The unmet challenge in prostate cancer (PCa) management is to discriminate it from benign prostate hyperplasia (BPH) due to the lack of specific diagnostic biomarkers. Contemporary research on ...potential PCa biomarkers is directed toward methylated cell-free DNA (cfDNA) from liquid biopsies since epigenetic mechanisms are strongly involved in PCa development.
In the present research, cfDNA methylation of the LGALS3 gene in blood and seminal plasma of PCa and BPH patients was assessed using pyrosequencing, as well as LGALS3 DNA methylation in tissue biopsies. Liquid biopsy samples were taken from patients with clinical suspicion of PCa, who were subsequently divided into two groups, that is, 42 with PCa and 55 with BPH, according to the histopathological analysis.
Statistically significant higher cfDNA methylation of LGALS3 in seminal plasma of BPH than in PCa patients was detected by pyrosequencing. ROC curve analysis showed that it could distinguish PCa and BPH patients with 56.4% sensitivity and 70.4% specificity, while PSA did not differ between the two patient groups. In contrast, there was no statistically significant difference in LGALS3 cfDNA methylation in blood plasma between the two patient groups. In prostate tumor tissue, there was a statistically significant DNA hypermethylation of LGALS3 compared to surrounding nontumor tissue and BPH tissue.
The DNA hypermethylation of the LGALS3 gene represents an event specific to PCa development. In conclusion, LGALS3 cfDNA methylation in seminal fluid discriminates early PCa and BPH presenting itself as a powerful novel PCa biomarker highly outperforming PSA.
Hallucinations may arise from an imbalance between sensory and higher cognitive brain regions, reflected by alterations in functional connectivity. It is unknown whether hallucinations across the ...psychosis continuum exhibit similar alterations in functional connectivity, suggesting a common neural mechanism, or whether different mechanisms link to hallucinations across phenotypes. We acquired resting-state functional MRI scans of 483 participants, including 40 non-clinical individuals with hallucinations, 99 schizophrenia patients with hallucinations, 74 bipolar-I disorder patients with hallucinations, 42 bipolar-I disorder patients without hallucinations, and 228 healthy controls. The weighted connectivity matrices were compared using network-based statistics. Non-clinical individuals with hallucinations and schizophrenia patients with hallucinations exhibited increased connectivity, mainly among fronto-temporal and fronto-insula/cingulate areas compared to controls (P < 0.001 adjusted). Differential effects were observed for bipolar-I disorder patients with hallucinations versus controls, mainly characterized by decreased connectivity between fronto-temporal and fronto-striatal areas (P = 0.012 adjusted). No connectivity alterations were found between bipolar-I disorder patients without hallucinations and controls. Our results support the notion that hallucinations in non-clinical individuals and schizophrenia patients are related to altered interactions between sensory and higher-order cognitive brain regions. However, a different dysconnectivity pattern was observed for bipolar-I disorder patients with hallucinations, which implies a different neural mechanism across the psychosis continuum.
Immunity is an important component of invasion success since it enables invaders’ adaptation to conditions of the novel environment as they expand their range. Immune response of invaders may vary ...along the invasion range due to encountered parasites/microbial communities, conditions of the local environment, and ecological processes that arise during the range expansion. Here, we analyzed changes in the immune response along the invasion range of one of the most successful aquatic invaders, the signal crayfish, in the recently invaded Korana River, Croatia. We used several standard immune parameters (encapsulation response, hemocyte count, phenoloxidaze activity, and total prophenoloxidaze) to: i) compare immune response of the signal crayfish along its invasion range, and between species (comparison with co-occurring native narrow-clawed crayfish), and ii) analyze effects of specific predictors (water temperature, crayfish abundance, and body condition) on crayfish immune response changes. Immune response displayed species-specificity, differed significantly along the signal crayfish invasion range, and was mostly affected by water temperature and population abundance. Specific immune parameters showed density-dependent variation corresponding to increased investment in them during range expansion. Obtained results offer baseline insights for elucidating the role of immunocompetence in the invasion success of an invertebrate freshwater invader.
The accurate management of testicular germ cell tumors (TGCTs) depends on identifying the individual histological tumor components. Currently available data on protein expression in TGCTs are ...limited. The human protein atlas (HPA) is a comprehensive resource presenting the expression and localization of proteins across tissue types and diseases. In this study, we have compared the data from the HPA with our in-house immunohistochemistry on core TGCT diagnostic genes to test reliability and potential biomarker genes. We have compared the protein expression of 15 genes in TGCT patients and non-neoplastic testicles with the data from the HPA. Protein expression was converted into diagnostic positivity. Our study discovered discrepancies in three of the six core TGCT diagnostic genes,
,
and
in HPA.
