Prediction of arsenic retention in vadose zone based on empirical relationship between soil properties and segmented retardation factors.

Arsenic (As) is a widespread environmental contaminant that poses a significant threat to ecosystems and human health. Although previous studies have qualitatively revealed the effects of individual soil properties on the transport and fate of As in the vadose zone, their integrated impacts remain obscure. Moreover, studies investigating the retardation factor therein, which is a key parameter for comprehending As transport in the vadose zone, are extremely limited. In this study, we investigated the interplay of soil properties with As transport and retention within the vadose zone, while focusing on the retardation factor of As. We employed steady-state unsaturated water-flow soil column experiments coupled with a mobile-immobile model and multiple linear regression analysis to elucidate the dependence of As retardation factors on the soil properties. In the mobile water zone, iron and organic matter contents emerged as the two most influential properties that impedes As mobility. Whereas, in the immobile water zone, the coefficient of uniformity and bulk density were the most influential factors that enhanced As retention. Finally, we derived an empirical equation for calculating the As retardation factors in each zone, offering a valuable tool for describing and predicting As behavior to protect the groundwater resources underneath.

Development of a predictive model for hypoxia due to sedatives in gastrointestinal endoscopy: a prospective clinical study in Korea.

Background/Aims: Sedation has become a standard practice for patients undergoing gastrointestinal (GI) endoscopy. However, considering the serious cardiopulmonary adverse events associated with sedatives, it is important to identify patients at high risk. Machine learning can generate reasonable prediction for a wide range of medical conditions. This study aimed to evaluate the risk factors associated with sedation during GI endoscopy and develop a predictive model for hypoxia during endoscopy under sedation. Methods: This prospective observational study enrolled 446 patients who underwent sedative endoscopy at the Korea University Ansan Hospital. Clinical data were used as predictor variables to construct predictive models using the random forest method that is a machine learning algorithm. Results: Seventy-two of the 446 patients (16.1%) experienced life-threatening hypoxia requiring immediate medical intervention. Patients who developed hypoxia had higher body weight, body mass index (BMI), neck circumference, and Mallampati scores. Propofol alone and higher initial and total dose of propofol were significantly associated with hypoxia during sedative endoscopy. Among these variables, high BMI, neck circumference, and Mallampati score were independent risk factors for hypoxia. The area under the receiver operating characteristic curve for the random forest-based predictive model for hypoxia during sedative endoscopy was 0.82 (95% confidence interval, 0.79-0.86) and displayed a moderate discriminatory power. Conclusions: High BMI, neck circumference, and Mallampati score were independently associated with hypoxia during sedative endoscopy. We constructed a model with acceptable performance for predicting hypoxia during sedative endoscopy.

Unveiling interfacial interaction between antimony oxyanions and boehmite nanorods: Spectroscopic evidence and density functional theory analysis.

In natural environments, the fate and migratory behavior of metalloid contaminants such as antimony (Sb) significantly depend on the interfacial reactivity of mineral surfaces. Although boehmite (γ-AlOOH) is widely observed in (sub)surface environments, its underlying interaction mechanism with Sb oxyanions at the molecular scale remains unclear. Considering Sb-contaminated environmental conditions in this study, we prepared boehmite under weakly acidic conditions for use in the systematic investigation of interfacial interactions with Sb(III) and Sb(V). The as-synthesized boehmite showed a nanorod morphology and comprised four crystal facets in the following order: 48.4% (010), 27.1% (101), 15.0% (001), and 9.5% (100). The combined results of spectroscopic analyses and theoretical calculations revealed that Sb(III) formed hydrogen bonding outer-sphere complexation on the (100), (010), and (001) facets and that Sb(V) preferred to form bidentate inner-sphere complexation via mononuclear edge-sharing configuration on the (100), (001), and (101) facets and binuclear corner-sharing configuration on the (010) facet. These findings indicate that the facet-mediated thermodynamic stability of the surface complexation determines the interaction affinity toward the Sb species. This work is the first to document the contribution of boehmite to (sub)surface media, improving the ability to forecast the fate and behavior of Sb oxyanions at mineral-water interfaces.

