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The cystic fibrosis transmembrane conductance regulator (CFTR), a cAMP-dependent Cl− channel, is closely associated with multiple pathogen infections, such as SARS-CoV-2. However, whether the function of the CFTR is involved in herpes simplex virus (HSV) infection has not been reported. To evaluate the association of CFTR activity with HSV infection, the antiviral effect of CFTR inhibitors in epithelial cells and HSV-infected mice was tested in this study. The data showed that treatment with CFTR inhibitors in different concentrations, Glyh-101 (5–20 μM), CFTRi-172 (5–20 μM) and IOWH-032 (5–20 μM), or the gene silence of the CFTR could suppress herpes simplex virus 1 (HSV-1) and herpes simplex virus 2 (HSV-2) replication in human HaCaT keratinocytes cells, and that a CFTR inhibitor, Glyh-101 (10–20 μM), protected mice from HSV-1 and HSV-2 infection. Intracellular Cl− concentration ([Cl−]i) was decreased after HSV infection via the activation of adenylyl cyclase (AC)-cAMP signaling pathways. CFTR inhibitors (20 μM) increased the reduced [Cl−]i caused by HSV infection in host epithelial cells. Additionally, CFTR inhibitors reduced the activity and phosphorylation of SGK1 in infected cells and tissues (from the eye and vagina). Our study found that CFTR inhibitors can effectively suppress HSV-1 and HSV-2 infection, revealing a previously unknown role of CFTR inhibitors in HSV infection and suggesting new perspectives on the mechanisms governing HSV infection in host epithelial cells, as well as leading to potential novel treatments. [ABSTRACT FROM AUTHOR]

In the mechanized harvesting of Lycium barbarum L. (L. barbarum), there are prominent problems such as low harvesting efficiency, high damage rate, incomplete separation of leaves and delayed transportation. Therefore, an integrated L. barbarum harvester was designed and developed in this study, which has the functions of picking, undertaking, transportation, winnowing and collection. The design requirements and constraints were identified by cultivation agronomy. Through simulation and physical tests, the tarpaulin was determined as the undertaking material. This machine achieved efficient picking with a vibrating picker with a multi-degree-of-freedom picking arm. The two-stage conveyor belts and the intermediate receiving plate were designed for low loss transportation of fruit. The axial flow fan and secondary buffer device were used to realize winnowing and reduce the damage rate. Through the three-factor and three-level orthogonal test, an optimal working parameter combination was determined: the vibration frequency of the picker was 20 Hz, the conveyor speed was 4 m/min, the airflow speed of the fan was 7 m/s. A field test was conducted under these parameters, and the results showed that the harvesting efficiency was about five times that of manual harvesting. The integrated L. barbarum harvester basically met the harvesting requirements and provided a new scheme for mechanized harvesting. [ABSTRACT FROM AUTHOR]

Speckle noise and the spatial resolution of the Sentinel−1 Synthetic Aperture Radar (SAR) image can cause significant difficulties in the detection of small objects, such as small ships. Therefore, in this study, the Polarimetric Combination-based Ship Detection (PCSD) approach is proposed for enhancing small ship detection performance, which combines three different characteristics of polarization: newVH, enhanced VH, and enhanced VV. Employing the Radar Cross Section (RCS) value in three stages, the newVH was utilized to detect Automatic Identification System (AIS) -ships and small ships. In the first step, the adaptive threshold (AT) method was applied to newVH with a high RCS condition (>−10.36 (dB)) for detecting AIS-ships. Secondly, the first small ship target was detected with the maximum suppression of false alarms by using the AT with a middle RCS condition (>−16.98 (dB)). In the third step, a candidate group was identified by applying a condition to the RCS values (>−23.01 (dB)), where both small ships and speckle noise were present simultaneously. Subsequently, the enhanced VH and VV polarizations were employed, and an optimized threshold value was selected for each polarization to detect the second small ship while eliminating noise pixels. Finally, the results were evaluated using the AIS and small fishing vessel tracking system (V-Pass) based on the detected ship positions and ship lengths. The average matching results from 26 scenes in 2022 indicated a matching rate of over 86.67% for AIS-ships. Regarding small ships, the detection performance of PCSD was 42.27%, which was over twice as accurate as the previous Constant False Alarm Rate (CFAR) ship detection model. As a result, PCSD enhanced the detection rate of small ships while maintaining the capacity for detecting AIS-equipped ships. [ABSTRACT FROM AUTHOR]

