Background: Alpha-methylfentanyl and acetyl-alpha-methylfentanyl are two extremely hazardous fentanyl analogues for which addiction data have not been reported. Methods: In this study, we assessed its abuse potential through conditioned position preference (CPP), drug self-administration, and drug discrimination and compared it with fentanyl. Naloxone was also tried in self-administration to suppress relapse behavior. Results: From the CPP results, both fentanyl and alpha-methylfentanyl produced conditioned place preference behavior at a dose of 30 μg/kg, while acetyl-alpha-methylfentanyl produced conditioned place preference behavior at a dose of 900 μg/kg. In self-administration, all three drugs produced a maximum number of infusions at 0.5 μg/kg/infusion, But the number of infusions of acetyl-alpha-methylfentanyl and alpha-methylfentanyl at the peak dose was higher than that of fentanyl. In addition, a single injection of naloxone was also effective in suppressing relapsing behavior in rats. In the drug discrimination experiments, the ED50 of fentanyl, alpha-methylfentanyl and acetyl-alpha-methylfentanyl were 11.06, 12.65 and 128.3 μg/kg, respectively. Discussion and conclusions: By comparing the experimental outcomes, we observed an intriguing phenomenon: the introduction of an alpha-positioned methyl group had a negligible impact on the CPP reward effect and the subjective effect, but significantly reduced reinforcement effect in self-administration experiment. Moreover, the length of the acyl side chain can markedly alter the addiction potential of the drug. Additionally, we tested that a single injection of naloxone can inhibit relapse behavior in rats. In conclusion, evaluation of their structure-addiction relationships can help predict the mechanisms of human drug addiction and identify potential treatment targets.

The resurgence of human metapneumovirus (hMPV) highlights its significant yet under-recognized role in respiratory infections globally. Recent outbreaks in China, India, and Europe underscore its clinical burden, with severe cases linked to bronchiolitis, pneumonia, and exacerbations of chronic conditions. Despite its impact, hMPV remains underdiagnosed due to limited access to molecular diagnostics and routine surveillance, particularly in low- and middle-income countries. The absence of antivirals or vaccines exacerbates its public health challenge. Advances in multiplex diagnostics and vaccine development offer hope but require sustained global investment. Addressing gaps in prevention, diagnostics, and treatment is critical to mitigating hMPV’s growing threat and ensuring equitable healthcare outcomes.

A document by Tingting Zhong. Click on the document to view its contents.

Global hydrological systems are transforming as regulation, reservoir operations, and intermittent flows reshape river regimes. Existing conceptual models, while interpretable, often underperform under conditions such as non-perennial flows and complex reservoir management. Fully distributed physically-based models, though robust, require extensive data and parameterization, limiting their utility in data-scarce contexts. Here, we develop a Hydro-Integrated Recurrent Neural Network (HIRNN), a fully differentiable hybrid framework that integrates conceptual modeling principles with the adaptive learning capabilities of recurrent neural networks. HIRNN explicitly accounts for intermittent flows and reservoir storage dynamics, achieving improved predictive performance and diagnostic insights. By explicitly modeling these key factors, HIRNN significantly improves predictive performance in 222 global basins, boosting Nash-Sutcliffe efficiency by up to 237.5\% in managed perennial catchments on modifying original model structure. This framework combines interpretability and scalability, enabling deployment in data-limited settings and informing adaptive water resource management as hydrological pressures intensify.

A document by Bronwen Merner. Click on the document to view its contents.

In recent years, photovoltaic energy has gained global attention due to the advantages of photovoltaic (PV) systems and the abundance of solar energy. Consequently, the installation capacity of PV systems has risen. Despite these benefits and the notable growth of PV systems, they face challenges such as high initial costs, low power conversion efficiency, reliance on environmental conditions, and vulnerability to faults. Fault detection in PV arrays is critical to minimize energy losses and maximize income for users while also improving electricity efficiency and system lifespan. However, because of the non-linear nature of PV systems, it is challenging for protection devices to detect faults, which can lead to safety risks and fire hazards in solar power plants. In this study, a convolutional neural network (CNN), a type of supervised model, was used for fault diagnosis. Yet, like other supervised models, it has several drawbacks: 1) Acquiring labeled PV data is costly and challenging. 2) Updating the trained model is difficult. 3) Visualizing the model is complex. To overcome these limitations, this study introduces a semi-supervised learning model that uses only a small amount of labeled data and normalizes it for better visualization.

