Precision Measurement of Reactor Antineutrino Oscillation at Kilometer-Scale Baselines by Daya Bay

We present a new determination of the smallest neutrino mixing angle θ_{13} and the mass-squared difference Δm_{32}^{2} using a final sample of 5.55×10^{6} inverse beta-decay (IBD) candidates with the final-state neutron captured on gadolinium. This sample is selected from the complete dataset obtained by the Daya Bay reactor neutrino experiment in 3158 days of operation. Compared to the previous Daya Bay results, selection of IBD candidates has been optimized, energy calibration refined, and treatment of backgrounds further improved. The resulting oscillation parameters are sin^{2}2θ_{13}=0.0851±0.0024, Δm_{32}^{2}=(2.466±0.060)×10^{-3}  eV^{2} for the normal mass ordering or Δm_{32}^{2}=-(2.571±0.060)×10^{-3}  eV^{2} for the inverted mass ordering.

[Effects of long working hours exposure on occupational stress and depression symptoms in couriers in Zhejiang Province]

Objective: To understand the current situation of long working hours exposure of couriers in Zhejiang Province, and to analyze the influence of long working hours exposure levels on their occupational stress and depression symptoms, and provide a basis for promoting the physical and mental health of couriers. Methods: From September to December 2021 , 1159 couriers from Zhejiang Express Transport Companies were selected as respondents by cluster sampling, and their basic information were collected. The occupational stress and depression symptoms of the couriers were assessed using the Core Occupational Stress Scale (COSS) and the Patient Health Questionnaire-9 (PHQ-9). The effects of long work hours (>48 h per week) on the occupational stress and depression symptoms of the couriers were analyzed. Results: The average age of 1159 courier in Zhejiang Province was (33.24±8.42) years, the average weekly working hours were (63.21±18.77) h, and 75.15% (871/1159) were long-term workers. The detection rates of occupational stress and depression symptoms in courier were 32.44% (376/1159) and 32.53% (377/1159), respectively. There were significant differences in the detection rates of occupational stress and depression symptoms among couriers with different ages, educational background, marital status, monthly average income, length of service, position or post, shift status, drinking status, and average weekly working hours (P <0.05). The adjusted logistic regression analysis showed that, after adjusting for the influence of confounding factors such as age, educational background, marital status, monthly average income, length of service, position or post, shift status and drinking status, compared with the weekly working hours ≤48 h, weekly working hours of 63-77 h, 78-92 h, ≥93 h were the risk factors for occupational stress (OR=1.547, 95%CI: 1.019-2.350; OR=1.886, 95%CI: 1.184-3.006; OR=2.338, 95%CI: 1.188-4.062) and depression symptoms (OR=1.897, 95%CI: 1.258-2.860; OR=2.041, 95%CI: 1.290-3.230; OR=4.978, 95%CI: 2.551-9.715) of couriers (P<0.05) . Conclusion: Long working hours could increase the risk of occupational stress and depression symptoms among couriers. It is necessary to arrange working hours reasonably to reduce the occurrence of occupational stress and depression symptoms of couriers.

IMC-MDA: Prediction of miRNA-disease association based on induction matrix completion

To comprehend the etiology and pathogenesis of many illnesses, it is essential to identify disease-associated microRNAs (miRNAs). However, there are a number of challenges with current computational approaches, such as the lack of "negative samples", that is, confirmed irrelevant miRNA-disease pairs, and the poor performance in terms of predicting miRNAs related with "isolated diseases", i.e. illnesses with no known associated miRNAs, which presents the need for novel computational methods. In this study, for the purpose of predicting the connection between disease and miRNA, an inductive matrix completion model was designed, referred to as IMC-MDA. In the model of IMC-MDA, for each miRNA-disease pair, the predicted marks are calculated by combining the known miRNA-disease connection with the integrated disease similarities and miRNA similarities. Based on LOOCV, IMC-MDA had an AUC of 0.8034, which shows better performance than previous methods. Furthermore, experiments have validated the prediction of disease-related miRNAs for three major human diseases: colon cancer, kidney cancer, and lung cancer.

