Comammox Nitrospira cooperate with anammox bacteria in a partial nitritation-anammox membrane bioreactor treating low-strength ammonium wastewater at high loadings.

Research has revealed that comammox Nitrospira and anammox bacteria engage in dynamic interactions in partial nitritation-anammox reactors, where they compete for ammonium and nitrite or comammox Nitrospria supply nitrite to anammox bacteria. However, two gaps in the literature are present: the know-how to manipulate the interactions to foster a stable and symbiotic relationship and the assessment of how effective this partnership is for treating low-strength ammonium wastewater at high hydraulic loads. In this study, we employed a membrane bioreactor designed to treat synthetic ammonium wastewater at a concentration of 60 mg N/L, reaching a peak loading of 0.36 g N/L/day by gradually reducing the hydraulic retention time to 4 hr. Throughout the experiment, the reactor achieved an approximately 80 % nitrogen removal rate through strategically adjusting intermittent aeration at every stage. Notably, the genera Ca. Kuenena, Nitrosomonas, and Nitrospira collectively constituted approximately 40 % of the microbial community. Under superior intermittent aeration conditions, the expression of comammox amoA was consistently higher than that of Nitrospira nxrB and AOB amoA in the biofilm, despite the higher abundance of Nitrosomonas than comammox Nitrospira, implying that the biofilm environment is favorable for fostering cooperation between comammox and anammox bacteria. We then assessed the in situ activity of comammox Nitrospira in the reactor by selectively suppressing Nitrosomonas using 1-octyne, thereby confirming that comammox Nitrospira played the primary role in facilitating the nitritation (33.1 % of input ammonium) rather than complete nitrification (7.3 % of input ammonium). Kinetic analysis revealed a specific ammonia-oxidizing rate 5.3 times higher than the nitrite-oxidizing rate in the genus Nitrospira, underscoring their critical role in supplying nitrite. These findings provide novel insights into the cooperative interplay between comammox Nitrospira and anammox bacteria, potentially reshaping the management of nitrogen cycling in engineered environments, and aiding the development of microbial ecology-driven wastewater treatment technologies.

Intelligent Phase Contrast Meta-Microscope System.

Phase contrast imaging techniques enable the visualization of disparities in the refractive index among various materials. However, these techniques usually come with a cost: the need for bulky, inflexible, and complicated configurations. Here, we propose and experimentally demonstrate an ultracompact meta-microscope, a novel imaging platform designed to accomplish both optical and digital phase contrast imaging. The optical phase contrast imaging system is composed of a pair of metalenses and an intermediate spiral phase metasurface located at the Fourier plane. The performance of the system in generating edge-enhanced images is validated by imaging a variety of human cells, including lung cell lines BEAS-2B, CLY1, and H1299 and other types. Additionally, we integrate the ResNet deep learning model into the meta-microscope to transform bright-field images into edge-enhanced images with high contrast accuracy. This technology promises to aid in the development of innovative miniature optical systems for biomedical and clinical applications.

Acidosis promotes the metastatic colonization of lung cancer via remodeling of the extracellular matrix and vasculogenic mimicry.

Acidosis is a hallmark of the tumor microenvironment caused by the metabolic switch from glucose oxidative phosphorylation to glycolysis. It has been associated with tumor growth and progression; however, the precise mechanism governing how acidosis promotes metastatic dissemination has yet to be elucidated. In the present study, a long­term acidosis model was established using patient­derived lung cancer cells, to identify critical components of metastatic colonization via transcriptome profiling combined with both in vitro and in vivo functional assays, and association analysis using clinical samples. Xenograft inoculates of 1 or 10 acidotic cells mimicking circulating tumor cell clusters were shown to exhibit increased tumor incidence compared with their physiological pH counterparts. Transcriptomics revealed that profound remodeling of the extracellular matrix (ECM) occurred in the acidotic cells, including upregulation of the integrin subunit α­4 (ITGA4) gene. In clinical lung cancer, ITGA4 expression was found to be upregulated in primary tumors with metastatic capability, and this trait was retained in the corresponding secondary tumors. Expression of ITGA4 was markedly upregulated around the vasculogenic mimicry structures of the acidotic tumors, while acidotic cells exhibited a higher ability of vasculogenic mimicry in vitro. Acidosis was also found to induce the enrichment of side population cells, suggesting an enhanced resistance to noxious attacks of the tumor microenvironment. Taken together, these results demonstrated that acidosis actively contributed to tumor metastatic colonization, and novel mechanistic insights into the therapeutic management and prognosis of lung cancer were discussed.

