How to construct neuroscience-informed psychiatric classification?Towards nomothetic networks psychiatry

Psychiatry remains in a permanent state of crisis,which fragmented psychiatry from the field of medicine.The crisis in psychiatry is evidenced by the many different competing approaches to psychiatric illness including psychodynamic,biological,molecular,pan-omics,precision,cognitive and phenomenological psychiatry,folk psychology,mind-brain dualism,descriptive psychopathology,and postpsychiatry.The current“gold standard”Diagnostic and Statistical Manual of Mental Disorders/International Classification of Diseases taxonomies of mood disorders and schizophrenia are unreliable and preclude to employ a deductive reasoning approach.Therefore,it is not surprising that mood disorders and schizophrenia research was unable to revise the conventional classifications and did not provide more adequate therapeutic approaches.The aim of this paper is to explain the new nomothetic network psychiatry(NNP)approach,which uses machine learning methods to build data-driven causal models of mental illness by assembling risk-resilience,adverse outcome pathways(AOP),cognitome,brainome,staging,symptomatome,and phenomenome latent scores in a causal model.The latter may be trained,tested and validated with Partial Least Squares analysis.This approach not only allows to compute pathway-phenotypes or biosignatures,but also to construct reliable and replicable nomothetic networks,which are,therefore,generalizable as disease models.After integrating the validated feature vectors into a well-fitting nomothetic network,clustering analysis may be applied on the latent variable scores of the R/R,AOP,cognitome,brainome,and phenome latent vectors.This pattern recognition method may expose new(transdiagnostic)classes of patients which if cross-validated in independent samples may constitute new(transdiagnostic)nosological categories.

Potential antioxidant properties and hepatoprotective effects of Juniperus phoenicea berries against CCl4 induced hepatic damage in rats

Objective:To investigate the antioxidant and hepatoprotective properties of Juniperus phoenicea(J.phoenicea)berries against CCl_4-induced oxidative damage in rats.Methods:Hepatotoxicity was induced in albino Wistar rats by single dose of CCl_4 dissolved in olive oil(1 mL/kg BW,1/1 in olive oil,ip).Aqueous extract of J.phoenicea berries(AEJP)was administered at the dose of 250 mg/kg/day by gavage for 12 days.Results:Obtained results revealed that administration of CCl_4 caused a significant increase in plasma ASAT,ALAT,ALP and LDH activities and total bilirubin concentration,compared to the control group.While,albumin and total protein concentration were significantly lower.Additionally,a significant decrease in the level of hepatic GSH,GPx and GST activities associated with a significant increase of MDA content in CCl_4 group than those of the control.However,the treatment of experimental rats with AEJP prevented these alterations and maintained the antioxidant status.The histopathological observations supported the biochemical evidences of hepatoprotection.Conclusions:The results of the present investigation indicate that J.phoenicea possesses hepatoprotective activity and this effect was may be due to its antioxidant proprerties.