Dairy consumption and cardiometabolic diseases: systematic review and updated meta-analyses of prospective cohort studies

Purpose of Review Dairy products contain both beneficial and harmful nutrients in relation to cardiometabolic diseases. Here, we provide the latest scientific evidence regarding the relationship between dairy products and cardiometabolic diseases by reviewing the literature and updating meta-analyses of observational studies. Recent Findings We updated our previous meta-analyses of cohort studies on type 2 diabetes, coronary heart disease (CHD), and stroke with nine studies and confirmed previous results. Total dairy and low-fat dairy (per 200 g/d) were inversely associated with a 3–4% lower risk of diabetes. Yogurt was non-linearly inversely associatedwith diabetes (RR = 0.86, 95%CI: 0.83–0.90 at 80 g/ d). Total dairy and milk were not associated with CHD (RR~1.0). An increment of 200 g of daily milk intake was associated with an 8% lower risk of stroke. Summary The latest scientific evidence confirmed neutral or beneficial associations between dairy products and risk of cardiometabolic diseases

Identification and correction of previously unreported spatial phenomena using raw Illumina BeadArray data

<p>Abstract</p> <p>Background</p> <p>A key stage for all microarray analyses is the extraction of feature-intensities from an image. If this step goes wrong, then subsequent preprocessing and processing stages will stand little chance of rectifying the matter. Illumina employ random construction of their BeadArrays, making feature-intensity extraction even more important for the Illumina platform than for other technologies. In this paper we show that using raw Illumina data it is possible to identify, control, and perhaps correct for a range of spatial-related phenomena that affect feature-intensity extraction.</p> <p>Results</p> <p>We note that feature intensities can be unnaturally high when in the proximity of a number of phenomena relating either to the images themselves or to the layout of the beads on an array. Additionally we note that beads neighbour beads of the same type more often than one might expect, which may cause concern in some models of hybridization. We highlight issues in the identification of a bead's location, and in particular how this both affects and is affected by its intensity. Finally we show that beads can be wrongly identified in the image on either a local or array-wide scale, with obvious implications for data quality.</p> <p>Conclusions</p> <p>The image processing issues identified will often pass unnoticed by an analysis of the standard data returned from an experiment. We detail some simple diagnostics that can be implemented to identify problems of this nature, and outline approaches to correcting for such problems. These approaches require access to the raw data from the arrays, not just the summarized data usually returned, making the acquisition of such raw data highly desirable.</p

Rules extraction from neural networks applied to the prediction and recognition of prokaryotic promoters

Promoters are DNA sequences located upstream of the gene region and play a central role in gene expression. Computational techniques show good accuracy in gene prediction but are less successful in predicting promoters, primarily because of the high number of false positives that reflect characteristics of the promoter sequences. Many machine learning methods have been used to address this issue. Neural Networks (NN) have been successfully used in this field because of their ability to recognize imprecise and incomplete patterns characteristic of promoter sequences. In this paper, NN was used to predict and recognize promoter sequences in two data sets: (i) one based on nucleotide sequence information and (ii) another based on stability sequence information. The accuracy was approximately 80% for simulation (i) and 68% for simulation (ii). In the rules extracted, biological consensus motifs were important parts of the NN learning process in both simulations

Instructor feedback versus no instructor feedback on performance in a laparoscopic virtual reality simulator: a randomized educational trial

