Mid- to late-Holocene archaeology, environment and climate in the northeast Kurdistan region of Iraq

This work presents new data from phytolith and speleothem analyses that cover the middle to late Holocene from northeastern Iraq in the Kurdistan region. Coupling these data with previous work, we demonstrate how the region’s environment and climate developed during a time when agriculture became not only established but settlements started to transform into larger urban areas. Results demonstrate a wetter phase during the middle Holocene relative to the present period; a highly seasonal climate with one rainy season is also suggested between 8025 ± 38 and 6977 ± 219 BP. Phytoliths not only suggest a relatively wet environment but they also indicate a diversity of plants used for settlement activity. Sedimentary results complement the indication of a relatively wetter middle Holocene. Archaeologically, terraced construction found in Gurga Chiya and the presence of drought tolerant crops suggest adaptation to stronger, seasonal rains and seasonal droughts in the middle Holocene. Sedimentary, phytolith, and speleothem results suggest relatively drier late-Holocene conditions, although the region continued to be conducive for rainfed agriculture

Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning

Background: For mechanically ventilated critically ill COVID-19 patients, prone positioning has quickly become an important treatment strategy, however, prone positioning is labor intensive and comes with potential adverse effects. Therefore, identifying which critically ill intubated COVID-19 patients will benefit may help allocate labor resources. Methods: From the multi-center Dutch Data Warehouse of COVID-19 ICU patients from 25 hospitals, we selected all 3619 episodes of prone positioning in 1142 invasively mechanically ventilated patients. We excluded episodes longer than 24 h. Berlin ARDS criteria were not formally documented. We used supervised machine learning algorithms Logistic Regression, Random Forest, Naive Bayes, K-Nearest Neighbors, Support Vector Machine and Extreme Gradient Boosting on readily available and clinically relevant features to predict success of prone positioning after 4 h (window of 1 to 7 h) based on various possible outcomes. These outcomes were defined as improvements of at least 10% in PaO2/FiO2 ratio, ventilatory ratio, respiratory system compliance, or mechanical power. Separate models were created for each of these outcomes. Re-supination within 4 h after pronation was labeled as failure. We also developed models using a 20 mmHg improvement cut-off for PaO2/FiO2 ratio and using a combined outcome parameter. For all models, we evaluated feature importance expressed as contribution to predictive performance based on their relative ranking. Results: The median duration of prone episodes was 17 h (11-20, median and IQR, N = 2632). Despite extensive modeling using a plethora of machine learning techniques and a large number of potentially clinically relevant features, discrimination between responders and non-responders remained poor with an area under the receiver operator characteristic curve of 0.62 for PaO2/FiO2 ratio using Logistic Regression, Random Forest and XGBoost. Feature importance was inconsistent between models for different outcomes. Notably, not even being a previous responder to prone positioning, or PEEP-levels before prone positioning, provided any meaningful contribution to predicting a successful next proning episode. Conclusions: In mechanically ventilated COVID-19 patients, predicting the success of prone positioning using clinically relevant and readily available parameters from electronic health records is currently not feasible. Given the current evidence base, a liberal approach to proning in all patients with severe COVID-19 ARDS is therefore justified and in particular regardless of previous results of proning. Keywords: Acute respiratory distress syndrome; COVID-19; Mechanical ventilation

Wake up, wake up! It's me! It's my life! patient narratives on person-centeredness in the integrated care context: a qualitative study

Person-centered care emphasizes a holistic, humanistic approach that puts patients first, at the center of medical care. Person-centeredness is also considered a core element of integrated care. Yet typologies of integrated care mainly describe how patients fit within integrated services, rather than how services fit into the patient's world. Patient-centeredness has been commonly defined through physician's behaviors aimed at delivering patient-centered care. Yet, it is unclear how 'person-centeredness' is realized in integrated care through the patient voice. We aimed to explore patient narratives of person-centeredness in the integrated care context

Factors affecting the motivation of healthcare professionals providing care to Emiratis with type 2 diabetes

OBJECTIVE: We aimed to identify facilitators of and barriers to healthcare professionals' motivation in a diabetes centre in the United Arab Emirates (UAE). DESIGN: A qualitative research approach was employed using semistructured interviews to assess perception of and attitudes regarding healthcare professionals' motivation in providing good quality diabetes care. SETTING: A diabetes centre located in Abu-Dhabi, UAE. PARTICIPANTS: Healthcare professionals including specialist physicians, dieticians, podiatrists, health educators and nurses were recruited through purposive sampling. MAIN OUTCOME MEASURES: After data collection, the audiotaped interviews were transcribed verbatim and subjected to content analysis. RESULTS: Nine semistructured interviews were conducted with healthcare professionals of various professional backgrounds. Important facilitators and barriers related to patient, professional, organization and cultural factors were identified. Barriers that related to heavy workload, disjointed care, lack of patient compliance and awareness, and cultural beliefs and attitudes about diabetes were common. Key facilitators included the patient's role in achieving therapeutic outcomes as well as compliance, cooperation and communication. CONCLUSION: This qualitative study provides some unique insights about factors affecting healthcare professionals' motivation in providing good quality care. To improve the motivation of healthcare professionals in the management of diabetes and therefore the quality of diabetes care, several steps are needed. Importantly, the role of primary care should be reinforced and strengthened regarding the management of type 2 diabetes mellitus, privacy of the consultation time should be highly protected and regulated, and awareness of the Emirate culture and its impact on health should be disseminated to the healthcare professionals providing care to Emirates with diabetes. Also, greater emphasis should be placed on educating Emiratis with diabetes on, and involving them in, the management of their condition

Serum amyloid A primes microglia for ATP-dependent interleukin-1\u3b2 release

Acute-phase response is a systemic reaction to environmental/inflammatory insults and involves production of acute-phase proteins, including serum amyloid A (SAA). Interleukin-1\u3b2 (IL-1\u3b2), a master regulator of neuroinflammation produced by activated inflammatory cells of the myeloid lineage, in particular microglia, plays a key role in the pathogenesis of acute and chronic diseases of the peripheral nervous system and CNS. IL-1\u3b2 release is promoted by ATP acting at the purinergic P2X7 receptor (P2X7R) in cells primed with toll-like receptor (TLR) ligands

Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

Search for chargino-neutralino production with mass splittings near the electroweak scale in three-lepton final states in √s=13 TeV pp collisions with the ATLAS detector

A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell W and Z bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of √s=13  TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139  fb−1. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015–2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full data set are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at the 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV