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Abstract Escherichia coli K1 (E. coli K1) meningitis early occurs in the gastrointestinal and causes severe damage to the central nervous system, including lifelong neurological complications in survivors. However, the cellular mechanism by which E. coli K1 may cause neuropathies is not well understood due to the lack of relevant human multi-organ models for studying multifaceted systemic inflammation across the gut-brain axis. Here, we reconstruct a multicellular model of the human gut-brain axis to identify the neuropathogenic mechanism driven by E. coli K1-colibactin meningitis. We observed that E. coli K1-genotoxic colibactin induced intestinal and peripheral interleukin 6, causing the blood-brain barrier injury and endothelial inflammation via the p38/p65 pathways. Serpin-E1 from the damaged cerebral endothelia induces reactive astrocytes to release IFN-γ, which reduces microglial phagocytosis of E. coli K1 and exacerbates detrimental neuroinflammation via NLRP3/IL-18 axis. Microglial IL-18 elevates neuronal reactive oxidative stress that worsens DNA double-strand breaks in E. coli K1-infected neurons, leading to H3K4 trimethylation and phosphorylation of alpha-synuclein. Our findings suggest therapeutic strategies for post-bacterial meningitis treatment to potentially prevent the initiation of synucleinopathy.

Abstract Multi-object imaging can obtain more comprehensive information to analyze the surrounding environment better and is widely used in many fields. While most multi-object imaging methods require objects not to be coaxial, which must ensure that each object is within the line-of-sight (LOS) of beam progression. In this paper, we present an approach for imaging multiple coaxial objects utilizing an Airy beam array, which can see hidden objects and is conducive to expanding the range of information perception. The feasibility of our scheme is verified through numerical simulations and experiments, and the imaging capability influenced by the axial distance and size of objects is studied. In addition, the minimum imaging distance of the imaging system is also derived. The results will open new ideas for non-line-of-sight (NLOS) imaging and may find applications in queue target imaging.

This randomized controlled trial aims to investigate the effects of educational and psychological interventions on the health outcomes of patients suffering from chronic diseases. We recruited 372 patients and randomly assigned them to one of two intervention arms during the trial, which lasted for a year. Both groups participated in a 12-month intervention program, where the intervention group received health education and supportive psychological therapy utilizing virtual reality (VR) technology, while the control group received conventional health education guidance. Statistical analysis showed that compared to the control group, the intervention group demonstrated significant improvements (p

Abstract Autoimmune related kidney diseases (ARKDs), including minimal change nephropathy (MCN), membranous nephropathy (MN), IgA nephropathy (IgAN), and lupus nephritis (LN), significantly affect renal function. These diseases are characterized by the formation of local immune complexes and the subsequent activation of the complement system, leading to kidney damage and proteinuria. Despite the known patterns of glomerular injury, the specific molecular mechanisms that contribute to renal tubular damage across ARKDs remain underexplored. Laser capture microdissection and liquid chromatography–tandem mass spectrometry (LC–MS/MS) were used to conduct a comparative proteomic analysis of renal tubular tissues from formalin-fixed paraffin-embedded samples. The cohort comprised of 10 normal controls (NC), 5 MCN, 4 MN, 17 IgAN, and 21 LN patients. Clinical parameters and histopathological assessments were integrated with proteomic findings to comprehensively investigate underlying pathogenic processes. Clinical evaluation indicated significant glomerular damage, as reflected by elevated urinary protein levels and reduced plasma albumin levels in patients with ARKD. Histological analyses confirmed varying degrees of tubular damage and deposition of immune complexes. Proteomic analyses identified significant changes in protein expression, particularly in complement components (C3, C4A, C4B, C8G, CFB, and SERPINA1) and mitochondrial proteins (ATP5F1E and ATP5PD), highlighting the common alterations in the complement system and mitochondrial proteins across ARKDs. These alterations suggest a novel complement–mitochondrial–epithelial–mesenchymal transition (EMT) pathway axis that contributes to tubular damage in ARKDs. Notably, significant alterations in CFB in tubular ARKD patients were revealed, implicating it as a therapeutic target. This study underscores the importance of complement activation and mitochondrial dysfunction in the pathogenesis of ARKDs, and proposes CFB as a potential therapeutic target to inhibit complement activation and mitigate tubular damage. Future research should validate the complement-mitochondrial-EMT pathway axis and explore the effects and mechanisms of CFB inhibitors in alleviating ARKD progression.

IntroductionBladder cancer (BCa) is a common malignancy in the urinary tract. It has high recurrence rates and often requires microscopic examination, which presents significant challenges in clinical treatment. Previous research has shown that circular TAF4B (circTAF4B) is significantly upregulated in BCa and is associated with a poor prognosis. However, the specific targets and molecular mechanisms by which circTAF4B functions in BCa are still not well - understood.MethodsIn this study, an RNA pull - down assay and mass spectrometry were utilized to identify MFN2 as a binding protein of circTAF4B. Additionally, siRNA was used to silence MFN2 to observe the amplification of the inhibitory effects of circTAF4B overexpression on cell growth and migration in BCa cells. Moreover, circTAF4B shRNA lentiviral particles were employed to study their impact on BCa progression by examining the regulation of p27 and the blocking of AKT signaling.ResultsIt was found that MFN2 is a binding protein of circTAF4B. Silencing MFN2 with siRNA enhanced the inhibitory effects of circTAF4B overexpression on cell growth and migration in BCa cells. Also, circTAF4B shRNA lentiviral particles inhibited BCa progression by upregulating p27 and blocking AKT signaling.DiscussionIn conclusion, the physical binding of circTAF4B to MFN2 is a crucial process in the tumorigenesis and progression of BCa. Targeting circTAF4B or its complexes may have potential as a therapeutic strategy for BCa diagnosis and treatment.

