Abstract
In this manuscript we explore the feasibility of using LWUV-VIS-SWNIR (340 - 1100 nm) spectroscopy to classify Saccharomyces cerevisiae colony structures in YP agar and YPD agar, under different growth conditions, such as: i) no alcohol; ii) 1% (nu/nu) Ethanol; iii) 1% (nu/nu) 1-Propanol; iv) 1% (nu/nu) 1-butanol; v) 1 % (nu/nu) Isopropanol; vi) 1% (nu/nu) (+/-)-1-Phenylethanol; vii) 1% (nu/nu) Isoamyl alcohol; viii) 1% (nu/nu) tert-Amyl alcohol (2-Methyl-2-butanol); and ix) 1% (nu/nu) Amyl alcohol. Results show that LWUV-VISSWNIR spectroscopy has the potential for yeasts metabolic state identification once the spectral signatures of colonies differs from each others, being possible to acheive 100% of classification in UV-VIS and VIS-SWNIR. The UV-VIS region present high discriminant information (350-450 nm), and different responses to UV excitation were obtained. Therefore, high precision is obtained because UV-VIS and VIS-NIR exhibit different kinds of information. In the future, high precision analytical chemistry techniques such as mass spectroscopy and molecular biology transcriptomic studies should be performed in order to understand the detailed cell metabolism and genomic phenomena that characterize the yeast colony state.

Abstract
One of the most studied bioprocesses is fermentation by yeasts. Although this is true, there is still the lack of real-time instrumentation that is capable of providing detailed information on metabolic state of fermentations. In this research we explore the possibility of using UV-VIS-SWNIR spectroscopy as a high-output, non-destructive and multivariate methodology of monitoring beer fermentation. We herein report the implementation of the a fibber optics sensor and the capacity for detecting key parameters by partial least squares regression for biomass, extract, pH and total sugars. Results show that UV-VIS-SWNIR is a robust technique for monitoring beer fermentations, being able to provide detailed information spectroscopic fingerprinting of the process. Calibrations were possible to obtain for all the studied parameters with R2 of 0.85 to 0.94 in the UV-VIS region and 0.95 to 0.97 in the VIS-SWNIR region. This preliminary study allowed to conclude that further improvements in experimental methodology and signal processing may turn this technique into a valuable instrument for detailed metabolic studies in biotechnology.

Abstract
Feline chronic kidney disease is a leading cause of mortality in geriatric cats, characterized by a progressive and irreversible loss of renal function. Despite its high prevalence, early diagnosis remains challenging due to nephron compensatory mechanisms and the limited sensitivity of traditional biomarkers, creating a diagnostic gap that necessitates the exploration of novel biomarkers for earlier detection. This review examines the complex pathophysiology of the disease, including renin-angiotensin-aldosterone system activation, tubulointerstitial fibrosis, and mineral metabolism disturbances. By analyzing recent scientific literature, this work evaluates current diagnostic landscape and clinical relevance of emerging biomarkers. Evidence indicates that symmetric dimethylarginine and fibroblast growth factor-23 improve detection of early metabolic and filtration changes, while urinary biomarkers like cystatin B and retinol-binding protein provide specific insights into tubular injury. Bridging the diagnostic gap requires a transition from a reactive, azotemia-based framework to a multi-parametric diagnostic approach that integrates novel biomarkers with serial clinical and laboratory monitoring. Although financial constraints and limited availability restrict widespread clinical implementation, incorporating these advances is essential for earlier prognostic stratification and timely therapeutic decision-making. This integrated strategy has the potential to slow disease progression and improve survival and quality of life in cats with chronic kidney disease.

Abstract
Visible-Near-Infrared (Vis-NIR) spectroscopy, spanning approximately 400 to 2500 nm, is an innovative technology with growing relevance for diagnostics performed at the point of care (POC). This review explores the potential of Vis-NIR in veterinary medicine, highlighting its advantages over complex techniques like Raman and Fourier transform infrared spectroscopy (FTIR) by being rapid, non-invasive, reagent-free, and compatible with miniaturized, portable devices. The methodology involves directing a broadband light source, often using LEDs, toward the sample (e.g., blood, urine, faeces), collecting spectral information related to molecular vibrations, which is then analyzed using chemometric methods. Successful veterinary applications include hemogram analysis in dogs, cats, and Atlantic salmon, and quantifying blood in ovine faeces for parasite detection. Key limitations include spectral interference from strong absorbers like water and hemoglobin, and the limited penetration depth of light. However, combining Vis-NIR with Self-Learning Artificial Intelligence (SLAI) is shown to isolate and mitigate these multi-scale interferences. Vis-NIR spectroscopy serves as an important complement to centralized laboratory testing, holding significant potential to accelerate clinical decisions, minimize stress on animals during assessment, and improve diagnostic capabilities for both human and animal health, aligning with the One Health concept.