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A novel strategy for segmenting mpox virus images is proposed to address the challenge of distinguishing lesion areas from muscle tissue and other regions of infection. This strategy leverages a multiscale inflated convolutional feature fusion and attentional Swin-Unet approach. In this method, a multi-scale extended convolution module is employed in the coding stage of the Swin-Unet network to enhance complementary features while preserving different features at different scales. Additionally, a triple attention module is integrated into the downsampling process to address the issue of inter-channel independence. Finally, the Swin Transformer Block is utilized to modulate the network segmentation performance by adjusting the iteration count in the encoding and decoding regions. Experimental results on a self-constructed mpox dataset demonstrate that the proposed network achieves a pixel segmentation accuracy of 90.4% and an average intersection-over-union ratio of 80.3%. These values represent improvements of 8.6% and 14.6%, respectively, compared to the original Swin-Unet. This enhancement provides valuable support for the ancillary diagnosis of mpox.

Abstract Backgrounds Allergic airway inflammation is prevalent worldwide and imposes a considerable burden on both society and affected individuals. This study aimed to investigate the therapeutic advantages of mesenchymal stem cells (MSCs) overexpressed interleukin-10 (IL-10) for the treatment of allergic airway inflammation, as both IL-10 and MSCs possess immunosuppressive properties. Methods Induced pluripotent stem cell (iPSC)-derived MSCs were engineered to overexpress IL-10 via lentiviral transfection (designated as IL-10-MSCs). MSCs and IL-10-MSCs were administered intravenously to mice with allergic inflammation induced by ovalbumin (OVA), and the features of allergic inflammation including inflammatory cell infiltration, Th cells in the lungs, and T helper 2 cell (Th2) cytokine levels in bronchoalveolar lavage fluid (BALF) were examined. MSCs and IL-10-MSCs were co-cultured with CD4+ T cells from patients with allergic rhinitis (AR), and the levels of Th2 cells and corresponding type 2 cytokines were studied. RNA-sequence was performed to further investigate the potential effects of MSCs and IL-10-MSCs on CD4+ T cells. Results Stable IL-10-MSCs were established and characterised by high IL-10 expression. IL-10-MSCs significantly reduced inflammatory cell infiltration and epithelial goblet cell numbers in the lung tissues of mice with allergic airway inflammation. Inflammatory cell and cytokine levels in BALF also decreased after the administration of IL-10-MSCs. Moreover, IL-10-MSCs showed a stronger capacity to inhibit the levels of Th2 after co-cultured with CD4+ T cells from patients with AR. Furthermore, we elucidated lower levels of IL-5 and IL-13 in IL-10-MSCs treated CD4+ T cells, and blockade of IL-10 significantly reversed the inhibitory effects of IL-10-MSCs. We also reported the mRNA profiles of CD4+ T cells treated with IL-10-MSCs and MSCs, in which IL-10 played an important role. Conclusion IL-10-MSCs showed positive effects in the treatment of allergic airway inflammation, providing solid support for the use of genetically engineered MSCs as a potential novel therapy for allergic airway inflammation.

IntroductionCotton (Gossypium hirsutum L.) is susceptible to long-term waterlogging stress; however, genomic information of cotton response mechanisms toward long days of waterlogging is quite elusive.MethodsHere, we combined the transcriptome and metabolome expression level changes in cotton roots after 10 and 20 days of waterlogging stress treatment pertaining to potential resistance mechanisms in two cotton genotypes.Results and discussionNumerous adventitious roots and hypertrophic lenticels were induced in CJ1831056 and CJ1831072. Transcriptome analysis revealed 101,599 differentially expressed genes in cotton roots with higher gene expression after 20 days of stress. Reactive oxygen species (ROS) generating genes, antioxidant enzyme genes, and transcription factor genes (AP2, MYB, WRKY, and bZIP) were highly responsive to waterlogging stress among the two genotypes. Metabolomics results showed higher expressions of stress-resistant metabolites sinapyl alcohol, L-glutamic acid, galactaric acid, glucose 1-phosphate, L-valine, L-asparagine, and melibiose in CJ1831056 than CJ1831072. Differentially expressed metabolites (adenosine, galactaric acid, sinapyl alcohol, L-valine, L-asparagine, and melibiose) significantly correlated with the differentially expressed PRX52, PER1, PER64, and BGLU11 transcripts. This investigation reveals genes for targeted genetic engineering to improve waterlogging stress resistance to enhance abiotic stress regulatory mechanisms in cotton at the transcript and metabolic levels of study.

