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[This paper is part of the "Focused Collection on Instructional Labs: Improving Traditions and New Directions."] Recent studies provide evidence that social constructivist pedagogical methods such as active learning, interactive engagement, and inquiry-based learning, while pedagogically more effective, can enable inequities in the classroom. By conducting a quantitative empirical examination of gender-inequitable group dynamics in two inquiry-based physics labs, we extend results of previous work. Using a survey on group work preferences and video recordings of lab sessions, we find similar patterns of gendered role taking noted in prior studies. These results are not reducible to differences in students' preferences. We find that an intervention which employed partner agreement forms, with the goal of reducing inequities, had a positive impact on students' engagement with equipment during a first-semester lab course. Our work will inform implementation of more effective interventions in the future and emphasizes challenges faced by instructors who are dedicated to both research-based pedagogical practices and efforts to promote diversity, equity, and inclusion in their classrooms.

Abstract A variety of scientific fields like proteomics and spintronics have created a new demand for on-chip devices capable of sensing parameters localized within a few tens of micrometers. Nano and microelectromechanical systems (NEMS/MEMS) are extensively employed for monitoring parameters that exert uniform forces over hundreds of micrometers or more, such as acceleration, pressure, and magnetic fields. However, they can show significantly degraded sensing performance when targeting more localized parameters, like the mass of a single cell. To address this challenge, we present a MEMS device that leverages the destructive interference of two topological radiofrequency (RF) counter-propagating wave modes along a piezoelectric Aluminum Scandium Nitride (AlScN) Su-Schrieffer-Heeger (SSH) interface. The reported MEMS device opens up opportunities for further purposes, including achieving more stable frequency sources for communication and timing applications.

The introduction of nonabsorbable barbed sutures in plastic surgery has allowed the achievement of significant results in terms of efficacy and short- and long-term outcomes. However, a nonabsorbable material with no antibacterial coating could act as a substrate for subclinical bacterial colonization and thereby determine recurrent subacute and chronic infective–inflammatory processes. The authors report a clinical experience of subacute infectious complications after two cases of diastasis recti surgical correction. The authors present a two-case series in which a nonabsorbable barbed suture was used for the repair of diastasis recti. The postoperative course was complicated by surgical site infection. The origin of the infectious process was clearly localized in the fascial suture used for diastasis correction. The suture was colonized by bacteria resulting in the formation of multiple granulomas of the abdominal wall a few months postoperatively. In both the reported cases, the patients partially responded to the antibiotic targeted therapy and reoperation was required. The microbiological analyses confirmed the colonization of sutures by Staphylococcus aureus. Barbed nonabsorbable sutures should be avoided for diastasis recti surgical correction to minimize the risk of infectious suture-related complications. The paper's main novel aspect is that this is the first clinical report describing infectious complications after surgical correction of diastasis recti with barbed polypropylene sutures. The risk of microbiological subclinical colonization of polypropylene suture untreated with antibacterial coating, therefore, should be taken into account.

Flaviviruses pose significant global health threats, infecting over 300 million people annually. Among their evasion strategies, the production of subgenomic flaviviral RNAs (sfRNAs) from the 3′ UTR of viral genomes is particularly notable. Utilizing a comprehensive in silico approach with the catRAPID algorithm, we analyzed over 300,000 interactions between sfRNAs and human proteins derived from more than 8000 flavivirus genomes, including Dengue, Zika, Yellow Fever, West Nile, and Japanese Encephalitis viruses. By providing the first extensive atlas of sfRNA interactions, we offer new insights into how flaviviruses can manipulate host cellular machinery to facilitate viral survival and persistence. Our study not only validated known interactions but also revealed novel human proteins that could be involved in sfRNA-mediated host defense evasion, including helicases, splicing factors, and chemokines. These findings significantly expand the known interactome of sfRNAs with human proteins, underscoring their role in modulating host cellular pathways. Intriguingly, we predict interaction with stress granules, a critical component of the cellular response to viral infection, suggesting a mechanism by which flaviviruses inhibit their formation to evade host defenses. Moreover, a set of highly-interacting proteins in common among the sfRNAs showed predictive power to identify sfRNA-forming regions, highlighting how protein signatures could be used to annotate viruses. This atlas not only serves as a resource for exploring therapeutic targets but also aids in the identification of sfRNA biomarkers for improved flavivirus diagnostics.

