The concentration of ammonia (NH₃) and the temperature of the air surrounding the rabbit habitat in the farm condition basic health processes such as breathing and feeding. The indoor climate in a rabbit farm is largely conditioned by the ventilation system (air conditioning). The objective of this study was to build a numerical model based on computational fluid dynamics (CFD) in order to evaluate, by numerical simulations, the air dynamics of a rustic farm. After the validation of the computational model, the thermal gradient and ammonia concentration were analyzed under three wind incidence angles (0°, 45°, and 90° with respect to the horizontal Z axis of the facility). The results of the simulations showed that, in the area occupied by the rabbits (AOR), the concentration of ammonia with respect to the source was reduced by 37.3% in the most favorable case (wind direction at 45°), and 21.2% in the least favorable case (wind direction at 0°), and the indoor temperature presented a maximum difference of 2 °C with respect to the outside temperature. Climate control is a more expensive cost in rabbit farm exploitation; dynamics modulation can serve as an auxiliary tool for reducing health risks in rabbits. The use of models based on fluid dynamics allowed us to understand the efficiency of the ventilation system, which must be increased to reduce the found temperature gradient. Through numerical simulation it will be possible to find alternatives to increase the ventilation rate. Full article

Azobenzene photoswitches are fundamental components in contemporary approaches aimed at light-driven control of intelligent materials. Significant endeavors are directed towards enhancing the light-triggered reactivity of azobenzenes for such applications and obtaining water-soluble molecules able to act as crosslinkers in a hydrogel. Here, we report the rational design and the synthesis of azobenzene/alginate photoresponsive hydrogels endowed with fast reversible sol–gel transition. We started with the synthesis of three cationic azobenzenes (AZOs A, B, and C) and then incorporated them in sodium alginate (SA) to obtain photoresponsive supramolecular hydrogels (SMHGs). The photoresponsive properties of the azobenzenes were investigated by UV–Vis and ¹H NMR spectroscopy. Upon irradiation with 365 nm UV light, the azobenzenes demonstrated efficient trans-to-cis isomerization, with complete isomerization occurring within seconds. The return to the trans form took several hours, with AZO C exhibiting the fastest return, possibly due to higher trans isomer stability. In the photoresponsive SMHGs, the minimum gelation concentration (MGC) of azobenzenes was determined for different compositions, indicating that small amounts of azobenzenes could induce gel formation, particularly in 5 wt% SA. Upon exposure to 365 nm UV light, the SMHGs exhibited reversible gel–sol transitions, underscoring their photoresponsive nature. This research offers valuable insights into the synthesis and photoresponsive properties of cationic, water-soluble azobenzenes, as well as their potential application in the development of photoresponsive hydrogels. Full article

Bivalves hold an important role in marine aquaculture and the identification of growth-related genes in bivalves could contribute to a better understanding of the mechanism governing their growth, which may benefit high-yielding bivalve breeding. Somatostatin receptor (SSTR) is a conserved negative regulator of growth in vertebrates. Although SSTR genes have been identified in invertebrates, their involvement in growth regulation remains unclear. Here, we identified seven SSTRs (PySSTRs) in the Yesso scallop, Patinopecten yessoensis, which is an economically important bivalve cultured in East Asia. Among the three PySSTRs (PySSTR-1, -2, and -3) expressed in adult tissues, PySSTR-1 showed significantly lower expression in fast-growing scallops than in slow-growing scallops. Then, the function of this gene in growth regulation was evaluated in dwarf surf clams (Mulinia lateralis), a potential model bivalve cultured in the lab, via RNA interference (RNAi) through feeding the clams Escherichia coli containing plasmids expressing double-stranded RNAs (dsRNAs) targeting MlSSTR-1. Suppressing the expression of MlSSTR-1, the homolog of PySSTR-1 in M. lateralis, resulted in a significant increase in shell length, shell width, shell height, soft tissue weight, and muscle weight by 20%, 22%, 20%, 79%, and 92%, respectively. A transcriptome analysis indicated that the up-regulated genes after MlSSTR-1 expression inhibition were significantly enriched in the fat digestion and absorption pathway and the insulin pathway. In summary, we systemically identified the SSTR genes in P. yessoensis and revealed the growth-inhibitory role of SSTR-1 in bivalves. This study indicates the conserved function of somatostatin signaling in growth regulation, and ingesting dsRNA-expressing bacteria is a useful way to verify gene function in bivalves. SSTR-1 is a candidate target for gene editing in bivalves to promote growth and could be used in the breeding of fast-growing bivalves. Full article

In this paper, we constructed a new and robust fixed point iterative scheme called the UO iterative scheme for the approximation of a contraction mapping. The scheme converges strongly to the fixed point of a contraction mapping. A rate of convergence result is shown with an example, and our scheme, when compared, converges faster than some existing iterative schemes in the literature. Furthermore, the stability and data dependence results are shown. Our new scheme is applied in the approximation of the solution to the oxygen diffusion model. Finally, our results are applied in the approximation of the solution to the boundary value problems using Green’s functions with an example. Full article

The article provides a narrative review of the social and cultural interpretation of pesticides in contemporary society. In so doing, it highlights the main fields of exploration investigated by social scientists concerning the perception and role played by these products among farmers and consumers. Following the WHO definition, pesticides are chemical compounds used to kill pests, including insects, rodents, fungi, and unwanted plants. They are contemporary cultural artefacts that social sciences explore in synergy with other disciplines to highlight their socio-cultural connections at both local and global levels. Specifically, the use of these products is connected with power relations, which are embedded in and reflect imbalances and inequalities in access to rights and resources, as well as specific articulation of the perception of risk arising from environmental contamination in terms of individual and collective psychophysical health. Furthermore, pesticides fit into various environmental conceptions and multiple local knowledge systems, representing the intersection of different cultural heritages, worldviews, and rationales that make the tradition–modernity dichotomy complex and dynamic. In this respect, therefore, pesticides can be understood not just as mere tools for agricultural practice but as vital windows through which to investigate multiple layers of meaning to support transitions towards sustainable pest management systems, both environmentally and socio-culturally. Full article

This paper proposes a novel five-dimensional (5D) memristor-based chaotic system by introducing a flux-controlled memristor into a 3D chaotic system with two stable equilibrium points, and increases the dimensionality utilizing the state feedback control method. The newly proposed memristor-based chaotic system has line equilibrium points, so the corresponding attractor belongs to a hidden attractor. By using typical nonlinear analysis tools, the complicated dynamical behaviors of the new system are explored, which reveals many interesting phenomena, including extreme homogeneous and heterogeneous multistabilities, hidden transient state and state transition behavior, and offset-boosting control. Meanwhile, the unstable periodic orbits embedded in the hidden chaotic attractor were calculated by the variational method, and the corresponding pruning rules were summarized. Furthermore, the analog and DSP circuit implementation illustrates the flexibility of the proposed memristic system. Finally, the active synchronization of the memristor-based chaotic system was investigated, demonstrating the important engineering application values of the new system. Full article

Groundwater, an invaluable resource crucial for irrigation and drinking purposes, significantly impacts human health and societal advancement. This study aims to evaluate the groundwater quality in the Mnasra region of the Gharb Plain, employing a comprehensive analysis of thirty samples collected from various locations, based on thirty-three physicochemical parameters. Utilizing tools like the Pollution Index of Groundwater (PIG), Nitrate Pollution Index (NPI), Water Quality Index (WQI), Irrigation Water Quality Index (IWQI), as well as Multivariate Statistical Approaches (MSA), and the Geographic Information System (GIS), this research identifies the sources of groundwater pollution. The results revealed Ca²⁺ dominance among cations and Cl⁻ as the primary anion. The Piper and Gibbs diagrams illustrated the prevalent Ca²⁺-Cl⁻ water type and the significance of water–rock interactions, respectively. The PIG values indicated that 86.66% of samples exhibited “Insignificant pollution”. NPI showed notable nitrate pollution (1.48 to 7.06), with 83.33% of samples rated “Good” for drinking based on the WQI. The IWQI revealed that 80% of samples were classified as “Excellent” and 16.66% as “Good”. Spatial analysis identified the eastern and southern sections as highly contaminated due to agricultural activities. These findings provide valuable insights for decision-makers to manage groundwater resources and promote sustainable water management in the Gharb region. Full article

Many botanic gardens are flourishing, and many others can learn from those leading the way; at the same time, all can form new allegiances informed by service research. We developed this paper to plant seeds for different stakeholders interested in putting a spotlight on botanic garden tourism opportunities. It is in response to a call to action by many stakeholders across the botanic garden sector for greater public engagement, to challenge plant awareness disparity, and to ensure the vitality and viability of the sector. Our commentary considers positive, transformative service making, marketing, management, and development. We recommend holistic, integrated services via ecosystemic thinking and collaborative partnerships across the sector and with non-traditional partnerships in the design of sustainable service ecosystems. It is envisaged that service research will spur on a more responsible, ethical, moral enterprise and sustainable botanic garden tourism with opportunities to drive positive, transformative change in meeting sustainable development goals for the good of plants, people, and planet. Full article

Efficient spectrum sharing is essential for maximizing data communication performance in Vehicular Networks (VNs). In this article, we propose a novel hybrid framework that leverages Multi-Agent Reinforcement Learning (MARL), thereby combining both centralized and decentralized learning approaches. This framework addresses scenarios where multiple vehicle-to-vehicle (V2V) links reuse the frequency spectrum preoccupied by vehicle-to-infrastructure (V2I) links. We introduce the QMIX technique with the Deep Q Networks (DQNs) algorithm to facilitate collaborative learning and efficient spectrum management. The DQN technique uses a neural network to approximate the Q value function in high-dimensional state spaces, thus mapping input states to (action, Q value) tables that facilitate self-learning across diverse scenarios. Similarly, the QMIX is a value-based technique for multi-agent environments. In the proposed model, each V2V agent having its own DQN observes the environment, receives observation, and obtains a common reward. The QMIX network receives Q values from all agents considering individual benefits and collective objectives. This mechanism leads to collective learning while V2V agents dynamically adapt to real-time conditions, thus improving VNs performance. Our research finding highlights the potential of hybrid MARL models for dynamic spectrum sharing in VNs and paves the way for advanced cooperative learning strategies in vehicular communication environments. Furthermore, we conducted an in-depth exploration of the simulation environment and performance evaluation criteria, thus concluding in a comprehensive comparative analysis with cutting-edge solutions in the field. Simulation results show that the proposed framework efficiently performs against the benchmark architecture in terms of V2V transmission probability and V2I peak data transfer. Full article

The increasing availability of longitudinal data (repeated numerical observations of the same units at different times) requires the development of flexible techniques to automatically detect errors in such data. Besides standard types of errors, which can be treated with generic error correction techniques, large longitudinal datasets may present specific problems not easily traceable by the generic techniques. In particular, after applying those generic techniques, time series in the data may contain trends, natural fluctuations and possible surviving errors. To study the data evolution, one main issue is distinguishing those elusive errors from the rest, which should be kept as they are and not flattened or altered. This work responds to this need by identifying some types of elusive errors and by proposing a statistical-mathematical approach to capture their complexity that can be applied after the above generic techniques. The proposed approach is based on a system of indicators and works at the formal level by studying the differences between consecutive values of data series and the symmetries and asymmetries of these differences. It operates regardless of the specific meaning of the data and is thus applicable in a variety of contexts. We implement this approach in a relevant database of European Higher Education institutions (ETER) by analyzing two key variables: “Total academic staff” and “Total number of enrolled students”, which are two of the most important variables, often used in empirical analysis as a proxy for size, and are considered by policymakers at the European level. The results are very promising. Full article

The Paleogene system of the Zhuyi Depression exhibits a pronounced mechanical compaction background. Despite this compaction, remarkable secondary porosity is observed in deep clastic rocks due to dissolution processes, with well-developed hydrocarbon reservoirs persisting in deeper strata. We conducted a comprehensive study utilising various analytical techniques to gain insights into the dissolution and transformation mechanisms of deep clastic rock reservoirs in the steep slope zone of the Lufeng Sag. The study encompassed the collection and analysis of the rock thin sections, XRD whole-rock mineralogy, and petrophysical properties from seven wells drilled into the Eocene. Our findings reveal that the nature of the parent rock, tuffaceous content, dominant sedimentary facies, and the thickness of individual sand bodies are crucial factors that influence the development of high-quality reservoirs under intense compaction conditions. Moreover, the sustained modification and efficient expulsion of organic–inorganic acidic fluids play a main role in forming secondary dissolution porosity zones within the En-4 Member of the LF X transition zone. Notably, it has been established that the front edge of the fan delta, the front of the thin layer, and the near margin of the thick layer of the braided river delta represent favorable zones for developing deep sweet-spot reservoirs. Furthermore, we have identified the LF X and LF Y areas as favourable exploration zones and established an Eocene petroleum-accumulation model. These insights will significantly aid in predicting high-quality dissolution reservoirs and facilitate deep oil and gas exploration efforts in the steep slope zone of the Zhuyi Depression. Full article

