Electrophoretic Microplate Protein Identification Based on Gold Staining of Molybdenum Disulfide Hydrogels.

Numerous high-performance nanotechnologies have been developed, but their practical applications are largely restricted by the nanomaterials' low stabilities and high operation complexity in aqueous substrates. Herein, we develop a simple and high-reliability hydrogel-based nanotechnology based on the in situ formation of Au nanoparticles in molybdenum disulfide (MoS2)-doped agarose (MoS2/AG) hydrogels for electrophoresis-integrated microplate protein recognition. After the incubation of MoS2/AG hydrogels in HAuCl4 solutions, MoS2 nanosheets spontaneously reduce Au ions, and the hydrogels are remarkably stained with the color of as-synthetic plasmonic Au hybrid nanomaterials (Au staining). Proteins can precisely mediate the morphologies and optical properties of Au/MoS2 heterostructures in the hydrogels. Consequently, Au staining-based protein recognition is exhibited, and hydrogels ensure the comparable stabilities and sensitivities of protein analysis. In comparison to the fluorescence imaging and dye staining, enhanced sensitivity and recognition performances of proteins are implemented by Au staining. In Au staining, exfoliated MoS2 semiconductors directly guide the oriented growth of plasmonic Au nanostructures in the presence of formaldehyde, showing environment-friendly features. The Au-stained hydrogels merge the synthesis and recognition applications of plasmonic Au nanomaterials. Significantly, the one-step incubation of the electrophoretic hydrogels leads to high simplicity of operation, largely challenging those multiple-step Ag staining routes which were performed with high complexity and formaldehyde toxicity. Due to its toxic-free, simple, and sensitive merits, the Au staining integrated with electrophoresis-based separation and microplate-based high-throughput measurements exhibits highly promising and improved practicality of those developing nanotechnologies and largely facilitates in-depth understanding of biological information.

Genomic profiling informs therapies and prognosis for patients with hepatocellular carcinoma in clinical practice.

Hepatocellular carcinoma (HCC) genomic research has discovered actionable genetic changes that might guide treatment decisions and clinical trials. Nonetheless, due to a lack of large-scale multicenter clinical validation, these putative targets have not been converted into patient survival advantages. So, it's crucial to ascertain whether genetic analysis is clinically feasible, useful, and whether it can be advantageous for patients. We sequenced tumour tissue and blood samples (as normal controls) from 111 Chinese HCC patients at Qingdao University Hospital using the 508-gene panel and the 688-gene panel, respectively. Approximately 95% of patients had gene variations related to targeted treatment, with 50% having clinically actionable mutations that offered significant information for targeted therapy. Immune cell infiltration was enhanced in individuals with TP53 mutations but decreased in patients with CTNNB1 and KMT2D mutations. More notably, we discovered that SPEN, EPPK1, and BRCA2 mutations were related to decreased median overall survival, although MUC16 mutations were not. Furthermore, we found mutant MUC16 as an independent protective factor for the prognosis of HCC patients after curative hepatectomy. In conclusion, this study connects genetic abnormalities to clinical practice and potentially identifies individuals with poor prognoses who may benefit from targeted treatment or immunotherapy.

Appropriate livestock grazing alleviates the loss of plant diversity and maintains community resistance in alpine meadows.

Alpine meadows constitute one of the major ecosystems on the Qinghai-Tibetan Plateau, with livestock grazing exerting a considerable impact on their biodiversity. However, the degree to which plant diversity influences community stability under different grazing intensities remains unclear in this region. This study conducted controlled grazing experiments across four levels of grazing intensity (no-, low-, medium-, and high-grazing) based on herbage utilization rate to assess the influence of grazing intensities on plant community structure and diversity-stability relationships. We discovered that high-grazing reduced plant diversity and attenuated the temporal stability and resistance of above-ground biomass. No- and low-grazing could alleviate plant biomass loss, with community resistance being optimal under low-grazing. The direct effects of livestock grazing on temporal stability were found to be negligible. Plant characteristics and diversity accounted for a substantial proportion of livestock grazing effects on community resistance (R2 = 0.46), as revealed by piecewise structural equation model analysis. The presence of plant diversity enhances the resistance of alpine meadows against disturbance and accelerates the recovery after grazing. Our results suggest that low-grazing intensity may represent a judicious option for preserving species diversity and community stability on the Qinghai-Tibetan Plateau.

[Research progress on chemical constituents and pharmacological activities of small molecule compounds in scorpions].

Scorpions, a group of oldest animals with wide distribution in the world, have a long history of medicinal use. Scorpio, the dried body of Buthus martensii, is a rare animal medicine mainly used for the treatment of liver diseases, spasm, and convulsions in children in China. The venom has been considered as the active substance of scorpions. However, little is known about the small molecules in the venom of scorpions. According to the articles published in recent years, scorpions contain amino acids, fatty acids, steroids, and alkaloids, which endow scorpions with antimicrobial, anticoagulant, metabolism-regulating, and antitumor activities. This paper summarizes the small molecule chemical components and pharmacological activities of scorpions, with a view to providing valuable information for the discovery of new active molecules and the clinical use of scorpions.

Mercury-Mediated Epitaxial Accumulation of Au Atoms for Stained Hydrogel-Improved On-Site Mercury Monitoring.

Trivalent Au ions are easily reduced to be zerovalent atoms by coexisting reductant reagents, resulting in the subsequent accumulation of Au atoms and formation of plasmonic nanostructures. In the absence of stabilizers or presence of weak stabilizers, aggregative growth of Au nanoparticles (NPs) always occurs, and unregular multidimensional Au materials are consequently constructed. Herein, the addition of nanomole-level mercury ions can efficiently prevent the epitaxial accumulation of Au atoms, and separated Au NPs with mediated morphologies and superior plasmonic characteristics are obtained. Experimental results and theoretical simulation demonstrate the Hg-concentration-reliant formation of plasmonic nanostructures with their mediated sizes and shapes in the presence of weak reductants. Moreover, the sensitive plasmonic responses of reaction systems exhibit selectivity comparable to that of Hg species. As a concept of proof, polymeric carbon dots (CDs) were used as the initial reductant, and the reactions between trivalent Au and CDs were studies. Significantly, Hg atoms prevent the epitaxial accumulation of Au atoms, and plasmonic NPs with decreased sizes were in situ synthesized, corresponding to varied surface plasmonic resonance absorption performance of the CD-induced hybrids. Moreover, with the integration of sensing substrates of CD-doped hydrogels, superior response stabilities, analysis selectivity, and sensitivity of Hg2+ ions were achieved on the basis of the mercury-mediated in situ chemical reactions between trivalent Au ions and reductant CDs. Consequently, a high-performance sensing strategy with the use of Au NP-staining hydrogels (nanostaining hydrogels) was exhibited. In addition to Hg sensing, the nanostaining hydrogels facilitated by doping of emerging materials and advanced chem/biostrategies can be developed as high-performance on-site monitoring routes to various pollutant species.

ROR1-AS1 might promote in vivo and in vitro proliferation and invasion of cholangiocarcinoma cells.

Long non-coding RNAs (lncRNAs) play important roles in many pathophysiological processes, including cancer progression. Namely, lncRNA Receptor-tyrosine-kinase-like orphan receptor-1 antisense 1 (ROR1-AS1) is crucial for cancer occurrence and progression in organs such as the liver or bladder. However, its expression and role in cholangiocarcinoma (CCA) have not been thoroughly explored.Firstly, we assessed cell viability, proliferation, invasion, and migration using three cell lines (HuCCT-1, QBC399, and RBE) to explore the biological characteristics of ROR1-AS1 in CCA. Secondly, to determine the in vivo effect of ROR1-AS1 on tumor growth, ROR1-AS1 knockdown (KD) HuCCT-1 cells were subcutaneously injected into nude mice to evaluate tumor growth. Finally, we conducted a bioinformatic analysis to confirm the role of ROR1-AS1 in the prognosis and immunity of CCA.In this study, we found that lncRNA ROR1-AS1 was increased in CCA samples and patients with higher ROR1-AS1 expression had a shorter overall survival period. siRNA-mediated KD of ROR1-AS1 significantly reduced cell proliferation and inhibited the migration of CCA cells. In addition, ROR1-AS1 KD HuCCT-1 cells injected into nude mice grew slower than normal CCA cells.In summary, our results show that ROR1-AS1 can promote CCA progression and might serve as a new target for diagnosis and treatment of CCA.

