An induced pluripotent stem cell line carrying a silencing-resistant calcium reporter allele.

Calcium indicators are sensitive tools to image neural activity. However, their use in human induced pluripotent stem cells (iPSC)-derived neurons is limited by silencing of the transgene. We generated the iPSC line MSE2336A carrying heterozygous insertion in the safe-harbor locus AAVS1 of the ultrasensitive protein calcium sensor (GCaMP6) under the control of CAG promoter and UCOE to maintain robust transgene expression in differentiated cells. The iPSC exhibited normal cell morphology, expression of pluripotency markers, genome integrity, and the ability to differentiate into the three primary germ layers. This line provides a powerful model to study activity in human neurons.

Identification of PANoptosis-related predictors for prognosis and tumor microenvironment by multiomics analysis in glioma.

PANoptosis is a newly described inflammatory programmed cell death, that highlights coordination between pyroptosis, apoptosis and necroptosis. However, the functions of PANoptosis-related genes in glioma progression still remain to be explored. This study aims to identify PANoptosis-related predictors that may be utilized for prognosis prediction and development of new therapeutic targets. Firstly, bulk and single-cell RNA-seq (scRNA-seq) data of glioma patients were extracted from TCGA, CGGA and GEO database. Genetic analysis indicates a considerably high mutation frequency of PANoptosis-related genes (PANRGs) in glioma. Consensus clustering was applied to reveal different subtypes of glioma based on PANRGs. Two PANoptosis subtypes with distinct prognostic and TME characteristics were identified. Then, with LASSO-Cox regression analysis, four PANoptosis-related predictors (MYBL2, TUBA1C, C21orf62 and KCNIP2) were determined from bulk and scRNA-seq analysis. Predictive PANRG score model was established with these predictors and its correlation with tumor microenvironment (TME) was investigated. The results showed that patients with low PANRG score, had higher infiltration of anti-tumor immune cells, higher MSI score and lower TIDE score, which are more likely to benefit from immunotherapy. Further analysis identified 16 potential drugs associated with PANoptosis-related predictors. Moreover, the expression levels of four PANoptosis-related predictors were examined in clinical samples and the results were consistent with those analyzed in the database. Besides, we also confirmed the biological functions of two oncogenic predictors (MYBL2 and TUBA1C) by cell experiments, which revealed that knockdown of MYBL2 or TUBA1C could significantly inhibit the proliferation and migration of glioma cells. These findings highlight the prognostic value and biological functions of PANRGs in glioma, which may provide valuable insights for individualized treatment.

Fermi-Level Pinning in ErAs Nanoparticles Embedded in III-V Semiconductors.

Embedding rare-earth monopnictide nanoparticles into III-V semiconductors enables unique optical, electrical, and thermal properties for THz photoconductive switches, tunnel junctions, and thermoelectric devices. Despite the high structural quality and control over growth, particle size (<3 nm), and density, the underlying electronic structure of these nanocomposite materials has only been hypothesized. Structural and electronic properties of ErAs nanoparticles with different shapes and sizes (cubic to spherical, 1.14, 1.71, and 2.28 nm) in AlAs, GaAs, InAs, and their alloys are investigated using first-principles calculations, revealing that spherical nanoparticles have lower formation energies. For the lowest-energy nanoparticles, the Fermi level is pinned near midgap in GaAs and AlAs but resonant in the conduction band in InAs. The Fermi level is shifted down as the particle size increases and is pinned on an absolute energy scale considering the band alignment at AlAs/GaAs/InAs interfaces, offering insights into the rational design of these nanomaterials.

Identification and Structural Characterization of Twisted Atomically Thin Bilayer Materials by Deep Learning.

