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Objective To analyze compensatory ability of the cerebral collateral circulation and relevant factors affecting cerebral ischemic tolerance for internal carotid artery (ICA) occlusion by Balloon Test Occlusion (BTO), providing reference basis for the selection of treatment methods in tumors or complicated aneurysms with ICA involved. Methods The clinical data of 87 cases BTO (85 patients, two of whom underwent bilateral BTO) of ICA in Tianjin Huanhu Hospital from June 2016 to September 2021 were analyzed retrospectively. The integrity of anterior or posterior of circulation structure, collateral compensatory capacity, tolerance to ICA occlusion and its influencing factors were analyzed. Results There were 8 [9.20% (8/87)] BTO positive cases. The positive rate was of cases with incomplete anterior communicating artery was higher than those with complete anterior communicating artery [3/5 vs. 6.10% (5/82); Fisher's exact probability: P=0.005]. The positive rate of cases with complete fetal posterior cerebral artery (fPCA) which was higher than those without complete fPCA [3/7 vs. 6.25% (5/80); Fisher's exact probability: P=0.015]. The positive rate of cases with non⁃open anterior circulation which was higher than those cases with open anterior circulation [3/6 vs. 6.17% (5/81); Fisher's exact probability: P=0.009]. The positive rate of cases with non⁃open posterior circulation which was higher than those cases with open posterior circulation [20% (5/25) vs. 0 (0/59); Fisher's exact probability: P=0.002]. Only the positive rate of patients with anterior circulation opening was higher than that of patients with open anterior circulation and open posterior circulation [13.04% (3/23) vs. 0 (0/3); Fisher's exact probability: P=0.022], neither anterior nor posterior circulation opening were significantly higher than those with only anterior circulation opening [2/2 vs. 13.04% (3/23); Fisher's exact probability: P=0.033] and both anterior and posterior circulation opening [2/2 vs. 0 (0/56); Fisher's exact probability: P=0.001]. Once the ICA occluded, the anterior circulation, the posterior circulation, both of anterior and posterior circulation could provide anterior cerebral artery (ACA) supplied area with compensatory blood flow for 88.10% (74/84), 3.57% (3/84), 5.95% (5/84) cases, respectively. The anterior circulation, the posterior circulation, both anterior and posterior circulation could provide middle cerebral artery (MCA) supplied area with compensatory blood flow for 27.38% (23/84), 16.67% (14/84), 53.57% (45/84) cases, respectively. There were statistically significant differences in the compensatory capacity between ACA (χ2=53.000, P=0.000) and MCA (χ2=54.244, P=0.000). The combined compensatory capacity of both anterior and posterior circulation was higher than that of single anterior circulation (Z=6.754, P=0.000; Z=6.180, P=0.000), single posterior circulation (Z=2.277, P=0.023; Z=5.065, P=0.000) and neither anterior nor posterior circulation (Z=1.991, P=0.047; Z=2.478, P=0.013). Conclusions The anterior circle is functionally much more important than the posterior circle. Non⁃open anterior circulation, especial absence of anterior communicating artery, complete fPCA, neither anterior nor posterior circulation were highly predictive for intolerance to ICA occlusion. For these cases, attention should be paid to the protection of ICA or active blood flow reconstruction technology to reduce the occurrence of cerebral ischemia. Those cases with both opened anterior circulation and opened posterior circulation provided higher compensatory ability than those with single circulation. For those cases, the ICA of could be sacrificed.

Objective To synthesize ethylene glycol chitosan-diethylenetriamine pentaacetic acid (GC-DTPA), and evaluate its cytocompatibility and systemic toxicity within the dose range of routine use. Methods DTPA was grafted onto ethylene glycol chitosan (GC) by organic synthesis and chemical cross-linking method, and was subsequently characterized with proton nuclear magnetic resonance (1H NMR) and Fourier transform infrared (FT-IR) spectroscopy. CCK-8 assay was used to detect the effects of different concentrations of GC-DTPA on the proliferation of ICE-6 cells. In addition, 80 healthy SPF SD rats (aged 6~8 weeks, body weight 180~220 g) were randomly divided into 4 groups (n=20): control group (given normal saline), and experimental groups (60, 90 and 120 mg/kg GC-DTPA, respectively by intragastric gavage). The change of body weight and survival rate of rats in each group were observed. Blood routine test and blood biochemical examination were performed in the rats on the 14th day after gavage with aid of automatic blood humoral and biochemical immunoassay analyzers respectively. Then, the rats were sacrificed and the pathological changes of organs were observed after HE staining. Results FT-IR spectroscopy and 1H-NMR suggested that DTPA was successfully grafted onto GC, and GC-DTPA exhibited excellent cytocompatibility, with cell viability all above 90% after its treatment at different concentrations. In 14 d after administration, no significant differences were seen in the results of blood routine and blood biochemical tests, or in pathological changes of organs and tissues in each group. Conclusion The GC-DTPA synthesized by chemical synthesis and cross-linking method shows no obvious cytotoxicity, and no systemic toxicity is seen even after oral administration dose up to 120 mg/kg