Feature selection translates drug response predictors from cell lines to patients.

Targeted therapies and chemotherapies are prevalent in cancer treatment. Identification of predictive markers to stratify cancer patients who will respond to these therapies remains challenging because patient drug response data are limited. As large amounts of drug response data have been generated by cell lines, methods to efficiently translate cell-line-trained predictors to human tumors will be useful in clinical practice. Here, we propose versatile feature selection procedures that can be combined with any classifier. For demonstration, we combined the feature selection procedures with a (linear) logit model and a (non-linear) K-nearest neighbor and trained these on cell lines to result in LogitDA and KNNDA, respectively. We show that LogitDA/KNNDA significantly outperforms existing methods, e.g., a logistic model and a deep learning method trained by thousands of genes, in prediction AUC (0.70-1.00 for seven of the ten drugs tested) and is interpretable. This may be due to the fact that sample sizes are often limited in the area of drug response prediction. We further derive a novel adjustment on the prediction cutoff for LogitDA to yield a prediction accuracy of 0.70-0.93 for seven drugs, including erlotinib and cetuximab, whose pathways relevant to anti-cancer therapies are also uncovered. These results indicate that our methods can efficiently translate cell-line-trained predictors into tumors.

Single-shot quantitative phase contrast imaging based on deep learning.

Quantitative differential phase-contrast (DPC) imaging is one of the commonly used methods for phase retrieval. However, quantitative DPC imaging requires several pairwise intensity measurements, which makes it difficult to monitor living cells in real-time. In this study, we present a single-shot quantitative DPC imaging method based on the combination of deep learning (DL) and color-encoded illumination. Our goal is to train a model that can generate an isotropic quantitative phase image (i.e., target) directly from a single-shot intensity measurement (i.e., input). The target phase image was reconstructed using a linear-gradient pupil with two-axis measurements, and the model input was the measured color intensities obtained from a radially asymmetric color-encoded illumination pattern. The DL-based model was trained, validated, and tested using thirteen different cell lines. The total number of training, validation, and testing images was 264 (10 cells), 10 (1 cell), and 40 (2 cells), respectively. Our results show that the DL-based phase images are visually similar to the ground-truth phase images and have a high structural similarity index (>0.98). Moreover, the phase difference between the ground-truth and DL-based phase images was smaller than 13%. Our study shows the feasibility of using DL to generate quantitative phase imaging from a single-shot intensity measurement.

Regulation of dendritic cell maturation in osimertinib-treated lung adenocarcinoma patients.

Osimertinib (OSI), a third-generation tyrosine kinase inhibitor (TKI), efficiently benefits lung adenocarcinoma (LUAD) patients with epidermal growth factor receptor (EGFR) mutations. However, combined OSI and immune checkpoint inhibitor in EGFR-mutant patients increases the incidence of interstitial lung disease (ILD), although the mechanism is unknown. Here, we investigated the interaction between dendritic cells (DCs), a potential critical player in ILD, and OSI. Seventeen LUAD patients received TKI therapy, and only the OSI therapy group (N = 10) showed a significant increase in CD40 and CD83 on immature DCs (iDCs), and an elevated trend for both markers on mature DCs (mDCs) during short- and long-term OSI therapy. Our results indicated that OSI therapy may potentially activate DC functions, which might increase the potential immune toxicity when combined with onco-immunotherapy.

