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Foot-and-mouth disease (FMD) is globally recognized as a highly economically devastating and prioritized viral disease affecting livestock. Vaccination remains a crucial preventive measure against FMD. The improvement of current vaccine platforms could help control outbreaks, leading to the potential eradication of the disease. In this review, we describe the variances in virulence and immune responses among FMD-susceptible host species, specifically bovines and pigs, highlighting the details of host–pathogen interactions and their impact on the severity of the disease. This knowledge serves as an important foundation for translating our insights into the rational design of vaccines and countermeasure strategies, including the use of interferon as a biotherapeutic agent. Ultimately, in this review, we aim to bridge the gap between our understanding of FMDV biology and the practical approaches to control and potentially eradicate FMD.

Cabbage (Brassica oleracea), a crop of major economic importance worldwide, is affected by numerous diseases, which are caused by a wide range of microorganisms, including fungi, oomycetes, bacteria, and viruses, which lead to important losses in yield and quality. The increasing availability of reference genomes of plant-associated microbes together with recent advances in metagenomic approaches provide new opportunities to identify microbes linked to distinct symptomatology in Brassica leaves. In this study, shotgun metagenomics was used to investigate the microbial community in leaves of B. oleracea plants from agricultural farmlands. Compared with conventional techniques based on culture-based methods, whole-genome shotgun sequencing allows the reliable identification of the microbial population inhabiting a plant tissue at the species level. Asymptomatic and symptomatic leaves showing different disease symptoms were examined. In the asymptomatic leaves, Xanthomonas species were the most abundant taxa. The relative abundance of bacterial and fungal communities varied depending on disease symptoms on the leaf. The microbiome of the leaves showing mild to severe levels of disease was enriched in bacterial populations (Sphingomonas, Methylobacterium, Paracoccus) and to a lesser degree in some fungal taxa, such as Alternaria and Colletotrichum (e.g., in leaves with high levels of necrotic lesions). Sclerotinia species were highly abundant in severely damaged leaves (S. sclerotium, S. trifolium, S. bolearis), followed by Botrytis species. The common and specific bacterial and fungal species associated to disease symptoms were identified. Finally, the analysis of the gene functions in the metagenomic data revealed enrichment in carbohydrate-active enzymes potentially involved in pathogenicity, whose distribution also varied among disease severity groups. Understanding the B. oleracea leaf microbiome in agricultural ecosystems will pave the way for the efficient management of diseases in this crop.

Multiple myeloma is a malignancy characterized by the accumulation of malignant plasma cells in bone marrow and the production of monoclonal immunoglobulin. A hallmark of cancer is the evasion of immune surveillance. Histone deacetylase inhibitors have been shown to promote the expression of silenced molecules and hold potential to increase the anti-MM efficacy of immunotherapy. The aim of the present work was to assess the potential effect of tinostamustine (EDO-S101), a first-in-class alkylating deacetylase inhibitor, in combination with daratumumab, an anti-CD38 monoclonal antibody (mAb), through different preclinical studies. Tinostamustine increases CD38 expression in myeloma cell lines, an effect that occurs in parallel with an increment in CD38 histone H3 acetylation levels. Also, the expression of MICA and MICB, ligands for the NK cell activating receptor NKG2D, augments after tinostamustine treatment in myeloma cell lines and primary myeloma cells. Pretreatment of myeloma cell lines with tinostamustine increased the sensitivity of these cells to daratumumab through its different cytotoxic mechanisms, and the combination of these two drugs showed a higher anti-myeloma effect than individual treatments in ex vivo cultures of myeloma patients’ samples. In vivo data confirmed that tinostamustine pretreatment followed by daratumumab administration significantly delayed tumor growth and improved the survival of mice compared to individual treatments. In summary, our results suggest that tinostamustine could be a potential candidate to improve the efficacy of anti-CD38 mAbs.

Hand pose recognition presents significant challenges that need to be addressed, such as varying lighting conditions or complex backgrounds, which can hinder accurate and robust hand pose estimation. This can be mitigated by employing MediaPipe to facilitate the efficient extraction of representative landmarks from static images combined with the use of Convolutional Neural Networks. Extracting these landmarks from the hands mitigates the impact of lighting variability or the presence of complex backgrounds. However, the variability of the location and size of the hand is still not addressed by this process. Therefore, the use of processing modules to normalize these points regarding the location of the wrist and the zoom of the hands can significantly mitigate the effects of these variabilities. In all the experiments performed in this work based on American Sign Language alphabet datasets of 870, 27,000, and 87,000 images, the application of the proposed normalizations has resulted in significant improvements in the model performance in a resource-limited scenario. Particularly, under conditions of high variability, applying both normalizations resulted in a performance increment of 45.08%, increasing the accuracy from 43.94 ± 0.64% to 89.02 ± 0.40%.