Sentiment analysis utilizes Natural Language Processing (NLP) techniques to extract opinions from text, which is critical for businesses looking to refine strategies and better understand customer feedback. Understanding people's sentiments about products through emotional tone analysis is paramount. However, analyzing sentiment in Arabic and its dialects poses challenges due to the language's intricate morphology, right-to-left script, and nuanced emotional expressions. To address this, this study introduces the Arb-MCNN-Bi Model, which integrates the strengths of the transformer-based AraBERT (Arabic Bidirectional Encoder Representations from Transformers) model with a Multi-channel Convolutional Neural Network (MCNN) and a Bidirectional Gated Recurrent Unit (BiGRU) for Arabic sentiment analysis. AraBERT, designed specifically for Arabic, captures rich contextual information through word embeddings. These embeddings are processed by the MCNN to enhance feature extraction and by the BiGRU to retain long-term dependencies. The final output is obtained through feedforward neural networks. The study compares the proposed model with various machine learning and deep learning methods, applying advanced NLP techniques such as Term Frequency-Inverse Document Frequency (TF-IDF), n-gram, Word2Vec (Skip-gram), and fastText (Skip-gram). Experiments are conducted on three Arabic datasets: the Arabic Customer Reviews Dataset (ACRD), Large-scale Arabic Book Reviews (LABR), and the Hotel Arabic Reviews dataset (HARD). The Arb-MCNN-Bi model with AraBERT achieved accuracies of 96.92%, 96.68%, and 92.93% on the ACRD, HARD, and LABR datasets, respectively. These results demonstrate the model's effectiveness in analyzing Arabic text data and outperforming traditional approaches. [ABSTRACT FROM AUTHOR]

Secondary‐metals promotion is key to tune the CO2 hydrogenation performance of Rh‐based catalyst. We describe the addition of Cu or Co in TiO2 nanorods supported Rh catalyst (viz., RhMx/TiO2), showing significant impact on the CO2 hydrogenation activity and productivity. Cu addition can promote the partial hydrogenation to alcohols (methanol and ethanol), whereas Co led to the deep hydrogenation to alkanes (CH4, C2H6). Comparative time‐resolved in situ DRIFTS studies with H2/D2 isotopic exchange further reveal that both surface adsorbed CO* and formates could be the key reaction intermediates during the CO2 hydrogenation over RhMx/TiO2 (especially the RhCu2.5/TiO2), in which the interaction strength of CO* regulated by secondary‐metals addition was key to tune the reaction pathways and productivity. The findings suggested that rational design of active metal sites, for example the synergy between Rh and secondary‐metals, is highly needed to promote the CO insertion and CC coupling to produce ethanol. [ABSTRACT FROM AUTHOR]

Calcium oxalate (CaOx) kidney stones are common and recurrent, lacking pharmacological prevention. Randall's plaques (RPs), calcium deposits in renal papillae, serve as niduses for some CaOx stones. This study explores the role of osteogenic‐like cells in RP formation resembling ossification. CaP crystals deposit around renal tubules, interstitium, and blood vessels in RP tissues. Human renal interstitial fibroblasts (hRIFs) exhibit the highest osteogenic‐like differentiation potential compared to chloride voltage‐gated channel Ka positive tubular epithelial cells, aquaporin 2 positive collecting duct cells, and vascular endothelial cells, echoing the upregulated osteogenic markers primarily in hRIFs within RP tissues. Utilizing RNA‐seq, osteomodulin (OMD) is found to be upregulated in hRIFs within RP tissues and hRIFs following osteogenic induction. Furthermore, OMD colocalizes with CaP crystals and calcium vesicles within RP tissues. OMD can enhance osteogenic‐like differentiation of hRIFs in vitro and in vivo. Additionally, crystal deposits are attenuated in mice with Omd deletion in renal interstitial fibroblasts following CaOx nephrocalcinosis induction. Mechanically, a positive feedback loop of OMD/BMP2/BMPR1A/RUNX2/OMD drives hRIFs to adopt osteogenic‐like fates, by which OMD induces osteogenic‐like microenvironment of renal interstitium to participate in RP formation. We identify OMD upregulation as a pathological feature of RP, paving the way for preventing CaOx stones. [ABSTRACT FROM AUTHOR]

