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The area of impervious surfaces serves as a critical metric to gauge urbanization levels and evaluates ecological health in a given region. However, in some areas with low-density impervious surfaces, these impervious surfaces are often small in size and distributed scatteredly, making them easily mistaken for the background. Therefore, accurately extracting these small and scattered impervious surfaces remains a significant challenge. In our previous work, TCA-Net pioneered the application of transformers for extracting impervious surfaces. However, owing to the limitations of transformers, TCA-Net struggled to precisely identify small, scattered impervious surfaces. In many cases, some minor roads extracted are discontinuous and incomplete. To enhance the transformer's performance in extracting impervious surfaces, we introduce MSTCA-Net, a dual-branch network. MSTCA-Net incorporates a multiscale transformer that preserves local details while capturing global context, and a Unet branch augmented with a coordinate attention mechanism, which captures intricate details while minimizing information redundancy. Experimental results show that MSTCA-Net proposed in this work can greatly outperform the traditional CNN models and our previous work, especially in extracting small and scattered impervious surfaces.

Abstract In terrestrial ecosystems, leaf litter is the main source of nutrients returning to the soil. Understanding how litter decomposition responds to stand age is critical for improving predictions of the effects of forest age structure on nutrient availability and cycling in ecosystems. However, the changes in this critical process with stand age remain poorly understood due to the complexity and diversity of litter decomposition patterns and drivers among different stand ages. In this study, we examined the effects of stand age on litter decomposition with two well-replicated age sequences of naturally occurring secondary forests and Chinese fir (Cunninghamia lanceolata) plantations in southern China. Our results showed that the litter decomposition rates in the secondary forests were significantly higher than those in the Chinese fir plantations of the same age, except for 40-year-old forests. The litter decomposition rate of the Chinese fir initially increased and then decreased with stand age, while that of secondary forests gradually decreased. The results of a structural equation model indicated that stand age, litter quality and microbial community were the primary factors driving nutrient litter loss. Overall, these findings are helpful for understanding the effects of stand age on the litter decomposition process and nutrient cycling in plantation and secondary forest ecosystems.

Abstract Cryo-electron tomography is a major tool used to study the structure of protein complexes in situ. However, the throughput of tilt-series image data collection is still quite low. Here, we show that GisSPA, a GPU accelerated program, can translationally and rotationally localize the target protein complex in cellular lamellae, as prepared with a focused ion beam, using single cryo-electron microscopy images without tilt-series, and reconstruct the protein complex at near-atomic resolution. GisSPA allows high-throughput data collection without the acquisition of tilt-series images and reconstruction of the tomogram, which is essential for high-resolution reconstruction of asymmetric or low-symmetry protein complexes. We demonstrate the power of GisSPA with 3.4-Å and 3.9-Å resolutions of resolving phycobilisome and tetrameric photosystem II complex structures in cellular lamellae, respectively. In this work, we present GisSPA as a practical tool that facilitates high-resolution in situ protein structure determination.

Abstract Background Proteins are of extremely vital importance in the human body, and no movement or activity can be performed without proteins. Currently, microscopy imaging technologies developed rapidly are employed to observe proteins in various cells and tissues. In addition, due to the complex and crowded cellular environments as well as various types and sizes of proteins, a considerable number of protein images are generated every day and cannot be classified manually. Therefore, an automatic and accurate method should be designed to properly solve and analyse protein images with mixed patterns. Results In this paper, we first propose a novel customized architecture with adaptive concatenate pooling and “buffering” layers in the classifier part, which could make the networks more adaptive to training and testing datasets, and develop a novel hard sampler at the end of our network to effectively mine the samples from small classes. Furthermore, a new loss is presented to handle the label imbalance based on the effectiveness of samples. In addition, in our method, several novel and effective optimization strategies are adopted to solve the difficult training-time optimization problem and further increase the accuracy by post-processing. Conclusion Our methods outperformed the SOTA method of multi-labelled protein classification on the HPA dataset, GapNet-PL, by above 2% in the F1 score. Therefore, experimental results based on the test set split from the Human Protein Atlas dataset show that our methods have good performance in automatically classifying multi-class and multi-labelled high-throughput microscopy protein images.

