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Summary: Advanced glycation end products (AGEs) in diabetes can cause endothelial damage. Heparin, widely known as a recognized anticoagulant, is also a multifunctional therapeutic drug. This study investigated whether heparin could ameliorate AGEs-induced endothelial injury. Remarkably, heparin effectively attenuated this cellular damage and assumed a reparative role. Furthermore, heparin inhibited the AGEs-RAGE-NFκB axis, thereby mitigating endothelial inflammatory injury. Comprehensive proteome and knockdown experiments suggested that heparin may exert a positive influence on cell growth and further alleviate pathological damage by upregulating the expression of LYAR (cell growth-regulating nucleolar protein). Diabetic mouse model was also used to further verify the changes of endothelial tissue in diabetic state and heparin intervention. In summary, these findings demonstrate that heparin has the potential to ameliorate AGEs-induced endothelial injury, opening new avenues for exploring the expanded therapeutic roles of heparin and its potential application in the management of diabetes and its associated complications.

Construction activities discharge considerable carbon emissions, causing serious environmental problems and gaining increasing attention. For the large-scale construction area, high emission intensity, and significant carbon reduction potential, embodied carbon emissions of buildings worth special studying. However, previous studies are usually post-evaluation and ignore the influences of project, construction and management. This paper focuses on critical building materials and adopts machine learning methods to realize carbon prediction at design stage. The activity data, including critical building materials, water, and energy consumption, is analyzed and 30 influencing factors at the project, construction, and management levels are identified. Three algorithms (artificial neural network, support vector regression and extreme gradient boosting) are used to develop machine learning models. The proposed methodology is applied to 70 projects in the Yangtze River Delta region of China. Results show that the established models achieved high interpretability (R2 >0.7) and small average error (5.33%), well proving theirs feasibility. Furthermore, an automated tool is developed to assist practitioners to predict the critical materials consumption and embodied carbon emissions conveniently. The proposed operable model and practical tool can efficiently support effective adjustments and improvement to reduce carbon in construction.

Abstract This study aimed to evaluate the value of dynamic contrast‐enhanced ultrasound (CEUS) combined with dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) in predicting pathological complete response (pCR) in patients with breast cancer receiving neoadjuvant chemotherapy (NAC). Fifty‐seven female patients with breast cancer (mean age, 50.46 years; range, 32–66 years) scheduled for NAC were recruited. CEUS and DCE‐MRI were performed before and after NAC. Imaging features and their changes were compared with postoperative pathological results. After the clinical differences were balanced using propensity score matching, univariate and multiple logistic regression analyses were used to derive the characteristics independently associated with pCR. Receiver operating characteristic curve analysis was performed to assess diagnostic performance. After six to eight cycles of NAC, 24 (42.1%) patients achieved pCR, while 33 (57.9%) did not. Multivariate analysis showed that enhancement order on CEUS and DCE‐MRI before NAC, reduction in diameter and enhancement shape on CEUS, maximum diameter on DCE‐MRI, and the type of progressive dynamic contrast enhancement after NAC were independently associated with pCR after NAC. The area under the receiver operating characteristic curve for CEUS+DCE‐MRI was 0.911 (95% confidence interval, 0.826–0.997), and the specificity and positive predictive values were 87.0% and 87.5%. CEUS and DCE‐MRI have the potential for assessing the pathological response to NAC in patients with breast cancer; their combination showed the best diagnostic performance. CEUS+DCE‐MRI has proved beneficial for comprehensive assessment and personalizing treatment strategies for patients with breast cancer.

Abstract Background Melatonin (MEL), an endogenous hormone, has been widely investigated in neurological diseases. Microglia (MG), a resident immunocyte localizing in central nervous system is reported to play important functions in the animal model of temporal lobe epilepsy (TLE). Some evidence showed that MEL influenced activation of MG, but the detailed model of action that MEL plays in remains uncertain. Methods In this study, we established a model of TLE in mice by stereotactic injection of kainic acid (KA). We treated the mice with MEL. Lipopolysaccharide, ROCK2‐knockdown (ROCK‐KD) and ‐overexpression (ROCK‐OE) of lentivirus‐treated cells were used in cell experiments to simulate an in vitro inflammatory model. Results The results of electrophysiological tests showed that MEL reduced frequency and severity of seizure. The results of behavioral tests indicated MEL improved cognition, learning, and memory ability. Histological evidences demonstrated a significant reduction of neuronal death in the hippocampus. In vivo study showed that MEL changed the polarization status of MG from a proinflammatory M1 phenotype to an anti‐inflammatory M2 phenotype by inversely regulating the RhoA/ROCK signaling pathway. In cytological study, we found that MEL had a significant protective effect in LPS‐treated BV‐2 cells and ROCK‐KD cells, while the protective effect of MEL was significantly attenuated in ROCK‐OE cells. Conclusion MEL played an antiepileptic role in the KA‐induced TLE modeling mice both in behavioral and histological levels, and changed MG polarization status by regulating the RhoA/ROCK signaling pathway.

