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The purpose of our study is to figure out the transitions of the cryptocurrency market due to the outbreak of COVID-19 through network analysis, and we studied the complexity of the market from different perspectives. To construct a cryptocurrency network, we first apply a mutual information method to the daily log return values of 102 digital currencies from January 1, 2019, to December 31, 2020, and also apply a correlation coefficient method for comparison. Based on these two methods, we construct networks by applying the minimum spanning tree and the planar maximally filtered graph. Furthermore, we study the statistical and topological properties of these networks. Numerical results demonstrate that the degree distribution follows the power-law and the graphs after the COVID-19 outbreak have noticeable differences in network measurements compared to before. Moreover, the results of graphs constructed by each method are different in topological and statistical properties and the network’s behavior. In particular, during the post-COVID-19 period, it can be seen that Ethereum and Qtum are the most influential cryptocurrencies in both methods. Our results provide insight and expectations for investors in terms of sharing information about cryptocurrencies amid the uncertainty posed by the COVID-19 pandemic.

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder with gut microbiota disequilibrium and regulatory T (Treg)/T helper 17 (Th17) immune imbalance. Stigmasterol, a plant-derived sterol, has shown anti-inflammatory effects. Our study aimed to identify the effects of stigmasterol on experimental colitis and the related mechanisms. Stigmasterol treatment restored the Treg/Th17 balance and altered the gut microbiota in a dextran sodium sulfate (DSS)-induced colitis model. Transplantation of the faecal microbiota of stigmasterol-treated mice significantly alleviated inflammation. Additionally, stigmasterol treatment enhanced the production of gut microbiota-derived short-chain fatty acids (SCFAs), particularly butyrate. Next, human naïve CD4+ T cells sorted from IBD patients were cultured under Treg- or Th17-polarizing conditions; butyrate supplementation increased the differentiation of Tregs and decreased Th17 cell differentiation. Mechanistically, butyrate activated peroxisome proliferator-activated receptor gamma (PPARγ) and reprogrammed energy metabolism, thereby promoting Treg differentiation and inhibiting Th17 differentiation. Our results demonstrate that butyrate-mediated PPARγ activation restores the balance of Treg/Th17 cells, and this may be a possible mechanism, by which stigmasterol attenuates IBD.

Differences in gene expression may play a major role in speciation and phenotypic diversity. We examined genome-wide differences in transcription factor (TF) binding in several humans and a single chimpanzee by using chromatin immunoprecipitation followed by sequencing. The binding sites of RNA polymerase II (Polli) and a key regulator of immune responses, nuclear factor κB (p65), were mapped in 10 lymphoblastoid cell lines, and 25 and 7.5% of the respective binding regions were found to differ between individuals. Binding differences were frequently associated with single-nucleotide polymorphisms and genomic structural variants, and these differences were often correlated with differences in gene expression, suggesting functional consequences of binding variation. Furthermore, comparing Polli binding between humans and chimpanzee suggests extensive divergence in TF binding. Our results indicate that many differences in individuals and species occur at the level of TF binding, and they provide insight into the genetic events responsible for these differences.

Tears have emerged as a promising alternative to blood for diagnosing diabetes. Despite increasing attempts to measure tear glucose using smart contact lenses, the controversy surrounding the correlation between tear glucose and blood glucose still limits the clinical usage of tears. Herein, we present an in-depth investigation of the correlation between tear glucose and blood glucose using a wireless and soft smart contact lens for continuous monitoring of tear glucose. This smart contact lens is capable of quantitatively monitoring the tear glucose levels in basal tears excluding the effect of reflex tears which might weaken the relationship with blood glucose. Furthermore, this smart contact lens can provide an unprecedented level of continuous tear glucose data acquisition at sub-minute intervals. These advantages allow the precise estimation of lag time, enabling the establishment of the concept called ‘personalized lag time’. This demonstration considers individual differences and is successfully applied to both non-diabetic and diabetic humans, as well as in animal models, resulting in a high correlation. The correlation between tear glucose and blood glucose is still controversial. Here, the authors demonstrated the correlation between tear glucose and blood glucose in both animal models and human subjects using smart contact lenses.

