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Environmental stressors can induce paternal epigenetic modifications that are a key determinant of the intergenerational inheritance of acquired phenotypes in mammals. Some of them can affect phenotypic expression through inducing changes in tRNA-derived small RNAs (tsRNAs), which modify paternal epigenetic regulation in sperm. However, it is unclear how these stressors can affect changes in the expression levels of tsRNAs and their related endonucleases in the male reproductive organs. We found that Ribonuclease inhibitor 1 (RNH1), an oxidation responder, interacts with ANG to regulate sperm tsRNA generation in the mouse caput epididymis. On the other hand, inflammation and oxidative stress induced by either lipopolysaccharide (LPS) or palmitate (PA) treatments weakened the RNH1-ANG interaction in the epididymal epithelial cells (EEC). Accordingly, ANG translocation increased from the nucleus to the cytoplasm, which led to ANG upregulation and increases in cytoplasmic tsRNA expression levels. In conclusion, as an antioxidant, RNH1 regulates tsRNA generation through targeting ANG in the mouse caput epididymis. Moreover, the tsRNA is an epigenetic factor in sperm that modulates paternal inheritance in offspring via the fertilization process.

The recent advancements in artificial intelligence have brought about significant changes in education. In the context of intelligent campus development, target detection technology plays a pivotal role in applications such as campus environment monitoring and the facilitation of classroom behavior surveillance. However, traditional object detection methods face challenges in open and dynamic campus scenarios where unexpected objects and behaviors arise. Open-World Object Detection (OWOD) addresses this issue by enabling detectors to gradually learn and recognize unknown objects. Nevertheless, existing OWOD methods introduce two major uncertainties that limit the detection performance: the unknown discovery uncertainty from the manual generation of pseudo-labels for unknown objects and the known discrimination uncertainty from perturbations that unknown training introduces to the known class features. In this paper, we introduce a Parallel OWOD Framework with Uncertainty Mitigation to alleviate the unknown discovery uncertainty and the known discrimination uncertainty within the OWOD task. To address the unknown discovery uncertainty, we propose an objectness-driven discovery module to focus on capturing the generalized objectness shared among various known classes, driving the framework to discover more potential objects that are distinct from the background, including unknown objects. To mitigate the discrimination uncertainty, we decouple the learning processes for known and unknown classes through a parallel structure to reduce the mutual influence at the feature level and design a collaborative open-world classifier to achieve high-performance collaborative detection of both known and unknown classes. Our framework provides educators with a powerful tool for effective campus monitoring and classroom management. Experimental results on standard benchmarks demonstrate the framework’s superior performance compared to state-of-the-art methods, showcasing its transformative potential in intelligent educational environments.

Tunnels play a vital role in enhancing traffic flow and supporting public transportation systems. However, the discharge of polluted air and waste heat from vehicles passing through tunnels significantly raises the temperature inside, presenting challenges in terms of occupant comfort, tunnel safety, and infrastructure integrity. Therefore, ensuring proper temperature control is essential for their efficient operation. This study aims to investigate the phenomenon of temperature rise in ultra-long tunnels during normal operations, as limited research has been conducted in this area. The Shanghai Yangtze River Tunnel serves as a case study, utilizing temperature and air velocity data collected throughout the year (2021) from the management company. The analysis reveals that the temperature distribution near the tunnel exit is influenced by outdoor temperature fluctuations and traffic volume. The highest temperatures occur on 25 August (39.74 °C) during peak traffic hours. On-site measurements of tunnel temperature, humidity, and air velocity during winter and summer seasons yield the following results. During winter, the air temperature and wall temperature inside the tunnel experience significant increases along its length. The air temperature rises by approximately 11 °C from the entrance to the exit, while the wall temperature increases by about 15 °C. In contrast, during summer, the air temperature only rises by 2.7 °C, and the wall temperature increases by around 3 °C. Consequently, the humidity decreases along the tunnel, and this decrease is correlated with the magnitude of temperature increase. Furthermore, measurements of air velocity indicate that natural and traffic-induced winds contribute to the overall airflow inside the tunnel. A temperature data logger installed in the tunnel recorded temperature changes during the period of pandemic lockdown and subsequent recovery, spanning the spring and summer seasons. During the lockdown period, there was a relatively small increase in temperature along the tunnel, suggesting that vehicle heat dissipation is the primary factor contributing to temperature rise inside. Additionally, a method is proposed to predict the cross-sectional temperature of the tunnel using measured air velocities.

