BiU-net: A dual-branch structure based on two-stage fusion strategy for biomedical image segmentation.

BACKGROUND AND OBJECTIVE: Computer-based biomedical image segmentation plays a crucial role in planning of assisted diagnostics and therapy. However, due to the variable size and irregular shape of the segmentation target, it is still a challenge to construct an effective medical image segmentation structure. Recently, hybrid architectures based on convolutional neural networks (CNNs) and transformers were proposed. However, most current backbones directly replace one or all convolutional layers with transformer blocks, regardless of the semantic gap between features. Thus, how to sufficiently and effectively eliminate the semantic gap as well as combine the global and local information is a critical challenge. METHODS: To address the challenge, we propose a novel structure, called BiU-Net, which integrates CNNs and transformers with a two-stage fusion strategy. In the first fusion stage, called Single-Scale Fusion (SSF) stage, the encoding layers of the CNNs and transformers are coupled, with both having the same feature map size. The SSF stage aims to reconstruct local features based on CNNs and long-range information based on transformers in each encoding block. In the second stage, Multi-Scale Fusion (MSF), BiU-Net interacts with multi-scale features from various encoding layers to eliminate the semantic gap between deep and shallow layers. Furthermore, a Context-Aware Block (CAB) is embedded in the bottleneck to reinforce multi-scale features in the decoder. RESULTS: Experiments on four public datasets were conducted. On the BUSI dataset, our BiU-Net achieved 85.50 % on Dice coefficient (Dice), 76.73 % on intersection over union (IoU), and 97.23 % on accuracy (ACC). Compared to the state-of-the-art method, BiU-Net improves Dice by 1.17 %. For the Monuseg dataset, the proposed method attained the highest scores, reaching 80.27 % and 67.22 % for Dice and IoU. The BiU-Net achieves 95.33 % and 81.22 % Dice on the PH2 and DRIVE datasets. CONCLUSIONS: The results of our experiments showed that BiU-Net transcends existing state-of-the-art methods on four publicly available biomedical datasets. Due to the powerful multi-scale feature extraction ability, our proposed BiU-Net is a versatile medical image segmentation framework for various types of medical images. The source code is released on (https://github.com/ZYLandy/BiU-Net).

Career adaptability among new oncology nurses: A longitudinal exploration.

AIM: This study aims to explore the longitudinal predictive effect of self-awareness on career adaptability in new nurses at a tumor specialty hospital and the mediating mechanisms of work readiness and transition shock. BACKGROUND: Career adaptability is crucial for the personal development of nurses and also intricately linked to the retention rates among newcomers in oncology nursing. Inadequate career adaptability contributes to higher turnover, which in turn exacerbates the shortage of qualified nursing personnel in this field. There is a pressing need for dedicated research and interventions that support new nurses, especially in specialized areas like oncology, to promote their well-being and career advancement. Comprehending these challenges is essential for devising effective strategies that will retain nursing talent and ensure the sustainability of a robust healthcare workforce. METHODS: Longitudinal data from four follow-up surveys were collected from 248 new clinical nurses at the National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, and Peking Union Medical College. Mediation analyses using R 4.1.2 were conducted to examine the pathways between self-awareness, work readiness, transition shock, and career adaptability. CONCLUSIONS: Self-awareness not only directly predicts career adaptability but also influences it through the bidirectional and chained mediating pathways of work readiness and transition shock. IMPLICATIONS FOR NURSING AND HEALTH POLICY: These findings equip nursing managers with flexible strategies to foster and enhance nurses' career adaptability, providing targeted support as nurses assimilate into their clinical roles. This not only strengthens workforce stability but also mitigates turnover, ultimately reinforcing the healthcare workforce.

Discovery and genetic characterization of novel paramyxoviruses from small mammals in Hubei Province, Central China.

