic gap was significantly associated with stroke recurrence in patients with ischemic stroke. The glycemic gap was consistently associated with stroke recurrence across subgroups and had varying effects depending on atrial fibrillation.

The relations between shyness and internalizing problems have been mainly explored at the individual level, with little known about its dynamics at the group level. This study aims to examine the mediating effect of individual-level sport engagement and the moderating effect of class-level sport participation in the relations between shyness and internalizing problems. The participants were 951 children attending primary and middle school from grade 3 to grade 7 (Mage = 11 years, 509 boys) in urban areas of China. Cross-sectional data were collected using self-report assessments. Multi-level analysis indicated that (1) shyness was positively associated with internalizing problems; (2) sport engagement partially mediated the relations between shyness and internalizing problems; and (3) class sport participation was a cross-level moderator in the mediating relations between shyness, sport engagement, and internalizing problems. Shy children in classes with a higher level of sport participation tend to have less sport engagement and more internalizing problems than those in classes with a lower level of sport participation. These findings illuminate implications from a multi-level perspective for shy children’s adjustment in a Chinese context. The well-being of shy children could be improved by intervening in sport activity, addressing both individual engagement and group dynamics, such as class participation.

In the domain of supervised learning, interpolation and extrapolation serve as crucial methodologies for predicting data points within and beyond the confines of a given dataset, respectively. The efficacy of these methods is closely linked to the nature of the dataset, with increased challenges when multivariate feature vectors are handled. This paper introduces a novel prediction framework that integrates interpolation and extrapolation techniques. Central to this method are two main innovations: an optimization model that effectively classifies new multivariate data points as either interior or exterior to the known dataset, and a hybrid prediction system that combines k-nearest neighbor (kNN) and linear regression. Tested on the port state control (PSC) inspection dataset at the port of Hong Kong, our framework generally demonstrates superior precision in predictive outcomes than traditional kNN and linear regression models. This research enriches the literature by illustrating the enhanced capability of combining interpolation and extrapolation techniques in supervised learning.

Modal parameter estimation is crucial in vibration-based damage detection and deserves increased attention and investigation. Concrete arch dams are prone to damage during severe seismic events, leading to alterations in their structural dynamic characteristics and modal parameters, which exhibit specific time-varying properties. This highlights the significance of investigating the evolution of their modal parameters and ensuring their accurate identification. To effectively accomplish the recursive estimation of modal parameters for arch dams, an adaptive recursive subspace (ARS) method with variable forgetting factors was proposed in this study. In the ARS method, the variable forgetting factors were adaptively updated by assessing the change rate of the spatial Euclidean distance of adjacent modal frequency identification values. A numerical simulation of a concrete arch dam under seismic loading was conducted by using ABAQUS software, in which a concrete damaged plasticity (CDP) model was used to simulate the dam body’s constitutive relation, allowing for the assessment of damage development under seismic loading. Utilizing the dynamic responses obtained from the numerical simulation, the ARS method was implemented for the modal parameter recursive estimation of the arch dam. The identification results revealed a decreasing trend in the frequencies of the four initial modes of the arch dam: from an undamaged state characterized by frequencies of 0.910, 1.166, 1.871, and 2.161 Hz to values of 0.895, 1.134, 1.842, and 2.134 Hz, respectively. Concurrently, increases in the damping ratios of these modes were observed, transitioning from 4.44%, 4.28%, 5.42%, and 5.56% to 4.98%, 4.91%, 6.61%, and 6.85%%, respectively. The correlation of the identification results with damage progression validated the effectiveness of the ARS method. This study’s outcomes have substantial theoretical and practical importance, facilitating the immediate comprehension of the dynamic characteristics and operational states of concrete arch dam structures.

The input current ripple problem of DC/DC converters receives more and more attention recently. To meet the increasingly demanding requirements, the fundamental components of the current ripple are researched and the corresponding current ripple reduction methods are proposed in this paper. On the one hand, due to the imbalance between the input and output power of the whole system when connected to the grid, the 100-Hz bus voltage ripple is induced. If the bus voltage ripple cannot be regulated effectively, the 100-Hz ripple will be reflected in the DC input side. On the other hand, with low pulse-width modulation (PWM) resolution, the quantized error of digital control is accumulated, which causes the quantized input current ripple. The 100-Hz ripple and the quantized ripple are the main input current ripple components. To solve the problems, a small-signal model of the DC/DC converter is built to calculate the input current ripple mathematically. Based on the theoretical analysis, the proportional–integral–differential-resonant (PIDR) control is proposed and high-resolution pulse-width modulation (HRPWM) technology is applied. Finally, a 2-kW bidirectional DC/DC converter prototype is built. According to the experiments, the current ripple is reduced dramatically by 81.5% at full load with the proposed current ripple reduction methods.

