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Streptococcus suis (S. suis) is a Gram-positive bacterium and the main culprit behind zoonotic outbreaks, posing a serious threat to public health. The prevalent strains in China are mainly of sequence types (ST) 1 and 7, with few cases of human infections caused by other sequence type being reported. This study presents the first isolation of a ST25 strain from the blood of a septicemic patient. A 57-year-old febrile patient was admitted to a hospital in Hainan of China, diagnosed as septicemia and hepatic dysfunction. A strain of S. suis was isolated from blood culture and confirmed to be serotype 2 and ST25 through 16S rRNA sequencing and whole-genome sequencing, and its genome was further analyzed for gene functions and presence of drug resistance genes. The full-length genome of strain HN28 spans 2,280,124 bp and encodes a total of 2291 proteins. Genes annotated in COG, GO, KEGG, CAZy, and PHl databases accounted for 75.38 %, 69.14 %, 55.35 %, 4.58 %, and 11.87 % of the total predicted proteins, respectively. Virulence factor analysis revealed the presence of seven putative virulence genes in strain HN28. Analysis using the CARD database identified 51 resistance genes in HN28, alongside abundant exocytosis systems. These findings underscore the occurrence of S. suis infections in humans caused by less common ST, emphasizing the need for enhanced epidemiological investigations and monitoring of S. suis infections in the human population.

Abstract Background The Gegen Qinlian Decoction (GGQLD) is a renowned traditional Chinese medicinal formula that has been used for centuries to effectively treat asymptomatic Hyperuricemia (HUA). This study aims to investigate the underlying mechanism of GGQLD's therapeutic effects on HUA. Methods The study enrolled a total of 25 healthy participants and 32 middle-aged and elderly individuals with asymptomatic HUA. All asymptomatic HUA participants were treated with GGQLD. Venous blood samples were collected from all participants to isolate peripheral blood mononuclear cells (PBMCs), which were then analyzed for biological profiles using flow cytometry. Network pharmacology analysis was utilized to identify the potential pathways involved in the therapeutic effects of GGQLD. Transcriptomic patterns of cultured proximal tubule epithelial cells (PTECs) were evaluated via bulk RNA-seq, and critical differentially expressed genes (DEGs) were identified and verified through ELISA. Molecular docking and molecular dynamics (MD) simulation were employed to investigate the potential compounds in GGQLD that may be involved in treating HUA. Results Network pharmacology analysis revealed that immune-related pathways might be involved in the therapeutic mechanism of GGQLD. RNA-seq analysis confirmed the involvement of innate lymphoid cell (ILC) development-related genes and clock genes. Polychromatic flow cytometric analysis demonstrated that GGQLD treatment reduced the proportion of ILC3s in total ILCs in asymptomatic HUA patients. ELISA results showed that GGQLD treatment reduced the levels of activating factors, such as ILC3-IL-18 and IL-1β, in the plasma of HUA patients. GGQLD was also found to regulate circadian clock gene expression in PBMCs to treat asymptomatic HUA. Furthermore, the interaction between 40 compounds in GGQLD and HDAC3 (Histone Deacetylase 3), NLRP3 (NOD-like receptor protein 3), RORA (RAR-related orphan receptor A), and REV-ERBα (nuclear receptor subfamily 1) revealed that GGQLD may regulate ILCs and clock genes to treat asymptomatic HUA. Conclusions The regulation of circadian clock gene expression and the proportion of ILC cells may be involved in the therapeutic effects of GGQLD on asymptomatic HUA patients.

Non-invasive external energy triggered efficient tumor therapy is a promising specific treatment strategy. Herein, a composite material of bismuth sodium titanate (BNT) and molybdenum disulfide (MoS2) with piezoelectric effect was designed for the synergistic treatment of breast cancer with near-infrared-II (NIR-II) light and ultrasound (US) activation. The BNT@MoS2 exhibit excellent photothermal and acoustic properties upon excitation by 1060 nm NIR-II laser and US, respectively. The synergistic effect of hyperthermia and reactive oxygen species (ROS) under photoacoustic action endows the BNT@MoS2 with remarkable anti-tumor activities, enabling them to eradicate breast cancer cells within 10 min. The work could provide new insights into the treatment of breast cancer.

Highlights 1. The expression of circTRIM28 was upregulated in BC. 2. Silencing circTRIM28 enhanced tamoxifen sensitivity and cell apoptosis, whereas curbed cell proliferation, cell migration and invasion in BC cells. 3. CircTRIM28 expedited BC by targeting miR-409-3p. 4. MiR-409-3p repressed BC by retarding HMGA2.

Abstract Background This study aims to construct a reliable diagnostic model for coronary artery disease (CAD) patients and explore its potential mechanism by consensus molecular subtypes of ferroptosis-related genes. Methods GSE12288 and GSE20680 were downloaded from Gene Expression Omnibus database. CAD patients were divided into different molecular subtypes according to the expression level of ferroptosis-related genes. Then, the distribution of differentially expressed genes, functional annotations and immune infiltration cells between the two subtypes were compared. Finally, a prognostic model of ferroptosis-related genes in CAD was constructed and verified. Results Two different molecular subtypes of CAD were obtained according to the expression level of ferroptosis-related genes. Then, a total of 1944 differentially expressed genes (DEGs) were found, among which, 236 genes were up-regulated and 1708 genes were down-regulated. In addition, 43 DEGs were ferroptosis-related genes. Functional enrichment analysis showed that these DEGs between two subtypes of CAD were mainly enriched in immune-related pathways and processes, such as T cell receptor, mTOR, NOD-like receptor and Toll-like receptor signaling pathways. We also found that 21 immune cells were significantly changed between two subtypes of CAD. The LASSO method was performed to identify and construct the 16 ferroptosis-related genes-based diagnostic signature. Diagnostic efficiency of diagnostic signature measured by AUC in the training set and validation cohort was 0.971 and 0.899, respectively. Conclusions This study contributes to a more comprehensive understanding of the mechanism of ferroptosis-related genes in CAD.

