Emergence of Long-Range Angular Correlations in Low-Multiplicity Proton-Proton Collisions

This Letter presents the measurement of near-side associated per-trigger yields, denoted ridge yields, from the analysis of angular correlations of charged hadrons in proton-proton collisions at sqrt[s]=13  TeV. Long-range ridge yields are extracted for pairs of charged particles with a pseudorapidity difference of 1.4<|Δη|<1.8 and a transverse momentum of 1 Collapse

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First Measurement of the |t| Dependence of Incoherent J/ψ Photonuclear Production

The first measurement of the cross section for incoherent photonuclear production of J/ψ vector mesons as a function of the Mandelstam |t| variable is presented. The measurement was carried out with the ALICE detector at midrapidity, |y|<0.8, using ultraperipheral collisions of Pb nuclei at a center-of-mass energy per nucleon pair of sqrt[s_{NN}]=5.02  TeV. This rapidity interval corresponds to a Bjorken-x range (0.3-1.4)×10^{-3}. Cross sections are given in five |t| intervals in the range 0.04<|t|<1  GeV^{2} and compared to the predictions by different models. Models that ignore quantum fluctuations of the gluon density in the colliding hadron predict a |t| dependence of the cross section much steeper than in data. The inclusion of such fluctuations in the same models provides a better description of the data.

ψ(2S) Suppression in Pb-Pb Collisions at the LHC

The production of the ψ(2S) charmonium state was measured with ALICE in Pb-Pb collisions at sqrt[s_{NN}]=5.02  TeV, in the dimuon decay channel. A significant signal was observed for the first time at LHC energies down to zero transverse momentum, at forward rapidity (2.5 Collapse

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Measurement of the Lifetime and Λ Separation Energy of _{Λ}^{3}H

The most precise measurements to date of the _{Λ}^{3}H lifetime τ and Λ separation energy B_{Λ} are obtained using the data sample of Pb-Pb collisions at sqrt[s_{NN}]=5.02  TeV collected by ALICE at the LHC. The _{Λ}^{3}H is reconstructed via its charged two-body mesonic decay channel (_{Λ}^{3}H→^{3}He+π^{-} and the charge-conjugate process). The measured values τ=[253±11(stat)±6(syst)]  ps and B_{Λ}=[102±63(stat)±67(syst)]  keV are compatible with predictions from effective field theories and confirm that the _{Λ}^{3}H structure is consistent with a weakly bound system.

Enhanced Deuteron Coalescence Probability in Jets

The transverse-momentum (p_{T}) spectra and coalescence parameters B_{2} of (anti)deuterons are measured in p-p collisions at sqrt[s]=13  TeV for the first time in and out of jets. In this measurement, the direction of the leading particle with the highest p_{T} in the event (p_{T}^{lead}>5  GeV/c) is used as an approximation for the jet axis. The event is consequently divided into three azimuthal regions, and the jet signal is obtained as the difference between the toward region, that contains jet fragmentation products in addition to the underlying event (UE), and the transverse region, which is dominated by the UE. The coalescence parameter in the jet is found to be approximately a factor of 10 larger than that in the underlying event. This experimental observation is consistent with the coalescence picture and can be attributed to the smaller average phase-space distance between nucleons in the jet cone as compared with the underlying event. The results presented in this Letter are compared to predictions from a simple nucleon coalescence model, where the phase-space distributions of nucleons are generated using pythia8 with the Monash 2013 tuning, and to predictions from a deuteron production model based on ordinary nuclear reactions with parametrized energy-dependent cross sections tuned on data. The latter model is implemented in pythia8.3. Both models reproduce the observed large difference between in-jet and out-of-jet coalescence parameters, although the almost flat trend of the B_{2}^{Jet} is not reproduced by the models, which instead give a decreasing trend.