Two-dimensional materials are expected to play an important role in next-generation electronics and optoelectronic devices. Recently, twisted bilayer graphene and transition metal dichalcogenides have attracted significant attention due to their unique physical properties and potential applications. In this study, we describe the use of optical microscopy to collect the color space of chemical vapor deposition (CVD) of molybdenum disulfide (MoS2) and the application of a semantic segmentation convolutional neural network (CNN) to accurately and rapidly identify thicknesses of MoS2 flakes. A second CNN model is trained to provide precise predictions on the twist angle of CVD-grown bilayer flakes. This model harnessed a data set comprising over 10,000 synthetic images, encompassing geometries spanning from hexagonal to triangular shapes. Subsequent validation of the deep learning predictions on twist angles was executed through the second harmonic generation and Raman spectroscopy. Our results introduce a scalable methodology for automated inspection of twisted atomically thin CVD-grown bilayers.

Emerging Nontrivial Topology in Ultrathin Films of Rare-Earth Pnictides.

Thin films of rare-earth monopnictide (RE-V) semimetals are expected to turn into semiconductors due to quantum confinement effects (QCE), lifting the overlap between electron pockets at Brillouin zone edges (X) and hole pockets at the zone center (Γ). Instead, using LaSb as an example, we find the emergence of the quantum spin Hall (QSH) insulator phase in (001)-oriented films as the thickness is reduced to 7, 5, or 3 monolayers (MLs). This is attributed to a strong QCE on the in-plane electron pockets and the lack of quantum confinement on the out-of-plane pocket projected onto the zone center, resulting in a band inversion. Spin-orbit coupling (SOC) opens a sizable nontrivial gap in the band structure of ultrathin films. Such effect is anticipated to be general in rare-earth monopnictides and may lead to interesting phenomena when coupled with the 4f magnetic moments present in other members of this family of materials.

Lidocaine ameliorates intestinal barrier dysfunction in irritable bowel syndrome by modulating corticotropin-releasing hormone receptor 2.

BACKGROUND: Intestinal barrier dysfunction is a prevalent pathogenic factor underlying various disorders. Currently there is no effective resolution. Previous studies have reported the potential anti-inflammatory properties of lidocaine and its ability to alleviate visceral hypersensitivity in individuals with irritable bowel syndrome (IBS). Therefore, our study will further verify the effect of lidocaine on intestinal barrier dysfunction in IBS and investigate the underlying mechanisms. METHODS: In this study, we investigated the role of lidocaine by assessing visceral hypersensitivity, body weight, inflammatory factors, fluorescein isothiocyanate-dextran 4000 (FD4) flux, tight junctions (TJs) and spleen and thymus index in rats subjected to water avoidance stress (WAS) to mimic intestinal barrier dysfunction in IBS with and without lidocaine. In vitro, we investigated the role of corticotropin-releasing hormone receptor 2 (CRHR2) in lidocaine-treated Caco2 cells using small interfering RNA (siRNA) targeting CRHR2. KEY RESULTS: In WAS rats, lidocaine significantly restored weight loss, damaged TJs, spleen index and thymus index and inhibited abdominal hypersensitivity as well as blood levels of markers indicating intestinal permeability, such as diamine oxidase (DAO), D-lactic acid (D-Lac) and lipopolysaccharide (LPS). Consequently, the leakage of FD4 flux from intestine was significantly attenuated in lidocaine group, and levels of intestinal inflammatory factors (IL-1ß, IFN-γ, TNF-α) were reduced. Interestingly, lidocaine significantly suppressed corticotropin-releasing hormone (CRH) levels in lamina propria cells, while the CRH receptor CRHR2 was upregulated in intestinal epithelial cells. In vitro, lidocaine enhanced the expression of CRHR2 on Caco-2 intestinal epithelial cells and restored disrupted TJs and the epithelial barrier caused by LPS. Conversely, these effects were diminished by a CRHR2 antagonist and siRNA-CRHR2, suggesting that the protective effect of lidocaine depends on CRHR2. CONCLUSIONS AND INFERENCES: Lidocaine ameliorates intestinal barrier dysfunction in IBS by potentially modulating the expression of CRHR2 on intestinal epithelial cells.

The interaction between dietary fiber and gut microbiota, and its effect on pig intestinal health.

