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Abstract Oomycete pathogens deliver many effectors to enhance virulence or suppress plant immunity. Plant immune networks are interconnected, in which a few effectors can trigger a strong defense response when recognized by immunity-related proteins. How effectors activate plant defense response remains poorly understood. Here we report Phytophthora capsici effector RxLR23KM can induce plant cell death and plant immunity. RxLR23KM specifically binds to ERD15La, a regulator of abscisic acid and salicylic acid pathway, and the binding intensity depends on the amino acid residues (K93 and M320). NbNAC68, a downstream protein of ERD15La, can stimulate plant immunity that is compromised after binding with ERD15La. Silencing of NbNAC68 substantially prevents the activation of plant defense response. RxLR23KM binds to ERD15La, releasing NbNAC68 to activate plant immunity. These findings highlight a strategy of plant defense response that ERD15La as a central regulator coordinates RxLR23KM to regulate NbNAC68-triggered plant immunity.

Utilizing biomaterials in tissue engineering has shown considerable promise for tissue regeneration, particularly through delivering multimodel cell-regulatory signals, including the material-related signals and extrinsic stimuli. In this research, we developed a magnetic-responsive aligned nanofiber fibrin hydrogel (MAFG), integrating the structured alignment of nanofibers and the pliability of fibrin hydrogel with an external magnetic field. This design aimed to enhance the regenerative response in spinal cord injury treatment. A medium-strength magnetic field, aligned with the spinal cord, was applied to aid motor function recovery in rats with spinal cord injuries. The use of MAFG in this context not only intensified the effect of the magnetic field but also encouraged the activation and differentiation of native neural stem cells. Furthermore, this method effectively steered macrophage polarization towards a beneficial M2 phenotype, addressing immune dysregulation at the injury site. The parallel application of magnetic field stimulation through MAFG in a spinal cord injury model contributed to the concurrent promotion of neurogenesis, angiogenesis, and immunomodulation, resulting in marked improvement in motor function in rats. This investigation underscores the therapeutic potential of magnetic field stimulation and highlights how aligning this stimulation with the spinal cord can significantly enhance the regenerative milieu at the injury site.

Abstract Background Trio-based whole-exome sequencing (trio-WES) enables identification of pathogenic variants, including copy-number variants (CNVs), in children with unexplained neurodevelopmental delay (NDD) and neurodevelopmental comorbidities (NDCs), including autism spectrum disorder (ASD), epilepsy, and attention deficit hyperactivity disorder. Further phenotypic and genetic analysis on trio-WES-tested NDD-NDCs cases may help to identify key phenotypic factors related to higher diagnostic yield of using trio-WES and novel risk genes associated with NDCs in clinical settings. Methods In this study, we retrospectively performed phenotypic analysis on 163 trio-WES-tested NDD-NDCs children to determine the phenotypic differences between genetically diagnosed and non-genetically diagnosed groups. Additionally, we conducted genetic analysis of ASD genes with the help of Simons Foundation for Autism Research Institute (SFARI) Gene database to identify novel possible ASD-risk genes underlying genetic NDD conditions. Results Among these 163 patients, pathogenic variants were identified in 82 cases (82/163, 50.3%), including 20 cases with CNVs. By comparing phenotypic variables between genetically diagnosed group (82 cases) and non-genetically diagnosed group (81 cases) with multivariate binary logistic regression analysis, we revealed that NDD-NDCs cases presenting with severe-profound NDD [53/82 vs 17/81, adjusted-OR (95%CI): 4.865 (2.213 – 10.694), adjusted-P < 0.001] or having multiple NDCs [26/82 vs 8/81, adjusted-OR (95%CI): 3.731 (1.399 – 9.950), adjusted-P = 0.009] or accompanying ASD [64/82 vs 35/81, adjusted-OR (95%CI): 3.256 (1.479 – 7.168), adjusted-P = 0.003] and head circumference abnormality [33/82 vs 11/81, adjusted-OR (95%CI): 2.788 (1.148 – 6.774), adjusted-P = 0.024] were more likely to have a genetic diagnosis using trio-WES. Moreover, 37 genes with monogenetic variants were identified in 48 patients genetically diagnosed with NDD-ASD, and 15 dosage-sensitive genes were identified in 16 individuals with NDD-ASD carrying CNVs. Most of those genes had been proven to be ASD-related genes. However, some of them (9 genes) were not proven sufficiently to correlate with ASD. By literature review and constructing protein-protein interaction networks among these 9 candidate ASD-risk genes and 102 established ASD genes obtained from the SFARI Gene database, we identified CUL4B, KCNH1, and PLA2G6 as novel possible ASD-risk genes underlying genetic NDD conditions. Conclusions Trio-WES testing is recommended for patients with unexplained NDD-NDCs that have severe-profound NDD or multiple NDCs, particularly those with accompanying ASD and head circumference abnormality, as these independent factors may increase the likelihood of genetic diagnosis using trio-WES. Moreover, NDD patients with pathogenic variants in CUL4B, KCNH1 and PLA2G6 should be aware of potential risks of developing ASD during their disease courses.

Abstract Background Ankle-foot orthoses (AFO) can improve gait posture and walking ability in post-stroke patients. However, the effect of AFO on gait parameters in post-stroke patients according to the Brunnstrom stage of stroke recovery of the lower limbs remains unclear. The study aimed to investigate whether stroke patients with different Brunnstrom stages benefit from wearing AFO. Methods Twenty-five post-stroke participants included 18 men (50 ± 13 years) and 7 women (60 ± 15 years). The patients were divided based on Brunnstrom stage III or IV of the lower limbs. All patients underwent the gait and timed up and go (TUG) test using a gait analysis system while walking barefoot or with an AFO. The spatiotemporal and asymmetric parameters were analyzed. Results All 25 patients completed the study. Significant differences were observed between barefoot and AFO use in TUG time (P 0.05). The main effect of the swing time ratio was significant in both groups (P 0.05). For barefoot versus AFO, the main effects of stride length (P 0.05). Conclusions Post-stroke patients with lower Brunnstrom stages benefitted more from AFO, particularly in gait asymmetry.

The success of vision Transformers (ViTs) relies heavily on the self-attention mechanism, which requires support from appropriate patch tokenization. However, hyperspectral image (HSI) often suffer from significant noise distortions and spectral uncertainty, which result in unstable attention patterns and overfitting due to equivocal tokenization. In this paper, we propose a neighborhood contrastive tokenization task (NeiCoT) to learn compact, semantically meaningful, and context-sensitive tokens for efficient Transformer encoding. Specifically, we employ a predictor on patch embedding to maximize the mutual information between local individuals and their global average anchor. This encourages neighboring tokens’ relevance and active participation in feature learning. Next, we revise a token-level contrastive loss to align predictions with local individuals and distinguish them from other samples in a mini-batch to enhance tokens rich in contextual semantics. Furthermore, we apply a Gaussian weighting to the tokens’ contrastive loss to balance the neighborhood contribution. Finally, we propose a sequence-specific MAE framework with NeiCoT to achieve HSI representation, and additionally validate NeiCoT on a supervised Transformer backbone. The results demonstrate that NeiCoT consistently enhances the robustness and generalization of the Transformer, achieving accurate object recognition and boundary localization even with limited training samples. Our code will be available at https://github.com/zoegnov07/NeiCoT.

