Non-Targeted Metabolomics Investigation of a Sub-Chronic Variable Stress Model Unveils Sex-Dependent Metabolic Differences Induced by Stress.

Depression is twice as prevalent in women as in men, however, most preclinical studies of depression have used male rodent models. This study aimed to examine how stress affects metabolic profiles depending on sex using a rodent depression model: sub-chronic variable stress (SCVS). The SCVS model of male and female mice was established in discovery and validation sets. The stress-induced behavioral phenotypic changes were similar in both sexes, however, the metabolic profiles of female plasma and brain became substantially different after stress, whereas those of males did not. Four stress-differential plasma metabolites-ß-hydroxybutyric acid (BHB), L-serine, glycerol, and myo-inositol-could yield biomarker panels with excellent performance to discern the stressed individuals only for females. Disturbances in BHB, glucose, 1,5-anhydrosorbitol, lactic acid, and several fatty acids in the plasma of stressed females implied a systemic metabolic shift to ß-oxidation in females. The plasma levels of BHB and corticosterone only in stressed females were observed not only in SCVS but also in an acute stress model. These results collectively suggest a sex difference in the metabolic responses by stress, possibly involving the energy metabolism shift to ß-oxidation and the HPA axis dysregulation in females.

A Randomized Trial of Behavioral Nudges Delivered Through Text Messages to Increase Influenza Vaccination Among Patients With an Upcoming Primary Care Visit.

PURPOSE: To evaluate if nudges delivered by text message prior to an upcoming primary care visit can increase influenza vaccination rates. DESIGN: Randomized, controlled trial. SETTING: Two health systems in the Northeastern US between September 2020 and March 2021. SUBJECTS: 74,811 adults. INTERVENTIONS: Patients in the 19 intervention arms received 1-2 text messages in the 3 days preceding their appointment that varied in their format, interactivity, and content. MEASURES: Influenza vaccination. ANALYSIS: Intention-to-treat. RESULTS: Participants had a mean (SD) age of 50.7 (16.2) years; 55.8% (41,771) were female, 70.6% (52,826) were White, and 19.0% (14,222) were Black. Among the interventions, 5 of 19 (26.3%) had a significantly greater vaccination rate than control. On average, the 19 interventions increased vaccination relative to control by 1.8 percentage points or 6.1% (P = .005). The top performing text message described the vaccine to the patient as "reserved for you" and led to a 3.1 percentage point increase (95% CI, 1.3 to 4.9; P < .001) in vaccination relative to control. Three of the top five performing messages described the vaccine as "reserved for you." None of the interventions performed worse than control. CONCLUSIONS: Text messages encouraging vaccination and delivered prior to an upcoming appointment significantly increased influenza vaccination rates and could be a scalable approach to increase vaccination more broadly.

A megastudy of text-based nudges encouraging patients to get vaccinated at an upcoming doctor's appointment.

Many Americans fail to get life-saving vaccines each year, and the availability of a vaccine for COVID-19 makes the challenge of encouraging vaccination more urgent than ever. We present a large field experiment (N = 47,306) testing 19 nudges delivered to patients via text message and designed to boost adoption of the influenza vaccine. Our findings suggest that text messages sent prior to a primary care visit can boost vaccination rates by an average of 5%. Overall, interventions performed better when they were 1) framed as reminders to get flu shots that were already reserved for the patient and 2) congruent with the sort of communications patients expected to receive from their healthcare provider (i.e., not surprising, casual, or interactive). The best-performing intervention in our study reminded patients twice to get their flu shot at their upcoming doctor's appointment and indicated it was reserved for them. This successful script could be used as a template for campaigns to encourage the adoption of life-saving vaccines, including against COVID-19.

Computational study of estimating 3D trabecular bone microstructure for the volume of interest from CT scan data.

Inspired by the self-optimizing capabilities of bone, a new concept of bone microstructure reconstruction has been recently introduced by using 2D synthetic skeletal images. As a preliminary clinical study, this paper proposes a topology optimization-based method that can estimate 3D trabecular bone microstructure for the volume of interest (VOI) from 3D computed tomography (CT) scan data with enhanced computational efficiency and phenomenological accuracy. For this purpose, a localized finite element (FE) model is constructed by segmenting a target bone from CT scan data and determining the physiological local loads for the VOI. Then, topology optimization is conducted with multiresolution bone mineral density (BMD) deviation constraints to preserve the patient-specific spatial bone distribution obtained from the CT scan data. For the first time, to our knowledge, this study has demonstrated that 60-µm resolution trabecular bone images can be reconstructed from 600-µm resolution CT scan data (a 62-year-old woman with no metabolic bone disorder) for the 4 VOIs in the proximal femur. The reconstructed trabecular bone includes the characteristic trabecular patterns and has morphometric indices that are in good agreement with the anatomical data in the literature. As for computational efficiency, the localization for the VOI reduces the number of FEs by 99%, compared with that of the full FE model. Compared with the previous single-resolution BMD deviation constraint, the proposed multiresolution BMD deviation constraints enable at least 65% and 47% reductions in the number of iterations and computing time, respectively. These results demonstrate the clinical feasibility and potential of the proposed method.

