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Parkinson’s disease (PD) is one of the most common neurodegenerative diseases affecting a large population worldwide. Parkinson’s disease is characterized by rigidity, slowness of movement and tremors at rest, these syndromes are frequently manifested in the deterioration of handwriting. The aim of this article is to perform online Arabic handwriting analysis for two types of tasks, TASK 1: copying arabic imposed text and TASK 2: writing arabic desired text. A novel method of handwriting selection features is proposed to obtain the relevant features to efficiently identify subjects with PD, based on Recursive Feature Elimination with Cross-Validation (RFECV), three different RFE estimators were compared: Support Vector Machine, Decision Trees and Random Forest, the selected features have been fed to the same classifiers above to determine the best classifier for predicting Parkinson’s disease. Result: An accuracy of 94.4% was obtained using SVM with Linear kernel, based on 55 features selected using RFE-SVM(Linear) for TASK 1, for TASK 2 an accuracy of 93.7% was obtained using SVM with RBF kernel, based only in 7 features selected using RFE-SVM(Linear). For all the classifiers used, this technique experimentally demonstrates an increase in performance metrics.

Introduction. Epidermal growth factor receptor (EGFR) is a transmembrane protein of the receptor tyrosine kinase family that is activated in various cancers (non-small cell lung cancer, colorectal cancer, head and neck tumors). In glial brain tumors, increased EGFR expression levels are characteristic of the most aggressive subtype, glioblastoma. Frequent structural changes of EGFR in glioblastoma are amplification of the chromosome region where the EGFR gene is located, point mutations, as well as deletion of exons 2–7 of the EGFR gene leading to the formation of EGFRvIII transcript.Aim. To determine structural changes of the EGFR gene (point mutations and amplification of the EGFR gene, EGFRvIII transcript) in tumor samples using different methods and to evaluate their potential clinical significance.Materials and methods. The study included 75 patients with brain gliomas (70 of them glioblastoma) aged 34 to 78 years (mean age 56 years). DNA and RNA isolation was performed from fresh frozen tumor tissue, as well as from peripheral blood leukocytes. EGFR gene mutations were determined by next-generation sequencing (NGS), and β allele frequency (BAF) comparative analysis (normal-tumor) was performed to determine the copy number of chromosome 7 regions. Quantitative polymerase chain reaction was used to confirm the EGFR gene amplification in tumor samples, and reverse transcription-PCR was used to detect EGFRvIII variant.Results. The NGS method revealed 11/70 (16 %) mutations in coding regions of EGFR gene in glioblastoma samples, the EGFR gene amplification was detected in 26/70 (37 %) cases; no structural changes of the EGFR gene were detected in 5 glioma samples (astrocytoma, oligodendroglioma). All cases of EGFR gene amplification detected by NGS were confirmed by quantitative polymerase chain reaction. To search for EGFRvIII transcript, 31 tumor RNA samples were examined, of which EGFR amplification was present in 12 samples. EGFRvIII transcript was detected only in samples with EGFR gene amplification – 4/12 (33 %). To assess the clinical significance of structural gene alterations, the frequency of occurrence in primary and recurrent glioblastoma samples was compared.Conclusion. The NGS method allows to detect both point mutations and amplification of the EGFR gene. The EGFR gene amplification was associated with EGFRvIII mutation in 33 % of cases. No statistically significant differences in the frequency of structural changes in the EGFR gene between primary and relapsed glioblastomas were found.

De l'adoption d'une comptabilité de gestion environnementale à la performance globale de l'entreprise Résumé : La préservation de l'environnement est prise plus sérieusement. Il est devenu un enjeu important au sein de la communauté internationale,des États et des particuliers qui sont touchés par la pollution des plages, des sols, entourés par les déchets, les citoyens souffrent chaque jour du bruit et de l'air pollué qu'ils respirent. Il faut cependant souligner l’exigence d’un développement durable qui associe une multiplicité de disciplines sur des questions complexes comme les externalités négatives de l’activité économique. La triple performance (économique, sociale, environnementale) des entreprises est aujourd'hui constatée par les parties prenantes et les entreprises les plus avancées, elle se réalise par la mise en place d'une comptabilité environnementale qui permet à l'entreprise d'orienter sa gestion environnementale vers la création de valeur. En effet, la comptabilité de gestion adressée à l'environnement se présente et prend une place importante dans une gestion responsable et environnementale. Cela nécessite de rapprocher une perspective économique et sociétale comme objet de recherche afin d’envisager les contestations auxquelles elle fait actuellement l’objet. Au cours de cette étude, notre objectif est de souligner à quel point la comptabilité de gestion peut apporter des solutions pertinentes à l’intégration des préoccupations environnementales. Mots-clés : Comptabilité de gestion environnementale, coûts environnementaux, développement durable, responsabilité sociale, performance environnementale.

