Emerging immunomodulatory strategies for cell therapeutics.

Cellular therapies are poised to transform the field of medicine by restoring dysfunctional tissues and treating various diseases in a dynamic manner not achievable by conventional pharmaceutics. Spanning various therapeutic areas inclusive of cancer, regenerative medicine, and immune disorders, cellular therapies comprise stem or non-stem cells derived from various sources. Despite numerous clinical approvals or trials underway, the host immune response presents a critical impediment to the widespread adoption and success of cellular therapies. Here, we review current research and clinical advances in immunomodulatory strategies to mitigate immune rejection or promote immune tolerance to cellular therapies. We discuss the potential of these immunomodulatory interventions to accelerate translation or maximize the prospects of improving therapeutic outcomes of cellular therapies for clinical success.

Correlation between SARS-CoV-2 RNA concentration in wastewater and COVID-19 cases in community: A systematic review and meta-analysis.

Wastewater-based epidemiology (WBE) has been considered as a promising approach for population-wide surveillance of coronavirus disease 2019 (COVID-19). Many studies have successfully quantified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater (CRNA). However, the correlation between the CRNA and the COVID-19 clinically confirmed cases in the corresponding wastewater catchments varies and the impacts of environmental and other factors remain unclear. A systematic review and meta-analysis were conducted to identify the correlation between CRNA and various types of clinically confirmed case numbers, including prevalence and incidence rates. The impacts of environmental factors, WBE sampling design, and epidemiological conditions on the correlation were assessed for the same datasets. The systematic review identified 133 correlation coefficients, ranging from -0.38 to 0.99. The correlation between CRNA and new cases (either daily new, weekly new, or future cases) was stronger than that of active cases and cumulative cases. These correlation coefficients were potentially affected by environmental and epidemiological conditions and WBE sampling design. Larger variations of air temperature and clinical testing coverage, and the increase of catchment size showed strong negative impacts on the correlation between CRNA and COVID-19 case numbers. Interestingly, the sampling technique had negligible impact although increasing the sampling frequency improved the correlation. These findings highlight the importance of viral shedding dynamics, in-sewer decay, WBE sampling design and clinical testing on the accurate back-estimation of COVID-19 case numbers through the WBE approach.

Lactoferrin as Immune-Enhancement Strategy for SARS-CoV-2 Infection in Alzheimer's Disease Patients.

Coronavirus 2 (SARS-CoV2) (COVID-19) causes severe acute respiratory syndrome. Severe illness of COVID-19 largely occurs in older people and recent evidence indicates that demented patients have higher risk for COVID-19. Additionally, COVID-19 further enhances the vulnerability of older adults with cognitive damage. A balance between the immune and inflammatory response is necessary to control the infection. Thus, antimicrobial and anti-inflammatory drugs are hopeful therapeutic agents for the treatment of COVID-19. Accumulating evidence suggests that lactoferrin (Lf) is active against SARS-CoV-2, likely due to its potent antiviral and anti-inflammatory actions that ultimately improves immune system responses. Remarkably, salivary Lf levels are significantly reduced in different Alzheimer's disease (AD) stages, which may reflect AD-related immunological disturbances, leading to reduced defense mechanisms against viral pathogens and an increase of the COVID-19 susceptibility. Overall, there is an urgent necessity to protect AD patients against COVID-19, decreasing the risk of viral infections. In this context, we propose bovine Lf (bLf) as a promising preventive therapeutic tool to minimize COVID-19 risk in patients with dementia or AD.

Lactoferrin as Immune-Enhancement Strategy for SARS-CoV-2 Infection in Alzheimer’s Disease Patients

Coronavirus 2 (SARS-CoV2) (COVID-19) causes severe acute respiratory syndrome. Severe illness of COVID-19 largely occurs in older people and recent evidence indicates that demented patients have higher risk for COVID-19. Additionally, COVID-19 further enhances the vulnerability of older adults with cognitive damage. A balance between the immune and inflammatory response is necessary to control the infection. Thus, antimicrobial and anti-inflammatory drugs are hopeful therapeutic agents for the treatment of COVID-19. Accumulating evidence suggests that lactoferrin (Lf) is active against SARS-CoV-2, likely due to its potent antiviral and anti-inflammatory actions that ultimately improves immune system responses. Remarkably, salivary Lf levels are significantly reduced in different Alzheimer’s disease (AD) stages, which may reflect AD-related immunological disturbances, leading to reduced defense mechanisms against viral pathogens and an increase of the COVID-19 susceptibility. Overall, there is an urgent necessity to protect AD patients against COVID-19, decreasing the risk of viral infections. In this context, we propose bovine Lf (bLf) as a promising preventive therapeutic tool to minimize COVID-19 risk in patients with dementia or AD.

Use of illicit drugs, alcohol and tobacco in Spain and Portugal during the COVID-19 crisis in 2020 as measured by wastewater-based epidemiology.

