bluuebunny/crossref_metadata_2025 huggingface dataset:
Short- and long-term outcome differences between patients undergoing left and right colon cancer surgery: cohort study
Authors: Kuliavas Justas , Marcinkevičiūtė Kristina , Baušys Augustinas , Bičkaitė Klaudija , Baušys Rimantas , Abeciūnas Vilius , Degutytė Austėja Elžbieta , Kryžauskas Marius , Stratilatovas Eugenijus , Dulskas Audrius , Poškus Tomas , Strupas Kęstutis
Published: May 2024

Purpose

Since the literature currently provides controversial data on the postoperative outcomes following right and left hemicolectomies, we carried out this study to examine the short- and long-term treatment outcomes.

Methods

This study included consecutive patients who underwent right or left-sided colonic resections from year 2014 to 2018 and then they were followed up. The short-term outcomes such as postoperative morbidity and mortality according to Clavien-Dindo score, duration of hospital stay, and 90-day readmission rate were evaluated as well as long-term outcomes of overall survival and disease-free survival. Multivariable Cox regression analysis was performed of overall and progression-free survival.

Results

In total, 1107 patients with colon tumors were included in the study, 525 patients with right-sided tumors (RCC) and 582 cases with tumors in the left part of the colon (LCC). RCC group patients were older (P < 0.001), with a higher ASA score (P < 0.001), and with more cardiovascular comorbidities (P < 0.001). No differences were observed between groups in terms of postoperative outcomes such as morbidity and mortality, except 90-day readmission which was more frequent in the RCC group. Upon histopathological analysis, the RCC group’s patients had more removed lymph nodes (29 ± 14 vs 20 ± 11, P = 0.001) and more locally progressed (pT3-4) tumors (85.4% versus 73.4%, P = 0.001). Significantly greater 5-year overall survival and disease-free survival (P = 0.001) were observed for patients in the LCC group, according to univariate Kaplan-Meier analysis.

Conclusions

Patients with right-sided colon cancer were older and had more advanced disease. Short-term surgical outcomes were similar, but patients in the LCC group resulted in better long-term outcomes.
Self-reported caffeine consumption miss-matched consumption measured by plasma levels of caffeine and its metabolites: results from two population-based studies
Authors: Laaboub Nermine , Ranjbar Setareh , Strippoli Marie-Pierre F. , Marques-Vidal Pedro , Estoppey-Younes Sandrine , Ponte Belen , Pruijm Menno , Vogt Bruno , Ansermot Nicolas , Crettol Séverine , Vandenberghe Frederik , Vollenweider Peter , Preisig Martin , Bochud Murielle , EAP Chin B.
Published: May 2024

Importance and objective

Self-reported caffeine consumption has been widely used in research while it may be subject to bias. We sought to investigate the associations between self-reported caffeine consumption and plasma levels of caffeine and its two main metabolites (paraxanthine and theophylline) in the community.

Methods

Data from two population-based studies (SKIPOGH1 and 2 (N = 1246) and CoLaus|PsyCoLaus (N = 4461)) conducted in Switzerland were used. Self-reported caffeine consumption was assessed using questionnaires. Plasma levels of caffeine and its metabolites were quantified by ultra-high performance liquid chromatography coupled to a tandem quadrupole mass spectrometer.

Results

In both studies, mean log plasma levels of caffeine and its two metabolites were over 6.48 (plasma levels = 652 ng/ml) when no caffeine consumption was reported. Subsequently, nonlinear associations between log plasma levels and self-reported caffeine consumption were observed in SKIPOGH, with a change of the slope at 3–5 cups of espresso per day in SKIPOGH1 but not SKIPOGH2. In CoLaus|PsyCoLaus, increased daily consumption of caffeinated beverages was associated with increased log plasma levels with a change of the slope at 3 cups. In both studies, declared caffeine consumption higher than 3–5 cups per day was not associated with higher plasma levels of caffeine and its metabolites.

Conclusion

Self-reports of no or low caffeine consumption and consumption of more than 3–5 cups of coffee should be interpreted with caution, with possible under- or over-estimation. Quantifying plasma levels of caffeine and its metabolites may contribute to a better estimation of caffeine intake.
Validation of the Quality Analysis of Medical Artificial Intelligence (QAMAI) tool: a new tool to assess the quality of health information provided by AI platforms
Authors: Vaira Luigi Angelo , Lechien Jerome R. , Abbate Vincenzo , Allevi Fabiana , Audino Giovanni , Beltramini Giada Anna , Bergonzani Michela , Boscolo-Rizzo Paolo , Califano Gianluigi , Cammaroto Giovanni , Chiesa-Estomba Carlos M. , Committeri Umberto , Crimi Salvatore , Curran Nicholas R. , di Bello Francesco , di Stadio Arianna , Frosolini Andrea , Gabriele Guido , Gengler Isabelle M. , Lonardi Fabio , Maglitto Fabio , Mayo-Yáñez Miguel , Petrocelli Marzia , Pucci Resi , Saibene Alberto Maria , Saponaro Gianmarco , Tel Alessandro , Trabalzini Franco , Trecca Eleonora M. C. , Vellone Valentino , Salzano Giovanni , De Riu Giacomo
Published: May 2024

Background

The widespread diffusion of Artificial Intelligence (AI) platforms is revolutionizing how health-related information is disseminated, thereby highlighting the need for tools to evaluate the quality of such information. This study aimed to propose and validate the Quality Assessment of Medical Artificial Intelligence (QAMAI), a tool specifically designed to assess the quality of health information provided by AI platforms.

Methods

The QAMAI tool has been developed by a panel of experts following guidelines for the development of new questionnaires. A total of 30 responses from ChatGPT4, addressing patient queries, theoretical questions, and clinical head and neck surgery scenarios were assessed by 27 reviewers from 25 academic centers worldwide. Construct validity, internal consistency, inter-rater and test–retest reliability were assessed to validate the tool.

Results

The validation was conducted on the basis of 792 assessments for the 30 responses given by ChatGPT4. The results of the exploratory factor analysis revealed a unidimensional structure of the QAMAI with a single factor comprising all the items that explained 51.1% of the variance with factor loadings ranging from 0.449 to 0.856. Overall internal consistency was high (Cronbach's alpha = 0.837). The Interclass Correlation Coefficient was 0.983 (95% CI 0.973–0.991; F (29,542) = 68.3; p < 0.001), indicating excellent reliability. Test–retest reliability analysis revealed a moderate-to-strong correlation with a Pearson’s coefficient of 0.876 (95% CI 0.859–0.891; p < 0.001).

Conclusions

The QAMAI tool demonstrated significant reliability and validity in assessing the quality of health information provided by AI platforms. Such a tool might become particularly important/useful for physicians as patients increasingly seek medical information on AI platforms.
The effect of NHFOV on hemodynamics in mild and moderately preterm neonates: a randomized clinical trial
Authors: Farag Marwa Mohamed , Hassan Mohamed Ahmed Amen , Fasseeh Nader Abd EL Moneim , Ghazal Hesham Abd EL Rahim
Published: May 2024

The aim of this study is to study cardio-respiratory effects of nasal high-frequency oscillatory ventilation (NHFOV) vs. NCPAP as an initial mode of ventilation in moderate-late-preterm infants. A randomized controlled trial was conducted in NICU of Alexandria University Maternity Hospital (AUMH). One-hundred late-moderate-preterm infants were randomly assigned to either NHFOV-group (n = 50) or NCPAP-group (n = 50). For both groups, functional echocardiography was performed in the first 24 h to detect hemodynamic changes and respiratory outcome was monitored throughout the hospital stay. The main outcomes were hemodynamic measurements and myocardial function using functional echocardiography of those infants along with the respiratory outcome and complications. Kaplan–Meier survival plot was used representing time course of NCPAP and NHFOV failure. Left ventricular output values were not significantly different in both groups with median 202 ml/kg /min and IQR (176–275) in NCPAP-group and 226 ml/kg/min with IQR (181–286) in NHFOV group. Nevertheless, ejection fraction and fractional shortening were significantly higher in NHFOV-group with P 0.001. The time to weaning, the time to reach 30%-FIO2, the need for invasive ventilation, oxygen support duration, and maximal-FIO2 were significantly more in NCAPAP group.

     Conclusion: NHFOV is an effective and promising tool of non-invasive-ventilation which can be used as a primary modality of respiratory support in preterm infants with variable forms of respiratory distress syndrome without causing detrimental effect on hemodynamics or significant respiratory complications.

     Trial registration: NCT05706428 (registered on January 21, 2023).

What is Known:• NHFOV might be beneficial as a secondary mode of ventilation and might have an impact on hemodynamics.

What is New:• NHFOV can be used as an initial mode of ventilation with CDP beyond the reported pressure limits of CPAP without causing neither CO2 retention nor adverse hemodynamic consequences.
Hybrid modeling of an ultracentrifugation process for separation of full and empty adeno-associated virus particles
Authors: De-Luca Riccardo , Pupo-Correia Miguel , Feldhofer Michael , Martins Duarte L. , Umprecht Alexandra , Shahmohammadi Ali , Corona Daniel , von Stosch Moritz
Published: May 2024

Ultracentrifugation is an attractive method for separating full and empty capsids, exploiting their density difference. Changes of the serotype/capsid, density of loading material, or the genetic information contained in the adeno-associated viruses (AAVs) require the adaptation of the harvesting parameters and the density gradient loaded onto the centrifuge. To streamline these adaptations, a mathematical model could support the design and testing of operating conditions.

Here, hybrid models, which combine empirical functions with artificial neural networks, are proposed to describe the separation of full and empty capsids as a function of material and operational parameters, i.e., the harvest model. In addition, critical quality attributes are estimated by a quality model which is operating on top of the harvest model. The performance of these models was evaluated using test data and two additional blind runs. Also, a “what-if” analysis was conducted to investigate whether the models’ predictions align with expectations.

