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Abstract Colorectal cancer (CRC) is a prevalent malignant tumor of the gastrointestinal system, with the third and second highest incidence and mortality rates globally in 2020, respectively. Immunotherapy has developed rapidly in recent years. Natural killer (NK) cells have received increasing attention in the field of tumor immunotherapy due to their recognition and killing tumor cells without the limitations of major histocompatibility complexes. However, constraints within the tumor microenvironment that impede the infiltration and proliferation of NK cells result in poor efficacy of NK cell therapy for solid tumors. Oncolytic viral therapy is an immunogenic treatment with the potential to enhance anti-tumour immune responses and promote immune cell infiltration. In this study, we synergistically combine NK cells with an oncolytic adenovirus carrying Decorin (rAd.DCN) for the treatment of colorectal cancer (CRC) in a xenograft mouse model. By using Flow cytometry, real-time quantitative PCR and Calcein-AM release assay, we found that rAd.DCN could effectively promote proliferation, activation and degranulation of NK cells, up-regulate expression and secretion of NK cell killing activity-related factors, and enhance their killing activity. The efficacy is better than that of the blank control oncolytic virus rAd.Null. Combined treatment significantly inhibited tumor growth, increased the number of NK cells in peripheral blood, promoted the killing function of NK cells, and increased the expression levels of perforin and IFN-γ. At the same time, more NK cells were recruited to infiltrate tumor tissue. Our study established the feasibility of combination NK cells and oncolytic adenovirus application, thus expanding the scope of potentially curative treatments for NK cells in CRC.

[Introduction] With the proposal of the "carbon peaking and carbon neutrality" and the increasing scale of the carbon market, how to manage carbon assets and realize the preservation and appreciation of carbon assets has become an important issue facing the green and low-carbon development of large-scale energy enterprises. This paper summarizes and analyzes the situation faced by large-scale energy enterprises, the status quo of management mode and the construction method of management system, and puts forward relevant suggestions for large-scale energy enterprises in China on carbon asset management.[Method] This paper first analyzed the situation faced by energy enterprises under the background of the start of the national carbon market and the upcoming restart of the national certified voluntary emission reduction CCER, and then analyzed the cost difference between the current unified management mode and the decentralized management mode of enterprise carbon assets, and then put forward the principle of "four unification" of carbon asset management, the three-level system of "enterprise headquarters-carbon asset management company-control enterprise", and the five principles of "transaction risk control", an ecological chain of carbon asset management business was constructed by building a unified carbon asset information management platform for large energy enterprises, gradually deepening the three major business segments of data management and development, low-carbon analysis and consulting, market transactions and carbon finance.[Results] Through the analysis of the current situation, development status and policy requirements of energy enterprises, the optimization method of carbon asset management system and the future business development direction are clarified. [Conclusion] This paper summarizes the carbon asset management system and business structure of large energy enterprises under the background of carbon peaking and carbon neutrality. At present, there are still a series of problems brought by decentralized management in the management mode. It is necessary to gradually optimize the management from the top-level management, organization and implementation, capital guarantee, risk control management, talent guarantee, incentive assessment and other ways, so as to maximize the preservation and appreciation of carbon assets, and help the local region and even the whole country to carry out the "carbon peaking and carbon neutrality" work smoothly.

Abstract Alzheimer’s disease (AD), characterized by cognitive decline, is increasingly recognized as a disorder marked by synaptic loss and dysfunction. Despite this understanding, the underlying pathophysiological mechanisms contributing to synaptic impairment remain largely unknown. In this study, we elucidate a previously undiscovered signaling pathway wherein the S-nitrosylation of the Cdk5 activator p39, a post-translational modification involving the addition of nitric oxide to protein cysteine residues, plays a crucial role in synaptic dysfunction associated with AD. Our investigation reveals heightened p39 S-nitrosylation in the brain of an amyloid precursor protein (APP)/presenilin 1 (PS1) transgenic mouse model of AD. Additionally, soluble amyloid-β oligomers (Aβ), implicated in synaptic loss in AD, induce p39 S-nitrosylation in cultured neurons. Notably, we uncover that p39 protein level is regulated by S-nitrosylation, with nitric oxide S-nitrosylating p39 at Cys265 and subsequently promoting its degradation. Furthermore, our study demonstrates that S-nitrosylation of p39 at Cys265 significantly contributes to amyloid-β (Aβ) peptide-induced dendrite retraction and spine loss. Collectively, our findings highlight S-nitrosylation of p39 as a novel aberrant redox protein modification involved in the pathogenesis of AD, suggesting its potential as a therapeutic target for the disease.

Electroencephalography (EEG) signals are crucial for investigating brain function and cognitive processes. This study aims to address the challenges of efficiently recording and analyzing high-dimensional EEG signals while listening to music to recognize emotional states. We propose a method combining Bidirectional Long Short-Term Memory (Bi-LSTM) networks with attention mechanisms for EEG signal processing. Using wearable EEG devices, we collected brain activity data from participants listening to music. The data was preprocessed, segmented, and Differential Entropy (DE) features were extracted. We then constructed and trained a Bi-LSTM model to enhance key feature extraction and improve emotion recognition accuracy. Experiments were conducted on the SEED and DEAP datasets. The Bi-LSTM-AttGW model achieved 98.28% accuracy on the SEED dataset and 92.46% on the DEAP dataset in multi-class emotion recognition tasks, significantly outperforming traditional models such as SVM and EEG-Net. This study demonstrates the effectiveness of combining Bi-LSTM with attention mechanisms, providing robust technical support for applications in brain–computer interfaces (BCI) and affective computing. Future work will focus on improving device design, incorporating multimodal data, and further enhancing emotion recognition accuracy, aiming to achieve practical applications in real-world scenarios.

Cassia Semen, derived from the dried ripe seeds of leguminous plant Cassia obtusifolia Linn. or Cassia. tora Linn., exhibits a variety of pharmacological effects such as clearing heat to brighten the eyes, lubricating the intestine to relieve constipation, lowering blood pressure and lipids, hepatoprotection and anti-diabetes, etc. And due to its homology of medicine and food, it has broad development prospects in the fields of medicine and food. Based on the summary and analysis of the published literatures, this paper systematically reviews the integrated research progress of Cassiae Semen in recent years from the aspects of bioactive ingredients, pharmacological effects, toxicity and its applications in the food field. Additionally, the emerging challenges and possible development directions for the study of Cassiae Semen are discussed as well. In future research on Cassiae Semen, more attention should be paid to the pharmacological effects of naphthopyranones and polysaccharides and their mechanisms underlying improving eye diseases. Meanwhile, it is essential to focus on strengthening the researches on the pharmacokinetics of Cassiae Semen and the safety evaluation of its related functional foods. This article provides new basic information for further research, development, and utilization of Cassiae Semen.

