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Abstract Inflammatory bowel disease (IBD) is a chronic and recurrent inflammatory disease of the gastrointestinal tract, including two subtypes: Crohn’s disease (CD) and ulcerative colitis (UC). Metabolic disorders are important factors in the development of IBD. However, the evidence for the causal relationship between blood metabolites and IBD remains limited. A two-sample MR analysis was applied to evaluate relationships between 486 blood metabolites and IBD. The inverse variance weighted method was chosen as the primary MR analysis method. False discovery rate correction was used to control for false positives in multiple testing. Following complementary and sensitivity analyses were conducted using methods such as weight median, MR-egger, weighted mode, simple mode, Cochran Q test, and MR-PRESSO. Moreover, we performed replication, meta-analysis, Steiger test, and linkage disequilibrium score regression to enhance the robustness of the results. Additionally, we performed metabolic pathway analysis to identify potential metabolic pathways. As a result, we identified four significant causal associations between four blood metabolites and two IBD subtypes. Specifically, one metabolite was identified as being associated with the development of CD (mannose: odds ratio (OR) = 0.19, 95% confidence interval (CI) 0.08–0.43, P = 8.54 × 10–5). Three metabolites were identified as being associated with the development of UC (arachidonate (20:4n6): OR = 0.18, 95% CI 0.11–0.30, P = 2.09 × 10–11; 1, 5-anhydroglucitol: OR = 2.21, 95% CI 1.47–3.34, P = 1.50 × 10–4; 2-stearoylglycerophosphocholine: OR = 2.66, 95% CI 1.53–4.63, P = 5.30 × 10–4). The findings of our study suggested that the identified metabolites and metabolic pathways can be considered as useful circulating metabolic biomarkers for the screening and prevention of IBD in clinical practice, as well as candidate molecules for future mechanism exploration and drug target selection.

Background: Mitochondrial DNA plays a crucial role in the pathophysiology of autoimmune diseases (ADs). However, the association between mitochondrial DNA copy number (mtDNA-CN) and ADs risk is controversial. In this study, Mendelian randomization (MR) analysis and meta-analysis were performed using three sets of independent instrumental variables (IVs) to investigate the potential association between mtDNA-CN and 20 types of ADs. Methods: The three sets of IVs were drawn primarily from participants in the UK Biobank and the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium using different methods. Outcome data for ADs were investigated using summary statistics from the FinnGen cohort. The potential causal associations were assessed using inverse-variance weighting (IVW), MR-Egger, and weighted median methods. Sensitivity analysis and the Steiger test were used to verify the robustness of the MR estimates. In addition, a meta-analysis was conducted to pool the results from three IV groups. Results: Overall, genetically predicted mtDNA-CN was not associated with ADs risk (OR = 1.046, 95 % CI: 0.964–1.135, P = 0.283). However, subgroup analyses showed positive causal associations of mtDNA-CN with autoimmune hypothyroidism (OR = 1.133, 95 % CI: 1.016–1.262, P = 0.024) and rheumatoid arthritis (OR = 1.219, 95 % CI: 1.028–1.445, P = 0.023). In contrast, there was no causal association between mtDNA-CN and atopic dermatitis as well as psoriasis, ulcerative colitis, adult-onset Still disease, type1 diabetes, Crohn disease, sarcoidosis, ankylosing spondylitis, multiple sclerosis, autoimmune hyperthyroidism, primary sclerosing cholangitis, systemic lupus erythematosus, systemic sclerosis, alopecia areata, myasthenia gravis, Guillain-Barre syndrome, dermatopolymyositis, and vitiligo. Conclusions: This MR analysis showed mtDNA-CN is causally associated with an increased risk of autoimmune hypothyroidism and rheumatoid arthritis at the genetic level. The findings have important implications for the use of mtDNA-CN as a biomarker for risk assessment of autoimmune hypothyroidism and rheumatoid arthritis in clinical practice.

