Long-term Variability Research Articles

Long-term variations in ecosystem water use efficiency in the Tibetan Plateau: Vegetation types, attribution methods and main drivers

Ecosystem water use efficiency (WUE) is a key indicator for understanding the response of carbon–water processes to environmental changes. However, as affected by uncertainty of WUE estimation and attribution, the individual contributions of environmental drivers to WUE changes and the underlying mechanisms remain unclear on the Tibetan Plateau (TP). Here, a theory-based analytical WUE model was modified by introducing an optimal stomatal behavior model, and used to estimate monthly WUE and their drivers during 1982–2018 for main vegetation types on the Tibetan Plateau (TP). Rationality of three mainstream analytical attribution methods—analytical-based partial derivative method (APDM), regression-based partial derivative method (NPDM), and climate elasticity method (CEM)—was examined. Furtherly, the contributions of various environmental drivers to WUE variation trend were estimated for various vegetation types. Results indicate that: (1) The modified model performed well in estimating WUE against with observed WUE at five eddy-covariance (EC) flux stations, which decreased the uncertainty of WUE estimation. WUE increased significantly in the TP with a slope of 0.49 × 10-2 g C kg−1 H2O yr−1 during 1982–2018 with forests increased most rapidly; (2) Only APDM captured both the variation and magnitude of WUE trends, and both NPDM and CEM failed to reproduce the magnitude of WUE trends, though CEM was better than NPDM benefited from its nonlinear structure. Through comparing these methods, we found that the nonlinear direct effects of these forcing variables on WUE change could be higher than their indirect effects caused by their interactions. (3) There are some differences in the main drivers of WUE trends for various vegetation types. Increase in WUE was mainly driven by the increase in leaf area index (LAI) for both steppes and meadows, while decreased air water vapor pressure deficit (VPD) and elevated CO2 showed higher positive effects for broad-leaf forests. The distinct response and extremely scarce EC observations of forests suggest that more attention should be paid to forests in the TP. This study could help in selection of attribution methods and understanding the mechanisms of carbon–water coupling of alpine ecosystems under a changing climate.

Long-Term Variability of Surface Ozone and Its Associations with NOx and Air Temperature Changes from Air Quality Monitoring at Belsk, Poland, 1995–2023

Surface ozone (O3) and nitrogen oxides (NOx = NO + NO2) measured at the rural station in Belsk (51.83° N, 20.79° E), Poland, over the period of 1995–2023, were examined for long-term variability of O3 and its relationship to changes in the air temperature and NOx. Negative and positive trends were found for the 95th and 5th percentile, respectively, in the O3 data. A weak positive correlation (statistically significant) of 0.33 was calculated between O3 and the temperature averaged from sunrise to sunset during the photoactive part of the year (April–September). Recently, O3 maxima have become less sensitive to temperature changes, reducing the incidence of photochemical smog. The ozone–climate penalty factor decreased from 4.4 µg/m3/°C in the 1995–2004 period to 3.9 µg/m3/°C in the 2015–2023 period. The relationship between Ox (O3 + NO2) and NOx concentrations averaged from sunrise to sunset determined the local and regional contribution to Ox variability. The seasonal local and regional contributions remained unchanged in the period of 1995–2023, stabilizing the average O3 level at Belsk. “NOx-limited” and “VOC-limited” photochemical regimes prevailed in the summer and autumn, respectively. For many winter and spring seasons between 1995 and 2023, the type of photochemical regime could not be accurately determined, making it difficult to build an effective O3 mitigation policy.

Sea surface circulation in the Baltic Sea: decomposed components and pattern recognition

By decomposing the total sea surface current into its geostrophic and ageostrophic components, we examined the contribution of each to the long-term variability of the total sea surface current. Our findings demonstrate the importance of geostrophic currents in Baltic Sea gyre formations. Additionally, ageostrophic currents contribute significantly to the flow across the region. Quantifying the difference between total sea surface current fields has revealed two dominant general sea surface circulation patterns in the Baltic Sea, whose characteristics correspond to the monthly mean climatology of sea surface current fields in May and December. Subsequently, a machine learning technique was employed to effectively detect the types of sea surface circulation patterns using wind vectors and sea level anomaly fields. This underscored the combined influence of sea level anomaly-driven and wind-driven components in shaping surface current vectors in the Baltic Sea, consistent with geostrophic and ageostrophic decompositions.

