Genetic Foundation of Male Spur Length and Its Correlation with Female Egg Production in Chickens.

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.

CNSMolGen: A Bidirectional Recurrent Neural Network-Based Generative Model for De Novo Central Nervous System Drug Design.

Central nervous system (CNS) drugs have had a significant impact on treating a wide range of neurodegenerative and psychiatric disorders. In recent years, deep learning-based generative models have shown great potential for accelerating drug discovery and improving efficacy. However, specific applications of these techniques in CNS drug discovery have not been widely reported. In this study, we developed the CNSMolGen model, which uses a framework of bidirectional recurrent neural networks (Bi-RNNs) for de novo molecular design of CNS drugs. Results showed that the pretrained model was able to generate more than 90% of completely new molecular structures, which possessed the properties of CNS drug molecules and were synthesizable. In addition, transfer learning was performed on small data sets with specific biological activities to evaluate the potential application of the model for CNS drug optimization. Here, we used drugs against the classical CNS disease target serotonin transporter (SERT) as a fine-tuned data set and generated a focused database against the target protein. The potential biological activities of the generated molecules were verified by using the physics-based induced-fit docking study. The success of this model demonstrates its potential in CNS drug design and optimization, which provides a new impetus for future CNS drug development.

Genetic parameter estimation and molecular foundation of chicken beak shape.

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 <0.01) and outside of high linkage disequilibrium (LD) regions, we also conducted rare variant association studies (RVA) and GWAS to find the association between genotype and phenotype. We also analyzed transcriptomic data from multiple tissues of chicken embryos and revealed that all of the 9 genes were highly expressed in beak of chicken embryos, indicating their potential function for beak development. Our results provided the genetic foundation of chicken beak shape, which could help chicken breeding on beak related traits.

PROSCA: an online platform for humanized scaffold mining facilitating rational protein engineering.

Protein scaffolds with small size, high stability and low immunogenicity show important applications in the field of protein engineering and design. However, no relevant computational platform has been reported yet to mining such scaffolds with the desired properties from massive protein structures in human body. Here, we developed PROSCA, a structure-based online platform dedicated to explore the space of the entire human proteome, and to discovery new privileged protein scaffolds with potential engineering value that have never been noticed. PROSCA accepts structure of protein as an input, which can be subsequently aligned with a certain class of protein structures (e.g. the human proteome either from experientially resolved or AlphaFold2 predicted structures, and the human proteins belonging to specific families or domains), and outputs humanized protein scaffolds which are structurally similar with the input protein as well as other related important information such as families, sequences, structures and expression level in human tissues. Through PROSCA, the user can also get excellent experience in visualizations of protein structures and expression overviews, and download the figures and tables of results which can be customized according to the user's needs. Along with the advanced protein engineering and selection technologies, PROSCA will facilitate the rational design of new functional proteins with privileged scaffolds. PROSCA is freely available at https://idrblab.org/prosca/.

Genetic parameter estimation and molecular foundation of chicken egg-laying trait.

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.

Molecular genetic foundation of a sex-linked tailless trait in Hongshan chicken by whole genome data analysis.

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.

Degradation of sulfamethazine by microbial electrolysis cell with nickel-cobalt co-modified biocathode.

In this study, nickel-cobalt co-modified stainless steel mesh (Ni-Co@SSM) was prepared and used as the biocathode in microbial electrolysis cell (MEC) for sulfamethazine (SMT) degradation. The optimal electrochemical performance of the Ni-Co@SSM was obtained at the electrodeposition time of 600 s, electrodeposition current density of 20 mA cm-2, and nickel-cobalt molar ratio of 1:2. The removal of SMT in MEC with the Ni-Co@SSM biocathode (MEC-Ni-Co@SSM) was 82%, which increased by 30% compared with the conventional anaerobic reactor. Thirteen intermediates were identified and the potential degradation pathways of SMT were proposed. Proteobacteria, Firmicutes, Patescibacteria, Chloroflexi, Bacteroidetes, and Euryarchaeota are the dominant bacteria at the phylum level in the MEC-Ni-Co@SSM, which are responsible for SMT metabolism. Due to the electrical stimulation, there was an increase in the abundance of the metabolic function and the genetic information processing. This work provides valuable insight into utilizing MECs for effective treatment of antibiotic-containing wastewater.

Ti3C2Tx MXene-based hybrid nanocoating for flame retardant, early fire-warning and piezoresistive tension sensing smart polyester fabrics.

