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New insights from the Dark Energy Spectroscopic Instrument (DESI) 2024 baryon acoustic oscillations (BAO) data, in conjunction with cosmic microwave background (CMB) and Type Ia supernova (SN) data, suggest that dark energy may not be a cosmological constant. In this work, we investigate the cosmological implications of holographic dark energy (HDE) and interacting holographic dark energy (IHDE) models, utilizing CMB, DESI BAO, and SN data. By considering the combined DESI BAO and SN data, we determine that in the IHDE model, the parameter c > 1 and the dark-energy equation of state w does not cross - 1 at the 1 σ confidence level, whereas in the HDE model, it marginally falls below this threshold. Upon incorporating CMB data, we observe that in the HDE model, the parameter c < 1 and w crosses - 1 at a level beyond 10 σ . Conversely, for the IHDE model, the likelihood of w crossing - 1 is considerably diminished, implying that the introduction of interaction within the HDE model could potentially resolve or mitigate the cosmic big rip conundrum. Furthermore, our analysis reveals that the HDE and IHDE models are statistically as viable as the Λ CDM model when assessing Bayesian evidence with DESI BAO data combined with SN data. However, when CMB data are added, the HDE and IHDE models are significantly less favored than the Λ CDM model. Our findings advocate for further exploration of the HDE and IHDE models using forthcoming, more precise late-universe observations.

The model of holographic dark energy in which dark energy interacts with dark matter is investigated in this paper. In particular, we consider the interacting holographic dark energy model in the context of a perturbed universe, which was never investigated in the literature. To avoid the large-scale instability problem in the interacting dark energy cosmology, we employ the generalized version of the parameterized post-Friedmann approach to treating the dark energy perturbations in the model. We use the current observational data to constrain the model. Since the cosmological perturbations are considered in the model, we can then employ the redshift-space distortions (RSD) measurements to constrain the model, in addition to the use of the measurements of expansion history, which has never been done in the literature. We find that, for both the cases with \\[Q= H _c\\] and with \\[Q= H_0 _c\\], the interacting holographic dark energy model is more favored by the current data, compared to the holographic dark energy model without interaction. It is also found that, with the help of the RSD data, a positive coupling \\[ \\] can be detected at the \\[2.95 \\] statistical significance for the case of \\[Q= H_0 _c\\].

Since the B-mode polarization of the cosmic microwave background (CMB) was detected by the BICEP2 experiment and an unexpectedly large tensor-to-scalar ratio, r = 0 . 20 - 0.05 + 0.07 , was found, the base standard cosmology should at least be extended to the 7-parameter Λ CDM+ r model. In this paper, we consider the extensions to this base Λ CDM+ r model by including additional base parameters relevant to neutrinos and/or other neutrino-like relativistic components. Four neutrino cosmological models are considered, i.e., the Λ CDM+ r + ∑ m ν , Λ CDM+ r + N eff , Λ CDM+ r + ∑ m ν + N eff , and Λ CDM+ r + N eff + m ν , sterile eff models. We combine the current data, including the Planck temperature data, the WMAP 9-year polarization data, the baryon acoustic oscillation data, the Hubble constant direct measurement data, the Planck Sunyaev–Zeldovich cluster counts data, the Planck CMB lensing data, the cosmic shear data, and the BICEP2 polarization data, to constrain these neutrino cosmological models. We focus on the constraints on the parameters ∑ m ν , N eff , and m ν , sterile eff . We also discuss whether the tension on r between Planck and BICEP2 can be relieved in these neutrino cosmological models.

In this paper we put forward a running coupling scenario for describing the interaction between dark energy and dark matter. The dark sector interaction in our scenario is free of the assumption that the interaction term Q is proportional to the Hubble expansion rate and the energy densities of dark sectors. We only use a time-variable coupling b ( a ) (with a the scale factor of the universe) to characterize the interaction Q . We propose a parametrization form for the running coupling b ( a )= b 0 a + b e (1− a ) in which the early-time coupling is given by a constant b e , while today the coupling is given by another constant, b 0 . For investigating the feature of the running coupling, we employ three dark energy models, namely, the cosmological constant model ( w =−1), the constant w model ( w = w 0 ), and the time-dependent w model ( w ( a )= w 0 + w 1 (1− a )). We constrain the models with the current observational data, including the type Ia supernova, the baryon acoustic oscillation, the cosmic microwave background, the Hubble expansion rate, and the X-ray gas mass fraction data. The fitting results indicate that a time-varying vacuum scenario is favored, in which the coupling b ( z ) crosses the noninteracting line ( b =0) during the cosmological evolution and the sign changes from negative to positive. The crossing of the noninteracting line happens at around z =0.2–0.3, and the crossing behavior is favored at about 1 σ confidence level. Our work implies that we should pay more attention to the time-varying vacuum model and seriously consider the phenomenological construction of a sign-changeable or oscillatory interaction between dark sectors.

