Recent publications
A dual-panel Positron Emission Mammography (PEM) scanner is a dedicated breast imaging device with higher spatial resolution and enhanced sensitivity, in comparison with conventional Positron Emission Tomography (PET) scanners. However, one of the main challenges this scanner faces are the limited angle artifacts that arise in the cross-planes. To mitigate such artifacts, deep learning regularization has been included in the List Mode Ordered Subsets Expectation Maximization (LM-OSEM) reconstruction algorithm. Regularization has been applied using a U-Net trained with Monte-Carlo simulated data. Network training was achieved using slices of cross-plane images of a PEM scanner as input and corresponding slices from a dedicated breast-PET ring scanner as target, since this scanner does not have the limited angle problem. In the regularization stage, the trained U-Net is employed to process the cross-plane slices of the preceding image estimation. Subsequently, the resultant output is fused with the former image estimate utilizing Forward-backward splitting expectation maximization (FBSEM). This image reconstruction framework has demonstrated a notable enhancement in image quality when assessed from the cross-plane perspective, while maintaining the quality of images when assessed from the in-plane perspective. With this approach, PEM images may be effectively analyzed as three-dimensional images. Acknowledgment We thank the support from PAPIIT grant IN108721 and the PhD scholarship of F. Moncada from
Cancer is the result of complex interactions of intrinsic and extrinsic cell processes, which promote sustained proliferation, resistance to apoptosis, reprogramming and reorganization. The evolution of any type of cancer emerges from the role of the microenvironmental conditions and their impact of some molecular complexes on certain signalling pathways. The understanding of the early onset of cancer requires a multiscale analysis of the cellular microenvironment. In this paper, we analyse a qualitative multiscale model of pancreatic adenocarcinoma by modelling the cellular microenvironment through elastic cell interactions and their intercellular communication mechanisms, such as growth factors and cytokines. We focus on the low-grade dysplasia (PanIN 1) and moderate dysplasia (PanIN 2) stages of pancreatic adenocarcinoma. To this end, we propose a gene-regulatory network associated with the processes of proliferation and apoptosis of pancreatic cells and its kinetics in terms of delayed differential equations to mimic cell development. Likewise, we couple the cell cycle with the spatial distribution of cells and the transport of growth factors to show that the adenocarcinoma evolution is triggered by inflammatory processes. We show that the oncogene RAS may be an important target for developing anti-inflammatory strategies that limit the emergence of more aggressive adenocarcinomas.
Mixing time is a parameter that describes the degree of agitation in a gas-stirred ladle. The literature is not conclusive on the effect of the tracer injection position on the mixing time under equal stirring conditions. This work conducted a systematic and comprehensive study on the effect of the tracer position on the mixing time for centric injection. Results in the form of a mixing time map indicate that the diagonal formed between the inlet and the upper wall region gets the fastest mixing, and specifically in the eye of the toroid of the circulation loop is the best position to mix solute rapidly. In contrast, the dead zones at the lower near-wall part of the ladle have the poorest mixing behavior for the tracer addition. The study also tested the ladle's axisymmetric assumption since two points were at different angular positions, but the same axial and radial points presented similar mixing time.
In this paper, we explore different methods to detect patterns in the activity of bus rapid transit (BRT) systems focusing on two aspects of transit: infrastructure and the movement of vehicles. To this end, we analyze records of velocity and position of each active vehicle in nine BRT systems located in the Americas. We detect collective patterns that characterize each BRT system obtained from the statistical analysis of velocities in the entire system (global scale) and at specific zones (local scale). We analyze the velocity records at the local scale applying the Kullback-Leibler divergence to compare the vehicular activity between zones. This information is organized in a similarity matrix that can be represented as a network of zones. The resulting structure for each system is analyzed using network science methods. In particular, by implementing community detection algorithms on networks, we obtain different groups of zones characterized by similarities in the movement of vehicles. Our findings show that the representation of the dataset with information of vehicles as a network is a useful tool to characterize at different scales the activity of BRT systems when geolocalized records of vehicular movement are available. This general approach can be implemented in the analysis of other public transportation systems.
