TimeTector: A Twin-Branch Approach for Unsupervised Anomaly Detection in Livestock Sensor Noisy Data (TT-TBAD)

Unsupervised anomaly detection in multivariate time series sensor data is a complex task with diverse applications in different domains such as livestock farming and agriculture (LF&A), the Internet of Things (IoT), and human activity recognition (HAR). Advanced machine learning techniques are necessary to detect multi-sensor time series data anomalies. The primary focus of this research is to develop state-of-the-art machine learning methods for detecting anomalies in multi-sensor data. Time series sensors frequently produce multi-sensor data with anomalies, which makes it difficult to establish standard patterns that can capture spatial and temporal correlations. Our innovative approach enables the accurate identification of normal, abnormal, and noisy patterns, thus minimizing the risk of misinterpreting models when dealing with mixed noisy data during training. This can potentially result in the model deriving incorrect conclusions. To address these challenges, we propose a novel approach called "TimeTector-Twin-Branch Shared LSTM Autoencoder" which incorporates several Multi-Head Attention mechanisms. Additionally, our system now incorporates the Twin-Branch method which facilitates the simultaneous execution of multiple tasks, such as data reconstruction and prediction error, allowing for efficient multi-task learning. We also compare our proposed model to several benchmark anomaly detection models using our dataset, and the results show less error (MSE, MAE, and RMSE) in reconstruction and higher accuracy scores (precision, recall, and F1) against the baseline models, demonstrating that our approach outperforms these existing models.

Solvation-property relationship of lithium-sulphur battery electrolytes

The Li-S battery is a promising next-generation battery chemistry that offers high energy density and low cost. The Li-S battery has a unique chemistry with intermediate sulphur species readily solvated in electrolytes, and understanding their implications is important from both practical and fundamental perspectives. In this study, we utilise the solvation free energy of electrolytes as a metric to formulate solvation-property relationships in various electrolytes and investigate their impact on the solvated lithium polysulphides. We find that solvation free energy influences Li-S battery voltage profile, lithium polysulphide solubility, Li-S battery cyclability and the Li metal anode; weaker solvation leads to lower 1st plateau voltage, higher 2nd plateau voltage, lower lithium polysulphide solubility, and superior cyclability of Li-S full cells and Li metal anodes. We believe that relationships delineated in this study can guide the design of high-performance electrolytes for Li-S batteries.

Recovery of isolated lithium through discharged state calendar ageing

Rechargeable Li-metal batteries have the potential to more than double the specific energy of the state-of-the-art rechargeable Li-ion batteries, making Li-metal batteries a prime candidate for next-generation high-energy battery technology1-3. However, current Li-metal batteries suffer from fast cycle degradation compared with their Li-ion battery counterparts2,3, preventing their practical adoption. A main contributor to capacity degradation is the disconnection of Li from the electrochemical circuit, forming isolated Li4-8. Calendar ageing studies have shown that resting in the charged state promotes further reaction of active Li with the surrounding electrolyte9-12. Here we discover that calendar ageing in the discharged state improves capacity retention through isolated Li recovery, which is in contrast with the well-known phenomenon of capacity degradation observed during the charged state calendar ageing. Inactive capacity recovery is verified through observation of Coulombic efficiency greater than 100% on both Li||Cu half-cells and anode-free cells using a hybrid continuous-resting cycling protocol and with titration gas chromatography. An operando optical setup further confirms excess isolated Li reactivation as the predominant contributor to the increased capacity recovery. These insights into a previously unknown pathway for capacity recovery through discharged state resting emphasize the marked impact of cycling strategies on Li-metal battery performance.

Pig Movement Estimation by Integrating Optical Flow with a Multi-Object Tracking Model

Pig husbandry constitutes a significant segment within the broader framework of livestock farming, with porcine well-being emerging as a paramount concern due to its direct implications on pig breeding and production. An easily observable proxy for assessing the health of pigs lies in their daily patterns of movement. The daily movement patterns of pigs can be used as an indicator of their health, in which more active pigs are usually healthier than those who are not active, providing farmers with knowledge of identifying pigs' health state before they become sick or their condition becomes life-threatening. However, the conventional means of estimating pig mobility largely rely on manual observations by farmers, which is impractical in the context of contemporary centralized and extensive pig farming operations. In response to these challenges, multi-object tracking and pig behavior methods are adopted to monitor pig health and welfare closely. Regrettably, these existing methods frequently fall short of providing precise and quantified measurements of movement distance, thereby yielding a rudimentary metric for assessing pig health. This paper proposes a novel approach that integrates optical flow and a multi-object tracking algorithm to more accurately gauge pig movement based on both qualitative and quantitative analyses of the shortcomings of solely relying on tracking algorithms. The optical flow records accurate movement between two consecutive frames and the multi-object tracking algorithm offers individual tracks for each pig. By combining optical flow and the tracking algorithm, our approach can accurately estimate each pig's movement. Moreover, the incorporation of optical flow affords the capacity to discern partial movements, such as instances where only the pig's head is in motion while the remainder of its body remains stationary. The experimental results show that the proposed method has superiority over the method of solely using tracking results, i.e., bounding boxes. The reason is that the movement calculated based on bounding boxes is easily affected by the size fluctuation while the optical flow data can avoid these drawbacks and even provide more fine-grained motion information. The virtues inherent in the proposed method culminate in the provision of more accurate and comprehensive information, thus enhancing the efficacy of decision-making and management processes within the realm of pig farming.

Local refinement mechanism for improved plant leaf segmentation in cluttered backgrounds

Plant phenotyping is a critical field in agriculture, aiming to understand crop growth under specific conditions. Recent research uses images to describe plant characteristics by detecting visual information within organs such as leaves, flowers, stems, and fruits. However, processing data in real field conditions, with challenges such as image blurring and occlusion, requires improvement. This paper proposes a deep learning-based approach for leaf instance segmentation with a local refinement mechanism to enhance performance in cluttered backgrounds. The refinement mechanism employs Gaussian low-pass and High-boost filters to enhance target instances and can be applied to the training or testing dataset. An instance segmentation architecture generates segmented masks and detected areas, facilitating the derivation of phenotypic information, such as leaf count and size. Experimental results on a tomato leaf dataset demonstrate the system's accuracy in segmenting target leaves despite complex backgrounds. The investigation of the refinement mechanism with different kernel sizes reveals that larger kernel sizes benefit the system's ability to generate more leaf instances when using a High-boost filter, while prediction performance decays with larger Gaussian low-pass filter kernel sizes. This research addresses challenges in real greenhouse scenarios and enables automatic recognition of phenotypic data for smart agriculture. The proposed approach has the potential to enhance agricultural practices, ultimately leading to improved crop yields and productivity.

Proximity Matters: Interfacial Solvation Dictates Solid Electrolyte Interphase Composition

The composition of the solid electrolyte interphase (SEI) plays an important role in controlling Li-electrolyte reactions, but the underlying cause of SEI composition differences between electrolytes remains unclear. Many studies correlate SEI composition with the bulk solvation of Li ions in the electrolyte, but this correlation does not fully capture the interfacial phenomenon of SEI formation. Here, we provide a direct connection between SEI composition and Li-ion solvation by forming SEIs using polar substrates that modify interfacial solvation structures. We circumvent the deposition of Li metal by forming the SEI above Li+/Li redox potential. Using theory, we show that an increase in the probability density of anions near a polar substrate increases anion incorporation within the SEI, providing a direct correlation between interfacial solvation and SEI composition. Finally, we use this concept to form stable anion-rich SEIs, resulting in high performance lithium metal batteries.

Image findings of anti-neutrophil cytoplasmic antibody-associated vasculitis involving the skull base

AIM

To investigate computed tomography (CT) and magnetic resonance imaging (MRI) features of skull bases involving anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAV).

MATERIALS AND METHODS

A retrospective review was undertaken to identify an institutional historical cohort of 17 patients with confirmed AAV who underwent CT or MRI and had skull base involvement between 2002 and 2021. Two radiologists reviewed the extent and features of the lesions, bone changes, and other MRI findings.

RESULTS

A total of 17 patients (12 men; mean age ± standard deviation, 46.5 ± 17.1 years) were selected. AAV presented as infiltrative lesions with involvement at various sites. Most cases involved the paranasal sinuses (PNS; 88%, 15/17), nasopharynx (88%, 15/17), pterygopalatine fossa (82%, 14/17), and parapharyngeal space (82%, 14/17), frequently accompanied by mucosal irregularity of the PNS and nasopharynx (71%, 12/17). Central skull base and temporal bone involvement were seen in 53% (9/17) and 38% (6/16) of cases, respectively. On T1-weighted imaging (WI) and T2WI MRI, all lesions (15/15) showed predominant signal iso-intensity to grey matter.

CONCLUSIONS

Although radiological findings of AAV are non-specific and skull base involvement is less common, AAV may be considered if infiltrative lesions predominantly involving the PNS, nasopharynx, pterygopalatine fossa, and parapharyngeal space with combined bone changes of skull base are seen.

In Situ Prelithiation by Direct Integration of Lithium Mesh into Battery Cells

Silicon (Si)-based anodes are promising for next-generation lithium (Li)-ion batteries due to their high theoretical capacity (∼3600 mAh/g). However, they suffer quantities of capacity loss in the first cycle from initial solid electrolyte interphase (SEI) formation. Here, we present an in situ prelithiation method to directly integrate a Li metal mesh into the cell assembly. A series of Li meshes are designed as prelithiation reagents, which are applied to the Si anode in battery fabrication and spontaneously prelithiate Si with electrolyte addition. Various porosities of Li meshes tune prelithiation amounts to control the degree of prelithiation precisely. Besides, the patterned mesh design enhances the uniformity of prelithiation. With an optimized prelithiation amount, the in situ prelithiated Si-based full cell shows a constant >30% capacity improvement in 150 cycles. This work presents a facile prelithiation approach to improve battery performance.

Dissolution of the Solid Electrolyte Interphase and Its Effects on Lithium Metal Anode Cyclability

At >95% Coulombic efficiencies, most of the capacity loss for Li metal anodes (LMAs) is through the formation and growth of the solid electrolyte interphase (SEI). However, the mechanism through which this happens remains unclear. One property of the SEI that directly affects its formation and growth is the SEI's solubility in the electrolyte. Here, we systematically quantify and compare the solubility of SEIs derived from ether-based electrolytes optimized for LMAs using in-operando electrochemical quartz crystal microbalance (EQCM). A correlation among solubility, passivity, and cyclability established in this work reveals that SEI dissolution is a major contributor to the differences in passivity and electrochemical performance among battery electrolytes. Together with our EQCM, X-ray photoelectron spectroscopy (XPS), and nuclear magnetic resonance (NMR) spectroscopy results, we show that solubility depends on not only the SEI's composition but also the properties of the electrolyte. This provides a crucial piece of information that could help minimize capacity loss due to SEI formation and growth during battery cycling and aging.

Data-driven electrolyte design for lithium metal anodes

Improving Coulombic efficiency (CE) is key to the adoption of high energy density lithium metal batteries. Liquid electrolyte engineering has emerged as a promising strategy for improving the CE of lithium metal batteries, but its complexity renders the performance prediction and design of electrolytes challenging. Here, we develop machine learning (ML) models that assist and accelerate the design of high-performance electrolytes. Using the elemental composition of electrolytes as the features of our models, we apply linear regression, random forest, and bagging models to identify the critical features for predicting CE. Our models reveal that a reduction in the solvent oxygen content is critical for superior CE. We use the ML models to design electrolyte formulations with fluorine-free solvents that achieve a high CE of 99.70%. This work highlights the promise of data-driven approaches that can accelerate the design of high-performance electrolytes for lithium metal batteries.

Revealing the Multifunctions of Li3N in the Suspension Electrolyte for Lithium Metal Batteries

Inorganic-rich solid-electrolyte interphases (SEIs) on Li metal anodes improve the electrochemical performance of Li metal batteries (LMBs). Therefore, a fundamental understanding of the roles played by essential inorganic compounds in SEIs is critical to realizing and developing high-performance LMBs. Among the prevalent SEI inorganic compounds observed for Li metal anodes, Li₃N is often found in the SEIs of high-performance LMBs. Herein, we elucidate new features of Li₃N by utilizing a suspension electrolyte design that contributes to the improved electrochemical performance of the Li metal anode. Through empirical and computational studies, we show that Li₃N guides Li electrodeposition along its surface, creates a weakly solvating environment by decreasing Li⁺-solvent coordination, induces organic-poor SEI on the Li metal anode, and facilitates Li⁺ transport in the electrolyte. Importantly, recognizing specific roles of SEI inorganics for Li metal anodes can serve as one of the rational guidelines to design and optimize SEIs through electrolyte engineering for LMBs.

Elevated IFNA1 and suppressed IL12p40 associated with persistent hyperinflammation in COVID-19 pneumonia

Introduction

Despite of massive endeavors to characterize inflammation in COVID-19 patients, the core network of inflammatory mediators responsible for severe pneumonia stillremain remains elusive.

Methods

Here, we performed quantitative and kinetic analysis of 191 inflammatory factors in 955 plasma samples from 80 normal controls (sample n = 80) and 347 confirmed COVID-19 pneumonia patients (sample n = 875), including 8 deceased patients.

Results

Differential expression analysis showed that 76% of plasmaproteins (145 factors) were upregulated in severe COVID-19 patients comparedwith moderate patients, confirming overt inflammatory responses in severe COVID-19 pneumonia patients. Global correlation analysis of the plasma factorsrevealed two core inflammatory modules, core I and II, comprising mainly myeloid cell and lymphoid cell compartments, respectively, with enhanced impact in a severity-dependent manner. We observed elevated IFNA1 and suppressed IL12p40, presenting a robust inverse correlation in severe patients, which was strongly associated with persistent hyperinflammation in 8.3% of moderate pneumonia patients and 59.4% of severe patients.

