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Diabetes Mellitus combined with Mild Cognitive Impairment (DM-MCI) is a high incidence disease among the elderly. Patients with DM-MCI have considerably higher risk of dementia, whose daily self-care and life management (i.e. self-management) have a significant impact on the development of their condition. Thus, the inclusion and discrimination of subsequent interventions according to their self-management is an urgent issue. A Sparse-representation-based Discriminative Classification model (SDC) is proposed in this paper to correctly classify MCI-DM patients based on their self-management ability. Specifically, an L1-minimization sparse representation model, an efficient machine learning model, is used to obtain the sparse histogram that encodes the identity of the test sample. Then, the coefficient of determination is adopted to determine the category based on the sparse histogram of the test sample. Extensive experiments on the self-management data of DM-MCI are conducted to verify the effectiveness of SDC. The experimental results show that the accuracy , precision , recall , and F1-score are 94.3%, 95.0%, 94.3%, and 94.5%, respectively, demonstrating the excellent performance of SDC. The model used in this study has high accuracy and can be used for subgroup discrimination. The use of the sparse representation model in this study has supportive implications for the inclusion of research subjects in clinical intervention strategies. [ABSTRACT FROM AUTHOR]

With growing environmental concerns and the exploitation of ubiquitous big data, smart transportation is transforming logistics business and operations into a more sustainable approach. To answer questions in intelligent transportation planning, such as which data are feasible, which methods are applicable for intelligent prediction of such data, and what are the available operations for prediction, this paper offers a new deep learning approach called bi-directional isometric-gated recurrent unit (BDIGRU). It is merged to the deep learning framework of neural networks for predictive analysis of travel time and business adoption for route planning. The proposed new method directly learns high-level features from big traffic data and reconstructs them by its own attention mechanism drawn by temporal orders to complete the learning process recursively in an end-to-end manner. After deriving the computational algorithm with stochastic gradient descent, we use the proposed method to perform predictive analysis of stochastic travel time under various traffic conditions (especially for congestions) and then determine the optimal vehicle route with the shortest travel time under future uncertainty. Based on empirical results with big traffic data, we show that the proposed BDIGRU method can (1) significantly improve the predictive accuracy of one-step 30 min ahead travel time compared to several conventional (data-driven, model-driven, hybrid, and heuristics) methods measured with several performance criteria, and (2) efficiently determine the optimal vehicle route in relation to the predictive variability under uncertainty. [ABSTRACT FROM AUTHOR]

In an effort to predict the storage life of a composite modified double base propellant (CMDB propellant) at 298.15 K, we investigated the relationship between the maximum elongation of the propellant and its stabilizer depletion. Thermally accelerated aging experiments were carried out at 323.15 K, 333.15 K, 343.15 K, and 353.15 K. The change in the amounts of N-methyl-4-nitroaniline (MNA) content and the maximum elongation of the propellant at different thermal aging temperatures were measured and analyzed. A modified exponential aging model for CMDB propellant was proposed. With the use of both MNA content and maximum elongation as aging indicators, the storage life of CMDB propellants at 298.15 K was predicted using the modified Arrhenius equation. The aging mechanism of CMDB propellant was analyzed, and a correlation function model for the relationship between the maximum elongation and stabilizer depletion was established. The results show that the maximum elongation and MNA content decrease with aging time as the aging temperature increases. The fitting correlation coefficients of the modified exponential aging model exceed 0.97. The storage life of CMDB at 298.15 K is estimated to be 20.84 years and 19.19 years, based on the MNA content and maximum elongation, respectively. The validity of the correlation function is validated by comparing the prediction results of the correlation function and the aging model for the maximum elongation under different aging times. The overall error is less than 15%, indicating the validity for predicting the maximum elongation of CMDB propellant based on the consumption of MNA. [ABSTRACT FROM AUTHOR]

Purpose: Arteriovenous fistulas (AVF) is the preferred type of hemodialysis access, but when an arteriovenous anastomosis (AVA) calcifies, surgical revision of the AVF may be required. We report a technique to create percutaneous artery-to-vein intervascular neo-fistulas for re-anastomosis of AVA and evaluate its safety and efficacy. Materials and Methods: 9 patients who failed either guidewire navigation or conventional balloon dilation for calcified AVA stenosis/occlusion underwent a salvage procedure of their dialysis shunt by the percutaneous creation of a new arteriovenous fistula. Needle puncture of the adjacent supplying artery and outflow vein under ultrasonographic and/or fluoroscopic guidance was performed and followed by balloon dilation, with or without stent graft placement. The detailed techniques, technical success, primary neo-fistula patency, primary and secondary access patency rates were reported herein. Results: Technical success was achieved in 100% of the 9 patients treated (7 neo-fistulas with stents and 2 neo-fistulas without stent placement). The median primary neo-fistula and access patencies were 15 and 5 months, respectively. The primary neo-fistula patency rates at 6, 12, and 18 months were 72.9%, 54.7% and 27.9%, respectively, with secondary neo-fistula and access patency rates of 72.9%, 72.9% and 72.9%, respectively. One delayed complication of pseudoaneurysm formation occurred, which was managed by the successful endovascular deployment of a stent graft on an out-patient basis. Conclusion: Percutaneous artery-to-vein intervascular neo-fistula creation is feasible for re-anastomosing calcified AVA, with low adverse effects and acceptable primary neo-fistula and secondary access patency. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is a heterogeneous and complex etiological disease. Understanding perturbations of circulating metabolites could improve prognosis. Methods: We recruited breast cancer patients from Kaohsiung Medical University (KMU) to perform untargeted (case–control design) and targeted (patient cohort) metabolomics analyses in the discovery and validation phases to evaluate interaction effects between clinical factors and plasma metabolites using multivariable Cox proportional hazards model. Results: In the discovery phase, partial least squares-discriminant analysis (PLS-DA) showed that plasma metabolites were significantly different between recurrent and non-recurrent breast cancer patients. Metabolite set enrichment analysis (MSEA) and metabolomic pathway analysis (MetPA) showed that valine, leucine, and isoleucine degradation was the significant pathway, and volcano plot showed significant ten upregulated and two downregulated metabolites between recurrent and non-recurrent cases. Combined with receiver operating characteristic (ROC) curve and biological significance, creatine, valine, methionine, and mannose were selected for the validation phase. In this patient cohort with 41 new-recurrent vs. 248 non-recurrent breast cancer cases, followed for 720.49 person-years, compared with low level of valine, high valine level was significantly negatively associated with recurrent breast cancer (aHR: 0.36, 95% CI: 0.18–0.72, P = 0.004), especially in ER-negative and PR-negative status. There were interaction effects between valine and ER (Pinteraction = 0.006) as well as PR (Pinteraction = 0.002) on recurrent breast cancer. After Bonferroni correction, stratification effects between valine and hormone receptors were still significant. Conclusion: Our study revealed that plasma metabolites were significantly different between recurrent and non-recurrent patients, proposing therapeutic insights for breast cancer prognosis. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central South University is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Although laser Doppler imaging (LDI) accurately delineates a hypoperfused area to help target hyaluronidase treatment, laser speckle contrast imaging (LSCI) is more appropriate for assessing microvascular hemodynamics and has greater reproducibility than LDI. This study investigated the use of LSCI in the evaluation and treatment of six patients who developed vascular complications after facial dermal filler injections. Methods: The areas of vascular occlusion were accurately defined in real time by LSCI and were more precise than visual inspections or photographic evidence for guiding needling and hyaluronidase treatment. Results: All patients had achieved satisfactory outcomes as early as Day 2 of treatment and no procedure-related complications were reported after a median follow-up of 9.5 (7–37) days. Conclusion: LSCI accurately and noninvasively delineated vascular occlusions in real time among patients experiencing complications of facial dermal filler injections. Moreover, LSCI was more accurate than visual and photographic evaluations. Clinicians can use LSCI to reliably follow-up therapeutic outcomes after salvage interventions for vascular occlusions. Level of Evidence IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266. [ABSTRACT FROM AUTHOR]

