Soil bacterial diversity and community structure of Suaeda glauca vegetation in the Hetao Irrigation District, Inner Mongolia, China.

Exploring the bacterial community in the S. glauca rhizosphere was of great value for understanding how this species adapted to the saline-alkali environment and for the rational development and use of saline-alkali soils. In this study, high-throughput sequencing technology was used to investigate the diversity characteristics and distribution patterns of soil bacterial communities in the rhizosphere of S.glauca-dominated communities in the Hetao Irrigation Distract, Inner Mongolia, China. The relationships among bacterial characteristics, soil physicochemical properties and vegetation in four sampling sites were analyzed. The soil bacterial communities in the rhizosphere of S. glauca-dominated communities were mainly composed of 16 phyla (i.e., Proteobacteria, Actinobacteria, Bacteroidetes, Gemmatimonadetes, Chloroflexi, Acidobacteria, Firmicutes, Planctomycetes, Deinococcus-Thermus, Verrucomicrobia, Saccharibacteria, Cyanobacteria, Nitrospirae, JL-ETNP-Z39, Parcubacteria and Chlorobi), and these populations accounted for more than 99% of the total bacterial community. At the genus level, the main bacterial communities comprised Halomonas, Nitriliruptor, Euzebya and Pelagibius, which accounted for 15.70% of the total bacterial community. An alpha diversity analysis indicated that the richness and diversity of rhizosphere soil bacteria differed significantly among the sampling sites, and the bacterial richness and diversity indices of severe saline-alkali land were higher than those of light and moderate saline-alkali land. The principal component analysis (PCA) and linear discriminant analysis effect size (LEfSe) showed significant differences in the species composition of the rhizosphere soil bacterial community among different sampling sites. A correlation analysis showed that the number of bacterial species exhibited the highest correlation with the soil water content (SWC). The richness and evenness indices were significantly correlated with the SWC and SO4 2-, K+ and Mg2+ concentrations. The electrical conductivity (EC), soluble ions (Na+, CO3 2- + HCO3 -, K+, Ca2+, Mg2+, and SO4 2+), SWC and vegetation coverage (VC) were the main drivers affecting the changes in its community structure. The bacterial community in the rhizosphere of S. glauca enhanced the adaptability of S. glauca to saline-alkali environment by participating in the cycling process of nutrient elements, the decomposition of organic matter and the production of plant growth regulating substances. These results provided a theoretical reference for further study on the relationship among rhizosphere soil microorganisms and salt tolerance in halophytes.

Single-cell transcriptomic analyses of mouse idh1 mutant growth plate chondrocytes reveal distinct cell populations responsible for longitudinal growth and enchondroma formation.

Enchondromas are a common tumor in bone that can occur as multiple lesions in enchondromatosis, which is associated with deformity of the effected bone. These lesions harbor mutations in IDH and driving expression of a mutant Idh1 in Col2 expressing cells in mice causes an enchondromatosis phenotype. In this study we compared growth plates from E18.5 mice expressing a mutant Idh1 with control littermates using single cell RNA sequencing. Data from Col2 expressing cells were analyzed using UMAP and RNA pseudo-time analyses. A unique cluster of cells was identified in the mutant growth plates that expressed genes known to be upregulated in enchondromas. There was also a cluster of cells that was underrepresented in the mutant growth plates that expressed genes known to be important in longitudinal bone growth. Immunofluorescence showed that the genes from the unique cluster identified in the mutant growth plates were expressed in multiple growth plate anatomic zones, and pseudo-time analysis also suggested these cells could arise from multiple growth plate chondrocyte subpopulations. This data identifies subpopulations of cells in control and mutant growth plates, and supports the notion that a mutant Idh1 alters the subpopulations of growth plate chondrocytes, resulting a subpopulation of cells that become enchondromas at the expense of other populations that contribute to longitudinal growth.

An antioxidant hydrogel dressing with wound pH indication function prepared based on silanized bacterial nanocellulose crosslinked with beet red pigment extract.

