bluuebunny/crossref_metadata_2025_split huggingface dataset:
Zero-dispersion soliton and broadband modulational instability Kerr microcombs in anomalous dispersion
Authors: Wu Kan , Xiao Zeyu , Li Tieying , Cai Minglu , Zhang Hongyi , Huang Yi , Li Chao , Yao Baicheng , Chen Jianping 
Published: August 2022

Abstract
The developing advances of microresonator-based Kerr cavity solitons have enabled versatile applications ranging from communication, signal processing to high-precision measurements. Resonator dispersion is the key factor determining the Kerr comb dynamics. Near the zero group-velocity-dispersion (GVD) region, low-noise and broadband microcomb sources are achievable, which is crucial to the application of the Kerr soliton. When the GVD is almost vanished, higher-order dispersion can significantly affect the Kerr comb dynamics. Although many studies have investigated the Kerr comb dynamics near the zero-dispersion region in microresonator or fiber ring system, limited by dispersion profiles and dispersion perturbations, the zero-dispersion soliton structure in the anomalous dispersion region is still elusive so far. Here, we theoretically and experimentally investigate the microcomb dynamics in fiber-based Fabry-Perot microresonator with ultra-small anomalous GVD. We obtain 2/3-octave-spaning microcombs with ~ 10 GHz spacing, > 84 THz span and > 8400 comb lines in the modulational instability (MI) state, without any external nonlinear spectral broadening. Such widely-spanned MI combs are also able to enter the soliton state. Moreover, we report the first observation of anomalous-dispersion based zero-dispersion solitons, which exhibits a local repetition rate up to 8.6 THz, an individual pulse duration < 100 fs, a span > 32 THz and > 3200 comb lines. These two distinct comb states have their own advantages. The broadband MI combs possess high conversion efficiency and wide existing range, while the zero-dispersion soliton exhibits the low phase noise and ultra-high local repetition rate. This work complements the dynamics of Kerr cavity soliton near the zero-dispersion region, and may stimulate cross-disciplinary inspirations ranging from dispersion-controlled microresonators to broadband coherent comb devices.
Fast Estimation and Choice of Confidence Interval Methods for Step Regression
Authors: Hua Shuangcheng , Fong Youyi , Kath Jarrod 
Published: August 2022

Abstract
In this paper we propose a new fast grid search algorithm for finding the least square estimators of a step regression model. This algorithm makes it practical to compute resampling-based confidence intervals for step regression models. We introduce five data generating models, including one where the mean model is a step model (model correctly specified) and four where the mean models are not step models (model misspecified), and use them to study the coverage probabilities of two new types of resampling-based confidence intervals for step regression: symmetric percentile bootstrap confidence intervals and subsampling confidence intervals using a new set of rules-of-thumb to select block size. Our results show that when the model is correctly specified, the symmetric percentile Efron bootstrap confidence intervals provide close-to-nominal coverage and have shorter intervals than the subsampling methods; when the model is misspecified, the subsampling method using the rules-of-thumb provides good coverage and shorter confidence intervals than the symmetric percentile Efron bootstrap method and the subsampling method using a double bootstrap-like procedure for block size selection. Finally, we apply the proposed methods to a real world environmental dataset on the relationship between grassland productivity, soil moisture anomalies and other hydro-climatic and land use variables to provide inference for the threshold in soil moisture anomalies, across which there is a jump in grassland productivity.
Thuja orientalis folium protects against Influenza A virus via inhibition of hemagglutinin and viral binding at early stage
Authors: Lee Myong-Min , Yang Hye Jin , Yim Nam-Hui , Cho Won-Kyung , Ma Jin Yeul 
Published: August 2022