In this study, a compact and low-power-consumption quantum random number generator (QRNG) based on a laser diode and a hybrid chip with integrated silicon photonics is proposed and verified experimentally. The hybrid chip’s size is 8.8 × 2.6 × 1 mm3, and the power of the entropy source is 80 mW. A common-mode rejection ratio greater than 40 dB was achieved using an optimized 1 × 2 multimode interferometer structure. A method for optimizing the quantum-to-classical noise ratio is presented. A quantum-to-classical noise ratio of approximately 9 dB was achieved when the photoelectron current is 1 μA using a balance homodyne detector with a high dark current GeSi photodiode. The proposed QRNG has the potential for use in scenarios of moderate MHz random number generation speed, with low power, small volume, and low cost prioritized.

In the context of building Child-Friendly Cities in China, child-friendly school environments are considered as having a profound impact on children’s development and growth. This study presents the development and validation of the Child-Friendly School Environment Questionnaire for assessing a child-friendly school environment. Utilizing open-ended questions and interviews, an initial questionnaire on the child-friendly school environment was compiled. An exploratory factor analysis of the preliminary test results with 696 primary school children in grades three to six was conducted to refine the questionnaire into a formal 19-item questionnaire. Subsequently, a confirmatory factor analysis was performed to analyze the evaluation results of 807 primary school children in grades three to six. The results indicated that a child-friendly school environment is a multi-dimensional construct encompassing Environment Friendly, Teaching Friendly, Peer Friendly, and Children Participation, with good reliability and validity. The promising outcomes of this study suggest that the Child-Friendly School Environment Questionnaire can be widely used as a powerful evaluation tool for the child-friendly school education practice in the future.

Accurate stroke assessment and consequent favorable clinical outcomes rely on the early identification and quantification of aneurysmal subarachnoid hemorrhage (aSAH) in non-contrast computed tomography (NCCT) images. However, hemorrhagic lesions can be complex and difficult to distinguish manually. To solve these problems, here we propose a novel Hybrid 2D/3D UNet deep-learning framework for automatic aSAH identification and quantification in NCCT images. We evaluated 1824 consecutive patients admitted with aSAH to four hospitals in China between June 2018 and May 2022. Accuracy and precision, Dice scores and intersection over union (IoU), and interclass correlation coefficients (ICC) were calculated to assess model performance, segmentation performance, and correlations between automatic and manual segmentation, respectively. A total of 1355 patients with aSAH were enrolled: 931, 101, 179, and 144 in four datasets, of whom 326 were scanned with Siemens, 640 with Philips, and 389 with GE Medical Systems scanners. Our proposed deep-learning method accurately identified (accuracies 0.993–0.999) and segmented (Dice scores 0.550–0.897) hemorrhage in both the internal and external datasets, even combinations of hemorrhage subtypes. We further developed a convenient AI-assisted platform based on our algorithm to assist clinical workflows, whose performance was comparable to manual measurements by experienced neurosurgeons (ICCs 0.815–0.957) but with greater efficiency and reduced cost. While this tool has not yet been prospectively tested in clinical practice, our innovative hybrid network algorithm and platform can accurately identify and quantify aSAH, paving the way for fast and cheap NCCT interpretation and a reliable AI-based approach to expedite clinical decision-making for aSAH patients.

Although previous studies have applied artificial intelligence techniques to improve the accuracy and efficiency of ship selection in port state control (PSC) inspections, the new inspection regime (NIR) is still in effect and widely adopted by PSC authorities in the Tokyo Memorandum of Understanding to select ships for inspection. It considers seven features, and each candidate value of a certain feature is assigned a fixed weighting point. The sum of the weighting points of these seven features determines the risk level of a ship. The assumption behind the NIR is that ships with values attached with higher weighting points should have more deficiencies. However, this paper finds that Simpson's paradox may exist for this assumption; that is, the average number of deficiencies of ships with values attached with higher weighting points is lower than that of ships with values attached with lower weighting points. Therefore, this paper examines the plausibility of the NIR's weighted-sum method and further explores which feature flips the effect. Finally, we arrive at the conclusion that the features selected by NIR are coupled with each other, so we should not use a simple weighted-sum method to determine the risk level of a candidate ship. Based on the results, we further provide suggestions for PSC authorities with respect to the improvement of the ship selection scheme of NIR.