Background and Objectives: Ascites, often associated with liver cirrhosis, poses diagnostic challenges, particularly in detecting bacterial infections. Traditional methods have limitations, prompting the exploration of advanced techniques such as 16S rDNA next-generation sequencing (NGS) for improved diagnostics in such low-biomass fluids. The aim of this study was to investigate whether the NGS method enhances detection sensitivity compared to a conventional ascites culture. Additionally, we aimed to explore the presence of a microbiome in the abdominal cavity and determine whether it has a sterile condition. Materials and Methods: Ten patients with clinically suspected spontaneous bacterial peritonitis (SBP) were included in this study. A traditional ascites culture was performed, and all ascites samples were subjected to 16S ribosomal RNA gene amplification and sequencing. 16S rRNA gene sequencing results were interpreted by comparing them to positive and negative controls for each sample. Results: Differential centrifugation was applied to all ascites samples, resulting in very small or no bacterial pellets being harvested. The examination of the 16S amplicon sequencing libraries indicated that the target amplicon products were either minimally visible or exhibited lower intensity than their corresponding negative controls. Contaminants present in the reagents were also identified in the ascites samples. Sequence analysis of the 16S rRNA gene of all samples showed microbial compositions that were akin to those found in the negative controls, without any bacteria isolated that were unique to the samples. Conclusions: The peritoneal cavity and ascites exhibit low bacterial biomass even in the presence of SBP, resulting in a very low positivity rate in 16S rRNA gene sequencing. Hence, the 16S RNA sequencing method does little to enhance the rate of positive samples compared to traditional culture methods, including in SBP cases. [ABSTRACT FROM AUTHOR]

Simple Summary: The authors conducted this research to improve the prediction of how patients with esophageal cancer respond to a treatment called neoadjuvant chemoradiotherapy, which can enhance survival rates. However, doctors struggle to accurately predict how well a patient will respond to this treatment using existing imaging methods. To address this, the researchers developed a computer-based method called DCRNet, that not only analyzes medical images but also considers the distribution of radiation therapy doses on the radiotherapy treatment plans to make more accurate predictions. They tested this method on 80 patients with esophageal cancer and found that the HRNetV2p model with DCR performed the best, significantly improving prediction accuracy compared to other models. This breakthrough has the potential to help doctors better anticipate patient responses to treatment, which could lead to more personalized and effective care, and improving the treatment planning of radiotherapy. Esophageal cancer is a deadly disease, and neoadjuvant chemoradiotherapy can improve patient survival, particularly for patients achieving a pathological complete response (ypCR). However, existing imaging methods struggle to accurately predict ypCR. This study explores computer-aided detection methods, considering both imaging data and radiotherapy dose variations to enhance prediction accuracy. It involved patients with node-positive esophageal squamous cell carcinoma undergoing neoadjuvant chemoradiotherapy and surgery, with data collected from 2014 to 2017, randomly split into five subsets for 5-fold cross-validation. The algorithm DCRNet, an advanced version of OCRNet, integrates RT dose distribution into dose contextual representations (DCR), combining dose and pixel representation with ten soft regions. Among the 80 enrolled patients (mean age 55.68 years, primarily male, with stage III disease and middle-part lesions), the ypCR rate was 28.75%, showing no significant demographic or disease differences between the ypCR and non-ypCR groups. Among the three summarization methods, the maximum value across the CTV method produced the best results with an AUC of 0.928. The HRNetV2p model with DCR performed the best among the four backbone models tested, with an AUC of 0.928 (95% CI, 0.884–0.972) based on 5-fold cross-validation, showing significant improvement compared to other models. This underscores DCR-equipped models' superior AUC outcomes. The study highlights the potential of dose-guided deep learning in ypCR prediction, necessitating larger, multicenter studies to validate the results. [ABSTRACT FROM AUTHOR]

