At Risk? Exploring the relationship between HIV-related knowledge and risky behavior in young females in Jamaica.

Young females are at three times higher risk of contracting HIV than their male counterparts in Jamaica. Using Jamaica’s 2004 Knowledge, Attitudes, Behaviour and Practices survey, this research investigates factors contributing to HIV/AIDS-related risky behaviors of young females. Risk perception as a function of knowledge and as an influence on behavior is also examined. The findings reveal that only older females, 25 to 49 years, practice safer behaviors in response to increased knowledge. This highlights the disjunction between knowledge and behavior, emphasizing the need for a holistic approach to addressing the social context within which adolescents are put at risk

Targeting the Mechanisms of Resistance to Chemotherapy and Radiotherapy with the Cancer Stem Cell Hypothesis

Despite advances in treatment, cancer remains the 2nd most common cause of death in the United States. Poor cure rates may result from the ability of cancer to recur and spread after initial therapies have seemingly eliminated detectable signs of disease. A growing body of evidence supports a role for cancer stem cells (CSCs) in tumor regrowth and spread after initial treatment. Thus, targeting CSCs in combination with traditional induction therapies may improve treatment outcomes and survival rates. Unfortunately, CSCs tend to be resistant to chemo- and radiation therapy, and a better understanding of the mechanisms underlying CSC resistance to treatment is necessary. This paper provides an update on evidence that supports a fundamental role for CSCs in cancer progression, summarizes potential mechanisms of CSC resistance to treatment, and discusses classes of drugs currently in preclinical or clinical testing that show promise at targeting CSCs

Sacrificial crystal templating of hyaluronic acid-based hydrogels

Natural tissues have intricate structures organized in a hierarchical fashion over multiple length scales (Å to cm). These tissues commonly incorporate pores as a key feature that may regulate cell behavior. To enable the development of tissues scaffolds with biomimetic pore structures, it is important to investigate methods to impart pores to biomaterials, such as the use of novel sacrificial porogens. Here we report the use of sacrificial crystals to impart pores to biopolymer hydrogels (based on a methacrylated hyaluronic acid derivative) with macroscopic crystal templated pores embedded within them. The pore structure was investigated using microscopy (cryoSEM and confocal), and the specific sacrificial porogen used was found not only to impact the pore structure, but also swelling and mechanical properties. Such templated hydrogels have prospects for application as instructive tissue scaffolds (where the pore structure controls cell alignment, migration, etc.)

Systems Analysis Implicates WAVE2 Complex in the Pathogenesis of Developmental Left-Sided Obstructive Heart Defects.

Genetic variants are the primary driver of congenital heart disease (CHD) pathogenesis. However, our ability to identify causative variants is limited. To identify causal CHD genes that are associated with specific molecular functions, the study used prior knowledge to filter de novo variants from 2,881 probands with sporadic severe CHD. This approach enabled the authors to identify an association between left ventricular outflow tract obstruction lesions and genes associated with the WAVE2 complex and regulation of small GTPase-mediated signal transduction. Using CRISPR zebrafish knockdowns, the study confirmed that WAVE2 complex proteins brk1, nckap1, and wasf2 and the regulators of small GTPase signaling cul3a and racgap1 are critical to cardiac development

EM-mosaic detects mosaic point mutations that contribute to congenital heart disease.

BackgroundThe contribution of somatic mosaicism, or genetic mutations arising after oocyte fertilization, to congenital heart disease (CHD) is not well understood. Further, the relationship between mosaicism in blood and cardiovascular tissue has not been determined.MethodsWe developed a new computational method, EM-mosaic (Expectation-Maximization-based detection of mosaicism), to analyze mosaicism in exome sequences derived primarily from blood DNA of 2530 CHD proband-parent trios. To optimize this method, we measured mosaic detection power as a function of sequencing depth. In parallel, we analyzed our cohort using MosaicHunter, a Bayesian genotyping algorithm-based mosaic detection tool, and compared the two methods. The accuracy of these mosaic variant detection algorithms was assessed using an independent resequencing method. We then applied both methods to detect mosaicism in cardiac tissue-derived exome sequences of 66 participants for which matched blood and heart tissue was available.ResultsEM-mosaic detected 326 mosaic mutations in blood and/or cardiac tissue DNA. Of the 309 detected in blood DNA, 85/97 (88%) tested were independently confirmed, while 7/17 (41%) candidates of 17 detected in cardiac tissue were confirmed. MosaicHunter detected an additional 64 mosaics, of which 23/46 (50%) among 58 candidates from blood and 4/6 (67%) of 6 candidates from cardiac tissue confirmed. Twenty-five mosaic variants altered CHD-risk genes, affecting 1% of our cohort. Of these 25, 22/22 candidates tested were confirmed. Variants predicted as damaging had higher variant allele fraction than benign variants, suggesting a role in CHD. The estimated true frequency of mosaic variants above 10% mosaicism was 0.14/person in blood and 0.21/person in cardiac tissue. Analysis of 66 individuals with matched cardiac tissue available revealed both tissue-specific and shared mosaicism, with shared mosaics generally having higher allele fraction.ConclusionsWe estimate that ~ 1% of CHD probands have a mosaic variant detectable in blood that could contribute to cardiac malformations, particularly those damaging variants with relatively higher allele fraction. Although blood is a readily available DNA source, cardiac tissues analyzed contributed ~ 5% of somatic mosaic variants identified, indicating the value of tissue mosaicism analyses

