Three-Dimensional Virtual Optical Clearing With Cycle-Consistent Generative Adversarial Network

High-throughput deep tissue imaging and chemical tissue clearing protocols have brought out great promotion in biological research. However, due to uneven transparency introduced by tissue anisotropy in imperfectly cleared tissues, fluorescence imaging based on direct chemical tissue clearing still encounters great challenges, such as image blurring, low contrast, artifacts and so on. Here we reported a three-dimensional virtual optical clearing method based on unsupervised cycle-consistent generative adversarial network, termed 3D-VoCycleGAN, to digitally improve image quality and tissue transparency of biological samples. We demonstrated the good image deblurring and denoising capability of our method on imperfectly cleared mouse brain and kidney tissues. With 3D-VoCycleGAN prediction, the signal-to-background ratio (SBR) of images in imperfectly cleared brain tissue areas also showed above 40% improvement. Compared to other deconvolution methods, our method could evidently eliminate the tissue opaqueness and restore the image quality of the larger 3D images deep inside the imperfect cleared biological tissues with higher efficiency. And after virtually cleared, the transparency and clearing depth of mouse kidney tissues were increased by up to 30%. To our knowledge, it is the first interdisciplinary application of the CycleGAN deep learning model in the 3D fluorescence imaging and tissue clearing fields, promoting the development of high-throughput volumetric fluorescence imaging and deep learning techniques

Exposure time relevance of response to nitrite exposure: Insight from transcriptional responses of immune and antioxidant defense in the crayfish, Procambarus clarkii

Abstract(#br)To understand the toxic effects of nitrite exposure on crayfish, expression of genes involved in the immune system, the antioxidant defense, and the heat shock protein 70 (HSP70) was measured after 12, 24, and 48 h of different nitrite concentrations exposure in the hepatopancreas and hemocytes of Procambarus clarkii . Nitrite exposure up-regulated mRNA levels of cytoplasmic Mn superoxide dismutase (cMn-SOD), catalase (CAT), glutathione peroxidase (GPx), and glutathione-S-transferase (GST), after 24 h nitrite exposure. At 48 h, nitrite exposure decreased the mRNA levels of mitochondrial MnSOD (mMn-SOD), CAT, and GPx. High concentrations of nitrite at 48 h of exposure decreased expression of β-1,3-glucan-bingding protein in the hepatopancreas, and lysozyme expression in hemocytes. Nitrite exposure caused little effect on the heat shock protein 70 (HSP70) in hemocytes. Through overall clustering analysis, we found that 24 h of nitrite exposure caused stronger transcriptional responses. Our study indicated that the response of P. clarkii to acute nitrite exposure was exposure time-dependent. These results will help to understand the dynamic response pattern of crustaceans to nitrite pollution, and improve our understanding of the toxicological mechanisms of nitrite in crustaceans

Antipsychotics-induced improvement of cool executive function in individuals living with schizophrenia

Cool executive dysfunction is a crucial feature in people living with schizophrenia which is related to cognition impairment and the severity of the clinical symptoms. Based on electroencephalogram (EEG), our current study explored the change of brain network under the cool executive tasks in individuals living with schizophrenia before and after atypical antipsychotic treatment (before_TR vs. after_TR). 21 patients with schizophrenia and 24 healthy controls completed the cool executive tasks, involving the Tower of Hanoi Task (THT) and Trail-Marking Test A-B (TMT A-B). The results of this study uncovered that the reaction time of the after_TR group was much shorter than that of the before_TR group in the TMT-A and TMT-B. And the after_TR group showed fewer error numbers in the TMT-B than those of the before_TR group. Concerning the functional network, stronger DMN-like linkages were found in the before_TR group compared to the control group. Finally, we adopted a multiple linear regression model based on the change network properties to predict the patient’s PANSS change ratio. Together, the findings deepened our understanding of cool executive function in individuals living with schizophrenia and might provide physiological information to reliably predict the clinical efficacy of schizophrenia after atypical antipsychotic treatment

Evidences for pressure-induced two-phase superconductivity and mixed structures of NiTe₂ and NiTe in type-II Dirac semimetal NiTe_(2-x) (x = 0.38 ± 0.09) single crystals

Bulk NiTe₂ is a type-II Dirac semimetal with non-trivial Berry phases associated with the Dirac fermions. Theory suggests that monolayer NiTe₂ is a two-gap superconductor, whereas experimental investigation of bulk NiTe_(1.98) for pressures (P) up to 71.2 GPa do not reveal any superconductivity. Here we report experimental evidences for pressure-induced two-phase superconductivity as well as mixed structures of NiTe₂ and NiTe in Te-deficient NiTe_(2-x) (x = 0.38±0.09) single crystals. Hole-dominant multi-band superconductivity with the P3M1 hexagonal-symmetry structure of NiTe₂ appears at P ≥ 0.5 GPa, whereas electron-dominant single-band superconductivity with the P2/m monoclinic-symmetry structure of NiTe emerges at 14.5 GPa < P < 18.4 GPa. The coexistence of hexagonal and monoclinic structures and two-phase superconductivity is accompanied by a zero Hall coefficient up to ∼ 40 GPa, and the second superconducting phase prevails above 40 GPa, reaching a maximum T_c = 7.8 K and persisting up to 52.8 GPa. Our findings suggest the critical role of Te-vacancies in the occurrence of superconductivity and potentially nontrivial topological properties in NiTe_(2-x)

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

Specific reactions of different striatal neuron types in morphology induced by quinolinic acid in rats.

Huntington's disease (HD) is a neurological degenerative disease and quinolinic acid (QA) has been used to establish HD model in animals through the mechanism of excitotoxicity. Yet the specific pathological changes and the underlying mechanisms are not fully elucidated. We aimed to reveal the specific morphological changes of different striatal neurons in the HD model. Sprague-Dawley (SD) rats were subjected to unilaterally intrastriatal injections of QA to mimic the HD model. Behavioral tests, histochemical and immunhistochemical stainings as well as Western blots were applied in the present study. The results showed that QA-treated rats had obvious motor and cognitive impairments when compared with the control group. Immunohistochemical detection showed a great loss of NeuN+ neurons and Darpp32+ projection neurons in the transition zone in the QA group when compared with the control group. The numbers of parvalbumin (Parv)+ and neuropeptide Y (NPY)+ interneurons were both significantly reduced while those of calretinin (Cr)+ and choline acetyltransferase (ChAT)+ were not changed notably in the transition zone in the QA group when compared to the controls. Parv+, NPY+ and ChAT+ interneurons were not significantly increased in fiber density while Cr+ neurons displayed an obvious increase in fiber density in the transition zone in QA-treated rats. The varicosity densities of Parv+, Cr+ and NPY+ interneurons were all raised in the transition zone after QA treatment. In conclusion, the present study revealed that QA induced obvious behavioral changes as well as a general loss of striatal projection neurons and specific morphological changes in different striatal interneurons, which may help further explain the underlying mechanisms and the specific functions of various striatal neurons in the pathological process of HD