bluuebunny/crossref_metadata_2025 huggingface dataset:
Category encoding method to select feature genes for the classification of bulk and single‐cell RNA‐seq data
Authors: Zhou Yan , Zhang Li , Xu Jinfeng , Zhang Jun , Yan Xiaodong
Published: May 2021

Bulk and single‐cell RNA‐seq (scRNA‐seq) data are being used as alternatives to traditional technology in biology and medicine research. These data are used, for example, for the detection of differentially expressed (DE) genes. Several statistical methods have been developed for the classification of bulk and single‐cell RNA‐seq data. These feature genes are vitally important for the classification of bulk and single‐cell RNA‐seq data. The majority of genes are not DE and they are thus irrelevant for class distinction. To improve the classification performance and save the computation time, removal of irrelevant genes is necessary. Removal will aid the detection of the important feature genes. Widely used schemes in the literature, such as the BSS/WSS (BW) method, assume that data are normally distributed and may not be suitable for bulk and single‐cell RNA‐seq data. In this article, a category encoding (CAEN) method is proposed to select feature genes for bulk and single‐cell RNA‐seq data classification. This novel method encodes categories by employing the rank of sequence samples for each gene in each class. Correlation coefficients are considered for gene and class with the rank of sample and a new rank of category. The highest gene correlation coefficients are considered feature genes, which are the most effective for classifying bulk and single‐cell RNA‐seq dataset. The sure screening method was also established for rank consistency properties of the proposed CAEN method. Simulation studies show that the classifier using the proposed CAEN method performs better than, or at least as well as, the existing methods in most settings. Existing real datasets were analyzed, with the results demonstrating superior performance of the proposed method over current competitors. The application has been coded into an R package named “CAEN” to facilitate wide use.
Progress in the Synthesis of Fused 1,2,3‐Triazoles
Authors: Kumar Hariom , Dhameja Manoj , Rizvi Marziya , Gupta Preeti
Published: May 2021

Fused heterocycles display prodigious prominence in diverse field ranging from medicinal chemistry to material science and chemical biology to catalysis. Owing to biological importance, fused 1,2,3‐triazoles have gained much attention and hence, enormous efforts on its synthesis is given by the chemists. Diverse functionalized fused polycyclic 1,2,3‐triazole heterocycles have been designed using Huisgen's thermal intramolecular cycloaddition, copper catalyzed cycloaddition, bimetallic catalytic, greener and other miscellaneous approaches. Novel methodologies that use modified substrates such as ketones, enals, β‐keto esters, olefins, enones, C−H acids etc. in place of alkynes have been developed. Herein, synthetic methodologies to construct fused 1,2,3‐triazoles are briefly discussed.
Design of Benzothiazolone‐Based Carboxylic Acid Aldose Reductase Inhibitors
Authors: Lei Yanqi , Zhang Xin , Zhang Xiaonan , Xu Long , Liu Wenchao , Chen Huan , Zhu Changjin , Ma Bing
Published: May 2021

Aldose Reductase (AR, ALR2) is a member of the aldo‐keto reductase superfamily that plays a critical role in diabetic complications. In this work, benzothiazolone was employed as the scaffold, and the C6 position was modified with aryl and heterocyclic groups to design potent inhibitor against ALR2. 2‐(6‐(4‐hydroxystyryl)‐2‐oxobenzothiazol‐3(2H)‐yl)acetic acid (6 c) was identified the most active with IC50value of 18.8 nM. 2‐(6‐(3,4‐dihydroxyphenyl)‐2‐oxobenzothiazol‐3(2H)‐yl)acetic acid (4 c) and 2‐(6‐(4‐hydroxy‐3‐methoxystyryl)‐2‐oxobenzothiazol‐3(2H)‐yl)acetic acid (6 b) were also strong in the ALR2 inhibition, and even exhibited good antioxidant activity by tests of DPPH radical scavenging and lipid peroxidation suppression.6 bhaving C6‐hydroxymethoxystyryl sidechain is suggested as a promising candidate for further structure optimizations.
A Polymer/Graphene Composite Cathode with Active Carbonyls and Secondary Amine Moieties for High‐Performance Aqueous Zn‐Organic Batteries Involving Dual‐Ion Mechanism
Authors: Zhang Hong , Xu Dongxiao , Wang Lipeng , Ye Zhuolin , Chen Bin , Pei Liyuan , Wang Zengyao , Cao Ziyi , Shen Jianfeng , Ye Mingxin
Published: May 2021

Aqueous zinc‐ion batteries (AZIBs) are regarded as one of the most promising alternative technology to lithium‐ion batteries on account of their low flammability and cost‐benefits. Among various cathode materials in AZIBs, environment‐friendly and sustainable organic electrode materials stand out owing to their structural diversity and tunability. However, their limited rate capability and cycle stability remain the obstacles to their further application in AZIBs. Herein, a mixed cathode design strategy including polymerization and carbon materials hybridization is adopted to assemble high‐rate and durable AZIBs. Specifically, a polymer/graphene composite cathode with active carbonyls and secondary amine moieties is prepared to construct high‐performance aqueous Zn‐organic batteries. Furthermore, a hybrid energy storage mechanism involving dual‐ion mechanism is confirmed by various ex situ characterization techniques, providing promising battery chemistry. Thus, this work opens up a new path to high performance AZIBs through a rational cathode design.
Nano‐3D‐Printed Photochromic Micro‐Objects
Authors: Ulrich Sebastian , Wang Xiaopu , Rottmar Markus , Rossi René Michel , Nelson Bradley J. , Bruns Nico , Müller Ralph , Maniura‐Weber Katharina , Qin Xiao‐Hua , Boesel Luciano Fernandes
Published: May 2021