To investigate the effects of nitrogen source nutrients on the growth and metabolism of Lactobacillus rhamnosus GG (LGG), this study used soybean protein isolates (dSPI) and soybean peptides (dPEP) from simulated gastrointestinal digestion as raw materials. The number of viable cells and the production of lactic acid and acetic acid in LGG were measured through mono-culture. LGG was co-cultured with Listeria monocytogenes to determine its utilization of soybean protein isolates and soybean peptides in the presence of pathogens. The results of mono-culture showed that both dPEP and dSPI could increase the viable number of LGG (P

Abstract Rhizome rot is a destructive soil-borne disease of Polygonatum kingianum and adversely affects the yield and sustenance of the plant. Understanding how the causal fungus Fusarium oxysporum infects P. kingianum may suggest effective control measures against rhizome rot. In germinating conidia of infectious F. oxysporum, expression of the zinc finger transcription factor gene Zfp1, consisting of two C2H2 motifs, was up-regulated. To characterize the critical role of ZFP1, we generated independent deletion mutants (zfp1) and complemented one mutant with a transgenic copy of ZFP1 (zfp1 tZFP1). Mycelial growth and conidial production of zfp1 were slower than those of wild type (ZFP1) and zfp1 tZFP1. Additionally, a reduced inhibition of growth suggested zfp1 was less sensitive to conditions promoting cell wall and osmotic stresses than ZFP1 and zfp1 tZFP1. Furthermore pathogenicity tests suggested a critical role for growth of zfp1 in infected leaves and rhizomes of P. kingianum. Thus ZFP1 is important for mycelial growth, conidiation, osmoregulation, and pathogenicity in P. kingianum.

Long-term mapping of winter wheat is vital for assessing food security and formulating agricultural policies. Landsat data are the only available source for long-term winter wheat mapping in the North China Plain due to the fragmented landscape in this area. Although various methods, such as index-based methods, curve similarity-based methods and machine learning-based methods, have been developed for winter wheat mapping based on remote sensing, the former two often require satellite data with high temporal resolution, which are unsuitable for Landsat data with sparse time-series. Machine learning is an effective method for crop classification using Landsat data. Yet, applying machine learning for winter wheat mapping in the North China Plain encounters two main issues: 1) the lack of adequate and accurate samples for classifier training; and 2) the difficulty of training a single classifier to accomplish the large-scale crop mapping due to the high spatial heterogeneity in this area. To address these two issues, we first designed a sample selection rule to build a large sample set based on several existing crop maps derived from recent Sentinel data, with specific consideration of the confusion error between winter wheat and winter rapeseed in the available crop maps. Then, we developed an optimal zoning method based on the quadtree region splitting algorithm with classification feature consistency criterion, which divided the study area into six subzones with uniform classification features. For each subzone, a specific random forest classifier was trained and used to generate annual winter wheat maps from 2013 to 2022 using Landsat 8 OLI data. Field sample validation confirmed the high accuracy of the produced maps, with an average overall accuracy of 91.1% and an average kappa coefficient of 0.810 across different years. The derived winter wheat area also has a good correlation (R2 = 0.949) with census area at the provincial level. The results underscore the reliability of the produced annual winter wheat maps. Additional experiments demonstrate that our proposed optimal zoning method outperforms other zoning methods, including Köppen climate zoning, wheat planting zoning and non-zoning methods, in enhancing wheat mapping accuracy. It indicates that the proposed zoning is capable of generating more reasonable subzones for large-scale crop mapping.

Prosthetic eye is indispensable as filler after enucleation in patients with anophthalmia, whereas there are still many complications including postoperative infection and eye socket depression or extrusion during the conventional artificial eye material applications. Some Ca-silicate biomaterials showed superior bioactivity but their biological stability in vivo limit the biomedical application as long-term or permanent implants. Herein we aimed to understand the physicochemical and potential biological responses of zinc doping in wollastonite bioceramic used for orbital implants. The wollastonite powders with different zinc dopant contents (CSi-Znx) could be fabricated as porous implants with strut or curve surface pore geometries (cubic, IWP) via ceramic stereolithography. The experimental results indicated that, by increasing zinc-substituting-Ca ratio (up to 9%), the sintering and mechanical properties could be significantly enhanced, and meanwhile the bio-dissolution in vitro and biodegradability in vivo were thoroughly inhibited. In particular, an appreciable angiogenic activity and expected antibacterial efficacy (over 90 %) were synergistically achieved at 9 mol% Zn dopant. In the back-embedding and enucleation and implantation model experiments in rabbits, the superior continuous angiogenesis was corroborated from the 2D/3D fibrovascular reconstruction in the IWP-pore CSi–Zn9 and CSi–Zn13.5 groups within very short time stages. Totally, the present silicate-based bioceramic via selective Zn doping could produce outstanding structural stability and bifunctional biological responses which is especially valuable for developing the next-generation implants with vascular insertion and fixation in orbital reconstruction prothesis.

Immunotherapy has changed the treatment landscape of advanced non-small cell lung cancer (NSCLC), showing great potential in the treatment of untreated and relapsed or refractory (R/R) patients. However, numerous issues that need further exploration remain with the wide application of immunotherapy. They include the exploration of biomarkers for efficacy prediction, the optimization of immunotherapy modalities, immune-related adverse effects, and the management of special populations. This review summarizes the progress of the research on immunotherapy for advanced NSCLC and discusses its challenges and future directions.

Abstract As a highly salt-resistant mangrove, Avicennia marina can thrive in the hypersaline water. The leaves of Avicennia marina play a crucial role in salinity stress adaptability by secreting salt. Although the functions of long non-coding RNAs (lncRNAs) in leaves remain unknown, they have emerged as regulators in leaf development, aging and salt response. In this study, we employed transcriptomic data of both short-term and long-term salt treated leaves to identify salt-associated lncRNAs of leaf tissue. As a result, 687 short-term and 797 long-term salt-associated lncRNAs were identified. Notably, both short-term and long-term salt-associated lncRNAs exhibited slightly longer lengths and larger exons, but smaller introns compared with salt-non-associated lncRNAs. Furthermore, salt-associated lncRNAs also displayed higher tissue-specificity than salt-non-associated lncRNAs. Most of the salt-associated lncRNAs were common to short- and long-term salt treatments. And about one fifth of the downregulated salt-associated lncRNAs identified both in two terms were leaf tissue-specific lncRNAs. Besides, these leaf-specific lncRNAs were found to be involved in the oxidation–reduction and photosynthesis processes, as well as several metabolic processes, suggesting the noticeable functions of salt-associated lncRNAs in regulating salt responses of Avicennia marina leaves.

