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Abstract The design of waveforms plays a critical role in integrated sensing and communication (ISAC) systems. An ISAC waveform with a 0dB peak‐to‐average power ratio (PAPR) is designed by combining a Golay complementary sequence with a constant envelope orthogonal frequency‐division multiplexing. By adjusting the phase modulation parameters, this waveform allows for a trade‐offs between communication and sensing capabilities. The authors focus on several key performance metrics for the proposed ISAC waveform, notably using mutual information as a holistic performance indicator to assess both sensing and communication effectiveness. Through extensive numerical simulations, the authors demonstrate that the ISAC waveform significantly enhances detection probability compared to traditional phase‐modulated waveforms. The findings suggest that this approach is beneficial for designing low PAPR phase‐modulated ISAC waveforms, enhancing both the functionality and efficiency of ISAC systems.

Primula meishanensis K.Huang & Z.X.Fu, sp. nov., a new species of Primulaceae from Meishan City, Sichuan Province, China, is described and illustrated. The morphological data and phylogenetic analysis, based on the complete chloroplast genome, suggest that Primula meishanensis is a separate species closely related to Primula dejuniana. The complete chloroplast genome of Primula meishanensis was 152,175 bp and the complete chloroplast genome of Primula dejuniana was 151,988 bp. The new species differs from the latter by the solitary scape, the length of petiole, acute leaf blade apex and pin flower. The distribution map, morphological comparison of related species and conservation status of the new species are also provided.

Abstract Iron is an essential biomineral in the human body. Here, we describe a subset of iron-loaded cancer-associated fibroblasts, termed as FerroCAFs, that utilize iron to induce immunosuppression in prostate cancer and predict an unfavorable clinical outcome. FerroCAFs secrete myeloid cell-associated proteins, including CCL2, CSF1 and CXCL1, to recruit immunosuppressive myeloid cells. We report the presence of FerroCAFs in prostate cancer from both mice and human, as well as in human lung and ovarian cancers, and identify a conserved cell surface marker, the poliovirus receptor. Mechanistically, the accumulated iron in FerroCAFs is caused by Hmox1-mediated iron release from heme degradation. The intracellular iron activates the Kdm6b, an iron-dependent epigenetic enzyme, to induce an accessible chromatin state and transcription of myeloid cell-associated protein genes. Targeting the FerroCAFs by inhibiting the Hmox1/iron/Kdm6b signaling axis incurs anti-tumor immunity and tumor suppression. Collectively, we report an iron-loaded FerroCAF cluster that drives immunosuppression through an iron-dependent epigenetic reprogramming mechanism and reveal promising therapeutic targets to boost anti-tumor immunity.

Abstract Background Cadonilimab is the first approved dual immune checkpoint inhibitor targeting programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), currently utilized for the treatment of various solid tumors. Oral mucosal adverse reactions, such as oral lichenoid lesions, represent one of the most prevalent immune-related adverse events associated with immune checkpoint antibodies. However, reports detailing oral side effects specifically linked to Cadonilimab are lacking. Documenting these side effects is essential to alert oncologists and stomatologists, facilitating timely intervention for affected patients. Case Presentation We present a case involving a 35-year-old male patient diagnosed with hepatocellular carcinoma who received Cadonilimab following hepatectomy and subsequently developed extensive oral lichenoid lesions along with mucosal erosion at 13–14 weeks post-treatment initiation. A biopsy was conducted revealing immunohistochemical findings of CD3+, CD4+, CD8+, CD20 + lymphocytes, CD68 + macrophages, and α-SMA + myofibroblasts infiltrating the tissue of the oral lichenoid lesions. The patient’s oral lesions improved after administration of systemic and local glucocorticoid therapy alongside cessation of Cadonilimab treatment. Conclusion This report marks the first documented instance of an oral adverse effect associated with Cadonilimab use. It underscores that administration of this agent may lead to significant lichenoid lesions and erosions within the oral cavity—an issue warranting increased vigilance from both oncologists and stomatologists.

Abstract Visual input is not equally processed over space. In recent years, a right visual field advantage during free walking and standing in orientation discrimination and contrast detection task was reported. The current study investigated the underlying mechanism of the previously reported right visual field advantage. It particularly tested if the advantage is driven by a stronger suppression of distracting input from the left visual field or improved processing of targets from the right visual field. Combing behavioural and electrophysiological measurements in a mobile EEG and augmented reality setup, human participants (n = 30) in a standing and a walking condition performed a line orientation discrimination task with stimulus eccentricity and distractor status being manipulated. The right visual field advantage, as demonstrated in accuracy and reaction time, was influenced by the distractor status. Specifically, the right visual field advantage was only observed when the target had an incongruent line orientation with the distractor. Neural data further showed that the right visual field advantage was paralleled by a strong modulation of neural activity in the right hemisphere (i.e. contralateral to the distractor). A significant positive correlation between this right hemispheric event related potential (ERP) and behavioural measures (accuracy and reaction time) was found exclusively for trials in which a target was presented on the right and an incongruent distractor was presented on the left. The right hemispheric ERP component further predicted the strength of the right visual field advantage. Notably, the lateralised brain activity and the right visual field advantage were both independent of stimulus eccentricity and the movement state of participants. Overall, our findings suggest an important role of spatially biased suppression of left distracting input in the right visual field advantage as found in orientation discrimination.

Abstract Interleukin-6 (IL-6) plays a crucial role in the pathogenesis of cardiovascular disease (CVD), and IL-6 receptor (IL-6R) blockade has emerged as a promising therapeutic option. However, their specific therapeutic effects in different types of CVDs remain unclear. This study aimed to assess the efficacy of IL-6R blockade in the management of various CVDs, including hypertension (HTN), coronary heart disease (CHD), myocardial infarction (MI), atrial fibrillation (AF), and heart failure (HF). The Mendelian randomization (MR) approach was utilized to investigate the therapeutic impact of IL-6R blockade on HTN, CHD, MI, AF, and HF based on the genome-wide association study (GWAS) summary statistics. MR-Egger intercept test, Cochran's Q test, and leave-one-out analysis were used for sensitivity analysis to verify the reliability of the MR results. The Bonferroni method was used to correct for bias caused by multiple comparisons. Inverse variance weighted (IVW) results demonstrated that IL-6R blockade significantly influenced CHD (odds ratio (OR) = 0.757, 95% confidence interval (CI): 0.690 - 0.832, P = 5.804 × 10–9) and MI (OR = 0.840, 95% CI: 0.744 - 0.949, P = 0.005). However, IL-6R blockade had no significant effect on HTN (OR = 1.015, 95% CI: 0.950 - 1.084, P = 0.663), AF (OR = 0.905, 95% CI: 0.800 - 1.025, P = 0.116) and HF (OR = 1.012, 95% CI: 0.921 - 1.113, P = 0.805). Genetically predicted IL-6R blockade was associated with a protective effect on CHD and MI, but not HTN, AF and HF. This study's findings offer valuable insights for tailoring IL-6R blockade treatment for different types of CVD, and serve as a reference for future research.

Abstract Background Microbes colonizing each compartment of terrestrial plants are indispensable for maintaining crop health. Although corn stalk rot (CSR) is a severe disease affecting maize (Zea mays) worldwide, the mechanisms underlying host–microbe interactions across vertical compartments in maize plants, which exhibit heterogeneous CSR-resistance, remain largely uncharacterized. Results Here, we investigated the microbial communities associated with CSR-resistant and CSR-susceptible maize cultivars using multi-omics analysis coupled with experimental verification. Maize cultivars resistant to CSR reshaped the microbiota and recruited Bacillus species with three phenotypes against Fusarium graminearum including niche pre-emption, potential secretion of antimicrobial compounds, and no inhibition to alleviate pathogen stress. By inducing the expression of Tyrosine decarboxylase 1 (TYDC1), encoding an enzyme that catalyzes the production of tyramine and dopamine, Bacillus isolates that do not directly suppress pathogen infection induced the synthesis of berberine, an isoquinoline alkaloid that inhibits pathogen growth. These beneficial bacteria were recruited from the rhizosphere and transferred to the stems but not grains of the CSR-resistant plants. Conclusions The current study offers insight into how maize plants respond to and interact with their microbiome and lays the foundation for preventing and treating soil-borne pathogens. Video Abstract

The species of Carpesium lipskyi C.Winkl. 1998 is an important traditional Chinese medicine in China. In this study, the complete chloroplast (cp) genome of C. lipskyi was determined and analyzed. The result showed that the complete cp genome of C. lipskyi was 151,244 bp in length, consisting of a large single-copy (LSC) region of 82,908 bp, a small single-copy (SSC) region of 18,430 bp, and a pair of inverted repeats (IRs) of 24,953 bp. The overall GC content of the C. lipskyi is 37.68%. The species of C. lipskyi possessed 127 genes, including 83 protein-coding genes, 36 transfer RNA genes, and eight ribosomal RNA genes. The present study found that Inula is sister groups with the closest genetic relationship. The obtained knowledge could provide useful information for future phylogenetic, taxonomic, and evolutionary studies on Inuleae.

