Sulfonamide Per- and Polyfluoroalkyl Substances Can Impact Microorganisms Used in Aromatic Hydrocarbon and Trichloroethene Bioremediation.

Per- and polyfluoroalkyl substances (PFASs) from aqueous film forming foams (AFFFs) can hinder bioremediation of co-contaminants such as trichloroethene (TCE) and benzene, toluene, ethylbenzene, and xylene (BTEX). Anaerobic dechlorination can require bioaugmentation of Dehalococcoides, and for BTEX, oxygen is often sparged to stimulate in situ aerobic biodegradation. We tested PFAS inhibition to TCE and BTEX bioremediation by exposing an anaerobic TCE-dechlorinating coculture, an aerobic BTEX-degrading enrichment culture, and an anaerobic toluene-degrading enrichment culture to n-dimethyl perfluorohexane sulfonamido amine (AmPr-FHxSA), perfluorohexane sulfonamide (FHxSA), perfluorohexanesulfonic acid (PFHxS), or nonfluorinated surfactant sodium dodecyl sulfate (SDS). The anaerobic TCE-dechlorinating coculture was resistant to individual PFAS exposures but was inhibited by >1000× diluted AFFF. FHxSA and AmPr-FHxSA inhibited the aerobic BTEX-degrading enrichment. The anaerobic toluene-degrading enrichment was not inhibited by AFFF or individual PFASs. Increases in amino acids in the anaerobic TCE-dechlorinating coculture compared to the control indicated stress response, whereas the BTEX culture exhibited lower concentrations of all amino acids upon exposure to most surfactants (both fluorinated and nonfluorinated) compared to the control. These data suggest the main mechanisms of microbial toxicity are related to interactions with cell membrane synthesis as well as protein stress signaling.

Radiology domain in the diagnosis of IgG4-RD according to the 2019 American College of Rheumatology and European League Against Rheumatism classification.

OBJECTIVES: To evaluate the performance of radiology-related inclusion criteria of the 2019 ACR-EULAR classification system in the diagnosis of IgG4-related disease (IgG4-RD). METHODS: This retrospective single-institution study included patients who received a diagnosis of IgG4-RD between January 2010 and December 2020. Two abdominal radiologists independently reviewed baseline imaging studies and scored radiology findings according to the 2019 ACR-EULAR classification criteria. Additional scores were assigned based on serological, histopathological, and immunostaining features. RESULTS: Seventy-four patients (58 males and 16 females) with a mean age of 59.3 ± 13.9 years diagnosed with IgG4-RD were included. 51/74 (68.9%) were classified as having IgG4-RD according to the 2019 ACR-EULAR classification criteria. To reach a score ≥ 20 in these 51 patients, the radiology domain was sufficient in 20/51 (39.2%) and adding the serology domain was required for another 20/51 (39.2%). The remaining 11/51 patients (21.6%) required the histopathology and immunostaining domains. Radiological involvement of two or more organs at presentation was significantly associated with a score of ≥ 20 and seen in 43/51 (84.3%) compared to 5/23 (21.7%) of the non-classified group (p < 0.001). The group classified as having IgG4-RD showed a significantly higher proportion of elevated IgG4 levels (39/51, 76.5%) than the non-classified group (8/23, 34.8%) (< 0.001). CONCLUSION: The study findings support the effectiveness of the radiology-related inclusion criteria of the 2019 ACR-EULAR classification system in diagnosing IgG4-RD. Combining radiology and serology domains achieved the cut-off in 80% of IgG-RD patients, enabling non-invasive diagnosis. The classification of IgG4-RD was significantly associated with multi-organ involvement, particularly affecting the pancreas and biliary system. CRITICAL RELEVANCE STATEMENT: This study is the first to evaluate the diagnostic performance of the radiology domain in the 2019 ACR-EULAR classification criteria. The study results confirm its utility and potential to enable non-invasive diagnosis when combined with serological testing in a significant proportion of patients. KEY POINTS: • A significant proportion of patients can be diagnosed with IgG4-RD using the radiology and serology domains exclusively. • Multi-organ involvement is significantly associated with classifying patients as IgG4-RD, with the pancreas and biliary system most frequently affected. • A high level of inter-reader agreement in the scoring of the radiology domain supports its reliability.