It is concluded that the models are sufficiently accurate to support the design of operating conditions, though the accuracy and applicability of the models can further be increased by training them on more specific data with higher variability.
A Tool for the Assessment of Swallowing Safety and Efficiency in Adults: Turkish Adaptation of Boston Residue and Clearance Scale
Authors: Tosun Samet , Topbaş Saime Seyhun , Aksoy Elif
Published: May 2024

The objective of this study was to create a Turkish language adaptation of the Boston Residue and Clearance Scale (BRACS), a validated and reliable tool. The BRACS scale was first translated into Turkish and a Turkish version was subsequently developed. Fiberoptic endoscopic examination of swallowing (FEES) was administered to collect data from 25 dysphagic patients who were hospitalized after a stroke. The recorded films were subjected to editing procedures to ensure their appropriateness for the assessment of swallowing disorders and were then dispatched to a panel of five speech and language therapists for evaluation using the adaptation of the BRACS instrument. The scoring by the experts was evaluated using both explanatory factor analysis (EFA) and confirmatory factor analysis (CFA). Convergent validity, item reliability, and construct (composite) reliability were measured by calculating the average variance extracted (AVE) values. For the 12 location items, EFA revealed 3 main latent factors: the laryngeal vestibule and the oropharynx and hypopharynx. The Turkish BRACS had excellent inter-rater reliability (Krippendorff’s alpha coefficient values ranged from 0.93 to 0.95) and high internal consistency (Cronbach’s alpha values ranged from 0.88 to 0.93). Inter-rater ICCs for the first and second sessions were 0.83 and 0.85, respectively. CFA showed that all fitted criteria reached acceptable or perfect fit levels. The findings indicated that the proposed factor structure was validated. The AVE values are between 0.61 and 0.73 which was taken as evidence of convergent validity. The Turkish adaptation of the BRACS tool demonstrates both reliablity and validity, rendering it a useful and credible tool for assessing residual severity, particularly in clinical settings.
Viable protoplast isolation, organelle visualization and transformation of the globally distributed plant pathogen Phytophthora cinnamomi
Authors: Kharel Aayushree , Rookes James , Ziemann Mark , Cahill David
Published: May 2024

Phytophthora cinnamomi is an oomycete plant pathogen with a host range of almost 5000 plant species worldwide and therefore poses a serious threat to biodiversity. Omics technology has provided significant progress in our understanding of oomycete biology, however, transformation studies of Phytophthora for gene functionalisation are still in their infancy. Only a limited number of Phytophthora species have been successfully transformed and gene edited to elucidate the role of particular genes. There is a need to escalate our efforts to understand molecular processes, gene regulation and infection mechanisms of the pathogen to enable us to develop new disease management strategies. The primary obstacle hindering the advancement of transformation studies in Phytophthora is their challenging and unique nature, coupled with our limited comprehension of why they remain such an intractable system to work with. In this study, we have identified some of the key factors associated with the recalcitrant nature of P. cinnamomi. We have incorporated fluorescence microscopy and flow cytometry along with the organelle-specific dyes, fluorescein diacetate, Hoechst 33342 and MitoTracker™ Red CMXRos, to assess P. cinnamomi-derived protoplast populations. This approach has also provided valuable insights into the broader cell biology of Phytophthora. Furthermore, we have optimized the crucial steps that allow transformation of P. cinnamomi and have generated transformed isolates that express a cyan fluorescent protein, with a transformation efficiency of 19.5%. We therefore provide a platform for these methodologies to be applied for the transformation of other Phytophthora species and pave the way for future gene functionalisation studies.
Open vs. robot-assisted preperitoneal inguinal hernia repair. Are they truly clinically different?
Authors: Rodrigues-Gonçalves V. , Verdaguer-Tremolosa M. , Martínez-López P. , Fernandes N. , Bel R. , López-Cano M.
Published: May 2024

Introduction

Inguinal hernia repair lacks a standard repair technique, with laparo-endoscopic and open preperitoneal methods showing similar outcomes. Despite higher costs, the popularity of robotic surgery is on the rise, driven by technological advantages. Controversies persist in comparing open repair techniques with the robotic approach, given contradictory results. The objective of this study was to compare postoperative outcomes, including complications, chronic pain, and recurrence, between open and robotic-assisted preperitoneal inguinal hernia repair.

Methods

This single-center retrospective study encompassed patients undergoing elective inguinal hernia repair in a specialized unit, employing both open preperitoneal and robotic-assisted laparoscopic approaches from September 2018 to May 2023. Comparative analysis of short- and long-term outcomes between these techniques was conducted. Additionally, multivariate logistic regression was employed to explore predictors of postoperative complications.

Results

A total of 308 patients met the inclusion criteria. 198 (64%) patients underwent surgery using an open preperitoneal approach and 110 (36%) using robot-assisted laparoscopy. Patients in the robot-assisted group were younger (P = 0.006) and had fewer comorbidities (P < 0.001). There were no differences between the groups in terms of postoperative complications (P = 0.133), chronic pain (P = 0.463) or recurrence (P = 0.192). Multivariate analysis identified ASA ≥ III (OR, 1.763; 95%CI, 1.068–3.994; P = 0.027) and inguinoscrotal hernias (OR, 2.371, 95%CI, 1.407–3.944; P = 0.001) as risk factors of postoperative complications.

