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BackgroundSystemic inflammatory response syndrome (SIRS) is a serious postoperative complication among older adult surgical patients that frequently develops into sepsis or even death. Notably, the incidences of SIRS and sepsis steadily increase with age. It is important to identify the risk of postoperative SIRS for older adult patients at a sufficiently early stage, which would allow preemptive individualized enhanced therapy to be conducted to improve the prognosis of older adult patients. In recent years, machine learning (ML) models have been deployed by researchers for many tasks, including disease prediction and risk stratification, exhibiting good application potential. ObjectiveWe aimed to develop and validate an individualized predictive model to identify susceptible and high-risk populations for SIRS in older adult patients to instruct appropriate early interventions. MethodsData for surgical patients aged ≥65 years from September 2015 to September 2020 in 3 independent medical centers were retrieved and analyzed. The eligible patient cohort in the Third Affiliated Hospital of Sun Yat-sen University was randomly separated into an 80% training set (2882 patients) and a 20% internal validation set (720 patients). We developed 4 ML models to predict postoperative SIRS. The area under the receiver operating curve (AUC), F1 score, Brier score, and calibration curve were used to evaluate the model performance. The model with the best performance was further validated in the other 2 independent data sets involving 844 and 307 cases, respectively. ResultsThe incidences of SIRS in the 3 medical centers were 24.3% (876/3602), 29.6% (250/844), and 6.5% (20/307), respectively. We identified 15 variables that were significantly associated with postoperative SIRS and used in 4 ML models to predict postoperative SIRS. A balanced cutoff between sensitivity and specificity was chosen to ensure as high a true positive as possible. The random forest classifier (RF) model showed the best overall performance to predict postoperative SIRS, with an AUC of 0.751 (95% CI 0.709-0.793), sensitivity of 0.682, specificity of 0.681, and F1 score of 0.508 in the internal validation set and higher AUCs in the external validation-1 set (0.759, 95% CI 0.723-0.795) and external validation-2 set (0.804, 95% CI 0.746-0.863). ConclusionsWe developed and validated a generalizable RF model to predict postoperative SIRS in older adult patients, enabling clinicians to screen susceptible and high-risk patients and implement early individualized interventions. An online risk calculator to make the RF model accessible to anesthesiologists and peers around the world was developed.

A new type of porous sound-absorbing sound barrier was developed with quartz sand and self-developed polysiloxane resin. The forming process of the material was studied. The test specimens of the porous sound-absorbing sound barrier were prepared with different mesh numbers of quartz sand and different proportions of resin, and the void properties, compressive strength, durability, and acoustic performance were investigated. Based on the mix design results, it is suggested that 20-mesh quartz sand and a 10:1 mass ratio of quartz sand are used to prepare the porous sound-absorbing sound barrier. The durability study showed that the porous sound-absorbing sound-barrier material had good salt and alkali resistance, poor acid resistance, good water stability, and freeze–thaw stability. The laboratory acoustic test and practical engineering application results showed that the porous sound-absorbing sound barrier had excellent acoustic performance and good noise-reduction effects.

Background: Predicting postoperative pain risk in patients with impacted mandibular third molar extractions is helpful in guiding clinical decision-making, enhancing perioperative pain management, and improving the patients’ medical experience. This study aims to develop a prediction model based on machine learning algorithms to identify patients at high risk of postoperative pain after tooth extraction. Methods: We conducted a prospective cohort study. Outpatients with impacted mandibular third molars were recruited and the outcome was defined as the NRS (Numerical Rating Scale) score of peak postoperative pain within 24 h after the operation ≥7, which is considered a high risk of postoperative pain. We compared the models built using nine different machine learning algorithms and conducted internal and time-series external validations to evaluate the model's predictive performances in terms of the area under the curve (AUC), accuracy, sensitivity, specificity, and F1-value. Results: A total of 185 patients and 202 cases of impacted mandibular third molar data were included in this study. Five modeling variables were screened out using least absolute selection and shrinkage operator regression, including physician qualification, patient self-reported maximum pain sensitivity, OHI–S–CI, BMI, and systolic blood pressure. The overall performance of the random forest model was evaluated. The AUC, sensitivity, and specificity of the prediction model built using the random forest method were 0.879 (0.861–0.891), 0.857, and 0.846, respectively, for the training set and 0.724 (0.673–0.732), 0.667, and 0.600, respectively, for the time series validation set. Conclusions: This study developed a machine learning-based postoperative pain risk prediction model for impacted mandibular third molar extraction, which is promising for providing a theoretical basis for better pain management to reduce postoperative pain after third molar extraction.