Elucidating adsorption mechanisms of benzalkonium chlorides (BACs) on polypropylene and polyethylene terephthalate microplastics (MPs): Effects of BACs alkyl chain length and MPs characteristics.

Since the onset of the COVID-19 pandemic, there has been an increase in the use of disposable plastics and disinfectants. This study systematically investigated the adsorption behavior and mechanisms of benzalkonium chlorides (BACs), commonly used disinfectants, on polypropylene (PP) and polyethylene terephthalate (PET) microplastics (MPs), considering various factors, such as characteristics of MPs, alkyl chain length of BACs, and environmental conditions. Our results demonstrated a higher adsorption capacity for PP-MPs with relatively hydrophobic properties compared to PET-MPs, where longer alkyl chains in BACs (i.e., higher octanol-water partition coefficients, Kow) significantly enhanced adsorption through hydrophobic interactions. The inverse relationship between particle size of MPs and adsorption was evident. While changes in pH minimally affected adsorption on PP-MPs, adsorption on PET-MPs increased with rising pH, highlighting the influence of pH on electrostatic interactions. Moreover, MP aging with UV/H2O2 amplified BAC adsorption on PP-MPs due to surface oxidation and fragmentation, whereas the properties of PET-MPs remained unaltered, resulting in unchanged adsorption capacities. Spectroscopy studies and density functional theory (DFT) calculations confirmed hydrophobic and electrostatic interactions as the primary adsorption mechanisms. These findings improve our understanding of MPs and BACs behavior in the environment, providing insights for environmental risk assessments related to combined pollution.

Can absolute arterial phase hyperenhancement improve sensitivity of detection of hepatocellular carcinoma in indeterminate nodules on CT?

OBJECTIVES: To determine if quantitative assessment of relative (R) and absolute (A) arterial phase hyperenhancement (APHE) and washout (WO) applied to indeterminate nodules on CT would improve the overall sensitivity of detection of hepatocellular carcinoma (HCC). METHODS: One-hundred and fourteen patients (90 male; mean age, 65 years) with 210 treatment-naïve HCC nodules (190 HCCs, 20 benign) who underwent 4-phase CT were included in this retrospective study. Four radiologists independently assigned a qualitative LR (LI-RADS) category per nodule. LR-3/4 nodules were then quantitatively analyzed by the 4 readers, placing ROIs within nodules and adjacent liver parenchyma. A/R-APHE and WO were calculated, and per-reader sensitivity and specificity updated. Interobserver agreement and AUCs were calculated per reader. RESULTS: Qualitative readers 1-4 categorized 57, 69, 57, and 63 nodules as LR-3/4 respectively with moderate to substantial agreement in LR category (kappa 0.56-0.69, p < 0.0001); their diagnostic performances in the detection of HCC were 80%, 73.2%, 77.4%, and 77.4% sensitivity, and 100%, 95%, 70%, and 100% specificity, respectively. A threshold of ≥ 20 HU for A-APHE increased overall sensitivity of HCC detection by 0.5-3.1% without changing specificity for the subset of nodules APHE - /WO + on qualitative read, with 2, 6, 6, and 1 additional HCC detected by readers 1-4. Relative and various A-WO formulae and thresholds all increased sensitivity, but with a drop in specificity for some/all readers. CONCLUSION: Quantitatively assessed A-APHE showed potential to increase sensitivity and maintain specificity of HCC diagnosis when selectively applied to indeterminate nodules demonstrating WO without subjective APHE. Quantitatively assessed R and A-WO increased sensitivity, however reduced specificity. CLINICAL RELEVANCE STATEMENT: A workflow using selective quantification of absolute arterial enhancement is routinely employed in the CT assessment of renal and adrenal nodules. Quantitatively assessed absolute arterial enhancement is a simple tool which may be used as an adjunct to help increase sensitivity and maintain specificity of HCC diagnosis in indeterminate nodules demonstrating WO without subjective APHE. KEY POINTS: • In indeterminate nodules categorized as LI-RADS 3/4 due to absent subjective arterial phase hyperenhancement, a cut-off for absolute arterial phase hyperenhancement of ≥ 20 HU may increase the overall sensitivity of detection of HCC by 0.5-3.1% without affecting specificity. • Relative and various absolute washout formulae and cut-offs increased sensitivity of HCC detection, but with a drop in specificity for some/all readers.

