Determining the Fate of NON-O157 Shiga Toxin-Producing Escherichia Coli in Dairy Compost During Storage using the Optimized Detection Method

Shiga toxin-producing Escherichia coli (STEC), a member of Enterobacteriaceae family, has been recognized as emerging pathogens. Dairy compost is commonly applied to farmland as a soil amendment. Despite the agricultural benefit of manure-based soil amendment, the inadequately treated compost can contribute to fresh produce contamination on the farm. Moreover, the epidemiological results showed that the non-O157 STEC cases have surpassed those of E. coli O157. Therefore, it is critical to evaluate the behavior of non-O157 STEC strains in the dairy manure-based compost. The objectives of this study were to: 1) optimize a culturing method for detecting non-O157 STEC from dairy compost, 2) determine the growth potential of top six non-O157 STEC serovars in dairy compost, and 3) conduct a persistence study of non-O157 STEC in dairy compost being held at room temperature. First, we optimized a culturing method for detecting STEC during enrichment. Cefixime-tellurite Sorbitol MacConkey Agar supplemented with 5 mg/l novobiocin (CTN-SMAC) was chosen for enumerating non-O157 STEC cells before or after enrichment, as CTN-SMAC is more cost effective than Modified Rainbow Agar (mRBA) and both agar plates enumerated the same level of STEC. The single step selective enrichment recovered ca. 0.54 log CFU/g more cells as compared to the two-step enrichment. In addition, without enrichment step, the detection limit of individual STEC serovar ranged from 250 to 2,500 CFU/g in dairy compost. For STEC O26 and O145, the detection limit by IMS was 2,500 CFU/g, but for other STEC serotypes (O45, O103, O111, and O121), the detection limit was 250 CFU/g. Our results demonstrated that a low level of STEC (ca. 100 CFU/g) could be detected within one day from dairy compost by culturing method through optimized enrichment procedure followed by immunomagnetic beads separation (IMS). Next, we investigated the survival potential of non-O157 STEC in dairy compost during storage at room temperature. A mixture of six non-O157 STEC serovars was inoculated into commercially available dairy compost with 30% moisture content at a final concentration of ca. 5.5 log CFU/g. During storage at room temperature for up to 42 days, STEC counts and other factors such as indigenous microorganism population, moisture contents and pH were analyzed at selected sampling intervals. Both moisture contents and pH values in dairy compost remained unchanged (p\u3e0.05) during the entire duration of trials, and so did the background bacterial level. As for the STEC population, a growth of ca. 0.5 log CFU/g was recorded within the first day post inoculation, followed by a rapid decrease of ca. 1.5 log CFU/g during 14 days of storage. By the end of the experiment, the population level of non-O157 STEC reduced ca. 1.7 logs, and the survival curve displayed an extensive tailing. Randomly selected colonies from the last 3 sampling times were confirmed as STEC by PCR. Our results demonstrated that low-level of STEC could be detected within one day from the finished dairy compost by culturing method through optimized enrichment procedure followed by IMS, and non-O157 STEC persisted in dairy compost for at least 42 days, indicating the long-term survival of non-O157 STEC in the finished dairy compost. Therefore, proper handling and testing of the finished dairy compost as soil amendment is critical for ensuring the microbiological safety of fresh produce and the farm environment

A unified methodology of maintenance management for repairable systems based on optimal stopping theory