Tracking the Growth of Chiral Plasmonic Nanocrystals at Molybdenum Disulfide Heterostructural Interfaces.

The way of accurately regulating the growth of chiral plasmonics is of great importance for exploring the chirality information and improving its potential values. Herein, cysteine enantiomers modulate the anisotropic and epitaxial growth of gold nanoplasmonics on seeds of exfoliated MoS2 nanosheets. The heterostructural Au and MoS2 hybrids induced by enantiomeric cysteine are presented with chiroptical characteristics, dendritic morphologies, and plasmonic performances. Moreover, the synthesis, condition optimization, formation mechanism, and plasmonic properties of Au and MoS2 dendritic nanostructures are studied. The chirality characteristics are identified using the circular dichroism spectra and scanning electron microscopy. Time-resolved transmission electron microscopy and UV-vis spectra of the intermediate products captured are analyzed to confirm the formation mechanism of dendritic plasmonic nanostructures at heterostructural surfaces. The specific dendritic morphologies originate from the synergistic impacts of heterostructural MoS2 interfaces and enantiomeric cysteine-induced anisotropic manipulation. Significantly, the developed synthesis strategy of chiral nanostructures at heterostructural interfaces is highly promising in promoting the understanding of the plasmonic function and crucial chirality bioinformation.

Immune regulation by fermented milk products: the role of the proteolytic system of lactic acid bacteria in the release of immunomodulatory peptides.

Food allergies have emerged as a pressing health concern in recent years, largely due to food resources and environmental changes. Dairy products fermented by lactic acid bacteria play an essential role in mitigating allergic diseases. Lactic acid bacteria have been found to possess a distinctive proteolytic system comprising a cell envelope protease (CEP), transporter system, and intracellular peptidase. Studying the impact of different Lactobacillus proteolytic systems on the destruction of milk allergen epitopes and their potential to alleviate allergy symptoms by releasing peptides containing immune regulatory properties is a valuable and auspicious research approach. This paper summarizes the proteolytic systems of different species of lactic acid bacteria, especially the correlation between CEPs and the epitopes from milk allergens. Furthermore, the mechanism of immunomodulatory peptide release was also concluded. Finally, further research on the proteolytic system of lactic acid bacteria will provide additional clinical evidence for the possible treatment and/or prevention of allergic diseases with specific fermented milk/dairy products in the future.

Modeling Indirect Greenhouse Gas Emissions Sources from Urban Wastewater Treatment Plants: Integrating Machine Learning Models to Compensate for Sparse Parameters with Abundant Observations.

Electricity consumption and sludge yield (SY) are important indirect greenhouse gas (GHG) emission sources in wastewater treatment plants (WWTPs). Predicting these byproducts is crucial for tailoring technology-related policy decisions. However, it challenges balancing mass balance models and mechanistic models that respectively have limited intervariable nexus representation and excessive requirements on operational parameters. Herein, we propose integrating two machine learning models, namely, gradient boosting tree (GBT) and deep learning (DL), to precisely pointwise model electricity consumption intensity (ECI) and SY for WWTPs in China. Results indicate that GBT and DL are capable of mining massive data to compensate for the lack of available parameters, providing a comprehensive modeling focusing on operation conditions and designed parameters, respectively. The proposed model reveals that lower ECI and SY were associated with higher treated wastewater volumes, more lenient effluent standards, and newer equipment. Moreover, ECI and SY showed different patterns when influent biochemical oxygen demand is above or below 100 mg/L in the anaerobic-anoxic-oxic process. Therefore, managing ECI and SY requires quantifying the coupling relationships between biochemical reactions instead of isolating each variable. Furthermore, the proposed models demonstrate potential economic-related inequalities resulting from synergizing water pollution and GHG emissions management.

Investigating the Shear Strength of Granitic Gneiss Residual Soil Based on Response Surface Methodology.

