China is progressing towards the goal of schistosomiasis elimination, but there are still some problems, such as difficult management of infection source and snail control. This study aimed to ...develop deep learning models with high-resolution remote sensing images for recognizing and monitoring livestock bovine, which is an intermediate source of Schistosoma japonicum infection, and to evaluate the effectiveness of the models for real-world application.
The dataset of livestock bovine's spatial distribution was collected from the Chinese National Platform for Common Geospatial Information Services. The high-resolution remote sensing images were further divided into training data, test data, and validation data for model development. Two recognition models based on deep learning methods (ENVINet5 and Mask R-CNN) were developed with reference to the training datasets. The performance of the developed models was evaluated by the performance metrics of precision, recall, and F1-score.
A total of 50 typical image areas were selected, 1125 bovine objectives were labeled by the ENVINet5 model and 1277 bovine objectives were labeled by the Mask R-CNN model. For the ENVINet5 model, a total of 1598 records of bovine distribution were recognized. The model precision and recall were 81.9% and 80.2%, respectively. The F1 score was 0.81. For the Mask R-CNN mode, 1679 records of bovine objectives were identified. The model precision and recall were 87.3% and 85.2%, respectively. The F1 score was 0.87. When applying the developed models to real-world schistosomiasis-endemic regions, there were 63 bovine objectives in the original image, 53 records were extracted using the ENVINet5 model, and 57 records were extracted using the Mask R-CNN model. The successful recognition ratios were 84.1% and 90.5% for the respectively developed models.
The ENVINet5 model is very feasible when the bovine distribution is low in structure with few samples. The Mask R-CNN model has a good framework design and runs highly efficiently. The livestock recognition models developed using deep learning methods with high-resolution remote sensing images accurately recognize the spatial distribution of livestock, which could enable precise control of schistosomiasis.
Gold nanoclusters (Au NCs) belong to a class of materials that is highly fluorescent and biocompatible. Bovine serum albumin (BSA) protected gold nanoclusters (BSA-Au NCs) have been extensively used ...in biological applications due to their easy synthesis and relatively high quantum yield. Therefore, understanding the behavior of BSA-Au NCs in different chemical and physical environments is essential to enhance their application in biological systems. In this study, we investigated the effect of plasmonic nanostructures with different localized surface plasmon resonance (LSPR) wavelengths on the behavior of BSA-Au NCs by recording time-dependent fluorescence spectra in the presence of silver nanoparticles (AgNPs) with various shapes. However, we did not observe any conclusive LSPR-wavelength-dependent fluorescent behavior. Additionally, the fluorescence intensity of BSA-Au NCs exhibited gradual decay under light excitation, even at several hundred μW/cm2 in a fluorescence spectrometer, indicating that they are not as photostable as previously assumed. We found further that the photostability of BSA-Au NCs is affected by the wavelength of the incident light (370, 420, 480, and 550 nm), which can be accurately described using bi-exponential decay functions. Our study provides an easy in situ method to evaluate the photostability of Au NCs under different-wavelength light irradiation using a commercial fluorescence spectrometer.
The gut microbiota has been demonstrated to be correlated with the clinical phenotypes of diseases, including cancers. However, there are few studies on clinical subtyping based on the gut ...microbiota, especially in breast cancer (BC) patients. Here, using machine learning methods, we analysed the gut microbiota of BC, colorectal cancer (CRC), and gastric cancer (GC) patients to identify their shared metabolic pathways and the importance of these pathways in cancer development. Based on the gut microbiota-related metabolic pathways, human gene expression profile and patient prognosis, we established a novel BC subtyping system and identified a subtype called "challenging BC". Tumours with this subtype have more genetic mutations and a more complex immune environment than those of other subtypes. A score index was proposed for in-depth analysis and showed a significant negative correlation with patient prognosis. Notably, activation of the TPK1-FOXP3-mediated Hedgehog signalling pathway and TPK1-ITGAE-mediated mTOR signalling pathway was linked to poor prognosis in "challenging BC" patients with high scores, as validated in a patient-derived xenograft (PDX) model. Furthermore, our subtyping system and score index are effective predictors of the response to current neoadjuvant therapy regimens, with the score index significantly negatively correlated with both treatment efficacy and the number of immune cells. Therefore, our findings provide valuable insights into predicting molecular characteristics and treatment responses in "challenging BC" patients.
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The 534 protein kinases encoded in the human genome constitute a large druggable class of proteins that include both well-studied and understudied “dark” members. Accurate prediction of dark kinase ...functions is a major bioinformatics challenge. Here, we employ a graph mining approach that uses the evolutionary and functional context encoded in knowledge graphs (KGs) to predict protein and pathway associations for understudied kinases. We propose a new scalable graph embedding approach, RegPattern2Vec, which employs regular pattern constrained random walks to sample diverse aspects of node context within a KG flexibly. RegPattern2Vec learns functional representations of kinases, interacting partners, post-translational modifications, pathways, cellular localization, and chemical interactions from a kinase-centric KG that integrates and conceptualizes data from curated heterogeneous data resources. By contextualizing information relevant to prediction, RegPattern2Vec improves accuracy and efficiency in comparison to other random walk-based graph embedding approaches. We show that the predictions produced by our model overlap with pathway enrichment data produced using experimentally validated Protein-Protein Interaction (PPI) data from both publicly available databases and experimental datasets not used in training. Our model also has the advantage of using the collected random walks as biological context to interpret the predicted protein-pathway associations. We provide high-confidence pathway predictions for 34 dark kinases and present three case studies in which analysis of meta-paths associated with the prediction enables biological interpretation. Overall, RegPattern2Vec efficiently samples multiple node types for link prediction on biological knowledge graphs and the predicted associations between understudied kinases, pseudokinases, and known pathways serve as a conceptual starting point for hypothesis generation and testing.