<p>Abstract</p> <p>Background</p> <p>Several studies have found a positive effect on the learning curve as well as the improvement of basic psychomotor skills in the operating room after virtual reality training. Despite this, the majority of surgical and gynecological departments encounter hurdles when implementing this form of training. This is mainly due to lack of knowledge concerning the time and human resources needed to train novice surgeons to an adequate level. The purpose of this trial is to investigate the impact of instructor feedback regarding time, repetitions and self-perception when training complex operational tasks on a virtual reality simulator.</p> <p>Methods/Design</p> <p>The study population consists of medical students on their 4^thto 6^thyear without prior laparoscopic experience. The study is conducted in a skills laboratory at a centralized university hospital. Based on a sample size estimation 98 participants will be randomized to an intervention group or a control group. Both groups have to achieve a predefined proficiency level when conducting a laparoscopic salpingectomy using a surgical virtual reality simulator. The intervention group receives standardized instructor feedback of 10 to 12 min a maximum of three times. The control group receives no instructor feedback. Both groups receive the automated feedback generated by the virtual reality simulator. The study follows the CONSORT Statement for randomized trials. Main outcome measures are time and repetitions to reach the predefined proficiency level on the simulator. We include focus on potential sex differences, computer gaming experience and self-perception.</p> <p>Discussion</p> <p>The findings will contribute to a better understanding of optimal training methods in surgical education.</p> <p>Trial Registration</p> <p><a href="http://www.clinicaltrials.gov/ct2/show/NCT01497782">NCT01497782</a></p

An iterative strategy combining biophysical criteria and duration hidden Markov models for structural predictions of Chlamydia trachomatis σ66 promoters

<p>Abstract</p> <p>Background</p> <p>Promoter identification is a first step in the quest to explain gene regulation in bacteria. It has been demonstrated that the initiation of bacterial transcription depends upon the stability and topology of DNA in the promoter region as well as the binding affinity between the RNA polymerase σ-factor and promoter. However, promoter prediction algorithms to date have not explicitly used an ensemble of these factors as predictors. In addition, most promoter models have been trained on data from <it>Escherichia coli</it>. Although it has been shown that transcriptional mechanisms are similar among various bacteria, it is quite possible that the differences between <it>Escherichia coli </it>and <it>Chlamydia trachomatis </it>are large enough to recommend an organism-specific modeling effort.</p> <p>Results</p> <p>Here we present an iterative stochastic model building procedure that combines such biophysical metrics as DNA stability, curvature, twist and stress-induced DNA duplex destabilization along with duration hidden Markov model parameters to model <it>Chlamydia trachomatis </it>σ⁶⁶promoters from 29 experimentally verified sequences. Initially, iterative duration hidden Markov modeling of the training set sequences provides a scoring algorithm for <it>Chlamydia trachomatis </it>RNA polymerase σ⁶⁶/DNA binding. Subsequently, an iterative application of Stepwise Binary Logistic Regression selects multiple promoter predictors and deletes/replaces training set sequences to determine an optimal training set. The resulting model predicts the final training set with a high degree of accuracy and provides insights into the structure of the promoter region. Model based genome-wide predictions are provided so that optimal promoter candidates can be experimentally evaluated, and refined models developed. Co-predictions with three other algorithms are also supplied to enhance reliability.</p> <p>Conclusion</p> <p>This strategy and resulting model support the conjecture that DNA biophysical properties, along with RNA polymerase σ-factor/DNA binding collaboratively, contribute to a sequence's ability to promote transcription. This work provides a baseline model that can evolve as new <it>Chlamydia trachomatis </it>σ⁶⁶promoters are identified with assistance from the provided genome-wide predictions. The proposed methodology is ideal for organisms with few identified promoters and relatively small genomes.</p

The Effects of Biting and Pulling on the Forces Generated during Feeding in the Komodo Dragon (Varanus komodoensis)

In addition to biting, it has been speculated that the forces resulting from pulling on food items may also contribute to feeding success in carnivorous vertebrates. We present an in vivo analysis of both bite and pulling forces in Varanus komodoensis, the Komodo dragon, to determine how they contribute to feeding behavior. Observations of cranial modeling and behavior suggest that V. komodoensis feeds using bite force supplemented by pulling in the caudal/ventrocaudal direction. We tested these observations using force gauges/transducers to measure biting and pulling forces. Maximum bite force correlates with both body mass and total body length, likely due to increased muscle mass. Individuals showed consistent behaviors when biting, including the typical medial-caudal head rotation. Pull force correlates best with total body length, longer limbs and larger postcranial motions. None of these forces correlated well with head dimensions. When pulling, V. komodoensis use neck and limb movements that are associated with increased caudal and ventral oriented force. Measured bite force in Varanus komodoensis is similar to several previous estimations based on 3D models, but is low for its body mass relative to other vertebrates. Pull force, especially in the ventrocaudal direction, would allow individuals to hunt and deflesh with high success without the need of strong jaw adductors. In future studies, pull forces need to be considered for a complete understanding of vertebrate carnivore feeding dynamics

