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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.
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.
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.
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.
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).
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).
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.
OBJECTIVES/GOALS: Biliary tract cancer is an uncommon, aggressive malignancy. Incidence varies geographically and is highest in East Asia and South America and lowest in Western countries. Previous dietary risk evaluations have primarily been case-control studies. We evaluated associations of dietary intakes with BTC risk in three cohort studies in two countries. METHODS/STUDY POPULATION: We evaluated 638,860 adults in China and the United Kingdom enrolled in the Shanghai Women’s Health Study (SWHS), Shanghai Men’s Health Study (SMHS), or UK Biobank (UKB). Dietary intake information was obtained from study participants at baseline using food frequency questionnaires previously validated for these studies. Dietary intakes of major food groups and macronutrients were divided into low, middle, and high intake tertiles. Cox regression was used to estimate hazard ratios and 95% CIs for biliary tract cancer risk associated with major food groups in all three cohorts and macronutrients in the SWHS and SMHS. Participants were excluded if, at enrollment, they had a history of cancer, CHD, stroke, a total daily Kcal count below 500 or exceeding 3500, or developed cancer or died within one year after enrollment. RESULTS/ANTICIPATED RESULTS: The analyzed cohort includes 558,372 participants: 66,945 SWHS, 55,750 SMHS, and 435,677 UKB participants with median enrollment ages of 49, 52, and 57 years old and median follow-up times of 18.1, 12.3, and 10.3 years, respectively. The SWHS observed 205 eligible BTC cases, SMHS 97, and UKB 366. SWHS and SMHS participants were combined for dietary evaluation and the highest tertile of fruit intake showed an inverse association with biliary tract cancer risk when compared to the lowest tertile: HR 0.74 (95% CI, 0.55-0.99); p-trend 0.044. In UKB, the highest tertile of fish intake was associated with a reduced risk when compared to the lowest tertile: HR 0.76 (95% CI, 0.59-0.98); p-trend 0.034. DISCUSSION/SIGNIFICANCE: High dietary fruit intake was associated with a reduced risk of biliary tract cancer only in SWHS and SMHS. High fish intake was associated with a reduced risk of biliary tract cancer only in UKB. Our findings reflect geographic-based BTC risk variation which we will further explore in our next model accounting for population-specific risk factors.
Mental disorders, including depression, obsessive compulsive disorder (OCD), and schizophrenia, share a common neuropathy of disturbed large-scale coordinated brain maturation. However, high-interindividual heterogeneity hinders the identification of shared and distinct patterns of brain network abnormalities across mental disorders. This study aimed to identify shared and distinct patterns of altered structural covariance across mental disorders.
Subject-level structural covariance aberrance in patients with mental disorders was investigated using individualized differential structural covariance network. This method inferred structural covariance aberrance at the individual level by measuring the degree of structural covariance in patients deviating from matched healthy controls (HCs). T1-weighted anatomical images of 513 participants (105, 98, 190 participants with depression, OCD and schizophrenia, respectively, and 130 age- and sex-matched HCs) were acquired and analyzed.
Patients with mental disorders exhibited notable heterogeneity in terms of altered edges, which were otherwise obscured by group-level analysis. The three disorders shared high difference variability in edges attached to the frontal network and the subcortical-cerebellum network, and they also exhibited disease-specific variability distributions. Despite notable variability, patients with the same disorder shared disease-specific groups of altered edges. Specifically, depression was characterized by altered edges attached to the subcortical-cerebellum network; OCD, by altered edges linking the subcortical-cerebellum and motor networks; and schizophrenia, by altered edges related to the frontal network.
These results have potential implications for understanding heterogeneity and facilitating personalized diagnosis and interventions for mental disorders.