MiT family translocation renal cell carcinomas (tRCCs) primarily include Xp11.2/transcription factor E3 (TFE3) gene fusion-associated renal cell carcinoma (Xp11.2 tRCC) and t(6;11)/TFEB gene fusion-associated RCC. Clinical cases of these carcinomas are rare. Fluorescence in situ hybridization can be used to identify the type, but there are no standard diagnostic and treatment methods available, and the prognosis remains controversial. Herein, we present a case of a patient with Xp11.2 tRCC at 29 weeks of gestation. The baby was successfully delivered, and radical surgery was performed for renal cancer at the same time. This is a unique and extremely rare case. We have described the case and performed a literature review to report the progress of current research on the treatment and prognosis of pregnant patients with Xp11.2/TFE3 translocation renal cell carcinoma. This study aims to contribute to improving the diagnosis and treatment of Xp11.2 tRCC in pregnant patients.

Abstract Clear cell renal cell carcinoma (ccRCC) is a type of kidney cancer that is both common and aggressive, with a rising incidence in recent decades. Hypoxia is a key factor that plays a vital role in the tumorigenesis and metastasis of malignancy. However, the precise mechanisms of hypoxia driving ccRCC progression were not totally uncovered. Our study found that hypoxia level was elevated in ccRCC and might be an independent risk factor of prognosis in ccRCC patients. We identified a key protein PLOD2 was induced under hypoxic conditions and strongly associated with poor prognosis in ccRCC patients. When PLOD2 was depleted, the proliferation and migration of ccRCC cells were reduced in vitro and in vivo, while overexpression of PLOD2 had the opposite effect. Mechanically, the study further revealed that PLOD2 was transcriptionally activated by HIF1A, which binds to a specific promoter region of the PLOD2 gene. PLOD2 was also shown to interact with EGFR, leading to the phosphorylation of the receptor. Furthermore, PLOD2 was responsible for binding to the extracellular domain of EGFR, which ultimately activated the AKT signaling pathway, thus promoting the malignant progression of ccRCC. Treatment with the PLOD2 inhibitor Minoxidil significantly suppressed ccRCC progression by inactivating the EGFR/AKT signaling axis. In summary, the findings of this study shed light on the molecular mechanisms behind PLOD2 expression in ccRCC and suggest that it may serve as a potential predictor and therapeutic target for the clinical prognosis and treatment of ccRCC.

Abstract How to ensure the safety of abandoned mine resources, scientifically develop and utilize abandoned mine resources, and promote the transformation of resource-exhausted mining areas have become an important issue in the field of energy and environment in the world today. Aiming at the stability of the surrounding rock in deep closed/abandoned mine chamber, the mechanical model of the surrounding rock under the coupling effect of anchorage and seepage field was proposed. Considering the elastic brittleness degradation and plastic dilatancy effect of rock mass, the analytical solutions of stress and displacement of rockbolt-seepage-surrounding rock coupling system were respectively deduced, and the accuracy of the results were verified. Based on the analytical results, the evolution law of stress and displacement of the surrounding rock under the combined action of seepage field and anchorage effect were further revealed, and a new quantitative design method of rockbolt parameters was proposed. Results show that the influence of rockbolt spacing and rod diameter on the mechanical field is obvious, while the rockbolt length and pre-tension load is small. Dense, short rockbolt with larger diameter should be used in the surrounding rock of deep chamber. The influence of seepage on the displacement of the surrounding rock is very significant. The more serious the seepage is, the more obvious the control effect of rockbolt on the displacement is. Appropriately increasing the density and diameter of rockbolt can effectively reduce the displacement of the surrounding rock.

With the rapid development of the modern world, it is imperative to achieve effective and efficient monitoring for territories of interest, especially for the broad ocean area. For surveillance of ship targets at sea, a common and powerful approach is to take advantage of satellite synthetic aperture radar (SAR) systems. Currently, using satellite SAR images for ship classification is a challenging issue due to complex sea situations and the imaging variances of ships. Fortunately, the emergence of advanced satellite SAR sensors has shed much light on the SAR ship automatic target recognition (ATR) task, e.g., utilizing dual-polarization (dual-pol) information to boost the performance of SAR ship classification. Therefore, in this paper we have developed a novel cross-polarimetric interaction network (CPINet) to explore the abundant polarization information of dual-pol SAR images with the help of deep learning strategies, leading to an effective solution for high-performance ship classification. First, we establish a novel multiscale deep feature extraction framework to fully mine the characteristics of dual-pol SAR images in a coarse-to-fine manner. Second, to further leverage the complementary information of dual-pol SAR images, we propose a mixed-order squeeze–excitation (MO-SE) attention mechanism, in which the first- and second-order statistics of the deep features from one single-polarized SAR image are extracted to guide the learning of another polarized one. Then, the intermediate multiscale fused and MO-SE augmented dual-polarized deep feature maps are respectively aggregated by the factorized bilinear coding (FBC) pooling method. Meanwhile, the last multiscale fused deep feature maps for each single-polarized SAR image are also individually aggregated by the FBC. Finally, four kinds of highly discriminative deep representations are obtained for loss computation and category prediction. For better network training, the gradient normalization (GradNorm) method for multitask networks is extended to adaptively balance the contribution of each loss component. Extensive experiments on the three- and five-category dual-pol SAR ship classification dataset collected from the open and free OpenSARShip database demonstrate the superiority and robustness of CPINet compared with state-of-the-art methods for the dual-polarized SAR ship classification task.

Nerve guidance conduits (NGCs) have been widely accepted as a promising strategy for peripheral nerve regeneration. Fabricating ideal NGCs with good biocompatibility, biodegradability, permeability, appropriate mechanical properties (space maintenance, suturing performance, etc.), and oriented topographic cues is still current research focus. From the perspective of translation, the technique stability and scalability are also an important consideration for industrial production. Recently, blow-spinning technique shows great potentials in nanofibrous scaffolds fabrication, possessing high quality, high fiber production rates, low cost, ease of maintenance, and high reliability. In this study, we proposed for the first time the preparation of a novel NGC via blow-spinning technique to obtain optimized performances and high productivity. A new collagen nanofibrous neuro-tube with the bilayered design was developed, incorporating inner oriented and outer random topographical cues. The bilayer structure enhances the mechanical properties of the conduit in dry and wet, displaying good radial support and suturing performance. The porous nature of the blow-spun collagen membrane enables good nutrient delivery and metabolism. The in vitro and in vivo evaluations indicated the bilayer-structure conduit could promoted Schwann cells growth, neurotrophic factors secretion, and axonal regeneration and motor functional recovery in rat.

Abstract Purpose To explore the relationship between ankle-brachial blood pressure index (ABPI) and all-cause or cardiovascular mortality in adults without arterial stiffness. Methods A total of 6784 participants without arterial stiffness were enrolled from National Health and Nutrition Examination Survey 1999–2004. The hazard ratio (HR) and 95% confidence interval (CI) of ABPI associating with the risk of all-cause and cardiovascular mortality was calculated by Cox proportional regression models adjusted for demographic and traditional risk factors. Dose-response relationship was explored with restricted cubic spines. Results After an average follow-up of 12.1 years, 1844 all-cause deaths and 299 cardiovascular deaths occurred. Compared with the lowest ABPI quartile, the second quartile was associated with the lowest risk of all-cause mortality (HR 0.89, 95%CI 0.79–0.98; p = 0.036) and cardiovascular mortality (HR 0.75, 95%CI 0.56–0.98; p = 0.048). Besides, dose-response analysis revealed that ABPI was nonlinearly correlated to all-cause mortality (p for nonlinearity

