ARID1A loss induces P4HB to activate fibroblasts to support lung cancer cell growth, invasion, and chemoresistance.

Loss of AT-interacting domain-rich protein 1A (ARID1A) frequently occurs in human malignancies including lung cancer. The biological consequence of ARID1A mutation in lung cancer is not fully understood. This study was designed to determine the effect of ARID1A-depleted lung cancer cells on fibroblast activation. Conditioned media was collected from ARID1A-depleted lung cancer cells and employed to treat lung fibroblasts. The proliferation and migration of lung fibroblasts were investigated. The secretory genes were profiled in lung cancer cells upon ARID1A knockdown. Antibody-based neutralization was utilized to confirm their role in mediating the cross-talk between lung cancer cells and fibroblasts. NOD-SCID-IL2RgammaC-null (NSG) mice received tumor tissues from patients with ARID1A-mutated lung cancer to establish patient-derived xenograft (PDX) models. Notably, ARID1A-depleted lung cancer cells promoted the proliferation and migration of lung fibroblasts. Mechanistically, ARID1A depletion augmented the expression and secretion of prolyl 4-hydroxylase beta (P4HB) in lung cancer cells, which induced the activation of lung fibroblasts through the ß-catenin signaling pathway. P4HB-activated lung fibroblasts promoted the proliferation, invasion, and chemoresistance in lung cancer cells. Neutralizing P4HB hampered the tumor growth and increased cisplatin cytotoxic efficacy in two PDX models. Serum P4HB levels were higher in ARID1A-mutated lung cancer patients than in healthy controls. Moreover, increased serum levels of P4HB were significantly associated with lung cancer metastasis. Together, our work indicates a pivotal role for P4HB in orchestrating the cross-talk between ARID1A-mutated cancer cells and cancer-associated fibroblasts during lung cancer progression. P4HB may represent a promising target for improving lung cancer treatment.

Molecular mechanisms and emerging therapies in wild-type transthyretin amyloid cardiomyopathy.

Wild-type transthyretin amyloid cardiomyopathy (ATTRwt-CM) is an underrecognized cause of heart failure due to misfolded wild-type transthyretin (TTRwt) myocardial deposition. The development of wild-type TTR amyloid fibrils is a complex pathological process linked to the deterioration of homeostatic mechanisms owing to aging, plausibly implicating multiple molecular mechanisms. The components of amyloid transthyretin often include serum amyloid P, proteoglycans, and clusterin, which may play essential roles in the localization and elimination of amyloid fibrils. Oxidative stress, impaired mitochondrial function, and perturbation of intracellular calcium dynamics induced by TTR contribute to cardiac impairment. Recently, tafamidis has been the only drug approved by the U.S. Food and Drug Administration (FDA) for the treatment of ATTRwt-CM. In addition, small interfering RNAs and antisense oligonucleotides for ATTR-CM are promising therapeutic approaches and are currently in phase III clinical trials. Newly emerging therapies, such as antibodies targeting amyloid, inhibitors of seed formation, and CRISPR‒Cas9 technology, are currently in the early stages of research. The development of novel therapies is based on progress in comprehending the molecular events behind amyloid cardiomyopathy. There is still a need to further advance innovative treatments, providing patients with access to alternative and effective therapies, especially for patients diagnosed at a late stage.

VASN promotes the aggressive phenotype in ARID1A-deficient lung adenocarcinoma.

