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The drying behaviour of monoammonium phosphate fertilizer was examined in a static tray dryer, establishing kinetic parameters that may be used to improve the design of dryers. Drying temperatures ranged from 80 to 95°C, and surface air velocity was 0.50 m/s. The material was previously separated into two particle sizes, between 1.40 and 2.38 mm mean diameter. Drying curves were analysed qualitatively and seven empirical kinetic thin-layer models were fitted. The drying kinetic showed to be temperature-dependent: a moisture ratio reduction of 90% was achieved twice as fast at 95°C than at 80°C. On the other hand, particle size did not exert significant influence on the drying rate. The results showed a decreasing drying rate throughout the whole process. All studied models adjusted well to the experimental data: R2 values were all above 0.999. The two-term model generated the lowest RMSE and χ2 values, between 0.00621 and 0.010743 and between 0.000044 and 0.000115, respectively.

Background: Olfactory neuroblastoma (ONB) is a rare malignant neoplasm of neuroectodermal origin. Within an already very rare neoplasm, an even rarer and lesser-known entity is ectopic ONB. Methods: A 57-year-old female patient was evaluated for a smooth ethmoidal mass. A contrast-enhanced MRI identified a lesion with epicenter in the osteo-meatal complex without cribriform plate and olfactory recesses involvement. Endoscopic guided biopsy showed ONB Hyams II. An endoscopic trans-nasal resection was performed. Results: The postoperative course was uneventful. A definitive histologic examination confirmed a Hyams grade II, Kadish B ONB, corroborating the ectopic localization. Due to the tumor stage and grade, no adjuvant treatment was performed. The patient was free of disease at one-year postoperative follow-up. Conclusions: Ectopic ONB should be considered in the differential diagnosis of a sinonasal mass. Olfactory bulb and dura resection should be dictated by the clinical or radiological involvement of the cribriform plate.

Here, we described the generation of human induced pluripotent stem cell lines (hiPSCs) from three sporadic Parkinson’s disease (sPD) patients by reprogramming of their peripheral blood mononuclear cells (PBMC).

Abstract A novel intumescent fire‐retardant coating formulation has been developed by taking advantage of the inherent stability of large cyclic polyphenols (e.g., tannic acid) to remove the need for a dedicated blowing agent, specifically melamine. Cone calorimetry data indicate a lower fire growth rate (FIGRA) (5.0 ± 1.3 vs. 2.4 ± 0.7 kW m−2 s−1) upon removal of melamine. Total smoke release (TSR) increases following this removal (178 ± 21.4 vs. 305 ± 13.2 m2 m−2), which indicates the role of tannic acid in gas generation. Thermogravimetric analysis resulted in similar residue yield from the examined systems (36 ± 1.3% vs. 34 ± 1.7%) despite removal of a dedicated blowing agent. These results indicate that tannic acids multistep degradation allows it to behave as both a char forming and blowing agent in intumescent systems. The observed reduction of acid loading between the melamine‐tannin system and the melamine‐free composition (15.6% vs. 10.6% wt. ammonium polyphosphate, respectively) is also significant. Tannic acid occurs in agricultural waste products, which is encouraging for the pursuit of sustainable chemistry and addressing potential adverse health effects in humans combined with reducing the overall phosphorous loading. Highlights Melamine was removed from the intumescent without compromising stability. The resulting intumescent char was stronger despite less expansion. Tannic acid is attributed as both the charring and blowing agent. The tannin‐based coating requires a lower acid loading for similar performance.

Microplastics and nanoplastics (MNPs) are becoming an increasingly severe global problem due to their widespread distribution and complex impact on living organisms. Apart from their environmental impact, the effects of MNPs on living organisms have also continued to attract attention. The harmful impact of MNPs has been extensively documented in marine invertebrates and larger marine vertebrates like fish. However, the research on the toxicity of these particles on mammals is still limited, and their possible effects on humans are poorly understood. Considering that MNPs are commonly found in food or food packaging, humans are primarily exposed to them through ingestion. It would be valuable to investigate the potential harmful effects of these particles on gut health. This review focuses on recent research exploring the toxicological impacts of micro- and nanoplastics on the gut, as observed in human cell lines and mammalian models. Available data from various studies indicate that the accumulation of MNPs in mammalian models and human cells may result in adverse consequences, in terms of epithelial toxicity, immune toxicity, and the disruption of the gut microbiota. The paper also discusses the current research limitations and prospects in this field, aiming to provide a scientific basis and reference for further studies on the toxic mechanisms of micro- and nanoplastics.

