Design and Development of a Multimodal Digital Intervention (SHIFT App) to Address Sexual Dysfunction in Hematopoietic Stem Cell Transplant (HSCT) Survivors.

Hematopoietic stem cell transplant (HSCT) survivors frequently experience persistent sexual dysfunction, which is associated with impaired quality of life and increased psychological distress. The lack of availability of clinicians with expertise in sexual health limits the capacity to address sexual health concerns in HSCT survivors. Digital health applications may offer a patient-centered and scalable solution to address sexual health concerns in cancer survivors. The objective of this report is to delineate the iterative process of adapting an in-person sexual health intervention into a self-administered digital application called "Sexual Health and Intimacy Following Transplant (SHIFT)" and the refinement of SHIFT using stakeholder feedback. We used a five-step development model to adapt SHIFT that included: (1) implementation of a multimodal bio-psycho-social conceptual framework, (2) development of a comprehensive intervention manual and SHIFT content, (3) translation of the intervention manual into an interactive storyline with a focus on enhancing patient engagement, (4) creation of initial SHIFT wireframes, and (5) refinement of SHIFT through iterative alpha and beta testing. At each step, key stakeholders including HSCT survivors, HSCT clinicians, and experts in sexual health, psychology, and digital health provided iterative feedback. We adapted SHIFT based on our conceptual framework, prior in-person intervention work, and iterative stakeholder feedback in each application development stage. SHIFT incorporates medical information, educational materials, intimacy exercises, and activities to address the multiple etiologies of sexual health concerns in HSCT survivors. SHIFT includes strategies to enhance engagement including gamification, personalization, and incorporation of video from HSCT survivors and clinicians. Based on stakeholder feedback, SHIFT was refined with a focus on inclusivity of gender, sexual orientation, relationship status, and body image concerns. SHIFT is novel, patient-centered digital application to address sexual dysfunction in HSCT survivors. Iterative feedback from key stakeholders including HSCT survivors guided SHIFT adaptation and refinement, to optimize patient engagement and ensure inclusivity. The final prototype of SHIFT was initially acceptable to key stakeholders and is now under further testing in a pilot randomized trial to assess its feasibility and preliminary efficacy for improving sexual health outcomes in HSCT survivors.

Multimodal deep learning methods enhance genomic prediction of wheat breeding.

While several statistical machine learning methods have been developed and studied for assessing the genomic prediction (GP) accuracy of unobserved phenotypes in plant breeding research, few methods have linked genomics and phenomics (imaging). Deep learning (DL) neural networks have been developed to increase the GP accuracy of unobserved phenotypes while simultaneously accounting for the complexity of genotype-environment interaction (GE); however, unlike conventional GP models, DL has not been investigated for when genomics is linked with phenomics. In this study we used 2 wheat data sets (DS1 and DS2) to compare a novel DL method with conventional GP models. Models fitted for DS1 were GBLUP, gradient boosting machine (GBM), support vector regression (SVR) and the DL method. Results indicated that for 1 year, DL provided better GP accuracy than results obtained by the other models. However, GP accuracy obtained for other years indicated that the GBLUP model was slightly superior to the DL. DS2 is comprised only of genomic data from wheat lines tested for 3 years, 2 environments (drought and irrigated) and 2-4 traits. DS2 results showed that when predicting the irrigated environment with the drought environment, DL had higher accuracy than the GBLUP model in all analyzed traits and years. When predicting drought environment with information on the irrigated environment, the DL model and GBLUP model had similar accuracy. The DL method used in this study is novel and presents a strong degree of generalization as several modules can potentially be incorporated and concatenated to produce an output for a multi-input data structure.

Supportive oncology care at home interventions: protocols for clinical trials to shift the paradigm of care for patients with cancer.