Conclusions

Both open preperitoneal and robotic-assisted laparoscopic approaches show similar outcomes for complications, chronic pain, and recurrence when performed by experienced surgeons. The open preperitoneal approach, with its quicker operative time, may be advantageous for high-comorbidity cases. Treatment choice should consider patient factors, surgeon experience, and healthcare resources.
Tracking and co-location of global point clouds for large-area indoor environments
Authors: Michiels Nick , Jorissen Lode , Put Jeroen , Liesenborgs Jori , Vandebroeck Isjtar , Joris Eric , Van Reeth Frank
Published: May 2024

Extended reality (XR) experiences are on the verge of becoming widely adopted in diverse application domains. An essential part of the technology is accurate tracking and localization of the headset to create an immersive experience. A subset of the applications require perfect co-location between the real and the virtual world, where virtual objects are aligned with real-world counterparts. Current headsets support co-location for small areas, but suffer from drift when scaling up to larger ones such as buildings or factories. This paper proposes tools and solutions for this challenge by splitting up the simultaneous localization and mapping (SLAM) into separate mapping and localization stages. In the pre-processing stage, a feature map is built for the entire tracking area. A global optimizer is applied to correct the deformations caused by drift, guided by a sparse set of ground truth markers in the point cloud of a laser scan. Optionally, further refinement is applied by matching features between the ground truth keyframe images and their rendered-out SLAM estimates of the point cloud. In the second, real-time stage, the rectified feature map is used to perform localization and sensor fusion between the global tracking and the headset. The results show that the approach achieves robust co-location between the virtual and the real 3D environment for large and complex tracking environments.
The smart home, a true home? How new technologies disrupt the experience of home for older persons
Authors: Felber Nadine Andrea , Alavi Hamed , Mugellini Elena , Wangmo Tenzin
Published: May 2024

Smart home technologies (SHTs) can support older persons to age in place. However, adoption of SHTs remains low among this population. A reason for this is that they are not accustomed to having a home that is technologically enhanced. In this article, we focus on the older persons’ lived experience of “home” and show how SHTs potentially disrupt it. In consulting the currently available literature, both theoretical and empirical, we propose and use the concept of somatic capability assessment (SCA) in the discussion surrounding the design of SHTs for older persons. First, we propose SCA as a concept to grasp how humans take decisions while relying on their physical body, undisturbed by suggestions from technologies. Furthermore, we show that SCA functions best in a familiar and private environment—the home. SHTs have the potential to make the home seem unfamiliar and exposed, precisely through added data and the resulting suggestions, as we show through related empirical studies. Thus, SHTs hold an increased disruptive potential for older persons at home. By introducing SCA into the discussion of SHTs for older persons, and thus paying attention on how SHTs potentially disrupt the experience of home, further advances the ethical discussion on the adequate use and design of technologies in daily life, especially for the group of older persons. Our analysis offers important insights for the design and implementation processes of SHTs for older persons.
Effects of an extreme weather event over reproduction and survival of Great Tits (Parus major) in eastern Spain
Authors: Solís Iris , Álvarez Elena , Barba Emilio
Published: May 2024

The frequency of extreme climatic and weather events has increased since 1950 due to global changes induced by human influence. These events can have significant impacts at the individual, population, and community levels across various taxonomic groups. They can be particularly detrimental to bird populations during their breeding season, affecting specific breeding parameters. This study originated from an exceptionally rare breeding season of a resident Great Tit population recorded in spring 2002 when an unusual mortality of nestlings was observed. We quantified weather conditions (temperature, rainfall) from the end of April, a few days before we started detecting failed nests, and compared them with previous and subsequent years. In early May, when many pairs were incubating or caring for newly hatched chicks, we detected unusually low ambient temperatures and unusually high rainfall. This event likely caused that many first clutches failed completely, and that, compared with previous and subsequent years, fledging and breeding success was relatively low in those which were successful. There was also an increased proportion of replacement clutches that year. Anyway, the overall production of fledglings per breeding pair over the breeding season was 2.39, lower than other years. Although recruitment rate in 2003 was similar to other years, the lower production of fledglings in 2002 probably resulted in a decrease in the number of breeding pairs in the following years.
Measurement of Serum Vitamins B2 and B6 in Patients with Hashimoto’s Thyroiditis by LC–MS/MS Method
Authors: Mikulska-Sauermann Aniceta Ada , Karaźniewicz-Łada Marta , Filipowicz Dorota , Ruchała Marek , Główka Franciszek
Published: May 2024

