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In the sheet forming process, the final bending angle is mostly determined based on experience rather than based on a reliable theoretical framework. Furthermore, the local bent areas tend to decrease in thickness. Thus, it is difficult to control the quality of the final products. In this study, we developed an optimized bending angle function by combining segment boundaries to improve the final sheet forming quality and reduce the local thinning defects. The finite element submodel method was used to establish a high-definition thickness-sensitive numerical model for the bottom bending area of the hat-shaped part. This method accurately simulated the thickness variation law of the bending area of roll forming and analyzed the optimization function of the bending angle of the segment boundary as well as the process parameters for local thinning. Finally, roll-bending experiments were conducted to analyze the bending angle distribution conditions and the change law with respect to the process parameters of the cap-shaped parts in case of local thinning defects to verify the accuracy of the finite element simulation process. The results showed that the local thinning defect in the bending area of the hat-shaped part was smaller during roll bending, and the forming quality obtained was better than that obtained using other previously reported methods. The experimental data were consistent with the simulation data, verifying the accuracy of our proposed approach. Moreover, the thickness of the thinning defect was influenced by the process parameters; the plate bending radius and yield strength increased, and thickness thinning gradually decreased. Furthermore, the local thinning defects increased with the increasing plate thickness. [ABSTRACT FROM AUTHOR]

Insect pathogenic fungi, also known as entomopathogenic fungi, are one of the largest insect pathogenic microorganism communities, represented by Beauveria spp. and Metarhizium spp. Entomopathogenic fungi have been proved to be a great substitute for chemical pesticide in agriculture. In fact, a lot of functional genes were also already characterized in entomopathogenic fungi, but more depth of exploration is still needed to reveal their complicated pathogenic mechanism to insects. Metarhizium rileyi (Nomuraea rileyi) is a great potential biocontrol fungus that can parasitize more than 40 distinct species (mainly Lepidoptera: Noctuidae) to cause large-scale infectious diseases within insect population. In this study, a comparative analysis of transcriptome profile was performed with topical inoculation and hemolymph injection to character the infectious pattern of M. rileyi. Appressorium and multiple hydrolases are indispensable constituents to break the insect host primary cuticle defense in entomopathogenic fungi. Within our transcriptome data, numerous transcripts related to destruction of insect cuticle rather growth regulations were obtained. Most importantly, some unreported ribosomal protein genes and novel unannotated protein (hypothetical protein) genes were proved to participate in the course of pathogenic regulation. Our current data provide a higher efficiency gene library for virulence factors screen in M. rileyi, and this library may be also useful for furnishing valuable information on entomopathogenic fungal pathogenic mechanisms to host. [ABSTRACT FROM AUTHOR]

A simple fluorescence resonance energy transfer (FRET) sensing platform (termed as USP), comprised of upconversion nanoparticles (UCNPs) as the energy donor and Cy5 as the energy acceptor, has been synthesized for cathepsin B (CTSB) activity detection in vitro and in vivo. When Cy5-modified peptide substrate (peptide-Cy5) of CTSB is covalently linked on the surface of UCNPs, the FRET between the UCNPs (excitation: 980 nm; emission: 541 nm/655 nm) and Cy5 (excitation: 645 nm) leads to a reduction in the red upconversion luminescence (UCL) signal intensity of UCNPs. Cy5 can be liberated from UCNPs in the presence of CTSB through the cleavage of peptide-Cy5 by CTSB, leading to the recovery of the red UCL signal of UCNPs. Because the green UCL signal of UCNPs remains constant during the CTSB digestion, it can be considered as an internal reference. The findings demonstrate the ability of USP to detect CTSB with the linear detection ranges of 1 to 100 ng·mL−1 in buffer and 2 × 103 to 1 × 105 cells in 0.2 mL cell lysates. The limits of detection (LODs) are 0.30 ng·mL−1 in buffer and 887 cells in 0.2 mL of cell lysates (S/N = 3). The viability of USP to detect CTSB activity in tumor-bearing mice is has further been investigated using in vivo fluorescent imaging. [ABSTRACT FROM AUTHOR]