Influence of iron (hydr)oxide mineralogy and contents in aquifer sediments on dissolved organic carbon attenuations during aquifer storage and recovery.

Aquifer storage and recovery (ASR) is a promising approach for managing water resources that enhances water quality through biogeochemical reactions occurring within aquifers. Iron (hydr)oxides, which are the predominant metallic oxides in soil, play a crucial role in degrading dissolved organic carbon (DOC), primarily through a process known as dissimilatory iron reduction (DIR). However, the efficiency of this reaction varies depending on the mineralogy and composition of the aquifer, and this understanding is essential for adequate water quality in ASR. The objective of this study is to investigate the impact of iron (hydr)oxide on acetate, as an organic carbon source, attenuation during the ASR. To achieve this, three sets of laboratory sediment columns were prepared, each containing a different type of iron (hydr)oxide minerals: ferrihydrite, goethite, and hematite. Following an acclimation period of 28 days to simulate the microcosm within an aquifer, the columns were continuously supplied with the simulated river water spiked with acetate (DOC 40-60 mg L-1), and the acetate concentration in the effluent was monitored. The result revealed that the column containing ferrihydrite achieved 97% acetate attenuation through DIR with anoxic conditions (DO < 0.1 mg L-1), while the goethite and hematite columns exhibited limited attenuation rates of 40 and 50%, respectively. Furthermore, the efficiency of acetate attenuation in the ferrihydrite columns increased with the content of ferrihydrite but experienced a rapidly declined at higher contents (3-4%), possibly due to the partial conversion of ferrihydrite to goethite as a result of the interaction between ferrihydrite and the Fe(II) produced during DIR. Additionally, an analysis of the microbial community demonstrated that microorganisms known to possess the ability to reduce iron (hydr)oxides under anaerobic conditions were abundant in the ferrihydrite columns.

A Potential Radiomics-Clinical Model for Predicting Failure of Lymph Node Control after Definite Radiotherapy in Locally Advanced Head and Neck Cancer.

Background and Objectives: To optimally predict lymph node (LN) failure after definite radiotherapy (RT) in head and neck cancer (HNC) with LN metastases, this study examined radiomics models extracted from CT images of different periods during RT. Materials and Methods: This study retrospectively collected radiologic and clinical information from patients undergoing definite RT over 60 Gy for HNC with LN metastases from January 2010 to August 2021. The same largest LNs in each patient from the initial simulation CT (CTpre) and the following simulation CT (CTmid) at approximately 40 Gy were indicated as regions of interest. LN failure was defined as residual or recurrent LN within 3 years after the end of RT. After the radiomics features were extracted, the radiomics alone model and the radiomics plus clinical parameters model from the set of CTpre and CTmid were compared. The LASSO method was applied to select features associated with LN failure. Results: Among 66 patients, 17 LN failures were observed. In the radiomics alone model, CTpre and CTmid had similar mean accuracies (0.681 and 0.697, respectively) and mean areas under the curve (AUC) (0.521 and 0.568, respectively). Radiomics features of spherical disproportion, size zone variance, and log minimum 2 were selected for CTpre plus clinical parameters. Volume, energy, homogeneity, and log minimum 1 were selected for CTmid plus clinical parameters. Clinical parameters including smoking, T-stage, ECE, and regression rate of LN were important for both CTpre and CTmid. In the radiomics plus clinical parameters models, the mean accuracy and mean AUC of CTmid (0.790 and 0.662, respectively) were more improved than those of CTpre (0.731 and 0.582, respectively). Conclusions: Both models using CTpre and CTmid were improved by adding clinical parameters. The radiomics model using CTmid plus clinical parameters was the best in predicting LN failure in our preliminary analyses.