The promotion of portable antibiotic rapid detection technology and instruments is of critical importance across various fields, including food safety, environmental monitoring, and healthcare. Building on the kanamycin aptamer electrochemical sensing platform and auxiliary test instruments developed in previous research, this study successfully overcomes the limitations of traditional electrochemical workstation by introducing a portable multi-channel electrochemical analyzer. This innovative device requires only the appropriate biosensor chip to detect relevant targets. It has been effectively utilized for both end-point and real-time detection of kanamycin and tetracycline in water samples. End-point quantitative analysis conducted at 20 minutes revealed detection limits of 0.49 and 45.1 μmol/L for kanamycin and tetracycline, respectively. The real-time analysis demonstrates the capability to differentiate between varying concentrations of kanamycin samples at an early stage. The sensor chip construction method is straightforward and exhibits good selectivity for the relevant targets, enabling rapid detection of different antibiotic residues in actual water samples. Furthermore, the portability of the self-developed electrochemical analyzer is anticipated to accelerate the practical implementation of antibiotic residue detection.

IntroductionAlthough developed countries have seen a decline in organophosphate poisoning cases due to stricter regulations on the use of these chemicals, developing countries continue to face clinical problems related to this issue in recent years. Pesticides are frequently used as a means of self- harm due to their lethality and widespread availability in the developing world. Therefore, developing countries that rely heavily on agriculture and often have less stringent pesticide regulations account for the majority of organophosphate poisoning cases. Research indicates that deliberate poisoning results in a higher mortality rate than accidental exposure to these compounds. [1]Cholinergic toxicity is caused by substances that stimulate, enhance, or mimic the neurotransmitter acetylcholine, the primary neurotransmitter of the parasympathetic nervous system. Acetylcholine stimulates muscarinic and nicotinic receptors to cause muscle contraction and glandular secretions. Cholinergic toxicity occurs when too much acetylcholine is present at the receptor synapse, leading to excessive parasympathetic effects. [2]The mechanism involves excessive cholinergic receptor stimulation, which can be caused by substances that mimic, stimulate, or enhance acetylcholine. The symptom complex produced by the agent depends on what type of receptor or combination of receptors is activated. There are three types of cholinergic receptors: central, muscarinic, and nicotinic. Excess acetylcholine at muscarinic receptors will result in symptoms of increased secretions, bronchoconstriction, bradycardia, vomiting, and abdominal cramping. Excess acetylcholine at nicotinic receptors causes muscle fasciculations or paralysis due to activation of the neuromuscular junction. Acetylcholine excess in the central nervous system can cause confusion, headache, or drowsiness. [3]We report the case of successful management of cholinergic syndrome following the ingestion of a powdered concoction from a traditional herbalist

Lung cancer is worldwide the leading non-skin cancer-related cause of death and the second most diagnosed malignancy. Currently, many immunohistochemistry essays can provide precise end of line histological diagnosis, improving overall survival through efficient individualized treatment schemes. There seems to be a radiological correlation between the two basic histological tumor subtypes (adenocarcinoma and squamous cells carcinoma) and nodule site presentation in chest imaging, and although this is considered in many radiology manuals, the reasons for such presentation patterns are seldom investigated. We intend to present hypothesis and reasonable explanations for the practical consensus widely acknowledged in the manuals, considering cell types in the lung topography and histological markers in carcinogenesis which should be able to clarify wether the imaging pattern is statistically true and why certain tumor types prefer their usual sites, being adenocarcinomas preferably peripheral and squamous cell carcinoma central.

