Stimulation of shoot regeneration through leaf thin cell layer culture of Passiflora edulis Sims.

Passiflora edulis Sims. belonged to the genus Passiflora, is one of the important economic crops of the world as well as Vietnam. Nowadays, the commercial P. edulis is mainly propagated by seeds, cuttings and grafting; however, these methods still have some limitations such as genetic degradation and heterogeneity and the spread of pathogenic viruses. Micro-propagation has been used for clonal breeding and disease-free plant breeding, as well as providing a source of materials for Passiflora breeding. In this study, leaf explants of P. edulis Sims. (2.0-month-old) excised from the in vitro culture of ex vitro axillary buds cut longitudinally and transversally into thin cell layers (lTCL and tTCL) were used as plant materials to evaluate the shoot regeneration. In addition, the effects of explant age and lighting condition on shoot regeneration were also investigated. After 8 weeks of culture, the results showed that shoot regeneration rate (100%) and shoot multiplication coefficient (13.33) of the in vitro leaf-tTCL-4 were higher than those of other treatments and control. The shoot regeneration rate of P. edulis Sims. also varied with the change of explant age. The highest shoot regeneration rate (100%) was obtained from leaf explants of 1.5-month-old shoots after 8 weeks of culture. Moreover, the light (fluorescent lamps with photoperiod of 16 hours/day and lighting intensity of 40 - 45 μmol.m-2.s-1) improved not only morphogenesis rate, but also shoot regeneration rate (100%) of leaf explants after 8 weeks of culture. This study provided a novel method for rapid micro-propagation of P. edulis Sims

From Selective Deep Convolutional Features to Compact Binary Representations for Image Retrieval

In the large-scale image retrieval task, the two most important requirements are the discriminability of image representations and the efficiency in computation and storage of representations. Regarding the former requirement, Convolutional Neural Network is proven to be a very powerful tool to extract highly discriminative local descriptors for effective image search. Additionally, to further improve the discriminative power of the descriptors, recent works adopt fine-tuned strategies. In this article, taking a different approach, we propose a novel, computationally efficient, and competitive framework. Specifically, we first propose various strategies to compute masks, namely, SIFT-masks , SUM-mask , and MAX-mask , to select a representative subset of local convolutional features and eliminate redundant features. Our in-depth analyses demonstrate that proposed masking schemes are effective to address the burstiness drawback and improve retrieval accuracy. Second, we propose to employ recent embedding and aggregating methods that can significantly boost the feature discriminability. Regarding the computation and storage efficiency, we include a hashing module to produce very compact binary image representations. Extensive experiments on six image retrieval benchmarks demonstrate that our proposed framework achieves the state-of-the-art retrieval performances. </jats:p

The Virome of Acute Respiratory Diseases in Individuals at Risk of Zoonotic Infections

The ongoing coronavirus disease 2019 (COVID-19) pandemic emphasizes the need to actively study the virome of unexplained respiratory diseases. We performed viral metagenomic next-generation sequencing (mNGS) analysis of 91 nasal-throat swabs from individuals working with animals and with acute respiratory diseases. Fifteen virus RT-PCR-positive samples were included as controls, while the other 76 samples were RT-PCR negative for a wide panel of respiratory pathogens. Eukaryotic viruses detected by mNGS were then screened by PCR (using primers based on mNGS-derived contigs) in all samples to compare viral detection by mNGS versus PCR and assess the utility of mNGS in routine diagnostics. mNGS identified expected human rhinoviruses, enteroviruses, influenza A virus, coronavirus OC43, and respiratory syncytial virus (RSV) A in 13 of 15 (86.7%) positive control samples. Additionally, rotavirus, torque teno virus, human papillomavirus, human betaherpesvirus 7, cyclovirus, vientovirus, gemycircularvirus, and statovirus were identified through mNGS. Notably, complete genomes of novel cyclovirus, gemycircularvirus, and statovirus were genetically characterized. Using PCR screening, the novel cyclovirus was additionally detected in 5 and the novel gemycircularvirus in 12 of the remaining samples included for mNGS analysis. Our studies therefore provide pioneering data of the virome of acute-respiratory diseases from individuals at risk of zoonotic infections. The mNGS protocol/pipeline applied here is sensitive for the detection of a variety of viruses, including novel ones. More frequent detections of the novel viruses by PCR than by mNGS on the same samples suggests that PCR remains the most sensitive diagnostic test for viruses whose genomes are known. The detection of novel viruses expands our understanding of the respiratory virome of animal-exposed humans and warrant further studies

The Virome of Acute Respiratory Diseases in Individuals at Risk of Zoonotic Infections

The ongoing coronavirus disease 2019 (COVID-19) pandemic emphasizes the need to actively study the virome of unexplained respiratory diseases. We performed viral metagenomic next-generation sequencing (mNGS) analysis of 91 nasal-throat swabs from individuals working with animals and with acute respiratory diseases. Fifteen virus RT-PCR-positive samples were included as controls, while the other 76 samples were RT-PCR negative for a wide panel of respiratory pathogens. Eukaryotic viruses detected by mNGS were then screened by PCR (using primers based on mNGS-derived contigs) in all samples to compare viral detection by mNGS versus PCR and assess the utility of mNGS in routine diagnostics. mNGS identified expected human rhinoviruses, enteroviruses, influenza A virus, coronavirus OC43, and respiratory syncytial virus (RSV) A in 13 of 15 (86.7%) positive control samples. Additionally, rotavirus, torque teno virus, human papillomavirus, human betaherpesvirus 7, cyclovirus, vientovirus, gemycircularvirus, and statovirus were identified through mNGS. Notably, complete genomes of novel cyclovirus, gemycircularvirus, and statovirus were genetically characterized. Using PCR screening, the novel cyclovirus was additionally detected in 5 and the novel gemycircularvirus in 12 of the remaining samples included for mNGS analysis. Our studies therefore provide pioneering data of the virome of acute-respiratory diseases from individuals at risk of zoonotic infections. The mNGS protocol/pipeline applied here is sensitive for the detection of a variety of viruses, including novel ones. More frequent detections of the novel viruses by PCR than by mNGS on the same samples suggests that PCR remains the most sensitive diagnostic test for viruses whose genomes are known. The detection of novel viruses expands our understanding of the respiratory virome of animal-exposed humans and warrant further studies.Peer reviewe

