Treatment of prepubertal labial adhesion with topical estriol: a case reportFahrur Rozi Illahi1, Bobby Indra Utama2, Yulia Margaretta Sari2Obstetrics and Gynecology Department, Andalas University – M Djamil Central Hospital of Padang.Urogynecology Division - Obstetrics and Gynecology Department, Andalas University – M Djamil Central Hospital of Padang.

Aim: This study aims to refine the anticholinergic burden (AB) scale developed in our previous research by incorporating additional drug properties, such as Lipophilicity and Molecular Weight, and implementing a new weighting approach to address the varying influence of each drug property on anticholinergic burden. The objective is to improve the scale’s predictive accuracy and compare its performance against established scales. Methods: The scale, which covers 87 drugs, was expanded to include seven drug properties, combining new properties, Lipophilicity and Molecular Weight, with previously utilised experimental and in silico ADME, physicochemical, and pharmacological properties. A weighting approach was introduced to the hierarchical clustering process to account for the differential impact of each drug property on AB. The performance of this revised scale was evaluated through 10-fold cross-validation against the clinical Anticholinergic Cognitive Burden (ACB) scale and the non-clinical Anticholinergic Toxicity Scores (ATS) scale. Results: The scale showed improved alignment with the ACB and ATS scales, agreeing with the rankings of 54 out of 87 drugs and 16 out of 25 drugs respectively. The Area Under the Receiver Operating Characteristic Curve (AUROC) indicated strong performance. The ML-ACB and ACB has an AUC of 0.99 and 0.81 respectively, whilst the ML-ACB and ATS had an AUC of 0.96 and 0.62. Conclusion: The ML-ACB scale offers improved alignment with the established ACB scale. This highlights the potential of the ML-ACB scale as a valuable tool for clinical and research applications, providing a data-driven alternative that closely correlates with existing validated scales.

During the botanical explorations in the grasslands of Pilibhit Tiger Reserve (Uttar Pradesh), the authors came across an interesting species of Careya herbacea Roxb. of the family Lecythidaceae. The species is very poorly known in India. A detailed description, color photographs, and note on ecology are provided.

Despite status as a game species in the western United States, rigorous monitoring of dusky grouse (Dendragapus obscurus) populations is limited. Obtaining an adequate number of observations for effective population monitoring of dusky grouse is challenging due to difficult-to-reach montane habitats, cryptic behaviors, and limited personnel, time, and funds at conservation agencies. While habitat accessibility and survey effort constraints may be outside a manager’s control, identifying the most effective protocols to better detect a target species is possible and will improve monitoring programs. Our objectives were to 1) evaluate field-based protocols for maximizing dusky grouse detections and 2) identify survey conditions and timing that maximize the probability of detecting dusky grouse in western Montana. We conducted replicated point-count surveys with and without electronic playback in spring and summer 2019, and spring surveys solely with electronic playback in 2020–2021. We used N-mixture models to compare the probability of detecting dusky grouse in spring verse summer sampling, and evaluate the effects of electronic playback of grouse calls, route type (off-trail, trail, and road), weather, background noise, day, and time on probability of detection. Spring sampling yielded significantly more dusky grouse detections than summer sampling. The use of electronic playback of female calls in the spring increased detection probability but chick distress calls during the summer did not improve detection rates. The probability of detecting a dusky grouse was similar across the different route types (off-trail, trail, and road), and maximized on clear days, with little wind and background noise, with surveys occurring 9–162 minutes post-sunrise during 3–23 May. By examining the effects of different factors on dusky grouse probability of detection, our results provide necessary information for the development of effective protocols for field surveys for population monitoring of dusky grouse.

