A Joint Statistical and Dynamical Assessment of Atmospheric Response to North Pacific Oceanic Variability in CCSM3

ABSTRACT Atmospheric response to North Pacific oceanic variability is assessed in Community Climate System Model, version 3 (CCSM3) using two statistical methods and one dynamical method. All methods identify an equivalent barotropic low response to a warmer sea surface temperature (SST) anomaly in the Kuroshio Extension region (KOE) during early-midwinter. While all three methods capture the major features of the response, the generalized equilibrium feedback assessment method (GEFA) isolates the impact of KOE SST from a complex context, and thus makes itself an excellent choice for similar practice

The mechanisms of Yu Ping Feng San in tracking the cisplatin-resistance by regulating ATP-binding cassette transporter and glutathione S-transferase in lung cancer cells

Cisplatin is one of the first line anti-cancer drugs prescribed for treatment of solid tumors; however, the chemotherapeutic drug resistance is still a major obstacle of cisplatin in treating cancers. Yu Ping Feng San (YPFS), a well-known ancient Chinese herbal combination formula consisting of Astragali Radix, Atractylodis Macrocephalae Rhizoma and Saposhnikoviae Radix, is prescribed as a herbal decoction to treat immune disorders in clinic. To understand the fast-onset action of YPFS as an anti-cancer drug to fight against the drug resistance of cisplatin, we provided detailed analyses of intracellular cisplatin accumulation, cell viability, and expressions and activities of ATP-binding cassette transporters and glutathione S-transferases (GSTs) in YPFS-treated lung cancer cell lines. In cultured A549 or its cisplatin-resistance A549/DDP cells, application of YPFS increased accumulation of intracellular cisplatin, resulting in lower cell viability. In parallel, the activities and expressions of ATP-binding cassette transporters and GSTs were down-regulated in the presence of YPFS. The expression of p65 subunit of NF-κB complex was reduced by treating the cultures with YPFS, leading to a high ratio of Bax/Bcl-2, i.e. increasing the rate of cell death. Prim-O-glucosylcimifugin, one of the abundant ingredients in YPFS, modulated the activity of GSTs, and then elevated cisplatin accumulation, resulting in increased cell apoptosis. The present result supports the notion of YPFS in reversing drug resistance of cisplatin in lung cancer cells by elevating of intracellular cisplatin, and the underlying mechanism may be down regulating the activities and expressions of ATP-binding cassette transporters and GSTs

Screening biomarkers for Sjogren’s Syndrome by computer analysis and evaluating the expression correlations with the levels of immune cells

BackgroundSjögren’s syndrome (SS) is a systemic autoimmune disease that affects about 0.04-0.1% of the general population. SS diagnosis depends on symptoms, clinical signs, autoimmune serology, and even invasive histopathological examination. This study explored biomarkers for SS diagnosis.MethodsWe downloaded three datasets of SS patients’ and healthy pepole’s whole blood (GSE51092, GSE66795, and GSE140161) from the Gene Expression Omnibus (GEO) database. We used machine learning algorithm to mine possible diagnostic biomarkers for SS patients. Additionally, we assessed the biomarkers’ diagnostic value using the receiver operating characteristic (ROC) curve. Moreover, we confirmed the expression of the biomarkers through the reverse transcription quantitative polymerase chain reaction (RT-qPCR) using our own Chinese cohort. Eventually, the proportions of 22 immune cells in SS patients were calculated by CIBERSORT, and connections between the expression of the biomarkers and immune cell ratios were studied.ResultsWe obtained 43 DEGs that were mainly involved in immune-related pathways. Next, 11 candidate biomarkers were selected and validated by the validation cohort data set. Besides, the area under curves (AUC) of XAF1, STAT1, IFI27, HES4, TTC21A, and OTOF in the discovery and validation datasets were 0.903 and 0.877, respectively. Subsequently, eight genes, including HES4, IFI27, LY6E, OTOF, STAT1, TTC21A, XAF1, and ZCCHC2, were selected as prospective biomarkers and verified by RT-qPCR. Finally, we revealed the most relevant immune cells with the expression of HES4, IFI27, LY6E, OTOF, TTC21A, XAF1, and ZCCHC2.ConclusionIn this paper, we identified seven key biomarkers that have potential value for diagnosing Chinese SS patients

Impact of biogenic SOA loading on the molecular composition of wintertime PM2.5 in urban Tianjin: an insight from Fourier transform ion cyclotron resonance mass spectrometry