The macroalgal bloom (MAB) is caused by brown algae forming a floating mat. Most of its parts stay below the water surface, unlike green algae; thus, its backscatter value becomes weaker in the synthetic aperture radar (SAR) images, such as Sentinel−1, due to the dampening effect. Thus, brown algae patches appear to be thin strands in contrast to green algae and their detection by using a global threshold, which is challenging due to a similarity between the MAB patch and the ship's sidelobe in the case of pixel value. Therefore, a novel approach is proposed to detect the MAB from the Sentinel−1 image by eliminating the ship's sidelobe. An individually optimized threshold is applied to extract the MAB and the ships with sidelobes from the image. Then, parameters are adjusted based on the object's area information and the ratio of length and width to filter out ships with sidelobes and clutter objects. With this method, an average detection accuracy of 82.2% is achieved by comparing it with the reference data. The proposed approach is simple and effective for detecting the thin MAB patch from the SAR image. [ABSTRACT FROM AUTHOR]

Virtual corporate social responsibility co-creation (VCSRC) became an effective strategic tool with which enterprises can fulfill social responsibilities and retain customers. This study investigated the drivers of consumers' continuous participation in VCSRC based on online survey data collected from 336 VCSRC participants. From a new perspective of self-expansion theory and by integrating consumer engagement (CE), we constructed a theoretical model and proposed a set of hypotheses, which were tested by using the structural equation model (SEM). Our findings show that self-expansion (experience-based expansion, competence-based expansion, and identity-based expansion) has a significant positive impact on continuous participation, with CE (conscious attention, enthusiasm, and social connection) playing a partial mediating role. Our research not only theoretically contributes to the research on VCSRC and self-expansion theory, but also inspires the operation of VCSRC projects in motivating consumers' continuous participation. [ABSTRACT FROM AUTHOR]

The amount of data in the maritime domain is rapidly increasing due to the increase in devices that can collect marine information, such as sensors, buoys, ships, and satellites. Maritime data is growing at an unprecedented rate, with terabytes of marine data being collected every month and petabytes of data already being made public. Heterogeneous marine data collected through various devices can be used in various fields such as environmental protection, defect prediction, transportation route optimization, and energy efficiency. However, it is difficult to manage vessel related data due to high heterogeneity of such marine big data. Additionally, due to the high heterogeneity of these data sources and some of the challenges associated with big data, such applications are still underdeveloped and fragmented. In this paper, we propose the Vessel Data Lakehouse architecture consisting of the Vessel Data Lake layer that can handle marine big data, the Vessel Data Warehouse layer that supports marine big data processing and AI, and the Vessel Application Services layer that supports marine application services. Our proposed a Vessel Data Lakehouse that can efficiently manage heterogeneous vessel related data. It can be integrated and managed at low cost by structuring various types of heterogeneous data using an open source-based big data framework. In addition, various types of vessel big data stored in the Data Lakehouse can be directly utilized in various types of vessel analysis services. In this paper, we present an actual use case of a vessel analysis service in a Vessel Data Lakehouse by using AIS data in Busan area. [ABSTRACT FROM AUTHOR]

Acute myeloid leukemia (AML) is one of the most common hematological malignancies with high heterogeneity, characterized by a differentiating block at the early progenitor stage. The selective BCL-2 inhibitor, Venetoclax (Ven), has shown exciting clinical results in a certain group of AML patients. However, Ven alone is insufficient to reach an enduringly complete response, which leads to the concern of Ven resistance. Alternative combined therapies with Ven are demanded in AML. Here, we reported the synergistic effect and molecular mechanism of the enhancer of zeste homolog 2 (EZH2) inhibitor DZNeP with Ven in AML cells. Results showed that the combination of DZNeP with Ven significantly induces cell proliferation arrest compared to single-drug control in AML cells and primary samples, and CalcuSyn analysis showed their significant synergy. The combination also significantly promotes apoptosis and increases the expression of pro-apoptotic proteins. The whole transcriptome analysis showed that phosphoinositide-3-kinase-interacting protein1 (PIK3IP1), the PI3K/AKT/mTOR signaling suppressor, is upregulated upon DZNeP treatment. Moreover, EZH2 is upregulated but PIK3IP1 is downregulated in 88 newly diagnosed AML cohorts compared to 70 healthy controls, and a higher expression of EZH2 is associated with poor outcomes in AML patients. Particularly, the combination of DZNeP with Ven dramatically eliminated CD117 (c-KIT) (+) AML blasts, suggesting the effect of the combination on tumor stem cells. In summary, our data indicated that DZNeP increases the sensitivity of Ven in AML by affecting PI3K and c-KIT signaling in AML. Our results also suggested that the therapeutic targeting of both EZH2 and BCL-2 provides a novel potential combined strategy against AML. [ABSTRACT FROM AUTHOR]

