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Abstract Background Smoking is the major risk factor for tracheal, bronchus, and lung (TBL) cancers. We investigated the feasibility of projecting TBL cancer incidence using smoking incidence rates by incorporating a range of latent periods from the main risk factor exposure to TBL cancer diagnosis. Methods In this ecological study, we extracted data on TBL cancer incidence rates in Iran from 1990 to 2018 from the Global Burden of Disease (GBD) database. We also collected data on Iranian cigarette smoking patterns over the past 40 years through a literature review. The weighted average smoking incidence was calculated using a fixed-effects model with Comprehensive Meta-Analysis (CMA) software. Using these data, the five-year TBL cancer incidence in Iran was projected through time series modeling with IT Service Management (ITSM) 2000 software. A second model was developed based on cigarette smoking incidence using linear regression with SPSS (version 22), incorporating different latent periods. The results of these two models were compared to determine the best latent periods. Results An increasing trend in TBL cancer incidence was observed from 2019 to 2023 (first model: 10.30 [95% CI: 9.62, 10.99] to 11.42 [95% CI: 10.85, 11.99] per 100,000 people). In the second model, the most accurate prediction was obtained with latent periods of 17 to 20 years, with the best prediction using a 17-year latent period (10.13 to 11.40 per 100,000 people) and the smallest mean difference of 0.08 (0.84%) per 100,000 people using the standard forecasting model (the ARIMA model). Conclusion Projecting an increase in TBL cancer incidence rates in the future, an optimal latent period of 17 to 20 years between exposure to cigarette smoke and TBL cancer incidence has implications for macrolevel preventive health policymaking to help reduce the burden of TBL cancer in upcoming years.

Background: Smoking is the major risk factor for tracheal, bronchus, and lung (TBL) cancers. We investigated the feasibility of projecting TBL cancer incidence using smoking incidence rates by incorporating a range of latent periods from the main risk factor exposure to TBL cancer diagnosis. Methods: In this ecological study, we extracted data on TBL cancer incidence rates in Iran from 1990 to 2018 from the Global Burden of Disease (GBD) database. We also collected data on Iranian cigarette smoking patterns over the past 40 years through a literature review. The weighted average smoking incidence was calculated using a fixed-effects model with Comprehensive Meta-Analysis (CMA) software. Using these data, the five-year TBL cancer incidence in Iran was projected through time series modeling with IT Service Management (ITSM) 2000 software. A second model was developed based on cigarette smoking incidence using linear regression with SPSS (version 22), incorporating different latent periods. The results of these two models were compared to determine the best latent periods. Results: An increasing trend in TBL cancer incidence was observed from 2019 to 2023 (first model: 10.30 [95% CI: 9.62, 10.99] to 11.42 [95% CI: 10.85, 11.99] per 100,000 people). In the second model, the most accurate prediction was obtained with latent periods of 17 to 20 years, with the best prediction using a 17-year latent period (10.13 to 11.40 per 100,000 people) and the smallest mean difference of 0.08 (0.84%) per 100,000 people using the standard forecasting model (the ARIMA model). Conclusion: Projecting an increase in TBL cancer incidence rates in the future, an optimal latent period of 17 to 20 years between exposure to cigarette smoke and TBL cancer incidence has implications for macrolevel preventive health policymaking to help reduce the burden of TBL cancer in upcoming years. Key messages: • The most accurate prediction of five-year TBL cancer incidence in Iran was obtained with latent periods of 17 to 20 years after initial exposure to cigarette smoke. • A more advanced model can potentially be leveraged to project the epidemiological indices of other non-communicable diseases that have a highly attributable risk factor, adequate information on previous trends, and a range of latent periods. [ABSTRACT FROM AUTHOR]

Background: Preterm prelabour rupture of membranes (PPROM) accounts for one-third of cases of preterm labour which is the leading cause of perinatal morbidity and mortality. The time from the rupture of membranes until labour, i.e. the latent period (LP), is an important factor in neonatal outcome. Aim of the study: The present study aims to determine the sensitivity and specificity of measuring the thickness of myometrium for the prediction of LP. Patients and methods: This crosssectional observational study was performed in Az-Zahraa Teaching Hospital in Najaf-Iraq during the period from the first of August 2016 to the first of October 2017. A total of 89 patients who admitted with the diagnosis of PPROM at the 26th to the 34th weeks of gestation with oligohydramnios were included in the study. The thickness of myometrium was measured via transabdominal ultrasound in the lower uterine segment (LSMT), anterior (AMT), posterior (PMT) and fundal (FMT) parts of uterus within 24 hours of membranes rupture. Results: The mean measurements of LSMT, AMT, PMT and FMT in patients with PPROM and oligohydramnios were 7.25±2.31, 7.87±3.45, 8.71±3.88 and 8.65±3.72 respectively. The sensitivity and specificity of measuring AMT for prediction of LP > 7 days were 80% and 53%; those for PFT were 80% and 34.1% respectively at a cut-off point of 6.5 mm while the FMT was found to be 60% sensitive and 34.1% specific. LSMT was 80% sensitive and 43.9% specific for recognition of LP > 7 days at a cut-off point of 7.5mm. Conclusions: measurement of the thickness of the myometrium may be a sensitive but non-specific tool for the prediction of the latent period. [ABSTRACT FROM AUTHOR]

Abstract Background The latent and incubation periods characterize the transmission of infectious viruses and are the basis for the development of outbreak prevention and control strategies. However, systematic studies on the latent period and associated factors with the incubation period for SAS-CoV-2 variants are still lacking. We inferred the two durations of Delta, BA.1, and BA.2 cases and analyzed the associated factors. Methods The Delta, BA.1, and BA.2 (and its lineages BA.2.2 and BA.2.76) cases with clear transmission chains and infectors from 10 local SAS-CoV-2 epidemics in China were enrolled. The latent and incubation periods were fitted by the Gamma distribution, and associated factors were analyzed using the accelerated failure time model. Results The mean latent period for 672 Delta, 208 BA.1, and 677 BA.2 cases was 4.40 (95%CI: 4.24 ~ 4.63), 2.50 (95%CI: 2.27 ~ 2.76), and 2.58 (95%CI: 2.48 ~ 2.69) days, respectively, with 85.65% (95%CI: 83.40 ~ 87.77%), 97.80% (95%CI: 96.35 ~ 98.89%), and 98.87% (95%CI: 98.40 ~ 99.27%) of them starting to shed viruses within 7 days after exposure. In 405 Delta, 75 BA.1, and 345 BA.2 symptomatic cases, the mean latent period was 0.76, 1.07, and 0.79 days shorter than the mean incubation period [5.04 (95%CI: 4.83 ~ 5.33), 3.42 (95%CI: 3.00 ~ 3.89), and 3.39 (95%CI: 3.24 ~ 3.55) days], respectively. No significant difference was observed in the two durations between BA.1 and BA.2 cases. After controlling for the sex, clinical severity, vaccination history, number of infectors, the length of exposure window and shedding window, the latent period [Delta: exp(β) = 0.81, 95%CI: 0.66 ~ 0.98, p = 0.034; Omicron: exp(β) = 0.82, 95%CI: 0.71 ~ 0.94, p = 0.004] and incubation period [Delta: exp(β) = 0.69, 95%CI: 0.55 ~ 0.86, p

