Efficient Transformation of Water Vapor into Hydrogen by Dielectric Barrier Discharge Loaded with Bamboo Carbon Bed Structured by Fibrous Material.

A new method of efficiently transforming water vapor into hydrogen was investigated by dielectric barrier discharge (DBD) loaded with bamboo carbon bed structured by fibrous material in an argon medium. Hydrogen productivity was measured in three different reactors: a non-loaded DBD (N-DBD), a bamboo carbon (BC) bed DBD (BC-DBD), and a quartz wool (QW)-loaded BC DBD (QC-DBD). The effects of the quality ratio of BC to QW and relative humidity on hydrogen productivity were also investigated in QC-DBD at various flow rates. The reaction process and mechanism were analyzed by scanning electron microscopy, X-ray photoelectron spectroscopy, N2 physisorption experiments, infrared spectroscopy, and optical emission spectroscopy. A new reaction pathway was developed by loading BC into the fibrous structured material to activate the reaction molecules and capture the O-containing groups in the DBD reactor. A hydrogen productivity of 17.3 g/kWh was achieved at an applied voltage of 5 kV, flow rate of 4 L/min, and 100% relative humidity (RH) in the QC-DBD with a quality ratio of BC to QW of 3.0.

Carbon superstructure-supported half-metallic V2O3 nanospheres for high-efficiency photorechargeable zinc ion batteries.

Photorechargeable zinc ion batteries (PZIBs), which can directly harvest and store solar energy, are promising technologies for the development of a renewable energy society. However, the incompatibility requirement between narrow band gap and wide coverage has raised severe challenges for high-efficiency dual-functional photocathodes. Herein, half-metallic vanadium (III) oxide (V2O3) was first reported as a dual-functional photocathode for PZIBs. Theoretical and experimental results revealed its unique photoelectrical and zinc ion storage properties for capturing and storing solar energy. To this end, a synergistic protective etching strategy was developed to construct carbon superstructure-supported V2O3 nanospheres (V2O3@CSs). The half-metallic characteristics of V2O3, combined with the three-dimensional superstructure assembled by ultrathin carbon nanosheets, established rapid charge transfer networks and robust framework for efficient and stable solar-energy storage. Consequently, the V2O3@CSs photocathode delivered record zinc ion storage properties, including a photo-assisted discharge capacities of 463 mAh∙g-1 at 2.0 A∙g-1 and long-term cycling stability over 3000 cycles. Notably, the PZIBs assembled using V2O3@CSs photocathodes could be photorecharged without an external circuit, exhibiting a high photo conversion efficiency (0.354%) and photorecharge voltage (1.0 V). This study offered a promising direction for the direct capture and storage of solar energy.

Artificial intelligence enables precision diagnosis of cervical cytology grades and cervical cancer.

Cervical cancer is a significant global health issue, its prevalence and prognosis highlighting the importance of early screening for effective prevention. This research aimed to create and validate an artificial intelligence cervical cancer screening (AICCS) system for grading cervical cytology. The AICCS system was trained and validated using various datasets, including retrospective, prospective, and randomized observational trial data, involving a total of 16,056 participants. It utilized two artificial intelligence (AI) models: one for detecting cells at the patch-level and another for classifying whole-slide image (WSIs). The AICCS consistently showed high accuracy in predicting cytology grades across different datasets. In the prospective assessment, it achieved an area under curve (AUC) of 0.947, a sensitivity of 0.946, a specificity of 0.890, and an accuracy of 0.892. Remarkably, the randomized observational trial revealed that the AICCS-assisted cytopathologists had a significantly higher AUC, specificity, and accuracy than cytopathologists alone, with a notable 13.3% enhancement in sensitivity. Thus, AICCS holds promise as an additional tool for accurate and efficient cervical cancer screening.

TET1 inhibits the migration and invasion of cervical cancer cells by regulating autophagy.