Fully automated segmentation of a hip joint using the patient-specific optimal thresholding and watershed algorithm.

BACKGROUND AND OBJECTIVE: Automated segmentation with high accuracy and speed is a prerequisite for FEA-based quantitative assessment with a large population. However, hip joint segmentation has remained challenging due to a narrow articular cartilage and thin cortical bone with a marked interindividual variance. To overcome this challenge, this paper proposes a fully automated segmentation method for a hip joint that uses the complementary characteristics between the thresholding technique and the watershed algorithm. METHODS: Using the golden section method and load path algorithm, the proposed method first determines the patient-specific optimal threshold value that enables reliably separating a femur from a pelvis while removing cortical and trabecular bone in the femur at the minimum. This provides regional information on the femur. The watershed algorithm is then used to obtain boundary information on the femur. The proximal femur can be extracted by merging the complementary information on a target image. RESULTS: For eight CT images, compared with the manual segmentation and other segmentation methods, the proposed method offers a high accuracy in terms of the dice overlap coefficient (97.24 ± 0.44%) and average surface distance (0.36 ± 0.07 mm) within a fast timeframe in terms of processing time per slice (1.25 ± 0.27 s). The proposed method also delivers structural behavior which is close to that of the manual segmentation with a small mean of average relative errors of the risk factor (4.99%). CONCLUSION: The segmentation results show that, without the aid of a prerequisite dataset and users' manual intervention, the proposed method can segment a hip joint as fast as the simplified Kang (SK)-based automated segmentation, while maintaining the segmentation accuracy at a similar level of the snake-based semi-automated segmentation.

Antidepressant-Induced Sexual Dysfunction among Newer Antidepressants in a Naturalistic Setting.

OBJECTIVE: Antidepressants used to treat depression are frequently associated with sexual dysfunction. Sexual side effects affect the patient's quality of life and, in long-term treatment, can lead to non-compliance and relapse. However, studies covering many antidepressants with differing mechanisms of action were scarce. The present study assessed and compared the incidence of sexual dysfunction among different antidepressants in a naturalistic setting. METHODS: Participants were married patients diagnosed with depression, per DSM-IV diagnostic criteria, who had been taking antidepressants for more than 1 month. We assessed the participants via the Arizona Sexual Experiences Scale (ASEX), Beck Depression Inventory (BDI), and State-Trait Anxiety Inventory (STAI), and assessed their demographic variables, types and dosages of antidepressants, and duration of antidepressant use via their medical records. RESULTS: One hundred and one patients (46 male, 55 female, age 42.2+/-7 years) completed the instruments. Thirteen were taking fluoxetine (mean dose 21.3+/-8.5 mg/day), 24 were taking paroxetine (mean dose 20.4+/-7.2 mg/day), 20 taking citalopram (mean dose 22.1+/-6.5 mg/day), 22, venlafaxine (mean dose 115.7+/-53.2 mg/day) and 22, mirtazapine (mean dose 18+/-8.7 mg/day). Mean ages, sex ratios, and BDI and STAI scores did not differ significantly across antidepressants. A substantial number of participants (46.5%, n=47) experienced sexual dysfunction. The prevalence of sexual dysfunction differed across drugs: citalopram 60% (n=12), venlafaxine 54.5% (n=12), paroxetine 54.2% (n=13), fluoxetine 46.2% (n=6), and mirtazapine 18.2% (n=4). Regression analyses revealed the significant factors for sexual dysfunction were being female, total scores on the BDI and SAI, and type of antidepressant (F=4.92, p<0.0001). Of the antidepressants, the mirtarzapine group's total ASEX score was significantly lower than the scores of the citalopram, fluoxetine, and paroxetine groups. CONCLUSION: The incidence of sexual dysfunction was substantially high during antidepressant treatment. The incidence of sexual dysfunction differed among antidepressants having different mechanisms of action. Our study suggests the need for clinicians to consider the impact of pharmacotherapy on patients' sexual functioning in the course of treatment with antidepressants.