This dissertation focuses on the study of maintenance management for repairable systems based on optimal stopping theory. From reliability engineering’s point of view, all systems are subject to deterioration with age and usage. System deterioration can take various forms, including wear, fatigue, fracture, cracking, breaking, corrosion, erosion and instability, any of which may ultimately cause the system to fail to perform its required function. Consequently, controlling system deterioration through maintenance and thus controlling the risk of system failure becomes beneficial or even necessary. Decision makers constantly face two fundamental problems with respect to system maintenance. One is whether or when preventive maintenance should be performed in order to avoid costly failures. The other problem is how to make the choice among different maintenance actions in response to a system failure. The whole purpose of maintenance management is to keep the system in good working condition at a reasonably low cost, thus the tradeoff between cost and condition plays a central role in the study of maintenance management, which demands rigorous optimization. The agenda of this research is to develop a unified methodology for modeling and optimization of maintenance systems. A general modeling framework with six classifying criteria is to be developed to formulate and analyze a wide range of maintenance systems which include many existing models in the literature. A unified optimization procedure is developed based on optimal stopping, semi-martingale, and lambda-maximization techniques to solve these models contained in the framework. A comprehensive model is proposed and solved in this general framework using the developed procedure which incorporates many other models as special cases. Policy comparison and policy optimality are studied to offer further insights. Along the theoretical development, numerical examples are provided to illustrate the applicability of the methodology. The main contribution of this research is that the unified modeling framework and systematic optimization procedure structurize the pool of models and policies, weed out non-optimal policies, and establish a theoretical foundation for further development

Validation of Physically Heat-Treated Process for Poultry Litter and Analysis of Microbial Community of Animal Waste-Based Soil Amendments Using Sequencing Approach

