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ObjectiveTo compare the effectiveness of radiomic features based on 18F-FDG PET/CT images within (intranodular) and around (perinodular) lung nodules/masses in distinguishing between lung adenocarcinoma and pulmonary granulomas.MethodsFor this retrospective study, 18F-FDG PET/CT images were collected for 228 patients. Patients diagnosed with lung adenocarcinoma (n = 156) or granulomas (n = 72) were randomly assigned to a training (n = 159) and validation (n = 69) groups. The volume of interest (VOI) of intranodular, perinodular (1–5 voxels, termed Lesion_margin1 to Lesion_margin5) and total area (intra- plus perinodular region, termed Lesion_total1 to Lesion_total5) on PET/CT images were delineated using PETtumor and Marge tool of segmentation editor. A total of 1,037 radiomic features were extracted separately from PET and CT images, and the optimal features were selected to develop radiomic models. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC).ResultsGood and acceptable performance was, respectively, observed in the training (AUC = 0.868, p < 0.001) and validation (AUC = 0.715, p = 0.004) sets for the intranodular radiomic model. Among the perinodular models, the Lesion_margin2 model demonstrated the highest AUC in both sets (0.883 and 0.616, p < 0.001 and p = 0.122). Similarly, in terms of total models, Lesion_total2 model was found to outperform others in the training (AUC = 0.879, p < 0.001) and validation (AUC = 0.742, p = 0.001) sets, slightly surpassing the intranodular model.ConclusionWhen intra- and perinodular radiomic features extracted from the immediate vicinity of the nodule/mass up to 2 voxels distance on 18F-FDG PET/CT imaging are combined, improved differential diagnostic performance in distinguishing between lung adenocarcinomas and granulomas is achieved compared to the intra- and perinodular radiomic features alone.

Understanding habitat demand is key to in situ fauna conservation. While there is increasing evidence of the importance of habitat selection research at multiple spatial scales, snake habitat research has typically neglected the rationality of selecting the size of each spatial scale and quantitative research at the macro scale. The Mangshan pit viper (Protobothrops mangshanensis) is a national first-class key protected species in China with a very narrow geographical distribution. Its habitat needs at multiple spatial scales have not yet been explored. Between 2016 and 2021, we studied the second order, third order, and fourth order of habitat selection of P. mangshanensis. The selection of macro (second order, third order) spatial scales refers to the size of the pit viper’s home range. For second order of habitat selection, P. mangshanensis selected areas with high average tree height (> 12 m), it avoiding areas with a high proportion of coniferous forest (< 27%). At the third order of habitat selection, it selectively used areas close to mountain streams (< 48 m), but avoided areas close to canopy gaps (> 52 m). At the fourth order of habitat selection, it chose fallen logs (> 22%) and vegetative coverage, such as shrubs (> 30%) and herbs (> 18%). The multiple spatial scale analysis reveals the relationship between P. mangshanensis and its habitat and demonstrates that more attention should be paid to habitat protection at different spatial scales.

Abstract Background Endocannabinoid anandamide (AEA), progesterone (P4) and β-human chorionic gonadotrophin (β-hCG) are associated with the threatened miscarriage in the early stage. However, no study has investigated whether combing these three hormones could predict threatened miscarriage. Thus, we aim to establish machine learning models utilizing these three hormones to predict threatened miscarriage risk. Methods This is a multicentre, observational, case-control study involving 215 pregnant women. We recruited 119 normal pregnant women and 96 threatened miscarriage pregnant women including 58 women with ongoing pregnancy and 38 women with inevitable miscarriage. P4 and β-hCG levels were detected by chemiluminescence immunoassay assay. The level of AEA was tested by ultra-high-performance liquid chromatography-tandem mass spectrometry. Six predictive machine learning models were established and evaluated by the confusion matrix, area under the receiver operating characteristic (ROC) curve (AUC), accuracy and precision. Results The median concentration of AEA was significantly lower in the healthy pregnant women group than that in the threatened miscarriage group, while the median concentration of P4 was significantly higher in the normal pregnancy group than that in the threatened miscarriage group. Only the median level of P4 was significantly lower in the inevitable miscarriage group than that in the ongoing pregnancy group. Moreover, AEA is strongly positively correlated with threatened miscarriage, while P4 is negatively correlated with both threatened miscarriage and inevitable miscarriage. Interestingly, AEA and P4 are negatively correlated with each other. Among six models, logistic regression (LR), support vector machine (SVM) and multilayer perceptron (MLP) models obtained the AUC values of 0.75, 0.70 and 0.70, respectively; and their accuracy and precision were all above 0.60. Among these three models, the LR model showed the highest accuracy (0.65) and precision (0.70) to predict threatened miscarriage. Conclusions The LR model showed the highest overall predictive power, thus machine learning combined with the level of AEA, P4 and β-hCG might be a new approach to predict the threatened miscarriage risk in the near feature.