Mate-guarding behaviour is thought to beneficially increase paternal share by lowering sperm competition. It is likely to be a plastic response that changes with the density of rivals in the surroundings. A recent study showed that the Parthenium beetle, Zygogramma bicolorata (Coleoptera: Chrysomelidae), exhibits mate-guarding behaviour through prolonged mating duration. The goal of the present study was to evaluate the flexibility of this behaviour when rivals were present. A pair of Z. bicolorata were placed in the physical presence and chemical cues of rivals of both sexes at different densities, and their precopulatory behaviours (time to commencement of mating, latent period, mate-guarding duration and reproductive output) were noted. We hypothesized that population densities of rivals of both sexes would influence the mate-guarding behaviour and reproductive outputs. Our results revealed that population density has significant effects on precopulatory parameters and reproductive outputs. Mate-guarding duration decreased in the physical presence of rivals, while it increased in the presence of chemical cues. In the physical presence of rivals, mate guarding probably decreased due to the repeated harassment of the focal pair, especially the male partner, by the rivals in the experimental arena. However, reproductive outputs (fecundity and percentage egg viability) were increased in both the physical presence and chemical cues of males and females. Hence our results clearly support the previous observation of mate-guarding behaviour through prolonged mating duration in the Parthenium beetle, and show its plasticity. • Plasticity of mate-guarding behaviour in response to adult density was studied. • Results revealed a significant effect of density on mate-guarding behaviour. • Physical presence of rivals significantly decreases mate guarding in focal pair. • Chemical cues of rival males or females increase mate guarding in focal pair. • Reproductive output increases with both physical and chemical presence of rivals. [ABSTRACT FROM AUTHOR]

In this paper, we consider an SEIS epidemic model with infectious force in latent and infected period, which incorporates by nonlinear incidence rates. The local stability of the equilibria is discussed. By means of Lyapunov functionals and LaSalle's invariance principle, we proved the global asymptotic stability of the disease-free equilibrium and the endemic equilibrium. An application is given and numerical simulation results based on real data of COVID-19 in Morocco are performed to justify theoretical findings. [ABSTRACT FROM AUTHOR]

One obstacle to pepper production is the high intensity of plant disease attacks. One of these is stem rot disease caused by the fungus Phytophthora capsici. Therefore, appropriate technology is needed to control disease and simultaneously increase plant growth by using rhizobacteria that are environmentally friendly and can produce growth hormones, dissolve phosphate, and fix nitrogen. This study aimed to obtain rhizobacterial isolates that can control the pathogen P. capsici, which causes root rot disease, while also increasing plant growth. This study was conducted at the Agronomy Laboratory of the Plant Cultivation Study Program, Samarinda State Agricultural Polytechnic. The study used a completely randomized design consisting of four treatments with four replicates to obtain 16 experimental units. The variables observed included the latent period, disease incidence and severity, increase in plant height, number of leaves, and stem diameter. The resulting data were analyzed using analysis of variance (ANOVA). The results of the analysis showing a real effect were followed by the Least Significant Difference test (BNT)a=0.05. The results of this study showed that the application of a combination of rhizobacteria was able to overcome stem rot disease and simultaneously increase the growth of pepper plant seedlings. The combination of rhizobacteria isolate P01 + TA2 treatment can reduce the latent period of disease to 12.00 days compared to 5.50 days without rhizobacteria, the disease incidence rate was 6.25% with a severity level of 2.50%, lower than of treatment (control) at 37.50 % (disease incidence) and 47.50% (disease severity). In addition, the combination of rhizobacterial isolates P01 + TA2 was able to increase the growth of pepper plant seeds, as shown by the increase in plant height, number of leaves, and stem diameter. [ABSTRACT FROM AUTHOR]

Varicella zoster is found exclusively in humans. Infected people with this virus result in chickenpox followed by dormant virus within neural ganglia. This dormant virus, once activated, may affect any ganglia or nerves of the body but most commonly involves the thoracic, cervical and trigeminal nerves in decreasing order of frequency. We review three such cases in which manipulation of the trigeminal ganglion resulted in reactivation of varicella at homologous operative sites. Each patient underwent surgeries in which the trigeminal ganglion was manipulated for the resection of trigeminal schwannoma under a microscope through various approaches. All three patients developed reactivation of varicella at homologous operative sites. A thorough history of chickenpox infection should be taken in patients who are undergoing surgeries for trigeminal pathology. Early diagnosis should be made once any vesicular lesions are seen with prompt treatment. Reassurance and counselling are necessary in these patients. If possible, prophylaxis may be started in all such patients. Further studies are warranted to determine the exact cause of reactivation. [ABSTRACT FROM AUTHOR]

The severe shortfall in testing supplies during the initial COVID-19 outbreak and ensuing struggle to manage the pandemic have affirmed the critical importance of optimal supply-constrained resource allocation strategies for controlling novel disease epidemics. To address the challenge of constrained resource optimization for managing diseases with complications like pre- and asymptomatic transmission, we develop an integro partial differential equation compartmental disease model which incorporates realistic latent, incubation, and infectious period distributions along with limited testing supplies for identifying and quarantining infected individuals. Our model overcomes the limitations of typical ordinary differential equation compartmental models by decoupling symptom status from model compartments to allow a more realistic representation of symptom onset and presymptomatic transmission. To analyze the influence of these realistic features on disease controllability, we find optimal strategies for reducing total infection sizes that allocate limited testing resources between ‘clinical’ testing, which targets symptomatic individuals, and ‘non-clinical’ testing, which targets non-symptomatic individuals. We apply our model not only to the original, delta, and omicron COVID-19 variants, but also to generically parameterized disease systems with varying mismatches between latent and incubation period distributions, which permit varying degrees of presymptomatic transmission or symptom onset before infectiousness. We find that factors that decrease controllability generally call for reduced levels of non-clinical testing in optimal strategies, while the relationship between incubation-latent mismatch, controllability, and optimal strategies is complicated. In particular, though greater degrees of presymptomatic transmission reduce disease controllability, they may increase or decrease the role of non-clinical testing in optimal strategies depending on other disease factors like transmissibility and latent period length. Importantly, our model allows a spectrum of diseases to be compared within a consistent framework such that lessons learned from COVID-19 can be transferred to resource constrained scenarios in future emerging epidemics and analyzed for optimality.

