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The Pinus densiflora var. ussuriensis forest is a unique pine forest type in Northeast China. The species grows normally under extremely adverse conditions because it has a strong tolerance to poor soils and drought. It also benefits the ecological environment significantly through water conservation, soil improvement and windbreak and sand fixation, thus making it an important pioneer species for improving site conditions. This paper systematically analyzes the geographical distribution, ecological and community characteristics, species composition and classification of Pinus densiflora var. ussuriensis forests in China through field surveys and literature review. The main findings are:(1) Based on the dominant species of each layer, Pinus densiflora var. ussuriensis forests can be divided into two categories of associations: Pinus densiflora var. ussuriensis - Rhododendron dauricum - Carex callitrichos association and Pinus densiflora var. ussuriensis + Quercus mongolica - Lespedeza bicolor - Carex caespitosa association.(2) According to sample plot surveys, a total of 134 vascular plant species, belonging to 59 families and 104 genera, were recorded in natural Pinus densiflora var. ussuriensis forests. Amongst them were one fern species, two gymnosperm species and 131 angiosperm species.(3) The composition of life forms in Pinus densiflora var. ussuriensis forests is dominated by terrestrial herbs, with fewer woody plants and with vines making up the smallest proportion.(4) The Pinus densiflora var. ussuriensis forests located on the hillocks of Xingkai Lake are in decline. If the soil in this area continues to increase in wetness, this community may eventually evolve into a broad-leaved mixed forest.

Globally, cardiovascular diseases (CVDs) remain the leading cause of death, and their prevention and treatment continue to face major challenges. Oxylipins, as novel circulating markers of cardiovascular disease, are crucial mediators linking cardiovascular risk factors such as inflammation and platelet activation, and they play an important role in unraveling cardiovascular pathogenesis and therapeutic mechanisms. Chinese herbal medicine plays an important role in the adjuvant treatment of cardiovascular diseases, which has predominantly focused on the key pathways of classic lipids, inflammation, and oxidative stress to elucidate the therapeutic mechanisms of cardiovascular diseases. However,The regulatory effect of traditional Chinese medicine on oxylipins in cardiovascular diseases remains largely unknown. With the increasing number of recent reports on the regulation of oxylipins by Chinese herbal medicine in cardiovascular diseases, it is necessary to comprehensively elucidate the regulatory role of Chinese herbal medicine in cardiovascular diseases from the perspective of oxylipins. This approach not only benefits further research on the therapeutic targets of Chinese herbal medicine, but also brings new perspectives to the treatment of cardiovascular diseases.

The diversity of liverworts in China is rich. It is of great significance to study the species distribution pattern of liverworts in China for the protection of liverworts diversity, flora research and biodiversity monitoring. On the basis of records from national and provincial liverwort lists, herbaria and online databases, a dataset of liverwort distributions was created to analyze the geographical distribution patterns of liverwort species diversity in China. According to the taxonomy of liverwort species in the CoLChina database, more than 60,000 distribution records of 34 provincial geographic units were standardized. ArcGIS 10.8 was used to map the overall richness of liverwort species, as were the individual maps of 14 taxonomic groups of liverworts. Southwest China presented very high species richness, followed by Central China and South China, which presented relatively high species richness. The centers of liverwort species diversity in China are highly consistent with the diversity centers of endemic liverwort in China, many sites from coastal areas to Mountains. The specific distribution centers include the Yunnan-Guizhou Plateau, Hengduan Mountain Range, coastal areas in southern China and Taiwan Mountain Range, as well as the Qinling Mountains and Taihang Mountains in the central region and the Changbai Mountains and Xiaoxing’an Mountains in northeast China. There was significant difference in the distribution patterns of liverwort groups among the different provincial regions in China. As large groups, Jungermanniales and Porellales are absolutely dominant, their distribution patterns are similar to the overall richness of liverwort. The distribution center of Jungermanniales is punctate, while the distribution center of Porellales is flaky. However, the diversity centers of the small and medium liverwort groups are abundant, and their distribution patterns are also significantly different, such as, Marchantiales and Metzgeriales are medium-sized taxa. There were five types of small groups. This study will help us record and understand the biogeographic patterns of liverwort, clarify the geographical distribution of the major phylogenetic groups (order) of liverwort, and analyze the geographical distribution of national endemic and provincial endemic liverworts in China, providing a theoretical basis for future assessments of conservation gaps and reasonable conservation actions for liverworts.

Chronic insomnia has the potential to significantly impact physical well-being, occupational performance, and overall quality of life. This review summarizes the clinical and basic research on the central regulatory mechanism of acupuncture in treating primary insomnia (PI), aiming to explore the clinical effectiveness and possible mechanism of acupuncture in treating PI. The currently available drugs for insomnia exhibit notable adverse effects and tend to induce dependence. Empirical evidence from clinical investigations has demonstrated that acupuncture has a favorable safety profile while substantially enhancing the sleep quality of individuals diagnosed with PI. The combination of acupuncture and medication has been shown to augment the therapeutic efficacy of medication while reducing the dosage and mitigating the occurrence of unwanted effects. A review of the current clinical and basic research on the effects of acupuncture on central alterations in PI patients revealed that acupuncture exerts a regulatory influence on the functional activity of brain regions implicated in cognitive and emotional processes. Additionally, acupuncture has been found to impact metabolite levels and circadian clock gene expression and enhance inflammatory responses and energy metabolism. Notably, a single acupuncture intervention had a modulatory effect on functional brain regions similar to that of cumulative acupuncture. The current clinical trials on acupuncture have been limited in scale, and basic research has focused on a single objective. With the continuous progress of brain research, extensive clinical randomized controlled trials of high quality can be combined with various neuroimaging technology modalities. Moreover, different targets and pathways can be explored through basic research. This may serve to enhance the understanding of the fundamental central nervous system mechanisms involved in the efficacy of acupuncture in treating PI.

Novel lattice structures were designed as unit cells through topological optimisation methods. Then the mechanical properties, heat transfer performance, and fluid flow characteristics of functional Ti-6Al-4 V porous components fabricated by laser powder bed melting (LPBF) were investigated, and the comprehensive performance evaluation model was established. Mechanical performance evaluations demonstrated that TopLC-L16 exhibits superior mechanical properties with a compressive strength of 486.87 MPa, a 70.76% improvement over TopFC-L16, and the fracture mechanism reveals a composite mode of ductile and brittle fracture. The temperature distributions indicate that the TopLC-L component exhibits the most efficient heat transfer performance, particularly the TopLC-L16, with a temperature gradient of 242.5 °C and a temperature gradient ratio of 64.7%. A comprehensive evaluation model shows that TopLC-L16 shows the best comprehensive performance. The study highlights the importance of optimising lattice structure design in enhancing mechanical performance and heat transfer efficiency, providing critical insights for advanced engineering applications.

Growing evidences indicate that dysfunction of autophagy contributes to the disease pathogenesis of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), two neurodegenerative disorders. The GGGGCC·GGCCCC repeat RNA expansion in chromosome 9 open reading frame 72 (C9orf72) is the most genetic cause of both ALS and FTD. According to the previous studies, GGGGCC·GGCCCC repeat undergoes the unconventional repeat-associated non-ATG translation, which produces dipeptide repeat (DPR) proteins. Although there is a growing understanding that C9orf72 DPRs have a strong ability to harm neurons and induce C9orf72-linked ALS/FTD, whether these DPRs can affect autophagy remains unclear. In the present study, we find that poly-GR and poly-PR, two arginine-containing DPRs which display the most cytotoxic properties according to the previous studies, strongly inhibit starvation-induced autophagy. Moreover, our data indicate that arginine-rich DPRs enhance the interaction between BCL2 and BECN1/Beclin 1 by inhibiting BCL2 phosphorylation, therefore they can impair autophagic clearance of neurodegenerative disease-associated protein aggregates under starvation condition in cells. Importantly, our study not only highlights the role of C9orf72 DPR in autophagy dysfunction, but also provides novel insight that pharmacological intervention of autophagy using SW063058, a small molecule compound that can disrupt the interaction between BECN1 and BCL2, may reduce C9orf72 DPR-induced neurotoxicity.

