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The selection of high-quality sperms is critical to intracytoplasmic sperm injection, which accounts for 70–80% of in vitro fertilization (IVF) treatments. So far, sperm screening is usually performed manually by clinicians. However, the performance of manual screening is limited in its objectivity, consistency, and efficiency. To overcome these limitations, we have developed a fast and noninvasive three-stage method to characterize morphology of freely swimming human sperms in bright-field microscopy images using deep learning models. Specifically, we use an object detection model to identify sperm heads, a classification model to select in-focus images, and a segmentation model to extract geometry of sperm heads and vacuoles. The models achieve an F1-score of 0.951 in sperm head detection, a z-position estimation error within ±1.5 μm in in-focus image selection, and a Dice score of 0.948 in sperm head segmentation, respectively. Customized lightweight architectures are used for the models to achieve real-time analysis of 200 frames per second. Comprehensive morphological parameters are calculated from sperm head geometry extracted by image segmentation. Overall, our method provides a reliable and efficient tool to assist clinicians in selecting high-quality sperms for successful IVF. It also demonstrates the effectiveness of deep learning in real-time analysis of live bright-field microscopy images.
This paper investigates the impact of the abolition of the civil service exam on local governance in early twentieth-century China. Before the abolition, local elites collected surtaxes that financed local public goods, but they were supervised by the state and could lose candidacy for higher status if they engaged in corrupt behavior. This prospect of upward mobility (POUM) gave them incentives to behave well, which the abolition of the exam removed. Using anti-elite protests as a proxy for the deterioration of local governance, we find that prefectures with a higher POUM experienced more incidents of anti-elite protests after the abolition.
This study is performed to figure out how the presence of diabetes affects the infection, progression and prognosis of 2019 novel coronavirus disease (COVID-19), and the effective therapy that can treat the diabetes-complicated patients with COVID-19. A multicentre study was performed in four hospitals. COVID-19 patients with diabetes mellitus (DM) or hyperglycaemia were compared with those without these conditions and matched by propensity score matching for their clinical progress and outcome. Totally, 2444 confirmed COVID-19 patients were recruited, from whom 336 had DM. Compared to 1344 non-DM patients with age and sex matched, DM-COVID-19 patients had significantly higher rates of intensive care unit entrance (12.43% vs. 6.58%, P = 0.014), kidney failure (9.20% vs. 4.05%, P = 0.027) and mortality (25.00% vs. 18.15%, P < 0.001). Age and sex-stratified comparison revealed increased susceptibility to COVID-19 only from females with DM. For either non-DM or DM group, hyperglycaemia was associated with adverse outcomes, featured by higher rates of severe pneumonia and mortality, in comparison with non-hyperglycaemia. This was accompanied by significantly altered laboratory indicators including lymphocyte and neutrophil percentage, C-reactive protein and urea nitrogen level, all with correlation coefficients >0.35. Both diabetes and hyperglycaemia were independently associated with adverse prognosis of COVID-19, with hazard ratios of 10.41 and 3.58, respectively.
Video materials require learners to manage concurrent verbal and pictorial processing. To facilitate second language (L2) learners’ video comprehension, the amount of presented information should thus be compatible with human beings’ finite cognitive capacity. In light of this, the current study explored whether a reduction in multimodal comprehension scaffolding would lead to better L2 comprehension gain when viewing captioned videos and, if so, which type of reduction (verbal vs. nonverbal) is more beneficial. A total of 62 L2 learners of English were randomly assigned to one of the following viewing conditions: (1) full captions + animation, (2) full captions + static key frames, (3) partial captions + animation, and (4) partial captions + static key frames. They then completed a comprehension test and cognitive load questionnaire. The results showed that while viewing the video with reduced nonverbal visual information (static key frames), the participants had well-rounded performance in all aspects of comprehension. However, their local comprehension (extraction of details) was particularly enhanced after viewing a key-framed video with full captions. Notably, this gain in local comprehension was not as manifest after viewing animated video content with full captions. The qualitative data also revealed that although animation may provide a perceptually stimulating viewing experience, its transient feature most likely taxed the participants’ attention, thus impacting their comprehension outcomes. These findings underscore the benefit of a reduction in nonverbal input and the interplay between verbal and nonverbal input. The findings are discussed in relation to the use of verbal and nonverbal input for different pedagogical purposes.
