Patient Health Literacy and Communication with Providers Among Women Living with HIV: A Mixed Methods Study

AIDS and Behavior - In this mixed-methods study, we examine the relationship between provider communication and patient health literacy on HIV continuum of care outcomes among women living with HIV...     

High mobility group 1 B-box mediates activation of human endothelium

OBJECTIVES: Severe sepsis and septic shock is a consequence of a generalized inflammatory systemic response because of an invasive infection that may result in acute organ dysfunction. Mortality is high despite access to modern intensive care units. The nuclear DNA binding protein high mobility group 1 (HMGB1) protein has recently been suggested to act as a late mediator of septic shock via its function as a macrophage-derived pro-inflammatory cytokine (J Exp Med 2000; 192: 565, Science1999; 285: 248). We investigated the pro-inflammatory activities of the A-box and the B-box of HMGB1 on human umbilical venular endothelial cells (HUVEC). DESIGN: The HUVEC obtained from healthy donors were used for experiments. Recombinant human full-length HMGB1, A-box and B-box were cloned by polymerase chain reaction (PCR) amplification from a human brain quick-clone cDNA. The activation of HUVEC was studied regarding (i) upregulation of adhesion molecules, (ii) the release of cytokines and chemokines, (iii) the adhesion of neutrophils to HUVEC, (iv) the activation of signalling transduction pathways and (v) the involvement of the receptor for advanced glycation end-products (RAGE). RESULTS: The full-length protein and the B-box of HMGB1 dose-dependently activate HUVEC to upregulate adhesion molecules such as ICAM-1, VCAM-1 and E-selectin and to release IL-8 and G-CSF. The activation of HUVEC could be inhibited to 50% by antibodies directed towards the RAGE. HMGB1-mediated HUVEC stimulation resulted in phosphorylation of the ELK-1 signal transduction protein and a nuclear translocation of p65 plus c-Rel, suggesting that HMGB1 signalling is regulated in endothelial cells through NF-kappaB. CONCLUSIONS: The HMGB1 acts as a potent pro-inflammatory cytokine on HUVEC and the activity is mainly mediated through the B-box of the protein. HMGB1 may be a key factor mediating part of the pro-inflammatory response occurring in septic shock and severe inflammation.     

The molecular epidemiology of HIV type 1 among Vietnamese Australian injecting drug users in Melbourne, Australia

The proportion of human immunodeficiency virus type 1 (HIV-1) among Vietnamese injecting drug users (IDUs) in Melbourne, Australia exceeds that of the background population. To investigate the molecular epidemiology of HIV-1 among this group, the C2-V4 region of the HIV-1 envelope was directly sequenced from 11 Vietnamese Australians and 19 non-Vietnamese Australian controls. A significant difference in the distribution of the HIV-1 subtypes was demonstrated, with greater than 50% of Vietnamese Australian IDU shown to be infected with CRF01_AE-the predominant subtype in Southeast Asia, rather than subtype B, which dominates the Australian epidemic and which was found in 89.5% of the non-Vietnamese controls. The genetic diversity of the CRF01_AE epidemic in Vietnamese Australian IDUs was substantially lower that that of the background subtype B, consistent with a more recent introduction of a limited number of viral strains from Vietnam. These results support public health policy targeting Australian IDUs of Vietnamese ethnicity as a distinct vulnerable population.     

Fear of Losing Emotional Control Is Associated With Cognitive Processing Therapy Outcomes in U.S. Veterans of Afghanistan and Iraq

Evidence‐based treatments for posttraumatic stress disorder (PTSD) can reduce symptoms and improve veterans’ psychological health. Unfortunately, many veterans leave treatment before receiving maximum benefit. Fear of emotions is related to severity of PTSD, and changes in fear of emotions are correlated with changes in PTSD symptoms. This study built upon the literature linking greater fear of emotions to PTSD severity by examining whether pretreatment fear of emotions, measured by the Affect Control Scale, was associated with completion of cognitive processing therapy (CPT) and severity of posttreatment PTSD in a sample of 89 U.S. veterans who had served in Afghanistan and Iraq. About 60% of veterans completed 10 or more therapy sessions. A logistic regression on 51 of the 89 subjects that more fear of anxiety at pretreatment was associated with decreased likelihood of completing treatment, OR = 0.93, 95% CI [0.87, 1.00]. Of those veterans who completed treatment, higher fear of anger at pretreatment was negatively related to severity of PTSD posttreatment (β = ?.29, p = .037), in a model with the other predictors. Assessing veterans for fear of anxiety and anger before CPT and teaching emotion regulation skills to those in need may reduce treatment dropout.     

From the Cover: Satellites can reveal global extent of forced labor in the world’s fishing fleet

While forced labor in the world’s fishing fleet has been widely documented, its extent remains unknown. No methods previously existed for remotely identifying individual fishing vessels potentially engaged in these abuses on a global scale. By combining expertise from human rights practitioners and satellite vessel monitoring data, we show that vessels reported to use forced labor behave in systematically different ways from other vessels. We exploit this insight by using machine learning to identify high-risk vessels from among 16,000 industrial longliner, squid jigger, and trawler fishing vessels. Our model reveals that between 14% and 26% of vessels were high-risk, and also reveals patterns of where these vessels fished and which ports they visited. Between 57,000 and 100,000 individuals worked on these vessels, many of whom may have been forced labor victims. This information provides unprecedented opportunities for novel interventions to combat this humanitarian tragedy. More broadly, this research demonstrates a proof of concept for using remote sensing to detect forced labor abuses.

Forced labor in fisheries, a type of modern slavery, is increasingly recognized as a human rights crisis. The International Labor Organization (ILO) defines forced labor as “all work or service which is exacted from any person under the menace of any penalty and for which the said person has not offered himself voluntarily” (1). The ILO provides a framework of 11 forced labor risk indicators (2) that have all been documented within the fisheries sector, including indicators representative of debt-bonded labor, as well as indicators representative of servitude or slave labor such as abusive working and living conditions. In 2015, reports emerged on forced labor in Thai fisheries (3) and the role of forced labor in producing seafood imported to the United States (4). More recent reports have described the global nature of the problem (5), and there has been a call to integrate social responsibility into ocean science (6). Despite widespread condemnation and ambitious commitments, forced labor remains poorly understood in the fisheries sector. Here we show that recently available high-frequency vessel monitoring of the global industrial fishing fleet can shed new light on forced labor at a much finer resolution. We combine expertise from on-the-ground human rights practitioners and satellite vessel monitoring data for over 16,000 industrial fishing vessels to estimate 1) the number of high-risk vessels and the number of crew who may be victims working on those vessels, 2) where these vessels fish, and 3) what ports these vessels visit. This information can inform new market, policy, and enforcement interventions to combat forced labor in global fisheries. This research more generally demonstrates how remote sensing can detect forced labor abuses by observing dynamic behavior.Current estimates of forced labor in fisheries are coarse and are based on country-level statistics. Using country-level household surveys, the ILO estimated that 16 million people were victims of forced labor in 2016, with 11% of these in agriculture, forestry, or fisheries (7). The Global Slavery Index reports that the seven countries with highest slavery risk in 2018 generated 39% of global fisheries catch (3, 8), and Tickler et al. found that the United States has slavery risks of 0.2 kg per metric ton for domestic seafood and 3.1 kg per metric ton for imported seafood (9). While these studies are important for broadly understanding which countries have risk, current methods are unable to detect this problem at the level of individual fishing vessels, which will be essential for targeted interventions.We empirically examine whether vessels reported to exhibit any of the ILO indicators of forced labor behave in ways that are systematically different from other vessels, and then exploit this information using machine learning to discriminate between vessels that use forced labor from those that do not. We do so by measuring a suite of features that can be observed using satellite Automatic Identification System (AIS) vessel monitoring data made available by Global Fishing Watch (GFW) (10). There may be many behavioral correlates with forced labor that could help to differentiate between high-risk and low-risk vessels. To determine which model features to include, we first conducted a literature review of investigative journalism reports and looked for instances of forced labor case accounts that detailed specific behaviors that could be observed using vessel monitoring data. We next conducted