Maintaining wound moisture and monitoring of infection are crucial aspects of chronic wound treatment. The development of a pH-sensitive functional hydrogel dressing is an effective approach to monitor, protect, and facilitate wound healing. In this study, beet red pigment extract (BRPE) served as a native and efficient pH indicator by being grafted into silane-modified bacterial nanocellulose (BNC) to prepare a pH-sensitive wound hydrogel dressing (S-g-BNC/BRPE). FTIR confirmed the successful grafting of BRPE into the BNC matrix. The S-g-BNC/BRPE showed superior mechanical properties (0.25 MPa), swelling rate (1251 % on average), and hydrophilic properties (contact angle 21.83°). The composite exhibited a notable color change as the pH changed between 4.0 and 9.0. It appeared purple-red when the pH ranged from 4.0 to 6.0, and appeared light pink at pH 7.0 and 7.4, and appeared ginger-yellow at pH 8.0 and 9.0. Subsequently, the antioxidant activity and cytotoxicity of the composite was evaluated, its DPPH·, ABTS+, ·OH scavenging rates were 32.33 %, 19.31 %, and 30.06 %, respectively, and the cytotoxicity test clearly demonstrated the safety of the dressing. The antioxidant hydrogel dressing, fabricated with a cost-effective and easy method, not only showed excellent biocompatibility and dressing performance but could also indicated the wound state based on pH changes.

Simultaneous detection of dental caries and fissure sealant in intraoral photos by deep learning: a pilot study.

BACKGROUND: Deep learning, as an artificial intelligence method has been proved to be powerful in analyzing images. The purpose of this study is to construct a deep learning-based model (ToothNet) for the simultaneous detection of dental caries and fissure sealants in intraoral photos. METHODS: A total of 1020 intraoral photos were collected from 762 volunteers. Teeth, caries and sealants were annotated by two endodontists using the LabelMe tool. ToothNet was developed by modifying the YOLOX framework for simultaneous detection of caries and fissure sealants. The area under curve (AUC) in the receiver operating characteristic curve (ROC) and free-response ROC (FROC) curves were used to evaluate model performance in the following aspects: (i) classification accuracy of detecting dental caries and fissure sealants from a photograph (image-level); and (ii) localization accuracy of the locations of predicted dental caries and fissure sealants (tooth-level). The performance of ToothNet and dentist with 1year of experience (1-year dentist) were compared at tooth-level and image-level using Wilcoxon test and DeLong test. RESULTS: At the image level, ToothNet achieved an AUC of 0.925 (95% CI, 0.880-0.958) for caries detection and 0.902 (95% CI, 0.853-0.940) for sealant detection. At the tooth level, with a confidence threshold of 0.5, the sensitivity, precision, and F1-score for caries detection were 0.807, 0.814, and 0.810, respectively. For fissure sealant detection, the values were 0.714, 0.750, and 0.731. Compared with ToothNet, the 1-year dentist had a lower F1 value (0.599, p < 0.0001) and AUC (0.749, p < 0.0001) in caries detection, and a lower F1 value (0.727, p = 0.023) and similar AUC (0.829, p = 0.154) in sealant detection. CONCLUSIONS: The proposed deep learning model achieved multi-task simultaneous detection in intraoral photos and showed good performance in the detection of dental caries and fissure sealants. Compared with 1-year dentist, the model has advantages in caries detection and is equivalent in fissure sealants detection.

Bulk Segregant Analysis Sequencing and RNA-Seq Analyses Reveal Candidate Genes Associated with Sepal Color Phenotype of Eggplant (Solanum melongena L.).

Eggplant is a highly significant vegetable crop and extensively cultivated worldwide. Sepal color is considered one of the major commercial traits of eggplant. Eggplant sepals develop from petals, and sepals have the ability to change color by accumulating anthocyanins, but whether the eggplants in sepal and their biosynthetic pathways are the same as those in petals is not known. To date, little is known about the underlying mechanisms of sepal color formation. In this study, we performed bulked segregant analysis and transcriptome sequencing using eggplant sepals and obtained 1,452,898 SNPs and 182,543 InDel markers, respectively, as well as 123.65 Gb of clean data using transcriptome sequencing. Through marker screening, the genes regulating eggplant sepals were localized to an interval of 2.6 cM on chromosome 10 by bulked segregant analysis sequencing and transcriptome sequencing and co-analysis, combined with screening of molecular markers by capillary electrophoresis. Eight possible candidate genes were then screened to further interpret the regulatory incentives for the eggplant sepal color.

Modeling Nitrogen Fate and Water and Nitrogen Use Efficiencies under Different Greenhouse Vegetable Production Systems Using the WHCNS-Veg Model.