Nitrogen (N) deposition rates have notably increased around the world, especially in high-altitude regions like the Qinghai–Tibetan Plateau (QTP). We conducted a six-year comprehensive experiment to simulate nitrogen deposition in an alpine grassland area near Qinghai Lake. Four levels of nitrogen depositions, i.e., 0 (CK), 8 kg N ha−1year−1 (N1), 40 kg N ha−1year−1 (N2), and 72 kg N ha−1year−1 (N3), with three replicates for each N treatment, were tested annually in early May and early July, with the meticulous collection of plant and soil samples during the peak growth period from 15 July to 15 August. We used the null model to evaluate the impact of environmental filtration and interspecific competition on the dynamics of the plant community was assessed based on the level of discrete species affinities within the plant community by constructing a phylogenetic tree. The results showed that the environmental filter was the predominant driver for the change of community’s genealogical fabric. The N2 and N3 treatments increased the influence of soil factors on the change of plant community structure. Climatic factors played a crucial role on the change of plant community in the CK grassland area, while soil factors were dominant in the N1- and N3-treated grasslands.

Peptide stapling, by employing a stable, preformed alpha-helical conformation, results in the production of peptides with improved membrane permeability and enhanced proteolytic stability, compared to the original peptides, and provides an effective solution to accelerate the rapid development of peptide drugs. Various reviews present peptide stapling chemistries, anchoring residues and one- or two-component cyclization, however, therapeutic stapled peptides have not been systematically summarized, especially focusing on various disease-related targets. This review highlights the latest advances in therapeutic peptide drug development facilitated by the application of stapling technology, including different stapling techniques, synthetic accessibility, applicability to biological targets, potential for solving biological problems, as well as the current status of development. Stapled peptides as therapeutic drug candidates have been classified and analysed mainly by receptor- and ligand-based stapled peptide design against various diseases, including cancer, infectious diseases, inflammation, and diabetes. This review is expected to provide a comprehensive reference for the rational design of stapled peptides for different diseases and targets to facilitate the development of therapeutic peptides with enhanced pharmacokinetic and biological properties.

Numerous studies have focused on the classification of N6-methyladenosine (m6A) modification sites in RNA sequences, treating it as a multi-feature extraction task. In these studies, the incorporation of physicochemical properties of nucleotides has been applied to enhance recognition efficacy. However, the introduction of excessive supplementary information may introduce noise to the RNA sequence features, and the utilization of sequence similarity information remains underexplored. In this research, we present a novel method for RNA m6A modification site recognition called M6ATMR. Our approach relies solely on sequence information, leveraging Transformer to guide the reconstruction of the sequence similarity matrix, thereby enhancing feature representation. Initially, M6ATMR encodes RNA sequences using 3-mers to generate the sequence similarity matrix. Meanwhile, Transformer is applied to extract sequence structure graphs for each RNA sequence. Subsequently, to capture low-dimensional representations of similarity matrices and structure graphs, we introduce a graph self-correlation convolution block. These representations are then fused and reconstructed through the local-global fusion block. Notably, we adopt iteratively updated sequence structure graphs to continuously optimize the similarity matrix, thereby constraining the end-to-end feature extraction process. Finally, we employ the random forest (RF) algorithm for identifying m6A modification sites based on the reconstructed features. Experimental results demonstrate that M6ATMR achieves promising performance by solely utilizing RNA sequences for m6A modification site identification. Our proposed method can be considered an effective complement to existing RNA m6A modification site recognition approaches.

Abstract The availability of oxygen and nutrients during the Mesoproterozoic (1.6–1.0 Ga) is thought to influence the rate of eukaryote evolution. The cause of the transition from low productivity in the upper Wumishan Formation to organic‐rich sediments in the Hongshuizhuang Formation remains unknown. We report FeHR/FeT, Fepy/FeHR, MoEF, UEF, VEF, and [Ce/Ce*]SN in one core of the Yanliao Basin to study the redox evolution and compare it with other sections in different depths of the Yanliao Basin to get clues of the spatial and temporal redox heterogeneity. Mo‐U covariation, low Co × Mn and CoEF × MnEF, and distribution patterns of trace metals indicate the upwelling events. An upwelling system could fuel nutrients to promote productivity levels in surface water and contribute to anoxic deep waters. The uniformly positive δ15N values are interpreted as sufficient NO3− reduction via denitrification and dissimilatory nitrate reduction to ammonium in a ferruginous upwelling condition.