This paper extends the standard double-exponential jump-diffusion (DEJD) model to allow for successive jumps to bring about different effects on the asset price process. The double-exponentially distributed jump sizes are no longer assumed to have the same parameters; instead, we assume that these parameters may take a series of different values to reflect growing or diminishing effects from these jumps. The mathematical analysis of the stock price requires an introduction of a number of distributions that are extended from the hypoexponential (HE) distribution. Under such a generalized setting, the European option price is derived in closed-form which ensures its computational convenience. Through our numerical examples, we examine the effects on the return distributions from the growing and diminishing severity of the upcoming jumps expected in the near future, and investigate how the option prices and the shapes of the implied volatility smiles are influenced by the varying severity of jumps. These results demonstrate the benefits of the modeling flexibility provided by our extension.
COVID-19 has long-term impacts on public mental health, while few research studies incorporate multidimensional methods to thoroughly characterise the psychological profile of general population and little detailed guidance exists for mental health management during the pandemic. This research aims to capture long-term psychological profile of general population following COVID-19 by integrating trajectory modelling approaches, latent trajectory pattern identification and network analyses.
Longitudinal data were collected from a nationwide sample of 18 804 adults in 12 months after COVID-19 outbreak in China. Patient Health Questionnaire-9, Generalised Anxiety Disorder-7 and Insomnia Severity Index were used to measure depression, anxiety and insomnia, respectively. The unconditional and conditional latent growth curve models were fitted to investigate trajectories and long-term predictors for psychological symptoms. We employed latent growth mixture model to identify the major psychological symptom trajectory patterns, and ran sparse Gaussian graphical models with graphical lasso to explore the evolution of psychopathological network.
At 12 months after COVID-19 outbreak, psychological symptoms generally alleviated, and five psychological symptom trajectories with different demographics were identified: normal stable (63.4%), mild stable (15.3%), mild-increase to decrease (11.7%), mild-decrease to increase (4.0%) and moderate/severe stable (5.5%). The finding indicated that there were still about 5% individuals showing consistently severe distress and approximately 16% following fluctuating psychological trajectories, who should be continuously monitored. For individuals with persistently severe trajectories and those with fluctuating trajectories, central or bridge symptoms in the network were mainly ‘motor abnormality’ and ‘sad mood’, respectively. Compared with initial peak and late COVID-19 phase, aftermath of initial peak might be a psychologically vulnerable period with highest network connectivity. The central and bridge symptoms for aftermath of initial peak (‘appetite change’ and ‘trouble of relaxing’) were totally different from those at other pandemic phases (‘sad mood’).
This research identified the overall growing trend, long-term predictors, trajectory classes and evolutionary pattern of psychopathological network of psychological symptoms in 12 months after COVID-19 outbreak. It provides a multidimensional long-term psychological profile of the general population after COVID-19 outbreak, and accentuates the essentiality of continuous psychological monitoring, as well as population- and time-specific psychological management after COVID-19. We believe our findings can offer reference for long-term psychological management after pandemics.
Because of the high photon flux, the Crab nebula pulsar is widely used as the observation target for X-ray pulsar-based navigation. The built profile of the Crab pulsar will change over time, however, which means that the pre-calibrated template cannot be used for the long term. In this paper, a novel pulsar-based template-independent navigation method is proposed. The detected phase propagation model is given as a term of position of the vehicle, taking the orbital motion into account. A different method of time-of-arrival process between the recovered profiles is introduced. With the aid of orbital transition matrix, a measurement model is derived to be a term of velocity error of the vehicle varying with time. The state errors of the vehicle are transformed into velocity errors by performing multi-segment observations to achieve the navigation system observability. The navigation equations of the system are then established and can be solved directly. Some simulations are performed to verify the method and suggest that the proposed method is feasible, effective and easy to implement. The precise orbit information of the vehicle can be determined. The state estimation accuracy is basically consistent with the traditional filtering algorithms, and the computational cost is still very low.
Elucidating individual aberrance is a critical first step toward precision medicine for heterogeneous disorders such as depression. The neuropathology of depression is related to abnormal inter-regional structural covariance indicating a brain maturational disruption. However, most studies focus on group-level structural covariance aberrance and ignore the interindividual heterogeneity. For that reason, we aimed to identify individualized structural covariance aberrance with the help of individualized differential structural covariance network (IDSCN) analysis.