Analysis of functional MRI data from the Human Connectome Project reveals the presence of a cortical gradient, which reflects functional topology and links the macroscale functional landscape with mesoscale laminar differentiation principles.

IntroductionPostoperative systemic inflammatory response syndrome (SIRS) is common in surgical patients especially in older patients, and the geriatric population with SIRS is more susceptible to sepsis, MODS, and even death. We aimed to develop and validate a model for predicting postoperative SIRS in older patients.MethodsPatients aged ≥65 years who underwent general anesthesia in two centers of Third Affiliated Hospital of Sun Yat-sen University from January 2015 to September 2020 were included. The cohort was divided into training and validation cohorts. A simple nomogram was developed to predict the postoperative SIRS in the training cohort using two logistic regression models and the brute force algorithm. The discriminative performance of this model was determined by area under the receiver operating characteristics curve (AUC). The external validity of the nomogram was assessed in the validation cohort.ResultsA total of 5,904 patients spanning from January 2015 to December 2019 were enrolled in the training cohort and 1,105 patients from January 2020 to September 2020 comprised the temporal validation cohort, in which incidence rates of postoperative SIRS were 24.6 and 20.2%, respectively. Six feature variables were identified as valuable predictors to construct the nomogram, with high AUCs (0.800 [0.787, 0.813] and 0.822 [0.790, 0.854]) and relatively balanced sensitivity (0.718 and 0.739) as well as specificity (0.718 and 0.729) in both training and validation cohorts. An online risk calculator was established for clinical application.ConclusionWe developed a patient-specific model that may assist in predicting postoperative SIRS among the aged patients.

Background: Blood-brain barrier dysfunction in active multiple sclerosis (MS) lesions leads to pathological changes in the cerebrospinal fluid (CSF). This study aimed to investigate the possible association between routine CSF findings, especially CSF chloride, at the time of the first lumbar puncture and the relapse risk and disability progression of relapsing–remitting MS (RRMS). Methods: This retrospective study included 77 patients with RRMS at the MS Center of our institution from January 2012 to December 2020. The Anderson and Gill (AG) model and Spearman correlation analysis were used to explore predictors of relapse and disability during follow-up. Results: In the multivariate AG model, patients with elevated CSF chloride level (hazard ratio [HR], 1.1; 95% confidence interval [CI]: 1.06–1.22; p = 0.001) had a high risk of MS relapse. Using median values of CSF chloride (123.2 mmol/L) as a cut-off, patients with CSF chloride level ≥ 123.2 mmol/L had a 120% increased relapse risk compared with those with CSF chloride level < 123.2 mmol/L (HR = 2.20; 95% CI: 1.19–4.05; p = 0.012). Conclusions: Elevated CSF chloride levels might be a biologically unfavorable predictive factor for disease relapse in RRMS.

This paper takes the surrounding rock of deep tunnel as the research object and considers the action mechanism under the influence of seepage. Based on the Mohr-Coulomb criterion, the stress mechanism of surrounding rock of deep buried tunnel is analyzed by a convergence constraint method. Based on the elastic-plastic solution, the nonlinear elastic-plastic solution of the interaction between surrounding rock and lining structure considering the effect of seepage force is proposed, and the radius of surrounding rock plastic zone is obtained. The relationship between surrounding rock stress and displacement, radial deformation of lining, and support reaction force was observed. At the same time, considering the effects of seepage, strain softening, and intermediate principal stress, the surrounding rock is divided into a plastic residual zone, plastic softening zone, and elastic zone, and the stress distribution expressions of the plastic zone and each zone of surrounding rock of circular tunnel are derived. The results show that with the change of nonuniform permeability coefficient, the seepage shows anisotropy in different directions, and the closer to the horizontal or vertical direction, the more obvious the influence of nonuniform permeability coefficient on pore water pressure distribution. Seepage and material softening have different effects on the distribution of surrounding rock stress field and the size of plastic zone. Material softening is more unfavorable to the stability of surrounding rock than seepage. The intermediate principal stress coefficient has a significant impact on the tangential stress and plastic zone of surrounding rock. When the intermediate principal stress effect is not considered, the calculation results are relatively conservative and cannot give full play to the strength of surrounding rock effectively. The research conclusion can provide a theoretical reference for studying the stability of surrounding rock in tunnel excavation under water-bearing rock.