At present, the barrier to HIV-1 functional cure is the persistence of HIV-1 reservoirs. The "shock (reversing latency) and kill (antiretroviral therapy)" strategy sheds light on reducing or eliminating the latent reservoir of HIV-1. However, the current limits of latency-reversing agents (LRAs) are their toxicity or side effects, which limit their practicability pharmacologically and immunologically. Our previous research found that HSF1 is a key transcriptional regulatory factor in the reversion of HIV-1 latency. We then constructed the in vitro HSF1-knockout (HSF1-KO) HIV-1 latency models and found that HSF1 depletion inhibited the reactivation ability of LRAs including salubrinal, carfizomib, bortezomib, PR-957 and resveratrol, respectively. Furthermore, bortezomib/carfizomib treatment induced the increase of heat shock elements (HSEs) activity after HSF1-KO, suggesting that HSEs participated in reversing the latent HIV-1. Subsequent investigation showed that latent HIV-1-reversal by H2O2-induced DNA damage was inhibited by PARP1 inhibitors, while PARP1 was unable to down-regulate HSF1-depleted HSE activity, indicating that PARP1 could serve as a replaceable protein for HSF1 in HIV-1 latent cells. In summary, we succeeded in finding the mechanisms by which HSF1 reactivates the latent HIV-1, which also provides a theoretical basis for the further development of LRAs that specifically target HSF1. [ABSTRACT FROM AUTHOR]

Researchers in the fields of psychology and sociology have demonstrated the profound influence of social status on people's behavior. Although existing studies show that social status matters, scholars have devoted little attention to how family social status affects individuals' risk-taking entrepreneurial behavior. In Chinese rural areas, where the idea of "family" is deeply embedded, how family social status affects farmers' entrepreneurial behavior is still an unsolved question. In this paper, we analyze the impact of family social status on farmer entrepreneurship and investigate the moderating effects of external institutional factors, such as regional policy uncertainty and local family culture. Our findings show that family social status has an important impact on farmers' risk preferences, therefore affecting their motivation to undertake entrepreneurial behaviors. By inspecting the role of social status at the family level, our study offers important implications for social class and entrepreneurial theorizing. [ABSTRACT FROM AUTHOR]

Objective: Healthcare workers and disaster service workers have been reported to be vulnerable to mental health problems during outbreaks of infectious diseases such as the COVID-19 pandemic. This study aimed to investigate the psychosocial characteristics of disaster service workers in charge of COVID-19-related work and also identify the factors affecting their quality of life. Methods: From June 2020 to June 2021, a survey was conducted of 526 disaster service workers in charge of COVID-19-related work. This included those working in public health care centers (PHC), 119 rescue and emergency medical services (119 REMS), public servants of city hall (PS), and police officers. The Korean version of the Fear of COVID-19 Scale, Patient Health Questionnaire-15, Hospital Anxiety and Depression Scale, Insomnia Severity Index, Connor–Davidson Resilience Scale, and World Health Organization quality of life assessment instrument brief form were used. A one-way ANOVA was conducted, and a stepwise regression analysis was carried out to determine the factors affecting quality of life. Results: Regarding quality of life, 119 REMS (180.64 ± 26.20) scored significantly higher than PHC (165.76 ± 23.73) and PS (163.90 ± 23.60), while police officers (176.87 ± 23.17) scored significantly higher than PS (163.90 ± 23.60) (F = 12.373, p < 0.001). Resilience (β = 0.897, p < 0.01) was the most significant explanatory variable, and together with insomnia (β = 0.154, p < 0.01), depression (β = −0.152, p < 0.01), and COVID-19 anxiety (β = −0.057, p < 0.01) accounted for 91.8% of the explanatory variance with regard to quality of life. Discussion: Quality of life was found to be negatively correlated with insomnia, depression, and COVID-19 anxiety while being positively correlated with resilience. Therefore, active interventions are needed to improve the resilience of disaster service workers. [ABSTRACT FROM AUTHOR]

