Integrated clinical and genomic models using machine-learning methods to predict the efficacy of paclitaxel-based chemotherapy in patients with advanced gastric cancer.

BACKGROUND: Paclitaxel is commonly used as a second-line therapy for advanced gastric cancer (AGC). The decision to proceed with second-line chemotherapy and select an appropriate regimen is critical for vulnerable patients with AGC progressing after first-line chemotherapy. However, no predictive biomarkers exist to identify patients with AGC who would benefit from paclitaxel-based chemotherapy. METHODS: This study included 288 patients with AGC receiving second-line paclitaxel-based chemotherapy between 2017 and 2022 as part of the K-MASTER project, a nationwide government-funded precision medicine initiative. The data included clinical (age [young-onset vs. others], sex, histology [intestinal vs. diffuse type], prior trastuzumab use, duration of first-line chemotherapy), and genomic factors (pathogenic or likely pathogenic variants). Data were randomly divided into training and validation sets (0.8:0.2). Four machine learning (ML) methods, namely random forest (RF), logistic regression (LR), artificial neural network (ANN), and ANN with genetic embedding (ANN with GE), were used to develop the prediction model and validated in the validation sets. RESULTS: The median patient age was 64 years (range 25-91), and 65.6% of those were male. A total of 288 patients were divided into the training (n = 230) and validation (n = 58) sets. No significant differences existed in baseline characteristics between the training and validation sets. In the training set, the areas under the ROC curves (AUROC) for predicting better progression-free survival (PFS) with paclitaxel-based chemotherapy were 0.499, 0.679, 0.618, and 0.732 in the RF, LR, ANN, and ANN with GE models, respectively. The ANN with the GE model that achieved the highest AUROC recorded accuracy, sensitivity, specificity, and F1-score performance of 0.458, 0.912, 0.724, and 0.579, respectively. In the validation set, the ANN with GE model predicted that paclitaxel-sensitive patients had significantly longer PFS (median PFS 7.59 vs. 2.07 months, P = 0.020) and overall survival (OS) (median OS 14.70 vs. 7.50 months, P = 0.008). The LR model predicted that paclitaxel-sensitive patients showed a trend for longer PFS (median PFS 6.48 vs. 2.33 months, P = 0.078) and OS (median OS 12.20 vs. 8.61 months, P = 0.099). CONCLUSIONS: These ML models, integrated with clinical and genomic factors, offer the possibility to help identify patients with AGC who may benefit from paclitaxel chemotherapy.

A Bayesian framework for modeling COVID-19 case numbers through longitudinal monitoring of SARS-CoV-2 RNA in wastewater.

Wastewater-based surveillance has become an important tool for research groups and public health agencies investigating and monitoring the COVID-19 pandemic and other public health emergencies including other pathogens and drug abuse. While there is an emerging body of evidence exploring the possibility of predicting COVID-19 infections from wastewater signals, there remain significant challenges for statistical modeling. Longitudinal observations of viral copies in municipal wastewater can be influenced by noisy datasets and missing values with irregular and sparse samplings. We propose an integrative Bayesian framework to predict daily positive cases from weekly wastewater observations with missing values via functional data analysis techniques. In a unified procedure, the proposed analysis models severe acute respiratory syndrome coronavirus-2 RNA wastewater signals as a realization of a smooth process with error and combines the smooth process with COVID-19 cases to evaluate the prediction of positive cases. We demonstrate that the proposed framework can achieve these objectives with high predictive accuracies through simulated and observed real data.

Surveillance for SARS-CoV-2 and its variants in wastewater of tertiary care hospitals correlates with increasing case burden and outbreaks.