Rapid and sensitive dilute-and-shoot analysis using LC-MS-MS for identification of multi-class psychoactive substances in human urine.

The emergence of new psychoactive substances currently exceeding a thousand is rapidly changing substance prevalence patterns and straining the methods used for detection, most of which are suitable only for a single class of substances. This study presents a rapid and facile dilute-and-shoot system operated in conjunction with an optimized liquid chromatographic separation system for the high-sensitivity detection of substances across a range of substance classes with 3 isotopes used only. The proposed method based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) is able to identify 68 substance and their metabolites in urine samples as small as 50 µL. Optimal chromatographic conditions including 95% water/methanol ratio with 0.1% added formic acid and a prolonged LC gradient run-time (15 min) improved the peak shape of polar compounds and enhanced signal strength by 5%. Under 4-fold dilution, all analytes were within 80-120% of tolerance response levels, indicating that the matrix effect was insignificant. In experiments, the limit of detection (LOD) ranged from 0.05 to 0.5 ng mL-1, while the coefficient of determination (R2) was > 0.9950. The retention time shift of each peak remained at < 2% with an inter-day relative standard deviation (RSD) of 0.9-14.9% and intra-day RSD of 1.1%- 13.8%. The rapid dilute-and-shoot presents a high-sensitivity, significant stability, robustness and reproducibility without serious interference. To demonstrate the effectiveness of the system, 532 urine samples were collected from suspected drug abusers, and the proposed method was used for rapid analysis. Of these samples, 79.5% contained between one and twelve analytes, and 12.4% tested positive for new psychoactive substances, mostly derivatives of amphetamine and synthetic cathinones. The study presents a high-sensitivity analytic system that is capable of detecting substances from multiple classes and can be used for effective monitoring of substance prevalence in urine.

Peruvoside is a novel Src inhibitor that suppresses NSCLC cell growth and motility by downregulating multiple Src-EGFR-related pathways.

The tyrosine kinase Src plays an essential role in the progression of many cancers and is involved in several epidermal growth factor receptor (EGFR)-mediated signalling pathways. To improve the efficacy of lung cancer treatments, this study aimed to identify novel compounds that can disrupt the Src-EGFR interaction and that are less dependent on EGFR status with wild-type and mutations than other compounds. We used the Src pY419 ELISA as the platform to screen a compound library of more than 400 plant-derived active ingredients and identified peruvoside as a candidate Src-EGFR crosstalk inhibitor. The effects of peruvoside were evaluated by western blotting, cell function assays, combination Index (CI)-isobologram analyses and in vivo experiments. Peruvoside significantly suppressed the phosphorylation of Src, EGFR, and signal transducer and activator of transcription 3 (STAT3) in a dose- and time-dependent manner and somewhat suppressed their protein expression. Cell function assays revealed that peruvoside inhibited the proliferation, invasion, migration, and colony formation of lung cancer cells in vitro and tumour growth in vivo. Furthermore, peruvoside sensitized gefitinib-resistant tumour cells (A549, PC9/gef and H1975) to gefitinib treatment, indicating that peruvoside may exert synergistic effects when used in combination with established therapeutic agents. Our data also demonstrated that the inhibitory effects of peruvoside on lung cancer progression might be attributed to its ability to regulate Src, phosphoinositide 3-kinase (PI3K), c-Jun N-terminal kinase (JNK), Paxillin, p130cas, and EGFR. Our findings suggest that peruvoside suppresses non-small-cell lung carcinoma (NSCLC) malignancy by downregulating multiple Src-related pathways and could serve as a potential base molecule for developing new anticancer drugs and therapeutic strategies for lung cancer.

Monitoring Phthalates in Maternal and Cord Blood: Implications for Prenatal Exposure and Birth Outcomes.

