bluuebunny/crossref_metadata_2025_split huggingface dataset:
Geochemical and geochronological studies of Abor volcanic rocks of eastern Himalaya
Authors: Baral Upendra , Ding Lin , Goswami Tapos Kumar , Sarma Mondip , Jan MQ , Wang Chao , Aminov Jovid , Qasim Muhammad , Bezbaruah Devojit 
Published: September 2021

The Indian Plate began drifting northward after the Gondwana breakup and collided with the Eurasian Plate during the Early Cenozoic, resulting in the consequential development of the Himalayan–Tibetan Orogeny. Several microcontinents were rifted from Gondwana and amalgamated with the Indian Plate, resulting in magmatism along the continental margin. The Abor volcanic rocks (AVRs) in the eastern Himalaya represent one of such magmatism, the emplacement mechanism, and the timing of which is still a topic of debate. The AVR comprises mafic and silicic rocks; the present study concerns the petrography and geochemistry of the mafic rocks. U–Pb geochronology on three samples shows the weighted mean age of 130 ± 1 Ma, 143 ± 1.2 Ma, and 155 ± 16 Ma. Whole‐rock geochemistry of eight samples shows Mg# of 45.48 to 57.7, except for one sample with 37.4, variable contents of CaO (4.4–9.5 wt%), K2O (0.1–2.6%), Lost on ignition (LOI) (0.9–3.6 wt%; average 2.4), and K2O/Na2O ratios (0.02–0.6 with a single one 1.0), Y/Nb (0.55–1.66, with one value of 2.44), and medium to high Zr/Nb (10.1–14.1) and Zr/Y (5.4–18.14). The Sr‐isotopic results from 11 samples show that the initial 87Sr/86Sr ratios vary between 0.7049 and 0.7110, and εNd(t) values range from +1.176 to −2.250. Geochemical and isotopic data suggest that the studied AVRs (mafic) are of subalkaline tholeiitic affinity. These volcanic rocks have continental intraplate characteristics and are sourced from the metasomatized mantle during the rifting event of the Indian subcontinent from Gondwana during Late Jurassic to Early Cretaceous.
Impact of new cancer therapies on outpatient treatment delivery for colorectal cancer: A population‐based study
Authors: Chen Leo , Speers Caroline H. , Cheung Winson Y. , Spinelli John J. , Kennecke Hagen F. 
Published: September 2021

AbstractWe investigated the impact of new systemic therapies approved in Canada for colorectal cancer on the frequency, intensity and duration of oncology clinic and infusion visits over five treatment phases from diagnosis (P1, P3) to treatment (P2, P4) of primary and metastatic disease, respectively, and during the last 6 months of life (P5). In total, 15,157 adult patients with newly diagnosed colorectal cancer and referred between 2000 and 2012 to any cancer clinic in British Columbia, Canada, were included. Frequency, intensity and duration of medical oncology clinic visits (CVs), oncology infusions (OIs) and oncology prescriptions (OPs) were measured by treatment phase. Mean, total and adjusted total duration for CVs increased for P1–5. CVs increased in P1–5, and in P1–4 when adjusted by treatment length. Adjusted and unadjusted OIs decreased in P1 coinciding with the introduction of an oral treatment option, but increased in P2–5. Mean OI duration increased in P1–5, while total and adjusted total decreased in P1 and increased in P2–5. OPs increased in P2–4, but were unchanged in P1 and P5. Multi‐fold increases in resources and time required per patient were also observed, which have significant implications for demand projections in cancer care planning and delivery. In conclusion, patients required more visits in almost all treatment phases, visits on average took longer and patients were in treatment for longer periods of time.
LncRNA CAIF suppresses LPS‐induced inflammation and apoptosis of cardiomyocytes through regulating miR‐16 demethylation
Authors: Wang Yan , Zhang Yi 
Published: September 2021