Abstract Data scarcity is one of the critical bottlenecks to utilizing machine learning in material discovery. Transfer learning can use existing big data to assist property prediction on small data sets, but the premise is that there must be a strong correlation between large and small data sets. To extend its applicability in scenarios with different properties and materials, here we develop a hybrid framework combining adversarial transfer learning and expert knowledge, which enables the direct prediction of carrier mobility of two-dimensional (2D) materials using the knowledge learned from bulk effective mass. Specifically, adversarial training ensures that only common knowledge between bulk and 2D materials is extracted while expert knowledge is incorporated to further improve the prediction accuracy and generalizability. Successfully, 2D carrier mobilities are predicted with the accuracy over 90% from only crystal structure, and 21 2D semiconductors with carrier mobilities far exceeding silicon and suitable bandgap are successfully screened out. This work enables transfer learning in simultaneous cross-property and cross-material scenarios, providing an effective tool to predict intricate material properties with limited data.

Abstract Background Mammalian or mechanistic target of rapamycin complex 1 (mTORC1) is an effective therapeutic target for diseases such as cancer, diabetes, aging, and neurodegeneration. However, an efficient tool for monitoring mTORC1 inhibition in living cells or tissues is lacking. Results We developed a genetically encoded mTORC1 sensor called TORSEL. This sensor changes its fluorescence pattern from diffuse to punctate when 4EBP1 dephosphorylation occurs and interacts with eIF4E. TORSEL can specifically sense the physiological, pharmacological, and genetic inhibition of mTORC1 signaling in living cells and tissues. Importantly, TORSEL is a valuable tool for imaging-based visual screening of mTORC1 inhibitors. Using TORSEL, we identified histone deacetylase inhibitors that selectively block nutrient-sensing signaling to inhibit mTORC1. Conclusions TORSEL is a unique living cell sensor that efficiently detects the inhibition of mTORC1 activity, and histone deacetylase inhibitors such as panobinostat target mTORC1 signaling through amino acid sensing.

BackgroundPrevious studies have shown an association between lipid-lowering drugs, circulating inflammatory factors, and atrial fibrillation (AF), but the specific effects of lipid-lowering drugs on AF and whether they can be mediated by circulating inflammatory factors remain unclear.MethodsWe collected 10 genetic variants encoding lipid-lowering drug targets (LDLR, HMGCR, PCSK9, NPC1L1, APOB, APOB, ABCG5, ABCG8, LPL, APOC3, and PPARA) and AF based on genome-wide association study (GWAS) summary statistics. Drug target Mendelian randomization (MR) was used to explore the causal relationship between lipid-lowering drugs and AF. In addition, we performed a mediation analysis of 91 circulating inflammatory factors to explore potential mediators. Sensitivity analyses were performed to verify the reliability of the MR Results by MR-Egger intercept test, Cochran's Q test and leave-one-out test.ResultsThe results of IVW method showed that LPL agonist had a protective effect on AF(OR = 0. 854, 95%CI: 0.816–0.894, P = 1.844E-11). However, the other nine lipid-lowering drug targets had no significant effect on AF. Notably, we found a mediator role of Fibroblast Growth Factor 5 (FGF5) in the protective effect of LPL agonist on AF with a mediator ratio of 9.22%. Sensitivity analyses supported the robustness of our findings, indicating a possible mediating pathway by which LPL agonists affect the risk of AF.ConclusionOur study provides new insights into the complex interactions among lipid-lowering agents, circulating inflammatory factors and AF, and also identified a potential mediating role of FGF5 in the pathogenesis of AF. Our findings highlight the potential of LPL agonists and targeting specific inflammatory factors for therapeutic intervention in AF, providing promising avenues for future research and clinical strategies for the management and prevention of AF.

Bone defects are highly prevalent diseases caused by trauma, tumors, inflammation, congenital malformations and endocrine abnormalities. Ideally effective and side effect free approach to dealing with bone defects remains a clinical conundrum. Klotho is an important protein, which plays an essential role in regulating aging and mineral ion homeostasis. More recently, research revealed the function of Klotho in regulating skeleton development and regeneration. Klotho has been identified in mesenchymal stem cells, osteoblasts, osteocytes and osteoclasts in different skeleton regions. The specific function and regulatory mechanisms of Klotho in long bone and craniofacial bone vary due to their different embryonic development, ossification and cell types, which remain unclear and without conclusion. Moreover, studies have confirmed that Klotho is a multifunctional protein that can inhibit inflammation, resist cancer and regulate the endocrine system, which may further accentuate the potential of Klotho to be the ideal molecule in inducing bone restoration clinically. Besides, as an endogenous protein, Klotho has a promising potential for clinical therapy without side effects. In the current review, we summarized the specific function of Klotho in long bone and craniofacial skeleton from phenotype to cellular alternation and signaling pathway. Moreover, we illustrated the possible future clinical application for Klotho. Further research on Klotho might help to solve the existing clinical difficulties in bone healing and increase the life quality of patients with bone injury and the elderly.

Abstract Dichrocephala benthamii C. B. Clarke has long been used as traditional Chinese medicine. However, the chloroplast (cp) genome of D. benthamii is poorly understood so far. In this study, we sequenced and analyzed the cp genome of D. benthamii. The results showed that the cp genome is 152,350 bp in length, with a pair of inverted repeat regions (IRa and IRb, each 24,982 bp), a large single-copy (LSC) region comprising 84,136 bp, and a small single-copy (SSC) region comprising 18,250 bp. The GC content of the cp genome was 37.3%. A total of 134 genes were identified, including 87 protein-coding genes (CDS), 38 tRNA genes, 8 rRNA genes, and 1 pseudogene (ycf1). Expansion or contraction of IR regions were detected in D. benthamii and other species of the tribe Astereae. Additionally, our analyses showed the types of sequence repeats and the highly variable regions discovered by analyzing the border regions, sequence divergence, and hot spots. The phylogenetic analysis revealed D. benthamii is the basal group of Astereae. The results of this study will be a significant contribution to the genetics and species identification related to D. benthamii.

PurposesOsimertinib, one of the third-generation EGFR-tyrosine kinase inhibitors (TKIs) designed to target EGFR T790M mutation, significantly improves the prognosis of lung cancer. However, drug resistance still happens and MET amplification is responsible for one of the main causes. Fluorescence in situ hybridization (FISH) is the gold standard for MET amplification detection, but fundamentally limited by observer subjectivity. Herein, we assessed the value of next-generation sequencing (NGS) method in MET amplification detection in non-small cell lung cancer (NSCLC), as well as revealed the mutation profiling of NSCLC patients with osimertinib resistance to provide some valuable clues to the mechanisms of resistance.MethodsA total of 317 cancer tissue samples from 317 NSCLC patients at time of progression following osimertinib were submitted to NGS and only 96 tissues were tested by FISH simultaneously. With FISH results as gold standard, enumeration algorithm was applied to establish the optimal model for identifying MET amplification using gene copy number (GCN) data.ResultsThe optimal model for identifying MET amplification was constructed based on the GCN of MET, BRAF, CDK6 and CYP3A4, which achieved a 74.0% overall agreement with FISH and performed well in identifying MET amplification except polysomy with a sensitivity of 85.7% and a specificity of 93.9%. The inconsistency between NGS and FISH occurred mainly in polysomy subtype, while MET GCN ≥ 5 could be reliably recognized by NGS. Moreover, the most frequently mutated genes in NSCLC patients with osimertinib resistance were EGFR (59.94%), followed by TP53 (43.85%), NRG1 (9.46%), PIK3CA (6.31%), and ATM (5.36%). The known resistance mechanisms, including MET amplification, EGFR (C797S, L718Q/R), TP53, CDK4, CDK6, CDKN2A, BRAF, KRAS, NRAS and PIK3CA mutations were also disclosed in our cohort.ConclusionsNGS assay can achieve a high concordance with FISH in MET amplification detection and has advantages in portraying various genetic alterations, which is of worthy in clinical promotion.

