Flexible wearable sensors for crop monitoring: a review.

Crops were the main source of human food, which have met the increasingly diversified demand of consumers. Sensors were used to monitor crop phenotypes and environmental information in real time, which will provide a theoretical reference for optimizing crop growth environment, resisting biotic and abiotic stresses, and improve crop yield. Compared with non-contact monitoring methods such as optical imaging and remote sensing, wearable sensing technology had higher time and spatial resolution. However, the existing crop sensors were mainly rigid mechanical structures, which were easy to cause damage to crop organs, and there were still challenges in terms of accuracy and biosafety. Emerging flexible sensors had attracted wide attention in the field of crop phenotype monitoring due to their excellent mechanical properties and biocompatibility. The article introduced the key technologies involved in the preparation of flexible wearable sensors from the aspects of flexible preparation materials and advanced preparation processes. The monitoring function of flexible sensors in crop growth was highlighted, including the monitoring of crop nutrient, physiological, ecological and growth environment information. The monitoring principle, performance together with pros and cons of each sensor were analyzed. Furthermore, the future opportunities and challenges of flexible wearable devices in crop monitoring were discussed in detail from the aspects of new sensing theory, sensing materials, sensing structures, wireless power supply technology and agricultural sensor network, which will provide reference for smart agricultural management system based on crop flexible sensors, and realize efficient management of agricultural production and resources.

Comprehensive quantitative radiogenomic evaluation reveals novel radiomic subtypes with distinct immune pattern in glioma.

BACKGROUND: Accurate classification of gliomas is critical to the selection of immunotherapy, and MRI contains a large number of radiomic features that may suggest some prognostic relevant signals. We aim to predict new subtypes of gliomas using radiomic features and characterize their survival, immune, genomic profiles and drug response. METHODS: We initially obtained 341 images of 36 patients from the CPTAC dataset for the development of deep learning models. Further 1812 images of 111 patients from TCGA_GBM and 152 images of 53 patients from TCGA_LGG were collected for testing and validation. A deep learning method based on Mask R-CNN was developed to identify new subtypes of glioma patients and compared the survival status, immune infiltration patterns, genomic signatures, specific drugs, and predictive models of different subtypes. RESULTS: 200 glioma patients (mean age, 33 years ± 19 [standard deviation]) were enrolled. The accuracy of the deep learning model for identifying tumor regions achieved 88.3 % (98/111) in the test set and 83 % (44/53) in the validation set. The sample was divided into two subtypes based on radiomic features showed different prognostic outcomes (hazard ratio, 2.70). According to the results of the immune infiltration analysis, the subtype with a poorer prognosis was defined as the immunosilencing radiomic (ISR) subtype (n = 43), and the other subtype was the immunoactivated radiomic (IAR) subtype (n = 53). Subtype-specific genomic signatures distinguished celllines into ISR celllines (n = 9) and control celllines (n = 13), and identified eight ISR-specific drugs, four of which were validated by the OCTAD database. Three machine learning-based classifiers showed that radiomic and genomic co-features better predicted the radiomic subtypes of gliomas. CONCLUSIONS: These findings provide insights into how radiogenomic could identify specific subtypes that predict prognosis, immune and drug sensitivity in a non-invasive manner.

Hyperspectral imaging combined with GA-SVM for maize variety identification.

The demand for identification of maize varieties has increased dramatically due to the phenomenon of mixed seeds and inferior varieties pretending to be high-quality varieties continuing to occur. It is urgent to solve the problem of efficient and accurate identification of maize varieties. A hyperspectral image acquisition system was used to acquire images of maize seeds. Regions of interest (ROI) with an embryo size of 10 × 10 pixel were extracted, and the average spectral information in the range of 949.43-1709.49 nm was intercepted for the subsequent study in order to eliminate random noise at both ends. Savitzky-Golay (SG) smoothing algorithm and multiple scattering correction (MSC) were used to pretreat the full-band spectrum. The feature wavelengths were screened by successive projection algorithms (SPA), competitive adaptive reweighted sampling (CARS) single screening, and two combinations of CARS-SPA and CARS + SPA, respectively. Support vector machines (SVMs) and models optimized based on genetic algorithm (GA), particle swarm optimization (PSO) were established by using full bands (FB) and feature bands as the model input. The results showed that the MSC-(CARS-SPA)-GA-SVM model had the best performance with 93.00% of the test set accuracy, 8 feature variables, and a running time of 24.45 s. MSC pretreatment can effectively eliminate the scattering effect of spectral data, and the feature wavelengths extracted by CARS-SPA can represent all wavelength information. The study proved that hyperspectral imaging combined with GA-SVM can realize the identification of maize varieties, which provided a theoretical basis for maize variety classification and authenticity identification.