Abstract Locoregional recurrences represent a frequently unexpected problem in head and neck squamous cell carcinoma (HNSCC). Relapse often (10–30%) occurs in patients with histologically negative resection margins (RMs), probably due to residual tumor cells or hidden pre-cancerous lesions in normal mucosa, both missed by histopathological examination. Therefore, definition of a ‘clean’ or tumor-negative RM is controversial, demanding for novel approaches to be accurately explored. Here, we evaluated next generation sequencing (NGS) and digital PCR (dPCR) as tools to profile TP53 mutational status and circulating microRNA expression aiming at scoring the locoregional risk of recurrence by means of molecular analyses. Serial monitoring of these biomarkers allowed identifying patients at high risk, laying the ground for accurate tracking of disease evolution and potential intensification of post-operative treatments. Additionally, our pipeline demonstrated its applicability into the clinical routine, being cost-effective and feasible in terms of patient sampling, holding promise to accurately (re)-stage RMs in the era of precision medicine.

We investigate the pairing properties of an effective shell-model interaction defined within a model space outside 132Sn and derived by means of perturbation theory from the CD-Bonn free nucleon-nucleon potential. It turns out that the neutron pairing component of the effective interaction is significantly weaker than the proton one, which accounts for the large pairing gap difference observed in the two-valence identical particle nuclei 134Sn and 134Te. The role of the contribution arising from one particle-one hole excitations in determining the pairing force is discussed and its microscopic structure is also analyzed in terms of the multipole decomposition.

Many authors have studied the effects of thyroid hormones and their diasteroisomers on mitochondrial activity. This topic is extensively debated because some authors have questioned the direct action of thyroid hormones on mitochondrial oxidative phosphorylation. […]

The study of the collective properties of nuclear excitations far from stability provides information about the shell structure at extreme conditions. Spectroscopic observables such as the energy or the transition probabilities of the lowest states, in nuclei with large neutron excess, allow to probe the density and isospin dependence of the effective interaction. Indeed, it was recently shown that tensor and three-body forces play an important role in breaking and creating magic numbers. Emblematic is the case of the evolution of the Ni isotopic chain where several features showed up moving from the most neutron rich stable isotope (64Ni) towards the 78Ni nucleus where the large neutron excess coincides with a double shell closure. In this framework, we have recently performed an experiment with the goal to extract the B(E2; 0+ → 2+) value for the 74Ni nucleus in an intermediate-energy Coulomb excitation experiment: preliminary results are discussed.

Abstract This study aimed at predicting the filtration surgery (FS) outcome using a machine learning (ML) approach. 102 glaucomatous patients undergoing FS were enrolled and underwent ocular surface clinical tests (OSCTs), determination of surgical site-related biometric parameters (SSPs) and conjunctival vascularization. Break-up-time, Schirmer test I, corneal fluorescein staining, Meibomian gland expressibility; conjunctival hyperemia, upper bulbar conjunctiva area of exposure, limbus to superior eyelid distance; and conjunctival epithelial and stromal (CET, CST) thickness and reflectivity (ECR, SCR) at AS-OCT were considered. Successful FS required a 30% baseline intraocular pressure reduction, with values ≤ 18 mmHg with or without medications. The classification tree (CT) was the ML algorithm used to analyze data. At the twelfth month, FS was successful in 60.8% of cases, whereas failed in 39.2%. At the variable importance ranking, CST and SCR were the predictors with the greater relative importance to the CART tree construction, followed by age. CET and ECR showed less relative importance, whereas OSCTs and SSPs were not important features. Within the CT, CST turned out the most important variable for discriminating success from failure, followed by SCR and age, with cut-off values of 75 µm, 169 on gray scale, and 62 years, respectively. The ROC curve for the classifier showed an AUC of 0.784 (0.692–0.860). In this ML approach, CT analysis found that conjunctival stroma thickness and reflectivity, along with age, can predict the FS outcome with good accuracy. A pre-operative thick and hyper-reflective stroma, and a younger age increase the risk of FS failure.

The study of the evolution of nuclear shells far from stability provides fundamental information about the shape and symmetry of the nuclear mean field. Nuclei with large neutron/proton ratio allow to probe the density dependence of the effective interaction. Indeed, it was recently shown that tensor and three-body forces play an important role in breaking and creating magic numbers. Of particular interest is the region of 78Ni where the large neutron excess coincides with a double shell closure. We have recently measured the B(E2; 0+ → 2+) of the 74Ni nucleus in an intermediate-energy Coulomb excitation experiment performed at the National Superconducting Cyclotron Laboratory of the Michigan State University. The 74Ni secondary beam has been produced by fragmentation of 86Kr at 140 AMeV on a thick Be target. Selected radioactive fragments impinged on a secondary 197Au target where the measurement of the emitted γ-rays allows to extract the Coulomb excitation cross section and related structure information. Preliminary B(E2) values do not point towards an enhancement of the transition matrix element and the comparison to what was already measured by Aoi and co-workers in [1] opens new scenarios in the interpretation of the shell evolution of the Z=28 isotopes.