Several sign language datasets are available in the literature. Most of them are designed for sign language recognition and translation. This paper presents a new sign language dataset for automatic motion generation. This dataset includes phonemes for each sign (specified in HamNoSys, a transcription system developed at the University of Hamburg, Hamburg, Germany) and the corresponding motion information. The motion information includes sign videos and the sequence of extracted landmarks associated with relevant points of the skeleton (including face, arms, hands, and fingers). The dataset includes signs from three different subjects in three different positions, performing 754 signs including the entire alphabet, numbers from 0 to 100, numbers for hour specification, months, and weekdays, and the most frequent signs used in Spanish Sign Language (LSE). In total, there are 6786 videos and their corresponding phonemes (HamNoSys annotations). From each video, a sequence of landmarks was extracted using MediaPipe. The dataset allows training an automatic system for motion generation from sign language phonemes. This paper also presents preliminary results in motion generation from sign phonemes obtaining a Dynamic Time Warping distance per frame of 0.37.

This paper proposes, analyzes, and evaluates a deep learning architecture based on transformers for generating sign language motion from sign phonemes (represented using HamNoSys: a notation system developed at the University of Hamburg). The sign phonemes provide information about sign characteristics like hand configuration, localization, or movements. The use of sign phonemes is crucial for generating sign motion with a high level of details (including finger extensions and flexions). The transformer-based approach also includes a stop detection module for predicting the end of the generation process. Both aspects, motion generation and stop detection, are evaluated in detail. For motion generation, the dynamic time warping distance is used to compute the similarity between two landmarks sequences (ground truth and generated). The stop detection module is evaluated considering detection accuracy and ROC (receiver operating characteristic) curves. The paper proposes and evaluates several strategies to obtain the system configuration with the best performance. These strategies include different padding strategies, interpolation approaches, and data augmentation techniques. The best configuration of a fully automatic system obtains an average DTW distance per frame of 0.1057 and an area under the ROC curve (AUC) higher than 0.94.

Rice is one of the most important crops in the world, and its production is severely affected by the rice blast disease caused by the fungus Magnaporthe oryzae. Several major blast resistance genes and QTLs associated with blast resistance have been described and mostly identified in indica rice varieties. In this work, we report the obtention of a blast-resistant rice breeding line derived from crosses between the resistant indica variety CT13432 and the japonica elite cultivar JSendra (highly susceptible to blast). The breeding line, named COPSEMAR9, was found to exhibit resistance to leaf blast and panicle blast, as demonstrated by disease assays under controlled and field conditions. Furthermore, a high-quality genome sequence of the blast-resistant breeding line was obtained using a strategy that combines short-read sequencing (Illumina sequencing) and long-read sequencing (Pacbio sequencing). The use of a whole-genome approach allowed the fine mapping of DNA regions of indica and japonica origin present in the COPSEMAR9 genome and the identification of parental gene regions potentially contributing to blast resistance in the breeding line. Rice blast resistance genes (including Pi33 derived from the resistant parent) and defense-related genes in the genome of COPSEMAR9 were identified. Whole-genome analyses also revealed the presence of microRNAs (miRNAs) with a known function in the rice response to M. oryzae infection in COPSEMAR9, which might also contribute to its phenotype of blast resistance. From this study, the genomic information and analysis methods provide valuable knowledge that will be useful in breeding programs for blast resistance in japonica rice cultivars.

Kidney transplantation is the preferred therapeutic option for end-stage renal disease; however, the alloimmune response is still the leading cause of renal allograft failure. To better identify immunologic disparities in order to evaluate HLA compatibility between the donor and the recipient, the concept of eplet load has arisen. Regular kidney function monitoring is essential for the accurate and timely diagnosis of allograft rejection and the appropriate treatment. Donor-derived cell-free DNA (dd-cfDNA) has been proposed as a potential biomarker of acute rejection and graft failure in kidney transplantation. The proportion of plasma dd-cfDNA was determined in forty-two kidney patients at 1 month after transplantation. A total of eleven (26.2%) patients had a dd-cfDNA proportion of ≥1.0%. The only pretransplant variable related to dd-cfDNA > 1.0% was the HLA class II eplet mismatch load, mainly the HLA-DQB1 eplet mismatch load. Furthermore, dd-cfDNA was able to discriminate the patients with antibody-mediated rejection (AbMR) (AUC 87.3%), acute rejection (AUC 78.2%), and troubled graft (AUC 81.4%). Increased dd-cfDNA levels were associated with kidney allograft deterioration, particularly rejection, as well as a greater HLA class II eplet mismatch load. Consequently, combining dd-cfDNA determination and HLA eplet mismatch load calculation should improve the assessment of the risk of short- and long-term allograft damage.

The development of de novo donor-specific antibodies is related to the poor matching of the human leukocyte antigen (HLA) between donor and recipient, which leads to dismal clinical outcomes and graft loss. However, new approaches that stratify the risks of long-term graft failure in solid organ transplantation have emerged, changing the paradigm of HLA compatibility. In addition, advances in software development have given rise to a new structurally based algorithm known as HLA Matchmaker, which determines compatibility at the epitope rather than the antigen level. Although this technique still has limitations, plenty of research maintains that this assessment represents a more complete and detailed definition of HLA compatibility. This review summarizes recent aspects of eplet mismatches, highlighting the most recent advances and future research directions.

