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Abstract RNA interference (RNAi) is a powerful tool for sequence-specific gene knockdown in therapeutic and research applications. However, spatiotemporal control of RNAi is required to decrease nonspecific targeting, potential toxicity, and allow targeting of essential genes. Herein we describe a class of de-novo-designed RNA switches that enable sequence-specific regulation of RNAi in mammalian cells. Using cis-repressing RNA elements, we engineer RNA devices that only initiate microRNA biogenesis when binding with cognate trigger RNAs. We demonstrate that this conditional RNAi system, termed Orthogonal RNA Interference induced by Trigger RNA (ORIENTR), provides up to 14-fold increases in artificial miRNA biogenesis upon activation in orthogonal libraries. We show that integration of ORIENTR triggers with dCas13d enhances dynamic range to up to 31-fold. We further demonstrate that ORIENTR can be applied to detect endogenous RNA signals and to conditionally knockdown endogenous genes, thus enabling regulatory possibilities including cell-type-specific RNAi and rewiring of transcriptional networks via RNA profile.

Abstract DNA base editing technologies predominantly utilize engineered deaminases, limiting their ability to edit thymine and guanine directly. In this study, we successfully achieve base editing of both cytidine and thymine by leveraging the translesion DNA synthesis pathway through the engineering of uracil-DNA glycosylase (UNG). Employing structure-based rational design, exploration of homologous proteins, and mutation screening, we identify a Deinococcus radiodurans UNG mutant capable of effectively editing thymine. When fused with the nickase Cas9, the engineered DrUNG protein facilitates efficient thymine base editing at endogenous sites, achieving editing efficiencies up to 55% without enrichment and exhibiting minimal cellular toxicity. This thymine base editor (TBE) exhibits high editing specificity and significantly restores IDUA enzyme activity in cells derived from patients with Hurler syndrome. TBEs represent efficient, specific, and low-toxicity approaches to base editing with potential applications in treating relevant diseases.

Traditional optical waveguides or mediums are often silica-based materials, but their applications in biomedicine and healthcare are limited due to the poor biocompatibility and unsuitable mechanical properties. In term of the applications in human body, a biocompatible hydrogel system with excellent optical transparency and mechanical flexibility could be beneficial. In this review, we explore the different designs of hydrogel-based optical waveguides derived from natural and synthetic sources. We highlighted key developments such as light emitting contact lenses, implantable optical fibres, biosensing systems, luminating and fluorescent materials. Finally, we expand further on the challenges and perspectives for hydrogel waveguides to achieve clinical applications.

Abstract Background At present, it has been found that many patients have acquired resistance to radiotherapy, which greatly reduces the effect of radiotherapy and further affects the prognosis. CircRNAs is involved in the regulation of radiosensitivity of many kinds of tumor cells. Therefore, the main purpose of this study is to explore the regulatory effect of CircRNA_101491 on radiosensitivity of ESCC and its related mechanism. Methods We established ESCC radiation-resistant cell line (KYSE150R cell) by gradient dose method, and tested the difference of KYSE150 between KYSE150R cell and parent cell in vitro. Then, after knocking down the expression of CircRNA_101491, a series of in vitro experiments were conducted to verify the effects of CircRNA_101491 on the phenotype and radiosensitivity of KYSE150R cells, and further analyzed the related regulatory mechanism. In addition, we also used the model of transplanted tumor in nude mice to investigate the effect of CircRNA_101491 on the radiosensitivity of ESCC in vivo. Results According to a series of in vitro experiments, we confirmed that KYSE150R cells lost the epithelial phenotype and obtained interstitial cell-like phenotype, and found that CircRNA_101491 was highly expressed in KYSE150R cells. In addition, we found that knocking down the expression of CircRNA_101491 will lift the inhibition of miR-125a-5p, and then reverse the process of EMT, accelerate the process of apoptosis, thus play a role in radiosensitization. The in vivo experiment of transplanted tumor in nude mice also showed that knocking down the expression of CircRNA_101491 could enhance the radiosensitivity of ESCC. Conclusion In conclusion, we confirmed that interfering with the expression of CircRNA_101491 can relieve the inhibition of miR-125a-5p, thus reverse the process of interstitial phenotype, accelerate the process of apoptosis, and enhance the radiosensitivity of ESCC.

Elevated levels of high mobility group protein B1 (HMGB1) play a significant role in the pathogenesis of many diseases, but is particularly important for the formation of malignant tumors. Nonetheless, the function of HMGB1 and the underlying mechanism of laryngeal squamous cell carcinoma (LSCC) remain incompletely understood, causing uncertainty. Here we found immunohistochemistry from 97 LSCC tissues showed HMGB1 was upregulated, which was associated with poor differentiation. HMGB1 knockdown could significantly inhibit wound closure and colony formation. The full-genome gene expression microarray was performed to investigate the mechanism. After knockdown of HMGB1 by siRNA, among the expressed differential genes, 10 genes were randomly selected for validation. Then, shRNA lentivirus targeting these genes were constructed to explore their role in LSCC by cell proliferation assay. LSM6 downregulation was dramatically promoted by HMGB1 knockdown, resulting in higher expression in LSCC tissues. Furthermore, downregulation of LSM6 could significantly suppress cell proliferation, migration and colony formation. This study indicated that HMGB1 promoted LSCC cell malignant phenotypes through regulation of LSM6. We anticipate that HMGB1-LSM6 could be a putative therapeutic target for LSCC.

Abstract Identification of interactions between chemical compounds and proteins is crucial for various applications, including drug discovery, target identification, network pharmacology, and elucidation of protein functions. Deep neural network-based approaches are becoming increasingly popular in efficiently identifying compound-protein interactions with high-throughput capabilities, narrowing down the scope of candidates for traditional labor-intensive, time-consuming and expensive experimental techniques. In this study, we proposed an end-to-end approach termed SPVec-SGCN-CPI, which utilized simplified graph convolutional network (SGCN) model with low-dimensional and continuous features generated from our previously developed model SPVec and graph topology information to predict compound-protein interactions. The SGCN technique, dividing the local neighborhood aggregation and nonlinearity layer-wise propagation steps, effectively aggregates K-order neighbor information while avoiding neighbor explosion and expediting training. The performance of the SPVec-SGCN-CPI method was assessed across three datasets and compared against four machine learning- and deep learning-based methods, as well as six state-of-the-art methods. Experimental results revealed that SPVec-SGCN-CPI outperformed all these competing methods, particularly excelling in unbalanced data scenarios. By propagating node features and topological information to the feature space, SPVec-SGCN-CPI effectively incorporates interactions between compounds and proteins, enabling the fusion of heterogeneity. Furthermore, our method scored all unlabeled data in ChEMBL, confirming the top five ranked compound-protein interactions through molecular docking and existing evidence. These findings suggest that our model can reliably uncover compound-protein interactions within unlabeled compound-protein pairs, carrying substantial implications for drug re-profiling and discovery. In summary, SPVec-SGCN demonstrates its efficacy in accurately predicting compound-protein interactions, showcasing potential to enhance target identification and streamline drug discovery processes. Scientific contributions The methodology presented in this work not only enables the comparatively accurate prediction of compound-protein interactions but also, for the first time, take sample imbalance which is very common in real world and computation efficiency into consideration simultaneously, accelerating the target identification and drug discovery process.

