Privacy-preserving Quantile Treatment Effect Estimation for Randomized Controlled Trials

In accordance with the principle of "data minimization", many internet companies are opting to record less data. However, this is often at odds with A/B testing efficacy. For experiments with units with multiple observations, one popular data minimizing technique is to aggregate data for each unit. However, exact quantile estimation requires the full observation-level data. In this paper, we develop a method for approximate Quantile Treatment Effect (QTE) analysis using histogram aggregation. In addition, we can also achieve formal privacy guarantees using differential privacy.Comment: Accepted to 2023 CODE conference as a parallel presentatio

Semi-active control system for magneto-rheological damper based on the identification model with fuzzy neural network

Semi-active suspensions that dissipate energy through controllable dampers have been used in trains, tractors and off-road vehicles in the last decades. Magneto-rheological (MR) fluids have been widely applied as a new material in the field of vibration control. Magneto-rheological (MR) damper is an extremely ideal semi-active control device compared with traditional semi-active damping control device for its superiorities of rapid response (in millisecond), far less response time than sampling time, and almost no time lag caused by the control devices. However, its complicated dynamic hysteresis characteristics vary with the currents imposed on it, resulting in the difficulty in establishing the mathematical model which can truly describe its dynamic behavior. Besides, an effective and precision mathematical model can be of help for constructing the semi-active control law. In this paper, the system identification method based on the theory of fuzzy neural network (FNN) is employed to identify the mathematical model that can accurately reflect the dynamic hysteresis characteristics of magneto-rheological (MR) damper. Under the semi-active control law, the structure on the damper can be stabilized at the fastest rate with an optimal current calculated by the identified mathematical model imposed on magneto-rheological (MR) damper. Consequently, vibration reduction can be effectively realized

Characterization of the rainbow trout transcriptome using Sanger and 454-pyrosequencing approaches

<p>Abstract</p> <p>Background</p> <p>Rainbow trout are important fish for aquaculture and recreational fisheries and serves as a model species for research investigations associated with carcinogenesis, comparative immunology, toxicology and evolutionary biology. However, to date there is no genome reference sequence to facilitate the development of molecular technologies that utilize high-throughput characterizations of gene expression and genetic variation. Alternatively, transcriptome sequencing is a rapid and efficient means for gene discovery and genetic marker development. Although a large number (258,973) of EST sequences are publicly available, the nature of rainbow trout duplicated genome hinders assembly and complicates annotation.</p> <p>Results</p> <p>High-throughput deep sequencing of the Swanson rainbow trout doubled-haploid transcriptome using 454-pyrosequencing technology yielded ~1.3 million reads with an average length of 344 bp, a total of 447 million bases. <it>De novo </it>assembly of the sequences yielded 151,847 Tentative Consensus (TC) sequences (average length of 662 bp) and 224,391 singletons. A combination assembly of both the 454-pyrosequencing ESTs and the pre-existing sequences resulted in 161,818 TCs (average length of 758 bp) and 261,071 singletons. Gene Ontology analysis of the combination assembly showed high similarities to transcriptomes of other fish species with known genome sequences.</p> <p>Conclusion</p> <p>The 454 library significantly increased the suite of ESTs available for rainbow trout, allowing improved assembly and annotation of the transcriptome. Furthermore, the 454 sequencing enables functional genome research in rainbow trout, providing a wealth of sequence data to serve as a reference transcriptome for future studies including identification of paralogous sequences and/or allelic variation, digital gene expression and proteomic research.</p

Self-supervised Video Representation Learning with Motion-Aware Masked Autoencoders

Masked autoencoders (MAEs) have emerged recently as art self-supervised spatiotemporal representation learners. Inheriting from the image counterparts, however, existing video MAEs still focus largely on static appearance learning whilst are limited in learning dynamic temporal information hence less effective for video downstream tasks. To resolve this drawback, in this work we present a motion-aware variant -- MotionMAE. Apart from learning to reconstruct individual masked patches of video frames, our model is designed to additionally predict the corresponding motion structure information over time. This motion information is available at the temporal difference of nearby frames. As a result, our model can extract effectively both static appearance and dynamic motion spontaneously, leading to superior spatiotemporal representation learning capability. Extensive experiments show that our MotionMAE outperforms significantly both supervised learning baseline and state-of-the-art MAE alternatives, under both domain-specific and domain-generic pretraining-then-finetuning settings. In particular, when using ViT-B as the backbone our MotionMAE surpasses the prior art model by a margin of 1.2% on Something-Something V2 and 3.2% on UCF101 in domain-specific pretraining setting. Encouragingly, it also surpasses the competing MAEs by a large margin of over 3% on the challenging video object segmentation task. The code is available at https://github.com/happy-hsy/MotionMAE.Comment: 17 pages, 6 figure

