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Here, we present the second generation of our bicyclic peptide library (NTB), featuring a stereodiversified structure and a simplified construction strategy. We utilized a tandem ring-opening metathesis and ring-closing metathesis reaction (ROM-RCM) to cyclize the linear peptide library in a single step, representing the first reported instance of this reaction being applied to the preparation of macrocyclic peptides. Moreover, the resulting bicyclic peptide can be easily linearized for MS/MS sequencing with a one-step deallylation process. We employed this library to screen against the E363-R378 epitope of MYC and identified several MYC-targeting bicyclic peptides. Subsequent in vitro cell studies demonstrated that one candidate, NT-B2R, effectively suppressed MYC transcription activities and cell proliferation.

Abstract Background Fish gut microbiota undergo dynamic changes under the influence of many factors and play an important role in the nutrition, immunity and development in fish. Although common carp (Cyprinus carpio L.) is an economically important freshwater fish, there are few reports on its gut microbiota changes at different early developmental stages. In the present study, the gut microbiota of common carp during the early developmental stages and its correlation with the feed and pond water flora were studied using the Illumina MiSeq sequencing platform. Results The results showed that the gut microbiota of common carp underwent continuous and mild changes over the development process, and the pond water environment might provide bacterial resources and have a certain influence on the changes in the gut microbiota of common carp. However, host selection pressure played a more important role in shaping the gut microbiota. Although the gut microbiota was affected by many factors, the presence of core microbiota indicated that some bacterial species adapt to the gut microenvironment of common carp and played a role in its growth process. Conclusions The dynamic changes of gut microbiota of carp in early development stage were related to the feed, water environment and host selection. The results of this study provide a theoretical basis for healthy farming and disease prevention of common carp.

Abstract Air quality is closely linked to human health and social development, making accurate air quality prediction highly significant. The Air Quality Index (AQI) is inherently a time series. However, most previous studies have overlooked its temporal features and have not thoroughly explored the relationship between pollutant emissions and air quality. To address this issue, this study establishes a historical correlation model for air quality based on a time series model—the Gaussian Hidden Markov Model (GHMM)—using industrial exhaust emissions and historical air quality data. Firstly, a traversal method is used to select the optimal number of hidden states for the GHMM. To optimize the traditional GHMM and reduce error accumulation in the prediction process, the Multi-day Weighted Matching method and the Fixed Training Set Length method are utilized. Both direct and indirect prediction modes are then used to predict the AQI in the Zhangdian District. Experimental results indicate that the improved GHMM with the indirect mode provides higher accuracy and more stable state estimation results (MAE = 13.59, RMSE = 17.59, mean forecasted value = 117.94). Finally, the air quality historical correlation model is integrated with the air quality meteorological correlation model from a previous study, further improving prediction accuracy (MAE = 11.59, RMSE = 14.87, mean forecasted value = 120.88). This study demonstrates that the GHMM’s strong ability to analyze temporal features significantly enhances the accuracy and stability of air quality predictions. The integration of the air quality historical correlation model with the air quality meteorological correlation model from a previous study leverages the strengths of each sub-model in handling different feature groups, leading to even more accurate predictions.

Abstract Background Atherogenic index of plasma (AIP) index is an important marker of insulin resistance and a significant risk factor for cardiovascular disease. Abdominal aortic calcification (AAC) is significantly associated with subclinical atherosclerotic disease. However, there are no studies that have examined the relationship between AIP index and AAC, so we investigated the potential association between them in the general population. Methods This was a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES, 2013–2014). The association of AIP with AAC was estimated by multivariable regression analysis. Results After adjusting for confounders, the odds of extensive AAC doubled per unit increase in the AIP index (OR = 2.00, 95% CI: 1.05, 3.83; P = 0.035). The multivariable OR and 95% CI of the highest AIP index tertile compared with the lowest tertile was significantly different. (OR = 1.73, 95% CI: 1.05, 2.83; P = 0.031). The subgroup analyses indicated that the association was consistent irrespective of age, sex, hypertension, diabetes, smoking status, eGFR and hypercholesteremia. Conclusions The AIP index was independently associated with the presence of extensive AAC in the study population. Further studies are required to confirm this relationship.

Abstract It is a time-consuming and costly process to develop affordable and high-performance organic photovoltaic materials. Computational methods are essential for accelerating the material discovery process by predicting power conversion efficiencies (PCE). In this study, we propose a deep learning-based framework (DeepAcceptor) to design and discover highly efficient small molecule acceptor materials. Specifically, an experimental dataset is constructed by collecting acceptor data from publications. Then, a deep learning-based model is customized to predict PCEs by applying graph representation learning to Bidirectional Encoder Representations from Transformers (BERT), with the atom, bond, and connection information in acceptor molecular structures as the input (abcBERT). The computational dataset derived from density functional theory (DFT) calculations and the experimental dataset from literature are used to pre-train and fine-tune the model, respectively. The abcBERT model outperforms other state-of-the-art models for the PCE prediction with MAE = 1.78 and R 2 = 0.67 on the test set. A molecular generation and screening process is built to find new high-performance acceptors for PM6. Three discovered candidates are further validated by experiment, and the best PCE reaches 14.61%. The released user-friendly interface of DeepAcceptor greatly boosts the accessibility and efficiency of designing and discovering high-performance acceptors. Altogether, the DeepAcceptor framework with abcBERT is promising to predict the PCE and accelerate the discovery of high-performance acceptor materials.