AbstractBackgroundThe long noncoding RNA, cardiac autophagy inhibitory factor (CAIF), and microRNA (miR)‐16 are reported to be involved in lipopolysaccharide (LPS)‐induced inflammatory responses and cell apoptosis in many diseases. Herein, we investigated the interaction between CAIF and miR‐16 in sepsis‐induced chronic heart failure (CHF).MethodsThe expression of CAIF and miR‐16 in plasma samples from sepsis‐induced CHF patients (n = 60) and healthy controls (n = 60) were measured using quantitative reverse‐transcription polymerase chain reaction (qRT‐PCR). The correlations between CAIF and miR‐16 across plasma samples from patients with sepsis‐induced CHF and healthy controls were analyzed using linear regression. The messenger RNA (mRNA) levels of inducible nitric oxide synthase, C‐C motif chemokine 2 (CCL2), growth‐regulated alpha protein (CXCL1), and interleukin‐6 (IL‐6) were evaluated using qRT‐PCR while nuclear factor κB activation was evaluated using luciferase assay.ResultsThe expression levels of CAIF and miR‐16 were downregulated in the plasma of sepsis‐induced CHF patients and were positively correlated in these patients. In cardiomyocytes, LPS treatment dose‐dependently decreased CAIF and miR‐16 levels. CAIF overexpression increased miR‐16 expression by demethylating miR‐16. CAIF and/or miR‐16 overexpression suppressed LPS‐induced CCL2, CXCL1, and IL‐6 expression at both the mRNA and protein levels. Analysis of cell apoptosis and western blot analysis showed that CAIF and/or miR‐16 overexpression inhibited LPS‐induced cardiomyocyte apoptosis by reducing Bax and cleaved caspase 3 levels and enhancing Bcl‐2 levels.ConclusionOur study is the first to report the abnormal expression of CAIF and miR‐16 in heart disease. CAIF plays a protective role in sepsis‐induced CHF by inhibiting cardiomyocyte apoptosis and inflammation, possibly by regulating miR‐16 demethylation.
Encapsulation and differentiation of adipose‐derived mesenchymal stem cells in a biomimetic purine cross‐linked chitosan sponge
Authors: Karoichan Antoine , Baudequin Timothée , Al‐Jallad Hadil , Tabrizian Maryam 
Published: September 2021

AbstractMesenchymal stem cells derived from adipose tissue have become a widely investigated cell source to use in tissue engineering applications. However, an optimal delivery scaffold for these cells is still needed. A rapidly gelling, injectable chitosan sponge was proposed in this study as a potential candidate for a suitable delivery scaffold. The results demonstrated the ability to encapsulate the stem cells at a 97.6% encapsulation efficiency and that the cells maintain their viability within the sponge. With the potential of using this scaffold for bone tissue engineering, ALP activity assay and fluorescent imaging for osteocalcin proved the ability to differentiate the encapsulated cells into the osteogenic lineage. Furthermore, co‐encapsulation of pyrophosphatase within the sponge was investigated as a method to overcome the inhibitory effects that the sponge degradation by‐products have on mineralization. Alizarin Red S staining demonstrated the beneficial effects of adding pyrophosphatase, where a significant increase in mineralization levels was achieved.
Serum Circ‐FAF1/Circ‐ELP3: A novel potential biomarker for breast cancer diagnosis
Authors: Omid‐Shafaat Ramtin , Moayeri Hassan , Rahimi Karim , Menbari Mohammad‐Nazir , Vahabzadeh Zakaria , Hakhamaneshi Mohammad‐Saied , Nouri Bijan , Ghaderi Bayazid , Abdi Mohammad 
Published: September 2021

AbstractBackgroundRecently, measurement of serum circular RNAs (circRNAs) as a non‐invasive tumor marker has been considered more. We designed the present study to investigate the diagnostic efficiency of serum Circ‐ELP3 and Circ‐FAF1, separately and simultaneously, for diagnosis of patients with breast cancer.MethodsSeventy‐eight female patients diagnosed as primary breast cancer participated in this study. We measured the level of circRNAs in serum specimens of the studied subjects. A receiver operating characteristic (ROC) curve was plotted and the diagnostic efficiency for both circRNAs was determined.ResultsCompared to non‐cancerous controls, Circ‐ELP3 was upregulated in breast cancer patients (p‐value = 0.004). On the other hand, serum Circ‐FAF1 was seen to be decreased in breast cancer patients than controls (p‐value = 0.001). According to ROC curve results, the area under the curve (AUC) for Circ‐ELP3 and Circ‐FAF1 was 0.733 and 0.787, respectively. Furthermore, the calculated sensitivity and specificity for Circ‐ELP3 and Circ‐FAF1 were 65, 64% and 77, 74%, respectively. Merging both circRNAs increased the diagnostic efficiency, with a better AUC, sensitivity and specificity values of 0.891, 96 and 62%, respectively.ConclusionBriefly, our results revealed the high diagnostic value for combined circRNAs panel, including Circ‐ELP3 and Circ‐FAF1 as a non‐invasive marker, in detection of breast carcinomas.
Global HIV mortality trends among children on antiretroviral treatment corrected for under‐reported deaths: an updated analysis of the International epidemiology Databases to Evaluate AIDS collaboration
Authors: Kassanjee Reshma , Johnson Leigh F. , Zaniewski Elizabeth , Ballif Marie , Christ Benedikt , Yiannoutsos Constantin T. , Nyakato Patience , Desmonde Sophie , Edmonds Andrew , Sudjaritruk Tavitiya , Pinto Jorge , Vreeman Rachel , Dahourou Désiré Lucien , Twizere Christelle , Kariminia Azar , Carlucci James G. , Kasozi Charles , Davies Mary‐Ann ,   the International epidemiology Databases to Evaluate AIDS (IeDEA) Collaboration
Published: September 2021