Modeling long-range dependencies among features has become a consensus to improve the results of single image super-resolution (SISR), which stimulates interest in enlarging the kernel sizes in convolutional neural networks (CNNs). Although larger kernels definitely improve the network performance, network parameters and computational complexities are raised sharply as well. Hence, an optimization of setting the kernel sizes is required to improve the efficiency of the network. In this work, we study the influence of the positions of larger kernels on the network performance, and propose a scalable attention network (SCAN). In SCAN, we propose a depth-related attention block (DRAB) that consists of several multi-scale information enhancement blocks (MIEBs) and resizable-kernel attention blocks (RKABs). The RKAB dynamically adjusts the kernel size concerning the locations of the DRABs in the network. The resizable mechanism allows the network to extract more informative features in shallower layers with larger kernels and focus on useful information in deeper layers with smaller ones, which effectively improves the SR results. Extensive experiments demonstrate that the proposed SCAN outperforms other state-of-the-art lightweight SR methods. Our codes are available at https://github.com/ginsengf/SCAN.

Summary: Background: Oesophagogastroduodenoscopy (OGD) quality and identification of the early upper gastrointestinal (UGI) neoplasm play an important role in detecting the UGI neoplasm. However, the optimal method for quality control in daily OGD procedures is currently lacking. We aimed to evaluate the efficacy of a real-time intelligent quality-control system (IQCS), which combines OGD quality control with lesion detection of early UGI neoplasms. Methods: We performed a multicentre, single-blinded, randomised controlled trial at 6 hospitals in China. Patients aged 40–80 years old who underwent painless OGD were screened for enrolment in this study. Patients with a history of advanced UGI cancer, stenosis, or obstruction in UGI tract were excluded. Eligible subjects were randomly assigned (1:1) to either the routine or IQCS group to undergo standard OGD examination and OGD examination aided by IQCS, respectively. Patients were masked to the randomisation status. The primary outcome was the detection of early UGI neoplasms. All analyses were done on a per-protocol basis. This trial is registered with ClinicalTrials.gov, NCT04720924. Findings: Between January 16, 2021 and December 23, 2022, 1840 patients were randomised (IQCS group: 919, routine group: 921). The full analysis set consisted of 914 in the IQCS group and 915 in the routine group. The early UGI neoplasms detection rate in the IQCS group (6.1%, 56/914) was significantly higher than in the routine group (2.3%, 21/915; P = 0.0001). The IQCS group had fewer blind spots (2.3 vs. 6.2, P

Shouchenglu is the first monograph on urban defense in ancient China. Based on Shouchenglu, combined with relevant historical documents and image data, this paper sorts out its content, and chooses to explore the internal logic of the evolution of urban defense in the Song Dynasty from three new perspectives: urban defense structure, city walls and their ancillary facilities, and coping strategies for siege weapons. We have carried out graphic translation of the miscellaneous contents of it, and through drawing analysis charts, we can more intuitively show the evolution of the urban defense system in the Song Dynasty and put forward analysis and conjecture. Through the study of Shouchenglu, we found that the evolution of the urban defense system in the Song Dynasty had a clear evolutionary logic. The evolution of the urban defense system in the Song Dynasty was not only the progress of architectural technology, but also the improvement of adaptability in the face of various complex situations. We believe that our research results have certain reference significance for the future urban excavation and the protection and restoration of historical heritage in the Song Dynasty.

Abstract Natural language inference (NLI) is a fundamental task of natural language processing (NLP). Most recent NLI research has focused on explaining the model’s decisions in generating causal explanations (i.e., why did a premise/hypothesis pair as input lead to their inference relation as output?). As layer-based language models can learn language structure information, this paper conducts a sample-by-sample analysis of the linguistic feature relation between premise and hypothesis that is expected to guide NLI modeling and interpretation better. Our empirical study verifies that the linguistic feature relation of premise/hypothesis pairs can be seen in NLI inference models, which can be used to interpret inference samples. Meanwhile, experimental results show that these linguistic features relation interpretation can help the NLI model achieve comparable inference accuracy compared with state-of-the-art methods.

Abstract Silicon (Si) anodes, known for their high capacity, confront obstacles such as volume expansion, the solid–electrolyte interface (SEI) formation, and limited cyclability, driving ongoing research for innovative solutions to enhance their performance in next‐generation lithium‐ion batteries (LIBs). This comprehensive review explores the forefront of one‐dimensional (1D) Si/carbon anodes for high‐performance LIBs. This review delves into cutting‐edge strategies for fabricating 1D Si/carbon structures, such as nanowires, nanotubes, and nanofibers, highlighting their advantages in mitigating volume expansion, enhancing electron/ion transport, and bolstering cycling stability. The review showcases remarkable achievements in 1D Si/carbon anode performance, including exceptional capacity retention, high‐rate capability, and prolonged cycle life. Challenges regarding scalability, cost‐effectiveness, and long‐term stability are addressed, providing insights into the path to commercialization. Additionally, future directions and potential breakthroughs are outlined, guiding researchers and industries toward harnessing the potential of 1D Si/carbon anodes in revolutionizing energy storage.

Abstract NF-κB signaling has been discovered for nearly 40 years. Initially, NF-κB signaling was identified as a pivotal pathway in mediating inflammatory responses. However, with extensive and in-depth investigations, researchers have discovered that its role can be expanded to a variety of signaling mechanisms, biological processes, human diseases, and treatment options. In this review, we first scrutinize the research process of NF-κB signaling, and summarize the composition, activation, and regulatory mechanism of NF-κB signaling. We investigate the interaction of NF-κB signaling with other important pathways, including PI3K/AKT, MAPK, JAK-STAT, TGF-β, Wnt, Notch, Hedgehog, and TLR signaling. The physiological and pathological states of NF-κB signaling, as well as its intricate involvement in inflammation, immune regulation, and tumor microenvironment, are also explicated. Additionally, we illustrate how NF-κB signaling is involved in a variety of human diseases, including cancers, inflammatory and autoimmune diseases, cardiovascular diseases, metabolic diseases, neurological diseases, and COVID-19. Further, we discuss the therapeutic approaches targeting NF-κB signaling, including IKK inhibitors, monoclonal antibodies, proteasome inhibitors, nuclear translocation inhibitors, DNA binding inhibitors, TKIs, non-coding RNAs, immunotherapy, and CAR-T. Finally, we provide an outlook for research in the field of NF-κB signaling. We hope to present a stereoscopic, comprehensive NF-κB signaling that will inform future research and clinical practice.

The appropriate volume of filtered water samples is crucial for accurately reflecting microbial community characteristics. Previous research has shown that changes in water sample volumes significantly affect bacterial diversity and the relative abundance of dominant taxa in marine environments. However, the specific impact on freshwater microbial diversity and community structure, particularly for eukaryotic microorganisms, remains unclear. To address this gap, we collected water samples from eutrophic Lake Taihu and mesotrophic Lake Bosten. We filtered the samples through 0.2 μm filters using volumes ranging from 0.1 to 2 L for Lake Taihu and 0.1 to 3.2 L for Lake Bosten. Analysis of 18S rRNA gene amplicons revealed that variations in filtered water sample volume significantly affected the diversity, community structure, and composition of eukaryotic microorganisms. In light of these findings, we recommend using a filtered water sample volume of approximately 0.2 L for eutrophic aquatic ecosystems and 0.8 L for mesotrophic aquatic ecosystems in microbial analyses. These recommendations underscore the importance of selecting the appropriate filtered water sample volume to ensure representative and reliable results in the study of eukaryotic microorganisms in freshwater ecosystems.

