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During the development of animal organs, various adverse stimuli or toxic environments can induce oxidative stress and delay ovarian development. Paeoniflorin (PF), the main active ingredient of the traditional Chinese herb Paeonia lactiflora Pall., has protective effects on various diseases by preventing oxidative stress. However, the mechanism by which PF attenuates oxidative damage in mouse ovaries remains unclear. We evaluated the protective effects of PF on ovaries in an H2O2-induced mouse oxidative stress model. The H2O2-induced mouse ovarian oxidative stress model was used to explore the protective effect of PF on ovarian development. Histology and follicular development were observed. We then detected related indicators of cell apoptosis, oxidative stress, and autophagy in mouse ovaries. We found that PF inhibited H2O2-induced ovarian cell apoptosis and ferroptosis and promoted granulosa cell proliferation. PF prevented oxidative stress by increasing nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) expression levels. In addition, the autophagic flux of ovarian cells was activated and was accompanied by increased lysosomal biogenesis. Moreover, PF-mediated autophagy was involved in clearing mitochondria damaged by H2O2. Importantly, PF administration significantly increased the number of primordial follicles, primary follicles, secondary follicles, and antral follicles. PF administration improved ovarian sizes compared with the H2O2 group. The present study suggested that PF administration reversed H2O2-induced ovarian developmental delay and promoted follicle development. PF-activated mitophagy is crucial for preventing oxidative stress and improving mitochondrial quality.

Zearalenone (ZEA), one of the non-steroidal estrogen mycotoxin, can cause male reproductive damage and genotoxicity in mammals. Testicular oxidative injury is an important factor causing male sterility. Testicular Sertoli cells are essential for spermatogenesis and male fertility. At present, the mechanism of oxidative injury in dairy goat Sertoli cells after exposure to ZEA remains unclear. This study explored the effects of ZEA on oxidative stress and autophagy in dairy goat Sertoli cells. It was found that treatment of primary Sertoli cells with 25, 50 and 100 μmol/L ZEA for 24 h can promote ROS production, decrease cell viability, antioxidant enzyme activity and mitochondrial membrane potential, induce caspase-dependent cell apoptosis and autophagy activity. ZEA-induced autophagy was confirmed by LC3-I/LC3-II transformation. More importantly, N-acetylcysteine (NAC) pretreatment can remarkably inhibit ZEA-induced oxidative stress, apoptosis and autophagy in Sertoli cells by eliminating ROS. In conclusion, this study indicates that ZEA induces oxidative stress and autophagy in dairy goat Sertoli cells by promoting ROS production.

Abstract Background Goat milk is very similar to human milk in terms of its abundant nutrients and ease of digestion. To derive greater economic benefit, farmers require more female offspring (does); however, the buck-to-doe offspring sex ratio is approximately 50%. At present, artificial insemination after the separation of X/Y sperm using flow cytometry is the primary means of controlling the sex of livestock offspring. However, flow cytometry has not been successfully utilised for the separation of X/Y sperm aimed at sexing control in dairy goats. Results In this study, a novel, simple goat sperm sexing technology that activates the toll-like receptor 7/8 (TLR7/8), thereby inhibiting X-sperm motility, was investigated. Our results showed that the TLR7/8 coding goat X-chromosome was expressed in approximately 50% of round spermatids in the testis and sperm, as measured from cross-sections of the epididymis and ejaculate, respectively. Importantly, TLR7/8 was located at the tail of the X-sperm. Upon TLR7/8 activation, phosphorylated forms of glycogen synthase kinase α/β (GSK3 α/β) and nuclear factor kappa-B (NF-κB) were detected in the X-sperm, causing reduced mitochondrial activity, ATP levels, and sperm motility. High-motility Y-sperm segregated to the upper layer and the low-motility X-sperm, to the lower layer. Following in vitro fertilisation using the TLR7/8-activated sperm from the lower layer, 80.52 ± 6.75% of the embryos were XX females. The TLR7/8-activated sperm were subsequently used for in vivo embryo production via the superovulatory response; nine embryos were collected from the uterus of two does that conceived. Eight of these were XX embryos, and one was an XY embryo. Conclusions Our study reveals a novel TLR7/8 signalling mechanism that affects X-sperm motility via the GSK3 α/β-hexokinase pathway; this technique could be used to facilitate the efficient production of sexed dairy goat embryos.