Analysis of the association between vestibular schwannoma and hearing status using a newly developed radiomics technique.

PURPOSE: Vestibular schwannoma is a benign tumor originating from Schwann cells surrounding the eighth cranial nerve and can cause hearing loss, tinnitus, balance problems, and facial nerve disorders. Because of the slow growth of the tumor, predicting the hearing function of patients with vestibular schwannoma's is important to obtain information that would be useful for deciding the treatment modality. This study aimed to analyze the association between magnetic resonance imaging features and hearing status using a new radiomics technique. METHODS: We retrospectively analyzed 115 magnetic resonance images and hearing results from 73 patients with vestibular schwannoma. A total of 70 radiomics features from each tumor volume were calculated using T1-weighted magnetic resonance imaging. Radiomics features were classified as histogram-based, shape-based, texture-based, and filter-based. The least absolute shrinkage and selection operator method was used to select the radiomics features among the 70 features that best predicted the hearing test. To ensure the stability of the selected features, the least absolute shrinkage and selection operator method was repeated 10 times. Finally, features set five or more times were selected as radiomics signatures. RESULTS: The radiomics signatures selected using the least absolute shrinkage and selection operator method were: minimum, variance, maximum 3D diameter, size zone variance, log skewness, skewness slope, and kurtosis slope. In random forest, the mean performance was 0.66 (0.63-0.77), and the most important feature was Log skewness. CONCLUSIONS: Newly developed radiomics features are associated with hearing status in patients with vestibular schwannoma and could provide information when deciding the treatment modality.

Synergetic effect of nitrate on dissolved organic carbon attenuation through dissimilatory iron reduction during aquifer storage and recovery.

Aquifer storage and recovery (ASR) is a promising water management technique in terms of quantity and quality. During ASR, iron (Fe) (hydr)oxides contained in the aquifer play a crucial role as electron acceptors in attenuating dissolved organic carbon (DOC) in recharging water through dissimilatory iron reduction (DIR). Considering the preference of electron acceptors, nitrate (NO3⁻), possibly coexisting with DOC as the prior electron acceptor to Fe (hydr)oxides, might influence DIR by interrupting electron transfer. However, this phenomenon is yet to be clarified. In this study, we systematically investigated the potential effect of NO3⁻ on DOC attenuation during ASR using a series of sediment columns representing typical aquifer conditions. The results suggest that DOC attenuation could be enhanced by the presence of NO3⁻. Specifically, total DOC attenuation was notably higher than that from the stoichiometric calculation simply employing NO3⁻ as the additional electron acceptor to Fe (hydr)oxides, implying a synergetic effect of NO3⁻ in the overall reactions. X-ray photoelectron spectroscopy analyzes revealed that the Fe(II) ions released from DIR transformed the Fe (hydr)oxides into a less bioavailable form, inhibiting further DIR. In the presence of NO3⁻, however, no aqueous Fe(II) was detected, and another form of Fe (hydr)oxide appeared on the sediment surface. This may be attributed to nitrate-dependent Fe(II) oxidation (NDFO), in which Fe(II) is (re)oxidized into Fe (hydr)oxide, which is available for the subsequent DOC attenuation. These mechanisms were supported by the dominance of DIR-relevant bacteria and the growth of NDFO-related bacteria in the presence of NO3⁻.

Complex behavior of petroleum hydrocarbons in vadose zone: A holistic analysis using unsaturated soil columns.