Background: Patients with chronic hepatitis B (CHB) with severe acute exacerbation (SAE) are at a progression stage of acute-on-chronic liver failure (ACLF) but uniform models for predicting ACLF occurrence are lacking. We aimed to present a risk prediction model to early identify the patients at a high risk of ACLF and predict the survival of the patient.Methods: We selected the best variable combination using a novel recursive feature elimination algorithm to develop and validate a classification regression model and also an online application on a cloud server from the training cohort with a total of 342 patients with CHB with SAE and two external cohorts with a sample size of 96 and 65 patients, respectively.Findings: An excellent prediction model called the PATA model including four predictors, prothrombin time (PT), age, total bilirubin (Tbil), and alanine aminotransferase (ALT) could achieve an area under the receiver operating characteristic curve (AUC) of 0.959 (95% CI 0.941–0.977) in the development set, and AUC of 0.932 (95% CI 0.876–0.987) and 0.905 (95% CI 0.826–0.984) in the two external validation cohorts, respectively. The calibration curve for risk prediction probability of ACLF showed optimal agreement between prediction by PATA model and actual observation. After predictive stratification into different risk groups, the C-index of predictive 90-days mortality was 0.720 (0.675–0.765) for the PATA model, 0.549 (0.506–0.592) for the end-stage liver disease score model, and 0.648 (0.581–0.715) for Child–Turcotte–Pugh scoring system.Interpretation: The highlypredictive risk model and easy-to-use online application can accurately predict the risk of ACLF with a poor prognosis. They may facilitate risk communication and guidetherapeutic options.

Background: It is often difficult to diagnose pituitary microadenoma (PM) by MRI alone, due to its relatively small size, variable anatomical structure, complex clinical symptoms, and signs among individuals. We develop and validate a deep learning -based system to diagnose PM from MRI.Methods: A total of 11,935 infertility participants were initially recruited for this project. After applying the exclusion criteria, 1,520 participants (556 PM patients and 964 controls subjects) were included for further stratified into 3 non-overlapping cohorts. The data used for the training set were derived from a retrospective study, and in the validation dataset, prospective temporal and geographical validation set were adopted. A total of 780 participants were used for training, 195 participants for testing, and 545 participants were used to validate the diagnosis performance. The PM-computer-aided diagnosis (PM-CAD) system consists of two parts: pituitary region detection and PM diagnosis. The diagnosis performance of the PM-CAD system was measured using the receiver operating characteristics (ROC) curve and area under the ROC curve (AUC), calibration curve, accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1-score.Results: Pituitary microadenoma-computer-aided diagnosis system showed 94.36% diagnostic accuracy and 98.13% AUC score in the testing dataset. We confirm the robustness and generalization of our PM-CAD system, the diagnostic accuracy in the internal dataset was 96.50% and in the external dataset was 92.26 and 92.36%, the AUC was 95.5, 94.7, and 93.7%, respectively. In human-computer competition, the diagnosis performance of our PM-CAD system was comparable to radiologists with >10 years of professional expertise (diagnosis accuracy of 94.0% vs. 95.0%, AUC of 95.6% vs. 95.0%). For the misdiagnosis cases from radiologists, our system showed a 100% accurate diagnosis. A browser-based software was designed to assist the PM diagnosis.Conclusions: This is the first report showing that the PM-CAD system is a viable tool for detecting PM. Our results suggest that the PM-CAD system is applicable to radiology departments, especially in primary health care institutions.