The atmospheric correction of hyperspectral data stands as a fundamental step in quantitative applications, crucial for the accurate analysis of hyperspectral information. Zhuhai-1 hyperspectral data, characterized by its high spatial and spectral resolution, holds substantial potential and advantages for the quantification of water body information. Nonetheless, the adoption of more precise physical models for atmospheric correction often demands extensive satellite and ground environmental parameters, which pose practical challenges in applying physical models The Dark Object Subtraction (DOS), leveraging the intrinsic spectral characteristics of the imagery, offers an efficient alternative for achieving improved atmospheric correction results tailored to the data and study area. In this context, this study presents a Dark Object Subtraction for Water body information extraction (DOSW), specifically designed to advance the quantification of water body information in Zhuhai-1 hyperspectral data. The proposed method is rigorously evaluated by comparing the correction results from the Foshan region and Feilaixia Reservoir with standard and measured spectra of typical objects. The results demonstrate the accuracy of DOSW in atmospheric correction, with correlation coefficients exceeding 0.7 when compared to standard spectra for three representative objects. Notably, DOSW achieves exceptional accuracy in water body correction, achieving a correlation coefficient of 0.95 and an RMSE of 0.002 in the Feilaixia Reservoir, and a correlation coefficient of 0.72 and an RMSE of 0.005 in the Foshan region. Overall, the results underscore the efficacy of DOSW in accurately addressing atmospheric correction challenges to Zhuhai-1 hyperspectral data, effectively meeting the requirements of hyperspectral quantification applications.

Abstract Sleep, locomotor and social activities are essential animal behaviors, but their reciprocal relationships and underlying mechanisms remain poorly understood. Here, we elicit information from a cutting-edge large-language model (LLM), generative pre-trained transformer (GPT) 3.5, which interprets 10.2–13.8% of Drosophila genes known to regulate the 3 behaviors. We develop an instrument for simultaneous video tracking of multiple moving objects, and conduct a genome-wide screen. We have identified 758 fly genes that regulate sleep and activities, including mre11 which regulates sleep only in the presence of conspecifics, and NELF-B which regulates sleep regardless of whether conspecifics are present. Based on LLM-reasoning, an educated signal web is modeled for understanding of potential relationships between its components, presenting comprehensive molecular signatures that control sleep, locomotor and social activities. This LLM-aided strategy may also be helpful for addressing other complex scientific questions.

Dexamethasone (DXMS), a synthetic glucocorticoid, is known for its pharmacological effects on anti-inflammation, stress response enhancement and immune suppression, and has been widely used to treat potential premature delivery and related diseases. However, emerging evidence has shown that prenatal DXMS exposure leads to increased susceptibility to multiple diseases. In the present study, we used zebrafish as a model to study the effects of embryonic DXMS exposure on liver development and disease. We discovered that embryonic DXMS exposure upregulated the levels of total cholesterol and triglycerides in the liver, increased the glycolysis process and ultimately caused hepatic steatosis in zebrafish larvae. Furthermore, DXMS exposure exacerbated hepatic steatosis in a zebrafish model of fatty liver disease. In addition, we showed that embryonic DXMS exposure worsened liver injury induced by paracetamol (N-acetyl-p-aminophenol, APAP), increased the infiltration of macrophages and neutrophils, and promoted the expression of inflammatory factors, leading to impeded liver regeneration. Taken together, our results provide new evidence that embryonic DXMS exposure exacerbates hepatic steatosis by activating glycolytic pathway, aggravates APAP-induced liver damage and impeded regeneration under a persistent inflammation, calling attention to DXMS administration during pregnancy with probable clinical implications for offspring.

The spray cooling and tempering technology has a series of advantages, such as improving the tempering quality and reducing energy consumption. In order to optimize the tempering technological parameters, it is necessary to accurately control the thermal history and temperature distribution of a hot glass surface during spray cooling. However, measuring the inner temperature of tempered glass proved challenging. The Euler-Lagrangian approach was utilized for simulating the process of spray cooling the glass surface. To validate the accuracy of model predictions, experimental studies were conducted on the tempering of glass by a single nozzle. The numerical outcomes exhibit strong correspondence with the experimental findings. Building upon the foundation, the study analyzed the heat transfer mechanisms in different states including film boiling, nucleate boiling, and forced convection. Subsequently, the effects of spray distance, spray loading fraction, spray pressure, and final cooling temperature on the heat transfer rate and temperature homogeneity were discussed. The results revealed that reducing the spray distance, increasing the spray loading fraction and spray pressure can improve the cooling rate and reduce energy consumption, but it aggravated the uneven distribution of temperature over the glass surface. Moderately increasing the final cooling temperature had little effect on the tempering quality of glass, but it significantly reduced the energy consumption for spray cooling. Within the experimental range, the optimal final cooling temperature was 573.15 K.

ABSTRACT Objective: Tibial plateau fractures are common intra-articular fractures that pose classification and treatment challenges for orthopedic surgeons. Objective: This study examines the value of 3D printing for classifying and planning surgery for complex tibial plateau fractures. Methods: We reviewed 54 complex tibial plateau fractures treated at our hospital from January 2017 to January 2019. Patients underwent preoperative spiral CT scans, with DICOM data processed using Mimics software. 3D printing technology created accurate 1:1 scale models of the fractures. These models helped subdivide the fractures into seven types based on the tibial plateau's geometric planes. Surgical approaches and simulated operations, including fracture reduction and plate placement, were planned using these models. Results: The 3D models accurately depicted the direction and extent of fracture displacement and plateau collapse. They facilitated the preoperative planning, allowing for precise reconstruction strategies and matching intraoperative details with the pre-printed models. Post-surgery, the anatomical structure of the tibial plateau was significantly improved in all 54 cases. Conclusion: 3D printing effectively aids in the classification and preoperative planning of complex tibial plateau fractures, enhancing surgical outcomes and anatomical restoration. Level of Evidence IV, Prospective Study.

Excessive buildup of highly reactive molecules can occur due to the generation and dysregulation of reactive oxygen species (ROS) and their associated signaling pathways. ROS have a dual function in cancer development, either leading to DNA mutations that promote the growth and dissemination of cancer cells, or triggering the death of cancer cells. Cancer cells strategically balance their fate by modulating ROS levels, activating pro-cancer signaling pathways, and suppressing antioxidant defenses. Consequently, targeting ROS has emerged as a promising strategy in cancer therapy. Shikonin and its derivatives, along with related drug carriers, can impact several signaling pathways by targeting components involved with oxidative stress to induce processes such as apoptosis, necroptosis, cell cycle arrest, autophagy, as well as modulation of ferroptosis. Moreover, they can increase the responsiveness of drug-resistant cells to chemotherapy drugs, based on the specific characteristics of ROS, as well as the kind and stage of cancer. This research explores the pro-cancer and anti-cancer impacts of ROS, summarize the mechanisms and research achievements of shikonin-targeted ROS in anti-cancer effects and provide suggestions for designing further anti-tumor experiments and undertaking further experimental and practical research.