Abstract
Background: Morbidity and mortality as a result of influenza is an ongoing global health issue. Macrophages are part of the immune defense mechanism, as they play a role in the inflammatory response that blocks viral replication. Thuja orientalis Folium (TOF) has been prescribed traditionally as an expectorant for inflammatory airway disease. In this investigation, we have assessed the anti-viral properties of TOF water extract on the infectivity of the influenza A (H1N1) virus in RAW 264.7 macrophages.Method: We assessed the ability of GFP-tagged influenza A virus (A/PR/8/34-GFP) to infect murine macrophages. To determine the potential of antiviral activity using Fluorescence-activated cell sorting (FACS), fluorescent microscopy with green fluorescent protein (GFP)-tagged Influenza A/PR/8/34 virus. Hemagglutination inhibition assay, Western blotting, and Immunofluorescence analyses were performed to find the target protein. To investigate which stage of viral infection is associated with the TOF antiviral impact, we evaluated viral infection at three stages: attachment, entry, and virucidal in the presence of TOF.Results: FACS and immunofluorescence analyses results showed that TOF significantly inhibited viral infection and 100 μg/mL of TOF repressed that up to 98% of untreated control. Consistently, Western blot and immunofluorescence analyses against the influenza viral protein confirmed the TOF extract reduced the influenza viral protein expression in a dose-dependent manner. Time of addition and hemagglutination assays elucidated that TOF suppresses influenza A viral infection at early stages and interfere with HA protein.Conclusion: The TOF extract was thus found to exhibit inhibitory effects on influenza virus infection by inhibiting hemagglutination, blocking viral attachment and entry, and through virucidal effects. Based on our results, TOF may be a potential natural resource that could be utilized to develop an antiviral reagent.
Detection of SARS-CoV-2 IgA and IgG in human milk and breastfeeding infant stool 6 months after maternal COVID-19 vaccination
Authors: Stafford Lauren , Valcarce Vivian , Henry Matthew , Neu Josef , Parker Leslie , Martina Mueller , Vicuna Valeria , Gowen Taylor , Cato Emilee , Kosik Ivan , Yewdell Jonathan , Atkinson Mark , Cacho Nicole , Li Nan , Larkin Joseph 
Published: August 2022

Abstract
Objective Assess the presence, durability, and neutralization capacity of SARS-CoV-2-specific antibodies in breastfeeding infants’ stools, mother’s plasma, and human milk following maternal vaccination.DesignThirty-seven mothers and 25 infants were enrolled between December 2020 and November 2021 for this prospective observational study. Human milk, maternal plasma, and infants' stools were collected pre-vaccination and at periods up to 6 months following COVID-19 vaccine series initiation/completion. SARS-CoV-2 antibody levels and their neutralization capacities were assessed in collected samples. Results SARS-CoV-2-specific IgA and IgG levels were higher in infant stool post-maternal vaccination amongst milk-fed compared to pre-COVID controls. Human milk and plasma SARS-CoV-2-specific IgA and IgG concentrations decreased over 6 months post-vaccination but remained higher than pre-vaccination levels. We observed improved neutralization capacity in milk antibodies over time.ConclusionsThe presence of neutralizing SARS-CoV-2-specific antibodies in infant stool following maternal vaccination offers further evidence of the lasting transfer of these antibodies through breastfeeding and their protective effect.
Differentiation of Pancreatic Ductal Adenocarcinoma and Chronic Pancreatitis using Graph Neural Networks on Histopathology and Collagen Fiber Features
Authors: Li Bin , Nelson Michael , Savari Omid , Loeffler Agnes , Eliceiri Kevin 
Published: August 2022

Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal human cancers. However, the symptoms and follow-up radiographic and histopathology assessments of PDAC are similar to chronic pancreatitis (CP) and can lead to misdiagnosis. The need for accurate differentiation of PDAC and CP has become a major topic in pancreatic pathology. These two diseases can present similar histomorphological features, such as excessive deposition of fibrotic stroma in the tissue microenvironment and inflammatory cell infiltration. In this paper, we present a quantitative analysis pipeline empowered by graph neural networks (GNN) capable of automatic detection and differentiation of PDAC and CP in human histological specimens. Modeling histological images as graphs and deploying graph convolutions can enable the capture of histomorphological features at different scales, ranging from nuclear size to the organization of ducts. The analysis pipeline combines image features computed from co-registered hematoxylin and eosin (H&E) images and Second-Harmonic Generation (SHG) microscopy images, with the SHG images enabling the extraction of collagen fiber morphological features. Evaluating the analysis pipeline on a human tissue micro-array dataset consisting of 786 cores and a tissue region dataset consisting of 268 images, it attained 86.4% accuracy with an average area under the curve (AUC) of 0.954 and 88.9% accuracy with an average AUC of 0.957, respectively. Moreover, incorporating topological features of collagen fibers computed from SHG images into the model further increases the classification accuracy on the tissue region dataset to 91.3% with an average AUC of 0.962, suggesting that collagen characteristics are diagnostic features in PDAC and CP detection and differentiation.
The Theory of Planned Behaviour as a predictor of intention to engage in BDSM and vanilla
Sex
Authors: Banbury Samantha , Sidorova Polina , Lusher Joanne , Nercessian Tiga Rose 
Published: August 2022