ObjectiveTo explore the outcomes of NMOSD attacks and investigate serum biomarkers for prognosis and severity.MethodPatients with NMOSD attacks were prospectively and observationally enrolled from January 2019 to December 2020 at four hospitals in Guangzhou, southern China. Data were collected at attack, discharge and 1/3/6 months after acute treatment. Serum cytokine/chemokine and neurofilament light chain (NfL) levels were examined at the onset stage.ResultsOne hundred patients with NMOSD attacks were included. The treatment comprised intravenous methylprednisolone pulse therapy alone (IVMP, 71%), IVMP combined with apheresis (8%), IVMP combined with intravenous immunoglobulin (18%) and other therapies (3%). EDSS scores decreased significantly from a medium of 4 (interquartile range 3.0–5.5) at attack to 3.5 (3.0–4.5) at discharge, 3.5 (2.0–4.0) at the 1-month visit and 3.0 (2.0–4.0) at the 3-month visit (p

Abstract Background Glioma accounts for a large proportion of cancer, and an effective treatment for this disease is still lacking because of the absence of specific driver molecules. Current challenges in the treatment of glioma are the accurate and timely diagnosis of brain glioma and targeted treatment plans. To investigate the diagnostic biomarkers and prospective role of miRNAs in the tumorigenesis and progression of glioma, we analyzed the expression of miRNAs and key genes in glioma based on The Cancer Genome Atlas database. Methods Of the 701 cases that were downloaded, five were normal and 696 were glioma. Then, 1626 differentially expressed genes were identified, and 173 aberrantly expressed miRNAs were calculated by edgeR. GO and KEGG pathway enrichment analyses were performed using Cytoscape software. A coexpression network was built by weighted correlation network analysis (WGCNA). A cell scratch test and transwell, cell apoptosis and cell cycle assays were performed to validate the function of hsa-let-7b-5p. Results Based on crosstalk genes in the KEGG, PPI network, and WGCNA analyses, PLK1, CCNA2, cyclin B2 (CCNB2), and AURKA were screened as candidate diagnostic marker genes. The survival analysis revealed that high mRNA expression of PLK1, CCNA2, and AURKA was significantly associated with poor overall survival. Furthermore, hsa-let-7b-5p was identified as a core miRNA in the regulation of candidate genes involved in glioma development. We confirmed that hsa-let-7b-5p could inhibit the migration, invasion, and cell cycle of glioma cells. Conclusions This study provides four potential biomarkers for the diagnosis of glioma, offers a potential explanation of its pathogenesis, and proposes hsa-let-7b-5p as a therapeutic target.

We investigated the growth-promoting mechanism of salt-tolerant plant growth promoting rhizobacteria (ST-PGPR) in wheat under sodium chloride (NaCl) stress by measuring the growth and physiological and biochemical responses of wheat plants inoculated with ST-PGPR under 0–400 mM NaCl. The results showed that ST-PGPR plays a significant role in the growth of wheat under NaCl stress. Under 300 mM NaCl, wheat plants inoculated with the three ST-PGPR strains increased in plant height, root length, dry weight, and fresh weight by 71.21%, 89.19%, 140.94%, and 36.31%, respectively, compared to the control group. The proline and soluble sugar contents of wheat inoculated with Bacillus thuringiensis increased by 38.8% and 21.4%, respectively. The average content of antioxidant enzymes increased by 13.89%, and compared with the control, in wheat inoculated with the three species of ST-PGPR, the average content of ethylene decreased 2.16-fold. In addition, a mathematical model based on the “interaction equation” revealed that the best results of mixed inoculation were due to the complementary strengths of the strains. The analysis of experimental phenomena and data revealed the mechanisms by which Brevibacterium frigoritolerans, Bacillus thuringiensis, and Bacillus velezensis alleviate NaCl stress in wheat: (1) by lowering of osmotic stress, oxidative stress, and ethylene stress in wheat and (2) by using root secretions to provide substances needed for wheat. This study provides a new approach for the comprehensive understanding and evaluation of ST-PGPR as a biological inoculant for crops under salt stress.

