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Low-temperature co-fired ceramics (LTCCs) have been attracting attention due to rapid advances in wireless telecommunications. Low-dielectric-constant (Dk) and low-dissipation-factor (Df) LTCCs enable a low propagation delay and high signal quality. However, the wide ranges of glass, ceramic filler compositions, and processing features in fabricating LTCC make property modulating difficult via experimental trial-and-error approaches. In this study, we explored Dk and Df values of LTCCs using a machine learning method with a Gaussian kernel ridge regression model. A principal component analysis and k-means methods were initially performed to visually analyze data clustering and to reduce the dimension complexity. Model assessments, by using a five-fold cross-validation, residual analysis, and randomized test, suggest that the proposed Dk and Df models had some predictive ability, that the model selection was appropriate, and that the fittings were not just numerical due to a rather small data set. A cross-plot analysis and property contour plot were performed for the purpose of exploring potential LTCCs for real applications with Dk and Df values less than 10 and 2 × 10−3, respectively, at an operating frequency of 1 GHz. The proposed machine learning models can potentially be utilized to accelerate the design of technology-related LTCC systems.

Simple Summary Photoperiods can affect sexual maturity, body weight, and body composition. In this work, we provided male mule ducks with a one-hour lighting from 20:00 to 21:00, in addition to the natural photoperiod, and evaluated its effects on their body weight, organ mass, gonadal function, and plasma levels of metabolites. The results indicate that the nocturnal lighting stimulated gonadal development and function and reduced fat deposition. This implies that nocturnal lighting is able to shorten the feeding period for the marketing of mature ducks. Abstract In this study, the effects of a nocturnal light pulse on body weight, organ mass, gonadal function, and plasma levels of metabolites were determined in male mule ducks. In total, 32 15-week-old mule ducks were randomly allocated to either Group C (control group) or L+ (lighting group). Group C was exposed to the natural photoperiod, whereas Group L+ was provided with a 1-h lighting over 20:00–21:00 every day, in addition to the natural photoperiod. At the end of the 42-day experiment, Group L+ had significantly lower relative weights (% of live weight) of the digestive tract and abdominal fat and higher relative weights of the breast meat and testes than Group C. Moreover, Group L+ had significantly higher plasma testosterone and lower plasma glucose levels. However, no between-group differences were observed in the triacylglycerol and uric acid levels. Histological examination demonstrated that the seminiferous tubule diameter was larger in Group L+ than in Group C. Moreover, the meiosis stage in spermatogenesis had begun in Group L+ but not in Group C. In conclusion, the supplemented 1-h lighting at 20:00 stimulated gonadal development and function and reduced fat deposition.

Objective Palladin is a ubiquitous phosphoprotein expressed in vertebrate cells that works as a scaffolding protein. Several isoforms deriving from alternative splicing are originated from the palladin gene and involved in mesenchymal and muscle cells formation, maturation, migration, and contraction. Recent studies have linked palladin to the invasive spread of cancer and myogenesis. However, since its discovery, the promoter region of the palladin gene has never been studied. The objective of this study was to predict, identify, and measure the activity of the promoter regions of palladin gene. Results By using promoter prediction programs, we successfully identified the transcription start sites for the Palld isoforms and revealed the presence of a variety of transcriptional regulatory elements including TATA box, GATA, MyoD, myogenin, MEF, Nkx2-5, and Tcf3 upstream promoter regions. The transcriptome profiling approach confirmed the active role of predicted transcription factors in the mouse genome. This study complements the missing piece in the characterization of palladin gene and certainly contributes to understanding the complexity and enrollment of palladin regulatory factors in gene transcription.