Molecular photoswitches that can reversibly change color upon irradiation are promising materials for applications in molecular actuation and photoresponsive materials. However, the fabrication of photochromic devices is limited to conventional approaches such as mold casting and spin‐coating, which cannot fabricate complex structures. Reported here is the first photoresist for direct laser writing of photochromic 3D micro‐objects via two‐photon polymerization. The integration of photochromism into thiol–ene photo‐clickable resins enables rapid two‐photon laser processing of highly complex microstructures and facile postmodification using a series of donor–acceptor Stenhouse adduct (DASA) photoswitches with different excitation wavelengths. The versatility of thiol–ene photo‐click reactions allows fine‐tuning of the network structure and physical properties as well as the type and concentration of DASA. When exposed to visible light, these microstructures exhibit excellent photoresponsiveness and undergo reversible color‐changing via photoisomerization. It is demonstrated that the fluorescence variations of DASAs can be used as a reporter of photoswitching and thermal recovery, allowing the reading of DASA‐containing sub‐micrometric structures in 3D. This work delivers a new approach for custom microfabrication of 3D photochromic objects with molecularly engineered color and responsiveness.
Low Temperature Deposition of Highly Cyclable Porous Prussian Blue Cathode for Lithium‐Ion Microbattery
Authors: Patnaik Sai Gourang , Pech David
Published: May 2021

Small dimension Li‐ion microbatteries are of great interest for embedded microsystems and on‐chip electronics. However, the deposition of fully crystallized cathode thin film generally requires high temperature synthesis or annealing, incompatible with microfabrication processes of integrated Si devices. In this work, a low temperature deposition process of a porous Prussian blue‐based cathode on Si wafers is reported. The active material is electrodeposited under aqueous conditions using a pulsed deposition protocol on a porous dendritic metallic current collector that ensures good electronic conductivity of the composite. The high voltage cathodes exhibit a huge areal capacity of ≈650 μAh cm−2 and are able to withstand more than 2000 cycles at 0.25 mA cm−2 rate. The application of these electrode composites with porous Sn based alloying anodes is also demonstrated for the first time in full cell configuration, with high areal energy of 3.1 J cm−2 and more than 95% reversible capacity. This outstanding performance can be attributed to uniform deposition of Prussian blue materials on conductive matrix, which maintains electronic conductivity while simultaneously providing mechanical integrity to the electrode. This finding opens new horizons in the monolithic integration of energy storage components compatible with the semiconductor industry for self‐powered microsystems.
Nanocage‐Based Capture‐Detection System for the Clinical Diagnosis of Autoimmune Disease
Authors: Zhang Yanan , Li Yingni , Zhang Jianlin , Chen Xuehui , Zhang Ruofei , Sun Guoming , Jiang Bing , Fan Kelong , Li Zhanguo , Yan Xiyun
Published: May 2021

The detection of autoantibodies is critical for diagnosis of autoimmune diseases. However, the sensitivity is often limited by the properties of the antigens and the detection systems such as enzyme‐linked immunosorbent assay (ELISA). Here, employing the multidisplay ability of ferritin, a highly sensitive nanocage‐based capture‐detection system is designed, of which the sensitivity is 100–1000‐fold higher than that of conventional ELISA methods. The capture nanocages are constructed by displaying the primary Sjögren's syndrome (pSS)‐related antigenic peptides on ferritin nanocage, which present epitopes effectively and high affinity, leading to tenfold higher capture capability for autoantibodies. Human IgG Fc‐binding peptides are also engineered on ferritin nanocage, which enable high binding affinity and efficient horseradish peroxidase (HRP)‐labeling. Compared with commercial HRP‐conjugated anti‐human IgG antibody, the nanocage‐based detecting probe exhibited more than tenfold increased sensitivity. Autoantibodies are then examined in 91 sera from patients with pSS, 51 from rheumatoid arthritis, 54 from systemic lupus erythematosus, and 55 from healthy individuals by using the nanocage‐based ELISA. The results indicate that the nanocage‐based capture‐detection system is an effective detection platform and provide a novel and more sensitive method for the diagnosis of autoimmune diseases.
Chemokine signaling is required for homeostatic and injury-induced neurogenesis in the olfactory epithelium
Authors: Senf Katja , Karius Julia , Stumm Ralf , Neuhaus Eva M.
Published: May 2021