The migration of petroleum hydrocarbons in vadose zone involves complex coupled processes such as downward displacement and natural attenuation. Despite its significance in determining groundwater vulnerability to petroleum contamination and optimizing the remedial strategy, it has not been comprehensively studied in terms of overall processes under field-relevant conditions. In this study, a series of unsaturated soil column experiments were conducted by simulating subsurface diesel contamination within a vadose zone using different soil textures at different soil bulk densities and initial diesel concentrations, while partly exposing them to simulated precipitation. The results showed that the soil column with less fine fraction was favorable for the downward migration of diesel but unfavorable for its natural degradation. However, precipitation complicated the relative conductivities of multiple fluids (water, air, and diesel) through the pore network, therby decreasing diesel migration and degradation. For example, the downward migration of diesel in the SL column decreased by 8.4% under precipitation, while the overall attenuation rate dropped to almost 0.24% of its original state. Lowering bulk density (from 1.5 to 1.23 g/cm3), however, could enhance the attenuation rate presumably due to the secured void space for the incoming fluids. A high initial concentration of diesel (2%; w/w) inhibited its natural attenuation, while its influence on its vertical propagation after the precipitation was not significant. The present findings provide a mechanistic basis for approximating the behavior of petroleum hydrocarbons in a random vadose zone.

Variable effects of soil organic matter on arsenic behavior in the vadose zone under different bulk densities.

The nonstationary nature of water and oxygen content in the vadose zone determines various biogeochemical reactions regarding arsenic (As) therein, which affects the groundwater vulnerability to As contamination at a site. In the present study, we evaluated the effect of soil organic matter (OM) on the behavior of As using specifically designed soil columns that simulated the vadose zone. Three wet-dry cycles were applied to each of the four columns with different OM contents and bulk densities. OM was found to exhibit variable effects, either inhibiting or accelerating the mobilization of As, depending on bulk density. At a moderate bulk density (< 1.27 g/cm3), OM slightly lowered the pH of pore water, which enhanced the sorption of As onto the iron (Fe) oxides, promoting the retention of As in soil. In the soil column with a relatively higher bulk density (1.36 g/cm3), however, the dissimilatory reduction of iron oxides was triggered by rich OM under oxygen-limited conditions. X-ray absorption spectroscopy analysis revealed that alternate wetting and drying transformed the Fe oxides in the soil by reductive dissolution and subsequent re-precipitation. Consequently, As was not stably retained in the soil, and its mobilization downwards was further accelerated.

Denitrification dynamics in unsaturated soils with different porous structures and water saturation degrees: A focus on the shift in microbial community structures.

Despite its environmental significance, little is known about denitrification in vadose zones owing to the complexity of such environments. Here, we investigated denitrification in unsaturated soils with different pore distributions. To this end, we performed batch-type denitrification experiments and analyzed microbial community shifts before and after possible reactions with nitrates to clarify the relevant denitrifying mechanism in the microcosms. For quantitative comparison, pore distribution in the test soil samples was characterized based on the uniformity coefficient (Cu) and water saturation degree (SD). Micro-CT analysis of the soil pore distribution confirmed that the proportion of bigger-sized pores increased with decreasing Cu. However, oxygen diffusion into the system was controlled by SD rather than Cu. Within a certain SD range (51-67%), the pore condition changed abruptly from an oxic to an anoxic state. Consequently, denitrification occurred even under unsaturated soil conditions when the SD increased beyond 51-67%. High throughput sequencing revealed that the same microbial species were potentially responsible for denitrification under both partially (SD 67%), and fully saturated (SD of 100%) conditions, implying that the mechanism of denitrification in a vadose zone, if it exists, might be possibly similar under varying conditions.

A multi-scale framework for modeling transport of microplastics during sand filtration: Bridging from pore to continuum.

The fate and transport of microplastics (MPs) during deep bed filtration were investigated using combined laboratory experiments and numerical modeling. A series of column experiments were conducted within the designated ranges of six operating parameters (i.e., size of the MP and collector, seepage velocity, porosity, temperature, and ionic strength). A variance-based sensitivity analysis, the Fourier amplitude sensitivity test, was conducted to determine the priority in affecting both the attachment coefficient at the pore scale, and the subsequent stabilized height of the breakthrough curve at the continuum scale, which follows non-monotonic trends with singularity in the size of MP (i.e., 1 µm). Finally, Damkohler numbers were introduced to analyze the dominant mechanisms (e.g., attachment, detachment, or straining) in the coupled hydro-chemical process. The robustness of conceptual frameworks bridges the gap between pore-scale interactions and the explicit MPs removal in the continuum scale, which could support decision-making in determining the priority of parameters to retain MPs during deep bed filtration.

