Field-resolved infrared spectroscopy of biological systems

Excited-State Mixing in the LOV Domain Proteins: Possible Physics behind the Difference in the Transient Absorption and Transient Stimulated Raman Spectroscopy

It remains uncertain whether excited electronic state mixing occurs in the flavin cofactor of the light-oxygen-voltage-sensing (LOV) domain. In this study, we present transient absorption and femtosecond stimulated Raman spectra of both free and EL222 binding flavin mononucleotide (FMN). We observed a change in the shape of the excited-state absorption around 800 nm in the S1 state transient absorption after binding to EL222, alongside a relative intensity increase of the N1-C2 and C2═O2 stretching modes in the S1 state Raman spectra. Based on the previous calculated geometric differences between the ππ* and nπ* states, we propose a probable electronic state mixing in EL222 binding FMN. This mixing is favored by the nonsymmetric hydrogen bonding interaction between the flavin O4 atom and the asparagine residue and fewer hydrogen bonds with the O2 atom in EL222.

Electric-Field Molecular Fingerprinting to Probe Cancer

Human biofluids serve as indicators of various physiological states, and recent advances in molecular profiling technologies hold great potential for enhancing clinical diagnostics. Leveraging recent developments in laser-based electric-field molecular fingerprinting, we assess its potential for in vitro diagnostics. In a proof-of-concept clinical study involving 2533 participants, we conducted randomized measurement campaigns to spectroscopically profile bulk venous blood plasma across lung, prostate, breast, and bladder cancer. Employing machine learning, we detected infrared signatures specific to therapy-naïve cancer states, distinguishing them from matched control individuals with a cross-validation ROC AUC of 0.88 for lung cancer and values ranging from 0.68 to 0.69 for the other three cancer entities. In an independent held-out test data set, designed to reflect different experimental conditions from those used during model training, we achieved a lung cancer detection ROC AUC of 0.81. Our study demonstrates that electric-field molecular fingerprinting is a robust technological framework broadly applicable to disease phenotyping under real-world conditions.

Mid-Infrared Energy Deposition Spectroscopy

It is generally assumed that the spectral acquisition speed in photothermal spectroscopy is fundamentally limited by the thermal diffusion process. Here, we demonstrate midinfrared energy deposition (MIRED) spectroscopy that offers both microsecond-scale temporal resolution and submicron spatial resolution. In this approach, the photothermal process is optically probed while the infrared pulses from a quantum cascade laser array are rapidly tuned. Based on Newton's law of heating and cooling, the energy deposition is the first derivative of local temperature rise over time and gives the instantaneous absorption. By employing time-resolved measurement of transient energy deposition, the upper limit for spectrum encoding shifts to the vibrational relaxation level, which occurs on the picosecond scale. This method significantly increases the detection bandwidth while retaining the sensitivity and resolution benefits of photothermal detection.

AI protocol for retrieving protein dynamic structures from two-dimensional infrared spectra

Understanding the dynamic evolution of protein structures is crucial for uncovering their biological functions. Yet, real-time prediction of these dynamic structures remains a significant challenge. Two-dimensional infrared (2DIR) spectroscopy is a powerful tool for analyzing protein dynamics. However, translating its complex, low-dimensional signals into detailed three-dimensional structures is a daunting task. In this study, we introduce a machine learning-based approach that accurately predicts dynamic three-dimensional protein structures from 2DIR descriptors. Our method establishes a robust "spectrum-structure" relationship, enabling the recovery of three-dimensional structures across a wide variety of proteins. It demonstrates broad applicability in predicting dynamic structures along different protein folding trajectories, spanning timescales from microseconds to milliseconds. This approach also shows promise in identifying the structures of previously uncharacterized proteins based solely on their spectral descriptors. The integration of AI with 2DIR spectroscopy offers insights and represents a significant advancement in the real-time analysis of dynamic protein structures.

Fourier Transform Infrared (FTIR) Spectroscopy as a Tool to Characterize Exercise and Physical Activity: A Systematic Review

BACKGROUND

Over the past few decades, the scientific community has recognized the impact of physical activity on health and performance. In parallel, researchers have been actively exploring novel methodologies to analyze the physiological and metabolic responses to exercise. Fourier transform infrared spectroscopy has emerged as a powerful tool in this effort, offering the potential to provide unique insights into exercise-related changes at the molecular level.

OBJECTIVE

The primary goal of this systematic review is to confirm the viability of utilizing Fourier transform infrared spectroscopy for the analysis of the biochemical changes associated with physical exercise and its potential applications.

METHODS

This systematic review adhered to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and examined studies employing Fourier transform infrared spectroscopy to analyze exercise and physical activity, focusing on a biological sample collection and spectral analysis. Four databases (PubMed, SPORTDiscus, Web of Science, and Scopus) were searched, and inclusion criteria encompassed original English-language studies involving human participants aged 18-50 years, a biological sample collection (urine, saliva, and blood), and the use of Fourier transform infrared spectroscopy. The studies were analyzed considering the type of exercise or sport that was investigated, and also the type of spectral analysis conducted.

RESULTS

The review encompassed 15 studies that demonstrated the versatility of Fourier transform infrared spectroscopy in assessing various aspects of exercise, including metabolism, cardiovascular responses, and muscular fatigue. The largest study evaluated 57 athletes from several different sports. On average, almost all the studies were performed with around 20 athletes. Notably, the technique's holistic approach allows for a comprehensive analysis of the complex network of metabolites and proteins within the human body. Data analysis methodologies, particularly when coupled with machine learning, show great potential for advancing the field of sports science.