2A12 hot-rolled aluminum alloy has high plasticity and toughness, and is widely used in the manufacturing of structural parts in aviation, aerospace, automobiles, and other fields. To explore the effect of friction stir welding process parameters on the welded joint properties of 2A12 hot-rolled aluminum alloy, experimental investigations were conducted. The surface appearance of the welded joints under different process parameters was observed, the microstructure, microhardness, tensile strength, yield strength, elongation and the fracture morphology of the welded joints were assessed. The findings suggested that when the rotation speed was 600 rpm and the forward speed was 250 mm/min, the tensile strength, yield strength and elongation of the welded joint were all maximum, which were 437.6 MPa, 381.6 MPa and 7.5 % respectively, reaching 85.5 %, 88.1 % and 35.7 % of the base material. Under the same forward speed, the tensile strength and elongation of the welded joint initially rose and subsequently declined with the increment of rotation speed. The microhardness distribution of the welded joint exhibited a W-shape pattern. The fracture morphology showed that the fracture type of the welded joint was a ductile fracture. Unlike the base material, the welded joints did not exhibit significant necking during the tensile testing. The research results can be utilized as a reference for the engineering application of friction stir welding of 2A12 hot-rolled aluminum alloy.

Introduction Stimulating acupoints is beneficial for improving heart health but the clinical efficacy of transcutaneous electrical acupoint stimulation (TEAS) as a complementary therapy for chronic coronary syndromes (CCSs) remains unclear. This study aims to evaluate whether TEAS can alleviate angina severity in patients with CCS and to explore the potential mechanisms underlying TEAS.Methods and analysis This study, conducted across two clinical centres, involved 90 participants distributed equally into three groups via simple randomisation (1:1:1 ratio). The research cycle was 28 weeks including a 4-week baseline, 12-week treatment and 12-week follow-up period. All groups will receive basic treatment with the TEAS group additionally receiving 36 sessions of TEAS stimulation over the 12 weeks. The two control groups will either undergo sham TEAS or no additional intervention alongside their basic treatment. The primary outcome is the 6-minute walk test; eight other indicators will serve as secondary outcomes.Ethics and dissemination Approval for this study was granted by the Medical Research Ethics Committee of the Third Clinical Affiliated Hospital of Changchun University of Chinese Medicine in May 2023. Findings will be disseminated through peer-reviewed publications.Trial registration number ChiCTR2400079383.

Research has started using Magnetic Resonance Imaging (MRI) to elucidate the action of acupuncture on neuroplasticity following ischemic stroke (IS). Acupuncture is thought to be a potentially beneficial treatment for IS. However, the results remain inconsistent because of MRI processing techniques and study design variations. Therefore, this coordinate-based meta-analysis and systematic review aimed to assess the current state of knowledge about the regional brain fMRI imaging characteristics in acupuncture-treated IS patients. Twenty studies—including 392 IS patients and 256 health controls—met the inclusion criteria after searches via Chinese and English databases. The design techniques utilized in this research were mainly owned before-and-after controlled and randomized controlled trials. Only one study used independent component analysis (ICA), while the majority of MRI analytical techniques focus on functional connectivity (FC) and fractional amplitude of low-frequency fluctuation (fALFF/ALFF). The findings demonstrated a significant rise in the ALFF value of the left supplementary motor region after treatment with acupuncture. The left cerebellum, right inferior frontal gyrus, and hemisphere lobule VIII all showed substantial activation of Reho values. The triangular portion, BA 48, the left inferior network and inferior longitudinal fasciculus, as well as other brain areas decreased in the left inferior frontal gyrus; most research has used FC analysis employing motor areas as seed regions. We found that acupuncture regulated the motor-related network and reorganized the language-related network. Furthermore, acupuncture appears therapeutic for several IS effects, which may be connected to how acupuncture regulates the brain's plasticity.

In this study, topological optimization techniques were employed to construct innovative TopS lattice structures, to achieve a lightweight design while simultaneously optimizing their mechanical properties and enhancing flow and heat transfer performance. Through model reconstruction and proportional scaling techniques, lightweight configurations with increased surface areas were achieved, leading to the successful fabrication of Ti-6Al-4V lattice structures via Laser Powder Bed Fusion (LPBF) technology. A comprehensive investigation combining numerical simulations and experimental testing revealed that the TopS-L16 lattice structure outperforms TopS-L1 and TopS-L4 in terms of compressive strength, demonstrating values of 386.00 MPa for compressive strength, 352.00 MPa for upper compressive yield strength, and 6938.00 MPa for elastic modulus. Furthermore, multilayer-filled lattice structures were found to effectively improve streamline distribution and vorticity, reducing boundary layers, which indicates a significant enhancement in fluid flow and heat transfer performance, with TopS-L16 exhibiting the best performance. The novelty of this work lies in its exploration of the interplay between lattice structures and their interactions with compressive deformation, energy absorption capabilities, and flow heat transfer.

Abstract Class I KNOTTED-like homeobox (KNOXI) genes are parts of the regulatory network that control the evolutionary diversification of leaf morphology. Their specific spatiotemporal expression patterns in developing leaves correlate with the degrees of leaf complexity between simple-leafed and compound-leafed species. However, KNOXI genes are not involved in compound leaf formation in several legume species. Here, we identify a pathway for dual repression of MtKNOXI function in Medicago truncatula. PINNATE-LIKE PENTAFOLIATA1 (PINNA1) represses the expression of MtKNOXI, while PINNA1 interacts with MtKNOXI and sequesters it to the cytoplasm. Further investigations reveal that UNUSUAL FLORAL ORGANS (MtUFO) is the direct target of MtKNOXI, and mediates the transition from trifoliate to pinnate-like pentafoliate leaves. These data suggest a new layer of regulation for morphological diversity in compound-leafed species, in which the conserved regulators of floral development, MtUFO, and leaf development, MtKNOXI, are involved in variation of pinnate-like compound leaves in M. truncatula.

The importance of the loss function in object detection algorithms based on deep learning has grown significantly technological progress. The accuracy of object detection is significantly affected by bounding box regression, which is a crucial factor. Since the introduction of the Intersection over Union (IoU) loss in 2016, many improvements have been proposed based on this loss function. These studies considered various geometric factors related to bounding boxes, and constructed penalty terms to address this issue. This paper summarizes these functions and introduces a new Fused IoU (FIoU) loss function that leads to superior performance. The FIoU loss function not only solves the problem of gradient vanishing during the backpropagation process of the IoU loss function but also solves the problem of some IoU-based loss functions degenerating into IoU loss functions under certain conditions. In addition, in the simulation experiments, the FIoU loss function resulted in faster convergence speed. In our ablation experiments across different datasets and algorithms, our aim was to compare the mAP metrics under different loss functions. On the test set of the Pascal VOC dataset, employing the Faster R-CNN algorithm, FIoU demonstrated improvements of 1.1% and 1.7% over GIoU and Smooth $\ell _{1}$ , respectively. With the YOLOX algorithm, FIoU outperformed GIoU and IoU by 1.0% and 0.8%. Utilizing the YOLOv7 algorithm, we evaluated seven loss functions, achieving optimal results with FIoU. On the validation set of the MS-COCO 2017 dataset, using YOLOv7 and YOLOv8, FIoU exhibited gains of 0.4%, 0.2%, 0.2% over EIoU, DIoU, GIoU, and 0.3%, 0.5%, 0.3% over EIoU, DIoU, GIoU, respectively.

