This study assessed the prevalence of myopia, cataracts, glaucoma, and macular degeneration among Koreans over 40, utilizing data from the 7th Korea National Health and Nutrition Examination Survey (KNHANES VII, 2018). We analyzed 204,973 adults (44% men, 56% women; mean age 58.70 ± 10.75 years), exploring the association between myopia and these eye diseases through multivariate logistic regression, adjusting for confounders and calculating adjusted odds ratios (ORs) with 95% confidence intervals (CIs). Results showed a myopia prevalence of 44.6%, cataracts at 19.4%, macular degeneration at 16.2%, and glaucoma at 2.3%, with significant differences across ages and genders. A potential link was found between myopia and an increased risk of cataracts and macular degeneration, but not with glaucoma. Additionally, a higher dietary intake of carbohydrates, polyunsaturated and n-6 fatty acids, vitamins, and minerals correlated with lower risks of these diseases, underscoring the importance of the diet in managing and preventing age-related eye conditions. These findings highlight the need for dietary considerations in public health strategies and confirm myopia as a significant risk factor for specific eye diseases in the aging Korean population. Full article

This study explores the nexus between digital financial inclusion and household participation in commercial insurance, utilizing data from the Peking University Digital Financial Inclusion Index and the 2018 CFPS database. Using Probit and Logit models, our research uncovers significant regional and risk -preference variations, emphasizing the influence of governance mechanisms. The study underscores the pivotal role of digital participation in a sustainable governance mechanism in shaping financial behavior, as well as the importance of advocating for regulatory interventions, enhanced financial literacy, and infrastructure development to foster equitable insurance access. Moreover, positive determinants, such as education level and social insurance participation, are identified, while discretionary spending emerges as a barrier. This study advocates for expedited digital financial inclusion initiatives to increase financial literacy with strengthened regulatory oversight and governance mechanisms which would ensure sustainable regional development and insurance market resilience. Full article

It is crucial to speed up the training process of multivariate deep learning models for forecasting time series data in a real-time adaptive computing service with automated feature engineering. Multivariate time series decomposition and recombining (MTS-DR) is proposed for this purpose with better accuracy. A proposed MTS-DR model was built to prove that not only the training time is shortened but also the error loss is slightly reduced. A case study is for demonstrating air quality forecasting in sub-tropical urban cities. Since MTS decomposition reduces complexity and makes the features to be explored easier, the speed of deep learning models as well as their accuracy are improved. The experiments show it is easier to train the trend component, and there is no need to train the seasonal component with zero MSE. All forecast results are visualized to show that the total training time has been shortened greatly and that the forecast is ideal for changing trends. The proposed method is also suitable for other time series MTS with seasonal oscillations since it was applied to the datasets of six different kinds of air pollutants individually. Thus, this proposed method has some commonality and could be applied to other datasets with obvious seasonality. Full article

Water pipe failures result in real water losses in the form of water outflowing into the porous medium, such as the surrounding soil. Such an outflow may result in the creation of suffosion holes. The appropriate management of the water supply network may contribute to reducing the number of failures, but due to their random nature, it is not possible to completely eliminate them. Therefore, alternative solutions are being sought to reduce the effects of the failures. This article presents a fragment of the results from a broader scope of the research, which attempted to determine the outflow zone in relation to the fractal characteristics of water outflows. The research included the analysis of the actual geometric structures created by the water outflows, which were simplified into linear structures using isometric transformations. The structures were analyzed in terms of the parameters characterizing them, including their fractal dimensions. As a result, it was found that there was no relationship between the analyzed fractal parameters and the leakage area or hydraulic pressure in the water pipe. However, the influence of the number of points forming each linear structure on the analyzed parameters was shown. This allowed for the determination of further research aimed at estimating the size of the water outflow zone after the unsealing of an underground water supply pipe. Full article

