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As a typical hard but brittle material, Si tends to fracture abruptly at a stress well below its theoretical strength, even if the tested volume goes down to submicron scale, at which materials are usually nearly free of flaws or extended defects. Here, via the thermal–oxidation–mediated healing of the surface that is the preferred site for cracks or dislocations initiation, the premature fracture can be effectively inhibited and the over 50% homogeneous plastic strain with the near‐theoretical strength (twice the value of the unhealed counterpart) are united in submicron‐sized Si particles. In situ transmission electron microscope observations and atomistic simulations elucidate the confinement effect from the passivated and smoothened thermal oxide, which retards the dislocation nucleation and transforms the dominant deformation mechanism from partial dislocation to the more mobile full dislocation. This work demonstrates an effective and feasible surface engineering pathway to optimize the mechanical properties of Si at small scales. [ABSTRACT FROM AUTHOR]

The topography significantly influences local climate precipitation and the intensity of precipitation events, yet the specific differences in its elevational effects require further understanding. This study focuses on precipitation in Zhengzhou City, Henan Province, utilizing hourly data and a topographic elevation precipitation increment model to assess the impact of topography on local climate precipitation and extreme heavy rainfall events. The results indicate that the daily precipitation attributed to topographic elevation in Zhengzhou in July was 0.21 mm, accounting for 4.9% of the total precipitation. In the extreme heavy rainfall event on 20 July 2021 ("7.20" event), the precipitation due to topographic elevation reaches 48.7 mm, constituting 15.8% of the total precipitation. Additionally, numerical simulations using the Weather Research and Forecasting (WRF) model for the 20–21 July 2021 rainfall event in Zhengzhou show that the WRF model effectively reproduces the spatiotemporal characteristics of the precipitation process. The simulated topographic elevation precipitation intensity is 49.8 mm/day, accounting for 16.6% of daily precipitation, closely resembling observational data. Sensitivity experiments further reveal that reducing the heights of the Taihang Mountains and Funiu Mountains weakens the low-level easterly winds around Zhengzhou. Consequently, as the center of the heavy rainfall shifts northward or westward, the intensity of topographic elevation-induced precipitation decreases to 7.3 mm/day and 12.9 mm/day. [ABSTRACT FROM AUTHOR]

The model simulation focuses on an extreme rainfall event that triggered a flood hazard in the Lake Victoria basin region of East Africa from June 24th to 26th, 2022. This study investigates the impacts of its urban canopy on the extreme rainfall events over the Lake Victoria basin in East Africa, employing the Weather Research and Forecasting (WRF) model at a convective-permitting resolution. The rapid urbanization of the region has given rise to an urban canopy, which has notable effects on local weather patterns, including the intensity and distribution of rainfall. The model incorporates high-resolution land use and urban canopy parameters to accurately capture the influences of urbanization on local weather patterns. This research comprises three sets of experiments, two with urban areas and one without, using the WRF model; the experiments focus on three days of an extreme rainfall event in the Lake Victoria basin. Satellite-based precipitation products and reanalysis datasets are employed for a synoptic analysis and model evaluation. The results demonstrate the model's effectiveness in capturing meteorological variables during an extreme event compared to observed data. The synoptic patterns reveal that, during the extreme event, the Mascarene and St. Helena influenced rainfall conditions over the Lake Victoria Basin by directing moist air toward the northwest. This led to increased moisture convergence from the urban–rural interface toward urban areas, enhancing convection and processes that result in extreme rainfall. Moreover, this study indicates that the urban canopy, specifically the building effect parameterization, significantly amplifies the intensity and duration of rainfall in the urban areas of the region. This research also indicates a general increase in air temperature, relative humidity, latent heat flux, and surface sensible heat flux due to the urban canopy. These findings highlight the substantial influence of urbanization on rainfall patterns in the urban environment. [ABSTRACT FROM AUTHOR]

Climate change has and will continue to affect food security in different dimensions. This study aims at comparing current and future maize and sorghum climate suitability and yield using five state-of-art climate models in the Representative Concentration Pathways (RCP8.5) in Couple Intercomparison Project Phase 5 (CMIP5). The study considered 1970–2000 as the baseline and 2040–2060 (the 2050s) and 2061–2080 (2070s) as the projection periods. The mechanist FAO Eco-crop model and statistical crop model were used. The results show that rainfall and temperature are projected to increase by 2050s and 2070s with certain (uncertainty) in temperature (rainfall) projection. The central and western highlands are the optimum suitable zones for maize. Gradual reduction of maize suitable zone is anticipated leading to a yield loss of 10.8% (23.7%) by 2050s (2070s). The sorghum climate suitable areas are expected to increase in the future leading to a yield gain of 114% (80.7%) by 2050s (2070s) from the baseline yield. Currently, temperature creates more uncertainties in crop yield than rainfall. The findings of this research enlighten the policymakers and farmers on the probable susceptibilities of the agricultural system in future climate and the viable strategic measures to curb food insecurity over the country. [ABSTRACT FROM AUTHOR]

Based on the reforecast data (1999–2010) of three operational models [the China Meteorological Administration (CMA), the National Centers for Environmental Prediction of the U.S. (NCEP) and the European Centre for Medium-Range Weather Forecasts (ECMWF)] that participated in the Subseasonal to Seasonal Prediction (S2S) project, we identified the major sources of subseasonal prediction skill for heatwaves over the Yangtze River basin (YRB). The three models show limited prediction skills in terms of the fraction of correct predictions for heatwave days in summer; the Heidke Skill Score drops quickly after a 5-day forecast lead and falls down close to zero beyond the lead time of 15 days. The superior skill of the ECMWF model in predicting the intensity and duration of the YRB heatwave is attributable to its fidelity in capturing the phase evolution and amplitude of high-pressure anomalies associated with the intraseasonal oscillation and the dryness of soil moisture induced by less precipitation via the land-atmosphere coupling. The effects of 10–30-day and 30–90-day circulation prediction skills on heatwave predictions are comparable at shorter forecast leads (10 days), while the biases in 30–90-day circulation amplitude prediction show close connection with the degradation of heatwave prediction skill at longer forecast leads (> 15–20 days). The biases of intraseasonal circulation anomalies further affect precipitation anomalies and thus land conditions, causing difficulty in capturing extremely hot days and their persistence in the S2S models. [ABSTRACT FROM AUTHOR]

Maize (Zea Mays) is the major food crop in Kenya. Its production variation has devastating consequences on people’s basic food availability. This study will investigate the relationships between climate variability and maize yield using observed weather data from Kenya Meteorological Department and national annual maize yield data from the Ministry of Agriculture for the period 1979-2012. Mann-Kendall test was used to detect a trend in precipitation, minimum, and maximum temperature. Location-wise correlation method was performed between each climate variable and maize yield in every station. Stations which had significant correlations were aggregated to form climate indices which were used to build multiple linear regression model. The results revealed that maize yield in Kenya was significantly decreasing at a rate of 0.07 tons/ha/decade at the 95% confidence level accompanied by high inter-annual variation, while world average was increasing at a rate of 0.6 tons/ha/decade. This reduction was accredited to a significant increasing temperature and reduction in seasonal rainfall. Empirical relationship derived from multiple regression models indicates that 67.53% of yield variance was attributed to varying seasonal climate indices. Precipitation is the dominant predictor accounting to 49.73% of yield variance. There is a significant correlation of 0.78 between the modeled and observed yield hence high credibility of the statistical model. A Continuous decrease of maize yield is expected under the influence of climate change which threatens national food security if effective measures to raise maize production are not endorsed. These findings form a framework for designing policies geared towards the reduction of climate-related vulnerability in many parts of the world. [ABSTRACT FROM AUTHOR]

Periodontitis is a common chronic inflammatory disease, which causes the destruction of both the soft and mineralized tissues. However, current treatments such as bone graft materials, barrier membranes, and protein products all have difficulties in regenerating the complete periodontal tissue structure. Stem cell-based tissue engineering has now emerged as one of the most effective treatments for the patients suffering from periodontal diseases. Plants not only can be substrates for life processes, but also contain hormones or functional molecules. Numbers of preclinical studies have revealed that products from plant can be successfully applied in modulating proliferation and differentiation of human mesenchymal stem cells. Plant-derived substances can induce stem cells osteogenic differentiation, and they also possess angiogenic potency. Furthermore, in the field of tissue engineering, plant-derived compounds or plant extracts can be incorporated with biomaterials or utilized as biomaterials for cell transplantation. So it is speculated that botanical products may become a new perspective in stem cell-based periodontal regeneration. However, the lack of achieving predict clinical efficacy and quality control has been the major impediment to its extensive application. This review gives an overview of the prospect of applying different plant-derived substances in various human mesenchymal stem cells-based periodontal regeneration. [ABSTRACT FROM AUTHOR]