Discussion

Aberrant persistence of pulmonary and systemic inflammation might be associated with long COVID-19 sequelae. Our comprehensive analysis of inflammatory mediators in plasmarevealed the complexity of pneumonic inflammation in COVID-19 patients anddefined critical modules responsible for severe pneumonic progression.

Classification of Alzheimer's disease stage using machine learning for left and right oxygenation difference signals in the prefrontal cortex: a patient-level, single-group, diagnostic interventional trial

OBJECTIVE

Recent evidence shows that indicators testing conventional olfactory function have a high degree of similarity to cognitive function tests and the potential to diagnose early-stage Alzheimer's disease (AD). In this study, the efficacy of functional near-infrared spectroscopy time-series data obtained through olfactory stimulation was investigated as an early diagnostic tool for mild cognitive impairment in AD using random forest, a machine learning algorithm.

PATIENTS AND METHODS

We conducted a patient-level, single-group, diagnostic interventional trial using near-infrared signals measured during olfactory stimulation in the prefrontal cortex of 178 older adults ranging from normal to participants with AD as markers to discriminate AD stages. We first divided the participants into normal older adults, AD mild cognitive impairment, and AD groups using dementia diagnostic criteria such as the Mini-Mental State Examination and Seoul Neuropsychological Screening Battery. We compared the left and right oxygenation difference by calculating the relative oxygenation difference from the change in relative oxygen concentration.

RESULTS

A total of 168 participants met the eligibility criteria: 70 (41.6%) had normal cognitive function; 42 (25%) mild cognitive impairment; 21 (12.5%) mild AD; and 35 (20.8%) moderate AD. A random forest machine learning model was developed to predict the AD stage, with an area under the receiver operating characteristic curve of 90.7% for mild cognitive impairment and AD, 90.99% for mild cognitive impairment, and 93.34% for AD only.

CONCLUSIONS

Based on the classification of the oxygenation difference index of the left and right prefrontal cortices during olfactory stimulation through machine learning, we found that it was possible to detect early-stage mild cognitive impairment in AD. Our results highlight the potential for early AD diagnosis using near-infrared signals from the prefrontal cortex obtained upon olfactory stimulation. Moreover, the results showed high similarity to the existing cognitive function tests and high accuracy in AD stage classification.

The UGT1A9*22 genotype identifies a high-risk group for irinotecan toxicity among gastric cancer patients

Several studies have shown associations between irinotecan toxicity and UGT1A genetic variations in colorectal and lung cancer, but only limited data are available for gastric cancer patients. We evaluated the frequencies of UGT1A polymorphisms and their relationship with clinicopathologic parameters in 382 Korean gastric cancer patients. Polymorphisms of UGT1A1*6, UGT1A1*27, UGT1A1*28, UGT1A1*60, UGT1A7*2, UGT1A7*3, and UGT1A9*22 were genotyped by direct sequencing. In 98 patients treated with irinotecan-containing regimens, toxicity and response were compared according to the genotype. The UGT1A1*6 and UGT1A9*22 genotypes showed a higher prevalence in Korean gastric cancer patients, while the prevalence of the UG1A1*28 polymorphism was lower than in normal Koreans, as has been found in other studies of Asian populations. The incidence of severe diarrhea after irinotecan-containing treatment was more common in patients with the UGT1A1*6, UGT1A7*3 and UGT1A9*22 polymorphisms than in controls. The presence of the UGT1A1*6 allele also showed a significant association with grade III–IV neutropenia. Upon haplotype and diplotype analyses, almost every patient bearing the UGT1A1*6 or UGT1A7*3 variant also had the UGT1A9*22 polymorphism, and all severe manifestations of UGT1A polymorphism-associated toxicity were related to the UGT1A9*22 polymorphism. By genotyping UGT1A9*22 polymorphisms, we could identify high-risk gastric cancer patients receiving irinotecan-containing chemotherapy, who would experience severe toxicity. When treating high-risk patients with the UGT1A9*22 polymorphism, clinicians should closely monitor them for signs of toxicity such as severe diarrhea or neutropenia.

Establishment of the large-scale longitudinal multi-omics dataset in COVID-19 patients: data profile and biospecimen

Understanding and monitoring virus-mediated infections has gained importance since the global outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Studies of high-throughput omics-based immune profiling of COVID-19 patients can help manage the current pandemic and future virus-mediated pandemics. Although COVID-19 is being studied since past 2 years, detailed mechanisms of the initial induction of dynamic immune responses or the molecular mechanisms that characterize disease progression remains unclear. This study involved comprehensively collected biospecimens and longitudinal multi-omics data of 300 COVID-19 patients and 120 healthy controls, including whole genome sequencing (WGS), single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA(+scTCR/BCR)-seq), bulk BCR and TCR sequencing (bulk TCR/BCR-seq), and cytokine profiling. Clinical data were also collected from hospitalized COVID-19 patients, and HLA typing, laboratory characteristics, and COVID-19 viral genome sequencing were performed during the initial diagnosis. The entire set of biospecimens and multi-omics data generated in this project can be accessed by researchers from the National Biobank of Korea with prior approval. This distribution of large-scale multi-omics data of COVID-19 patients can facilitate the understanding of biological crosstalk involved in COVID-19 infection and contribute to the development of potential methodologies for its diagnosis and treatment.

Establishment of the large-scale longitudinal multi-omics dataset in COVID-19 patients: data profile and biospecimen

Understanding and monitoring virus-mediated infections has gained importance since the global outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Studies of high-throughput omics-based immune profiling of COVID-19 patients can help manage the current pandemic and future virus-mediated pandemics. Although COVID-19 is being studied since past 2 years, detailed mechanisms of the initial induction of dynamic immune responses or the molecular mechanisms that characterize disease progression remains unclear. This study involved comprehensively collected biospecimens and longitudinal multi-omics data of 300 COVID-19 patients and 120 healthy controls, including whole genome sequencing (WGS), single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA(+scTCR/BCR)-seq), bulk BCR and TCR sequencing (bulk TCR/BCR-seq), and cytokine profiling. Clinical data were also collected from hospitalized COVID-19 patients, and HLA typing, laboratory characteristics, and COVID-19 viral genome sequencing were performed during the initial diagnosis. The entire set of biospecimens and multi-omics data generated in this project can be accessed by researchers from the National Biobank of Korea with prior approval. This distribution of largescale multi-omics data of COVID-19 patients can facilitate the understanding of biological crosstalk involved in COVID-19 infection and contribute to the development of potential methodologies for its diagnosis and treatment. [BMB Reports 2022; 55(9): 465-471].