Long COVID (LC) syndrome is a complex multiorgan symptom that persists beyond >12 weeks after SARS-CoV-2 infection. The most frequently associated symptom is fatigue. Physical activity and exercise are recommended, although specific studies are lacking. The objectives of the present work are to analyze the impact of a supervised exercise program on the clinical evolution of LC with fatigue patients and to identify whether certain circulating biomarkers could predict the response to rehabilitation. The rehabilitation treatment response was analyzed in 14 women diagnosed with LC and fatigue, based on the changes in the 6 min walk test and Borg/Fatigue Impact scales. Patients who showed improvement in the meters walked were considered “responders” to the therapy. A total of 65% of patients responded to the exercise program, with an improvement in the meters walked and in oxygen saturation, with stability in the percentage of meters walked. Participants with obesity and those double-vaccinated against SARS-CoV-2 presented a lower degree of fatigue. LC patients presented a favorable response to a supervised exercise program. Differences in creatinine and protein levels were observed between rehabilitation therapy “responders” and “nonresponders”. A good state of protein nutrition was related to a better rehabilitation response. The results are promising regarding possible predictive biomarkers of rehabilitation response, such as creatinine.

Sensor- orientation is a critical aspect in a Human Activity Recognition (HAR) system based on tri-axial signals (such as accelerations); different sensors orientations introduce important errors in the activity recognition process. This paper proposes a new preprocessing module to reduce the negative impact of sensor-orientation variability in HAR. Firstly, this module estimates a consistent reference system; then, the tri-axial signals recorded from sensors with different orientations are transformed into this consistent reference system. This new preprocessing has been evaluated to mitigate the effect of different sensor orientations on the classification accuracy in several state-of-the-art HAR systems. The experiments were carried out using a subject-wise cross-validation methodology over six different datasets, including movements and postures. This new preprocessing module provided robust HAR performance even when sudden sensor orientation changes were included during data collection in the six different datasets. As an example, for the WISDM dataset, sensors with different orientations provoked a significant reduction in the classification accuracy of the state-of-the-art system (from 91.57 ± 0.23% to 89.19 ± 0.26%). This important reduction was recovered with the proposed algorithm, increasing the accuracy to 91.46 ± 0.30%, i.e., the same result obtained when all sensors had the same orientation.

Foot-and-mouth disease (FMD), caused by the FMD virus (FMDV), is a highly contagious disease of cloven-hoofed livestock that can have severe economic impacts. Control and prevention strategies, including the development of improved vaccines, are urgently needed to effectively control FMD outbreaks in endemic settings. Previously, we employed two distinct strategies (codon pair bias deoptimization (CPD) and codon bias deoptimization (CD)) to deoptimize various regions of the FMDV serotype A subtype A12 genome, which resulted in the development of an attenuated virus in vitro and in vivo, inducing varying levels of humoral responses. In the current study, we examined the versatility of the system by using CPD applied to the P1 capsid coding region of FMDV serotype A subtype, A24, and another serotype, Asia1. Viruses carrying recoded P1 (A24-P1Deopt or Asia1-P1Deopt) exhibited different degrees of attenuation (i.e., delayed viral growth kinetics and replication) in cultured cells. Studies in vivo using a mouse model of FMD demonstrated that inoculation with the A24-P1Deopt and Asia1-P1Deopt strains elicited a strong humoral immune response capable of offering protection against challenge with homologous wildtype (WT) viruses. However, different results were obtained in pigs. While clear attenuation was detected for both the A24-P1Deopt and Asia1-P1Deopt strains, only a limited induction of adaptive immunity and protection against challenge was detected, depending on the inoculated dose and serotype deoptimized. Our work demonstrates that while CPD of the P1 coding region attenuates viral strains of multiple FMDV serotypes/subtypes, a thorough assessment of virulence and induction of adaptive immunity in the natural host is required in each case in order to finely adjust the degree of deoptimization required for attenuation without affecting the induction of protective adaptive immune responses.

Entry into quiescence in the fission yeast Schizosaccharomyces pombe is induced by nitrogen starvation. In the absence of nitrogen, proliferating fission yeast cells divide twice without cell growth and undergo cell cycle arrest in G1 before becoming G0 quiescent cells. Under these conditions, autophagy is induced to produce enough nitrogen for the two successive cell divisions that take place before the G1 arrest. In parallel to the induction of autophagy, the Greatwall–Endosulfine switch is activated upon nitrogen starvation to down-regulate protein phosphatase PP2A/B55 activity, which is essential for cell cycle arrest in G1 and implementation of the quiescent program. Here we show that, although inactivation of PP2A/B55 by the Greatwall–Endosulfine switch is not required to promote autophagy initiation, it increases autophagic flux at least in part by upregulating the expression of a number of autophagy-related genes.