Up to 50% of individuals develop post-traumatic osteoarthritis (PTOA) within 10 years following knee-joint injuries such as anterior cruciate ligament rupture or acute meniscal tear. Lower-extremity PTOA prevalence is estimated to account for ≥12% of all symptomatic osteoarthritis (OA), or approximately 5.6 million cases in the USA. With knowledge of the inciting event, it might be possible to 'catch PTOA in the act' with sensitive imaging and soluble biomarkers and thereby prevent OA sequelae by early intervention. Existing biomarker data in the joint-injury literature can provide insights into the pathogenesis and early risk trajectory related to PTOA and can help to elucidate a research agenda for preventing or slowing the onset of PTOA. Non-traumatic OA and PTOA have many clinical, radiological and genetic similarities, and efforts to understand early risk trajectories in PTOA might therefore contribute to the identification and classification of early non-traumatic OA, which is the most prevalent form of OA. Early identification of osteoarthritis (OA) prior to the development of symptoms is challenging. Post-traumatic OA provides a model for the development of OA following a defined event. In this Review, the authors describe the existing knowledge relating to the biomarkers of post-traumatic OA, which might also be applicable to the identification of early non-traumatic OA. Key points: Molecular biomarkers have potential for monitoring of the post-traumatic osteoarthritis (PTOA) trajectory, as treatment targets for the prevention of PTOA, and as indicators of the efficacy of PTOA prevention strategies. The early inflammatory response to joint injury is acutely beneficial, but thereafter contributes to PTOA development; the optimal approach and timing of anti-inflammatory interventions are yet to be determined. Biomarker expression varies with time after injury; the optimal timing and choice of biomarkers for definitive identification of a PTOA trajectory are yet to be determined. Long-term elevation of elastase after injury could identify a group at a high risk of PTOA. The early appearance of collagen biomarkers after injury, portending irreversible joint damage, suggests the possible need for very early intervention to prevent PTOA. Haemarthrosis related to injury and surgery is a risk factor for cartilage degradation that deserves more widespread recognition and early amelioration in clinical practice to prevent PTOA. [ABSTRACT FROM AUTHOR]

Objectives: To develop a multitask deep learning (DL) algorithm to automatically classify mammography imaging findings and predict the existence of extensive intraductal component (EIC) in invasive breast cancer. Methods: Mammograms with invasive breast cancers from 2010 to 2019 were downloaded for two radiologists performing image segmentation and imaging findings annotation. Images were randomly split into training, validation, and test datasets. A multitask approach was performed on the EfficientNet-B0 neural network mainly to predict EIC and classify imaging findings. Three more models were trained for comparison, including a single-task model (predicting EIC), a two-task model (predicting EIC and cell receptor status), and a three-task model (combining the abovementioned tasks). Additionally, these models were trained in a subgroup of invasive ductal carcinoma. The DeLong test was used to examine the difference in model performance. Results: This study enrolled 1459 breast cancers on 3076 images. The EIC-positive rate was 29.0%. The three-task model was the best DL model with an area under the curve (AUC) of EIC prediction of 0.758 and 0.775 at the image and breast (patient) levels, respectively. Mass was the most accurately classified imaging finding (AUC = 0.915), followed by calcifications and mass with calcifications (AUC = 0.878 and 0.824, respectively). Cell receptor status prediction was less accurate (AUC = 0.625–0.653). The multitask approach improves the model training compared to the single-task model, but without significant effects. Conclusions: A mammography-based multitask DL model can perform simultaneous imaging finding classification and EIC prediction. Clinical relevance statement: The study results demonstrated the potential of deep learning to extract more information from mammography for clinical decision-making. Key Points: • Extensive intraductal component (EIC) is an independent risk factor of local tumor recurrence after breast-conserving surgery. • A mammography-based deep learning model was trained to predict extensive intraductal component close to radiologists' reading. • The developed multitask deep learning model could perform simultaneous imaging finding classification and extensive intraductal component prediction. [ABSTRACT FROM AUTHOR]

Gamma (γ)-ray irradiation is one of the important modern breeding methods. Gamma-ray irradiation can affect the growth rate and other characteristics of plants. Plant growth rate is crucial for plants. In horticultural crops, the growth rate of plants is closely related to the growth of leaves and flowering time, both of which have important ornamental value. In this study, 60Co-γ-ray was used to treat P. equestris plants. After irradiation, the plant's leaf growth rate increased, and sugar content and antioxidant enzyme activity increased. Therefore, we used RNA-seq technology to analyze the differential gene expression and pathways of control leaves and irradiated leaves. Through transcriptome analysis, we investigated the reasons for the rapid growth of P. equestris leaves after irradiation. In the analysis, genes related to cell wall relaxation and glucose metabolism showed differential expression. In addition, the expression level of genes encoding ROS scavenging enzyme synthesis regulatory genes increased after irradiation. We identified two genes related to P. equestris leaf growth using VIGS technology: PeNGA and PeEXPA10. The expression of PeEXPA10, a gene related to cell wall expansion, was down-regulated, cell wall expansion ability decreased, cell size decreased, and leaf growth rate slowed down. The TCP-NGATHA (NGA) molecular regulatory module plays a crucial role in cell proliferation. When the expression of the PeNGA gene decreases, the leaf growth rate increases, and the number of cells increases. After irradiation, PeNGA and PeEXPA10 affect the growth of P. equestris leaves by influencing cell proliferation and cell expansion, respectively. In addition, many genes in the plant hormone signaling pathway show differential expression after irradiation, indicating the crucial role of plant hormones in plant leaf growth. This provides a theoretical basis for future research on leaf development and biological breeding. [ABSTRACT FROM AUTHOR]

