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The aim of this study is to determine the impact of the COVID-19 pandemic on an independent restaurant chain in Puebla, Mexico, through longitudinal censuses with employees who had direct contact with diner guests (frontline employees) in 2019 and 2023. The survey data was analyzed through the algorithm Synthetic Minority Over-sampling Technique (SMOTE) to balance sample sizes and Information Gain to determine the dependence between the study variables. The results revealed the health crisis has led to changes in pivotal factors that drove better performance from frontline employees and managers in restaurants in Mexico. After the pandemic, frontline employees began to favor standard compliance due to the reinforcement of hygiene protocols. However, there are implications for the structure of teams and work styles on account of the decline in the number of frontline employees and the creation of multifunctional positions. Regarding the manager's factors, Linear Communication, which consists of providing clear and timely information, has become more relevant. While, there has been a decrease in Dynamic Communication oriented towards dialogue and Productive Communication focused on participation and the achievement of objectives. COVID-19 has accentuated the vulnerability of female frontline employees, who, since the pandemic, occupy multifunctional positions; the number of employees has decreased in greater proportion than the number of restaurants that have closed, impacting team dynamics; the most affected restaurants are located in automotive industrial parks, while restaurants in tourist or commercial areas have managed to maintain their workforce. The selected independent restaurant chain has focused on the functional aspects of the restaurant, as denoted by their current transactional leadership style and hierarchical organizational culture. However, there is an important theoretical implication related to the post-pandemic context, characterized by the presence of multifunctional roles and the pressure to meet customer service standards. Frontline employees have adopted individualistic behaviors, negatively impacting collaborative teamwork. These finding challenges existing literature that often emphasizes the positive aspects of employee empowerment and multifunctionality; it suggests that, under certain conditions, these factors may inadvertently hinder team cohesion and collaborative efforts. This study highlights the need to capitalize on Mexican restaurants by not only valuing the strategies from senior management but also by incorporating interpersonal perspectives from frontline employees to improve the organization in procedural and relational terms to adapt to future crises. Doi: 10.28991/ESJ-2024-08-05-021 Full Text: PDF

With a growing number of predictive biomarkers needed to manage patients with non-small cell lung cancer (NSCLC), there has been a paradigm shift in care and handling of diagnostic samples. Among the various testing methods, immunohistochemistry (IHC) is the most cost- effective and widely available. Furthermore, over the past decade immunotherapy has emerged as one of the most promising cancer treatments. In this scenario IHC is the most used testing method available for PDL-1/PD1 immunotherapy. Several monoclonal antibodies targeting programmed death 1 (PD-1)/programmed death ligand-1 (PD-L1) pathways have been integrated into standard-of-care treatments of a wide range of cancer types, once provided evidence of PD-L1 expression in tumor cells by immunohistochemistry (IHC). Since currently available PD-L1 assays have been developed on formalin-fixed paraffin embedded (FFPE) histological specimens, a growing body of research is being dedicated to confirm the feasibility of applying PDL-1 assays also to cytological samples. Albeit promising results have been reported, several important issues still need to be addressed. Among these are the type of cytological samples, pre-analytical issues, cyto-histological correlation, and inter-observer agreement. This review briefly summarizes the knowledge of the role of cytopathology in the analysis of PD-L1 by immunocytochemistry (ICC) and future directions of cytopathology in the immunotherapy setting.

Over the past decade, molecular cytopathology has emerged as a relevant area of modern pathology. Notably, in patients with advanced-stage cancer, cytological samples could be the only material available for diagnosis and molecular biomarker testing to identify patients suitable for targeted therapies. As a result, the contemporary cytopathologist’s role extends beyond morphological assessments to include critical skills such as evaluating the adequacy of the cytological samples and managing these specimens for molecular testing. This case collection can be a valuable source of insight, especially for young pathologists, who should learn to combine the opportunities offered by molecular biology with the basis of morphological evaluation.