Objective: To evaluate the synergistic potential of Focused Ultrasound (FUS) in conjunction with microbubbles (MB) and recombinant adeno-associated virus serotype 9 (rAAV9) vectors for targeted gene delivery to neuronal cells in rats, optimizing gene expression conditions and assessing any adverse effects. Methods: The parameters for permeability enhancement of the rat's blood-brain barrier (BBB) were established using FUS+MB, with MRI scans and Evans Blue (EB) dye assisting in the evaluation. Rats underwent FUS-mediated transfection using rAAV9-Syn-EGFP vectors produced via a triple-transfection in HEK293T cells. Following this, the uptake and expression of GFP in targeted brain regions were evaluated using confocal fluorescence microscopy at various time intervals. Inflammatory responses post-FUS treatment were tracked by observing levels of GFAP, a marker for astrocytic activation, and TNF-α, a pro-inflammatory cytokine. Motor behavior effects post-intervention were gauged using the Rotarod test across multiple groups over a span of four weeks. Results: FUS+MB affected BBB permeability, with optimal results at 4 W for 200 s showing 85 % permeability and evident Gd-DTPA leakage. Settings beyond these resulted in tissue damage. Control groups exhibited a basal GFP expression of 2 % ± 0.5 %, whereas FUS+MB with rAAV-EGFP injections substantially increased GFP expression to about 67 % ± 6 % in targeted neurons. This GFP expression peaked at three weeks post-treatment and remained evident six months later. Following FUS treatment, both GFAP and TNF-α levels underwent fluctuations before eventually nearing their baseline values. The Rotarod test revealed no significant behavioral differences post-treatments among the groups. Conclusions: Combining FUS+MB with rAAV offers an innovative approach to enhance therapeutic delivery to the central nervous system (CNS) by transiently adjusting BBB permeability.

To solve the low power transfer efficiency and magnetic field leakage problems of cardiac pacemaker wireless powering, we proposed a wireless power supply system suitable for implanted cardiac pacemaker based on mu-negative (MNG) and mu-near-zero (MNZ) metamaterials. First, a hybrid metamaterial consisted of central MNG unit for magnetic field concentration and surrounding MNZ units for magnetic leakage shielding was established by theoretical calculation. Afterwards, the magnetic field distribution of wireless power supply system with MNG-MNZ metamaterial slab was acquired via finite element simulation and verified to be better than the distribution with conventional MNG slab deployed. Finally, an experimental platform of wireless power supply system was established with which power transfer experiment and system temperature rise experiment were conducted. Simulation and experimental results showed that the power transfer efficiency was improved from 44.44%, 19.42%, 8.63% and 6.19% to 55.77%, 62.39%, 20.81% and 14.52% at 9.6 mm, 20 mm, 30 mm and 50 mm, respectively. The maximum SAR acquired by SAR simulation under human body environment was -7.14 dbm and maximum reduction of the magnetic field strength around the receiving coil was 2.82 A/m. The maximum temperature rise during 30min charging test was 3.85°C, and the safety requirements of human bodies were met.

Abstract Background A temporal network of generalized anxiety disorder (GAD) symptoms could provide valuable understanding of the occurrence and maintenance of GAD. We aim to obtain an exploratory conceptualization of temporal GAD network and identify the central symptom. Methods A sample of participants (n = 115) with elevated GAD-7 scores (Generalized Anxiety Disorder 7-Item Questionnaire [GAD-7] ≥ 10) participated in an online daily diary study in which they reported their GAD symptoms based on DSM-5 diagnostic criteria (eight symptoms in total) for 50 consecutive days. We used a multilevel VAR model to obtain the temporal network. Results In temporal network, a lot of lagged relationships exist among GAD symptoms and these lagged relationships are all positive. All symptoms have autocorrelations and there are also some interesting feedback loops in temporal network. Sleep disturbance has the highest Out-strength centrality. Conclusions This study indicates how GAD symptoms interact with each other and strengthen themselves over time, and particularly highlights the relationships between sleep disturbance and other GAD symptoms. Sleep disturbance may play an important role in the dynamic development and maintenance process of GAD. The present study may develop the knowledge of the theoretical model, diagnosis, prevention and intervention of GAD from a temporal symptoms network perspective.

Abstract Exploring an active and cost-effective electrocatalyst alternative to carbon-supported platinum nanoparticles for alkaline hydrogen evolution reaction (HER) have remained elusive to date. Here, we report a catalyst based on platinum single atoms (SAs) doped into the hetero-interfaced Ru/RuO2 support (referred to as Pt-Ru/RuO2), which features a low HER overpotential, an excellent stability and a distinctly enhanced cost-based activity compared to commercial Pt/C and Ru/C in 1 M KOH. Advanced physico-chemical characterizations disclose that the sluggish water dissociation is accelerated by RuO2 while Pt SAs and the metallic Ru facilitate the subsequent H* combination. Theoretical calculations correlate with the experimental findings. Furthermore, Pt-Ru/RuO2 only requires 1.90 V to reach 1 A cm−2 and delivers a high price activity in the anion exchange membrane water electrolyzer, outperforming the benchmark Pt/C. This research offers a feasible guidance for developing the noble metal-based catalysts with high performance and low cost toward practical H2 production.

Urbanization is an important symbol of regional economic development and social progress. Studying the urbanization level is greatly important for the scientific development of towns and cities, and for the efficient decision-making of governments. The nighttime light data, which encompasses valuable insights into human activities, economic progress, and social development, effectively addresses the limitations associated with the indicator method in terms of uncertainty and lag issues. Those data can also provide a more intuitive reflection of the level of urbanization and offer novel insights for research on urbanization. In this study, based on the 2000–2020 EANTLI_Like nighttime light remote sensing data, the characteristics of the spatial and temporal dynamic changes in the land urbanization level in China were measured. Results were analyzed at four scales: national, regional, provincial, and municipal. Finally, the main economic indicators affecting urbanization were selected as variables to simply analyze the driving force of land urbanization through spatial autocorrelation and spatiotemporal geographically weighted regression model. Results indicated that China's land urbanization level continued to grow from 2000 to 2020, with an average annual growth rate of 2.51%. The spatial distribution of land urbanization varied significantly across regions. The level of land urbanization in the eastern coastal region was significantly higher than that in the inland and western provinces, at the agricultural and provincial scales. Hong Kong, Macao, and Shanghai ranked high in terms of land urbanization, and the Pearl River Delta and Yangtze River Delta regions in which they were located also belong to the cluster of high land urbanization levels. Meanwhile, the goodness of fit among GDP, the proportion of output of secondary and tertiary industries, freight volume, and land urbanization level were higher than 0.86. Among them, GDP and the output of secondary and tertiary industries had a more obvious role in promoting land urbanization. The freight volume exhibited positive effects on land urbanization level in the western region, Heilongjiang, and Jilin provinces. This study is very important for understanding the law of urban construction land expansion in China, the regional differences in land urbanization level, and the optimization of land use layout.

Abstract The study of walkability is of great significance to the construction of healthy cities. In this paper, taking 1283 articles of walkability, which were included in Web of Science, as the research object. This paper adopts to analysis the research progress by using the method of scientometrics and knowledge networks analysis. Objectively and systematically analyze the research progress of walkability abroad from the aspects of publication overview, knowledge foundation, research direction and hot spots, etc. It is found that foreign researches on walkability mainly include three core directions: walkability and physical activity, walkability evaluation, walkability and urban design. Among them, walkability and physical activity orientation have been studied from various perspectives, such as various groups, various environmental types, different behavioral patterns and various chronic diseases. With the increasingly prominent urbanization problems and the rapid development of new technologies, multiple data, new methods and interdisciplinary cooperation will actively promote the vigorous development of walking suitability research.

Abstract Ferroptosis, a novel form of cell death triggered by iron-dependent phospholipid peroxidation, presents significant therapeutic potential across diverse cancer types. Central to cellular metabolism, the metabolic pathways associated with ferroptosis are discernible in both cancerous and immune cells. This review begins by delving into the intricate reciprocal regulation of ferroptosis between cancer and immune cells. It subsequently details how factors within the tumor microenvironment (TME) such as nutrient scarcity, hypoxia, and cellular density modulate ferroptosis sensitivity. We conclude by offering a comprehensive examination of distinct immunophenotypes and environmental and metabolic targets geared towards enhancing ferroptosis responsiveness within the TME. In sum, tailoring precise ferroptosis interventions and combination strategies to suit the unique TME of specific cancers may herald improved patient outcomes.

