IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing.

Determining interactions of multi-component environmental mixtures towards accurate risk assessment.

Vibrational spectroscopy provides a spectral fingerprint identifying the effects of carbonbased nanoparticles in bacterial cells. 3 ABSTRACTNanoparticles appear to induce toxic effects through a variety of mechanisms including generation of reactive oxygen species (ROS), physical contact with the cell membrane and indirect catalysis due to remnants from manufacture. The development and subsequent increasing usage of nanomaterials has highlighted a growing need to characterize and assess the toxicity of nanoparticles, particularly those that may have detrimental health effects such as carbon-based nanomaterials (CBNs). Due to interactions of nanoparticles with some reagents, many traditional toxicity tests are unsuitable for use with CBNs. Infrared (IR) spectroscopy is a non-destructive, high throughput technique, which is unhindered by such problems. We explored the application of IR spectroscopy to investigate the effects of CBNs on Gram-negative (Pseudomonas fluorescens) and Gram-positive (Mycobacterium vanbaalenii PYR-1) bacteria. Two types of IR spectroscopy were compared: attenuated total reflection Fourier-transform infrared (ATR-FTIR) and synchrotron radiation-based FTIR (SR-FTIR) spectroscopy. This showed that Gram-positive and Gram-negative bacteria exhibit differing alterations when exposed to CBNs. Gram-positive bacteria appear more resistant to these agents and this may be due to the protection afforded by their more sturdy cell wall. Markers of exposure also vary according to Gram status; Amide II was consistently altered in Gram-negative bacteria and carbohydrate altered in Gram-positive bacteria. ATR-FTIR and SR-FTIR spectroscopy could both be applied to extract biochemical alterations induced by each CBN that were consistent across the two bacterial species; these may represent potential biomarkers of nanoparticle-induced alterations. Vibrational spectroscopy approaches may provide a novel means of fingerprinting the effects of CBNs in target cells.

Cervical cancer remains a major cause of morbidity and mortality among women, especially in the developing world. Increased synthesis of proteins, lipids and nucleic acids is a pre-condition for the rapid proliferation of cancer cells. We show that scanning near-field optical microscopy, in combination with an infrared free electron laser (SNOM-IR-FEL), is able to distinguish between normal and squamous lowgrade and high-grade dyskaryosis, and between normal and mixed squamous/glandular pre-invasive and adenocarcinoma cervical lesions, at designated wavelengths associated with DNA, Amide I/II and lipids. These findings evidence the promise of the SNOM-IR-FEL technique in obtaining chemical information relevant to the detection of cervical cell abnormalities and cancer diagnosis at spatial resolutions below the diffraction limit (≥0.2 μm). We compare these results with analyses following attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy; although this latter approach has been demonstrated to detect underlying cervical atypia missed by conventional cytology, it is limited by a spatial resolution of ~3 μm to 30 μm due to the optical diffraction limit.Cervical cancer is associated with the persistent infection of high-risk types of human papillomavirus (HPV), together with other socioeconomic co-factors 1 . Screening involves cytological and histological classification of cervical cells. In the UK, cytological examination of cervical squamous cells is classified as normal, borderline or mild dyskaryosis, moderate or severe dyskaryosis and invasive cervical cancer (ICC). Histology is defined as normal, cervical intra-epithelial neoplasia (CIN): CIN1, CIN2, CIN3, or invasive cervical cancer. For atypical cells found in the glandular cells of the cervix, the pre-invasive lesion of adenocarcinoma is defined by changes termed cervical glandular intraepithelial neoplasia (CGIN), and sub-classified as low-grade cervical glandular intra-epithelial neoplasia (LGCGIN) and high-grade cervical glandular intra-epithelial neoplasia (HGCGIN). Squamous and glandular lesions may co-exist together and are defined by the level of CIN together with either LGCGIN or HGCGIN. Conventional screening is flawed as it is dependent on the subjective visual inspection of cytology; this often results in mis-diagnoses when grading samples 2 .

Organochlorine (OC) pesticides pose a significant environmental risk to wildlife and humans and have been associated with Alzheimer's disease (AD). This study aims to spectroscopically analyze brains from free-flying birds and link the results to OC exposure and consequent amyloid aggregation. As long-lived apex predators, predatory birds represent a sentinel species similar to humans. Therefore, the results have implications for both species and may also add to our understanding of the role OC pesticides play in the development of AD. Brains of wild Sparrowhawks were analyzed using ATR-FTIR and Raman spectroscopy and Congo red staining; results were correlated with OC pesticide concentrations in livers. Effects of OC exposure were sex- and age-dependent and associated alterations were seen in lipids and protein secondary structure. A shift from α-helix to β-sheet conformation of proteins indicated that concentrations of OC pesticides >7.18 μg/g may lead to cerebral amyloid aggregation.