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In vertebrates, maternally supplied yolk is typically used in one of two ways: either intracellularly by endodermal cells or extracellularly via the yolk sac. This study delves into the distinctive gut development in sturgeons, which are among the most ancient extant fish groups, contrasting it with that of other vertebrates. Our observations indicate that while sturgeon endodermal cells form the archenteron (i.e., the primitive gut) dorsally, the floor of the archenteron is uniquely composed of extraembryonic yolk cells (YCs). As development progresses, during neurulation, the archenteric cavity inflates, expands laterally, and roofs a semicircle of YCs. By the pharyngula stage, the cavity fully encompasses the YC mass, which begins to be digested at the hatching stage. This suggests a notable deviation in sturgeon gut development from that in other vertebrates, as their digestive tract initiates its function by processing endogenous nutrition even before external feeding begins. Our findings highlight the evolutionary diversity of gut development strategies among vertebrates and provide new insights into the developmental biology of sturgeons.

In order to analyze the effects of tea saponin (TS) on soy hydrolyzed peptide (SHP) structure and functional properties in SHP-TS complex, comparative analysis SHP and TS were 1:0, 1:0.5, 1:1, 1:2 (w/w) respectively. The Fourier transformed infrared spectrum, fluorescence spectrum and UV-visible absorption spectrum were used to characterize the spatial structural changes of the protein in the SHP-TS complex and to clarify the relationship between SHP conformational changes and functional properties in the complex. The results showed that the addition of TS could change the secondary structure of SHP, and the hydrogen bond was involved in the formation of the SHP-TS complex. SHP strongly interacted with TS and the spatial conformation changes. In addition, the more TS content increased, the more emulsifying and antioxidant properties of the complex were enhanced, the mean of particle size first decreased and then increased, and the absolute value of the ζ-potential first increased and then decreased. When the SHP:TS ratio was 1:1 (w/w), an excellent comprehensive SHP-TS complex was obtained. Compared with the single SHP system, the emulsion stability coefficient of the complex was the highest at this time. The mean particle size of the emulsion was the smallest and the absolute value of the ζ-potential was the highest. This study would provide a theoretical basis for the development of new emulsifiers in the food industry.

Abstract Obesity, a worldwide epidemic in recent years, is mainly due to the uncontrolled development of adipose tissues, which includes adipocyte hypertrophy and hyperplasia. Adipocyte differentiation is a process involving multiple transcription factor cascades, and the exact mechanism has not yet been defined. As a bHLH transcription factor, Twist1 exerts its activity by forming homo- or heterodimers with other factors. In this study, we showed Twist1 restricts adipogenesis through PPARγ. Expression of various differentiation markers (including PPARγ and adiponectin) and triglyceride-containing lipid droplets were decreased with overexpression of Twist1. Pathway enrichment analysis of RNA-seq data showed that differentially expressed genes (DEGs) caused by Twist1 overexpression were significantly related to lipolysis and PPARγ signaling. This implicates that Twist1 plays important regulatory roles in these processes. ChIP and dual luciferase assays showed that Twist1 could bind either PPARγ or adiponectin promoter to repress their respective transcription or directly to PPARγ protein to regulate its transcriptional activity. Furthermore, Twist1 directly interacted RXRα, which usually forms heterodimer with PPARγ to regulate adipogenesis. Taken together, our results suggest that Twist1 is an inhibitory modulator of adipogenesis and its function is likely through direct interaction with PPARγ protein or its gene promoter.

Abstract An important challenge in genetics, evolution and biotechnology is to understand and predict how mutations combine to alter phenotypes, including molecular activities, fitness and disease. In diploids, mutations in a gene can combine on the same chromosome or on different chromosomes as a “heteroallelic combination”. However, a direct comparison of the extent, sign, and stability of the genetic interactions between variants within and between alleles is lacking. Here we use thermodynamic models of protein folding and ligand-binding to show that interactions between mutations within and between alleles are expected in even very simple biophysical systems. Protein folding alone generates within-allele interactions and a single molecular interaction is sufficient to cause between-allele interactions and dominance. These interactions change differently, quantitatively and qualitatively as a system becomes more complex. Altering the concentration of a ligand can, for example, switch alleles from dominant to recessive. Our results show that intra-molecular epistasis and dominance should be widely expected in even the simplest biological systems but also reinforce the view that they are plastic system properties and so a formidable challenge to predict. Accurate prediction of both intra-molecular epistasis and dominance will require either detailed mechanistic understanding and experimental parameterization or brute-force measurement and learning.

Summary: Background: Molecular diagnosis is crucial for biomarker-assisted glioma resection and management. However, some limitations of current molecular diagnostic techniques prevent their widespread use intraoperatively. With the unique advantages of ultrasound, this study developed a rapid intraoperative molecular diagnostic method based on ultrasound radio-frequency signals. Methods: We built a brain tumor ultrasound bank with 169 cases enrolled since July 2020, of which 43483 RF signal patches from 67 cases with a pathological diagnosis of glioma were a retrospective cohort for model training and validation. IDH1 and TERT promoter (TERTp) mutations and 1p/19q co-deletion were detected by next-generation sequencing. We designed a spatial–temporal integration model (STIM) to diagnose the three molecular biomarkers, thus establishing a rapid intraoperative molecular diagnostic system for glioma, and further analysed its consistency with the fifth edition of the WHO Classification of Tumors of the Central Nervous System (WHO CNS5). We tested STIM in 16-case prospective cohorts, which contained a total of 10384 RF signal patches. Two other RF-based classical models were used for comparison. Further, we included 20 cases additional prospective data for robustness test (ClinicalTrials.gov NCT05656053). Findings: In the retrospective cohort, STIM achieved a mean accuracy and AUC of 0.9190 and 0.9650 (95% CI, 0.94–0.99) respectively for the three molecular biomarkers, with a total time of 3 s and a 96% match to WHO CNS5. In the prospective cohort, the diagnostic accuracy of STIM is 0.85 ± 0.04 (mean ± SD) for IDH1, 0.84 ± 0.05 for TERTp, and 0.88 ± 0.04 for 1p/19q. The AUC is 0.89 ± 0.02 (95% CI, 0.84–0.94) for IDH1, 0.80 ± 0.04 (95% CI, 0.71–0.89) for TERTp, and 0.85 ± 0.06 (95% CI, 0.73–0.98) for 1p/19q. Compared to the second best available method based on RF signal, the diagnostic accuracy of STIM is improved by 16.70% and the AUC is improved by 19.23% on average. Interpretation: STIM is a rapid, cost-effective, and easy-to-manipulate AI method to perform real-time intraoperative molecular diagnosis. In the future, it may help neurosurgeons designate personalized surgical plans and predict survival outcomes. Funding: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