The global outbreak of SARS-CoV-2/COVID-19 provided the stage to accumulate an enormous biomedical data set and an opportunity as well as a challenge to test new concepts and strategies to combat the pandemic. New research and molecular medical protocols may be deployed in different scientific fields, e.g., glycobiology, nanopharmacology, or nanomedicine. We correlated clinical biomedical data derived from patients in intensive care units with structural biology and biophysical data from NMR and/or CAMM (computer-aided molecular modeling). Consequently, new diagnostic and therapeutic approaches against SARS-CoV-2 were evaluated. Specifically, we tested the suitability of incretin mimetics with one or two pH-sensitive amino acid residues as potential drugs to prevent or cure long-COVID symptoms. Blood pH values in correlation with temperature alterations in patient bodies were of clinical importance. The effects of biophysical parameters such as temperature and pH value variation in relation to physical-chemical membrane properties (e.g., glycosylation state, affinity of certain amino acid sequences to sialic acids as well as other carbohydrate residues and lipid structures) provided helpful hints in identifying a potential Achilles heel against long COVID. In silico CAMM methods and in vitro NMR experiments (including 31P NMR measurements) were applied to analyze the structural behavior of incretin mimetics and SARS-CoV fusion peptides interacting with dodecylphosphocholine (DPC) micelles. These supramolecular complexes were analyzed under physiological conditions by 1H and 31P NMR techniques. We were able to observe characteristic interaction states of incretin mimetics, SARS-CoV fusion peptides and DPC membranes. Novel interaction profiles (indicated, e.g., by 31P NMR signal splitting) were detected. Furthermore, we evaluated GM1 gangliosides and sialic acid-coated silica nanoparticles in complex with DPC micelles in order to create a simple virus host cell membrane model. This is a first step in exploring the structure–function relationship between the SARS-CoV-2 spike protein and incretin mimetics with conserved pH-sensitive histidine residues in their carbohydrate recognition domains as found in galectins. The applied methods were effective in identifying peptide sequences as well as certain carbohydrate moieties with the potential to protect the blood–brain barrier (BBB). These clinically relevant observations on low blood pH values in fatal COVID-19 cases open routes for new therapeutic approaches, especially against long-COVID symptoms.

Osteoarthritis belongs to the most common joint diseases in humans and animals and shows increased incidence in older patients. The bioactivities of collagen hydrolysates, sulfated glucosamine and a special fatty acid enriched dog-food were tested in a dog patient study of 52 dogs as potential therapeutic treatment options in early osteoarthritis. Biophysical, biochemical, cell biological and molecular modeling methods support that these well-defined substances may act as effective nutraceuticals. Importantly, the applied collagen hydrolysates as well as sulfated glucosamine residues from marine organisms were strongly supported by both an animal model and molecular modeling of intermolecular interactions. Molecular modeling of predicted interaction dynamics was evaluated for the receptor proteins MMP-3 and ADAMTS-5. These proteins play a prominent role in the maintenance of cartilage health as well as innate and adapted immunity. Nutraceutical data were generated in a veterinary clinical study focusing on mobility and agility. Specifically, key clinical parameter (MMP-3 and TIMP-1) were obtained from blood probes of German shepherd dogs with early osteoarthritis symptoms fed with collagen hydrolysates. Collagen hydrolysate, a chondroprotective food supplement was examined by high resolution NMR experiments. Molecular modeling simulations were used to further characterize the interaction potency of collagen fragments and glucosamines with protein receptor structures. Potential beneficial effects of collagen hydrolysates, sulfated glycans (i.e., sulfated glucosamine from crabs and mussels) and lipids, especially, eicosapentaenoic acid (extracted from fish oil) on biochemical and physiological processes are discussed here in the context of human and veterinary medicine.