Background Respiratory syncytial virus (RSV), a leading cause of lower respiratory tract infection (LRTI) among children, has resurged in the form of endemic or even pandemic in many countries and areas after the easing of COVID-19 containment measures. This study aimed to investigate the differences in epidemiological and clinical characteristics of children hospitalized for RSV infection during pre- and post-COVID-19 eras in Yunnan, China. Methods A total of 2553 pediatric RSV inpatients from eight hospitals in Yunnan were retrospectively enrolled in this study, including 1451 patients admitted in 2018–2019 (pre-COVID-19 group) and 1102 patients admitted in 2023 (post-COVID-19 group). According to the presence or absence of severe LRTI (SLRTI), patients in the pre- and post-COVID-19 groups were further divided into the respective severe or non-severe subgroups, thus analyzing the risk factors for RSV-associated SLRTI in the two eras. Demographic, epidemiological, clinical, and laboratory data of the patients were collected for the final analysis. Results A shift in the seasonal pattern of RSV activity was observed between the pre-and post-COVID-19 groups. The peak period of RSV hospitalizations in the pre-COVID-19 group was during January–April and October–December in both 2018 and 2019, whereas that in the post-COVID-19 group was from April to September in 2023. Older age, more frequent clinical manifestations (fever, acute otitis media, seizures), and elevated laboratory indicators [neutrophil-to-lymphocyte ratio (NLR), c-reactive protein (CRP), interleukin 6 (IL-6), co-infection rate] were identified in the post-COVID-19 group than those in the pre-COVID-19 group (all P  < 0.05). Furthermore, compared to the pre-COVID-19 group, the post-COVID-19 group displayed higher rates of SLRTI and mechanical ventilation, with a longer length of hospital stay (all P  < 0.05). Age, low birthweight, preterm birth, personal history of atopy, underlying condition, NLR, IL-6 were the shared independent risk factors for RSV-related SLRTI in both pre- and post-COVID-19 groups, whereas seizures and co-infection were independently associated with SLRTI only in the post-COVID-19 group. Conclusions An off-season RSV endemic was observed in Yunnan during the post-COVID-19 era, with changed clinical features and increased severity. Age, low birthweight, preterm birth, personal history of atopy, underlying condition, NLR, IL-6, seizures, and co-infection were the risk factors for RSV-related SLRTI in the post-COVID-19 era.

Off-season upsurge of respiratory syncytial virus (RSV) infection with changed characteristics and heightened clinical severity during the post-COVID-19 era are raising serious concerns. This study aimed to develop and validate a nomogram for predicting the risk of severe acute lower respiratory tract infection (SALRTI) in children hospitalized for RSV infection during the post-COVID-19 era using machine learning techniques. A multicenter retrospective study was performed in nine tertiary hospitals in Yunnan, China, enrolling children hospitalized for RSV infection at seven of the nine participating hospitals during January-December 2023 into the development dataset. Thirty-nine variables covering demographic, clinical, and laboratory characteristics were collected. Primary screening and dimension reduction of data were performed using Least Absolute Shrinkage and Selection Operator (LASSO) regression, followed by identification of independent risk factors for RSV-associated SALRTI using Logistic regression, thus finally establishing a predictive nomogram model. Performance of the nomogram was internally evaluated by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) based on the development dataset. External validation of our model was conducted using same methods based on two independent RSV cohorts comprising pediatric RSV inpatients from another two participating hospitals between January-March 2024. The development dataset included 1102 patients, 239 (21.7%) of whom developed SALRTI; while the external validation dataset included 249 patients (142 in Lincang subset and 107 in Dali subset), 58 (23.3%) of whom were diagnosed as SALRTI. Nine variables, including age, preterm birth, underlying condition, seizures, neutrophil-lymphocyte ratio (NLR), interleukin-6 (IL-6), lactate dehydrogenase (LDH), D-dimer, and co-infection, were eventually confirmed as the independent risk factors of RSV-associated SALRTI. A predictive nomogram was established via integrating these nine predictors. In both internal and external validations, ROC curves indicated that the nomogram had satisfactory discrimination ability, calibration curves demonstrated good agreement between the nomogram-predicted and observed probabilities of outcome, and DCA showed that the nomogram possessed favorable clinical application potential. A novel nomogram combining several common clinical and inflammatory indicators was successfully developed to predict RSV-associated SALRTI. Good performance and clinical effectiveness of this model were confirmed by internal and external validations.