Spermatogenesis holds considerable promise for human-assisted reproduction and livestock breeding based on stem cells. It occurs in seminiferous tubules within the testis, which mainly comprise male germ cells and Sertoli cells. While the developmental progression of male germ cells and Sertoli cells has been widely reported in mice, much less is known in other large animal species, including dairy goats. In this study, we present the data of single cell RNA sequencing (scRNA-seq) for 25,373 cells from 45 (pre-puberty), 90 (puberty), and 180-day-old (post-puberty) dairy goat testes. We aimed to identify genes that are associated with key developmental events in male germ cells and Sertoli cells. We examined the development of spermatogenic cells and seminiferous tubules from 15, 30, 45, 60, 75, 90, 180, and 240-day-old buck goat testes. scRNA-seq clustering analysis of testicular cells from pre-puberty, puberty, and post-puberty goat testes revealed several cell types, including cell populations with characteristics of spermatogonia, early spermatocytes, spermatocytes, spermatids, Sertoli cells, Leydig cells, macrophages, and endothelial cells. We mapped the timeline for male germ cells development from spermatogonia to spermatids and identified gene signatures that define spermatogenic cell populations, such as AMH, SOHLH1, INHA, and ACTA2. Importantly, using immunofluorescence staining for different marker proteins (UCHL1, C-KIT, VASA, SOX9, AMH, and PCNA), we explored the proliferative activity and development of male germ cells and Sertoli cells. Moreover, we identified the expression patterns of potential key genes associated with the niche-related key pathways in male germ cells of dairy goats, including testosterone, retinoic acid, PDGF, FGF, and WNT pathways. In summary, our study systematically investigated the elaborate male germ cells and Sertoli cells developmental patterns in dairy goats that have so far remained largely unknown. This information represents a valuable resource for the establishment of goat male reproductive stem cells lines, induction of germ cell differentiation in vitro, and the exploration of sequential cell fate transition for spermatogenesis and testicular development at single-cell resolution.

Abstract Background This study aims to implement a validated prediction model and application medium for postoperative pneumonia (POP) in elderly patients with hip fractures in order to facilitate individualized intervention by clinicians. Methods Employing clinical data from elderly patients with hip fractures, we derived and externally validated machine learning models for predicting POP. Model derivation utilized a registry from Nanjing First Hospital, and external validation was performed using data from patients at the Fourth Affiliated Hospital of Nanjing Medical University. The derivation cohort was divided into the training set and the testing set. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used for feature screening. We compared the performance of models to select the optimized model and introduced SHapley Additive exPlanations (SHAP) to interpret the model. Results The derivation and validation cohorts comprised 498 and 124 patients, with 14.3% and 10.5% POP rates, respectively. Among these models, Categorical boosting (Catboost) demonstrated superior discrimination ability. AUROC was 0.895 (95%CI: 0.841–0.949) and 0.835 (95%CI: 0.740–0.930) on the training and testing sets, respectively. At external validation, the AUROC amounted to 0.894 (95% CI: 0.821–0.966). The SHAP method showed that CRP, the modified five-item frailty index (mFI-5), and ASA body status were among the top three important predicators of POP. Conclusion Our model’s good early prediction ability, combined with the implementation of a network risk calculator based on the Catboost model, was anticipated to effectively distinguish high-risk POP groups, facilitating timely intervention.

