High pressure-sensitive and stable fiber Fabry-Perot interferometer with nano-diaphragm assembled by H-O catalysis bonding.

Herein, a high pressure-sensitive and stable fiber Fabry-Perot (FP) interferometer with nano-diaphragm assembled by H-O catalysis bonding is proposed and demonstrated. In order to assemble a nano-diaphragm-based fiber FP interferometer by H-O catalysis bonding technique, a SiO2 film, introduced as a bridging layer on the nano-diaphragm, can be regarded as a solid adhesive to bridge hollow-core fiber end-face and nano-diaphragm. As thus, by depositing bonded layers on different diaphragm materials, this H-O catalysis bonding technology can be used to for assembling FP interferometer with different materials nano-diaphragms. Experimentally, Si nano-diaphragm is transferred to hollow-core fiber end-face to build a stable fiber FP interferometer without polymeric adhesive. Experimental results reveal that this Si nano-diaphragm-based fiber FP interferometer has a high (79.6 pm/kPa) pressure sensitivity and a low (17.3 pm/°C) temperature sensitivity. Besides that, different materials nano-diaphragm also can be assembled by using this H-O catalysis bonding technique, and the functional FP interferometer can be realized by using functional nano-diaphragm material. Thus, a Pd nano-diaphragm is successfully assembled to build a FP interferometer with a hydrogen concentration measurement capacity. Further investigation will focus on exploitation of multi-material nano-film patterning transfer and different nano-film integration by using this H-O catalysis bonding transfer.

Study on the solid-liquid equilibrium and thermodynamic model of the L-phenylalanine + L-tryptophan + water system.

Amino acids hold significant importance in the diagnosis and treatment of various chronic diseases. Accurate solid-liquid equilibrium data are the key to drug synthesis and chemical production. However, the studies on the solid-liquid equilibrium of amino acids remain limited. In this work, the solid-liquid equilibrium of the L-tryptophan + L-phenylalanine + water ternary system under atmospheric pressure at temperatures of 278.15 K-318.15 K was explored via isothermal solution saturation. The isothermal equilibrium phase diagram of the ternary system was constructed. The obtained solid-liquid equilibrium data were correlated with a semi-empirical-model, yielding thermodynamic parameters pa, pb, pc, and k. Furthermore, the model can be used to effectively predict the solid-liquid equilibrium data of ternary systems at other temperatures, and the dY and dP are 0.005 and 4.34%, respectively. The solid-liquid equilibrium data and ternary equilibrium phase diagrams of the system were utilized for the separation and purification of an L-tryptophan and L-phenylalanine mixture. By employing thermodynamic models to calculate the relevant phase diagram data for mixtures with different proportions, effective separation and purification of the mixture could be achieved using the principles of variable temperature phase diagrams. These works are valuable for optimizing chemical processes and have practical implications in the field.

Identifying Minimal Hepatic Encephalopathy: A New Perspective from Magnetic Resonance Imaging.

Type C hepatic encephalopathy (HE) is a condition characterized by brain dysfunction caused by liver insufficiency and/or portal-systemic blood shunting, which manifests as a broad spectrum of neurological or psychiatric abnormalities, ranging from minimal HE (MHE), detectable only by neuropsychological or neurophysiological assessment, to coma. Though MHE is the subclinical phase of HE, it is highly prevalent in cirrhotic patients and strongly associated with poor quality of life, high risk of overt HE, and mortality. It is, therefore, critical to identify MHE at the earliest and timely intervene, thereby minimizing the subsequent complications and costs. However, proper and sensitive diagnosis of MHE is hampered by its unnoticeable symptoms and the absence of standard diagnostic criteria. A variety of neuropsychological or neurophysiological tests have been performed to diagnose MHE. However, these tests are nonspecific and susceptible to multiple factors (eg, aging, education), thereby limiting their application in clinical practice. Thus, developing an objective, effective, and noninvasive method is imperative to help detect MHE. Magnetic resonance imaging (MRI), a noninvasive technique which can produce many objective biomarkers by different imaging sequences (eg, Magnetic resonance spectroscopy, DWI, rs-MRI, and arterial spin labeling), has recently shown the ability to screen MHE from NHE (non-HE) patients accurately. As advanced MRI techniques continue to emerge, more minor changes in the brain could be captured, providing new means for early diagnosis and quantitative assessment of MHE. In addition, the advancement of artificial intelligence in medical imaging also presents the potential to mine more effective diagnostic biomarkers and further improves the predictive efficiency of MHE. Taken together, advanced MRI techniques may provide a new perspective for us to identify MHE in the future. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

The Effect of Warm Acupuncture on EOS, IgE, Inflammatory Factors, and T Lymphocyte Subsets in Patients with Allergic Rhinitis of Lung Qi Deficiency and Cold-Type.

Objective: The purpose of this study was to investigate the effects of warming needle therapy on eosinophils, specific immunoglobulin E (IgE), inflammatory factors, and T lymphocyte subsets in patients with lung qi deficiency and cold-type allergic rhinitis (AR). Methods: A total of 155 patients with lung qi deficiency and cold-type AR from May 2021 to December 2022 were randomly divided into a study group of 76 cases and a control group of 79 cases. The control group received medication (chlorpheniramine and fluticasone), and the study group received medication combined with warming needle therapy. The efficacy, TCM syndrome score, eosinophils, IgE, inflammatory factors (interleukin-6 (IL-6), IL-8, and tumor necrosis factor-alpha (TNF-α)), T lymphocyte subsets (CD3+, CD4+, and CD8+), and rhinoconjunctivitis quality of life questionnaire (RQLQ) scores were evaluated after 2 weeks of treatment. Results: The total effective rate in the study group was 92.11%, which was higher than that in the control group (77.22%) (P < .05). The TCM syndrome scores of the study group were lower than those of the control group after 1 and 2 weeks of treatment (P < .05). The positive rate of eosinophils in the study group was lower than that in the control group after 1 week (47.37% vs. 64.56%, P < .05) and after 2 weeks (21.05% vs. 37.97%, P < .05) of treatment. The serum levels of specific IgE, IL-6, IL-8, and TNF-α in the study group were lower than those in the control group after 1 and 2 weeks of treatment (P < .05). The peripheral blood levels of CD3+ and CD4+ were higher and the peripheral blood level of CD8+ was lower in the study group than in the control group after 1 and 2 weeks of treatment (P < .05). The RQLQ scores of the study group were lower than those of the control group after 1 and 2 weeks of treatment (P < .05). Conclusion: Warming needle therapy can effectively improve the clinical symptoms of patients with lung qi deficiency and cold-type AR, reduce inflammation, and enhance immune function.

Computed Tomography-derived intratumoral and peritumoral radiomics in predicting EGFR mutation in lung adenocarcinoma.

OBJECTIVE: To investigate the value of Computed Tomography (CT) radiomics derived from different peritumoral volumes of interest (VOIs) in predicting epidermal growth factor receptor (EGFR) mutation status in lung adenocarcinoma patients. MATERIALS AND METHODS: A retrospective cohort of 779 patients who had pathologically confirmed lung adenocarcinoma were enrolled. 640 patients were randomly divided into a training set, a validation set, and an internal testing set (3:1:1), and the remaining 139 patients were defined as an external testing set. The intratumoral VOI (VOI_I) was manually delineated on the thin-slice CT images, and seven peritumoral VOIs (VOI_P) were automatically generated with 1, 2, 3, 4, 5, 10, and 15 mm expansion along the VOI_I. 1454 radiomic features were extracted from each VOI. The t-test, the least absolute shrinkage and selection operator (LASSO), and the minimum redundancy maximum relevance (mRMR) algorithm were used for feature selection, followed by the construction of radiomics models (VOI_I model, VOI_P model and combined model). The performance of the models were evaluated by the area under the curve (AUC). RESULTS: 399 patients were classified as EGFR mutant (EGFR+), while 380 were wild-type (EGFR-). In the training and validation sets, internal and external testing sets, VOI4 (intratumoral and peritumoral 4 mm) model achieved the best predictive performance, with AUCs of 0.877, 0.727, and 0.701, respectively, outperforming the VOI_I model (AUCs of 0.728, 0.698, and 0.653, respectively). CONCLUSIONS: Radiomics extracted from peritumoral region can add extra value in predicting EGFR mutation status of lung adenocarcinoma patients, with the optimal peritumoral range of 4 mm.

Recent Advances on F-Doped Layered Transition Metal Oxides for Sodium Ion Batteries.

With the development of social economy, using lithium-ion batteries in energy storage in industries such as large-scale electrochemical energy storage systems will cause lithium resources to no longer meet demand. As such, sodium ion batteries have become one of the effective alternatives to LIBs. Many attempts have been carried out by researchers to achieve this, among which F-doping is widely used to enhance the electrochemical performance of SIBs. In this paper, we reviewed several types of transition metal oxide cathode materials, and found their electrochemical properties were significantly improved by F-doping. Moreover, the modification mechanism of F-doping has also been summed up. Therefore, the application and commercialization of SIBs in the future is summarized in the ending of the review.

Analyzing the Robustness of Complex Networks with Attack Success Rate.

Analyzing the robustness of networks against random failures or malicious attacks is a critical research issue in network science, as it contributes to enhancing the robustness of beneficial networks and effectively dismantling harmful ones. Most studies commonly neglect the impact of the attack success rate (ASR) and assume that attacks on the network will always be successful. However, in real-world scenarios, attacks may not always succeed. This paper proposes a novel robustness measure called Robustness-ASR (RASR), which utilizes mathematical expectations to assess network robustness when considering the ASR of each node. To efficiently compute the RASR for large-scale networks, a parallel algorithm named PRQMC is presented, which leverages randomized quasi-Monte Carlo integration to approximate the RASR with a faster convergence rate. Additionally, a new attack strategy named HBnnsAGP is introduced to better assess the lower bound of network RASR. Finally, the experimental results on six representative real-world complex networks demonstrate the effectiveness of the proposed methods compared with the state-of-the-art baselines.

Rasmussen's encephalitis is characterized by relatively lower production of IFN-ß and activated cytotoxic T cell upon herpes viruses infection.

BACKGROUND: The etiology of Rasmussen's encephalitis (RE), a rare chronic neurological disorder characterized by CD8+ T cell infiltration and unihemispheric brain atrophy, is still unknown. Various human herpes viruses (HHVs) have been detected in RE brain, but their contribution to RE pathogenesis is unclear. METHODS: HHVs infection and relevant immune response were compared among brain tissues from RE, temporal lobe epilepsy (TLE) and traumatic brain injury (TBI) patients. Viral antigen or genome, CD8+ T cells, microglia and innate immunity molecules were analyzed by immunohistochemical staining, DNA dot blot assay or immunofluorescence double staining. Cytokines were measured by multiplex flow cytometry. Cell apoptosis was visualized by TUNEL staining. Viral infection, immune response and the severity of unihemispheric atrophy were subjected to correlation analysis. RESULTS: Antigens of various HHVs were prevalent in RE and TLE brains, and the cumulative viral score of HHVs positively correlated with the unihemispheric atrophy in RE patients. CD8+ T cells infiltration were observed in both RE and TLE brains and showed co-localization with HHV antigens, but their activation, as revealed by Granzyme B (GZMB) release and apoptosis, was found only in RE. In comparison to TLE, RE brain tissues contained higher level of inflammatory cytokines, but the interferon-ß level, which was negatively correlated with cumulative viral score, was relatively lower. In line with this, the DNA sensor STING and IFI16, rather than other innate immunity signaling molecules, were insufficiently activated in RE. CONCLUSIONS: Compared with TBI, both RE and TLE had prevalently HHV infection and immune response in brain tissues. However, in comparison to TLE, RE showed insufficient activation of antiviral innate immunity but overactivation of cytotoxic T cells. Our results show the relatively lower level of antiviral innate immunity and overactivation of cytotoxic T cells in RE cases upon HHV infection, the overactivated T cells might be a compensate to the innate immunity but the causative evidence is lack in our study and need more investigation in the future.

A comparative analysis of ESM-1 and vascular endothelial cell marker (CD34/CD105) expression on pituitary adenoma invasion.

