Cisplatin is a potent compound in anti-tumor chemotherapy; however, its clinical utility is hampered by dose-limiting nephrotoxicity. This study investigated whether papaverine could mitigate cisplatin-induced kidney damage while preserving its chemotherapeutic efficacy. Integrative bioinformatics analysis predicted papaverine modulation of the mechanistic pathways related to cisplatin renal toxicity; notably, mitogen-activated protein kinase 1 (MAPK1) signaling. We validated protective effects in normal kidney cells without interfering with cisplatin cytotoxicity on a cancer cell line. Concurrent in vivo administration of papaverine alongside cisplatin in rats prevented elevations in nephrotoxicity markers, including serum creatinine, blood urea nitrogen, and renal oxidative stress markers (malondialdehyde, inducible nitric oxide synthase (iNOS), and pro-inflammatory cytokines), as tumor necrosis factor alpha (TNF-α), monocyte chemoattractant protein 1 (MCP-1), and interleukin-6 (IL-6). Papaverine also reduced apoptosis markers such as Bcl2 and Bcl-2–associated X protein (Bax) and kidney injury molecule-1 (KIM-1), and histological damage. In addition, it upregulates antioxidant enzymes like catalase (CAT), superoxide dismutase (SOD) and glutathione peroxidase (GPx) while boosting anti-inflammatory signaling interleukin-10 (IL-10). These effects were underlined by the ability of Papaverine to downregulate MAPK-1 expression. Overall, these findings show papaverine could protect against cisplatin kidney damage without reducing its cytotoxic activity. Further research would allow the transition of these results to clinical practice. Full article

Background: The fitness sector has experienced significant expansion, with fitness instructors (FIs) playing a pivotal role. Given the demands of their profession, understanding their health profile is crucial. This study’s purpose is to explore the prevalence of fitness instructors’ occupational health-related problems. Methods: A questionnaire covering sociodemographic, occupational, and health-related items was administered. Statistical analyses, including Mann–Whitney U and chi-square tests, Spearman’s rho correlations, and logistic regressions, were conducted. Results: Fifty-nine FIs reported occupational health-related problems, with the majority occurring during instruction (66.1%), being muscular (32.2%), and knee (15.3%), the most common type and localization. Significant statistical differences were observed between injured and non-injured FIs, including sex (p = 0.012), years as an FI (p = 0.001), weekly days worked (p = 0.039), and daily hours worked (p = 0.013). Weak negative (−0.284 – −0.362) statistically significant correlations were found between health problems; weight; height; main activity; and FIs in the workplace. Logistic regressions identified significant models showing that having a sport/physical exercise background and practicing it regularly were less likely to report bursitis (OR 0.018; p = 0.020) and hip injuries (OR 0.026; p = 0.037). Conclusions: Approximately one-third of FIs reported occupational-related health problems, predominantly musculoskeletal injuries. Sociodemographic, personal, and occupational factors appear to influence the prevalence of these health problems. Full article

This paper aims to highlight examples of artistic motifs common throughout Egyptian history but augmented in novel ways during the 27th Dynasty, a time when Egypt was part of the Achaemenid empire and ruled by Persian kings. These kings represented themselves as traditional pharaohs within Egypt’s borders and utilized longstanding Egyptian artistic motifs in their monumental constructions. These motifs, however, were manipulated in subtle ways to send targeted messages to audience(s) of this art. Art historians tend to situate visual styles and motifs within the longue durée of artistic tradition and pick a singular, official, and centralized perspective to narrate the history and reception of that art. In the case of Egypt, this perspective is often that of the king, and there is an assumption that there was a monolithic message sent to his people. But we are not dealing with a homogenous people; a diverse population would have had varied reactions to and interpretations of this visual signaling. By highlighting both the augmentation of traditional motifs undertaken by the Achaemenid administration and the multiplicity of perspectives they held for their audience(s), we can better understand ancient art as being dynamic in function and interpretation, rather than as a static snapshot of carbon-copied royal authority. Full article