Background: Clinical reasoning (CR) is fundamental in medical education. However, the Italian curriculum has not incorporated a structured CR format yet. Therefore, we introduced the Clinical Case Discussions (CCD), to medical students attending the University of Bologna as a tool for developing CR abilities. CCDs are a case-based peer-teaching format, simulating the diagnostic process using published patient cases. Methods: Students of all clinical years of the University of Bologna Medical School were invited to voluntarily participate in a two-day CCD training program. They completed pre- and post-training questionnaires assessing their expectations before and impressions after the training and comparing learning outcomes to their usual classes. Results: Twenty-one students participated in this pilot program. Before the training, more than half of the participants expressed either interest or a strong interest in all proposed learning objectives. Afterward, 84.6% of the students stated that the training much exceeded (63.5%) or exceeded (23.1%) their expectations considering its utility for their future medical activities. A total of 92.3% strongly agreed (84.6%) or agreed (7.7%) to have improved their CR. Conclusions: Although this pilot program had some intrinsic limitations, the students’ positive feedback on this CCD format (combining the benefits of case-based learning and peer teaching) encourages further research on its potential role in the Italian curriculum.

Abstract For the Laplacian of an n-Riemannian manifold X, the Weyl law states that the k-th eigenvalue is asymptotically proportional to (k/V)2/n , where V is the volume of X. We show that this result can be derived via physical considerations by demanding that the gravitational potential for a compactification on X behaves in the expected (4+n)-dimensional way at short distances. In simple product compactifications, when particle motion on X is ergodic, for large k the eigenfunctions oscillate around a constant, and the argument is relatively straightforward. The Weyl law thus allows to reconstruct the four-dimensional Planck mass from the asymptotics of the masses of the spin 2 Kaluza-Klein modes. For warped compactifications, a puzzle appears: the Weyl law still depends on the ordinary volume V, while the Planck mass famously depends on a weighted volume obtained as an integral of the warping function. We resolve this tension by arguing that in the ergodic case the eigenfunctions oscillate now around a power of the warping function rather than around a constant, a property that we call weighted quantum ergodicity. This has implications for the problem of gravity localization, which we discuss. We show that for spaces with Dp-brane singularities the spectrum is discrete only for p = 6, 7, 8, and for these cases we rigorously prove the Weyl law by applying modern techniques from RCD theory.

Abstract Background Healthcare-Associated Infections (HAIs) are a global public health issue, representing a significant burden of disease that leads to prolonged hospital stays, inappropriate use of antimicrobial drugs, intricately linked to the development of resistant microorganisms, and higher costs for healthcare systems. The study aimed to measure the prevalence of HAIs, the use of antimicrobials, and assess healthcare- and patient-related risk factors, to help identify key intervention points for effectively reducing the burden of HAIs. Methods A total of 28 acute care hospitals in the Lombardy region, Northern Italy, participated in the third European Point Prevalence Survey (PPS-3) coordinated by ECDC for the surveillance of HAIs in acute care hospitals (Protocol 6.0). Results HAIs were detected in 1,259 (10.1%, 95% CI 9.6–10.7%) out of 12,412 enrolled patients. 1,385 HAIs were reported (1.1 HAIs per patient on average). The most common types of HAIs were bloodstream infections (262 cases, 18.9%), urinary tract infections (237, 17.1%), SARS-CoV-2 infections (236, 17.0%), pneumonia and lower respiratory tract infections (231, 16.7%), and surgical site infections (152, 11.0%). Excluding SARS-CoV-2 infections, the overall prevalence of HAIs was 8.4% (95% CI 7.9–8.9%). HAIs were significantly more frequent in patients hospitalized in smaller hospitals and in intensive care units (ICUs), among males, advanced age, severe clinical condition and in patients using invasive medical devices. Overall, 5,225 patients (42.1%, 95% CI 41.3–43.0%) received systemic antimicrobial therapy. According to the WHO’s AWaRe classification, the Access group accounted for 32.7% of total antibiotic consumption, while Watch and Reserve classes accounted for 57.0% and 5.9% respectively. From a microbiological perspective, investigations were conducted on only 64% of the HAIs, showing, however, a significant pattern of antibiotic resistance. Conclusions The PPS-3 in Lombardy, involving data collection on HAIs and antimicrobial use in acute care hospitals, highlights the crucial need for a structured framework serving both as a valuable benchmark for individual hospitals and as a foundation to effectively channel interventions to the most critical areas, prioritizing future regional health policies to reduce the burden of HAIs.

