An Optical Tweezer Array of Ultracold Molecules

Arrays of single ultracold molecules promise to be a powerful platform for many applications ranging from quantum simulation to precision measurement. Here we report on the creation of an optical tweezer array of single ultracold CaF molecules. By utilizing light-induced collisions during the laser cooling process, we trap single molecules. The high densities attained inside the tweezer traps have also enabled us to observe in the absence of light molecule-molecule collisions of laser cooled molecules for the first time

Application of machine learning algorithms to construct and validate a prediction model for coronary heart disease risk in patients with periodontitis: a population-based study

BackgroundThe association between periodontitis and cardiovascular disease is increasingly recognized. In this research, a prediction model utilizing machine learning (ML) was created and verified to evaluate the likelihood of coronary heart disease in individuals affected by periodontitis.MethodsWe conducted a comprehensive analysis of data obtained from the National Health and Nutrition Examination Survey (NHANES) database, encompassing the period between 2009 and 2014.This dataset comprised detailed information on a total of 3,245 individuals who had received a confirmed diagnosis of periodontitis. Subsequently, the dataset was randomly partitioned into a training set and a validation set at a ratio of 6:4. As part of this study, we conducted weighted logistic regression analyses, both univariate and multivariate, to identify risk factors that are independent predictors for coronary heart disease in individuals who have periodontitis. Five different machine learning algorithms, namely Logistic Regression (LR), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Classification and Regression Tree (CART), were utilized to develop the model on the training set. The evaluation of the prediction models’ performance was conducted on both the training set and validation set, utilizing metrics including AUC (Area under the receiver operating characteristic curve), Brier score, calibration plot, and decision curve analysis (DCA). Additionally, a graphical representation called a nomogram was created using logistic regression to visually depict the predictive model.ResultsThe factors that were found to independently contribute to the risk, as determined by both univariate and multivariate logistic regression analyses, encompassed age, race, presence of myocardial infarction, chest pain status, utilization of lipid-lowering medications, levels of serum uric acid and serum creatinine. Among the five evaluated machine learning models, the KNN model exhibited exceptional accuracy, achieving an AUC value of 0.977. The calibration plot and brier score illustrated the model's ability to accurately estimate probabilities. Furthermore, the model's clinical applicability was confirmed by DCA.ConclusionOur research showcases the effectiveness of machine learning algorithms in forecasting the likelihood of coronary heart disease in individuals with periodontitis, thereby aiding healthcare professionals in tailoring treatment plans and making well-informed clinical decisions

Automated quantitative gait analysis in animal models of movement disorders

<p>Abstract</p> <p>Background</p> <p>Accurate and reproducible behavioral tests in animal models are of major importance in the development and evaluation of new therapies for central nervous system disease. In this study we investigated for the first time gait parameters of rat models for Parkinson's disease (PD), Huntington's disease (HD) and stroke using the Catwalk method, a novel automated gait analysis test. Static and dynamic gait parameters were measured in all animal models, and these data were compared to readouts of established behavioral tests, such as the cylinder test in the PD and stroke rats and the rotarod tests for the HD group.</p> <p>Results</p> <p>Hemiparkinsonian rats were generated by unilateral injection of the neurotoxin 6-hydroxydopamine in the striatum or in the medial forebrain bundle. For Huntington's disease, a transgenic rat model expressing a truncated huntingtin fragment with multiple CAG repeats was used. Thirdly, a stroke model was generated by a photothrombotic induced infarct in the right sensorimotor cortex. We found that multiple gait parameters were significantly altered in all three disease models compared to their respective controls. Behavioural deficits could be efficiently measured using the cylinder test in the PD and stroke animals, and in the case of the PD model, the deficits in gait essentially confirmed results obtained by the cylinder test. However, in the HD model and the stroke model the Catwalk analysis proved more sensitive than the rotarod test and also added new and more detailed information on specific gait parameters.</p> <p>Conclusion</p> <p>The automated quantitative gait analysis test may be a useful tool to study both motor impairment and recovery associated with various neurological motor disorders.</p

