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This paper examines the impact of the Belt and Road Initiative (BRI) on China's political influence in international affairs, as mediated by Chinese economic integration with the BRI countries. We propose that the BRI plays a role in influencing partner countries to support China's presence in the international community, and the economic integration of the BRI positively mediates the willingness of partner countries to align with China in international affairs. This paper uses panel data from 147 BRI countries collected between 2009 and 2020, and the difference-in-differences method, to estimate the political influence of the BRI. The results suggest that the BRI motivates partner countries to support the growth of China's influence in international affairs. The results of the causal mechanism analysis indicate that a significant and positive association between the implementation of the BRI and China's influence is mediated by promoting Chinese contracts, trade overseas, and outward FDI. The examinations of heterogeneity demonstrate that BRI countries that are developing, non-landlocked, non-neighboring, having signed the memorandum of understanding or cooperation memorandum of understanding, or lacking a Chinese investment guide are more likely to support China's political presence. This paper concludes with insights into how China implements the BRI to enhance its political ascent in the global order by facilitating economic integration of the BRI. [ABSTRACT FROM AUTHOR]

The role of policy advisory systems in the bureaucratic policy-making process has expanded greatly, yet little is known about officials' trust in the analyses they produce. This study investigates whether mid-career administrators in China place greater trust in policy analyses produced by governmental, quasi-governmental, or private think tanks, and the extent to which trust biases among administrators differ based on their age, gender, or the department they work in. We test for the predicted differences through a web-based randomized controlled experiment conducted with mid-career administrators selected for an executive MPA program (N = 405). The findings, derived from ordinal logistic and OLS regression analyses, reveal that bureaucratic officials have greater trust in reports produced by governmental think tanks. Women, older officials, and officials working in social service departments exhibit greater trust bias favoring government produced analyses. The discussion explores how close institutionalized linkages with the party-state align analyses conducted by governmental think tanks with agencies' strategic direction. In contrast, the dependency of quasi-governmental and private think tanks on external resources may undercut their credibility, leading their analyses to serve as a complement to, rather than substitute for that of governmental think tanks. [ABSTRACT FROM AUTHOR]

Aim: The aim of this study was to determine the usefulness of magnetic resonance imaging (MRI) characteristics in discriminating H3 K27M-mutant gliomas from wildtype gliomas in the spinal cord. Materials and methods: Fifty-eight patients with spinal cord gliomas were enrolled in this study. The H3 K27 gene status was identified by Sanger sequencing or immunohistochemistry test of resection tumor specimens. The MR imaging characteristics were evaluated and compared between H3 K27M-mutant and wildtype gliomas using the χ2 test and the Mann–Whitney U test. Results: Of 58 recruited patients, 23 (39.7%) were diagnosed with H3 K27M-mutant glioma. The H3 K27M-mutant gliomas were found to more likely occur in men compared with wildtype gliomas (87.0% vs. 42.9%, p = 0.001). On T2-weighted MR images, the signal-to-noise ratio (SNR) of H3 K27M-mutant gliomas was significantly lower than that of wildtype gliomas (103.9 ± 72.0 vs. 168.9 ± 86.8, p < 0.001). Of 35 wildtype tumors, 60% showed well-defined margin but this feature was not found in all mutant tumors (p < 0.001). The SNR of tumors on contrast-enhanced T1-weighted images of the H3 K27M-mutant gliomas was significantly lower than that of wildtype gliomas (187.7 ± 160.4 vs. 295.1 ± 207.8, p = 0.006). Receiver operating-characteristic analysis revealed that area under curve (AUC) of combination of 1/SNR on T2-weighted images, 1/SNR on contrast-enhanced T1-weighted images, ill-defined margin, and sex reached 0.937 (95% CI, 0.873–1.000) in discriminating H3 K27M-mutant gliomas. Conclusions: The MR imaging characteristics are valuable in discriminating H3 K27M-mutant from wildtype gliomas in the spinal cord and the combination of these imaging features with sex had a high strength in this discrimination. [ABSTRACT FROM AUTHOR]

It can provide a basis for decision making for the conservation and sustainable use of forest ecosystems in mountains to understand the stoichiometric properties and nutrient allocation strategies of major tree species. However, the plant nutrient allocation strategies under different environmental gradients in forest systems of arid and semi-arid mountains are not fully understand. Therefore, three typical regions in the Qilian Mountains on the eastern edge of the Qinghai-Tibet Plateau were selected based on precipitation and temperature gradients, and the stoichiometric characteristics and nutrient allocation strategies of Qinghai spruce (Picea crassifolia) of the dominant tree species under different environmental gradients were investigated. The results showed that (1) the stoichiometric characteristics of plant tissues were different in the three regions. (2) The importance of each tissue in the plant nutrient allocation varied in different regions, showing that the plant roots are more important in the warm-wet region, while the plant leaves, branches and trunks are more important in the transition and hot-dry regions. (3) The influencing factors affecting plant nutrient allocation strategies were inconsistent across regions, which showed that plant nutrient allocation strategies in the warm-wet and transition region were mainly influenced by soil factors, while they were more influenced by climatic factors in the hot-dry region. The patterns of plant nutrient allocation strategies and drivers under different environmental gradients could help us better understand the ecological adaptation mechanism and physiological adjustment mechanism of forest ecosystem in mountains. [ABSTRACT FROM AUTHOR]

Background: Cancer-related depression is a well-documented condition that significantly impacts long-term quality of life. Brain-derived neurotrophic factor (BDNF), a neurotrophin essential for neurogenesis and neuronal plasticity, has been implicated in various neuropsychological disorders including depression associated with cancer. Cytokines, on the other hand, play a crucial role in regulating depression, potentially by influencing BDNF expression. Transforming growth factor-β (TGF-β), a key immune regulator within the tumor microenvironment, has been found to elevate BDNF levels, establishing a link between peripheral immune responses and depression. The study aims to investigate the correlation of TGF-β and BDNF in cancer-related depression. Methods: This study involved a cohort of 153 gynecological patients, including 61 patients with gynecological cancer and 92 patients without cancer. Depression levels were assessed using the subscale of Hospital Anxiety and Depression Scale (HADS-D), and TGF-β and BDNF plasma levels were measured using enzyme-linked immunosorbent assay (ELISA). Results: The study revealed elevated plasma TGF-β levels in patients with cancer (32.24 ± 22.93 ng/ml) compared to those without cancer (25.24 ± 19.72 ng/ml) (P = 0.046). Additionally, reduced levels of BDNF were observed in patients presenting depression symptoms (44.96 ± 41.06 pg/ml) compared to those without depression (133.5 ± 176.7 pg/ml) (P = 0.036). Importantly, a significant correlation between TGF-β and BDNF was found in patients without cancer but with depression (correlation coefficient = 0.893, **P < 0.01). Interestingly, cancer appeared to influence the association between TGF-β and BDNF in patients with depression, as evidenced by a significant difference in the correlation of TGF-β and BDNF between cancer and non-cancer groups (P = 0.041). Conclusions: These findings underscore the active involvement of TGF-β and BDNF crosstalk in the context of cancer-related depression. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC), a globally common cancer, often presents late and shows high resistance to chemotherapy, resulting in suboptimal treatment efficacy. Components from traditional Chinese medicines have been recognized for their anti-cancer properties. Objective: Exploring the mechanism of Schisandra chinensis lignans and acteoside in suppressing Epithelial-Mesenchymal Transition (EMT) in hepatoma cells through the Extracellular signal-Regulated Kinases (ERK)1/2 pathway and identifying biomarkers, molecular subtypes, and targets via multi-omics for precision oncology. Methods: Proliferation was assessed using cell counting kit-8 (CCK-8) assays, with scratch and transwell assays for evaluating invasion and migration. Flow cytometry quantified apoptosis rates. Expression levels of CCL20, p-ERK1/2, c-Myc, Vimentin, and E-cadherin/N-cadherin were analyzed by real-time PCR and Western blot. Tumor volume was calculated with a specific formula, and growth. Results: The Schisandra chinensis lignans and acteoside combination decreased CCL20 expression, inhibited hepatoma proliferation and migration, and enhanced apoptosis in a dose- and time-dependent manner. Molecular analysis revealed increased E-cadherin and decreased N-cadherin, p-ERK1/2, c-Myc, and Vimentin expression, indicating ERK1/2 pathway modulation. In vivo, treated nude mice showed significantly reduced tumor growth and volume. Conclusion: Schisandra chinensis lignans and acteoside potentially counteract CCL20-induced EMT, invasion, and migration in hepatocellular carcinoma cells via the ERK1/2 pathway, enhancing apoptosis. Multi-omics analysis further aids in pinpointing novel biomarkers for precision cancer therapy. [ABSTRACT FROM AUTHOR]

Purpose: To compare the clinical characteristics, virus serotype, and outcome in cases of mild and severe enteroviral infection at a tertiary neonatal intensive care unit in China. Methods: A retrospective analysis of cases hospitalized between June and August 2019. Samples (stool or throat swabs) were examined using reverse transcription polymerase chain reaction. Positive cases were divided into two groups: mild infection and severe infection. Results: A total of 149 cases were assigned to one of two groups: mild infection (n = 104) and severe infection (n = 45). There were no significant differences between the groups in terms of sex, gestational age, birth weight, mode of delivery, and onset within 7 days. Clinical symptoms in both groups mostly resembled sepsis (fever, rash, poor feeding, and lethargy); however, there were significant variations in concomitant symptoms such as hepatitis, thrombocytopenia, encephalitis, coagulopathy, and myocarditis. Severe cases were more likely to have abnormal complete blood counts, biochemical parameters, and cerebrospinal fluid markers. The predominant serotypes implicated in neonatal enterovirus infections were echoviruses and Coxsackievirus B. Invasive ventilation, intravenous immunoglobulin, vasoactive medications, and blood product transfusions were often required, with high mortality rates among severe cases. Conclusion: We found significant differences between mild and severe cases of neonatal enterovirus infection with respect to complications, laboratory findings, and enterovirus serotypes. It is crucial to exercise caution when newborns exhibit symptoms of sepsis, during an enterovirus outbreak. Anemia, thrombocytopenia, abnormal liver function, and coagulation dysfunction should be monitored closely as they could indicate the presence of a severe enteroviral infection. [ABSTRACT FROM AUTHOR]

Introduction: Radiofrequency thermocoagulation (RFT) effectively alleviates idiopathic trigeminal neuralgia (ITN); however, postoperative facial numbness poses a significant challenge. This issue arises due to the close proximity of high-temperature thermocoagulation, which not only ablates pain-related nociceptive fibers but also affects tactile fibers. Intraoperative sensory stimulation voltage (SV), which reflects the distance between the RFT cannula and the target nerve, potentially possesses the ability to prevent tactile fiber injury. This study aimed to investigate the influence of SV on postoperative facial numbness and provide valuable insights to mitigate its occurrence. Methods: A retrospective analysis was performed on 72 ITN patients with maxillary division (V2) pain who underwent RFT between 2020 and 2022. Among them, 13 patients with SV ≤ 0.2 V constituted the low SV group. Subsequently, a matched-cohort analysis was conducted on the remaining 59 patients. The patients paired with the low SV patients were subsequently enrolled in the high SV group, adhering to a 1:1 match ratio. The primary outcome was the facial numbness scale assessment at 3 days, 3 months and 6 months post-surgery. The pain intensity and medication burden served as the secondary outcomes. Results: We successfully matched a cohort consisting of 12 patients in the low SV group and 12 patients in the high SV group. Each patient experienced various degrees of facial numbness at 3 days post-RFT. Notably, the low SV group exhibited a higher incidence of moderate numbness (66.7% vs. 16.67%, P = 0.036), whereas the high SV group had more cases of mild numbness at the 6-month follow-up (25% vs. 83.3%, P = 0.012). Both groups demonstrated significant decreases in pain intensity and medication burden compared to before the operation. Conclusions: SV proved to be a reliable parameter for mitigating the degree of postoperative facial numbness in RFT treatment for ITN. A relatively high sensory SV ranging from 0.3 to 0.6 V during the RFT procedure results in less facial numbness in the treatment of ITN. [ABSTRACT FROM AUTHOR]

A set of colour tuning K2Ba(MoO4)2: Dy3+/Eu3+ (KBM: Dy3+/Eu3+) phosphors were fabricated by solid-state method. The phase purity of as-prepared materials was validated by XRD and DRS analyses. The KBM: 0.03Dy3+ sample exhibits two major luminescence lines at 481 and 572 nm when excited by 351 nm light, corresponding to Dy3+ ions' typical transitions of 4F9/2 → 6HJ (J = 15/2, 13/2). By introducing Eu3+ ions into KBM: 0.03Dy3+ phosphor, the ET from Dy3+ to Eu3+ ions arises, leading to colour tuning from green via yellowish green to pink with changing Eu3+ ions' concentration, along with the lowest CCT of KBM: 0.03Dy3+/0.03Eu3+ sample. It can be verified by PLE and PL spectra analysis combined with the decay times of KBM: 0.03Dy3+/yEu3+ samples. The energy transfer mechanism is also expounded. Meanwhile, the emission intensities at 423 K still maintain 72.8% for Dy3+ ions and 91.2% for Eu3+ ions relative to 303 K of the KBM: 0.03Dy3+/0.03Eu3+ sample, displaying its brilliant thermal stability. All these results connote that KBM: Dy3+/Eu3+ phosphors are prospected to be used for the near-UV excited white light-emitting diodes. [ABSTRACT FROM AUTHOR]

The brown planthopper (BPH), Nilaparvata lugens (Stål), is one of the most important rice pests in Asia rice regions. BPH has monophagy, migration, rapid reproduction and strong environmental adaptability, and its control is a major problem in pest management. Adult BPH exhibit wing dimorphism, and the symbiotic microbiota enriched in the gut can provide energy for wing flight muscles as a source of nutrition. In order to study the diversity of symbiotic microbiota in different winged BPHs, this paper takes female BPH as the research object. It was found that the number of symbiotic microbiota of different winged BPHs would change at different development stages. Then, based on the 16S rRNA and ITS sequences, a metagenomic library was constructed, combined with fluorescent quantitative PCR and high-throughput sequencing, the dominant symbiotic microbiota flora in the gut of different winged BPHs was found, and the community structure and composition of symbiotic microbiota in different winged BPHs were further determined. Together, our results preliminarily revealed that symbiotic microbiota in the gut of BPHs have certain effects on wing morphology, and understanding the mechanisms underlying wing morph differentiation will clarify how nutritional factors or environmental cues alter or regulate physiological and metabolic pathways. These findings also establish a theoretical basis for subsequent explorations into BPH-symbiont interplay. [ABSTRACT FROM AUTHOR]

The thermal conductivity of soil is an essential parameter for designing geothermal energy foundations and borehole heat exchange systems. To effectively improve the development efficiency of geothermal resources in the loess region of China, the plane heat source method was used to measure the thermal conductivity of loess samples with different water contents and temperatures, and scanning electron microscopy tests were conducted. Analyze the effects of water content, temperature, and soil microstructure on thermal conductivity. A weighted geometric mean model considering the soil temperature effect is proposed and compared with the traditional model. The experimental results reveal that soil thermal conductivity increases in stages as the temperature rises. After the temperature exceeds 30℃, the contribution of steam latent heat transfer to soil thermal conductivity gradually becomes significant. Within the temperature range of 1–60℃, the thermal conductivity increases with increasing saturation and tends to stabilize after saturation exceeds 60%; When the temperature is greater than 60℃, the thermal conductivity peaks near a saturation of 60%. As the water content increases, there is a significant difference in the thermal conductivity of undisturbed and remolded loess, which is related to the microstructure changes of the soil. The model calculation shows that the weighted geometric mean model proposed in this paper has the best prediction performance. The Leong model has good predictive performance for the thermal conductivity of loess, while the Gori and Lusen models have the lowest predictive accuracy. [ABSTRACT FROM AUTHOR]

Water shortages and population surges pose notable challenges to food security. North China is an important grain base of the country, with limited available water resources. Therefore, it is necessary to research the patterns of photosynthate accumulation, distribution, and transfer in summer maize under water stress. On the basis of existing methods, in this study, we considered the impact of water stress with two methods, namely the distribution coefficient method and the distribution index method. The results showed that the water correction coefficient indices of the stem–leaf ratio spike–stem ratio, and root–shoot ratio were 0.2705, 0.3530, and −0.2097, respectively, which revealed that water stress caused a decrease in the stem–leaf ratio and spike–stem ratio and an increase in the root–shoot ratio. Water stress caused a reduction in the stem distribution index and leaf distribution index and a slight increase in the spike distribution index. The filling stage was the critical period for water stress to affect the distribution coefficient of each organ, while the jointing stage was the critical period for water stress to affect the leaf distribution index. During the middle growth period, water stress exerted the greatest impact on the distribution parameters. Water stress imposed a greater influence on the distribution coefficient than on the distribution index. The two methods effectively simulated the accumulation and distribution process of photosynthates under water stress conditions, and the R2, average absolute percentage and root mean square error values were 0.9358–0.9997, 4.15–22.71%, and 2.6–24.37%, respectively. The change trend of the photosynthate transfer rate calculated by the distribution coefficient method under water stress conditions was more consistent with that of the actual values. The distribution coefficient method generally performed better than the distribution index method. This study avoids the problem of solely relying on experimental data to determine crop growth dynamics and provides a way to describe crop photosynthate accumulation continuously and quantitatively. [ABSTRACT FROM AUTHOR]