Abstract Background Artificial Intelligence(AI)-based solutions for Gleason grading hold promise for pathologists, while image quality inconsistency, continuous data integration needs, and limited generalizability hinder their adoption and scalability. Methods We present a comprehensive digital pathology workflow for AI-assisted Gleason grading. It incorporates A!MagQC (image quality control), A!HistoClouds (cloud-based annotation), Pathologist-AI Interaction (PAI) for continuous model improvement, Trained on Akoya-scanned images only, the model utilizes color augmentation and image appearance migration to address scanner variations. We evaluate it on Whole Slide Images (WSI) from another five scanners and conduct validations with pathologists to assess AI efficacy and PAI. Results Our model achieves an average F1 score of 0.80 on annotations and 0.71 Quadratic Weighted Kappa on WSIs for Akoya-scanned images. Applying our generalization solution increases the average F1 score for Gleason pattern detection from 0.73 to 0.88 on images from other scanners. The model accelerates Gleason scoring time by 43% while maintaining accuracy. Additionally, PAI improve annotation efficiency by 2.5 times and led to further improvements in model performance. Conclusions This pipeline represents a notable advancement in AI-assisted Gleason grading for improved consistency, accuracy, and efficiency. Unlike previous methods limited by scanner specificity, our model achieves outstanding performance across diverse scanners. This improvement paves the way for its seamless integration into clinical workflows.

Abstract Idiopathic pulmonary fibrosis (IPF) is a life-threatening interstitial lung disease. Identifying biomarkers for early diagnosis is of great clinical importance. The epididymis protein 4 (HE4) is important in the process of inflammation and fibrosis in the epididymis. Its prognostic value in IPF, however, has not been studied. The mRNA and protein levels of HE4 were used to determine the prognostic value in different patient cohorts. In this study, prognostic nomograms were generated based on the results of the cox regression analysis. We identified the HE4 protein level increased in IPF patients, but not the HE4 gene expression. The increased expression of HE4 correlated positively with a poor prognosis for patients with IPF. The HR and 95% CI were 2.62 (1.61–4.24) (p

Abstract Multi-agent reinforcement learning encounters a non-stationary challenge, where agents concurrently update their policies, leading to changes in the environment. Existing approaches have tackled this challenge through communication among agents to obtain their partners’ actions, but this introduces computational complexity known as partner sample complexity. An alternative approach is to develop partner models that generate samples instead of direct communication to mitigate this complexity. However, a discrepancy arises between the real policies distribution and the policy of partner models, termed as model bias, which can significantly impact performance when heavily relying on partner models. In order to achieve a trade-off between sample complexity and performance, a novel multi-agent model-based reinforcement learning algorithm called decentralized adaptive partner modeling (DAPM) is proposed, which utilizes fictitious self play (FSP) to construct partner models and update policies. Model bias is addressed by establishing an upper bound to restrict the usage of partner models. Coupled with that, an adaptive rollout approach is introduced, enabling real agents to dynamically communicate with partner models based on their quality, ensuring that agent performance can progressively improve with partner model samples. The effectiveness of DAPM is exhibited in two multi-agent tasks, showing that DAPM outperforms existing model-free algorithms in terms of partner sample complexity and training stability. Specifically, DAPM requires 28.5% fewer communications compared to the best baseline and exhibits reduced fluctuations in the learning curve, indicating superior performance.

Silicon (Si)-based quantum-dot (QD) device by advanced CMOS process is one of important technologies for quantum computing application and currently, it needs a fast and accurate quantum characteristics simulation for designing and optimizing the devices. In this paper, for the first time, a fast hybrid simulation method is proposed by incorporating simplified quantum master equation model with the traditional TCAD tool. Additionally, a SPICE MODEL is incorporated for transient current correction to achieve results closer to real observations. The QD devices forming on advanced stacked Si nanowire (NW) and stacked Si nanosheet (NS) are constructed and simulated by this method, yielding Coulomb diamond plot and charge energies for different structures at 1 K. Notably, a Coulomb blockade region of approximately 82 mV and a first Coulomb step width approximately 1.6 times wider than the blockade region are observed, consistent with theoretical expectations and confirming the method’s efficacy. Simulation characteristics of advanced diamond-like channel devices are obtained within 1277 s, demonstrating over 85% matching with experimental data. Meanwhile, the influence of quantum characteristics varying with the transistor’s structure and process parameters is also analyzed, which in turn provide a guidance for the design and the optimization of the QD device by advanced Si CMOS process.

Abstract Preimplantation genetic testing (PGT) can minimize the risk of birth defects. However, the accuracy and applicability of routine PGT is confounded by uneven genome coverage and high allele drop‐out rate from existing single‐cell whole genome amplification methods. Here, a method to diagnose genetic mutations and concurrently evaluate embryo competence by leveraging the abundant mRNA transcript copies present in trophectoderm cells is developed. The feasibility of the method is confirmed with 19 donated blastocysts. Next, the method is applied to 82 embryos from 26 families with monogenic defects for simultaneous mutation detection and competence assessment. The accuracy rate of direct mutation detection is up to 95%, which is significantly higher than DNA‐based method. Meanwhile, this approach correctly predicted seven out of eight (87.5%) embryos that failed to implant. Of six embryos that are predicted to implant successfully, four met such expectations (66.7%). Notably, this method is superior at conditions for mutation detection that are challenging when using DNA‐based PGT, such as when detecting pathogenic genes with a high de novo rate, multiple pseudogenes, or an abnormal expansion of CAG trinucleotide repeats. Taken together, this study establishes the feasibility of an RNA‐based PGT that is also informative for assessing implantation competence.

Conventional photodynamic therapy (PDT) approaches face challenges including limited light penetration, low uptake of photosensitizers by tumors, and lack of oxygen in tumor microenvironments. One promising solution is to internally generate light, photosensitizers, and oxygen. This can be accomplished through endogenous production, such as using bioluminescence as an endogenous light source, synthesizing genetically encodable photosensitizers in situ, and modifying cells genetically to express catalase enzymes. Furthermore, these strategies have been reinforced by the recent rapid advancements in synthetic biology. In this review, we summarize and discuss the approaches to overcome PDT obstacles by means of endogenous production of excitation light, photosensitizers, and oxygen. We envision that as synthetic biology advances, genetically engineered cells could act as precise and targeted “living factories” to produce PDT components, leading to enhanced performance of PDT.