Along with tree ring width, carbon isotopes are also good proxies for climate change. Water use efficiency (WUE) can be calculated more quickly and accurately based on carbon isotopes. In this study, according to the principle of dendroclimatology, the sequence of δ13C and WUE of tree rings of Picea meyeri are built. Pearson correlation analysis and multiple regression analysis are used to explore the response of carbon stable isotopes of Picea meyeri to climate change, which revealed the relationship between δ13C of Picea meyeri and climatic factors. Based on δ13C, we calculated the WUE of Picea meyeri and analyzed its response to climate change. The main conclusions are as follows: (1) The δ13C of Picea meyeri decreases year-by-year from 1957 to 2020, in the range from −23.89‰~−21.67‰, and the average value is −22.67‰. The water use efficiency of Picea meyeri increases in the range from 17.26~61.31, with an average of 39.45. (2) The δ13C of Picea meyeri is negatively correlated with temperature, which has the highest correlation with the temperature of the growing season (c5–c9), and its coefficient is higher than that of the mean temperature of each month. (3) There is a significant positive correlation between WUE sequence and temperature. Meanwhile, due to the effect of precipitation and temperature, the Picea meyeri is subject to drought stress to some extent. Above all, temperature is the main climatic factor affecting the δ13C and WUE of Picea meyeri on Luya mountain.

Cartusia hunanesis sp. nov. was isolated from a stream in China, and two strains (ZJJ02 and ZJJ03) of which were inquired using morphological features, ecological evidence, and molecular data consisting of the 16S rRNA gene and 16S–23S rRNA intergenic transcribed spacer (ITS) region. Cartusia hunanesis varies from the type species Cartusia fontana by having only a single trichome in the sheath and large granules near the cross wall. The investigated strains of C. hunanesis were revealed to be a sister clade of C. fontana, according to the phylogenetic analysis based on the 16S rRNA gene. In addition, the Cartusia was clustered with the family Oculatellaceae members, genera Pegethrix and Elainella. These two strains displayed 97.6% similarity to C. fontana. The ITS region of C. hunanesis was found to be considerably distinct from that of C. fontana in terms of the secondary structure, which demonstrated that C. hunanesis is a novel species owing to the divergences in its morphological and genetic data compared with the related C. fontana.

Climate change significantly affects global forest ecosystems, and the alpine treeline is sensitive to global warming. The alpine treeline data using high-resolution remote sensing images during four periods from 1987 to 2020 at Taibai Mountain are extracted. The dynamic change process of the alpine treeline and the response of vegetation near the alpine treeline to climate change are analyzed. The results showed that the alpine treeline of Taibai Mountain was primarily distributed in the range of 2266-3692 m, and the average elevation of the alpine treeline showed a trend of “rising-decreasing.” The elevation of the alpine treelines of the sunny slopes were much higher than that of the shady slopes, and the highest values typically appeared on slopes and steep slopes of 15-35°. Vegetation is sensitive to temperature changes, and it typically displays a synchronous increase and decrease. However, there was a lag in the precipitation of approximately one year, and the rising temperatures of the sunny slopes were not conducive to vegetation growth. The vegetation will be dominated by a trend of unsustainable improvement in the future, and there exists a risk of continuous vegetation degradation on the northern slopes. However, a warm and humid climate will be conducive to vegetation growth above the alpine treeline.

Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death among women. Various mechanisms are involved in the initiation and progression of breast cancer. Metabolic dysregulation has been associated with increasing breast cancer incidence and mortality. However, little is known about how metabolic disease regulates the development and progression of breast cancer at the molecular level. Here, using a hybridization capture-based panel including 124 cancer-associated genes, we performed targeted next-generation sequencing of tumor tissues and matched blood samples from 20 postmenopausal patients with primary breast cancer, in which 6 cases suffered from preexisting metabolic disorders including hypertension, type 2 diabetes, and coronary heart disease. We took only the protein-altering variants and identified 170 somatic mutations of 59 genes. Among these, 40 mutated genes were found in the metabolic disease group, and 33 mutated genes were found in the non–metabolic disease group. Importantly, nonsynonymous mutations of 26 genes (MSH3, BRAF, MLH3, MTOR, DDR2, ALK, etc.) were uniquely present in the metabolic disease group. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed to investigate biological functions and key pathways of somatic mutations. TP53, PIK3CA, and PTEN were the top three commonly mutated genes at a higher frequency compared with the Cancer Genome Atlas (TCGA) data, and several novel but infrequent mutations in other genes were also found. Although further studies are required to validate these variants, our results are the first to suggest a specific molecular profile of breast cancer with preexisting metabolic disease.