Anatomical location of gliomas has been considered as a factor implicating the contributions of a specific precursor cells during the tumor growth. Isocitrate dehydrogenase 1 (IDH1) is a pathognomonic biomarker with a significant impact on the development of gliomas and remarkable prognostic effect. The correlation between anatomical location of tumor and IDH1 states for low-grade gliomas was analyzed quantitatively in this study. Ninety-two patients diagnosed of low-grade glioma pathologically were recruited in this study, including 65 patients with IDH1-mutated glioma and 27 patients with wide-type IDH1. A convolutional neural network was designed to segment the tumor from three-dimensional magnetic resonance imaging images. Voxel-based lesion symptom mapping was then employed to study the tumor location distribution differences between gliomas with mutated and wild-type IDH1. In order to characterize the location differences quantitatively, the Automated Anatomical Labeling Atlas was used to partition the standard brain atlas into 116 anatomical volumes of interests (AVOIs). The percentages of tumors with different IDH1 states in 116 AVOIs were calculated and compared. Support vector machine and AdaBoost algorithms were used to estimate the IDH1 status based on the 116 location features of each patient. Experimental results proved that the quantitative tumor location measurement could be a very important group of imaging features in biomarker estimation based on radiomics analysis of glioma. [ABSTRACT FROM PUBLISHER]

Objective: The status of isocitrate dehydrogenase 1 (IDH1) is highly correlated with the development, treatment and prognosis of glioma. We explored a noninvasive method to reveal IDH1 status by using a quantitative radiomics approach for grade II glioma.Methods: A primary cohort consisting of 110 patients pathologically diagnosed with grade II glioma was retrospectively studied. The radiomics method developed in this paper includes image segmentation, high-throughput feature extraction, radiomics sequencing, feature selection and classification. Using the leave-one-out cross-validation (LOOCV) method, the classification result was compared with the real IDH1 situation from Sanger sequencing. Another independent validation cohort containing 30 patients was utilised to further test the method.Results: A total of 671 high-throughput features were extracted and quantized. 110 features were selected by improved genetic algorithm. In LOOCV, the noninvasive IDH1 status estimation based on the proposed approach presented an estimation accuracy of 0.80, sensitivity of 0.83 and specificity of 0.74. Area under the receiver operating characteristic curve reached 0.86. Further validation on the independent cohort of 30 patients produced similar results.Conclusions: Radiomics is a potentially useful approach for estimating IDH1 mutation status noninvasively using conventional T2-FLAIR MRI images. The estimation accuracy could potentially be improved by using multiple imaging modalities.Key Points: • Noninvasive IDH1 status estimation can be obtained with a radiomics approach. • Automatic and quantitative processes were established for noninvasive biomarker estimation. • High-throughput MRI features are highly correlated to IDH1 states. • Area under the ROC curve of the proposed estimation method reached 0.86. [ABSTRACT FROM AUTHOR]

Fetal nuchal translucency (NT) thickness is one of the most important parameters in prenatal screening. Locating the mid-sagittal plane is one of the key points to measure NT. In this paper, an automatic method for the sagittal plane detection using 3-D ultrasound data is proposed. To avoid unnecessary massive searching and the corresponding huge computation load, a model is proposed to turn the sagittal plane detection problem into a symmetry plane and axis searching problem. The deep belief network (DBN) and a modified circle detection method provide prior knowledge for the searching. The experiments show that in most cases, the result plane has small distance error and angle error at the same time-88.6% of the result planes have a distance error less than 4 mm and 71.0% have angle error less than 20°. [ABSTRACT FROM AUTHOR]

The tropical cyclone genesis number (TCGN) in July-October (JASO) over the western North Pacific (WNP) exhibits a robust interannual variation. It shows a longitudinally tri-pole pattern with a high in the eastern WNP and South China Sea (SCS) and a low in the western WNP, which explain 42.2 and 23.4 % of total TCGN variance in the eastern WNP and SCS, respectively. The high-low-high pattern is similar to that derived from a TC genesis potential index (GPI). To understand the cause of the longitudinal distribution of the dominant interannual mode, we examine the contributions of environmental parameters associated with GPI. It is found that relative humidity and relative vorticity are important factors responsible for TC variability in the SCS, while vertical shear and relative vorticity are crucial in determining TC activity in eastern WNP. A simultaneous correlation analysis shows that the WNP TCGN in JASO is significantly negatively correlated (with a correlation coefficient of −0.5) with sea surface temperature anomalies (SSTA) in the tropical North Atlantic (TNA). The longitudinal distribution of TC genesis frequency regressed onto TNA SSTA resembles that regressed upon the WNP TCGN series. The spatial patterns of regressed environmental variables onto the SSTA over the TNA also resemble those onto TCGN in the WNP, that is, an increase of relative humidity in the SCS and a weakening of vertical shear in the eastern WNP are all associated with cold SSTA in the TNA. Further analyses show that the cold SSTA in the TNA induce a negative heating in situ. In response to this negative heating, a low (upper)-level anomalous aniti-cyclonic (cyclonic) flows appear over the subtropical North Atlantic and eastern North Pacific, and to east of the cold SSTA, anomalous low-level westerlies appear in the tropical Indian Ocean. Given pronounced mean westerlies in northern Indian Ocean in boreal summer, the anomalous westerly flows increase local surface wind speed and surface evaporation and cool the SST in situ. Cold SSTA in northern Indian Ocean further suppress local convection, inducing anomalous westerlies to its east, leading to enhanced cyclonic vorticity and low surface pressure over the WNP monsoon trough region. Idealized numerical experiments further confirm this Indian Ocean relaying effect, through which cold SSTA in the tropical Atlantic exert a remote impact to circulation in the WNP. [ABSTRACT FROM AUTHOR]

The Generalized Equilibrium Feedback Analysis method was used to isolate the contributions of major sea-surface temperature anomaly (SSTA) modes over three oceanic basins to the climate variability of tropical cyclone (TC) genesis number (TCGN) in the peak TC season over the western North Pacific (WNP) between 1970 and 2012. The results show that TCGN variation has a statistically significant response to the first SST mode over the tropical North Pacific (TNP1), Indian Ocean (IOBM) and North Atlantic (NA1). The dominant SSTA modes in the three basins contribute 16.6, 12.1 and 13.6% of total TCGN variance, respectively. Among them, TNP1 and NA1 are primarily responsible for TCGN interdecadal variability, with a contribution of 22 and 14.5% to its interdecadal variance at 96 and 93% confidence levels, respectively. TCGN interannual variability, on the other hand, is significantly influenced by IOBM and NA1 with a contribution of 17.6 and 14.3% of the total interannual variance, respectively. The maximum TCGN variability centres are located in the central WNP and South China Sea. The former is primarily associated with responses of low-level relative vorticity to TNP1 and NA1 and the latter is closely linked to the forcing from IOBM and NA1. [ABSTRACT FROM AUTHOR]

As a fundamental task for geographical information updating, 3D city modeling, and other critical applications, the automatic extraction of building footprints from high-resolution remote sensing images has been substantially explored and received increasing attention over recent years. Among different types of building extraction methods, the polygonal segmentation methods produce vector building polygons that are in a more realistic format compared with those obtained from pixel-wise semantic labeling and contour-based methods. However, existing polygonal building segmentation methods usually require a perfect segmentation map and a complex post-processing procedure to guarantee the polygonization quality, or produce inaccurate vertex prediction results that suffer from wrong vertex sequence, self-intersections, fixed vertex quantity, etc. In our previous work, we have proposed a method for polygonal building segmentation from remote sensing images that addresses the above limitations of existing methods. In this paper, we propose PolyCity, which further extends and improves our previous work in terms of the application scenario, methodology design, and experimental results. Our proposed PolyCity contains the following three components: (1) a pixel-wise multi-task network for learning the semantic and geometric information via three tasks, i.e., building segmentation, boundary prediction, and edge orientation prediction; (2) a simple but effective vertex selection module (VSM), which effectively bridges the gap between pixel-wise and graph-based models via transforming the segmentation map into valid polygon vertices; (3) a graph-based vertex refinement network (VRN) for automatically adjusting the coordinates of VSM-generated valid polygon vertices, producing the final building polygons with more precise vertices. Results on three large-scale building extraction datasets demonstrate that our proposed PolyCity generates vector building footprints with more accurate vertices, edges, shapes, etc., achieving significant vertex score improvements while maintaining high segmentation and boundary scores compared with the current state-of-the-art. The code of PolyCity will be released at https://github.com/liweijia/polycity. [ABSTRACT FROM AUTHOR]

Although many criteria were proposed to predict the glass forming ability (GFA) of alloys, the precise correlation between the minor addition of elements and the glass formation remains a challenge. To solve this problem, we propose a simple parameter α' derived from thermal expansion coefficient based on the details of the intrinsic interatomic potential. It has been found that α' has the capability of precisely predict the changes of GFA, indicating the important role of anharmonicity of atomic vibration in glass formation. This anharmonicity-related parameter α' relates to atomic mobility behavior, and could be well embodied by the competition between characteristic types of clusters in terms of the fragility concept upon the liquid-solid evolution. This work not only helps to uncover atomic and cluster origins of glass formation from interatomic potential, but also provides a novel route to precisely evaluate the effect of minor addition of elements on GFA. [Display omitted] [ABSTRACT FROM AUTHOR]