Clinical and experimental data hints that prolonged and repeated epileptic seizures can lead to molecular, biochemical, metabolic, and structural changes in the brain, a continuous process of chronic brain injury that ultimately leads to neuronal death. The histological characteristics of hippocampal structure determine its high sensitivity to excitotoxicity and present different types of neuronal death, including apoptosis, necroptosis, autophagy, pyroptosis, and ferroptosis. Hippocampal neuronal death promotes the progression of epileptogenesis, seizures, and epilepsy and is closely related to the impairment of cognitive function. Massive evidence indicates that oxidative stress plays a critical role in different forms of neuronal death induced by epileptic seizures. The brain is particularly vulnerable to damage caused by oxidative stress, and an increase in oxidative stress biomarkers was found in various epilepsy types. The purpose of this review is to elucidate the molecular mechanism of neuronal death and explore the moderating effect of oxidative stress on epileptic seizure-induced neuronal death patterns so as to find potential intervention targets for neuroprotective treatment after epileptic seizures. [ABSTRACT FROM AUTHOR]

Purpose: To compare the accuracy of 14 formulas in calculating intraocular lens (IOL) power in extremely long eyes with axial length (AL) over 30.0 mm.In this retrospective study, 211 eyes (211 patients) with ALs > 30.0 mm were successfully treated with cataract surgery without complications. Ocular biometric parameters were obtained from IOLMaster 700. Fourteen formulas were evaluated using the optimized A constants: Barrett Universal II (BUII), Kane, Emmetropia Verifying Optical (EVO) 2.0, PEARL-DGS, T2, SRK/T, Holladay 1, Holladay 2, Haigis and Wang-Koch AL adjusted formulas (SRK/Tmodified-W/K, Holladay 1modified-W/K, Holladay 1NP-modified-W/K, Holladay 2modified-W/K, Holladay 2NP-modified-W/K). The mean prediction error (PE) and standard deviation (SD), mean absolute errors (MAE), median absolute errors (MedAE), and the percentage of prediction errors (PEs) within ± 0.25 D, ± 0.50 D, ± 1.00 D were analyzed.The Kane formula had the smallest MAE (0.43 D) and MedAE (0.34 D). The highest percentage of PE within ± 0.25 D was for EVO 2.0 (37.91%) and the Holladay 1NP-modified-W/K formulas (37.91%). The Kane formula had the highest percentage of PEs in the range of ± 0.50, ± 0.75, ± 1.00, and ± 2.00 D. There was no significant difference in PEs within ± 0.25, ± 0.50 ± 0.75 and ± 1.00 D between BUII, Kane, EVO 2.0 and Wang-Koch AL adjusted formulas (P > .05) by using Cochran’s Q test. The Holladay 2modified-W/K formula has the lowest percentage of hyperopic outcomes (29.38%).The BUII, Kane, EVO 2.0 and Wang-Koch AL adjusted formulas have comparable accuracy for IOL power calculation in eyes with ALs > 30.0 mm.Methods: To compare the accuracy of 14 formulas in calculating intraocular lens (IOL) power in extremely long eyes with axial length (AL) over 30.0 mm.In this retrospective study, 211 eyes (211 patients) with ALs > 30.0 mm were successfully treated with cataract surgery without complications. Ocular biometric parameters were obtained from IOLMaster 700. Fourteen formulas were evaluated using the optimized A constants: Barrett Universal II (BUII), Kane, Emmetropia Verifying Optical (EVO) 2.0, PEARL-DGS, T2, SRK/T, Holladay 1, Holladay 2, Haigis and Wang-Koch AL adjusted formulas (SRK/Tmodified-W/K, Holladay 1modified-W/K, Holladay 1NP-modified-W/K, Holladay 2modified-W/K, Holladay 2NP-modified-W/K). The mean prediction error (PE) and standard deviation (SD), mean absolute errors (MAE), median absolute errors (MedAE), and the percentage of prediction errors (PEs) within ± 0.25 D, ± 0.50 D, ± 1.00 D were analyzed.The Kane formula had the smallest MAE (0.43 D) and MedAE (0.34 D). The highest percentage of PE