Changes in global precipitation patterns have had important impacts on terrestrial ecosystems. However, the relationship between alpine vegetation species composition and precipitation patterns remained uncertain. Based on in situ observations, long-term datasets of monthly aboveground biomass (AGB) and daily precipitation were applied in an alpine grassland on the Qinghai–Tibet Plateau (QTP), in order to characterize the responses of multi-species biomass to changing rainfall patterns. In this study, vegetation species composition exhibited obvious variations during 1997–2011 in alpine grasslands on the Qinghai–Tibet Plateau. Rapid increases in weed, Kobresia humilis, and Poa crymophila Keng squeezed the living space of the dominant species, Stipa sareptana var. krylovii. Meanwhile, effective precipitation had stronger effects on vegetation biomass, which were heterogeneous in different precipitation periods. Therefore, the crucial effective precipitation, accounting the effective precipitation in crucial periods, could better explain vegetation biomass variations, which could be a new representative climatic indicator to accurately describe vegetation change in alpine grasslands. In addition, crucial periods of effective precipitation appeared to influence heterogeneity for different vegetation species, which showed the heterogeneous adaptability of species to the changes in precipitation patterns. Precipitation patterns during 1997–2011 were more conducive to the growth of Poa crymophila Keng and Kobresia humilis, thereby changing the species composition in alpine grasslands. The coupling of biological environmental adaptability and abiotic crucial effective precipitation determined the variations of vegetation species composition. The new indicator of crucial effective precipitation could provide a new perspective for studying and predicting the species dynamics of alpine grassland.

The radial growth of coniferous trees in the mid–high latitudes of the Northern Hemisphere has an unstable response to climate warming. We analyzed the differences in the radial growth patterns of the two dominant species (Larix principis-rupprechtii Mayr and Picea meyeri Rehd. et Wils.) on Guancen Mountain, north-central China, and the differences in the stability of their radial growth in response to climate change. Pearson correlation and sliding analysis were performed to study the correlations and dynamic relationships between radial growth and climatic factors. The main results are as follows: (1) the standard chronologies of L. principis-rupprechtii and P. meyeri contained rich climate information, and the radial growth of L. principis-rupprechtii was more sensitive to climatic factors than that of P. meyeri; (2) on a long-term scale, changes in the radial growth of L. principis-rupprechtii and P. meyeri in response to the monthly mean temperature and standardized precipitation evapotranspiration index (SPEI) were unstable; (3) after the abrupt temperature change, the interannual basal area increments (BAIs) of the two dominant species followed an upward trend, and the radial growth rate of L. principis-rupprechtii was much greater than that of P. meyeri. The results of this paper can help to understand the response of the radial growth of coniferous forests in north-central China to future climate change, and provide a basis for future forest cultivation in the middle and high latitudes of the northern hemisphere.

Regrowth of forests is expected to be an important driver in the large uptake of anthropogenic CO2 emissions by the terrestrial biosphere. Yet estimates of carbon sink capacity in mid-high latitude regrowth forests still remain unclear. The Loess Plateau (LP), a key region of the Grain to Green Program (GTGP), leads in the greening of China, while China leads in the greening of the world. For the sake of global ecological sustainability and accurate global carbon sink evaluation, the detection and attribution of vegetation growth on the LP requires further research after 20 years of ecological restoration. In this study, significant continuous rises (increases of 7.45 gC·m−2·a−2, R2 = 0.9328, p < 0.01) in net primary production (NPP) have occurred in the past 20 years. Rapid growth of forest NPP and expansion of forested areas in the southeastern regions has led to vegetation restoration on the LP. Human activities contributed 64.2% to the NPP increases, while climate variations contributed 35.8%. NPP in forests and croplands was dominated by human activities, while grassland NPP was mainly influenced by climate variations on the LP. Meanwhile, a strong El Niño event exacerbated the obstruction of large-scale ecological restoration. These conclusions can provide theoretical support for carbon-cycle assessment and the evaluation of sustainable development.