Background and Objectives Stem rust, also known as black rust and caused by the fungus Puccinia graminis f. sp. tritici (Pgt), poses a substantial threat to global food security by potentially devastating wheat crops. This disease can lead to a 100% loss in wheat crop yields under epidemic conditions. The combined impact of rust, including stripe rust, leaf rust, and stem rust, on overall wheat production is estimated at around $5 billion annually. Stem rust exhibits distinctive symptoms, such as dark brown pustules, appearing across all parts of the wheat plant. Recent reports highlight recurring stem rust epidemics across various global regions. Notably, there has been a significant spread of stem rust in Europe, particularly in England and Italy. Iran has also experienced two severe stem rust epidemics. The most effective strategy to mitigate the impact of this disease involves identifying and incorporating resistant genes from cultivars displaying robust resistance into favored wheat genotypes. This approach aims to establish enduring genetic resistance, representing a crucial method for disease control. Materials and Methods To uncover novel sources of resistance, an experiment was conducted to assess the resistance reactions of 30 wheat genotypes and a susceptible check (Morocco) against six distinct Pgt races, each characterized by unique pathogenicity patterns (TKTTF, TTTF, TTRTF, PKRTF, PKSTF, and TKSTC). The experiment followed a randomized complete block design with three replications. Each Pgt race was independently utilized for evaluating the genotypes, with the measured resistance components encompassing the infection type and latent period. Statistical analyses were performed using SAS software (v. 3.9) to perform analysis of variance (ANOVA) for the experimental design, Minitab (v. 16) for normality tests, and SPSS (v. 16) software for cluster analysis. The bi-plot method, grounded in multivariable models, emerged as a valuable statistical approach for classifying environments (races) due to its simplicity, high accuracy in analyses, and evaluative capabilities. Additionally, this method proved effective in identifying resistant genotypes to each of the races and elucidating the relationships between them. Results The results indicated that the differential genotypes carrying the Sr11, Sr21, Sr30 and Sr13+17 genes exhibited a distinct resistance reaction against the studied races. Notably, the Sr11 gene demonstrated a notable effect on four out of the six races. Among the races, TKSTC and TTTTF displayed the highest positive correlation, while PKSTF and TTRTF races exhibited the lowest correlation with each other. Phenotyping and ANOVA revealed significant phenotypic diversity among wheat genotypes concerning the measured resistance components to Pgt races. Cluster analysis effectively categorized the wheat genotypes into three primary groups: resistant, susceptible, and moderately resistant to moderately susceptible. Among the studied wheat genotypes, 11 (35%) displayed susceptibility to all races, while four genotypes (G1, G2, G3, and G17) (13%) showed resistance against all races. The remaining 16 genotypes (52%) demonstrated moderately resistant to moderately susceptible (specific reaction) responses. The biplot analysis (GGE biplot) identified genotype G17 as the most resistant genotype with a uniform response to all races. Discussion Genotypes with varying degrees of resistance to Pgt races identified in this study can serve as new and sustainable sources of resistance for breeding wheat cultivars with a broad genetic basis of resistance. Expanding the study to include a broader array of races and differential isogenic lines can refine conditions, enabling more precise identification of effective resistance genes in each genotype. Furthermore, evaluating the resistance of the examined genotypes at the adult plant stage proves invaluable in identifying resistance genes, which carry greater significance than those observed solely at the seedling stage. The existence of resistance genes at the adult plant stage remains plausible, even in cases where the genotype exhibits sensitivity during the seedling stage. The strategic and reasonable utilization of effective resistance genes at both the seedling and adult plant stages is envisioned to contribute to the development of new, resilient varieties with stable resistance. [ABSTRACT FROM AUTHOR]

Wheat stripe rust (WSR) is an airborne disease that causes severe damage to wheat. The rapid and early detection of WSR is essential for the prevention and control of this disease. The minimum detection limit (MDL) is one of the most important characteristics of quantitative methods that can be used to determine the scope and applicability of a measurement technique. Three wheat cultivars were inoculated with Puccinia striiformis f.sp. tritici (Pst), and a spectrometer was used to collect the canopy hyperspectral data, and the Pst content was obtained via a duplex real-time polymerase chain reaction (PCR) during the latent period, respectively. The disease index (DI) and molecular disease index (MDI) were calculated. The regression tree algorithm was used to determine the MDL of the Pst based on hyperspectral feature parameters. The logistic, IBK, and random committee algorithms were used to construct the classification model based on the MDL. The results showed that when the MDL was 0.7, IBK had the best recognition accuracy. The optimal model, which used the spectral feature R_2nd.dv ((the second derivative of the original hyperspectral value)) and the modeling ratio 2:1, had an accuracy of 91.67% on the testing set and 90.67% on the 10-fold cross-validation. Thus, during the latent period, the MDL of Pst was determined using hyperspectral technology as 0.7. [ABSTRACT FROM AUTHOR]

The severe shortfall in testing supplies during the initial COVID-19 outbreak and ensuing struggle to manage the pandemic have affirmed the critical importance of optimal supplyconstrained resource allocation strategies for controlling novel disease epidemics. To address the challenge of constrained resource optimization for managing diseases with complications like pre- and asymptomatic transmission, we develop an integro partial differential equation compartmental disease model which incorporates realistic latent, incubation, and infectious period distributions along with limited testing supplies for identifying and quarantining infected individuals. Our model overcomes the limitations of typical ordinary differential equation compartmental models by decoupling symptom status from model compartments to allow a more realistic representation of symptom onset and presymptomatic transmission. To analyze the influence of these realistic features on disease controllability, we find optimal strategies for reducing total infection sizes that allocate limited testing resources between 'clinical' testing, which targets symptomatic individuals, and 'non-clinical' testing, which targets non-symptomatic individuals. We apply our model not only to the original, delta, and omicron COVID-19 variants, but also to generically parameterized disease systems with varying mismatches between latent and incubation period distributions, which permit varying degrees of presymptomatic transmission or symptom onset before infectiousness. We find that factors that decrease controllability generally call for reduced levels of non-clinical testing in optimal strategies, while the relationship between incubation-latent mismatch, controllability, and optimal strategies is complicated. In particular, though greater degrees of presymptomatic transmission reduce disease controllability, they may increase or decrease the role of nonclinical testing in optimal strategies depending on other disease factors like transmissibility and latent period length. Importantly, our model allows a spectrum of diseases to be compared within a consistent framework such that lessons learned from COVID-19 can be transferred to resource constrained scenarios in future emerging epidemics and analyzed for optimality. [ABSTRACT FROM AUTHOR]

Background and Objectives Fusarium wilt disease is one of the most important diseases of melon, which causes damage between 20 and 80% in melon fields. In favorable conditions, the spread of the disease can reach 100%. In the improvement programs, achieving resistant cultivars is considered one of the most important methods of controlling this disease. Materials and Methods In this research, 46 melon landraces were collected from different parts of Razavi, Northern and Southern Khorasan provinces, along with two separate lines, Isabel and Charente T respectively as resistant and sensitive control cultivars to identify new sources of wilt disease resistance to Fusarium oxysporum f. sp. melonis. The experiments were carried out in a randomized complete block design with three replications in the greenhouse of the agricultural campus of Tarbiat Modares University. The seeds were grown in trays containing cocopeat and perlite in a ratio of 2:1; fourteen days after cultivation, the roots of the young seedlings were removed from the culture tray and inoculated for two minutes with the isolate Mt13-3a of F. oxysporum f. sp. melonis race 1.2 spore suspension solution, with a concentration of 106 conidium per milliliter. The symptom was evaluated nine days after inoculation. The spread of symptoms on the plants was recorded every day for 30 days until the complete death of the plant. Evaluation of resistance was calculated using the indices of the area under the disease progress curve (AUDPC), latent period (LP), disease severity index (DSI), and standardized area under the disease progress curve (SAUDPC) in landraces. Investigating the variation of the resistance of the studied landraces based on the mentioned indices was done using analysis of variance and cluster analysis. Results The results of the analysis of variance of the data indicated the existence of a significant difference of 1% between the landraces for all four studied indices. Based on the heat map results, there is resistance to race 1.2 of F. oxysporum f. sp. melonis in the genotype Isabel and Tude Qaenat. Also, the cluster analysis of landraces based on Ward's method led to identifying six resistance groups from the 46 landraces studied, along with two differential control lines. Discussion The results of the present research showed that for all four indices of LP, AUDPC, DSI and SAUDPC, there is resistance to race 1.2 of F. oxysporum f. sp. melonis in Isabel genotype as a resistant control and the landraces of Qaenat, Till Magasi, Till Zard, Till Torgh, Laki 1 and Till Keshideh compared to the sensitive control (Charente T). [ABSTRACT FROM AUTHOR]