Selected cutaneous adverse events in patients treated with ICI monotherapy and combination therapy: a retrospective pharmacovigilance study and meta-analysis

Introduction: Cutaneous adverse events are commonly reported immune-related adverse events (irAEs), some of which are serious or even life-threatening, and it is essential to study these specific cutaneous AEs to understand their characteristics and risk.Methods: We performed a meta-analysis of published clinical trials for immune checkpoint inhibitors (ICIs) to evaluate the incidence of cutaneous adverse events, using data from PubMed, Embase, and the Cochrane Library databases.Results: A total of 232 trials with 45,472 patients were involved. Results showed that anti-PD-1 and targeted therapy combinations were associated with higher risk for most of the selected cutaneous adverse events. In addition, a retrospective pharmacovigilance study was conducted using the Food and Drug Administration (FDA) Adverse Events System database. Reporting odds ratio (ROR) and Bayesian information components (IC) were used to perform the disproportionality analysis. Cases were extracted from January 2011 to September 2020. We identified 381 (20.24%) maculopapular rash, 213 (11.32%) vitiligo, 215 (11.42%) Stevens‐Johnson syndrome (SJS), and 165 (8.77%) toxic epidermal necrolysis (TEN) cases. For vitiligo, anti-PD-1/L1 combined with anti-CTLA-4 therapy showed the strongest signal (ROR: 55.89; 95% CI: 42.34–73.78; IC025: 4.73). Palmar-plantar erythrodysesthesia (PPE) was reported with the most significant association with combined anti-PD-1/L1 and VEGF (R)-TKIs (ROR: 18.67; 95% CI: 14.77–23.60; IC025: 3.67). For SJS/TEN, antiPD-1 inhibitors showed the strongest signal (ROR: 3.07; 95% CI: 2.68–3.52; IC025: 1.39). The median onset time of vitiligo and SJS/TEN was 83 and 24 days, respectively.Conclusion: Overall, in selected cutaneous AEs, each of them showed specific characteristics. It is necessary to realize their differences and take appropriate interventions in patients with different regimens

Cognitive impairment in diffuse axonal injury patients with favorable outcome

Background and purposeTraumatic brain injury (TBI), especially the severe TBI are often followed by persistent cognitive sequalae, including decision-making difficulties, reduced neural processing speed and memory deficits. Diffuse axonal injury (DAI) is classified as one of the severe types of TBI. Part of DAI patients are marginalized from social life due to cognitive impairment, even if they are rated as favorable outcome. The purpose of this study was to elucidate the specific type and severity of cognitive impairment in DAI patients with favorable outcome.MethodsThe neurocognition of 46 DAI patients with favorable outcome was evaluated by the Chinese version of the Montreal Cognitive Assessment Basic (MoCA-BC), and the differences in the domains of cognitive impairment caused by different grades of DAI were analyzed after data conversion of scores of nine cognitive domains of MoCA-BC by Pearson correlation analysis.ResultsAmong the 46 DAI patients with favorable outcome, eight had normal cognitive function (MoCA-BC ≥ 26), and 38 had cognitive impairment (MoCA-BC &lt; 26). The MoCA-BC scores were positively correlated with pupillary light reflex (r = 0.361, p = 0.014), admission Glasgow Coma Scale (GCS) (r = 0.402, p = 0.006), and years of education (r = 0.581, p &lt; 0.001). Return of consciousness (r = −0.753, p &lt; 0.001), Marshall CT (r = −0.328, p = 0.026), age (r = −0.654, p &lt; 0.001), and DAI grade (r = −0.403, p = 0.006) were found to be negatively correlated with the MoCA-BC scores. In patients with DAI grade 1, the actually deducted scores (Ads) of memory (r = 0.838, p &lt; 0.001), abstraction (r = 0.843, p &lt; 0.001), and calculation (r = 0.782, p &lt; 0.001) were most related to the Ads of MoCA-BC. The Ads of nine cognitive domains and MoCA-BC were all proved to be correlated, among patients with DAI grade 2. However, In the DAI grade 3 patients, the highest correlation with the Ads of MoCA-BC were the Ads of memory (r = 0.904, p &lt; 0.001), calculation (r = 0.799, p = 0.006), orientation (r = 0.801, p = 0.005), and executive function (r = 0.869, p = 0.001).ConclusionDAI patients with favorable outcome may still be plagued by cognitive impairment, and different grades of DAI cause different domains of cognitive impairment

