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Purpose: The purpose of this clinical focus article was to discuss the important relationship between executive function and language skills and to provide speech-language pathologists (SLPs) with strategies for promoting student success. Background and Method: The impact of executive function processes on language and literacy begins in the preschool years and becomes increasingly important from third grade onward. These executive function processes play a more dominant role when tasks require students to integrate and synthesize multiple linguistic and other subskills in order to read and comprehend, write, complete projects, and study for quizzes and tests. In this clinical focus article, we provide a brief overview of research-based executive function strategies that are beneficial for all learners and are essential for students with language weaknesses as well as learning and attention difficulties. We focus on the key executive function processes that are the foundation of academic performance, namely, goal setting, organizing and prioritizing, thinking and problem-solving flexibly, accessing information in working memory, and self-monitoring. We discuss a theoretical framework for understanding and promoting metacognition and executive function as part of assessment and treatment plans for SLPs. Finally, we address the importance of executive function strategies for improving students' effort, academic performance, and resilience. Conclusion: SLPs can promote student success by offering structured and systematic approaches to teaching executive function strategies.

We sought to evaluate the effectiveness of a novel Internal Medicine (IM) transition to residency (TTR) curriculum.We performed a paired pre-/postsurvey evaluation of graduating fourth-year medical students' perceived preparedness and medical knowledge after participating in a recently developed IM TTR course.The response rate was 51% (24 of 47). There was a significant improvement in 15 of 17 perceived preparedness items and significant improvement in the medical students' performance on the 8-question medical knowledge test.The IM TTR curriculum improved medical students' medical knowledge and perceived preparedness for internship on a variety of high-yield clinical topics. The curriculum may be appealing to other institutions that are developing or revamping TTR courses.

Gollop-Wolfgang complex is defined as the presence of a distal bifid femur and tibial hemimelia with or without hand ectrodactyly. The condition commonly presents with several skeletal abnormalities and internal organ congenital defects. We hereby report a case with a classical presentation of Gollop-Wolfgang complex.

OVERVIEW The following README contains: i) the raw count matrix relative to all nuclei of the dataset, called “filtered_feature_bc_matrix”; ii) the cell cycle genes lists (G2/M and S phase specific markers) named “cycle_gene”; iii) the markers gene lists used to generate the Dot Plots for the All_cells and Neuronal clustering (glial and neuronal markers); iv) the instruction to set up an R environment (R version 4.1.2) and to install R Studio on a Windows/macOS operative systems; iii) the instructions to install Seurat 3.2.3 along with all its dependencies; iv) the software code used to generate all the plots and figure as showed in the manuscript. SYSTEM REQUIREMENTS The following analysis can be performed on a standard computer with sufficient RAM to support the in-memory operation required by Seurat 3.2.3. The installation of Seurat 3.2.3 and all its dependencies have been tested on both Windows (version 10 64-bit ) and macOS (Big Sur version 11.6.1) operating systems. ALL PACKAGES and DEPENDENCIES R version 4.1.2 (2021-11-01) Platform: x86_64-apple-darwin17.0 (64-bit) Running under: macOS Monterey 12.2.1 Matrix products: default LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] dplyr_1.0.8 scales_1.1.1 RColorBrewer_1.1-2 viridis_0.6.2 viridisLite_0.4.0 ggplot2_3.3.5 Matrix_1.3-4 [8] biomaRt_2.50.3 Seurat_3.2.3 loaded via a namespace (and not attached): [1] BiocFileCache_2.2.1 plyr_1.8.6 igraph_1.2.11 lazyeval_0.2.2 splines_4.1.2 [6] listenv_0.8.0 scattermore_0.8 GenomeInfoDb_1.30.1 digest_0.6.29 htmltools_0.5.2 [11] fansi_1.0.2 magrittr_2.0.3 memoise_2.0.1 tensor_1.5 cluster_2.1.2 [16] ROCR_1.0-11 limma_3.50.1 remotes_2.4.2 globals_0.14.0 Biostrings_2.62.0 [21] matrixStats_0.61.0 prettyunits_1.1.1 colorspace_2.0-3 blob_1.2.2 rappdirs_0.3.3 [26] ggrepel_0.9.1 crayon_1.5.0 RCurl_1.98-1.6 jsonlite_1.8.0 spatstat_1.64-1 [31] spatstat.data_2.1-2 survival_3.2-13 zoo_1.8-9 glue_1.6.2 polyclip_1.10-0 [36] gtable_0.3.0 zlibbioc_1.40.0 XVector_0.34.0 leiden_0.3.9 future.apply_1.8.1 [41] BiocGenerics_0.40.0 abind_1.4-5 DBI_1.1.2 miniUI_0.1.1.1 Rcpp_1.0.8 [46] xtable_1.8-4 progress_1.2.2 reticulate_1.24 bit_4.0.4 rsvd_1.0.5 [51] stats4_4.1.2 htmlwidgets_1.5.4 httr_1.4.2 ellipsis_0.3.2 ica_1.0-2 [56] pkgconfig_2.0.3 XML_3.99-0.9 farver_2.1.0 uwot_0.1.11 dbplyr_2.1.1 [61] deldir_1.0-6 utf8_1.2.2 tidyselect_1.1.2 labeling_0.4.2 rlang_1.0.2 [66] reshape2_1.4.4 later_1.3.0 AnnotationDbi_1.56.2 munsell_0.5.0 tools_4.1.2 [71] cachem_1.0.6 cli_3.2.0 generics_0.1.2 RSQLite_2.2.10 pacman_0.5.1 [76] ggridges_0.5.3 stringr_1.4.0 fastmap_1.1.0 goftest_1.2-3 bit64_4.0.5 [81] fitdistrplus_1.1-6 purrr_0.3.4 RANN_2.6.1 KEGGREST_1.34.0 sceasy_0.0.6 [86] pbapply_1.5-0 future_1.24.0 nlme_3.1-153 mime_0.12 xml2_1.3.3 [91] compiler_4.1.2 rstudioapi_0.13 plotly_4.10.0 filelock_1.0.2 curl_4.3.2 [96] png_0.1-7 spatstat.utils_2.3-0 tibble_3.1.6 stringi_1.7.6 lattice_0.20-45 [101] vctrs_0.3.8 pillar_1.7.0 lifecycle_1.0.1 BiocManager_1.30.16 lmtest_0.9-39 [106] RcppAnnoy_0.0.19 data.table_1.14.2 cowplot_1.1.1 bitops_1.0-7 irlba_2.3.5 [111] httpuv_1.6.5 patchwork_1.1.1 R6_2.5.1 promises_1.2.0.1 KernSmooth_2.23-20 [116] gridExtra_2.3 IRanges_2.28.0 parallelly_1.30.0 codetools_0.2-18 MASS_7.3-54 [121] assertthat_0.2.1 withr_2.5.0 sctransform_0.3.3 S4Vectors_0.32.3 GenomeInfoDbData_1.2.7 [126] mgcv_1.8-38 parallel_4.1.2 hms_1.1.1 grid_4.1.2 rpart_4.1-15 [131] tidyr_1.2.0 Rtsne_0.15 Biobase_2.54.0 shiny_1.7.1 SOFTWARE INSTALLATION GUIDE 1. R version 4.1.2 for Windows and for macOS can be downloaded at: https://cran.rstudio.com/. 2. All packages used can be installed running the following command install.packages() from R console. 3. Seurat 3.2.3 and all its dependencies can be installed running the following command line: remotes::install_version("Seurat", version = "3.2.3"). 4. A typical installation time on a “normal” desktop computer is around 15-20 minutes. INSTRUCTION FOR USE/EXPECTED OUTPUT/EXPECTED RUN TIME All the instructions to install and run the code on the data provided in this folder are in the document “SCRIPT.txt”. The expected outputs of the code are: 1) “NEURONS_markers.csv”; 2) Figure 5;3) Supplementary Figure12. Expected run time is about 10 min for all the analyses.

