Boosting Strategy Research Articles

A systematic approach for learning imbalanced data: enhancing zero-inflated models through boosting

In this paper, we propose systematic approaches for learning imbalanced data based on a two-regime process: regime 0, which generates excess zeros (majority class), and regime 1, which contributes to generating an outcome of one (minority class). The proposed model contains two latent equations: a split probit (logit) equation in the first stage and an ordinary probit (logit) equation in the second stage. Because boosting improves the accuracy of prediction versus using a single classifier, we combined a boosting strategy with the two-regime process. Thus, we developed the zero-inflated probit boost (ZIPBoost) and zero-inflated logit boost (ZILBoost) methods. We show that the weight functions of ZIPBoost have the desired properties for good predictive performance. Like AdaBoost, the weight functions upweight misclassified examples and downweight correctly classified examples. We show that the weight functions of ZILBoost have similar properties to those of LogitBoost. The algorithm will focus more on examples that are hard to classify in the next iteration, resulting in improved prediction accuracy. We provide the relative performance of ZIPBoost and ZILBoost, which rely on the excess kurtosis of the data distribution. Furthermore, we show the convergence and time complexity of our proposed methods. We demonstrate the performance of our proposed methods using a Monte Carlo simulation, mergers and acquisitions (M&A) data application, and imbalanced datasets from the Keel repository. The results of the experiments show that our proposed methods yield better prediction accuracy compared to other learning algorithms.

A superior heterologous prime-boost vaccination strategy against COVID-19: A bivalent vaccine based on yeast-derived RBD proteins followed by a heterologous vaccine.

Various vaccines have been challenged by SARS-CoV-2 variants. Here, we reported a yeast-derived recombinant bivalent vaccine (Bivalent wild-type [Wt]+De) based on the wtand Delta receptor-binding domain (RBD). Yeast derived RBD proteins based on the wtand Delta mutant were used as the prime vaccine. It was found that, in the presence of aluminium hydroxide (Alum) and unmethylated CpG-oligodeoxynucleotides (CpG) adjuvants, more cross-protective immunity against SARS-CoV-2 prototype and variants were elicited by bivalent vaccine than monovalent wtRBD or Delta RBD. Furthermore, a heterologous boosting strategy consisting of two doses of bivalent vaccines followed by one dose adenovirus vectored vaccine exhibited cross-neutralization capacity and specific T cell responses against Delta and Omicron (BA.1 and BA.4/5) variants in mice, superior to a homologous vaccination strategy. This study suggested that heterologous prime-boost vaccination with yeast-derived bivalent protein vaccine could be a potential approach to address the challenge of emerging variants.

Ameliorative Effect of Coenzyme Q10 on Phenotypic Transformation in Human Smooth Muscle Cells with FBN1 Knockdown.

Mutations of the FBN1 gene lead to Marfan syndrome (MFS), which is an autosomal dominant connective tissue disorder featured by thoracic aortic aneurysm risk. There is currently no effective treatment for MFS. Here, we studied the role of mitochondrial dysfunction in the phenotypic transformation of human smooth muscle cells (SMCs) and whether a mitochondrial boosting strategy can be a potential treatment. We knocked down FBN1 in SMCs to create an MFS cell model and used rotenone to induce mitochondrial dysfunction. Furthermore, we incubated the shFBN1 SMCs with Coenzyme Q10 (CoQ10) to assess whether restoring mitochondrial function can reverse the phenotypic transformation. The results showed that shFBN1 SMCs had decreased TFAM (mitochondrial transcription factor A), mtDNA levels and mitochondrial mass, lost their contractile capacity and had increased synthetic phenotype markers. Inhibiting the mitochondrial function of SMCs can decrease the expression of contractile markers and increase the expression of synthetic genes. Imposing mitochondrial stress causes a double-hit effect on the TFAM level, oxidative phosphorylation and phenotypic transformation of FBN1-knockdown SMCs while restoring mitochondrial metabolism with CoQ10 can rapidly reverse the synthetic phenotype. Our results suggest that mitochondria function is a potential therapeutic target for the phenotypic transformation of SMCs in MFS.