Effect of doping and loading Parameters on photocatalytic degradation of brilliant green using Sn doped ZnO loaded CSAC

Sn doped ZnO loaded cotton stalk activated carbon (Sn-ZnO/CSAC) was prepared by chemical precipitation method, and the products were characterized. The XRD resultants confirm that the presence of hexagonal wurtzite phase of the bare ZnO. Furthermore, particular particle size gradually decreases (21.49 nm) due to doping and loading. UV-Vis absorption intensity of doped/loaded sample was red-shifted and then PL intensity is reduced. The photocatalytic performances of bare, Sn-doped ZnO and Sn-ZnO/CSAC was estimated by photodegradation of brilliant green (BG) under sunlight. The photodegradation of BG dye in 120 min over Sn-doped ZnO/CSAC is nearly 96.52%, which is considerably improved than bare ZnO (72.60%), respectively.

Suspension electrolyte with modified Li+ solvation environment for lithium metal batteries

Designing a stable solid-electrolyte interphase on a Li anode is imperative to developing reliable Li metal batteries. Herein, we report a suspension electrolyte design that modifies the Li⁺ solvation environment in liquid electrolytes and creates inorganic-rich solid-electrolyte interphases on Li. Li₂O nanoparticles suspended in liquid electrolytes were investigated as a proof of concept. Through theoretical and empirical analyses of Li₂O suspension electrolytes, the roles played by Li₂O in the liquid electrolyte and solid-electrolyte interphases of the Li anode are elucidated. Also, the suspension electrolyte design is applied in conventional and state-of-the-art high-performance electrolytes to demonstrate its applicability. Based on electrochemical analyses, improved Coulombic efficiency (up to ~99.7%), reduced Li nucleation overpotential, stabilized Li interphases and prolonged cycle life of anode-free cells (~70 cycles at 80% of initial capacity) were achieved with the suspension electrolytes. We expect this design principle and our findings to be expanded into developing electrolytes and solid-electrolyte interphases for Li metal batteries.

Single-Cell RNA Sequencing of Human Pluripotent Stem Cell-Derived Macrophages for Quality Control of The Cell Therapy Product

Macrophages exhibit high plasticity to achieve their roles in maintaining tissue homeostasis, innate immunity, tissue repair and regeneration. Therefore, macrophages are being evaluated for cell-based therapeutics against inflammatory disorders and cancer. To overcome the limitation related to expansion of primary macrophages and cell numbers, human pluripotent stem cell (hPSC)-derived macrophages are considered as an alternative source of primary macrophages for clinical application. However, the quality of hPSC-derived macrophages with respect to the biological homogeneity remains still unclear. We previously reported a technique to produce hPSC-derived macrophages referred to as iMACs, which is amenable for scale-up. In this study, we have evaluated the biological homogeneity of the iMACs using a transcriptome dataset of 6,230 iMACs obtained by single-cell RNA sequencing. The dataset provides a valuable genomic profile for understanding the molecular characteristics of hPSC-derived macrophage cells and provide a measurement of transcriptomic homogeneity. Our study highlights the usefulness of single cell RNA-seq data in quality control of the cell-based therapy products.

Steric Effect Tuned Ion Solvation Enabling Stable Cycling of High-Voltage Lithium Metal Battery

1,2-Dimethoxyethane (DME) is a common electrolyte solvent for lithium metal batteries. Various DME-based electrolyte designs have improved long-term cyclability of high-voltage full cells. However, insufficient Coulombic efficiency at the Li anode and poor high-voltage stability remain a challenge for DME electrolytes. Here, we report a molecular design principle that utilizes a steric hindrance effect to tune the solvation structures of Li⁺ ions. We hypothesized that by substituting the methoxy groups on DME with larger-sized ethoxy groups, the resulting 1,2-diethoxyethane (DEE) should have a weaker solvation ability and consequently more anion-rich inner solvation shells, both of which enhance interfacial stability at the cathode and anode. Experimental and computational evidence indicates such steric-effect-based design leads to an appreciable improvement in electrochemical stability of lithium bis(fluorosulfonyl)imide (LiFSI)/DEE electrolytes. Under stringent full-cell conditions of 4.8 mAh cm^-2 NMC811, 50 μm thin Li, and high cutoff voltage at 4.4 V, 4 M LiFSI/DEE enabled 182 cycles until 80% capacity retention while 4 M LiFSI/DME only achieved 94 cycles. This work points out a promising path toward the molecular design of non-fluorinated ether-based electrolyte solvents for practical high-voltage Li metal batteries.

Potentiometric Measurement to Probe Solvation Energy and Its Correlation to Lithium Battery Cyclability

The electrolyte plays a critical role in lithium-ion batteries, as it impacts almost every facet of a battery's performance. However, our understanding of the electrolyte, especially solvation of Li⁺, lags behind its significance. In this work, we introduce a potentiometric technique to probe the relative solvation energy of Li⁺ in battery electrolytes. By measuring open circuit potential in a cell with symmetric electrodes and asymmetric electrolytes, we quantitatively characterize the effects of concentration, anions, and solvents on solvation energy across varied electrolytes. Using the technique, we establish a correlation between cell potential (E_cell) and cyclability of high-performance electrolytes for lithium metal anodes, where we find that solvents with more negative cell potentials and positive solvation energies-those weakly binding to Li⁺-lead to improved cycling stability. Cryogenic electron microscopy reveals that weaker solvation leads to an anion-derived solid-electrolyte interphase that stabilizes cycling. Using the potentiometric measurement for characterizing electrolytes, we establish a correlation that can guide the engineering of effective electrolytes for the lithium metal anode.

Modelling Toxoplasma gondii infection in human cerebral organoids

Pluripotent stem cell-derived cerebral organoids have the potential to recapitulate the pathophysiology of in vivo human brain tissue, constituting a valuable resource for modelling brain disorders, including infectious diseases. Toxoplasma gondii, an intracellular protozoan parasite, infects most warm-blooded animals, including humans, causing toxoplasmosis. In immunodeficient patients and pregnant women, infection often results in severe central nervous system disease and fetal miscarriage. However, understanding the molecular pathophysiology of the disease has been challenging due to limited in vitro model systems. Here, we developed a new in vitro model system of T. gondii infection using human brain organoids. We observed that tachyzoites can infect human cerebral organoids and are transformed to bradyzoites and replicate in parasitophorous vacuoles to form cysts, indicating that the T. gondii asexual life cycle is efficiently simulated in the brain organoids. Transcriptomic analysis of T. gondii-infected organoids revealed the activation of the type I interferon immune response against infection. In addition, in brain organoids, T. gondii exhibited a changed transcriptome related to protozoan invasion and replication. This study shows cerebral organoids as physiologically relevant in vitro model systems useful for advancing the understanding of T. gondii infections and host interactions.