The prolonged duration of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic has resulted in the continuous emergence of variants of concern (VOC, e.g., Omicron) and variants of interest (VOI, e.g., Lambda). These variants have challenged the protective efficacy of current COVID-19 vaccines, thus calling for the development of novel therapeutics against SARS-CoV-2 and its VOCs. Here, we constructed a novel fusion inhibitor-based recombinant protein, denoted as 5-Helix, consisting of three heptad repeat 1 (HR1) and two heptad repeat 2 (HR2) fragments. The 5-Helix interacted with the HR2 domain of the viral S2 subunit, the most conserved region in spike (S) protein, to block homologous six-helix bundle (6-HB) formation between viral HR1 and HR2 domains and, hence, viral S-mediated cell–cell fusion. The 5-Helix potently inhibited infection by pseudotyped SARS-CoV-2 and its VOCs, including Delta and Omicron variants. The 5-Helix also inhibited infection by authentic SARS-CoV-2 wild-type (nCoV-SH01) strain and its Delta variant. Collectively, our findings suggest that 5-Helix can be further developed as either a therapeutic or prophylactic to treat and prevent infection by SARS-CoV-2 and its variants. [ABSTRACT FROM AUTHOR]

For this study, we demonstrated three different types of twisted nematic (TN) liquid crystal (LC) terahertz (THz) phase shifters using pristine poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT: PSS) thin films as transparent conducting electrodes (TCEs). The transmittance of spin-coated pristine PEDOT: PSS thin film was as high as 92% in the frequency range of 0.2–1.2 THz. This is among the highest reported. Several TN-LC cells were constructed in a comparative study, which confirmed the reliability of pristine PEDOT: PSS as a TCE layer for THz phase shifter applications. The highest phase shift, required root-mean-square (RMS) driving voltage, and threshold voltage achieved by devices tested were 95.2° at 1 THz, 7.2 VRMS, and 0.5 VRMS, respectively. The thickness of the LC layer for the phase shifter was 250 µm, approximately half as thick as previous designs. In addition, the pristine PEDOT: PSS-based TN-LC phase shifter exhibited a figure-of-merit (FOM) value of approximately 6.65 degree·dB−1·V−1. This compared favorably with previously reported homogeneously aligned phase shifters with an FOM of 2.19 degree·dB−1·V−1. Our results indicated that a twisted nematic LC cell with pristine PEDOT: PSS thin films as electrodes is a good combination for a THz phase shifter and wave plates as well as other LC-based THz devices. [ABSTRACT FROM AUTHOR]

We have investigated tunable terahertz (THz) phase shifters that are based on a sandwiched liquid crystal (LC) cell with indium–tin–oxide (ITO) nanowhiskers (NWhs) as transparent electrodes. More than 360° of phase shift at 1.0 THz was achieved at a driving voltage as low as ~2.6 V (rms). This is approximately 40 times smaller than that reported in previous works using an electrically tuned LC device. Significance of the NWhs in reducing the required voltage is demonstrated. Overall transmittance of the device is as high as 30%, which is accountable by absorption losses of ITO NWhs, quartz substrate and LC. Experimental results are in good agreement with a theoretical formulism while taking into account super-thick LC cells (~1 mm) and pretilt angles. We also propose and demonstrate a novel THz technique for measuring pretilt angles of liquid crystals. [ABSTRACT FROM AUTHOR]

The discovery of the BRAFV600E mutation led to the development of vemurafenib (PLX4032), a selective BRAF inhibitor specific to the kinase, for the treatment of metastatic melanomas. However, initial success of the drug was dampened by the development of acquired resistance. Melanoma was shown to relapse in patients following treatment with vemurafenib which eventually led to patients' deaths. It has been proposed that mechanisms of resistance can be due to (1) reactivation of the mitogen-activated protein kinase (MAPK) signalling pathway via secondary mutations, amplification or activation of target kinase(s), (2) the bypass of oncogenic pathway via activation of alternative signalling pathways, (3) other uncharacterized mechanisms. Studies showed that receptor tyrosine kinases (RTK) such as PDGFRβ, IGF1R, EGFR and c-Met were overexpressed in melanoma cells. Along with increased secretion of growth factors such as HGF and TGF-α, this will trigger intracellular signalling cascades. This review discusses the role MAPK and Phosphatidylinositol-3-kinase-protein kinase B-mammalian target of rapamycin (PI3K-AKT-mTOR) pathways play in the mechanism of resistance of melanomas. [ABSTRACT FROM AUTHOR]