Biomass burning is one of the key sources of urban aerosols in the North China Plain, especially in winter when the impact of secondary organic aerosols (SOA) formed from biogenic volatile organic compounds (BVOCs) is generally considered to be minor. However, little is known about the influence of biogenic SOA loading on the molecular composition of wintertime organic aerosols. Here, we investigated the water-soluble organic compounds in fine particles (PM2.5) from urban Tianjin by ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Our results show that most of the CHO and CHON compounds were derived from biomass burning; they contain O-poor and highly unsaturated compounds with aromatic rings, which are sensitive to photochemical reactions, and some of which probably contribute to light-absorbing chromophores. Under moderate to high SOA loading conditions, the nocturnal chemistry is more efficient than photooxidation to generate secondary CHO and CHON compounds with high oxygen content. Under low SOA-loading, secondary CHO and CHON compounds with low oxygen content are mainly formed by photochemistry. Secondary CHO compounds are mainly derived from oxidation of monoterpenes. But nocturnal chemistry may be more productive to sesquiterpene-derived CHON compounds. In contrast, the number- and intensity-weight of S-containing groups (CHOS and CHONS) increased significantly with the increase of biogenic SOA-loading, which agrees with the fact that a majority of the S-containing groups are identified as organosulfates and nitrooxy-organosulfates that are derived from the oxidation of BVOCs. Terpenes may be potential major contributors to the chemical diversity of organosulfates and nitrooxy-organosulfates under photo-oxidation. While the nocturnal chemistry is more beneficial to the formation of organosulfates and nitrooxy-organosulfates under low SOA-loading. The SOA-loading is an important factor associating with the oxidation degree, nitrate group content and chemodiversity of nitrooxy-organosulfates. Furthermore, our study suggests that the hydrolysis of nitrooxy-organosulfates is a possible pathway for the formation of organosulfates.</p

Abrupt onset of the Little Ice Age triggered by volcanism and sustained by sea-ice/ocean feedbacks

[1] Northern Hemisphere summer temperatures over the past 8000 years have been paced by the slow decrease in summer insolation resulting from the precession of the equinoxes. However, the causes of superposed century-scale cold summer anomalies, of which the Little Ice Age (LIA) is the most extreme, remain debated, largely because the natural forcings are either weak or, in the case of volcanism, short lived. Here we present precisely dated records of ice-cap growth from Arctic Canada and Iceland showing that LIA summer cold and ice growth began abruptly between 1275 and 1300 AD, followed by a substantial intensification 1430– 1455 AD. Intervals of sudden ice growth coincide with two of the most volcanically perturbed half centuries of the past mil-lennium. A transient climate model simulation shows that explosive volcanism produces abrupt summer cooling at these times, and that cold summers can be maintained by sea-ice/ ocean feedbacks long after volcanic aerosols are removed. Our results suggest that the onset of the LIA can be linked to an unusual 50-year-long episode with four large sulfur-rich explosive eruptions, each with global sulfate loading&gt;60 Tg. The persistence of cold summers is best explained by conse-quent sea-ice/ocean feedbacks during a hemispheric summer insolation minimum; large changes in solar irradiance are not required. Citation: Miller, G. H., et al. (2012), Abrupt onset of the Little Ice Age triggered by volcanism and sustained by sea-ice/ocea

Design Features and Methodological Quality of Researches about Prediction Models Based on Machine Learning in Primary Care: a Scoping Review

Background Researches about prediction models based on machine learning in primary care developed rapidly in recent years, but there are few researches about the design features and methodological quality. Objective To systematacially summarize and analyze the design features and methodological quality of researches about prediction models based on machine learning in primary care. Methods Researches about prediction models based on machine learning in primary care was searched in PubMed, Embase, CNKI, Wanfang Data published from base-building to 2023-02-21, descriptive summary and description methods were used to analyze the basic characteristics of the included literature, types of prediction models, sample size, handling method of missing value, types of machine learning algorithms, model performance evaluation index and prediction efficiency, and model verification method. Results Totally 30 literature were enrolled, involving 106 prediction models, thereinto 17 literature were published between 2021 and 2023; research topics: respiratory disease in 6 literature, tumour in 4 literature, outpatient appointment in 3 literature; sample size over 1 000 in 26 literature (accounting for 86.67%, 95%CI=68.36%-95.64%) ; using machine learning methods to hand missing value in 7 literature; 65 prediction models used tree-based machine learning algorithm, in which random forest was the most frequently used (accounting for 32.08%, 95%CI=23.53%-41.95%) ; 61 prediction models used AUC of ROC or consistency (C statistic) as the differentiation evaluation index (accounting for 57.55%, 95%CI=47.57%-66.97%), but only 14 prediction models reported prediction models (accounting for 13.21%, 95%CI=7.67%-21.50%) ; the differentiation of most of the 106 prediction models was good, but bias risk assessment results of 92 prediction models were high-risk (accounting for 86.79%, 95%CI=78.50%-92.33%) ; only 7 literature involved prediction models conducted the external validation. Conclusion Researches about prediction models based on machine learning in primary care increase gradually in the past three years, in which the topics mainly involve respiratory disease, tumour, outpatient appointment and so on; there are significant difference in sample size and handling method of missing value in the 106 prediction models, most of the 106 prediction models are with good differentiation, but most of them did not conducted the external validation, and the overall risk of bias is relatively high