Systemic immune-inflammation index is associated with cardiac complications following acute ischemic stroke: A retrospective single-center study.

BACKGROUND: Stroke-induced heart syndrome is a feared complication of ischemic stroke, that is commonly encountered and has a strong association with unfavorable prognosis. More research is needed to explore underlying mechanisms and inform clinical decision making. This study aims to explore the relationship between the early systemic immune-inflammation (SII) index and the cardiac complications after acute ischemic stroke. METHODS: Consecutive patients with acute ischemic stroke were prospectively collected from January 2020 to August 2022 and retrospectively analyzed. We included subjects who presented within 24 hours after symptom onset and were free of detectable infections or cancer on admission. SII index [(neutrophils × platelets/ lymphocytes)/1000] was calculated from laboratory data at admission. RESULTS: A total of 121 patients were included in our study, of which 24 (19.8 %) developed cardiac complications within 14 days following acute ischemic stroke. The SII level was found higher in patients with stroke-heart syndrome (p<.001), which was an independent predictor of stroke-heart syndrome (adjusted odds ratio 5.089, p=.002). CONCLUSION: New-onset cardiovascular complications diagnosed following a stroke are very common and are associated with early SII index.

Effects of Auricularia auricula-judae (Bull.) Quél. polysaccharide acid hydrolysate on glucose metabolism in diabetic mice under oxidative stress.

BACKGROUND: Oxidative stress can lead to uncontrolled glucose metabolism and, thus, diabetes. Auricularia auricula-judae (Bull.) Quél. polysaccharides possess biological activities, such as antioxidant and hypoglycemic effects, but their mechanism of their acid hydrolysates on oxidative stress-injured glucose metabolism disorders is unclear. PURPOSE: Using diabetic mice, we investigated the effect of the acid hydrolysate of polysaccharides from Auricularia auricula-judae (Bull.) Quél. on improving diabetes. STUDY DESIGN AND METHODS: The structural information of sample polysaccharides was measured by high performance gel permeation chromatography, nuclear magnetic resolution, and high performance liquid chromatography. The diabetic model was established by intraperitoneal injection of streptozotocin. For eight consecutive weeks, the mice were orally administered sample polysaccharides (100, 200, and 300 mg/kg b.w. per day) for intervention. The improvement effect of the samples on diabetes was explored by detecting the changes in biochemical indicators in mice, and the underlying mechanism was studied by transcriptomic and metabolomic analysis. RESULTS: The results showed that acid hydrolysate of Auricularia auricula-judae (Bull.) Quél. polysaccharides consisted mainly of mannose, xylose, glucuronic acid, and glucose; its weight-averaged molecular weight was 6.3842 × 104 Dalton, its number average molecular weight was 2.9594 × 104 Dalton; and the molecule contained α-Glc(1→4)-, ß-Glc(1→3)-, and ß-Man(1→4)-linked glycosidic bonds. A total of 100 mg/kg b.w. per day sample was the best intervention concentration. After eight weeks of intervention, the sample polysaccharides significantly reduced dynamic blood glucose and serum lipids, enhanced antioxidant enzyme activities, promoted glucagon like peptide-1 and insulin secretion, improved insulin sensitivity and alleviated insulin resistance in diabetic mice. Transcriptomic and metabolomic analyses showed that sample polysaccharides was able to ameliorate disorders of glucose metabolism by modulating gene expression such as glucokinase; and modulate the state of oxidative stress in mice in vivo by regulating the glutathione metabolism pathway. CONCLUSION: Acid hydrolysate of Auricularia auricula-judae (Bull.) Quél. polysaccharides improved glucose metabolism disorders by slowing down the oxidative stress injury in mice, thereby alleviating diabetes. This study provided a basis for determining the underlying mechanism of the antidiabetic effect of Auricularia auricula-judae (Bull.) Quél. polysaccharides, which would significantly improve the deep development and application of these materials in diabetes control.