Abstract Background Individuals with metabolic syndrome face elevated cardiovascular and mortality risks, and there is ongoing debate regarding the cardiovascular effects of niacin and its impact on the prognosis of metabolic syndrome. Exposure Levels of dietary niacin intake based on 24-hour dietary recall. Methods Kaplan-Meier survival curves were used to compare survival status among quartiles of dietary niacin intake. Weighted Cox proportional hazards models and restricted cubic splines were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the risk of all-cause and CVD mortality associated with the exposure. Results This cohort study included 8,744 participants, and during a median follow-up period of 106 months, 1,552 (17.7%) deaths were recorded, with 511 attributed to cardiovascular disease. Kaplan-Meier curves comparing quartiles of dietary niacin intake showed significant differences in both all-cause and cardiovascular mortality rates (log-rank p

Abstract Background The glucose-to-glycated hemoglobin ratio (GAR) represents stress hyperglycemia, which has been closely associated with adverse outcomes in cardio-cerebrovascular diseases. No studies have examined the association between stress hyperglycemia and atrial fibrillation (AF) in critically ill patients. This study aims to explore the relationship between GAR and the prognosis of critically ill patients with AF. Methods A retrospective cohort of patients was selected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The GAR was calculated based on fasting blood glucose and glycated hemoglobin levels measured after admission. The primary outcome was the 30-day mortality rate, with secondary outcomes being the 90-day and 365-day mortality rates. The GAR was divided into tertiles, and Kaplan–Meier analysis was employed to compare differences in mortality rates between groups. The Cox proportional hazards model and restricted cubic splines (RCS) were utilized to evaluate the relationship between the GAR and mortality. Subsequently, a segmented regression model was constructed to analyze threshold effects in cases where nonlinear relationships were determined. Results In this cohort, the second tertile of the GAR exhibited lower mortality rates at 30 days (10.56% vs 6.33% vs 14.51%), 90 days (17.11% vs 10.09% vs 17.88%), and 365 days (25.30% vs 16.15% vs 22.72%). In the third tertile, the risk of mortality at 30 days increased by 165% (HR = 2.65, 95% CI 1.99–3.54, p

Geometric and floral models are an important part of clothing and have been used for thousands of years. Although the styles of geometric models and flower models have undergone changes over the centuries, they are still one of the important factors of clothing patterns, the important carrier of aesthetics, and the manifestation of people’s spiritual views and cultural needs. The development and application of digital printing technology have freed people from excessive dependence on sewing and embroidery processes. Therefore, while deeply studying the design of clothing patterns, this work sorted and analyzed the geometric flower models of clothing through interactive genetic algorithms, and optimized programming to enrich the models of clothing with geometric textures. The results showed that the deviation value of geometric flower pattern design was constantly decreasing, while the optimal strategy value was constantly increasing. The mean deviation value was 0.82, which was a decrease of 0.21 on the seventh day compared with the first day; the mean value of the optimal strategy value was 0.84, which was an increase of 0.19 on the seventh day compared with the first day. The visual effect and creativity of the clothing flower pattern design under the interactive genetic algorithm are better than the traditional flower pattern design, and the visual effect and creativity under the interactive genetic algorithm are 9% higher than the traditional one.

Multiplex protein imaging technologies enable deep phenotyping and provide rich spatial information about biological samples. Existing methods have shown great success but also harbored trade-offs between various pros and cons, underscoring the persisting necessity to expand the imaging toolkits. Here we present PACIFIC: photoactive immunofluorescence with iterative cleavage, a new modality of multiplex protein imaging methods. PACIFIC achieves iterative multiplexing by implementing photocleavable fluorophores for antibody labeling with one-step spin-column purification. PACIFIC requires no specialized instrument, no DNA encoding, or chemical treatments. We demonstrate that PACIFIC can resolve cellular heterogeneity in both formalin-fixed paraffin-embedded (FFPE) samples and fixed cells. To further highlight how PACIFIC assists discovery, we integrate PACIFIC with live-cell tracking and identify phosphor-p70S6K as a critical driver that governs U87 cell mobility. Considering the cost, flexibility, and compatibility, we foresee that PACIFIC can confer deep phenotyping capabilities to anyone with access to traditional immunofluorescence platforms.

Abstract Lipid metabolism reprogramming stands as a fundamental hallmark of cancer cells. Unraveling the core regulators of lipid biosynthesis holds the potential to find promising therapeutic targets in pancreatic ductal adenocarcinoma (PDAC). Here, it is demonstrated that platelet‐derived growth factor C (PDGFC) orchestrated lipid metabolism, thereby facilitated the malignant progression of PDAC. Expression of PDGFC is upregulated in PDAC cohorts and is corelated with a poor prognosis. Aberrantly high expression of PDGFC promoted proliferation and metastasis of PDAC both in vitro and in vivo. Mechanistically, PDGFC accelerated the malignant progression of PDAC by upregulating fatty acid accumulation through sterol regulatory element‐binding protein 1 (SREBP1), a key transcription factor in lipid metabolism. Remarkably, Betulin, an inhibitor of SREBP1, demonstrated the capability to inhibit proliferation and metastasis of PDAC cell lines, along with attenuating the process of liver metastasis in vivo. Overall, the study underscores the pivotal role of PDGFC‐mediated lipid metabolism in PDAC progression, suggesting PDGFC as a potential biomarker for PDAC metastasis. Targeting PDGFC‐induced lipid metabolism emerges as a promising therapeutic strategy for metastatic PDAC, with the potential to improve clinical outcomes.

Abstract Cytopathology, crucial in disease diagnosis, commonly uses microscopic slides to scrutinize cellular abnormalities. However, processing high volumes of samples often results in numerous negative diagnoses, consuming significant time and resources in healthcare. To address this challenge, a surface acoustic wave‐enhanced multi‐view acoustofluidic rotation cytometry (MARC) technique is developed for pre‐cytopathological screening. MARC enhances cellular morphology analysis through comprehensive and multi‐angle observations and amplifies subtle cell differences, particularly in the nuclear‐to‐cytoplasmic ratio, across various cell types and between cancerous and normal tissue cells. By prioritizing MARC‐screened positive cases, this approach can potentially streamline traditional cytopathology, reducing the workload and resources spent on negative diagnoses. This significant advancement enhances overall diagnostic efficiency, offering a transformative vision for cytopathological screening.