PurposeTo investigate and evaluate the value of thoracic low dose computed tomography (LDCT) scan in the diagnosis of anemia.Materials and methods661 patients who received thoracic computed tomography (CT) examination and underwent a peripheral blood examination were retrospectively included. 341 patients underwent conventional dose CT (CDCT), and 320 patients underwent LDCT. Regions of interest (ROI) were placed on the left ventricular cavity (LV), descending aorta (DAo), and interventricular septum (IVS). The corresponding CT attenuation was measured, and the CT attenuation difference between LV and IVS (IVS-LV) and between DAo and IVS (IVS-DAo) was calculated, respectively. One-way analysis of variance (ANOVA) and linear regression were performed to analyze the relationship between these indicators and Hb levels. The receiver operating characteristic (ROC) curve was used to evaluate prediction performance.ResultsBoth attenuation on LDCT and CDCT showed significant differences between the healthy group and the anemic group (P < 0.05). In the LDCT group, the LV and DAo were more relevant with the hemoglobin (Hb) level (correlation coefficient 0.618 and 0.602) than other indicators, with AUCs of 0.815 (95% CI: 0.763–0.868) and 0.803 (95% CI: 0.747–0.859), respectively. The linear regression formulas for Hb level with the LV and DAo were 19.14 + 0.15 × HU [95% CI: (16.52, 21.75) + (0.12, 0.17) × HU] and 19.46 + 0.16 × HU [95% CI: (16.55, 22.36) + (0.13, 0.18) × HU], respectively. Youden’s index indicated that 37.5 HU and 38.5 HU were the best thresholds to diagnose anemia for LV and DAo, respectively. In the CDCT group, the LV and IVS-LV got obviously higher correlation coefficients (0.813 and 0.812), with AUCs of 0.831 (95% CI: 0.786–0.877) and 0.851 (95% CI: 0.808–0.894), respectively. The optimal thresholds for LV and IVS-LV were 40.5 HU and 9.5 HU, respectively.ConclusionIn LDCT examinations, an approximation of Hb level and detecting of anemia can be conducted based on simple attenuation measurements.

The watershed habitat, especially floodplains, is often impacted by the interaction between the natural environment and human activities, and the fragile ecological balance is easily disturbed. Therefore, the study of the changes in habitat quality in floodplains is significant for the reconstruction of damaged habitats. In this study, the landscape patterns and habitat quality in the Yongding River floodplain from 1967 to 2018 were evaluated. We employed spatial analysis to explore the characteristics and correlation of its spatio-temporal pattern change. Our results show that, first, the overall landscape pattern of the Yongding River floodplain was dominated by arable land and forestland while the construction land expanded. Second, the landscape pattern tended toward fragmentation, and the degree of landscape complexity increased. Third, the habitat quality was generally above the medium level. However, the low-quality area continued to increase. Furthermore, there was a strong correlation between habitat quality and the Aggregation Index, Diversity Index, and the area of water and forestland. In this context, the protection of the integrity and diversity of the landscape, reducing or even prohibiting the loss of water and forestland habitats, and restoring the ecological river, should be strengthened. The contribution of this paper provides a scientific reference to the comprehensive management and ecological restoration of river ecosystems.

