Testamentary Freedom Vs. the Natural Right to Inherit: The Misuse of No-Contest Clauses As Disinheritance Devices

Testamentary freedom is the bedrock of inheritance law. The freedom is curbed in some respects in order to allow spouses and other groups access to an estate. However, there is no restriction on a parent\u27s ability to disinherit their children. This note is a critique of the permitted disinheritance of children in the name of testamentary freedom. According to John Locke, the right to inherit emanates from natural law and should be recognized as such. Through forced heirship, as recognized in other modern nations, the U.S. can respect the natural right of children to inherit and leave room for testamentary freedom. Forced heirship can alleviate the unjustifiable harms imposed on adult children and preserve familial relationships after the death of a parent. Until forced heirship is recognized, disinherited beneficiaries seeking access to an estate must navigate around laws governing no-contest clauses, devices that are often used to disinherit children. In California, that path is through its probable cause exception to no-contest clauses and the intentional interference with an expected inheritance tort. Until forced heirship is recognized, courts should not permit no-contest clauses to effectuate disinheritance but restrict enforcement of no-contest clauses for protecting estates from complicated ownership disputes and outsiders attempting to gain access to an estate

The availability of local aerial photography in southern California

Some of the major photography and photogrammetric suppliers and users located in Southern California are listed. Recent trends in aerial photographic coverage of the Los Angeles basin area are also noted, as well as the uses of that imagery

Effects of Shading on Post-fire Seedlings of Laurel Sumac (Malosma laurina) in the Santa Monica Mountains

The interactions between post-fire plants is crucial directly after fire. A recent fire on Pepperdine campus allowed for a study to be performed on these interactions. The dominant chapparal plant, Malosma lauraina, laural sumac, both re-sprouts and grows from seeds after fire. Marah Macrocarpus, wild cucumber, grows rapidly after rain following a fire. Some M. lauraina seedlings end up under the M. Macrocarpus yet survive. This study aimed to find differences between those seedlings interacting with M. Macrocarpus and those that are not. Three groups of specimen were used. One control group grew in the sun, one control group in the shade of M. Macrocarpus, and one experimental group that began growing in the shade but was then exposed to sunlight when the wild cucumber was removed. The data showed that none of the groups had a significant difference in growth rate but did show a significant difference in height. The light levels varied across all groups except the experimental and control shade groups. Although there were significant differences in stomatal conductance between the experimental and control groups, there was no significant difference when conditions for the experimental was changed, nor was there a significant difference between the two control groups

Moving from Forecast to Prediction: How Honors Programs Can Use Easily Accessible Predictive Analytics to Improve Enrollment Management

Most enrollment management systems today use historical data to build rough forecasts of what percentage of students will likely accept an offer of enrollment based on historical acceptance rates. While this aggregate forecast method has its uses, we propose that building an enrollment model based on predicting an individual’s likelihood of matriculation can be much more beneficial to an honors director than a historical aggregate forecast. Many complex predictive analytics techniques and specialized software can build such models, but here we show that a basic approach can also be easily accessible to honors directors where a small amount of data collection and basic spreadsheet software allow them to capture most of the benefits without needing the skills of a data scientist. The first step comes in understanding the difference between a forecast and a prediction. A forecast is an estimate of a future event, generally in aggregate form. For example, today I might forecast that our ice cream store will likely sell 1,000 scoops of ice cream based on weather, time of year, day of the week, and regional events—all useful information for staffing and inventory management as well as profitability analysis. Historically, an honors administrator might use this approach to predict the total number of students matriculating to the university or to an individual program. However, with predictive analytics one can acquire even more detail that could be useful in a setting like an honors program where not just the total number of “customers” matter but which ones will create a well-rounded, diverse honors program with students from multiple backgrounds (Siegel). In the ice cream case, a predictive analytics example might predict not just how many total ice cream scoops might be sold but how likely each individual is to buy ice cream. Deeper analysis might predict the type of ice cream, time of day customers might come, and how frequently they might visit the store. Predictive analytics might also lead to prescriptive analytics, where you learn what might be done to persuade someone who was not planning to buy ice cream to do so, e.g., what it might take to change a consumer’s mind so that she will buy ice cream today or how we can we get her to buy two scoops instead of one or to bring a friend. This type of predictive and prescriptive analytics has helped many organizations improve their efficiency and effectiveness (Siegel), and we believe that honors directors can also use it. In this approach, each potential honors student would receive an individualized probability score reflecting his or her likelihood of accepting an offer of admission. This score could still be aggregated into a direct forecast of how many students would likely attend, but it would also show the likelihood that any individual student would attend. The scores could predict how many from a certain group (e.g., science majors or Hispanic students) are likely to attend. This information could help strategically determine scholarship offers as well as the staff’s time commitments to recruitment and follow-up activities