Opinion statement: Acute myeloid leukemia (AML) is a fatal blood malignancy. With the development of immunotherapy, particularly chimeric antigen receptor T cells (CAR-T), the treatment of AML has undergone a significant change. Despite its advantages, CAR-T still faces a number of limitations and challenges while treating AML. Finding novel targets, altering the structure of CAR to increase efficacy while lowering side effects, and using double-target CAR and logic circuits are typical examples of key to answer these problems. With the advancement of gene editing technology, gene editing of tumor cells or normal cells to create therapeutic effects has grown in popularity. Additionally, the combination of multiple drugs is routinely used to address some of the obstacles and difficulties associated with CAR-T therapy. The review's primary goal was to summarize recent strategies and developments of CAR-T therapy for AML. [ABSTRACT FROM AUTHOR]

As the high calibre candidate of lightweight and flexible solar cells, polymer solar cells (PSCs) have made tremendous progress in recent years. However, the active photovoltaic materials in PSCs are mainly synthesized by metal-mediated coupling reaction requiring harsh reaction conditions, multiple-step synthesis, and cumbersome purification, which is not cost-efficient and may bring toxicity concerns. It is not favorable to the production of photovoltaic polymers and PSC devices on a large scale, and therefore unsuitable for the PSCs industrialization. Direct arylation coupling reaction via aromatic C—H bonds activation enables the synthesis of conjugated polymers under mild conditions and simultaneously reduces synthetic steps, difficulty, and toxic reaction byproducts. This review provides an overview of the history of preparing representative photovoltaic polymers utilized in PSCs through direct arylation reactions and discusses the activity and selectivity of C—H bonds in typical building blocks under different reaction conditions. Especially, the impact of direct arylation condition on defect formation and photovoltaic performance of the photovoltaic polymers is addressed and compared with conventional Stille coupling methods. [ABSTRACT FROM AUTHOR]

Purpose: In this study, we assessed whether the overexpression of MAP3K1 promotes the proliferation, migration, and invasion of breast cancer cells, which affect the prognosis of hormone receptor (HR)–positive, human epidermal growth factor receptor 2 (HER2)–negative early stage breast cancer. Methods: Two HR-positive, HER2-negative breast cancer cell lines (MCF7 and T-47D) overexpressing MAP3K1 were transfected with two MAP3K1 short hairpin RNA plasmids (shMAP3K1 [#3] and shMAP3K1 [#5]). The proliferation, migration, and invasion of these cells were then examined. We assessed whether shMAP3K1 affects the cell cycle, levels of downstream signaling molecules (ERK, JNK, p38 MAPK, and NF-κB), and sensitivity to chemotherapeutic and hormonal agents. To assess the anti-tumor effect of MAP3K1 knockdown in the breast cancer orthotopic model, MCF7 and T-47D cells treated with or without shMAP3K1 (#3) and shMAP3K1 (#5) were inoculated into the mammary fat pads of mice. In total, 182 patients with HR-positive, HER2-negative T1 and T2 breast cancer and 0–3 nodal metastases were included. Additionally, 73 patients with T1 and T2 breast cancer and negative nodes who received adjuvant endocrine therapy alone were selected as an independent validation cohort. Results: In both cell lines, shMAP3K1 (#3) and shMAP3K1 (#5) significantly reduced cell growth, migration, and invasion by downregulating MMP-9 and by blocking the G2/M phase of the cell cycle and its regulatory molecule cyclin B1. Moreover, both shMAP3K1 (#3) and shMAP3K1 (#5) downregulated ERK-, JNK-, p38 MAPK-, and NF-κB-dependent gene transcription and enhanced the sensitivity of both cell lines to doxorubicin, docetaxel, and tamoxifen. We observed that both shMAP3K1 (#3) and shMAP3K1 (#5) inhibited tumor growth compared with that in the scrambled group of MCF7 and T-47D cell orthotopic tumors. Patients with MAP3K1 overexpression exhibited significantly poorer 10-year disease-free survival (DFS) (70.4% vs. 88.6%, p = 0.003) and overall survival (OS) (81.9% vs. 96.3%, p = 0.001) than those without MAP3K1 overexpression. Furthermore, phospho-ERK (p < 0.001) and phospho-JNK (p < 0.001) expressions were significantly associated with MAP3K1 expression, and both phospho-ERK and phospho-JNK expressions were significantly correlated with poor 10-year DFS and OS. These biological findings, including a significant association between DFS and OS, and the expressions of MAP3K1, phospho-ERK, and phospho-JNK were further validated in an independent cohort. Multivariate analysis identified MAP3K1 expression as an independent poor prognostic factor for DFS and OS. Conclusion: Our results indicate that the overexpression of MAP3K1 plays a major role in the poor prognosis of HR-positive, HER2-negative early stage breast cancer. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central South University is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The molecular mechanisms contributing to the regulation of Th17-mediated inflammation remain underexplored. We here report a SUMO-specific protease (SENP)2-mediated pathway induced in pathogenic Th17 cells that restricts the pathogenesis of inflammatory colitis. SENP2 regulates the maturation of small ubiquitin-like modifiers (SUMO) and recycles SUMO from the substrate proteins. We find higher levels of SENP2 in pathogenic Th17 cells. By deleting Senp2 in T-cell lineages in mice, we demonstrate that the lack of Senp2 exacerbates the severity of experimental colitis, which is linked to elevated levels of GM-CSF+IL-17A+ pathogenic Th17 cells and more severe dysbiosis of the intestinal microbiome. Adoptive transfer experiments demonstrate the cell-autonomous effect of Senp2 in restraining Th17 differentiation and colitis. The enzymatic activity of SENP2 is important for deSUMOylation of Smad4, which reduces Smad4 nuclear entry and Rorc expression. Our findings reveal a SENP2-mediated regulatory axis in the pathogenicity of Th17 cells. SENP2 is involved in the regulation of post-translational modification by SUMOylation of Smad4 in Th17 cells and intestinal bowel diseases, as shown by more rapid progress of inflammatory colitis in a T cell-specific Senp2 knockout mouse model. [ABSTRACT FROM AUTHOR]