BackgroundDifferent intratumoral microbiotaexist in different tumors and play a crucial function in carcinogenesis. However, whether they impact clinical outcomes in esophageal squamous cell carcinoma (ESCC) and their mechanism remain unclear.Methods16S rDNA amplicon sequencing was performed on surgically resected samples from 98 ESCC patients to analyze intratumoral microbiome abundance and composition. Multiplex fluorescent immunohistochemistry staining was used to profile the phenotypes of immune infiltrates in the tumor microenvironment (TME).ResultsPatients with higher intratumoral Shannon index had significantly worse surgical outcomes. When patients were divided into short-term survivors and long-term survivors based on the median survival time, both intratumoral alpha-diversity and beta-diversity were found to be significantly inconsistent, and the relative abundance of Lactobacillus and Leptotrichia emerged as the two microorganisms that probably influenced the survival of ESCC patients. Only Lactobacillus in ESCC was validated to significantly worsen patients’ prognoses and to be positively correlated with the Shannon index. Multivariate analysis revealed that the intratumoral Shannon index, the relative abundance of Lactobacillus, and the pathologic tumor–node–metastasis (pTNM) stage were independently associated with patients’ overall survival. Furthermore, the relative abundance of both Lactobacillus and Shannon index was positively correlated with the proportions of PD-L1+ epithelial cells (ECs) and tumor-associated macrophages (TAMs). The Shannon index was negatively correlated with the proportions of natural killer (NK) cells in the TME.ConclusionsA high abundance of intratumoral Lactobacillus and bacterial alpha-diversity was associated with the formation of the immunosuppressive TME and predicted poor long-term survival in ESCC patients.

Abstract Fine‐grained visual categorization (FGVC) is a challenging task, facing the issues such as inter‐class similarities, large intra‐class variances, scale variation, and angle variation. To address these issues, the authors propose a novel multiscale attention dynamic aware network (MADA‐Net). The core of network consists of three parallel sub‐networks, which learn features from different scales. Each sub‐network is composed of three serial sub‐modules: (1) A self‐attention module (SAM) locates objects according to relative importance scattered throughout feature map. (2) A multiscale feature extractor (MFE) learns the non‐linear features of objects. (3) A dynamic aware module (DAM) enhances the learning capability of spatial deformation of the network to generate high‐quality feature map. In addition, the authors propose a multiscale adjusted loss (MA‐Loss) to improve the performance of network. Experiments on three prevailing benchmark datasets demonstrate that our method can achieve state‐of‐the‐art performance.

BackgroundCNS tumors, particularly gliomas, are associated with a high rate of disability and lethality, and are typically diagnosed with histopathology and immunohistochemistry. Our research aims to develop a minimally invasive method for diagnosing, grading and molecular typing glioma.MethodsWe collected patients who underwent surgery for glioma, Trigeminal neuralgia/Hemifacial spasm, schwannoma, pituitary adenomas and meningioma at our hospital from June 2019 to June 2021. Preoperative WBCs, neutrophils, lymphocytes, monocytes, platelet counts and albumin levels were collected. Preoperative NLR, dNLR, PLR, LMR and PNI were calculated, and the correlation between them and glioma diagnosis as well as grading was analyzed. We also evaluated the diagnostic significance of NLR, dNLR, PLR, LMR, PNI and their combinations for gliomas, particularly GBM, as well as the diagnostic significance of IDH molecular typing of gliomas.ResultsThere were 182 healthy samples and 3101 diseased samples in our study. Compared with other groups, glioma patients had significantly higher preoperative NLR, dNLR and PLR values, but lower LMR and PNI values. Further analysis showed that NLR, dNLR, and PLR were positively correlated with glioma grading, while LMR and PNI were negatively correlated with glioma grading. For the diagnosis of glioma, NLR showed a maximum AUC value of 0.8099 (0.7823-0.8374). For GBM, NLR showed a maximum AUC value of 0.9585 (0.9467-0.9703). In the combination, NLR+dNLR showed the highest AUC value of 0.8070(0.7849-0.8291). NLR showed significant statistical significance in all grades of glioma IDH molecular typing, while PLR did not show statistical significance.ConclusionsNLR has the greatest value for the diagnosis, differential diagnosis, grading and molecular typing of gliomas. The NLR+dNLR combination also showed high sensitivity and specificity. We believe that inflammatory parameters may serve as economical and specific markers for glioma diagnosis, grading, molecular typing, and progression.

Common carp (Cyprinus carpio) is the fourth most-produced fish species in aquaculture and frequently used model species with significant effort invested in development of biotechnological applications. In present study, we attempted to establish an in vitro germ cell culture condition for short term cell culture, which could facilitate further applications such as surrogacy or gene manipulation. Basal media and different types of feeder cells were investigated to optimize carp germ cell culture condition to favor maintenance of mitotic proliferation. Results indicated that germ cells cultured with hESC media and RTG2 cell line as feeder possessed significantly higher proliferation and survival rate compared to that cultured with StemPro media and Sertoli cell line as feeder. In addition, we compared two dissection strategies to compare risk of cell culture contamination and body cavity was open from dorsal part or from ventral part. As a result, carp open from the dorsal side can minimize the risk of contamination. In summary, this is the first study to optimize the cultivation of germ cells in common carp. This opens up new opportunities for the application of specific techniques in the breeding of those species with high commercial value and frequent use as a model fish. Results obtained in this study are important for implementation of new strategies in common carp breeding, conservation of genetic resources, restoration of lines or development of clonal and isogenic carp lines.