A document by Kiara Reyes Gamas. Click on the document to view its contents.

Biodiversity can underpin stability in communities, allowing them to withstand environmental fluctuations without changes in aggregate properties like total abundance or biomass. We investigated the influence of biodiversity on two crucial population-level mechanisms governing abundance stability in mesopredatory coral reef fishes: (i) ’community asynchrony’, where species populations fluctuate inversely over time, and (ii) ’species population stability’, where highly abundant species with significant community contributions display minimal population fluctuations. Analyzing temporal data from 81 reef fish communities across the Indian and Pacific Oceans over a decade, we found that community asynchrony, rather than species population stability, primarily predicts community stability. Functional diversity, not taxonomic diversity, characterised this stability, emphasizing the role of niche differences in stabilizing communities. We highlight that community attributes that promote asynchronous population fluctuations, enhancing response diversity and tempering strong trophic interactions, are vital for stabilizing mesopredatory reef fish communities in the face of global change.

Ecological filters play a significant role in shaping communities by excluding species based on their morphological, physiological, and behavioral adaptations. Ants are excellent models for studying the effects of these filters, as their traits enable them to occupy a wide range of microhabitats. Individual characteristics, such as color and size, allow some species to overcome environmental filtering. In this study, we investigated how microhabitat and seasonality influence the distribution patterns of ants and how these patterns are shaped by the ants' size and color. The study was conducted in the highly diverse Amazon-Cerrado transition zone, where the regional species pool includes a mix of species from both phytophysiognomies as well as endemic species. We collected ants using pitfall traps placed in the soil and vegetation, and we measured the color and size of individuals from each species. In total, we recorded 2,659 ant occurrences, distributed across 236 species, 53 genera, and 8 subfamilies. Our results showed that ant species richness is higher during the dry season, particularly in the soil. Differences between strata and seasons were primarily driven by species turnover. However, this turnover was not consistent, as some soil-dwelling ants, particularly the large and light-colored ones, migrated to the vegetation during the rainy season, contributing to a nestedness pattern across seasons and strata. Furthermore, larger ants were consistently found in the vegetation, whereas smaller ants were more commonly observed in the soil. This indicates an interaction between biological and environmental filters in determining local communities, as the relaxation of environmental filters can allow ground-dwelling ants to forage on lower vegetation. These findings provide valuable insights into community assembly across different seasons and emphasize that a snapshot approach to community assessment may lead to incomplete conclusions about species richness and community dynamics.

Salinity is one kind of abiotic stress that hinders crop productivity, especially in the coastal region. The present study focused on the salinity-tolerance of a bacterial isolate identified as Enterobacter sp. based on 16S rRNA gene sequencing and its growth-promoting potential in the rice cultivar MTU1010 (a high-yielding, short-duration variety) under the salinity stress. The isolate could tolerate NaCl up to 900 mM, but increased cell size was observed under the salinity stress. It was sensitive to neomycin and streptomycin at 100 ppm concentration and positive for indole acetic acid, siderophore, and amino-cyclopropane carboxylate deaminase production. The results of greenhouse experiments revealed that the isolate KUSP04 inoculation increased rice seed germination rate, and bacteria inoculation in the potting soil promoted the shoot and root fresh weight by 96.26% and 25.32%, and shoot and root length by 37.75% and 35.42%, respectively as compared to the control set. KUSP04 inoculation mitigated any adverse effects of salinity stress, and increments of shoot and root fresh weight 137.44% and 427.20%, and shoot and root length 36.14% and 47.78%, respectively, were observed under 100 mM salinity level as compared to their uninoculated counterparts. In addition, the inoculation improved the chlorophyll content of the tissues of the rice seedling and reduced oxidative stress by expressing antioxidant enzymes like ascorbate peroxidase and catalase and reducing the proline content of the inoculated plants. All the data suggested that Enterobacter sp. KUSP04 could be potentially used as a bio-inoculant in salinized agricultural lands to increase rice productivity.

Here we present extinction, extirpation and coexistence conditions where / when two communities combine. We consider one specific model where two communities coalesce, and another model where the communities coexist side by side, blending in a transitionary zone called the ecotone. Specifically, (1) we analytically calculate the shifts in abundances as a function of mixing strength. (2) Obtain a critical value for the mixing strength leading to extinction. (3) Derive an inequality condition for full coexistent mixing. (4) find how the individual communities penetrate into one other as a function of mixing strength. (5) derive the conditions for one species to cross the ecotone and invade an neighboring community and (6) conditions for a native species to get extirpated. Lastly, (7) we spatially investigate the species richness within the ecotone and derive a condition that determines whether the ecotone will have higher or lower richness compared to its surrounding habitats.

We applied the second law of thermodynamics to provide proper physical foundations in biological evolution. We found that biological evolution transpires via oscillating state variables of entropy, energy, temperature, pressure, and volume. These fluctuations, parallel genetic and morphological complexity, include low entropy order increasing transformations and high entropy competition. Low entropy conditions favor maximum energy use, formulated by the maximum power principle. In contrast, high entropy states demand minimal entropy production and favor highly specialized species, as Prigogine's minimum entropy production theory shows. Our argument reconciles the contradictions between the two theories. In this framework, periodic mass extinctions act as pivotal reset points, removing highly specialized evolutionary dead ends while creating opportunities for renewal in surviving species. Identifying the contrasting energy profiles and entropic environments in which these two principles operate can aid a more in-depth understanding of the Darwinian Theory.

Ecologists and other statistical practitioners with access to high-resolution spatial data lack guidance on best approaches for discerning meaningful spatial scales for environmental covariates which is necessary when spatial factors influence environmental processes. Recently developed methods have attempted to automate investigating spatial scales for covariates by evaluating models for which potential explanatory variables are derived from concentric circles of increasing size centered at survey locations. However, these methods make a strong assumption on the inclusion of the covariate and do not help discern whether a covariate should be included in the model. We present an approach that utilizes researcher guidance to create informative priors on the model space that, along with parallelizable Reversible Jump MCMC techniques, enables efficient estimation of posterior model probabilities to assist with the choice of meaningful spatial scales for environmental covariates.

To date, the use of CRISPR/Cas9 technology in ecological-model species for validating genotype to phenotype connections has focused primarily on visual phenotypes using G0 mutations coupled with analyses of resulting mosaic phenotypes. However, studies of physiological phenotypes necessitate germline mutations in order to assess non-visible phenotypic effects, thus dedicated efforts to developing efficient germline mutations in ecological model species are needed. Here we applied the CRISPR/Cas9 technology to an ecological model species, the speckled wood butterfly (Pararge aegeria). We targeted yellow-y, which is required for the production of black melanin, as yellow-y loss of function (LOF) mutations are not lethal and easy to phenotype, affording efficient assessment of F0 and germline mutations. To explore what factors may affect efficiency of transformation, we employed four alternative treatments, including variation in sgRNAs and their concentrations. Color changes in the head capsule of first larval instar as well as adult wing color were used as indicators of successful knockouts. Individuals with wings that were at least 50% transformed were mated, with their F1 offspring assessed for the presence of germline mutations. Our CRISPR/Cas9 technique was highly efficient at generating LOF mutations in yellow-y. Across all treatments, nearly 80% of adults exhibited mosaic LOF phenotypes, of which nearly 30% appeared to have 100% LOF phenotypes. Crosses between adults exhibiting at least 50% LOF phenotypes resulted in fully transformed offspring, revealing high incidence of germline LOF mutations in yellow-y. We provide a detailed protocol on how to obtain high germline LOF mutation efficiency in order to advance the study of genotype-phenotype connections for non-visible physiological traits across natural populations of this and other model ecological species.