This research employs Martins, Fernandes, and Nascimento (MFN), a statistical confidence interval estimation method for information theory quantifiers, Permutation entropy (𝐻 𝑠), and Fisher information measure (𝐹 𝑠), encompassing financial assets' daily closing price time series. Specifically, we examine the five more relevant cryptocurrencies, considering market cap and volume: Bitcoin (BTC), Ethereum (ETH), BNB, Solana (SOL), and XRP. At the same time, we investigate two stock market indexes, the S&P 500 and NYSA Composite (NYA), one commodity (Gold), and one exchange rate (EUR/USD). Based on the values of 𝐻 𝑠 and 𝐹 𝑠 , we construct the Shannon-Fisher Causality Plane (SFCP), which allows us to quantify disorder and evaluate randomness in the daily closing prices of various financial assets. Also, we provide novel insights related to the SFCP with density contours. Our findings reveal that XRP, BNB, and BTC are positioned close to the random ideal position (𝐻 𝑠 = 1, 𝐹 𝑠 = 0) on the SFCP, indicating a higher level of disorder, a low level of predictability, a high level of informational efficiency, a low levels of informational asymmetry and speculative activity. Otherwise, S&P 500, NYA and Gold are further from this random ideal position, suggesting a higher susceptibility to market inefficiencies and speculation. Moreover, cryptocurrencies are characterized by less dense density contours with high 𝐻 𝑠 and low 𝐹 𝑠. In contrast, classical financial assets are marked by denser density contours with low 𝐻 𝑠 and high 𝐹 𝑠. Specifically, XRP, BNB and BTC showed less dense contours than the other financial assets. Gold, NYA and S&P 500 showed the densest density contours. The Principal Component Analysis (PCA) technique validated our findings, verifying that cryptocurrencies, S&P 500, NYSA and Gold are safe haven financial assets. Our results underscore the potential of these cryptocurrencies to provide more reliable signals for investment decisions, thereby reducing risks associated with information asymmetry and speculative trading.

Constructing a Wireless Nerve Electrical Stimulation System to Repair Peripheral Nerve DefectsBo Wang1*, Changfeng Lu1, Xiaojin Luo2, Shuai Han1, Guixi Zhang3, Yue Cui2✉, PeixunZhang1✉1Department of Orthopedics and Trauma, Peking UniversityPeople’s Hospital; Key Laboratory of Trauma and Neural Regeneration (Ministry of Education/Peking University), National Center for Trauma Medicine, Beijing, China.*The first author is now working at Beijing Jishuitan Hospital after graduated from Peking University from July, 2021.2 School of Materials Science and Engineering, Peking University, Beijing, China.3Hongkong University Shenzhen Hospital, Shenzhen,China.Correspondence: [email protected]; [email protected]: This study was supported by the Beijing National Science Foundation (7212121)， National Natural Science Foundation of China (22278003, 52072007), Beijing Science and Technology Rising Star Program Foundation (20220484233); Peking University People’s Hospital Research and Development Fund (RDH2020-01); National Center for Trauma Medicine (BMU2020XY005-01, BMU2021XY008-01); Shenzhen City Trauma Sanming Project (SZSM202011001); National Key R&D Program of China (No. 2018YFB1307301).AbstractPurpose: The repair effect of peripheral nerve injury mainly depends on rapid regeneration of proximal axons, accurate docking, and effective nerve re-innervation of target organs. Accordingly, identifying effective methods to protect the functional state of target organs and realize rapid regeneration of proximal nerve fibers is of great significance. The purpose of this study is to build a nervous electrical stimulation system powered by electromagnetic induction and evaluate its repair effect on a rat sciatic nerve defect model.Methods: Biodegradable materials [magnesium (Mg), polylactic acid (PLLA), chitosan, and silk fibroin] were chosen to build thein vivo part of the wireless electrical nerve stimulation system (including a receiving coil, electrode, and Mg-PLLA conductive scaffold) by three-dimensional printing and electrostatic spinning technology. Electromagnetic induction properties of the receiving coil, and mechanical properties and cytotoxicity of the conductive scaffold were studied in vivo . The effects of electric field stimulation of alternating current (AC) on the migration and growth of dorsal root ganglion neurons and secretion of Schwann cells were studied. A rat sciatic nerve defect model of 10 mm was established and repaired with the wireless electrical nerve stimulation system. The repair effects were evaluated by motor function recovery, muscle recovery, electrophysiological detection, morphological analysis of regenerated axons, and quantity analysis of motor end plates.Results: The wireless neural electrical stimulation system generates effective electrical signals through the electromagnetic induction coils in vitro and in vivo , and shows good mechanical properties and biocompatibility. Specific AC stimulation promotes neurotrophic factor secretion by Schwann cells. The effect of 1-h daily electric field stimulation on Schwann cell secretion mainly took effect within 24 h. The effect of the wireless electrical nerve stimulation system in repairing the sciatic nerve defect in rats was significantly better than that of the simple conductive scaffold group and inferior to the group repaired by an autologous nerve graft. However, the degree of myelination of regenerated nerve fibers in the wireless electrical nerve stimulation group was similar to the autologous nerve repair group.Conclusion: An implantable electrical nerve stimulation system without battery implantation was successfully constructed. The system acquired effective electrical signal stimulation through radio magnetic induction, and the conductive nerve scaffold was used as a carrier to accurately stimulate the injury site. The system could effectively promote the repair of rat sciatic nerve defects.KEY WORDS: Peripheral nerve injury, Electrical stimulation, Wireless, Schwann cells, Nerve defect