Attention plays an important role in not only the awareness and perception of tinnitus but also its interactions with external sounds. Recent evidence suggests that attention is heightened in the tinnitus brain, likely as a result of relatively local cortical changes specific to deafferentation sites or global changes that help maintain normal cognitive capabilities in individuals with hearing loss. However, most electrophysiological studies have used passive listening paradigms to probe the tinnitus brain and produced mixed results in terms of finding a distinctive biomarker for tinnitus. Here, we designed a selective attention task, in which human adults attended to one of two interleaved tonal (500 Hz and 5 kHz) sequences. In total, 16 tinnitus (5 females) and 13 age- and hearing-matched control (8 females) subjects participated in the study, with the tinnitus subjects matching the tinnitus pitch to 5.4 kHz (range = 1.9–10.8 kHz). Cortical responses were recorded in both passive and attentive listening conditions, producing no differences in P1, N1, and P2 between the tinnitus and control subjects under any conditions. However, a different pattern of results emerged when the difference was examined between the attended and unattended responses. This attention-modulated cortical response was significantly greater in the tinnitus than control subjects: 3.9-times greater for N1 at 5 kHz (95% CI: 2.9 to 5.0, p = 0.007, η_p² = 0.24) and 3.0 for P2 at 500 Hz (95% CI: 1.9 to 4.5, p = 0.026, η_p² = 0.17). We interpreted the greater N1 modulation as local neural changes specific to the tinnitus frequency and the greater P2 as global changes to hearing loss. These two cortical measures were used to differentiate between the tinnitus and control subjects, producing 83.3% sensitivity and 76.9% specificity (AUC = 0.81, p = 0.006). These results suggest that the tinnitus brain is more plastic than that of the matched non-tinnitus controls and that the attention-modulated cortical response can be developed as a clinically meaningful biomarker for tinnitus. Full article

Agricultural green development represents an environmentally friendly and resource-efficient agricultural model, and it is a key way to achieve sustainable agricultural development. With the rapid rise of the digital economy, its influence is gradually spreading from urban to rural areas, and it has played a significant and far-reaching role in promoting the green transformation of agriculture. This paper employs the entropy weight method to measure the level of digital economy and agricultural green development in rural areas in 30 provincial administrative regions in China from 2012 to 2021 and analyzes the relationship between the two and the mechanisms behind it. The research results show that (1) the rural digital economy significantly promotes agricultural green development. (2) With the enhancement of agricultural green development, the impact of the rural digital economy on it initially increases and then declines. (3) The rural digital economy fosters agricultural green development by advancing agricultural technology, easing credit constraints, and promoting agricultural industry agglomeration. (4) Environmental regulation intensifies the positive influence of the rural digital economy on agricultural green development. This research significantly enhances our understanding of the mechanism by which the rural digital economy facilitates agricultural green development. It offers empirical evidence and recommendations for the government to formulate and implement effective policies to advance agricultural green transformation in the context of digital economy trends. Full article

Type I collagen, prevalent in the extracellular matrix, is biocompatible and crucial for tissue engineering and wound healing, including angiogenesis and vascular maturation/stabilization as required processes of newly formed tissue constructs or regeneration. Sometimes, improper vascularization causes unexpected outcomes. Vascularization failure may be caused by extracellular matrix collagen and non-collagen components heterogeneously. This study compares the angiogenic potential of collagen type I-based scaffolds and collagen type I/glycosaminoglycans scaffolds by using the chick embryo chorioallantoic membrane (CAM) model and IKOSA digital image analysis. Two clinically used biomaterials, Xenoderm (containing type I collagen derived from decellularized porcine extracellular matrix) and a dual-layer collagen sponge (DLC, with a biphasic composition of type I collagen combined with glycosaminoglycans) were tested for their ability to induce new vascular network formation. The AI-based IKOSA app enhanced the research by calculating from stereomicroscopic images angiogenic parameters such as total vascular area, branching sites, vessel length, and vascular thickness. The study confirmed that Xenoderm caused a fast angiogenic response and substantial vascular growth, but was unable to mature the vascular network. DLC scaffold, in turn, produced a slower angiogenic response, but a more steady and organic vascular maturation and stabilization. This research can improve collagen-based knowledge by better assessing angiogenesis processes. DLC may be preferable to Xenoderm or other materials for functional neovascularization, according to the findings. Full article

