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MicroRNA (miRNA) has garnered considerable attention due to its diagnostic capabilities, such as in hypoxic cognitive impairment and cancers. However, the existing miRNA detection methods are commonly criticized for the drawbacks of low sensitivity and false-positive detection derived from interfering molecules. Here, we provide a novel, sensitive and portable method for miRNA detection by combining target identification based cyclization of padlocks, immobilized primer-based signal amplification and a personal glucose meter. The proposed method exhibits several advantages, including precise identification of specific sites, exceptional sensitivity and instrument-free feature. These attributes hold great promise for the diagnosis and clinical investigation of various diseases, such as cancer and hypoxic cognitive impairment, enabling a deeper understanding of their pathological and physiological aspects.

Abstract The testes are the organs of gamete production and testosterone synthesis. Up to date, no model system is available for mammalian testicular development, and only few studies have characterized the mouse testis transcriptome from no more than three postnatal ages. To describe the transcriptome landscape of the developing mouse testis and identify the potential molecular mechanisms underlying testis maturation, we examined multiple RNA-seq data of mouse testes from 3-week-old (puberty) to 11-week-old (adult). Sperm cells appeared as expected in 5-week-old mouse testis, suggesting the proper sample collection. The principal components analysis revealed the genes from 3w to 4w clustered away from other timepoints, indicating they may be the important nodes for testicular development. The pairwise comparisons at two adjacent timepoints identified 7,612 differentially expressed genes (DEGs), resulting in 58 unique mRNA expression patterns. Enrichment analysis identified functions in tissue morphogenesis (3-4w), regulation of peptidase activity (4-5w), spermatogenesis (7-8w), and antigen processing (10-11w), suggesting distinct functions in different developmental periods. 50 hub genes and 10 gene cluster modules were identified in the testis maturation process by protein-protein interaction (PPI) network analysis, and the miRNA-lncRNA-mRNA, miRNA-circRNA-mRNA and miRNA-circRNA-lncRNA-mRNA competing endogenous RNA (ceRNA) networks were constructed. The results suggest that testis maturation is a complex developmental process modulated by various molecules, and that some potential RNA-RNA interactions may be involved in specific developmental stages. In summary, this study provides an update on the molecular basis of testis development, which may help to understand the molecular mechanisms of mouse testis development and provide guidance for mouse reproduction.

Background: Spinal cord injury (SCI) is a serious and difficult to treat traumatic disease of the central nervous system. Spinal cord injury causes a variety of detrimental effects, including neuroinflammation and ferroptosis, leading to chronic functional impairment and death. Recent studies have shown that microglia/macrophages (M/Ms) at the injury site remain primarily in the pro-inflammatory state, which is detrimental to recovery. However, information on the factors behind pro-inflammatory polarization skew in the injured spinal cord remains unclear. In this study, we found that Tumor Necrosis Factor-α(TNF-α) ablation protected after SCI by suppressing neuroinflammation and ferroptosis. Though using TNF-α knock out mice (TNF−/−), we induced downregulation of TNF-α in M/Ms and further investigated its effect on SCI outcome. In TNF−/− mice, significant behavioral improvements were observed as early as 7 days after injury. We showed that TNF-α inhibition promote injury-mediated M/Ms polarization from pro-inflammatory to anti-inflammatory phenotype in vivo. Furthermore, accumulated iron in M/Ms after SCI increased the expression of TNF-α and the population of M/Ms to pro-inflammatory phenotype. Moreover, zinc supplement reduced the secondary damage caused by iron overload. In conclusion, we found that knock out of TNF-α promotes recovery of motor function after spinal cord injury in mice by inhibiting ferroptosis and promoting the shift of macrophages to an anti-inflammatory phenotype, indicating that there is great potential for this therapy to SCI.

ABSTRACT The skin microbiome plays a pivotal role in human health by providing protective and functional benefits. Furthermore, its inherent stability and individual specificity present novel forensic applications. These aspects have sparked considerable research enthusiasm among scholars across various fields. However, the selection of specific 16S rRNA hypervariable regions for skin microbiome studies is not standardized and should be validated through extensive research tailored to different research objectives and targeted bacterial taxa. Notably, third-generation sequencing (TGS) technology leverages the full discriminatory power of the 16S gene and enables more detailed and accurate microbial community analyses. Here, we conducted full-length 16S sequencing of 141 skin microbiota samples from multiple human anatomical sites using the PacBio platform. Based on this data, we generated derived 16S sub-region data through an in silico experiment. Comparisons between the 16S full-length and the derived variable region data revealed that the former can provide superior taxonomic resolution. However, even with full 16S gene sequencing, limitations arise in achieving 100% taxonomic resolution at the species level for skin samples. Additionally, the capability to resolve high-abundance bacteria (TOP30) at the genus level remains generally consistent across different 16S variable regions. Furthermore, the V1-V3 region offers a resolution comparable with that of full-length 16S sequences, in comparison to other hypervariable regions studied. In summary, while acknowledging the benefits of full-length 16S gene analysis, we propose the targeting of specific sub-regions as a practical choice for skin microbial research, especially when balancing the accuracy of taxonomic classification with limited sequencing resources, such as the availability of only short-read sequencing or insufficient DNA.IMPORTANCESkin acts as the primary barrier to human health. Considering the different microenvironments, microbial research should be conducted separately for different skin regions. Third-generation sequencing (TGS) technology can make full use of the discriminatory power of the full-length 16S gene. However, 16S sub-regions are widely used, particularly when faced with limited sequencing resources including the availability of only short-read sequencing and insufficient DNA. Comparing the 16S full-length and the derived variable region data from five different human skin sites, we confirmed the superiority of the V1-V3 region in skin microbiota analysis. We propose the targeting of specific sub-regions as a practical choice for microbial research.

ABSTRACT: In this study, we sought to determine the effects of intestinal flora on the feed efficiency of meat ducks by evaluating the correlation between intestinal flora and residual feed intake. The F2 generation of Cherry Valley ducks × Runzhou Crested White ducks was used as the study subjects, and feed consumption being recorded from d 21 to 42. RFI was calculated based on growth performance, and 20 low RFI and 20 high RFI ducks were randomly selected to characterize the effect of RFI on growth performance. To analyze the intestinal flora affecting RFI, 16s rDNA sequencing was performed on the contents of 5 intestinal segments from the HR and LR groups, and macrogenomic sequencing was performed on the cecal contents. Feed intake, average daily feed intake, feed conversion ratio, and residual feed intake were lower in low RFI. Analysis of the intestinal flora revealed the cecum to be more highly enriched in the carbohydrate metabolism pathway and less enriched with potentially pathogenic taxa than the other assessed intestinal regions. Further analysis of the cecal microbiota identified nine significantly differentially enriched intestinal flora. In this study, we accordingly identified a basis for the mechanisms underlying the effects of the intestinal flora on meat duck feed efficiency.

