Search

B-cell lymphoma 10 (Bcl10) is a scaffolding protein that functions as an upstream regulator of NF-κB signaling by forming a complex with Mucosa-associated lymphoid tissue lymphoma translocation protein 1 (Malt1) and CARD-coiled coil protein family. This study showed that Bcl10 was involved in type I interferon (IFN) expression in response to DNA virus infection and that Bcl10-deficient mice were more susceptible to Herpes simplex virus 1 (HSV-1) infection than control mice. Mechanistically, DNA virus infection can trigger Bcl10 recruitment to the STING-TBK1 complex, leading to Bcl10 phosphorylation by TBK1. The phosphorylated Bcl10 undergoes droplet-like condensation and forms oligomers, which induce TBK1 phosphorylation and translocation to the perinuclear region. The activated TBK1 phosphorylates IRF3, which induces the expression of type I IFNs. This study elucidates that Bcl10 induces an innate immune response by undergoing droplet-like condensation and participating in signalosome formation downstream of the cGAS-STING pathway.

In the field of preference-based evolutionary multiobjective optimization, optimization algorithms are required to search for the Pareto optimal solutions preferred by the decision-maker (DM). The reference point is a type of techniques that effectively describe the preferences of DM. So far, the reference point is either static or interactive with the evolutionary process. However, the existing reference point techniques do not cover all application scenarios. A novel case, i.e., the reference point changes over time due to the environment change, has not been considered. This paper focuses on the multiobjective optimization problems with dynamic preferences of the DM. First, we propose a change model of the reference point to simulate the change of the preference by the DM over time. Then, a dynamic preference-based multiobjective evolutionary algorithm framework with a clonal selection algorithm (ĝa-NSCSA) and a genetic algorithm (ĝa-NSGA-II) is designed to solve such kind of optimization problems. In addition, in terms of practical applications, the experiments on the portfolio optimization problems with the dynamic reference point model are tested. Experimental results on the benchmark problems and the practical applications show that ĝa-NSCSA exhibits better performance among the compared optimization algorithms.

Background Chronic musculoskeletal pain has been linked to dementia; however, chronic pain typically occurs in multiple sites; therefore, this study was to investigate whether greater number of chronic pain sites is associated with a higher risk of dementia and its subtypes. Methods Participants (N = 356,383) in the UK Biobank who were dementia-free at baseline were included. Pain in the hip, knee, back, and neck/shoulder or ‘all over the body’ and its duration were assessed. Participants were categorised into six groups: no chronic pain; chronic pain in 1, 2, 3, and 4 sites, and ‘all over the body’. All-cause dementia and its subtypes were ascertained using hospital inpatient and death registry records. Cox regression was used to investigate the associations between the number of chronic pain sites and the incidence of all-cause dementia and its subtypes. Results Over a median follow-up of 13 years, 4959 participants developed dementia. After adjustment for sociodemographic, lifestyle, comorbidities, pain medications, psychological problems, and sleep factors, greater number of chronic pain sites was associated with an increased risk of incident all-cause dementia (hazard ratio [HR] = 1.08 per 1 site increase, 95% CI 1.05–1.11) and Alzheimer’s disease (AD) (HR = 1.09 per 1-site increase, 95% CI 1.04–1.13) in a dose–response manner but not vascular and frontotemporal dementia. No significant association was found between the number of chronic pain sites and the risk of incident all-cause dementia among a subsample that underwent a fluid intelligence test. Conclusions Greater number of chronic pain sites was associated with an increased risk of incident all-cause dementia and AD, suggesting that chronic pain in multiple sites may contribute to individuals’ dementia risk and is an underestimated risk factor for dementia.

This article constructed a food taste deviation index using text analysis based on food culture as a measure of cultural inclusion. Cultural inclusion was related to corporate total factor productivity, aiming to investigate whether the cultural inclusion affects corporate sustainability. The findings showed uneven distribution of cultural inclusion in various areas of China, contributing to the unbalanced sustainable development of firms in different regions, as reflected by the higher total factor productivity of firms located in regions with higher cultural inclusion. A test using mountainous undulation as an instrumental variable verified the causal relationship between cultural inclusion and firm sustainability. Besides, a regression discontinuity design was employed to mitigate the impacts of the bidirectional causality. Moreover, a high level of cultural inclusion in top managers’ hometown significantly improved corporate sustainability, suggesting that executives can transmit cultural inclusion in society. In addition, firms in more inclusive regions are more motivated to increase their social responsibility to staff as a way to promote their total factor productivity, suggesting that cultural inclusion promotes firm sustainability by increasing firms’ care for staff. This article also found that cultural inclusion has heterogeneous effects across firms of different levels of industry competition, and different levels of analyst attention. The research reveals the impact of cultural inclusion on the real economy and help academics dissect the informal institutional reasons behind the sustainable development of firms in different geographies from a new perspective, contributing to the promotion of economic sustainability at the regional level and related policy formulation.

