Ancient genomics support deep divergence between Eastern and Western Mediterranean Indo-European languages.

The Indo-European languages are among the most widely spoken in the world, yet their early diversification remains contentious. It is widely accepted that the spread of this language family across Europe from the 5th millennium BP correlates with the expansion and diversification of steppe-related genetic ancestry from the onset of the Bronze Age. However, multiple steppe-derived populations co-existed in Europe during this period, and it remains unclear how these populations diverged and which provided the demographic channels for the ancestral forms of the Italic, Celtic, Greek, and Armenian languages.

Extensive Deep Vein Thrombosis and Pulmonary Embolism in a Young Patient With Heterozygous Factor V Leiden Mutation and Antiphospholipid Syndrome.

Although thrombotic events are uncommon in young individuals, patients with genetic mutations in coagulation factors may develop extensive multisite thrombosis. We present the case of a 26-year-old patient, a smoker for nine years, who was admitted to the hospital complaining of right thigh pain with swelling, right flank abdominal pain, dyspnea, and hemoptysis. A medical history provided by the patient indicated that one month prior to presentation, an accidental fall had resulted in multiple rib fractures, bilateral hemopneumothorax, and pneumomediastinum.

Automated Mapping of Land Cover Type within International Heterogenous Landscapes Using Sentinel-2 Imagery with Ancillary Geospatial Data.

A near-global framework for automated training data generation and land cover classification using shallow machine learning with low-density time series imagery does not exist. This study presents a methodology to map nine-class, six-class, and five-class land cover using two dates (winter and non-winter) of a Sentinel-2 granule across seven international sites. The approach uses a series of spectral, textural, and distance decision functions combined with modified ancillary layers (such as global impervious surface and global tree cover) to create binary masks from which to generate a balanced set of training data applied to a random forest classifier.