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with an overall five-year survival rate of 11%. Potential curative resection is possible if the tumor is detected at an early stage, with a five-year survival rate of 42%. The only current FDA-cleared biomarker for PDAC is the carbohydrate antigen 19-9 (CA19-9), which is intended for monitoring response to therapy but not for early detection. CA19-9 blood tests have varying sensitivity to detect PDAC and are prone to false positives in the presence of other underlying pancreatic conditions and to false negatives in subpopulations unable to express CA19-9. The goal of our pilot study was to determine if a multiomics approach using cell-free DNA and CA19-9 would be better than CA19-9 alone in detecting PDAC. In this retrospective study of 75 participants, we performed targeted methylation profiling of circulating cell-free DNA and quantitation of plasma CA19-9 abundance. Participants with PDAC (n=39) were 51% male with a mean age of 74.9 years, and consisted of stage II (n=9), stage III (n=11) and stage IV (n=19) pancreatic cancer. Controls (n=36) were 33% male with a mean age of 74.2 years, and included both healthy control/normal pancreas (n=17) and various benign abnormalities of the pancreas or biliary system (n=19). We developed a novel machine learning model that combines CA19-9 and methylation signals to build a joint multiomics prediction. We compared the joint predictions to those based on methylation or CA19-9 alone. Five resamplings of three-fold cross-validation were performed, and sensitivity was calculated for decision thresholds that achieved the desired test set specificity. Across all stages, the multiomics approach achieved a sensitivity of 93% at a specificity of 96%, which was greater than methylation or CA19-9 alone. At 96% specificity, methylation alone achieved a sensitivity of 74% while CA19-9 alone achieved a sensitivity of 87%. In stages II, III and IV, the multiomics approach achieved a sensitivity of 82%, 89%, and 100%, respectively and was also more sensitive than either methylation or CA19-9 alone. These proof-of-concept data demonstrate the promise of using a multiomics approach to develop a highly sensitive and specific test for the early detection of pancreatic cancer. Additional studies are underway, focusing on early-stage disease (stage I/II), to validate these results. Citation Format: Teng-Kuei Hsu, Tzu-Yu Liu, Billie Gould, Christine Decapite, Amer Zureikat, Alessandro Paniccia, Eric Ariazi, Marvin Bertin, Richard Bourgon, Kaitlyn Coil, Hayley Donnella, Adam Drake, Julie M. Granka, Preet Kaur, Maggie C. Louie, Shivani Mahajan, Amit Pasupathy, Ofer Shapira, Peter Ulz, Chun Yang, C. Jimmy Lin, Randall Brand. Plasma-based detection of pancreatic cancer: A multiomics approach [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-007.

For this study, we designed learning activities in which students applied newly acquired knowledge to solve meaningful daily life problems in their local community – a real, familiar, and relevant environment for students. For example, students learned about signs and rules in class and then applied this new knowledge to create their own rules for a location in their community (e.g., playground rules that tell visitors what is or is not allowed to do in a local playground) to make it more environmentally friendly. To facilitate this, we developed a mobile learning system equipped with a dictionary as well as textual annotation, recording, and sharing functions. This mobile learning system enables students to take pictures of objects, describe them verbally or in writing, and share their work with peers. Our goal was to study the effectiveness of learning activities supported by a mobile learning system on the cognitive learning process by examining the changes in students’ cognitive processes and the distribution of students who reach a certain level of cognition before and after learning. Fifty-seven junior high school students participated in the research, and their views of the mobile learning system and interest in continuing use were also explored. Students were divided into one control $({{\mathrm{n}} = 26})$ group and one experimental $({{\mathrm{n}} = 31})$ group. The control group completed learning activities using a traditional approach while the experimental group used a learning system installed in tablet PCs. The effectiveness of the mobile PC system on students’ cognitive processes was tested by comparing the control and experimental groups’ pre-test and post-test outcomes. Changes in students’ cognitive processes were measured by calculating the differences in student scores among three tasks. The distribution of students who reached a certain level of cognition was derived based on their learning performance. Students’ perceptions were evaluated using a questionnaire survey. The mobile learning system kept records of how students used it. Our results show that the experimental students significantly outperformed the control students on test items related to high cognitive levels. Students made clear cognitive progress from the second topic to the third one. Most students rated the learning system highly and want to use it in the future. Finally, the results show that creating text annotations is the best indicator of learning. Based on these results, we recommend applying appropriate learning activities supported by a mobile learning system to facilitate students’ cognitive processes when they are studying English as a foreign language in an authentic environment.

Additional file 2: Table S2. Transcription start sites (TSS) prediction by Promoter 2.0 Prediction Server.

Background The present study aimed to develop a new scale to evaluate the level of difficulty in treating major depressive disorder with antidepressants based on the lifetime treatment profile. Methods In addition to evaluating the difficulty of treatment with antidepressants (A subscale), the Treatment Resistance to Antidepressants Evaluation Scale (TRADES) is comprised of a subscale to account for the attributes that compromise the efficacy of treatment (B subscale). One hundred and six participants aged 18 to 65 years with remitted major depressive disorder were enrolled. Eligible cases were those with at least 2 years from disease onset until the scoring date of the TRADES (the index date), with a complete treatment record. Various psychosocial and clinical features, such as neuroticism, harm avoidance, and utilization of psychiatric services, were used to validate the TRADES. Results The mean duration of the course before and after the index date were 5.5 ± 3.5 and 3.1 ± 1.7 years, respectively. In a multiple regression analysis, the final total scores of the TRADES independently correlated with higher levels of neuroticism and harm avoidance. Total scores were also associated with a higher utilization of psychiatric outpatient and admission services before the index date. Furthermore, it is thought that total scores could predict a higher number of visits to psychiatric outpatient, emergency, and admission services following the index date. Conclusions The TRADES has acceptable validity and could help to quantify the level of treatment difficulty with antidepressants in major depressive disorder.

Additional file 3: Figure S1. Transcription factors general expression.

