Background: Fanconi anemia (FA) is a rare genomic instability disorder, characterized by congenital abnormalities, progressive bone marrow failure and predisposition to cancer. FA is caused by (likely) pathogenic variants in any of the 23 ( FANCA-FANCY) linked genes. Procedure: Retrospective analysis of 13 FA patients with a causative variant was performed to allow insights into FA. Patients (6 boys and 7 girls) aged from 9 to 26 years old, (mean age of 7.3 years), at diagnosis. Results: Phenotype evaluation demonstrated in 11/13 patients’ congenital anomalies, primarily pigmentary changes and short stature, in 90% of cases. Haematological abnormalities were present in 10/11 patients, with thrombocytopenia being the prominent finding. Genetic analysis for the most common complementation group FA-A revealed that 12/13 patients belonged to this group and only one patient was found to be FA-E. Exon deletions, single nucleotide variations, and duplications were identified. Familial patterns, due to consanguinity, were evident in one case. Twelve patients underwent hematopoietic stem cell transplantation (HSCT), with variable pre-HSCT supportive treatments. Post-HSCT data showed that 9 out of 10 patients for whom follow up data was available, survived for a median time of 5.4. Complications like acute graft-versus-host disease were noted. Conclusions: Our study highlights the importance of genotype-phenotype correlations towards tailored clinical management including the optimum time for HSCT in patients with FA.

Purpose This study investigated the interaction between neighborhood-level social determinants of health (SDOH) and neurological risk on cognitive outcomes in children treated for brain tumors (CTBT). Additionally, the impact of redlining practices on cognitive outcomes was explored. Methods A retrospective chart review of 161 CTBT aged 5-17 was conducted. Cognitive outcomes were measured using standardized neuropsychological assessments, and SDOH were assessed using the Childhood Opportunity Index (COI) and redlining data. The Neurological Predictor Scale (NPS) measured treatment-related neurological risk. Results Compared to those in moderate and high-opportunity neighborhoods, children living in low-opportunity neighborhoods exhibited lower intellectual functioning (IF) (F[2,154]=17.7, p < .01, η 2 = .19), processing speed (PS) ( F[2,89] = 4.41, p = .015, η 2 = .09), perceptual reasoning (PR) (F[2,64] = 3.60, p = .03, η 2 = .10), and verbal reasoning (VR) ( F[2,90] = 10.09, p < .01, η 2 = .18) scores. COI levels moderated the association between NPS and IF ( F [2,174] = .038, p = .013), with a negative effect of NPS on IF in high-opportunity neighborhoods ( t = -3.82, p < .01). Children from neighborhoods less affected by redlining had better IF performance, U = 94.50, Z = -2.30, p = .021. Conclusions This study highlights the role of neurological risk and neighborhood-level SODH in cognitive outcomes in CTBT. These findings underscore the need for targeted interventions and policies aimed at mitigating the effects of systemic inequities. Future research should explore early interventions to support cognitive development in survivors from communities with less resources.

Background: Sacrococcygeal teratoma (SCT) is considered the most common congenital neoplasm in neonates. This study aimed to assess long-term impacts on urinary and anorectal functions and quality of life (QoL) in patients who underwent surgery for SCT and to identify predictive factors for these outcomes, with a focus on the Intrapelvic Tumor Height (ITH). Methods: This retrospective study included patients treated surgically for SCT, between 1984 and 2017 at the Armand Trousseau Hospital. Urologic and anorectal functions were evaluated through clinical assessments and patient-reported outcomes through questionnaires. Statistical analysis was performed to explore correlations between these factors and long-term functional outcomes. Results: Twenty-six patients (median age=17 years) were identified. With a median follow-up of 180 months [96-444 months], 12 patients (46%) presented functional impairments: seven had isolated anorectal dysfunction and five had both urinary and anorectal dysfunctions, including neurogenic bladder (n=2) and/or detrusor-sphincter dyssynergia (n=3). A significant correlation was observed between adverse outcomes and intrapelvic tumor height (ITH) (median ITH was 27 mm in patients with impairments versus 15 mm in those without, p<0.05). Of the 12 questionnaire respondents, two patients experienced urinary and anorectal dysfunctions and five experienced isolated anorectal dysfunction. Most patients reported a good QoL, only one patient reporting a severe impact on daily life. Conclusions: This study highlights that long-term urologic and anorectal dysfunctions are prevalent in patients treated for SCT, although the overall impact on quality of life remains moderate. Importantly, ITH emerged as a more objective and accurate predictor of functional outcomes than tumor size or Altman classification.