Loss of ARID1A has been reported to drive the progression of lung adenocarcinoma, yet the underlying mechanism remains elusive. In this study, we performed secretome analysis to identify the key secreted proteins regulating lung adenocarcinoma progression. We showed that the VASN level was significantly elevated in the conditioned medium from ARID1A-depleted A549 and H1299 cells. Restoration of ARID1A in ARID1A-depleted lung adenocarcinoma cells prevented the upregulation and secretion of VASN. Clinical analysis demonstrated a negative correlation between ARID1A and VASN expression in ARID1A-mutated lung adenocarcinomas. The patients with ARID1A-mutated lung adenocarcinoma had significantly higher concentrations of serum VASN than healthy controls. Moreover, serum VASN concentrations were associated with TNM stage, lymph node metastasis, and overall survival of the patients with ARID1A-mutated lung adenocarcinoma. Functional studies indicated that VASN overexpression potentiated the proliferation, invasion, and tumorigenesis of lung adenocarcinoma cells. Antibody neutralization of VASN suppressed the aggressiveness of ARID1A-depleted lung adenocarcinoma cells both in vitro and in vivo. Addition of recombinant VASN protein promoted the proliferation and invasion of lung adenocarcinoma cells. Additionally, knockdown of Notch1 blocked the aggressive phenotype induced by recombinant VASN protein. In conclusion, our data uncover the role of VASN in mediating the progression of ARID1A-depleted lung adenocarcinoma and highlight VASN as a promising therapeutic target for this disease.

A Bayesian multivariate hierarchical model for developing a treatment benefit index using mixed types of outcomes.

BACKGROUND: Precision medicine has led to the development of targeted treatment strategies tailored to individual patients based on their characteristics and disease manifestations. Although precision medicine often focuses on a single health outcome for individualized treatment decision rules (ITRs), relying only on a single outcome rather than all available outcomes information leads to suboptimal data usage when developing optimal ITRs. METHODS: To address this limitation, we propose a Bayesian multivariate hierarchical model that leverages the wealth of correlated health outcomes collected in clinical trials. The approach jointly models mixed types of correlated outcomes, facilitating the "borrowing of information" across the multivariate outcomes, and results in a more accurate estimation of heterogeneous treatment effects compared to using single regression models for each outcome. We develop a treatment benefit index, which quantifies the relative benefit of the experimental treatment over the control treatment, based on the proposed multivariate outcome model. RESULTS: We demonstrate the strengths of the proposed approach through extensive simulations and an application to an international Coronavirus Disease 2019 (COVID-19) treatment trial. Simulation results indicate that the proposed method reduces the occurrence of erroneous treatment decisions compared to a single regression model for a single health outcome. Additionally, the sensitivity analyses demonstrate the robustness of the model across various study scenarios. Application of the method to the COVID-19 trial exhibits improvements in estimating the individual-level treatment efficacy (indicated by narrower credible intervals for odds ratios) and optimal ITRs. CONCLUSION: The study jointly models mixed types of outcomes in the context of developing ITRs. By considering multiple health outcomes, the proposed approach can advance the development of more effective and reliable personalized treatment.

Association between COVID-19 convalescent plasma antibody levels and COVID-19 outcomes stratified by clinical status at presentation.

BACKGROUND: There is a need to understand the relationship between COVID-19 Convalescent Plasma (CCP) anti-SARS-CoV-2 IgG levels and clinical outcomes to optimize CCP use. This study aims to evaluate the relationship between recipient baseline clinical status, clinical outcomes, and CCP antibody levels. METHODS: The study analyzed data from the COMPILE study, a meta-analysis of pooled individual patient data from 8 randomized clinical trials (RCTs) assessing the efficacy of CCP vs. control, in adults hospitalized for COVID-19 who were not receiving mechanical ventilation at randomization. SARS-CoV-2 IgG levels, referred to as 'dose' of CCP treatment, were retrospectively measured in donor sera or the administered CCP, semi-quantitatively using the VITROS Anti-SARS-CoV-2 IgG chemiluminescent immunoassay (Ortho-Clinical Diagnostics) with a signal-to-cutoff ratio (S/Co). The association between CCP dose and outcomes was investigated, treating dose as either continuous or categorized (higher vs. lower vs. control), stratified by recipient oxygen supplementation status at presentation. RESULTS: A total of 1714 participants were included in the study, 1138 control- and 576 CCP-treated patients for whom donor CCP anti-SARS-CoV2 antibody levels were available from the COMPILE study. For participants not receiving oxygen supplementation at baseline, higher-dose CCP (/control) was associated with a reduced risk of ventilation or death at day 14 (OR = 0.19, 95% CrI: [0.02, 1.70], posterior probability Pr(OR < 1) = 0.93) and day 28 mortality (OR = 0.27 [0.02, 2.53], Pr(OR < 1) = 0.87), compared to lower-dose CCP (/control) (ventilation or death at day 14 OR = 0.79 [0.07, 6.87], Pr(OR < 1) = 0.58; and day 28 mortality OR = 1.11 [0.10, 10.49], Pr(OR < 1) = 0.46), exhibiting a consistently positive CCP dose effect on clinical outcomes. For participants receiving oxygen at baseline, the dose-outcome relationship was less clear, although a potential benefit for day 28 mortality was observed with higher-dose CCP (/control) (OR = 0.66 [0.36, 1.13], Pr(OR < 1) = 0.93) compared to lower-dose CCP (/control) (OR = 1.14 [0.73, 1.78], Pr(OR < 1) = 0.28). CONCLUSION: Higher-dose CCP is associated with its effectiveness in patients not initially receiving oxygen supplementation, however, further research is needed to understand the interplay between CCP anti-SARS-CoV-2 IgG levels and clinical outcome in COVID-19 patients initially receiving oxygen supplementation.