In recent years, convolutional neural networks (CNNs) have made great achievements in the field of medical image segmentation, especially full convolutional neural networks based on U-shaped structures and skip connections. However, limited by the inherent limitations of convolution, CNNs-based methods usually exhibit limitations in modeling long-range dependencies and are unable to extract large amounts of global contextual information, which deprives neural networks of the ability to adapt to different visual modalities. In this paper, we propose our own model, which is called iU-Net bacause its structure closely resembles the combination of i and U. iU-Net is a multiple encoder-decoder structure combining Swin Transformer and CNN. We use a hierarchical Swin Transformer structure with shifted windows as the primary encoder and convolution as the secondary encoder to complement the context information extracted by the primary encoder. To sufficiently fuse the feature information extracted from multiple encoders, we design a feature fusion module (W-FFM) based on wave function representation. Besides, a three branch up sampling method(Tri-Upsample) has developed to replace the patch expand in the Swin Transformer, which can effectively avoid the Checkerboard Artifacts caused by the patch expand. On the skin lesion region segmentation task, the segmentation performance of iU-Net is optimal, with Dice and Iou reaching 90.12% and 83.06%, respectively. To verify the generalization of iU-Net, we used the model trained on ISIC2018 dataset to test on PH2 dataset, and achieved 93.80% Dice and 88.74% IoU. On the lung feild segmentation task, the iU-Net achieved optimal results on IoU and Precision, reaching 98.54% and 94.35% respectively. Extensive experiments demonstrate the segmentation performance and generalization ability of iU-Net.

Evolutionary multimodal optimization algorithms aim to provide multiple solutions simultaneously. Many studies have been conducted to design effective evolutionary algorithms for solving multimodal optimization problems. However, optimization problems with many global and acceptable local optima have not received much attention. This type of problem is undoubtedly challenging. In this study, we focus on problems with many optima, the so-called many-modal optimization problems, and this study is an extension of our previous conference work. First, a test suite including additively nonseparable many-modal optimization problems and partially additively separable many-modal optimization problems is designed. Second, an improved difficulty-based cooperative co-evolution algorithm (DBCC2) is proposed, which dynamically estimates the difficulties of subproblems and allocates the computational resources during the search. Experimental results show that DBCC2 has competitive performance.

Objective The conventional breast Diffusion-weighted imaging (DWI) was subtly influenced by microcirculation owing to the insufficient selection of the b values. However, the multiparameter derived from multiple b-value exhibits more reliable image quality and maximize the diagnostic accuracy. We aim to evaluate the diagnostic performance of stand-alone parameter or in combination with multiparameter derived from multiple b-value DWI in differentiating malignant from benign breast lesions. Methods A total of forty-one patients diagnosed with benign breast tumor and thirty-eight patients with malignant breast tumor underwent DWI using thirteen b values and other MRI functional sequence at 3.0 T magnetic resonance. Data were accepted mono-exponential, bi-exponential, stretched-exponential, aquaporins (AQP) model analysis. A receiver operating characteristic curve (ROC) was used to evaluate the diagnostic performance of quantitative parameter or multiparametric combination. The Youden index, sensitivity and specificity were used to assess the optimal diagnostic model. T-test, logistic regression analysis, and Z-test were used. P value Result The ADCavg, ADCmax, f, and α value of the malignant group were lower than the benign group, while the ADCfast value was higher instead. The ADCmin, ADCslow, DDC and ADCAQP showed no statistical significance. The combination (ADCavg-ADCfast) yielded the largest area under curve (AUC = 0.807) with sensitivity (68.42%), specificity (87.8%) and highest Youden index, indicating that multiparametric combination (ADCavg-ADCfast) was validated to be a useful model in differentiating the benign from breast malignant lesion. Conclusion The current study based on the multiple b-value diffusion model demonstrated quantitatively multiparametric combination (ADCavg-ADCfast) exhibited the optimal diagnostic efficacy to differentiate malignant from benign breast lesions, suggesting that multiparameter would be a promising non-invasiveness to diagnose breast lesions.