Carbon farming is a nature-based solution to capture atmospheric CO2 and store it as soil organic carbon (SOC). Carbon farming trading schemes (CFTS) incentivize farmers to adopt these practices. Integral to CFTS is forecasting the SOC changes of individual projects, typically achieved using traditional multicompartmental soil carbon models (mSCM), and monitor total SOC stocks. However, traditional mSCM simulate unmeasurable compartments, leading to overparameterization and indeterminable partitioning among carbon compartments, suggesting a need for structural improvements. The ProCarbon-Soil (PROCS) model addresses this need abstracting fundamental principles of mSCM, reducing SOC state variables to two (total carbon and decomposability), and employing only one stabilization parameter, compared to the 4–8 state variables and 7–20 parameters typically required by mSCM. We mathematically derive methods for decomposability estimation and model initialization using successive carbon measurements. PROCS can handle environmental modifiers and events such as crop rotations, tillage, and manuring events, and respond to soil characteristics and weather conditions. Tests show that PROCS can accurately reproduce synthetic SOC trajectories generated by an mSCM with perturbed parameters using short-term data (12 years) with acceptable accuracy (median RMSE < 1.03 Mg ha-1 and absolute median of MB < 0.55 Mg ha-1). In a cross-validation test, the mean NRMSE closely aligns with the CV of white noise introduced in the synthetic data (4.15% vs 4.00%, respectively) for augmented carbon inflow scenarios, whereas the model exhibits higher errors for the no-carbon-inflow scenario (NRMSE = 5.48, 7.25 and 8.99% for 12, 24 and 50 years, respectively).

A document by Nikolaos Atreas. Click on the document to view its contents.

Genetic defects that result from mutations negatively affect animal health and productivity. The cytokine signaling pathway opens a whole world of study of signal transducers and activator proteins (STATs). These transcription factors play an important role in cellular processes, acting not only as signal transducers in the cytoplasm but also as activators of transcription in the nucleus. The gene was chosen because of its influence on reproduction processes in different animal species. About 12 genes have been discovered that affect the fertilization process and embryo survival in ruminants. The STAT5A 13516 gene regulates interferon-γ (IFNT) transmission, controls prolactin levels and activation of milk protein expression. Currently, many alterations of this gene have been discovered that affect the reproductive qualities of animals. The article presents the results of the study of STAT5A_13516 gene polymorphism and its influence on the reproductive ability of Aberdeen Angus cows. The study aims to investigate the relationship between STAT5A_13516 genotype and the duration of productive use of cows. Aberdeen-Angus cows (n=164) of the farm ”APF ”Nasha Zhitnitsa” located in Gagarinsky district of Smolensk region were selected as the study sample. The study focused on the analysis of several key indicators: age of the first insemination of heifers, duration of the interbreeding period, live weight at the first insemination of heifers, calf yield, Doha fertility index and reproductive capacity coefficient. It was found that polymorphism of STAT5A_13516 gene is represented by two alleles T and G, respectively 3 genotypes: GG, TG, TT. The T allele is associated with decreased fertility in cattle. During the study it was found that cows with STAT5ATT genotype, which are homozygous for this gene, had worse performance compared to groups of cows (STAT5ATG and STAT5AGG). Further use of these cows in the farm is inexpedient, it can lead to a decrease in reproduction of healthy calves and an increase in financial costs for their maintenance.

The increasing adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies has created new possibilities in improving accessibility and communication for people with disabilities. One of the most significant challenges faced by the deaf and mute communities is the communication barrier with non-sign language users. This paper proposes an AI/ML-based real-time sign language converter that enables seamless communication via audio calls for deaf and mute individuals. The proposed system integrates multiple components, including gesture recognition technology and computer vision, to translate sign language gestures into text and audio. The real-time converter uses machine learning models to recognize hand and facial gestures, then converts the recognized gestures into text, which is subsequently converted into speech via a text-to-speech (TTS) engine. The system also ensures minimal latency, enhancing the user experience during live interactions. Experimental results show that the system offers an efficient, real-time solution for overcoming communication barriers, fostering inclusivity and independence for deaf and mute individuals.