Vitamin B2 and vitamin B6 are cofactors and coenzymes in many biochemical reactions, and their sufficient serum concentrations may be crucial for the proper functioning of the thyroid gland. The aim of the study was to develop and validate a novel high-performance liquid chromatography–tandem mass spectrometry (LC–MS/MS) method for the determination of vitamin B2 and vitamin B6 in the serum of patients with Hashimoto’s thyroiditis (HT). Detection of the analytes was performed on a triple-quadrupole MS with multiple reaction monitoring using electrospray ionization. The mobile phase consisted of water and methanol, both containing 0.1% (v/v) formic acid. The analytes were isolated from serum by the one-step sample preparation of the trichloroacetic acid precipitation. Validation parameters, including linearity, accuracy, precision, limits of detection and quantification, and stability, were determined and fulfilled the criteria for analyzing compounds in biological fluids. The method was applied for the determination of the above vitamin concentrations in serum samples of 74 patients with HT and 33 healthy controls. The concentration of vitamin B2 was significantly lower in patients with HT compared to the control group (7.20 ± 7.86 ng/mL vs. 12.03 ± 9.62 ng/mL) and the concentration of vitamin B6 was also lower, but without a statistically significant difference (30.09 ± 19.16 ng/mL vs. 37.29 ± 23.02 ng/mL). We concluded that the vitamins concentration measurement may be helpful in the diagnosis of vitamin deficiencies and the supplementation strategy.
A machine learning approach for package size estimation using UHF RFID interrogation signature
Authors: Vales-Alonso Javier , López-Matencio Pablo
Published: May 2024

This paper introduces a new approach for performing package classification and sizing using Radio-Frequency Identification (RFID) systems. This technique is applicable when packages are labeled with or contain multiple RFID-tagged items. During the interrogation of the tags, received signal strength (RSS) statistics and other information, such as the frame count or the reading time, are collected by the reader and used to predict the package type from a set of candidate classes using an Artificial Neural Network (ANN). The primary challenge lies in acquiring sufficient training data for a target scenario to ensure reliable predictions. To address this, a two-phase training process based on transfer learning is adopted. Initially, a base model is developed using synthetic data generated from a detailed RFID simulator, designed to suit diverse scenarios, establish detailed link budgets, and comprehensively simulate the communication protocols. This model is then refined using a small dataset collected experimentally in the actual scenario. This method was validated in a real testbed with four different package types. The base model was trained using 1000 synthetic samples per package type (4000 in total), whereas the refined model was trained with a dataset consisting of only 25 real interrogation traces (samples) per package type (100 in total). The experimental samples were obtained using a software-defined radio unit, the Ettus B210 Universal Software Radio Peripheral (USRP) platform. This experiment achieved an accuracy of over 92%. In summary, this approach introduces a new feature to existing RFID setups, demonstrating potential for advanced package handling and cost optimization in the logistics sector.
Privacy-preserving visual analysis: training video obfuscation models without sensitive labels
Authors: De Coninck Sander , Wang Wei-Cheng , Leroux Sam , Simoens Pieter
Published: May 2024

Visual analysis tasks, including crowd management, often require resource-intensive machine learning models, posing challenges for deployment on edge hardware. Consequently, cloud computing emerges as a prevalent solution. To address privacy concerns associated with offloading video data to remote cloud platforms, we present a novel approach using adversarial training to develop a lightweight obfuscator neural network. Our method focuses on pedestrian detection as an example of visual analysis, allowing the transformation of video frames on the camera itself to retain only essential information for pedestrian detection while preserving privacy. Importantly, the obfuscated data remains compatible with publicly available object detectors, requiring no modifications or significant loss in accuracy. Additionally, our technique overcomes the common limitation of relying on labeled sensitive attributes for privacy preservation. By demonstrating the inability of pedestrian attribute recognition models to detect attributes in obfuscated videos, we validate the efficacy of our privacy protection method. Our results suggest that this scalable approach holds promise for enabling camera usage in video analytics while upholding personal privacy.
Assessment of Roughness Characterization Methods for Data-Driven Predictions
Authors: Yang Jiasheng , Stroh Alexander , Lee Sangseung , Bagheri Shervin , Frohnapfel Bettina , Forooghi Pourya
Published: May 2024

A comparative analysis is undertaken to explore the impact of various roughness characterization methods as input variables on the performance of data-driven predictive models for estimating the roughness equivalent sand-grain size $$k_s$$

k
s

. The first type of model, denoted as $$\text {ENN}_\text {PS}$$

ENN
PS

, incorporates the roughness height probability density function (p.d.f.) and power spectrum (PS), while the second type of model, $$\text {ENN}_\text {PA}$$

ENN
PA

, utilizes a finite set of 17 roughness statistical parameters as input variables. Furthermore, a simplified parameter-based model, denoted as $$\text {ENN}_\text {PAM}$$

ENN
PAM

, is considered, which features only 6 input roughness parameters. The models are trained based on identical databases and evaluated using roughness samples similar to the training databases as well as an external testing database based on literature. While the predictions based on p.d.f. and PS achieves a stable error level of around 10% among all considered testing samples, a notable deterioration in performance is observed for the parameter-based models for the external testing database, indicating a lower extrapolating capability to diverse roughness types. Finally, the sensitivity analysis on different types of roughness confirms an effective identification of distinct roughness effects by $$\text {ENN}_\text {PAM}$$

ENN
PAM

, which is not observed for $$\text {ENN}_\text {PA}$$

ENN
PA

. We hypothesize that the successful training of $$\text {ENN}_\text {PAM}$$

ENN
PAM

is attributed to the enhanced training efficiency linked to the lower input dimensionality.
Tumor-infiltrating lymphocytes as a predictor of axillary and primary tumor pathological response after neoadjuvant chemotherapy in patients with breast cancer: a retrospective cohort study
Authors: Chin Kian , Landén Amalia H. , Kovács Anikó , Wärnberg Fredrik , Ekholm Maria , Karlsson Per , Olofsson Bagge Roger
Published: May 2024

Purpose

Tumor-infiltrating lymphocytes (TILs) can predict complete pathological response (pCR) of tumor in the breast but not so well-defined in the axilla after neoadjuvant chemotherapy. Since axillary surgery is being increasingly de-escalated after NACT, we aimed to investigate the relationship between TILs and pCR in the axilla and breast, as well as survival amongst NACT patients.