Currently, for underwater close-range large-target localization, visual localization techniques fail since large targets completely occupy the camera’s field of view at ultraclose ranges. To address the issue, a multi-stage optical localization method combining a binocular camera and a single-point laser rangefinder is proposed in this paper. The proposed method comprises three parts. First, the imaging model of the underwater camera is modified, and a laser rangefinder is used to further correct the underwater calibration results of the binocular camera. Second, YOLOv8 is applied to recognize the targets to prepare for target localization. Third, extrinsic calibration of the binocular camera and laser rangefinder is performed, and a Kalman filter is employed to fuse the target position information measured by the binocular camera and laser rangefinder. The experimental results show that, compared with using a binocular camera alone, the proposed method can accurately and stably locate the target at close ranges with an average error of only 2.27 cm, without the risk of localization failure, and reduces binocular localization error by 90.57%. Full article

Legitimate identification of devices is crucial to ensure the security of present and future IoT ecosystems. In this regard, AI-based systems that exploit intrinsic hardware variations have gained notable relevance. Within this context, on-chip sensors included for monitoring purposes in a wide range of SoCs remain almost unexplored, despite their potential as a valuable source of both information and variability. In this work, we introduce and release a dataset comprising data collected from the on-chip temperature and voltage sensors of 20 microcontroller-based boards from the STM32L family. These boards were stimulated with five different algorithms, as workloads to elicit diverse responses. The dataset consists of five acquisitions (1.3 billion readouts) that are spaced over time and were obtained under different configurations using an automated platform. The raw dataset is publicly available, along with metadata and scripts developed to generate pre-processed T–V sequence sets. Finally, a proof of concept consisting of training a simple model is presented to demonstrate the feasibility of the identification system based on these data. Full article

The escalating demand for power load is increasingly prone to triggering power quality (PQ) issues, leading to severe economic losses. Aiming at reducing the economic losses, this paper focuses on the coordinated relationship between PQ and economic costs. Firstly, a multilayer multiple linear stepwise regression method is employed to screen PQ indicators, identifying harmonic and voltage deviation as the primary influencing factors of PQ. Secondly, a gradient descent optimization algorithm based on the Least Absolute Shrinkage and Selection Operator (LASSO) is proposed, enabling rapid computation of the minimum PQ cost. Finally, through validations of two case studies, the results confirm that the proposed method can rapidly calculate the minimum PQ cost based on real-time load demands, enabling the dynamic adjustment of PQ cost to meet the evolving needs of power system development. Full article

Prostate cancer is the most common non-cutaneous cancer among men in the UK, causing significant health and economic burdens. Diagnosis and risk prognostication can be challenging due to the genetic and clinical heterogeneity of prostate cancer as well as uncertainties in our knowledge of the underlying biology and natural history of disease development. Urinary extracellular vesicles (EVs) are microscopic, lipid bilayer defined particles released by cells that carry a variety of molecular cargoes including nucleic acids, proteins and other molecules. Urine is a plentiful source of prostate-derived EVs. In this narrative review, we summarise the evidence on the function of urinary EVs and their applications in the evolving field of prostate cancer diagnostics and active surveillance. EVs are implicated in the development of all hallmarks of prostate cancer, and this knowledge has been applied to the development of multiple diagnostic tests, which are largely based on RNA and miRNA. Common gene probes included in multi-probe tests include PCA3 and ERG, and the miRNAs miR-21 and miR-141. The next decade will likely bring further improvements in the diagnostic accuracy of biomarkers as well as insights into molecular biological mechanisms of action that can be translated into opportunities in precision uro-oncology. Full article

The planned pilot CO₂ storage Zar-3 is an oil field with a gas cap in the final production stage in the SE Czech Republic. It is composed of a dolomite Jurassic reservoir sealed by three different formations that differ significantly in lithology. Previous studies left open questions on the nature of pore space and connectivity and the quality of the seal in the future CO₂ storage complex. Microscopic petrography of the reservoir suggests dolomitisation in shallow water followed by karstification and brecciation with fracture-correct-dominated porosity. The seal horizons have porosity limited to the micro- and nanoscales. The oil consists of significantly biodegraded black oil of Jurassic origin mixed with less biodegraded gasoline-range hydrocarbons. Biomarkers in the caprock bitumens trapped in nanopores show a genetic relationship to the reservoir oil. Gas in the not yet fully depleted gas cap of the field is of thermogenic origin with no contribution of microbial methane. The formation water has total dissolved solids typical of isolated brines not diluted by infiltrated fresh water. The geochemical characteristics of the storage system together with the fact that the initial oil column is about 105 m tall with another 150 m of gas cap suggest that the seals are efficient and the Zar-3 future storage complex is tight and safe. Full article