Methylation modifications play pertinent roles in regulating gene expression and various biological processes. The silencing of the demethylase enzyme TET1 can affect the expressions of key oncogenes or tumour suppressor genes, thus contributing to tumour formation. Nonetheless, how TET1 affects the progression of cervical cancer is yet to be elucidated. In this study, we found that the expression of TET1 was significantly downregulated in cervical cancer tissues. Functionally, TET1 knockdown in cervical cancer cells can promote cell proliferation, migration, invasion, cervical xenograft tumour formation and EMT. On the contrary, its overexpression can reverse the aforementioned processes. Moreover, the autophagy level of cervical cancer cells can be enhanced after TET1 knockdown. Mechanistically, methylated DNA immunoprecipitation (MeDIP)-sequencing and MeDIP quantitative real-time PCR revealed that TET1 mediates the methylation of autophagy promoter regions. These findings suggest that TET1 affects the autophagy of cervical cancer cells by altering the methylation levels of NKRF or HIST1H2AK, but the specific mechanism needs to be investigated further.

Epigenetic Mechanism of SETD1B-mediated Histone Methylation in Cognitive Impairment Induced by Sevoflurane Anesthesia in Neonatal Mice.

Sevoflurane (Sev) anesthesia is associated with cognitive deficits and neurotoxicity. This study explores the epigenetic mechanism of SET domain containing 1B (SETD1B) in Sev-induced cognitive impairment in neonatal mice. Neonatal mice (C57BL/6, n = 72) were exposed to 3% Sev for 2 h per day at P6, 7, and 8, and the control neonatal mice were only separated from the mother for 2 h. The mice were divided into groups of 12 individuals, with an equal number of male and female mice in each group. Mice were intraperitoneally injected with adenovirus-packaged SETD1B overexpression vector. Behavioral tests (Morris water maze, open field test, T-maze, novel object recognition, etc.) were performed at P30. Mouse hippocampal neuronal cells were cultured in vitro. SETD1B, C-X-C motif chemokine receptor 4 (CXCR4), NLR family pyrin domain containing 1 (NLRP1), Cleaved Caspase1, and GSDMD-N expressions in hippocampal tissues or cells were determined by quantitative real-time polymerase chain reaction and Western blot. SETD1B and histone H3 lysine 4 methylation (H3K4me1, H3K4me2, and H3K4me3) enrichment on the CXCR4 promoter was analyzed by ChIP. Sev insulted cognitive impairment and diminished SETD1B expression in mouse hippocampal tissues. SETD1B overexpression mitigated cognitive impairment, enhanced H3K4me3 levels in hippocampal tissues, and restrained hippocampal neuronal pyroptosis. SETD1B increased CXCR4 expression by elevating the H3K4me3 level on the CXCR4 promoter, thereby curbing NLRP1/Caspase1-mediated hippocampal neuronal pyroptosis. To conclude, SETD1B enhances CXCR4 expression by elevating the H3K4me3 level on the CXCR4 promoter, thereby suppressing NLRP1/Caspase1-triggered hippocampal neuronal pyroptosis and alleviating Sev-induced cognitive impairment in neonatal mice.

MRI-based radiomic models to predict surgical margin status and infer tumor immune microenvironment in breast cancer patients with breast-conserving surgery: a multicenter validation study.

OBJECTIVES: Accurate preoperative estimation of the risk of breast-conserving surgery (BCS) resection margin positivity would be beneficial to surgical planning. In this multicenter validation study, we developed an MRI-based radiomic model to predict the surgical margin status. METHODS: We retrospectively collected preoperative breast MRI of patients undergoing BCS from three hospitals (SYMH, n = 296; SYSUCC, n = 131; TSPH, n = 143). Radiomic-based model for risk prediction of the margin positivity was trained on the SYMH patients (7:3 ratio split for the training and testing cohorts), and externally validated in the SYSUCC and TSPH cohorts. The model was able to stratify patients into different subgroups with varied risk of margin positivity. Moreover, we used the immune-radiomic models and epithelial-mesenchymal transition (EMT) signature to infer the distribution patterns of immune cells and tumor cell EMT status under different marginal status. RESULTS: The AUCs of the radiomic-based model were 0.78 (0.66-0.90), 0.88 (0.79-0.96), and 0.76 (0.68-0.84) in the testing cohort and two external validation cohorts, respectively. The actual margin positivity rates ranged between 0-10% and 27.3-87.2% in low-risk and high-risk subgroups, respectively. Positive surgical margin was associated with higher levels of EMT and B cell infiltration in the tumor area, as well as the enrichment of B cells, immature dendritic cells, and neutrophil infiltration in the peritumoral area. CONCLUSIONS: This MRI-based predictive model can be used as a reliable tool to predict the risk of margin positivity of BCS. Tumor immune-microenvironment alteration was associated with surgical margin status. CLINICAL RELEVANCE STATEMENT: This study can assist the pre-operative planning of BCS. Further research on the tumor immune microenvironment of different resection margin states is expected to develop new margin evaluation indicators and decipher the internal mechanism. KEY POINTS: • The MRI-based radiomic prediction model (CSS model) incorporating features extracted from multiple sequences and segments could estimate the margin positivity risk of breast-conserving surgery. • The radiomic score of the CSS model allows risk stratification of patients undergoing breast-conserving surgery, which could assist in surgical planning. • With the help of MRI-based radiomics to estimate the components of the immune microenvironment, for the first time, it is found that the margin status of breast-conserving surgery is associated with the infiltration of immune cells in the microenvironment and the EMT status of breast tumor cells.