Measurement of the Positive Muon Anomalous Magnetic Moment to 0.46 ppm

We present the first results of the Fermilab National Accelerator Laboratory (FNAL) Muon g-2 Experiment for the positive muon magnetic anomaly a_{μ}≡(g_{μ}-2)/2. The anomaly is determined from the precision measurements of two angular frequencies. Intensity variation of high-energy positrons from muon decays directly encodes the difference frequency ω_{a} between the spin-precession and cyclotron frequencies for polarized muons in a magnetic storage ring. The storage ring magnetic field is measured using nuclear magnetic resonance probes calibrated in terms of the equivalent proton spin precession frequency ω[over ˜]_{p}^{'} in a spherical water sample at 34.7 °C. The ratio ω_{a}/ω[over ˜]_{p}^{'}, together with known fundamental constants, determines a_{μ}(FNAL)=116 592 040(54)×10^{-11} (0.46 ppm). The result is 3.3 standard deviations greater than the standard model prediction and is in excellent agreement with the previous Brookhaven National Laboratory (BNL) E821 measurement. After combination with previous measurements of both μ^{+} and μ^{-}, the new experimental average of a_{μ}(Exp)=116 592 061(41)×10^{-11} (0.35 ppm) increases the tension between experiment and theory to 4.2 standard deviations.

Exome Chip Analysis of 14,026 Koreans Reveals Known and Newly Discovered Genetic Loci Associated with Type 2 Diabetes Mellitus

BACKGROUND

Most loci associated with type 2 diabetes mellitus (T2DM) discovered to date are within noncoding regions of unknown functional significance. By contrast, exonic regions have advantages for biological interpretation.

METHODS

We analyzed the association of exome array data from 14,026 Koreans to identify susceptible exonic loci for T2DM. We used genotype information of 50,543 variants using the Illumina exome array platform.

RESULTS

In total, 7 loci were significant with a Bonferroni adjusted P=1.03×10-6. rs2233580 in paired box gene 4 (PAX4) showed the highest odds ratio of 1.48 (P=1.60×10-10). rs11960799 in membrane associated ring-CH-type finger 3 (MARCH3) and rs75680863 in transcobalamin 2 (TCN2) were newly identified loci. When we built a model to predict the incidence of diabetes with the 7 loci and clinical variables, area under the curve (AUC) of the model improved significantly (AUC=0.72, P<0.05), but marginally in its magnitude, compared with the model using clinical variables (AUC=0.71, P<0.05). When we divided the entire population into three groups-normal body mass index (BMI; <25 kg/m2), overweight (25≤ BMI <30 kg/m2), and obese (BMI ≥30 kg/m2) individuals-the predictive performance of the 7 loci was greatest in the group of obese individuals, where the net reclassification improvement was highly significant (0.51; P=8.00×10-5).

CONCLUSION

We found exonic loci having a susceptibility for T2DM. We found that such genetic information is advantageous for predicting T2DM in a subgroup of obese individuals.

Companilactobacillus pabuli sp. nov., a lactic acid bacterium isolated from animal feed

A Gram-positive, facultative anaerobic, catalase-negative, non-motile, non-spore-forming and rod-shaped lactic acid bacterium strain, denoted as NFFJ11^T and isolated from total mixed fermentation feed in the Republic of Korea, was characterized through polyphasic approaches, including sequence analyses of the 16S rRNA gene and housekeeping genes (rpoA and pheS), determination of average nucleotide identity and in silico DNA-DNA hybridization, fatty acid methyl ester analysis, and phenotypic characterization. Phylogenetic analyses based on 16S rRNA, rpoA and pheS gene sequences revealed that strain NFFJ11^T belonged to the genus Companilactobacillus. The 16S rRNA gene sequence of strain NFFJ11^T exhibited high similarity to Companilactobacillus formosensis S215^T (99.66 %), Companilactobacillus farciminis Rv4 na^T (99.53 %), Companilactobacillus crustorum LMG 23699^T (99.19 %), Companilactobacillus futsaii YM 0097^T (99.06 %), Companilactobacillus zhachilii HBUAS52074^T (98.86 %) and Companilactobacillus heilongiiangensis S4-3^T (98.66 %). However, average nucleotide identity and in silico DNA-DNA hybridization values for these type strains were in the range of 79.90-92.93 % and 23.80-49.30 %, respectively, which offer evidence that strain NFFJ11^T belongs to a novel species of the genus Companilactobacillus. The cell-wall peptidoglycan type was A4α (l-Lys-d-Asp) and the G+C content of the genomic DNA was 35.7 mol%. The main fatty acids of strain NFFJ11^T were C_18 : 1  ω9c (43.3 %), C_16 : 0 (20.1 %) and summed feature 7 (18.3 %; comprising any combination of C_19 : 1  ω7c, C_19 : 1  ω6c and C_19 : 0 cyclo ω10c). Through polyphasic taxonomic analysis, it was observed that strain NFFJ11^T represents a novel species belonging to the genus Companilactobacillus, for which the name Companilactobacillus pabuli sp. nov. is proposed. The type strain is NFFJ11^T (= KACC 21771^T= JCM 34088^T).

Underpotential lithium plating on graphite anodes caused by temperature heterogeneity

Rechargeability and operational safety of commercial lithium (Li)-ion batteries demand further improvement. Plating of metallic Li on graphite anodes is a critical reason for Li-ion battery capacity decay and short circuit. It is generally believed that Li plating is caused by the slow kinetics of graphite intercalation, but in this paper, we demonstrate that thermodynamics also serves a crucial role. We show that a nonuniform temperature distribution within the battery can make local plating of Li above 0 V vs. Li0/Li+ (room temperature) thermodynamically favorable. This phenomenon is caused by temperature-dependent shifts of the equilibrium potential of Li0/Li+ Supported by simulation results, we confirm the likelihood of this failure mechanism during commercial Li-ion battery operation, including both slow and fast charging conditions. This work furthers the understanding of nonuniform Li plating and will inspire future studies to prolong the cycling lifetime of Li-ion batteries.

Air-Filtering Masks for Respiratory Protection from PM2.5 and Pandemic Pathogens

Air-filtering masks, also known as respirators, protect wearers from inhaling fine particulate matter (PM2.5) in polluted air, as well as airborne pathogens during a pandemic, such as the ongoing COVID-19 pandemic. Fibrous medium, used as the filtration layer, is the most essential component of an air-filtering mask. This article presents an overview of the development of fibrous media for air filtration. We first synthesize the literature on several key factors that affect the filtration performance of fibrous media. We then concentrate on two major techniques for fabricating fibrous media, namely, meltblown and electrospinning. In addition, we underscore the importance of electret filters by reviewing various methods for imparting electrostatic charge on fibrous media. Finally, this article concludes with a perspective on the emerging research opportunities amid the COVID-19 crisis.

Gene Expression Profiling Identifies Akt as a Target for Radiosensitization in Gastric Cancer Cells

Background

Despite the important role of radiotherapy in cancer treatment, a subset of patients responds poorly to treatment majorly due to radioresistance. Particularly the role of radiotherapy has not been established in gastric cancer (GC). Herein, we aimed to identify a radiosensitivity gene signature and to discover relevant targets to enhance radiosensitivity in GC cells.