To investigate the optimum parameters of gas chromatography ion mobility spectrometry (GC-IMS) in determination of flavors and fragrances in tobacco. The effects of reaction parameters such as chromatographic column temperature, incubation temperature, incubation time and injection volume are evaluated with the number of identified characteristic peaks, peak intensity and peak pacing as indexes by an orthogonal L9 (34) test. Furthermore, prediction of test results is conducted based on the PLS method. Particle Swarm Optimization (PSO) is used to optimize the parameters. The collection of 30 different flavors and fragrances are tested by GC – IMS which operation parameters are set according to optimal results. The results show that a total of 60 kinds of the volatile organic compounds (VOCs) are identified across all samples, including aldehydes, ketones, alcohols, esters, ethers and so on. Therefore, by means of fingerprints can infer the general composition of fragrance-base or distinguish flavors and fragrances.

Xanthomonas citri subsp. citri (Xcc), the causal agent of citrus canker, elicits canker symptoms in citrus plants because of the transcriptional activator-like (TAL) effector PthA4, which activates the expression of the citrus susceptibility gene CsLOB1. This study reports the regulation of the putative carbohydrate-binding protein gene Cs9g12620 by PthA4-mediated induction of CsLOB1 during Xcc infection. We found that the transcription of Cs9g12620 was induced by infection with Xcc in a PthA4-dependent manner. Even though it specifically bound to a putative TAL effector-binding element in the Cs9g12620 promoter, PthA4 exerted a suppressive effect on the promoter activity. In contrast, CsLOB1 bound to the Cs9g12620 promoter to activate its expression. The silencing of CsLOB1 significantly reduced the level of expression of Cs9g12620, which demonstrated that Cs9g12620 was directly regulated by CsLOB1. Intriguingly, PhtA4 interacted with CsLOB1 and exerted feedback control that suppressed the induction of expression of Cs9g12620 by CsLOB1. Transient overexpression and gene silencing revealed that Cs9g12620 was required for the optimal development of canker symptoms. These results support the hypothesis that the expression of Cs9g12620 is dynamically directed by PthA4 for canker formation through the PthA4-mediated induction of CsLOB1.

Abstract Pure shift NMR spectroscopy enables the robust probing on molecular structure and dynamics, benefiting from great resolution enhancements. Despite extensive application landscapes in various branches of chemistry, the long experimental times induced by the additional time dimension generally hinder its further developments and practical deployments, especially for multi‐dimensional pure shift NMR. Herein, this study proposes and implements the fast, reliable, and robust reconstruction for accelerated pure shift NMR spectroscopy with lightweight attention‐assisted deep neural network. This deep learning protocol allows one to regain high‐resolution signals and suppress undersampling artifacts, as well as furnish high‐fidelity signal intensities along with the accelerated pure shift acquisition, benefitting from the introduction of the attention mechanism to highlight the spectral feature and information of interest. Extensive results of simulated and experimental NMR data demonstrate that this attention‐assisted deep learning protocol enables the effective recovery of weak signals that are almost drown in the serious undersampling artifacts, and the distinction and recognition of close chemical shifts even though using merely 5.4% data, highlighting its huge potentials on fast pure shift NMR spectroscopy. As a result, this study affords a promising paradigm for the AI‐assisted NMR protocols toward broader applications in chemistry, biology, materials, and life sciences, and among others.

The genus Ainsliaea DC. is one of the major groups within the tribe Pertyeae (Asteraceae). It comprises several important Chinese medicinal species. However, the phylogenetic position has undergone a long process of exploration. The complete chloroplast (cp) genome sequences data has not been employed in species identification and phylogeny of Ainsliaea. In this study, the complete cp genomes of two Ainsliaea species (A. gracilis and A. henryi) were reported, followed by structural, comparative, and phylogenetic analyses within the tribe Peryteae. Both cp genomes displayed a typical quadripartite circular structure, with the LSC and SSC regions separated by the IR regions. The genomes were 152,959 (A. gracilis) and 152,805 (A. henryi) base pairs (bp) long, with a GC content of 37.6%. They were highly conserved, containing 134 genes, including 87 protein-coding genes, 37 tRNA genes, 8 rRNA genes, and 2 pseudogenes (rps19 and ycf1). Moreover, thirteen highly polymorphic regions (e.g., trnK-UUU, trnG-UCC, trnT-GGU, accD-psaI, and rpl22-rps19) were identified, indicating their potential as DNA barcodes. The phylogenetic analysis confirmed the placement of Ainsliaea in the tribe Pertyeae, revealing close relationships with the genera Myripnois and Pertya. In comparison with Ainsliaea, Myripnois was more closely related to Pertya. This study lays a theoretical foundation for future research on species identification, population genetics, resource conservation, and sustainable utilization within Ainsliaea and Pertyeae.

In order to solve the problems of conventional water injection development difficulties and low recovery factor in low-permeability reservoirs, the method of high-pressure air drive is adopted to achieve the purpose of reservoir energy enhancement and efficiency improvement. This paper conducted an experimental study on the mechanism of low-temperature oxidation (LTO) for crude oil in the process of high-pressure air flooding, elaborated the relationship between the LTO properties of crude oil and the temperature, pressure, and water saturation of the reservoir, and analyzed the differences in LTO oxygen consumption and oil components under different reaction conditions. In addition, combined with the air flooding physical simulation experiment, the dynamic evolution law of recovery rate in the air flooding process was revealed. Findings from this inquiry indicate that an escalation in the oxidation temperature significantly amplifies the oxygen incorporation reaction within the crude oil matrix. This augmentation in oxidative conditions leads to an uptick in oxygen consumption, which subsequently precipitates a reduction in the lighter fractions of the oxidized oil while enriching its heavier components. Elevated pressures were found to enhance the propensity for the amalgamation of unstable hydrocarbons with oxygen, fostering comprehensive and heterogeneous oxidation reactions. Notably, an excessive presence of water was observed to detrimentally affect the thermal efficacy of crude oil oxidation processes. In the context of low-permeability reservoirs, air injection techniques have emerged as superior in effectuating oil displacement, although an increase in injection pressures has been associated with the phenomenon of gas channeling. Interestingly, adopting a sequential strategy of initiating water flooding before air flooding facilitated the conveyance of high-pressure air via established flushing channels, although it appeared to attenuate the intensity of crude oil oxidation, culminating in an oil recovery efficiency peaking at 51%.

BackgroundChronic heart failure (CHF) patients exhibit alterations in cerebral cortical structure and cognitive function. However, the mechanisms by which CHF affects cortical structure and functional regions remain unknown. This study aims to investigate potential causal relationship between CHF and cerebral cortical structure through Mendelian randomization (MR).MethodsThe research utilized genome-wide association studies (GWAS) to explore the causal association between CHF and cerebral cortical structure. The results were primarily analyzed using the inverse-variance weighted (IVW). The reliability of the data was verified through horizontal pleiotropy and heterogeneity analysis by MR-Egger intercept test and Cochran's Q-test, respectively. Replication analysis was conducted in the Integrative Epidemiology Unit (IEU) OpenGWAS project for further validation. In addition, we collected mediator genes that mediate causality to reveal potential mechanisms. Integrated bioinformatics analysis was conducted using the Open Target Genetics platform, the STRING database, and Cytoscape software.ResultsThe IVW results did not reveal any significant causal association between genetically predicted CHF and the overall structure of the cerebral cortex or the surface area (SA) of the 34 functional regions of the cerebral cortex (P > 0.05). However, the results revealed that CHF increased the thickness (TH) of pars opercularis (IVW: β = 0.015, 95% CI: 0.005–0.025, P = 3.16E-03). Replication analysis supported the causal association between CHF and pars opercularis TH (IVW: β = 0.02, 95% CI: 0.010–0.033, P = 1.84E-04). We examined the degree centrality values of the top 10 mediator genes, namely CDKN1A, CELSR2, NME5, SURF4, PSMA5, TSC1, RPL7A, SURF6, PRDX3, and FTO.ConclusionGenetic evidence indicates a positive correlation between CHF and pars opercularis TH.

