The urinary C-terminal telopeptide fragment of type II collagen (uCTX-II) has been reported as the efficient blood-based biomarker for osteoarthritis, which affects knees, hands, spine, and hips. This study reports a sensing strategy with antibody-conjugated gold nanoparticles (GNP) on an interdigitated electrode (IDE) to determine uCTX-II. The GNP-antibody complex was chemically immobilized on the IDE surface through the amine linker. uCTX-II was determined by monitoring the alteration in current upon interacting the GNP-complexed antibody. This strategy was improved the detection by attracting higher uCTX-II molecules, and the detection limit falls in the range of 10-100 pM with an acceptable regression value [y = 0.6254x - 0.4073, R² = 0.9787]. The sensitivity of the detection was recognized at 10 pM. Additionally, upon increasing the uCTX-II concentration, the current changes were increased in a linear fashion. Control detection with nonimmune antibody and control protein do not increase the current level, confirming the specific detection of uCTX-II. This method of detection helps in diagnosing osteoarthritis and its follow-up treatment.
Since its first emergence in 1998 in Malaysia, Nipah virus (NiV) has become a great threat to domestic animals and humans. Sporadic outbreaks associated with human-to-human transmission caused hundreds of human fatalities. Here, we collected all available NiV sequences and combined phylogenetics, molecular selection, structural biology and receptor analysis to study the emergence and adaptive evolution of NiV. NiV can be divided into two main lineages including the Bangladesh and Malaysia lineages. We formly confirmed a significant association with geography which is probably the result of long-term evolution of NiV in local bat population. The two NiV lineages differ in many amino acids; one change in the fusion protein might be involved in its activation via binding to the G protein. We also identified adaptive and positively selected sites in many viral proteins. In the receptor-binding G protein, we found that sites 384, 386 and especially 498 of G protein might modulate receptor-binding affinity and thus contribute to the host jump from bats to humans via the adaption to bind the human ephrin-B2 receptor. We also found that site 1645 in the connector domain of L was positive selected and involved in adaptive evolution; this site might add methyl groups to the cap structure present at the 5'-end of the RNA and thus modulate its activity. This study provides insight to assist the design of early detection methods for NiV to assess its epidemic potential in humans.
Sewage sludge is an important class of bioresources whose energy content could be exploited using pyrolysis technology. However, some harmful trace elements in sewage sludge can escape easily to the gas phase during pyrolysis, increasing the potential of carcinogenic material emissions to the atmosphere. This study investigates emission characteristics of arsenic, cadmium and lead under different pyrolysis conditions for three different sewage sludge samples. The increased temperature (within 723-1123K) significantly promoted the cadmium and lead emissions, but its influence on arsenic emission was not pronounced. The releasing rate order of the three trace elements is volatile arsenic compounds>cadmium>lead in the beginning of pyrolysis. Fast heating rates promoted the emission of trace elements for the sludge containing the highest amount of ash, but exhibited an opposite effect for other studied samples. Overall, the high ash sludge released the least trace elements almost under all reaction conditions.
The Abu Gabra and Bentiu formations are widely distributed within the interior Muglad Basin. Recently, much attention has been paid to study, evaluate and characterize the Abu Gabra Formation as a proven reservoir in Muglad Basin. However, few studies have been documented on the Bentiu Formation which is the main oil/gas reservoir within the basin. Therefore, 33 core samples of the Great Moga and Keyi oilfields (NE Muglad Basin) were selected to characterize the Bentiu Formation reservoir using sedimentological and petrophysical analyses. The aim of the study is to de-risk exploration activities and improve success rate. Compositional and textural analyses revealed two main facies groups: coarse to-medium grained sandstone (braided channel deposits) and fine grained sandstone (floodplain and crevasse splay channel deposits). The coarse to-medium grained sandstone has porosity and permeability values within the range of 19.6% to 32.0% and 1825.6 mD to 8358.0 mD respectively. On the other hand, the fine grained clay-rich facies displays poor reservoir quality as indicated by porosity and permeability ranging from 1.0 to 6.0% and 2.5 to 10.0 mD respectively. A number of varied processes were identified controlling the reservoir quality of the studies samples. Porosity and permeability were enhanced by the dissolution of feldspars and micas, while presence of detrital clays, kaolinite precipitation, iron oxides precipitation, siderite, quartz overgrowths and pyrite cement played negative role on the reservoir quality. Intensity of the observed quartz overgrowth increases with burial depth. At great depths, a variability in grain contact types are recorded suggesting conditions of moderate to-high compactions. Furthermore, scanning electron microscopy revealed presence of micropores which have the tendency of affecting the fluid flow properties in the Bentiu Formation sandstone. These evidences indicate that the Bentiu Formation petroleum reservoir quality is primarily inhibited by grain size, total clay content, compaction and cementation. Thus, special attention should be paid to these inhibiting factors to reduce risk in petroleum exploration within the area.
Forests are major components of the global carbon cycle, providing substantial feedback to atmospheric greenhouse gas concentrations. Our ability to understand and predict changes in the forest carbon cycle--particularly net primary productivity and carbon storage--increasingly relies on models that represent biological processes across several scales of biological organization, from tree leaves to forest stands. Yet, despite advances in our understanding of productivity at the scales of leaves and stands, no consensus exists about the nature of productivity at the scale of the individual tree, in part because we lack a broad empirical assessment of whether rates of absolute tree mass growth (and thus carbon accumulation) decrease, remain constant, or increase as trees increase in size and age. Here we present a global analysis of 403 tropical and temperate tree species, showing that for most species mass growth rate increases continuously with tree size. Thus, large, old trees do not act simply as senescent carbon reservoirs but actively fix large amounts of carbon compared to smaller trees; at the extreme, a single big tree can add the same amount of carbon to the forest within a year as is contained in an entire mid-sized tree. The apparent paradoxes of individual tree growth increasing with tree size despite declining leaf-level and stand-level productivity can be explained, respectively, by increases in a tree's total leaf area that outpace declines in productivity per unit of leaf area and, among other factors, age-related reductions in population density. Our results resolve conflicting assumptions about the nature of tree growth, inform efforts to undertand and model forest carbon dynamics, and have additional implications for theories of resource allocation and plant senescence.
The first evidence for the Higgs boson decay to a Z boson and a photon is presented, with a statistical significance of 3.4 standard deviations. The result is derived from a combined analysis of the searches performed by the ATLAS and CMS Collaborations with proton-proton collision datasets collected at the CERN Large Hadron Collider (LHC) from 2015 to 2018. These correspond to integrated luminosities of around 140 fb^{-1} for each experiment, at a center-of-mass energy of 13 TeV. The measured signal yield is 2.2±0.7 times the standard model prediction, and agrees with the theoretical expectation within 1.9 standard deviations.