AbstractBackground and aims Assessment of the patient’s gastric contents is the key to avoiding aspiration incidents, however, there is no effective method to determine whether elective painless gastrointestinal endoscopy (GIE) patients have a full stomach or an empty stomach. And previous studies have shown that preoperative oral carbohydrates (POCs) can improve the discomfort induced by fasting, but there are different perspectives on their safety. This study aimed to develop a convenient, accurate machine learning (ML) model to predict full stomach. And based on the model outcomes, evaluate the safety and comfort improvements of POCs in empty- and full stomach groups.Methods We enrolled 1386 painless GIE patients between October 2022 and January 2023 in Nanjing First Hospital, and 1090 patients without POCs were used to construct five different ML models to identify full stomach. The metrics of discrimination and calibration validated the robustness of the models. For the best-performance model, we further interpreted it through SHapley Additive exPlanations (SHAP) and constructed a web calculator to facilitate clinical use. We evaluated the safety and comfort improvements of POCs by propensity score matching (PSM) in the two groups, respectively.Results Random Forest (RF) model showed the greatest discrimination with the area under the receiver operating characteristic curve (AUROC) 0.837 [95% confidence interval (CI): 79.1–88.2], F1 71.5%, and best calibration with a Brier score of 15.2%. The web calculator can be visited at https://medication.shinyapps.io/RF_model/. PSM results demonstrated that POCs significantly reduced the full stomach incident in empty stomach group (p 0.05). Comfort improved in both groups and was more significant in empty stomach group.Conclusions The developed convenient RF model predicted full stomach with high accuracy and interpretability. POCs were safe and comfortably improved in both groups, with more benefit in empty stomach group. These findings may guide the patients’ gastrointestinal preparation.

Food provides abundant nutrients for human beings, but also has sensory functions and physiological regulation. Lipids are the main components of food as well as the important structural and functional components of cells. Nevertheless, lipids are easily oxidized by different ways, such as thermal oxidation and air oxidation. Lipid oxidation has adverse effects on food quality and human health. Therefore, efforts should be made to reduce lipid oxidation and improve its stability. This review focuses on important knowledge about lipid oxidation, including the concept of lipids and lipid oxidation, the main pathways and mechanisms of lipid oxidation, factors affecting lipid oxidation, strategies to improve the stability of lipid oxidation, and the recent research progress of lipid oxidation in food science and nutritional health.

DHA-enriched eggs have gained popularity due to their unique nutritional value, but their flavor can be challenging for some consumers to accept. The study analyzed the correlation of lipids and flavors in DHA-enriched egg yolks using comprehensive lipidomics and volatile compound analysis. The results showed that 411 lipids were detected in two egg yolk samples. Among them, 148 lipid species, including 48 DHA-containing lipids, were significantly higher in DHA-enriched egg yolks than in Common ones (P ​

BackgroundProlonged mechanical ventilation (PMV) has been proven as a risk factor for poor prognosis in patients with neurocritical illness. Spontaneous basal ganglia intracerebral hemorrhage (ICH) is one common subtype of hemorrhagic stroke and is associated with high morbidity and mortality. The systemic immune-inflammation index (SII) is used as a novel and valuable prognostic marker for various neoplastic diseases and other critical illnesses.ObjectiveThis study aimed to analyze the predictive value of preoperative SII for PMV in patients with spontaneous basal ganglia ICH who underwent surgical operations.MethodsThis retrospective study was conducted in patients with spontaneous basal ganglia ICH who underwent surgical operations between October 2014 and June 2021. SII was calculated using the following formula: SII = platelet count × neutrophil count/lymphocyte count. Multivariate logistic regression analysis and receiver operating characteristics curve (ROC) were used to evaluate the potential risk factors of PMV after spontaneous basal ganglia ICH.ResultsA total of 271 patients were enrolled. Of these, 112 patients (47.6%) presented with PMV. Multivariate logistic regression analysis showed that preoperative GCS (OR, 0.780; 95% CI, 0.688–0.883; P < 0.001), hematoma size (OR, 1.031; 95% CI, 1.016–1.047; P < 0.001), lactic acid (OR, 1.431; 95% CI, 1.015–2.017; P = 0.041) and SII (OR, 1.283; 95% CI, 1.049–1.568; P = 0.015) were significant risk factors for PMV. The area under the ROC curve (AUC) of SII was 0.662 (95% CI, 0.595–0.729, P < 0.001), with a cutoff value was 2,454.51.ConclusionPreoperative SII may predict PMV in patients with spontaneous basal ganglia ICH undergoing a surgical operation.