Background: Reprogramming of metabolism is strongly associated with the development of cancer. However, the role of metabolic reprogramming in the remodeling of pre-metastatic niche (PMN), a key step in metastasis, is still unknown. We aimed to investigate the metabolic alternation during lung PMN formation in breast cancer. Methods: We assessed the transcriptomes and lipidomics of lung of MMTV-PyVT mice by microarray and liquid chromatography-tandem mass mass spectrometry before lung metastasis. The validation of gene or protein expressions was performed by quantitative real-time polymerase chain reaction or immunoblot and immunohistochemistry respectively. The lung fibroblasts were isolated from mice and then co-cultured with breast cancer to identify the influence of cancer on the change of lung fibroblasts in PMN. Results: We demonstrated changes in the lipid profile and several lipid metabolism genes in the lungs of breast cancer-bearing MMTV-PyVT mice before cancer spreading. The expression of ACACA (acetyl-CoA carboxylase α) was downregulated in the lung fibroblasts, which contributed to changes in acetylation of protein's lysine residues and the synthesis of fatty acid. The downregulation of ACACA in lung fibroblasts triggered a senescent and inflammatory phenotypic shift of lung fibroblasts in both in vivo and in vitro models. The senescence-associated secretory phenotype of lung fibroblasts enabled the recruitment of immunosuppressive granulocytic myeloid-derived suppressor cells into the lungs through the production of CXCL1 in the lungs. Knock-in of ACACA prevented lung metastasis in the MMTV-PyVT mouse model, further supporting that ACACA was involved in the remodeling of the lung PMN. Conclusions: Taken together, these data revealed a mechanism by which ACACA downregulation directed the formation of an immunosuppressive lung PMN in breast cancer. [ABSTRACT FROM AUTHOR]

The determination of sudden cardiac death (SCD) is one of the difficult tasks in the forensic practice, especially in the absence of specific morphological changes in the autopsies and histological investigations. In this study, we combined the metabolic characteristics from corpse specimens of cardiac blood and cardiac muscle to predict SCD. Firstly, ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry (UPLC-HRMS)–based untargeted metabolomics was applied to obtain the metabolomic profiles of the specimens, and 18 and 16 differential metabolites were identified in the cardiac blood and cardiac muscle from the corpses of those who died of SCD, respectively. Several possible metabolic pathways were proposed to explain these metabolic alterations, including the metabolism of energy, amino acids, and lipids. Then, we validated the capability of these combinations of differential metabolites to distinguish between SCD and non-SCD through multiple machine learning algorithms. The results showed that stacking model integrated differential metabolites featured from the specimens showed the best performance with 92.31% accuracy, 93.08% precision, 92.31% recall, 91.96% F1 score, and 0.92 AUC. Our results revealed that the SCD metabolic signature identified by metabolomics and ensemble learning in cardiac blood and cardiac muscle has potential in SCD post-mortem diagnosis and metabolic mechanism investigations. [ABSTRACT FROM AUTHOR]

This paper investigates the collaborative design problem aiming to achieve state-constrained bipartite tracking of the interconnected robotic systems (IRSs) with prescribed performance. In practical applications, the physical limitations of the robots are inevitable. Besides, it is difficult to ensure that the target trajectory is known for each robot of the IRSs in advance. Thus, it is important to follow the target trajectory and meanwhile obey the state constraint being generated from the physical limitations and the external environment of the IRSs. To this end, we propose a new hierarchical state-constrained estimator-based control framework with the characteristics of low computation complexity and high task adaptability. With limited accessibility of the target trajectory, we newly present the estimator to observe it at each time interval through the interconnections among the robots. The state constraint is never violated throughout the convergence process by using the presented control algorithm. The theoretical proof and simulation results are presented to validate the feasibility of the control framework. [ABSTRACT FROM AUTHOR]

Key message: Analysis of the flower color formation mechanism of 'Rhapsody in Blue' by BF and WF transcriptomes reveals that RhF3'H and RhGT74F2 play a key role in flower color formation. Rosa hybrida has colorful flowers and a high ornamental value. Although rose flowers have a wide range of colors, no blue roses exist in nature, and the reason for this is unclear. In this study, the blue-purple petals (BF) of the rose variety 'Rhapsody in Blue' and the white petals (WF) of its natural mutant were subjected to transcriptome analysis to find genes related to the formation of the blue-purple color. The results showed that the anthocyanin content was significantly higher in BF than in WF. A total of 1077 differentially expressed genes (DEGs) were detected by RNA-Seq analysis, of which 555 were up-regulated and 522 were down-regulated in the WF vs. BF petals. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses of the DEGs revealed that a single gene up-regulated in BF was related to multiple metabolic pathways including metabolic process, cellular process, protein-containing complex, etc. Additionally, the transcript levels of most of the structural genes related to anthocyanin synthesis were significantly higher in BF than in WF. Selected genes were analyzed by qRT-PCR and the results were highly consistent with the RNA-Seq results. The functions of RhF3'H and RhGT74F2 were verified by transient overexpression analyses, and the results confirmed that both affect the accumulation of anthocyanins in 'Rhapsody in Blue'. We have obtained comprehensive transcriptome data for the rose variety 'Rhapsody in Blue'. Our results provide new insights into the mechanisms underlying rose color formation and even blue rose formation. [ABSTRACT FROM AUTHOR]

Landscape structures drive biogeographic patterns and population connectivity of animals distributed across diverse biotopes. Here, we provide a fresh insight on the impact of five landscape types in East Asia on the phylogeography and acoustic variability of the widespread Mongolian Toad, Strauchbufo raddei. For the first time, we reconstructed the biogeography of S. raddei over the species' entire range throughout East Asia (N = 293; assembled up to 2,613 bp of concatenated CR-COI-12S rRNA-16S rRNA) using fossil-based molecular dating and genetic connectivity assessments. In addition, we addressed past population dynamics in relation to landscape types, and geographic variations in release calls for the clades occurring in the steppes of northern Mongolia and the Amur River basin (N = 147). Our results recovered two separate ancestors of S. raddei in East Asia, supporting a basal split between the northeastern and southern lineages in the Middle Miocene, c. 9.48–13.77 Mya. Ancestral range estimates suggested a Late Miocene radiation within the northeastern lineage, likely due to aridity-induced vicariance and dispersal from the central Asian steppes, c. 7.89 (5.25–11.50) Mya. The southern lineage emerged subsequently from glacial refugia, c. 6.84 (3.48–2.63) Mya, expanding northward and crossing the Gobi Desert and current-day Mongolia, c. 2.60 (1.15–3.72) Mya. At the exception of the pre-Tibetan Plateau clade, our reconstruction of migration trajectories highlighted the presence of effective gene flow across other landscapes, notably among the central and northeastern Chinese clades in the habitats defined as steppe, river basin and canyon. Significant variation in release calls between the clades in northern Mongolia and the Amur River Basin reflected the isolation between the two clades, and supported the presence of a northern refugium and post-glacial expansion of the southern lineage into northwestern Mongolia. In contrast with prior studies, our finding indicates that release calls can reflect phylogeographic patterns. [ABSTRACT FROM AUTHOR]