OBJECTIVE: Pituitary adenomas are benign neoplasms that display invasive behavior-a characteristic traditionally associated with malignancy-through an ill-defined mechanism. The role of angiogenesis-related molecules in this pathological condition remains perplexing. Our purpose is to assess the impact of endocan (endothelial cell specific molecule-1, ESM-1), CD34 and CD105 on pituitary adenoma invasion. METHODS: In this study, immunohistochemical analyses for endocan, CD34 and CD105 were performed on paraffin-embedded samples of 66 pituitary adenomas, five normal pituitaries, and five primary hepatic carcinomas. Knosp tumor grades based on magnetic resonance imaging coronal scanning were used to assess the invasiveness of each sample. The associations between endocan expression, CD34/CD105-positive microvessel densities (MVDs), and Knosp tumor invasion grades were evaluated. RESULTS: These results showed that endocan protein expression in tumor cells (TCs) was higher than that in endothelial cells (ECs) and strongly correlated with Knosp grades (P < 0.001, Spearman's r = 0.616). Moreover, while endocan-positive TCs localized around the blood vessels in adenomas with higher Knosp grades, no significant association was found between CD34/CD105-MVDs and Knosp grades (CD34: P = 0.256, r = 0.142; CD105: P = 0.183, r = 0.166). Normal pituitary seemed to exhibit lower endocan expression and contained more CD34/CD105-MVDs than pituitary adenomas. CONCLUSION: Endocan expresses in both TCs and ECs of pituitary adenoma. Endocan overexpression in TCs more accurately reflects invasiveness compared to that of CD34/CD105-MVDs and that angiogenesis may not be the primary driver of endocan-medicated pituitary adenoma invasion.

Sunitinib in patients with chemotherapy-refractory thymoma and thymic carcinoma: an open-label phase 2 trial.

BACKGROUND: No standard treatments are available for advanced thymic epithelial tumours after failure of platinum-based chemotherapy. We investigated the activity of sunitinib, an orally administered tyrosine kinase inhibitor. METHODS: Between May 15, 2012, and Oct 2, 2013, we did an open-label phase 2 trial in patients with histologically confirmed chemotherapy-refractory thymic epithelial tumours. Patients were eligible if they had disease progression after at least one previous regimen of platinum-containing chemotherapy, an Eastern Cooperative Oncology Group performance status of two or lower, measurable disease, and adequate organ function. Patients received 50 mg of sunitinib orally once a day, in 6-week cycles (ie, 4 weeks of treatment followed by 2 weeks without treatment), until tumour progression or unacceptable toxic effects arose. The primary endpoint was investigator-assessed best tumour response at any point, which we analysed separately in thymoma and thymic carcinoma cohorts. Patients who had received at least one cycle of treatment and had their disease reassessed were included in the analyses of response. The trial was registered with ClinicalTrials.gov, number NCT01621568. FINDINGS: 41 patients were enrolled, 25 with thymic carcinoma and 16 with thymoma. One patient with thymic carcinoma was deemed ineligible after enrolment and did not receive protocol treatment. Of patients who received treatment, one individual with thymic carcinoma was not assessable because she died. Median follow-up on trial was 17 months (IQR 14.0-18.4). Of 23 assessable patients with thymic carcinoma, six (26%, 90% CI 12.1-45.3, 95% CI 10.2-48.4) had partial responses, 15 (65%, 95% CI 42.7-83.6) achieved stable disease, and two (9%, 1.1-28.0) had progressive disease. Of 16 patients with thymoma, one (6%, 95% CI 0.2-30.2) had a partial response, 12 (75%, 47.6-92.7) had stable disease, and three (19%, 4.1-45.7) had progressive disease. The most common grade 3 and 4 treatment-related adverse events were lymphocytopenia (eight [20%] of 40 patients), fatigue (eight [20%]), and oral mucositis (eight [20%]). Five (13%) patients had decreases in left-ventricular ejection fraction, of which three (8%) were grade 3 events. Three (8%) patients died during treatment, including one individual who died of cardiac arrest that was possibly treatment-related. INTERPRETATION: Sunitinib is active in previously treated patients with thymic carcinoma. Further studies are needed to identify potential biomarkers of activity. FUNDING: National Cancer Institute (Cancer Therapy Evaluation Program).

Enhanced matrix inference with Seq2seq models via diagonal sorting.

