Timely and accurate dengue diagnosis is important for differential diagnosis and immediate implementation of appropriate disease control measures. In this study, we compared the usefulness and applicability of NS1 RDT (NS1 Ag Strip) and qRT-PCR tests in complementing the IgM ELISA for dengue diagnosis on single serum specimen (n = 375). The NS1 Ag Strip and qRT-PCR showed a fair concordance (κ = 0.207, p = 0.001). While the NS1 Ag Strip showed higher positivity than qRT-PCR for acute (97.8% vs. 84.8%) and post-acute samples (94.8% vs. 71.8%) of primary infection, qRT-PCR showed higher positivity for acute (58.1% vs. 48.4%) and post-acute (50.0% vs.41.4%) samples in secondary infection. IgM ELISA showed higher positivity in samples from secondary dengue (74.2-94.8%) than in those from primary dengue (21.7-64.1%). More primary dengue samples showed positive with combined NS1 Ag Strip/IgM ELISA (99.0% vs. 92.8%) whereas more secondary samples showed positive with combined qRT-PCR/IgM ELISA (99.4% vs. 96.2%). Combined NS1 Ag Strip/IgM ELISA is a suitable combination tests for timely and accurate dengue diagnosis on single serum specimen. If complemented with qRT-PCR, combined NS1 Ag Strip/IgM ELISA would improve detection of secondary dengue samples.
Vaccination may be an alternative treatment for infection with multidrug-resistance (MDR) Acinetobacter baumannii. The study reported here evaluated the bactericidal antibody responses following immunization of mice using an inactivated whole-cell vaccine derived from antibiotic-exposed MDR A. baumannii (I-M28-47-114). Mice inoculated with I-M28-47 (non-antibiotic-exposed control) and I-M28-47-114 showed a high IgG antibody response by day 5 post-inoculation. Sera from mice inoculated with I-M28-47-114 collected on day 30 resulted in 80.7 ± 12.0% complement-mediated bacteriolysis in vitro of the test MDR A. baumannii treated with imipenem, which was a higher level of bacteriolysis over sera from mice inoculated with I-M28-47. Macrophage-like U937 cells eliminated 49.3 ± 11.6% of the test MDR A. baumannii treated with imipenem when opsonized with sera from mice inoculated with I-M28-47-114, which was a higher level of elimination than observed for test MDR A. baumannii opsonized with sera from mice inoculated with I-M28-47. These results suggest that vaccination with I-M28-47-114 stimulated antibody responses capable of mounting high bactericidal killing of MDR A. baumannii. Therefore, the inactivated antibiotic-exposed whole-cell vaccine (I-M28-47-114) has potential for development as a candidate vaccine for broad clearance and protection against MDR A. baumannii infections.
Outbreaks involving the Asian genotype Chikungunya virus (CHIKV) caused over one million infections in the Americas recently. The outbreak was preceded by a major nationwide outbreak in the Philippines. We examined the phylogenetic and phylogeographic relationships of representative CHIKV isolates obtained from the 2012 Philippines outbreak with other CHIKV isolates collected globally. Asian CHIKV isolated from the Philippines, China, Micronesia and Caribbean regions were found closely related, herein denoted as Cosmopolitan Asian CHIKV (CACV). Three adaptive amino acid substitutions in nsP3 (D483N), E1 (P397L) and E3 (Q19R) were identified among CACV. Acquisition of the nsP3-483N mutation in Compostela Valley followed by E1-397L/E3-19R in Laguna preceded the nationwide spread in the Philippines. The China isolates possessed two of the amino acid substitutions, nsP3-D483N and E1-P397L whereas the Micronesian and Caribbean CHIKV inherited all the three amino acid substitutions. The unique amino acid substitutions observed among the isolates suggest multiple independent virus dissemination events. The possible biological importance of the specific genetic signatures associated with the rapid global of the virus is not known and warrant future in-depth study and epidemiological follow-up. Molecular evidence, however, supports the Philippines outbreak as the possible origin of the CACV.