The microstructure of conventionally solidified and rapidly solidified Ti–46Al–8Nb-2.5V alloys was analyzed with phase transformation geometric models, revealing the phase transformation mechanisms. The β→α→γ phase transformation processes follow Burgers and Blackburn orientation relationships (ORs), respectively, from which the calculated transformation between the β/β0 and γ phases follow K–S OR. Whlie, the direct β/β0→γ phase transformation can be directly observed in the microstructure, which follows a variety of ORs, mainly following the K–S OR but also following the N–W or Bain ORs, most of which deviate from the strict ORs. In cases where N–W and Bain ORs are followed, there is a large dislocation spacing between the habit planes of the β/β0 and γ phases, resulting in low static energy at the interface and narrow elongated morphology of precipitated phases. Conversely, when following K–S OR for β/β0 → γ phase transformation, interfacial migration energy is relatively lower and grain precipitated phases is larger. The rapidly solidified microstructure of Ti–46Al–8Nb-2.5V alloy consists of the massive α2 phase, massive γ phase, and basket-weave β0 phase closely resembling those found in β-type titanium alloys. After annealing at service temperature, the rapidly solidified alloy forms a microstructure highly similar to that of conventionally solidified TiAl alloy. Various metastable phases, such as the Ti2Al, L12 and Ti1.4Al phases, precipitate in the blocky γ phase, which provides a theoretical basis for studying the phase transformations of TiAl alloys in service.

Abstract Feature selection is a fundamental pre‐processing step in machine learning that aims to reduce the dimensionality of a dataset by selecting the most effective features from the original features. This process is regarded as a combinatorial optimization problem, and the grey wolf optimizer (GWO), a novel meta‐heuristic algorithm, has gained popularity in feature selection due to its fast convergence speed and easy implementation. In this paper, an improved binary GWO algorithm incorporating a novel Population Adaptation strategy called PA‐BGWO is proposed. The PA‐BGWO takes into account the characteristics of the feature selection problem and designs three strategies. The proposed strategy includes an adaptive individual update procedure to enhance the exploitation ability and accelerate convergence speed, a head wolf fine‐tuned mechanism to exert the impact on each independent feature of the objective function, and a filter‐based method ReliefF for calculating feature weights with dynamically adjusted mutation probabilities based on the ranking features to effectively escape from local optima. Experimental comparisons with several state‐of‐the‐art feature selection methods on 15 classification problems demonstrate that the proposed approach can select a small feature subset with higher classification accuracy in most cases.

Specimen data play a crucial role in geographical distribution research. In this study, the collection information of liverwort specimens in China was compiled and analyzed to investigate the history, current status, and limitations of liverwort research in China. By utilizing the latest systematic research findings and corresponding environmental data, a niche model was developed to offer theoretical support for exploring the potential geographical distribution and diversity of liverwort resources. A total of 55,427 liverwort specimens were collected in China, resulting in the recording of 1212 species belonging to 169 genera and 63 families. However, there are imbalances in the distributions of liverwort data among different groups, collection units, and geographical areas, with families such as Lejeuneaceae, Porellaceae, and Plagiochilaceae having the highest number of specimens. Similarly, genera such as Porella, Frullania, and Horikawaella were well represented. Remarkably, 125 species had specimen counts exceeding 100. Unfortunately, approximately 51.77% of the species had fewer than 10 recorded specimens. There were four obvious peaks in the collection years of the bryophyte specimens in China, among which the largest collection occurred from 2010 to 2023. Notably, the number of specimens collected at different stages closely aligned with the history of taxonomic research on liverworts in China. The results of the integrity of the liverwort collection indicate that there is insufficient representation of some families and genera, with a concentration of common and widely distributed large families and genera. Tropical and subtropical humid areas are key regions for liverwort diversity, with water and temperature being the primary environmental factors influencing their geographical distribution. The specific temporal and spatial data of species recorded from plant specimens will enhance the study of species diversity, comprehensive protection, and sustainable utilization. Additionally, these data will contribute to the investigation of large-scale biodiversity distribution patterns and the impact of global change on diversity.

Abstract To explore potential metabolomics biomarkers in predicting post-herpetic neuralgia (PHN) induced by herpes zoster (HZ). A total of 90 eligible patients were prospectively enrolled and assigned into an acute pain (ACP) group and a PHN group. Serum samples were collected before clinical intervention to perform metabolomics profiling analyses using gas chromatography mass spectrometry (GC–MS). Key metabolites were identified using partial least squares discriminant analysis (PLS-DA). A binary logistic regression was used to build a combined biomarker model to predict PHN from ACP. The discriminating efficiency of the combined biomarker model was investigated and validated by internal validation. Six metabolites were identified as the key metabolites related to PHN. All these metabolites (N-Acetyl-5-hydroxytryptaMine, glucose, dehydroascorbic acid, isopropyl-beta-d-thiogalactopyranoside, 1,5-anhydro-d-sorbitol, and glutamic acid) were found elevated in the PHN group. Pathway analyses showed that glucose-alanine cycle, tryptophan metabolism, tyrosine metabolism, lactose degradation, malate-aspartate shuttle were top five metabolic pathways evolved in PHN. The AUC was 0.85 (95% CI 0.76–0.93) for the combined biomarker model, and was 0.91 (95% CI 0.84–1.00) for the internal validation data set to predict PHN. Metabolomics analyses of key metabolites could be used to predict PHN induced by HZ.

Abstract Computed tomography (CT) scans have been shown to be an effective way of improving diagnostic efficacy and reducing lung cancer mortality. However, distinguishing benign from malignant nodules in CT imaging remains challenging. This study aims to develop a multiple-scale residual network (MResNet) to automatically and precisely extract the general feature of lung nodules, and classify lung nodules based on deep learning. The MResNet aggregates the advantages of residual units and pyramid pooling module (PPM) to learn key features and extract the general feature for lung nodule classification. Specially, the MResNet uses the ResNet as a backbone network to learn contextual information and discriminate feature representation. Meanwhile, the PPM is used to fuse features under four different scales, including the coarse scale and the fine-grained scale to obtain more general lung features of the CT image. MResNet had an accuracy of 99.12%, a sensitivity of 98.64%, a specificity of 97.87%, a positive predictive value (PPV) of 99.92%, and a negative predictive value (NPV) of 97.87% in the training set. Additionally, its area under the receiver operating characteristic curve (AUC) was 0.9998 (0.99976–0.99991). MResNet's accuracy, sensitivity, specificity, PPV, NPV, and AUC in the testing set were 85.23%, 92.79%, 72.89%, 84.56%, 86.34%, and 0.9275 (0.91662–0.93833), respectively. The developed MResNet performed exceptionally well in estimating the malignancy risk of pulmonary nodules found on CT. The model has the potential to provide reliable and reproducible malignancy risk scores for clinicians and radiologists, thereby optimizing lung cancer screening management.

Abstract Regional bias of N 6-methyladenosine (m6A) mRNA modification avoiding splice site region, calls for an open hypothesis whether exon-intron boundary could affect m6A deposition. By deep learning modeling, we find that exon-intron boundary represses a proportion (12% to 34%) of m6A deposition at adjacent exons (~100 nt to splice site). Experiments validate that m6A signal increases once the host gene does not undergo pre-mRNA splicing to produce the same mRNA. Inhibited m6A sites have higher m6A enhancers and lower m6A silencers locally and show high heterogeneity at different exons genome-widely, with only a small proportion (12% to 15%) of exons showing strong inhibition, enabling more stable mRNAs and flexible protein coding. m6A is majorly responsible for why mRNAs with more exons be more stable. Exon junction complex (EJC) only partially contributes to this exon-intron boundary m6A inhibition in some short internal exons, highlighting additional factors yet to be identified.

