Efficient high-charge Laguerre-Gaussian mode conversion by using a periscopic axicon mirror

Laguerre-Gaussian (LG) modes can be converted from fundamental Gaussian mode by using phase optical elements such as spiral phase plates (SPP), but the conversion efficiency is strongly reduced in high charge plates because of the transverse intensity deviation. In this paper, a three-step scheme is proposed to dramatically improve the conversion efficiency. First, a fundamental Gaussian beam is converted to a 1st-order LG beam via a 1st-order SPP and a spatial filtering system. Then, by using a periscopic axicon mirror (PAM), the lst-order LG beam is transformed into an annular beam with larger beam radius. Finally, by using a second high-order SPP, this intensity-matched ring beam can be effectively converted to a high-charge LG0l beam. Through optimization of the PAM's parameter, the total conversion efficiency from fundamental Gaussian beam to LG0l mode as high as 91.85% is obtained, which is much higher than the case without PAM. Numerical simulations are carried out by the particle-in-cell (PIC) code EPOCH to verify the effectiveness of the scheme.

Five Major Psychiatric Disorders and Alzheimer’s Disease: A Bidirectional Mendelian Randomization Study

Background: Extensive studies put forward the association between Alzheimer’s disease (AD) and psychiatric disorders; however, it remains unclear whether these associations are causal. Objective: We aimed to assess the potential causal relationship between major psychiatric disorders and AD. Methods: A bidirectional two-sample Mendelian randomization (MR) was applied to evaluate potential causality between five psychiatric disorders and AD by selecting the single-nucleotide polymorphisms from the genome-wide association studies as instrumental variables. Inverse-variance weighted (IVW) method was used as the main analyzing approach to estimate possible causal effects, alternative methods including MR-Egger, the MR pleiotropy residual sum and outlier, and leave-one-out analysis method were implemented as sensitivity analyzing approaches to ensure the robustness of results. Results: All forward and reverse MR analyses consistently suggested absent causal relations between psychiatric disorders and AD risk [forward IVW: ORADHD, 1.030, 95% CI, 0.908–1.168, p = 0.674; ORanxiety disorders, 0.904, 95% CI, 0.722–1.131, p = 0.377; ORASD, 0.973, 95% CI, 0.746–1.272, p = 0.846; ORBIP, 1.033, 95% CI, 0.925–1.153, p = 0.564; and ORschizophrenia, 1.039, 95% CI, 0.986–1.095, p = 0.156; reverse IVW: ORADHD, 0.993, 95% CI, 0.954–1.034, p = 0.746; ORanxiety disorders, 1.000, 95% CI, 0.999–1.000, p = 0.898; ORASD, 1.001, 95% CI, 0.962–1.042, p = 0.949; ORBIP, 0.997, 95% CI, 0.966–1.028, p = 0.831; and ORschizophrenia, 1.013, 95% CI, 0.978–1.051, p = 0.466]. Conclusion: There is no significant evidence supporting the causal association between the five major psychiatric disorders and AD.

[Effect and influence factors of cardiopulmonary resuscitation in children with congenital heart disease in pediatric intensive care unit]

Objective: To investigate the prognostic factors of children with congenital heart disease (CHD) who had undergone cardiopulmonary resuscitation (CPR) in pediatric intensive care unit (PICU) in China. Methods: From November 2017 to October 2018, this retrospective multi-center study was conducted in 11 hospitals in China. It contained data from 281 cases who had undergone CPR and all of the subjects were divided into CHD group and non-CHD group. The general condition, duration of CPR, epinephrine doses during resuscitation, recovery of spontaneous circulation (ROSC), discharge survival rate and pediatric cerebral performance category in viable children at discharge were compared. According to whether malignant arrhythmia is the direct cause of cardiopulmonary arrest or not, children in CHD and non-CHD groups were divided into 2 subgroups: arrhythmia and non-arrhythmia, and the ROSC and survival rate to discharge were compared. Data in both groups were analyzed by t-test, chi-square analysis or ANOVA, and logistic regression were used to analyze the prognostic factors for ROSC and survival to discharge after cardiac arrest (CA). Results: The incidence of CA in PICU was 3.2% (372/11 588), and the implementation rate of CPR was 75.5% (281/372). There were 144 males and 137 females with median age of 32.8 (5.6, 42.7) months in all 281 CPA cases who received CPR. CHD group had 56 cases while non-CHD had 225 cases, with the percentage of 19.9% (56/281) and 80.1% (225/281) respectively. The proportion of female in CHD group was 60.7% (34/56) which was higher than that in non-CHD group (45.8%, 103/225) (χ²=4.00, P=0.045). There were no differences in ROSC and rate of survival to discharge between the two groups (P>0.05). The ROSC rate of children with arthythmid in CHD group was 70.0% (28/40), higher than 6/16 for non-arrhythmic children (χ²=5.06, P=0.024). At discharge, the pediatric cerebral performance category scores (1-3 scores) of CHD and non-CHD child were 50.9% (26/51) and 44.9% (92/205) respectively. Logistic regression analysis indicated that the independent prognostic factors of ROSC and survival to discharge in children with CHD were CPR duration (odds ratio (OR)=0.95, 0.97; 95%CI: 0.92~0.97, 0.95~0.99; both P<0.05) and epinephrine dosage (OR=0.87 and 0.79, 95%CI: 0.76-1.00 and 0.69-0.89, respectively; both P<0.05). Conclusions: There is no difference between CHD and non-CHD children in ROSC and survival rate of survival to discharge was low. The epinephrine dosage and the duration of CPR are related to the ROSC and survival to discharge of children with CHD.