Abstract Background Spinal cord stimulation (SCS) is a surgical technique used in patients with chronic intractable pain, and its effectiveness and safety have been validated by multiple studies. However, to maintain an optimal and steady long-term effect is still challenging. Here, we report a new management paradigm integrating smartphone application and remote programming. Chronic pain patients with SCS implants can monitor their pain status on the phone and change stimulation parameters accordingly. The PreMaSy study is a randomized controlled trial to evaluate the clinical effectiveness and safety of this precise management system. Methods Patients with chronic intractable pain will be screened for eligibility, and 82 participants are anticipated to be enrolled in this trial. After the electrode implantation, the stimulation effectiveness will be tested. Participants with a reduction of more than 50% in the visual analog scale (VAS) will receive implantation of an implantable pulse generator and randomized (1:1) into the experimental group or control group. All participants will be asked to take online follow-ups and complete assessments using a smartphone application. Daily pain characteristic assessments and monthly quality of life questionnaires are integrated into the App, and participants will be required to complete these assessments. The daily VAS for pain intensity will be monitored and a threshold will be set based on baseline VAS score. The interventional appointment will be scheduled once the threshold is reached. The primary outcome is the health condition and quality of life assessed by the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L). Utility values of EQ-5D-5L will be assessed at baseline and 1, 3, and 6 months post-operative. Discussion The PreMaSy study aims to evaluate the effectiveness and safety of a novel App-based, patient-centered, self-assessment management system for chronic intractable pain. A randomized controlled trial is designed to test the non-inferiority of this precise management system compared to the monthly online follow-ups. It is also expected to yield valuable experiences regarding precision medicine. Trial registration ClinicalTrials.gov NCT05761392. Registered on March 07, 2023.

Abstract Background The triglyceride and glucose (TyG) index has been considered a simple surrogate marker of insulin resistance, related to a high risk of mortality. However, few studies have investigated the specific relationship between the TyG index and all-cause mortality among population with cardiovascular diseases. Methods 2,072 participants with cardiovascular diseases were enrolled from the National Health and Nutrition Examination Survey (NHANES) 1999–2014. The TyG index was calculated as log [fasting triglycerides (mg/dL) x fasting glucose (mg/dL)/2]. Outcomes were all-cause mortality and cardiovascular mortality. The baseline levels of TyG associated with the risk of mortality were evaluated on a continuous scale (restricted cubic splines) and by a priori defined quantile categories with Cox regression models. Results After a follow-up of 16.8 years, 791 all-cause deaths and 184 cardiovascular deaths occurred. Restricted cubic splines showed that the association between levels of TyG index and the risk of all-cause mortality was non-linear (p

Abstract Background Determining the grade and molecular marker status of intramedullary gliomas is important for assessing treatment outcomes and prognosis. Invasive biopsy for pathology usually carries a high risk of tissue damage, especially to the spinal cord, and there are currently no non-invasive strategies to identify the pathological type of intramedullary gliomas. Therefore, this study aimed to develop a non-invasive machine learning model to assist doctors in identifying the intramedullary glioma grade and mutation status of molecular markers. Methods A total of 461 patients from two institutions were included, and their sagittal (SAG) and transverse (TRA) T2-weighted magnetic resonance imaging scans and clinical data were acquired preoperatively. We employed a transformer-based deep learning model to automatically segment lesions in the SAG and TRA phases and extract their radiomics features. Different feature representations were fed into the proposed neural networks and compared with those of other mainstream models. Results The dice similarity coefficients of the Swin transformer in the SAG and TRA phases were 0.8697 and 0.8738, respectively. The results demonstrated that the best performance was obtained in our proposed neural networks based on multimodal fusion (SAG-TRA-clinical) features. In the external validation cohort, the areas under the receiver operating characteristic curve for graded (WHO I–II or WHO III–IV), alpha thalassemia/mental retardation syndrome X-linked (ATRX) status, and tumor protein p53 (P53) status prediction tasks were 0.8431, 0.7622, and 0.7954, respectively. Conclusions This study reports a novel machine learning strategy that, for the first time, is based on multimodal features to predict the ATRX and P53 mutation status and grades of intramedullary gliomas. The generalized application of these models could non-invasively provide more tumor-specific pathological information for determining the treatment and prognosis of intramedullary gliomas.

The Bell state is a crucial resource for the realization of quantum information tasks, and when combined with orbital angular momentum (OAM), it enables a high-dimensional Hilbert space, which is essential for high-capacity quantum communication. In this study, we demonstrate the recognition of OAM Bell states using interference patterns generated by a classical light source and a single-photon source from a Sagnac interferometer-based OAM Bell state evolution device. The interference patterns exhibit a one-to-one correspondence with the input Bell states, providing conclusive evidence for the full recognition of OAM Bell states. Furthermore, we introduce machine learning to the field of Bell state recognition by proposing a neural network model capable of accurately recognizing higher order single-photon OAM Bell states, even in the undersampling case. In particular, the model’s training set includes interference patterns of OAM Bell states generated by classical light sources, yet it is able to recognize single-photon OAM Bell states with high accuracy, without relying on quantum resources during training. Our innovative application of neural networks to the recognition of single-photon OAM Bell states not only circumvents the resource consumption and experimental difficulties associated with quantum light sources but also facilitates the study of OAM-based quantum information.

Strip filling mining in a goaf is of great significance for solving the ‘three under’ coal-pressure and mining-area ecological environment problems in Central and Eastern China, but the disturbance characteristics of filling parameters on overlying rock are not clear at present. Taking the geological conditions of the CT30101 working face in Mahuangliang coal mine and the short-wall interval strip filling as a background, the strength parameters (cohesion and friction angle), deformation parameters (elastic modulus and Poisson’s ratio), and structural parameters (strip width and spacing) of the filling body were selected as experimental factors, and the maximum settlement of the direct roof and the ground surface was taken as the evaluation index. The influence degree of each factor was quantitatively characterized via a variance analysis and an F test, and the main control factors of the strip filling overburden settlement were proposed. The roof and surface displacement, the stress evolution law of the filling body, and the shape change of the surrounding rock plastic zone under different levels of main control factors in the entire process of mining filling coupling were analyzed in detail. The results showed that the cohesion of the backfill had a highly significant impact on the direct roof settlement, the strip spacing and the friction angle of backfill had a significant impact on it, the cohesion of the backfill and the strip spacing had a certain impact on the surface settlement, and the two had a cross-coupling effect. In the process of mining and filling, the stress evolution of the filling body was extremely complex, and it finally presented a saddle shape that was high on both sides and low in the middle; the majority of the strata and the filling body primarily exhibited shear damage, with a small amount of tensile failure zones appearing only in the direct roof and mid-section of the filling body. The above conclusions have a certain guiding significance for the optimal design of strip filling in a goaf.

In this paper we study the Marcinkiewicz–Zygmund-type strong law of large numbers with general normalizing sequences under sublinear expectation. Specifically, we establish complete convergence in the Marcinkiewicz–Zygmund-type strong law of large numbers for sequences of negatively dependent and identically distributed random variables under certain moment conditions. We also give results for sequences of independent and identically distributed random variables. The moment conditions in this paper are based on a class of slowly varying functions that satisfy some convergence properties. Moreover, some special examples and comparisons to existing results are also given.

The fungal genus Phyllosticta has been reported from all around the world and accommodates numerous pathogenic and endophytic species isolated from a wide range of plant hosts. Based on multilocus phylogenies from a combined dataset of genes encoding internal transcribed spacer (ITS), large subunit of ribosomal RNA (LSU rDNA), translation elongation factor 1 alpha (TEF1α), actin (ACT) and glycerol-3-phosphate dehydrogenase (GPDH), in conjunction with morphological characteristics, we describe two new species P. oblongifoliae sp. nov. and P. pterospermi sp. nov., as well as a new Chinese record P. capitalensis. Their similarity and dissimilarity to morphologically-allied and phylogenetically-related species are also annotated and discussed.

