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Despite various treatment options for canine atopic dermatitis (cAD), therapeutic limitations still exist, including adverse effects and low absorption ratios. This study evaluated the effects of a membrane-free stem cell extract (MFSCE) on the clinical signs of atopic dogs. Thirty client-owned dogs previously diagnosed with cAD were separated into placebo (n = 10) and MFSCE-treated groups (n = 20). The dogs were treated with a cream (MFSCE and placebo) via dermal administration twice daily for 14 days, and the clinical response was recorded on days 0, 7, and 14. The MFSCE-treated group showed significantly decreased severity of pruritus on day 14 compared to that on day 0. In addition, the erythema, pigmentation, skin dryness, and thickness were remarkably decreased in the MFSCE-treated group on day 14 compared to those on day 0 whereas no significant changes were observed in the placebo-treated group. No general clinical signs or adverse effects were observed in this study. These results suggest that MFSCE could be a surrogate treatment option for cAD.

Gender and biological sex have distinct impacts on the pathogenesis of type 2 diabetes (T2D). Estrogen deficiency is known to predispose female mice to T2D. In our previous study, we found that a high-fat, high-sucrose diet (HFHSD) induces T2D in male mice through the miR-10b-5p/KLF11/KIT pathway, but not in females, highlighting hormonal disparities in T2D susceptibility. However, the underlying molecular mechanisms of this hormonal protection in females remain elusive. To address this knowledge gap, we utilized ovariectomized, estrogen-deficient female mice, fed them a HFHSD to induce T2D, and investigated the molecular mechanisms involved in estrogen-deficient diabetic female mice, relevant cell lines, and female T2D patients. Initially, female mice fed a HFHSD exhibited a delayed onset of T2D, but ovariectomy-induced estrogen deficiency promptly precipitated T2D without delay. Intriguingly, insulin (INS) was upregulated, while insulin receptor (INSR) and protein kinase B (AKT) were downregulated in these estrogen-deficient diabetic female mice, indicating insulin-resistant T2D. These dysregulations of INS, INSR, and AKT were mediated by a miR-10a/b-5p-NCOR2 axis. Treatment with miR-10a/b-5p effectively alleviated hyperglycemia in estrogen-deficient T2D female mice, while β-estradiol temporarily reduced hyperglycemia. Consistent with the murine findings, plasma samples from female T2D patients exhibited significant reductions in miR-10a/b-5p, estrogen, and INSR, but increased insulin levels. Our findings suggest that estrogen protects against insulin-resistant T2D in females through miR-10a/b-5p/NCOR2 pathway, indicating the potential therapeutic benefits of miR-10a/b-5p restoration in female T2D management. [ABSTRACT FROM AUTHOR]

In this paper, modified transformer-based fault detection for a hydraulic pump is performed using the pressure signals of the hydraulic pump. The pump is considered a swash plate axial piston pump used in the excavator. Additionally, the outlet pressure data of the pump are extracted based on Amesim. The proposed transformer is a modified transformer, which allows fast fault detection by modifying the transformer and reducing the size of this model. The classes are normal and 6 fault types, and comparison models are long short-term memory (LSTM) and its family models, which are representative time series models. Unlike comparison models, the modified transformer has an average accuracy of 100% and a detection time of 0.00271 s, which is a slight difference of 0.00036 s from the single LSTM that showed the shortest operation time among the models. We also perform fault detection by changing data points and show a stable high accuracy of 99.93% for all data points of 500, 1,000, and 1,500 without any optimization. Various external noises are added because excavators are construction equipment used in rough terrain. Therefore, we conduct detection performance analysis at different additional noise levels with Gaussian noise with zero mean. As a result, we confirm that the modified transformer showed a high detection accuracy of over 98.08% up to standard deviation 4, where data characteristics were well maintained, unlike other time series models. Through the various analyses above, we confirm that fast and accurate fault detection is possible based on the modified transformer.