Time-resolved NMR spectra provide unique structural and dynamical information, but their measurement in systems undergoing chemical reactions is challenging. Here the authors, combining single-scan spectroscopic imaging, rapid mixing and continuous flow techniques, obtain chemically resolved snapshots of a reacting system throughout the reaction coordinate.

IntroductionThe mid-transverse colon cancer is relatively uncommon in all colon cancers and the optimal surgical approach of mid-transverse colon cancer remains debatable.Aim and ObjectivesOur study aimed to depict the techniques and outcomes of laparoscopic transverse colectomy in one single clinical center and compare this surgical approach to traditional laparoscopic right hemicolectomy and laparoscopic left hemicolectomy.MethodThis was a retrospective cohort study of patients with mid-transverse colon cancer in one single clinical center from February 2012 to October 2020. The enrolled patients were divided into two groups undergoing laparoscopic transverse colectomy and laparoscopic right/left hemicolectomy, respectively. The intraoperative, postoperative complications, oncological outcomes and functional outcomes were compared between the two groups. The primary endpoint was disease free survival (DFS).ResultsThe study enrolled 70 patients with 40 patients undergoing laparoscopic transverse colectomy and 30 patients undergoing laparoscopic hemicolectomy. The intraoperative accidental hemorrhage and multiple organ resection occurred similarly in the two groups. In transverse colectomy, caudal-to-cephalic approach was likely to harvest more lymph nodes although require more operation time than cephalic-to-caudal approach (23.1 ± 14.3 vs. 13.4 ± 5.4 lymph nodes, P = 0.004; 184.3 ± 37.1 min vs. 146.3 ± 44.4 min, P = 0.012). The laparoscopic transverse colectomy was marginally associated with lower incidence of overall postoperative complications and shorter postoperative hospital stay although without statistical significance (8(20.0%) vs. 12(40.0%), P = 0.067; 7(5–12) vs. 7(5–18), P = 0.060). The 3-year DFS showed no significant difference (3-year DFS 89.7% in transverse colectomy vs. 89.9% in hemicolectomy, P = 0.688) between the two groups. The alternating consistency of defecation occurred significantly less after laparoscopic transverse colectomy than laparoscopic hemicolectomy (15(51.7%) vs. 20(80.0%), P = 0.030).ConclusionThe laparoscopic transverse colectomy is technically feasible with satisfactory oncological and functional outcomes for mid-transverse colon cancer. Performing the caudal-to-cephalic approach might be more advantageous in lymphadenectomy.

Treatment of implant-associated infection is becoming more challenging, especially when bacterial biofilms form on the surface of the implants. Developing multi-mechanism antibacterial methods to combat bacterial biofilm infections by the synergistic effects are superior to those based on single modality due to avoiding the adverse effects arising from the latter. In this work, TiO2 nanorod arrays in combination with irradiation with 808 near-infrared (NIR) light are proven to eradicate single specie biofilms by combining photothermal therapy, photodynamic therapy, and physical killing of bacteria. The TiO2 nanorod arrays possess efficient photothermal conversion ability and produce a small amount of reactive oxygen species (ROS). Physiologically, the combined actions of hyperthermia, ROS, and puncturing by nanorods give rise to excellent antibacterial properties on titanium requiring irradiation for only 15 min as demonstrated by our experiments conducted in vitro and in vivo. More importantly, bone biofilm infection is successfully treated efficiently by the synergistic antibacterial effects and at the same time, the TiO2 nanorod arrays improve the new bone formation around implants. In this protocol, besides the biocompatible TiO2 nanorod arrays, an extra photosensitizer is not needed and no other ions would be released. Our findings reveal a rapid bacteria-killing method based on the multiple synergetic antibacterial modalities with high biosafety that can be implemented in vivo and obviate the need for a second operation. The concept and antibacterial system described here have large clinical potential in orthopedic and dental applications.

Heat transfer simulations play an important role in predicting solidification conditions that determine microstructure properties of additive manufactured products. High-fidelity heat transfer models, e.g., Truchas [1], provide a numerical framework capable of resolving many desired physics (e.g., thermal radiation, elemental vaporization, gas-solid-liquid interactions, etc.), but they are often too computationally expensive to simulate the solidification conditions at the AM process-scale. Recently, Stump et al. [2] proposed a low-fidelity analytical heat conduction model capable of simulating solidification conditions on the process-scale. This model makes the problem analytically tractable by neglecting many important physics that may have an impact on the accuracy of the predicted solidification conditions. An effective way of improving the accuracy of the analytical with little computational effort is to determine an optimal set of parameters that minimize the discrepancy between the low-fidelity analytical model and a high-fidelity numerical model. In this work, a model approximation problem is formulated which can be solved by leveraging blackbox optimization methods. Multiple heat sources are used in the analytical model to improve the calibration performance in a flexible framework. Two blackbox optimization methods, i.e., Bayesian optimization and directional Gaussian smoothing methods, are employed to address the challenge that the gradient of the loss function is inaccessible during optimization. The results show that the single-beam analytical model has limitations in fitting the high-fidelity model, but the proposed multi-beam analytical model provides satisfactory approximations to the high-fidelity temperature and melt pool fields.

Co-Cr-Fe-Ni-Mn high entropy alloys (HEAs) have attracted extensive attention due to their broad cryogenic engineering application potential, reasonable control of alloying elements can significantly improve its mechanical performance. In this work, the effects of Co content on the phase stability and mechanical behavior CoxCrFeNiMnAl0.3 HEAs were investigated. It is found that with the decrease of the Co content, the stability of the face-centered cubic (FCC) solid solution phase in the alloy decreases, resulting in the precipitation of the BCC (body-centered cubic) phase from the FCC phase, thereby obtaining the FCC + BCC dual-phase structure. During annealing, the precipitated BCC phase can effectively suppress the grain growth and recrystallization of the FCC solid solution, forming an ultrafine-grained microstructure. In addition, the Ni-Al type nano-B2 phase can form in the BCC phase under the influence of the negative formation enthalpy during solidification. This micro/nano hierarchical structure can effectively improve the mechanical properties of the alloys. Co0.25CrFeNiMnAl0.3 maintains relatively excellent tensile yield strength (486 MPa), the tensile elongation remains above 20 %. This study regulates the formation of the BCC phase and B2 phase by reducing the content of Co, which provides a new idea for the preparation of low-cost HEAs with excellent mechanical properties.

Context: Retrorectal tumours are rare with developmental cysts being the most common type. Conventionally, large retrorectal developmental cysts (RRDCs) require the combined transabdomino-sacrococcygeal approach. Aims: This study aims to investigate the surgical outcomes of the laparoscopic approach for large RRDCs. Settings and Design: A retrospective case series analysis. Subjects and Methods: Data of patients with RRDCs of 10 cm or larger in diameter who underwent the laparoscopic surgery between 2012 and 2017 at our tertiary centre were retrospectively analyzed. Statistical Analysis Used: Results are presented as median values or mean ± standard deviation for continuous variables and numbers (percentages) for categorical variables. Results: Twenty consecutive cases were identified (19 females; median age, 36 years). Average tumour size was 10.9 ± 1.1 cm. Cephalic ends of lesions ranged from S1/2 junction to S4 level. Caudally, 18 cysts extended to the sacrococcygeal hypodermis. Seventeen patients underwent the pure laparoscopy; three patients received a combined laparoscopic-posterior approach. The operating time was 167.1 ± 57.3 min for the pure laparoscopic group and 212.0 ± 24.5 min for the combined group. The intraoperative haemorrhage was 68.2 ± 49.7 and 66.7 ± 28.9 (mL), respectively. Post-operative complications included one trocar site hernia, one wound infection and one delayed rectal wall perforation. The median post-operative hospital stay was 7 days. With a median follow-up period of 36 months, 1 lesions recurred. Conclusions: The laparoscopic approach can provide a feasible and effective alternative for large RRDCs, with advantages of the minimally invasive surgery. For lesions with ultra-low caudal ends, especially those closely clinging to the rectum, a combined posterior approach is still necessary.

Background and AimPreoperative endoscopic markers have been extensively used for the localization of colonic neoplastic lesions in laparoscopic surgery. We conducted this respective cohort study to compare the localization accuracy of two commonly used endoscopic marker strategies (endoscopic clip plus abdominal plain film and endoscopic tattooing).MethodsPatients who received preoperative colonoscopy localization for colonic neoplasia and underwent an elective laparoscopic operation afterward between 2013 and 2020 were included in this retrospective study. The localization accuracy of the two endoscopic strategies was compared, and the predictors of successful endoscopic localization were identified by multivariate regression.ResultsIn total, 195 patients [average age 62.4 ± 9.2 years, 123 male (63.1%)] undergoing preoperative colonoscopy localization and subsequent laparoscopic colectomy for colonic neoplasms were included. Endoscopic localization was finally proven to be successful in 150 (76.9%) patients in the surgery. Compared to the tattooing group, patients who had successful localization for colonic lesions were fewer in the clip group (64 of 101 cases, 63.4% vs. 86 of 94 cases, 91.5%, p < 0.001). The multivariate regression analysis showed that the endoscopic tattooing strategy, endoscopic clip strategy, and lesion location were all predictors for successful localization (all with p < 0.001).ConclusionCompared with endoscopic clip plus abdominal plain film, endoscopic tattooing had higher localization accuracy and less intraoperative colonoscopy counseling; the endoscopic clip strategy, tattooing strategy, and colonic lesion location were all predictors of successful endoscopic localization.

