Diagnostic Accuracy and Acceptability of the Primary Care Posttraumatic Stress Disorder Screen for the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) among US Veterans

Importance: Posttraumatic stress disorder (PTSD) is a serious mental health disorder that can be effectively treated with empirically based practices. PTSD screening is essential for identifying undetected cases and providing patients with appropriate care. Objective: To determine whether the Primary Care PTSD screen for the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (PC-PTSD-5) is a diagnostically accurate and acceptable measure for use in Veterans Affairs (VA) primary care clinics. Design, Setting, and Participants: This cross-sectional, diagnostic accuracy study enrolled participants from May 19, 2017, to September 26, 2018. Participants were recruited from primary care clinics across 2 VA Medical Centers. Session 1 was conducted in person, and session 2 was completed within 30 days via telephone. A consecutive sample of 1594 veterans, aged 18 years or older, who were scheduled for a primary care visit was recruited. Data analysis was performed from March 2019 to August 2020. Exposures: In session 1, participants completed a battery of questionnaires. In session 2, a research assistant administered the PC-PTSD-5 to participants, and then a clinician assessor blind to PC-PTSD-5 results conducted a structured diagnostic interview for PTSD. Main Outcomes and Measures: The range of PC-PTSD-5 cut points overall and across gender was assessed, and diagnostic performance was evaluated by calculating weighted κ values. Results: In total, 495 of 1594 veterans (31%) participated, and 396 completed all measures and were included in the analyses. Participants were demographically similar to the VA primary care population (mean [SD] age, 61.4 [15.5] years; age range, 21-93 years) and were predominantly male (333 participants [84.1%]) and White (296 of 394 participants [75.1%]). The PC-PTSD-5 had high levels of diagnostic accuracy for the overall sample (area under the receiver operating characteristic curve [AUC], 0.927; 95% CI, 0.896-0.959), men (AUC, 0.932; 95% CI, 0.894-0.969), and women (AUC, 0.899, 95% CI, 0.824-0.974). A cut point of 4 ideally balanced false negatives and false positives for the overall sample and for men. However, for women, this cut point resulted in high numbers of false negatives (6 veterans [33.3%]). A cut point of 3 fit better for women, despite increasing the number of false positives. Participants rated the PC-PTSD-5 as highly acceptable. Conclusions and Relevance: The PC-PTSD-5 is an accurate and acceptable screening tool for use in VA primary care settings. Because performance parameters will change according to sample, clinicians should consider sample characteristics and screening purposes when selecting a cut point

The Design and Development of the SMEX-Lite Power System

This paper describes the design and development of a 250W orbit average electrical power system electronic Power Node and software for use in Low Earth Orbit missions. The mass of the Power Node is 3.6 Kg (8 lb.). The dimensions of the Power Node are 30cm x 26cm x 7.9cm (11 in. x 10.25 in x 3.1 in.) The design was realized using software, Field Programmable Gate Array (FPGA) digital logic and surface mount technology. The design is generic enough to reduce the non-recurring engineering for different mission configurations. The Power Node charges one to five, low cost, 22-cell 4 AH D-cell battery packs independently. The battery charging algorithms are executed in the power software to reduce the mass and size of the power electronic. The Power Node implements a peak-power tracking algorithm using an innovative hardware/software approach. The power software task is hosted on the spacecraft processor. The power software task generates a MIL-STD-1553 command packet to update the Power Node control settings. The settings for the battery voltage and current limits, as well as minimum solar array voltage used to implement peak power tracking are contained in this packet. Several advanced topologies are used in the Power Node. These include synchronous rectification in the bus regulators, average current control in the battery chargers and quasi-resonant converters for the Field Effect Transistor (FET) transistor drive electronics. Lastly, the main bus regulator uses a feed-forward topology with the PWM implemented in an FPGA

Mental Health Service Utilization before and after Receipt of a Service‐Connected Disability Award for PTSD: Findings from a National Sample

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146624/1/hesr12859.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146624/2/hesr12859-sup-0001-AppendixSA1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146624/3/hesr12859_am.pd

Yeast-Derived Formulations Are Differentially Fermented by the Canine and Feline Microbiome As Assessed in a Novel in Vitro Colonic Fermentation Model

The current study evaluated the effect of five yeast-derived formulations (T1-T5) on microbial metabolism and composition of the canine and feline gut microbiota using a novel in vitro colonic incubation approach. This novel in vitro model allowed for growth of the entire spectrum of dog- and cat-derived bacteria from the inoculum, thus offering an excellent platform to evaluate effects of nutritional interventions on the gut microbiota. Further, yeast-derived ingredients differentially increased production of acetate, propionate, butyrate, ammonium, and branched short-chain fatty acids, with T5 and T1 consistently stimulating propionate and butyrate, respectively. 16S-targeted Illumina sequencing coupled with flow cytometry provided unprecedented high-resolution quantitative insights in canine and feline microbiota modulation by yeast-derived ingredients, revealing that effects on propionate production were related to Prevotellaceae, Tannerellaceae, Bacteroidaceae, and Veillonellaceae members, while effects on butyrate production were related to Erysipelotrichaceae, Lachnospiraceae, Ruminococcaceae, and Fusobacteriaceae. Overall, these findings strengthen the health-promoting potential of yeast-derived ingredients