Zika virus (ZIKV) infection is a serious public health concern. ZIKV infection has been associated with increased occurrences of microcephaly among newborns and incidences of Guillain-Barré syndrome among adults. No specific therapeutics or vaccines are currently available to treat and protect against ZIKV infection. Here, a plant-secreted phytoalexin, resveratrol (RES), was investigated for its ability to inhibit ZIKV replication in vitro. Several RES treatment regimens were used. The ZIKV titers of mock- and RES-treated infected cell cultures were determined using the focus-forming assay and the Zika mRNA copy number as determined using qRT-PCR. Our results suggested that RES treatment reduced ZIKV titers in a dose-dependent manner. A reduction of >90% of virus titer and ZIKV mRNA copy number was achieved when infected cells were treated with 80 µM of RES post-infection. Pre-incubation of the virus with 80 µM RES showed >30% reduction in ZIKV titers and ZIKV mRNA copy number, implying potential direct virucidal effects of RES against the virus. The RES treatment reduced >70% virus titer in the anti-adsorption assay, suggesting the possibility that RES also interferes with ZIKV binding. However, there was no significant decrease in ZIKV titer when a short-period of RES treatment was applied to cells before ZIKV infection (pre-infection) and after the virus bound to the cells (virus internalization inhibition), implying that RES acts through its continuous presence in the cell cultures after virus infection. Overall, our results suggested that RES exhibited direct virucidal activity against ZIKV and possessed anti-ZIKV replication properties, highlighting the need for further exploration of RES as a potential antiviral molecule against ZIKV infection.
Getah virus (GETV), a mosquito-borne alphavirus, is an emerging animal pathogen causing outbreaks among racehorses and pigs. Early detection of the GETV infection is essential for timely implementation of disease prevention and control interventions. Thus, a rapid and accurate nucleic acid detection method for GETV is highly needed. Here, two TaqMan minor groove binding (MGB) probe-based quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assays were developed. The qRT-PCR primers and TaqMan MGB probe were designed based on the conserved region of nsP1 and nsP2 genes of 23 GETV genome sequences retrieved from GenBank. Only the qRT-PCR assay using nsP2-specific primers and probe detected all two Malaysia GETV strains (MM2021 and B254) without cross-reacting with other closely related arboviruses. The qRT-PCR assay detected as few as 10 copies of GETV RNA, but its detection limit at the 95% probability level was 63.25 GETV genome copies (probit analysis, P ≤ 0.05). Further validation of the qRT-PCR assay using 16 spiked simulated clinical specimens showed 100% for both sensitivity and specificity. In conclusion, the qRT-PCR assay developed in this study is useful for rapid, sensitive and specific detection and quantification of GETV.
Neonatal microcephaly and adult Guillain-Barré syndrome are severe complications of Zika virus (ZIKV) infection. The robustly induced inflammatory cytokine expressions in ZIKV-infected patients may constitute a hallmark for severe disease. In the present study, the potential role of high mobility group box 1 protein (HMGB1) in ZIKV infection was investigated. HMGB1 protein expression was determined by the enzyme-linked immunosorbent assay (ELISA) and immunoblot assay. HMGB1's role in ZIKV infection was also explored using treatment with dexamethasone, an immunomodulatory drug, and HMGB1-knockdown (shHMGB1) Huh7 cells. Results showed that the Huh7 cells were highly susceptible to ZIKV infection. The infection was found to induce HMGB1 nuclear-to-cytoplasmic translocation, resulting in a > 99% increase in the cytosolic HMGB1 expression at 72-h post-infection (h.p.i). The extracellular HMGB1 level was elevated in a time- and multiplicity of infection (MOI)-dependent manner. Treatment of the ZIKV-infected cells with dexamethasone (150 µM) reduced HMGB1 extracellular release in a dose-dependent manner, with a maximum reduction of 71 ± 5.84% (P
The COVID-19 pandemic first emerged in Malaysia in Jan 2020. As of 12th Sept 2021, 1,979,698 COVID-19 cases that occurred over three major epidemic waves were confirmed. The virus contributing to the three epidemic waves has not been well-studied. We sequenced the genome of 22 SARS-CoV-2 strains detected in Malaysia during the second and the ongoing third wave of the COVID-19 epidemic. Detailed phylogenetic and genetic variation analyses of the SARS-CoV-2 isolate genomes were performed using these newly determined sequences and all other available sequences. Results from the analyses suggested multiple independent introductions of SARS-CoV-2 into Malaysia. A new B.1.524(G) lineage with S-D614G mutation was detected in Sabah, East Malaysia and Selangor, Peninsular Malaysia on 7th October 2020 and 14th October 2020, respectively. This new B.1.524(G) group was not the direct descendant of any of the previously detected lineages. The new B.1.524(G) carried a set of genetic variations, including A701V (position variant frequency = 0.0007) in Spike protein and a novel G114T mutation at the 5'UTR. The biological importance of the specific mutations remained unknown. The sequential appearance of the mutations, however, suggests that the spread of the new B.1.524(G) lineages likely begun in Sabah and then spread to Selangor. The findings presented here support the importance of SARS-CoV-2 full genome sequencing as a tool to establish an epidemiological link between cases or clusters of COVID-19 worldwide.