This study explores the development and implementation of an AI-based online translation teaching system with a layered architecture, including data, foundation, business, and user layers. The data layer integrates SQL and NoSQL databases for efficient storage and querying of various data types. The foundation layer combines system management with intelligent services, utilizing large models and multimodal technologies to enhance teaching efficiency, support blended learning, and drive the digital transformation of resources. The business layer supports four key platforms---translation teaching, training, self-learning, and testing---along with an intelligent terminal service platform. The user layer, with four interfaces based on participant roles, ensures smooth system operation. A microservices architecture improves stability and resource utilization. Built on the Langchain framework, the intelligent foundation has been tested for reliability and performance, and the terminal service can handle multiple concurrent connections and process students' audio data accurately.

The COVID-19 pandemic, caused by SARS-CoV-2, has severely impacted global public health and the economy. While effective vaccination programmes, lockdown and distancing measures have helped to decelerate the spread of the virus across the globe, the constant mutation of the virus leading new variants is alarming. A possible alternative approach to combat the virus is to develop an epitope-based peptide vaccine, which is conserved across multiple variants of the virus. Although several studies have predicted CD8+ and CD4+ epitopes of SARS-CoV-2, the bases of focus have primarily been MHC-peptide binding and epitope conservancy, which are not enough to support epitope viability. Here, we sought to identify promising CD8+ and CD4+ epitopes based on a combination of 6 different strategies. Using bioinformatics tools, we screened complete SARS-CoV-2 spike, envelope, membrane, nsp2, nsp12 and nsp13 protein sequences to predict possible epitopes before filtering them based on MHC-peptide binding, antigen processing and transport, immunogenicity, conservancy, and cross-reactivity. We identified 18 promising CD8+ epitopes and 4 promising CD4+ epitopes providing a cumulative global population coverage of 94.53%. These peptides are predicted to be immunogenic, conserved across multiple variants including the delta and omicron mutants, and are not cross reactive with human proteins. The findings of our study provide insights on SARS-CoV-2 T-cell epitopes and together with the known B-cell epitopes, potential multi-epitope-based peptide vaccine constructs for preclinical and clinical studies against Covid-19 and a way forward to serve as a novel platform for future vaccine design.

Alzheimer’s disease (AD) manifests by many behavioral changes, including anxiety and social withdrawal, which often precede and accompany cognitive decline. The TgF344-AD rat model recapitulates several AD-like pathological features and cognitive deficits, yet the progression of anxiety-like and social behavior impairments remains poorly characterized. In this study, we investigated anxiety-like and social behaviors in male and female TgF344-AD rats at 10 and 14 months of age using the open-field task, elevated plus-maze, and social interaction paradigms. While standard anxiety measures showed limited genotype effects, we observed subtle behavioral alterations in 10-month-old TgF344-AD rats, including decreased exploratory behavior and reduced locomotor activity in the elevated plus-maze. Notable social interaction deficits were identified in TgF344-AD rats, persisting across both age points. Our behavioral assessment provides an essential characterization of this model at intermediate disease stages when neuropathological changes and cognitive symptoms typically emerge. Most importantly, this work provides evidence for social behavior deficits in the TgF344-AD model and contributes to the understanding of non-cognitive changes in AD.

1. Cities are growing ecosystems in the modern world. Due to their heterogeneity, urban areas have multifaceted influences on organisms, including bees. However, in many specific city greenspace designs and management implementations, our understanding of their functionality remains limited. This is also true for urban flower meadows (UFMs). 2. We extensively examined UFMs in three large cities to answer the following question: what features of UFMs and their surroundings (urban matrix) are the most important in supporting bees in cities? 3. Our multifaceted approach revealed that the mosaics of habitats surrounding UFMs are at least as necessary to support bees as the local features of UFMs. An abundance of bees responded positively to the number of flowering units and to the blue and yellow colors of flowers, and increased cover of industrial areas, green urban areas, and pastures in a 100-m buffer. Increasing the cover of the continuous urban fabric in all buffer zones (100 m, 300 m, and 500 m) positively affected bee species richness and abundance. 4. Due to the lack of design guidelines for urban flower meadows, our results are helpful for the further planning of UFMs to optimize bee-friendly areas in urban landscapes.

The transition from the Last Glacial to the Holocene was marked by significant warming. This forced a compositional turnover of terrestrial plant and mammal communities discovered by diverse palaeoecological techniques. In this study, we analysed ancient environmental DNA from eight lake sediment cores, collected in northern Eurasia and Alaska, to elucidate the relationship of past bird communities and vegetation structure across the last 21,000 years. We leveraged all DNA reads assigned to the class “Aves” to characterise the compositional changes of the bird community. The dominance of chicken birds (mainly ptarmigans) during the Last Glacial Maximum turned into a higher taxonomic bird diversity along with the late glacial loss of the steppe-tundra and the increase of shrub and tree cover. This was accompanied by an increased relative abundance of songbirds, raptors and waterfowl. Compared to the northern boreal areas, vegetation and bird communities were more stable in the northern tundra sites, where open landscapes prevailed throughout. Reconstruction of past avian community changes support the predictions of distribution changes in the course of future ecosystem change.