SUMMARY: Introduction: Scarless latissimus dorsi (LD) flap is a breast reconstruction technique, which allow to cover the lower pole of implant with a large portion of the LD muscle without skin paddle; it represents a surgical solution that transpose vascularized tissue avoiding the failure of breast reconstruction, following necrosis of mastectomy skin flaps. Material and Method: A retrospective review of patients undergoing immediate or delayed breast reconstruction using scarless LD flap reconstructions was performed. Clinical data obtained from follow-up visits were recorded. To evaluate breast shape contentment and patient satisfaction, the patients were requested to answer the Breast-Q, version 2.0 reduction module postoperative scales questionnaire at the 12-month follow-up. Results: We performed 19 scarless LD flap reconstructions between September 2019 and June 2022. The surgical time in average (considering minutes ± SD) was 130 (±15) minutes. The aesthetic assessment was good/excellent in 83% of patients. This was statistically significant (P=0.0). Conclusions: The scarless LD flap reconstruction is a valid and reliable solution, which has the advantage to reduce the risk of exposed prosthesis if native skin necrosis occurs.

Effective marine management requires balancing conservation and sustainable use of resources. Food web models are useful for simulating direct and indirect effects of management scenarios on ecosystem functioning by using multiple indicators. However, a key challenge is consolidating these indicators into a single, comprehensive, measure, which is often required to guide management decisions, such as in Strategic Environmental Assessment. This study applies spatial multi-criteria analysis to food web model outputs to develop a single index for different marine management applications. We applied this framework to the case of the “Tegnùe di Chioggia”, a Special Area of Conservation (SAC; IT3250047) under the Natura 2000 European network, located in the northern Adriatic Sea (Italy). This area, characterised by the presence of biogenic rocky outcrops, currently lacks a formal management plan. Using the Ecospace module of the Ecopath with Ecosim software, we simulated three management scenarios: 1) SAC expansion; 2) winter artisanal fishing in the SAC; 3) a combination of both. In line with ecosystem-based management, we focused on economically important trophic groups in the region, such as the Mediterranean mussel, Mytilus galloprovincialis, and striped venus clam, Chamelea gallina, which are present near the SAC. We also considered the efforts of the local fishing fleets. Ecosystem structure and functioning indicators, generated by the spatial food-web model, were linked to three criteria aligned with the management priorities of the area: nature conservation, aquaculture productivity, and fishing productivity. These criteria were aggregated into a final score to compare the management scenarios. The results showed that none of the scenarios would significantly alter community composition or ecosystem functioning compared to the current situation. However, they did show contrasting responses in the food web model. The SAC expansion scenario notably increased total biomass and commercial fish biomass, especially pectinids and cephalopods. The fishing scenario had a minimal impact on trophic groups. Ecosystem resilience and structure indicators were less sensitive to management scenarios than biomass indicators. However, the multi-criteria analysis revealed that the fishing scenario limited the benefits of expanding the SAC, due to reduced catches. The final score effectively ranked proposed scenarios, highlighting key indicators that influenced these variations. The proposed approach shows potential for supporting participatory modelling and engaging stakeholders in developing management scenarios.