Abstract Background This study aimed to analyze associations between genetic variants and plasma concentrations along with clinical outcomes in dabigatran in patients with non-valvular atrial fibrillation (NVAF). Methods We conducted a prospective study and enrolled NVAF patients treated with dabigatran in the real world. A total of 86 patients treated with 110 mg DE twice daily were recruited for this study. Blood samples were obtained from each patient and used for genotyping and determination of plasma dabigatran concentration. All bleeding and thromboembolic complications were recorded during the 1.5 years of follow-up. Results Eighty-three patients provided samples at the trough plasma level of dabigatran, and 58 patients provided samples at the peak plasma level of dabigatran. There was a significant association between the CES1 SNP rs8192935 and trough plasma concentrations of dabigatran (P = 0.013). Our results showed that the CES1 SNP rs8192935 significantly influenced dabigatran trough concentrations in the Chinese population, and carriers of the G allele had increased trough plasma concentrations of dabigatran compared to noncarriers. The ABCB1 SNP c.2482-2236G > A (rs4148738) was associated with major bleeding events in the addictive model (P = 0.046, OR = 3.29) and dominant model (P = 0.040, OR = 8.17). Additionally, the ABCB1 SNP c.3435 C > T (rs1045642) was associated with the incidence of major bleeding events in the addictive model (P = 0.043, OR = 3.34) and dominant model (P = 0.046, OR = 7.77). However, no significant associations were found between all the SNPs and the incidence of minor bleeding events. Conclusion Our results indicated that the CES1 polymorphism rs8192935 was associated with trough plasma concentrations of dabigatran. Carriers of the G allele had increased trough plasma concentrations of dabigatran compared to noncarriers. The ABCB1 polymorphisms rs4148738 and rs1045642 were associated with an increased risk for major bleeding events for the first time in a Chinese population.

In recent years, an increasing number of studies have examined the mechanisms underlying nonverbal emotional information processing in people with high social anxiety (HSA). However, most of these studies have focused on the processing of facial expressions, and there has been scarce research on gesture or even face-gesture combined processing in HSA individuals. The present study explored the processing characteristics and mechanism of the interaction between gestures and facial expressions in people with HSA and low social anxiety (LSA). The present study recruited university students as participants and used the Liebowitz Social Anxiety Scale scores to distinguish the HSA and LSA groups. We used a 2 (group: HSA and LSA) × 2 (emotion valence: positive, negative) × 2 (task: face, gesture) multifactor mixed design, and videos of a single face or gesture and combined face-gesture cues were used as stimuli. We found that (1) there is a distinction in the processing of faces and gestures, with individuals recognizing gestures faster than faces; (2) there is an attentional enhancement in the processing of gestures, particularly for negative gestures; and (3) when the emotional valence of faces and gestures align, it facilitates the recognition of both. However, incongruent gestures have a stronger impact on the processing of facial expressions compared to facial expressions themselves, suggesting that the processing of facial emotions is more influenced by environmental cues provided by gestures. These findings indicated that gestures played an important role in emotional processing, and facial emotional processing was more dependent on the environmental cues derived from gestures, which helps to clarify the reasons for biases in the interpretation of emotional information in people with HSA.

The discovery of alternative medicines with less adverse effects is extremely urgent for rheumatoid arthritis (RA). Phillyrin (Phil), the predominant lignan glycoside of Forsythia suspensa, has been reported to exert several pharmacological effects, such as antivirus, anti-inflammation, anti-oxidation, anti-obesity, and antipyretic activity. However, the effect of Phil on RA remains unknown. In this study, We utilized both in vivo collagen-induced arthritis (CIA) rat models and in vitro TNFα-induced fibroblast-like synoviocytes (FLSs) to study the inhibitory effects of Phil on RA. The in vivo studies revealed that Phil treatment effectively ameliorated synovial inflammation and bone erosion in CIA rats. The in vitro studies demonstrated that Phil could significantly suppress the proliferation and migration of arthritic FLSs. In addition, treatment with Phil resulted in decreased mRNA expression of proinflammatory cytokines including TNFα, IL-1β, IL-6, IL-8 and MMP9. Molecular mechanistic investigations revealed that the suppressive effects of Phil were mediated by blockade of the MAPK (ERK, p38, and JNK) and NF-κB pathways. Taken together, our findings suggest that Phil has an anti-arthritic effect in CIA rats by inhibiting the pathogenic characteristic of arthritic FLSs throught suppression of NF-κB and MAPKs signaling pathways. These results demonstrate the potential of Phil as a novel therapeutic agent for the treatment of RA.