Flammability feature of textiles is a big underlying risk causing fire disasters. The fabrication of reliable fire resistant and quick fire warning fabrics is imperative but challenging. Herein, three types of early fire-warning polyester fabrics, namely, FPP@AM-X, FPP@PM-X and FPP@AX-M1, with good flame retardant and piezoresistive sensing performance were developed by fabricating polyethyleneimine (PEI), ammonium polyphosphate (APP), phytic acid (PA) and MXenes onto phosphorus-containing flame retardant polyethylene terephthalate (FRPET) via polydopamine (PDA) mediated layer-by-layer self-assembly. Owing to the improved thermoelectric properties of MXenes, FPP@A5-M1 exhibited a maximum thermoelectric voltage of 0.59 mV at a temperature difference of 130 °C and can provide an ideal cyclic early fire warning response within 4 s. In addition, due to the synergistic flame retardant effect of MXenes and APP in the coating layer, FPP@A5-M1 could be self-extinguished within 2 s after ignition and the value of peak heat release ratio and total smoke production decreased by 41.9% and 30.4%, respectively. Besides, the MXene-based hybrid coated fabric can detect the movement of human fingers and elbows, illustrating its potential application in piezoresistive tension sensing. This work provides a new route to designing and developing multi-functional and smart fire protection fabrics.

The genotoxicity impact of heavy metals on the Escherichia coli.

In present work, the genotoxicity of Hg2+, Ag+, Cr6+, Ni2+, Pb2+, Co2+, Mn2+, Zn2+, and Cr3+ was investigated via a quantitative toxicogenomics assay, to understand the toxic mechanism of heavy metals with greater depth. Under the experimental conditions, Hg2+, Ag+, and Cr6+ showed a more serious toxic impact on the expression of functional genes (eg., oxyR, katG, grxA, osmE, emrE, dinG) than Ni2+, Pb2+, Co2+, Mn2+, Zn2+, and Cr3+, while the protein, oxidative, and membrane stress response pathways were more sensitive to the toxicity of Hg2+, Ag+, and Cr6+ than the DNA and general stress response pathways. Compared with the other kinds of heavy metals, Ni2+, Pb2+, Co2+, and Mn2+ altered the expression of functional genes (uvrY, recX, mutY, and sbmC) related to the DNA stress response pathways more seriously, while Zn2+ and Cr3+ changed the expression of the functional genes (yfjG, ydgL, ssrA, and osmC) associated with the general stress response pathway more significantly. Meanwhile, the toxicity of Ni2+, Pb2+, Co2+, and Mn2+ was slightly higher than that of Zn2+ and Cr3+ in terms of the total value of transcriptional effect level Index (TELI) by detecting the promoter activities of different functional genes. In addition, to survive the toxicity of heavy metals, the expression of multidrug efflux genes (ydgL, cyoA, emrA, and emrE) and toxicity-resistant genes (Ion, dnaJ, clpB, mutY, dnaK, rpoD, sbmC) mainly functioned.

UV-induced microplastics (MPs) aging leads to comprehensive toxicity.

Herein, the toxicity of 4 MPs and additives released from MPs during UV-aging was quantitatively evaluated by the transcriptional effect level index (TELI) based on E. coli whole-cell microarray assay, and MPs-antibiotics complex pollutants. Results showed that MPs and these additives had high toxicity potential, the maximum TELI was 5.68/6.85 for polystyrene (PS)/bis(2-ethylhexyl) phthalate (DEHP). There were many similar toxic pathways between MPs and additives, indicating that part of the toxicity risk of MPs was caused by the release of additives. MPs were compounded with antibiotics, the toxicity value changed significantly. The TELI values of amoxicillin (AMX) + polyvinyl chloride (PVC) and ciprofloxacin (CIP) + PVC were as high as 12.30 and 14.58 (P < 0.05). Three antibiotics all decreased the toxicity of PS and had little effect on polypropylene (PP) and polyethylene (PE). The combined toxicity mechanism of MPs and antibiotics was very complicated, and the results could be divided into four types: MPs (PVC/PE + CIP), antibiotics (PVC + TC, PS + AMX/ tetracycline (TC)/CIP, PE + TC), both (PP + AMX/TC/CIP), or brand-new mechanisms (PVC + AMX).

Adsorption of antibiotics on different microplastics (MPs): Behavior and mechanism.