Predicting the U.S. Drought Monitor Using Precipitation, Soil Moisture, and Evapotranspiration Anomalies. Part II: Intraseasonal Drought Intensification Forecasts

Probabilistic forecasts of U.S. Drought Monitor (USDM) intensification over 2-, 4-, and 8-week time periods are developed based on recent anomalies in precipitation, evapotranspiration, and soil moisture. These statistical forecasts are computed using logistic regression with cross validation. While recent precipitation, evapotranspiration, and soil moisture do provide skillful forecasts, it is found that additional information on the current state of the USDM adds significant skill to the forecasts. The USDM state information takes the form of a metric that quantifies the ‘‘distance’’ from the next-higher drought category using a nondiscrete estimate of the current USDM state. This adds skill because USDM states that are close to the next-higher drought category are more likely to intensify than states that are farther from this threshold. The method shows skill over most of the United States but is most skillful over the north-central United States, where the cross-validated Brier skill score averages 0.20 for both 2- and 4-week forecasts. The 8-week forecasts are less skillful in most locations. The 2- and 4-week probabilities have very good reliability. The 8-week probabilities, on the other hand, are noticeably overconfident. For individual drought events, the method shows the most skill when forecasting high-amplitude flash droughts and when large regions of the United States are experiencing intensifying drought

Assessing the Evolution of Soil Moisture and Vegetation Conditions during a Flash Drought–Flash Recovery Sequence over the South-Central United States

This study examines the evolution of soil moisture, evapotranspiration, vegetation, and atmospheric conditions during an unusual flash drought–flash recovery sequence that occurred across the south-central United States during 2015. This event was characterized by a period of rapid drought intensification (flash drought) during late summer that was terminated by heavy rainfall at the end of October that eliminated the extreme drought conditions over a 2-week period (flash recovery). A detailed analysis was performed using time series of environmental variables derived from meteorological, remote sensing, and land surface modeling datasets. Though the analysis revealed a similar progression of cascading effects in each region, characteristics of the flash drought such as its onset time, rate of intensification, and vegetation impacts differed between regions due to variations in the antecedent conditions and the atmospheric anomalies during its growth. Overall, flash drought signals initially appeared in the near-surface soil moisture, followed closely by reductions in evapotranspiration. Total column soil moisture deficits took longer to develop, especially in the western part of the region where heavy rainfall during the spring and early summer led to large moisture surpluses. Large differences were noted in how land surface models in the North American Land Data Assimilation System depicted soil moisture evolution during the flash drought; however, the models were more similar in their assessment of conditions during the flash recovery period. This study illustrates the need to use multiple datasets to track the evolution and impacts of rapidly evolving flash drought and flash recovery event

Mapping Hydration Dynamics around a β‑Barrel Protein

Protein surface hydration is fundamental to its structure, flexibility, dynamics, and function, but it has been challenging to disentangle their ultimate relationships. Here, we report our systematic characterization of hydration dynamics around a β-barrel protein, rat liver fatty acid-binding protein (rLFABP), to reveal the effect of different protein secondary structures on hydration water. We employed a tryptophan scan to the protein surface one at a time and examined a total of 17 different sites. We observed three types of hydration water relaxation with distinct time scales, from hundreds of femtoseconds to a hundred picoseconds. We also examined the anisotropy dynamics of the corresponding tryptophan side chains and observed two distinct relaxations from tens to hundreds of picoseconds. Integrating our previous findings on α-helical proteins, we conclude the following: (1) The hydration dynamics is highly heterogeneous around the protein surface of both α-helical and β-sheet proteins. The outer-layer water of the hydration shell behave like a bulk and relaxes in hundreds of femtoseconds. The inner-layer water collectively relaxes in two time scales, reorientation motions in a few picoseconds and network restructuring in tens to a hundred picoseconds. (2) The hydration dynamics are always faster than local protein relaxations and in fact drive the protein fluctuations on the picosecond time scale. (3) The hydration dynamics in general are more retarded around β-sheet structures than α-helical motifs. A thicker hydration shell and a more rigid interfacial hydration network are observed in the β-sheet protein. Overall, these findings elucidate the intimate relationship between water–protein interactions and dynamics on the ultrafast time scale