Severe Outbreaks Research Articles

Application of Reverse Vaccinology and Immunoinformatics to Design a Multitope Vaccine against Gastrointestinal Cancer-inducing Cryptosporidium Parvum

Cryptosporidium parvum (C. parvum) is an apicomplexan protozoan known as a frequent cause of diarrhea. Because of its severe outbreaks and the association with different types of gastrointestinal cancers, it became an urgent need to develop effective solutions against that parasite. In the current study, the complete proteome of C. parvum was analyzed, and after applying several filtration steps, two proteins, namely Glycoprotein 60 (gp40/15) and thrombospondin-related adhesive protein (TRAP C-1), were selected as the protein candidates for epitope prediction. Next, CTL, HTL and BCL epitopes of each protein candidate were defined, and the best epitopes of each category were assembled alongside suitable linkers and adjuvants to initiate a potential multitope vaccine construct finally. That construct was evaluated for several properties, including its antigenicity, allergenicity, stability, secondary and tertiary structure, and the ability of that 3D predicted model to bind to TLR4. Furthermore, the stability of the constructed vaccine ligand in the TLR4 receptor was deeply investigated through a molecular dynamics simulation. The current study describes the stages of the multitope construct design. It demonstrates the results of that construct computational evaluation where the generated scores support the nomination of that potential vaccine as a solution for C. parvum infection, and further wet lab experiments are required to validate our current findings.

Food and Waterborne Cryptosporidiosis from a One Health Perspective: A Comprehensive Review

A sharp rise in the global population and improved lifestyles has led to questions about the quality of both food and water. Among protozoan parasites, Cryptosporidium is of great importance in this regard. Hence, Cryptosporidium’s associated risk factors, its unique characteristics compared to other protozoan parasites, its zoonotic transmission, and associated economic losses in the public health and livestock sectors need to be focused on from a One Health perspective, including collaboration by experts from all three sectors. Cryptosporidium, being the fifth largest food threat, and the second largest cause of mortality in children under five years of age, is of great significance. The contamination of vegetables, fresh fruits, juices, unpasteurized raw milk, uncooked meat, and fish by Cryptosporidium oocysts occurs through infected food handlers, sewage-based contamination, agricultural effluents, infected animal manure being used as biofertilizer, etc., leading to severe foodborne outbreaks. The only Food and Drug Administration (FDA)-approved drug, Nitazoxanide (NTZ), provides inconsistent results in all groups of patients, and currently, there is no vaccine against it. The prime concerns of this review are to provide a deep insight into the Cryptosporidium’s global burden, associated water- and foodborne outbreaks, and some future perspectives in an attempt to effectively manage this protozoal disease. A thorough literature search was performed to organize the most relevant, latest, and quantified data, justifying the title. The estimation of its true burden, strategies to break the transmission pathways and life cycle of Cryptosporidium, and the search for vaccine targets through genome editing technology represent some future research perspectives.

Pathogen Composition and Fungicide Sensitivity in Rice Spikelet Rot Disease.

Rice spikelet rot disease (RSRD) is an emerging threat to rice crops, with sporadic but severe outbreaks in China in recent years. The composition of its pathogenic fungi has not been consistently identified, and chemical control methods remain unclear. This study aims to characterize the pathogen species responsible for RSRD and develop effective control strategies. Regional variations in disease symptoms and pathogen compositions were analyzed, which led to the identification of six novel pathogens, including Fusarium tanahbumbuense, Alternaria gaisen, Curvularia verruculosa, Curvularia brachyspora, Curvularia muehlenbeckiae, and Curvularia hominis. The pathogenic composition of RSRD exhibited considerable variation across different latitudes within China. Specifically, Alternaria spp. predominated in the Heilongjiang and Liaoning Provinces. Whereas Fusarium spp. and Curvularia spp. were more prevalent in the Hainan and Fujian Provinces. In contrast, Fusarium spp. and Alternaria spp. were the dominant pathogens in the Anhui and Jiangsu Provinces. Furthermore, an assessment of the sensitivity of these predominant pathogens to four chemical compounds was conducted, which led to the identification of potential fungicides for effective disease control. This research provides valuable insights into the pathogenic profile of RSRD across different regions and offers strategic recommendations for fungicide-based management of the disease.