Relationship of depression, disability, and family caregiver attitudes to the quality of life of Kuwaiti persons with multiple sclerosis: a controlled study

<p>Abstract</p> <p>Background</p> <p>Assessment of subjective quality of life (QOL) of persons with multiple sclerosis (MS) could facilitate the detection of psychosocial aspects of disease that may otherwise go unrecognized. The objectives of the study were to (i) compare the QOL ratings of relapsing remitting (RRMS) and progressive (PMS) types of MS with those of a general population group and the impression of their family caregivers; and (ii) assess the association of demographic, clinical, treatment, depression, and caregiver variables with patients' QOL.</p> <p>Methods</p> <p>Consecutive clinic attendees at the national neurology hospital were assessed with the 26 -item WHOQOL Instrument, Beck's Depression Inventory and Expanded Disability Scale. Caregivers rated their impression of patients' QOL and attitudes to patients' illness.</p> <p>Results</p> <p>The 170 patients (60 m, 109 f) consisted of 145(85.3%) with RRMS and 25 with PMS, aged 32.4(SD 8.8), age at onset 27.1(7.7), EDSS score 2.9 (1.8), and 76% were employed. The patients were predominantly dissatisfied with their life circumstances. The RRMS group had higher QOL domain scores (P < 0.001), and lower depression(P > 0.05) and disability (P < 0.0001) scores than the PMS group. Patients had significantly lower QOL scores than the control group (P < 0.001). Caregiver impression was significantly correlated with patients' ratings. Depression was the commonest significant covariate of QOL domains. When we controlled for depression and disability scores, differences between the two MS groups became significant for only one (out of 6) QOL domains. Patients who were younger, better educated, employed, felt less sick and with lesser side effects, had higher QOL. The predictors of patients' overall QOL were disability score, caregiver impression of patients' QOL, and caregiver fear of having MS.</p> <p>Conclusion</p> <p>Our data indicate that MS patients in stable condition and with social support can hope to have better QOL, if clinicians pay attention to depression, disability, the impact of side effects of treatment and family caregiver anxieties about the illness. The findings call for a regular program of psychosocial intervention in the clinical setting, to address these issues and provide caregiver education and supports, in order to enhance the quality of care.</p

Association between depression, anxiety and weight change in young adults

Background To investigate whether there are bi-directional associations between anxiety and mood disorders and body mass index (BMI) in a cohort of young adults. Methods We analysed data from the 2004–2006 (baseline) and 2009–2011 (follow-up) waves of the Childhood Determinants of Adult Health study. Lifetime DSM-IV anxiety and mood disorders were retrospectively diagnosed with the Composite International Diagnostic Interview. Potential mediators were individually added to the base models to assess their potential role as a mediator of the associations. Results In males, presence of mood disorder history at baseline was positively associated with BMI gain (β = 0.77, 95% CI: 0.14–1.40), but baseline BMI was not associated with subsequent risk of mood disorder. Further adjustment for covariates, including dietary pattern, physical activity, and smoking reduced the coefficient (β) to 0.70 (95% CI: 0.01–1.39), suggesting that the increase in BMI was partly mediated by these factors. In females, presence of mood disorder history at baseline was not associated with subsequent weight gain, however, BMI at baseline was associated with higher risk of episode of mood disorder (RR per kg/m2: 1.04, 95% CI: 1.01–1.08), which was strengthened (RR per kg/m2 = 1.07, 95% CI: 1.00–1.15) after additional adjustment in the full model. There was no significant association between anxiety and change in BMI and vice-versa. Conclusion The results do not suggest bidirectional associations between anxiety and mood disorders, and change in BMI. Interventions promoting healthy lifestyle could contribute to reducing increase in BMI associated with mood disorder in males, and excess risk of mood disorder associated with BMI in females