The dynamic car rental industry faces significant challenges in demand forecasting, with about 50% of companies reporting inaccuracies that result in fleet utilization rates of only 70-75% instead of the optimal 85-90%. The study integrates customer segmentation and demand forecasting into a framework using various ML models. The study involved collecting extensive historical rental data from Secured Wheels and performing data preprocessing steps like cleaning, feature selection, and data splitting. The study employs decision trees, random forests, and clustering algorithms such as DBSCAN, Agglomerative clustering, Fuzzy-C-Means, and Affinity Propagation for segmentation. For demand forecasting, it uses ARIMA, regression model, and Holt-Winters. Performance metrics like accuracy, precision, silhouette coefficient, and Mean Absolute Error (MAE) evaluated the models, and the framework’s results were benchmarked against existing methods. Results indicate that the Agglomerative clustering achieved a silhouette coefficient of 0.9238 and a Davies-Bouldin index of 0.0031. At the same time, the HW model recorded a lower Mean Absolute Error (MAE) of 29.3641 and a Mean Squared Error (MSE) of 1183. The HW model was trained with customer segmentation features and the five cluster groups. These enhanced blended models enable more tailored marketing strategies and personalized customer experiences, increasing customer satisfaction and loyalty.

Background . Several induction quality scoring systems (IQSS) have been described to evaluate drugs and risk factors of this perilous anaesthetic period in horses, but no attempts to compare their reliability have been performed. Objectives . To elucidate reliability of three IQSS: the visual analogue scale (VAS), a simple descriptive scale (SDS) and a composite grading scale (CGS) proposed by the authors. Study design. Reliability study. Methods. Eight randomly selected video-recorded anaesthetic inductions from horses that underwent general anaesthesia were evaluated by 4 observers twice. The three aforementioned IQSS were used. To assess reliability, intra and inter-rater intraclass correlation coefficient (ICC), and their 95%, confidence intervals (CI) were calculated based on a mean-rating (k = 4), absolute-agreement, 2-way random-effects model. Results . The higher inter-rater ICC found was for the VAS, presenting almost a very good reliability (0.74 ± 0.11). The CGS and the SDS had lower inter-rater agreement than the VAS, classified as moderate to good reliability (0.65 ± 0.22 and 0.63 ± 0.21, respectively). Intra-rater agreement results demonstrated very good reliability for both VAS and SDS (0.82 ± 0.08; 0.81 ± 0.18, respectively); and excellent reliability for the CGS (0.91 ± 0.08). Main limitations . Limitations of this study include the use of video-recordings, that may affect inter-observer results when anaesthetic inductions are assessed in situ. Additionally, these findings are applicable only when free inductions are assessed. Conclusions . VAS and the proposed CGS are reliable IQSS in horses, outperforming the widely used SDS. For research purposes, the VAS is advised if multiple evaluators assess induction quality, whereas the CGS would be selected for studies involving a single observer. Standardizing the VAS as IQSS may facilitate broader multi-centre studies as it is a simple, user-friendly and adequate for short-lasting events scale.

Developmental dyslexia (DD) is a common reading disorder with neurological underpinnings, yet its spectral power and network topology abnormalities in Chinese DD remain unclear. This study investigates these abnormalities in Hong Kong Chinese children with DD using electroencephalography (EEG) data collected during resting states and a one-back Chinese-Korean character reading task. EEG recordings from 85 children with DD and 51 typically developing (TD) peers (aged 7–11) were analyzed using Fast Fourier Transform (FFT) for spectral power and minimum spanning tree (MST) metrics for brain topology. Children with DD exhibited significantly reduced alpha power in both resting and task states, suggesting impaired inhibitory control and cortical hyperactivation, which may contribute to cognitive deficits in DD. This widespread alpha power reduction, observed across multiple scalp areas in both resting and task states, underscores its potential as a neural biomarker for DD. Additionally, a less integrated resting-state beta band network topology was observed, reflecting disrupted large-scale connectivity in children with DD. Enhanced alpha band network integration during task performance, however, may indicate compensatory mechanisms engaged during cognitive challenges. Language familiarity modulated neural responses, with higher alpha and beta power during familiar Chinese stimuli, suggesting more efficient and automatic processing. Lower beta band network integration indicated reduced cognitive effort needed to process familiar Chinese stimuli. Correlation results suggest that a more integrated beta band network during rest is associated with better Chinese word reading fluency in children with DD. These findings provide key insights into spectral and topological markers of Chinese DD, offering a comprehensive view of brain activity and network abnormalities in Chinese children with DD, emphasizing the potential of alpha power as a stable neural biomarker and highlighting language familiarity’s role in modulating brain activity and network organization.

