COVID-19, Chikungunya, Dengue and Zika Diseases: An Analytical Platform Based on MALDI-TOF MS, IR Spectroscopy and RT-qPCR for Accurate Diagnosis and Accelerate Epidemics Control

Functionalized cascaded tapered optical fiber sensor for simultaneous detection of dengue II E and SARS-CoV-2 S proteins

This work demonstrates a label-free dual-sensing biosensor utilizing cascaded single-mode tapered fiber (SMTF) for the concurrent detection of Dengue II envelope (E) and SARS-CoV-2 spike (S) proteins. Two fiber tapers of different dimensions were employed in-line, with each taper functionalized with specific complementary antibodies to the targeted antigens. The cascaded interferometric effect yielded composite spectral output that exhibited discrete response toward localized refractive index changes due to binding of antigens and antibodies. Consistent red shifts were observed with increasing concentration of the targeted analyte, which led to sensitivity values of 6.91 nm/nM for SMTF1 and 9.96 nm/nM for SMTF2, with a detection limit of 0.1 pM. This dual-sensing platform demonstrates high sensitivity and specificity, rapid response times, and the potential for integration into portable diagnostic devices, presenting it as a promising tool for point-of-care diagnostics and simultaneous detection of multiple disease biomarkers.

MALDI-TOF Mass Spectrometry Characterization of Culturable Microbiota Associated with the Skin of Amphibians from the Southern Andes Mountains of Ecuador

Ecuador is recognized for having a high diversity of anuran species, which are distributed mainly south of the Andes mountains. However, due to their geographic location and accessibility, there are few studies related to the culturable microbiota of these amphibians in this region. The objective of this study was to explore the bacterial and fungal biodiversity present on the skin of wild anuran species in the southern Andes of Ecuador and to observe whether geographical barriers in the region could increase the variability of the culturable microbiota through MALDI-TOF mass spectrometry. This analysis revealed the presence of 29 bacterial taxa and 9 fungal taxa, consisting mainly of: Pseudomonas chlororaphis (28%), Acinetobacter iwoffii (14%), Pseudomonas fluorescens (14%), and Hortaea werneckii (26.4%), Fusarium solani (20.5%), Syncephalastrum spp. (20.5%), respectively. Diversity varied across the five sampling locations, with geographic location proving to be a significant driver of diversity. Some of the most abundant bacterial and fungal genera have important associations with skin diseases in wildlife and humans. This work represents a glimpse into the complex biodiversity of bacteria and fungi that inhabit the skin substrate, and further studies will be needed to better understand bacterial and fungal biodiversity with potential implications for establishing conservation strategies, along with the development of necessary animal protection measures.

Instant Diagnosis Using Raman Spectroscopy and Generative Adversarial Networks: A Blood-Based Study on Seasonal Flu, COVID-19, and Dengue

Rapid detection of infectious diseases like COVID-19, flu, and dengue is crucial for healthcare professionals preparing for contagious outbreaks. Given the constant mutations in viruses and the recurring emergence of threats like Nipah and Zika, there is an urgent demand for a technology capable of distinguishing between infections that share similar symptoms. In this paper, we utilize laser-based Raman scattered signals from a drop of dried blood plasma, combined with generative artificial intelligence, to provide a rapid and precise diagnosis. Our optimized model exhibits exceptional performance, yielding high predictive scores of 96%, 98%, and 100% for flu, COVID-19, and dengue, respectively. The proposed Raman spectroscopic analysis, with a rapid turnaround time, can ensure a near-accurate diagnosis and proper quarantining of highly infectious cases. Furthermore, the potential extension of our method to include other viral diseases offers an alternative to the challenge of developing different diagnostic kits for each disease.