The olfactory epithelium (OE) possesses unique lifelong neuroregenerative capacities and undergoes constitutive neurogenesis throughout mammalian lifespan. Two populations of stem cells, frequently dividing globose basal cells (GBCs) and quiescent horizontal basal cells (HBCs), readily replace olfactory neurons throughout lifetime. Although lineage commitment and neuronal differentiation of stem cells has already been described in terms of transcription factor expression, little is known about external factors balancing between differentiation and self-renewal. We show here that expression of the CXC-motif chemokine receptor 4 (CXCR4) distinguishes both types of stem cells. Extensive colocalization analysis revealed exclusive expression of CXCR4 in proliferating GBCs and their neuronal progenies. Moreover, only neuronal lineage cells were derived from CXCR4-CreER-tdTomato reporter mice in the OE. Furthermore, Cre-tdTomato mice specific for HBCs (Nestin+ and Cytokeratin14+) did not reduce CXCR4 expression when bred to mice bearing floxed CXCR4 alleles, and did not show labeling of the neuronal cells. CXCR4 and its ligand CXCL12 were markedly upregulated upon induction of GBC proliferation during injury-induced regeneration. in vivo overexpression of CXCL12 did downregulate CXCR4 levels, which results in reduced GBC maintenance and neuronal differentiation. We proved that these effects were caused by CXCR4 downregulation rather than over-activation by showing that the phenotypes of CXCL12-overexpressing mice were highly similar to the phenotypes of CXCR4 knockout mice. Our results demonstrate functional CXCR4 signaling in GBCs regulates cell cycle exit and neural differentiation. We propose that CXCR4/CXCL12 signaling is an essential regulator of olfactory neurogenesis and provide new insights into the dynamics of neurogenesis in the OE.
Advanced Chemical Methods for Stereoselective Sialylation and Their Applications in Sialoglycan Syntheses
Authors: Vibhute Amol M. , Komura Naoko , Tanaka Hide‐Nori , Imamura Akihiro , Ando Hiromune
Published: May 2021

Sialic acid is an important component of cell surface glycans, which are responsible for many vital body functions and should therefore be thoroughly studied to understand their biological roles and association with disorders. The difficulty of isolating large quantities of homogenous‐state sialoglycans from natural sources has inspired the development of the corresponding chemical synthesis methods affording acceptable purities, yields, and amounts. However, the related syntheses are challenging because of the difficulties in α‐glycosylation of sialic acid, which arises from its certain structural features such as the absence of a stereodirecting group at the C3 position and presence of carboxyl group at the anomeric position. Moreover, the structural complexities of sialoglycans with diverse numbers and locations of sialic acid on the glycan chains pose additional barriers. Thus, efficient α‐stereoselective routes to sialosides remain highly sought after, although various types of sialyl donors/acceptors have been developed for the straightforward synthesis of α‐sialosides. Herein, we review the latest progress in the α‐stereoselective synthesis of sialosides and their applications in the preparation of gangliosides and other sialoglycans.
Evolution of Earth‐Abundant 3 d‐Metallaelectro‐Catalyzed C−H Activation: From Chelation‐Assistance to C−H Functionalization without Directing Groups
Authors: Samanta Ramesh C. , Ackermann Lutz
Published: May 2021

Catalyzed C−H functionalizations have emerged as a transformative platform for molecular syntheses. Despite of indisputable advances, oxidative C−H activations have been largely restricted to precious transition metals and stoichiometric amounts of chemical oxidants. In contrast, we herein discuss the potential of earth‐abundant, environmentally‐benign 3d transition metals for C−H activation, which has recently gained major momentum. Thus, a strategy for full resource economy has been established in our group, with green electricity as a renewable redox agent, giving valuable hydrogen as the sole byproduct under redox mediator‐free conditions. In this account, we detail our accomplishments in 3d metallaelectrocatalysis towards green syntheses until March 2021.
A Distance Learning Instructional Framework for Early Literacy
Authors: Fisher Douglas , Frey Nancy
Published: May 2021

Literacy instruction does not just happen during the language arts block, as students can learn more about reading and writing during science, social studies, and mathematics. This department features examples of how teachers can teach literacy across various content areas.
Derive Lovelock gravity from string theory in cosmological background
Authors: Wang Peng , Wu Houwen , Yang Haitang , Ying Shuxuan
Published: May 2021

Abstract

It was proved more than three decades ago, that the first order α′ correction of string effective theory could be written as the Gauss-Bonnet term, which is the quadratic term of Lovelock gravity. In cosmological background, with an appropriate field redefinition, we reorganize the infinite α′ corrections of string effective action into a finite term expression for any specific dimension. This finite term expression matches Lovelock gravity exactly and thus fix the couplings of Lovelock gravity by the coefficients of string effective action. This result thus provides a strong support to string theory.
Interactions of ants with native and invasive lady beetles and the role of chemical cues in intraguild interference
Authors: Bucher Roman , Japke Laura M. , Ünlü Ayse Gül , Menzel Florian
Published: May 2021