Methods

Clinicopathological data on patients who underwent NACT between 2013 and 2020 were retrospectively examined. Specifically, pre-TILs (before NACT), post-TILs (after NACT) and ΔTIL (changes in TILs) were assessed. Primary endpoint was pCR and secondary endpoints were breast cancer-free interval (BCFI) and overall survival (OS).

Results

Two hundred and twenty patients with nodal metastases were included. Overall axillary and breast pCR rates were 42.7% (94/220) and 39.1% (86/220), respectively, whereas the combined pCR rate was 32.7% (72/220). High pre-TILs (OR 2.03, 95% CI 1.02–4.05; p = 0.04) predicted axillary pCR whereas, high post-TILs (OR 0.33, 95% CI 0.14–0.76; p = 0.009) and increased ΔTILs (OR 0.25, 95% CI 0.08–0.79; p = 0.02) predicted non-axillary pCR. TILs were not a significant predictor for BCFI and OS.

Conclusions

This study supports the potential use of pre-TILs to select initially node-positive patients for axillary surgical de-escalation after NACT.
The Efficacy of Different Material Scaffold-Guided Cell Transplantation in the Treatment of Spinal Cord Injury in Rats: A Systematic Review and Network Meta-analysis
Authors: Wang Zhihua , Li Jun , Xu Tianqi , Guo Boyu , Xie Zhiping , Li Meihua
Published: May 2024

Cell transplantation is a promising treatment option for spinal cord injury (SCI). However, there is no consensus on the choice of carrier scaffolds to host the cells. This study aims to evaluate the efficacy of different material scaffold-mediated cell transplantation in treating SCI in rats. According to PRISMA’s principle, Embase, PubMed, Web of Science, and Cochrane databases were searched, and relevant literature was referenced. Only original research on cell transplantation plus natural or synthetic scaffolds in SCI rats was included. Direct and indirect evidence for improving hind limb motor function was pooled through meta-analysis. A subgroup analysis of some factors that may affect the therapeutic effect was conducted to understand the results fully. In total, 25 studies met the inclusion criteria, in which 293 rats received sham surgery, 78 rats received synthetic material scaffolds, and 219 rats received natural materials scaffolds. The network meta-analysis demonstrated that although synthetic scaffolds were slightly inferior to natural scaffolds in terms of restoring motor function in cell transplantation of SCI rats, no statistical differences were observed between the two (MD: −0.35; 95% CI −2.6 to 1.9). Moreover, the subgroup analysis revealed that the type and number of cells may be important factors in therapeutic efficacy (P < 0.01). Natural scaffolds and synthetic scaffolds are equally effective in cell transplantation of SCI rats without significant differences. In the future, the findings need to be validated in multicenter, large-scale, randomized controlled trials in clinical practice.

Trial registration: Registration ID CRD42024459674 (PROSPERO).

Graphical Abstract
Meiotic drive against chromosome fusions in butterfly hybrids
Authors: Boman Jesper , Wiklund Christer , Vila Roger , Backström Niclas
Published: May 2024

Species frequently differ in the number and structure of chromosomes they harbor, but individuals that are heterozygous for chromosomal rearrangements may suffer from reduced fitness. Chromosomal rearrangements like fissions and fusions can hence serve as a mechanism for speciation between incipient lineages, but their evolution poses a paradox. How can rearrangements get fixed between populations if heterozygotes have reduced fitness? One solution is that this process predominantly occurs in small and isolated populations, where genetic drift can override natural selection. However, fixation is also more likely if a novel rearrangement is favored by a transmission bias, such as meiotic drive. Here, we investigate chromosomal transmission distortion in hybrids between two wood white (Leptidea sinapis) butterfly populations with extensive karyotype differences. Using data from two different crossing experiments, we uncover that there is a transmission bias favoring the ancestral chromosomal state for derived fusions, a result that shows that chromosome fusions actually can fix in populations despite being counteracted by meiotic drive. This means that meiotic drive not only can promote runaway chromosome number evolution and speciation, but also that it can be a conservative force acting against karyotypic change and the evolution of reproductive isolation. Based on our results, we suggest a mechanistic model for why chromosome fusion mutations may be opposed by meiotic drive and discuss factors contributing to karyotype evolution in Lepidoptera.
A new binary chaos-based metaheuristic algorithm for software defect prediction
Authors: Arasteh Bahman , Arasteh Keyvan , Ghaffari Ali , Ghanbarzadeh Reza
Published: May 2024