Intraductal carcinoma of the prostate (IDC-P) has emerged as a distinct entity with significant clinical implications in prostate cancer (PCa) management. Despite historically being considered an extension of invasive PCa, IDC-P shows unique biological characteristics that challenge traditional diagnostic and therapeutic settings. This review explores the clinical management of IDC-P. While the diagnosis of IDC-P relies on specific morphological criteria, its detection remains challenging due to inter-observer variability. Emerging evidence underscores the association of IDC-P with aggressive disease and poor clinical outcomes across various PCa stages. However, standardized management guidelines for IDC-P are lacking. Recent studies suggest considering adjuvant and neoadjuvant therapies in specific patient cohorts to improve outcomes and tailor treatment strategies based on the IDC-P status. However, the current level of evidence regarding this is low. Moving forward, a deeper understanding of the pathogenesis of IDC-P and its interaction with conventional PCa subtypes is crucial for refining risk stratification and therapeutic interventions. Full article

With the rapid advancements in computer vision, using deep learning for strawberry disease recognition has emerged as a new trend. However, traditional identification methods heavily rely on manual discernment, consuming valuable time and imposing significant financial losses on growers. To address these challenges, this paper presents BerryNet-Lite, a lightweight network designed for precise strawberry disease identification. First, a comprehensive dataset, encompassing various strawberry diseases at different maturity levels, is curated. Second, BerryNet-Lite is proposed, utilizing transfer learning to expedite convergence through pre-training on extensive datasets. Subsequently, we introduce expansion convolution into the receptive field expansion, promoting more robust feature extraction and ensuring accurate recognition. Furthermore, we adopt the efficient channel attention (ECA) as the attention mechanism module. Additionally, we incorporate a multilayer perceptron (MLP) module to enhance the generalization capability and better capture the abstract features. Finally, we present a novel classification head design approach which effectively combines the ECA and MLP modules. Experimental results demonstrate that BerryNet-Lite achieves an impressive accuracy of 99.45%. Compared to classic networks like ResNet34, VGG16, and AlexNet, BerryNet-Lite showcases superiority across metrics, including loss value, accuracy, precision, F1-score, and parameters. It holds significant promise for applications in strawberry disease identification. Full article

Sesame seeds are important resources for relieving oxidation stress-related diseases. Although a significant variation in seeds’ antioxidant capability is observed, the underlying biochemical and molecular basis remains elusive. Thus, this study aimed to reveal major seed components and key molecular mechanisms that drive the variability of seeds’ antioxidant activity (AOA) using a panel of 400 sesame accessions. The seeds’ AOA, total flavonoid, and phenolic contents varied from 2.03 to 78.5%, 0.072 to 3.104 mg CAE/g, and 2.717 to 21.98 mg GAE/g, respectively. Analyses revealed that flavonoids and phenolic acids are the main contributors to seeds’ AOA variation, irrespective of seed coat color. LC-MS-based polyphenol profiling of high (HA) and low (LA) antioxidant seeds uncovered 320 differentially accumulated phenolic compounds (DAPs), including 311 up-regulated in HA seeds. Tricin, persicoside, 5,7,4′,5′-tetrahydro-3′,6-dimethoxyflavone, 8-methoxyapigenin, and 6,7,8-tetrahydroxy-5-methoxyflavone were the top five up-regulated in HA. Comparative transcriptome analysis at three seed developmental stages identified 627~2357 DEGs and unveiled that differential regulation of flavonoid biosynthesis, phenylpropanoid biosynthesis, and stilbene biosynthesis were the key underlying mechanisms of seed antioxidant capacity variation. Major differentially regulated phenylpropanoid structural genes and transcription factors were identified. SINPZ0000571 (MYB), SINPZ0401118 (NAC), and SINPZ0500871 (C3H) were the most highly induced TFs in HA. Our findings may enhance quality breeding. Full article