Abstract Brain metastases (BM) are common in patients with epidermal growth factor receptor (EGFR)‐mutant non‐small cell lung cancer (NSCLC) and confer poor prognoses. Zorifertinib (AZD3759), an EGFR‐tyrosine kinase inhibitor (TKI) with high blood‐brain barrier penetration, has previously demonstrated promising systemic and intracranial antitumor activity in phase 1–3 studies. This is the first report of a patient with EGFR‐mutant (exon 21 L858R) NSCLC and symptomatic untreated multiple BM who achieved a long overall survival (OS) of more than 65 months after sequential treatment with zorifertinib and a third‐generation EGFR‐TKI. This new treatment paradigm offers a new treatment option and deserves further clinical exploration to prolong OS of patients with EGFR‐mutant NSCLC and untreated multiple BM.

Introduction Micropapillary serous borderline ovarian tumours (MP-SBOTs) are an aggressive subtype of serous borderline ovarian tumours (SBOTs). Surgery is the mainstay of treatment. Radical surgery (RS, including debulking) is an alternative. However, for patients who are of reproductive age, another treatment option is fertility-sparing surgery (FSS). Up to now, the best surgical approach for MP-SBOTs and whether different procedures will have an impact on postoperative recurrence are still up for debate. This protocol outlines a systematic review and meta-analysis to investigate whether FSS adversely affected outcomes compared with RS in patients with MP-SBOTs. Additionally, we will do a prognosis analysis of BOTs with no microcapillary pattern and MP-SOBTs, if possible.Methods and analysis This protocol will consider non-randomised studies comparing outcomes in patients with MP-SBOTs treated with RS or FSS. The following databases will be searched: Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, MEDLINE, Embase Medline, PubMed, Web of Science, China Biological Medicine Database, China National Knowledge Infrastructure and Wan Fang database. We will try our best to search the grey literature to avoid missing crucial research. Data collection and extraction will be performed according to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines. Risk of Bias in Non-randomised Studies of intervention will be used to assess non-randomized studies. We will assess the certainty of the evidence using the GRADEpro methodology and describe the degree of certainty of our results using suggested wording based on the GRADEpro assessment. We will conduct a meta-analysis and offer summary statistics for each result if there is enough data available. Instead, we will report the findings narratively where the data do not permit a statistical assessment.Ethics and dissemination Ethics approval was not required for this study. Results will be published through a peer-reviewed publication and communicated at scientific events once complete.PROSPERO registration number CRD42023439136.

Stroke ranks as the second most significant contributor to mortality worldwide and is a major factor in disability. Ischemic strokes account for 71% of all stroke incidences globally. The foremost approach to treating ischemic stroke prioritizes quick reperfusion, involving methods such as intravenous thrombolysis and endovascular thrombectomy. These techniques can reduce disability but necessitate immediate intervention. After cerebral ischemia, inflammation rapidly arises in the vascular system, producing pro-inflammatory signals that activate immune cells, which in turn worsen neuronal injury. Following reperfusion, an overload of intracellular iron triggers the Fenton reaction, resulting in an excess of free radicals that cause lipid peroxidation and damage to cellular membranes, ultimately leading to ferroptosis. The relationship between inflammation and ferroptosis is increasingly recognized as vital in the process of cerebral ischemia-reperfusion (I/R). Inflammatory processes disturb iron balance and encourage lipid peroxidation (LPO) through neuroglial cells, while also reducing the activity of antioxidant systems, contributing to ferroptosis. Furthermore, the lipid peroxidation products generated during ferroptosis, along with damage-associated molecular patterns (DAMPs) released from ruptured cell membranes, can incite inflammation. Given the complex relationship between ferroptosis and inflammation, investigating their interaction in brain I/R is crucial for understanding disease development and creating innovative therapeutic options. Consequently, this article will provide a comprehensive introduction of the mechanisms linking ferroptosis and neuroinflammation, as well as evaluate potential treatment modalities, with the goal of presenting various insights for alleviating brain I/R injury and exploring new therapeutic avenues.

The steady increase in the prevalence of inflammatory bowel disease (IBD) is regarded as a worldwide health issue. Gut microorganisms could modulate host immune and metabolic status and are associated with health effects. Probiotics, Lactobacillus rhamnosus GG (LGG), are beneficial microorganisms that ameliorate disease and exert advantageous effects on intestinal homeostasis. However, the viability of probiotics will suffer from various risk factors in the digestive tract. In this view, we developed a probiotic coating with nanocomposite using tannic acid (TA) and casein phosphopeptide (CPP) through layer-by-layer technology to overcome the challenges after oral administration. LGG showed an improved survival rate in simulated gastrointestinal conditions after coated. The coating (LGG/TA-Mg2+/CPP) had potent reactive oxygen species (ROS) scavenging ability and improved the survival rate of colorectal epithelial cells after H2O2 stimulation. In DSS-induced colitis, administration of LGG/TA-Mg2+/CPP ameliorated intestinal inflammation and reduced the disruption of barrier function. Furthermore, LGG/TA-Mg2+/CPP increased the abundance and diversity of the gut microbiota. In the mouse model of DSS colitis, LGG/TA-Mg2+/CPP can better activate the EGFR/AKT signaling pathway, thereby protecting the epithelial barrier function of the colon epithelium. In conclusion, the probiotic coating with nanocomposite may become a delivery platform for probiotics applied to IBD.

Abstract Backgrounds Increased respiratory drive has been demonstrated to correlate with weaning failure, which could be quantified by electrical activity of the diaphragm (EAdi). We described the physiological process of EAdi-based parameters during the spontaneous breathing trial (SBT) and evaluated the change of EAdi-based parameters as potential predictors of weaning failure. Methods We conducted a prospective study in 35 mechanically ventilated patients who underwent a 2-hour SBT. EAdi and ventilatory parameters were continuously measured during the SBT. Diaphragm ultrasound was performed before the SBT and at the 30 min of the SBT. Three EAdi-based parameters were calculated: neuro-ventilatory efficiency, neuro-excursion efficiency and neuro-discharge per min. Results Of the thirty 35 patients studied, 25 patients were defined as SBT success, including 22 patients weaning successfully and 3 patients reintubated. Before the SBT, neuro-excursion efficiency differed significantly between two groups and had the highest predictive value for SBT failure (AUROC 0.875, p

Abstract A comprehensive understanding of the transient characteristics in solid oxide cells (SOCs) is crucial for advancing SOC technology in renewable energy storage and conversion. However, general formulas describing the relationship between SOC transients and multiple parameters remain elusive. Through comprehensive numerical analysis, we find that the thermal and gaseous response times of SOCs upon rapid electrical variations are on the order of two characteristic times (τ h and τ m), respectively. The gaseous response time is approximately 1τ m, and the thermal response time aligns with roughly 2τ h. These characteristic times represent the overall heat and mass transfer rates within the cell, and their mathematical relationships with various SOC design and operating parameters are revealed. Validation of τ h and τ m is achieved through comparison with an in-house experiment and existing literature data, achieving the same order of magnitude for a wide range of electrochemical cells, showcasing their potential use for characterizing transient behaviors in a wide range of electrochemical cells. Moreover, two examples are presented to demonstrate how these characteristic times can streamline SOC design and control without the need for complex numerical simulations, thus offering valuable insights and tools for enhancing the efficiency and durability of electrochemical cells.