Unmanned Surface Vehicles (USVs) are rapidly becoming mission-indispensable for a variety of naval operations, from search and rescue to environmental monitoring and surveillance. Path planning lies at the heart of the operational effectiveness of USVs, since it represents the key technology required to enable the vehicle to transit the unpredictable dynamics of the marine environment in an efficient and safe way. The paper develops a critical review of the most recent advances in USV path planning and a novel classification of algorithms according to operational complexity: Basic Pathfinders, Responsive Pathfinders, and Advanced Strategic Pathfinders. Each category can adapt to different requirements, from environmental predictability to the desired degree of human intervention, and from stable and controlled environments to highly dynamic and unpredictable conditions. The review includes current methodologies and points out the state-of-the-art algorithmic approaches in their experimental validations and real-time applications. Particular attention is paid to the description of experimental setups and navigational scenarios showing the realistic impact of these technologies. Moreover, this paper goes through the key, open challenges in the field and hints at the research direction to leverage in order to enhance the robustness and adaptability of path planning algorithms. This paper, by offering a critical analysis of the current state-of-the-art, lays down the foundation of future USV path planning algorithms.

Abstract Purpose In osteoporosis, the balance between osteogenic and adipogenic differentiation of mesenchymal stem cells (MSCs) is disrupted. The osteogenic differentiation of bone marrow MSCs (BMSCs) is important for improving osteoporosis. The aim of this study was to explore the role and molecular mechanism of miR-210 in the balance of osteogenic/adipogenic differentiation of BMSCs in postmenopausal osteoporosis. Methods Postmenopausal osteoporosis rat models were constructed by ovariectomy (OVX). BMSCs were isolated from the femur in rats of Sham and OVX groups. MiR-210 was overexpressed and suppressed by miR-210 mimics and inhibitor, respectively. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the relative mRNA expression of miR-210, ephrin type-A receptor 2 (EPHA2), alkaline phosphatase (ALP), osterix (OSX), osteocalcin (Bglap), Runt-related transcription factor 2 (Runx2), peroxisome proliferator activated receptor gamma, and fatty acid binding protein 4 (FABP4) in each group of rat femoral tissues or BMSCs. Western blot was applied to detect the protein expression level of EPHA2 in rat femoral tissues and cells. Alizarin red S staining and oil red O staining were performed to assess the osteogenic and adipogenic differentiation of BMSCs, respectively. In addition, the targeting relationship between miR-210 and EPHA2 was verified by a dual luciferase gene reporter assay. Results The expression of miR-210 was significantly reduced in femoral tissues and BMSCs of OVX rats, and its low expression was associated with reduced bone formation. The osteogenic differentiation was enhanced in OVX rats treated with miR-210 mimic. Overexpression of miR-210 in transfected BMSCs was also found to significantly promote osteogenic differentiation and even inhibit adipogenic differentiation in BMSCs, while knockdown of miR-210 did the opposite. Further mechanistic studies showed that miR-210 could target and inhibit the expression of EPHA2 in BMSCs, thus promoting osteogenic differentiation and inhibiting adipogenic differentiation of BMSCs. Conclusion MiR-210 promotes osteogenic differentiation and inhibits adipogenic differentiation of BMSCs by down-regulating EPHA2 expression. As it plays an important role in the osteogenic/adipogenic differentiation of osteoporosis, miR-210 can serve as a potential miRNA biomarker for osteoporosis.

PurposeTo review the outcome of PGT-M in hormone-related hereditary tumor syndrome and evaluate the effect of ovarian induction on tumor growth in those patients.MethodsMedical records of PGT-M were retrospectively analyzed in patients with hormone-related heritage tumors in our reproductive center. A total of eleven women with hereditary breast and ovarian cancer (HBOC) (including BRCA1/2 mutation carriers), and Lynch syndrome (including MMR gene mutation carriers) were included. Thirteen IVF/PGT-M cycles were performed. Eleven for PGT-M and two for fertility preservation. The ovulation protocol, numbers of oocytes retrieved and two pronuclei (2PN) zygotes, PGT-M results, and clinical outcomes were analyzed. Tumor progression was also estimated by comparing transvaginal ultrasound (TVS), MR, CT, or colonoscopy according to the follow-up requirements of different tumors.ResultsEleven IVF/PGT-M cycles were performed with an antagonist protocol; Two cycles were performed with a mild stimulation protocol. The total dose of gonadotropin (Gn) was 1827 IU per patient (range from 1200 to 2625 IU). The median number of oocytes retrieved was 13 (range from 4 to 30), and the median number of 2PN zygotes was 8 (range from 2 to 16). A total of 32 embryos underwent PGT-M, and 9 (28.1%) embryos were suitable for transfer. Six transfer cycles were performed, and 5 cycles got clinical pregnancy (83%) with five newborns (83%). The follow-up examinations conducted 10-18 months after PGT-M/delivery revealed no new lesions or tumor progression.ConclusionPGT-M results can provide important information for improving the consultation of hormone-related heritage tumor patients regarding their fertility preservation and reproductive options. Ovarian induction for women with hormone-related hereditary tumor syndrome is not associated with tumor progression.

In order to investigate the effects of different drying methods on the properties of porous starch. The present study used four drying methods, namely hot air drying (HD), spray drying (SPD), vacuum freeze drying (FD) and supercritical carbon dioxide drying (SCD) to prepare maize and kudzu porous starch. Findings indicated that the physicochemical properties (e.g., morphology, crystallinity, enthalpy value, porosity, surface area and water absorption capacity as well as dye absorption capacity, particle size) of porous starch were significantly affected by the drying method. Compared with other samples, SCD-treated porous starch exhibited the highest surface areas of the starch (2.943 and 3.139 m2/g corresponding to kudzu and maize, respectively), amylose content (22.02 % and 16.85 % corresponding to kudzu and maize, respectively), MB and NR absorption capacity (90.63 %, 100.26 % and 90.63 %, 100.26 %, corresponding to kudzu ad maize, respectively), and thermal stability, whereas HD-treated porous starch showed the highest water-absorption capacity (123.8 % and 131.31 % corresponding to kudzu and maize, respectively). The dye absorption of the maize and kudzu porous starch was positively correlated with surface area, according to Pearson's correlation analysis. Therefore, in this study, our aim was to explore the effects of different drying methods on the Structure and properties of porous starch, and provide reference for selecting the best drying method for its application in different fields.