Objective: Successful application of deep machine learning could reduce time-consuming and labor-intensive clinical work of calculating the amount of radiographic bone loss (RBL) in diagnosing and treatment planning for periodontitis. This study aimed to test the accuracy of RBL classification by machine learning. Materials and methods: A total of 236 patients with standardized full mouth radiographs were included. Each tooth from the periapical films was evaluated by three calibrated periodontists for categorization of RBL and radiographic defect morphology. Each image was pre-processed and augmented to ensure proper data balancing without data pollution, then a novel multitasking InceptionV3 model was applied. Results: The model demonstrated an average accuracy of 0.87 ± 0.01 in the categorization of mild (< 15%) or severe (≥ 15%) bone loss with fivefold cross-validation. Sensitivity, specificity, positive predictive, and negative predictive values of the model were 0.86 ± 0.03, 0.88 ± 0.03, 0.88 ± 0.03, and 0.86 ± 0.02, respectively. Conclusions: Application of deep machine learning for the detection of alveolar bone loss yielded promising results in this study. Additional data would be beneficial to enhance model construction and enable better machine learning performance for clinical implementation. Clinical relevance: Higher accuracy of radiographic bone loss classification by machine learning can be achieved with more clinical data and proper model construction for valuable clinical application. [ABSTRACT FROM AUTHOR]

Background: Smoking behavior is influenced by multiple genes, including the bitter taste gene TAS2R38. It has been reported that the correlation between TAS2R38 and smoking behavior has ethnicity-based differences. However, the TAS2R38 status in Chinese smokers is still unclear. Objective: This study aims to investigate the possible relationship between genetic variations in TAS2R38 (A49P, V262A and I296V) and smoking behaviors in the Han Chinese population. Methods: The haplotype analyses were performed and smoking behavior questionnaire was completed by 1271 individuals. Genetic association analyses for smoking behavior were analyzed using chi-square test. Further, for investigating the molecular mechanism of TAS2R38 variants effect on smoking behavior, we conducted TAS2R38-PAV and TAS2R38-AVI expression plasmids and tested the cellular calcium assay by cigarette smoke compounds stimulus in HEK293. Results: Significant associations of genetic variants within TAS2R38 were identified with smoking behavior. We found a higher PAV/PAV frequency than AVI/AVI in moderate and high nicotine dependence (FTND ≥ 4; X2 = 4.611, 1 df, p = 0.032) and strong cigarette smoke flavor intensity preference (X2 = 4.5383, 1 df, p = 0.033) in participants. Furthermore, in the in vitro cellular calcium assay, total particle matter (TPM), N-formylnornicotine and cotinine, existing in cigarette smoke, activated TAS2R38-PAV but not TAS2R38-AVI-transfected cells. Conclusion: Our data highlights that genetic variations in TAS2R38 are related to smoking behavior, especially nicotine dependence and cigarette smoke flavor intensity preference. Our findings may encourage further consideration of the taste process to identify individuals susceptible to nicotine dependence, particularly Han Chinese smokers. [ABSTRACT FROM AUTHOR]

The tumor microenvironment represents one of the main obstacles in breast cancer treatment owing to the presence of heterogeneous stromal cells, such as adipose-derived stem cells (ADSCs), that may interact with breast cancer cells and promote cancer development. Resistin is an adipocytokine associated with adverse breast cancer progression; however, its underlying mechanisms in the context of the breast tumor microenvironment remain largely unidentified. Here, we utilized a transwell co-culture model containing patient-derived ADSCs and breast cancer cell lines to investigate their potential interaction, and observed that breast cancer cells co-cultured with resistin-treated ADSCs (R-ADSCs) showed enhanced cancer cell growth and metastatic ability. Screening by proteome arrays revealed that C-X-C motif chemokine ligand 5 (CXCL5) was released in the conditioned medium of the co-culture system, and phosphorylated ERK was increased in breast cancer cells after co-culture with R-ADSCs. Breast cancer cells treated with the recombinant proteins of CXCL5 showed similarly enhanced cell migration and invasion ability as occurred in the co-culture model, whereas application of neutralizing antibodies against CXCL5 reversed these phenomena. The orthotopic xenograft in mice by breast cancer cells after co-culture with R-ADSCs had a larger tumor growth and more CXCL5 expression than control. In addition, clinical analysis revealed a positive correlation between the expression of resistin and CXCL5 in both tumor tissues and serum specimens of breast cancer patients. The current study suggests that resistin-stimulated ADSCs may interact with breast cancer cells in the tumor microenvironment via CXCL5 secretion, leading to breast cancer cell malignancy. [ABSTRACT FROM AUTHOR]

This paper studies the task-space predefined-time time-varying formation tracking (TVFT) problem in networked heterogeneous Euler–Lagrange systems (NHELSs) subject to parametric uncertainties and external disturbances. A novel hierarchical predefined-time control algorithm based on the use of non-singular terminal sliding mode control method is proposed, which can achieve the TVFT with digraphs in a predefined time. In this way, the settling time can be predetermined arbitrarily in advance as a control parameter. By virtue of the Lyapunov stability and the nearest neighbor-interactions rules, some sufficient criteria for realizing the task-space predefined-time TVFT of the NHELSs are obtained. Eventually, numerical simulation results are provided to demonstrate the effectiveness of the provided results. [ABSTRACT FROM AUTHOR]

Background: Human leukocyte antigen (HLA) genes play critical roles in immune surveillance, an important defence against tumors. Imputing HLA genotypes from existing single-nucleotide polymorphism datasets is low-cost and efficient. We investigate the relevance of the major histocompatibility complex region in breast cancer susceptibility, using imputed class I and II HLA alleles, in 25,484 women of Asian ancestry. Methods: A total of 12,901 breast cancer cases and 12,583 controls from 12 case–control studies were included in our pooled analysis. HLA imputation was performed using SNP2HLA on 10,886 quality-controlled variants within the 15–55 Mb region on chromosome 6. HLA alleles (n = 175) with info scores greater than 0.8 and frequencies greater than 0.01 were included (resolution at two-digit level: 71; four-digit level: 104). We studied the associations between HLA alleles and breast cancer risk using logistic regression, adjusting for population structure and age. Associations between HLA alleles and the risk of subtypes of breast cancer (ER-positive, ER-negative, HER2-positive, HER2-negative, early-stage, and late-stage) were examined. Results: We did not observe associations between any HLA allele and breast cancer risk at P < 5e−8; the smallest p value was observed for HLA-C*12:03 (OR = 1.29, P = 1.08e−3). Ninety-five percent of the effect sizes (OR) observed were between 0.90 and 1.23. Similar results were observed when different subtypes of breast cancer were studied (95% of ORs were between 0.85 and 1.18). Conclusions: No imputed HLA allele was associated with breast cancer risk in our large Asian study. Direct measurement of HLA gene expressions may be required to further explore the associations between HLA genes and breast cancer risk. [ABSTRACT FROM AUTHOR]

