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The great demographic pressure brings tremendous volume of beef demand. The key to solve this problem is the growth and development of Chinese cattle. In order to find molecular markers conducive to the growth and development of Chinese cattle, sequencing was used to determine the position of copy number variations (CNVs), bioinformatics analysis was used to predict the function of ZNF146 gene, real-time fluorescent quantitative polymerase chain reaction (qPCR) was used for CNV genotyping and one-way analysis of variance was used for association analysis. The results showed that there exists CNV in Chr 18: 47225201-47229600 (5.0.1 version) of ZNF146 gene through the early sequencing results in the laboratory and predicted ZNF146 gene was expressed in liver, skeletal muscle and breast cells, and was amplified or overexpressed in pancreatic cancer, which promoted the development of tumour through bioinformatics. Therefore, it is predicted that ZNF146 gene affects the proliferation of muscle cells, and then affects the growth and development of cattle. Furthermore, CNV genotyping of ZNF146 gene was three types (deletion type, normal type and duplication type) by Real-time fluorescent quantitative PCR (qPCR). The association analysis results showed that ZNF146-CNV was significantly correlated with rump length of Qinchuan cattle, hucklebone width of Jiaxian red cattle and heart girth of Yunling cattle. From the above results, ZNF146-CNV had a significant effect on growth traits, which provided an important candidate molecular marker for growth and development of Chinese cattle.
We describe a large outbreak of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) involving an acute-care hospital emergency department during December 2020 and January 2021, in which 27 healthcare personnel worked while infectious, resulting in multiple opportunities for SARS-CoV-2 transmission to patients and other healthcare personnel. We provide recommendations for improving infection prevention and control.
The incidence of scarlet fever has increased dramatically in recent years in Chongqing, China, but there has no effective method to forecast it. This study aimed to develop a forecasting model of the incidence of scarlet fever using a seasonal autoregressive integrated moving average (SARIMA) model. Monthly scarlet fever data between 2011 and 2019 in Chongqing, China were retrieved from the Notifiable Infectious Disease Surveillance System. From 2011 to 2019, a total of 5073 scarlet fever cases were reported in Chongqing, the male-to-female ratio was 1.44:1, children aged 3–9 years old accounted for 81.86% of the cases, while 42.70 and 42.58% of the reported cases were students and kindergarten children, respectively. The data from 2011 to 2018 were used to fit a SARIMA model and data in 2019 were used to validate the model. The normalised Bayesian information criterion (BIC), the coefficient of determination (R2) and the root mean squared error (RMSE) were used to evaluate the goodness-of-fit of the fitted model. The optimal SARIMA model was identified as (3, 1, 3) (3, 1, 0)12. The RMSE and mean absolute per cent error (MAPE) were used to assess the accuracy of the model. The RMSE and MAPE of the predicted values were 19.40 and 0.25 respectively, indicating that the predicted values matched the observed values reasonably well. Taken together, the SARIMA model could be employed to forecast scarlet fever incidence trend, providing support for scarlet fever control and prevention.
For a common micro-satellite, orbiting in a circular sun-synchronous orbit (SSO) at an altitude between 500 and 600km, the satellite attitude during off-nadir imaging and staring-imaging operations can be up to ±45 degree on roll and pitch angles. During these off-nadir pointing for both multi-trip operation and staring imaging operations, the spacecraft body is commonly subject to high-rate motion. This posts challenges for a spacecraft attitude determination subsystem called Gyro Stellar Inertial Attitude Estimate (GS IAE), which employs gyros and star sensors to maintain the required attitude knowledge, since star trackers will severely degrade attitude estimation accuracies when the spacecraft is subject to high-rate motion. This paper analyses the star motion-induced errors for a typical star tracker, models the star motion-induced errors to assess the performance impact on the attitude estimation accuracy, and investigates the adaptive extended Kalman filter design in the GS IAE while evaluating its effectiveness.
Identification of treatment-specific predictors of drug therapies for bipolar disorder (BD) is important because only about half of individuals respond to any specific medication. However, medication response in pediatric BD is variable and not well predicted by clinical characteristics.