A cold neutron induced fission experiment recently took place at the Institute Laue-Langevin (ILL) in Grenoble. The neutron beam was provided by the nuclear reactor facility at ILL and the detector setup that was used for the γ-spectroscopy of the fission products consisted mainly of the detectors of the EXOGAM array [1], thereby the name of the campaign is EXILL. The main purpose of our measurement was to investigate the nuclei in the region with N = 50 close to 78Ni as well as the nuclei close to the N = 82 shell closure. In this paper, the motivation of the experiment is described as well as the experimental setup and the status of the ongoing data analysis.

Inflammatory bowel diseases (IBDs) are intricate systemic conditions that can extend beyond the gastrointestinal tract through both direct and indirect mechanisms. Sarcopenia, characterized by a reduction in muscle mass and strength, often emerges as a consequence of the clinical course of IBDs. Indeed, sarcopenia exhibits a high prevalence in Crohn’s disease (52%) and ulcerative colitis (37%). While computed tomography and magnetic resonance imaging remain gold-standard methods for assessing muscle mass, ultrasound is gaining traction as a reliable, cost-effective, and widely available diagnostic method. Muscle strength serves as a key indicator of muscle function, with grip strength test emerging nowadays as the most reliable assessment method. In IBDs, sarcopenia may arise from factors such as inflammation, malnutrition, and gut dysbiosis, leading to the formulation of the ‘gut–muscle axis’ hypothesis. This condition determines an increased need for surgery with poorer post-surgical outcomes and a reduced response to biological treatments. Sarcopenia and its consequences lead to reduced quality of life (QoL), in addition to the already impaired QoL. Of emerging concern is sarcopenic obesity in IBDs, a challenging condition whose pathogenesis and management are still poorly understood. Resistance exercise and nutritional interventions, particularly those aimed at augmenting protein intake, have demonstrated efficacy in addressing sarcopenia in IBDs. Furthermore, anti-TNF biological therapies showed interesting outcomes in managing this condition. This review seeks to furnish a comprehensive overview of sarcopenia in IBDs, elucidating diagnostic methodologies, pathophysiological mechanisms, and clinical implications and management. Attention will also be paid to sarcopenic obesity, exploring the pathophysiology and possible treatment modalities of this condition.

El objetivo de este artículo es ofrecer una perspectiva analítica para comprender y situar en su dimensión específica los diferentes debates que atraviesan la conversación pública sobre las Inteligencias Artificiales generativas y los modelos de lenguaje grandes (LLM, por sus siglas en inglés). En primer lugar, identificamos cinco rasgos de las IA: no son una tecnología, sino que se trata de metatecnologías; constituyen no un dispositivo técnico, sino un mundoambiente; pueden ser tecnologías de alto riesgo y requieren de un tratamiento acorde en su ciclo de vida; las IA generativas y en particular los LLM no son sólo Inteligencia Artificial, sino también Sociedad Artificial; la perspectiva de la ética de la IA no es suficiente para abordarlas y es preciso promover un enfoque desde la ética organizacional de la IA y desde el pensamiento sistémico. En segundo lugar, recortamos las distintas escalas en las que actualmente se desarrollan las IA: la escala micro, la escala meso (la más propia para situar las políticas públicas) y la escala macro. En tercer lugar, presentamos dos enfoques transversales para el abordaje de las IA: el jurídico, orientado a la responsabilidad, y el sistémico, orientado a la protección y a la seguridad.

Expression of the bHLH transcription protein Atoh7 is a crucial factor conferring competence to retinal progenitor cells for the development of retinal ganglion cells. Several studies have emerged establishing ATOH7 as a retinal disease gene. Remarkably, such studies uncovered ATOH7 variants associated with global eye defects including optic nerve hypoplasia, microphthalmia, retinal vascular disorders, and glaucoma. The complex genetic networks and cellular decisions arising downstream of atoh7 expression, and how their dysregulation cause development of such disease traits remains unknown. To begin to understand such Atoh7-dependent events in vivo, we performed transcriptome analysis of wild-type and atoh7 mutant (lakritz) zebrafish embryos at the onset of retinal ganglion cell differentiation. We investigated in silico interplays of atoh7 and other disease-related genes and pathways. By network reconstruction analysis of differentially expressed genes, we identified gene clusters enriched in retinal development, cell cycle, chromatin remodeling, stress response, and Wnt pathways. By weighted gene coexpression network, we identified coexpression modules affected by the mutation and enriched in retina development genes tightly connected to atoh7. We established the groundwork whereby Atoh7-linked cellular and molecular processes can be investigated in the dynamic multi-tissue environment of the developing normal and diseased vertebrate eye.