Although many phthalates are endocrine-disrupting chemicals that are associated with adverse birth outcomes, the relationship between maternal phthalate exposure and birth outcomes is not yet conclusive. The objective of the present study was to investigate the association between prenatal exposure to phthalates in human maternal and cord blood and birth outcomes of the infants. Sixty-five mother-infant pairs were recruited in Taipei City and New Taipei City, and birth outcomes of the infants were recorded. Twelve phthalate metabolites were measured in maternal and cord blood samples. The mean of mono-ethyl phthalate, mono-isobutyl phthalate (MiBP), mono-n-butyl phthalate (MnBP), and mono-(2-ethylhexyl) phthalate (MEHP) was relatively higher than that of the other metabolites in both maternal and infant blood. There was a significant difference (p < 0.05) for mono-methyl phthalate (MMP) and MnBP between the maternal blood and cord blood of male infants. Mono-benzyl phthalate (MBzP), MMP, MiBP, and ∑di-2-ethylhexyl phthalate (∑DEHP) in maternal blood were inversely correlated with the anogenital index (AGI) of male infants, with a p value between 0.011 and 0.033. Mono-n-octyl phthalate, MMP, MiBP, MnBP, and MBzP were positively correlated with the AGI of female infants, with a p value between 0.001 and 0.034. Cord blood levels of MnBP, mono-(2-ethyl-5-oxohexyl)-phthalate, MEHP, and ∑DEHP were found to be inversely associated with head circumference in all the infants, adjusted for gestational age. Phthalate monoesters are potentially estrogenic and antiandrogenic chemicals. Longitudinal follow-up of the present study population could help clarify the long-term impact of phthalates on growth and the health effects of background exposure levels. Environ Toxicol Chem 2022;41:715-725. © 2022 SETAC.

A proposed approach to confirm heroin administration - Regional differences in heroin purity is a major factor.

In forensic toxicology, a marker of street heroin use is urgent especially in the absence of urinary 6-monoacetylmorphine. ATM4G, the Glucuronide of Acetylated product of Thebaine compound 4 Metabolite (ATM4), arising from byproducts of street heroin synthesis has been considered as a useful marker in some European studies. However, whether ATM4G is a universal marker particularly in Southeast Asia due to 'street' heroin with high purity, it's still unclear. To investigate putative markers for different regions, ATM4G and other metabolites including the Acetylated product of Thebaine compound 3 Metabolite (ATM3) and thebaol, also originated from thebaine were detected in 552 urine samples from heroin users in Taiwan. Results were compared with that from samples collected in the UK and Germany. Only a sulfo-conjugate of ATM4, ATM4S, was detected in 28 Taiwanese users using a sensitive MS3 method whilst out of 351 samples from the UK and Germany, ATM4G was present in 91. Thebaol-glucuronide was first time detected in 118. No markers were detected in urine following herbal medicine use or poppy seed ingestion. The presence of ATM4S/ATM4G might be affected by ethnicities and heroin supplied in regions. Thebaol-glucuronide is another putative marker with ATM4G and ATM4S for street heroin use.

Tumor microenvironment-based screening repurposes drugs targeting cancer stem cells and cancer-associated fibroblasts.