The traditional method for synthesizing NH3 is the Haber–Bosch process which results in high‐fuel consumption and environmental pollution. Therefore, ecofriendly electrochemical synthesis of NH3 through nitrate (NO3−) reduction is a good choice. Herein, an integral Au/Cu electrode to catalyze NO3− reduction to NH3 is introduced. The catalyst exhibits not only the highest NH3 yield rate (73.4 mg h−1 cm−2) up to now but also a very high Faradaic efficiency of 98.02% at −0.7 V at room temperature. It is commonly believed that the transformation of NO3− to nitrite (NO2−) is an obstacle to the NH3 generation from NO3− reduction. Surprisingly, unlike most of the other catalysts, Au/Cu exhibits better activity for NO3− reduction than that for NO2− reduction. Based on the detailed experimental and density functional theory calculations, the excellent performance of Au/Cu for selective NO3− reduction lies in the enhanced adsorption capabilities of Au/Cu to NO3− in the alkaline environment and the lower energy barriers of the electrochemical reduction reaction.

Abstract Holographic metasurfaces and their applications have garnered significant attention owing to their role in polarization control. In this study, we demonstrate that the quantum properties of holographic metasurfaces can be obtained by quantum state tomography (QST) and quantum process tomography (QPT). We perform QST to obtain the experimental output states by extracting information from holograms encoded on the holographic metasurface, and develop a QPT-based method to estimate the quantum process of the metasurface. The theoretical output states derived from the estimated quantum process are in good agreement with the experimental output states, proving the effectiveness of our method. Our work not only provides theoretical and experimental analysis for understanding the quantum properties of holographic metasurfaces, but also paves the way for the application of holographic metasurfaces in quantum field.

ObjectiveThis study aims to explore the clinical value of artificial intelligence (AI)-assisted bone age assessment (BAA) among children with growth hormone deficiency (GHD).MethodsA total of 290 bone age (BA) radiographs were collected from 52 children who participated in the study at Sun Yat-sen Memorial Hospital between January 2016 and August 2017. Senior pediatric endocrinologists independently evaluated BA according to the China 05 (CH05) method, and their consistent results were regarded as the gold standard (GS). Meanwhile, two junior pediatric endocrinologists were asked to assessed BA both with and without assistance from the AI-based BA evaluation system. Six months later, around 20% of the images assessed by the junior pediatric endocrinologists were randomly selected to be re-evaluated with the same procedure half a year later. Root mean square error (RMSE), mean absolute error (MAE), accuracy, and Bland-Altman plots were used to compare differences in BA. The intra-class correlation coefficient (ICC) and one-way repeated ANOVA were used to assess inter- and intra-observer variabilities in BAA. A boxplot of BA evaluated by different raters during the course of treatment and a mixed linear model were used to illustrate inter-rater effect over time.ResultsA total of 52 children with GHD were included, with mean chronological age and BA by GS of 6.64 ± 2.49 and 5.85 ± 2.30 years at baseline, respectively. After incorporating AI assistance, the performance of the junior pediatric endocrinologists improved (P

BackgroundThe prevalence of depression has been increasing worldwide in recent years, posing a heavy burden on patients and society. However, the diagnostic and therapeutic tools available for this disease are inadequate. Therefore, this research focused on the identification of potential biomarkers in the peripheral blood of patients with depression.MethodsThe expression dataset GSE98793 of depression was provided by the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/gds). Initially, differentially expressed genes (DEGs) were detected in GSE98793. Subsequently, the most relevant modules for depression were screened according to weighted gene co-expression network analysis (WGCNA). Finally, the identified DEGs were mapped to the WGCNA module genes to obtain the intersection genes. In addition, Gene Ontology (GO), Disease Ontology (DO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were conducted on these genes. Moreover, biomarker screening was carried out by protein-protein interaction (PPI) network construction of intersection genes on the basis of various machine learning algorithms. Furthermore, the gene set enrichment analysis (GSEA), immune function analysis, transcription factor (TF) analysis, and the prediction of the regulatory mechanism were collectively performed on the identified biomarkers. In addition, we also estimated the clinical diagnostic ability of the obtained biomarkers, and performed Mfuzz expression pattern clustering and functional enrichment of the most potential biomarkers to explore their regulatory mechanisms. Finally, we also perform biomarker-related drug prediction.ResultsDifferential analysis was used for obtaining a total of 550 DEGs and WGCNA for obtaining 1,194 significant genes. Intersection analysis of the two yielded 140 intersection genes. Biological functional analysis indicated that these genes had a major role in inflammation-related bacterial infection pathways and cardiovascular diseases such as atherosclerosis. Subsequently, the genes S100A12, SERPINB2, TIGIT, GRB10, and LHFPL2 in peripheral serum were identified as depression biomarkers by using machine learning algorithms. Among them, S100A12 is the most valuable biomarker for clinical diagnosis. Finally, antidepressants, including disodium selenite and eplerenone, were predicted.ConclusionThe genes S100A12, TIGIT, SERPINB2, GRB10, and LHFPL2 in peripheral serum are viable diagnostic biomarkers for depression. and contribute to the diagnosis and prevention of depression in clinical practice.

ObjectiveThis study analyzed eight Chinese short stature children with aggrecan deficiency, and aimed to investigate potential genotype–phenotype correlations, differences in clinical characteristics between the Chinese and the Western populations, and effectiveness of recombinant human growth hormone therapy in patients with ACAN variants through a review of the literature.MethodsPediatric short stature patients with ACAN heterozygous variants were identified using whole-exome sequencing. Subsequently, a literature review was carried out to summarize the clinical features, genetic findings, and efficacy of growth-promoting therapy in patients with ACAN variants.ResultsWe identified seven novel ACAN mutations and one recurrent variant. Patients in our center manifested with short stature (average height SDS: -3.30 ± 0.85) with slight dysmorphic characteristics. The prevalence of dysmorphic features in the Chinese populations is significantly lower than that in the Western populations. Meanwhile, only 24.24% of aggrecan-deficient Chinese children showed significantly advanced bone age (BA). Promising therapeutic benefits were seen in the patients who received growth-promoting treatment, with an increase in growth velocity from 4.52 ± 1.00 cm/year to 8.03 ± 1.16 cm/year.ConclusionThis study further expanded the variation spectrum of the ACAN gene and demonstrated that Chinese children with short stature who carried ACAN heterozygous variants exhibited early growth cessation, which may remain unnoticed by clinicians as most of these children had very mild dysmorphic characteristics and showed BA that was consistent with the chronological age. Genetic testing may help in the diagnosis.

Background: We aimed to analyze the predictive role of serum test and questionnaire in Early Gastric Cancer in The First Affiliated Hospital of Xingtai Medical College, Hebei Province from 2019 to 2020. Methods: In this prospective study, 280 medical examiners underwent questionnaire, serum test and gastroscopy. They were divided into Gastric cancer (GC) and Non-Gastric cancer (NGC) group. NGC group was divided into Low-grade intraepithelial neoplasia (LGIN), Chronic atrophic gastritis (CAG) and Non-chronic atrophic gastritis (NCAG) group. Results: Age, drinking, sex and Gastrin-17(G-17) was respectively independent risk factors for GC. Age, drinking and G-17 was independent risk factors for GC in men. G-17 of GC group was higher than that of LGIN and NCAG group (P

Abstract Background Cardiac hypertrophy is an independent risk factor of many cardiovascular diseases. Studies have demonstrated that microRNA-126 (miR-126) was involved in angiogenesis during physiological and pathological process. However, its role in cardiac hypertrophy has not been known clearly. Our previous study demonstrated that asiatic acid (AA) has obvious protective effect on cardiac hypertrophy. Here, this study aimed to discover the regulatory role of miR-126 and its mechanism in cardiac hypertrophy, and to determine whether AA’s anti-hypertrophy effect is partially miR-126 dependent. Methods Male Sprague Dawley rats were AngII infused via osmotic minipumps for 4 weeks and were treated with AA (20 mg/kg/day) by oral gavage. Cardiac hypertrophy was assessed using the echocardiography and histological analysis. In vitro studies,cardiomyocyte and cardiac fibroblasts (CF) were treted with AngII and AngII plus AA. And, the effect of AA on miR-126 and PI3K/AKT signaling pathway was investigated. Results Treatment of rats with AA decreased the ratio of heart weight to tibia length and hypertrophy markers. In vitro exprements demonstrated that AA significantly attenuated AngII-induced cardiac growth and cardiac fibroblast collagen expression. Moreover, our results found downregulation of miR-126 and activation of PI3K/AKT signaling pathway in AngII infusion induced cardiac hypertrophy model. It was also determined that miR-126 targets PIK3R2 directly. Conclusions AA supplementation upregulated the expression of miR-126 and conferred cardio-protection effect against AngII induced cardiac hypertrophy.