Robust multimodal fusion network using adversarial learning for brain tumor grading.

BACKGROUND AND OBJECTIVE: Gliomas are graded using multimodal magnetic resonance imaging, which provides important information for treatment and prognosis. When modalities are missing, the grading is degraded. We propose a robust brain tumor grading model that can handle missing modalities. METHODS: Our method was developed and tested on Brain Tumor Segmentation Challenge 2017 dataset (n = 285) via nested five-fold cross-validation. Our method adopts adversarial learning to generate the features of missing modalities relative to the features obtained from a full set of modalities in the latent space. An attention-based fusion block across modalities fuses the features of each available modality into a shared representation. Our method's results are compared to those of two other models where 15 missing-modality scenarios are explicitly considered and a joint training approach with random dropouts is used. RESULTS: Our method outperforms the two competing methods in classifying high-grade gliomas (HGGs) and low-grade gliomas (LGGs), achieving an area under the curve of 87.76% on average for all missing-modality scenarios. The activation maps derived with our method confirm that it focuses on the enhancing portion of the tumor in HGGs and on the edema and non-enhancing portions of the tumor in LGGs, which is consistent with prior expertise. An ablation study shows the added benefits of a fusion block and adversarial learning for handling missing modalities. CONCLUSION: Our method shows robust grading of gliomas in all cases of missing modalities. Our proposed network might have positive implications in glioma care by learning features robust to missing modalities.

Influence of inter-aquifer leakage on well-injection capacity: Theory and aquifer-scale mapping for artificial recharge.

Aquifer storage and recovery (ASR) is an important water resources management technique that involves the injection of a large volume of water underground. For the successful implementation of an ASR project, a target aquifer should have a sufficient injection capacity, which is the maximum volume of water that can be safely injected. In nature, no aquitard is perfectly impermeable, and inter-aquifer leakage may have a major impact on injection capacity. Despite the importance of determining the injection capacity for ASR planning, there is no quantitative methodology that estimates the injection capacity of leaky aquifers. In this study, we first develop a solution for injection capacity with inter-aquifer leakage based on the Hantush - Jacob solution, and conduct a comprehensive sensitivity analysis to elucidate the influence of inter-aquifer leakage on injection capacity. From the sensitivity analysis, we show that inter-aquifer leakage can impact injection capacity by more than one order of magnitude, depending on the hydrogeological and operational parameters. We then develop a practical mapping methodology that estimates the injection capacity of leaky aquifers. We demonstrate the proposed methodology by applying it to a potential ASR site in Minnesota, USA, where ASR is considered as a solution to alleviate groundwater contamination by PFAS chemicals. The case study results reveal significant spatial variability in injection capacity over the study area and show an average increase in the injection capacity of about 26% compared to that in the nonleaky scenario. We also analyze the uncertainty in the estimated injection capacity due to the variability of aquitard properties and show that the variability of aquitard vertical hydraulic conductivity leads to a larger uncertainty in the estimated injection capacity than does the variability of aquitard thickness. This study elucidates the effects of inter-aquifer leakage on injection capacity and provides a practical methodology for injection capacity mapping.

Zn speciation and fate in soils and sediments along the ground transportation route of Zn ore to a smelter.

