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Purpose: To analyze the factors influencing the progression of myopia in adolescents receiving orthokeratology. Methods: This prospective cohort study collected the data of 378 myopia patients receiving orthokeratology. The follow-up time was 12 months ranging from December 2015 to December 2019. The group-based trajectory modeling (GBTM) was used to identify similar developmental trajectories in the levels of uncorrected visual acuity and changes of axial length elongation. Univariate and multivariate logistic regression analyses were conducted to explore the influencing factors of myopia development in patients wearing orthokeratology. Results: There was no factor having effect on visual acuity (left) and visual acuity (right) in different trajectories (all P>0.05). The corneal curvature K1 (left) (OR=0.382, 95% CI: 0.188-0.776), corneal curvature K2 (left) (OR=0.362, 95% CI: 0.187-0.699), degree of spherical refraction (left) (OR=0.139, 95% CI: 0.082-0.235) and spherical equivalent (left) (OR=7.276, 95% CI: 3.724-14.215) were factors associated with the changes of axial length elongation (left). The corneal curvature K1 (right) (OR=0.260, 95% CI: 0.116-0.585), corneal curvature K2 (left) (OR=0.272, 95% CI: 0.121-0.610) and degree of spherical refraction (right) (OR=0.129, 95% CI: 0.068-0.244) were correlated with the changes of axial length elongation (right). All P<0.05. Conclusion: Orthokeratology is a promising method for controlling the progression of myopia. The corneal curvature, degree of spherical refraction and spherical equivalent were factors influencing the changes of axial length elongation in myopia patients wearing orthokeratology. The findings might give a reference for the application of orthokeratology in clinic.

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As one of three top-priority eutrophic lakes in China, Dianchi Lake has received national attention due to its severe eutrophication in recent decades. Meteorological factors are the main factors driving the formation and persistence of algae blooms. In addition, meteorological variation-induced algal blooms usually have a hysteresis effect. However, there have been few quantitative studies on this hysteresis effect. In the present study, Landsat images were used to extract the dynamic characteristics of changes in algal blooms in Dianchi Lake from 1988 to 2020. The hysteresis effect of meteorological factors driving algal blooms was studied by employing the modified lag-correlation method. The results showed that the algal blooms in Dianchi Lake were most severe between 1998 and 2008. During the periods of algal blooms, the values of air temperature (AT) and precipitation (PP) were significantly higher, while those wind velocity (WV) and sunshine duration (SSD) were obviously lower, than the corresponding annual mean values. AT and PP were significantly positively correlated with algal bloom factors in both the formation and persistence stages of algal blooms, while SSD and WV both promoted their regression, but these effects were less significant in the persistence period than in the formation period. Moreover, rainfall led to a decrease in SSD and WV, indirectly contributing to algal blooms. Furthermore, AT, PP and SSD are the main factors impacting the duration of persistent blooms. The time periods during which each meteorological factor was most influential were as follows: 1) AT - 25-30 days before the maximum bloom. 2) PP - within the first 10 days before the maximum bloom. 3) Both SSD and WV - 15-20 days before the maximum bloom. The results of this study support the prediction of algal blooms in Dianchi Lake.

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PURPOSE: Ovarian cancer is one of the most common gynecological cancers in women with a low 5-year survival rate. Evaluation of hyaluronic acid-binding protein 1 (HABP1) level can provide important information for the diagnosis and treatment of ovarian cancer. In this study, we designed a novel HABP1 probe based on 99mTc-radiolabeled small-interference RNA (siRNA) for detecting HABP1 expression noninvasively in vivo, thereby providing a new method for its diagnosis and treatment. METHODS: A specific siHABP1 was selected because of its targetability and silencing effect. A negative control siRNA (NCsiRNA) with no homology with the human genome was used. SiHABP1 and NCsiRNA were radiolabeled with 99mTc using the bifunctional chelating agent hydrazinonicotinamide (HYNIC). The radiochemical purity and in vitro stability of the probe were determined by HPLC. The binding activity was measured by western blotting (WB) and RT-PCR. The HABP1-overexpressing human ovarian cancer cell line HO-8910 was used for cell uptake experiments, which were performed with or without transfection and measured with a gamma counter. HO8910-bearing mice were imaged at 1, 4, and 10 h, and biodistribution analysis was performed at 1, 4, 6, and 10 h after injection of 99mTc-HYNIC-siRNA. RESULTS: 99mTc-HYNIC-siHABP1 had high radiochemical purity and good in vitro stability, and showed the same binding capacity and silencing effect as siHABP1. SPECT imaging showed that tumors were clearly visualized at 10 h after injection of 99mTc-HYNIC-siHABP1 but not after 99mTc-HYNIC-NCsiRNA, implying specific binding. The biodistribution results were consistent with those of SPECT imaging. CONCLUSIONS: We showed that 99mTc-HYNIC-siHABP1 is a feasible probe for the noninvasive visualization of HABP1 expression in ovarian cancer.