AbstractIntroductionThe Joint United Nations Programme on HIV/AIDS (UNAIDS) projections of paediatric HIV prevalence and deaths rely on the International epidemiology Databases to Evaluate AIDS (IeDEA) consortium for mortality estimates among children living with HIV (CHIV) receiving antiretroviral therapy (ART). Previous estimates, based on data through 2014, may no longer be accurate due to expanded paediatric HIV care and treatment eligibility, and the possibility of unreported deaths in CHIV considered lost to follow‐up (LTFU). We therefore estimated all‐cause mortality and its trends in CHIV (<15 years old) on ART using extended and new IeDEA data.MethodsWe analysed (i) IeDEA observational data from CHIV in routine care globally, and (ii) novel data from an IeDEA tracing study that determined outcomes in a sample of CHIV after being LTFU in southern Africa. We included 45,711 CHIV on ART during 2004 to 2017 at 72 programmes in Africa, Asia‐Pacific and Latin America. We used mixed effects Poisson regression to estimate mortality by age, sex, CD4 at ART start, time on ART, region and calendar year. For Africa, in an adjusted analysis that accounts for unreported deaths among those LTFU, we first modified the routine data by simulating mortality outcomes within six months after LTFU, based on a Gompertz survival model fitted to the tracing data (n = 221).ResultsObserved mortality rates were 1.8 (95% CI: 1.7 to 1.9) and 9.4 (6.3 to 13.4) deaths per 100 person‐years in the routine and tracing data, respectively. We found strong evidence of higher mortality at shorter ART durations, lower CD4 values, and in infancy. Averaging over covariate patterns, the adjusted mortality rate was 54% higher than the unadjusted rate. In unadjusted analyses, mortality reduced by an average 60% and 73% from 2005 to 2017, within and outside of Africa, respectively. In the adjusted analysis for Africa, this temporal reduction was 42%.ConclusionsMortality rates among CHIV have decreased substantially over time. However, when accounting for worse outcomes among those LTFU, mortality estimates increased and temporal improvements were slightly reduced, suggesting caution in interpreting analyses based only on programme data. The improved and updated IeDEA estimates on mortality among CHIV on ART support UNAIDS efforts to accurately model global HIV statistics.
Disease progression and mortality with untreated HIV infection: evidence synthesis of HIV seroconverter cohorts, antiretroviral treatment clinical cohorts and population‐based survey data
Authors: Glaubius Robert , Kothegal Nikhil , Birhanu Sehin , Jonnalagadda Sasi , Mahiane Severin Guy , Johnson Leigh F. , Brown Tim , Stover John , Mangal Tara D. , Pantazis Nikos , Eaton Jeffrey W. 
Published: September 2021

