Assessing Students’ Approaches and Perceptions to Learning in Physics Experiments Based on Simulations and At-Home Lab Kits

Our study evaluates students’ approaches to and perceptions of the use of hands-on at-home laboratory kits (HALK) experiments, open-source computer-based simulations (OSCBS), and their combination (OSCBS-HALK) in undergraduate introductory asynchronous online physics courses. Anonymous survey data from students who had completed online physics courses with labs based on simulations, at-home lab kits, or both were collected using a modified version of the Learn Questionnaire (MVLQ). Findings in this study indicate that among the six scales (interest and relevance; peer support; staff enthusiasm and support; teaching for understanding; alignment; and constructive feedback) used to measure students’ perceptions of the teaching and learning environments, interest and relevance, peer support, and teaching for understanding had statistically significant different means across the three lab types. Post-hoc comparisons using the Tukey HSD test for the interest and relevance scale indicated that students viewed using a combination approach of OSCBS and HALK labs (M = 3.98, SD = 0.61) more significantly positive than using computer-simulated labs only (M = 3.56, SD = 0.75). Compared to other labs, computer-simulated labs were perceived to lead to a deep approach to learning. However, they had the lowest interest and relevance, peer support, and alignment ranking among the three lab groups. Thus, developing strategies to improve students’ engagement and ability to translate the simulations into physical processes is recommended for OSCBS.

Identification and Characterization of the Detoxification Genes Based on the Transcriptome of Tomicus yunnanensis

Bark beetle, as a trunk borer, has caused a large number of tree deaths and seriously damaged the mountain forest ecosystem. Bark beetles oxidize the secondary metabolites of plants, degrade them, and excrete them from the body or convert them into components needed by the body. This process is completed by the cooperation of CYPs, GSTs, and CCEs and occurs in different tissues of the insects, including the gut (i.e., the part where beetle pheromone is produced and accumulated) and antennae (i.e., the olfactory organ used to sense defensive monoterpenes and other plant-related compounds and pheromones in the air). In this study, we identified and characterized three gene superfamilies of CYPs, GSTs, and CCEs involved in the detoxification of endobiotics (e.g., hormones and steroids) and xenobiotics (e.g., insecticides, sex pheromones, and plant allelochemicals) through a combination approach of bioinformatics, phylogenetics, and expression profiles. Transcriptome analyses led to the identification of 113 transcripts encoding 51 P450s, 33 GSTs, and 29 CCEs from Tomicus yunnanensis Kirkendall and Faccoli, 2008 (Coleoptera, Scolytinae). The P450s of T. yunnanensis were phylogenetically classified into four clades, representing the majority of the genes in the CYP3 clan. The CCEs from T. yunnanensis were separately grouped into five clades, and the GST superfamily was assigned to five clades. Expression profiles revealed that the detoxification genes were broadly expressed in various tissues as an implication of functional diversities. Our current study has complemented the resources for the detoxification genes in the family Coleoptera and allows for functional experiments to identify candidate molecular targets involved in degrading plants’ secondary metabolites, providing a theoretical basis for insect resistance in mixed forests.

Optimal Tests for Combining p-Values

Combining information (p-values) obtained from individual studies to test whether there is an overall effect is an important task in statistical data analysis. Many classical statistical tests, such as chi-square tests, can be viewed as being a p-value combination approach. It remains challenging to find powerful methods to combine p-values obtained from various sources. In this paper, we study a class of p-value combination methods based on gamma distribution. We show that this class of tests is optimal under certain conditions and several existing popular methods are equivalent to its special cases. An asymptotically and uniformly most powerful p-value combination test based on constrained likelihood ratio test is then studied. Numeric results from simulation study and real data examples demonstrate that the proposed tests are robust and powerful under many conditions. They have potential broad applications in statistical inference.

Forecasting Sugarcane Yield of India based on rough set combination approach

This study applied a novel rough set combination approach for forecasting sugarcane production in India. The paper uses autoregressive integrated moving average (ARIMA), double exponential smoothing (DES) and Grey model (GM) to generate the single forecasts. Also, the weight coefficient is evaluated by underlying the rough set approach to combine the single forecasts obtained from different models. To validate our proposed analysis, Sugarcane from 1950 to 2011 was used for the overall empirical analysis and generate out-sample forecasts from 2012 to 2021 for the comparative analysis. Also, ARIMA (2, 1, 1) model is found more appropriate for forecasting Sugarcane production.