The effectiveness of sequence-to-sequence (seq2seq) models in natural language processing has been well-established over time, and recent studies have extended their utility by treating mathematical computing tasks as instances of machine translation and achieving remarkable results. However, our exploratory experiments have revealed that the seq2seq model, when employing a generic sorting strategy, is incapable of inferring on matrices of unseen rank, resulting in suboptimal performance. This paper aims to address this limitation by focusing on the matrix-to-sequence process and proposing a novel diagonal-based sorting. The method constructs a stable ordering structure of elements for the shared leading principal submatrix sections in matrices with varying ranks. We conduct experiments involving maximal independent sets and Sudoku laws, comparing seq2seq models utilizing different sorting methods. Our findings demonstrate the advantages of the proposed diagonal-based sorting in inference, particularly when dealing with matrices of unseen ranks. By introducing and advocating for this method, we enhance the suitability of seq2seq models for investigating the laws of matrix inclusion and exploring their potential in solving matrix-related tasks.

Layered double hydroxide-based electrode materials derived from metal-organic frameworks: synthesis and applications in supercapacitors.

Metal-organic frameworks (MOFs) have emerged as promising electrode materials for supercapacitors (SCs) due to their highly porous structures, tunable chemical compositions, and diverse morphologies. However, their applications are hindered by low conductivity and poor cycling performance. A novel approach for resolving this issue involves the growth of layered double hydroxides (LDHs) using MOFs as efficient templates or precursors for electrode material preparation. This method effectively enhances the stability, electrical conductivity, and mass transport ability of MOFs. The MOF-derived LDH exhibits a well-defined porous micro-/nano-structure, facilitating the dispersion of active sites and preventing the aggregation of LDHs. Firstly, this paper introduces synthesis strategies for converting MOFs into LDHs. Subsequently, recent research progress in MOF-derived LDHs encompassing pristine LDH powders, LDH composites, and LDH-based arrays, along with their applications in SCs, is overviewed. Finally, the challenges associated with MOF-derived LDH electrode materials and potential solutions are discussed.

Preparation of catalyst for CO2 hydrogenation reaction based on the idea of element sharing and preliminary exploration of catalytic mechanism.

Under the background of the continuous rise of CO2 annual emissions, the development of CO2 capture and utilization technology is urgent. This study focuses on improving the catalytic capacity of the catalyst for CO2 hydrogenation, improving the efficiency of CO2 conversion to methanol, and converting H2 into chemical substances to avoid the danger of H2 storage. Based on the concept of element sharing, the ASMZ (Aluminum Shares Metal Zeolite catalysts) series catalyst was prepared by combining the CuO-ZnO-Al2O3 catalyst with the ZSM-5 zeolite using the amphoteric metal properties of the Al element. The basic structural properties of ASMZ catalysts were compared by XRD, FTIR, and BET characterization. Catalytic properties of samples were measured on a micro fixed-bed reactor. The catalytic mechanism of the catalyst was further analyzed by SEM, TEM, XPS, H2-TPR, and NH3-TPD. The results show that the ASMZ3 catalyst had the highest CO2 conversion rate (26.4%), the highest methanol selectivity (76.0%), and the lowest CO selectivity (15.3%) in this study. This is mainly due to the fact that the preparation method in this study promotes the exposure of effective weakly acidic sites and medium strength acidic sites (facilitating the hydrogenation of CO2 to methanol). At the same time, the close binding of Cu-ZnO-Al2O3 (CZA) and ZSM-5 zeolite also ensures the timely transfer of catalytic products and ensures the timely play of various catalytic active centers. The preparation method of the catalyst in this study also provides ideas for the preparation of other catalysts.

Luminescent fiber UV detection.

Herein, a luminescent fiber device for detecting ultraviolet (UV) intensity, which comprises a UV probe and a photoelectric converter, is proposed. The UV probe consists of a glass tube filled with luminescent material, which can be used for the efficient radiation conversion of UV radiation to the visible spectral region. The luminescent material, Y2O2S:Eu3+, is mixed with polydimethylsiloxane (PDMS) to form the core of the UV probe. Subsequently, the UV radiation response of the luminescent fiber device is investigated; the experimental results demonstrate that the direction-independent UV detection can be realized by using this luminescent fiber UV detection device while UV light is radiated radially along the UV probe. In addition, since partial discharge (PD) is accompanied by UV radiation, we hope to develop a spectral PD detection scheme based on optical fiber technology, which can broaden the role of optical technology and optical fiber technology in the field of PD detection.