Paramyxoviruses are a group of single-stranded, negative-sense RNA viruses, some of which are responsible for acute human disease, including parainfluenza virus, measles virus, Nipah virus and Hendra virus. In recent years, a large number of novel paramyxoviruses, particularly members of the genus Jeilongvirus, have been discovered in wild mammals, suggesting that the diversity of paramyxoviruses may be underestimated. Here we used hemi-nested reverse transcription PCR to obtain 190 paramyxovirus sequences from 969 small mammals in Hubei Province, Central China. These newly identified paramyxoviruses were classified into four clades: genera Jeilongvirus, Morbillivirus, Henipavirus and Narmovirus, with most of them belonging to the genus Jeilongvirus. Using Illumina sequencing and Sanger sequencing, we successfully recovered six near-full-length genomes with different genomic organizations, revealing the more complex genome content of paramyxoviruses. Co-divergence analysis of jeilongviruses and their known hosts indicates that host-switching occurred more frequently in the evolutionary histories of the genus Jeilongvirus. Together, our findings demonstrate the high prevalence of paramyxoviruses in small mammals, especially jeilongviruses, and highlight the diversity of paramyxoviruses and their genome content, as well as the evolution of jeilongviruses.

Effectiveness of shared decision-making for mode of delivery after caesarean section: A systematic review and meta-analysis of randomized controlled trials.

AIM: To review the content, format and effectiveness of shared decision-making interventions for mode of delivery after caesarean section for pregnant women. DESIGN: Systematic review and meta-analysis. METHODS: Six databases (PubMed, Web of science Core Collection, Cochrance Network, Embase, CINAHL, PsycINFO) were searched starting at the time of establishment of the database to May 2023. Following the PRISMAs and use Review Manager 5.3 software for meta-analysis. Two review authors independently assessed the quality of the studies using the risk of bias 2 tool. The protocol was registered in PROSPERO (CRD42023410536). RESULTS: The search strategy obtained 1675 references. After abstract and full text screening, a total of seven studies were included. Shared decision-making interventions include decision aids and counselling that can help pregnant women analyse the pros and cons of various options and help them make decisions that are consistent with their values. The pooled results showed that shared decision-making intervention alleviated decisional conflicts regarding mode of delivery after caesarean section, but had no effect on knowledge and informed choice. CONCLUSION: The results of our review suggest that shared decision-making is an effective intervention to improve the quality of decision-making about the mode of delivery of pregnant women after caesarean section. However, due to the low quality of the evidence, it is recommended that more studies be conducted in the future to improve the quality of the evidence. CORRELATION WITH CLINICAL PRACTICE: This systematic review and meta-analysis provides evidence for the effectiveness of shared decision-making for mode of delivery after cesarean section and may provide a basis for the development of intervention to promote the participation of pregnant women in the decision-making process.

AtRKD5 inhibits the parthenogenic potential mediated by AtBBM.

Parthenogenesis, the development of unfertilized egg cells into embryos, is a key component of apomixis. AtBBM (BABY BOOM), a crucial regulator of embryogenesis in Arabidopsis, possesses the capacity to shift nutritional growth toward reproductive growth. However, the mechanisms underlying AtBBM-induced parthenogenesis remain largely unexplored in dicot plants. Our findings revealed that in order to uphold the order of sexual reproduction, the embryo-specific promoter activity of AtBBM as well as repressors that inhibit its expression in egg cells combine to limiting its ability to induce parthenogenesis. Notably, AtRKD5, a RWP-RK domain-containing (RKD) transcription factor, binds to the 3' end of AtBBM and is identified as one of the inhibitory factors for AtBBM expression in the egg cell. In the atrkd5 mutant, we successfully achieved enhanced ectopic expression of AtBBM in egg cells, resulting in the generation of haploid offspring via parthenogenesis at a rate of 0.28%. Furthermore, by introducing chimeric Arabidopsis and rice BBM genes into the egg cell, we achieved a significant 4.6-fold enhancement in haploid induction through the atdmp8/9 mutant. These findings lay a strong foundation for further exploration of the BBM-mediated parthenogenesis mechanism and the improvement of haploid breeding efficiency mediated by the dmp8/9 mutant.

Lipid-lowering, antihypertensive, and antithrombotic effects of nattokinase combined with red yeast rice in patients with stable coronary artery disease: a randomized, double-blinded, placebo-controlled trial.