Patients with cancer who receive doxorubicin (DOX) treatment can experience cardiac dysfunction, which can finally develop into heart failure. Oxidative stress is considered the most important mechanism for DOX-mediated cardiotoxicity. Rutaecarpine (Rut), a quinazolinocarboline alkaloid extracted from Evodia rutaecarpa was shown to have a protective effect on cardiac disease. The purpose of this study is to investigate the role of Rut in DOX-induced cardiotoxicity and explore the underlying mechanism. Intravenous injection of DOX (5 mg/kg, once a week) in mice for 4 weeks was used to establish the cardiotoxic model. Echocardiography and pathological staining analysis were used to detect the changes in structure and function in the heart. Western blot and real-time PCR analysis were used to detect the molecular changes. In this study, we found that DOX time-dependently decreased cardiac function with few systemic side effects. Rut inhibited DOX-induced cardiac fibrosis, reduction in heart size, and decrease in heart function. DOX-induced reduction in superoxide dismutase (SOD) and glutathione (GSH), enhancement of malondialdehyde (MDA) was inhibited by Rut administration. Meanwhile, Rut inhibited DOX-induced apoptosis in the heart. Importantly, we further found that Rut activated AKT or nuclear factor erythroid 2-related factor 2 (Nrf-2) which further upregulated the antioxidant enzymes such as heme oxygenase-1 (HO-1) and GSH cysteine ligase modulatory subunit (GCLM) expression. AKT inhibitor (AKTi) partially inhibited Nrf-2, HO-1, and GCLM expression and abolished the protective role of Rut in DOX-induced cardiotoxicity. In conclusion, this study identified Rut as a potential therapeutic agent for treating DOX-induced cardiotoxicity by activating AKT.

Introduction: Cotton (Gossypium hirsutum L.) is susceptible to long-term waterlogging stress; however, genomic information of cotton response mechanisms toward long days of waterlogging is quite elusive. Methods: Here, we combined the transcriptome and metabolome expression level changes in cotton roots after 10 and 20 days of waterlogging stress treatment pertaining to potential resistance mechanisms in two cotton genotypes. Results and discussion: Numerous adventitious roots and hypertrophic lenticels were induced in CJ1831056 and CJ1831072. Transcriptome analysis revealed 101,599 differentially expressed genes in cotton roots with higher gene expression after 20 days of stress. Reactive oxygen species (ROS) generating genes, antioxidant enzyme genes, and transcription factor genes (AP2, MYB, WRKY, and bZIP) were highly responsive to waterlogging stress among the two genotypes. Metabolomics results showed higher expressions of stress-resistant metabolites sinapyl alcohol, L-glutamic acid, galactaric acid, glucose 1-phosphate, L-valine, L-asparagine, and melibiose in CJ1831056 than CJ1831072. Differentially expressed metabolites (adenosine, galactaric acid, sinapyl alcohol, L-valine, L-asparagine, and melibiose) significantly correlated with the differentially expressed PRX52, PER1, PER64, and BGLU11 transcripts. This investigation reveals genes for targeted genetic engineering to improve waterlogging stress resistance to enhance abiotic stress regulatory mechanisms in cotton at the transcript and metabolic levels of study. [ABSTRACT FROM AUTHOR]

Abstract Ligand-induced receptor dimerization or oligomerization is a widespread mechanism for ensuring communication specificity, safeguarding receptor activation, and facilitating amplification of signal transduction across the cellular membrane. However, cell-surface antigen-induced multimerization (dubbed AIM herein) has not yet been consciously leveraged in chimeric antigen receptor (CAR) engineering for enriching T cell-based therapies. We co-developed ciltacabtagene autoleucel (cilta-cel), whose CAR incorporates two B-cell maturation antigen (BCMA)-targeted nanobodies in tandem, for treating multiple myeloma. Here we elucidated a structural and functional model in which BCMA-induced cilta-cel CAR multimerization amplifies myeloma-targeted T cell-mediated cytotoxicity. Crystallographic analysis of BCMA–nanobody complexes revealed atomic details of antigen–antibody hetero-multimerization whilst analytical ultracentrifugation and small-angle X-ray scattering characterized interdependent BCMA apposition and CAR juxtaposition in solution. BCMA-induced nanobody CAR multimerization enhanced cytotoxicity, alongside elevated immune synapse formation and cytotoxicity-mediating cytokine release, towards myeloma-derived cells. Our results provide a framework for contemplating the AIM approach in designing next-generation CARs.

Abstract Lateral interaction in the biological brain is a key mechanism that underlies higher cognitive functions. Linear self‐organising map (SOM) introduces lateral interaction in a general form in which signals of any modality can be used. Some approaches directly incorporate SOM learning rules into neural networks, but incur complex operations and poor extendibility. The efficient way to implement lateral interaction in deep neural networks is not well established. The use of Laplacian Matrix‐based Smoothing (LS) regularisation is proposed for implementing lateral interaction in a concise form. The authors’ derivation and experiments show that lateral interaction implemented by SOM model is a special case of LS‐regulated k‐means, and they both show the topology‐preserving capability. The authors also verify that LS‐regularisation can be used in conjunction with the end‐to‐end training paradigm in deep auto‐encoders. Additionally, the benefits of LS‐regularisation in relaxing the requirement of parameter initialisation in various models and improving the classification performance of prototype classifiers are evaluated. Furthermore, the topologically ordered structure introduced by LS‐regularisation in feature extractor can improve the generalisation performance on classification tasks. Overall, LS‐regularisation is an effective and efficient way to implement lateral interaction and can be easily extended to different models.