[Attach great importance to the significance of serum anti-müllerian hormone and androgen in the evaluation of polycystic ovary syndrome]

Polycystic ovary syndrome (PCOS) is a common endocrine disease in women of childbearing age, which seriously affects women's reproductive health. In recent years, more and more studies have found that serum anti-Müllerian hormone (AMH) has certain significance in the diagnosis and treatment evaluation of PCOS. In addition, with the improvement of detection methods, more attention has been paid to the significance of female androgens and AMH in the evaluation of PCOS. This article reviews the recent research progress of serum AMH and androgens in the evaluation of PCOS.

Cross-Scene Joint Classification of Multisource Data With Multilevel Domain Adaption Network

Domain adaption (DA) is a challenging task that integrates knowledge from source domain (SD) to perform data analysis for target domain. Most of the existing DA approaches only focus on single-source-single-target setting. In contrast, multisource (MS) data collaborative utilization has been extensively used in various applications, while how to integrate DA with MS collaboration still faces great challenges. In this article, we propose a multilevel DA network (MDA-NET) for promoting information collaboration and cross-scene (CS) classification based on hyperspectral image (HSI) and light detection and ranging (LiDAR) data. In this framework, modality-related adapters are built, and then a mutual-aid classifier is used to aggregate all the discriminative information captured from different modalities for boosting CS classification performance. Experimental results on two cross-domain datasets show that the proposed method consistently provides better performance than other state-of-the-art DA approaches.

Role and Mechanism of Cold Plasma in Inactivating Alicyclobacillus acidoterrestris in Apple Juice

A. acidoterrestris has been identified as the target bacterium in fruit juice production due to its high resistance to standard heat treatment. Multiple studies have shown that cold plasma can effectively inactivate pathogenic and spoilage microorganisms in juices. However, we are aware of only a few studies that have used cold plasma to inactivate A. acidoterrestris. In this study, the inactivation efficacy of cold plasma was determined using the plate count method and described using a biphasic model. The effects of the food matrix, input power, gas flow rate, and treatment time on inactivation efficacy were also discovered. Scavenging experiments with reactive oxygen species (•OH, •O2−, and 1O2), scanning electron microscopy (SEM), Raman spectra, as well as an in vitro toxicology assay kit, were used to determine the inactivation mechanism. According to the plate count method, a maximum reduction of 4.14 log CFU/ mL could be achieved within 7 s, and complete inactivation could be achieved within 240 s. The scavenging experiments showed that directly cold plasma-produced singlet oxygen plays the most crucial role in inactivation, which was also confirmed by the fluorescence probe SOSG. The scanning electron microscopy (SEM) and Raman spectra showed that the cold plasma treatment damaged the membrane integrity, DNA, proteins, lipids, and carbohydrates of A. acidoterrestris. The plate count results and the apple juice quality evaluation showed that the cold plasma treatment (1.32 kV) could inactivate 99% of A. acidoterrestris within 60 s, with no significant changes happening in apple juice quality, except for slight changes in the polyphenol content and color value.

The role of RNA methyltransferase METTL3 in gynecologic cancers: Results and mechanisms

N6-methyladenosine (m6A) methylation is the most prevalent mRNA modification in eukaryotes, and it is defined as the methylation of nitrogen atoms on the six adenine (A) bases of RNA in the presence of methyltransferases. Methyltransferase-like 3 (Mettl3), one of the components of m6A methyltransferase, plays a decisive catalytic role in m6A methylation. Recent studies have confirmed that m6A is associated with a wide spectrum of biological processes and it significantly affects disease progression and prognosis of patients with gynecologic tumors, in which the role of Mettl3 cannot be ignored. Mettl3 is involved in numerous pathophysiological functions, such as embryonic development, fat accumulation, and tumor progression. Moreover, Mettl3 may serve as a potential target for treating gynecologic malignancies, thus, it may benefit the patients and prolong survival. However, there is a need to further study the role and mechanism of Mettl3 in gynecologic malignancies. This paper reviews the recent progression on Mettl3 in gynecologic malignancies, hoping to provide a reference for further research.

Aspergillus cristatus attenuates DSS-induced intestinal barrier damage through reducing the oxidative stress, regulating short-chain fatty acid and inhibiting MAPK signaling pathways

BACKGROUND

Probiotics are regarded as a promising strategy for relieving colitis caused by dextran sulfate sodium (DSS). One of the dominant probiotic fungi in Fuzhuan brick tea is identified as Aspergillus cristatus, but whether it can effectively improve colitis remains poorly understood. Here, the improving effect of A. cristatus on colitis was investigated.