Nattokinase (NK) and red yeast rice (RYR) are both indicated for their potential in cardiovascular disease prevention and management, but their combined effects especially in coronary artery disease (CAD) are scarcely examined. This 90-day randomized, double-blind trial aims to investigate the effect of NK and RYR supplementations on cardiometabolic parameters in patients with stable CAD. 178 CAD patients were randomized to four groups: NK + RYR, NK, RYR, and placebo. No adverse effects due to the interventions were reported. In comparisons across groups, NK + RYR showed the maximum effect in reducing triglyceride (-0.39 mmol), total cholesterol (-0.66 mmol/L), diastolic blood pressure (-7.39 mmHg), and increase in high-density lipoprotein cholesterol (0.195 mmol/L) than other groups (all p for multiple groups comparison<0.01). Both NK + RYR and NK groups had significantly better-improved lactate dehydrogenase than the others (-29.1 U/L and - 26.4 U/L). NK + RYR group also showed more potent reductions in thromboxane B2 and increases in antithrombin III compared to placebo (both p < 0.01). These improved markers suggest that combined NK and RYR may preferably alter antithrombin and COX-1 pathways, potentially reducing thrombosis risks in CAD patients. Overall, the combined NK and RYR supplementation is safe and more effective than separately in improving cardiometabolic markers among CAD patients with multiple heart medications use.

Clpf encodes pentatricopeptide repeat protein (PPR5) and regulates pink flesh color in watermelon (Citrullus lanatus L.).

KEY MESSAGE: The gene controlling pink flesh in watermelon was finely mapped to a 55.26-kb region on chromosome 6. The prime candidate gene, Cla97C06G122120 (ClPPR5), was identified through forward genetics. Carotenoids offer numerous health benefits; while, they cannot be synthesized by the human body. Watermelon stands out as one of the richest sources of carotenoids. In this study, genetic generations derived from parental lines W15-059 (red flesh) and JQ13-3 (pink flesh) revealed the presence of the recessive gene Clpf responsible for the pink flesh (pf) trait in watermelon. Comparative analysis of pigment components and microstructure indicated that the disparity in flesh color between the parental lines primarily stemmed from variations in lycopene content, as well as differences in chromoplast number and size. Subsequent bulk segregant analysis (BSA-seq) and genetic mapping successfully narrowed down the Clpf locus to a 55.26-kb region on chromosome 6, harboring two candidate genes. Through sequence comparison and gene expression analysis, Cla97C06G122120 (annotated as a pentatricopeptide repeat, PPR) was predicted as the prime candidate gene related to pink flesh trait. To further investigate the role of the PPR gene, its homologous gene in tomato was silenced using a virus-induced system. The resulting silenced fruit lines displayed diminished carotenoid accumulation compared with the wild-type, indicating the potential regulatory function of the PPR gene in pigment accumulation. This study significantly contributes to our understanding of the forward genetics underlying watermelon flesh traits, particularly in relation to carotenoid accumulation. The findings lay essential groundwork for elucidating mechanisms governing pigment synthesis and deposition in watermelon flesh, thereby providing valuable insights for future breeding strategies aimed at enhancing fruit quality and nutritional value.

The Autophagy-Related Protein ATG8 Orchestrates Asexual Development and AFB1 Biosynthesis in Aspergillus flavus.

Autophagy, a conserved cellular recycling process, plays a crucial role in maintaining homeostasis under stress conditions. It also regulates the development and virulence of numerous filamentous fungi. In this study, we investigated the specific function of ATG8, a reliable autophagic marker, in the opportunistic pathogen Aspergillus flavus. To investigate the role of atg8 in A. flavus, the deletion and complemented mutants of atg8 were generated according to the homologous recombination principle. Deletion of atg8 showed a significant decrease in conidiation, spore germination, and sclerotia formation compared to the WT and atg8C strains. Additionally, aflatoxin production was found severely impaired in the ∆atg8 mutant. The stress assays demonstrated that ATG8 was important for A. flavus response to oxidative stress. The fluorescence microscopy showed increased levels of reactive oxygen species in the ∆atg8 mutant cells, and the transcriptional result also indicated that genes related to the antioxidant system were significantly reduced in the ∆atg8 mutant. We further found that ATG8 participated in regulating the pathogenicity of A. flavus on crop seeds. These results revealed the biological role of ATG8 in A. flavus, which might provide a potential target for the control of A. flavus and AFB1 biosynthesis.

Parathyroid Hormone is Negatively Correlated with Glycated Hemoglobin in Newly Diagnosed Type 2 Diabetic Patients.