Zambia's battle against cholera outbreaks and the path to public health resilience: a narrative review

ABSTRACT In Zambia, cholera has been a persistent public health concern for decades, mainly attributed to inadequate sanitation and restricted access to clean water in some parts of the country. The literature was collected from PubMed, Google Scholar, and public health organization websites, focusing on cholera outbreaks in Zambia since 2000. Key search terms included ‘cholera prevention’ and ‘Zambia outbreaks.’ A total of 30 articles were analyzed to assess public health strategies and identify gaps for future planning. Periodic outbreaks of cholera have characterized Zambia's history by significant fluctuations in case numbers and fatalities since 1977. Notably, the years 1993, 1999, 2003/2004, 2005/2006, 2010, 2017/2018, and the most recent outbreak from October 2023 to February 2024 have marked significant episodes in the country's struggle against this waterborne disease. This narrative review examines the recurrent outbreaks of cholera in Zambia to understand the recent outbreak's extraordinary spread and severity in the context of public health resilience. The most recent outbreak with staggering 19,719 cases and 682 deaths, underscores the unprecedented scale and severity of the current public health emergency. The findings highlight the need for a holistic public health approach that prioritizes resilience in disease prevention.

Investigating a severe acute malnutrition outbreak in Dubti District, Awsiresu Zone, Afar Region, Northeast Ethiopia (2022)

Investigating a severe acute malnutrition outbreak in Dubti District, Awsiresu Zone, Afar Region, Northeast Ethiopia (2022)

PANoptosis Regulation in Reservoir Hosts of Zoonotic Viruses

Zoonotic viruses originating from reservoir hosts, such as bats and birds, often cause severe illness and outbreaks amongst humans. Upon zoonotic virus transmission, infected cells mount innate immune responses that include the activation of programmed cell death pathways to recruit innate immune cells to the site of infection and eliminate viral replication niches. Different inflammatory and non-inflammatory cell death pathways, such as pyroptosis, apoptosis, necroptosis, and PANoptosis can undergo concurrent activation in humans leading to mortality and morbidity during zoonosis. While controlled activation of PANoptosis is vital for viral clearance during infection and restoring tissue homeostasis, uncontrolled PANoptosis activation results in immunopathology during zoonotic virus infections. Intriguingly, animal reservoirs of zoonotic viruses, such as bats and birds, appear to have a unique immune tolerance adaptation, allowing them to host viruses without succumbing to disease. The mechanisms facilitating high viral tolerance in bats and birds are poorly understood. In this perspective review, we discuss the regulation of PANoptotic pathways in bats and birds and indicate how they co-exist with viruses with mild clinical signs and no immunopathology. Understanding the PANoptotic machinery of bats and birds may thus assist us in devising strategies to contain zoonotic outbreaks amongst humans.

Quantifying social media predictors of violence during the 6 January US Capitol insurrection using Granger causality.

Protests involving brute force are growing in number and are viewed as a likely source of increased collective violence in industrialized nations. Yet, our scientific understanding of how violent protests are related to a leader's social media communications during protests remains nascent. Here, we analyse new data from the 6 January 'march on the US Capitol' to quantify the links between leadership, social media and levels of violence. Using data on thousands of live footage videos, Trump's tweets and rally speech, other rally speeches and #StopTheSteal tweets, we apply Granger regression methods to analyse the links between former President Trump's tweets, #StopTheSteal tweets, rally speeches and the severity and duration of outbreaks of violence and weapons use during the riot. We find that Trump's tweets predict bursts in rioters' levels and duration of violence and weapons use. Trump's tweets also predict changes in the volume and sentiments of #StopTheSteal tweets, which in turn explain additional variance in levels of violence and weapons use over the course of the riot. Our findings reveal new patterns of behaviour that link an authority figure's online behaviour during a protest and the shift from peaceful protesting to violence.