A total of 121 youth with early course BD (acute manic/mixed episode) were prospectively recruited and randomized to 6 weeks of double-blind treatment with quetiapine (n = 71) or lithium (n = 50). Participants completed structural magnetic resonance imaging (MRI) at baseline before treatment and 1 week after treatment initiation, and brain morphometric features were extracted for each individual based on MRI scans. Positive antimanic treatment response at week 6 was defined as an over 50% reduction of Young Mania Rating Scale scores from baseline. Two-stage deep learning prediction model was established to distinguish responders and non-responders based on different feature sets.
Pre-treatment morphometry and morphometric changes occurring during the first week can both independently predict treatment outcome of quetiapine and lithium with balanced accuracy over 75% (all p < 0.05). Combining brain morphometry at baseline and week 1 allows prediction with the highest balanced accuracy (quetiapine: 83.2% and lithium: 83.5%). Predictions in the quetiapine and lithium group were found to be driven by different morphometric patterns.
These findings demonstrate that pre-treatment morphometric measures and acute brain morphometric changes can serve as medication response predictors in pediatric BD. Brain morphometric features may provide promising biomarkers for developing biologically-informed treatment outcome prediction and patient stratification tools for BD treatment development.
We report the experimental results of the commissioning phase in the 10 PW laser beamline of the Shanghai Superintense Ultrafast Laser Facility (SULF). The peak power reaches 2.4 PW on target without the last amplifying during the experiment. The laser energy of 72 ± 9 J is directed to a focal spot of approximately 6 μm diameter (full width at half maximum) in 30 fs pulse duration, yielding a focused peak intensity around 2.0 × 1021 W/cm2. The first laser-proton acceleration experiment is performed using plain copper and plastic targets. High-energy proton beams with maximum cut-off energy up to 62.5 MeV are achieved using copper foils at the optimum target thickness of 4 μm via target normal sheath acceleration. For plastic targets of tens of nanometers thick, the proton cut-off energy is approximately 20 MeV, showing ring-like or filamented density distributions. These experimental results reflect the capabilities of the SULF-10 PW beamline, for example, both ultrahigh intensity and relatively good beam contrast. Further optimization for these key parameters is underway, where peak laser intensities of 1022–1023 W/cm2 are anticipated to support various experiments on extreme field physics.
The early identification and prediction of hand-foot-and-mouth disease (HFMD) play an important role in the disease prevention and control. However, suitable models are different in regions due to the differences in geography, social economy factors. We collected data associated with daily reported HFMD cases and weather factors of Zibo city in 2010~2019 and used the generalised additive model (GAM) to evaluate the effects of weather factors on HFMD cases. Then, GAM, support vectors regression (SVR) and random forest regression (RFR) models are used to compare predictive results. The annual average incidence was 129.72/100 000 from 2010 to 2019. Its distribution showed a unimodal trend, with incidence increasing from March, peaking from May to September. Our study revealed the nonlinear relationship between temperature, rainfall and relative humidity and HFMD cases and based on the predictive result, the performances of three models constructed ranked in descending order are: SVR > GAM> RFR, and SVR has the smallest prediction errors. These findings provide quantitative evidence for the prediction of HFMD for special high-risk regions and can help public health agencies implement prevention and control measures in advance.
The cosmic evolution of the chemical elements from the Big Bang to the present time is driven by nuclear fusion reactions inside stars and stellar explosions. A cycle of matter recurrently re-processes metal-enriched stellar ejecta into the next generation of stars. The study of cosmic nucleosynthesis and this matter cycle requires the understanding of the physics of nuclear reactions, of the conditions at which the nuclear reactions are activated inside the stars and stellar explosions, of the stellar ejection mechanisms through winds and explosions, and of the transport of the ejecta towards the next cycle, from hot plasma to cold, star-forming gas. Due to the long timescales of stellar evolution, and because of the infrequent occurrence of stellar explosions, observational studies are challenging, as they have biases in time and space as well as different sensitivities related to the various astronomical methods. Here, we describe in detail the astrophysical and nuclear-physical processes involved in creating two radioactive isotopes useful in such studies,
. Due to their radioactive lifetime of the order of a million years, these isotopes are suitable to characterise simultaneously the processes of nuclear fusion reactions and of interstellar transport. We describe and discuss the nuclear reactions involved in the production and destruction of
, the key characteristics of the stellar sites of their nucleosynthesis and their interstellar journey after ejection from the nucleosynthesis sites. This allows us to connect the theoretical astrophysical aspects to the variety of astronomical messengers presented here, from stardust and cosmic-ray composition measurements, through observation of
rays produced by radioactivity, to material deposited in deep-sea ocean crusts and to the inferred composition of the first solids that have formed in the Solar System. We show that considering measurements of the isotopic ratio of
eliminate some of the unknowns when interpreting astronomical results, and discuss the lessons learned from these two isotopes on cosmic chemical evolution. This review paper has emerged from an ISSI-BJ Team project in 2017–2019, bringing together nuclear physicists, astronomers, and astrophysicists in this inter-disciplinary discussion.