A strategy for boosting photovoltaic performance based on a two-dimensional ZrSSe/HfSSe van der Waals heterostructure.

Identifying high-efficiency solar photovoltaic systems with two-dimensional (2D) materials is still an urgent challenge to meet modern energy requirements. Very recently, a 2D heterostructure with type-II band alignment has been confirmed to be more favorable for application in photoelectric conversion. However, the staggered band offset of 2D type-II heterostructures cannot always be guaranteed, nor the intrinsic hindrance mechanism of carrier recombination being clear. In this study, taking the emerging ZrSSe/HfSSe van der Waals heterostructure (vdWH) as a generic example, a boosting strategy for improving the photoelectric performances of 2D vdWHs is proposed. Through a series of in-depth systematic research studies based on first-principles, we demonstrate that via applying a vertical strain, an anticipated band alignment transition from type-I to favorable type-II of this ZrSSe/HfSSe vdWH can be induced due to the interfacial charge redistribution, during which a corresponding enlarged photocurrent can be detected from the latter based device compared to the former. Essentially, such enhanced photocurrent at the incident photon energy (Eph) around the band gap is attributed to the suppressed recombination rate of photoexcited carriers. Moreover, when Eph is increased into the visible light region, the photoelectric conversion performances can be further controlled by vertical strain. These generalized findings not only provide an effective manipulation strategy for enhancing the performances of 2D solar photovoltaic systems, but the intrinsic physical mechanism can also be extended to the next practical design and regulation of other 2D photovoltaic devices.

A Strategy for Power Density Amelioration of Capacitive Reverse Electrodialysis Systems with a Single Membrane.

Blue energy refers to the osmotic energy released while combining solutions of different salinity. Recently, single-membrane-based capacitive reverse electrodialysis cells were developed for blue energy harvesting. The performance of these cells is limited by the low ion-electron flux transfer efficiency of the capacitive electrodes in the current operating regimes. To optimize it, we point out an original boosting strategy of using a secondary voltage source E0 placed in series with the capacitive concentration cell. The net recovered power is defined as the difference between the power dissipated in the load resistor and the power supplied by the secondary voltage. Experimental results indicate a maximum power density of 5.26 W·m-2 (where the salinity difference is 0.17 and 5.13 M), which corresponds to a 59.8% increase compared with its power density of 3.29 W·m-2 without boosting strategy. A good agreement on power density is reached for theoretical simulations and experimental results. Influential factors are systematically studied to further reveal the boosting strategy.

CEBoosting: Online sparse identification of dynamical systems with regime switching by causation entropy boosting.

Regime switching is ubiquitous in many complex dynamical systems with multiscale features, chaotic behavior, and extreme events. In this paper, a causation entropy boosting (CEBoosting) strategy is developed to facilitate the detection of regime switching and the discovery of the dynamics associated with the new regime via online model identification. The causation entropy, which can be efficiently calculated, provides a logic value of each candidate function in a pre-determined library. The reversal of one or a few such causation entropy indicators associated with the model calibrated for the current regime implies the detection of regime switching. Despite the short length of each batch formed by the sequential data, the accumulated value of causation entropy corresponding to a sequence of data batches leads to a robust indicator. With the detected rectification of the model structure, the subsequent parameter estimation becomes a quadratic optimization problem, which is solved using closed analytic formulas. Using the Lorenz 96 model, it is shown that the causation entropy indicator can be efficiently calculated, and the method applies to moderately large dimensional systems. The CEBoosting algorithm is also adaptive to the situation with partial observations. It is shown via a stochastic parameterized model that the CEBoosting strategy can be combined with data assimilation to identify regime switching triggered by the unobserved latent processes. In addition, the CEBoosting method is applied to a nonlinear paradigm model for topographic mean flow interaction, demonstrating the online detection of regime switching in the presence of strong intermittency and extreme events.

