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MicroRNAs (miRNAs) are small RNAs that suppress gene expression by their interaction with 3’untranslated region of specific target mRNAs. Although the dysregulation of miRNAs has been identified in human cancer, only a few of these miRNAs have been functionally documented in breast cancer. Thus, defining the important miRNA and functional target involved in chemoresistance is an urgent need for human breast cancer treatment. In this study, we, for the first time, identified a key role of miRNA 520h (miR-520h) in drug resistance. Through protecting cells from paclitaxel-induced apoptosis, expression of miR-520h promoted the drug resistance of human breast cancer cells. Bioinformatics prediction, compensatory mutation and functional validation further confirmed the essential role of miR-520h-suppressed Death-associated protein kinase 2 (DAPK2) expression, as restoring DAPK2 abolished miR-520h-promoted drug resistance, and knockdown of DAPK2 mitigated cell death caused by the depletion of miR-520h. Furthermore, we observed that higher level of miR-520h is associated with poor prognosis and lymph node metastasis in human breast cancer patients. These results show that miR-520h is not only an independent prognostic factor, but is also a potential functional target for future applications in cancer therapeutics.

Assimilation of remotely sensed soil moisture data (SM-DA) to correct soil water stores of rainfall-runoff models has shown skill in improving streamflow prediction. In the case of large and sparsely monitored catchments, SM-DA is a particularly attractive tool. Within this context, we assimilate satellite soil moisture (SM) retrievals from the Advanced Microwave Scanning Radiometer (AMSR-E), the Advanced Scatterometer (ASCAT) and the Soil Moisture and Ocean Salinity (SMOS) instrument, using an Ensemble Kalman filter to improve operational flood prediction within a large (> 40 000 km2) semi-arid catchment in Australia. We assess the importance of accounting for channel routing and the spatial distribution of forcing data by applying SM-DA to a lumped and a semi-distributed scheme of the probability distributed model (PDM). Our scheme also accounts for model error representation by explicitly correcting bias in soil moisture and streamflow in the ensemble generation process, and for seasonal biases and errors in the satellite data. Before assimilation, the semi-distributed model provided a more accurate streamflow prediction (Nash–Sutcliffe efficiency, NSE = 0.77) than the lumped model (NSE = 0.67) at the catchment outlet. However, this did not ensure good performance at the \"ungauged\" inner catchments (two of them with NSE below 0.3). After SM-DA, the streamflow ensemble prediction at the outlet was improved in both the lumped and the semi-distributed schemes: the root mean square error of the ensemble was reduced by 22 and 24%, respectively; the false alarm ratio was reduced by 9% in both cases; the peak volume error was reduced by 58 and 1%, respectively; the ensemble skill was improved (evidenced by 12 and 13% reductions in the continuous ranked probability scores, respectively); and the ensemble reliability was increased in both cases (expressed by flatter rank histograms). SM-DA did not improve NSE. Our findings imply that even when rainfall is the main driver of flooding in semi-arid catchments, adequately processed satellite SM can be used to reduce errors in the model soil moisture, which in turn provides better streamflow ensemble prediction. We demonstrate that SM-DA efficacy is enhanced when the spatial distribution in forcing data and routing processes are accounted for. At ungauged locations, SM-DA is effective at improving some characteristics of the streamflow ensemble prediction; however, the updated prediction is still poor since SM-DA does not address the systematic errors found in the model prior to assimilation.

Remote sensing, in situ networks and models are now providing unprecedented information for environmental monitoring. To conjunctively use multi-source data nominally representing an identical variable, one must resolve biases existing between these disparate sources, and the characteristics of the biases can be non-trivial due to spatio-temporal variability of the target variable, inter-sensor differences with variable measurement supports. One such example is of soil moisture (SM) monitoring. Triple collocation (TC) based bias correction is a powerful statistical method that is increasingly being used to address this issue, but is only applicable to the linear regime, whereas the non-linear method of statistical moment matching is susceptible to unintended biases originating from measurement error. Since different physical processes that influence SM dynamics may be distinguishable by their characteristic spatio-temporal scales, we propose a multi-timescale linear bias model in the framework of a wavelet-based multi-resolution analysis (MRA). The joint MRA-TC analysis was applied to demonstrate scale-dependent biases between in situ, remotely sensed and modelled SM, the influence of various prospective bias correction schemes on these biases, and lastly to enable multi-scale bias correction and data-adaptive, non-linear de-noising via wavelet thresholding.

The International Union of Immunological Societies (IUIS) expert committee (EC) on Inborn Errors of Immunity (IEI) reports here the 2022 updated phenotypic classification, which accompanies and complements the most-recent genotypic classification. This phenotypic classification is aimed for clinicians at the bedside and focuses on clinical features and laboratory phenotypes of specific IEI. In this classification, 485 IEI underlying phenotypes as diverse as infection, malignancy, allergy, auto-immunity and auto-inflammation are described, including 55 novel monogenic defects and 1 autoimmune phenocopy. Therefore, all 485 diseases of the genetic classification are presented in this paper in the form of colored tables with essential clinical or immunological phenotype entries.