Assessment of Zn toxicity/mobility based on its speciation and transformations in soils is critical for maintaining human and ecosystem health. Zn-concentrate (56 % Zn as ZnS, sphalerite) has been imported through a seaport and transported to a Zn-smelter for several decades, and smelting processes resulted in aerial deposition of Zn and sulfuric acids in two geochemically distinct territories around the smelter (mountain-slope and riverside). XAFS analysis showed that the mountain-slope soils contained franklinite (ZnFe2O4) and amorphous (e.g., sorbed) species of Zn(II), whereas the riverside sediments contained predominantly hydrozincite [Zn5(OH)6(CO3)2], sphalerite, and franklinite. The mountain-slope soils had low pH and moderate levels of total Zn (~ 1514 ppm), whereas the riverside sediments had neutral pH and higher total Zn (12,363 ppm). The absence of sphalerite and the predominance of franklinite in the mountain-slope soils are attributed to the susceptibility of sphalerite and the resistance of franklinite to dissolution at acidic pH. These results are compared to previous Zn analyses along the transportation routes, which showed that Zn-concentrate spilled along the roadside in dust and soils underwent transformation to various O-coordinated Zn species. Overall, Zn-concentrate dispersed in soils and sediments during transportation and smelting transforms into Zn phases of diverse stability and bioavailability during long-term weathering.

Incremental benefits of size-zone matrix-based radiomics features for the prognosis of lung adenocarcinoma: advantage of spatial partitioning on tumor evaluation.

OBJECTIVES: Prognostic models of lung adenocarcinoma (ADC) can be built using radiomics features from various categories. The size-zone matrix (SZM) features have a strong biological basis related to tumor partitioning, but their incremental benefits have not been fully explored. In our study, we aimed to evaluate the incremental benefits of SZM features for the prognosis of lung ADC. METHODS: A total of 298 patients were included and their pretreatment computed tomography images were analyzed in fivefold cross-validation. We built a risk model of overall survival using SZM features and compared it with a conventional radiomics risk model and a clinical variable-based risk model. We also compared it with other models incorporating various combinations of SZM features, other radiomics features, and clinical variables. A total of seven risk models were compared and evaluated using the hazard ratio (HR) on the left-out test fold. RESULTS: As a baseline, the clinical variable risk model showed an HR of 2.739. Combining the radiomics signature with SZM feature was better (HR 4.034) than using radiomics signature alone (HR 3.439). Combining radiomics signature, SZM feature, and clinical variable (HR 6.524) fared better than just combining radiomics signature and clinical variables (HR 4.202). These results confirmed the added benefits of SZM features for prognosis in lung ADC. CONCLUSION: Combining SZM feature with the radiomics signature was better than using the radiomics signature alone and the benefits of SZM features were maintained when clinical variables were added confirming the incremental benefits of SZM features for lung ADC prognosis. KEY POINTS: • Size-zone matrix (SZM) features provide incremental benefits for the prognosis of lung adenocarcinoma. • Combining the radiomics signature with SZM features performed better than using a radiomics signature alone.

Coupled effect of porous network and water content on the natural attenuation of diesel in unsaturated soils.

The natural attenuation potential of a vadose zone against diesel is critical for optimizing remedial actions and determining groundwater vulnerability to contamination. Here, diesel attenuation in unsaturated soils was systematically examined to develop a qualitative relationship between physical soil properties and the natural attenuation capacity of a vadose zone against diesel. The uniformity coefficient (Cu) and water saturation (Sw, %) were considered as the proxies reflecting the degree of effects by porous network and water content in different soils, respectively. These, in turn, are related to the primary diesel attenuation mechanisms of volatilization and biodegradation. The volatilization of diesel was inversely proportional to Cu and Sw, which could be attributed to effective pore channels facilitating gas transport. Conversely, biodegradation was highly proportional to Cu under unsaturated conditions (Sw = 35-71%), owing to nutrients typically associated with fine soil particles. The microbial community in unsaturated soils was affected by Sw rather than Cu. The overall diesel attenuation including volatilization and biodegradation was optimized at Sw = 35% for all tested soils.

Transient behavior of arsenic in vadose zone under alternating wet and dry conditions: A comparative soil column study.

