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Piezo1-mediated mechanotransduction controls osteocyte maturation and dendrite development via a YAP-CCN-Src signaling axis
The treatment based on calcineurin inhibitors and their conversion to sirolimus alter the morphology in the rat testis
Abstract The effects of three-drug immunosuppressive regimens on the testis are still not fully known. The aim of this study was to evaluate the long-term effects of immunosuppressive protocols based on calcineurin inhibitors (CNIs) and their conversion to monotherapy with sirolimus on morphology, proliferation, and nuclear DNA fragmentation in the male gonad using an experimental model. For 6 months, male Wistar rats were treated with cyclosporin A (CsA), tacrolimus (FK-506), sirolimus (SRL), mycophenolate mofetil (MMF), and prednisone (Pred). The following protocols were used: CMP (CsA, MMF, and Pred), CMP/S (CsA, MMF, and Pred with conversion to SRL), TMP (FK-506, MMF, and Pred), and TMP/S (FK-506, MMF, and Pred with conversion to SRL). Morphological analyses, including morphometric analysis, immunohistochemical evaluation for proliferation (Ki67), and nuclear DNA fragmentation using the terminal deoxynucleotidyl transferase dUTP nick-end labelling (TUNEL) method in the testis, were conducted. In the testes of all the experimental groups, disorders in the organization of the seminiferous epithelium, a lower diameter and area of seminiferous tubules, and a lower percentage of Ki67-positive germinal cells than those in the control group were observed. A lower height of the seminiferous epithelium in the CMP, CMP/S and TMP/S groups than in the control group was noted. A higher percentage of TUNEL-positive germinal cells was detected in the CMP and TMP groups. In the groups with conversion to SRL, a lower diameter and area of seminiferous tubules and height of the seminiferous epithelium (TMP/S vs. TMP) and a lower percentage of Ki67- and TUNEL-positive cells (TMP/S vs. TMP; CMP/S vs. CMP) were revealed. The long-term administration of CNIs in multiple regimens can influence the course of spermatogenesis in the testes of rats, which manifests as morphological alterations in the seminiferous epithelium, vascular accumulation of collagen fibres in interstitial tissue, decreased proliferation of germinal cells and increased nuclear DNA fragmentation related to the apoptotic process. The conversion of treatment with CNIs to SRL also had adverse effects on the seminiferous epithelium; however, it had positive antiapoptotic effects. The obtained results may allow for a better understanding of changes in men undergoing immunosuppressive therapy and a preliminary assessment of which drug combination would be most beneficial in specific clinical cases.
Overlapping community and entropy of neighborhood information for identifying influential nodes in complex networks
Gene therapy delivery of anti-Müllerian hormone in prepubertal female domestic cats induces long-term sterilization
Abstract The uncontrolled reproduction of free-roaming domestic cats exacerbates their welfare challenges and the ecological pressure they exert on wildlife populations. Because of logistic and economic constraints, surgical sterilization alone cannot scale to control the reproduction of the hundreds of millions of intact cats worldwide. Herein, we report that the single administration of an adeno-associated viral vector delivering an anti-Müllerian hormone transgene to prepubertal cats can fully prevent pregnancy once females reach adulthood. Treated kittens were closely monitored for up to 21 months to assess long-term health, transgene expression, reproductive hormones, and reproductive function. The intramuscular injection was well tolerated and did not impact physical growth. The sustained expression of anti-Müllerian hormone did not impact spermatogenesis in males. However, it induced sterility in mated females by preventing breeding-induced ovulation and increases in progesterone associated with luteal phases, resulting in safe and potentially lifetime sterilization in the female domestic cat.
Ad hoc bandwidth requests and power conservation in 5G wireless networks with tiny cells
Optimization of cable tension in large-span cable-stayed bridges based on RBF neural network and improved sea-gull algorithm
IFN-γ-driven UBE2D3 upregulation impairs antigen presentation pathways and anti-tumor immunity in pancreatic cancer
Multi-modal fusion fault diagnosis for high-voltage transformers based on STFT-ResBIGRUNet
Research on location optimization and application of the gob-side entry retaining by roof cutting in close-distance coal seams
Efficacy, safety, and predictive biomarkers of neoadjuvant nab-paclitaxel and pembrolizumab in hormone receptor-positive breast cancer: A randomized pilot trial
Disentangling the cave centipede Lithobius stygius species complex through molecular phylogenetics and redescription of L. stygius s. str.
Abstract Distinguishing species is fundamental for obtaining reliable biological insights, yet due to their morphological similarity many species remain undetected until molecular methods are employed. This work uncovers species diversity in the caves of the Dinaric Karst (Europe), shedding light on the understudied cave centipedes. We focus on the taxonomically challenging species Lithobius stygius Latzel, 1880, the first scientifically described cave centipede from the Balkans. Multi-locus phylogeny and uni-locus species delimitation based on extensive sampling revealed that many morphologically and ecologically similar populations previously reported as L. stygius belong to at least five clades, consisting of numerous molecular operational taxonomic units. We propose some taxonomic changes, including reinstating species Lithobius luciani (Folkmanová, 1935) and Lithobius intermedius Folkmanová, 1946. By providing a detailed redescription of L. stygius based on the type and new material, addressing morphological variability, and providing reliable molecular characterization, we set the baseline for further investigations of taxa concealed under the name L. stygius . The species complex represents an interesting case for the study of its evolutionary history, indicating possible multiple cave colonizations. Although disentangling the species complex requires an appropriate molecular and morphological framework, it is invaluable for reliable species identification and recognition of true species diversity.