Abstract
The authors postulate that the Theory of Planned Behaviour (TPB) offers a hypothetically valuable framework for investigating Bondage, Discipline, Dominance, Submission and Sadomasochism (BDSM) and non-BDSM sexual behaviours, i.e. “vanilla” sex. This is because it examines attitudes, beliefs, subjective norms, intention, and perceived behavioural control over exhibited behaviours. Online cross-sectional data were gathered from participants classified as “BDSM” (n = 61) and “vanilla” (n = 41). Measures included the Theory of Planned Behaviour Questionnaire (TPB Constructs), as well as Anxiety (GAD–7), Depression (PHQ–9), and Self-Efficacy questionnaires. Findings revealed that the constructs of attitude towards vanilla sex predicts the person’s intention to engage in this behaviour (β = .42, p = .005). Similarly, perceived behavioural control predicts intention to engage in paraphilic or BDSM sex (β = .47, p < .001). This study concludes that the TPB is a useful model for predicting BDSM and vanilla sexual behavioural intention. Future research could uncover additional underlying determining or correlating factors associated with BDSM and vanilla sex, such as mental illness and childhood experiences. Having this understanding of the role that social cognition plays in the development and behaviour of different sexual practices, would benefit the development of sexual wellbeing programmes.
In which cases does collecting system entry occur in robot-assisted partial nephrectomy? Development of a novel predictive model based on the contact surface area of the tumor to the renal parenchyma
Authors: Umemoto Tatsuya , Hasegawa Masanori , Yuzuriha Soichiro , Kano Tatsuo , Ogawa Takahiro , Kawakami Masayoshi , Nakano Mayura , Kim Hakushi , Nitta Masahiro , Kawamura Yoshiaki , Shoji Sunao , Mizuno Ryuichi , Miyajima Akira 
Published: August 2022

Abstract
Background
Collecting system entry in robot-assisted partial nephrectomy may occur even in cases showing a low N factor in the R.E.N.A.L nephrometry score. Therefore, we focused on the tumor contact surface area with the adjacent renal parenchyma and attempted to construct a novel predictive model for collecting system entry.
Methods
Among 190 patients who underwent robot-assisted partial nephrectomy at our institution from 2015 to 2021, 94 patients with a low N factor (12) were analyzed. Contact surface was measured with three-dimensional imaging software and defined as the C factor, classified as C1, < 10 cm2; C2, ≥ 10 and < 15 cm2; and C3: ≥ 15 cm2. Additionally, a modified R factor (mR) was classified as mR1, < 20 mm; mR2, ≥ 20 and < 40 mm; and mR3, ≥ 40 mm. We discussed the factors influencing collecting system entry, including the C factor, and created a novel collecting system entry predictive model.
Results
Collecting system entry was observed in 32 patients with a low N factor (34%). The C factor was the only independent predictive factor for collecting system entry in multivariate regression analysis (odds ratio: 4.195, 95% CI: 2.160–8.146, p < 0.0001). Models including the C factor showed better discriminative power than the models without the C factor.
Conclusions
The new predictive model, including the C factor in N1-2 cases, may be beneficial, considering its indication for preoperative ureteral catheter placement in patients undergoing robot-assisted partial nephrectomy.
Development of optimized self nano emulsifying systems of entrectinib for enhanced dissolution
Authors: Reddy Muthadi Radhika , Gubbiyappa Kumar Shiva 
Published: August 2022