Additional file 4: Figure S2. Expression of palladin isoforms and myogenic genes.

Additional file 1: Table S1. Oligonucleotides used for qPCR.

Emergency usage intention and behavior are crucial to business service success for m-Health providers and patient healthcare service. This study aimed to identify the factors that influence m-Health acceptance and the effect of emergency use intentions on usage behavior among Taiwanese m-Health users by adopting and extending the Unified Theory of Acceptance and Use of Technology (UTAUT). This study also examines the moderating role of gender and age in the effects of the independent variables on satisfaction with m-Health services. An online questionnaire was used to collect data from 371 participants. The results revealed that performance expectancy, facilitating conditions, and trust had positive effects on user satisfaction. Additionally, m-Health knowledge and user satisfaction had positive effects on emergency use intentions. However, social influence and effort expectancy did not have a significant effect on satisfaction. Moreover, age and gender significantly moderated the effects of some predictors.

For this study the researchers designed learning activities to enhance students’ high level cognitive processes. Students learned new information in a classroom setting and then applied and analyzed their new knowledge in familiar authentic contexts by taking pictures of objects found there, describing them, and sharing their homework with peers. An experiment was carried out in which 58 junior high school students were divided into a control (n = 30) and an experimental (n = 28) group. The control group studied and completed learning activities with traditional textbooks while the experimental group used electronic textbooks and a learning system, Virtual Pen for Tablet PC (VPenTPC), in order to gauge the feasibility of the proposed approach. The post-test results show a significant difference between the control and experimental groups. In our analysis of the various approaches students took to complete the task, we were able to identify thirty cognitive and metacognitive strategies for using mobile technology, from which we selected the ten most frequently used ones. The results show that low ability students make better use of strategies than their high ability peers, resulting in significant learning gains. The results also show that most students perceive VPenTPC positively. Based on these results, we suggest some implications along with conclusions and directions for future research.

43 Background: Blood-based screening tests for colorectal cancer (CRC) with high sensitivity and specificity are needed to improve adherence, facilitate early detection, and ultimately reduce mortality from CRC. Current stool-based tests have a sensitivity of 24-42% for colorectal advanced adenomas (AAs), while blood tests that rely on tumor-derived cell-free DNA (cfDNA) methylation signatures have shown limited sensitivity for AAs. Here we demonstrate the ability to detect AAs from blood using a multiomics test that incorporates both tumor- and immune-derived signatures, and compare it to the performance of a cfDNA methylation-only test. Methods: Participants enrolled in a prospective study (NCT03688906) were included in this analysis. The multiomics test includes signatures for cell-free nucleic acids based on next-generation sequencing, and for plasma proteins based on high-throughput multiplexed assays. Signatures are integrated computationally with a combination of convolutional neural networks and regularized logistic regression. We compared the multiomics test with one based on cfDNA methylation only. Results: This sub-study included 542 participants (AA: n = 122; colonoscopy-confirmed negative controls: n = 420). Participants with AA were 56% male with a mean age of 63 years, and colonoscopy-confirmed negative controls were 54% male with a mean age of 61 years. The multiomics test achieved a sensitivity of 41% (n = 50/122, 95% CI 34-48%) at 90% specificity (377/420). By contrast, the cfDNA methylation-only test achieved a sensitivity of 20% (24/122, 95% CI 15-25%) at 91% specificity (383/420). Performance was also analyzed by histological subtype and location, and superiority of the multiomics test to the cfDNA-methylation-only test was consistently observed. Conclusions: A novel multiomics blood test can detect colorectal AAs at a sensitivity and specificity comparable to existing stool-based tests. Combining signatures from both tumor- and immune-derived sources resulted in AA sensitivity greater than that of cfDNA-methylation alone.