within ± 0.25 D was for EVO 2.0 (37.91%) and the Holladay 1NP-modified-W/K formulas (37.91%). The Kane formula had the highest percentage of PEs in the range of ± 0.50, ± 0.75, ± 1.00, and ± 2.00 D. There was no significant difference in PEs within ± 0.25, ± 0.50 ± 0.75 and ± 1.00 D between BUII, Kane, EVO 2.0 and Wang-Koch AL adjusted formulas (P > .05) by using Cochran’s Q test. The Holladay 2modified-W/K formula has the lowest percentage of hyperopic outcomes (29.38%).The BUII, Kane, EVO 2.0 and Wang-Koch AL adjusted formulas have comparable accuracy for IOL power calculation in eyes with ALs > 30.0 mm.Results: To compare the accuracy of 14 formulas in calculating intraocular lens (IOL) power in extremely long eyes with axial length (AL) over 30.0 mm.In this retrospective study, 211 eyes (211 patients) with ALs > 30.0 mm were successfully treated with cataract surgery without complications. Ocular biometric parameters were obtained from IOLMaster 700. Fourteen formulas were evaluated using the optimized A constants: Barrett Universal II (BUII), Kane, Emmetropia Verifying Optical (EVO) 2.0, PEARL-DGS, T2, SRK/T, Holladay 1, Holladay 2, Haigis and Wang-Koch AL adjusted formulas (SRK/Tmodified-W/K, Holladay 1modified-W/K, Holladay 1NP-modified-W/K, Holladay 2modified-W/K, Holladay 2NP-modified-W/K). The mean prediction error (PE) and standard deviation (SD), mean absolute errors (MAE), median absolute errors (MedAE), and the percentage of prediction errors (PEs) within ± 0.25 D, ± 0.50 D, ± 1.00 D were analyzed.The Kane formula had the smallest MAE (0.43 D) and MedAE (0.34 D). The highest percentage of PE within ± 0.25 D was for EVO 2.0 (37.91%) and the Holladay 1NP-modified-W/K formulas (37.91%). The Kane formula had the highest percentage of PEs in the range of ± 0.50, ± 0.75, ± 1.00, and ± 2.00 D. There was no significant difference in PEs within ± 0.25, ± 0.50 ± 0.75 and ± 1.00 D between BUII, Kane, EVO 2.0 and Wang-Koch AL adjusted formulas (P > .05) by using Cochran’s Q test. The Holladay 2modified-W/K formula has the lowest percentage of hyperopic outcomes (29.38%).The BUII, Kane, EVO 2.0 and Wang-Koch AL adjusted formulas have comparable accuracy for IOL power calculation in eyes with ALs > 30.0 mm.Conclusions: To compare the accuracy of 14 formulas in calculating intraocular lens (IOL) power in extremely long eyes with axial length (AL) over 30.0 mm.In this retrospective study, 211 eyes (211 patients) with ALs > 30.0 mm were successfully treated with cataract surgery without complications. Ocular biometric parameters were obtained from IOLMaster 700. Fourteen formulas were evaluated using the optimized A constants: Barrett Universal II (BUII), Kane, Emmetropia Verifying Optical (EVO) 2.0, PEARL-DGS, T2, SRK/T, Holladay 1, Holladay 2, Haigis and Wang-Koch AL adjusted formulas (SRK/Tmodified-W/K, Holladay 1modified-W/K, Holladay 1NP-modified-W/K, Holladay 2modified-W/K, Holladay 2NP-modified-W/K). The mean prediction error (PE) and standard deviation (SD), mean absolute errors (MAE), median absolute errors (MedAE), and the percentage of prediction errors (PEs) within ± 0.25 D, ± 0.50 D, ± 1.00 D were analyzed.The Kane formula had the smallest MAE (0.43 D) and MedAE (0.34 D). The highest percentage of PE within ± 0.25 D was for EVO 2.0 (37.91%) and the Holladay 1NP-modified-W/K formulas (37.91%). The Kane formula had the highest percentage of PEs in the range of ± 0.50, ± 0.75, ± 1.00, and ± 2.00 D. There was no significant difference in PEs within ± 0.25, ± 0.50 ± 0.75 and ± 1.00 D between BUII, Kane, EVO 2.0 and Wang-Koch AL adjusted formulas (P > .05) by using Cochran’s Q test. The Holladay 2modified-W/K formula has the lowest percentage of hyperopic outcomes (29.38%).The BUII, Kane, EVO 2.0 and Wang-Koch AL adjusted formulas have comparable accuracy for IOL power calculation in eyes with ALs > 30.0 mm. [ABSTRACT FROM AUTHOR]