BACKGROUND: Patients with cancer often endure substantial symptoms and treatment toxicities leading to high healthcare utilization, including hospitalizations and emergency department visits, throughout the continuum of their illness. Innovative oncology care models are needed to improve patient outcomes and reduce their healthcare utilization. Using a novel hospital at home care platform, we developed a Supportive Oncology Care at Home intervention to address the needs of patients with cancer. METHODS: We are conducting three trials to delineate the role of Supportive Oncology Care at Home for patients with cancer. The Supportive Oncology Care at Home intervention includes: (1) a hospital at home care model for symptom assessment and management; (2) remote monitoring of daily patient-reported symptoms, vital signs, and body weight; and (3) structured communication with the oncology team. Our first study is a randomized controlled trial to test the efficacy of Supportive Oncology Care at Home versus standard oncology care for improving healthcare utilization, cancer treatment interruptions, and patient-reported outcomes in patients with cancer receiving definitive treatment of their cancer. Participants include adult patients with gastrointestinal and head and neck cancer, as well as lymphoma, receiving definitive treatment (e.g., treatment with curative intent). The second study is a single-arm trial assessing the feasibility and acceptability of the Supportive Oncology Care at Home intervention for hospitalized patients with advanced cancer. Eligible participants include adult patients with incurable cancer who are admitted with an unplanned hospitalization. The third study is a single-arm trial assessing the feasibility and acceptability of the Supportive Oncology Care at Home intervention to enhance the end-of-life care for patients with advanced hematologic malignancies. Eligible participants include adult patients with relapsed or refractory hematologic malignancy receiving palliative therapy or supportive care alone. DISCUSSION: These studies are approved by the Dana-Farber/Harvard Cancer Center Institutional Review Board and are being conducted in accordance with the Consolidated Standards of Reporting Trials statement for non-pharmacological trials. This work has the potential to transform the paradigm of care for patients with cancer by providing them with the necessary support at home to improve their health outcomes and care delivery. TRIAL REGISTRATIONS: NCT04544046, NCT04637035, NCT04690205.

Healthcare Utilization and End-of-Life Outcomes in Patients Receiving CAR T-Cell Therapy.

BACKGROUND: CAR T-cell therapy has revolutionized the treatment of patients with hematologic malignancies, but it can result in prolonged hospitalizations and serious toxicities. However, data on the impact of CAR T-cell therapy on healthcare utilization and end-of-life (EoL) outcomes are lacking. METHODS: We conducted a retrospective analysis of 236 patients who received CAR T-cell therapy at 2 tertiary care centers from February 2016 through December 2019. We abstracted healthcare utilization and EoL outcomes from the electronic health record, including hospitalizations, receipt of ICU care, hospitalization and receipt of systemic therapy in the last 30 days of life, palliative care, and hospice referrals. RESULTS: Most patients (81.4%; n=192) received axicabtagene ciloleucel. Overall, 28.1% of patients experienced a hospital readmission and 15.5% required admission to the ICU within 3 months of CAR T-cell therapy. Among the deceased cohort, 58.3% (49/84) were hospitalized and 32.5% (26/80) received systemic therapy in the last 30 days of life. Rates of palliative care and hospice referrals were 47.6% and 30.9%, respectively. In multivariable logistic regression, receipt of bridging therapy (odds ratio [OR], 3.15; P=.041), index CAR-T hospitalization length of stay >14 days (OR, 4.76; P=.009), hospital admission within 3 months of CAR T-cell infusion (OR, 4.29; P=.013), and indolent lymphoma transformed to diffuse large B-cell lymphoma (OR, 9.83; P=.012) were associated with likelihood of hospitalization in the last 30 days of life. CONCLUSIONS: A substantial minority of patients receiving CAR T-cell therapy experienced hospital readmission or ICU utilization in the first 3 months after CAR T-cell therapy, and most deceased recipients of CAR T-cell therapy received intensive EoL care. These findings underscore the need for interventions to optimize healthcare delivery and EoL care for this population.

Genome-Wide Association Study Reveals Genomic Regions Associated With Ten Agronomical Traits in Wheat Under Late-Sown Conditions.