Abstract Background Berberine and Bifidobacterium have been reported to improve glucose tolerance in people with hyperglycemia or other metabolic disorders. This study aimed to assess the hypoglycemic effect and the regulation of the gut microbiota caused by berberine and Bifidobacterium and the possible additive benefits of their combination. Methods This was an 18-week, multi-center, randomized, double-blind, parallel-controlled study of patients newly diagnosed with hyperglycemia. After a 2-week run-in period, 300 participants were randomly assigned to the following four groups for 16 weeks of treatment: berberine (Be), Bifidobacterium (Bi), berberine and Bifidobacterium (BB), and placebo group. The primary efficacy endpoint was the absolute value of fasting plasma glucose (FPG) compared with baseline after 16 weeks of treatment. Results Between October 2015 and April 2018, a total of 297 participants were included in the primary analysis. Significant reductions of FPG were observed in the Be and BB groups compared with the placebo group, with a least square (LS) mean difference of − 0.50, 95% CI [− 0.85, − 0.15] mmol/L, and − 0.55, 95% CI [− 0.91, − 0.20] mmol/L, respectively. The Be and BB groups also showed significant reductions in 2-h postprandial plasma glucose. A pronounced decrease in HbA1c occurred in the BB group compared to the placebo group. Moreover, compared with the Bi and placebo groups, the Be and BB groups had more changes in the gut microbiota from the baseline. Conclusions Berberine could regulate the structure and function of the human gut microbiota, and Bifidobacterium has the potential to enhance the hypoglycemic effect of berberine. These findings provide new insights into the hypoglycemic potential of berberine and Bifidobacterium. Trial registration ClinicalTrials.gov , NCT03330184. Retrospectively registered on 18 October 2017

Post-translational modifications of tubulins regulate microtubule properties and neural development. Here, the authors report that one such post-translational modification, α-TubK40me3, is required for neuronal polarization and migration by promoting microtubule formation.

Alkaline pH can induce triacylglyceride accumulation in microalgae, however its molecular mechanism remains elusive. Here, we investigated the effect of 2-[N-cyclohexylamino]-ethane-sulfonic acid (CHES) -induced intracellular alkalization on the lipid production in Phaeodactylum tricornutum. Intracellular pH was increased upon CHES treatment, displaying a high BCECF fluorescence ratio. CHES treatment significantly induced lipid accumulation but had no change in cell density and biomass. The expression of genes involved in photoreaction, carbon fixation, glycolysis, pentose phosphate pathway, amino acid catabolism, GS/GOGAT cycle, TCA cycle, triacylglyceride assembly, de novo fatty acid synthesis were up-regulated, while that in amino acid biosynthesis were down-regulated under CHES conditions. Correspondingly, the activity of phosphoribulokinase, carbonic anhydrase, pyruvate dehydrogenase and acetaldehyde dehydrogenase were enhanced by CHES treatment. Chloroplast-specific biological processes were activated by CHES treatment in P. tricornutum, which redirects the flux of carbon into lipid biosynthesis, meanwhile stimulates de novo fatty acid biosynthesis, leading to lipid accumulation under CHES conditions. These indicate an enhancement of intermediate metabolism, resulting in lipid accumulation by CHES.

Understanding changes in urban internal structure and land surface temperature (LST) is essential. The local climate zone (LCZ) scheme has been extensively applied to characterize urban spatial structure, which has potential for urban climate research. We combined optical imagery and synthetic aperture radar (SAR) data (Landsat-5 and PALSAR for 2008; Sentinel-2 and PALSAR-2 for 2020) to map the LCZs in Shanghai, China. The results showed that the areas of open high-rise and open mid-rise buildings significantly increased from 2008 to 2020. Then, we investigated the spatiotemporal variations in LST based on the LCZ data from 2008 to 2020 using the grid method. The mean daytime LST (obtained from Landsat-5 and Landsat-8) was higher in 2020 than in 2008 for each LCZ type in spring. The mean daytime LSTs of compact mid-rise, compact low-rise, large low-rise and heavy industry zones were higher than those of other LCZ types in spring and summer. The mean nighttime LST (obtained from ASTER) in the downtown area was higher than that in the suburbs in summer. Furthermore, the mean nighttime LST of the built types was also generally higher than that of the natural types in summer. A comparison of the mean daytime LSTs in 2008 and 2020 revealed that the expansion trend of the higher LST areas in spring and summer is consistent with the expansion areas of the mid-rise and high-rise built types.

The study investigated the extrusion modification of wheat bran and its effects on structural and rheological properties of wheat flour dough. Extruded bran showed better solubility of dietary fiber and structural porosity, leading to higher hydration and swelling power. Addition of extruded bran to dough caused water redistribution as an intensive aggregation of bound water to gluten matrix with reduced mobility. The bran–gluten interaction influenced by water sequestering caused partial gluten dehydration and conversion of β-turn into β-sheet, which demonstrated the formation of a more polymerized and stable gluten network. Farinographic data confirmed the promotion of dough stability with extruded bran addition at lower gluten content, while viscoelastic data suggested improved dough elasticity at all gluten contents by increasing elastic moduli and decreasing loss tangent. This study would be useful for interpreting the modification effect and mechanism of extrusion on cereal brans and provide valuable guidance for applying it as an effective modification technology on the commercial production of cereal bran and its flour products.

N6-methyladenosine (m6A) RNA methylation is an epigenetic modification that has emerged in the last few years and has received increasing attention as the most abundant internal RNA modification in eukaryotic cells. m6A modifications affect multiple aspects of RNA metabolism, and m6A methylation has been shown to play a critical role in the progression of multiple cancers through a variety of mechanisms. This review summarizes the mechanisms by which m6A RNA methylation induced peripheral cancer cell progression and its potential role in the infiltration of immune cell of the glioblastoma microenvironment and novel immunotherapy. Assessing the pattern of m6A modification in glioblastoma will contribute to improving our understanding of microenvironmental infiltration and novel immunotherapies, and help in developing immunotherapeutic strategies.