Estimating key epidemiological parameters, such as incubation period, serial interval (SI), generation interval (GI) and latent period, is essential to quantify the transmissibility and effects of various interventions of COVID-19. These key parameters play a critical role in quantifying the basic reproduction number. With the hard work of epidemiological investigators in South Korea, estimating these key parameters has become possible based on infector-infectee surveillance data of COVID-19 between February 2020 and April 2021. Herein, the mean incubation period was estimated to be 4.9 days (95% CI: 4.2, 5.7) and the mean generation interval was estimated to be 4.3 days (95% CI: 4.2, 4.4). The mean serial interval was estimated to be 4.3, with a standard deviation of 4.2. It is also revealed that the proportion of presymptomatic transmission was ~57%, which indicates the potential risk of transmission before the disease onset. We compared the time-varying reproduction number based on GI and SI and found that the time-varying reproduction number based on GI may result in a larger estimation of Rt, which refers to the COVID-19 transmission potential around the rapid increase of cases. This highlights the importance of considering presymptomatic transmission and generation intervals when estimating the time-varying reproduction number.

Dynamic SEIR (Susceptible, Exposed, Infectious, Removed) compartmental models provide a tool for predicting the size and duration of both unfettered and managed outbreaks-the latter in the context of interventions such as case detection, patient isolation, vaccination and treatment. The reliability of this tool depends on the validity of key assumptions that include homogeneity of individuals and spatio-temporal homogeneity. Although the SEIR compartmental framework can easily be extended to include demographic (e.g. age) and additional disease (e.g. healthcare workers) classes, dependence of transmission rates on time, and metapopulation structure, fitting such extended models is hampered by both a proliferation of free parameters and insufficient or inappropriate data. This raises the question of how effective a tool the basic SEIR framework may actually be. We go some way here to answering this question in the context of the 2014-2015 outbreak of Ebola in West Africa by comparing fits of an SEIR time-dependent transmission model to both country- and district-level weekly incidence data. Our novel approach in estimating the effective-size-of-the-populations-at-risk ( Neff) and initial number of exposed individuals ( E0) at both district and country levels, as well as the transmission function parameters, including a time-to-halving-the-force-of-infection ( tf/2) parameter, provides new insights into this Ebola outbreak. It reveals that the estimate R0 ≈ 1.7 from country-level data appears to seriously underestimate R0 ≈ 3.3 - 4.3 obtained from more spatially homogeneous district-level data. Country-level data also overestimate tf/2 ≈ 22 weeks, compared with 8-10 weeks from district-level data. Additionally, estimates for the duration of individual infectiousness is around two weeks from spatially inhomogeneous country-level data compared with 2.4-4.5 weeks from spatially more homogeneous district-level data, which estimates are rather high compared with most values reported in the literature. This article is part of the theme issue Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes. This issue is linked with the subsequent theme issue Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control.

Dynamic SEIR (Susceptible, Exposed, Infectious, Removed) compartmental models provide a tool for predicting the size and duration of both unfettered and managed outbreaks-the latter in the context of interventions such as case detection, patient isolation, vaccination and treatment. The reliability of this tool depends on the validity of key assumptions that include homogeneity of individuals and spatio-temporal homogeneity. Although the SEIR compartmental framework can easily be extended to include demographic (e.g. age) and additional disease (e.g. healthcare workers) classes, dependence of transmission rates on time, and metapopulation structure, fitting such extended models is hampered by both a proliferation of free parameters and insufficient or inappropriate data. This raises the question of how effective a tool the basic SEIR framework may actually be. We go some way here to answering this question in the context of the 2014-2015 outbreak of Ebola in West Africa by comparing fits of an SEIR time-dependent transmission model to both country- and district-level weekly incidence data. Our novel approach in estimating the effective-size-of-the-populations-at-risk ( Neff) and initial number of exposed individuals ( E0) at both district and country levels, as well as the transmission function parameters, including a time-to-halving-the-force-of-infection ( tf/2) parameter, provides new insights into this Ebola outbreak. It reveals that the estimate R0 ≈ 1.7 from country-level data appears to seriously underestimate R0 ≈ 3.3 - 4.3 obtained from more spatially homogeneous district-level data. Country-level data also overestimate tf/2 ≈ 22 weeks, compared with 8-10 weeks from district-level data. Additionally, estimates for the duration of individual infectiousness is around two weeks from spatially inhomogeneous country-level data compared with 2.4-4.5 weeks from spatially more homogeneous district-level data, which estimates are rather high compared with most values reported in the literature. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.

It is widely hypothesized that there is a seizure-free state, termed the “latent period,” between brain injury and the onset of symptomatic epilepsy. During the latent period, structural and functional alterations gradually mediate epileptogenesis. Kainate (KA) induces epilepsy in rats in a manner similar to that induced by human epilepsy. During the model's latent period, rats administered KA-exhibited innate behaviour such as self-grooming. We previously reported that self-grooming bouts are facilitated during the latent period in this model. Here, we investigated self-grooming changes during the latent period of the KA rat model. We analysed various parameters of self-grooming – including duration, number, and percentage of correct transitions (CT%). Self-grooming bouts included a syntactic chain consisting of CT. CT% was defined as the ratio of the number of CT scans to the total number of transitions. The results showed that CT%, number, and duration were significantly increased during the latent period in KA rats. We attempted to mine the features that detect the latent period using a neural network. Our results suggest that the CT% of self-grooming will detect changes in the latent period in the KA rat epilepsy model.