Gefitinib Induces Apoptosis in NSCLC Cells by Promoting Glutaminolysis and Inhibiting the MEK/ERK Signaling Pathway.

BACKGROUND: Over 80% of lung cancer cases constitute non-small cell lung cancer (NSCLC), making it the most prevalent type of lung cancer globally and the leading cause of cancer-related deaths. The treatment of NSCLC patients with gefitinib has demonstrated promising initial efficacy. However, the underlying mechanism remains unclear. This study aims to investigate how gefitinib affects the mitogen-activated protein kinase kinase (MEK)/extracellular regulated protein kinases (ERK) signaling pathway-mediated growth and death of NSCLC cells. METHODS: In this study, the NSCLC cell line A549 was cultured in vitro and divided into a control group and a gefitinib group. The viability of the A549 cells was assessed using the methylthiazolyldiphenyl-tetrazolium bromide (MTT) assay. Flow cytometry was employed to detect apoptosis in A549 cells, and the expression of glutamate dehydrogenase (GDH1) mRNA in these cells was determined using real-time quantitative PCR (RT-PCR). Western blotting was utilized to evaluate the protein expression levels of key components in the MEK/ERK signaling pathway, including phospho-MEK1/2, MEK1/2, phospho-ERK1/2, and ERK1/2. Additionally, intracellular glutamine content in A549 cells was measured using a colorimetric method. RESULTS: In contrast to the control group, the proliferation of A549 cells, the transcription level of glutamate dehydrogenase (GDH1), the intracellular glutamine content, and the protein expression levels of phospho-MEK1/2 and phospho-ERK1/2 were significantly lower in the gefitinib group. Moreover, apoptosis markedly increased. CONCLUSIONS: Gefitinib expedites apoptosis and diminishes proliferation in the NSCLC cell line A549 by downregulating the epidermal growth factor receptor (EGFR)/MEK/ERK signaling pathway. This effect is accomplished by fostering the expression of GDH1 to augment glutaminolysis in A549 cells.

Dishevelled Segment Polarity Protein 3 (DVL3) Induced by Bacterial LPS Promotes the Proliferation and Migration of Prostate Cancer Cells through the TLR4 Pathway.

BACKGROUND: Chronic inflammation is associated with various malignant tumors. Bacterial lipopolysaccharides (LPSs) play a significant part in the event and development of prostate cancer. Dishevelled segment polarity protein 3 (DVL3) is a shared component of the Wnt/ß-catenin and Notch signaling pathways, which are involved in tumor progression, chemoresistance, and maintenance of stem cell-like properties. According to reports, prostatic cancer cell invasion and proliferation are mediated by toll-like receptor 4 (TLR4). However, the role and regulation of DVL3 in prostate cancer and its relationship with TLR4 remain unclear. METHODS: Survival curves were plotted to evaluate the relationship between DVL3 expression and prognosis in patients with prostate cancer. DVL3 was silenced in PC3 and DU145 cells using small interfering RNAs (siRNAs). Subsequently, cell counting kit-8 (CCK-8) assay, colony formation assay, transwell migration assay, and quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) were performed to investigate the role of DVL3 in cell proliferation and migration in vitro. The protein markers of potential pathways were analyzed via western blotting. RESULTS: DVL3 expression was linked to prognosis in patients with prostate cancer; In particular, patients with high DVL3 expression had a poor prognosis. LPS stimulation increased (p < 0.01) the expression of DVL3 in PC3 cells. DVL3 regulated tumor cell proliferation and migration by mediating the increase (p < 0.01) in TLR4 expression. Knockout of TLR4 validated that TLR4 played a crucial role in LPS-induced DVL3 expression. Silencing of DVL3 decreased (p < 0.01) the LPS-induced proliferation and migration of PC3 cells. CONCLUSIONS: Bacterial LPS-induced DVL3 promoted the multiplication and migration of prostate cancer cells through the TLR4 pathway. This study offers a valuable reference for the development and clinical application of targeted drugs for prostate cancer.

