Robot-Assisted Complex Hilar Tumor Resection: A Case of Ectopic Adrenocortical AdenomaYunqiang Shi1,#, Kai Deng1,#, Xiaofang Bi1, Jie Xiong1, Meng Yang1, Lin Zhang1, Chunhui Wang1,*1Department of Urology, Yan ’an Hospital Afiliated to Kunming Medical University, Kunming 650000, China#Equal contribution*Corresponding authors:Wang ChunhuiDepartment of Urology, Yan ’an Hospital Afiliated to Kunming Medical University, Kunming 650000, China. Email: 13211604155@163.com

Vernicia fordii, a tropical and subtropical oil tree, is valued for its fruit but has a slow economic return. Intercropping can alter rhizosphere soil microorganisms, either promoting or inhibiting growth, and allow multiple harvests, speeding up economic returns. In this study, Polygonati odoratum, a Chinese herbal medicine, was intercropped with V. fordii, while non-intercropped V. fordii forest and single-crop V. fordii served as comparison areas. We studied the effects of rhizome intercropping on the soil microbial community by collecting rhizosphere soil samples, conducting 16S rDNA and ITS sequencing, and performing property analysis. Intercropping significantly improved soil quality, with increases of 19.77% in soil organic matter, 36.46% in available potassium, 26.67% in alkaline hydrolysable nitrogen, and a 38.70% enhancement in sucrase activity. Additionally, this planting method has notably altered the community structure of bacteria and fungi in the soil, adjusting their composition and abundance, thus positively impacting biogeochemical processes in the environment. After the implementation of the intercropping mode, the seedling height, ground diameter, and biomass of P. odoratum (a medicinal plant) all exhibited significant increases, with respective improvements of 4.16%, 9.75%, and 28.80%. Concurrently, the contents of flavonoids and saponins also rose, with enhancements of 32.92% and 13.92% respectively. These changes strongly attest to the remarkable effect of intercropping on enhancing the quality of P. odoratum. Moreover, an in-depth predictive analysis of soil microbial ecological functions revealed that intercropping not only enhanced the nitrogen-fixing ability of soil microorganisms but also effectively reduced the risk of plant diseases. Symbiotic network analysis reveals that intercropping enhances the connectivity of soil bacterial networks, increasing their complexity through the addition of network nodes. Compared to the monocropping systems of V. fordii trees and P. odoratum, the microbial networks in intercropped systems are more tightly connected. These changes in soil microbial community structure may be closely linked to environmental factors such as organic matter content and pH value. Intercropping encourages the proliferation of specific bacterial groups (including Actinobacteria, Bacteroidetes, Chloroflexi, and Verrucomicrobia) and fungal groups (such as Ascomycota and Basidiomycota). The study suggests that introducing P. odoratum alters the soil microbial community of V. fordii trees, making the rhizosphere microbial network denser and more complex. This research offers valuable insights for the management of Ford’s Fleabane plantations, with the potential to enhance agricultural strategies for greater efficiency and economic benefits.