Abstract Predicting recurrence in low-grade, early-stage endometrial cancer (EC) is both challenging and clinically relevant. We present a weakly-supervised deep learning framework, NaroNet, that can learn, without manual expert annotation, the complex tumor-immune interrelations at three levels: local phenotypes, cellular neighborhoods, and tissue areas. It uses multiplexed immunofluorescence for the simultaneous visualization and quantification of CD68 + macrophages, CD8 + T cells, FOXP3 + regulatory T cells, PD-L1/PD-1 protein expression, and tumor cells. We used 489 tumor cores from 250 patients to train a multilevel deep-learning model to predict tumor recurrence. Using a tenfold cross-validation strategy, our model achieved an area under the curve of 0.90 with a 95% confidence interval of 0.83–0.95. Our model predictions resulted in concordance for 96,8% of cases (κ = 0.88). This method could accurately assess the risk of recurrence in EC, outperforming current prognostic factors, including molecular subtyping.

Objective: The study objective was to determine the relationship between lung resection and the development of postoperative hiatal hernia. Methods: Preoperative and postoperative computed tomography imaging from 373 patients from the International Early Lung Cancer Action Program and the Initiative for Early Lung Cancer Research on Treatment were compared at a median of 31.1 months of follow-up after resection of clinical early-stage non–small cell lung cancer. Incidence of new hiatal hernia or changes to preexisting hernias were recorded and evaluated by patient demographics, surgical approach, extent of resection, and resection site. Results: New hiatal hernias were seen in 9.6% of patients after lung resection (5.6% after wedge or segmentectomy and 12.4% after lobectomy; P = .047). The median size of new hernias was 21 mm, and the most commonly associated resection site was the left lower lobe (24.2%; P = .04). In patients with preexisting hernias, 53.5% demonstrated a small but significant increase in size from 21 to 22 mm (P

The evolution of Web technologies leads to software premature obsolescence requiring technology-independent representations to increase the reuse rates during the development process. They also require integration into service-oriented architectures to exchange information with different Web systems supporting runtime interoperability. Web Applications (WebApps) run on devices with different capabilities and limitations increasing the complexity of the development process. To address these challenges, different proposals have emerged to facilitate the development of WebApps, which is still an open research field with many challenges to address. This paper presents a model transformation architecture based on software standards to automatically generate full stack multi-layered WebApps covering Persistence, Service, and Presentation layers. This transformation architecture also generates the set of test cases to test WebApp business logic. The proposed transformation architecture only requires a UML platform-independent class model as an input to generate fully functional Web applications in a three-tier architecture including the three layers, while most proposals focus on the generation of the Presentation layer. In addition, this architecture employs software industry standards to enable an easy integration into third-party tools and development environments. The transformation Architecture proposed has been empirically validated on the case study of a fully functional travel management WebApp that is generated using a UML class diagram employing a third-party tool integrated into the same integrated development environment.

Tangible User Interfaces have enriched and expanded the user experience when interacting with computers and smart devices. The monopoly of graphical user interfaces has been broken thanks to the emergence of new complementary technologies that allow for new ways of interacting with computer systems, such as tangible interaction, among others. Due to the scope and number of research articles addressing the Tangible User Interface that have been published, it can now be considered an interaction mechanism that is relatively mature and integrated within society. However, while the application of tangible interfaces in different areas is described as a success, there are only a limited number of research articles about their impact on education and learning systems. As a result, it is difficult to show the actual impact of Tangible User Interface technology in K12 education settings. This study tries to fill this gap by performing a systematic mapping study that shows the current state of research on the impact of this technology in these settings, analyzing the findings and identifying the main advances and limitations of this novel technology.

In the era of personalized medicine, there is an increasing demand for comprehensive and complex diagnosis using minimally invasive techniques. Nowadays, it is mandatory to integrate biomarkers in the diagnostic process, as well as in the treatment and clinical management of many cancer patients. Patients with non-small cell lung cancer (NSCLC), for instance, are frequently diagnosed in advanced stages, at a point when only cytological material or small biopsies can be obtained. This pathology constitutes an interesting challenge for the testing of biomarkers in cytology. Furthermore, there is a growing development of imaging techniques that guide non-invasive approaches to obtain small biopsies or cytological samples. This has allowed fine needle aspiration cytology and fine needle aspiration biopsy (FNAC, FNAB) to become front-line procedures in the management of patients with NSCLC. It is well known that the list of biomarkers to be tested in these patients continues to increase. Nevertheless, there are several of essential biomarkers that should always be analyzed in all patients with NSCLC, not only in non-squamous but also in some squamous carcinomas (SqCC). Some of them, such as PDL1, are tested by immunocytochemistry (ICC), while others, mainly ALK and ROS1, can be tested by ICC and confirmed using other techniques such a Fluorescence In Situ Hybridization (FISH). Other biomarkers, namely EGFR and BRAF mutations, are currently evaluated by polymerase chain reaction (PCR)-based techniques including Next-Generation Sequencing (NGS). In this review, we will address the particularities and challenges that ICC and FISH pose in different types of cytological samples from an eminently practical point of view.

