Massachusetts companion program bolsters COVID-19 vaccine rates among seniors.

In parts of the United States, COVID-19 vaccination rates remained low until late in Fall 2021 owing to both limited vaccine access and hesitancy. With colliding epidemics of RSV, flu, and COVID-19 in the winter, the retrospective evaluation of vaccine incentive policies is needed to inform future routine immunization campaigns. The Massachusetts companion program is one example of a policy that could boost vaccine uptake among older populations. Our regression discontinuity analysis suggests that the program was associated with an increase of up to 22 percentage points in the proportion of individuals aged 75 and older who have been fully vaccinated. Going forward, similar intervention strategies could be invaluable in scenarios where household contacts pose the greatest risk of transmission or where social ties can strongly influence individual decision-making.

Innovations in dengue virus detection: An overview of conventional and electrochemical biosensor approaches.

Globally, people are in great threat due to the highly spreading of viral infectious diseases. Every year like 100-300 million cases of infections are found, and among them, above 80% are not recognized and irrelevant. Dengue virus (DENV) is an arbovirus infection that currently infects people most frequently. DENV encompasses four viral serotypes, and they each express comparable sign. From a mild febrile sickness to a potentially fatal dengue hemorrhagic fever, dengue can induce a variety of symptoms. Presently, the globe is being challenged by the untimely identification of dengue infection. Therefore, this review summarizes advances in the detection of dengue from conventional methods (nucleic acid-based, polymerase chain reaction-based, and serological approaches) to novel biosensors. This work illustrates an extensive study of the current designs and fabrication approaches involved in the formation of electrochemical biosensors for untimely identifications of dengue. Additionally, in electrochemical sensing of DENV, we skimmed through significances of biorecognition molecules like lectins, nucleic acid, and antibodies. The introduction of emerging techniques such as the CRISPR/Cas' system and their integration with biosensing platforms has also been summarized. Furthermore, the review revealed the importance of electrochemical approach compared with traditional diagnostic methods.

Vaccine development: Current trends and technologies.

Despite the effectiveness of vaccination in reducing or eradicating diseases caused by pathogens, there remain certain diseases and emerging infections for which developing effective vaccines is inherently challenging. Additionally, developing vaccines for individuals with compromised immune systems or underlying medical conditions presents significant difficulties. As well as traditional vaccine different methods such as inactivated or live attenuated vaccines, viral vector vaccines, and subunit vaccines, emerging non-viral vaccine technologies, including viral-like particle and nanoparticle vaccines, DNA/RNA vaccines, and rational vaccine design, offer new strategies to address the existing challenges in vaccine development. These advancements have also greatly enhanced our understanding of vaccine immunology, which will guide future vaccine development for a broad range of diseases, including rapidly emerging infectious diseases like COVID-19 and diseases that have historically proven resistant to vaccination. This review provides a comprehensive assessment of emerging non-viral vaccine production methods and their application in addressing the fundamental and current challenges in vaccine development.

Resistive random access memory: introduction to device mechanism, materials and application to neuromorphic computing.

The modern-day computing technologies are continuously undergoing a rapid changing landscape; thus, the demands of new memory types are growing that will be fast, energy efficient and durable. The limited scaling capabilities of the conventional memory technologies are pushing the limits of data-intense applications beyond the scope of silicon-based complementary metal oxide semiconductors (CMOS). Resistive random access memory (RRAM) is one of the most suitable emerging memory technologies candidates that have demonstrated potential to replace state-of-the-art integrated electronic devices for advanced computing and digital and analog circuit applications including neuromorphic networks. RRAM has grown in prominence in the recent years due to its simple structure, long retention, high operating speed, ultra-low-power operation capabilities, ability to scale to lower dimensions without affecting the device performance and the possibility of three-dimensional integration for high-density applications. Over the past few years, research has shown RRAM as one of the most suitable candidates for designing efficient, intelligent and secure computing system in the post-CMOS era. In this manuscript, the journey and the device engineering of RRAM with a special focus on the resistive switching mechanism are detailed. This review also focuses on the RRAM based on two-dimensional (2D) materials, as 2D materials offer unique electrical, chemical, mechanical and physical properties owing to their ultrathin, flexible and multilayer structure. Finally, the applications of RRAM in the field of neuromorphic computing are presented.

Evolving Face Mask Guidance During a Pandemic and Potential Harm to Public Perception: Infodemiology Study of Sentiment and Emotion on Twitter.

