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Abstract Antimicrobial resistance (AMR) is a growing public health crisis that requires innovative solutions. Current susceptibility testing approaches limit our ability to rapidly distinguish between antimicrobial-susceptible and -resistant organisms. Salmonella Typhimurium (S. Typhimurium) is an enteric pathogen responsible for severe gastrointestinal illness and invasive disease. Despite widespread resistance, ciprofloxacin remains a common treatment for Salmonella infections, particularly in lower-resource settings, where the drug is given empirically. Here, we exploit high-content imaging to generate deep phenotyping of S. Typhimurium isolates longitudinally exposed to increasing concentrations of ciprofloxacin. We apply machine learning algorithms to the imaging data and demonstrate that individual isolates display distinct growth and morphological characteristics that cluster by time point and susceptibility to ciprofloxacin, which occur independently of ciprofloxacin exposure. Using a further set of S. Typhimurium clinical isolates, we find that machine learning classifiers can accurately predict ciprofloxacin susceptibility without exposure to it or any prior knowledge of resistance phenotype. These results demonstrate the principle of using high-content imaging with machine learning algorithms to predict drug susceptibility of clinical bacterial isolates. This technique may be an important tool in understanding the morphological impact of antimicrobials on the bacterial cell to identify drugs with new modes of action.

Various data analysis techniques and procedures (correlation heatmap, linear discriminant analysis, quadratic discriminant analysis) rely on the estimation of the covariance matrix or its inverse (the precision matrix). However, missing data can pose significant challenges to this parameter estimation problem. When missing data is presented, imputation is a common way to circumvent the issue as it renders the data complete. Nevertheless, it is imperative to scrutinize the potential trade-offs when opting for imputation as opposed to task-specific methods for handling missing data, especially in the context of subsequent data analysis and inference. In this study, we undertake both empirical and theoretical investigations to assess the impact of imputation in contrast to direct parameter estimation approaches. We focus on the task of estimating the covariance matrix and precision matrix and present an analysis of the error induced by estimating the precision matrix by the inverse of an estimated covariance matrix. Additionally, we propose a sufficient condition that ensures improved performance guarantees for precision matrix estimation based on covariance matrix estimation. The experimental results show that when the number of features is small, direct parameter estimations can be recommended to estimate the precision matrix by inverting the corresponding estimated covariance matrix. However, when the number of features is not small, then inverting the covariance matrix of imputed data gives better results.

Live coccidiosis vaccines have mainly been used to reduce Eimeria species infection, which is considered the most economically important disease in the poultry industry. Evaluation data on vaccine effectiveness through large-scale field experiments are lacking, especially in broilers. Thus, the effectiveness of a commercial coccidiosis vaccine was evaluated in approximately 900,000 chicks reared on three open-broiler farms where coccidiosis is prevalent. The vaccine’s effectiveness after vaccination of 1-day-old chicks was monitored using three parameters (lesion score, fecal oocyst shedding, and production index, PI) in nine trials performed three times on each farm. Lesion scores were confirmed in three different areas of the intestine because the vaccine contained four Eimeria species. The average lesion scores were 0.36 to 0.64 in the duodenal region, 0.30 to 0.39 in the jejuno-ileal region, and 0.18 to 0.39 in the cecal region. The average fecal oocyst shedding rate ranged from 19,766 to 100,100 oocysts per gram, showing large variations depending on farms and buildings within the farm. Compared with the PI of the previous 9–10 trials on each farm, the PI increased by 2.45 to 23.55. Because of the potential for perturbation of the fecal microbiota by live coccidiosis vaccines, the fecal microbiota was investigated using 16S rRNA microbial profiling. Although the β-diversity was significantly different in distribution and relative abundance among farms (PERMANOVA, pseudo-F = 4.863, p = 0.009), a Kyoto Encyclopedia of Genes and Genomes pathway analysis found no significant bacterial invasion of the epithelial cell pathway across farms. This large-scale field trial of a live Eimeria vaccine indicates that coccidiosis vaccines can have meaningful effects on the poultry industry and could be used as an alternative to the prophylactic use of anticoccidial drugs under field conditions.