Metalloendopeptidase ADAM-Like Decysin 1 (ADAMDEC1) is an anti-inflammatory peptidase that is almost exclusively expressed in the gastrointestinal (GI) tract. We have recently found abundant and selective expression of Adamdec1 in colonic mucosal PDGFRα+ cells. However, the cellular origin for this gene expression is controversial as it is also known to be expressed in intestinal macrophages. We found that Adamdec1 mRNAs were selectively expressed in colonic mucosal subepithelial PDGFRα+ cells. ADAMDEC1 protein was mainly released from PDGFRα+ cells and accumulated in the mucosal layer lamina propria space near the epithelial basement membrane. PDGFRα+ cells significantly overexpressed Adamdec1 mRNAs and protein in DSS-induced colitis mice. Adamdec1 was predominantly expressed in CD45− PDGFRα+ cells in DSS-induced colitis mice, with only minimal expression in CD45+ CD64+ macrophages. Additionally, overexpression of both ADAMDEC1 mRNA and protein was consistently observed in PDGFRα+ cells, but not in CD64+ macrophages found in human colonic mucosal tissue affected by Crohn's disease. In summary, PDGFRα+ cells selectively express ADAMDEC1, which is localized to the colon mucosa layer. ADAMDEC1 expression significantly increases in DSS-induced colitis affected mice and Crohn's disease affected human tissue, suggesting that this gene can serve as a diagnostic and/or therapeutic target for intestinal inflammation and Crohn's disease. [ABSTRACT FROM AUTHOR]

Leatherback turtles Dermochelys coriacea are experiencing population declines due to various anthropogenic threats. Beaches play a crucial role in the survival of sea turtle species since reproductive success is affected by environmental conditions inside the nest. Climate change is predicted to increase sand temperatures and affect rainfall, which will change the nest microenvironment, and thus may alter not only hatch and emergence success but also hatchling morphology and performance. This study examined the relationship between nest incubation temperatures and leatherback hatchling terrestrial performance, as the crawl from the nest to the sea is a critical phase for hatchling survival. Temperature data loggers were placed in 12 leatherback turtle nests on the day they were laid across the early, middle, and late South Florida nesting season. Upon emergence, hatchlings were tested for righting ability and crawling speeds. Mean nest temperatures ranged from 29.0 to 32.5°C and were significantly higher in mid- and late-season nests compared to early-season nests. Hatching and emergence success correlated with temperature, where the mid-season nests were the most successful. Hatchling morphology also correlated with temperature; nests with lower temperatures produced larger hatchlings than nests with hotter temperatures. Righting response scores were significantly lower in hatchlings from late-season, hotter nests, while there was no correlation between crawling speeds and temperature. However, more studies are needed to investigate these relationships since the sample size of this study was relatively small. Our data provide insight into how rising nest temperatures may impact hatchling performance and, in turn, affect their survival.

Abstract Background Large-scale data on the photosynthetic characteristics of whole crop canopy is crucial for improving yield. However, current data collection methods remain challenging, and the time constraints associated with photosynthetic data collection further complicate matters. Developing a practical yet easy-to-use tool for collecting whole-canopy data is essential to address these challenges. Furthermore, it is necessary to obtain instantaneous measurements of photosynthetic rate over a wide range of CO2 concentrations under an unsteady state to enable faster data collection and obtain reliable biochemical limits of carbon assimilation. This study developed a semi-open chamber system with steady and unsteady state measurement techniques to collect biochemical photosynthetic data from an entire cucumber canopy, emphasizing the correction procedures for CO2 concentration of unsteady state measurements applicable regardless of chamber scale. Results After constructing a semi-open chamber system, we described how to correct measurement errors according to chamber volume. In order to assess the accuracy of the newly developed system, an analysis was conducted to determine the overall measurement error resulting from variations in the reference, sample CO2 concentration, and leakage flow rate. The total measurement error was accurate to no more than 10%. Furthermore, the difference between the photosynthetic rate of the single leaf and that of the whole-canopy was not significant in Rubisco activity-limited carboxylation range. In addition, the Farquhar–von Caemmerer–Berry (FvCB) model parameters and the photosynthetic rate estimation values were compared to evaluate the steady- and unsteady state measurement methods between the cucumber seedlings' single-leaf and whole-canopy. The average root mean square error of the FvCB model in the steady (standard A-Ci response) and unsteady states (800 to 400 ramp) of the chambers was 1.4 and 2.3, respectively. Results show that the developed system is suitable for measuring the gas exchange rate of the cucumber canopy. Conclusions We demonstrate the correction method for measurement errors to enable the gas exchange rate of the whole-canopy even in an unsteady state. The correction method of the measurement system of the gas exchange rate for the whole- canopy can be applied regardless of the volume of the chamber, and it can be applied simply to other chamber systems. In addition, an unsteady state measurement method for fast data collection was also applicable. However, it was deemed necessary to identify a more optimal measurement range by conducting measurements across a broader range of values.