Background Polycystic ovary syndrome (PCOS) is one of the most common endocrine and metabolic disorders in women of reproductive age. It is frequently comorbid with obesity and negative emotions. Currently, there are few reports on the relationship between obesity and negative emotions in patients with PCOS. Here we performed both basic and clinical studies to study the relationship between obesity and negative emotions in PCOS.Methods We performed a cross-sectional study including 608 patients with PCOS and 184 healthy participants to assess the mental health status of people with different body mass indices (BMI). Self-rated anxiety, depression, and perceived stress scales were used for subjective mood evaluations. Rat PCOS models fed 45 and 60% high-fat diets were used to confirm the results of the clinical study. Elevated plus maze and open field tests were used to assess anxiety- and depression-like behaviors in rats.Results We observed overweight/obesity, increased depression, anxiety, and perceived stress in women with PCOS, and found that anxiety and depression were negatively correlated with BMI in patients with severe obesity and PCOS. Similar results were confirmed in the animal study; the elevated plus maze test and open field test demonstrated that only 60% of high fat diet-induced obesity partly reversed anxiety- and depression-like behaviors in PCOS rats. A high-fat diet also modulated rat hypothalamic and hippocampal luteinizing hormone and testosterone levels.Conclusion These results reveal a potential relationship between obesity and negative emotions in PCOS and prompt further investigation. The interactions between various symptoms of PCOS may be targeted to improve the overall well-being of patients.

Background This study aims to investigate the incidence and prognosis of malignancy in individuals with thrombospondin type-1 domain-containing 7A (THSD7A)-associated membranous nephropathy (MN).Methods First, we performed a systematic literature review of prevalence of malignancy in THSD7A-associated MN. Then, we conducted a retrospective analysis of 454 patients diagnosed with MN through renal biopsy at our hospital between January 2016 and December 2020. We assessed the presence of serum anti-THSD7A antibodies and performed immunohistochemical staining of renal tissue for THSD7A. Subsequently, we followed patients with THSD7A-associated MN for a minimum of 3–5 years, collecting their clinical, pathological characteristics, and prognosis. Additionally, we conducted a literature review on patients with THSD7A-associated MN in conjunction with malignancy.Results We identified a total of nine articles containing comprehensive data on THSD7A-associated MN and malignancy. Among 235 patients with THSD7A-positive MN, 36 individuals had concurrent malignancies, resulting in a malignancy prevalence of 13.3% (95% CI: 8.9–17.7%). In our center, we followed up with 15 patients diagnosed with THSD7A-associated MN and observed three cases of concomitant tumors: two cases of lung adenocarcinoma and one case of small cell lung cancer with multiple metastases. The prevalence of malignancy in our cohort was 20%. Notably, we detected positive THSD7A staining in both renal and lung cancer tissues in one patient with small cell lung cancer.Conclusions Patients with THSD7A-associated MN should undergo vigilant follow-up assessments, with a particular focus on actively seeking potential tumorigenic lesions to prevent misdiagnosis or oversight.

Gliomas are typical malignant brain tumours affecting a wide population worldwide. Operation, as the common treatment for gliomas, is always accompanied by postoperative drug chemotherapy, but cannot cure patients. The main challenges are chemotherapeutic drugs have low blood-brain barrier passage rate and a lot of serious adverse effects, meanwhile, they have difficulty targeting glioma issues. Nowadays, the emergence of nanoparticles (NPs) drug delivery systems (NDDS) has provided a new promising approach for the treatment of gliomas owing to their excellent biodegradability, high stability, good biocompatibility, low toxicity, and minimal adverse effects. Herein, we reviewed the types and delivery mechanisms of NPs currently used in gliomas, including passive and active brain targeting drug delivery. In particular, we primarily focused on various hopeful types of NPs (such as liposome, chitosan, ferritin, graphene oxide, silica nanoparticle, nanogel, neutrophil, and adeno-associated virus), and discussed their advantages, disadvantages, and progress in preclinical trials. Moreover, we outlined the clinical trials of NPs applied in gliomas. According to this review, we provide an outlook of the prospects of NDDS for treating gliomas and summarise some methods that can enhance the targeting specificity and safety of NPs, like surface modification and conjugating ligands and peptides. Although there are still some limitations of these NPs, NDDS will offer the potential for curing glioma patients.

Buildings play a crucial role in geographic information systems, and advancements in the resolution of remote sensing imagery have facilitated their extraction on a larger scale. However, this progress has simultaneously heightened the requirements for methods to demonstrate efficiency and enhanced generalization performance. For this purpose, we propose a lightweight building semantic segmentation network, named CaSaFormer. Specifically, we propose an efficient module composed of Cross-attention and Self-attention Blocks connected in series (CaSa Block), to extract valuable semantic information from the feature pyramid. Furthermore, a novel Cross-Attention Gate Fusion (CAGF) module was developed to effectively integrate complementary components from global semantic features and local spatial features. Experiment results have demonstrated that our CaSaFormer outperforms state-of-the-art (SOTA) lightweight methods with best trade-off between accuracy and efficiency, showing a 1.92 % improvement in IoU and 16 % of the computation complexity. When compared to non-lightweight methods under equivalent computational resources, an impressive 1.69 % IoU gain is also achieved with only 1.7 % of the computation complexity. The code is available at: https://github.com/YpingHu/CaSaFormer.

In this paper, a novel study on the way inter-individual information interacts in meta-heuristic algorithms (MHAs) is carried out using a scheme known as population interaction networks (PIN). Specifically, three representative MHAs, including the differential evolutionary algorithm (DE), the particle swarm optimization algorithm (PSO), the gravitational search algorithm (GSA), and four classical variations of the gravitational search algorithm, are analyzed in terms of inter-individual information interactions and the differences in the performance of each of the algorithms on IEEE Congress on Evolutionary Computation 2017 benchmark functions. The cumulative distribution function (CDF) of the node degree obtained by the algorithm on the benchmark function is fitted to the seven distribution models by using PIN. The results show that among the seven compared algorithms, the more powerful DE is more skewed towards the Poisson distribution, and the weaker PSO, GSA, and GSA variants are more skewed towards the Logistic distribution. The more deviation from Logistic distribution GSA variants conform, the stronger their performance. From the point of view of the CDF, deviating from the Logistic distribution facilitates the improvement of the GSA. Our findings suggest that the population interaction network is a powerful tool for characterizing and comparing the performance of different MHAs in a more comprehensive and meaningful way.

IntroductionIn the era of the Internet, online digital traces have become a new way to study the online attention of scenic spots and tourists’ purchase behavior. The public’s information search on major search platforms is a series of manifestations of potential tourists’ attention and interest in scenic spots, but there are few studies on how attention, interest and information search affect potential tourists to generate real purchase behavior.MethodThis paper selects four dimensions of short video platform, travel website, search engine and social media to comprehensively measure the online attention of high-quality scenic spots in Yunnan Province, and then establishes a gray association analytic hierarchy process based on the relevant variables of the AISAS model to empirically analyze the primary and secondary factors affecting tourists’ purchase behavior.Results(1) From the perspective of the online attention of scenic spots on different platforms, the intensity of the public’s scenic spots online attention on the four types of media platforms is in the order of travel websites, search engines, short videos and social media (2) From the perspective of spatial distribution characteristics, the online attention of high-quality scenic spots in Yunnan Province is unevenly distributed, that is, there is a big difference between the attention of higher star scenic spots and their star rating and popularity, while the attention of low-star scenic spots is not much different from their star rating and popularity (3) From the perspective of spatial agglomeration characteristics, the comprehensive online attention of high-quality scenic spots in Yunnan Province presents the spatial agglomeration characteristics of “the multi-core linkage of high-density in the east and north, and sub-high-density in the south” (4) The factors influencing the purchase behavior of potential tourists are sharing experience, attracting attention, generating interest and searching information.DiscussionBy exploring the formation mechanism of high-quality scenic spots online attention in Yunnan Province and the mechanism of its spatial differentiation, this study not only enriches the logical chain of “tourism information source → potential tourists → demand driven → tourism information search → travel preference → destination selection → purchase decision → travel experience → real tourists → feelings after traveling → focus on feedback → tourism information source,” but also broadens the application scenarios and application boundaries of travel preference theory and AISAS behavior model to a certain extent.