Subpectoral implant-based breast reconstruction following mastectomy commonly severs the inferior border of the pectoralis major muscle for better projection of the lower pole. This can affect a patient's postoperative motor function and result in animation deformity. Implant-based breast reconstruction using partial muscle coverage with an acellular dermal matrix (ADM) can be costly. There is an unmet clinical need for a novel surgical method for submuscular implant-based breast reconstruction.We describe an innovative technique for submuscular implant-based breast reconstruction following mastectomy. The approach utilizes the serratus anterior muscle fascia connected to the lateral margin of the pectoralis major muscle to form a lateral tissue pocket for implant coverage. This method preserves the inferior border of the pectoralis major muscle and minimizes the size of ADM coverage. Patient satisfaction on the BREAST-Q Reconstruction Module and complications were assessed 12 months after surgery.The novel surgical design was safe and used minimal ADM (6 × 5cmSubmuscular implant-based breast reconstruction following mastectomy utilizing the serratus anterior muscle fascia connected to the lateral margin of the pectoralis major muscle to form a lateral tissue pocket for implant coverage is safe, feasible, and generates good aesthetic outcomes.

Synthetic genomics has provided new bottom-up platforms for the functional study of viral and microbial genomes. The construction of the large, gigabase (Gb)-sized genomes of higher organisms will deepen our understanding of genetic blueprints significantly. But for the synthesis and assembly of such large-scale genomes, the development of new or expanded methods is required. In this study, we develop an efficient pipeline for the construction of large DNA fragments sized 100 kilobases (kb) or above from scratches and describe an efficient method for "scar-free" engineering of the assembled sequences. Our method, therefore, should provide a standard framework for producing long DNA molecules, which are critical materials for synthetic genomics and metabolic engineering.

Hong Kong is considered to be a marginal area for coral growth due to its subtropical geography with relatively low winter sea temperatures. Corals can only form non-reefal communities and are believed to host only a low diversity of symbionts with limited flexibility in their symbiont changes. Whether these previously predicted low symbiont diversity is true or is simply a technical artifact and whether these symbionts are generalists or specialists have not fully resolved. To address these issues, we investigated symbiodiniacean diversity and community structure of 30 species of Hong Kong corals using high-throughput sequencing of the nuclear ribosomal RNA gene ITS2. We found high Symbiodiniaceae species richness, with each coral hosting multiple distinct ITS2 symbiont types. Using SymPortal pipeline to alleviate effects of intraspecific ITS polymorphism, the 4662 Symbiodiniaceae ITS2 sequence variants (DIVs) found in our samples were collapsed into 13 distinct ITS2-type profiles, covering Symbiodinium, Breviolum, Cladocopium, and Durusdinium genera, seven of which were coral specific. Cladocopium goreaui was the most diversified (six profiles) and prevalent lineage, dominating the symbiont communities in 29 of the 30 corals species examined. The stress-tolerant Oulastrea crispata was exceptional as its symbionts were dominated by Durusdinium eurythalpos (D13-D13b-D12-D13c profile). Interestingly, Cladocopium C15 was diversified into two ITS2-type profiles, one being Porites lobata specific, while the other was associated with both P. aranetai and P. lutea. Overall, most corals harbor a single dominant generalist symbiont, while some corals host both generalist and specialist symbionts. This work lays the foundation for future research to understand how the generalist and specialist as well as dominant and rare symbionts contribute to the responses and resilience of their host corals against environmental fluctuations in a marginal coral ecosystem, like that in Hong Kong.

Al–Mg–Sc–Zr alloys manufactured using selective laser melting (SLM) possess outstanding static mechanical properties and thus have great potential application in the aerospace industry. However, their fatigue performance has not been clearly investigated and understood. In this work, the high cycle fatigue properties of an Al–Mg–Sc–Zr alloy manufactured via SLM with optimised process parameters (relative density over 99%) was studied with focus on the defects, whose size, shape and distribution were determined through X-ray tomography. Microstructure analysis results show that the Al–Mg–Sc–Zr alloy produced using SLM presents a periodic, inhomogeneous structure consisting of equiaxed grains at the boundary and columnar grains at the centre of one molten pool, which causes a significant difference in deformational mismatch under the fabrication conditions. Furthermore, X ray-CT results show that the defects, mainly porosity, are randomly distributed with the critical flaw size to initiate fatigue crack, thereby reducing fatigue life. When the stress ratio (R) is 0.1, the annealed sample presents good fatigue strength (σf) reaching 100.5 MPa, which is close to that of high-strength wrought 7075Al. Finally, a fatigue crack propagation mode connected with defect microstructure characteristics was established for prediction of fatigue properties.

