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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.
In this paper, effects of discharge parameters and modulation frequency on the signal of laser-induced fluorescence measurements of ion velocity distribution functions are investigated in the LIF Test Source. A maximum modulation frequency is found for each given set of parameters, beyond which the signal gradually declines. Meanwhile, this maximum modulation frequency occurred consistently at ~1/10 of the theoretical frequency limit and photon counts received by a photomultiplier tube, which indicates that as modulation frequency and the associated per-pulse-excitation-event count decrease, the transition from the macroscopic statistical signal to the microscopic probabilistic signal is a gradual process.
Linoleic acid (LA) has a two-sided effect with regards to serum cholesterol lowering and pro-inflammation, although whether this fatty acid reduces serum cholesterol and the development of atherosclerosis under high-cholesterol conditions has yet to be ascertained. In this study, we examine the effects of dietary LA on reducing serum cholesterol and atherosclerosis development under high-cholesterol conditions. Male and female apolipoprotein E-deficient (Apo E-/-) mice were fed AIN-76-based diets containing 10% saturated fatty acids and 0.04 % cholesterol (SFA), 10% LA and 0.04% low cholesterol (LALC), or 10% LA and 0.1% high cholesterol (LAHC) for 9 weeks. The results revealed significant reduction in serum cholesterol levels and aortic lesions with increasing levels of pro-inflammatory biomarkers (urinary isoprostane and aortic MCP-1 mRNA) in male and female LALC groups compared with those in the SFA groups (P < 0.05). Furthermore, whereas there were significant increases in the serum cholesterol levels and aortic lesions (P < 0.05), there was no difference in aortic MCP-1 mRNA levels in male and female LAHC groups compared with those in the LALC groups. A high dietary intake of cholesterol eliminated the serum cholesterol-lowering activity of LA but had no significant effect on aortic inflammation in either male or female ApoE-/- mice. The inhibitory effect of LA on arteriosclerosis is cancelled by a high-cholesterol diet due to a direct increase in serum cholesterol levels. Accordingly, serum cholesterol levels might represent a more prominent pathogenic factor than aortic inflammation in promoting the development of atherosclerosis.
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.
The association between executive dysfunction, brain dysconnectivity, and inflammation is a prominent feature across major psychiatric disorders (MPDs), schizophrenia, bipolar disorder, and major depressive disorder. A dimensional approach is warranted to delineate their mechanistic interplay across MPDs.
This single site study included a total of 1543 participants (1058 patients and 485 controls). In total, 1169 participants underwent diffusion tensor and resting-state functional magnetic resonance imaging (745 patients and 379 controls completed the Wisconsin Card Sorting Test). Fractional anisotropy (FA) and regional homogeneity (ReHo) assessed structural and functional connectivity, respectively. Pro-inflammatory cytokine levels [interleukin (IL)-1β, IL-6, and tumor necrosis factor-α] were obtained in 325 participants using blood samples collected with 24 h of scanning. Group differences were determined for main measures, and correlation and mediation analyses and machine learning prediction modeling were performed.
Executive deficits were associated with decreased FA, increased ReHo, and elevated IL-1β and IL-6 levels across MPDs, compared to controls. FA and ReHo alterations in fronto-limbic-striatal regions contributed to executive deficits. IL-1β mediated the association between FA and cognition, and IL-6 mediated the relationship between ReHo and cognition. Executive cognition was better predicted by both brain connectivity and cytokine measures than either one alone for FA-IL-1β and ReHo-IL-6.
Transdiagnostic associations among brain connectivity, inflammation, and executive cognition exist across MPDs, implicating common neurobiological substrates and mechanisms for executive deficits in MPDs. Further, inflammation-related brain dysconnectivity within fronto-limbic-striatal regions may represent a transdiagnostic dimension underlying executive dysfunction that could be leveraged to advance treatment.