BACKGROUND: Throughout the COVID-19 pandemic, US Centers for Disease Control and Prevention policies on face mask use fluctuated. Understanding how public health communications evolve around key policy decisions may inform future decisions on preventative measures by aiding the design of communication strategies (eg, wording, timing, and channel) that ensure rapid dissemination and maximize both widespread adoption and sustained adherence. OBJECTIVE: We aimed to assess how sentiment on masks evolved surrounding 2 changes to mask guidelines: (1) the recommendation for mask use on April 3, 2020, and (2) the relaxation of mask use on May 13, 2021. METHODS: We applied an interrupted time series method to US Twitter data surrounding each guideline change. Outcomes were changes in the (1) proportion of positive, negative, and neutral tweets and (2) number of words within a tweet tagged with a given emotion (eg, trust). Results were compared to COVID-19 Twitter data without mask keywords for the same period. RESULTS: There were fewer neutral mask-related tweets in 2020 (ß=-3.94 percentage points, 95% CI -4.68 to -3.21; P<.001) and 2021 (ß=-8.74, 95% CI -9.31 to -8.17; P<.001). Following the April 3 recommendation (ß=.51, 95% CI .43-.59; P<.001) and May 13 relaxation (ß=3.43, 95% CI 1.61-5.26; P<.001), the percent of negative mask-related tweets increased. The quantity of trust-related terms decreased following the policy change on April 3 (ß=-.004, 95% CI -.004 to -.003; P<.001) and May 13 (ß=-.001, 95% CI -.002 to 0; P=.008). CONCLUSIONS: The US Twitter population responded negatively and with less trust following guideline shifts related to masking, regardless of whether the guidelines recommended or relaxed mask usage. Federal agencies should ensure that changes in public health recommendations are communicated concisely and rapidly.

A comprehensive SARS-CoV-2-human protein-protein interactome reveals COVID-19 pathobiology and potential host therapeutic targets.

Studying viral-host protein-protein interactions can facilitate the discovery of therapies for viral infection. We use high-throughput yeast two-hybrid experiments and mass spectrometry to generate a comprehensive SARS-CoV-2-human protein-protein interactome network consisting of 739 high-confidence binary and co-complex interactions, validating 218 known SARS-CoV-2 host factors and revealing 361 novel ones. Our results show the highest overlap of interaction partners between published datasets and of genes differentially expressed in samples from COVID-19 patients. We identify an interaction between the viral protein ORF3a and the human transcription factor ZNF579, illustrating a direct viral impact on host transcription. We perform network-based screens of >2,900 FDA-approved or investigational drugs and identify 23 with significant network proximity to SARS-CoV-2 host factors. One of these drugs, carvedilol, shows clinical benefits for COVID-19 patients in an electronic health records analysis and antiviral properties in a human lung cell line infected with SARS-CoV-2. Our study demonstrates the value of network systems biology to understand human-virus interactions and provides hits for further research on COVID-19 therapeutics.

Current Update on Biomarkers for Detection of Cancer: Comprehensive Analysis.

Early and effective diagnosis of cancer is decisive for its proper management. In this context biomarker-based cancer diagnosis is budding as one of the promising ways for early detection, disease progression monitoring, and effective cancer therapy. Integration of Biosensing devices with different metallic/nonmetallic nanoparticles offers amplification and multiplexing capabilities for simultaneous detection of cancer biomarkers (CB's). This study provides a comprehensive analysis of the most recent designs and fabrication methodologies designed for developing electrochemical biosensors (EB) for early detection of cancers. The role of biomarkers in cancer therapeutics is also discussed.

The Colloquy between Microbiota and the Immune System in Colon Cancer: Repercussions on the Cancer Therapy.

Colorectal cancer is the second leading cause of cancer deaths worldwide and has engrossed researchers' attention toward its detection and prevention at early stages. Primarily associated with genetic and environmental risk factors, the disease has also shown its emergence due to dysbiosis in microbiota. The microbiota not only plays a role in modulating the metabolisms of metastatic tissue but also has a keen role in cancer therapy. The immune cells are responsible for secreting various chemokines and cytokines, and activating pattern recognition receptors by different microbes can lead to the trail by which these cells regulate cancer. Furthermore, mixed immune reactions involving NK cells, tumor-associated macrophages, and lymphocytes have shown their connection with the microbial counterpart of the disease. The microbes like Bacteroides fragilis, Fusobacterium nucleatum, and Enterococcus faecalis and their metabolites have engendered inflammatory reactions in the tumor microenvironment. Hence the interplay between immune cells and various microbes is utilized to study the changing metastasis stage. Targeting either immune cells or microbiota could not serve as a key to tackling this deadly disorder. However, harnessing their complementation towards the disease can be a powerful weapon for developing therapy and diagnostic/prognostic markers. In this review, we have discussed various immune reactions and microbiome interplay in CRC, intending to evaluate the effectiveness of chemotherapy and immunotherapy and their parallel relationship.

