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Objetivo: El objetivo de este estudio fue analizar si la potencia es un buen indicador del rendimiento en competiciones de bicicleta todo terreno (BTT), específicamente en la SuperCup cross country olímpico (XCO) BTT de Banyoles-España. Metodología: Se monitorizó la potencia de 10 ciclistas hombres profesionales de XCO-BTT durante la carrera y se analizó su relación con el rendimiento durante las subidas, las bajadas y los tramos llanos de la vuelta más rápida. Resultados: Se encontró una correlación fuerte entre el rendimiento y la potencia media (Potmed) (R² = -.652, p = .041), y muy fuerte entre el rendimiento y la potencia relativa (Potrel) (R² = -.887, p = .001); durante las subidas, la correlación fue fuerte entre el rendimiento y la Potmed (R² = -.719, p = .019), y muy fuerte entre el rendimiento y la Potrel (R² = -.888, p = .001). La relación entre el rendimiento y la Potmed durante los tramos llanos fue fuerte (R² = -.780, p = .008), y muy fuerte entre el rendimiento y la Potrel (R² = -.821, p = .004). Durante las bajadas no se encontró correlación entre el rendimiento y la Potmed y se encontró una correlación moderada entre el rendimiento y la Potrel (R² = -.530, p = .115). Discusión: Este estudio destaca la importancia de la Potrel como indicador del rendimiento en las competiciones de XCO-BTT. Conclusiones: El gran hallazgo de este estudio ha sido que la potencia no es un buen indicador del rendimiento durante las bajadas, donde este parece determinado por aspectos técnicos de conducción.

Phloroglucinol is a key byproduct of gut microbial metabolism that has been widely used as a treatment for irritable bowel syndrome. Here, we demonstrate that phloroglucinol tempers macrophage responses to pro-inflammatory pathogens and stimuli. In vivo, phloroglucinol administration decreases gut and extraintestinal inflammation in murine models of inflammatory bowel disease and systemic infection. The metabolite induces modest modifications in the microbiota. However, the presence of an active microbiota is required to preserve its anti-inflammatory activity. Remarkably, the protective effect of phloroglucinol lasts partially at least 6 months. Single-cell transcriptomic analysis of bone marrow progenitors demonstrates the capacity of the metabolite to induce long-lasting innate immune training in hematopoietic lineages, at least partially through the participation of the receptor and transcription factor, aryl hydrocarbon receptor (AhR). Phloroglucinol induces alterations in metabolic and epigenetic pathways that are most prevalent in upstream progenitors as hallmarks of central trained immunity. These data identify phloroglucinol as a dietary-derived compound capable of inducing central trained immunity and modulating the response of the host to inflammatory insults.

Abstract Testicular large B‐cell lymphoma (TLBCL) is an infrequent and aggressive lymphoma arising in an immune‐privileged site and has recently been recognized as a distinct entity from diffuse large B‐cell lymphoma (DLBCL). We describe the genetic features of TLBCL and compare them with published series of nodal DLBCL and primary large B‐cell lymphomas of the CNS (PCNSL). We collected 61 patients with TLBCL. We performed targeted next‐generation sequencing, copy number arrays, and fluorescent in situ hybridization to assess chromosomal rearrangements in 40 cases with available material. Seventy percent of the cases showed localized stages. BCL6 rearrangements were detected in 36% of cases, and no concomitant BCL2 and MYC rearrangements were found. TLBCL had fewer copy number alterations (p