Summary: Background: The accurate evaluation of axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) in breast cancer holds great value. This study aimed to develop an artificial intelligence system utilising multiregional dynamic contrast-enhanced MRI (DCE-MRI) and clinicopathological characteristics to predict axillary pathological complete response (pCR) after NAC in breast cancer. Methods: This study included retrospective and prospective datasets from six medical centres in China between May 2018 and December 2023. A fully automated integrated system based on deep learning (FAIS-DL) was built to perform tumour and ALN segmentation and axillary pCR prediction sequentially. The predictive performance of FAIS-DL was assessed using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. RNA sequencing analysis were conducted on 45 patients to explore the biological basis of FAIS-DL. Findings: 1145 patients (mean age, 50 years ±10 [SD]) were evaluated. Among these patients, 506 were in the training and validation sets (axillary pCR rate of 40.3%), 127 in the internal test set (axillary pCR rate of 37.8%), 414 in the pooled external test set (axillary pCR rate of 48.8%), and 98 in the prospective test set (axillary pCR rate of 43.9%). For predicting axillary pCR, FAIS-DL achieved AUCs of 0.95, 0.93, and 0.94 in the internal test set, pooled external test set, and prospective test set, respectively, which were also significantly higher than those of the clinical model and deep learning models based on single-regional DCE-MRI (all P

Increasing evidence indicates that the remodeling of immune microenvironment heterogeneity influences pancreatic cancer development, as well as sensitivity to chemotherapy and immunotherapy. However, a gap remains in the exploration of the immunosenescence microenvironment in pancreatic cancer. In this study, we identified two immunosenescence-associated isoforms (IMSP1 and IMSP2), with consequential differences in prognosis and immune cell infiltration. We constructed the MLIRS score, a hazard score system with robust prognostic performance (area under the curve, AUC = 0.91), based on multiple machine learning algorithms (101 cross-validation methods). Patients in the high MLIRS score group had worse prognosis (P

Abstract This study aimed to explore the link between various forms of obesity, including body mass index (BMI) and waist circumference (WC), and the risk of dyslipidemia among Chinese residents. We selected the study population through a multi-stage random sampling method from permanent residents aged 35 and older in Ganzhou. Obesity was categorized as non-obesity, general obesity, central obesity, or compound obesity according to established diagnostic criteria. We employed a logistic regression model to assess the relationship between different types of obesity and the risk of dyslipidemia. Additionally, we used the restricted cubic spline model to analyze the association between BMI, WC, and the risk of dyslipidemia. The study included 2030 residents aged 35 or older from Ganzhou, China. The prevalence of dyslipidemia was found to be 39.31%, with an age-standardized prevalence of 36.51%. The highest prevalence of dyslipidemia, 58.79%, was observed among those with compound obesity. After adjusting for confounding factors, we found that the risk of dyslipidemia in those with central and compound obesity was respectively 2.00 (95% CI 1.62–2.46) and 2.86 (95% CI 2.03–4.03) times higher than in the non-obese population. Moreover, the analysis using the restricted cubic spline model indicated a nearly linear association between BMI, WC, and the risk of dyslipidemia. The findings emphasize the significant prevalence of both dyslipidemia and obesity among adults aged 35 and above in Ganzhou, China. Notably, individuals with compound obesity are at a substantially increased risk of dyslipidemia. Therefore, it is crucial to prioritize the use of BMI and WC as screening and preventive measures for related health conditions.

Abstract The evolution processes of complex systems carry key information in the systems’ functional properties. Applying machine learning algorithms, we demonstrate that the historical formation process of various networked complex systems can be extracted, including protein-protein interaction, ecology, and social network systems. The recovered evolution process has demonstrations of immense scientific values, such as interpreting the evolution of protein-protein interaction network, facilitating structure prediction, and particularly revealing the key co-evolution features of network structures such as preferential attachment, community structure, local clustering, degree-degree correlation that could not be explained collectively by previous theories. Intriguingly, we discover that for large networks, if the performance of the machine learning model is slightly better than a random guess on the pairwise order of links, reliable restoration of the overall network formation process can be achieved. This suggests that evolution history restoration is generally highly feasible on empirical networks.

Summary: Invadopodia are actin-rich protrusions on the tumor cell membrane that degrade the extracellular matrix and play a crucial role in tumor cell invasion and metastasis. Here, we present a protocol to examine invadopodia’s ability to form and degrade the extracellular matrix during tumor invasion and metastasis. We detail the procedure for using immunofluorescence staining to indirectly detect invadopodia formation and assess their extracellular matrix degradation capability via the gelatin degradation assay.For complete details on the use and execution of this protocol, please refer to Huang et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