The predator-predator naïveté hypothesis suggests that non-native predators benefit from being unknown to native predators, resulting in reduced intraguild interference with native predators. This novelty advantage should depend on the ability of native predators to recognize cues of non-native predators. Here, we compared ant aggression and lady beetle reaction in four native and the invasive lady beetle species Harmonia axyridis. In addition, we tested whether lady beetle cuticular hydrocarbons (CHCs) are involved in species recognition, which might explain naïveté if the invasive species has a specific CHC profile. To this end, we conducted behavioral assays confronting two native ant species with both living lady beetles and lady beetle elytra bearing or lacking CHCs of different lady beetle species. Finally, we characterized CHC profiles of the lady beetles using GC–MS. In general, the aggression of Lasius niger was more frequent than that of Myrmica rubra and L. niger aggression was more frequent towards most native lady beetle species compared to H. axyridis. The removal of CHCs from lady beetle elytra reduced aggression of both ant species. If CHCs of respective lady beetle species were added on cue-free elytra, natural strength of L. niger aggression could be restored. CHC analyses revealed a distinct cue composition for each lady beetle species. Our experiments demonstrate that the presence of chemical cues on the surface of lady beetles contribute to the strength of ant aggression against lady beetles. Reduced aggression of L. niger towards H. axyridis and reduced avoidance behavior in H. axyridis compared to the equally voracious C. septempunctata might improve the invasive lady beetle’s access to ant-tended aphids.
Do outcomes of psychiatric hospital treatment differ for migrants and non-migrants?
Authors: Anderson Kimberley , Giacco Domenico , Bird Victoria , Bauer Michael , Pfennig Andrea , Lasalvia Antonio , Ruggeri Mirella , Lorant Vincent , Nicaise Pablo , Moskalewicz Jacek , Welbel Marta , Priebe Stefan
Published: May 2021

Purpose

Providing effective treatment for immigrants is an increasing challenge for mental health services across Europe. Yet, little is known as to whether current practice is associated with different outcomes in migrant and non-migrant patients. We compared outcomes of inpatient psychiatric treatment for migrants and non-migrants in a sample from five European countries.

Methods

Patients with psychotic disorders, affective disorders or anxiety/somatisation disorders admitted to routine psychiatric inpatient treatment were assessed in hospitals in Belgium, Germany, Italy, Poland and the United Kingdom. Treatment outcomes were satisfaction with care during hospitalisation, length of stay, readmission to hospital (any and, specifically, involuntary re-hospitalisation), as well as untoward incidents in a 1-year follow-up period. Outcomes were compared between patients born inside (non-migrants) and outside (migrants) the country of treatment, through mixed regression models.

Results

Across all sites, 985 migrant patients and 6298 non-migrant patients were included. After accounting for the influence of confounding patient characteristics, migrants reported significantly lower treatment satisfaction, but there were no significant differences for length of stay and re-hospitalisations, in general and involuntary ones. Migrants had a lower rate of suicide attempts, but there was no significant difference in other types of untoward incidents in the year following the index admission.

Conclusion

The study suggests that migrants are less satisfied with their hospital treatment, there is no evidence that routine inpatient care as currently provided results overall in poorer objective outcomes for migrants than in non-migrant populations.
Secure Communication Channel Establishment: TLS 1.3 (over TCP Fast Open) versus QUIC
Authors: Chen Shan , Jero Samuel , Jagielski Matthew , Boldyreva Alexandra , Nita-Rotaru Cristina
Published: May 2021

Secure channel establishment protocols such as Transport Layer Security (TLS) are some of the most important cryptographic protocols, enabling the encryption of Internet traffic. Reducing latency (the number of interactions between parties before encrypted data can be transmitted) in such protocols has become an important design goal to improve user experience. The most important protocols addressing this goal are TLS 1.3, the latest TLS version standardized in 2018 to replace the widely deployed TLS 1.2, and Quick UDP Internet Connections (QUIC), a secure transport protocol from Google that is implemented in the Chrome browser. There have been a number of formal security analyses for TLS 1.3 and QUIC, but their security, when layered with their underlying transport protocols, cannot be easily compared. Our work is the first to thoroughly compare the security and availability properties of these protocols. Toward this goal, we develop novel security models that permit “layered” security analysis. In addition to the standard goals of server authentication and data confidentiality and integrity, we consider the goals of IP spoofing prevention, key exchange packet integrity, secure channel header integrity, and reset authentication, which capture a range of practical threats not usually taken into account by existing security models that focus mainly on the cryptographic cores of the protocols. Equipped with our new models we provide a detailed comparison of three low-latency layered protocols: TLS 1.3 over TCP Fast Open (TFO), QUIC over UDP, and QUIC[TLS] (a new design for QUIC that uses TLS 1.3 key exchange) over UDP. In particular, we show that TFO’s cookie mechanism does provably achieve the security goal of IP spoofing prevention. Additionally, we find several new availability attacks that manipulate the early key exchange packets without being detected by the communicating parties. By including packet-level attacks in our analysis, our results shed light on how the reliability, flow control, and congestion control of the above layered protocols compare, in adversarial settings. We hope that our models will help protocol designers in their future protocol analyses and that our results will help practitioners better understand the advantages and limitations of secure channel establishment protocols.
Surface phenomena of gradient materials
Authors: Krawietz Arnold
Published: May 2021

The behavior of third gradient materials is analyzed. They possess stress tensor fields of second, third and fourth order. Starting from the principle of virtual power, we derive the admissible boundary conditions. Those on free surfaces can only be obtained by the application of the divergence theorem of surfaces. On the other hand, such an application to fictitious internal cuts makes no sense although it is usually practiced. We prove that some of the boundary conditions on a free surface may be interpreted as the equilibrium conditions of a shell. So a crust shell exists on such a surface and a beam exists where patches of the surface meet. On the other hand, no such shells or beams can be found with fictitious surfaces in the interior of a continuum. Our finding does not depend on any specific constitutive assumption.
International Conference on Advanced and Competitive Manufacturing Technologies milling tool wear prediction using unsupervised machine learning
Authors: Gittler Thomas , Glasder Magnus , Öztürk Elif , Lüthi Michel , Weiss Lukas , Wegener Konrad
Published: May 2021