Wastewater-based SARS-CoV-2 surveillance enables unbiased and comprehensive monitoring of defined sewersheds. We performed real-time monitoring of hospital wastewater that differentiated Delta and Omicron variants within total SARS-CoV-2-RNA, enabling correlation to COVID-19 cases from three tertiary-care facilities with >2100 inpatient beds in Calgary, Canada. RNA was extracted from hospital wastewater between August/2021 and January/2022, and SARS-CoV-2 quantified using RT-qPCR. Assays targeting R203M and R203K/G204R established the proportional abundance of Delta and Omicron, respectively. Total and variant-specific SARS-CoV-2 in wastewater was compared to data for variant specific COVID-19 hospitalizations, hospital-acquired infections, and outbreaks. Ninety-six percent (188/196) of wastewater samples were SARS-CoV-2 positive. Total SARS-CoV-2 RNA levels in wastewater increased in tandem with total prevalent cases (Delta plus Omicron). Variant-specific assessments showed this increase to be mainly driven by Omicron. Hospital-acquired cases of COVID-19 were associated with large spikes in wastewater SARS-CoV-2 and levels were significantly increased during outbreaks relative to nonoutbreak periods for total SARS-CoV2, Delta and Omicron. SARS-CoV-2 in hospital wastewater was significantly higher during the Omicron-wave irrespective of outbreaks. Wastewater-based monitoring of SARS-CoV-2 and its variants represents a novel tool for passive COVID-19 infection surveillance, case identification, containment, and potentially to mitigate viral spread in hospitals.

Multi-Filter Clustering Fusion for Feature Selection in Rotating Machinery Fault Classification.

In the fault classification process, filter methods that sequentially remove unnecessary features have long been studied. However, the existing filter methods do not have guidelines on which, and how many, features are needed. This study developed a multi-filter clustering fusion (MFCF) technique, to effectively and efficiently select features. In the MFCF process, a multi-filter method combining existing filter methods is first applied for feature clustering; then, key features are automatically selected. The union of key features is utilized to find all potentially important features, and an exhaustive search is used to obtain the best combination of selected features to maximize the accuracy of the classification model. In the rotating machinery examples, fault classification models using MFCF were generated to classify normal and abnormal conditions of rotational machinery. The obtained results demonstrated that classification models using MFCF provide good accuracy, efficiency, and robustness in the fault classification of rotational machinery.

Updating the modified Thompson test by using whole-body bioluminescence imaging to replace traditional efficacy testing in experimental models of murine malaria.

BACKGROUND: Rodent malaria models are extensively used to predict treatment outcomes in human infections. There is a constant need to improve and refine these models by innovating ways to apply new scientific findings and cutting edge technologies. In addition, and in accordance with the three R's of animal use in research, in vivo studies should be constantly refined to avoid unnecessary pain and distress to the experimental animals by using preemptive euthanasia as soon as the main scientific study objective has been accomplished. METHODS: The new methodology described in this manuscript uses the whole-body bioluminescence signal emitted by transgenic, luciferase-expressing Plasmodium berghei parasites to assess the parasite load predicted parasitaemia (PLPP) in drug and control treated female ICR-CD1 mice infected with 1 × 105 luciferase-expressing P. berghei (ANKA strain) infected erythrocytes. This methodology can replace other time-consuming and expensive methods that are routinely used to measure parasitaemia in infected animals, such as Giemsa-stained thin blood smears and flow cytometry. RESULTS: There is a good correlation between whole-body bioluminescence signal and parasitaemia measured using Giemsa-stained thin blood smears and flow cytometry respectively in donor and study mice in the modified Thompson test. The algebraic formulas which represent these correlations can be successfully used to assess PLPP in donor and study mice. In addition, the new methodology can pinpoint sick animals 2-8 days before they would have been otherwise diagnosed based on behavioural or any other signs of malaria disease. CONCLUSIONS: The new method for predicting parasitaemia in the modified Thompson test is simple, precise, objective, and minimizes false positive results that can lead to the premature removal of animals from study. Furthermore, from the animal welfare perspective of replace, reduce, and refine, this new method facilitates early removal of sick animals from study as soon as the study objective has been achieved, in many cases well before the clinical signs of disease are present.

SDF-1α/CXCR4 signaling mediates digit tip regeneration promoted by BMP-2.