With the promotion of the “carbon neutrality” and “carbon peak” initiatives, green credit plays an important role in helping enterprises to change their high-pollution, high-energy-consumption production methods and establishing a sound green, low-carbon, and circular economic system. This study used spatial correlation analysis and a fixed effects SDM model to examine the spatiotemporal and causal relationship between green credit levels and enterprise green technology innovation in 271 prefecture level cities in China from 2013 to 2021. It found that (1) green credit and green technology innovation levels are both highest in the eastern region, followed by the central region, and exhibit spatial correlation characteristics. The main types of agglomeration are high–high and low–low agglomeration. (2) Green credit has a significant enhancing effect on green technology innovation in enterprises, and this conclusion still holds after robustness and endogeneity tests. (3) There is significant regional heterogeneity in the impact of green credit on green technology innovation, mainly concentrated in the central and western regions. (4) Green credit can significantly increase enterprise R&D investment and enhance the level of green technology innovation through this channel. Finally, some policy implications are provided to the decision-making departments that can be used for reference.

With the complication of the power system, features of the resonance interaction behave diversely and pose a threat to the effectiveness of the resonance suppression strategies. Existing resonance suppression strategies are usually designed for specific scenarios which are in close correlation with the impedance frequency-amplitude distribution, and their adaptability under different scenarios is hard to evaluate. In this paper, the resonance suppression domain of a DC distribution network is derived based on the node impedance variation before/after the resonance is suppressed. The derived criterion takes the admittance change of the resonance suppression strategies as variables, and the conservative/ideal suppression domain criteria are defined. On this basis, a method for evaluating the effectiveness of resonance suppression strategies is proposed, which simplifies the evaluation process and avoids a complicated matrix inverse process to each resonance suppression strategy during the system impedance calculation. Furthermore, a DC active damper control strategy based on the resonance suppression strategy evaluation is proposed, and the proposed strategy could suppress resonances under different scenarios by a targeted design of the reshaping admittance parameters. Time domain simulations with a 5-node distribution network are carried out to verify the proposed method.

In recent years, the nitrogen-vacancy (NV) center in diamonds has been demonstrated to be a high-performance multiphysics sensor, where a lock-in amplifier (LIA) is often adopted to monitor photoluminescence changes around the resonance. It is rather complex when multiple resonant points are utilized to realize a vector or temperature-magnetic joint sensing. In this article, we present a novel scheme to realize multipoint lock-in detection with only a single-channel device. This method is based on a direct digital synthesizer (DDS) and frequency-shift keying (FSK) technique, which is capable of freely hopping frequencies with a maximum of 1.4 GHz bandwidth and encoding an unlimited number of resonant points during the sensing process. We demonstrate this method in experiments and show it would be generally useful in quantum multi-frequency excitation applications, especially in the portable and highly mobile cases.

Abstract Background D-ribose is involved in the pathogenesis of Alzheimer’s Disease. The study aimed to determine the association between D-ribose and cognitive function in a sample of community-dwelling older adults. Methods A cross-sectional study was conducted in Chaoyang District, Beijing in 2019–2020. Eligible participants were community-based older adults aged 60 years and above. D-ribose was analyzed from the morning urine. Cognitive function, subjective cognitive decline, and depressive symptoms were measured by a battery of neuropsychological tests. Linear regressions were performed to determine the relationship between the urine D-ribose levels and cognitive performance. Results A sample of 1725 participants (67.1% female) aged 60 to 85 years (69.40 ± 5.87 years, mean ± SD) was enrolled in the analysis. The urine D-ribose concentrations ranged from 1.53 to 208.89 μmol/L (median 38.10 μmol/L; interquartile range 22.52—64.96 μmol/L). Higher levels of D-ribose were associated with worse performance on Mini-Mental State Examination and verbal fluency when age, gender, education, depressive symptoms, and cardiovascular risk factors were included as covariates. Conclusions The urine D-ribose was negatively correlated with cognitive function in community-dwelling older adults. The findings suggest that the dysmetabolism of D-ribose may play a role at the early stage of cognitive impairment.