As an independent characteristic of electromagnetic radiation, the polarization of light is sensitive to the scattering and absorption characteristics of the mineral particles. The combination of polarization and infrared absorption spectroscopy is conducive to rapidly and accurately detecting the SiO2 content of metallurgical sandstone deposits. In this study, the 8–14 μm polarized infrared absorption spectra and the grade of the sandstone ore samples were used to analyse the spectral characteristics of the sandstone powder samples. Principal component analysis (PCA) and the successive projection algorithm (SPA) were used to reduce the dimension of the original data, first-order derivative, reciprocal logarithm, and multivariate scattering correction (MSC) data. Then, generalized regression neural network (GRNN), partial least squares regression (PLSR), and convolutional neural network (CNN) were employed to establish a hyperspectral prediction model of SiO2 grade. The results show that the quantitative model by the PCA-CNN algorithm has the better prediction precision for the reciprocal logarithm data, with a coefficient of determination (R2), root mean square error (RMSE), and ratio of performance to interquartile range (RPIQ) of 0.907, 0.023, and 5.11, respectively. This method indicates that the polarized infrared absorption spectra and the PCA-CNN model can provide a more robust and significant spectral interpretation than single infrared spectra, and it is expected to be applied to any high-purity quartz deposit type for in situ and rapid analysis.

A wide range of phenolic compounds participate in oilseed growth, regulate oxidative stability of corresponding vegetable oil, and serve as important minor food components with health-promoting effects. Composition distribution of phenolic compounds varied in oilseeds. Isoflavones, sinapic acid derivatives, catechin and epicatechin, phenolic alcohols, chlorogenic acid, and lignans were the main phenolic compounds in soybean, rapeseed, peanut skin, olive, sunflower seed, sesame and flaxseed, respectively. Among which, the total isoflavones content in soybean seeds reached from 1,431 to 2,130 mg/100 g; the main phenolic compound in rapeseed was sinapine, representing 70–90%; chlorogenic acid as the predominant phenolic compound in sunflower kernels, represented around 77% of the total phenolic content. With the rapid development of analytical techniques, it is becoming possible for the comprehensive profiling of these phenolic compounds from oilseeds. This review aims to provide recently developments about the composition distribution of phenolic compounds in common oilseeds, advanced technologies for profiling of phenolic compounds by the metabolomics approaches based on mass spectrometry. As there is still limited research focused on the comprehensive extraction and determination of phenolics with different bound-forms, future efforts should take into account the non-targeted, pseudo-targeted, and spatial metabolomic profiling of phenolic compounds, and the construction of phenolic compound database for identifying and quantifying new types of phenolic compounds in oilseeds and their derived products.

The coupling between optically active substances of algae particles and inorganic suspended solids of water makes the characteristics of reflection spectra of water complex and changeable. This makes modeling and inversion of polarization remote sensing in class II water difficult. In our study, considering the influence of the mixing ratio of algae particles and inorganic suspended solids, the sensor incidence angle, and the solar zenith angle on the polarization reflection spectrum, we analyzed the coupling characteristics of the polarized bidirectional reflectance of particulate matter through control experiments of mixed components of water particles in the laboratory. With Chaohu Lake in China as an example, the polarized reflectance coupling characteristics of water particles was investigated by the water-leaving radiation. The results showed that in the characteristic bands of 570, 675, and 705 nm, the degree of linear polarization (DOLP) was sensitive to the water-leaving radiation of the particles rather than to the reflectance. With the variation of observation angle, the reflection spectra were strongly interfered with by solar flare when the sensor zenith angle was close to 50° on the meridian plane with an azimuth angle of 180°, but DOLP was less affected, while also having a low correlation in the high concentration region. Combined with the coupling characteristics of particles at 675 and 705 nm, the model of DOLP ratio was established by partial least squares regression (PLSR) with a determination coefficient (R2) of 0.91, root mean square error (RMSE) 0.035, and a verification accuracy of 0.959. This shows that the model has better prediction ability for the coupling characteristics of water particles by the polarization reflection spectra and provides good support for mixed spectral unmixing of class II water.