MET inhibitors have shown activity in non‐small‐cell lung cancer patients (NSCLC) with MET amplification and exon 14 skipping (METΔex14). However, patient stratification is imperfect, and thus, response rates have varied widely. Here, we studied MET alterations in 474 advanced NSCLC patients by nCounter, an RNA‐based technique, together with next‐generation sequencing (NGS), fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), and reverse transcriptase polymerase chain reaction (RT–PCR), exploring correlation with clinical benefit. Of the 474 samples analyzed, 422 (89%) yielded valid results by nCounter, which identified 13 patients (3%) with METΔex14 and 15 patients (3.5%) with very‐high MET mRNA expression. These two subgroups were mutually exclusive, displayed distinct phenotypes and did not generally coexist with other drivers. For METΔex14, 3/8 (37.5%) samples positive by nCounter tested negative by NGS. Regarding patients with very‐high MET mRNA, 92% had MET amplification by FISH and/or NGS. However, FISH failed to identify three patients (30%) with very‐high MET RNA expression, among which one received MET tyrosine kinase inhibitor treatment deriving clinical benefit. Our results indicate that quantitative mRNA‐based techniques can improve the selection of patients for MET‐targeted therapies.

Human Papillomavirus (HPV) type 16 is the main etiological agent of cervical cancer worldwide. Mutations within the virus genome may lead to an increased risk of cancer development and decreased vaccine response, but there is a lack of information about strains circulating in Sub-Saharan Africa. Endocervical cytology samples were collected from 480 women attending a voluntary cervical cancer screening program at Monkole Hospital and four outpatient centers in Kinshasa, Democratic Republic of the Congo (DRC). The prevalence of HPV infection was 18.8% and the most prevalent high-risk types were HPV16 (12.2%) followed by HPV52 (8.8%) and HPV33/HPV35 (7.8% each). HPV16 strains were characterized: 57.1% were classified as C lineage; two samples (28.6%) as A1 and one sample belonged to B1 lineage. HPV33, HPV35, HPV16, and HPV58 were the most frequent types associated with low-grade intraepithelial lesion while high-grade squamous intraepithelial lesions were predominantly associated with HPV16. Several L1 mutations (T266A, S282P, T353P, and N181T) were common in Kinshasa, and their potential effect on vaccine-induced neutralization, especially the presence of S282P, should be further investigated. Long control region (LCR) variability was high with frequent mutations like G7193T, G7521A, and G145T that could promote malignancy of these HPV16 strains. This study provides a helpful basis for understanding HPV16 variants circulating in Kinshasa and the potential association between mutations of LCR region and malignancy and of L1 and vaccine activity.

Online social networks are part of our daily life. They are widely used among university students. These platforms have positive and negative aspects. Focusing on the positive aspects, positive reinforcement social networks (PRSNs) have been used to improve the participation of high school students in the classroom. The main objective of this study is to analyze online social interaction on PRSNs, in order to find out if they have a positive impact on classroom participation and students’ self-perceptions of their own social skills, especially in the supposedly difficult STEM (Science, Technology, Engineering and Mathematics) subjects, where engagement tends to be lower. An education-oriented PRSN platform has been developed and used by the experimental group of students to promote discussion and facilitate the sharing of different types of materials. These materials had to be related to students’ academic and professional life, but not necessarily related to Mathematics. A total of 72 Geometry students (K–12) and their teacher participated in a semester-long experimental study. Analyses of the interactions through the proposed platform combined with classroom participation revealed that students from the experimental group showed an improvement not found in the control group. Moreover, perceptions of students’ own online skills were analyzed, showing a positive impact after the experiment.