Depression is a mental disorder that has become a serious global health problem with cases increasing every year, particularly among young adults. This study aimed to explore the antidepressant effect of the ethanol extract of Gynura procumbens (EEGP). In all, 20 male Balb/c mice were divided into five groups, each of which contained four mice: normal group; negative control; and extract group E1 (200-mg/kg BW), E2 (400-mg/kg BW), and E3 (600-mg/kg BW). The normal group was not given any treatment, whereas the other groups were induced using unpredictable mild stress (CUMS) for 28 days. The antidepressant activity was assessed using a forced swim test and a tail suspension test. In this study, CUMS induced changes in the weight of the mice, the emergence of abnormal behaviour, and abnormal histological features of the hippocampus. EEGP with a dose of 200-mg/kg BW to a dose of 600-mg/kg BW could reduce the duration of immobility when compared with the negative control group. EEGP possessed antidepressant activity by reducing the duration of immobility. Thus, further research is needed to understand the mechanism of action of the EEGP antidepressant activity.

This review dissects the reintegration landscape of prisoners in India, revealing social stigma, limited employment opportunities, and fragmented family support as formidable roadblocks. Navigating effective prisoner reintegration transcends opening prison doors, but explores dismantling societal chains. This study analyzes how societal biases, economic barriers, and strained relationships can significantly hinder reintegration efforts. It questions obstacles posed by current policy frameworks while prescribing a path forward. Through conducting a coherent policy analysis and evaluating best global practices, this review identifies prime areas of development. This review recommends initiatives to enforce a robust reintegration ecosystem in India through the inclusion of bolstering existing schemes with increased funding and implementation, bridging the skills gap through vocational training, forging stronger community connections through support groups, and prioritizing mental health services to former offenders to reduce recidivism. This review intends to pave the way for a future where prison becomes a transformative pause, not a permanent sentence.Key Words: Prisoner Rights, Rehabilitation, Recidivism

As benchmark image datasets expand in sample size and feature complexity, the challenge of managing increased dimensionality becomes apparent. Contrary to the expectation that more features equate to enhanced information and improved outcomes, the curse of dimensionality often hampers performance. This paper reviews existing literature on filter feature selection techniques applied to image features, highlighting when they are applied to both classical and deep-learning-based feature extraction methods. Additionally, this study explores how different feature selection methods behave when applied to image features through big data technologies. Different experiments were performed to compare the results when using feature selection techniques with various reduction percentages. Experimental results demonstrated that an important reduction of the extracted features provides classification results similar to those obtained with the full set of features. Furthermore, applying dimensionality reduction techniques outperforms, in some cases, the results achieved using broad feature vectors.