The lymphatic system is an important part of the circulatory system, as an auxiliary system of the vein, which has the functions of immune defense, maintaining the stability of the internal environment, and regulating the pressure of the tissue. It has long been thought that there are no typical lymphatic vessels consisting of endothelial cells in the central nervous system (CNS). In recent years, studies have confirmed the presence of lymphatic vessels lined with endothelial cells in the meninges. The periventricular meninges of the CNS host different populations of immune cells that affect the immune response associated with the CNS, and the continuous drainage of interstitial and cerebrospinal fluid produced in the CNS also proceeds mainly by the lymphatic system. This fluid process mobilizes to a large extent the transfer of antigens produced by the CNS to the meningeal immune cells and subsequently to the peripheral immune system through the lymphatic network, with clinically important implications for infectious diseases, autoimmunity, and tumor immunology. In our review, we discussed recent research advances in intracranial lymphatic circulation and the pathogenesis of its associated diseases, especially the discovery of meningeal lymphatic vessels, which has led to new therapeutic targets for the treatment of diseases associated with the intracranial lymphatic system.

Abstract China's food industry is a large energy consumer and carbon emitter due to its huge scale, so it cannot be ignored if China wants to achieve the goals of energy conservation, emission reduction, and clean production. It is necessary to conduct an in‐depth analysis of the energy environment efficiency of the industry. This paper measures the total‐factor energy environment efficiency (TFEEE) of China's food industry and calculates its energy‐saving and CO2 emission‐reduction potential. A method that combines the slacks‐based measure (SBM) model with meta‐frontier technology is adopted, which considers the heterogeneity of production between regions while dealing with the undesirable output (CO2 emissions). This method is used to calculate the energy environment efficiency of each province based on the group frontier (GTFEEE) and the meta‐frontier (MTFEEE). Through the difference between these two efficiencies, the energy‐saving potential is further decomposed into energy saving from management efficiency improvement and energy saving from technology catch‐up. The results show that, overall, the energy environment efficiency of China's food industry is low, and there are obvious technology gaps between regions. In 2013, the energy‐saving potential of China's food industry reached 49.28 million tce, accounting for 60.7% of the industry's energy consumption that year. Among them, 76% came from the improvement of management efficiency. And the CO2 emission‐reduction potential was 154.6 million tons. Finally, targeted energy saving and emission reduction recommendations were put forward.

Sturgeons are among the most ancient linages of actinopterygians. At present, many sturgeon species are critically endangered. Surrogate production could be used as an affordable and a time-efficient method for endangered sturgeons. Our study established a method for identifying and isolating type A spermatogonia from different developmental stages of testes using flow cytometric cell sorting (FCM). Flow cytometric analysis of a whole testicular cell suspension showed several well-distinguished cell populations formed according to different values of light scatter parameters. FCM of these different cell populations was performed directly on glass slides for further immunocytochemistry to identify germ cells. Results showed that the cell population in gate P1 on a flow cytometry plot (with high forward scatter and high side scatter parameter values) contains the highest amount of type A spermatogonia. The sorted cell populations were characterized by expression profiles of 10 germ cell specific genes. The result confirmed that setting up for the P1 gate could precisely sort type A spermatogonia in all tested testicular developmental stages. The P2 gate, which was with lower forward scatter and side scatter values mostly, contained type B spermatogonia at a later maturing stage. Moreover, expressions of plzf, dnd, boule, and kitr were significantly higher in type A spermatogonia than in later developed germ cells. In addition, plzf was firstly found as a reliable marker to identify type A spermatogonia, which filled the gap of identification of spermatogonial stem cells in sterlet. It is expected to increase the efficiency of germ stem cell culture and transplantation with plzf identification. Our study thus first addressed a phenotypic characterization of a pure type A spermatogonia population in sterlet. FCM strategy can improve the production of sturgeons with surrogate broodstock and further the analysis of the cellular and molecular mechanisms of sturgeon germ cell development.

To study the nonlinear vibration behaviors of rotor system coupled with floating raft-airbag-displacement restrictor under ship heaving motion, the dynamic model is established considering the effect of heaving motion, its steady-state responses are numerically obtained using Runge-Kutta method and the results are surveyed by tools such as the spectrum waterfall diagram, time-domain response, frequency-domain response, axis orbit, and Poincaré map. The effects of rotating speed, ship heaving amplitude, and its frequency on the nonlinear dynamic behavior of the system are mainly studied. The results show that the responses of the rotor and raft are of obvious nonlinear behaviors such as amplitude jumping, bifurcation, and chaos due to the effects of nonlinear oil film force and ship heaving motion. With the increase of rotating speed, the motion of rotor and raft presents quasi-periodic and chaotic vibrations. Ship heaving amplitude and its frequency all have great effect on the vibration of rotor and raft; as heaving amplitude or frequency increases, the motion state of rotor and raft changes, and the amplitude of raft increases significantly. The displacement restrictor can effectively limit the vibrating displacements of the raft when ship heaving amplitude or its frequency is large.

Kinetic data reporting the rate of electron transfer across an electrified interface are of fundamental as well as practical importance. They report the electric current caused by coupling the flow of electrons inside the electronically conducting electrode and the flow of ions in the adjacent ionically conducting phase. At equilibrium or rest, potential currents in both directions at the established dynamic equilibrium have the same absolute value: the net current is zero. This current describes the electrocatalytic activity of an electrode and is called the exchange current; with respect to the surface area, it is called the exchange current density. This study inspected the actually used surface areas because the reported activities may depend critically on the selection of this area. Charge transfer resistances corresponding to exchange currents I0 were determined for a simple redox system using a platinum disc electrode with constant geometric surface area but variable roughness. At all studied degrees of roughness, changes in I0 were found. With an electrochemically active surface area, exchange current densities j0 could be calculated, but the obtained values showed a dependency on roughness that could not be accounted for by using this surface area instead of the geometric one. It is suggested that j0 may be reported with respect to geometric surface area, but at least roughness data of the studied electrode should be provided.

Motivated by the fact that the multi-stable property is becoming more and more important both in biological neural networks and in artificial intelligence, this paper is concerned with the multi-synchronization problem of stochastic coupled multi-stable-state neural networks (SCMNNs) with time-varying delay. First, we give the sufficient conditions to guarantee that every sub-system or sub-network owns more than one stable points or locally exponential stable periodic orbits. Second, via the impulsive control strategy and by choosing an appropriate Lyapunov function, some sufficient conditions for multi-synchronization of the controlled time-varying delayed SCMNNs are achieved. Moreover, by use of obtained sufficient conditions, which are expressed in the form of linear matrix inequalities, a novel control protocol based on the impulsive system theory for time-varying delayed SCMNNs with two types of topological structure is devised. The validity of the proposed results is verified by a numerical simulation.

