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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.
N-acetylcysteine (NAC) possesses a strong capability to ameliorate high-fat diet (HFD)-induced nonalcoholic-fatty liver disease (NAFLD) in mice, but the underlying mechanism is still unknown. Our study aimed to clarify the involvement of long noncoding RNAs (lncRNAs) in the beneficial effects of NAC on HFD-induced NAFLD. C57BL/6J mice were fed a normal-fat diet (10 % fat), a HFD (45 % fat), or a HFD plus NAC (2 g/L in the drinking water). After 14-week of intervention, NAC obviously rescued the deleterious alterations induced by HFD, including the changes in body and liver weights, hepatic triglycerides (TGs), plasma alanine aminotransferase (ALT), plasma aspartate transaminase (AST), and liver histomorphology (H&E and Oil red O staining). Through whole-transcriptome sequencing, 52167 (50758 known and 1409 novel) hepatic lncRNAs were detected. Our cross-comparison data revealed the expression of 175 lncRNAs were significantly changed by HFD but reversed by NAC. Five of those lncRNAs, lncRNA-NONMMUT148902.1 (NO_902.1), lncRNA-XR_001781798.1 (XR_798.1), lncRNA-NONMMUT141720.1 (NO_720.1), lncRNA-XR_869907.1 (XR_907.1), and lncRNA-ENSMUST00000132181 (EN_181) were selected based on an absolute log2 fold change (FC) value of greater than 4, P-value < 0.01, and P-adjusted value < 0.01. Further qRT-PCR analysis showed that the levels of lncRNA-NO_902.1, lncRNA-XR_798.1, and lncRNA-EN_181 were dramatically decreased by HFD but restored by NAC, consistent with the RNA-sequencing. Finally, we constructed a ceRNA network containing lncRNA-EN_181, 3 miRNAs, and 13 mRNAs, which was associated with the NAC-ameliorated NAFLD. Overall, lncRNA-EN_181 might be a potential target in NAC-ameliorated NAFLD. This finding enhanced our understanding of the biological mechanisms underlying the beneficial role of NAC.
The effect of hydrodynamic interactions on the collective locomotion of fish schools is still poorly understood. In this paper, the flow-mediated organization of two tandem flapping foils, which are free in both the longitudinal and lateral directions, is numerically studied. It is found that the tandem formation is unstable for two foils when they can self-propel in both the longitudinal and lateral directions. Three types of resultant regular formations are observed, i.e. semi-tandem formation, staggered formation and transitional formation. Which type of regular formation occurs depends on the flapping parameters and the initial longitudinal distance between the two foils. Moreover, there is a threshold value of the cycle-averaged longitudinal distance (which is approximately 0.55) below which both velocity enhancement and efficiency augmentation can be achieved by two foils in regular formations. The results obtained here may shed some light on understanding the emergence of regular formations of fish schools.
Ediacaran cap dolostone atop Marinoan glacial deposits contains complex sedimentary structures with extremely negative δ13Ccarb values in close association with oscillations in palaeoclimatic and oceanographic proxy records. However, the precise geological, geochronological and geochemical context of the cap dolostone is not clarified, which hampers us from correctly interpreting the extremely negative δ13Ccarb values and their causal relationships with the Snowball Earth hypothesis. In this study, we conducted detailed in situ geochronological and geochemical analyses on the calcite within the cap dolostone from the Ediacaran Doushantuo Formation in South China in order to define its formation and relationship to the Snowball Earth hypothesis. Petrographic observations show that formation of dolomite pre-dates precipitation of calcite and pyrite, which pre-dates quartz cementation in the basal cap carbonate. Calcite cement within the cap dolostone yielded a U–Pb age of 636.5 ± 7.4/17.8 Ma (2σ, MSWD = 1.6, n = 36/40), which is within uncertainty of a published dolomite U–Pb age of 632 ± 17 Ma (recalculated as 629.3 ± 16.7/22.9 Ma). These age constraints negate the possibility that the calcite cement was formed by late Ediacaran or Cambrian hydrothermal activity. The rare earth element distribution patterns suggest a dominant seawater origin overprinted by subsequent early Ediacaran hydrothermal activity. The combined age, petrographic and geochemical data suggest oxidization of methane clathrates in response to complicated interplay between eustasy and isostatic rebound and hydrothermal fluids.
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.
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 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.
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.
Understanding factors associated with post-discharge sleep quality among COVID-19 survivors is important for intervention development.
Aims
This study investigated sleep quality and its correlates among COVID-19 patients 6 months after their most recent hospital discharge.
Method
Healthcare providers at hospitals located in five different Chinese cities contacted adult COVID-19 patients discharged between 1 February and 30 March 2020. A total of 199 eligible patients provided verbal informed consent and completed the interview. Using score on the single-item Sleep Quality Scale as the dependent variable, multiple linear regression models were fitted.
Results
Among all participants, 10.1% reported terrible or poor sleep quality, and 26.6% reported fair sleep quality, 26.1% reported worse sleep quality when comparing their current status with the time before COVID-19, and 33.7% were bothered by a sleeping disorder in the past 2 weeks. After adjusting for significant background characteristics, factors associated with sleep quality included witnessing the suffering (adjusted B = −1.15, 95% CI = −1.70, −0.33) or death (adjusted B = −1.55, 95% CI = −2.62, −0.49) of other COVID-19 patients during hospital stay, depressive symptoms (adjusted B = −0.26, 95% CI = −0.31, −0.20), anxiety symptoms (adjusted B = −0.25, 95% CI = −0.33, −0.17), post-traumatic stress disorders (adjusted B = −0.16, 95% CI = −0.22, −0.10) and social support (adjusted B = 0.07, 95% CI = 0.04, 0.10).
Conclusions
COVID-19 survivors reported poor sleep quality. Interventions and support services to improve sleep quality should be provided to COVID-19 survivors during their hospital stay and after hospital discharge.
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.
Tungstophosphoric acid-intercalated MgAl layer double hydroxides (LDHs) are active catalysts for removing naphthenic acids (NAs) from petroleum via esterification. Due to their active sites being in the interlayer, the interlayer spacing of LDHs might affect their activity, particularly for NAs with various structures. Herein, two tungstophosphoric acid-intercalated MgAl LDHs with various interlayer spacings (d003 = 1.46 and 1.07 nm) synthesized by varying the ion-exchange time were used as catalysts for esterification between NAs and ethylene glycol. Six NAs with various side chains and rings were used as model compounds to investigate the effects of NA structures and d003 values on the activity of LDHs. In general, NAs with large molecule sizes and steric hindrances are less reactive over the same catalyst. The LDH with a larger d003 value favours the esterification of NAs regardless of their structure, particularly NAs with large molecule sizes and steric hindrances. However, a large d003 is less effective for esterification of NAs with conjugated carboxyl groups. An enlarged interlayer space might facilitate NA molecules to access the interlayer of LDHs so as to come into contact with the catalytic sites, making this process responsible for the enhanced reactivity. The esterification kinetics of cyclohexanecarboxylic acid over these LDHs follow a first-order reaction. The activation energies for the LDHs with large and small d003 values are 26.25 and 32.18 kJ mol–1, respectively.
Nutritional Risk Screening index is a standard tool to assess nutritional risk, but epidemiological data are scarce on controlling nutritional status (CONUT) as a prognostic marker in acute haemorrhagic stroke (AHS). We aimed to explore whether the CONUT may predict a 3-month functional outcome in AHS. In total, 349 Chinese patients with incident AHS were consecutively recruited, and their malnutrition risks were determined using a high CONUT score of ≥ 2. The cohort patients were divided into high-CONUT (≥ 2) and low-CONUT (< 2) groups, and primary outcomes were a poor functional prognosis defined as the modified Rankin Scale (mRS) score of ≥ 3 at post-discharge for 3 months. Odds ratios (OR) with 95 % confidence intervals (CI) for the poor functional prognosis at post-discharge were estimated by using a logistic analysis with additional adjustments for unbalanced variables between the high-CONUT and low-CONUT groups. A total of 328 patients (60·38 ± 12·83 years; 66·77 % male) completed the mRS assessment at post-discharge for 3 months, with 172 patients at malnutrition risk at admission and 104 patients with a poor prognosis. The levels of total cholesterol and total lymphocyte counts were significantly lower in high-CONUT patients than low-CONUT patients (P = 0·012 and < 0·001, respectively). At 3-month post discharge, there was a greater risk for the poor outcome in the high-CONUT compared with the low-CONUT patients at admission (OR: 2·32, 95 % CI: 1·28, 4·17). High-CONUT scores independently predict a 3-month poor prognosis in AHS, which helps to identify those who need additional nutritional managements.