Variations in antibiotic resistance genes and microbial community in sludges passing through biological nutrient removal and anaerobic digestion processes in municipal wastewater treatment plants

Antimicrobial resistance (AMR) represents a relentless, silent pandemic. Contributing to this are wastewater treatment plants (WWTPs), a potential source of antibiotic resistance genes' (ARGs) transmission to the environment, threatening public health. The presence of ARGs in pathogenic bacteria and their release into the environment by WWTPs threatens the public health. The current study investigated changes in ARGs' abundance in biological nutrient removal (BNR) processes and anaerobic digestion (AD) reactors of two WWTPs. Also, microbial community structure, which is known to shape the distribution and abundance of ARGs, was also analyzed. The relative abundance of eight ARGs (tetX, tetA, tetM, TEM, sul1, sul2, ermB and qnrD) was quantified as ARGs' copies/16 S rRNA gene copies using quantitative polymerase chain reaction (qPCR). Microbial community composition was assessed by 16 S rRNA microbiome sequencing analysis. TetX was prevalent among the eight ARGs, followed by TEM and sul1. However, its abundance was decreased in the AD sludges compared to BNR sludges. Proteobacteria was the major bacterial phylum found in all the sludge samples, while Arcobacter, 12up and Acidovorax were the predominant genera. Acinetobacter and Flavobacterium were significantly more abundant in the BNR sludges, while 12up and Aeromonas were predominant in AD sludges. Principal component analysis (PCA) revealed a clear difference in dominant ARGs and bacteria between the sludges in the processes of BNR and AD of the two WWTPs. Clinically relevant bacterial genera, Klebsiella and Enterococcus, found in both the BNR and AD sludges, were significantly correlated with the tetX gene. Throughout this study, the relationship between microbial communities and specific ARGs was revealed, illustrating that the composition of the microbial community could play a vital role in the abundance of ARGs. These results will better inform future studies aimed at controlling the spread of ARGs and their potential hosts from WWTPs.

High-Resolution T2-Weighted Imaging for Surveillance in Postoperative Vestibular Schwannoma: Equivalence with Contrast-Enhanced T1WI for Measurement and Surveillance of Residual Tumor

BACKGROUND AND PURPOSE

Patients with surgically resected vestibular schwannoma will undergo multiple postoperative surveillance examinations, typically including postcontrast sequences. The purpose of this study was to compare high-resolution T2WI with gadolinium T1WI in the postoperative assessment of vestibular schwannoma.

MATERIALS AND METHODS

This was a retrospective study of patients with a history of resected vestibular schwannoma at a single institution. High-resolution T2WI and gadolinium T1WI were independently evaluated for residual disease. In addition, 3D and 2D measurements were performed in the group of patients with residual tumor. Statistical analysis was performed to evaluate the agreement between sequences on the binary assessment (presence/absence of tumor on initial postoperative examination) and to evaluate the equivalence of measurements for the 2 sequences on 3D and 2D quantitative assessment in individuals with residual disease.

RESULTS

One hundred forty-eight patients with retrosigmoid-approach resection of vestibular schwannomas were included in the final analysis. There was moderate-to-substantial agreement between the 2 sequences for the evaluation of the presence versus absence of tumor (Cohen κ coefficient = 0.78; 95% CI, 0.68-0.88). The 2 sequences were significantly equivalent for 2D and 3D quantitative assessments (short-axis P value = .021; long-axis P value = .015; 3D P value = .039).

CONCLUSIONS

In this retrospective study, we demonstrate moderate-to-substantial agreement in the categoric assessment for the presence versus absence of tumor and equivalence between the 2 sequences for both 2D and volumetric tumor measurements as performed in the subset of patients with measurable residual. On the basis of these results, high-resolution T2WI alone may be sufficient for early postoperative imaging surveillance in this patient population.