Low molecular weight glutenin subunits (LWM-GSs) play a crucial role in determining wheat flour processing quality. In this work, 35 novel LMW-GS genes (32 active and three pseudogenes) from three Aegilops umbellulata (2n = 2x = 14, UU) accessions were amplified by allelic-specific PCR. We found that all LMW-GS genes had the same primary structure shared by other known LMW-GSs. Thirty-two active genes encode 31 typical LMW-m-type subunits. The MZ424050 possessed nine cysteine residues with an extra cysteine residue located in the last amino acid residue of the conserved C-terminal III, which could benefit the formation of larger glutenin polymers, and therefore may have positive effects on dough properties. We have found extensive variations which were mainly resulted from single-nucleotide polymorphisms (SNPs) and insertions and deletions (InDels) among the LMW-GS genes in Ae. umbellulata. Our results demonstrated that Ae. umbellulata is an important source of LMW-GS variants and the potential value of the novel LMW-GS alleles for wheat quality improvement.
Streptococcus agalactiae (S. agalactiae) infection is a significant cause of mastitis, resulting in loss of cellular homeostasis and tissue damage. Autophagy plays an essential function in cell survival, defense, and the preservation of cellular homeostasis, and is often part of the response to pathogenic challenge. However, the effect of autophagy induced by S. agalactiae in bovine mammary epithelial cells (bMECs) is mainly unknown. So in this study, an intracellular S. agalactiae infection model was established. Through evaluating the autophagy-related indicators, we observed that after S. agalactiae infection, a significant quantity of LC3-I was converted to LC3-II, p62 was degraded, and levels of Beclin1 and Bcl2 increased significantly in bMECs, indicating that S. agalactiae induced autophagy. The increase in levels of LAMP2 and LysoTracker Deep Red fluorescent spots indicated that lysosomes had participated in the degradation of autophagic contents. After autophagy was activated by rapamycin (Rapa), the amount of p-Akt and p-mTOR decreased significantly, whilst the amount of intracellular S. agalactiae increased significantly. Whereas the autophagy was inhibited by 3-methyladenine (3MA), the number of intracellular pathogens decreased. In conclusion, the results demonstrated that S. agalactiae could induce autophagy through PI3K/Akt/mTOR pathway and utilize autophagy to survive in bMECs.
Although serum lactate levels are widely accepted markers of haemodynamic instability, an alternative method to evaluate haemodynamic stability/instability continuously and non-invasively may assist in improving the standard of patient care. We hypothesise that blood lactate in paediatric ICU patients can be predicted using machine learning applied to arterial waveforms and perioperative characteristics.
Methods:
Forty-eight post-operative children, median age 4 months (2.9–11.8 interquartile range), mean baseline heart rate of 131 beats per minute (range 33–197), mean lactate level at admission of 22.3 mg/dL (range 6.3–71.1), were included. Morphological arterial waveform characteristics were acquired and analysed. Predicting lactate levels was accomplished using regression-based supervised learning algorithms, evaluated with hold-out cross-validation, including, basing prediction on the currently acquired physiological measurements along with those acquired at admission, as well as adding the most recent lactate measurement and the time since that measurement as prediction parameters. Algorithms were assessed with mean absolute error, the average of the absolute differences between actual and predicted lactate concentrations. Low values represent superior model performance.
Results:
The best performing algorithm was the tuned random forest, which yielded a mean absolute error of 3.38 mg/dL when predicting blood lactate with updated ground truth from the most recent blood draw.
Conclusions:
The random forest is capable of predicting serum lactate levels by analysing perioperative variables, including the arterial pressure waveform. Thus, machine learning can predict patient blood lactate levels, a proxy for haemodynamic instability, non-invasively, continuously and with accuracy that may demonstrate clinical utility.
We numerically investigate turbulent Rayleigh–Bénard convection through two immiscible fluid layers, aiming to understand how the layer thickness and fluid properties affect the heat transfer (characterized by the Nusselt number $\mbox {Nu}$) in two-layer systems. Both two- and three-dimensional simulations are performed at fixed global Rayleigh number $\mbox {Ra}=10^8$, Prandtl number $\mbox {Pr}=4.38$ and Weber number $\mbox {We}=5$. We vary the relative thickness of the upper layer between $0.01 \le \alpha \le 0.99$ and the thermal conductivity coefficient ratio of the two liquids between $0.1 \le \lambda _k \le 10$. Two flow regimes are observed. In the first regime at $0.04\le \alpha \le 0.96$, convective flows appear in both layers and $\mbox {Nu}$ is not sensitive to $\alpha$. In the second regime at $\alpha \le 0.02$ or $\alpha \ge 0.98$, convective flow only exists in the thicker layer, while the thinner one is dominated by pure conduction. In this regime, $\mbox {Nu}$ is sensitive to $\alpha$. To predict $\mbox {Nu}$ in the system in which the two layers are separated by a unique interface, we apply the Grossmann–Lohse theory for both individual layers and impose heat flux conservation at the interface. Without introducing any free parameter, the predictions for $\mbox {Nu}$ and for the temperature at the interface agree well with our numerical results and previous experimental data.