A comprehensive SARS-CoV-2-human protein-protein interactome network identifies pathobiology and host-targeting therapies for COVID-19.

Physical interactions between viral and host proteins are responsible for almost all aspects of the viral life cycle and the host's immune response. Studying viral-host protein-protein interactions is thus crucial for identifying strategies for treatment and prevention of viral infection. Here, we use high-throughput yeast two-hybrid and affinity purification followed by mass spectrometry to generate a comprehensive SARS-CoV-2-human protein-protein interactome network consisting of both binary and co-complex interactions. We report a total of 739 high-confidence interactions, showing the highest overlap of interaction partners among published datasets as well as the highest overlap with genes differentially expressed in samples (such as upper airway and bronchial epithelial cells) from patients with SARS-CoV-2 infection. Showcasing the utility of our network, we describe a novel interaction between the viral accessory protein ORF3a and the host zinc finger transcription factor ZNF579 to illustrate a SARS-CoV-2 factor mediating a direct impact on host transcription. Leveraging our interactome, we performed network-based drug screens for over 2,900 FDA-approved/investigational drugs and obtained a curated list of 23 drugs that had significant network proximities to SARS-CoV-2 host factors, one of which, carvedilol, showed promising antiviral properties. We performed electronic health record-based validation using two independent large-scale, longitudinal COVID-19 patient databases and found that carvedilol usage was associated with a significantly lowered probability (17%-20%, P < 0.001) of obtaining a SARS-CoV-2 positive test after adjusting various confounding factors. Carvedilol additionally showed anti-viral activity against SARS-CoV-2 in a human lung epithelial cell line [half maximal effective concentration (EC 50 ) value of 4.1 µM], suggesting a mechanism for its beneficial effect in COVID-19. Our study demonstrates the value of large-scale network systems biology approaches for extracting biological insight from complex biological processes.

Development of paper-based DNA sensor for detection of O. tsutsugamushi using sustainable GQDs@AuNPs nanocomposite.

The graphene quantum dots (GQDs) was synthesized using potato starch and water by hydrothermal method and further used for reduction of tetracholoroauric acid to form graphene quantum dots-gold (GQDs@AuNPs) nanocomposite. The GQDs/GQDs@AuNPs were analyzed using FTIR, UV-Vis, Flourometry and HR-TEM. The synthesized GQDs@AuNPs were further used for fabrication of cost-effective screen-printed paper electrode (SPPE) based DNA sensor for the detection of O. tsutsugamushi using htrA gene specific 5'NH2 linked DNA probe. Modification of SPPE using GQDs@AuNPs nanocomposite and ssDNA probe was monitored using EIS, FTIR, FE-SEM and AFM. The sensor detection limit (LOD) was assessed as 0.002 ng/µl from the standard calibration curve with the correlation coefficient, R2 = 0.993. The sensitivity of the DNA sensor was calculated as 7700 µA/cm2/ng for ssGDNA of O. tsutsugamushi using cyclic voltammetry. The sensor validation was done using scrub typhus patient's blood DNA samples. The sensor showed good storage stability at 4 °C for six months with just a loss of 12% of the initial current values. The SPPE/DNA sensor developed is very specific, sensitive, stable and detects O. tsutsugamushi in less time.

A 3D structural SARS-CoV-2-human interactome to explore genetic and drug perturbations.

Emergence of new viral agents is driven by evolution of interactions between viral proteins and host targets. For instance, increased infectivity of SARS-CoV-2 compared to SARS-CoV-1 arose in part through rapid evolution along the interface between the spike protein and its human receptor ACE2, leading to increased binding affinity. To facilitate broader exploration of how pathogen-host interactions might impact transmission and virulence in the ongoing COVID-19 pandemic, we performed state-of-the-art interface prediction followed by molecular docking to construct a three-dimensional structural interactome between SARS-CoV-2 and human. We additionally carried out downstream meta-analyses to investigate enrichment of sequence divergence between SARS-CoV-1 and SARS-CoV-2 or human population variants along viral-human protein-interaction interfaces, predict changes in binding affinity by these mutations/variants and further prioritize drug repurposing candidates predicted to competitively bind human targets. We believe this resource ( http://3D-SARS2.yulab.org ) will aid in development and testing of informed hypotheses for SARS-CoV-2 etiology and treatments.

Graphene Oxide Nanoparticles Modified Paper Electrode as a Biosensing Platform for Detection of the htrA Gene of O. tsutsugamushi.