BackgroundMarfan syndrome (MFS) and familial non–syndromal thoracic aortic aneurysm and dissection (ns‐TAAD) are genetic aortopathies causing aortic dilatation with increased aortic stiffness. Left ventricular (LV) contractility and ventricular‐vascular coupling index (VVI) were compared between MFS and ns‐TAAD and determinants of VVI were investigated. Methods and ResultsPatients with MFS (M 57, F 47) and ns‐TAAD (M 72, F 39) were studied by echocardiography and compared with controls (M 77, F 71). Aortic geometry, hemodynamics, LV work, LV contractility (end‐systolic elastance [Ees]), and VVI were documented. Aortic sinuses were equally dilated in MFS (19.7±2.4) and ns‐TAAD (19.8±1.8) compared to controls (16.2±1.4 mm·m−2, P

There is no highly effective chemotherapy for malignant gliomas to date. We found that dimethylaminomicheliolide (DMAMCL), a selective inhibitor of acute myeloid leukemia (AML) stem/progenitor cells, inhibited the growth of glioma cells.The distribution of DMAMCL in brain was analyzed by an ultraperformance liquid chromatography-mass spectrometry (UPLC-MS/MS) system. The anti-tumor evaluations of DMAMCL in vitro were performed by MTT, FACS and RT-PCR. In vivo, the mixture of C6 cells and matrigel was injected into caudatum, and the anti-tumor activity of DMAMCL was evaluated by tumor growth and rat survival. The toxicity of DMAMCL was evaluated by body weight, daily food intake, hematological or serum biochemical analyses, and histological appearance of tissues.The IC50 values of DMAMCL against the C6 and U-87MG cell lines in vitro were 27.18 ± 1.89 μM and 20.58 ± 1.61 μM, respectively. DAMMCL down-regulated the anti-apoptosis gene Bcl-2 and increased apoptosis in C6 and U-87MG cells in a dose-dependent manner. In a C6 rat tumor model, daily administration of DMAMCL for 21 days reduced the burden of C6 tumors by 60% to 88% compared to controls, and more than doubled the mean lifespan of tumor-bearing rats. Distribution analysis showed that the DMAMCL concentration was higher in the brain than in plasma. Evaluations for toxicity revealed that oral administration of DMAMCL at 200 or 300 mg/kg once a day for 21 days did not result in toxicity.These results suggest that DMAMCL is highly promising for the treatment of glioma.

Abstract Background Boron (B) is an essential micronutrient for plants. Inappropriate B supply detrimentally affects the productivity of numerous crops. Understanding of the molecular responses of plants to different B supply levels would be of significance in crop improvement and cultivation practices to deal with the problem. Results We conducted a comprehensive analysis of the transcriptome and proteome of tobacco seedlings to investigate the expression changes of genes/proteins in response to different B supply levels, with a particular focus on B deficiency. The global gene and protein expression profiles revealed the potential mechanisms involved in the responses of tobacco to B deficiency, including up-regulation of the NIP5;1-BORs module, complex regulation of genes/proteins related to cell wall metabolism, and up-regulation of the antioxidant machinery. Conclusion Our results demonstrated that B deficiency caused severe morphological and physiological disorders in tobacco seedlings, and revealed dynamic expression changes of tobacco genes/proteins in response to different B supply levels, especially to B deficiency, thus offering valuable insights into the molecular responses of tobacco to B deficiency.

Summary: Familial hypercholesterolemia (FH) is a genetic disorder that affects 1 in 300 people, leading to high cholesterol levels and significantly increased cardiovascular risk. The limitations of existing FH treatments underscore the need for innovative therapeutics, and gene therapy offers a promising alternative to address FH more effectively. In this review, we survey approved gene therapy drugs first and then delve into the landscape of gene addition, gene inactivation, and gene editing therapies for hypercholesterolemia, highlighting both approved interventions and those in various stages of development. We also discussed recent advancements in gene editing tools that are essential for their application in gene therapy. Safety considerations inherent to gene therapy are also discussed, emphasizing the importance of mitigating potential risks associated with such treatments. Overall, this review highlights the progress and prospects of gene therapies for FH treatments, underscoring their potential to revolutionize the management of this prevalent and challenging condition.