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Context Organic resources application can increase soil nitrogen (N) sequestion and improve the pigsical structure while preventing soil compaction, yet the impact of vermicompost application on soil macro-and micro-aggregates as related to changes in soil organic N fractions within aggregates has not been studied well, especially in continuous protected vegetable fields with serious deterioration of soil structure. Methods We evaluated the effect of three fertilizer practices on soil dry aggregate size distribution, aggregate stability, particulate organic matter N (PON) and mineral-associated organic matter N (MON) distributions within different particle fractions, as well as their relationships in two soil layers (0-20 cm and 20-40 cm) in a protected tomato (twice a year) continuous cropping system. Treatments included commercial organic fertilizer applied (COF), reduced commercial organic fertilizer combined with vermicompost (RCOF+VC), vermicompost applied only (VC) in a 2-year field trial. Equal amounts of chemical inorganic fertilizers were applied for different treatments. Results Compared with COF, RCOF+VC was not conductive to soil macro-aggregation and aggregate stabilization in 20-40 cm, though larger amounts of organic matter were applied. The disadvantages could be due to reduced PON and MON concentrations within aggregates (being a complete loss in micro-aggregates), which were significantly correlated with soil macro-aggregation and stability characteristics. In comparision, VC had no significant disadvantages on soil macro-aggregation and stability characteristics, while effective in N rehabilitation by preventing degradation of organic N compounds in aggregates, especially in 0-20 cm. For all fertilizer treatments, most PON and MON (average 86.05%) were distributed in the macroaggregate-occluded fractions. The positive regulation of PON and MON from macro-aggregates was larger than that from smaller aggregates, showing the dominant role of organic N fractions within macro-aggregates for the quality of soil agglomeration structure. In all fractioned aggregate sizes, compared with PON, MON completely dominated due to its large mass proportions, regardless of the specific concentrations, demonstrating the MON in macro-aggregates as a primary fate and resevior pool of exogenous organic-derived N. Although with quite different numbers, the PON and MON in macro-aggregates functioned almost equally in promoting soil macro-aggregation. Whereas in the aspect of aggregate stabilization, MON in macro-aggregates played a more pivotal role. A direct regulating role rather than an indirect role through the conversion to MON was found for PON within macro-aggregates. Conclusions We suggest the vermicompost as a economical substitute for commercial organic fertilizer in terms of maintaining soil aggregate structure and the occluded organic N fractions.

Health disparities in pediatric, adolescent, and young adult (AYA) oncology remain a significant challenge, with socioeconomic status, geographic location, race, and ethnicity contributing to unequal access to care and poorer outcomes. Emerging technologies, including artificial intelligence (AI) and immersive tools such as virtual and augmented reality (VR/AR), offer transformative solutions to address these inequities. AI has demonstrated potential in enhancing diagnostic accuracy, tailoring treatment plans, and providing personalized patient navigation to guide families through complex care pathways. Immersive technologies have shown promise in delivering equitable supportive care, including VR-based psychological support, pain management, physical rehabilitation, and patient education. This paper explores how integrating AI and immersive technology tools into cancer care can enhance quality of life, and bridge gaps in care delivery for pediatric and AYA patients. Additionally, the increasing availability of internet-enabled devices presents an unprecedented opportunity to overcome traditional barriers to care in underserved populations. The paper also addresses critical challenges, including the digital divide, ethical considerations, and cost barriers, while proposing strategies for equitable implementation. By leveraging these technologies, healthcare providers can create more inclusive and effective treatment environments, ensuring that the benefits of innovation reach all patients, regardless of background or circumstance.

Quorum Sensing (QS) and Machine Learning (ML) hybrid systems represent a groundbreaking innovation in synthetic biology, offering unprecedented control and adaptability in microbial gene regulation and metabolic processes. QS, a microbial communication mechanism, is crucial for coordinating gene expression in response to population density, impacting behaviors such as biofilm formation, virulence, and resource optimization. However, traditional QS systems are constrained by their reliance on static, pre-programmed feedback loops, limiting their flexibility in dynamic, complex environments. This review highlights how integrating advanced ML algorithms—such as reinforcement learning and deep learning—into QS systems can overcome these limitations by enabling real-time data processing, predictive modeling, and dynamic feedback control. Through these innovations, QS-ML systems can autonomously adjust gene expression and metabolic outputs, making them more efficient and scalable in applications ranging from pathogen control to precision medicine and industrial biomanufacturing. Key case studies illustrate the successful deployment of QS-ML systems to combat antimicrobial resistance, optimize bio-production, and enhance therapeutic precision in cancer and immune modulation. Despite the clear advantages, challenges remain in data integration, system robustness, and regulatory oversight. Addressing these hurdles through interdisciplinary collaboration and developing scalable, multi-omics data platforms will be critical for advancing QS-ML systems from experimental settings to real-world applications. This review underscores the transformative potential of QS-ML systems in revolutionizing synthetic biology, with profound implications for personalized medicine, sustainable biomanufacturing, and environmental health.

Background: Eosinophilic esophagitis (EoE) is a recently defined chronic immune-mediated disease of atopic etiology with esophageal dysfunction and mucosal eosinophilic infiltrate. Among esophageal high-resolution manometry (HRM) parameters, intrabolus pressure (IBP) has shown the possibility to distinguish patients with mucosal inflammation, who benefit from proton pump inhibitors (PPI), from those with initial fibrosis and lack of response to treatment. In this study, we aimed to identify biomarkers able to identify which group a patient belongs to and obtain an early response. Methods: Combining diagnostic and esophageal function tests, proteomic and histological immunohistochemical analysis we studied 24 patients with EoE to extrapolate a protein profile from biopsies of the middle third of the esophagus analysis. Among them, 20 patients also underwent esophageal HRM. Results: IBP values were found to be significantly different among the controls, responsive and non-responsive patients, in relation to PPI treatment. Proteomic analysis identified 1,445 proteins, 456 shared between the two groups of patients, with 58 proteins identified as differentially expressed (DEPs) between the two groups of patients. Among all identified proteins, we found that, by immunohistochemistry, Gal-3 was overexpressed in patients’ responder to PPI, and with image analysis the difference between the two groups was statistically significant (% positive cells p<0.01, % positive area p<0.005) Conclusions: This study showed the chance of knowing forward the response to PPI therapy, improving patients’ personalized therapy and quality of life.

Core images provide a high-resolution dataset of the textures and fabrics of sedimentary rocks, but their availability is often limited by cost and/or poor core recovery. An alternative solution is to utilize advanced high-resolution micro-resistivity images acquired through wireline logging, such as the Formation MicroScanner (FMS). But interpreting FMS image logs requires specialized knowledge that not all geologists possess. In this study, we explore the potential of Generative Adversarial Networks (GANs) in generating realistic core images from FMS logs using unsupervised and supervised image-to-image translation models. We trained a total of 12 models, testing various combinations of FMS data input formats, image processing methods, GAN architecture, and training hyperparameters. The supervised pix2pixHD model trained using concatenated FMS pad images with a batch size of 4 produces the most realistic core images: these have low Root Mean Square Error (RMSE), high Peak Signal to Noise Ratio (PSNR) and high Structural Similarity Index Method (SSIM) values when compared to the ground truth core images. Our results also stress the importance of a diversified dataset to reduce bias and enhance the applicability of the trained models to other wells and fields. Blind testing with geologists shows that their classification accuracy for Dunham textures increases from 14% on FMS image logs to 73% on synthetic core images. The approach proposed here has thus the potential to transform the field of subsurface characterization by bridging the gap between the limited availability of core samples and the need for comprehensive geological facies classification.

In recent years, multimodal sentiment analysis has become a hot research topic at the intersection of natural language processing and computer vision. Especially in applications like short videos and social media, text, visual, and audio information collectively convey rich emotional expressions. However, efficiently fusing information from different modalities remains a challenge. Existing methods often suffer from performance degradation due to insufficient inter-modal information fusion or by treating each modality’s features equally. To address this issue, this paper proposes a Multimodal Information Fusion with Self-Attention (MIFSA) model based on self-attention mechanisms and information fusion. The model first encodes the extracted feature sequences through an encoder. Then, it utilizes a maximum mutual information method to optimize the correlations between text and visual modalities, as well as between text and audio modalities, combining text-visual and text-audio fused modalities with unimodal contrastive information for training. Subsequently, a self-attention mechanism is employed to dynamically assign weights to the fused features of text, visual, and audio. Finally, a multilayer perceptron is used for sentiment prediction. Experimental results show that MIFSA improves the Mean Absolute Error (MAE) and Pearson Correlation Coefficient (Corr) on the CMU-MOSI dataset by 2.27% and 1.13%, respectively, compared to the optimal model MSTFN; on the CMU-MOSEI dataset, it achieves improvements of 2.42% and 1.84%. The results from ablation studies and case analyses further validate the effectiveness of the MIFSA model in multimodal sentiment analysis tasks.