Quantitative evaluation of the effects of diverse greenhouse vegetable production systems (GVPS) on vegetable yield, soil water consumption, and nitrogen (N) fates could provide a scientific basis for identifying optimum water and fertilizer management practices for GVPS. This research was conducted from 2013 to 2015 in a greenhouse vegetable field in Quzhou County, North China. Three production systems were designed: conventional (CON), integrated (INT), and organic (ORG) systems. The WHCNS-Veg model was employed for simulating vegetable growth, water dynamics, and fates of N, as well as water and N use efficiencies (WUE and NUE) for four continuous growing seasons. The simulation results revealed that nitrate leaching and gaseous N emissions constituted the predominant N loss within GVPS, which separately accounted for 11.5-59.4% and 6.0-21.1% of the N outputs. The order of vegetable yield, N uptake, WUE, and NUE under different production systems was ORG > INT > CON, while the order of nitrate leaching and gaseous N loss was CON > INT > ORG. Compared to CON, ORG exhibited a significant increase in yield, N uptake, WUE, and NUE by 24.6%, 24.2%, 26.1%, and 89.7%, respectively, alongside notable reductions in nitrate leaching and gaseous N loss by 67.7% and 63.2%, respectively. The ORG system should be recommended to local farmers.

Decouple Graph Neural Networks: Train Multiple Simple GNNs Simultaneously Instead of One.

Graph neural networks (GNN) suffer from severe inefficiency due to the exponential growth of node dependency with the increase of layers. It extremely limits the application of stochastic optimization algorithms so that the training of GNN is usually time-consuming. To address this problem, we propose to decouple a multi-layer GNN as multiple simple modules for more efficient training, which is comprised of classical forward training (FT) and designed backward training (BT). Under the proposed framework, each module can be trained efficiently in FT by stochastic algorithms without distortion of graph information owing to its simplicity. To avoid the only unidirectional information delivery of FT and sufficiently train shallow modules with the deeper ones, we develop a backward training mechanism that makes the former modules perceive the latter modules, inspired by the classical backward propagation algorithm. The backward training introduces the reversed information delivery into the decoupled modules as well as the forward information delivery. To investigate how the decoupling and greedy training affect the representational capacity, we theoretically prove that the error produced by linear modules will not accumulate on unsupervised tasks in most cases. The theoretical and experimental results show that the proposed framework is highly efficient with reasonable performance, which may deserve more investigation.

Green manure removal with reduced nitrogen improves saline-alkali soil organic carbon storage in a wheat-green manure cropping system.

The incorporation of green manure into cropping systems is a potential strategy for sequestering soil carbon (C), especially in saline-alkali soil. Yet, there are still unknown about the substitution impacts of green manure on nitrogen (N) fertilizer in wheat-green manure multiple cropping system. Herein, a five-year field experiment was performed to determine the impact of three levels of N fertilizer inputs [i.e., N fertilizer reduced by 0 % (100N), 10 % (90 N), and 20 % (80 N)] with aboveground biomass of green manure removal (0GM) and return (100GM) on soil organic carbon (SOC) storage and its primary determinants. The results demonstrated that no significant interaction on SOC storage was detected between green manure and N fertilizer management. 80 N enhanced SOC storage in bulk soil by 7.4 and 13.2 % in 0-20 cm soil depth relative to 100 N and 90 N (p < 0.05). Regardless of N fertilizer levels, compared with 100GM, 0GM increased SOC storage in bulk soil by 14.2-34.6 % in 0-40 cm soil depth (p < 0.05). This was explained by an increase in soil macro-aggregates (>2 and 0.25-2 mm) proportion contributing to SOC physical protection. Meanwhile, the improvement of SOC storage under 0GM was due to the decrease of soil C- and N-acquisition enzyme activities, and microbial resource limitation. Alternatively, the variation partitioning analyses (VPA) results further suggested that C- and N-acquisition enzyme activities, as well as microbial resource limitation were the most important factors for SOC storage. The findings highlighted those biological factors played a dominant role in SOC accumulation compared to physical factors. The aboveground biomass of green manure removal with N fertilizer reduced by 20 % is a viable option to enhance SOC storage in a wheat-green manure multiple cropping system.