This paper investigates the predefined-time time-varying formation tracking problem of the networked autonomous surface vehicles with the external disturbance and without model information. For addressing such a complicated issue, a novel model-free integrated algorithm without velocity measurement is newly designed, which consists of the distributed predefined-time estimator algorithm, the predefined-time extended state observer, and the predefined-time local sliding mode controller. Specifically, the distributed predefined-time estimator is designed based on the time-regulator function such that each vehicle can obtain the virtual leader's information indirectly. The predefined-time extended state observer is utilized to observe the external disturbance, the unmodelled dynamics, and the velocity states through a new parameter design method. Further, the local predefined-time sliding mode controller is constructed based on the above algorithms to address the considered control problem in a velocity- and model-free manner. Finally, numerical simulations have been performed to verify the main results. [ABSTRACT FROM AUTHOR]

This paper develops a hierarchical nonlinear model predictive control (MPC) algorithm for the cooperative control of vehicle-to-vehicle (V2V) networks. In the hierarchical algorithm, an estimator is proposed as a single layer, namely, the estimated layer for generating sub-targets with local physical constraints. Then, based on an augmented simplified vehicle model, a nonlinear MPC technique is newly presented in the local layer for planning the desired trajectory with its optimization solved by a continuation/generalized minimal residual (C/GMRES) method. Note that, by considering the error components between the planned trajectory and the measured positions, a controller with a two-loop structure is adopted to improve tracking performances. Therefore, the control objective is obtained, namely, the vehicle platoon in the desired path is generated and the collisions among vehicles are avoided. The simulation results with comparisons are finally given to illustrate the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

Global warming is the main cause for the rise of both global temperatures and sea-level, both major variables threatening biodiversity. Rising temperatures threaten to breach the thermal limits of organisms while rising sea-level threatens the osmotic balance of coastal animals through habitat salinization. However, variations in thermal tolerance under different salinity stresses have not yet been thoroughly studied. In this study, we assessed the critical thermal maxima (CTmax) of amphibian tadpoles in different salinity conditions. We collected tadpoles of Duttaphrynus melanostictus, Fejervarya limnocharis and Microhyla fissipes from coastal areas and housed them in freshwater, low, and high salinity treatments for 7 days of acclimation. The CTmax, survival rate, and development rate of tadpoles in high salinity treatments were significantly lower than that of the two other treatments. Our results indicate that physiological performances and heat tolerances of tadpoles are negatively affected by salinization. Maximum entropy models showed that CTmax and sea-level rise are predicted to negatively affect the distribution of the three focal species. The present results suggest that global warming can lead to negative dual-impacts on coastal animals because of reduced thermal tolerances at elevated salinity. The impacts of global warming on anurans in coastal areas and other habitats impacted by salinization may be more severe than predicted and it is likely to cause similar dual-impacts on other ectotherms. [ABSTRACT FROM AUTHOR]

Proper utilization of lower cost waste materials and industrial by-products for subgrade filling soil stabilization is an avenue of resource conservation and environmental protection. In this study, red Pisha sandstone (RPS) and carbide slag (CS) were selected to stabilize silty clay. The improvement effects of RPS–CS-stabilized soil with different admixture contents were evaluated through strength and durability tests. In addition, the mechanism of the improvement was investigated. The results indicate that the triaxial compressive strength of silty clay stabilized with 15 wt.% RPS and 15 wt.% CS was 81–136% times that of the unstabilized silty clay. After 20 freeze–thaw cycles, the strength loss ratio was 0.4–4.7% and the compression coefficient increased from 0.053 to 0.069 MPa−1. More sand-size particles are beneficial to the adequate agglomeration and hydration reactions of RPS and CS. Large amounts of small rounded and plate-like calcium silicate hydrates (C–S–H gels) filled the soil's pores and the number of isolated pore fractures in the samples decreased, which was responsible for the excellent mechanical properties of the RPS–CS-stabilized silty clay. The results of this study provide a reference for the utilization of red Pisha sandstone and carbide slag as sustainable stabilizers in embankment applications in seasonally frozen regions. [ABSTRACT FROM AUTHOR]

The aryl hydrocarbon receptor (AhR) is a ligand-binding protein that responds to environmental aromatic hydrocarbons and stimulates the transcription of downstream phase I enzyme–related genes by binding the cis element of dioxin-responsive elements (DREs)/xenobiotic-responsive elements. Dimethyl sulfoxide (DMSO) is a well-known organic solvent that is often used to dissolve phase I reagents in toxicology and oxidative stress research experiments. In the current study, we discovered that 0.1% DMSO significantly induced the activation of the AhR promoter via DREs and produced reactive oxygen species, which induced apoptosis in mouse embryonic fibroblasts (MEFs). Moreover, Jun dimerization protein 2 (Jdp2) was found to be required for activation of the AhR promoter in response to DMSO. Coimmunoprecipitation and chromatin immunoprecipitation studies demonstrated that the phase I–dependent transcription factors, AhR and the AhR nuclear translocator, and phase II–dependent transcription factors such as nuclear factor (erythroid-derived 2)–like 2 (Nrf2) integrated into DRE sites together with Jdp2 to form an activation complex to increase AhR promoter activity in response to DMSO in MEFs. Our findings provide evidence for the functional role of Jdp2 in controlling the AhR gene via Nrf2 and provide insights into how Jdp2 contributes to the regulation of ROS production and the cell spreading and apoptosis produced by the ligand DMSO in MEFs. [ABSTRACT FROM AUTHOR]

The era of big data brings opportunities and challenges to developing new statistical methods and models to evaluate social programs or economic policies or interventions. This paper provides a comprehensive review on some recent advances in statistical methodologies and models to evaluate programs with high-dimensional data. In particular, four kinds of methods for making valid statistical inferences for treatment effects in high dimensions are addressed. The first one is the so-called doubly robust type estimation, which models the outcome regression and propensity score functions simultaneously. The second one is the covariate balance method to construct the treatment effect estimators. The third one is the sufficient dimension reduction approach for causal inferences. The last one is the machine learning procedure directly or indirectly to make statistical inferences to treatment effect. In such a way, some of these methods and models are closely related to the de-biased Lasso type methods for the regression model with high dimensions in the statistical literature. Finally, some future research topics are also discussed. [ABSTRACT FROM AUTHOR]

The association between phthalate exposure and breast cancer remains controversial. We performed a prospective patient cohort design to explore the interaction between creatinine-corrected urinary phthalate metabolites and hormone receptors as well as body mass index (BMI) on recurrent breast cancer. In this follow-up study, 636 female breast cancer patients and 45 new recurrent cases diagnosed for a total of 1576.68 person-years of follow-up were recruited. Mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP) was negatively associated with breast cancer recurrence, with adjusted hazard ratio (aHR) 3rd vs. 1st quartile of 0.15 (95% CI 0.04–0.51). The MEOHP presented as a non-monotonic dose–response (NMDR) curve, being U-shaped. In the stratification of hormone receptors, MEOHP still exhibited a U-shaped dose–response curve. The third quartile of MEOHP showed significant lowest recurrent risk in the status of ER-positive (aHR 0.18, 95% CI 0.05–0.66), PR-negative (aHR 0.14, 95% CI 0.03–0.63), and HER2-negative (aHR 0.24, 95% CI 0.08–0.76). Whether in BMI < 25 or in BMI ≥ 25, the third quartile of MEOHP was negatively associated with recurrent breast cancer, and there was a negative interaction on an additive scale between MEOHP and BMI (pinteraction = 0.042). The association between MEOHP and recurrent breast cancer was modified by hormone receptors and BMI. [ABSTRACT FROM AUTHOR]