Targeted Isolation of Antiviral Labdane Diterpenes from the Bark of Neo-uvaria foetida (Annonaceae) using LC-MS/MS-Based Molecular Networking

In the search of new inhibitors for human coronavirus (HCoV), we screened extracts of endemic Annonaceae plants on an assay using a cellular model of Huh-7 cells infected with the human alphacoronavirus HCoV-229E. The EtOAc bark extract of the rare Southeast Asian plant Neo-uvaria foetida exhibited inhibition of HCoV-229E and SARS-CoV-2 viruses with IC50 values of 3.8 and 7.8 μg/mL, respectively. Using LC-MS/MS and molecular networking analysis guided isolation, we discovered two new labdane-type diterpenoids, 8-epi-acuminolide (1) and foetidalabdane A (4), and three known labdane diterpenoids, acuminolide (2), 17-O-acetylacuminolide (3), and spiroacuminolide (5). A new norlabdane diterpene, 16-foetinorlabdoic acid (6), was also isolated and identified. Excluding compounds 5 and 6, all other metabolites were active against the virus HCoV-229E. Terpenoids 1 and 4 presented antiviral activity against SARS-CoV-2 with IC50 values of 63.3 and 93.5 μM, respectively, indicating lower potency. Additionally, virological assays demonstrated that compounds 1, 2, and 3 exert antiviral effects against Zika virus by specifically interfering with the late stage of its infectious cycle with IC50 values of 76.0, 31.9, and 14.9 μM, respectively.

Identification of the Hub Genes Involved in Chikungunya Viral Infection

Background Chikungunya virus (CHIKV) infection poses a significant global health threat, necessitating a deeper understanding of its molecular mechanisms for effective management and treatment. This study aimed to understand the molecular and genetic mechanisms of CHIKV infection by analyzing microarray expression data. Methodology National Center for Biotechnology Information (NCBI) GEO2R with an adjusted p-value cut-off of <0.05 and |log2FC ≥ 1.5| was used to identify the differentially expressed genes involved in CHIKV infection using microarray data from the Gene Expression Omnibus (GEO) database, followed by enrichment analysis, protein-protein interaction (PPI) network construction, and, finally, hub gene identification. Results Analysis of the microarray dataset revealed 25 highly significant differentially expressed genes (DEGs), including 21 upregulated and four downregulated genes. PPI network analysis elucidated interactions among these DEGs, with hub genes such as ACTB and CTNNB1 exhibiting central roles. Enrichment analysis identified crucial pathways, including leukocyte transendothelial migration, regulation of actin cytoskeleton, and thyroid hormone signaling, implicating their involvement in CHIKV infection. Furthermore, the study highlights potential therapeutic targets such as ACTB and CTNNB1, which showed significant upregulation in infected cells. Conclusions These findings underscore the complex interplay between viral infection and host cellular processes, shedding light on novel avenues for diagnostic marker discovery and advancing antiviral strategies. In this study, we shed light on the molecular and genetic mechanisms of CHIKV infection and the potential role of ACTB and CTNNB1 genes.

Distinguishing SARS-CoV-2 Infection and Non-SARS-CoV-2 Viral Infections in Adult Patients through Clinical Score Tools

This study aimed to determine distinguishing predictors and develop a clinical score to differentiate COVID-19 and common viral infections (influenza, respiratory syncytial virus (RSV), dengue, chikungunya (CKV), and zika (ZKV)). This retrospective study enrolled 549 adults (100 COVID-19, 100 dengue, 100 influenza, 100 RSV, 100 CKV, and 49 ZKV) during the period 2017−2020. CKV and ZKV infections had specific clinical features (i.e., arthralgia and rash); therefore, these diseases were excluded. Multiple binary logistic regression models were fitted to identify significant predictors, and two scores were developed differentiating influenza/RSV from COVID-19 (Flu-RSV/COVID) and dengue from COVID-19 (Dengue/COVID). The five independent predictors of influenza/RSV were age > 50 years, the presence of underlying disease, rhinorrhea, productive sputum, and lymphocyte count < 1000 cell/mm3. Likewise, the five independent predictors of dengue were headache, myalgia, no cough, platelet count < 150,000/mm3, and lymphocyte count < 1000 cell/mm3. The Flu-RSV/COVID score (cut-off value of 4) demonstrated 88% sensitivity and specificity for predicting influenza/RSV (AUROC = 0.94). The Dengue/COVID score (cut-off value of 4) achieved 91% sensitivity and 94% specificity for differentiating dengue and COVID-19 (AUROC = 0.98). The Flu-RSV/COVID and Dengue/COVID scores had a high discriminative ability for differentiating influenza/RSV or dengue infection and COVID-19. The further validation of these scores is needed to ensure their utility in clinical practice.