Spatial and temporal effects of fish feed on antibiotic resistance in coastal aquaculture farms

For the first time, both spatial and temporal effects of fish feed on changes in abundance of antibiotic resistance genes (ARGs) were investigated in South Korea via quantifying ARGs and analyzing physicochemical parameters in the influent (IN) and effluent before (BF) and 30 min after (AF) the fish feeding time of sixteen flow-through fish farms. The absolute abundance of ARGs in AF samples was 5 times higher than in BF and 12 times higher than in IN samples. Values of physicochemical parameters such as ammonia, total nitrogen, suspended solids and turbidity in the effluent significantly increased by 21.6, 4.2, 2.6 and 1.65 times, respectively, after fish feeding. Spatially, the fish farms on Jeju Island exhibited higher relative abundance (3.02 × 10^-4 - 6.1 × 10^-2) of ARGs compared to the farms in nearby Jeollanam-do (3.4 × 10^-5 - 8.3 × 10^-3). Seasonally, samples in summer and autumn showed a higher abundance of ARGs than in winter and spring. To assess risk to the food chain as well as public health, further studies are warranted to explore the pathogenic potential of these ARGs.

Temporal characterization of a two-color laser field using tunneling ionization

The superposition of a fundamental laser pulse and its second harmonic can form an asymmetric laser field that is useful in many applications. The temporal characterization of the two-color laser field becomes necessary. However, the temporal characterization of the two-color laser pulse is a challenging task due to its broad bandwidth and a spectral gap between the two frequency components. Here we demonstrate the temporal characterization of the two-color laser field using multiple ionization yield measurements near the laser focus. This new approach enables the complete temporal characterization of the two-color laser field, including the relative phase between the two frequency components.

Longitudinal effects of antidepressant treatment on resting state functional connectivity in adolescents with major depressive disorder

Introduction

Adolescents with major depressive disorder (MDD) often show reduced prefrontal functional connectivity with the subcortical regions than healthy controls (HC) (Tang et al., 2018). However, relatively little is known about longitudinal effects of antidepressant (AD) treatment on resting state functional connectivity (RSFC) in the prefrontal cortex (PFC).

Objectives

This study aimed to investigate abnormal PFC RSFC in MDD adolescents compared to HC and longitudinal effects of AD on PFC RSFC.

Methods

This study included 59 adolescents with MDD and 43 HC. MDD adolescents were treated with escitalopram in an 8 week, open-label trial. The treatment outcome was assessed by Children’s Depression Rating Scale (CDRS-R) and patients showing at least a 40% improvement in CDRS-R scores from baseline to week 8 were defined as “responders”. Functional and T1 images collected before and after treatment were processed using AFNI and Freesurfer. Our seed was the lateral PFC (LPFC, BA46). T-tests and repeated measures ANCOVAs, controlling for age and IQ, were conducted to examine abnormal PFC RSFC and longitudinal effects of AD on LPFC RSFC.

Results

Relative to HC, MDD showed increased LPFC RSFC with the posterior middle temporal gyrus (pMTG) and superior frontal cortex (SFG) involved in attentional networks. Responders showed greater changes in LPFC RSFC with the MTG and SFG after AD treatment compared to non-responders and HC (Figure 1).

Conclusions

Our finding suggests that reduced LPFC RSFC with the pMTG and SFG reflecting decreased attentional network connectivity may serve as a biomarker to predict AD treatment outcome in adolescents with MDD.

Disclosure

No significant relationships.

Abundance and diversity of antibiotic resistance genes and bacterial communities in the western Pacific and Southern Oceans

This study investigated the abundance and diversity of antibiotic resistance genes (ARGs) and the composition of bacterial communities along a transect covering the western Pacific Ocean (36°N) to the Southern Ocean (74°S) using the Korean icebreaker R/V Araon (total cruise distance: 14,942 km). The relative abundances of ARGs and bacteria were assessed with quantitative PCR and next generation sequencing, respectively. The absolute abundance of ARGs was 3.0 × 10⁶ ± 1.6 × 10⁶ copies/mL in the western Pacific Ocean, with the highest value (7.8 × 10⁶ copies/mL) recorded at a station in the Tasman Sea (37°S). The absolute abundance of ARGs in the Southern Ocean was 1.8-fold lower than that in the western Pacific Ocean, and slightly increased (0.7-fold) toward Terra Nova Bay in Antarctica, possibly resulting from natural terrestrial sources or human activity. β-Lactam and tetracycline resistance genes were dominant in all samples (88-99%), indicating that they are likely the key ARGs in the ocean. Correlation and network analysis showed that Bdellovibrionota, Bacteroidetes, Cyanobacteria, Margulisbacteria, and Proteobacteria were positively correlated with ARGs, suggesting that these bacteria are the most likely ARG carriers. This study highlights the latitudinal profile of ARG distribution in the open ocean system and provides insights that will help in monitoring emerging pollutants on a global scale.

