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Ceftriaxone suppresses the severity of paclitaxel-induced glutamate-mediated chronic pain in experimental animals

Environmental enrichment as a therapeutic strategy against methamphetamine induces depressive behaviors in mice

Methamphetamine (METH) abuse is associated with addiction, emotional dysregulation, motor impairments, cognitive deficits, and depressive symptoms, which are exacerbated by stress and social isolation. This study investigated the therapeutic potential of combined treatment and environmental enrichment in METH withdrawn mice. Behavioral, biochemical and neurochemical outcomes were evaluated. Post-treatment results demonstrated: motor and exploratory behavior via OFT (open field test) mobility increased to from 32.37 meters (withdrawal group) to 59.52 meters, anxiety reduction indicated in EPM (elevated plus maze test) open arm rose from 33.2 to 74.2 sec, while cognitive improvement by MWM (morris water maze test) escape latency decreased from 225.4 to 127.4 sec in hidden platform trial. Moreover, memory and exploration activity were determined by NOR (novel object recognition test) and HBT (hole board test) which showed enhanced novel object exploration (16.4 vs 5 sec) and exploratory behavior (17.6 explored areas vs 8.6). Social interaction time increased to 41.64 sec, and light-dark compartment preference improved to 68.4%. Biochemical analysis revealed elevated antioxidants enzymes activity POD (peroxidase) (0.178 U/min) SOD (superoxide dismutase) (0.82 U/mg protein) and CAT (catalase) (3.6 U/min) indicating improved oxidative stress resilience. Neurotransmitters restoration was observed with serotonin (0.21 µg/mg) and dopamine (0.46 µg/mg) levels rebounding from negligible withdrawn group. These findings demonstrate that combined treatment and enriched environment robustly accelerate functional recovery in METH-withdrawn mice, suggesting a promising strategy for mitigating addiction-related deficits.

Photothermal therapy and radiotherapy of Bi2S3-GNRs hybrid nanoparticles in treatment of breast cancer

Clinical & laboratory profiles and treatment outcome of Kawasaki disease in children: Experience from a tertiary care hospital

Background A total of 40 cases of Kawasaki Disease (KD), diagnosed & categorized on the basis of criteria set by the American Heart Association were studied. We sought to evaluate their clinical and laboratory analysis along with their treatment. Methods After inclusion, they underwent thorough clinical and laboratory analysis and were treated with intravenous immunoglobulin and aspirin. Their clinical & laboratory findings and treatment outcome were analyzed further using Epi info and at a probability of (p value) < 0.05, was considered statistically significant. Results The mean age of the cases was 4.1 ± 2.9 years and boys outnumber the girls (57% vs. 43%). Most (65%) of the cases were incomplete KD compared to 35% as complete KD. The mean duration of fever was 11.7 ± 5.53 days. The frequency of the different classic clinical findings of KD were- cracking of lips & redness of oral cavity (72%), polymorphous skin rash (50%), conjunctival injection (45%), changes in the distal extremities (38%), cervical lymphadenitis (30%) and erythema on BCG scar (7.5%). High C-Reactive protein (CRP > 10 mg/dl), thrombocytosis, anaemia and leukocytosis were 85%, 45%, 43%, 38% respectively. Echocardiography showed coronary artery abnormalities (CAA) dilatation and aneurysm in 82.5% and 12.5% cases respectively which came down to 68% and 10% after receiving treatment with IVIg and Aspirin. Conclusion & Recommendation Diagnosis of KD is essentially clinical and criteria-based and 95% were complicated with CAA. Timely intervention with IVIG was mostly effective. Therefore, high index of suspicion of a long-continued febrile child is recommended to reach the diagnosis and to initiate timely intervention so as to potentially prevent CAA.

Impact of socio-economic factors and lifestyle behaviours on the quality of life of diabetes patients in Markurdi Benue state Nigeria

Energy expenditure and enjoyment of instructor-led exercise videos for children ages 7–13