The exponential distribution optimizer (EDO) represents a heuristic approach, capitalizing on exponential distribution theory to identify global solutions for complex optimization challenges. This study extends the EDO's applicability by introducing its multi-objective version, the multi-objective EDO (MOEDO), enhanced with elite non-dominated sorting and crowding distance mechanisms. An information feedback mechanism (IFM) is integrated into MOEDO, aiming to balance exploration and exploitation, thus improving convergence and mitigating the stagnation in local optima, a notable limitation in traditional approaches. Our research demonstrates MOEDO's superiority over renowned algorithms such as MOMPA, NSGA-II, MOAOA, MOEA/D and MOGNDO. This is evident in 72.58% of test scenarios, utilizing performance metrics like GD, IGD, HV, SP, SD and RT across benchmark test collections (DTLZ, ZDT and various constraint problems) and five real-world engineering design challenges. The Wilcoxon Rank Sum Test (WRST) further confirms MOEDO as a competitive multi-objective optimization algorithm, particularly in scenarios where existing methods struggle with balancing diversity and convergence efficiency. MOEDO's robust performance, even in complex real-world applications, underscores its potential as an innovative solution in the optimization domain. The MOEDO source code is available at: https://github.com/kanak02/MOEDO .
Agriculture plays a pivotal role in the economic development of a nation, but, growth of agriculture is affected badly by the many factors one such is plant diseases. Early stage prediction of these disease is crucial role for global health and even for game changers the farmer's life. Recently, adoption of modern technologies, such as the Internet of Things (IoT) and deep learning concepts has given the brighter light of inventing the intelligent machines to predict the plant diseases before it is deep-rooted in the farmlands. But, precise prediction of plant diseases is a complex job due to the presence of noise, changes in the intensities, similar resemblance between healthy and diseased plants and finally dimension of plant leaves. To tackle this problem, high-accurate and intelligently tuned deep learning algorithms are mandatorily needed. In this research article, novel ensemble of Swin transformers and residual convolutional networks are proposed. Swin transformers (ST) are hierarchical structures with linearly scalable computing complexity that offer performance and flexibility at various scales. In order to extract the best deep key-point features, the Swin transformers and residual networks has been combined, followed by Feed forward networks for better prediction. Extended experimentation is conducted using Plant Village Kaggle datasets, and performance metrics, including accuracy, precision, recall, specificity, and F1-rating, are evaluated and analysed. Existing structure along with FCN-8s, CED-Net, SegNet, DeepLabv3, Dense nets, and Central nets are used to demonstrate the superiority of the suggested version. The experimental results show that in terms of accuracy, precision, recall, and F1-rating, the introduced version shown better performances than the other state-of-art hybrid learning models.
Recently, most service or product-oriented industries have been focusing on their activities to uphold the green and sustainable environment protocol owing to the increased environmental pollution. Concerning this issue, industries are now concentrating on developing recyclable or waste materials products. This research advocates developing and validating a banana fiber sandwich composite to promote the beneficial usage of bio-waste. The composite sandwich specimens were fabricated with resin-impregnated woven banana fiber mat as a skin, and the core was reinforced with three different weight percentages (5, 7.5 and 10%) of chopped banana fiber. The sandwich specimens were pressed into a three-point bending test to validate the structural integrity. The flexural characteristics like flexural strength and modulus were examined experimentally, whereas the key strength indices like flexural stiffness and core shear modulus were evaluated analytically. Post-fracture surfaces were studied through a scanning electron microscope to investigate the failure mechanism. The experimental and analytical results indicate that 10% banana fiber content in the sandwich core increases the flexural strength and flexural modulus to 225% and 147%, respectively, compared to the neat epoxy core. The numerical simulation was also performed through FEA to validate the experimental findings. The numerical results are in good concurrence with the experimental one.
Pain intensity classification using facial images is a challenging problem in computer vision research. This work proposed a patch and transfer learning-based model to classify various pain intensities using facial images. The input facial images were segmented into dynamic-sized horizontal patches or "shutter blinds". A lightweight deep network DarkNet19 pre-trained on ImageNet1K was used to generate deep features from the shutter blinds and the undivided resized segmented input facial image. The most discriminative features were selected from these deep features using iterative neighborhood component analysis, which were then fed to a standard shallow fine k-nearest neighbor classifier for classification using tenfold cross-validation. The proposed shutter blinds-based model was trained and tested on datasets derived from two public databases-University of Northern British Columbia-McMaster Shoulder Pain Expression Archive Database and Denver Intensity of Spontaneous Facial Action Database-which both comprised four pain intensity classes that had been labeled by human experts using validated facial action coding system methodology. Our shutter blinds-based classification model attained more than 95% overall accuracy rates on both datasets. The excellent performance suggests that the automated pain intensity classification model can be deployed to assist doctors in the non-verbal detection of pain using facial images in various situations (e.g., non-communicative patients or during surgery). This system can facilitate timely detection and management of pain.
