Improving OFDR sensing performance based on SEFR in both reference and measurement stages.

In addition to laser frequency sweep nonlinearity, sensing point misalignment caused by a random laser frequency sweep range (LFSR) is a key factor limiting the sensing performance of the optical frequency domain reflectometer (OFDR). Here we propose a synchronous equal frequency resampling (SEFR) method for the first time to our knowledge to simultaneously compensate both the random LFSR and sweep nonlinearity. A new linear frequency sequence has been constructed to perform signal resampling of both the reference and measurement stages, which eliminates the sensing point misalignment and nonlinear frequency interval at the same time.

Observation of heat pumping effect by radiative shuttling.

Heat shuttling phenomenon is characterized by the presence of a non-zero heat flow between two bodies without net thermal bias on average. It was initially predicted in the context of nonlinear heat conduction within atomic lattices coupled to two time-oscillating thermostats. Recent theoretical works revealed an analog of this effect for heat exchanges mediated by thermal photons between two solids having a temperature dependent emissivity.

Machine intelligence accelerated design of conductive MXene aerogels with programmable properties.

Designing ultralight conductive aerogels with tailored electrical and mechanical properties is critical for various applications. Conventional approaches rely on iterative, time-consuming experiments across a vast parameter space. Herein, an integrated workflow is developed to combine collaborative robotics with machine learning to accelerate the design of conductive aerogels with programmable properties.

Few-Shot Classification with Multiscale Feature Fusion for Clinical Skin Disease Diagnosis.

Introduction: Skin disease is one of the most common diseases and can affect people of all ages and races. However, the diagnosis of skin diseases via observation is a highly challenging task for both doctors and patients, and would benefit from the use of an intelligent system. Building a large benchmark with professional dermatologists is resource-intensive, and we believe that few-shot learning (FSL) methods would be helpful in solving the problem of annotated data scarcity.

Results from the long-term extension of PRIME: A randomized Phase 1b trial of aducanumab.

Introduction: Aducanumab selectively targets aggregated forms of amyloid beta (Aβ), a neuropathological hallmark of Alzheimer's disease (AD).

Methods: PRIME was a Phase 1b, double-blind, randomized clinical trial of aducanumab. During the 12-month placebo-controlled period, participants with prodromal AD or mild AD dementia were randomized to receive aducanumab or placebo.

Machine intelligence-accelerated discovery of all-natural plastic substitutes.

One possible solution against the accumulation of petrochemical plastics in natural environments is to develop biodegradable plastic substitutes using natural components. However, discovering all-natural alternatives that meet specific properties, such as optical transparency, fire retardancy and mechanical resilience, which have made petrochemical plastics successful, remains challenging. Current approaches still rely on iterative optimization experiments.

Machine Learning Integrated Workflow for Predicting Schwann Cell Viability on Conductive MXene Biointerfaces.

Severe injuries to the peripheral nervous system (PNS) require Schwann cells to aid in neuronal regeneration. Low-frequency electrical stimulation is known to induce the cogrowth of neurons and Schwann cells in an injured PNS. However, the correlations between electrical stimulation and Schwann cell viability are complex and not well understood.

Generating Semantic Adversarial Examples via Feature Manipulation in Latent Space.

The susceptibility of deep neural networks (DNNs) to adversarial intrusions, exemplified by adversarial examples, is well-documented. Conventional attacks implement unstructured, pixel-wise perturbations to mislead classifiers, which often results in a noticeable departure from natural samples and lacks human-perceptible interpretability. In this work, we present an adversarial attack strategy that implements fine-granularity, semantic-meaning-oriented structural perturbations.

Multistage orbital hybridization induced by multisite exchange interactions in high-entropy perovskites for high oxygen evolution reaction.

The oxygen evolution reaction (OER) has garnered considerable attention because of its promising prospects in electrochemical energy conversion applications, but a significant challenge is faced by the insufficient understanding of sluggish OER kinetics. In fact, the intrinsic "acceptance-donation" process of electrons between active sites and reactants is responsible for improving OER activity. Herein, we suggest a multielement hybridization strategy to rematch spin electron occupation and energy splitting in high-entropy perovskites with multiple orbital coordination.

CSF biomarker concordance with amyloid PET in Phase 3 studies of aducanumab.

Introduction: We assessed the use of cerebrospinal fluid (CSF) biomarkers as an alternative to positron emission tomography (PET) for brain amyloid beta (Aβ) pathology confirmation in the EMERGE and ENGAGE clinical trials.

Methods: EMERGE and ENGAGE were randomized, placebo-controlled, Phase 3 trials of aducanumab in participants with early Alzheimer's disease. Concordance between CSF biomarkers (Aβ42, Aβ40, phosphorylated tau 181, and total tau) and amyloid PET status (visual read) at screening was examined.

Discovery of cysteine-targeting covalent histone methyltransferase inhibitors.