China is one of the most biodiverse countries in the world and has given birth to unique ecosystems, abundant species and rich genetic variety. More and more attention has been paid to biodiversity research in China. The Wanda Mountains, located in the east of Heilongjiang Province in northeast Chia, is a northern extension of the Changbai Mountains, one of the main mountains ranges in the region. In this study, we present the first checklist of spermatophyte and invasive alien plant species in the Wanda Mountains, which was compiled using published materials, specimen records and field surveys conducted from 2018 to 2020. This checklist, which has been published in the Global Biodiversity Information Facility (GBIF), provides a comprehensive overview of the plant species richness of the Wanda Mountains.This data paper presents the first checklist of spermatophytes and invasive alien plants in the Wanda Mountains, comprising a total of 704 species and infraspecific taxa. Amongst these, there are 656 native plants belonging to 328 genera and 94 families and 48 invasive alien plants belonging to 39 genera and 20 families. The checklist includes 251 new records of native plants and 39 new records of invasive plants. This is the first widely shared data on an independent floristic unit in northeast China and can serve as a valuable resource for future biodiversity research in this region and, moreover, trigger more biodiversity data papers in this data-valued country.

The development of automated tools using advanced technologies like deep learning holds great promise for improving the accuracy of lung nodule classification in computed tomography (CT) imaging, ultimately reducing lung cancer mortality rates. However, lung nodules can be difficult to detect and classify, from CT images since different imaging modalities may provide varying levels of detail and clarity. Besides, the existing convolutional neural network may struggle to detect nodules that are small or located in difficult-to-detect regions of the lung. Therefore, the attention pyramid pooling network (APPN) is proposed to identify and classify lung nodules. First, a strong feature extractor, named vgg16, is used to obtain features from CT images. Then, the attention primary pyramid module is proposed by combining the attention mechanism and pyramid pooling module, which allows for the fusion of features at different scales and focuses on the most important features for nodule classification. Finally, we use the gated spatial memory technique to decode the general features, which is able to extract more accurate features for classifying lung nodules. The experimental results on the LIDC-IDRI dataset show that the APPN can achieve highly accurate and effective for classifying lung nodules, with sensitivity of 87.59%, specificity of 90.46%, accuracy of 88.47%, positive predictive value of 95.41%, negative predictive value of 76.29% and area under receiver operating characteristic curve of 0.914.

PINK1 (PTEN induced kinase 1) and PRKN-mediated mitophagy is an important mitochondrial quality control pathway which selectively degrades damaged mitochondria and is tightly associated with neurodegenerative diseases, including Parkinson disease and amyotrophic lateral sclerosis. The current model of PINK1-PRKN-mediated mitophagy is that PRKN ubiquitinates multiple outer mitochondrial membrane (OMM) proteins, and then the ubiquitin chains on the OMM interact with autophagy receptors which bind Atg8-family protein labeled phagophores. However, little work has been focused on the PRKN-mediated ubiquitination of inner mitochondrial membrane (IMM) proteins during mitophagy. Our recent work revealed that PRKN binds and ubiquitinates PHB2 (prohibitin 2), an essential IMM protein which was previously recognized as a mitophagy receptor, after the OMM is ruptured by proteasomal degradation. Using biochemical and microscopy approaches, we found that mutations of PRKN-targeted ubiquitination sites on PHB2 decrease the recognition of damaged mitochondria by the phagophore and the clearance of damaged mitochondria. In conclusion, our findings revealed a critical role for PRKN-PHB2 interaction in mitochondrial quality control by regulating IMM-associated recognition of mitochondria by the autophagy machinery.

Graphene oxide particles (GOp) were implanted on the surface of H62 copper alloy to prepare an H62/GOp-modified layer by friction stir surface processing (FSSP). The Raman spectrum and microstructure of the modified layer were tested and analyzed. The results showed that the H62/GOp-modified layer prepared under different parameters by FSSP had characteristic Raman spectrum peaks graphene oxide (GO), which indicates that the modified layer containing GO can be prepared by FSSP on the copper alloy surface. The surface grain structure of the H62/GOp-modified layer of each sample was refined, and their large-angle grain boundary ratios were above 85 % and higher than that of the base metal. In addition, the grain volume fraction in the dynamic recrystallization region of each sample was above 60 vol%, and the maximum was 73.9 vol%, which indicates the desirable microstructure consistency of the H62/GOp-modified layer prepared under different parameters by FSSP.

Autophagy is a critical protein and organelle quality control system, which regulates cellular homeostasis and survival. Growing pieces of evidence suggest that autophagic dysfunction is strongly associated with many human diseases, including neurological diseases and cancer. Among various autophagic regulators, microphthalmia (MiT)/TFE transcription factors, including transcription factor EB (TFEB), have been shown to act as the master regulators of autophagosome and lysosome biogenesis in both physiological and pathological conditions. According to the previous studies, chlorpromazine (CPZ), an FDA-approved antipsychotic drug, affects autophagy in diverse cell lines, but the underlying mechanism remains elusive. In our present study, we find that CPZ treatment induces TFEB nuclear translocation through Rag GTPases, the upstream regulators of mechanistic target of rapamycin complex 1 (mTORC1) signaling. Meanwhile, CPZ treatment also blocks autophagosome–lysosome fusion. Notably, we find a significant accumulation of immature autophagosome vesicles in CPZ-treated cells, which may impede cellular homeostasis due to the dysfunction of the autophagy–lysosome pathway. Interestingly and importantly, our data suggest that the expression of the active form of Rag GTPase heterodimers helps in reducing the accumulation of autophagosomes in CPZ-treated cells, further suggesting a major contribution of the Rag GTPase–mTORC1–TFEB signaling axis in CPZ-induced autophagic impairment.

Gefitinib, a well-known epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor for the targeted therapy of lung cancer, induces autophagy in association with drug resistance. However, it remains unclear whether gefitinib treatment can affect the selective form of autophagy (i.e., mitophagy) and be beneficial for the treatment of human diseases with decreased autophagy, such as neurodegenerative diseases. Here, we show that gefitinib treatment promotes PINK1/Parkin-mediated mitophagy in both nonneuronal and neuronal cells, and this effect is independent of EGFR. Moreover, we found that gefitinib treatment increases the recruitment of the autophagy receptor optineurin (OPTN) to damaged mitochondria, which is a downstream signaling event in PINK1/Parkin-mediated mitophagy. In addition, gefitinib treatment significantly alleviated neuronal damage in TBK1-deficient neurons, resulting in impeded mitophagy. In conclusion, our study suggests that gefitinib promotes PINK1/Parkin-mediated mitophagy via OPTN and may be beneficial for the treatment of neurodegenerative diseases that are associated with defective mitophagy.

IntroductionDiabetic cognitive impairment (DCI) is a chronic complication of the central nervous system (CNS) caused by diabetes that affects learning and memory capacities over time. Recently, acupuncture has been shown to improve cognitive impairment in streptozotocin-induced diabetic rats. However, the effects of electroacupuncture on DCI and its underlying mechanism have not yet been elucidated in detail. MethodsIn this study, we used db/db mice as DCI animal models which showed low cognitive, learning and memory functions. Electroacupuncture significantly ameliorated DCI, which is reflected by better spatial learning and memory function using behavioral tests. The db/db mice with cognitive impairment were randomly divided into a model group (Mod) and an electroacupuncture treatment group (Acup), while db/m mice were used as a normal control group (Con). First, the mice were subjected to behavioural tests using the Morris water maze (MWM), and body weight, blood glucose, insulin, triglycerides (TG) and total cholesterol (TC) were observed; HE, Nissl, and TUNEL staining were used to observe the morphological changes and neuronal apoptosis in the mice hippocampus; Finally, Western blot and rt-PCR were applied to detect the essential proteins and mRNA of ERS and insulin signalling pathway, as well as the expression levels of Tau and Aβ.ResultsElectroacupuncture significantly ameliorated DCI, which is reflected by better spatial learning and memory function using behavioral tests. Moreover, electroacupuncture attenuated diabetes-induced morphological structure change, neuronal apoptosis in the hippocampus of db/db mice. Our results revealed that electroacupuncture could regulate the expression levels of Tau and Aβ by improving hippocampal ERS levels in db/db mice, inhibiting JNK activation, attenuating IRS1 serine phosphorylation, and restoring normal transduction of the insulin signaling pathway.DiscussionIn summary, ERS and insulin signaling pathway paly causal roles in DCI development. Electroacupuncture can significantly alleviate the pathogenesis of DCI, improve mice's learning and memory ability, and improve cognitive dysfunction. This study adds to our understanding of the effect of acupuncture on DCI and opens the door to further research on DCI.