Riemerella anatipestifer (RA) is an economically important pathogen in the duck industry worldwide that causes high mortality and morbidity in infected birds. We previously found that upregulated IL-17A expression in ducks infected with RA participates in the pathogenesis of the disease, but this mechanism is not linked to IL-23, which primarily promotes Th17 cell differentiation and proliferation. RNA sequencing analysis was used in this study to investigate other mechanisms of IL-17A upregulation in RA infection. A possible interaction of IL-26 and IL-17 was discovered, highlighting the potential of IL-26 as a novel upstream cytokine that can regulate IL-17A during RA infection. Additionally, this process identified several important pathways and genes related to the complex networks and potential regulation of the host immune response in RA-infected ducks. Collectively, these findings not only serve as a roadmap for our understanding of RA infection and the development of new immunotherapeutic approaches for this disease, but they also provide an opportunity to understand the immune system of ducks.

The spread of antibiotic-resistant Enterococcus in the poultry industry poses significant public health challenges due to multidrug resistance and biofilm formation. We investigated the antibiotic resistance profiles and biofilm characteristics of E. faecalis and E. faecium isolates from chicken meat in poultry slaughterhouses in South Korea. Ninety-six isolates (forty-eight each of E. faecalis and E. faecium) were collected between March and September 2022. Both species were analyzed using MALDI-TOF, PCR, antibiotic susceptibility testing, and biofilm assays. A high level of multidrug resistance was observed in E. faecalis (95.8%) and E. faecium (93.8%), with E. faecium exhibiting a broader range of resistance, particularly to linezolid (52.1%) and rifampicin (47.9%). All E. faecalis isolates formed biofilm in vitro, showing stronger biofilm formation than E. faecium with a significant difference (p < 0.001) in biofilm strength. Specific genes (cob, ccf, and sprE) were found to be correlated with biofilm strength. In E. faecium isolates, biofilm strength was correlated with resistance to linezolid and rifampicin, while a general correlation between antibiotic resistance and biofilm strength was not established. Through analysis, correlations were noted between antibiotics within the same class, while no general trends were evident in other analyzed factors. This study highlights the public health risks posed by multidrug-resistant enterococci collected from poultry slaughterhouses, emphasizing the complexity of the biofilm-resistance relationship and the need for enhanced control measures.

Avian influenza virus (AIV) is a pathogen with zoonotic and pandemic potential. Migratory birds are natural reservoirs of all known subtypes of AIVs, except for H17N10 and H18N11, and they have been implicated in previous highly pathogenic avian influenza outbreaks worldwide. This study identified and characterized the first isolate of the H13N6 subtype from a Vega gull (Larus vegae mongolicus) in South Korea. The amino acid sequence of hemagglutinin gene showed a low pathogenic AIV subtype and various amino acid substitutions were found in the sequence compared to the reference sequence and known H13 isolates. High sequence homology with other H13N6 isolates was found in HA, NA, PB1, and PA genes, but not for PB2, NP, M, and NS genes. Interestingly, various point amino acid mutations were found on all gene segments, and some are linked to an increased binding to human-type receptors, resistance to antivirals, and virulence. Evolutionary and phylogenetic analyses showed that all gene segments are gull-adapted, with a phylogeographic origin of mostly Eurasian, except for PB2, PA, and M. Findings from this study support the evidence that reassortment of AIVs continuously occurs in nature, and migratory birds are vital in the intercontinental spread of avian influenza viruses.

Protaetia brevitarsis larvae are farm-raised for food, are used in traditional East Asian medicine, and convert organic waste into biofertilizers. Here, the comparative analysis of the gut microbiota of third-instar larvae obtained from five different farms was investigated using 16S rRNA microbial profiling. Species richness, evenness, and diversity results using α-diversity analysis (observed species, Chao1, Shannon, Simpson) were similar between farms, except for those between the TO and KO farms. β-diversity was significantly different in distribution and relative abundance between farms (PERMANOVA, pseudo-F = 13.20, p = 0.001). At the phylum level, Bacillota, Bacteroidota, Actinomycetota, and Pseudomonadota were the most dominant, accounting for 73–88% of the hindgut microbial community. At the genus level, Tuberibacillus, Proteiniphilum, Desulfovibrio, Luoshenia, and Thermoactinomyces were the most abundant. Although oak sawdust was the main feed component, there were large variations in distribution and relative abundance across farms at the phylum and genus levels. Venn diagram and linear discriminant analysis effect size analyses revealed large variations in the hindgut microbial communities of P. brevitarsis larvae between farms. These results suggest environmental factors were more important than feed ingredients or genetic predisposition for the establishment of the intestinal microbiota of P. brevitarsis larvae. These findings serve as reference data to understand the intestinal microbiota of P. brevitarsis larvae.