Long-term trend forecast of chlorophyll-a concentration over eutrophic lakes based on time series decomposition and deep learning algorithm

Long-term trend forecast of chlorophyll-a concentration (Chla) holds significant implications for eutrophication management and pollution control planning on lakes, especially under the background of climate change. However, it is a challenging task due to the mixture of trend, seasonal and residual components in time series and the nonlinear relationships between Chla and the hydro-environmental factors. Here we developed a hybrid approach for long-term trend forecast of Chla in lakes, taking the Lake Taihu as an instantiation case, by the integration of Seasonal and Trend decomposition using Loess (STL), wavelet coherence, and Convolutional Neural Network with Bidirectional Long Short-Term Memory (CNN-BiLSTM). The results showed that long-term trends of Chla and the hydro-environmental factors could be effectively separated from the seasonal and residual terms by STL method, thereby enhancing the characterization of long-term variation. The resonance pattern and time lag between Chla and the hydro-environmental factors in the time-frequency domain were accurately identified by wavelet coherence. Chla responded quickly to variations in TP, but showed a time lag response to variations in WT in Lake Taihu. The forecasting method using multivariate and CNN-BiLSTM largely outperformed the other methods for Lake Taihu with regards to R2, RMSE, IOA and peak capture capability, owning to the combination of CNN for extracting local features and the integration of bidirectional propagation mechanism for the acquisition of higher-level features. The proposed hybrid deep learning approach offers an effective solution for the long-term trend forecast of algal blooms in eutrophic lakes and is capable of addressing the complex attributes of hydro-environmental data.

Climate change in hell: Long-term variation in transits of the evaporating planet K2-22b

Rocky planets on ultra-short period orbits can have surface magma oceans and rock-vapour atmospheres in which dust can condense. Observations of that dust can inform us about the composition and surface conditions on these objects. We constrained the properties and long-term (decade) behaviour of the transiting dust cloud from the evaporating planet K2-22b. We observed K2-22b around 40 predicted transits with MuSCAT ground-based multi-optical channel imagers, and complemented these data with long-term monitoring by the ground-based ATLAS (2018-2024) and space-based (2021-2023) surveys. We detected signals during 7 transits, none of which showed significant wavelength dependence. The expected number of MuSCAT-detected transits is $ indicating a decline in mean transit depth since the discovery observations in 2014. The lack of a significant wavelength dependence indicates that dust grains are large or the cloud is optically thick. Long-term trends of depth could be due to a magnetic cycle on the host star or to overturn of the planet's dayside surface magma ocean. The possibility that K2-22b is disappearing altogether is ruled out by the stability of the transit ephemeris against non-gravitational forces, which constrains the mass to be at least comparable to Ceres.

Long-term spatiotemporal variation of benzo[a]pyrene in Japan: Significant decrease in ambient concentrations, human exposure, and health risk

Although Benzo[a]pyrene (BaP) is considered carcinogenic to humans, the health effects of exposure to ambient levels have not been sufficiently investigated. This study estimated the long-term spatiotemporal variation of BaP in Japan over nearly two decades at a fine spatial resolution of 1 km. This study aimed to obtain an accurate spatiotemporal distribution of BaP that can be used in epidemiological studies on the health effects of ambient BaP exposure. The annual BaP concentrations were estimated using an ensemble machine learning approach using various predictors, including the concentrations and emission intensities of the criteria air pollutants, and meteorological, land use, and traffic-related variables. The model performance, evaluated by location-based cross-validation, exhibited satisfactory accuracy (R2 of 0.693). Densely populated areas showed higher BaP levels and greater temporal reduction, whereas BaP levels remained higher in some industrial areas. The population-weighted BaP in 2018 was 0.12 ng m−3, a decrease of approximately 70% from its 2000 value of 0.44 ng m−3, which was also reflected in the estimated excess number of lung cancer incidences. Accordingly, the proportion of BaP exposure below 0.12 ng m−3, which is the BaP concentration associated with an excess lifetime cancer risk of 10−5, reached 67% in 2018. Our estimates can be used in epidemiological studies to assess the health effects of BaP exposure at ambient concentrations.

