Fluorescent hydrogen-bonded organic framework act as a multifunctional platform for Fe3+ and F- sensing, and for information encryption.

Due to their exceptional optical properties and adjustable functional characteristics, hydrogen-bonded organic frameworks (HOFs) demonstrate significant potential in applications such as sensing, information encryption. However, studies on the synthesis of HOFs designed to construct multifunctional platforms are scant. In this work, we report the synthesis of a new fluorescent HOF by assembling melem and isophthalic acid (IPA), designated as HOF-IPA. HOF-IPA exhibited good selectivity and sensitivity towards Fe3+, making it suitable as a fluorescent sensor for Fe3+ detection. The sensor achieved satisfactory recoveries ranging from 97.79 % to106.42 % for Fe3+ sensing, with a low relative standard deviation (RSD) of less than 3.33 %, indicating significant application potential for HOF-IPA. Due to the ability of F- to mask the electrostatic action on the surface of Fe3+ and inhibit the photoelectron transfer (PET) of HOF-IPA, the HOF-IPA - Fe3+ system can be utilized as a fluorescent "off-on" sensor for F- detection. Additionally, owing to the colorless, transparent property of HOF-IPA in aqueous solution under sunlight and its blue fluorescence property under UV light (color) or microplate reader (fluorescence intensity), HOF-IPA based ink can be used for various types of information encryption, and all yielding favorable outcomes.

Early deep-to-light sedation versus continuous light sedation for ICU patients with mechanical ventilation: a cohort study.

BACKGROUND: Sedation strategies have not been well established for patients being treated with invasive mechanical ventilation (MV). This study aimed to compare the potential effects of alternative sedation strategies - including early deep-to-light sedation (DTLS), continuous deep sedation (CDS) and continuous light sedation (CLS, the currently recommended strategy) - on ventilator, intensive care unit (ICU) or hospital mortality. METHODS: A cohort study was conducted using two large validated ICU databases, including the Registry of Healthcare-associated Infections in ICUs in China (ICU-HAI) and the Medical Information Mart for Intensive Care (MIMIC). Patients who received MV for more than 3 days with one of three sedation strategies were included. Multivariable survival analyses with inverse probability-weighted competing risk models were conducted separately for ICU-HAI and MIMIC cohorts. Adjusted estimates were pooled using fixed-effects models. RESULTS: In total, 6700 patients (2627 ICU-HAI, 4073 MIMIC) were included in the cohort study, of whom 2689 received CLS, 2079 CDS and 1932 DTLS. Compared to CLS, DTLS was associated with lower ICU mortality (9.3% vs. 11.0%; pooled adjusted HR 0.78, 95% CI 0.66-0.94) and hospital mortality (16.0% vs. 14.1%; 0.86, CI 0.74-1.00); and CDS was associated with higher ventilator mortality (32.8% vs. 7.0%; 4.65, 3.91-5.53), ICU mortality (40.6% vs. 11.0%; 3.39, 2.95-3.90) and hospital mortality (46.8% vs. 14.1%; 3.27, 2.89-3.71) than CLS. All HRs were qualitatively consistent in both cohorts. CONCLUSIONS: Compared to the continuous light sedation, early deep-to-light sedation strategy was associated with improved patient outcomes, and continuous deep sedation was confirmed with poorer patient outcomes.

Contrast-Enhanced Ultrasound-Based Radiomics for the Prediction of Axillary Lymph Nodes Status in Breast Cancer.

BACKGROUND: Breast cancer is the leading cause of cancer-related deaths in the female population. Axillary lymph nodes (ALN) are a group of the most common metastatic sites of breast cancer. Timely assessment of ALN status is of paramount clinical importance for medical decision making. AIMS: To utilize contrast-enhanced ultrasound (CEUS)-based radiomics models for noninvasive pretreatment prediction of ALN status. METHODS AND RESULTS: Clinical data and pretreatment CEUS images of primary breast tumors were retrospectively studied to build radiomics signatures for pretreatment prediction of nodal status between May 2015 and July 2021. The cases were divided into the training cohorts and test cohorts in a 9:1 ratio. The mRMR approach and stepwise forward logistic regression technique were used for feature selection, followed by the multivariate logistic regression technique for building radiomics signatures in the training cohort. The confusion matrix and receiver operating characteristic (ROC) analysis were used for accessing the prediction efficacy of the radiomics models. The radiomics models, which consist of six features, achieved predictive accuracy with the area under the ROC curve (AUC) of 0.713 in the test set for predicting lymph node metastasis. CONCLUSION: The CEUS-based radiomics is promising to be developed as a reliable noninvasive tool for predicting ALN status.