Previously we demonstrated that BMP signaling is required for endogenous digit tip regeneration, and that treatment with BMP-2 or -7 induces a regenerative response following amputation at regeneration-incompetent levels (Yu et al., 2010, 2012). Both endogenous regeneration and BMP-induced regeneration are associated with the transient formation of a blastema, however the formation of a regeneration blastema in mammals is poorly understood. In this study, we focus on how blastema cells respond to BMP signaling during neonatal digit regeneration in mice. First, we show that blastema cells retain regenerative properties after expansion in vitro, and when re-introduced into the amputated digit, these cells display directed migration in response to BMP-2. However, in vitro studies demonstrate that BMP-2 alone does not influence blastema cell migration, suggesting a requirement of another pivotal downstream factor for cell recruitment. We show that blastema cell migration is stimulated by the cytokine, SDF-1α, and that SDF-1α is expressed by the wound epidermis as well as endothelial cells of the blastema. Blastema cells express both SDF-1α receptors, CXCR4 and CXCR7, although the migration response is inhibited by the CXCR4-specific antagonist, AMD3100. Mice treated with AMD3100 display a partial inhibition of skeletal regrowth associated with the regeneration response. We provide evidence that BMP-2 regulates Sdf-1α expression in endothelial cells but not cells of the wound epidermis. Finally, we show that SDF-1α-expressing COS1 cells engrafted into a regeneration-incompetent digit amputation wound resulted in a locally enhanced population of CXCR4 positive cells, and induced a partial regenerative response. Taken together, this study provides evidence that one downstream mechanism of BMP signaling during mammalian digit regeneration involves activation of SDF-1α/CXCR4 signaling by endothelial cells to recruit blastema cells.

Potential health risks to disinfection workers from exposure to active substances in COVID-19 biocidal products.

The importance of disinfection has recently been emphasized due to the increasing risk of the spread of infections such as coronavirus disease-2019 (COVID-19). In addition, disinfection for preventing the spread of COVID-19 is highly recommended. The increased use of biocidal products raises concerns regarding the potential health risks from exposure among disinfection workers. This study aimed to assess these exposure and health risks using questionnaires targeting disinfection workers who were exposed to the active substances in biocidal products used for disinfection during the COVID-19 pandemic. A follow-up survey was conducted among 271 disinfection workers for 10 working days within two weeks, and exposure factors with reference to disinfection were evaluated through interview-administered questionnaires. An exposure algorithm was used to evaluate the exposure of disinfection workers during disinfection. The hazard index (HI) was calculated by dividing the inhalation concentration obtained using the exposure algorithm and the dermal dose according to occupational exposure limits (OEL). A sensitivity analysis was conducted to identify the exposure factors with the greatest impact on the inhalation and dermal exposure algorithms. A logistic regression analysis was performed to verify the relationship with health effects and sociodemographic and exposure characteristics. The average number of disinfections performed during 10 working days was 17.5 ± 12.3 times. The type of disinfection work was divided into 2806 cases of COVID-19 prevention and disinfection and 1956 cases of regular pesticide application to prevent and remove any pests. The HI was ≥1, indicating a potential health risk, with the use of ethanol (6.50E+00), quaternary ammonium compounds (QACs; 1.49E+01), and benzalkonium chloride (BKC; 1.73E+00). Dermal exposure was more hazardous than inhalation exposure for 6 of the 11 active substances in biocidal products. The weight fraction and exposure time were the factors that most significantly influenced the inhalation and dermal exposure algorithms in the sensitivity analysis. Higher exposure concentrations were more likely to affect health (AOR: 3.239, 95% CI: 1.155-9.082). This study provides valuable information regarding the exposure and risk of disinfection workers to 11 biocidal active substances included in common disinfectants. Our results suggest that the use of ethanol, BKC, and QACs has potential health risks to disinfection workers, with a higher possibility of negative health impacts with increasing exposure concentration.

BMP2 induces segment-specific skeletal regeneration from digit and limb amputations by establishing a new endochondral ossification center.