This study presents a comprehensive examination of Pinus kesiya var. langbianensis (Pinus kesiya var. langbianensis), the primary resin-extraction tree species in Yunnan Province, China. In this study, we formulated different concentration gradients of 0.25%, 0.5%, 1%, and 2% of diquat solution as tapping stimulant to test the effect of different concentrations on the resin gain rate of Pinus kesiya, and analyzed the relationship between anatomical structure, major chemical composition of turpentine and resin yield by methods such as wood anatomy and chemical composition analysis of turpentine. The primary focus of the investigation was on exploring the interrelationships among resin-tapping stimulants, anatomical structures, turpentine components, and resin yield. Research findings demonstrate a significant enhancement in resin production due to the application of stimulants, with the highest increase rate reaching 55% in a specific group, while others achieved approximately 30% increments. Moreover, measurement data about resin duct dimensions indicate a noteworthy increase in resin duct area for the stimulant-treated group compared to the control group. However, it should be noted that the impact on resin duct area by varying stimulant concentrations was relatively minor. Furthermore, continuous observation of resin extraction from different resin-yield classes of P. kesiya revealed insignificant variation in resin yield over time for the low and moderate resin-yield groups. In contrast, the high resin-yield group exhibited a gradual increase in resin production. Interestingly, the high resin-yield group exhibited the smallest resin duct area, but the highest resin duct density, indicating an interconnectedness of resin duct-related data that influences resin yield. Additionally, correlative investigations between anatomical structures and resin yield demonstrate a positive correlation between resin duct area and resin yield, total resin production, and average resin yield. This underscores the importance of resin duct area as a significant factor in resin production. On the other hand, the influence of stimulant concentrations on the turpentine components was found to be negligible. Overall, the correlation results suggest that turpentine components cannot reliably predict or differentiate between high and low resin-yield trees. This study provides a comprehensive analysis of the interrelationships among stimulants, anatomical structures, and turpentine components, offering a theoretical foundation for the resin extraction and resin processing industries in Yunnan Province. Full article

The reconstruction of patients who possess multi morbid medical histories remains a challenge. With the ever-increasing number of patients with diabetes, infections, and trauma, there is a consistent need for promotion of soft tissue healing and a reliable substrate to assist with every aspect of soft tissue reconstruction, as well as the loss of fascial domain. Several proprietary products filled some of these needs but have failed to fulfill the needs of the clinician when faced with reconstructing multiple soft tissue systems, such as the integument and the musculoskeletal system. In this paper we discuss the use of decellularized human dermis (DermaPure^®, Tissue Regenix, Universal City, TX, USA) through which a unique human tissue processing technique (dCELL^® technology, Tissue Regenix, Universal City, TX, USA) and the creation of multiple product forms have proven to exhibit versatility in a wide range of clinical needs for successful soft tissue reconstruction. The background of human tissue processing, basic science, and early clinical studies are detailed, which has translated to the rationale for the success of this unique soft tissue substrate in orthoplastic reconstruction, which is also provided here in detail. Full article

As one of the four major bay areas in the world, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a highly integrated mega urban agglomeration and its unparalleled urbanization has induced prominent land contradictions between humans and nature, which hinders its sustainability and has become the primary concern in this region. In this paper, we probed the historical characteristics of land use and land cover change (LUCC) in the GBA from 2005 to 2015, and forecasted its future land use pattern for 2030, 2050, and 2070, using a cellular automata–Markov (CA–Markov) model, under three typical tailored scenarios, i.e., urban development (UD), cropland protection (CP), and ecology security (ES), for land use optimization. The major findings are as follows: (1) The encroachments of build-up land on the other land uses under rapid urbanization accounted for the leading forces of LUCCs in the past decade. Accordingly, the urban sprawl was up to 1441.73 km² (23.47%), with cropland, forest land, and water areas reduced by 570.77 km² (4.38%), 526.05 km² (1.76%), and 429.89 km² (10.88%), respectively. (2) Based on the validated CA–Markov model, significant differences are found in future land use patterns under multiple scenarios, with the discrepancy magnified over time and driven by different orientations. (3) Through comprehensive comparisons and tradeoffs, the ES scenario mode seems optimal for the GBA in the next decades, which optimizes the balance between socio-economic development and ecological protection. These results serve as an early warning for future land problems and can be applied to land use management and policy formulation to promote the sustainable development of the GBA. Full article