Achieving widely distributed feature matches using flattened-affine-SIFT algorithm for fisheye images.

Performing correction first is the most common methods to address feature matching issues for fisheye images, but corrections often result in significant loss of scene details or stretching of images, leaving peripheral regions without matches. In this paper, we propose a novel approach, named flattened-affine-SIFT, to find widely distributed feature matches between stereo fisheye images. Firstly, we establish a new imaging model that integrates a scalable model and a hemisphere model. Utilizing the extensibility of the imaging model, we design a flattened array model to reduce the distortion of fisheye images. Additionally, the affine transformation is performed on the flattened simulation images, which are computed using the differential expansion and the optimal rigidity transformation. Then feature matches are extracted and matched from the simulated images. Experiments on indoor and outdoor fisheye images show that the proposed algorithm can find a large number of reliable feature matches. Moreover, these matches tend to be dispersed over the entire effective image, including peripheral regions with dramatic distortion.

Dishevelled Segment Polarity Protein 3 (DVL3) Induced by Bacterial LPS Promotes the Proliferation and Migration of Prostate Cancer Cells through the TLR4 Pathway

Background: Chronic inflammation is associated with various malignant tumors. Bacterial lipopolysaccharides (LPSs) play a significant part in the event and development of prostate cancer. Dishevelled segment polarity protein 3 (DVL3) is a shared component of the Wnt/β-catenin and Notch signaling pathways, which are involved in tumor progression, chemoresistance, and maintenance of stem cell-like properties. According to reports, prostatic cancer cell invasion and proliferation are mediated by toll-like receptor 4 (TLR4). However, the role and regulation of DVL3 in prostate cancer and its relationship with TLR4 remain unclear. Methods: Survival curves were plotted to evaluate the relationship between DVL3 expression and prognosis in patients with prostate cancer. DVL3 was silenced in PC3 and DU145 cells using small interfering RNAs (siRNAs). Subsequently, cell counting kit-8 (CCK-8) assay, colony formation assay, transwell migration assay, and quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) were performed to investigate the role of DVL3 in cell proliferation and migration in vitro. The protein markers of potential pathways were analyzed via western blotting. Results: DVL3 expression was linked to prognosis in patients with prostate cancer; In particular, patients with high DVL3 expression had a poor prognosis. LPS stimulation increased (p < 0.01) the expression of DVL3 in PC3 cells. DVL3 regulated tumor cell proliferation and migration by mediating the increase (p < 0.01) in TLR4 expression. Knockout of TLR4 validated that TLR4 played a crucial role in LPS-induced DVL3 expression. Silencing of DVL3 decreased (p < 0.01) the LPS-induced proliferation and migration of PC3 cells. Conclusions: Bacterial LPS-induced DVL3 promoted the multiplication and migration of prostate cancer cells through the TLR4 pathway. This study offers a valuable reference for the development and clinical application of targeted drugs for prostate cancer. (AU)

Metabolic-Related Gene Prognostic Index for Predicting Prognosis, Immunotherapy Response, and Candidate Drugs in Ovarian Cancer.