Aging is a time-dependent complex biological process of organisms with gradual deterioration of the anatomical and physiological functions. The role of gut microbiota is inevitable in the aging process. Probiotic interventions improve gut homeostasis and support healthy aging by enhancing beneficial species and microbial biodiversity in older adults. The present preliminary clinical trial delves into the impact of an 8-week Lactobacillus rhamnosus intervention (10 × 10⁹ CFU per day) on the glycaemic index, lipid profile, and microbiome of elderly subjects. Body weight, body fat, fasting blood glucose, total cholesterol, triglyceride, high-density lipoprotein, and low-density lipoprotein (LDL) are assessed at baseline (Week 0) and after treatment (Week 8) in placebo and probiotic groups. Gaussian regression analysis highlights a significant improvement in LDL cholesterol in the probiotic group (p = 0.045). Microbiome analysis reveals numeric changes in taxonomic abundance at various levels. At the phylum level, Proteobacteria increases its relative frequency (RF) from 14.79 ± 5.58 at baseline to 23.46 ± 8.02 at 8 weeks, though statistically insignificant (p = 0.100). Compared to the placebo group, probiotic supplementations significantly increased the proteobacteria abundance. Genus-level analysis indicates changes in the abundance of several microbes, including Escherichia-Shigella, Akkermansia, and Bacteroides, but only Butyricimonas showed a statistically significant level of reduction in its abundance. Probiotic supplementations significantly altered the Escherichia-Shigella and Sutterella abundance compared to the placebo group. At the species level, Bacteroides vulgatus substantially increases after probiotic treatment (p = 0.021). Alpha and beta diversity assessments depict subtle shifts in microbial composition. The study has limitations, including a small sample size, short study duration, single-strain probiotic use, and lack of long-term follow-up. Despite these constraints, the study provides valuable preliminary insights into the multifaceted impact of L. rhamnosus on elderly subjects. Further detailed studies are required to define the beneficial effect of L. rhamnosus on the health status of elderly subjects. Full article

This paper discusses the health evaluation of an urban rail transit switch machine. In this paper, the working current data of the S700K switch machine are processed, and four common abnormal operating current curves are obtained through the existing data. Then, the MLP is used as the feature extractor of the action current curve to analyze the input action current data, learn and capture deep features from raw current data as Q-networks, and build MLP-DQN models. The monitoring of the abnormal state operation current of the switch machine is optimized by learning and optimizing the model weight through repeated experience. The experimental results show that the training accuracy of this model is stable at about 96.67%. Finally, the Fréchet distance was used to analyze the abnormal motion current curve, combined with the occurrence frequency and repair complexity of the abnormal type curve, the calculated results were analyzed, and the health of the switch machine was evaluated, which proved the high efficiency and superiority of the MLP-DQN method in the fault diagnosis of the switch machine equipment. The good health evaluation function of the switch machine can effectively support the maintenance of the equipment, and it has an important reference value for the intelligent operation and maintenance of subway signal equipment. The research results mark the maintenance of key equipment of urban rail transit systems, represent a solid step towards intelligent and automated transformation, and provide strong technical support for the safe operation and intelligent management of future rail transit systems. Full article

Although the biochemical composition and biological properties of the volatile fraction of the halophyte sea fennel (Crithmum maritimum L.) have been largely described, little is known about its polar constituents and bioactivities. Here, a hydromethanolic extract of Crithmum maritimum (L.) leaves was fractionated, and the fractions were evaluated in vitro for antioxidant (using DPPH, ABTS, and FRAP bioassays), anti-inflammatory (inhibition of NO production in RAW 264.7 macrophages), antidiabetic (alpha-glucosidase inhibition), neuroprotective (inhibition of acetylcholinesterase), and skin-protective (tyrosinase and melanogenesis inhibitions) activities. Polar fractions of the extract were rich in phenolics and, correlatively, displayed a strong antioxidant power. Moreover, fractions eluted with MeOH₂₀ and MeOH₈₀ exhibited a marked inhibition of alpha-glucosidase (IC₅₀ = 0.02 and 0.04 mg/mL, respectively), MeOH₆₀ fractions showed a strong capacity to reduce NO production in macrophages (IC₅₀ = 6.4 μg/mL), and MeOH₈₀ and MeOH₁₀₀ fractions had strong anti-tyrosinase activities (630 mgKAE/gDW). NMR analyses revealed the predominance of chlorogenic acid in MeOH₂₀ fractions, 3,5-dicaffeoylquinic acid in MeOH₄₀ fractions, and 3-O-rutinoside, 3-O-glucoside, 3-O-galactoside, and 3-O-robinobioside derivatives of quercetin in MeOH₆₀ fractions. These compounds likely account for the strong antidiabetic, antioxidant, and anti-inflammatory properties of sea-fennel polar extract, respectively. Overall, our results make sea fennel a valuable source of medicinal or nutraceutical agents to prevent diabetes, inflammation processes, and oxidative damage. Full article