Combined Live Oral Priming and Intramuscular Boosting Regimen with Rotarix® and a Nanoparticle-Based Trivalent Rotavirus Vaccine Evaluated in Gnotobiotic Pig Models of G4P[6] and G1P[8] Human Rotavirus Infection.

Human rotavirus (HRV) is the causative agent of severe dehydrating diarrhea in children under the age of five, resulting in up to 215,000 deaths each year. These deaths almost exclusively occur in low- and middle-income countries where vaccine efficacy is the lowest due to chronic malnutrition, gut dysbiosis, and concurrent enteric viral infection. Parenteral vaccines for HRV are particularly attractive as they avoid many of the concerns associated with currently used live oral vaccines. In this study, a two-dose intramuscular (IM) regimen of the trivalent, nanoparticle-based, nonreplicating HRV vaccine (trivalent S60-VP8*), utilizing the shell (S) domain of the capsid of norovirus as an HRV VP8* antigen display platform, was evaluated for immunogenicity and protective efficacy against P[6] and P[8] HRV using gnotobiotic pig models. A prime-boost strategy using one dose of the oral Rotarix® vaccine, followed by one dose of the IM trivalent nanoparticle vaccine was also evaluated. Both regimens were highly immunogenic in inducing serum virus neutralizing, IgG, and IgA antibodies. The two vaccine regimens failed to confer significant protection against diarrhea; however, the prime-boost regimen significantly shortened the duration of virus shedding in pigs challenged orally with the virulent Wa (G1P[8]) HRV and significantly shortened the mean duration of virus shedding, mean peak titer, and area under the curve of virus shedding after challenge with Arg (G4P[6]) HRV. Prime-boost-vaccinated pigs challenged with P[8] HRV had significantly higher P[8]-specific IgG antibody-secreting cells (ASCs) in the spleen post-challenge. Prime-boost-vaccinated pigs challenged with P[6] HRV had significantly higher numbers of P[6]- and P[8]-specific IgG ASCs in the ileum, as well as significantly higher numbers of P[8]-specific IgA ASCs in the spleen post-challenge. These results suggest the promise of and warrant further investigation into the oral priming and parenteral boosting strategy for future HRV vaccines.

Application of extreme gradient boosting method for evaluating the properties of episodic failure of borehole breakout

In petroleum engineering, determining in situ stresses and breakout dimensions are crucial. Nowadays, hydraulic fracturing is a frequently used method for identifying in stresses and breakout dimensions. Regrettably, the hydraulic fracturing procedure is costly and time-consuming. In petroleum engineering, it is very appealing to use the in-situ stresses and properties of the stone to calculate the breakout dimensions (rB/a, and θB). However, since the rB/a, and θB are so complicated prediction is challenging. In this case, impactful algorithms were established utilizing the hybridized extreme gradient boosting (XGB) strategy on collected data in order to accurately anticipate the rB/a, and θB. In addition, a number of recently developed optimization algorithms, including Fire Hawk Optimization (FHO), Artificial Hummingbird Algorithm (AHA), Flow Direction Algorithm (FDA), and COOT Optimization Algorithm (COA), were used to tune the XGB's hyperparameters. By analyzing XGB-based developed models considering various aspects of analysis, the suggested FHO−XGB could be identified as the superior model in the prediction of rB/a, and θB, which can be utilized in order to reduce the hydraulic fracture attempts.