Machine learning radiomics of magnetic resonance imaging predicts recurrence-free survival after surgery and correlation of LncRNAs in patients with breast cancer: a multicenter cohort study.

BACKGROUND: Several studies have indicated that magnetic resonance imaging radiomics can predict survival in patients with breast cancer, but the potential biological underpinning remains indistinct. Herein, we aim to develop an interpretable deep-learning-based network for classifying recurrence risk and revealing the potential biological mechanisms. METHODS: In this multicenter study, 1113 nonmetastatic invasive breast cancer patients were included, and were divided into the training cohort (n = 698), the validation cohort (n = 171), and the testing cohort (n = 244). The Radiomic DeepSurv Net (RDeepNet) model was constructed using the Cox proportional hazards deep neural network DeepSurv for predicting individual recurrence risk. RNA-sequencing was performed to explore the association between radiomics and tumor microenvironment. Correlation and variance analyses were conducted to examine changes of radiomics among patients with different therapeutic responses and after neoadjuvant chemotherapy. The association and quantitative relation of radiomics and epigenetic molecular characteristics were further analyzed to reveal the mechanisms of radiomics. RESULTS: The RDeepNet model showed a significant association with recurrence-free survival (RFS) (HR 0.03, 95% CI 0.02-0.06, P < 0.001) and achieved AUCs of 0.98, 0.94, and 0.92 for 1-, 2-, and 3-year RFS, respectively. In the validation and testing cohorts, the RDeepNet model could also clarify patients into high- and low-risk groups, and demonstrated AUCs of 0.91 and 0.94 for 3-year RFS, respectively. Radiomic features displayed differential expression between the two risk groups. Furthermore, the generalizability of RDeepNet model was confirmed across different molecular subtypes and patient populations with different therapy regimens (All P < 0.001). The study also identified variations in radiomic features among patients with diverse therapeutic responses and after neoadjuvant chemotherapy. Importantly, a significant correlation between radiomics and long non-coding RNAs (lncRNAs) was discovered. A key lncRNA was found to be noninvasively quantified by a deep learning-based radiomics prediction model with AUCs of 0.79 in the training cohort and 0.77 in the testing cohort. CONCLUSIONS: This study demonstrates that machine learning radiomics of MRI can effectively predict RFS after surgery in patients with breast cancer, and highlights the feasibility of non-invasive quantification of lncRNAs using radiomics, which indicates the potential of radiomics in guiding treatment decisions.

Synergistic effects of multitype carbon doping and oxygen vacancies in TiO2/CNTs composite fabricated via nonthermal plasma for formaldehyde removal.

Formaldehyde as one of the typical indoor pollutants has long been concerned as it can pose a threat to human health. TiO2/CNTs composite with oxygen vacancies and multitype carbon doping (C-TiO2/CNTs) was fabricated using nonthermal plasma for the photocatalytic degradation of formaldehyde. The maximum degradation rate of formaldehyde was 93% and 83% via the new catalyst (with 5% CNTs content) under solar and visible light, respectively. The characterization of the catalyst confirmed the in-situ multitype carbon doping and oxygen vacancies: interstitial carbon doping and oxygen vacancies could dramatically reduce the bandgap and contribute to the improved absorption capability of formaldehyde and electrons. Interfacial carbon doping in the form of C-O-Ti bonds provided a migration channel, whereby photogenerated electrons could efficiently transfer from CNTs to TiO2 and then quench the holes left in the VB of TiO2. Therefore, the multitype carbon doping and oxygen vacancies can expand the light response as well as promote the separation of photo-generated electron/hole pairs. EPR results and experiment section indicated that O2·- plays the most significant role in formaldehyde removal due to the reverse transfer of the electrons. This work advances the understanding of photo-degradation of TiO2/CNTs composite and provides a new route for the abatement of formaldehyde.

