A Network of Psychopathological, Cognitive, and Motor Symptoms in Schizophrenia Spectrum Disorders

Schizophrenia spectrum disorders (SSDs) are complex syndromes involving psychopathological, cognitive, and also motor symptoms as core features. A better understanding of how these symptoms mutually impact each other could translate into diagnostic, prognostic, and, eventually, treatment advancements. The present study aimed to: (1) estimate a network model of psychopathological, cognitive, and motor symptoms in SSD; (2) detect communities and explore the connectivity and relative importance of variables within the network; and (3) explore differences in subsample networks according to remission status. A sample of 1007 patients from a multisite cohort study was included in the analysis. We estimated a network of 43 nodes, including all the items from the Positive and Negative Syndrome Scale, a cognitive assessment battery and clinical ratings of extrapyramidal symptoms. Methodologies specific to network analysis were employed to address the study’s aims. The estimated network for the total sample was densely interconnected and organized into 7 communities. Nodes related to insight, abstraction capacity, attention, and suspiciousness were the main bridges between network communities. The estimated network for the subgroup of patients in remission showed a sparser density and a different structure compared to the network of nonremitted patients. In conclusion, the present study conveys a detailed characterization of the interrelations between a set of core clinical elements of SSD. These results provide potential novel clues for clinical assessment and intervention

Comment on "Critique of q-entropy for thermal statistics" by M. Nauenberg

It was recently published by M. Nauenberg [1] a quite long list of objections about the physical validity for thermal statistics of the theory sometimes referred to in the literature as {\it nonextensive statistical mechanics}. This generalization of Boltzmann-Gibbs (BG) statistical mechanics is based on the following expression for the entropy: S_q= k\frac{1- \sum_{i=1}^Wp_i^q}{q-1} (q \in {\cal R}; S_1=S_{BG} \equiv -k\sum_{i=1}^W p_i \ln p_i) . The author of [1] already presented orally the essence of his arguments in 1993 during a scientific meeting in Buenos Aires. I am replying now simultaneously to the just cited paper, as well as to the 1993 objections (essentially, the violation of "fundamental thermodynamic concepts", as stated in the Abstract of [1]).Comment: 7 pages including 2 figures. This is a reply to M. Nauenberg, Phys. Rev. E 67, 036114 (2003

Seminal plasma proteins and their relationship with percentage of morphologically normal sperm in 2-year-old Brahman (Bos indicus) bulls

The objective was to determine the relationship between seminal plasma proteins and sperm morphology in Bos indicus bulls of the Brahman breed. Fifty-six 24-month-old Australian Brahman bulls were electroejaculated and samples were examined to determine the percentage of morphologically normal sperm (PNS24) and the seminal plasma protein composition was identified and quantified by 2-D gel electrophoresis. The total integrated optical density of 152 seminal plasma protein spots (SPPs) across all gels was determined using the PDQuest software version 8.0 (Bio Rad, USA). Using a single regression mixed model with the density of individual spots as a covariate for PNS24, 17 SPPs were significantly associated with PNS24 (

Integrative analysis based on HPLC-DAD-MS/MS and NMR of Bertholletia excelsa Bark Biomass Residues: Determination of ellagic acid derivatives

Bertholletia excelsa Bonpl. (Lecythidaceae) is a South American tree worldwide known for providing the Brazil nuts. In the Amazon Region, B. excelsa is found in monocultures, integrating agroforestries and providing raw materials for food and timber industries. Through the application of an integrative analysis based on high-performance liquid chromatography coupled with diode array detector and tandem mass spectrometry (HPLC-DAD-MS/MS) and nuclear magnetic resonance (NMR) techniques, the present study showed that B. excelsa bark biomass residues contain large quantities of ellagic acid (EA) and its derivatives. Qualitatively, five compounds were characterized for the first time in this species. Quantitations were carried out to determine the total amount of these compounds in outer and inner bark tissues. A total of 4.96 and 44.09 g of EA derivatives per kg of dry residues was determined for the outer and inner barks, respectively. Among the EA derivatives, eschweilenol C, ellagic acid and valoneic acid dilactone were the main compounds. These results pointed B. excelsa barks as a valuable biomass residue with potential to be source of health-promoting compounds. Therefore, a potential raw material as source of valuable bioactive phenolic compounds is described herein. © 2019 Sociedade Brasileira de Química