BackgroundPsoriasis is a chronic dermatological condition characterized by a complex pathogenesis that impacts approximately 3% of adults in the United States and brings enormous social burdens. For many diseases, the systemic immune-inflammatory index (SII), defined as neutrophils × platelets/lymphocytes, has been recognized as a prognostic indicator. Therefore, we conducted a cross-sectional study to assess the association between SII and psoriasis among outpatient US adults.MethodsIn this cross-sectional study, we used data on the US adults 20 to 59 years of age from the National Health and Nutrition Examination Survey (NHANES) spanning 2003–2006 and 2009–2014. Sample-weighted logistic regression and stratified analysis of subgroups were used.ResultsAmong the 16,831 adults, there were 8,801 women and 8,030 men, with a psoriasis prevalence rate of 3.0%. A fully adjusted model revealed a positive association between a SII higher than 479.15 × 109/L and a high risk of psoriasis. According to subgroup analysis and interaction testing (p for interaction > 0.05), age, sex, alcohol drinking status, marital status, and body mass index (BMI) were not significantly correlated with this positive association.ConclusionOur findings suggested that SII higher than 479.15 × 109/L was positively associated with a high risk of psoriasis among outpatient US adults. To the best of our knowledge, this is the first cross-sectional study using NHANES data focused on the risk of higher SII on psoriasis among outpatient US adults. The outcomes of this cross-sectional serve to supplement previous research, indicating a need for larger-scale prospective cohorts for further validation.

Microorganisms have a significant role in regulating the absorption and transportation of Cd in the soil-plant system. However, the mechanism by which key microbial taxa play a part in response to the absorption and transportation of Cd in rice under Cd stress requires further exploration. In this study, the cadmium-tolerant endophytic bacterium Herbaspirillum sp. R3 (R3) and Fe-Mn-modified biochar (Fe-Mn) were, respectively, applied to cadmium-contaminated rice paddies to investigate the effects of key bacterial taxa in the soil-rice system on the absorption and transportation of Cd in rice under different treatments. The results showed that both R3 and Fe-Mn treatments considerably decreased the content of cadmium in roots, stems and leaves of rice at the peak tillering stage by 17.24–49.28% in comparison to the control (CK). The cadmium content reduction effect of R3 treatment is better than that of Fe-Mn treatment. Further analysis revealed that the key bacterial taxa in rice roots under R3 treatment were Sideroxydans and Actinobacteria, and that their abundance showed a substantial positive correlation and a significant negative correlation with the capacity of rice roots to assimilate Cd from the surroundings, respectively. The significant increase in soil pH under Fe-Mn treatment, significant reduction in the relative abundances of Acidobacteria, Verrucomicrobia, Subdivision3 genera incertae sedis, Sideroxydans, Geobacter, Gp1, and Gp3, and the significant increase in the relative abundance of Thiobacillus among the soil bacterial taxa may be the main reasons for the decrease in available Cd content of the soil. In addition, both the R3 and Fe-Mn treatments showed some growth-promoting effects on rice, which may be related to their promotion of transformations of soil available nutrients. This paper describes the possible microbial mechanisms by which strain R3 and Fe-Mn biochar reduce Cd uptake in rice, providing a theoretical basis for the remediation of Cd contamination in rice and soil by utilizing key microbial taxa.

Abstract The MYC oncogene is often dysregulated in human cancer, including hepatocellular carcinoma (HCC). MYC is considered undruggable to date. Here, we comprehensively identify genes essential for survival of MYC high but not MYC low cells by a CRISPR/Cas9 genome-wide screen in a MYC-conditional HCC model. Our screen uncovers novel MYC synthetic lethal (MYC-SL) interactions and identifies most MYC-SL genes described previously. In particular, the screen reveals nucleocytoplasmic transport to be a MYC-SL interaction. We show that the majority of MYC-SL nucleocytoplasmic transport genes are upregulated in MYC high murine HCC and are associated with poor survival in HCC patients. Inhibiting Exportin-1 (XPO1) in vivo induces marked tumor regression in an autochthonous MYC-transgenic HCC model and inhibits tumor growth in HCC patient-derived xenografts. XPO1 expression is associated with poor prognosis only in HCC patients with high MYC activity. We infer that MYC may generally regulate and require altered expression of nucleocytoplasmic transport genes for tumorigenesis.

Fractional vegetation cover (FVC) is an essential parameter of vegetation canopy. Understanding its dynamics is vital for agricultural monitoring and climate change response. The physically based method for retrieving FVC from remote sensing data has great potential due to the theoretical basis of the radiative transfer model (RTM). However, the method is limited when applied to satellite imagery due to its uncertainty in simulating canopy reflectance. This article proposes a method that combines three-dimensional (3-D) RTM and convolutional neural network based transfer learning (CNN–TL) to address the inconsistency between simulated and satellite reflectance, improving maize FVC retrieval accuracy. First, 3-D RTM was employed to generate canopy reflectance datasets of maize at various growth stages. Second, CNN–TL is used to eliminate the discrepancy between 3-D RTM simulated reflectance and satellite reflectance, and the retrieval accuracy of CNN–TL is compared with random forest regression (RF) and CNN. Finally, the feasibility of the method was validated using time-series of measured data from multiple samples covering different growth stages of maize from 2021 to 2023. The results showed that, when retrieving maize FVC on GF-1, HJ-2, and Sentinel-2, CNN–TL performed the best (RMSE = 0.117, 0.063, and 0.081) compared to RF (RMSE = 0.186, 0.226, and 0.184) and CNN (RMSE = 0.133, 0.117, and 0.098). The spatial distribution of FVC maps remains highly consistent across all three satellites, indicating the exceptional performance of CNN–TL. These results contribute to the development of physically based methods for FVC retrieval and serve as a reference for multisource satellite studies.

Vesicle-associated membrane protein (VAMP)-associated proteins (VAP27s), which are widely expressed in plants and animals, play an important role in metabolism, physiology, growth, and development, disease resistance, and immunity. While the function of this family has been elucidated in model plants like Arabidopsis thaliana and tomato, its role in grapevine remains unclear. In this present study, 12 vesicle-associated protein-membrane protein genes were identified in the grapevine genome by bioinformatics, designated as the VAP27 gene family. A phylogenetic tree, encompassing 53 genes from three model plants, Arabidopsis thaliana, Oryza sativa, and Solanum lycopersicum, revealed the subdivision of the VAP27 gene family into three subfamilies, each presumably serving different functions, besides localizing in endoplasmic reticulum, individual members also localize in nucleus. Additionally, we compared the transcriptional levels and subcellular localizations of the VvVAP27 family members across different plant tissues (flower, leaf, seed, root, fruit, tendril, and stem), indicating site-specific functionalities for different gene members. To investigate the responsiveness of the VAP27 gene family to pathogen infection, particularly Plasmopara viticola on host plants, we analyzed the expression patterns of VAP27 genes post-infection. Our findings revealed divergent expression profiles among different members at different stages of infection. The gene family responded to the infection of downy mildew on grapevine and could inhibit the spread of Phytophthora capsici lesions in Nicotiana benthamiana. These results provide an important basis for further studies delving into the functions of the VAP27 gene family in plant growth and disease resistance.

When measurement equipment for marine refractive index is calibrated, the existing calibration methods have problems such as low quantity, high price, and complicated operation. Based on the existing empirical model of seawater refractive index, the dynamic range of the corresponding refractive index was calculated with reference to the dynamic range of temperature and salinity in the range of 0–2 000 m in the South China Sea. This paper also proposed an equipment calibration method for measuring seawater refractive index based on distilled water. The distilled water medium was selected, and within the dynamic range of refractive index suitable for marine measurement, a refractive index measurement experiment with a temperature interval of 0.1 °C was carried out. By comparing with the theoretical interpolation value of the Tilton empirical model, the accuracy of the theoretical value obtained by the empirical model was verified, and a credible data set was selected for the subsequent calibration and application of the equipment for measuring seawater refractive index based on distilled water.