Catalytic hydrodechlorination (HDC) is considered as one of the most promising strategies for the treatment of chlorinated environmental pollutants. Here we proposed a strategy for rapid complete dechlorination by exploiting a B–N co-doped hierarchically porous carbon material (BNC) to immobilize Pd NPs, which makes use of not only the micro/meso porous structure to accelerate the mass transport and to provide enormous active sites, but also the synergistic effect for codoping of B–N to enhance the interaction between Pd NPs and support and thus to stabilize and disperse the small size of the Pd particle. Ascribed to these combined advantages, Pd/BNC exhibited more distinctive catalytic dehalogenation activity (k = −0.14 min−1) and better stability (about 90.0% activity retention after 5 cycles) than Pd/C (k = −0.0070 min−1). Additionally, density functional theory (DFT) calculation indicates that the incorporation of N and B atoms in the carbon skeleton will reduce the adsorption energy of Cl− and thus Pd/BNC exhibits more remarkable stability than Pd/C during long-term HDC reactions. As a result, ultrafine Pd particles and high Pd2+/(Pd2+ + Pd0) ratios were found in Pd/BNC. [ABSTRACT FROM AUTHOR]

Highlights: [•] A novel unsplit implementation of PML is proposed for the second-order equation system. [•] The PML is derived by ADE and complex coordinate stretching techniques. [•] It is far more memory-efficient and easier to implement than existing methods. [Copyright &y& Elsevier]

Purpose: Assessment of the fetal cerebellar volume on 3D ultrasound data sets is very important in the clinical evaluation of the fetal growth and health. However, the irregular shape of the cerebellum and the strong artifacts of ultrasound images complicate the segmentation without manual intervention. In this paper, the authors propose an approach to locate the cerebellum automatically, which is considered as a prework of the segmentation. Methods: The authors present a weighted Hough transform and a constrained randomized Hough transform to detect the fetal brain midline and the skull, respectively. By combining the location information of these two structures with local image features, a constrained probabilistic boosting tree is then proposed to search the cerebellum. Results: This algorithm was tested on ultrasound volumes of the fetal head with the gestational age ranging from 20 to 33 weeks. Compared with manual measurements, this algorithm obtained a satisfactory performance with the mean Dice similarity coefficient of 0.92 and the average processing time of 0.75 s per case. Conclusions: The results demonstrate that the proposed method is an automatic, fast, and accurate tool for searching the fetal cerebellum on ultrasound volumes. [ABSTRACT FROM AUTHOR]

Many studies demonstrate that the type of adjacent mesenchymal cells can affect epidermal morphogenesis of bilayered tissue-engineered skin. However, whether a mixture of different mesenchymal cell types can improve epidermal morphogenesis of bioengineered skin remains unknown. In this study, keratinocytes, dermal fibroblasts and adipose tissue-derived stem cells (ADSCs) were isolated and purified from human skin and subcutaneous fat. Conditioned medium generated from a mixture of dermal fibroblasts and ADSCs at the ratio of 1:1 was superior to that from fibroblasts or ADSCs alone in promoting keratinocyte proliferation, as indicated by MTT assay. Furthermore, ELISA results showed that the cytokine levels of human hepatocyte growth factor and keratinocyte growth factor (also known as FGF7) in the mixed fibroblasts/ADSC group were higher than those in the ADSC or dermal fibroblasts group. To examine the potential roles of mixed fibroblasts and ADSCs on epidermal morphogenesis, a three-dimensional tissue engineered skin system was applied. Histological analyses demonstrated that keratinocytes proliferated extensively over the mixture of fibroblasts and ADSCs, and formed a thick epidermal layer with well-differentiated structures. Keratin 10 (epidermal differentiation marker) was expressed in the suprabasal layer of bilayered tissue-engineered skin in the mixed fibroblasts and ADSCs group. Desmosomes and hemidesmosomes were detected in the newly formed epidermis by transmission electron microscopy analysis. Together, these findings revealed for the first time that a mixture of fibroblasts and ADSCs in bilayered tissue-engineered skin can improve epidermal morphogenesis. Copyright © 2012 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Objective: Compared with normal birth weight fetuses (2,500-4,000 g), accurate fetal weight estimation for fetuses with low or excessive weight is considered more important for fetal compromise prediction and labor management. New formulas were developed to estimate weight for low birth weight (LBW) fetuses and macrosomic fetuses, respectively. Methods: A total of 523 fetuses with birth weight less than 2,500 g, 652 fetuses with normal birth weight, and 239 fetuses with birth weight more than 4,000 g were included in the study. As much as 25 existing formulas which incorporate regularly defined fetal measurements were evaluated and compared. Performance evaluation of existing formulas showed that no formulas can provide consistently accurate weight estimation both for LBW fetuses and macrosomic fetuses. A total of 1,034 cases were utilized to generate an overall regression formula. If the pre-estimated weight fell into the suspicious LBW and macrosomia range, the value was then updated by using the new regression formulas for LBW fetuses and macrosomic fetuses. As the training group, 262 LBW fetuses and 120 macrosomic fetuses were employed in a stepwise linear regression to obtain two update regression formulas for suspicious LBW fetuses and macrosomic fetuses. As the validation group, another 261 LBW fetuses and 119 macrosomic fetuses were assessed. Results: The new overall formula has the form of Log(10)BW = 0.180(HC) + 0.00628(AC) - 0.00318(HC)(2) + 0.00173(AC)(FL) + 0.0000430(BPD)(HC)(2). The update formula for suspicious LBW fetuses is LnBW = 1.470(BPD) + 0.0169(HC) - 0.0873(BPD)(2) + 0.00518(AC)(FL) and for macrosomic fetuses is Log(10)BW = 0.730(BPD) - 0.0375(BPD)(2) + 0.000264(AC)(FL). For LBW fetuses, the new method gave 7.6 ± 209.0 (g) of estimation error and 8.3 ± 7.8 (%) of absolute percentage error, while the best existing formula provided -0.7 ± 226.0 (g) and 9.1 ± 8.3 (%). With the new method, 71.3% of estimates fell within ±10% of the actual birth weight, while the best existing formula gave 65.5%. For macrosomic fetuses, the new method gave -87.9 ± 231.0 (g) of estimation error and 4.4 ± 3.9 (%) of absolute percentage error, while the best existing formula provided 115.6 ± 345.1 (g) and 6.8 ± 5.4 (%). With the new method, 89.1% of estimates fell within ±10% of the actual birth weight, while the best existing formula gave 75.6%. Conclusions: To improve the weight estimation accuracy for low or excessive weight fetuses, separate formulas are necessary. The new method provides significant improvement on fetal weight estimation for LBW fetuses and macrosomic fetuses. [ABSTRACT FROM AUTHOR]

This study investigated the effects of a newly-developed scaffold, nano-hydroxyapatite/collagen/poly(L-lactide) (nHAC/PLA), on the attachment, proliferation and osteogenic capability of dog periodontal ligament stem cells (PDLSCs) in vitro and in vivo. Hydroxyapatite/tricalcium phosphate (HA/TCP), a commonly used bone substitute, was used as a positive control. PDLSCs isolated from dog molar were incubated in an osteogenic medium to evaluate their osteogenic differentiation in vitro, and then seeded onto nHAC/PLA and HA/TCP scaffolds. In vitro cell attachment, proliferation and differentiation were assessed by scanning electron microscopy (SEM), cell counting, 3-[4,5-dimethythiazol-2-yl]-5-[3-carboxy-phenyl]-2-[4-sulfophenyl]-2H-tetrazolium and alkaline phosphate activity, and reverse transcription-polymerase chain reaction, respectively. Finally, the constructs were implanted subcutaneously into dogs to investigate their osteogenic capacity. After osteogenic induction for 21 days, PDLSCs differentiated into osteogenic lineage, as indicated by the expressions of osteoblastic differentiation genes CoL-I, OCN and OPN mRNA, and the formation of mineral deposits. When seeded onto scaffolds, the cells attached and spread well, and retained their osteogenic phenotypes on both scaffolds. Comparatively, cell number and proliferative viability on nHAC/PLA constructs were greater than those on HA/TCP constructs (P < 0.05). Histological results showed that new bone and osteoid was formed in both groups, and histomorphometric analysis demonstrated that the amount of newly formed bone in the nHAC/PLA group was higher than that in the HA/TCP group (P < 0.05). This study suggests that nHAC/PLA can be used as a potent scaffold for alveolar bone regeneration. [ABSTRACT FROM AUTHOR]