Biological soil amendments of animal origin (BSAAO), such as animal waste or animal waste-based composts, commonly used as organic fertilizer, may contain human pathogens such as Salmonella and Listeria monocytogenes. To reduce harmful microorganisms, animal waste can be treated by composting or other validated scientific methods. But insufficient treatment may introduce pathogens into agricultural fields. As a nutrient-rich fertilizer, poultry litter may also contain human pathogens with Salmonella spp. as a primary focus. Physical heat treatments can kill Salmonella in poultry litter with or without the composting process, but validation studies or guidelines are still needed for the litter processing industry to ensure the microbial safety of their products. Further, due to the ubiquitous nature of L. monocytogenes, it is essential to understand the ecology of this pathogen where it inhabits and then develop strategies to reduce Listeria contamination. We hypothesized that compost-adapted competitive exclusion (CE) microorganisms against L. monocytogenes exist in animal waste-based compost. In combination with the culturing method, the use of next-generation sequencing approaches is expected to speed up the discovery of those compost-borne CE microorganisms for controlling L. monocytogenes in pre-harvest environments. Therefore, the objectives of this study were to 1) test a nonpathogenic surrogate microorganism for validating desiccation-adapted Salmonella inactivation in physically heat-treated broiler litter, 2) validate the physical heat treatment of poultry litter composts using surrogate and indicator microorganisms for Salmonella in industrial settings, 3) use next-generation sequencing approaches to understand the microbial community profile and functions in animal waste-based compost in the presence and absence of L. monocytogenes, and 4) isolate and identify the competitive exclusion microorganisms against L. monocytogenes in biological soil amendments.In order to test a non-pathogenic surrogate for validating desiccation-adapted Salmonella inactivation in physically heat-treated broiler litter, thermal resistance of desiccation-adapted S. ser. Senftenberg 775/W was compared with that of Enterococcus faecium NRRL B-2354 in aged broiler litter. Samples of aged broiler litter with 20, 30, and 40% moisture content were inoculated separately with desiccation-adapted S. Senftenberg 775/W and E. faecium NRRL B-2354 at ca. 5 to 6 log CFU/g, and then heat-treated at 75, 85, and 150°C. At all tested temperatures, desiccation-adapted E. faecium NRRL B-2354 was more heat-resistant than desiccation-adapted S. Senftenberg 775/W (P \u3c 0.05). During the treatments at 75 and 85°C, E. faecium NRRL B-2354 in aged broiler litter with all moisture contents was reduced by 2.9- to 4.1-log, and was above the detection limit of direct plating (1.3 log CFU/g), whereas S. Senftenberg 775/W could not be detected by enrichment (\u3e 5-log reductions) during holding time at these temperatures. At 150°C, E. faecium NRRL B-2354 in aged broiler litter with 20 and 30% moisture contents was still detectable by enrichment after heat exposure for up to 15 min, whereas S. Senftenberg 775/W in aged broiler litter with all moisture contents could not be detected throughout the entire treatment. Our results revealed that E. faecium NRRL B-2354 can be used as a surrogate for Salmonella to validate the thermal processing of poultry litter by providing a sufficient safety margin. This study provides a practical tool for poultry litter processors to evaluate the effectiveness of their thermal processing. Next, we used indicator and surrogate microorganisms for Salmonella to validate the processes for physically heat-treated poultry litter compost in both lab settings and commercial plants. Initial lab validation studies indicated that 1.2- to 2.7-log or more reductions of desiccation-adapted E. faecium NRRL B-2354 were equivalent to \u3e 5-log reductions of desiccation-adapted Salmonella Senftenberg 775/W in poultry litter compost, depending on treatment conditions and compost types. Industrial plant validation studies were performed in one turkey litter processor and one laying hen litter processor. E. faecium was inoculated at ca.7-log CFU/g into the composted turkey litter and at ca. 5 log CFU/g into laying hen litter compost with respectively targeted moisture contents. The thermal processes in the two plants yielded reductions in E. faecium of 2.8 - \u3e 6.4 log CFU/g (\u3e 99.86%) of the inoculated. Similarly, for the processing control samples, reductions of presumptive indigenous enterococci were in the order of 1.8-3.7 log CFU/g (98.22% to 99.98 %) of the total naturally present. In contrast, there was less reduction of indigenous mesophiles (1.7-2.9 log CFU) and thermophiles (0.4-3.2 log CFU/g). Statistical analysis indicated that more indigenous enterococci were inactivated in the presence of higher moisture in the poultry litter compost. In conclusion, based on the data collected under the laboratory conditions, the processing conditions in both plants were adequate to reduce any potential Salmonella contamination of processed poultry litter material by at least 5-log, even though the processing conditions varied among trials and plants. Further, to understand the complex interactions between native compost microorganisms and L. monocytogenes, compost samples collected across the US were subjected to the inoculation of L. monocytogenes, and then systematically analyzed using 16S rRNA gene, shotgun-metagenomic, and metatranscriptomic sequencing approaches along with culturing methods. The reductions of L. monocytogenes in dairy and poultry compost with 40 or 80% moisture content at room temperature after 72 h of incubation ranged from 0.1 to 1.1 log CFU/g. Regrowth of L. monocytogenes occurred in some compost samples after 72 h of incubation, ranging from 0.1 to 1.5 log CFU/g. The major bacterial phyla identified in all farms are Firmicutes (23%), Proteobacteria (23%), Actinobacteria (19%), Chloroflexi (13%), Bacteroidetes (12%), Gemmatimonadetes (2%), and Acidobacteria (2%). The statistical analysis of sequencing data revealed that microbial interactions were affected by environmental factors such as compost types and location, moisture levels and incubation length, rather than the inoculation of L. monocytogenes. Although the similarities percentage (SIMPER) results are not significant for all samples, some specific genera (Bacillus, Sphaerobacter, Filomicrobium, Paucisalibacillus, Brumimicrobium, Steroidobacter Flavobacterium, or Chryseolinea) were identified as discriminant microorganisms contributing to the variation in community composition due to the presence of L. monocytogenes on multiple farms. After 72 h of incubation, changes in the metabolic pathways and the increased abundance of the bacteriocins category in the compost samples containing L. monocytogenes suggest that the interactions between L. monocytogenes and compost microbiome may include competition for compost nutrients and the presence of antimicrobials produced by the compost microbiome. Findings from this study clearly indicated that microbial diversity and functional profiles were significantly (P \u3c 0.05) affected by the compost source, compost stage, and collection farm. Furthermore, the presence of specific discriminant microbial species may suggest certain compost samples as the potential sources for isolating CE microorganisms against L. monocytogenes. Competitive exclusion (CE) microorganisms have shown great potential as environmentally friendly tools to control harmful microorganisms. In consideration of dairy and poultry compost containing a diversity of microbial species, it was hypothesized that the compost may be a good source for isolating compost-borne CE microorganisms, which can inhibit the growth of Listeria monocytogenes. In this study, CE strains were screened and isolated from compost using double- or triple-agar-layer methods. The addition of resuscitation promoting factor (Rpf) produced by Micrococcus luteus promoted the growth of slow-growing/viable but non-culturable species from compost. A total of 40 bacterial isolates were confirmed with anti-L. monocytogenes activities, and then tested for Gram-reaction, motility, biofilm-forming ability, and inhibitory spectra against produce outbreak-associated L. monocytogenes and surrogate strains, followed by identification via 16S rRNA gene sequencing. About 50% of the isolated CE strains were identified as Bacillus spp., and 17 of 40 isolates can inhibit more than 10 produce outbreak-associated L. monocytogenes strains, while 9 CE strains isolated from poultry litter compost were confirmed as motile and competitive biofilm formers. Those 40 CE isolates based on the origin of isolation were separated into two groups, i.e. poultry and dairy CE groups, and then tested for anti-L. monocytogenes activity in both compost extracts and the compost. After 168 h incubation, the growth potentials of L. monocytogenes were reduced by co-culturing with CE strains in compost extracts under all conditions by 0.1- to 1.9- log depending on incubation temperature, types, and ratio of the compost extracts. Results showed that the inhibition effect from CE strains was higher in more concentrated compost extract (1:5) at 35°C or room temperature. In compost samples, the addition of CE strains can reduce L. monocytogenes population by ca. 1.2 log CFU/g at room temperature after 24 to 168 h incubation. The efficacy of CE strains was greater in the dairy compost as compared to that in the poultry litter compost. Findings from this study suggested that compost-adapted CE microorganisms have the potential as a biological control agent to control L. monocytogenes in agricultural environments. In summary, current processes for physically heat-treated poultry litter in industrial settings have been validated, In addition, this study provided tools (surrogate and/or indicator microorganism for Salmonella, and custom-designed sampler) for litter processors to modify their existing process parameters to produce Salmonella-free physically heat-treated poultry litter, which can be used by the produce industry to grow microbiologically safe products. Both compositional and functional changes in microbial communities of compost samples were studied, and the CE microorganisms with antagonistic activities against L. monocytogenes were identified. Based on metagenomics and culturing approaches, we have demonstrated that composts can be a rich source of CE microorganisms as potential biological control agents, which can be used for foodborne pathogen control in both preharvest and postharvest environments. Results generated from this study have provided both validation and biological control tools for ensuring microbiological safety of animal waste-based biological soil amendments