Association with Combined Occupational Hazards Exposure and Risk of Metabolic Syndrome: A Workers' Health Examination Cohort 2012-2021.

Background: This study aimed to evaluate the association between exposure to occupational hazards and the metabolic syndrome. A secondary objective was to analyze the additive and multiplicative effects of exposure to risk factors. Methods: This retrospective cohort was based on 31,615 health examinees at the Pusan National University Yangsan Hospital in Republic of Korea from 2012-2021. Demographic and behavior-related risk factors were treated as confounding factors, whereas three physical factors, 19 organic solvents and aerosols, and 13 metals and dust were considered occupational risk factors. Time-dependent Cox regression analysis was used to calculate hazard ratios. Results: The risk of metabolic syndrome was significantly higher in night shift workers (hazard ratio = 1.45: 95% confidence interval = 1.36-1.54) and workers who were exposed to noise (1.15:1.07-1.24). Exposure to some other risk factors was also significantly associated with a higher risk of metabolic syndrome. They were dimethylformamide, acetonitrile, trichloroethylene, xylene, styrene, toluene, dichloromethane, copper, antimony, lead, copper, iron, welding fume, and manganese. Among the 28 significant pairs, 19 exhibited both positive additive and multiplicative effects. Conclusions: Exposure to single or combined occupational risk factors may increase the risk of developing metabolic syndrome. Working conditions should be monitored and improved to reduce exposure to occupational hazards and prevent the development of the metabolic syndrome.

Mineralization of a Fully Halogenated Organic Compound by Persulfate under Conditions Relevant to in Situ Reduction and Oxidation: Reduction of Hexachloroethane by Ethanol Addition Followed by Oxidation.

Fully halogenated compounds are difficult to remediate by in situ chemical oxidation (ISCO) because carbon-halogen bonds react very slowly with the species that typically initiate contaminant transformation: sulfate radical (SO4•-) and hydroxyl radical (•OH). To enable the remediation of this class of contaminants by persulfate (S2O82-)-based ISCO, we employed a two-phase process to dehalogenate and oxidize a representative halogenated compound (i.e., hexachloroethane). In the first phase, a relatively high concentration of ethanol (1.8 M) was added, along with concentrations of S2O82- that are typically used for ISCO (i.e., 450 mM). Hexachloroethane underwent rapid dehalogenation when carbon-centered radicals produced by the reaction of ethanol and radicals formed during S2O82- decomposition reacted with carbon-halogen bonds. Unlike conventional ISCO treatment, hexachloroethane transformation and S2O82- decomposition took place on the time scale of days without external heating or base addition. The presence of O2, Cl-, and NO3- delayed the onset of hexachloroethane transformation when low concentrations of S2O82- (10 mM) were used, but these solutes had negligible effects when S2O82- was present at concentrations typical of in situ remediation (450 mM). The second phase of the reaction was initiated after most of the ethanol had been depleted when thermolytic S2O82- decomposition resulted in production of SO4•- that oxidized the partially dehalogenated transformation products. With proper precautions, S2O82--based ISCO with ethanol could be a useful remediation technology for sites contaminated with fully halogenated compounds.

Improved Likelihood Probability in MIMO Systems Using One-Bit ADCs.

This study considers an improved likelihood probability in multi-input multi-output (MIMO) systems using one-bit analog-to-digital converters (ADCs). MIMO systems using one-bit ADCs are known to exhibit from performance degradation because of inaccurate likelihood probabilities. To overcome this degradation, the proposed method leverages the detected symbols to estimate the true likelihood probability by combining the initial likelihood probability. An optimization problem is formulated to minimize the mean-squared error between the true and combined likelihood probabilities, and a solution is derived using the least-squares method. Simulation results show that the proposed method obtains a signal-to-noise gain of approximately 0.3 dB to achieve a frame error rate of 10-1 compared to conventional methods. This improvement in performance is attributed to the enhanced reliability of the likelihood probability.