Objective: The growing evidence shows that parathyroid hormone (PTH) may affect glucose metabolism. However, the relationship between them is still controversial among diabetic patients. The current study aimed to investigate the relationship between PTH and glucose metabolism in the patients with newly diagnosed type 2 diabetes (T2D). Methods: A total of 532 participants, including 387 patients with newly diagnosed T2D and 145 healthy controls, were recruited in the present study. PTH and metabolic parameters were measured in all participants. Results: The PTH levels were significantly lower in the newly diagnosed T2D patients compared with the control group (35.10 (25.90, 47.20) vs. 47.15 (35.83, 58.65) pg/ml, P < 0.001). The T2D patients with a higher glycated hemoglobin (HbA1c) tertile had lower PTH levels than the patients with a lower HbA1c tertile (32.90 (24.85, 41.40) vs. 37.50 (26.10, 54.55) pg/ml, P < 0.001). Spearman correlation analysis showed that PTH was positively correlated with the body mass index (BMI), fasting insulin (FINS), homeostasis model assessment of ß-cell function (HOMA-ß), and homeostasis model assessment of insulin resistance (HOMA-IR) and negatively correlated with HbA1c, blood calcium (Ca), blood phosphorus (P), and 25-hydroxyvitamin D3 (25-OH-D3). Multiple linear regression analysis demonstrated that PTH was significantly associated with HbA1c (ß = -1.475, P=0.003) and HOMA-ß (ß = 0.090, P=0.001) after adjusting for age, sex, BMI, season, 25-OH-D3, Ca, and P. Conclusion: PTH was negatively correlated with HbA1c in the newly diagnosed T2D patients. Our results suggested that the PTH level within the reference range is related to islet ß-cell function and hyperglycemia.

Functional near-infrared spectroscopy-based diagnosis support system for distinguishing between mild and severe depression using machine learning approaches.

Significance: Early diagnosis of depression is crucial for effective treatment. Our study utilizes functional near-infrared spectroscopy (fNIRS) and machine learning to accurately classify mild and severe depression, providing an objective auxiliary diagnostic tool for mental health workers. Aim: Develop prediction models to distinguish between severe and mild depression using fNIRS data. Approach: We collected the fNIRS data from 140 subjects and applied a complete ensemble empirical mode decomposition with an adaptive noise-wavelet threshold combined denoising method (CEEMDAN-WPT) to remove noise during the verbal fluency task. The temporal features (TF) and correlation features (CF) from 18 prefrontal lobe channels of subjects were extracted as predictors. Using recursive feature elimination with cross-validation, we identified optimal TF or CF and examined their role in distinguishing between severe and mild depression. Machine learning algorithms were used for classification. Results: The combination of TF and CF as inputs for the prediction model yielded higher classification accuracy than using either TF or CF alone. Among the prediction models, the SVM-based model demonstrates excellent performance in nested cross-validation, achieving an accuracy rate of 92.8%. Conclusions: The proposed model can effectively distinguish mild depression from severe depression.

Application of texture signatures based on multiparameter-magnetic resonance imaging for predicting microvascular invasion in hepatocellular carcinoma: Retrospective study.

BACKGROUND: Despite continuous changes in treatment methods, the survival rate for advanced hepatocellular carcinoma (HCC) patients remains low, highlighting the importance of diagnostic methods for HCC. AIM: To explore the efficacy of texture analysis based on multi-parametric magnetic resonance (MR) imaging (MRI) in predicting microvascular invasion (MVI) in preoperative HCC. METHODS: This study included 105 patients with pathologically confirmed HCC, categorized into MVI-positive and MVI-negative groups. We employed Original Data Analysis, Principal Component Analysis, Linear Discriminant Analysis (LDA), and Non-LDA (NDA) for texture analysis using multi-parametric MR images to predict preoperative MVI. The effectiveness of texture analysis was determined using the B11 program of the MaZda4.6 software, with results expressed as the misjudgment rate (MCR). RESULTS: Texture analysis using multi-parametric MRI, particularly the MI + PA + F dimensionality reduction method combined with NDA discrimination, demonstrated the most effective prediction of MVI in HCC. Prediction accuracy in the pulse and equilibrium phases was 83.81%. MCRs for the combination of T2-weighted imaging (T2WI), arterial phase, portal venous phase, and equilibrium phase were 22.86%, 16.19%, 20.95%, and 20.95%, respectively. The area under the curve for predicting MVI positivity was 0.844, with a sensitivity of 77.19% and specificity of 91.67%. CONCLUSION: Texture analysis of arterial phase images demonstrated superior predictive efficacy for MVI in HCC compared to T2WI, portal venous, and equilibrium phases. This study provides an objective, non-invasive method for preoperative prediction of MVI, offering a theoretical foundation for the selection of clinical therapy.