Activated hepatic stellate cells (HSCs) have been widely recognized as a primary source of pathological myofibroblasts, leading to the accumulation of extracellular matrix and liver fibrosis. CD47, a transmembrane glycoprotein expressed on the surface of various cell types, has been implicated in non-alcoholic fatty liver disease. However, the precise role of CD47 in HSC activation and the underlying regulatory mechanisms governing CD47 expression remain poorly understood. In this study, we employed single-cell RNA sequencing analysis to investigate CD47 expression in HSCs from mice subjected to a high-fat diet. CD47 silencing in HSCs markedly inhibited the expression of fibrotic genes and promoted apoptosis. Mechanistically, we found that Yes-associated protein (YAP) collaborates with TEAD4 to augment the transcriptional activation of CD47 by binding to its promoter region. Notably, disruption of the interaction between YAP and TEAD4 caused a substantial decrease in CD47 expression in HSCs and reduced the development of high-fat diet-induced liver fibrosis. Our findings highlight CD47 as a critical transcriptional target of YAP in promoting HSC activation in response to a high-fat diet. Targeting the YAP/TEAD4/CD47 signaling axis may hold promise as a therapeutic strategy for liver fibrosis.

Objective: Motivated by Health Care 4.0, this study aims to reducing the dimensionality of traditional EEG features based on manual extracted features, including statistical features in the time and frequency domains. Methods: A total of 22 multi-scale features were extracted from the UNM and Iowa datasets using a 4th order Butterworth filter and wavelet packet transform. Based on single-channel validation, 29 channels with the highest R2 scores were selected from a pool of 59 common channels. The proposed channel selection scheme was validated on the UNM dataset and tested on the Iowa dataset to compare its generalizability against models trained without channel selection. Results: The experimental results demonstrate that the proposed model achieves an optimal classification accuracy of 100%. Additionally, the generalization capability of the channel selection method is validated through out-of-sample testing based on the Iowa dataset Conclusions: Using single-channel validation, we proposed a channel selection scheme based on traditional statistical features, resulting in a selection of 29 channels. This scheme significantly reduced the dimensionality of EEG feature vectors related to Parkinson’s disease by 50%. Remarkably, this approach demonstrated considerable classification performance on both the UNM and Iowa datasets. For the closed-eye state, the highest classification accuracy achieved was 100%, while for the open-eye state, the highest accuracy reached 93.75%.

Soil organic phosphorus (P) mineralization is catalyzed by phosphatases synthesized by plants or microorganisms, particularly when organic P is present and inorganic P is limited. We investigated how P status affects the substrate induction response of phosphatase activities and changes in labile inorganic P (ΔNaHCO3-Pi) by adding phosphodiester to long-term low P and high P-fertilized soils. Phosphodiester addition significantly increased acid phosphomonoesterase activity and ΔNaHCO3-Pi, while exhibiting non-significant effect on phosphodiesterase activity. No significant differences were observed in phosphodiester-induced phosphatase activities and ΔNaHCO3-Pi between the low P and high P-fertilized soils. Our results indicate that phosphodiester may incentivize microbially mediated enzymatic P mineralization not necessarily for P but possibly for energy. This emphasizes the importance of phosphodiester in the development of microbial strategies for mobilizing soil P.

Vaccination is the most feasible way of preventing rabies, an ancient zoonosis that remains a major public health concern globally. However, administration of inactivated rabies vaccination without adjuvants is always inefficient and necessitates four to five injections. In the current study, we explored the adjuvant characteristics of cordycepin, a major bioactive component of Cordyceps militaris, to boost immune responses against a commercially available rabies vaccine. We found that cordycepin could stimulate stronger phenotypic and functional maturation of dendritic cells (DCs). For animal experiments, mice were immunized 3 times with rabies vaccine in the presence or absence of cordycepin at 1-week interval. Analysis of T cell differentiation and serum antibody isotypes showed that humoral immunity was dominant with a Th2 biased immune response. These results were also supported by the raised ratio of follicular helper T cells (TFH) and germinal center B cells (GCB). Thus, titer of rabies virus neutralizing antibody (RVNAb) and rabies virus-specific memory B cells were both raised as a result. Furthermore, administration of cordycepin did not cause pathological phenomena or body weight loss. The findings indicate that cordycepin could be used as a promising adjuvant for rabies vaccines to get a higher range of protection without any side effects.

The Digital Elevation Model (DEM) super-resolution approach aims to improve the spatial resolution or detail of an existing DEM by applying techniques such as machine learning or spatial interpolation. Convolutional Neural Networks and Generative Adversarial Networks have exhibited remarkable capabilities in generating high-resolution DEMs from corresponding low-resolution inputs, significantly outperforming conventional spatial interpolation methods. Nevertheless, these current methodologies encounter substantial challenges when tasked with processing exceedingly high-resolution DEMs (256×256,512×512, or higher), specifically pertaining to the accurate restore maximum and minimum elevation values, the terrain features, and the edges of DEMs. Aiming to solve the problems of current super-resolution techniques that struggle to effectively restore topographic details and produce high-resolution DEMs that preserve coordinate information, this paper proposes an improved DEM super-resolution Transformer(DSRT) network for large-scale DEM super-resolution and account for geographic information continuity. We design a window attention module that is used to engage more elevation points in low-resolution DEMs, which can learn more terrain features from the input high-resolution DEMs. A GeoTransform module is designed to generate coordinates and projections for the DSRT network. We conduct an evaluation of the network utilizing DEMs of various types of terrains and elevation differences at resolutions of 64×64,256×256 and 512 × 512. The network demonstrated leading performance across all assessments in terms of root mean square error (RMSE) for elevation, slope, aspect, and curvature, indicating that Transformer-based deep learning networks are superior to CNNs and GANs in learning DEM features.