Reinforcement Learning-Aided Channel Estimator in Time-Varying MIMO Systems.

This paper proposes a reinforcement learning-aided channel estimator for time-varying multi-input multi-output systems. The basic concept of the proposed channel estimator is the selection of the detected data symbol in the data-aided channel estimation. To achieve the selection successfully, we first formulate an optimization problem to minimize the data-aided channel estimation error. However, in time-varying channels, the optimal solution is difficult to derive because of its computational complexity and the time-varying nature of the channel. To address these difficulties, we consider a sequential selection for the detected symbols and a refinement for the selected symbols. A Markov decision process is formulated for sequential selection, and a reinforcement learning algorithm that efficiently computes the optimal policy is proposed with state element refinement. Simulation results demonstrate that the proposed channel estimator outperforms conventional channel estimators by efficiently capturing the variation of the channels.

Automated Laser-Fiber Coupling Module for Optical-Resolution Photoacoustic Microscopy.

Photoacoustic imaging has emerged as a promising biomedical imaging technique that enables visualization of the optical absorption characteristics of biological tissues in vivo. Among the different photoacoustic imaging system configurations, optical-resolution photoacoustic microscopy stands out by providing high spatial resolution using a tightly focused laser beam, which is typically transmitted through optical fibers. Achieving high-quality images depends significantly on optical fluence, which is directly proportional to the signal-to-noise ratio. Hence, optimizing the laser-fiber coupling is critical. Conventional coupling systems require manual adjustment of the optical path to direct the laser beam into the fiber, which is a repetitive and time-consuming process. In this study, we propose an automated laser-fiber coupling module that optimizes laser delivery and minimizes the need for manual intervention. By incorporating a motor-mounted mirror holder and proportional derivative control, we successfully achieved efficient and robust laser delivery. The performance of the proposed system was evaluated using a leaf-skeleton phantom in vitro and a human finger in vivo, resulting in high-quality photoacoustic images. This innovation has the potential to significantly enhance the quality and efficiency of optical-resolution photoacoustic microscopy.

C2RL: Convolutional-Contrastive Learning for Reinforcement Learning Based on Self-Pretraining for Strong Augmentation.

Reinforcement learning agents that have not been seen during training must be robust in test environments. However, the generalization problem is challenging to solve in reinforcement learning using high-dimensional images as the input. The addition of a self-supervised learning framework with data augmentation in the reinforcement learning architecture can promote generalization to a certain extent. However, excessively large changes in the input images may disturb reinforcement learning. Therefore, we propose a contrastive learning method that can help manage the trade-off relationship between the performance of reinforcement learning and auxiliary tasks against the data augmentation strength. In this framework, strong augmentation does not disturb reinforcement learning and instead maximizes the auxiliary effect for generalization. Results of experiments on the DeepMind Control suite demonstrate that the proposed method effectively uses strong data augmentation and achieves a higher generalization than the existing methods.

Non-Orthogonal Multiple Access with One-Bit Analog-to-Digital Converters Using Threshold Adaptation.

In digital communication systems featuring high-resolution analog-to-digital converters (ADCs), the utilization of successive interference cancellation and detection can enhance the capacity of a Gaussian multiple access channel (MAC) by combining signals from multiple transmitters in a non-orthogonal manner. Conversely, in systems employing one-bit ADCs, it is exceedingly difficult to eliminate non-orthogonal interference using digital signal processing due to the considerable distortion present in the received signal when employing such ADCs. As a result, the Gaussian MAC does not yield significant capacity gains in such cases. To address this issue, we demonstrate that, under a given deterministic interference, the capacity of a one-bit-quantized channel becomes equivalent to the capacity without interference when an appropriate threshold value is chosen. This finding suggests the potential for indirect interference cancellation in the analog domain, facilitating the proposition of an efficient successive interference cancellation and detection scheme. We analyze the achievable rate of the proposed scheme by deriving the mutual information between the transmitted and received signals at each detection stage. The obtained results indicate that the sum rate of the proposed scheme generally outperforms conventional methods, with the achievable upper bound being twice as high as that of the conventional methods. Additionally, we have developed an optimal transmit power allocation algorithm to maximize the sum rate in fading channels.