Based on the measurements conducted over the landfast sea ice in Prydz Bay, East Antarctica during the sea-ice growth season in 2016, various parameterization schemes in the high-resolution thermodynamic snow/ice model HIGHTSI are evaluated. The parameterization scheme of turbulent fluxes produces the largest errors compared with the parameterization schemes for other surface heat fluxes. However, the sea-ice thickness simulation is most sensitive to the differences in upward longwave radiation at the surface. In addition, the sea-ice thickness simulation during the growth season is highly sensitive to the oceanic heat flux, and a new oceanic heat flux parameterization scheme based on the bulk method is proposed. The new parameterization scheme is tested in a second year, and it significantly improves the model performance relative to the standard configuration when compared against observations. Finally, the seasonal variation in the heat budget and its influence on the sea-ice thickness variation are analyzed. The net shortwave radiation, sensible heat flux and conductive heat flux (the net longwave radiation and latent heat flux) are found to be the surface heat sources (heat sinks) during the growth season. The larger conductive heat flux and the smaller oceanic heat flux can intensify the growth of sea ice.
Accumulating evidence suggests that supplementation of omega-3 polyunsaturated fatty acids (ω−3 PUFAs) was associated with reduction in risk of major cardiovascular events. This meta-analysis was to systematically evaluate whether daily supplementation and accumulated intake of ω−3 PUFAs is associated with improved left ventricular (LV) remodeling in patients with chronic heart failure (CHF). Articles were obtained from Pubmed, Clinical key and Web of Science from inception to January 1 in 2021, and a total of 12 trials involving 2162 participants were eligible for inclusion. The sources of study heterogeneity were explained by I2 statistic and subgroup analysis. Compared with placebo groups, ω−3 PUFAs supplementation improved LV ejection fraction (LVEF) (11 trials, 2112 participants, WMD=2.52, 95%CI 1.25 to 3.80, I2=87.8%) and decreased LV end-systolic volume (LVESV) (5 studies, 905 participants, WMD=−3.22, 95%CI −3.67 to −2.77, I2=0.0%) by using the continuous variables analysis. Notably, the high accumulated ω−3 PUFAs dosage groups (≥600g) presented a prominent improvement in LVEF, while the low and middle accumulated dosage (≤300g and 300-600g) showed no effects on LVEF. In addition, ω−3 PUFAs supplementation decreased the levels of pro-inflammatory mediators including tumor necrosis factor−α (TNF-α), interleukin-6 (IL-6) and hypersensitive-c-reactive protein (Hs-CRP). Therefore, the present meta-analysis demonstrated that ω−3 PUFAs consumption was associated with a substantial improvement of LV function and remodeling in patients subjected to CHF. The accumulated dosage of ω-3 PUFAs intake is vital for its cardiac protective role.
Vaginitis is a prevalent gynecologic disease that threatens millions of women’s health. Although microscopic examination of vaginal discharge is an effective method to identify vaginal infections, manual analysis of microscopic leucorrhea images is extremely time-consuming and labor-intensive. To automate the detection and identification of visible components in microscopic leucorrhea images for early-stage diagnosis of vaginitis, we propose a novel end-to-end deep learning-based cells detection framework using attention-based detection with transformers (DETR) architecture. The transfer learning was applied to speed up the network convergence while maintaining the lowest annotation cost. To address the issue of detection performance degradation caused by class imbalance, the weighted sampler with on-the-fly data augmentation module was integrated into the detection pipeline. Additionally, the multi-head attention mechanism and the bipartite matching loss system of the DETR model perform well in identifying partially overlapping cells in real-time. With our proposed method, the pipeline achieved a mean average precision (mAP) of 86.00% and the average precision (AP) of epithelium, leukocyte, pyocyte, mildew, and erythrocyte was 96.76, 83.50, 74.20, 89.66, and 88.80%, respectively. The average test time for a microscopic leucorrhea image is approximately 72.3 ms. Currently, this cell detection method represents state-of-the-art performance.
Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.
Aims
To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers.
