Prevent Disease Spread Research Articles

Serological follow-up after syphilis diagnosis in Israel.

The global incidence of syphilis is increasing. Continuity of care challenges the control of sexually transmitted diseases. In this study, we assessed the follow-up and serological decline differences between community- and hospital-diagnosed patients in Israel. A historical cohort study was conducted using the Israel National Syphilis Center (NSC) repository. Patients with a positive non-specific Venereal Disease Research Laboratory (VDRL) test between 2011 and 2020 were included. Rates of serological follow-up and serological titre decreases were compared between hospital- and community-diagnosed patients. The study included 4,445 patients, 2,596 (58.4%) were diagnosed in community clinics and 1,849 (41.6%) in hospitals. Of community-diagnosed patients, 1,957 (75.4%) performed follow-up testing, compared with 834 (51.2%) hospital-diagnosed patients (p<0.001). On multivariate analysis, the odds ratio of serology follow-up among community-diagnosed patients was 2.8 (95 per cent confidence interval (95% CI): 2.2-3.5) that of hospital-diagnosed patients. There were 1,397 (71.4%) community-diagnosed patients with serological titre decrease, compared with 626 (74.9%) hospital-diagnosed patients (p=0.03). On multivariate analysis, this difference diminished. Serological follow-up testing is suboptimal and was performed more often among patients initially diagnosed in the community compared to hospitals. Continuity of care should be improved to promote successful patient care and prevent disease spread.

Application of a composite, multi-scale COVID-19 mitigation framework: US border use-case

ABSTRACT Airborne pathogen transmission within crowded facilities can be modelled by combining several interrelated mechanisms of spread: movement of people, airflow dynamics, and aerosol dispersion. This paper describes a composite model framework combining analytical models to demonstrate the spread of an airborne pathogen in a crowded, confined space at an immigrant processing centre on the southern US border during the border crisis of March 2021. Recommendations that could reduce current COVID-19 infection rate from 11% to 6.16% at relatively low additional cost to the government are given. These recommendations could also lower the infection rate by approximately five times from 31.14% worst case from long indoor exposures down to 6.35% when immigrant processing times surge to 10 days. This work highlights the challenges of managing COVID-19 in crowded facilities, and provides quantitative decision options with potential both to slow and prevent disease spread, while lessening the economic burden on communities.

Basic Substances and Potential Basic Substances: Key Compounds for a Sustainable Management of Seedborne Pathogens

Seedborne pathogens represent a critical issue for successful agricultural production worldwide. Seed treatment with plant protection products constitutes one of the first options useful for reducing seed infection or contamination and preventing disease spread. Basic substances are active, non-toxic substances already approved and sold in the EU for other purposes, e.g., as foodstuff or cosmetics, but they can also have a significant role in plant protection as ecofriendly, safe, and ecological alternatives to synthetic pesticides. Basic substances are regulated in the EU according to criteria presented in Article 23 of Regulation (EC) No 1107/2009. Twenty-four basic substances are currently approved in the EU and some of them such as chitosan, chitosan hydrochloride, vinegar, mustard seed powder, and hydrogen peroxide have been investigated as seed treatment products due to their proven activity against fungal, bacterial, and viral seedborne pathogens. Another basic substance, sodium hypochlorite, is under evaluation and may be approved soon for seed decontamination. Potential basic substances such as essential oils, plant extracts, and ozone were currently found effective as a seed treatment for disease management, although they are not yet approved as basic substances. The aim of this review, run within the Euphresco BasicS project, is to collect the recent information on the applications of basic substances and potential basic substances for seed treatment and describe the latest advanced research to find the best application methods for seed coating and make this large amount of published research results more manageable for consultation and use.