An Improved YOLOv5 Method to Detect Tailings Ponds from High-Resolution Remote Sensing Images

Tailings ponds’ failure and environmental pollution make tailings monitoring very important. Remote sensing technology can quickly and widely obtain ground information and has become one of the important means of tailings monitoring. However, the efficiency and accuracy of traditional remote sensing monitoring technology have difficulty meeting the management needs. At the same time, affected by factors such as the geographical environment and imaging conditions, tailings have various manifestations in remote sensing images, which all bring challenges to the accurate acquisition of tailings information in large areas. By improving You Only Look Once (YOLO) v5s, this study designs a deep learning-based framework for the large-scale extraction of tailings ponds information from the entire high-resolution remote sensing images. For the improved YOLOv5s, the Swin Transformer is integrated to build the Swin-T backbone, the Fusion Block of efficient Reparameterized Generalized Feature Pyramid Network (RepGFPN) in DAMO-YOLO is introduced to form the RepGFPN Neck, and the head is replaced with Decoupled Head. In addition, sample boosting strategy (SBS) and global non-maximum suppression (GNMS) are designed to improve the sample quality and suppress repeated detection frames in the entire image, respectively. The model test results based on entire Gaofen-6 (GF-6) high-resolution remote sensing images show that the F1 score of tailings ponds is significantly improved by 12.22% compared with YOLOv5, reaching 81.90%. On the basis of both employing SBS, the improved YOLOv5s boots the mAP@0.5 of YOLOv5s by 5.95%, reaching 92.15%. This study provides a solution for tailings ponds’ monitoring and ecological environment management.

Tissue-specific effects of exercise as NAD+ -boosting strategy: Current knowledge and future perspectives.

Nicotinamide adenine dinucleotide (NAD+ ) is an evolutionarily highly conserved coenzyme with multi-faceted cell functions, including energy metabolism, molecular signaling processes, epigenetic regulation, and DNA repair. Since the discovery that lower NAD+ levels are a shared characteristic of various diseases and aging per se, several NAD+ -boosting strategies have emerged. Other than pharmacological and nutritional approaches, exercise is thought to restore NAD+ homeostasis through metabolic adaption to chronically recurring states of increased energy demand. In this review we discuss the impact of acute exercise and exercise training on tissue-specific NAD+ metabolism of rodents and humans to highlight the potential value as NAD+ -boosting strategy. By interconnecting results from different investigations, we aim to draw attention to tissue-specific alterations in NAD+ metabolism and the associated implications for whole-body NAD+ homeostasis. Acute exercise led to profound alterations of intracellular NAD+ metabolism in various investigations, with the magnitude and direction of changes being strongly dependent on the applied exercise modality, cell type, and investigated animal model or human population. Exercise training elevated NAD+ levels and NAD+ metabolism enzymes in various tissues. Based on these results, we discuss molecular mechanisms that might connect acute exercise-induced disruptions of NAD+ /NADH homeostasis to chronic exercise adaptions in NAD+ metabolism. Taking this hypothesis-driven approach, we hope to inspire future research on the molecular mechanisms of exercise as NAD+ -modifying lifestyle intervention, thereby elucidating the potential therapeutic value in NAD+ -related pathologies.

Groundwater contaminant source identification based on an ensemble learning search framework associated with an auto xgboost surrogate

Groundwater contaminant source identification (GCSI) is commonly accompanied by search process which tweaks the unknown contaminant source information to match the simulation model outputs with the measurements. When solving identification task, search accuracy and time cost have always been challenges that must be tackled. In the present study, a novel ensemble learning search framework associated with auto extreme gradient boosting tree (xgboost) was proposed to solve GCSI. In particular, auto xgboost was employed to reduce the calculation burden caused by repeatedly running simulation model. To promote search efficiency, boosting strategy (BOS) was employed to sequentially concatenate iterative ensemble smoother, differential evolution particle filter (DEPF), and swarm evolution algorithm. The identification results indicated that: 1. Auto xgboost could substitute a numerical simulation model with desired accuracy and expeditious running speed. 2. BOS could achieve better search accuracy, but with the sacrifice of infinitesimal calculated time cost, when compared with bagging strategy.