ABSTRACTIon mobility spectrometry coupled to gas-chromatographic (GC-IMS) is tested regarding their ability to analyze various refined edible vegetable oils, including sunflower seed, rapeseed, sesame, soybean, peanut, corn, camellia, linseed, walnut, coconut, grape seed and extra virgin olive oils. GC-IMS assay displays peak difference of each edible vegetable oil in three-dimensional information at retention time in gas phase and at ion mobility rate in IMS. Moreover, 74 main peak intensities are extracted and imported into Excel for analysis. Then, chemometric methods are employed to establish discriminant models. The results show that based on Kennards-Stone (KS), the prediction accuracy of the soft independent modeling of class analogy (SIMCA) is perfect. Therefore, the GC-IMS system is shown to be an effective method to classification of edible vegetable oils.

Surface heat source (SHS) is a crucial factor affecting local weather systems. Particularly SHS on the Tibetan Plateau (TP) significantly influences East Asian atmospheric circulation and global climate. Accurate prediction of summer SHS on the TP is of urgent demand for economic development and local climate change. To evaluate the performance of SHS on the TP, the observed SHS data from the eleven sites on the TP verified against CRA40-land (CRA) is evidenced significantly better than ERA5-land (ERA5), another widely used reanalysis. The predictive capability of the CMA Climate Prediction System Model (CMA-CPS) for SHS on the TP was assessed using multiple scoring methods, including the anomaly correlation coefficient and temporal correlation coefficient, among others. Furthermore, relative variability and trend analysis were conducted. Finally, based on these assessments, the causes of the biases were preliminarily discussed. The CMA-CPS demonstrates a reasonable ability to predict the spatial distribution patterns of SHS, sensible heat (SH), and latent heat (LH) on the TP in summer. Specifically, the prediction results of SHS and LH exhibit an “east-high and west-low” distribution, while the distribution of the predicted SH is opposite. Nevertheless, the predicted values are generally lower than CRA, particularly in interannual variations and trends. Among the predictions, LH exhibits the highest temporal correlation coefficients, consistently above 0.6, followed by SHS, while SH predictions are less accurate. The spatial distribution and skill scores indicate that LH on the TP contributes more significantly to SHS than SH in summer. Furthermore, discrepancies in the predictions of surface temperature gradients, ground wind speed, and humidity on the TP may partly explain the biases in SHS and their components.

Tight sandstone reservoirs, despite their low porosity and permeability, present considerable exploration potential as unconventional hydrocarbon resources. Natural fractures play a crucial role in hydrocarbon migration, accumulation, and present engineering challenges such as late-stage reformation in these reservoirs. This study examines fractures in the seventh member of the Triassic Yanchang Formation’s tight sandstone within the Ordos Basin using a range of methods, including field outcrops, core samples, imaging and conventional logging, thin sections, and scanning electron microscopy. The study clarifies the characteristics of fracture development and evaluates the relationship between dynamic and static rock mechanics parameters, including the calculation of the brittleness index. Primary factors influencing fracture development were quantitatively assessed through a combination of outcrop, core, and mechanical test data. Findings reveal that high-angle structural fractures are predominant, with some bedding and diagenetic fractures also present. Acoustic, spontaneous potential, and caliper logging, in conjunction with imaging data, enabled the development of a comprehensive probabilistic index for fracture identification, which produced favorable results. The analysis identifies four key factors influencing fracture development: stratum thickness, brittleness index, lithology, and rock mechanical stratigraphy. Among these factors, stratum thickness is negatively correlated with fracture development. Conversely, the brittleness index positively correlates with fracture development and significantly influences fracture length, aperture, and linear density. Fractures are most prevalent in siltstone and fine sandstone, with minimal development in mudstone. Different rock mechanics layer types also impact fracture development. These insights into fracture characteristics and controlling factors are anticipated to enhance exploration efforts and contribute to the study of similar unconventional reservoirs.

This study explored the sustainable valorization of fruit waste extracts from sugarcane bagasse (SB), banana peel (BP), and watermelon rind (WR) for Euglena gracilis biomass and β-1,3-glucan production. The extracts were prepared using water extraction (WE), high-temperature and pressure treatment (HTP), and dilute sulfuric acid treatment (DSA). The DSA-treated extracts consistently yielded the best results. E. gracilis cultured in SB-DSA showed the highest cell density with a 2.08-fold increase compared to the commercial HUT medium, followed by BP-DSA (1.35-fold) and WR-DSA (1.70-fold). Photosynthetic pigment production increased significantly, with chlorophyll a yield being highest in SB-DSA (1.90-fold increase). The chlorophyll a/b ratio and total carotenoid content also improved, indicating enhanced light-harvesting capacity and photoprotection. Photosynthetic efficiency, measured by chlorophyll fluorescence, notably improved. The maximum quantum yield of PSII (Fv/Fm) increased by up to 25.88% in SB-DSA, suggesting reduced stress and improved overall photosynthetic health. The potential photochemical efficiency (Fv/F0) showed even greater improvements: up to 40.53% in SB-DSA. Cell morphology analysis revealed larger cell aspect ratios, implying a more active cellular physiological state. β-1,3-glucan yield also increased by 23.99%, 12.92%, and 23.38% in SB-DSA, BP-DSA, and WR-DSA, respectively. This study demonstrates the potential of pretreated fruit waste as a cost-effective and sustainable medium for E. gracilis cultivation, offering the dual benefits of waste valorization and high-value compound production. These findings contribute to the development of more efficient biorefinery processes and align with the circular economy principles in food biotechnology.

Effective forest management necessitates spatially explicit information about tree species composition. This information supports the safeguarding of native species, sustainable timber harvesting practices, precise mapping of wildlife habitats, and identification of invasive species. Tree species identification and geo-location by machine learning classification of UAV aerial imagery offer an alternative to tedious ground surveys. However, the timing (season) of the aerial surveys, input variables considered for classification, and the model type affect the classification accuracy. This work evaluates how the seasons and input variables considered in the species classification model affect the accuracy of species classification in a temperate broadleaf and mixed forest. Among the considered models, a Random Forest (RF) classifier demonstrated the highest performance, attaining an overall accuracy of 83.98% and a kappa coefficient of 0.80. Simultaneously using input data from summer, winter, autumn, and spring seasons improved tree species classification accuracy by 14–18% from classifications made using only single-season input data. Models that included vegetation indices, image texture, and elevation data obtained the highest accuracy. These results strengthen the case for using multi-seasonal data for species classification in temperate broadleaf and mixed forests since seasonal differences in the characteristics of species (e.g., leaf color, canopy structure) improve the ability to discern species.

In the field of autonomous driving, it is important to protect vulnerable road users (VRUs) and ensure the safety of autonomous driving effectively by improving the detection accuracy of VRUs in the driver’s field of vision. However, due to the strong temporal similarity between pedestrians and cyclists, the insensitivity of the traditional least squares method to their differences results in its suboptimal classification performance. In response to this issue, this paper proposes an algorithm for classifying pedestrian and cyclist targets based on the micro-Doppler effect. Firstly, distinct from conventional time-frequency fusion methods, a preprocessing module was developed to solely perform frequency-domain fitting on radar echo data of pedestrians and cyclists in forward motion, with the purpose of generating fitting coefficients for the classification task. Herein, wavelet threshold processing, short-time Fourier transform, and periodogram methods are employed to process radar echo data. Then, for the heightened sensitivity to inter-class differences, a fractional polynomial is introduced into the extraction of micro-Doppler characteristics of VRU targets to enhance extraction precision. Subsequently, the support vector machine technique is embedded for precise feature classification. Finally, subjective comparisons, objective explanations, and ablation experiments demonstrate the superior performance of our algorithm in the field of VRU target classification.