In this study, we propose a biochemical sensor that features a photonic cavity integrated with graphene. The tunable hybrid plasmonic-photonic sensor can detect the molecular fingerprints of biochemicals with a small sample volume. The stacking sequence of the device is "ITO grating/graphene/TiO2/Au/Si substrate", which composes a photonic band gap structure. A defect is created within the ITO gratings to form a resonant cavity. The plasmonic-photonic energy can be confined in the cavity to enhance the interaction between light and the analyte deposited in the cavity. The finite element simulation results indicated that the current sensor exhibits very high values in resonance shift and sensitivity. Moreover, the resonance spectrum with a broad resonance linewidth can identify the molecular vibration bands, which was exemplified by the fingerprint detections of protein and the chemical compound CBP. The sensor possesses an electrical tunability by including a graphene layer, which allowed us to tune the effective refractive index of the cavity to increase the sensor's sensing performance. In addition, our device admits a phononic bandgap as well, which was exploited to sense the mechanical properties of two particular dried proteins based on the simplified elastic material model instead of using the more realistic viscoelastic model. The dual examinations of the optical and mechanical properties of analytes from a phoxonic sensor can improve the selectivity in analyte detections. [ABSTRACT FROM AUTHOR]

Early folliculogenesis begins with the activation of the follicle and ends with the formation of the follicular antrum, which takes up most of the time of folliculogenesis. In this long process, follicles complete a series of developmental events, including but not limited to granulosa cell (GC) proliferation, theca folliculi formation, and antrum formation. However, the logical or temporal sequence of these events is not entirely clear. This study demonstrated in a mouse model that completion of early folliculogenesis required a minimum of two weeks. The oocyte reached its largest size in the Type 4–5 stage, which was therefore considered as the optimum period for studying oogenesis. Postnatal days (PD) 10–12 were regarded as the crucial stage of theca folliculi formation, as Lhcgr sharply increased during this stage. PD13–15 was the rapid growth period of early follicles, which was characterized by rapid cell proliferation, the sudden emergence of the antrum, and increased Fshr expression. The ovarian morphology remained stable during PD15–21, but antrum follicles accumulated gradually. Atresia occurred at all stages, with the lowest rate in Type 3 follicles and no differences among early Type 4–6 follicles. The earliest vaginal opening was observed at PD24, almost immediately after the first growing follicular wave. Therefore, the period of PD22–23 could be considered as a suitable period for studying puberty initiation. This study objectively revealed the pattern of early folliculogenesis and provided time windows for the study of biological events in this process. [ABSTRACT FROM AUTHOR]

Ship type classification of synthetic aperture radar imagery with convolution neural network (CNN) has been faced with insufficient labeled datasets, unoptimized and noised polarization images that can deteriorate a classification performance. Meanwhile, numerous labeled text information for ships, such as length and breadth, can be easily obtained from various sources and can be utilized in a classification with k-nearest neighbor (KNN). This study proposes a method to improve the efficiency of ship type classification from Sentinel-1 dual-polarization data with 10 m pixel spacing using both CNN and KNN models. In the first stage, Sentinel-1 intensity images centered on ship positions were used in a rectangular shape to apply an image processing procedure such as head-up, padding and image augmentation. The process increased the accuracy by 33.0% and 31.7% for VH (vertical transmit and horizontal receive) and VV (vertical transmit and vertical receive) polarization compared to the CNN-based classification with original ship images, respectively. In the second step, a combined method of CNN and KNN was compared with a CNN-alone case. The f1-score of CNN alone was up to 85.0%, whereas the combination method showed up to 94.3%, which was a 9.3% increase. In the future, more details on an optimization method will be investigated through field experiments of ship classification. [ABSTRACT FROM AUTHOR]

Although melatonin has been extensively studied in animal reproduction, the mechanism of melatonin in puberty remains elusive. This study was designed to explore the effect of intraperitoneal administration of melatonin on puberty onset in female mice. The injection of melatonin into postnatal days 10 mice at a dose of 15 mg/kg accelerated the puberty onset in mice. Mechanistically, there was no difference in physical growth and serum Leptin levels after melatonin administration. Meanwhile, the serum levels of reproductive hormones involved in hypothalamic-pituitary-ovarian axis, such as FSH and estrogen level in serum were increased. The mRNA levels of GnRH and GnRHr were not affected by melatonin, while the expressions of FSHβ in pituitary and Cyp19a1 in ovary were significantly up-regulated. In addition, melatonin still promoted FSH synthesis after ovariectomy. Furthermore, the enhanced activity of ERK1/2 signaling verified that the expression of FSHβ increased in pituitary. We confirmed that melatonin promoted the FSH synthesis in pituitary, thereby increased serum estrogen levels and ultimately accelerated puberty onset. However, these effects of melatonin may be pharmacological due to the high dose. This study would help us to understand the functions of melatonin in pubertal regulation comprehensively. [ABSTRACT FROM AUTHOR]