Construction of 2-azidacetic acid functionalized high-crystallinity fluorescent covalent organic framework: Applications in mitoxantrone and Fe3+ sensing and adsorption.

Due to the dual functions of fluorescence detection and adsorption, fluorescent covalent organic frameworks (COFs) have attracted significant attention. However, common fluorescent COFs often exhibit unsatisfactory fluorescence properties and selectivity, coupled with poor solution dispersibility, which limit their effectiveness in detection and adsorption applications. In response, a novel post-modified fluorescent COF (named AZC-COF) was synthesized by connecting a fluorescent COF (COF-TB) with 2-azidacetic acid through a copper-catalyzed aide-alkyne cycloaddition (CuAAC) reaction. AZC-COF demonstrated excellent solution dispersibility and robust green fluorescence, boasting an absolute fluorescence quantum yield (QY) of 7.58%, which was 13.5 times higher than that of COF-TB. Furthermore, leveraging the active carboxylic acid and triazole sites, AZC-COF exhibited remarkable binding abilities for mitoxantrone (MIX) and Fe3+, enabling sensitive detection and efficient adsorption of them. In contrast, due to the absence of these functional sites, COF-TB showed poor detection and enrichment capabilities for MIX and Fe3+. The impressive detection and adsorption efficiencies of MIX and Fe3+ in environmental water, aquatic organism (fish) and plasma samples underscore the potential of AZC-COF as a detection-adsorption platform. Additionally, AZC-COF demonstrated low toxicity and hemolytic activity, alongside promising potential for cell imaging and detection of MIX and Fe3+, highlighting its considerable application prospect in biological systems.

Achieving rapid start-up and efficient nitrogen removal of partial-denitrification/anammox process using organic matter in brewery wastewater as carbon source.

To find a cost-efficient carbon source for the partial denitrification/anaerobic ammonium oxidation (anammox) (PD/A) process, the practicability of using the organic matter contained in brewery wastewater as carbon source was investigated. Quick self-enrichment of denitrifying bacteria was achieved by supplying brewery wastewater as organic carbon source and using the mature anammox sludge as the seeding sludge. The PD/A process was successfully established after 33-day operation and then the average total nitrogen removal efficiency reached 92.29% when the influent CODCr: NO3--N: NH4+-N ratio was around 2.5: 1.0: 0.67. The relative abundance of Thauera increased from 0.03% in the seeding sludge to 54.29% on day 110, whereas Candidatus brocadia decreased from 30.66% to 2.08%. The metagenomic analysis indicated that the sludge on day 110 contained more nar and napA (total of 41.24%) than nirK and nirS (total of 11.93%). Thus NO2--N was accumulated efficiently in the process of denitrification and sufficient NO2--N was supplied for anammox bacteria in the PD/A process. Using brewery wastewater as carbon source not only saved the cost of nitrogen removal but also converted waste into resource and reduced the treatment expense of brewery wastewater.

Chemoenzymatic Oxidation of Labdane and Formal Synthesis of Nimbolide.

In nature, basic terpene skeletons are produced and subsequently undergo enzymatic or nonenzymatic oxidative transformations, leading to diverse structural variations. To date, thousands of natural products featuring a variety of oxidation patterns have been isolated solely from the labdane family. This work describes a strategy for the comprehensive introduction of oxidation states into the labdane core by employing a combination of enzyme library screening, directed evolution, and sequential chemical oxidation processes. Furthermore, we showcase the functional viability of our chemoenzymatic approach by accomplishing a formal synthesis of nimbolide, highlighting its potential for streamlining the synthesis of complex natural products.

Automatic Graph Topology-Aware Transformer.