The brown planthopper, Nilaparvata lugens (Stål), is a major pest of rice crops, and its control is critical for food security. Pymetrozine has been recommended as an alternative to imidacloprid for controlling N. lugens, but the pest has developed high resistance to it, making its prohibition and restriction urgent. To address this issue, we conducted a study using a mixture of pymetrozine and zhongshengmycin with the effective ratio of 1:40, to evaluate the fitness costs in N. lugens. Our results showed that N. lugens had a relative fitness of 0.03 under this ratio, with significantly reduced longevity, female and male adult periods, total pre-oviposition days, and fecundity. Moreover, the expression levels of the uricase gene (EC1.7.3.3) and farnesyl diphosphate farnesyl transferase gene (EC2.5.1.21) were reduced in N. lugens. These genes are involved in urea metabolism and steroid biosynthesis pathway, respectively, and their suppression can interfere with the normal nutritional function of N. lugens. Our study demonstrates that the combination of chemical insecticides and antimicrobials can delay the development of resistance and improve the efficiency of pest control. This information is valuable for researchers developing management strategies to delay the development of pymetrozine resistance in N. lugens.

BackgroundAcupuncture, a traditional Chinese medicine therapy, is an effective migraine treatment, especially in improving pain. In recent years, many acupuncture brain imaging studies have found significant changes in brain function following acupuncture treatment of migraine, providing a new perspective to elucidate the mechanism of action of acupuncture.ObjectiveTo analyse and summarize the effects of acupuncture on the modulation of specific patterns of brain region activity changes in migraine patients, thus providing a mechanism for treating migraine by acupuncture.MethodsChinese and English articles published up to May 2022 were searched in three English databases (PubMed, Embase and Cochrane) and four Chinese databases (China national knowledge infrastructure, CNKI; Chinese Biomedical Literature database, CBM; the Chongqing VIP database, VIP; and the Wanfang database, WF). A neuroimaging meta-analysis on ALFF, ReHo was performed on the included studies using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) software. Subgroup analyses were used to compare differences in brain regions between acupuncture and other groups. Meta-regression was used to explore the effect of demographic information and migraine alterations on brain imaging outcomes. Linear models were drawn using MATLAB 2018a, and visual graphs for quality evaluation were produced using R and RStudio software.ResultsA total of 7 studies comprising 236 patients in the treatment group and 173 in the control group were included in the meta-analysis. The results suggest that acupuncture treatment helps to improve pain symptoms in patients with migraine. The left angular gyrus is hyperactivation, and the left superior frontal gyrus and the right superior frontal gyrus are hypoactivated. The migraine group showed hyperactivation in the corpus callosum compared to healthy controls.ConclusionAcupuncture can significantly regulate changes in brain regions in migraine patients. However, due to the experimental design of neuroimaging standards are not uniform, the results also have some bias. Therefore, to better understand the potential mechanism of acupuncture on migraine, a large sample, multicenter controlled trial is needed for further study. In addition, the application of machine learning methods in neuroimaging studies could help predict the efficacy of acupuncture and screen migraine patients suitable for acupuncture treatment.

Nowadays, tardiness has become a significant risk in the logistics industry. To address this problem, we introduce the tardiness risk index to quantify both the magnitude of the tardiness risk and the maximum probability of tardiness occurring. In this paper, we investigate the contract design problem with the tardiness risk index to mitigate the tardiness risk when a fourth-party logistics company (4PL) delegates the delivery task of a client to a third-party logistics company (3PL). Specifically, the contracts are designed in a decentralized system with information symmetry and information asymmetry when 3PL is risk neutral and risk averse. Furthermore, the incentive problems demonstrated that the 3PL is encouraged to make the optimal effort for delivery and the 4PL determines the optimal fixed payment and penalty coefficient. Through analyzing the experimental simulation results, we can find that the contract can effectively mitigate the tardiness risk and the maximum probability of risk occurrence.

Abstract Background Painful diabetic peripheral neuropathy (PDPN) has a great impact on an individual’s quality of life. The current researchers’ previous trial suggested that acupuncture was a promising adjunctive treatment for PDPN. However, the underlying mechanism of action of acupuncture treatment for PDPN is still unclear, especially its effects at the cerebral level. The aim of this trial will be to explore how acupuncture works in treating PDPN by using multimodal cerebral imaging. Method and design This will be a randomized controlled trial. A total of 150 participants will be recruited and assigned to one of three groups: the healthy group, the DM without PDPN group and the DM with PDPN group. Participants in the DM without PDPN and the DM with PDPN groups will each be further divided between an electroacupuncture group and a sham electroacupuncture group. Participants will receive six treatment sessions per week for 4 weeks. Multimodal cerebral imaging includes resting-state functional magnetic resonance imaging (rs-fMRI), diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS); this neurophysiological testing will be the primary outcome measure. Subjective pain scales and blood analysis will be a secondary outcome measure and will be used to assess the clinical efficacy of the intervention. Multimodal cerebral imaging will be used to detect cerebral activity changes in each treatment group. The clinical data and fMRI data will be analysed for all the groups. Multiple correlation regression analyses will be used to assess the association between changes in cerebral functional activity and the improvement of clinical outcomes after acupuncture treatment. Discussion This study is based on the results of the researchers’ previous study, and using combined clinical and cerebral function changes, it will help evaluate the effects of acupuncture on PDPN. The investigation of acupuncture’s central mechanism of action will further expand the understanding of acupuncture treatment of PDPN. Trial registration Chinese Clinical Trial Registry ChiCTR1900024109 . Registered on 26 June 2019.

Abstract Background Diabetic cognitive impairment (DCI) is a serious chronic complication caused by diabetes. The pathogenesis of DCI is complex, but brain nerve injury and brain nerve cell apoptosis are important pathological changes. Multimodal brain imaging is one of the most important techniques to study the neural mechanism of the brain. For the clinical treatment of DCI, there is no effective targeted Western medicine and a lack of clear drug intervention methods. Therefore, there is an urgent need to find effective complementary and alternative methods and clarify their mechanism. This research seeks to explore the multimodal brain imaging effect of “Adjust Zang-fu and Arouse Spirit” electroacupuncture for DCI. Methods This clinical research will be a randomized, sham-controlled pilot trial. Eligible participants will be randomly assigned to the intervention group (n = 60) and the control group (n = 30). The intervention group will be divided into the “Adjust Zang-fu and Arouse Spirit” electroacupuncture group (n = 30) and sham electroacupuncture group (n = 30). All participants will continue to receive routine hypoglycemic therapy. The treatment period is the same in both groups. The primary outcomes include functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), Montreal Cognitive Assessment Scale (MoCA), and Clinical Dementia Rating (CDR). The secondary outcomes include blood glucose and blood lipid tests, Instrumental Activities of Daily Living Scale (IADL), Hachinski Ischemic Scale (HIS), Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS). Outcomes will be assessed at baseline and before and after treatment, and adverse events will be examined. Inter- and intragroup analyses will be performed. Discussion This randomized controlled study, combined with multimodal brain imaging techniques and a clinical evaluation scale, was designed to explore the mechanism of “Adjust Zang-fu and Arouse Spirit” electroacupuncture in improving the central nervous system in DCI. Trial registration Chinese Clinical Trial Registration ChiCTR2000040268 . Registered on 26 November 2020