RESULTS

Our results showed that A. cristatus intervention prominently alleviated gut damage as evidenced by the inhibition of shortened colon length, goblet cell depletion, and histological injury. Mechanistically, after administration with low concentrations of A. cristatus H-1 and A. cristatus S-6, the expression of interleukin-6, tumor necrosis factor-α, interleukin-1β, nitric oxide, and malondialdehyde were significantly downregulated, and the content of glutathione, catalase, interleukin-10, immunoglobulin G, claudin-1, occludin, and zonula occludens-1 were effectively upregulated. More importantly, live A. cristatus supplementation lightened DSS-induced gut barrier damage by suppressing activation of the mitogen-activated protein kinase (MAPK) signaling pathway, increasing the synthesis of short-chain fatty acids (SCFAs) and stimulating the increase in peroxisome proliferator-activated receptor γ expression.

CONCLUSION

Together, A. cristatus can attenuate DSS-induced intestinal barrier damage through reducing the oxidative stress, regulating SCFA and inhibiting MAPK signaling pathways (P38/JNK/ERK). Our findings indicate that A. cristatus replenishment has potential as a new probiotic fungi to reduce DSS-induced colitis. © 2022 Society of Chemical Industry.

Single-source Domain Expansion Network for Cross-Scene Hyperspectral Image Classification

Currently, cross-scene hyperspectral image (HSI) classification has drawn increasing attention. It is necessary to train a model only on source domain (SD) and directly transferring the model to target domain (TD), when TD needs to be processed in real time and cannot be reused for training. Based on the idea of domain generalization, a Single-source Domain Expansion Network (SDEnet) is developed to ensure the reliability and effectiveness of domain extension. The method uses generative adversarial learning to train in SD and test in TD. A generator including semantic encoder and morph encoder is designed to generate the extended domain (ED) based on encoder-randomization-decoder architecture, where spatial randomization and spectral randomization are specifically used to generate variable spatial and spectral information, and the morphological knowledge is implicitly applied as domain invariant information during domain expansion. Furthermore, the supervised contrastive learning is employed in the discriminator to learn class-wise domain invariant representation, which drives intra-class samples of SD and ED. Meanwhile, adversarial training is designed to optimize the generator to drive intra-class samples of SD and ED to be separated. Extensive experiments on two public HSI datasets and one additional multispectral image (MSI) dataset demonstrate the superiority of the proposed method when compared with state-of-the-art techniques. The codes will be available from the website: https://github.com/YuxiangZhang-BIT/IEEE_TIP_SDEnet.

Substituting inert phosphate with redox-active silicate towards advanced polyanion-type cathode materials for sodium-ion batteries

Polyanion-type phosphate materials with Na-super-ionic conductor structures are promising for next-generation sodium-ion battery cathodes, although the intrinsically low electroconductivity and limited energy density have restricted their practical applications. In this study, we put forward substituting an inert phosphate with a redox-active silicate to improve the energy density and intrinsic electroconductivity of polyanion-type phosphate materials, thus enabling an advance in sodium-ion battery cathodes. As a proof of concept, some of the phosphate of Na₃V₂(PO₄)₃ was replaced by silicate to fabricate Na₃V₂(PO₄)_2.9(SiO₄)_0.1, which exhibited a higher average discharge voltage of 3.36 V and a higher capacity of 115.8 mA h g^-1 than pristine Na₃V₂(PO₄)₃ (3.31 V, 109.6 mA h g^-1) at 0.5 C, therefore improving the energy density. Moreover, the introduced silicate enhanced the intrinsic electroconductivity of Na₃V₂(PO₄)₃ materials, as confirmed by both theoretical simulation and electrochemical measurements. After pairing with a commercial hard carbon anode, the optimized Na₃V₂(PO₄)_2.9(SiO₄)_0.1 cathode enabled a stable-cycling full cell with 90.1% capacity retention after 300 cycles at 5 C and a remarkable average coulombic efficiency of 99.88%.