Existing efforts are dedicated to designing many topologies and graph-aware strategies for the graph Transformer, which greatly improve the model's representation capabilities. However, manually determining the suitable Transformer architecture for a specific graph dataset or task requires extensive expert knowledge and laborious trials. This article proposes an evolutionary graph Transformer architecture search (EGTAS) framework to automate the construction of strong graph Transformers. We build a comprehensive graph Transformer search space with the micro-level and macro-level designs. EGTAS evolves graph Transformer topologies at the macro level and graph-aware strategies at the micro level. Furthermore, a surrogate model based on generic architectural coding is proposed to directly predict the performance of graph Transformers, substantially reducing the evaluation cost of evolutionary search. We demonstrate the efficacy of EGTAS across a range of graph-level and node-level tasks, encompassing both small-scale and large-scale graph datasets. Experimental results and ablation studies show that EGTAS can construct high-performance architectures that rival state-of-the-art manual and automated baselines.

Causal Inference Meets Deep Learning: A Comprehensive Survey.

Deep learning relies on learning from extensive data to generate prediction results. This approach may inadvertently capture spurious correlations within the data, leading to models that lack interpretability and robustness. Researchers have developed more profound and stable causal inference methods based on cognitive neuroscience. By replacing the correlation model with a stable and interpretable causal model, it is possible to mitigate the misleading nature of spurious correlations and overcome the limitations of model calculations. In this survey, we provide a comprehensive and structured review of causal inference methods in deep learning. Brain-like inference ideas are discussed from a brain-inspired perspective, and the basic concepts of causal learning are introduced. The article describes the integration of causal inference with traditional deep learning algorithms and illustrates its application to large model tasks as well as specific modalities in deep learning. The current limitations of causal inference and future research directions are discussed. Moreover, the commonly used benchmark datasets and the corresponding download links are summarized.

Development and Validation of a Contrast-Enhanced US VI-RADS for Evaluating Muscle Invasion in Bladder Cancer.

Background Contrast-enhanced US (CEUS) can be used preoperatively for evaluating muscle invasion in bladder cancer, which is important for determining appropriate treatment. However, diagnostic criteria for assessing this at CEUS have not been standardized. Purpose To develop and validate a CEUS Vesical Imaging Reporting and Data System (VI-RADS) for evaluating muscle invasion in bladder cancer. Materials and Methods This single-center prospective study consecutively enrolled patients with suspected bladder cancer. Participants underwent transabdominal or intracavity CEUS between July 2021 and May 2023. Participants were divided into a training set and a validation set at a 2:1 ratio based on the chronologic order of enrollment. The training set was used to identify major imaging features to include in CEUS VI-RADS, and the likelihood of muscle invasion per category was determined using a pathologic reference standard. The optimal VI-RADS category cutoff for muscle invasion was determined with use of the maximum Youden index. The validation set was assessed by novice and expert readers and used to validate the diagnostic performance and interreader agreement of the developed system. Results Overall, 126 participants (median age, 64 years [IQR, 57-71 years]; 107 male) and 67 participants (median age, 64 years [IQR, 56-69 years]; 49 male) were included in the training and validation set, respectively. In the training set, the optimal CEUS VI-RADS category cutoff for muscle invasion was VI-RADS 4 or higher (Youden index, 0.77). In the validation set, CEUS VI-RADS achieved good performance for both novice and expert readers (area under the receiver operating characteristic curve, 0.80 [95% CI: 0.70, 0.90] vs 0.88 [95% CI: 0.80, 0.97]; P = .09). The interreader agreement regarding the evaluation of CEUS VI-RADS category was 0.77 (95% CI: 0.65, 0.85) for novice readers, 0.87 (95% CI: 0.79, 0.92) for expert readers, and 0.78 (95% CI: 0.70, 0.84) for all readers. Conclusion The developed CEUS VI-RADS showed good performance and interreader agreement for the assessment of muscle invasion in bladder cancer. Chinese Clinical Trial Registry no. ChiCTR2100049435 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Morrell in this issue.

Exposure-response relationships of mirvetuximab soravtansine in patients with folate receptor-α-positive ovarian cancer: Justification of therapeutic dose regimen.