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.

Effect of type of coagulants on removal efficiency and removal mechanisms of antibiotic resistance genes in anaerobic digestion of primary sludge produced via a chemically enhanced primary treatment process

The potential impact of the trivalent coagulant cations on the removal mechanisms, removal efficiencies and removal patterns of antibiotic resistance genes (ARGs) during anaerobic digestion (AD) of chemically enhanced primary treatment sludge (CEPTS) was investigated using polyaluminium chloride (PACl), ferric chloride (FeCl₃) and mixed FeCl₃-PACl. The removal efficiency of 23 ARGs and intI1 improved to 72.1% in AD of primary sludge with 100 mg/L FeCl₃ and was lowest (only 54.4 %) in AD of primary sludge with 25 mg/L PACl. The removal of ARGs in AD of CEPTS with addition of single or mixed types of Al-based coagulant began to increase rapidly at the onset of batch operation. On the other hand, both the rapid increase in the removal efficiency of ARGs in AD with FeCl₃ and the maximum removal efficiency were attained later than in the other ADs.

Reduction of antibiotic resistome in influent of a wastewater treatment plant (WWTP) via a chemically enhanced primary treatment (CEPT) process

Chemically enhanced primary treatment (CEPT) has been considered for maximizing wastewater energy recovery by enhancing the carbon captured through the primary treatment. However, evaluating the potential of CEPT as a primary treatment process for removing antibiotic resistance genes (ARGs) in the influent from a wastewater treatment plant (WWTP) has seldom been investigated. In this study, CEPT was conducted to assess simultaneous reduction of 13 major targeted ARGs and common pollutants in wastewater compared with primary sedimentation alone (non-CEPT). CEPT processes using three types of coagulants (PACl, FeCl₃ and alum) effectively reduced absolute abundance of ARGs and intI1 in the influent from municipal WWTP. Average log-removal of absolute abundance of ARGs was achieved up to 1.77 ± 0.41 along with 90% turbidity reduction compared to non-CEPT. Through the simultaneous reduction of ARGs and intI1 genes during a CEPT process, ARGs proliferation may be limited directly through reduction of antibiotic resistant bacteria or indirectly through decreasing the possibility of horizontal gene transfer by intI1 removal. Reduction of ARGs and intI1 was improved by increasing coagulants' doses: abundances of residual ARGs under optimal dose conditions were similar, regardless of the different characteristics of coagulant types. The strongly positive correlation between reduction of turbidity/total phosphorus (T-P) and ARGs was explored, identifying that turbidity or T-P might be suitable indicators linked with variations in the abundance of ARGs during CEPT. As a result, CEPT may prove promising in efforts to control ARGs flowing into a WWTP.

Temporal triggers of N2O emissions during cyclical and seasonal variations of a full-scale sequencing batch reactor treating municipal wastewater