Background: Recently, the distinction between left- and right-sided colon cancer (LCC and RCC) has been brought into focus. RCC is associated with an inferior overall survival and progression-free survival. We aimed to perform a detailed analysis of the diversity of extracellular vesicles (EV) between LCC and RCC using quantitative proteomics and to identify for new diagnostic and prognostic biomarkers. Methods: We isolated EVs from patients with LCC, RCC and healthy volunteers, and treated colorectal cancer cell line with serum-derived EVs. We then performed a quantitative proteomics analysis of the serum-derived EVs and cell line treated with EVs. Proteomic data are available via ProteomeXchange with the identifiers PXD012283 and PXD012304. In addition, we assessed the performance of EV SPARC and LRG1 as diagnosis and prognosis biomarkers in colon cancer. Findings: The expression profile of the serum EV proteome in patients with RCC was different from that of patients with LCC. Serum-derived EVs in RCC promoted cellular mobility more significantly than EVs derived from LCC. EV SPARC and LRG1 expression levels demonstrated area under the receiver-operating characteristic curve values of 0.95 and 0.93 for discriminating patients with colon cancer from healthy controls. Moreover, the expression levels of SPARC and LRG1 correlated with tumour sidedness and were predictive of tumour recurrence. Interpretation: We identified differences in EV protein profiles between LCC and RCC. Serum-derived EVs of RCC may promote metastasis via upregulation of extracellular matrix (ECM)-related proteins, especially SPARC and LRG1, which may serve as diagnosis and prognosis biomarkers in colon cancer. Keywords: Colon cancer, Extracellular vesicles, Proteomics, Metastasis, Tumour location

Abstract Background It is becoming increasingly clear that cancers can rarely be ascribed to just one or a few genomic variations. Genes generally do not function alone, but in groups that function as “networks”. This study aimed to develop a competing endogenous RNA (ceRNA) network to elucidate the role of long non-coding RNA H19 in colorectal cancer. Methods Large-scale RNA-seq data was obtained from The Cancer Genome Atlas database. Differentially expressed RNAs were identified by bioinformatics analysis, and a competing endogenous RNA network was constructed. Functional enrichment analysis and correlation analysis between competing endogenous RNAs and clinical features were performed to reveal their roles in the tumorigenesis of colorectal cancer. To verify the conclusions derived from bioinformatics analysis, we investigated the effect of lncRNA H19 knockdown in human colorectal cancer cell lines HT-29 and HCT116. Results The present study successfully identify various cancer-specific lncRNAs and pseudogenes in CRC. The lncRNA/pseudogene–miRNA–mRNA ceRNA network was constructed using 10 lncRNAs, 5 pseudogenes, 122 mRNAs and 39 miRNAs. In the ceRNA network of CRC, H19 up-regulates various cancer-related mRNA by competitively sponging various miRNA, and participates in PI3K–Akt signaling pathway in this manner. Cox regression and correlation analysis showed that H19 and some other competing endogenous RNAs in the network are associated with poor prognosis and clinical parameters such as tumor grade and metastasis. Knockdown of H19 reduces the protein level of MET, ZEB1, and COL1A1 in vitro. Conclusions H19 regulates PI3K–Akt signal pathway through a competing endogenous RNA network and predicts poor prognosis in colorectal cancer. The pseudogene RPLP0P2 may be an important oncogene like H19 and needs to be studied further.

There is increasing effort to improve the signal sensitivity and explore the hyperpolarization dynamics. Here the authors demonstrate the parahydrogen spin transfer dynamics in compounds containing 15N using SABRE hyperpolarization technique with different strengths of the magnetic field.

Local-gradient-based optimization approaches lack nonlocal exploration ability required for escaping from local minima in non-convex landscapes. A directional Gaussian smoothing (DGS) approach was proposed in our recent work and used to define a truly nonlocal gradient, referred to as the DGS gradient, in order to enable nonlocal exploration in high-dimensional black-box optimization. Promising results show that replacing the traditional local gradient with the nonlocal DGS gradient can significantly improve the performance of gradient-based methods in optimizing highly multi-modal loss functions. However, the current DGS method is designed for unbounded and unconstrained optimization problems, making it inapplicable to real-world engineering design optimization problems where the tuning parameters are often bounded and the loss function is usually constrained by physical processes. In this work, we propose to extend the DGS approach to the constrained inverse design framework in order to find a better design. The proposed framework has its advantages in portability and flexibility to naturally incorporate the parameterization, physics simulation, and objective formulation together to build up an effective inverse design workflow. A series of adaptive strategies for smoothing radius and learning rate updating are developed to improve the computational efficiency and robustness. To enable a clear binarized design, a dynamic growth mechanism is imposed on the projection strength in parameterization. The methodology is demonstrated by an example of wavelength demultiplexer. Our method shows superior performance compared to the state-of-the-art approaches. By incorporating volume constraints, the optimized design achieves an equivalently high performance but significantly reduces the amount of material usage.

High entropy alloys (HEAs) are promising next-generation materials due to their various excellent properties. To understand these properties, it's necessary to characterize the chemical ordering and identify order-disorder transitions through efficient simulation and modeling of thermodynamics. In this study, a robust data-driven framework based on Bayesian approaches is proposed for the accurate and efficient prediction of configurational energy of high entropy alloys. The recently proposed effective pair interaction (EPI) model with ensemble sampling is used to map the configuration and its corresponding energy. Given limited data calculated by first-principles calculations, Bayesian regularized regression not only offers an accurate and stable prediction but also effectively quantifies the uncertainties associated with EPI parameters. Compared with the arbitrary truncation of model complexity, we further conduct a physical feature selection to identify the truncation of coordination shells in EPI model using Bayesian information criterion. The results achieve efficient and robust performance in predicting the configurational energy, particularly given small data. The developed methodology is applied to study a series of refractory HEAs, i.e. NbMoTaW, NbMoTaWV and NbMoTaWTi where it is demonstrated how dataset size affects the confidence when data is sparse. Keywords: High entropy alloys, Uncertainty quantification, Bayesian regression, Bayesian information criterion, First-principles calculations, Machine learning