The purpose of this study was to indicate the validity of using enzymatically interesterified fats as a fat emulsion base. A study was conducted to determine the stability of emulsion systems based on enzymatically interesterified fats and fats containing mixed fats. The fats used in the modifications were mutton tallow and hemp oil. It was found that emulsions based on esterified fats, regardless of the type of modified fat, showed a higher shelf life and had high homogeneity. On the other hand, emulsions based on mixed fats already showed destabilization characteristics in the first days. Their structure was heterogeneous. Microscopic evaluation clearly showed large droplets of the dispersed phase, indicating a tendency to delaminate. Consumer evaluation showed that the sensory quality of the presented emulsion systems based on enzymatically interesterified fats was fully accepted by the participating consumers. Based on the results of the study, it was concluded that all of the consumer-evaluated emulsions received good or very good acceptance in terms of the sensory characteristics evaluated. Full article

In the competitive landscape of steel-strip production, ensuring the high quality of steel surfaces is paramount. Traditionally, human visual inspection has been the primary method for detecting defects, but it suffers from limitations such as reliability, cost, processing time, and accuracy. Visual inspection technologies, particularly automation techniques, have been introduced to address these shortcomings. This paper conducts a thorough survey examining vision-based methodologies related to detecting and classifying surface defects on steel products. These methodologies encompass statistical, spectral, texture segmentation based methods, and machine learning-driven approaches. Furthermore, various classification algorithms, categorized into supervised, semi-supervised, and unsupervised techniques, are discussed. Additionally, the paper outlines the future direction of research focus. Full article

Background: Cidofovir, an antiviral drug approved for cytomegalovirus retinitis, has emerged as an alternative treatment option for virally induced cutaneous and mucocutaneous conditions, as well as being trialed as a treatment for select neoplasms. In this review, we highlight the existing evidence, clinical uses, and rationale of using cidofovir for the treatment of cutaneous pathologies. Methods: A PubMed database literature search was conducted to identify relevant articles for inclusion in this review. Results: Cidofovir has several cutaneous applications in various formulations including intravenous, topical, and subcutaneous administrations. Primarily through case reports, case series, and retrospective reviews, cidofovir has demonstrated efficacy in treating a variety of virally induced conditions—verruca vulgaris, herpes simplex virus, molluscum contagiosum—as well as in adjuvant treatment for select neoplasms. The drug has shown efficacy in immunocompromised and immunocompetent adults and children alike. Conclusions: The body of literature supports the use of cidofovir as an effective and well-tolerated treatment for many viral cutaneous pathologies, and encourages further study for its use as an adjuvant therapy for neoplastic disease. Full article

Traditional fish farming methods suffer from backward production, low efficiency, low yield, and environmental pollution. As a result of thorough research using deep learning technology, the industrial aquaculture model has experienced gradual maturation. A variety of complex factors makes it difficult to extract effective features, which results in less-than-good model performance. This paper proposes a fish detection method that combines a triple attention mechanism with a You Only Look Once (TAM-YOLO)model. In order to enhance the speed of model training, the process of data encapsulation incorporates positive sample matching. An exponential moving average (EMA) is incorporated into the training process to make the model more robust, and coordinate attention (CA) and a convolutional block attention module are integrated into the YOLOv5s backbone to enhance the feature extraction of channels and spatial locations. The extracted feature maps are input to the PANet path aggregation network, and the underlying information is stacked with the feature maps. The method improves the detection accuracy of underwater blurred and distorted fish images. Experimental results show that the proposed TAM-YOLO model outperforms YOLOv3, YOLOv4, YOLOv5s, YOLOv5m, and SSD, with a mAP value of 95.88%, thus providing a new strategy for fish detection. Full article

In recent years, renewable and sustainable triboelectric nanogenerators have attracted attention due to their high energy conversion rate, and enhancing their functionality further contributes to their applicability across various fields. A pH-sensitive triboelectric nanogenerator (pH-TENG) has been prepared by electrostatic spinning technology, with anthocyanin as the pH indicator and environmentally friendly polyvinyl alcohol (PVA) as the substrate. Among many friction-negative materials, the pH-TENG exhibits the best combination with fluorinated ethylene propylene (FEP) and yields an open-circuit voltage of 62 V, a short-circuit current of 370 nA, and a transferred charge of 21.8 nC. At a frequency of 3 Hz, it can charge a 4.7 μF capacitor to 2 V within 45 s, effectively powering a thermometer. Furthermore, the presence of anthocyanin does not affect the pH-TENG’s power generation performance and enables the monitoring of a wide range of environmental pH changes, with an ΔE change of 28.8 ± 7.6. Therefore, pH-TENG prepared with environmentally friendly materials can bring new available materials to the biological and medical fields. Full article