Background The Interrupting Prolonged sitting with ACTivity (InPACT) at Home intervention provides youth with access to virtual, instructor-led exercise videos to promote physical activity in the home. While this program has had statewide reach, there is a need to understand the efficacy of the exercise videos to (1) induce positive cardiometabolic benefits in youth and (2) promote exercise enjoyment in the home. Purpose The purpose of this study was to determine and compare the effects of the InPACT at Home exercise videos on physical activity energy expenditure and physical activity enjoyment in children ages 7–13 years. Methods Thirty-nine participants ages 7–13 years were recruited to participate in this study. Participants completed five, 8-minute InPACT at Home exercise videos (cardio, strength, sports skills, and mindfulness) and one, 8-minute control video (sedentary). Physical activity energy expenditure was assessed using indirect calorimetry. Physical activity enjoyment was assessed using the Physical Activity Enjoyment Scale. Results Exercise videos elicited significantly higher physical activity energy expenditure and enjoyment compared to the control video (p < 0.05). There were also significant differences in physical activity energy expenditure by video type with the highest energy expenditure recorded during the cardio videos (24.84 ± 9.14 kcals) followed by the strength (20.97 ± 9.97 kcals), sports skills (20.66 ± 7.72 kcals), and mindfulness videos (17.34 ± 7.80 kcals, p < 0.05). There were no significant differences in physical activity enjoyment by exercise video type (all p’s > 0.05). Conclusion On average, children expended approximately 22 kcals while engaging in the InPACT at Home videos and rated all the videos as enjoyable. These findings highlight the potential of the InPACT at Home intervention to provide sustainable opportunities for youth to engage in health-enhancing physical activity in the home.

Secure and energy-efficient transmission in UAV-assisted intelligent reflecting surface networks

Understanding social inclusion: A directed content analysis

Background Social inclusion can be defined as a process that enhances opportunities for social participation, strengthens social bonds, and ensures equitable access to opportunities and decision-making. It emphasizes the interconnectedness of society and the active roles individuals play in upholding shared values and responsibilities. This study aimed to explore factors contributing to social inclusion from the perspective of families in Kingston, Ontario who self-identified as having a history of adversity and as being resilient during the COVID-19 pandemic. Methods Participants consisted of a maximum variation sample of families who demonstrated family level resilience during the COVID-19 pandemic. Focus groups and semi-structured in-depth interviews were conducted to allow participants to explore what helped or hindered their family resilience during and beyond the pandemic. Using directed content analysis, line-by-line coding of interview transcripts was conducted to explore the fit between data and an existing social inclusion framework. Results The majority of data fit meaningfully into the dimensions established in the social inclusion framework:(1) Quality Education; (2) Innovation & Technology; (3) Governmental Policies & Laws; (4) Transportation & Infrastructure; (5) Employment & Organizations; (6) Poverty & Economy; (7) Medical & Health; and (8) Community & Culture. However, we noted that some dimensions could be both sources of and barriers to social inclusion. Additionally, our study identified specific elements not discussed in the original inclusion framework, including informal education, public gathering spaces, nature, the social dimensions of poverty, and mental health care. Conclusions Participants perceived social inclusion as a facilitator of resilience. Interventions targeting the many dimensions of social inclusion must be implemented to drive positive community transformation.

Development of a prognostic multiomic biomarker of progression-free survival in advanced non-small cell lung cancer patients treated with first line immunotherapy

Evaluation of the antidiarrheal activity of dichloromethane-methanol crude extract of the aerial parts of Croton kinondoensis (Euphorbiaceae) in Mice

Background Diarrhea remains a major global health concern, particularly in developing countries. Resistance to conventional antibiotics underscores the need for effective, plant-based alternatives. Croton kinondoensis, a traditional Kenyan remedy for gastrointestinal ailments, has yet to be scientifically validated. This study assessed its antidiarrheal and antimotility effects in vivo mouse models. Methods Leaf extracts were prepared using dichloromethane/methanol (1:1). Phytochemical screening confirmed the presence of flavonoids, tannins, alkaloids and phenolics. Acute toxicity was assessed via OECD guideline 425. Antidiarrheal activity was tested using a castor oil-induced diarrhea model, and gastrointestinal motility was evaluated using the charcoal meal test. Mice were divided into five groups (n = 6): negative control (distilled water), positive control (loperamide 3 mg/kg), and three test groups receiving C. kinondoensis extract at doses of 100, 200, and 400 mg/kg). Statistical significance was determined using ANOVA and Tukey’s post hoc test to determine significance (p < 0.05). Results The extract showed no toxicity at 2000 mg/kg. In the castor oil-induced diarrhea model, the C. kinondoensis extract at 400 mg/kg inhibited diarrhea by 25.57% (p < 0.05), compared to 71.43% inhibition by loperamide (p < 0.001) e. The charcoal meal transit test, 400 mg/kg of the extract reduced intestinal transit by 27.98% (p < 0.01), compared to 33.43% by loperamide (p < 0.001. Conclusion C. kinondoensis exhibits dose-dependent antidiarrheal and antimotility effects, supporting its traditional use. Although its efficacy was lower than loperamide, the extract demonstrated significant potential as a natural remedy for diarrhea.