Abstract Background Epidemiological studies have confirmed that abnormal circadian rhythms are associated with tumorigenesis in breast cancer. However, few studies have investigated the pathological roles of rhythm genes in breast cancer progression. In this study, we aimed to evaluate the aberrant expression of 32 rhythm genes in breast cancer and detect the pathological roles and molecular mechanisms of the altered rhythm gene in regulating the progression of triple negative breast cancer (TNBC). Methods The aberrant expression of rhythm genes in breast cancer was screened by searching the GEPIA database and validated by using qRT-PCR and immunohistochemistry staining. Bioinformatics analysis combined with luciferase reporter experiment and chromatinimmunopercitation (ChIP) were used to investigate the molecular mechanism about aberrant expression of identified rhythm gene in breast cancer. The pathological roles of identified rhythm gene in TNBC progression was evaluated by colony formation assay, wound healing experiment, transwell assay, subcutaneous tumor formation and the mouse tail vein injection model through gain-of-function and loss-of-function strategies respectively. mRNA array, bioinformatics analysis, luciferase reporter experiment, ChIP and immunoflurescence assay were employed to investigate the key molecules and signaling pathways by which the identified rhythm gene regulating TNBC progression. Results We identified that nuclear factor interleukin 3 regulated (NFIL3) expression is significantly altered in TNBC compared with both normal breast tissues and other subtypes of breast cancer. We found that NFIL3 inhibits its own transcription, and thus, downregulated NFIL3 mRNA indicates high expression of NFIL3 protein in breast cancer. We demonstrated that NFIL3 promotes the proliferation and metastasis of TNBC cells in vitro and in vivo, and higher expression of NFIL3 is associated with poor prognosis of patients with TNBC. We further demonstrated that NFIL3 enhances the activity of NF-κB signaling. Mechanistically, we revealed that NFIL3 directly suppresses the transcription of NFKBIA, which blocks the activation of NF-κB and inhibits the progression of TNBC cells in vitro and in vivo. Moreover, we showed that enhancing NF-κB activity by repressing NFKBIA largely mimics the oncogenic effect of NFIL3 in TNBC, and anti-inflammatory strategies targeting NF-κB activity block the oncogenic roles of NFIL3 in TNBC. Conclusion NFIL3 promotes the progression of TNBC by suppressing NFKBIA transcription and then enhancing NF-κB signaling-mediated cancer-associated inflammation. This study may provide a new target for TNBC prevention and therapy. Graphical Abstract

It is worth noting that neuroinflammation is well recognized as a symptom of neurodegenerative diseases (NDs). The regulation of neuroinflammation becomes an attractive focus for innovative ND treatment technologies. There is evidence that IL-22 is associated with the development and progression of a wide assortment of NDs. For example, IL-22 can activate glial cells, causing them to generate pro-inflammatory cytokines and encourage lymphocyte infiltration in the brain. IL-22 mRNA is highly expressed in Alzheimer’s disease (AD) patients, and a high expression of IL-22 has also been detected in the brains of patients with other NDs. We examine the role of IL-22 in the development and treatment of NDs in this review, and we believe that IL-22 has therapeutic potential in these diseases.

IntroductionEarly diagnosis could lead to a cure of colorectal cancer (CRC). Since CRC is related to aging and lifestyles, we tested if the environmental information-enriched monosaccharide composite (MC) of circulating glycans could serve as an early diagnostic biomarker for CRC. Meanwhile, we evaluated its role in predicting prognosis.MethodsHPAEC-PAD was used to quantify glycan monosaccharide compositions from a total of 467 serum samples including CRC patients, colorectal adenoma (CRA) patients and healthy individuals. Two diagnostic model was constructed by logistic regression analysis. The diagnostic performance of the two models was verified in the retrospective validation group and the prospective validation group. The prognostic performance of the model was assessed by survival analysis.ResultsThe concentrations of monosaccharides in serum were significantly higher in CRA and CRC patients than in healthy individuals. Two diagnostic models were constructed: MC1 was used to distinguish between healthy individuals and CRC; MC2 was used to distinguish between healthy individuals and CRA. Area under receptor operating characteristic curve (AUC) of MC2 and MC1 was 0.8025 and 0.9403 respectively. However, the AUC of CEA between healthy individuals and CRC was 0.7384. Moreover, in early stage of CRC (without lymph node metastasis), the positive rates of CEA and MC1 were 28% and 80%, respectively. The follow-up data showed that the increased MC1 value was associated with poor survival in patients with CRC (p=0.0010, HR=5.30).DiscussionThe MC1 model is superior to CEA in the diagnosis of CRC, especially in the early diagnosis. MC1 can be used for predicting prognosis of CRC patients, and elevated MC1 values indicate poor survival.