To investigate the major triggers of nitrous oxide (N₂O) production in a full-scale wastewater treatment plant, N₂O emissions and wastewater characteristics (ammonia, nitrite, nitrate, total nitrogen, dissolved inorganic carbon, dissolved organic carbon, pH, temperature, dissolved oxygen and specific oxygen uptake rate), the results of variations in the cycling of a sequential batch reactor (SBR, where only full nitrification was performed), were monitored seasonally for 16 months. Major triggers of N₂O production were investigated based on a seasonal measured database using a random forest (RF) model and sensitivity analysis, which was applied to identify important input variables. As the result of seasonal monitoring in the full-scale SBR, the N₂O emission factor relative to daily total nitrogen removal ranged from 0.05 to 2.68%, corresponding to a range of N₂O production rate from 0.02 to 0.70 kg-N/day. Results from the RF model and sensitivity analysis revealed that emissions during nitrification were directly or indirectly related to nitrite accumulation, temperature, ammonia loading rate and the specific oxygen uptake rate ratio between ammonia oxidizing bacteria and nitrite oxidizing bacteria (sOUR-ratio). However, changes in the microbial community did not significantly impact N₂O emissions. Based on these results, the sOUR-ratio could represent the major trigger for N₂O emission in a full-scale BNR system: a higher sOUR-ratio value with an average of 3.13 ± 0.23 was linked to a higher N₂O production rate with an average value of 1.27 ± 0.12 kg-N/day (corresponding to 3.96 ± 1.20% of N₂O emission factor relative to daily TN removal), while a lower sOUR-ratio with an average value of 2.39 ± 0.27 was correlated with a lower N₂O production average rate of 0.17 ± 0.11 kg-N/day (corresponding to 0.74 ± 0.69% of N₂O emission factor) (p-value = 0.00001, Mann-Whitney test).

Prediction of biogas production in anaerobic co-digestion of organic wastes using deep learning models

Interest in anaerobic co-digestion (AcoD) has increased significantly in recent decades owing to enhanced biogas productivity due to the utilization of different organic wastes, such as food waste and sewage sludge. In this study, a robust AcoD model for biogas prediction is developed using deep learning (DL). We propose a hybrid DL architecture, i.e., DA-LSTM-VSN, wherein a dual-stage-attention (DA)-based long short-term memory (LSTM) network is integrated with variable selection networks (VSNs). To enhance the model predictability, we perform hyperparameter optimization. The model accuracy is validated using long-term AcoD monitoring data measured over two years of municipal wastewater treatment plant operation and then compared with those of two other DL-based models (i.e., DA-LSTM and the standard LSTM). In addition, the feature importance (FI) is analyzed to investigate the relative contribution of input variables to biogas production prediction. Finally, we demonstrate the successful application of the validated DL model to the AcoD process optimization. Results show that the model accuracy improved significantly by incorporating DA into LSTM, i.e., the coefficient of determination (R²) increased from 0.38 to 0.68; however, the R² can be further increased to 0.76 by combining DA-LSTM with a VSN. For the biogas prediction of the AcoD model, the VSN contributes significantly by employing the discontinuous time series of measurement data on biodegradable organic-associated variables during AcoD. In addition, the VSN allows the AcoD model to be interpretable via FI analysis using its weighted input features. The FI results show that the relative importance is vital to variables associated with food waste leachate, whereas it is marginal for those associated with the primary and chemically assisted sedimentation sludges. In conclusion, the AcoD model proposed herein can be utilized in practical applications as a robust tool because it can provide the optimal sludge conditions to improve biogas production. This is because it facilitates the time-series biogas prediction at the full scale using unprocessed datasets with either missing value imputation or outlier removal.

Associations between changing patterns of ST-T waves morphologies in rest electrocardiography and cardiovascular risk in an asymptomatic low risk population: a report from Ansan-Ansung cohort study

Background

While clinical significance of ST-T wave abnormalities (STA) in rest electrocardiography (ECG) on long-term cardiovascular outcomes has been on debate, few studies have been reported on the association between the changes in ST-T waves in rest ECG and cardiovascular outcomes in low risk populations. We investigate the changing patterns of STA in rest ECG and the predictive value of the changes in ST-T wave in rest ECG for cardiovascular events in an asymptomatic general population.

Methods

A longitudinal community-based cohort study was conducted for 12 years. Koreans aged 40–69 years were followed biennially through scheduled revisit for comprehensive assessments. Among 10,030 participants, 6,648 participants who did not have any cardiovascular diseases, angina-related symptoms or pathologic Q waves in rest ECG at baseline were included for analysis. Changes in STAs were defined using the changes between ECG at baseline and that at the first revisit. A major adverse cardiovascular events was defined as a composite of cardiac death, myocardial infarction, clinical diagnosis of coronary artery disease and stroke.