Aquiflexum gelatinilyticum sp. nov., isolated from river water.

Two Gram-stain-negative, strictly aerobic, rod-shaped, non-motile and non-gliding bacteria, designated as XJ19-10T and XJ19-11, were isolated from river water in Xinjiang Uygur Autonomous Region, PR China. Cells of these strains were catalase-, oxidase- and gelatinase-positive and contained carotenoids but no flexirubins. Growth occurred at 10-30 °C, pH 7.0-9.0 and with 0-2.5% (w/v) NaCl. On the basis of the results of 16S rRNA gene sequence and genome analyses, the two isolates represented members of the genus Aquiflexum, and the closest relative was Aquiflexum aquatile Z0201T with 16S rRNA gene sequence pairwise similarities of 97.9-98.1%. Furthermore, the average nucleotide identities and digital DNA-DNA hybridization identities between the two isolates and other relatives were all less than 82.9 and 28.2 %, respectively, all below the species delineation thresholds. The results of pan-genomic analysis indicated that the type strain XJ19-10T shared 2813 core gene clusters with other three type strains of members of the genus Aquiflexum, as well as having 623 strain-specific clusters. The major polar lipids were phosphatidylethanolamine, phosphatidylcholine, an unidentified aminolipid and unidentified lipids. The predominant fatty acids (>10% of the total contents) were iso-C15 : 0, iso-C15 : 1G, iso-C17 : 0 3-OH and summed feature 9, and MK-7 was the respiratory quinone. On the basis of the results of phenotypic, physiological, chemotaxonomic and genotypic characterization, strains XJ19-10T and XJ19-11 are considered to represent a novel species, for which the name Aquiflexum gelatinilyticum sp. nov. is proposed. The type strain is XJ19-10T (=CGMCC 1.19385T =KCTC 92266T).

Developing a Bayesian hierarchical model for a prospective individual patient data meta-analysis with continuous monitoring.

BACKGROUND: Numerous clinical trials have been initiated to find effective treatments for COVID-19. These trials have often been initiated in regions where the pandemic has already peaked. Consequently, achieving full enrollment in a single trial might require additional COVID-19 surges in the same location over several years. This has inspired us to pool individual patient data (IPD) from ongoing, paused, prematurely-terminated, or completed randomized controlled trials (RCTs) in real-time, to find an effective treatment as quickly as possible in light of the pandemic crisis. However, pooling across trials introduces enormous uncertainties in study design (e.g., the number of RCTs and sample sizes might be unknown in advance). We sought to develop a versatile treatment efficacy assessment model that accounts for these uncertainties while allowing for continuous monitoring throughout the study using Bayesian monitoring techniques. METHODS: We provide a detailed look at the challenges and solutions for model development, describing the process that used extensive simulations to enable us to finalize the analysis plan. This includes establishing prior distribution assumptions, assessing and improving model convergence under different study composition scenarios, and assessing whether we can extend the model to accommodate multi-site RCTs and evaluate heterogeneous treatment effects. In addition, we recognized that we would need to assess our model for goodness-of-fit, so we explored an approach that used posterior predictive checking. Lastly, given the urgency of the research in the context of evolving pandemic, we were committed to frequent monitoring of the data to assess efficacy, and we set Bayesian monitoring rules calibrated for type 1 error rate and power. RESULTS: The primary outcome is an 11-point ordinal scale. We present the operating characteristics of the proposed cumulative proportional odds model for estimating treatment effectiveness. The model can estimate the treatment's effect under enormous uncertainties in study design. We investigate to what degree the proportional odds assumption has to be violated to render the model inaccurate. We demonstrate the flexibility of a Bayesian monitoring approach by performing frequent interim analyses without increasing the probability of erroneous conclusions. CONCLUSION: This paper describes a translatable framework using simulation to support the design of prospective IPD meta-analyses.

