Immunohistological studies of medullary thyroid carcinoma and C cell hyperplasia

A series of 59 thyroidal C cell neoplasms was studied by immunoperoxidase histology. These neoplasms included human medullary thyroid carcinoma and C cell hyperplasia and rat medullary thyroid carcinoma. In addition to calcitonin, the tumors were studied by immunohistology for the presence of beta-endorphin, ACTH, and somatostain. All but one of the neoplasms were positive for calcitonin, 25 of 31 were positive for beta-endorphin, 12 of 18 were positive for ACTH, and 9 of 19 were positive for somatostatin immunoreactivity. Many tissues contained all 4 peptides, and in some sections these peptide immunoreactivities seemed to be present in the same cells. These studies suggest that there is a relationship in these tumors among the 4 peptides studied, but the basis of this relationship is not clear.     

Regulation of insulin and glucagon secretion from a human islet cell adenoma.

The regulation of insulin biosynthesis, and insulin and glucagon secretion have been investigated in a human islet cell adenoma, by incubation of tumour fragments. Both biosynthesis and secretion of insulin were strongly stimulated by incubation of islet tumour cells in the presence of increasing glucose concentrations in the range 2-8 mmol/1. However, 20 mM-glucose or 20 mM-glucose plus isobutyl methylxanthine (IBMX), both of which provide potent secretagogues for normal B cells, failed to stimulate proinsulin biosynthesis and secretion from the tumour cells. Overall rates of secretion, expressed as a proportion of total insulin content, were up to 20-fold higher than those expected for normal pancreatic tissue. Glucagon secretion from the tumour was stimulated by low glucose concentrations; normal A cells also respond in this way under these conditions. However, no stimulation of glucagon secretion occurred in the presence of IBMX. There was therefore a major alteration in the regulation both of insulin and glucagon secretion, in that release of neither hormone was stimulated by cyclic AMP. Ultrastructural examination showed the tumour to be rather heterogeneous. A and B cells with normal storage granule content and structure were seen, as well as a rather larger number of B cells containing some granules of atypical appearance. The insulin content of the tumour (13 i.u./g wet wt) was consistent with 6-8% of the tumour cells being B cells.     

Hypoxanthine uptake and release by equilibrative nucleoside transporter 2 (ENT2) of rat microvascular endothelial cells

The cardioprotective actions of adenosine are terminated by its uptake into endothelial cells with subsequent metabolism through hypoxanthine to uric acid. This process involves xanthine oxidase-mediated generation of reactive oxygen species (ROS), which have been implicated in the vascular dysfunction observed in ischemia-reperfusion injury. The equilibrative nucleoside transporter, ENT2, mediates the transfer of hypoxanthine into cells. We hypothesize that ENT2 also mediates the cellular release of hypoxanthine, which would limit the amount of intracellular hypoxanthine available for xanthine oxidase-mediated ROS production. Rat microvascular endothelial cells (MVECs) were isolated from skeletal muscle by lectin-affinity purification. The transport of [(3)H]hypoxanthine was assessed using an oil-stop method, and hypoxanthine metabolites were identified by thin-layer chromatography. MVECs accumulated hypoxanthine with a K(m) of 300 microM and a V(max) of 2.8 pmol microl(-1) s(-1). ATP-depleted cells loaded with [(3)H]hypoxanthine released the radiolabel with kinetics similar to that obtained for [(3)H]hypoxanthine influx. The uptake and release of [(3)H]hypoxanthine were both blocked by ENT2 inhibitors with similar order of potency. Thus, ENT2 mediates both the influx and efflux of hypoxanthine. Inhibition of ENT2 in MVECs might be expected to increase the amount of intracellular hypoxanthine available for metabolism by xanthine oxidase and enhance the intracellular production of ROS.     

Homozygous and compound heterozygous mutations in the ATP6V1B1 gene in patients with renal tubular acidosis and sensorineural hearing loss

Mohebbi N, Vargas‐Poussou R, Hegemann SCA, Schuknecht B, Kistler AD, Wüthrich RP, Wagner CA. Homozygous and compound heterozygous mutations in the ATP6V1B1 gene in patients with renal tubular acidosis and sensorineural hearing loss. Distal renal tubular acidosis (dRTA) is characterized by the inability to excrete acid in the renal collecting ducts resulting in inappropriately alkaline urine and hyperchloremic (normal anion gap) metabolic acidosis in the context of a normal (or near‐normal) glomerular filtration rate. Inborn dRTA can be due to autosomal dominant or recessive gene defects. Clinical symptoms vary from mild acidosis, incidental detection of kidney stones or renal tract calcification to severe findings such as failure to thrive, severe metabolic acidosis, and nephrocalcinosis. The majority of patients with recessive dRTA present with sensorineural hearing loss (SNHL). Few cases with abnormal widening of the vestibular aqueduct have been described with dRTA. Mutations in three different genes have been identified, namely SLC4A1, ATP6V1B1, and ATP6V0A4. Patients with mutations in the ATP6V1B1 proton pump subunit develop dRTA and in most of the cases sensorineural hearing loss early in childhood. We present two patients from two different and non‐consanguineous families with dRTA and SNHL. Direct sequencing of the ATP6V1B1 gene revealed that one patient harbors two homozygous mutations and the other one is a compound heterozygous. To our knowledge, this is the first case in the literature describing homozygosity in the same dRTA gene on both alleles.     

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).     

Bilateral occurrence of pheochromocytoma in patients with the multiple endocrine neoplasia syndrome type 2A (Sipple's syndrome)

Two kindreds with the multiple endocrine neoplasia type 2A syndrome were studied. Of one of these we examined 150 members, 20 of whom were treated with thyroidectomy for medullary carcinoma and nine with bilateral adrenalectomy for pheochromocytoma. Of the second kindred 59 members were examined, seven of whom were thyroidectomized and seven treated with bilateral adrenalectomy. Pheochromocytomas were invariably found on both sides, even in four cases in which the adrenals on one side appeared to be completely normal, not only at preoperative roentgenologic examination but also on inspection during the operation. The microscopic finding of micronodules and a cluster of abnormal medullary cells identical with those found in pheochromocytomas in one of the apparently normal adrenals represents a first stage in the development of diffuse medullary hyperplasia as well as nodular hyperplasia. This is in accordance with the fact that in the MEN type 2A syndrome pheochromocytomas are always multicentric and multiple in origin. On the basis of these findings we conclude that all patients with the MEN 2A syndrome who show symptoms and signs of active pheochromocytoma should be subjected to bilateral adrenalectomy, even when one or both of the adrenals appear to be normal at roentgenologic investigation.