Ovarian cancer (OC) is a highly heterogeneous disease, with patients at different tumor staging having different survival times. Metabolic reprogramming is one of the key hallmarks of cancer; however, the significance of metabolism-related genes in the prognosis and therapy outcomes of OC is unclear. In this study, we used weighted gene coexpression network analysis and differential expression analysis to screen for metabolism-related genes associated with tumor staging. We constructed the metabolism-related gene prognostic index (MRGPI), which demonstrated a stable prognostic value across multiple clinical trial end points and multiple validation cohorts. The MRGPI population had its distinct molecular features, mutational characteristics, and immune phenotypes. In addition, we investigated the response to immunotherapy in MRGPI subgroups and found that patients with low MRGPI were prone to benefit from anti-PD-1 checkpoint blockade therapy and exhibited a delayed treatment effect. Meanwhile, we identified four candidate therapeutic drugs (ABT-737, crizotinib, panobinostat, and regorafenib) for patients with high MRGPI, and we evaluated the pharmacokinetics and safety of the candidate drugs. In summary, the MRGPI was a robust clinical feature that could predict patient prognosis, immunotherapy response, and candidate drugs, facilitating clinical decision making and therapeutic strategy of OC.

Exosome-Derived Cargos in Immune Microenvironment in Esophageal Carcinoma: A Mini-Review.

Esophageal carcinoma, a lethal malignancy with limited treatment options and poor prognosis, necessitates understanding its underlying mechanisms and identifying novel therapeutic targets. Recent studies have highlighted the critical role of the immune microenvironment in esophageal carcinoma, particularly the interplay between tumor cells and immune cells mediated by exosomes and their cargos. Exosomes, small extracellular vesicles secreted by various cells, including tumor cells, facilitate intercellular communication by transferring bioactive molecules such as proteins, nucleic acids, and lipids to recipient cells. In the context of esophageal carcinoma, tumor-derived exosomes have been shown to play a significant role in shaping the immune microenvironment. In esophageal carcinoma, exosomal cargos have been found to modulate immune cell function and impact tumor progression. These cargos can carry immune inhibitory molecules, such as programmed death-ligand 1 (PD-L1), to suppress T-cell activity and promote immune evasion by tumor cells. Furthermore, exosomal cargos can activate antigen- presenting cells, enhancing their ability to present tumor-specific antigens to T cells and thereby promoting anti-tumor immune responses. Additionally, the cargos of exosomes have been implicated in the induction of immune regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs) within the esophageal carcinoma microenvironment. These immunosuppressive effectors inhibit the activity of T cells, contributing to tumor immune evasion and resistance to immune therapies. In summary, exosomes and their cargo play a crucial role in the immune microenvironment of esophageal carcinoma. Understanding the mechanisms by which exosomal cargos regulate immune cell function and tumor progression may reveal novel therapeutic targets for this devastating disease.

Eu3+ -Directed Supramolecular Metallogels with Reversible Quadruple-Stimuli Response Behaviors.

Smart luminescent materials that have the ability to reversibly adapt to external environmental stimuli and possess a wide range of responses are continually emerging, which place higher demands on the means of regulation and response sites. Here, europium ions (Eu3+ )-directed supramolecular metallogels are constructed by orthogonal self-assembly of Eu3+ based coordination interactions and hydrogen bonding. A new organic ligand (L) is synthesized, consisting of crown ethers and two flexible amide bonds-linked 1,10-phenanthroline moieties to coordinate with Eu3+ . Synergistic intermolecular hydrogen bonding in L and Eu3+ -L coordination bonding enable Eu3+ and L to self-assemble into shape-persistent 3D coordination metallogels in MeOH solution. The key to success is the utilization of crown ethers, playing dual roles of acting both as building blocks to build L with C2 -symmetrical structure, and as the ideal monomer for increasing the energy transfer from L to Eu3+ 's excited state, thus maintaining the excellent luminescence of metallogels. Interestingly, such assemblies show K+ , pH, F- , and mechano-induced reversible gel-sol transitions and tunable luminescence properties. Above findings are useful in the studies of molecular switches, dynamic assemblies, and smart luminescent materials.

Effect of Meditation on Brain Activity during an Attention Task: A Comparison Study of ASL and BOLD Task fMRI.

