Multilocus phylogeny reveals <i>Gibsmithia hawaiiensis</i> (Dumontiaceae, Rhodophyta) to be a species complex from the Indo-Pacific, with the proposal of <i>G. eilatensis</i> sp. nov.

Gibsmithia hawaiiensis is a peculiar red alga characterized by furry gelatinous lobes arising from a cartilaginous stalk. The species has been recorded from tropical reef systems throughout the Indo-Pacific. A multilocus phylogeny (UPA, rbcL, COI-5P) of 36 specimens collected throughout the species distribution range, showed high genetic diversity at species level. Two major groups were identified, each consisting of multiple lineages. Genetic variability was low in the Hawaiian Islands and the northern Red Sea and high in the Western Indian Ocean and the Coral Triangle, where lineages overlap in distribution. Genetic distances suggest that G. hawaiiensis represents a complex of five cryptic species, with no difference observed in the external morphology corresponding to separate lineages. Anatomical and reproductive differences were observed at the microscopic level for the lineage from the Red Sea, which is here described as G. eilatensis sp. nov. The geographic range of the species complex is here expanded to include Madagascar, the Red Sea and the Indo-Malay region, and the generitype seems endemic to the Hawaiian Islands. Algal diversity on coral reef systems is discussed from a conservation perspective using G. hawaiiensis as an example

The overdiagnosis nightmare: a time for caution

Overdiagnosis (and overtreatment) of cancers not bound to become symptomatic during lifetime is an unavoidable drawback of mammography screening. The magnitude of overdiagnosis has been estimated to be in the range of 5-10%, and thus acceptable in view of screening benefits as to reduced mortality. In a recent research article in BMC Women's Health, Jørgensen, Zahl and Gøtzsche suggest that overdiagnosis may be as high as 33%, based on their analysis of breast cancer incidence in screened and non-screened areas in Denmark. Here we consider how reliable such analyses can be, why it might have been useful to adjust comparisons between screened and non-screened areas for early detection lead time, and what further evidence might be needed to build on or confirm these results

Bifidobacterium Is Enriched in Gut Microbiome of Kashmiri Women with Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is a very common endocrine condition in women in India. Gut microbiome alterations were shown to be involved in PCOS, yet it is remarkably understudied in Indian women who have a higher incidence of PCOS as compared to other ethnic populations. During the regional PCOS screening program among young women, we recruited 19 drug naive women with PCOS and 20 control women at the Sher-i-Kashmir Institute of Medical Sciences, Kashmir, North India. We profiled the gut microbiome in faecal samples by 16S rRNA sequencing and included 40/58 operational taxonomic units (OTUs) detected in at least 1/3 of the subjects with relative abundance (RA) ≥ 0.1%. We compared the RAs at a family/genus level in PCOS/non-PCOS groups and their correlation with 33 metabolic and hormonal factors, and corrected for multiple testing, while taking the variation in day of menstrual cycle at sample collection, age and BMI into account. Five genera were significantly enriched in PCOS cases: Sarcina, Megasphaera, and previously reported for PCOS Bifidobacterium, Collinsella and Paraprevotella confirmed by different statistical models. At the family level, the relative abundance of Bifidobacteriaceae was enriched, whereas Peptococcaceae was decreased among cases. We observed increased relative abundance of Collinsella and Paraprevotella with higher fasting blood glucose levels, and Paraprevotella and Alkalibacterium with larger hip, waist circumference, weight, and Peptococcaceae with lower prolactin levels. We also detected a novel association between Eubacterium and follicle-stimulating hormone levels and between Bifidobacterium and alkaline phosphatase, independently of the BMI of the participants. Our report supports that there is a relationship between gut microbiome composition and PCOS with links to specific reproductive health metabolic and hormonal predictors in Indian women

Excess cases of prostate cancer and estimated overdiagnosis associated with PSA testing in East Anglia