Compositional and Functional Changes in Microbial Communities of Composts Due to the Composting-Related Factors and the Presence of \u3ci\u3eListeria monocytogenes\u3c/i\u3e

Listeria monocytogenes is a leading foodborne pathogen that can contaminate fresh produce in farm environment, resulting in deadly outbreaks. Composts contain a diversity of microorganisms, and some of them may be compost-adapted competitive exclusion microorganisms against L. monocytogenes. To understand interactions between compost microflora and the pathogen, both dairy- and poultry-wastes based composts (n = 12) were inoculated with L. monocytogenes, and then analyzed by next-generation sequencing approaches along with culturing methods. DNA extraction and enumeration of L. monocytogenes were performed at 0 and 72 h post-incubation at room temperature. The major bacterial phyla were identified as Firmicutes (23%), Proteobacteria (23%), Actinobacteria (19%), Chloroflexi (13%), Bacteroidetes (12%), Gemmatimonadetes (2%), and Acidobacteria (2%). The top three indicator genera enriched in different compost types were identified by LEfSe with LDA score . 2. The interactions between L. monocytogenes and indigenous microflora were limited as no significant changes in the dominant microbial members in compost ecosystem, but some discriminatory species such as Bacillus, Geobacillus, and Brevibacterium were identified by Random Forest analysis. Besides, changes in metabolic pathways and the increased abundance of bacteriocins category in the compost samples containing L. monocytogenes after 72 h postinoculation were revealed by metatranscriptomic sequencing. Taken together, the compost-related factors such as compost types, composting stages, and the collection farms are major drivers that affect compost microbial compositions, and the analysis of compost metagenome implied that interactions between L. monocytogenes and compost microflora may include competition for nutrients and the presence of antimicrobials