Introduction. Rubella virus is an RNA-containing virus capable of infecting human cells and causing infectious disease. Infection of pregnant women with rubella virus can lead to abortion or congenital rubella syndrome (CRS), a set of long-term birth defects including incomplete fetal organ development and mental retardation. There is no specific treatment for rubella and CRS. The regulation of antiviral immune response and viral reproduction by long non-coding RNAs is currently under active investigation. In this study, we evaluated the changes in the expression profile of long non-coding RNAs in rubella virus-infected A549 epithelial by RNA sequencing. Materials and Methods. A549 cells were infected with a wild-type variant of laboratory strain C-77 of rubella virus with a multiplicity of infection of 1.0 infectious units per cell and incubated for 72 hours. Virus titres were determined by the CCID method in the sensitive RK-13 cell culture. 48 h after infection, the cell monolayer was lysed, RNA was isolated, and libraries were prepared for sequencing. Sequencing was performed on the NextSeq500 platform (Illumina, USA) in paired-end reading mode. Validation of the obtained RNA sequencing data was performed using quantitative real-time PCR. Results. Rubella virus replication affects the production of some long non-coding RNAs by altering their expression profile. Thus, upon infection of A549 epithelial cells with rubella virus, there was a significant increase in the expression of such long non-coding RNAs as GAS5, NEAT1, LUCAT1, MIR210HG, MEG3, EPB41L4A-AS1, ZFAS1, and SNHG 1, 7, 12, 29, 32. DANCR, IGFL2-AS1, IGFL2-AS1, MIR1915HG, and SNHG14 were most significantly decreased in expression. Gene ontology (GO)-analysis revealed that long non-coding RNAs are involved at different levels in the mechanisms of immune response, in particular, RNA processing and nucleic acid metabolism; therefore, up- and down-regulation of these molecules leads to modulation of human antiviral immune response in response to rubella virus infection. Conclusion. Thus, the regulation of long non-coding RNA production by rubella virus has been shown for the first time. Differentially expressed long non-coding RNAs can be used as prognostic and diagnostic biomarkers of viral diseases.

The COVID-19 pandemic has affected educational systems worldwide, leading some scholars to scrutinise the consequences of lockdown and school closure on learners' learning habits and teachers' teaching practices. In this regard, this paper aims to explore the teachers' challenges while implementing a reading strategy-based instruction for beginners during the COVID-19 pandemic, taking the Algerian middle schools as a case in point. It highlights the difficulties to achieving quality in developing learners' procedural knowledge and strategic awareness in EFL reading classes. The leading approach to the issue is the interactive approach. To attain the objective of the research, the qualitative method was adopted. Classroom observation and structured interviews were used to collect data. The population targeted was composed of 20 teachers from 16 middle schools in Tizi-Ouzou. The collected data were subjected to qualitative content analysis. The results of the study reveal that most teachers are aware of the importance of reading strategy-based instruction. However, they do not teach them systematically or consistently. Indeed, lack of targeted teacher training, time constraints, and disregard of metacognitive instruction are likely to be obstacles to the efficient implementation of reading strategy-instruction. Furthermore, the COVID-19 pandemic has thrown up several psychological and cognitive learners' difficulties, including decreased motivation and lack of cognitive focus, making the teaching process more challenging. The results imply a need for a revision of teachers' professional development programs and a re-consideration of the elementary EFL courses.

The Social Package for the Social Sciences (SPSS) is among the most common programs used by researchers in language studies to explore, examine, and analyze quantitative data for the sake of drawing valid conclusions. The current action research aims to offer insights into the utilization of SPSS by Master’s students in their empirical studies for statistical analysis. Specifically, it attempts to depict the way SPSS is employed in academic pursuits, and discern the inherent challenges faced by students, offering insights into the obstacles that may impede their effective use of SPSS as a tool for statistical exploration and interpretation in academic research. To reach these objectives, ten Master’s dissertations written by EFL students at the Department of English at Mouloud Mammeri University in language studies were scrutinized though a qualitative content analysis. Findings indicate that the students limit the scope of their use of SPSS to quantitative variables and descriptive statistics. In addition, it has been found that the most commonly used statistical technique is ‘the mean’ or ‘the average’ that could be easily measured without any sophisticated software. Furthermore, no reference to inferential statistics in order to compare among groups or to measure the impact of a variable on another is made. The overall conclusion drawn from the analysis of the corpus is that students exhibit reluctance to the use of inferential statistics in their empirical studies and unconsciously believe that SPSS, inferential statistics, or any other sophisticated software are tightly related to natural sciences and could not be easily applied in social sciences. On the basis of the findings, a number of recommendations are suggested like organizing workshops with computer scientists. In addition, students’ self-confidence should be increased in order to change their perception of their potential and abilities to feel more at ease with statistics and technologies while doing academic research in language studies.