Geniposidic Acid Confers Neuroprotective Effects in a Mouse Model of Alzheimer's Disease through Activation of a PI3K/AKT/GAP43 Regulatory Axis

BACKGROUND

Alzheimer's disease (AD) is a major cause of dementia, which is a growing global health problem and has a huge impact on individuals and society. As the modifying role of geniposidic acid (GPA) has been suggested in AD, this study sets out to determine if and how GPA treatment affects AD progression in mice.

METHODS

Potential downstream target genes of GPA during AD were identified by bioinformatics analysis, revealing GAP43 as a primary candidate protein. Then, mPrP-APPswe/PS1De9 AD transgenic mice were treated with GPA via intragastric administration. This allowed for gain- and loss-of-function assays of candidate proteins being carried out with or without GPA treatment, after which behavioral tests could be conducted for mice. Cortical neuron apoptosis was measured by TUNEL staining, Amyloid β-protein (Aβ) expression in cerebral cortex by Thioflavin-s staining, and Aβ, IL-1β, IL-6, IL-4 and TNF-α levels in cerebral cortex by ELISA. GAP43 expression in cerebral cortex of mice was detected by immunohistochemistry. Primary cortical neurons of embryonic mice were isolated and induced by Aβ1-42 to construct AD cell model. Cell viability was assessed by CCK-8, and axon growth by immunofluorescence.

RESULTS

GPA administration significantly improved the cognitive impairment, reducing Aβ accumulation and neuronal apoptosis in AD mice, and alleviated inflammation and axonal injury of Aβ1-42-induced neurons. GAP43 was shown experimentally to be the target of GPA in AD. Silencing of GAP43 repressed the neuroprotective effect of GPA treatment on AD mice. GPA elevated GAP43 expression via PI3K/AKT pathway activation and ultimately improved nerve injury in AD mice.

CONCLUSION

GPA activates a PI3K/AKT/GAP43 regulatory axis to alleviate AD progression in mice.

Implication of microglia in ketamine-induced long-term cognitive impairment in murine pups

BACKGROUND

Ketamine, a non-competitive N-methyl-D-aspartate receptor (NMDAR) antagonist, is widely applicable to anesthesia, analgesia, and sedation. However, the function and mechanisms of ketamine in the long-term learning and memory function of neonatal mice are unclear.

OBJECTIVE

The present study aims to investigate whether long-term learning and memory function will be affected by multiple ketamine exposures in the early development period.

METHODS

The mRNA and protein levels were measured by RT-qPCR and western blot, respectively. The Morris Water Maze test was performed to assess spatial learning and memory.

RESULTS

We identified that neonatal exposure to ketamine downsized the positive neurons for microtubule-associated protein doublecortin (DCX) and Ki67 in hippocampal dentate gyrus at the juvenile and late adolescence stages. Double-labeling tests demonstrated that the counts of Iba1⁺ cells and Ki67⁺ cells were pronouncedly diminished with exposure to ketamine. Further, qPCR assays to screen the key factors predisposing the populations and maturation of microglia exhibited remarkable decline of CX3CR1 mRNA levels in ketamine group versus the control group. The close relation of microglia to synaptic plasticity was depicted by the significantly downregulated synaptic plasticity-related proteins NR2B and PSD-95 subsequent to multiple exposures to ketamine. Finally, we found that both the protein and mRNA levels of BDNF were markedly decreased in ketamine group versus the control group.