T1-weighted anatomical images of 195 first-episode untreated patients with depression and matched healthy controls (n = 78) were acquired. We obtained IDSCN for each patient and identified subtypes of depression based on shared differential edges.
As a result, patients with depression demonstrated tremendous heterogeneity in the distribution of differential structural covariance edges. Despite this heterogeneity, altered edges within subcortical-cerebellum network were often shared by most of the patients. Two robust neuroanatomical subtypes were identified. Specifically, patients in subtype 1 often shared decreased motor network-related edges. Patients in subtype 2 often shared decreased subcortical-cerebellum network-related edges. Functional annotation further revealed that differential edges in subtype 2 were mainly implicated in reward/motivation-related functional terms.
In conclusion, we investigated individualized differential structural covariance and identified that decreased edges within subcortical-cerebellum network are often shared by patients with depression. The identified two subtypes provide new insights into taxonomy and facilitate potential clues to precision diagnosis and treatment of depression.
The role of dietary factors in osteoporotic fractures (OFs) in women is not fully elucidated. We investigated the associations between incidence of OF and dietary calcium, magnesium and soy isoflavone intake in a longitudinal study of 48 584 postmenopausal women. Multivariable Cox regression was applied to derive hazard ratios (HRs) and 95 % confidence intervals (CIs) to evaluate associations between dietary intake, based on the averages of two assessments that took place with a median interval of 2⋅4 years, and fracture risk. The average age of study participants is 61⋅4 years (range 43⋅3–76⋅7 years) at study entry. During a median follow-up of 10⋅1 years, 4⋅3 % participants experienced OF. Compared with daily calcium intake ≤400 mg/d, higher calcium intake (>400 mg/d) was significantly associated with about a 40–50 % reduction of OF risk among women with a calcium/magnesium (Ca/Mg) intake ratio ≥1⋅7. Among women with prior fracture history, high soy isoflavone intake was associated with reduced OF risk; the HR was 0⋅72 (95 % CI 0⋅55, 0⋅93) for the highest (>42⋅0 mg/d) v. lowest (<18⋅7 mg/d) quartile intake. This inverse association was more evident among recently menopausal women (<10 years). No significant association between magnesium intake and OF risk was observed. Our findings provide novel information suggesting that the association of OF risk with dietary calcium intake was modified by Ca/Mg ratio, and soy isoflavone intake was modified by history of fractures and time since menopause. Our findings, if confirmed, can help to guide further dietary intervention strategies for OF prevention.
This study evaluated the association between inflammatory diets as measured by the Dietary Inflammatory index (DII), inflammation biomarkers and the development of preeclampsia among the Chinese population. We followed the reporting guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology statement for observational studies. A total of 466 preeclampsia cases aged over 18 years were recruited between March 2016 and June 2019, and 466 healthy controls were 1:1 ratio matched by age (±3 years), week of gestation (±1 week) and gestational diabetes mellitus. The energy-adjusted DII (E-DII) was computed based on dietary intake assessed using a seventy-nine item semiquantitative FFQ. Inflammatory biomarkers were analysed by ELISA kits. The mean E-DII scores were −0·65 ± 1·58 for cases and −1·19 ± 1·47 for controls (P value < 0·001). E-DII scores positively correlated with interferon-γ (rs = 0·194, P value = 0·001) and IL-4 (rs = 0·135, P value = 0·021). After multivariable adjustment, E-DII scores were positively related to preeclampsia risk (Ptrend < 0·001). The highest tertile of E-DII was 2·18 times the lowest tertiles (95 % CI = 1·52, 3·13). The odds of preeclampsia increased by 30 % (95 % CI = 18 %, 43 %, P value < 0·001) for each E-DII score increase. The preeclampsia risk was positively associated with IL-2 (OR = 1·07, 95 % CI = 1·03, 1·11), IL-4 (OR = 1·26, 95 % CI = 1·03, 1·54) and transforming growth factor beta (TGF-β) (OR = 1·17, 95 % CI = 1·06, 1·29). Therefore, proinflammatory diets, corresponding to higher IL-2, IL-4 and TGF-β levels, were associated with increased preeclampsia risk.