AbstractIntroductionModel‐based estimates of key HIV indicators depend on past epidemic trends that are derived based on assumptions about HIV disease progression and mortality in the absence of antiretroviral treatment (ART). Population‐based HIV Impact Assessment (PHIA) household surveys conducted between 2015 and 2018 found substantial numbers of respondents living with untreated HIV infection. CD4 cell counts measured in these individuals provide novel information to estimate HIV disease progression and mortality rates off ART.MethodsWe used Bayesian multi‐parameter evidence synthesis to combine data on (1) cross‐sectional CD4 cell counts among untreated adults living with HIV from 10 PHIA surveys, (2) survival after HIV seroconversion in East African seroconverter cohorts, (3) post‐seroconversion CD4 counts and (4) mortality rates by CD4 count predominantly from European, North American and Australian seroconverter cohorts. We used incremental mixture importance sampling to estimate HIV natural history and ART uptake parameters used in the Spectrum software. We validated modelled trends in CD4 count at ART initiation against ART initiator cohorts in sub‐Saharan Africa.ResultsMedian untreated HIV survival decreased with increasing age at seroconversion, from 12.5 years [95% credible interval (CrI): 12.1–12.7] at ages 15–24 to 7.2 years (95% CrI: 7.1–7.7) at ages 45–54. Older age was associated with lower initial CD4 counts, faster CD4 count decline and higher HIV‐related mortality rates. Our estimates suggested a weaker association between ART uptake and HIV‐related mortality rates than previously assumed in Spectrum. Modelled CD4 counts in untreated people living with HIV matched recent household survey data well, though some intercountry variation in frequencies of CD4 counts above 500 cells/mm3 was not explained. Trends in CD4 counts at ART initiation were comparable to data from ART initiator cohorts. An alternate model that stratified progression and mortality rates by sex did not improve model fit appreciably.ConclusionsSynthesis of multiple data sources results in similar overall survival as previous Spectrum parameter assumptions but implies more rapid progression and longer survival in lower CD4 categories. New natural history parameter values improve consistency of model estimates with recent cross‐sectional CD4 data and trends in CD4 counts at ART initiation.
Naomi: a new modelling tool for estimating HIV epidemic indicators at the district level in sub‐Saharan Africa
Authors: Eaton Jeffrey W. , Dwyer‐Lindgren Laura , Gutreuter Steve , O'Driscoll Megan , Stevens Oliver , Bajaj Sumali , Ashton Rob , Hill Alexandra , Russell Emma , Esra Rachel , Dolan Nicolas , Anifowoshe Yusuf O. , Woodbridge Mark , Fellows Ian , Glaubius Robert , Haeuser Emily , Okonek Taylor , Stover John , Thomas Matthew L. , Wakefield Jon , Wolock Timothy M. , Berry Jonathan , Sabala Tomasz , Heard Nathan , Delgado Stephen , Jahn Andreas , Kalua Thokozani , Chimpandule Tiwonge , Auld Andrew , Kim Evelyn , Payne Danielle , Johnson Leigh F. , FitzJohn Richard G. , Wanyeki Ian , Mahy Mary I. , Shiraishi Ray W. 
Published: September 2021

AbstractIntroductionHIV planning requires granular estimates for the number of people living with HIV (PLHIV), antiretroviral treatment (ART) coverage and unmet need, and new HIV infections by district, or equivalent subnational administrative level. We developed a Bayesian small‐area estimation model, called Naomi, to estimate these quantities stratified by subnational administrative units, sex, and five‐year age groups.MethodsSmall‐area regressions for HIV prevalence, ART coverage and HIV incidence were jointly calibrated using subnational household survey data on all three indicators, routine antenatal service delivery data on HIV prevalence and ART coverage among pregnant women, and service delivery data on the number of PLHIV receiving ART. Incidence was modelled by district‐level HIV prevalence and ART coverage. Model outputs of counts and rates for each indicator were aggregated to multiple geographic and demographic stratifications of interest. The model was estimated in an empirical Bayes framework, furnishing probabilistic uncertainty ranges for all output indicators. Example results were presented using data from Malawi during 2016–2018.ResultsAdult HIV prevalence in September 2018 ranged from 3.2% to 17.1% across Malawi's districts and was higher in southern districts and in metropolitan areas. ART coverage was more homogenous, ranging from 75% to 82%. The largest number of PLHIV was among ages 35 to 39 for both women and men, while the most untreated PLHIV were among ages 25 to 29 for women and 30 to 34 for men. Relative uncertainty was larger for the untreated PLHIV than the number on ART or total PLHIV. Among clients receiving ART at facilities in Lilongwe city, an estimated 71% (95% CI, 61% to 79%) resided in Lilongwe city, 20% (14% to 27%) in Lilongwe district outside the metropolis, and 9% (6% to 12%) in neighbouring Dowa district. Thirty‐eight percent (26% to 50%) of Lilongwe rural residents and 39% (27% to 50%) of Dowa residents received treatment at facilities in Lilongwe city.ConclusionsThe Naomi model synthesizes multiple subnational data sources to furnish estimates of key indicators for HIV programme planning, resource allocation, and target setting. Further model development to meet evolving HIV policy priorities and programme need should be accompanied by continued strengthening and understanding of routine health system data.
Accounting for misclassified and unknown cause of death data in vital registration systems for estimating trends in HIV mortality
Authors: Kyu Hmwe H. , Jahagirdar Deepa , Cunningham Matthew , Walters Magdalene , Brewer Edmond , Novotney Amanda , Wool Eve , Dippennar Ilse , Sharara Fablina , Han Chieh , Balassyano Shelly , Bertolacci Greg , Murray Christopher J. L. , Naghavi Mohsen 
Published: September 2021