We aimed to develop a more accurate transpiration model for cucumber (Cucumis sativus L.) plants to optimize irrigation and nutrient usage in soilless greenhouse cultivation. Accurate modeling of transpiration in greenhouse-grown cucumbers is crucial for effective cultivation practices. Existing models have limitations that hinder their applicability. Therefore, this research focused on refining the modeling approach to address these limitations. To achieve this, a comprehensive methodology was employed. The actual transpiration rates of three cucumber plants were measured using a load cell, enabling crop fresh weight changes to be calculated. The transpiration model was developed by making specific corrections to the formula derived from the Penman-Monteith equation. In addition, the study investigated the relationship between transpiration rate and solar radiation (Rad) and vapor pressure deficit (VPD), identifying a nonlinear association between these variables. The transpiration model was adjusted to account for these nonlinear relationships and compensate for Rad and VPD. Comparative analysis between the actual and estimated transpiration rates demonstrated that the developed cucumber transpiration model reduced overestimation by 23.69%. Furthermore, the model exhibited higher coefficients of determination and root mean square error (RMSE) values than existing models, suggesting its superior accuracy in predicting transpiration rates. Implementing the transpiration model-based irrigation method demonstrated the potential for ∼21% nutrient savings compared with conventional irrigation practices. This finding highlights the practical applications of the developed model—accounting for a nonlinearity of Rad and VPD—in optimizing irrigation practices for greenhouse cucumber cultivation.

A randomly connected single-walled carbon nanotube (CNT) network film is suggested as an optically homogenous thin film to implement a tunable diffractive optical element with a subwavelength thickness. A Fresnel zone plate (FZP) as a thin-film lens is successfully realized by mask-free direct laser writing onto the CNT network film with a thickness of 450 nm. The fabricated FZP exhibits an intense three-dimensional focus having lateral and axial focal sizes of 0.95λ and 7.10λ, respectively, at the wavelength of 1550 nm. Furthermore, we show that the intensities at focal points of the first and second diffraction orders can be significantly modulated by 72% and 40% through ion-gel gating between +1.8 V and −1.8 V. These results may offer the potential for electro-optic tunability in multifocal diffraction flat optics and the like.

The receptacle of strawberry is a more direct part than the flower for predicting yield as they eventually become fruits. Thus, we tried to predict the yield by combining an AI technique for receptacle detection in images and statistical analysis on the relationship between the number of receptacles detected and the strawberry yield over a period of time. Five major cultivars were cultivated to consider the cultivar characteristics and environmental factors for two years were collected to consider the climate difference. Faster R–CNN based object detector was used to estimate the number of receptacles per strawberry plant in given two-dimensional images, which achieved a mAP of 0.6587 for our dataset. However, not all receptacles appear on the two-dimensional images, and Bayesian analysis was used to model the uncertainty associated with the number of receptacles missed by the AI. After estimating the probability of fruiting per receptacle, prediction models for the total strawberry yield at the end of harvest season were evaluated. Even though the detection accuracy was not perfect, the results indicated that counting the receptacles by object detection and estimating the probability of fruiting per receptacle by Bayesian modeling are more useful for predicting the total yield per plant than knowing its cumulative yield during the first month.

Aims In this study, we aimed to explore surgical variations in the Femoral Neck System (FNS) used for stable fixation of Pauwels type III femoral neck fractures. Methods Finite element models were established with surgical variations in the distance between the implant tip and subchondral bone, the gap between the plate and lateral femoral cortex, and inferior implant positioning. The models were subjected to physiological load. Results Under a load of single-leg stance, Pauwels type III femoral neck fractures fixed with 10 mm shorter bolts revealed a 7% increase of the interfragmentary gap. The interfragmentary sliding, compressive, and shear stress remained similar to models with bolt tips positioned close to the subchondral bone. Inferior positioning of FNS provided a similar interfragmentary distance, but with 6% increase of the interfragmentary sliding distance compared to central positioning of bolts. Inferior positioning resulted in a one-third increase in interfragmentary compressive and shear stress. A 5 mm gap placed between the diaphysis and plate provided stability comparable to standard fixation, with a 7% decrease of interfragmentary gap and sliding distance, but similar compressive and shear stress. Conclusion Finite element analysis with FNS on Pauwels type III femoral neck fractures revealed that placement of the bolt tip close to subchondral bone provides increased stability. Inferior positioning of FNS bolt increased interfragmentary sliding distance, compressive, and shear stress. The comparable stability of the fixation model with the standard model suggests that a 5 mm gap placed between the plate and diaphysis could viably adjust the depth of the bolt. Cite this article: Bone Joint Res 2022;11(2):102–111.