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Background and Aims:The Liver Frailty Index (LFI) is a well-studied tool that evaluates frailty in patients with cirrhosis. Consisting of grip strength, chair stands, and balance testing, the LFI has been associated with increased mortality in patients awaiting liver transplant. We aimed to extend our understanding of frailty in cirrhosis by exploring the relationship between the LFI and the risk of (1) cirrhosis progression, (2) mortality, and (3) unplanned hospitalizations, in both compensated and decompensated disease. Approach and Results: Adult patients with cirrhosis from four centers inNorth America and one in India were included. Frailty was measured at baseline using the LFI and categorized as robust (LFI < 3.2), prefrail (LFI 3.2-4.5), and frail (LFI > 4.5). Progression of cirrhosis was defined by an increase in clinical stage, ranging from 1 to 5, from baseline using the D'Amico classification. Factors associated with progression, mortality, and hospitalizations were evaluated using multivariate regression models, with transplant as a competing risk. In total, 822 patients with cirrhosis were included. Average Model for End-Stage Liver Disease (MELD) score was 15.5 ± 6.0. In patients with compensated cirrhosis, being frail versus robust was associated with increased risk of progression to the next cirrhosis stage or to death (HR, 2.45; 95% CI, 1.14-5.29) and with an increased risk of unplanned hospitalizations (2.32; 95% CI, 1.13-4.79), after adjusting for age, sex, and MELD score. Similar HRs were observed in patients with decompensated cirrhosis. Conclusions:Frailty was an independent predictor of cirrhosis progression or death and unplanned hospitalization across patients with compensated and decompensated cirrhosis. Future studies are needed to evaluate the possibility of slowing cirrhosis disease progression by reversing or preventing frailty.

Prostaglandin-E 2 (PGE 2 ), an important mediator of inflammation, achieves its functions via four different G protein-coupled receptors (EP1, EP2, EP3, and EP4). We previously demonstrated that the EP2 receptor plays a proinflammatory and neurodegenerative role after status epilepticus (SE). We recently developed TG8-260 as a second-generation highly potent and selective EP2 antagonist. Here, we investigate whether TG8-260 is anti-inflammatory and combats neuropathology caused by pilocarpineinduced SE in rats. Adult male Sprague-Dawley rats were injected subcutaneously with pilocarpine (380-400 mg/kg) to induce SE. Following 60 min of SE, the rats were administered three doses of TG8-260 or vehicle and were allowed to recover. Neurodegeneration, neuroinflammation, gliosis, and blood-brain barrier (BBB) integrity were examined 4 days after SE. The results confirmed that pilocarpine-induced SE results in hippocampal neurodegeneration and a robust inflammatory response that persists days after SE. Furthermore, inhibition of the EP2 receptor by TG8-260 administered beginning 2 h after SE significantly reduced hippocampal neuroinflammation and gliosis but, in distinction to the earlier generation EP2 antagonist, did not mitigate neuronal injury or BBB breakdown. Thus, attenuation of neuroinflammation and gliosis is a common feature of EP2 inhibition following SE.

Invasive neural recording in humans shows promise for understanding the circuit basis of brain disorders. Most recordings have been done for short durations from externalized brain leads in hospital settings, or from first-generation implantable sensing devices that offer only intermittent brief streaming of time series data. Here we report the first human use of an implantable neural interface for wireless multichannel streaming of field potentials over long periods, with and without simultaneous therapeutic neurostimulation, untethered to receiving devices. Four Parkinson's disease patients streamed bilateral 4-channel motor cortical and basal ganglia field potentials at home for over 500 hours, paired with wearable monitors that behaviorally categorize states of inadequate or excessive movement. Motor state during normal home activities was efficiently decoded using either supervised learning or unsupervised clustering algorithms. This platform supports adaptive deep brain stimulation, and may be widely applicable to brain disorders treatable by invasive neuromodulation.