Abstract: An ultrasound speckle reduction method is proposed in this paper. The filter, which enhances the power of anisotropic diffusion with the Smallest Univalue Segment Assimilating Nucleus (SUSAN) edge detector, is referred to as the SUSAN-controlled anisotropic diffusion (SUSAN_AD). The SUSAN edge detector finds image features by using local information from a pseudo-global perspective. Thanks to the noise insensitivity and structure preservation properties of SUSAN, a better control can be provided to the subsequent diffusion process. To enhance the adaptability of the SUSAN_AD, the parameters of the SUSAN edge detector are calculated based on the statistics of a fully formed speckle (FFS) region. Different FFS estimation schemes are proposed for envelope-detected speckle images and log-compressed ultrasonic images. Adaptive diffusion threshold estimation and automatic diffusion termination criterion are employed to enhance the robustness of the method. Both synthetic and real ultrasound images are used to evaluate the proposed method. The performance of the SUSAN_AD is compared with four other existing speckle reduction methods. It is shown that the proposed method is superior to other methods in both noise reduction and detail preservation. [Copyright &y& Elsevier]

This paper reports on an analysis of the tropical cyclone (TC) potential intensity (PI) and its control parameters in transient global warming simulations. Specifically, the TC PI is calculated for phase 3 of the Coupled Model Intercomparison Project (CMIP3) integrations during the first 70 yr of a transient run forced by a 1% yr-1 CO2 increase. The linear trend over the period is used to project a 70-yr change in relevant model parameters. The results for a 15-model ensemble-mean climate projection show that the thermodynamic potential intensity (THPI) increases on average by 1.0% to ∼3.1% over various TC basins, which is mainly attributed to changes in the disequilibrium in enthalpy between the ocean and atmosphere in the transient response to increasing CO2 concentrations. This modest projected increase in THPI is consistent with that found in other recent studies. In this paper the effects of evolving large-scale dynamical factors on the projected TC PI are also quantified, using an empirical formation that takes into account the effects of vertical shear and translational speed based on a statistical analysis of present-day observations. Including the dynamical efficiency in the formulation of PI leads to larger projected changes in PI relative to that obtained using just THPI in some basins and smaller projected changes in others. The inclusion of the dynamical efficiency has the largest relative effect in the main development region (MDR) of the North Atlantic, where it leads to a 50% reduction in the projected PI change. Results are also presented for the basin-averaged changes in PI for the climate projections from each of the 15 individual models. There is considerable variation among the results for individual model projections, and for some models the projected increase in PI in the eastern Pacific and south Indian Ocean regions exceeds 10%. [ABSTRACT FROM AUTHOR]

Abstract: In many applications of medical image analysis, the density of an object is the most important feature for isolating an area of interest (image segmentation). In this research, an object density-based image segmentation methodology is developed, which incorporates intensity-based, edge-based and texture-based segmentation techniques. The proposed method consists of three main stages: preprocessing, object segmentation and final segmentation. Image enhancement, noise reduction and layer-of-interest extraction are several subtasks of preprocessing. Object segmentation utilizes a marker-controlled watershed technique to identify each object of interest (OI) from the background. A marker estimation method is proposed to minimize over-segmentation resulting from the watershed algorithm. Object segmentation provides an accurate density estimation of OI which is used to guide the subsequent segmentation steps. The final stage converts the distribution of OI into textural energy by using fractal dimension analysis. An energy-driven active contour procedure is designed to delineate the area with desired object density. Experimental results show that the proposed method is 98% accurate in segmenting synthetic images. Segmentation of microscopic images and ultrasound images shows the potential utility of the proposed method in different applications of medical image processing. [Copyright &y& Elsevier]

Abstract: A simple cleft-shaped anion receptor 1 containing amide and hydroxyl as recognition units was synthesized and its anion recognition properties were investigated by naked-eye observation, UV–vis, fluorescence and 1H NMR spectra. Receptor 1 could effectively recognize F− via multiple H-bonding interactions, along with visible color change and remarkable fluorescence enhancement. Interestingly, reference compound 2 only containing amide groups did not display any interaction for all of the examined anions, including F−. [Copyright &y& Elsevier]

Abstract: A novel kernel anisotropic diffusion (KAD) method is proposed for robust noise reduction and edge detection. The KAD incorporates a kernelized gradient operator in the diffusion, leading to more effective edge detection and providing a better control to the diffusion process. Adaptive diffusion threshold estimation and automatic diffusion termination criterion are also introduced to enhance the robustness of the KAD. The KAD outperforms several previous anisotropic diffusion-based methods for low SNR images. [Copyright &y& Elsevier]

Abstract: Two crucial growth factors, FGF2 and TGFβ1, were investigated in this study to determine their inductive effects on the odontoblastic differentiation of human dental pulp stem cells (DPSCs) in vitro. DPSCs were isolated by immunomagnetic bead selection using the STRO-1 antibody, and then co-cultured respectively with FGF2, TGFβ1 and FGF2+TGFβ1. The results showed that FGF2 can exert a significant effect on the cell proliferation, while TGFβ1 or FGF2+TGFβ1 can initiate an odontoblast-like differentiation of DPSCs. Moreover, FGF2 can synergistically upregulate the effects of TGFβ1 on the odontoblastic differentiation of DPSCs, as indicated by the increased alkaline phosphatase activity, the polarized cell appearance and secretary ultrastructural features, the formation of mineralized nodules and the gene/protein expression of dentin sialoprotein and dentin matrix protein-1. Together, FGF2 acted primarily on the cell proliferation, while TGFβ1 and FGF2+TGFβ1 mainly stimulated the odontoblastic differentiation of DPSCs. This study provides interesting progress in the odontoblastic differentiation of DPSCs induced by FGF2 and TGFβ1. [Copyright &y& Elsevier]

Abstract: A novel method is developed for the fetal abdominal contour extraction and measurement in ultrasound images. Fetal abdominal circumference (AC) is one of the standardized measurements in the antepartum ultrasound monitoring. Among several standardized measurements, AC is best correlated with fetal growth but is also the most difficult to be accurately measured. To overcome the difficulties in the abdominal contour extraction, the proposed method is a four-step procedure that integrates several image segmentation techniques. The proposed method is able to make the best use of the strength of different segmentation algorithms, while avoiding their deficiencies. An enhanced instantaneous coefficient of variation (ICOV) edge detector is first developed to detect edges of the abdominal contour and alleviate the effects of most speckle noise. Then, the Fuzzy C-Means clustering is employed to distinguish salient edges attributable to the abdominal contour from weak edges due to the other texture. Subsequently, the iterative Hough transform is applied to determine an elliptical contour and obtain an initial estimation of the AC. Finally, the gradient vector field (GVF) snake adapts the initial ellipse to the real edges of the abdominal contour. Quantitative validation of the proposed method on synthetic images under different imaging conditions achieves satisfactory segmentation accuracy (98.78% ± 0.16%). Experiments on 150 clinical images are carried out in three aspects: comparisons between inter-observer and inter-run variation, the fitness analysis between the automatically detected ellipse and the manual delineation, and the accuracy comparisons between automatic measurements and manual measurements in estimation of fetal weight (EFW). Experimental results show that the proposed method can provide consistent and accurate measurements. The reductions of the mean absolute difference and the standard deviation of EFW based on automatic measurements are about 1.2% and 2.1%, respectively, which indicate its potential in clinical antepartum monitoring application. (E-mail: yywang@fudan.edu.cn) [Copyright &y& Elsevier]

Conflicting evidence exists regarding the effectiveness of magnesium supplementation during pregnancy in gestational diabetes mellitus (GDM) patients. This meta‐analysis examines the effect of magnesium on glycemic indices and metabolic status in GDM. We searched databases for randomized controlled trials (RCTs) conducted, and after applying inclusion and exclusion criteria, a total of four RCTs were considered eligible for the analysis. Outcome parameters included markers for glycemic control and metabolic status. A total of four RCTs with 198 participants (control = 99; magnesium supplemented = 99) were selected for the analysis. Magnesium supplementation resulted in a significant reduction in markers of glycemic control—fasting plasma glucose (standard mean difference (μ^) = −0.83; 95% CI: [−1.13, –0.54]; p‐value <.0001), and insulin levels (μ^ = −0.95; 95% CI: [−1.38, −0.52]; p‐value <.0001). Also, Mg intake resulted in altered oxidative stress markers TAC (μ^ = 1.09; 95% CI: [0.10, 2.07]; p‐value =.03) of the pregnant women. No significant effect on GSH and CRP levels was observed. This study provides evidence of the positive effects of magnesium intervention on insulin sensitivity and oxidative stress in GDM patients. [ABSTRACT FROM AUTHOR]