A novel method for colposcopic shunting in HPV-positive women: Quantitative detection of HPV E7 oncoprotein.

The objective of the study was to evaluate the clinical application potential of quantitatively detecting human papillomavirus (HPV) E7 oncoprotein in HPV-positive women, with the goal of detecting potential high-grade cervical squamous intraepithelial lesions (HSIL) and cervical cancer improving the accuracy of colposcopic shunting in these patients.HPV-positive women (N = 611) were selected for quantitatively detecting HPV E7 protein levels by magnetic particle-based chemiluminescence immunoassay before colposcopy. Receiver operating characteristic (ROC) curve analysis was performed (n = 400) to determine diagnostic detection thresholds for HPV E7 oncoprotein. ThinPrep cytology test (TCT) and Aptima HPV E6/E7 mRNA analysis were also performed (n = 211). The diagnostic performance of these three diagnostic methods in detecting HSIL and cervical cancer was compared with the gold standard of pathological diagnosis. The area under the ROC curve was 0.724. The diagnostic detection threshold of HPV E7 oncoprotein was ≥10.88 ng/mL. The sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV), and Youden index of HPV E7 oncoprotein for the identification of HSIL and cervical cancer were 78.7 %, 77.9 %, 72.2 %, 83.3 %, and 56.6 %, respectively, which were higher than those of TCT and HPV E6/E7 mRNA.The results indicate that quantitative detection of HPV E7 oncoprotein can effectively shunt HPV-positive women and reduce unnecessary colposcopy and biopsy. It can detect potential HSIL and cervical cancer in a timely manner and prevent high-risk patients from missing diagnosis.

Excitation characteristics of circumferential SH guided waves in steel pipes generated by EMATs with few-cycle PPM.

Circumferential Shear Horizontal (CSH) guided waves provide an effective method for detecting defects like axial cracks and corrosion in pipes. Periodic Permanent Magnet Electromagnetic Acoustic Transducers (PPM EMATs) are typically used to generate CSH guided waves. However, there is an offset problem to which little attention has been paid. The offset problem refers to the offset of the center (position of maximum energy) of the operating region caused by the variation in the peak frequency of the spatial spectra of PPM with 2 or fewer cycles. Furthermore, the excitability of guided waves is one of the factors that needs to be considered when selecting the excitation parameters of EMATs, but there are still some studies that have not sufficiently addressed this issue. In this paper, the offset problem and the excitability of CSH guided waves were investigated. Firstly, by obtaining the operating regions corresponding to PPM with different cycles, the cause and influences of the offset problem were studied. The results show that the offset in the peak frequency of the spatial spectrum of PPM is the fundamental reason causing the offset problem, and it not only leads to incorrect prediction of the excitation efficiency of guided waves but also affects the selection of the excitation parameters of EMATs. Secondly, finite element simulations and experiments were performed to assess the influence of the excitability on the excitation efficiency of the CSH0 and CSH1 modes in pipes. By analyzing the simulation and experimental results of 2-cycle PPM, as well as the simulation results for PPM with 1 to 5 cycles, the impact of the excitability on the CSH1 mode was confirmed from two perspectives. The final conclusion indicates that an accurate prediction of the amplitudes of CSH guided waves with different modes is only possible through a comprehensively consideration of the operating region of EMAT and the excitability of guided waves.

A spatially adaptive regularization based three-dimensional reconstruction network for quantitative susceptibility mapping.

Objective.Quantitative susceptibility mapping (QSM) is a new imaging technique for non-invasive characterization of the composition and microstructure ofin vivotissues, and it can be reconstructed from local field measurements by solving an ill-posed inverse problem. Even for deep learning networks, it is not an easy task to establish an accurate quantitative mapping between two physical quantities of different units, i.e. field shift in Hz and susceptibility value in ppm for QSM.Approach. In this paper, we propose a spatially adaptive regularization based three-dimensional reconstruction network SAQSM. A spatially adaptive module is specially designed and a set of them at different resolutions are inserted into the network decoder, playing a role of cross-modality based regularization constraint. Therefore, the exact information of both field and magnitude data is exploited to adjust the scale and shift of feature maps, and thus any information loss or deviation occurred in previous layers could be effectively corrected. The network encoding has a dynamic perceptual initialization, which enables the network to overcome receptive field intervals and also strengthens its ability to detect features of various sizes.Main results. Experimental results on the brain data of healthy volunteers, clinical hemorrhage and simulated phantom with calcification demonstrate that SAQSM can achieve more accurate reconstruction with less susceptibility artifacts, while perform well on the stability and generalization even for severe lesion areas.Significance. This proposed framework may provide a valuable paradigm to quantitative mapping or multimodal reconstruction.