Intestinal health is closely associated with overall animal health and performance and, consequently, influences the production efficiency and profit in feed and animal production systems. The gastrointestinal tract (GIT) is the main site of the nutrient digestive process and the largest immune organ in the host, and the gut microbiota colonizing the GIT plays a key role in maintaining intestinal health. Dietary fiber (DF) is a key factor in maintaining normal intestinal function. The biological functioning of DF is mainly achieved by microbial fermentation, which occurs mainly in the distal small and large intestine. Short-chain fatty acids (SCFAs), the main class of microbial fermentation metabolites, are the main energy supply for intestinal cells. SCFAs help to maintain normal intestinal function, induce immunomodulatory effects to prevent inflammation and microbial infection, and are vital for the maintenance of homeostasis. Moreover, because of its distinct characteristics (e.g. solubility), DF is able to alter the composition of the gut microbiota. Therefore, understanding the role that DF plays in modulating gut microbiota, and how it influences intestinal health, is essential. This review gives an overview of DF and its microbial fermentation process, and investigates the effect of DF on the alteration of gut microbiota composition in pigs. The effects of interaction between DF and the gut microbiota, particularly as they relate to SCFA production, on intestinal health are also illustrated.

Digital transformation, technological innovation, and operational resilience of port firms in case of supply chain disruption.

To investigate how the digital transformation of port firms improves their operational resilience, we design methods to measure their digital transformation grade (DTG), technological innovation capacity (TIC), and port operational resilience (POR) respectively. Based on 3586 samples retrieved from 334 Chinese port firms from 2011 to 2021, their relationships are statistically described and preliminarily regressed by an ordinary least-squares model and a fixed-effect model. After testing the effects of supply chain disruption, endogeneity, and robustness, we reveal that digital transformation improves firms' competitiveness and operational resilience by coordinating human resources, information, and technology. We confirm that TIC plays an intermediate role and an adverse event has an enhancement effect. An inverted-U curve between DTG and POR proves that port firms often suffer growing pains at the initial stage and their POR will be promoted by continuous digital inputs, but the leading port firms would gain fewer marginal benefits.

Soil variables and reflected light revealed the plasticity of grape and wine composition: Regulation of the flavoromics under inner row gravel covering.

Abundant gravel in vineyards bothers growers. To investigate the gravel covering inner-row effect on grapes and wines, a two-year experiment was carried out. Regional climate and vine microclimate were collected, the flavoromics of grapes and wines were determined by HPLC-MS and HS/SPME-GC-MS. Gravel covering reduced the soil moisture. Light-colored gravel covering (LGC) enhanced the reflected light by 7-16% and cluster-zone temperature by up to 2.5 °C. Dark-colored gravel covering (DGC) absorbed 13% of the solar radiation and cooled the cluster-zones. DGC promoted the accumulation of 3'4'5'-hydroxylated anthocyanins and C6/C9 compounds in grapes, while grapes of LGC were accompanied by higher flavonols. The phenolic profiles of grapes and wines among treatments were consistent. The overall aroma of grapes from LGC was lower, while DGC helped to weaken the negative effects of rapid ripening in warm vintages. Our results revealed the gravel regulate grape and wine quality through soil and cluster microclimate.

Failure progression and toughening mechanism of 3D-printed nacre-like structures under in-plane compression.

Nacre (also called mother-of-pearl) is known to have a delicate balance of stiffness, strength, and toughness, which originates from its 'brick-and-mortar' structure. In this study, nacre-like structures are fabricated using a high-resolution, multi-material 3D printer, where two different polyurethane acrylates (one that is hard and another that is soft) are used to represent the tablets and matrix. Six nacre-like structures are designed and fabricated to explore the influence of geometric parameters on the mechanical behaviors. Quasi-static in-plane compression tests and simulations are carried out to explore the failure mechanism of the nacre-like structures. The results show that the quasi-static compression responses of nacre-like structures have four stages: elastic, plateau, fragmentation, and densification. It is found that tuning the nacre architecture can optimize the mechanical performance of the specimen, including the peak load, ductility and stress reduction behavior et al. As the results of the numerical model show good agreement with the stress-strain response observed in the experiments, the model is applied to further investigate the strain distributions of the nacre-like structures. The patterns of the strain distribution suggest that synergistic deformation is the key toughening mechanism for the nacre-like structures.