Developing catalysts based on non-precious metals is crucial for the electrochemical oxidation of ethanol, a pivotal anodic reaction in direct ethanol fuel cells. In this study, we crafted a series of Mn oxyhydroxides/Ni catalysts via a straightforward electrochemical deposition of Mn onto Ni foam. By carefully modulating the concentration of Mn2+ during electrodeposition, we achieved a tunable surface Mn/Ni ratio and Mn–Ni synergy. It is observed that with increasing Mn/Ni ratio, the electrochemically active surface area (ECSA) increases monotonously, while the intrinsic activity increased first and then decreased. Consequently, electrodes with surface ratios of 6.1 and 8.6 exhibit relatively lower intrinsic activity but higher ECSA, ultimately attaining the highest apparent activity (94–98 mA cm−2 peak current density at 1.50 V vs. reversible hydrogen electrode) for ethanol oxidation. This work provides an accessible approach to tailor Mn–Ni synergy, paving the way for the design of highly efficient catalysts for electrochemical ethanol oxidation. [ABSTRACT FROM AUTHOR]

Aiming at the solution to the time-consuming and low-precision disadvantage of present methodologies,the light field depth estimation method combining context information of the scene is proposed.This method is based on an end-to-end convolutional neural network,with the advantage of obtaining depth map from a single light field image.On merit of the reduced computational cost from this method,the time consumption is consequently decreased.For improvement in calculation accuracy,multi orientation epipolar plane image volumes of the light field images are input to network,from which feature can be extracted by the multi-stream encoding module,and then aggregated by the encoding-decoding architecture with skip connection,resulting in fuse the context information of the neighborhood of the target pixel in the process of per-pixel disparity estimation.Furthermore,the model uses convolutional blocks of different depths to extract the structural features of the scene from the central viewpoint image,by introducing these structural features into the corresponding skip connection,additional references for edge features are obtained and the calculation accuracy is further improved.Experiments in the HCI 4D Light Field Benchmark show that the BadPix index and MSE index of the proposed method are respectively 31.2% and 54.6% lower than those of the comparison me-thod,and the average calculation time of depth estimation is 1.2 seconds,which is much faster than comparison method.

PurposeTo investigate the changes in immunity and clinical infection events among patients with chronic insomnia.Materials and methodsForty-two patients with chronic insomnia (age = 64.44 ± 10.53) and 47 normal controls (age = 67.08 ± 7.822) were selected to determine differences in data, such as complete blood counts (CBCs), biochemical indices, lymphocyte subsets, immunoglobulin (Ig), complement C3 and C4 and interleukin-6 (IL-6), as well as to compare the incidence of clinical infection between the two groups.ResultsThere were significant differences in erythrocyte, hemoglobin, hematocrit, albumin, globulin, creatinine, IgG, IgG/IgM ratio, CD4+ T-lymphocytes, CD19-lymphocytes, CD4+/CD8+ ratio, platelet/lymphocyte ratio, CD19/CD3 ratio, and clinical infection events between the chronic insomnia group and the control group (p < 0.05). There was no significant difference in neutrophil, lymphocyte, monocyte, and platelet counts; lymphocyte subsets CD8+ T and CD56+; platelet-to-lymphocyte ratio (PLR); neutrophil-to-lymphocyte ratio (NLR); complement C3; complement C4; IgM; IgA; and IL-6 between the experimental group and their controls (p > 0.05). The systolic and diastolic blood pressures of the chronic insomnia group did not vary widely from those of the controls (p > 0.05).ConclusionPatients with chronic insomnia have immunological abnormalities, characterized by a higher incidence of clinical infection.

MotivationCombining a 16S rRNA (16S) gene database with metagenomic shotgun sequences promises unbiased identification of known and novel microbes.ResultsTo achieve this, we herein report reference-based ribosome assembly (RAMBL), a computational pipeline, which integrates taxonomic tree search and Dirichlet process clustering to reconstruct full-length 16S gene sequences from metagenomic sequencing data with high accuracy. By benchmarking against the synthetic and real shotgun sequences, we demonstrated that full-length 16S gene assemblies of RAMBL were a good proxy for known and putative microbes, including Candidate Phyla Radiation. We found that 30-40% of bacteria genera in the terrestrial and intestinal biomes have no closely related genome sequences. We also observed that RAMBL was able to generate a more accurate determination of environmental microbial diversity and yield better disease classification, suggesting that full-length 16S gene assemblies are a powerful alternative to marker gene set and 16S short reads. RAMBL first realizes the access to full-length 16S gene sequences in the near-terabase-scale metagenomic shotgun sequences, which markedly improve metagenomic data analysis and interpretation.Availability and implementationRAMBL is available at https://github.com/homopolymer/RAMBL for academic use.Contactzengfeng@xmu.edu.cn.Supplementary informationSupplementary data are available at Bioinformatics online.