Blood-based markers can be used to non-invasively predict cancer progression after treatment. Here, cell-free DNA (cfDNA) and plasma proteins were evaluated to explore biological signatures of progression in non-small cell lung cancer (NSCLC). Baseline plasma samples (n=24; 16 progressors, 8 non-progressors) were from patients diagnosed in 2004 with stage I-III NSCLC, collected prior to surgical resection, and retrospectively analyzed. Six patients were treated with neoadjuvant therapies, one with adjuvant therapy, and 17 with surgery alone. Progression was defined as a relapse event or death by any cause. Whole-genome sequencing was performed to characterize cfDNA fragments, which reflect nucleosome protection and chromatin state. Transcriptional activation for protein-coding genes was inferred by modeling fragment distribution around each transcription start site. Univariate comparisons of gene activation between progressors and non-progressors and Cox proportional hazard ratios (HRs) were calculated by grouping patients above or below the median of the marker of interest. This analysis revealed IL-1RN, the gene encoding for the IL-1RA antagonist to the IL-1 receptor complex, as the gene most negatively correlated with progression-free survival (PFS) (r = -0.76, p < 0.0001; Cox HR = 13.77, p < 0.001). This gene was also significantly more active in progressors than in non-progressors (p < 0.005). The binding activity of ~500 transcription factors was also inferred by measuring chromatin accessibility across the genome, revealing SOX-9 to be significantly associated with progression (p < 0.0001, FDR = 1.1%) and the factor most negatively correlated with PFS (r = -0.72, p < 0.001, FDR = 16.9%). Both IL-1RN and SOX-9 have been previously reported to affect survival in NSCLC patients.In addition, the abundances of ~450 proteins including cytokines, receptors, and enzymes were measured. Six proteins were identified as differentially abundant between progression groups. Among these, IL-1α was more abundant in progressors vs. non-progressors (effect size = 0.92, p < 0.05). Notably, IL-1RA abundance did not differ between these groups. Both IL-1α (r = -0.61, p < 0.01; Cox HR = 3.78, p < 0.05) and IL-1RA (r = -0.75, p < 0.001; Cox HR = 1.13, p = 0.78) were negatively correlated with PFS in progressors. Finally, all features and analytes were integrated to identify biological signatures that may be shared among proteins and cfDNA. These signatures differed significantly (p < 0.05) between progressors and non-progressors, suggesting differences in cytokine signaling. The multiomics platform described here integrates biological signals with computational featurization to reveal clinically relevant signatures. Specifically, findings from a small cohort of early-stage NSCLC patients demonstrated the potential of this platform to reveal signatures of progression in NSCLC. Citation Format: Francesco Vallania, Hayley Warsinske, Peter Ulz, Tzu-Yu Liu, Karen Assayag, Krishnan K. Palaniappan, Mitch Bailey, Irving Wang, David E. Weinberg, Riley Ennis, C Jimmy Lin, Anne-Marie Martin, Nancy Krunic. Multiomic plasma profiling identifies potential signatures of disease progression in early-stage NSCLC [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2433.

BackgroundBlood-based methods using cell-free DNA (cfDNA) are under development as an alternative to existing screening tests. However, early-stage detection of cancer using tumor-derived cfDNA has proven challenging because of the small proportion of cfDNA derived from tumor tissue in early-stage disease. A machine learning approach to discover signatures in cfDNA, potentially reflective of both tumor and non-tumor contributions, may represent a promising direction for the early detection of cancer.MethodsWhole-genome sequencing was performed on cfDNA extracted from plasma samples (N=546 colorectal cancer and 271 non-cancer controls). Reads aligning to protein-coding gene bodies were extracted, and read counts were normalized. cfDNA tumor fraction was estimated using IchorCNA. Machine learning models were trained using k-fold cross-validation and confounder-based cross-validation to assess generalization performance.ResultsIn a colorectal cancer cohort heavily weighted towards early-stage cancer (80% stage I/II), we achieved a mean AUC of 0.92 (95% CI 0.91-0.93) with a mean sensitivity of 85% (95% CI 83-86%) at 85% specificity. Sensitivity generally increased with tumor stage and increasing tumor fraction. Stratification by age, sequencing batch, and institution demonstrated the impact of these confounders and provided a more accurate assessment of generalization performance.ConclusionsA machine learning approach using cfDNA achieved high sensitivity and specificity in a large, predominantly early-stage, colorectal cancer cohort. The possibility of systematic technical and institution-specific biases warrants similar confounder analyses in other studies. Prospective validation of this machine learning method and evaluation of a multi-analyte approach are underway.

Figure S1. Performance of confounding variable in k-fold and target CV procedure (ROC curves) for: a) Age and binned-age CV b) Batch and k-batch CV c) Processing date and ordered k-batch CV d) Institution and balanced k-batch CV. Note that stratification CVs (i.e., binned-age, k-batch, and ordered k-batch) perform at chance (mean AUC of 0.50) when the distribution of labels in the test covariate is even and would result in an ROC that is just a diagonal line. The variance seen in some of the target procedures is due to class imbalance in the test data. (DOCX 420 kb)

Figure S2. Percentage of colorectal cancer samples by stage and non-cancer controls in each range of estimated TF (based on observed CNV using an IchorCNA-based estimate). (DOCX 74 kb)

Figure S3. IchorCNA-based estimated TF alone to predict case status (i.e., cancer or control) achieved an AUC of 0.67 in the IU age range, meaningfully lower than results from the ML model under any analyzed CV procedure. (DOCX 101 kb)

Figure S4. Non-linear relationship between the total number of samples used for training and sensitivity at 85% specificity for colorectal cancer detection. The method was trained again with k-fold, except the number of training samples per fold was downsampled. The lower numbers are comparable to those available for balanced k-batch and were used to investigate decreased classifier performance due to smaller sample sizes in training. (DOCX 60 kb)