Noise is a significant factor affecting imaging quality because it seriously reduces the detection signal-to-noise ratio (SNR), especially in feeble-light detection. In this paper, we propose a practical method to separate signal from noise background in ghost imaging (GI) systems based on correlation calculation. Experiments have shown that this method can significantly increase the SNR of the reconstructed images. Our research provides a novel method for suppressing noise influence on feeble-light GI, which has valuable reference value in biomedicine and remote sensing.

Background: Charcot-Marie-Tooth type 1A (CMT1A), the most frequent type of Charcot-Marie-Tooth disease, is mainly caused by a 1.4-Mb duplication containing the PMP22 gene. There is no effective treatment other than general supportive care and symptomatic treatment. Preimplantation genetic testing for monogenic defects (PGT-M) is an alternative approach for obtaining healthy babies. Methods: A new technology and analysis method based on next-generation sequencing (NGS) was developed to detect duplication mutations directly. Simultaneously, aneuploidy and linkage analyses were performed to achieve a comprehensive and accurate embryo diagnosis. Results: Eight couples were recruited in this study; PMP22 duplication was validated in seven couples, and PMP22 splicing mutation was found in one. Forty-five embryos from 12 PGT cycles were successfully detected using this novel method. The direct detection results for all embryos were consistent with the linkage analyses, suggesting a 100 % accuracy rate, and the aneuploidy rate of the biopsied blastocysts was 33.3 %. Eventually, 18 of the 45 diagnosed embryos were deemed suitable for transfer. Four healthy babies from three families were delivered and their genetic status confirmed by amniocentesis. Additionally, there were no adverse effects of anesthesia or increased pregnancy complications during PGT-M in female patients with CMT1A. Conclusions: This study provided a simple, reliable, and efficient method that can directly detect PMP22 mutations based on NGS data and does not require positive family members. A clinical workflow for CMT1A interruption in the offspring before embryo implantation is also summarized.

Summary: Programmable control over therapeutic processes in phototherapy, like photodynamic therapy (PDT), is promising but challenging. This study uses an energy segmentation-based strategy to synthesize core-multi-shell upconversion nanoparticles (UCNPs), which can release three different colors (red, green, and blue) upon exposure to different near-infrared light (1550 nm, 808 nm, and 980 nm). By combining these UCNPs with photosensitizers and nitric oxide (NO) donors, a smart “off-on” PDT nanoplatform is developed. UCNPs enable independent activation of imaging, release of NO, and generation of reactive oxygen species using specific light wavelengths. The results show that sequential NO release before PDT can greatly alleviate tumor hypoxia by reducing oxygen consumption. This stepwise approach shows potential for precise NIR light-activated and imaging-guided phototherapy.

Silicon qubits based on specific SOI FinFETs and nanowire (NW) transistors have demonstrated promising quantum properties and the potential application of advanced Si CMOS devices for future quantum computing. In this paper, for the first time, the quantum transport characteristics for the next-generation transistor structure of a stack nanosheet (NS) FET and the innovative structure of a fishbone FET are explored. Clear structures are observed by TEM, and their low-temperature characteristics are also measured down to 6 K. Consistent with theoretical predictions, greatly enhanced switching behavior characterized by the reduction of off-state leakage current by one order of magnitude at 6 K and a linear decrease in the threshold voltage with decreasing temperature is observed. A quantum ballistic transport, particularly notable at shorter gate lengths and lower temperatures, is also observed, as well as an additional bias of about 1.3 mV at zero bias due to the asymmetric barrier. Additionally, fishbone FETs, produced by the incomplete nanosheet release in NSFETs, exhibit similar electrical characteristics but with degraded quantum transport due to additional SiGe channels. These can be improved by adjusting the ratio of the channel cross-sectional areas to match the dielectric constants.

Lactic acid bacteria (LAB) are organic supplements that have several advantages for the health of the host. Tibetan chickens are an ancient breed, which evolve unique gut microbiota due to their adaptation to the hypoxic environment of high altitude. However, knowledge of LAB isolated from Tibetan chickens is very limited. Thus, the purpose of this study was to assess the probiotic properties of Lactobacillus Plantarum (LP1), Weissella criteria (WT1), and Pediococcus pentosaceus (PT2) isolated from Tibetan chickens and investigate their effects on growth performance, immunoregulation and intestinal microbiome in broiler chickens. Growth performance, serum biochemical analysis, real-time PCR, and 16S rRNA sequencing were performed to study the probiotic effects of LP1, WT1, and PT2 in broiler chickens. Results showed that LP1, WT1 and PT2 were excellent inhibitors against Escherichia coli (E. coli ATCC25922), meanwhile, LP1, WT1, and PT2 significantly increased weekly weight gain, villus height, antioxidant ability and gut microbiota diversity indexes in broilers. In addition, LP1 and PT2 increased the relative abundance of Lactobacillus and decreased Desulfovibrio in comparison with T1 (control group). Additionally, oral LAB can reduce cholesterol and regulate the expression of tight junction genes in broiler chickens, suggesting that LAB can improve the integrity of the cecal barrier and immune response. In conclusion, LAB improved the growth performance, gut barrier health, intestinal flora balance and immune protection of broiler chickens. Our findings revealed the uniqueness of LAB isolated from Tibetan chickens and its potential as a probiotic additive in poultry field.

An optimized method of ultrasound-assisted extraction (UAE) was proposed for the effective extraction of polyphenols from the mushroom of Cantharelles cibarius and evaluated by response surface methodology. In this study, solid-liquid ratio, ultrasonic temperature, ethanol concentration and ultrasonic time were investigated and optimized using a central composite rotatable design. The main polyphenols were identified by UPLC-MS method. Besides, traditional extracting methods including maceration and soxhlet extraction methods were also carried out for comparison. Moreover, the antioxidant activity of polyphenols was evaluated by the scavenging abilities of DPPH free radical, ABTS+ free radical and measuring Fe3+ reduction capacity. The results showed that the best extraction conditions were ethanol concentration 40%, solid-liquid ratio 1:32 g/mL, ultrasonic temperature 40 ℃ and ultrasonic time 21 min . Ultrasonic assisted extraction of polyphenols was the highest, 11.80 mg/g, the content of extracted polyphenols was 8.60 mg/g, the polyphenols of Soxhlet heat reflux was 3.60 mg/g. The result of UPLC-MS analysis showed that the main phenols contained gallic acid, caffeic acid and eugenic acis. Compared to conventional methods, the ultrasonic assisted extraction was an efficient, rapid and simple approach for the extraction of polyphenols with good antioxidants activity from Cantharelles cibarius.