Abstract Background Coccidiosis is a poultry disease that occurs worldwide and is caused by Eimeria species. The infection is associated with reduced feed efficiency, body weight gain, and egg production. This study aimed to investigate the current status of coccidiosis and anticoccidial resistance to anticoccidial drugs used as part of control strategies for this disease in Korean chicken farms. Results An overall prevalence of 75% (291/388) was found. Positive farms contained several Eimeria species (mean = 4.2). Of the positive samples, E. acervulina (98.6%), E. maxima (84.8%), and E. tenella (82.8%) were the most prevalent species. Compared with cage-fed chickens, broilers and native chickens reared in free-range management were more at risk of acquiring an Eimeria infection. Sensitivities to six anticoccidial drugs (clopidol, diclazuril, maduramycin, monensin, salinomycin, and toltrazuril) were tested using nine field samples. Compared with untreated healthy control chickens, the body weight gains of infected chickens and treated/infected chickens were significantly reduced in all groups. Fecal oocyst shedding was significantly reduced in four clopidol-treated/infected groups, three diclazuril-treated/infected groups, two toltrazuril-treated/infected groups, one monensin-treated/infected group, and one salinomycin-treated/infected group, compared with the respective untreated/infected control groups. Intestinal lesion scores were also reduced in three clopidol-treated/infected groups, one monensin-treated/infected group, and one toltrazuril-treated/infected group. However, an overall assessment using the anticoccidial index, percent optimum anticoccidial activity, relative oocyst production, and reduced lesion score index found that all field samples had strong resistance to all tested anticoccidial drugs. Conclusion The results of this large-scale epidemiological investigation and anticoccidial sensitivity testing showed a high prevalence of coccidiosis and the presence of severe drug resistant Eimeria species in the field. These findings will be useful for optimizing the control of coccidiosis in the poultry industry.

Measurement(s) diseases and abnormal findings from chest X-ray scans Technology Type(s) AI is used to detect diseases and abnormal findings Sample Characteristic - Location Vietnam

The volume and complexity of publicly available real estate data have been snowballing. As a result, information extraction and processing have become increasingly challenging and essential for many PropTech (Property Technology) companies worldwide. The challenges are even more pronounced with languages other than English, such as Vietnamese, where few studies in this field have taken place. This paper presents an end-to-end framework for automatically collecting real estate advertisement posts from different data sources, extracting useful information, and storing computed data into proper data warehouses and data marts for the Vietnamese advertisement posts in real estate. After that, one can serve aggregated data for other descriptive and predictive analytics. We combine two models for constructing the most appropriate extraction step: Noise Filtering and Named Entity Recognition (NER). These models can help process initial input data and extract all helpful information. The experiment results show that using $\text{PhoBERT}_{large}$ can achieve the best performance compared to other approaches. Furthermore, we can obtain the corresponding F1 scores of the Noise filtering module and the NER module as 0.8697 and 0.8996, respectively. Finally, we utilize Superset for implementing analytic dashboards to visualize the predicted results and serve for further analysis and management processes.

Summary: Background: We conducted a community-based seroprevalence study using three HBV seromarkers (HBsAg, anti-HBs, anti-HBc) in Ho Chi Minh City (HCMC), Vietnam, to (1) determine the prevalence of HBV serologic profiles; (2) document factors associated with HBV infection or susceptibility; and (3) propose strategies toward HBV elimination by 2030. Methods: During 2019–2020, we deployed a multistage cluster design with probability proportionate to size, to recruit 20,000 adults for an HBV screening and linkage to care program citywide. Screening results with interpretation, recommendations, and health education materials were returned to participants. Post-study surveys were conducted within three months to identify gaps in linkage to care. Findings: Of the 17,600 adults invited, 15,275 (86.7%) participated in the study, 14,674 (96.1%) completing all data for final analyses. The prevalence of HBsAg (+) and HBV-naïve were 7.5% and 37.7%, respectively. HBV vaccination rates were 18.7% and about 50% of HCMC population had been exposed to HBV. Of the persons with HBsAg (+), 27.1% linked to care (76% used health insurance). There were wide variations in HBsAg (+) and HBV vaccination rates between districts, risk factors, and socio-economic statuses. Interpretation: The significant disease burden of and gaps in the continuum of care highlight the need and urgency to address the HBV public health problem in Vietnam. Using three screening seromarkers that tailor interventions to the needs of HBV micro-populations could be an effective strategy to pursue HBV elimination goals. Funding: Gilead Sciences Inc; Roche Diagnostic International Ltd; Roche Diagnostics-Vietnam; Abbott Diagnostics-Vietnam; Hepatitis B Foundation; Medic MedicalCenter, Vietnam; Center of Excellence for Liver Disease in Vietnam, Johns Hopkins University School of Medicine.