Global warming is threatening ectotherms, with strong repercussions on their population dynamics. Body temperature in ectotherm reptiles is crucial to perform all their biological functions, which are maximized within a narrow interval. When faced with new or adverse thermal conditions, reptiles will respond with distributional changes, behavioural adjustments to maintain their internal temperature, or by adapting to the new environment, otherwise, extinctions will occur. Higher temperatures may have negative repercussions, for example, shortening periods of activity, affecting embryo development during gestation or decreasing viability of sperm cells in males. Through behavioural thermoregulation, reptiles can compensate for environmental variations (Bogert effect). Furthermore, according to Janzen’s hypothesis, the physiological cost of responding to adverse thermal conditions will be low in species exposed to higher thermal overlap. Here, we analysed the effect of a change in the thermal regime on sperm cell viability in Sceloporus megalepidurus, a small viviparous lizard from central Mexico. We hypothesized that an active thermoregulator inhabiting temperate mountains is able to prevent the effects of thermal change on sperm cell viability. We found that the change in thermal regime did not modify sperm cell viability, nor does it affect the maturation of sperm cells in the epididymis. Our results support the Bogert effect and suggest that, despite the high temperatures and low thermal quality, S. megalepidurus can maintain its body temperature within an optimal range for sperm cell viability.
Aggregation pathway of amyloid-β (25-35) in water affects the oxidative stress in the brain observed after administration of aggregated peptide in animals in vivo. Our studies on peptide aggregation ex situ prior to injection suggest that from the onset of peptide incubation in aqueous media, all samples exhibit the formation of fibril-like aggregates, characterized by a significant amount of β-sheets. This induces significant oxidative stress in vivo as observed for up to 60 min of peptide aggregation time. As the aggregation advances, the fibril-like aggregates become longer and intertwined, while the amount of β-sheets does not change significantly. An injection of such large, thick, and entangled aggregates in the animal brain results in a drastic increase in oxidative stress. This may be related to the number of activated microglia that initiate a sequence of inflammatory responses in the presence of large, highly interconnected fibrils.
Laser-matter interactions in laser powder bed fusion for metals (LPBF-Ms) significantly impact the final properties of the fabricated components. Critical process parameters, such as the linear energy density (LED), the ratio of laser power to scan speed, modify the energy input and consequently modify the melt pool geometry. LED strongly influences the melt pool cross-sectional profile, which dictates the thermal effects, microstructure, and mechanical properties of the finished part. Recognizing the crucial role of the melt pool in additive manufacturing, researchers have developed predictive models to estimate its dimensions and morphology. These models aid in tailoring part properties, optimizing process parameters, and reducing the number of experimental trials. However, existing models are either computationally expensive or analytically overly simplified for general LPBF-M applications. This study proposes an improved model that incorporates the Rosenthal equation as described by Tang to increase the accuracy of melt pool depth prediction. By using the thermal gradient per unit time, termed the “thermal dose” in this paper, corresponding to the LED value that produces experimental near-semicircular melt pool shapes for each studied material, we can improve the melt pool depth estimation. The trend revealed a good fit across the LED range compared with experimental measurements, suggesting the model’s effectiveness.
Purpose
Breast cancer is the most prevalent cancer type in Mexico, with male breast cancer accounting for only 1% of all breast cancer cases. A limited number of studies have described the clinical-pathological profiles of males with breast cancer in low- and middle-income countries. This study presents an analysis of patients with breast cancer seen at three different institutions in México.
Methods
A retrospective review of the medical records was performed to analyze the clinical and pathological characteristics of 49 men diagnosed with breast cancer and their overall survival.
Results
The mean age at diagnosis was 64.65 years. A significant proportion of patients presented at diagnosis with stage IV disease (n = 11, 22.45%), had triple-negative subtype (n = 6, 12.24%), and nuclear grade III (n = 20, 40.8%). Primary endocrine resistance was observed in 10 patients (31.25%). Genetic analysis was performed on 24 patients (48.9%), revealing a germline BRCA pathogenic variant in 8.33%.