AIMS: This study aimed to investigate exposure-response (ER) relationships in efficacy and safety for mirvetuximab soravtansine (MIRV) which is a first-in-class antibody-drug conjugate approved for the treatment of folate receptor-α-positive platinum-resistant ovarian cancer. METHODS: MIRV was characterized in 4 clinical studies. Exposure metrics for MIRV, its payload and a metabolite were derived from a population pharmacokinetic model. Efficacy was analysed in MIRV-treated patients (n = 215) in a recent confirmatory, randomized, chemotherapy-controlled MIRASOL trial and safety was evaluated in patients pooled across all 4 clinical studies (n = 757). RESULTS: In the MIRASOL trial (NCT04209855), MIRV demonstrated significant benefit over chemotherapy in progression-free survival (PFS), objective response rate (ORR) and overall survival (OS). The most common adverse events (AEs) included ocular disorders, peripheral neuropathy and pneumonitis. For PFS, ORR and OS, the trough concentration of MIRV was the predictor consistently found in ER models for efficacy. In contrast, for ocular AEs (as well as the time to onset of ocular AEs) and peripheral neuropathy, the area under the concentration-time curve (AUC) of MIRV was identified as the exposure metric in ER models for safety. No exposure parameters were found to correlate with pneumonitis. Covariates in all models did not show clinically meaningful impact on efficacy or safety. Logistic regression models for ORR and ocular AEs based on AUC of MIRV were used to justify the clinical dose regimen approved for MIRV. CONCLUSION: The trough concentration of MIRV correlated with efficacy whereas the AUC of MIRV was associated with major AEs. The ER relationships supported the selected therapeutic dose regimen.

Comprehensive proteomic characterization of urethral stricture disease in the Chinese population.

Background: Male urethral stricture disease (USD) is predominantly characterized by scar formation. There are few effective therapeutic drugs, and comprehensive molecular characterizations of USD formation remain undefined. Methods: The proteomic profiling of twelve scar tissues and five matched normal adjacent tissues (NATs). Proteomic analysis methods were applied to explore the molecular characterizations of USD formation, including uncovering mechanistic pathways and providing novel biomarkers for scar formation. Results: Comparative proteomic analysis showed that the extracellular matrix (ECM) and complement cascade signaling were predominant in scar tissues. COL11A1 and CD248 significantly contributed to the accumulation of ECM components. Our study presented diverse molecular mechanisms of scar formation across different ages and suggested the potential effects of PXK in Age 1 (<45) patients. Furthermore, immune infiltration studies indicated the therapeutic potential of inhibiting the complement system (C4A, C4B) in Age 2 (≥45) patients, providing a potential clinical strategy for USD. Conclusion: This study illustrated the pathogenesis of USD formation and the diverse characteristics of USD patients with different ages, enhancing our understanding of the disease's pathogenesis and providing a valuable resource for USD treatment.

Nature-Inspired Intelligent Computing: A Comprehensive Survey.

Nature, with its numerous surprising rules, serves as a rich source of creativity for the development of artificial intelligence, inspiring researchers to create several nature-inspired intelligent computing paradigms based on natural mechanisms. Over the past decades, these paradigms have revealed effective and flexible solutions to practical and complex problems. This paper summarizes the natural mechanisms of diverse advanced nature-inspired intelligent computing paradigms, which provide valuable lessons for building general-purpose machines capable of adapting to the environment autonomously. According to the natural mechanisms, we classify nature-inspired intelligent computing paradigms into 4 types: evolutionary-based, biological-based, social-cultural-based, and science-based. Moreover, this paper also illustrates the interrelationship between these paradigms and natural mechanisms, as well as their real-world applications, offering a comprehensive algorithmic foundation for mitigating unreasonable metaphors. Finally, based on the detailed analysis of natural mechanisms, the challenges of current nature-inspired paradigms and promising future research directions are presented.

Identification of differentially expressed genes, pathways, and immune infiltration in diabetes.

This study aimed to perform exhaustive bioinformatic analysis by using GSE29221 micro-array maps obtained from healthy controls and Type 2 Diabetes (T2DM) patients. Raw data are downloaded from the Gene Expression Omnibus database and processed by the limma package in R software to identify Differentially Expressed Genes (DEGs). Gene ontology functional analysis and Kyoto Gene Encyclopedia and Genome Pathway analysis are performed to determine the biological functions and pathways of DEGs. A protein interaction network is constructed using the STRING database and Cytoscape software to identify key genes. Finally, immune infiltration analysis is performed using the Cibersort method. This study has implications for understanding the underlying molecular mechanism of T2DM and provides potential targets for further research.

Artemisinin ameliorates thyroid function and complications in adult male hypothyroid rats via upregulation of the L1 cell adhesion molecule.

BACKGROUND: Hypothyroidism, a common worldwide syndrome caused by insufficient thyroid hormone secretion, affects number of people at different ages. Artemisinin (ART), a well-known effective agent in the treatment of malaria, also has anti-oxidative stress functions in various diseases. The L1 cell adhesion molecule exerts multiple protective roles in diseased systems. The aim of the present study was to evaluate the role of ART in adult male hypothyroid rats and the underlying mechanisms. METHODS: The propylthiouracil (PTU) rat model was treated with or without 5 mg/kg ART and with or without L1 short-interfering RNA (siRNA), followed by the experiments to determine the effect of ART on thyroid function, depression and anxiety, cognition impairments, liver, kidney and heart functions, and oxidative stress. RESULTS: In the current study, it was shown that ART can ameliorate thyroid function, mitigate depression and anxiety symptoms, attenuate cognition impairments, improve liver, kidney and heart functions, and inhibit oxidative stress; however, the effects exerted by ART could not be observed when L1 was silenced by L1 siRNA. CONCLUSION: These results indicated that ART can upregulate the L1 cell adhesion molecule to ameliorate thyroid function and the complications in adult male hypothyroid rats, laying the foundation for ART to be a novel strategy for the treatment of hypothyroidism.

An innovative walnut cracker: Self-grading and multi-station extrusion mechanism with high efficiency.

The walnut cracking process is the most critical and delicate step for achieving high-quality kernels. The traditional method for cracking (manually) is labor-intensive, time-consuming, and tedious. The existing cracking approaches are low production efficiency and serious walnut kernel breakage. Increasing cracking efficiency with minimum kernel breakage has been a challenging issue in the preliminary processing of walnuts. Therefore, this study develops an innovative walnut cracker with self-grading and multi-station extrusion, combined with theoretical investigation and experiment verification. First, a statistical analysis of walnut physical properties was conducted, including dimensions, shell thickness as well as shape characteristics. The mechanical properties of walnut cracking were examined by a series of experiments. Based on mechanical theory, a grading mechanism was designed for preliminary processing before walnut cracking. Then a shaftless screw conveying mechanism and an extrusion cracking mechanism were developed. To evaluate the cracker's performance, a comprehensive examination was carried out. The experiments yielded impressive results, with a grading rate of 87.3%, a shell-breaking rate of 91.50%, and a kernel-exposed rate of 84.72%. These outcomes signify a substantial improvement in production efficiency while minimizing kernel breakage. The developed walnut cracker plays a crucial role in walnut processing and kernel extraction, thereby elevating economic value. PRACTICAL APPLICATION: A self-grading multi-station extrusion walnut cracker is developed, which includes a grading mechanism with a shaftless screw conveyor and a grid-type trommel screen for conveying and classifying walnuts. This cracker can adapt to different walnut varieties by changing the gap-adjusting guide to control the breaking gap. Compared to similar extrusion-type walnut crackers, the developed cracker not only incorporates preliminary classification but also exhibits superior performance. HIGHLIGHTS: A novel multi-station extrusion mechanism for walnuts cracking is developed. The cracker can accommodate various walnut sizes for self-grading and screening. The design with semi-arc plates converts extrusion force into alternating stress. The shell-breaking rate and kernel-exposed rate achieves 91.50% and 84.72%.

The relationship between NLR, LDL-C/HDL-C, NHR and coronary artery disease.