Relationship Between the Expression of PD-1 and CTLA-4 on T Lymphocytes and the Severity and Prognosis of Sepsis.

Purpose: The study aimed to investigate the relationship between the expression of PD-1 and CTLA-4 on the surface of peripheral blood T lymphocyte subsets in patients with sepsis and the severity and prognosis of the disease. Patients and Methods: The study included patients with sepsis who were admitted to the intensive care unit. The expression of PD-1 and CTLA-4 on T lymphocyte subsets was detected by flow cytometry, and the severity of sepsis was assessed using the SOFA score. Results: The expression of PD-1 on CD4+T cells, PD-1 on Tregs, and CTLA-4 on Tregs increased with the severity of the disease (P<0.05). Multivariate logistic regression analysis showed that PD-1 expression on CD4+T cells, CTLA-4 expression on Tregs, and the SOFA score were independent risk factors for 28-day mortality in patients with sepsis (P<0.05). The area under the curve of the SOFA score combined with the expression of PD-1 on CD4+T cells and CTLA-4 on Treg cells was significantly higher than any single indicator (P<0.05). Patients with high expression of PD-1 on CD4+T cells (>31.25%) and CTLA-4 on Tregs (>12.64%) had a lower 28-day survival rate (P<0.05). Conclusion: The increased expression of PD-1 and CTLA-4 on CD4+T cells and Tregs is significantly associated with the severity and prognosis of sepsis patients. The combination of the SOFA score and the expression of PD-1 on CD4+T cells and CTLA-4 on Tregs can further improve the prognostic predictive value. These findings may be promising biomarkers for prognostic assessment, risk stratification, and identification of immunosuppression in patients with sepsis.

Radiomic and clinical data integration using machine learning predict the efficacy of anti-PD-1 antibodies-based combinational treatment in advanced breast cancer: a multicentered study.

BACKGROUND: Immune checkpoint inhibitors (ICIs)-based therapy, is regarded as one of the major breakthroughs in cancer treatment. However, it is challenging to accurately identify patients who may benefit from ICIs. Current biomarkers for predicting the efficacy of ICIs require pathological slides, and their accuracy is limited. Here we aim to develop a radiomics model that could accurately predict response of ICIs for patients with advanced breast cancer (ABC). METHODS: Pretreatment contrast-enhanced CT (CECT) image and clinicopathological features of 240 patients with ABC who underwent ICIs-based treatment in three academic hospitals from February 2018 to January 2022 were assigned into a training cohort and an independent validation cohort. For radiomic features extraction, CECT images of patients 1 month prior to ICIs-based therapies were first delineated with regions of interest. Data dimension reduction, feature selection and radiomics model construction were carried out with multilayer perceptron. Combined the radiomics signatures with independent clinicopathological characteristics, the model was integrated by multivariable logistic regression analysis. RESULTS: Among the 240 patients, 171 from Sun Yat-sen Memorial Hospital and Sun Yat-sen University Cancer Center were evaluated as a training cohort, while other 69 from Sun Yat-sen University Cancer Center and the First Affiliated Hospital of Sun Yat-sen University were the validation cohort. The area under the curve (AUC) of radiomics model was 0.994 (95% CI: 0.988 to 1.000) in the training and 0.920 (95% CI: 0.824 to 1.000) in the validation set, respectively, which were significantly better than the performance of clinical model (0.672 for training and 0.634 for validation set). The integrated clinical-radiomics model showed increased but not statistical different predictive ability in both the training (AUC=0.997, 95% CI: 0.993 to 1.000) and validation set (AUC=0.961, 95% CI: 0.885 to 1.000) compared with the radiomics model. Furthermore, the radiomics model could divide patients under ICIs-therapies into high-risk and low-risk group with significantly different progression-free survival both in training (HR=2.705, 95% CI: 1.888 to 3.876, p<0.001) and validation set (HR=2.625, 95% CI: 1.506 to 4.574, p=0.001), respectively. Subgroup analyses showed that the radiomics model was not influenced by programmed death-ligand 1 status, tumor metastatic burden or molecular subtype. CONCLUSIONS: This radiomics model provided an innovative and accurate way that could stratify patients with ABC who may benefit more from ICIs-based therapies.