We aimed to investigate the prognostic value of the relative maximum standardized uptake value (SUV) of metastatic lymph node (LN) compared with that of primary tumor (SUVLN/SUVTumor) based on a pretreatment [18F]-FDG PET/CT scan in patients with clinically node-positive esophageal squamous cell carcinoma (cN+ ESCC) treated with definitive chemoradiotherapy (dCRT). We retrospectively evaluated cN+ ESCC patients who underwent a PET/CT scan before dCRT. Time-dependent receiver operating characteristics analysis was performed to identify the optimal cutoff value for SUVLN/SUVTumor. Prognostic influences of SUVLN/SUVTumor on distant metastasis-free survival (DMFS) and overall survival (OS) were evaluated using the Kaplan–Meier method and log-rank test for univariate analysis and Cox's proportional hazards regression model for multivariate analysis. We identified 112 patients with newly diagnosed cN+ ESCC. After a median follow-up of 32.0 months, 50 (44.6%) patients had distant failure and 84 (75.0%) patients died. Patients with high SUVLN/SUVTumor (≥ 0.39) experienced worse outcomes than low SUVLN/SUVTumor (< 0.39) (two-year DMFS: 26% vs. 70%, p < 0.001; two-year OS: 21% vs. 48%, p = 0.001). Multivariate analysis showed that SUVLN/SUVTumor was an independent prognostic factor for both DMFS (adjusted HR 2.24, 95% CI 1.34–3.75, p = 0.002) and OS (adjusted HR 1.61, 95% CI 1.03–2.53, p = 0.037). Pretreatment of SUVLN/SUVTumor is a simple and useful marker for prognosticating DMFS and OS in cN+ ESCC patients treated with dCRT, which may help in tailoring treatment and designing future clinical trials. [ABSTRACT FROM AUTHOR]

This study proposes an approaching method of identifying sea fog by using Geostationary Ocean Color Imager (GOCI) data through applying a Convolution Neural Network Transfer Learning (CNN-TL) model. In this study, VGG19 and ResNet50, pre-trained CNN models, are used for their high identification performance. The training and testing datasets were extracted from GOCI images for the area of coastal regions of the Korean Peninsula for six days in March 2015. With varying band combinations and changing whether Transfer Learning (TL) is applied, identification experiments were executed. TL enhanced the performance of the two models. Training data of CNN-TL showed up to 96.3% accuracy in matching, both with VGG19 and ResNet50, identically. Thus, it is revealed that CNN-TL is effective for the detection of sea fog from GOCI imagery. [ABSTRACT FROM AUTHOR]

For more than 100 years, liquid crystals (LCs) have been extensively investigated and LC displays now are becoming ubiquitous in our daily life, from TVs, mobile phones to indoor/outdoor signage. However, the LC display technology is maturing very fast and the LC display industry is gradually saturating due to the rapid progress with other emerging display technologies including Organic Light Emitting Diode (OLED) and micro-LED displays. The sphere phase LC filter exhibits a wide wavelength tuning range of 256 nm by thermal modulation and 76 nm by electrical modulation [[3]], and the templated blue phase LC may reflect multi-wavelengths in one filter with a much narrower reflection bandwidth of less than 15 nm [[4]]. [Extracted from the article]

It is significant to analyze the blend homogeneity of cohesive powders during pharmaceutical manufacturing in order to provide the exact content of the active pharmaceutical ingredient (API) for each individual dose unit. In this paper, an online monitoring platform using an MEMS near infrared (NIR) sensor was designed to control the bin blending process of cohesive powders. The state of blend homogeneity was detected by an adaptive algorithm, which was calibration free. The online control procedures and algorithm's parameters were fine-tuned through six pilot experiments and were successfully transferred to the industrial production. The reliability of homogeneity detection results was validated by 16 commercial scale experiments using 16 kinds of natural product powders (NPPs), respectively. Furthermore, 19 physical quality attributes of all NPPs and the excipient were fully characterized. The blending end time was used to denote the degree of difficulty of blending. The empirical relationships between variability of NPPs and the blending end time were captured by latent variable modeling. The critical material attributes (CMAs) affecting the blending process were identified as the particle shape and flowability descriptors of cohesive powders. Under the framework of quality by design (QbD) and process analytical technology (PAT), the online NIR spectroscopy together with the powder characterization facilitated a deeper understanding of the mixing process. [ABSTRACT FROM AUTHOR]