A Combination Approach in Inhibiting Type 2 Diabetes-Related Enzymes Using Ecklonia radiata Fucoidan and Acarbose

Although there are chemotherapeutic efforts in place for Type 2 diabetes mellitus (T2DM), there is a need for novel strategies (including natural products) to manage T2DM. Fucoidan, a sulphated polysaccharide was extracted from Ecklonia radiata. The integrity of the fucoidan was confirmed by structural analysis techniques such as FT-IR, NMR and TGA. In addition, the fucoidan was chemically characterised and tested for cell toxicity. The fucoidan was investigated with regards to its potential to inhibit α-amylase and α-glucosidase. The fucoidan was not cytotoxic and inhibited α-glucosidase (IC50 19 µg/mL) more strongly than the standard commercial drug acarbose (IC50 332 µg/mL). However, the fucoidan lacked potency against α-amylase. On the other hand, acarbose was a more potent inhibitor of α-amylase (IC50 of 109 µg/mL) than α-glucosidase. Due to side effects associated with the use of acarbose, a combination approach using acarbose and fucoidan was investigated. The combination showed synergistic inhibition (>70%) of α-glucosidase compared to when the drugs were used alone. The medicinal implication of this synergism is that a regimen with a reduced acarbose dose may be used, thus minimising side effects to the patient, while achieving the desired therapeutic effect for managing T2DM.

DDRE-01. CDK PATHWAY INHIBITION WITH ABEMACICLIB IMPROVES INTRACRANIAL AND EXTRACRANIAL RESPONSE TO CHECKPOINT BLOCKADE IN PRE-CLINICAL MODELS OF MELANOMA BRAIN METASTASIS

While immune checkpoint inhibitors (ICI) have revolutionized treatment of metastatic melanoma, few of the 75% of patients who develop brain metastases benefit from immunotherapy. Inhibition of CDK4/6 pathway – altered in ~90% of melanoma patients – can reportedly increase tumor inflammation and sensitize extracranial tumors to ICI. To determine whether intracranial melanoma can be similarly sensitized, we studied efficacy of combination CDK4/6 inhibitor Abemaciclib and ICI in immunocompetent mouse models of melanoma brain metastases bearing concurrent intracranial and extracranial tumors. 8-week-old female C57BL/6 mice received subcutaneous injections of 2x105 YUMM1.7 or B16-F10 melanoma cells 3 days prior to intracranial injections of 5x104 YUMM1.7 cells or 5x103 B16-F10 cells respectively. Mice were randomized into 6 treatment groups (n=5-7/group): Abemaciclib alone, anti-PD-1 monotherapy, anti-PD-1 and anti-CTLA4 combined (combination ICI), Abemaciclib and anti-PD-1, Abemaciclib combined with anti-PD-1 and anti-CTLA4 (triple therapy), and treatment with vehicle and isotype-matched antibodies as control. In mice bearing YUMM1.7 tumors, subcutaneous tumor growth was significantly reduced compared to control in mice treated with Abemaciclib alone (p< 0.05), combination ICI (p< 0.05) and triple therapy (p< 0.05). However, improvement in survival was only observed with triple therapy (p=0.039) compared to control group. In mice bearing B16-F10 tumors, we observed striking reduction in subcutaneous tumor growth in mice treated with Abemaciclib and anti-PD-1 compared to control-treated mice (p=0.0016) or to mice receiving anti-PD-1 monotherapy (p=0.000056). This further corresponded to a significant increase in survival of Abemaciclib and anti-PD-1 treated mice compared to control (p=0.02). Additionally, we observed improved survival in mice treated with combination ICI (p=0.006) or triple therapy (p=0.01). These results indicate CDK4/6 inhibition with Abemaciclib can improve both extracranial and intracranial responses to ICI and sensitize melanoma brain metastases to immunotherapy. Our pre-clinical findings warrant further investigation to determine whether this combination approach can improve patient outcomes.