The Qinling Mountains are located on the dividing line between the north and the south of China. Mt. Taibai, the study site, is the highest peak in the Qinling Mountains and also the highest peak in eastern mainland China. At Mt. Taibai, several dendroecological studies have been conducted on the relationship between tree-ring indices and climatic factors using traditional statistical methods. In this study, the response of Larix chinensis Beissn radial growth to climatic factors was explored in the treeline area of Mt. Taibai using the process-based Vaganov–Shashkin-Lite (VSL) model for the first time. The conclusions were obtained according to the analysis of the L. chinensis tree-ring samples collected from both the northern and southern slopes of Mt. Taibai. The VSL model showed that temperature limits L. chinensis growth during the entire growing season, while the model did not indicate precipitation as a limiting factor. The model showed significant positive correlations between the simulated and observed tree-ring chronologies for 1959–2013, excluding the uppermost sample site on the northern slope. However, the model performance deteriorated with increasing altitude, which may be due to the decreased sensitivity of radial growth to climatic factors above the treeline.

Abstract Land surface temperature (LST) is often a direct control on herbaceous plants but has been underappreciated on the alpine grassland phenology in response to climate change. In the present study, we used satellite data of the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) and LST products to study the land surface phenology (LSP) of alpine grasslands in response to LST changes in the Qinghai Lake Basin (QLB), which is on the northeastern Tibetan Plateau. Our results showed that LSP, including the start (SOS), end (EOS), and length (GSL) of the growing season, presented high spatial heterogeneity and had significant correlation with landform elevations. Both averaged SOS and EOS across QLB were advanced from 2001 to 2017, but the greater advancement of SOS compared to that of EOS led to an overall prolonged GSL. Daytime LST (LSTd) and nighttime LST (LSTn) had the contrasting effects on SOS (i.e., SOS can be delayed with the increase in LSTd, while it can be advanced with the increase in LSTn). However, increase in LSTd and LSTn in August had the same advancing effect on EOS. Moreover, LSTd played the dominant role in controlling the grassland phenology. Specifically, an 1°C increase in the LSTd in the nongrowing season (i.e., from previous October to April) significantly postponed the SOS by 2.2 d and advanced the EOS by 1.1 d in August. This study highlights the utility and biological relevance of LST in research of grassland phenology and differential impacts of daytime and nighttime LST on grassland phenology.

A cyanobacterial strain (ZJJ01), morphologically identified as a Leptolyngbya-like species was isolated from a freshwater pond in Zhangjiajie National Forest Park, China, and it was characterized through a polyphasic study based on morphological, ecological, and molecular data. Morphologically, the strain fits the description of Leptolyngbya well, but under further examination, it formed a distinctive structure, namely nodules, which confirmed that it belonged to the genus of Nodosilinea. The 16S rRNA gene threshold value and 16S rRNA phylogenetic analyses clearly confirmed that the studied strain belongs to the genus Nodosilinea but that it is phylogenetically distinct from the 10 other species of Nodosilinea. Furthermore, The D1–D1’ and Box–B helix of the 16S–23S ITS region of the strain ZJJ01 were also different from those of previously described Nodosilinea species. On the basis of this polyphasic approach, here, we provide a description of the new taxon: Nodosilinea hunanesis sp. nov.

Larix principis-rupprechtii is an important afforestation tree species in the North China alpine coniferous forest belt. Studying the correlations and response relationships between Larix principis-rupprechtii radial growth and climatic factors at different elevations is helpful for understanding the growth trends of L. principis-rupprechtiind its long-term sensitivity and adaptability to climate change. Pearson correlation, redundancy (RDA), and sliding analysis were performed to study the correlations and dynamic relationships between radial growth and climatic factors. The main conclusions are as follows: (1) The three-elevation standard chronologies all exhibited high characteristic values, contained rich climate information and were suitable for tree-ring climatological analyses. (2) Both temperature and precipitation restricted low-elevation L. principis-rupprechtii radial growth, while monthly maximum temperatures mainly affected mid-high-elevation L. principis-rupprechtii radial growth. (3) Mid-elevation L. principis-rupprechtii radial growth responded to climate factors with a “lag effect” and was not restricted by spring and early summer drought. (4) Long-term sliding analysis showed that spring temperatures and winter precipitation were the main climatic factors restricting L. principis-rupprechtii growth under warming and drying climate trends at different elevations. The tree-ring width index and Palmer drought severity index (PDSI) were positively correlated, indicating that L. principis-rupprechtii growth is somewhat restricted by drought. These results provide a reference and guidance for L. principis-rupprechtii management and sustainable development in different regions under warming and drying background climate trends.