Unmanned Aerial Vehicles (UAVs) play an important role in remote sensing image classification because they are capable of autonomously monitoring specific areas and analyzing images. The embedded platform and deep learning are used to classify UAV images in real-time. However, given the limited memory and computational resources, deploying deep learning networks on embedded devices and real-time analysis of ground scenes still has challenges in actual applications. To balance computational cost and classification accuracy, a novel lightweight network based on the original GhostNet is presented. The computational cost of this network is reduced by changing the number of convolutional layers. Meanwhile, the fully connected layer at the end is replaced with the fully convolutional layer. To evaluate the performance of the Modified GhostNet in remote sensing scene classification, experiments are performed on three public datasets: UCMerced, AID, and NWPU-RESISC. Compared with the basic GhostNet, the Floating Point Operations (FLOPs) are reduced from 7.85 MFLOPs to 2.58 MFLOPs, the memory is reduced from 16.40 MB to 5.70 MB, and the predicted time is improved by 18.86%. Our modified GhostNet also increases the average accuracy (Acc) (4.70% in AID experiments, 3.39% in UCMerced experiments). These results indicate that our Modified GhostNet can improve the performance of lightweight networks for scene classification and effectively enable real-time monitoring of ground scenes.

BackgroundComputed tomography (CT) is an effective way to scan for lung cancer. The classification of lung nodules in CT screening is completely doctor dependent, which has drawbacks, including difficulty classifying tiny nodules, subjectivity, and high false-positive rates. In recent years, deep convolutional neural networks, a deep learning technology, have been shown to be effective in medical imaging diagnosis. Herein, we propose a deep convolutional neural network technique (TransUnet) to automatically classify lung nodules accurately.MethodsTransUnet consists of three parts: the transformer, the Unet, and global average pooling (GAP). The transformer encodes discriminative features via global self-attention modeling on CT image patches. The Unet, which collects context by constricting route, enables exact lunge nodule localization. The GAP categorizes CT images, assigning each sample a score. Python was employed to pre-process all CT images in the LIDI-IDRI, and the obtained 8,474 images (3,259 benign and 5,215 lung nodules) were used to evaluate the method's performance.ResultsThe accuracies of TransUnet in the training and testing sets were 87.90 and 84.62%. The sensitivity, specificity, and AUC of the proposed TransUnet on the testing dataset were 70.92, 93.17, and 0.862%, respectively (0.844–0.879). We also compared TransUnet to three well-known methods, which outperformed these methods.ConclusionThe experimental results on LIDI-IDRI demonstrated that the proposed TransUnet has a great performance in classifying lung nodules and has a great potential application in diagnosing lung cancer.

The prolonged operation of machines in the production process can lead to continuous deterioration or even failure, and the necessary maintenance measures can alleviate the above negative effects. For this reason, this study investigates a joint optimization problem of single-machine production and preventive maintenance (PM) considering linear deterioration effects. The objective is to obtain an integrated sequence of degrading jobs and PM activities in order to simultaneously minimize the makespan and the total cost. Based on the problem characteristics, an adaptive PM strategy is first designed. To efficiently solve the problem, an improved multi-objective evolutionary algorithm based on decomposition (IMOEA/D) is tailored, where the biased-distribution weight vector is proposed to enhance the search capability at both ends of the Pareto front. Five instances are used to evaluate the performance of the customized IMOEA/D and two classical multi-objective evolutionary algorithms. Numerical studies show that the IMOEA/D can substantially improve the hypervolume metric, the maximum spread metric, and the distributivity of the Pareto front at a slight sacrifice of the spacing metric.

The global supply chain is facing huge uncertainties due to potential emergencies, and the disruption of any link may threaten the security of the supply chain. This paper considers a disruption scenario in which supply disruption and distribution center failure occur simultaneously from the point of view of the manufacturer. A resilient supply chain optimization model is developed based on a combination of proactive and reactive defense strategies, including manufacturer’s raw material mitigation inventory, preference for temporary distribution center locations, and product design changes, with the objective of obtaining maximum expected profit. The proposed stochastic planning model with demand uncertainty is approximated as a mixed integer linear programming model using Latin hypercube sampling (LHS), sample average approximation (SAA), and scenario reduction (SR) methods. In addition, an improved genetic algorithm (GA) is also developed to determine the approximate optimal solution. The algorithm ensures the feasibility of the solution and improves the solving efficiency through specific heuristic repair strategies. Numerical experiments are conducted to verify the application and advantages of the proposed disruption recovery model and approach. The experimental results show that the proposed resilient supply chain optimization model can effectively reduce the recovery cost of manufacturers after disruption, and the proposed approach performs well in dealing with related problems.

In recent years, integration of production scheduling and machine maintenance has gained increasing attention in order to improve the stability and efficiency of flowshop manufacturing systems. This paper proposes a Q-learning-based aquila optimizer (QL-AO) for solving the integrated optimization problem of blocking flowshop scheduling and preventive maintenance since blocking in the jobs processing requires to be considered in the practice manufacturing environments. In the proposed algorithmic framework, a Q-learning algorithm is designed to adaptively adjust the selection probabilities of four key population update strategies in the classic aquila optimizer. In addition, five local search methods are employed to refine the quality of the individuals according to their fitness level. A series of numerical experiments are carried out according to two groups of flowshop scheduling benchmark. Experimental results show that QL-AO significantly outperforms six peer algorithms and two state-of-the-art hybrid algorithms based on Q-Learning on the investigated integrated scheduling problem. Additionally, the proposed Q-learning and local search strategies are effective in improving its performance.

BackgroundAs a non-pharmacological therapy, acupuncture has significant efficacy in treating Mild Cognitive Impairment (MCI) compared to pharmacological therapies. In recent years, advances in neuroimaging techniques have provided new perspectives to elucidate the central mechanisms of acupuncture for MCI. Many acupuncture brain imaging studies have found significant improvements in brain function after acupuncture treatment of MCI, but the underlying mechanisms of brain regions modulation are unclear.ObjectiveA meta-analysis of functional magnetic resonance imaging studies of MCI patients treated with acupuncture was conducted to summarize the effects of acupuncture on the modulation of MCI brain regions from a neuroimaging perspective.MethodsUsing acupuncture, neuroimaging, magnetic resonance, and Mild Cognitive Impairment as search terms, PubMed, EMBASE, Web of Science, Cochrane Library, Cochrane Database of Systematic Reviews, Cochrane Database of Abstracts of Reviews of Effects (DARE), Google Scholar, China National Knowledge Infrastructure (CNKI), China Biology Medicine disk (CBM disk), Wanfang and Chinese Scientific Journal Database (VIP) for brain imaging studies on acupuncture on MCI published up to April 2022. Voxel-based neuroimaging meta-analysis of fMRI data was performed using voxel-based d Mapping with Permutation of Subject Images (SDM-PSI), allowing for Family-Wise Error Rate (FWER) correction correction for correction multiple comparisons of results. Subgroup analysis was used to compare the differences in brain regions between the acupuncture treatment group and other control groups. Meta-regression was used to explore demographic information and altered cognitive function effects on brain imaging outcomes. Linear models were drawn using MATLAB 2017a, and visual graphs for quality evaluation were produced using R software and RStudio software.ResultsA total of seven studies met the inclusion criteria, with 94 patients in the treatment group and 112 patients in the control group. All studies were analyzed using the regional homogeneity (ReHo) method. The experimental design of fMRI included six task state studies and one resting-state study. The meta-analysis showed that MCI patients had enhanced activity in the right insula, left anterior cingulate/paracingulate gyri, right thalamus, right middle frontal gyrus, right median cingulate/paracingulate gyri, and right middle temporal gyrus brain regions after acupuncture treatment. Further analysis of RCT and longitudinal studies showed that Reho values were significantly elevated in two brain regions, the left anterior cingulate/paracingulate gyrus and the right insula, after acupuncture. The MCI group showed stronger activity in the right supramarginal gyrus after acupuncture treatment compared to healthy controls. Meta-regression analysis showed that the right anterior thalamic projection ReHo index was significantly correlated with the MMSE score after acupuncture treatment in all MCI patients.ConclusionsAcupuncture therapy has a modulating effect on the brain regions of MCI patients. However, due to the inadequate experimental design of neuroimaging studies, multi-center neuroimaging studies with large samples are needed better to understand the potential neuroimaging mechanisms of acupuncture for MCI. In addition, machine learning algorithm-based predictive models for evaluating the efficacy of acupuncture for MCI may become a focus of future research.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022287826, identifier: CRD 42022287826.