Time-course transcriptome analysis reveals regulation of Arabidopsis seed dormancy by the transcription factors WOX11/12

The induction of seed dormancy and its release involve a finely regulated genetic program controlled by various environmental and developmental cues that are critical for plant survival and population expansion. Light plays a key role in seed dormancy and germination, but the molecular mechanisms underlying the control of dormancy are unclear. In the present study, high-resolution temporal RNA-seq in Arabidopsis identified WOX11 as encoding a hub transcription factor during the seed dormancy induction and release stages. This gene might have evolved from gymnosperms and expanded in angiosperms with highly conserved expression patterns in seeds. WOX11 and its homolog WOX12 were highly expressed from 2 d after pollination, and mRNA abundance was greatly increased during the seed dormancy induction and release stages. Further, we found that WOX11 plays a role in the regulation of seed dormancy downstream of phytochrome B (PHYB)-mediated red-light signaling during the induction stage, indicating that WOX11/12 are newly identified components of red-light signaling transduction. Taken together, our results suggest that WOX11/12-mediated PHYB signaling regulates seed dormancy in Arabidopsis, and provide insights into the developmental regulation and evolutionary adaptation of plants to changes in the light environment.

Instrumental variable-based high-dimensional mediation analysis with unmeasured confounders for survival data in the observational epigenetic study

Background: High dimensional mediation analysis is frequently conducted to explore the role of epigenetic modifiers between exposure and health outcome. However, the issue of high dimensional mediation analysis with unmeasured confounders for survival analysis in observational study has not been well solved. Methods: In this study, we proposed an instrumental variable based approach for high dimensional mediation analysis with unmeasured confounders in survival analysis for epigenetic study. We used the Sobel's test, the Joint test, and the Bootstrap method to test the mediation effect. A comprehensive simulation study was conducted to decide the best test strategy. An empirical study based on DNA methylation data of lung cancer patients was conducted to illustrate the performance of the proposed method. Results: Simulation study suggested that the proposed method performed well in the identifying mediating factors. The estimation of the mediation effect by the proposed approach is also reliable with less bias compared with the classical approach. In the empirical study, we identified two DNA methylation signatures including cg21926276 and cg26387355 with a mediation effect of 0.226 (95%CI: 0.108-0.344) and 0.158 (95%CI: 0.065-0.251) between smoking and lung cancer using the proposed approach. Conclusion: The proposed method obtained good performance in simulation and empirical studies, it could be an effective statistical tool for high dimensional mediation analysis.

Predicting Six-Month Re-Admission Risk in Heart Failure Patients Using Multiple Machine Learning Methods: A Study Based on the Chinese Heart Failure Population Database

Since most patients with heart failure are re-admitted to the hospital, accurately identifying the risk of re-admission of patients with heart failure is important for clinical decision making and management. This study plans to develop an interpretable predictive model based on a Chinese population for predicting six-month re-admission rates in heart failure patients. Research data were obtained from the PhysioNet portal. To ensure robustness, we used three approaches for variable selection. Six different machine learning models were estimated based on selected variables. The ROC curve, prediction accuracy, sensitivity, and specificity were used to evaluate the performance of the established models. In addition, we visualized the optimized model with a nomogram. In all, 2002 patients with heart failure were included in this study. Of these, 773 patients experienced re-admission and a six-month re-admission incidence of 38.61%. Based on evaluation metrics, the logistic regression model performed best in the validation cohort, with an AUC of 0.634 (95%CI: 0.599-0.646) and an accuracy of 0.652. A nomogram was also generated. The established prediction model has good discrimination ability in predicting. Our findings are helpful and could provide useful information for the allocation of healthcare resources and for improving the quality of survival of heart failure patients.

Humanized V(D)J-rearranging and TdT-expressing mouse vaccine models with physiological HIV-1 broadly neutralizing antibody precursors

Antibody heavy chain (HC) and light chain (LC) variable region exons are assembled by V(D)J recombination. V(D)J junctional regions encode complementarity-determining-region 3 (CDR3), an antigen-contact region immensely diversified through nontemplated nucleotide additions ("N-regions") by terminal deoxynucleotidyl transferase (TdT). HIV-1 vaccine strategies seek to elicit human HIV-1 broadly neutralizing antibodies (bnAbs), such as the potent CD4-binding site VRC01-class bnAbs. Mice with primary B cells that express receptors (BCRs) representing bnAb precursors are used as vaccination models. VRC01-class bnAbs uniformly use human HC VH1-2 and commonly use human LCs Vκ3-20 or Vκ1-33 associated with an exceptionally short 5-amino-acid (5-aa) CDR3. Prior VRC01-class models had nonphysiological precursor levels and/or limited precursor diversity. Here, we describe VRC01-class rearranging mice that generate more physiological primary VRC01-class BCR repertoires via rearrangement of VH1-2, as well as Vκ1-33 and/or Vκ3-20 in association with diverse CDR3s. Human-like TdT expression in mouse precursor B cells increased LC CDR3 length and diversity and also promoted the generation of shorter LC CDR3s via N-region suppression of dominant microhomology-mediated Vκ-to-Jκ joins. Priming immunization with eOD-GT8 60mer, which strongly engages VRC01 precursors, induced robust VRC01-class germinal center B cell responses. Vκ3-20-based responses were enhanced by N-region addition, which generates Vκ3-20-to-Jκ junctional sequence combinations that encode VRC01-class 5-aa CDR3s with a critical E residue. VRC01-class-rearranging models should facilitate further evaluation of VRC01-class prime and boost immunogens. These new VRC01-class mouse models establish a prototype for the generation of vaccine-testing mouse models for other HIV-1 bnAb lineages that employ different HC or LC Vs.