The incidence rate of necrotizing fasciitis(NF) is low, but it has a high mortality rate. At present, it lacks experience in clinical treatment in municipal and county-level hospitals, insufficient awareness of disease risk, lack of experience in disease surgical intervention, and lack of a set of mature treatment norms and standards. Most patients have no time to transfer to a higher hospital for treatment. In January and April 2022, two cases of large-scale necrotizing fasciitis of the scrotum and abdominal wall were treated in the Department of Urology of Weifang people's Hospital respectively and were clinically cured after active surgical debridement combined with broad-spectrum antibiotics. Through the retrospective analysis of the diagnosis and treatment of two cases of necrotizing fasciitis, this paper analyzes and summarizes the scope of surgical debridement of NF, postoperative dressing changing skills, timing of multiple debridements, application and timing of vacuum sealing drainage(VSD), and the combined use of antibiotics. To provide experience for clinical diagnosis and treatment of necrotizing fasciitis.

Salt cress (Eutrema salsugineum), an Arabidopsis-related halophyte, can naturally adapt to various harsh climates and soil conditions; thus, it is considered a desirable model plant for deciphering mechanisms of salt and other abiotic stresses. Accumulating evidence has revealed that compared with Arabidopsis, salt cress possesses stomata that close more tightly and more succulent leaves during extreme salt stress, a noticeably higher level of proline, inositols, sugars, and organic acids, as well as stress-associated transcripts in unstressed plants, and they are induced rapidly under stress. In this review, we systematically summarize the research on the morphology, physiology, genome, gene expression and regulation, and protein and metabolite profile of salt cress under salt stress. We emphasize the latest advances in research on the genome adaptive evolution encountering saline environments, and epigenetic regulation, and discuss the mechanisms underlying salt tolerance in salt cress. Finally, we discuss the existing questions and opportunities for future research in halophytic Eutrema. Together, the review fosters a better understanding of the mechanism of plant salt tolerance and provides a reference for the research and utilization of Eutrema as a model extremophile in the future. Furthermore, the prospects for salt cress applied to explore the mechanism of salt tolerance provide a theoretical basis to develop new strategies for agricultural biotechnology.

Convolutional neural networks (CNNs) have improved the accuracy of hyperspectral image (HSI) classification significantly. However, CNN models usually generate a large number of feature maps, which lead to high redundancy and cannot guarantee to effectively extract discriminative features for well characterizing the complex structures of HSIs. In this article, two novel mixed link networks (MLNets) are proposed to enhance the representational ability of CNNs for HSI classification. Specifically, the proposed mixed link architectures integrate the feature reusage property of the residual network and the capability of effective new feature exploration of the densely convolutional network, extracting more discriminative features from HSIs. Compared with the dual path architecture, the proposed mixed link architectures can further improve the information flow throughout the network. Experimental results on three hyperspectral benchmark datasets demonstrate that our MLNets achieve competitive results compared with other state-of-the-art HSI classification approaches.

This work reported a facile route for fabricating super-hydrophobic concrete via sizing sand grains. It was found that mixing the sands with a size ranging from 150–180 μ m into cement enabled the formation of a lotus-like surface with a papillary structure at micro-scale. SEM showed that the size of bumper was about 3 μ m. When spraying a fluorocarbon solution onto this surface, the porous nature of the cement matrix showed the advantage of taking the fluorocarbon into the internal structure of the concrete via capillary force. As a result, the sub surface up to a depth of ∼1.5 mm were transformed into a thick superhydrophobic layer directly. The contact angle (CA) of water droplets could reach 157° on this surface, and which could remain more than 150° after abrasion 100 cycles under a weight of 300 g at 360 grit sandpaper. This thick hydrophobic layer significantly reduced the corrosion rate of the steel the concrete at the Cl ^- environment by 620 times. The measurement of British pendulum number and compression strength revealed that this superhydrophobic layer was beneficial for maintaining the friction coefficient of the concrete surface in wet condition without altering the mechanical integrity of the concrete.

Species of Pseudoplagiostomataceae were mainly introduced as endophytes, plant pathogens, or saprobes from various hosts. Based on multi-locus phylogenies from the internal transcribed spacers (ITS), the large subunit of nuclear ribosomal RNA gene (LSU), partial DNA-directed RNA polymerase II subunit two gene (rpb2), the partial translation elongation factor 1-alpha gene (tef1α), and the partial beta-tubulin gene (tub2), in conjunction with morphological characteristics, we describe three new species, viz. Pseudoplagiostoma alsophilae sp. nov., P. bambusae sp. nov., and P. machili sp. nov. Molecular clock analyses on the divergence times of Pseudoplagiostomataceae indicated that the conjoint ancestor of Pseudoplagiostomataceae and Apoharknessiaceae occurred in the Cretaceous period. and had a mean stem age of 104.1 Mya (95% HPD of 86.0–129.0 Mya, 1.0 PP), and most species emerged in the Paleogene and Neogene period. Historical biogeography was reconstructed for Pseudoplagiostomataceae by the RASP software with a S–DEC model, and suggested that Asia, specifically Southeast Asia, was probably the ancestral area.

Abstract Genomic amplification of OTUD7B is frequently found across human cancers. But its role in tumorigenesis is poorly understood. Lysine‐specific demethylase 1 (LSD1) is known to execute epigenetic regulation by forming corepressor complex with CoREST/histone deacetylases (HDACs). However, the molecular mechanisms by which cells maintain LSD1/CoREST complex integrity are unknown. Here, it is reported that LSD1 protein undergoes K63‐linked polyubiquitination. OTUD7B is responsible for LSD1 deubiquitination at K226/277 residues, resulting in dynamic control of LSD1 binding partner specificity and cellular homeostasis. OTUD7B deficiency increases K63‐linked ubiquitination of LSD1, which disrupts LSD1/CoREST complex formation and targets LSD1 for p62‐mediated proteolysis. Consequently, OTUD7B deficiency impairs genome‐wide LSD1 occupancy and enhances the methylation of H3K4/H3K9, therefore profoundly impacting global gene expression and abrogating breast cancer metastasis. Moreover, physiological fluctuation of OTUD7B modulates cell cycle‐dependent LSD1 oscillation, ensuring the G1/S transition. Both OTUD7B and LSD1 proteins are overpresented in high‐grade or metastatic human breast cancer, while dysregulation of either protein is associated with poor survival and metastasis. Thus, OTUD7B plays a unique partner‐switching role in maintaining the integrity of LSD1/CoREST corepressor complex, LSD1 turnover, and breast cancer metastasis.