Abstract Background Diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) provide more comprehensive and informative perspective on microstructural alterations of cerebral white matter (WM) than single-shell diffusion tensor imaging (DTI), especially in the detection of crossing fiber. However, studies on systemic lupus erythematosus patients without neuropsychiatric symptoms (non-NPSLE patients) using multi-shell diffusion imaging remain scarce. Methods Totally 49 non-NPSLE patients and 41 age-, sex-, and education-matched healthy controls underwent multi-shell diffusion magnetic resonance imaging. Totally 10 diffusion metrics based on DKI (fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, mean kurtosis, axial kurtosis and radial kurtosis) and NODDI (neurite density index, orientation dispersion index and volume fraction of the isotropic diffusion compartment) were evaluated. Tract-based spatial statistics (TBSS) and atlas-based region-of-interest (ROI) analyses were performed to determine group differences in brain WM microstructure. The associations of multi-shell diffusion metrics with clinical indicators were determined for further investigation. Results TBSS analysis revealed reduced FA, AD and RK and increased ODI in the WM of non-NPSLE patients (P

Abstract Background Certain studies have indicated a link between obstructive sleep apnea and insulin resistance in specific populations. To gain more clarity, extensive research involving a broad sample of the overall population is essential. The primary objective of this study was to investigate this correlation by utilizing data from the National Health and Nutrition Examination Survey database. Methods The analysis incorporated data from the National Health and Nutrition Examination Survey database spanning the time periods from 2005 to 2008 and from 2015 to 2018, with a focus on American adults aged 18 years and older after applying weight adjustments. Key variables such as obstructive sleep apnea, triglyceride glucose index, and various confounding factors were considered. A generalized linear logistic regression model was used to investigate the association between obstructive sleep apnea and the triglyceride glucose index, with additional exploration of the consistency of the results through hierarchical analysis and other techniques. Results The study included participants aged between 18 and 90 years, with an average age of 46.75 years. Among the total sample, 50.76% were male. The triglyceride glucose index demonstrated a diagnostic capability for obstructive sleep apnea, with an AUC of 0.701 (95% CI: 0.6619–0.688). According to the fully adjusted model, individuals in the fourth quartile of the triglyceride glucose index showed an increased likelihood of having obstructive sleep apnea compared to those in the first quartile (OR: 1.45; 95% CI: 1.02–2.06; P

The security of the Earth system has been extensively discussed through the concept of planetary boundaries, which hypothesizes the Anthropocene as the crisis for pushing environmental variables beyond safe limits. Cities, as burgeoning population centers, warrant heightened attention to issues surrounding planetary boundaries and ecological security. While groundwork has been laid for environmental change detection, the acoustic or soundscape perspective is rarely considered. This paper presents abundant empirical evidence supporting the feasibility of leveraging the soundscape as a valuable lens for exploring ecosystem structures, functions, and their contribution to human well-being. Particularly, it proposes spatialized soundscape maps as practical tools to implement this innovative perspective. We elaborate on two key aspects: (i) soundscape as a reflection of ecosystem evolution, enabling evaluation of ecosystem structures, interactions, and the ecosystem's functions; (ii) soundscape has the attribution of providing cultural services, allowing assessment of its impact on human health. Consequently, we propose two paradigms: (i) “security in soundscape” and (ii) “security of soundscape”, thereby initiated the concept of “soundscape for security”. Furthermore, we outline two generalized pathways: (i) soundscape monitoring, encompassing long-term strategies for real-time tracking of ecosystem evolution, and (ii) soundscape perception, involving detailed surveys to investigate perception and public participatory sensing for large-scale evaluation of ecosystem cultural services. We argue that integrating soundscape considerations holds promise in urban ecological security initiatives and the pursuit of sustainable cities. Moving forward, collective efforts among academics are crucial to establish widely accepted protocols to maximize the value of soundscape for urban ecological security.

Abstract Music plays a vital role in human culture and society, serving as a universal form of expression. However, accurately classifying music emotions remains challenging due to the intricate nature of emotional expressions in music and the integration of diverse data sources. To address these challenges, we propose the Multilayered Music Decomposition and Multimodal Integration Interaction (MMD-MII) model. This model employs cross-processing to facilitate interaction between audio and lyrics, ensuring coherence in emotional representation. Additionally, we introduce a hierarchical framework based on the music theory, focusing on the main and chorus sections, with the chorus processed separately to extract precise emotional representations. Experimental results on the DEAM and FMA datasets demonstrate the effectiveness of the MMD-MII model, achieving accuracies of 49.68% and 49.54% respectively. Compared with the existing methods, our model outperforms in accuracy and F1 scores, offering promising implications for music recommendation systems, healthcare, psychology, and advertising, where accurate emotional analysis is essential.

Abstract With the popularity and advancement of 3D point cloud data acquisition technologies and sensors, research into 3D point clouds has made considerable strides based on deep learning. The semantic segmentation of point clouds, a crucial step in comprehending 3D scenes, has drawn much attention. The accuracy and effectiveness of fully supervised semantic segmentation tasks have greatly improved with the increase in the number of accessible datasets. However, these achievements rely on time‐consuming and expensive full labelling. In solve of these existential issues, research on weakly supervised learning has recently exploded. These methods train neural networks to tackle 3D semantic segmentation tasks with fewer point labels. In addition to providing a thorough overview of the history and current state of the art in weakly supervised semantic segmentation of 3D point clouds, a detailed description of the most widely used data acquisition sensors, a list of publicly accessible benchmark datasets, and a look ahead to potential future development directions is provided.

Abstract Background Syncope is a common condition that increases the risk of injury and reduces the quality of life. Abdominal pain as a precursor to vasovagal syncope (VVS) in adults is rarely reported and is often misdiagnosed.​. Methods We present three adult patients with VVS and presyncopal abdominal pain diagnosed by synchronous multimodal detection (transcranial Doppler [TCD] with head-up tilt [HUT]) and discuss the relevant literature. Results Case 1: A 52-year-old man presented with recurrent decreased consciousness preceded by six months of abdominal pain. Physical examinations were unremarkable. Dynamic electrocardiography, echocardiography, head and neck computed tomography angiography, magnetic resonance imaging (MRI), and video electroencephalogram showed no abnormalities. Case 2: A 57-year-old woman presented with recurrent syncope for 30 + years, accompanied by abdominal pain. Physical examination, electroencephalography, and MRI showed no abnormalities. Echocardiography showed large right-to-left shunts. Case 3: A 30-year-old woman presented with recurrent syncope for 10 + years, with abdominal pain as a precursor. Physical examination, laboratory analysis, head computed tomography, electrocardiography, and echocardiography showed no abnormalities. Syncope secondary to abdominal pain was reproduced during HUT. Further, HUT revealed vasovagal syncope, and synchronous TCD showed decreased cerebral blood flow; the final diagnosis was VVS in all cases. Conclusions Abdominal pain may be a precursor of VVS in adults, and our findings enrich the clinical phenotypic spectrum of VVS. Prompt recognition of syncopal precursors is important to prevent incidents and assist in treatment decision-making. Abdominal pain in VVS may be a sign of sympathetic overdrive. Synchronous multimodal detection can help in diagnosing VVS and understanding hemodynamic mechanisms.