Conclusion
Our findings described the clinical and pathological profile of breast cancer in a male cohort in Mexico, with a significantly high proportion of advanced disease, triple-negative subtype, nuclear grade III, and endocrine resistance. Further comprehensive studies, including research into somatic mutations, are needed.
In this study, the interaction of antimicrobial peptide Maximin 3 (Max3) with three different lipid bilayer models was investigated to gain insight into its mechanism of action and membrane specificity. Bilayer perturbation assays using liposome calcein leakage dose–response curves revealed that Max3 is a selective membrane‐active peptide. Dynamic light scattering recordings suggest that the peptide incorporates into the liposomal structure without producing a detergent effect. Langmuir monolayer compression assays confirmed the membrane inserting capacity of the peptide. Attenuated total reflection‐Fourier transform infrared spectroscopy showed that the fingerprint signals of lipid phospholipid hydrophilic head groups and hydrophobic acyl chains are altered due to Max3‐membrane interaction. On the other hand, all‐atom molecular dynamics simulations (MDS) of the initial interaction with the membrane surface corroborated peptide‐membrane selectivity. Peptide transmembrane MDS shed light on how the peptide differentially modifies lipid bilayer properties. Molecular mechanics Poisson–Boltzmann surface area calculations revealed a specific electrostatic interaction fingerprint of the peptide for each membrane model with which they were tested. The data generated from the in silico approach could account for some of the differences observed experimentally in the activity and selectivity of Max3.
Older adults suffering from cognitive impairment no dementia (CIND) are at higher risk of developing a severe neurodegenerative disorder, such as Alzheimer’s disease. The diagnosis of CIND is commonly carried out by neuropsychological methods; however, physiological markers may not only corroborate but are posing significant challenges for an early, objective, and automatized identification of CIND. A novel approach using Poincaré maps, a mathematical tool commonly employed in dynamical systems analysis is presented. Based on Electroencephalographic (EEG) recordings during the eyes-closed resting state condition, Poincaré maps were constructed, transforming these data into phase-space representations. By examining the structure and characteristics of these maps, CIND was identified by subtle alterations that may demonstrate the ability of Poincaré maps to capture underlying cognitive patterns and reveal deviations from normal cognitive aging. These deviations are observed as distinct clusters or irregularities in the map, serving as potential biomarkers for CIND detection. Moreover, the complex correlation measure (CCM) was incorporated to precisely quantify the temporal dynamics within the Poincaré maps, it was expected to visualize such differences in the temporal dynamics plots as well as in the reported CCM values from the two experimental groups, using specialized visualization software developed for this purpose. It was hypothesized, and verified, that Poincaré maps for the CIND group will exhibit smaller SD1 (short-term variability) and SD2 (long-term variability) values in the EEG regions associated with decision-making and memory compared to the control group. In addition, the temporal dynamics illustrated using CCM were expected to exhibit greater complexity and larger scale in the CU compared to the CIND group. This is particularly novel as it introduces a unique approach to differentiating between CU and CIND groups using Poincaré maps and CCM, a method not previously documented in EEG recordings during resting state.
Integrating natural fibers derived from local industrial waste streams into thermoplastic starch (TPS) proves to be a promising approach towards sustainable flame retardant biocomposites. Initially, three types of waste fibers from the agave, coconut, and leather industries were evaluated for their flame retardant properties in combination with aluminum trihydroxide (ATH), an environmental friendly flame retardant. Leather fiber (BLF) exhibited the best flame retardant performance and were further investigated along with ATH and varying amounts of bentonite nanoclay to enhance the residual protective layer. The combination of multiple components shows improvement in performance while reducing the total load of filler. The images of the fire residues revealed that a more enclosed surface correlates with a reduction in the peak of heat release rate. Whereas higher amounts of bentonite does not deliver further inprovements, only 1 phr nanoclay in the novel multicomponent system of TPS, ATH, BLF, and bentonite synergistically improved the UL-94 rating from HB to V1. The proposed system brings together the different approaches using a renewable biopolymer, natural waste fibres, and envirnmentally friendly flame retardancy and thus, is striking for its combination of outstanding sustainablity, instant feasability, and sufficient fire performance.