Abstract Background The association between body mass index (BMI) and dementia risk differs depending on follow-up time and age at BMI measurement. The relationship between BMI trajectories in late-middle age (50–65 years old) and the risk of dementia in older age (> 65 years old) has not been revealed. Methods In the present study, participants from the Health and Retirement Study were included. BMI trajectories were constructed by combining BMI trend and variation information. The association between BMI trajectories at the age of 50–65 years and dementia risk after the age of 65 years was investigated. Participants with European ancestry and information on polygenic scores for cognitive performance were pooled to examine whether genetic predisposition could modify the association. Results A total of 10,847 participants were included in the main analyses. A declining BMI trend and high variation in late-middle age were associated with the highest subsequent dementia risk in older age compared with an ascending BMI trend and low variation (RR = 1.76, 95% CI = 1.45–2.13). Specifically, in stratified analyses on BMI trajectories and dementia risk based on each individual's mean BMI, the strongest association between a declining BMI trend with high variation and elevated dementia risk was observed in normal BMI group (RR = 2.66, 95% CI = 1.72–4.1). Similar associations were found when participants were stratified by their genetic performance for cognition function without interaction. Conclusions A declining BMI trend and high variation in late-middle age were associated with a higher risk of dementia. Early monitoring of these individuals is needed to prevent dementia in older individuals.

Abstract Background Immense attention has been given to the outcome of COVID-19 infection. However, comprehensive studies based on large populational cohort with long-term follow-up are still lacking. This study aimed to investigate the risk of various short-term comorbidities (within one month) and long-term sequelae (above one month) after COVID-19 infection. Methods In this large prospective cohort study with 14 months follow-up information based on UK biobank, we included 16,776 COVID-19-positive participants and 58,281 COVID-19-negative participants matched for comparison. The risk of each comorbidity and sequela was evaluated by multivariable logistic regression analysis and presented as hazard ratio (HR) and 95% confidence interval (95% CI). Results COVID-19-positive individuals had a higher risk of 47 types of comorbidities within one month following COVID-19 infection, especially those who were older, male, overweight/obese, ever-smoked, with more pre-existing comorbidities and hospitalized. About 70.37% of COVID-19 patients with comorbidities had more than one co-occurring comorbidities. Additionally, only 6 high-risk sequelae were observed after one month of COVID-19 infection, and the incidence was relatively low (

Abstract Overproduction of reactive oxygen species (ROS) and aberrant lipid metabolism are established hallmarks of cancer; however, the role of ROS in lipid synthesis during tumorigenesis is almost unknown. Herein, we show that ROS regulates lipid synthesis and thus controls colorectal tumorigenesis through a p53-dependent mechanism. In p53 wild-type colorectal cancer (CRC) cells, hydrogen peroxide (H2O2)-induced p53 expression represses the transcription of deubiquitinase USP22, which otherwise deubiquitinates and stabilizes Fatty Acid Synthase (FASN), and thus inhibits fatty acid synthesis. Whereas, in p53-deficient CRC cells, ROS-mediated inhibition of USP22 is relieved, leading to FASN stabilization, which thus promotes lipid synthesis and tumor growth. In human CRC specimens, USP22 expression is positively correlated with FASN expression. Our study demonstrates that ROS critically regulates lipid synthesis and tumorigenesis through the USP22-FASN axis in a p53-dependent manner, and targeting the USP22-FASN axis may represent a potential strategy for the treatment of colorectal cancer.

Based on the distant hybridization derived from Hypophthalmichthys nobilis (bighead carp, BIC, 2n ​= ​48) (♀) ​× ​Megalobrama amblycephala (blunt snout bream, BSB, 2n ​= ​48) (♂), we obtained a novel hybrid (BB) in this study. We comparatively investigated the morphological traits, chromosome numbers, DNA contents, microsatellite patterns, and DNA variations in 5S rDNA and Hox genes. The chromosome and flow cytometer results indicated that BB was a diploid hybrid with 48 chromosomes. We confirmed successful hybridization with microsatellite DNA markers and analyzed the Hox gene family in the parental and hybrid lines. The sequences of 5S rDNA in BB mapped to those in BIC and BSB, indicating that the genetic materials of BB were derived from BIC and BSB. The breeding experiment showed that BB had the characteristics of herbivore and fast growth. This diploid hybrid is of great significance for fish genetic breeding and applied research.