Abstract Background Codon usage is an important determinant of gene expression levels that can help us understand codon biology, evolution and mRNA translation of species. The majority of previous codon usage studies have focused on single species analysis, although few studies have focused on the species within the same genus. In this study, we proposed a multispecies codon usage analysis workflow to reveal the genetic features and correlation in citrus. Results Our codon usage analysis workflow was based on the GC content, GC plot, and relative synonymous codon usage value of each codon in 8 citrus species. This approach allows for the comparison of codon usage bias of different citrus species. Next, we performed cluster analysis and obtained an overview of the relationship in citrus. However, traditional methods cannot conduct quantitative analysis of the correlation. To further estimate the correlation among the citrus species, we used the frequency profile to construct feature vectors of each species. The Pearson correlation coefficient was used to quantitatively analyze the distance among the citrus species. This result was consistent with the cluster analysis. Conclusions Our findings showed that the citrus species are conserved at the genetic level and demonstrated the existing genetic evolutionary relationship in citrus. This work provides new insights into codon biology and the evolution of citrus and other plant species.

Background: As demand for cardiopulmonary exercise test using a supine position has increased, so have the testing options. However, it remains uncertain whether the existing evaluation criteria for the upright position are suitable for the supine position. The purpose of this meta-analysis is to compare the differences in peak oxygen uptake (VO2peak) between upright and supine lower extremity bicycle exercise.Methods: We searched PubMed, Web Of Science and Embase from inception to March 27, 2021. Self-control studies comparing VO2peak between upright and supine were included. The quality of the included studies was assessed using a checklist adapted from published papers in this field. The effect of posture on VO2peak was pooled using random/fixed effects model.Results: This meta-analysis included 32 self-control studies, involving 546 participants (63% were male). 21 studies included only healthy people, 9 studies included patients with cardiopulmonary disease, and 2 studies included both the healthy and cardiopulmonary patients. In terms of study quality, most of the studies (n = 21, 66%) describe the exercise protocol, and we judged theVO2peak to be valid in 26 (81%) studies. Meta-analysis showed that the upright VO2peak exceeded the supine VO2peak [relative VO2peak: mean difference (MD) 2.63 ml/kg/min, 95% confidence interval (CI) 1.66-3.59, I2 = 56%, p < 0.05; absolute VO2peak: MD 0.18 L/min, 95% CI 0.10-0.26, I2 = 63%, p < 0.05). Moreover, subgroup analysis showed there was more pooled difference in healthy people (4.04 ml/kg/min or 0.22 L/min) than in cardiopulmonary patients (1.03 ml/kg/min or 0.12 L/min).Conclusion: VO2peak in the upright position is higher than that in supine position. However, whether this difference has clinical significance needs further verification.Systematic Review Registration: identifier, CRD42021233468.

Abstract Fibroblast activation plays an important role in the occurrence and development of idiopathic pulmonary fibrosis (IPF), which is a progressive, incurable, and fibrotic lung disease. However, the underlying mechanism of fibroblast activation in IPF remains elusive. Here, we showed that the expression levels of STX11 and SNAP25 were downregulated in the lung tissues from patients with IPF and mice with bleomycin (BLM)-induced lung fibrosis as well as in the activated fibroblasts. Upregulation of STX11 or SNAP25 suppressed TGF-β1-induced activation of human lung fibroblasts (HLFs) via promoting autophagy. However, they failed to suppress fibroblast actviation when autophagy was blocked with the use of chloroquine (CQ). In addition, STX11 or SNAP25 could inhibit TGF-β1-induced fibroblast proliferation and migration. In vivo, overexpression of STX11 exerted its protective role in the mice with BLM-induced lung fibrosis. STX11 and SNAP25 mutually promoted expression of each other. Co-IP assay indicated that STX11 has an interaction with SNAP25. Mechanistically, STX11-SNAP25 interaction activated fibroblast autophagy and further inhibited fibroblast activation via blocking the PI3K/AKT/mTOR pathway. Overall, the results suggested that STX11-SNAP25 interaction significantly inhibited lung fibrosis by promoting fibroblast autophagy and suppressing fibroblast activation via blocking the PI3K/ATK/mTOR signaling pathway. Therefore, STX11 serves as a promising therapeutic target in IPF.

