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Spiking neural networks can exhibit complex emergent dynamics, but the credibility of spatially explicit agent-based implementations depends on systematic verification and validation (V&V). This study introduces LANA (Local Adaptive Neural Agents), an agent-based spiking neural network in which neurons, propagating signals, directed synapses, and a diffusive environmental field are represented as distinct interacting components. We present a five-level V&V framework spanning operator-level tests, single-neuron mechanisms, propagation behavior, network-level dynamics, and sensitivity/robustness analysis. Across 13 predefined tests and approximately 2000 simulation runs, the model satisfied all prespecified pass criteria: synaptic delays reproduced the expected propagation law exactly, environmental decay and diffusion matched analytical expectations, threshold and refractory mechanisms behaved as predicted, inhibition suppressed firing monotonically, and environmental coupling induced a transition toward higher variability and oscillatory-like activity. Matched-seed comparisons further showed that explicit signal transport and environmental feedback substantially amplify activity relative to a neuron-only baseline while leaving synaptic delay propagation unchanged. Additional regime and lesion experiments demonstrated distinct resting, hyperexcitable, and focal-lesion states, with the lesion condition producing an acute decline followed by only partial recovery. Together, these results provide a transparent V&V baseline for LANA and illustrate how agent-based spiking models can be tested and interpreted across multiple scales.

Agent-based neural models often encode transmission within neuron state updates, which can make it difficult to separately log and quantify spatial recruitment patterns, delay structure, and environment-mediated feedback effects. We present LANA (Local Adaptive Neural Agents), a dual-agent neural agent-based model in which neurons and propagating signals are represented as distinct interacting entities embedded in a dynamic environmental field. The model combines discrete leaky integrate-and-fire neuron dynamics, mobile signal agents, synaptic links with distance-dependent delays, and a bounded environment-to-neuron feedback mechanism. LANA is intended as a normalized phenomenological mesoscopic framework for mechanism-level comparison rather than as a circuit-specific biophysical reconstruction. To support interpretability and reproducibility, we report a compact internal verification block for the implemented operators, including delay propagation, environmental decay and diffusion, threshold activation, and refractory enforcement. We then compare the full LANA model against a matched neuron-only baseline and summarize spatial recruitment using first-spike maps, cumulative recruitment times, and wavefront speed as a secondary descriptive metric. Finally, we evaluate two controlled operating regimes, a resting regime (S1) and a hyperexcitable regime (S2), under fixed network size, stimulation schedule, and matched random seeds. Relative to the baseline, the full model sustains and spreads activity more effectively and provides spatially resolved recruitment summaries, including first-spike timing and cumulative recruitment measures, that are not available in the same form when transmission is represented only through neuron-level updates. Relative to S1, S2 exhibits earlier activation, higher firing activity, stronger environmental accumulation, and faster cumulative recruitment. Local and factorial sensitivity analyses further identify the parameters that most strongly govern these regime differences. Together, these results position LANA as a normalized mesoscopic and computationally tractable framework for studying how excitability, transport state dynamics, delayed coupling, and environment-mediated feedback jointly shape emergent activity in controlled simulation settings.

Background: Deep Acute pancreatitis (AP) is an urging cause of hospitalization in the gastroenterology due to different causes and an unpredictable outcome. Known causes are grouped into four main groups: metabolic, mechanical, vascular and infectious. Objective: To determine the role of certain biochemical or radiological parameters as predictors of an involvement of other organs in AP different pathological staging and the surgical outcome in the treatment of AP. Methods: Ninety-seven AP patients hospitalized in General Hospital “Prim.dr Abdulah Nakaš” Sarajevo, in a period between 2016 and 2021 for both sexes, were divided according to the etiological factors of AP into four groups: nutritional factors, biliary concernments, alcohol and morphological changes of the pancreas. Beside laboratory tests, the imaging methods of abdomen (transabdominal ultrasound, abdominal computed tomography) used in determining morphological changes in the pancreas and other organs were analyzed in relation to parameters that predict the need for surgical outcomes.Results: AP etiological factors of patients differ significantly by gender and showed the dominance of dietary factors in female subjects (51%), followed by the presence of concernments in the biliary tract in 36% of cases, and alcohol consumption in male subjects in 28% of cases. The only variable correlated with the indicator of necessity for surgery is the existence of pleural effusion (coefficient of correlation was 0.38; risk ratio was 5.5) resulting that patients with pleural effusion have a 5.5 times higher chance of surgery indication than other patients. Conclusion: The application of simple parameters such as creatinine value with the values of amylases in serum and urine and the presence of pleural effusion confirmed by radiological imaging of the lungs opens the possibility of a simple and effective selection of patients for surgical treatment with a more severe form of AP.