Accurate remaining useful life (RUL) prediction under the noisy environment is a big challenge for the health management of modern industrial systems since the extraction of the accurate data structure from heavily corrupted data is difficult. In recent years, the kernel adaptive filter (KAF) has been widely adopted to solve the robust regression problem due to its low-complexity and high-approximation capability and robustness while the applications in battery RUL prediction are still few and far between. Thus, this paper is concerned with long-term RUL prediction using the KAF method. At first, concretely speaking, a robust KAF algorithm is derived based on the double-Gaussian-mixture (DGM) cost function, which is used to learn the capacity degradation mechanism from contaminated capacity data and so as to build the long-term prediction model. Second, a robust unscented Kalman filter (UKF) algorithm employing the DGM-based cost function is developed, which is then combined with the KAF-based prediction model to realize a more accurate and reliable prediction. Under the hybrid prognostic framework, the proposed UKF algorithm is applied to filter the noisy observations. When the observation data are inaccessible, the predicted data from the off-line trained KAF-based prediction model are adopted as the approximated value of the real observations for the UKF algorithm to optimize the prediction results and to provide the uncertainty representation. The experimental results reveal that the proposed method has great robustness when the measurements contain noise and large outliers, which makes it possible to get satisfactory prediction performance without preprocessing the data manually.

Background and objective The detection of driver oncogenes of lung cancer is of great importance. There are various gene detection techniques nowadays which are different from each other. We carried out this study to investigate the specificity and sensitivity of assay panels based on an Amplification Refractory Mutation System-polymerase chain reaction (ARMS-PCR) technique of Amplification Mutation Specific System (AMSS) in detection of lung cancer gene mutation. To estimate the applicable value of assay panels in clinical settings. Methods We collected cancer tissue specimens or fluid specimens from 309 patients. Mutation results were presented for those samples previously detected by ARMS-PCR. In comparison, we carried out AMSS-PCR using (epidermal growth factor receptor, EGFR) assay panel and Six-Alliance assay panel as well as Sanger sequencing. Software SPSS 22.0 (SPSS IBM) was used for statistical analysis. Results The rates of consistency between the results by assay panels and Sanger sequencing or ARMS-PCR were 97.41% and 97.73%, respectively. Besides, EGFR assay panel had higher consistency rates with other detection methods than Six-Alliance assay panel. As for consistency test, the Kappa values of assay panels with Sanger sequencing, assay panels with ARMS-PCR, and ARMS-PCR with Sanger sequencing were 0.946, 0.953, and 0.913, respectively. The receiver operating characteristic curve (ROC) area under curve (AUC) of assay panels was 0.976 referring to Sanger sequencing, and 0.975 as ARMS-PCR was referred to. Conclusion AMSS-PCR can make an optimal cancer gene mutation detection method for clinical settings.

Gastric cancer is the second most lethal type of malignant tumor in the world. Early diagnosis of gastric cancer can reduce the transformation to advanced cancer and improve the early treatment rate. As a cheap, real-time, non-invasive examination method, oral contrast-enhanced ultrasonography (OCUS) is a more acceptable way to diagnose gastric cancer than interventional diagnostic methods such as gastroscopy. In this paper, we proposed a new method for the diagnosis of gastric diseases by automatically analyzing the hierarchical structure of gastric wall in gastric ultrasound images, which is helpful to quantify the diagnosis information of gastric diseases and is a useful attempt for early screening of gastric cancer. We designed a gastric wall detection network based on U-net. On this basis, anisotropic diffusion technology was used to extract the layered structure of the gastric wall. A simple and useful gastric cancer screening model was obtained by calculating and counting the thickness of the five-layer structure of the gastric wall. The experimental results showed that our model can accurately identify the gastric wall, and it was found that the layered parameters of abnormal gastric wall is significantly different from that of normal gastric wall. For the screening of gastric disease, a statistical model based on gastric wall stratification can give a screening accuracy of 95% with AUC of 0.92.

Solid lubricants have been applied diffusely in numerous domains. This article investigates the impacts of each component in composite solid lubricants on the tribological performance and compares the antifriction effects of different kinds of solid lubricants to solve the lubrication problem of sliding bearing. Surface textures with dimples were fabricated on the surfaces of GCr15 bearing steel by a Q-switched solid-state Nd:YAG laser. The composite solid lubricants were filled in the micro-dimples by the deposition processes of heat-maintaining and pressure-maintaining, consisting of blinding elements and lubricating elements. Tribological performances under sliding friction for different kinds of adhesives and lubricants with different grain sizes were evaluated by ring-on-disk tribometer. On this basis, an orthogonal experiment of four factors and three levels (3 4 ) was designed to investigate the impacts of different components of the solid lubricants on the tribological performance. Solid lubricants with nanoparticles can enhance antifriction ability: the friction coefficient of nano-graphite is 18.9% lower than that of micron-graphite, and the friction coefficient of nano-sized molybdenum disulfide declines 7.6% comparing to that of micron-sized molybdenum disulfide. According to the results of the orthogonal experiment, the optimal formula of the composite solid lubricants was graphite:molybdenum disulfide:polyimide:carbon nano-tubes = 4:1:0.5:0.4.

Local climate zone (LCZ) maps have been used widely to study urban structures and urban heat islands. Because remote sensing data enable automated LCZ mapping on a large scale, there is a need to evaluate how well remote sensing resources can produce fine LCZ maps to assess urban thermal environments. In this study, we combined Sentinel-2 multispectral imagery and dual-polarized (HH + HV) PALSAR-2 data to generate LCZ maps of Nanchang, China using a random forest classifier and a grid-cell-based method. We then used the classifier to evaluate the importance scores of different input features (Sentinel-2 bands, PALSAR-2 channels, and textural features) for the classification model and their contribution to each LCZ class. Finally, we investigated the relationship between LCZs and land surface temperatures (LSTs) derived from summer nighttime ASTER thermal imagery by spatial statistical analysis. The highest classification accuracy was 89.96% when all features were used, which highlighted the potential of Sentinel-2 and dual-polarized PALSAR-2 data. The most important input feature was the short-wave infrared-2 band of Sentinel-2. The spectral reflectance was more important than polarimetric and textural features in LCZ classification. PALSAR-2 data were beneficial for several land cover LCZ types when Sentinel-2 and PALSAR-2 were combined. Summer nighttime LSTs in most LCZs differed significantly from each other. Results also demonstrated that grid-cell processing provided more homogeneous LCZ maps than the usual resampling methods. This study provided a promising reference to further improve LCZ classification and quantitative analysis of local climate.