Method
We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites.
Results
We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19–85.74%; sensitivity, 75.31–89.29% and area under the receiver operating characteristic curve, 0.797–0.909.
Conclusions
These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.
The current study aimed to investigate the protective effects of dietary thiamine supplementation on the regulation of colonic integrity and mucosal inflammation in goats fed a high-concentrate (HC) diet. Twenty-four Boer goats (live weight of 35·62 (sem 2·4) kg) were allocated to three groups (CON: concentrate/forage = 30:70; HC; concentrate/forage = 70:30 and HCT: concentrate/forage = 70:30 with 200 mg thiamine/kg DMI) for 12 weeks. Results showed that compared with the HC treatment, the HCT group had a significantly higher ruminal pH value from 0 to 12 h after the feeding. The haematoxylin–eosin staining showed that desquamation and severe cellular damage were observed in the colon epithelium of the HC group, whereas the HCT group exhibited more structural integrity of the epithelial cell morphology. Compared with the HC treatment, the HCT group showed a markedly increase in pyruvate dehydrogenase and α-ketoglutarate dehydrogenase enzymes activity. The mRNA expressions in the colonic epithelium of SLC19A2, SLC19A3, SLC25A19, Bcl-2, occludin, claudin-1, claudin-4 and ZO-1 in the HCT group were significantly increased in comparison with the HC diet treatment. Compared with the HC treatment, the HCT diet significantly increased the protein expression of claudin-1 and significantly decreased the protein expression of NF-κB-related proteins p65. The results show that dietary thiamine supplementation could improve the colon epithelial barrier function and alleviate mucosal inflammation injury in goats after lipopolysaccharide and low pH challenge.
The optimization of laser pulse shapes is of great importance and a major challenge for laser direct-drive implosions. In this paper, we propose an efficient intelligent method to perform laser pulse optimization via hydrodynamic simulations guided by the genetic algorithm and random forest algorithm. Compared to manual optimizations, the machine-learning guided method is able to efficiently improve the areal density by a factor of 63% and reduce the in-flight-aspect ratio by a factor of 30% at the same time. A relationship between the maximum areal density and ion temperature is also achieved by the analysis of the big simulation dataset. This design method has been successfully demonstrated by the 2021 summer double-cone ignition experiments conducted at the SG-II upgrade laser facility and has great prospects for the design of other inertial fusion experiments.
The vertebrate retina contains a large number of different types of neurons that can be distinguished by their morphological properties. Assuming that no location should be without a contribution from the circuitry and function linked to a specific type of neuron, it is expected that the dendritic trees of neurons belonging to a type will cover the retina in a regular manner. Thus, for most types of neurons, the contribution to visual processing is thought to be independent of the exact location of individual neurons across the retina. Here, we have investigated the distribution of AII amacrine cells in rat retina. The AII is a multifunctional amacrine cell found in mammals and involved in synaptic microcircuits that contribute to visual processing under both scotopic and photopic conditions. Previous investigations have suggested that AIIs are regularly distributed, with a nearest-neighbor distance regularity index of ~4. It has been argued, however, that this presumed regularity results from treating somas as points, without taking into account their actual spatial extent which constrains the location of other cells of the same type. When we simulated random distributions of cell bodies with size and density similar to real AIIs, we confirmed that the simulated distributions could not be distinguished from the distributions observed experimentally for AIIs in different regions and eccentricities of the retina. The developmental mechanisms that generate the observed distributions of AIIs remain to be investigated.
This numerical study presents a simple but extremely effective way to considerably enhance heat transport in turbulent wall-bounded multiphase flows, namely by using oleophilic walls. As a model system, we pick the Rayleigh–Bénard set-up, filled with an oil–water mixture. For oleophilic walls, using only $10\,\%$ volume fraction of oil in water, we observe a remarkable heat transport enhancement of more than $100\,\%$ as compared to the pure water case. In contrast, for oleophobic walls, the enhancement is only of about $20\,\%$ as compared to pure water. The physical explanation of the heat transport increment for oleophilic walls is that thermal plumes detach from the oil-rich boundary layer and carry the heat with them. In the bulk, the oil–water interface prevents the plumes from mixing with the turbulent water bulk and to diffuse their heat. To confirm this physical picture, we show that the minimum amount of oil necessary to achieve the maximum heat transport is set by the volume fraction of the thermal plumes. Our findings provide guidelines of how to optimize heat transport in wall-bounded thermal turbulence. Moreover, the physical insight of how coherent structures are coupled with one of the phases of a two-phase system has very general applicability for controlling transport properties in other turbulent wall-bounded multiphase flows.