Plasmid shuttle vectors are a common tool used to study yeast physiology. The majority of yeast plasmids have been optimized for Saccharomyces cerevisiae lab strain compatibility, relying on auxotrophic complementation as their selective property. We sought to construct a series of plasmid shuttle vectors to extend functionality beyond strains with auxotrophic requirements, and test compatibility across a diverse panel of yeasts. We constructed 18 plasmids which were successfully maintained by yeasts from several genera. From a panel of 24 yeast strains, these plasmids were maintained by 18 yeasts, spanning 11 species within the genera Lachancea, Metschnikowia, Pichia, Saccharomyces, and Torulaspora. Additionally, an integrated gene expression reporter was assayed for functional compatibility with the 18 strains. Plasmid-derived gene expression was observed for 13 strains, spanning five species within the Saccharomyces genus, in addition to Torulaspora delbrueckii. These results indicate that this plasmid series is broadly useful for advancements and applications within academia, biotechnology, and the food and fermentation industries for research utilizing diverse Saccharomyces and non-Saccharomyces yeasts.

High-performance automated detection methods for epilepsy play a crucial role in clinical diagnostic support. To address the challenge of effectively extracting features from epileptic EEG signals, characterized by strong spontaneity and complexity, a novel feature extraction approach based on Window Kullback-Leibler Divergence (WKLD) is proposed, coupled with discrete wavelet analysis for EEG signal feature extraction. Then, a Residual Multidimensional Taylor Network (ResMTN) classifier is applied for epilepsy state classification. Experimental results demonstrate an accuracy of 98% in classifying EEG signals during seizure and interictal periods, with both specificity and sensitivity reaching 98.18%, outperforming existing widely-used feature extraction and classification methods.

The usage of Mg–Al–Zn alloys for lithium-ion battery shell is able to achieve further lightweight of electric vehicles, and their corrosion resistance would highly determine the service life. In this work, therefore, a Y-modified AZ91 magnesium alloy (AZ91-0.5Y) was first prepared by conventional casting and following hot extrusion, and the influence of solution treatment (ST) and subsequent pre-deformation (SP) treatments on its electrochemical corrosion and stress corrosion cracking (SCC) resistance in 1 mol/L LiPF6 electrolyte were then investigated. The results indicated that the presence of large lamellar or rod-like β-Mg17Al12 phase in as-extruded AZ91-0.5Y alloy would lead to serious micro-galvanic corrosion and SCC. After solution treatment, the β-Mg17Al12 phase almost completely dissolved into Mg matrix, weakening the micro-galvanic corrosion and anodic dissolution (AD) and hydrogen embrittlement (HE) effect. Further, the subsequent pre-deformation treatment could introduce dislocation, more precipitation of Al2Y phase, massive twins and optimized texture, leading to the improved corrosion resistance and mechanical strength as well as the formation of well-integrated protective corrosion product film MgF2 with low porosity. As a result, the corrosion and SCC resistance of as-extruded, ST and SP specimens is ordered from low to high.

ABSTRACT: The bird beak is mainly functioned as feeding and attacking, and its shape has extremely important significance for survival and reproduction. In chickens, since beak shape could lead to some disadvantages including pecking and waste of feed, it is important to understand the inheritance of chicken beak shape. In the present study, we firstly established 4 indicators to describe the chicken beak shapes, including upper beak length (UL), lower beak length (LL), distance between upper and lower beak tips (DB) and upper beak curvature (BC). And then, we measured the 4 beak shape indicators as well as some production traits including body weight (BW), shank length (SL), egg weight (EW), eggshell strength (ES) of a layer breed, Rhode Island Red (RIR), in order to estimate genetic parameters of chicken beak shape. The heritabilities of UL and LL were 0.41 and 0.37, and the heritabilities of DB and BC were 0.22 and 0.21, indicating that beak shape was a highly or mediumly heritable. There were significant positive genetic and phenotypic correlations among UL, LL, and DB. And UL was positively correlated with body weight (BW18) and shank length (SL18) at 18 weeks of age in genetics, and DB was positively correlated with BC in terms of genetics and phenotype. We also found that layers of chicken cages played a role on beak shape, which could be attributed to the difference of lightness in different cage layers. By a genome-wide association study (GWAS) for the chicken UL, we identified 9 significant candidate genes associated with UL in RIR. For the variants with low minor allele frequencies (MAF

ABSTRACT: Plumage color is a characteristic trait of ducks that originates as a result of natural and artificial selection. As a conspicuous phenotypic feature, it is a breed characteristic. Previous studies have identified some genes associated with the formation of black and white plumage in ducks. However, studies on the genetic basis underlying the red plumage phenotype in ducks are limited. Here, genome-wide association analysis (GWAS) and selection signal detection (Fst, θπ ratio, and cross-population composite likelihood ratio [XP-CLR]) were conducted to identify candidate regions and genes underlying duck plumage color phenotype. Selection signal detection revealed 29 overlapping genes (including ENPP1 and ULK1) significantly associated with red plumage color in Ji'an Red ducks. ENSAPLG00000012679, ESRRG, and SPATA5 were identified as candidate genes associated with red plumage using GWAS. Selection signal detection revealed that 19 overlapping genes (including GMDS, PDIA6, and ODC1) significantly correlated with light brown plumage in Brown Tsaiya ducks. GWAS to narrow down the significant regions further revealed nine candidate genes (AKT1, ATP6V1C2, GMDS, LRP4, MAML3, PDIA6, PLD5, TMEM63B, and TSPAN8). Notably, in Brown Tsaiya ducks, GMDS, ODC1, and PDIA6 exhibit significantly differentiated allele frequencies among other feather-colored ducks, while in Ji'an Red ducks, ENSAPLG00000012679 has different allele frequency distributions compared with that in other feather-colored ducks. This study offers new insights into the variation and selection of the red plumage phenotype using GWAS and selective signals.

ABSTRACT: As a Chinese local chicken breed, Hongshan chickens have 2 kinds of tail feather phenotypes, normal and taillessness. Our previous studies showed that taillessness was a sex-linked dominant trait. Abnormal development of the tail vertebrae could be explained this phenomenon in some chicken breeds. However, the number of caudal vertebrae in rumpless Hongshan chickens was normal, so rumplessness in Hongshan chicken was not related to the development of the caudal vertebrae. Afterwards, we found that rumplessness in Hongshan was due to abnormal development of tail feather rather than abnormal development of caudal vertebrae. In order to understand the genetic foundation of the rumplessness of Hongshan chickens, we compared and reanalyzed 2 sets of data in normal and rumpless Hongshan chickens from our previous studies. By joint analysis of genome-wide selection signature analysis and genome-wide association approach, we found that 1 overlapping gene (EDIL3) and 16 peak genes (ENSGALG00000051843, ENSGALG00000053498, ENSGALG00000054800, KIF27, PTPRD, ENSGALG00000047579, ENSGALG00000041052, ARHGEF28, CAMK4, SERINC5, ENSGALG00000050776, ERCC8, MCC, ADAMTS19, ENSGALG00000053322, CHRNA8) located on the Z chromosome was associated with the rumpless trait. The results of this study furtherly revealed the molecular mechanism of the rumpless trait in Hongshan chickens, and identified the candidate genes associated with this trait. Our results will help to improve the shape of chicken tail feathers and to rise individual economic value in some specific market in China.