African Swine Fever Virus (ASFV) is the causative agent of a highly contagious and lethal vector-borne disease in suids. Recently, a live attenuated virus strain, developed using the currently circulating, virulent Georgia strain (ASFV-G) with a single gene deletion (ASFV-G-ΔI177L), resulted in an effective vaccine. Nevertheless, protective immune response mechanisms induced by this candidate are poorly understood. In this study, Yorkshire crossbred swine intramuscularly vaccinated with 106 50% hemadsorption dose (HAD50) of ASFV-G-ΔI177L or a vehicle control were challenged at 28 days post-inoculation (dpi) with 102 HAD50 of ASFV-G. Analysis of purified peripheral blood mononuclear cells following inoculation and challenge revealed that CD4+, CD8+ and CD4+CD8+ central memory T cells (CD44+CD25−CD27−CD62L+CCR7+, Tcm) decreased significantly by 28 dpi in ASFV-G-ΔI177L-vaccinated swine compared to baseline and time-matched controls. Conversely, CD4+, CD8+ and CD4+CD8+ effector memory T cells (CD44+CD25−CD27−CD62−CCR7−, Tem) increased significantly among ASFV-G-ΔI177L-vaccined swine by 28 dpi compared to baseline and time-matched controls. Additionally, the percentage of natural killer (NK), CD4+ and CD4+CD8+ Tem and CD8+ Tcm and Tem positive for IFNγ increased significantly following inoculation, surpassing that of controls by 28 dpi or earlier. These results suggest that NK and memory T cells play a role in protective immunity and suggest that studying these cell populations may be a surrogate immunity marker in ASF vaccination.

Ovarian cancer (OC) is the most lethal gynecological malignancy; therefore, more effective treatments are urgently needed. We recently reported that chloroquine (CQ) increased reactive oxygen species (ROS) in OC cell lines (OCCLs), causing DNA double-strand breaks (DSBs). Here, we analyzed whether these lesions are repaired by nonhomologous end joining (NHEJ), one of the main pathways involved in DSB repair, and if the combination of CQ with NHEJ inhibitors (NHEJi) could be effective against OC. We found that NHEJ inhibition increased the persistence of γH2AX foci after CQ-induced DNA damage, revealing an essential role of this pathway in the repair of the lesions. NHEJi decreased the proliferation of OCCLs and a strong in vitro synergistic effect on apoptosis induction was observed when combined with CQ. This effect was largely abolished by the antioxidant N-Acetyl-L-cysteine, revealing the critical role of ROS and DSB generation in CQ/NHEJi-induced lethality. We also found that the NHEJ efficiency in OCCLs was not affected by treatment with Panobinostat, a pan-histone deacetylase inhibitor that also synergizes with CQ in OCCLs by impairing homologous recombination. Accordingly, the triple combination of CQ-NHEJi-Panobinostat exerted a stronger in vitro synergistic effect. Altogether, our data suggest that the combination of these drugs could represent new therapeutic strategies against OC.

Under experimental conditions, pigs infected with Ebola Virus (EBOV) develop disease and can readily transmit the virus to non-human primates or pigs. In the event of accidental or intentional EBOV infection of domestic pigs, complex and time-consuming safe depopulation and carcass disposal are expected. Delaying or preventing transmission through a reduction in viral shedding is an absolute necessity to limit the spread of the virus. In this study, we tested whether porcine interferon-α or λ3 (porIFNα or porIFNλ3) delivered by a replication-defective human type 5 adenovirus vector (Ad5-porIFNα or Ad5-porIFNλ3) could limit EBOV replication and shedding in domestic pigs. Our results show that pigs pre-treated with Ad5-porIFNα did not develop measurable clinical signs, did not shed virus RNA, and displayed strongly reduced viral RNA load in tissues. A microarray analysis of peripheral blood mononuclear cells indicated that Ad5-porIFNα treatment led to clear upregulation in immune and inflammatory responses probably involved in protection against disease. Our results indicate that administration of Ad5-porIFNα can potentially be used to limit the spread of EBOV in pigs.

Nursing home residents (NHR) have been targeted as a vaccination priority due to their higher risk of worse outcome after COVID-19 infection. The mRNA-based vaccine BTN2b2 was first approved in Europe for NHRs. The assessment of the specific vaccine immune response (both humoral and cellular) at long term in NHRs has not been addressed yet. A representative sample of 624 NHR subjects in Northern region of Spain was studied to assess immune response against full vaccination with BTN2b2. The anti-S1 antibody levels and specific T cells were measured at two and six months after vaccination. 24.4% of NHR had a previous infection prior to vaccination. The remaining NHR were included in the full vaccination assessment group (FVA). After two months, a 94.9% of the FVA presented anti-S1 antibodies, whereas those seronegative without specific cellular response were 2.54%. At long-term, the frequency of NHR within the FVA group with anti-S1 antibodies at six months were 88.12% and the seronegative subjects without specific cellular response was 8.07%. The cellular immune assays complement the humoral test in the immune vaccine response assessment. Therefore, the cellular immune assessment in NHRs allows for the fine tuning of those seronegative subjects with potential competent immune responses against the vaccine.