Sugarcane bagasse, a metal-organic framework, and magnetite nanoparticles form a composite that can be used as absorbent materials for the removal of three pesticides (atrazine, carbofuran, and iprodione). Magnetite nanoparticles were synthesized, functionalized, and supported on the SCB while the metal-organic framework grew on the surface. The adsorption process was performed in water; the pH was close to 7, the room temperature was 23 °C, and the separation of the material was promoted by a magnetic field. The maximum adsorption capacities of the composite were 52.38 mg g ⁻¹ for iprodione, 55.45 mg g ⁻¹ for atrazine, and 48.03 mg g ⁻¹ for carbofuran. The adsorption process occurs through hydrogen bridges with certain steric impediments owing to the ramifications and large sizes of the molecules involved.
Intestinal parasites are part of the intestinal ecosystem and have been shown to establish close interactions with the intestinal microbiota. However, little is known about the influence of intestinal protozoa on the regulation of the immune response. In this study, we analyzed the regulation of the immune response of germ-free mice transplanted with fecal microbiota (FMT) from individuals with multiple parasitic protozoans (P) and non-parasitized individuals (NP). We determined the production of intestinal cytokines, the lymphocyte populations in both the colon and the spleen, and the genetic expression of markers of intestinal epithelial integrity. We observed a general downregulation of the intestinal immune response in mice receiving FMT-P. We found significantly lower intestinal production of the cytokines IL-6, TNF, IFN-γ, MCP-1, IL-10, and IL-12 in the FMT-P. Furthermore, a significant decrease in the proportion of CD3+, CD4+, and Foxp3+ T regulatory cells (Treg) was observed in both, the colon and spleen with FMT-P in contrast to FMT-NP. We also found that in FMT-P mice there was a significant decrease in tjp1 expression in all three regions of the small intestine; ocln in the ileum; reg3γ in the duodenum and relmβ in both the duodenum and ileum. We also found an increase in colonic mucus layer thickness in mice colonized with FMT-P in contrast with FMT-NP. Finally, our results suggest that gut protozoa, such as Blastocystis hominis, Entamoeba coli, Endolimax nana, Entamoeba histolytica/E. dispar, Iodamoeba bütschlii, and Chilomastix mesnili consortia affect the immunoinflammatory state and induce functional changes in the intestine via the gut microbiota. Likewise, it allows us to establish an FMT model in germ-free mice as a viable alternative to explore the effects that exposure to intestinal parasites could have on the immune response in humans.
During seed maturation, plants may experience severe desiccation, leading to the accumulation of late embryogenesis abundant (LEA) proteins. These intrinsically disordered proteins also accumulate in plant tissues under water deficit. Functional roles of LEA proteins have been proposed based on in vitro studies, where monomers are considered as the functional units. However, the potential formation of homo‐oligomers has been little explored. In this work, we investigated the potential self‐association of Arabidopsis thaliana group 4 LEA proteins (AtLEA4) using in vitro and in vivo approaches. LEA4 proteins represent a compelling case of study due to their high conservation throughout the plant kingdom. This protein family is characterized by a conserved N‐terminal region, with a high alpha‐helix propensity and invitro protective activity, as compared to the highly disordered and low‐conserved C‐terminal region. Our findings revealed that full‐length AtLEA4 proteins oligomerize and that both terminal regions are sufficient for self‐association in vitro. However, the ability of both amino and carboxy regions of AtLEA4‐5 to self‐associate invivo is significantly lower than that of the entire protein. Using high‐resolution and quantitative fluorescence microscopy, we were able to disclose the unreported ability of LEA proteins to form high‐order oligomers in planta. Additionally, we found that high‐order complexes require the simultaneous engagement of both terminal regions, indicating that the entire protein is needed to attain such structural organization. This research provides valuable insights into the self‐association of LEA proteins in plants and emphasizes the role of protein oligomer formation.