Nitric oxide-mediated regulation of Aspergillus flavus asexual development by targeting TCA cycle and mitochondrial function.

Nitric oxide (NO) is a signaling molecule with diverse roles in various organisms. However, its role in the opportunistic pathogen Aspergillus flavus remains unclear. This study investigates the potential of NO, mediated by metabolites from A. oryzae (AO), as an antifungal strategy against A. flavus. We demonstrated that AO metabolites effectively suppressed A. flavus asexual development, a critical stage in its lifecycle. Transcriptomic analysis revealed that AO metabolites induced NO synthesis genes, leading to increased intracellular NO levels. Reducing intracellular NO content rescued A. flavus spores from germination inhibition caused by AO metabolites. Furthermore, exogenous NO treatment and dysfunction of flavohemoglobin Fhb1, a key NO detoxification enzyme, significantly impaired A. flavus asexual development. RNA-sequencing and metabolomic analyses revealed significant metabolic disruptions within tricarboxylic acid (TCA) cycle upon AO treatment. NO treatment significantly reduced mitochondrial membrane potential (Δψm) and ATP generation. Additionally, aberrant metabolic flux within the TCA cycle was observed upon NO treatment. Further analysis revealed that NO induced S-nitrosylation of five key TCA cycle enzymes. Genetic analysis demonstrated that the S-nitrosylated Aconitase Acon and one subunit of succinate dehydrogenase Sdh2 played crucial roles in A. flavus development by regulating ATP production. This study highlights the potential of NO as a novel antifungal strategy to control A. flavus by compromising its mitochondrial function and energy metabolism.

The effect of health quotient and time management skills on self-management behavior and glycemic control among individuals with type 2 diabetes mellitus.

Objective: The aim of this study was to evaluate the present status of self-management behavior and glycemic control in individuals diagnosed with Type 2 Diabetes Mellitus (T2D), as well as to examine the impact of health quotient (HQ) and time management skills on both self-management behavior and glycemic control. Methods: Between October 2022 and March 2023, a purposive sampling method had been utilized to select 215 participants with type T2D. The survey concluded a general information questionnaire, an HQ scale, a diabetes time management questionnaire and a self-management behavior questionnaire. The health quotient(HQ)encompasses the individuals' knowledge, attitude toward health, and the ability to maintain their own well-being. The diabetes time management questionnaire was reverse-scored, with higher scores indicating an enhanced competence in time management. The path among variables was analyzed using structural equation modeling(SEM). Results: SEM showed that the direct effect of HQ on time management was -0.566 (p < 0.05), the direct effect of time management on the effect of self-management was -0.617 (p < 0.05), the direct effect of HQ on self-management was 0.156, and the indirect effect was 0.349 (p < 0.05); the relationship between health quotient and self-management was partially mediated by time management, with a mediating effect size of 68.8%. In addition, self-management had a direct effect on HbAlc, with a size of -0.394 (p < 0.05); The impacts of both HQ and time management on HbAlc were found to be mediated by self-management, with HQ demonstrating an indirect effect of -0.199 (p < 0.05) and time management showing an indirect effect of 0.244 (p < 0.05). Conclusion: Health quotient and time management in patients with T2D serve as catalysts for self-management behavior. They affect HbAlc level indirectly through self-management practices. The suggestion is to prioritize the cultivation of rational time organization and management skills in T2D patients, as well as enhance their health quotient level. This can facilitate a more effective improvement in patients' self-management behaviors, ultimately achieving the objective of maintaining optimal glycemic control.

SPP1 represents a therapeutic target that promotes the progression of oesophageal squamous cell carcinoma by driving M2 macrophage infiltration.