Bone morphogenetic proteins (BMPs) are required for bone development, the repair of damage skeletal tissue, and the regeneration of the mouse digit tip. Previously we showed that BMP treatment can induce a regeneration response in mouse digits amputated at a proximal level of the terminal phalangeal element (P3) (Yu et al., 2010). In this study, we show that the regeneration-inductive ability of BMP2 extends to amputations at the level of the second phalangeal element (P2) of neonatal digits, and the hindlimb of adult limbs. In these models the induced regenerative response is restricted in a segment-specific manner, thus amputated skeletal elements regenerate distally patterned skeletal structures but does not form joints or more distal skeletal elements. Studies on P2 amputations indicate that BMP2-induced regeneration is associated with a localized proliferative response and the transient expression of established digit blastema marker genes. This is followed by the formation of a new endochondral ossification center at the distal end of the bone stump. The endochondral ossification center contains proliferating chondrocytes that establish a distal proliferative zone and differentiate proximally into hypertrophic chondrocytes. Skeletal regeneration occurs from proximal to distal with the appearance of osteoblasts that differentiate in continuity with the amputated stump. Using the polarity of the endochondral ossification centers induced by BMP2 at two different amputation levels, we show that BMP2 activates a level-dependent regenerative response indicative of a positional information network. In summary, our studies provide evidence that BMP2 induces the regeneration of mammalian limb structures by stimulating a new endochondral ossification center that utilizes an existing network of positional information to regulate patterning during skeletal regeneration.

Regeneration of the elbow joint in the developing chick embryo recapitulates development.

Synovial joints are among the most important structures that give us complex motor abilities as humans. Degenerative joint diseases, such as arthritis, cause loss of normal joint functioning and affect over 40 million people in the USA and approximately 350 million people worldwide. Therapies based on regenerative medicine hold the promise of effectively repairing or replacing damaged joints permanently. Here, for the first time, we introduce a model for synovial joint regeneration utilizing the chick embryo. In this model, a block of tissue that contains the prospective elbow is excised, leaving a window with strips of anterior and posterior tissue intact (window excision, WE). In contrast, we also slice out the same area containing the elbow and the distal piece of the limb is pinned back onto the stump (slice excision, SE). Interestingly, when the elbow is removed via WE, regeneration of the joint takes place, whereas the elbow joint does not regenerate following SE. In order to investigate whether the regeneration response recapitulates the developmental program of forming joints, we used GDF-5 and Autotaxin (Atx) as joint tissue specific markers, and Sox-9 and Col-9 as cartilage markers for in situ hybridization on sections at different time points after WE and SE surgeries. Re-expression of GDF-5 and Atx is observed in the WE samples by 60h after surgery. In contrast, the majority of the samples that underwent SE surgery did not express GDF-5 and Atx. Also, in SE fusion of cartilage elements takes place and the joint interzone does not form. This is indicated by continuous Col-9 expression in SE limbs, whereas Col-9 is downregulated at the joint interzone in the regenerating WE samples. This order and pattern of gene expression observed in regenerates is similar to the development of a joint suggesting that regeneration recapitulates development at the molecular level. This model defines some of the conditions required for inducing joint regeneration in an otherwise nonregenerating environment. This knowledge can be useful for designing new therapeutic approaches for joint loss or for conditions affecting joint integrity in humans.

BMP signaling induces digit regeneration in neonatal mice.

The regenerating digit tip of mice is a novel epimorphic response in mammals that is similar to fingertip regeneration in humans. Both display restricted regenerative capabilities that are amputation-level dependent. Using this endogenous regeneration model in neonatal mice, we have found that noggin treatment inhibits regeneration, thus suggesting a bone morphogenetic protein (BMP) requirement. Using non-regenerating amputation wounds, we show that BMP7 or BMP2 can induce a regenerative response. BMP-induced regeneration involves the formation of a mammalian digit blastema. Unlike the endogenous regeneration response that involves redifferentiation by direct ossification (evolved regeneration), the BMP-induced response involves endochondral ossification (redevelopment). Our evidence suggests that BMP treatment triggers a reprogramming event that re-initiates digit tip development at the amputation wound. These studies demonstrate for the first time that the postnatal mammalian digit has latent regenerative capabilities that can be induced by growth factor treatment.