Abstract Circular RNAs (circRNAs) have been reported to play essential roles in tumorigenesis and progression. This study aimed to identify dysregulated circRNAs in gastric cancer (GC) and investigate the functions and underlying mechanism of these circRNAs in GC development. Here, we identify circ_CEA, a circRNA derived from the back-splicing of CEA cell adhesion molecule 5 (CEA) gene, as a novel oncogenic driver of GC. Circ_CEA is significantly upregulated in GC tissues and cell lines. Circ_CEA knockdown suppresses GC progression, and enhances stress-induced apoptosis in vitro and in vivo. Mechanistically, circ_CEA interacts with p53 and cyclin-dependent kinases 1 (CDK1) proteins. It serves as a scaffold to enhance the association between p53 and CDK1. As a result, circ_CEA promotes CDK1-mediated p53 phosphorylation at Ser315, then decreases p53 nuclear retention and suppresses its activity, leading to the downregulation of p53 target genes associated with apoptosis. These findings suggest that circ_CEA protects GC cells from stress-induced apoptosis, via acting as a protein scaffold and interacting with p53 and CDK1 proteins. Combinational therapy of targeting circ_CEA and chemo-drug caused more cell apoptosis, decreased tumor volume and alleviated side effect induced by chemo-drug. Therefore, targeting circ_CEA might present a novel treatment strategy for GC.

Building a high-precision bathymetry digital elevation model is essential for navigation planning, marine and lake resource planning, port construction, and underwater archaeological projects. However, existing bathymetry methods have yet to be effectively and comparatively analyzed. This paper comprehensively reviews state-of-the-art bathymetry methods, including data acquisition techniques, model accuracy, and interpolation algorithms for underwater terrain mapping. First, We assess the merits and drawbacks of novel data acquisition devices, such as single-beam/multi-beam echo sounders and light detection and ranging systems. After that, we analyze the accuracy of the ETOPO1, GEBCO_2022 and SRTM15 to provide valuable insights into their performance. Furthermore, we evaluate ANUDEM, Inverse Distance Weighting, Kriging and Nearest Neighbor interpolation algorithms in different underwater terrains by comparing their applicability, reliability, and accuracy in various underwater environments. Finally, we discuss the development trends and challenges in underwater bathymetry technology and offer a forward-looking perspective on the future of this essential field.

BackgroundMultiple regimens have been widely used in the eradication treatment of Helicobacter pylori infection in children. However, there is a lack of comparison and evaluation of their effectiveness in different regions of the world.MethodsRandomized controlled trials were retrieved. Review Manager 5.4, Stata SE 15 and R 4.0.4 statistical software were used to analyze date. The ranking probability is assessed according to the surfaces under cumulative ranking (SUCRA).Results163 studies were eligible for this study, involving 336 arms and 18,257 children, and 10 different interventions. The results showed that the eradication rates of sequential therapy with probiotics (SP), bismuth-containing quadruple (Quadruple) therapy, concomitant therapy and PCN therapy were at least 90%. Cumulative ranking showed that SP therapy had the best eradication effect (SUCRA 92.7%) whereas Bismuth-containing triple therapy (B) had the worst (SUCRA 3.5%). Subgroup analysis suggested that SP therapy ranked first in China and other regions, and the ranking of Triple therapy with probiotics therapy (TP) was equally stable (SUCRA 72.0% vs 76.4% respectively). The security of the SP and TP therapy had great advantages.ConclusionsAs for the eradication treatment of Helicobacter pylori infection in children, SP therapy ranks highest. SP and TP therapies are most safe.

Biochar-immobilized bacteria have been widely used to remove organic pollutants; however, the enhanced effect of biochar-immobilized bacteria on tetrabromobisphenol A (TBBPA) removal has not been fully investigated and the removal mechanism remains unclear. In this study, a bacterial strain with high TBBPA degradation ability, Burkholderia cepacian Y17, was isolated from an e-waste disassembly area, immobilized with biochar, and used for the removal of TBBPA. Comparisons were performed of the factors affecting the immobilization and TBBPA removal efficiency, including the biochar preparation temperature, immobilization temperature, and pH. The highest 7-day TBBPA removal efficiency by immobilized bacteria was observed with the most suitable biochar preparation temperature (BC500) and an immobilization pH and temperature of 7 and 35 °C, respectively. The TBBPA removal efficiency reached 59.37%, which was increased by 30.23% and 15.88% compared to that of free and inactivated immobilized Y17, respectively. The suitable biochar preparation temperature BC500, immobilization temperature of 35 °C, and neutral pH of 7 increased the bacterial population and extracellular polymer concentration, which facilitated bacterial immobilization on biochar and promoted TBBPA removal. In this case, the high immobilized bacteria concentration (4.62 × 108 cfu∙g−1) and protein and polysaccharide contents (28.43 and 16.16 mg·g−1) contributed to the removal of TBBPA by facilitating TBBPA degradation. The main TBBPA degradation processes by BC500-immobilized Y17 involved debromination, β-scission, demethylation, O-methylation, hydroxylation, and hydroxyl oxidation. This study proposes a method for preparing immobilized bacteria for TBBPA removal and enriches the microbial degradation technology for TBBPA.

Aqueous zinc (Zn)‐ion batteries (ZIBs) have been considered as the most promising candidate for large‐scale energy storage system. However, the severe and uncontrollable dendrite growth of Zn anodes hinders the practical application. Herein, an ultraconformal horizontal Zn deposition is achieved, which is profiting from the epitaxial interface (InGaZn6O9) formed via spontaneously alloying between liquid Ga–In alloy (EGaIn) and Zn. The exposed (0016) plane of InGaZn6O9 matches well with (002) plane of Zn, inducing horizontal and dense Zn deposition. The resultant anode endows with prolonged cycling stability, and the full battery paired with MnO2 exhibits a stable lifespan over 4400 cycles at 5 A g−1. Meanwhile, the self‐formed ultraconformal interface realizes 360° no dead angle protection of anode, which is promising in flexible electronics. And there is no obvious capacity recession of the pouch cell even after bending 180°, demonstrating impressive flexibility. More importantly, the interface can be simply fabricated over a large area, displaying the large‐scale viability. The tailored approach delivers a constructive guideline for dendrite‐free Zn anode, showing great potential in the industrial production.