To describe the cumulative seroprevalence of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) antibodies during the coronavirus disease 2019 (COVID-19) pandemic among employees of a large pediatric healthcare system.
Design, setting, and participants:
Prospective observational cohort study open to adult employees at the Children’s Hospital of Philadelphia, conducted April 20–December 17, 2020.
Employees were recruited starting with high-risk exposure groups, utilizing e-mails, flyers, and announcements at virtual town hall meetings. At baseline, 1 month, 2 months, and 6 months, participants reported occupational and community exposures and gave a blood sample for SARS-CoV-2 antibody measurement by enzyme-linked immunosorbent assays (ELISAs). A post hoc Cox proportional hazards regression model was performed to identify factors associated with increased risk for seropositivity.
In total, 1,740 employees were enrolled. At 6 months, the cumulative seroprevalence was 5.3%, which was below estimated community point seroprevalence. Seroprevalence was 5.8% among employees who provided direct care and was 3.4% among employees who did not perform direct patient care. Most participants who were seropositive at baseline remained positive at follow-up assessments. In a post hoc analysis, direct patient care (hazard ratio [HR], 1.95; 95% confidence interval [CI], 1.03–3.68), Black race (HR, 2.70; 95% CI, 1.24–5.87), and exposure to a confirmed case in a nonhealthcare setting (HR, 4.32; 95% CI, 2.71–6.88) were associated with statistically significant increased risk for seropositivity.
Employee SARS-CoV-2 seroprevalence rates remained below the point-prevalence rates of the surrounding community. Provision of direct patient care, Black race, and exposure to a confirmed case in a nonhealthcare setting conferred increased risk. These data can inform occupational protection measures to maximize protection of employees within the workplace during future COVID-19 waves or other epidemics.
We report on experimental observation of non-laminar proton acceleration modulated by a strong magnetic field in laser irradiating micrometer aluminum targets. The results illustrate the coexistence of ring-like and filamentation structures. We implement the knife edge method into the radiochromic film detector to map the accelerated beams, measuring a source size of 30–110 μm for protons of more than 5 MeV. The diagnosis reveals that the ring-like profile originates from low-energy protons far off the axis whereas the filamentation is from the near-axis high-energy protons, exhibiting non-laminar features. Particle-in-cell simulations reproduced the experimental results, showing that the short-term magnetic turbulence via Weibel instability and the long-term quasi-static annular magnetic field by the streaming electric current account for the measured beam profile. Our work provides direct mapping of laser-driven proton sources in the space-energy domain and reveals the non-laminar beam evolution at featured time scales.
Background: Standardized magnetic resonance imaging (MRI) guidelines published in 2015 by the Europoean MAGNIMS group and in 2016 by the CMSC are important for the diagnosis and monitoring of patients with multiple sclerosis (MS) and for the appropriate use of MRI in routine clinical practice. Methods: Two panels of experts convened to update existing guidelines for a standardized MRI protocol. The MAGNIMS panel convened in Graz, Austria in April 2019. The CMSC NAIMS panel met separately and independently in Newark, USA in October 2019. Subsequently, the MAGNIMS, NAIMS, and CMSC working groups combined their efforts to reach an international consensus Results: The revised guidelines on MRI in MS merges recommendations from MAGNIMS, CMSC, and NAIMS to improve the use of MRI for diagnosis, prognosis and monitoring of individuals with MS. 3D acquisitions are emphasized for optimal comparison over time. Core brain sequences include a 3D-T2wFLAIR for lesion identification and monitoring treatment effectiveness. Gadolinium-based contrast is recommended for diagnostic studies and judicious use for routine monitoring of MS patients. DWI sequences are recommended for PML safety monitoring. Conclusions: The international consensus guidelines strive for global acceptance of a useful and usable standard of care for patients with MS.