Dengue virus and SARS-CoV-2 Co-infection dynamics: An emerging threat among African countries

The rising circulation of the vector borne disease such as dengue fever amidst the COVID-19 pandemic in African countries is on the rise, which pose a significant public health threat. In this article, we discussed the co-infection of dengue virus (DENV) (the causative agent of dengue fever) and SARS-CoV-2 (the causative agents of COVID-19) as well as the associated risk factors involved. Our review highlights that the continuous increase in the incidence and disease mortality from the co-infection of dengue Virus and SARS-CoV-2 is as result of inadequate surveillance and limited testing centers. Second, the overlapping clinical features and indistinguishable symptoms from both infections is a major challenge. Third, lack of scientific prudence among stakeholders has played a significant impact on how to contain these diseases. Therefore, there is a need to reassess research priorities in understanding the risk factors involved from the coinfection. Also, the development of accurate point-of-care diagnostics for COVID-19 and dengue fever coupled with community-based health intervention programs is highly essential for control.

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In Africa, the incidence and disease mortality rate from the co-infection of dengue fever and COVID- 19 is on the rise due to inadequate surveillance and limited testing centers.

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Overlapping clinical features and lack of scientific prudence among stakeholders have played a significant impact on how to contain these infectious diseases.

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Research priorities need to be reassessed with focus on understanding risk factors involved.

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Development of accurate point-of-care diagnostics and community-based health intervention programs for both infection is highly essential for control.

Pro-Inflammatory Profile of Children Exposed to Maternal Chikungunya Virus Infection during the Intrauterine Period: A One-Year Follow-Up Study

Chikungunya virus (CHIKV) vertical transmission occurs due to maternal viremia in the prepartum. Clinical presentation in neonates can be varied; however, the consequences of intrauterine exposure on the immune response are unclear. Thus, we aimed to analyze inflammatory alterations in children exposed to maternal CHIKV infection. This is a cross-sectional study that included children exposed to maternal CHIKV infection (confirmed by RT-qPCR and/or IgM). Circulant immune mediators were analyzed by a multiplex assay. RESULTS: We included 33 children, with a mean age of 3 ± 2.9 months-old, and 19 (57.6%) were male. Only one child presented neurological alterations. CHIKV-exposed infants showed elevated levels of MIP-1α, MIP-1β, and CCL-2 (p < 0.05). Pro-inflammatory cytokines such as TNFα, IL-6, and IL-7 (p < 0.0001) were also increased. In addition, lower levels of PDGF-BB and GM-CSF were observed in the same group (p < 0.0001). Principal component (PC) analysis highlighted a distinction in the inflammatory profile between groups, where PC explained 56.6% of the alterations. Our findings suggest that maternal exposure to CHIKV can affect the circulating levels of pro-inflammatory cytokines during the infants’ first year of life. The long-term clinical consequences of these findings should be investigated.