Autonomous path planning along riverbanks is crucial for unmanned surface vehicles (USVs) to execute specific tasks such as levee safety detection and underwater pipe inspections, which are vital for riverbank safety and water environment protection. Given the intricate shapes of riverbanks, the dynamic nature of tidal influences, and constraints in real-time cartographic updates, there is a heightened susceptibility to inaccuracies during manual waypoint designation. These factors collectively impact the efficiency of USVs in following riverbank paths. We introduce a riverbank following planner (RBFP) for USVs to tackle this challenge. This planner, utilizing 2D LiDAR, autonomously selects the following point to follow riverbank shapes. Additionally, a PID controller is integrated to compensate for position and yaw errors. Our proposed method reduces the deviation between the USV’s planned path and the actual riverbank shape. We simulated straight, convex, and concave riverbanks in the Virtual RobotX (VRX) simulator while considering the impacts of wind, waves, and USV dynamics. The experimental result indicates the following performance of 96.92%, 67.30%, and 61.15% for straight, convex, and concave banks, respectively. The proposed RBFP can support a novel autonomous navigation scenario for autonomous paths following along the riverbank without any preplanned paths or destinations.

A zebrafish behavioral model is prevalent and has potential to be an important component of chemical screening and toxicity evaluations. However, applications of such zebrafish behavioral assays remain limited because of flaws in monitoring procedures and designs and inconsistent test methodology among published studies. In the present study, a behavioral assay method based on zebrafish larvae was established for rapid chemical toxicity evaluation, which included the optimization of test conditions and the development of behavioral parameters, such as accumulated distance, frequency of active state, acceleration and mobility. To validate the reliability and investigate the specificity of the method developed, the behavioral effects were evaluated for a set of 28 chemicals (flame retardants, pesticides, fungicides or heavy metals) typically reported in the environment and showing effects by various modes of action (MOAs). Our results showed that the most suitable container and volume for behavioral tests of zebrafish larvae was 24-well plate containing 8-mm depth of solution, and the most appropriate developmental period for monitoring was at 5 days post-fertilization (dpf). Chemical exposure led to various dose-dependent responses of the behavioral parameters via different MOAs, e.g. estrogenic chemicals caused hyperactivity through neurodevelopment disturbance and neurotoxic chemicals led to hypoactivity through disruption of nerve signal transmission. Our results suggested that the optimized behavior monitioring method have the potential for identification and classification of neurotoxic chemicals.

This study was aimed to investigate the characteristics of refractive parameters in premature infants and children aged 3–8 years with mild retinopathy of prematurity (ROP) and to explore the effects of premature delivery and mild ROP on the development of refractive status and ocular optical components. Premature infants who underwent ocular fundus oculi screening in our hospital between January 2009 and February 2011 were included and divided into the ROP group and the non-ROP group. Full-term infants were the controls. The results of the annual ocular examination conducted between 2014 and 2018 were analysed, and the refractive status, optical components, and developmental trends were compared among the three groups. The total follow-up time was 4–5 years. The prevalence of myopia and astigmatism was high in the ROP group (P

Induction of antigen-specific immune response by maturing dendritic cells (DCs) is a promising strategy for anti-tumor immunotherapy. However, the immunosuppressive tumor microenvironment (TME) and the ineffective tumor-associated antigen (TAAs) presentation of DCs have hindered the efficacy of immunotherapy. Herein, we developed an immunostimulatory nanosphere by direct self-assembly of cyanine5 labeled CPG oligodeoxynucleotide and doxorubicin (Cy5-CPG/DOX). The introduction of Cy5 into CPG could increase the interaction of Cy5-CPG and DOX, accelerating the formation of Cy5-CPG/DOX nanosphere. In vivo, DOX can effectively downregulate the level of regulatory T cells to reverse and abrogate immunosuppressive. Meanwhile, DOX induce immunogenic cell death to produce TAAs, which combined with Cy5-CPG promote the maturation of DCs, improving the TAAs presentation ability of DCs. Thus, the Cy5-CPG/DOX could awaken the innate immune system, sensitizing tumors to immune checkpoint inhibitors mediated by the programmed death-ligand 1 (PD-L1) antibody. In this way, the Cy5-CPG/DOX combined with PD-L1 can decrease the exhaustion of cytotoxic T lymphocytes, eliciting a durable systemic anti-tumor immunity to eradicate cancer. Our work establishes a stable approach for constructing immunostimulatory nanodrug, promoting the development of progressive therapeutic systems.

Chromosomal mosaicism is common throughout human pre- and post-implantation development. However, the incidence and characteristics of mosaicism in human blastocyst remain unclear. Concerns and confusions still exist regarding the interpretation of chromosomal mosaicism on preimplantation genetic testing for aneuploidy (PGT-A) results and embryo development. Here, we aimed to estimate the genetic concordance between trophectoderm (TE), inner cell mass (ICM) and the corresponding human embryonic stem cells (hESCs), and to explore the characteristics of mosaicism in human blastocyst and hESCs on a single cell level. The single cell sequencing results of TE cells indicated that 65.71% of the blastocysts were mosaic (23 in 35 embryos), while the ICM sequencing results suggested that 60.00% of the blastocysts were mosaic (9 in 15 embryos). The incidence of mosaicism for the corresponding hESCs was 33.33% (2 in 6 embryos). No significant difference was observed between the mosaic rate of TE and that of ICM. However, the mosaic rate of the corresponding hESCs was significantly lower than that of TE and ICM cells, suggesting that the incidence of mosaicism may decline during embryonic development. Upon single cell sequencing, we found several "complementary" copy number variations (CNVs) that were usually not revealed in clinical PGT-A which used multi-cell DNA sequencing (or array analysis). This indicates the potential diagnostic risk of PGT-A based multi-cell analysis routinely in clinical practice. This study provided new insights into the characteristics, and considerable influences, of mosaicism on human embryo development, as well as the clinical risks of PGT-A based on multi-cell biopsies and bulk DNA assays.