OBJECTIVE: Chronic inflammation and dyslipidemia are key risk factors for atherosclerotic cardiovascular diseases. We retrospectively explored the association between the neutrophil to lymphocyte ratio (NLR), the ratio of low-density lipoprotein cholesterol (LDL-C) to high-density lipoprotein cholesterol (HDL-C), and the neutrophil to HDL-C ratio (NHR), and the severity of coronary lesions in patients with acute coronary syndrome (ACS). METHOD: In June 2023, we selected 1210 patients who were diagnosed with ACS based on chest pain from January 2017 to December 2022. Of these, 1100 patients with abnormal coronary angiography were categorized into the experimental group, and 110 patients with normal coronary angiography were classified as the control group. We collected routine blood tests, lipid profiles, and coronary angiography results at admission (before coronary angiography). Patients were then stratified into a control group (Gensini score = 0) and an experimental group (Gensini score = 0) based on the Gensini score. The experimental group was further divided into a low score group (Gensini score < 69) and a high score group (Gensini score ≥ 69). RESULT: 1. Statistically significant differences were observed between the control and experimental groups in terms of gender, age, body mass index (BMI), hypertension, diabetes, smoking history, and counts of neutrophils (NEU), lymphocytes (LYM), monocytes (MON), eosinophils (EOS), red cell distribution width (RDW), total cholesterol (TC), HDL-C, LDL-C, NLR, LDL-C/HDL-C, and NHR (P<0.05). Furthermore, differences in BMI, hypertension, diabetes, smoking history, NEU, LYM, MON, TC, triglyceride (TG), HDL-C, LDL-C, NLR, LDL-C/HDL-C, and NHR were significant between the low and high score groups (P<0.05). 2. NEU, LYM, MON, TC, HDL-C, LDL-C, NLR, LDL-C/HDL-C, and NHR showed significant correlations with the Gensini score (r>0.2, P<0.05), with NLR and LDL-C/HDL-C showing the strongest correlations (r = 0.822, P = 0.000). 3. The Receiver Operating Characteristic (ROC) curve indicated that the combination of NLR and LDL-C/HDL-C had superior sensitivity and specificity in predicting the severity of coronary lesions, with a significant difference (P<0.05). The sensitivity was 87.1%, the specificity was 90.9%, and the cut-off point was 2.04. 4. A predictive model was developed based on the ratio of NLR and LDL-C/HDL-C to the Gensini score. The final model score was calculated as 6.803 + 7.029NLR + 13.079LDL-C/HDL-C (R2 = 0.708). CONCLUSION: Compared to NLR, LDL-C/HDL-C, and NHR, the combined NLR and LDL-C/HDL-C ratio is a more accurate marker for assessing the severity of coronary artery disease in ACS patients. Its convenience and effectiveness make it a promising tool for early assessment, timely risk stratification, and appropriate clinical intervention, ultimately improving clinical outcomes for ACS patients.

Gonadal hormones and metabolic syndrome in middle-aged and elderly males: results from a prospective cohort study in China.

Background: Research has shown that gonadal hormones are involved in metabolic pathways relevant to metabolic syndrome (MetS). Nevertheless, no longitudinal study has been conducted on the association between SHBG and MetS in Chinese. The objective of our study was to determine whether there is any association between middle-aged and elderly males in China. Methods: A total of 531 eligible male subjects, aged above 40 years or older, without MetS at baseline, were recruited. Sex hormone binding globulin (SHBG), total testosterone (TT), follicle-stimulating hormone (FSH), and luteinizing hormone (LH) were measured. A harmonized definition and recommended thresholds for the Chinese population were used to determine metabolic syndrome. Results: During 3.2 years of follow-up, 20.7% of subjects had developed MetS. Compared with the non-MetS group, subjects in the new-onset MetS group had significantly lower SHBG (43.5 nmol/L [28.8, 74.9] vs 53.7nmol/L [33.8, 115.0], P=0.0018), TT (18.1nmol/L [13.6-21.7] vs 19.5nmol/L[15.0-23.6], P=0.0204), and LH (5.13mIU/L [3.63-7.29] vs 5.87mIU/L [4.05-8.36]) at baseline. The incidence of MetS was decreased according to elevated SHBG quartiles (Q1:26.9%, Q2:22.7%, Q3:21.1%, Q4:12.1%, P for trend =0.0035), TT (Q1: 25.2%, Q2:23.7%, Q3: 17.3%, Q4: 16.7%, P for trend=0.0425), and LH (Q1:25.0%, Q2:21.8%, Q3: 21.8%, Q4: 14.3%, P for trend=0.0411). Compared with those in quartile 4, the OR[CI] of incident MetS for participants in Quartile 1 was 2.33[1.13-4.79] after multiple adjustments. But associations between incident MetS and different quartiles of LH, TT, and FSH were not observed after multiple adjustments. In the subgroup analyses, the significant association between SHBG level and Mets was detected in subjects over 60 years or older, with normal BMI, without insulin resistance, and with eGFR ≥90 mL/min per 1.73m2. Conclusion: Compared with TT, LH, and FSH, a lower level of SHBG is significantly related to the incidence of MetS among middle-aged and elderly males in China.