The Y Balance Test (YBT) is a dynamic balance assessment typically used in sports medicine. This work proposes a deep learning approach to automatically score this YBT by estimating the normalized reach distance (NRD) using a wearable sensor to register inertial signals during the movement. This paper evaluates several signal processing techniques to extract relevant information to feed the deep neural network. This evaluation was performed using a state-of-the-art human activity recognition system based on recurrent neural networks (RNNs). This deep neural network includes long short-term memory (LSTM) layers to learn features from time series by modeling temporal patterns and an additional fully connected layer to estimate the NRD (normalized by the leg length). All analyses were carried out using a dataset with YBT assessments from 407 subjects, including young and middle-aged volunteers and athletes from different sports. This dataset allowed developing a global and robust solution for scoring the YBT in a wide range of applications. The experimentation setup considered a 10-fold subject-wise cross-validation using training, validation, and testing subsets. The mean absolute percentage error (MAPE) obtained was 7.88 ± 0.20%. Moreover, this work proposes specific regression systems to estimate the NRD for each direction separately, obtaining an average MAPE of 7.33 ± 0.26%. This deep learning approach was compared to a previous work using dynamic time warping and k-NN algorithms, obtaining a relative MAPE reduction of 10%.

Meiotic defects derived from incorrect DNA repair during gametogenesis can lead to mutations, aneuploidies and infertility. The coordinated resolution of meiotic recombination intermediates is required for crossover formation, ultimately necessary for the accurate completion of both rounds of chromosome segregation. Numerous master kinases orchestrate the correct assembly and activity of the repair machinery. Although much less is known, the reversal of phosphorylation events in meiosis must also be key to coordinate the timing and functionality of repair enzymes. Cdc14 is a crucial phosphatase required for the dephosphorylation of multiple CDK1 targets in many eukaryotes. Mutations that inactivate this phosphatase lead to meiotic failure, but until now it was unknown if Cdc14 plays a direct role in meiotic recombination. Here, we show that the elimination of Cdc14 leads to severe defects in the processing and resolution of recombination intermediates, causing a drastic depletion in crossovers when other repair pathways are compromised. We also show that Cdc14 is required for the correct activity and localization of the Holliday Junction resolvase Yen1/GEN1. We reveal that Cdc14 regulates Yen1 activity from meiosis I onwards, and this function is essential for crossover resolution in the absence of other repair pathways. We also demonstrate that Cdc14 and Yen1 are required to safeguard sister chromatid segregation during the second meiotic division, a late action that is independent of the earlier role in crossover formation. Thus, this work uncovers previously undescribed functions of the evolutionary conserved Cdc14 phosphatase in the regulation of meiotic recombination.

During meiosis, the budding yeast polo-like kinase Cdc5 is a crucial driver of the prophase I to meiosis I (G2/M) transition. The meiotic recombination checkpoint restrains cell cycle progression in response to defective recombination to ensure proper distribution of intact chromosomes to the gametes. This checkpoint detects unrepaired DSBs and initiates a signaling cascade that ultimately inhibits Ndt80, a transcription factor required for CDC5 gene expression. Previous work revealed that overexpression of CDC5 partially alleviates the checkpoint-imposed meiotic delay in the synaptonemal complex-defective zip1Δ mutant. Here, we show that overproduction of a Cdc5 version (Cdc5-ΔN70), lacking the N-terminal region required for targeted degradation of the protein by the APC/C complex, fails to relieve the zip1Δ-induced meiotic delay, despite being more stable and reaching increased protein levels. However, precise mutation of the consensus motifs for APC/C recognition (D-boxes and KEN) has no effect on Cdc5 stability or function during meiosis. Compared to the zip1Δ single mutant, the zip1Δ cdc5-ΔN70 double mutant exhibits an exacerbated meiotic block and reduced levels of Ndt80 consistent with persistent checkpoint activity. Finally, using a CDC5-inducible system, we demonstrate that the N-terminal region of Cdc5 is essential for its checkpoint erasing function. Thus, our results unveil an additional layer of regulation of polo-like kinase function in meiotic cell cycle control.

Rice is a staple food for more than half of the global population. Rice production is, however, severely affected by biotic and abiotic stresses. Fertilisers and pesticides are widely used in rice farming to maintain optimal yield and to prevent losses caused by environmental stress. However, the indiscriminate use of agrochemicals has adverse effects on the environment and human health. Stress caused by nutrient excess or deficiency has an impact on plant disease resistance. The interference of plant responses induced by nutrient stress can result in a positive or negative impact on resistance to pathogen infection. In this review, we explore the effects of combined stresses in rice, focusing on nutrient stress, such as nitrogen and phosphorous supply, and infection by fungal pathogen Magnaporthe oryzae, the causal agent of rice blast disease. Crosstalk between nutrient stress-induced and pathogen-induced signalling pathways in rice is discussed, as well, with particular emphasis on regulatory microRNAs. Understanding the interconnected regulations between nutrient stress and disease resistance will lay a foundation for rationally optimising fertiliser and pesticide use in rice production.