Viral Metagenomic Analysis of Cerebrospinal Fluid from Patients with Acute Central Nervous System Infections of Unknown Origin, Vietnam.

Central nervous system (CNS) infection is a serious neurologic condition, although the etiology remains unknown in >50% of patients. We used metagenomic next-generation sequencing to detect viruses in 204 cerebrospinal fluid (CSF) samples from patients with acute CNS infection who were enrolled from Vietnam hospitals during 2012-2016. We detected 8 viral species in 107/204 (52.4%) of CSF samples. After virus-specific PCR confirmation, the detection rate was lowered to 30/204 (14.7%). Enteroviruses were the most common viruses detected (n = 23), followed by hepatitis B virus (3), HIV (2), molluscum contagiosum virus (1), and gemycircularvirus (1). Analysis of enterovirus sequences revealed the predominance of echovirus 30 (9). Phylogenetically, the echovirus 30 strains belonged to genogroup V and VIIb. Our results expanded knowledge about the clinical burden of enterovirus in Vietnam and underscore the challenges of identifying a plausible viral pathogen in CSF of patients with CNS infections

Evaluation of the Luminex xTAG Respiratory Viral Panel FAST v2 assay for detection of multiple respiratory viral pathogens in nasal and throat swabs in Vietnam.

BACKGROUND: Acute respiratory infections (ARI) are among the leading causes of hospitalization in children ≤5 years old. Rapid diagnostics of viral pathogens is essential to avoid unnecessary antibiotic treatment, thereby slowing down antibiotic-resistance. We evaluated the diagnostic performance of the Luminex xTAG Respiratory Viral Panel FAST v2 against viral specific PCR as reference assays for ARI in Vietnam. METHODS: Four hundred and forty two nose and throat swabs were collected in viral transport medium, and were tested with Luminex xTAG Respiratory Viral Panel FAST v2. Multiplex RT-PCR and single RT-PCR were used as references.    Results: Overall, viral pathogens were detected in a total count of 270/294 (91.8%, 95% CI 88.1-94.7) by the Luminex among reference assays, whilst 112/6336 (1.8%, 95% CI, 1.4-2.1) of pathogens were detected by the Luminex, but not by reference assays. Frequency of pathogens detected by Luminex and reference assays was 379 and 292, respectively. The diagnostic yield was 66.7% (295/442, 95%CI 62.1-71.1%) for the Luminex assay and 54.1% (239/442, 95% CI, 49.3-58.8%) for reference assays. The Luminex kit had higher yields for all viruses except influenza B virus, respiratory syncytial virus, and human bocavirus. High agreements between both methods [mean (range): 0.91 (0.83-1.00)] were found for 10/15 viral agents. CONCLUSIONS: The Luminex assay is a high throughput multiplex platform for rapid detection of common viral pathogens causing ARI. Although the current high cost may prevent Luminex assays from being widely used, especially in limited resource settings where ARI are felt most, its introduction in clinical diagnostics may help reduce unnecessary use of antibiotic prescription

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

Early Pandemic Influenza (2009 H1N1) in Ho Chi Minh City, Vietnam: A Clinical Virological and Epidemiological Analysis

Rogier van Doorn and colleagues analyze the initial outbreak, attempts at containment, and establishment of community transmission of pandemic H1N1 influenza in Ho Chi Minh City, Vietnam

Associations of Underlying Health Conditions With Anxiety and Depression Among Outpatients: Modification Effects of Suspected COVID-19 Symptoms, Health-Related and Preventive Behaviors

Objectives: We explored the association of underlying health conditions (UHC) with depression and anxiety, and examined the modification effects of suspected COVID-19 symptoms (S-COVID-19-S), health-related behaviors (HB), and preventive behaviors (PB).Methods: A cross-sectional study was conducted on 8,291 outpatients aged 18–85 years, in 18 hospitals and health centers across Vietnam from 14th February to May 31, 2020. We collected the data regarding participant's characteristics, UHC, HB, PB, depression, and anxiety.Results: People with UHC had higher odds of depression (OR = 2.11; p &lt; 0.001) and anxiety (OR = 2.86; p &lt; 0.001) than those without UHC. The odds of depression and anxiety were significantly higher for those with UHC and S-COVID-19-S (p &lt; 0.001); and were significantly lower for those had UHC and interacted with “unchanged/more” physical activity (p &lt; 0.001), or “unchanged/more” drinking (p &lt; 0.001 for only anxiety), or “unchanged/healthier” eating (p &lt; 0.001), and high PB score (p &lt; 0.001), as compared to those without UHC and without S-COVID-19-S, “never/stopped/less” physical activity, drinking, “less healthy” eating, and low PB score, respectively.Conclusion: S-COVID-19-S worsen psychological health in patients with UHC. Physical activity, drinking, healthier eating, and high PB score were protective factors