Prior computational and imaging studies described changes in flow patterns for patients with Marfan syndrome, but studies are lacking for related populations. This pilot study addresses this void by characterizing wall shear stress (WSS) indices for patients with Loeys-Dietz and undifferentiated connective tissue diseases. Using aortic valve-based velocity profiles from magnetic resonance imaging as input to patient-specific fluid structure interaction (FSI) models, we determined local flow patterns throughout the aorta for four patients with various connective tissue diseases (Loeys-Dietz with the native aorta, connective tissue disease of unclear etiology with native aorta in female and male patients, and an untreated patient with Marfan syndrome, as well as twin patients with Marfan syndrome who underwent valve-sparing root replacement). FSI simulations used physiological boundary conditions and material properties to replicate available measurements. Time-averaged WSS (TAWSS) and oscillatory shear index (OSI) results are presented with localized comparison to age- and gender-matched control participants. Ascending aortic dimensions were greater in almost all patients with connective tissue diseases relative to their respective control. Differences in TAWSS and OSI were driven by local morphological differences and cardiac output. For example, the model for one twin had a more pronounced proximal descending aorta in the vicinity of the ductus ligamentum that impacted WSS indices relative to the other. We are optimistic that the results of this study can serve as a foundation for larger future studies on the connective tissue disorders presented in this article.

Leaves are the primary photosynthetic structures, while photosynthesis is the direct motivation of crop yield formation. As a legume plant, peanut (Arachis hypogaea) is one of the most economically essential crops as well as an important source of edible oil and protein. The leaves of A. hypogaea are in the tetrafoliate form, which is different from the trifoliate leaf pattern of Medicago truncatula, a model legume species. In A. hypogaea, an even-pinnate leaf with a pair of proximal and distal leaflets was developed; however, only a single terminal leaflet and a pair of lateral leaflets were formed in the odd-pinnate leaf in M. truncatula. In this study, the development of compound leaf in A. hypogaea was investigated. Transcriptomic profiles revealed that the common and unique differentially expressed genes were identified in a proximal leaflet and a distal leaflet, which provided a research route to understand the leaf development in A. hypogaea. Then, a naturally occurring mutant line with leaf developmental defects in A. hypogaea was obtained, which displayed a pentafoliate form with an extra terminal leaflet. The characterization of the mutant indicated that cytokinin and class I KNOTTED-LIKE HOMEOBOX were involved in the control of compound leaf pattern in A. hypogaea. These results expand our knowledge and provide insights into the molecular mechanism underlying the formation of different compound leaf patterns among species.

Four tool plunging paths including a one-time plunging path and three step-by-step plunging paths were designed to study the effects of the tool plunging path on the welded joint properties of pinless friction stir spot welding (PFSSW). The appearance, cross-sectional microstructure, welding temperature, microhardness, and tensile shear failure load of the PFSSW of thin copper sheets under different tool plunging paths were explored. Furthermore, the fracture modes of welded joints under different tool plunging paths were analyzed. Studies showed that path 1 (plunge total depth at one time) produced the largest range of stirring zone, but the grains in the stirring zone were larger and the width of the thermal-mechanical affected zone was smaller. Path 1 obtained the highest peak temperature during the welding process, and path 3 (plunge 1/3 total depth + plunge 2/3 total depth) gained the lowest peak temperature. The greater the initial plunging amount of the tool, the faster the temperature rise rate in the welding stage. The tensile shear failure loads for path 1, path 2 (plunge 1/2 total depth + plunge 1/2 total depth), path 3, and path 4 (plunge 2/3 total depth + plunge 1/3 total depth) were 8.65 kN, 8.15 kN, 8.25 kN, and 8.85 kN, respectively. The tensile shear failure load of path 4 was 2.3% higher than that of path 1. The fracture modes of welded joints under different tool plunging paths were all nugget pullout fractures. The fracture morphology indicated that the fracture type was ductile fracture. The step-by-step plunging path proposed in this work extends the traditional PFSSW process. The findings of this study can provide a reference for the selection and design of tool plunging paths for PFSSW.

Summary: Soil-borne diseases cause serious economic losses in agriculture. Managing diseases with microbial preparations is an excellent approach to soil-borne disease prevention. However, microbial preparations often exhibit unstable effects, limiting their large-scale application. This review introduces and summarizes disease-suppressive soils, the relationship between carbon sources and the microbial community, and the application of human microbial preparation concepts to plant microbial preparations. We also propose an innovative synthetic microbial community assembly strategy with synergistic prebiotics to promote healthy plant growth and resistance to disease. In this review, a new approach is proposed to improve traditional microbial preparations; provide a better understanding of the relationships among carbon sources, beneficial microorganisms, and plants; and lay a theoretical foundation for developing new microbial preparations.

Introduction Studies have shown that acupuncture has significant therapeutic effects on painful diabetic peripheral neuropathy (PDPN) yet the precise mechanism of action underpinning these effects remains controversial. Resting-state functional MRI (rs-fMRI) is an advanced imaging technique that can be used to monitor changes in the activity of the brain, particularly in PDPN. However, the data from several studies remain inconclusive and there is currently no systematic review and meta-analysis for the use of rs-fMRI in PDPN.Methods and analysis In this study, we will select all eligible studies published on or before 30 June 2021. Four English and four Chinese databases will be searched, specifically, PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, WanFang database, China Science Technology Journal Database (VIP) and China Doctor/Master Dissertations Full-text Database. Only clinical trials and the first cycle of a cross-over trial linked to acupuncture for PDPN will be included in the analysis. The main outcomes include the amplitude of low-frequency fluctuation, regional homogeneity, functional connectivity of the brain, bilateral superficial peroneal nerve sensory nerve conduction velocity, bilateral dorsal current perception threshold values and the degree of subjective pain. The secondary outcomes include biochemical indicators, the degree of depression and anxiety and changes in efficiency. The study selection, data extraction and risk of bias assessment will be performed by two investigators. For statistical analyses, Review Manager V.5.4 software will be used. If necessary, heterogeneity testing, data synthesis, and subgroup analysis will be performed.Ethics and dissemination Our systematic review and meta-analysis will be based on published literature for data extraction and will not include the use of individual patient data and so no ethical approval required.PROSPERO registration number CRD42021211644.

Abstract Background SQUAMOSA Promoter Binding Protein-Likes (SPLs) proteins are plant-specific transcription factors that play many crucial roles in plant growth and development. However, there is little information about SPL family in the model legume Medicago truncatula. Results In this study, a total of 23 MtSPL genes were identified in M. truncatula genome, in which 17 of the MtSPLs contained the putative MtmiR156 binding site at the coding or 3′ UTR regions. Tissue-specific expression pattern analysis showed that most MtmiR156-targeted MtSPLs were highly expressed in seed and pod. The observation of MtmiR156B-overexpressing plants reveals that MtmiR156/MtSPL modules are not only involved in the development of leaves and branches, but also in the seed pod development, especially the formation of spine on pod. Conclusion The spines on pods are developed in many plant species, which allow pods to adhere to the animals, and then be transported on the outside. This study sheds light on the new function of SPL family in seed dispersal by controlling the formation of spiky pod, and provides insights on understanding evolutionary divergence of the members of SPL gene family among plant species.