The water and oxygen contents of the vadose zone change cyclically depending upon the meteorological condition (e.g., intermittent rainfall), which can affect the biogeochemical reactions that govern the fate of arsenic (As). To simulate and evaluate the transient behavior of As in this zone when subjected to repeated wet and dry conditions, soil column experiments with different soil properties were conducted. Three wetting-drying cycles resulted in the fluctuation of water and dissolved oxygen contents, and consequently, the reduction-oxidation potential in the soil columns. Under these circumstances, the biotic reduction of As(V) to As(III) was observed, especially in the column filled with soils enriched in organic matter. Most of the As was found to be associated with soil particles rather than to be dissolved in the pore water in all of the columns tested. Retention of As was more preferable in the soil column with a higher Fe content and bulk density, which provided more sorption sites and reaction time, respectively. However, a considerable amount of soil-bound As could be remobilized and released back to the pore water with the repetition of wetting and drying due to the transformation of As(V) to As(III).

What determines the efficacy of landfarming for petroleum-contaminated soils: Significance of contaminant characteristics.

Identifying the cause of inconsistent landfarming efficacy is critical to designing optimal remedial strategies for petroleum-contaminated sites. We assessed contaminated soils collected from two former military bases in South Korea to better understand the role and influence of different factors. Landfarming remediation was simulated in the laboratory by applying comparable practices (such as tillage and bioaugmentation) and the relevant mechanism was examined. We then systematically examined potential factors affecting petroleum-removal efficacy, including the content of fine soil particles, the initial concentration and composition of petroleum contaminants, and the degree of soil-contaminant interaction. The distribution range of total petroleum hydrocarbons (TPHs) and the size of unresolved complex mixture (UCM) found in gas chromatography data showed that petroleum composed of TPHs with lower carbon numbers and having smaller size of UCM could be treated more effectively by landfarming. Incorporating the evaluation of the distribution range and UCM properties of petroleum, rather than simply considering its total concentration, is a more accurate and efficient method for determining the site-specific suitability of landfarming as a remedial option, as well as for assessing the necessity of supplementary processes.

Evaluation of Response to Immune Checkpoint Inhibitors Using a Radiomics, Lesion-Level Approach.

Conventional methods to determine the response to immune checkpoint inhibitors (ICIs) are limited by the unique responses to an ICI. We performed a radiomics approach for all measurable lesions to identify radiomic variables that could distinguish hyperprogressive disease (HPD) on baseline CT scans and classify a dissociated response (DR). One hundred and ninety-six patients with advanced lung cancer, treated with ICI monotherapy, who underwent at least three CT scans, were retrospectively enrolled. For all 621 measurable lesions, HPDv was determined from baseline CT scans using the tumor growth kinetics (TGK) ratio, and radiomics features were extracted. Multivariable logistic regression analysis of radiomics features was performed to discriminate DR. Radiomics features that significantly discriminated HPDv on baseline CT differed according to organ. Of the 196 patients, 54 (27.6%) had a DR and 142 (72.4%) did not have a DR. Overall survival in the group with a DR was significantly inferior to that in the group without a DR (log rank test, p = 0.04). Our study shows that lesion-level analysis using radiomics features has great potential for discriminating HPDv and understanding heterogeneous tumor progression, including a DR, after ICI treatment.

Discrimination methods for diesel origin by analyzing fatty acid methyl ester (FAME) composition in diesel-contaminated soil.

The biodiesel containing fatty acid methyl esters (FAMEs) are blended with refined diesel products. Here, we evaluate relative FAME composition ratio as a potential index to discriminate the pollution origin in diesel-contaminated soil. Artificially contaminated soil was prepared to mimic the release of petroleum products using four different refined diesels; in addition, the contaminated soil was put under natural weathering conditions. The variations in the relative FAME composition ratio was compared with those of the corresponding diesel origin using principal component analysis (PCA) for 60 days. All soil samples could be classified into four groups according to diesel origin using two principal components. The proposed method can be used to discriminate the specific diesel pollution origin in contaminated soils.