Observation of Collisions between Two Ultracold Ground-State CaF Molecules

We measure inelastic collisions between ultracold CaF molecules by combining two optical tweezers, each containing a single molecule. We observe collisions between $^2\Sigma$ CaF molecules in the absolute ground state $|X,v=0, N=0,F=0\rangle$, and in excited hyperfine and rotational states. In the absolute ground state, we find a two-body loss rate of $7(4) \times 10^{-11} \text{cm}^{3}/\text{s}$, which is below, but close to the predicted universal loss rate.Comment: 5 pages, 4 figure

Raman sideband cooling of molecules in an optical tweezer array to the 3-D motional ground state

Ultracold polar molecules are promising for quantum information processing and searches for physics beyond the Standard Model. Laser cooling to ultracold temperatures is an established technique for trapped diatomic and triatomic molecules. Further cooling of the molecules to near the motional ground state is crucial for reducing various dephasings in quantum and precision applications. In this work, we demonstrate Raman sideband cooling of CaF molecules in optical tweezers to near their motional ground state, with average motional occupation quantum numbers of $\bar{n}_{x}=0.16(12)$, $\bar{n}_{y}=0.17(17)$ (radial directions), $\bar{n}_{z}=0.22(16)$ (axial direction) and a 3-D motional ground state probability of $54\pm18\%$. This paves the way to increase molecular coherence times in optical tweezers for robust quantum computation and simulation applications.Comment: 10 pages, 6 figure

Observation of Microwave Shielding of Ultracold Molecules

Harnessing the potential wide-ranging quantum science applications of molecules will require control of their interactions. Here, we use microwave radiation to directly engineer and tune the interaction potentials between ultracold calcium monofluoride (CaF) molecules. By merging two optical tweezers, each containing a single molecule, we probe collisions in three dimensions. The correct combination of microwave frequency and power creates an effective repulsive shield, which suppresses the inelastic loss rate by a factor of six, in agreement with theoretical calculations. The demonstrated microwave shielding shows a general route to the creation of long-lived, dense samples of ultracold molecules and evaporative cooling

Distinct lesion features and underlying mechanisms in patients with acute multiple infarcts in multiple cerebral territories

ObjectiveTo determine the etiology spectrum and lesion distribution patterns of patients with acute multiple infarcts in multiple cerebral territories (AMIMCT) and provide guidance for treatment and prevention strategies in these patients.MethodsPatients with acute ischemic stroke diagnosed using diffusion-weighted imaging (DWI) were consecutively included in this study between June 2012 and Apr 2022. AMIMCT was defined as non-contiguous focal lesions located in more than one cerebral territory with acute neurological deficits. We retrospectively analyzed the clinical and imaging characteristics, etiology spectra and underlying mechanisms in patients with and without AMIMCT. Infarct lesion patterns on DWI and their relevance to etiology were further discussed.ResultsA total of 1,213 patients were enrolled, of whom 145 (12%) were diagnosed with AMIMCT. Patients with AMIMCT tended to be younger (P = 0.016), more often female (P = 0.001), and exhibited less common conventional vascular risk factors (P &lt; 0.05) compared to those without AMIMCT. The constitution of the Trial of Org 10,172 in Acute Stroke Treatment classification was significantly different between patients with and without AMIMCT (P = 0.000), with a higher proportion of stroke of other determined causes (67.6% vs. 12.4%). For detailed etiologies, autoimmune or hematologic diseases were the most common (26.2%) etiologies of AMIMCT, followed by periprocedural infarcts (15.2%), cardioembolism (12.4%), tumor (12.4%), large artery atherosclerosis (10.3%), and sudden drop in blood pressure (8.3%). Hypercoagulability and systemic hypoperfusion are common underlying mechanisms of AMIMCT. Distinctive lesion distribution patterns were found associated with stroke etiologies and mechanisms in AMIMCT. Most of patients with large artery atherosclerosis (73.3%), autoimmune/hematologic diseases (57.9%) manifested the disease as multiple infarct lesions located in bilateral supratentorial regions. However, 66.7% of cardioembolism and 83.8% of cardiovascular surgery related stroke presented with both supratentorial and infratentorial infarct lesions.ConclusionThe etiologies and mechanisms of patients with AMIMCT were more complex than those without AMIMCT. The distribution characteristics of infarct lesions might have important implications for the identification of etiology and mechanism in the future, which could further guide and optimize clinical diagnostic strategies