This study aimed to estimate the extent of 'overdiagnosis' of prostate cancer attributable to prostate-specific antigen (PSA) testing in the Cambridge area between 1996 and 2002. Overdiagnosis was defined conceptually as detection of prostate cancer through PSA testing that otherwise would not have been diagnosed within the patient's lifetime. Records of PSA tests in Addenbrookes Hospital were linked to prostate cancer registrations by NHS number. Differences in prostate cancer registration rates between those receiving and not receiving prediagnosis PSA tests were calculated. The proportion of men aged 40 years or over with a prediagnosis PSA test increased from 1.4 to 5.2% from 1996 to 2002. The rate of diagnosis of prostate cancer was 45% higher (rate ratios (RR) = 1.45, 95% confidence intervals (CI) 1.02-2.07) in men with a history of prediagnosis PSA testing. Assuming average lead times of 5 to 10 years, 40-64% of the PSA-detected cases were estimated to be overdiagnosed. In East Anglia, from 1996 to 2000, a 1.6% excess of cases was associated with PSA testing (around a quarter of the 5.3% excess incidence cases observed in East Anglia from 1996 to 2000). Further quantification of the overdiagnosis will result from continued surveillance and from linkage of incidence to testing in other hospitals

Depressive and anxiety disorders in concert-A synthesis of findings on comorbidity in the NESDA study

Background: Comorbidity of depressive and anxiety disorders is common and remains incompletely comprehended. This paper summarizes findings from the Netherlands Study of Depression and Anxiety (NESDA) regarding prevalence, temporal sequence, course and longitudinal patterns; sociodemographic, vulnerability and neurobiological indicators; and functional, somatic and mental health indicators of comorbidity. Methods: Narrative synthesis of earlier NESDA based papers on comorbidity (n=76). Results: Comorbidity was the rule in over three-quarter of subjects with depressive and/or anxiety disorders, most often preceded by an anxiety disorder. Higher severity and chronicity characterized a poorer comorbidity course. Over time, transitions between depressive and anxiety disorders were common. Consistent comorbidity risk indicators in subjects with depressive and anxiety disorders were childhood trauma, neuroticism and early age of onset. Psychological vulnerabilities, such as trait avoidance tendencies, were more pronounced in comorbid than in single disorders. In general, there were few differences in biological markers and neuroimaging findings between persons with comorbid versus single disorders. Most functional, somatic, and other mental health indicators, ranging from disability to cardiovascular and psychiatric multimorbidity, were highest in comorbid disorders. Limitations: The observational design of NESDA limits causal inference. Attrition was higher in comorbid relative to single disorders. Conclusions: As compared to single disorders, persons with comorbid depressive and anxiety disorders were characterized by more psychosocial risk determinants, more somatic and other psychiatric morbidities, more functional impairments, and poorer outcome. These results justify specific attention for comorbidity of depressive and anxiety disorders, particularly in treatment settings.Stress-related psychiatric disorders across the life spa

The impact of cannabidiol treatment on resting state functional connectivity, prefrontal metabolite levels and reward processing in recent-onset patients with a psychotic disorder

The first clinical trials with cannabidiol (CBD) as treatment for psychotic disorders have shown its potential as an effective and well-tolerated antipsychotic agent. However, the neurobiological mechanisms underlying the antipsychotic profile of CBD are currently unclear. Here we investigated the impact of 28-day adjunctive CBD or placebo treatment (600 mg daily) on brain function and metabolism in 31 stable recent-onset psychosis patients (&lt;5 years after diagnosis). Before and after treatment, patients underwent a Magnetic Resonance Imaging (MRI) session including resting state functional MRI, proton Magnetic Resonance Spectroscopy (1H-MRS) and functional MRI during reward processing. Symptomatology and cognitive functioning were also assessed. CBD treatment significantly changed functional connectivity in the default mode network (DMN; time × treatment interaction p = 0.037), with increased connectivity in the CBD (from 0.59 ± 0.39 to 0.80 ± 0.32) and reduced connectivity in the placebo group (from 0.77 ± 0.37 to 0.62 ± 0.33). Although there were no significant treatment effects on prefrontal metabolite concentrations, we showed that decreased positive symptom severity over time was associated with both diminishing glutamate (p = 0.029) and N-acetyl-aspartate (NAA; neuronal integrity marker) levels (p = 0.019) in the CBD, but not the placebo group. CBD treatment did not have an impact on brain activity patterns during reward anticipation and receipt or functional connectivity in executive and salience networks. Our results show that adjunctive CBD treatment of recent-onset psychosis patients induced changes in DMN functional connectivity, but not prefrontal metabolite concentrations or brain activity during reward processing. These findings suggest that DMN connectivity alteration may be involved in the therapeutic effects of CBD.</p

Identification of plasma lipid biomarkers for prostate cancer by lipidomics and bioinformatics

Background: Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer. Methodology/Principal Findings: Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer. Conclusions/Significance: Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy