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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 millennium. 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 >60 Tg. The persistence of cold summers is best explained by consequent sea‐ice/ocean feedbacks during a hemispheric summer insolation minimum; large changes in solar irradiance are not required. Key Points Little Ice Age began abruptly in two steps Decadally paced explosive volcanism can explain the onset A sea‐ice/ocean feedback can sustain the abrupt cooling

This study uses the flash drought intensity index (FDII) to develop a multivariate flash drought climatology for the contiguous U.S. using data from 2001 to 2021. The FDII method uses the rate of intensification (FD‐INT) and subsequent drought severity (DRO‐SEV) to determine when a flash drought occurred and the strength of the event. Overall, the results showed that flash drought occurrence and severity varied with season and region and were sensitive to the drought indicator used to compute the FDII. Precipitation‐based indicators identified more flash droughts across the western U.S. whereas soil moisture (SM) and evapotranspiration indicators identified more flash droughts across the central and eastern U.S. When assessed over the entire U.S., the most flash droughts were found when using an evaporative demand indicator. Though FD‐INT was larger than DRO‐SEV across the U.S. for most indicators, regional patterns were also evident in their relative importance. For example, a distinct east‐west gradient was present in the SM and evapotranspiration FD‐INT, with relatively large values in the central and eastern U.S. A combined data set synthesizing information from multiple indicators showed that the strongest flash droughts from a multivariate perspective were located in the central and southeastern U.S. A seasonal analysis revealed a distinct seasonal cycle in flash drought onset across the western and central U.S. Together, the results illustrate the need to use a multivariate framework to identify and characterize the occurrence and severity of flash droughts. Plain Language Summary Flash droughts are characterized by rapid intensification leading to sustained drought conditions that impact natural and human ecosystems. This study used several drought monitoring data sets to develop a multivariate flash drought climatology for the contiguous U.S. that captures both when flash droughts occur and their severity. Overall, the results revealed that flash drought occurrence and severity varied with season and region and were sensitive to the indicator used to characterize these events. Precipitation‐based indicators identified more flash droughts across the western U.S. while SM and evapotranspiration indicators identified more flash droughts across the central and eastern U.S. When assessed over the entire U.S., the most flash droughts were identified when using an indicator of evaporative demand. A combined indicator that synthesizes information from multiple indicators showed that the strongest flash droughts were located in the central and southeastern U.S. A seasonal analysis revealed a distinct seasonal cycle in flash drought occurrence across the western and central U.S. Together, the results illustrate the need to use a multivariate analysis framework to identify and characterize the severity of flash droughts. Key Points A multivariate climatology of flash drought onset and severity is created for the United States using several drought indicators Flash drought occurrence and severity varied with season and region and the indicator used to identify flash drought events The strongest flash droughts when evaluated using a multivariate perspective occurred in the central and southeastern United States

BackgroundSystemic lupus erythematosus (SLE) is an autoimmune illness caused by a malfunctioning immunomodulatory system. China has the second highest prevalence of SLE in the world, from 0.03% to 0.07%. SLE is diagnosed using a combination of immunological markers, clinical symptoms, and even invasive biopsy. As a result, genetic diagnostic biomarkers for SLE diagnosis are desperately needed.MethodFrom the Gene Expression Omnibus (GEO) database, we downloaded three array data sets of SLE patients’ and healthy people’s peripheral blood mononuclear cells (PBMC) (GSE65391, GSE121239 and GSE61635) as the discovery metadata (nSLE = 1315, nnormal = 122), and pooled four data sets (GSE4588, GSE50772, GSE99967, and GSE24706) as the validate data set (nSLE = 146, nnormal = 76). We screened the differentially expressed genes (DEGs) between the SLE and control samples, and employed the least absolute shrinkage and selection operator (LASSO) regression, and support vector machine recursive feature elimination (SVM-RFE) analyze to discover possible diagnostic biomarkers. The candidate markers’ diagnostic efficacy was assessed using the receiver operating characteristic (ROC) curve. The reverse transcription quantitative polymerase chain reaction (RT-qPCR) was utilized to confirm the expression of the putative biomarkers using our own Chinese cohort (nSLE = 13, nnormal = 10). Finally, the proportion of 22 immune cells in SLE patients was determined using the CIBERSORT algorithm, and the correlations between the biomarkers’ expression and immune cell ratios were also investigated.ResultsWe obtained a total of 284 DEGs and uncovered that they were largely involved in several immune relevant pathways, such as type І interferon signaling pathway, defense response to virus, and inflammatory response. Following that, six candidate diagnostic biomarkers for SLE were selected, namely ABCB1, EIF2AK2, HERC6, ID3, IFI27, and PLSCR1, whose expression levels were validated by the discovery and validation cohort data sets. As a signature, the area under curve (AUC) values of these six genes reached to 0.96 and 0.913, respectively, in the discovery and validation data sets. After that, we checked to see if the expression of ABCB1, IFI27, and PLSCR1 in our own Chinese cohort matched that of the discovery and validation sets. Subsequently, we revealed the potentially disturbed immune cell types in SLE patients using the CIBERSORT analysis, and uncovered the most relevant immune cells with the expression of ABCB1, IFI27, and PLSCR1.ConclusionOur study identified ABCB1, IFI27, and PLSCR1 as potential diagnostic genes for Chinese SLE patients, and uncovered their most relevant immune cells. The findings in this paper provide possible biomarkers for diagnosing Chinese SLE patients.

Projected changes in the relative abundance and timing of autumn-winter migration are assessed for seven dabbling duck species across the Mississippi and Atlantic Flyways for the mid- and late 21st century. Species-specific observed relationships are established between cumulative weather severity in autumn-winter and duck population rate of change. Dynamically downscaled projections of weather severity are developed using a high-resolution regional climate model, interactively coupled to a one-dimensional lake model to represent the Great Lakes and associated lake-effect snowfall. Based on the observed relationships and downscaled climate projections of rising air temperatures and reduced snow cover, delayed autumn-winter migration is expected for all species, with the least delays for the Northern Pintail and the greatest delays for the Mallard. Indeed, the Mallard, the most common and widespread duck in North America, may overwinter in the Great Lakes region by the late 21st century. This highlights the importance of protecting and restoring wetlands across the mid-latitudes of North America, including the Great Lakes Basin, because dabbling ducks are likely to spend more time there, which would impact existing wetlands through increased foraging pressure. Furthermore, inconsistency in the timing and intensity of the traditional autumn-winter migration of dabbling ducks in the Mississippi and Atlantic Flyways could have social and economic consequences to communities to the south, where hunting and birdwatching would be affected.

Flash droughts are characterized by a period of rapid intensification over sub-seasonal time scales that culminates in the rapid emergence of new or worsening drought impacts. This study presents a new flash drought intensity index (FDII) that accounts for both the unusually rapid rate of drought intensification and its resultant severity. The FDII framework advances our ability to characterize flash drought because it provides a more complete measure of flash drought intensity than existing classification methods that only consider the rate of intensification. The FDII is computed using two terms measuring the maximum rate of intensification (FD_INT) and average drought severity (DRO_SEV). A climatological analysis using soil moisture data from the Noah land surface model from 1979–2017 revealed large regional and interannual variability in the spatial extent and intensity of soil moisture flash drought across the US. Overall, DRO_SEV is slightly larger over the western and central US where droughts tend to last longer and FD_INT is ~75% larger across the eastern US where soil moisture variability is greater. Comparison of the FD_INT and DRO_SEV terms showed that they are strongly correlated (r = 0.82 to 0.90) at regional scales, which indicates that the subsequent drought severity is closely related to the magnitude of the rapid intensification preceding it. Analysis of the 2012 US flash drought showed that the FDII depiction of severe drought conditions aligned more closely with regions containing poor crop conditions and large yield losses than that captured by the intensification rate component (FD_INT) alone.

Sjögren'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. We 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. We 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. In this paper, we identified seven key biomarkers that have potential value for diagnosing Chinese SS patients.

The response of tropical Pacific SST to increased atmospheric CO₂ concentration is reexamined with a new focus on the latitudinal SST gradient. Available evidence, mainly from climate models, suggests that an important tropical SST fingerprint to global warming is an enhanced equatorial warming relative to the subtropics. This enhanced equatorial warming provides a fingerprint of SST response more robust than the traditionally studied El Niño–like response, which is characterized by the zonal SST gradient. Most importantly, the mechanism of the enhanced equatorial warming differs fundamentally from the El Niño–like response; the former is associated with surface latent heat flux, shortwave cloud forcing, and surface ocean mixing, while the latter is associated with equatorial ocean upwelling and wind-upwelling dynamic ocean–atmosphere feedback.