Abstract
CAR T-cell therapy is well tolerated and effective in patients with Hodgkin lymphoma (HL) and anaplastic large cell lymphoma (ALCL). However, even second- generation anti-CD30 CAR T-cells ...with CD28 (28z) costimulatory domains failed to achieve the desired rate of complete responses. In the present study, we developed second-generation (CD28z) and third-generation (CD28BBz) CAR T-cells targeting CD30 and investigated their efficacy in vitro and in vivo. Both of CD28z and CD28BBz anti-CD30 CAR T cells were similar regarding amplification, T cell subsets distribution, T cell activity, effector/memory and exhaustion. However, we found that the 28BBz anti-CD30 CAR T-cells persist long-term, specifically homing to the tumor and mediating powerful antitumor activity in tumor xenograft models. Subsequently, we also demonstrated that the third generation anti-CD30 CAR T-cells have miner side effects or potential risks of tumorigenesis. Thus, anti-CD30 CAR T-cells represent a safe and effective treatment for Hodgkin lymphoma.
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This study developed a new high-throughput strategy, designated as hot-isostatic-pressing-based micro-synthesis approach (HIP-MSA), to optimize high-performance nickel-based superalloys in a rapid, ...efficient, and cost-effective manner. A specific honeycomb-array structure containing 106 discrete cells was designed and optimized using finite element analysis (FEA) and then applied to create a combinatorial library consisting of 106 Ni-based superalloys with various Co, Nb and Ta concentrations. By integration with high-throughput characterization tools, extensive composition and phase structure data were collected quickly and efficiently. In the superalloys with higher amounts of Nb and Ta, the detrimental η phase displaying needle-like morphology was observed, and its content (wt%) increased drastically with Ta and Nb contents increasing. However, the increase of Co addition in those alloys was confirmed to be surprisingly beneficial by significantly suppressing the formation of η phase that was induced by high Nb and Ta contents. The zero-phase-fraction (ZPF) line of η phase was established, which is critical to design superalloy chemistry for superior microstructural stability at high-temperature service conditions.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The technology of infrared dim- and small-target detection is irreplaceable in many fields, such as those of missile early warning systems and forest fire prevention, among others. However, numerous ...components interfere with infrared imaging, presenting challenges for achieving successful detection of infrared dim and small targets with a low rate of false alarms. Hence, we propose a new infrared dim- and small-target detection network, Multiscale Feature Extraction U-Net for Infrared Dim- and Small-Target Detection (MFEU-Net), which can accurately detect targets in complex backgrounds. It uses the U-Net structure, and the encoders and decoders consist of ReSidual U-block and Inception, allowing rich multiscale feature information to be extracted. Thus, the effectiveness of algorithms in detecting very small-sized targets can be improved. In addition, through the multidimensional channel and spatial attention mechanism, the model can be adjusted to focus more on the target area in the image, improving its extraction of target information and detection performance in different scenarios. The experimental results show that our proposed algorithm outperforms other advanced algorithms in detection performance. On the MFIRST, SIRST, and IRSTD-1k datasets, we achieved detection rates of 0.864, 0.962, and 0.965; IoU values of 0.514, 0.671, and 0.630; and false alarm rates of 3.08 × 10−5, 2.61 × 10−6, and 1.81 × 10−5, respectively.
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The Huayu-Qiangshen-Tongbi (HQT) decoction, a Chinese medical formula, has been identified to show a potent therapeutic effect on rheumatoid arthritis (RA). However, the specific molecular mechanism ...of HQT in RA has not been well studied. In the present study, LPS-treated human rheumatoid fibroblast-like synoviocyte (FLS) MH7A cells and collagen-induced arthritis (CIA) mice were utilized as in vitro and in vivo models. Our results demonstrated that HQT could efficiently inhibit RA-induced inflammation by reducing the production of cytokines including tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1β), and interleukin-6 (IL-6). Moreover, HQT significantly upregulated the expression of miR-125b. Besides, analysis of bioinformatics suggested casein kinase 2 (CK2) was a potential target of miR-125b. Luciferase reporter assay was performed and revealed that miR-125b suppressed CK2 expression in MH7A cells. Furthermore, miR-125b inhibited LPS-induced NF-kappa-B (NF-κB) activation, which is a downstream target of CK2. In addition, the NF-κB inhibitor ammonium pyrrolidinedithiocarbamate (PDTC) and NF-kappa-B inhibitor alpha (IkB-α) enhanced the inhibitory effect of miR-125b on the expression of TNF-α, IL-1β, and IL-6. Taken together, our study revealed that HQT could attenuate RA through upregulating miR-125b to suppress NF-κB-induced inflammation by targeting CK2. The findings of this study should facilitate investigating the mechanism of HQT on RA and discovering novel therapeutic targets for RA.
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DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