Entropy indexes are widely used to measure the complexity of precipitation and its spatiotemporal variability, due to their advantages in quantifying the complex and nonlinear interactions of climate variables. However, different entropy indexes may provide different outcomes on the complexity of precipitation, thus causing difficulties in the assessment of actual complexity. In this study, we identified and chose the optimal entropy index from six entropy indexes based on the reliability and stability of entropy values, to assess the complexity of precipitation. The six entropy indexes considered are: information entropy (IE), fuzzy entropy (FE), approximate entropy (AE), sample entropy (SE), wavelet entropy (WE), and permutation entropy (PE). We implemented the approach on the monthly precipitation data observed over the period 1968–2017 at 58 meteorological stations in Beijing, China. The results indicated that the SE index was the optimal index with the best reliability and stability and, thus, was used to examine the complexity of the 58 monthly precipitation series in Beijing. The results also suggested that the complexity of precipitation can be viewed in terms of four sub-regions in Beijing. The precipitation in the 'Northern Mountain Area', with high complexity, was more affected by the interactions between the terrain and climate variability, compared with that in the 'Southern Mountain Area' with low complexity. The precipitation in the 'Central Urban Area' was more significantly impacted by the extensive urbanization than that in the 'Northeast Suburban Area', causing higher complexity in the former. At temporal scale, the complexity of precipitation in the 'Southern Mountain Area' exhibited the largest increasing rate due to the highest impacts of climate variability, followed by the 'Central Urban Area' with a moderate increasing rate of complexity of precipitation due to the impacts of human activities. However, the complexity of precipitation in the 'Northern Mountain Area' and 'Northeast Suburban Area' exhibited small changes due to relatively weak sensitivity to climate variability and human activities. [ABSTRACT FROM AUTHOR]

Distributed deep learning can effectively accelerate neural model training, which employs multiple workers at a cluster of nodes to train a neural network in a parallel way. In this paper, we propose InHAD, an asynchronous distributed deep learning protocol, whose key novelty lies in the design of hierarchical gradient communication and aggregation. The local aggregation is conducted inside a computing node to aggregate the gradients produced by local workers, while global aggregation is conducted at the parameter server to calculate new model parameters based on results of local aggregations. An iteration number-based mechanism is designed to guarantee the convergence of the training. Worker nodes keep sending IN to parameter server and the latter decides when to pull gradients from workers by counting IN and updates global model weights/parameters. With the IN-based hierarchical aggregation technique, InHAD can save communication cost by reducing the number of gradients transferred and speed up the convergence by limiting the staleness of gradients. We conduct extensive experiments at the Tianhe-2 supercomputer system to evaluate the performance of InHAD. Two neural networks are trained on two classical datasets, and similar protocols like Horovod and ASP are tested for comparisons. The results show that InHAD can achieve much higher acceleration than ASP and nearly the same accuracy as Horovod. [ABSTRACT FROM AUTHOR]

Question answering, serving as one of important tasks in natural language processing, enables machines to understand questions in natural language and answer the questions concisely. From web search to expert systems, question answering systems are widely applied to various domains in assisting information seeking. Deep learning methods have boosted various tasks of question answering and have demonstrated dramatic effects in performance improvement for essential steps of question answering. Thus, leveraging deep learning methods for question answering has drawn much attention from both academia and industry in recent years. This paper provides a systematic review of the recent development of deep learning methods for question answering. The survey covers the scope including methods, datasets, and applications. The methods are discussed in terms of network structure characteristics, methodology innovations, and their effectiveness. The survey is expected to be a contribution to the summarization of recent research progress and future directions of deep learning methods for question answering. [ABSTRACT FROM AUTHOR]

The kinematic errors of the linear axis play a key role in machining precision of high-end CNC (computer numerical control) machine tool. The quantification of error relationship is still an urgent problem to be solved in the assembly process of the linear axis, especially considering the effect of the elastic deformation of rollers. In order to obtain the kinematic errors of the linear axis of machine tool, a systematic error equivalence model of slider is proposed. The linear axis contains the base, the linear guide rail, and carriage. Firstly, the geometric errors of assembly surface of linear guide rail are represented by small displacement torsor. Then, according to the theory of different motion of robots, the error equivalence model of a single slider is established, namely the geometric errors of assembly surface of linear guide rail and the pose error of slider are equivalent to the elastic deformation of roller. Based on the principle of vector summation, the kinematic error of a single slider is mapped to the carriage, and the kinematic error of the linear axis is obtained. At the same time, experiments validation of kinematic error model of the linear axis is carried out. It is indicated that the proposed model is accurate and feasible. The analysis of key design parameters shows that the proposed model can provide an accurate guidance for the manufacturing and operation performance of the linear axis in quantification, and a more effective reference for the engineers at the design and assembly stage. [ABSTRACT FROM AUTHOR]