Sodium propionate is widely used as a preservative in food. The widespread use of preservatives is known to cause both environmental and public health problems. This study aimed to investigate the effects of sodium propionate on the developmental behavior and glucose metabolism of zebrafish. Our results showed that sodium propionate had no significant effect on the embryonic morphological development of zebrafish embryos but changed the head eye area. Then we found sodium propionate disturbed the thigmotaxis behavior, impaired neural development. Moreover, changes in clock gene expression disrupted the circadian rhythm of zebrafish. Circadian genes regulated insulin sensitivity and secretion in various tissues. Then our results showed that the disorder of circadian rhythm in zebrafish affected glucose metabolism and insulin resistance, which damaged the development of retina. Therefore, the safety of propionate should be further evaluated.

Background and purpose: Guidelines recommend that the axillary lymph node dissection can be omitted for T 1-2 breast cancer patients with 1-2 positive sentinel lymph nodes who undergo breast-conserving mastectomy and whole breast radiation. This study aimed to explore the independent prognostic factors for elderly breast cancer patients with 1-2 positive lymph nodes who underwent mastectomy and construct a nomogram to predict their survival following different axillary surgeries. Methods: T 1-2 invasive breast cancer patients with 1-2 positive nodes and mastectomy from 2010 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) program and divided into the training cohort (n=3 647) and the validation cohort (n=1 216). Univariate and multivariate Cox analyses were used to identify independent risk factors for overall survival (OS). The nomogram was constructed to predict 3- and 5-year OS, which was validated by the concordance index (C-index) and calibration curves. Results: A total of 4 863 patients were included with a 42 months median follow-up time. The nomogram was constructed by incorporating nine independent prognostic factors (age, race, marital status, grade, subtype, T stage, axillary surgery, radiation and chemotherapy) identified by multivariate Cox analysis (P

Skin cancer is a prevalent and perilous form of cancer and presents significant diagnostic challenges due to its high costs, dependence on medical experts, and time-consuming procedures. The existing diagnostic process is inefficient and expensive, requiring extensive medical expertise and time. To tackle these issues, researchers have explored the application of artificial intelligence (AI) tools, particularly machine learning techniques such as shallow and deep learning, to enhance the diagnostic process for skin cancer. These tools employ computer algorithms and deep neural networks to identify and categorize skin cancer. However, accurately distinguishing between skin cancer and benign tumors remains challenging, necessitating the extraction of pertinent features from image data for classification. This study addresses these challenges by employing Principal Component Analysis (PCA), a dimensionality-reduction approach, to extract relevant features from skin images. Additionally, accurately classifying skin images into malignant and benign categories presents another obstacle. To improve accuracy, the AdaBoost algorithm is utilized, which amalgamates weak classification models into a robust classifier with high accuracy. This research introduces a novel approach to skin cancer diagnosis by integrating Principal Component Analysis (PCA), AdaBoost, and EfficientNet B0, leveraging artificial intelligence (AI) tools. The novelty lies in the combination of these techniques to develop a robust and accurate system for skin cancer classification. The advantage of this approach is its ability to significantly reduce costs, minimize reliance on medical experts, and expedite the diagnostic process. The developed model achieved an accuracy of 93.00% using the DermIS dataset and demonstrated excellent precision, recall, and F1-score values, confirming its ability to correctly classify skin lesions as malignant or benign. Additionally, the model achieved an accuracy of 91.00% using the ISIC dataset, which is widely recognized for its comprehensive collection of annotated dermoscopic images, providing a robust foundation for training and validation. These advancements have the potential to significantly enhance the efficiency and accuracy of skin cancer diagnosis and classification. Ultimately, the integration of AI tools and techniques in skin cancer diagnosis can lead to cost reduction and improved patient outcomes, benefiting both patients and healthcare providers. [ABSTRACT FROM AUTHOR]