Vaccine efficacy is based on clinical data. Currently, the assessment of immune response after SARS-CoV-2 vaccination is scarce. A total of 52 healthcare workers were immunized with the same lot of BNT162b2 vaccine. The immunological response against the vaccine was tested using a T-specific assay based on the expression of CD25 and CD134 after stimulation with anti-N, -S, and -M specific peptides of SARS-CoV-2. Moreover, IgG anti-S2 and -RBD antibodies were detected using ELISA. Furthermore, the cell subsets involved in the response to the vaccine were measured in peripheral blood by flow cytometry. Humoral-specific responses against the vaccine were detected in 94% and 100% after the first and second doses, respectively. Therefore, anti-S T-specific responses were observed in 57% and 90% of the subjects after the first and second doses of the vaccine, respectively. Thirty days after the second dose, significant increases in T helper 1 memory cells (p < 0.001), peripheral memory T follicular helper (pTFH) cells (p < 0.032), and switched memory (p = 0.005) were observed. This study describes the specific humoral and cellular immune responses after vaccination with the new mRNA-based BNT162b2 vaccine. A mobilization of TFH into the circulation occurs, reflecting a specific activation of the immune system.

During the COVID-19 pandemic, many studies have been carried out to evaluate different immune system components to search for prognostic biomarkers of the disease. A broad multiparametric antibody panel of cellular and humoral components of the innate and the adaptative immune response in patients with active SARS-CoV-2 infection has been evaluated in this study. A total of 155 patients were studied at admission into our center and were categorized according to the requirement of oxygen therapy as mild or severe (the latter being those with the requirement). The patients with severe disease were older and had high ferritin, D-dimer, C-reactive protein, troponin, interleukin-6 (IL-6) levels, and neutrophilia with lymphopenia at admission. Moreover, the patients with mild symptoms had significantly increased circulating non-classical monocytes, innate lymphoid cells, and regulatory NK cells. In contrast, severe patients had a low frequency of Th1 and regulatory T cells with increased activated and exhausted CD8 phenotype (CD8+CD38+HLADR+ and CD8+CD27−CD28−, respectively). The predictive model included age, ferritin, D-dimer, lymph counts, C4, CD8+CD27−CD28−, and non-classical monocytes in the logistic regression analysis. The model predicted severity with an area under the curve of 78%. Both innate and adaptive immune parameters could be considered potential predictive biomarkers of the prognosis of COVID-19 disease.

Chronic hepatitis C infection (HCV) activates a systemic cell-mediated immune response characterized by the production of IFNγ and an innate immune response addressed by the activation of TLR signaling. We aimed to investigate whether HCV eradication by direct acting antivirals (DAA) leads to a recovery in cell-mediated immune response and TLR expression and functionality. Blood samples were obtained in HCV infected patients before DAA treatment and at week +48 after the end of treatment. Results were compared to healthy controls. Cell surface expression of TLR8 was assessed on peripheral blood mononuclear cells (PBMCs) by flow cytometry. Freshly isolated PBMCs were cultured with specific TLR8 agonists and intracellular production of cytokines was determined by flow-cytometry after ex vivo TLR8 activation with ssRNA 40. Production of IFNγ, IL2 and IL17 was assessed by flow cytometry in T cells after polyclonal activation. Included were 50 HCV-infected patients and 15 controls. TLR8 expression in PBMCs was significantly increased before treatment and recovered normal levels at week +48. Production of IL1b, IL6 and TNFα dependent on the activation of TLR8 in PBMCs was also increased in patients before DAA treatment, with a significant reduction at week +48. Combined expression of IFNγ and IL2 in CD4+ T cells in HCV-infected patients was significantly increased compared to controls and recovered normal levels at week +48. DAA-mediated clearance of HCV is associated with a decreased expression and activation of TLR8 in PBMCs until healthy control levels which is accompanied by a reduction in the Th1 response.

BH3-mimetics targeting anti-apoptotic proteins such as MCL-1 (S63845) or BCL-2 (venetoclax) are currently being evaluated as effective therapies for the treatment of multiple myeloma (MM). Interleukin 6, produced by mesenchymal stromal cells (MSCs), has been shown to modify the expression of anti-apoptotic proteins and their interaction with the pro-apoptotic BIM protein in MM cells. In this study, we assess the efficacy of S63845 and venetoclax in MM cells in direct co-culture with MSCs derived from MM patients (pMSCs) to identify additional mechanisms involved in the stroma-induced resistance to these agents. MicroRNAs miR-193b-3p and miR-21-5p emerged among the top deregulated miRNAs in myeloma cells when directly co-cultured with pMSCs, and we show their contribution to changes in MCL-1 and BCL-2 protein expression and in the activity of S63845 and venetoclax. Additionally, direct contact with pMSCs under S63845 and/or venetoclax treatment modifies myeloma cell dependence on different BCL-2 family anti-apoptotic proteins in relation to BIM, making myeloma cells more dependent on the non-targeted anti-apoptotic protein or BCL-XL. Finally, we show a potent effect of the combination of S63845 and venetoclax even in the presence of pMSCs, which supports this combinatorial approach for the treatment of MM.