Abstract Objective The purpose of this article is to systematically review the association between dry eye and sleep quality. Methods PubMed, EMBASE, Cochrane, Web of Science, and grey literature databases were searched for observational studies published before April 2023. Meta-analysis was performed using STAT15 software. Results A total of 21 studies with 419,218 participants were included. The results showed that the dry eye subjects had a worse sleep quality than the healthy population, with poorer subjective sleep quality, longer sleep latency, and a higher risk of unhealthy sleep duration such as insufficient sleep or excessive sleep. The Pittsburgh Sleep Quality Index (PSQI) scores of the dry eye subjects were significantly higher than those of the control subjects (WMD = 1.78, 95%CI: 1.06, 2.50, P

Abstract Water splitting is a critical process for the production of green hydrogen, contributing to the advancement of a circular economy. However, the application of water splitting devices on a large scale is primarily impeded by the sluggish oxygen evolution reaction (OER) at the anode. Thus, developing and designing efficient OER catalysts is a significant target. NiFe‐based catalysts are extensively researched as excellent OER electrocatalysts due to their affordability, abundant reserves, and intrinsic activities. However, they still suffer from long‐term stability challenges. To date, few systematic strategies for improving OER durability have been reported. In this review, various advanced NiFe‐based catalysts are introduced. Moreover, the OER stability challenges of NiFe‐based electrocatalysts in alkaline media, including iron segregation, structural degradation, and peeling from the substrate are summarized. More importantly, strategies to enhance OER stability are highlighted and opportunities are discussed to facilitate future stability studies for alkaline water electrolysis. This review presents a design strategy for NiFe‐based electrocatalysts and anion exchange membrane (AEM) electrolyzers to overcome stability challenges in OER, which also emphasizes the importance of long‐term stability in alkaline media and its significance for achieving large‐scale commercialization.

Abstract Background The sustainable supply of medicinal plants is important, and cultivating and domesticating them has been suggested as an optimal strategy. However, this can lead to a loss of genetic diversity. Tripterygium wilfordii Hook. f. is a medicinal plant commonly used in traditional Chinese medicine, but its wild populations are dwindling due to excessive harvesting. To protect the species and meet the increasing demand, it is urgent to cultivate it on a large scale. However, distinguishing between T. wilfordii and T. hypoglaucum, two similar species with different medicinal properties, is challenging. Therefore, it is crucial to understand the genetic diversity and population structure of these species for their sustainable utilization. Results In this study, we investigated the genetic diversity and population structure of the two traditional medicinal semiwoody vines plant species, Tripterygium wilfordii and T. hypoglaucum, including wild and cultivated populations using chloroplast DNA (cpDNA) sequences and microsatellite loci. Our results indicated that the two species maintain a high level of genetic divergence, indicating possible genetic bases for the different contents of bioactive compounds of the two species. T. wilfordii showed lower genetic diversity and less subdivided population structures of both markers than T. hypoglaucum. The potential factors in shaping these interesting differences might be differentiated pollen-to-seed migration rates, interbreeding, and history of population divergence. Analyses of cpDNA and microsatellite loci supported that the two species are genetically distinct entities. In addition, a significant reduction of genetic diversity was observed for cultivated populations of the two species, which mainly resulted from the small initial population size and propagated vegetative practice during their cultivation. Conclusion Our findings indicate significant genetic divergence between T. wilfordii and T. hypoglaucum. The genetic diversity and population structure analyses provide important insights into the sustainable cultivation and utilization of these medicinal plants. Accurate identification and conservation efforts are necessary for both species to ensure the safety and effectiveness of crude drug use. Our study also highlighted the importance of combined analyses of different DNA markers in addressing population genetics of medicinal plants because of the contrasts of inheritance and rates of gene flow. Large-scale cultivation programs should consider preserving genetic diversity to enhance the long-term sustainability of T. wilfordii and T. hypoglaucum. Our study proposed that some populations showed higher genetic diversity and distinctness, which can be considered with priority for conservation and as the sources for future breeding and genetic improvement.

The chemical compositions and volatile profiles of wax gourd seed oil (WGSO), watermelon seed oil (WSO), pumpkin seed oil (PSO), cucumber seed oil (CSO), and bitter gourd seed oil (BGSO) were comparatively explored for the first time. All oils complied with standards for physicochemical properties and BGSO had the highest phenolic content. Their mineral levels varied significantly. The fatty acid composition of WGSO, WSO, PSO, and CSO was similar, predominantly linoleic acid. Whereas BGSO exhibited a distinct fatty acid profile with 55.38 % α-eleostearic acid. All samples were rich in tocopherols and squalene, with WSO having the highest total tocopherol content and PSO having the highest squalene content. HS-GC–IMS and HS-SPME-GC–MS detected 118 and 67 VOCs, respectively, primarily consisting of aliphatic aldehydes, alcohols, esters, and ketones. Principal component analysis confirmed that BGSO had the most distinctive volatile characteristics, while the other four seed oils shared similar VOC profiles.

The global incidence and prevalence of inflammatory bowel disease (IBD) are gradually increasing. A high-fat diet (HFD) is known to disrupt intestinal homeostasis and aggravate IBD, yet the underlying mechanisms remain largely undefined. Here, a positive correlation between dietary fat intake and disease severity in both IBD patients and murine colitis models is observed. A HFD induces a significant decrease in indole-3-acetic acid (IAA) and leads to intestinal barrier damage. Furthermore, IAA supplementation enhances intestinal mucin sulfation and effectively alleviates colitis. Mechanistically, IAA upregulates key molecules involved in mucin sulfation, including 3’-phosphoadenosine 5’-phosphosulfate synthase 2 (Papss2) and solute carrier family 35 member B3 (Slc35b3), the synthesis enzyme and the transferase of 3’-phosphoadenosine-5’-phosphosulfate (PAPS), via the aryl hydrocarbon receptor (AHR). More importantly, AHR can directly bind to the transcription start site of Papss2. Oral administration of Lactobacillus reuteri, which can produce IAA, contributes to protecting against colitis and promoting mucin sulfation, while the modified L. reuteri strain lacking the iaaM gene (LactobacillusΔiaaM) and the ability to produce IAA fail to exhibit such effects. Overall, IAA enhances intestinal mucin sulfation through the AHR-Papss2-Slc35b3 pathway, contributing to the protection of intestinal homfeostasis.