Identification of tomato bacterial wilt severity based on hyperspectral imaging technology and spectrum Transformer network

Bacterial wilt (BW) is an essential soil-borne disease in tomato production, which seriously decreases tomato yield and quality. Accurate monitoring of tomato BW status can prevent disease spread and reduce control costs. This study proposes a method for identifying tomato BW severity based on hyperspectral imaging (HSI) technology combined with spectrum Transformer network (STNet). The STNet utilizes Transformer modules to capture the associative information of spectral data in the global range, enhancing the ability of features to represent raw spectral data. The proposed network is trained by using the transfer learning strategy, that is, a huge amount of unlabeled pixel-level spectral data are used to pre-train STNet's backbone network to improve the generalization of extracted features, and then the labeled average spectral data are used to fine-tune STNet to identify tomato BW severity. Compared with the competitive random forest, support vector machine, one-dimensional convolution neural network (1DCNN), and self-attention 1DCNN, the STNet achieved the best identification performance with an average F1 of 0.9309, an overall accuracy of 91.93%, and a kappa coefficient of 0.8903. This study verifies the feasibility of using HSI technology combined with STNet to identify tomato BW severity.

Swine industry stakeholders' perception on the use of water-based foam as an emergency mass depopulation method.

The U.S. pork supply chain is vulnerable to various internal and external threats and in need of prompt, comprehensive response plans. Under urgent circumstances, for example in the case of foreign disease incursions, swine farms will have to perform on-farm animal depopulation to prevent disease spread. Several animal depopulation methods including water-based foam (WBF) have been proposed and are under evaluation for feasibility in the field. However, the psychological/emotional impacts of applying depopulation methods for personnel managing and carrying on the tasks are not currently well understood. Thus, this study aimed to investigate WBF as an alternative for depopulation compared to existing methods approved by the American Veterinary Medical Association. Swine industry stakeholders were invited to voluntarily observe a WBF depopulation trial and to provide their self-reported perspectives before and after the observation. A survey was designed to explore key areas on expected and perceived method effectiveness, efficiency, and animal welfare considerations, as well as to evaluate short-term post-observation psychological impacts. Among 42 recruited stakeholders, 31.0% (13/42) were educators/researchers followed by animal health officials (26.2%, 11/42) and veterinarians (23.8%, 10/42), with an average of 11.7 ± 12.6 (n = 39) years of work experience. After the trial, respondents' positive perception of WBF depopulation increased specifically regarding the animal loading process being less stressful than restrained in-barn depopulation options (P = 0.003) and by the observation of fewer swine escape attempts and vocalizations than expected (P < 0.001). Respondents' positive perception of WBF also increased regarding to the time required to fill the trailer with foam, to stop hearing animal vocalization, and stop hearing animal movement, as the observed trial times were faster than their pre-observation estimates (P < 0.001). Additionally, 79.5% (31/39) of respondents agreed that the rapid destruction of animal populations had priority over animal welfare under urgent scenarios. Minor post-traumatic stress disorder-like (PTSD-like) symptoms from the observed trials were reported (26.7%, 4/15 respondents) one month after the observation. This study showed that the WBF depopulation process was perceived positively by swine stakeholders and may have limited short-term psychological impacts on personnel involved in animal depopulation.

Improved Stability and Manufacturability of Nucleocapsid Antigens for SARS-CoV2 Diagnostics through Protein Engineering.

The COVID-19 pandemic has had a significant impact on human health management. A rapid diagnosis of SARS-CoV2 at the point-of-care (POC) is critical to prevent disease spread. As a POC device for remote settings, a LFIA should not require cold-chain maintenance and should be kept at normal temperatures. Antigen stability can be enhanced by addressing instability issues when dealing with fragile components, such as proteinaceous capture antigens. This study used immunologically guided protein engineering to enhance the capture nucleocapsid (NP) antigen stability of SARS-CoV2. A search of the IEDB database revealed that antibodies detecting epitopes are almost uniformly distributed over NP1-419. In contrast, N-terminal stretches of NP1-419 are theoretically more unstable than C-terminal stretches. We identified NP250-365 as a NP stretch with a low instability index and B-cell epitopes. Apart from NP1-419, two other variants (NP121-419 and NP250-365) were cloned, expressed, and purified. The degradation pattern of the proteins was observed on SDS-PAGE after three days of stability studies at -20 °C, 4 °C, and 37 °C. NP1-419 was the most degraded while NP250-365 exhibited the least degradation. Also, NP1-419, NP250-365, and NP121-419 reacted with purified antibodies from COVID-19 patient serum. Our results suggest that NP250-365 may be used as a stable capture antigen in LFIA devices to detect COVID-19.