The tumorous niche may drive the plasticity of heterogeneity and cancer stemness, leading to drug resistance and metastasis, which is the main reason of treatment failure in most cancer patients. The aim of this study was to establish a tumor microenvironment (TME)-based screening to identify drugs that can specifically target cancer stem cells (CSCs) and cancer-associated fibroblasts (CAFs) in the TME. Methods: Lung cancer patient-derived cancer cell and CAFs were utilized to mimic the TME and reproduce the stemness properties of CSCs in vitro and develop a high-throughput drug screening platform with phenotypical parameters. Limiting dilution assay, sphere-forming and ALDH activity assay were utilized to measure the cancer stemness characteristics. In vivo patient-derived xenograft (PDX) models and single-cell RNA sequencing were used to evaluate the mechanisms of the compounds in CSCs and CAFs. Results: The TME-based drug screening platform could comprehensively evaluate the response of cancer cells, CSCs and CAFs to different treatments. Among the 1,524 compounds tested, several drugs were identified to have anti-CAFs, anticancer and anti-CSCs activities. Aloe-emodin and digoxin both show anticancer and anti-CSCs activity in vitro and in vivo, which was further confirmed in the lung cancer PDX model. The combination of digoxin and chemotherapy improved therapeutic efficacy. The single-cell transcriptomics analysis revealed that digoxin could suppress the CSCs subpopulation in CAFs-cocultured cancer cells and cytokine production in CAFs. Conclusions: The TME-based drug screening platform provides a tool to identify and repurpose compounds targeting cancer cells, CSCs and CAFs, which may accelerate drug development and therapeutic application for lung cancer patients.

DNA methylome and transcriptome landscapes of cancer-associated fibroblasts reveal a smoking-associated malignancy index.

Unlike the better-studied aberrant epigenome in the tumor, the clinicopathologic impact of DNA methylation in the tumor microenvironment (TME), especially the contribution from cancer-associated fibroblasts (CAFs), remains elusive. CAFs exhibit profound patient-to-patient tumorigenic heterogeneity. We asked whether such heterogeneity may be exploited to quantify the level of TME malignancy. We developed a robust and efficient methylome/transcriptome co-analytical system for CAFs and paired normal fibroblasts (NFs) from non-small-cell lung cancer patients. We found 14,781 CpG sites of CAF/NF differential methylation, of which 3,707 sites showed higher methylation changes in ever-smokers than in nonsmokers. Concomitant CAF/NF differential gene expression analysis pointed to a subset of 54 smoking-associated CpG sites with strong methylation-regulated gene expression. A methylation index that summarizes the ß values of these CpGs was built for NF/CAF discrimination (MIND) with high sensitivity and specificity. The potential of MIND in detecting premalignancy across individual patients was shown. MIND succeeded in predicting tumor recurrence in multiple lung cancer cohorts without reliance on patient survival data, suggesting that the malignancy level of TME may be effectively graded by this index. Precision TME grading may provide additional pathological information to guide cancer prognosis and open up more options in personalized medicine.

Genome-Wide Epigenetic Landscape of Lung Adenocarcinoma Links HOXB9 DNA Methylation to Intrinsic EGFR-TKI Resistance and Heterogeneous Responses.

PURPOSE: Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) show efficacy in treating patients with lung adenocarcinoma with EGFR-activating mutations. However, a significant subset of targeted patients fail to respond. Unlike acquired resistance (AR), intrinsic resistance (IR) remains poorly understood. We investigated whether epigenomic factors contribute to patient-to-patient heterogeneity in the EGFR-TKI response and aimed to characterize the IR subpopulation that obtains no benefit from EGFR-TKIs. PATIENTS AND METHODS: We conducted genome-wide DNA methylation profiling of 79 tumors sampled from patients with advanced lung adenocarcinoma before they received EGFR-TKI treatment and analyzed the patient responses. Pyrosequencing was performed in a validation cohort of 163 patients with EGFR-activating mutations. RESULTS: A DNA methylation landscape of 216 CpG sites with differential methylation was established to elucidate the association of DNA methylation with the characteristics and EGFR-TKI response status of the patients. Functional analysis of 37 transcription-repressive sites identified the enrichment of transcription factors, notably homeobox (HOX) genes. DNA methylation of HOXB9 (cg13643585) in the enhancer region yielded 88% sensitivity for predicting drug response (odds ratio [OR], 6.64; 95% CI, 1.98 to 25.23; P = .0009). Pyrosequencing validated that HOXB9 gained methylation in patients with a poor EGFR-TKI response (OR, 3.06; 95% CI, 1.13 to 8.19; P = .019). CONCLUSION: Our data suggest that homeobox DNA methylation could be a novel tumor cellular state that can aid the precise categorization of tumor heterogeneity in the study of IR to EGFR-TKIs. We identified, for the first time, an epigenomic factor that can potentially complement DNA mutation status in discriminating patients with lung adenocarcinoma who are less likely to benefit from EGFR-TKI treatment, thereby leading to improved patient management in precision medicine.