The shear strength of granitic gneiss residual soil (GGRS) determines the stability of colluvial landslides in the Huanggang area, China. It depends on several parameters that represent its structure and state as well as their interactions, and therefore requires accurate assessment. For an effective evaluation of shear strength parameters of GGRS based on these factors and their interactions, three parameters, namely, moisture content, bulk density, and fractal dimension of grain size, were selected as influencing factors in this study based on a thorough investigation of the survey data and physical property tests of landslides in the study area. The individual effects and interaction of the factors were then incorporated by implementing a series of direct shear tests employing the response surface methodology (RSM) into the regression model of the shear parameters. The results indicate that the factors affecting shear parameters in the order of greater to lower are bulk density, moisture content, and fractal dimension, and their interactions are insignificant. The proposed model was validated by applying it to soil specimens from other landslide sites with the same parent bedrock, showing the validity of the strength regression model. This study demonstrates that RSM can be applied for parameter estimation of soils and provide reliable performance, and is also significant for conducting landslide investigation, evaluation, and regional risk assessment.

Harnessing Oxidative Microenvironment for In Vivo Synthesis of Subcellular Conductive Polymer Microesicles Enhances Nerve Reconstruction.

Conductive polymers (CPs) are promising biomaterials to address signal connection at biointerfaces for tissue regeneration. However, regulating material microstructure at the subcellular scale to provide a more seamless interface between conductive substrates and cells remains a great challenge. Here, we demonstrate that chemical factors and enzyme-carried subcellular structures at lesion site provide a natural bioreactor to self-assemble conductive microvesicles (CMVs) for improving bioelectrical signal reconstruction. The synthesized CMVs contribute to the electrical conduction of the injured nerve in the early stage. Moreover, CMVs are eventually expelled via lymphatic capillary to minimize space-occupying and chronic inflammation. Therefore, we provide a prototype to integrate specific physiological microenvironments and polymer chemistry to manufacture subcellular functional materials with self-adaptive interface in vivo for biomedical applications.

Artificial intelligence for histological subtype classification of breast cancer: combining multi-scale feature maps and the recurrent attention model.

AIMS: The aim of this study was to apply a two-stage deep model combining multi-scale feature maps and the recurrent attention model (RAM) to assist with the pathological diagnosis of breast cancer histological subtypes by the use of whole slide images (WSIs). METHODS AND RESULTS: In this article, we propose an integrated framework combining multi-scale feature maps from Inception V3 and the recurrent attention model to classify the six histological subtypes of breast cancer. This model was trained with 194 WSIs, and on 63 validation WSIs the model achieved accuracies of 0.9030 for patch-level classification and 0.8889 for WSI-level classification. In the testing stage, a total of 65 WSIs were used to achieve an accuracy of 0.8462 without any form of data curation. The t-distributed stochastic neighbour embedding showed that features extracted by the feature network of the RAM from WSIs of the same category can cluster together after training, and the visualization of decision steps showed that the decision-making glimpses are focused on the middle tumour area of an example from test WSIs. Finally, the false classification patches indicated that the morphological similarities between tumour tissues of different subtypes or non-tumour tissues and tumour tissues in patches might contribute to misclassification. CONCLUSIONS: This model can imitate the diagnostic process of pathologists, pay attention to a series of local features on the pathology image, and summarize related information, in order to accurately classify breast cancer into its histological subtypes, which is important for treatment and prognosis.

DNA sequencing based on electronic tunneling in a gold nanogap: a first-principles study.

Deoxyribonucleic acid (DNA) sequencing has found wide applications in medicine including treatment of diseases, diagnosis and genetics studies. Rapid and cost-effective DNA sequencing has been achieved by measuring the transverse electronic conductance as a single-stranded DNA is driven through a nanojunction. With the aim of improving the accuracy and sensitivity of DNA sequencing, we investigate the electron transport properties of DNA nucleobases within gold nanogaps based on first-principles quantum transport simulations. Considering the fact that the DNA bases can rotate within the nanogap during measurements, different nucleobase orientations and their corresponding residence time within the nanogap are explicitly taken into account based on their energetics. This allows us to obtain an average current that can be compared directly to experimental measurements. Our results indicate that bare gold electrodes show low distinguishability among the four DNA nucleobases while the distinguishability can be substantially enhanced with sulfur atom decorated electrodes. We further optimized the size of the nanogap by maximizing the residence time of the desired orientation.

Aberrant functional connectivity in insular subregions in somatic depression: a resting-state fMRI study.