The equilibria of Ta-W-Al-Si-O system at 1200 °C

Solid reactions among Ta-W-Al-Si oxides are discussed and the phase compatibilities of these oxides at 1200 °C have been investigated. The results showed that complex oxides of TaWO, TaWO, TaWO, AlWO and AlTaO could be formed by solid reactions. Liquid phase formed by AlO-WO in WO-SiO-AlO benefits the mullitization reaction, thus mullite can be formed at 1200 °C in ternary system. Solid solution with a formula of (1-x)TaO·xWO was formed, and up to 25.0% SiO and 6.0% AlO can be dissolved in the solid solution. Liquid phase first appeared in the TaO-WO-AlO ternary system at 1300 °C in the WO-rich corner. As the temperature increased, the liquidus area expanded towards the AlO- and the TaO-rich corners

Transcriptome profiling reveals the crucial biological pathways involved in cold response in Moso bamboo (Phyllostachys edulis).

Most bamboo species including Moso bamboo (Phyllostachys edulis) are tropical or subtropical plants that greatly contribute to human well-being. Low temperature is one of the main environmental factors restricting bamboo growth and geographic distribution. Our knowledge of the molecular changes during bamboo adaption to cold stress remains limited. Here, we provided a general overview of the cold-responsive transcriptional profiles in Moso bamboo by systematically analyzing its transcriptomic response under cold stress. Our results showed that low temperature induced strong morphological and biochemical alternations in Moso bamboo. To examine the global gene expression changes in response to cold, 12 libraries (non-treated, cold-treated 0.5, 1 and 24 h at -2 °C) were sequenced using an Illumina sequencing platform. Only a few differentially expressed genes (DEGs) were identified at early stage, while a large number of DEGs were identified at late stage in this study, suggesting that the majority of cold response genes in bamboo are late-responsive genes. A total of 222 transcription factors from 24 different families were differentially expressed during 24-h cold treatment, and the expressions of several well-known C-repeat/dehydration responsive element-binding factor negative regulators were significantly upregulated in response to cold, indicating the existence of special cold response networks. Our data also revealed that the expression of genes related to cell wall and the biosynthesis of fatty acids were altered in response to cold stress, indicating their potential roles in the acquisition of bamboo cold tolerance. In summary, our studies showed that both plant kingdom-conserved and species-specific cold response pathways exist in Moso bamboo, which lays the foundation for studying the regulatory mechanisms underlying bamboo cold stress response and provides useful gene resources for the construction of cold-tolerant bamboo through genetic engineering in the future

Developing an Active Canopy Sensor-Based Integrated Precision Rice Management System for Improving Grain Yield and Quality, Nitrogen Use Efficiency, and Lodging Resistance