Continuous in-home monitoring of Parkinson’s Disease (PD) symptoms might allow improvements in assessment of disease progression and treatment effects. As a first step towards this goal, we evaluate the feasibility of a wrist-worn wearable accelerometer system to detect PD tremor in the wild (uncontrolled scenarios). We evaluate the performance of several feature sets and classification algorithms for robust PD tremor detection in laboratory and wild settings. We report results for both laboratory data with accurate labels and wild data with weak labels. The best performance was obtained using a combination of a pre-processing module to extract information from the tremor spectrum (based on non-negative factorization) and a deep neural network for learning relevant features and detecting tremor segments. We show how the proposed method is able to predict patient self-report measures, and we propose a new metric for monitoring PD tremor (i.e., percentage of tremor over long periods of time), which may be easier to estimate the start and end time points of each tremor event while still providing clinically useful information.

Nocardia species, one of the most predominant Actinobacteria of the soil microbiota, cause infection in humans following traumatic inoculation or inhalation. The identification, typing, phylogenetic relationship and antimicrobial susceptibilities of 38 soil Nocardia strains from Lara State, Venezuela, were studied by 16S rRNA and gyrB (subunit B of topoisomerase II) genes, multilocus sequence analysis (MLSA), whole-genome sequencing (WGS), and microdilution. The results were compared with those for human strains. Just seven Nocardia species with one or two strains each, except for Nocardia cyriacigeorgica with 29, were identified. MLSA confirmed the species assignments made by 16S rRNA and gyrB analyses (89.5% and 71.0% respectively), and grouped each soil strain with its corresponding reference and clinical strains, except for 19 N. cyriacigeorgica strains found at five locations which grouped into a soil-only cluster. The soil strains of N. cyriacigeorgica showed fewer gyrB haplotypes than the examined human strains (13 vs. 17) but did show a larger number of gyrB SNPs (212 vs. 77). Their susceptibilities to antimicrobials were similar except for beta-lactams, fluoroquinolones, minocycline, and clarithromycin, with the soil strains more susceptible to the first three (p ≤ 0.05). WGS was performed on four strains belonging to the soil-only cluster and on two outside it, and the results compared with public N. cyriacigeorgica genomes. The average nucleotide/amino acid identity, in silico genome-to-genome hybridization similarity, and the difference in the genomic GC content, suggest that some strains of the soil-only cluster may belong to a novel subspecies or even a new species (proposed name Nocardia venezuelensis).

Immunosuppression withdrawal after graft failure seems to favor sensitization. A high percentage of calculated panel-reactive antibody (cPRA) and the development of de novo donor specific antibodies (dnDSA) indicate human leukocyte antigen (HLA) sensitization and may hinder the option of retransplantation. There are no established protocols on the immunosuppressive treatment that should be maintained after transplant failure. A retrospective analysis including 77 patients who lost their first renal graft between 1 January 2006–31 December 2015 was performed. Two sera were selected per patient, one immediately prior to graft loss and another one after graft failure. cPRA was calculated by Single Antigen in all patients. It was possible to analyze the development of dnDSA in 73 patients. By multivariate logistic regression analysis, the absence of calcineurin inhibitor (CNI) at 6 months after graft failure was related to cPRA > 75% (OR 4.8, CI 95% 1.5–15.0, p = 0.006). The absence of calcineurin inhibitor (CNI) at 6 months after graft loss was significantly associated with dnDSA development (OR 23.2, CI 95% 5.3–100.6, p < 0.001). Our results suggest that the absence of CNI at the sixth month after graft loss is a risk factor for sensitization. Therefore, maintenance of an immunosuppressive regimen based on CNI after transplant failure should be considered when a new transplant is planned, since it seems to prevent HLA allosensitization.

Automatic irrigation scheduling systems are highly demanded in the agricultural sector due to their ability to both save water and manage deficit irrigation strategies. Elaborating a functional and efficient automatic irrigation system is a very complex task due to the high number of factors that the technician considers when managing irrigation in an optimal way. Automatic learning systems propose an alternative to traditional irrigation management by means of the automatic elaboration of predictions based on the learning of an agronomist (DSS). The aim of this paper is the study of several learning techniques in order to determine the goodness and error relative to expert decision. Nine orchards were tested during 2018 using linear regression (LR), random forest regression (RFR), and support vector regression (SVR) methods as engines of the irrigation decision support system (IDSS) proposed. The results obtained by the learning methods in three of these orchards have been compared with the decisions made by the agronomist over an entire year. The prediction model errors determined the best fitting regression model. The results obtained lead to the conclusion that these methods are valid engines to develop automatic irrigation scheduling systems.