MPs can adsorb antibiotics to coexist and accumulate in the aquatic environment in the form of complexes, resulting in unforeseeable adverse consequences. The adsorption behavior and mechanism of three antibiotics amoxicillin (AMX), ciprofloxacin (CIP), and tetracycline (TC) by four MPs Polyvinyl chloride (PVC), polystyrene (PS), polypropylene (PP), and polyethylene (PE) were studied. Results showed that the adsorption of antibiotics onto MPs follows the pseudo-second-order kinetic and the Freundlich isotherm model, indicating a multilayer chemical adsorption. Combined with FTIR, XRD, and SEM analyses, the adsorption behavior was simultaneously governed by physical processes. Additionally, the equilibrium adsorption capacity was inhibited in the research concentration range of NaCl from 10 mg/L to 10 g/L. The higher the salt concentration, the more pronounced the inhibition phenomenon was. The high (9) and low (3) pH also inhibited the adsorption of antibiotics to MPs. The humic acid (HA) concentration in the range of 0-20 mg/L generally inhibited the MPs-antibiotics adsorption, but the higher HA concentration showed less inhabitation than the lower one. The adsorption inhibition of TC on the four MPs by SA also followed the above rule. However, the adsorption inhibition of sodium alginate (SA) on AMX and CIP on the four MPs was enhanced with its concentration (0-50 mg/L).

Graph based multi-scale neighboring topology deep learning for kidney and tumor segmentation.

Objective.Effective learning and modelling of spatial and semantic relations between image regions in various ranges are critical yet challenging in image segmentation tasks.Approach.We propose a novel deep graph reasoning model to learn from multi-order neighborhood topologies for volumetric image segmentation. A graph is first constructed with nodes representing image regions and graph topology to derive spatial dependencies and semantic connections across image regions. We propose a new node attribute embedding mechanism to formulate topological attributes for each image region node by performing multi-order random walks (RW) on the graph and updating neighboring topologies at different neighborhood ranges. Afterwards, multi-scale graph convolutional autoencoders are developed to extract deep multi-scale topological representations of nodes and propagate learnt knowledge along graph edges during the convolutional and optimization process. We also propose a scale-level attention module to learn the adaptive weights of topological representations at multiple scales for enhanced fusion. Finally, the enhanced topological representation and knowledge from graph reasoning are integrated with content features before feeding into the segmentation decoder.Main results.The evaluation results over public kidney and tumor CT segmentation dataset show that our model outperforms other state-of-the-art segmentation methods. Ablation studies and experiments using different convolutional neural networks backbones show the contributions of major technical innovations and generalization ability.Significance.We propose for the first time an RW-driven MCG with scale-level attention to extract semantic connections and spatial dependencies between a diverse range of regions for accurate kidney and tumor segmentation in CT volumes.

Convolutional bi-directional learning and spatial enhanced attentions for lung tumor segmentation.

BACKGROUND AND OBJECTIVE: Accurate lung tumor segmentation from computed tomography (CT) is complex due to variations in tumor sizes, shapes, patterns and growing locations. Learning semantic and spatial relations between different feature channels, image regions and positions is critical yet challenging. METHODS: We propose a new segmentation method, PRCS, by learning and integrating multi-channel contextual relations, and spatial and position dependencies across image regions. Firstly, to extract contextual relationships between different deep image feature tensor channels, we propose a new convolutional bi-directional gated recurrent unit based module for forward and backward learning. Secondly, a novel cross-channel region-level attention mechanism is proposed to discriminate the contributions of different local regions and associated features in the global learning process. Finally, spatial and position dependencies are formulated by a new position-enhanced self-attention mechanism. The new attention can measure the diverse contributions of other positions to a target position and obtain an enhanced adaptive feature vector for the target position. RESULTS: Our model outperformed seven state-of-the-art segmentation methods on both public and in-house lung tumor datasets in terms of spatial overlapping and shape similarity. Ablation study results proved the effectiveness of three technical innovations and generalization ability on different 3D CNN segmentation backbones. CONCLUSION: The proposed model enhanced the learning and propagation of contextual, spatial and position relations in 3D volumes, improving lung tumours' segmentation performance with large variations and indistinct boundaries. PRCS provides an effective automated approach to support precision diagnosis and treatment planning of lung cancer.

Trends in cervical cancer mortality in China from 1989 to 2018: an age-period-cohort study and Joinpoint analysis.