,
and
were presented as potential novel TGCT biomarkers.
was confirmed while
and
were identified as biomarkers of healthy testicular tissue. Finally,
,
,
and
dysregulation in the surrounding testicular tissue with complete preserved spermatogenesis of TGCT patients was detected, a potential early sign of neoplastic transformation. We highlight the importance of a multidisciplinary collaborative approach to fully understand the protein landscape of human testis and its pathologies.
Austropotamobius torrentium
is one of four native European crayfish species inhabiting Croatian freshwaters. Existence of eight divergent monophyletic mtDNA phylogroups was described within
A. ...torrentium
; six of them are distributed in Croatia, with the highest genetic diversity established in its northern-central Dinaric region. Recent small-scale study of the stone crayfish morphological variability indicated significant differences among different phylogroups. In the present study larger sample size, covering populations from five phylogroups, was analysed with the aim of determining whether there are morphological characteristics that reliably separate stone crayfish from different phylogroups. Aiming this, 245 stone crayfish were analysed through traditional (TM) and, for the first time, geometric morphometric (GM) analyses. Multivariate discriminant analyses included 24 TM characteristics per crayfish, while GM comprised analyses of 22 landmarks on the dorsal side of cephalon. Both methods revealed congruent results, and significant differences among phylogroups in analysed features were obtained, with the cephalon shape contributing the most to crayfish discrimination. Research confirmed that both approaches, combined with statistical methods, are useful in distinguishing and separating crayfish phylogroups. Findings of present study are compatible with the previous molecular findings; stone crayfish present several distinct evolutionary lineages whose species status are currently undefined and require urgent clarification.
Austropotamobius torrentium
est l'une des quatre espèces indigènes d'écrevisses européennes qui peuplent les eaux douces croates. L'existence de huit phylogroupes divergents d'ADNmt monophylétiques a été décrite chez
A. torrentium
; six d'entre eux sont distribués en Croatie, avec la plus grande diversité génétique établie dans sa région dinarique nord-centre. Une étude récente à petite échelle de la variabilité morphologique de l'écrevisse des torrents a révélé des différences significatives entre les différents phylogroupes. Dans la présente étude, on a analysé des échantillons de plus grande taille, couvrant des populations de cinq phylogroupes, dans le but de déterminer s'il existe des caractéristiques morphologiques qui séparent de façon fiable les écrevisses des torrents des différents phylogroupes. Dans ce but, 245 écrevisses des torrents ont été analysées par des analyses traditionnelles (TM) et, pour la première fois, morphométriques géométriques (GM). Les analyses discriminantes à plusieurs variables comprenaient 24 caractéristiques TM par écrevisse, tandis que les analyses GM comprenaient des analyses de 22 repères sur la face dorsale du céphalon. Les deux méthodes ont révélé des résultats congruents, et des différences significatives entre les phylogroupes dans les traits analysés ont été obtenues, la forme du céphalon contribuant le plus à la discrimination des écrevisses. La recherche a confirmé que les deux approches, combinées à des méthodes statistiques, sont utiles pour distinguer et séparer les phylogroupes d'écrevisses. Les résultats de la présente étude sont compatibles avec ceux des études moléculaires précédentes ; les écrevisses des torrents présentent plusieurs lignées évolutives distinctes dont le statut d'espèce n'est pas encore défini et nécessite une clarification urgente.
Although structural magnetic resonance imaging (MRI) has revealed partly non-overlapping brain abnormalities in schizophrenia and bipolar disorder, it is unknown whether structural MRI scans can be ...used to separate individuals with schizophrenia from those with bipolar disorder. An algorithm capable of discriminating between these two disorders could become a diagnostic aid for psychiatrists. Here, we scanned 66 schizophrenia patients, 66 patients with bipolar disorder and 66 healthy subjects on a 1.5T MRI scanner. Three support vector machines were trained to separate patients with schizophrenia from healthy subjects, patients with schizophrenia from those with bipolar disorder, and patients with bipolar disorder from healthy subjects, respectively, based on their gray matter density images. The predictive power of the models was tested using cross-validation and in an independent validation set of 46 schizophrenia patients, 47 patients with bipolar disorder and 43 healthy subjects scanned on a 3T MRI scanner. Schizophrenia patients could be separated from healthy subjects with an average accuracy of 90%. Additionally, schizophrenia patients and patients with bipolar disorder could be distinguished with an average accuracy of 88%.The model delineating bipolar patients from healthy subjects was less accurate, correctly classifying 67% of the healthy subjects and only 53% of the patients with bipolar disorder. In the latter group, lithium and antipsychotics use had no influence on the classification results. Application of the 1.5T models on the 3T validation set yielded average classification accuracies of 76% (healthy vs schizophrenia), 66% (bipolar vs schizophrenia) and 61% (healthy vs bipolar). In conclusion, the accurate separation of schizophrenia from bipolar patients on the basis of structural MRI scans, as demonstrated here, could be of added value in the differential diagnosis of these two disorders. The results also suggest that gray matter pathology in schizophrenia and bipolar disorder differs to such an extent that they can be reliably differentiated using machine learning paradigms.