AbstractIntroductionMisclassification of HIV deaths can substantially diminish the usefulness of cause of death data for decision‐making. In this study, we describe the methods developed by the Global Burden of Disease Study to account for the misclassified cause of death data from vital registration systems for estimating HIV mortality in 132 countries and territories.MethodsThe cause of death data were obtained from the World Health Organization Mortality Database and official country‐specific mortality databases. We implemented two steps to adjust the raw cause of death data: (1) redistributing garbage codes to underlying causes of death, including HIV/AIDS by applying methods, such as analysis of multiple cause data and proportional redistribution, and (2) reassigning HIV deaths misclassified as other causes to HIV/AIDS by examining the age patterns of underlying causes in location and years with and without HIV epidemics.ResultsIn 132 countries, during the period from 1990 to 2018, 1,848,761 deaths were reported as caused by HIV/AIDS. After garbage code redistribution in these 132 countries, this number increased to 4,165,015 deaths. An additional 1,944,291 deaths were added through correction of HIV deaths misclassified as other causes in 44 countries. The proportion of HIV deaths derived from garbage code redistribution decreased over time, from 0.4 in 1990 to 0.1 in 2018. The proportion of deaths derived from HIV misclassification correction peaked at 0.4 in 2006 and declined afterwards to 0.08 in 2018. The greatest contributors to garbage code redistribution were “immunodeficiency antibody” (ICD 9: 279‐279.1; ICD 10: D80‐D80.9) and “immunodeficiency other” (ICD 9: 279, 279.5‐279.9; ICD 10: D83‐D84.9, D89, D89.8‐D89.9), which together contributed 77% of all redistributed deaths at their peak in 1995. Respiratory tuberculosis (ICD 9: 010–012.9; ICD 10: A10‐A14, A15‐A16.9) contributed the greatest proportion of all HIV misclassified deaths (25–62% per year) over the most years.ConclusionsCorrecting for miscoding and misclassification of cause of death data can enhance the utility of the data for analyzing trends in HIV mortality and tracking progress toward the Sustainable Development Goal targets.
The rhipidoglossan radula: Formation and development in Margarites helicinus Phipps, 1774 (Trochoidea, Vetigastropoda)
Authors: Vortsepneva Elena , Herbert David G. , Kantor Yuri 
Published: September 2021

AbstractThe gastropod radula exhibits exceptional morphological variability. Despite this enormous diversity, the main patterns of synthesis of the teeth and radula membrane, characteristic of different groups can be identified. The rhipidoglossan radula contains numerous teeth in each transverse row and was found in phylogenetically distant groups of Gastropoda. Studying radula formation through stages of ontogeny in species with this type of radula is important in determining the main patterns of radula formation in gastropods. We studied the formation of the radula during development of one species of trochid vetigastropod, Margarites helicinus, using light and electron microscopy as well as confocal laser scanning microscopy. The adult radula is formed in the blind end of the radular sac, which bifurcates into two horns in vetigastropods. The numerous marginal teeth are synthesized in these horns while the central and lateral teeth form in the region where the horns fuse. This morphology of the formation zone appears to be a common pattern for all vetigastropods. The juvenile radula of M. helicinus consists of seven teeth per transverse row and its formation in the radular sac differs significantly from that in the adult. In the juvenile, the formation zone of the radular sac is not split into two horns, and the teeth and radular membrane are synthesized by relatively few, uniform cells. This organization of the larval radular sac is thought to represent a widely occurring larval pattern potentially present in all groups of gastropods. It is associated with early formation of all organs by few cells rather than representing a phylogenetic trait.
Training data distribution significantly impacts the estimation of tissue microstructure with machine learning
Authors: Gyori Noemi G. , Palombo Marco , Clark Christopher A. , Zhang Hui , Alexander Daniel C. 
Published: September 2021

PurposeSupervised machine learning (ML) provides a compelling alternative to traditional model fitting for parameter mapping in quantitative MRI. The aim of this work is to demonstrate and quantify the effect of different training data distributions on the accuracy and precision of parameter estimates when supervised ML is used for fitting.MethodsWe fit a two‐ and three‐compartment biophysical model to diffusion measurements from in‐vivo human brain, as well as simulated diffusion data, using both traditional model fitting and supervised ML. For supervised ML, we train several artificial neural networks, as well as random forest regressors, on different distributions of ground truth parameters. We compare the accuracy and precision of parameter estimates obtained from the different estimation approaches using synthetic test data.ResultsWhen the distribution of parameter combinations in the training set matches those observed in healthy human data sets, we observe high precision, but inaccurate estimates for atypical parameter combinations. In contrast, when training data is sampled uniformly from the entire plausible parameter space, estimates tend to be more accurate for atypical parameter combinations but may have lower precision for typical parameter combinations.ConclusionThis work highlights that estimation of model parameters using supervised ML depends strongly on the training‐set distribution. We show that high precision obtained using ML may mask strong bias, and visual assessment of the parameter maps is not sufficient for evaluating the quality of the estimates.