Depression in Zimbabwe: a community approach to prevention and treatment

A position paper on primary health care for the management of mental health in Zimbabwe.This paper reports on a process whereby research findings, generated by a collaborative project between primary health care workers and a University team, were utilized by a community to formulate local plans for the prevention and management of depression. Action-oriented research, with a high level of community participation, follows on directly from the Declaration of Alma-Ata1 and has been called Health Systems Research (HSR). The principle of HSR is that it should be useful and have a direct focus on solving practical and relevant problems.2 Priorities should be generated by health workers and by the community rather than purely by academics and as much as possible of the research should be carried out by those already working at ground level. Results should lead to implementable recommendations and the research is not complete until those recommendations are underway

Development of nuclear analysis capabilities for DOE waste management activities

The objective of this project is to develop and demonstrate prototypic analysis capabilities that can be used by the nuclear safety analysis practitioners to: (1) demonstrate a more thorough understanding of the underlying physics phenomena that can lead to improved reliability and defensibility of safety evaluations; and (2) optimize operations related to the handling, storage, transportation, and disposal of fissile material and DOE spent fuel. To address these problems, the project will investigate the implementation of sensitivity and uncertainty methods within existing Monte Carlo codes used for criticality safety analyses, as well as within a new deterministic code that allows specification of arbitrary grids to accurately model the geometry details required in a criticality safety analysis. This capability can facilitate improved estimations of the required subcritical margin and potentially enable the use of a broader range of experiments in the validation process. The new arbitrary-grid radiation transport code will also enable detailed geometric modeling valuable for improved accuracy in application to a myriad of other problems related to waste characterization. Application to these problems will also be explored

The significance of 'the visit' in an English category-B prison: Views from prisoners, prisoners' families and prison staff

A number of claims have been made regarding the importance of prisoners staying in touch with their family through prison visits, firstly from a humanitarian perspective of enabling family members to see each other, but also regarding the impact of maintaining family ties for successful rehabilitation, reintegration into society and reduced re-offending. This growing evidence base has resulted in increased support by the Prison Service for encouraging the family unit to remain intact during a prisoner’s incarceration. Despite its importance however, there has been a distinct lack of research examining the dynamics of families visiting relatives in prison. This paper explores perceptions of the same event – the visit – from the families’, prisoners’ and prison staffs' viewpoints in a category-B local prison in England. Qualitative data was collected with 30 prisoners’ families, 16 prisoners and 14 prison staff, as part of a broader evaluation of the visitors’ centre. The findings suggest that the three parties frame their perspective of visiting very differently. Prisoners’ families often see visits as an emotional minefield fraught with practical difficulties. Prisoners can view the visit as the highlight of their time in prison and often have many complaints about how visits are handled. Finally, prison staff see visits as potential security breaches and a major organisational operation. The paper addresses the current gap in our understanding of the prison visit and has implications for the Prison Service and wider social policy

Growth of Inflaton Perturbations and the Post-Inflation Era in Supersymmetric Hybrid Inflation Models

It has been shown that hybrid inflation may end with the formation of non-topological solitons of inflaton field. As a first step towards a fully realistic picture of the post-inflation era and reheating in supersymmetric hybrid inflation models, we study the classical scalar field equations of a supersymmetric hybrid inflation model using a semi-analytical ansatz for the spatial dependence of the fields. Using the minimal D-term inflation model as an example, the inflaton field is evolved using the full 1-loop effective potential from the slow-rolling era to the U(1)_{FI} symmetry-breaking phase transition. Spatial perturbations of the inflaton corresponding to quantum fluctuations are introduced for the case where there is spatially coherent U(1)_{FI} symmetry breaking. The maximal growth of the dominant perturbation is found to depend only on the ratio of superpotential coupling \lambda to the gauge coupling g. The inflaton condensate fragments to non-topological solitons for \lambda/g > 0.09. Possible consequences of non-topological soliton formation in fully realistic SUSY hybrid inflation models are discussed.Comment: 27 pages LaTeX, 8 figures. Additional references and discussio

Does Respondent Driven Sampling Alter the Social Network Composition and Health-Seeking Behaviors of Illicit Drug Users Followed Prospectively?