In this article the authors present a new concept, activeness, as a dynamic psychological and cognitive state of effective engaged language learning. It is defined in terms of "investment," "integration" and "performance," and empowers vulnerable students to exercise control of their learning and progress based on their needs and desired outcomes. It is argued that activeness has a double didactic and linguistic dimension, implemented as a design feature in course materials and activities, and more importantly, promoted in forum communication. Therefore, participating in a strategically designed and scaffolded inclusive LMOOC can serve the triple purpose of enabling more effective target language learning, empowering vulnerable learners, and developing student potential to become engaged members of the language learning community. This engagement is arguably an important step towards doing the same in the real world. A study is presented of the second edition of an LMOOC on Spanish for immediate needs for vulnerable groups to explore the ways in which activeness was incorporated into the course and the effects it had. This research was conducted following a mixed-method approach which involved the platform's analytics, forum messages, pre- and post-questionnaires, and course observation. Evidence is provided of the progressive presence of activeness across different linguistic levels and the effect it had on students' satisfaction, course completion, and linguistic interaction. The results from this LMOOC provide evidence that it is possible to create a supportive online environment that meets the learning needs of vulnerable groups.

Real-time estimation of fish biomass plays a crucial role in real-world fishery production, as it helps formulate feeding strategies and other management decisions. In this paper, a dense fish counting network called Swin-CSRNet is proposed. Specifically, the VGG16 layer in the front-end is replaced with the Swin transformer to extract image features more efficiently. Additionally, a squeeze-and-excitation (SE) module is introduced to enhance feature representation by dynamically adjusting the importance of each channel through “squeeze” and “excitation”, making the extracted features more focused and effective. Finally, a multi-scale fusion (MSF) module is added after the back-end to fully utilize the multi-scale feature information, enhancing the model’s ability to capture multi-scale details. The experiment demonstrates that Swin-CSRNet achieved excellent results with MAE, RMSE, and MAPE and a correlation coefficient R2 of 11.22, 15.32, 5.18%, and 0.954, respectively. Meanwhile, compared to the original network, the parameter size and computational complexity of Swin-CSRNet were reduced by 70.17% and 79.05%, respectively. Therefore, the proposed method not only counts the number of fish with higher speed and accuracy but also contributes to advancing the automation of aquaculture.

In this article a proposal is presented for a theoretical framework that could provide the structure and coherence needed for the development of effective LMOOCs (Language MOOCs) and MALL (Mobile Assisted Language Learning) apps in a systematic way that would facilitate online second language learning. The framework is argued to be appropriate for language teaching and learning since it could be used for the elaboration of online courses such as LMOOCs and syllabi and didactic materials for MALL apps, regardless of the number of students. It has been refined during the process of designing and developing a Professional English LMOOC and the examples provided here are from that course. The framework is built upon the CEFR (The Common European Framework of Reference for Languages: Learning, Teaching, Assessment) since it offers a way to structure the knowledge and skills required in second language learning in a way which is coherent with the constructivist paradigm, following widely accepted European recommendations. It has been adopted because it provides a notional-functional classification of language use and learning ("elegantly" capturing the vastness and complexity of languages and their functional nature), and it is the first general attempt to produce a taxonomy of the elements that intervene in language use and learning, enabling comparable syllabi to be created for all European languages.

NESIM-RT is a specialized tool designed for simulating neuromorphic systems. In this new release we extend its capabilities to include state-of-the art models like the AdexLIF and Izhikevich, and to incorporate dynamic synaptic mechanisms such as Spike-Timing Dependent Plasticity (STDP). With these new features, researchers can now observe in real-time how different parameters influence these models and learning rules, thereby gaining deeper insights into neuronal function and network dynamics.