Metamaterials, including their two-dimensional counterparts, are composed of subwavelength-scale artificial particles. These materials have novel electromagnetic properties, and can be artificially tailored for various applications. Based on metamaterials and metasurfaces, many abnormal physical phenomena have been realized, such as negative refraction, invisible cloaking, abnormal reflection and focusing, and many new functions and devices have been developed. The effective medium theory lays the foundation for design and application of metamaterials and metasurfaces, connecting metamaterials with real world applications. In this Element, the authors combine these essential ingredients, and aim to make this Element an access point to this field. To this end, they review classical theories for dielectric functions, effective medium theory, and effective parameter extraction of metamaterials, also introducing front edge technologies like metasurfaces with theories, methods, and potential applications. Energy densities are also included.
As acute infectious pneumonia, the coronavirus disease-2019 (COVID-19) has created unique challenges for each nation and region. Both India and the United States (US) have experienced a second outbreak, resulting in a severe disease burden. The study aimed to develop optimal models to predict the daily new cases, in order to help to develop public health strategies. The autoregressive integrated moving average (ARIMA) models, generalised regression neural network (GRNN) models, ARIMA–GRNN hybrid model and exponential smoothing (ES) model were used to fit the daily new cases. The performances were evaluated by minimum mean absolute per cent error (MAPE). The predictive value with ARIMA (3, 1, 3) (1, 1, 1)14 model was closest to the actual value in India, while the ARIMA–GRNN presented a better performance in the US. According to the models, the number of daily new COVID-19 cases in India continued to decrease after 27 May 2021. In conclusion, the ARIMA model presented to be the best-fit model in forecasting daily COVID-19 new cases in India, and the ARIMA–GRNN hybrid model had the best prediction performance in the US. The appropriate model should be selected for different regions in predicting daily new cases. The results can shed light on understanding the trends of the outbreak and giving ideas of the epidemiological stage of these regions.
As a neuroprogressive illness, depression is accompanied by brain structural abnormality that extends to many brain regions. However, the progressive structural alteration pattern remains unknown.
To elaborate the progressive structural alteration of depression according to illness duration, we recruited 195 never-treated first-episode patients with depression and 130 healthy controls (HCs) undergoing T1-weighted MRI scans. Voxel-based morphometry method was adopted to measure gray matter volume (GMV) for each participant. Patients were first divided into three stages according to the length of illness duration, then we explored stage-specific GMV alterations and the causal effect relationship between them using causal structural covariance network (CaSCN) analysis.
Overall, patients with depression presented stage-specific GMV alterations compared with HCs. Regions including the hippocampus, the thalamus and the ventral medial prefrontal cortex (vmPFC) presented GMV alteration at onset of illness. Then as the illness advanced, others regions began to present GMV alterations. These results suggested that GMV alteration originated from the hippocampus, the thalamus and vmPFC then expanded to other brain regions. The results of CaSCN analysis revealed that the hippocampus and the vmPFC corporately exerted causal effect on regions such as nucleus accumbens, the precuneus and the cerebellum. In addition, GMV alteration in the hippocampus was also potentially causally related to that in the dorsolateral frontal gyrus.
Consistent with the neuroprogressive hypothesis, our results reveal progressive morphological alteration originating from the vmPFC and the hippocampus and further elucidate possible details about disease progression of depression.
Black nightshade (Solanum nigrum L.) is one of the worst weeds in crop fields, and it spreads mainly by the dispersal of seeds. Temperature is one of the key environmental factors affecting seed germination. We investigated the seed germination response to temperature in six populations of S. nigrum from mid- to northern China and derived mathematical models from germination data. The results showed that S. nigrum seeds exhibit distinct germination responses to temperature within the range of 15 to 35 C. The optimum temperature for populations XJ1600, JL1697, and HLJ2134 was 30 C, and those for populations NMG1704, HN2160, and LN2209 were 25, 20, and 15 C, respectively. Based on the nonlinear fitting and thermal time models, the predicted base temperatures of the six populations ranged from 2.3 to 6.4 C, and the required accumulated growing degree days (GDD) ranged from 50.3 to 106.0 C·d. The base temperatures and the accumulated GDD for germination differed among populations, and there was a significant negative correlation. HLJ2134 population required a high base temperature and accumulated GDD for germination, indicating that it might be highly adapted to a warmer and moister environment. Based on the different germination responses of S. nigrum populations to temperature, the thermal time model reflects an innate relationship between base temperature and accumulated GDD required for initiation of seed germination, which provides a better basis for predicting seedling emergence and the timing for optimal control of S. nigrum under field conditions.