Methods

An oligonucleotide microarray (containing 22,740 probes) was performed in 12 GC cell lines prior to radiation. A clonogenic assay was performed to evaluate the survival fraction at 2 Gy (SF2) as a surrogate marker for radiosensitivity. Genes differentially expressed (fold change > 6, q-value < 0.025) were identified between radiosensitive and radioresistant cell lines, and quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) was performed for validation. Gene set and pathway analyses were performed using Ingenuity Pathway Analysis (IPA).

Results

Radiosensitive (SF2 < 0.4) and radioresistant cell lines (SF2 ≥ 0.6) exhibited a marked difference in gene expression. We identified 68 genes that are differentially expressed between radiosensitive and radioresistant cell lines. The identified genes showed interactions via AKT, HIF1A, TGFB1, and TP53, and their functions were associated with the genetic networks associated with cellular growth and proliferation, cellular movement, and cell cycle. The Akt signaling pathway exhibited the highest association with radiosensitivity. Combinatorial treatment with MK-2206, an allosteric Akt inhibitor, and radiotherapy significantly increased cell death compared with radiotherapy alone in two radioresistant cell lines (YCC-2 and YCC-16).

Conclusion

We identified a GC-specific radiosensitivity gene signature and suggest that the Akt signaling pathway could serve as a therapeutic target for GC radiosensitization.

Management of isolated recurrence after surgery for pancreatic adenocarcinoma

BACKGROUND

Recurrence of pancreatic cancer after primary pancreatectomy occurs in the vast majority of patients. The role of surgical treatment for recurrent pancreatic cancer is not well established.

METHODS

Patients who underwent primary pancreatectomy with curative intent from 2000 to 2014 at a single large-volume centre were evaluated retrospectively. CT or PET was used to select patients with an isolated recurrence. The clinicopathological features and survival outcomes were compared according to treatment modalities.

RESULTS

Of the 1610 patients with pancreatic cancer who underwent resection, 1346 (83·6 per cent) were diagnosed with recurrent pancreatic cancer. Recurrence was locoregional in 366 patients (27·2 per cent), distant multifocal in 251 (18·6 per cent), distant isolated in 188 (14·0 per cent), locoregional plus distant in 153 (11·4 per cent) and peritoneal seeding in 388 (28·8 per cent). Of the 1346 patients with recurrence, 197 (14·6 per cent) had isolated recurrence; of these, 48 (24·4 per cent of all isolated recurrences; 3·6 per cent of all recurrences) underwent resection. Median survival of the 197 patients after diagnosis of isolated recurrence was 14·7 months; it was longer in patients who underwent surgical resection than among those treated non-surgically (23·5 versus 12·0 months; P = 0·014). Multivariable analysis showed that chemotherapy and resection for recurrence were associated with better prognosis. Median survival after recurrence was longest in the 23 patients with isolated pulmonary recurrence (33·3 months). Survival after recurrence was better in patients who underwent resection of isolated recurrence in the remnant pancreas (median 28·0 versus 12·0 months, P = 0·010) and lung (median 36·5 versus 9·5 months; P = 0·010) than in those who did not undergo resection.

CONCLUSION

Surgical resection may be considered an option for treatment of patients with isolated recurrent pancreatic cancer.

Efficacy, Immunogenicity, and Safety of a 9-Valent Human Papillomavirus Vaccine: Subgroup Analysis of Participants From Asian Countries

Background

A 9-valent human papillomavirus-6/11/16/18/31/33/45/52/58 (9vHPV) vaccine extends coverage to 5 next most common oncogenic types (31/33/45/52/58) in cervical cancer versus quadrivalent HPV (qHPV) vaccine. We describe efficacy, immunogenicity, and safety in Asian participants (India, Hong Kong, South Korea, Japan, Taiwan, and Thailand) from 2 international studies: a randomized, double-blinded, qHPV vaccine-controlled efficacy study (young women aged 16–26 years; NCT00543543; Study 001); and an immunogenicity study (girls and boys aged 9–15 years; NCT00943722; Study 002).

Methods

Participants (N = 2519) were vaccinated at day 1 and months 2 and 6. Gynecological samples (Study 001 only) and serum were collected for HPV DNA and antibody assessments, respectively. Injection-site and systemic adverse events (AEs) were monitored. Data were analyzed by country and vaccination group.

Results

9vHPV vaccine prevented HPV-31/33/45/52/58–related persistent infection with 90.4%–100% efficacy across included countries. At month 7, ≥97.9% of participants seroconverted for each HPV type. Injection-site AEs occurred in 77.7%–83.1% and 81.9%–87.5% of qHPV and 9vHPV vaccine recipients in Study 001, respectively, and 62.4%–85.7% of girls/boys in Study 002; most were mild to moderate.

Conclusions

The 9vHPV vaccine is efficacious, immunogenic, and well tolerated in Asian participants. Data support 9vHPV vaccination programs in Asia.

Clinical Trials Registration

NCT00543543; NCT00943722.

Long-term survival of pig-to-rhesus macaque renal xenografts is dependent on CD4 T cell depletion

The shortage of available organs remains the greatest barrier to expanding access to transplant. Despite advances in genetic editing and immunosuppression, survival in experimental models of kidney xenotransplant has generally been limited to <100 days. We found that pretransplant selection of recipients with low titers of anti-pig antibodies significantly improved survival in a pig-to-rhesus macaque kidney transplant model (6 days vs median survival time 235 days). Immunosuppression included transient pan-T cell depletion and an anti-CD154-based maintenance regimen. Selective depletion of CD4⁺ T cells but not CD8⁺ T cells resulted in long-term survival (median survival time >400 days vs 6 days). These studies suggested that CD4⁺ T cells may have a more prominent role in xenograft rejection compared with CD8⁺ T cells. Although animals that received selective depletion of CD8⁺ T cells showed signs of early cellular rejection (marked CD4⁺ infiltrates), animals receiving selective CD4⁺ depletion exhibited normal biopsy results until late, when signs of chronic antibody rejection were present. In vitro study results suggested that rhesus CD4⁺ T cells required the presence of SLA class II to mount an effective proliferative response. The combination of low pretransplant anti-pig antibody and CD4 depletion resulted in consistent, long-term xenograft survival.

COEX-Seq: Convert a Variety of Measurements of Gene Expression in RNA-Seq

Next generation sequencing (NGS), a high-throughput DNA sequencing technology, is widely used for molecular biological studies. In NGS, RNA-sequencing (RNA-Seq), which is a short-read massively parallel sequencing, is a major quantitative transcriptome tool for different transcriptome studies. To utilize the RNA-Seq data, various quantification and analysis methods have been developed to solve specific research goals, including identification of differentially expressed genes and detection of novel transcripts. Because of the accumulation of RNA-Seq data in the public databases, there is a demand for integrative analysis. However, the available RNA-Seq data are stored in different formats such as read count, transcripts per million, and fragments per kilobase million. This hinders the integrative analysis of the RNA-Seq data. To solve this problem, we have developed a web-based application using Shiny, COEX-seq (Convert a Variety of Measurements of Gene Expression in RNA-Seq) that easily converts data in a variety of measurement formats of gene expression used in most bioinformatic tools for RNA-Seq. It provides a workflow that includes loading data set, selecting measurement formats of gene expression, and identifying gene names. COEX-seq is freely available for academic purposes and can be run on Windows, Mac OS, and Linux operating systems. Source code, sample data sets, and supplementary documentation are available as well.