Climate change has led to a ~ 40% reduction in summer Arctic sea-ice cover extent since the 1970s. Resultant increases in light availability may enhance phytoplankton production. Direct evidence for factors currently constraining summertime phytoplankton growth in the Arctic region is however lacking. GEOTRACES cruise GN05 conducted a Fram Strait transect from Svalbard to the NE Greenland Shelf in summer 2016, sampling for bioessential trace metals (Fe, Co, Zn, Mn) and macronutrients (N, Si, P) at ~ 79°N. Five bioassay experiments were conducted to establish phytoplankton responses to additions of Fe, N, Fe + N and volcanic dust. Ambient nutrient concentrations suggested N and Fe were deficient in surface seawater relative to typical phytoplankton requirements. A west-to-east trend in the relative deficiency of N and Fe was apparent, with N becoming more deficient towards Greenland and Fe more deficient towards Svalbard. This aligned with phytoplankton responses in bioassay experiments, which showed greatest chlorophyll-a increases in + N treatment near Greenland and + N + Fe near Svalbard. Collectively these results suggest primary N limitation of phytoplankton growth throughout the study region, with conditions potentially approaching secondary Fe limitation in the eastern Fram Strait. We suggest that the supply of Atlantic-derived N and Arctic-derived Fe exerts a strong control on summertime nutrient stoichiometry and resultant limitation patterns across the Fram Strait region.
The insect male accessory gland (MAG) is an internal reproductive organ responsible for the synthesis and secretion of seminal fluid components, which play a pivotal role in the male reproductive strategy. In many species of insects, the effective ejaculation of the MAG products is essential for male reproduction. For this purpose, the fruit fly Drosophila has evolved binucleation in the MAG cells, which causes high plasticity of the glandular epithelium, leading to an increase in the volume of seminal fluid that is ejaculated. However, such a binucleation strategy has only been sporadically observed in Dipteran insects, including fruit flies. Here, we report the discovery of binucleation in the MAG of the common bed bug, Cimex lectularius, which belongs to hemimetabolous Hemiptera phylogenetically distant from holometabolous Diptera. In Cimex, the cell morphology and timing of synchrony during binucleation are quite different from those of Drosophila. Additionally, in Drosophila, the position of the two nuclei in the adult stage changes as a result of the mating history or the nutrient conditions; however, it remains stable in Cimex. These differences suggest that binucleation in the Cimex MAG plays a unique role in the male reproductive system that is distinct from that of Drosophila.
Surface plasmon resonance (SPR) is a medical diagnosis technique with high sensitivity and specificity. In this research, a new method based on SPR is proposed for rapid, 10-minute detection of the anti-dengue virus in human serum samples. This novel technique, known as rapid immunoglobulin M (IgM)-based dengue diagnostic test, can be utilized quickly and easily at the point of care. Four dengue virus serotypes were used as ligands on a biochip. According to the results, a serum volume of only 1 μl from a dengue patient (as a minimized volume) is required to indicate SPR angle variation to determine the ratio of each dengue serotype in samples with 83-93% sensitivity and 100% specificity.
MYB proteins are highly conserved DNA-binding domains (DBD) and mutations in MYB oncoproteins have been reported to cause aberrant and augmented cancer progression. Identification of MYB molecular biomarkers predictive of cancer progression can be used for improving cancer management. To address this, a biomarker discovery pipeline was employed in investigating deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in predicting damaging and potential alterations on the properties of proteins. The nsSNP of the MYB family; MYB, MYBL1, and MYBL2 was extracted from the NCBI database. Five in silico tools (PROVEAN, SIFT, PolyPhen-2, SNPs&GO and PhD-SNP) were utilized to investigate the outcomes of nsSNPs. A total of 45 nsSNPs were predicted as high-risk and damaging, and were subjected to PMut and I-Mutant 2.0 for protein stability analysis. This resulted in 32 nsSNPs with decreased stability with a DDG score lower than - 0.5, indicating damaging effect. G111S, N183S, G122S, and S178C located within the helix-turn-helix (HTH) domain were predicted to be conserved, further posttranslational modifications and 3-D protein analysis indicated these nsSNPs to shift DNA-binding specificity of the protein thus altering the protein function. Findings from this study would help in the field of pharmacogenomic and cancer therapy towards better intervention and management of cancer.