BACKGROUND: Somatic depression (SD) is different from non-somatic depression (NSD), and insular subregions have been associated with somatic symptoms. However, the pattern of damage in the insular subregions in SD remains unclear. The aim of this study was to use functional connectivity (FC) analyses to explore the bilateral ventral anterior insula (vAI), bilateral dorsal anterior insula (dAI), and bilateral posterior insula (PI) brain circuits in SD patients. METHODS: The study included 28 SD patients, 30 NSD patients, and 30 matched healthy control (HC) subjects. All participants underwent 3.0 T resting state functional magnetic resonance imaging. FC analyses were used to explore synchronization between insular subregions and the whole brain in the context of depression with somatic symptoms. Pearson correlation analyses were performed to assess relationships between FC values in brain regions showing significant differences and the total and factor scores on the 17-item Hamilton Rating Scale for Depression (HAMD17). RESULTS: Compared with the NSD group, the SD group showed significantly decreased FC between the left vAI and the right rectus gyrus, right fusiform gyrus, and right angular gyrus; between the right vAI and the right middle cingulate cortex, right precuneus, and right superior frontal gyrus; between the left dAI and the left fusiform gyrus; and between the right dAI and the left postcentral gyrus. Relative to the NSD group, the SD group exhibited increased FC between the left dAI and the left fusiform gyrus. There were no differences in FC between bilateral PI and any brain regions among the SD, NSD, and HC groups. Within the SD group, FC values between the left vAI and right rectus gyrus were positively correlated with cognitive impairment scores on the HAMD17; FC values between the right vAI and right superior frontal gyrus were positively related to the total scores and cognitive impairment scores on the HAMD17 (p < 0.05, uncorrected). CONCLUSIONS: Aberrant FC between the anterior insula and the frontal and limbic cortices may be one possible mechanism underlying SD.

Factors associated with patient delay for older adults with benign prostatic hyperplasia: A descriptive qualitative study.

Based on the theory of planned behavior, the aim of this study was to describe the influencing factors of patient delay intentions and behaviors in benign prostatic hyperplasia (BPH) patients and to provide a reference for the development of a patient delay intention scale. This study was carried out over 4 months in 2021 in Daqing, Heilongjiang, China. The participants were 20 patients with BPH who were aged 60 to 82 years and experienced patient delay; participants were selected through a purposive sampling method. The data were collected via face-to-face semistructured interviews. Five main themes emerged from the interviews, including an insufficient understanding of symptoms, experiences of coping instead of seeking health care, negative attitudes toward care-seeking, the influence of others on decision-making for care-seeking, and obstacles to seeking health care. In conclusion, the patient delay intentions and behaviors of BPH patients are the result of a combination of many factors.

Controlling the emission frequency of graphene nanoribbon emitters based on spatially excited topological boundary states.

Graphene nanoribbons (GNRs) with atomically precise heterojunction interfaces are exploited as nanoscale light emitting devices with modulable emission frequencies. By connecting GNRs with different widths and lengths, topological boundary states can be formed and manipulated. Using first-principles-based atomistic simulations, we studied the luminescence properties of a STM GNR junction and explored the applications of these topological states as nanoscale light sources. Taking advantage of the ultrahigh resolution of the STM tip, direct injection of high energy carriers at selected boundary states can be achieved. In this way, the emission color can be controlled by precisely changing the tip position. The GNR heterojunction can therefore represent a robust and controllable light-emitting device that takes a step forward towards the fabrication of nanoscale graphene-based optoelectronic devices.

Do emotional labour strategies influence emotional exhaustion and professional identity or vice versa? Evidence from new nurses.

AIMS: The aim was to examine the reciprocal relationships of emotional labour strategies with emotional exhaustion and professional identity. DESIGN: This study adopted a four-wave cross-lagged panel design. METHODS: Survey data were collected in 2018 from a sample of 171 newly hired nurses from 58 hospitals in 11 provinces of China. Nurses' emotional labour (i.e., deep acting and surface acting), emotional exhaustion and professional identity were repeatedly measured. Cross-lagged panel analyses were conducted to examine the reciprocal relationships we hypothesized. RESULTS: We found that emotional exhaustion was positively related to surface acting (but not vice versa); deep acting was negatively related to emotional exhaustion (but not vice versa); professional identity was positively related to deep acting (but not vice versa). CONCLUSION: Our findings suggest that deep acting and professional identity may decrease the level of emotional exhaustion, whereas emotionally exhausted nurses are more likely to employ surface acting strategies. IMPACT: This research finding will have an impact on the nursing management. Healthcare managers may consider workshops or training and development programs that promote nurses' professional identify to promote nurses' use of deep acting and consequently reduce their level of emotional exhaustion, which has been associated with a variety of negative consequences, such as low quality of patient service, high medical accidents, and turnover rate.