Investigating Development and Defense Systems in Early Reproductive Stages of Male and Female Gonads in Black Scorpionfish Scorpaena porcus (Linnaeus, 1758).

One of the most crucial biological indicators in tracking long-term variations in the reproductive cycle is sexual development. Scorpaena porcus (Linnaeus, 1758), commonly known as the black scorpionfish, is a small teleost from the family Scorpaenidae. Much is known about its ecology, but data on its reproductive and defense systems are still lacking. Antimicrobial peptides (AMPs), such as piscidins, are integral components of the innate immune system in fish. These peptides exhibit a wide range of activity against bacteria, fungi, viruses, and protozoa and act as the first line of host defense. This study aims to investigate the primary sexual development stages in male and female gonads of black scorpionfish, providing additional knowledge on the reproductive biology of this teleost while evaluating concomitant changes in the expression of a Piscidin-1 antimicrobial peptide. The results show a histological, morpho-structural change from the immature stage to the developing virgin stage. Immunohistochemical analyses show that germinal and somatic cells are strongly reactive to Piscidin-1 in both gonads at an early ontogeny stage. These data suggest that Piscidin-1 may play a key role in the local defense system of scorpionfish gonads at this delicate stage, which is critical for the continuation and maintenance of the species. The present findings are potentially useful for a better understanding of the reproductive cycle of this fish, improving our knowledge of the interaction between the immune system and reproduction.

Multidecadal variations in North Atlantic SSTs modulate the relationship between ENSO and the South Atlantic Subtropical Dipole since 1900

Abstract This study investigates the long-term variability of the relationship between the El Niño South/Oscillation (ENSO) and the South Atlantic Subtropical Dipole (SASD), and their connection to multidecadal variations in the North Atlantic sea surface temperature (MDV-SST). Using a century’s worth of SST and atmospheric data and the Community Atmosphere Model version 5, the study found significant interdecadal variability in the correlation between the Niño3.4 index and the SASD index. This variability is closely linked to the North Atlantic MDV-SST, often interpreted as Atlantic Multidecadal Oscillation (AMO). This is demonstrated by significant ENSO-SASD correlations during warm (positive) phases of MDV-SST (1930–1960 and 2001–2020) and insignificant correlations during cold (negative) phases (1900–1929 and 1961–2000). Through a Gill-type response, MDV-SST excites Rossby wave over the tropical Pacific Ocean, influencing surface wind, SST, convective activities and upper-level zonal wind over the Pacific Ocean. During warm MDV-SST phases, the more eastward positioned Rossby wave source (RWS), triggered by SST and precipitation anomalies over the South Pacific Ocean, along with a stronger, more northward subtropical jet stream, propagates the wavetrain more eastwards into the South Atlantic Ocean, thereby strengthening the SST anomalies in the SASD. Conversely, during the cold MDV-SST phases, the more westward-positioned ENSO-related RWS and a stronger mid-latitude jet stream guide the wavetrain southeastwards into the southeastern Pacific Ocean, exerting less influence on the SST anomalies in the SASD. The Ekman pumping caused by anomalous surface pressure and the associated surface wind field as well as surface turbulent heat flux also affect the SST anomalies in the SASD and the ENSO-SASD relation.

Autonomic Nervous System and Sarcopenia in Elderly Patients: Insights from Long-Term Heart Rate Variability Monitoring in a Hospital Setting.