Peach diseases seriously affect peach yield and people’s health. The precise identification of peach diseases and the segmentation of the diseased areas can provide the basis for disease control and treatment. However, the complex background and imbalanced samples bring certain challenges to the segmentation and recognition of lesion area, and the hard samples and imbalance samples can lead to a decline in classification of foreground class and background class. In this paper we applied deep network models (Mask R-CNN and Mask Scoring R-CNN) for segmentation and recognition of peach diseases. Mask R-CNN and Mask Scoring R-CNN are classic instance segmentation models. Using instance segmentation model can obtain the disease names, disease location and disease segmentation, and the foreground area is the basic feature for next segmentation. Focal Loss can solve the problems caused by difficult samples and imbalance samples, and was used for this dataset to improve segmentation accuracy. Experimental results show that Mask Scoring R-CNN with Focal Loss function can improve recognition rate and segmentation accuracy comparing to Mask Scoring R-CNN with CE loss or comparing to Mask R-CNN. When ResNet50 is used as the backbone network based on Mask R-CNN, the segmentation accuracy of segm_mAP_50 increased from 0.236 to 0.254. When ResNetx101 is used as the backbone network, the segmentation accuracy of segm_mAP_50 increased from 0.452 to 0.463. In summary, this paper used Focal Loss on Mask R-CNN and Mask Scoring R-CNN to generate better mAP of segmentation and output more detailed information about peach diseases.

The emergence of multi-drug resistant bacteria and the lack of novel antibiotics to combat them have led to the revival of polymyxin B, a previously abandoned antibiotic due to its potential nephrotoxicity and neurotoxicity. To facilitate its widely clinical applications, increasing effort has been devoted to molecularly engineer polymyxin B for the targeted imaging and effective treatment of bacterial infections. Herein, the molecular engineering strategies will be summarized in this mini review, with selected recent advances for illustration. Perspective of the challenges and trends in this exciting and eagerly anticipated research area will also be provided in the end. We hope this mini review will inspire researchers from diverse fields to bring forward the next wave of exploiting molecular engineering approaches to propel the “old” polymyxin B to “new” clinical significance in combating bacterial infections.

ObjectiveBased on non-contrast-enhanced (NCE)/contrast-enhanced (CE) computed tomography (CT) images, we try to identify a combined-radiomics model and evaluate its predictive capacity regarding response to anti-PD1 immunotherapy of patients with non-small-cell lung cancer (NSCLC).Methods131 patients with NSCLC undergoing anti-PD1 immunotherapy were retrospectively enrolled from 7 institutions. Using largest lesion (LL) and target lesions (TL) approaches, we performed a radiomics analysis based on pretreatment NCE-CT (NCE-radiomics) and CE-CT images (CE-radiomics), respectively. Meanwhile, a combined-radiomics model based on NCE-CT and CE-CT images was constructed. Finally, we developed their corresponding nomograms incorporating clinical factors. ROC was used to evaluate models’ predictive performance in the training and testing set, and a DeLong test was employed to compare the differences between different models.ResultsFor TL approach, both NCE-radiomics and CE-radiomics performed poorly in predicting response to immunotherapy. For LL approach, NCE-radiomics nomograms and CE-radiomics nomograms incorporating with clinical factor of distant metastasis all showed satisfactory results, reflected by the AUCs in the training (AUC=0.84, 95% CI: 0.75-0.92; AUC=0.77, 95% CI: 0.67-0.87) and test sets (AUC=0.78, 95% CI: 0.64-0.92, AUC=0.73, 95% CI: 0.57-0.88), respectively. Compared with the NCE-radiomics nomograms, the combined-radiomics nomogram showed incremental predictive capacity in the training set (AUC=0.85, 95% CI: 0.77-0.92) and test set (AUC=0.81, 95% CI: 0.67-0.94), respectively, but no statistical difference (P=0.86, P=0.79).ConclusionCompared with radiomics based on single NCE or CE-CT images, the combined-radiomics model has potential advantages to identify patients with NSCLC most likely to benefit from immunotherapy, and may effectively improve more precise and individualized decision support.