Cardiac arrest is a leading cause of death globally. Only 25.8% of in-hospital and 33.5% of out-of-hospital individuals who achieve spontaneous circulation following cardiac arrest survive to leave the hospital. Respiratory failure and acute coronary syndrome are the two most common etiologies of cardiac arrest. Effort has been made to improve the outcomes of individuals resuscitated from cardiac arrest. Magnesium is an ion that is critical to the function of all cells and organs. It is often overlooked in everyday clinical practice. At present, there have only been a small number of reviews discussing the role of magnesium in cardiac arrest. In this review, for the first time, we provide a comprehensive overview of magnesium research in cardiac arrest focusing on the effects of magnesium on the occurrence and prognosis of cardiac arrest, as well as in the two main diseases causing cardiac arrest, respiratory failure and acute coronary syndrome. The current findings support the view that magnesium disorder is associated with increased risk of cardiac arrest as well as respiratory failure and acute coronary syndrome.

Cloud and shadow (CS) detection is crucial prerequisite for application of remote sensing images. Current deep learning-based detection algorithms mainly employ Convolutional Neural Networks (CNNs). However, the local receptive field in CNNs cannot effectively capture global contextual information, which hinders accurate characterization of the dependency between clouds and shadows. In vision Transformers, self-attention mechanisms can effectively capture the long-distance dependencies between different regions in an image. Inspired by this, this paper proposed a new CS Detection algorithm based on a Transformer, called CSDFormer. Specifically, we exclusively employed a hierarchical Transformer structure in the encoder stage to extract features of CS. Each Transformer layer contains several multi-head self-attention mechanisms for calculating pixel-wise long-distance connectivity. The designed structure enables the Transformer to better extract global context information, which helps to strengthen the comprehension of the semantic relationships between clouds and shadows. Benefiting from the global feature extraction capability of the encoder stage, we employed several simple multilayer perceptron layers for multi-scale feature map fusion and pixel classification in the decoder stage. The proposed CSDFormer was validated using 898 Landsat 8 Biome images with 512 × 512 pixels, producing an overall accuracy of 95.28 % and a mean intersection over union of 84.08 %, outperforming three state-of-the-art CNN-based algorithms. CSDFormer is consistently more accurate in detection of both clouds and shadows. Owing to the parallel computing capability of the self-attention mechanism, CSDFormer is computationally more efficient than the three CNN-based benchmark methods. For the input spectral bands, the performance of CSDFormer produced can be further enhanced with additional thermal infrared bands.

Abstract Upgrading ethanol to long-chain alcohols (LAS, C6+OH) offers an attractive and sustainable approach to carbon neutrality. Yet it remains a grand challenge to achieve efficient carbon chain propagation, particularly with noble metal-free catalysts in aqueous phase, toward LAS production. Here we report an unconventional but effective strategy for designing highly efficient catalysts for ethanol upgrading to LAS, in which Ni catalytic sites are controllably exposed on surface through sulfur modification. The optimal catalyst exhibits the performance well exceeding previous reports, achieving ultrahigh LAS selectivity (15.2% C6OH and 59.0% C8+OH) at nearly complete ethanol conversion (99.1%). Our in situ characterizations, together with theoretical simulation, reveal that the selectively exposed Ni sites which offer strong adsorption for aldehydes but are inert for side reactions can effectively stabilize and enrich aldehyde intermediates, dramatically improving direct-growth probability toward LAS production. This work opens a new paradigm for designing high-performance non-noble metal catalysts for upgrading aqueous EtOH to LAS.

Abstract Background Cigarette smoke (CS) is an important risk factor for chronic obstructive pulmonary disease, including emphysema. MicroRNAs (miRNAs) are important regulators of emphysema progression. However, miR‐23a‐3p role in emphysema is unclear. Methods CS exposure was used to construct emphysema mice models, and cigarette smoke extract (CSE)‐induced pulmonary vascular endothelial cells (PMVECs) were used to mimic emphysema cell models. Mouse lung tissue was stained by immunohistochemical staining, hematoxylin and eosin staining, and TUNEL staining. MiR‐23a‐3p and DnaJ homolog subfamily B member 1 (DNAJB1) levels were tested using quantitative real‐time PCR. DNAJB1 and apoptosis‐related markers' protein levels were examined via western blot analysis. Cell viability and apoptosis were analyzed by MTT assay and flow cytometry. The interaction between miR‐23a‐3p and DNAJB1 was evaluated by dual‐luciferase reporter assay and RIP assay. Results MiR‐23a‐3p was downregulated, and DNAJB1 was upregulated in CS‐induced emphysema mice models and CSE‐induced PMVECs. MiR‐23a‐3p overexpression promoted viability and repressed apoptosis in CSE‐induced PMVECs. MiR‐23a‐3p targeted DNAJB1 and negatively regulated DNAJB1 expression. Moreover, DNAJB1 knockdown repressed CSE‐induced PMVECs apoptosis, and miR‐23a‐3p inhibitor reversed this effect. Additionally, miR‐23a‐3p alleviated lung tissue injury and improved emphysema in mice by reducing DNAJB1 expression. Conclusion MiR‐23a‐3p alleviated emphysema progression, which could inhibit CSE‐induced PMVECs apoptosis by targeting DNAJB1.

ABSTRACTRemote sensing-based vegetation index (VI) data are significantly impacted by cloud contamination. Spatiotemporal reconstruction methods demonstrate higher accuracy than temporal reconstruction methods. However, the computing time and random access memory (RAM) consumption of these spatiotemporal reconstruction methods for large-scale reconstruction remains unclear. In this study, a method called spatial-interannual reconstruction (SIR) was proposed to reconstruct cloud-contaminated pixels in MODIS normalized difference VI (NDVI) and enhanced VI (EVI) data. SIR has four major advantages: (1) High accuracy. The average mean absolute error of SIR was 0.0338, which was 20.2% and 23.4% lower than that of two state-of-the-art spatiotemporal reconstruction methods (i.e. interpolation of the mean anomalies (IMA) and Gapfill). (2) High computing speed. The average computing time of SIR was 99.7% and 98.8% lower than IMA and Gapfill, respectively. (3) Low RAM consumption. (4) Simultaneous reconstruction of all invalid values. Reconstructed 250 m spatial resolution and 16-day composite NDVI and EVI datasets in China from 2000 to 2022 (written as ReVIChina) were developed based on the SIR method and MODIS MOD13Q1 data. Spatiotemporal analyses revealed that the reconstructed datasets were more reliable than the original product and a similar dataset.

Highlights The electrochemical principles/mechanism of Li–S batteries and origin of the shuttle effect have been discussed. The efficient strategies have been summarized to inhibit the shuttle effect. The recent advances of inhibition of shuttle effect in Li–S batteries for all components from anode to cathode.