The dynamic changes in grassland types are crucial for conserving grassland biodiversity, conducting comprehensive health assessments, and gaining insights into ecosystem evolution. However, accurately mapping grassland types remains an ongoing challenge, especially over large areas. In response, we developed a hierarchical classification framework using random forest to tackle this task. This framework was structured into two tiers: land cover (LC) classification and grassland-type mapping, with each tier using specific features tailored to its respective objectives. In this framework, LC samples were automatically generated using existing LC products combined with vegetation indices and phenological features. We fused spectral information, phenological features, and habitat factors such as topographic indices, soil, and climate from multisource earth observation (EO) data to enhance grassland-type mapping performance. This framework successfully generated distribution maps of grassland types on the Qinghai Plateau for the years 1990–2020. Our findings revealed the following: (1) Using the two-tier classification framework and fusing multisource features, an ideal distribution map of grassland types was obtained, with a macro-average F1 score (F1) of 91% and an overall accuracy (OA) of 96%; (2) Compared to a one-shot classification framework, the two-tier classification framework achieved higher accuracy, with F1 and OA increasing by 11% and 7%, respectively; (3) Climate, topographical, soil, and phenological features assisted in distinguishing grassland types with similar spectral characteristics, especially for zonal grasslands. Adding these features increased F1 by 21%, 10%, 7%, and 3%, respectively, while OA increased by 9%, 5%, 5%, and 2%, respectively. Among these features, relative humidity, total precipitation from May to September, geographic coordinates, and elevation had the greatest effect on grassland type differentiation. June and July were the optimal phenological periods for mapping; (4) Over the 30-year period, the grasslands on the Qinghai Plateau showed an expanding trend, with extensive areas of alpine steppes transforming into alpine meadows. The results of this study provide the first elucidation of grassland-type changes across the Qinghai Plateau from 1990 to 2020. Moreover, they underscore the potential of hierarchical classification frameworks and the integration of multisource EO data in mapping grassland-type distribution.

Unilateral auditory deprivation (UAD) results in cross-modal reorganization of the auditory cortex (AC), which can impair auditory and cognitive functions and diminish the recovery effect of cochlear implantation. Moreover, the subcortical areas provide extensive ascending projections to the AC. To date, a thorough systematic study of subcortical auditory neural plasticity has not been undertaken. Therefore, this review aims to summarize the current evidence on the bidirectional remodeling of the central auditory system caused by UAD, particularly the changes in subcortical neural plasticity. Lateral changes occur in the cochlear nucleus, lateral superior olive, medial nucleus of the trapezoid body, inferior colliculus, and AC of individuals with UAD. Moreover, asymmetric neural activity becomes less prominent in the higher auditory nuclei, which may be due to cross-projection regulation of the bilateral pathway. As a result, subcortical auditory neural plasticity caused by UAD may contribute to the outcomes of cochlear implantation in patients with single-sided deafness (SSD), and the development of intervention strategies for patients with SSD is crucial. Considering that previous studies have focused predominantly on the neural plasticity of the AC, we believe that bidirectional remodeling of subcortical areas after UAD is also crucial for investigating the mechanisms of interventions.

PurposeThis study aimed to develop and validate a radiogenomics nomogram for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC) on the basis of MRI and microRNAs (miRNAs).Materials and methodsThis cohort study included 168 patients (training cohort: n = 116; validation cohort: n = 52) with pathologically confirmed HCC, who underwent preoperative MRI and plasma miRNA examination. Univariate and multivariate logistic regressions were used to identify independent risk factors associated with MVI. These risk factors were used to produce a nomogram. The performance of the nomogram was evaluated by receiver operating characteristic curve (ROC) analysis, sensitivity, specificity, accuracy, and F1-score. Decision curve analysis was performed to determine whether the nomogram was clinically useful.ResultsThe independent risk factors for MVI were maximum tumor length, rad-score, and miRNA-21 (all P < 0.001). The sensitivity, specificity, accuracy, and F1-score of the nomogram in the validation cohort were 0.970, 0.722, 0.884, and 0.916, respectively. The AUC of the nomogram was 0.900 (95% CI: 0.808–0.992) in the validation cohort, higher than that of any other single factor model (maximum tumor length, rad-score, and miRNA-21).ConclusionThe radiogenomics nomogram shows satisfactory predictive performance in predicting MVI in HCC and provides a feasible and practical reference for tumor treatment decisions.

With the widespread application of energy storage stations, BMS has become an important subsystem in modern power systems, leading to an increasing demand for improving the accuracy of SOC prediction in lithium-ion battery energy storage systems. Currently, common methods for predicting battery SOC include the Ampere-hour integration method, open circuit voltage method, and model-based prediction techniques. However, these methods often have limitations such as single-variable research, complex model construction, and inability to capture real-time changes in SOC. In this paper, a novel prediction method based on the KF-SA-Transformer model is proposed by combining model-based prediction techniques with data-driven methods. By using temperature, voltage, and current as inputs, the limitations of single-variable studies in the Ampere-hour integration method and open circuit voltage method are overcome. The Transformer model can overcome the complex modeling process in model-based prediction techniques by implementing a non-linear mapping between inputs and SOC. The presence of the Kalman filter can eliminate noise and improve data accuracy. Additionally, a sparse autoencoder mechanism is integrated to optimize the position encoding embedding of input vectors, further improving the prediction process. To verify the effectiveness of the algorithm in predicting battery SOC, an open-source lithium-ion battery dataset was used as a case study in this paper. The results show that the proposed KF-SA-Transformer model has superiority in improving the accuracy and reliability of battery SOC prediction, playing an important role in the stability of the grid and efficient energy allocation.

Epilepsy is a common chronic brain disorder. Detecting epilepsy by observing electroencephalography (EEG) is the main method neurologists use, but this method is time-consuming. EEG signals are non-stationary, nonlinear, and often highly noisy, so it remains challenging to recognize epileptic EEG signals more accurately and automatically. This paper proposes a novel classification system of epileptic EEG signals for single-channel EEG based on the attention network that integrates time-frequency and nonlinear dynamic features. The proposed system has three novel modules. The first module constructs the Hilbert spectrum (HS) with high time-frequency resolution into a two-channel parallel convolutional network. The time-frequency features are fully extracted by complementing the high-dimensional features of the two branches. The second module constructs a grayscale recurrence plot (GRP) that contains more nonlinear dynamic features than traditional RP, fed into the residual-connected convolution module for effective learning of nonlinear dynamic features. The third module is the feature fusion module based on a self-attention mechanism to assign optimal weights to different types of features and further enhance the information extraction capability of the system. Therefore, the system is named HG-SANet. The results of several classification tasks on the Bonn EEG database and the Bern-Barcelona EEG database show that the HG-SANet can effectively capture the contribution degree of the extracted features from different domains, significantly enhance the expression ability of the model, and improve the accuracy of the recognition of epileptic EEG signals. The HG-SANet can improve the diagnosis and treatment efficiency of epilepsy and has broad application prospects in the fields of brain disease diagnosis.