From emergence to endemicity of highly pathogenic H5 avian influenza viruses in Taiwan

A/goose/Guangdong/1/96-like (GsGd) highly pathogenic avian influenza (HPAI) H5 viruses cause severe outbreaks in poultry when introduced. Since emergence in 1996, control measures in most countries have suppressed local GsGd transmission following introductions, making persistent transmission in domestic birds rare. However, geographical expansion of clade 2.3.4.4 sublineages has raised concern about establishment of endemic circulation, while mechanistic drivers leading to endemicity remain unknown. We reconstructed the evolutionary history of GsGd sublineage, clade 2.3.4.4c, in Taiwan using a time-heterogeneous rate phylogeographic model. During Taiwan’s initial epidemic wave (January 2015 - August 2016), we inferred that localised outbreaks had multiple origins from rapid spread between counties/cities nationwide. Subsequently, outbreaks predominantly originated from a single county, Yunlin, where persistent transmission harbours the trunk viruses of the sublineage. Endemic hotspots determined by phylogeographic reconstruction largely predicted the locations of re-emerging outbreaks in Yunlin. The transition to endemicity involved a shift to chicken-dominant circulation, following the initial bidirectional spread between chicken and domestic waterfowl. Our results suggest that following their emergence in Taiwan, source-sink dynamics from a single county have maintained GsGd endemicity up until 2023, pointing to where control efforts should be targeted to eliminate the disease.

New emerging Pseudomonads as causal agents of bean blight disease

Common bean (Phaseolus vulgaris) production is negatively affected by several bacterial plant diseases. A severe outbreak of bean blight was observed in the nine major bean-producing provinces of Iran during 2021–2022. Necrotic spots were observed on leaves which become necrotic with chlorosis beyond it. One hundred-sixty bacterial strains with a greyish-white colony appearance were consistently isolated from the one-hundred eighteen symptomatic bean leaf, pod, seed and root samples on nutrient agar. All strains were screened for their ability to cause disease bean leaves among which 134 strains induced chlorosis three days after inoculation on bean leaves of cv. Yaghoot followed by necrotic spots on the inoculated sites one week after inoculation. The pathogenic strains clustered in three groups based on phenotypic characters and multilocus sequencing analyses. Three housekeeping genes including gyrB, rpoB, and rpoD of representative strains were partially sequenced. In the phylogenetic tree based on concatenated sequences of these three genes or each gene individually, the strains were divided into three clusters each with high bootstrap support. The first group of the strains clustered with Pseudomonas simiae CCUG 50988T. This is the first report of this species as causal agent of bean blight. The second group clustered close to Pseudomonas alloputida NMI5768T which apparently belong to a new species. The third group clustered in a separate clade in Pseudomonas chlororaphis species which belongs to a new subspecies based on pathogenicity on bean, phenotypic characters, sequences of five housekeeping genes which named as subsp. phaseoli subsp. nov. with the type strain UT-M315.

Assessing the validity of social media in fighting COVID-19 in Africa

The severe outbreak of the COVID-19 pandemic has had a significant impact on global health, the economy, and society as a whole. To this effect, various measures both national and international were taken to respond to the pandemic. Among these measures was the rapid involvement of social media which played a vital role in the context of information dissemination, coordination of medical resources, promotion of public health campaigns, and population management and disease tracing. Besides these facilities put forward by social media, there were some weaknesses like misinformation, lack of guidance, and information leakage. Based on these numerous controversies brought about by social media during the pandemic periods, we aim to examine in this study the socio-economic effect of social media in the fight against Pandemics with particular attention on the case of the COVID-19 outbreak in Africa. Using Driscoll and Kraay's fixed effects and the Lewbel-2SLS estimators on 30 African countries, the results reveal that social media in Africa through the penetration rate of Facebook, Twitter, Instagram, Pinterest, and YouTube contribute significantly in disseminating COVID-19 in Africa. The findings equally reveal the mixed effect of other determinants of COVID-19 in this nexus. While Diabetes prevalence, the proportion of people aged 65 + , and population density contribute to the increased spread of the disease, GDP per capita and Hand Washing facilities instead prove a reducing effect of the disease. Sensitivity analysis reveals that this effect is homogenous for regional considerations of the overall sample. Based on this, appropriate suggestions are made to the various governments regarding the use of social media to prevent pandemics in the future.