BACKGROUND: Worldwide, cervical cancer is the second-most-common malignancy of the female reproductive system. Due to its large population, China accounted for 11.9% of cervical cancer deaths, and 12.3% of global cervical cancer DALYs in 2017. In 2009, China launched a nationwide screening program, yet mortality from cervical cancer has shown an upward trend in recent years. The aim of this study was to explore factors affecting cervical cancer mortality rates in China, and contribute to their future reduction. METHODS: In this descriptive study, a Joinpoint regression analysis and age-period-cohort (APC) model based on the intrinsic estimator (IE) algorithm were utilized. Data from the period 1989-2018 were extracted from the International Agency for Research on Cancer (IARC) Database of WHO (1989-2000) and China Health Statistical Yearbook database (2002-2018). RESULTS: Our study found mortality from cervical cancer to have initially declined, but increase thereafter over the entire observation period in both rural and urban China. The influence of age, period and cohort effect on the mortality rate had statistical significance. The effect of age increased with years, becoming a contributing factor in women aged over 45 years countrywide. Conversely, the cohort effect became a protective factor for women born after 1938 in urban areas, and for women born after 1958 in rural areas. The period effect was relatively less impactful. CONCLUSIONS: The study indicates that organized cervical screening projects facilitated the identification of potential patients, or patients with comorbidities. Correspondingly, mortality was found to increase with incidence, particularly among elderly women, indicating that newly diagnosed patients were at an advanced stage of cervical cancer, or were not receiving appropriate treatment. Therefore, the coverage of cervical cancer screening should be improved, and women's health awareness promoted. Early diagnosis and treatment is critical to reduce the disease burden and improve outcomes.

Acute impact of Hg2+, Cu2+, and Ag+ on the formation of biopolymers and nitrogenous soluble microbiological products in activated sludge for wastewater treatment.

In the present work, acute impact of heavy metals on activated sludge was investigated, specifically the release of biopolymers and nitrogenous soluble microbiological products (N-SMP) that significantly impact tertiary effluent quality. Based on the previously reported studies, Hg2+ and Ag+ were selected as representative "non-essential" heavy metals, while Cu2+ was selected as the "essential" heavy metal. Stress tests show that under the present experimental conditions, adding a higher concentration of heavy metals to the activated sludge increases the concentration of biopolymers and SMP in the supernatant; N-SMP increased more significantly than carbonaceous products, implying a greater risk of formation of toxic nitrogenous disinfection by-products or membrane fouling in relevant tertiary treatment processes. The severity of the release of SMP into the supernatant depended on the heavy metal, with an order of Hg2+ > Ag+ > Cu2+ ("non-essential" > "essential") under identical molar concentrations. The mass balance of typical organics (e.g., biopolymers) in SMP and extracellular polymeric substances (EPS) in activated sludge was analyzed, and a negative correlation between the organics in the SMP and tightly bound EPS was observed, implying that a significant fraction of the SMP could be quickly released from the tightly bound EPS under heavy metal shock conditions and could be related to cell response or damage.

Impact of heavy metals on the formation and properties of solvable microbiological products released from activated sludge in biological wastewater treatment.

This study investigated the acute impact of heavy metals on activated sludge with respect to the amount properties of biopolymers and other solvable microbiological products (SMPs) released from the sludge. Ten heavy metals were selected for the evaluation. Under the experimental conditions, exposing activated sludge to different metals led to an increase in SMPs, with a more significant increase in nitrogenous organics than in carbonaceous ones, where Hg2+, Ag+, Cu2+, and Cr6+ led to the highest increase in SMP species, while Cd2+, Ni2+, Mn2+, Pb2+, and Co2+ caused limited increase in the middle and small SMP molecules, and Zn2+ and Cr3+ resulted in a decrease in SMP content. To probe the molecular impact of heavy metals and the association between cellular stress and SMP formation, the toxicity of heavy metals was evaluated using a toxicogenomics assay. Based on a correlation analysis between the increase in SMP and the molecular toxicity index-transcriptional effect level index (TELI) of different genes under corresponding stress conditions, eight genes demonstrated a strong correlation with SMP properties and were pre-assumed to have the most significant influence on the increment in SMPs. We further validated the correlation equation established to predict SMP production based on the molecular disturbance of the eight key biomarkers, using arsenic As3+ and vanadium V5+ as tests, and by quantifying the amount of SMPs released from the activated sludge under the influence of these metals using a TELI-derived equation. In addition, the heavy metals that generated greater amounts of reactive oxygen species also caused larger increases in SMPs.