Abstract Understanding the impact of long‐term opioid exposure on the embryonic brain is critical due to the surging number of pregnant mothers with opioid dependency. However, this has been limited by human brain inaccessibility and cross‐species differences in animal models. Here, a human midbrain model is established that uses hiPSC‐derived midbrain organoids to assess cell‐type‐specific responses to acute and chronic fentanyl treatment and fentanyl withdrawal. Single‐cell mRNA sequencing of 25,510 cells from organoids in different treatment groups reveals that chronic fentanyl treatment arrests neuronal subtype specification during early midbrain development and alters synaptic activity and neuron projection. In contrast, acute fentanyl treatment increases dopamine release but does not significantly alter gene expression related to cell lineage development. These results provide the first examination of the effects of opioid exposure on human midbrain development at the single‐cell level.

Delivering cargo molecules across the plasma membrane is critical for biomedical research, and the need to develop molecularly well-defined tags that enable cargo transportation is ever-increasing. We report here a hydrophilic endocytosis-promoting peptide (EPP6) rich in hydroxyl groups with no positive charge. EPP6 can transport a wide array of small-molecule cargos into a diverse panel of animal cells. Mechanistic studies revealed that it entered the cells through a caveolin- and dynamin-dependent endocytosis pathway, mediated by the surface receptor fibrinogen C domain-containing protein 1. After endocytosis, EPP6 trafficked through early and late endosomes within 30 min. Over time, EPP6 partitioned among cytosol, lysosomes, and some long-lived compartments. It also demonstrated prominent transcytosis abilities in both in vitro and in vivo models. Our study proves that positive charge is not an indispensable feature for hydrophilic cell-penetrating peptides and provides a new category of molecularly well-defined delivery tags for biomedical applications.

In forestry genetics and industry, tree morphological traits such as height, crown size, and shape are critical for understanding growth dynamics and productivity. Traditional methods for measuring these traits are limited in efficiency, scalability, and accuracy, posing challenges for large-scale forest assessments. This study focuses on integrating unmanned aerial vehicle (UAV) technology with GWAS to improve genomic association studies in slash pine (Pinus elliottii). Seven key morphological traits have been identified (canopy area (CA), crown base height (CBH), crown length (CL), canopy volume (CV), crown width (CW), crown width height (CWH), and tree height (H)) through advanced UAV-based phenotyping. These associations account for a remarkable range of heritability in slash pine, with traits such as CBH, CL, CV, and H showing relatively high heritability across both Single nucleotide polymorphisms (SNP) and pedigree methods, indicating strong genetic influence, while traits such as CWH show lower heritability, suggesting greater environmental influence or non-additive genetic variance. The GWAS identified 28 associations, including 22 different SNPs localized to 16 candidate genes, that were significantly associated with the morphological traits of Slash Pine. Notably, two of these candidate genes, annotated as putative DEAD-like helicase and ethylene-responsive element binding factor (ERF), were present at different mutation sites and were significantly associated with CW and CA traits, respectively. These results demonstrate that the UAV imaging enables a comprehensive analysis of the Morphological growth response of slash pine and can facilitate the discovery of informative alleles to elucidate the genetic structure underlying complex phenotypic variation in conifers.

Abstract Background Previous studies have found that frailty and sarcopenia are commonly diagnosed in inflammatory bowel disease (IBD) patients, indicating an association between these conditions. Nonetheless, the cause‒effect connection between IBD, frailty, and sarcopenia remains unclear. Methods We sourced the genetic variants for the exposures and outcomes from publicly accessible, extensive genome-wide association studies (GWAS). Specifically, we obtained IBD data from the International IBD Genetics Consortium, frailty index (FI) data from the United Kingdom Biobank and Swedish TwinGene, and sarcopenia data from a recent GWAS meta-analysis. Five methods, including inverse variance weighted (IVW), simple mode, MR-Egger, weighted mode, and the weighted median, were used to proceed with MR estimates. We also performed heterogeneity and horizontal pleiotropy tests. Results Our results indicated a positive causal relationship between ulcerative colitis (UC) (IVW: β = 0.014, 95% CI, 0.006 to 0.021, p = 0.001) and Crohn's disease (CD) (IVW: β = 0.012; 95% CI, 0.006 to 0.018, p = 2e−04) with the FI. However, we uncovered no proof of a cause-and-effect relationship between UC (IVW: β = 0.001, 95% CI, −0.015 to 0.017, p = 0.344) or CD (IVW: β = 0.003, 95% CI, −0.009 to 0.015, p = 0.214) and sarcopenia. Additionally, in the inverse order, we also discovered no cause-and-effect connection between FI or sarcopenia on UC or CD in this study. Conclusion The MR analysis showed a positive causal association between IBD and FI, indicating that IBD patients may exhibit aging-related characteristics. Therefore, frailty assessments should be conducted as early as possible in IBD patients.