Abstract Background Bioactive peptides are important bioactive molecules composed of short-chain amino acids that play various crucial roles in the body, such as regulating physiological processes and promoting immune responses and antibacterial effects. Due to their significance, bioactive peptides have broad application potential in drug development, food science, and biotechnology. Among them, understanding their biological mechanisms will contribute to new ideas for drug discovery and disease treatment. Results This study employs generative adversarial capsule networks (CapsuleGAN), gated recurrent units (GRU), and convolutional neural networks (CNN) as base classifiers to achieve ensemble learning through voting methods, which not only obtains high-precision prediction results on the angiotensin-converting enzyme (ACE) inhibitory peptides dataset and the anticancer peptides (ACP) dataset but also demonstrates effective model performance. For this method, we first utilized the protein language model—evolutionary scale modeling (ESM-2)—to extract relevant features for the ACE inhibitory peptides and ACP datasets. Following feature extraction, we trained three deep learning models—CapsuleGAN, GRU, and CNN—while continuously adjusting the model parameters throughout the training process. Finally, during the voting stage, different weights were assigned to the models based on their prediction accuracy, allowing full utilization of the model's performance. Experimental results show that on the ACE inhibitory peptide dataset, the balanced accuracy is 0.926, the Matthews correlation coefficient (MCC) is 0.831, and the area under the curve is 0.966; on the ACP dataset, the accuracy (ACC) is 0.779, and the MCC is 0.558. The experimental results on both datasets are superior to existing methods, demonstrating the effectiveness of the experimental approach. Conclusion In this study, CapsuleGAN, GRU, and CNN were successfully employed as base classifiers to implement ensemble learning, which not only achieved good results in the prediction of two datasets but also surpassed existing methods. The ability to predict peptides with strong ACE inhibitory activity and ACPs more accurately and quickly is significant, and this work provides valuable insights for predicting other functional peptides. The source code and dataset for this experiment are publicly available at https://github.com/Zhou-Jianren/bioactive-peptides .

Abstract Background Systemic lupus erythematosus (SLE) is an autoimmune disease of unknown cause. N6-methyladenosine (m6A) is the most common mRNA modification and participates in various immune processes such as interferon production and immune cell regulation. However, the role of m6A in dysregulated immune response of SLE remains unknown. Methods PBMCs from SLE patients were collected to compare the m6A modification profile by methylated RNA immunoprecipitation sequencing (MeRIP-seq). Interferon regulatory factor 4 (IRF4) was identified by combination with MeRIP-seq and RNA-Seq. IRF4 and methyltransferase 3 (METTL3) were detected using qRT-PCR and WB. Clinical significance of IRF4 in SLE patients was explored subsequently. IRF4 expression in B cell subsets of female MRL/lpr mice was detected by flow cytometry. Adeno-associated viruses (AAV) including AAV9-METTL3-OE and/or AAV9-IRF4-sh were treated with female MRL/lpr mice. Autoantibody levels and kidney injury were tested by ELISA, pathological staining, and immunofluorescence. m6A level of IRF4 was detected by MeRIP-qPCR. The downstream effectors of IRF4 contributing to renal pathology were explored by RNA-seq and verified by qRT-PCR. Results m6A methylation features were obviously aberrant in SLE patients, and IRF4 was the upregulated gene modified by m6A. METTL3 and IRF4 expressions were elevated in SLE patients and kidney of MRL/lpr mice. Clinical analysis indicated that SLE patients with high IRF4 level were more prone to kidney damage. IRF4 expression was especially increased in plasma cells of MRL/lpr mice. METTL3 induced renal IRF4 expression, plasma creatinine, ANA and urine ALB levels, IgG and C3 deposition, and renal damage and plasma cell infiltration were aggravated in MRL/lpr mice. However, IRF4 depletion could partially reduce METTL3-induced kidney damage. Meanwhile, m6A level of IRF4 elevated with METTL3 overexpression. Also, the expression of Cxcl1, Bcl3, and Fos mRNA were significantly reduced after knockdown of IRF4, which were mainly involved in TNF signaling pathway. Conclusions Our study confirmed that upregulated METTL3 promoting IRF4 expression in an m6A-dependent manner, thus causing plasma cell infiltration-mediated kidney damage of SLE. This provides new evidence for the role of m6A in SLE kidney injury.