Background2021 World Health Organization (WHO) Central Nervous System (CNS) tumor classification increasingly emphasizes the important role of molecular markers in glioma diagnoses. Preoperatively non-invasive “integrated diagnosis” will bring great benefits to the treatment and prognosis of these patients with special tumor locations that cannot receive craniotomy or needle biopsy. Magnetic resonance imaging (MRI) radiomics and liquid biopsy (LB) have great potential for non-invasive diagnosis of molecular markers and grading since they are both easy to perform. This study aims to build a novel multi-task deep learning (DL) radiomic model to achieve preoperative non-invasive “integrated diagnosis” of glioma based on the 2021 WHO-CNS classification and explore whether the DL model with LB parameters can improve the performance of glioma diagnosis.MethodsThis is a double-center, ambispective, diagnostical observational study. One public database named the 2019 Brain Tumor Segmentation challenge dataset (BraTS) and two original datasets, including the Second Affiliated Hospital of Nanchang University, and Renmin Hospital of Wuhan University, will be used to develop the multi-task DL radiomic model. As one of the LB techniques, circulating tumor cell (CTC) parameters will be additionally applied in the DL radiomic model for assisting the “integrated diagnosis” of glioma. The segmentation model will be evaluated with the Dice index, and the performance of the DL model for WHO grading and all molecular subtype will be evaluated with the indicators of accuracy, precision, and recall.DiscussionSimply relying on radiomics features to find the correlation with the molecular subtypes of gliomas can no longer meet the need for “precisely integrated prediction.” CTC features are a promising biomarker that may provide new directions in the exploration of “precision integrated prediction” based on the radiomics, and this is the first original study that combination of radiomics and LB technology for glioma diagnosis. We firmly believe that this innovative work will surely lay a good foundation for the “precisely integrated prediction” of glioma and point out further directions for future research.Clinical trail registrationThis study was registered on ClinicalTrails.gov on 09/10/2022 with Identifier NCT05536024.

The functional effects of genetic loci associated with autoimmune disease are not well understood. By dissecting an autoimmune disease genetic locus, the authors define an immune cell-type-specific enhancer and the molecular mechanisms underlying the dysregulation of IRF8 expression by lupus risk variants.

Rapid and accurate detection of pathogen spores is an important step to achieve early diagnosis of diseases in precision agriculture. Traditional detection methods are time-consuming, laborious, and subjective, and image processing methods mainly rely on manually designed features that are difficult to cope with pathogen spore detection in complex scenes. Therefore, an MG-YOLO detection algorithm (Multi-head self-attention and Ghost-optimized YOLO) is proposed to detect gray mold spores rapidly. Firstly, Multi-head self-attention is introduced in the backbone to capture the global information of the pathogen spores. Secondly, we combine weighted Bidirectional Feature Pyramid Network (BiFPN) to fuse multiscale features of different layers. Then, a lightweight network is used to construct GhostCSP to optimize the neck part. Cucumber gray mold spores are used as the study object. The experimental results show that the improved MG-YOLO model achieves an accuracy of 0.983 for detecting gray mold spores and takes 0.009 s per image, which is significantly better than the state-of-the-art model. The visualization of the detection results shows that MG-YOLO effectively solves the detection of spores in blurred, small targets, multimorphology, and high-density scenes. Meanwhile, compared with the YOLOv5 model, the detection accuracy of the improved model is improved by 6.8%. It can meet the demand for high-precision detection of spores and provides a novel method to enhance the objectivity of pathogen spore detection.

Pure red-cell aplasia (PRCA) is a syndrome associated with reduced erythroid precursors. This report presents the case of an elderly PRCA patient with significantly proliferated γδT cells and clonal T-cell receptor (TCR) gene rearrangement. The cause of this patient’s PRCA was confirmed to be an autoimmune disorder rather than malignancy on the basis of flow cytometry, TCR gene rearrangement, and positron emission tomography/computed tomography (PET/CT) findings. Moreover, the γδT cell group identified in this case was captured for the first time under the microscope; this CD4+/CD8− (extremely high CD4/CD8 ratio) population is rare in PRCA patients. Our patient with a monoclonal and polyclonal hybrid of TCR gene rearrangement was sensitive to cyclosporin A (CsA), despite previous reports suggesting that patients with TCR clonal rearrangement may respond poorly to this drug. Overall, this case presents valuable clinical findings for the future diagnosis and management of PRCA caused by autoimmune conditions and further research on γδT cells’ autoimmune pathophysiology and gene rearrangement.