Abstract Background Pyroptosis plays a pivotal role in the tumor immune microenvironment (TME) dynamics, particularly in non‐small cell lung cancer (NSCLC). The aim of our study was to explore its effects on tumor progression, TME patterns, and the efficacy of therapeutic interventions in NSCLC. Methods Our investigation encompassed a thorough analysis of pyroptosis‐related genes (PRGs), integrating immunohistochemistry (IHC) data, TME characteristics, stemness indices, and anticancer drug sensitivities. We aimed to analyze mRNA expression profiles across various cancers, constructing benchmark datasets to assess the clinical significance of PRGs in NSCLC. This included evaluating their association with clinical responses and efficacy. Notably, both our and HPA IHC data demonstrated significantly elevated GSDMD‐N protein levels in lung squamous cell carcinoma (LUSC) tissues. Results The expression of PRGs differed significantly between tumor and normal tissues across various cancers, as validated by IHC data, and was correlated with prognosis (p

Abstract Non-alcoholic fatty liver disease (NAFLD) has been shown to influence breast cancer progression, but the underlying mechanisms remain unclear. In this study, we investigated the impact of NAFLD on breast cancer tumor growth and cell viability through the potential mediator, hepatic fibroblast growth factor 21 (FGF21). Both peritumoral and systemic administration of FGF21 promoted breast cancer tumor growth, while FGF21 knockout attenuated the tumor-promoting effects of the high-fat diet. Mechanistically, exogenous FGF21 treatment enhanced the anti-apoptotic ability of breast cancer cells through STAT3 and Akt/FoXO1 signaling pathways, and mitigated doxorubicin-induced cell death. Furthermore, we observed overexpression of FGF21 in tumor tissues from breast cancer patients, which was associated with poor prognosis. These findings suggest a novel role for FGF21 as an upregulated mediator in the context of NAFLD, promoting breast cancer development and highlighting its potential as a therapeutic target for cancer treatment.

Abstract Radial spokes (RS) transmit mechanochemical signals between the central pair (CP) and axonemal dynein arms to coordinate ciliary motility. Atomic-resolution structures of metazoan RS and structures of axonemal complexes in ependymal cilia, whose rhythmic beating drives the circulation of cerebrospinal fluid, however, remain obscure. Here, we present near-atomic resolution cryo-EM structures of mouse RS head-neck complex in both monomer and dimer forms and reveal the intrinsic flexibility of the dimer. We also map the genetic mutations related to primary ciliary dyskinesia and asthenospermia on the head-neck complex. Moreover, we present the cryo-ET and sub-tomogram averaging map of mouse ependymal cilia and build the models for RS1-3, IDAs, and N-DRC. Contrary to the conserved RS structure, our cryo-ET map reveals the lack of IDA-b/c/e and the absence of Tektin filaments within the A-tubule of doublet microtubules in ependymal cilia compared with mammalian respiratory cilia and sperm flagella, further exemplifying the structural diversity of mammalian motile cilia. Our findings shed light on the stepwise mammalian RS assembly mechanism, the coordinated rigid and elastic RS-CP interaction modes beneficial for the regulation of asymmetric ciliary beating, and also facilitate understanding on the etiology of ciliary dyskinesia-related ciliopathies and on the ependymal cilia in the development of hydrocephalus.

Standard AA5083 (ZSE000), AA5083 modified with 0.3 wt.% Zr and 0.3wt.% Sc (ZSE330) and AA5083 modified with 0.3 wt.% Zr, 0.2wt.% Sc and 0.1wt.%Er(ZSE321) sheets were fabricated through a short process (including a simulated twin-belt continuous casting, subsequent direct rolling, intermediate annealing, cold rolling and stress-relief annealing) to systematically investigate the influence of partially substituting Er for Sc on the microstructure, mechanical properties and corrosion resistance of short-processed Al-4.7Mg-0.6Mn-0.3Zr-0.3Sc sheets. The results show that ZSE321 presents the optimal tensile properties (UTS: 541 MPa; 0.2%PS: 469 MPa and EF:7.7%) among the three experimental sheets. This is attributed to significant grain refinement, the inhibition of the recrystallization and promotion on the precipitation of Al3(Sc, Zr, Er) nanoparticles. Furthermore, the corrosion properties of the experimental sheets were also explored in this study, and the short-processed ZSE321 sheet presents the optimum corrosion resistance.

The long-term excessive use of chemical fertilizers may result in soil degradation, but manure and straw application is considered to be an effective approach for alleviating this problem. The aim of this study is to examine the long-term impacts of different fertilization patterns on soil quality variables in a wheat–sweet potato rotation system. Four treatments were conducted in a field trial for a duration of twelve years, including (1) no fertilizer (control, CK); (2) application of mineral fertilizers (NPK) alone; (3) NPK with crop straw return (NPKs); (4) combined use of NPK and farmyard manure (NPKm). Thirteen physical, chemical, and biological soil parameters were measured. The results showed that the NPKm and NPKs significantly improved the proportion of macroaggregates (>0.25 mm) by 24.7% and 21.9% compared to the NPK alone, respectively. The proportion of microaggregates (0.053–0.25 mm) under the NPKm was 47.4% significantly higher than the NPKs. Additionally, the NPKm resulted in a 22.2% and 19.6% increase in the SOC content than the NPK and NPKs, respectively. In terms of soil-available K, the NPKs resulted in levels that were 42.1% and 49.6% higher than the NPKm and NPK alone, respectively. Long-term fertilization significantly decreased soil pH by 0.95–1.85 units compared to the control, whereas manure application could alleviate soil acidification, as shown when the pH increased by 10.6–18.7%. The NPKm and NPKs resulted in significantly increased soil pHs by 10.6% and 18.7% compared to the NPK alone, respectively. In addition, the NPKm and NPKs increased N-acetyl-β-D-glucosaminidase activity by 52.6% and 60.3% compared to the NPK alone. Determined by the minimum data set method, the NPKm treatment exhibited the highest soil quality index, followed by the NPKs and NPK. Our findings suggested that the combined use of chemical fertilizers with organic amendments proved beneficial for enhancing soil quality.