Introduction. Despite the end of the COVID-19 pandemic, the problem of vaccine prevention of this disease appears highly relevant. The emergence and widespread distribution of the Omicron SARS-CoV-2 variant of concern (VOC) and its sublineages has dramatically reduced the efficacy of vaccination. The possible approach to solving this problem is to develop a nasal live attenuated vaccine capable of activating humoral, mucosal, and cell-mediated immunity, providing a prolonged immune response and cross-protection against different VOCs. The aim of the study was to determine the immunization efficacy with attenuated cold-adapted Wuhan-like SARS-CoV-2 D-D2 strain against homologous and heterologous challenges. Materials and methods. The study was conducted on an animal model of coronavirus pneumonia in golden Syrian hamsters. The efficacy of immunization was assessed by comparing the dynamics of weight, viral load in organs and histopathological changes in the lungs in immunized and unimmunized animals. Results. Single intranasal immunization of golden Syrian hamsters with D-D2 strain showed its high immunogenicity: seroconversion was evident in all immunized animals. Wuhan-like D-D2 strain provides highly effective protection of hamsters against the development of productive infection and pneumonia when challenged both with ancestral virus and heterologous strains related to Delta (AY.122) and Omicron (sublineages BA.1.1 and BA.5.2) variants. Conclusion. SARS-CoV-2 attenuation is a promising strategy for the development of a highly effective nasal live COVID-19 vaccine.

In this paper, we report the modelling of quantum capacitance in both single-layer and bilayer graphene devices to investigate the temperature dependence. The model includes the existence of electron and hole puddles due to local fluctuations of the potential, which is taken into account with the possibility of finite lifetimes of electronic states to calculate the quantum capacitance using the Gaussian distribution. The results indicate that the simulations are in agreement with the experimental measurements, which proves the accuracy of the proposed model. On the other hand, temperature dependence around the charge neutrality point has been reported for both single and bilayer graphene.

This study evaluates the oncolytic potential of the Moscow strain of reovirus against human metastatic melanoma and glioblastoma cells. The Moscow strain effectively infects and replicates within human melanoma cell lines and primary glioblastoma cells, while sparing non-malignant human cells. Infection leads to the selective destruction of neoplastic cells, mediated by functional viral replication. A positive correlation was identified between viral RNA accumulation and tumor cell death, with no replication observed in non-malignant cells. This study highlights the critical roles of cathepsins B, L, and S as mediators of the oncolytic process. The pharmacological inhibition of these enzymes significantly attenuated reovirus-induced cytotoxicity in melanoma and glioblastoma cells. Conversely, PKR production analysis revealed minimal activation in reovirus-infected tumor cells, suggesting that the hyperactivation of the RAS-signaling pathway and subsequent PKR inhibition do not directly contribute to the selective efficacy of reovirus. Moreover, infected tumor cells exhibited features of both apoptotic and non-apoptotic death, emphasizing the intricate mechanisms of reovirus-mediated oncolysis. These findings underscore the therapeutic promise of the Moscow strain of reovirus as a selective and potent oncolytic agent for targeting melanoma and glioblastoma cells.

Over the course of the year, temperate trees experience extremes in temperature and day length. In order to protect themselves from frost damage in winter, they enter a dormant state with no visible growth where all leaves are shed and buds are dormant. Also the young floral tissues need to withstand harsh winter conditions, as temperature fruit trees like apple develop their flower buds in the previous year of fruit development. So far, the genetic control of induction and release of dormancy is not fully understood. However, the transcription factor family of DORMANCY-Associated MADS-box (DAM) genes plays a major role in the control of winter dormancy. One of these genes is MdDAM4. This gene is expressed in the early phase of bud dormancy, but little is known about its function. Six transgenic apple lines were produced to study the function of MdDAM4 in apple. For plant transformation, the binary plasmid vector p9oN-35s-MdDAM4 was used that contains the coding sequence of MdDAM4 driven by the 35S promoter. Transgenicity of the lines was proven by PCR and southern hybridization. Based on siRNA sequencing and phenotypic observations, it was concluded that line M2024 overexpresses MdDAM4 whereas the gene is silenced in all other lines. Phenotyping of the transgenic lines provided evidence that the overexpression of MdDAM4 leads to an earlier induction and a later release of dormancy. Silencing this gene had exactly the opposite effects and thereby led to an increased duration of the vegetation period. Expression experiments revealed genes that were either potentially repressed or activated by MdDAM4. Among the potentially suppressed genes were several homologs of the cytokinin oxidase 5 (CKX5), five LOX homologs, and several expansins, which may indicate a link between MdDAM4 and the control of leaf senescence. Among the potentially activated genes is MdDAM1, which is in line with observed expression patterns during winter dormancy. MdDAM2, which shows little expression during endodormancy also appears to be activated by MdDAM4. Overall, this study provides experimental evidence with transgenic apple trees for MdDAM4 being an important regulator of the onset of bud dormancy in apple.