Abstract Holography relates gravitational theories in five dimensions to four-dimensional quantum field theories in flat space. Under this map, the equation of state of the field theory is encoded in the black hole solutions of the gravitational theory. Solving the five-dimensional Einstein’s equations to determine the equation of state is an algorithmic, direct problem. Determining the gravitational theory that gives rise to a prescribed equation of state is a much more challenging, inverse problem. We present a novel approach to solve this problem based on physics-informed neural networks. The resulting algorithm is not only data-driven but also informed by the physics of the Einstein’s equations. We successfully apply it to theories with crossovers, first- and second-order phase transitions.

Abstract The Indian Ocean Basin (IOB) mode is believed to favor the decay of El Niño via modulating the zonal wind anomalies in the western equatorial Pacific, while the contribution of the Indian Ocean Dipole (IOD) mode to the following year’s El Niño remains highly controversial. In this study, we use the evolution of fast and slow decaying El Niño events during 1950–2020 to demonstrate that the positive IOD with a strong western pole prompts the termination of El Niño, whereas a weak western pole has no significant effect. The strong western pole of a positive IOD leads to a strong IOB pattern peaking in the late winter (earlier than normal), enhancing local convection and causing anomalous rising motions over the tropical Indian Ocean and sinking motions over the western tropical Pacific. The surface equatorial easterly wind anomalies on the western flank of the sinking motions stimulate oceanic equatorial upwelling Kelvin waves, which shoal the thermocline in the eastern equatorial Pacific and rapidly terminate the equatorial warming during El Niño. However, a weak western pole of the IOD induces a weak IOB mode that peaks in the late spring, and the above-mentioned cross-basin physical processes do not occur.

Examination of the periodic differences in temperature in the Qinling Mountains at different time scales is highly important in research on the long-term evolution of the regional climate system and ecological environment. Based on February-April temperature data from 1835 to 2013 obtained at 27 weather stations in the Qinling Mountains reconstructed through tree rings, the multiscale characteristics of the early spring temperature time series on the southern and northern slopes of the Qinling Mountains and the response to climate signals were analyzed. The results indicate that the early spring temperature in the Qinling Mountains exhibits significant periodic characteristics on multiple time scales. Reconstruction at the different time scales reveals that the interannual scale change in the temperature variation on the northern slope of the Qinling Mountains plays a decisive role. The temperature on the northern slope exhibits a higher amplitude at the interannual and interdecadal scales than does that on the southern slope, and temporal differences occur at the quasi-century scale. The temperature achieves the strongest correlation with the original Atlantic Multidecadal Oscillation (AMO) sequence during the entire study period. In addition, the different time scales reveal that a significant response relationship exists between the temperature at the interannual scale and the May sea temperature in the NINO3.4 area, which lags by one year. At the different time scales and various time ranges, the Qinling early spring temperature responds differently to the climate signals, which is an important factor leading to a lower correlation during the entire study period. [ABSTRACT FROM AUTHOR]

Numerous lakes formed in the area where the Huai River and the Grand Canal converged during the historical period, and it played a substantial role in the evolution of the regional environment. Gaoyou Lake is a vital detention reservoir in the lower reaches of the Huai River. Variations in hydrology and basin-wide environmental changes were analyzed based on pollen assemblages, grain size data, and lithology from sediment cores collected at Gaoyou Lake. This study focused on variations in the hydrodynamic processes of Gaoyou Lake that were responses to changes in climate, regional hydrological events, and human activity. The high percentages of pollen from terrestrial herbs and results of principal component analysis suggested that the environment of eastern China was arid from AD 900 to 1300 and that this corresponded to the dry conditions of the Medieval Climate Anomaly. The subsequent period between AD 1300 and 1650 was more humid, as revealed by an increase in aquatic pollen and a decrease in grain size. A rise in xerophytic herb taxa (particularly Artemisia and Chenopodioideae) indicated that the climate became arid again from AD 1650 to 1850, during the Little Ice Age. The modern period (AD 1850 onwards) was characterized by another increase in moisture, as reflected by a decrease in herb pollen and grain sizes. The shifts in the course of the Yellow River in AD 1194 and AD 1855 were recorded by abrupt changes in lithology, sediment characteristics, and the percentages of alien pollen taxa. Intense human impacts were demonstrated by cereal-type pollen and an increase in pollen of other cultivated plants such as Cruciferae and Poaceae. This study provides a foundation for further analysis of the dynamic mechanisms between lake development, climate change, and the effects of significant river changes. [ABSTRACT FROM AUTHOR]