Objectives: Anti-HER2 targeted therapy significantly reduces risk of relapse in HER2 + breast cancer. New measures are needed for a precise risk stratification to guide (de-)escalation of anti-HER2 strategy. Methods: A total of 726 HER2 + cases who received no/single/dual anti-HER2 targeted therapies were split into three respective cohorts. A deep learning model (DeepTEPP) based on preoperative breast magnetic resonance (MR) was developed. Patients were scored and categorized into low-, moderate-, and high-risk groups. Recurrence-free survival (RFS) was compared in patients with different risk groups according to the anti-HER2 treatment they received, to validate the value of DeepTEPP in predicting treatment efficacy and guiding anti-HER2 strategy. Results: DeepTEPP was capable of risk stratification and guiding anti-HER2 treatment strategy: DeepTEPP-Low patients (60.5%) did not derive significant RFS benefit from trastuzumab (p = 0.144), proposing an anti-HER2 de-escalation. DeepTEPP-Moderate patients (19.8%) significantly benefited from trastuzumab (p = 0.048), but did not obtain additional improvements from pertuzumab (p = 0.125). DeepTEPP-High patients (19.7%) significantly benefited from dual HER2 blockade (p = 0.045), suggesting an anti-HER2 escalation. Conclusions: DeepTEPP represents a pioneering MR-based deep learning model that enables the non-invasive prediction of adjuvant anti-HER2 effectiveness, thereby providing valuable guidance for anti-HER2 (de-)escalation strategies. DeepTEPP provides an important reference for choosing the appropriate individualized treatment in HER2 + breast cancer patients, warranting prospective validation. Clinical relevance statement: We built an MR-based deep learning model DeepTEPP, which enables the non-invasive prediction of adjuvant anti-HER2 effectiveness, thus guiding anti-HER2 (de-)escalation strategies in early HER2-positive breast cancer patients. Key Points: • DeepTEPP is able to predict anti-HER2 effectiveness and to guide treatment (de-)escalation. • DeepTEPP demonstrated an impressive prognostic efficacy for recurrence-free survival and overall survival. • To our knowledge, this is one of the very few, also the largest study to test the efficacy of a deep learning model extracted from breast MR images on HER2-positive breast cancer survival and anti-HER2 therapy effectiveness prediction. [ABSTRACT FROM AUTHOR]

The detrimental impacts of climate change have drawn the interest of many climate scientists toward understanding the past climate for the sake of preparing for the future. The current study evaluates the performance of 12 rainfall models available in Coupled Model Intercomparison Project Phase 5 (CMIP5) in reproducing observed rainfall over Kenya from 1979 to 2005. Several statistical metrics were deployed in quantifying the disparities between CMIP5 models, in situ, and the Global Precipitation Climatology Centre (GPCC v7) rainfall datasets. The results show satisfactory skill of CMIP5 models' in simulating the bimodal rainfall regime despite exhibiting dry (wet) bias during March–May (MAM) and October–November (OND) season, respectively. The models' skills in reproducing the interannual variability is relatively weak. However, majority of the models captures the temporal pattern with reasonable skills in OND than in MAM and annual rainfall. The impacts of Indian Ocean Dipole (IOD) and El Niño southern oscillation (ENSO) are marked in observed OND rains with no significance link in MAM rains. Overall, CMIP5 models' skills in replicating the mean statistics and teleconnection links are relatively weak. Remarkably, the performance of models at different time scale, metrics, simulation of dynamical and teleconnection patterns are inconsistent among models. Nevertheless, based on skill score, the models are listed from top to bottom as; MPI-ESM-MR, CSIRO-MK3-6-0, GISS-E2-R, MRI-CGCM2.3.3, EC-EARTH, MIROC-ESM-CHEM, FGOALS-g2, BCC-CSM1.1-M, HADGEM-AO, CanESM2, GFDL-ESM2G, IPSL-CM5A-MR, and MME model. This study sheds light on the use of statistical metrics and teleconnection pattern to rank CMIP5 models and forms basis on model selection. Model parameterization over tropics is prudent, and bias correction is paramount in future projections and impacts studies. • Various ranking metrics of models leads to different types of models' selection. • Models performance differ from one locale to another and even within different climate variables. • Models evaluation may include teleconnection link apart from reproducing mean rainfall statistics. • Failure of a model should be based on the intended use of the models. • Caution should be exercised when using CMIP5 models' projection over Kenya. [ABSTRACT FROM AUTHOR]

Analyzing spatiotemporal dynamics of meteorological variables in evolving climate, especially in regions where rain-fed agribusiness is predominant is paramount. In this regard, this study examines the spatiotemporal variability, trend, and magnitude of observed rainfall from 33 synoptic stations during 1979–2017 over Kenya. Non-parametric techniques like Mann–Kendall test, Sequential Mann-Kendall (SMK), and Sen's slope estimator (SSE) were deployed in assessing trend, change points, and magnitude. Results indicate that significant net change of monthly total rainfall mean is observed in May and December. Boreal spring and annual rainfall are insignificantly diminishing at a rate of −1.58 and −0.93 mm/year respectively. During boreal autumn, rainfall is insignificantly increasing at a rate of 1.48 mm/year. High interannual variability was observed, but no abrupt change was recorded during the study period. Spatial distribution of trend reveals dynamic variations from station to station. Amidst boreal spring (autumn), 27 (29) of stations considered had negative (positive) trends wherein 4 (8) stations recorded significant trend at α ≤ 0.01, respectively. At the annual scale, 10 (23) of the stations reported positive (negative) with 1 (5) significant trends at α ≤ 0.01, respectively. At all-time scales, stations at lower eastern and northeastern parts of the country reported a negative trend. Spatial decadal analysis portrays anomalous dry event over the study domain with the first decade being the wettest during boreal spring. To date, anomalously wet conditions exist throughout the country except lower eastern parts during boreal autumn. Comprehensive knowledge about variability, trend, and change point in precipitation is of unprecedented interest to scientists since they are prerequisites for developing effective contingency strategies to curb the impacts of climate change and future preparedness. • Trend, change points and abrupt changes in seasonal and annual rainfall from 33 synoptic stations in Kenya from 1979 to 2017 are assessed. • Rainfall is decreasing (increasing) insignificantly during boreal springs (autumn) and decreasing at annual scale. • Spatial distribution of seasonal and annual trend revealed that trend is dynamic and varied from station to station. • At all-time scales, stations at lower eastern and northeastern parts of the country reported negative trend. • Drying decadal trend in rainfall is observed during boreal springs while current decades are becoming wetter during boreal autumn. [ABSTRACT FROM AUTHOR]

Objectives: As a few types of glioma, young high-risk low-grade gliomas (HRLGGs) have higher requirements for postoperative quality of life. Although adjuvant chemotherapy with delayed radiotherapy is the first treatment strategy for HRLGGs, not all HRLGGs benefit from it. Accurate assessment of chemosensitivity in HRLGGs is vital for making treatment choices. This study developed a multimodal fusion radiomics (MFR) model to support radiochemotherapy decision-making for HRLGGs. Methods: A MFR model combining macroscopic MRI and microscopic pathological images was proposed. Multiscale features including macroscopic tumor structure and microscopic histological layer and nuclear information were grabbed by unique paradigm, respectively. Then, these features were adaptively incorporated into the MFR model through attention mechanism to predict the chemosensitivity of temozolomide (TMZ) by means of objective response rate and progression free survival (PFS). Results: Macroscopic tumor texture complexity and microscopic nuclear size showed significant statistical differences (p < 0.001) between sensitivity and insensitivity groups. The MFR model achieved stable prediction results, with an area under the curve of 0.950 (95% CI: 0.942–0.958), sensitivity of 0.833 (95% CI: 0.780–0.848), specificity of 0.929 (95% CI: 0.914–0.936), positive predictive value of 0.833 (95% CI: 0.811–0.860), and negative predictive value of 0.929 (95% CI: 0.914–0.934). The predictive efficacy of MFR was significantly higher than that of the reported molecular markers (p < 0.001). MFR was also demonstrated to be a predictor of PFS. Conclusions: A MFR model including radiomics and pathological features predicts accurately the response postoperative TMZ treatment. Clinical relevance statement: Our MFR model could identify young high-risk low-grade glioma patients who can have the most benefit from postoperative upfront temozolomide (TMZ) treatment. Key Points: • Multimodal radiomics is proposed to support the radiochemotherapy of glioma. • Some macro and micro image markers related to tumor chemotherapy sensitivity are revealed. • The proposed model surpasses reported molecular markers, with a promising area under the curve (AUC) of 0.95. [ABSTRACT FROM AUTHOR]