p-Benzoquinone (BQ) is a promising candidate for next-generation sodium-ion batteries (SIBs) because of its high theoretical specific capacity, good reaction reversibility, and high resource availability. However, practical application of BQ faces many challenges, such as a low discharge plateau (∼2.7 V) as cathode material or a high discharge plateau as anode material compared with inorganic materials for SIBs and high solubility in organic electrolytes, resulting in low power and energy densities. Here, tetrahydroxybenzoquinone tetrasodium salt (Na4C6O6) is synthesized through a simple neutralization reaction at low temperatures. The four −ONa electron-donating groups introduced on the structure of BQ greatly lower the discharge plateau by over 1.4 V from ∼2.70 V to ∼1.26 V, which can change BQ from cathode to anode material for SIBs. At the same time, the addition of four −ONa hydrophilic groups inhibits the dissolution of BQ in the organic electrolyte to a certain extent. As a result, Na4C6O6 as the anode displays a moderate discharge capacity and cycling performance at an average work voltage of ∼1.26 V versus Na/Na+. When evaluated as a Na-ion full cell (NIFC), a Na3V2(PO4)3 ‖ Na4C6O6 NIFC reveals a moderate discharge capacity and an average discharge plateau of ∼1.4 V. This research offers a new molecular structure design strategy for reducing the discharge plateau and simultaneously restraining the dissolution of organic electrode materials.

Early recognition of cachexia is essential for ensuring the prompt intervention and treatment of cancer patients. However, the diagnosis of cancer cachexia (CC) usually is delayed. This study aimed to establish an accurate and high-efficiency diagnostic system for CC.A total of 4834 cancer inpatients were enrolled in the INSCOC project from July 2013 to June 2020. All cancer patients in the study were randomly assigned to a development cohort (n=3384, 70%) and a validation cohort (n=1450, 30%). The least absolute shrinkage and selection operator (LASSO) method and multivariable logistic regression were used to identify the independent predictors for developing the dynamic nomogram. Discrimination and calibration were adopted to evaluate the ability of nomogram. A decision curve analysis (DCA) was used to evaluate clinical use.We combined 5 independent predictive factors (age, NRS2002, PG-SGA, QOL by the QLQ-C30, and cancer categories) to establish the online dynamic nomogram system. The C-index, sensitivity, and specificity of the nomo-system to predict CC was 0.925 (95%CI, 0.916-0.934, P0.001), 0.826, and 0.862 in the development set, while the values were 0.923 (95%CI, 0.909-0.937, P0.001), 0.854, and 0.829 in the validation set. In addition, the calibration curves of the diagnostic nomogram also presented good agreement with the actual situation. DCA showed that the model is clinically useful and can increase the clinical benefit in cancer patients.This study developed an online dynamic nomogram system with outstanding accuracy to help clinicians and dieticians estimate the probability of cachexia. This simple-to-use online nomogram can increase the clinical benefit in cancer patients and is expected to be widely adopted.

Background To explore the value of preoperative prognostic immune and nutritional index (PINI) in predicting postoperative complications and long-term outcomes in patients with stage I–III colorectal cancer (CRC). Methods Restricted cubic splines were used to assess the relationship between PINI and survival in patients with CRC. The Kaplan–Meier method and log-rank test were used to plot the survival curves. The Cox proportional hazards model was used to evaluate independent prognostic predictors in patients with CRC. A logistic regression analysis was performed to identify independent predictors of postoperative complications. The least absolute shrinkage and selection operator (LASSO) logistic regression algorithm was used for feature screening. Results An evident positive dose–response relationship between PINI and survival in patients with CRC was identified. Compared with patients with a high PINI, those with a low PINI had worse disease-free survival (DFS) (47.9% vs. 66.9%, p p p p p Conclusion PINI is an effective biomarker for predicting postoperative complications, DFS, and OS in patients with stage I–III CRC.

