https://www.selleckchem.com/products/ly2874455.html A marker for distinguishing patients with obsessive-compulsive disorder (OCD) spectrum has not yet been identified. Whole-brain resting-state effective and functional connectivity (rsEC and rsFC, respectively) networks were constructed for 50 unmedicated OCD (U-OCD) patients, 45 OCD patients in clinical remission (COCD), 47 treatment-resistant OCD (T-OCD) patients, 42 chronic schizophrenia patients who exhibit OCD symptoms (SCHOCD), and 50 healthy controls (HCs). Multivariate pattern analysis (MVPA) was performed to investigate the accuracy of using connectivity alterations to distinguished among the aforementioned groups. Compared to HCs, rsEC connections were significantly disrupted in the U-OCD (n = 15), COCD (n = 8), and T-OCD (n = 19) groups. Additionally, 21 rsEC connections were significantly disrupted in the T-OCD group compared to the SCHOCD group. The disrupted rsEC networks were associated mainly with the frontal-parietal cortex, basal ganglia, limbic regions, and the cerebellum. Classification accuracies for distinguishing OCD patients from HCs and SCHOCD patients ranged from 66.6% to 98.0%. In conclusion, disrupted communication from the frontal-parietal cortices to subcortical basal nuclei and the cerebellum may represent a functional pathological feature of the OCD spectrum. MVPA based on both abnormal rsEC and rsFC patterns may aid in early differential diagnosis of OCD.Nowadays, organic solar cells (OSCs) with non-fullerene electron acceptors provide the highest efficiencies among all studied OSCs. To further improve the efficiencies of fullerene-free organic solar cells, end-capped acceptor modification is made with strong electron withdrawing groups. In this report, we have theoretically designed five new novel Benzodithiophene core-based acceptor molecules (H1-H5) with the aim to study the possible enhancement in photophysical, optoelectronic, and photovoltaic properties of newly designed molecu