Since there exists a single point of server failure in conventional centralized federated learning, the decentralized federated learning (DFL) framework has become increasingly popular in recent years. However, when a large number of edge devices participate in DFL, it requires frequent model interactions between edge devices and long convergence time. In this work, we combat the impact of device heterogeneity in the large-scale DFL framework. To improve communication efficiency between edge devices, we propose a decentralized edge devices clustering (DEDC) approach to adaptively group edge devices with dense connectivity and similar data distributions into one cluster and form a novel multi-cluster decentralized federated edge learning (MD-FEEL) framework. We propose an asynchronous algorithm in the formed MD-FEEL framework, which consists four steps, i.e., local stochastic gradient descent (SGD) update, gradient consensus, intra-cluster model aggregation and inter-cluster model aggregation. We prove the convergence of our proposed asynchronous MD-FEEL algorithm on a non-convex setting and elaborate on the effect of some hyperparameters. Empirically, we evaluate our proposed asynchronous MD-FEEL on the MNIST and CIFAR-10 datasets. The simulations show that our proposed asynchronous MD-FEEL can perform better in terms of convergence speed and generalization performance than some benchmark algorithms.

This research introduces Intelligent Car Learning for Mobile Robot Path Planning (ICLMRPP). The primary objectives of these techniques are to expand the best minimum path distance, minimize energy consumption, ensure a smooth trajectory, minimize task completion time, reduce identification risk, enhance communication reliability, prioritize missions, maximize obstacle avoidance, and improve environmental sensing. The robot operates in both static and dynamic environments, utilizing a grid map. The holonomic and non-holonomic constraints related to car learning mobile robots are considered. The Multi-objective Deep Q Network (MODQN) algorithm is proposed to address the ICLMRPP problem. The obstacle avoidance, implemented using DQN in the proposed MODQN, incorporates nine improvements. The proposed algorithm is compared to the Multi-objective Double Deep Q Networks (MODDQN) technique. Experiments on a car learning mobile robot validate the efficacy of the proposed algorithm techniques. This work demonstrates that the proposed MODQN algorithm, when applied to ICLMRPP problems, generates safe paths with collision avoidance, optimized path distance efficiency, and practical implementability. The simulations of MODQN and MODDQN are deemed acceptable, with simulation and experimental deviations less than 3%, and a path distance error of 1.125%.

Nigeria has seen outbreaks of multiple infectious diseases, a major public health concern, in the past ten years, including the Ebola virus in 2014, monkeypox in 2017, COVID-19 in 2020, Lassa fever in 2022, measles in 2023, diphtheria in 2023, and the current cholera outbreak in 2024. This emphasizes the importance of implementing a robust infectious disease surveillance system for illness response, prevention, and control. This review examines the current status of infectious disease surveillance system in Nigeria and its usefulness in preparing for future outbreaks. A network of laboratories, community health workers, health facilities, and epidemiology units was established during the COVID-19 epidemic by the Nigeria Centre for Disease Control (NCDC), which is essential to disease surveillance. One of the surveillance system’s tiers, state epidemiology units, was in charge of overseeing the gathering and reporting of regional data. Community health workers also carried out contact tracing and public health education as a grassroots method of disease surveillance. The NCDC adopted the Surveillance Outbreak Response Management and Analysis Systems as a primary digital surveillance platform for implementing the Integrated Disease Surveillance and Response system, which is specifically tailored for the surveillance of priority diseases of public health importance in Nigeria. This was done to effectively improve the surveillance capacity and data management. It is critical to enhance the current surveillance system’s ability to monitor, anticipate, and quickly respond to disease outbreaks. The COVID-19 outbreak highlighted the need for surveillance system improvement, particularly gaps that need to be closed to monitor future outbreaks or resurgences. In order to fortify the surveillance system for infectious diseases, it is imperative to continue utilizing the knowledge gained from prior outbreaks, enhance data collection, enhance national and sub-national surveillance systems, and enhance laboratory surveillance systems with precise data gathering and dissemination.