Coinfection between SARS-CoV-2 and vector-borne diseases in Luanda, Angola

Co-epidemics happening simultaneously can generate a burden on healthcare systems. The co-occurrence of SARS-CoV-2 with vector-borne diseases (VBD), such as malaria and dengue in resource-limited settings represents an additional challenge to the healthcare systems. Herein, we assessed the coinfection rate between SARS-CoV-2 and VBD to highlight the need to carry out an accurate diagnosis and promote timely measures for these infections in Luanda, the capital city of Angola. This was a cross-sectional study conducted with 105 subjects tested for the SARS-CoV-2 and VBD with a rapid detection test in April 2021. The participants tested positive for SARS-CoV-2 (3.80%), malaria (13.3%), and dengue (27.6%). Low odds related to testing positivity to SARS-CoV-2 or VBD were observed in participants above or equal to 40 years (odds ratio [OR]: 0.60, p = 0.536), while higher odds were observed in male (OR: 1.44, p = 0.392) and urbanized areas (OR: 3.78, p = 0.223). The overall co-infection rate between SARS-CoV-2 and VBD was 11.4%. Our findings showed a coinfection between SARS-CoV-2 with malaria and dengue, which could indicate the need to integrate the screening for VBD in the SARS-CoV-2 testing algorithm and the adjustment of treatment protocols. Further studies are warranted to better elucidate the relationship between COVID-19 and VBD in Angola.

Multiplex Technologies in COVID-19 Research, Diagnostics, and Prognostics: Battling the Pandemic

Due to continuous technical developments and new insights into the high complexity of infectious diseases such as COVID-19, there is an increasing need for multiplex biomarkers to aid clinical management and support the development of new drugs and vaccines. COVID-19 disease requires rapid diagnosis and stratification to enable the most appropriate treatment course for the best possible outcomes for patients. In addition, these tests should be rapid, specific, and sensitive. They should rule out other potential causes of illness with simultaneous testing for other diseases. Elevated levels of specific biomarkers can be used to establish severity risks of chronic diseases so that patients can be provided the proper medication at the right time. This review describes the state-of-the-art technologies in proteomics, transcriptomics, and metabolomics, for multiplex biomarker approaches in COVID-19 research.

The global emergence of Chikungunya infection: An integrated view

Chikungunya virus (CHIKV) is one of the emerging viruses around the globe. It belongs to the family Togaviridae and genus Alphavirus and is an arthropod borne virus that transmits by the bite of an infected mosquito, mainly through Aedes aegypti and Aedes albopcitus. It is a spherical, enveloped virus with positive single stranded RNA genome. It was first discovered during 1952-53 in Tanganyika, after which outbreaks were documented in many regions of the world. CHIKV has two transmission cycles; an enzootic sylvatic cycle and an urban cycle. CHIKV genome contains 11,900 nucleotides and two open reading frames and shows great sequence variability. Molecular mechanisms of virus host-cell interactions and the pathogenesis of disease are not fully understood. The disease involves three phases; acute, post-acute and chronic with symptoms including high-grade fever, arthralgia, macupapular rashes and headache. There is no licensed vaccine or specific treatment for CHIKV infection. This lack of specific interventions combined with difficulties in making a precise diagnosis together make the disease difficult to manage. In this review we aim to present the current knowledge of global epidemiology, transmission, structure, various aspects of diagnosis as well as highlight potential antiviral drugs and vaccines against CHIKV.

Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) Analysis for the Identification of Pathogenic Microorganisms: A Review

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been used in the field of clinical microbiology since 2010. Compared with the traditional technique of biochemical identification, MALDI-TOF MS has many advantages, including convenience, speed, accuracy, and low cost. The accuracy and speed of identification using MALDI-TOF MS have been increasing with the development of sample preparation, database enrichment, and algorithm optimization. MALDI-TOF MS has shown promising results in identifying cultured colonies and rapidly detecting samples. MALDI-TOF MS has critical research applications for the rapid detection of highly virulent and drug-resistant pathogens. Here we present a scientific review that evaluates the performance of MALDI-TOF MS in identifying clinical pathogenic microorganisms. MALDI-TOF MS is a promising tool in identifying clinical microorganisms, although some aspects still require improvement.