Artificial retinas have revolutionized the lives of many blind people by enabling their ability to perceive vision via an implanted chip. Despite significant advancements, there are some limitations that cannot be ignored. Presenting all objects captured in a scene makes their identification difficult. Addressing this limitation is necessary because the artificial retina can utilize a very limited number of pixels to represent vision information. This problem in a multi-object scenario can be mitigated by enhancing images such that only the major objects are considered to be shown in vision. Although simple techniques like edge detection are used, they fall short in representing identifiable objects in complex scenarios, suggesting the idea of integrating primary object edges. To support this idea, the proposed classification model aims at identifying the primary objects based on a suggested set of selective features. The proposed classification model can then be equipped into the artificial retina system for filtering multiple primary objects to enhance vision. The suitability of handling multi-objects enables the system to cope with real-world complex scenarios. The proposed classification model is based on a multi-label deep neural network, specifically designed to leverage from the selective feature set. Initially, the enhanced images proposed in this research are compared with the ones that utilize an edge detection technique for single, dual, and multi-object images. These enhancements are also verified through an intensity profile analysis. Subsequently, the proposed classification model’s performance is evaluated to show the significance of utilizing the suggested features. This includes evaluating the model’s ability to correctly classify the top five, four, three, two, and one object(s), with respective accuracies of up to 84.8%, 85.2%, 86.8%, 91.8%, and 96.4%. Several comparisons such as training/validation loss and accuracies, precision, recall, specificity, and area under a curve indicate reliable results. Based on the overall evaluation of this study, it is concluded that using the suggested set of selective features not only improves the classification model’s performance, but aligns with the specific problem to address the challenge of correctly identifying objects in multi-object scenarios. Therefore, the proposed classification model designed on the basis of selective features is considered to be a very useful tool in supporting the idea of optimizing image enhancement. Full article

Remembering objects and their associated location (object–location memory; OLM), is a fundamental cognitive function, mediated by cortical and subcortical brain regions. Previously, the combination of OLM training and transcranial direct current stimulation (tDCS) suggested beneficial effects, but the evidence remains heterogeneous. Here, we applied focal tDCS over the right temporoparietal cortex in 52 participants during a two-day OLM training, with anodal tDCS (2 mA, 20 min) or sham (40 s) on the first day. The focal stimulation did not enhance OLM performance on either training day (stimulation effect: −0.09, 95%CI: [−0.19; 0.02], p = 0.08). Higher electric field magnitudes in the target region were not associated with individual performance benefits. Participants with content-related learning strategies showed slightly superior performance compared to participants with position-related strategies. Additionally, training gains were associated with individual verbal learning skills. Consequently, the lack of behavioral benefits through focal tDCS might be due to the involvement of different cognitive processes and brain regions, reflected by participant’s learning strategies. Future studies should evaluate whether other brain regions or memory-relevant networks may be involved in the modulation of object–location associations, investigating other target regions, and further exploring individualized stimulation parameters. Full article

Human activities overwhelm our environment with CO₂ and other global warming issues. The current electricity landscape necessitates a superior, continuous power supply and addressing such environmental concerns. These issues can be resolved by incorporating renewable energy sources (RESs) into the utility grid. Thus, this paper presents an optimized hybrid fuzzy logic self-tuning PID controller to control the automatic generation control (AGC) of various renewable sources. This controller regulates the frequency deviations of the power system and governs the change in the tie-line load of a multi-area hybrid energy system composed of wind, biomass, and photovoltaic energy sources. MATLAB Simulink software was applied to design and test the system. The PID controller has been tuned using four algorithms, namely, genetic algorithm (GA), pattern search (PS), simulated annealing (SA), and particle swarm optimization (PSO), and we compared the results with the proposed novel optimized PID controller (GA-fuzzy logic self-tuning technique) to validate it. The results show the superiority of the proposed hybrid GA-fuzzy logic self-tuning algorithm over the other algorithms in bringing the power system back to its regular operation. The paper also proposes an operation strategy to lower the utilization of biomass energy in the presence of other renewable energy sources. Full article