This work sheds lights on the complex gene regulatory networks underlying heat stress response and tolerance in chickpea ( Cicer arietinum L.) using a transcriptomic approach integrated with key phenotypic traits. Two pairs of Near Isogenic Lines (NILs) derived from a cross between early- (E) and late-flowering (L) genotypes (224E, 224L, 309E and 309L) and a reference cultivar ICC 4958 were subjected to high temperature (38/28 oC (day/night) for 4 days during the pod set) during the seed-filling stage, Heat stress impacted seed yield, revealing significant differences between early and late flowering lines primarily by reducing seed number due to fertilization failure. The ICC 4958 and 224L genotypes were more severely affected than the 309E and L and 224E lines. The differential gene expression profiles highlighted genotype-specific responses to heat stress, with both the 309 lines exhibiting greater heat tolerance and fewer differentially expressed genes compared to 224E, 224L and ICC 4958, indicating their higher resilience to heat stress. Key responses included significant changes in photosynthesis-related genes, alterations in primary and secondary metabolism, and modulation of phytohormone pathways, which collectively contribute to the 309 lines’ ability to cope with and recover from heat stress. The efficient recovery mechanisms observed in early flowering lines, such as rapid re-establishment of photosynthetic functions and effective nutrient redistribution, underline their potential for maintaining yield under heat stress conditions.

Background: Hypertension is the leading cause of preventable deaths globally, yet reports on its burden and risk factors in rural Sub-Saharan Africa have been inconsistent. This study aimed to assess the prevalence, awareness, and factors associated with hypertension among adults in a rural community in southwestern Uganda. Methods: A baseline survey was conducted in Ngango, Mbarara district, involving adults aged 18-79 from eleven villages. Research assistants and community health workers enrolled consenting participants from their homes using the WHO STEPS questionnaire, gathering demographic, behavioral characteristics (e.g., tobacco and alcohol use), and lifestyle factors including dietary habits and physical activity. Blood pressure (BP) readings were taken three times. Hypertension was defined as BP ≥140/90 mmHg or self-reported use of antihypertensive medication. We used logistic regression to identify factors associated with hypertension. Results: A total of 953 adults were enrolled, with a median (IQR) age of 43 (30-57) years, 61.5% female and only 43.5% recalled ever having a BP measure. The prevalence of hypertension was found to be 27.3% with 61.5% unaware of their condition. Only 27.7% receiving treatment and 65.3% had controlled BP. Despite 66.8% reporting good physical activity, 63.7% were overweight. Key factors associated with hypertension included being over 40 years old (OR 2.26), consuming fewer than three servings of fruits or vegetables weekly (OR 1.62), and being overweight or obese (OR 1.57 and OR 2.73, respectively). Conclusion: The prevalence of hypertension in rural southwestern Uganda is high, highlighting the need for targeted interventions, particularly in a relatively young and physically active population