Long-Term Ultrasound Follow-Up of Incidentally Detected Thyroglossal Duct Cysts in Adults

BACKGROUND AND PURPOSE

There has been no previous study that used ultrasonography for longitudinal changes of thyroglossal duct cysts, to our knowledge. We assessed the prevalence and interval changes in incidentally detected thyroglossal duct cysts in adults.

MATERIALS AND METHODS

From January 2010 to December 2016, we identified 796 ultrasonography radiologic reports from 513 subjects that contained the words "thyroglossal" or "TGDC" among 54,369 participants. Of 513 subjects, 172 (M/F = 103:69, mean age, 53 ± 11 years) who underwent ≥2 sonography studies were enrolled. Two reviewers determined ultrasonography features, including maximal diameter, location, internal echogenicity, wall thickness, and the presence of posterior enhancement, internal septa, and solid components.

RESULTS

The mean follow-up time of total 172 lesions was 2.01 ± 1.13 years. Thyroglossal duct cysts ranged from 2 to 32 mm (mean, 8.77 ± 3.83 mm) on the initial ultrasonography examination. On follow-up ultrasonography studies, 14 lesions (8.2%) increased by >2 mm, while most thyroglossal duct cysts (133 lesions, 77.3%) remained stable in size. During the follow-up period, 31 lesions (18.0%) showed interval changes in ultrasonography features. There was no significant relationship between the presence of ultrasonography feature changes and size changes (P = .12).

CONCLUSIONS

On ultrasonography, 0.9% of adults had incidental thyroglossal duct cysts. Most did not increase in size with time despite changes in various ultrasonography features. Therefore, we recommend performing an observation at long intervals of 2-3 years for asymptomatic thyroglossal duct cysts, and we suggest that fine-needle aspiration can be suspended unless suspicious findings of malignancy are detected.

Correction: The mutational landscape of ocular marginal zone lymphoma identifies frequent alterations in TNFAIP3 followed by mutations in TBL1XR1 and CREBBP

[This corrects the article DOI: 10.18632/oncotarget.14928.].

Anion gap and base deficit are predictors of mortality in acute pesticide poisoning

BACKGROUND:

Acute pesticide poisoning has long been a serious problem as a method of suicide worldwide. This poisoning is a highly fatal condition that requires a rapid and precise diagnosis for adequate treatment. However, various studies on mortality predictor factors have been insufficient for whole pesticide treatments. We hypothesized that the initial plasma anion gap (AG) and base deficit (BD) are reliable prognostic factors.

METHODS:

A retrospective study analyzed 561 patients with a diagnosis of acute pesticide poisoning between January 1, 2014 and June 30, 2017. The initial AG and BD values were divided into quartiles according to the number of patients. Survival at 30 days from admission was estimated using the Kaplan-Meier survival analysis. Receiver-operator characteristic (ROC) curves were drawn, and the areas under the curve for AG and BD for mortality were calculated.

RESULTS:

Fifty-eight (10.3%) of 561 patients died within 30 days. The highest AG quartile (>22 mEq/L) was associated with an increased risk of 30-day hospital mortality. Compared to patients with an AG less than 14.7 mEq/L, these patients had a 4.18-fold higher risk of 30-day hospital mortality and the highest BD quartile (>7.9 mEq/L) was associated with an increased risk of 30-day hospital mortality. Compared to patients with a BD less than 1.4 mEq/L, these patients had 2.23-fold higher risk of 30-day hospital mortality. The areas under the ROC for AG and BD curve were 0.699 and 0.744, respectively.

CONCLUSIONS:

Initial high AG and BD values could predict mortality and require precise intensive care.

The biological response to laser-aided direct metal-coated Titanium alloy (Ti6Al4V)

Objectives

Laser-engineered net shaping (LENS) of coated surfaces can overcome the limitations of conventional coating technologies. We compared the in vitro biological response with a titanium plasma spray (TPS)-coated titanium alloy (Ti6Al4V) surface with that of a Ti6Al4V surface coated with titanium using direct metal fabrication (DMF) with 3D printing technologies.

Methods

The in vitro ability of human osteoblasts to adhere to TPS-coated Ti6Al4V was compared with DMF-coating. Scanning electron microscopy (SEM) was used to assess the structure and morphology of the surfaces. Biological and morphological responses to human osteoblast cell lines were then examined by measuring cell proliferation, alkaline phosphatase activity, actin filaments, and RUNX2 gene expression.

Results

Morphological assessment of the cells after six hours of incubation using SEM showed that the TPS- and DMF-coated surfaces were largely covered with lamellipodia from the osteoblasts. Cell adhesion appeared similar in both groups. The differences in the rates of cell proliferation and alkaline phosphatase activities were not statistically significant.

Conclusions

The DMF coating applied using metal 3D printing is similar to the TPS coating, which is the most common coating process used for bone ingrowth. The DMF method provided an acceptable surface structure and a viable biological surface. Moreover, this method is automatable and less complex than plasma spraying.

Cite this article: T. Shin, D. Lim, Y. S. Kim, S. C. Kim, W. L. Jo, Y. W. Lim. The biological response to laser-aided direct metal-coated Titanium alloy (Ti6Al4V). Bone Joint Res 2018;7:357–361. DOI: 10.1302/2046-3758.75.BJR-2017-0222.R1.

International Bullous Diseases Group: consensus on diagnostic criteria for epidermolysis bullosa acquisita

BACKGROUND

Epidermolysis bullosa acquisita (EBA) is a complex autoimmune bullous disease disease with variable clinical presentations and multiple possible diagnostic tests, making an international consensus on the diagnosis of EBA essential.

OBJECTIVES

To obtain an international consensus on the clinical and diagnostic criteria for EBA.

METHODS

The International Bullous Diseases Group (IBDG) met three times to discuss the clinical and diagnostic criteria for EBA. For the final voting exercise, 22 experts from 14 different countries voted on 50 different items. When > 30% disagreed with a proposal, a discussion was held and re-voting carried out.

RESULTS

In total, 48 of 50 proposals achieved consensus after discussion. This included nine diagnostic criteria, which are summarized in a flow chart. The IBDG was unable to determine one procedure that would be applicable worldwide. A limitation of the study is that differential diagnosis of bullous systemic lupus erythematosus has not been addressed.

CONCLUSIONS

This first international consensus conference established generally agreed-upon clinical and laboratory criteria defining the clinical classification of and diagnostic testing for EBA. Holding these voting exercises in person with the possibility of discussion prior to voting has advantages in reaching consensus over Delphi exercises with remote voting.