Subsurface organic amendment of a saline soil increases ecosystem multifunctionality and sunflower yield.

Salt stress poses a growing constraint to crop productivity in arid regions globally. Previous evidence indicates that organic amendment is a pivotal management practice for enhancing crop yield and soil fertility in agroecosystems. How organic amendment depth influences the interaction between soil health, ecosystem multifunctionality (EMF), and crop yield, however, still remains unclear. Thus, a 3-year field experiment was carried out to investigate the impacts of surface (0-15 cm) and subsurface (15-30 cm) applications of humic acid and manure on the soil quality index (SQI), enzyme activities, EMF, and crop yield on saline soils. Subsurface organic amendment improved the SQI (at the 0-45 cm layers) by 20-47 %, while the surface amendment improved the SQI at the 0-30 cm layer by 15-51 %. The higher soil quality under subsurface organic amendment was characterized by increases in soil organic carbon and available nutrients, and a decrease in electrical conductivity compared to surface organic amendment. The organic amendment increased microbial diversity and richness, stimulated enzyme activities, and ultimately improved soil EMF. The soil EMF increased by 122-214 % at the 0-30 cm layer under subsurface organic amendment and by only 178 % at the 0-15 cm layer under surface organic amendment. Pairwise comparisons further confirmed that electrical conductivity was negatively, and soil organic carbon positively, correlated with soil ecological functions within the 0-45 cm layer. The higher soil quality and microenvironment with better EMF under subsurface organic amendment increased sunflower yield by 16 % and 8 % as compared to inorganic fertilizer only and surface organic amendment, respectively. This relates to the considerable improvement in soil electrical conductivity, soil organic carbon, ß-glucosidase activity, and diversity and richness of microbial communities resulting from deep organic amendment. Overall, subsurface organic amendment is an effective way to enhance soil EMF and crop yield on saline soils.

BacPE: a versatile prime-editing platform in bacteria by inhibiting DNA exonucleases.

Prime editing allows precise installation of any single base substitution and small insertions and deletions without requiring homologous recombination or double-strand DNA breaks in eukaryotic cells. However, the applications in bacteria are hindered and the underlying mechanisms that impede efficient prime editing remain enigmatic. Here, we report the determination of vital cellular factors that affect prime editing in bacteria. Genetic screening of 129 Escherichia coli transposon mutants identified sbcB, a 3'→5' DNA exonuclease, as a key genetic determinant in impeding prime editing in E. coli, combinational deletions of which with two additional 3'→5' DNA exonucleases, xseA and exoX, drastically enhanced the prime editing efficiency by up to 100-fold. Efficient prime editing in wild-type E. coli can be achieved by simultaneously inhibiting the DNA exonucleases via CRISPRi. Our results pave the way for versatile applications of prime editing for bacterial genome engineering.

Subclinical Keratoconus Detection and Characterization Using Motion-Tracking Brillouin Microscopy.