This study investigated the audiometric and sound localisation results in patients with conductive hearing loss after bilateral Bonebridge implantation.
Eight patients with congenital microtia and atresia supplied with bilateral Bonebridge devices were enrolled in this study. Hearing tests and sound localisation were tested under unaided, unilateral and bilateral aided conditions.
Mean functional gain was higher with a bilateral fitting than with a unilateral fitting, especially at 1.0–4.0 kHz (p < 0.05, both). The improvement in speech reception threshold in noise with a bilateral fitting was a 2.3 dB higher signal-to-noise ratio compared with unilateral fitting (p < 0.05). Bilateral fitting had better sound localisation than unilateral fitting (p <0.001). Four participants who attended follow up showed improved sound localisation ability after one year.
Patients demonstrated better hearing threshold, speech reception thresholds in noise and directional hearing with bilateral Bonebridge devices than with a unilateral Bonebridge device. Sound localisation ability with bilateral Bonebridge devices can be improved through long-term training.
The extent of the reduction of maize (Zea mays L.) kernel moisture content through drying is closely related to field temperature (or accumulated temperature; AT) following maturation. In 2017 and 2018, we selected eight maize hybrids that are widely planted in Northeastern China to construct kernel drying prediction models for each hybrid based on kernel drying dynamics. In the traditional harvest scenario using the optimal sowing date (OSD), maize kernels underwent drying from 4th September to 5th October, with variation coefficients of 1.0–1.9. However, with a latest sowing date (LSD), drying occurred from 14th September to 31st October, with variation coefficients of 1.3–3.0. In the changed harvest scenario, the drying time of maize sown on the OSD condition was from 12th September to 9th November with variation coefficients of 1.3–3.0, while maize sown on the LSD had drying dates of 26th September to 28th October with variation coefficients of 1.5–3.6. In the future harvest scenario, the Fengken 139 (FK139) and Jingnongke 728 (JNK728) hybrids finished drying on 20th October and 8th November, respectively, when sown on the OSD and had variation coefficients of 2.7–2.8. Therefore, the maize kernel drying time was gradually delayed and was associated with an increased demand for AT ⩾ 0°C late in the growing season. Furthermore, we observed variation among different growing seasons likely due to differences in weather patterns, and that sowing dates impact variations in drying times to a greater extent than harvest scenarios.
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
First-episode psychosis (FEP) is a particularly high-risk period in which risk for suicide death is elevated by 60% as compared to individuals in later stages of psychotic illness. Clinical insight and cognition have been studied in schizophrenia in relation to suicide ideation and attempt, yet, less is understood within the context of early-phase of illness and FEP.
This study examined whether clinical insight and cognitive functioning served as a mechanism in the relationships between depression, positive symptoms, negative symptoms, and suicide ideation over time among individuals in FEP.
Data were obtained from the Recovery After an Initial Schizophrenia Episode (RAISE) project. Participants (n=404) included adults in FEP between ages 15 and 40. Structural equation modeling was used in Mplus8 to examine the proposed mediation model.
Clinical insight and working memory functioned as mechanisms in the relationships between depression, positive symptoms, negative symptoms, and suicide ideation. As depression decreased and positive and negative symptoms increased, clinical insight was shown to be poorer, which in turn related to decreased suicide ideation. As positive symptoms increased and negative symptoms decreased, working memory was shown to be stronger, which in turn related to decreased suicide ideation.
Implications surround the importance of cognitive testing and approaches aiming to strengthen cognitive functioning given the relationships between cognition and suicide ideation in FEP. Also, of importance, it is imperative practitioners have awareness of the insight paradox given the complex and dynamic relationships between clinical insight and suicide thoughts and behaviors.
In 829 hospital encounters for patients with COVID-19, 73.2% included orders for antibiotics; however, only 1.8% had respiratory cultures during the first 3 hospital days isolating bacteria. Case–control analysis of 30 patients and 96 controls found that each antibiotic day increased the risk of isolating multidrug-resistant gram-negative bacteria (MDR-GNB) in respiratory cultures by 6.5%.