Emerging evidence suggests a link between muscle health and the autonomic nervous system, but research is scarce. This study examines the connection between long-term heart rate variability (HRV) measured autonomic function and sarcopenia in the elderly, focusing on muscle mass and strength. This retrospective cross-sectional study comprised 132 elderly hospitalized patients. Sarcopenia was defined according to the European Working Group on Sarcopenia in Older People (EWGSOP2) criteria, involving reduced muscle mass and strength. HRV was assessed using standard deviation of NN intervals (SDNN), with values below 100 milliseconds indicating reduced HRV. Multivariate logistic regression and Pearson's correlation analyses were conducted to explore the associations between sarcopenia, muscle metrics, and HRV parameters. Among elderly hospitalized patients, 45.45% had reduced HRV, with sarcopenia patients showing a fivefold higher risk (OR: 5.042; p = 0.034). Grip strength and SARC-CalF scores were independent factors associated with reduced HRV. Moderate correlations were noted between grip strength and HRV indices, particularly with SDNN (r = 0.393, p = 0.001) and the triangular index (r = 0.385, p < 0.001), while a weaker correlation was found with very low frequency power (VLF) (r = 0.283, p = 0.006). No significant correlations were identified between HRV and muscle mass. Regression analyses revealed significant independent associations between HRV parameters and the decline in muscle strength and the onset of sarcopenia. Reduced HRV is closely linked to sarcopenia and diminished muscle strength in the elderly, with the triangular index and SDNN as key indicators, highlighting HRV's potential in muscle health assessment.

Study of the patterns of variations in ice lakes and the factors influencing these changes on the southeastern Tibetan plateau

The ice lakes in the southeastern Qinghai–Tibet Plateau have exhibited a pronounced expansion against the backdrop of global warming, consequently amplifying the local risk of ice lake outburst disasters. However, surveys of ice lake changes in the entire region have consistently been incomplete due to the prevalent high cloud density. On the basis of Landsat remote sensing images and the Google Earth Engine (GEE) cloud computing platform, in this study, the full convolution segmentation algorithm is utilized to accurately and comprehensively map the regional distribution of ice lakes in southeastern Tibet at consistent time intervals in 1993, 2008, and 2023. Furthermore, the formation, distribution, and dynamic changes in these ice lakes are investigated. The numbers of ice lakes discovered in 1993, 2008, and 2023 were 2520, 3198, and 3877, respectively. These lakes covered areas of approximately 337.64 ± 36.86 km2, 363.92 ± 40.90 km2, and 395.74 ± 22.72 km2, respectively. These ice lakes are located primarily between altitudes of 4442 m and 4909 m. The total area experienced an annual growth rate of approximately 0.57 % from 1993 to 2023. In the present study, the long-term variations in ice lakes in each district and county are examined. These findings indicate that between 1993 and 2023, the expansion of ice lakes was more pronounced in regions with a large number of marine glaciers. Notably, Basu County presented the highest annual growth rate of the ice lake population, at 6.23 %, followed by Bomi County, at 4.28 %, and finally, Zayul County, at 2.94 %. The accelerated shrinkage of marine glaciers induced by global warming is the primary driver behind the expansion of ice lakes. The results obtained from this research will enhance our overall understanding of the complex dynamics and mechanisms that govern the formation of ice lakes while also offering valuable perspectives on the potential risks linked to their expansion in this particular area.

The Effect of Sodium Glucose Cotransporter-2 Inhibitors on Hemoglobin A1c Variability and Acute Kidney Injury: A Causal Mediation Analysis.