Anchor-free temporal action localization via Progressive Boundary-aware Boosting

Enormous untrimmed videos from the real world are difficult to analyze and manage. Temporal action localization algorithms can help us to locate and recognize human activity clips in untrimmed videos. Recently, anchor-free temporal action localization methods have gained increasing attention due to small computational costs and no complex hyperparameters of pre-set anchors. Although the performance has been significantly improved, most existing anchor-free temporal action localization methods still suffer from inaccurate action boundary predictions. In this paper, we want to alleviate the above problem through boundary refinement and temporal context aggregation. To this end, a novel Progressive Boundary-aware Boosting Network (PBBNet) is proposed for anchor-free temporal action localization. The PBBNet consists of three main modules: Temporal Context-aware Module (TCM), Instance-wise Boundary-aware Module (IBM), and Frame-wise Progressive Boundary-aware Module (FPBM). The TCM aggregates the temporal context information and provides features for the IBM and the FPBM. The IBM generates multi-scale video features to predict action results coarsely. Compared with IBM, the FPBM focuses on instance features corresponding to action predictions and uses more supervision information for boundary regression. Given action results from IBM, the FPBM uses a progressive boosting strategy to refine the boundary predictions multiple times with supervision from weak to strong. Extensive experiments on three benchmark datasets THUMOS14, ActivityNet-v1.3 and HACS show our PPBNet outperforms all existing anchor-free methods. Further, our PPBNet achieves state-of-the-art performance (72.5% mAP at tIoU = 0.5) on THUMOS14 dataset.

Biomineralized hydrogel DC vaccine for cancer immunotherapy: A boosting strategy via improving immunogenicity and reversing immune-inhibitory microenvironment

The postoperative recurrence and metastasis of triple negative breast cancer (TNBC) remain one fatal reason for the failure of clinical treatments. Although the rise of immunotherapy has brought hopes for reducing postoperative recurrence and potential metastasis, the low immune response and immunosuppression of tumor microenvironment (TME) still restrain its extensive application. Herein, we reported a boosting strategy by improving immunogenicity and reversing suppressive TME to realize efficient immunotherapy of TNBC. In this work, a CaCO3 biomineralized hydrogel DC vaccine was synthesized by fixing the membrane proteins of 4T1 cells-DCs fusion cells (FP) into biomineralized silk fibroin hydrogel. On one side, the FP-containing biomineralized hydrogel vaccine (SH@FP@CaCO3) has increased immunogenicity by providing a wide variety of tumor-associated antigens (TAAs) and realizing long-term protein release for DCs maturation and T cell activation. On the other side, the introduction of CaCO3 would increase the pH of TME and promote the polarization of M2-type macrophages to M1-type macrophages, thus reversing the immune-inhibitory microenvironment and relieving the immunosuppressive effect on T cells. The results indicate that the biomineralized hydrogel vaccine shows excellent immune activation effects by simultaneously enhancing the immunogenicity and reversing the immunosuppression TME, which provides a promising strategy for cancer immunotherapy.

A Hybrid Learning Framework for Imbalanced Classification

Class imbalance is a well-known and challenging algorithmic research topic among the machine learning community as traditional classifiers generally perform poorly on imbalanced problems, where data to be learned have skewed distributions between their classes. This paper presents a hybrid framework named PRUSBoost for learning imbalanced classification. It combines a selective data under-sampling procedure and a powerful boosting strategy to effectively enhance classification performance on imbalanced problems. Different from the simple random under sampling algorithm, this framework constructs the training data of the majority or negative class by using a newly developed partition based under sampling approach. Experiments on several datasets from different application domains that carry skewed class distributions have shown that the proposed framework provides a very competitive, consistent, and effective solution to imbalanced classification problems.