Purpose: The study aimed to extend inferences on the Average Treatment Effects (ATEs) from a Flatiron Health Clinico-Genomic Database (CGDB) Non-Small Cell Cancer (NSCLC) sample to the target population represented by SEER cancer registrations. The work also demonstrates the potential for the non-random selection to cause bias through a quantitative framework that compares the marginal and joint distributions of effect modifiers through each non-random selection process. Methods: ATEs for a binary treatment were estimated within the sample (SATE) and extended to the population (PATE) using combined information from SEER and a weighted estimator to standardize the joint distributions of effect modifiers. To understand potential biases through selection, the marginal and joint distributions of effect modifiers were compared through each stepwise process using two referent populations: SEER registrations and a superset of all NSCLC patients in the Flatiron Health network. Results: Within a subset of 1,166 stage III-IV NSCLCs receiving a binary treatment and combined information from 149,056 SEER registrations, the SATE & PATE for differences in survival at month 48 were -3.7 (-8.7, 1.6) & -3.4 (-8.7, 2.8) percentage points. Through each sequential selection, the joint distributions of effect modifiers were not discernibly different among the selected & unselected. Estimates of survival were unbiased by selection. Conclusions: Combined information from cancer registrations can be used to extend inferences from a selected sample to the target population. ATEs within a CGDB were an unbiased estimate of the population because the sequential selection did not differentially select effect modifiers causative of survival.

We performed epidemiological, genetic, and antigenic characterization of an influenza A/H3N2 outbreak in a congregate setting of young adults with high vaccination rates. We noted substantial duty-days lost, rapid spread, and vaccine antigenic divergence. The risk of influenza in healthy vaccinated adults underscores the need to develop universal influenza vaccines.

In a typical picture-word interference (PWI) task, picture-naming is faster/more accurate when the preceding prime words are identical to the picture name, but slower/less accurate when they are semantically related. However, ERPs time-locked to picture onset typically only show priming (facilitation) effects for both related prime types (smaller negativities compared to unrelated prime words). We replicated these effects and then conducted a novel behavior-contingent analysis for the semantic condition in which single-trial ERP data were re-averaged for word-picture pairs that either showed a facilitation pattern or an inhibition pattern (faster or slower RTs for related than unrelated pairs). The “facilitation bins” produced typical priming in early (200-400ms) and late (400-600ms) N400 epochs, while the “inhibition bins” produced reversed priming (greater negativity for related than unrelated prime words) in the late N400 epoch. In addition, after correcting for speech artifact, we observed reversed priming for the semantic condition in a later epoch (700-1200ms) that overlapped with the naming response (for both bin types). Overall, these results help resolve the apparent conflict between neural and behavioral responses in the PWI paradigm. Further, the pattern of results suggests that competition between lexical items can occur during both lexico-semantic activation and later speech production processes, lending some support to both lexical selection and response centered accounts of PWI effects.

Little is known about the role of antibiotics and associated resistance in microbial ecosystems in the absence of clinical antibiotic pressure. The Soft Rot Pectobacteriaceae (SRP) species complex, which comprises 37 bacterial species that are collectively responsible for the severe rotting of many crops, is an interesting model to analyse the role of β-lactam and β-lactamases in natural ecosystems. In particular, within this complex, most Pectobacterium versatile strains harbour a β-lactamase called BlaPEC-1. The aim of our work was to analyse the role of BlaPEC-1 during infection. To this end, two blaPEC-1-deleted strains were constructed and compared with their wild-type counterparts in vitro and in potato tuber infections. In vitro, the BlaPEC-1 β-lactamase enables P. versatile to resist ampicillin or carbapenem produced by Pectobacterium brasiliense. In mono-infections on potato tubers, blaPEC-1-deleted strains were unaffected in terms of virulence, fitness or association with commensal bacteria. In mixed infections, the BlaPEC-1 β-lactamase proved necessary for the coexistence of P. versatile with the carbapenem-producing strain, and also for the protection of carbapenem-sensitive strains both in vitro and in planta. Interestingly, in planta protection was observed even if the blaPEC-1 gene was repressed and bacteria expressing BlaPEC-1 were in the minority within the symptom. These results indicate that BlaPEC-1 exerts a true β-lactamase function during the infection process and acts as a public good of the SRP species complex. Finally, our results highlight the important role of β-lactamase in maintaining of strains diversity in natural ecosystem.