The g-C3N4/Ag/Bi2O2CO3 nanosheets were synthesized using a mixture of precursors containing melamine and nitrates of silver and bismuth through a simple one-pot synthesis strategy. In the presence of ammonium nitrate, g-C3N4/Ag/Bi2O2CO3 composite catalysts with different silver mass ratios were prepared, and the photodegradation performance of the composite samples was evaluated by photodegradation of tetracycline hydrochloride (TC) under simulated solar light irradiation. The synthesized composites were characterized by XPD, XPS, FT-IR, TEM, UV–vis DRS and PL. It was found that the g-C3N4/Ag/Bi2O2CO3 catalyst with Ag mass ratio of 4% exhibited the highest catalytic activity, and the degradation effect was more than 9 times that of pure C3N4 and nearly 5 times that of g-C3N4/Bi2O2CO3.In addition, cyclic experiments showed that g-C3N4/Ag/Bi2O2CO3 composites had certain stability. The photocatalytic performance of the g-C3N4/Ag/Bi2O2CO3 composites was attributable to the heterogeneous junction of Bi2O2CO3 and g-C3N4 and the surface plasmon resonance effect (SPR) of Ag nanoparticles. The energy levels of Bi2O2CO3 and g-C3N4 were properly matched to form a heterojunction, which promoted the separation and transfer of photogenerated electrons and holes, thereby improving the photocatalytic performance. The Ag surface plasmon resonance (SPR) effect not only accelerated the separation and transmission of electron–hole pairs, but also enhanced the absorption of visible light. Finally, based on the above basis, a possible photocatalytic mechanism was proposed. [ABSTRACT FROM AUTHOR]

The H ∞ control problem is studied for discrete-time Markov jump systems with both discrete and distributed delays. The controller to be designed allows for mode mismatch with the plant, and the mode mismatch behavior is described by a hidden Markov model. The conditional probabilities are permitted to be uncertain, which belong to an interval with precise upper and lower bounds. A sufficient condition that ensures the stochastic stability and H ∞ disturbance-attenuation performance of the system is derived by employing a Lyapunov functional involving multiple quadratic items associated with the system modes. Then, two design methods are proposed for the desired controller. The first method does not utilize the property that the row sum of the conditional probability matrix is one, while the second method incorporates this property into the design process. The scenario where all the conditional probabilities are known in advance is also investigated, and corresponding controller design methods are presented. Finally, two examples are applied to validate the effectiveness of the design methods. [ABSTRACT FROM AUTHOR]

Photocatalytic ethanol conversion into high-valuable chemicals while realizing hydrogen production is attractive and challenging. In this study, flower-like, porous flower-like, and net-like CdS nanostructures were prepared by solvothermal technique and were used to investigate the effect of morphology on ethanol conversion. It was found by characterization that the one-dimensional net-like CdS had the best crystallinity and the largest specific surface area, which provided more active sites and possessed superior ethanol conversion activity. The ethanol conversion was 4.7% in 10 h with a hydrogen production rate of 1.32 mmol g−1 h−1 and an acetaldehyde (AA) production rate of 1.96 mmol g−1 h−1 with a selectivity of 51%. In comparison, 2,3-butanediol(2,3-BDO) was produced at a rate of 0.61 mmol g−1 h−1 with a selectivity of 32%. The pore structure of one-dimensional net-like CdS with predominantly large mesopores showed better selectivity for 2,3-BDO, indicating that the pore size of the catalyst plays an important role in the C–C coupling reaction. Further, the catalysts were modified by depositing Pt nanoparticles on net-like CdS and the photocatalytic ethanol conversion performance was improved by about 3.5 times. [ABSTRACT FROM AUTHOR]

Compared to japonica, the lower genetic transformation efficiency of indica is a technical bottleneck for rice molecular breeding. Specifically, callus browning frequently occurs during the culture of the elite indica variety 93-11, leading to poor culturability and lower genetic transformation efficiency. Here, 67 QTLs related to culturability were detected using 97 introgression lines (designated as 9DILs) derived from Dongxiang common wild rice (DXCWR, Oryza rufipogon Griff.) with 93-11 genetic background, explaining 4% ~12% of the phenotypic variations. The QTL qCBT9 on chromosome 9 was a primary QTL for reducing callus browning derived from DXCWR. Five 9DILs with light callus browning and high differentiation were screened. We evaluated the callus browning index (CBI) of 100 F2 population crossed of 93-11 and 9DIL71 and the recombinant plants screened from 3270 individuals. The qCBT9 was delimited to a ~148kb region between the markers X16 and X23. RNA-seq analysis of DEGs between 9DIL71 and 93-11 showed three upregulated DEGs (Os09g0526500, Os09g0527900, Os09g0528200,) and three downregulated DEGs (Os09g0526700, Os09g0526800, Os09g0527700) were located in the candidate region of qCBT9. Furthermore, callus browning may be involved in cell senescence and death caused by oxidative stress. The differentiation of indica and japonica in this region suggested that qCBT9 was possibly a vital QTL contributed to better culturability of japonica. Our results laid a foundation for further cloning of the gene for reduced callus browning in O. rufipogon, and also provided a new genetic resource and material basis for improving the culturability and genetic transformation efficiency of cultivated rice. [ABSTRACT FROM AUTHOR]

Graph databases have received increased interests as many applications are handled as graph problems. Shortest distance queries are one of the fundamental operations and have been studied for recent years. To ensure the data and query privacy, researchers have introduced some secure graph encryption schemes which support the shortest distance queries on a large-scale graph database. Unfortunately, most of them only provide an approximate result by pre-computing and storing a distance oracle. To provide the exact shortest path, our solution employs a distributed two-trapdoor public-key crypto-system to perform addition and comparison operations over ciphertexts. The detailed security analysis indicates that our scheme achieves semantically secure under DDH assumption and the experiments are performed on various real-world database and random database. The experimental result shows the feasibility of our scheme. [ABSTRACT FROM AUTHOR]

Highlights: Evaporation and solution two-step hybrid process are used to fabricate conformal growth of perovskite film on textured silicon substrates. F-PMAI additive enlarged the perovskite grains, induced the (111) preferred orientation and passivated interface defects. We obtained a champion efficiency of 30.05% for a monolithic perovskite/silicon tandem solar cell based on a silicon thin film tunneling junction. Monolithic textured perovskite/silicon tandem solar cells (TSCs) are expected to achieve maximum light capture at the lowest cost, potentially exhibiting the best power conversion efficiency. However, it is challenging to fabricate high-quality perovskite films and preferred crystal orientation on commercially textured silicon substrates with micrometer-size pyramids. Here, we introduced a bulky organic molecule (4-fluorobenzylamine hydroiodide (F-PMAI)) as a perovskite additive. It is found that F-PMAI can retard the crystallization process of perovskite film through hydrogen bond interaction between F− and FA+ and reduce (111) facet surface energy due to enhanced adsorption energy of F-PMAI on the (111) facet. Besides, the bulky molecular is extruded to the bottom and top of perovskite film after crystal growth, which can passivate interface defects through strong interaction between F-PMA+ and undercoordinated Pb2+/I−. As a result, the additive facilitates the formation of large perovskite grains and (111) preferred orientation with a reduced trap-state density, thereby promoting charge carrier transportation, and enhancing device performance and stability. The perovskite/silicon TSCs achieved a champion efficiency of 30.05% based on a silicon thin film tunneling junction. In addition, the devices exhibit excellent long-term thermal and light stability without encapsulation. This work provides an effective strategy for achieving efficient and stable TSCs. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the survival outcomes of neoadjuvant radiochemotherapy (NARCT) for early breast cancer. Female patients ≤ 80 years old with unilateral T1-T4 invasive ductal breast cancer treated with neoadjuvant chemotherapy (NAC) and radiation therapy (RT) between 2006 and 2015 were enrolled from SEER database. Baseline differences in clinical and pathological characteristics were evaluated using chi-square test. The survival outcomes were estimated by Kaplan–Meier analysis and compared using Cox hazards models. The effects of baseline differences on survival outcome in patients treated with neoadjuvant radiation therapy (NART) and post-operation radiation therapy (PORT) were circumvented by propensity score matching (PSM). Altogether 14,151 patients receiving NAC and RT were enrolled, among whom 386 underwent NART. Based on a 1:4 PSM cohort, NART was an independent unfavorable prognostic factor for breast cancer-specific survival (BCSS) and overall survival (OS) for the whole cohort. However, among patients receiving breast conserving surgery (BCS) (HR 1.029, P = 0.915 for BCSS; HR 1.003, P = 0.990 for OS) or implant-based immediate breast reconstruction (IBR) (HR 1.039, P = 0.921 for BCSS; HR 1.153, P = 0.697 for OS), those treated with NART had similar survival outcomes compared with patients treated with PORT. In conclusion, NARCT was a safe and feasible approach for patients undergoing BCS and IBR. [ABSTRACT FROM AUTHOR]

