Housing Boston's Chronically Homeless Unsheltered Population: 14 Years Later.

OBJECTIVE: The long-term outcomes of permanent supportive housing for chronically unsheltered individuals, or rough sleepers, are largely unknown. We therefore assessed housing outcomes for a group of unsheltered individuals who were housed directly from the streets after living outside for decades. METHODS: Using an open-cohort design, 73 chronically unsheltered individuals were enrolled and housed in permanent supportive housing directly from the streets of Boston from 2005 to 2019. Through descriptive, regression, and survival analysis, we assessed housing retention, housing stability, and predictors of survival. RESULTS: Housing retention at ≥1 year was 82% yet fell to 36% at ≥5 years; corresponding Kaplan-Meier estimates for retention were 72% at ≥1, 42.5% at ≥5, and 37.5% at ≥10 years. Nearly half of the cohort (45%) died while housed. The co-occurrence of medical, psychiatric, and substance use disorder, or "trimorbidity," was common. Moves to a new apartment were also common; 38% were moved 45 times to avoid an eviction. Each subsequent housing relocation increased the risk of a tenant returning to homelessness. Three or more housing relocations substantially increased the risk of death. CONCLUSIONS: Long-term outcomes for this permanent supportive housing program for chronically unsheltered individuals showed low housing retention and poor survival. Housing stability for this vulnerable population likely requires more robust and flexible and long-term medical and social supports.

When did Homo sapiens first reach Southeast Asia and Sahul?

Anatomically modern humans (Homo sapiens, AMH) began spreading across Eurasia from Africa and adjacent Southwest Asia about 50,000-55,000 years ago (ca 50-55 ka). Some have argued that human genetic, fossil, and archaeological data indicate one or more prior dispersals, possibly as early as 120 ka. A recently reported age estimate of 65 ka for Madjedbebe, an archaeological site in northern Sahul (Pleistocene Australia-New Guinea), if correct, offers what might be the strongest support yet presented for a pre-55-ka African AMH exodus. We review evidence for AMH arrival on an arc spanning South China through Sahul and then evaluate data from Madjedbebe. We find that an age estimate of >50 ka for this site is unlikely to be valid. While AMH may have moved far beyond Africa well before 50-55 ka, data from the region of interest offered in support of this idea are not compelling.

Substance consumption and intoxication patterns in a medically supervised overdose prevention program for people experiencing homelessness.

Background: Opioid overdose is a leading cause of death among homeless individuals. Combining psychoactive substances with opioids increases overdose risk. This study aimed to describe intoxication patterns at a drop-in space offering medical monitoring and harm reduction services to individuals who arrive intoxicated and at risk of overdose. Methods: We examined data from visits to the Supportive Place for Observation and Treatment at Boston Health Care for the Homeless Program between January 1, 2017 and December 31, 2017. We used k-means cluster analysis to characterize intoxication patterns based on clinically assessed sedation levels and vital sign parameters. Multinomial logistic regression analysis assessed demographic and substance consumption predictors of cluster membership. Linear and logistic regression models examined associations between cluster membership and care outcomes. Results: Across 305 care episodes involving 156 unique patients, cluster analysis revealed 3 distinct intoxication patterns. Cluster A (26.6%) had mild sedation and normal vital signs. Cluster B (44.5%) featured greater sedation with bradycardia and/or hypotension. Cluster C (28.9%) was comparable to cluster B but with the addition of hypoxia. Self-reported consumption of non-opioid sedatives prior to arrival was common (63.3% of episodes) and predicted membership in cluster B (aOR 2.75, 95% CI 1.40, 5.40) and cluster C (aOR 3.38, 95% CI 1.48, 7.70). In comparison to cluster A episodes, cluster C episodes were longer (mean 4.8 vs. 2.3 hours, p < 0.001) and more likely to require supplemental oxygen (27.3% vs. 2.5%, p < 0.001). Few episodes required hospital transfer (4.7%) or naloxone (1.0%). No deaths occurred. Conclusions: In a medically supervised overdose monitoring program, reported use of non-opioid sedatives strongly predicted more complex clinical courses and should be factored into overdose prevention efforts. Low-threshold medical monitoring in an ambulatory setting was sufficient for most episodes, suggesting a role for such programs in reducing harm and averting costly emergency services.

Ultrasound Image Classification of Thyroid Nodules Using Machine Learning Techniques.

Background and Objectives: Thyroid nodules are lumps of solid or liquid-filled tumors that form inside the thyroid gland, which can be malignant or benign. Our aim was to test whether the described features of the Thyroid Imaging Reporting and Data System (TI-RADS) could improve radiologists' decision making when integrated into a computer system. In this study, we developed a computer-aided diagnosis system integrated into multiple-instance learning (MIL) that would focus on benign-malignant classification. Data were available from the Universidad Nacional de Colombia. Materials and Methods: There were 99 cases (33 Benign and 66 malignant). In this study, the median filter and image binarization were used for image pre-processing and segmentation. The grey level co-occurrence matrix (GLCM) was used to extract seven ultrasound image features. These data were divided into 87% training and 13% validation sets. We compared the support vector machine (SVM) and artificial neural network (ANN) classification algorithms based on their accuracy score, sensitivity, and specificity. The outcome measure was whether the thyroid nodule was benign or malignant. We also developed a graphic user interface (GUI) to display the image features that would help radiologists with decision making. Results: ANN and SVM achieved an accuracy of 75% and 96% respectively. SVM outperformed all the other models on all performance metrics, achieving higher accuracy, sensitivity, and specificity score. Conclusions: Our study suggests promising results from MIL in thyroid cancer detection. Further testing with external data is required before our classification model can be employed in practice.

SPIN2: Predicting sequence profiles from protein structures using deep neural networks.

Designing protein sequences that can fold into a given structure is a well-known inverse protein-folding problem. One important characteristic to attain for a protein design program is the ability to recover wild-type sequences given their native backbone structures. The highest average sequence identity accuracy achieved by current protein-design programs in this problem is around 30%, achieved by our previous system, SPIN. SPIN is a program that predicts sequences compatible with a provided structure using a neural network with fragment-based local and energy-based nonlocal profiles. Our new model, SPIN2, uses a deep neural network and additional structural features to improve on SPIN. SPIN2 achieves over 34% in sequence recovery in 10-fold cross-validation and independent tests, a 4% improvement over the previous version. The sequence profiles generated from SPIN2 are expected to be useful for improving existing fold recognition and protein design techniques. SPIN2 is available at http://sparks-lab.org.

Hunter-gatherer studies and human evolution: A very selective review.

The century long publication of this journal overlapped major changes in the sciences it covers. We have been eyewitnesses to vast changes during the final third of the last century and beginning of this one, momentous enough to fundamentally alter our work separately and collectively. One (NBJ) from animal ethology, another from western North American archaeology (JOC), and a third (KH) from cultural anthropology came to longtime collaboration as evolutionary ecologists with shared focus on studying modern hunter-gatherers to guide hypotheses about human evolution. Our findings have radically revised hypotheses each of us took for granted when we began. Our (provisional) conclusions are not the consensus among hunter-gatherer specialists; but grateful that personal reflections are invited, we aim to explain how and why we continue to bet on them.