Degraded or defect machine components and consumables negatively impact manufacturing quality and productivity. Diagnosing and predicting the wear or degradation status of critical machine components or parts are therefore of general interest. To tackle this challenge, data-driven approaches based on supervised machine learning principles have demonstrated promising results. However, supervised learning models capable of degradation identification require large quantities of data. In practice, run-to-failure data in large amounts is usually not available and expensive to obtain. To overcome this issue, this study proposes an unsupervised learning approach for degradation prognostics of machine tool components and consumables. It uses time series of multi-sensor signal data, which are transformed into a feature representation. The features consist of various characterizations of the time series, allowing to make different signal measurements comparable, and cluster them according to their feature values. The herewith obtained density-based clustering model is used to diagnose and predict the degradation states of components and parts in unknown conditions. The novelty in the proposed approach lies within the identification of continuous component and part degradation states based on unsupervised learning principles. The proposal is verified and demonstrated on an exemplary data set containing a small sample of run-to-failure multi-sensor signals of milling inserts and their corresponding wear state. By the application of the proposed procedure on the exemplary data set, we demonstrate that an unsupervised clustering approach is capable of separating wear data such that meaningful and accurate estimations of the part condition are possible. The advantages are its ability to cope with scarce data sets, its limited engineering and hyperparameter tuning effort, and its straightforward implementation to a multitude of degradation and wear diagnostics scenarios.
The electrophysiological effects of cannabidiol on action potentials and transmembrane potassium currents in rabbit and dog cardiac ventricular preparations
Authors: Topal Leila , Naveed Muhammad , Orvos Péter , Pászti Bence , Prorok János , Bajtel Ákos , Kiss Tivadar , Csupor-Löffler Boglárka , Csupor Dezső , Baczkó István , Varró András , Virág László , Jost Norbert
Published: May 2021

Cannabis use is associated with known cardiovascular side effects such as cardiac arrhythmias or even sudden cardiac death. The mechanisms behind these adverse effects are unknown. The aim of the present work was to study the cellular cardiac electrophysiological effects of cannabidiol (CBD) on action potentials and several transmembrane potassium currents, such as the rapid (IKr) and slow (IKs) delayed rectifier, the transient outward (Ito) and inward rectifier (IK1) potassium currents in rabbit and dog cardiac preparations. CBD increased action potential duration (APD) significantly in both rabbit (from 211.7 ± 11.2. to 224.6 ± 11.4 ms, n = 8) and dog (from 215.2 ± 9.0 to 231.7 ± 4.7 ms, n = 6) ventricular papillary muscle at 5 µM concentration. CBD decreased IKr, IKs and Ito (only in dog) significantly with corresponding estimated EC50 values of 4.9, 3.1 and 5 µM, respectively, without changing IK1. Although the EC50 value of CBD was found to be higher than literary Cmax values after CBD smoking and oral intake, our results raise the possibility that potassium channel inhibition by lengthening cardiac repolarization might have a role in the possible proarrhythmic side effects of cannabinoids in situations where CBD metabolism and/or the repolarization reserve is impaired.
Geometric Rényi Divergence and its Applications in Quantum Channel Capacities
Authors: Fang Kun , Fawzi Hamza
Published: May 2021

Having a distance measure between quantum states satisfying the right properties is of fundamental importance in all areas of quantum information. In this work, we present a systematic study of the geometric Rényi divergence (GRD), also known as the maximal Rényi divergence, from the point of view of quantum information theory. We show that this divergence, together with its extension to channels, has many appealing structural properties, which are not satisfied by other quantum Rényi divergences. For example we prove a chain rule inequality that immediately implies the “amortization collapse” for the geometric Rényi divergence, addressing an open question by Berta et al. [Letters in Mathematical Physics 110:2277–2336, 2020, Equation (55)] in the area of quantum channel discrimination. As applications, we explore various channel capacity problems and construct new channel information measures based on the geometric Rényi divergence, sharpening the previously best-known bounds based on the max-relative entropy while still keeping the new bounds single-letter and efficiently computable. A plethora of examples are investigated and the improvements are evident for almost all cases.
The signing body: extensive sign language practice shapes the size of hands and face
Authors: Mora Laura , Sedda Anna , Esteban Teresa , Cocchini Gianna
Published: May 2021

The representation of the metrics of the hands is distorted, but is susceptible to malleability due to expert dexterity (magicians) and long-term tool use (baseball players). However, it remains unclear whether modulation leads to a stable representation of the hand that is adopted in every circumstance, or whether the modulation is closely linked to the spatial context where the expertise occurs. To this aim, a group of 10 experienced Sign Language (SL) interpreters were recruited to study the selective influence of expertise and space localisation in the metric representation of hands. Experiment 1 explored differences in hands’ size representation between the SL interpreters and 10 age-matched controls in near-reaching (Condition 1) and far-reaching space (Condition 2), using the localisation task. SL interpreters presented reduced hand size in near-reaching condition, with characteristic underestimation of finger lengths, and reduced overestimation of hands and wrists widths in comparison with controls. This difference was lost in far-reaching space, confirming the effect of expertise on hand representations is closely linked to the spatial context where an action is performed. As SL interpreters are also experts in the use of their face with communication purposes, the effects of expertise in the metrics of the face were also studied (Experiment 2). SL interpreters were more accurate than controls, with overall reduction of width overestimation. Overall, expertise modifies the representation of relevant body parts in a specific and context-dependent manner. Hence, different representations of the same body part can coexist simultaneously.
On the Boussinesq Equations with Non-monotone Temperature Profiles
Authors: Zillinger Christian
Published: May 2021