Previous analyses of the Community Climate System Model, version 3 (CCSM3) standard integration have revealed pronounced multidecadal variability in the Pacific climate system. The purpose of the present work is to investigate physical mechanism underlying this Pacific multidecadal variability (PMV). To better isolate the mechanism that selects the long multidecadal time scale for the PMV, a few specifically designed sensitivity experiments are carried out. When the propagating Rossby waves are blocked in the subtropics from the midbasin, the PMV remains outstanding. In contrast, when the Rossby waves are blocked beyond the subtropics across the entire North Pacific, the PMV is virtually suppressed. It suggests that the PMV relies on propagating Rossby waves in the subpolar Pacific, whereas those in the subtropics are not critical. A novel mechanism of PMV is advanced based on a more comprehensive analysis, which is characterized by a crucial role of the subpolar North Pacific Ocean. The multidecadal ocean temperature and salinity anomalies may originate from the subsurface of the subpolar North Pacific because of the wave adjustment to the preceding basin-scale wind curl forcing. The anomalies then ascend to the surface and are amplified through local temperature–salinity convective feedback. Along the southward Oyashio, these anomalies travel to the Kuroshio Extension (KOE) region and are further intensified through a similar convective feedback. The oceanic temperature anomaly in the KOE is able to feed back to the large-scale atmospheric circulation, inducing a wind curl anomaly over the subpolar North Pacific, which in turn generates anomalous oceanic circulation and causes temperature and salinity variability in the subpolar subsurface. Thereby, a closed loop of PMV is established in the form of an extratropical delayed oscillator. The phase transition of PMV is driven by the delayed negative feedback that resides in the wave adjustment of the subpolar North Pacific via propagating Rossby waves, whereas the convective positive feedback provides the growth mechanism. A significant role of salinity variability is unveiled in both the delayed negative feedback and convective positive feedback.

Background End-stage renal disease (ESRD) is a condition that is characterized by the loss of kidney function. ESRD patients suffer from various endothelial dysfunctions, inflammation, and immune system defects. Lysine malonylation (Kmal) is a recently discovered post-translational modification (PTM). Although Kmal has the ability to regulate a wide range of biological processes in various organisms, its specific role in ESRD is limited. Methods In this study, the affinity enrichment and liquid chromatography-tandem mass spectrometry (LC-MS/MS) techniques have been used to create the first global proteome and malonyl proteome (malonylome) profiles of peripheral blood mononuclear cells (PBMCs) from twenty patients with ESRD and eighty-one controls. Results On analysis, 793 differentially expressed proteins (DEPs) and 12 differentially malonylated proteins (DMPs) with 16 Kmal sites were identified. The Rap1 signaling pathway and platelet activation pathway were found to be important in the development of chronic kidney disease (CKD), as were DMPs TLN1 and ACTB, as well as one malonylated site. One conserved Kmal motif was also discovered. Conclusions These findings provided the first report on the Kmal profile in ESRD, which could be useful in understanding the potential role of lysine malonylation modification in the development of ESRD.

This paper presents a comprehensive assessment of the observed influence of the global ocean on U.S. precipitation variability using the method of Generalized Equilibrium Feedback Assessment (GEFA), which enables an unambiguous attribution of the influence from multiple ocean basins within a unified framework. The GEFA assessment based on observations for 1950–99 suggests that the tropical Pacific SST variability has the greatest consequence for U.S. precipitation, as both ENSO and meridional modes are associated with notable responses in seasonal mean precipitation. The anomalously cold tropical Indian Ocean is a good indicator for U.S. dry conditions during spring and late winter. The impact of North Pacific SST variability is detected in springtime precipitation, yet it is overshadowed by that of the tropical Indo-Pacific on seasonal-to-interannual time scales. Tropical Atlantic forcing of U.S. precipitation appears to be most effective in winter, whereas the northern Atlantic forcing is likely more important during spring and summer. Global ocean influence on U.S. precipitation is found to be most significant in winter, explaining over 20% of the precipitation variability in the Southwest and southern Great Plains throughout the cold seasons and in the northern Great Plains and northeast United States during late winter. The Southwest and southern Great Plains is likely the region that is most susceptible to oceanic influence, primarily to the forcing of the tropical Indo-Pacific. The Pacific Northwest is among the regions that may experience the least oceanic influence as far as precipitation variability is concerned.