Background: Sarculator and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms are freely available risk prediction scores for surgically treated patients with primary sarcomas. Due to the rarity of angiosarcomas, these scores have only been tested on small cohorts of angiosarcoma patients. In neither the original patient cohort upon which the Sarculator is based nor in subsequent studies was a distinction made between primary and secondary angiosarcomas, as the app is intended to be applied to primary sarcomas. Therefore, the objective of our investigation was to assess whether the Sarculator reveals a difference in prognosis and whether such differentiation aligns with actual clinical data. Patients and Methods: Thirty-one patients with primary or secondary soft tissue angiosarcoma, treated at our Sarcoma Center from 2001 to 2023, were included in the study. Actual survival rates were compared with nomogram-derived data for predicted 5-year survival (Sarculator), as well as 4-, 8- and 12-year sarcoma-specific death probabilities (MSKCC). Harrell’s c-index was utilized to assess predictive validity. Results: In total, 31 patients were analyzed. The actual overall 5-year survival was 22.57% with a predicted 5-year survival rate of 25.97%, and the concordance index was 0.726 for the entire cohort. The concordance index results from MSKCC for angiosarcoma patients were below 0.7 indicating limited predictive accuracy in this cohort, particularly when compared to Sarculator. Summary: Nomogram-based predictive models are valuable tools in clinical practice for rapidly assessing prognosis. They can streamline the decision-making process for adjuvant treatments and improve patient counselling especially in the treatment of rare and complicated tumor entities such as angiosarcomas. Full article

This study presents a data-driven model for identifying failure modes (FMs) and predicting the corresponding punching shear resistance of slab-column connections with shear reinforcement. An experimental database that contains 328 test results is used to determine nine input variables based on the punching shear mechanism. A comparison is conducted between three typical machine learning (ML) approaches: random forest (RF), light gradient boosting machine (LightGBM), extreme gradient boosting (XGBoost) and two hybrid optimized algorithms: grey wolf optimization (GWO) and whale optimization algorithm (WOA). It was found that the XGBoost classifier had the highest accuracy rate, precision, and recall values for FM identification. In testing, WOA-XGBoost has the best accuracy in predicting punching shear resistance, with R², MAE, and RMSE values of 0.9642, 0.087 MN, and 0.126 MN, respectively. However, a comparison between experimental values and calculated values derived from classical analytical methods clearly demonstrates that existing design codes need to be improved. Additionally, Shapley additive explanations (SHAP) were applied to explain the model’s predictions, with factors categorized according to their impact on failure modes and punching shear resistance. By modifying these parameters, punching resistance can be improved while reducing unpredictable failure. With the proposed hybrid algorithms, it is possible to determine the failure modes and the punching shear resistance of slabs during the preliminary stages of the construction. Full article

A low-complexity multibeam wideband transmit beamformer using a 2D sparse FIR filter design capable of multiple beams is proposed as a digital building block for fully digital beamformers. The 2D sparse FIR filter has multiple trapezoid-shaped passbands pertaining to wideband beams aimed at particular directions. The proposed multibeam digital beamformer drives a uniform linear array of wideband antenna elements to achieve the wideband multibeam transmit-mode signals desired by the communication system. The 2D sparse FIR filter is designed to be optimal in the minimax sense using convex optimization techniques. Full-wave electromagnetic simulations using real antenna models confirm that the proposed wideband transmit beamformer can achieve multibeam transmission in the 1.3–2.8 GHz frequency range, with more than 70% fractional bandwidth. Furthermore, the adoption of the wideband transmit multibeam beamformer leads to a significant reduction in digital arithmetic (computational) complexity compared with previously reported wideband transmit beamformers of similar transfer function type, without deteriorating beam directionality and causing increases in the side-lobe level. The proposed sparse 2D FIR multibeam beamformer architecture is well-suited for both sub-6 GHz (legacy) band transmit beamforming, frequency range three (FR3) beamforming up to 28 GHz, and mmWave operation for emerging 5G/6G applications. Full article