The formulation of irrigation and nitrogen application strategies under multi-dimensional soil fertility targets based on preference neural network.

With the aim of improving soil fertility, it is of great significance to put forward optimal irrigation and nitrogen fertilizer application strategies for improving land productivity and alleviating non-point source pollution effects. To overcome this task, a 6-hidden layer neural network with a preference mechanism, namely Preference Neural network (PNN), has been developed in this study based on the field data from 2018 to 2020. PNN takes soil total nitrogen, organic matter, total salt, pH, irrigation time and target soil depth as input, and irrigation amount and nitrogen application rate (N rate) as output, and the prior preference matrix was used to adjust the learning of weight matrix of each layer. The outcomes indicated that the predictive accuracy of PNN for irrigation amount were (R2 = 0.913, MAE = 0.018, RMSE = 0.022), and for N rate were (R2 = 0.943, MAE = 0.009, RMSE = 0.011). The R2 predicted by PNN at the irrigation amount and N rate were 40.03% to more than 99% and 40.33% to more than 99% higher than those obtained using support vector regression (SVR), linear regression (LR), logistic regression (LOR) and traditional back propagation neural network (BPNN), respectively. In addition, compared with the neural network (Reverse Multilayer Perceptron, RMLP) with the same structure but no preference structure, the R2 of the predicted irrigation amount and N rate by PNN increased by 25.81% and 27.99%, respectively. The results showed that, through the irrigation of 93 to 102, 92 to 98 and 92 to 98 mm, along with nitrogen applications of 65 to 71, 64 to 73 and 72 to 81 kg/hm2 at 17, 59 and 87 days after sowing, respectively, the organic matter, total nitrogen, total salt content and pH of the soil would reach high fertility levels simultaneously.

Physins in digestive system neoplasms.

The physin family of proteins, synaptophysin (SYP), synaptophysin like 1 (SYPL1), synaptophysin like 2 (SYPL2) and synaptoporin (SYNRP), are tetratransmembrane transport vesicle proteins distributed throughout the digestive system. Of these, SYP is a required marker for histopathologic identification of neuroendocrine neoplasms (NENs), especially in gastroenteropancreatic NENs (GEP-NENs). Recently, bloodstream SYP, i.e., on platelets and circulating tumor cells, has been correlated to clinicopathologic features of GEP-NENs and may have prognostic significance. Serum SYPL1 also represents a promising biomarker for colorectal cancer. This chapter provides an overview of physin structures and potential use as diagnostic, prognostic and therapeutic tools for digestive tract neoplasms.

Bi2Se3 Growth on (001) GaAs Substrates for Terahertz Integrated Systems.

Terahertz (THz) technologies have been of interest for many years due to the variety of applications including gas sensing, nonionizing imaging of biological systems, security and defense, and so forth. To date, scientists have used different classes of materials to perform different THz functions. However, to assemble an on-chip THz integrated system, we must understand how to integrate these different materials. Here, we explore the growth of Bi2Se3, a topological insulator material that could serve as a plasmonic waveguide in THz integrated devices, on technologically important GaAs(001) substrates. We explore surface treatments and find that an atomically smooth GaAs surface is critical to achieving high-quality Bi2Se3 films despite the relatively weak film/substrate interaction. Calculations indicate that the Bi2Se3/GaAs interface is likely selenium-terminated and shows no evidence of chemical bonding between the Bi2Se3 and the substrate. These results are a guide for integrating van der Waals materials with conventional semiconductor substrates and serve as the first steps toward achieving an on-chip THz integrated system.

Mapping cis-regulatory elements in human neurons links psychiatric disease heritability and activity-regulated transcriptional programs.