A combined microRNA and target protein-based panel for predicting the probability and severity of uraemic vascular calcification: a translational study.

AIMS: Vascular calcification (VC) increases the future risk of cardiovascular events in uraemic patients, but effective therapies are still unavailable. Accurate identification of those at risk of developing VC using pathogenesis-based biomarkers is of particular interest and may facilitate individualized risk stratification. We aimed to uncover microRNA (miRNA)-target protein-based biomarker panels for evaluating uraemic VC probability and severity. METHODS AND RESULTS: We created a three-tiered in vitro VC model and an in vivo uraemic rat model receiving high phosphate diet to mimic uraemic VC. RNAs from the three-tiered in vitro and in vivo uraemic VC models underwent miRNA and mRNA microarray, with results screened for differentially expressed miRNAs and their target genes as biomarkers. Findings were validated in original models and additionally in an ex vivo VC model and human cells, followed by functional assays of identified miRNAs and target proteins, and tests of sera from end-stage renal disease (ESRD) and non-dialysis-dependent chronic kidney disease (CKD) patients without and with VC. Totally 122 down-regulated and 119 up-regulated miRNAs during calcification progression were identified initially; further list narrowing based on miRNA-mRNA pairing, anti-correlation, and functional enrichment left 16 and 14 differentially expressed miRNAs and mRNAs. Levels of four miRNAs (miR-10b-5p, miR-195, miR-125b-2-3p, and miR-378a-3p) were shown to decrease throughout all models tested, while one mRNA (SULF1, a potential target of miR-378a-3p) exhibited the opposite trend concurrently. Among 96 ESRD (70.8% with VC) and 59 CKD patients (61% with VC), serum miR-125b2-3p and miR-378a-3p decreased with greater VC severity, while serum SULF1 levels increased. Adding serum miR-125b-2-3p, miR-378a-3p, and SULF1 into regression models for VC substantially improved performance compared to using clinical variables alone. CONCLUSION: Using a translational approach, we discovered a novel panel of biomarkers for gauging the probability/severity of uraemic VC based on miRNAs/target proteins, which improved the diagnostic accuracy.

The M1/M2 spectrum and plasticity of malignant pleural effusion-macrophage in advanced lung cancer.

BACKGROUND: Malignant pleural effusion (MPE)-macrophage (Mφ) of lung cancer patients within unique M1/M2 spectrum showed plasticity in M1-M2 transition. The M1/M2 features of MPE-Mφ and their significance to patient outcomes need to be clarified; furthermore, whether M1-repolarization could benefit treatment remains unclear. METHODS: Total 147 stage-IV lung adenocarcinoma patients undergoing MPE drainage were enrolled for profiling and validation of their M1/M2 spectrum. In addition, the MPE-Mφ signature on overall patient survival was analyzed. The impact of the M1-polarization strategy of patient-derived MPE-Mφ on anti-cancer activity was examined. RESULTS: We found that MPE-Mφ expressed both traditional M1 (HLA-DRA) and M2 (CD163) markers and showed a wide range of M1/M2 spectrum. Most of the MPE-Mφ displayed diverse PD-L1 expression patterns, while the low PD-L1 expression group was correlated with higher levels of IL-10. Among these markers, we identified a novel two-gene MPE-Mφ signature, IL-1ß and TGF-ß1, representing the M1/M2 tendency, which showed a strong predictive power in patient outcomes in our MPE-Mφ patient cohort (N = 60, p = 0.013) and The Cancer Genome Atlas Lung Adenocarcinoma dataset (N = 478, p < 0.0001). Significantly, ß-glucan worked synergistically with IFN-γ to reverse the risk signature by repolarizing the MPE-Mφ toward the M1 pattern, enhancing anti-cancer activity. CONCLUSIONS: We identified MPE-Mφ on the M1/M2 spectrum and plasticity and described a two-gene M1/M2 signature that could predict the outcome of late-stage lung cancer patients. In addition, we found that "re-education" of these MPE-Mφ toward anti-cancer M1 macrophages using clinically applicable strategies may overcome tumor immune escape and benefit anti-cancer therapies.