ABSTRACT: The age of first egg (AFE) in chicken can affect early and even life-time egg production performance to some extent, and therefore is an important economic trait that affects production efficiency. To better understand the genetic patterns of AFE and other production traits including body weight at first egg (BWA), first egg weight (FEW), and total egg number from AFE to 58 wk of age (total-EN), we recorded the production performance of 2 widely used layer breeds, white leghorn (WL) and Rhode Island Red (RIR) and estimated genetic parameters based on pedigree and production data. The results showed that the heritability of AFE in both breeds ranged from 0.4 to 0.6, and AFE showed strong positive genetic and phenotypic correlations to BWA as well as FEW, while showing strong negative genetic and phenotypic correlations with total-EN. Furtherly, by genome-wide association analysis study (GWAS), we identified 12 and 26 significant SNPs to be related to AFE in the 2-layer breeds, respectively. A total of 18 genes were identified that could affect AFE based on the significant SNP annotations obtained, but there were no gene overlapped in the 2 breeds indicating the genetic foundation of AFE could differ from breed to breed. Our results provided a deeper understanding of genetic patterns and molecular basement of AFE in different breeds and could help in the selection of egg production traits.

Yeast plays a crucial role in the fermentation industry, particularly in alcoholic beverage production, where robustness and metabolic flexibility are essential. This study aimed to investigate the stress tolerance and metabolic capabilities of seven commercial ale yeast strains under various stress conditions, including temperature, pH, osmotic pressure, glucose starvation, and ethanol concentration. Detailed growth assays and stress tolerance tests were utilized to evaluate fermentation efficiency, carbon source utilization, and stress adaptation. Significant variability was observed among the strains. ACY169 and ACY150 demonstrated high overall stress tolerance, making them suitable for high-gravity brewing and processes involving extreme temperature fluctuations. ACY10 showed robust performance under acid stress, making it ideal for sour beer production. In contrast, ACY5 exhibited limited adaptability under stress, with longer doubling times and reduced metabolic activity. The study also revealed differences in carbon source utilization, with ACY169 displaying exceptional metabolic versatility by efficiently fermenting various sugars, including glucose, fructose, maltose, and raffinose. ACY10 and ACY150 exhibited balanced fermentation profiles with high ethanol production rates, while ACY9 demonstrated the highest glucose consumption rate but lower ethanol yields and significant acidification.

Resolution of global climate models (GCMs) significantly influences their capacity to simulate extreme weather such as tropical cyclones (TCs). However, improving the GCM resolution is computationally expensive and time-consuming, making it challenging for many research organizations worldwide. Here, we develop a downscaling model, MSG-SE-GAN, based on the Generative Adversarial Networks (GAN) together with Multiscale Gradient (MSG) technique and a Squeeze-and-Excitation (SE) Net, to achieve 10-folded downscaling. GANs consist of a generator and a discriminator network that are trained adversarially, and are often used for generating new data that resembles a given dataset. MSG enables generation and discrimination of multi-scale images within a single model. Inclusion of an attention layer of SE captures better underlying spatial structure while preserving accuracy. The MSG-SE-GAN is stable and fast converging. It outperforms traditional bilinear interpolation and other deep-learning methods such as Super-Resolution Convolutional Neural Networks (SRCNN) and MSG-GAN in downscaling low-resolution meteorological data in assessment metrics and power spectral density. The MSG-SE-GAN has been used to downscale the TC-related variables in the western North Pacific in the low-resolution GCMs of HadGEM3-GC31 and EC-Earth3P, respectively. The downscaled data show highly similar TC activities to the direct outputs of the high-resolution HadGEM3-GC31 and EC-Earth3P, respectively. These results not only suggest the validity of the MSG-SE-GAN but also indicate its possible portability among low-resolution GCMs.

Situational Awareness (SA) assessment is of paramount importance in various domains, with particular significance in the military for safe aviation decision-making. It involves encompassing perception, comprehension, and projection levels in human beings. Accurate evaluation of SA statuses across these three levels is crucial for mitigating human false-positive and false-negative rates in monitoring complex scenarios in the aviation context. This study proposes a comprehensive comparative analysis by involving two types of physiological records: electroencephalogram (EEG) signals and brain electrical activity mapping (BEAM) images. These two modalities are leveraged to automate precise SA evaluation using both conventional machine learning and advanced deep learning techniques. Benchmarking experiments reveal that the BEAM-based deep learning models attain state-of-the-art performance scores of 0.955 for both SA perception and comprehension levels, respectively. Conversely, the EEG signals-based manual feature extraction, selection, and classification approach achieved a superior accuracy of 0.929 for the projection level of SA. These findings collectively highlight the potential of deploying diverse physiological records as valuable computational tools for enhancing SA evaluation throughout aviation decision-making safety.

The present study investigated the effects of Astragalus membranaceus extract (AME) on growth performance, immune response, and energy metabolism of juvenile largemouth bass (Micropterus salmoides). Seven diets containing 0%, 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, and 0.6% AME (Con, AME0.1, AME0.2, AME0.3, AME0.4, AME0.5, and AME0.6 groups) were formulated and fed to M. salmoides for 8 weeks. Final body weight (FBW), feed intake (FI), weight gain (WG), and specific growth rate (SGR) were all significantly higher in AME0.4 group than in Con group (P

Lignin is one of the most widespread organic compounds found on earth, boasting a wealth of aromatic molecules. The use of lignin feedstock for biochemical productions is of great importance for achieving “carbon neutrality.” In recent years, a strategy for lignin valorization known as the “bio-funnel” has been proposed as a means to generate a variety of commercially valuable chemicals from lignin-derived compounds. The implementation of biocatalysis and metabolic engineering techniques has substantially advanced the biotransformation of depolymerized lignin into chemicals and materials within the supply chain. In this review, we present an overview of the latest advancements in microbial upcycling of depolymerized lignin into value-added chemicals. Besides, the review provides insights into the problems facing current biological lignin valorization while proposing further research directions to improve these technologies for the extensive accomplishment of the lignin upcycling.

Background: To investigate the expression of high mobility group box B-1 (HMGB-1) in patients with colorectal cancer (CRC) and its association with clinicopathological features and prognosis in colorectal carcinoma by combining bioinformatics and clinical data analysis, and to clarify the role of HMGB-1. To examine whether HMGB-1 expression is related to the damage of the intestinal mucosal barrier, and then explore the potential HMGB-1-dependent mechanisms affecting the progression of CRC. Methods: CRC datasets of GSE12945, GSE17536, and GSE17537 from the public gene chip database were screened and downloaded. Clinical information and CRC tissue samples from patients with stage I-III CRC from the hospital were collected. Serum samples of patients were applied by enzyme-linked immunosorbent assay on HMGB-1, and were divided into high and low HMGB-1 expression, which was examined by 16S rDNA sequencing. Immunohistochemistry was performed to examine the relationship between the expression of HMGB-1 and tight junction protein, occludin, tumor necrosis factor-α, and interferon-γ. Results: Based on the Cutoff value of 10.24 ng/mL, the CRC patients were divided into high and low expression groups. In the HMGB-1H patient group, the TNM staging, overall survival, disease-free survival, recurrence, and metastasis were inferior to the HMGB-1L group. The results of 16S rDNA sequencing demonstrated that the Providencia genus was found to be enriched in the HMGB-1L group. Immunohistochemical results showed that HMGB-1 expression was negatively correlated with the expression of ZO-1 and occludin ( R = 0.035, R = 0.003, P

Spurs, which mainly appear in roosters, are protrusions near the tarsometatarsus on both sides of the calves of chickens, and are connected to the tarsometatarsus by a bony core. As a male-biased morphological characteristic, the diameter and length of spurs vary significantly between different individuals, mainly related to genetics and age. As a specific behavior of hens, egg-laying also varies greatly between individuals in terms of traits such as age at first egg (AFE), egg weight (EW), and so on. At present, there are few studies on chicken spurs. In this study, we investigated the inheritance pattern of the spur trait in roosters with different phenotypes and the correlations between spur length, body weight at 18 weeks of age (BW18), shank length at 18 weeks of age (SL18), and the egg-laying trait in hens (both hens and roosters were from the same population and were grouped according to their family). These traits related to egg production included AFE, body weight at first egg (BWA), and first egg weight (FEW). We estimated genetic parameters based on pedigree and phenotype data, and used variance analysis to calculate broad-sense heritability for correcting the parameter estimation results. The results showed that the heritability of male left and right spurs ranged from 0.6 to 0.7. There were significant positive correlations between left and right spur length, BW18, SL18, and BWA, as well as between left and right spur length and AFE. We selected 35 males with the longest spurs and 35 males with the shortest spurs in the population, and pooled them into two sets to obtain the pooled genome sequencing data. After genome-wide association and genome divergency analysis by FST, allele frequency differences (AFDs), and XPEHH methods, we identified 7 overlapping genes (CENPE, FAT1, FAM149A, MANBA, NFKB1, SORBS2, UBE2D3) and 14 peak genes (SAMD12, TSPAN5, ENSGALG00000050071, ENSGALG00000053133, ENSGALG00000050348, CNTN5, TRPC6, ENSGALG00000047655,TMSB4X, LIX1, CKB, NEBL, PRTFDC1, MLLT10) related to left and right spur length through genome-wide selection signature analysis and a genome-wide association approach. Our results identified candidate genes associated with chicken spurs, which helps to understand the genetic mechanism of this trait and carry out subsequent research around it.

Intracerebral hemorrhage (ICH) is the cerebrovascular disease with the highest disability and mortality rates, causing severe damage to the health of patients and imposing a significant socioeconomic burden. Aging stands as a foremost risk factor for ICH, with a significant escalation in ICH incidence within the elderly demographic, highlighting a close association between ICH and aging. In recent years, with the acceleration of the “aging society” trend, exploring the intricate relationship between aging and ICH has become increasingly urgent and worthy of in-depth attention. We have summarized the characteristics of ICH in the elderly, reviewing how aging influences the onset and development of ICH by examining its etiology and the mechanisms of damage via ICH. Additionally, we explored the potential impacts of ICH on accelerated aging, including its effects on cognitive abilities, quality of life, and lifespan. This review aims to reveal the connection between aging and ICH, providing new ideas and insights for future ICH research.

Background: The accuracy of decoding fine motor imagery (MI) tasks remains relatively low due to the dense distribution of active areas in the cerebral cortex. Methods: To enhance the decoding of unilateral fine MI activity in the brain, a weight-optimized EEGNet model is introduced that recognizes six types of MI for the right upper limb, namely elbow flexion/extension, wrist pronation/supination and hand opening/grasping. The model is trained with augmented electroencephalography (EEG) data to learn deep features for MI classification. To address the sensitivity issue of the initial model weights to classification performance, a genetic algorithm (GA) is employed to determine the convolution kernel parameters for each layer of the EEGNet network, followed by optimization of the network weights through backpropagation. Results: The algorithm’s performance on the three joint classification is validated through experiment, achieving an average accuracy of 87.97%. The binary classification recognition rates for elbow joint, wrist joint, and hand joint are respectively 93.92%, 90.2%, and 94.64%. Thus, the product of the two-step accuracy value is obtained as the overall capability to distinguish the six types of MI, reaching an average accuracy of 81.74%. Compared to commonly used neural networks and traditional algorithms, the proposed method outperforms and significantly reduces the average error of different subjects. Conclusions: Overall, this algorithm effectively addresses the sensitivity of network parameters to initial weights, enhances algorithm robustness and improves the overall performance of MI task classification. Moreover, the method is applicable to other EEG classification tasks; for example, emotion and object recognition.

Abstract As the Human Microbiome Project (HMP) progresses, the relationship between microbes and human health has been receiving increasing attention. A growing number of reports support the correlation between cancer and microbes. However, most studies have focused on bacteria, rather than fungal communities. In this study, we studied the alteration in lung mycobiome in patients with non-small-cell lung cancer (NSCLC) using metagenomic sequencing and qPCR. The higher fungal diversity and more complex network were observed in the patients with NSCLC. In addition, Alternaria arborescens was found as the most relevant fungus to NSCLC, and the enrichment of it in cancerous tissue was also detected. This study proposes that the changes in fungal communities may be closely related to lung cancer, and provides insights into further exploration the relationship between lung cancer and fungi.

As high temperature and heat wave have become great threats to human survival, social stability, and ecological safety, it is of great significance to master the spatial and temporal dynamic changes of temperature to prevent high temperature and heat wave risks. The meteorological station can provide accurate near-ground temperature, but only within a specific space and time. In order to meet the needs of large-scale research, spatial interpolation methods were widely used to obtain spatially continuous temperature maps. However, these methods often ignore the influence of external factors on temperature, such as land cover, height, etc., and neglect to supplement temporal-wise information. To deal with these issues, a joint spatio-temporal method is proposed to obtain dense temperature mapping from multisource remote sensing data, which combining a geographically weighted regression model and a polynomial fitting model. Besides, a heat wave risk model is also built based on the dense temperature maps and population data, in order to evaluate the heat wave risk of different areas. Accuracy evaluations and experiments have verified the effectiveness of the proposed methods. Case study on the four cities of Zhejiang Province, China have demonstrated that areas with higher degree of urbanization are often accompanied by higher heat wave risks, such as the northern part of the study area. The study also found that the heat wave risks have presented a centralized distribution and spatial autocorrelation characteristics in the study area.

The escalating thermal power density in electronic devices necessitates advanced thermal management technologies. Polymer-based materials, prized for their electrical insulation, flexibility, light weight, and strength, are extensively used in this field. However, the inherent low thermal conductivity of polymers requires enhancement for effective heat dissipation. This work proposes a novel paradigm, emphasizing ordered structures with functional units, to create triple-level, ordered, low-filler loading of multi-walled carbon nanotube (MWCNT)/poly(vinyl alcohol)(PVA) nanofibrous films. By addressing interfacial thermal resistance through –OH groups, the coupling between polymer and MWCNT is strengthened. The triple-level ordered structure comprises aligned PVA chains, aligned MWCNTs, and aligned MWCNT/PVA composite fibers. Focusing on the filler’s impact on thermal conductivity and chain orientation, the thermal transport mechanisms have been elucidated level by level. Our MWCNT/PVA composite, with lower filler loadings (10 wt.%), achieves a remarkable TC exceeding 35.4 W/(m·K), surpassing other PVA composites with filler loading below 50 wt.%.