The unique structural and electrochemical properties of graphene oxide (GO) make it an ideal material for the fabrication of biosensing devices. Therefore, in the present study, graphene oxide nanoparticles modified paper electrodes were used as a low-cost matrix for the development of an amperometric DNA sensor. The graphene oxide was synthesized using the modified hummers method and drop cast on a screen-printed paper electrode (SPPE) to enhance its electrochemical properties. Further, the GO/SPPE electrode was modified with a 5'NH2 labeled ssDNA probe specific to the htrA gene of Orientia tsutsugamushi using carbodiimide cross-linking chemistry. The synthesized GO was characterized using UV-Vis, FTIR, and XRD. The layer-by-layer modification of the paper electrode was monitored via FE-SEM, cyclic voltammetry, and electrochemical impedance spectroscopy (EIS). The sensor response after hybridization with single-stranded genomic DNA (ssGDNA) of O. tsutsugamushi was recorded using differential pulse voltammetry (DPV). Methylene blue (1 mM in PBS buffer, pH 7.2) was used as a hybridization indicator and [Fe(CN)6]-3/-4 (2.5 mM in PBS buffer, pH 7.2) as a redox probe during electrochemical measurements. The developed DNA sensor shows excellent sensitivity (1228.4 µA/cm2/ng) and LOD (20 pg/µL) for detection of O. tsutsugamushi GDNA using differential pulse voltammetry (DPV).

Leptospira interrogans Outer Membrane Protein-Based Nanohybrid Sensor for the Diagnosis of Leptospirosis.

Leptospirosis is an underestimated tropical disease caused by the pathogenic Leptospira species and responsible for several serious health problems. Here, we aimed to develop an ultrasensitive DNA biosensor for the rapid and on-site detection of the Loa22 gene of Leptospira interrogans using a gold nanoparticle-carbon nanofiber composite (AuN/CNF)-based screen-printed electrode. Cyclic voltammetry and electrochemical impedance were performed for electrochemical analysis. The sensitivity of the sensor was 5431.74 µA/cm2/ng with a LOD (detection limit) of 0.0077 ng/µL using cyclic voltammetry. The developed DNA biosensor was found highly specific to the Loa22 gene of L. interrogans, with a storage stability at 4 °C for 180 days and a 6% loss of the initial response. This DNA-based sensor only takes 30 min for rapid detection of the pathogen, with a higher specificity and sensitivity. The promising results obtained suggest the application of the developed sensor as a point of care device for the diagnosis of leptospirosis.

Point-of-care detection of tuberculosis using magnetoresistive biosensing chip.

In this paper, a highly sensitive and specific technique based on the principle of giant magnetoresistance (GMR) has been proposed for the early stage Tuberculosis (TB) diagnostics. This GMR biosensing assay employs monoclonal antibodies against M. tuberculosis specific ESAT-6 antigen with the use of magnetic nanoparticles (MNPs) as labels. MNPs bind to the GMR sensor in presence of ESAT-6 and the binding is proportional to the ESAT-6 protein concentration leading to the change in overall resistance of GMR sensor. GMR biosensor simulation showed that ESAT-6 concentration can be detected in the range of pg/mL in comparison to the other transduction techniques available for ESAT-6 detection and further, the signal strength increased with the increase in the concentration. This work has shown that the GMR biosensing strategy is pertinent for the TB detection at the primitive phases when compared with other magnetic techniques used for TB diagnostics.

In-depth and 3-dimensional exploration of the budding yeast phosphoproteome.

Phosphorylation is one of the most dynamic and widespread post-translational modifications regulating virtually every aspect of eukaryotic cell biology. Here, we assemble a dataset from 75 independent phosphoproteomic experiments performed in our laboratory using Saccharomyces cerevisiae. We report 30,902 phosphosites identified from cells cultured in a range of DNA damage conditions and/or arrested in distinct cell cycle stages. To generate a comprehensive resource for the budding yeast community, we aggregate our dataset with the Saccharomyces Genome Database and another recently published study, resulting in over 46,000 budding yeast phosphosites. With the goal of enhancing the identification of functional phosphorylation events, we perform computational positioning of phosphorylation sites on available 3D protein structures and systematically identify events predicted to regulate protein complex architecture. Results reveal hundreds of phosphorylation sites mapping to or near protein interaction interfaces, many of which result in steric or electrostatic "clashes" predicted to disrupt the interaction. With the advancement of Cryo-EM and the increasing number of available structures, our approach should help drive the functional and spatial exploration of the phosphoproteome.

AuNPs/CNF-modified DNA biosensor for early and quick detection of O. tsutsugamushi in patients suffering from scrub typhus.