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A cornerstone of theoretical neuroscience is the circuit model: a system of equations that captures a hypothesized neural mechanism. Such models are valuable when they give rise to an experimentally observed phenomenon -- whether behavioral or a pattern of neural activity -- and thus can offer insights into neural computation. The operation of these circuits, like all models, critically depends on the choice of model parameters. A key step is then to identify the model parameters consistent with observed phenomena: to solve the inverse problem. In this work, we present a novel technique, emergent property inference (EPI), that brings the modern probabilistic modeling toolkit to theoretical neuroscience. When theorizing circuit models, theoreticians predominantly focus on reproducing computational properties rather than a particular dataset. Our method uses deep neural networks to learn parameter distributions with these computational properties. This methodology is introduced through a motivational example of parameter inference in the stomatogastric ganglion. EPI is then shown to allow precise control over the behavior of inferred parameters and to scale in parameter dimension better than alternative techniques. In the remainder of this work, we present novel theoretical findings in models of primary visual cortex and superior colliculus, which were gained through the examination of complex parametric structure captured by EPI. Beyond its scientific contribution, this work illustrates the variety of analyses possible once deep learning is harnessed towards solving theoretical inverse problems.

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Context-based sensorimotor routing is a hallmark of executive control. Pharmacological inactivations in rats have implicated the midbrain superior colliculus (SC) in this process. But what specific role is this, and what circuit mechanisms support it? Here we report a subset of rat SC neurons that instantiate a specific link between the representations of context and motor choice. Moreover, these neurons encode animals' choice far earlier than other neurons in the SC or in the frontal cortex, suggesting that their neural dynamics lead choice computation. Optogenetic inactivations revealed that SC activity during context encoding is necessary for choice behavior, even while that choice behavior is robust to inactivations during choice formation. Searches for SC circuit models matching our experimental results identified key circuit predictions while revealing some a priori expected features as unnecessary. Our results reveal circuit mechanisms within the SC that implement response inhibition and context-based vector inversion during executive control.

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Survival in a dynamic environment requires animals to plan future actions based on past sensory evidence, known as motor planning. However, the neuronal circuits underlying this crucial brain function remain elusive. Here, we employ projection-specific imaging and perturbation methods to investigate the direct pathway linking two key nodes in the motor planning network, the secondary motor cortex (M2) and the midbrain superior colliculus (SC), in mice performing a memory-dependent perceptual decision task. We find dynamic coding of choice information in SC-projecting M2 neurons during motor planning and execution, and disruption of this information by inhibiting M2 terminals in SC selectively impaired decision maintenance. Furthermore, we show that while both excitatory and inhibitory SC neurons receive synaptic inputs from M2, these SC subpopulations display differential temporal patterns in choice coding during behavior. Our results reveal the dynamic recruitment of the premotor-collicular pathway as a circuit mechanism for motor planning.

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The posterior parietal cortex (PPC) has been implicated in perceptual decision-making and categorization, but whether its activity plays a causal role remains controversial. Here we examined the population dynamics of PPC activity during an auditory-guided decision task in mice. We found that silencing of PPC activity impaired several aspects of decision-making. First, categorization of new, but not well-learned, stimuli was impaired. Second, re-categorization of previously experienced stimuli based on newly learned categories was also impaired. Third, the bias on behavioral choices created by preceding trials significantly increased. In vivo two-photon imaging of PPC activity during stimulus categorization revealed differential dynamics in representations of new stimuli and learned categories, consistent with rapid incorporation of new sensory information during categorization. At the circuit level, inactivation of PPC axonal projections to the auditory cortex also significantly reduced categorization performance. Thus, PPC circuits play a causal role in decision-making during stimulus categorization.