Fat deposition is an important factor affecting meat quality and feed conversion efficiency in meat ducks. This study aims to identify key circRNAs and genes affecting abdominal fat deposition. The correlations between abdominal fat and other growth performances were analyzed in 304 F2 generation of Cherry Valley duck Runzhou Crested White ducks, and an RNA-seq analysis of abdominal fat tissues from ducks with high and low rates of abdominal fat was performed. Growth performance results showed that Abdominal fat ratio and Intramuscular fat were significantly higher in the high rates of abdominal fat (HF)group than in the low rates of abdominal fat (LF) group for ducks. RNA-seq analysis of abdominal fat tissue unveiled 85 upregulated and 72 downregulated circRNAs among the differentially expressed ones. Notably, 74 circRNAs displayed more than four-fold differential expression, constituting 47.13% of the differentially expressed genes. Functional enrichment analysis of the differentially expressed circRNA source and target genes indicated that 17 circRNAs might partake in regulating duck abdominal fat production by influencing pathways like PPAR signaling, lipid droplets, and triglyceride metabolism. Lastly, multiple circRNA-microRNA-messenger RNA interaction networks were constructed. The results of this study establish the groundwork for understanding the molecular mechanisms that regulate abdominal fat deposition in ducks, offering a theoretical reference for the selective breeding of high-quality meat-producing ducks.

Abstract Reactivation of chemotherapy-induced dormant cancer cells is the main cause of relapse and metastasis. The molecular mechanisms underlying remain to be elucidated. In this study, we introduced a cellular model that mimics the process of cisplatin responsiveness in NSCLC patients. We found that during the process of dormancy and reactivation induced by cisplatin, NSCLC cells underwent sequential EMT-MET with enrichment of cancer stem cells. The ATAC-seq combined with motif analysis revealed that OCT4-SOX2-TCF-NANOG motifs were associated with the enrichment of cancer stem cells induced by chemotherapy. Gene expression profiling suggested a dynamic regulatory mechanism during the process of enrichment of cancer stem cells, where Nanog showed upregulation in the dormant state and SOX2 showed upregulation in the reactivated state. Further, we showed that EphB1 and p-EphB1 showed dynamic expression in the process of cancer cell dormancy and reactivation, where the expression profiles of EphB1 and p-EphB1 showed negatively correlated. In the dormant EMT cells which showed disrupted cell-cell contacts, ligand-independent EphB1 promoted entry of lung cancer cells into dormancy through activating p-p38 and downregulating E-cadherin. On the contrary, in the state of MET, in which cell-cell adhesion was recovered, interactions of EphB1 and ligand EphrinB2 in trans promoted the stemness of cancer cells through upregulating Nanog and Sox2. In conclusion, lung cancer stem cells were enriched during the process of cellular response to chemotherapy. EphB1 cis- and trans- signalings function in the dormant and reactivated state of lung cancer cells respectively. It may provide a therapeutic strategy that target the evolution process of cancer cells induced by chemotherapy.

A green roof can modify the roof outer surface temperature (Tr) to influence indoor air temperature (Ti). Green roof design and roof-slab thermal insulation jointly determine the coupled-roof system’s thermal performance. This study investigated their joint effects on subtropical winter warming, which were seldom investigated. Custom-built houses without (bare roof) and with a 20-cm soil layer at circa 20% moisture content (soil roof) provided experiment plots to collect field data. The measured data tested the corrected finite element analysis model and simulated the combined influence of soil cover (properties kept constant) and a gradation of roof-slab thermal insulation on Tiin the unsteady heat transfer mode. Such multiple-factor and complex spatiotemporal studies are difficult using only field experiments and measurements. Average Tiwas raised by 0.44 °C on a typical winter day, bringing 4.55% energy saving to indoor-heating budget. With poor roof-slab insulation, the soil roof significantly retained indoor warmth. With improved roof-slab insulation, the soil roof’s influence on Tiwaned. A tipping point at 0.95 W/(m K) thermal conductivity signified a maximum threshold above which the green roof would not retain additional indoor heat. An upper threshold of thermal insulation at 0.35–0.05 W/(m K) was found, above which further insulation increase would not keep additional indoor warmth. Subtropical winter indoor warming by green roof was verified via two heat preservation mechanisms: retaining indoor heat to bring passive warming and delivering heat indoors to bring active warming. They were triggered by slightly warmed and notably warmed green-roof soil, respectively. The results ascertained quantitatively the complementary thermal role of green roof and roof slab. The findings can optimize the subtropical green-roof design and achieve winter indoor warming and thermal comfort.

Abstract Fat storage-inducing transmembrane proteins (FITMs) were initially identified in 2007 as members of a conserved endoplasmic reticulum (ER) resident transmembrane protein gene family, and were found to be involved in lipid droplet (LD) formation. Recently, several studies have further demonstrated that the ability of FITMs to directly bind to triglyceride and diacylglycerol, and the diphosphatase activity of hydrolyzing fatty acyl-CoA, might enable FITMs to maintain the formation of lipid droplets, engage in lipid metabolism, and protect against cellular stress. Based on the distribution of FITMs in tissues and their important roles in lipid droplet biology and lipid metabolism, it was discovered that FITMs were closely related to muscle development, adipocyte differentiation, and energy metabolism. Accordingly, the abnormal expression of FITMs was not only associated with type 2 diabetes and lipodystrophy, but also with cardiac disease and several types of cancer. This study reviews the structure, distribution, expression regulation, and functionality of FITMs and their potential relationships with various metabolic diseases, hoping to provide inspiration for fruitful research directions and applications of FITM proteins. Moreover, this review will provide an important theoretical basis for the application of FITMs in the diagnosis and treatment of related diseases.

Abstract Solid polymer electrolytes (SPEs) are still being considered as a candidate to replace liquid electrolytes for high‐safety and flexible lithium batteries due to their superiorities including light‐weight, good flexibility, and shape versatility. However, inefficient ion transportation of linear polymer electrolytes is still the biggest challenge. To improve ion transport capacity, developing novel polymer electrolytes are supposed to be an effective strategy. Nonlinear topological structures such as hyperbranched, star‐shaped, comb‐like, and brush‐like types have highly branched features. Compared with linear polymer electrolytes, topological polymer electrolytes possess more functional groups, lower crystallization, glass transition temperature, and better solubility. Especially, a large number of functional groups are beneficial to dissociation of lithium salt for improving the ion conductivity. Furthermore, topological polymers have strong design ability to meet the requirements of comprehensive performances of SPEs. In this review, the recent development in topological polymer electrolytes is summarized and their design thought is analyzed. Outlooks are also provided for the development of future SPEs. It is expected that this review can raise a strong interest in the structural design of advanced polymer electrolyte, which can give inspirations for future research on novel SPEs and promote the development of next‐generation high‐safety flexible energy storage devices.

Driven by natural and artificial selection, the domestic Huoyan geese from Northern China have gradually generated specific phenotypes and climatic adaptations. To understand the genetic basis of the two specific phenotypes that are sex linked, including upper eyelid coloboma and gosling feather color, as well as the climatic adaptations of the Huoyan goose, which can contribute to the artificial selection and breeding of geese. We selected Huoyan geese and nine Southern Chinese goose breeds and identified their divergence on the genomic level. Using selective sweep analysis, we found that PTPRM on chromosome Z influences the upper eyelid coloboma phenotype of the Huoyan goose, and TYRP1 is a plausible candidate gene for the Huoyan gosling feather color. We obtained a number of genes related to cold adaptation in Huoyan geese, mainly involved in physiological functions such as metabolism, angiogenesis contraction and circulatory system, apoptosis, immunity, stress, and neural system. The most interesting candidates for cold adaptation are PIP5K1B and NMNAT3 that are associated with energy metabolism and stress. We also obtained some genes related to heat adaptation, including AGTPBP1, associated with neurology; GDA, associated with skin pigmentation; and NAA35, associated with apoptosis. These findings deepen our understanding of the genetics of specific phenotypes and climate adaptation in local geese and provide insights for the selection of goose breeds.