Seed shattering is an undesirable trait that leads to crop yield loss. Improving silique resistance to shattering is critical for grain and oil crops. In this study, we found that miR319-targeted TEOSINTE BRANCHED 1, CYCLOIDEA, and PROLIFERATING CELL NUCLEAR ANTIGEN BINDING FACTOR (TCPs) inhibited the process of post-fertilized fruits (silique) elongation and dehiscence via regulation of FRUITFULL (FUL) expression in Arabidopsis thaliana and Brassica napus. AtMIR319a activation resulted in a longer silique with thickened and lignified replum, whereas overexpression of an miR319a-resistant version of AtTCP3 (mTCP3) led to a short silique with narrow and less lignified replum. Further genetic and expressional analysis suggested that FUL acted downstream of TCP3 to negatively regulate silique development. Moreover, hyper-activation of BnTCP3.A8, a B. napus homolog of AtTCP3, in rapeseed resulted in an enhanced silique resistance to shattering due to attenuated replum development. Taken together, our findings advance our knowledge of TCP-regulated silique development and provide a potential target for genetic manipulation to reduce silique shattering in Brassica crops.

Tight sandstone gas reservoirs are characterized by deep burial, high pressure, tight matrix, fracture development, and the prevalence of edge and bottom water. Because of the small pore throats, the phenomenon of capillary force is evident. In addition, the low permeability of the reservoir and the difference in fluid properties make the gas reservoir undergo severe water-blocking damage. In this paper, centrifugal and nuclear magnetic resonance methods are used. The relationship between pore throat characteristics, fluid distribution, and gas reservoir water-blocking mechanism is studied and analyzed. The experimental results show that fracture formation increases the porosity of the small pores and expands the pore size distribution. It is conducive to the displacement of the bound water in the small pore space and the reduction in the bound water saturation. When increasing the same displacement pressure, the core porosity increases. More residual water in the tiny pores is converted to moveable water, thereby reducing the capillary resistance. The high-angle penetration fractures and complex seam networks are created by fractures. They connect the pores to form a fracture network structure, which is conducive to the communication of seepage channels. The increase in porosity and the creation of a complex fracture network make the water inrush along the fractures more even in the process of mining. This slows the advance speed of the water invasion front and reduces the damage of water blocking. The results enhance the understanding of the water invasion mechanism of edge and bottom water so as to improve the recovery factors of tight sandstone gas reservoirs.

Formation of nodules on legume roots results from symbiosis with rhizobial bacteria. Here, we identified two GATA transcription factors, MtHAN1 and MtHAN2, in Medicago truncatula, which are the homologs of HANABA TARANU (HAN) and HANABA TARANU LIKE in Arabidopsis thaliana. Our analysis revealed that MtHAN1 and MtHAN2 are expressed in roots and shoots including the root tip and nodule apex. We further show that MtHAN1 and MtHAN2 localize to the nucleus where they interact and that single and double loss-of-function mutants of MtHAN1 and MtHAN2 did not show any obvious phenotype in flower development, suggesting their role is different than their closest Arabidopsis homologues. Investigation of their symbiotic phenotypes revealed that the mthan1 mthan2 double mutant develop twice as many nodules as wild type, revealing a novel biological role for GATA transcription factors. We found that HAN1/2 transcript levels respond to nitrate treatment like their Arabidopsis counterparts. Global gene transcriptional analysis by RNA sequencing revealed different expression genes enriched for several pathways important for nodule development including flavonoid biosynthesis and phytohormones. In addition, further studies suggest that MtHAN1 and MtHAN2 are required for the expression of several nodule-specific cysteine-rich genes, which they may activate directly, and many peptidase and peptidase inhibitor genes. This work expands our knowledge of the functions of MtHANs in plants by revealing an unexpected role in legume nodulation.

Triterpenoid saponins constitute a diverse class of bioactive compounds in medicinal plants. Salicylic acid (SA) is an efficient elicitor for secondary metabolite production, but a transcriptome-wide regulatory network of SA-promoted triterpenoid saponin biosynthesis remains little understood. In the current study, we described the establishment of the hairy root culture system for Psammosilene tunicoides, a triterpenoid saponin-producing medicinal herb in China, using genetic transformation by Agrobacterium rhizogenes. Compared to controls, we found that total saponin content was dramatically increased (up to 2.49-fold) by the addition of 5 mg/L SA in hairy roots for 1 day. A combination of single-molecule real-time (SMRT) and next-generation sequencing (Illumina RNA-seq) was generated to analyze the full-length transcriptome data for P. tunicoides, as well as the transcript profiles in treated (8 and 24 h) and non-treated (0 h) groups with 5 mg/L SA in hairy roots. A total of 430,117 circular consensus sequence (CCS) reads, 16,375 unigenes and 4,678 long non-coding RNAs (lncRNAs) were obtained. The average length of unigenes (2,776 bp) was much higher in full-length transcriptome than that derived from single RNA-seq (1,457 bp). The differentially expressed genes (DEGs) were mainly enriched in the metabolic process. SA up-regulated the unigenes encoding SA-binding proteins and antioxidant enzymes in comparison with controls. Additionally, we identified 89 full-length transcripts encoding enzymes putatively involved in saponin biosynthesis. The candidate transcription factors (WRKY, NAC) and structural genes (AACT, DXS, SE, CYP72A) might be the key regulators in SA-elicited saponin accumulation. Their expression was further validated by quantitative real-time PCR (qRT-PCR). These findings preliminarily elucidate the regulatory mechanisms of SA on triterpenoid saponin biosynthesis in the transcriptomic level, laying a foundation for SA-elicited saponin augmentation in P. tunicoides.

Infrared images are robust against illumination variation and disguises, containing the sharp edge contours of objects. Visible images are enriched with texture details. Infrared and visible image fusion seeks to obtain high-quality images, keeping the advantages of source images. This paper proposes an object-aware image fusion method based on a deep residual shrinkage network, termed as DRSNFuse. DRSNFuse exploits residual shrinkage blocks for image fusion and introduces a deeper network in infrared and visible image fusion tasks than existing methods based on fully convolutional networks. The deeper network can effectively extract semantic information, while the residual shrinkage blocks maintain the texture information throughout the whole network. The residual shrinkage blocks adapt a channel-wise attention mechanism to the fusion task, enabling feature map channels to focus on objects and backgrounds separately. A novel image fusion loss function is proposed to obtain better fusion performance and suppress artifacts. DRSNFuse trained with the proposed loss function can generate fused images with fewer artifacts and more original textures, which also satisfy the human visual system. Experiments show that our method has better fusion results than mainstream methods through quantitative comparison and obtains fused images with brighter targets, sharper edge contours, richer details, and fewer artifacts.

The ultimate goal of semantic web (SW) is to implement mutual collaborations among ontology-based intelligent systems. To this end, it is necessary to integrate those domain-independent and cross-domain ontologies by finding the correspondences between their entities, which is the so-called ontology matching. To improve the quality of ontology alignment, in this work, the ontology matching problem is first defined as a sparse multi-objective optimization problem (SMOOP), and then, a multi-objective evolutionary algorithm with a relevance matrix (MOEA-RM) is proposed to address it. In particular, a relevance matrix (RM) is presented to adaptively measure the relevance of each individual’s genes to the objectives, which is applied in MOEA’s initialization, crossover and mutation to ensure the population’s sparsity and to speed up the the algorithm’s convergence. The experiment verifies the performance of MOEA-RM by comparing it with the state-of-the-art ontology matching techniques, and the experimental results show that MOEA-RM is able to effectively address the ontology matching problem with different heterogeneity characteristics.