Abstract

Entrectinib is a novel potent anticancer drug with poor aqueous solubility. A supersaturable self nano emulsifying drug delivery system of entrectinib is developed using a super saturation promoter. The components of the isotropic mixture of SNEDDS were selected based on solubility and emulsification study. The optimum composition was identified using phase diagrams and further optimized by mixture design. The supersaturated SNEDDS was prepared using HPMC K4M as precipitation inhibitor. The droplet of sSNEDDS ranges from 118.42 ± 1.26 to 128.34 ± 0.63 nm with PDI values ranges from 0.112 to 0.204, which is significantly smaller than that observed with plain SNEDDS. The percent transmittance of the diluted formulation was found to be 98.78 ± 0.74. The viscosity was found to be 528 ± 32 centipoises indicating the good flow ability. FTIR and DSC studies indicated the amorphization of the drug. The dissolution profile of sSNEDDS indicated the faster release of drug compared to both pure drug suspension and SNEDDS formulation. The drug release rate is directly proportional to the concentration of the drug. The drug release from the insoluble matrix is a square root of time dependent Fickian diffusion process. The formulation was found to be stable and transparent at all pH values and the percent transmittance was more than 95%. No significant difference was observed with all the samples exposed at different storage conditions. This study demonstrated the feasibility of stabilizing and improving the in-vitro performance of SNEDDS by incorporating HPMC K4M as precipitation inhibitor.
Unsupervised Deep Learning of Bright Field Images for Apoptotic Cell Classification
Authors: Zheng Zhuo , Sun Beini , He Siqi , Wang Guanchen , Bi Chenyang , Chen Tongsheng 
Published: August 2022

Abstract
The classification of apoptotic and living cells is significant in drug screening and treating various diseases. Conventional supervised methods require a large amount of prelabelled data, which is often costly and consumes immense human resources in the biological field. In this study, unsupervised deep-learning algorithms were used to extract cell characteristics and classify cells. A model integrating a convolutional neural network and an auto-encoder network was utilised to extract cell characteristics, and a hybrid clustering approach was employed to obtain cell feature clustering results. Experiments on both public and private datasets revealed that the proposed unsupervised strategy performs well in cell categorisation. For instance, in the public dataset, our method obtained a precision of 96.72% on only 1000 unlabelled cells. To the best of our knowledge, this is the first time unsupervised deep learning has been applied to distinguish apoptosis and live cells with high accuracy.
Accidental acquisition of a JEV rescued virus with introns unspliced in the viral genome using intron-based stabilization approach
Authors: Huang Ying , Xu Hongshan , Liu Shan , Lu Jiansheng , Jia Lili , Li Yuhua , Wang Rong , Yu Yongxin , Yang Zhixin 
Published: August 2022

Abstract
The intron-based stabilization approach is a very useful strategy for construction of stable flavivirus infectious clones. SA14-14-2 is a highly attenuated Japanese encephalitis live vaccine and widely used in China. To develop safe and effective recombinant vaccines with SA14-14-2 as a backbone vector, we constructed the DNA-based infectious clone pCMW-JEV of the vaccine strain using the intron-based stabilization approach, and acquired the rescued virus rDJEV which retained the identical biological properties of the parental virus. Unexpectedly, a rescued virus strain, designated rHV-DJEV, with altered virulence was acquired in one of the transfection experiments. rHV-DJEV showed up to 105-fold increased neurovirulence compared with SA14-14-2 parental strain. Genome sequencing found that the inserted introns still existed in the genome of rHV-DJEV. Therefore, we think that the intron-based stabilization approach should be used carefully in vaccine development and direct iDNA immunization.
The Power Spectrum Of Primordial Gravitational Waves Generated by Anisotropic Metric
Authors: Mohammadi Taimur , Malekolkalami Behrooz 
Published: August 2022

Abstract
One of the predictions from simple inflation models is stochastic background of gravitational waves (or literally what is called Primordial Gravitational Waves (PGW)) with a nearly scale– invariant spectrum. To discuss a possible direct detection of PGW, the quantity so–called Spectral Energy Density (SED) has crucial role. In this work, we consider PGW amplified by inflation and generated by perturbing the Anisotropic (Bianchi type–I) metric. We focus on the SED quantity of these gravity waves. The intended frameworks are the Einstein’s and modified (pure quadratic Ricci scalar) gravities. The spectral graphs for SED shows that in Einstein’s gravity, the anisotropic model has the ability to adapt to the observational data (BBN bounds) and in the modified gravity, in addition to observational constraint adaptation, the scale–invariant character of the spectrum is much more pronounced.
Stable, reproducible, and binder-free gold/copper core-shell nanostructures for high-sensitive non-enzymatic glucose detection
Authors: Siampour Hossein , Abbasian Sara , Moshaii Ahmad , Amirsoleimani Amir R. 
Published: August 2022