The general relationships between vegetation and water yield under different climatic regimes are well established at a small watershed scale in the past century. However, applications of these basic theories to evaluate the regional effects of land cover change on water resources remain challenging due to the complex interactions of vegetation and climatic variability and hydrologic processes at the large scale. The objective of this study was to explore ways to examine the spatial and temporal effects of a large ecological restoration project on water yield across the Loess Plateau region in northern China. We estimated annual water yield as the difference between precipitation input and modelled actual evapotranspiration (ET) output. We constructed a monthly ET model using published ET data derived from eddy flux measurements and watershed streamflow data. We validated the ET models at a watershed and regional levels. The model was then applied to examine regional water yield under land cover change and climatic variability during the implementation of the Grain-for-Green (GFG) project during 1999–2007. We found that water yield in 38% of the Loess Plateau area might have decreased (1–48 mm per year) as a result of land cover change alone. However, combined with climatic variability, 37% of the study area might have seen a decrease in water yield with a range of 1–54 mm per year, and 35% of the study area might have seen an increase with a range of 1–10 mm per year. Across the study region, climate variability masked or strengthened the water yield response to vegetation restoration. The absolute annual water yield change due to vegetation restoration varied with precipitation regimes with the highest in wet years, but the relative water yield changes were most pronounced in dry years. We concluded that the effects of land cover change associated with ecological restoration varied greatly over time and space and were strongly influenced by climatic variability in the arid region. The current regional vegetation restoration projects have variable effects on local water resources across the region. Land management planning must consider the influences of spatial climate variability and long-term climate change on water yield to be more effective for achieving environmental sustainability.

We present a statistical study of prominence and filament eruptions observed by the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO). Several properties are recorded for 904 events that were culled from the Heliophysics Event Knowledgebase (HEK) and incorporated into an online catalog for general use. These characteristics include the filament and eruption type, eruption symmetry and direction, apparent twisting and writhing motions, and the presence of vertical threads and coronal cavities. Associated flares and white-light coronal mass ejections (CME) are also recorded. Total rates are given for each property along with how they differ among filament types. We also examine the kinematics of 106 limb events to characterize the distinct slow- and fast-rise phases often exhibited by filament eruptions. The average fast-rise onset height, slow-rise duration, slow-rise velocity, maximum field-of-view (FOV) velocity, and maximum FOV acceleration are 83 Mm, 4.4 hours, 2.1 km s −1 , 106 km s −1 , and 111 m s −2 , respectively. All parameters exhibit lognormal probability distributions similar to that of CME speeds. A positive correlation between latitude and fast-rise onset height is found, which we attribute to a corresponding negative correlation in the average vertical magnetic field gradient, or decay index, estimated from potential field source surface (PFSS) extrapolations. We also find the decay index at the fast-rise onset point to be 1.1 on average, consistent with the critical instability threshold theorized for straight current channels. Finally, we explore relationships between the derived kinematics properties and apparent twisting motions. We find that events with evident twist have significantly faster CME speeds and significantly lower fast-rise onset heights, suggesting relationships between these values and flux rope helicity.

Recent advances in materials, mechanics and design have led to the development of ultrathin, lightweight electronic devices that can conformally interface with human skin. With few exceptions, these devices rely on electrical power to support sensing, wireless communication and signal conditioning. Unfortunately, most sources of such power consist of batteries constructed using hazardous materials, often with form factors that frustrate incorporation into skin-like, or epidermal, electronic devices. Here we report a biocompatible, sweat-activated battery technology that can be embedded within a soft, microfluidic platform. The battery can be used in a detachable electronic module that contains wireless communication and power management systems, and is capable of continuous on-skin recording of physiological signals. To illustrate the practical utility of our approach, we show using human trials that the sweat-activated batteries can operate hybrid microfluidic/microelectronic systems that simultaneously monitor heart rate, sweat chloride and sweat pH. Sweat-activated, biocompatible batteries can be used to power flexible on-skin electronic systems that monitor and wirelessly transmit physiological signals.

Secondary mutation of epidermal growth factor receptor (EGFR) resulting in drug resistance is one of the most critical issues in lung cancer therapy. Several drugs are being developed to overcome EGFR tyrosine kinase inhibitor (TKI) resistance. Here, we report that pyruvate kinase M2 (PKM2) stabilized mutant EGFR protein by direct interaction and sustained cell survival signaling in lung cancer cells. PKM2 silencing resulted in markedly reduced mutant EGFR expression in TKI-sensitive or -resistant human lung cancer cells, and in inhibition of tumor growth in their xenografts, concomitant with downregulation of EGFR-related signaling. Mechanistically, PKM2 directly interacted with mutant EGFR and heat-shock protein 90 (HSP90), and thus stabilized EGFR by maintaining its binding with HSP90 and co-chaperones. Stabilization of EGFR relied on dimeric PKM2, and the protein half-life of mutant EGFR decreased when PKM2 was forced into its tetramer form. Clinical levels of PKM2 positively correlated with mutant EGFR expression and with patient outcome. These results reveal a previously undescribed non-glycolysis function of PKM2 in the cytoplasm, which contribute to EGFR-dependent tumorigenesis and provide a novel strategy to overcome drug resistance to EGFR TKIs.