Epidemiological analysis of event-based surveillance data of Crimean-Congo Hemorrhagic Fever (CCHF) outbreaks across Balochistan Province, Pakistan, from 2000 to August 2021

Background Crimean-Congo hemorrhagic fever (CCHF) is endemic in Balochistan, caused by the Bunyaviridae family’s tick-borne virus (Nairovirus). The CCHF virus leads to severe viral hemorrhagic fever outbreaks with a fatality rate of 10–40%. This study aims to describe the epidemiological trend of CCHF in Balochistan and provide recommendations for controlling current and future outbreaks. Methods A descriptive approach was adopted for data analysis, utilizing the standard case definition of the Vector-Borne Diseases (VBD) program. “Any person of any age and gender residing in Balochistan from 2000 until August 10, 2021, presenting with the acute onset of illness, featuring a high-grade fever (38.5°C) persisting for more than 3 days but less than 10 days. Individuals should also exhibit any two of the following symptoms: hemorrhagic or purpuric rash, nosebleed, blood in vomit/sputum/stool, or other hemorrhagic symptoms. Moreover, there should be no known predisposing factors for hemorrhagic manifestations, and individuals must have had contact with a confirmed patient or engaged in handling animals and raw animal products.” The study covered cases identified from 2000 to August 10, 2021, and the descriptive study was conducted at the Provincial Disease Surveillance and Response Unit (PDSRU) in Quetta. Frequencies were calculated, and Excel 2016 was used to generate tables and graphs. Results Based on the case definition, 1418 laboratory-confirmed cases of CCHF were identified out of 2542 reported cases from 2000 to August 10, 2021. Most cases (89%, n = 1262) were found to be males. The case fatality rate increased from 5% to 13% over the last decade. The highest number of CCHF cases occurred in 2017 (n = 172), followed by 2005 (n = 108) and 2004 (n = 107). Direct animal contact was reported in 61% of cases, with 22% being butchers and farmers each. CCHF poses a significant public health issue in Balochistan. Conclusion This study provides a detailed overview of CCHF in Balochistan over the last 21 years, recommending the declaration of CCHF as a public health emergency. Establishing a comprehensive tick surveillance system, ecological studies, and health education sessions in collaboration with the livestock department is crucial to prevent future outbreaks.

How increasing temperature affects the innate immune system of sea urchin Paracentrotus lividus (Lamarck, 1816) reared in a RAS system

The purple sea urchin, Paracentrotus lividus, is the most exploited and economically important in Southern Europe due to the high value of its gonads. Temperature generally affects several physiological functions of marine invertebrates and the ocean warming has been linked to increasing frequency and severity of disease outbreaks in several echinoderms. Sea urchins have an innate immune system consisting of coelomocytes, the cellular components responsible for the immune response, supported by proteases and lysozymes. The present study aimed to investigate the effect of increasing seawater temperature on the immunological response of P. lividus. In this experiment, the animals were exposed to an increase in temperature up to 24 °C for 36 days, after which cellular and humoral immunity parameters were measured. The number of coelomocytes in the animals increased with the temperature rise, mainly the phagocytes and the colourless granulocytes. In the humoral response of the animals, only the concentration of lysozyme responded to the increase in temperature.

Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States.

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here, we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection ynamics, presumably via heterosubtypic cross-immunity.

Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here, we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997—2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection ynamics, presumably via heterosubtypic cross-immunity.

Epidemiological Analysis of Foot and Mouth Disease (FMD) Outbreak in 2014 in Sri Lanka

Sri Lanka faced a massive Foot and Mouth Disease (FMD) outbreak in 2014, which was initiated in Jaffna district in December 2013, and lasted for a period of more than a year, until January 2015. The disease spread throughout the country, affecting 68895 domestic animals, and causing 2007 deaths. The aim of this study was to epidemiologically analyze the data of 2014 FMD outbreak in order to understand the pattern and determinants of the massive disease distribution. Data were collected regarding the number of cases and deaths in relation to the time and location. Data in Disease Outbreak Reports, Follow-up Reports, Disease Investigation Reports and Laboratory Investigation Reports were reviewed, and descriptive and simple statistical analyses were carried out concerning the 57 epidemiological week study period. Disease Incidence, Period Prevalence, Mortality Rate, and Case Fatality Ratio of the disease were determined to be 68895, 6.11%, 0.18% and 2.91%, respectively. Seasonal animal movements and unauthorized livestock transportation appeared to be the main causes for the extensive spreading of the disease, while inadequate vaccination and poor awareness seemingly facilitated the development of three epidemic curves during the outbreak period. Newly identified causative agent, the sub-lineage O/ME-SA/Ind-2001d has led to a more severe FMD outbreak in 2014 compared to the previous outbreaks occurred in Sri Lanka.