Summary: Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a spectrum of disease states ranging from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH), which can eventually lead to the development of cirrhosis and hepatocellular carcinoma. Macrophages have long been implicated in driving the progression from steatosis to end-stage disease, yet we still know relatively little about the precise involvement of these cells in MASLD progression and/or regression. Rather, there are a considerable number of conflicting reports regarding the precise roles of these cells. This confusion stems from the fact that, until recently, macrophages in the liver were considered a homogenous population. However, thanks to recent technological advances including multi-parameter flow cytometry, single-cell RNA sequencing and spatial proteogenomics, we now know that this is not the case. Rather hepatic macrophages, even in the healthy liver, are heterogenous, existing in multiple subsets with distinct transcriptional profiles and hence likely functions. This heterogeneity is even more prominent in MASLD, where the macrophage pool consists of multiple different subsets of resident and recruited cells. To probe the unique functions of these cells and determine if targeting macrophages may be a viable therapeutic strategy in MASLD, we first need to unravel this complexity and decipher which populations and/or activation states are present and what functions each of these may play in driving MASLD progression. In this review, we summarise recent advances in the field, highlighting what is currently known about the hepatic macrophage landscape in MASLD and the questions that remain to be tackled.

Mental disorders are disorders of the cognitive, emotional or behavioral condition of an individual. They can have several origins and are usually associated with expressive anguish and difficulty in various aspects of life, including school education. Mental disorders are accompanied by social stigmas which may be linked to the belief in genetic determinism, i.e., in the perception that mental disorders are unchanging. The objective of the present study was to understand the perception of Brazilian teachers of all levels about the etiology of mental disorders. The results showed that most of the teachers studied believe in the predominance or exclusivity of genes in mental disorders, and do not consider the environment as a potential influencer of their occurrence or mitigation. This perception approaches the belief in genetic determinism and can justify the labeling of students with mental disorders and the consequent perpetuation of social stigmas. It is therefore recommended to promote knowledge in this area, including knowledge of the dynamics of interaction between genes and the environment, helping educators to prepare and to be able to act according to the reality of each student without creating inappropriate stereotypes.

Optimization of machine learning architectures is essential in determining the efficacy and the applicability of any neural architecture to real world problems. In this work a generalized Newton's method (GNM) is presented as a powerful approach to learning in deep neural networks (DNN). This technique was compared to two popular approaches, namely the stochastic gradient descent (SGD) and the Adam algorithm, in two popular classification tasks. The performance of the proposed approach confirmed it as an attractive alternative to state-of-the-art first order solutions. Due to the good results presented in the case of shallow DNN, in the last part of the article an hybrid optimization method is presented. This method consists in combining two optimization algorithms, i.e. GNM and Adam or GNM and SGD, during the training phase within the layers of the neural network. This configuration aims to benefit from the strengths of both first- and second-order algorithms. In this case a convolutional neural network is considered and its parameters are updated with a different optimization algorithm. Also in this case, the hybrid approach returns the best performance with respect to the first order algorithms.

ABSTRACT: Infectious Bursal Disease is a highly contagious disease that affects young chickens and leads to significant economic losses. Its causal agent is a double-stranded RNA virus that, due to its high error rate during the replication process, gives rise to a constant generation of new virus variants. Until 2014, strains of Infectious Bursal Diseases Virus (IBDV) belonging to genogroup 4 predominated in Argentina, but there have been no reports since then regarding the circulating genogroups in poultry. In this study, 11 recent sequences of Argentine from the hypervariable region of VP2 protein (hvVP2) were analyzed to determine their genogroup, origin, evolution, and amino acid sequence. Samples from chickens showing signs of IBDV infection were collected, and the hvVP2 region was amplified using RT-PCR, followed by sequencing. The results indicated that the analyzed strains belong to genogroup 2, with an estimated evolutionary rate of 1.74 × 10−3 substitutions/site/year. It is speculated that the predominant group of sequences began to spread in Argentina around 2014 and had its origins in China. Another sample is related to strains from South Korea and is not closely linked to the main group. Furthermore, the predicted amino acid sequences show similarity to strains that can evade vaccine-induced immunity. These findings underscore the importance of active surveillance in poultry to mitigate losses caused by IBDV.