Dlx5 and Msx2 regulate mouse anterior neural tube closure through ephrinA5-EphA7.

Homeodomain-containing transcription factors Dlx5 and Msx2 are able to form a heterodimer, and together can regulate embryonic development including skeletogenesis. Dlx5 functions as a transcriptional activator and Msx2 a transcriptional repressor, and they share common target genes. During mouse digit development, the expression domains of Dlx5 and Msx2 overlap at the distal region of the developing terminal phalange, although digit formation and regeneration are not altered in the Dlx5 and Msx2 null mutant embryos. Interestingly, we observed a high rate of defects in neural tube formation in Dlx5 and Msx2 double null mutants. In the absence of both Dlx5 and Msx2, a high occurrence of exencephaly and severe defects in craniofacial morphology are observed. Additionally, Dlx5 and Msx2 expression domain analysis showed overlap of the genes at the apex of the neural folds just prior to neural fold fusion. The expression patterns of ephrinA5 and two isoforms of EphA7 were tested as downstream targets of Dlx5 and Msx2. Results show that EphrinA5 and the truncated isoform of EphA7 are regulated by Dlx5 and Msx2 together, although the full length isoform of EphA7 expression is not altered. Overall, these data show that Dlx5 and Msx2 play a critical role in controlling cranial neural tube morphogenesis by regulating cell adhesion via the ephrinA5 and EphA7 pathway.

Thermal annealing effects on the physical properties of styrenic pentablock ionomers and their electromechanical responses.

Thermal annealing effect on the physical properties of two ionic (poly((t-butyl-styrene)-b-(ethylene-r-propylene)-b-(styrene-r-styrene sulfonate)-b-(ethylene-r-propylene)-b-(t-butyl-styrene (SSPB) pentablock copolymers with different ion exchange capacities (IEC; 1.5 and 2.0 meq/g) and their electromechanical responses in ionic polymer-metal composite (IPMC) devices have been investigated. The ionic SSPB formed the microphase-separated morphology on the several tens nanometer scale and the selectively sulfonated styrene middle blocks formed the ionic channels through which ions can pass in the membrane. The thermal annealing at a high temperature led to the well developed interconnectivity between adjacent ionic channels, and thus enhanced the ion conductivity and mechanical strength of membranes, resulting in an actuation enhancement of the SSPB-based ionic actuator.

Differential effects of wastewater treatment plant effluents on the antibiotic resistomes of diverse river habitats.

Wastewater treatment plants (WWTPs) are key sources of antimicrobial resistance genes (ARGs) that could influence the resistomes of microbial communities in various habitats of the receiving river ecosystem. However, it is currently unknown which habitats are most impacted and whether ARGs, like certain chemical contaminants, could be accumulated or enriched in the river ecosystem. We conducted a systematic metagenomic survey on the antibiotic resistomes of WWTP effluent, four riverine habitats (water, suspended particles, sediment, epilithic biofilm), and freshwater amphipod gut microbiomes. The impact of WWTP effluent on the downstream habitats was assessed in nine Swiss rivers. While there were significant differences in resistomes across habitats, the wastewater resistome was more similar to the resistome of receiving river water than to the resistomes of other habitats, and river water was the habitat most strongly impacted by the WWTPs effluent. The sulfonamide, beta-lactam, and aminoglycoside resistance genes were among the most abundant ARGs in the WWTP effluents, and especially aadA, sul1, and class A beta-lactamase genes showed significantly increased abundance in the river water of downstream compared to upstream locations (p < 0.05). However, this was not the case for the sediment, biofilm, and amphipod gut habitats. Accordingly, evidence for accumulation or enrichment of ARGs through the riverine food web was not identified. Our study suggests that monitoring riverine antimicrobial resistance determinants could be conducted using "co-occurrence" of aadA, sul1, and class A beta-lactamase genes as an indicator of wastewater-related pollution and should focus on the water as the most affected habitat.

Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism.