A Novel Photocatalytic Functional Coating Applied to the Degradation of Xylene in Coating Solvents under Solar Irradiation.

A novel photocatalytic functional coating was prepared with g-C3N4/TiO2 composites as the photocatalytic active component modified by dielectric barrier discharge (DBD), and it showed an efficient catalytic performance under solar light irradiation. The degradation of xylene released from fluorocarbon coating solvents by the g-C3N4/TiO2 composite coatings was investigated under simulated solar irradiation. The degradation efficiency of the coating mixed with DBD-modified 10%-g-C3N4/TiO2 showed a stable, long-lasting, and significantly higher activity compared to the coatings mixed with the unmodified catalyst. Ninety-eight percent of the xylene released from fluorocarbon coating solvents was successfully removed under solar light irradiation in 2 h. The properties of the catalyst samples before and after modification were evaluated using scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FT-IR), ultraviolet-visible (UV-vis) spectroscopy, X-ray photoelectron spectroscopy (XPS), and other characterization techniques. The results suggested that DBD-modified g-C3N4/TiO2 showed an improved capture ability and utilization efficiency of solar light with reduced band gap and lower complexation rate of electron-hole pairs. The prepared photocatalytic coating offers an environmentally friendly approach to purify the volatile organic compounds (VOCs) released from solvent-based coatings.

The pan-cancer analysis identified DIAPH3 as a diagnostic biomarker of clinical cancer.

OBJECTIVE: This study aimed to determine prognostic biomarkers of cervical cancer by pan-cancer analysis. MATERIALS AND METHODS: Common differentially expressed genes in Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) database were demonstrated using R software analysis, and these genes were enriched by the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology. Genes with prognostic value were identified by least absolute contraction and selection regression, Cox regression, and survival analysis, and pan-cancer analysis was conducted using the Tumor Immune Estimation Resource database and TCGA database. Western blot, qRT-PCR, and immunohistochemistry were used to preliminarily verify its expression in cervical cancer (S1). RESULTS: The prognostic marker Diaphanous Related Formin 3 (DIAPH3) was obtained from us. The enrichment analysis revealed that DIAPH3 was involved in tumor proliferation, invasion, and inflammation. The pan-cancer analysis revealed that it was highly expressed in various cancers. Immune infiltration analysis revealed that its expression was related to B cells, effector T cells, and macrophage infiltration; however, immune checkpoint correlation analysis and tumor mutation burden analysis revealed the correlation between gene expression and immunotherapy. The expression of DIAPH3 in cervical cancer was significantly different from that in normal cervical tissues. CONCLUSION: The expression of DIAPH3 in cervical cancer was significantly increased, which may be related to the proliferation, metastasis, immune invasion, and immunotherapy of cervical cancer.

Knowledge, attitude, and perception regarding HPV-related diseases and vaccination among the general public in Guizhou Province of China.

BACKGROUND: The rising prevalence of high-risk human papillomavirus (HR-HPV) type-related diseases pose an ongoing health challenge in China. In this study, we assessed the current views of the general public of the Guizhou Province on HPV and HPV vaccinations to provide recommendations for future directions regarding the rollout of HPV vaccination in the area. METHODS: An online questionnaire survey was conducted that included 3412 (2532 females and 880 males) native adult residents of the Guizhou Province. Data on the socio-demographic characteristics, knowledge of HPV, and perceptions of HPV vaccinations were collected. Data comparisons were made between students and non-students and between participants with and without medical backgrounds. All statistical analyses were performed using SPSS 26.0. RESULTS: The self-reported HPV infection rates were 5.85% in women and 0.86% in men. A total of 46.29% of women and 34.43% of men achieved acceptable knowledge levels of HPV and 47.54% of women possessed an acceptable knowledge level of HPV vaccines. Non-students and medical participants performed significantly better in the knowledge tests than their respective opposing groups. Online media was the most popular HPV information source for all the participants. A total of 93.58% of women and 87.88% of men expressed willingness toward HPV vaccination. The major facilitators of vaccination acceptance were females (OR = 1.932, 95% CI: 1.390-2.685, p < 0.001) or students (OR = 2.276, 95% CI: 1.207-4.291, p = 0.011), and participants with higher HPV knowledge level (OR = 1.796, 95% CI: 1.300-2.481, p < 0.001). Ages 41-50 (OR = 0.255, 95% CI: 0.121-0.538, p = 0.001) or > 50 (OR = 0.141, 95% CI: 0.059-0.337, p < 0.001) were significant predictors of a negative attitude towards HPV vaccination. CONCLUSION: Guizhou residents had poor knowledge of HPV-related issues. The percentage of healthcare workers who achieved acceptable knowledge levels was one-half or less. The increasing HPV prevalence and cervical cancer incidence can be contained if more affordable vaccines are developed and the low knowledge levels pervading young adults and medical staff is eliminated.

