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Bovine mastitis harms milk quality and cattle health. Val-Pro-Pro (VPP) and Ile-Pro-Pro (IPP) are well-known milk-derived bioactive peptides with anti-inflammatory activity. However, the impact of VPP and IPP on mastitis remain unknown. This study aimed to investigate the anti-inflammatory effects and the underlying mechanisms of VPP and IPP in lipopolysaccharide (LPS)-induced inflammation. When cells were treated with LPS (1 µg/mL) for 24 h, the protein levels of pro-inflammatory factors (tumor necrosis factor-α (TNF-α), interleukin(IL)-1β and IL-6)) and chemokine (monocyte chemotactic protein-1 (MCP-1)) were markedly increased, and the protein level of anti-inflammatory cytokine (IL-10) was reduced. Both VPP and IPP with concentrations of 50 and 100 µM reversed these phenomena and further inhibited the protein expression of β-casein induced by LPS. In a mouse mastitis model, different concentrations of VPP and IPP (300, 600 µM/kg) pretreatment alleviated histopathological lesions in the mammary gland and suppressed the mRNA expression of TNFα, IL1β, and IL6 induced by LPS. VPP and IPP also maintained the integrity of the blood–milk barrier in mice. RNA-seq analyses indicated that enriched phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) and mitogen-activated protein kinase (MAPK) signaling pathways likely contribute to the changes observed (P < 0.05 and |log2 fold change (FC)| ≥ 1). Notably, fibronectin was identified as an important hub by protein–protein interaction (PPI) analysis and molecular docking combined with molecular dynamics simulation. In summary, VPP and IPP exerted a protective effect on LPS-induced inflammation by regulating PI3K/AKT signaling pathway via fibronectin.
Little is known about the association between iodine nutrition status and bone health. The present study aimed to explore the connection between iodine nutrition status, bone metabolism parameters, and bone disease (osteopenia and osteoporosis). A cross-sectional survey was conducted involving 391, 395, and 421 adults from iodine fortification areas (IFA), iodine adequate areas (IAA), and iodine excess areas (IEA) of China. Iodine nutrition status, bone metabolism parameters and BMD were measured. Our results showed that, in IEA, the urine iodine concentrations (UIC) and serum iodine concentrations (SIC) were significantly higher than in IAA. BMD and Ca2+ levels were significantly different under different iodine nutrition levels and the BMD were negatively correlated with UIC and SIC. Univariate linear regression showed that gender, age, BMI, menopausal status, smoking status, alcohol consumption, UIC, SIC, free thyroxine, TSH, and alkaline phosphatase were associated with BMD. The prevalence of osteopenia was significantly increased in IEA, UIC ≥ 300µg/L and SIC > 90µg/L groups. UIC ≥ 300µg/L and SIC > 90µg/L were risk factors for BMD T value < -1.0 SD. In conclusion, excess iodine can not only lead to changes in bone metabolism parameters and BMD, but is also a risk factor for osteopenia and osteoporosis.
Knowledge of the critical periods of crop–weed competition is crucial for designing weed management strategies in cropping systems. In the Lower Yangtze Valley, China, field experiments were conducted in 2011 and 2012 to study the effect of interference from mixed natural weed populations on cotton growth and yield and to determine the critical period for weed control (CPWC) in direct-seeded cotton. Two treatments were applied: allowing weeds to infest the crop or keeping plots weed-free for increasing periods (0, 1, 2, 4, 6, 8, 10, 12, 14, and 20 wk) after crop emergence. The results show that mixed natural weed infestations led to 35- to 55-cm shorter cotton plants with stem diameters 10 to 13 mm smaller throughout the season, fitting well with modified Gompertz and logistic models, respectively. Season-long competition with weeds reduced the number of fruit branches per plant by 65% to 82%, decreasing boll number per plant by 86% to 96% and single boll weight by approximately 24%. Weed-free seed cotton yields ranged from 2,900 to 3,130 kg ha−1, while yield loss increased with the duration of weed infestation, reaching up to 83% to 96% compared with permanent weed-free plots. Modified Gompertz and logistic models were used to analyze the impact of increasing weed control duration and weed interference on relative seed cotton yield (percentage of season-long weed-free cotton), respectively. Based on a 5% yield loss threshold, the CPWC was found to be from 145 to 994 growing degree days (GDD), corresponding to 14 to 85 d after emergence (DAE). These findings emphasize the importance of implementing effective weed control measures from 14 to 85 DAE in the Lower Yangtze Valley to prevent crop losses exceeding a 5% yield loss threshold.
Previous research has shown abnormal functional network gradients in Alzheimer’s disease (AD). Structural network gradient is capable of capturing continuous changes in brain morphology and has the ability to elucidate the underlying processes of neurodevelopment. However, it remains unclear whether structural network gradients are altered in AD and what associations exist between these changes and cognitive function, and gene expression profiles.
Methods
By constructing an individualized structural network gradient decomposition framework, we calculated the morphological similarity network (MSN) gradients for 404 subjects (186 AD patients and 218 normal controls). We investigated AD-related alterations in MSN gradients, along with the associations between MSN gradients and cognitive function, MSN topological properties, and gene expression profiles.
Results
Our findings indicated that the principal MSN gradient alterations in AD were primarily characterized by an increase in the primary and secondary sensory cortices and a decrease in the association cortex 1. The primary and higher-order cortices exhibited opposite associations with cognition, including executive function, language skills, and memory processes. Moreover, the principal MSN gradients were found to significantly predict cognitive function in AD. The altered gradient pattern was 14.8% attributable to gene expression profiles, and the genes demonstrating the highest correlation are involved in metabolic activity and synaptic signaling.
Conclusions
Our results offered novel insights into the underlying mechanisms of structural brain network impairment in AD patients, enhancing our understanding of the neurobiological processes responsible for impaired cognition in patients with AD, and offering a new dimensional structural biomarker for AD.
In this work, we confirm a Pr3+:LiYF4 pulsed laser with high power and high energy at 639 nm based on the acousto-optic cavity dumping technique. The maximum average output power, narrowest pulse width, highest pulse energy and peak power of the pulsed laser at a repetition rate of 0.1 kHz are 532 mW, 112 ns, 5.32 mJ and 47.5 kW, respectively. A 639 nm pulsed laser with such high pulse energy and peak power has not been reported previously. Furthermore, we obtain a widely tunable range of repetition rates from 0.1 to 5000 kHz. The diffracted beam quality factors M2 are 2.18 (in the x direction) and 2.04 (in the y direction). To the best of our knowledge, this is the first time that a cavity-dumped all-solid-state pulsed laser in the visible band has been reported. This work provides a promising method for obtaining high-performance pulsed lasers.
In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.
Methods
To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.
Results
Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.
Conclusions
This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.
This study examined the sour grapes/sweet lemons rationalization through 2 conditions: ‘attainable’ (sweet lemons) and ‘unattainable’ (sour grapes), reflecting China’s 2019-nCoV vaccination strategy. The aim was to find ways to change people’s beliefs and preferences regarding vaccines by easing their safety concerns and encouraging more willingness to get vaccinated. An online survey was conducted from January 22 to 27, 2021, with 3,123 residents across 30 provinces and municipalities in the Chinese mainland. The direction of belief and preference changed in line with the sour grapes/sweet lemons rationalization. Using hypothetical and real contrasts, we compared those for whom the vaccine was relatively unattainable (‘sour grapes’ condition) with those who could get the vaccine easily (‘sweet lemons’). Whether the vaccine was attainable was determined in the early stage of the vaccine roll-out by membership in a select group of workers that was supposed to be vaccinated to the greatest extent possible, or, by being in the second stage when the vaccine was available to all. The attainable conditions demonstrated higher evaluation in vaccine safety, higher willingness to be vaccinated, and lower willingness to wait and see. Hence, we propose that the manipulation of vaccine attainability, which formed the basis of the application of sour grapes/sweet lemons rationalization, can be utilized as a means to manipulate the choice architecture to nudge individuals to ease vaccine safety concerns, reducing wait-and-see tendencies, and enhancing vaccination willingness. This approach can expedite universal vaccination and its associated benefits in future scenarios resembling the 2019-nCoV vaccine rollout.