Ember accumulation on and around homes can lead to spot fires and home ignition. Post wildland fire assessments suggest that this mechanism is one of the leading causes of home destruction in wildland urban interface (WUI) fires. However, the process of ember deposition and accumulation on and around houses remains poorly understood. Herein, we develop a deep learning (DL) model to analyze data from a series of ember-related wind tunnel experiments for a range of wind conditions and roof slopes. The developed model is designed to identify building roof regions where embers will remain in contact with the rooftop. Our results show that the DL model is capable of accurately predicting the position and fraction of the roof on which embers remain in place as a function of the wind speed, wind direction, roof slope, and location on the windward and leeward faces of the rooftop. The DL model was augmented with explainable AI (XAI) measures to examine the extent of the influence of these parameters on the rooftop ember coverage and potential ignition. Full article

Group B Streptococcus (GBS) is a major cause of contagious bovine mastitis (CBM) in Brazil. The GBS population is composed of host-generalist and host-specialist lineages, which may differ in antimicrobial resistance (AMR) and zoonotic potential, and the surveillance of bovine GBS is crucial to developing effective CBM control and prevention measures. Here, we investigated bovine GBS isolates (n = 156) collected in Brazil between 1987 and 2021 using phenotypic testing and whole-genome sequencing to uncover the molecular epidemiology of bovine GBS. Clonal complex (CC) 61/67 was the predominant clade in the 20th century; however, it was replaced by CC91, with which it shares a most common recent ancestor, in the 21st century, despite the higher prevalence of AMR in CC61/67 than in CC91, and high selection pressure for AMR from indiscriminate antimicrobial use in the Brazilian dairy industry. CC103 also emerged as a dominant CC in the 21st century, and a considerable proportion of herds had two or more GBS strains, suggesting poor biosecurity and within-herd evolution due to the chronic nature of CBM problems. The majority of bovine GBS belonged to serotype Ia or III, which was strongly correlated with CCs. Ninety-three isolates were resistant to tetracycline (≥8 μg/mL; tetO = 57, tetM = 34 or both = 2) and forty-four were resistant to erythromycin (2.0 to >4 μg/mL; ermA = 1, ermB = 38, mechanism unidentified n = 5). Only three isolates were non-susceptible to penicillin (≥8.0 μg/mL), providing opportunities for improved antimicrobial stewardship through the use of narrow-spectrum antimicrobials for the treatment of dairy cattle. The common bovine GBS clades detected in this study have rarely been reported in humans, suggesting limited risk of interspecies transmission of GBS in Brazil. This study provides new data to support improvements to CBM and AMR control, bovine GBS vaccine design, and the management of public health risks posed by bovine GBS in Brazil. Full article