De novo germline variants of the casein kinase 2α subunit (CK2α) gene ( CSNK2A1 ) have been reported in individuals with the congenital neuropsychiatric disorder Okur–Chung neurodevelopmental syndrome (OCNS). Here, we report on two unrelated children with OCNS and review the literature to explore the genotype–phenotype relationship in OCNS. Both children showed facial dysmorphism, growth retardation, and neuropsychiatric disorders. Using whole-exome sequencing, we identified two novel de novo CSNK2A1 variants: c.479A>G p.(H160R) and c.238C>T p.(R80C). A search of the literature identified 12 studies that provided information on 35 CSNK2A1 variants in various protein-coding regions of CK2α. By quantitatively analyzing data related to these CSNK2A1 variants and their corresponding phenotypes, we showed for the first time that mutations in protein-coding CK2α regions appear to influence the phenotypic spectrum of OCNS. Mutations altering the ATP/GTP-binding loop were more likely to cause the widest range of phenotypes. Therefore, any assessment of clinical spectra for this disorder should be extremely thorough. This study not only expands the mutational spectrum of OCNS, but also provides a comprehensive overview to improve our understanding of the genotype–phenotype relationship in OCNS.

Abstract Background Myricetin, a major flavonoid found in several foods including berries, grapes and wine, exhibited strong antioxidant potency, yet the effect on atherosclerosis is not fully understood. In this study, we examined the effect of myricetin on lipid accumulation in macrophage and atherosclerosis in atherosclerosis-prone low density lipoprotein receptor-deficient (Ldlr −/− ) mice. Methods Ldlr −/− mice were fed an atherogenic diet supplemented with myricetin (0.15% in the diet, v/v) for 8 weeks. Body weight, adipose tissue weight, food intake, serum biochemical parameters were measured. Atherosclerosis lesions and macrophages accumulaton in lesions were analyzed and quantified. Macrophages were exposed to 20 μM of myricetin before incubated with oxidized low-density lipoprotein (ox-LDL) (25μg/mL) or Dil-ox-LDL for the indicated time. Lipid uptake and foam cell formation were evaluated by flow cytometry and microscopy. The intracellular lipids were extracted and measured. mRNA expression and protein of cholesterol metabolism related receptors were analyzed. Results Myricetin administration reduced the weight, plasma lipid levels but not food intake in Ldlr −/− mice when fed an atherogenic diet. Myceritin-treated Ldlr −/− mice displayed significantly less atherosclerotic areas and macrophages in the cross sections of the aortic root. There were also less lipophilic areas in En face Oil red O staining of aorta from myceritin-treated Ldlr −/− mice. Myceritin treatment also markedly ameliorated ox-LDL-induced cholesterol accumulation in macrophages. The expression of CD36 were decreased in myricetin treated macrophages with ox-LDL incubation, while scavenger receptors class A (SR-A) and scavenger receptors class B (SR-BI) expression was not altered, indicating that these effect of myricetin were dependent on CD36 pathway. Conclusions Our findings indicated that myricetin suppressed cholesterol accumulation in macrophage foam cells by inhibition of CD36-mediated ox-LDL uptake, and suggested myricetin may have an important therapeutic function for atherosclerosis.

To learn discriminative features, hyperspectral image (HSI), containing 3-D cube data, is a preferable means of capturing multi-head self-attention from both spatial and spectral domains if the burden in model optimization and computation is low. In this paper, we design a dual multi-head contextual self-attention (DMuCA) network for HSI classification with the fewest possible parameters and lower computation costs. To effectively capture rich contextual dependencies from both domains, we decouple the spatial and spectral contextual attention into two sub-blocks, SaMCA and SeMCA, where depth-wise convolution is employed to contextualize the input keys in the pure dimension. Thereafter, multi-head local attentions are implemented as group processing when the keys are alternately concatenated with the queries. In particular, in the SeMCA block, we group the spatial pixels by evenly sampling and create multi-head channel attention on each sampling set, to reduce the number of the training parameters and avoid the storage increase. In addition, the static contextual keys are fused with the dynamic attentional features in each block to strengthen the capacity of the model in data representation. Finally, the decoupled sub-blocks are weighted and summed together for 3-D attention perception of HSI. The DMuCA module is then plugged into a ResNet to perform HSI classification. Extensive experiments demonstrate that our proposed DMuCA achieves excellent results over several state-of-the-art attention mechanisms with the same backbone.

Species in Microdochium, potential agents of biocontrol, have often been reported as plant pathogens, occasionally as endophytes and fungicolous fungi. Combining multiple molecular markers (ITS rDNA, LSU rDNA, TUB2 and RPB2) with morphological characteristics, this study proposes three new species in the genus Microdochium represented by seven strains from the plant hosts Miscanthus sinensis and Phragmites australis in Hainan Island, China. These three species, Microdochium miscanthi sp. Nov., M. sinense sp. Nov. and M. hainanense sp. Nov., are described with MycoBank number, etymology, typification, morphological features and illustrations, as well as placement on molecular phylogenetic trees. Their affinity with morphologically allied and molecularly closely related species are also analyzed. For facilitating identification, an updated key to the species of Microdochium is provided herein.

LUX ARRHYTHMO (LUX) plays a key role in circadian rhythms and flowering. Here, we identified the MtLUX gene which is the putative ortholog of LUX in Medicago truncatula. The roles of MtLUX, in both the nodulation belowground and leaf movement aboveground, were investigated by characterizing a loss-of-function mtlux mutant. MtLUX was required for the control of flowering time under both long-day and short-day conditions. Further investigations showed that the early flowering in the mtlux mutant was correlated with the elevated expression level of the MtFTa1 gene but in a CO-like independent manner. MtLUX played a conserved role in the regulatory interactions with MtLHY, MtTOC1, and MtPRR genes, which is similar to those in other species. Meanwhile, the unexpected functions of MtLUX were revealed in nodule formation and nyctinastic leaf movement, probably through the indirect regulation in MtLHY. Its participation in nodulation is of interest in the context of functional conservation and the neo-functionalization of the products of LUX orthologs.

Background: Several guidelines and expert consensuses have been developed for management of primary aldosteronism (PA). It is important to understand the detailed recommendations and quality of these guidelines to help physicians make informed and reliable decision.Methods: PubMed, EMBASE, and three websites were searched for practice guidelines or consensuses of PA from inception to January 24, 2019. We summarized the major recommendations on the management of PA from these guidelines and consensuses. The Appraisal of Guidelines for Research and Evaluation II was used to assess quality of the included guidelines and consensuses.Results: We identified three clinical practice guidelines and three consensus statements. Most of the recommendations on the diagnosis and treatment of PA from these guidelines and consensuses were consistent. Some minor conflicts were recorded for patient's screen and confirmation test. All included guideline documents have a good quality (score, >70%) on the scope and purpose (mean score, 81.02%) and clarity of presentation of the recommendations (mean score, 86.88%). However, the reporting for the stakeholder involvement (mean score, 54.32%) and applicability (mean score, 47.92%) were insufficient. There was an insufficient rigorousness in most of the guideline documents (mean score, 45.56%) on the development process. The Endocrine Society practice guideline 2016 ranked highest in quality (score, 81.13%).Conclusions: Existing guideline documents provided valuable recommendations on the management of PA, but further efforts are needed to improve the methodological quality. The Endocrine Society practice guideline 2016 was recommended for use.