Femtosecond oscillators with gigahertz (GHz) repetition rate are appealing sources for spectroscopic applications benefiting from the individually accessible and high-power comb line. The mode mismatch between the potent pump laser diode (LD) and the incredibly small laser cavity, however, limits the average output power of existing GHz Kerr-lens mode-locked (KLM) oscillators to tens of milliwatts. Here, we present a novel method that solves the difficulty and permits high average power LD-pumped KLM oscillators at GHz repetition rate. We propose a numerical simulation method to guide the realization of Kerr-lens mode-locking and comprehend the dynamics of the Kerr-lens mode-locking process. As a proof-of-principle demonstration, an LD-pumped Yb:KGW oscillator with up to 6.17-W average power and 184-fs pulse duration at 1.6-GHz repetition rate is conducted. The simulation had a good agreement with the experimental results. The cost-effective, compact and powerful laser source opens up new possibilities for research and industrial applications.
The practical implementation of machine learning in flow control is limited due to its significant training expenses. In the present study the convolutional neural network (CNN) trained with the data of the restricted nonlinear (RNL) model is used to predict the normal velocity on a detection plane at $y^+=10$ in a turbulent channel flow, and the predicted velocity is used as wall blowing and suction for drag reduction. An active control test is carried out by using the well-trained CNN in direct numerical simulation (DNS). Substantial drag reduction rates up to 19 % and 16 % are obtained based on the spanwise and streamwise wall shear stresses, respectively. Furthermore, we explore the online control of wall turbulence by combining the RNL model with reinforcement learning (RL). The RL is constructed to determine the optimal wall blowing and suction based on its observation of the wall shear stresses without using the label data on the detection plane for training. The controlling and training processes are conducted synchronously in a RNL flow field. The control strategy discovered by RL has similar drag reduction rates with those obtained previously by the established method. Also, the training cost decreases by over thirty times at $Re_{\tau }=950$ compared with the DNS-RL model. The present results provide a perspective that combining the RNL model with machine learning control for drag reduction in wall turbulence can be effective and computationally economical. Also, this approach can be easily extended to flows at higher Reynolds numbers.
A spatially developing flat-plate boundary layer free from and two-way coupled with inertial solid particles is simulated to investigate the interaction between particles and the turbulent/non-turbulent interface. Particle Stokes numbers based on the outer scale are $St=2$ (low), 11 (moderate) and 53 (high). The Eulerian–Lagrangian point-particle approach is deployed for the simulation of particle-laden flow. The outer edge of the turbulent/non-turbulent interface layer is detected as an iso-surface of vorticity magnitude. Results show that the particles tend to accumulate below the interface due to the centrifugal effect of large-scale vortices in the outer region of wall turbulence and the combined barrier effect of potential flow. Consequently, the conditionally averaged fluid velocity and vorticity vary more significantly across the interface through momentum exchange and the feedback of force in the enstrophy transport. The large-scale structures in the outer layer of turbulence become smoother and less inclined in particle-laden flow due to the modulation of turbulence by the inertial particles. As a result, the geometric features of the interface layer are changed, namely, the spatial undulation increases, the fractal dimension decreases and the thickness becomes thinner in particle-laden flow as compared with unladen case. These effects become more pronounced as particle inertia increases.
Using the instrumental variable approach on nationally representative, individual-level data on middle-aged pension participants in China, this study quantifies the peer effect in the context of forming pension expectations. The study confirms the existence of the peer effect in forming pension expectations in the community. The probability of having optimistic pension expectations significantly increases by 0.309 percentage points if the proportion of optimists in the community increases by 1 percentage point. Moreover, the study explores the channels through which the peer effect operates and finds that the social learning channel dominates the social norms channel. The study also provides empirical evidence that village and township leaders as well as those with old pension program experience are opinion leaders in their peer group. Lastly, we find peer effects in other pension decisions, e.g., contribution size, and the contribution size increases by the proportion of optimists in the community. The study provides policy implications on ways to improve willingness to contribute to pension programs.
Based on 30 high-resolution U-Th dating controls, we reconstruct stalagmite δ18O records from 45 to 15 thousand years ago (ka B.P., before AD 1950) from the Shizhu Cave, which is located in southwestern China under the influence of both the Indian Summer Monsoon (ISM) and the East Asian Summer Monsoon (EASM). By integrating with the other stalagmite δ18O records in Asia during the middle to late last glacial, our results reveal two main moisture trajectories: one from the Indian Ocean, through the Shizhu Cave towards central China, and the other from the Pacific Ocean to central and northern China. The systematic decrease of the average values of stalagmite δ18O records from oceans to inland China reveals a spatial pattern of water vapour fractionation and moisture trajectory during the middle to late last glacial. In contrast, the variation amplitude, which is defined as the departures apart from the background δ18O records during Heinrich stadials 1 to 4 (HS1–HS4), show an increasing trend from the coastal oceans to mid-latitude inland China, presenting a ‘coastal-inland’ pattern, which can be interpreted by the enhanced East Asian Winter Monsoon (EAWM) and the weakened EASM. More specifically, the enriched stalagmite δ18O records in the EASM region during HS1 to HS4 are caused by the decreased summer rainfall amount or/and the increased proportion of summer moisture resources from the Pacific Ocean. These new observations deepen our understanding of the complicated stalagmite δ18O records in the EASM region.
This study compared the concentrations, types and distributions of sialic acid (SA) in human milk at different stages of the postnatal period with those in a range of infant formulas. Breast milk from mothers of healthy, full-term and exclusively breastfed infants was collected on the 2nd (n 246), 7th (n 135), 30th (n 85) and 90th (n 48) day after birth. The SA profiles of human milk, including their distribution, were analysed and compared with twenty-four different infant formulas. Outcome of this observational study was the result of natural exposure. Only SA of type Neu5Ac was detected in human milk. Total SA concentrations were highest in colostrum and reduced significantly over the next 3 months. Approximately 68·7–76·1 % of all SA in human milk were bound to oligosaccharides. Two types of SA, Neu5Ac and Neu5Gc, have been detected in infant formulas. Most SA was present in infant formulas combined with protein. Breastfed infants could receive more SA than formula-fed infants with the same energy intake. Overall, human milk is a preferable source of SA than infant formulas in terms of total SA content, dynamics, distribution and type. These SA profiles in the natural state are worth to be considered by the production of formulas because they may have a great effect on infant nutrition and development.
There is growing evidence that gray matter atrophy is constrained by normal brain network (or connectome) architecture in neuropsychiatric disorders. However, whether this finding holds true in individuals with depression remains unknown. In this study, we aimed to investigate the association between gray matter atrophy and normal connectome architecture at individual level in depression.
Methods
In this study, 297 patients with depression and 256 healthy controls (HCs) from two independent Chinese dataset were included: a discovery dataset (105 never-treated first-episode patients and matched 130 HCs) and a replication dataset (106 patients and matched 126 HCs). For each patient, individualized regional atrophy was assessed using normative model and brain regions whose structural connectome profiles in HCs most resembled the atrophy patterns were identified as putative epicenters using a backfoward stepwise regression analysis.
Results
In general, the structural connectome architecture of the identified disease epicenters significantly explained 44% (±16%) variance of gray matter atrophy. While patients with depression demonstrated tremendous interindividual variations in the number and distribution of disease epicenters, several disease epicenters with higher participation coefficient than randomly selected regions, including the hippocampus, thalamus, and medial frontal gyrus were significantly shared by depression. Other brain regions with strong structural connections to the disease epicenters exhibited greater vulnerability. In addition, the association between connectome and gray matter atrophy uncovered two distinct subgroups with different ages of onset.
Conclusions
These results suggest that gray matter atrophy is constrained by structural brain connectome and elucidate the possible pathological progression in depression.
The Hamiltonian of a conventional quantum system is Hermitian, which ensures real spectra of the Hamiltonian and unitary evolution of the system. However, real spectra are just the necessary conditions for a Hamiltonian to be Hermitian. In this paper, we discuss the metric operators for pseudo-Hermitian Hamiltonian which is similar to its adjoint. We first present some properties of the metric operators for pseudo-Hermitian Hamiltonians and obtain a sufficient and necessary condition for an invertible operator to be a metric operator for a given pseudo-Hermitian Hamiltonian. When the pseudo-Hermitian Hamiltonian has real spectra, we provide a new method such that any given metric operator can be transformed into the same positive-definite one and the new inner product with respect to the positive-definite metric operator is well defined. Finally, we illustrate the results obtained with an example.
For a group G and $m\ge 1$, let $G^m$ denote the subgroup generated by the elements $g^m$, where g runs through G. The subgroups not of the form $G^m$ are the nonpower subgroups of G. We classify the groups with at most nine nonpower subgroups.
We first introduce the concept of weak random periodic solutions of random dynamical systems. Then, we discuss the existence of such periodic solutions. Further, we introduce the definition of weak random periodic measures and study their relationship with weak random periodic solutions. In particular, we establish the existence of invariant measures of random dynamical systems by virtue of their weak random periodic solutions. We use concrete examples to illustrate the weak random periodic phenomena of dynamical systems induced by random and stochastic differential equations.