IntroductionMicrostate analysis enables the characterization of quasi-stable scalp potential fields on a sub-second timescale, preserving the temporal dynamics of EEG and spatial information of scalp potential distributions. Owing to its capacity to provide comprehensive pathological insights, it has been widely applied in the investigation of schizophrenia (SCZ). Nevertheless, previous research has primarily concentrated on differences in individual microstate temporal characteristics, neglecting potential distinctions in microstate semantic sequences and not fully considering the issue of the universality of microstate templates between SCZ patients and healthy individuals.MethodsThis study introduced a microstate semantic modeling analysis method aimed at schizophrenia recognition. Firstly, microstate templates corresponding to both SCZ patients and healthy individuals were extracted from resting-state EEG data. The introduction of a dual-template strategy makes a difference in the quality of microstate sequences. Quality features of microstate sequences were then extracted from four dimensions: Correlation, Explanation, Residual, and Dispersion. Subsequently, the concept of microstate semantic features was proposed, decomposing the microstate sequence into continuous sub-sequences. Specific semantic sub-sequences were identified by comparing the time parameters of sub-sequences.ResultsThe SCZ recognition test was performed on the public dataset for both the quality features and semantic features of microstate sequences, yielding an impressive accuracy of 97.2%. Furthermore, cross-subject experimental validation was conducted, demonstrating that the method proposed in this paper achieves a recognition rate of 96.4% between different subjects.DiscussionThis research offers valuable insights for the clinical diagnosis of schizophrenia. In the future, further studies will seek to augment the sample size to enhance the effectiveness and reliability of this method.

Objective: Laryngeal cancer (LC) is one of the most common squamous cell carcinomas of the head and neck in clinical practice, and its incidence has been increasing in recent years, but the prognosis of the patients is not favorable. Hence, it is critical to re-understand and deeply study the causes and mechanisms of LC and explore new effective treatment methods and strategies. In this study, we analyzed the effect of Dihydroartemisinin (DHA) on the pathological progression of LC through the periostin (POSTN)/Yes-associated protein (YAP)/interleukin (IL)-6 pathway, which can provide new clinical references and guidelines. Methods: POSTN, YAP, and IL-6 levels in 18 pairs of fresh LC tissues and adjacent counterparts in our hospital were detected. Additionally, LC TU686 cell line was purchased for DHA treatment of various concentrations to detect changes in cell biological behavior. Finally, we built a tumor-bearing mouse model with C57BL/6 mice and intragastrically administrated DHA to the animals to observe the growth of living tumors and to measure POSTN, YAP, and IL-6 expression in tumor tissues. Results: As indicated by PCR, Western blotting, and immunohistochemistry, POSTN, YAP, and IL-6 presented higher expression in LC tissues than in adjacent counterparts. In cell experiments, the cloning rate of LC cells decreased and the apoptosis rate increased after DHA intervention, with 160 μmol/L DHA contributing to the most significant effect on LC activity inhibition. Furthermore, DHA-intervened cells exhibited markedly reduced POSTN, YAP, and IL-6 levels. Finally, the tumorigenesis experiment in nude mice showed inhibited tumor growth after DHA administration. And consistently, the expressions of POSTN, YAP, and IL-6 in living tumors decreased. Conclusions: DHA can inhibit POSTN/YAP/IL-6 transduction, accelerate LC cell apoptosis, and alleviate the malignant progression of LC.

Background: Malignant tumours, particularly non-small cell lung cancer (NSCLC), pose a significant threat to human health due to their prevalence and lethality. Treatment methods for NSCLC vary greatly among individuals, making it crucial to identify predictive markers. Moreover, during tumour initiation and progression, tumour cells can release signaling molecules to induce polarization of macrophages towards a more tumour friendly M2 phenotype, which can promote tumour growth, metastasis, and drug resistance. Methods: We employed a comprehensive approach, combining bulk RNA-seq and single-cell sequencing analysis. Results: In our study, we used bulk RNA-seq and single-cell sequencing methods to analyze differential cells in NSCLC and adjacent tissues, searching for relevant marker genes that can predict prognosis and drug efficacy. We scrutinized biological phenomena such as macrophage-related gene methylation, copy number variation, and alternative splicing. Additionally, we utilized a co-culture technique of immune and tumour cells to explore the role of these genes in macrophage polarization. Our findings revealed distinct differences in macrophages between cancerous and adjacent tissues. We identified ANP32A, CCL20, ERAP2, MYD88, TMEM126B, TUBB6, and ZNF655 as macrophage-related genes that correlate with NSCLC patient prognosis and immunotherapy efficacy. Notably, ERAP2, TUBB6, CCL20, and TMEM126B can induce macrophage M0 to M2 polarization, promoting tumour proliferation. Conclusion: These findings significantly contribute to our understanding of the NSCLC tumour immune microenvironment. They pave the way for further research into the potential of these genes as targets for regulating tumour occurrence and development.

AIM: To investigate the changes in retinal nerve fiber layer(RNFL)and macular retinal thickness(MRT)in children with refractive abnormalities and amblyopia, and their predictive value of outcome.METHODS: A total of 168 children with myopic refractive abnormalities and monocular amblyopia admitted to our hospital from January 2020 to October 2022 were selected as the observation group, with 118 cases of mild to moderate amblyopia and 50 cases of severe amblyopia, and 168 children with normal vision were included as the control group in a 1:1 ratio during the same period. The changes of RNFL and MRT in two groups of children were statistically counted, and the correlation between the severity of refractive abnormalities and RNFL and MRT in children with amblyopia was analyzed. Additionally, the observation group was divided into effective subgroup and ineffective subgroup based on the therapeutic effect. The general information, as well as RNFL and MRT of the effective subgroup and the ineffective subgroups before and after treatment were compared. Logistic was used to analyze the factors influencing efficacy, and ROC curves was plotted to analyze the predictive value of RNFL and MRT alone or in combination for efficacy.RESULTS: RNFL and MRT of cases of severe amblyopia were higher than those of the mild to moderate amblyopia and the control groups(all P