Stick-slip phenomenon in some mechanical structures, especially in machine tools, should be eliminated or inhibited, otherwise the vibration will occur and the position error will inevitably be obtained. In this study, different kinds of surface textures were carried out on the lower samples of the pin-on-disk contact. The starting process of the machine tools was simulated on an Rtec-Multi-Function Tribometer. The stick-slip phenomenon was observed in each kind of samples. However, the stick-slip phenomenon of smooth sample is larger than that of the textured samples. The bulge-textured surface shows excellent anti-stick-slip effect, and the critical stick-slip speed of bulge-textured surface is 95.9% lower than that of the smooth surface. Simultaneously, the anti-stick-slip effect of bulge-textured surface is superior to that of the dent-shaped texturing surface. What’s more, when the amount of lubricating oil is 15 mL, the standard deviation values of friction coefficient and critical speed of stick-slip phenomena (rotational speed when the standard deviation of friction coefficient is abrupt) are the lowest at different rotational speeds. It can be predicted that the bulge textures and adequate amount of lubricating oil (15 mL) can eliminate stick-slip phenomenon when processed in the surface of the machine tool because the bulge textures and adequate amount of lubricating oil can improve frictional state effectively and avoid the slip of the contact surface.

A two-dimensional numerical model considering recoil pressure and Hertz-Knudsen ablation rate was established on the foundation of the laser remelting model to investigate the influence of laser processing parameters on crater feature and melted zone, and it was verified through experiments. The temperature and flow velocity distribution of the molten pool during the formation of the crater were analyzed. The results showed that the ablation velocity could be considered under a higher laser peak power density or higher pulse width due to the metal evaporation caused by heat accumulation. The depth and diameter of the crater were significantly affected by laser peak power density and laser pulse duration. Simultaneously, the height of the edge bulge decreased with the increase in pulse duration after 1.5 ms, and the growth rate of central depth was more rapid than that of edge bulge height with the increase of laser peak power density. In the texture with the same depth, a larger melted zone could be obtained with a longer laser duration than the higher peak power density.

Bandwidth is the crucial knowledge to sampling, reconstruction or estimation of the graph signal (GS). However, it is typically unknown in practice. In this paper, we focus on detecting the bandwidth of bandlimited GS with a small sample size, where the number of spectral components of GS to be tested may greatly exceed the sample size. To control the significance of the result, the detection procedure is implemented by multi-stage testing. In each stage, a Bayesian score test, which introduces a prior to the spectral components, is adopted to face the high dimensional challenge. By setting different priors in each stage, we make the test more powerful against alternatives that have similar bandwidth to the null hypothesis. We prove that the Bayesian score test is locally most powerful in expectation against the alternatives following the given prior. Finally, numerical analysis shows that our method has a good performance in bandwidth detection and is robust to the noise.

Abstract In this paper, we investigate the quasi-two-body decays $$B_c \rightarrow K_0^{*}(1430,1950) D_{(s)} \rightarrow K \pi D_{(s)}$$ B c → K 0 ∗ ( 1430 , 1950 ) D ( s ) → K π D ( s ) within the perturbative QCD (PQCD) framework. The S-wave two-meson distribution amplitudes (DAs) are introduced to describe the final state interactions of the $$K\pi $$ K π pair, which involve the time-like form factors and the Gegenbauer polynomials. In the calculations, we adopt two kinds of parameterization schemes to describe the time-like form factors: one is the relativistic Breit–Wigner (RBW) formula, which is usually more suitable for the narrow resonances, and the other is the LASS line shape proposed by the LASS Collaboration, which includes both the resonant and nonresonant components. We find that the branching ratios and the direct CP violations for the decays $$B_c \rightarrow K_0^{*}(1430) D_{(s)}$$ B c → K 0 ∗ ( 1430 ) D ( s ) obtained from those of the quasi-two-body decays $$B_c \rightarrow K_0^{*}(1430) D_{(s)} \rightarrow K \pi D_{(s)}$$ B c → K 0 ∗ ( 1430 ) D ( s ) → K π D ( s ) under the narrow width approximation (NWA) can be consistent well with the previous PQCD results calculated in the two-body framework by assuming that $$K^*_0(1430)$$ K 0 ∗ ( 1430 ) is the lowest lying $$\bar{q} s$$ q ¯ s state, which is the so-called scenario II (SII). We conclude that the LASS parameterization is more suitable to describe the $$K_0^{*}(1430)$$ K 0 ∗ ( 1430 ) than the RBW formula, and the nonresonant components play an important role in the branching ratios of the decays $$B_c \rightarrow K_0^{*}(1430) D_{(s)} \rightarrow K \pi D_{(s)}$$ B c → K 0 ∗ ( 1430 ) D ( s ) → K π D ( s ) . In view of the large difference between the decay width measurements for the $$K_0^{*}(1950)$$ K 0 ∗ ( 1950 ) given by BaBar and LASS collaborations, we calculate the branching ratios and the CP violations for the quasi-two-body decays $$B_c \rightarrow K_0^{*}(1950) D_{(s)} \rightarrow K \pi D_{(s)}$$ B c → K 0 ∗ ( 1950 ) D ( s ) → K π D ( s ) by using two values, $$\Gamma _{K^*_0(1950)}=0.100\pm 0.04$$ Γ K 0 ∗ ( 1950 ) = 0.100 ± 0.04 GeV and $$\Gamma _{K^*_0(1950)}=0.201\pm 0.034$$ Γ K 0 ∗ ( 1950 ) = 0.201 ± 0.034 GeV, besides the two kinds of parameterizations for the resonance $$K^*_0(1950)$$ K 0 ∗ ( 1950 ) . We find that the branching ratios and the direct CP violations for the decays $$B_c \rightarrow K_0^{*}(1950) D_{(s)} \rightarrow K \pi D_{(s)}$$ B c → K 0 ∗ ( 1950 ) D ( s ) → K π D ( s ) have not as large difference between the two parameterizations as the case of decays involving the $$K^*_0(1430)$$ K 0 ∗ ( 1430 ) , especially for the results with $$\Gamma _{K^*_0(1950)}=0.201\pm 0.034$$ Γ K 0 ∗ ( 1950 ) = 0.201 ± 0.034 GeV. The effect of the nonresonant component in the $$K^*_0(1950)$$ K 0 ∗ ( 1950 ) may be not so serious as that in the $$K^*_0(1430)$$ K 0 ∗ ( 1430 ) . The quasi-two-body decays $$B^+_c \rightarrow K^{*+}_0(1430) D^{0} \rightarrow K^0 \pi ^+ D^{0}$$ B c + → K 0 ∗ + ( 1430 ) D 0 → K 0 π + D 0 and $$B^+_c \rightarrow K^{*0}_0(1430) D^{+} \rightarrow K^+ \pi ^- D^{+}$$ B c + → K 0 ∗ 0 ( 1430 ) D + → K + π - D + have large branching ratios, which can reach to the order of $$10^{-4}$$ 10 - 4 and are most likely to be observed in the future LHCb experiments. Furthermore, the branching ratios of the quasi-two-body decays $$B_c \rightarrow K_0^{*}(1950) D_{(s)} \rightarrow K \pi D_{(s)}$$ B c → K 0 ∗ ( 1950 ) D ( s ) → K π D ( s ) are about one order smaller than those of the corresponding decays $$B_c \rightarrow K_0^{*}(1430) D_{(s)} \rightarrow K \pi D_{(s)}$$ B c → K 0 ∗ ( 1430 ) D ( s ) → K π D ( s ) .