Aluminum Tolerance QTL in Diploid Alfalfa

Aluminum (Al) toxicity associated with acid soils greatly inhibits alfalfa (Medicago sativa L.) productivity throughout much of the world’s major grassland areas. In this paper, we report the identification of quantitative trait loci (QTL) controlling aluminum tolerance in diploid alfalfa (Medicago sativa L). An in vitro callus growth bioassay was used to select aluminum tolerant and aluminum sensitive parents, and to screen an F2 population for aluminum tolerance. Fifty-eight cDNA probes were mapped to nine linkage groups, and the F2 genotypic classes were contrasted with means from the callus growth bioassay using ANOVA. We also used Mapmaker-QTL to identify markers associated with aluminum tolerance. Four markers, UGAc044, UGAc053, UGAc141, and UGAc782, were found to be associated with aluminum tolerance. UGAc044 had the greatest effect, accounting for 15% (LOD 2.3) of the variation in aluminum tolerance

Synergistic drug combinations from electronic health records and gene expression.

ObjectiveUsing electronic health records (EHRs) and biomolecular data, we sought to discover drug pairs with synergistic repurposing potential. EHRs provide real-world treatment and outcome patterns, while complementary biomolecular data, including disease-specific gene expression and drug-protein interactions, provide mechanistic understanding.MethodWe applied Group Lasso INTERaction NETwork (glinternet), an overlap group lasso penalty on a logistic regression model, with pairwise interactions to identify variables and interacting drug pairs associated with reduced 5-year mortality using EHRs of 9945 breast cancer patients. We identified differentially expressed genes from 14 case-control human breast cancer gene expression datasets and integrated them with drug-protein networks. Drugs in the network were scored according to their association with breast cancer individually or in pairs. Lastly, we determined whether synergistic drug pairs found in the EHRs were enriched among synergistic drug pairs from gene-expression data using a method similar to gene set enrichment analysis.ResultsFrom EHRs, we discovered 3 drug-class pairs associated with lower mortality: anti-inflammatories and hormone antagonists, anti-inflammatories and lipid modifiers, and lipid modifiers and obstructive airway drugs. The first 2 pairs were also enriched among pairs discovered using gene expression data and are supported by molecular interactions in drug-protein networks and preclinical and epidemiologic evidence.ConclusionsThis is a proof-of-concept study demonstrating that a combination of complementary data sources, such as EHRs and gene expression, can corroborate discoveries and provide mechanistic insight into drug synergism for repurposing

Altered Expression of Telomere-Associated Genes in Leukocytes among BRCA1 and BRCA2 Carriers

Telomere dysfunction resulting from telomere shortening and deregulation of shelterin components has been linked to the pathogenesis of age-related disorders, including cancer. Recent evidence suggests that BRCA1/2 (BRCA1 and BRCA2) tumor suppressor gene products play an important role in telomere maintenance. Although telomere shortening has been reported in BRCA1/2 carriers, the direct effects of BRCA1/2 haploinsufficiency on telomere maintenance and predisposition to cancer development are not completely understood. In this study, we assessed the telomere-associated and telomere-proximal gene expression profiles in peripheral blood leukocytes from patients with a BRCA1 or BRCA2 mutation, compared to samples from sporadic and familial breast cancer individuals. We found that 25 genes, including TINF2 gene (a negative regulator of telomere length), were significantly differentially expressed in BRCA1 carriers. Leukocyte telomere length analysis revealed that BRCA1/2 carriers had relatively shorter telomeres than healthy controls. Further, affected BRCA1/2 carriers were well differentiated from unaffected BRCA1/2 carriers by the expression of telomere-proximal genes. Our results link BRCA1/2 haploinsufficiency to changes in telomere length, telomere-associated as well as telomere-proximal gene expression. Thus, this work supports the effect of BRCA1/2 haploinsufficiency in the biology underlying telomere dysfunction in cancer development. Future studies evaluating these findings will require a large study population

Avoidant Coping and Self-efficacy Mediate Relationships between Perceived Social Constraints and Symptoms among Long-term Breast Cancer Survivors