Aim: Human stem cells from the apical papilla (SCAPs) are an appealing stem cell source for tissue regeneration engineering. Circular RNAs (circRNAs) are known to exert pivotal regulatory functions in various cell differentiation processes, including osteogenesis of mesenchymal stem cells. However, few studies have shown the potential mechanism of circRNAs in the odonto/osteogenic differentiation of SCAPs. Herein, we identified a novel circRNA, circ‐ZNF236 (hsa_circ_0000857) and found that it was remarkably upregulated during the SCAPs committed differentiation. Thus, in this study, we showed the significance of circ‐ZNF236 in the odonto/osteogenic differentiation of SCAPs and its underlying regulatory mechanisms. Methodology: The circular structure of circ‐ZNF236 was identified via Sanger sequencing, amplification of convergent and divergent primers. The proliferation of SCAPs was detected by CCK‐8, flow cytometry analysis and EdU incorporation assay. Western blotting, qRT‐PCR, Alkaline phosphatase (ALP) and Alizarin red staining (ARS) were performed to explore the regulatory effect of circ‐ZNF236/miR‐218‐5p/LGR4 axis in the odonto/osteogenic differentiation of SCAPs in vitro. Fluorescence in situ hybridization, as well as dual‐luciferase reporting assays, revealed that circ‐ZNF236 binds to miR‐218‐5p. Transmission electron microscopy (TEM) and mRFP‐GFP‐LC3 lentivirus were performed to detect the activation of autophagy. Results: Circ‐ZNF236 was identified as a highly stable circRNA with a covalent closed loop structure. Circ‐ZNF236 had no detectable influence on cell proliferation but positively regulated SCAPs odonto/osteogenic differentiation. Furthermore, circ‐ZNF236 was confirmed as a sponge of miR‐218‐5p in SCAPs, while miR‐218‐5p targets LGR4 mRNA at its 3′‐UTR. Subsequent rescue experiments revealed that circ‐ZNF236 regulates odonto/osteogenic differentiation by miR‐218‐5p/LGR4 in SCAPs. Importantly, circ‐ZNF236 activated autophagy, and the activation of autophagy strengthened the committed differentiation capability of SCAPs. Subsequently, in vivo experiments showed that SCAPs overexpressing circ‐ZNF236 promoted bone formation in a rat skull defect model. Conclusions: Circ‐ZNF236 could activate autophagy through increasing LGR4 expression, thus positively regulating SCAPs odonto/osteogenic differentiation. Our findings suggested that circ‐ZNF236 might represent a novel therapeutic target to prompt the odonto/osteogenic differentiation of SCAPs. [ABSTRACT FROM AUTHOR]

Background: Digital histopathology provides valuable information for clinical decision-making. We hypothesized that a deep risk network (DeepRisk) based on digital pathology signature (DPS) derived from whole-slide images could improve the prognostic value of the tumor, node, and metastasis (TNM) staging system and offer chemotherapeutic benefits for gastric cancer (GC). Methods: DeepRisk is a multi-scale, attention-based learning model developed on 1120 GCs in the Zhongshan dataset and validated with two external datasets. Then, we assessed its association with prognosis and treatment response. The multi-omics analysis and multiplex Immunohistochemistry were conducted to evaluate the potential pathogenesis and spatial immune contexture underlying DPS. Results: Multivariate analysis indicated that the DPS was an independent prognosticator with a better C-index (0.84 for overall survival and 0.71 for disease-free survival). Patients with low-DPS after neoadjuvant chemotherapy responded favorably to treatment. Spatial analysis indicated that exhausted immune clusters and increased infiltration of CD11b+CD11c+ immune cells were present at the invasive margin of high-DPS group. Multi-omics data from the Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD) hint at the relevance of DPS to myeloid derived suppressor cells infiltration and immune suppression. Conclusion: DeepRisk network is a reliable tool that enhances prognostic value of TNM staging and aid in precise treatment, providing insights into the underlying pathogenic mechanisms. [ABSTRACT FROM AUTHOR]

Background: Microglial activation in the spinal trigeminal nucleus (STN) plays a crucial role in the development of trigeminal neuralgia (TN). The involvement of adenosine monophosphate-activated protein kinase (AMPK) and N-methyl-D-aspartate receptor 1 (NMDAR1, NR1) in TN has been established. Initial evidence suggests that stem cells from human exfoliated deciduous teeth (SHED) have a potential therapeutic effect in attenuating TN. In this study, we propose that SHED-derived exosomes (SHED-Exos) may alleviate TN by inhibiting microglial activation. This study sought to assess the curative effect of SHED-Exos administrated through the tail vein on a unilateral infraorbital nerve chronic constriction injury (CCI-ION) model in mice to reveal the role of SHED-Exos in TN and further clarify the potential mechanism. Results: Animals subjected to CCI-ION were administered SHED-Exos extracted by differential ultracentrifugation. SHED-Exos significantly alleviated TN in CCI mice (increasing the mechanical threshold and reducing p-NR1) and suppressed microglial activation (indicated by the levels of TNF-α, IL-1β and IBA-1, as well as p-AMPK) in vivo and in vitro. Notably, SHED-Exos worked in a concentration dependent manner. Mechanistically, miR-24-3p-upregulated SHED-Exos exerted a more significant effect, while miR-24-3p-inhibited SHED-Exos had a weakened effect. Bioinformatics analysis and luciferase reporter assays were utilized for target gene prediction and verification between miR-24-3p and IL1R1. Moreover, miR-24-3p targeted the IL1R1/p-p38 MAPK pathway in microglia was increased in CCI mice, and participated in microglial activation in the STN. Conclusions: miR-24-3p-encapsulated SHED-Exos attenuated TN by suppressing microglial activation in the STN of CCI mice. Mechanistically, miR-24-3p blocked p-p38 MAPK signaling by targeting IL1R1. Theoretically, targeted delivery of miR-24-3p may offer a potential strategy for TN. [ABSTRACT FROM AUTHOR]

Aim: Recently, miR‐27b‐5p was shown to be abundantly expressed in extracellular vehicles (EVs) from the inflammatory microenvironment. This study determined the role of miR‐27b‐5p in regulating osteogenic and odontogenic differentiation of stem cells from human exfoliated deciduous teeth (SHEDs) and further examined the regulatory mechanism of bone morphogenetic protein receptor type‐1A (BMPR1A). Methodology: Characteristics of SHEDs and SHEDs‐EVs derived from SHEDs were evaluated respectively. The expression of miR‐27b‐5p in SHEDs and EVs was detected during osteo‐induction. Mechanically, SHEDs were treated with miR‐27b‐5p mimics or an inhibitor, and the osteogenic/odontogenic differentiation and proliferation were assessed. Bioinformatic analysis and luciferase reporter were utilized for target gene prediction and verification. Finally, BMPR1A‐overexpressed plasmids were transfected into SHEDs to investigate the participation of the BMPR1A/SMAD4 pathway. Data were analysed using Student's t‐test, one‐way analysis of variance and Chi‐square test. Results: MiR‐27b‐5p was expressed in both SHEDs and EVs and was significantly increased at the initial stage of differentiation and then decreased in a time‐dependent manner (p <.01). Upregulation of miR‐27b‐5p significantly suppressed osteogenic/odontogenic differentiation of SHEDs and inhibited proliferation (p <.05), whereas inhibition of miR‐27b‐5p enhanced the differentiation (p <.05). Dual‐luciferase reporter assay and pull‐down assay confirmed the binding site between miR‐27b‐5p and BMPR1A (p <.05). The overexpression of BMPR1A rescued the effect of miR‐27b‐5p, while contributed to the decrease of pluripotency (p <.05). Additionally, miR‐27b‐5p maintained pluripotency in BMPR1A‐overexpressed SHEDs (p <.05). Conclusions: MiR‐27b‐5p in SHEDs/EVs was inversely associated with differentiation and suppressed the osteogenic and odontogenic differentiation of SHEDs and maintained the pluripotency of SHEDs partly by shuttering BMPR1A‐targeting BMP signalling. Theoretically, inhibition of miR‐27b‐5p represents a potential strategy to promote osteanagenesis and dentinogenesis. However, miR‐27b‐5p capsuled EVs might maintain cell pluripotency and self‐renewal for non‐cell‐targeted therapy. [ABSTRACT FROM AUTHOR]

A correction to the article "Contribution of major SSTA modes to the climate variability of tropical cyclone genesis frequency over the western North Pacific" that was published in the February 3, 2016 issue is presented

In recent years, plane-wave imaging (PWI) has attracted considerable attention because of its high temporal resolution. However, the low spatial resolution of PWI limits its clinical applications, which has inspired various studies on the high spatial resolution reconstruction of PW ultrasound images. Although compounding methods and traditional high spatial resolution reconstruction approaches can improve the image quality, these techniques decrease the temporal resolution. Since learning methods can fully reserve the high temporal resolution of PW ultrasounds, a novel convolutional neural network (CNN) model for the high spatial–temporal resolution reconstruction of PW ultrasound images is proposed in this paper. Considering the multiangle form of PW data, a multichannel model is introduced to produce balanced training. To combine local and contextual information, the multiscale model is adopted. These two innovations constitute our multichannel and multiscale CNN (MMCNN) model. Compared with traditional CNN methods, the proposed model uses a two-stage structure in which a cascading wavelet postprocessing stage is combined with the trained MMCNN model. Cascading wavelet postprocessing aims to preserve speckle information. Furthermore, a feedback system is appended to the iteration process of the network training to solve the overfitting problem and help produce convergence. Based on these improvements, an end-to-end mapping is established between a single-angle B-mode PW image and its corresponding multiangle compounded, high-resolution image. The experiments were conducted on simulated, phantom, and real human data. The advantages of our proposed method were compared with a coherent PW compounding method, a conventional maximuma posteriori-based high spatial resolution reconstruction method, and a 2-D CNN compounding method, and the results verified that our approach is capable of attaining a better temporal resolution and comparable spatial resolution. In clinical usage, the proposed method is equipped to satisfy with many ultrafast imaging applications, which require high spatial–temporal resolution. i [ABSTRACT FROM AUTHOR]