Loss of vision may enhance the capabilities of auditory perception, but the mechanisms mediating these changes remain elusive. Here, visual deprivation in rats resulted in altered oscillatory activities, which appeared to be the result of a common mechanism underlying neuronal assembly formation in visual and auditory centers. The power of high-frequency β and γ oscillations in V1 (the primary visual cortex) and β oscillations in the LGN (lateral geniculate nucleus) was increased after one week of visual deprivation. Meanwhile, the power of β oscillations in A1 (the primary auditory cortex) and the power of β and γ oscillations in the MGB (medial geniculate body) were also enhanced in the absence of visual input. Furthermore, nerve tracing revealed a bidirectional nerve fiber connection between V1 and A1 cortices, which might be involved in transmitting auditory information to the visual cortex, contributing to enhanced auditory perception after visual deprivation. These results may facilitate the better understanding of multisensory cross-modal plasticity.

Multilayer colloidal crystal has been prepared by the layer-by-layer deposition of silica microspheres on a glass slide. Each layer is a slab consisting of a fcc close-packed colloidal arrays. By properly choosing the sizes of spheres, the whole spectral feature of multilayer colloidal crystal can be tuned. Here, we engineered a multilayer superlattice structure with an effective passband between two stop bands. This gives a strong narrowing effect on emission spectrum. With the stop bands at the shortwave and longwave edges of emission spectrum, the passband in the central wavelength region can be regarded as a strong decrease of suppression effect and enhancement of a narrow wavelength region of emission. The spectral narrowing modification effect of suitably engineered colloidal crystals shows up their importance in potential application as optical filters and lasing devices.DOI: http://dx.doi.org/10.5755/j01.ms.23.3.16320

This paper, through mass spectrometric (MS) analysis for nitro compound explosives on a direct analysis in a real-time time-of-flight MS, indicates that even on a high-resolution MS with accurate mass measurement capabilities, there is no guarantee to obtain the unique molecular formula of a compound. By calculating spectra accuracy, highly accurate isotope pattern matching can be conducted to significantly improve performance of compound confirmation or identification.

In this effort we propose a data-driven learning framework for reduced order modeling of fluid dynamics. Designing accurate and efficient reduced order models for nonlinear fluid dynamic problems is challenging for many practical engineering applications. Classical projection-based model reduction methods generate reduced systems by projecting full-order differential operators into low-dimensional subspaces. However, these techniques usually lead to severe instabilities in the presence of highly nonlinear dynamics, which dramatically deteriorates the accuracy of the reduced-order models. In contrast, our new framework exploits linear multistep networks, based on implicit Adams−Moulton schemes, to construct the reduced system. The advantage is that the method optimally approximates the full order model in the low-dimensional space with a given supervised learning task. Moreover, our approach is non-intrusive, such that it can be applied to other complex nonlinear dynamical systems with sophisticated legacy codes. We demonstrate the performance of our method through the numerical simulation of a two-dimensional flow past a circular cylinder with Reynolds number Re = 100. The results reveal that the new data-driven model is significantly more accurate than standard projection-based approaches.

We present a pseudoreversible normalizing flow method for efficiently generating samples of the state of a stochastic differential equation (SDE) with various initial distributions. The primary objective is to construct an accurate and efficient sampler that can be used as a surrogate model for computationally expensive numerical integration of SDEs, such as those employed in particle simulation. After training, the normalizing flow model can directly generate samples of the SDE's final state without simulating trajectories. The existing normalizing flow model for SDEs depends on the initial distribution, meaning the model needs to be retrained when the initial distribution changes. The main novelty of our normalizing flow model is that it can learn the conditional distribution of the state, i.e., the distribution of the final state conditional on any initial state, such that the model only needs to be trained once and the trained model can be used to handle various initial distributions. This feature can provide a significant computational saving in studies of how the final state varies with the initial distribution. Additionally, we propose to use a pseudoreversible network architecture to define the normalizing flow model, which has sufficient expressive power and training efficiency for a variety of SDEs in science and engineering, e.g., in particle physics. We provide a rigorous convergence analysis of the pseudoreversible normalizing flow model to the target probability density function in the Kullback--Leibler divergence metric. Numerical experiments are provided to demonstrate the effectiveness of the proposed normalizing flow model. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the safety and value of hyperpolarized (HP) MRI of [1-13C]pyruvate in healthy volunteers using deuterium oxide (D2O) as a solvent. Methods: Healthy volunteers (n=5), were injected with HP [1-13C]pyruvate dissolved in D2O and imaged with a metabolite-specific 3D dual-echo dynamic EPI sequence at 3T at one site (Site 1). Volunteers were monitored following the procedure to assess safety. Image characteristics, including SNR, were compared to data acquired in a separate cohort using water as a solvent (n=5) at another site (Site 2). The apparent spin-lattice relaxation time (T1) of [1-13C]pyruvate was determined both in vitro and in vivo from a mono-exponential fit to the image intensity at each time point of our dynamic data. Results: All volunteers completed the study safely and reported no adverse effects. The use of D2O increased the T1 of [1-13C]pyruvate from 66.5±1.6 s to 92.1±5.1 s in vitro, which resulted in an increase in signal by a factor of 1.46±0.03 at the time of injection (90 s after dissolution). The use of D2O also increased the apparent relaxation time of [1-13C]pyruvate by a factor of 1.4±0.2 in vivo. After adjusting for inter-site SNR differences, the use of D2O was shown to increase image SNR by a factor of 2.6±0.2 in humans. Conclusions: HP [1-13C]pyruvate in D2O is safe for human imaging and provides an increase in T1 and SNR that may improve image quality. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the clinical efficacy of suspension training and Mulligan technique in combination with celecoxib in the management of chronic lower back ache of unknown causes. Methods: A total of 100 subjects with persistent lower back pain of unknown etiology treated in the Sports Medical Rehabilitation Center, Shijiazhuang, China from June 2019 to December 2020, were assigned at random to control and study cohorts (n = 50/group). Celecoxib (100 to 200 mg/day) was taken orally, once or twice daily by the control cohort, while the other cohort received suspension training, Mulligan technology (once a day, 8 weeks) and celecoxib. The treatment effect, pain and dysfunction scores, inflammatory indicators, quality of life, and complications were compared on Visual Analogue Scale (VAS) and Oswestry Disability Index (ODI). Results: The effect of Macnab standard in study group was significantly better than that in control group (p < 0.05). After treatment, VAS and ODI scores in both cohorts were significantly lower than pretreatment values, but were significantly lesser in the study cohort. Furthermore, TNF-a level, and levels of CRP and IL-6 were significantly reduced when compared with pre-treatment levels, and were significantly lower in study cohort. The GQOL-74 scores in both groups were significantly increased after treatment, but were significantly lower in the control cohort (p < 0.05). No significant variations were seen in cases of complications between both cohorts. Conclusion: The use of suspension training and Mulligan technology in combination with celecoxib in treating persistent lower back pain of unknown cause is beneficial in reducing lower back pain, mitigating dysfunction, and improving patients' quality of life. There is however a need for more studies to validate these findings. [ABSTRACT FROM AUTHOR]