Highly laborious plating of cultures onto solid media is inevitable in conventional yeast two-hybrid systems. We have successfully developed Liquid Y2H-Seq, a method which replaces solid media with liquid media for culturing and that displaces visual inspection of colonies with sequencing. Soybean (Glycine max) is a typical photoperiod-sensitive crop, meaning that specific duration light regime has a huge impact on soybean flowering and production. We obtained a lot of putatively interactions for soybean flowering genes. Finally, these reports introduce a labor-reducing and time-saving method for identifying protein-protein interactions, based on simple modifications to a ubiquitous protocol in life science research.

Segmentation of cardiomyocytes in microscopic 3D volumes is key to our understanding of cardiac (patho-)physiology; however, it poses substantial experimental and analytical challenges. Therefore, researchers often resort to inferring 3D information from 2D segmentations, assuming rotational symmetry in the third direction which can lead to biased or even incorrect conclusions. Deep learning-based methods are showing promise in robustly segmenting objects in volumes acquired using various imaging modalities; yet, they have not been applied to high-resolution 3D cardiomyocyte segmentations, and suitable open-source tools and datasets are lacking. Here, we present a deep learning-enabled toolkit for segmentation of individual cardiomyocytes in 3D confocal microscopy volumes. We include a dataset of 73 volumes with expert annotations, covering seven species, including mouse, human, and elephant, and containing samples generated under different experimental conditions, such as post-myocardial infarction and ex vivo slice cultures. The toolkit additionally contains an image restoration workflow for spatially varying blur. Our automatic cardiomyocyte segmentation workflow achieved an adapted Rand error of 0.063 +/- 0.034 on the test set. Our semi-automatic workflow reached a throughput of 3 cells/minute on a challenging, previously unseen dataset. The toolkit and data are open-source and accessible through a dedicated graphical user interface. In summary, we provide an accessible toolkit enabling researchers to extract quantitative data on cardiomyocyte morphology from 3D confocal image stacks of cardiac tissue. Given the size and diversity of our dataset, we expect our methods to perform well across species and experimental conditions, facilitating high-quality 3D reconstructions of large numbers of individual cardiomyocytes.

Bloomy rind sign in leptomeningeal metastasis of primary

A document by Yang Yang. Click on the document to view its contents.

Introduction:Iliopsoas abscess (IPA) is a rare infection in the iliopsoas muscle compartment that occurs from primary or secondary causes [1]. Primary IPA is due to an infectious organism’s hematogenous or lymphatic spread from a distant site. Secondary IPA is due to the direct expansion of an infectious process into the iliopsoas muscle [2]. The majority of cases are due to secondary causes, which include Crohn’s disease, diverticulitis, appendicitis, colorectal carcinoma, UTI, instrumentation, osteomyelitis, sacroiliitis, septic arthritis, trauma, endocarditis, hepatocellular carcinoma, and femoral artery catheterization [3]. They often present with non-specific symptoms, leading to diagnostic delays. The condition is commonly secondary to abdominal surgery, with 75–85% occurring as a complication of it [4]. Second is Crohn’s disease, where internal fistulae occur in up to 15% of patients [5]. Other causes include gastrointestinal malignancies, with 0.3%–0.4% of patients with colon cancer [6].The treatment involves a multidisciplinary team, including gastroenterologists, surgeons, and infectious disease specialists, as many cases are complex. The treatment recommendations vary depending on the severity and etiology of the IPA. In this case report, we discuss a rare incidence of iliopsoas abscess due to a fistula from the sigmoid colon caused by the patient’s complex history of cancer, chemotherapy, and radiation treatment, which was closed by an endoscopic clip.

A document by Carlos Mendiola-Villalobos. Click on the document to view its contents.

Introduction:According to the World Health Organization’s international database of adverse reactions, the most frequently reported medicines implicated in drug-induced pancreatitis (DIP) are anti-HIV agents, atypical antipsychotics, azathioprine, mesalazine, estrogens, statins and tetracyclines (1), however, ceftriaxone, a third-generation cephalosporin has also been implicated in causing acute pancreatitis. (2). We report a case of a 62-year-old man with ceftriaxone-induced acute pancreatitis.