Nosema bombycis is a destructive and specific intracellular parasite of silkworm, which is extremely harmful to the silkworm industry. N. bombycis is considered as a quarantine pathogen of sericulture because of its long incubation period and horizontal and vertical transmission. Herein, two single-chain antibodies targeting N. bombycis hexokinase (NbHK) were cloned and expressed in fusion with the N-terminal of Slmb (a Drosophila melanogaster FBP), which contains the F-box domain. Western blotting demonstrated that Sf9-III cells expressed NSlmb–scFv-7A and NSlmb–scFv-6H, which recognized native NbHK. Subsequently, the NbHK was degraded by host ubiquitination system. When challenged with N. bombycis, the transfected Sf9-III cells exhibited better resistance relative to the controls, demonstrating that NbHK is a prospective target for parasite controls and this approach represents a potential solution for constructing N. bombycis-resistant Bombyx mori.
We investigated the drug resistance of Mycobacterium tuberculosis isolates from patients with tuberculosis (TB) and HIV, and those diagnosed with only TB in Sichuan, China. TB isolates were obtained from January 2018 to December 2020 and subjected to drug susceptibility testing (DST) to 11 anti-TB drugs and to GeneXpert MTB/RIF testing. The overall proportion of drug-resistant TB (DR-TB) isolates was 32.1% (n = 10 946). HIV testing was not universally available for outpatient TB cases, only 29.5% (3227/10 946) cases had HIV testing results. The observed proportion of multidrug-resistant TB (MDR-TB) isolates was almost double than that of the national level, with approximately 1.5% and 0.1% of the isolates being extensively drug resistant and universally drug resistant, respectively. The proportions of resistant isolates were generally higher in 2018 and 2019 than in 2020. Furthermore, the sensitivities of GeneXpert during 2018–2020 demonstrated a downward trend (80.9, 95% confidence intervals (CI) 76.8–85.0; 80.2, 95% CI 76.4–84.1 and 75.4, 95% CI 70.7–80.2, respectively). Approximately 69.0% (7557/10 946) of the TB cases with DST results were subjected to GeneXpert detection. Overall, the DR-TB status and the use of GeneXpert in Sichuan have improved, but DR-TB challenges remain. HIV testing for all TB cases is recommended.
Coronavirus disease-2019 (COVID-19) elicits a range of different responses in patients and can manifest into mild to very severe cases in different individuals, depending on many factors. We aimed to establish a prediction model of severe risk in COVID-19 patients, to help clinicians achieve early prevention, intervention and aid them in choosing effective therapeutic strategy. We selected confirmed COVID-19 patients who were admitted to First Hospital of Changsha city between 29 January and 15 February 2020 and collected their clinical data. Multivariate logical regression was used to identify the factors associated with severe risk. These factors were incorporated into the nomogram to establish the model. The ROC curve, calibration plot and decision curve were used to assess the performance of the model. A total of 228 patients were enrolled and 33 (14.47%) patients developed severe pneumonia. Univariate and multivariate analysis showed that shortness of breath, fatigue, creatine kinase, lymphocytes and h CRP were independent factors for severe risk in COVID-19 patients. Incorporating age, chronic obstructive pulmonary disease (COPD) and these factors, the nomogram achieved good concordance indexes of 0.89 [95% confidence interval (CI) 0.832–0.949] and well-fitted calibration plot curves (Hosmer–Lemeshow test: P = 0.97). The model provided superior net benefit when clinical decision thresholds were between 15% and 85% predicted risk. Using the model, clinicians can intervene early, improve therapeutic effects and reduce the severity of COVID-19, thus ensuring more targeted and efficient use of medical resources.