Borderline Personality and the Detection of Angry Faces

Background

Many studies have assessed emotion recognition in patients with Borderline Personality Disorder and considerable evidence has been accumulated on patients’ ability to categorize emotions. In contrast, their ability to detect emotions has been investigated sparsely. The only two studies that assessed emotion detection abilities found contradictory evidence on patients’ ability to detect angry faces.

Methods

To clarify whether patients with Borderline Personality Disorder show enhanced detection of angry faces, we conducted three experiments: a laboratory study (n = 53) with a clinical sample and two highly powered web studies that measured Borderline features (n₁ = 342, n₂ = 220). Participants in all studies completed a visual search paradigm, and the reaction times for the detection of angry vs. happy faces were measured.

Results

Consistently, data spoke against enhanced detection of angry faces in the Borderline groups, indicated by non-significant group (Borderline vs. healthy control) × target (angry vs. happy) interactions, despite highly satisfactory statistical power to detect even small effects.

Conclusions

In contrast to emotion categorization, emotion detection appears to be intact in patients with Borderline Personality Disorder and individuals high in Borderline features. The importance of distinguishing between these two processes in future studies is discussed.     

Monitoring population‐level responses of marine mammals to human activities

We provide guidance for monitoring whether human activities affect the physiology or behavior of marine mammals and, if so, whether those effects may lead to changes in survival and reproduction at the population level. We suggest that four elements be included in designing and implementing such a monitoring program. The first is development of a theory of change: a set of mechanistic hypotheses that outline why a given activity might be expected to have one or more measurable effects on individuals and populations, and ideally the magnitude, timing, and duration of the effects. The second element, definition of biologically meaningful effect sizes, ultimately facilitates the development of a monitoring program that can detect those magnitudes of effect with the desired levels of precision. The third element, selection of response variables for monitoring, allows inference to whether observed changes in the status of individuals or populations are attributable to a given activity. Visual observations, passive acoustic and tagging instruments, and direct physical measurements all can provide data that facilitate quantitative hypothesis testing. The fourth element is specification of the temporal sequence of monitoring. These elements also can be used to inform monitoring of the responses of other taxonomic groups to human activities.     

Immunogenicity of plant‐produced porcine circovirus‐like particles in mice

Porcine circovirus type 2 (PCV‐2) is the main causative agent associated with a group of diseases collectively known as porcine circovirus‐associated disease (PCAD). There is a significant economic strain on the global swine industry due to PCAD and the production of commercial PCV‐2 vaccines is expensive. Plant expression systems are increasingly regarded as a viable technology to produce recombinant proteins for use as pharmaceutical agents and vaccines. However, successful production and purification of PCV‐2 capsid protein (CP) from plants is an essential first step towards the goal of a plant‐produced PCV‐2 vaccine candidate. In this study, the PCV‐2 CP was transiently expressed in Nicotiana benthamiana plants via agroinfiltration and PCV‐2 CP was successfully purified using sucrose gradient ultracentrifugation. The CP self‐assembled into virus‐like particles (VLPs) resembling native virions and up to 6.5 mg of VLPs could be purified from 1 kg of leaf wet weight. Mice immunized with the plant‐produced PCV‐2 VLPs elicited specific antibody responses to PCV‐2 CP. This is the first report describing the expression of PCV‐2 CP in plants, the confirmation of its assembly into VLPs and the demonstration of their use to elicit a strong immune response in a mammalian model.     

Associations of plasma high-sensitivity C-reactive protein concentrations with all-cause and cause-specific mortality among middle-aged and elderly individuals

Background

The plasma level of the inflammatory biomarker soluble urokinase plasminogen activator receptor (suPAR) is a strong predictor of disease development and premature mortality in the general population. Unhealthy lifestyle habits such as smoking or unhealthy eating is known to elevate the suPAR level. We aimed to investigate whether change in lifestyle habits impact on the suPAR level, and whether the resultant levels are associated with mortality.

Results

Paired suPAR measurements from baseline- and the 5-year visit of the population-based Inter99 study were compared with the habits of diet, smoking, alcohol consumption, and physical activity. Paired suPAR measurements for 3225 individuals were analyzed by linear regression, adjusted for demographics and lifestyle habits. Compared to individuals with a healthy lifestyle, an unhealthy diet, low physical activity, and daily smoking were associated with a 5.9, 12.8, and 17.6% higher 5-year suPAR, respectively. During 6.1 years of follow-up after the 5-year visit, 1.6% of those with a low suPAR (mean 2.93 ng/ml) died compared with 3.8% of individuals with a high suPAR (mean 4.73 ng/ml), P <  0.001. In Cox regression analysis, adjusted for demographics and lifestyle, the hazard ratio for mortality per 5-year suPAR doubling was 2.03 (95% CI: 1.22–3.37).

Conclusion

Lifestyle has a considerable impact on suPAR levels; the combination of unhealthy habits was associated with 44% higher 5-year suPAR values and the 5-year suPAR was a strong predictor of mortality. We propose suPAR as a candidate biomarker for lifestyle changes as well as the subsequent risk of mortality.

     

Association between the ACCN1 gene and multiple sclerosis in Central East Sardinia

Multiple genome screens have been performed to identify regions in linkage or association with Multiple Sclerosis (MS, OMIM 126200), but little overlap has been found among them. This may be, in part, due to a low statistical power to detect small genetic effects and to genetic heterogeneity within and among the studied populations. Motivated by these considerations, we studied a very special population, namely that of Nuoro, Sardinia, Italy. This is an isolated, old, and genetically homogeneous population with high prevalence of MS. Our study sample includes both nuclear families and unrelated cases and controls. A multi-stage study design was adopted. In the first stage, microsatellites were typed in the 17q11.2 region, previously independently found to be in linkage with MS. One significant association was found at microsatellite D17S798. Next, a bioinformatic screening of the region surrounding this marker highlighted an interesting candidate MS susceptibility gene: the Amiloride-sensitive Cation Channel Neuronal 1 (ACCN1) gene. In the second stage of the study, we resequenced the exons and the 3' untranslated (UTR) region of ACCN1, and investigated the MS association of Single Nucleotide Polymorphisms (SNPs) identified in that region. For this purpose, we developed a method of analysis where complete, phase-solved, posterior-weighted haplotype assignments are imputed for each study individual from incomplete, multi-locus, genotyping data. The imputed assignments provide an input to a number of proposed procedures for testing association at a microsatellite level or of a sequence of SNPs. These include a Mantel-Haenszel type test based on expected frequencies of pseudocase/pseudocontrol haplotypes, as well as permutation based tests, including a combination of permutation and weighted logistic regression analysis. Application of these methods allowed us to find a significant association between MS and the SNP rs28936 located in the 3' UTR segment of ACCN1 with p = 0.0004 (p = 0.002, after adjusting for multiple testing). This result is in tune with several recent experimental findings which suggest that ACCN1 may play an important role in the pathogenesis of MS.