This work presents a probabilistic scheme for solving semilinear nonlocal diffusion equations with volume constraints and integrable kernels. The nonlocal model of interest is defined by a time-dependent semilinear partial integro-differential equation (PIDE), in which the integrodifferential operator consists of both local convection-diffusion and nonlocal diffusion operators. Our numerical scheme is based on the direct approximation of the nonlinear Feynman-Kac formula that establishes a link between nonlinear PIDEs and stochastic differential equations. The exploitation of the Feynman-Kac representation avoids solving dense linear systems arising from nonlocal operators. Compared with existing stochastic approaches, our method can achieve first-order convergence after balancing the temporal and spatial discretization errors, which is a significant improvement of existing probabilistic/stochastic methods for nonlocal diffusion problems. Error analysis of our numerical scheme is established. The effectiveness of our approach is shown in two numerical examples. The first example considers a three-dimensional nonlocal diffusion equation to numerically verify the error analysis results. The second example presents a physics problem motivated by the study of heat transport in magnetically confined fusion plasmas. [ABSTRACT FROM AUTHOR]

Due to the curse of dimensionality and the limitation on training data, approximating high-dimensional functions is a very challenging task even for powerful deep neural networks. Inspired by the Nonlinear Level-set Learning (NLL) method, which uses the reversible residual network (RevNet), in this paper, we propose a new method of Dimension Reduction via Learning Level Sets (DRiLLS) for function approximation. Our method contains two major components: one is the pseudoreversible neural network (PRNN) module, which effectively transforms high-dimensional input variables to low-dimensional active variables, and the other is the synthesized regression module for approximating function values based on the transformed data in the low-dimensional space. The PRNN not only relaxes the invertibility constraint of the nonlinear transformation present in the NLL method due to the use of RevNet but also adaptively weights the influence of each sample and controls the sensitivity of the function to the learned active variables. The synthesized regression uses Euclidean distance in the input space to select neighboring samples whose projections on the space of active variables are used to perform local least-squares polynomial fitting. This helps to resolve numerical oscillation issues present in traditional local and global regressions. Extensive experimental results demonstrate that our DRiLLS method outperforms both the NLL and active subspace methods, especially when the target function possesses critical points in the interior of its input domain. [ABSTRACT FROM AUTHOR]

The emergence of halide perovskites (HPs) has attracted significant research interest due to their fascinating optoelectronic properties, such as superior absorption coefficient, tunable emission, and high color purity. With the laboratory scale perovskite solar cell or display efficiency rapidly approaching the commercial application level, there is an urgent need for scalable and patterned fabrication suitable for future commercialization. Inkjet printing (IJP), a maskless, noncontact, and material-effective technique, is the most promising candidate, and remarkable results have been achieved although IJP has only been recently employed in the fabrication of perovskite optoelectronic devices. Herein, we discuss different IJP techniques and analyze the four factors required to achieve stable printing, high resolution and good morphology of perovskites: ink design, droplet formation, evaporation, and nucleation/crystallization control. Then we summarize the recent progress in printed perovskite optoelectronic devices, including solar cells, light emitting diodes, and visible/X-ray photodetectors. Finally, a brief summary and an outlook on device performance improvement, industrial-scale fabrication, and broader application are presented as future research efforts. [ABSTRACT FROM AUTHOR]

This work aims to explore the risk factors of lung metastasis (LM) in differentiated thyroid cancer (DTC) (LM-DTC) and the effect of treatment and to detect the relationship between LM-DTC and the levels of matrix metalloproteinase-13 (MMP-13) and micro ribonucleic acid (RNA)-142 (miR-142) in peripheral blood. The data of 420 patients with DTC who are admitted from March 2020 to December 2021 are collected and divided into a non-metastasis group (non-LM group) of 400 cases and metastasis group (LM group) of 20 cases according whether the mung metastasis is found. In addition, risk factors of LM-DTC are analysed and compared. The results of multivariate logistic analysis show that age, disease course, and imaging timing are independent in=uencing factors of the radionuclide treatment effect. Follicular carcinoma, abnormal expressions of MMP-13, and miR-142 can increase the risk of LM-DTC. MMP-13 and miR-142 can be undertaken as auxiliary diagnostic biological indicators. [ABSTRACT FROM AUTHOR]

The impressive expressive power of deep neural networks (DNNs) underlies their widespread applicability. However, while the theoretical capacity of deep architectures is high, the practical expressive power achieved through successful training often falls short. Building on the insights gained from Neural ODEs, which explore the depth of DNNs as a continuous variable, in this work, we generalize the traditional fully connected DNN through the concept of continuous width. In the Generalized Deep Neural Network (GDNN), the traditional notion of neurons in each layer is replaced by a continuous state function. Using the finite rank parameterization of the weight integral kernel, we establish that GDNN can be obtained by employing the Integral Activation Transform (IAT) as activation layers within the traditional DNN framework. The IAT maps the input vector to a function space using some basis functions, followed by nonlinear activation in the function space, and then extracts information through the integration with another collection of basis functions. A specific variant, IAT-ReLU, featuring the ReLU nonlinearity, serves as a smooth generalization of the scalar ReLU activation. Notably, IAT-ReLU exhibits a continuous activation pattern when continuous basis functions are employed, making it smooth and enhancing the trainability of the DNN. Our numerical experiments demonstrate that IAT-ReLU outperforms regular ReLU in terms of trainability and better smoothness. [ABSTRACT FROM AUTHOR]

Polycyclic aromatic hydrocarbons (PAHs) are environmental pollutants generated from the incomplete combustion of organic material. PAHs have been studied as genotoxicants, but some also act via non-genotoxic mechanisms in estrogen-dependent malignancies, such as breast cancer. PAHs require metabolic activation to electrophilic metabolites to exert their genotoxicity but non-genotoxic properties may also contribute to their carcinogenicity. The role of PAHs in endometrial cancer, a cancer associated with unopposed estrogen action is unknown. We assessed the metabolism of the representative PAH, benzo[a]pyrene (B[a]P), to estrogenic compounds in Ishikawa human endometrial cells in the presence and absence of cytochrome P450 induction. Using stable-isotope dilution high-performance liquid chromatography and APCI tandem mass spectrometry in the selected reaction monitoring mode, we analyzed B[a]P metabolism in Ishikawa cells. Estrogenic activity of B[a]P metabolites was determined by the endogenous estrogen inducible alkaline phosphatase reporter gene and an exogenous estrogen response element (ERE) luciferase reporter gene construct. We also assessed whether PAHs can induce a proliferative phenotype via estrogen receptor (ER)- and non-ER-regulated pathways. We demonstrate that B[a]P can be metabolized in human endometrial cells into 3-OH-B[a]P and B[a]P-7,8-dione in sufficient amounts to activate ERs. We also show that only B[a]P-7,8-dione induces endometrial cell proliferation at concentrations lower than required to activate the ER; instead nongenomic signaling by the EGF receptor (EGFR) and activation of the mitogen-activated protein kinase (MAPK) pathway was responsible. This work indicates that human endometrial cells can metabolize PAHs into estrogenic metabolites, which may induce cell proliferation through non-ER-regulated pathways. [ABSTRACT FROM AUTHOR]

The long noncoding RNA nuclear paraspeckle assembly transcript 1 (NEAT1) is involved in a variety of human cancers. Two overlapping NEAT1 isoforms, NEAT1_1 and NEAT1_2, are produced through mutually exclusive alternative 30 end formation. Previous studies extensively investigated NEAT1 dysregulation in tumors, but often failed to achieve distinct quantification of the two NEAT1 isoforms. Moreover, molecular mechanisms governing the biogenesis of NEAT1 isoforms and the functional impacts of their dysregulation in tumorigenesis remain poorly understood. In this study, we employed an isoform-specific quantification assay and found differential dysregulation of NEAT1 isoforms in patient-derived glioblastoma multiforme cells. We further showed usage of the NEAT1 proximal polyadenylation site (PAS) is a critical mechanism that controls glioma NEAT1 isoform production. CRISPRCas9–mediated PAS deletion reduced NEAT1_1 and reciprocally increased NEAT1_2, which enhanced nuclear paraspeckle formation in human glioma cells. Moreover, the utilization of the NEAT1 PAS is facilitated by the RNA-binding protein quaking (QKI), which binds to the proximal QKI recognition elements. Functionally, we identified transcriptomic changes and altered biological pathways caused by NEAT1 isoform imbalance in glioma cells, including the pathway for the regulation of cell migration. Finally, we demonstrated the forced increase of NEAT1_2 upon NEAT1 PAS deletion is responsible for driving glioma cell migration and promoting the expression of genes implicated in the regulation of cell migration. Together, our studies uncovered a novel mechanism that regulates NEAT1 isoforms and their functional impacts on the glioma transcriptome, which affects pathological pathways of glioma, represented by migration. [ABSTRACT FROM AUTHOR]