Software defect prediction is a critical challenge within software engineering aimed at enhancing software quality by proactively identifying potential defects. This approach involves selecting defect-prone modules ahead of the testing phase, thereby reducing testing time and costs. Machine learning methods provide developers with valuable models for categorising faulty software modules. However, the challenge arises from the numerous elements present in the training dataset, which frequently reduce the accuracy and precision of classification. Addressing this, selecting effective features for classification from the dataset becomes an NP-hard problem, often tackled using metaheuristic algorithms. This study introduces a novel approach, the Binary Chaos-based Olympiad Optimisation Algorithm, specifically designed to select the most impactful features from the training dataset. By selecting these influential features for classification, the precision and accuracy of software module classifiers can be notably improved. The study's primary contributions involve devising a binary variant of the chaos-based Olympiad optimisation algorithm to meticulously select effective features and construct an efficient classification model for identifying faulty software modules. Five real-world and standard datasets were utilised across both the training and testing phases of the classifier to evaluate the proposed method's effectiveness. The findings highlight that among the 21 features within the training datasets, specific metrics such as basic complexity, the sum of operators and operands, lines of code, quantity of lines containing code and comments, and the sum of operands have the most significant influence on software defect prediction. This research underscores the combined effectiveness of the proposed method and machine learning algorithms, significantly boosting accuracy (91.13%), precision (92.74%), recall (97.61%), and F1 score (94.26%) in software defect prediction.
“People are Way too Obsessed with Rank”: Trust System in Social Virtual Reality
Authors: Chen Qijia , Cai Jie , Jacucci Giulio
Published: May 2024

Social Virtual Reality (VR) is growing in popularity and has drawn the attention of HCI academics. Social VR experiences harassment just like other online environments. The Trust System (TS) in VRChat, one of the most prominent social VR platforms, is designed to measure and indicate users’ trustworthiness in order to reduce toxicity in the platform. In this research, we analyzed data from “r/VRChat,” to understand how users perceive the system. We found that users interpret the system differently. Problems in its implementation cause distrust. The trust ranks, while intended to promote positive interactions, can actually lead to stereotyping and discourage communication between users of different ranks. The hierarchical structure within the ranks exacerbates discrimination and conflicts, particularly against the low-ranked users. We further discuss that trust ranks present challenges to newcomers and contribute to a competitive atmosphere that hinders the formation of less toxic norms. Finally, we provide implications for the future design of similar systems.
Hunting bugs: Towards an automated approach to identifying which change caused a bug through regression testing
Authors: Maes-Bermejo Michel , Serebrenik Alexander , Gallego Micael , Gortázar Francisco , Robles Gregorio , González Barahona Jesús María
Published: May 2024

Context

Finding code changes that introduced bugs is important both for practitioners and researchers, but doing it precisely is a manual, effort-intensive process. The perfect test method is a theoretical construct aimed at detecting Bug-Introducing Changes (BIC) through a theoretical perfect test. This perfect test always fails if the bug is present, and passes otherwise.

Objective

To explore a possible automatic operationalization of the perfect test method.

Method

To use regression tests as substitutes for the perfect test. For this, we transplant the regression tests to past snapshots of the code, and use them to identify the BIC, on a well-known collection of bugs from the Defects4J dataset.

Results

From 809 bugs in the dataset, when running our operationalization of the perfect test method, for 95 of them the BIC was identified precisely and in the remaining 4 cases, a list of candidates including the BIC was provided.

Conclusions

We demonstrate that the operationalization of the perfect test method through regression tests is feasible and can be completely automated in practice when tests can be transplanted and run in past snapshots of the code. Given that implementing regression tests when a bug is fixed is considered a good practice, when developers follow it, they can detect effortlessly bug-introducing changes by using our operationalization of the perfect test method.
Minkowski Space from Quantum Mechanics
Authors: Szabados László B.
Published: May 2024

Penrose’s Spin Geometry Theorem is extended further, from SU(2) and E(3) (Euclidean) to E(1, 3) (Poincaré) invariant elementary quantum mechanical systems. The Lorentzian spatial distance between any two non-parallel timelike straight lines of Minkowski space, considered to be the centre-of-mass world lines of E(1, 3)-invariant elementary classical mechanical systems with positive rest mass, is expressed in terms of E(1, 3)-invariant basic observables, viz. the 4-momentum and the angular momentum of the systems. An analogous expression for E(1, 3)-invariant elementary quantum mechanical systems in terms of the basic quantum observables in an abstract, algebraic formulation of quantum mechanics is given, and it is shown that, in the classical limit, it reproduces the Lorentzian spatial distance between the timelike straight lines of Minkowski space with asymptotically vanishing uncertainty. Thus, the metric structure of Minkowski space can be recovered from quantum mechanics in the classical limit using only the observables of abstract quantum mechanical systems.
Breakage Indices for Constitutive Models to Track the Evolution of Particle Crushing Under Continuous Shearing
Authors: Irani Nazanin , Tafili Merita , Prada-Sarmiento Luis Felipe , Wichtmann Torsten
Published: May 2024