This cross-sectional study investigated the association between glaucoma and B vitamin dietary intake. A total of 5025 enrolled individuals participated in self-reported glaucoma questionnaire and 3264 participated in International Society Geographical and Epidemiological Ophthalmology (ISGEO) criteria. In self-reported glaucoma, the risk of having self-reported glaucoma was lower in the third quartile of vitamin B1 intake (odds ratio [odds ratio [OR] 0.63, 95% confidence interval [CI] 0.40–0.97), and P trend (P trend = 0.004) for vitamin B12 was significant; in males, the third quartile of vitamin B1 intake (OR 0.44, 95% CI 0.24–0.83) and the fourth quartile of vitamin B2 intake (OR 0.39, 95% CI 0.17–0.89) were associated with a lower risk. In glaucoma based on ISGEO criteria, the increase of niacin intake (OR 0.94, 95% CI 0.89–0.99) was negatively associated with the odds of self-reported glaucoma. After sex-stratified analysis, the third quartile of vitamin B6 intake (OR 0.21, 95% CI 0.08–0.60) in males were associated with reduced odds of glaucoma. The restricted cubic spline analysis revealed a nonlinear association of vitamin B2 (p for nonlinearity = 0.04) and B9 (p for nonlinearity = 0.024) intake with glaucoma diagnosed by ISGEO criteria in females. [ABSTRACT FROM AUTHOR]

Imaging technologies have played a pivotal role in advancing biological research by enabling visualization of biological structures and processes. While traditional electron microscopy (EM) produces two-dimensional images, emerging techniques now allow high-resolution three-dimensional (3D) characterization of specimens in situ, meeting growing needs in molecular and cellular biology. Combining transmission electron microscopy (TEM) with serial sectioning inaugurated 3D imaging, attracting biologists seeking to explore cell ultrastructure and driving advancement of 3D EM reconstruction. By comprehensively and precisely rendering internal structure and distribution, 3D TEM reconstruction provides unparalleled ultrastructural insights into cells and molecules, holding tremendous value for elucidating structure–function relationships and broadly propelling structural biology. Here, we first introduce the principle of 3D reconstruction of cells and tissues by classical approaches in TEM and then discuss modern technologies utilizing TEM and on new SEM-based as well as cryo-electron microscope (cryo-EM) techniques. 3D reconstruction techniques from serial sections, electron tomography (ET), and the recent single-particle analysis (SPA) are examined; the focused ion beam scanning electron microscopy (FIB-SEM), the serial block-face scanning electron microscopy (SBF-SEM), and automatic tape-collecting lathe ultramicrotome (ATUM-SEM) for 3D reconstruction of large volumes are discussed. Finally, we review the challenges and development prospects of these technologies in life science. It aims to provide an informative reference for biological researchers. [ABSTRACT FROM AUTHOR]

Learning-related attention is one of the most important factors influencing learning. Although technologies have enabled the automatic detection of students' attention levels, previous studies mainly focused on colleges or high schools, lacking further validations in primary school students. More importantly, the detected attention might fail to be learning-related if students did not attend learning tasks in the first place, which is common in real-world learning. This phenomenon poses challenges to the practical application of automatic attention detection, especially at the primary school stage, which is crucial for students to develop learning attitudes/strategies. Inspired by the emerging inter-person perspective in neuroscience, we proposed an inter-brain attention coupling method to detect learning-related attention as an extension to the existing single-person-based method. To test this method, wearable electroencephalogram devices were used to monitor students' attention levels in a primary school classroom. We found that one's inter-brain attention coupling, defined as the degree to which an individual student's attention dynamics match the attention dynamics averaged across other classmates, was positively correlated with academic performance: higher performances are associated with higher coupling to the class-average attention dynamics. Moreover, the attention detection framework based on the inter-person perspective outperforms as an indicator of academic performance compared with the widely-used attention level within an individual. The results provide practical insights by extending the applications of detected attention levels from an inter-person perspective and demonstrating its feasibility in monitoring learning-related attention among primary school students. [ABSTRACT FROM AUTHOR]

Purpose: Tumors bearing mismatch repair deficiency (MMRd) are characterized by a high load of neoantigens and are believed to trigger immunogenic reactions upon immune checkpoint blockade treatment such as anti-PD-1/PD-L1 therapy. However, the mechanisms are still ill-defined, as multiple cancers with MMRd exhibit variable responses to immune checkpoint inhibitors (ICIs). In endometrial cancer (EC), a distinct tumor microenvironment (TME) exists that may correspond to treatment-related efficacies. We aimed to characterize EC patients with aberrant MMR pathways to identify molecular subtypes predisposed to respond to ICI therapies. Methods: We applied digital spatial profiling, a high-plex spatial transcriptomic approach covering over 1,800 genes, to obtain a highly resolved TME landscape in 45 MMRd-EC patients. We cross-validated multiple biomarkers identified using immunohistochemistry and multiplexed immunofluorescence using in-study and independent cohorts totaling 123 MMRd-EC patients and validated our findings using external TCGA data from microsatellite instability endometrial cancer (MSI-EC) patients. Results: High-plex spatial profiling identified a 14-gene signature in the MMRd tumor-enriched regions stratifying tumors into "hot", "intermediate" and "cold" groups according to their distinct immune profiles, a finding highly consistent with the corresponding CD8 + T-cell infiltration status. Our validation studies further corroborated an existing coregulatory network involving HLA class I and DNMT3A potentially bridged through dynamic crosstalk incorporating CCL5. Conclusion: Our study confirmed the heterogeneous TME status within MMRd-ECs and showed that these ECs can be stratified based on potential biomarkers such as HLA class I, DNMT3A and CD8 in pathological settings for improved ICI therapeutic efficacy in this subset of patients. [ABSTRACT FROM AUTHOR]

With the rapid development of artificial intelligence and Internet of Things (IoT) technology, increasingly edge devices have entered people's daily lives. However, due to the limited performance of edge devices, complex models can affect the response speed and efficiency of the whole system. Existing research still cannot simultaneously satisfy the demand for accuracy and response speed of edge devices. This paper proposes a lightweight and highly accurate object detection model that uses the Transformer to address edge devices' limited computational capacity and storage space. Specifically, the proposed model adopts the Swin Transformer for multi-scale feature extraction to achieve better global modeling capability. In addition, we propose the Neck module with path aggregation network (PAN), which is designed with a two-feature pyramid structure capable of combining semantic and localization information in order to improve the operational performance by exploiting the underlying location features. A lightweight detection head is then developed using group convolution, fusing the two localization branches and removes the additional decoupling operation. Finally, we conduct comparative experiments on three datasets: the Retail-cabinet dataset, the Roadsign dataset, and the Pascal VOC dataset. Experimental results show that compared with the baseline model, our model achieves an 11.8% improvement in mAP on the Retail-cabinet dataset while reducing Params and FLOPs by 23.19% and 71.50%, respectively. The proposed model effectively reduces the model's computational complexity and improves detection performance, thereby possessing high practical value. This code is released on https://github.com/ydlam/ST-YOLOX. [ABSTRACT FROM AUTHOR]

Objective: We aimed to develop a radiomics-clinical nomogram using multi-sequence MRI to predict recurrence-free survival (RFS) in bladder cancer (BCa) patients and assess its superiority over clinical models. Methods: A retrospective cohort of 229 BCa patients with preoperative multi-sequence MRI was divided into a training set (n = 160) and a validation set (n = 69). Radiomics features were extracted from T2-weighted images, diffusion-weighted imaging, apparent diffusion coefficient, and dynamic contrast-enhanced images. Effective features were identified using the least absolute shrinkage and selection operator (LASSO) method. Clinical risk factors were determined via univariate and multivariate Cox analysis, leading to the creation of a radiomics-clinical nomogram. Kaplan-Meier analysis and log-rank tests assessed the relationship between radiomics features and RFS. We calculated the net reclassification improvement (NRI) to evaluate the added value of the radiomics signature and used decision curve analysis (DCA) to assess the nomogram's clinical validity. Results: Radiomics features significantly correlated with RFS (log-rank p < 0.001) and were independent of clinical factors (p < 0.001). The combined model, incorporating radiomics features and clinical data, demonstrated the best prognostic value, with C-index values of 0.853 in the training set and 0.832 in the validation set. Compared to the clinical model, the radiomics-clinical nomogram exhibited superior calibration and classification (NRI: 0.6768, 95% CI: 0.5549-0.7987, p < 0.001). Conclusion: The radiomics-clinical nomogram, based on multi-sequence MRI, effectively assesses the BCa recurrence risk. It outperforms both the radiomics model and the clinical model in predicting BCa recurrence risk. Critical relevance statement: The radiomics-clinical nomogram, utilizing multi-sequence MRI, holds promise for predicting bladder cancer recurrence, enhancing individualized clinical treatment, and performing tumor surveillance. Key points: • Radiomics plays a vital role in predicting bladder cancer recurrence. • Precise prediction of tumor recurrence risk is crucial for clinical management. • MRI-based radiomics models excel in predicting bladder cancer recurrence. [ABSTRACT FROM AUTHOR]