Lombard effect in Algerian Dialect Speech: Investigation of boosting and bypass strategies in narrowband noisy environment

The paper presents the first investigation on the Lombard effect (LE) in the Algerian Dialect (AD) speech. It is devoted to the examination of boosting and bypass strategies in narrowband noisy environments (0.49–6.8 kHz). Speakers who adopt the boosting tactic would attempt to improve their audibility in noise by increasing the global intensity (I), the local intensity, and the duration (D) of their speech. The boost of the local intensity consists in amplifying the spectral magnitude of the speech waveform in the frequency region wherein the masking noise is beyond 55 dB. However, speakers who apply the bypass strategy would raise their speech in noise so that their fundamental frequency (F0) and first Formant (F1) will decrease. We built the AD Lombard Speech Corpus (ADLSC) that consists of continuous speech files uttered by eight native speakers in quiet and noisy conditions. The corpus contains phonetically rich words that cover all AD phonemes. To examine these strategies, we assessed the change in I, D, F0 and F1 from quiet to noisy environments. Subsequently, we evaluated the change in the local intensity via the computation of the Power Spectrum Ratio (PSR). Statistical tests were conducted to confirm the significance of the acoustic analysis. We found out that speakers raised their vocal effort in I and D. Furthermore, the measured PSRs confirmed the evidence that LE is frequency-specific in humans. Similarly, we noticed that speakers increased their F0 and F1 in noisy conditions. The results we obtained confirmed the boosting strategy but denied the bypass tactic. We compared our findings with the results reported in the state-of-the-art studies. The comparison revealed that LE in narrowband does not exhibit the same acoustic variations in AD and English.

Comparison of immune responses induced by two or three doses of an alum-adjuvanted inactivated SARS-CoV-2 vaccine in mice.

Waning antibodies and rapidly emerging variants are challenges for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) vaccine development. Adjusting existing immunization schedules and further boosting strategies are under consideration. Here, the immune responses induced by an alum‐adjuvanted inactivated SARS‐CoV‐2 vaccine in mice were compared among immunization schedules with two or three doses. For the two‐dose schedule, a 0–28‐day schedule induced 5‐fold stronger spike‐specific IgG responses than a 0–14‐day schedule, with only a slight elevation of spike‐specific cellular immunity 14 days after the last immunization. A third homologous boost 2 or 5 months after the second dose for the 0–28‐day schedule slightly strengthened humoral responses (1.3‐fold for the 0–1–3‐month schedule, and 1.8‐fold for the 0–1–6‐month schedule) 14 days after the last immunization. Additionally, a third homologous boost (especially with the 0–1–3‐month schedule) induced significantly stronger cell‐mediated immunity than both two‐dose immunization schedules for all indexes tested, with a response similar to that induced by a one‐dose heterologous boost with BNT162b2 in clinical trials, according to cellular immunity analysis (1.5‐fold). These T cell responses were Th2 oriented, with good CD4+ and CD8+ memory. These results may offer clues for applying a homologous boosting strategy for alum‐adjuvanted inactivated SARS‐CoV‐2 vaccines.

Ultrasensitive Detection for Cadaverine Gas Using Energy Transfer from Graphene to Gold Nanorod Based on Plasmon Boosting Strategy

Ultrasensitive Detection for Cadaverine Gas Using Energy Transfer from Graphene to Gold Nanorod Based on Plasmon Boosting Strategy

Personalized Control Strategy of Electronic Brake Booster With Driving Behaviors Identification

To improve the comfort and user acceptance of the intelligent vehicle braking system, this paper proposes a control strategy for the electronic brake booster (Ebooster) that considers differences in driving behaviors. First, a real-vehicle driving data collection platform is built to collect the driving behavior data of 84 drivers under typical vehicle-following braking conditions. Subsequently, the k-means clustering algorithm optimized by particle swarm optimization (PSO) is used to realize the cluster analysis of driving behaviors, and the support vector machine (SVM) algorithm optimized by the genetic algorithm (GA) is used to complete the identification of driving behaviors. Next, through the analysis of the boost characteristics of the self-designed Ebooster, driving behaviors are matched with boost characteristics, and a personalized basic boosting control strategy based on the driver behavior is designed. Finally, a hardware-in-the-loop (HiL) bench and a real-vehicle test platform are designed and built to verify the effectiveness of the personalized control strategy of the Ebooster. The results show that this method can effectively identify the type of driver and make personalized adjustments to the basic boosting strategy of the Ebooster, which effectively improves the personalization of the braking system, resulting in a higher pedal response and user acceptance.