Devosia ureilytica sp. nov., isolated from Kuche River in China.

Two novel strains, designated XJ19-45T and XJ19-1, were isolated from water of Kuche River in Xinjiang Uygur Autonomous Region, China. Their cells were Gram-stain-negative, aerobic and motile rods. The phylogenetic analyses based on 16S rRNA genes and genomes showed that the two isolates belonged to the genus Devosia and the closest relative was Devosia subaequoris HST3-14T. The 16S rRNA genes sequences pairwise similarities, average nucleotide identities, digital DNA-DNA hybridizations and average amino acid identities between type strain XJ19-45T and other relatives were all less than 98.3, 80.3, 23.6 and 85.7 %, respectively, all below the species delineation thresholds. Pan-genomic analysis indicated that the novel isolate XJ19-45T shared 1594 core gene clusters with the 11 closely related type strains in Devosia, and the number of strain-specific clusters was 390. The major cellular fatty acids (>10 %) of the two isolates were summed feature 8, C18 : 1 ω7c 11-methyl and C16 : 0. Diphosphatidylglycerol, phosphatidylglycerol and glycolipids were the major polar lipids, and Q10 was the detected respiratory quinone. Based on the results of phenotypic, physiological, chemotaxonomic and genotypic characterizations, we propose that the isolates represent a novel species, for which the name Devosia ureilytica sp. nov. is proposed. The type strain is XJ19-45T (=CGMCC 1.19388T=KCTC 92263T).

Visible Light-Induced Coupling Cyclization Reaction of α-Diazosulfonium Triflates with α-Oxocarboxylic Acids or Alkynes.

A photocatalyst-free radical cleavage of α-diazo sulfonium salts has been developed for the first time. The reaction provides an efficient method for the generation of diazomethyl radicals from α-diazosulfonium triflates under photochemical conditions. Utilizing the in situ generated diazomethyl radicals as key intermediate, the coupling cyclization reaction of α-diazosulfonium triflates with α-oxocarboxylic acids or alkynes has been achieved. The method affords a diverse set of important 2,5-disubstituted 1,3,4-oxadiazoles and 3,5-disubstituted-1H-pyrazoles with excellent regioselectivity in a single step. A reaction mechanism involving a radical pathway was further supported by control experiments and DFT calculations.

Test-Retest Reliability of a New Device Versus a Long-Arm Goniometer to Evaluate Knee Proprioception.