Microstructure and Mechanical Properties of Refill Friction Stir Spot-Welded Joints of 2A12Al and 7B04Al: Effects of Tool Size and Welding Parameters.

To solve problems in dissimilarly light metal joints, refilled friction stir spot welding (RFSSW) is proposed instead of resistance spot welding. However, rotation speed, dwell time, plunge depth, and the diameter of welding tools all have a great influence on joints, which brings great challenges in optimizing welding parameters to ensure their mechanical properties. In this study, the 1.5 mm thick 2A12Al and 2 mm thick 7B04Al lap joints were prepared by Taguchi orthogonal experiment design and RFSSW. The welding tool (shoulder) diameters were 5 mm and 7 mm, respectively. The macro/microstructures of the cross-section, the geometrical characteristics of the effective welding depth (EWD), the stir zone area (SZA), and the stir zone volume (SZV) were characterized. The shear strength and failure mode of the lap joint were analyzed using an optical microscope. It was found that EWD, SZA, and SZV had a good correlation with tensile-shear force. The optimal welding parameters of 5 mm diameter joints are 1500 rpm of rotation speed, 2.5 mm of plunge depth, and 0 s of dwell time, which for 7 mm joints are 1200 rpm, 1.5 mm, and 2 s. The tensile-shear force of 5 mm and 7 mm joints welded with these optical parameters was 4965 N and 5920 N, respectively. At the same time, the 5 mm diameter joints had better strength and strength stability.

Mice with type I interferon signaling deficiency are prone to epilepsy upon HSV-1 infection.

Viral encephalitis continues to be a significant public health concern. In our previous study, we discovered a lower expression of antiviral factors, such as IFN-ß, STING and IFI16, in the brain tissues of patients with Rasmussen's encephalitis (RE), a rare chronic neurological disorder often occurred in children, characterized by unihemispheric brain atrophy. Furthermore, a higher cumulative viral score of human herpes viruses (HHVs) was also found to have a significant positive correlation with the unihemispheric atrophy in RE. Type I IFNs (IFN-I) signaling is essential for innate anti-infection response by binding to IFN-α/ß receptor (IFNAR). In this study, we infected WT mice and IFNAR-deficient A6 mice with herpes simplex virus 1 (HSV-1) via periocular injection to investigate the relationship between IFN-I signaling and HHVs-induced brain lesions. While all mice exhibited typical viral encephalitis lesions in their brains, HSV-induced epilepsy was only observed in A6 mice. The gene expression matrix, functional enrichment analysis and protein-protein interaction network revealed four gene models that were positively related with HSV-induced epilepsy. Additionally, ten key genes with the highest scores were identified. Taken together, these findings indicate that intact IFN-I signaling can effectively limit HHVs induced neural symptoms and brain lesions, thereby confirming the positive correlation between IFN-I signaling repression and brain atrophy in RE and other HHVs encephalitis.

Array comparative genomic hybridization-based characterization of genetic alterations in pulmonary neuroendocrine tumors.

The goal of this study was to characterize and classify pulmonary neuroendocrine tumors based on array comparative genomic hybridization (aCGH). Using aCGH, we performed karyotype analysis of 33 small cell lung cancer (SCLC) tumors, 13 SCLC cell lines, 19 bronchial carcinoids, and 9 gastrointestinal carcinoids. In contrast to the relatively conserved karyotypes of carcinoid tumors, the karyotypes of SCLC tumors and cell lines were highly aberrant. High copy number (CN) gains were detected in SCLC tumors and cell lines in cytogenetic bands encoding JAK2, FGFR1, and MYC family members. In some of those samples, the CN of these genes exceeded 100, suggesting that they could represent driver alterations and potential drug targets in subgroups of SCLC patients. In SCLC tumors, as well as bronchial carcinoids and carcinoids of gastrointestinal origin, recurrent CN alterations were observed in 203 genes, including the RB1 gene and 59 microRNAs of which 51 locate in the DLK1-DIO3 domain. These findings suggest the existence of partially shared CN alterations in these tumor types. In contrast, CN alterations of the TP53 gene and the MYC family members were predominantly observed in SCLC. Furthermore, we demonstrated that the aCGH profile of SCLC cell lines highly resembles that of clinical SCLC specimens. Finally, by analyzing potential drug targets, we provide a genomics-based rationale for targeting the AKT-mTOR and apoptosis pathways in SCLC.