Objective To investigate the network structure of psychological symptoms in non-lockdown populations during the COVID-19 pandemic’s latter stages and cross-validated this structure in lockdown-affected populations. Methods We conducted a cross-sectional survey from December 12, 2022, to January 18, 2023. Psychological symptoms were assessed using the Beck Anxiety Inventory (BAI), Beck Depression Inventory (BDI), Athens Insomnia Scale (AIS), Connor-Davidson Resilience Scale (CD-RISC), Post-traumatic Stress Disorder Checklist-Civilian Version (PCL-C), and World Health Organization Quality of Life Scale-Brief Version (WHOQOL-BREF). Regularized partial correlation network analysis (EBICglasso) constructed psychological symptom networks for students with (n = 780) and without (n = 1201) lockdown experience. We assessed node centrality, network stability, and conducted a network comparison test to examine global strength, structure, and specific edge strength. We also explored symptom clustering using the community detection algorithm (Walktrap). Results: Depression had the highest centrality in both groups’ symptom networks. Post-traumatic symptoms were significantly stronger in the lockdown group (p = .034), and the lockdown group exhibited a stronger correlation between anxiety and post-traumatic symptoms compared to the non-lockdown group (p = .002). Conclusions: The psychological symptom networks of Chinese university students, both affected and unaffected by lockdown, were largely similar in the post-pandemic era, with some variations. Notably, the lockdown group showed increased prominence and impact of post-traumatic symptoms, underscoring the need for targeted interventions. Addressing these symptoms can effectively mitigate psychological distress in this demographic during the pandemic’s latter stages.

The Himalayan orogen is a classic fold-thrust belt in a collisional plate tectonic setting. Quantifying magnitudes and determining patterns of crustal shortening in the Himalaya is therefore crucial for understanding deformation in convergent plate margins. However, gaps in our knowledge of various sectors of the Himalaya remain primarily due to lack of studies that combine geologic mapping with detrital zircon geochronology and kinematic history analysis. The Okhaldhunga region in eastern Nepal is one such area. In this study, we present a new geological map, two crustal-scale balanced cross-sections and kinematic restorations to reveal the kinematic history of Himalayan fold-thrust belt of eastern Nepal. New zircon U-Pb ages from fourteen samples and igneous zircon U-Pb ages from four samples show that the Okhaldhunga window primarily exposes the Ramgarh thrust sheet, composed of Paleoproterozoic Lesser Himalayan rocks and a hinterland dipping bumpy-roof duplex comprising Paleo-Mesoproterozoic Lesser Himalayan rocks and middle Paleozoic Gondwana Sequence rocks. Neoproterozoic-Cambrian Greater Himalayan rocks in the hanging wall of the Main Central thrust are exposed toward the south in the synformal Mahabharat Range and in the north in the Rolwaling-Sagarmatha region. A new minimum shortening estimate of ~500 km for rocks structurally below the South Tibetan detachment indicates eastward decline in shortening rates in the Himalayan fold-thrust belt.

The rapid development of Artificial Intelligence (AI) algorithms has created a need for a resource-optimised hardware accelerator. Among various platforms, Coarse-Grained Reconfigurable Array (CGRA) have gained importance as on-edge accelerators. They comprise of heterogeneous Processing Element (PE) matrix, which allows for high flexibility and parallelisation of calculations. They are mainly used for speeding up Data Flow Graph (DFG) execution. We aim to provide a general purpose, highly parameterised, and flexible architecture for AI on-edge data crunching. We propose a CGRA with a vector extension which allows for dynamically adjustable precision of calculation while maintaining a desired performance-power-area optimisation. It targets 4 bits integer (INT4) and 8 bits integer (INT8) quantization for fast and efficient Neural Network (NN) processing. In this paper, we examined hardware costs required to support the vector extension functionality. We synthesised the design on the 40nm Standard-Cell technology from TSMC. The obtained results show that the proposed extension attains on average 28.2% decrease in power consumption and 21.6% decrease in area compared to a reference design of the same computation power.

During a lichenological survey on a semiarid area with huge changes in land use in the western slopes of Binalud Mt., two species of Sarcogyne Flot. (Acarosporaceae) were found. The species S. calcifraga is recorded for the first time in Iran. S. clavus is added to the known lichen biota of the province Razavi Khorasan, NE Iran. A comparison on the base of characters distinguishing these two species from the most similar Sarcogyne taxa is done. A key for the known species of Sarcogyne in Iran is also provided.