Maximizing cancer therapy via complementary mechanisms of immune activation: PD-1 blockade, neoantigen vaccination, and Tregs depletion

BackgroundA number of different immune pathways are involved in the effective killing of cancer cells, collectively named as the ‘Cancer Immunity Cycle’. Anti-PD-1 checkpoint blockade (CPB) therapy is active on one of these pathways and reinvigorates anticancer T cell immunity, leading to long-term responses in a limited fraction of patients with cancer. We have previously shown that neoantigens-based adenovirus vectored vaccine in combination with anti-PD-1 further expands pre-existing anticancer immunity and elicits novel neoantigen-specific T cells thereby increasing efficacy to 50% of tumor clearance in mice. Here we added a third component to the CPB plus vaccine combination, which is able to modify the suppressive tumor microenvironment by reducing the number of tumor-infiltrating regulatory T cells (Tregs), as strategy for improving the therapeutic efficacy and overcoming resistance.MethodsThe antitumor efficacy of anti-PD-1, neoantigen vaccine and Treg modulating agents, either Bempegaldesleukin (BEMPEG: NKTR-214) or an anti-CTLA-4 mAb with Treg-depleting activity, was investigated in murine tumor models. We evaluated tumor growth in treated animals, neoantigen-specific T cells in tumors, tumor-infiltrating lymphocytes (TILs) and intratumoral Tregs.ResultsThe addition of BEMPEG or anti-CTLA-4 to the combination of vaccine and anti-PD-1 led to complete eradication of large tumors in nearby 100% of treated animals, in association with expansion and activation of cancer neoantigen-specific T cells and reduction of tumor-infiltrating Tregs.ConclusionThese data support the notion that the integrated regulation of three steps of the cancer immunity cycle, including expansion of neoantigen-specific T cells, reversal of the exhausted T cell phenotype together with the reduction of intratumoral Tregs may represent a novel rationally designed drug combination approach to achieve higher cure rates.

PARP Inhibitors in Combination with Radiotherapy: To Do or Not to Do?

Background: Despite the large use of inhibitors of Poly-ADP ribose polymerase (PARP-I), the feasibility and safety of their combination with radiotherapy (RT) is unclear. Aim: We conducted a literature analysis with the aim to evaluate the efficacy and safety profile of a combination with RT and PARP-I. Method: The key issues for the current review were expressed in two questions according to the Population, Intervention, Control, Outcome (PICO) criteria: 1. What is the outcome and 2. What is the toxicity in patients treated with a combination of PARP-I and RT for a newly diagnosed or recurrent tumors? Results: A total of 12 clinical studies met the inclusion criteria including seven single-arm dose-escalation phase I studies, two phase II (two- and three-arms controlled trials) trials, one parallel-arm phase I study, and two phase I/II studies published between 2015 and 2021. RT was performed with photon beams and several schedules according to the clinical situation. The acute toxicity ≥ grade 3 ranged between 25% and >96%, which was divided into hematological or non-hematological adverse events. Conclusions: despite the heterogeneity of the evaluated patient populations and tumor types, and the limited number of the studies, this review suggests that a combination approach is feasible even though the efficacy profile remains unclear.

Multi-modal program inference: a marriage of pre-trained language models and component-based synthesis

Multi-modal program synthesis refers to the task of synthesizing programs (code) from their specification given in different forms, such as a combination of natural language and examples. Examples provide a precise but incomplete specification, and natural language provides an ambiguous but more "complete" task description. Machine-learned pre-trained models (PTMs) are adept at handling ambiguous natural language, but struggle with generating syntactically and semantically precise code. Program synthesis techniques can generate correct code, often even from incomplete but precise specifications, such as examples, but they are unable to work with the ambiguity of natural languages. We present an approach that combines PTMs with component-based synthesis (CBS): PTMs are used to generate candidates programs from the natural language description of the task, which are then used to guide the CBS procedure to find the program that matches the precise examples-based specification. We use our combination approach to instantiate multi-modal synthesis systems for two programming domains: the domain of regular expressions and the domain of CSS selectors. Our evaluation demonstrates the effectiveness of our domain-agnostic approach in comparison to a state-of-the-art specialized system, and the generality of our approach in providing multi-modal program synthesis from natural language and examples in different programming domains.