The role of lower hemoglobin A1c (HbA1c) variability in the effect of sodium glucose cotransporter-2 inhibitors (SGLT2i) on acute kidney injury (AKI) remains unclear. We compared AKI risk between SGLT2i and dipeptidyl peptidase 4 inhibitors (DPP4i) initiators. Additionally, we aimed to explore the extent to which SGLT2i's influence on AKI risk is mediated by reducing long-term HbA1c variability. Using 2018-2022 year data in Yinzhou Regional Health Care Database, we included adult, type 2 diabetes patients who were new users of SGLT2i or DPP4i. The effect of SGLT2i versus DPP4i on AKI, HbA1c variability, and AKI through HbA1c variability was compared using inverse probability of treatment weighted Cox proportional hazards models, median regression models, and causal mediation analysis. With a median follow-up of 1.76 years, 19 717 adults (for SGLT2i, n = 6008; for DPP4i, n = 13 709) with type 2 diabetes were included. The adjusted hazard ratio for SGLT2i versus DPP4i was 0.79 (95% confidence interval [CI] 0.64-0.98) for AKI. The adjusted differences in median HbA1c variability score (HVS) and HbA1c reduction were -16.67% (95% CI: -27.71% to -5.62%) and -1.98% (95% CI: -14.34% to 10.38%), respectively. Furthermore, lower AKI risk associated with SGLT2i was moderately mediated (22.77%) through HVS. The results remained consistent across various subgroups and sensitivity analyses. Compared to DPP4i, lower AKI risk associated with SGLT2i is moderately mediated through HbA1c variability. These findings enhance our understanding of the effect of SGLT2i on AKI and underscore the importance of considering HbA1c variability in diabetes treatment and management.

Investigating Optical Variability of the Blazar S5 0716+714 on Diverse Timescales

We present the results of the observational study of the blazar S5 0716+716 in the optical bands B, V, R, and I between 2019 March and 2023 August to investigate its variability on diverse timescales. The blazar was followed up by the T60 robotic telescope in Türkiye for 416 nights to obtain long-term variability during this period. In order to search for the intraday variability of the object, we have carried out 21 nights of observations with the T100 telescope for at least 1 hr. The blazar showed a ∼2.47 mag variation in the optical R band during our monitoring period, the brightest state on 2020 January 18 (MJD 58866) as R = 12.109 ± 0.011 mag and the faintest state on 2019 March 23 (MJD 58565) as R = 14.580 ± 0.013 mag. We employed the nested ANOVA test and the power-enhanced F-test to quantify intraday variability, which showed that the blazar was significantly variable in the R band on 12 out of 21 nights. Correlation analysis of the light curves shows that the emission in the BVRI optical bands was strongly correlated both in the short and long term without any time lag. The blazar has likely quasiperiods of 186 ± 30 and 532 ± 76 days in the optical R-band light curve according to the weighted wavelet Z-transform and Lomb–Scargle periodogram. The intraday variation and long-term variation features are discussed within the frame of prospective scenarios.

Long-term effects of litter characteristics on reproduction in female cavies (Cavia aperea)

In mammals, birth mass is an important predictor of early growth and survival. Within litters, heavier siblings are usually able to outcompete smaller siblings and gain more resources, thereby often permanently shaping phenotypic development. Early body size and growth are particularly important for later fitness. Only few studies investigated if and how differences within the early family environment contribute to long-term variation in fitness among individuals. We quantified if initial differences in size translate to size differences in adulthood and whether birth mass, relative size within the litter, litter size or the litter sex-ratio affect maturation and reproductive output of female wild cavies (Cavia aperea). Initial differences in mass were maintained until animals reached maximum adult mass at two years of age. Heavier sisters matured earlier and invested more into their first litter than smaller sisters, presumably because smaller sisters invested more into their own growth during the first pregnancy. Growing up in mixed-sexed litters in comparison to female-only litters slowed down maturation in smaller but not the heaviest female within a litter and had no effect on female reproductive effort. Variation in reproduction of multiparous females was to a lesser extent explained by the initial relative size of siblings. Offspring survival to independence was high but slightly lower when mothers had been born as smaller sisters. Our results demonstrate that factors of the early family environment not only affect immediate offspring development but lead to long-term fitness consequences.

Interstellar Scintillations of Sources B0821+394 and B1812+412 as Observed by the LPA LPI Radio Telescope

The search for long-term variability of compact components of radio sources B0821+394 and B1812+412 over an interval of ten years was carried out. The LPA LPI radio telescope with an operating frequency of 111 MHz was used for observations. According to our estimates, the characteristic time of variability for both sources is 1.5–2.5 years. It is shown that the observed variability is not related to intrinsic variations in the radiation flux, but is due to refractive scintillation on inhomogeneities of the interstellar medium. From the obtained upper estimates of the apparent angular dimensions of the sources, it follows that the main contribution to the scattering of radio emission is made by turbulent plasma concentrated in sufficiently thin screens, the distance to which does not exceed 300–400 pc.