Polymer composites are fabricated by incorporating fillers into a polymer matrix. The intent for addition of fillers is to improve the physical, mechanical, chemical and rheological properties of the composite. This study reports on a unique polymer composite using hydrochar, synthesised by microwave-assisted hydrothermal carbonization of rice husk, as filler in polylactide matrix. The polylactide/hydrochar composites were fabricated by incorporating hydrochar in polylactide at 5%, 10%, 15% and 20 wt% by melt processing in a Haake rheomix at 170 °C. Both the neat polylactide and polylactide/hydrochar composite were characterized for mechanical, structural, thermal and rheological properties. The tensile modulus of polylactide/hydrochar composites was improved from 2.63 GPa (neat polylactide) to 3.16 GPa, 3.33 GPa, 3.54 GPa, and 4.24 GPa after blending with hydrochar at 5%, 10%, 15%, and 20%, respectively. Further, the incorporation of hydrochar had little effect on storage modulus (G') and loss modulus (G″). The findings of this study reported that addition of hydrochar improves some characteristics of polylactide composites suggesting the potential of hydrochar as filler for polymer/hydrochar composites.
Gait data collection from overweight individuals walking on irregular surfaces is a challenging task that can be addressed using inertial measurement unit (IMU) sensors. However, it is unclear how many IMUs are needed, particularly when body attachment locations are not standardized. In this study, we analysed data collected from six body locations, including the torso, upper and lower limbs, to determine which locations exhibit significant variation across different real-world irregular surfaces. We then used deep learning method to verify whether the IMU data recorded from the identified body locations could classify walk patterns across the surfaces. Our results revealed two combinations of body locations, including the thigh and shank (i.e., the left and right shank, and the right thigh and right shank), from which IMU data should be collected to accurately classify walking patterns over real-world irregular surfaces (with classification accuracies of 97.24 and 95.87%, respectively). Our findings suggest that the identified numbers and locations of IMUs could potentially reduce the amount of data recorded and processed to develop a fall prevention system for overweight individuals.
Parkinson's disease (PD) is a member of a larger group of neuromotor diseases marked by the progressive death of dopamineproducing cells in the brain. Providing computational tools for Parkinson disease using a set of data that contains medical information is very desirable for alleviating the symptoms that can help the amount of people who want to discover the risk of disease at an early stage. This paper proposes a new hybrid intelligent system for the prediction of PD progression using noise removal, clustering and prediction methods. Principal Component Analysis (PCA) and Expectation Maximization (EM) are respectively employed to address the multi-collinearity problems in the experimental datasets and clustering the data. We then apply Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector Regression (SVR) for prediction of PD progression. Experimental results on public Parkinson's datasets show that the proposed method remarkably improves the accuracy of prediction of PD progression. The hybrid intelligent system can assist medical practitioners in the healthcare practice for early detection of Parkinson disease.
Two novel types of anion exchange membranes (AEMs) having imidazolium-type functionalised nanofibrous substrates were prepared using the facile and potentially scalable method. The membranes' precursors were prepared by graft copolymerization of vinylbenzyl chloride (VBC) onto syndiotactic polypropylene (syn-PP) and polyamide-66 (PA-66) nanofibrous networks followed by crosslinking with 1,8-octanediamine, thermal treatment and subsequent functionalisation of imidazolium groups. The obtained membranes displayed an ion exchange capacity (IEC) close to 1.9 mmol g-1 and ionic (OH-) conductivity as high as 130 mS cm-1 at 80 °C. This was coupled with a reasonable alkaline stability representing more than 70% of their original conductivity under accelerated degradation test in 1 M KOH at 80 °C for 360 h. The effect of ionomer binder on the performance of the membrane electrode assembly (MEA) in AEM fuel cell was evaluated with the optimum membrane. The MEA showed a power density of as high as 440 mW cm-2 at a current density is 910 mA cm-2 with diamine crosslinked quaternized polysulfone (DAPSF) binder at 80 °C with 90% humidified H2 and O2 gases. Such performance was 2.3 folds higher than the corresponding MEA performance with quaternary ammonium polysulfone (QAPS) binder at the same operating conditions. Overall, the newly developed membrane was found to possess not only an excellent combination of physico-chemical properties and a reasonable stability but also to have a facile preparation procedure and cheap ingredients making it a promising candidate for application in AEM fuel cell.