Antibody-mediated rejection (AbMR) is one of the leading causes of graft loss in kidney transplantation and B cells play an important role in the development of it. A B-cell activating factor (BAFF) is a cytokine involved in B cell ontogeny. Here, we analyzed whether B cell maturation and the effect of B cell soluble factors, such as BAFF could be involved in AbMR. Serum BAFF levels and B and T cell subpopulations were analyzed 109 kidney transplant patients before transplantation and at 6 and 12 months after kidney transplantation. Pretransplant serum BAFF levels as well as memory B cell subpopulations were significantly higher in those patients who suffered clinical AbMR during the first 12 months after kidney transplantation. Similar results were observed in the prospective analysis of patients with subclinical antibody-mediated rejection detected in the surveillance biopsy performed at 12 months after kidney transplantation. A multivariate analysis confirmed the independent role of BAFF in the development of AbMR, irrespective of other classical variables. Pretransplant serum BAFF levels could be an important non-invasive biomarker for the prediction of the development of AbMR and posttransplant increased serum BAFF levels contribute to AbMR.

B-cells have been long accepted as the main cellular component in humoral responses. Their effector function is based on antibody and cytokine production. The development of donor-specific antibodies by B-cells has deleterious consequences in graft and patients survival. Recently, a new subset of IL-10-secreting B-cells with regulatory capacity in allergic and autoimmune diseases has been shown. Such regulatory function changes the apprehension of B-cells as effector cells and increases the complexity to the immuno-regulatory networks. New therapies targeting B-cells should consider that depleting B-cells potentially impairs regulatory B-cells (Bregs) and that modulating or favoring the maintenance and function of Bregs would be important for the achievement of humoral tolerance. Unfortunately, few direct pieces of evidence of Breg involvement in allograft tolerance models has been described. Here, we summarize the current knowledge of the role of Bregs in transplantation.

This paper presents an in-situ storage topology for ultra-high-speed burst mode imagers, enabling low noise operation while keeping a high frame depth. The proposed pixel architecture contains a 4T pinned photodiode, a correlated double sampling (CDS) amplification stage, and an in-situ memory bank. Focusing on the sampling noise, the system level trade-off of the proposed pixel architecture is discussed, showing its advantages on the noise, power, and scaling capability. Integrated with an AC coupling CDS stage, the amplification is obtained by exploiting the strong capacitance to the voltage relation of a single NMOS transistor. A comprehensive noise model is developed for optimizing the trade-off between the area and noise. As a proof-of-concept, a prototype imager with a 30 µm pixel pitch was fabricated in a CMOS 130 nm technology. A 108-cell memory bank is implemented allowing dense layout and parallel readout. Two types of CDS amplification stages were investigated. Despite the limited memory capacitance of 10 fF/cell, the photon transfer curves of both pixel types were measured over different operation speeds up to 20 Mfps showing a noise performance of 8.4 e−.

Current evidence suggests that gut dysbiosis drives obesity and non-alcoholic fatty liver disease (NAFLD) pathogenesis. Toll-like receptor 2 (TLR2) and TLR6 specifically recognize components of Gram-positive bacteria. Despite the potential implications of TLR2 in NAFLD pathogenesis, the role of TLR6 has not been addressed. Our aim is to study a potential role of TLR6 in obesity-related NAFLD. Forty morbidly obese patients undergoing bariatric surgery were prospectively studied. Cell surface expression of TLR2 and TLR6 was assessed on peripheral blood mononuclear cells (PBMCs) by flow cytometry. Freshly isolated monocytes were cultured with specific TLR2/TLR6 agonists and intracellular production of cytokines was determined by flow-cytometry. In liver biopsies, the expression of TLR2 and TLR6 was analyzed by immunohistochemistry and cytokine gene expression using RT-qPCR. TLR6 expression in PBMCs from non-alcoholic steatohepatitis (NASH) patients was significantly higher when compared to those from simple steatosis. The production of pro-inflammatory cytokines in response to TLR2/TLR6 stimulation was also significantly higher in patients with lobular inflammation. Hepatocyte expression of TLR6 but not that of TLR2 was increased in NAFLD patients compared to normal liver histology. Deregulated expression and activity of peripheral TLR6 in morbidly obese patients can mirror the liver inflammatory events that are well known drivers of obesity-related NASH pathogenesis. Moreover, TLR6 is also significantly overexpressed in the hepatocytes of NAFLD patients compared to their normal counterparts. Thus, deregulated TLR6 expression may potentiate TLR2-mediated liver inflammation in NAFLD pathogenesis, and also serve as a potential peripheral biomarker of obesity-related NASH.

When developing a fully automatic system for evaluating motor activities performed by a person, it is necessary to segment and recognize the different activities in order to focus the analysis. This process must be carried out by a Human Activity Recognition (HAR) system. This paper proposes a user adaptation technique for improving a HAR system based on Hidden Markov Models (HMMs). This system segments and recognizes six different physical activities (walking, walking upstairs, walking downstairs, sitting, standing and lying down) using inertial signals from a smartphone. The system is composed of a feature extractor for obtaining the most relevant characteristics from the inertial signals, a module for training the six HMMs (one per activity), and the last module for segmenting new activity sequences using these models. The user adaptation technique consists of a Maximum A Posteriori (MAP) approach that adapts the activity HMMs to the user, using some activity examples from this specific user. The main results on a public dataset have reported a significant relative error rate reduction of more than 30%. In conclusion, adapting a HAR system to the user who is performing the physical activities provides significant improvement in the system’s performance.