We conducted the first detailed mineral magnetic investigation of more than nine loess–paleosol couplets of the composite Titel-Stari Slankamen loess section in Serbia, which provides one of the longest and most complete terrestrial record of paleoclimatic changes in Europe since ~1.0 Ma. The results show that the ferrimagnetic mineral assemblage of the loess units is dominated by partially oxidized multidomain (MD) and pseudo-single domain (PSD) magnetite; however, with an increasing degree of pedogenesis, the eolian contribution is gradually masked by pedogenic superparamagnetic(SP) and single-domain (SD) ferrimagnets (mainly maghemite). The overall consistency of ferrimagnetic grain-size parameters indicates an absence of dissolution of the fine-grained ferrimagnetic fraction despite changes in climate regime over the past 1.0 Ma. The variations of normalized dJ/dT@120K and normalized χheating@530°C reflect a long-term stepwise increase in aridity during glacials with a major step at ~0.6–0.5 Ma, over the last 1.0 Ma. Overall, the results provide an improved basis for the future use of the magnetic properties of Serbian loess deposits for paleoclimatic reconstruction.
Despite the fact that social deficits among individuals with autism spectrum disorder (ASD) are lifelong and impact many aspects of personal functioning, evidence-based programs for social skills training were not available until recently. The Program for the Education and Enrichment of Relational Skills (PEERS®) has been shown to effectively improve social skills for adolescents on the spectrum across different social cultures. However, the effectiveness for young adults beyond North America has yet to be examined. This study aimed to investigate the effectiveness of the PEERS intervention in Taiwanese young adults with ASD, and examine its durability and clinical correlates.
Methods
We recruited 82 cognitively-able young adults with ASD, randomized to the PEERS treatment or treatment-as-usual.
Results
Following treatment, significant improvement was found in aspects of social deficits, autism severity, social interaction anxiety, empathy, and social skills knowledge either by self-report or coach-report. Additionally, communicative behaviors rated by observers improved throughout the sessions, showing a trend toward more appropriate eye contact, gestures, facial expression during conversation, and appropriate maintenance of conversation and reciprocity. Most effects maintained at 3-month and 6-month follow-ups. The improvement of social deficits was positively correlated with baseline severity, while gains in social skills knowledge were positively correlated with IQ. The improvement of social deficits, autism severity, and empathy were positively correlated with each other.
Conclusion
Overall, the PEERS intervention appears to effectively improve social functioning in Taiwanese young adults with ASD. Improvement of social response and knowledge may be predicted by baseline severity and intelligence respectively.
Schizophrenia is a severe and complex psychiatric disorder that needs treatment based on extensive experience. Antipsychotic drugs have already become the cornerstone of the treatment for schizophrenia; however, the therapeutic effect is of significant variability among patients, and only around a third of patients with schizophrenia show good efficacy. Meanwhile, drug-induced metabolic syndrome and other side-effects significantly affect treatment adherence and prognosis. Therefore, strategies for drug selection are desperately needed. In this study, we will perform pharmacogenomics research and set up an individualised preferred treatment prediction model.
Aims
We aim to create a standard clinical cohort, with multidimensional index assessment of antipsychotic treatment for patients with schizophrenia.
Method
This trial is designed as a randomised clinical trial comparing treatment with different kinds of antipsychotics. A total sample of 2000 patients with schizophrenia will be recruited from in-patient units from five clinical research centres. Using a computer-generated program, the participants will be randomly assigned to four treatment groups: aripiprazole, olanzapine, quetiapine and risperidone. The primary outcomes will be measured as changes in the Positive and Negative Syndrome Scale of schizophrenia, which reflects the efficacy. Secondary outcomes include the measure of side-effects, such as metabolic syndromes. The efficacy evaluation and side-effects assessment will be performed at baseline, 2 weeks, 6 weeks and 3 months.
Results
This trial will assess the efficacy and side effects of antipsychotics and create a standard clinical cohort with a multi-dimensional index assessment of antipsychotic treatment for schizophrenia patients.
Conclusion
This study aims to set up an individualized preferred treatment prediction model through the genetic analysis of patients using different kinds of antipsychotics.