Folate, also known as vitamin B9, is a water-soluble vitamin. Previous studies on dietary folate intake in severe headache patients were equivocal. Therefore, we conducted a cross-sectional study to elucidate the relationship between folate intake and severe headache. This cross-sectional study used data from participants over 20 years old who participated in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2004. The diagnosis of severe headache was made through participants’ self-report in the NHANES questionnaire section. We performed multivariate logistic regression and restricted cubic spline (RCS) regression to explore the relationship between folate intake and severe headache. A total of 9859 participants took part in the study, 1965 of whom were severe headache patients and the rest were non-severe headache. We found that dietary folate intake was significantly and inversely associated with severe headache. Compared with participants with lower folate intake Q1 (≤ 229·97 ug/d), the adjusted OR values for dietary folate intake and severe headache in Q2 (229·98–337 ug/d), Q3 (337·01–485 ug/d) and Q4 (≥ 485·01 ug/d) were 0·81 (95 % CI: 0·67, 0·98, P = 0·03), 0·93 (95 % CI: 0·77, 1·12, P = 0·41) and 0·63 (95 % CI: 0·49, 0·80, P < 0·001), respectively. For women aged 20–50 years, there was a non-linear association between folate intake and severe headache in the RCS. Women aged 20–50 years should have higher awareness of dietary folate and increase their dietary intake of folate, which may aid in preventing severe headache.
Obsessive-compulsive disorder (OCD) is a chronic mental illness characterized by abnormal functional connectivity among distributed brain regions. Previous studies have primarily focused on undirected functional connectivity and rarely reported from network perspective.
Methods
To better understand between or within-network connectivities of OCD, effective connectivity (EC) of a large-scale network is assessed by spectral dynamic causal modeling with eight key regions of interests from default mode (DMN), salience (SN), frontoparietal (FPN) and cerebellum networks, based on large sample size including 100 OCD patients and 120 healthy controls (HCs). Parametric empirical Bayes (PEB) framework was used to identify the difference between the two groups. We further analyzed the relationship between connections and Yale-Brown Obsessive Compulsive Scale (Y-BOCS).
Results
OCD and HCs shared some similarities of inter- and intra-network patterns in the resting state. Relative to HCs, patients showed increased ECs from left anterior insula (LAI) to medial prefrontal cortex, right anterior insula (RAI) to left dorsolateral prefrontal cortex (L-DLPFC), right dorsolateral prefrontal cortex (R-DLPFC) to cerebellum anterior lobe (CA), CA to posterior cingulate cortex (PCC) and to anterior cingulate cortex (ACC). Moreover, weaker from LAI to L-DLPFC, RAI to ACC, and the self-connection of R-DLPFC. Connections from ACC to CA and from L-DLPFC to PCC were positively correlated with compulsion and obsession scores (r = 0.209, p = 0.037; r = 0.199, p = 0.047, uncorrected).
Conclusions
Our study revealed dysregulation among DMN, SN, FPN, and cerebellum in OCD, emphasizing the role of these four networks in achieving top-down control for goal-directed behavior. There existed a top-down disruption among these networks, constituting the pathophysiological and clinical basis.
Currently there is lack of knowledge on how new types of alternative fuels and their storage conditions change the droplet evaporation characteristics. Liquid fuel is commonly stored in wide varieties of containers, where fuel characteristics may change because of the exposure to the material of the container. This study evaluates the impact of different storage containers on droplet evaporation characteristics of different fuels. It was found that there is a distinct phase transition between high volatility to low volatility phase in each fuel stored in steel drums verses fuel that is stored in plastic drums. The type of fuel contaminated by polymer additive has a high impact on fuel droplet burn rates. Polymer additives also have an impact on nucleate boiling, sub-droplets and soot particles. The burning rate constant, K, of selected pure aromatics, various fuel mixtures and Jet A with different cetane numbers have been evaluated. Research has shown that in the low volatility combustion phase a trend reduction of lowest boiling point pure aromatic burning rate to the highest boiling point pure aromatic burning rate is obvious. Irregular change in droplet diameter between the high volatility phase and low volatility phase during the combustion of aromatics blend was observed. This work has also evaluated the relationship between burning rates and cetane numbers.