Background: GLP-1 RAs are widely used for T2DM treatment due to their cardiorenal and metabolic benefits. This study examines the risk of pancreatic cancer with GLP-1 RA use in patients with T2DM. Methods: We analyzed TriNetX’s deidentified research database using the U.S. Collaborative Network comprising 62 healthcare organizations across the U.S.A. Patients with T2DM were split into two cohorts: one receiving GLP-1 RAs, and one not receiving GLP-1 RAs. We excluded patients with known risk factors for pancreatic cancer, including pancreatic cysts, a personal or family history of BRCA1, BRCA2, CDKN2A, KRAS, MEN1, MLH1, MSH2, NOTCH1, PALB2, PMS2, and PRSS1S genes, family history of pancreatic cancer, and VHL syndrome. Using a 1:1 propensity score-matching model based on baseline characteristics and comorbidities, we created comparable cohorts. We then compared the rate of pancreatic cancer between the two cohorts at a 7-year interval. Results: Out of 7,146,015 identified patients with T2DM, 10.3% were on a GLP-1 RA and 89.7% were not. Post-PSM, 721,110 patients were in each group. Patients on GLP-1 RAs had a 0.1% risk compared to a 0.2% risk of pancreatic cancer in the 7-year timeframe. Conclusion: The use of GLP-1 RAs in patients with type 2 diabetes mellitus (T2DM) does not appear to substantially elevate the risk of pancreatic cancer; in fact, it may potentially exert a protective effect. Full article

This article proposes a proportional-integral-resonant (PIR) current control strategy for a wind-driven brushless doubly fed generator (WDBDFG) during network unbalance. Firstly, four control objectives of WDBDFG, including eliminating unbalanced currents of power winding (PW), pulsations of control winding (CW) currents, torque, and PW power, are discussed and different from current controls in which the references to PW currents were computed; the CW current references are derived here. Then, an improved CW current controller using a PIR controller is proposed to achieve different control objectives. In contrast with current controls, CW currents are not involved with sequence extraction in the proposed control and can be totally regulated only in a positive synchronous reference frame. Hence, the system control structure is greatly simplified, and dynamic characteristics are improved. Furthermore, in order to obtain completely decoupled control of current and average power, feedforward control, considering all the couplings and perturbances, is also applied in CW current loops. Simulation results for a 2 MW grid-connected WDBDFG show that the proposed control is capable of achieving four control objectives, including canceling CW current distortion, PW current unbalance, pulsations of PW active power or pulsations of reactive power, and machine torque. Its dynamic process is much more smoothly and quickly than that of current controls, and therefore the proposed control has better dynamic control characteristics during network unbalance. Full article

Tailored disaster preparedness interventions may be more effective and equitable, yet little is known about specific factors associated with disaster household preparedness for older adults and/or those with African American/Black identities. This study aims to ascertain differences in the importance features of machine learning models of household disaster preparedness for four groups to inform culturally tailored intervention recommendations for nursing practice. A machine learning model was developed and tested by combining data from the 2018, 2019, and 2020 Federal Emergency Management Agency National Household Survey. The primary outcome variable was a composite readiness score. A total of 252 variables from 15,048 participants were included. Over 10% of the sample self-identified as African American/Black and 30.3% reported being 65 years of age or older. Importance features varied regarding financial and insurance preparedness, information seeking and transportation between groups. These results reiterate the need for targeted interventions to support financial resilience and equitable resource access. Notably, older adults with Black racial identities were the only group where TV, TV news, and the Weather Channel was a priority feature for household disaster preparedness. Additionally, reliance on public transportation was most important among older adults with Black racial identities, highlighting priority needs for equity in disaster preparedness and policy. Full article