Sulfur (S) is one of the main components of important biomolecules, which has been paid more attention in the anaerobic environment of rice cultivation. In this study, 12 accessions of rice materials, belonging to two Asian rice domestication systems and one African rice domestication system, were used by shotgun metagenomics sequencing to compare the structure and function involved in S cycle of rhizosphere microbiome between wild and cultivated rice. The sulfur cycle functional genes abundances were significantly different between wild and cultivated rice rhizosphere in the processes of sulfate reduction and other sulfur compounds conversion, implicating that wild rice had a stronger mutually-beneficial relationship with rhizosphere microbiome, enhancing sulfur utilization. To assess the effects of sulfate reduction synthetic microbiomes, Comamonadaceae and Rhodospirillaceae, two families containing the genes of two key steps in the dissimilatory sulfate reduction, aprA and dsrA respectively, were isolated from wild rice rhizosphere. Compared with the control group, the dissimilatory sulfate reduction in cultivated rice rhizosphere was significantly improved in the inoculated with different proportions groups. It confirmed that the synthetic microbiome can promote the S-cycling in rice, and suggested that may be feasible to construct the synthetic microbiome step by step based on functional genes to achieve the target functional pathway. In summary, this study reveals the response of rice rhizosphere microbial community structure and function to domestication, and provides a new idea for the construction of synthetic microbiome. [ABSTRACT FROM AUTHOR]

A recent study by Liu et al. (2020) suggested that due to the saturation of equatorially trapped planetary waves with different dynamical types, temporal periods, meridional and baroclinic modes, complex layer structures of vertical velocity shear and hence turbulent mixing could frequently occur in the thermocline of the eastern equatorial Pacific. We investigated the occurrence of the interior turbulent mixing as indicated by shear instabilities, above the Equatorial Undercurrent (EUC) core at three equatorial sites along 140°W, 170°W, and 165°E, respectively, based mainly on data from the Tropical Atmosphere and Ocean (TAO) mooring array. We found that turbulent mixing bursts persisted in the thermocline of all three sites. Specifically, the interior turbulent mixing layers (ITMLs) could occur in probability of approximately 68%, 53%, and 48% at the three sites, respectively. The overall occurrence probability shows obvious and similar biannual variations at 140°W and 170°W, which is higher in boreal from late summer to winter and lower in spring. Vertically, the ITMLs are primarily located above the EUC core and prevail in deeper (shallower) layers from late summer to winter (spring). Most ITMLs (70%) lasted for hours to 3 days, and a few of them (15%) for more than 7 days. The thicknesses of ITMLs were concentrated between 15 and 55 m. At 165°E, the vertical distribution of ITML occurrence probability was different from that at 140°W and 170°W, as it did not show a preference for depths; the durations of ITMLs are short (also from hours to several days) and their thicknesses were between 5 and 25 m. These properties, particularly the high occurrence probability, and short durations demonstrated the persistence of thermocline mixing in the western to eastern equatorial Pacific thermocline and confirmed the generation mechanism by persistent equatorial waves as well. [ABSTRACT FROM AUTHOR]

Methyltransferase-like protein 7A (METTL7A) is an m6A RNA methyltransferase that has been linked to cancer prognosis and drug resistance. However, a comprehensive analysis of METTL7A is lacking. The expression of METTL7A, prognostic performance, correlation with microsatellite instability (MSI), tumor mutational burden (TMB), and immune infiltration was investigated in The Cancer Genome Atlas (TCGA). Immunohistochemistry staining was applied to detect METTL7A in 6 tumors. METTL7A was significantly decreased in 19 cancers in TCGA including LUAD. Alterations of METTL7A include amplification and mutation, and epigenetic alterations revealed increased promoter methylation may result in down-regulation of METTL7A in LUAD. We also found that METTL7A was linked to both TMB and MSI in LUAD. METTL7A was increasingly correlated with invasive immune cells, while being negatively associated with Macrophages M0, Mast cells activated, activated memory CD4 T cells, CD8 T cells, and follicular helper T cells in several tumors. Additionally, METTL7A showed similar correlation with immune therapy-related genes across cancers. Our biological validation found that the protein levels of METTL7A were down-regulated in breast cancer (BRCA), endometrioid cancer (UCEC), colon cancer (COAD), prostate cancer (PRAD), and kidney clear cell carcinoma (KIRC), as detected by immunohistochemistry staining. Overall, our work indicates that METTL7A may serve as promising diagnostic and prognostic indicator of LUAD, and our work sheds light on the potential immunological and prognostic roles of METTL7A in human cancers. [ABSTRACT FROM AUTHOR]

Objectives: To develop a deep learning (DL) model for differentiating between osteolytic osteosarcoma (OS) and giant cell tumor (GCT) on radiographs. Methods: Patients with osteolytic OS and GCT proven by postoperative pathology were retrospectively recruited from four centers (center A, training and internal testing; centers B, C, and D, external testing). Sixteen radiologists with different experiences in musculoskeletal imaging diagnosis were divided into three groups and participated with or without the DL model's assistance. DL model was generated using EfficientNet-B6 architecture, and the clinical model was trained using clinical variables. The performance of various models was compared using McNemar's test. Results: Three hundred thirty-three patients were included (mean age, 27 years ± 12 [SD]; 186 men). Compared to the clinical model, the DL model achieved a higher area under the curve (AUC) in both the internal (0.97 vs. 0.77, p = 0.008) and external test set (0.97 vs. 0.64, p < 0.001). In the total test set (including the internal and external test sets), the DL model achieved higher accuracy than the junior expert committee (93.1% vs. 72.4%; p < 0.001) and was comparable to the intermediate and senior expert committee (93.1% vs. 88.8%, p = 0.25; 87.1%, p = 0.35). With DL model assistance, the accuracy of the junior expert committee was improved from 72.4% to 91.4% (p = 0.051). Conclusion: The DL model accurately distinguished osteolytic OS and GCT with better performance than the junior radiologists, whose own diagnostic performances were significantly improved with the aid of the model, indicating the potential for the differential diagnosis of the two bone tumors on radiographs. Critical relevance statement: The deep learning model can accurately distinguish osteolytic osteosarcoma and giant cell tumor on radiographs, which may help radiologists improve the diagnostic accuracy of two types of tumors. Key points: • The DL model shows robust performance in distinguishing osteolytic osteosarcoma and giant cell tumor. • The diagnosis performance of the DL model is better than junior radiologists'. • The DL model shows potential for differentiating osteolytic osteosarcoma and giant cell tumor. [ABSTRACT FROM AUTHOR]

Heat shock protein 90α (HSP90α) has been regarded as an important indicator for judging tumor metastasis and prognosis due to its significant upregulation in various tumors. Therefore, the accurate quantification of HSP90α is of great significance for clinical diagnosis and therapy of cancers. However, the lack of HSP90α certified reference material (CRM) leads to the accuracy and consistency of quantification methods not being effectively evaluated. Besides, quantitative results without traceability make comparisons between different studies difficult. In this study, an HSP90α solution CRM was developed from the recombinant protein raw material. The recombinant protein is a dimer, and the purity of the CRM candidate reached 96.71%. Both amino acid analysis-isotope dilution mass spectrometry (AAA-IDMS) and unique peptide analysis-isotope dilution mass spectrometry (UPA-IDMS) were performed to measure the content of HSP90α in the solution CRM candidate, and the certified value was assessed to be 66.2 ± 8.8 µg/g. Good homogeneity of the CRM was identified, and the stability examination suggested that the CRM was stable for at least 4 months at − 80 °C and for 7 days at 4 °C. With traceability to SI unit (kg), this CRM has potential to help establish a metrological traceability chain for quantification of HSP90α, which will make the quantification results standardized and comparable regardless of the quantitative methods. [ABSTRACT FROM AUTHOR]