Review on the recent infectious diseases in the State of God’s own country

The burden of communicable and non-communicable diseases is increasing in Kerala. Despite the State’s past success in keeping a variety of communicable diseases under control, the recent research of Dengue, Malaria, Leptospirosis, Hepatitis, Chikungunya and H5N1 has resulted in a marked rise in morbidity and mortality. Infectious diseases continue to be the main causes of morbidity and mortality in humans and animals with enormous healthcare costs in India. Over the past few years, Kerala, a state in the nation of India, has conflicted with nature. The nation’s diverse terrains, extreme geoclimatic variations, and unequal population distribution exhibit distinctive patterns of viral illness dispersion. The state of Kerala has faced a significant public health issue over the past decade due to the resurgence of infectious illnesses, resulting in elevated rates of both mortality and morbidity. Methodology: This review article aims to investigate and discuss epidemics that are known to have happened during the 21st century. For this purpose, the investigator has done a literature review through Google Scholar and PubMed. All articles pertaining to reported infections in the state of Kerala and factors contributing to the outbreak of an infection were chosen for inclusion in the review. Results: From a number of sources, we culled a selection of articles covering the topic of viral infections. We found that many people in the Kerala state have fallen victim to and suffered many deaths from bacterial infectious diseases like chikungunya fever, scrub typhus fever, rotavirus diarrhea, the break bone fever, Nipah virus, Kyasanur Forest Disease (KFDV), leptospirosis, COVID-19 and monkeypox in the past decade. The people of Kerala are fortunate to have access to excellent medical care, and the government has recently begun to prioritize illness prevention and control. Conclusion: This report emphasizes the Kerala’s infectious disease management strategy and the necessity for other Indian states to emulate it. States can prevent disease spread and protect residents by taking comparable steps.

A peptide nucleic acid probe-based multiplex qPCR assay for rapid and accurate detection and quantification of fish-pathogenic Edwardsiella species

Edwardsiellosis causes severe economic losses in the aquaculture industry worldwide. Accurate identification of the fish pathogenic Edwardsiella species is crucial for preventing disease spread and providing effective treatment strategies in the aquaculture industry. These species have high phenotypic and genetic similarities (> 99% in 16S rRNA sequences), which makes their differentiation challenging. In this study, we developed a multiplex real-time PCR diagnostic assay based on the single-copy DNA gyrase subunit B (gyrB) gene using a peptide nucleic acid (PNA) probe to discriminate among four fish pathogenic Edwardsiella species, E. tarda, E. piscicida, E. anguillarum, and E. ictaluri. Through phylogenetic analysis based on gyrB sequences (1462 bp), 57 Korean Edwardsiella isolates were affiliated to E. piscicida, E. anguillarum, and E. tarda, accounting for host and geographical origin specificity. The assay targeted a conserved region in gyrB, and designed four probes, each capable of distinguishing among the four Edwardsiella species, even in cases of 1–3 nucleotide mismatch, based on differences in melting temperature. The assay exhibited high specificity and sensitivity, with reaction efficiency in the range 85–100% and a reliable quantifiable limit of 102 copies per reaction for all fluorescence signals. In addition, it could detect and quantify the four species, even in mixed infections, allowing accurate identification within 2 h in a single reaction. This PNA probe-based multiplex qPCR assay could be a practical and reliable diagnostic tool in the field and provide correct taxonomic assignment for further research on the widened host range and niche, pathogenicity, and susceptibility of each Edwardsiella species, to help establish appropriate treatment and vaccine strategies.

Nurses' Experiences of Care in Portuguese Nursing Homes during the COVID-19 Pandemic: A Focus Group Study.