The splicing of pre-mRNA can be constitutive or alternative. The resulting transcripts may play significant roles in plant development and responses to environmental changes. Wild soybean, as a wild relative of cultivated soybean, has excellent traits such as alkali tolerance and is an ideal material for studying stress mechanisms and mining resistant genes. In this study, we identified a splicing factor GsSCL30a of the SR family that depends on the GsSnRK1 protein kinase. Y2H and BiFC assays verified the interaction between GsSnRK1 and GsSCL30a. In vitro phosphorylation experiments confirmed that GsSnRK1 could phosphorylate GsSCL30a, and six phosphorylation sites of GsSCL30a by GsSnRK1 were determined. qRT-PCR results showed that the expression level of GsSCL30a was highest in wild soybean leaves, and its transcription level was upregulated under alkali stress. Splicing factor reporter analysis found that GsSCL30a could self-splice the third intron, which contains multiple conserved regions of the GAAG motif. In addition, the phosphorylation of GsSCL30a by GsSnRK1 promoted its self-splicing. Y2H experiments proved that there is a physical interaction between GsSCL30a and the U1 snRNP-specific protein U1-70K, indicating that GsSCL30a plays an important role at the 5’ splicing site. We overexpressed GsSCL30a-GsSnRK1 in soybean hairy roots. It was found that OE# GsSCL30a-GsSnRK1 could synergistically enhance the tolerance of soybean to alkali stress. Our study revealed the response mechanism of GsSCL30a in soybean under alkali stress conditions, that is, GsSCL30a relies on GsSnRK1 for phosphorylation modification during the alkali stress process, which affects the activity of the splicing factor and then regulates the plant’s response to alkali stress, providing a new idea for improving the stress resistance ability of crops.

Different genomes of various organisms imply the creation of anatomical and physiological differences within their nervous systems, which translates into diverse cognitive or broader mental abilities among different species. These changes are largely based on structural mutations, such as duplications or inversions, though smaller changes like single deletions can also occur. The genes affected by these changes are associated with various functions and ultimately lead to different brain development, its structure and function. This work presents the most important type of genes and their changes that may affect the formation of the human brain. In this aspect, we review and discuss genes contribution to brain structures, as well as summarize recent knowledge regarding their involvement in various disorders.

Whether motor imagery (MI) engages the motor system or relies on perceptual/cognitive processes is a matter of debate. Here we used the size weight illusion to create dissociation between perception and action to address the nature of MI. Participants alternated lifting bricks of equal mass but where one brick was larger than the other, resulting in a perceptual illusion. Fifty-seven participants (M=20, F=37, 22.54.4 years; collected 2019-22) were divided into three groups differing in the modality used for training (MI and overt execution; OE) and exposure to the size weight illusion pre-training (one (MI-2) and five (MI-10 and OE) lifts of each brick). We hypothesized that the MI groups would use lifting dynamics post-training consistent with the illusion, whereas the OE group would maintain accurate lifting forces. Contrary to our hypothesis, the OE and MI-10 groups maintained the effect of the illusion post-training. In the MI-2 group, perception of the bricks’ weight reverted to the participant’s prior belief that large objects are heavy and they correspondingly adjusted their lifting force post-training. These results demonstrate that perceptual and motor processes are engaged during MI, and that the simulation of the motor component of the movement during MI guides the performed action.

This paper is mainly concerned with the asymptotic dynamics of stochastic diffusive coral reef ecosystems with L e ̵́ vy noise. Firstly, we prove the well-posedness and energy estimates of solution. Secondly, under some suitable conditions, we prove the existence and uniqueness of weak pullback mean random attractors and invariant measures. Finally, a large deviation principle result for solutions of stochastic diffusive coral reef ecosystems with L e ̵́ vy noise is obtained by a variational formula for positive functionals of a Poisson random measure and the method of weak convergence.

