Bacteremia is a life-threatening complication and a leading cause of sepsis and septic shock in patients. Conventional diagnostic methods, such as blood culture, remain the clinical gold standard but require 24-72 h, often necessitating the empirical use of broad-spectrum antibiotics, which significantly contribute to the development and spread of antimicrobial resistance (AMR). We hypothesized that the host immune system mounts a specific, detectable systemic metabolic response to bloodstream infection, biochemically distinct from that elicited by focal bacterial infection (FBI) or viral etiologies. This study presents a rapid (<1 h), objective, and culture-independent diagnostic method for bacteremia based on host-response profiling using Fourier-transform infrared (FTIR) spectroscopy of white blood cells (WBCs). Blood samples from 410 pediatric oncology patients were clinically categorized into 71 bacteremia cases, 75 FBI, 157 viral infections, and 107 afebrile controls. WBCs were analyzed using FTIR spectroscopy to capture immune-metabolic fingerprints. Spectral profiles were classified using Logistic Regression with Principal Component Analysis (PCA) feature vectors and Log-Likelihood Ratio decision logic to differentiate bacteremia. The FTIR + Machine Learning (ML) platform successfully resolved the subtle biochemical differences, achieving 94.5% accuracy, 96.5% sensitivity, and 87.8% specificity in diagnosing bacteremia from all other categories combined (FBI, viral, and control). Importantly, the platform maintained high diagnostic performance, achieving 94.6% accuracy in distinguishing bacteremia from the FBI. This approach provides early, targeted diagnostic information that can support clinical decision-making, offering a powerful analytical tool to guide antibiotic stewardship and combat the global threat of AMR in this vulnerable population.

Chemically diverse: Chemotaxonomic discrimination and comparative fingerprinting of intact lichens from different families and genera using Fourier transform infrared (FTIR) spectroscopy and chemometrics.

Investigation of biochemical alterations in the brain of db/db diabetic mice using integrated FTIR and Raman spectroscopy combined with machine learning.

Strain-level typing of Candida albicans and Saccharomyces cerevisiae using Fourier transform infrared spectroscopy and whole-genome sequencing.

A novel multi-feature fusion technology of FTIR spectroscopy based on attention and adaptive gate for disease diagnosis.

FTIR spectroscopy coupled with chemometrics for evaluating functional food efficacy in an in vitro model of iron deficiency anemia.

Determination of the adulteration of benzyl alcohol and dipropylene glycol in sage, mint, and oregano essential oils belonging to the Lamiaceae Family by FTIR using Chemometry and 2D-COS.

A structurally distinct neutral polysaccharide from Polygonatum odoratum (Mill.) Druce improves hyperglycemia via the PI3K-AKT-GSK3β/FoxO1 signaling pathway.

Research on the degradation mechanism and products of 2,4,6-tribromophenol in the water environment and the mechanism of competition between T4 and TTR binding.

Evaluation of shear bond strength, adhesive remnant index, and degree of conversion of orthodontic composite adhesives: An in vitro study using human premolars.

The optimization of the mechanical, optical, structural, and shielding features of the heavy borosilicate glass system: Role of adding Nd2O3.

In this study, reduced graphene oxide (rGO) was synthesized from graphene oxide (GO) via an ascorbic acid-assisted reduction process. GO was synthesized from graphite powder using a modified Hummers technique. The surface morphology, structure, functional groups, and elemental compositions of the produced materials were studied using various methods, such as scanning electron microscopy (SEM)/EDX, X-ray diffraction (XRD), atomic force microscopy (AFM), Fourier transform infrared (FTIR), and UV-Vis. The removal of oxygen-containing functional groups in rGO through reduction resulted in poor sample quality. In addition, FTIR investigations revealed that GO contained more oxygen-containing functional groups than rGO. Typical peaks at 26.7081° and 26.65° for rGO and GO, respectively, were characterized using XRD. Additionally, a UV-Vis study confirmed the successful reduction by observing a redshift in the absorption peak from 363 nm to 371 nm, indicating partial restoration of the π-conjugation system. Overall, the results demonstrated that graphene oxide was successfully oxidized from graphite and that rGO was efficiently reduced from GO, yielding a material with improved properties for the target application.

Optimization of FTIR-PLS models for adulteration detection in sesame oil: a comparative study of genetic algorithm, particle swarm optimization, and a hybrid GA-PSO approach.