Approximately 80% of individuals encounter lower back pain (LBP), a prevalent clinical issue largely attributed to intervertebral disc degeneration (IDD). Ferroptosis is an iron-dependent lipid peroxidation-driven cell death, and there is growing evidence that ferroptosis plays an important role in various human diseases. However, the underlying mechanism of ferroptosis in IDD remains unclear. This study aims to reveal the potential hub genes and related pathways of ferroptosis in the pathogenesis and progression of IDD. In this study, we analyzed three microarray datasets from the GEO database. Additionally, we downloaded ferroptosis-related genes from FerrDb-V2 and extracted apoptosis-related genes from UniProt as a control to show the specificity of ferroptosis. Weighted gene co-expression network analysis (WGCNA) was performed to identify the IDD-related module genes. Then, ferroptosis-related genes and apoptosis-related genes were separately overlapped with the IDD-related module genes, resulting in the identification of 35 ferroptosis-related module genes (FRMG) and 142 apoptosis-related module genes (ARMG). Furthermore, we performed functional enrichment analysis and protein–protein interaction network, and Cytoscape along with CytoHubba was used to identify the hub genes. Finally, logistic regression models were constructed and identified two hub FRMGs (PTEN and EGFR) and one hub ARMG (CTNNB1), which could distinguish IDD patients from controls (P < 0.05). The areas under the ROC curves were 0.792 and 0.730, respectively, suggesting that ferroptosis is more specific than apoptosis in IDD. In conclusion, this study provided fresh perspectives on ferroptosis in the pathogenesis and progression of IDD that can be used to evaluate potential biomarker genes and therapeutic targets. [ABSTRACT FROM AUTHOR]

Multi-pass single-point incremental forming achieves large-angle part processing through multiple forming, and as the number of forming times increases, the number of forming defects on the workpiece also increases, significantly affecting the forming quality of the workpiece. This study focuses on multi-pass single-point incremental forming defects, investigating the effects of machining paths and different variable parameters on forming defects. It comprehensively analyses the effects of axial and radial compensation machining paths on forming defects through simulations and experiments. The results show that the greater the axial compensation, the more severe the wall thickness reduction and the fewer the sink mark defects. After radial compensation, the minimum wall thickness of the formed parts is reduced, and the larger the radial compensation, the more obvious the sink mark defects. The effects of variable pass angle, tool diameter, and layer feed rate on forming defects were also investigated. The results show that a decrease in the angle between passes reduces the minimum wall thickness of the workpiece. Furthermore, gradually increasing the tool diameter and decreasing the feed rate can increase the wall thickness of the workpiece; gradually decreasing the angle between passes increases the number of sink defects, whereas gradually increasing the tool diameter can reduce the number of sink defects. The sink defect is the smallest with the same layer feed rate. The effectiveness and accuracy of the simulation results have been verified through experiments, and this is of great significance for improving the forming accuracy of workpieces. [ABSTRACT FROM AUTHOR]

This paper presents a statistical analysis on the relationship between shear strength and water saturation of cohesive soils based on a comprehensive database (labeled as Cohesive Soil/3/2119). In this study, the cohesive soils are categorized into three general types including clay, silty clay, and silt. For each of the three types, the statistical characteristics including mean, standard deviation (SD), coefficient of variation (COV), standard error of mean (SEM), and distribution type of the shear strength parameters at different water saturation intervals are derived. Further, several empirical formulas are proposed for predicting the statistical characteristics of shear strength of cohesive soils as a function of degree of saturation. The empirical formulas and relationships for different soil types are compared. For the three soil types, the decreasing rate of mean cohesion with the increase of water saturation is highest for silt and lowest for clay; however, the decreasing rate for mean friction angle is highest for clay and lowest for silt. The statistics in terms of SD and COV for shear strength versus water saturation are also analyzed. The developed correlations provide useful guidelines in the reliability-based geotechnical design for estimating the statistical characteristics of shear strength of cohesive soils based on the moisture conditions. [ABSTRACT FROM AUTHOR]