Astaxanthin Counteracts Vascular Calcification In Vitro Through an Early Up-Regulation of SOD2 Based on a Transcriptomic Approach.

Vascular calcification (VC) is a critical contributor to the rising cardiovascular risk among at-risk populations such as those with diabetes or renal failure. The pathogenesis of VC involves an uprising of oxidative stress, for which antioxidants can be theoretically effective. However, astaxanthin, a potent antioxidant, has not been tested before for the purpose of managing VC. To answer this question, we tested the efficacy of astaxanthin against VC using the high phosphate (HP)-induced vascular smooth muscle cell (VSMC) calcification model. RNAs from treated groups underwent Affymetrix microarray screening, with intra-group consistency and inter-group differential expressions identified. Candidate hub genes were selected, followed by validation in experimental models and functional characterization. We showed that HP induced progressive calcification among treated VSMCs, while astaxanthin dose-responsively and time-dependently ameliorated calcification severities. Transcriptomic profiling revealed that 3491 genes exhibited significant early changes during VC progression, among which 26 potential hub genes were selected based on closeness ranking and biologic plausibility. SOD2 was validated in the VSMC model, shown to drive the deactivation of cellular senescence and enhance antioxidative defenses. Astaxanthin did not alter intracellular reactive oxygen species (ROS) levels without HP, but significantly lowered ROS production in HP-treated VSMCs. SOD2 knockdown prominently abolished the anti-calcification effect of astaxanthin on HP-treated VSMCs, lending support to our findings. In conclusion, we demonstrated for the first time that astaxanthin could be a potential candidate treatment for VC, through inducing the up-regulation of SOD2 early during calcification progression and potentially suppressing vascular senescence.

Proteogenomics of Non-smoking Lung Cancer in East Asia Delineates Molecular Signatures of Pathogenesis and Progression.

Lung cancer in East Asia is characterized by a high percentage of never-smokers, early onset and predominant EGFR mutations. To illuminate the molecular phenotype of this demographically distinct disease, we performed a deep comprehensive proteogenomic study on a prospectively collected cohort in Taiwan, representing early stage, predominantly female, non-smoking lung adenocarcinoma. Integrated genomic, proteomic, and phosphoproteomic analysis delineated the demographically distinct molecular attributes and hallmarks of tumor progression. Mutational signature analysis revealed age- and gender-related mutagenesis mechanisms, characterized by high prevalence of APOBEC mutational signature in younger females and over-representation of environmental carcinogen-like mutational signatures in older females. A proteomics-informed classification distinguished the clinical characteristics of early stage patients with EGFR mutations. Furthermore, integrated protein network analysis revealed the cellular remodeling underpinning clinical trajectories and nominated candidate biomarkers for patient stratification and therapeutic intervention. This multi-omic molecular architecture may help develop strategies for management of early stage never-smoker lung adenocarcinoma.

Landscape of Mitochondria Genome and Clinical Outcomes in Stage 1 Lung Adenocarcinoma.