In the 1980s, Shandong Province took the lead in establishing breakthrough industrialized seedling raising and breeding technologies for Apostichopus japonicus and successfully led the 'fifth wave of mariculture' in China. In 2008, the experiment of 'raising sea cucumber from north to south' proved successful, and sea cucumber culture gradually radiated and extended to Fujian, Jiangsu, Guangdong, and Zhejiang Provinces in southern China. The total output of sea cucumber culture in Shandong Province accounts for more than 70% of the market in China, and the sea cucumber industry is now a pillar of the fishery economy in Shandong Province. This paper systematically introduces the development status of the sea cucumber breeding industry in Shandong Province in recent ten years, summarizes the current problems and challenges, and puts forwards development suggestions; this guidance has significance for the healthy and sustainable development of the sea cucumber breeding industry in both Shandong Province and the whole country. [ABSTRACT FROM AUTHOR]

Average-rendezvous problem with connectivity preservation of constant reference signals is investigated for first-order multiagent systems. According to a constructive potential function, a proportional–integral average-rendezvous algorithm is proposed to make agents converge to the average value of constant reference signals as well as the network connectivity is preserved all the time. Sufficient convergence conditions are obtained for the algorithm by designing the proper Lyapunov functions. Numerical examples illustrate the correctness of theoretical results.

We report the physical properties of the 18 brightest ( S _870 _μ _m = 12.4–19.2 mJy) and not strongly lensed 870 μ m–selected dusty star-forming galaxies (DSFGs), also known as submillimeter galaxies (SMGs), in the COSMOS field. This sample is part of an ALMA band 3 spectroscopic survey (AS2COSPEC), and spectroscopic redshifts are measured in 17 of them at z = 2–5. We perform spectral energy distribution analyses and deduce a median total infrared luminosity of L _IR = (1.3 ± 0.1) × 10 ^13 L _⊙ , infrared-based star formation rate (SFR) of SFR _IR = 1390 ± 150 M _⊙ yr ^−1 , stellar mass of M _* = (1.4 ± 0.6) × 10 ^11 M _⊙ , dust mass of M _dust = (3.7 ± 0.5) × 10 ^9 M _⊙ , and molecular gas mass of M _gas = ( α _CO /0.8)(1.2 ± 0.1) × 10 ^11 M _⊙ , suggesting that they are one of the most massive, ISM-enriched, and actively star-forming systems at z = 2–5. In addition, compared to less massive and less active galaxies at similar epochs, SMGs have comparable gas fractions; however, they have a much shorter depletion time, possibly caused by more active dynamical interactions. We determine a median dust emissivity index of β = 2.1 ± 0.1 for our sample, and by combining our results with those from other DSFG samples, we find no correlation of β with redshift or infrared luminosity, indicating similar dust grain compositions across cosmic time for infrared luminous galaxies. We also find that AS2COSPEC SMGs have one of the highest dust-to-stellar mass ratios, with a median of 0.02 ± 0.01, significantly higher than model predictions, possibly due to too-strong active galactic nucleus feedback implemented in the model. Finally, our complete and uniform survey enables us to put constraints on the most massive end of the dust and molecular gas mass functions.

We present the initial results of an ongoing survey with the Karl G. Jansky Very Large Array targeting the CO( J = 1–0) transition in a sample of 30 submillimeter-selected, dusty star-forming galaxies (SFGs) at z = 2–5 with existing mid- J CO detections from the Atacama Large Millimeter/submillimeter Array and NOrthern Extended Millimeter Array, of which 17 have been fully observed. We detect CO(1–0) emission in 11 targets, along with three tentative (∼1.5 σ –2 σ ) detections; three galaxies are undetected. Our results yield total molecular gas masses of 6–23 × 10 ^10 ( α _CO /1) M _⊙ , with gas mass fractions, f _gas = M _mol /( M _* + M _mol ), of 0.1–0.8 and a median depletion time of (140 ± 70) Myr. We find median CO excitation ratios of r _31 = 0.75 ± 0.39 and r _41 = 0.63 ± 0.44, with significant scatter. We find no significant correlation between the excitation ratio and a number of key parameters such as redshift, CO(1–0) line width, or Σ _SFR . We only find a tentative positive correlation between r _41 and the star-forming efficiency, but we are limited by our small sample size. Finally, we compare our results to predictions from the SHARK semi-analytical model, finding a good agreement between the molecular gas masses, depletion times, and gas fractions of our sources and their SHARK counterparts. Our results highlight the heterogeneous nature of the most massive SFGs at high redshift, and the importance of CO(1–0) observations to robustly constrain their total molecular gas content and interstellar medium properties.