Introduction: The burden of stroke in patients with hypertension is very high, and its prediction is critical. Objectives: We aimed to use plasma lipidomics profiling to identify lipid biomarkers for predicting incident stroke in patients with hypertension. Methods: This was a nested case-control study. Baseline plasma samples were collected from 30 hypertensive patients with newly developed stroke, 30 matched patients with hypertension, 30 matched patients at high risk of stroke, and 30 matched healthy controls. Lipidomics analysis was performed by ultrahigh-performance liquid chromatography–tandem mass spectrometry, and differential lipid metabolites were screened using multivariate and univariate statistical methods. Machine learning methods (least absolute shrinkage and selection operator, random forest) were used to identify candidate biomarkers for predicting stroke in patients with hypertension. Results: Co-expression network analysis revealed that the key molecular alterations of the lipid network in stroke implicate glycerophospholipid metabolism and choline metabolism. Six lipid metabolites were identified as candidate biomarkers by multivariate statistical and machine learning methods, namely phosphatidyl choline(40:3p)(rep), cholesteryl ester(20:5), monoglyceride(29:5), triglyceride(18:0p/18:1/18:1), triglyceride(18:1/18:2/21:0) and coenzyme(q9). The combination of these six lipid biomarkers exhibited good diagnostic and predictive ability, as it could indicate a risk of stroke at an early stage in patients with hypertension (area under the curve = 0.870; 95% confidence interval: 0.783–0.957). Conclusions: We determined lipidomic signatures associated with future stroke development and identified new lipid biomarkers for predicting stroke in patients with hypertension. The biomarkers have translational potential and thus may serve as blood-based biomarkers for predicting hypertensive stroke. [ABSTRACT FROM AUTHOR]

Designing a Student Management System based on big data and deep learning is paramount in the modern educational landscape. This innovative approach allows institutions to harness the power of vast datasets to gain actionable insights into student performance, preferences, and learning patterns. The research begins by identifying various facets and modules within the student ecosystem that impact student success, including examination results, health records, grades analysis, demographics, co-curricular activities, teacher information, and parental details. The data pertaining to these modules are inherently distributed, and the system organizes it into a unified format using the big data tool Apache Hadoop. The goal is to consolidate the data for utilization by deep learning models in predicting student success. Apache Hadoop, as a robust big data tool, facilitates efficient storage and analysis of large datasets. Subsequently, a Feed Forward Neural Network (FNN) model is developed to extract distinctive patterns indicative of student success. The planned FNN architecture incorporates 128 neurons and employs Rectified Linear Unit (RELU) and SoftMax activation functions to enhance predictive capabilities. The increased number of neurons in the model allows for a comprehensive exploration of all student data sources, thereby improving the true positive rate. Ultimately, the computation of execution and timely interventions by teachers, parents, and administration demonstrates heightened precision resulting from the analysis and rotation creation methods, leading to an efficient student management system. A thorough comparison with earlier approaches underscores its superior effectiveness, with a noteworthy 45% increase in accuracy and a significant 55% enhancement in precision. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the significance of chemotherapy (CT) among metaplastic breast cancer (MpBC), and to compare the survival outcomes between triple negative MpBC (MpBC-TNBC) and triple negative invasive ductal carcinoma (IDC-TNBC). SEER database was indexed to identify female unilateral primary MpBC diagnosed from 2010 to 2017. Patients were classified into neoadjuvant chemotherapy (NAC) with response (NAC-response), NAC-no response, adjuvant chemotherapy, and no CT. Breast cancer-specific survival (BCSS) and overall survival (OS) was estimated using the Kaplan–Meier method and compared by log-rank test. Cox regression was used to evaluate the independent prognostic factors. A 1:4 propensity score matching method was adopted to balance baseline differences. Altogether 1186 MpBC patients were enrolled, among them 181 received NAC, 647 received adjuvant CT and 358 did not receive any CT. Chemotherapy was an independent favorable prognostic factor. NAC-response and adjuvant CT had a significant or an obvious trend of survival improvement compared with NAC-no response or no CT. MpBC-TNBC was an independent unfavorable prognostic factor compared with IDC-TNBC. Among them, there was significant or trend of survival improvement among all TNBCs receiving NAC or adjuvant CT compared with no CT. Chemotherapy was of important significance to MpBC prognosis and should be integrated in comprehensive treatment for MpBC. [ABSTRACT FROM AUTHOR]

Purpose: This study intends to assess the reference range of lamotrigine concentration for treating childhood epilepsy. Methods: PubMed, Ovid-Embase, The Cochrane Library, CNKI, WanFang data and VIP databases were searched from database inception to January 2022. RCT, cohort study, case–control study, cross-sectional study that estimated the reference range of lamotrigine for children epilepsy treatment were included. The data extracted included basic information, statistical methods, data type, and results of reference range. Descriptive analysis was performed for them. Results: 8 studies were included and estimated the reference range, and all of them were calculated based on efficacy data and/or concentration data. Statistical methods including ROC curve, concentration-effect curve, mean ± standard deviation, 95% confidence interval and percentile interval were utilized. For lamotrigine monotherapy, the lower limits ranged from 2.06 mg/L to 3.99 mg/L, and the upper limits ranged from 8.43 mg/L to 9.08 mg/L, showing basic consistency. However, for lamotrigine concomitant with valproate, the lower limits ranged from 2.00 mg/L to 8.00 mg/L, and the upper limit was 11.50 mg/L, for lamotrigine concomitant with other antiepileptics, the lower limits ranged from 1.00 mg/L to 3.09 mg/L, and the upper limits varied from 5.90 mg/L to 16.24 mg/L, indicating inconsistency. Conclusion: Several studies have estimated the reference range of lamotrigine for childhood epilepsy, while controversy exist and no studies have determined the upper limit of the range based on safety data. To establish the optimal reference range, further high-quality studies are necessary that consider both efficacy and safety data. [ABSTRACT FROM AUTHOR]

Neuroinflammation is an important pathogenesis of neurological diseases and causes a series of physiopathological changes, such as abnormal activation of glial cells, neuronal degeneration and death, and disruption of the blood‒brain barrier. Therefore, modulating inflammation may be an important therapeutic tool for treating neurological diseases. Mesenchymal stem cells (MSCs), as pluripotent stem cells, have great therapeutic potential for neurological diseases due to their regenerative ability, immunity, and ability to regulate inflammation. However, recent studies have shown that MSC-derived exosomes (MSC-Exos) play a major role in this process and play a key role in neuroprotection by regulating neuroglia. This review summarizes the recent progress made in regulating neuroinflammation by focusing on the mechanisms by which MSC-Exos are involved in the regulation of glial cells through signaling pathways such as the TLR, NF-κB, MAPK, STAT, and NLRP3 pathways to provide some references for subsequent research and therapy. Exosomes derived from MSCs exhibit neuroprotective effects by regulating signaling pathways and mitigating neuroinflammation triggered by glial cells. [ABSTRACT FROM AUTHOR]

Reticulated porous MgO ceramics were fabricated by suspension impregnation method, which involves replication of polyurethane foam with mixed slurry of MgO and MgF2 and subsequent sintering treatments. The objective of the present study is to find a suitable method to ensure uniform macropore or micropore structure of ceramics foam using low-melting additives at moderate sintering temperatures. The microstructures of Magnesia Foam Ceramics (MFC) were evaluated by scanning electron microscopy (SEM) coupled with X-ray diffraction (XRD). The loading amount and apparent porosity of MFC are related to the slurry viscosity and PPI of PU foam. More importantly, compared with different filtration methods of molten crude magnesium, we can draw a conclusion that MFC can clean MgO inclusions and refining agent effectively based on the test results of electron dispersive spectroscopy (EDS) and density of crude magnesium before and after filtration.These results are attributed to the formation of filter sieve removing particles larger than or close to the pore size and to liquid inclusions held to the filter wall by surface forces, owing to specific surface area resulted by macropores and micropores formed in MFC in the presence of polyurethane foam and sintering binder MgF2 powders. [ABSTRACT FROM AUTHOR]

Since 2020, novel coronavirus pneumonia has been spreading rapidly around the world, bringing tremendous pressure on medical diagnosis and treatment for hospitals. Medical imaging methods, such as computed tomography (CT), play a crucial role in diagnosing and treating COVID-19. A large number of CT images (with large volume) are produced during the CT-based medical diagnosis. In such a situation, the diagnostic judgement by human eyes on the thousands of CT images is inefficient and time-consuming. Recently, in order to improve diagnostic efficiency, the machine learning technology is being widely used in computer-aided diagnosis and treatment systems (i.e., CT Imaging) to help doctors perform accurate analysis and provide them with effective diagnostic decision support. In this paper, we comprehensively review these frequently used machine learning methods applied in the CT Imaging Diagnosis for the COVID-19, discuss the machine learning-based applications from the various kinds of aspects including the image acquisition and pre-processing, image segmentation, quantitative analysis and diagnosis, and disease follow-up and prognosis. Moreover, we also discuss the limitations of the up-to-date machine learning technology in the context of CT imaging computer-aided diagnosis. [ABSTRACT FROM AUTHOR]