Abstract Based on outputs of 28 coupled models from the Phase 6 of the Coupled Model Intercomparison Project (CMIP6), we show that the response of the Southeast Asian summer monsoon to the El Niño‐Southern Oscillation (ENSO) during post‐ENSO summer will likely strengthen in a warmer climate, which can be attributed to concurrently weakened sea‐surface temperature anomalies (SSTAs) in the western equatorial Pacific (WEP). The weakened WEP SSTAs are primarily caused by enhanced latent heat damping due to increased surface wind speed anomalies, which are associated with the eastward shift of the El Niño‐induced anomalous Walker circulation due to El Niño‐like sea surface temperature change in the tropical Pacific under global warming. Besides, the climatological zonal ocean currents will slow down due to the weakening of climatological Walker circulation, which also acts to weaken the WEP SSTAs via reducing the advection of anomalous temperature by the mean current.

Abstract Notch signaling is a conserved signaling pathway that participates in many aspects of mammary gland development and homeostasis, and has extensively been associated with breast tumorigenesis. Here, to unravel the as yet debated role of Notch3 in breast cancer development, we investigated its expression in human breast cancer samples and effects of its loss in mice. Notch3 expression was very weak in breast cancer cells and was associated with good patient prognosis. Interestingly, its expression was very strong in stromal cells of these patients, though this had no prognostic value. Mechanistically, we demonstrated that Notch3 prevents tumor initiation via HeyL-mediated inhibition of Mybl2, an important regulator of cell cycle. In the mammary glands of Notch3-deficient mice, we observed accelerated tumor initiation and proliferation in a MMTV-Neu model. Notch3-null tumors were enriched in Mybl2 mRNA signature and protein expression. Hence, our study reinforces the anti-tumoral role of Notch3 in breast tumorigenesis.

Background: The current study aims to evaluate the expression and diagnostic value of exosomal miR-148a-3p in the serum of DTC patients. Methods: Exosomes were isolated from the serum of DTC patients and were identified using a transmission electron microscope. RT-PCR was performed to determine the level of exosomal miR-148a-3p in DTC patients. The possible target gene of miR-148a-3p was determined using dual luciferase reporter assay. ROC analysis was performed to determine the diagnostic value of exosomal miR-148a-3p in DTC patients. Results: We identified a novel exosomal miRNA, exosomal miR-148a-3p, that was significantly decreased in the serum of DTC patients compared with that of benign thyroid tumor patients and healthy controls. Further study showed that exosomal miR-148a-3p was correlated with the malignant characteristics of DTC, including tumor diameter, lymph node metastasis (LNM), and higher TNM staging. Dual luciferase reporter assay indicated that IGF-1 was a target gene of miR-148a-3p. ROC analysis demonstrated that the AUC of exosomal miR-148a-3p was better than TgAb and Tg in DTC patients. More importantly, combined use of exosomal miR-148a-3p, TgAb, and Tg significantly enhanced the sensitivity and specificity, indicating exosomal miR-148a-3p is a sensitive biomarker in DTC patients. Conclusions: Altogether, reduced exosomal miR-148a-3p was associated with the risk of DTC and may be used as a biomarker for the diagnosis of DTC. [ABSTRACT FROM AUTHOR]

This study examines the performance of 52 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in capturing the effects of the Indian summer monsoon on the evolution of El Niño–Southern Oscillation (ENSO). The ISM’s impacts on ENSO show a substantial diversity among the models. While some models simulate the strength of the impacts comparable to observations, others represent much weaker influences. Results indicate that the diversity is highly related to inter-model spread in interannual variability of ISM rainfall (ISMR) among the models. Models with a larger ISMR variability simulate stronger ISM-induced anomalies in precipitation and atmospheric circulation over the western North Pacific during the monsoon season. As a result, these models exhibit larger wind anomalies induced by monsoon on the south flank of the anomalous circulation in the western Pacific, thereby influencing subsequent ENSO evolution more significantly by causing stronger air-sea coupling processes over the tropical Pacific.