Abstract Active compounds were usually incorporated into biopolymer films to enhance their properties. The tensile strength (TS) and elongation at break (EAB) of the gelatin composite films increased along with the addition of ε‐polylysine (ε‐PL) and zinc oxide nanoparticles (nano‐ZnO). When the concentrations of ε‐PL and nano‐ZnO were 4% and 0.5%, TS and EAB reached to the maximum which were 53.98 ± 2.61 MPa and 16.05 ± 1.76%. The water vapor permeability, water solubility, and water content of the composite films decreased from 2.01 ± 0.04 10−10 g m−1 Pa−1 s−1 to 1.56 ± 0.07 × 10−10 g m−1 Pa−1 s−1, from 45.23 ± 1.54% to 31.39 ± 1.24% and from 23.89 ± 1.41% to 17.34 ± 2.61%, respectively, compared with gelatin film. The light barrier capacity of the composite film was improved. The surface of the film was relatively smooth, and the cross‐section was overall flat. FTIR results indicated that no chemical reaction occurred among ε‐PL, nano‐ZnO and gelatin. The chemical structure of the films remained unchanged throughout the heat‐sealing process. Moreover, the gelatin films containing ε‐PL and nano‐ZnO showed excellent antibacterial activity. Our findings suggest that the gelatin composite films with antibacterial property hold promise for the application in food packaging materials.

Facial expression recognition (FER) plays a crucial role in affective computing, enhancing human-computer interaction by enabling machines to understand and respond to human emotions. Despite advancements in deep learning, current FER systems often struggle with challenges such as occlusions, head pose variations, and motion blur in natural environments. These challenges highlight the need for more robust FER solutions. To address these issues, we propose the Attention-Enhanced Multi-Layer Transformer (AEMT) model, which integrates a dual-branch Convolutional Neural Network (CNN), an Attentional Selective Fusion (ASF) module, and a Multi-Layer Transformer Encoder (MTE) with transfer learning. The dual-branch CNN captures detailed texture and color information by processing RGB and Local Binary Pattern (LBP) features separately. The ASF module selectively enhances relevant features by applying global and local attention mechanisms to the extracted features. The MTE captures long-range dependencies and models the complex relationships between features, collectively improving feature representation and classification accuracy. Our model was evaluated on the RAF-DB and AffectNet datasets. Experimental results demonstrate that the AEMT model achieved an accuracy of 81.45% on RAF-DB and 71.23% on AffectNet, significantly outperforming existing state-of-the-art methods. These results indicate that our model effectively addresses the challenges of FER in natural environments, providing a more robust and accurate solution. The AEMT model significantly advances the field of FER by improving the robustness and accuracy of emotion recognition in complex real-world scenarios. This work not only enhances the capabilities of affective computing systems but also opens new avenues for future research in improving model efficiency and expanding multimodal data integration.

Abstract Dendrite growth and other side‐reaction problems of zinc anodes in aqueous zinc‐ion batteries heavily affect their cycling lifespan and Coulombic efficiency, which can be effectively alleviated by the application of polymer‐based functional protection layer on the anode. However, the utilization rate of functional groups is difficult to improve without destroying the polymer chain. Here, a simple and well‐established strategy is proposed by controlling the orientation of functional groups (─SO3H) to assist the optimization of zinc anodes. Depending on the electrostatic effect, the surface‐enriched ─SO3H groups increase the ionic conductivity and homogenize the Zn2+ flux while inhibiting anionic permeation. This approach avoids the destruction of the polymer backbone by over‐sulfonation and amplifies the effect of functional groups. Therefore, the modified sulfonated polyether ether ketone (H‐SPEEK) coating‐optimized zinc anode is capable of longtime stable zinc plating/stripping, and moreover an enhanced cycling steadiness under high current densities is also detected in a series of Zn batteries with different cathode materials, which achieved by the inclusion of H‐SPEEK coating without causing any harmful effects on the electrolyte and cathode. This work provides an easy and efficient approach to further optimize the plating/stripping of cations on metal electrodes, and sheds lights on the scale‐up of high‐performance aqueous zinc‐ion battery technology.

Abstract Avicennia marina, known for its remarkable adaptability to the challenging coastal environment, including high salinity, tide, and anaerobic soils, holds pivotal functions in safeguarding the coastal ecosystem. Long non‐coding RNAs (lncRNAs) have emerged as significant players in various natural processes of plants such as development. However, lncRNAs in A. marina remain largely unknown and uncharacterized. Here, we employed the transcriptome datasets from multiple tissues, such as root, leaf, and seed, to detect and characterize the lncRNAs of A. marina. Analyzing synthetically, we finally identified 6333 lncRNAs in the A. marina. These lncRNAs exhibited distinct features compared to messenger RNAs, including larger exons, lower guanine‐cytosine contents, lower expression levels, and higher tissue specificities. Moreover, we identified thousands of tissue‐specific lncRNAs across the examined tissues and further found that these tissue‐specific lncRNAs were significantly enriched in biological processes related to the major functions of their corresponding tissues. For instance, leaf‐specific lncRNAs showed prominent enrichment in photosynthesis, oxidation–reduction processes, and light harvesting. By providing a comprehensive dataset and functional annotations for A. marina lncRNAs, this study offers a valuable overview of lncRNAs in A. marina and lays the fundamental foundation for further functional exploring of them.

Abstract We conducted an experimental investigation to examine the immiscible radial displacement flows of air invading three-dimensional foam in a Hele-Shaw cell. Our study successfully identified three distinct flow regimes. In the initial regime, characterized by relatively low fingertip velocities, the foam underwent a slow displacement through plug flow. During this process, the three-phase contact lines slipped at the cell walls. Notably, we discovered that the air injection pressure exhibited a proportional relationship with the power of the fingertip velocity. This relationship demonstrated excellent agreement with a power law, where the exponent was determined to be 2/3. Transitioning to the second regime, we observed relatively high velocities, resulting in the displacement of the foam as a plug within single layers of foam bubbles. The movement of these bubbles near the cell walls was notably slower. Similar to the first regime, the behavior in this regime also adhered to a power law. In the third regime, which manifested at higher air injection pressures, the development of air fingers occurred through narrow channels. These channels had the potential to isolate the air fingers as they underwent a process of "healing." Furthermore, our results unveiled a significant finding that the width of the air fingers exhibited a continuous scaling with the air injection pressure, irrespective of the flow regimes being observed.