Rapid urbanization has led to landscape fragmentation and habitat loss. As an organic structure integrating green space, an urban ecological network can effectively reduce ecological risks and protect biodiversity if its landscape connectivity is maintained. Chaoyang District in Beijing is facing the challenge of transformational development due to excessive urbanization. Taking this district as the study area, this study assessed the environmental impact of different development scenarios on landscape connectivity indices and explored the most relevant strategies for important green space patches by combining ecological network modeling (Graphab) and scenario simulation techniques (FLUS model). The results show that under the urban expansion scenario, the probability of connectivity (PC) decreases by 59.7%, while under the master plan scenario, it increases by 102.1%. Even under the ideal ecological scenario, the ecological network structure of the region faces structural problems. Patches and corridors with high delta probabilities of connectivity (dPC) are concentrated in the north, with no effective connection between the north and south. Finally, planning strategies and priorities for important patches under different urban development goals are proposed through a strategy matrix. Overall, this study proposes a framework for decision-makers to solve planning conflicts between urban expansion and biodiversity conservation, especially for cities in transition.

ObjectiveWe aimed to identify imaging biomarkers to assess predictive capacity of radiomics nomogram regarding treatment response status (responder/non-responder) in patients with advanced NSCLC undergoing anti-PD1 immunotherapy.Methods197 eligible patients with histologically confirmed NSCLC were retrospectively enrolled from nine hospitals. We carried out a radiomics characterization from target lesions (TL) approach and largest target lesion (LL) approach on baseline and first follow-up (TP1) CT imaging data. Delta-radiomics feature was calculated as the relative net change in radiomics feature between baseline and TP1. Minimum Redundancy Maximum Relevance (mRMR) and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression were applied for feature selection and radiomics signature construction.ResultsRadiomics signature at baseline did not show significant predictive value regarding response status for LL approach (P = 0.10), nor in terms of TL approach (P = 0.27). A combined Delta-radiomics nomogram incorporating Delta-radiomics signature with clinical factor of distant metastasis for target lesions had satisfactory performance in distinguishing responders from non-responders with AUCs of 0.83 (95% CI: 0.75–0.91) and 0.81 (95% CI: 0.68–0.95) in the training and test sets respectively, which was comparable with that from LL approach (P = 0.92, P = 0.97). Among a subset of those patients with available pretreatment PD-L1 expression status (n = 66), models that incorporating Delta-radiomics features showed superior predictive accuracy than that of PD-L1 expression status alone (P

The present work introduces an analysis of the measurement and model effects that exist in monopile scour protection experiments with repeated small scale tests. The damage erosion is calculated using the three dimensional global damage number S3D and subarea damage number S3D,i. Results show that the standard deviation of the global damage number σ(S3D)=0.257 and is approximately 20% of the mean S3D, and the standard deviation of the subarea damage number σ(S3D,i)=0.42 which can be up to 33% of the mean S3D. The irreproducible maximum wave height, chaotic flow field and non-repeatable armour layer construction are regarded as the main reasons for the occurrence of strong model effects. The measurement effects are limited to σ(S3D)=0.039 and σ(S3D,i)=0.083, which are minor compared to the model effects.

Objective(s): Ten-eleven translocation (TET) family members have been shown to be involved in the development of many tumors. However, the biological role of the TET family and its mechanism of action in colorectal carcinogenesis and progression remain poorly understood. Materials and Methods:We measured the expression levels of TET family members in colorectal cancer (CRC) specimens, in the corresponding normal tissues and in cell lines using quantitative real-time PCR (qRT-PCR) and in situ hybridization (ISH). Both the protein function and the protein-independent role of TETs were investigated by cell viability assays and cell invasion assays using in vitro and in vivo models. Results: We found that all three TET genes were strongly up-regulated at the transcript level in CRC samples compared to matched normal tissues. The same results were observed in colorectal cancer cell lines. Knockdown of TETs by shTET1/2/3 showed that TET family members inhibited CRC growth and metastasis. We showed that TET family member degradation by miR-506 inhibits cell proliferation and invasion in colorectal cancer. Conclusion: Through this study, we advance our understanding of the expression levels TETs and miR-506 in CRC and further clarify the internal regulatory mechanism of miR-506 by targeting TET during CRC processes. These findings may contribute to a novel avenue for researching and developing targeted therapies for CRC.