BACKGROUND: Tumour-associated macrophages (TAMs) are an important component of the tumour microenvironment (TME). However, the crosstalk between oesophageal squamous cell carcinoma (ESCC) cells and TAMs remains largely unexplored. METHODS: Clinical samples and the TCGA database were used to evaluate the relevance of SPP1 and TAM infiltration in ESCC. Mouse models were constructed to investigate the roles of macrophages educated by SPP1 in ESCC. Macrophage phenotypes were determined using qRT‒PCR and immunohistochemical staining. RNA sequencing was performed to elucidate the mechanism. RESULTS: Increasing expression of SPP1 correlated with M2-like TAM accumulation in ESCC, and they both predicted poor prognosis in the ESCC cohort. Knockdown of SPP1 significantly inhibited the infiltration of M2 TAMs in xenograft tumours. In vivo mouse model experiments showed that SPP1-mediated education of macrophages plays an essential role in the progression of ESCC. Mechanistically, SPP1 recruited macrophages and promoted M2 polarisation via CD44/PI3K/AKT signalling activation and then induced VEGFA and IL6 secretion to sustain ESCC progression. Finally, blockade of SPP1 with RNA aptamer significantly inhibited tumour growth and M2 TAM infiltration in xenograft mouse models. CONCLUSIONS: This study highlights SPP1-mediated crosstalk between ESCC cells and TAMs in ESCC. SPP1 could serve as a potential target in ESCC therapy.

Part-Object Progressive Refinement Network for Zero-Shot Learning.

Zero-shot learning (ZSL) recognizes unseen images by sharing semantic knowledge transferred from seen images, encouraging the investigation of associations between semantic and visual information. Prior works have been devoted to the alignment of global visual features with semantic information, i.e., attribute vectors, or further mining the local part regions related to each attribute and then simply concatenating them for category decisions. Although effective, these works ignore intrinsic interactions between local parts and the whole object, which enables a more discriminative and representative knowledge transfer for ZSL. In this paper, we propose a Part-Object Progressive Refinement Network (POPRNet), where discriminative and transferable semantics are progressively refined by the cooperation between parts and the whole object. Specifically, POPRNet incorporates discriminative part semantics and object-centric semantics guided by semantic intensity to improve cross-domain transferability. To achieve part-object learning, a semantic-augment transformer (SaT) is proposed to model the part-object relation at the part-level via an encoder and at the object-level via a decoder, generating a comprehensive semantic representation to boost discriminability and transferability. By introducing the prototype updating module embedded with the prototype selection layers, the discriminative ability of the updated category prototype is enhanced to further improve the recognition performance of ZSL. Extensive experiments are conducted to demonstrate the superiority and competitiveness of our proposed POPRNet method on three public benchmark datasets. The code is available at https://github.com/ManLiuCoder/POPRNet.

The effects of ambient temperature and feeding regimens on cecum bacteria composition and circadian rhythm in growing rabbits.

Seasonal environmental shifts and improper eating habits are the important causes of diarrhea in children and growing animals. Whether adjusting feeding time at varying temperatures can modify cecal bacterial structure and improve diarrhea remains unknown. Three batches growing rabbits with two groups per batch were raised under different feeding regimens (fed at daytime vs. nighttime) in spring, summer and winter separately, and contents were collected at six time points in 1 day and used 16S rRNA sequencing to investigate the effects of feeding regimens and season on the composition and circadian rhythms of cecum bacteria. Randomized forest regression screened 12 genera that were significantly associated with seasonal ambient temperature changes. Nighttime feeding reduced the abundance of the conditionally pathogenic bacteria Desulfovibrio and Alistipes in summer and Campylobacter in winter. And also increases the circadian rhythmic Amplicon Sequence Variants in the cecum, enhancing the rhythm of bacterial metabolic activity. This rhythmic metabolic profile of cecum bacteria may be conducive to the digestion and absorption of nutrients in the host cecum. In addition, this study has identified 9 genera that were affected by the combination of seasons and feeding time. In general, we found that seasons and feeding time and their combinations affect cecum composition and circadian rhythms, and that daytime feeding during summer and winter disrupts the balance of cecum bacteria of growing rabbits, which may adversely affect cecum health and induce diarrhea risk.

Humoral immune response to tumor-associated antigen Ubiquilin 1 (UBQLN1) and its tumor-promoting potential in lung cancer.