Respondent driven sampling (RDS) was originally developed to sample and provide peer education to injection drug users at risk for HIV. Based on the premise that drug users' social networks were maintained through sharing rituals, this peer-driven approach to disseminate educational information and reduce risk behaviors capitalizes and expands upon the norms that sustain these relationships. Compared with traditional outreach interventions, peer-driven interventions produce greater reductions in HIV risk behaviors and adoption of safer behaviors over time, however, control and intervention groups are not similarly recruited. As peer-recruitment may alter risk networks and individual risk behaviors over time, such comparison studies are unable to isolate the effect of a peer-delivered intervention. This analysis examines whether RDS recruitment (without an intervention) is associated with changes in health-seeking behaviors and network composition over 6 months. New York City drug users (N = 618) were recruited using targeted street outreach (TSO) and RDS (2006–2009). 329 non-injectors (RDS = 237; TSO = 92) completed baseline and 6-month surveys ascertaining demographic, drug use, and network characteristics. Chi-square and t-tests compared RDS- and TSO-recruited participants on changes in HIV testing and drug treatment utilization and in the proportion of drug using, sex, incarcerated and social support networks over the follow-up period. The sample was 66% male, 24% Hispanic, 69% black, 62% homeless, and the median age was 35. At baseline, the median network size was 3, 86% used crack, 70% used cocaine, 40% used heroin, and in the past 6 months 72% were tested for HIV and 46% were enrolled in drug treatment. There were no significant differences by recruitment strategy with respect to changes in health-seeking behaviors or network composition over 6 months. These findings suggest no association between RDS recruitment and changes in network composition or HIV risk, which supports prior findings from prospective HIV behavioral surveillance and intervention studies

Immune Checkpoint Inhibitors Targeting the PD-1/PD-L1 Pathway in Advanced, Recurrent Endometrial Cancer: A Scoping Review with SWOT Analysis

Results of recent clinical trials using the immune check point inhibitors (ICI) pembrolizumab or dostarlimab with/without lenvatinib has led to their approval for specific molecular subgroups of advanced recurrent endometrial cancer (EC). Herein, we summarise the clinical data leading to this first tissue-agnostic approval. As this novel therapy is not yet available in the United Kingdom standard care setting, we explore the strengths, weaknesses, opportunities, and threats (SWOT) of ICI treatment in EC. Major databases were searched focusing on clinical trials using programmed cell death protein 1 (PD-1) and its ligand (PD-L1) ICI which ultimately contributed to anti-PD-1 approval in EC. We performed a data quality assessment, reviewing survival and safety analysis. We included 15 studies involving 1609 EC patients: 458 with mismatch repair deficiency (MMRd)/microsatellite instability-high (MSI-H) status and 1084 with mismatch repair proficiency/microsatellite stable (MMRp/MSS) status. Pembrolizumab/dostarlimab have been approved for MMRd ECs, with the addition of lenvatinib for MMRp cases in the recurrent setting. Future efforts will focus on the pathological assessment of biomarkers to determine molecular phenotypes that correlate with response or resistance to ICI in order to identify patients most likely to benefit from this treatment

Play Analysis and Digital Portfolio of Major Oil Reservoirs in the Permian Basin: Application and Transfer of Advanced Geological and Engineering Technologies for Incremental Production Opportunities

A play portfolio is being constructed for the Permian Basin in west Texas and southeast New Mexico, the largest onshore petroleum-producing basin in the United States. Approximately 1,300 reservoirs in the Permian Basin have been identified as having cumulative production greater than 1 MMbbl (1.59 x 10{sup 5} m{sup 3}) of oil through 2000. Of these significant-sized reservoirs, approximately 1,000 are in Texas and 300 in New Mexico. There are 32 geologic plays that have been defined for Permian Basin oil reservoirs, and each of the 1,300 major reservoirs was assigned to a play. The reservoirs were mapped and compiled in a Geographic Information System (GIS) by play. The final reservoir shapefile for each play contains the geographic location of each reservoir. Associated reservoir information within the linked data tables includes RRC reservoir number and district (Texas only), official field and reservoir name, year reservoir was discovered, depth to top of the reservoir, production in 2000, and cumulative production through 2000. Some tables also list subplays. Play boundaries were drawn for each play; the boundaries include areas where fields in that play occur but are smaller than 1 MMbbl (1.59 x 10{sup 5} m{sup 3}) of cumulative production. Oil production from the reservoirs in the Permian Basin having cumulative production of >1 MMbbl (1.59 x 10{sup 5} m{sup 3}) was 301.4 MMbbl (4.79 x 10{sup 7} m{sup 3}) in 2000. Cumulative Permian Basin production through 2000 was 28.9 Bbbl (4.59 x 10{sup 9} m{sup 3}). The top four plays in cumulative production are the Northwest Shelf San Andres Platform Carbonate play (3.97 Bbbl [6.31 x 10{sup 8} m{sup 3}]), the Leonard Restricted Platform Carbonate play (3.30 Bbbl [5.25 x 10{sup 8} m{sup 3}]), the Pennsylvanian and Lower Permian Horseshoe Atoll Carbonate play (2.70 Bbbl [4.29 x 10{sup 8} m{sup 3}]), and the San Andres Platform Carbonate play (2.15 Bbbl [3.42 x 10{sup 8} m{sup 3}]). Detailed studies of three reservoirs are in progress: Kelly-Snyder (SACROC unit) in the Pennsylvanian and Lower Permian Horseshoe Atoll Carbonate play, Fullerton in the Leonard Restricted Platform Carbonate play, and Barnhart (Ellenburger) in the Ellenburger Selectively Dolomitized Ramp Carbonate play. For each of these detailed reservoir studies, technologies for further, economically viable exploitation are being investigated