Background Gait characteristics are important risk factors for falls, hospitalisations and mortality in older adults, but the impact of COPD on gait performance remains unclear. We aimed to identify differences in gait characteristics between adults with COPD and healthy age-matched controls during 1) laboratory tests that included complex movements and obstacles, 2) simulated daily-life activities (supervised) and 3) free-living daily-life activities (unsupervised). Methods This case–control study used a multi-sensor wearable system (INDIP) to obtain seven gait characteristics for each walking bout performed by adults with mild-to-severe COPD (n=17; forced expiratory volume in 1 s 57±19% predicted) and controls (n=20) during laboratory tests, and during simulated and free-living daily-life activities. Gait characteristics were compared between adults with COPD and healthy controls for all walking bouts combined, and for shorter (≤30 s) and longer (>30 s) walking bouts separately. Results Slower walking speed (−11 cm·s−1, 95% CI: −20 to −3) and lower cadence (−6.6 steps·min−1, 95% CI: −12.3 to −0.9) were recorded in adults with COPD compared to healthy controls during longer (>30 s) free-living walking bouts, but not during shorter (≤30 s) walking bouts in either laboratory or free-living settings. Double support duration and gait variability measures were generally comparable between the two groups. Conclusion Gait impairment of adults with mild-to-severe COPD mainly manifests during relatively long walking bouts (>30 s) in free-living conditions. Future research should determine the underlying mechanism(s) of this impairment to facilitate the development of interventions that can improve free-living gait performance in adults with COPD.

Purpose Regulatory authorities including the Food and Drug Administration and the European Medicines Agency are encouraging to conduct clinical trials using routinely collected data. The aim of the TransFAIR experimental comparison was to evaluate, within real-life conditions, the ability of the Electronic Health Records to Electronic Data Capture (EHR2EDC) module to accurately transfer from EHRs to EDC systems patients’ data of clinical studies in various therapeutic areas.Methods A prospective study including six clinical trials from three different sponsors running in three hospitals across Europe has been conducted. The same data from the six studies were collected using both traditional manual data entry and the EHR2EDC module. The outcome variable was the percentage of data accurately transferred using the EHR2EDC technology. This percentage was calculated considering all collected data and the data in four domains: demographics (DM), vital signs (VS), laboratories (LB) and concomitant medications (CM).Results Overall, 6143 data points (39.6% of the data in the scope of the TransFAIR study and 16.9% when considering all data) were accurately transferred using the platform. LB data represented 65.4% of the data transferred; VS data, 30.8%; DM data, 0.7% and CM data, 3.1%.Conclusions The objective of accurately transferring at least 15% of the manually entered trial datapoints using the EHR2EDC module was achieved. Collaboration and codesign by hospitals, industry, technology company, supported by the Institute of Innovation through Health Data was a success factor in accomplishing these results. Further work should focus on the harmonisation of data standards and improved interoperability to extend the scope of transferable EHR data.

This article considers the chrono-cultural evolution in the Northwest Africa territories during the Neolithic period. A systematic chronology based on specialized literature on the chrono-cultural features of this period in the Sahara and the Maghreb was inferred. It covers the following three major Neolithic currents characteristic of the Neolithic period in Northwest Africa: the Saharan Sudanese Neolithic, the Neolithic of Capsian Tradition, and the Mediterranean Neolithic. These currents were studied using the data on cultural behaviors with some radiocarbon dates. The results obtained revealed the features of the evolution from the Neolithization process to the full establishment of the Neolithic economy of production, as well as, a possible continuity to a Final Neolithic phase that lasted longer in some regions despite other regions that transitioned to the Eneolithic and the Iron Age. It was concluded that the evolution path that determined the characteristics of the Early, Middle, Late, and Final Neolithic phases was almost the same in different territories of the northwestern part of the African continent.