Vascular dementia (VaD) has a serious impact on the patients' quality of life. Icariin (Ica) possesses neuroprotective potential for treating VaD, yet its oral bioavailability and blood–brain barrier (BBB) permeability remain challenges. This research introduced a PEG–PLGA-loaded chitosan hydrogel-based binary formulation tailored for intranasal delivery, enhancing the intracerebral delivery efficacy of neuroprotective agents. The formulation underwent optimization to facilitate BBB crossing, with examinations conducted on its particle size, morphology, drug-loading capacity, in vitro release, and biodistribution. Using the bilateral common carotid artery occlusion (BCCAO) rat model, the therapeutic efficacy of this binary formulation was assessed against chitosan hydrogel and PEG–PLGA nanoparticles loaded with Ica. Post-intranasal administration, enhanced cognitive function was evident in chronic cerebral hypoperfusion (CCH) rats. Further mechanistic evaluations, utilizing immunohistochemistry (IHC), RT-PCR, and ELISA, revealed augmented transcription of synaptic plasticity-associated proteins like SYP and PSD-95, and a marked reduction in hippocampal inflammatory markers such as IL-1β and TNF-α, highlighting the formulation's promise in alleviating cognitive impairment. The brain-derived neurotrophic factor (BDNF)/tropomyosin related kinase B (TrkB) pathway was activated significantly in the binary formulation compared with the other two. Our study demonstrates that the intranasal application of chitosan hydrogel loaded with Ica-encapsulated PEG–PLGA could effectively deliver Ica into the brain and enhance its neuroprotective effect. [ABSTRACT FROM AUTHOR]

The digestion of community solid waste has great development prospects and economic benefits in the context of waste segregation. However, a large amount of biogas slurry is produced in the anaerobic digestion process and needs to be treated. In this study, the digestion performance and optimal recirculation batch in the digestion of community solid waste were investigated when multiple batches of recirculated slurry were mixed with inoculated sludge in the optimal ratio (a sludge volume percentage of 50%) as the inoculum. The results showed that the biogas yield and methane yield per unit load increased gradually with the number of recirculation batches and reached their maximum values in the seventh batch, which were 80.63% (1382.2 mL/g volatile solids) and 51.0% (812.4 mL/g volatile solids) more than the respective initial values. After four cycles of cultivation, the accumulation of volatile fatty acids (VFAs) was significantly alleviated, and the total VFA concentration in the seventh batch was reduced by 49.7% in comparison with the initial value. The digestion process produced methane mainly via hydrogenotrophic methanogenesis and syntrophic acetic acid-oxidizing methanogenesis. The genera Methanobacterium and Methanomassiliicoccus were closely associated with the biogas production performance. These results are helpful to increase the utilization rate of biogas slurry, improve the performance of multiple-batch digestion of community solid waste, and provide relevant biological evidence. [ABSTRACT FROM AUTHOR]

The development and performance of a DNA probe adsorbing Mn2+-modified black phosphorus (BP@Mn2+/DNA) hybrid nanosensor is reported that enables rapid detection of cancer-derived exosomal microRNAs (miRNAs) and exosomes. This two-dimensional (2D) nanosensor can spontaneously penetrate the lipid bilayer of exosome membranes owing to its ultra-thin geometry. Subsequently, the adsorbed probe specifically hybridizes with the target miRNA and then dissociates from the nanosensor surface, generating fluorescent signals. Therefore, the BP@Mn2+/DNA nanosensor can differentiate between colorectal cancer (CRC) cell-derived exosomes and those derived from intestinal epithelial cells through sensing of exosomal miRNAs. Furthermore, when the epithelial cell adhesion molecule (EpCAM) aptamer is adsorbed onto BP@Mn2+ instead of the miRNA probe, the nanosensor is able to distinguish exosomes derived from the plasma of CRC patients from those of healthy controls by the recognition ability of the EpCAM aptamer. By utilizing this nanosensor, we were able to effectively differentiate cancer-derived exosomes through the direct detection of miRNA-21 within the exosomes, as well as the identification of specific exosomal membrane proteins. This nanosensor design paves the way for the development of rapid and efficient cancer-derived exosomal miRNA and exosome biosensing nanoplatforms. [ABSTRACT FROM AUTHOR]

Cell-cultivated fish offers the potential for a more ethical, sustainable, and safe seafood system. However, fish cell culture is relatively understudied in comparison to mammalian cells. Here, we established and characterized a continuous Atlantic mackerel (Scomber scombrus) skeletal muscle cell line ("Mack" cells). The cells were isolated from muscle biopsies of fresh-caught fish, with separate isolations performed from two distinct fish. Mack1 cells (cells from the first isolation) were cultured for over a year and subcultured over 130 times. The cells proliferated at initial doubling times of 63.9 h (± 19.1 SD). After a spontaneous immortalization crisis from passages 37–43, the cells proliferated at doubling times of 24.3 h (± 4.91 SD). A muscle phenotype was confirmed through characterization of muscle stemness and differentiation via paired-box protein 7 and myosin heavy chain immunostaining, respectively. An adipocyte-like phenotype was also demonstrated for the cells through lipid accumulation, confirmed via Oil Red O staining and quantification of neutral lipids. New qPCR primers (HPRT, PAX3B, MYOD1, MYOG, TNNT3A, and PPARG) were tailored to the mackerel genome and used to characterize mackerel cell genotypes. This work provides the first spontaneously immortalized fish muscle cell line for research, ideally serving as a reference for subsequent investigation. [ABSTRACT FROM AUTHOR]