We consider the models of vacuum energy interacting with cold dark matter in this study, in which the coupling can change sigh during the cosmological evolution. We parameterize the running coupling b by the form b（a） = boa ＋ be（1 - a）, where at the earlytime the coupling is given by a constant be and today the coupling is described by another constant bo. We explore six specific models with （i） Q = b（a）Hoρo, （ii） Q = b（a）Hoρde, （iii） Q = b（a）Hoρc, （iv） Q = b（a）Hρo, （v） Q = b（a）Hρde, and （vi） Q = b（a）Hρc. The current observational data sets we use to constrain the models include the JLA compilation of type Ia supernova data, the Planck 2015 distance priors data of cosmic microwave background observation, the baryon acoustic oscillations measurements and the Hubble constant direct measurement. We find that, for all the models, we have b0 〈 0 and be 〉 0 at around the lolevel, and b0 and be are in extremely strong anti-correlation. Our results show that the coupling changes sign during the evolution at about the lolevel, i.e., the energy transfer is from dark matter to dark energy when dark matter dominates the universe and the energy transfer is from dark energy to dark matter when dark energy dominates the universe.

The honey bee has been regarded as a key species in the environmental risk assessment of biotech crops. Here, the potential adverse effects of Cry1Ie toxin on the midgut bacteria of the worker bees ( Apis mellifera ligustica ) were investigated under laboratory conditions. Newly emerged bees were fed with different concentrations of Cry1Ie toxin syrups (20 ng/mL, 200 ng/mL and 20 μg/mL), pure sugar syrup and 48 ppb of imidacloprid syrups, then sampled after 15 and 30 d. We characterized the dominant midgut bacteria and compared the composition and structure of the midgut bacterial community in all samples using the Illumina MiSeq platform targeting the V3–V4 regions of 16S rDNA. No significant differences in the diversity of the midgut bacteria were observed between the five treatments. This work was the first to show the effects of Cry1Ie toxin on honey bees and our study provided a theoretical basis for the biosafety assessment of transgenic Cry1Ie maize.

The aim of this study was to investigate the quantitative flow ratio (QFR) outcomes in the left circumflex artery (LCX) following the placement of a crossover stent from the left main coronary artery (LM) to the left anterior descending artery (LAD) in LM bifurcation lesions. In addition, we sought to assess the relationship between these QFR results and clinical prognoses. The treatment approach for LM bifurcation lesions remains a topic of debate, with the LM-LAD single-stent technique being one possible option. QFR, a fractional flow reserve calculation method derived from angiography that does not require pressure guide wires, could serve as an alternative functional assessment of the LCX. This study aims to evaluate the clinical outcomes of postoperative LCX by utilizing QFR measurements, addressing a current gap in the relevant literature on this topic. This study was a retrospective, single-center analysis of patients with LM bifurcation lesions who underwent percutaneous coronary intervention (PCI) guided by intravascular ultrasound. QFR values were derived from angiographies. The primary endpoint was the 1-year rate of major adverse cardiac events, defined as a composite of cardiovascular death, target bifurcation-related myocardial infarction (MI), or target bifurcation revascularization. The secondary clinical endpoint was defined as the persistence or recurrence of angina pectoris after PCI. We analyzed 91 patients from a total of 180 who were screened for LM bifurcation lesions. All patients completed the 1-year follow-up. The pre- and post-PCI QFR values were 0.89 ± 0.09 and 0.86 ± 0.11, respectively. Subgroup analysis showed that 74 patients were in the postoperative QFR ≥0.80 group, whereas 17 patients were in the QFR <0.80 group. In addition, 32 patients had a ΔQFR ≥0, and 58 patients had a ΔQFR <0. Nine patients (9.9%) achieved the primary endpoint, including one patient with non-ST elevation myocardial infarction who received revascularization in both the LM-LAD and LCX arteries. In addition, nine patients (9.9%) reported no substantial improvement in their chest pain symptoms. Post-LCX-QFR <0.8 was associated with a higher 1-year incidence of cardiovascular death or MI (  = 0.036). ΔQFR proved to be a robust predictor of the 1-year incidence of the primary endpoint, with an incidence of 15.3% in the ΔQFR ≥0 group compared to 0% in the ΔQFR <0 group (area under the curve: 0.822; 95% CI: 0.728-0.895,  < 0.001), especially when ΔQFR ≤-0.03. After the LM-LAD single-stent strategy for LM bifurcation lesions, a ΔQFR of LCX ≤-0.03 was associated with a higher risk of 1-year main adverse cardiac events, indicating the superior prognostic value of the post-PCI physiological assessment.