Deep Learning-Based Modified YOLACT Algorithm on Magnetic Resonance Imaging Images for Screening Common and Difficult Samples of Breast Cancer.

Computer-aided methods have been extensively applied for diagnosing breast lesions with magnetic resonance imaging (MRI), but fully-automatic diagnosis using deep learning is rarely documented. Deep-learning-technology-based artificial intelligence (AI) was used in this work to classify and diagnose breast cancer based on MRI images. Breast cancer MRI images from the Rider Breast MRI public dataset were converted into processable joint photographic expert group (JPG) format images. The location and shape of the lesion area were labeled using the Labelme software. A difficult-sample mining mechanism was introduced to improve the performance of the YOLACT algorithm model as a modified YOLACT algorithm model. Diagnostic efficacy was compared with the Mask R-CNN algorithm model. The deep learning framework was based on PyTorch version 1.0. Four thousand and four hundred labeled data with corresponding lesions were labeled as normal samples, and 1600 images with blurred lesion areas as difficult samples. The modified YOLACT algorithm model achieved higher accuracy and better classification performance than the YOLACT model. The detection accuracy of the modified YOLACT algorithm model with the difficult-sample-mining mechanism is improved by nearly 3% for common and difficult sample images. Compared with Mask R-CNN, it is still faster in running speed, and the difference in recognition accuracy is not obvious. The modified YOLACT algorithm had a classification accuracy of 98.5% for the common sample test set and 93.6% for difficult samples. We constructed a modified YOLACT algorithm model, which is superior to the YOLACT algorithm model in diagnosis and classification accuracy.

Causal Associations between Functional/Structural Connectivity and Stroke: A Bidirectional Mendelian Randomization Study.

Disruption of brain resting-state networks (RSNs) is known to be related to stroke exposure, but determining causality can be difficult in epidemiological studies. We used data on genetic variants associated with the levels of functional (FC) and structural connectivity (SC) within 7 RSNs identified from a genome-wide association study (GWAS) meta-analysis among 24,336 European ancestries. The data for stroke and its subtypes were obtained from the MEGASTROKE consortium, including up to 520,000 participants. We conducted a two-sample bidirectional Mendelian randomization (MR) study to investigate the causality relationship between FC and SC within 7 RSNs and stroke and its subtypes. The results showed that lower global mean FC and limbic network FC were associated with a higher risk of any ischemic stroke and small vessel stroke separately. Moreover, ventral attention network FC and default mode network SC have a positive causal relationship with the risk of small vessel stroke and large artery stroke, respectively. In the inverse MR analysis, any stroke and large artery stroke were causally related to dorsal attention network FC and somatomotor FC, respectively. The present study provides genetic support that levels of FC or SC within different RSNs have contrasting causal effects on stroke and its subtypes. Moreover, there is a combination of injury and compensatory physiological processes in brain RSNs following a stroke. Further studies are necessary to validate our results and explain the physiological mechanisms.

Optimization of preparation of NaA zeolite from fly ash for CO2 capture.

The green synthesis method of fly ash-based NaA zeolite was explored to reduce the synthesis cost and environmental hazards. For the prepared NaA samples, the effects of crystallization time, solid-liquid ratio, and Si/Al ratio were systematically studied. CO2 adsorption isotherm is used for adsorption model fitting analysis and adsorption selectivity determination. According to the experimental results, the optimized NaA zeolite synthesis conditions are as follows: the Si/Al ratio of NaA zeolite is 1.4, the solid-liquid ratio is 10, and the crystallization time is 6 h. The green synthesis method reported in this study can successfully prepare NaA zeolite and exhibit excellent CO2 adsorption performance, reaching 4.34 mmol/g, with high CO2 selective adsorption ability, reaching 89.2 for N2, 257.1 for O2, and 45.8 for CH4. The adsorbed CO2 can be released for further utilization, and NaA zeolite also has strong adsorption and regeneration performance, with a ten cycle adsorption capacity only decreasing by 1.17%. In addition, the use of cheap raw materials synthesis methods will promote the large-scale industry application of green synthesis technology in the future.