CONTEXT: Many methods used to evaluate knee proprioception have shortcomings that limit their use in clinical settings. Based on an inexpensive 3D camera, a new portable device was recently used to evaluate the joint position sense (JPS) of the knee joint. However, the test-retest reliability of the new method remains unclear. This study aimed to evaluate the test-retest reliability of the new device and a long-arm goniometer for assessing knee JPS, and to compare the variability of the 2 methods. DESIGN: Prospective observational study of the test-retest reliability of knee JPS measurements. METHODS: Twenty-one healthy adults were tested in 2 sessions with a 1-week interval. Three target knee flexion angles (30°, 45°, and 60°) were reproduced in each session. Target and reproduced angles were measured with both methods. Intraclass correlation coefficients, standard error of the measurement, and Bland-Altman plots were used to quantify test-retest reliability. Paired t tests were used to compare knee JPS (absolute error of the target-reproduced angle) between the methods. RESULTS: The new device (good to excellent intraclass correlation coefficients .74-.80; standard error of the measurement 0.52°-0.61°) demonstrated better test-retest reliability than the goniometer (poor to fair intraclass correlation coefficients .23-.43; standard error of the measurement 0.89°-2.07°) and better test-retest agreement (respective mean differences for the 30°, 45°, and 60° knee angles: 0.11°, 0.13°, and 0.41° for the new system; 0.84°, 1.52°, and 1.18° for the goniometer). The measurements (absolute errors of the target-reproduced angles) with the goniometer were significantly greater than those with the new device (P < .05); the SDs of repeated measurements with the goniometer (1.50°-2.41°) were greater than with the new device (1.08°-1.38°). CONCLUSIONS: Given that the new device has good reliability and sufficient precision, it is the better alternative for evaluating knee JPS. Goniometers should be used with caution to assess knee JPS.

Notoginsenoside R1 alleviates TEGDMA-induced mitochondrial apoptosis in preodontoblasts through activation of Akt/Nrf2 pathway-dependent mitophagy.

Incomplete polymerization or biodegradation of dental resin materials results in the release of resin monomers such as triethylene glycol dimethacrylate (TEGDMA), causing severe injury of dental pulp cells. To date, there has been no efficient treatment option for this complication, in part due to the lack of understanding of the mechanism underlying these phenomena. Here, for the first time, we found that notoginsenoside R1 (NR1), a bioactive ingredient extracted from Panax notoginseng, exerted an obvious protective effect on TEGDMA-induced mitochondrial apoptosis in the preodontoblast mDPC6T cell line. In terms of the mechanism of action, NR1 enhanced the level of phosphorylated Akt (protein kinase B), resulting in the activation of a transcriptional factor, nuclear factor erythroid 2-related factor 2 (Nrf2), and eventually upregulating cellular ability to resist TEGDMA-related toxicity. Inhibiting the Akt/Nrf2 pathway by pharmaceutical inhibitors significantly decreased NR1-mediated cellular antioxidant properties and aggravated mitochondrial oxidative damage in TEGDMA-treated cells. Interestingly, NR1 also promoted mitophagy, which was identified as the potential downstream of the Akt/Nrf2 pathway. Blocking the Akt/Nrf2 pathway inhibited mitophagy and abolished the protection of NR1 on cells exposed to TEGDMA. In conclusion, these findings reveal that the activation of Akt/Nrf2 pathway-mediated mitophagy by NR1 might be a promising approach for preventing resin monomer-induced dental pulp injury.

Roseomonas oleicola sp. nov., isolated from an oil production mixture in Yumen Oilfield, and emended description of Roseomonas frigidaquae.

A pink, ovoid-shaped, Gram-stain-negative, strictly aerobic and motile bacterial strain, designated ROY-5-3T, was isolated from an oil production mixture from Yumen Oilfield in PR China. The strain grew at 4-42 °C (optimum, 30 °C), at pH 5-10 (optimum, 7) and with 0-5 % (w/v) NaCl (optimum, 0%). The results of phylogenetic analysis based on 16S rRNA gene sequences indicated that ROY-5-3T belongs to the genus Roseomonas and shared the highest pairwise similarities with Roseomonas frigidaquae CW67T (98.1%), Roseomonas selenitidurans BU-1T (97.8%), Roseomonas tokyonensis K-20T (97.7%) and Roseomonas stagni HS-69T (97.3%). The average nucleotide identity and digital DNA-DNA hybridization values between ROY-5-3T and other related type strains of Roseomonas species were less than 84.08 and 28.60 %, respectively, both below the species delineation threshold. Pan-genomic analysis showed that the novel isolate ROY-5-3T shared 3265 core gene families with the four closely related type strains in Roseomonas, and the number of strain-specific gene families was 513. The major fatty acids were identified as summed feature 8 (C18 : 1 ω6c/C18 : 1 ω7c), summed feature 3 (C16 : 1 ω6c/C16 : 1 ω7c) and C16 : 0. Strain ROY-5-3T contained Q-10 as the main ubiquinone and the genomic DNA G+C content was 69.8 mol%. The major polar lipids were diphosphatidylglycerol, phosphatidylcholine, phosphatidylethanolamine and phosphatidylglycerol. Based on the phylogenetic, morphological, physiological, chemotaxonomic and genome analyses, strain ROY-5-3T represents a novel species of the genus Roseomonas for which the name Roseomonas oleicola sp. nov. is proposed. The type strain is ROY-5-3T (=CGMCC 1.13459T =KCTC 82484T).