Preparation of “Open/closed” pores of PLGA-microsphere for controlled release of protein drug

Poly(D,L-lactic-co-glycolic acid)  has been extensively used as a controlled release carrier for drug delivery due to its good biocompatibility, biodegradability, and mechanical strength. In this study, porous PLGA microspheres were fabricated by an emulsion-solvent evaporation technique using poly ethylene glycol (PEG) as an extractable porogen and loaded with  protein (lysozyme) by suspending them in protein solution. For controlled release of protein, porous microspheres containing lysozyme were treated with water-miscible solvents in aqueous phase for production of pore-closed microspheres. The surface morphology of microspheres were investigated using scanning electron microscopy (SEM) for confirmation of its porous microstructure structure. Protein property after release was observed by enzymatic activity assay. The pore-closing process resulted in nonporous microspheres which exhibited sustained release patterns over an extended period.

Prevalence and detection of low-allele-fraction variants in clinical cancer samples

Accurate detection of genomic alterations using high-throughput sequencing is an essential component of precision cancer medicine. We characterize the variant allele fractions (VAFs) of somatic single nucleotide variants and indels across 5095 clinical samples profiled using a custom panel, CancerSCAN. Our results demonstrate that a significant fraction of clinically actionable variants have low VAFs, often due to low tumor purity and treatment-induced mutations. The percentages of mutations under 5% VAF across hotspots in EGFR, KRAS, PIK3CA, and BRAF are 16%, 11%, 12%, and 10%, respectively, with 24% for EGFR T790M and 17% for PIK3CA E545. For clinical relevance, we describe two patients for whom targeted therapy achieved remission despite low VAF mutations. We also characterize the read depths necessary to achieve sensitivity and specificity comparable to current laboratory assays. These results show that capturing low VAF mutations at hotspots by sufficient sequencing coverage and carefully tuned algorithms is imperative for a clinical assay.

High-throughput sequencing is used to identify somatic variants in cancer patients. Here, the authors perform panel-based profiling of 5095 clinical samples and demonstrate that many clinically-actionable variants have low variant allele fractions, requiring assays with high detection sensitivity.

A Robust Deep-Learning-Based Detector for Real-Time Tomato Plant Diseases and Pests Recognition

Plant Diseases and Pests are a major challenge in the agriculture sector. An accurate and a faster detection of diseases and pests in plants could help to develop an early treatment technique while substantially reducing economic losses. Recent developments in Deep Neural Networks have allowed researchers to drastically improve the accuracy of object detection and recognition systems. In this paper, we present a deep-learning-based approach to detect diseases and pests in tomato plants using images captured in-place by camera devices with various resolutions. Our goal is to find the more suitable deep-learning architecture for our task. Therefore, we consider three main families of detectors: Faster Region-based Convolutional Neural Network (Faster R-CNN), Region-based Fully Convolutional Network (R-FCN), and Single Shot Multibox Detector (SSD), which for the purpose of this work are called "deep learning meta-architectures". We combine each of these meta-architectures with "deep feature extractors" such as VGG net and Residual Network (ResNet). We demonstrate the performance of deep meta-architectures and feature extractors, and additionally propose a method for local and global class annotation and data augmentation to increase the accuracy and reduce the number of false positives during training. We train and test our systems end-to-end on our large Tomato Diseases and Pests Dataset, which contains challenging images with diseases and pests, including several inter- and extra-class variations, such as infection status and location in the plant. Experimental results show that our proposed system can effectively recognize nine different types of diseases and pests, with the ability to deal with complex scenarios from a plant's surrounding area.

Belatacept-Resistant Rejection Is Associated With CD28+ Memory CD8 T Cells

Recently, newer therapies have been designed to more specifically target rejection in an effort to improve efficacy and limit unwanted toxicity. Belatacept, a CD28-CD80/86 specific reagent, is associated with superior patient survival and graft function compared with traditional therapy, but its adoption as a mainstay immunosuppressive therapy has been tempered by increased rejection rates. It is essential that the underlying mechanisms associated with this rejection be elucidated before belatacept is more widely used. To that end, we designed a study in a nonhuman primate kidney transplant model where animals were treated with either a belatacept- or a tacrolimus-based immunosuppressive regimen. Interestingly, we found that elevated pretransplant frequencies of CD28⁺ CD8⁺ T_EMRA cells are associated with rejection on belatacept but not tacrolimus treatment. Further analysis showed that the CD28⁺ CD8⁺ T_EMRA cells rapidly lose CD28 expression after transplant in those animals that go on to reject with the allograft infiltrate being predominantly CD28^- . These data suggest that CD28⁺ memory T cells may be resistant to belatacept, capable of further differentiation including loss of CD28 expression while maintaining effector function. The unique signaling requirements of CD28⁺ memory T cells provide opportunities for the development of targeted therapies, which may synergize with belatacept to prevent costimulation-independent rejection.

Patterns and predictors of persistent opioid use following hip or knee arthroplasty

OBJECTIVE

The relationship between arthroplasty and long-term opioid use in patients with knee or hip osteoarthritis is not well studied. We examined the prevalence, patterns and predictors of persistent opioid use after hip or knee arthroplasty.

METHOD

Using claims data (2004-2013) from a US commercial health plan, we identified adults who underwent hip or knee arthroplasty and filled ≥1 opioid prescription within 30 days after the surgery. We defined persistent opioid users as patients who filled ≥1 opioid prescription every month during the 1-year postoperative period based on group-based trajectory models. Multivariable logistic regression was used to determine preoperative predictors of persistent opioid use after surgery.

RESULTS

We identified 57,545 patients who underwent hip or knee arthroplasty. The mean ± SD age was 61.5 ± 7.8 years and 87.1% had any opioid use preoperatively. Overall, 7.6% persistently used opioids after the surgery. Among patients who used opioids in 80% of the time for ≥4 months preoperatively (n = 3023), 72.1% became persistent users. In multivariable analysis, knee arthroplasty vs hip, a longer hospitalization stay, discharge to a rehabilitation facility, preoperative opioid use (e.g., a longer duration and greater dosage and frequency), a higher comorbidity score, back pain, rheumatoid arthritis, fibromyalgia, migraine and smoking, and benzodiazepine use at baseline were strong predictors for persistent opioid use (C-statistic = 0.917).

CONCLUSION

Over 7% of patients persistently used opioids in the year after hip or knee arthroplasty. Given the adverse health effects of persistent opioid use, strategies need to be developed to prevent persistent opioid use after this common surgery.

Efficient extraction of oil from droplet microfluidic emulsions

Droplet microfluidic techniques can perform large numbers of single molecule and cell reactions but often require controlled, periodic flow to merge, split, and sort droplets. Here, we describe a simple method to convert aperiodic flows into periodic ones. Using an oil extraction module, we efficiently remove oil from emulsions to readjust the droplet volume fraction, velocity, and packing, producing periodic flows. The extractor acts as a universal adaptor to connect microfluidic modules that do not operate under identical flow conditions, such as droplet generators, incubators, and merger devices.