Immunogenicity and Safety of an Intradermal BNT162b2 mRNA Vaccine Booster after Two Doses of Inactivated SARS-CoV-2 Vaccine in Healthy Population.

Effective vaccine coverage is urgently needed to tackle the COVID-19 pandemic. Inactivated vaccines have been introduced in many countries for emergency usage, but have only provided limited protection. Heterologous vaccination is a promising strategy to maximise vaccine immunogenicity. Here, we conducted a phase I, randomised control trial to observe the safety and immunogenicity after an intradermal boost, using a fractional dosage (1:5) of BNT162b2 mRNA vaccine in healthy participants in Songkhla, Thailand. In total, 91 volunteers who had been administered with two doses of inactivated SARS-CoV-2 (CoronaVac) were recruited into the study, and then randomised (1:1:1) to received different regimens of the third dose. An intramuscular booster with a full dose of BNT162b2 was included as a conventional control, and a half dose group was included as reciprocal comparator. Both, immediate and delayed adverse events following immunisation (AEFI) were monitored. Humoral and cellular immune responses were examined to observe the booster effects. The intradermal booster provided significantly fewer systemic side effects, from 70% down to 19.4% (p < 0.001); however, they were comparable to local reactions with the conventional intramuscular booster. In the intradermal group after receiving only one fifth of the conventional dosage, serum Anti-RBD IgG was halved compared to the full dose of an intramuscular injection. However, the neutralising function against the Delta strain remained intact. T cell responses were also less effective in the intradermal group compared to the intramuscular booster. Together, the intradermal booster, using a fractional dose of BNT162b2, can reduce systemic reactions and provides a good level and function of antibody responses compared to the conventional booster. This favourable intradermal boosting strategy provides a suitable alternative for vaccines and effective vaccine management to increase the coverage during the vaccine shortage.

The Antiviral Activity of Bacterial, Fungal, and Algal Polysaccharides as Bioactive Ingredients: Potential Uses for Enhancing Immune Systems and Preventing Viruses.

Viral infections may cause serious human diseases. For instance, the recent appearance of the novel virus, SARS-CoV-2, causing COVID-19, has spread globally and is a serious public health concern. The consumption of healthy, proper, functional, and nutrient-rich foods has an important role in enhancing an individual's immune system and preventing viral infections. Several polysaccharides from natural sources such as algae, bacteria, and fungi have been considered as generally recognized as safe (GRAS) by the US Food and Drug Administration. They are safe, low-toxicity, biodegradable, and have biological activities. In this review, the bioactive polysaccharides derived from various microorganisms, including bacteria, fungi, and algae were evaluated. Antiviral mechanisms of these polysaccharides were discussed. Finally, the potential use of microbial and algal polysaccharides as an antiviral and immune boosting strategy was addressed. The microbial polysaccharides exhibited several bioactivities, including antioxidant, anti-inflammatory, antimicrobial, antitumor, and immunomodulatory activities. Some microbes are able to produce sulfated polysaccharides, which are well-known to exert a board spectrum of biological activities, especially antiviral properties. Microbial polysaccharide can inhibit various viruses using different mechanisms. Furthermore, these microbial polysaccharides are also able to modulate immune responses to prevent and/or inhibit virus infections. There are many molecular factors influencing their bioactivities, e.g., functional groups, conformations, compositions, and molecular weight. At this stage of development, microbial polysaccharides will be used as adjuvants, nutrient supplements, and for drug delivery to prevent several virus infections, especially SARS-CoV-2 infection.