The COVID-19 pandemic has had a considerable influence on long-term care facilities, exposing the shortcomings of nursing homes in implementing recommendations by health authorities. It also emphasizes the need for a nursing management model customized to the vulnerable status of residents, organizational demands, and occupational nursing requirements. We aimed to characterize the perspectives of nurses who have experienced COVID-19 in nursing homes regarding measures implemented to avoid or manage outbreaks in that environment. An interview was conducted with a focus group following the consolidated Criteria for Reporting Qualitative research guidelines. Data analysis was performed using WebQDA software following a thematic category orientation. Eight Portuguese nurses working in nursing homes from the country's central area participated in this study. We identified three major significant areas for long-term care respiratory outbreak management: strategic (policy, staffing, and resources); tactical (training, organization, engagement, and supervision); and operational planning (vigilance, prevention of disease spread, and family involvement). From the participants' view, the management of COVID-19 in nursing homes must be highly supportive and responsive, offering resources to control risks, supporting residents' care, and ensuring the safety and well-being of residents and staff members. Saturation was not reached; thus, further research is needed in this area.

Characteristics of VOCs and Assessment of Emission Reduction Effect During the Epidemic Lockdown Period in Shenzhen Urban Area

To prevent disease spreading during the COVID-19 epidemic, Shenzhen adopted lockdown measures in March of 2022. This provided an opportunity to study the response of changes in anthropogenic volatile organic compounds (AVOCs) in Shenzhen to emission reduction and to evaluate the effectiveness of current emission reduction measures. This study analyzed the variety of AVOCs before, during, and after the epidemic lockdown based on the online observation data of pollutants at Lianhua Station in Shenzhen from March 7, 2022 to March 27, 2022. Additionally, the sensitivity of ozone formation and the assessment of the reduction effect of precursors was conducted by an observation based model(OBM). The results showed that:affected by regional influences and the interference of meteorological conditions, the average value of AVOCs in Shenzhen urban areas did not drop significantly during the lockdown period compared to that before the lockdown. However, the peak of AVOCs at the morning peak time under the influence of "sea and land wind" during the epidemic lockdown period dropped by 46% on average compared with that during the non-lockdown period, and the aromatic hydrocarbon component dropped the most by 59%. Additionally, under the influence of continuous easterly wind, or during the accumulation and increase of AVOCs affected by regional transmission, aromatic components also decreased by an average of 25% and 21%, respectively. During the lockdown period of the epidemic in Shenzhen, the O3 formation in urban areas was still AVOCs-limited. Increasing the emission reduction ratio of AVOCs was the most effective measure to reduce O3 in the short term. In order to ensure the effectiveness of emission reduction, it was recommended that the coordinated emission reduction ratio of AVOCs and NOx should be greater than 1:2. It was only possible to enter the downward channel of O3 if the deep emission reduction was more than 60%. This study revealed that the emission reduction of AVOCs during the morning traffic peak during the epidemic lockdown period was conducive to inhibiting the formation of O3, whereas the control of NOx would promote it. Strengthening the control of local aromatic hydrocarbon components during the regional impact process could also significantly reduce O3 production. At this stage, Shenzhen should strengthen the management and control of industrial solvents, especially to reduce the aromatic hydrocarbon components in the solvent source that have a greater impact on the generation of O3. Further, Shenzhen should continue to promote the reform of the energy structure of motor vehicles to reduce the emission of VOCs in fuel combustion.

Multipatch stochastic epidemic model for the dynamics of a tick-borne disease

Spatial heterogeneity and migration of hosts and ticks have an impact on the spread, extinction and persistence of tick-borne diseases. In this paper, we investigate the impact of between-patch migration of white-tailed deer and lone star ticks on the dynamics of a tick-borne disease with regard to disease extinction and persistence using a system of Itô stochastic differential equations model. It is shown that the disease-free equilibrium exists and is unique. The general formula for computing the basic reproduction number for all patches is derived. We show that for patches in isolation, the basic reproduction number is equal to the largest patch reproduction number and for connected patches it lies between the minimum and maximum of the patch reproduction numbers. Numerical simulations for a two-patch deterministic and stochastic differential equation models are performed to illustrate the dynamics of the disease for varying migration rates. Our results show that the probability of eliminating or minimizing the disease in both patches is high when there is no migration unlike when it is present. The results imply that the probability of disease extinction can be increased if deer and tick movement are controlled or even prohibited especially when there is an outbreak in one or both patches since movement can introduce a disease in an area that was initially disease-free. Thus, screening of infectives in protected areas such as deer farms, private game parks or reserves, etc. before they migrate to other areas can be one of the intervention strategies for controlling and preventing disease spread.