Purpose: As an important component of the microenvironment, the gastric microbiota and its metabolites are associated with tumour occurrence, progression, and metastasis. However, the relationship between the gastric microbiota and the development of gastric cancer is unclear. The present study investigated the role of the gastric mucosa microbiome and metabolites as aetiological factors in gastric carcinogenesis.Gastric biopsies from different stomach microhabitats (n = 70) were subjected to 16S rRNA gene sequencing, and blood samples (n = 95) were subjected to untargeted metabolome (gas chromatography‒mass spectrometry, GC‒MS) analyses. The datasets were analysed using various bioinformatics approaches.The microbiota diversity and community composition markedly changed during gastric carcinogenesis. High Helicobacter. pylori colonization modified the overall diversity and composition of the microbiota associated with gastritis and cancer in the stomach. Most importantly, analysis of the functional features of the microbiota revealed that nitrate reductase genes were significantly enriched in the tumoral microbiota, while urease-producing genes were significantly enriched in the microbiota of H. pylori-positive patients. A panel of 81 metabolites was constructed to discriminate gastric cancer patients from gastritis patients, and a panel of 15 metabolites was constructed to discriminate H. pylori-positivepatients from H. pylori-negative patients. receiver operator characteristic (ROC) curve analysis identified a series of gastric microbes and plasma metabolites as potential biomarkers of gastric cancer.The present study identified a series of signatures that may play important roles in gastric carcinogenesis and have the potential to be used as biomarkers for diagnosis and for the surveillance of gastric cancer patients with minimal invasiveness.Methods: As an important component of the microenvironment, the gastric microbiota and its metabolites are associated with tumour occurrence, progression, and metastasis. However, the relationship between the gastric microbiota and the development of gastric cancer is unclear. The present study investigated the role of the gastric mucosa microbiome and metabolites as aetiological factors in gastric carcinogenesis.Gastric biopsies from different stomach microhabitats (n = 70) were subjected to 16S rRNA gene sequencing, and blood samples (n = 95) were subjected to untargeted metabolome (gas chromatography‒mass spectrometry, GC‒MS) analyses. The datasets were analysed using various bioinformatics approaches.The microbiota diversity and community composition markedly changed during gastric carcinogenesis. High Helicobacter. pylori colonization modified the overall diversity and composition of the microbiota associated with gastritis and cancer in the stomach. Most importantly, analysis of the functional features of the microbiota revealed that nitrate reductase genes were significantly enriched in the tumoral microbiota, while urease-producing genes were significantly enriched in the microbiota of H. pylori-positive patients. A panel of 81 metabolites was constructed to discriminate gastric cancer patients from gastritis patients, and a panel of 15 metabolites was constructed to discriminate H. pylori-positivepatients from H. pylori-negative patients. receiver operator characteristic (ROC) curve analysis identified a series of gastric microbes and plasma metabolites as potential biomarkers of gastric cancer.The present study identified a series of signatures that may play important roles in gastric carcinogenesis and have the potential to be used as biomarkers for diagnosis and for the surveillance of gastric cancer patients with minimal invasiveness.Results: As an important component of the microenvironment, the gastric microbiota and its metabolites are associated with tumour occurrence, progression, and metastasis. However, the relationship between the gastric microbiota and the development of gastric cancer is unclear. The present study investigated the role of the gastric mucosa microbiome and metabolites as aetiological factors in gastric carcinogenesis.Gastric biopsies from different stomach microhabitats (n = 70) were subjected to 16S rRNA gene sequencing, and blood samples (n = 95) were subjected to untargeted metabolome (gas chromatography‒mass spectrometry, GC‒MS) analyses. The datasets were analysed using various bioinformatics approaches.The microbiota diversity and community composition markedly changed during gastric carcinogenesis. High Helicobacter. pylori colonization modified the overall diversity and composition of the microbiota associated with gastritis and cancer in the stomach. Most importantly, analysis of the functional features of the microbiota revealed that nitrate reductase genes were significantly enriched in the tumoral microbiota, while urease-producing genes were significantly enriched in the microbiota of H. pylori-positive patients. A panel of 81 metabolites was constructed to discriminate gastric cancer patients from gastritis patients, and a panel of 15 metabolites was constructed to discriminate H. pylori-positivepatients from H. pylori-negative patients. receiver operator characteristic (ROC) curve analysis identified a series of gastric microbes and plasma metabolites as potential biomarkers of gastric cancer.The present study identified a series of signatures that may play important roles in gastric carcinogenesis and have the potential to be used as biomarkers for diagnosis and for the surveillance of gastric cancer patients with minimal invasiveness.Conclusion: As an important component of the microenvironment, the gastric microbiota and its metabolites are associated with tumour occurrence, progression, and metastasis. However, the relationship between the gastric microbiota and the development of gastric cancer is unclear. The present study investigated the role of the gastric mucosa microbiome and metabolites as aetiological factors in gastric carcinogenesis.Gastric biopsies from different stomach microhabitats (n = 70) were subjected to 16S rRNA gene sequencing, and blood samples (n = 95) were subjected to untargeted metabolome (gas chromatography‒mass spectrometry, GC‒MS) analyses. The datasets were analysed using various bioinformatics approaches.The microbiota diversity and community composition markedly changed during gastric carcinogenesis. High Helicobacter. pylori colonization modified the overall diversity and composition of the microbiota associated with gastritis and cancer in the stomach. Most importantly, analysis of the functional features of the microbiota revealed that nitrate reductase genes were significantly enriched in the tumoral microbiota, while urease-producing genes were significantly enriched in the microbiota of H. pylori-positive patients. A panel of 81 metabolites was constructed to discriminate gastric cancer patients from gastritis patients, and a panel of 15 metabolites was constructed to discriminate H. pylori-positivepatients from H. pylori-negative patients. receiver operator characteristic (ROC) curve analysis identified a series of gastric microbes and plasma metabolites as potential biomarkers of gastric cancer.The present study identified a series of signatures that may play important roles in gastric carcinogenesis and have the potential to be used as biomarkers for diagnosis and for the surveillance of gastric cancer patients with minimal invasiveness. [ABSTRACT FROM AUTHOR]