Abstract Ultra-compact spectrometers are becoming increasingly popular for their promising applications in biomedical analysis, environmental monitoring, and food safety. In this work, we report a single-pixel-photodetector spectrometer with a spectral range from 480 nm to 820 nm, based on the AlGaAs/GaAs p-graded-n junction with a voltage-tunable optical response. To reconstruct the optical spectrum, we propose a tailored method called Neural Spectral Fields (NSF) that leverages the unique wavelength and bias-dependent responsivity matrix. Our spectrometer achieves a high spectral wavelength accuracy of up to 0.30 nm and a spectral resolution of up to 10 nm. Additionally, we demonstrate the high spectral imaging performance of the device. The compatibility of our demonstration with the standard III-V process greatly accelerates the commercialization of miniaturized spectrometers.

Abstract Background Parenting is both a complex and stressful endeavor, so parents sometimes experience parenting burnout. The main objective of this study was to provide an overview of factors related to general parental burnout (PB) among parents with at least one child based on the Ecological Systems Theory (EST). Methods PubMed, Web of Science, EBSCO, CNKI and WanFang were systematically searched for studies published from 2010 to July 2023 for peer-reviewed articles using keywords extracted from Medical Subject Headings such as “parenting”, “parental”, “burnout”, “psychological burnout”, “burn-out syndrome”. Studies were included if they described associations between factors and PB among parents of children aged 0-18 years old in the general population, and published in an English or Chinese language peer-reviewed journal. The Quality Assessment Tool for Studies with Diverse Designs (QATSDD) was employed to assess the risk of bias of included studies. Results Of 2037 articles, 26 articles met the inclusion criteria. Based on the Ecological Systems Theory (EST), we found that microsystem-individual factors such as gender, educational level, income, parental personality, internalization of maternal parental motivation, unmitigated communion, self-compassion and concern for others, alexithymia, anxiety and depressive symptoms, parental perfectionism, resilience, low self-esteem and high need for control, mother's attachment style were identified as being associated with parenting burnout. Mesosystem-interpersonal factors involve parent-child relationship and marital satisfaction. The exosystem-organizational or community factors include the number of children in the household, neighborhood and the number of hours spent with children, child's illness, child's behavior problems and social support. The macrosystem-society/policy or culture factors are mainly personal values and cultural values. Conclusions This systematic review found several factors that have been investigated in relation to PB. However, the majority of the factors were reported by one or two studies often implementing a cross-sectional design. Nevertheless, we still recommend that health policymakers and administrators relieve parenting burnout among parents with children by adjusting these modifiable factors.

With the expansion and implementation of rural revitalization strategies, there is a constant need for new energy sources for the construction of new townships. Consequently, integrated energy systems with the interconnection and interaction of multiple energy sources are developing rapidly. Biomass energy, a renewable green energy source with low pollution and wide distribution, has significant application potential in integrated energy systems. Considering the application of biomass energy in townships, this study established an integrated biomass energy system and proposed a model to optimize its operation. Lowest economic cost and highest clean energy utilization rate were considered as the objective functions. In addition, a plan was suggested to adjust the heat-electricity ratio based on the characteristics of the combined heat and power of the biomass. Finally, a simulation analysis conducted for a town in China was discussed, demonstrating that the construction of a township integrated-energy system and the use of biomass can significantly reduce operating costs and improve the energy utilization rate. Moreover, by adjusting the heat-electricity ratio, the economic cost was further reduced by 6.70%, whereas the clean energy utilization rate was increased by 5.14%.

Visual selective attention studies generally tend to apply cuing paradigms to instructively direct observers’ attention to certain locations, features or objects. However, in real situations, attention in humans often flows spontaneously without any specific instructions. Recently, a concept named “willed attention” was raised in visuospatial attention, in which participants are free to make volitional attention decisions. Several ERP components during willed attention were found, along with a perspective that ongoing alpha activity may bias the subsequent attentional choice. However, it remains unclear whether similar neural mechanisms exist in feature- or object-based willed attention. Here, we included choice cues and instruct cues in a feature-based selective attention paradigm, allowing participants to freely choose or to be instructed to attend a color for the subsequent target detection task. Pre-cue ongoing alpha oscillations, cue-evoked potentials and target-related steady-state visual evoked potentials (SSVEPs) were simultaneously measured as markers of attentional processing. As expected, SSVEP responses were similarly modulated by attention between choice and instruct cue trials. Similar to the case of spatial attention, a willed-attention component (Willed Attention Component, WAC) was isolated during the cue-related choice period by comparing choice and instruct cues. However, pre-cue ongoing alpha oscillations did not predict the color choice (yellow vs blue), as indicated by the chance level decoding accuracy (50%). Overall, our results revealed both similarities and differences between spatial and feature-based willed attention, and thus extended the understanding toward the neural mechanisms of volitional attention.

Rapid and accurate identification of cancerous areas during surgery is crucial for guiding surgical procedures and reducing postoperative recurrence rates. Dynamic Cell Imaging (DCI) has emerged as a promising alternative to traditional frozen section pathology, offering high-resolution displays of tissue structures and cellular characteristics. However, challenges persist in segmenting DCI images using deep learning methods, such as color variation and artifacts between patches in whole slide DCI images, and the difficulty in obtaining precise annotated data. In this paper, we introduce a novel two-stage framework for DCI image generation and segmentation. Initially, the Dual Semantic Diffusion Model (DSDM) is specifically designed to generate high-quality and semantically relevant DCI images. These images not only serve as an effective means of data augmentation to assist downstream segmentation tasks but also help in reducing the reliance on expensive and hard-to-obtain large annotated medical image datasets. Furthermore, we reuse the pretrained DSDM to extract diffusion features, which are then infused into the segmentation network via a cross-attention alignment module. This approach enables our network to capture and utilize the characteristics of DCI images more effectively, thereby significantly enhancing segmentation results. Our method was validated on the DCI dataset and compared with other methods for image generation and segmentation. Experimental results demonstrate that our method achieves superior performance in both tasks, proving the effectiveness of the proposed model.

The use of edge computing devices in bank outlets for passenger flow analysis, security protection, risk prevention and control is increasingly widespread, among which the performance and power consumption of AI reasoning chips have become a very important factor in the selection of edge computing devices.Aiming at the problems of recurrent neural network, such as high power consumption, weak reasoning performance and low energy efficiency, which were caused by data dependence and low data reusability, this paper realized a sparse RNN low-power accelerator with scalable voltage by using FPGA, and verifies it on the edge design and calculation equipment.Firstly, the sparse -RNN was analyzed and the processing array was designed by network compression.Secondly, due to the unbalanced workload of sparse RNN, it introduced voltage scaling method to maintain low power consumption and high throughput.Experiments show that this method could significantly improve the RNN reasoning speed of the system and reduce the processing power consumption of the chip.