Developing novel silicon quantum dots (Si-QDs) on conventional CMOS process is one of the most important technologies in Si quantum computing to realize multi-bit integration with a large scale. In this paper, an analysis model based on master equation and realized by Python code is established to predict and optimize the performance of fabricated diamond channel Si-QDs for potential circuit applications. The model can fast describe the I-V characteristics of devices both in qualitative and semi quantitative method. The inherent tunneling process of Si-QDs can be well simulated by introducing additional parameters and the contribution of neighboring states can be analyzed by setting global parameters. In addition, the calculation speed and accuracy can be readily balanced by modifying the setting parameters. The simulation results of the model are in good agreement with the experimental results at low temperature, which lays a foundation for the performance prediction, structure and process optimization of the Si-QDs for a large scale circuit applications.

Advanced adenoma (AA) holds a significantly increased risk for progression to colorectal cancer (CRC), and we developed a noninvasive DNA methylation prediction model to monitor the risk of AA progression to CRC. We analyzed the differential methylation markers between 53 normal mucosa and 138 CRC tissues, as well as those in cfDNA (cell-free DNA) between 59 AA and 68 early-stage CRC patients. We screened the overlapping markers between tissue DNA and cfDNA for model variables and optimized the selected variables. Then, we established a cfDNA methylation prediction model (SDMBP model) containing seven methylation markers that can effectively discriminate early-stage CRC and AA in the training and validation cohorts, and the AUC (area under the curve) reached 0.979 and 0.918, respectively. Our model also reached high precision (AUC=0.938) in detecting advanced CRC (stage III/IV) and presented better performance than serum CEA and CA199 in screening CRC. The cd-score of the SDMBP model could also robustly predict the TNM stage of CRC. Overall, our SDMBP model can monitor the malignant progression from AA to CRC, and may provide a noninvasive monitoring method for high-risk populations with AA.

Due to the rapidly increasing number of students at universities in recent years, universities may arrange students from different majors in the same class, which may bring several challenges in teaching and learning for students and teachers, such as poor class experience, less class discussion and more workload for teachers. In this paper, we investigate the learning achievements of students with different major backgrounds based on a large-size course of Introduction to Java Programming. Approaches of difficulty index, incrimination index, failure rate, median average mark, average mark and standard deviation are used to evaluate students’ learning achievements based on students’ coursework assignments, continuous assessment and the final exam. Results show that major backgrounds could significantly affect learning achievements even in the same teaching and learning environment. To achieve a better learning experience and performance, we finally divided the original module into two separate modules for students with different major backgrounds.

Reductive biodegradation by microorganisms has been widely explored for detoxifying recalcitrant contaminants; however, the biodegradation capacity of microbes is limited by the energy level of the released electrons. Here, we developed a method to self-assemble Shewanella oneidensis-CdS nanoparticle hybrids with significantly improved reductive biodegradation capacity and constructed a living material by encapsulating the hybrids in hydrogels. The material confines the nano-bacteria hybrids and protects them from environmental stress, thus improving their recyclability and long-term stability (degradation capacity unhindered after 4 weeks). The developed living materials exhibited efficient photocatalytic biodegradation of various organic dyes including azo and nitroso dyes. This study highlights the feasibility and benefits of constructing self-assembled nano-bacteria hybrids for bioremediation and sets the stage for the development of novel living materials from nano-bacteria hybrids.

Most high-performance semantic segmentation networks are based on complicated deep convolutional neural networks, leading to severe latency in real-time detection. However, the state-of-the-art semantic segmentation networks with low complexity are still far from detecting objects accurately. In this paper, we propose a real-time semantic segmentation network, RecepNet, which balances accuracy and inference speed well. Our network adopts a bilateral architecture (including a detail path, a semantic path and a bilateral aggregation module). We devise a lightweight baseline network for the semantic path to gather rich semantic and spatial information. We also propose a detail stage pattern to store optimized high-resolution information after removing redundancy. Meanwhile, the effective feature-extraction structures are designed to reduce computational complexity. RecepNet achieves an accuracy of 78.65% mIoU (mean intersection over union) on the Cityscapes dataset in the multi-scale crop and flip evaluation. Its algorithm complexity is 52.12 GMACs (giga multiply–accumulate operations) and its inference speed on an RTX 3090 GPU is 50.12 fps. Moreover, we successfully applied RecepNet for blue-green algae real-time detection. We made and published a dataset consisting of aerial images of water surface with blue-green algae, on which RecepNet achieved 82.12% mIoU. To the best of our knowledge, our dataset is the world’s first public dataset of blue-green algae for semantic segmentation.

Path-keeping requires unmanned surface vehicles (USVs) to follow a planned path in autonomous navigation. It is essential for USVs to carry out autonomous tasks such as collecting various data of water quality and surrounding terrain for exploration and protection of water environments. However, due to obstacle avoidance and other factors such as wind, water waves, and dynamics of USVs, USVs usually deviate from the original planned path during autonomous navigation. This paper proposes a novel path-keeping algorithm based on the artificial potential field method (PK-APF) for USVs. To minimize the deviation between the actual path and the original planned path, the vertical distance and the virtual foot points of the current position of USVs to the original path (a line connecting the previous navigation point and the next navigation point) are calculated. When the vertical distance is larger than a threshold, we regard the vertical foot point as a virtual goal point to guide the USVs to navigate the original path in real-time to achieve high-precision path-keeping. Obstacle avoidance is simulated in the MATLAB and Virtual RobotX (VRX) simulators, and the influence of wind and water waves is considered in VRX. Experiments are conducted in typical scenarios and results show that PK-APF outperforms the traditional APF by at least 22%. The work provides an important basis for real-life environments. Substantial further work is planned for applying the method on a physical USV.