Results

Among 5,924 participants without STA at baseline, only 187 participants (3.2%) developed new STA. Among 724 patients (10.9%) with STA at baseline, 274 patients (37.8%) persistently showed STA at the first revisit. MACEs occurred more frequently in the participants persistently with STA and those with newly-developed STA than in the participants persistently without STA (Figure 1). Multivariate Cox-proportional hazard models showed that a higher risk of MACE was only associated with the persisted STA (HR 1.69; 95% CI 1.10–2.63). In participants with baseline STA, persisted T-wave flattening was associated with a higher risk of MACE, whereas T-wave inversion, either persisted or fluctuated was not associated with a higher risk of MACE, compared with persistent absence of STA (Figure 2). In the participants without baseline STAs, multivariate Cox-proportional hazard model showed that newly-developed T-wave flattening (HR 1.85; 95% CI 0.20–2.84), not T-wave inversion (HR 1.50; 95% CI 0.85–2.65) was associated with a higher risk of MACE. Survival receiver operating curve analysis showed that the changes in STAs had a C-index of 0.538 (95% CI 0.511–0.558), a sensitivity of 13.0% and a specificity of 92.5% and add only a small value to the predictive power of 10-year atherosclerotic cardiovascular diseases risk estimator (C-index without STA changes 0.708 [0.681–0.736] vs. C-index with STA changes 0.721 [0.694–0.748]).

Conclusions

STAs uncommonly developed while frequently disappeared spontaneously in the asymptomatic general population. Persisted STA and newly developed STA in rest ECG were predictive of future cardiovascular events in the asymptomatic general population. However, the changes in STAs did not significantly improve the predictive value of the conventional risk estimator, when added.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Research Foundation of Korea Figure 1Figure 2

Simulation and validation for count-based binary decision of target blood pressure achievement in home blood pressure monitoring data analysis for clinical practice

Introduction

Home blood pressure monitoring (HBPM) is a useful tool to identify hypertension and to decide whether a patient's blood pressure (BP) is controlled. The use of automatized oscillometric BP measurement devices has become increasingly popular with help of information technology and internet of things to the devices. However, applying HBPM to daily clinical practices is still challenging, because most patients with hypertension are in age groups not familiar to digital devices and internet and high BP criteria using average home BP values are often useless in outpatient clinics without easily accessible average BP calculation tools. Therefore, we developed a simple and straightforward method to interpret HBPM through counts of BP ≥135/85 mmHg.

Methods

We simulated 400 cases of HBPM using a random number generator function in statistical software. The simulated average home systolic BP (SBP) and its standard deviation (SD) were 125±15 mmHg and 12±5 mmHg and the number of HBP readings was 24 times. The simulated diastolic BP (DBP) was randomly selected to 50–75% of the SBP. The validation of the binary interpretation method was conducted using actual HBPM data from 386 subjects in a rural area of South Korea. Receiver operating characteristics curve analysis was conducted, and linear regression and logarithmic models were fitted between the numbers of home BP ≥135/85 mmHg and mean BP. Hypertension was defined with average home BP ≥135/85 mmHg.

Results

In the simulated cohort, hypertension was presented in 197 cases (49.3%). The C-index of the numbers of BP readings ≥135/85 mmHg was 0.994 (95% confidence interval [CI] 0.990–0.998), and ≥12 of 24 BP readings ≥135/85 mmHg showed a sensitivity of 95.4%, a specificity of 95.1% and an accuracy of 95.3% for the diagnosis of hypertension. In validation cohort, the numbers of home BP measurements varied from 8 to 81 times. The validation cohort similarly showed that the C-index of the ratio between the number of high BP readings (≥135/85 mmHg) to the number of BP measurements (R-NHBP/NBP) was 0.985 (95% CI, 0.976–0.994) and the best accuracy was shown at R-NHBP/NBP of ≥0.45. R-NHBP/NBP of ≥0.5 showed a sensitivity of 0.957, a specificity of 0.907 and an accuracy of 0.927. The accuracy of the R-NHBP/NBP of ≥0.5 decreased as SD and the range of SBP increased, whereas it did not change with the number of measurements (Figure 1). R-NHBP/NBP &lt;0.2 predicted normotension and R-NHBP/NBP &gt;0.8 predicted hypertension in 95% confidence. Mean widths of the 95 prediction intervals for the average SBP and DBP were 18.2 mmHg and 12.6 mmHg, respectively (Figure 2).