Genomic Insights Into the Evolution and Demographic History of the SARS-CoV-2 Omicron Variant: Population Genomics Approach.

A thorough understanding of the patterns of genetic subdivision in a pathogen can provide crucial information that is necessary to prevent disease spread. For SARS-CoV-2, the availability of millions of genomes makes this task analytically challenging, and traditional methods for understanding genetic subdivision often fail. The aim of our study was to use population genomics methods to identify the subtle subdivisions and demographic history of the Omicron variant, in addition to those captured by the Pango lineage. We used a combination of an evolutionary network approach and multivariate statistical protocols to understand the subdivision and spread of the Omicron variant. We identified subdivisions within the BA.1 and BA.2 lineages and further identified the mutations associated with each cluster. We further characterized the overall genomic diversity of the Omicron variant and assessed the selection pressure for each of the genetic clusters identified. We observed concordant results, using two different methods to understand genetic subdivision. The overall pattern of subdivision in the Omicron variant was in broad agreement with the Pango lineage definition. Further, 1 cluster of the BA.1 lineage and 3 clusters of the BA.2 lineage revealed statistically significant signatures of selection or demographic expansion (Tajima's D<-2), suggesting the role of microevolutionary processes in the spread of the virus. We provide an easy framework for assessing the genetic structure and demographic history of SARS-CoV-2, which can be particularly useful for understanding the local history of the virus. We identified important mutations that are advantageous to some lineages of Omicron and aid in the transmission of the virus. This is crucial information for policy makers, as preventive measures can be designed to mitigate further spread based on a holistic understanding of the variability of the virus and the evolutionary processes aiding its spread.

Application of Convolutional Neural Networks for COVID-19 Detection in X-ray Images Using InceptionV3 and U-Net.

COVID-19 has expanded overall across the globe after its initial cases were discovered in December 2019 in Wuhan-China. Because the virus has impacted people's health worldwide, its fast identification is essential for preventing disease spread and reducing mortality rates. The reverse transcription polymerase chain reaction (RT-PCR) is the primary leading method for detecting COVID-19 disease; it has high costs and long turnaround times. Hence, quick and easy-to-use innovative diagnostic instruments are required. According to a new study, COVID-19 is linked to discoveries in chest X-ray pictures. The suggested approach includes a stage of pre-processing with lung segmentation, removing the surroundings that do not provide information pertinent to the task and may result in biased results. The InceptionV3 and U-Net deep learning models used in this work process the X-ray photo and classifies them as COVID-19 negative or positive. The CNN model that uses a transfer learning approach was trained. Finally, the findings are analyzed and interpreted through different examples. The obtained COVID-19 detection accuracy is around 99% for the best models.

Identification of disease propagation paths in two-layer networks

To determine the path of disease in different types of networks, a new method based on compressive sensing is proposed for identifying the disease propagation paths in two-layer networks. If a limited amount of data from network nodes is collected, according to the principle of compressive sensing, it is feasible to accurately identify the path of disease propagation in a multilayer network. Experimental results show that the method can be applied to various networks, such as scale-free networks, small-world networks, and random networks. The impact of network density on identification accuracy is explored. The method could be used to aid in the prevention of disease spread.