Poor understanding of the genetic and molecular basis of heat tolerance component traits is a major bottleneck in designing heat tolerant wheat cultivars. The impact of terminal heat stress is generally reported in the case of late sown wheat. In this study, our aim was to identify genomic regions for various agronomic traits under late sown conditions by using genome-wide association approach. An association mapping panel of 205 wheat accessions was evaluated under late sown conditions at three different locations in India. Genotyping of the association panel revealed 15,886 SNPs, out of which 11,911 SNPs with exact physical locations on the wheat reference genome were used in association analysis. A total of 69 QTLs (10 significantly associated and 59 suggestive) were identified for ten different traits including productive tiller number (17), grain yield (14), plant height (12), grain filling rate (6), grain filling duration (5), days to physiological maturity (4), grain number (3), thousand grain weight (3), harvest index (3), and biomass (2). Out of these associated QTLs, 17 were novel for traits, namely PTL (3), GY (2), GFR (6), HI (3) and GNM (3). Moreover, five consistent QTLs across environments were identified for GY (4) and TGW (1). Also, 11 multi-trait SNPs and three hot spot regions on Chr1Ds, Chr2BS, Chr2DS harboring many QTLs for many traits were identified. In addition, identification of heat tolerant germplasm lines based on favorable alleles HD2888, IC611071, IC611273, IC75240, IC321906, IC416188, and J31-170 would facilitate their targeted introgression into popular wheat cultivars. The significantly associated QTLs identified in the present study can be further validated to identify robust markers for utilization in marker-assisted selection (MAS) for development of heat tolerant wheat cultivars.

High-throughput phenotyping for crop improvement in the genomics era.

Tremendous progress has been made with continually expanding genomics technologies to unravel and understand crop genomes. However, the impact of genomics data on crop improvement is still far from satisfactory, in large part due to a lack of effective phenotypic data; our capacity to collect useful high quality phenotypic data lags behind the current capacity to generate high-throughput genomics data. Thus, the research bottleneck in plant sciences is shifting from genotyping to phenotyping. This article review the current status of efforts made in the last decade to systematically collect phenotypic data to alleviate this 'phenomics bottlenecks' by recording trait data through sophisticated non-invasive imaging, spectroscopy, image analysis, robotics, high-performance computing facilities and phenomics databases. These modern phenomics platforms and tools aim to record data on traits like plant development, architecture, plant photosynthesis, growth or biomass productivity, on hundreds to thousands of plants in a single day, as a phenomics revolution. It is believed that this revolution will provide plant scientists with the knowledge and tools necessary for unlocking information coded in plant genomes. Efforts have been also made to present the advances made in the last 10 years in phenomics platforms and their use in generating phenotypic data on different traits in several major crops including rice, wheat, barley, and maize. The article also highlights the need for phenomics databases and phenotypic data sharing for crop improvement. The phenomics data generated has been used to identify genes/QTL through QTL mapping, association mapping and genome-wide association studies (GWAS) for genomics-assisted breeding (GAB) for crop improvement.

Regular physical activity and risk of atrial fibrillation: a systematic review and meta-analysis.

BACKGROUND: Although previous studies have suggested that competitive athletes have a higher risk of atrial fibrillation than the general population, limited and inconsistent data are available on the association between regular physical activity and the risk of atrial fibrillation. METHODS AND RESULTS: A systematic, comprehensive literature search was performed using MEDLINE, EMBASE, and COCHRANE until 2011. Extracted data from the eligible studies were meta-analyzed using fixed effects model. Four studies, which included 95 526 subjects, were eligible for meta-analysis. For all of the studies included, the extreme groups (ie, maximum versus minimal amount of physical activity) were used for the current analyses. The total number of participants belonging to the extreme groups was 43 672. The pooled odds ratio (95% confidence interval) for atrial fibrillation among regular exercisers was 1.08 (0.97-1.21). CONCLUSIONS: Our data do not support a statistically significant association between regular physical activity and increased incidence of atrial fibrillation.

3-d volumetric evaluation of human mandibular growth.

Bone growth is a complex process that is controlled by a multitude of mechanisms that are not fully understood.Most of the current methods employed to measure the growth of bones focus on either studying cadaveric bones from different individuals of different ages, or successive two-dimensional (2D) radiographs. Both techniques have their known limitations. The purpose of this study was to explore a technique for quantifying the three dimensional (3D) growth of an adolescent human mandible over the period of one year utilizing cone beam computed tomography (CBCT) scans taken for regular orthodontic records. Three -dimensional virtual models were created from the CBCT data using mainstream medical imaging software. A comparison between computer-generated surface meshes of successive 3-D virtual models illustrates the magnitude of relative mandible growth. The results of this work are in agreement with previously reported data from human cadaveric studies and implantable marker studies. The presented method provides a new relatively simple basis (utilizing commercially available software) to visualize and evaluate individualized 3D (mandibular) growth in vivo.