ABSTRACTThis study aimed to explore alterations in growth performance, glycolipid metabolism disorders, intestinal mucosal barrier, cecal microbiota community, and metabolites in a chronic corticosterone (CORT)-induced stress (CCIS) broiler model. Results showed that compared with control (CON) broilers, in CCIS broilers: (i) the final body weight (BW), BW gain, and average daily gain were significantly reduced. (ii) The glycolipid metabolism disorder and impairement of intestinal immune barrier and physical barrier function were observed. (iii) Diversity and richness of cecal microbiota were obviously increased. From phylum to genus level, the abundances of Firmicutes and Faecalibacterium were significantly decreased, while the abundances of Proteobacteria, RuminococcaceaeUCG-005, and Escherichia coli (Shigella) were significantly increased. Microbial network analysis and function pathways prediction showed that cecal microbiota was mainly concentrated in translation, metabolism, nucleotide metabolism, and endocrine system. (iv) The main differential metabolites identified include steroids and their derivatives, amino acids, fatty acids, and carbohydrates; among which 37 metabolites were significantly upregulated, while 27 metabolites were significantly downregulated. These differential metabolites were mainly enriched in pathways related to steroid hormone biosynthesis and tyrosine metabolism. (v) Correlation between cecal microbiota and glycolipid metabolism indexes showed that BW and total cholesterol (TC) were positively correlated with Christensenellaceae_R.7_group and Escherichia_Shigella, respectively. Furthermore, the downregulated Faecalibacterium and Christensenellaceae were negatively correlated with the upregulated differentially expressed metabolites. These findings suggested that CCIS altered cecal microbiota composition and metabolites, which led to glycolipid metabolism disorder and impaired the nutritional metabolism and immune homeostasis, providing a theoretical basis for efforts to eliminate the harm of chronic stress to human health and animal production.IMPORTANCEThe study aimed to determine the influence of altered intestinal mucosal barrier, cecum flora community, and metabolites on anti-growth performance, glycolipid metabolism disorders of chronic corticosterone (CORT)-induced stress (CCIS) broilers. Compared with control (CON) broilers, in CCIS broilers: (i) anti-growth performance, glycolipid metabolism disorder, and impaired intestinal immune barrier and physical barrier function were observed. (ii) From phylum to genus level, the abundances of Firmicutes and Faecalibacterium were decreased; whereas, the abundances of Proteobacteria, RuminococcaceaeUCG-005, and Escherichia coli (Shigella) were increased. (iii) Differential metabolites in cecum were mainly enriched in steroid hormone biosynthesis and tyrosine metabolism. (iv) Body weight (BW) and total cholesterol (TC) were positively correlated with Christensenellaceae_R.7_group and Escherichia_Shigella, respectively, while downregulated Faecalibacterium and Christensenellaceae were negatively correlated with upregulated metabolites. Our findings suggest that CCIS induces anti-growth performance and glycolipid metabolism disorder by altering cecum flora and metabolites, providing a theoretical basis for efforts to eliminate the effect of chronic stress on human health and animal production.

Aster L. is an economically and phylogenetically important genus in the tribe Astereae. Here, the complete plastomes of the eight Aster species were assembled and characterized using next-generation sequencing datasets. The results indicated the complete plastomes of Aster had a quadripartite structure. These genomes were 152,045–152,729 bp in length and contained 132–133 genes, including 87 protein-coding genes, 37–38 tRNA genes, and eight rRNA genes. Expansion or contraction of inverted repeat regions and forward, palindromic, complement, and reverse repeats were detected in the eight Aster species. Additionally, our analyses showed the richest type of simple sequence repeats was A/T mononucleotides, and 14 highly variable regions were discovered by analyzing the border regions, sequence divergence, and hotspots. Phylogenetic analyses indicated that 27 species in Astereae were clustered into six clades, i.e., A to D, North American, and outgroup clades, and supported that the genera Heteropappus, Kalimeris, and Heteroplexis are nested within Aster. The results indicated the clades B to D might be considered as genera. Divergence time estimate showed the clades A, B, C, and D diverged at 23.15 Mya, 15.13 Mya, 24.29 Mya, and 21.66 Mya, respectively. These results shed light on the phylogenetic relationships of Aster and provided new information on species identification of Aster and its related genera.

Abstract As emerging alternatives to natural enzymes, nanoscale materials featuring enzyme‐like catalytic behaviors (nanozymes) exhibit some attractive merits including robust activity, low cost, and easy‐to‐regulate performance. These merits have enabled them to be intensively used in the biomedical field in recent years. To remedy the lack of catalytic selectivity in most nanozymes, deoxyribonucleic acid (DNA) chains with specific recognition functions are utilized to integrate with nanozymes to produce various nanozyme–DNA combinations via adsorption/desorption. In the formed combinations, the DNA component provides the molecular/ionic recognition role, and the nanozyme part offers response with catalytically amplified signals, enabling them to detect analytes and biomarkers selectively and sensitively. To highlight this interesting topic, here we made a critical review of the interactions between nanozymes and DNA and their applications in biosensing and disease diagnosis. First, strategies for the conjugation of DNA chains onto nanozyme surface were introduced briefly. Then, the interactions between DNA and nanozymes were summarized in detail, where flexible modulations of nanozyme activity by DNA adsorption/desorption as well as various factors were analyzed, and potential impacts caused by nanozymes on the recognition characteristics of DNA chains were pointed out. After that, typical applications of DNA‐mediated nanozyme modulation in toxic ion sensing, health risk factor monitoring, and biomedical diagnosis were introduced. In the end, prospects of the combination of nanozymes and DNA chains were presented, and future challenges of the emerging field were also discussed, to attract more interest and effort to advance this promising area.

Chemotherapy-induced peripheral neuropathy (CIPN) is the most common off-target adverse effects caused by various chemotherapeutic agents, such as cisplatin, oxaliplatin, paclitaxel, vincristine and bortezomib. CIPN is characterized by a substantial loss of primary afferent sensory axonal fibers leading to sensory disturbances in patients. An estimated of 19–85% of patients developed CIPN during the course of chemotherapy. The lack of preventive measures and limited treatment options often require a dose reduction or even early termination of life-saving chemotherapy, impacting treatment efficacy and patient survival. In this Review, we summarized the current understanding on the pathogenesis of CIPN. One prominent change induced by chemotherapeutic agents involves the disruption of neuronal cytoskeletal architecture and axonal transport dynamics largely influenced by the interference of microtubule stability in peripheral neurons. Due to an ineffective blood-nerve barrier in our peripheral nervous system, exposure to some chemotherapeutic agents causes mitochondrial swelling in peripheral nerves, which lead to the opening of mitochondrial permeability transition pore and cytochrome c release resulting in degeneration of primary afferent sensory fibers. The exacerbated nociceptive signaling and pain transmission in CIPN patients is often linked the increased neuronal excitability largely due to the elevated expression of various ion channels in the dorsal root ganglion neurons. Another important contributing factor of CIPN is the neuroinflammation caused by an increased infiltration of immune cells and production of inflammatory cytokines. In the central nervous system, chemotherapeutic agents also induce neuronal hyperexcitability in the spinal dorsal horn and anterior cingulate cortex leading to the development of central sensitization that causes CIPN. Emerging evidence suggests that the change in the composition and diversity of gut microbiota (dysbiosis) could have direct impact on the development and progression of CIPN. Collectively, all these aspects contribute to the pathogenesis of CIPN. Recent advances in RNA-sequencing offer solid platform for in silico drug screening which enable the identification of novel therapeutic agents or repurpose existing drugs to alleviate CIPN, holding immense promises for enhancing the quality of life for cancer patients who undergo chemotherapy and improve their overall treatment outcomes.

Abstract A primary challenge of high-throughput imaging flow cytometry (IFC) is to analyze the vast amount of imaging data, especially in applications where ground truth labels are unavailable or hard to obtain. We present an unsupervised deep embedding algorithm, the Deep Convolutional Autoencoder-based Clustering (DCAEC) model, to cluster label-free IFC images without any prior knowledge of input labels. The DCAEC model first encodes the input images into the latent representations and then clusters based on the latent representations. Using the DCAEC model, we achieve a balanced accuracy of 91.9% for human white blood cell (WBC) clustering and 97.9% for WBC/leukemia clustering using the 3D IFC images and 3D DCAEC model. Above all, although no human recognizable features can separate the clusters of cells with protein localization, we demonstrate the fused DCAEC model can achieve a cluster balanced accuracy of 85.3% from the label-free 2D transmission and 3D side scattering images. To reveal how the neural network recognizes features beyond human ability, we use the gradient-weighted class activation mapping method to discover the cluster-specific visual patterns automatically. Evaluation results show that the automatically identified salient image regions have strong cluster-specific visual patterns for different clusters, which we believe is a stride for the interpretable neural network for cell analysis with high-throughput IFCs.

Abstract Background Doxorubicin (DOX)-induced cardiotoxicity (DIC) is a major impediment to its clinical application. It is indispensable to explore alternative treatment molecules or drugs for mitigating DIC. WGX50, an organic extract derived from Zanthoxylum bungeanum Maxim, has anti-inflammatory and antioxidant biological activity, however, its function and mechanism in DIC remain unclear. Methods We established DOX-induced cardiotoxicity models both in vitro and in vivo. Echocardiography and histological analyses were used to determine the severity of cardiac injury in mice. The myocardial damage markers cTnT, CK-MB, ANP, BNP, and ferroptosis associated indicators Fe2+, MDA, and GPX4 were measured using ELISA, RT-qPCR, and western blot assays. The morphology of mitochondria was investigated with a transmission electron microscope. The levels of mitochondrial membrane potential, mitochondrial ROS, and lipid ROS were detected using JC-1, MitoSOX™, and C11-BODIPY 581/591 probes. Results Our findings demonstrate that WGX50 protects DOX-induced cardiotoxicity via restraining mitochondrial ROS and ferroptosis. In vivo, WGX50 effectively relieves doxorubicin-induced cardiac dysfunction, cardiac injury, fibrosis, mitochondrial damage, and redox imbalance. In vitro, WGX50 preserves mitochondrial function by reducing the level of mitochondrial membrane potential and increasing mitochondrial ATP production. Furthermore, WGX50 reduces iron accumulation and mitochondrial ROS, increases GPX4 expression, and regulates lipid metabolism to inhibit DOX-induced ferroptosis. Conclusion Taken together, WGX50 protects DOX-induced cardiotoxicity via mitochondrial ROS and the ferroptosis pathway, which provides novel insights for WGX50 as a promising drug candidate for cardioprotection. Graphic abstract

Abstract Background The COVID-19 pandemic led many educational institutions to shift to online courses, making blended education a significant trend in teaching. We examined the effectiveness of blended learning in an evidence-based medicine course. Methods We compared the examination scores of a blended learning group, an online only group, and a traditional offline group and conducted a questionnaire survey on students’ preferences for different learning modes and the reasons for their preferences. A total of 2100 undergraduate students in clinical medicine were included in this cross-sectional study. Examination results were collected, and questionnaires were administered to the study participants. We compared the mean scores and exam pass rates of the three teaching groups using ANOVA and c2test for multiple comparisons. Results The blended group’s exam scores and pass rate were significantly higher than those of the offline and online groups. Furthermore, 71.6% preferred the blended teaching mode. In the survey on " learning effectiveness”, the majority of the students believed that blended education could better enhance the initiative of learning, the interest of the course, the pertinence of the learning content, the comprehension of evidence-based medical thinking, and the basic skills of evidence-based practice. Subsequently, in a questionnaire administered to a blended group of students, their foremost reason for liking online instruction was ‘flexible in time and space’ (99%), followed by ‘can be viewed repeatedly, facilitating a better understanding of knowledge points’ (98%). Their foremost reason for liking offline teaching was ‘helps to create a good learning atmosphere’ (97%), followed by ‘teachers can control students’ learning status in real time’ (89%). Conclusions This study explored the effectiveness of learning in evidence-based medicine courses by comparing the learning outcomes and personal perceptions of three different teaching modes. This is the first cross-sectional study in which three different teaching models are compared and discussed in an evidence-based medicine course. We also elaborate on the specific instructional protocols for each model. This study shows that using a blended education approach in evidence-based medicine courses can improve students’ learning motivation, autonomy, and satisfaction. It also enhances instructional efficiency, thereby improving students’ understanding of the course content.

Simultaneous partial nitrification, anammox, denitrification, and fermentation (SNADF) is a novel process achieving simultaneous advanced sludge reduction and nitrogen removal. The influence of low temperatures on the SNADF reactor was explored to facilitate the application of mainstream anammox. When temperature decreased from 32 to 16 °C, efficient nitrogen removal was achieved, with a nitrogen removal efficiency of 81.9–94.9%. Microbial community structure analysis indicated that the abundance of Candidatus Brocadia (dominant anaerobic ammonia oxidizing bacteria (AnAOB) in the system) increased from 0.03% to 0.18%. The abundances of Nitrospira and Nitrosomonas increased from 1.6% and 0.16% to 2.5% and 1.63%, respectively, resulting in an increase in the ammonia-oxidizing bacteria (AOB) to nitrite-oxidizing bacteria (NOB) abundance ratio from 0.1 to 0.64. This ensured sufficient nitrite for AnAOB, promoting nitrogen removal. In addition, Candidatus Competibacter, which plays a role in partial denitrification, was the dominant denitrification bacteria (DNB) and provided more nitrite for AnAOB, facilitating AnAOB enrichment. Based on the findings from microbial correlation network analysis, Nitrosomonas (AOB), Thauera, and Haliangium (DNB), and A4b and Saprospiraceae (fermentation bacteria), were center nodes in the networks and therefore essential for the stability of the SNADF system. Moreover, fermentation bacteria, DNB, and AOB had close connections in substrate cooperation and resistance to adverse environments; therefore, they also played important roles in maintaining stable nitrogen removal at low temperatures. This study provided new suggestions for mainstream anammox application.

The shale oil reservoirs of the Lower Permian Fengcheng Formation in the northern Mahu Sag are promising targets. However, complex geology and strong heterogeneity in the area pose great difficulties in the numerical simulation of in situ stress fields, which have for a long time been poorly understood. This study provides a systematic and accurate 3D in situ stress numerical simulation workflow based on comprehensive data. In this research, optimized ant tracking was applied to construct refined geological models. Acoustic impedance is taken as what we refer to as “hard” data to reflect variations in geomechanical parameters. Logging and mechanical tests were taken as “soft” data to restrict the numerical range of the geomechanical parameters. With the integration of “hard” data and “soft” data, accurate 3D geomechanical models can be attained. The finite element method was ultimately utilized to simulate the 3D in situ stress field of the Fengcheng Formation. Numerical simulation results reveal that the stress state of the Fengcheng Formation is quite complicated. The magnitude of the horizontal principal stress, horizontal stress difference and horizontal stress difference coefficient are correlated with burial depth, faults, and geomechanical parameters to some degree. The parameter Aφ was introduced in this research to better analyze the stress regime, the result of which demonstrates that the main stress regime in the study region is the reverse faulting stress regime. By evaluating the fault stability, it was found that there is basically no possibility of slippage regarding the faults in northern Mahu Sag. The results of this research provide evidence for well deployment optimization, borehole stability, and so on, all of which are of great significance in hydrocarbon exploration and exploitation.

The study of underwater vehicle wake detection is of significant importance within the field of target detection, localisation, and tracking of underwater vehicles. Given that propellers are the propellers of modern ships and underwater vehicles, the propeller wake field represents the principal target source for wake detection in underwater vehicles. The objective of this paper is to propose a method for measuring the wake of an underwater propeller based on a position-sensitive detector. A theoretical model of the relationship between the laser spot displacement and the change in the refractive index of the wake field is established on the basis of the principle of laser beam deflection. A prototype experimental setup for underwater propeller wake measurement was constructed based on the aforementioned optical measurement method. Furthermore, the simulation of the propeller wake flow field with strong density stratification and linear density stratification was conducted based on the experimental setup. Furthermore, experiments were conducted to detect the flow field of a propeller wake. The experimental results indicate that the wake dissipation times of the propeller in a strong density-stratified water environment are approximately 800 s and 750 s. Following the stabilisation of the wake field density, the laser spot position is observed to be stable at 0.341 mm and 0.441 mm, respectively, with a corresponding refractive index change of 2.99 × 10−6 RIU (refractive index unit) and 3.87 × 10−6 RIU, respectively. These experimental results are found to be in general agreement with the simulation results of the propeller wake field. A comparison of the experimental wake measurements based on the device with the wake measurements based on a CTD (conductivity–temperature–depth) device reveals a consistent trend. The realisation of this detection technique is of great significance for the advancement of research in the field of optical detection of underwater vehicle wake streams.