The quality control of drug products during manufacturing processes is important, particularly the presence of different polymorphic forms in active pharmaceutical ingredients (APIs) during production, which could affect the performance of the formulated products. The objective of this study was to investigate the phase transformation of fexofenadine hydrochloride (FXD) and its influence on the quality and performance of the drug. Water addition was key controlling factor for the polymorphic conversion from Form I to Form II (hydrate) during the wet granulation process of FXD. Water-induced phase transformation of FXD was studied and quantified with XRD and thermal analysis. When FXD was mixed with water, it rapidly converted to Form II, while the conversion is retarded when FXD is formulated with excipients. In addition, the conversion was totally inhibited when the water content was w/w. The relationship between phase transformation and water content was studied at the small scale, and it was also applicable for the scale-up during wet granulation. The effect of phase transition on the FXD tablet performance was investigated by evaluating granule characterization and dissolution behavior. It was shown that, during the transition, the dissolved FXD acted as a binder to improve the properties of granules, such as density and flowability. However, if the water was over added, it can lead to the incomplete release of the FXD during dissolution. In order to balance the quality attributes and the dissolution of granules, the phase transition of FXD and the water amount added should be controlled during wet granulation.

Epigenetic regulation plays a critical role in controlling fungal secondary metabolism. Here, we report the pleiotropic effects of the epigenetic regulator HdaA (histone deacetylase) on secondary metabolite production and the associated biosynthetic gene clusters (BGCs) expression in the plant endophytic fungus Penicillium chrysogenum Fes1701. Deletion of the hdaA gene in strain Fes1701 induced a significant change of the secondary metabolite profile with the emergence of the bioactive indole alkaloid meleagrin. Simultaneously, more meleagrin/roquefortine-related compounds and less chrysogine were synthesized in the ΔhdaA strain. Transcriptional analysis of relevant gene clusters in ΔhdaA and wild strains indicated that disruption of hdaA had different effects on the expression levels of two BGCs: the meleagrin/roquefortine BGC was upregulated, while the chrysogine BGC was downregulated. Interestingly, transcriptional analysis demonstrated that different functional genes in the same BGC had different responses to the disruption of hdaA. Thereinto, the roqO gene, which encodes a key catalyzing enzyme in meleagrin biosynthesis, showed the highest upregulation in the ΔhdaA strain (84.8-fold). To our knowledge, this is the first report of the upregulation of HdaA inactivation on meleagrin/roquefortine alkaloid production in the endophytic fungus P. chrysogenum. Our results suggest that genetic manipulation based on the epigenetic regulator HdaA is an important strategy for regulating the productions of secondary metabolites and expanding bioactive natural product resources in endophytic fungi.

Formulas derived from theoretical physics provide important insights about the nematocyst discharge process of Cnidaria (Hydra, jellyfishes, box-jellyfishes and sea-anemones). Our model description of the fastest process in living nature raises and answers questions related to the material properties of the cell- and tubule-walls of nematocysts including their polysialic acid (polySia) dependent target function. Since a number of tumor-cells, especially brain-tumor cells such as neuroblastoma tissues carry the polysaccharide chain polySia in similar concentration as fish eggs or fish skin, it makes sense to use these findings for new diagnostic and therapeutic approaches in the field of nanomedicine. Therefore, the nematocyst discharge process can be considered as a bionic blue-print for future nanomedical devices in cancer diagnostics and therapies. This approach is promising because the physical background of this process can be described in a sufficient way with formulas presented here. Additionally, we discuss biophysical and biochemical experiments which will allow us to define proper boundary conditions in order to support our theoretical model approach. PolySia glycans occur in a similar density on malignant tumor cells than on the cell surfaces of Cnidarian predators and preys. The knowledge of the polySia-dependent initiation of the nematocyst discharge process in an intact nematocyte is an essential prerequisite regarding the further development of target-directed nanomedical devices for diagnostic and therapeutic purposes. The theoretical description as well as the computationally and experimentally derived results about the biophysical and biochemical parameters can contribute to a proper design of anti-tumor drug ejecting vessels which use a stylet-tubule system. Especially, the role of nematogalectins is of interest because these bridging proteins contribute as well as special collagen fibers to the elastic band properties. The basic concepts of the nematocyst discharge process inside the tubule cell walls of nematocysts were studied in jellyfishes and in Hydra which are ideal model organisms. Hydra has already been chosen by Alan Turing in order to figure out how the chemical basis of morphogenesis can be described in a fundamental way. This encouraged us to discuss the action of nematocysts in relation to morphological aspects and material requirements. Using these insights, it is now possible to discuss natural and artificial nematocyst-like vessels with optimized properties for a diagnostic and therapeutic use, e.g., in neurooncology. We show here that crucial physical parameters such as pressure thresholds and elasticity properties during the nematocyst discharge process can be described in a consistent and satisfactory way with an impact on the construction of new nanomedical devices.