Broader functions of TIR domains in Arabidopsis immunity

TIR domains are NAD-degrading enzymes that function during immune signaling in prokaryotes, plants, and animals. In plants, most TIR domains are incorporated into intracellular immune receptors termed TNLs. In Arabidopsis, TIR-derived small molecules bind and activate EDS1 heterodimers, which in turn activate RNLs, a class of cation channel-forming immune receptors. RNL activation drives cytoplasmic Ca2+ influx, transcriptional reprogramming, pathogen resistance, and host cell death. We screened for mutants that suppress an RNL activation mimic allele and identified a TNL, SADR1. Despite being required for the function of an autoactivated RNL, SADR1 is not required for defense signaling triggered by other tested TNLs. SADR1 is required for defense signaling initiated by some transmembrane pattern recognition receptors and contributes to the unbridled spread of cell death in lesion simulating disease 1. Together with RNLs, SADR1 regulates defense gene expression at infection site borders, likely in a non-cell autonomous manner. RNL mutants that cannot sustain this pattern of gene expression are unable to prevent disease spread beyond localized infection sites, suggesting that this pattern corresponds to a pathogen containment mechanism. SADR1 potentiates RNL-driven immune signaling not only through the activation of EDS1 but also partially independently of EDS1. We studied EDS1-independent TIR function using nicotinamide, an NADase inhibitor. Nicotinamide decreased defense induction from transmembrane pattern recognition receptors and decreased calcium influx, pathogen growth restriction, and host cell death following intracellular immune receptor activation. We demonstrate that TIR domains can potentiate calcium influx and defense and are thus broadly required for Arabidopsis immunity.

MosChito rafts as effective and eco-friendly tool for the delivery of a Bacillus thuringiensis-based insecticide to Aedes albopictus larvae

Adult mosquito females, through their bites, are responsible for the transmission of different zoonotic pathogens. Although adult control represents a pillar for the prevention of disease spread, larval control is also crucial. Herein we characterized the effectiveness of a suitable tool, named “MosChito raft”, for the aquatic delivery of a Bacillus thuringiensis var. israelensis (Bti) formulate, a bioinsecticide active by ingestion against mosquito larvae. MosChito raft is a floating tool composed by chitosan cross-linked with genipin in which a Bti-based formulate and an attractant have been included. MosChito rafts (i) resulted attractive for the larvae of the Asian tiger mosquito Aedes albopictus, (ii) induced larval mortality within a few hours of exposure and, more importantly, (iii) protected the Bti-based formulate, whose insecticidal activity was maintained for more than one month in comparison to the few days residual activity of the commercial product. The delivery method was effective in both laboratory and semi-field conditions, demonstrating that MosChito rafts may represent an original, eco-based and user-friendly solution for larval control in domestic and peri-domestic aquatic habitats such as saucers and artificial containers in residential or urban environments.

COVID-19 spread algorithm in the international airport network-DetArpds.

Due to COVID-19, the spread of diseases through air transport has become an important issue for public health in countries globally. Moreover, mass transportation (such as air travel) was a fundamental reason why infections spread to all countries within weeks. In the last 2 years in this research area, many studies have applied machine learning methods to predict the spread of COVID-19 in different environments with optimal results. These studies have implemented algorithms, methods, techniques, and other statistical models to analyze the information in accuracy form. Accordingly, this study focuses on analyzing the spread of COVID-19 in the international airport network. Initially, we conducted a review of the technical literature on algorithms, techniques, and theorems for generating routes between two points, comprising an analysis of 80 scientific papers that were published in indexed journals between 2017 and 2021. Subsequently, we analyzed the international airport database and information on the spread of COVID-19 from 2020 to 2022 to develop an algorithm for determining airport routes and the prevention of disease spread (DetARPDS). The main objective of this computational algorithm is to generate the routes taken by people infected with COVID-19 who transited the international airport network. The DetARPDS algorithm uses graph theory to map the international airport network using geographic allocations to position each terminal (vertex), while the distance between terminals was calculated with the Euclidian distance. Additionally, the proposed algorithm employs the Dijkstra algorithm to generate route simulations from a starting point to a destination air terminal. The generated routes are then compared with chronological contagion information to determine whether they meet the temporality in the spread of the virus. Finally, the obtained results are presented achieving a high probability of 93.46% accuracy for determining the entire route of how the disease spreads. Above all, the results of the algorithm proposed improved different computational aspects, such as time processing and detection of airports with a high rate of infection concentration, in comparison with other similar studies shown in the literature review.