Patterns of Relapse and Complications of Immunoglobulin G4-Related Disease.

BACKGROUND: Immunoglobulin G4-related disease (IgG4-RD) is a multisystemic fibroinflammatory condition potentially resulting in organ dysfunction. We aimed to evaluate imaging characteristics of disease relapse and complications in this cohort of patients. METHODS: This was a cohort study of IgG4-RD patients imaged between 2010 and 2020. Radiological manifestations of disease activity (remission/stability vs. relapse and complications) were correlated with clinical symptoms. Univariate analyses were performed with χ2 , Fisher exact, and Mann-Whitney U tests. Times to relapse and organ atrophy were studied with Kaplan-Meier analyses. RESULTS: A total of 69 patients had imaging surveillance over a median duration of 47 months. Radiological relapse occurred in 50.7% (35/69) with median time to relapse at 74 months (95% confidence interval, 45-122 months); 42.8% (15/35) of this cohort had different-site relapse with the following recognized primary-secondary patterns: pancreas-hepatobiliary ( p = 0.005), hepatobiliary-pancreas ( p = 0.013), and periaortitis-mesenteric ( p = 0.006). Clinical symptoms were significantly associated with imaging characteristics ( p < 0.001). Abdominal complications were detected in 52.2% (36/69) of patients, mostly solid organ atrophy (97.2% [35/36]). New-onset diabetes was more likely in pancreatic IgG4-RD (n = 51) when accompanied by gland atrophy (4/21 vs. 0/30 nonatrophy, p = 0.024). CONCLUSION: Radiological relapse of IgG4-RD is common over prolonged imaging surveillance and is significantly associated with symptomatic relapse. A multisystem review to detect new/different sites of disease and abdominal complications may help predict future organ dysfunction.

Epidemiology of occupational injuries in construction workers between 2009 and 2018 in South Korea.

BACKGROUND: This study aimed to investigate the characteristics of occupational injuries based on fatality, sex, and classification of occupations among construction workers using workers' compensation (WC) insurance data in South Korea. METHODS: We collected WC insurance data from the Korea Workers' Compensation & Welfare Service for all construction workers between 2009 and 2018. Data from 158,947 accepted claims for occupational injury were extracted, and the demographic features, occupational injury types, and annual trends were analyzed for fatal and nonfatal cases. The annual incidence and mortality trends of occupational injury were estimated using negative binomial regression and Poisson regression models, for injury incidence and mortality respectively. RESULTS: Among a total of 158,947 occupational injury cases, there were 155,772 (98%) nonfatal injuries and 3175 (2%) fatal injuries. For all occupational injuries, Construction Elementary Workers (6th Korean Standard Classification of Occupations (KSCO) 910; 45.7%) was the most frequent occupation, followed by Construction-Related Technical Workers (6th KSCO 772; 39.2%). The most frequent injury type was a fracture, followed by ruptures or lacerations and contusions. The incidence of all occupational injuries increased from 700.36 per 100,000 persons in 2009 to 1,195.98 per 100,000 persons in 2018. Further, deaths from injuries at work followed a significantly increasing annual trend [mortality rate ratio 1.04 (95% CI: 1.03-1.05)] from 2009 to 2018. CONCLUSION: The over two-thirds increased incidence of occupational injuries and significantly increasing mortality trends for occupational injuries during the last 10 years indicate the need for aggressive intervention in occupational safety and health management within the Korean construction industry.

Germline BRCA2 variants in advanced pancreatic acinar cell carcinoma: A case report and review of literature.