BACKGROUND: This study aims to investigate the expression of UBQLN1 in lung cancer (LC) tissue and the diagnostic capability of autoantibody to UBQLN1 (anti-UBQLN1) in the detection of LC and the discrimination of pulmonary nodules (PNs). METHODS: Sera from 798 participants were used to discover and validate the level of autoantibodies via HuProt microarray and Enzyme-linked immunosorbent assay (ELISA). Logistic regression analysis was applied to establish model. Receiver operating characteristic curve (ROC) analysis was performed to evaluate the diagnostic potential. Immunohistochemistry was performed to detect UBQLN1 expression in 88 LC tissues and 88 para-tumor tissues. qRT-PCR and western blotting were performed to detect the expression of UBQLN1 at the mRNA and protein levels, respectively. Trans-well assay and cell counting kit-8 (CCK-8) was used to investigate the function of UBQLN1. RESULTS: Anti-UBQLN1 was identified with the highest fold change by protein microarray. The level of anti-UBQLN1 in LC patients was obviously higher than that in NC or patients with benign lung disease of validation cohort 1 (P<0.05). The area under the curve (AUC) of anti-UBQLN1 was 0.610 (95%CI: 0.508-0.713) while reached at 0.822 (95%CI: 0.784-0.897) when combining anti-UBQLN1 with CEA, CYFRA21-1, CA125 and three CT indicators (vascular notch sign, lobulation sign and mediastinal lymph node enlargement) in the discrimination of PNs. UBQLN1 protein was overexpressed in lung adenocarcinoma (LUAD) tissues compared to para-tumor tissues. UBQLN1 knockdown remarkably inhibited the migration, invasion and proliferation of LUAD cell lines. CONCLUSIONS: Anti-UBQLN1 might be a potential biomarker for the diagnosis of LC and the discrimination of PNs.

AmCBF1 activates the expression of GhClpR1 to mediate dark-green leaves in cotton (Gossypium hirsutum).

KEY MESSAGE: The transcription factor AmCBF1 deepens the leaf colour of transgenic cotton by binding to the promoter of the chloroplast development-related protein GhClpR1 to promote photosynthesis. The ATP-dependent caseinolytic protease (Clp protease) family plays a crucial role within chloroplasts, comprising several Clp proteins to maintain chloroplast homeostasis. At present, research on Clp proteins mainly focuses on Arabidopsis, leaving its function in other plants, particularly in crops, less explored. In this study, we overexpressed AmCBF1 from Ammopiptanthus mongolicus (A. mongolicus) in wild type (R15), and found a significant darkening of leaf colour in transgenic plants (L28 and L30). RNA-seq analysis showed an enrichment of pathways associated with photosynthesis. Subsequent screening of differentially expressed genes revealed a significant up-regulation of GhClpR1, a gene linked to chloroplast development, in the transgenic strain. In addition, GhClpR1 was consistently expressed in upland cotton, with the highest expression observed in leaves. Subcellular localization analysis revealed that the protein encoded by GhClpR1 was located in chloroplasts. Yeast one hybrid and dual luciferase experiments showed that the AmCBF1 transcription factor positively regulates the expression of GhClpR1. VIGs-mediated silencing of GhClpR1 led to a significant yellowing phenotype in the leaves. This was accompanied by a reduction in chlorophyll content, and microscopic examination of chloroplast ultrastructure revealed severe developmental impairment. Finally, yeast two-hybrid assays showed that GhClpR1 interacts with the Clp protease complex accessory protein GhClpT2. Our study provides a foundation for studying the function of the Clp protease complex and a new strategy for cultivating high-light-efficiency cotton resources.

Biomedical image segmentation algorithm based on dense atrous convolution.

Biomedical images have complex tissue structures, and there are great differences between images of the same part of different individuals. Although deep learning methods have made some progress in automatic segmentation of biomedical images, the segmentation accuracy is relatively low for biomedical images with significant changes in segmentation targets, and there are also problems of missegmentation and missed segmentation. To address these challenges, we proposed a biomedical image segmentation method based on dense atrous convolution. First, we added a dense atrous convolution module (DAC) between the encoding and decoding paths of the U-Net network. This module was based on the inception structure and atrous convolution design, which can effectively capture multi-scale features of images. Second, we introduced a dense residual pooling module to detect multi-scale features in images by connecting residual pooling blocks of different sizes. Finally, in the decoding part of the network, we adopted an attention mechanism to suppress background interference by enhancing the weight of the target area. These modules work together to improve the accuracy and robustness of biomedical image segmentation. The experimental results showed that compared to mainstream segmentation networks, our segmentation model exhibited stronger segmentation ability when processing biomedical images with multiple-shaped targets. At the same time, this model can significantly reduce the phenomenon of missed segmentation and missegmentation, improve segmentation accuracy, and make the segmentation results closer to the real situation.