Abstract Background Double-J (DJ) stent placement is an important procedure during laparoscopic pyeloplasty (LP). Failing to insert the DJ stent may indicate the patient was also complicated with uretero-vesical junction obstruction (UVJO), and surgeons have to change to another alternative drainage method. In the present study, we analyzed the risk factors of failure of DJ stent placement during the LP and reviewed the clinical outcomes of these challenging pyeloplasties. Methods We retrospectively analyzed the clinical data of patients with ureteropelvic junction obstruction (UPJO) who underwent LP in our department from January 2016 to September 2020. For patients who developed a difficult process of inserting the DJ stent, the externalized uretero-pyelostomy (EUP) stent was indwelled. Patients were finally divided into two groups: DJ group and EUP group. The primary outcomes were recurrent UPJO, postoperative uretero-vesical junction obstruction (UVJO) and complications. Results A total of 535 patients were included in the study, of which 37 patients (6.9%) failed to insert the DJ stent. Age was younger, and weight was lower (P 0.05). The incidence of postoperative UVJO in the EUP group was significantly higher than in the DJ group (10.8% vs. 0.2%, P

Vegetation plays a key role in trapping sediments and further controlling pollutants. However, few studies were conducted to clarify the erosion and deposition laws of sediments and the influence factors caused by vegetation patch properties, which is not conducive to the revelation of riverbank protection and erosion prevention. Therefore, this study investigated the change in scouring and deposition characteristics around submerged vegetation patches of nine kinds of typical configurations and their influencing factors. Vegetation patches were assembled from three vegetation densities (G/d = 0.83, 1.3, and 1.77, representing dense, medium, and sparse, respectively), and three vegetation patch thicknesses (dn = 170, 400, and 630, representing narrow, usual, and wide, respectively), to measure vegetation patch property influences. Flow velocity, scouring, and deposition characteristics under nine patches were determined by a hydraulic flume experiment, three-dimensional acoustic Doppler velocimetry (ADV), and three-dimensional laser scanner, and then ten geometry and morphology indices were measured and calculated based on the results of laser scanning. Results showed that both vegetation patch density and thickness were positively related to the turbulence kinetic energy (TKE) above the vegetation canopy, and only vegetation patch density was negatively related to the flow velocity above the vegetation canopy. The relation between the product of density and vegetation patch thickness and erosion area in planform (EA) showed a power function (R2 = 0.644). Both density and vegetation patch thickness determined the scouring degree, but deposition location and amount did not rely on each one simply. On average, medium density showed the smallest maximum erosion length (MEL), EA, deposition area in planform (DA), and average deposition length (ADL) and a minimum of the above parameters also occurred at narrow vegetation patch thickness. The shape factor of the erosion volume (SFEV), the shape factor of the deposition volume (SFDV), ADL, and MEL of medium density and narrow thickness vegetation patch (G/d = 1.3, dn = 170) were significantly smaller than that of other types of patches. DA and equivalent prismatic erosion depth on the erosion area (EPED) were significantly linearly related (R2 = 0.766). Consequently, most sediment was deposited close to the vegetation patch edge. It is suggested that vegetation patch thickness and density should be given to control sediment transport. In particular, natural vegetation growth changes vegetation patch density and then alters vegetation patch thickness. Management and repair need to be first considered. The results of this study shed light on riparian zone recovery and vegetation filter strip mechanism.

IntroductionWhen doctors’ work stress increases, their joy in work decreases, severely affecting the quality of care and threatening patient safety. Analysis of the latent categories of joy in work of doctors in public hospitals and the differences in the characteristics of each category can help uncover hidden messages that enhance doctors’ joy in work.MethodsQuestionnaires were administered to 426 doctors working in public hospitals using the general information questionnaire and the public hospital doctor’s joy in work evaluation scale. Upon identifying their potential categories using latent profile analysis, chi-square test, and multinomial logistic regression were performed to analyze the differences in the characteristics of each category.ResultsThe 426 public hospital doctors could be divided into three potential categories: “low joy in work” (11.27%), “medium joy in work” (59.86%), and “high joy in work” (28.87%). Most of the doctors did not have much joy in work, with 71.13% of them having “low to medium joy in work.” Doctors who work in secondary or tertiary hospitals, have a personnel agency or contract, and are older than 45 years are more likely to belong to the “low joy in work” category. Some of the protective factors are having an average monthly income (RMB) of 10,001–15,000 yuan and having a fair or good self-rated health status.ConclusionThere are obvious classification characteristics of doctors’ level of joy in work. Hospital managers can take commensurate actions to improve their joy in work, thereby improving patient safety and the quality of medical services.

The prevalence of cadmium (Cd) contamination has emerged as a significant global concern. Exposure to Cd during pregnancy is associated with adverse pregnancy outcomes, including miscarriage. However, there is currently a lack of comprehensive summaries on Cd-induced miscarriage. Therefore, it is imperative to further strengthen research into in vivo studies, clinical status, pathological mechanisms, and pharmacological interventions for Cd-induced miscarriage. This study systematically presents the current knowledge on animal models and clinical trials investigating Cd exposure-induced miscarriage. The underlying mechanisms involving oxidative stress, inflammation, endocrine disruption, and placental dysfunction caused by Cd-induced miscarriage are also extensively discussed. Additionally, potential drug interventions such as melatonin, vitamin C, and vitamin E are highlighted for their pharmacological role in mitigating adverse pregnancy outcomes induced by Cd.

Objective: This study aimed to explain the change of disc position at different over-corrected place after arthroscopic disc repositioning and suturing surgery. Study design: Patients treated with temporomandibular joint arthroscopic disc repositioning and suturing surgery were reviewed. All patients underwent magnetic resonance imaging (MRI) before, immediately after surgery and at 2-year follow-up. The position of disc was checked and the change was compared. Results: 133 patients were included in the final analysis with 203 TMJ sides. The incidence rate for anterior movement of the disc after surgery was 33.0 %. Disc repositioned between 12 and 1 o'clock showed smaller movement rate of 22.6 %, while higher movement rate of 53.6 % was seen when repositioned between 2 and 3 o'clock. Conclusions: After arthroscopic disc repositioning and suturing surgery for ADD patients, the repositioned disc showed tendency to move forward. 12 to 1 o'clock was optional disc site for repositioning while excessive over-correction was not recommended.

Abstract Cells constantly sense and respond to not only biochemical but also biomechanical changes in their microenvironment, demanding for dynamic metabolic adaptation. ECM stiffening is a hallmark of cancer aggressiveness, while survival under substrate detachment also associates with poor prognosis. Mechanisms underlying this, non‐linear mechano‐response of tumor cells may reveal potential double‐hit targets for cancers. Here, an integrin‐GSK3β‐FTO‐mTOR axis is reported, that can integrate stiffness sensing to ensure both the growth advantage endowed by rigid substrate and cell death resistance under matrix detachment. It is demonstrated that substrate stiffening can activate mTORC1 and elevate mTOR level through integrins and GSK3β‐FTO mediated mRNA m6A modification, promoting anabolic metabolism. Inhibition of this axis upon ECM detachment enhances autophagy, which in turn conveys resilience of tumor cells to anoikis, as it is demonstrated in human breast ductal carcinoma in situ (DCIS) and mice malignant ascites. Collectively, these results highlight the biphasic mechano‐regulation of cellular metabolism, with implications in tumor growth under stiffened conditions such as fibrosis, as well as in anoikis‐resistance during cancer metastasis.