The decision problems in the design and control of warehousing order picking process include layout design, storage assignment, routing, and order batching policies. Previous researches on layout design for pick-and-pass systems are not abundant. However, a pick-and-pass system is a commonly used approach because of the growth of e-commerce and the faster delivery of small and frequent orders. This paper presents an algorithm to determine the number of zones, and the number of picking bins and racks in each zones for the pick-and-pass systems such that both investment and operational costs can be minimized. A cycle time evaluation model is developed and incorporated into the proposed algorithm to aid a warehouse designer to quickly evaluate design alternatives for warehouse configurations. The result indicates that the cycle time evaluation model appears to be sufficiently accurate for practical purpose and the optimal layout can be determined by the proposed algorithm. [ABSTRACT FROM AUTHOR]

Taking into account the spatial diffusion effect, this paper deals with the stability problem of genetic regulatory networks with both time-varying discrete delays (DDs) and distributed delays (DTDs). By virtue of the theories of delayed partial differential equation and Lyapunov stability, new algebraic conditions are established to guarantee the global exponential stability of the genetic regulatory networks with spatial diffusion (SDGRNs) with time-varying hybrid delays. The obtained conditions are generalized and easily calculated based on the system parameters. Besides, some extended results are presented for SDGRNs without diffusion effect or DTDs. Finally, the effectiveness and feasibility of the theoretical results are illustrated by two numerical examples and the corresponding simulation results. [ABSTRACT FROM AUTHOR]

Excessive glutamate leading to excitotoxicity worsens brain damage after SAH and contributes to long-term neurological deficits. The drug ifenprodil is a non-competitive antagonist of GluN1-GluN2B N-methyl-d-aspartate (NMDA) receptor, which mediates excitotoxic damage in vitro and in vivo. Here, we show that cerebrospinal fluid (CSF) glutamate level within 48 h was significantly elevated in aSAH patients who later developed poor outcome. In rat SAH model, ifenprodil can improve long-term sensorimotor and spatial learning deficits. Ifenprodil attenuates experimental SAH-induced neuronal death of basal cortex and hippocampal CA1 area, cellular and mitochondrial Ca2+ overload of basal cortex, blood-brain barrier (BBB) damage, and cerebral edema of early brain injury. Using in vitro models, ifenprodil declines the high-concentration glutamate-mediated intracellular Ca2+ increase and cell apoptosis in primary cortical neurons, reduces the high-concentration glutamate-elevated endothelial permeability in human brain microvascular endothelial cell (HBMEC). Altogether, our results suggest ifenprodil improves long-term neurologic deficits through antagonizing glutamate-induced excitotoxicity. [ABSTRACT FROM AUTHOR]

In Western countries, breast cancer tends to occur in older postmenopausal women. However, in Asian countries, the proportion of younger premenopausal breast cancer patients is increasing. Increasing evidence suggests that the gut microbiota plays a critical role in breast cancer. However, studies on the gut microbiota in the context of breast cancer have mainly focused on postmenopausal breast cancer. Little is known about the gut microbiota in the context of premenopausal breast cancer. This study aimed to comprehensively explore the gut microbial profiles, diagnostic value, and functional pathways in premenopausal breast cancer patients. Here, we analyzed 267 breast cancer patients with different menopausal statuses and age-matched female controls. The α-diversity was significantly reduced in premenopausal breast cancer patients, and the β-diversity differed significantly between breast cancer patients and controls. By performing multiple analyses and classification, 14 microbial markers were identified in the different menopausal statuses of breast cancer. Bacteroides fragilis was specifically found in young women of premenopausal statuses and Klebsiella pneumoniae in older women of postmenopausal statuses. In addition, menopausal-specific microbial markers could exhibit excellent discriminatory ability in distinguishing breast cancer patients from controls. Finally, the functional pathways differed between breast cancer patients and controls. Our findings provide the first evidence that the gut microbiota in premenopausal breast cancer patients differs from that in postmenopausal breast cancer patients and shed light on menopausal-specific microbial markers for diagnosis and investigation, ultimately providing a noninvasive approach for breast cancer detection and a novel strategy for preventing premenopausal breast cancer. Breast cancer: gut microbes before and after menopause Women developing breast cancer before the menopause have less diverse gut microbe populations than their healthy peers, and significantly different gut microbial profiles than postmenopausal breast cancer patients. There is increasing evidence of a link between gut microbes and breast cancer, but most studies have focused on women after the menopause. The incidence of breast cancer in premenopausal women is increasing, especially in Asia. Researchers in Taiwan led by Chih-Po Chiang at Kaohsiung Medical University Hospital compared gut microbial populations in 267 breast cancer patients at different menopausal stages to matched controls. The results suggest that gut microbe profiling might offer a novel and noninvasive method for diagnosing and monitoring breast cancer. It may also lead to new strategies for prevention and treatment, as evidence emerges of a link between gut microbes and cancer. [ABSTRACT FROM AUTHOR]

This paper gives a class of novel predefined-time sliding mode surfaces based on the time-regulator function, forcing the states on them to approach the origin in a predefined time, which can be employed to replace the linear sliding mode surface that is used in the existing literatures focused on the predefined-time set stabilization problems such that the zero-error predefined-time stability can be achieved. In this way, the settling time is independent of the initial conditions and can be explicitly predefined as a specific control parameter. Later, such sliding mode surfaces are utilized to construct the nonsingular sliding mode control (SMC) for both uncertain second-order systems and disturbed Euler–Lagrange systems. The sufficient conditions for the proposed control schemes to guarantee the predefined-time stability, satisfactory capability of disturbance rejection, and nonsingularity of the control input are derived through systematic stability analysis. Finally, several numerical simulations are performed on generalized uncertain second-order systems and 2-DOF (degree of freedom) robot manipulator to show the effectiveness and the performance of the presented control schemes. [ABSTRACT FROM AUTHOR]