A novel approach has been developed for the detection of 56 kDa tissue-specific antigen (TSA) gene of Orientia tsutsugamushi a causative agent of scrub typhus disease. The approach was developed by immobilization of 5' NH2 labeled ssDNA probe selective to 56 kDa TSA gene, to the surface of AuNPs/CNF modified screen-printed electrode. An electrochemical response was recorded with single stranded genomic DNA (ssDNA) of O. tsutsugamushi isolated from patient sample, using cyclic voltammetry and electrochemical impedance spectroscopy. The electrode surface was characterized by Field-Emission Scanning electron microscope (FE-SEM), Fourier Transform Infrared Spectroscopy (FTIR) and Raman Spectroscopy at each step of fabrication. The DNA biosensor shows optimum response within 50-60 s at room temperature (25 ± 3 °C). The sensor shows higher sensitivity [7849 (µA/cm2)/ng DNA], fast response time (60 s), wider linear range (0.04-2.6 ng) with limit of detection of 0.02 ng/µl of ssDNA sample.

Maximized quantitative phosphoproteomics allows high confidence dissection of the DNA damage signaling network.

The maintenance of genomic stability relies on DNA damage sensor kinases that detect DNA lesions and phosphorylate an extensive network of substrates. The Mec1/ATR kinase is one of the primary sensor kinases responsible for orchestrating DNA damage responses. Despite the importance of Mec1/ATR, the current network of its identified substrates remains incomplete due, in part, to limitations in mass spectrometry-based quantitative phosphoproteomics. Phosphoproteomics suffers from lack of redundancy and statistical power for generating high confidence datasets, since information about phosphopeptide identity, site-localization, and quantitation must often be gleaned from a single peptide-spectrum match (PSM). Here we carefully analyzed the isotope label swapping strategy for phosphoproteomics, using data consistency among reciprocal labeling experiments as a central filtering rule for maximizing phosphopeptide identification and quantitation. We demonstrate that the approach allows drastic reduction of false positive quantitations and identifications even from phosphopeptides with a low number of spectral matches. Application of this approach identifies new Mec1/ATR-dependent signaling events, expanding our understanding of the DNA damage signaling network. Overall, the proposed quantitative phosphoproteomic approach should be generally applicable for investigating kinase signaling networks with high confidence and depth.

Diagnosis of scrub typhus: recent advancements and challenges.

Scrub typhus is a mite-borne, acute febrile illness caused by the bacterium Orientia tsutsugamushi. It is a re-emerging infectious disease of the tsutsugamushi triangle. Scrub typhus is transmitted through bites of contaminated chiggers (larval stage). Diagnosis of scrub typhus is challenging as its symptoms mimic with other acute febrile illnesses. Several methods are effectual for diagnosis of scrub typhus that includes enzyme-linked immunosorbent assay (ELISA), immunofluorescence assay (IFA), immunochromatographic test (ICT), Weil-Felix, polymerase chain reaction (PCR) and loop-mediated isothermal amplification (LAMP). Weil-Felix test was initially used for the diagnosis of scrub typhus in underdeveloped countries but not preferred due to a lack of both specificity and sensitivity. Other immuno-based methods like IFA and ELISA are most outrank for detection of scrub typhus due to their higher sensitivity and specificity, but not vigorous to lay bare the infection at early stages and need the convalescent sampling for verification of positive samples. On another deed, PCR based methods becoming acceptable over era due to its dexterity of early-stage diagnosis with higher specificity and sensitivity but lack its applicability in circumstances of scrub typhus due to the variegated genetic makeup of Orientia tsutsugamushi among its serotypes. The present review focused on various detection methods along with their advantages and disadvantages used in the diagnosis of scrub typhus. A comparison between available methods of diagnosis with challenges in the detection of scrub typhus is also summarized.

PlcA-based nanofabricated electrochemical DNA biosensor for the detection of Listeria monocytogenes in raw milk samples.

The electrochemical DNA biosensor has been developed for the detection of Listeria monocytogenes in raw milk samples. The electrochemical studies of the developed biosensor was recorded by cyclic voltammetry (CV) and electrochemical impedance (EI) using methylene blue (MB) and potassium ferricyanide K3Fe(CN)- 6 as redox indicators. The selectivity of the developed biosensor was demonstrated using complementary and mismatch oligonucleotide sequences. The sensitivity (S) of the developed sensor was recorded as 3461 (µA/cm2)/ng and limit of detection (LOD) was found to be 82 fg/6 µl with the regression coefficient (R 2) 0.941 using CV. The sensor was characterized by field emission scanning electron microscopy (FE-SEM). The electrode was found to be stable for six months, with only 10% loss in the initial CV current.