Bioactivity of zinc oxide nanoparticles (ZnO-NPs) synthesized from Phoebe zhennan and Croton tiglium.

Synergistic recognition SERS sensor of MgO-protected AgNPs functionalized with tryptophan and β-cyclodextrin for trace monosultap analysis.

The increasing number of artificial dyes from industrial processes contaminating water sources requires more efficient and sustainable techniques for wastewater remediation. This study involves the utilization of litchi (Litchi chinensis) fruit peels in the green synthesis of magnesium oxide nanoparticles (MgO-NPs). Further, for the characterization of eco-friendly MgO-NPs, ultraviolet-visible spectra, Fourier transform infrared (FTIR) spectroscopy, dynamic light scattering, scanning electron microscopy (SEM), and X-ray diffraction (XRD) spectroscopy were utilized. An absorption peak at 274 nm from UV-visible spectroscopy indicates the development of MgO-NPs. The particle average size was found to be 96.33 nm with a polydispersity index of 0.32. The application of the synthesized nanoparticle was evaluated for the removal of malachite green and Eriochrome Black T. The biosynthesized nanoparticles demonstrated an enhanced photocatalytic activity, effectively removing malachite green (95.66%) and Eriochrome Black T (92.69%) from contaminated water under solar light irradiation. These results reveal that the green-synthesized MgO-NPs achieved significant efficiency in dye removal, highlighting their potential as a cost-effective and sustainable approach for wastewater treatment applications.

In-vitro refolding of biotherapeutic inclusion bodies has long been recognized as a bottleneck in protein production in host systems such as Escherichia coli. Low throughput, costly reagents, and offline analysis often plague refolding development efforts. Refolding optimization typically employs statistical approaches such as Design of Experiments (DoE). While DOE offers advantage over univariate one-factor-at-a-time analysis, but it requires large subset sampling, which is cost-inefficient and labour-intensive. This paper demonstrates a knowledge-based refolding optimization, contrasted to the typical DoE-based protocol for proinsulin. The reaction is monitored and segmented into two parts (segment 1: 0-2 h and segment 2:2-6 h) based on the Fourier transform infrared (FTIR), Oxidation Reduction Potential (ORP) and Reverse Phase- High Performance Liquid Chromatography (RP-HPLC) analysis. The data is fed to a multi-objective optimization (MOO) method that utilize XGBoost, coupled with an NSGA-II optimizer. Based on the Pareto front, a linear correlation between parameters was observed in segments 1 and 2. An ensemble coupled non-dominated sorting genetic algorithm II (NSGA-II) was developed to optimize the reaction conditions beforehand. The proposed optimizer was then compared with the traditional DoE-based optimization. The developed optimization framework increased the yield to 65% ± 1.78% compared to 54% ± 2.62% in the traditional DoE-based approach (relatively 20% higher). The approach could combine screening and optimization analysis in a single step, dramatically reducing the overall experimental efforts by ∼50%.

Molecular composition changes of soil dissolved organic matter (SDOM) during non-thermal plasma treatment.

Temperature-triggered structural arrangement and properties of transparent pectin-arginine films.

Vitex negundo L. (Verbenaceae) is a well-known medicinal plant used in traditional medicine for the treatment of inflammatory, microbial, and oxidative stress-related disorders. The present study aimed to evaluate antibacterial and antioxidant activities of Vitex negundo leaf extracts, along with their chemical characterization using Fourier transform infrared (FT-IR) spectroscopy and gas chromatography-mass spectrometry (GC-MS). Antibacterial activity of acetone, methanol, and aqueous extracts was assessed by agar well diffusion method against four bacterial strains. The acetone extract exhibited notable antibacterial activity, particularly against Bacillus cereus and Bacillus subtilis. Antioxidant potential was evaluated using the DPPH radical scavenging assay, where acetone and methanol extracts demonstrated the highest activity in a dose-dependent manner. FT-IR analysis confirmed the presence of various functional groups associated with bioactive compounds. GC-MS profiling identified 24 compounds in the acetone extract and 20 compounds in the methanol extract, with major constituents such as isoambreinolide, catechol, n-hexadecanoic acid, kojic acid, karanjin, and phytol, many of which are known for their antimicrobial, antioxidant and anti-inflammatory properties. Overall, the findings indicate that Vitex negundo leaves are rich in bioactive phytochemicals and possess significant antibacterial and antioxidant activities, supporting their traditional medicinal use and highlighting their potential for pharmaceutical applications.