Investigation of the long-term variation of gravity waves over South America using empirical orthogonal function analysis

The spatial and temporal variability of gravity waves (GWs) potential energy (Ep) over South America (SA) was examined by analyzing temperature profiles obtained through the utilization of Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) from January 2002 to December 2021. We used the empirical orthogonal function (EOF) analysis to decompose GWs parameters and to analyze the GW variations over SA. We considered the first three eigenmodes (EOF1, EOF2, and EOF3) and their principal components (PC1, PC2, and PC3) of the EOF decomposition, which accounts for ∼80–90% of the total GWs variation over SA. Further, we analyzed the coupled variation of Ep and zonal mean wind (U) to verify their inter-dependencies using the singular value decomposition (SVD). The spatial variation showed that different localized mechanisms generate GWs at different sectors of the continent. The EOF1 of Ep comprised more than 50%, the EOF2 ∼20–25%, and the third ∼10–15% of the total GWs variation. The positive variation of GWs energy in the EOF1 is localized in the tropical region from the lower stratosphere to the lower mesosphere and southward below 1.5° S in the upper mesosphere. The spectral analysis of GWs energy showed biannual, annual, semiannual, and 11-year variations at different eigenvectors. Relative Ep (REp) showed an asymmetric hemispheric response to solar flux over South America. The REp response to QBO showed a modulating effect below 70 km and a positive response above 70 km. There is a good positive correlation between the temporal component of EOF2 of Ep and the quasi-biennial oscillation (QBO) at 30 mb and 50 mb in the PC2 temporal variation.Graphical

Signal completion using generative adversarial networks for enhanced photoplethysmography measurement accuracy

Despite the growing adoption of wearable photoplethysmography (PPG) devices in personal health management, their measurement accuracy remains limited due to susceptibility to noise. This paper proposes a novel signal completion technique using generative adversarial networks that ensures both global and local consistency. Our approach innovatively addresses both short- and long-term PPG variations to restore waveforms while maintaining waveform consistency within and between pulses. We evaluated our model by removing up to 50 % of segments from segmented PPG waveforms and comparing the original and reconstructed waveforms, including systolic peak information. The results demonstrate that our method accurately reconstructs waveforms with high fidelity, producing natural and seamless transitions without discontinuities at reconstructed boundaries. Additionally, the reconstructed waveforms preserve typical PPG shapes with minimal distortion, underscoring the effectiveness and novelty of our technique.

A long-term (1984–2021) wetland classification dataset for the Yangtze River Basin from continuous Landsat image collections

The wetlands along the Yangtze River Basin (YRB) have provided a variety of ecological and economic benefits. However, the lack of a long-term wetland classification dataset with comprehensive wetland categories has created in a barrier to evaluating the long-term variations of YRB wetlands for their habitat health, carbon storage, greenhouse gas emissions, and ecosystem service capacity. Therefore, this study aimed to generate a wetland classification dataset for the YRB covering the time period from 1984 to 2021. The dataset named Long-Term Wetland Classification Dataset for YRB (LTWCD_YRB) was created using a Random Forest machine learning classifier on Google Earth Engine with 30 m resolution Landsat 5, 7, 8 muti-spectral images. The maps of LTWCD_YRB demonstrated the spatial distribution, annual variability, and seasonal cycle of nine wetland categories in the extent, and the total validation accuracy can reach 85 %. The LTWCD_YRB indicates that the total wetland area of the YRB in 2021 was larger than that in 1984, with a constant increase in human-made wetlands and fluctuating natural wetlands. Aquaculture ponds expanded the most by 4,987 km2, while inland marshes in the source region exhibited the most fluctuations. Seasonal changes in wetlands were prominent in the Poyang Lake Basin, Dongting Lake Basin, and YRB source region. Human activities were found to be more dominant than natural driving forces in affecting wetlands. The LTWCD_YRB offers a consistent agreement of wetland area variations with the other satellite-based wetland datasets in the YRB, making it valuable for researchers, policymakers, and stakeholders to better understand the YRB wetlands and to support sustainable wetland management practices.