Background: Consistent evidence have demonstrated that patients with primary aldosteronism (PA) have higher risk of cardiovascular events to patients with essential hypertension (EH). Whether the long-term risk of mortality for PA patients is higher than EH patients is unclear. We aim to compare the long-term mortality of patients with PA to patients with EH.Methods: We searched PubMed, Embase, and Cochrane Central Register of Controlled Trials for eligible studies from inception to 14 Nov 2018. We combined the relative risks (RR) of each included study by random-effect model. The amount of between study heterogeneity was measured by the I2 statistic.Results: We totally included six studies with cohort design, including 3,039 PA and 45,495 EH patients. The pooled RRs for patients with PA were 1.97 (95%CI: 1.33, 2.91; P = 0.0007) for a follow-up of 3 years, 0.96 (95%CI: 0.75, 1.23; P = 0.76) for 5 years, 0.86 (95%CI: 0.51, 1.46) for 7.5 years, and 0.95 (95%CI: 0.61, 1.48; P = 0.58) for 10 years. For patients with aldosterone-producing adenomas (APA), evidence of lower risk of long-term mortality was observed. Our sensitivity analysis suggested our results were stable.Conclusions: Current evidence supported a higher risk of mortality for patients with primary aldosteronism at 3 years compared to patients with essential hypertension, however this risk no longer sustains as the follow-up time increased to 5 or more years. Patients with aldosterone-producing adenomas may have lower long-term mortality rate than patients with essential hypertension due to the better recovery of adrenalectomy.

Background: MicroRNA-122 (miR-122), a pivotal liver-specific miRNA, is frequently repressed in hepatocellular carcinoma (HCC) and associated with poor prognosis. Long non-coding RNA (lncRNA) HOTAIR has been proved to function as an oncogene in multiple cancers including HCC. However, the relationship between HOTAIR and miR-122 in HCC remains largely unknown. Methods: We investigated the function of HOTAIR and miR-122 in HCC cell models and a xenograft mouse model. The regulatory network between HOTAIR and miR-122 was further detected following overexpression or knockdown of HOTAIR. DNA methylation status of miR-122 promoter region, as well as expression levels of DNMTs, EZH2 and Cyclin G1 were analyzed. Findings: In this study, we found that HOTAIR was highly expressed whereas miR-122 was suppressed in HCC, and HOTAIR negatively regulated miR-122 expression in HCC cells. Furthermore, knockdown of HOTAIR dramatically inhibited HCC cell proliferation and induced cell cycle arrest in vitro and suppressed tumorigenicity in vivo by upregulating miR-122 expression. Mechanistically, a CpG island was located in the miR-122 promoter region. HOTAIR epigenetically suppressed miR-122 expression via DNMTs-mediated DNA methylation. Moreover, HOTAIR upregulated DNMTs expression via EZH2. In addition, suppression of miR-122 induced by HOTAIR directly reactivated oncogene Cyclin G1 expression. Collectively, our results suggest that HOTAIR epigenetically suppresses miR-122 expression via DNA methylation, leading to activation of Cyclin G1 and promotion of tumorigenicity in HCC, which provide new insight into the mechanism of HOTAIR-mediated hepatocarcinogenesis via suppressing miR-122. Keywords: Hepatocellular carcinoma, LncRNA HOTAIR, microRNA-122, DNA methylation, Epigenetics

Hyperspectral images (HSIs), acquired as a 3D data set, contain spectral and spatial information that is important for ground–object recognition. A 3D convolutional neural network (3DCNN) could therefore be more suitable than a 2D one for extracting multiscale neighborhood information in the spectral and spatial domains simultaneously, if it is not restrained by mass parameters and computation cost. In this paper, we propose a novel lightweight multilevel feature fusion network (LMFN) that can achieve satisfactory HSI classification with fewer parameters and a lower computational burden. The LMFN decouples spectral–spatial feature extraction into two modules: point-wise 3D convolution to learn correlations between adjacent bands with no spatial perception, and depth-wise convolution to obtain local texture features while the spectral receptive field remains unchanged. Then, a target-guided fusion mechanism (TFM) is introduced to achieve multilevel spectral–spatial feature fusion between the two modules. More specifically, multiscale spectral features are endowed with spatial long-range dependency, which is quantified by central target pixel-guided similarity measurement. Subsequently, the results obtained from shallow to deep layers are added, respectively, to the spatial modules, in an orderly manner. The TFM block can enhance adjacent spectral correction and focus on pixels that actively boost the target classification accuracy, while performing multiscale feature fusion. Experimental results across three benchmark HSI data sets indicate that our proposed LMFN has competitive advantages, in terms of both classification accuracy and lightweight deep network architecture engineering. More importantly, compared to state-of-the-art methods, the LMFN presents better robustness and generalization.

Convolutional neural networks (CNNs) are the go-to model for hyperspectral image (HSI) classification because of the excellent locally contextual modeling ability that is beneficial to spatial and spectral feature extraction. However, CNNs with a limited receptive field pose challenges for modeling long-range dependencies. To solve this issue, we introduce a novel classification framework which regards the input HSI as a sequence data and is constructed exclusively with multilayer perceptrons (MLPs). Specifically, we propose a spectral-spatial MLP (SS-MLP) architecture, which uses matrix transposition and MLPs to achieve both spectral and spatial perception in global receptive field, capturing long-range dependencies and extracting more discriminative spectral-spatial features. Four benchmark HSI datasets are used to evaluate the classification performance of the proposed SS-MLP. Experimental results show that our pure MLP-based architecture outperforms other state-of-the-art convolution-based models in terms of both classification performance and computational time. When comparing with the SSSERN model, the average accuracy improvement of our approach is as high as 3.03%. We believe that our impressive experimental results will foster additional research on simple yet effective MLP-based architecture for HSI classification.

Recently, with the extensive application of deep learning techniques in the hyperspectral image (HSI) field, particularly convolutional neural network (CNN), the research of HSI classification has stepped into a new stage. To avoid the problem that the receptive field of naive convolution is small, the dilated convolution is introduced into the field of HSI classification. However, the dilated convolution usually generates blind spots in the receptive field, resulting in discontinuous spatial information obtained. In order to solve the above problem, a densely connected pyramidal dilated convolutional network (PDCNet) is proposed in this paper. Firstly, a pyramidal dilated convolutional (PDC) layer integrates different numbers of sub-dilated convolutional layers is proposed, where the dilated factor of the sub-dilated convolution increases exponentially, achieving multi-sacle receptive fields. Secondly, the number of sub-dilated convolutional layers increases in a pyramidal pattern with the depth of the network, thereby capturing more comprehensive hyperspectral information in the receptive field. Furthermore, a feature fusion mechanism combining pixel-by-pixel addition and channel stacking is adopted to extract more abstract spectral–spatial features. Finally, in order to reuse the features of the previous layers more effectively, dense connections are applied in densely pyramidal dilated convolutional (DPDC) blocks. Experiments on three well-known HSI datasets indicate that PDCNet proposed in this paper has good classification performance compared with other popular models.

Convolutional neural networks (CNNs) have achieved great results in hyperspectral image (HSI) classification in recent years. However, convolution kernels are reused among different spatial locations, known as spatial-agnostic or weight-sharing kernels. Furthermore, the preference of spatial compactness in convolution (typically, 3×3 kernel size) constrains the receptive field and the ability to capture long-range spatial interactions. To mitigate the above two issues, in this article, we combine a novel operation called involution with residual learning and develop a new deep residual involution network (DRIN) for HSI classification. The proposed DRIN could model long-range spatial interactions well by adopting enlarged involution kernels and realize feature learning in a fairly lightweight manner. Moreover, the vast and dynamic involution kernels are distinct over different spatial positions, which could prioritize the informative visual patterns in the spatial domain according to the spectral information of the target pixel. The proposed DRIN achieves better classification results when compared with both traditional machine learning-based and convolution-based methods on four HSI datasets. Especially in comparison with the convolutional baseline model, i.e., deep residual network (DRN), our involution-powered DRIN model increases the overall classification accuracy by 0.5%, 1.3%, 0.4%, and 2.3% on the University of Pavia, the University of Houston, the Salinas Valley, and the recently released HyRANK HSI benchmark datasets, respectively, demonstrating the potential of involution for HSI classification.