Benefiting from large-scale pretrained vision language models (VLMs), the performance of visual question answering (VQA) has approached human oracles. However, finetuning such models on limited data often suffers from overfitting and poor generalization issues, leading to a lack of model robustness. In this paper, we aim to improve input robustness from an information bottleneck perspective when adapting pretrained VLMs to the downstream VQA task. Input robustness refers to the ability of models to defend against visual and linguistic input variations, as well as shortcut learning involved in inputs. Generally, the representations obtained by pretrained VLMs inevitably contain irrelevant and redundant information for a specific downstream task, resulting in statistically spurious correlations and insensitivity to input variations. To encourage representations to converge to a minimal sufficient statistic in multimodal learning, we propose Correlation Information Bottleneck (CIB), which seeks a tradeoff between compression and redundancy in representations by minimizing the mutual information (MI) between inputs and representations while maximizing the MI between outputs and representations. Moreover, we derive a tight theoretical upper bound for the mutual information between multimodal inputs and representations, incorporating different internal correlations that guide models to learn more robust representations and facilitate modality alignment. Extensive experiments consistently demonstrate the effectiveness and superiority of the proposed CIB in terms of input robustness and accuracy. [ABSTRACT FROM AUTHOR]

Purpose: To describe the association of refraction development and axial length (AL) in young children and provide new insights into the progression of cylinder power. Methods: Children (2–3 grades) were enrolled from primary schools in Shanghai and followed up for two years. Cycloplegic refraction, AL, and corneal curvature radius were measured. Refraction parameters were compared among groups with different AL, AL1 (AL < 23.5 mm), AL2 (23.5 mm ≤ AL < 24.5 mm), and AL3 (AL ≥ 24.5 mm). Multiple regression analysis was used to explore risk factors of diopter of cylinder (DC) progression. Results: In total, out of 6891 enrolled children, 5961 participants (7–11 yrs) were included in the final analysis. Over the two-year period, the cylinder power significantly changed, and those with longer AL had more rapid DC progression over the two years (AL1, -0.09 ± 0.35 D; AL2, -0.15 ± 0.39 D; AL3, -0.29 ± 0.44 D) (P < 0.001). The change in DC was independently associated with AL at baseline (P < 0.001). The proportion of with-the-rule astigmatism increased from 91.3% to 92.1% in AL1 group, from 89.1% to 91.8% in AL2 group and from 87.1% to 92.0% in AL3 group. Conclusions: Young children with long AL experienced rapid progression of cylinder power. Both the control of myopia progression and attention to the correction of astigmatism are necessary in the health management of children with long AL. The significantly increased AL in participants might contribute to both the extent and direction of astigmatism. [ABSTRACT FROM AUTHOR]

A natural language interface (NLI) to databases is an interface that translates a natural language question to a structured query that is executable by database management systems (DBMS). However, an NLI that is trained in the general domain is hard to apply in the spatial domain due to the idiosyncrasy and expressiveness of the spatial semantics. Moreover, there are a wide range of database servers available, and a unilingual NLI model limits its practical usage. In this article, we propose to not only address the spatial domain generalization challenge, but also support multilingual back-end, i.e., supporting different query languages, such as SQL and Prolog. For the challenge of spatial semantics, we propose a spatial comprehension model that is able to recognize the meaning of spatial entities based on the semantics of context and effectively resolve the ambiguity given the spatial semantics. The spatial semantics learned from the spatial comprehension model is then injected to the natural language question to ease the burden of capturing the spatial-specific semantics. We also propose to add a prefix symbol to support the multilingual back-end (e.g., query languages). With our spatial comprehension model and symbol injections, our NLI for the spatial domain, named SpatialNLI, is able to capture the semantic structure of the question and translate it to the corresponding syntax of an executable query accurately. We also experimentally ascertain that SpatialNLI outperforms state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Subcortical brain regions play essential roles in the pathology of social anxiety disorder (SAD). While adolescence is the peak period of SAD, the relationships between altered development of the subcortical regions during this period and SAD are still unclear. This study investigated the age-dependent alterations in structural co-variance among subcortical regions and between subcortical and cortical regions, aiming to reflect aberrant coordination during development in the adolescent with SAD. High-resolution T1-weighted images were obtained from 76 adolescents with SAD and 67 healthy controls (HC), ranging from 11 to 17.9 years. Symptom severity was evaluated with the Social Anxiety Scale for Children (SASC) and the Depression Self Rating Scale for Children (DSRS-C). Structural co-variance and sliding age-window analyses were used to detect age-dependent group differences in inter-regional coordination patterns among subcortical regions and between subcortical and cortical regions. The volume of the striatum significantly correlated with SAD symptom severity. The SAD group exhibited significantly enhanced structural co-variance among key regions of the striatum (putamen and caudate). While the co-variance decreased with age in healthy adolescents, the co-variance in SAD adolescents stayed high, leading to more apparent group differences in middle adolescence. Moreover, the striatum's mean structural co-variance with cortical regions decreased with age in HC but increased with age in SAD. Adolescents with SAD suffer aberrant developmental coordination among the key regions of the striatum and between the striatum and cortical regions. The degree of incoordination is age-dependent, which may represent a neurodevelopmental trait of SAD. [ABSTRACT FROM AUTHOR]

Machine learning models have been widely used in landslide susceptibility prediction. However, landslide multidimensional feature extraction, model generalization ability, and prediction quantification of deep learning are still challenging. This paper proposes a new approach, the landslide density-based bidirectional long short-term memory (LD-BiLSTM) model with multichannel input and an optimized sampling strategy to predict and map landslide susceptibility in active seismic mountainous areas of Sichuan Province, China. First, to ensure the generalization ability of the LD-BiLSTM model, other regions in Sichuan were selected as the model training area independent of the prediction area (Luding County). Multichannel landslide datasets were constructed to extract high-dimensional geospatial features of landslides. Subsequently, the landslide density of each grid cell was utilized as the label for the corresponding input sample. The LD-BiLSTM model was improved by using transfer learning and sampling optimization strategies, which makes our method attenuate the impact of historical landslide inventory deviation on the spatial susceptibility mode compared with the existing DL model, which usually uses landslide objects (LO) as input sample labels. Model performance evaluation results show that the LD-BiLSTM model (precision = 0.903, recall = 0.899, F1-score = 0.901, Area under receiver operating characteristic curve (AUC) = 0.940) outperformed the LO-BiLSTM model (precision = 0.812, recall = 0.815. F1-score = 0.813, AUC = 0.910) in the case areas. Meanwhile, the performance of the LD-BiLSTM model (AUC = 0.9407) significantly outperformed both the information value (IV) (AUC = 0.7207) model and the random forest (RF) (AUC = 0.8116) models in the landslide prediction area (Luding), which confirms that the proposed LD-based method is superior to traditional LO-based methods. Significantly, our approach can effectively extract the spatial distribution of landslides and predict potential landslides in complex high-mountain environments. [ABSTRACT FROM AUTHOR]

Purpose: After the COVID-19 pandemic, many challenges arose regarding the impact of this disease on people with ulcerative colitis. The aims of this study were to estimate the prevalence, severity, and death consequences of COVID-19 in patients with ulcerative colitis using a systematic review and meta-analysis. Methods: This study was conducted using a systematic review and meta-analysis method in the field of prevalence, severity, and clinical consequences of COVID-19 in people with ulcerative colitis worldwide. The search was conducted in international scientific databases, such as Web of Science, PubMed, Scopus, Cochrane Library, and Google Scholar, from the beginning of 2020 to October 2023. The quality of the eligible studies was assessed using the Strobe and Newcastle Ottawa checklists. The data were analyzed using a fixed-effects model in the meta-analysis. Subgroup analysis and meta-regression were performed using STATA version 17. Results: Nineteen studies with a sample size of 224,520 patients were included in this meta-analysis. The results showed that, in COVID-19 patients with ulcerative colitis, the prevalence of hospitalization, death, COVID-19 severity, and mortality rate in severe patients was 54% (95% CI, 27–80%), 10% (95% CI, 4–16%), 20% (95% CI, 8–34%), 63% (95% CI, 46–80%), respectively. In comparison with the general population, the odds ratio (OR) of hospitalization in patients due to COVID-19 was OR = 1.28 (95% CI, 1.19–1.38, P < 0.001), and the chance of severe COVID-19 was OR = 1.30 (95% CI, 1.22–1.53, P < 0.001). Conclusion: The probability of contracting the severe type of COVID-19 and hospitalization in patients with ulcerative colitis was higher than in the general population. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM) is a complex disease to treat owing to its profound chemoresistance. Therefore, we evaluated the combined effect and therapeutic efficacy of temozolomide (TMZ), a potent alkylating agent and the current gold standard therapy for GBM, and cryptotanshinone (CTS), which inhibits glioma cell proliferation in GBM cells. Using LN229 and U87-MG human GBM cells in a short-term stimulation in vitro model, the cytotoxic and anti-proliferative effects of single and combined treatment with 4 μM CTS and 200 μM TMZ were investigated. Furthermore, cell viability, DNA damage, apoptosis rate, and signal transducer and activator of transcription 3 (STAT3) protein were measured using cytotoxic assay, comet assay, flow cytometry, and western blotting analysis, respectively. The two drugs' synergistic interaction was validated using the synergy score. We found that the anti-proliferative effects of combination therapy using the two drugs were greater than that of each agent used alone (CTS or TMZ). Western blot analysis indicated that treatment of GBM cells with CTS combined with TMZ more significantly decreased the expression of MGMT and STAT3, than that with TMZ alone. Combined treatment with CTS and TMZ might be an effective option to overcome the chemoresistance of GBM cells in a long-term treatment strategy. [ABSTRACT FROM AUTHOR]