•We separated patients with schizophrenia and bipolar disorder based on their sMRI scans.•We trained a support vector machine (SVM) model to do this in a 1.5T ‘discovery set’.•Using cross-validation the model obtained a classification accuracy of >80% in this set.•Applying this model to an independent 3T ‘validation set’ yielded 66% accuracy.•Patterns of brain abnormalities differ between schizophrenia and bipolar disorder.
Childhood trauma increases risk for psychopathology and cognitive impairment. Prior research mainly focused on the hippocampus and amygdala in single diagnostic categories. However, other brain ...regions may be impacted by trauma as well, and effects may be independent of diagnosis. This cross-sectional study investigated cortical and subcortical gray matter volume in relation to childhood trauma severity.
We included 554 participants: 250 bipolar-I patients, 84 schizophrenia-spectrum patients and 220 healthy individuals without a psychiatric history. Participants filled in the Childhood Trauma Questionnaire. Anatomical T1 MRI scans were acquired at 3T, regional brain morphology was assessed using Freesurfer.
In the total sample, trauma-related gray matter reductions were found in the frontal lobe (
= -0.049,
= 0.008;
= 0.048), this effect was driven by the right medial orbitofrontal, paracentral, superior frontal regions and the left precentral region. No trauma-related volume reductions were observed in any other (sub)cortical lobes nor the hippocampus or amygdala, trauma-by-group (i.e. both patient groups and healthy subjects) interaction effects were absent. A categorical approach confirmed a pattern of more pronounced frontal gray matter reductions in individuals reporting multiple forms of trauma and across quartiles of cumulative trauma scores. Similar dose-response patterns were revealed within the bipolar and healthy subgroups, but did not reach significance in schizophrenia-spectrum patients.
Findings show that childhood trauma is linked to frontal gray matter reductions, independent of psychiatric morbidity. Our results indicate that childhood trauma importantly contributes to the neurobiological changes commonly observed across psychiatric disorders. Frontal volume alterations may underpin affective and cognitive disturbances observed in trauma-exposed individuals.
BackgroundIn a large and comprehensively assessed sample of patients with bipolar disorder type I (BDI), we investigated the prevalence of psychotic features and their relationship with life course, ...demographic, clinical, and cognitive characteristics. We hypothesized that groups of psychotic symptoms (Schneiderian, mood incongruent, thought disorder, delusions, and hallucinations) have distinct relations to risk factors.MethodsIn a cross-sectional study of 1342 BDI patients, comprehensive demographical and clinical characteristics were assessed using the Structured Clinical Interview for DSM-IV (SCID-I) interview. In addition, levels of childhood maltreatment and intelligence quotient (IQ) were assessed. The relationships between these characteristics and psychotic symptoms were analyzed using multiple general linear models.ResultsA lifetime history of psychotic symptoms was present in 73.8% of BDI patients and included delusions in 68.9% of patients and hallucinations in 42.6%. Patients with psychotic symptoms showed a significant younger age of disease onset (β = −0.09, t = −3.38, p = 0.001) and a higher number of hospitalizations for manic episodes (F11 338 = 56.53, p < 0.001). Total IQ was comparable between groups. Patients with hallucinations had significant higher levels of childhood maltreatment (β = 0.09, t = 3.04, p = 0.002).ConclusionsIn this large cohort of BDI patients, the vast majority of patients had experienced psychotic symptoms. Psychotic symptoms in BDI were associated with an earlier disease onset and more frequent hospitalizations particularly for manic episodes. The study emphasizes the strength of the relation between childhood maltreatment and hallucinations but did not identify distinct subgroups based on psychotic features and instead reported of a large heterogeneity of psychotic symptoms in BD.
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