Inhibition of p62 and/or NFE2L2 induced autophagy impaires esophageal squamous cell cancer metastasis by reversing EMT.

Esophageal squamous cell carcinoma (ESCC) pathogenesis is influenced by both NFE2L2 (nuclear factor erythroid 2-related factor 2) and SQSTM1 (sequestosome 1), also known as p62. However, while there is evidence that these two proteins can interact with one another in a range of pathological contexts, whether these interactions govern the development or progression of ESCC remains unknown. In the present study, analyses of the GEPIA database revealed the simultaneous upregulation of both NFE2L2 and p62 in ESCC, as was further confirmed through biochemical analyses conducted with a human tumor microarray. Knocking down the expression of one or both of these factors demonstrated that both p62 and NFE2L2 mediate the progression of ESCC, as such downregulation altered the morphological characteristics of these cells and suppressed the epithelial-mesenchymal transition (EMT). Strikingly, these experiments revealed synergistic interactions between NFE2L2 and p62 in the promotion of ESCC invasivity and EMT induction. The treatment of cells with the autophagy inhibitors 3-MA, however, was sufficient to partially reverse the anti-metastatic effects of knocking down p62 and/or NFE2L2. Together, these data illustrate the ability of p62 and NFE2L2 to function in a synergistic manner, promoting ESCC cell metastatic progression and EMT induction through mechanisms linked to autophagic activity. As such, efforts to simultaneously target both of these proteins may represent a viable means of providing new treatment options to ESCC patients.

Time delay interferometry with a transfer oscillator.

In this work, we experimentally perform time delay interferometry by using a transfer oscillator, which is capable of reducing the laser frequency noise and the clock noise simultaneously in the post processing. The iodine frequency reference is coherently downconverted to the microwave frequency using a laser frequency comb. The residual noise of the downconversion network is 5 × 10-6Hz/Hz1/2 at 0.7 mHz, and 4 × 10-6Hz/Hz1/2 at 0.1 Hz, indicating high homology between the optical frequency and the microwave frequency. We carry out time delay interferometry with the aid of the electrical delay module, which can introduce large time delays. The results show that the laser frequency noise and the clock noise can be reduced simultaneously by ten and three orders of magnitude, respectively, in the frequency band from 0.1 mHz to 0.1 Hz. The performance of the noise reduction can reach 6 × 10-8Hz/Hz1/2 at 0.1 mHz, and 7 × 10-7Hz/Hz1/2 at 1 mHz, meeting the requirements of the space-borne gravitational wave detection. Our work will be able to offer an alternative method for the frequency comb-based time delay interferometry in the future space-borne gravitational wave detectors.

N-acetyl Cysteine Inhibits Cell Proliferation and Differentiation of LPSInduced MC3T3-E1 Cells Via Regulating Inflammatory Cytokines.