Pipeline embolization devices for the treatment of nonsaccular aneurysms in pediatric patients

Objective

Pediatric nonsaccular aneurysms are rare but challenging lesions; pipeline embolization devices (PEDs) are their potential treatment option. In this study, we aimed to evaluate the safety and efficacy of PEDs for treatment of these aneurysms.

Methods

We retrospectively selected pediatric patients with nonsaccular aneurysms treated using PEDs between June 2015 and July 2021 from our prospectively maintained database. For each patient, demographics, aneurysm characteristics, procedure details, and clinical and angiographic follow-up data were collected and summarized.

Results

This study included 16 pediatric patients with 16 nonsaccular aneurysms treated with PEDs. A median clinical follow-up time of 1,376 days was achieved in 93.75% of the patients. The complication rate of the included patients was 25%, with two patients developing mass effect, one patient undergoing major ischemic stroke, and one patient experiencing stent foreshortening after the procedure. The complete occlusion rate of aneurysms without any neurologic sequelae was 93.33%, with a median angiographic follow-up period of 246 days. The mortality rate was 6.25%.

Conclusions

The use of PEDs to treat pediatric nonsaccular aneurysms is feasible, with a high rate of complete occlusion of the aneurysm and favorable follow-up outcomes.

How can an ecological compensation threshold be determined? A discriminant model integrating the minimum data approach and the most appropriate land use scenarios

Ecological compensation has become very common worldwide due to the imbalance in the development of modern society, economy, and the environment and the increased pressure on ecosystem carrying capacity. Nonetheless, the various approaches for quantifying ecological compensation standards differ significantly. Thus, the process for determining a reasonable ecological compensation threshold is important to understand. To ensure the maximization of ecosystem service supply and economic benefit incentives for farmers, this paper constructs a discriminant model of an ecological compensation threshold based on the minimum data approach and the most appropriate land use scenario to define the ecological compensation threshold of the Sloping Land Conversion Program in the upper Yangtze River basin. The results show that with an increase in the compensation price, the proportion of farmers participating in returning farmland to forests and grassland increases, and water conservation increases. However, the discriminant curve first increases to a certain threshold point and then decreases, after which the ecoefficiency rate obtained from the compensation decreases. The ecological compensation thresholds for Chongqing, Sichuan, Yunnan, Guizhou, Hubei, Qinghai, Gansu, Tibet and Shaanxi provinces are 17.74 yuan/m³, 13.79 yuan/m³, 19.1 yuan/m³, 17.79 yuan/m³, 15.28 yuan/m³, 45.14 yuan/m³, 17.23 yuan/m³, 25.2 yuan/m³ and 22.36 yuan/m³, respectively. This research examines ecological compensation standards in different watersheds throughout the world and discusses the relationship between ecological compensation and water conservation. The discriminant model of the ecological compensation threshold can provide a new reference for the implementation and management of ecological compensation policies.