Objectives: This retrospective cohort study aimed to analyze volumes of craniomaxillofacial bone and masticatory muscles of young adults with bilateral idiopathic condylar resorption. Methods: This was a retrospective cohort study of 84 adults with bilateral idiopathic condylar resorption (BCR) and 48 adults with normal temporal-mandibular joint (TMJ) matched for age and sex (mean age, 23.2 ± 3.6 years). The volumes of craniomaxillofacial bone and masticatory muscles, as well as intercondylar angle were measured. Unpaired t-tests and Pearson correlation tests were applied to analyze the data. Multivariable linear regression models were used to estimate the association between bilateral condylar volume and volumes of craniomaxillofacial bone and masticatory muscles adjusted for age, sex, and disc status. Results: Compared to the control group, the BCR group displayed significant decreased volumes of craniomaxillofacial bone (p

PurposeThis study endeavors to investigate ways to optimize the role of teachers in undergraduate dental basic research education (UDBRE) with the aim of nurturing the research potential of undergraduate students.MethodsWe conducted a cross-sectional study among medical undergraduates enrolled at the School of Stomatology, Guangzhou Medical University. Descriptive statistics were employed to comprehensively analyze UDBRE’s fundamental aspects. Kendall rank correlation analysis was performed to evaluate the relationship between the quality of feedback provided by tutors to undergraduates and the students’ scientific research abilities. Additionally, multivariate logistic regression analysis was employed to uncover the factors influencing the effectiveness of UDBRE.ResultsA total of 168 medical students were surveyed with a valid response rate of 93.85%. The effectiveness of UDBRE was demonstrated by undergraduates’ self-rated research abilities, active participation in scientific research projects, and a certain amount of academic outputs. Significant and positive correlations (𝓣b> 0.5, p

IntroductionThe gastrointestinal tract and oral cavity of animal species harbor complex microbial communities, the composition of which is indicative of the behavior, co-evolution, diet, and immune system of the host.MethodsThis study investigated the microbial composition in snakes from varying altitudinal ranges by assessing the fecal and oral bacterial communities in Protobothrops mucrosquamatus, Elaphe dione, and Gloydius angusticeps from Sichuan Province, China, using metagenomic sequencing.Results and discussionIt was revealed that Bacteroidetes, Proteobacteria, Firmicutes, and Fusobacteria were the core microbial phyla in fecal samples across all three species, while Proteobacteria, Bacteroidetes, Actinobacteria, and Firmicutes were the core microbial phyla in oral samples across all three species. Notably, the dominance of Armatimonadetes was documented for the first time in the feces of all three species. Comparative analysis of the microbiomes of the three species indicated distinct microbiological profiles between snakes living at low- and high-altitude regions. Furthermore, 12 to 17 and 22 to 31 bacterial pathogens were detected in the oral and fecal samples, respectively, suggesting that snakes may serve as a novel reservoir for emerging diseases. Overall, this study provides a comparative analysis of the fecal and oral microbiomes in three snake species. Future investigations are anticipated to further elucidate the influence of age, genetics, behavior, diet, environment, ecology, and evolution on the gut and oral microbial communities of snakes.

The last decades have witnessed a rapid development of noninvasive plant phenotyping, capable of detecting plant stress scale levels from the subcellular to the whole population scale. However, even with such a broad range, most phenotyping objects are often just concerned with leaves. This review offers a unique perspective of noninvasive plant stress phenotyping from a multi-organ view. First, plant sensing and responding to abiotic stress from the diverse vegetative organs (leaves, stems, and roots) and the interplays between these vital components are analyzed. Then, the corresponding noninvasive optical phenotyping techniques are also provided, which can prompt the practical implementation of appropriate noninvasive phenotyping techniques for each organ. Furthermore, we explore methods for analyzing compound stress situations, as field conditions frequently encompass multiple abiotic stressors. Thus, our work goes beyond the conventional approach of focusing solely on individual plant organs. The novel insights of the multi-organ, noninvasive phenotyping study provide a reference for testing hypotheses concerning the intricate dynamics of plant stress responses, as well as the potential interactive effects among various stressors.

Setaria italica (S. italica, Linnaeus, 1753) is a drought-resistant, barren-tolerant, and widely adapted C-4 crop that plays a vital role in maintaining agricultural and economic stability in arid and barren regions of the world. However, the potential habitat of S. italica under current and future climate scenarios remains to be explored. Predicting the potential global geographic distribution of S. italica and clarifying its ecological requirements can help promote sustainable agriculture, which is crucial for addressing the global food crisis. In this study, we predicted the potential global geographic distribution of S. italica based on 3,154 global distribution records using the Maxent model and ArcGIS software. We assessed the constraints on its potential distribution based on the contribution of environmental factors variables. The predictive accuracy of the Maxent model was evaluated using AUC values, TSS values, and Kappa statistics, respectively. The results showed that the Maxent model had a high prediction accuracy, and the simulation results were also reliable; the total suitable habitats of S. italica is 5.54×107 km2, which mainly included the United States (North America), Brazil (South America), Australia (Oceania), China, India (Asia), and the Russian Federation (Europe). The most suitable habitat of S. italica was 0.52×107 km2, accounting for 9.44% of the total areas, mainly in the United States, India, the Russian Federation, and China. Soil and precipitation (driest monthly precipitation, hottest seasonal precipitation) are the most critical factors limiting the potential distribution of S. italica. Compared with the modern potential distribution, we predict that the four future climate change scenarios will result in varying reductions in the possible geographic ranges of S. italica. Overall, climate change may significantly affect the global distribution of S. italica, altering its worldwide production and trade patterns.

Aiming at the problem that the traditional path planning algorithm does not have real-time planning performance in the dynamic and complex power equipment maintenance environment, or it is challenging to avoid dynamic obstacle obstacles due to poor real-time version, this paper proposes an artificial potential field method for real-time planning. The characteristics of dynamic obstacle in a dynamic complex environment, the dynamic obstacles are simplified as moving particles, and the repulsion function of the dynamic obstacles is added to avoid the collision. Within the influence range of dynamic obstacles in a busy complex environment, the robot avoids the dynamic obstacles through real-time local path planning under the influence of the repulsive force of the dynamic obstacle to reach the target point. At the same time, aiming at the problems of unevenness and fluctuation of the path generated by the traditional artificial potential field method, the non-uniform rational B-spline and moving average filtering algorithm are used to improve the local path planning algorithm of the conventional artificial potential field, and the generated path is smoother and smoother than the traditional algorithm.

Models for maturity discrimination and polyphenol content determination of Aronia melanocarpa (AM) were established to nondestructively determinethe maturityand polyphenol content of AM based on the hyperspectral imaging (HSI) technology. The HSI technology was adopted to collect the image information of Fukangyuan No. 1 AM in different maturity levels, and the Folin-Ciocalteu colorimetric method was employed to determine the polyphenol content. The Monte Carlo method was used to eliminate the outliers. The original image information was preprocessed with the following procedures: Moving average, median filter, normalize, baseline calibration, multiple scattering correction, detrending, and standard normal variate. Meanwhile, the sample set partitioning based on joint x-y distance method was applied to divide the samples. The competitive adaptive reweighting sampling and uninformative variable elimination method were selected to extract the feature wavelengths, based on which the partial least squares model (PLS) and support vector machine (SVM) model were established and compared. The results showed that the UVE-SVM model after multiple scattering correction showed the best performance among all established discriminant models, with the comprehensive recognition rate of 94.62%, Rc2 of 0.9712, and accuracy of 100%. The CARS-SVM model after median filter exhibited the best efficiency in detection of polyphenol content, with the Rc2 of 0.8331. In addition, this work proved that the polyphenol content in AM was visual. This work provided a theoretical basis for the application of HSI technology in berry industry.