Background: Osteomyelitis (OM) is an inflammatory condition of bone characterized by cortical bone devascularization and necrosis. Dysregulation of bone remodelling is triggered by OM. Bone remodelling is precisely coordinated by bone resorption and formation via a reversal phase. However, the cellular and molecular mechanisms underlying bone remodelling failure after osteomyelitis remain elusive. Methods: To elucidate the cellular and molecular mechanism underlying bone healing after osteomyelitis, we employed single-cell RNA sequencing (scRNA-seq) to depict the atlas of human cortical bone in normal, infected and reconstructed states. Dimensionality reduction by t-stochastic neighbourhood embedding (t-SNE) and graph-based clustering were applied to analyse the detailed clusters of osteoclast lineages. After trajectory analysis of osteoclast lineages over pseudotime, real-time PCR and immunofluorescence (IF) staining were applied to identify marker gene expression of various osteoclast lineages in the osteoclast induction model and human bone sections, respectively. The potential function and communication of osteoclasts were analysed via gene set enrichment analysis (GSEA) and CellChat. The chemotactic ability of mesenchymal stem cells (MSCs) and osteoclast lineage cells in various differentiation states was determined by transwell assays and coculture assays. The effects of various osteoclast lineages on the osteogenic differentiation potential of MSCs were also determined by using this coculture system. A normal mouse tibia fracture model and an osteomyelitis-related tibia fracture model were generated via injection of luciferase-labelled Staphylococcus aureus to verify the relationships between a novel osteoclast lineage and MSCs. Then, the infection was detected by a bioluminescence imaging system. Finally, immunofluorescence staining was used to detect the expression of markers of MSCs and novel osteoclast lineages in different remodelling phases in normal and infected bone remodelling models. Results: In this study, we constructed a cell atlas encompassing normal, infected, and reconstructed cortical bone. Then, we identified a novel subset at the earlier stage of the osteoclast lineage that exhibited increased expression of IDO1, CCL3, and CCL4. These IDO1highCCL3highCCL4high cells, termed osteostaticytes (OSCs), were further regarded as the reservoir of osteoclasts in the reversal phase. Notably, OSCs exhibited the highest chemotactic activity, surpassing other lineage subsets. We also discovered that cells at the earlier stage of the osteoclast lineage play a significant role in recruiting mesenchymal stem cells (MSCs). Finally, the data revealed that OSCs might be positively related to the occurrence of bone MSCs and the contribution of bone remodelling. Conclusion: Collectively, our findings revealed a novel stage (OSC) within the osteoclast lineage, potentially representing elusive bone reversal cells due to its increased chemotactic ability towards MSCs and potential contribution to bone remodelling. This study provides valuable insights into the intricate mechanisms of the reversal phase during bone remodelling and unveils potential therapeutic strategies for diseases associated with bone uncoupling. Translational potential of this article: This study identified a new subset, referred to as IDO1(plus symbol) CCL3(plus symbol) CCL4(plus symbol) osteostaticytes which displayed the highest chemotactic activity among all osteoclast lineages and may serve as reversal cells in bone remodelling. These findings offer new insights and insights for understanding bone reversal-related diseases and may serve as novel therapeutic targets for conditions such as osteomyelitis and delayed bone healing.

Erdheim-Chester Disease (ECD) is a rare form of histiocytosis characterized by xanthomatous infiltration of affected organs. We present a case of a 62-year-old man with ECD initially presenting with constrictive pericarditis. Comprehensive imaging revealed systemic involvement, including the skeleton, orbit, pituitary, lung, kidney, and retroperitoneum, despite the absence of related symptoms. The diagnosis of ECD was eventually confirmed through histopathological evidence from a CT-guided biopsy. The patient responded well to interferon-α2b treatment, with gradual symptom amelioration and improvement in imaging and laboratory findings over a 5-month follow-up period. This case highlights the importance of considering ECD in the differential diagnosis of constrictive pericarditis and the utility of multimodal imaging for accurate diagnosis and management of this rare disease. The patient's positive response to treatment also highlights the potential for effective management of ECD, particularly with early diagnosis and intervention.

Abstract This study was desinged to evaluate the efficacy and safety of activated allograft combined with the induced membrane technique for reconstruction of infected segment bone defects of lower limbs. A retrospective analysis was conducted on 19 patients from May 2015 to February 2017. After debridements, the bone defects were filled with antibiotic bone cement to form the induced membrane. Autologous mesenchymal stem cells were seeded onto allografts to construct activated allograft, which was implanted into the induced membrane after infection was controlled. The clinical efficacy and complications were observed. 19 patients with 20 infected segment bone defect were evaluated. The average deficit size was 11.08 (4–17) cm in length. After a mean follow-up of 71.84 (61–82) months, bone union was achieved in 16 patients (17 sites), resulting in a final union rate of 84.21% (16/19 patients). The average bone union time was 10.18 (5–28) months. There were 2 patients with recurrence of infection, 3 patients with graft absorption, and 1 patient with malunion due to implant breakage. There were no graft-related complications. This study provides clinical significance for the treatment of patients with insufficient autologous bone.