Conclusion

Counting the number of BP ≥135/85 mmHg can provide accurate assessments for the BP levels. R-NHBP/NBP of ≥0.5 is a simple and accurate marker of high BP in HBPM, and R-NHBP/NBP could be a useful tool to assess BP levels in patients practicing HBPM.

Funding Acknowledgement

Type of funding sources: None. Figure 1Figure 2

Capecitabine plus temozolomide in patients with grade 3 unresectable or metastatic gastroenteropancreatic neuroendocrine neoplasms with Ki-67 index <55%: single-arm phase II study

BACKGROUND

Grade 3 neuroendocrine neoplasms (NENs) of gastroenteropancreatic (GEP) origin with Ki-67 indices <55% do not respond well to platinum-based chemotherapy. The combination of capecitabine and temozolomide (CAPTEM) has shown favorable responses in grade 1-2 NENs, but has rarely been studied in patients with grade 3 NENs.

PATIENTS AND METHODS

This open-label, single-arm phase II trial included patients with unresectable or metastatic grade 3 NENs of GEP origin with Ki-67 indices <55% enrolled between June 2017 and July 2020. Patients received oral capecitabine 750 mg/m2 twice daily on days 1 to 14 and oral temozolomide 200 mg/m2 once daily on days 10 to 14 every 4 weeks. Histologic findings were centrally reviewed after the completion of enrollment. The primary endpoint was overall response rate, and the secondary endpoints were progression-free survival (PFS), overall survival (OS), and adverse events.

RESULTS

Of the 30 patients included in the full analysis set, 1 (3.3%) achieved complete response, 8 (26.7%) had partial responses, and 14 (46.7%) had stable disease, making the overall response rate 30.0%. At a median follow-up of 19.2 months, the median PFS was 5.9 months and the median OS was not reached. Patients with well-differentiated NENs showed significantly better median PFS (9.3 months versus 3.5 months, P = 0.005) and median OS (not reached versus 6.2 months, P = 0.004) than patients with poorly differentiated tumors. Expression of O6-methyl-guanine methyltransferase protein did not correlate with clinical outcomes. The most common grade 3-4 adverse events were thrombocytopenia (10%), anemia (6.7%), and nausea (6.7%).

CONCLUSIONS

CAPTEM was effective and well tolerated in patients with grade 3 GEP-NENs with Ki-67 indices <55%, with superior efficacy outcomes compared with the historical controls receiving platinum-based chemotherapy.

Effects of biological pretreatments of microalgae on hydrolysis, biomethane potential and microbial community

Parameters of temperature-phased anaerobic digestion (TPAD) were varied to study their effects on hydrolysis, biomethane potential (BMP), and microbial diversity of microalgae biodegradation. Anaerobic pretreatments at 85 °C demonstrated the release of soluble carbohydrate and protein molecules under low microbial metabolic activity. However, at 55 °C, anaerobic pretreatments showed superior performance in methane yield, nutrient release, and volatile fatty acids (VFAs) production due to dominant Clostridium. Furthermore, the highest destruction of volatile solids (VS) was observed during aerobic pretreatments at 55 °C under the influence of various quantities of these genera - Luteimonas, Symbiobacterium, Soehngenia, Thermobacillus, and Ureibacillus. Statistical analysis revealed that hydrolysis and BMP were not correlated. However, soluble nitrogen and phosphorous showed strong correlation with methane (r = 0.623 and 0.948, respectively) under thermo-anaerobic pretreatment, while VS removal and concentrations of acetic and butyric acids and lipids were positively correlated with each other under thermo-aerobic pretreatment.