A dynamic time warping (DTW) algorithm has been suggested for the purpose of devising a motion-sensitive microelectronic system for the realization of remote motion abnormality detection. In combination with an inertial measurement unit (IMU), the algorithm is potentially applicable for remotely monitoring patients who are at risk of certain exceptional motions. The fixed interval signal sampling mechanism has normally been adopted when devising motion detection systems; however, dynamically capturing the particular motion patterns from the IMU motion sensor can be difficult. To this end, the DTW algorithm, as a kind of nonlinear pattern-matching approach, is able to optimally align motion signal sequences tending towards time-varying or speed-varying expressions, which is especially suitable to capturing exceptional motions. Thus, this paper evaluated this kind of abnormality detection using the proposed DTW algorithm on the basis of its theoretical fundamentals to significantly enhance the viability of the methodology. To validate the methodological viability, an artificial neural network (ANN) framework was intentionally introduced for performance comparison. By incorporating two types of designated preprocessors, i.e., a DFT interpolation preprocessor and a convolutional preprocessor, to equalize the unequal lengths of the matching sequences, two kinds of ANN frameworks were enumerated to compare the potential applicability. The comparison eventually confirmed that the direct template-matching DTW is excellent in practical application for the detection of time-varying or speed-varying abnormality, and reliably captures the consensus exceptions. [ABSTRACT FROM AUTHOR]

This work focuses on the detection of tiny macroalgae patches in the eastern parts of the Yellow Sea (YS) using high-resolution Landsat-8 images from 2014 to 2017. In the comparison between floating algae index (FAI) and normalized difference vegetation index (NDVI) better detection by FAI was observed, but many tiny patches still remained undetected. By applying a modification on the FAI around 12% to 27% increased and correct detection of macroalgae is achieved from 35 images compared to the original. Through this method many scattered tiny patches were detected in June or July in Korea Bay and Gyeonggi Bay. Though it was a small-scale phenomenon they occurred in the similar period of macroalgal bloom occurrence in the YS. Thus, by using this modified method we could detect macroalgae in the study areas around one month earlier than the previously used Geostationary Ocean Color Imager NDVI-based detection. Later, more macroalgae patches including smaller ones occupying increased areas were detected. Thus, it seems that those macroalgae started growing locally from tiny patches rather than being transported from the western parts of the YS. Therefore, this modified FAI could be used for the precise detection of macroalgae. [ABSTRACT FROM AUTHOR]

Background and Objectives : This study sought to investigate the natural course, the chronicity and recurrence rate, and the risk factors of chronic and recurrent herpes zoster ophthalmicus (HZO). We also evaluated the effects of long-term treatment for HZO. Materials and Methods : Patients diagnosed and treated for HZO were included in the retrospective medical chart review. Multivariable-adjusted logistic and Cox regression models were used to show risk factors for chronic and recurrent HZO along with hazard ratios (HRs) and 95% confidence intervals (CIs). Results : Among a total 130 of HZO patients, 31 patients (23.85%) had chronic disease and 19 patients (14.62%) had recurrent disease. The rate of chronic disease was higher in HZO with conjunctivitis, epithelial keratitis, and stromal keratitis. The recurrence rate increased in patients with chronic HZO (HR: 34.4, 95% CI: 3.6-324.6), epithelial keratitis (HR: 5.5, 95% CI: 1.3-30.0), stromal keratitis (HR: 18.8, 95% CI: 3.0-120.8), and increased intraocular pressure (IOP) (HR: 7.3, 95% CI: 1.6-33.2). Length of systemic antiviral therapy and anti-inflammatory eyedrop treatment were not associated with recurrent HZO ( p = 0.847 and p = 0.660, respectively). The most common ocular manifestation for recurrent HZO was stromal keratitis. Conclusions : This study demonstrated a considerable frequency of chronic and recurrent HZO. Chronic HZO in the form of epithelial or stromal keratitis with increased IOP provoked a significant rise in the risk of recurrence.