The effects of early thiamine use on clinical outcomes in critically ill patients with acute kidney injury (AKI) are unclear. The purpose of this study was to investigate the associations between early thiamine administration and clinical outcomes in critically ill patients with AKI. The data of critically ill patients with AKI within 48 h after ICU admission were extracted from the Medical Information Mart for Intensive Care III (MIMIC III) database. PSM was used to match patients early receiving thiamine treatment to those not early receiving thiamine treatment. The association between early thiamine use and in-hospital mortality due to AKI was determined using a logistic regression model. A total of 15 066 AKI patients were eligible for study inclusion. After propensity score matching (PSM), 734 pairs of patients who did and did not receive thiamine treatment in the early stage were established. Early thiamine use was associated with lower in-hospital mortality (OR 0·65; 95 % CI 0·49, 0·87; P < 0·001) and 90-d mortality (OR 0·58; 95 % CI 0·45, 0·74; P < 0·001), and it was also associated with the recovery of renal function (OR 1·26; 95 % CI 1·17, 1·36; P < 0·001). In the subgroup analysis, early thiamine administration was associated with lower in-hospital mortality in patients with stages 1 to 2 AKI. Early thiamine use was associated with improved short-term survival in critically ill patients with AKI. It was possible beneficial role in patients with stages 1 to 2 AKI according to the Kidney Disease: Improving Global Outcomes criteria.
The present study evaluated effects of dietary supplementation with tryptophan (Trp) on muscle growth, protein synthesis and antioxidant capacity in hybrid catfish Pelteobagrus vachelli♀ × Leiocassis longirostris♂. Fish were fed six different diets containing 2·6 (control), 3·1, 3·7, 4·2, 4·7 and 5·6 g Trp/kg diet for 56 d, respectively. Results showed that dietary Trp significantly (1) improved muscle protein content, fibre density and frequency of fibre diameter; (2) up-regulated the mRNA levels of PCNA, myf5, MyoD1, MyoG, MRF4, IGF-I, IGF-II, IGF-IR, PIK3Ca, TOR, 4EBP1 and S6K1; (3) increased phosphorylation levels of AKT, TOR and S6K1; (4) decreased contents of MDA and PC, and increased activities of CAT, GST, GR, ASA and AHR; (5) up-regulated mRNA levels of CuZnSOD, CAT, GST, GPx, GCLC and Nrf2, and decreased Keap1 mRNA level; (6) increased nuclear Nrf2 protein level and the intranuclear antioxidant response element-binding ability, and reduced Keap1 protein level. These results indicated that dietary Trp improved muscle growth, protein synthesis as well as antioxidant capacity, which might be partly related to myogenic regulatory factors, IGF/PIK3Ca/AKT/TOR and Keap1/Nrf2 signalling pathways. Finally, based on the quadratic regression analysis of muscle protein and MDA contents, the optimal Trp requirements of hybrid catfish (21·82–39·64 g) were estimated to be 3·94 and 3·93 g Trp/kg diet (9·57 and 9·54 g/kg of dietary protein), respectively.
The tropical areas of eastern Asia contain a high diversity of foliicolous lichens, including various species of the genus Badimia. Badimia xanthocampylidia W. C. Wang & J. C. Wei is described from tropical rainforests in southern China and Thailand based on morphology, chemistry, and combined mtSSU, ITS and nrLSU sequences. It is characterized by a pale green thallus with yellow verrucae and bright yellow campylidia and the presence of isousnic acid. Three other species, B. multiseptata Papong & Lücking, B. pallidula (Kremp.) Vězda and B. polillensis (Vain.) Vězda, are discussed and the genus Badimia is newly reported from China. A worldwide key to currently known species in the genus is presented.
Microtubule-severing protein (MTSP) is critical for the survival of both mitotic and postmitotic cells. However, the study of MTSP during meiosis of mammalian oocytes has not been reported. We found that spastin, a member of the MTSP family, was highly expressed in oocytes and aggregated in spindle microtubules. After knocking down spastin by specific siRNA, the spindle microtubule density of meiotic oocytes decreased significantly. When the oocytes were cultured in vitro, the oocytes lacking spastin showed an obvious maturation disorder. Considering the microtubule-severing activity of spastin, we speculate that spastin on spindles may increase the number of microtubule broken ends by severing the microtubules, therefore playing a nucleating role, promoting spindle assembly and ensuring normal meiosis. In addition, we found the colocalization and interaction of collapsin response mediator protein 5 (CRMP5) and spastin in oocytes. CRMP5 can provide structural support and promote microtubule aggregation, creating transportation routes, and can interact with spastin in the microtubule activity of nerve cells (30). Knocking down CRMP5 may lead to spindle abnormalities and developmental disorders in oocytes. Overexpression of spastin may reverse the abnormal phenotype caused by the deletion of CRMP5. In summary, our data support a model in which the interaction between spastin and CRMP5 promotes the assembly of spindle microtubules in oocytes by controlling microtubule dynamics, therefore ensuring normal meiosis.
Schizophrenia is considered a polygenic disorder. People with schizophrenia and those with genetic high risk of schizophrenia (GHR) have presented with similar neurodevelopmental deficits in hemispheric asymmetry. The potential associations between neurodevelopmental abnormalities and schizophrenia-related risk genes in both schizophrenia and those with GHR remains unclear.
To investigate the shared and specific alternations to the structural network in people with schizophrenia and those with GHR. And to identify an association between vulnerable structural network alternation and schizophrenia-related risk genes.
A total of 97 participants with schizophrenia, 79 participants with GHR and 192 healthy controls, underwent diffusion tensor imaging (DTI) scans at a single site. We used graph theory to characterise hemispheric and whole-brain structural network topological metrics. For 26 people in the schizophrenia group and 48 in the GHR group with DTI scans we also calculated their schizophrenia-related polygenic risk scores (SZ-PRSs). The correlations between alterations to the structural network and SZ-PRSs were calculated. Based on the identified genetic–neural association, bioinformatics enrichment was explored.
There were significant hemispheric asymmetric deficits of nodal efficiency, global and local efficiency in the schizophrenia and GHR groups. Hemispheric asymmetric deficit of local efficiency was significantly positively correlated with SZ-PRSs in the schizophrenia and GHR groups. Bioinformatics enrichment analysis showed that these risk genes may be linked to signal transduction, neural development and neuron structure. The schizophrenia group showed a significant decrease in the whole-brain structural network.
The shared asymmetric deficits in people with schizophrenia and those with GHR, and the association between anomalous asymmetry and SZ-PRSs suggested a vulnerability imaging marker regulated by schizophrenia-related risk genes. Our findings provide new insights into asymmetry regulated by risk genes and provides a better understanding of the genetic–neural pathological underpinnings of schizophrenia.
It is important to maintain the psychological well-being of front-line healthcare staff during the coronavirus disease 2019 (COVID-19) pandemic.
To examine COVID-19-related stress and its immediate psychological impact on healthcare staff.
All healthcare staff working in the fever clinic, from 20 January 2020 to 26 March 2020, of a tertiary general hospital were enrolled. Stress management procedures were in place to alleviate concerns about the respondents’ own health and the health of their families, to help them adjust their work and to provide psychological support via a hotline. Qualitative interviews were undertaken and the Sources of Distress and the Impact of Event Scale-Revised (IES-R) were administered.
Among the 102 participants (25 males; median age 30 years, interquartile range (IQR) = 27–36), the median IES-R total score was 3 (IQR = 0–8), and 6 participants (6.0%) scored above the cut-off on the IES-R (≥20). Safety and security were acceptable or better for 92 (90.2%) participants. The top four sources of distress were worry about the health of one's family/others at 0.88 (IQR = 0.25–1.25), worry about the virus spread at 0.50 (IQR = 0.00–1.00), worry about changes in work at 0.50 (IQR = 0.00–1.00) and worry about one's own health at 0.25 (IQR = 0.25–0.75). There was a moderate correlation between the IES-R score and the Sources of Distress score (rho = 0.501, P = 0.001).
The stress levels of healthcare staff in the fever clinic during the COVID-19 epidemic were not elevated. Physio-psychosocial interventions, including fulfilment of basic needs, activation of self-efficacy and psychological support, are helpful and worth recommending in fighting COVID-19.