This study evaluates the oncolytic potential of the Moscow strain of reovirus against human metastatic melanoma and glioblastoma cells. The Moscow strain effectively infects and replicates within human melanoma cell lines and primary glioblastoma cells, while sparing non-malignant human cells. Infection leads to the selective destruction of neoplastic cells, mediated by functional viral replication. A positive correlation was identified between viral RNA accumulation and tumor cell death, with no replication observed in non-malignant cells. This study highlights the critical roles of cathepsins B, L, and S as mediators of the oncolytic process. The pharmacological inhibition of these enzymes significantly attenuated reovirus-induced cytotoxicity in melanoma and glioblastoma cells. Conversely, PKR production analysis revealed minimal activation in reovirus-infected tumor cells, suggesting that the hyperactivation of the RAS-signaling pathway and subsequent PKR inhibition do not directly contribute to the selective efficacy of reovirus. Moreover, infected tumor cells exhibited features of both apoptotic and non-apoptotic death, emphasizing the intricate mechanisms of reovirus-mediated oncolysis. These findings underscore the therapeutic promise of the Moscow strain of reovirus as a selective and potent oncolytic agent for targeting melanoma and glioblastoma cells. [ABSTRACT FROM AUTHOR]

Gliomas are a heterogeneous group of brain tumors, among which the most aggressive subtype is glioblastoma, accounting for 60% of cases in adults. Available systemic treatment options are few and ineffective, so new approaches to therapies for glioblastoma are in high demand. In total, 131 patients with diffuse glioma were studied. Paired tumor–normal samples were sequenced on the Illumina platform; the panel included 812 genes associated with cancer development. Molecular profiles in clinically distinct groups were investigated. In low-grade glioma (LGG) patients (n = 18), the most common mutations were IDH1/2 (78%), ATRX (33%), TP53 (33%), PIK3CA (17%), and co-deletion 1p/19q (22%). In high-grade glioma (HGG) patients (n = 113), more frequently affected genes were CDKN2A/B (33%), TERTp (71%), PTEN (60%), TP53 (27%), and EGFR (40%). The independent predictors of better prognosis were tumor grade and IDH1/2 mutations. In IDH—wildtype glioblastoma patients, a history of other precedent cancer was associated with worse overall survival (OS), while re-operation and bevacizumab therapy increased OS. Also, among genetic alterations, TERTp mutation and PTEN deletion were markers of poor prognosis. Nine patients received molecular targeted therapy, and the results were evaluated. The search for molecular changes associated with tumor growth and progression is important for diagnosis and choice of therapy. [ABSTRACT FROM AUTHOR]

A comprehensive study on the whole spectrum of viruses and viroids in five Iranian grapevine cultivars was carried out using sRNA libraries prepared from phloem tissue. A comparison of two approaches to virus detection from sRNAome data indicated a significant difference in the results and performance of the aligners in viral genome reconstruction. The results showed a complex virome in terms of viral composition, abundance, and richness. Thirteen viruses and viroids were identified in five Iranian grapevine cultivars, among which the grapevine red blotch virus and grapevine satellite virus were detected for the first time in Iranian vineyards. Grapevine leafroll-associated virus 1 (GLRaV1) and grapevine fanleaf virus (GFLV) were highly dominant in the virome. However, their frequency and abundance were somewhat different among grapevine cultivars. The results revealed a mixed infection of GLRaV1/grapevine yellow speckle viroid 1 (GYSVd1) and GFLV/GYSVd1 in grapevines that exhibited yellows and vein banding. We also propose a threshold of 14% of complete reconstruction as an appropriate threshold for detection of grapevine viruses that can be used as indicators for reliable grapevine virome profiling or in quarantine stations and certification programs.

Introduction. Oncolytic virotherapy is one of the approaches in immunotherapy of solid brain tumors. Measles virus vaccine strains are prospective agents for the therapy of cancers such as neuroblastoma, mesothelioma, and glioblastoma multiforme. The hyperexpression of the CD46 and other receptors on the surface of malignant cells allows the measles virus to infect and lyse the tumor, thus inducing an immune response. However, widespread immunization of the population and the resistance of neoplasms to oncolysis present difficulties in clinical practice.Text. This review covers approaches to modifying the measles virus genome in order to increase specificity of virotherapy, overcome existing immunity, and enhance the oncolytic effect. It was shown that expression of proinflammatory cytokines on viral particles leads to tumor regression in mice and triggers a T-cell response. Several approaches have been used to overcome virus-neutralizing antibodies: shielding viral particles, using host cells, and altering the epitope of the protein that enables entry of the virus into the cell. Furthermore, the insertion of reporter genes allows the infection of target cells to be monitored in vivo. A combination with the latest immunotherapies, such as immune checkpoint inhibitors, demonstrates synergistic effects, which suggests the successful use of combined approaches in the therapy of refractory tumors.Conclusion. Measles virus attenuated strains appear to be an easy-to-modify and reliable platform for the therapy of solid brain tumors.