Background China has piloted Long-Term Care Insurance (LTCI) to address increasing care demand. However, many cities neglected adjusting LTCI premiums since the pilot, risking the long-term sustainability of LTCI. Therefore, using Zhejiang Province as a case, this study simulated mortality-adjusted long-term care demand and the balance of LTCI funds through dynamic financing mechanism under diverse life expectancy and disability scenarios. Methods Three-parameter log-quadratic model was used to estimate the mortality from 1990 to 2020. Mortality with predicted interval from 2020 to 2080 was projected by Lee-Carter method extended with rotation. Cohort-component projection model was used to simulate the number of older population with different degrees of disability. Disability data of the older people is sourced from China Health and Retirement Longitudinal Study 2018. The balance of LTCI fund was simulated by dynamic financing actuarial model. Results Life expectancy of Zhejiang for male (female) is from 80.46 (84.66) years in 2020 to 89.39 [86.61, 91.74] (91.24 [88.90, 93.25]) years in 2080. The number of long-term care demand with severe disability in Zhejiang demonstrates an increasing trend from 285 [276, 295] thousand in 2023 to 1027 [634, 1657] thousand in 2080 under predicted mean of life expectancy. LTCI fund in Zhejiang will become accumulated surplus from 2024 to 2080 when annual premium growth rate is 5.25% [4.20%, 6.25%] under various disability scenarios, which is much higher than the annual growth of unit cost of long-term care services (2.25%). The accumulated balance of LTCI fund is sensitive with life expectancy. Conclusions Dynamic growth of LTCI premium is essential in dealing with current deficit around 2050 and realizing Zhejiang’s LTCI sustainability in the long-run. The importance of dynamic monitoring disability and mortality information is emphasized to respond immediately to the increase of premiums. LTCI should strike a balance between expanding coverage and controlling financing scale. This study provides implications for developing countries to establish or pilot LTCI schemes.

Cardiovascular and renal benefits of sodium glucose co-transporter 2 inhibitors (SGLT2i) have been clearly demonstrated. However, studies comparing the effects of dapagliflozin and empagliflozin are scarce. In addition, relatively few studies have analyzed the effects of SGLT2i in diabetic patients without established atherosclerotic cardiovascular disease (ASCVD), chronic kidney disease (CKD), or heart failure (HF), and current guidelines recommend SGLT2i and other antidiabetic drugs equally in this population. Therefore, we aimed to compare the clinical outcomes between dapagliflozin, empagliflozin, and dipeptidyl peptidase-4 inhibitors (DPP4i) in patients with type 2 diabetes without prior ASCVD, CKD, or HF. Using a propensity-score matching method, we retrospectively analyzed 921 patients treated with dapagliflozin, 921 patients treated with empagliflozin, and 1842 patients treated with DPP4i (control group). Study outcomes comprised composite coronary events (acute coronary syndrome and coronary revascularization), composite ischemic events (coronary events and stroke), and composite heart failure and renal events. During follow up (median, 43.4 months), the incidence of composite coronary events was significantly lower in the SGLT2i groups than in the control group, and the incidence of composite ischemic events was lower in the dapagliflozin group than in the control group. Dapagliflozin and empagliflozin both demonstrated significant benefits in terms of HF and renal outcomes, supported by renoprotective effects, as assessed by the change in glomerular filtration rate. At 24-36 months of treatment, the empagliflozin group had higher low-density lipoprotein cholesterol levels, and lower glycated hemoglobin levels, compared to those in the dapagliflozin and control groups. SGLT2i use was associated with a significantly reduced risk of ASCVD, HF hospitalization, and renal events, compared to that with DPP4i use among diabetic patients without prior ASCVD, CKD, or HF. There were no significant differences in clinical outcomes between dapagliflozin and empagliflozin, supporting a SGLT2i class effect.

T1 mapping on cardiac magnetic resonance (CMR) imaging is useful for diagnosis and prognostication in patients with light-chain cardiac amyloidosis (AL-CA). We conducted this study to evaluate the performance of T1 mapping parameters, derived from artificial intelligence (AI)-automated segmentation, for detection of cardiac amyloidosis (CA) in patients with left ventricular hypertrophy (LVH) and their prognostic values in patients with AL-CA. A total of 300 consecutive patients who underwent CMR for differential diagnosis of LVH were analyzed. CA was confirmed in 50 patients (39 with AL-CA and 11 with transthyretin amyloidosis), hypertrophic cardiomyopathy in 198, hypertensive heart disease in 47, and Fabry disease in 5. A semi-automated deep learning algorithm (Myomics-Q) was used for the analysis of the CMR images. The optimal cutoff extracellular volume fraction (ECV) for the differentiation of CA from other etiologies was 33.6% (diagnostic accuracy 85.6%). The automated ECV measurement showed a significant prognostic value for a composite of cardiovascular death and heart failure hospitalization in patients with AL-CA (revised Mayo stage III or IV) (adjusted hazard ratio 4.247 for ECV ≥40%, 95% confidence interval 1.215-14.851, p-value = 0.024). Incorporation of automated ECV measurement into the revised Mayo staging system resulted in better risk stratification (integrated discrimination index 27.9%, p = 0.013; categorical net reclassification index 13.8%, p = 0.007). T1 mapping on CMR imaging, derived from AI-automated segmentation, not only allows for improved diagnosis of CA from other etiologies of LVH, but also provides significant prognostic value in patients with AL-CA.