CONCLUSION

We found that multiple exposures to ketamine in neonatal mice lead to spatial learning and memory dysfunction. The alterations of microglial development and function are the possible mechanisms of long-term learning and memory impairment.

Machine learning in the differentiation of follicular lymphoma from diffuse large B-cell lymphoma with radiomic [18F]FDG PET/CT features

BACKGROUND

One of the challenges in the management of patients with follicular lymphoma (FL) is the identification of individuals with histological transformation, most commonly into diffuse large B-cell lymphoma (DLBCL). [¹⁸F]FDG-PET/CT is used for staging of patients with lymphoma, but visual interpretation cannot reliably discern FL from DLBCL. This study evaluated whether radiomic features extracted from clinical baseline [¹⁸F]FDG PET/CT and analyzed by machine learning algorithms may help discriminate FL from DLBCL.

MATERIALS AND METHODS

Patients were selected based on confirmed histopathological diagnosis of primary FL (n=44) or DLBCL (n=76) and available [¹⁸F]FDG PET/CT with EARL reconstruction parameters within 6 months of diagnosis. Radiomic features were extracted from the volume of interest on co-registered [¹⁸F]FDG PET and CT images. Analysis of selected radiomic features was performed with machine learning classifiers based on logistic regression and tree-based ensemble classifiers (AdaBoosting, Gradient Boosting, and XG Boosting). The performance of radiomic features was compared with a SUV_max-based logistic regression model.

RESULTS

From the segmented lesions, 121 FL and 227 DLBCL lesions were included for radiomic feature extraction. In total, 79 radiomic features were extracted from the SUVmap, 51 from CT, and 6 shape features. Machine learning classifier Gradient Boosting achieved the best discrimination performance using 136 radiomic features (AUC of 0.86 and accuracy of 80%). SUV_max-based logistic regression model achieved an AUC of 0.79 and an accuracy of 70%. Gradient Boosting classifier had a significantly greater AUC and accuracy compared to the SUV_max-based logistic regression (p≤0.01).

CONCLUSION

Machine learning analysis of radiomic features may be of diagnostic value for discriminating FL from DLBCL tumor lesions, beyond that of the SUV_max alone.

Lipid Metabolism in the Development and Progression of Vascular Cognitive Impairment: A Systematic Review

Background: Vascular cognitive impairment (VCI) is a major public health problem. The current diagnosis of VCI is made based on the assessment of clinical symptoms and neuropsychological measurements, and is supported by neuroimaging. These methods are both time-consuming and expensive, which leads to needs for alternative biomarkers for VCI. Metabolomics is an emerging and powerful tool to discover of new biomarkers of disease, which can investigate variations in different metabolic processes such as lipid, since the brain is highly enriched in lipids and that lipid changes may lead to pathology in the brain. Vascular cognitive impairment is vulnerable to the disturbance of lipid metabolism. Furthermore, blood samples, which could be identified as reliable clinical biomarkers are relatively convenient to obtain and provide a non-invasive assessment. Therefore, our study aims to understand whether peripheral lipid biomarkers can be used as diagnostic biomarkers and monitor the progression of VCI.

Methods: We systematically searched the PubMed, Embase, CNKI, and VIP databases to find VCI and lipid metabolism in reports from inception through February 2021. Studies meeting the following criteria were eligible: (1) original studies in humans; (2) lipid metabolites in blood; (3) reports of VCI.

Results: Through our review, nine original articles were eligible. Blood-based metabolites that might be potential biomarkers were identified. Most of them including PC, PE, Cers, and ChEs were significantly lower, while elevation of FAs and DGs were associated with VCI. Most importantly, these blood-based metabolites might be proposed as potential biomarkers for VCI, which provides direction for further validation.

Discussion and Conclusion: To the best of our knowledge, this is the first systemic review concerning the relationship of lipid metabolism and VCI. It identifies potential biomarkers and provides insights into the disease pathobiology. However, more advanced studies and researches on a lipidomic platform must be done to understand the exact pathology behind and identify potential lipid biomarkers, which might help achieve the goal of discovering novel therapeutics.

EGFR testing patterns and detection of EGFR exon 20 insertions among patients with NSCLC in the US

Introduction/Objective

Epidermal growth factor receptor (EGFR) mutations are common in non-small cell lung cancer (NSCLC). EGFR exon 20 insertions (EGFRex20ins), a rare subset of EGFR mutations, are refractory to tyrosine kinase inhibitors. With the development of targeted therapies for EGFRex20ins, such as mobocertinib, molecular testing is required to optimize treatment. A better understanding of real-world EGFR detection patterns is needed to maximize patient outcomes.