Abstract Background Autistic girls are underdiagnosed compared to autistic boys, even when they experience similar clinical impact. Research suggests that girls present with distinct symptom profiles across a variety of domains, such as language, which may contribute to their underdiagnosis. In this study, we examine sex differences in the temporal dynamics of natural conversations between naïve adult confederates and school-aged children with or without autism, with the goal of improving our understanding of conversational behavior in autistic girls and ultimately improving identification. Methods Forty-five school-aged children with autism (29 boys and 16 girls) and 47 non-autistic/neurotypical (NT) children (23 boys and 24 girls) engaged in a 5-min “get-to-know-you” conversation with a young adult confederate that was unaware of children’s diagnostic status. Groups were matched on IQ estimates. Recordings were time-aligned and orthographically transcribed by trained annotators. Several speech and pause measures were calculated. Groups were compared using analysis of covariance models, controlling for age. Results Autistic girls used significantly more words than autistic boys, and produced longer speech segments than all other groups. Autistic boys spoke more slowly than NT children, whereas autistic girls did not differ from NT children in total word counts or speaking rate. Autistic boys interrupted confederates’ speech less often and produced longer between-turn pauses (i.e., responded more slowly when it was their turn) compared to other children. Within-turn pause duration did not differ by group. Limitations Our sample included verbally fluent children and adolescents aged 6–15 years, so our study results may not replicate in samples of younger children, adults, and individuals who are not verbally fluent. The results of this relatively small study, while compelling, should be interpreted with caution and replicated in a larger sample. Conclusion This study investigated the temporal dynamics of everyday conversations and demonstrated that autistic girls and boys have distinct natural language profiles. Specifying differences in verbal communication lays the groundwork for the development of sensitive screening and diagnostic tools to more accurately identify autistic girls, and could inform future personalized interventions that improve short- and long-term social communication outcomes for all autistic children.

Abstract Autism was formally recognized by the medical community in the first half of the twentieth century. Almost 100 years later, a small but growing literature has reported sex differences in the behavioral expression of autism. Recent research has also begun to explore the internal experiences of individuals with autism, including social and emotional insight. The current study examines sex differences in language-based markers of social and emotional insight in girls and boys with autism and non-autistic peers during semi-structured clinical interviews. Sixty-four participants aged 5 to 17 years were individually matched on chronological age and full-scale IQ to form four groups: autistic girls, autistic boys, non-autistic girls, and non-autistic boys. Transcribed interviews were scored using four scales that index aspects of social and emotional insight. Results revealed the main effects of diagnosis, such that youth with autism exhibited lower insight than non-autistic youth on scales indexing social cognition and object relations, emotional investment, and social causality. With regards to sex differences, across diagnoses, girls were rated higher than boys on the social cognition and object relations, emotional investment, and social causality scales. Examined within each diagnosis separately, clear sex differences emerged: both autistic and non-autistic girls demonstrated better social cognition and understanding of social causality than boys in their respective diagnostic groups. No within-diagnosis sex differences were found on the emotional insight scales, however. These results suggest that relatively enhanced social cognition and understanding of social causality in girls may be a population-level sex difference that is preserved in autism, despite the core social challenges that characterize this condition. The current findings reveal critical new information about insight into social and emotional thinking and relationships in autistic girls versus boys that have important implications for improving identification and designing effective interventions.

Purpose: To evaluate the ability of preoperative MRI-based measurements to predict the pathological T (pT) stage and cervical lymph node metastasis (CLNM) via machine learning (ML)-driven models trained in oral tongue squamous cell carcinoma (OTSCC). Materials and methods: 108 patients with a new diagnosis of OTSCC were enrolled. The preoperative MRI study included post-contrast high-resolution T1-weighted images acquired in all patients. MRI-based depth of invasion (DOI) and tumor dimension—together with shape-based and intensity-based features—were extracted from the lesion volume segmentation. The entire dataset was randomly divided into a training set and a validation set, and the performances of different types of ML algorithms were evaluated and compared. Results: MRI-based DOI and tumor dimension together with several shape-based and intensity-based signatures significantly discriminated the pT stage and LN status. The overall accuracy of the model for predicting the pT stage was 0.86 (95%CI, 0.78–0.92) and 0.81 (0.64–0.91) in the training and validation sets, respectively. There was no improvement in the model performance upon including shape-based and intensity-based features. The model for predicting CLNM based on DOI and tumor dimensions had a fair accuracy of 0.68 (0.57–0.78) and 0.69 (0.51–0.84) in the training and validation sets, respectively. The shape-based and intensity-based signatures have shown potential for improving the model sensitivity, with a comparable accuracy. Conclusion: MRI-based models driven by ML algorithms could stratify patients with OTSCC according to the pT stages. They had a moderate ability to predict cervical lymph node metastasis.