Whole-genome doubling (WGD) is an early macro-evolutionary event in tumorigenesis, involving the doubling of an entire chromosome complement. However, its impact on breast cancer subtypes remains unclear. Here, we performed a comprehensive and quantitative analysis of WGD and its influence on breast cancer subtypes in patients from Taiwan and consequently highlight the genomic association between WGD and homologous recombination deficiency (HRD). A higher manifestation of WGD was reported in triple-negative breast cancer, conferring high chromosomal instability (CIN), while HER2 + tumors exhibited early WGD events, with widely varied CIN levels, compared to luminal-type tumors. An association of higher activity of de novo indel signature 2 with WGD and HRD in Taiwanese breast cancer patients was reported. A control test between WGD and pseudo non-WGD samples was further employed to support this finding. The study provides a better comprehension of tumorigenesis in breast cancer subtypes, thus assisting in personalized treatment. Wu, Hsieh et al. analyze Taiwanese breast cancer patient samples using whole-exome sequencing to examine the heterogeneity and homogeneity in the timing and dependencies of somatic aberrations across disease subtypes. The authors focus on somatic alterations and related features that correlate with whole genome doubling, including homologous recombination deficiencies. [ABSTRACT FROM AUTHOR]

The artificial ground freezing (AGF) method has been widely used in underground engineering construction. As the main load-bearing elements of the AGF method, the strength of frozen walls is expected to play a crucial role in engineering stability. To improve the accuracy of quantitative evaluations of engineering stability, it is necessary to grasp the strength characteristics of frozen rock during service. To achieve this, the red sandstone taken from a frozen shaft project was tested via triaxial compression at different temperatures (−5°C,−10°C,−15°C,−20°C,−25°C, and −30°C). After that, a damage constitutive model with a Weibull distribution was derived to characterize the damage development of the frozen sandstone. Based on the validated model, the variation of damage degree was analyzed. The results show that the crack initiation stress, crack dilation stress, and peak strength all increase with decreasing temperature. The crack damage threshold increases as the frozen sandstone strength increases. The presented damage constitutive model can reflect the damage evolution of frozen sandstone. When the stress exceeds the crack initiation stress, the damage degree begins to increase, and it increases quickly when the stress approaches the peak strength. The model parameters can reflect the influence of negative temperatures on the strength of frozen sandstone. The crack damage threshold could be treated as an essential intrinsic property for predicting the failure process of frozen sandstones. The results can provide an important reference for the design and construction of frozen ground engineering. [ABSTRACT FROM AUTHOR]

This paper investigates the time-varying formation tracking (TVFT) problem of multiple heterogeneous Euler–Lagrange agents (MHELAs) with predefined-time convergence ability under directed interaction topology, where both the parametric uncertainties and external disturbances are taken into account. A new predefined-time hierarchical control (PTHC) algorithm is designed to solve the aforementioned challenging problem. Specifically, the TBG-based distributed estimator algorithm utilizing the time base generator (TBG) is firstly designed to estimate the states of the virtual leader in a predefined time. Besides, based on the obtained estimators, the predefined-time controller is presented to accomplish the robust time-varying formation tracking of the MHELAs in the local control layer. By employing the Lyapunov and Lagrange stability theory, the sufficient conditions for achieving the desired performance of the MHELAs are derived. Eventually, numerical simulations are performed to illustrate that the aforementioned theoretical results for MHELAs are effective. [ABSTRACT FROM AUTHOR]

Key message: Our results provide insights into heat response mechanisms among Clematis species. Overexpressing CvHSFA2 enhanced the heat resistance of yeast and silencing NbHSFA2 reduced the heat resistance of tobacco. Clematis species are commonly grown in western and Japanese gardens. Heat stress can inhibit many physiological processes mediating plant growth and development. The mechanism regulating responses to heat has been well characterized in Arabidopsis thaliana and some crops, but not in horticultural plants, including Clematis species. In this study, we found that Clematis alpina 'Stolwijk Gold' was heat-sensitive whereas Clematis vitalba and Clematis viticella 'Polish Spirit' were heat-tolerant based on the physiological analyses in heat stress. Transcriptomic profiling identified a set of heat tolerance-related genes (HTGs). Consistent with the observed phenotype in heat stress, 41.43% of the differentially expressed HTGs between heat treatment and control were down-regulated in heat-sensitive cultivar Stolwijk Gold, but only 9.80% and 20.79% of the differentially expressed HTGs in heat resistant C. vitalba and Polish Spirit, respectively. Co-expression network, protein–protein interaction network and phylogenetic analysis revealed that the genes encoding heat shock transcription factors (HSFs) and heat shock proteins (HSPs) may played an essential role in Clematis resistance to heat stress. Two clades of heat-induced CvHSFs were further identified by phylogenetic tree, motif analysis and qRT-PCR. Ultimately, we proposed that overexpressing CvHSFA2-2 could endow yeast with high temperature resistance and silencing its homologous gene NbHSFA2 reduced the heat resistance of tobacco. This study provides first insights into the diversity of the heat response mechanisms among Clematis species. [ABSTRACT FROM AUTHOR]

Long noncoding RNAs (lncRNAs) are known to regulate DNA damage response (DDR) and genome stability in proliferative cells. However, it remains unknown whether lncRNAs are involved in these vital biological processes in post-mitotic neurons. Here, we report and characterize a lncRNA, termed Brain Specific DNA-damage Related lncRNA1 (BS-DRL1), in the central nervous system. BS-DRL1 is a brain-specific lncRNA and depletion of BS-DRL1 in neurons leads to impaired DDR upon etoposide treatment in vitro. Mechanistically, BS-DRL1 interacts with HMGB1, a chromatin protein that is important for genome stability, and is essential for the assembly of HMGB1 on chromatin. BS-DRL1 mediated DDR exhibits cell-type specificity in the cortex and cerebellum in gamma-irradiated mice and BS-DRL1 knockout mice show impaired motor function and concomitant purkinje cell degeneration. Our study extends the understanding of lncRNAs in DDR and genome stability and implies a protective role of lncRNA against neurodegeneration. Long noncoding RNAs (lncRNAs) are known to regulate the DNA damage response (DDR), however their role in the brain is less well studied. Here, the authors demonstrate a neuron-specific role for Brain Specific DNA-damage Related lncRNA1 (BS-DRL1) and show BS-DRL1 modulates DDR by interacting with HMGB1 in a cell-type specific manner. [ABSTRACT FROM AUTHOR]

This paper investigates the global exponential synchronization problem of switching genetic oscillator networks with time-varying delays by using a newly-designed partial impulsive control scheme. This scheme is only required to control partial molecules of each gene node, different from the traditional pinning impulsive control scheme, in which all the molecules of the chosen nodes are assumed to be under control. Besides, both the number of controlled molecules and the impulsive strength of the presented control scheme are mode-dependent, either identical or different with respect to different topologies. Based on the Lyapunov stability theory and comparison principle, the sufficient criteria for guaranteeing the exponential synchronization of genetic oscillator networks with finite arbitrarily switching topologies are established. Finally, two illustrative examples are presented to verify the main results. [ABSTRACT FROM AUTHOR]