In this study, a new type of Labidocera fluviatilis has been collected and recorded forthe first time. L. fluviatilis was collected from the coast water of Banias Cityin the period between March and August(Spring and Summer) 2017 in three regions differ from each other in their environmental characteristics that make them distinct impact on the crustacean zooplankton, The samples were also accompanied with different hydrophysical and hydrochemical measurements in all sampling areas and in different depths. 14 individuals were collected, among which 11 females and 3 males. Results showed that this species appeared in all sampling areas and in different water layers. The species was found to occur in haline range of 31 to 38‰, pH of 6.7 to 8.2 and temperature of 25 to 33 0C. Results showed that this species appeared in all sampling areas and in different water layers.

Abstract :   It is possible to identify individual molecules through their unique noise particles in current nanocommunication signals.  Improved knowledge of the molecular origin and interaction of nanoparticle-based carbon nanotube-based electronic noise should lead to the development of electronics that use noise to improve their performance rather than degrade it. Introduction :Quantum interference or quantum parallelism gives us enormous computational power, especially in source coding, where information about the entire content is needed instead of individual inputs.  Molecular communication is the sending and receiving of information encoded in molecules  , while electromagnetic communication is the sending and receiving  of electromagnetic radiation from various nanoscale devices  . Of these methods, molecular communication and electromagnetic communication  are considered wireless methods.  In electromagnetic communication, electromagnetic communication between nanosensors  depends on the development and fabrication of two important parts, the nanoantenna and  its associated transceiver  . At the nanoscale, graphene-based antennas  are used to transmit EM waves. Graphene is an extremely thin single-atom sheet  of confined carbon atoms arranged on a crystal lattice  . Due to the extremely small dimensions of nanosensors, nanoantennas  need to operate at very high frequencies to be useful. However, using  graphene helps to solve this problem to a great extent.

Post-stroke angiogenesis improves structural and functional recovery, outlining the promises of pro-angiogenic therapies. Unfortunately, vascular endothelial growth factor (VEGF)-A-mediated angiogenesis resulted in mitigated outcomes, as it significantly increases the risk of exacerbating injury via destabilization of the cerebrovascular network. VEGF-E, a non-mammalian VEGF-A homolog, has been reported to promote stable neovascularization upon skin injuries, and thus represents an interesting safe alternative to promote post-stroke angiogenesis. C57BL6/J wildtype mice were subjected to ischemic stroke using transient middle cerebral artery occlusion (MCAo), and recombinant VEGF-E was intranasally delivered throughout the subacute phase. Our results indicate that VEGF-E reduces neuronal loss and improves motor recovery after stroke. VEGF-E attenuates cerebrovascular permeability at the injury site and increases the density of mature CD31+ microvessels. Furthermore, we show that VEGF-E reduces the events of microvascular stalls and improves brain endothelial cell coverage by perivascular cells, required for cerebrovascular stability. VEGF-E increases the density of angiogenic active CD105+ microvessels, while improving the recruitment of CD13+ pericytes, outlining synergistic effects on microvessel formation and stabilization. Using cell-based assays, we demonstrate that VEGF-E activates key pro-survival pathways in brain endothelial cells exposed to ischemia/reperfusion-like conditions, namely extracellular signal-regulated kinase (ERK)1/2 and P38 mitogen-activated protein kinase (MAPK) while preserving the tight junctions. Importantly, we report that the secretome of VEGF-stimulated brain endothelial cells improves perivascular cell migration that is required to mediate the interaction with endothelial cells. Our study indicates that VEGF-E promotes a stable neovascularization after ischemic stroke, paving the way to develop new strategies for therapeutic angiogenesis.