Focused attention meditation (FAM) training has been shown to improve attention, but the neural basis of FAM on attention has not been thoroughly understood. Here, we aim to investigate the neural effect of a 2-month FAM training on novice meditators in a visual oddball task (a frequently adopted task to evaluate attention), evaluated with both ASL and BOLD fMRI. Using ASL, activation was increased in the middle cingulate (part of the salience network, SN) and temporoparietal (part of the frontoparietal network, FPN) regions; the FAM practice time was negatively associated with the longitudinal changes in activation in the medial prefrontal (part of the default mode network, DMN) and middle frontal (part of the FPN) regions. Using BOLD, the FAM practice time was positively associated with the longitudinal changes of activation in the inferior parietal (part of the dorsal attention network, DAN), dorsolateral prefrontal (part of the FPN), and precentral (part of the DAN) regions. The effect sizes for the activation changes and their association with practice time using ASL are significantly larger than those using BOLD. Our study suggests that FAM training may improve attention via modulation of the DMN, DAN, SN, and FPN, and ASL may be a sensitive tool to study the FAM effect on attention.

Tumor biology, immune infiltration and liver function define seven hepatocellular carcinoma subtypes linked to distinct drivers, survival and drug response.

BACKGROUND & AIMS: Tumor heterogeneity is jointly determined by the components of the tumor ecosystem (TES) including tumor cells, immune cells, stromal cells, and non-cellular components. We aimed to identify subtypes using TES-related genes and determine subtype specific drivers and treatments for hepatocellular carcinoma (HCC). METHODS: We collected 68 genesets depicting tumor biology, immune infiltration, and liver function, totaling 2831 genes, and collected mRNA profiles and clinical data for over 6000 tumors from 65 datasets in the GEO, TCGA, ICGC, and several other databases. We designed a three-step clustering pipeline to identify subtypes. The microenvironment, genomic alteration, and drug response differences were systematically compared among subtypes. RESULTS: Seven subtypes (TES-1/2/3/4/5/6/7) were revealed in 159 tumors from the CHCC-HBV cohort. We constructed a single sample classifier using paired genes (sscpgsTES). TES subtypes were significantly associated with multiple clinical variables including etiology, and survival in 14 of 17 cohorts and the meta-cohort. TES-1 had the poorest prognosis and highest proliferation level. Both TES-2 and TES-7 were immune-enriched, however, TES-2 had a significantly worse prognosis, and hypoxic and immunosuppressive microenvironment. TES-4 had activated Wnt pathway, driven by CTNNB1 mutation. Good prognosis TES-6 exhibited the best differentiation. TES-5 and TES-3 were considered as novel subclasses by comparing with ten previous subtyping systems. TES-5 tumors had high AFP but good overall survival, and ∼45% of them harbored AXIN1 mutation. TES-3 was immune and stromal desert, may be driven by high copy number alteration burden, and had the poorest response to immune checkpoint inhibitor. TES-1 and TES-2 had significantly lower response to transarterial chemoembolization, but they showed significantly higher sensitivity to compound YM-155. CONCLUSIONS: Tumor ecosystem subtypes expand existing HCC subtyping systems, have distinct drivers, prognosis, and treatment vulnerabilities.

Photo-induced adsorption-desorption behavior of methylene blue on CA-BMO under visible light irradiation.

In this work, the modification of Bi2MoO6 with critic acid (CA-BMO) to achieve enhanced adsorption of methylene blue (MB) solution in dark and desorption under visible light irradiation was reported. The as-prepared materials were synthesized by a hydrothermal method and characterized via SEM, FT-IR, XRD, and XPS techniques. Only 16.5% of 10 mg L-1 MB was removed within 10 min by using 0.5 g L-1 Bi2MoO6, while 92.9% removal of MB could be achieved by using 0.5 g L-1 CA-BMO, which enhanced the adsorption removal by a factor of 4.6. The adsorption capacity for MB was 18.9 mg g-1. Desorption efficiency of MB was only observed in CA-BMO system, and it depends on the wavelength of the light source, pH, and the presence of metal ions. Characterization results suggested that carboxyl groups, which were modified onto the surface of Bi2MoO6, could serve as adsorption sites for MB, and the connections were damaged under light, thus leading to the desorption of MB from the surface of the CA-BMO. This study provides a novel reagent-free desorption strategy for dye recovery without secondary pollution, which facilitates the development and application of Bi-based adsorbent for dye-containing wastewater treatment.