Introduction : depuis février 2020, la pandémie de Covid-19 a contaminé plus de 200 000 personnes en Algérie et a entrainé plus de 5500 décès. Cependant, les changements dynamiques du profil clinique des patients atteints de Covid-19 restent inconnus. Méthodes : dans cette étude rétrospective, les caractéristiques démographiques, les antécédents médicaux et les symptômes de tous les patients reçus au CHU d’Oran pour Covid-19 entre le 18 mars 2020 et le 31 aout 2021 ont été recueillis. Les patients ont été répartis selon les trois vagues de Covid-19 qu’a vécu l’Algérie. Les caractéristiques des patients ont été comparées entre les trois groupes. Résultats : sur l’ensemble des 2442 cas Covid-19 reçus au CHU d’Oran, il y a eu 1055 patients lors de la première vague, 905 patients lors de la deuxième vague et 482 patients lors de la troisième vague. La troisième vague a été caractérisée par une démographie plus jeune, plus de symptômes et moins de comorbidités. Conclusion : notre étude a fourni des informations importantes sur la dynamique du Covid-19 et ceci pourrait aider les médecins et les responsables de la santé à faire face à la pandémie actuelle.

Unimodal biometric systems rely on a single source or unique individual biological trait for measurement and examination. Fingerprint-based biometric systems are the most common, but they are vulnerable to presentation attacks or spoofing when a fake fingerprint is presented to the sensor. To address this issue, we propose an enhanced biometric system based on a multimodal approach using two types of biological traits. We propose to combine fingerprint and Electrocardiogram (ECG) signals to mitigate spoofing attacks. Specifically, we design a multimodal deep learning architecture that accepts fingerprints and ECG as inputs and fuses the feature vectors using stacking and channel-wise approaches. The feature extraction backbone of the architecture is based on data-efficient transformers. The experimental results demonstrate the promising capabilities of the proposed approach in enhancing the robustness of the system to presentation attacks.

The use of digital health products has gained considerable interest as a new way to improve therapeutic research and development. Although these products are being adopted by various industries and stakeholders, their incorporation in clinical trials has been slow due to a disconnect between the promises of digital products and potential risks in using these new technologies in the absence of regulatory support. The Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium hosted a public workshop to address challenges and opportunities in this field. Important characteristics of tool development were addressed in a series of presentations, case studies, and open panel sessions. The workshop participants endorsed the usefulness of an evidentiary criteria framework, highlighted the importance of early patient engagement, and emphasized the potential impact of digital monitoring tools and precompetitive collaborations. Concerns were expressed about the lack of real‐life validation examples and the limitations of legacy standards used as a benchmark for novel tool development and validation. Participants recognized the need for novel analytical and statistical approaches to accommodate analyses of these novel data types. Future directions are to harmonize definitions to build common methodologies and foster multidisciplinary collaborations; to develop approaches toward integrating digital monitoring data with the totality of the data in clinical trials, and to continue an open dialog in the community. There was a consensus that all these efforts combined may create a paradigm shift of how clinical trials are planned, conducted, and results brought to regulatory reviews.

Health care has had to adapt rapidly to COVID-19, and this in turn has highlighted a pressing need for tools to facilitate remote visits and monitoring. Digital health technology, including body-worn devices, offers a solution using digital outcomes to measure and monitor disease status and provide outcomes meaningful to both patients and health care professionals. Remote monitoring of physical mobility is a prime example, because mobility is among the most advanced modalities that can be assessed digitally and remotely. Loss of mobility is also an important feature of many health conditions, providing a read-out of health as well as a target for intervention. Real-world, continuous digital measures of mobility (digital mobility outcomes or DMOs) provide an opportunity for novel insights into health care conditions complementing existing mobility measures. Accepted and approved DMOs are not yet widely available. The need for large collaborative efforts to tackle the critical steps to adoption is widely recognised. Mobilise-D is an example. It is a multidisciplinary consortium of 34 institutions from academia and industry funded through the European Innovative Medicines Initiative 2 Joint Undertaking. Members of Mobilise-D are collaborating to address the critical steps for DMOs to be adopted in clinical trials and ultimately health care. To achieve this, the consortium has developed a roadmap to inform the development, validation and approval of DMOs in Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease and recovery from proximal femoral fracture. Here we aim to describe the proposed approach and provide a high-level view of the ongoing and planned work of the Mobilise-D consortium. Ultimately, Mobilise-D aims to stimulate widespread adoption of DMOs through the provision of device agnostic software, standards and robust validation in order to bring digital outcomes from concept to use in clinical trials and health care.