Deciphering the role of apoptosis signature on the immune dynamics and therapeutic prognosis in breast cancer: Implication for immunotherapy

Background: In breast cancer oncogenesis, the precise role of cell apoptosis holds untapped potential for prognostic and therapeutic insights. Thus, it is important to develop a model predicated for breast cancer patients’ prognosis and immunotherapy response based on apoptosis-related signature.Methods: Our approach involved leveraging a training dataset from The Cancer Genome Atlas (TCGA) to construct an apoptosis-related gene prognostic model. The model’s validity was then tested across several cohorts, including METABRIC, Sun Yat-sen Memorial Hospital Sun Yat-sen University (SYSMH), and IMvigor210, to ensure its applicability and robustness across different patient demographics and treatment scenarios. Furthermore, we utilized Quantitative Polymerase Chain Reaction (qPCR) analysis to explore the expression patterns of these model genes in breast cancer cell lines compared to immortalized mammary epithelial cell lines, aiming to confirm their differential expression and underline their significance in the context of breast cancer.Results: Through the development and validation of our prognostic model based on seven apoptosis-related genes, we have demonstrated its substantial predictive power for the survival outcomes of breast cancer patients. The model effectively stratified patients into high and low-risk categories, with high-risk patients showing significantly poorer overall survival in the training cohort and across all validation cohorts. Importantly, qPCR analysis confirmed that the genes constituting our model indeed exhibit differential expression in breast cancer cell lines when contrasted with immortalized mammary epithelial cell lines.Conclusion: Our study establishes a groundbreaking prognostic model using apoptosis-related genes to enhance the precision of breast cancer prognosis and treatment, particularly in predicting immunotherapy response

RAS/BRAF Circulating Tumor DNA Mutations as a Predictor of Response to First-Line Chemotherapy in Metastatic Colorectal Cancer Patients

Background. Since circulating tumor DNA (ctDNA) offers clear advantages as a minimally invasive method for tumor monitoring compared with tumor tissue, we aimed to evaluate genotyping ctDNA using a next-generation sequencing- (NGS-) based panel to identify the prognostic value of mutation status in metastatic colorectal cancer (mCRC) patients with primary tumor resected and with subsequent lines of treatment in this study. Methods. 76 mCRC patients treated in Beijing Chao-Yang Hospital from 2011 to 2017 were enrolled. Genotyping of RAS/BRAF in tumor tissue and ctDNA was determined by ARMS PCR and with a 40-gene panel using NGS, respectively. Patient clinicopathologic features and RAS/BRAF gene mutation status were evaluated by survival analysis for disease-free survival (DFS) and progression-free survival (PFS). Results. Among 76 patients, KRAS distributions were not significantly correlated with any clinicopathologic features. The concordance between tumor tissue and ctDNA KRAS mutation was 81.25%. Mutations of RAS/BRAF had no significant impact on DFS after surgery (hazard ratio (HR), 1.205; 95% CI, 0.618 to 2.349; P=0.5837) but prognosticated poorer PFS in subsequent first-line therapy (HR, 3.351; 95% CI, 1.172 to 9.576; P=0.024). Conclusion. ctDNA was comparable with tumor tissue for mutation detection. RAS/BRAF mutations detected in ctDNA predict a worse PFS in mCRC patients with first-line chemotherapy. Our results provide support for the prognostic value of RAS/BRAF ctDNA mutation detection in mCRC patients

The draft genomes of soft­shell turtle and green sea turtle yield insights into the development and evolution of the turtle­ specific body plan

The unique anatomical features of turtles have raised unanswered questions about the origin of their unique body plan. We generated and analyzed draft genomes of the softshell turtle (Pelodiscus sinensis) and the green sea turtle (Chelonia mydas); our results indicated the close relationship of the turtles to the bird-crocodilian lineage, from which they split ~267.9–248.3 million years ago (Upper Permian to Triassic). We also found extensive expansion of olfactory receptor genes in these turtles. Embryonic gene expression analysis identified an hourglass-like divergence of turtle and chicken embryogenesis, with maximal conservation around the vertebrate phylotypic period, rather than at later stages that show the amniotecommon pattern. Wnt5a expression was found in the growth zone of the dorsal shell, supporting the possible co-option of limb-associated Wnt signaling in the acquisition of this turtlespecific novelty. Our results suggest that turtle evolution was accompanied by an unexpectedly conservative vertebrate phylotypic period, followed by turtle-specific repatterning of development to yield the novel structure of the shell