Burden of dilated perivascular spaces in patients with moyamoya disease and moyamoya syndrome is related to middle cerebral artery stenosis

Background and objectiveThe correlation between intracranial large artery disease and cerebral small vessel disease (CSVD) has become a noteworthy issue. Dilated perivascular spaces (dPVS) are an important marker of CSVD, of which cerebral atrophy has been regarded as one of the pathological mechanisms. DPVS has been found to be associated with vascular stenosis in patients with moyamoya disease (MMD), but the underlying mechanism remains unclear. The purpose of our study was to explore the correlation between the middle cerebral artery (MCA) stenosis and dPVS in the centrum semiovale (CSO-dPVS) in patients with MMD/moyamoya syndrome (MMS) and to determine whether brain atrophy plays a mediating role in this relationship.MethodsA total of 177 patients were enrolled in a single-center MMD/MMS cohort. Images of their 354 cerebral hemispheres were divided into three groups according to dPVS burden: mild (dPVS 0–10), moderate (dPVS 11–20), and severe (dPVS &gt; 20). The correlations among cerebral hemisphere volume, MCA stenosis, and CSO-dPVS were analyzed, adjusting for the confounding factors of age, gender, and hypertension.ResultsAfter adjustment for age, gender, and hypertension, the degree of MCA stenosis was independently and positively associated with ipsilateral CSO-dPVS burden (standardized coefficient: β = 0.247, P &lt; 0.001). A stratified analysis found that the subgroup with a severe CSO-dPVS burden exhibited a significantly higher risk of severe stenosis of the MCA [p &lt; 0.001, OR = 6.258, 95% CI (2.347, 16.685)]. No significant correlation between CSO-dPVS and ipsilateral hemisphere volume was found (p = 0.055).ConclusionIn our MMD/MMS cohort, there was a clear correlation between MCA stenosis and CSO-dPVS burden, which may be a direct effect of large vessel stenosis, without a mediating role of brain atrophy

Consecutive Slides on Axial View Is More Effective Than Transversal Diameter to Differentiate Mechanisms of Single Subcortical Infarctions in the Lenticulostriate Artery Territory

Objective: Lipohyalinosis or atherosclerosis might be responsible for single subcortical infarctions (SSIs); however, ways of differentiating between the two clinically remain uncertain. We aimed to investigate whether consecutive slides on axial view or transversal diameter is more effective to differentiate mechanisms by comparing their relationships with white matter hyperintensities (WMHs).Methods: All the participants from the Standard Medical Management in Secondary Prevention of Ischemic stroke in China (SMART) cohort who had SSIs in the lenticulostriate artery territory were included and categorized according to consecutive slides on axial view (≥4 consecutive slices or not) and transversal diameter (≥15 mm or not). The associations between the severity of WMHs and the different categories were analyzed.Results: Among the 3,821 patients of the SMART study, 281 had diffusion-weighted image-proven SSIs in the lenticulostriate artery territory. When classified by consecutive slides on axial view, SSIs on ≥4 slices were significantly associated with the severity of the WMHs, both in deep WMH (DWMH) (odds ratio [OR], 0.32; 95% confidence interval [CI], 0.11–0.97; p = 0.04) and periventricular hyperintensity (PVH) (OR, 0.37; 95% CI, 0.17–0.78; p = 0.01). No such association was found on the basis of the transversal diameter (p &gt; 0.1).Conclusion: Consecutive slides on axial view (≥4 consecutive slices) might be more effective than transversal diameter to identify the atherosclerotic mechanisms of SSIs in the lenticulostriate artery territory.Clinical Trial Registration:http://www.clinicaltrials.gov. Unique identifier: NCT0066484