Prediction of antibiotic-resistance genes occurrence at a recreational beach with deep learning models

Antibiotic resistance genes (ARGs) have been reported to threaten the public health of beachgoers worldwide. Although ARG monitoring and beach guidelines are necessary, substantial efforts are required for ARG sampling and analysis. Accordingly, in this study, we predicted ARGs occurrence that are primarily found on the coast after rainfall using a conventional long short-term memory (LSTM), LSTM-convolutional neural network (CNN) hybrid model, and input attention (IA)-LSTM. To develop the models, 10 categories of environmental data collected at 30-min intervals and concentration data of 4 types of major ARGs (i.e., aac(6'-Ib-cr), bla_TEM, sul1, and tetX) obtained at the Gwangalli Beach in South Korea, between 2018 and 2019 were used. When individually predicting ARGs occurrence, the conventional LSTM and IA-LSTM exhibited poor R² values during training and testing. In contrast, the LSTM-CNN exhibited a 2-6-times improvement in accuracy over those of the conventional LSTM and IA-LSTM. However, when predicting all ARGs occurrence simultaneously, the IA-LSTM model exhibited a superior performance overall compared to that of LSTM-CNN. Additionally, the influence of environmental variables on prediction was investigated using the IA-LSTM model, and the ranges of input variables that affect each ARG were identified. Consequently, this study demonstrated the possibility of predicting the occurrence and distribution of major ARGs at the beach based on various environmental variables, and the results are expected to contribute to management of ARG occurrence at a recreational beach.

Designing a marine outfall to reduce microbial risk on a recreational beach: Field experiment and modeling

A marine outfall can be a wastewater management system that discharges sewage and stormwater into the sea; hence, it is a source of microbial pollution on recreational beaches, including antibiotic resistant genes (ARGs), which lead to an increase in untreatable diseases. In this regard, a marine outfall must be efficiently located to mitigate these risks. This study aimed to 1) investigate the spatiotemporal variability of Escherichia coli (E. coli) and ARGs on a recreational beach and 2) design marine outfalls to reduce microbial risks. For this purpose, E. coli and ARGs with influential environmental variables were intensively monitored on Gwangalli beach, South Korea in this study. Environmental fluid dynamic code (EFDC) was used and calibrated using the monitoring data, and 12 outfall extension scenarios were explored (6 locations at 2 depths). The results revealed that repositioning the marine outfall can significantly reduce the concentrations of E. coli and ARGs on the beach by 46-99%. Offshore extended outfalls at the bottom of the sea reduced concentrations of E. coli and ARGs on the beach more effectively than onshore outfalls at the sea surface. These findings could be helpful in establishing microbial pollution management plans at recreational beaches in the future.

Hydrometeorological Influence on Antibiotic-Resistance Genes (ARGs) and Bacterial Community at a Recreational Beach in Korea

We investigated the occurrence and distribution of antibiotic-resistance genes (ARGs) and the composition of a bacterial community under conditions of rainfall on a recreational beach in Korea. Seawater samples, collected every 1‒5 hours in June 2018 and May 2019, were analyzed using quantitative real-time polymerase chain reaction and next-generation sequencing. We found a substantial influence of rainfall and tidal levels on the relative abundance of total ARGs and bacterial operational taxonomic units (OTUs), which showed 1.9 × 10³ and 1.1 × 10¹ fold increases, respectively. In particular, the elevated levels of ARGs were maintained for up to 32 hours after rainfall. An increased abundance of sewage-related ARGs and bacterial OTUs suggested that combined sewer overflow (CSO) may be the major factor contributing to the increase in the number and diversity of ARGs and related bacterial communities. Network analysis of ARGs and OTUs indicated that, at the genus level, Acinetobacter, Pseudomonas, and Prevotella were the main potential pathogens carrying the observed ARGs in the recreational seawater. Overall, these findings highlight the potential threat to public health on beaches, and indicate the requirement for more adequate monitoring, with greater efforts to mitigate the propagation of ARGs arising from CSOs.