Whether anthropometric or body composition indices are better indicators of metabolic risk remains unclear. The objectives of this study were to compare the association of metabolic risk factors with anthropometric and body composition indices and to identify the better indicators for risk factors in a large-scale Korean population. In this cross-sectional study, the associations of body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) as anthropometric indices and trunk fat mass (TFM), percent trunk fat mass (%TFM), whole-body total fat mass (WBTFM), and percent whole-body total fat mass (%WBTFM) as body composition indices with metabolic risk factors were compared by complex-samples multiple logistic regression models based on complex-sample survey data. In men, WHtR, BMI, and TFM were similarly associated with hypertension. Diabetes, hyperlipidemia, and hypo-high-density lipoprotein (HDL) cholesterolemia tended to be more strongly associated with WHtR and WC than body composition indices. Hypertriglyceridemia and hypercholesterolemia were more strongly associated with WHtR and %TFM than other indices. In women, hypertension tended to be more strongly associated with WHtR than other indices. TFM, %TFM, and WHtR were similarly associated with hyperlipidemia. Diabetes and hypo-HDL cholesterolemia were more strongly associated with WHtR and WC than body composition indices. Hypertriglyceridemia and hypercholesterolemia were more strongly associated with WHtR and %TFM than other indices. Among six metabolic risk factors, the validity and utility of the anthropometric indices in identifying risk factors tended to be similar to or better than those of the body composition indices, except for hypertension and hypercholesterolemia in men and hyperlipidemia and hypercholesterolemia in women.

Infrared absorption spectroscopy enabling direct access to vibrational fingerprints of the molecular structure is a powerful method for functional studies of bio-molecules. Although the intrinsic absorption cross-sections of IR active modes of proteins are nearly 10 orders of magnitude larger than the corresponding Raman cross-sections, they are still small compared to that of fluorescencelabel based methods. Here, we developed a new tool based on collective excitation of plasmonic nanoantenna arrays and demonstrated direct detection of vibrational signatures of single protein monolayers. We first tailored the geometry of individual nanoantennas to form resonant structures that match the molecular vibrational modes. The tailored nanoantennas are then arranged in such a way that their in-phase dipolar coupling leads to a collective excitation of the ensemble with strongly enhanced near fields. The combined collective and individual plasmonic responses of the antenna array play a critical role in attaining signal enhancement factors of 10⁴-10⁵. We achieved measurement of the vibrational spectra of proteins at zeptomole levels for the entire array, corresponding to only 145 molecules per antenna. The near-field nature of the plasmonic enhancement of the absorption signals is demonstrated with progressive loading of the nanoantennas with varying protein film thicknesses. Finally, an advanced model based on nonequilibrium Green's function formalism is introduced, which explains the observed Fano-type absorption line-shapes and tuning of the absorption strengths with the antenna resonance.

As China’s regional development enters a critical stage of population redistribution and urban transformation, the impact of population mobility on regional demographic structures and urban functional restructuring has become increasingly prominent. Against this backdrop of accelerating Beijing–Tianjin–Hebei integration, cities of varying types have been confronted with growing complexity in demographic transitions and socioeconomic stratification during their processes of absorbing or exporting populations. This study employed microdata from the National Bureau of Statistics to construct migration flow matrices and utilized a decomposition quantification approach to explore the impact of internal migration on the population structure and quality in 13 cities within the Beijing–Tianjin–Hebei region. The findings indicated that, while Beijing has achieved some success in population control, it overall exhibits a “large inflow and large outflow” pattern. Langfang has attracted a large number of highly educated individuals and male migrants under the spillover effect from Beijing. Shijiazhuang’s population attractiveness has increased, yet the outflow of highly educated individuals remains unmitigated. Meanwhile, the internal migrant structures in industrial cities such as Tianjin and Tangshan have undergone significant changes following the industrial transformation. Cities in the passive outflow area and agricultural transformation area have experienced siphoning effects, but they face different potential risks due to their unique characteristics. This study further enriches the understanding of the impact mechanisms underlying domestic population mobility and provides differentiated policy references for cities to reconcile their development objectives with demographic realities.