Wastewater-based surveillance (WBS) of infectious diseases is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19's impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.4 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5 % (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4524 unrelated absences COVID-19 cases were recorded. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (P < 0.0001). The Poisson regression with wastewater as a one-week leading signal has an Akaike information criterion (AIC) of 858, compared to a null model (excluding wastewater predictor) with an AIC of 1895. The likelihood-ratio test comparing the model with wastewater signal with the null model shows statistical significance (P < 0.0001). We also assessed the variation of predictions when the regression model was applied to new data, with the predicted values and corresponding confidence intervals closely tracking actual absenteeism data. Wastewater-based surveillance has the potential to be used by employers to anticipate workforce requirements and optimize human resource allocation in response to trackable respiratory illnesses like COVID-19.

Campus node-based wastewater surveillance enables COVID-19 case localization and confirms lower SARS-CoV-2 burden relative to the surrounding community.

Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this approach has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021 and April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater using qPCR assays from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary's campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Real-time contact tracing data was used to evaluate an association between wastewater SARS-CoV-2 burden and clinically confirmed cases and to assess the potential of WBS as a tool for disease monitoring across worksites. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites - regardless of several normalization strategies - with certain catchments consistently demonstrating values 1-2 orders higher than the others. Relative to clinical cases identified in specific sewersheds, WBS provided one-week leading indicator. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p≤0.001). Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.

Wastewater bypass is a major temporary point-source of antibiotic resistance genes and multi-resistance risk factors in a Swiss river.

Untreated combined sewage (bypass) is often discharged by wastewater treatment plants to receiving rivers during stormwater events, where it may contribute to increased levels of antibiotic resistance genes (ARGs) and multi-resistance risk factors (multi-resistant bacteria and multi-resistance genomic determinants (MGDs)) in the receiving water. Other contamination sources, such as soil runoff and resuspended river sediment could also play a role during stormwater events. Here we report on stormwater event-based sampling campaigns to determine temporal dynamics of ARGs and multi-resistance risk factors in bypass, treated effluent, and the receiving river, as well as complimentary data on catchment soils and surface sediments. Both indicator ARGs (qPCR) and resistome (ARG profiles revealed by metagenomics) indicated bypass as the main contributor to the increased levels of ARGs in the river during stormwater events. Furthermore, we showed for the first time that the risk of exposure to bypass-borne multi-resistance risk factors increase under stormwater events and that many of these MGDs were plasmid associated and thus potentially mobile. In addition, elevated resistance risk factors persisted for some time (up to 22 h) in the receiving water after stormwater events, likely due to inputs from distributed overflows in the catchment. This indicates temporal dynamics should be considered when interpreting the risks of exposure to resistance from event-based contamination. We propose that reducing bypass from wastewater treatment plants may be an important intervention option for reducing dissemination of antibiotic resistance.

Identification of factors affecting removal of antibiotic resistance genes in full-scale anaerobic digesters treating organic solid wastes.

Efficiencies of removing antibiotic resistance genes (ARGs) and intI1 were explored using eight full-scale anaerobic digesters. The digesters demonstrated different characteristics on the basis of substrate types (food waste, manure or sludge); configuration (single or two-stage); temperature (psychrophilic, mesophilic or thermophilic); hydraulic retention time (HRT) (9.7-44 days); and operation mode (continuous stirred tank reactor or plug flow reactor). Digesters' configuration or operating parameters showed a greater effect on abundance of ARGs than the type of input substrate. Redundancy analysis (RDA) accounted for 85.2% of the total variances and digesters with the same configuration and operational conditions showed similar performance for removal of ARGs. The highest efficiencies of removing ARGs (99.99%) were observed in two-stage thermophilic digesters with relatively long HRTs (32 days). The lowest removal efficiency (97.93%) was observed in single-stage mesophilic with relatively short HRTs (9.7 days), likely due to vertical and horizontal gene transfer.

Long-term enrichment of anaerobic propionate-oxidizing consortia: Syntrophic culture development and growth optimization.