The proper coordination of directional overcurrent relays (DOCRs) is crucial in electrical power systems. The coordination of DOCRs in a multi-loop power system is expressed as an optimization problem. The aim of this study focuses on improving the protection system’s performance by minimizing the total operating time of DOCRs via effective coordination with main and backup DOCRs while keeping the coordination constraints within allowable limits. The coordination problem of DOCRs is solved by developing a new application strategy called Fractional Order Derivative Moth Flame Optimizer (FODMFO). This approach involves incorporating the ideas of fractional calculus (FC) into the mathematical model of the conventional moth flame algorithm to improve the characteristics of the optimizer. The FODMFO approach is then tested on the coordination problem of DOCRs in standard power systems, specifically the IEEE 3, 8, and 15 bus systems as well as in 11 benchmark functions including uni- and multimodal functions. The results obtained from the proposed method, as well as its comparison with other recently developed algorithms, demonstrate that the combination of FOD and MFO improves the overall efficiency of the optimizer by utilizing the individual strengths of these tools and identifying the globally optimal solution and minimize the total operating time of DOCRs up to an optimal value. The reliability, strength, and dependability of FODMFO are supported by a thorough statistics study using the box-plot, histograms, empirical cumulative distribution function demonstrations, and the minimal fitness evolution seen in each distinct simulation. Based on these data, it is evident that FODMFO outperforms other modern nature-inspired and conventional algorithms. Full article

Artificial intelligence, particularly machine learning, has gained prominence in medical research due to its potential to develop non-invasive diagnostics. Pulmonary hypertension presents a diagnostic challenge due to its heterogeneous nature and similarity in symptoms to other cardiovascular conditions. Here, we describe the development of a supervised machine learning model using non-invasive signals (orthogonal voltage gradient and photoplethysmographic) and a hand-crafted library of 3298 features. The developed model achieved a sensitivity of 87% and a specificity of 83%, with an overall Area Under the Receiver Operator Characteristic Curve (AUC-ROC) of 0.93. Subgroup analysis showed consistent performance across genders, age groups and classes of PH. Feature importance analysis revealed changes in metrics that measure conduction, repolarization and respiration as significant contributors to the model. The model demonstrates promising performance in identifying pulmonary hypertension, offering potential for early detection and intervention when embedded in a point-of-care diagnostic system. Full article

Pickup vehicle scheduling in steel logistics parks is an important problem for determining the outbound efficiency of steel products. In a steel logistics park, each yard contains different types of steel products, which provides flexible yard selection for each pickup operation. In this case, the yard allocation and the loading sequence for each vehicle must be considered simultaneously in pickup vehicle scheduling, which greatly increases the scheduling complexity. To overcome this challenge, in this paper, we propose a pickup vehicle scheduling problem with mixed steel storage (PVSP-MSS) to optimize the makespan of pickup vehicles and the makespan of steel logistics parks simultaneously. The optimization problem is formulated as a multi-objective mixed-integer linear programming model, and an enhanced algorithm based on SPEA2 (ESPEA) is proposed to solve the problem with a high efficiency. In the ESPEA, a cooperative initialization strategy is firstly proposed to initialize the vehicle pickup sequence for each yard. Then, an insertion decoding method is designed to improve the scheduling efficiency, utilizing the idle time of a yard. Furthermore, local search technology based on critical paths is proposed for the ESPEA to improve the solution quality. Experiments are executed based on data collected from a real steel logistics park. The results confirm that the ESPEA can significantly reduce both the makespan of each pickup vehicle and the makespan of the steel logistics park. Full article

Background: The prevalence of obesity has increased in patients with type 1 diabetes (T1D) and latent autoimmune diabetes of the adult (LADA), limiting the use of clinical features such as the body mass index for its differentiation with type 2 diabetes (T2D). Additionally, some patients with maturity-onset diabetes of the young (MODY) or LADA are misdiagnosed as having T2D. The evaluation of autoantibodies and genetic testing are not fully available. We aimed to evaluate the utility of a widely available and less expensive diagnostic tool such as C-peptide to differentiate between T1D, T2D, MODY, and LADA. Methods: Our study included 38 patients with T1D, 49 with T2D, 13 with MODY, and 61 with LADA. We recorded anthropometric measurements, biochemical profiles, and antidiabetic treatment and determined C-peptide, anti-GAD65, and anti-IA2 antibodies. Results: C-peptide concentration differed significantly among populations (T1D: 0.2 ng/mL; T2D: 2.4 ng/mL; MODY: 1.14 ng/mL; LADA: 1.87 ng/mL). Through a ROC curve, we observed that the C-peptide cut-off point of 0.95 ng/mL allows differentiation between T1D and T2D (sensitivity 82%, specificity 77%); 0.82 ng/mL between T1D and LADA (sensitivity 82%, specificity 77%); and 1.65 ng/mL between T2D and MODY (sensitivity 72%, specificity 72%). Conclusions: C-peptide is useful for the diagnostic differentiation of patients with type 1, type 2 diabetes, MODY, and LADA. Full article