When encountering crisis events, systems, organizations, and people must react and handle these unpredictable events. Under these circumstances, important social functions and infrastructures must be restored or adapted as quickly as possible. This capacity refers to resilience. Although considerable research has been conducted on the resilience of infrastructure systems over the past years, a critical review of these studies remains lacking. Therefore, this study aims to bridge the knowledge gap by presenting a comprehensive review of infrastructure research conducted in the past decade, namely, from 2011 to 2021. On the basis of a systematic search, this study identified 222 journal articles investigating infrastructure resilience. A review of the identified papers revealed five research streams in the area of infrastructure resilience (IR), namely, the assessment of infrastructure resilience, improvement of infrastructure resilience, conceptualizing infrastructure resilience from various perspectives, factors influencing infrastructure resilience, and the prediction of infrastructure resilience. This study also presented some directions that future research can pursue. These directions include analyzing factors influencing infrastructure resilience based on simulation, assessing the resilience of green infrastructure, improving the resilience of interdependent infrastructure, and predicting the resilience of infrastructure based on empirical research.

Abstract The Spectacled Fulvetta (Fulvetta ruficapilla) is the type species of Fulvetta, an evolutionarily distinct group whose species show a high degree of sympatry in distribution and phenotypic convergence. To pave the way for insights into their adaptive evolution and speciation, we have assembled the first high quality reference genome for F. ruficapilla using high-fidelity (HiFi) long-read and Hi-C sequencing technologies. The resulting assembly spans a total of ~1.21 Gb with a contig N50 of 18.8 Mb and scaffold N50 of 75.9 Mb, and has a BUSCO completeness of 97.0%. The quality assessment suggests a high standard in base accuracy, continuity, and completeness of the assembly, comparable or close to that of Vertebrate Genomes Project. On this basis, we have annotated 23,774 protein-coding genes, of which 18,832 are functionally identified. The availability of this high-quality genome provides a solid foundation for the future studies of evolution and local adaptation in birds.

We reconstruct the phenotype of Balto, the heroic sled dog renowned for transporting diphtheria antitoxin to Nome, Alaska, in 1925, using evolutionary constraint estimates from the Zoonomia alignment of 240 mammals and 682 genomes from dogs and wolves of the 21st century. Balto shares just part of his diverse ancestry with the eponymous Siberian husky breed. Balto's genotype predicts a combination of coat features atypical for modern sled dog breeds, and a slightly smaller stature. He had enhanced starch digestion compared with Greenland sled dogs and a compendium of derived homozygous coding variants at constrained positions in genes connected to bone and skin development. We propose that Balto's population of origin, which was less inbred and genetically healthier than that of modern breeds, was adapted to the extreme environment of 1920s Alaska.

Steller's sea cow, an extinct sirenian and one of the largest Quaternary mammals, was described by Georg Steller in 1741 and eradicated by humans within 27 years. Here, we complement Steller's descriptions with paleogenomic data from 12 individuals. We identified convergent evolution between Steller's sea cow and cetaceans but not extant sirenians, suggesting a role of several genes in adaptation to cold aquatic (or marine) environments. Among these are inactivations of lipoxygenase genes, which in humans and mouse models cause ichthyosis, a skin disease characterized by a thick, hyperkeratotic epidermis that recapitulates Steller's sea cows' reportedly bark-like skin. We also found that Steller's sea cows' abundance was continuously declining for tens of thousands of years before their description, implying that environmental changes also contributed to their extinction.

The gray wolf (Canis lupus) is among the few large carnivores that survived the Late Pleistocene megafaunal extinctions. Thanks to their complex history of admixture and extensive geographic range, the number of gray wolf subspecies and their phylogenetic relationships remain poorly understood. Here, we perform whole-genome sequencing of a gray wolf collected from peninsular India that was phenotypically distinct from gray wolves outside India. Genomic analyses reveal that the Indian gray wolf is an evolutionarily distinct lineage that diverged from other extant gray wolf lineages ∼110 thousand years ago. Demographic analyses suggest that the Indian wolf population declined continuously decline since separating from other gray wolves and, today, has exceptionally low genetic diversity. We also find evidence for pervasive and mosaic gene flow between the Indian wolf and African canids including African wolf, Ethiopian wolf, and African wild dog despite their current geographical separation. Our results support the hypothesis that the Indian subcontinent was a Pleistocene refugium and center of diversification and further highlight the complex history of gene flow that characterized the evolution of gray wolves.