The current study aimed to investigate the neuropharmacological properties of ethanol, acetone, and ethyl acetate leaf extracts of Chassalia curviflora (C. curviflora) in mouse models. The neuropharmacological properties of this plant were studied on Swiss albino mice at dosages of 50, 100, and 200 mg/kg body weight in thiopental sodium-induced sleeping time test, and at dosages of 100 and 200 mg/kg body weight in other tests. The extracts caused a marked reduction in the initiation and sleep length (P

Background: Adverse cutaneous drug reactions (ACDRs) present with different morphologies and times of onset. Knowledge about the common drugs causing them, their reaction time (time interval between drug intake and the onset of symptoms), and the clinical presentations are helpful in identifying an offending drug, especially in the setting of multiple drug therapies, thereby reducing the morbidity and mortality associated with them. Aims: This study aims to identify causative drugs and clinical patterns of ACDRs in a tertiary care center and to estimate their reaction time. Methods: Sixty-two patients diagnosed to have ACDRs who attended the department of dermatology of a tertiary care teaching hospital during an 18-month period were selected for the study. They were classified into certain, probable, or possible categories as per the World Health Organization-Uppsala Monitoring Centre (WHO-UMC) classification. The frequency of each type of drug reaction, common causative agents, and reaction time of different drug reactions was analyzed. Results: Of the 62 patients, 40 (64.5%) were probable, 18 (29%) possible, and 4 (6.4%) were certain. The most common types of reactions encountered were fixed drug eruption (FDE) (13, 21%), drug hypersensitivity syndrome (12, 19.4%), and maculopapular rash (9, 14.5%). As a single group of drugs, antimicrobials were the most common causative agents (23, 37%) followed by anticonvulsants (16, 25.8%). As an individual drug, phenytoin was the most common causative agent (10, 16.1%), followed by paracetamol (7, 11.3%) and isoniazid (5, 8.1%). Reaction time varied from less than an hour for FDE and urticaria to 3–4 months for exfoliative dermatitis, lichenoid eruption, and folliculitis. Limitations: Small sample size was the major limitation. Conclusion: Reaction time varied from less than 24 h in FDE, urticaria, and angioedema to 3–4 months in exfoliative dermatitis, lichenoid eruption, and folliculitis.

The current study aimed to investigate the spatial and temporal patterns of high-frequency oscillations (HFOs) in the intra-/extrahippocampal areas during epileptogenesis. Local field potentials were bilaterally recorded from hippocampus (CA1), thalamus, motor cortex, and prefrontal cortex in 13 rats before and after intrahippocampal kainic acid (KA) lesions. HFOs in the ripple (100-200 Hz) and fast ripple (250-500 Hz) ranges were detected and their rates were computed during different time periods (1-5 weeks) after KA-induced status epilepticus (SE). Recurrent spontaneous seizures were observed in 7 rats after SE, and the other 6 rats did not develop epilepsy. During the latent period, the rate of hippocampal HFOs increased at the ipsilateral site of the KA lesion in both groups, and the HFO rate was significantly higher in the animals that later developed epilepsy. Animals that later developed epilepsy also demonstrated widespread appearance of HFOs, in both the ripple and the fast ripple range, whereas animals that did not develop epilepsy only exhibited changes in the ipsilateral intrahippocampal HFO rate. This study demonstrates an association between an increased rate of widespread HFOs and the later development of epilepsy, suggesting the formation of large-scale distributed pathological networks during epileptogenesis.

Foot-and-mouth disease is an acute, highly infectious, and economically significant transboundary animal disease. Vaccination is an efficient and cost-effective measure to prevent the transmission of this disease. The primary way that foot-and-mouth disease spreads is through direct contact with infected animals, although it can also spread through contact with contaminated environments. This paper uses a diffuse foot-and-mouth disease model to account for the efficacy of vaccination in managing the disease. First, we transform an age-space structured foot-and-mouth disease into a diffusive epidemic model with nonlocal infection coupling the latent period and the latent diffusive rate. The basic reproduction number, which determines the outbreak of the disease, is then explicitly formulated. Finally, numerical simulations demonstrate that increasing vaccine efficacy has a remarkable effect than increasing vaccine coverage.

In this paper, a delayed differential model of citrus Huanglongbing infection is analyzed, in which the latencies of the citrus tree and Asian citrus psyllid are considered as two time delay factors. We compute the equilibrium points and the basic reproductive numbers with and without time delays, i.e. R 0 and R ̃ 0 , and then show that R ̃ 0 completely determines the local stability of the disease-free equilibrium. Moreover, the conditions for the existence of transcritical bifurcation are derived from Sotomayor's Theorem. The stability of the endemic equilibrium and the existence of Hopf bifurcation are investigated in four cases: (1) τ 1 = τ 2 = 0 , (2) τ 1 > 0 , τ 2 = 0 , (3) τ 1 = 0 , τ 2 > 0 and (4) τ 1 > 0 , τ 2 > 0. Optimal control theory is then applied to the model to study two time-dependent treatment efforts and minimize the infection in citrus and psyllids, while keeping the implementation cost at a minimum. Numerical simulations of the overall systems are implemented in MatLab for demonstration of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper is to analyze Susceptible-Exposed-Infectious-Recovered (SEIR) COVID-19 pandemic model. In this article, a modified SEIR model is constructed, and is also discussed various aspects of it with mathematical analysis to study the dynamic behavior of this model. The spread of this disease through immigration can be represented by the SEIR model. COVID-19 is a highly infectious disease that spreads through talking, sneezing, coughing, and touching. In this model, there is an incubation period during the spread of the disease. During the gestation period, a patient is attacked by SARS-CoV-2 coronavirus and shows symptoms of COVID-19, but cannot spread the disease. The horizontal transmission of COVID-19 worldwide can be represented and explained by SEIR model. Maximal control of the pandemic disease COVID-19 can be possible by the optimum vaccination policies. The study also investigates the equilibrium of the disease. In the study, a Lyapunov function is created to analyze the global stability of the disease-free equilibrium. The generation matrix method is analyzed to obtain the basic reproduction number and has discussed the global stability of COVID-19 spreading. [ABSTRACT FROM AUTHOR]

Wheat stripe rust (WSR) is an airborne disease that causes severe damage to wheat. The rapid and early detection of WSR is essential for the prevention and control of this disease. The minimum detection limit (MDL) is one of the most important characteristics of quantitative methods that can be used to determine the scope and applicability of a measurement technique. Three wheat cultivars were inoculated with Puccinia striiformis f.sp. tritici (Pst), and a spectrometer was used to collect the canopy hyperspectral data, and the Pst content was obtained via a duplex real-time polymerase chain reaction (PCR) during the latent period, respectively. The disease index (DI) and molecular disease index (MDI) were calculated. The regression tree algorithm was used to determine the MDL of the Pst based on hyperspectral feature parameters. The logistic, IBK, and random committee algorithms were used to construct the classification model based on the MDL. The results showed that when the MDL was 0.7, IBK had the best recognition accuracy. The optimal model, which used the spectral feature R_2nd.dv ((the second derivative of the original hyperspectral value)) and the modeling ratio 2:1, had an accuracy of 91.67% on the testing set and 90.67% on the 10-fold cross-validation. Thus, during the latent period, the MDL of Pst was determined using hyperspectral technology as 0.7.