In this article, we consider the asymptotic stability of the two-dimensional Boussinesq equations with partial dissipation near a combination of Couette flow and temperature profilesT(y). As a first main result, we show that if$$T'$$T′is of size at most$$\nu ^{1/3}$$ν1/3in a suitable norm, then the linearized Boussinesq equations with only vertical dissipation of the velocity but not of the temperature are stable. Thus, mixing enhanced dissipation can suppress Rayleigh–Bénard instability in this linearized case. We further show that these results extend to the (forced) nonlinear equations with vertical dissipation in both temperature and velocity.
The use of a non-biological, bridging, antiprotrusio cage in complex revision hip arthroplasty and periacetabular reconstructive oncologic surgery. Is still today a valid option?: A mid/long-term survival and complications’ analysis
Authors: Innocenti Matteo , Muratori Francesco , Mazzei Giacomo , Guido Davide , Frenos Filippo , Lucenteforte Ersilia , Capanna Rodolfo , Campanacci Domenico Andrea
Published: May 2021

Introduction

Burch–Schneider-like antiprotrusio cages (B-SlAC) still remain helpful implants to bridge severe periacetabular bone losses. The purpose of this study was to evaluate outcomes and estimate both cages’ failures and complication risks in a series of B-SlAC implanted in revision of failed total hip arthroplasties (THA) or after resection of periacetabular primary or secondary bone malignancies. Risk factors enhancing the chance of dislocations and infections were checked.

Materials and methods

We evaluated 73 patients who received a B-SlAC from January 2008 to January 2018. Group A, 40 oncological cases (22 primary tumors; 18 metastases); Group B, 33 failed THAs. We compared both Kaplan–Meier estimates of risk of failure and complication with the cumulative incidence function, taking account the competing risk of death. Cox proportional hazards model was utilized to identify possible predictors of instability and infection. Harris hip score HHS was used to record clinical outcomes.

Results

Medium follow-up was 80 months (24–137). Average final HHS was 61 (28–92), with no differences within the two groups (p > 0.05). The probabilities of failure and complications were 57% and 26%, respectively, lower in the oncologic group than in the rTHA group (p =0 .176; risk 0.43) (p = 0.52; risk 0.74). Extended ileo-femoral approach and proximal femur replacement (p =0.02, risk ratio = 3.2;p = 0.04, rr = 2.1) were two significant independent predictors for dislocations, while belonging to group B (p = 0.04, rr = 2.6) was predictable for infections.

Conclusion

Burch–Schneider-like antiprotrusio cages are a classical non-biological acetabular reconstruction method that surgeons should bear in mind when facing gross periacetabular bone losses, independently of their cause. However, dislocation and infection rates are high. Whenever possible, we suggest preserving the proximal femur in revision THA, and to use a less-invasive postero-lateral approach to reduce dislocation rates in non-oncologic cases.
Vitali’s generalized absolute differential calculus
Authors: Cogliati Alberto
Published: May 2021

The paper provides an analysis of Giuseppe Vitali’s contributions to differential geometry over the period 1923–1932. In particular, Vitali’s ambitious project of elaborating a generalized differential calculus regarded as an extension of Ricci-Curbastro tensor calculus is discussed in some detail. Special attention is paid to describing the origin of Vitali’s calculus within the context of Ernesto Pascal’s theory of forms and to providing an analysis of the process leading to a fully general notion of covariant derivative. Finally, the reception of Vitali’s theory is discussed in light of Enea Bortolotti and Enrico Bompiani’s subsequent works.
SARS-CoV-2 infection and acute ischemic stroke in Lombardy, Italy
Authors: Pezzini Alessandro , Grassi Mario , Silvestrelli Giorgio , Locatelli Martina , Rifino Nicola , Beretta Simone , Gamba Massimo , Raimondi Elisa , Giussani Giuditta , Carimati Federico , Sangalli Davide , Corato Manuel , Gerevini Simonetta , Masciocchi Stefano , Cortinovis Matteo , La Gioia Sara , Barbieri Francesca , Mazzoleni Valentina , Pezzini Debora , Bonacina Sonia , Pilotto Andrea , Benussi Alberto , Magoni Mauro , Premi Enrico , Prelle Alessandro Cesare , Agostoni Elio Clemente , Palluzzi Fernando , De Giuli Valeria , Magherini Anna , Roccatagliata Daria Valeria , Vinciguerra Luisa , Puglisi Valentina , Fusi Laura , Diamanti Susanna , Santangelo Francesco , Xhani Rubjona , Pozzi Federico , Grampa Giampiero , Versino Maurizio , Salmaggi Andrea , Marcheselli Simona , Cavallini Anna , Giossi Alessia , Censori Bruno , Ferrarese Carlo , Ciccone Alfonso , Sessa Maria , Padovani Alessandro ,   the STROKOVID group
Published: May 2021

Objective

To characterize patients with acute ischemic stroke related to SARS-CoV-2 infection and assess the classification performance of clinical and laboratory parameters in predicting in-hospital outcome of these patients.