A systematic review of epidemiological modelling in response to lumpy skin disease outbreaks.

Lumpy skin disease (LSD) is an infectious disease currently spreading worldwide and poses a serious global threat. However, there is limited evidence and understanding to support the use of models to inform decision-making in LSD outbreak responses. This review aimed to identify modelling approaches that can be used before and during an outbreak of LSD, examining their characteristics and priorities, and proposing a structured workflow. We conducted a systematic review and identified 60 relevant publications on LSD outbreak modelling. The review identified six categories of question to be addressed following outbreak detection (origin, entry pathway, outbreak severity, risk factors, spread, and effectiveness of control measures), and five analytical techniques used to address them (descriptive epidemiology, risk factor analysis, spatiotemporal analysis, dynamic transmission modelling, and simulation modelling). We evaluated the questions each analytical technique can address, along with their data requirements and limitations, and accordingly assigned priorities to the modelling. Based on this, we propose a structured workflow for modelling during an LSD outbreak. Additionally, we emphasise the importance of pre-outbreak preparation and continuous updating of modelling post-outbreak for effective decision-making. This study also discusses the inherent limitations and uncertainties in the identified modelling approaches. To support this workflow, high-quality data must be collected in standardised formats, and efforts should be made to reduce inherent uncertainties of the models. The suggested modelling workflow can be used as a process to support rapid response for countries facing their first LSD occurrence and can be adapted to other transboundary diseases.

Mass mortality associated with carpione rhabdovirus in golden pompano (Trachinotus ovatus) in China: First report

From August to November 2023, a severe epizootic outbreak occurred in an offshore cultured golden pompano (Trachinotus ovatus) population in Zhanjiang City, Guangdong Province, China, resulting in a cumulative mortality rate of 65–82 %. The diseased fish showed clinical signs of lethargy, anorexia, whirling movements, and hemorrhage at the base of the fins and in the upper and lower jaws before mass mortality. A rhabdovirus strain, designated as CARPV2023, was successfully isolated using fathead minnow (FHM) cells. The cytopathic effects of the tissue filtrate from the diseased golden pompano on FHM and epithelioma papulosum cyprini (EPC) cell monolayers were characterized by rounded cells, grape-like cluster formation, detachment, and lysis. Histopathology revealed congestion, hemorrhage, and necrosis in the spleen, liver, trunk kidney, and intestinal tissues of naturally and experimentally infected golden pompanos. Electron microscopy showed that bullet-shaped viral particles, measuring 183.5–217.6 nm in length and 57.3–82.7 nm in width, budded from the cell membrane or aggregated around the infected FHM cells. The virus remained stable for 7 d at 4–33 °C and replicated optimally at 28 °C. Whole-genome sequencing and subsequent phylogenetic analysis further indicated that the carpione rhabdovirus (CARPV)2023 strain is a new carpione rhabdovirus, and is related to novirhabdoviruses, however, is thus far unclassified. A specific nested reverse transcription-polymerase chain reaction assay confirmed the presence of CARPV in the affected golden pompano. Significantly higher mortality was observed in challenged golden pompanos than that in the controls through intraperitoneal injection and immersion infection. Fluorescence in situ hybridization showed showed positive reactions for RNA in multiple tissues (liver, spleen, trunk kidney, brain, heart, gill, and muscle) from infected fish. The highest expression level was confirmed in the spleen through qPCR. This is the first study to report natural CARPV infections in marine fish.