Deep Convolutional Neural Networks for Automatic Detection of Orbital Blowout Fractures.

Orbital blow out fracture is a common disease in emergency department and a delay or failure in diagnosis can lead to permanent visual changes. This study aims to evaluate the ability of an automatic orbital blowout fractures detection system based on computed tomography (CT) data.Orbital CT scans of adult orbital blowout fractures patients and normal cases were obtained from Shanghai Ninth People's Hospital between January and March 2017. The region of fractures was annotated using 3D Slicer. The Inception V3 convolutional neural networks were constructed utilizing the Python programming language with PyTorch as the framework to extract high dimension features from each slice in a CT scan. These extracted features are processed through a XGBoost model to make the final differentiation of fracture cases and nonfracture ones. Accuracy, receiver operating characteristics, and area under the curve were evaluated.This study used 94 CT scans diagnosed with orbital blowout fractures and 94 healthy control cases. The automatic detection system showed accuracy of 92% in single-image classification and 87% in patient level detection. The area under the receiver operating characteristic curve was 0.9574.Using a deep learning-based automatic detection system of orbital blowout fracture can accurately detect and classify orbital blowout fractures from CT scans. The convolutional neural networks model combined with an accurate annotation system could achieve good performance in a small dataset. Further studies with large and multicenter data are required to refine this technology for possible clinical applications.

Effect of high pressure homogenization treatment on the rheological properties of citrus peel fiber/corn oil emulsion.

BACKGROUND: Citrus fiber is a main component in the peel of citrus and contains natural dietary fiber. It is often used as a functional additive to improve the texture or nutritional property of food. It is also widely used to reduce the content of absorbable fat in sausages and other meat products, and to improve food stability as an emulsifier. In this research, the dynamic rheological properties (linear and non-linear) of citrus peel fiber/corn oil (CF/CO) emulsion system under high pressure homogenization (HPH) treatment was investigated. RESULT: Rheological results illustrated HPH treatment significantly increased the apparent viscosity of the emulsion, reduced the activation energy of the emulsion and distinctly improved the viscoelasticity of the emulsion. Meanwhile, HPH treatment increased the linear viscoelastic region of the sample, and the behavior of the emulsion converted from strain thinning (without HPH treatment) to weak strain overshoot (with HPH treatment). Lissajous curves indicated the viscosity of the sample increased first and then decreased with strain increasing and the third harmonic contributed much more to the first harmonic compared with the fifth harmonic. Chebyshev stress decomposition revealed that, as strain increased, the samples with HPH treatment showed internal-cycle strain hardening behavior first, then turned to internal-cycle softening behavior. CONCLUSION: HPH treatment can significantly improve the processing performance of CF/CO emulsion as well as the stability against large periodic oscillations in food processing. © 2020 Society of Chemical Industry.

Habitat Selection and Genetic Structure of the Endangered Frog Species Odorrana wuchuanensis (Anura: Ranidae).

Understanding the habitat selection and population genetic structure of an endangered species can play important roles in its protection. The Wuchuan odorous frog (Odorrana wuchuanensis) is endemic to the karst regions of southwest China. This frog is currently listed as "Critically Endangered" by the IUCN, but little is known about its habitat selection and population genetics. In this study, we conducted analyses of habitat selection with occurrence/absence sites and environmental data, and assessed the genetic structure between north and south populations in Guizhou provinces in China using three mitochondrial markers. The results revealed that the probability of this frog occupying cave habitats increased with higher average humidity in July and higher lowest temperature in January, but was negatively related to precipitation in January. Analyses of F statistics combined with analyses of median-joining haplotype networks and the phylogenetic tree showed low genetic differentiation between the two populations of O. wuchuanensis. Considering the small population size and geographic isolation because of the complex karst terrains, we suggest careful management practices are needed to protect this species.