Parahippocampal activation reveals countermeasure use in a sentence-based complex trial protocol guilty knowledge test with P900 source localization

Dementia as a risk factor for 30-day mortality in community-acquired pneumonia in Colombia (CAP): A survival study

Background Community-acquired pneumonia (CAP) represents a significant clinical challenge, particularly in patients with comorbidities, such as dementia, which increases the risk of mortality and hospitalization. Despite its relevance, dementia has not been considered a CAP severity assessment tool. Furthermore, there is limited information on this topic in Latin America. Therefore, this study aimed to analyze 30-day survival in patients with CAP and dementia in Colombia with the objective of identifying the impact of dementia on clinical outcomes and understanding this phenomenon in the region. Methods A multicenter retrospective cohort study with survival analysis was conducted on patients with CAP admitted to two tertiary care institutions in Colombia between January 2010 and December 2020. Results The study included 3,374 subjects: 354 (10.5%) with dementia and 3,020 (89.5%) without dementia. The mean age was 65.5 years, higher in the dementia group (82.5 vs. 63.5 years, p < 0.001). Patients with dementia showed a higher prevalence of cyanosis, retraction, altered consciousness, and rales (p < 0.001). They also had higher rates of hypertension, heart failure, cerebrovascular disease, and chronic kidney disease (p < 0.001). Laboratory findings showed lower hemoglobin and sodium levels and higher BUN levels (p < 0.001). The 30-day mortality was 26.3% in the dementia group and 7.1% in the non-dementia group (p < 0.001), with a HR of 2.28 (95% CI: 1.756–2.962). The 30-day survival rate was 73.7% and 92.9%, respectively (p < 0.001). Conclusion Patients with dementia who developed pneumonia had a significantly higher mortality rate. They were also characterized by advanced age, multiple comorbidities, and greater disease severity. Our findings emphasize the importance of prioritizing individualized care to improve clinical outcomes and quality of life.

Adaptive power-saving mode control in NB-IoT networks using soft actor-critic reinforcement learning for optimal power management

Abstract In the evolving landscape of the Internet of Things (IoT), optimizing power efficiency in Narrowband IoT (NB-IoT) networks is crucial for extending device lifetimes while maintaining performance. This research leverages the Soft Actor-Critic (SAC) reinforcement learning algorithm to intelligently manage power-saving modes in NB-IoT devices. The study compares SAC with Proximal Policy Optimization, and Deep Q-Network. The methodology involves simulating an NB-IoT environment and evaluating performance using metrics such as total reward, overall energy efficiency, power consumption, mode count and duration, and duty cycle percentage. The SAC-based approach demonstrated significant improvements in power efficiency, achieving balanced enhancements in power conservation and network performance. These findings suggest that reinforcement learning techniques like SAC can play a pivotal role in advancing the efficiency and sustainability of NB-IoT networks, leading to prolonged device operation, reduced costs, and enhanced overall performance, thus paving the way for more resilient and scalable IoT deployments.

Experiment study on the cross-layer propagation characteristics of hydraulic fracturing cracks in coal roof rocks

Fracture of the overlying roof of a coal seam has become the main method to increase the permeability of coal seam in coalbed methane exploitation. Because the fracture must grow into the coal and through any stone layers, the mechanical property difference between the overlying roof rocks and coal inevitably leads to significant changes in the crack propagation behaviors. In this study, an embedded strain sensor with low cost and simple operation is used to measure the strain in laboratory samples representing the coal seam and roof near the interface for fractures initiated in the roof to obtain the width change of the hydraulic fracture at the interface. At the same time, the propagation behavior of hydraulic fractures at the interface is expressed by combining fracture images and pumping pressure. The results show that a larger horizontal stress difference, larger flow rate, lower coal seam modulus, and smaller intermediate layer thickness are beneficial for the propagation of hydraulic fractures from the roof into the coal seam and the activation of the roof-coal interface. On-site hydraulic fracturing design should fully consider the in-situ stress and coal seam modulus, and design reasonable fracturing drilling location and injection flow. The width of hydraulic fracture in coal seam is larger than that in roof, and increases with the modulus of coal and roof approach, which is beneficial to the migration of proppant in roof-coal seam hydraulic fracture. Therefore, the migration of fracturing proppant in an actual coal seam roof is limited by the width of hydraulic fractures in the roof.

Low dose naloxone mitigates opioid tolerance and dependence and restores mesenchymal stem cell function for cell therapy in addiction

GEOTrat Points as a free resource in QGIS for mapping the performance of agricultural experiments