Application of Shannon Entropy in Assessing Changes in Precipitation Conditions and Temperature Based on Long-Term Sequences Using the Bootstrap Method

This study delves into the application of Shannon entropy to analyze the long-term variability in climate data, specifically focusing on precipitation and temperature. By employing data from 1901 to 2010 across 377 catchments worldwide, we investigated the dynamics of climate variables using the generalized extreme value (GEV) distribution and Shannon entropy measures. The methodology hinged on the robust bootstrap technique to accommodate the inherent uncertainties in climatic data, enhancing the reliability of our entropy estimates. Our analysis revealed significant trends in entropy values, suggesting variations in the unpredictability and complexity of climate behavior over the past century. These trends were critically assessed using non-parametric tests to discern the underlying patterns and potential shifts in climate extremes. The results underscore the profound implications of entropy trends in understanding climate variability and aiding the prediction of future climatic conditions. This research not only confirms the utility of Shannon entropy in climatological studies but also highlights its potential in enhancing our understanding of complex and chaotic climate systems. The study’s findings are vital for developing adaptive strategies in response to the evolving nature of climate extremes, thus contributing to more informed decision-making in environmental management and policy formulation.

Non-invasive ventilation restores the gut microbiota in rats with acute heart failure

Heart failure (HF) is an increasingly prevalent disease in humans; it induces multiple symptoms and damages health. The animal gut microbiota has critical roles in host health, which might be related to HF symptoms. Currently, several options are used to treat HF, including non-invasive ventilation (NIV). However, studies on gut microbiota responses to acute HF and associated treatments effects on gut communities in patients are scarce. Here, short-term (1 week after treatments) and long-term (3 months after treatment) variations in gut microbiota variations in rats with acute HF treated were examined NIV through high-throughput sequencing of the bacterial 16S rRNA gene. Through comparison of gut microbiota alpha diversity, it was observed lower gut microbiota richness and diversity in animals with acute HF than in normal animals. Additionally, beta-diversity analysis revealed significant alterations in the gut microbiota composition induced by acute HF, as reflected by increased Firmicutes/Bacteroidetes (F/B) ratios and Proteobacteria enrichment. When network analysis results were combined with the null model, decreased stability and elevated deterministic gut microbiota assemblies were observed in animals with acute HF. Importantly, in both short- and long-term periods, NIV was found to restore gut microbiota dysbiosis to normal states in acute HF rats. Finally, it was shown that considerable gut microbiota variations existed in rats with acute HF, that underlying microbiota mechanisms regulated these changes, and confirmed that NIV is suitable for HF treatment. In future studies, these findings should be validated with different model systems or clinical samples.

Variable Radio Emission of Neutron Star X-Ray Binary Ser X–1 during Its Persistent Soft State

Ser X–1 is a low-mass neutron star X-ray binary and has been persistently accreting since its discovery in the 1960s. It has always been observed to be in a soft spectral state and has never showed substantial long-term X-ray variability. Ser X–1 has one previous radio observation in the literature in which radio emission was detected during this soft state, which is contrary to the behavior of black hole X-ray binaries. We have recently obtained 10 randomly sampled radio epochs of Ser X–1 in order to further investigate its anomalous soft-state radio emission. Out of 10 epochs, we find 8 nondetections and 2 detections at 10 GHz flux densities of 19.9 ± 4.2 μJy and 32.2 ± 3.6 μJy, respectively. We do not detect polarization in either epoch, ruling out very high polarization levels (≲63% and 34%). We compare these Ser X–1 results to other X-ray binaries and consider explanations for its long-term variable radio behavior.