The COVID-19 pandemic spread rapidly worldwide in the year 2020, which was initially restrained by drastic mobility restrictions. In this work, we investigated the use of illicit drugs (amphetamine, methamphetamine, ecstasy, cocaine and cannabis), and licit substances of abuse (alcohol and tobacco) during the earlier months (March-July 2020) of the pandemic restrictions in four Spanish (Bilbao and its metropolitan area, Vitoria-Gasteiz, Castellón and Santiago de Compostela) and two Portuguese (Porto and Vila do Conde) locations by wastewater-based epidemiology (WBE). The results show that no methamphetamine was detected in any of the locations monitored, while amphetamine use was only detectable in the two locations from the Basque Country (Bilbao and its metropolitan area and Vitoria-Gasteiz), with high estimated average usage rates (700-930 mg day-1 1000 inhabitant-1). The remaining substances were detected in all the investigated catchment areas. In general, no remarkable changes were found in population normalized loads compared to former years, except for cocaine (i.e. its main metabolite, benzoylecgonine). For this drug, a notable decrease in use was discernible in Castellón, while its usage in Porto and Santiago de Compostela seemed to continue in a rising trend, already initiated in former years. Furthermore, two events of ecstasy (3,4-methylenedioxymethamphetamine, MDMA) dumping in the sewage network were confirmed by enantiomeric analysis, one in Santiago de Compostela just prior the lockdown and the second one in the Bilbao and its metropolitan area in July after relieving the more stringent measures. The latter could also be associated with a police intervention. The comparison of WBE with (web) survey data, which do not provide information at a local level, points towards contradictory conclusions for some of the substances, thereby highlighting the need for stable WBE networks capable of near real-time monitoring drug use.

Immunotherapeutic nanoparticles: From autoimmune disease control to the development of vaccines.

The development of nanoparticles (NPs) with potential therapeutic uses represents an area of vast interest in the scientific community during the last years. Recently, the pandemic caused by COVID-19 motivated a race for vaccines creation to overcome the crisis generated. This is a good demonstration that nanotechnology will most likely be the basis of future immunotherapy. Moreover, the number of publications based on nanosystems has significantly increased in recent years and it is expected that most of these developments can go on to experimentation in clinical stages soon. The therapeutic use of NPs to combat different diseases such as cancer, allergies or autoimmune diseases will depend on their characteristics, their targets, and the transported molecules. This review presents an in-depth analysis of recent advances that have been developed in order to obtain novel nanoparticulate based tools for the treatment of allergies, autoimmune diseases and for their use in vaccines. Moreover, it is highlighted that by providing targeted delivery an increase in the potential of vaccines to induce an immune response is expected in the future. Definitively, the here gathered analysis is a good demonstration that nanotechnology will be the basis of future immunotherapy.

Artificial neural network-based estimation of COVID-19 case numbers and effective reproduction rate using wastewater-based epidemiology.

As a cost-effective and objective population-wide surveillance tool, wastewater-based epidemiology (WBE) has been widely implemented worldwide to monitor the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater. However, viral concentrations or loads in wastewater often correlate poorly with clinical case numbers. To date, there is no reliable method to back-estimate the coronavirus disease 2019 (COVID-19) case numbers from SARS-CoV-2 concentrations in wastewater. This greatly limits WBE in achieving its full potential in monitoring the unfolding pandemic. The exponentially growing SARS-CoV-2 WBE dataset, on the other hand, offers an opportunity to develop data-driven models for the estimation of COVID-19 case numbers (both incidence and prevalence) and transmission dynamics (effective reproduction rate). This study developed artificial neural network (ANN) models by innovatively expanding a conventional WBE dataset to include catchment, weather, clinical testing coverage and vaccination rate. The ANN models were trained and evaluated with a comprehensive state-wide wastewater monitoring dataset from Utah, USA during May 2020 to December 2021. In diverse sewer catchments, ANN models were found to accurately estimate the COVID-19 prevalence and incidence rates, with excellent precision for prevalence rates. Also, an ANN model was developed to estimate the effective reproduction number from both wastewater data and other pertinent factors affecting viral transmission and pandemic dynamics. The established ANN model was successfully validated for its transferability to other states or countries using the WBE dataset from Wisconsin, USA.

Ivermectin & COVID-19: Let's keep a One Health perspective.

Despite uncertainty about its clinical benefit, ivermectin has been used for COVID 19, even in prophylaxis. The European Medicines Agency (EMA) has advised against its use for the prevention or treatment of COVID-19 outside randomised clinical trials. Although the potential negative environmental effects of ivermectin have been widely recognised when used in veterinary medicine, scarce attention has been devoted to the potential ecotoxicological impact of human use. We believe is time to include One Health's philosophy in our daily practice. In the specific case of ivermectin & COVID 19, environmental aspects should also be on the table.

Early SARS-CoV-2 outbreak detection by sewage-based epidemiology

Sewage can be used to determine the scale of COVID-19 outbreak. Sewage Epidemiology or Waste Based Epidemiology (WBE) approach has been successfully used to track and provide early warnings of outbreaks of pathogenic viruses such as Hepatitis A, Poliovirus and Norovirus. In untreated wastewater COVID-19 (excreted via faeces then introduced to wastewater) can survive from hours to days. Detection of COVID-19 can be carried out with nucleic acid-based polymerase chain reaction (PCR) assay, used for confirmation of COVID-19 patients around the globe. New cheaper and faster monitoring tools are being developed to detect Covid-19 in wastewater by biosensors, ELISA, or paper-based indicator methods. This will allow to reveal true scale of Covid-19 outbreak associated with population link to a specific wastewater treatment plant.