Abstract Background Despite numerous previous studies, the consideration of tumor location as a prognostic factor in resectable non–small cell lung cancer (NSCLC) remains controversial. The present study analyzed the association between tumor location and clinical outcome in patients with resectable NSCLC who had undergone lobectomy with systematic lymphadenectomy and who had presented with varying nodal statuses. Methods The data from a cohort of 627 eligible patients treated in Sun Yat-sen University Cancer Center between January 2000 and December 2008 were retrospectively collected, and the nodal statuses of patients with different tumor locations were compared. Cox proportional hazards regression model was used to determine the independent factors related to cancer-specific survival (CSS). Results Multivariate analysis demonstrated that left lower lobe (LLL) tumors [hazard ratio (HR): 1.465, 95% confidence interval (CI) 1.090–1.969, P = 0.011], lymph node metastasis (HR: 2.742, 95% CI 2.145–3.507, P < 0.001), and a tumor size of >4 cm (HR: 1.474, 95% CI 1.151–1.888, P = 0.002) were three independent prognosticators in patients with resectable NSCLC. However, LLL tumors were associated only with CSS in node-positive patients (HR: 1.528, 95% CI 1.015–2.301, P = 0.042), and a tumor size of >4 cm was the only independent risk predictor in the node-negative subgroup (HR: 1.889, 95% CI 1.324–2.696, P < 0.001). Conclusions Tumor location is related to the long-term CSS of NSCLC patients with lymph node metastasis. LLL tumors may be upstaged in node-positive patients to facilitate an optimal treatment strategy.

Spermatogenesis is a continuous and dynamic developmental process, in which a single diploid spermatogonial stem cell (SSC) proliferates and differentiates to form a mature spermatozoon. Herein, we summarize the accumulated knowledge of SSCs and their distribution in the testes of teleosts. We also reviewed the primary endocrine and paracrine influence on spermatogonium self-renewal vs. differentiation in fish. To provide insight into techniques and research related to SSCs, we review available protocols and advances in enriching undifferentiated spermatogonia based on their unique physiochemical and biochemical properties, such as size, density, and differential expression of specific surface markers. We summarize in vitro germ cell culture conditions developed to maintain proliferation and survival of spermatogonia in selected fish species. In traditional culture systems, sera and feeder cells were considered to be essential for SSC self-renewal, in contrast to recently developed systems with well-defined media and growth factors to induce either SSC self-renewal or differentiation in long-term cultures. The establishment of a germ cell culture contributes to efficient SSC propagation in rare, endangered, or commercially cultured fish species for use in biotechnological manipulation, such as cryopreservation and transplantation. Finally, we discuss organ culture and three-dimensional models for in vitro investigation of fish spermatogenesis.

The human brain is a complex system composed by several large scale intrinsic networks with distinct functions. The low frequency oscillation (LFO) signal of blood oxygen level dependent (BOLD), measured through resting-state fMRI, reflects the spontaneous neural activity of these networks. We propose to characterize these networks by applying the multiple frequency bands analysis (MFBA) to the LFO time courses (TCs) resulted from the group independent component analysis (ICA). Specifically, seven networks, including the default model network (DMN), dorsal attention network (DAN), control executive network (CEN), salience network, sensorimotor network, visual network and limbic network, are identified. After the power spectral density (PSD) analysis, the amplitude of low frequency fluctuation (ALFF) and the fractional amplitude of low frequency fluctuation (fALFF) is determined in three bands:

Pigs are commonly used as an animal model to evaluate the toxic effects of exogenous compounds. Cytochrome P450 1A1 (CYP1A1) metabolizes numerous exogenous compounds and is abundantly expressed in the liver, kidneys, and intestines. The high amino acid similarity between human and porcine CYP1A1 indicates that they probably have the same metabolic characteristics. Therefore, understanding the regulatory mechanism of CYP1A1 expression in pigs is particularly important for predicting the toxicology and metabolic kinetics of exogenous chemicals. Currently, the transcriptional regulation of porcine CYP1A1 has rarely been studied, especially regarding basal transcription. In this study, we first confirmed that the key regulatory elements of porcine CYP1A1 basal transactivation are in the proximal promoter region using promoter truncation analysis via a dual luciferase assay in a porcine kidney cell line LLC-PK1. Two overlapping cis-elements, the xenobiotic response element (XRE) and GC box, in this proximal region potentially play key roles in the basal transactivation of porcine CYP1A1. Furthermore, using electrophoretic mobility shift assay and chromatin immunoprecipitation, the GC box binding protein Sp1 was confirmed to bind to the proximal promoter of porcine CYP1A1, instead of AhR, the XRE binding protein. In LLC-PK1 cells, by knocking down either Sp1 or AhR, the expression of porcine CYP1A1 at the mRNA level and protein level was significantly downregulated, suggesting both proteins are important for porcine CYP1A1 expression. However, promoter activity analysis in LLC-PK1 cells treated with an AhR agonist and antagonist confirmed that AhR does not participate in the basal regulation of porcine CYP1A1 at the proximal promoter. In conclusion, our study revealed that the proximal promoter is the key regulatory region for porcine CYP1A1 basal expression. Although AhR plays an important role in the transactivation of porcine CYP1A1 expression, the key determinant transcription factor for its basal transactivation is Sp1 at the proximal promoter of porcine CYP1A1.