informal phone interviews with experts from several nongovernmental organizations (NGOs) working in this field, during which we asked interviewees what observable vessel behaviors they would look for if they wanted to identify suspicious activity. The machine-learning approach we use does not assume that vessels behave in any particular way; rather, it merely uses the features identified by literature review and expert insight to exploit any observed empirical differences between vessels that use forced labor and other vessels. NGO experts and investigative journalism suggest that gaps in AIS transmission, port avoidance, transshipment, and extended time at sea may indicate the presence of forced labor (11). Certain features, like information on catch and the species being targeted, could also be helpful in discriminating between high- and low-risk behavior by providing more context on the fishing taking place. However, these data are not currently available at the vessel level on a global scale. Data on recruitment practices and vessel ownership and information on from where the crew originates could also be helpful, but, again, these data are not widely available. We arrived at a list of 27 vessel behavior and characteristic features for which we have globally available data at the vessel level (SI Appendix, Table S1, and SI Appendix).To build a predictive model for identifying high-risk vessels, we developed a training dataset that includes the behavior and characteristics of known forced-labor vessels, as well as the behavior and characteristics of other vessels. We compiled a comprehensive database of vessels that were reported to display one or more of the ILO forced labor indicators (2); these vessels are labeled as “positives.” We do not, however, know which vessels do not use forced labor (“negatives”). Rather, any vessel that we do not label as positive is “unlabeled,” and may in fact be a positive vessel that has not yet been identified or may truly be a negative vessel. This is an example of “positive-unlabeled (PU)” learning, a less straightforward problem than traditional supervised machine learning (12). We use PU learning to predict whether or not 16,261 longliner, trawler, and squid jigger fishing vessels were high-risk during each year they operated between 2012 and 2018 (“vessel-years”). We focus on this subset of vessels because they broadcasted sufficient and reliable AIS positions and because these are the only fishing gear types with documented cases of forced labor aboard vessels that broadcasted sufficient AIS data. These vessels represent 33% of the total time at sea spent by all fishing vessels operating in this time period tracked by GFW. Our PU approach leverages information from all positively labeled vessels (n = 22 unique vessels across 22 vessel-years using our baseline model assumption), but places less emphasis on unlabeled vessels given their uncertain nature (n = 16,257 unique vessels across 66,314 vessel-years using our baseline model assumption).     

Does Prior Abdominal Surgery Influence Conversion Rates and Outcomes of Laparoscopic Right Colectomy in Patients with Neoplasia?

Purpose  The study investigated the impact of prior abdominal surgery on conversions and outcomes of laparoscopic right colectomy. Methods  A consecutive series of 414 patients with cancer or adenomas who underwent a laparoscopic right colectomy from March 1996 to November 2006 were studied for surgical conversions and outcomes. Conversion was defined as an incision length > 7 cm. Results  Patients with prior abdominal surgery (n = 191) were compared with patients with no prior abdominal surgery (n = 223), and showed no significant differences in age, ASA classification, length of stay, operative time, blood loss, harvested nodes, tumor size, and specimen length. Significantly more wound infections occurred in the prior abdominal surgery group (22 vs.12, P = 0.023). Body mass index > 30 showed a three-fold increased risk of conversion. Fifteen percent of the no prior abdominal surgery patients and 17 percent of the prior abdominal surgery patients were converted (P > 0.05). Conversion was associated with a longer mean length of stay (8.8 days) relative to laparoscopically completed cases (6.3 days) regardless of prior abdominal surgery history (P < 0.0001). Conclusions  Laparoscopic right colectomy for neoplasia was not associated with a higher conversion rate or morbidity in patients with prior abdominal surgery. Prior abdominal surgery is not a contraindication to laparoscopic right colectomy. Presented at the 15th International Congress of the European Association of Endoscopic Surgery, Athens, Greece, July 4 to 7, 2007.