BACKGROUND: Pancreatic acinar cell carcinoma (PACC) is a rare tumor. Up to 45% of PACCs have alterations in the DNA damage repair pathway and 23% harbor rearrangements in the BRAF or RAF1 genes. We present a PACC case with a germline BRCA2 likely pathogenic variant (LPV) to highlight the impact of genomic testing on treatment decisions and patient outcomes. In our larger case series, we provide clinic-based information on additional 10 PACC patients treated in our center. CASE SUMMARY: A 70-year-old male was diagnosed with advanced PACC. At presentation, he was cachectic with severe arthralgia despite prednisolone and a skin rash that was later confirmed to be panniculitis. He was treated with modified FOLFIRINOX (mFFX) with the knowledge of the germline BRCA2 LPV. Following 11 cycles of mFFX, a computed tomography (CT) scan demonstrated significant tumor response in the pancreatic primary and hepatic metastases, totaling 70% from baseline as per Response Evaluation Criteria in Solid Tumors. Resolution of the skin panniculitis was also noted. We identified two additional PACCs with druggable targets in our case series. Our data contribute to practical evidence for the value of germline and somatic profiling in the management of rare diseases like PACC. CONCLUSION: This patient and others in our larger case series highlight the importance of genomic testing in PACC with potential utility in personalized treatment.

Cooperative DF Protocol for MIMO Systems Using One-Bit ADCs.

This study considers a detection scheme for cooperative multi-input-multi-output (MIMO) systems using one-bit analog-to-digital converters (ADCs) in a decode-and-forward (DF) relay protocol. The use of one-bit ADCs is a promising technique for reducing the power consumption, which is necessary for supporting future wireless systems comprising a large number of antennas. However, the use of a large number of antennas remains still limited to mobile devices owing to their size. Cooperative communication using a DF relay can resolve this limitation; however, detection errors at the relay make it difficult to employ cooperative communication directly. This difficulty is more severe in a MIMO system using one-bit ADCs due to its nonlinear nature. To efficiently address the difficulty, this paper proposes a detection scheme that mitigates the error propagation effect. The upper bound of the pairwise error probability (PEP) of one-bit ADCs is first derived in a weighted Hamming distance form. Then, using the derived PEP, the proposed detection for the DF relay protocol is derived as a single weighted Hamming distance. Finally, the complexity of the proposed detection is analyzed in terms of real multiplications. The simulation results show that the proposed detection method efficiently mitigates the error propagation effect but has a relatively low level of complexity when compared to conventional detection methods.

Spherical-Cap Approximation of Vector Quantization for Quantization-Based Combining in MIMO Broadcast Channels with Limited Feedback.

The spherical-cap approximation of vector quantization (SCVQ) is an analytical model used for the mathematical analysis of multiple-input multiple-output (MIMO) systems with limited feedback. SCVQ closely emulates the distribution of the quantization error induced by the finite-rate quantization of a channel using a simple and analytically tractable approach. However, the conventional SCVQ model is not applicable when antenna-combining schemes such as quantization-based combining (QBC) are considered. Because QBC is an effective antenna-combining method that minimizes channel quantization errors, it can be adopted for various practical MIMO broadcast systems. Nevertheless, evaluating the performance of QBC-based MIMO systems with an explicit codebook can be extremely difficult, depending on the system complexity. To resolve this, this study generalizes the conventional SCVQ to be compatible with the QBC. The proposed generalized version of the SCVQ effectively emulates the quantization error obtained using QBC, while enabling a simple simulation independent of the number of feedback bits and mathematically tractable analysis. We validate the effectiveness of the proposed model by presenting a wireless communication application based on a dense cellular network.

A Low-Complexity Algorithm for a Reinforcement Learning-Based Channel Estimator for MIMO Systems.

This paper proposes a low-complexity algorithm for a reinforcement learning-based channel estimator for multiple-input multiple-output systems. The proposed channel estimator utilizes detected symbols to reduce the channel estimation error. However, the detected data symbols may include errors at the receiver owing to the characteristics of the wireless channels. Thus, the detected data symbols are selectively used as additional pilot symbols. To this end, a Markov decision process (MDP) problem is defined to optimize the selection of the detected data symbols. Subsequently, a reinforcement learning algorithm is developed to solve the MDP problem with computational efficiency. The developed algorithm derives the optimal policy in a closed form by introducing backup samples and data subblocks, to reduce latency and complexity. Simulations are conducted, and the results show that the proposed channel estimator significantly reduces the minimum-mean square error of the channel estimates, thus improving the block error rate compared to the conventional channel estimation.