Introduction: Emerging variants of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) have resulted in new challenges for epidemic prevention and control worldwide. However, little is known about the latent period of coronavirus disease by the SARS‐CoV‐2 Delta variant of concern (VOC) in the postvaccination era. Methods: The epidemiology and clinical data of cases with confirmed SARS‐CoV‐2 Delta VOC infection were retrospective collected. Dates of the first positive PCR test were collected to estimate the distribution of latent period. Results: Of the 40 patients, 16 were male (40%). The median age of patients was 47.5 years. The median latent period of patients was 6.0 days (interquartile range [IQR], 4.0−9.0 days) and the longest latent period was 13.0 days after exposure. The latent periods were longer in male patients compared to female patients (median, 8.5 days vs. 5.0 days, p =.041). The median latent period was comparable among fully vaccinated cases (6.5 days), no vaccinated cases (7.5 days), and partially vaccinated cases (5.5 days). Conclusions: The median latent period of SARS‐CoV‐2 Delta VOC infection was 6.0 days. The latent period between vaccinated and non‐vaccinated patients was not significantly different. The 14‐day quarantine program is sufficient to prevent the transmission of COVID‐19 by Delta VOC in the postvaccination era. [ABSTRACT FROM AUTHOR]

Fusarium head blight (FHB) is a global significant threat to crop production in small grains such as wheat. Till recently, we still lack empirical data on the selective effects of wheat quantitative resistance on aggressiveness changes in diverse FHB pathogens which may lead to potential resistance erosion because of the difficulty of conducting such studies under field conditions. Four FHB causative agents were used to study the evolution of aggressiveness using in vitro serial passage assays on susceptible "S" and moderately resistant "MR" wheat cultivars. These pathogens were previously tested and were found to be highly aggressive in vitro. Differences due to the selective impact of a cultivar among non-selected and selected isolates were measured for traits contributing to parasitic (latent period (LP) and area under disease progress curve (AUDPC)) and saprophytic (growth rate) fitness. The pathogen populations evolved faster on "MR" cultivars than "S" cultivars. Selected isolates were significantly more aggressive than non-selected isolates for LP and AUDPC, while no increase in aggressiveness was found on potato dextrose agar, indicating that the evolution of aggressiveness in FHB agents is associated with the presence of wheat plants with contrasted resistance levels. Selected isolates from "MR" cultivars were more aggressive than selected isolates from "S" cultivars, as they had a shorter LP (48.8%) and a higher level of AUDPC (18.4%). These results provide the first direct evidence that FHB pathogens adapt to wheat by increasing aggressiveness, suggesting a risk of directional selection and possible erosion of FHB resistance, an essential element for the development of durable management strategies for resistant wheat cultivars to FHB infection. [ABSTRACT FROM AUTHOR]

More than 100 Russian varieties and collection samples of winter rye were studied under the conditions of the Kirov region against the natural infectious background of the development of mycoses (2019-2020). The degree of damage by powdery mildew during the years of research reached 86.3 %, septoria – 63.3 %, brown rust – 40.5 %, stem rust – 60.0 %, rhynchosporiosis – 29.3 %. During plant ontogenesis (from phases 31 to 85 Zadoks scale), the growth of fungal infection in varietal biocenoses was analyzed. When accounting for diseases, well-known methods were used. The nature of plant-microbial interactions and the parameters of resistance were assessed by indicators of ADDC (area under the curve of disease development), IR (resistance index) and LP (latency period). A close relationship was established between the duration of LP and the degree of septoria infection (r = -0.98), brown rust (r = -0.95), powdery mildew (r = -0.92), stem rust (r = -0.80), rhynchosporiosis (r = -0.67). The regression equations are linear (R2 = 0.84 ... 0.96) and indicate a daily increase in diseases (from 0.52 to 0.88 %). In the course of immunological management, there have been identified about 20 varieties of Russian selection distinguished by nonspecific resistance to two or more diseases, slow (slow rusting) growth of infection in varietal biocenoses and a long latent period of pathogenesis. Among them are the varieties of the Federal Agricultural Research Center of the North-East named N.V. Rudnitsky (Falyonskaya 4, Vyatka 2, Rushnik, Kirovskaya 89, Snezhana, Flora, Rumba), other scientific institutions of the Russian Federation (Alisa, Pamyati Bambysheva, P-01/14, GP-901 and others) and new samples from the VIR collection (Trinodis 4 Minvak – 139/09 NP, Estet NP 42/14 and others). They can be used in breeding as sources, and indicators of ADDC, IR, LP – as immunologically significant parameters of nonspecific resistance.

Abstract Introduction Emerging variants of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) have resulted in new challenges for epidemic prevention and control worldwide. However, little is known about the latent period of coronavirus disease by the SARS‐CoV‐2 Delta variant of concern (VOC) in the postvaccination era. Methods The epidemiology and clinical data of cases with confirmed SARS‐CoV‐2 Delta VOC infection were retrospective collected. Dates of the first positive PCR test were collected to estimate the distribution of latent period. Results Of the 40 patients, 16 were male (40%). The median age of patients was 47.5 years. The median latent period of patients was 6.0 days (interquartile range [IQR], 4.0−9.0 days) and the longest latent period was 13.0 days after exposure. The latent periods were longer in male patients compared to female patients (median, 8.5 days vs. 5.0 days, p = .041). The median latent period was comparable among fully vaccinated cases (6.5 days), no vaccinated cases (7.5 days), and partially vaccinated cases (5.5 days). Conclusions The median latent period of SARS‐CoV‐2 Delta VOC infection was 6.0 days. The latent period between vaccinated and non‐vaccinated patients was not significantly different. The 14‐day quarantine program is sufficient to prevent the transmission of COVID‐19 by Delta VOC in the postvaccination era.

Using detailed exposure information on COVID-19 cases, we estimated the mean latent period to be 5.5 (95% CI: 5.1–5.9) days, shorter than the mean incubation period (6.9 days). Laboratory testing may allow shorter quarantines since 95% of COVID-19 cases shed virus within 10.6 (95% CI: 9.6–11.6) days of infection. [ABSTRACT FROM AUTHOR]

The current study aimed to investigate the neuropharmacological properties of ethanol, acetone, and ethyl acetate leaf extracts of Chassalia curviflora (C. curviflora) in mouse models. The neuropharmacological properties of this plant were studied on Swiss albino mice at dosages of 50, 100, and 200 mg/kg body weight in thiopental sodium-induced sleeping time test, and at dosages of 100 and 200 mg/kg body weight in other tests. The extracts caused a marked reduction in the initiation and sleep length (P<0.05) in studies on thiopental sodium-induced sleeping time at dosages of 100 and 200 mg/kg and a significant decrease (P<0.05) was found in terms of unconstrained locomotor and explorative activities in both hole crossing and open field tests at dosages of 100 and 200 mg/kg. Furthermore, the extracts increased sleeping time with a dosage-dependent onset of action. The hole-board test extracts also reduced the number of head dips at dosages of 100 and 200 mg/kg (P<0.05). It was found in this study that C. curviflora had the best neuropharmacological properties at a dosage of 200 ml/kg. Our findings also showed that all of the extracts from C. curviflora were experimentally active in an in vivo model. The study results suggested that the leaves had strong anti-depressant and hypnotic CNS properties that might be exploited for neuropharmacological adjuvant therapy in conventional medicine. However, pharmacological studies are warranted to explore the active substances and the mode of action. [ABSTRACT FROM AUTHOR]