Genome-wide association studies (GWASs) have identified hundreds of loci associated with psychiatric diseases, yet there is a lack of understanding of disease pathophysiology. Common risk variants can shed light on the underlying molecular mechanisms; however, identifying causal variants remains challenging. We map cis-regulatory elements in human neurons derived from pluripotent stem cells. This system allows us to determine enhancers that activate the transcription of neuronal activity-regulated gene programs, which are thought to be critical for synaptic plasticity and are not possible to identify from postmortem tissues. Using the activity-by-contact model, we create variant-to-gene maps to interpret the function of GWAS variants. Our work nominates a subset of variants to elucidate the molecular mechanisms involving GWAS-significant loci. It also highlights that in vitro human cellular models are a powerful platform for identifying and mechanistic studies of human trait-associated genetic variants in cell states that are inaccessible from other types of human samples.

Direct Differentiation of Functional Neurons from Human Pluripotent Stem Cells (hPSCs).

Somatic cell nuclear transfer and in vitro induction of pluripotency in somatic cells by defined factors provided unambiguous evidence that the epigenetic state of terminally differentiated somatic cells is not static and can be reversed to a more primitive one. Inspired by these results, stem cell biologists have identified approaches to directly convert fibroblasts into induced neuronal (iN) cells, indicating that direct lineage conversions are possible between distantly related cell types. More recently, we took advantages of pro-neurogenic capacity of iN factors and developed methods to rapidly derive functionally mature neurons directly from human pluripotent stem cells (hPSCs) through a brief induction of defined transcription factors. In this chapter, we describe the detailed methods used to attain the direct conversion from hPSCs to glutamatergic and GABAergic iN cells.

In-situ investigation of dye pollutant adsorption performance on graphitic carbon nitride surface: ATR spectroscopy experiment and MD simulation insight.

The adsorption performances on graphitic carbon nitride (g-C3N4) surface were investigated for organic dye pollutants by both experimental and calculation methods. For experimental investigation, adsorption thermodynamics and kinetics results were in-situ obtained and evaluated. With [Formula: see text] by Langmuir modeling, g-C3N4 showed superior adsorption spontaneity of MB+ >MO-. With linear and exponential modeling, g-C3N4 showed only adsorption process for MB+ but both diffusion and adsorption processes for MO-. For simulation insight, all MB+ molecules but only parts of MO- molecules were inclined to orient in parallel position at g-C3N4 surface after optimization during low concentration. And both MB+ and MO- molecules were inclined to orient in perpendicular position at g-C3N4 surface after optimization during high concentration. Combined with experimental and calculation results, a molecular-orientation and force-dominance mechanism adsorption model are proposed to explain the surface interaction processes between dyes and g-C3N4. Electrostatic interaction and π-π stacking interaction were revealed to dominate for MB+ adsorption, and π-π stacking interaction and van der Waals force were revealed to dominate for MO- adsorption. This work obtained 'localized' interfacial information and elucidated in-situ intermolecular interactions at g-C3N4 interface, which can provide fundamental basis for operation removal of organic dye pollutants by g-C3N4.

Comprehensive mutanome analysis of Lewis lung cancer reveals immunogenic neoantigens for therapeutic vaccines.

Personalized neoantigen vaccines are capable of eliciting vigorous T-cell responses and have been demonstrated to achieve striking therapeutic effects against cancer. Here we performed comprehensive mutanome analysis of the mouse Lewis lung cancer cells to identify tumor neoantigens followed by prediction of their MHC affinity and immunogenicity. We adopted a strategy that enables us to select neoantigens that were predicted to have high affinity to both MHC I and MHC II. Ten neoantigens were selected to synthesize peptide vaccines and tested in vivo for immunogenicity. Four neoantigen peptide vaccines were found to elicit robust immune reactivity and were further examined for tumor inhibition in mice with xenografted LLC tumors. Two neoantigen peptide vaccines showed significant inhibition on tumor growth and prolonged the survival of tumor-bearing mice. Our studies explored the neoantigen peptide vaccines to treat lung cancer and provide rationale for the optimization of tumor neoantigen selection for therapeutic vaccines.

Perspectives of People Who Are Overweight and Obese on Using Wearable Technology for Weight Management: Systematic Review.