Methods

In the setting of the STROKOVID study including patients with acute ischemic stroke consecutively admitted to the ten hub hospitals in Lombardy, Italy, between March 8 and April 30, 2020, we compared clinical features of patients with confirmed infection and non-infected patients by logistic regression models and survival analysis. Then, we trained and tested a random forest (RF) binary classifier for the prediction of in-hospital death among patients with COVID-19.

Results

Among 1013 patients, 160 (15.8%) had SARS-CoV-2 infection. Male sex (OR 1.53; 95% CI 1.06–2.27) and atrial fibrillation (OR 1.60; 95% CI 1.05–2.43) were independently associated with COVID-19 status. Patients with COVID-19 had increased stroke severity at admission [median NIHSS score, 9 (25th to75th percentile, 13) vs 6 (25th to75th percentile, 9)] and increased risk of in-hospital death (38.1% deaths vs 7.2%; HR 3.30; 95% CI 2.17–5.02). The RF model based on six clinical and laboratory parameters exhibited high cross-validated classification accuracy (0.86) and precision (0.87), good recall (0.72) and F1-score (0.79) in predicting in-hospital death.

Conclusions

Ischemic strokes in COVID-19 patients have distinctive risk factor profile and etiology, increased clinical severity and higher in-hospital mortality rate compared to non-COVID-19 patients. A simple model based on clinical and routine laboratory parameters may be useful in identifying ischemic stroke patients with SARS-CoV-2 infection who are unlikely to survive the acute phase.
A critical re-analysis of cases of post-transplantation recurrence in genetic nephrotic syndrome
Authors: Mason Anna E. , Saleem Moin A. , Bierzynska Agnieszka
Published: May 2021

Background

Genetic defects in podocyte proteins account for up to 30% of steroid-resistant nephrotic syndrome (SRNS) in the paediatric population. Most children with genetic SRNS are resistant to immunosuppression and at high risk of progression to stage 5 chronic kidney disease. Kidney transplantation is often the treatment of choice. The possibility of post-transplantation disease recurrence in genetic SRNS remains controversial, and poses fundamental questions about disease biology.

Methods

We critically evaluated the published cases of post-transplantation recurrence in genetic patients, particularly testing ‘mutations’ against the most recent population variant databases, in order to clarify the diagnoses, and compare the clinical courses and responses to therapy.

Results

Biallelic pathogenic variants in NPHS1 leading to a complete absence of nephrin were the most commonly reported and best understood instance of nephrotic syndrome occurring post-transplantation. This is an immune-mediated process driven by antibody production against the novel nephrin protein in the allograft. We also identified a number of plausible reported cases of post-transplantation recurrence involving pathogenic variants in NPHS2 (8 patients, biallelic), one in WT1 (monoallelic) and one in NUP93 (biallelic). However, the mechanism for recurrence in these cases remains unclear. Other instances of recurrence in genetic disease were difficult to interpret due to differing clinical criteria, inclusion of patients without true pathogenic variants or the influence of other factors on renal outcome.

Conclusions

Overall, post-transplantation recurrence remains very rare in patients with genetic SRNS. It appears to occur later after transplantation than in other patients and usually responds well to plasmapheresis with a good renal outcome.
Genetic factors explain a significant part of associations between adolescent well-being and the social environment
Authors: van de Weijer Margot P. , Pelt Dirk H. M. , van Beijsterveldt Catharina E. M. , Willemsen Gonneke , Bartels Meike
Published: May 2021

Socio-environmental factors play an important role in adolescent well-being, but potential genetic contributions to these associations are rarely assessed. To address this gap in the literature, associations between well-being and family conflict and functioning, number of friends, friendship importance and satisfaction, and leisure time variables were studied inN =  ~ 4700 twin pairs from the Netherlands Twin Register, us ing generalized estimating equations and twin-difference scores. When twin-difference scores indicated a role for genetic factors, we used bivariate genetic models to quantify genetic and environmental contributions to these associations. We identify significant associations between well-being and family functioning, family conflict, different leisure time activities, number of friends, and satisfaction with friendships. Additionally, we find evidence for large (73–91%) genetic influence on the associations between well-being and family conflict and functioning, leisure time sport/scouting clubs, and satisfaction with friendships. Finally, findings support the hypothesis of a causal association between well-being and family conflict and functioning. These findings have important implications for research into the social correlates of well-being in adolescence, as not taking genetic factors into account leads to overestimations of the influence of identified correlates and consequently to recommendations of these correlates as intervention targets.
Neural predictive monitoring and a comparison of frequentist and Bayesian approaches
Authors: Bortolussi Luca , Cairoli Francesca , Paoletti Nicola , Smolka Scott A. , Stoller Scott D.
Published: May 2021