We developed a domain decomposition model reduction method for linear steadystate convection-diffusion equations with random coefficients. Of particular interest to this effort are the diffusion equation with random diffusivity and the convection-dominated transport equation with random velocity. We investigated two types of random fields, i.e., colored noises and discrete white noises, both of which can lead to high-dimensional parametric dependence in practice. The motivation is to exploit domain decomposition to reduce the parametric dimension of local problems in subdomains, such that an entire parametric map can be approximated with a small number of expensive partial differential equation (PDE) simulations. The new method combines domain decomposition with model reduction and sparse polynomial approximation, so as to simultaneously handle the high dimensionality and irregular behavior of the PDEs under consideration. The advantages of our method lie in three aspects: (i) online-offline decomposition, i.e., the online cost is independent of the size of the triangle mesh; (ii) sparse approximation of operators involving nonaffine high-dimensional random fields; (iii) an effective strategy to capture irregular behaviors, e.g., sharp transitions of the PDE solutions. Two numerical examples are provided to demonstrate the advantageous performance of our method. [ABSTRACT FROM AUTHOR]

This work proposes a hyperspherical sparse approximation framework for detecting jump discontinuities in functions in high-dimensional spaces. The need for a novel approach results from the theoretical and computational inefficiencies of well-known approaches, such as adaptive sparse grids, for discontinuity detection. Our approach constructs the hyperspherical coordinate representation of the discontinuity surface of a function. Then sparse approximations of the transformed function are built in the hyperspherical coordinate system, with values at each point estimated by solving a one-dimensional discontinuity detection problem. Due to the smoothness of the hypersurface, the new technique can identify jump discontinuities with significantly reduced computational cost, compared to existing methods. Several approaches are used to approximate the transformed discontinuity surface in the hyperspherical system, including adaptive sparse grid and radial basis function interpolation, discrete least squares projection, and compressed sensing approximation. Moreover, hierarchical acceleration techniques are also incorporated to further reduce the overall complexity. Rigorous complexity analyses of the new methods are provided, as are several numerical examples that illustrate the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

A significant challenge in realizing the promise of the dissolution dynamic nuclear polarization technique for signal enhancement in high-resolution NMR lies in the nonrenewability of the hyperpolarized spin state. This property prevents the application of traditional two-dimensional correlation spectroscopy, which relies on regeneration of spin polarization before each successive increment of the indirect dimension. Since correlation spectroscopy is one of the most important approaches for the identification and structural characterization of molecules by NMR, it is important to find easily applicable methods that circumvent this problem. Here, we introduce the application of scaling of heteronuclear couplings by optimal tracking (SHOT) to achieve this goal. SHOT decoupling pulses have been numerically optimized on the basis of optimal control algorithms to obtain chemical shift correlations in C–H groups, either by acquiring a single one-dimensional 13C spectrum with ¹H off-resonance decoupling or vice versa. Vanillin, which contains a number of functional groups, was used as a test molecule, allowing the demonstration of SHOT decoupling tailored toward simplified and accurate data analysis. This strategy was demonstrated for two cases: First, a linear response to chemical shift offset in the correlated dimension was optimized. Second, a pulse with alternating linear responses in the correlated dimension was chosen as a goal to increase the sensitivity of the decoupling response to the chemical shift offset. In these measurements, error ranges of ±0.03 ppm for the indirectly determined ¹H chemical shifts and of ±0.4 ppm for the indirectly determined 13C chemical shifts were found. In all cases, we show that chemical shift correlations can be obtained from information contained in a single scan, which maximizes the ratio of signal to stochastic noise. Furthermore, a comprehensive discussion of the robustness of the method toward nonideal conditions is included based on experimental and simulated data. Unique features of this technique include the abilities to control the accuracy of chemical shift determination in spectral regions of interest and to acquire such chemical shift correlations rapidly—the latter being of interest for potential application in real-time spectroscopy. [ABSTRACT FROM AUTHOR]

In this paper we propose a new type of θ-scheme with four parameters ({θi}4 i=1) for solving the backward stochastic differential equation -dyt = f(t, yt, zt)dt - ztdWt. We rigorously prove some error estimates for the proposed scheme, and in particular, we show that accuracy of the scheme can be high by choosing proper parameters. Various numerical examples are also presented to verify the theoretical results. [ABSTRACT FROM AUTHOR]

Objective: To study the effects of Ringer's sodium pyruvate solution on tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) upon septic shock., Methods: Ninety emergency patients with septic shock were divided into a treatment group and a control group by random draw. The control group was resuscitated with 50 ml of compound sodium chloride (Ringer's solution), and the treatment group was given 50 ml of Ringer's sodium pyruvate solution. Both groups were basically treated., Results: All patients were successfully resuscitated. After treatment, extravascular lung water index, intrathoracic blood volume index, systemic vascular resistance index and cardiac index of the two groups were significantly improved compared with those before treatment (P<0.05). However, there were no significant inter-group differences at different time points (P>0.05). Blood lactic acid level, central venous oxygen saturation index and urine output were also improved after treatment, with significant inter-group differences (P<0.05). Serum TNF-α and IL-6 levels of both groups significantly decreased after treatment (P<0.05), and the levels of the treatment group were significantly lower than those of the control group (P<0.05). During 28 days of follow-up, the mortality rate of the treatment group (4.4%) was significantly lower than that of the control group (20.0%) (P<0.05)., Conclusion: Patients with septic shock are complicated with disordered expressions of inflammatory factors. During resuscitation, Ringer's sodium pyruvate solution can effectively promote blood circulation, mitigate inflammation and maintain acid-base equilibrium, thus decreasing the prognostic mortality rate.