The pressure of human activity in river valley environments has always been high. Even today, despite the increasing awareness of societies around the world regarding the need to protect water and biodiversity, there are concerns that the current river valley management systems are insufficient. Therefore, the aim of this study was to assess the state of knowledge about the soils and forest ecosystems of river valleys in terms of the possibility of protecting river valley environments. This study used data obtained from the Forest Data Bank (FDB) database, which focuses on forests in Poland. After analyzing 17,820 forest sections where the soils were described as fluvisols, it was found that forest areas associated with fluvisols (typical, fertile soils of river valleys) are quite well recognized and protected in Poland. Most (55%) forested fluvisols are located in Natura 2000 sites (an important European network of biodiversity hotspots), 4% in nature reserves, and 1% in national parks. Additionally, the main forest habitat type associated with fluvisols is riparian forest, composed mainly of Quercus, Ulmus, and Fraxinus, which is protected as Natura 2000 habitat type 91F0. Preserving the sustainability of the forest is also a form of soil protection. Despite the identification of soils and forests in river valleys, as well as appropriate legal tools, their protection may be ineffective due to the fragmentation of forms of protection and the lack of a coherent system for managing river valleys. Because the conservation status of the river valleys is also influenced by the management of areas located outside the river valleys, in order to protect river valley ecosystems, integrated conservation plans for entire catchments should be implemented. Due to potential conflicts related to the management of areas with diverse expectations of local communities, it would be advisable for such plans to be created by local experts but under the supervision of a specialist/specialists from outside the area covered by a given river basin. Full article

(1) Background: With autistic children’s high pervasiveness of eating problems and inappropriate feeding behaviors by their caregivers, this study wanted to inspect the connection between caregivers’ pressure to eat and food neophobia in these children. (2) Methods: Cross-sectional overview of 160 guardians of kids aged 2 to 7 years. After one-on-one questioning by the researcher, the collected information on the socio-demographic characteristics of the children with autism, caregiver feeding behavior, and new food neophobia (FN) scores was entered into the Questionnaire Star system. (3) Results: The mean FN score was 25.56 ± 6.46. The caregiver’s pressure to eat positively related to children’s FN (β = 0.164 95% CI, 0.078, 2.163). In these children, we found a negative correlation between FN score and the frequency of vegetable intake (p ≤ 0.001), fruit intake (p ≤ 0.05), aquatic product intake (p ≤ 0.05), and dietary diversity score (p ≤ 0.01), and positively correlated with the frequency of snack intake (p ≤ 0.05). (4) Conclusions: Caregiver pressure to eat was positively associated with high levels of FN in Chinese kids with ASD, which in turn negatively impacted dietary quality. To improve eating habits, caregivers should reconsider their feeding strategies and avoid using forceful methods to ease food neophobia in these children. Full article

Necrotizing enterocolitis (NEC) is the most common gastrointestinal emergency of prematurity. Postulated mechanisms leading to inflammatory necrosis of the ileum and colon include activation of the pathogen recognition receptor Toll-like receptor 4 (TLR4) and decreased levels of transforming growth factor beta (TGFβ). Extracellular nicotinamide phosphoribosyltransferase (eNAMPT), a novel damage-associated molecular pattern (DAMP), is a TLR4 ligand and plays a role in a number of inflammatory disease processes. To test the hypothesis that eNAMPT is involved in NEC, an eNAMPT-neutralizing monoclonal antibody, ALT-100, was used in a well-established animal model of NEC. Preterm Sprague–Dawley pups delivered prematurely from timed-pregnant dams were exposed to hypoxia/hypothermia and randomized to control—foster mother dam-fed rats, injected IP with saline (vehicle) 48 h after delivery; control + mAB—foster dam-fed rats, injected IP with 10 µg of ALT-100 at 48 h post-delivery; NEC—orally gavaged, formula-fed rats injected with saline; and NEC + mAb—formula-fed rats, injected IP with 10 µg of ALT-100 at 48 h. The distal ileum was processed 96 h after C-section delivery for histological, biochemical, molecular, and RNA sequencing studies. Saline-treated NEC pups exhibited markedly increased fecal blood and histologic ileal damage compared to controls (q < 0.0001), and findings significantly reduced in ALT-100 mAb-treated NEC pups (q < 0.01). Real-time PCR in ileal tissues revealed increased NAMPT in NEC pups compared to pups that received the ALT-100 mAb (p < 0.01). Elevated serum levels of tumor necrosis factor alpha (TNFα), interleukin 6 (IL-6), interleukin-8 (IL-8), and NAMPT were observed in NEC pups compared to NEC + mAb pups (p < 0.01). Finally, RNA-Seq confirmed dysregulated TGFβ and TLR4 signaling pathways in NEC pups that were attenuated by ALT-100 mAb treatment. These data strongly support the involvement of eNAMPT in NEC pathobiology and eNAMPT neutralization as a strategy to address the unmet need for NEC therapeutics. Full article