The COVID-19 pandemic has accelerated innovations for supporting learning and teaching online. However, online learning also means a reduction of opportunities in direct communication between teachers and students. Given the inevitable diversity in learning progress and achievements for individual online learners, it is difficult for teachers to give personalized guidance to a large number of students. The personalized guidance may cover many aspects, including recommending tailored exercises to a specific student according to the student′s knowledge gaps on a subject. In this paper, we propose a personalized exercise recommendation method named causal deep learning (CDL) based on the combination of causal inference and deep learning. Deep learning is used to train and generate initial feature representations for the students and the exercises, and intervention algorithms based on causal inference are then applied to further tune these feature representations. Afterwards, deep learning is again used to predict individual students′ score ratings on exercises, from which the Top-N ranked exercises are recommended to similar students who likely need enhancing of skills and understanding of the subject areas indicated by the chosen exercises. Experiments of CDL and four baseline methods on two real-world datasets demonstrate that CDL is superior to the existing methods in terms of capturing students′ knowledge gaps in learning and more accurately recommending appropriate exercises to individual students to help bridge their knowledge gaps.

Summary: Asphalt binder is inevitably aged by ultraviolet (UV) light during its service period. UV ageing can significantly decrease the technical properties of asphalt binder. The sensitivity of asphalt to UV ageing and thermal-oxidative ageing differs, such that the UV ageing performance cannot be determined based on the thermal-oxidative ageing performance. Previous researches mainly focused on the chemical composite and technical performance changes of asphalt binder during UV ageing, and the UV light parameters effect on the ageing rate of asphalt binder. However, the theory for characterizing and explaining the development of UV ageing depth does not get too much attentions, and the UV ageing mechanism of asphalt binder is not very clear. Therefore, it cannot guide to develop or select the good methods or anti-UV ageing additives for asphalt binders. This paper focuses on the latest researches of the mechanisms and anti-ageing methods of asphalt binders. With the increase of UV ageing time, the UV ageing of asphalt binder develops gradually from the surface to inner part. There are various methods, such as low-penetration grade asphalt, less air void ratio, UV stabilizers and UV light absorbers, that can improve the UV ageing resistance of asphalt binders. A new theory of sensitive wavelengths of asphalt UV ageing is proposed, which can enrich the basic theory of asphalt UV ageing. Depending on this theory, different wavelengths of UV light have different ageing effects on asphalt binder. The composite anti-UV ageing additives with barrier and specific absorption effects on UV light is proposed, and may have better improvement effect on the anti-UV ageing performance of asphalt binder.

Abstract Creating gradients of nanostructure on the surface has found broad applications such as enhanced optical spectroscopy, optical storage of information, and broadband solar energy harvesting. Here, a facile strategy is presented for fabricating gradient nanoparticle arrays with tunable size. It takes a ZnO:Ga microwire as the starting material, and the Ga3+ doping gradient along the microwire is induced by the high voltage applied. Such a doping gradient facilitates the formation of a temperature gradient in a Joule heating process. And this temperature gradient produced by this technique can be as high as 800 °C/mm, which could be later used for gradient annealing of thin metal films. After annealing, the thin metal films turn to gradient nanoparticle arrays. The obtained gradient nanoparticle arrays are confirmed effective in multi-wavelength surface enhanced Raman scattering enhancement.

Abstract Lithium metal batteries hold promise for energy storage applications but suffer from uncontrolled lithium dendrites. In this study, a new composite membrane based on modified natural polymer and ZIF‐67 is designed and prepared by the in situ composite method for the first time. Among them, a modified natural polymer composed of lithium alginate (LA) and polyacrylamide (PAM) can be obtained by electrospinning. Importantly, the polar functional groups of natural polymers can interact by hydrogen bonding and MOFs can construct lithium‐ion transport channels. Consequently, compared with LA‐PAM electrolyte without MOF, the electrochemical stability window of ZIF‐67‐LA‐PAM electrolyte becomes wider from 4.5 to 5.2 V, and the lithium‐ion transference number (tLi+) enhances from 0.326 to 0.627 at 30°C. It is worth noting that the symmetric cells with ZIF‐67‐LA‐PAM have superior stable cycling performance at 40 and 100 mA cm−2, and a high rate at 10C and 20C for LFP cells. Besides, the cell with NCM811 high‐voltage cathode can run stably for 400 cycles with an initial discharge capacity of 136.1 mAh g−1 at 0.5C. This work provides an effective method for designing and preparing MOF‐natural polymer composite electrolytes and exhibits an excellent application prospect in high‐energy‐density lithium metal batteries.

Ethnopharmacological relevanceDanshen preparations are widely used in the treatment of ischaemic cerebrovascular disease. However, the clinical efficacy of such preparations remains unclear. Consequently, Danshen preparations are used to a lesser extent in vascular cognitive impairment (VCI).Aim of the studyIn this study, we aimed to systematically assess the clinical efficacy and safety of Danshen preparations in VCI. To this end, we examined and performed a meta-analysis (MA) of the evidence available from randomised controlled trials (RCTs) of Danshen preparations conducted in patients with VCI.MethodsWe queried the following sources and collected all articles reporting on RCTs of Danshen preparations published prior to December 2021: PubMed, China National Knowledge Infrastructure (CNKI), Wanfang Data, Chongqing VIP Database (CQVIP), and China Biology Medicine (CBM) disc databases. The assessment of treatments that were included in references were performed by RevMan 5.2 software based on guidelines from Cochrane Handbook for Systematic Reviews of Interventions.ResultsWe included a total of 12 RCTs that included data on clinical therapeutic effects. The evaluation criteria included the following: National Institutes of Health Stroke Scale (NIHSS), modified Rankin Scale (mRS), Barthel Index (BI), Mini-Mental State Assessment (MMSE), Montreal Cognitive Assessment (MOCA), Activities of Daily Living Scale (ADL), treatment effect index, and incidence of adverse reaction index. In the included studies, the observation groups included 656 cases and the control groups included 660 cases. The results of the MA were as follows: the mean difference (MD) value after combining the effect size for NIHSS was −2.91, with a 95% confidence interval (CI) of −4.22 to −1.59; the combined effect quantity hypothesis test revealed that Z = 4.33 (p

Hyperphenylalaninemia (HPA) is the most common amino acid metabolism defect in humans. It is an autosomal-recessive disorder of the phenylalanine (Phe) metabolism, in which high Phe concentrations and low tyrosine (Tyr) concentrations in the blood cause phenylketonuria (PKU), brain dysfunction, light pigmentation and musty odor. Newborn screening data of HPA have revealed that the prevalence varies worldwide, with an average of 1:10,000. Most cases of HPA result from phenylalanine hydroxylase (PAH) deficiency, while a small number of HPA are caused by defects in the tetrahydrobiopterin (BH4) metabolism and DnaJ heat shock protein family (Hsp40) member C12 (DNAJC12) deficiency. Currently, the molecular pathophysiology of the neuropathology associated with HPA remains incompletely understood. Dietary restriction of Phe has been highly successful, although outcomes are still suboptimal and patients find it difficult to adhere to the treatment. Pharmacological treatments, such as BH4 and phenylalanine ammonia lyase, are available. Gene therapy for HPA is still in development.