Conjugation of multiple peptides by their N-termini is a promising technique to produce branched multiantigenic vaccines. We established a double conjugation strategy that combines a mercapto-acryloyl Michael addition and a copper-catalysed alkyne-azide 1,3-dipolar cycloaddition (CuAAC) reaction to synthesise self-adjuvanting branched multiantigenic vaccine candidates. These vaccine candidates aim to treat cervical cancer and include two HPV-16 derived epitopes and a novel self-adjuvanting moiety. This is the first report of mercapto-acryloyl conjugation applied to the hetero conjugation of two unprotected peptides by their N-termini followed by a CuAAC reaction to conjugate a novel synthetic lipoalkyne self-adjuvanting moiety. In vivo experiments showed that the most promising vaccine candidate completely eradicated tumours in 46% of the mice (6 out of 13 mice).

Human papillomaviruses (HPVs) are associated with various cancers, with HPV16 linked to more than half of cervical cancer cases. Vaccines to prevent HPV infection and cancer development have proven effective, but are not useful in individuals with prior HPV exposure. Treatment vaccines to eradicate or control HPV-associated lesions are therefore desirable for these patients. Herein we describe the development of a process to enable the production of semisynthetic vaccines based on the site-specific attachment of synthetic bacterial lipid analogs (e.g., Pam2Cys) to a non-oncogenic mutant HPV16 E7 protein to generate molecularly defined vaccines. Many cytotoxic lymphocyte (CTL) epitopes from E7 are delivered by this approach; potentially ensuring that large numbers of immunized individuals can generate CTLs to clear HPV infected cells. Delivery of this construct reduced the growth of HPV16-associated tumors in a TC1 mouse model, the effects of which were better than the potent CTL epitope HPV16 E7(44-57) administered with Montanide ISA51 adjuvant.

Glyoxalase 1 (GLO1) and HMG-CoA reductase (HMGCR) are highly expressed in most tumor cells and little in normal cells. In this study, treatment of HL-60 cells with lovastatin induced characteristic apoptosis in a dose-dependent manner. We demonstrated that lovastatin treatment inhibited Ras and Raf protein translocation to cell membrane and eliminated the phosphorylation of the downstream effectors Akt and ERK, and the subsequent NF-κB translocation into nucleus. Specific inhibitors and γ-tocotrienol confirmed the Ras/Raf/ERK/NF-κB/GLO1 and Ras/Akt/NF-κB/GLO1 pathways. Data revealed that lovastatin induced HL-60 cell death was attenuated by mevalonate treatment. We demonstrated also that γ-tocotrienol showed its apoptotic effect on the HL-60 cell through the same pathway. γ-Tocotrienol enhanced the apoptotic effect of lovastatin through the down-regulation of GLO1 and HMGCR resulting in an increase of methylglyoxal and a decrease of cholesterol and led to the apoptosis of HL-60 cells. Data also revealed that both lovastatin and gamma-tocotrienol induced significant HL-60 cell differentiation. These results suggest that both lovastatin and gamma-tocotrienol could induce differentiation and followed by apoptosis.

We designed learning activity in which language learning was combined with physical exercise. Our participants applied new knowledge to solve real life problems in their local community. Walking around the community during the learning activity enabled participants to be physically active. We provided students with smart watches to support their learning and monitor physical activities. We aimed to explore (1) whether our learning activity supported by smart watches can be useful for learning, make it healthy, and bring positive emotions to students.

International audience; Modern developments in light microscopy have allowed the observation of cell deformation with remarkable spatiotemporal resolution and reproducibility. Analyzing such phenomena is of particular interest for the signal processing and computer vision communities due to the numerous computational challenges involved, from image acquisition all the way to shape analysis and pattern recognition and interpretation. This article aims at providing an up-to-date overview of the problems, solutions, and remaining challenges in deciphering the morphology of living cells via computerized approaches, with a particular focus on shape description frameworks and their exploitation using machine-learning techniques. As a concrete illustration, we use our recently acquired data on amoeboid cell deformation, motivated by its direct implication in immune responses, bacterial invasion, and cancer metastasis.

Ribosome profiling is a widespread tool for studying translational dynamics in human cells. Its central assumption is that ribosome footprint density on a transcript quantitatively reflects protein synthesis. Here, we test this assumption using pulsed-SILAC (pSILAC) high-accuracy targeted proteomics. We focus on multiple myeloma cells exposed to bortezomib, a first-line chemotherapy and proteasome inhibitor. In the absence of drug effects, we found that direct measurement of protein synthesis by pSILAC correlated well with indirect measurement of synthesis from ribosome footprint density. This correlation, however, broke down under bortezomib-induced stress. By developing a statistical model integrating longitudinal proteomic and mRNA-sequencing measurements, we found that proteomics could directly detect global alterations in translational rate caused by bortezomib; these changes are not detectable by ribosomal profiling alone. Further, by incorporating pSILAC data into a gene expression model, we predict cell-stress specific proteome remodeling events. These results demonstrate that pSILAC provides an important complement to ribosome profiling in measuring proteome dynamics.