Propionate is a quantitatively important methanogenic intermediate in anaerobic digesters and only limited number of microbes can utilize it under syntrophic association with methanogens. The syntrophic propionate oxidizing bacterias are known to be slow growers due to the low energy yield. Thus, propionate get accumulated frequently in anaerobic digesters and it negatively affect digester performance. In this study, propionate degrading consortia from four different seeding sources were enriched in sequential bath mode in two phases; first adaption phase with 1 g/L of propionate concentration and later, high-strength phase with 3 g/L. From 16s rRNA gene based metagenomics analysis of the former phase, four syntrophic microbial groups, Syntrophaceae, Syntrophomonadaceae, Methanobacterium and Methanosaeta were found to be dominant with complete degradation of propionate. The substrate accelerated microbial shifts were observed at high-strength phase with significant decrease of Syntrophaceae up to 26.9 %. Using Response Surface Methodology, pH 6.8-6.9 and temperature 34.5-34.9 °C were found to be optimum growth conditions for the propionate degradation culture. Observed results could be useful to improve degradation efficiencies and obtained enriched culture can be used to recover propionate-accumulated digesters by bio-augmentation.

Deployment of the 1st Area Medical Laboratory to South Korea in Response to the COVID-19 Pandemic.

In December 2019, an outbreak of pneumonia caused by a novel coronavirus, severe acute respiratory syndrome (SARS)-CoV-2, occurred in Wuhan city, Hubei province, China.1 South Korea saw its first confirmed Coronavirus Disease 2019 (COVID-19) case on January 20, 2020, when an infected woman from Wuhan, China arrived in S. Korea via Incheon International Airport.1 By mid-February, SARS-CoV-2 was rapidly spreading in the southern city of Daegu, S. Korea in proximity to three US Forces Korea (USFK) military installations. COVID-19 cases continued to increase during the following weeks, reaching a peak of nearly 1,000 confirmed cases per day by the end of February. As cases surged dramatically, over 28,000 USFK service members, family members, and Department of Defense (DoD) employees were at a risk of exposure to COVID-19. On February 24, clinicians diagnosed the first confirmed case in the USFK population, a 61 year-old widow of a retired service member. This individual, who experienced a mild illness, was the spouse of a retired US military veteran living in S. Korea. The retiree and his spouse both had access to military posts in S. Korea, and the spouse tested positive after she had been on one of the military bases in Area IV (Figure 1). The following day, USFK reported its first confirmed case in a service member, which was the triggering event for the 1st Area Medical Laboratory (AML) to deploy to S. Korea.

Unraveling the riverine antibiotic resistome: The downstream fate of anthropogenic inputs.

River networks are one of the main routes by which the public could be exposed to environmental sources of antibiotic resistance, that may be introduced e.g. via treated wastewater. In this study, we applied a comprehensive integrated analysis encompassing mass-flow concepts, chemistry, bacterial plate counts, resistance gene quantification and shotgun metagenomics to track the fate of the resistome (collective antibiotic resistance genes (ARGs) in a microbial community) of treated wastewater in two Swiss rivers at the kilometer scale. The levels of certain ARGs and the class 1 integron integrase gene (intI1) commonly associated with anthropogenic sources of ARGs decreased quickly over short distances (2-2.5 km) downstream of wastewater discharge points. Mass-flow analysis based on conservative tracers suggested this decrease was attributable mainly to dilution but ARG loadings frequently also decreased (e.g., 55.0-98.5 % for ermB and tetW) over the longest studied distances (6.8 and 13.7 km downstream). Metagenomic analysis confirmed that ARG of wastewater-origin did not persist in rivers after 5 ~ 6.8 km downstream distance. sul1 and intI1 levels and loadings were more variable and even increased sharply at 5 ~ 6.8 km downstream distance on one occasion. While input from agriculture and in-situ positive selection pressure for organisms carrying ARGs cannot be excluded, in-system growth of biomass is a more probable explanation. The potential for direct human exposure to the resistome of wastewater-origin thus appeared to typically abate rapidly in the studied rivers. However, the riverine aquatic resistome was also dynamic, as evidenced by the increase of certain gene markers downstream, without obvious sources of anthropogenic contamination. This study provides new insight into drivers of riverine resistomes and pinpoints key monitoring targets indicative of where human sources and exposures are likely to be most acute.