Mutations might challenge the paternity index calculation in forensic identification. While many studies have focussed on the autosomal short tandem repeats (A-STR), the mutation status of sex chromosomes and single nucleotide polymorphism (SNP) remain blank. Next generation sequencing (NGS), known as high throughput and large sequence polymorphism, is a promising tool for forensic genetics. To describe the mutation landscapes in the paternity cases with genetic inconsistencies, a total of 63 parentage confirmed paternity cases contained at least one mismatched locus have been collected. The mutations were subsequently evaluated using Verogen’s MPS ForenSeqTM DNA Signature Kit and a microsatellite instability (MSI) detection kit. The result showed 98.41% (62/63) of the cases had no additional autosomal mutations even when the number of A-STRs increased to 27. As for the sex chromosomes, about 11.11% (7/63) of the cases exhibited either X-STR or Y-STR mutations. D2S1338, FGA and Penta E were the most frequent altered STRs, which suggested they might be the mutation hotspots. In addition, a male with sex chromosome abnormality was observed accidently, whose genotype might be 47, XXY, rather than MSI. Nearly 56.90% of the STR loci possessed isoalleles, which might result in higher STR polymorphisms. No Mendelian incompatibility was detected among the SNP markers, which indicated that SNP was a more reliable genetic marker in the genetic-inconsistent paternity cases.Supplemental data for this article is available online at https://doi.org/10.1080/20961790.2021.2009631 .

Type 2 bradykinin receptor (B2R) is essential in vasodilation and cardioprotection. Here the authors present two cryo-EM structures of human B2R-Gq in complex with bradykinin and kallidin to elucidate the mechanisms for ligand binding, receptor activation, and Gq proteins coupling.

The rare sugar D-allulose is a potential replacement for sucrose with a wide range of health benefits. Conventional production involves the employment of the Izumoring strategy, which utilises D-allulose 3-epimerase (DAEase) or D-psicose 3-epimerase (DPEase) to convert D-fructose into D-allulose. Additionally, the process can also utilise D-tagatose 3-epimerase (DTEase). However, the process is not efficient due to the poor thermotolerance of the enzymes and low conversion rates between the sugars. This review describes three newly identified DAEases that possess desirable properties for the industrial-scale manufacturing of D-allulose. Other methods used to enhance process efficiency include the engineering of DAEases for improved thermotolerance or acid resistance, the utilization of Bacillus subtilis for the biosynthesis of D-allulose, and the immobilization of DAEases to enhance its activity, half-life, and stability. All these research advancements improve the yield of D-allulose, hence closing the gap between the small-scale production and industrial-scale manufacturing of D-allulose.

Coal is expected to be an important energy resource for some developing countries in the coming decades; thus, the rapid classification and qualification of coal quality has an important impact on the improvement in industrial production and the reduction in pollution emissions. The traditional methods for the proximate analysis of coal are time consuming and labor intensive, whose results will lag in the combustion condition of coal-fired boilers. However, laser-induced breakdown spectroscopy (LIBS) assisted with machine learning can meet the requirements of rapid detection and multi-element analysis of coal quality. In this work, 100 coal samples from 11 origins were divided into training, test, and prediction sets, and some clustering models, classification models, and regression models were established for the performance analysis in different application scenarios. Among them, clustering models can cluster coal samples into several clusterings only by coal spectra; classification models can classify coal with labels into different categories; and the regression model can give quantitative prediction results for proximate analysis indicators. Cross-validation was used to evaluate the model performance, which helped to select the optimal parameters for each model. The results showed that K-means clustering could effectively divide coal samples into four clusters that were similar within the class but different between classes; naive Bayesian classification can distinguish coal samples into different origins according to the probability distribution function, and its prediction accuracy could reach 0.967; and partial least squares regression can reduce the influence of multivariate collinearity on prediction, whose root mean square error of prediction for ash, volatile matter, and fixed carbon are 1.012%, 0.878%, and 1.409%, respectively. In this work, the built model provided a reference for the selection of machine learning methods for LIBS when applied to classification and qualification.

Cisplatin-based chemotherapy remains the standard care for non-small cell lung cancer (NSCLC) patients. Relapse after chemotherapy-induced dormancy affects the overall survival of patients. The evolution of cancer cells under chemotherapy stress is regulated by transcription factors (TFs) with binding sites initially buried deep within inaccessible chromatin. The transcription machinery and dynamic epigenetic alterations during the process of dormancy-reactivation of lung cancer cells after chemotherapy need to be investigated. Here, we investigated the chromatin accessibility of lung cancer cells after cisplatin treatment, using an assay for transposase-accessible chromatin sequencing (ATAC-seq). We observed that global chromatin accessibility was extensively improved. Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining (TRRUST) v.2 was used to elucidate TF-target interaction during the process of dormancy and reactivation. Enhancer regions and motifs specific to key TFs including JUN, MYC, SMAD3, E2F1, SP1, CTCF, SMAD4, STAT3, NFKB1, and KLF4 were enriched in differential loci ATAC-seq peaks of dormant and reactivated cancer cells induced by chemotherapy. The findings suggest that these key TFs regulated gene expressions during the process of dormancy and reactivation of cancer cells through altering promoter accessibility of target genes. Our study helps advance understanding of how cancer cells adapt to the stress induced by chemotherapy through TF binding motif accessibility.

Abstract Background Cisplatin‐based chemotherapy is a therapeutic strategy against non‐small cell lung cancer (NSCLC). However, cancers relapse after chemotherapy due to a dormant state of residual cancer cells. Extracellular vesicles and particles (EVPs) are active carriers of proteins and nucleic acid. Here, we aimed to study the molecular alterations and proteomic characteristics of EPV in dormant and reactivated cancer cells induced by cisplatin. Methods We used a short‐term single dose of cisplatin to induce the dormant and reactivated cell status. We examined the gene expressional profiling and proteomic profiling of EVPs from dormant and reactivated cancer cells by RNA‐sequencing and LC–MS/MS. Results We found substantial changes in gene expression and protein level in EVP. The genes with higher expression in dormant cancer cells were lipid transporter‐ and lipid metabolic‐related genes. A total of 111 EVP proteins were upregulated in dormant cancer cells compared to those in control cells. Fifty differential expressed proteins (DEPs) were identified in EVPs from reactivated cancer cells compared to those in dormant cancer cells. Among the DEPs, we found that apolipoproteins such as APOA1 and APOE were significantly increased in dormant cancer cell‐derived EVPs. Integration of EVP proteomes with transcriptional profiles of cancer cells revealed that the proteomic profiling of EVP derived from cancer cells can reflect the cellular status of cancer cells, which showed an activated lipid metabolism in dormant state. Conclusion Lipoproteins enriched in EVPs reflect the activated lipid metabolism in dormant cancer cells and may provide potential biomarkers or therapeutic targets for cisplatin‐based therapy.