Early screening and frequent monitoring effectively decrease the risk of severe scoliosis, but radiation exposure is a consequence of traditional radiograph examinations. Additionally, traditional X-ray images on the coronal or sagittal plane have difficulty providing three-dimensional (3-D) information on spinal deformities. The Scolioscan system provides an innovative 3-D spine imaging approach via ultrasonic scanning, and its feasibility has been demonstrated in numerous studies. In this paper, to further examine the potential of spinal ultrasonic data for describing 3-D spinal deformities, we propose a novel deep-learning tracker named Si-MSPDNet for extracting widely employed landmarks (spinous process (SP)) in ultrasonic images of spines and establish a 3-D spinal profile to measure 3-D spinal deformities. Si-MSPDNet has a Siamese architecture. First, we employ two efficient two-stage encoders to extract features from the uncropped ultrasonic image and the patch centered on the SP cut from the image. Then, a fusion block is designed to strengthen the communication between encoded features and further refine them from channel and spatial perspectives. The SP is a very small target in ultrasonic images, so its representation is weak in the highest-level feature maps. To overcome this, we ignore the highest-level feature maps and introduce parallel partial decoders to localize the SP. The correlation evaluation in the traditional Siamese network is also expanded to multiple scales to enhance cooperation. Furthermore, we propose a binary guided mask based on vertebral anatomical prior knowledge, which can further improve the performance of our tracker by highlighting the potential region with SP. The binary-guided mask is also utilized for fully automatic initialization in tracking. We collected spinal ultrasonic data and corresponding radiographs on the coronal and sagittal planes from 150 patients to evaluate the tracking precision of Si-MSPDNet and the performance of the generated 3-D spinal profile. Experimental results revealed that our tracker achieved a tracking success rate of 100% and a mean IoU of 0.882, outperforming some commonly used tracking and real-time detection models. Furthermore, a high correlation existed on both the coronal and sagittal planes between our projected spinal curve and that extracted from the spinal annotation in X-ray images. The correlation between the tracking results of the SP and their ground truths on other projected planes was also satisfactory. More importantly, the difference in mean curvatures was slight on all projected planes between tracking results and ground truths. Thus, this study effectively demonstrates the promising potential of our 3-D spinal profile extraction method for the 3-D measurement of spinal deformities using 3-D ultrasound data. • A novel tracker is proposed to real-time extracting spinous processes in 3D ultrasonic images. • Vertebral anatomical prior and spinal continuity are introduced into our tracker. • Experimental results indicate that our tracker can effectively describe 3-D spinal deformities. [ABSTRACT FROM AUTHOR]

Accurate and rapid segmentation of the hippocampus can help doctors perform intractable temporal lobe epilepsy (TLE) preoperative evaluations to identify good surgical candidates. This study aims to establish a radiomics system for the automatic diagnosis of hippocampal sclerosis with the help of machine learning. A total of 240 cases were analysed to develop a diagnostic model. First, an automatic hippocampal segmentation process was established that exploits a priori knowledge of the relatively fixed location of the hippocampus in brain partitions, as well as a deep-learning segmentation network based on an Attention U-net. Then, we extracted 527 radiomics features from each side of the segmented hippocampus. The iterative sparse representation based on feature selection and a support vector machine classifier were finally used to establish the diagnostic model of hippocampal sclerosis. The diagnostic model consists of two consecutive steps: distinguish hippocampal sclerosis (HS) from normal control (NC) and detect whether the HS is located on the left or right side. When the automatic diagnosis model identified HS and NC, the sensitivity and specificity reached 0.941 and 0.917 in the 10-fold cross-validation set and 0.920 and 0.909 in the independent testing set. When the diagnostic model detected HS lateralization, the sensitivity and specificity reached 0.923 and 0.920 in cross-validation and 0.909 and 0.929 in independent testing. Our results show that the developed radiomics model can help detect TLE patients with hippocampal sclerosis and has the potential to simplify preoperative evaluations and select surgical candidates. [ABSTRACT FROM AUTHOR]

Cisplatin resistance poses a substantial hurdle in effectively treating head and neck squamous cell carcinoma (HNSCC). Utilizing multiple tumor models and examining an internal HNSCC cohort, squalene epoxidase (SQLE) is pinpointed as a key driver of chemoresistance and tumorigenesis, operating through a cholesterol‐dependent pathway. Comprehensive transcriptomic analysis reveals that SQLE is essential for maintaining c‐Myc transcriptional activity by stabilizing the c‐Myc protein and averting its ubiquitin‐mediated degradation. Mechanistic investigation demonstrates that SQLE inhibition diminishes Akt's binding affinity to lipid rafts via a cholesterol‐dependent process, subsequently deactivating lipid raft‐localized Akt, reducing GSK‐3β phosphorylation at S9, and increasing c‐Myc phosphorylation at T58, ultimately leading to c‐Myc destabilization. Importantly, employing an Sqle conditional knockout mouse model, SQLE's critical role in HNSCC initiation and progression is established. The preclinical findings demonstrate the potent synergistic effects of combining terbinafine and cisplatin in arresting tumor growth. These discoveries not only provide novel insights into the underlying mechanisms of SQLE‐mediated cisplatin resistance and tumorigenesis in HNSCC but also propose a promising therapeutic avenue for HNSCC patients unresponsive to conventional cisplatin‐based chemotherapy. [ABSTRACT FROM AUTHOR]

Moyamoya disease (MMD) is a serious intracranial cerebrovascular disease. Cerebral hemorrhage caused by MMD will bring life risk to patients. Therefore, MMD detection is of great significance in the prevention of cerebral hemorrhage. In order to improve the accuracy of digital subtraction angiography (DSA) in the diagnosis of ischemic MMD, in this paper, a deep network architecture combined with 3D convolutional neural network (3D CNN) and bidirectional convolutional gated recurrent unit (BiConvGRU) is proposed to learn the spatiotemporal features for ischemic MMD detection. Firstly, 2D convolutional neural network (2D CNN) is utilized to extract spatial features for each frame of DSA. Secondly, the long-term spatiotemporal features of DSA sequence are extracted by BiConvGRU. Thirdly, the short-term spatiotemporal features of DSA are further extracted by 3D convolutional neural network (3D CNN). In addition, different features are extracted when gray images and optical flow images pass through the network, and multiple features are extracted by features fusion. Finally, the fused features are utilized to classify. The proposed method was quantitatively evaluated on a data sets of 630 cases. The experimental results showed a detection accuracy of 0.9788, sensitivity and specificity were 0.9780 and 0.9796, respectively, and area under curve (AUC) was 0.9856. Compared with other methods, we can get the highest accuracy and AUC. The experimental results show that the proposed method is stable and reliable for ischemic MMD detection, which provides an option for doctors to accurately diagnose ischemic MMD. [ABSTRACT FROM AUTHOR]

Objective: This study aims to investigate the regulatory effect of hypoxia on human periodontal ligament stem cells (PDLSCs) through RNA sequencing (RNA SEQ). Human PDLSCs were cultured in normoxia (20% O2) or hypoxia (2% O2). Material and Methods: Total RNA was extracted and sequenced. The expression profiles of circRNAs, lncRNAs, and miRNAs were determined, and the lncRNA/circRNA‐miRNA‐mRNA networks were analyzed. Results: In total, 15 miRNAs, 449 lncRNAs, and 53 circRNAs were differentially expressed. Among them, 21 circRNAs, 262 lncRNAs, 5 miRNAs, and 5 mRNAs were selected to construct competing endogenous RNA (ceRNA) networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were carried out to explore potential related pathways and regulatory functions. Several ceRNA axes (lncRNA‐FTX/circRNA‐FAT1‐hsa‐miR‐4781‐3p‐SMAD5 and circRNA LPAR1‐hsa‐miR‐342‐3p‐ADAR) may provide a theoretical basis on the study of osteogenic differentiation of PDLSCs under hypoxia. Conclusion: This study revealed that the expression profiles of circRNAs, lncRNAs, and miRNAs had changed significantly in PDLSCs cultured in 2% O2; specific circRNAs/lncRNAs may play a competitive role in the differentiation of PDLSCs. [ABSTRACT FROM AUTHOR]