Researchers have developed numerous breakage indices, predominantly relying on comparisons between pre- and post-test Grain Size Distribution (GSD) curves determined through conventional sieve analysis. Although these indices enable a precise estimation of particle breakage extent, a significant limitation arises when attempting to integrate them into constitutive models, especially when those models cannot consider GSD as an input. This paper addresses the need for tailored breakage indices designed to suit the specific requirements of different families of constitutive models. The new indices have been developed based on stress and strain tensor invariants or combinations thereof, ensuring the future ease of implementation into various constitutive models. The proposed equations have been validated using five different sets of experiments performed on rockfill material, calcareous, and quartz sands. The comparison between the available experimental data and the estimated degree of particle breakage using the suggested indices demonstrates their adequate performance. The novel indices can be integrated into different constitutive models, including hypoplastic, elastoplastic, and thermodynamically consistent approaches, as well as tested for their practical applicability for boundary value problems.
Ground Tire Rubber as a Sustainable Additive: Transforming Desert Sand Behavior
Authors: Ismael Nabil , Ismael Dalya , Al-Ahmad Asmaa
Published: May 2024

Managing waste tires presents a significant challenge globally, particularly in regions experiencing high temperatures and shortage of landfill sites. This issue is affecting countries like Kuwait, where the abundance of waste tires is a major source of environmental and safety risks, particularly during the intensely hot summer months. This extreme heat has sparked numerous fires, leading to substantial air pollution due to thick black smoke. Given the limited disposal options, recycling waste tires and finding practical applications for ground tire rubber (GTR) is essential. To address the challenge, a comprehensive laboratory testing program was conducted, using locally produced rubber aggregates as an additive to Kuwait's local surface sands. Two new variables were examined namely the size and gradation of the GTR, and the density of the compacted mixes. For this purpose, two different sizes of rubber aggregates, fine and coarse produced locally, were utilized, and the impact of relative compaction on the strength and compressibility of the mixtures was investigated by testing samples compacted to the maximum density and to 95% of the maximum density. The results suggest that combining local surface sands with rubber tire additives results in a lighter, more permeable, and compressible material, contributing significantly to sustainable waste management. With 20% rubber additive the maximum dry density decreased by nearly 20%, and the permeability increased by 1.74–3.11 times and the compression index increased by 6.15 and 3.8 times with fine and coarse rubber respectively. The angle of friction remained unchanged at 36° with the addition of coarse rubber and decreased by 3°–4° with fine rubber. The change in behavior although not an increase in the strength and stiffness, offers a range of suitable practical applications in civil engineering and environmental management, including use as a drainage layer, embankment construction on soft ground, earth fill around retaining walls, an additive in asphalt mixes, and in manufacturing compressible tiles for sports facilities.
Characterization of olive (Olea europaea L.) cultivars; colour properties, biochemical contents, antioxidant activity and nutrient contents
Authors: Tunç Yazgan , Yaman Mehmet , Keçe Yusuf Murat , Yilmaz Kadir Uğurtan , Yildiz Ercan , Güneş Adem
Published: May 2024

The olive tree, scientifically known as Olea europaea L., is an evergreen xerophytic tree that defines the natural flora, historical background, and cultural essence of the Mediterranean Basin. This study aimed to establish relationships using multivariate analysis methods between the nutrient content of soil conditions in which olive cultivars grown in Türkiye are cultivated and the nutrient element content, phytochemical contents, antioxidant activity, total chlorophyll amount, and leaf colors of these cultivars. All data sets used in the study were analyzed in 2022 and 2023, and average values were used in the research. According to Tukey's comparison result, it was determined that the soil structure of the garden was homogeneous in terms of nutrients it contained. In nutrient analysis conducted on leaves, in the ‘Çelebi’ cultivar, Al (59.25 mg kg−1), B (6.53 mg kg−1), Cu (48.36 mg kg−1), Fe (69.34 mg kg−1), K (1438.11 mg kg−1), Na (197.12 mg kg−1) nutrients are the highest; in the ‘Gemlik-21’ cultivar, Ca (5485.03 mg kg−1) nutrient is the highest; in the ‘Sarı Haşebi’ cultivar, Mg (928.11 mg kg−1), Mn (19.71 mg kg−1), S (632.77 mg kg−1) nutrients are the highest; and in the ‘Tavşan Yüreği’ cultivar, Ni (1.71 mg kg−1), Zn (9.76 mg kg−1) nutrients are the highest. The L* (49.19), b* (29.43) color values are highest in the ‘Sarı Yaprak’ cultivar, while the a* (28.84) value is highest in the ‘Girit Zeytini’ cultivar. The highest leaf chlorophyll content was determined in the ‘Girit Zeytini’ cultivar (95.57). Total phenolics, total flavonoids, antioxidant capacity were determined to be highest in the ‘Manzanilla’ (151.49 mg GAE/100 g), ‘Edincik Su’ (39.01 mg QE/100 g), ‘Nizip Yağlık’ (91.18%) cultivars, respectively. According to the principal component analysis, the first three principal components accounted for 82% of the total variation. The correlation matrix analysis revealed that high levels of certain minerals in the soil led to an increase in the leaves, resulting in positive correlation, while the opposite was true for negative correlation. According to heat map analysis, mineral elements in the leaf were in the same group, while other data sets were in different groups. The data obtained will shed light on future research on similar topics.