The aim of the present study was to evaluate depressive-like, anxiety-like, and perseverative-like behaviors in a binge eating model. Juvenile Wistar rats, using the binge eating model, were compared to caloric restriction, induced stress, and control groups. Rats of the induced stress group presented binge-like behaviors in standard food intake in the second cycle of the experiment when compared to the caloric restriction group and the binge eating model group. Depressive-like behavior was observed in the binge eating model group with longer immobility time (p < 0.001) and less swim time (p < 0.001) in comparison to the control group. Anxiety-like behavior was observed by shorter duration of burying latency in the binge eating model group when compared to the induced stress group (p = 0.04) and a longer duration of burying time when compared to the control group (p = 0.02). We observed perseverative-like behavior by the binge model group, who made more entries to the new arm (p = 0.0004) and spent a longer time in the new arm when compared to the control group (p = 0.0001). Our results show differences in behaviors between the groups of rats studied. These results suggest that calorie restriction–refeeding, along with stress, may lead to depressive-like, anxiety-like, and perseverative-like behavioral changes in male Wistar rats. Full article

Aging and age-related diseases are associated with a decline in the capacity of protein turnover. Intrinsically disordered proteins, as well as proteins misfolded and oxidatively damaged, prone to aggregation, are preferentially digested by the ubiquitin-independent proteasome system (UIPS), a major component of which is the 20S proteasome. Therefore, boosting 20S activity constitutes a promising strategy to counteract a decrease in total proteasome activity during aging. One way to enhance the proteolytic removal of unwanted proteins appears to be the use of peptide-based activators of the 20S. In this study, we synthesized a series of peptides and peptidomimetics based on the C-terminus of the Rpt5 subunit of the 19S regulatory particle. Some of them efficiently stimulated human 20S proteasome activity. The attachment of the cell-penetrating peptide TAT allowed them to penetrate the cell membrane and stimulate proteasome activity in HEK293T cells, which was demonstrated using a cell-permeable substrate of the proteasome, TAS3. Furthermore, the best activator enhanced the degradation of aggregation-prone α-synuclein and Tau-441. The obtained compounds may therefore have the potential to compensate for the unbalanced proteostasis found in aging and age-related diseases. Full article

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease widespread in Europe and Asia. HFRS is caused by negative-sensed single-stranded RNA orthohantaviruses transmitted to humans through inhaling aerosolized excreta of infected rodents. Symptoms of HFRS include acute kidney injury, thrombocytopenia, hemorrhages, and hypotension. The immune response raised against viral antigens plays an important role in the pathogenesis of HFRS. Inhibitory co-receptors are essential in regulating immune responses, mitigating immunopathogenesis, and reducing tissue damage. Our research showed an increased soluble form of inhibitory co-receptors TIM-3, LAG-3, and PD-1 in HFRS patients associated with disease severity. Our study aimed to investigate the impact of HFRS on the concentrations of soluble forms of inhibitory receptors TIM-3, LAG-3, and PD-1 in the patient’s serum and the potential correlation with key clinical parameters. Our study aimed to investigate the impact of HFRS on the concentrations of soluble forms of inhibitory receptors TIM-3, LAG-3, and PD-1 in the patient’s serum and their possible association with relevant clinical parameters. Using multiplex immunoassay, we found elevated levels of TIM-3, LAG-3, and PD-1 proteins in the serum of HFRS patients. Furthermore, increased levels were associated with creatinine, urea, lactate dehydrogenase concentrations, and platelet count. These findings suggest that these proteins play a role in regulating the immune response and disease progression. Full article