A Spatial-Spectral Relation-Guided Fusion Network for Multisource Optical RS Image Classification.

Multisource optical remote sensing (RS) image classification has obtained extensive research interest with demonstrated superiority. Existing approaches mainly improve classification performance by exploiting complementary information from multisource data. However, these approaches are insufficient in effectively extracting data features and utilizing correlations of multisource optical RS images. For this purpose, this article proposes a generalized spatial-spectral relation-guided fusion network ( S2 RGF-Net) for multisource optical RS image classification. First, we elaborate on spatial-and spectral-domain-specific feature encoders based on data characteristics to explore the rich feature information of optical RS data deeply. Subsequently, two relation-guided fusion strategies are proposed at the dual-level (intradomain and interdomain) to integrate multisource image information effectively. In the intradomain feature fusion, an adaptive de-redundancy fusion module (ADRF) is introduced to eliminate redundancy so that the spatial and spectral features are complete and compact, respectively. In interdomain feature fusion, we construct a spatial-spectral joint attention module (SSJA) based on interdomain relationships to sufficiently enhance the complementary features, so as to facilitate later fusion. Experiments on various multisource optical RS datasets demonstrate that S2 RGF-Net outperforms other state-of-the-art (SOTA) methods.

Deciphering the maize gene ZmGF14-3: implications for plant height based on co-expression networks.

The evolutionary analysis showed that the GF14 family was conserved, however, there was limited evidence linking GF14s to plant height. In our investigations, we discovered a co-expression relationship between ZmGF14s and functionally characterized genes linked to plant height. In the co-expression network, we identified ZmGF14-3, a gene expression exhibiting a positive correlation with plant height in three maize varieties, we postulated that this gene could be intimately linked to plant height development. Subsequently, we cloned ZmGF14-3 from the maize B73 inbred line and overexpressed it in Arabidopsis, resulting in markedly dwarfed transgenic phenotypes. Measurements of endogenous phytohormones disclosed a significant reduction in concentrations of Gibberellic Acid 7 (GA7) and Indole-3-Acetic Acid (IAA) in the overexpressed Arabidopsis, furthermore, qPCR results highlighted a pronounced decrease in the expression levels of plant height-related genes when compared to the wild type, therefore, it is plausible to posit that ZmGF14-3 plays a pivotal role in regulating the growth and development of maize through interactions with various phytohormone-related genes. Thus, delving into the potential interactions between ZmGF14-3 and these genes holds the promise of yielding valuable insights into the molecular mechanisms underpinning plant height development in maize.

Response of soil nematode community structure and metabolic footprint to nitrogen addition in alfalfa fields on the Loess Plateau.

Nematodes serve as key indicators of soil health in ecological studies. Therefore, the current study examined the community structure and metabolic footprint of soil nematodes in alfalfa fields across varying levels of N supply in the semi-arid Loess Plateau. The findings offer theoretical guidance for the sustainable management of artificial alfalfa grasslands in this region. The research was based on alfalfa fields with different N application rates (0, 50, 100, 150 kg/ha2) as the research object, The shallow plate method was used to separate and extract soil nematodes, identify soil nematode groups, calculate ecological function index and metabolic footprint, and identify indicator species. A total of 6346 nematodes were isolated in this study, belonging to 27 genera and 19 families. Notably, the plant parasitic nematode Helicotylenchus was predominant. As N addition increased, the plant parasitic index (PPI) increased significantly. A N50 application significantly enhanced the soil nematode diversity index ( H ) and the free-living index (MI). The findings showcased a noticeable decrease in disturbance within the N50 soil nematode community. This resulted in a mature and stable community structure primarily attributed to the heightened abundance of omnivorous/predatory nematodes. Across various N levels, soil nematode communities underwent significant alterations in the soil food web structure through shifts in their metabolic footprint. Future strategies should focus on refining N management practices and integrating sustainable approaches like crop rotation and pest management. These efforts will contribute to guidelines ensuring artificial alfalfa grasslands lasting health and productivity.