Agricultural experimentation requires careful selection of the experimental design and model for analyzing treatment data. However, even with rigorous experimental control, the discrepancies between treatments are so subtle that traditional statistical models fail to highlight statistically significant differences that occur in field practice. The incorporation of geotechnologies offers the ability to map agricultural variability, but a gap still exists in the availability of tools designed to map and evaluate the effectiveness of agricultural experiments. To overcome this limitation and promote the wider application of Geographic Information Systems in agriculture, the scope of this study focuses on the development of a resource in QGIS software, aimed at evaluating agricultural experiments using a randomized block design with up to five treatments. The resource developed incorporates spatial interpolation techniques using geostatistical kriging, map generation, and statistics. The study used yield samples from six different crops to identify quantitative and spatial differences between two-treatment experiments in terms of yield gain. The performance evaluation included statistical measures such as Root Mean Square Error (RMSE) and Pearson’s correlation coefficient to validate the accuracy of interpolated surfaces. The results consisted of two surfaces representing the study area treated with each of the treatments, as well as a surface reflecting the yield gain of the reference treatment in relation to the control treatment, accompanied by relevant descriptive statistics measures on this gain surface. The experiments showed that RMSE varied between 4.6% and 69.71%, depending on the crop and treatment, while Pearson’s correlation ranged from −0.16 to 0.86, indicating varying degrees of agreement between interpolated and observed data. The tool successfully generated yield gain maps, allowing spatial visualization of treatment differences, with an accuracy of up to 95.40% in detecting spatial and numerical variations between treatments. The tool, called GEOTrat - Points, offers the flexibility to evaluate agricultural experiments of various designs, encompassing different crops and different quantities of samples, providing both numerical and spatial analysis.

Patch2MAP combines patch-clamp electrophysiology with super-resolution structural and protein imaging in identified single neurons without genetic modification

An affordable solution for investigating zebra finch intracranial electroencephalography (iEEG) signals

The zebra finch is a well-studied animal model for investigating the neural mechanisms of vocal learning, and electrophysiology is the primary technique for understanding their song system. Most of the studies on zebra finches have focused on intracerebral recordings. However, these methods are only affordable for limited laboratories. Recently, different open-source hardware for acquiring electroencephalography (EEG) signals has been developed. It’s unclear whether these solutions suit zebra finch studies as they have not been evaluated. Electrocorticography signals can provide a preliminary guide for more in-depth inquiries and also aid in understanding the global behavior of the bird’s brain, as opposed to the more common localized approach. We present a detailed protocol for acquiring intracranial electroencephalography (iEEG) data from zebra finches using the OpenBCI Cyton board, an open-source device. We implemented stainless steel electrodes on the brain’s surface and recorded the brain signals from two recording sites above two auditory-responsive nuclei. To validate our method, we ran two different experiments. In the first experiment, we recorded neural activity under various concentrations of isoflurane and extracted the suppression duration to measure anesthesia depth. In the second experiment, we head-fixed the birds and, under light anesthesia, presented them with various auditory stimuli to evaluate event-related potentials (ERP) and generate spectrograms. The results showed a significant increase in suppression duration with deeper anesthesia, and the ERP and spectrogram responses to auditory stimuli differed accordingly. These findings indicate that using our methodology, one can successfully collect iEEG signals from zebra finches. These findings pave the way for future studies to use iEEG to investigate bird cognition in a more affordable way.

Extended antibiotic exposure and exacerbations, mortality, and healthcare costs in asthma

Optimal gestational weight gain and pregnancy outcomes, by BMI and height, in a marginalised population of women with short stature living along the Thailand-Myanmar border: A retrospective cohort, 2004–2023

Background Existing gestational weight gain (GWG) standards may not be applicable to women of short stature and those who have limited access to healthcare and are vulnerable to compromised nutrition during pregnancy. To inform the development of population-specific recommendations, this study investigated optimal GWG, by height and Body Mass Index (BMI), in a minority migrant and refugee population living along the Thailand-Myanmar border. Methods Records of all women attending antenatal care in the first trimester at the Shoklo-Malaria Research Unit between 2004 and 2023 were retrospectively examined. GWG of 17,194 women was assessed against maternal, delivery and neonatal outcomes, by height and per Asia-Pacific BMI category. The Gestation Related Optimal Weight centiles were used to classify small, appropriate and large for gestational age neonates. Multivariable logistic regression analysis, including natural cubic splines, was used to assess the relationships between GWG and outcomes of interest. Optimal GWG per BMI group was defined as the GWG associated with the lowest composite risk for adverse outcomes. The optimal range included GWG values that did not exceed a 5% increase from the corresponding minimum composite risk. Results Optimal GWG in women shorter than 153 cm was lower per BMI group than the National Academy of Medicine and Intergrowth-21 recommendations: underweight 12.1 kg (10.0–14.5), normal 10.4 kg (8.0–12.9), overweight/obese 5.3 kg (3.1–8.5); but comparable for women 153 cm or more: underweight 13.1 kg (11.0–15.1), normal 12.3 kg (9.7–15.3), overweight/obese 9.5 kg (6.4–13.4). Conclusion Optimal GWG ranges are lower for this population with short stature compared to existing international guidelines. Clinical and contextual factors must be considered when implementing GWG recommendations for this, and other marginalized and short-stature populations.