Noncompressible torso hemorrhage (NCTH) is a major challenge in prehospital bleeding control and is associated with high mortality. This study was performed to estimate medical knowledge and the perceived barriers to information acquisition among health-care workers (HCWs) regarding NCTH in China.
Methods:
A self-administered and validated questionnaire was distributed among 11 WeChat groups consisting of HCWs engaged in trauma, emergency, and disaster rescue.
Results:
A total of 575 HCWs participated in this study. In the knowledge section, the majority (87.1%) denied that successful hemostasis could be obtained by external compression. Regarding attitudes, the vast majority of HCWs exhibited positive attitudes toward the important role of NCTH in reducing prehospital preventable death (90.4%) and enthusiasm for continuous learning (99.7%). For practice, fewer than half of HCWs (45.7%) had heard of NCTH beforehand, only a minority (14.3%) confirmed they had attended relevant continuing education, and 16.3% HCWs had no access to updated medical information. The most predominant barrier to information acquisition was the lack of continuing training (79.8%).
Conclusions:
Knowledge and practice deficiencies do exist among HCWs. Obstacles to update medical information warrant further attention. Furthermore, education program redesign is also needed.
The genus Echinochloa constitutes some of the most prominent weed species found in rice (Oryza sativa L.) production worldwide. The taxonomy of Echinochloa is complex due to its morphological variations. The morphophysiological diversity and taxonomic characteristics of Echinochloa ecotypes infesting rice fields in Texas are unknown. A total of 54 Echinochloa ecotypes collected during late-season field surveys in 2015 and 2016 were characterized in a common garden in 2017. Plants were characterized for 14 morphophysiological traits, including stem angle; stem color; plant height; leaf color; leaf texture; flag leaf length, width, and angle; days to flowering; panicle length; plant biomass; seed shattering; seed yield; and seed dormancy. Principal component analysis indicated that 4 (plant height, flag leaf length, seed shattering, and seed germination) of the 14 phenological traits characterized here had significantly contributed to the overall morphological diversity of Echinochloa spp. Results showed wide interpopulation diversity for the measured traits among the E. colona ecotypes, as well as diverse intrapopulation variability in all three Echinochloa species studied, including barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.], junglerice [Echinochloa colona (L.) Link], and rough barnyardgrass [Echinochloa muricata (P. Beauv.) Fernald]. Taxonomical classification revealed that the collection consisted of three Echinochloa species, with E. colona being the most dominant (96%), followed by E. crus-galli (2%), and E. muricata (2%). Correlation analysis of morphophysiological traits and resistance status to commonly used preemergence (clomazone, quinclorac) and postemergence herbicides (propanil, quinclorac, imazethapyr, and fenoxaprop-ethyl) failed to show any significant association. Findings from this study provided novel insights into the morphophysiological characteristics of Echinochloa ecotypes in rice production in Texas. The morphological diversity currently present in Echinochloa ecotypes could contribute to their adaptation to selection pressure imposed by different management tools, emphasizing the need for a diversified management approach to effectively control this weed species.
Chronic inflammation exerts pleiotropic effects in the aetiology and progression of chronic obstructive pulmonary disease (COPD). Glucosamine is widely used in many countries and may have anti-inflammatory properties. We aimed to prospectively evaluate the association of regular glucosamine use with incident COPD risk and explore whether such association could be modified by smoking in the UK Biobank cohort, which recruited more than half a million participants aged 40–69 years from across the UK between 2006 and 2010. Cox proportional hazards models with adjustment for potential confounding factors were used to calculate hazard ratios (HR) as well as 95 % CI for the risk of incident COPD. During a median follow-up of 8·96 years (interquartile range 8·29–9·53 years), 9016 new-onset events of COPD were documented. We found that the regular use of glucosamine was associated with a significantly lower risk of incident COPD with multivariable adjusted HR of 0·80 (95 % CI, 0·75, 0·85; P < 0·001). When subgroup analyses were performed by smoking status, the adjusted HR for the association of regular glucosamine use with incident COPD were 0·84 (0·73, 0·96), 0·84 (0·77, 0·92) and 0·71 (0·62, 0·80) among never smokers, former smokers and current smokers, respectively. No significant interaction was observed between glucosamine use and smoking status (Pfor interaction = 0·078). Incident COPD could be reduced by 14 % to 84 % through a combination of regular glucosamine use and smoking cessation.