Deep Learning-Based Dose Prediction To Improve the Plan Quality of Volumetric Modulated Arc Therapy for Gynecologic Cancers

Background: In recent years, deep‐learning models have been used to predict entire three‐dimensional dose distributions. However, the usability of dose predictions to improve plan quality should be further investigated. Purpose: To develop a deep‐learning model to predict high‐quality dose distributions for volumetric modulated arc therapy (VMAT) plans for patients with gynecologic cancer and to evaluate their usability in driving plan quality improvements. Methods: A total of 79 VMAT plans for the female pelvis were used to train (47 plans), validate (16 plans), and test (16 plans) 3D dense dilated U‐Net models to predict 3D dose distributions. The models received the normalized CT scan, dose prescription, and target and normal tissue contours as inputs. Three models were used to predict the dose distributions for plans in the test set. A radiation oncologist specializing in the treatment of gynecologic cancers scored the test set predictions using a 5‐point scale (5, acceptable as‐is; 4, prefer minor edits; 3, minor edits needed; 2, major edits needed; and 1, unacceptable). The clinical plans for which the dose predictions indicated that improvements could be made were reoptimized with constraints extracted from the predictions. Results: The predicted dose distributions in the test set were of comparable quality to the clinical plans. The mean voxel‐wise dose difference was −0.14 ± 0.46 Gy. The percentage dose differences in the predicted target metrics of D1% and D98% were −1.05% ± 0.59% and 0.21% ± 0.28%, respectively. The dose differences in the predicted organ at risk mean and maximum doses were −0.30 ± 1.66 Gy and −0.42 ± 2.07 Gy, respectively. A radiation oncologist deemed all of the predicted dose distributions clinically acceptable; 12 received a score of 5, and four received a score of 4. Replanning of flagged plans (five plans) showed that the original plans could be further optimized to give dose distributions close to the predicted dose distributions. Conclusions: Deep‐learning dose prediction can be used to predict high‐quality and clinically acceptable dose distributions for VMAT female pelvis plans, which can then be used to identify plans that can be improved with additional optimization

Evaluation of a novel rash scale and a serum proteomic predictor in a randomized phase II trial of sequential or concurrent cetuximab and pemetrexed in previously treated non-small cell lung cancer

BACKGROUND: Candidate predictive biomarkers for epidermal growth factor receptor inhibitors (EGFRi), skin rash and serum proteomic assays, require further qualification to improve EGFRi therapy in non-small cell lung cancer (NSCLC). In a phase II trial that was closed to accrual because of changes in clinical practice we examined the relationships among candidate biomarkers, quantitative changes in tumor size, progression-free and overall survival. METHODS: 55 patients with progressive NSCLC after platinum therapy were randomized to receive (Arm A) cetuximab, followed by pemetrexed at progression, or (Arm B) concurrent cetuximab and pemetrexed. All received cetuximab monotherapy for the first 14 days. Pre-treatment serum and weekly rash assessments by standard and EGFRi-induced rash (EIR) scales were collected. RESULTS: 43 patients (20-Arm A, 23-Arm B) completed the 14-day run-in. Median survival was 9.1 months. Arm B had better median overall (Arm B = 10.3 [95% CI 7.5, 16.8]; Arm A = 3.5 [2.8, 11.7] months P = 0.046) and progression-free survival (Arm B = 2.3 [1.6, 3.1]; Arm A = 1.6 [0.9, 1.9] months P = 0.11). The EIR scale distributed ratings among 6 rather than 3 categories but ordinal scale rash severity did not predict outcomes. The serum proteomic classifier and absence of rash after 21 days of cetuximab did. CONCLUSIONS: Absence of rash after 21 days of cetuximab therapy and the serum proteomic classifier, but not ordinal rash severity, were associated with NSCLC outcomes. Although in a small study, these observations were consistent with results from larger retrospective analyses. TRIAL REGISTRATION: Clinicaltrials.gov Identifier NCT0020393

Factors associated with compliance with the recommended frequency of postnatal care services in three rural districts of Tanzania