Purpose: Hepatocellular carcinoma (HCC) is one of the most common cancers in the world with a high mortality rate. Receptor tyrosine kinases play important roles in the occurrence and development of various cancers. Discoid protein domain receptor 1 (DDR1) is a special type of transmembrane receptor tyrosine kinase. Here, we show that the expression of DDR1 is significantly increased in HCC and is related to a poor clinical prognosis. Methods: The expression of DDR1 in HCC cell lines and primary HCC specimens was evaluated using Western blotting and immunohistochemistry. A correlation between DDR1 and SLC1A5 expression was also investigated in primary HCC specimens. Cell proliferation was evaluated using in vitro CCK8 and colony formation assays. Gene knock-down and overexpression assays, CHX, NH4CL and Mg132 interference tests and immunoprecipitation, as well as nude mouse xenograft models were used to assess the mechanism by which DDR1 promotes tumorigenesis in vitro and in vivo. Results: We found that DDR1 promotes the proliferation of HCC cells and accelerates the growth of HCC tumor xenografts, while DDR1 downregulation had the opposite effect. We also found that loss or gain of DDR1 expression affected HCC cell cycle progression. Mechanistically, we found that DDR1 interacts with SLC1A5, which belongs to the solute carrier (SLC) family of transporters, and regulates its stability, thereby affecting the mTORC1 signaling pathway. In addition, we found that SLC1A5 regulation by DDR1 can be restored by lysosome inhibitors. We also found that DDR1 is highly expressed in HCC tissues and that increased DDR1 expression predicts a shorter overall survival (OS) time. We additionally found that the expression of SLC1A5 was positively correlated with that of DDR1. Together, our data indicate that DDR1 acts as a tumor-promoting factor that can control HCC cell proliferation and cell cycle progression by stabilizing SLC1A5 in a lysosome-dependent way. Conclusions: Our study reveals a new mechanism by which DDR1 plays a liver cancer-promoting role. We also found that DDR1 expression serves as an independent prognostic marker, and that DDR1 and SLC1A5 expression levels are positively correlated in clinical samples. Our findings provide a new perspective for understanding HCC development and offers new targets for the treatment and management of HCC. [ABSTRACT FROM AUTHOR]