Background Timely identification and treatment can greatly enhance the prognosis of patients with distant metastases(DM). This study aims to reveal the risk factors for DM in appendiceal malignant neoplasms patients, and establish a machine learning (ML) model for predicting the risk of DM. Methods A total of 9,376 patients with appendiceal malignant neoplasms, categorized based on the AJCC 8th TNM staging system, were chosen for the study from the Surveillance, Epidemiology, and End Results (SEER) database. Building on this, we developed four machine learning algorithm models along with a Nomogram model. The model was assessed based on confusion matrix, receiver operating characteristic (ROC) curve AUC, calibration curve analysis, and decision curve analysis (DCA). Additionally, the relationship between clinical pathological features and target variables was explored using the SHAP algorithm based on the optimal model. To assess its performance and generalizability, we validated the best model using 52 cases of appendiceal malignant neoplasms from the First Affiliated Hospital of Shantou University Medical College, China. Results Univariate logistic regression analysis and multivariable logistic regression analysis suggested that gender, histological type, grade, T stage, N stage, CEA level, tumor size and distant lymph nodal metastasis were risk factor for DM, while age and race may be related to DM rather than independent risk factors. Five models were constructed incorporated the clinical features. The XGBoost model demonstrated the best performance, achieving an AUC of 0.9917 in the training group and 0.9738 in the internal validation group, respectively. The accuracy was higher than 0.9 in both cohorts. Furthermore, the XGBoost model was evaluated in the outer-validation group, achieving an accuracy of 0.8654 and an AUC of 0.8792. Both the DCA and calibration curves further supported its robust predictive capability. Conclusions Our model was capable of accurately predicting the risk of DM in patients with appendiceal malignant neoplasms, which is crucial for the early identification of high-risk patients and subsequent clinical decision-making.

Background and Objectives: The role of neoadjuvant chemotherapy (NAC) in treating initially resectable colorectal cancer liver metastases (CRCLM) remains controversial. Methods: We retrospectively compared outcomes between patients who underwent upfront surgery and those who received NAC followed by curative CRCLM surgery. Factors associated with early relapse were also investigated. Fifty-three patients were included (upfront surgery: n = 31, NAC: n = 22). Results: The 3-year overall survival (OS) and relapse-free survival (RFS) rates were comparable between the upfront surgery and NAC groups (OS: 83.9% vs. 81.8%, P = 0.9, hazard ratio [HR] = 1.07; RFS: 58.1% vs. 36.4%, P = 0.1, HR = 1.87). However, among metachronous CRCLM cohorts, the 3-year OS rates were 88.2% and 90.0% (P = 0.9, HR = 0.85), and the 3-year RFS rates were 76.4% and 30.0% (P = 0.015, HR = 4.03), respectively. Patients with higher computed tomography values in CRCLM had significantly better RFS than those with lower values (P = 0.04). Conversely, a higher number of CRCLM after NAC was significantly correlated with shorter RFS (P = 0.007). Conclusions: Routine NAC for initially resectable metachronous CRCLM should be avoided because of the high risk of early relapse.

A document by Inés Armenteros-Yeguas. Click on the document to view its contents.

Pro-angiogenic factors play a crucial role in the treatment of malignant tumors, particularly in anti-angiogenic therapies. This study evaluated vascular and lymphatic adverse events (AEs) associated with four anti-tumor angiogenesis drugs in the WHO-VigiAccess database. It also compared the adverse drug reaction (ADR) profiles of these drugs to support personalized treatment decisions and optimize therapeutic benefits and safety.

This paper deals with the mathematical study of a new nonlinear forager-exploiter-fluid system that characterizes the interactions between two predators and prey in a Newtonian fluid medium. Weak solutions for the proposed system are established based on the Schauder fixed-point theory, a priori estimates, and compactness arguments. Finally, we provide the numerical simulation for the proposed model in two-dimensional spatial settings.