Acetoin is an important aroma-active chemical in cereal vinegars. Acetobacter pasteurianus was reported to make a significant contribution to acetoin generation in cereal vinegars. However, the related acetoin biosynthesis mechanism was largely unknown. Two annotated acetolactate synthase (ALS) genes of A. pasteurianus were investigated in this study to analyze their functions and regulatory mechanisms. Heterologous expression in Escherichia coli revealed that only AlsS1 exhibited ALS activity and had the optimal activity at 55 °C and pH 6.5. Two alsS-defective mutants of A. pasteurianus CICC 22518 were constructed, and their acetoin yields were both reduced, suggesting that two alsS genes participated in acetoin biosynthesis. A total 79.1% decrease in acetoin yield in the alsS1-defective mutant revealed that alsS1 took a major role. The regulator gene alsR disruptant was constructed to analyze the regulation effect. The decline of the acetoin yield and down-regulation of the alsD and alsS1 gene transcriptions were detected, but the alsS2 gene transcription was not affected. Acetoin was an important metabolite of lactate catabolism in A. pasteurianus. The coexistence of two alsS genes can help strains rapidly and securely assimilate lactate to deal with the lactate pressure in a vinegar brewing environment, which represented a new genetic mode of acetoin production in bacteria.

WUSCHEL (WUS) is thought to be required for the establishment of the shoot stem cell niche in Arabidopsis thaliana. HEADLESS (HDL), a gene that encodes a WUS-related homeobox family transcription factor, is thought to be the Medicago truncatula ortholog of the WUS gene. HDL plays conserved roles in shoot apical meristem (SAM) and axillary meristem (AM) maintenance. HDL is also involved in compound leaf morphogenesis in M. truncatula; however, its regulatory mechanism has not yet been explored. Here, the significance of HDL in leaf development was investigated. Unlike WUS in A. thaliana, HDL was transcribed not only in the SAM and AM but also in the leaf. Both the patterning of the compound leaves and the shape of the leaf margin in hdl mutant were abnormal. The transcriptional profile of the gene SLM1, which encodes an auxin efflux carrier, was impaired and the plants’ auxin response was compromised. Further investigations revealed that HDL positively regulated auxin response likely through the recruitment of MtTPL/MtTPRs into the HDL repressor complex. Its participation in auxin-dependent compound leaf morphogenesis is of interest in the context of the functional conservation and neo-functionalization of the products of WUS orthologs.

Background: Coronary artery disease (CAD) is a major problem worldwide. As an endothelium-enriched microRNA (miRNA), miR-126 has been reported to serve as a potential biomarker of acute myocardial infarction. However, the relationship between miR-126 and the severity of CAD remains unknown. This study was designed to test whether circulating miR-126 levels are associated with the severity of CAD. Methods: The present study enrolled 40 patients who had risk factors for CAD without angiographically significant CAD, and 110 patients presenting with stable angina pectoris, who were validated left main coronary artery disease (LMCA) and/or multi-vessel disease by coronary angiography. The expression levels of plasma miR-126-5p from all enrolled subjects were estimated by quantitative real-time polymerase chain reaction (qRT-PCR). Then, the relationships between plasma miR-126-5p levels, number of diseased vessels and the corresponding Synergy between PCI with Taxus and Cardiac surgery (SYNTAX) score were analyzed. Results: The expression of circulating miR-126-5p was affected by some CAD risk factors including aging, dyslipidemia and DM. Furthermore, plasma miR-126-5p levels were significantly down-regulated in CAD patients with multi-vessel disease, higher SYNTAX score, rather than isolated LMCA and low SYNTAX score. Conclusion: Circulating miR-126-5p has emerged as a potential biomarker for complexity and severity of CAD in patients with stable angina pectoris.

Cytokinins promote plant growth and development under normal plant growth conditions and also play an important role in plant resistance to stress. Understanding the working mechanisms of cytokinins under adverse conditions will help to make full use of cytokinins in agriculture to increase production and efficiency of land use. In this article, we review the progress that has been made in cytokinin research in plant response to stress and propose its future application prospects.

Background: Preoperative hematological markers that indicate nutritional, coagulation, and inflammation statuses have prognostic value for gliomas. This study aimed to investigate hematological markers with regard to tumor grades, isocitrate dehydrogenase mutations (IDH), age, and sex in patients with gliomas.Methods: From 2008 to 2017, patients with a pathological diagnosis of glioma who underwent surgery were retrospectively enrolled in this study. Information from clinical records, including age, sex, preoperative experiment tests (routine blood tests, biochemistry, and coagulation examinations), pathological results, and IDH status, was collected. A univariable survival analysis was performed. Hematological factors such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte-ratio (PLR), and albumin-to-globulin (AGR) were calculated. The prognostic nutrition index (PNI) was calculated as 10 × serum albumin value (g/dl) + 0.005 × peripheral lymphocyte count (per mm3).Results: Our study included 706 patients. The univariate analysis showed that age, IDH-1, and hematological factors were all significantly associated with overall survival (OS) in patients with gliomas. Our results showed that inflammation markers (NLR, PLR, and fibrinogen) were positively associated with age, whereas AGR was negatively associated with age. The PLR was significantly increased, whereas the AGR and PNI were decreased in women with gliomas, as compared with men. We found that inflammation markers increased and nutrition markers decreased with gliomas grade. However, these hematological markers did not significantly differ with IDH status. NLR was the best single hematological marker for distinguishing glioblastoma (GBM) [0.684 (0.645–0.723)], IDH-wt GBM [0.672 (0.631–0.71)] from other gliomas subtypes. Combinations of age with PNI and age with AGR were the best predictors of GBM [0.750 (0.713–0.786)] and IDH-wt GBM [0.759 (0.719–0.798)], respectively.Conclusion: Preoperative hematological marker levels vary among glioma grades and have high predictive values for GBM.

The convolutional neural network (CNN) can automatically extract hierarchical feature representations from raw data and has recently achieved great success in the classification of hyperspectral images (HSIs). However, most CNN based methods used in HSI classification neglect adequately utilizing the strong complementary yet correlated information from each convolutional layer and only employ the last convolutional layer features for classification. In this paper, we propose a novel fully dense multiscale fusion network (FDMFN) that takes full advantage of the hierarchical features from all the convolutional layers for HSI classification. In the proposed network, shortcut connections are introduced between any two layers in a feed-forward manner, enabling features learned by each layer to be accessed by all subsequent layers. This fully dense connectivity pattern achieves comprehensive feature reuse and enforces discriminative feature learning. In addition, various spectral-spatial features with multiple scales from all convolutional layers are fused to extract more discriminative features for HSI classification. Experimental results on three widely used hyperspectral scenes demonstrate that the proposed FDMFN can achieve better classification performance in comparison with several state-of-the-art approaches.

Filter banks transferred from a pre-trained deep convolutional network exhibit significant performance in heightening the inter-class separability for hyperspectral image feature extraction, but weakening the intra-class consistency simultaneously. In this paper, we propose a new superpixel-based relational auto-encoder for cohesive spectral−spatial feature learning. Firstly, multiscale local spatial information and global semantic features of hyperspectral images are extracted by filter banks transferred from the pre-trained VGG-16. Meanwhile, we utilize superpixel segmentation to construct the low-dimensional manifold embedded in the spectral domain. Then, representational consistency constraint among each superpixel is added in the objective function of sparse auto-encoder, which iteratively assist and supervisedly learn hidden representation of deep spatial feature with greater cohesiveness. Superpixel-based local consistency constraint in this work not only reduces the computational complexity, but builds the neighborhood relationships adaptively. The final feature extraction is accomplished by collaborative encoder of spectral−spatial feature and weighting fusion of multiscale features. A large number of experimental results demonstrate that our proposed method achieves expected results in discriminant feature extraction and has certain advantages over some existing methods, especially on extremely limited sample conditions.