Single‐specimen analysis of planktic foraminiferal geochemistry has gained increasing popularity for its potential in reconstructing climate variability. However, the comparability between single‐specimen and conventional multi‐specimen Mg/Ca data remains unclear, which has raised questions concerning the suitability of multi‐specimen Mg/Ca‐temperature calibrations for single‐specimen data. This study developed and evaluated the effects of four single‐specimen cleaning procedures on the Mg/Ca ratio of Trilobatus sacculifer. These procedures varied in their inclusion or exclusion of the reductive step and heating for chemical reactions. The most effective single‐specimen cleaning procedure (procedure Dsingle) incorporated the oxidative step while excluding the reductive step and heating. This procedure was subsequently applied to five additional planktic foraminifera species. With procedure Dsingle, we obtained statistically indistinguishable mean Mg/Ca values for single‐specimen and multi‐specimen samples of T. sacculifer, Orbulina universa, and Pulleniatina obliquiloculata, regardless of the intensity of the multi‐specimen cleaning procedures. For single‐specimen samples of Globigerinoides ruber and Neogloboquadrina dutertrei, the mean Mg/Ca values only matched those of the multi‐specimen samples when procedures excluded the reductive step and heating. In contrast, single‐specimen mean Mg/Ca values of Globorotalia menardii were consistently higher than those obtained through multi‐specimen cleaning. The mean Mg/Ca differences between single‐specimen and multi‐specimen cleaning procedures across species are likely attributable to differences in the microstructure of the calcite tests. In summary, when cleaning procedures involving identical steps and heating conditions were utilized, both single‐specimen and multi‐specimen analyses yielded comparable mean Mg/Ca values, suggesting that the multi‐specimen Mg/Ca calibrations are applicable to single‐specimen data. Plain Language Summary Understanding past climate swings is essential for predicting future extremes. In this context, sea surface temperature (SST) estimates provide valuable insights and can be derived from the elemental (Mg/Ca) ratio in the shell of foraminifera, which are single‐celled marine organisms. To obtain accurate Mg/Ca measurements, contaminants such as clay, organic matter, and coatings must be removed from the shells using a multi‐stage cleaning process. However, intense chemical cleaning procedures can alter shell Mg/Ca ratios. Climate variability reconstructions typically use single‐shell samples with low‐intensity cleaning, while temperature equations rely on multiple‐shell samples subjected to higher‐intensity cleaning, raising concerns about the validity of applying these equations to single‐shell data. This study tested how different cleaning intensities affect the Mg/Ca ratios in single‐ and multiple‐shell samples. The effects on Mg/Ca ratios varied with species when reductive cleaning used to remove coatings was included. However, excluding heating and reductive cleaning yielded comparable Mg/Ca values for both sample types. This finding suggests that equations based on multiple‐shell samples can reliably estimate SST from single‐shell samples, thereby improving confidence in climate variability reconstructions. Key Points Comparable Mg/Ca means from single‐ and multi‐specimen analyses for G. ruber, T. sacculifer, O. universa, P. obliquiloculata, and N. dutertrei Single‐specimen Mg/Ca averages of G. menardii are higher than those obtained using multi‐specimen cleaning procedures Multi‐specimen Mg/Ca calibrations are applicable to single‐specimen data obtained using procedure Dsingle

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with a 382-nucleotide deletion (∆382) in the open reading frame 8 (ORF8) region of the genome have been detected in Singapore and other countries. We investigated the effect of this deletion on the clinical features of infection. We retrospectively identified patients who had been screened for the ∆382 variant and recruited to the PROTECT study—a prospective observational cohort study conducted at seven public hospitals in Singapore. We collected clinical, laboratory, and radiological data from patients' electronic medical records and serial blood and respiratory samples taken during hospitalisation and after discharge. Individuals infected with the ∆382 variant were compared with those infected with wild-type SARS-CoV-2. Exact logistic regression was used to examine the association between the infection groups and the development of hypoxia requiring supplemental oxygen (an indicator of severe COVID-19, the primary endpoint). Follow-up for the study's primary endpoint is completed. Between Jan 22 and March 21, 2020, 278 patients with PCR-confirmed SARS-CoV-2 infection were screened for the ∆382 deletion and 131 were enrolled onto the study, of whom 92 (70%) were infected with the wild-type virus, ten (8%) had a mix of wild-type and ∆382-variant viruses, and 29 (22%) had only the ∆382 variant. Development of hypoxia requiring supplemental oxygen was less frequent in the ∆382 variant group (0 [0%] of 29 patients) than in the wild-type only group (26 [28%] of 92; absolute difference 28% [95% CI 14–28]). After adjusting for age and presence of comorbidities, infection with the ∆382 variant only was associated with lower odds of developing hypoxia requiring supplemental oxygen (adjusted odds ratio 0·07 [95% CI 0·00–0·48]) compared with infection with wild-type virus only. The ∆382 variant of SARS-CoV-2 seems to be associated with a milder infection. The observed clinical effects of deletions in ORF8 could have implications for the development of treatments and vaccines. National Medical Research Council Singapore.