Abstract
The core-shell non-enzymatic glucose sensors are generally fabricated by chemical synthesis approaches followed by a binder-based immobilization process. Here, we have introduced a new approach to directly synthesis the core-shell of Au@Cu and its Au@CuxO oxides on an FTO electrode for non-enzymatic glucose detection. Physical vapor deposition of Au thin film followed by thermal annealing has been used to fabricate Au nanocores on the electrode. The Cu shells have been deposited selectively on the Au cores using an electrodeposition method. Additionally, Au@Cu2O and Au@CuO have been synthesized via post thermal annealing of the Au@Cu electrode. This binder-free and selective-growing approach has the merit of high electrooxidation activity owing to improving electron transfer ability and providing more active sites on the surface. Electrochemical measurements indicate the superior activity of the Au@Cu2O electrode for glucose oxidation. The high sensitivity of 1601 μAcm-2mM-1 and a low detection limit of 0.6 μM are achieved for the superior electrode. Additionally, the sensor indicates remarkable reproducibility and supplies accurate results for glucose detection in human serums. Moreover, this synthesis approach can be used for fast, highly controllable and precise fabrication of many core-shell structures by adjusting the electrochemical deposition and thermal treatment parameters.
Effect Analysis of Different Environmental Disinfection Methods on Reducing Contamination of Surfaces of Omicron Ba.2.2 Variant of Sars-Cov-2 in the Fever Clinic in The Out- Broken of Shanghai
Authors: liu Tingliang , Dong Wenfang , Shen Xiaoyu , Han Feng , Liu Chenxi , Wang Yirou , Xu Xuemei , Wu Yufen , Zhou Sha , Cao Qing 
Published: August 2022

Abstract
To investigate the effect of different environmental disinfection methods on reducing contamination of surfaces (CSS) of omicron BA.2.2 of Sars-Cov-2 in the fever clinic between March 20 to May 30, 2022 and analyze influence and related factors of the CSS. This study includes survey data from 389 positive patients (SPP) and 204 CSS in the fever clinic including the CSS type, the disinfection method; the duration time in the clinic, CT value, name, age, weight, mask type and gender of the SPP. Associations between study variables and specified outcomes were explored using uni-variate regression analyses. Among the 389 SPP, 22 SPP (CRP, 5.66%) caused CSS in the separate isolation room. 219 SPP (56.30%) were male. The mean age of SPP was 4.34±3.92 years old and the mean CT value was 12.44±5.11. In total, sampling times with exposure history were 9952, including 204 (2.05%) of CSS. Among the CSS, the positive rate of flat surface is the highest in either public area (2.52%) or separate isolation room (4.75%). Disinfection methods of Ultraviolet radiation + Chemical can significantly reduce the CSS in either public area (0% vs 4.56%) or separate isolation room (0.76% vs 2.64%) compared with the chemical alone (P＜0.05). Compared with ordinary SPP, the CRP is older (6.04y vs 4.23y) and the male proportion is higher (72.73% vs 55.31%). In particular, it is found that SPP contaminated their surroundings and therefore imposed risks for other people. Environment disinfection should be emphasized in Ultraviolet radiation + Chemical. The findings may be useful to guide infection control practice to omicron BA.2.2 of Sars-Cov-2.
SSTR2 as an anatomical imaging marker and a safety switch to monitor and manage CAR T cell toxicity
Authors: Alcaina Yago , Yang Yanping , Vedvyas Yogindra , McCloskey Jaclyn E. , Jin Moonsoo M. 
Published: August 2022

AbstractThe ability to image adoptively transferred T cells in the body and to eliminate them to avoid toxicity will be vital for chimeric antigen receptor (CAR) T cell therapy, particularly against solid tumors with higher risk of off-tumor toxicity. Previously, we have demonstrated the utility of somatostatin receptor 2 (SSTR2) for CAR T cell imaging, illustrating the expansion and contraction of CAR T cells in tumor as well as off-tumor expansion. Using intercellular adhesion molecule 1-specific CAR T cells that secrete interleukin 12 (IL-12) as a model, herein we examined the potential of SSTR2 as a safety switch when combined with the SSTR2-specific maytansine-octreotate conjugate PEN-221. After rapid elimination of tumors, constitutive secretion of IL-12 led to continuous expansion of CAR T cells, causing systemic toxicity and elevated graft-versus-host disease (GvHD). Treatment with PEN-221 rapidly reduced the abundance of CAR T cells, decreasing the severity of toxicity and GvHD, and led to elongated survival. Our study supports the development of SSTR2 as a single genetic marker for CAR T cells that is readily applicable to humans both for anatomical detection of T cell distribution and an image-guided safety switch for rapid elimination of CAR T cells.