Active crop sensor-based precision nitrogen (N) management can significantly improve N use efficiency but generally does not increase crop yield. The objective of this research was to develop and evaluate an active canopy sensor-based precision rice management system in terms of grain yield and quality, N use efficiency, and lodging resistance as compared with farmer practice, regional optimum rice management system recommended by the extension service, and a chlorophyll meter-based precision rice management system. Two field experiments were conducted from 2011 to 2013 at Jiansanjiang Experiment Station of China Agricultural University in Heilongjiang, China, involving four rice management systems and two varieties (Kongyu 131 and Longjing 21). The results indicated that the canopy sensor-based precision rice management system significantly increased rice grain yield (by 9.4–13.5%) over the farmer practice while improving N use efficiency, grain quality, and lodging resistance. Compared with the already optimized regional optimum rice management system, in the cool weather year of 2011, the developed system decreased the N rate applied in Kongyu 131 by 12% and improved N use efficiency without inducing yield loss. In the warm weather year of 2013, the canopy sensor-based management system recommended an 8% higher N rate to be applied in Longjing 21 than the regional optimum rice management, which improved rice panicle number per unit area and eventually led to increased grain yield by over 10% and improved N use efficiency. More studies are needed to further test the developed active canopy sensor-based precision rice management system under more diverse on-farm conditions and further improve it using unmanned aerial vehicle or satellite remote sensing technologies for large-scale applications.publishedVersio

An injection-locked single-longitudinal-mode fiber ring laser with cylindrical vector beam emission

We demonstrate a fiber ring laser with narrow bandwidth single-longitudinal-mode cylindrical vector beam (CVB) output at C-band wavelength range for the first time to the best of our knowledge. A step index two-mode fiber Bragg grating is used as a transverse mode selector for CVB generation, while both the injection-locking technique and narrow bandwidth of the fiber Bragg grating lead to single-longitudinal-mode operation. The 3-dB bandwidth of the laser output is measured to be 60 dB. Mode distribution and optical spectra of few-mode fibers with periodic modulated refractive index profile, namely the few-mode fiber Bragg gratings with bent radius, are investigated theoretically and experimentally, which provide a comprehensive exploration of CVB's generation

Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach

Fairness in machine learning has attracted increasing attention in recent years. The fairness methods improving algorithmic fairness for in-distribution data may not perform well under distribution shifts. In this paper, we first theoretically demonstrate the inherent connection between distribution shift, data perturbation, and model weight perturbation. Subsequently, we analyze the sufficient conditions to guarantee fairness (i.e., low demographic parity) for the target dataset, including fairness for the source dataset, and low prediction difference between the source and target datasets for each sensitive attribute group. Motivated by these sufficient conditions, we propose robust fairness regularization (RFR) by considering the worst case within the model weight perturbation ball for each sensitive attribute group. We evaluate the effectiveness of our proposed RFR algorithm on synthetic and real distribution shifts across various datasets. Experimental results demonstrate that RFR achieves better fairness-accuracy trade-off performance compared with several baselines. The source code is available at \url{https://github.com/zhimengj0326/RFR_NeurIPS23}.Comment: NeurIPS 202

Retiring Δ\DeltaDP: New Distribution-Level Metrics for Demographic Parity

Demographic parity is the most widely recognized measure of group fairness in machine learning, which ensures equal treatment of different demographic groups. Numerous works aim to achieve demographic parity by pursuing the commonly used metric $\Delta DP$. Unfortunately, in this paper, we reveal that the fairness metric $\Delta DP$ can not precisely measure the violation of demographic parity, because it inherently has the following drawbacks: i) zero-value $\Delta DP$ does not guarantee zero violation of demographic parity, ii) $\Delta DP$ values can vary with different classification thresholds. To this end, we propose two new fairness metrics, Area Between Probability density function Curves (ABPC) and Area Between Cumulative density function Curves (ABCC), to precisely measure the violation of demographic parity at the distribution level. The new fairness metrics directly measure the difference between the distributions of the prediction probability for different demographic groups. Thus our proposed new metrics enjoy: i) zero-value ABCC/ABPC guarantees zero violation of demographic parity; ii) ABCC/ABPC guarantees demographic parity while the classification thresholds are adjusted. We further re-evaluate the existing fair models with our proposed fairness metrics and observe different fairness behaviors of those models under the new metrics. The code is available at https://github.com/ahxt/new_metric_for_demographic_parityComment: Accepted by TMLR. Code available at https://github.com/ahxt/new_metric_for_demographic_parit