Organic electrochemistry has attracted tremendous interest within the novel sustainable methodologies that have not only reduced the undesired byproducts, but also utilized cleaner and renewable energy sources. Particularly, oxidative electrochemistry has gained major attention. On the contrary, reductive electrolysis remains an underexplored research direction. In this context, we discuss advances in transition-metal-free cathodically generated radicals for selective organic transformations since 2016. We highlight the electroreductive reaction of alkyl radicals, aryl radicals, acyl radicals, silyl radicals, fluorosulfonyl radicals and trifluoromethoxyl radicals.

The verification efficiency and precision of copper ore grade has a great influence on copper ore mining. At present, the common method for the exploration of reserves often uses chemical analysis and identification, which have high costs, long cycles, and pollution risks but cannot realize the in situ determination of the copper grade. The existing scalar spectrometric techniques generally have limited accuracy. As a vector spectrum, polarization state information is sensitive to mineral particle distribution and composition, which is conducive to high-precision detection. Taking the visible-near infrared parallel polarization reflectance spectrum data and grade data of a copper mine in Xiaoyuan village, Huaining County, Anhui Province, China, as an example, the characteristics of the parallel polarization spectra of the copper mine were analyzed. The spectra were pretreated by first-order derivative transform and wavelet denoising, and the dimensions of wavelet denoising spectra, parallel polarization spectra, and first-order derivative spectra were also reduced by principal component analysis (PCA). Three, four, and eight principal components of the three types of spectra were selected as variables. Four machine learning models, the radial basis function (RBF), support vector machine (SVM), generalized regression neural network (GRNN), and partial least squares regression (PLSR), were selected to establish the PCA parallel polarization reflectance spectrum and copper grade prediction model. The accuracy of the model was evaluated by the determination coefficient (R2) and root mean square error (RMSE). The results show that, for parallel polarization spectra, first-order derivative spectra, and wavelet denoising spectra, the PCA-SVM model has better results, with R2 values of 0.911, 0.942, and 0.953 and RMSE values of 0.022, 0.019, and 0.017, respectively. This method can effectively reduce the redundancy of polarized hyperspectral data, has better model prediction ability, and provides a useful exploration for the grade analysis of hydrothermal copper deposits at meso-low temperatures.

Here, a simple, efficient, and rapid solid phase extraction-gas chromatography (SPE–GC) method was developed for the simultaneous analysis of free/combined phytosterols in rapeseed and their dynamic changes during microwave pretreatment and oil processing. First, by comparing different methods for extracting free/combined phytosterols from rapeseed and rapeseed cake, the Folch method was considered to be the optimal method and was selected in subsequent experiments. Subsequently, the extraction method was validated by determining the recoveries of standards (brassinosterol, campesterol, β-sitosterol and cholesteryl oleate) spiked in rapeseed and rapeseed oil samples, and the recoveries were in the range from 82.7% to 104.5% and 83.8% to 116.3%, respectively. The established method was applied to study the dynamic changes of the form and content of phytosterols in rapeseed and its products (rapeseed oil and cake) during rapeseed microwave pretreatment and the oil production process. Additionally, the results showed that more than 55% of the free/combined phytosterols in rapeseed were transferred to rapeseed oil during the oil processing, and this proportion will increase after microwave pretreatment of rapeseed. This work will provide analytical methods and data support for a comprehensive understanding of phytosterols in rapeseed and its products during oil processing.