This paper presents a series of large-scale wave flume experiments on the scour protection damage around a monopile under combined waves and current conditions with model scales of 1:16.67 and 1:8.33. The main objective is to compare the damage data obtained from these large-scale models with existing monopile scour protection design approaches, which were proposed based on small scale wave flume experiments, and to study the applicability of the existing approaches. The static stability (onset of motion and bed shear stress) and the dynamic stability (three-dimensional damage numbers) of the scour protection are investigated. Both results show that the existing design approaches can be conservative when applied to large scale models, which highlights the need of further investigations on scale and model effects. In addition, this paper also analyses the scour protection damage depth. It is observed that damage depths of the scour protection layer under low Keulegan–Carpenter number (KC) conditions are smaller than predictions. The study provides valuable large scale experimental data for future research on the monopile scour protection design.

With the widespread deployment and use of MTC（machine-type communication）devices,MTC has been closely integrated with the mobile communication network.Significant increase in the number of MTC devices causes more strict requirements for communication system.According to the characteristics of MTC communication and the development trend,three key areas of MTC in current LTE-Advanced network were discussed:RAN overload contro1,efficient radio resource allocation and energy savings.Several research challenges that need to be addressed for scalable support of MTC devices for R12 and beyond were summarized,typical optimization methods and solutions were introduced,and corresponding improvement directions according to the current application status were put forward.

This paper describes experimental research on a floating moored Oscillating Water Column (OWC)-type Wave-Energy Converter (WEC) carried out in the wave flume of the Coastal Engineering Research Group of Ghent University. This research has been introduced to cover the existing data scarcity and knowledge gaps regarding response of moored floating OWC WECs. The obtained data will be available in the future for the validation of nonlinear numerical models. The experiment focuses on the assessment of the nonlinear motion and mooring-line response of a 1:25 floating moored OWC WEC model to regular waves. The OWC WEC model motion has 6 degrees of freedom and is limited by a symmetrical 4-point mooring system. The model is composed of a chamber with an orifice on top of it to simulate the power-take-off (PTO) system and the associated damping of the motion of the OWC WEC model. In the first place, the motion response in waves of the moored floating OWC WEC model is investigated and the water surface elevation in the OWC WEC chamber is measured. Secondly, two different mooring-line materials (iron chains and nylon ropes) are tested and the corresponding OWC WEC model motions and mooring-line tensions are measured. The performance of these two materials is similar in small-amplitude waves but different in large wave-amplitude conditions. Thirdly, the influence of different PTO conditions is investigated by varying the diameter of the top orifice of the OWC WEC model. The results show that the PTO damping does not affect the OWC WEC motion but has an impact on the water surface elevation inside the OWC chamber. In addition, an unbalanced mooring configuration is discussed. Finally, the obtained data for a moored cubic model in waves are presented, which is a benchmarking case for future validation purposes.

This study aims to improve the design of scour protection around offshore wind turbine monopiles, as well as future-proofing them against the impacts of climate change. A series of large-scale experiments have been performed in the context of the European HYDRALAB-PLUS PROTEUS (Protection of offshore wind turbine monopiles against scouring) project in the Fast Flow Facility in HR Wallingford. These experiments make use of state of the art optical and acoustic measurement techniques to assess the damage of scour protections under the combined action of waves and currents. These novel PROTEUS tests focus on the study of the grading of the scour protection material as a stabilizing parameter, which has never been done under the combined action of waves and currents at a large scale. Scale effects are reduced and, thus, design risks are minimized. Moreover, the generated data will support the development of future scour protection designs and the validation of numerical models used by researchers worldwide. The testing program objectives are: (i) to compare the performance of single-layer wide-graded material used against scouring with current design practices; (ii) to verify the stability of the scour protection designs under extreme flow conditions; (iii) to provide a benchmark dataset for scour protection stability at large scale; and (iv) to investigate the scale effects on scour protection stability.