PURPOSE: To characterize focal biomechanical alterations in subclinical keratoconus (SKC) using motion-tracking (MT) Brillouin microscopy and evaluate the ability of MT Brillouin metrics to differentiate eyes with SKC from normal control eyes. DESIGN: Prospective cross-sectional study. PARTICIPANTS: Thirty eyes from 30 patients were evaluated, including 15 eyes from 15 bilaterally normal patients and 15 eyes with SKC from 15 patients. METHODS: All patients underwent Scheimpflug tomography and MT Brillouin microscopy using a custom-built device. Mean and minimum MT Brillouin values within the anterior plateau region and anterior 150 µm were generated. Scheimpflug metrics evaluated included inferior-superior (IS) value, maximum keratometry (Kmax), thinnest corneal thickness, asymmetry indices, Belin/Ambrosio display total deviation, and Ambrosio relational thickness. Receiver operating characteristic (ROC) curves were generated for all Scheimpflug and MT Brillouin metrics evaluated to determine the area under the ROC curve (AUC), sensitivity, and specificity for each variable. MAIN OUTCOME MEASURES: Discriminative performance based on AUC, sensitivity, and specificity. RESULTS: No significant differences were found between groups for age, sex, manifest refraction spherical equivalent, corrected distance visual acuity, Kmax, or KISA% index. Among Scheimpflug metrics, significant differences were found between groups for thinnest corneal thickness (556 µm vs. 522 µm; P < 0.001), IS value (0.29 diopter [D] vs. 1.05 D; P < 0.001), index of vertical asymmetry (IVA; 0.10 vs. 0.19; P < 0.001), and keratoconus index (1.01 vs. 1.05; P < 0.001), and no significant differences were found for any other Scheimpflug metric. Among MT Brillouin metrics, clear differences were found between control eyes and eyes with SKC for mean plateau (5.71 GHz vs. 5.68 GHz; P < 0.0001), minimum plateau (5.69 GHz vs. 5.65 GHz; P < 0.0001), mean anterior 150 µm (5.72 GHz vs. 5.68 GHz; P < 0.0001), and minimum anterior 150 µm (5.70 GHz vs. 5.66 GHz; P < 0.001). All MT Brillouin plateau and anterior 150 µm mean and minimum metrics fully differentiated groups (AUC, 1.0 for each), whereas the best performing Scheimpflug metrics were keratoconus index (AUC, 0.91), IS value (AUC, 0.89), and IVA (AUC, 0.88). CONCLUSIONS: Motion-tracking Brillouin microscopy metrics effectively characterize focal corneal biomechanical alterations in eyes with SKC and clearly differentiated these eyes from control eyes, including eyes that were not differentiated accurately using Scheimpflug metrics. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Novel Nitrophenyl Substituted Anthranilic Diamide Derivatives: Design, Synthesis, Selectivity, and Antiresistance.

Diamide insecticides have gained popularity due to their high efficacy and low toxicity to nontarget organisms. However, diamide-associated resistance has emerged recently, causing a significant reduction in their potency, thereby hindering sustainable agricultural development. Here, we explored novel diamide insecticide analogs and, using a structure-based approach, rationally designed and synthesized 28 nitrophenyl substituted anthranilic diamides. Most of the compounds showed moderate to good activity against Mythimna separata, Plutella xylostella, and Spodoptera frugiperda. Among them, compounds Ia and Im showed extraordinarily high activity and their mode of action was verified on isolated neurons. Additionally, Im exhibited over 10-fold greater potency than chlorantraniliprole in a HEK293 cell line stably expressing S. frugiperda ryanodine receptors (SfRyRs) containing the resistance mutations, G4891E and I4734M. The binding modes of Im in the SfRyRs were predicted using in silico molecular docking analysis. Our novel nitrophenyl substituted anthranilic diamide derivatives provide valuable insights for the design of insecticidal RyR-targeting compounds to effectively control both wild type and diamide insecticide-resistant lepidopteran pests.

The effect of albumin and hemoglobin levels on the prognosis of early-stage cervical cancer: a prospective, single-center-based cohort study.

BACKGROUND: Serum albumin (ALB) and hemoglobin (HGB) are important serum biochemical indices of the nutritional status of patients and are associated with cancer development. We investigated the relationship between ALB and HGB levels and clinicopathologic characteristics of early-stage cervical cancer to determine the influence of ALB and HGB on the prognosis of early-stage cervical cancer. METHODS: The clinical data of 560 patients with International Federation of Gynaecology and Obstetrics (FIGO, 2009) stage IA1-IIA2 cervical cancer from January 2005 to December 2010 were retrospectively analyzed. The relationship between serum ALB and HGB levels and clinicopathological characteristics of patients were analyzed. The patients were followed-up for 12-138 months. The effects of ALB and HGB levels on the prognosis were analyzed by Cox regression, log-rank test, and the Kaplan-Meier method. RESULTS: The rate of patients with pelvic lymph node metastasis (PLNM), tumor diameter ≥ 4 cm, lymphovascular space invasion (LVSI), and deep stromal invasion was significantly higher in the anemia and hypoalbuminemia group than in the normal group (P < 0.05). The progression-free survival (PFS) and overall survival (OS) of patients in the hypoalbuminemia group and anemia group were significantly lower than that of the normal group (P < 0.05). FIGO stage, tumor diameter, PLNM, depth of stromal invasion, LVSI, the levels of ALB and HGB were risk factors for the prognosis of cervical cancer patients (P < 0.05). CONCLUSION: Patients with hypoproteinemia and anemia in early-stage cervical cancer are more likely to have higher tumor stage, larger tumor size, PLNM, LVSI, and deep stromal invasion. In addition, patients with hypoproteinemia and anemia have a poorer prognosis than those without the condition. Therefore, it is of great significance to detect the ALB and HGB levels of patients and improve the nutritional status of patients in a timely manner for better prognosis of cervical cancer.