Microorganisms in the oral cavity are abundant in the human body. At present, more than 700 species of oral microorganisms have been identified. Recently, a lot of literature has indicated that the oral microbiota plays an important role in the occurrence, development, and prognosis of oral squamous cell carcinoma (OSCC) through various mechanisms. And researchers are now trying to utilize oral microbiota in cancer diagnosis and treatment. However, few articles systematically summarize the effects of oral microbes in the diagnosis, treatment, and disease outcomes of oral cancer. Herein, we made a summary of the microbial changes at cancerous sites and placed more emphasis on the mechanisms by which the oral microbiome promotes cancerization. Moreover, we aimed to find out the clinical value of the oral microbiome in OSCC.

This study focused on systematic literature measurement and visual analysis of ''pine polyphenols'' to explore the research status, cutting-edge dynamics, and hot prospects of pine polyphenols, with a view to providing theoretical references for research of relevant personnel. In addition, literature related to pine polyphenols included in the 2005~2022 CNKI (China National Knowledge Infrastructure) and WOS (Web of Science) core collection databases had been used to conduct the data visualization analysis on the publication volume, authors, publication countries, research units, and keywords of sonpolyphenols through the Cite Space scientific knowledge mapping tool and bibliometric analysis platform. Results showed that, the overall number of articles published about pine polyphenols in Chinese tended to decrease, while English presented an upward trend. With Wang Zhenyu and Garcia D (Garcia Danny, Garcia D) as the core authors of the Chinese and English articles, research on pine polyphenols had yet to form a stable research group. China was a country with the most research on pine polyphenols, followed by Spain and the United States. The Northeast Forestry University and Harbin Institute of Technology as the main research units in China, and the CSIC (Consejo Superior de Investigaciones Cientificas, CSIC) and the UC (University of Concepcion, UC) as the main research units internationally. Combining a timeline knowledge map and keyword prominence analysis, this study determined that Chinese and English research mainly focuses on anti-oxidation, anti-tumor, isolation and purification, etc., and speculated that the future development direction of pine polyphenos research would be on chemical components, expansion of functional activity, and application in the pharmaceutical industry and health products.

The consensus problem in stochastic multi-agent systems (MASs) with Markovian switching is addressed by proposing a novel distributed dynamic event-triggered (DDET) technique based on periodic sampling to reduce information transmission. Unlike traditional event-triggered control, the proposed periodic sampling-based DDET method is characterized by the following three advantages: (1) The need for continuous monitoring of the event trigger is eliminated. (2) Zeno behavior in stochastic MASs is effectively prevented. (3) Communication costs are significantly reduced. Based on this, sufficient conditions for achieving consensus in the mean-square sense are derived using Lyapunov–Krasovskii functions, providing a solid theoretical foundation for the proposed strategy. The effectiveness of the proposed DDET control is validated through two numerical examples.

Proton-conducting solid oxide fuel cells (P-SOFCs) are widely studied for their lower working temperatures than oxygen-ion-conducting SOFCs (O-SOFCs). Due to the elevated preparation and operation temperatures varying from 500 °C to 1500 °C, high mechanical stresses can be developed in the electrolytes of SOFCs. The stresses will in turn impact the electrical conductivities, which is often omitted in current studies. In this work, the mechanical–conductive behaviors of Y-doped BaZrO3 (BZY) electrolytes for P-SOFCs under high temperatures are studied through molecular dynamics modeling. The Young’s moduli of BZY in fully hydrated and non-hydrated states are calculated with different Y-doping concentrations and at different temperatures. It is shown that Y doping, oxygen vacancies, and protonic point defects all lead to a decrease in the Young’s moduli of BZY at 773 K. The variations in the conductivities of BZY are then investigated by calculating the diffusion rates of protons in BZY at different triaxial, biaxial, and uniaxial strains from 673 K to 873 K. In all cases, the diffusion rate present a trend of first increasing and then decreasing from compression state to tension state. The variations in elementary affecting factors of proton diffusion, including hydroxide rotation, proton transfer, proton trapping, and proton distribution, are then analyzed in detail under different strains. It is concluded that the influences of strains on these factors collectively determine the changes in proton conductivity.

Background: The present study aimed to explore the association of ATP-binding cassette B1 (ABCB1)/multiple drug resistance 1 (MDR1) gene polymorphisms (rs1128503 and rs1045642) with labor analgesia in primiparas. Methods: The cohort comprised 239 primiparas who received epidural analgesia (0.5 μg/L sufentanil + 0.1% ropivacaine). Visual analog scale (VAS) scores were recorded at 0, 1, and 2 h, respectively, after epidural analgesia. The outcomes (VAS score and adverse reactions) of labor analgesia among patients carrying different genotypes of ABCB1 gene polymorphisms were compared using a one-way analysis of variance (ANOVA) or chi-square test. ABCB1 polymorphisms were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). The correlation between ABCB1 gene polymorphisms and labor analgesia outcomes (including VAS score and adverse reactions) was evaluated using logistic regression analysis. Results: Genotype distributions of rs1128503 and rs1045642 polymorphisms were detected using Hardy-Weinberg equilibrium (HWE) test. Age, body mass index, and gestational age did not differ significantly between genotypes of rs1128503 and rs1045642 polymorphisms. A higher 2 h-VAS score was observed in the rs1045642 TT genotype than in the rs1045642 CC and CT genotypes, while abnormal fetal heart rate (FHR) monitoring and 1 min Apgar scores were frequently discovered in patients with the rs1128503 TT genotype (p < 0.05). Logistic regression analysis suggested that 2 h-VAS score (p = 0.025, odds ratio (OR) = 0.497, 95% confidence interval (95% CI) = 0.270–0.915), nausea (p = 0.042, OR = 0.188, 95% CI = 0.038–0.940) and Apgar score at 1 min (p = 0.026, OR = 1.774, 95% CI = 1.069–2.942) were distinctly correlated with the rs1128503 TC + CC genotypes. VAS 2 h score (p = 0.000, OR = 3.673, 95% CI = 1.900–7.101) was positively related to the rs1045642 CT + TT genotypes. Conclusions: ABCB1 gene rs1128503 and rs1045642 polymorphisms were significantly correlated with the analgesic effect and adverse reactions of labor analgesia in primiparas.

Aimed at the problems of optical frequency combs, such as their large number of comb lines, their high flatness, and their lack of ease in generating, as well as the fact that the channelization efficiency of the scheme based on optical frequency combs is low, we proposed a microwave photonic channelization receiver based on signal polarization multiplexing. Using two-line local optical frequency combs with different frequencies to demodulate the RF signal in the orthogonal polarization state, 16 sub-channels with a bandwidth of 1 GHz can be received simultaneously. The experimental results show that the image rejection ratio can reach 28 dB, and the third-order spurious-free dynamic range of the system can reach 96.8 dB·Hz2∕3. This scheme has the advantages of a large number of sub-channels and a high channelization efficiency; it has great application potential in broadband wireless communication, radar, and electronic warfare systems.