Tissue harmonic imaging (THI) utilizes harmonic signals generating within the tissue as the result of nonlinear acoustic wave propagation. With inadequate transmitting acoustic energy, THI is incapable to detect the small objects since poor harmonic signals have been generated. In most cases, high transmission energy cannot be guaranteed because of the imaging safety issue or specific imaging modality such as the plane wave imaging (PWI). Discrimination of small point targets such as calcification, however, is particularly important in the ultrasound diagnosis. Few efforts have been made to pursue the THI with high resolution and good small target visibility at the same time. In this paper, we proposed a new eigenspace-based coherence factor (ESBCF) beamformer to solve this problem. A new kind of coherence factor (CF), named as ESBCF, is firstly proposed to detect the point targets. The detected region-of-interest (ROI) is then enhanced adaptively by using a newly developed beamforming method. The ESBCF combines the information from signal eigenspace and coherence factor by expanding the CF to the covariance matrix of signal. Analogous to the image processing but in the radio frequency (RF) data domain, the proposed method fully utilizes the information from the fundamental and harmonic components. The performance of the proposed method is demonstrated by simulation and phantom experiments. The improvement of the point contrast ratio (PCR) is 7.6 dB in the simulated data, and 6.0 dB in the phantom experiment. Thanks to the improved small point detection ability of the ESBCF, the proposed beamforming algorithm can enhance the PCR considerably and maintain the high resolution of the THI at the same time. [ABSTRACT FROM AUTHOR]

This paper introduces a new beamformer, which combines the eigenspace based minimum variance (ESBMV) beamformer with a subarray coherence based postfilter (SCBP), for improving the quality of ultrasound plane-wave imaging. The ESBMV beamformer has been validated in improving the imaging contrast, but the difficulty in dividing the signal subspace limits the usage of it in the low signal-to-noise ratio (SNR) scenarios. Coherence factor (CF) based methods could optimize the output of a distortionless beamformer to reduce sidelobes, but the influence by the subarray decorrelation technique on the postfilter design has not attracted enough concern before. Accordingly, an ESBMV-SCBP beamformer was proposed in this paper, which used the coherence of the subarray signal to compute an SCBP to optimize the ESBMV results. Simulated and experimental data were used to evaluate the performance of the proposed method. The results showed that the ESBMV-SCBP method achieved an improved imaging quality compared with the ESBMV beamformer. In the simulation study, the contrast ratio (CR) for an anechoic cyst was improved by 9.88 dB and the contrast-to-noise ratio (CNR) was improved by 0.97 over the ESBMV. In the experimental study, the CR improvements for two anechoic cysts were 7.32 dB and 9.45 dB, while the CNRs were improved by 1.27 and 0.66, respectively. The ESBMV-SCBP also showed advantages over the ESBMV-Wiener beamformer in preserving a less grainy speckle, which is closer to that of distortionless beamformers and benefits the imaging contrast. With a relatively small extra computational load, the proposed method has potential to enhance the quality of the ultrasound plane-wave imaging. [ABSTRACT FROM AUTHOR]

Azoles have been widely employed for the treatment of invasive fungal diseases; however, their efficacy is diminished as pathogenic fungi tolerate them due to their fungistatic properties. Geldanamycin (GdA) can render azoles fungicidal by inhibiting the ATPase and molecular chaperone activities of heat shock protein 90 (Hsp90). Nonetheless, the clinical applicability of GdA is restricted due to its cytotoxic ansamycin scaffold structure, its induction of cytoprotective heat shock responses, and the conservative nature of Hsp90. Hence, it is imperative to elucidate the mechanism of action of GdA to confer fungicidal properties to azoles and mitigate the toxic adverse effects associated with GdA. Through various experimental methods, including the construction of gene-deleted Candida albicans mutants, in vitro drug sensitivity experiments, Western blot analysis, reactive oxygen species (ROS) assays, and succinate dehydrogenase activity assays, we identified Hsp90 client proteins associated with the tolerance of C. albicans to azoles. It was observed that GdA effectively hindered the entry of Hsp90 into mitochondria, resulting in the alleviation of inhibitory effect of Hsp90 on succinate dehydrogenase. Consequently, the activation of succinate dehydrogenase led to an increased production of ROS. within the mitochondria, thereby facilitating the antifungal effects of azoles against C. albicans. This research presents a novel approach for conferring fungicidal properties to azoles, which involves specifically disrupting the interaction of between Hsp90 and succinate dehydrogenase rather than employing a non-specific inhibition of ATPase activity of Hsp90. [ABSTRACT FROM AUTHOR]

Background: Extracellular vesicles (EVs) play a key role in constructing a microenvironment that favors the differentiation of stem cells. The present work aimed to determine the molecular mechanisms by which EV derived from inflammatory dental pulp stem cell (iDPSC-EV) influence periodontal ligament stem cells (PDLSCs) and provide a potential strategy for bone and dental pulp regeneration.Methods: The osteogenic and odontogenic differentiation was assessed by quantitative real-time polymerase chain reaction (qRT-PCR), western blot, alkaline phosphatase (ALP) activity assay, ALP staining, alizarin red S (ARS) staining, and immunofluorescence staining. To detect proliferation, the Cell Counting Kit-8 (CCK-8) assay, and flow cytometry analysis were used. EVs were isolated by the Exoperfect kit and ultrafiltration and characterized by transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and western blot. The expression profile of miRNAs in EVs was studied using miRNA sequence and bioinformatics, and one of the upregulated miRNAs was evaluated on PDLSCs.Results: The inflammatory microenvironment stimulated osteogenic and odontogenic differentiation of DPSCs and iDPSC-EV behaved alike on PDLSCs. MiR-758-5p was upregulated in iDPSC-EV and was demonstrated to play a significant role in the osteogenic and odontogenic commitment of PDLSCs. A dual-luciferase reporter assay confirmed the binding site between miR-758-5p and limb development membrane protein 1 (LMBR1). The knockdown of LMBR1 also enhanced the above potential. Mechanically, bone morphogenetic protein (BMP) signaling was activated.Conclusions: EVs from the inflammatory microenvironment enhanced the osteogenic and odontogenic differentiation of PDLSCs partly by shuttering LMBR1-targeting miR-758-5p via BMP signaling. [ABSTRACT FROM AUTHOR]

Background: This study explored the feasibility of radiofrequency (RF)-based radiomics analysis techniques for the preoperative prediction of programmed cell death protein 1 (PD-1) in patients with hepatocellular carcinoma (HCC).Methods: The RF-based radiomics analysis method used ultrasound multifeature maps calculated from the RF signals of HCC patients, including direct energy attenuation (DEA) feature map, skewness of spectrum difference (SSD) feature map, and noncentrality parameter S of the Rician distribution (NRD) feature map. From each of the above ultrasound maps, 345 high-throughput radiomics features were extracted. Then, the useful radiomics features were selected by the sparse representation method and input into support vector machine (SVM) classifier for PD-1 prediction.Results and Conclusion: Among all the RF-based prediction models and the ultrasound grayscale comparative model, the RF-based model using all of the three ultrasound feature maps had the highest prediction accuracy (ACC) and area under the curve (AUC), which were 92.5% and 94.23%, respectively. The method proposed in this paper is effective for the meaningful feature extraction of RF signals and can effectively predict PD-1 in patients with HCC. [ABSTRACT FROM AUTHOR]

Background: Traumatic brain injury is a common and devastating injury that is the leading cause of neurological disability and death worldwide. Patients with cerebral lobe contusion received conservative treatment because of their mild manifestations, but delayed intracranial hematoma may increase and even become life-threatening. We explored the noninvasive method to predict the prognosis of progression and Glasgow Outcome Scale (GOS) by using a quantitative radiomics approach and statistical analysis. Methods: Eighty-eight patients who were pathologically diagnosed were retrospectively studied. The radiomics method developed in this work included image segmentation, feature extraction, and feature selection. The nomograms were established based on statistical analysis and a radiomics method. We conducted a comparative study of hematoma progression and GOS between the clinical factor alone and fusion radiomics features. Results: Nineteen clinical factors, 513 radiomics features, and 116 locational features were considered. Among clinical factors, international normalized ratio, prothrombin time, and fibrinogen were enrolled for hematoma progression. As for GOS, treatment strategy, age, Glasgow Coma Scale score, and blood platelet were associated factors. Eight features for GOS and five features for hematoma progression were filtered by using sparse representation and locality preserving projection-combined method. Four nomograms were constructed. After fusion radiomics features, area under the curve of hematoma progression prediction increased from 0.832 to 0.899, whereas GOS prediction went from 0.794 to 0.844. Conclusions: A radiomic-based model that merges radiomics and clinical features is a noninvasive approach to predict hematoma progression and clinical outcomes of cerebral contusions in traumatic brain injury. [ABSTRACT FROM AUTHOR]