It is worthy of note that since the outbreak of insecurity in Nigeria, the economy of the country has remained in shamble and the lives of the people were jeopardized. This necessitated the government to form Community Policing. The essence of this is to help the security agents to tackle crime related activities especially in the local villages. It will also serve as a channel of information dissemination to Nigeria security agents and also serve as a mediator in inter community clash disputes. Systems theory was adopted as the theoretical framework for this study. The expository qualitative method of inquiry was used for data collection, which entails the in-depth acquisition of documentary material, and the data was analyzed using the content analysis technique. The study found, among others, that lack of information dissemination at the local villages has hampered the ability to apprehend criminals that are terrorizing the country. So, the formation of community police will aid in curbing criminal related activities. To curb these challenges, the study recommends that the Federal Ministry of Interior/Affairs, in collaboration with the Security personnel’s should recruit and train competent people that will be fully armed at the local villages for proper security.

Regulation of cellular metabolism is a central element governing the fate and function of T cells. However, the in vivo metabolic characteristics of rare cells, such as non-lymphoid tissue T cells, are poorly understood due to experimental limitations. Most techniques measuring cell metabolism require large cell numbers. The recent SCENITHTM method allows studying the metabolism of rare cells by flow cytometry. However, this technique requires cells to be isolated and cultured ex vivo, which may alter their metabolism. Here, we propose a new experimental approach, called in vivo SCENITH, to investigate the cellular metabolism of T cells in vivo at steady state in the spleen and lungs. For this purpose, we administered the metabolic modulators directly in mice, instead of applying these reagents ex vivo, as in the classical SCENITHTM method. Whereas ex vivo manipulation impacted viability and phenotype of T cells, this toxic effect was not observed in the in vivo SCENITH. We observed that conventional and regulatory T cells shared similar metabolic profiles. Importantly, whereas spleen T cells used both oxidative phosphorylation and glycolysis, the metabolism of T cell in the lungs was mainly based on oxidative phosphorylation. Finally, metabolic inhibitors that interfere with protein translation and energy availability downregulated Foxp3 expression in regulatory T cells. These results describe an expansion of SCENITHTM that allows to measure the metabolic profile of rare cells in vivo, revealing a high dependence on oxidative phosphorylation of lung T cells.

Based on Fourier series, we adapt an approach discussed in a recent work on the Laplace operator to classical results obtained in the literature, describing the singularities of solutions to a fourth-order elliptic problem on a polygonal domain of the plane that may appear near a concave corner. We demonstrate how the Fourier series method provides explicit decomposition and precise description of the coefficients of singularities of the solution. As a main result, explicit and sharp estimates with respect to the opening angle parameter can be obtained via this method. We recall that such estimates can be useful for the asymptotic analysis of solutions near corners where the opening angle generates a jump in singularity in Sobolev's exponent.

Pediatric bronchoscopy is a crucial diagnostic and therapeutic procedure widely employed to assess and manage respiratory conditions in children. Despite its utility, bronchoscopy is frequently associated with postoperative complications, such as laryngeal edema, hypoxemia, and respiratory distress. These complications can significantly delay recovery and prolong hospitalization. For instance, hypoxemia is particularly concerning in pediatric patients due to their smaller airway diameters and higher metabolic rates 1,2. Consequently, effective postoperative management is critical to reduce these risks. Nursing interventions, such as continuous monitoring of oxygen saturation, airway management, and sedation protocols, play an essential role in mitigating these complications 3,4.Nursing interventions have the potential to mitigate these complications; however, their overall effectiveness in pediatric populations remains under-investigated. This meta-analysis aimed to evaluate the impact of nursing interventions on the incidence of postoperative complications following pediatric bronchoscopy. A random-effects model was applied to calculate pooled odds ratios (OR) with 95% confidence intervals (CI), estimating the effect of nursing interventions on postoperative complications. Heterogeneity was assessed using the I 2 statistic, and publication bias was evaluated using funnel plots and Egger’s test. Nursing interventions were associated with a significant reduction in postoperative complications, with a pooled OR of 0.22 (95% CI: 0.13, 0.37; p < 0.0001). The heterogeneity across studies was low (I 2 = 0%), indicating consistent results across the included studies 1,3,6. Funnel plot analysis revealed slight asymmetry; however, Egger’s test did not indicate significant publication bias (p = 0.1213) 7. Given the consistency of these findings, integrating structured nursing protocols into postoperative care has the potential to substantially improve patient outcomes. Further research is warranted to explore the long-term impacts and cost-effectiveness of these interventions 9,10.