BACKGROUND: Obesity is a large contributor to preventable chronic diseases and health care costs. The efficacy of wearable devices for weight management has been researched; however, there is limited knowledge on how these devices are perceived by users. OBJECTIVE: This study aimed to review user perspectives on wearable technology for weight management in people who are overweight and obese. METHODS: We searched the online databases Pubmed, Scopus, Embase, and the Cochrane library for literature published from 2008 onward. We included all types of studies using a wearable device for delivering weight-loss interventions in adults who are overweight or obese, and qualitative data were collected about participants' perspectives on the device. We performed a quality assessment using criteria relevant to different study types. The Cochrane risk of bias tool was used for randomized controlled trials. The Risk of Bias in Non-randomized Studies - of Interventions (ROBINS-I) was used for nonrandomized studies. The Oxman and Guyatt Criteria were used for systematic reviews. We used the critical appraisal checklist for qualitative studies. Data were extracted into a data extraction sheet and thematically analyzed. RESULTS: We included 19 studies: 5 randomized controlled trials, 6 nonrandomized studies, 5 qualitative studies, and 3 reviews. Mixed perceptions existed for different constructs of wearable technologies, which reflects the differences in the suitability of wearable technology interventions for different individuals in different contexts. This also indicates that interventions were not often tailored to participants' motivations. In addition, very few wearable technology interventions included a thorough qualitative analysis of the participants' view on important features of the intervention that made it successful. CONCLUSIONS: This study highlights the importance of determining the type of intervention most suitable for an individual before the intervention is used. Our findings could help participants find a suitable intervention that is most effective for them. Further research needs to develop a user-centered tool for obtaining comprehensive user feedback. TRIAL REGISTRATION: PROSPERO CRD42018096932; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=96932.

Learning Graph Embedding With Adversarial Training Methods.

Graph embedding aims to transfer a graph into vectors to facilitate subsequent graph-analytics tasks like link prediction and graph clustering. Most approaches on graph embedding focus on preserving the graph structure or minimizing the reconstruction errors for graph data. They have mostly overlooked the embedding distribution of the latent codes, which unfortunately may lead to inferior representation in many cases. In this article, we present a novel adversarially regularized framework for graph embedding. By employing the graph convolutional network as an encoder, our framework embeds the topological information and node content into a vector representation, from which a graph decoder is further built to reconstruct the input graph. The adversarial training principle is applied to enforce our latent codes to match a prior Gaussian or uniform distribution. Based on this framework, we derive two variants of the adversarial models, the adversarially regularized graph autoencoder (ARGA) and its variational version, and adversarially regularized variational graph autoencoder (ARVGA), to learn the graph embedding effectively. We also exploit other potential variations of ARGA and ARVGA to get a deeper understanding of our designs. Experimental results that compared 12 algorithms for link prediction and 20 algorithms for graph clustering validate our solutions.

Rapidly mitigating antibiotic resistant risks in chicken manure by Hermetia illucens bioconversion with intestinal microflora.

Antibiotic resistance genes (ARGs) in animal manure are an environmental concern due to naturally occurring bacteria being exposed to these wastes and developing multidrug resistance. The bioconversion of manure with fly larvae is a promising alternative for recycling these wastes while attenuating ARGs. We investigated the impact of black soldier fly (BSF, Hermetia illucens) larval bioconversion of chicken manure on the persistence of associated ARGs. Compared with traditional composting or sterile larval treatments (by 48.4% or 88.7%), non-sterile BSF larval treatments effectively reduced ARGs and integrin genes by 95.0% during 12 days, due to rapid decreases in concentrations of the genes and associated bacteria as they passed through the larval gut and were affected by intestinal microbes. After larval treatments, bacterial community composition differed significantly, with the percentage of Firmicutes possibly carrying ARGs reduced by 65.5% or more. On average, human pathogenic bacteria populations declined by 70.7%-92.9%, effectively mitigating risks of these bacteria carrying ARGs. Environmental pH, nitrogen content and antibiotic concentrations were closely related to both bacterial community composition and targeted gene attenuation in larval systems. Selective pressures of larval gut environments with intestinal microbes, larval bacteriostasis and reformulation of manure due to larval digestion contributed to ARG attenuation.