Summary: Background: A baseline of hepatitis C virus (HCV) burden and other HCV epidemiological profiles is necessary for HCV micro-elimination in Ho Chi Minh City (HCMC), Viet Nam. This study aimed to determine HCV exposure and prevalence of HCV viremia as well as the proportion of HCV testing and treatment uptake among participants. Methods: From 2019 to 2020, the probability proportionate to size sampling method was deployed to representatively invite approximately 20,000 adults (18 or older) throughout HCMC to free screening and linkage to care for HCV. Findings: In HCMC, the weighted prevalence of anti-HCV was 1·3% (95% CI, 1·1%-1·6%). Individuals born from 1945 to 1964 had the anti-HCV prevalence of 3·6% (95% CI, 3·0%-4·2%) and represented 40·4% of all HCV cases. There were wide variations in anti-HCV prevalence in HCMC, including variations between districts, risk factors, and socioeconomic statuses. A baseline HCV continuum of care for the city demonstrated that only 28·5% (85/298, 95%CI 23·4-33·7%) of persons with anti-HCV (+) were aware of their HCV status, with 77.6% (66/85, 95%CI 68·8-86·5%) diagnosing HCV incidentally, 82·7% (62/75, 95%CI 74·1-91·2%) initiating anti-HCV therapy, and 53.6% (30/56, 95%CI 40·5-66·6%) achieving HCV cures. Interpretation: There remains a considerable disease burden of HCV in HCMC of which a significant proportion was in the age group born between 1945 to 1964. Additionally, there were significant gaps in HCV awareness, screening, and access to care in the community in Viet Nam. Thus, future interventions must have pragmatic targets, be tailored to the local needs, and emphasise screening. Funding: This work was supported by investigator-sponsored research grants from Gilead Sciences Inc. (Grant No: IN-US-987-5382); Roche Diagnostic International Ltd. (Grant No. SUB-000196); and in-kind donations from Abbott Diagnostic Viet Nam; Hepatitis B Foundation; Medic Medical Center, Viet Nam; Johns Hopkins University School of Medicine's Center of Excellence for Liver Disease in Viet Nam; and the Board of Directors, Viet Nam Viral Hepatitis Alliance (V-VHA).

In the present study, the photocatalytic activity of Ti-SBA-15/C3N4 catalysts was investigated to degrade 2,4-Dichlorophenoxyacetic acid (2,4-D) herbicides in water under visible light irradiation. The catalysts were synthesized via a simple hydrothermal method and characterized by various analytical techniques, including SAXS, N2 adsorption-desorption isotherms, Zeta potential, PL, FT-IR, XRF, TGA, and UV-DRS. Our study indicated that the 2.5Ti-SBA-15/C3N4 had higher efficiency in the degradation of 2,4-D than Ti-SBA-15 and C3N4. The decomposition of 2,4-D reached 60% under 180 minutes of visible light irradiation at room temperature on 2.5Ti-SBA-15/C3N4. Moreover, the degradation of 2,4-D on Ti-SBA-15/C3N4 was pseudo-first-order kinetics with the highest rate constant (0.00484 min−1), which was much higher than that obtained for other photocatalysts reported recently. Furthermore, the catalyst can be reused at least two times for photodegradation of 2,4-D solution under visible light irradiation within a slight decrease in catalytic activity.