Recent studies combining electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have shown promising results by correlating EEG characteristics with the spatial information provided by fNIRS. The present study aims to analyze the topographical effect of auditory stimulus intensity on cortical activation using fNIRS and to correlate this hemodynamic response with auditory evoked potentials (AEPs) P1, N1, and P2 and their possible habituation. Forty volunteers (13 males, 27 females; mean age = 22.27 ± 3.96 years) participated in this study. The experimental section involved the presentation of complex tones of different intensities (50-, 70-, and 90-dB SPL) including 7 different frequencies (400, 850, 1150, 1650, 1950, 2450, 2750 Hz), in blocks of five stimuli, while EEG and fNIRS signals were recorded. Our results indicate that increasing sound intensity led to amplitude changes in AEPs, and enhanced neural recruitment in auditory and prefrontal cortices, as analyzed by fNIRS. Correlation analyses suggest a prefrontal source for the P2 component. In addition, the observed correlation between the habituation index and specific prefrontal cortex channels in the inferior and superior frontal gyri would suggest the involvement of cognitive resources in the habituation process to block stimuli. These findings provide insight into the relationship between auditory stimulus intensity and neural engagement, with potential implications for understanding auditory perception in both healthy and clinical populations.

Background. Chronic venous disease (CVD) is one of the most common disorders of peripheral vessels. The search for an optimal treatment option is a challenging issue. Micronized purified flavonoid fraction (MPFF) is expected to act on the different mechanisms involved in CVD pathogenesis. Considering the high prevalence of CVD in general population, its significant impact on health-related quality of life in both younger and older patients, this study was brought up to study the effects of pharmacotherapy with MPFF and invasive treatment with EVLA, either alone or in combination, on the key serum biomarkers of vascular inflammation and remodeling, and patient quality-of-life (QoL). Objective. To study the effects of MPFF, EVLA, and the combination on vein-specific inflammatory biomarkers QoL in CEAP C2-C3 patients with varicose veins. Methods. In this prospective cohort study all subjects (N=95) received compression therapy and were allocated non-randomly to: control (compression only); MPFF; EVLA without adjuvant MPFF; and EVLA plus MPFF. Serum levels of E-selectin, MCP-1, VEGF, MMP-2 were measured, and a QoL questionnaire (CIVIQ-20) performed. Results. Treatments were associated with significant reductions in inflammatory biomarkers including E-selectin, MCP-1, and VEGF for MPFF (p<0.001), and E-selectin, MCP-1 and MMP-2 for EVLA (p<0.001). MPFF plus EVLA was associated with reductions in all studied biomarkers (p<0.001). CIVIQ-20 was improved by 23%, 29%, 36% and 40% at 2 months in the compression only, MPFF, EVLA, and EVLA plus MPFF groups, respectively. Conclusion. Reductions in serum biomarkers and improvement in QoL appeared greatest among patients treated with EVLA plus MPFF. Highlights: MPFF improves biochemistry and quality of life in chronic venous disease

1 INTRODUCTIONNeuroblastoma is an embryonic tumor derived from the neural crest with migratory neuroectodermal cells (1). It is one of the most common extracranial solid tumors in infants and children. More than 90% of neuroblastoma cases occur in children under 5 years old (2,3). The clinical signs and symptoms of neuroblastoma are highly dependent on the origin and spread of the tumor (4). Neuroblastoma with a primary lesion in the central nervous system is defined as primary central nervous system neuroblastoma (PCNSN), which is rare and carries a poor prognosis (5). In PCNSN, primary tumors located in the pineal gland are exceedingly rare, and there is no previous report thus far. Here, we report an adult patient diagnosed with primary pineal neuroblastoma who received surgical resection and postoperative radiotherapy.