Measurement was conducted at the INFN-LNL, employing a Tandem accelerator to achieve a 95 MeV ¹⁴N beam focused on ¹⁰B target (201 µg/cm²) with the aim to explore the cluster structures of light carbon isotopes. The main focus of this report will be on the ¹³C nucleus. Data were collected with a six-telescope detection system that allowed for the observation of many-body exit channels. Here are presented some results of the data analysis for the excited states of ¹³C from reactions with two and three products in the exit channel. In the ¹⁰B(¹⁴N,¹¹C)¹³C reaction, well-defined peaks were identified at 2.0, 3.7, 5.7, 7.4, 9.4, 11.7, 13.9, and 15.9 MeV. The states from ground state to 5.7 MeV are well understood and are used to correct the spectrum, while more states can contribute to the states at higher excitations and further investigation is needed. In the ¹⁰B(¹⁴N,¹¹C⁹Be)⁴He channel, states were identified at 13.1, 13.9, 15.6, and 18.5 MeV. The experimental results show consistency with the previously published data, supporting theoretical models of clustering and molecular-like structures in ¹³C. Further analysis of other reaction channels and states will be presented in future publications, aiming to enhance our understanding of multi-center clustering in carbon isotopes.
The physics of clusters in heavy neutron-rich ions is a topic of constant interest in the worldwide scientific community. In recent times, many interesting phenomena have been investigated especially thanks to the development of new radioactive beam production facilities. One example is the clustering of α particles in neutron-rich isotopes of self-conjugated nuclei, such as ¹⁰Be or ¹⁶C, exhibiting even very large nuclear deformations. At Laboratori Nazionali del Sud of INFN, a study was carried out on the topic of α clustering, employing the CHIMERA and FARCOS detectors. Radioactive ions of interest, such as ¹⁰Be, ¹³B and ¹⁶C, were produced in a cocktail beam through the In-Flight fragmentation technique by the FRIBs@LNS facility. Particularly important for this study was the employment of four FARCOS detectors, offering high angular and energetic resolutions. Several calibration and analysis techniques have been exploited and developed in this experiment for the analysis of the data collected by FARCOS. Finally, some preliminary results on the analysis of ¹⁰Be and ¹⁶C spectroscopy will be shown, in relation to some results already collected in the literature.
Colorectal cancer (CRC) is one of the most common and deadly neoplasms worldwide, with a growing burden in low-and middle-income countries, such as Mexico. This study seeks to evaluate the knowledge, attitudes, and practices related to CRC in a community in Mexico City. A cross-sectional survey was conducted between March and April 2023 among adults aged 45 to 74 residing in six neighborhoods of the Tlalpan borough in Mexico City. The questionnaire included sections on sociodemographic characteristics, medical family history, lifestyle habits, knowledge about CRC, attitudes towards prevention, and willingness to undergo screening. Data were analyzed using logistic regression models to identify factors associated with greater knowledge, attitudes, and practices. A total of 349 people were surveyed. A total of 35.2% reported knowing what CRC is, with greater knowledge of CRC being associated with higher education levels and having a family history of cancer. A total of 23.8% showed positive attitudes towards CRC screening, influenced by having a tertiary level of education. A total of 80.8% of participants expressed willingness to undergo CRC screening if offered, with lower intention observed among men. Levels of knowledge about CRC within the studied community are low, especially among those with lower education levels and without a family history of cancer. Intervention strategies should improve CRC education and foster positive attitudes towards early detection, particularly in high-risk groups.
Philosophers interested in conceptual engineering take it for granted that the same concept can unproblematically play diverse functions, but this view overlooks the fact that conceptual and functional change often impair concepts and even functions themselves. I demonstrate that while conceptual and functional engineering may improve concepts and functions, they can also produce detrimental effects. Therefore, it is crucial to carefully assess the potential benefits or problems before making any modifications. Frequently, we overlook the fact that, for instance, adding extra functions to our concepts modifies them; this may increase, but also impair, their theoretical and practical efficacy. I analyze and clarify these possibilities through a general classificatory framework encompassing concepts, functions, and conceptual and functional change. The larger aim of this paper is to bring attention to these complex and under-researched relationships and pave the way for further research in this area.
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