66 Background: Despite population screening efforts, screening rates for colorectal cancer (CRC) remain suboptimal. A non-invasive, blood-based screening test with high sensitivity and specificity in early-stage disease should improve adherence and ultimately reduce mortality; however, tests based only on tumor-derived biomarkers have limited sensitivity. Here we used a multiomic, machine learning platform to discover, refine, and combine tumor- and immune-derived signals to develop a blood test for the detection of early-stage CRC. Methods: Samples from 591 participants enrolled in a prospective study including average-risk screening and case-control cohorts (NCT03688906) were included in this analysis (CRC: n = 43; colonoscopy-confirmed CRC-negative controls: n = 548). Participants with CRC were 60% male with a mean age of 63, and controls were 55% male with a mean age of 60. Stage distribution was 54% early (I/II) and 34% late (III/IV) with 11% unknown. Plasma was analyzed by whole-genome sequencing, bisulfite sequencing, and protein quantification methods. Computational methods were used to assess and infer the performance of individual and combined assays. Results: For colorectal adenocarcinoma, which represents ~95% of all CRCs, our multiomic test achieved a mean sensitivity of 92% in early stage (n = 17) and 84% in late stage (n = 11) at a specificity of 90%. Across all CRC pathological subtypes, our test achieved a mean sensitivity of 80% in early stage (n = 19) and 83% in late stage (n = 12) at a specificity of 90%; the test detected the single squamous cell carcinoma but missed both neuroendocrine tumors. Individual assays achieved a mean sensitivity of 50% in early stage and 66% in late stage at a specificity of 90%. Conclusions: In a prospective cohort, we demonstrated high sensitivity and specificity for early-stage adenocarcinoma by combining tumor- and immune-derived signals from cfDNA, epigenetic, and protein biomarkers. While most CRCs are adenocarcinomas, detection of all pathological subtypes is required to maximize sensitivity in a screening population. Further analysis of molecular and pathological subtypes, as well as the entire ~3000 patient cohort, is underway. Clinical trial information: NCT03688906.

Vanadium is a rare chemical element and it primarily comes from the by-product of other minerals. In this study, the material source mainly comes from vanadium-rich aluminum slag. This experiment aims to separate vanadium and other impurities, such as aluminum and zirconium. First, the slag was dissolved in the sodium hydroxide solution at pH value 13, and part of the alumina was precipitated. After removing the precipitation, the strong acid cation exchange resin, Dowex® G26, was added to eliminate the remaining impurities. In this procedure, the parameter of reaction time, the mass of ion exchange resin and pH value were supplied. Moreover, the adsorption isotherms described by means of the Langmuir and Freundlich isotherms were used to investigate the ion-exchange behaviors of vanadium. To sum up, this study will provide the best conditions of ion exchange to get high purity about 95% of vanadate.

Vaccination can provide a safe alternative to chemotherapy by using the body's natural defense mechanisms to create a potent immune response against tumor cells. Peptide-based therapeutic vaccines against human papillomavirus (HPV)-related cancers are usually designed to elicit cytotoxic T cell responses by targeting the HPV-16 E7 oncoprotein. However, peptides alone lack immunogenicity, and an additional adjuvant or external delivery system is required. In this study, we developed new polymer-peptide conjugates to create an efficient self-adjuvanting system for peptide-based therapeutic vaccines. These conjugates reduced tumor growth and eradicated E7-positive TC-1 tumors in mice after a "single shot" immunization, without the help from an external adjuvant. The new conjugates had a significantly higher anticancer efficacy than the antigen formulated with a commercial adjuvant. Furthermore, the polymer-peptide conjugates were promptly taken up by antigen presenting cells, including dendritic cells and macrophages, and efficiently activated CD4(+) T-helper cells and CD8(+) cytotoxic T lymphocyte cells.