Cardiovascular outcomes in the AFFIRM Trial (Atrial Fibrillation Follow-Up Investigation of Rhythm Management). An assessment of individual antiarrhythmic drug therapies compared with rate control with propensity score-matched analyses.

OBJECTIVES: The impact of individual antiarrhythmic drugs (AADs) on mortality and hospital stay in atrial fibrillation (AF) was evaluated. BACKGROUND: Cardiovascular (CV) outcomes in AF patients receiving pharmacologic rhythm control therapy have not been compared with rate control therapy on the basis of AAD selection. METHODS: We compared CV outcomes in the AFFIRM (Atrial Fibrillation Follow-Up Investigation of Rhythm Management) trial in subgroups defined by the initial AAD selected with propensity score matched subgroups from the rate arm (Rate). RESULTS: Seven hundred twenty-nine amiodarone patients, 606 sotalol patients, and 268 Class 1C patients were matched. The composite outcome of mortality or cardiovascular hospital stays (CVH) showed better outcomes with Rate compared with amiodarone (hazard ratio [HR]: 1.18, 95% confidence interval [CI]: 1.03 to 1.36, p = 0.02), sotalol (HR: 1.32, 95% CI: 1.13 to 1.54, p < 0.001), and Class 1C (HR: 1.22, 95% CI: 0.97 to 1.56, p = 0.10). There was a nonsignificant increase in mortality with amiodarone (HR: 1.20, 95% CI: 0.94 to 1.53, p = 0.15) with the risk of non-CV death being significantly higher with amiodarone versus Rate (HR: 1.11, 95% CI: 1.01 to 1.24, p = 0.04). First CVH event rates at 3 years were 47% for amiodarone, 50% for sotalol, and 44% for Class 1C versus 40%, 40%, and 36%, respectively, for Rate (amiodarone HR: 1.20, 95% CI: 1.03 to 1.40, p = 0.02, sotalol HR: 1.364, 95% CI: 1.16 to 1.611, p < 0.001, Class 1C HR: 1.24, 95% CI: 0.96 to 1.60, p = 0.09). Time to CVH with intensive care unit stay or death was shorter with amiodarone (HR: 1.22, 95% CI: 1.02 to 1.46, p = 0.03). CONCLUSIONS: In AFFIRM, composite mortality and CVH outcomes differed for Rate and AADs due to differences in CVH; CVH event rates during follow-up were high for all cohorts, but they were higher for all groups on AADs. Death, intensive care unit hospital stay, and non-CV death were more frequent with amiodarone.

Biomechanical analysis of proximal humeral fixation using locking plate fixation with an intramedullary fibular allograft.

BACKGROUND: Loss of locking plate fixation has been reported in proximal humeral fractures, particularly in older patients with poor bone density. In such fractures, the medial support between the humeral head and shaft is occasionally missing, resulting in varus collapse of the construct. A biomechanical study was performed to understand the behaviour of the interface of these fractures fixed with a locking plate fixation with and without augmentation. The augmentation consisted of an intramedullary fibular allograft (bone peg) that has been reported for use in these fractures. METHODS: Six embalmed pairs of specimens were utilized; each pair of specimens had one humerus repaired with the locking plate fixation, and the other humerus repaired with the plate fixation and bone peg. The constructs were tested in bending to determine the relative movement between the humeral head and the shaft under bending loads, and the failure loads of both constructs. Digital Imaging Correlation was used to determine the relative movement. FINDINGS: The bone peg increased the failure load of the constructs by 1.72 (SD 0.54) times (P=0.02). The relative movement was measured by comparing the initial stiffness of both constructs. Initial stiffness of the construct was increased 3.84 (SD 1.92) times (P=0.005) with the use of the bone peg. INTERPRETATION: The intramedullary bone peg significantly decreases the relative movement at the interface. Further studies are needed to accurately determine the effect this reduction has on the healing process, and overall clinical result.