A conditional multi-label model to improve prediction of a rare outcome: An illustration predicting autism diagnosis.

OBJECTIVE: This study aimed to develop a novel approach using routinely collected electronic health records (EHRs) data to improve the prediction of a rare event. We illustrated this using an example of improving early prediction of an autism diagnosis, given its low prevalence, by leveraging correlations between autism and other neurodevelopmental conditions (NDCs). METHODS: To achieve this, we introduced a conditional multi-label model by merging conditional learning and multi-label methodologies. The conditional learning approach breaks a hard task into more manageable pieces in each stage, and the multi-label approach utilizes information from related neurodevelopmental conditions to learn predictive latent features. The study involved forecasting autism diagnosis by age 5.5 years, utilizing data from the first 18 months of life, and the analysis of feature importance correlations to explore the alignment within the feature space across different conditions. RESULTS: Upon analysis of health records from 18,156 children, we are able to generate a model that predicts a future autism diagnosis with moderate performance (AUROC=0.76). The proposed conditional multi-label method significantly improves predictive performance with an AUROC of 0.80 (p < 0.001). Further examination shows that both the conditional and multi-label approach alone provided marginal lift to the model performance compared to a one-stage one-label approach. We also demonstrated the generalizability and applicability of this method using simulated data with high correlation between feature vectors for different labels. CONCLUSION: Our findings underscore the effectiveness of the developed conditional multi-label model for early prediction of an autism diagnosis. The study introduces a versatile strategy applicable to prediction tasks involving limited target populations but sharing underlying features or etiology among related groups.

Causal oscillations in the visual thalamo-cortical network in sustained attention in ferrets.

Sustained visual attention allows us to process and react to unpredictable, behaviorally relevant sensory input. Sustained attention engages communication between the higher-order visual thalamus and its connected cortical regions. However, it remains unclear whether there is a causal relationship between oscillatory circuit dynamics and attentional behavior in these thalamo-cortical circuits. By using rhythmic optogenetic stimulation in the ferret, we provide causal evidence that higher-order visual thalamus coordinates thalamo-cortical and cortico-cortical functional connectivity during sustained attention via spike-field phase locking. Increasing theta but not alpha power in the thalamus improved accuracy and reduced omission rates in a sustained attention task. Further, the enhancement of effective connectivity by stimulation was correlated with improved behavioral performance. Our work demonstrates a potential circuit-level causal mechanism for how the higher-order visual thalamus modulates cortical communication through rhythmic synchronization during sustained attention.

Effect of fangchinoline on oxidant status in male albino rats with streptozotocin-induced diabetes

BACKGROUND Diabetes is a metabolic disorder caused by defects in insulin production and activity. During disease progression, changes in lipid peroxidation cause structural modifications via production of free radicals. Fangchinoline is a well-known alkaloid present in Stephaniae tetrandrine S. Moore, which has demonstrated antioxidant, anticancer, and anti-inflammatory activities. RESULTS The present study analyzed the anti-diabetic and antioxidant effects of fangchinoline in male rats with streptozotocin-induced diabetes. Rats were divided into the following groups: normal control, diabetic, diabetic + fangchinoline 100 mg/kg, diabetic + fangchinoline 200 mg/kg and diabetic + glibencla mide 600 mg/kg. The treatment was administered orally for 45 consecutive days. Lipid peroxidation was substantially increased by >50% in the serum, as well as the liver, kidney, and heart tissues of diabetic rats. However, fangchinoline supplementation significantly reduced lipid peroxidation to near normal levels. Reactive oxygen species levels were substantially increased by >500% in the serum, as well as the liver, kidney, and heart tissues of diabetic rats. Fangchinoline supplementation reduced reactive oxygen species to near normal levels. Fangchinoline supplementation significantly improved superoxide dismutase, glutathione peroxidase, catalase, and reduced glutathione levels in diabetic rats. Total hexoses, sialic acid, hexosamines, and fucose were increased in diabetic rats, whereas fangchinoline supplementation significantly reduced these total hexoses, sialic acid, hexosamines, and fucose to near normal levels CONCLUSIONS Supplementation with fangchinoline led to significant attenuation of the levels of lipid peroxidation, ROS, and glycoprotein components such as total hexoses, hexosamines, sialic acid, and fucose, while improving antioxidant marker levels

Transcranial alternating current stimulation entrains alpha oscillations by preferential phase synchronization of fast-spiking cortical neurons to stimulation waveform.

Computational modeling and human studies suggest that transcranial alternating current stimulation (tACS) modulates alpha oscillations by entrainment. Yet, a direct examination of how tACS interacts with neuronal spiking activity that gives rise to the alpha oscillation in the thalamo-cortical system has been lacking. Here, we demonstrate how tACS entrains endogenous alpha oscillations in head-fixed awake ferrets. We first show that endogenous alpha oscillations in the posterior parietal cortex drive the primary visual cortex and the higher-order visual thalamus. Spike-field coherence is largest for the alpha frequency band, and presumed fast-spiking inhibitory interneurons exhibit strongest coupling to this oscillation. We then apply alpha-tACS that results in a field strength comparable to what is commonly used in humans (<0.5 mV/mm). Both in these ferret experiments and in a computational model of the thalamo-cortical system, tACS entrains alpha oscillations by following the theoretically predicted Arnold tongue. Intriguingly, the fast-spiking inhibitory interneurons exhibit a stronger entrainment response to tACS in both the ferret experiments and the computational model, likely due to their stronger endogenous coupling to the alpha oscillation. Our findings demonstrate the in vivo mechanism of action for the modulation of the alpha oscillation by tACS.