End-stage kidney disease (ESKD) is associated with cognitive impairment (CI) and affects different aspects of cortical morphometry, but where these changes converge remains unclear. Fractal dimension (FD) is used to represent cortical complexity (CC), which describes the structural complexity of the cerebral cortex by integrating different cortical morphological measures. This study aimed to investigate changes in CC in patients with ESKD prior to initiation of dialysis and to evaluate the relationship between changes in CC, cognitive performance, and uremic toxins. Forty-nine patients with ESKD naive to dialysis and 31 healthy controls (HCs) were assessed using structural magnetic resonance imaging (MRI) and cognitive tests, including evaluations of global cognitive function, memory, and executive function. Clinical laboratory blood tests were performed on all patients with ESKD, including measurement of nine uremic toxin-related indices. CC was measured using MRI data to determine regional FD values. We estimated the association between cognitive performance, uremic toxin levels, and CC changes. Compared to HCs, patients with ESKD showed significantly lower CC in the left precuneus (p = 0.006), left middle temporal cortex (p = 0.010), and left isthmus cingulate cortex (p = 0.018). Furthermore, lower CC in the left precuneus was associated with impaired long-term delayed memory (Pearson r = 0.394, p = 0.042) in patients with ESKD. Our study suggests that regional decreases in CC are an additional characteristic of patients with ESKD naive to dialysis, related to impaired long-term memory performance. These findings may help further understand the underlying neurobiological mechanisms between brain structural changes and CI in patients with ESKD.

ObjectiveTo investigate the effect of weight loss on pregnancy outcomes, PCOS related neuronal-reproductive-metabolic hormones and ovarian granulosa cell gene expression profiles in obese PCOS infertile patients undergoing in vitro fertilization-embryo transfer (IVF-ET).Methods75 patients undergoing IVF-ET due to tubal factors alone collected as the control group (group A), and 352 patients with obese PCOS infertility were divided into four groups according to the amount of weight loss before IVF: 0 kg (group B), 1-5 kg (group C), 5-10 kg (group D), and >10 kg (group E). Six cases of ovarian granulosa cells were collected randomly with the random number table method in each group for detecting mRNA profiling. Pathway networks and biological functions of the differentially expressed genes were analyzed. Validation by RT-PCR was performed.Results(1) The levels of luteinizing hormone(LH), testosterone(T) and homeostasis model assessment insulin resistance(HOMA-IR) in group E were significantly lower than those in groups B and C (P

Abstract Background Children with severe acute malnutrition (SAM) have inadequate levels of fatty acids (FAs) and limited capacity for enteral nutritional rehabilitation. We hypothesized that topical high-linoleate sunflower seed oil (SSO) would be effective adjunctive treatment for children with SAM. Methods This study tested a prespecified secondary endpoint of a randomized, controlled, unblinded clinical trial with 212 children with SAM aged 2 to 24 months in two strata (2 to

In recent years, topological insulators have drawn growing interest as a unique electronic state of matter toward quantum information technology. Despite the logic devices with magnetization switching through spin–orbit torque or the topological magneto-electric effect, realizing memory devices based on topological insulators has been urged in quantum computing applications. In this work, we report the design and fabrication of a non-volatile memory device that employs polarization of Bi2Se3 thin films achieving fast memory speed, sufficient memory window, and good reliability. The Bi2Se3 film polarizes under an external electrical field with charges accumulated on the top and bottom surfaces separating the electrons and holes. Such polarization is much faster than the carrier tunneling in conventional floating-gate flash memory and ferroelectric-based memory devices. In addition, good memory retention and endurance properties have also been obtained, showing great potential in high-performance memory application in future topological insulator-involved information technology.

BackgroundParaganglioma is a kind of neuroendocrine tumor that originates from paraganglia outside the adrenal gland. Gastrointestinal tract paraganglioma is very rare and only four cases of paraganglioma originating in the colon have been reported.Case PresentationWe report a case of metastatic paraganglioma originating in the colon, in which the differential diagnosis was established by comprehensively considering clinical information, histology, immunohistochemistry, and findings of fluorescence in situ hybridization and next generation sequencing analyses. The patient has remained well for over 14 months after the treatment.ConclusionSince all paraganglioma have metastatic potential, we believe that radical surgical resection and regular follow-up are necessary. Genetic testing may be indicative of metastatic potential and prognosis. Because colonic paraganglioma is very rare, differential diagnosis is very important. Our report provides experience for the diagnosis and study of paraganglioma in rare sites.

Introduction: The pathological rare category of thyroid is a type of lesion with a low incidence rate and is easily misdiagnosed in clinical practice, which directly affects a patient’s treatment decision. However, it has not been adequately investigated to recognize the rare, benign, and malignant categories of thyroid using the deep learning method and recommend the rare to pathologists.Methods: We present an empirical decision tree based on the binary classification results of the patch-based UNet model to predict rare categories and recommend annotated lesion areas to be rereviewed by pathologists.Results: Applying this framework to 1,374 whole-slide images (WSIs) of frozen sections from thyroid lesions, we obtained an area under a curve of 0.946 and 0.986 for the test datasets with and without WSIs, respectively, of rare types. However, the recognition error rate for the rare categories was significantly higher than that for the benign and malignant categories (p < 0.00001). For rare WSIs, the addition of the empirical decision tree obtained a recall rate and precision of 0.882 and 0.498, respectively; the rare types (only 33.4% of all WSIs) were further recommended to be rereviewed by pathologists. Additionally, we demonstrated that the performance of our framework was comparable to that of pathologists in clinical practice for the predicted benign and malignant sections.Conclusion: Our study provides a baseline for the recommendation of the uncertain predicted rare category to pathologists, offering potential feasibility for the improvement of pathologists’ work efficiency.