Background and purpose: Increasing evidence suggests that the sympathetic nervous system profoundly interacts with skeletal muscle, influencing both muscle fiber function and composition. β2-Adrenoceptors (β2-ARs), the predominant adrenergic receptor subtype in muscle fibers, have been shown to enhance protein synthesis, reduce protein degradation, facilitate muscle contraction and relaxation, and improve neuromuscular junction (NMJ) transmission upon activation. In this study, we investigated the effects of Formoterol, a highly selective β2-AR agonist, on the presynaptic terminal of motor neurons. Experimental Approach: We used electromyography, FM1-43 fluorescent dye assays, and transmission electron microscopy to evaluate the neuromuscular junction following β2-receptor activation. Key Results: We demonstrated that β2-AR activation by Formoterol enhances muscle contractility and both spontaneous and evoked exocytosis of acetylcholine (ACh)-containing synaptic vesicles at the mouse diaphragm NMJ. Formoterol-induced morphological changes in diaphragmatic NMJs were consistent with increased exo-endocytic activity. Notably, Formoterol-evoked exocytosis displayed sexual dimorphism, with females showing a significantly milder response compared to males. In females, Formoterol-induced synaptic vesicles exocytosis was mediated solely by P/Q-type voltage-activated Ca2+ channels, whereas in males, it involved both P/Q-type channels, TRPV1 calcium channels, and an additional, yet unidentified, component. Orchiectomized males exhibited responses to Formoterol similar to the females., whereas ovariectomy did not modify female drug responses, indicating that male sex-hormonal environment orchestrates the sex-differences herein described. Conclusion and implications: These findings not only highlight the importance of sex-specific mechanisms but also reveal a novel effect of β2-AR activation directly on presynaptic terminals, enhancing exocytosis at the NMJ and thereby increasing neuromuscular transmission.

Background and purpose: Hexahydrocannabinol (HHC) is a novel psychoactive substance that has gained attention due to its psychotropic effects and temporary legal status. It is widely abused in several EU and US countries, where it serves as a legal and easily accessible alternative to ∆9-tetrahydrocannabinol (∆9-THC). Despite its widespread use, few studies have examined its in vivo effects and safety profile. Experimental approach: This study investigated the pharmacokinetics, systemic toxicity, and acute behavioural effects of HHC in male Wistar rats. A mixture of (9R)-HHC and (9S)-HHC epimers (in a 1:1 ratio) was administered via intragastric gavage at doses of 1, 5, and 10 mg/kg. Behavioural effects were assessed using the Open field test and the Prepulse inhibition of acoustic startle response. Key results: Two hours after 10 mg/kg administration, concentrations of both HHC epimers peaked in blood serum and brain tissue. According to the OECD 423 toxicity test, HHC was classified as a Category 4 substance, with an estimated lethal dose of 1000 mg/kg. Compared to the control group (administered sunflower oil), the highest dose (10 mg/kg) led to reduced locomotor activity, increased anxiety, and impaired sensorimotor gating. Conclusions & Implications: HHC readily crosses the blood-brain barrier, exhibits mild toxicity, and produces behavioural effects similar to THC-like cannabinoids.

Abstract— To provide near-lossless compression for both color and grayscale images, this study offers RIFD-LZW, a novel hybrid image compression algorithm that combines the Rounding the Intensity and Dividing (RIFD) technique with Lempel-Ziv-Welch (LZW) encoding. The methodology achieves a higher compression ratio than either technique alone as it uses RIFD to reduce image redundancy and LZW to efficiently encode data. When applied to the Kodak dataset, experimental results show that RIFD-LZW decreases file size by 73.03% and improves compression ratio by 9.7% when compared to RIFD-Huffman. Additionally, it attains a compression ratio for grayscale images that is 29.6% greater. With average Mean Squared Error (MSE) values of 2.88, 2.93, and 2.78 for the EPFL, Kodak, and Waterloo datasets, respectively, the proposed algorithm keeps up its outstanding visual quality. The tiny distortion that is introduced matches the MSE of RIFD and is undetectable to the human visual system. These results validate that RIFD-LZW is a strong contender for both lossy and near-lossless compression applications since it offers effective image compression with good image fidelity preservation.