In the field of radar target detection, the conventional approach is to employ the range profile energy accumulation method for detecting extended targets. However, this method becomes ineffective when dealing with non-stationary and non-uniform radar clutter scenarios, as well as long-distance targets with weak radar cross sections (RCSs). In such cases, the signal-to-noise ratio (SNR) of the target echo is severely degraded, rendering the energy accumulation detection algorithm unreliable. To address this issue, this paper presents a new extended target detection method based on the maximum eigenvalue of the Hermitian matrix. This method utilizes a detection model that incorporates observed data and employs the likelihood ratio test (LRT) theory to derive the maximum eigenvalue detector at low SNR. Specifically, the detector constructs a matrix using a sliding window block with the available data and then computes the maximum eigenvalue of the covariance matrix. Subsequently, the maximum eigenvalue matrix is transformed into a one-dimensional eigenvalue image, enabling extended target detection through analogy with the energy accumulation detection method. Furthermore, this paper analyzes the proposed extended target detection method from both theoretical and experimental perspectives, validating it through field-measured data. The results obtained from the measured data demonstrate that the method effectively enhances the SNR in low SNR conditions, thereby improving target detection performance. Additionally, the method exhibits robustness across different scattering center targets. Full article

The effects of parity and somatic cell count in milk (SCC) threshold on the udder morphology, milkability traits, and milk composition was evaluated in 41 Canarian goats in mid-lactation. The animals were divided according to parity (1st, 2nd, and 3rd), and a SCC threshold of 2000 × 10³ cells/mL in milk was set to evaluate the effect of this factor on the different measured parameters. Results showed that primiparous goats had the udder smaller and less distended than multiparous goats, but no differences were detected on milk flow parameters. Furthermore, SCC and total bacterial count (TBC) tended to be higher when the parity increased. On the other hand, goats with SCC ≤ 2000 × 10³ had higher cistern-floor distance (CF) and lower TBC values compared with those goats with a count above the predetermined threshold. The results suggest that a reduction in SCC can be achieved by a selection of udder morphological traits. Moreover, milk flow parameters do not seem to be a tool to determine the udder health status in Canarian goats, but long-term studies are needed to verify it. Full article

The challenges and tensions experienced by mid-career faculty (MCF) can lead to frustration, disengagement, or leaving the professoriate altogether, a trend noted by researchers prior to and especially after the pandemic. In this article, we explore the role that collegial support and career reflection and assessment strategies targeting mid-career faculty can play to preserve institutional vitality, support faculty agency, and promote student success. Additionally, we propose initiatives and supports that may assist these faculty members in staying in the academy and staying well as they pursue professional fulfillment and work towards their goals, including promotion to full professorship. We contend that post-secondary campuses should invest in keeping MCF engaged because of the crucial roles they serve on campus. Full article

The endothelial glycocalyx (EGC) is a layer of proteoglycans (associated with glycosaminoglycans) and glycoproteins, which adsorbs plasma proteins on the luminal surface of endothelial cells. Its main function is to participate in separating the circulating blood from the inner layers of the vessels and the surrounding tissues. Physiologically, the EGC stimulates mechanotransduction, the endothelial charge, thrombocyte adhesion, leukocyte tissue recruitment, and molecule extravasation. Hence, severe impairment of the EGC has been implicated in various pathological conditions, including sepsis, diabetes, chronic kidney disease, inflammatory disorders, hypernatremia, hypervolemia, atherosclerosis, and ischemia/reperfusion injury. Moreover, alterations in EGC have been associated with altered responses to therapeutic interventions in conditions such as cardiovascular diseases. Investigation into the function of the glycocalyx has expanded knowledge about vascular disorders and indicated the need to consider new approaches in the treatment of severe endothelial dysfunction. This review aims to present the current understanding of the molecular mechanisms underlying cardiovascular diseases and to elucidate the impact of heart surgery on EGC dysfunction. Full article

Fowl aviadenovirus (FAdV) is a member of the Aviadenovirus genus within the Adenoviridae family. FAdVs are divided into five species based on genomic differences: Fowl aviadenovirus A to Fowl aviadenovirus E (FAdV-A to FAdV-E). They are classified into twelve serotypes (FAdV-1 to FAdV-8a and FAdV-8b to FAdV-11) through cross-neutralization tests. FAdVs are mainly associated with hepatitis hydropericardium syndrome (HHS), adenoviral gizzard erosion (AGE), and inclusion body hepatitis (IBH). The serotypes commonly involved in IBH are FAdV-2, FAdV-11, FAdV-8a, and FAdV-8b. IBH causes significant economic losses in the poultry industry, mainly due to high mortality, reduced productivity, and immunosuppression. This is the first case report on IBH in Chile caused—according to post-mortem findings, molecular analysis, sequencing, and phylogenetic analysis—by FAdV-11. Since the serotype had not previously been reported in Chile, continued monitoring of IBH cases is required to determine the serotype of the circulating FAdVs and adapt preventative vaccination programs. Full article