Three-dimensional chromatin organization varies across different cell types and is essential for gene regulation. Functional genomic elements that reside kilobases to megabases away can be brought into spatial proximity by chromatin folding. In fixed cells, DNA fluorescence in situ hybridization and super-resolution microscopy can measure the distances between loci at ~10-100nm resolution, while chromosome conformation capture followed by next-generation sequencing (Hi-C) is able to profile genome-wide chromatin organization at kilobase-pair level resolution by measuring contact probabilities between pairs of loci. These methods provide a static snapshot of genome compaction and organization in different cellular states. However, assessing in vivo genome-wide chromatin organization changes non-invasively and longitudinally in patients is challenging due to the limitations of current technologies. Recently, circulating cell-free DNA (cfDNA) in blood has been shown as a promising biomarker to capture the genetic and local epigenetic changes within patients. Here, we inferred in vivo chromatin organization in blood cells from co-fragmentation patterns of cfDNA by using fragment lengths estimated from paired-end whole genome sequencing (WGS). We performed cfDNA WGS on 100 healthy, 34 colorectal cancer, 48 lung cancer, and 19 melanoma patients. The inferred chromatin organization is highly concordant with Hi-C performed on white blood cells and not explained by technical biases, sequence composition, or other epigenetic factors. Further, we developed methods to identify the tissue-of-origin of cfDNA based on its co-fragmentation pattern and Hi-C signal in reference cell types, which confirmed that most cfDNA in healthy individuals is derived from hematopoietic cells. In cancer patients, we observed an increased contribution to cfDNA from cancer cells that was quantitatively correlated with estimated tumor fraction in cfDNA and qualitatively matched tumor type. We also verified the results using publicly available cfDNA WGS data from different healthy and cancer patients. These results are consistent with previous studies that directly measured DNA methylation or that inferred nucleosome positions from WGS on cfDNA. However, our method has distinct advantages including using only low-coverage WGS, not requiring bisulfite treatment, and providing a more robust and quantitative estimation of cell type contributions. Collectively, our results demonstrate the potential of using cfDNA WGS to non-invasively assess the in vivo three-dimensional chromatin organization and determine tissue-of-origin in different physiological and pathological conditions, which may be useful for detecting, monitoring and treating different diseases. Citation Format: Yaping Liu, Tzu-Yu Liu, David Weinberg, Chris J. De La Torre, Catherine L. Tan, Anthony D. Schmitt, Siddarth Selvaraj, Vy Tran, Louise C. Laurent, François-Clément Bidard, Imran S. Haque. Spatial co-fragmentation pattern of cell-free DNA recapitulates in vivo chromatin organization and identifies tissue-of-origin [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 5177.

The rapid, inducible, reversible modulation of molecular activities by dual CID systems. Rapamycin (Rapa) treatment induces relocation of FRB-POI to the GAIs-FKBP-C2(LACT)-labeled plasma membrane and activates POI-dependent signaling event. A subsequent GA3-AM treatment induces second relocation of a whole GAIs-FKBP-C2(LACT)/rapamycin/FRB-POI complex from the plasma membrane to the Tom20-GID1-labeled mitochondria and leads to termination of POI-dependent signaling.

SummaryMany small molecule chemotherapeutics induce stresses that globally inhibit mRNA translation, remodeling the cancer proteome and governing response to treatment. Here we measured protein synthesis in multiple myeloma cells treated with low-dose bortezomib by coupling pulsed-SILAC (pSILAC) with high-accuracy targeted quantitative proteomics. We found that direct measurement of protein synthesis by pSILAC correlated well with the indirect measurement of protein synthesis by ribosome profiling under conditions of robust translation. By developing a statistical model integrating longitudinal proteomic and mRNA-seq measurements, we found that proteomics could directly detect global alterations in translational rate as a function of therapy-induced stress after prolonged bortezomib exposure. Finally, the model we develop here, in combination with our experimental data including both protein synthesis and degradation, predicts changes in proteome remodeling under a variety of cellular perturbations. pSILAC therefore provides an important complement to ribosome profiling in directly measuring proteome dynamics under conditions of cellular stress.

Immunotherapy is one of the most promising strategies for the treatment of cancer. Human papillomavirus (HPV) is responsible for virtually all cases of cervical cancer. The main purpose of a therapeutic HPV vaccine is to stimulate CD8(+) cytotoxic T lymphocytes (CTLs) that can eradicate HPV infected cells. HPV oncoproteins E6 and E7 are continuously expressed and are essential for maintaining the growth of HPV-associated tumor cells. We designed polymer-based multi-antigenic formulations/constructs that were comprised of the E6 and E7 peptide epitopes. We developed an N-terminus-based epitope conjugation to conjugate two unprotected peptides to poly tert-butyl acrylate. This method allowed for the incorporation of the two antigens into a polymeric dendrimer in a strictly equimolar ratio. The most effective formulations eliminated tumors in up to 50% of treated mice. Tumor recurrence was not observed up to 3months post initial challenge.

The genetic, epigenetic, and physiological differences among cells in clonal microbial colonies are underexplored opportunities for discovery. A recently developed genetic assay reveals that transient losses of heterochromatic repression, a heritable form of gene silencing, occur throughout the growth of Saccharomyces colonies. This assay requires analyzing two-color fluorescence patterns in yeast colonies, which is qualitatively appealing but quantitatively challenging. In this paper, we developed a suite of automated image processing, visualization, and classification algorithms (MORPHE) that facilitated the analysis of heterochromatin dynamics in the context of colonial growth and that can be broadly adapted to many colony-based assays in Saccharomyces and other microbes. Using the features that were automatically extracted from fluorescence images, our classification method distinguished loss-of-silencing patterns between mutants and wild type with unprecedented precision. Application of MORPHE revealed subtle but significant differences in the stability of heterochromatic repression between various environmental conditions, revealed that haploid cells experienced higher rates of silencing loss than diploids, and uncovered the unexpected contribution of a sirtuin to heterochromatin dynamics.