Neural state classification (NSC) is a recently proposed method for runtime predictive monitoring of hybrid automata (HA) using deep neural networks (DNNs). NSC trains a DNN as an approximate reachability predictor that labels an HA state x as positive if an unsafe state is reachable from x within a given time bound, and labels x as negative otherwise. NSC predictors have very high accuracy, yet are prone to prediction errors that can negatively impact reliability. To overcome this limitation, we present neural predictive monitoring (NPM), a technique that complements NSC predictions with estimates of the predictive uncertainty. These measures yield principled criteria for the rejection of predictions likely to be incorrect, without knowing the true reachability values. We also present an active learning method that significantly reduces the NSC predictor’s error rate and the percentage of rejected predictions. We develop two versions of NPM based, respectively, on the use of frequentist and Bayesian techniques to learn the predictor and the rejection rule. Both versions are highly efficient, with computation times on the order of milliseconds, and effective, managing in our experimental evaluation to successfully reject almost all incorrect predictions. In our experiments on a benchmark suite of six hybrid systems, we found that the frequentist approach consistently outperforms the Bayesian one. We also observed that the Bayesian approach is less practical, requiring a careful and problem-specific choice of hyperparameters.
Charcot knee — presentation, diagnosis, management — a scoping review
Authors: Lu Victor , Zhang James , Thahir Azeem , Zhou Andrew , Krkovic Matija
Published: May 2021

Background

Charcot arthropathy is a progressive, non-infectious, destructive inflammatory process. Charcot arthropathy of the knee (CK) is rare and diagnosis is often delayed, resulting in detrimental outcomes. This scoping review aims to investigate the literature on CK, present the pathognomonic features of CK to aid early diagnosis, and suggest gaps in the literature for future research.

Methods

A systematic search of PubMed, EMBASE, Web of Science for literature relevant to CK was performed. Primary studies such as case reports, case series, retrospective studies were included. Review articles and animal studies were excluded.

Results

Of the 513 results, 58 were included in qualitative synthesis. Average time from symptom onset to CK diagnosis was 50.5 months. Eighteen and twenty-one studies included patients who had diabetes mellitus and syphilis, respectively. Twenty-one studies reported pain as a presenting complaint, but the degree of pain didn’t correspond with the level of destruction. Oedema and joint effusion were noticed in 34 studies. Twenty-nine studies reported lower limb hypoesthesia and 17 studies reported decreased tendon reflex. Twenty-eight studies reported initial conservative treatment, often in a knee brace with minimal weight bearing, 9 of which needed subsequent surgical management. Twelve studies utilised arthrodesis, with fracture at the intramedullary nail entry site being the most common complication. Twenty-four studies utilised TKA.

Conclusion

The literature on CK remains sparse, with most publications being case reports. Given that CK dramatically reduces quality of life, increases morbidity of patients, there is need for more literature on evidence-based options for early diagnoses and management.
In vitro testing of explanted shunt valves in hydrocephalic patients with suspected valve malfunction
Authors: Bettag Christoph , von der Brelie Christian , Freimann Florian Baptist , Thomale Ulrich-Wilhelm , Rohde Veit , Fiss Ingo
Published: May 2021

Diagnosis of symptomatic valve malfunction in hydrocephalic patients treated with VP-Shunt (VPS) might be difficult. Clinical symptoms such as headache or nausea are nonspecific, hence cerebrospinal fluid (CSF) over- or underdrainage can only be suspected but not proven. Knowledge concerning valve malfunction is still limited. We aim to provide data on the flow characteristics of explanted shunt valves in patients with suspected valve malfunction. An in vitro shunt laboratory setup was used to analyze the explanted valves under conditions similar to those in an implanted VPS. The differential pressure (DP) of the valve was adjusted stepwise to 20, 10, 6, and 4 cmH2O. The flow rate of the explanted and the regular flow rate of an identical reference valve were evaluated at the respective DPs. Twelve valves of different types (Codman CertasPlus valve n = 3, Miethke Shuntassistant valve n = 4, Codman Hakim programmable valve n = 3, DP component of Miethke proGAV 2.0 valve n = 2) from eight hydrocephalic patients (four male), in whom valve malfunction was assumed between 2016 and 2017, were replaced with a new valve. Four patients suffered from idiopathic normal pressure (iNPH), three patients from malresorptive and one patient from obstructive hydrocephalus. Post-hoc analysis revealed a significant difference (p < 0.001) of the flow rate between each explanted valve and their corresponding reference valve, at each DP. In all patients, significant alterations of flow rates were demonstrated, verifying a valve malfunction, which could not be objectified by the diagnostic tools used in the clinical routine. In cases with obscure clinical VPS insufficiency, valve deficiency should be considered.
Convolutional neural networks (CNNs): concepts and applications in pharmacogenomics
Authors: Vaz Joel Markus , Balaji S.
Published: May 2021

Convolutional neural networks (CNNs) have been used to extract information from various datasets of different dimensions. This approach has led to accurate interpretations in several subfields of biological research, like pharmacogenomics, addressing issues previously faced by other computational methods. With the rising attention for personalized and precision medicine, scientists and clinicians have now turned to artificial intelligence systems to provide them with solutions for therapeutics development. CNNs have already provided valuable insights into biological data transformation. Due to the rise of interest in precision and personalized medicine, in this review, we have provided a brief overview of the possibilities of implementing CNNs as an effective tool for analyzing one-dimensional biological data, such as nucleotide and protein sequences, as well as small molecular data, e.g., simplified molecular-input line-entry specification, InChI, binary fingerprints, etc., to categorize the models based on their objective and also highlight various challenges. The review is organized into specific research domains that participate in pharmacogenomics for a more comprehensive understanding. Furthermore, the future intentions of deep learning are outlined.