Discretize Relaxed Solution of Spectral Clustering via a Nonheuristic Algorithm.

Spectral clustering and its extensions usually consist of two steps: 1) constructing a graph and computing the relaxed solution and 2) discretizing relaxed solutions. Although the former has been extensively investigated, the discretization techniques are mainly heuristic methods, e.g., k -means (KM), spectral rotation (SR). Unfortunately, the goal of the existing methods is not to find a discrete solution that minimizes the original objective. In other words, the primary drawback is the neglect of the original objective when computing the discrete solution. Inspired by the first-order optimization algorithms, we propose to develop a first-order term to bridge the original problem and discretization algorithm, which is the first nonheuristic to the best of our knowledge. Since the nonheuristic method is aware of the original graph cut problem, the final discrete solution is more reliable and achieves the preferable loss value. We also theoretically show that the continuous optimum is beneficial to discretization algorithms though simply finding its closest discrete solution is an existing heuristic algorithm which is also unreliable. Sufficient experiments significantly show the superiority of our method.

Weighted gene co-expression network analysis identified hub genes critical to fatty acid composition in Gushi chicken breast muscle.

BACKGROUND: The composition and content of fatty acids in the breast muscle are important factors influencing meat quality. In this study, we investigated the fatty acid composition and content in the breast muscle of Gushi chickens at different developmental stages (14 weeks, 22 weeks, and 30 weeks). Additionally, we utilized transcriptomic data from the same tissue and employed WGCNA and module identification methods to identify key genes associated with the fatty acid composition in Gushi chicken breast muscle and elucidate their regulatory networks. RESULTS: Among them, six modules (blue, brown, green, light yellow, purple, and red modules) showed significant correlations with fatty acid content and metabolic characteristics. Enrichment analysis revealed that these modules were involved in multiple signaling pathways related to fatty acid metabolism, including fatty acid metabolism, PPAR signaling pathway, and fatty acid biosynthesis. Through analysis of key genes, we identified 136 genes significantly associated with fatty acid phenotypic traits. Protein-protein interaction network analysis revealed that nine of these genes were closely related to fatty acid metabolism. Additionally, through correlation analysis of transcriptome data, we identified 51 key ceRNA regulatory networks, including six central genes, 7 miRNAs, and 28 lncRNAs. CONCLUSION: This study successfully identified key genes closely associated with the fatty acid composition in Gushi chicken breast muscle, as well as their post-transcriptional regulatory networks. These findings provide new insights into the molecular regulatory mechanisms underlying the flavor characteristics of chicken meat and the composition of fatty acids in the breast muscle.

The Foxi3 transcription factor is necessary for the fate restriction of placodal lineages at the neural plate border.

The Foxi3 transcription factor, expressed in the neural plate border at the end of gastrulation, is necessary for the formation of posterior placodes and is thus important for ectodermal patterning. We have created two knock-in mouse lines expressing GFP or a tamoxifen-inducible Cre recombinase to show that Foxi3 is one of the earliest genes to label the border between the neural tube and epidermis, and that Foxi3-expressing neural plate border progenitors contribute primarily to cranial placodes and epidermis from the onset of expression, but not to the neural crest or neural tube lineages. By simultaneously knocking out Foxi3 in neural plate border cells and following their fates, we show that neural plate border cells lacking Foxi3 contribute to all four lineages of the ectoderm - placodes, epidermis, crest and neural tube. We contrast Foxi3 with another neural plate border transcription factor, Zic5, the progenitors of which initially contribute broadly to all germ layers until gastrulation and gradually become restricted to the neural crest lineage and dorsal neural tube cells. Our study demonstrates that Foxi3 uniquely acts early at the neural plate border to restrict progenitors to a placodal and epidermal fate.