Many fragile watermark methods have been proposed for image recovery and their performance has been greatly improved. However, jagged edges and confusion still exist in the restored areas and these problems need to be solved to achieve a better visual effect. In this paper, a method for improving recovery quality is proposed that adopts singular value decomposition (SVD) and edge detection for tamper detection and then uses a median filter for image recovery. Variable watermark information can be generated that corresponds to block classifications. With mapping and neighborhood adjustment, the area that has been tampered can be correctly detected. Subsequently, we adopt a filtering operation for the restored image obtained after the inverse watermark embedding process. During the filtering operation, a median filter is used to smooth and remove noise, followed by minimum, maximum and threshold operations to balance the image intensity. Finally, the corresponding pixels of the restored image are replaced with the filtered results. The experimental results of six different tampering attacks conducted on eight test images show that tamper detection method with the edge detection can identify the tampered region correctly but has a higher false alarm rate than other methods. In addition, compared with the other three similar methods previously, using a median filter during image recovery not only improves the visual effect of the restored image but also enhances its quality objectively under most tampering attack conditions.

To expand germ cell populations and provide a consistent supply for transplantation, we established basal culture conditions for sturgeon germ cells and subsequently increased their mitotic activity by eliminating gonad somatic cells, supplementing with growth factor, and replacing fetal bovine serum (FBS). The initial basal culture conditions were Leibovitz’s L-15 medium (pH 8.0) supplemented with 5% FBS (p < 0.001) at 21 °C. Proliferation of germ cells was significantly enhanced and maintained for longer periods by elimination of gonad somatic cells and culture under feeder-cell free conditions, with addition of leukemia inhibitory factor and glial-cell-derived neurotrophic factor (p < 0.001). A serum-free culture medium improved germ cell proliferation compared to the L-15 with FBS (p < 0.05). Morphology remained similar to that of fresh germ cells for at least 40 d culture. Germline-specific gene expression analysis revealed no significant changes to germ cells before and after culture. Sterlet Acipenser ruthenus germ cells cultured more than 40 days showed development after transplant into Russian sturgeon Acipenser gueldenstaedtii. Polymerase chain reaction showed 33.3% of recipient gonads to contain sterlet cells after four months. This study developed optimal culture condition for sturgeon germ cells. Germ cells after 40 d culture developed in recipient gonads. This study provided useful information for culture of sturgeon germ cells.

There is comprehensive work on the tribological properties and lubrication mechanisms of oil lubricant used on textured surfaces, however the use of grease lubrication on textured surfaces is rather new. This research article presents an experimental study of the frictional behaviours of grease lubricated sliding contact under mixed lubrication conditions. The influences of surface texture parameters on the frictional properties were investigated using a disc-on-ring tribometer. The results showed that the friction coefficient is largely dependent on texture parameters, with higher and lower texture density resulting in a higher friction coefficient at a fixed texture depth. The sample with texture density of 15% and texture depth of 19 μm exhibited the best friction properties in all experimental conditions because it can store more grease and trap wear debris. The reduction of friction is mainly attributable to the formation of a stable grease lubrication film composed of oil film, transfer film and deposited film, and the hydrodynamic pressure effect of the surface texture, which increases the mating gap and reduces the probability of asperity contact. This result will help in understanding the tribological behaviour of grease on a textured surface and in predicting the lubrication conditions of sliding bearings for better operation in any machinery.

To meet the growing demands of higher data rates and larger bandwidth in the future wireless communications, several methods including the optimization of reference phase, multiple frequency matching, and dispersion engineering method have been investigated to design millimeter wave (mm-wave) antennas. However, the optimization process in these methods necessitate complex calculation and experience. In this study, we proposed a novel approach that optimizes reference phases and transmission magnitudes at multiple frequencies assisting with deep learning method to design an ultra-wideband mm-wave circularly polarization antenna. The first neural network intelligently provides the required geometric parameters of the unit cells, while the second neural network validates the phase shifts and predicts the transmission magnitudes based on inputs from the first neural network. The particle swarm optimization (PSO) algorithm is also utilized to optimizes the reference phases at multiple frequencies to minimize the matching errors. To validate the design, a 3-D printed compact CP antenna is fabricated and the measured results show that this antenna achieves a 1-dB gain bandwidth of 31.4%, and the 3-dB axis ratio (AR) covers the full W-band from 75 GHz to 110 GHz. The results show that our proposed method is more intelligent and faster than alternative approaches.

Observing poultry activity is crucial for assessing their health status; however, the inspection process is often time-consuming and labor-intensive, particularly in cases involving large numbers of chickens. Inexperienced breeders may also misjudge their activity levels, potentially missing opportunities for prevention and treatment. This study integrates traditional video surveillance with an advanced monitoring system to identify various broiler behaviors in a breeding environment. A two-stage deep learning approach is employed: in the first stage, the broilers are detected, and in the second stage, five key body points (head, abdomen, two legs, and tail) are identified. A skeleton-based model is then developed centered around the abdomen, with six angles calculated using trigonometric methods. These angles are analyzed by a long short-term memory network to estimate behaviors such as “Standing”, “Walking”, “Resting”, “Eating”, “Preening”, and “Flapping”, selecting the behavior with the highest probability. Dual-layer fuzzy logic inference systems were used to evaluate the proportion of time broilers spent in static versus dynamic states, providing a robust determination of their activity levels. Validated in a mixed-sex breeding environment, the proposed system achieved accuracies of at least 85.2% for identifying broiler type, 79.2% for identifying body parts, and 50.8% for identifying behaviors. The activity level evaluation results were consistent with those conducted by experienced poultry experts.