Background High neonatal mortality persists in Tanzania. Rates of decline are slow, in part because postnatal care (PNC) services for addressing this problem remain severely underutilized. This study assesses factors associated with utilization of PNC among mothers in rural Tanzania. Methods This study analyzed household survey data collected in 2011 to understand health service utilization patterns among women of reproductive age and children less than 5 years of age in the Rufiji, Kilombero, and Ulanga districts of Tanzania. A total of 889 mothers were eligible for the current analysis. Multinomial logistic regression was used to determine factors associated with the likelihood of mothers seeking the WHO recommended PNC visits. Results The percent of newborns and their mothers with full PNC was low (10.4 %). Factors explaining PNC completion were district of residence, ethnic group, pregnancy wantedness, ANC attendance, place of delivery, and any incidence of newborn. Mothers of unwanted pregnancies were less likely to attend PNC services compared to mothers of wanted pregnancies [for at least two PNC: aRRR = 0.57, 95 % CI 0.35–0.94]. Sick newborns were more likely to receive PNC than newborns who were not sick during the first month after childbirth [for at least two PNC, aRRR = 3.52, 95 % CI 2.12–5.86]. Mothers who attended ANC services more frequently were more likely to receive PNC services compared to those who had attended fewer than 2 ANC services [for 1 PNC, aRRR = 1.89, 95 % CI 1.23–2.90]. Mothers who delivered at a health facility were less likely to attend PNC services compared to mothers who delivered outside a facility [for at least 2 PNC: aRRR = 0.42, 95 % CI 0.26–0.76]. Model with interactions between ANC attendance and place of delivery shown that only ANC attendance had a positive and statistically significant effect on PNC visit. Conclusion To achieve the WHO recommended number of PNC in rural Tanzania, our findings suggest the need to provide PNC through the community-based primary health care. Efforts to improve coverage of PNC should include expanding health education and counseling during childbirth and neonatal period to more effectively advocate PNC for newborns perceived to be healthy

Dysregulated protocadherin-pathway activity as an intrinsic defect in induced pluripotent stem cell-derived cortical interneurons from subjects with schizophrenia.

We generated cortical interneurons (cINs) from induced pluripotent stem cells derived from 14 healthy controls and 14 subjects with schizophrenia. Both healthy control cINs and schizophrenia cINs were authentic, fired spontaneously, received functional excitatory inputs from host neurons, and induced GABA-mediated inhibition in host neurons in vivo. However, schizophrenia cINs had dysregulated expression of protocadherin genes, which lie within documented schizophrenia loci. Mice lacking protocadherin-α showed defective arborization and synaptic density of prefrontal cortex cINs and behavioral abnormalities. Schizophrenia cINs similarly showed defects in synaptic density and arborization that were reversed by inhibitors of protein kinase C, a downstream kinase in the protocadherin pathway. These findings reveal an intrinsic abnormality in schizophrenia cINs in the absence of any circuit-driven pathology. They also demonstrate the utility of homogenous and functional populations of a relevant neuronal subtype for probing pathogenesis mechanisms during development

Automatic End-To-End VMAT Treatment Planning for Rectal Cancers

BACKGROUND: The treatment planning process from segmentation to producing a deliverable plan is time-consuming and labor-intensive. Existing solutions automate the segmentation and planning processes individually. The feasibility of combining auto-segmentation and auto-planning for volumetric modulated arc therapy (VMAT) for rectal cancers in an end-to-end process is not clear. PURPOSE: To create and clinically evaluate a complete end-to-end process for auto-segmentation and auto-planning of VMAT for rectal cancer requiring only the gross tumor volume contour and a CT scan as inputs. METHODS: Patient scans and data were retrospectively selected from our institutional records for patients treated for malignant neoplasm of the rectum. We trained, validated, and tested deep learning auto-segmentation models using nnU-Net architecture for clinical target volume (CTV), bowel bag, large bowel, small bowel, total bowel, femurs, bladder, bone marrow, and female and male genitalia. For the CTV, we identified 174 patients with clinically drawn CTVs. We used data for 18 patients for all structures other than the CTV. The structures were contoured under the guidance of and reviewed by a gastrointestinal (GI) radiation oncologist. The predicted results for CTV in 35 patients and organs at risk (OAR) in six patients were scored by the GI radiation oncologist using a five-point Likert scale. For auto-planning, a RapidPlan knowledge-based planning solution was modeled for VMAT delivery with a prescription of 25 Gy in five fractions. The model was trained and tested on 20 and 34 patients, respectively. The resulting plans were scored by two GI radiation oncologists using a five-point Likert scale. Finally, the end-to-end pipeline was evaluated on 16 patients, and the resulting plans were scored by two GI radiation oncologists. RESULTS: In 31 of 35 patients, CTV contours were clinically acceptable without necessary modifications. The CTV achieved a Dice similarity coefficient of 0.85 (±0.05) and 95% Hausdorff distance of 15.25 (±5.59) mm. All OAR contours were clinically acceptable without edits, except for large and small bowel which were challenging to differentiate. However, contours for total, large, and small bowel were clinically acceptable. The two physicians accepted 100% and 91% of the auto-plans. For the end-to-end pipeline, the two physicians accepted 88% and 62% of the auto-plans. CONCLUSIONS: This study demonstrated that the VMAT treatment planning technique for rectal cancer can be automated to generate clinically acceptable and safe plans with minimal human interventions