Aneurysmal subarachnoid hemorrhage (aSAH) is caused by abnormal blood vessel dilation and subsequent rupture, resulting in blood pooling in the subarachnoid space. This neurological insult results in the activation of the inflammasome, a multiprotein complex that processes pro-inflammatory interleukin (IL)-1 cytokines leading to morbidity and mortality. Moreover, increases in inflammasome proteins are associated with clinical deterioration in many neurological diseases. Limited studies have investigated inflammasome protein expression following aSAH. Reliable markers of the inflammatory response associated with aSAH may allow for earlier detection of patients at risk for complications and aid in the identification of novel pharmacologic targets. Here, we investigated whether inflammasome signaling proteins may serve as potential biomarkers of the inflammatory response in aSAH. Serum and cerebrospinal fluid (CSF) from fifteen aSAH subjects and healthy age-matched controls and hydrocephalus (CSF) no-aneurysm controls were evaluated for levels of inflammasome signaling proteins and downstream pro-inflammatory cytokines. Protein measurements were carried out using Simple Plex and Single-Molecule Array (Simoa) technology. The area under the curve (AUC) was calculated using receiver operating characteristics (ROCs) to obtain information on biomarker reliability, specificity, sensitivity, cut-off points, and likelihood ratio. In addition, a Spearman r correlation matrix was performed to determine the correlation between inflammasome protein levels and clinical outcome measures. aSAH subjects demonstrated elevated caspase-1, apoptosis-associated speck-like protein with a caspase recruiting domain (ASC), IL-18 and IL-1β levels in serum, and CSF when compared to controls. Each of these proteins was found to be a promising biomarker of inflammation in aSAH in the CSF. In addition, ASC, caspase-1, and IL-1β were found to be promising biomarkers of inflammation in aSAH in serum. Furthermore, we found that elevated levels of inflammasome proteins in serum are useful to predict worse functional outcomes following aSAH. Thus, the determination of inflammasome protein levels in CSF and serum in aSAH may be utilized as reliable biomarkers of inflammation in aSAH and used clinically to monitor patient outcomes.

Background: Aging and comorbidities like type 2 diabetes and obesity contribute to the development of chronic systemic inflammation, which impacts the development of heart failure and vascular disease. Increasing evidence suggests a role of pro-inflammatory M1 macrophages in chronic inflammation. A shift of metabolism from mitochondrial oxidation to glycolysis is essential for the activation of the pro-inflammatory M1 phenotype. Thus, reprogramming the macrophage metabolism may alleviate the pro-inflammatory phenotype and protect against cardiovascular diseases. In the present study, we hypothesized that the activation of estrogen receptors leads to the elevation of the mitochondrial deacetylase Sirt3, which supports mitochondrial function and mitigates the pro-inflammatory phenotype in macrophages. Materials and Methods: Experiments were performed using the mouse macrophage cell line RAW264.7, as well as primary male or female murine bone marrow macrophages (BMMs). Macrophages were treated for 24 h with estradiol (E2) or vehicle (dextrin). The effect of E2 on Sirt3 expression was investigated in pro-inflammatory M1, anti-inflammatory/immunoregulatory M2, and naïve M0 macrophages. Mitochondrial respiration was measured by Seahorse assay, and protein expression and acetylation were determined by western blotting. Results: E2 treatment upregulated mitochondrial Sirt3, reduced mitochondrial protein acetylation, and increased basal mitochondrial respiration in naïve RAW264.7 macrophages. Similar effects on Sirt3 expression and mitochondrial protein acetylation were observed in primary female but not in male murine BMMs. Although E2 upregulated Sirt3 in naïve M0, pro-inflammatory M1, and anti-inflammatory/immunoregulatory M2 macrophages, it reduced superoxide dismutase 2 acetylation and suppressed mitochondrial reactive oxygen species formation only in pro-inflammatory M1 macrophages. E2 alleviated the pro-inflammatory phenotype in M1 RAW264.7 cells. Conclusions: The study suggests that E2 treatment upregulates Sirt3 expression in macrophages. In primary BMMs, female-specific Sirt3 upregulation was observed. The Sirt3 upregulation was accompanied by mitochondrial protein deacetylation and the alleviation of the oxidative and pro-inflammatory phenotype in M1 macrophages. Thus, the E2–Sirt3 axis might be used in a therapeutic strategy to fight chronic systemic inflammation and prevent the development of inflammation-linked diseases.