In the complex planting area with scattered parcels, combining the parcel vector data with remote sensing images to extract the winter wheat planting information can make up for the deficiency of the classification from remote sensing images simply. It is a feasible direction for precision agricultural subsidies, but it is difficult to collect large-scale parcel data and obtain high spatial resolution or time-series remote sensing images in mass production. It is a beneficial exploration of making use of existing parcel data generated by the ground survey and medium-resolution remote sensing images with suitable time and spatial resolution to extract winter wheat planting areas for large-scale precision agricultural subsidies. Therefore, this paper proposes a new algorithm to extract winter wheat planting areas based on ownership parcel data and medium-resolution remote sensing images for improving classification accuracy. Initially, the segmentation of the image is carried out. To this end, the parcel data is used to generate the region of interest (ROI) of each parcel. Second, the homogeneity of each ROI is detected by its statistical indices (mean value and standard deviation). Third, the parallelepiped classifier and rule-based feature extraction classification methods are utilized to conduct the homogeneous and nonhomogeneous ROIs. Finally, two classification results are combined as the final classification result. The new algorithm was applied to a complex planting area of 103.60 km2 in central China based on the ownership parcel data and Gaofen-1 PMS and WFV remote sensing images in this paper. The experimental results show that the new algorithm can effectively extract winter wheat planting area, eliminate the problem of salt-and-pepper noise, and obtain high-precision classification results (kappa = 0.9279, overall accuracy = 96.41%, user’s accuracy = 99.16%, producer’s accuracy = 93.39%, commission errors = 0.84%, and omission errors = 6.61%) when the size of ownership parcels matches the spatial resolution of remote sensing images.

As the second most abundant greenhouse gas after carbon dioxide (CO2), methane not only plays an important role in global and regional photochemical reactions, but also has an important impact on energy balance and climate change. To explore the long-term trends and spatiotemporal variation of methane concentration over China, we verified the accuracy of the column-averaged, dry air-mixing ratio of CH4 (abbreviated as XCH4 hereafter) merged by SCIAMACHY and GOSAT products, utilizing the data of six surface observation stations in China and the surrounding areas. The root mean square error (RMSE) was mostly less than 2.5%, and the correlation coefficients (r) were 0.77, 0.84, 0.66, 0.42, 0.62 and 0.75. Furthermore, we analyzed the temporal and spatial variation patterns of the XCH4 concentration over China from 2003 to 2020. The results showed that the XCH4 concentration had an increasing trend over China from 2003 to 2020; the average growth rate was 6.64 ppb·a−1, and the value range of the increase rate was from 4.66 ppb·a−1 to 8.46 ppb·a−1. The lowest XCH4 concentration was located over Tibet (1764.03 ppb), and the high values were located in the Sichuan Basin, Central China (Hunan, Hubei, and Henan) and East China (Anhui and Jiangxi) (1825–1845 ppb). The XCH4 concentration was higher in autumn and summer, low in winter and spring, and had obvious seasonal variations. Human factors such as population density, GDP and energy consumption have a significant impact on the XCH4 concentration over China.

Compared with a traditional optical system, the single-lens curved compound eye imaging system has superior optical performance, such as a large field of view (FOV), small size, and high portability. However, defocus and low resolution hinder the further development of single-lens curved compound eye imaging systems. In this study, the design of a nonuniform curved compound eye with multiple focal lengths was used to solve the defocus problem. A two-step gas-assisted process, which was combined with photolithography, soft photolithography, and ultraviolet curing, was proposed for fabricating the ommatidia with a large numerical aperture precisely. Ommatidia with high resolution were fabricated and arranged in five rings. Based on the imaging experimental results, it was demonstrated that the high-resolution and small-volume single-lens curved compound eye imaging system has significant advantages in large-field imaging and rapid recognition.

Curved compound eyes have generated great interest owing to the wide field of view but the application of devices is hindered for the lack of proper detectors. One-lens curved compound eyes with multi-focal microlenses provide a solution for wide field imaging integrated in a commercial photo-detector. However, it is still a challenge for manufacturing this kind of compound eye. In this paper, a rapid and accurate method is proposed by a combination of photolithography, hot embossing, soft photolithography, and gas-assisted deformation techniques. Microlens arrays with different focal lengths were firstly obtained on a polymer, and then the planar structure was converted to the curved surface. A total of 581 compound eyes with diameters ranging from 152.8 µm to 240.9 µm were successfully obtained on one curved surface within a few hours, and the field of view of the compound eyes exceeded 108°. To verify the characteristics of the fabricated compound eyes, morphology deviation was measured by a probe profile and a scanning electron microscope. The optical performance and imaging capability were also tested and analyzed. As a result, the ommatidia made up of microlenses showed not only high accuracy in morphology, but also imaging uniformity on a focal plane. This flexible massive fabrication of compound eyes indicates great potential for miniaturized imaging systems.