Risk factors including genetic effects are still being investigated in lung adenocarcinoma (LUAD). Mitochondria play an important role in controlling imperative cellular parameters, and anomalies in mitochondrial function might be crucial for cancer development. The mitochondrial genomic aberrations found in lung adenocarcinoma and their associations with cancer development and progression are not yet clearly characterized. Here, we identified a spectrum of mitochondrial genome mutations in early-stage lung adenocarcinoma and explored their association with prognosis and clinical outcomes. Next-generation sequencing was used to reveal the mitochondrial genomes of tumor and conditionally normal adjacent tissues from 61 Stage 1 LUADs. Mitochondrial somatic mutations and clinical outcomes including relapse-free survival (RFS) were analyzed. Patients with somatic mutations in the D-loop region had longer RFS (adjusted hazard ratio, adjHR = 0.18, p = 0.027), whereas somatic mutations in mitochondrial Complex IV and Complex V genes were associated with shorter RFS (adjHR = 3.69, p = 0.012, and adjHR = 6.63, p = 0.002, respectively). The risk scores derived from mitochondrial somatic mutations were predictive of RFS (adjHR = 9.10, 95%CI: 2.93-28.32, p < 0.001). Our findings demonstrated the vulnerability of the mitochondrial genome to mutations and the potential prediction ability of somatic mutations. This research may contribute to improving molecular guidance for patient treatment in precision medicine.

Predicting the Associations between Meridians and Chinese Traditional Medicine Using a Cost-Sensitive Graph Convolutional Neural Network.

Natural products are the most important and commonly used in Traditional Chinese Medicine (TCM) for healthcare and disease prevention in East-Asia. Although the Meridian system of TCM was established several thousand years ago, the rationale of Meridian classification based on the ingredient compounds remains poorly understood. A core challenge for the traditional machine learning approaches for chemical activity prediction is to encode molecules into fixed length vectors but ignore the structural information of the chemical compound. Therefore, we apply a cost-sensitive graph convolutional neural network model to learn local and global topological features of chemical compounds, and discover the associations between TCM and their Meridians. In the experiments, we find that the performance of our approach with the area under the receiver operating characteristic curve (ROC-AUC) of 0.82 which is better than the traditional machine learning algorithm and also obtains 8%-13% improvement comparing with the state-of-the-art methods. We investigate the powerful ability of deep learning approach to learn the proper molecular descriptors for Meridian prediction and to provide novel insights into the complementary and alternative medicine of TCM.

Determination of synthetic cathinone α-pyrrolidinovalero-phenone and its metabolite in urine using solid-phase extraction and gas chromatography-mass spectrometry.

RATIONALE: The presence of α-pyrrolidinovalerophenone (α-PVP) and its metabolites in urine is evidence of the administration of α-PVP. A toxicological challenge is that the metabolites of α-PVP exhibit amphoteric properties, which make them unsuitable for detection using gas chromatography-mass spectrometry (GC/MS). In the study reported, proper derivatization and sample extraction were essential for improving the sensitivity for GC/MS analysis. METHODS: An automated solid-phase extraction (SPE) method has been developed and optimized. The derivatization efficiency was tested using longer reaction time and the addition of polar pyridine into a mixture of N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA) with 1% trimethylchlorosilane. Method validation, including linearity, limit of detection, precision, accuracy, and recovery, was evaluated using automatic SPE and GC/MS. RESULTS: The results suggested that adding pyridine to BSTFA (1:1, v/v) significantly improved derivatization efficiency and precision. After optimization, the linear range was from 25 to 1000 ng mL-1 with R2 > 0.9950. The limit of detection was 5 ng mL-1 for α-PVP and 25 ng mL-1 for OH-α-PVP. The recovery for SPE was over 88%. The inter-day and intra-day precisions were less than 15%. A forensic sample has been found containing α-PVP (67.3 ng mL-1 ) and OH-α-PVP (560.2 ng mL-1 ). CONCLUSIONS: This study is the first to validate an auto-SPE-GC/MS method for the quantification and qualification of α-PVP and OH-α-PVP in urine. We have successfully improved the derivatization efficiency and developed a sensitive and semi-automatic approach. This approach is desirable for the detection of synthetic cathinone at trace levels in biological samples.