The UV aging of bitumen has a significant influence on the pavement service life, therefore, the research on UV aging has attracted increasing attention recently. It is known that the aging of bituminous pavements does not occur instantly through the full depth, instead, the aging depth of the bitumen increases gradually with the increasing aging time. The limitation of the research is that the development mechanism of the aging depth of bitumen is not clearly known. Various thicknesses of bituminous membranes were prepared and the UV light transmission and absorption properties of bituminous membranes were investigated by UV–visible spectrophotometric, aiming to determine the penetration depth of UV light in bitumen after UV aging. It is concluded that, for the same bituminous membrane, the transmittance of UV light increases with the increase of the light wavelength; while the transmittance of UV light decreases significantly with the increase of bituminous membrane thickness. The penetration depth of UV light in bitumen increases gradually with increasing UV aging time. The relationship between UV light penetration depth in bitumen and aging depth of bitumen was analyzed, and UV aging models of three parts of bitumen were established to reveal the development mechanism of the UV aging depth of bitumen during UV aging. The increasing aging depth of bitumen is due to the increase of UV light penetration depth in bitumen, and the diffusion action of aging products from surface bitumen to deeper bitumen. During the UV aging, the bitumen actually comprises three parts, namely, the surface direct aging part (UV light can reach), the deeper diffusion aging part (aged by the diffusion action) and the internal unaged part (UV light and diffusion action can not affect).

Novel genetic marker microhaplotype has led to an upsurge in forensic genetic research. This study established a 163 microhaplotype (MH) multiplex assay based on next-generation sequencing (NGS) and evaluated the assay’s performance and applicability. Our results showed that the 163 MH assay was accurate, repeatable and reliable, and could distinguish between African, European-American, Southern Asia and Eastern Asia populations. Among the 163 MH makers, 48 MHs with Ae > 3.0 in China Eastern Han were selected and confirmed to be highly polymorphic, with a combined power of discrimination of 1–8.26 × 10–44 and the combined power of exclusion in duos and trios of 1–1.26 × 10–8 and 1–8.27 × 10–16, respectively. Moreover, the mixture study demonstrated the realizability of the MHs in deconvoluting mixtures with different proportions of two to five-person. In conclusion, our findings support the use of this MH assay for ancestry inference, human identification, paternity testing and mixture deconvolution in forensic research.

These days energy-related enterprises started using a fancy terminology called circular economy (CE) to display their progress in opting for innovative approaches to mitigate carbon emissions and waste gas released in the enterprise during the operation. Hence, this paper examines whether there is any mediating role of innovation from a CE point of view or not in managing the waste resources and minimising the carbon emission on the innovation and quality of new energy products. For this, secondary data with a sample observation of 608 was selected from Chinese listed enterprises from 2015–2020. The empirical results revealed that the waste resource utilisation by firms is helpful to the quality of their products but does not significantly affect the innovation of their new energy products. In addition, the evidence from developing countries shows that companies’ carbon reduction behaviour benefits their new energy product innovation. However, it does not significantly impact the quality of their products. Model validation analyses the existence of corporate waste resource utilisation through corporate new energy product innovation, thereby contributing to corporate product quality. Overall, this paper facilitates enterprises’ new energy product development activities and fills the research gap between companies’ waste gas resource utilisation and new energy product innovation.

Erosion and the stripping effect of moisture on asphalt mixtures is one of the main reasons for the shortened service life of asphalt pavements. The common mean of preventing asphalt pavements from being damaged by moisture is adding anti-stripping agents (ASAs) to asphalt mixtures. However, the effect regularity and mechanism of anti-stripping agents on the physicochemical properties of asphalt is not exactly defined. This study compared the physical properties of ASA-modified asphalt (AMAs) to determine the optimal dosage and investigated the rheological and adhesion properties. Based on the roller bottle method and water immersion method, the moisture susceptibility of AMAs with three particle sizes was investigated. The results showed that the modification of asphalt using anti-stripping agents was a physical modification. At the optimum dosage of anti-stripping agents (0.3%), the basic physical properties of AMA1 were the most desirable. ASA2 increased the resistance of asphalt for deformation at high temperature by 46%, and AMA3 had the best low-temperature performance. ASAs enhanced the dispersed and polar components in the asphalt binder, improving the adhesion energy of asphalt. AMA3 had the strongest adhesion to the aggregate, with an increase in adhesion work by 2.8 times and a 45% of increase in ER value. This was attributed to ASA3 containing with a large number of metal cations and polar functional groups. It was shown that ASAs provided the most improvement in the anti-stripping performance of asphalt mixtures with 9.5–13.2 mm particles. The amide ASA, phosphate ASA and aliphatic amine ASA improved the water damage resistance of asphalt by 65%, 45% and 78%, respectively. This study can help engineers realize the effects of different types of ASAs on the physicochemical properties of asphalt and select the most suitable type of ASAs according to the service requirements.

Liver fibrosis represents the reversible pathological process with the feature of the over-accumulation of extracellular matrix (ECM) proteins within the liver, which results in the deposition of fibrotic tissues and liver dysfunction. Circular noncoding RNAs (CircRNAs) have the characteristic closed loop structures, which show high resistance to exonuclease RNase, making them far more stable and recalcitrant against degradation. CircRNAs increase target gene levels by playing the role of a microRNA (miRNA) sponge. Further, they combine with proteins or play the role of RNA scaffolds or translate proteins to modulate different biological processes. Recent studies have indicated that CircRNAs play an important role in the occurrence and progression of liver fibrosis and may be the potential diagnostic and prognostic markers for liver fibrosis. This review summarizes the CircRNAs roles and explores their underlying mechanisms, with a special focus on some of the latest research into key CircRNAs related to regulating liver fibrosis. Results in this work may inspire fruitful research directions and applications of CircRNAs in the management of liver fibrosis. Additionally, our findings lay a critical theoretical foundation for applying CircRNAs in diagnosing and treating liver fibrosis.

This article considers the problem of selecting two-level designs under the baseline parameterisation when some two-factor interactions are important. We propose a minimum aberration criterion, which minimises the bias caused by the non-negligible effects. Using this criterion, a class of optimal designs can be further distinguished from one another, and we present an algorithm to find the minimum aberration designs among the D-optimal designs. Sixteen-run and twenty-run designs are summarised for practical use.

BackgroundThe pandemic of COVID-19 has been shaping economic developments of the world. From the standpoint of government measures to prevent and control the epidemic, the lockdown was widely used. It is essential to access the economic losses in a lockdown environment which will provide government administration with a necessary reference for decision making in controlling the epidemic.MethodsWe introduce the concept of “standard unit incident” and an economic losses assessment methodology for both the standard and the assessed area. We build a “standard unit lockdown” economic losses assessment system and indicators to estimate the economic losses for the monthly lockdown. Using the comprehensive assessment system, the loss infected coefficient of monthly economic losses during lockdown in the 40 countries has been calculated to assess the economic losses by the entropy weighting method (EWM) with data from the CSMAR database and CDC website.ResultsWe observe that countries in North America suffered the most significant economic losses due to the epidemic, followed by South America and Europe, Asia and Africa, and Oceania and Antarctica suffered relatively minor economic losses. The top 10 countries for monthly economic losses during lockdown were the United States, India, Brazil, France, Turkey, Russia, the United Kingdom, Italy, Spain, and Germany. The United States suffered the greatest monthly economic losses under lockdown ($65.3 billion), roughly 1.5 times that of China, while Germany suffered the least ($56.4 billion), roughly 1.3 times that of China.ConclusionLockdown as a control and mitigation strategy has great impact on the economic development and causes huge economic losses. The economic impact due to the pandemic has varied widely among the 40 countries. It will be important to conduct further studies to compare and understand the differences and the reasons behind.