BACKGROUND: Health-related quality of life (HRQoL) has been a widely used measurement method in pediatric rehabilitation. Although self-reporting is the gold standard, parent reports are commonly used in adolescents with cerebral palsy. Explaining the agreement and differences between adolescent self-reports and caregiver/physiotherapist reports could provide a comprehensive perspective on adolescents with cerebral palsy. METHODS: Ninety-seven adolescent and parents and their physiotherapists completed the Pediatric Quality of Life Inventory (PedsQL). Intraclass Correlation Coefficients (ICCs) and The ‘paired sample-t’ test evaluated group agreement and differences. RESULTS: The agreement on HRQoL was found to be excellent between adolescent-caregivers (ICC: 0.876), adolescent-physiotherapists (ICC: 0.872) and caregiver-physiotherapists (ICC: 0.926). The agreement decreased from excellent to moderate in the Pain and Hurt (ICC:0.492-0.604) and Fatigue (ICC:0.484-0.604) subdomains. There was a significant difference between adolescent-parents reports and adolescent-physiotherapist reports (p<0.001), but no significant difference was found between caregiver and physiotherapist reports. CONCLUSION: Compared to physiotherapists and their families, adolescents with cerebral palsy perceive their health-related quality of life better. Although there is an excellent agreement between adolescents with CP, parents and physiotherapists, agreement decreases in subjective areas such as pain and fatigue.

Background: Low voltage bridge mapping (LVBM) is an approach to AVNRT ablation that has been postulated to facilitate the procedure. In our center, AVNRT ablations were performed with the traditional RF current approach using the CARTO mapping system. The use of LVBM in children has been well described with cryoablation but not with RF. LVBM was introduced in our center in April 2023 and is now routinely used for all AVNRT RF ablations. The aim of this study was to analyze how the introduction of the LVBM influenced the results of the pediatric AVNRT ablations using the RF current. Methods: We analyzed all AVNRT ablations performed between January1,2019, and June30,2024, and compared traditional and LVBM approaches. Results: The study group (LVBM) consisted of 40 and the control group of 61 children. Both groups did not differ significantly regarding age, body weight, and sex distribution. In the LVBM group, the total time of RF applications was significantly shorter, and the number of RF applications was smaller than in the control group. Total procedural time did not differ significantly between the groups. The success rate at 3 months follow-up was higher in the LVBM group but failed to differ statistically. No complications were reported in either of groups. Conclusions: The introduction of the LVBM in RF AVNRT ablations in children allows for limiting the number and time of RF applications required, without prolonging the total procedure time. Our experience shows LVBM can also be effectively used in RF ablations of AVNRT.

In bacteria, the regulation of gene expression involves complex networks that integrate both transcriptional and post-transcriptional mechanisms. At the transcriptional level, nucleoid-associated proteins (NAPs) such as H-NS, HU, Lrp, IHF, Fis and Hfq are key players as they not only compact bacterial DNA, but also regulate transcription. Small non-coding RNAs (sRNAs), on the other hand, affect bacterial gene expression post-transcriptionally by base pairing with the target mRNA. Interestingly, certain NAPs also influence the function of sRNAs and, conversely, sRNAs themselves can modulate the activity of NAPs, creating a complex bidirectional regulatory network. Here, we summarise the current knowledge of the major NAPs, focusing on the specific role of Hfq. Examples of the regulation of NAPs by sRNAs, the regulation of sRNAs by NAPs and the role of sRNAs in nucleoid structuring are also discussed. This review focuses on the cross-talk between NAPs and sRNAs in an attempt to understand how the interplay between cellular proteins and regulatory RNAs contributes to the fine-tuning regulation of bacterial gene expression.