Simple Summary: Head and neck cancer disparities in outcomes for Black Americans have been well recognized. However, the specific drivers of the inferior outcomes remain poorly understood. We investigated the biologic features of patient oral cancers and performed a follow-up study of the patient post-surgery recurrences and metastases aiming to explore potential mechanisms that might underpin the poorer outcomes among Black American patients. It was found that high levels of tumor stemness and tumor-promoting stromal characteristics were linked to patient recurrence and metastasis. There were more cases of Black American than White American exhibiting high stemness traits and strong tumor-promoting stromal features associated with tumor recurrences and metastases, although the investigated cases displayed comparable clinical diagnoses. Our findings revealed that the differences in tumor stemness and stromal property among cancers with similar diagnoses contribute to patient outcome disparities. Black Americans (BAs) with head and neck cancer (HNC) have worse survival outcomes compared to the White patients. While HNC disparities in patient outcomes for BAs have been well recognized, the specific drivers of the inferior outcomes remain poorly understood. Here, we investigated the biologic features of patient tumor specimens obtained during the surgical treatment of oral cancers and performed a follow-up study of the patients' post-surgery recurrences and metastases with the aim to explore whether tumor biologic features could be associated with the poorer outcomes among BA patients compared with White American (WA) patients. We examined the tumor stemness traits and stromal properties as well as the post-surgery recurrence and metastasis of oral cancers among BA and WA patients. It was found that high levels of tumor self-renewal, invasion, tumorigenesis, metastasis, and tumor-promoting stromal characteristics were linked to post-surgery recurrence and metastasis. There were more BA than WA patients demonstrating high stemness traits and strong tumor-promoting stromal features in association with post-surgery tumor recurrences and metastases, although the investigated cases displayed clinically comparable TNM stages and histological grades. These findings demonstrated that the differences in tumor stemness and stromal property among cancers with comparable clinical diagnoses contribute to the outcome disparity in HNCs. More research is needed to understand the genetic and molecular basis of the biologic characteristics underlying the inferior outcomes among BA patients, so that targeting strategies can be developed to reduce HNC disparity. [ABSTRACT FROM AUTHOR]

In existing image retrieval algorithms, negative samples often appear at the forefront of retrieval results. To this end, in this paper, we propose a feature fusion-based re-ranking method for home textile image retrieval, which utilizes high-level semantic similarity and low-level texture similarity information of an image and strengthens the feature expression via late fusion. Compared with single-feature re-ranking, the proposed method combines the ranking diversity of multiple features to improve the retrieval accuracy. In our re-ranking process, Markov random walk is used to update the similarity metrics, and we propose local constraint diffusion based on contextual similarity. Finally, the fusion–diffusion algorithm is used to optimize the sorted list via combining multiple similarity metrics. We set up a large-scale home textile image dataset, which contains 89 k home textile product images from 12 k categories, and evaluate the image retrieval performance of the proposed model with the Recall@k and mAP@K metrics. The experimental results show that the proposed re-ranking method can effectively improve the retrieval results and enhance the performance of home textile image retrieval. [ABSTRACT FROM AUTHOR]

The changing climate and intensifying human activities have made an impact on the hydrological processes in the upper Yangtze River (UYR), but quantifying their effects remains uncertain. This study used the Budyko framework to investigate the response of runoff (Q) to climate change and human activities during 1956–2017 and evaluate the impacts of human activities, including land use/cover change, water use, dam construction, and vegetation change, on watershed characteristic. Results show that climate change is the dominant driver of Q variations in the Wujiang River (WJR), Jialing River (JLR), and Jinsha River (JSR) watersheds, with contributions of 58.6%, 66.9%, and 67.6%, respectively. However, in Mingjiang River (MJR) and UYR watersheds, human activities contribute more to Q variations with 55.2% and 51.2%, respectively. Human activities play important roles in variation of watershed characteristics, and they can explain 22%, 26%, 36%, 25%, and 53% of the watershed character change in UYR, WJR, JLR, MJR, and JSR, respectively. This study conducts a comprehensive analysis of the causes of Q change in UYR, and provides a new perspective to explore the effects of specific human activities on watershed characteristics. Plain Language Summary: With climate change and intensifying human activities, the water cycle has been changed. Runoff is an essential component of the water cycle, and its response to changing environments has drawn broad attention. This study aims to quantify the contributions of climate change and human activities to runoff changes in the upper Yangtze River (UYR) and its four sub‐watersheds over the past half‐century. According to the results, human activities and climate change have been responsible for approximately 51.2% and 48.8% of the observed runoff changes in UYR, respectively. It suggests that both human activities and climate change have played significant roles, and their contributions are remarkably comparable. In addition, the impacts of human activities on watershed environment changes are analyzed. The results suggest that increased settlement area and industrial water use are the dominant influencing factors. Key Points: Human activities and climate change have made comparable contributions to the runoff reduction in the upper Yangtze RiverWater use, land use/cover change, vegetation change, and dam construction together explain 22% of the watershed environment changesHuman settlements and increased industrial water use have been the principal factors contributing to the changes in watershed environment [ABSTRACT FROM AUTHOR]