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To study rapid sensorimotor remapping, we developed a method to train rats in a behavior in which subjects are cued, on each trial, to apply a sensorimotor association to orient either toward a visual target ("Pro") or away from it, toward its reverse ("Anti"). Multiple behavioral asymmetries suggested that Anti behavior is cognitively demanding while Pro is easier to learn and perform. This is consistent with a prominent hypothesis in the primate literature that Anti requires prefrontal cortex (PFC), whereas Pro could be mediated by midbrain superior colliculus (SC). Pharmacological inactivation of rat medial PFC supported its expected role in Anti. Remarkably, bilateral SC inactivation substantially impaired Anti while leaving Pro essentially intact. Moreover, SC inactivation eliminated the performance cost of switching from Anti to Pro tasks. Our results establish a rodent model of single-trial sensorimotor remapping and suggest a critical role for SC in the cognitively demanding Anti task.

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Numerous brain regions have been shown to have neural correlates of gradually accumulating evidence for decision-making, but the causal roles of these regions in decisions driven by accumulation of evidence have yet to be determined. Here, in rats performing an auditory evidence accumulation task, we inactivated the frontal orienting fields (FOF) and posterior parietal cortex (PPC), two rat cortical regions that have neural correlates of accumulating evidence and that have been proposed as central to decision-making. We used a detailed model of the decision process to analyze the effect of inactivations. Inactivation of the FOF induced substantial performance impairments that were quantitatively best described as an impairment in the output pathway of an evidence accumulator with a long integration time constant (>240 ms). In contrast, we found a minimal role for PPC in decisions guided by accumulating auditory evidence, even while finding a strong role for PPC in internally-guided decisions.

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Gradual accumulation of evidence is thought to be fundamental for decision-making, and its neural correlates have been found in several brain regions. Here we develop a generalizable method to measure tuning curves that specify the relationship between neural responses and mentally accumulated evidence, and apply it to distinguish the encoding of decision variables in posterior parietal cortex and prefrontal cortex (frontal orienting fields, FOF). We recorded the firing rates of neurons in posterior parietal cortex and FOF from rats performing a perceptual decision-making task. Classical analyses uncovered correlates of accumulating evidence, similar to previous observations in primates and also similar across the two regions. However, tuning curve assays revealed that while the posterior parietal cortex encodes a graded value of the accumulating evidence, the FOF has a more categorical encoding that indicates, throughout the trial, the decision provisionally favoured by the evidence accumulated so far. Contrary to current views, this suggests that premotor activity in the frontal cortex does not have a role in the accumulation process, but instead has a more categorical function, such as transforming accumulated evidence into a discrete choice. To probe causally the role of FOF activity, we optogenetically silenced it during different time points of the trial. Consistent with a role in committing to a categorical choice at the end of the evidence accumulation process, but not consistent with a role during the accumulation itself, a behavioural effect was observed only when FOF silencing occurred at the end of the perceptual stimulus. Our results place important constraints on the circuit logic of brain regions involved in decision-making.

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Most adults consume alcohol with relative impunity, but about 10-20% of users persist (or progress) in their consumption, despite mounting and serious repercussions. Identifying at-risk individuals before neuroadaptative changes associated with chronic use become well ingrained is thus a key step in mitigating and preventing the end stage disease and its devastating impacts. Explaining liability has been impeded, in part, by the absence of animal models for assessing initial sensitivity to the drug's reinforcing properties, an important endophenotype in the trajectory toward excessive drinking. Here we assess the initial rewarding effects of the drug in a novel application of the conditioned place preference paradigm. In contrast to previous studies that have all employed repeated drug administration, we demonstrated a robust preference for a context paired with a single exposure to 1.5 g/kg EtOH in male and female subjects of three strains. This model validates an assay of initial sensitivity to the subjective rewarding effects of alcohol, a widely used drug with multifarious impacts on both brain and society, and provides a new tool for theory-driven endophenotypic pharmacogenetic approaches to understanding and treating addiction.

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