Due to their unique properties, vortex lasers have high application value in frontier fields such as optical micromanipulation, super-resolution imaging, quantum entanglement, and optical communication. In this study, we demonstrated a 946/1030 nm Laguerre-Gaussian (LG01) mode dual-wavelength vortex laser by using an intracavity cascade pumped structure and a spot-defect output mirror. Using a coaxial linear cavity structure, the 808 nm laser diode (LD) was used to end-pump the Nd:YAG crystal to generate a 946 nm laser and then use it to directly pump the Yb:YAG crystal in the cavity to generate a 1030 nm laser, and finally a 946/1030 nm dual-wavelength laser came out. By making a spot defect in the center of the output mirror to suppress the oscillation of the fundamental Gaussian mode laser and carefully adjusting the position of the laser crystals, the LG01 mode dual-wavelength vortex laser was output in single handedness. When the pump power was 40 W, the total output was 664 mW (356 and 308 mW at 946 and 1030 nm LG01 mode vortex lasers), and the total optical-optical conversion efficiency was 1.7%; the output power fluctuations of 946 and 1030 nm LG01 mode vortex lasers within 1 h were 3.43% and 3.13%, respectively; the beam quality factors M2 of 946 and 1030 nm LG01 mode vortex lasers were 2.35 and 2.40, respectively. It was proved that the generated dual-wavelength vortex laser had the wavefront phase expiϕ by the self-interference method.

An urban agglomeration is a highly developed spatial area formed by integrated cities. While previous studies have analyzed green space allocation at the provincial and city scales, there is insufficient information on green space allocation in urban agglomerations. For this research, a database of green spaces in eight urban agglomerations (133 cities) in China from 2002 to 2019 was constructed to better understand the equity of green space distribution among land resources. A green space equity index (GEI) was established based on the Theil index and combined with GeoDetector to analyze the differences in urban agglomeration green spaces. The main conclusions are as follows: The sum of the GEI of China’s urban agglomerations has increased significantly, rising from 3.74 in 2002 to 6.34 in 2019. The GEI value for each of the eight urban agglomerations was kept under 0.01. Polarized development has occurred within urban agglomeration cities, and the allocation of green space in megacities is relatively weak, especially in the more economically developed Yangtze River Delta and Guanzhong urban agglomerations. The average temperature, humidity, and precipitation have dominant influences in determining the GEI values. This paper provides a new perspective on the management and allocation of urban agglomeration green spaces.

Enhancers shape gene expression patterns and are involved in disease pathogenesis. Here the authors demonstrate a strategy to screen functional regulatory elements for non-coding RNAs ― illustrated with miR-146a ― and link autoimmune disease risk genetic variants to autoimmune disease etiology.

BackgroundDetection of circulating tumor cells (CTCs) is a promising technology in tumor management; however, the slow development of CTC identification methods hinders their clinical utility. Moreover, CTC detection is currently challenging owing to major issues such as isolation and correct identification. To improve the identification efficiency of glioma CTCs, we developed a karyoplasmic ratio (KR)-based identification method and constructed an automatic recognition algorithm. We also intended to determine the correlation between high-KR CTC and patients’ clinical characteristics.MethodsCTCs were isolated from the peripheral blood samples of 68 glioma patients and analyzed using DNA-seq and immunofluorescence staining. Subsequently, the clinical information of both glioma patients and matched individuals was collected for analyses. ROC curve was performed to evaluate the efficiency of the KR-based identification method. Finally, CTC images were captured and used for developing a CTC recognition algorithm.ResultsKR was a better parameter than cell size for identifying glioma CTCs. We demonstrated that low CTC counts were independently associated with isocitrate dehydrogenase (IDH) mutations (p = 0.024) and 1p19q co-deletion status (p = 0.05), highlighting its utility in predicting oligodendroglioma (area under the curve = 0.770). The accuracy, sensitivity, and specificity of our algorithm were 93.4%, 81.0%, and 97.4%, respectively, whereas the precision and F1 score were 90.9% and 85.7%, respectively.ConclusionOur findings remarkably increased the efficiency of detecting glioma CTCs and revealed a correlation between CTC counts and patients’ clinical characteristics. This will allow researchers to further investigate the clinical utility of CTCs. Moreover, our automatic recognition algorithm can maintain high precision in the CTC identification process, shorten the time and cost, and significantly reduce the burden on clinicians.