Introduction. Neutropenia, which is an abnormally low concentration of neutrophils in the blood, is one of the common side effects in patients receiving radio- or chemotherapy. Neutropenia usually leads to higher risks of severe bacterial and fungal infections. Such medicines as colonystimulating factor filgrastim (and its conjugates) are used to prevent and treat neutropenia in oncology patients. Immunogenicity is a potential concern for any biological product, thus, its assessment is one of the most critical necessities during the development and registration of such products.Aim. The main aim of this study was to validate the ELISA method for anti-pegfilgrastim antibodies detection in human serum samples and to apply the validated method to pegfilgrastim drugs immunogenicity assessment.Materials and methods. To assess pegfilgrastim immunogenicity, the commercial ELISA kit «PEGylated Filgrastim (Neulasta®) ADA ELISA» was used for screening, confirmatory and titer assay. Moreover, to confirm the chosen commercial kit suits the study aims it was revalidated. The absorbance values were obtained using plate immunoassay analyzer Stat Fax 3200, plate washing was performed using an automatic twochannel plate washer.Results and discussion. The ELISA method for anti-pegfilgrastim antibodies determination in human serum samples was validated and applied to the analytical part of the comparative, multicenter, blind, randomized study of pegfilgrastim efficacy and safety in patients with breast cancer, receiving myelosuppressive chemotherapy. Human serum samples were first screened for anti-drug antibodies, then «screening positive» samples were analyzed in confirmatory assay with % inhibition calculation for each sample. The «confirmed positive» samples were further characterized in titer assay.Conclusions. The ELISA method for anti-pegfilgrastim antibodies determination in human serum samples was successfully validated and applied for pegfilgrastim drugs immunogenicity assessment.

The electrocardiogram (ECG) signal is shown to be promising as a biometric. To this end, it has been demonstrated that the analysis of ECG signals can be considered as a good solution for increasing the biometric security levels. This can be mainly due to its inherent robustness against presentation attacks. In this work, we present a deep contrastive learning-based system for ECG biometric identification. The proposed system consists of three blocks: a feature extraction backbone based on short time Fourier transform (STFT), a contrastive learning network, and a classification network. We evaluated the proposed system on the Heartprint dataset, a new ECG biometrics multi-session dataset. The experimental analysis shows promising capabilities of the proposed method. In particular, it yields an average top1 accuracy of 98.02% on a new dataset built by gathering 1539 ECG records from 199 subjects collected in multiple sessions with an average interval between sessions of 47 days.

Glioblastoma multiforme (GBM) accounts for almost half of all primary malignant brain tumors in adults and has a poor prognosis. Here we demonstrated the oncolytic potential of the L-16 vaccine strain of measles virus (MV) against primary human GBM cells and characterized the genetic patterns that determine the sensitivity of primary human GBM cells to oncolytic therapy. MV replicated in all GBM cells, and seven out of eight cell lines underwent complete or partial oncolysis. RNA-Seq analysis identified about 1200 differentially expressed genes (FDR < 0.05) with at least two-fold expression level change between MV-infected and uninfected cells. Among them, the most significant upregulation was observed for interferon response, apoptosis and cytokine signaling. One out of eight GBM cell lines was defective in type I interferon production and, thus, in the post-interferon response, other cells lacked expression of different cellular defense factors. Thus, none of the cell lines displayed induction of the total gene set necessary for effective inhibition of MV replication. In the resistant cells, we detected aberrant expression of metalloproteinase genes, particularly MMP3. Thus, such genes could be considered intriguing candidates for further study of factors responsible for cell sensitivity and resistance to L-16 MV infection.

Over the course of the year, temperate trees experience extremes in temperature and day length. In order to protect themselves from frost damage in winter, they enter a dormant state with no visible growth where all leaves are shed and buds are dormant. Also the young floral tissues need to withstand harsh winter conditions, as temperature fruit trees like apple develop their flower buds in the previous year of fruit development. So far, the genetic control of induction and release of dormancy is not fully understood. However, the transcription factor family of DORMANCY-Associated MADS-box (DAM) genes plays a major role in the control of winter dormancy. One of these genes is MdDAM4. This gene is expressed in the early phase of bud dormancy, but little is known about its function. Six transgenic apple lines were produced to study the function of MdDAM4 in apple. For plant transformation, the binary plasmid vector p9oN-35s-MdDAM4 was used that contains the coding sequence of MdDAM4 driven by the 35S promoter. Transgenicity of the lines was proven by PCR and southern hybridization. Based on siRNA sequencing and phenotypic observations, it was concluded that line M2024 overexpresses MdDAM4 whereas the gene is silenced in all other lines. Phenotyping of the transgenic lines provided evidence that the overexpression of MdDAM4 leads to an earlier induction and a later release of dormancy. Silencing this gene had exactly the opposite effects and thereby led to an increased duration of the vegetation period. Expression experiments revealed genes that were either potentially repressed or activated by MdDAM4. Among the potentially suppressed genes were several homologs of the cytokinin oxidase 5 (CKX5), five LOX homologs, and several expansins, which may indicate a link between MdDAM4 and the control of leaf senescence. Among the potentially activated genes is MdDAM1, which is in line with observed expression patterns during winter dormancy. MdDAM2, which shows little expression during endodormancy also appears to be activated by MdDAM4. Overall, this study provides experimental evidence with transgenic apple trees for MdDAM4 being an important regulator of the onset of bud dormancy in apple. [ABSTRACT FROM AUTHOR]