With technological innovations happening at workplaces, 21st century organizations demand competencies in thinking creatively and critically. These two skills will potentially help prospective employees become confident individuals, concerned citizens, self-directed learners, and active professionals. In this context, it becomes imperative to overhaul the lecture-based and banking model of the traditional pedagogical approach in order to impart such skills among undergraduate and graduate students. To address this issue, a lab-based teaching-learning method focused on problem-solving and design thinking was introduced at OAMK Labs in Finland. This study assesses the efficacy of lab-based learning in enhancing creativity and critical thinking among students from engineering, management, and science backgrounds of Kathmandu University, Nepal. The study was conducted in a workshop setting using a randomized control trial (RCT) where participants were divided into control and treatment groups. Participants in treatment group took part in a design thinking workshop that applied lab-based learning pedagogy, while those in the control group were given some reading material on improving creativity and critical thinking. Standard tests on both critical and creative thinking in a pre- and post-stages were administered to both groups. Data was analyzed using standard Difference-in-Differences technique. The results showed that while the level of critical thinking improved significantly, among the learners in treatment group alone, the creativity level in the post-stage increased significantly among learners in both groups. Results validated the efficacy of lab-based teaching-learning in addressing the need for critical and creative thinking skills among learners. Keywords: critical thinking, creativity, lab based learning, innovation, higher education, Difference-in-Differences

In the last decade, boot camp residency preparatory courses for fourth-year medical students have become increasingly popular in medical schools across the USA; however, the curricular content of these courses varies widely. The authors surveyed internal medicine interns at a large academic medical center regarding clinical and non-clinical topics that would be useful for an internal medicine residency preparatory curriculum. The response rate was 79% (64/81). A rational approach to antibiotics (42%) and electrolyte management (41%) were the most frequent clinical topics and cross-cover (69%) was the most frequent non-clinical topic selected by interns.

We describe a cohort of 25 Iranian patients with infantile inflammatory bowel disease (IBD), 14 (56%) of whom had monogenic defects. After proper screening, patients were referred for whole exome sequencing (WES). Four patients had missense mutations in the

The Lab's Quarterly, XXIV(1), 33-48