Epidemiology of COVID-19 in Berlin-Neukölln nursing homes

BackgroundThe COVID-19 pandemic has affected various urban population groups in different ways. Earlier studies have shown that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disproportionally impacts nursing home residents by increasing morbidity and mortality following viral exposure. However, little is known about the epidemiology of this disease in detail. Therefore, the objective of this study is to analyze the development of the COVID-19 pandemic in 14 nursing homes across Berlin-Neukölln, Germany, during pandemic waves 1 to 5 (Feb 2020 - May 2022). MethodsReporting data to the Neukölln Department of Public Health on COVID-19 cases in connection with nursing homes were extracted from the SORMAS database. The case fatality rates (CFRs) and odds ratios (ORs) of demographic parameters, prevalent variants of concern (VOCs) and vaccine availability were calculated. In addition, the temporal course in waves 1–5 in Neukölln and the relevant government measures were examined. ResultsData collected from nursing homes providing age-dependent physical care revealed that 1.9 % of the total 108,600 cases registered in Berlin-Neukölln during the study period were related one of the 14 facilities. Compared to the general population in Neukölln, nursing homes exhibited a 20-fold increase in the CFR. Notably, nursing homes with higher bed capacities displayed a greater CFR than did smaller nursing homes. Similarly, elderly residents living in nursing homes faced a much greater mortality rate than did their counterparts living outside of medical settings (OR = 3.5). The original wild-type SARS-CoV-2 strain had the most severe direct impact, with a CFR of 16.7 %, compared to the alpha (CFR = 6.9 %), delta (CFR = 10.2 %) and omicron (CFR = 2.8 %) variants in nursing homes. Interestingly, the number of infections increased following vaccination campaigns, but this trend was accompanied by a decrease in the number of deaths from 2.6 to 1.1 per week. As a result, the CFR significantly decreased from 18.4 to 5.5, while still exceeding the mean CFR compared to that of the general population of Neukölln. ConclusionsOur findings reveal the changing patterns of outbreak frequency and severity across the five pandemic waves. They highlight the crucial role of rapid vaccination programs for residents, staff, visitors, and third-party services in safeguarding nursing homes. Additionally, improvements in containment and cluster strategies are essential in prevaccination scenarios to prevent future infection traps for elderly individuals in long-term care facilities. The presented data highlight the importance of tailored protection measures for one of the most vulnerable populations in our society.

Grid Search Optimized Machine Learning based Modeling of CO2 Emissions Prediction from Cars for Sustainable Environment

Carbon emissions have increased dramatically because of industrialization, trapping heat in the atmosphere and hastening climate change. This is a serious threat to the wealth, security, and well-being of the world. The effects are extensive, ranging from severe weather, disease outbreaks, and economic disruption to food insecurity and water scarcity. The World Health Organization (WHO) has determined that climate change poses the greatest threat to public health in the twenty-first century. Thus, precise CO2 emissions have emerged as a crucial concern in recent times. Several studies have tried to forecast the amount CO2 from industry and power plant using statistical analysis. Efficiency, robustness and diverse application was the limitation of the study. In this study, we have proposed an AI based model that is able to predict the amounts of CO2 emissions from cars. We applied a grid search-optimized machine learning approach using the publicly available Canadian dataset. Incorporation of different statistical analyses and preprocessing techniques such as duplicate data management, outlier rejection, scaling contributed to enhance the quality of the dataset. Later, grid search techniques were applied to tune the KNN, RF, and SVR models. The approach has enhanced the performance of CO2 emissions prediction. In the study, we further used the explainability of the random forest model to check the bias and fairness of predictability. MSE, RMSE, and R-squared metrics of the proposed approach were the highest as the state of the art.

Clonostachys rosea, a Pathogen of Brown Rot in Gastrodia elata in China.

Gastrodia elata, commonly known as Tian Ma, is a perennial mycoheterotrophic orchid. Qianyang Tian Ma (QTM), a geographical indication agricultural product from Hongjiang City, Hunan Province, China, is primarily characterized by the red variety, G. elata f. elata. A severe outbreak of tuber brown rot disease was documented in QTM during the harvesting season in Hunan. The fungal pathogen associated with the disease was isolated on potato saccharose agar (PSA) and identified through morphological and phylogenetic analyses. Pathogenicity tests were performed on healthy tubers of G. elata f. elata. The results showed that the representative isolate, named TMB, produced white hyphal colonies with a ring structure, broom-like phialides, partially curved ellipsoidal conidia, and orange-yellow spherical ascocarps on PSA. Phylogenetic analysis of the ITS, LSU, rpb2 and tub2 sequences using Bayesian and maximum-likelihood methods identified the isolate TMB as Clonostachys rosea, based on morphological and phylogenetic data. Pathogenicity tests revealed typical disease symptoms on healthy G. elata tubers 15 days post-inoculation with the isolate TMB. C. rosea is known to cause diseases in economically important crops, but there are no reports of its occurrence on G. elata f. elata in China. This study provides valuable insights into the occurrence, prevention, and control of brown rot disease in G. elata f. elata.