The red swamp crayfish (Procambarus clarkii) is a well-known invasive species. It has become one of the most important freshwater aquaculture resources in China. In this study, we reported the karyotype and whole mitochondrial genome of Procambarus clarkii. In addition, we performed transcriptome analysis of Procambarus clarkii from two different body size populations. The three large individuals, namely, the LS group, were randomly chosen, with body lengths and weights of 16.24–18.85 ​cm and 38.96–45.36 ​g, respectively. The three small individuals, namely, the SS group, were randomly chosen, with body lengths and weights of 10.50–12.70 ​cm and 19.56–25.95 ​g, respectively. Comparative transcriptomic analysis of Procambarus clarkii characterized 36 differentially expressed genes (DEGs), comprising 20 upregulated genes and 16 downregulated genes in the SS group. Functional analyses revealed that four genes (metalloreductase STEAP4-like (Steap4), myosin heavy chain fast skeletal muscle, muscle-like (MH), vitelline membrane outer layer protein I-like protein (VMO-I), and secreted protein acidic and rich in cysteine (SPARC)) were involved in the regulation of cell proliferation, muscle growth and energy metabolism, suggesting that four genes were related to growth in P. clarkii. We validated the expression levels of these four differentially expressed genes in LS and SS using Quantitative real-time PCR. These results provide insights into the regulatory mechanisms underlying the difference in P. clarkii growth.

BackgroundThe current American Joint Committee on Cancer (AJCC) system only considered the importance of the size and laterality of lymph nodes while not the positive lymph node number (PLNN) for hypopharyngeal squamous cell carcinoma (HPSCC).MethodsA total of 973 patients with HPSCC from the Surveillance, Epidemiology, and End Results database (2004–2015) were identified. Univariate and multivariate Cox regression analyses were used to evaluate the prognostic effects. We applied six Cox regression models to compare the survival prognostic values of PLNN and AJCC systems.ResultsPositive lymph node number showed a significant association with overall survival (OS) and cancer-specific survival (CSS) (P < 0.001) in univariate and multivariable analyses. The increased PLNN of HPSCC gave rise to poor OS and CSS. The survival model incorporating a composite of PLNN and TNM classification (C-index for OS:0.682, C-index for CSS:0.702) performed better than other models.ConclusionsA positive lymph node number could serve as a survival predictor for patients with HPSCC and a complement to enhance the prognostic assessment effects of TNM cancer staging systems.

Abstract Background Hox transcription factors are master regulators of animal development. Although highly conserved, they can contribute to the formation of novel biological characteristics when modified, such as during the generation of hybrid species, thus potentially serving as species-specific molecular markers. Here, we systematically studied the evolution of genomic sequences of Hox loci in an artificial allotetraploid lineage (4nAT, 4n = 200) derived from a red crucian carp (♀, RCC, 2n = 100) × common carp (♂, CC, 2n = 100) cross and its parents (RCC and CC). Results PCR amplification yielded 23 distinct Hox gene fragments from 160 clones in 4nAT, 22 fragments from 90 clones in RCC, and 19 fragments from 90 clones in CC. Sequence alignment of the HoxA3a and HoxC10a genes indicated both the inheritance and loss of paternal genomic DNA in 4nAT. The HoxA5a gene from 4nAT consisted of two subtypes from RCC and two subtypes from CC, indicating that homologous recombination occurred in the 4nAT hybrid genome. Moreover, 4nAT carried genomic pseudogenization in the HoxA10b and HoxC13a loci. Interestingly, a new type of HoxC9a gene was found in 4nAT as a hybrid sequence of CC and RCC by recombination in the intronic region. Conclusion The results revealed the influence of Hox genes during polyploidization in hybrid fish. The data provided insight into the evolution of vertebrate genomes and might be benefit for artificial breeding programs.