Limited studies have been conducted to identify and validate multiple sclerosis (MS) genetic loci associated with disability progression. We aimed to identify MS genetic loci associated with worsening of disability over time, and to develop and validate ensemble genetic learning model(s) to identify people with MS (PwMS) at risk of future worsening. We examined associations of 208 previously established MS genetic loci with the risk of worsening of disability; we learned ensemble genetic decision rules and validated the predictions in an external dataset. We found 7 genetic loci (rs7731626: HR 0.92, P = 2.4 × 10–5; rs12211604: HR 1.16, P = 3.2 × 10–7; rs55858457: HR 0.93, P = 3.7 × 10–7; rs10271373: HR 0.90, P = 1.1 × 10–7; rs11256593: HR 1.13, P = 5.1 × 10–57; rs12588969: HR = 1.10, P = 2.1 × 10–10; rs1465697: HR 1.09, P = 1.7 × 10–128) associated with risk worsening of disability; most of which were located near or tagged to 13 genomic regions enriched in peptide hormones and steroids biosynthesis pathways by positional and eQTL mapping. The derived ensembles produced a set of genetic decision rules that can be translated to provide additional prognostic values to existing clinical predictions, with the additional benefit of incorporating relevant genetic information into clinical decision making for PwMS. The present study extends our knowledge of MS progression genetics and provides the basis of future studies regarding the functional significance of the identified loci.

Adoptive transfer of antigen-specific T cells represents a major advance in cancer immunotherapy, with robust clinical outcomes in some patients1. Both the number of transferred T cells and their differentiation state are critical determinants of effective responses2,3. T cells can be expanded with T cell receptor (TCR)-mediated stimulation and interleukin-2, but this can lead to differentiation into effector T cells4,5 and lower therapeutic efficacy6, whereas maintenance of a more stem-cell-like state before adoptive transfer is beneficial7. Here we show that H9T, an engineered interleukin-2 partial agonist, promotes the expansion of CD8+ T cells without driving terminal differentiation. H9T led to altered STAT5 signalling and mediated distinctive downstream transcriptional, epigenetic and metabolic programs. In addition, H9T treatment sustained the expression of T cell transcription factor 1 (TCF-1) and promoted mitochondrial fitness, thereby facilitating the maintenance of a stem-cell-like state. Moreover, TCR-transgenic and chimeric antigen receptor-modified CD8+ T cells that were expanded with H9T showed robust anti-tumour activity in vivo in mouse models of melanoma and acute lymphoblastic leukaemia. Thus, engineering cytokine variants with distinctive properties is a promising strategy for creating new molecules with translational potential. H9T, an engineered IL-2 partial agonist, promotes the expansion of T cells while maintaining a stem-cell-like state, leading to improved efficacy of adoptive cell therapy in mouse models of melanoma and acute lymphoblastic leukaemia.

Yeast is widely used for industrial production of various types of products, such as ethanol and enzymes. However, its fermentation efficiency is strongly reduced by harmful environmental stresses. Specifically, harmful environmental stresses damage important cellular components, such as cell wall, cell membrane, proteins, etc. Then, these damages cause cellular metabolic disorders or even death. In the past decades, there has been a portfolio of studies on the environmental stress tolerance of yeasts, which mainly aimed at cell damages caused by different environmental stresses, different ways to improve yeast environmental stress tolerance or a tolerance mechanism for certain environmental stress. However, a comprehensive overview of how yeasts respond to environmental stresses is lacking, and the correlation of tolerance mechanism between different environmental stresses is unclear. In this review, we summarized the general damages induced by most of environmental stresses, the existing major mechanisms of environmental stress tolerance from the perspective of key signalling pathways, and the common ways to improve the resistance to environmental stresses in yeast cells. The tolerance mechanisms of yeast cells to different environmental stresses are diverse, but sometimes they share the same signalling pathway. Cells use sensors on the cell surface to recognize environmental stresses and transmit signals to the nucleus to cause changes in gene expression. By summarizing the main signalling pathways, including MAPK pathway, cAMP/PKA pathway, YAP1/SKN7 pathway, it will provide a powerful reference for future efforts to promote yeast environmental stress tolerance and study yeast tolerance mechanisms.

A new model for predicting elastic flexural wave band gaps in periodic composite plate structures containing interconnected, star-shaped, transversely isotropic, magneto-electro-elastic (MEE) inclusions is developed using a microstructure-dependent Mindlin plate model. The Floquet–Bloch theorem and the plane wave expansion method for periodic media are employed to solve the non-classical wave equations and to determine the band gaps incorporating the microstructure effect. The current non-classical model recovers its classical elasticity-based counterpart as a special case if the microstructure effect is suppressed. A parametric study is performed to demonstrate the newly developed model. The numerical results of the study show that the microstructure effect on band gaps is large when the plate is very thin. In addition, the unit cell edge length, inclusion geometry and MEE coupling have significant effects on band gap sizes, and large band gaps can be generated by tailoring the controlling parameters.