Background. Heracleum sosnowskyi Manden. (family Umbelliferae = Apiaceae) is included in the lists of invasive species in many regions of Russia and European countries. Mericarps (fruits conventionally called seeds) of Heracleum L. spp. are characterized by an underdeveloped embryo and a complex morphophysiological type of dormancy; two-stage stratification is needed for their germination.Methods. In the period from 2014 to 2019, fruits of H. sosnowskyi were collected near settlements in Vyborg and Gatchina Districts, Leningrad Province; collecting was carried out from August through March. Seed size and 1000 seed weight were measured. Germination experiments were performed in the laboratory (22–24°C) monthly, from the time of collection in August until May. Seeds were germinated in Petri dishes on filter paper with three replications.Results. Large seeds on marginal umbellules of the central umbel were the largest in size. Their length was from 0.6 to 1.4 cm, width from 5 to 11 mm, and 1000 seed weight from 9 to 18 g. The length of smaller fruits was from 7 to 9 mm, width from 3 to 5 mm, and 1000 seed weight from 10.5 to 11.8 g. Germination of seeds collected in late summer was protracted. Under laboratory conditions, the emergence of the first seedlings was observed after 5–7 days. For the fruits stored in the laboratory, germination was reduced. Germination rate of stratified seeds varied from 55 to 99%.Conclusion. The biometric parameters of H. sosnowskyi mericarps were slightly affected by the place of growth and the year of maturation. Under laboratory conditions, H. sosnowskyi seeds collected in August showed germination rates from 3 to 15%. In years with a warm and long autumn, part of the fruit germinated in the year of maturation and managed to reach their juvenile state. Plump mericarps remained viable for at least three years. Sosnowsky’s hogweed fruits stored under laboratory conditions lost their germination ability within a year.

Fusarium head blight (FHB) leads to significant quality and yield losses makes the FHB disease an important threat in all barley-growing areas of the world. Till now, available empirical data are limited on the efficiency of quantitative barley resistance expected to reduce in several generations because of the selection of FHB isolates with a high level of quantitative component of pathogenicity, i.e., aggressiveness, because of the difficulty of conducting such studies in the field. To achieve this goal, the evolutionary aggressiveness response was analyzed in four FHB pathogens faced with selective pressure using in vitro serial passage assays on susceptible "S" and moderately resistant "MR" barley. Differences due to the selective effect of a cultivar among non-selected and selected FHB isolates were quantified for traits participating to parasitic (area under disease progress curve (AUDPC) and latent period (LP)) fitness. The pathogen populations adapted quickly to the "MR" cultivar than the "S" cultivar. The selective barley impact on the analyzed FHB pathogens seemed to be species-specific. The results showed that selected isolates on the "MR" cultivar presenting a high level of aggressiveness than selected isolates from "S" cultivar, as they had a shorter LP (21.8%) and a higher level of AUDPC (22.1%). These findings provide the first direct evidence that FHB pathogens evolve rapidly to adapt by increasing aggressiveness to barley, indicating a risk of directional selection (i.e., deployment of a resistance gene) and possible erosion, evolution of aggressiveness due to resistance selection pressure over generations can lead to quantitative resistance erosion, of barely resistance, a vital component for the progress of durable control policies for resistant barley cultivars to FHB infection. [ABSTRACT FROM AUTHOR]

Citrus limon L. is an ingenious alternative medication and has a broad scope in managing several health conditions as part of natural remedies. Recently, medicinal plants have witnessed incredible consideration worldwide in the field of neuroscience for remedial intervention. The present work has investigated the phytochemical compounds and neuropharmacological potential of the seed extract of Citrus limon as a step to partially validate its formulations as nutraceuticals using an in vivo model. Diverse phytochemical groups such as alkaloids, glycosides, flavonoids, tannins, gums, saponins, steroids were qualitatively identified through colorimetric methods utilizing standard compounds. The neuropharmacological properties were studied in Swiss albino mice with the sleep time induced by thiopental sodium taken as an end-point, in standard hole cross, hole board, and open-field experiments at varying doses of 50 and 100 mg/kg body weight. Phytochemical screening showed that alkaloids, flavonoids, saponins, tannins, steroids, and glycosides are present in the aqueous extract of the seed. The extracts demonstrated a significant reduction in sleep onset and enhanced the sleep duration in a dose-dependent manner in thiopental sodium-induced sleeping time, along with a marked decrease in unconstrained locomotors and explorative properties in both hole cross and open field tests. Moreover, in the hole board study, the extracts minimized the count of head dips observed in the treated mice. The results shown in this study demonstrate that Citrus limon extracts have neuropharmacological properties that can be further examined for their potential role as an adjuvant with conventional medications or nutraceuticals. [ABSTRACT FROM AUTHOR]

Background and Objectives: Citrus greening (HLB) is one of the most damaging citrus diseases worldwide. As well, the three most important causal agents of this disease in the world include "Candidatus (Ca.) Liberibacter asiaticus ("CLas"), Ca. Liberibacter africanus ("CLaf"), and Ca. Liberibacter americanus ("CLam"). Accordingly, these were reported from Asian-American, African, and American countries, respectively. Of note, "CLas" species is found as the most important causal agent of this disease in all countries in the world, including Iran. It seems that the most effective way to reduce HLB is finding those cultivars that are resistant or tolerant to HLB. Accordingly, in the present study, an attempt was made to evaluate the reaction of a number of common citrus cultivars to this bacterium. Materials and Methods: In the present research, ten commercial rootstocks and cultivars of the common citrus in the south of Iran, including Mexican lime, sour orange, mandarin orange, Kinnow mandarin, Orlando tangelo mandarin, local orange, Valencia orange, sweet lemon, grapefruit, and Lisbon lemons were prepared as seedlings. After checking their health, they were inoculated with the citrus greening agent and then kept in an insect-free greenhouse at night at 25°C and during the day at 30°C.By passing two months from the inoculation, the pathogen was detected by performing specialized tests in inoculated seedlings. Thereafter, three two-year-old seedlings from each one of the above-mentioned rootstocks and cultivars were grafted with two infected buds. Two months after the inoculation, normal and nested PCR tests were performed on the vein tissue extract of the infected seedlings, once every two months, for a 12-month duration. Finally, both sensitivity and relative resistance of cultivars were evaluated based on the average number of days until the detection of the first Ca. L. asiaticus by PCR and also the incubation period of the disease, in each seedling. Results: The causal agent of this disease ("CLas") was detected at the earliest time(in Valencia oranges and Orlando tangelo mandarin after 180 and 200 days, respectively) after the inoculation with infected graft, compared to other cultivars and rootstocks. Among the studied species, the "CLas" was detected in both Mexican lime and Lisbon lemon with the longest delay (by passing 330 and 300 days from the inoculation, respectively). According to the results, "CLas" was detected in sour orange and sweet lemon 290 and 280 days after the inoculation with infected graft, respectively. Based on the average number of days until the detection of the first Ca. L. asiaticus by PCR and also the incubation period of the disease, in each seedling, Mexican lime and Lisbon lemon were found as the most tolerant species and Valencia oranges and Orlando tangelo mandarin were found as the most susceptible ones to HLB. Moreover, sour orange and sweet lemon seedlings were moderately susceptible ones; and grapefruit, local orange, local, and Kinnow mandarin were moderately tolerant to HLB. Discussion: Due to the reason that this bacterium does not grow in conventional medium, in this study, it was not possible to multiply it in artificial medium and then contaminate the plant with it. Therefore, performing the inoculation through grafting the seedlings with HLB infected buds was considered as the most appropriate method for seedlings inoculation with the pathogen. The faster the pathogen can settle and multiply and the symptoms appear in the host, the greater the susceptibility of the host to the disease. Early pathogen's detection and symptoms' observation in some hosts such as Valencia oranges and Orlando tangelo mandarin, indicate better bacterial proliferation in both cultivars. Notably, no symptoms of the disease were observed in Mexican lime and Lisbon lemons after 15 months, and one year after the inoculation in sour orange and sweet lemon plants. There is evidence that all known citrus cultivars are affected to this pathogen with different degrees of susceptibility. Based on the results of this study and the results of previous researchers in the world, it seems that researchers should look for the sources of resistance factors to HLB in more species and cultivars. Correspondingly, these sources can be used in the following two ways: used as a rootstock or scion, and used in the efforts of breeders to produce a resistant cultivar. [ABSTRACT FROM AUTHOR]