Riemerella anatipestifer is one of the most devastating pathogens affecting the global duck farms. Infection is involved in secretion of proinflammatory cytokines, including interleukin- (IL-) 17A. During the immune response to infection, IL-22 and IL-17A are often produced concurrently and at high levels in inflamed tissues. Little is known about duck IL-22 (duIL-22) during R. anatipestifer infection. We describe the characterization of duIL-22 and its mRNA expression analysis in splenic lymphocytes and macrophages treated with heat-killed R. anatipestifer and in the spleens and livers of R. anatipestifer-infected ducks. Full-length cDNA of duIL-22 encoded 197 amino acids. The deduced amino acid sequence of duIL-22 shared a 30.4–40.5% similarity with piscine counterparts, 57.4–60.1% with mammalian homologs, and 93.4% similarity to the chicken. Duck IL-22 mRNA expression level was relatively high in the skin of normal ducks. It was increased in mitogen-stimulated splenic lymphocytes and in killed R. anatipestifer-activated splenic lymphocytes and macrophages. Compared with healthy ducks, IL-22 transcript expression was significantly upregulated in the livers and spleens on days 1 and 4 postinfection, but not on day 7. IL-17A was significantly increased in the spleens only on day 4 postinfection and in the livers at all time points. When splenic lymphocytes were stimulated with heat-killed R. anatipestifer, CD4+ cells predominantly produced IL-22 while IL-17A was expressed both by CD4+ and CD4- cells. These results suggested that IL-22 and IL-17A are likely expressed in different cell types during R. anatipestifer infection.

The explosive rise of intelligent devices with ubiquitous connectivity have dramatically increased Internet of Things (IoT) traffic in the cloud environment and created potential attack surfaces for cyber-attacks. Traditional security approaches are insufficient and inefficient to address security threats in cloud-based IoT networks. In this vein, software defined networking (SDN), network function virtualization (NFV), and machine learning techniques introduce numerous advantages that can effectively resolve cybersecurity matters for cloud-based IoT systems. In this paper, we propose a collaborative and intelligent network-based intrusion detection system (NIDS) architecture, namely SeArch for SDN-based cloud IoT networks. It composes a hierarchical layer of intelligent IDS nodes working in collaboration to detect anomalies and formulate policy into the SDN-based IoT gateway devices to stop malicious traffic as fast as possible. We first describe a new NIDS architecture with a comprehensive analysis in terms of the system resource and path selection optimizations. Next, the system process logic is extensively investigated through main consecutive procedures, including initialization, runtime operation, and database update. Afterward, we conduct a detailed implementation of the proposed solution in an SDN-based environment and perform a variety of experiments. Finally, evaluation results of the SeArch architecture yield outstanding performance in anomaly detection and mitigation as well as bottleneck problem handling in the SDN-based cloud IoT networks in comparison with existing solutions.

Wraparound programs that provide comprehensive evidence-based outpatient treatment, transportation, social services, and housing supports have shown promise for improving clinical behavioral health-related outcomes to reduce the need for institutionalized care; however, the majority of evidence is based on wraparound programs for children. This study examined the impact of a wraparound program for adult Medicaid managed care organization members with serious mental health or substance use disorders on health care costs and utilization. This retrospective observational study used 2013-2018 claims data collected from a large Medicaid managed care organization operating in multiple states. We used an intention-to-treat difference-in-difference study design to examine the association of the wraparound with costs and utilization. Adult Medicaid members with an emergency department (ED) or inpatient visit for a behavioral health condition (index visit) were eligible for the study. Outcomes included all-cause and behavioral health-related costs and utilization during follow-up after the index visit's admission date. Outcomes were calculated overall, as well as separately by inpatient, ED, and outpatient/wraparound settings. We found that during the first post-admission month, the wraparound program was associated with 27.6 percentage points (PP) and 27.2 PP reductions in the number of behavioral health-related inpatient nights and costs, respectively. However, during subsequent months (median follow-up ranging from 7 to 10 months) there were no associations with per-member-per-month total all-cause or behavioral health-related costs. Nonetheless, the wraparound program was associated with 12.3 PP reduction in all-cause cost during the entire study period among a subset of members who were high cost at the baseline. Reduced hospital utilization and costs during the first month of wraparound services were fully counteracted by outpatient, housing, and other wraparound services costs during the following months. This indicates the importance of proper payment arrangements with value-based contracting or performance targets with wraparound services providers to align the objective of reducing inpatient use. Future wraparound programs may consider a more focused recruitment from high-cost members with complex care needs. However, our estimates were conservative given that it's from a single Medicaid managed care organization's perspective and some benefit from investing in addressing social needs may be realized in longer term (beyond our study period). States' Medicaid programs may consider the longer-term cost and broader, societal benefit of wraparound investment.