Methods/Case Report

This retrospective study describes EGFR testing and EGFRex20ins detection patterns in patients with NSCLC in the United States. The Flatiron Health electronic health record database was used to identify patients ≥18 years, with advanced NSCLC, and with ≥2 clinic visits between 01/01/2011 and 12/31/2020. Baseline demographics, clinical characteristics, EGFR testing, and EGFRex20ins detection rates by sex, race, and smoking history were summarized.

Results (if a Case Study enter NA)

A total of 67,281 patients with NSCLC were identified. EGFR testing increased from 44% in 2011 to 77% in 2020. Of all patients, 44,926 (66.8%) were tested: 50.8% female; 3.3% Asian; 16.0% never-smokers. Of all patients, 22,355 (33.2%) were not tested: 41.4% female; 1.2% Asian; 7.5% never-smokers. Of those tested, 6,245 (13.9%) patients had EGFR mutations: 65.9% female; 11.8% Asian; 48.4% never-smokers.

EGFRex20ins detection rates changed from 0.6% in 2011 to 1.0% in 2019 and 0.7% in 2020. Of those tested, 304 patients had EGFRex20ins: 58.2% female; 8.2% Asian; 50.3% never-smokers. EGFR testing was higher in females (71.2%) than males (62.8%), never-smokers (84.5%) than those with a smoking history (64.6%), and Asian patients (84.2%) than White (66.6%), Black (65.4%), or other patients (69.5%). Of those tested, EGFRex20ins mutations were detected in 0.8% of females (males: 0.6%), 2.2% of never-smokers (with smoking history: 0.4%), and 1.7% of Asians (White: 0.6%, Black: 0.6%, other patients: 0.7%) had EGFRex20ins. A similar trend was observed for EGFR mutations with higher proportions of females, never-smokers, and Asian patients affected.

Conclusion

EGFR testing and EGFRex20ins detection rates have increased. However, not all patient subgroups were tested at the same rate and undertesting occurred in all subgroups. Further education of specialists diagnosing NSCLC is warranted to ensure all patients receive biomarker testing and benefit from emerging EGFRex20ins- targeted therapies.

Deceleration and Trapping of SrF Molecules

We report on the electrostatic trapping of neutral SrF molecules. The molecules are captured from a cryogenic buffer-gas beam source into the moving traps of a 4.5-m-long traveling-wave Stark decelerator. The SrF molecules in X^{2}Σ^{+}(v=0,N=1) state are brought to rest as the velocity of the moving traps is gradually reduced from 190  m/s to zero. The molecules are held for up to 50 ms in multiple electric traps of the decelerator. The trapped packets have a volume (FWHM) of 1  mm^{3} and a velocity spread of 5(1)  m/s, which corresponds to a temperature of 60(20) mK. Our result demonstrates a factor 3 increase in the molecular mass that has been Stark decelerated and trapped. Heavy molecules (mass>100  amu) offer a highly increased sensitivity to probe physics beyond the standard model. This work significantly extends the species of neutral molecules of which slow beams can be created for collision studies, precision measurement, and trapping experiments.

P Doping Promotes the Spontaneous Visible-Light-Driven Photocatalytic Water Splitting in Isomorphic Type II GaSe/InS Heterostructure

The development and design of clean and efficient water splitting photocatalysts is important for the current situation of energy shortage and environmental pollution. A new type of isomorphic GaSe/InS heterostructure is constructed, and the optoelectronic properties were studied through first-principles calculations. The results show that GaSe/InS vdW heterostructure is a type II semiconductor with a band gap of 2.09 eV. However, through the analysis of the energy band edge position and Gibbs free energy change of water splitting, it is found that the GaSe/InS heterostructure is difficult to undergo overall water splitting. Therefore, nonmetallic element P doping is considered, the established P-doped GaSe/InS (P-GaSe/InS) heterostructure could maintain the type II band arrangement, and under acidic conditions, P-GaSe/InS heterostructure could spontaneously undergo overall water splitting thermodynamically. Furthermore, the low exciton binding energy of P-GaSe/InS heterostructure highlights better light absorption performance. Therefore, these findings indicate that P-GaSe/InS heterostructure is a promising photocatalyst in overall water splitting.