Objective Many breast cancer survivors feel constrained in discussing their cancer experience with others. Limited evidence suggests that social constraints (e.g., avoidance and criticism) from loved ones may negatively impact breast cancer survivors' global health, but research has yet to examine relationships between social constraints and common physical symptoms. Informed by social cognitive processing theory, this study examined whether perceived social constraints from partners and healthcare providers (HCPs) were associated with fatigue, sleep disturbance, and attentional functioning among long-term breast cancer survivors (N = 1052). In addition, avoidant coping and self-efficacy for symptom management were examined as potential mediators of these relationships. Methods Long-term breast cancer survivors (mean years since diagnosis = 6) completed questionnaires assessing social constraints from partners and HCPs, avoidant coping, self-efficacy for symptom management, and symptoms (i.e., fatigue, sleep disturbance, and attentional functioning). Structural equation modeling was used to evaluate the hypothesized relationships among variables in two models: one focused on social constraints from partners and one focused on social constraints from HCPs. Results Both models demonstrated good fit. Consistent with theory and prior research, greater social constraints from both partners and HCPs were associated with greater symptom burden (i.e., greater fatigue and sleep disturbance, poorer attentional functioning). In addition, all relationships were mediated by avoidant coping and self-efficacy for symptom management. Conclusions Findings are consistent with social cognitive processing theory and suggest that symptom management interventions may be enhanced by addressing the impact of social constraints from survivors' partners and HCPs on their coping and self-efficacy

Impact of Genetic Ancestry on Outcomes in ECOG-ACRIN-E5103

Purpose: Racial disparity in breast cancer outcomes exists between African American and Caucasian women in the United States. We have evaluated the impact of genetically determined ancestry on disparity in efficacy and therapy-induced toxicity for breast cancer patients in the context of a randomized, phase III adjuvant trial. Patients and Methods: This study compared outcomes between 386 patients of African ancestry (AA) and 2473 patients of European ancestry (EA) in a randomized, phase III breast cancer trial; ECOG-ACRIN-E5103. The primary efficacy endpoint, invasive disease free survival (DFS) and clinically significant toxicities were compared including: anthracycline-induced congestive heart failure (CHF), taxane-induced peripheral neuropathy (TIPN), and bevacizumab-induced hypertension. Results: Overall, AAs had significantly inferior DFS (p=0.002; HR=1.5) compared with EAs. This was significant in the estrogen receptor-positive subgroup (p=0.03); with a similar, non-significant trend for those who had triple negative breast cancer (TNBC; p=0.12). AAs also had significantly more grade 3-4 TIPN (OR=2.9; p=2.4 ×10-11) and grade 3-4 bevacizumab-induced hypertension (OR=1.6; p=0.02), with a trend for more CHF (OR=1.8; p=0.08). AAs had significantly more dose reductions for paclitaxel (p=6.6 ×10-6). In AAs, dose reductions in paclitaxel had a significant negative impact on DFS (p=0.03); whereas in EAs, dose reductions did not impact outcome (p=0.35). Conclusion: AAs had inferior DFS with more clinically important toxicities in ECOG-ACRIN-E5103. The altered risk to benefit ratio for adjuvant breast cancer chemotherapy should lead to additional research with the focus centered on the impact of genetic ancestry on both efficacy and toxicity. Strategies to minimize dose reductions for paclitaxel, especially due to TIPN, are warranted for this population

Charcot-Marie-Tooth gene, SBF2, associated with taxaneinduced peripheral neuropathy in African Americans

PURPOSE: Taxane-induced peripheral neuropathy (TIPN) is one of the most important survivorship issues for cancer patients. African Americans (AA) have previously been shown to have an increased risk for this toxicity. Germline predictive biomarkers were evaluated to help identify a priori which patients might be at extraordinarily high risk for this toxicity. EXPERIMENTAL DESIGN: Whole exome sequencing was performed using germline DNA from 213 AA patients who received a standard dose and schedule of paclitaxel in the adjuvant, randomized phase III breast cancer trial, E5103. Cases were defined as those with either grade 3-4 (n=64) or grade 2-4 (n=151) TIPN and were compared to controls (n=62) that were not reported to have experienced TIPN. We retained for analysis rare variants with a minor allele frequency <3% and which were predicted to be deleterious by protein prediction programs. A gene-based, case-control analysis using SKAT was performed to identify genes that harbored an imbalance of deleterious variants associated with increased risk of TIPN. RESULTS: Five genes had a p-value < 10-4 for grade 3-4 TIPN analysis and three genes had a p-value < 10-4 for the grade 2-4 TIPN analysis. For the grade 3-4 TIPN analysis, SET binding factor 2 (SBF2) was significantly associated with TIPN (p-value=4.35 x10-6). Five variants were predicted to be deleterious in SBF2. Inherited mutations in SBF2 have previously been associated with autosomal recessive, Type 4B2 Charcot-Marie-Tooth (CMT) disease. CONCLUSION: Rare variants in SBF2, a CMT gene, predict an increased risk of TIPN in AA patients receiving paclitaxel