Experimental Investigation: Vibration Measurement of a Rotating Blade with Digital Image Correlation and Blade Tip-Timing

High cycle fatigue has been known as an important form of aeroengine blade failure. This study aims to achieve a method of investigation for a rotating blade vibration measurement, combining the two non-contact optical techniques of digital image correlation (DIC) and blade tip-timing (BTT). Dynamic parameters of a thin-blade were obtained on a stationary vibration platform with stereo-DIC system. Meanwhile, the finite element analysis (FEA) of this thin-blade was performed within different rotating speeds. Then, the set of thin-blades was mounted in a simulated compressor test rig equipped with BTT and a wireless strain gauge (SG) system. A rotor speed sweep experiment was carried out and the blade synchronous resonance parameters were extracted. Results show that the displacement mode shapes match well between DIC and FEA, and that MAC values of the first six order modes are over than 0.88. The predicting strain from the FE model and SG agreed to within 32.41% in the worst case, and the predicting strain from the DIC model corresponds to 28.53% in the worst case. This is an effective non-contact, high-precision full-field deformation measurement method that is worth exploring for structural design and dynamic strain assessment of vibrating components.

Geometry-Guided Dense Perspective Network for Speech-Driven Facial Animation

Realistic speech-driven 3D facial animation is a challenging problem due to the complex relationship between speech and face. In this paper, we propose a deep architecture, called Geometry-guided Dense Perspective Network (GDPnet), to achieve speaker-independent realistic 3D facial animation. The encoder is designed with dense connections to strengthen feature propagation and encourage the re-use of audio features, and the decoder is integrated with an attention mechanism to adaptively recalibrate point-wise feature responses by explicitly modeling interdependencies between different neuron units. We also introduce a non-linear face reconstruction representation as a guidance of latent space to obtain more accurate deformation, which helps solve the geometry-related deformation and is good for generalization across subjects. Huber and HSIC (Hilbert-Schmidt Independence Criterion) constraints are adopted to promote the robustness of our model and to better exploit the non-linear and high-order correlations. Experimental results on the public dataset and real scanned dataset validate the superiority of our proposed GDPnet compared with state-of-the-art model. The code is available for research purposes at http://cic.tju.edu.cn/faculty/likun/projects/GDPnet.

[Efficacy of selective bronchial occlusion in the treatment of intractable pneumothorax]

Objective: To analyze the effect of selective bronchial occlusion (SBO) in the treatment of intractable pneumothorax. Methods: A total of 86 patients with refractory pneumothorax treated with SBO in the Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital of Fujian Medical University from January 1, 2019 to December 31, 2021 were included in this study. The basic information, diagnosis and treatment of the patients were collected and analyzed based on their inpatient records. Results: The age of the subjects was (62±11) years old, and 83 cases (96.5%) were male. The first time SBO cure rate was 30.2% (26/86). The effective rate of the first time SBO treatment was 38.4% (33/86), and the final cure rate of SBO was 59.3% (51/86). The total cure rate of SBO combined with other therapies was 73.3% (63/86). The median time [M (Q₁, Q₃)] from the first plugging to the complete cessation of air leakage in SBO cured patients was 6.5 (3, 7) days, which was shorter than that in the final extubation patients after SBO [11 (7, 19) days] (H=30.24, P<0.001). The median [M (Q₁, Q₃)] length of hospital stay of the first SBO cured patients was 19 (14, 25) days, which was shorter than that of all patients [28 (19, 37) days] (H=12.89, P=0.002). The median [M (Q₁, Q₃)] hospitalization expenses of patients with first SBO cure, effective SBO treatment and ineffective SBO treatment were 23 187 (18 906, 27 798), 41 580 (29 388, 50 762) and 38 462 (27 542, 51 720) yuan, respectively, and the difference was statistically significant (H=18.58, P<0.001). The incidence of complications after SBO was 7.59% (11/145). Conclusion: SBO has good efficacy and relative high safety in the treatment of intractable pneumothorax.

Siglec10-An immunosuppressor and negative predictor of survival prognosis in gliomas

Glioma is a type of tumor occurring in the central nervous system. In recent decades, specific gene mutations and molecular aberrations have been used to conduct the glioma classification and clinical decisions. Siglec10 is a member of the sialic acid-binding immunoglobulin superfamily. In this study, we investigated the expression and functions of siglec10 in gliomas. We analyzed the siglec10 expression in glioma patients with immunohistochemical (IHC) staining and evaluated the survival prognosis. The high siglec10 expression had a shorter survival prognosis than the low siglec10 expression in patients, especially in malignant gliomas. Bioinformatic datasets, including TCGA and CGGA, validated the IHC results and discovered the expression of siglec10 was higher in the malignant subtype than a benign subtype of gliomas. So, siglec10 is associated with the poor prognosis of gliomas. Furthermore, the related mechanisms of siglec10 in gliomas were investigated by functional enrichment analysis, including GSEA, GO, and KEGG analysis. Siglec10 was correlated with inflammatory mediators, inflammatory cells, and inflammatory pathways in gliomas. Siglec10 might take part in the immune response in the tumor microenvironment to induce glioma's progression and metastasis. This study showed siglec10 was a biomarker in glioma, and it might be the potential target of glioma immunotherapy in the future.