A model of opinion dynamics in a social network that is a multiagent system with a finite number of agents is considered. There is a center influencing the agents' opinions by applying control, which is an influence level at every time. The center's costs are represented by a linear-quadratic function of a state variable (agents' opinions) and its controls. The center of influence aims to choose a finite number of opinion verification moments to compare the agents' opinions with the target one. A solution method for this dynamic problem on a finite time interval is proposed and implemented. In numerical simulation, we show how to find optimal opinion verification moments and the corresponding optimal state trajectories and controls. [ABSTRACT FROM AUTHOR]

Heart failure (HF) and permanent atrial fibrillation (AF) interact mutually, exacerbating hemodynamic effects and causing adverse outcomes and increased healthcare costs. Monitoring hemodynamic indicators in patients with these comorbidities is crucial for effective clinical management. Transthoracic impedance cardiography (ICG) has been widely employed in assessing hemodynamic status in clinical settings. Given the limited research on the prognostic significance of ICG parameters in HF with permanent AF, we undertook this study. A total of 66 HF patients with permanent AF were included in this retrospective study, and the primary outcome was rehospitalization due to worsening HF within 180-day post-discharge. Cox regression analysis was performed to explore the connection between ICG-evaluated parameters and the outcome risk. Receiver operating characteristic (ROC) curve analysis determined the optimal cutoff values of risk factors, subsequently applied in plotting Kaplan Meier (KM) survival curves. Multivariate Cox regression analysis revealed that systemic vascular resistance (SVR) both on admission and at discharge independently predicted rehospitalization for worsening HF. ROC analysis established optimal SVR cutoff values: 320.89 (kPa s/L) on admission and 169.94 (kPa s/L) at discharge (sensitivity 70%, specificity 94.4%, area under the curve (AUC) 0.831, respectively, sensitivity 90%, specificity 55.6%, AUC 0.742). KM survival curves analysis showed that patients with SVR > 320.89 (kPa s/L) on admission had an 8.14-fold (P < 0.001) increased risk of the end-point event compared with those with SVR ≤ 320.89 (kPa s/L). Similarly, patients with SVR > 169.94 (kPa s/L) at discharge faced a risk elevated by 6.57 times (P = 0.002) relative to those with SVR ≤ 169.94 (kPa s/L). In HF patients with permanent AF, SVR measured by ICG emerges as an independent risk factor and clinical predictor for HF deterioration-related readmission within 180 days after discharge. Higher SVR levels, both upon admission and at discharge, correlate with an incremental rehospitalization risk. [ABSTRACT FROM AUTHOR]

Aquifer connectivity could greatly affect groundwater flow and further control the contaminant transport in fractured medium. However, assessing connectivity of fractured aquifer at regional scales is still a challenge because such connectivity is difficult to be measured directly. This study proposes a framework for assessing connectivity of a fractured aquifer, with Qitaihe area, Heilongjiang Province, northeastern China as an illustrating study area. The 3-D finite difference numerical models were established to interpret the results of three multi-well pumping tests and inversely estimate the distribution of hydraulic conductivity (K) in the fractured aquifer. A static connectivity metric of the minimum hydraulic resistance (MHR) was calculated, based on the optimized K-field, to evaluate the hydraulic connectivity in the aquifer, and the corresponding least resistance paths (LRPs) were identified. The results indicate a better horizontal connectivity in the fractured aquifer in the northeastern and middle parts than in the southwestern part of the study area. The identified LRP indicated that the preferential flow channels at regional scales were controlled mainly by aquifer connectivity instead of local high-K zones. The results of this study can provide a method for aquifer connectivity estimation at regional scales. [ABSTRACT FROM AUTHOR]

Adulteration of meat and meat products causes a concerning threat for consumers. It is necessary to develop novel robust and sensitive methods which can authenticate the origin of meat species to compensate for the drawbacks of existing methods. In the present study, the sarcoplasmic proteins of six meat species, namely, pork, beef, mutton, chicken, duck and turkey, were analyzed by one-dimensional gel electrophoresis. It was found that enolase could be used as a potential biomarker protein to distinguish between livestock and poultry meats. The glycosylation sites and glycans of enolase were analyzed by UPLC-QTOF-MS and a total of 41 glycopeptides were identified, indicating that the enolase N-glycopeptide profiles of different meats were species-specific. The identification models of livestock meat, poultry and mixed animal were established based on the glycopeptide contents, and the explanation degree of the three models was higher than 90%. The model prediction performance and feasibility results showed that the average prediction accuracy of the three models was 75.43%, with the animal-derived meat identification model showing superiority in identifying more closely related species. The obtained results indicated that the developed strategy was promising for application in animal-derived meat species monitoring and the quality supervision of animal-derived food. [ABSTRACT FROM AUTHOR]

Ischemic stroke (IS) is the most common type of stroke and is characterized by high rates of mortality and long-term injury. The prediction and early diagnosis of IS are therefore crucial for optimal clinical intervention. Proteomics has provided important techniques for exploring protein markers associated with IS, but there has been no systematic evaluation and review of research that has used these techniques. Here, we review the differential proteins that have been found in cell- and animal- based studies and clinical trials of IS in the past 10 years; determine the key pathological proteins that have been identified in clinical trials; summarize the target proteins affected by interventions aimed at treating IS, with a focus on traditional Chinese medicine treatments. Overall, we clarify findings and problems that have been identified in recent proteomics research on IS and provide suggestions for improvements in this area. We also suggest areas that could be explored for determining the pathogenesis and developing interventions for IS. [ABSTRACT FROM AUTHOR]

Introduction: A multicenter prospective randomized controlled study was used to investigate the effect and safety of a new corneal wetting agent called the Corneal Surface Viscoelastic Protector (CsVisc, Success Bio-Tech Co., Ltd, China), on the corneal epithelium during ophthalmic surgery by comparison with the commercially available Cornea Protect (CP, Valeant Med Sp. zo. o. Leobendorf, Austria). Methods: This multicenter prospective randomized controlled study comprised patients scheduled for cataract surgery and pars plana vitrectomy. The patients were randomly assigned to receive either a new corneal wetting agent (CsVisc) or Cornea Protect (CP, Valeant Med Sp. zo. o. Leobendorf, Austria). Optical clarity during surgery, application frequency, duration of effect, diffusion time of corneal wetting agents, fluorescein staining, intraocular pressure (IOP), tear-film break-up time (TBUT), and Schirmer I test (SIT) were assessed. Adverse events were noted on the designated patient case report forms. Results: A total of 149 eyes (149 patients, mean age 62 years; range 25–80 years) were included in the study. There were 74 eyes in the control group and 75 eyes in the study group. In patients who underwent vitrectomy, the frequency of application was 1.62 ± 1.03 in the study group and 1.39 ± 0.66 in the control group, with no significant difference (P = 0.399), and the duration of effect was 19.16 ± 6.94 min in the study group and 19.06 ± 7.22 min in the control group, with no significant difference (P = 0.835). The optical clarity of the study group was not significantly different from that of the control group (P = 0.485). In patients who underwent cataract surgery, the frequency of application was 1.10 ± 0.38 in the study group and 1.07 ± 0.26 in the control group, and the difference was not significant (P = 0.950). The difference between the duration of effect in the study group (8.32 ± 2.50 min) and the control group (7.63 ± 2.52 min) was not significant (P = 0.310). The difference in optical clarity scores between the two groups was not statistically significant (P = 0.600). Among all patients in this study, the diffusion time of the corneal wetting agent was 14.97 ± 10.07 s in the control group and 11.23 ± 8.41 s in the study group, with a statistically significant difference (p = 0.008). The frequency of adverse events was 20.00% (15/75) in the study group and 14.86% (11/74) in the control group, with no statistically significant difference (P = 0.409). There were no serious adverse events related to the test medical device or causing patients to withdraw from the study. Conclusions: The CsVisc is safe and effective in preventing intraoperative corneal epithelial damage due to corneal dryness and can be comparable to the CP. In addition, the CsVisc has a shorter diffusion time. [ABSTRACT FROM AUTHOR]