Capnocytophaga periodontitidis sp. nov., isolated from subgingival plaque of periodontitis patient.

Two carbon dioxide-requiring, gliding, Gram-stain-negative strains, designated p1a2T and 051621, were isolated from subgingival plaque in association with severe periodontitis. The 16S rRNA gene sequence analysis revealed that they represented members of the genus Capnocytophaga and had less than 96.4 % pairwise similarity with species with validly published names in this genus. The whole-genome sequences of those strains had less than 91.9 % average nucleotide identity and 48.4 % digital DNA-DNA hybridization values with the other type strains of species of the genus Capnocytophaga, both below the species delineation threshold. The results of pan-genomic analysis indicated that p1a2T and 051621 shared 765 core gene families with the other ten species in this genus, and the numbers of strain-specific gene families were 493 and 455, respectively. The major fatty acids were iso-C15 : 0 and C16 : 0. A combination of phenotypic, chemotaxonomic, phylogenetic and genotypic data clearly indicate that p1a2T and 051621 should be considered to represent a novel species of the genus Capnocytophaga, for which the name Capnocytophaga periodontitidis sp. nov. is proposed. The type strain is p1a2T (=CGMCC 1.17337T=JCM 34126T).

Prospective individual patient data meta-analysis: Evaluating convalescent plasma for COVID-19.

As the world faced the devastation of the COVID-19 pandemic in late 2019 and early 2020, numerous clinical trials were initiated in many locations in an effort to establish the efficacy (or lack thereof) of potential treatments. As the pandemic has been shifting locations rapidly, individual studies have been at risk of failing to meet recruitment targets because of declining numbers of eligible patients with COVID-19 encountered at participating sites. It has become clear that it might take several more COVID-19 surges at the same location to achieve full enrollment and to find answers about what treatments are effective for this disease. This paper proposes an innovative approach for pooling patient-level data from multiple ongoing randomized clinical trials (RCTs) that have not been configured as a network of sites. We present the statistical analysis plan of a prospective individual patient data (IPD) meta-analysis (MA) from ongoing RCTs of convalescent plasma (CP). We employ an adaptive Bayesian approach for continuously monitoring the accumulating pooled data via posterior probabilities for safety, efficacy, and harm. Although we focus on RCTs for CP and address specific challenges related to CP treatment for COVID-19, the proposed framework is generally applicable to pooling data from RCTs for other therapies and disease settings in order to find answers in weeks or months, rather than years.

Resolving Entangled JH-H-Coupling Patterns for Steroidal Structure Determinations by NMR Spectroscopy.

For decades, high-resolution 1H NMR spectroscopy has been routinely utilized to analyze both naturally occurring steroid hormones and synthetic steroids, which play important roles in regulating physiological functions in humans. Because the 1H signals are inevitably superimposed and entangled with various JH-H splitting patterns, such that the individual 1H chemical shift and associated JH-H coupling identities are hardly resolved. Given this, applications of thess information for elucidating steroidal molecular structures and steroid/ligand interactions at the atomic level were largely restricted. To overcome, we devoted to unraveling the entangled JH-H splitting patterns of two similar steroidal compounds having fully unsaturated protons, i.e., androstanolone and epiandrosterone (denoted as 1 and 2, respectively), in which only hydroxyl and ketone substituents attached to C3 and C17 were interchanged. Here we demonstrated that the JH-H values deduced from 1 and 2 are universal and applicable to other steroids, such as testosterone, 3ß, 21-dihydroxygregna-5-en-20-one, prednisolone, and estradiol. On the other hand, the 1H chemical shifts may deviate substantially from sample to sample. In this communication, we propose a simple but novel scheme for resolving the complicate JH-H splitting patterns and 1H chemical shifts, aiming for steroidal structure determinations.