In-situ reinforced coatings were prepared by laser cladding Ni60A + WC powder on R60702 zirconium. The microstructural evolution, microhardness, and corrosion resistance of in-situ reinforced composite coatings were analyzed. The reinforcements in the coatings were mainly composed of cross and fishbone-like α-Zr dendrites, block ZrC(B, Si)2, and slender needle-like NiZr. The results show that ZrC/ZrB2 reinforcements grew on the transition layer on the molten WC's surface, fell off, and connected. Some small particles acted as preferential nucleation points and preferentially grew into cross-shaped dendrites in the direction of greater supercooling. The cross-shaped dendrites were closely arranged in the direction of the main axis, and the axial growth rate was smaller than that of the side arms. During the growth process of the cross-shaped dendrites, Zr precipitated towards the side arms, forming α-Zr. Finally, the dendrites interconnected, forming fishbone-like reinforcements. As the laser power increased, the microhardness and corrosion resistance increased significantly. The microhardness (700 HV0.5) and corrosion resistance were highest when the laser power was 2.5 kW and the powder used was Ni60A + 25% WC.

The joining of zirconium alloys is an important issue in the field of nuclear energy since zirconium alloys are often used as nuclear fuel cladding tube. The article reviews the research progress on the diffusion bonding, brazing and resistance welding of zirconium alloys. The main focus of this work is on the process parameters, interfacial microstructure and mechanical properties of joint. For diffusion bonding, the process parameters including temperature and interlayer have significant influence on the properties of joint. The range of temperature and the selection of interlayer was reviewed and the influence of them on interfacial microstructure and properties of joints was also discussed. For brazing, the influence of brazing filler, temperature and holding time on the properties of joint was summarized. For resistance welding, the main process parameters include welding current and contact resistance. Numerical simulation method was often used to describe the influence of process parameters on microstructure during welding end plug with cladding tube. Some suggestions for the further research direction on the welding and joining of zirconium alloys were also proposed.

In order to evaluate the influences of the topology design of a Halbach Magnet Array (HA) on the performance of a motor, a PMSM with an outer coreless rotor using a Halbach Magnet Array (HAORPMSM) is proposed in this article. The design parameters of the HA could be separated into dividing methods per pole, magnet thickness, and initial magnetization direction angle. The phase Back-EMF under constant mechanical speed is chosen as the index to measure the performance of the motor. To start with, different dividing methods of the HA are evaluated. After that, the influence of thickness considering the utilization of the magnet is studied. Lastly, the relationship between initial magnetization direction and motor manufacturing is represented. The results show that the HA design meets the optimized performance considering the balance of the amount of magnet usage and manufacturing when using specific HA parameters.

Soil acidification is a significant form of agricultural soil degradation, which is accelerated by irrational fertilizer application. Sweetpotato and wheat rotation has emerged as an important rotation system and an effective strategy to optimize nutrient cycling and enhance soil fertility in hilly areas, which is also a good option to improve soil acidification and raise soil quality. Studying the effects of different fertilization regimes on soil acidification provides crucial data for managing it effectively. An eight-year field experiment explored seven fertilizer treatments: without fertilization (CK), phosphorus (P) and potassium (K) fertilization (PK), nitrogen (N) and K fertilization (NK), NP fertilization (NP), NP with K chloride fertilization (NPK1), NP with K sulfate fertilization (NPK2), and NPK combined with organic fertilization (NPKM). This study focused on the soil acidity, buffering capacity, and related indicators. After eight years of continuous fertilization in the sweetpotato–wheat rotation, all the treatments accelerated the soil acidification. Notably, N fertilization reduced the soil pH by 1.30–1.84, whereas N-deficient soil showed minimal change. Organic fertilizer addition resulted in the slowest pH reduction among the N treatments. Both N-deficient (PK) and organic fertilizer addition (NPKM) significantly increased the soil cation exchange capacity (CEC) by 8.83% and 6.55%, respectively, compared to CK. Similar trends were observed for the soil-buffering capacity (pHBC). NPK2 increased the soil K+ content more effectively than NPK1. NPKM reduced the sodium and magnesium content compared to CK, with the highest magnesium content among the treatments at 1.60 cmol·kg−1. Regression tree analysis identified the N input and soil magnesium and calcium content as the primary factors influencing the pHBC changes. Structural equation modeling showed that the soil pH is mainly influenced by the soil ammonium N content and pHBC, with coefficients of −0.28 and 0.29, respectively. Changes in the soil pH in the sweetpotato–wheat rotation were primarily associated with the pHBC and N input, where the CEC content emerged as the main factor, modulated by magnesium and calcium. Long-term organic fertilization enhances the soil pHBC and CEC, slowing the magnesium reduction and mitigating soil acidification in agricultural settings.

In recent years, the Chinese hook snout carp (Opsariichthys bidens) is becoming increasingly popular due to its high nutritional value and delicious taste. However, anthropogenic influences have caused a rapid reduction in its population. Considering long-term development sustainability, it is essential to conduct research on its reproductive development. In this study, the germ-cell related genes dazl (Obdazl) and dnd (Obdnd) were cloned, and their expression patterns were revealed. RT-PCR analysis indicated that Obdazl and Obdnd were specifically expressed in gonads. In the testis, Obdazl and Obdnd RNAs have a similar expression pattern: their transcripts were abundant in spermatogonia, gradually decreased, and eventually disappeared during spermatogenesis. Early oocytes in the ovary exhibited strong expression of Obdazl and Obdnd RNAs and reduced remarkably after peak expression at III oocytes. Surprisingly, Obdazl RNA was dynamically found in perinuclear spots that finally aggregated into the Balbiani body (Bb) in the early oocytes. Moreover, Obdazl 3′ UTR enabled the reporter gene to be expressed stably in medaka PGCs, suggesting that dazl was identified as the germ cell marker in O. bidens, which may provide perspectives for further studies on the development of PGCs in the future.