BACKGROUND: Peri-implantitis is one of the most common complications in oral implantation and could lead to the loss of the function of bone tissues around implants. METHODS: This study used lipopolysaccharide (LPS) as a stimulant for MC3T3-E1 cells and N-acetyl cysteine (NAC) as an inhibitor to inhibit the effect of LPS to investigate the effect of NAC on the expression of bone formation related factors and inflammatory-related factors of osteoblasts under the action of LPS. RESULTS: In this study, we found that the cell proliferation and cell differentiation were significantly promoted when NAC concentrations were between 0 ~ 0.5 mM, but were inhibited when the concentration exceeded 0.5 mM. LPS had a slightly promoting effect on the cell proliferation before 20 µg/mL but inhibited the cell proliferation after 20 µg/mL. LPS reduced protein and gene expressions of Runx2, ALP and BGP and increased protein and gene expressions of NF-κB and TNF-α. NAC reversibly regulated the LPS's regulation on the expression of MC3T3-E1 cell cytokine gene and protein. CONCLUSION: The optimal NAC concentration for treating MC3T3-E1 cells is 0.5 mM, and the optimal LPS concentration for stimulating MC3T3-E1 cells is 20 µg/mL. NAC plays an active role in regulating the differentiation of MC3T3-E1 cells, and can inhibit LPS to regulate the differentiation of MC3T3-E1 cells. NAC promotes the expression of an osteogenic factor of MC3T3-E1cells and inhibits the expression of inflammatory cytokines.

Deep learning magnetic resonance imaging predicts platinum sensitivity in patients with epithelial ovarian cancer.

Objective: The aim of the study is to develop and validate a deep learning model to predict the platinum sensitivity of patients with epithelial ovarian cancer (EOC) based on contrast-enhanced magnetic resonance imaging (MRI). Methods: In this retrospective study, 93 patients with EOC who received platinum-based chemotherapy (≥4 cycles) and debulking surgery at the Sun Yat-sen Memorial Hospital from January 2011 to January 2020 were enrolled and randomly assigned to the training and validation cohorts (2:1). Two different models were built based on either the primary tumor or whole volume of the abdomen as the volume of interest (VOI) within the same cohorts, and then a pre-trained convolutional neural network Med3D (Resnet 10 version) was transferred to automatically extract 1,024 features from two MRI sequences (CE-T1WI and T2WI) of each patient to predict platinum sensitivity. The performance of the two models was compared. Results: A total of 93 women (mean age, 50.5 years ± 10.5 [standard deviation]) were evaluated (62 in the training cohort and 31 in the validation cohort). The AUCs of the whole abdomen model were 0.97 and 0.98 for the training and validation cohorts, respectively, which was better than the primary tumor model (AUCs of 0.88 and 0.81 in the training and validation cohorts, respectively). In k-fold cross-validation and stratified analysis, the whole abdomen model maintained a stable performance, and the decision function value generated by the model was a prognostic indicator that successfully discriminates high- and low-risk recurrence patients. Conclusion: The non-manually segmented whole-abdomen deep learning model based on MRI exhibited satisfactory predictive performance for platinum sensitivity and may assist gynecologists in making optimal treatment decisions.

Weak-Light Phase-Locking Time Delay Interferometry with Optical Frequency Combs.

In the future space-borne gravitational wave (GW) detector, the optical transponder scheme, i.e., the phase-locking scheme, will be utilized so as to maintain the signal-to-noise ratio (SNR). In this case, the whole constellation will share one common laser equivalently, which enables the considerable simplification of time delay interferometry (TDI) combinations. Recently, and remarkably, the unique combination of TDI and optical frequency comb (OFC) has shown a bright prospect for the future space-borne missions. When the laser frequency noise and the clock noise are synchronized using OFC as the bridge, the data streams will be reasonably simplified. However, in the optical transponder scheme, the weak-light phase-locking (WLPL) loops could bring additional noises. In this work, we analyze the phase-locking scheme with OFC and transfer characteristics of the noises including the WLPL noise. We show that the WLPL noise can be efficiently reduced by using the specific TDI combination, and the cooperation of phase-locking and frequency combs can greatly simplify the post-processing.

Constraining the Symmetron Model with the HUST-2020 Torsion Pendulum Experiment.

The search for dynamically screening the coupling between the scalar field and matter in high-density environment is achievable with the symmetron model. The high-accuracy and short-range gravity experiment is proposed to test the symmetron model. In this Letter, the data of the HUST-2020 torsion pendulum experiment testing the inverse-square law at submillimeter range is analyzed to constrain the symmetron model. The results show that the HUST-2020 experiment is uniquely sensitive to probe the symmetron model with a mass scale of µ=7.2×10^{-3} eV, and the self-coupling parameter λ≲105 is excluded at mass scale M=0.3 TeV. Especially, at the dark energy scale µ=2.4×10^{-3} eV, the constraint at M=1.3 TeV is improved by about 10 times the previous constraints on the torsion pendulum experiment.