Abstract. Background:. The HELIOS stent is a sirolimus-eluting stent with a biodegradable polymer and titanium oxide film as the tie-layer. The study aimed to evaluate the safety and efficacy of HELIOS stent in a real-world setting. Methods:. The HELIOS registry is a prospective, multicenter, cohort study conducted at 38 centers across China between November 2018 and December 2019. A total of 3060 consecutive patients were enrolled after application of minimal inclusion and exclusion criteria. The primary endpoint was target lesion failure (TLF), defined as a composite of cardiac death, non-fatal target vessel myocardial infarction (MI), and clinically indicated target lesion revascularization (TLR) at 1-year follow-up. Kaplan–Meier methods were used to estimate the cumulative incidence of clinical events and construct survival curves. Results:. A total of 2998 (98.0%) patients completed the 1-year follow-up. The 1-year incidence of TLF was 3.10% (94/2998, 95% closed interval: 2.54–3.78%). The rates of cardiac death, non-fatal target vessel MI and clinically indicated TLR were 2.33% (70/2998), 0.20% (6/2998), and 0.70% (21/2998), respectively. The rate of stent thrombosis was 0.33% (10/2998). Age ≥60 years, diabetes mellitus, family history of coronary artery disease, acute myocardial infarction at admission, and device success were independent predictors of TLF at 1 year. Conclusion:. The 1-year incidence rates of TLF and stent thrombosis were 3.10% and 0.33%, respectively, in patients treated with HELIOS stents. Our results provide clinical evidence for interventional cardiologists and policymakers to evaluate HELIOS stent. Clinical trial registration:. ClinicalTrials.gov, NCT03916432

Abstract Alternative splicing is an important mechanism that enhances protein functional diversity. To date, our understanding of alternative splicing variants has been based on mRNA transcript data, but due to the difficulty in predicting protein structures, protein tertiary structures have been largely unexplored. However, with the release of AlphaFold, which predicts three-dimensional models of proteins, this challenge is rapidly being overcome. Here, we present a dataset of 315 predicted structures of abnormal isoforms in 18 uveal melanoma patients based on second- and third-generation transcriptome-sequencing data. This information comprises a high-quality set of structural data on recurrent aberrant isoforms that can be used in multiple types of studies, from those aimed at revealing potential therapeutic targets to those aimed at recognizing of cancer neoantigens at the atomic level.

Abstract Background Cancers aggressively reorganize collagen in their microenvironment, leading to the evasion of tumor cells from immune surveillance. However, the biological significance and molecular mechanism of collagen alignment in breast cancer (BC) have not been well established. Methods In this study, BC-related RNA-Seq data were obtained from the TCGA database to analyze the correlation between DDR1 and immune cells. Mouse BC cells EO771 were selected for in vitro validation, and dual-luciferase experiments were conducted to examine the effect of TFAP2A on DDR1 promoter transcription activity. ChIP experiments were performed to assess TFAP2A enrichment on the DDR1 promoter, while Me-RIP experiments were conducted to detect TFAP2A mRNA m6A modification levels, and PAR-CLIP experiments were conducted to determine VIRMA’s binding to TFAP2A mRNA and RIP experiments to investigate HNRNPC’s recognition of m6A modification on TFAP2A mRNA. Additionally, an in vivo mouse BC transplant model and the micro-physiological system was constructed for validation, and Masson staining was used to assess collagen fiber arrangement. Immunohistochemistry was conducted to identify the number of CD8-positive cells in mouse BC tumors and Collagen IV content in ECM, while CD8 + T cell migration experiments were performed to measure CD8 + T cell migration. Results Bioinformatics analysis showed that DDR1 was highly expressed in BC and negatively correlated with the proportion of anti-tumor immune cell infiltration. In vitro cell experiments indicated that VIRMA, HNRNPC, TFAP2A, and DDR1 were highly expressed in BC cells. In addition, HNRNPC promoted TFAP2A expression and, therefore, DDR1 transcription by recognizing the m6A modification of TFAP2A mRNA by VIRMA. In vivo animal experiments further confirmed that VIRMA and HNRNPC enhanced the TFAP2A/DDR1 axis, promoting collagen fiber alignment, reducing anti-tumor immune cell infiltration, and promoting immune escape in BC. Conclusion This study demonstrated that HNRNPC promoted DDR1 transcription by recognizing VIRMA-unveiled m6A modification of TFAP2A mRNA, which enhanced collagen fiber alignment and ultimately resulted in the reduction of anti-tumor immune cell infiltration and promotion of immune escape in BC.

Abstract Background It is believed that negative postoperative behavioral changes (NPOBC) is associated with negative perioperative outcomes in children. The importance of development of a predictive model of NPOBC was noted. This study aims to identify potential risk factors develop a nomogram to predict NPOBC on postoperative day 3 based on a prospective cohort. Methods A prospective observational study was conducted on children(American Society of Anesthesiologists I ~ III) aged 2 ~ 12 years who underwent selective surgery under general anesthesia between September 2022 and February 2023. The patient’s clinical data were analyzed. The method of measuring NPOBC is with the The Posthospital Behaviour Questionnaire (PHBQ), and all of children remained hospitalized at the time of assessment. The enrolled patients were categorized into the NPOBC group and the non-NPOBC group according to if children developed NPOBC on postoperative day 3. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors and develop the nomogram to predict NPOBC. Internal validation was performed using the parametric bootstrapping method. Results One hundred ninety-two patients were enrolled in the study, 44.8% (86/192 patients) of children developed NPOBC on postoperative day 3. Univariate and multivariate logistic regression analysis demonstrated that the Pediatric Anesthesia Behavior (PAB) score (OR: 1.23, 95%CI: 1.14–1.33), cerebral desaturation (OR: 1.16, 95%CI: 1.02–1.32), and postoperative pain score (OR: 1.07, 95%CI: 1.02–1.13) were independent predictors for NPOBC on postoperative day 3 (P

Abstract Infectious preterm birth (PTB) is one of the most important causes of perinatal death. It is difficult to find reliable biomarkers accurate to gestational weeks for infectious PTB prediction clinically. Infectious PTB is found usually accompanied with immune imbalance. Thus, the systematic study to find the priority of inflammatory biomarkers and innovative inflammatory clusters for infectious PTB prediction is urgently needed. This systematic study that focused on the inflammatory clusters and infectious PTB in the PubMed database was analyzed by using the criteria of the Population, Intervention, Comparison, Outcome, and Study design (PICOS) framework according to the recommendations of preferred reporting items for systematic reviews and meta-analysis (PRISMA). The network meta-analyzed results showed that the prioritization of the inflammatory factors for infectious PTB prediction is soluble tumor necrosis factor receptor 2 (sTNFR2) > tumor necrosis factor α (TNFα) > interleukin-10 (IL-10) > interleukin-6 (IL-6) > C-reactive protein (CRP) > interleukin-1β (IL-1β). Furthermore, the results also indicated that global consideration of multiple inflammatory factors, such as CRP/IL-1β/IL-6 biomarker cluster in gestational 27–34 weeks, and the tumor necrosis factor/nerve growth factor (TNF/NGF) family during gestational 25–33 weeks, were potential biomarker clusters that specific for infectious PTB prediction. This study systematically pointed out prioritization of the inflammatory factors for infectious PTB prediction. The results also provided evidence that maternal inflammatory clusters can predict infectious PTB occurrence at accurate gestational week. The global consideration of multiple inflammatory factors at accurate gestational age is highlighted.