Natural variation of GmFATA1B regulates seed oil content and composition in soybean.

Soybean (Glycine max) produces seeds that are rich in unsaturated fatty acids and is an important oilseed crop worldwide. Seed oil content and composition largely determine the economic value of soybean. Due to natural genetic variation, seed oil content varies substantially across soybean cultivars. Although much progress has been made in elucidating the genetic trajectory underlying fatty acid metabolism and oil biosynthesis in plants, the causal genes for many quantitative trait loci (QTLs) regulating seed oil content in soybean remain to be revealed. In this study, we identified GmFATA1B as the gene underlying a QTL that regulates seed oil content and composition, as well as seed size in soybean. Nine extra amino acids in the conserved region of GmFATA1B impair its function as a fatty acyl-acyl carrier protein thioesterase, thereby affecting seed oil content and composition. Heterogeneously overexpressing the functional GmFATA1B allele in Arabidopsis thaliana increased both the total oil content and the oleic acid and linoleic acid contents of seeds. Our findings uncover a previously unknown locus underlying variation in seed oil content in soybean and lay the foundation for improving seed oil content and composition in soybean.

Deeper topsoils enhance ecosystem productivity and climate resilience in arid regions, but not in humid regions.

Understanding the controlling mechanisms of soil properties on ecosystem productivity is essential for sustaining productivity and increasing resilience under a changing climate. Here we investigate the control of topsoil depth (e.g., A horizons) on long-term ecosystem productivity. We used nationwide observations (n = 2401) of topsoil depth and multiple scaled datasets of gross primary productivity (GPP) for five ecosystems (cropland, forest, grassland, pasture, shrubland) over 36 years (1986-2021) across the conterminous USA. The relationship between topsoil depth and GPP is primarily associated with water availability, which is particularly significant in arid regions under grassland, shrubland, and cropland (r = .37, .32, .15, respectively, p < .0001). For every 10 cm increase in topsoil depth, the GPP increased by 114 to 128 g C m-2 year-1 in arid regions (r = .33 and .45, p < .0001). Paired comparison of relatively shallow and deep topsoils while holding other variables (climate, vegetation, parent material, soil type) constant showed that the positive control of topsoil depth on GPP occurred primarily in cropland (0.73, confidence interval of 0.57-0.84) and shrubland (0.75, confidence interval of 0.40-0.94). The GPP difference between deep and shallow topsoils was small and not statistically significant. Despite the positive control of topsoil depth on productivity in arid regions, its contribution (coefficients: .09-.33) was similar to that of heat (coefficients: .06-.39) but less than that of water (coefficients: .07-.87). The resilience of ecosystem productivity to climate extremes varied in different ecosystems and climatic regions. Deeper topsoils increased stability and decreased the variability of GPP under climate extremes in most ecosystems, especially in shrubland and grassland. The conservation of topsoil in arid regions and improvements of soil depth representation and moisture-retention mechanisms are critical for carbon-sequestration ecosystem services under a changing climate. These findings and relationships should also be included in Earth system models.

Hyperspectral imaging combined with CNN for maize variety identification.