The electrocardiogram (ECG) signal produced by the human heart is an emerging biometric modality that can play an important role in the future generation’s identity recognition with the support of machine learning techniques. One of the major obstacles in the progress of this modality is the lack of public datasets with a long interval between sessions of data acquisition to verify the uniqueness and permanence of the biometric signature of the heart of a subject. To address this issue, we put forward Heartprint, a large biometric database of multisession ECG signals comprising 1539 records captured from the fingers of 199 healthy subjects. The capturing time for each record was 15 s, and recordings were made in resting and reading conditions. They were collected in multiple sessions over ten years, and the average interval between first session (S1) and third session (S3L) was 1572.2 days. The dataset also covers several demographic classes such as genders, ethnicities, and age groups. The combination of raw ECG signals and demographic information turns the Heartprint dataset, which is made publicly available online, into a valuable resource for the development and evaluation of biometric recognition algorithms.

In a quickly growing world, there is increasing demand for a secure food supply, a reduction in the intensive use of natural resources, and the enhancement of sustainability for future long-term maintenance. In this regard, plant health, including fruit and foliar diseases, which can cause a vast amount of crop loss, potentially has a huge effect on food security. The integration of new, innovative technological tools and data management techniques into the traditional agricultural practices is a promising approach to combat future food shortages. The use of the same principles of precision agriculture to “do the right thing, at the right time, in the right place” will allow for providing detailed, real-time information that will help farmers to protect their crops and choose healthier, as well as more productive, farming methods. The presented narrative review reports on several items of innovation, including monitoring and surveillance, diagnostic, and decision-making tools, with a specific focus devoted to digital solutions that can be applied in agriculture in order to improve the quality and the speed of the decision-making process and specifically, to set up a digital collaboration that can be crucial under certain circumstances to reach sustainability goals, particularly in the Near East and North Africa (NENA) Region, where an effective and rapid solution for phytosanitary control is needed.

Apple trees require a long exposure to chilling temperature during winter to acquire competency to flower and grow in the following spring. Climate change or adverse meteorological conditions can impair release of dormancy and delay bud break, hence jeopardizing fruit production and causing substantial economic losses. In order to characterize the molecular mechanisms controlling bud dormancy in apple we focused our work on the MADS-box transcription factor gene MdDAM1. We show that MdDAM1 silencing is required for the release of dormancy and bud break in spring. MdDAM1 transcript levels are drastically reduced in the low-chill varieties ‘Anna’ and ‘Dorsett Golden’ compared to ‘Golden Delicious’ corroborating its role as a key genetic factor controlling the release of bud dormancy in Malus species. The functional characterization of MdDAM1 using RNA silencing resulted in trees unable to cease growth in winter and that displayed an evergrowing, or evergreen, phenotype several years after transgenesis. These trees lost their capacity to enter in dormancy and produced leaves and shoots regardless of the season. A transcriptome study revealed that apple evergrowing lines are a genocopy of ‘Golden Delicious’ trees at the onset of the bud break with the significant gene repression of the related MADS-box gene MdDAM4 as a major feature. We provide the first functional evidence that MADS-box transcriptional factors are key regulators of bud dormancy in pome fruit trees and demonstrate that their silencing results in a defect of growth cessation in autumn. Our findings will help producing low-chill apple variants from the elite commercial cultivars that will withstand climate change.

The multi-label classification problem in Unmanned Aerial Vehicle (UAV) images is particularly challenging compared to single-label classification due to its combinatorial nature. To tackle this issue, we propose in this paper a deep learning approach based on encoder-decoder neural network architecture with channel and spatial attention mechanisms. Specifically, the encoder module which is based on a pre-trained convolutional neural network (CNN) has the task to transform the input image to a set of feature maps using an opportune feature combination. To improve the feature representation further, this module incorporates a squeeze excitation (SE) layer for modelling the interdependencies between the channels of the feature maps. The decoder module which is based on a long short terms memory (LSTM) network has the task of generating, in a sequential way, the classes present in the image. At each time step, it predicts the next class-label by aligning its hidden state to the corresponding region in the image by means of an adaptive spatial attention mechanism. The experiments carried out on two UAV datasets with a spatial resolution of 2-cm show that our method is promising in predicting the labels present in the image while attending the relevant objects in the image. Additionally, it is able to provide better classification results compared to state-of-the-art methods.