Till now, no published study is available on the variation in pathogenicity of Fusarium head blight (FHB) pathogens in relation to their isolation origin in barley head. To end this, two barley cultivars of contrasting quantitative resistance were artificially infected by four FHB species under field conditions over two consecutive growing seasons. Then, pathogenicity tests were conducted under in vitro conditions on single-spore cultures originated from both kernels and glumes in the heads. Different pathogenicity was detected among Fusarium species originated from both kernels and glumes, indicating that the same isolate from glumes and kernels differs in pathogenicity on leaves/seedlings. Isolates of Fusarium culmorum and Fusarium verticillioides originated from infected kernels had shorter latent periods and higher area under disease progress curves compared to isolates originated from glumes, and the reverse was observed for the Fusarium equiseti isolate. In the case of Fusarium solani, isolates originated from kernels or from glumes were equally pathogenic. Primarily findings in this first in-depth study have implications for breeding programs relied principally on actual quantification of pathogenicity in Fusarium species present in a given environment. The sampling of fungi should take into account the presence of Fusarium species of interest on kernels or glumes. [ABSTRACT FROM AUTHOR]

The spread of a contagious disease clearly depends on when infected individuals come into contact with susceptible ones. Such effects, however, have remained largely unexplored in the study of epidemic outbreaks. In particular, it remains unclear how the timing of contacts interacts with the latent and infectious stages of the disease. Here, we use real-world physical proximity data to study this interaction and find that the temporal statistics of actual human contact patterns (i) destabilize epidemic outbreaks and (ii) modulate the basic reproduction number R _0 . We explain both observations by distinct aspects of the observed contact patterns. On the one hand, we find the destabilization of outbreaks to be caused by the temporal clustering of contacts leading to over-dispersed offspring distributions and increased probabilities of otherwise rare events (zero- and super-spreading). Notably, our analysis enables us to disentangle previously elusive sources of over-dispersion in empirical offspring distributions. On the other hand, we find the modulation of R _0 to be caused by a periodically varying contact rate. Both mechanisms are a direct consequence of the memory in contact behavior, and we showcase a generative process that reproduces these non-Markovian statistics. Our results point to the importance of including non-Markovian contact timings into studies of epidemic outbreaks.

Viral impacts on microbial populations depend on interaction phenotypes-including viral traits spanning the adsorption rate, latent period, and burst size. The latent period is a key viral trait in lytic infections. Defined as the time from viral adsorption to viral progeny release, the latent period of bacteriophage is conventionally inferred via one-step growth curves in which the accumulation of free virus is measured over time in a population of infected cells. Developed more than 80 years ago, one-step growth curves do not account for cellular-level variability in the timing of lysis, potentially biasing inference of viral traits. Here, we use nonlinear dynamical models to understand how individual-level variation of the latent period impacts virus-host dynamics. Our modeling approach shows that inference of the latent period via one-step growth curves is systematically biased-generating estimates of shorter latent periods than the underlying population-level mean. The bias arises because variability in lysis timing at the cellular level leads to a fraction of early burst events, which are interpreted, artefactually, as an earlier mean time of viral release. We develop a computational framework to estimate latent period variability from joint measurements of host and free virus populations. Our computational framework recovers both the mean and variance of the latent period within simulated infections including realistic measurement noise. This work suggests that reframing the latent period as a distribution to account for variability in the population will improve the study of viral traits and their role in shaping microbial populations.IMPORTANCEQuantifying viral traits-including the adsorption rate, burst size, and latent period-is critical to characterize viral infection dynamics and develop predictive models of viral impacts across scales from cells to ecosystems. Here, we revisit the gold standard of viral trait estimation-the one-step growth curve-to assess the extent to which assumptions at the core of viral infection dynamics lead to ongoing and systematic biases in inferences of viral traits. We show that latent period estimates obtained via one-step growth curves systematically underestimate the mean latent period and, in turn, overestimate the rate of viral killing at population scales. By explicitly incorporating trait variability into a dynamical inference framework that leverages both virus and host time series, we provide a practical route to improve estimates of the mean and variance of viral traits across diverse virus-microbe systems., Competing Interests: The authors declare no conflict of interest.

Drug reaction with eosinophilia and systemic symptoms (DRESS) is a severe drug reaction characterized by skin rash, organ involvement, lymph node swelling, eosinophilia, and atypical lymphocytosis, with myocarditis being a rare but potentially fatal complication. It has been reported that in patients with cardiac involvement due to DRESS, older age and shorter periods between offending drug exposure and symptom onset are associated with mortality. We report a case of fatal DRESS-associated myocarditis in a young woman, occurring one month after drug exposure, despite intensive immunosuppressive therapy. This case report highlights the risk of mortality from DRESS-associated myocarditis even in patients lacking known risk factors., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Watanabe et al.)

Temporal Lobe Epilepsy (TLE) is a neurological condition characterized by focal brain hyperexcitability, resulting in abnormal neuronal discharge and uncontrollable seizures. The hippocampus, with its inherently highly synchronized firing patterns and relatively high excitability, is prone to epileptic seizures, and it is usually the focus of TLE. Researchers have identified hippocampal high-frequency oscillations (HFOs) as a salient feature in people with TLE and animal models of this disease, arising before or at the onset of the epileptic event. To a certain extent, these pathological HFOs have served as a marker and a potential target for seizure attenuation using electrical or optogenetic interventions. However, many questions remain about whether we can reliably distinguish pathological from non-pathological HFOs and whether they can tell us about the development of the disease. While this would be an arduous task to perform in humans, animal models of TLE provide an excellent opportunity to study the characteristics of HFOs in predicting how epilepsy evolves. This minireview will (1) summarize what we know about the oscillatory disruption in TLE, (2) summarize knowledge about oscillatory changes in the latent period and their role in predicting seizures, and (3) propose future studies essential to uncovering potential treatments based on early detection of pathological HFOs. [ABSTRACT FROM AUTHOR]