Monitoring and warning of lipophilic marine algal toxins in mariculture zone based on toxin profiles of phytoplankton.

Some toxigenic dinoflagellates can produce lipophilic marine algal toxins (LMATs), which are potent threats to marine breeding industries. In this study, a new method based on the profiling analysis of six LMAT classes in phytoplankton was developed for the monitoring and warning of LMATs in mariculture zones. This method was applied to monitor and evaluate LMATs in the Jiaozhou Bay and the Changjiang estuary in China. Results demonstrated that the occurrence and spatiotemporal variations of LMATs in mariculture zones can be revealed by the toxin profiles of phytoplankton, indicating the method's effectiveness for the comprehensive monitoring of the composition and levels of various LMATs in coastal aquaculture zones. The method was further used as an alarm for potential pollution risk from LMATs in mariculture zones at an early stage. The "alert" thresholds of LMAT pollution in the mariculture zones were preliminarily proposed based on the statistical data analysis of LMATs in phytoplankton in three typical mariculture areas in China. This study is the first to conduct simultaneous monitoring and warning of multi-class LMATs based on toxin profiles of phytoplankton, thereby providing new insight into the monitoring and early warning of natural poisonous pollutants in coastal aquaculture zones around the world.

Synthesis and purification of biotinylated oligodeoxynucleotides containing single TpT dimeric pyrimidine (6-4) pyrimidone lesion.

Ultraviolet (UV) radiation could induce pyrimidine-related dimeric lesions in genomic DNA. Though the cyclobutane pyrimidine dimers (CPDs) are the most abundant UV-induced lesions, the pyrimidine (6-4) pyrimidone photoproducts (6-4PPs) may have more serious, potentially lethal, and mutagenic effects. It is important to have 6-4PP-containing oligodeoxynucleotides to be prepared for studying their adverse biological effects. Here, we developed a UV-irradiated water droplet method for the preparation of a biotinylated, 6-4PP-containing 10-mer oligodeoxynucleotide. By the use of HPLC purification and enrichment twice, the final yield is estimated to be about 8.1%. In contrast, without applying droplet technique, the direct UV irradiation against oligonucleotide-containing aqueous solution, the product yield is very low. The enzymatic hydrolyzation of the obtained product shows a 6-4PP characteristic ion transition of 545.12 → 432.13 in negative ion mode UHPLC-Q-TOF/MS. The established procedure for the preparation of 6-4PP-containing oligonucleotides is convenient with an improved yield. Graphical abstract ᅟ.

Affinity maturation of an antibody for the UV-induced DNA lesions 6,4 pyrimidine-pyrimidones.

DNA lesions, associated mostly with minor changes in DNA structure, may induce permanent change in heritable coding information. Biochemically, these minor structural changes are difficult to be explored for generating high-affinity antibodies to detect specific DNA lesions in varying sequence contexts. Herein, we established a platform of bacterial display to facilitate antibodies to be matured with high affinity and high specificity against DNA lesions. To achieve this goal, we, for the first time, developed a two-round mutation/screening strategy: (1) using multiple lesion-containing DNA probes for primary maturation and (2) using single lesion-containing DNA probes for second maturation. Specifically, we capitalized on 64M-2 as a parental template to improve affinity for 6-4PP by 710-fold, compared with the model one. In addition, the matured antibody (9c3) is found to be much less dependent on the bases surrounding 6-4PPs than the model one. The mechanistic study from both computational simulation and reverse mutations revealed the critical roles of the two-round mutations in the enhanced binding affinity and independence of surrounding bases. This selection strategy opens a new way to improve affinity and specificity of antibodies for other DNA lesions.

Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN.

Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features.