Poly(lactic acid) (PLA) is widely used in the field of medicine due to its biocompatibility, versatility, and cost-effectiveness. Three-dimensional (3D) printing or the systematic deposition of PLA in layers has enabled the fabrication of customized scaffolds for various biomedical and clinical applications. In tissue engineering and regenerative medicine, 3D-printed PLA has been mostly used to generate bone tissue scaffolds, typically in combination with different polymers and ceramics. PLA’s versatility has also allowed the development of drug-eluting constructs for the controlled release of various agents, such as antibiotics, antivirals, anti-hypertensives, chemotherapeutics, hormones, and vitamins. Additionally, 3D-printed PLA has recently been used to develop diagnostic electrodes, prostheses, orthoses, surgical instruments, and radiotherapy devices. PLA has provided a cost-effective, accessible, and safer means of improving patient care through surgical and dosimetry guides, as well as enhancing medical education through training models and simulators. Overall, the widespread use of 3D-printed PLA in biomedical and clinical settings is expected to persistently stimulate biomedical innovation and revolutionize patient care and healthcare delivery.

The real-time classification of fish feeding behavior plays a crucial role in aquaculture, which is closely related to feeding cost and environmental preservation. In this paper, a Fish Feeding Intensity classification model based on the improved Vision Transformer (CFFI-Vit) is proposed, which is capable of quantifying the feeding behaviors of rainbow trout (Oncorhynchus mykiss) into three intensities: strong, moderate, and weak. The process is outlined as follows: firstly, we obtained 2685 raw feeding images of rainbow trout from recorded videos and classified them into three categories: strong, moderate, and weak. Secondly, the number of transformer encoder blocks in the internal structure of the ViT was reduced from 12 to 4, which can greatly reduce the computational load of the model, facilitating its deployment on mobile devices. And finally, a residual module was added to the head of the ViT, enhancing the model’s ability to extract features. The proposed CFFI-Vit has a computational load of 5.81 G (Giga) Floating Point Operations per Second (FLOPs). Compared to the original ViT model, it reduces computational demands by 65.54% and improves classification accuracy on the validation set by 5.4 percentage points. On the test set, the model achieves precision, recall, and F1 score of 93.47%, 93.44%, and 93.42%, respectively. Additionally, compared to state-of-the-art models such as ResNet34, MobileNetv2, VGG16, and GoogLeNet, the CFFI-Vit model’s classification accuracy is higher by 6.87, 8.43, 7.03, and 5.65 percentage points, respectively. Therefore, the proposed CFFI-Vit can achieve higher classification accuracy while significantly reducing computational demands. This provides a foundation for deploying lightweight deep network models on edge devices with limited hardware capabilities.

Mesenchymal stem/stromal cells (MSCs) have emerged as a promising therapeutic approach for a variety of diseases due to their immunomodulatory and tissue regeneration capabilities. Despite their potential, the clinical application of MSC therapies is hindered by limited cell retention and engraftment at the target sites. Electrospun scaffolds, with their high surface area-to-volume ratio and tunable physicochemical properties, can be used as platforms for MSC delivery. However, synthetic polymers often lack the bioactive cues necessary for optimal cell-scaffold interactions. Integrating electrospun scaffolds and biological polymers, such as polysaccharides, proteins, and composites, combines the mechanical integrity of synthetic materials with the bioactivity of natural polymers and represents a strategic approach to enhance cell-scaffold interactions. The molecular interactions between MSCs and blended or functionalized scaffolds have been examined in recent studies, and it has been shown that integration can enhance MSC adhesion, proliferation, and paracrine secretion through the activation of multiple signaling pathways, such as FAK/Src, MAPK, PI3K/Akt, Wnt/β-catenin, and YAP/TAZ. Preclinical studies on small animals also reveal that the integration of electrospun scaffolds and natural polymers represents a promising approach to enhancing the delivery and efficacy of MSCs in the context of regenerating bone, cartilage, muscle, cardiac, vascular, and nervous tissues. Future research should concentrate on identifying the distinct characteristics of the MSC niche, investigating the processes involved in MSC-scaffold interactions, and applying new technologies in stem cell treatment and biofabrication to enhance scaffold design. Research on large animal models and collaboration among materials scientists, engineers, and physicians are crucial to translating these advancements into clinical use.