Respondent-Driven Sampling of Injection Drug Users in Two U.S.–Mexico Border Cities: Recruitment Dynamics and Impact on Estimates of HIV and Syphilis Prevalence

Respondent-driven sampling (RDS), a chain referral sampling approach, is increasingly used to recruit participants from hard-to-reach populations, such as injection drug users (IDUs). Using RDS, we recruited IDUs in Tijuana and Ciudad (Cd.) Juárez, two Mexican cities bordering San Diego, CA and El Paso, TX, respectively, and compared recruitment dynamics, reported network size, and estimates of HIV and syphilis prevalence. Between February and April 2005, we used RDS to recruit IDUs in Tijuana (15 seeds, 207 recruits) and Cd. Juárez (9 seeds, 197 recruits), Mexico for a cross-sectional study of behavioral and contextual factors associated with HIV, HCV and syphilis infections. All subjects provided informed consent, an anonymous interview, and a venous blood sample for serologic testing of HIV, HCV, HBV (Cd. Juárez only) and syphilis antibody. Log-linear models were used to analyze the association between the state of the recruiter and that of the recruitee in the referral chains, and population estimates of the presence of syphilis antibody were obtained, correcting for biased sampling using RDS-based estimators. Sampling of the targeted 200 recruits per city was achieved rapidly (2 months in Tijuana, 2 weeks in Cd. Juárez). After excluding seeds and missing data, the sample prevalence of HCV, HIV and syphilis were 96.6, 1.9 and 13.5% respectively in Tijuana, and 95.3, 4.1, and 2.7% respectively in Cd. Juárez (where HBV prevalence was 84.7%). Syphilis cases were clustered in recruitment trees. RDS-corrected estimates of syphilis antibody prevalence ranged from 12.8 to 26.8% in Tijuana and from 2.9 to 15.6% in Ciudad Juárez, depending on how recruitment patterns were modeled, and assumptions about how network size affected an individual’s probability of being included in the sample. RDS was an effective method to rapidly recruit IDUs in these cities. Although the frequency of HIV was low, syphilis prevalence was high, particularly in Tijuana. RDS-corrected estimates of syphilis prevalence were sensitive to model assumptions, suggesting that further validation of RDS is necessary

Feature Selection is Critical for 2-Year Prognosis in Advanced Stage High Grade Serous Ovarian Cancer by Using Machine Learning

Introduction Accurate prediction of patient prognosis can be especially useful for the selection of best treatment protocols. Machine Learning can serve this purpose by making predictions based upon generalizable clinical patterns embedded within learning datasets. We designed a study to support the feature selection for the 2-year prognostic period and compared the performance of several Machine Learning prediction algorithms for accurate 2-year prognosis estimation in advanced-stage high grade serous ovarian cancer (HGSOC) patients. Methods The prognosis estimation was formulated as a binary classification problem. Dataset was split into training and test cohorts with repeated random sampling until there was no significant difference (p = 0.20) between the two cohorts. A ten-fold cross-validation was applied. Various state-of-the-art supervised classifiers were used. For feature selection, in addition to the exhaustive search for the best combination of features, we used the-chi square test of independence and the MRMR method. Results Two hundred nine patients were identified. The model's mean prediction accuracy reached 73%. We demonstrated that Support-Vector-Machine and Ensemble Subspace Discriminant algorithms outperformed Logistic Regression in accuracy indices. The probability of achieving a cancer-free state was maximised with a combination of primary cytoreduction, good performance status and maximal surgical effort (AUC 0.63). Standard chemotherapy, performance status, tumour load and residual disease were consistently predictive of the mid-term overall survival (AUC 0.63–0.66). The model recall and precision were greater than 80%. Conclusion Machine Learning appears to be promising for accurate prognosis estimation. Appropriate feature selection is required when building an HGSOC model for 2-year prognosis prediction. We provide evidence as to what combination of prognosticators leads to the largest impact on the HGSOC 2-year prognosis