This study used batch ozonation and O3/UV (ultraviolet) processes to investigate factors such as pH, ultraviolet, alkalinity, and humic acid that might affect the degradation and mineralization of mefenamic acid (MEF). The results show that ozonation and O3/UV processes were efficient in degrading MEF. A decrease of pH could enhance MEF removal by both the ozonation and O3/UV processes. Results also show that the presence of humic acid decreased the removal of MEF. In addition, the degradation of MEF could be expressed in a parallel first-order kinetic model, i.e., rapid and slow kinetic regimes, of the ozonation reaction. The simulation results show that both the fraction and rate constant of the rapid reaction increased as the pH value decreased, which is in agreement with the trend of the removal efficiency of MEF. Besides, the O3/UV process usually exhibits a higher γ, the ratio of residual MEF concentration through the rapid reaction to the slow reaction, than ozonation within just 10 min, which suggests that the rapid reaction could enhance the efficiency and effectiveness of degradation in the O3/UV process.

Attempts at depositing uniform films of nanoparticles by drop-drying have been frustrated by the "coffee-stain" effect due to convective macroscopic flow into the contact line. Here, we show that uniform deposition of nanoparticles in aqueous suspensions can be attained easily by drying the droplet in an ethanol vapor atmosphere. This technique allows the particle-laden water droplets to spread on a variety of surfaces such as glass, silicon, mica, PDMS, and even Teflon. Visualization of droplet shape and internal flow shows initial droplet spreading and strong recirculating flow during spreading and shrinkage. The initial spreading is due to a diminishing contact angle from the absorption of ethanol from the vapor at the contact line. During the drying phase, the vapor is saturated in ethanol, leading to preferential evaporation of water at the contact line. This generates a surface tension gradient that drives a strong recirculating flow and homogenizes the nanoparticle concentration. We show that this method can be used for depositing catalyst nanoparticles for the growth of single-walled carbon nanotubes as well as to manufacture plasmonic films of well-spaced, unaggregated gold nanoparticles.

The different transport pathways of 5-nm polymer-coated gold nanoparticles (Au NPs) crossing epithelial Caco-2 cell monolayers were explored. We found that the majority of cationic and neutral Au NPs depended heavily on endocytosis for cellular uptake and transport, and the anionic charged nanoparticles trafficked preferentially through the tight junctions (i.e., a paracellular pathway). The current study demonstrates that the surface chemistry of neutral polymer coatings dictate the trafficking through Caco-2 cell monolayers; poly(ethylene glycol)-coated Au NPs traffic via an endocytosis pathway assisted by microtubules; poly(2,3-hydroxy-propylacrylamide)-coated Au NPs traffic via endocytosis but assisted by other nonmicrotubular pathways. The Au NPs coated with poly( N -isopropylacrylamide) (hydrophobic above the lower critical solution temperature of 32°C) traffic via either the microtubule-assisted endocytosis pathway or the paracellular pathway depending on the temperature. This knowledge will aid in the future of the design of nanoparticles as potential oral drug carriers. From the Clinical Editor The authors examined different transport pathways of polymer-coated gold nanoparticles to cross epithelial Caco-2 cells, concluding that surface chemistry of neutral polymer coatings dictates the trafficking through monolayers.

We synthesized a library of polymer-coated gold nanoparticles (AuNPs) with well-defined sizes (5, 10, and 20 nm) and surface properties, and investigated their efficiency to cross the Caco-2 epithelial barrier and disrupt tight junctions connecting the cellular barrier. The positively charged and hydrophobic polymer-coated AuNPs showed little or no translocation across the model Caco-2 monolayer. Most of these positive and hydrophobic nanoparticles were either bound to the surface or internalized within the cell. The neutral and negatively charged polymer-coated AuNPs with a size of 5 nm showed a significantly higher translocation. All polymer-coated AuNPs induced the translocation of small molecules across the cellular monolayer, suggesting the loosening of the paracellular tight junction joining individual cells. The decrease in the TEER values of the monolayers supported the opening of the tight junctions. These tight junctions fully recovered for most polymer-coated AuNPs 12 h after removal of the nanoparticles. The exception was the cationic polymer-coated AuNPs in which the barrier function only recovered up to 62%. The library of polymer-coated AuNPs showed no apparent signs of hemolysis to erythrocytes at physiological pH. Our investigation has provided insight on the influence of polymer coatings on the epithelial barrier.