Enhanced hybrid deep neural network for EEG-based schizophrenia diagnosis using functional and temporal features
Abstract Schizophrenia is a complex psychiatric disorder that disrupts cognition, emotions, and social behavior. Timely and accurate diagnosis is essential for effective treatment. Traditional diagnostic methods relying on clinical assessments have limitations, including subjectivity and time consumption. To address these challenges, there is increasing interest in utilizing neuroimaging techniques like electroencephalography (EEG) for schizophrenia diagnosis. EEG provides direct measures of brain activity and can reveal unique patterns associated with the disorder. This study proposes a novel approach that utilizes EEG signals to accurately diagnose schizophrenia, aiming to overcome the limitations of traditional methods. EEG data was collected from two groups: individuals diagnosed with schizophrenia and a healthy control group. During a visual task, EEG signals were recorded and underwent preprocessing to remove artifacts and noise. The data was segmented into non-overlapping time windows, and functional and time-domain features were extracted. These features were then used as inputs to a hybrid deep neural network specifically designed for EEG data. The primary objective of the network was to distinguish between healthy individuals and those with schizophrenia. The proposed approach was benchmarked against established methods such as support vector machines and k-nearest neighbors, and it demonstrated superior performance. The evaluation was carried out using a robust k-fold cross-validation approach. Various performance metrics, including accuracy, sensitivity, and characteristic criterion, were used to assess the diagnostic accuracy and discriminative power of the network. The results showed that the hybrid deep neural network effectively identified individuals with schizophrenia. This study highlights the potential of EEG-based diagnostic approaches in accurately diagnosing schizophrenia and offers a promising avenue for reducing subjectivity and improving the efficiency of the diagnostic process. Future research should focus on expanding the dataset, investigating generalizability across different populations, and exploring potential clinical applications in real-world settings.
Electrocatalytic CO2 reduction to ethylene in an acid-fed membrane electrode assembly at 10 A
Abstract Electrocatalytic CO 2 reduction reaction (CO 2 RR) using membrane electrode assembly (MEA) systems requires complex regulation of protons, hydroxyls, carbonate ions and alkali-metal ions across both electrodes to efficiently produce multicarbon products. In acid-fed CO₂RR MEAs, excessive proton migration and accumulation on the catalyst surface suppress CO₂ adsorption and promote hydrogen evolution, leading to low Faradaic and energy efficiencies. Sluggish hydroxide transport further triggers carbonate precipitation, undermining system stability. Here we report an acid-fed membrane electrode assembly system for highly efficient CO 2 RR by integrating hydrazone-linked covalent organic framework (COF) and catalyst on the anion-exchange membrane to enable bidirectional pathway for hydroxide and potassium ions diffusion, while enhancing transport of CO 2 to the catalyst surface. As a result, the scaled-up MEA operates at a full-cell voltage of ~4.5 V under a total current of 10 A (current density of 204 mA cm⁻²), delivering a Faradaic efficiency of ~50% for CO₂-to-C₂H₄ conversion and maintaining stability for over 300 hours.
Structural functionalization of TEMPO modified Ni-MOF for electrocatalytic applications
Quantifying medical device cybersecurity risk with CVSS BTE
In-situ cross-linking mass spectrometry reveals compartment-specific proteasomal interactions and structural heterogeneity
Reformulation of soy sauce to reduce sodium content and assessment of manufacturer readiness, consumer acceptance, and shelf life
Design of a parameter self-tuning PID controller based on an ER-SLP for a variable-frequency air compressor in a rapid deballasting system
Contribution of amygdala to dynamic model arbitration under uncertainty
Abstract Intrinsic uncertainty in the reward environment requires the brain to run multiple models simultaneously to predict outcomes from preceding cues or actions. For example, reward outcomes may be linked to specific stimuli and actions, corresponding to stimulus- and action-based learning. But how does the brain arbitrate between such models? Here, we combined multiple computational approaches to quantify concurrent learning in male monkeys performing tasks with different levels of uncertainty about the model of the environment. By comparing behavior in control monkeys and monkeys with bilateral lesions to the amygdala or ventral striatum, we found evidence for a dynamic, competitive interaction between stimulus-based and action-based learning, and for a distinct role of the amygdala in model arbitration. We demonstrated that the amygdala adjusts the initial balance between the two learning systems and is essential for updating arbitration according to the correct model, which in turn alters the interaction between arbitration and learning that governs the time course of learning and choice behavior. In contrast, VS lesions lead to an overall reduction in stimulus-value signals. This role of the amygdala reconciles existing contradictory observations and provides testable predictions for future studies into circuit-level mechanisms of flexible learning and choice under uncertainty.