Introduction: As the third largest food crop in the world, maize has wide varieties with similar appearances, which makes identification difficult. To solve the problem of identification of hybrid maize varieties, a method based on hyperspectral image technology combined with a convolutional neural network (CNN) is proposed to identify maize varieties. Methods: In this study, 735 maize seeds from seven half-parent hybrid maize varieties were regarded as the research object. The maize seed images in the range of 900 ~ 1700nm were obtained by hyperspectral image acquisition system. The region of interest (ROI) of the embryo surface was selected, and the spectral reflectance of maize seeds was extracted. After Savitzky-Golay (SG) Smoothing pretreatment, Maximum Normalization (MN) pretreatment was performed. The 56 feature wavelengths were selected by Competitive Adaptive Reweighting Algorithm (CARS) and Successive Projection Algorithm (SPA). And the 56 wavelengths were mapped to high-dimensional space by high-dimensional feature mapping and then reconstructed into three-dimensional image features. A five-layer convolution neural network was used to identify three-dimensional image features, and nine (SG+MN)-(CARS+SPA)-CNN maize variety identification models were established by changing the input feature dimension and the depth factor size of the model layer. Results and Discussion: The results show that the maize variety classification model works best, when the input feature dimension is 768 and the layer depth factor d is 1.0. At this point, the model accuracy of the test set is 96.65% and the detection frame rate is1000 Fps/s in GPU environment, which can realize the rapid and effective non-destructive detection of maize varieties. This study provides a new idea for the rapid and accurate identification of maize seeds and seeds of other crops.

Reconstructing the immunosenescence core pathway reveals global characteristics in pan-cancer.

Immunosenescence has been demonstrated to play an important role in tumor progression. However, there is lacking comprehensive analyses of immunosenescence-related pathways. Meanwhile, the sex disparities of immunosenescence in cancer are still poorly understood. In this study, we analyzed the multi-omics data of 12,836 tumor samples, including genomics, transcriptomics, epigenomics, proteomics, and metabolomics. We systematically identified immunosenescence pathways that were disordered across cancer types. The mutations and copy number variations of immunosenescence pathways were found to be more active in pan-cancer. We reconstructed the immunosenescence core pathways (ISC-pathways) to improve the ability of prognostic stratification in 33 cancer types. We also found the head and neck squamous carcinoma (HNSC) contained abundant sex-specific immunosenescence features and showed sex differences in survival. We found that OSI-027 was a potential sex-specific drug in HNSC tumors, which tended to be more effective in male HNSC by targeting the MTOR gene in the PI3K-Akt signaling pathway. In conclusion, our study provided a systematic understanding of immunosenescence pathways and revealed the global characteristics of immunosenescence in pan-cancer. We highlighted MTOR gene could be a powerful immunosenescence biomarker of HNSC that helps to develop sex-specific immunosenescence drugs.

Overexpression of GmWRKY172 enhances cadmium tolerance in plants and reduces cadmium accumulation in soybean seeds.

Introduction: Cadmium (Cd) stress is a significant threat to soybean production, and enhancing Cd tolerance in soybean is the focus of this study. The WRKY transcription factor family is associated with abiotic stress response processes. In this study, we aimed to identify a Cd-responsive WRKY transcription factor GmWRKY172 from soybean and investigate its potential for enhancing Cd tolerance in soybean. Methods: The characterization of GmWRKY172 involved analyzing its expression pattern, subcellular localization, and transcriptional activity. To assess the impact of GmWRKY172, transgenic Arabidopsis and soybean plants were generated and examined for their tolerance to Cd and Cd content in shoots. Additionally, transgenic soybean plants were evaluated for Cd translocation and various physiological stress indicators. RNA sequencing was performed to identify the potential biological pathways regulated by GmWRKY172. Results: GmWRKY172 was significantly upregulated by Cd stress, highly expressed in leaves and flowers, and localized to the nucleus with transcriptional activity. Transgenic plants overexpressing GmWRKY172 showed enhanced Cd tolerance and reduced Cd content in shoots compared to WT. Lower Cd translocation from roots to shoots and seeds was also observed in transgenic soybean. Under Cd stress, transgenic soybean accumulated less malondialdehyde (MDA) and hydrogen peroxide (H2O2) than WT plants, with higher flavonoid and lignin contents, and peroxidase (POD) activity. RNA sequencing analysis revealed that many stress-related pathways were regulated by GmWRKY172 in transgenic soybean, including flavonoid biosynthesis, cell wall synthesis, and peroxidase activity. Discussion: Our findings demonstrated that GmWRKY172 enhances Cd tolerance and reduces seed Cd accumulation in soybean by regulating multiple stress-related pathways, and could be a promising candidate for breeding Cd-tolerant and low Cd soybean varieties.