Assessment of Documented Vaccination of Adolescent Schoolchildren in Various Cities of Russian Federation

Epidemiological surveillance of preventive vaccinations implementation is the most crucial component in the immunoprophylaxis organization. Assessment of documented vaccination coverage indicators allows to determine the quality of routine preventive vaccination and indirectly evaluate the possible state of population immunity to vaccine preventable diseases. Continuous quality control of routine vaccination, therefore, is a component of the system for epidemic management of infectious diseases. Specific decisions should be based on its results to improve preventive vaccination quality.Сomparative analysis of the vaccination history in adolescents (studying in schools in large cities of different federal districts of Russian Federation) and recommended national immunisation schedule allowed to identify widespread systemic mistakes of vaccination status. These issues led to the uprise and spread of vaccine preventable diseases. The study results confirmed the topicality of awareness-raising activities among medical staff working on preventive vaccination. Moreover, long-standing need of vaccination schemes correction is also important through development of medical technology aimed on improvement of catch-up vaccination approach.

SILKBOT : Orchestrating Silk Symphony - A Comprehensive Approach towards Silk Production and Enhancement in Sericulture Applications

In this paper, the orchestrating of the silk symphony - a comprehensive approach towards silk production and enhancement in sericulture applications is presented. The final year project work undertaken by us involves the design &amp; development of a silkbot, which will give us the comprehensive approach towards Silk Production and Enhancement in the quality of silk produced. The aim of the project is to revolutionize silk production through a comprehensive approach encompassing four critical components that are Segregation of cocoon based on gender, Identification of diseased cocoons to curb disease spread and enhance yield, maintenance of ideal temperature conditions for the enhanced growth of cocoons and Maintenance of optimal feeding conditions tailored to cocoon growth and needs. Cocoon Segregation System - Focuses on the segregation of cocoons based on their genders which will be ensuring optimal silk production and controlled environment for the female cocoon who produce more raw silk than male and prevent Disease Spread. Diseased Cocoon Identification - Aims to implement an automated system for the identification of diseased cocoons, mitigating the spread of diseases that can significantly impact yield and harvest rates. Temperature Control System - Emphasizes the maintenance of ideal temperature conditions for the enhanced growth of Silkworms, optimizing the quality and quantity of silk production. Optimized Feeding System -Tailored feeding based on the growth stages and nutritional needs of the Silkworms for optimal silk production. The work carried out is the seventh semester main-project by the students of Electronics &amp; Communication Engineering under the guidance of the faculties supervision (guide).

Nanozyme-catalyzed cascade reaction enables a highly sensitive detection of live bacteria.

The accurate and timely detection of bacteria is critically important for human health as it helps to determine the original source of bacterial infections and prevent disease spread. Herein, gold nanoparticles (AuNPs) were synthesized using polyoxometalates (POMs) as the stabilizing agent. Since AuNPs have glucose oxidase (GOx)-like activity and POMs possess peroxidase (HRP)-like activity, the as-prepared Au@POM nanoparticles have double enzyme-like activities and facilitate cascade reaction. As known, glucose is required as an energy resource during bacterial metabolism, the concentration of glucose decreases with the increase of bacteria content in a system with bacteria and glucose. Therefore, when we use Au@POM nanozymes to trigger the cascade catalysis of glucose and 3,3',5,5'-tetramethylbenzidine (TMB), the concentration of glucose and bacteria can be sensitively detected using the absorbance intensity at 652 nm in the visible spectrum. As demonstration, S. aureus and E. coli were used as model bacteria. The experimental results show that the present method has a good linear relationship in the bacterial concentration range of 1 to 7.5 × 107 colony-forming units (CFU) mL-1 with a detection limit of 5 CFU mL-1. This study shows a great promise of nanozyme cascade reactions in the construction of biosensors and clinical detections.