Analysis on the Spatio-Temporal Evolution Characteristics of the Impact of China's Digitalization Process on Green Total Factor Productivity

Green production is an inevitable choice for China's high-quality economic development. With the rise of the digital technology revolution, China's digital transformation may play an integral and important role in increasing green total factor productivity (GTFP). Based on the panel data of 30 Chinese provinces from 2014-2020, the impact of digitization on GTFP was explored using the model of geographically and temporally weighted regression (GTWR), and the spatial and temporal distribution characteristics and development trends of such effects were further explored. The main findings are as follows: (1) China's digitalization level and GTFP has significant spatial autocorrelation and similar spatial distribution characteristics. (2) Digitalization has a significant positive impact on GTFP, but this impact decreases yearly, and there are noticeable regional differences. Digitalization in the eastern and central regions has a more significant impact on GTFP than in the west. (3) The region where China's digital development has extensively promoted GTFP has shifted from China's southern coastal region to the northwest and northeast regions. (4) The time-series fluctuations of the regression coefficients of the digitization level in each province in China also show agglomeration characteristics. That is, the regression coefficients of neighboring provinces have similar time-series fluctuations.

Denoise ultra-low-field 3D magnetic resonance images using a joint signal-image domain filter

Ultra-low-field magnetic resonance imaging (MRI) could suffer from heavy uncorrelated noise, and its removal could be a critical post-processing task. As a primary source of interference, Gaussian noise could corrupt the sampled MR signal (k-space data), especially at lower B₀ field strength. For this reason, we consider both signal and image domains by proposing a new joint filter characterized by a Kalman filter with linear prediction and a nonlocal mean filter with higher-order singular value decomposition (HOSVD) for denoising 3D MR data. The Kalman filter first attenuates the noise in k-space, and then its reconstruction images are used to guide HOSVD denoising process with exploring self-similarity among 3D structures. The clearer prefiltered images could also generate improved HOSVD learned bases used to transform the noise corrupted patch groups in the original MR data. The flexibility of proposed method is also demonstrated by integrating other k-space filters into the algorithm scheme. Experimental data includes simulated MR images with the varying noise level and real MR images obtained from our 50 mT MRI scanner. The results reveal that our method has a better noise-removal ability and introduces lesser unexpected artifacts than other related MRI denoising approaches.

Stroke mortality attributable to high red meat intake in China and South Korea: An age-period-cohort and joinpoint analysis

The high intake of red meat is well recognized as a major health concern worldwide. It has been recognized as a risk factor for several non-communicable chronic diseases, including stroke. However, previously published studies have not performed a comprehensive analysis of the long-time trend of stroke mortality attributable to high red meat intake in China and South Korea, two countries with similar dietary patterns and changing trends. Therefore, this study aimed to reveal the influence of age, time period, and birth cohort on long-term trends of stroke mortality attributable to high red meat intake and relative gender differences in China and South Korea. Data were obtained from the Global Burden of Disease 2019 database. The age–period–cohort model was used to estimate the effect of age, time period, and birth cohort. The average and annual percent changes were estimated using the joinpoint regression analysis. Results indicated that the overall attributable age-standardized mortality rates of stroke in China decreased by 1.0% (P < 0.05) for female and 0.1% (P > 0.05) for male individuals, compared with a decrease of 4.9% for female and 3.7% for male individuals in South Korea (both P < 0.05). Age–period–cohort analysis revealed that the attributable stroke mortality decreased along with the time period, and increased along with age. Significant gender differences were observed, male individuals in both countries were at higher risk than their female counterparts, especially in China. Joinpoint analysis suggested that the attributable stroke mortality for both genders in South Korea and female individuals in China showed a decreasing trend, while it is stable for male individuals in China. Although prominent reductions were observed during the past decades, the attributable stroke mortality risk in China and South Korea is still high. Our findings indicate that controlling the intake of red meat may be a cost-effective strategy to reduce stroke mortality risk and the corresponding disease burden, especially for Chinese male individuals.