Background: B7-H3, also known as CD276, an important immune checkpoint member of the B7-CD28 family, is confirmed as a promising target after PD-L1 in clinical trials. Although the overexpression of B7-H3 has been associated with invasive metastatic potential and poor prognosis in multiple types of cancer, nothing is known regarding the expression profiles of B7-H3 in papillary thyroid carcinoma (PTC). In this study, we carried out a large-scale analysis of B7-H3 expression in PTC patients and evaluated the potential clinical significance of B7-H3.Methods: In total, data from 1,210 samples, including 867 cases from TCGA and four GEO datasets, were collected for B7-H3–related transcriptome analyses, and 343 postoperative, whole-tumor sections were collected from patients with PTC at our institute for B7-H3–specific immunohistochemistry (IHC) staining. The statistical analysis was primarily accomplished using the R project for statistical computing.Results: B7-H3 positivity was found in 84.8% of PTC patients (291/343), and the mRNA and protein expression levels of B7-H3 in PTC were markedly higher than those of para-tumor tissues (p < 0.001), demonstrating that B7-H3 can serve as a potential diagnostic biomarker for PTC. The significant upregulation of B7-H3 in PTC is caused by distinct patterns of CNVs and CpG DNA methylation. Functional enrichment analysis confirmed that high B7-H3 expression was significantly associated with specific immune features and angiogenesis. High B7-H3 protein expression was associated with tumor size (p = 0.022), extrathyroidal extension (ETE) (p = 0.003), and lymph node metastasis (LNM) (p < 0.001). More importantly, multivariate analysis confirmed that B7-H3 was an independent predictor of relapse-free survival (RFS) (p < 0.05). In the subgroup analysis, positive B7-H3 staining was associated with worse RFS in patients with primary tumor size ≥2 cm (p < 0.05), age ≥55 years (p < 0.05), LNM (p = 0.07), multifocality (p < 0.05), and ETE (p < 0.05). In addition, Circos plots indicated that B7-H3 was significantly associated with other immune checkpoints in the B7-CD28 family.Conclusion: This is the first comprehensive study to elucidate the expression profile of B7-H3 in PTC. Our observations revealed that B7-H3 is a novel independent biomarker for predicting LNM and disease recurrence for PTC patients, and it thus may serve as an indicator that could be used to improve risk-adapted therapeutic strategies and a novel target for immunotherapy strategies for patients who undergo an aggressive disease course.

It is known that schistosome-derived antigens induce innate and adaptive immune responses that are essential for the formation of hepatic immunopathology. Here, we screened and synthesized four peptides derived from Schistosoma japonicum (S. japonicum) heat shock protein 90α (Sjp90α-1, -2, -3, and -4), which is widely expressed in adults and eggs of the genus S. japonicum and induces remarkable immune reactions. To define the antigenicity of these peptides, we stimulated splenocytes with peptides, and the results showed that only the Sjp90α-1 peptide could predominately induce the activation of dendritic cells (DCs) and macrophages as well as alter the proportion of follicular helper T (Tfh) cells. Next, CD4+ T cells were purified and cocultured with mouse bone-marrow-derived DCs (BMDCs) with or without Sjp90α-1 peptide stimulation in vitro, and the results showed that Sjp90α-1-stimulated BMDCs can significantly induce CD4+ T-cell differentiation into Tfh cells, while the direct stimulation of CD4+ T cells with Sjp90α-1 did not induce Tfh cells, indicating that the Sjp90α-1 peptide promotes Tfh cell differentiation depending on the presence of DCs. Furthermore, we selected and prepared an Sjp90α-1-peptide-based antibody and illustrated that it has excellent reactivity with the immunizing peptide and detects a single band of 29 kDa corresponding to the Sjp90α protein. The immunolocalization results showed that the protein recognized by this Sjp90α-1-peptide-based antibody is present in the mature eggs and the tegument of adults, implying that the parasite-derived peptide has a potential interaction with the host immune system. Finally, we evaluated antipeptide IgG antibodies and revealed a significantly higher level of anti-Sjp90α-1 peptide IgG antibodies in mice 3 weeks after S. japonicum infection. In conclusion, we illustrate that these synthetic peptides warrant further investigation by evaluating their antigen-specific immune response and their ability to efficiently induce Tfh cells. Moreover, they may constitute a potentially helpful method for the laboratory diagnosis of schistosomiasis japonica.