Post-translational methylation of histone lysine or arginine residues by histone methyltransferases (HMTs) plays crucial roles in gene regulation and diverse physiological processes and is implicated in a plethora of human diseases, especially cancer. Therefore, histone methyltransferases have been increasingly recognized as potential therapeutic targets. Consequently, the discovery and development of histone methyltransferase inhibitors have been pursued with steadily increasing interest over the past decade.

Factors affecting acceptance of organ donation in mainland China: A national cross-sectional study.

Aims And Objectives: To explore the acceptances and associated influences of organ donation in mainland China.

Background: The shortage of organ donors has limited the development of organ transplantation in China. It is important to recognise the target population who has high intention to donate their organs may change the status.

Posttranslational modifications optimize the ability of SARS-CoV-2 spike for effective interaction with host cell receptors.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein is the prime target for vaccines, diagnostics, and therapeutic antibodies against the virus. While anchored in the viral envelope, for effective virulence, the spike needs to maintain structural flexibility to recognize the host cell surface receptors and bind to them, a property that can heavily depend upon the dynamics of the unresolved domains, most prominently the stalk. Construction of the complete, membrane-bound spike model and the description of its dynamics are critical steps in understanding the inner working of this key element of the viral infection by SARS-CoV-2.

Construction and external validation of a 5-gene random forest model to diagnose non-obstructive azoospermia based on the single-cell RNA sequencing of testicular tissue.

Non-obstructive azoospermia (NOA) is among the most severe factors for male infertility, but our understandings of the latent biological mechanisms remain insufficient. The single-cell RNA sequencing (scRNA-seq) data of 432 testicular cells isolated from the patient with NOA was analyzed, and the cell samples were grouped into 5 cell clusters. A sum of 455 cell markers was identified and then included in the protein-protein interaction network.

Impact of Reference and Target Region Selection on Amyloid PET SUV Ratios in the Phase 1b PRIME Study of Aducanumab.

SUV ratios (SUVRs) are commonly used to quantify tracer uptake in amyloid-β PET. Here, we explore the impact of target and reference region-of-interest (ROI) selection on SUVR effect sizes using interventional data from the ongoing phase 1b PRIME study (NCT01677572) of aducanumab (BIIB037) in patients with prodromal or mild Alzheimer disease. The florbetapir PET SUVR was calculated at baseline (screening) and at weeks 26 and 54 for patients randomized to receive placebo and each of 4 aducanumab doses (1, 3, 6, and 10 mg/kg) using the whole cerebellum, cerebellar gray matter, cerebellar white matter, pons, and subcortical white matter as reference regions.

Addendum: The antibody aducanumab reduces Aβ plaques in Alzheimer's disease.

This corrects the article DOI: 10.1038/nature21361.

Purification, structural features, antioxidant and moisture-preserving activities of an exopolysaccharide from Lachnum YM262.

A water-soluble exopolysaccharide, designated as LEP-2a, was isolated from Lachnum YM262 and purified by DEAE-Cellulose 52 and Sepharose CL-6B chromatographic columns. LEP-2a was a homogeneous polysaccharide, with a molecular weight of 1.52×10 Da.

Support Vector Hazards Machine: A Counting Process Framework for Learning Risk Scores for Censored Outcomes.

Learning risk scores to predict dichotomous or continuous outcomes using machine learning approaches has been studied extensively. However, how to learn risk scores for time-to-event outcomes subject to right censoring has received little attention until recently. Existing approaches rely on inverse probability weighting or rank-based regression, which may be inefficient.

The antibody aducanumab reduces Aβ plaques in Alzheimer's disease.

Alzheimer's disease (AD) is characterized by deposition of amyloid-β (Aβ) plaques and neurofibrillary tangles in the brain, accompanied by synaptic dysfunction and neurodegeneration. Antibody-based immunotherapy against Aβ to trigger its clearance or mitigate its neurotoxicity has so far been unsuccessful. Here we report the generation of aducanumab, a human monoclonal antibody that selectively targets aggregated Aβ.

Amyloid PET Screening for Enrichment of Early-Stage Alzheimer Disease Clinical Trials: Experience in a Phase 1b Clinical Trial.

Amyloid positron emission tomography (PET) imaging is being investigated as a screening tool to identify amyloid-positive patients as an enrichment strategy for Alzheimer disease (AD) clinical trial enrollment. In a multicenter, phase 1b trial, patients meeting clinical criteria for prodromal or mild AD underwent florbetapir PET scanning at screening. PET, magnetic resonance imaging, and coregistered PET/magnetic resonance imaging scans were reviewed by 2 independent readers and binary visual readings tabulated.

Multiple kernel learning with random effects for predicting longitudinal outcomes and data integration.

Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although, kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data, but not for longitudinal data.

Predicting cumulative risk of disease onset by redistributing weights.

We propose a simple approach predicting the cumulative risk of disease accommodating predictors with time-varying effects and outcomes subject to censoring. We use a nonparametric function for the coefficient of the time-varying effect and handle censoring through self-consistency equations that redistribute the probability mass of censored outcomes to the right. The computational procedure is extremely convenient and can be implemented by standard software.