CONCLUSIONS

Fourier transform infrared spectroscopy emerges as a promising tool for monitoring and enhancing the performance of high-level athletes, preventing overtraining or even over-reaching, and assessing metabolism. Its accuracy, efficiency, and affordability also make it a candidate for broader applications in assessing the health and fitness of the general population. Future research should explore its applicability across diverse exercise modalities and demographic groups, aiming to prescribe exercise plans that consider a multitude of parameters for larger, more intricate exercise cohorts.

CLINICAL TRIAL REGISTRATION

The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) under the ID number CRD42023441965.

Quantum-enhanced time-domain spectroscopy

The time-resolved detection of mid- to far-infrared electric fields absorbed and emitted by molecules is among the most sensitive spectroscopic approaches and has the potential to transform sensing in fields such as security screening, quality control, and medical diagnostics. However, the sensitivity of the standard detection approach, which relies on encoding the far-infrared electric field into amplitude modulation of a visible or near-infrared probe laser pulse, is limited by the shot noise of the latter. This constraint cannot be overcome without using a quantum resource. Here, we show that this constraint can be overcome using a two-mode squeezed state. Quantum-correlated ultrashort pulses, generated by parametric down-conversion, enhance the sensitivity of far-infrared detection beyond the classical limit, achieving a twofold reduction in measured noise. This advancement paves the way for further development of ultrafast quantum metrology, moving toward quantum-enhanced time-resolved electric field spectroscopy with sensitivities beyond the standard quantum limit.

Carrier-envelope-phase characterization of ultrafast mid-infrared laser pulses through harmonic generation and interference in argon

The propagation of an intense, femtosecond, mid-infrared laser pulse in a gaseous medium results in the efficient generation of spectrally overlapping low-order harmonics, whose optical carrier phases are linked to the carrier-envelope phase (CEP) of the mid-infrared driver pulse. Random peak-power fluctuations of the driver pulses, converted to the fluctuations of the nonlinear phases, acquired by the pulses on propagation, cause this phase correlation to smear out. We show that this seemingly irreversible loss of phase can be recovered, and that the complete information needed for the phase correction is contained in the harmonic spectra itself. The optical phases of the intense driver pulse and its harmonics, as fragile as they appear to be against even weak disturbances, evolve deterministically during highly nonlinear propagation through the extended ionization region.

Spectral broadening of µJ-level pulses around 8 µm in a Germanium-based multi-pass scheme

A 2.6-fold spectral broadening of mid-infrared femtosecond µJ-level pulses has been achieved using an unfolded multi-pass configuration of germanium plates and zinc selenide lenses. This method maintains a throughput higher than 60% while preserving the spatial quality and the temporal duration of the input beam. Numerical simulations match the experimental results and show the potential to tailor the parameters of the cell to obtain different spectra.

Near infrared spectroscopy (NIRS) and machine learning as a promising tandem for fast viral detection in serum microsamples: A preclinical proof of concept

Fast detection of viral infections is a key factor in the strategy for the prevention of epidemics expansion and follow-up. Hepatitis C is paradigmatic within viral infectious diseases and major challenges to elimination still remain. Near infrared spectroscopy (NIRS) is an inexpensive, clean, safe method for quickly detecting viral infection in transmission vectors, aiding epidemic prevention. Our objective is to evaluate the combined potential of machine learning and NIRS global molecular fingerprint (GMF) from biobank sera as an efficient method for HCV activity discrimination in serum. GMF of 151 serum biobank microsamples from hepatitis C patients were obtained with a FT-NIR spectrophotometer in reflectance mode. Multiple scatter correction, smoothing and Saviztsky-Golay second derivative were applied. Spectral analysis included Principal Component Analysis (PCA), Bootstrap and L1-penalized classification. Microsamples of 70 µl were sufficient for GMF acquisition. Bootstrap evidenced significant difference between HCV PCR positive and negative sera. PCA renders a neat discrimination between HCV PCR-positive and negative samples. PCA loadings together with L1-penalized classification allow the identification of discriminative bands. Active virus positive sera are associated to free molecular water, whereas water in solvation shells is associated to HCV negative samples. Divergences in the water matrix structure and the lipidome between HCV negative and positive sera, as well as the relevance of prooxidants and glucose metabolism are reported as potential biomarkers of viral activity. Our proof of concept demonstrates that NIRS GMF of hepatitis C patients' sera aided by machine learning allows for efficient discrimination of viral presence and simultaneous potential biomarker identification.

Broadband spectral tuning and multi-molecular detection in a BaGa4Se7 optical parametric amplifier

Broadband spectral tuning of long-wavelength infrared (LWIR) femtosecond lasers without rotating nonlinear crystals has special usefulness in applications of nonlinear integrated photonics and microscopic ultrafast dynamics studies with stringent requirements on beam pointing. Here, we demonstrate, for the first time to the best of our knowledge, a temperature-tuning LWIR femtosecond optical parametric amplifier (OPA), based on a BaGa4Se7 (BGSe) crystal. Broadband spectral tunability from 8.4 to 17.1 µm over a crystal temperature range of 20-140°C at three fixed phase-matching (PM) angles is achieved with mini-watts output power. As a proof of concept, multiple trace gas detections are demonstrated on sulfur hexafluoride, ethane, and acetylene through only temperature variation. Our results validate the feasibility of achieving an ultra-broadband LWIR spectral tuning through temperature variation in a BGSe OPA, which is beneficial for unique applications such as on-chip spectroscopy and microscopic pump-and-probe experiments.

The Perils of Molecular Interpretations from Vibrational Spectra of Complex Samples

Vibrational spectroscopy is a widely used technique for chemical characterizations across various analytical sciences. Its applications are increasingly extending to the analysis of complex samples such as biofluids, providing high-throughput molecular profiling. While powerful, the technique suffers from an inherent limitation: The overlap of absorption information across different spectral domains hinders the capacity to identify individual molecular substances contributing to measured signals. Despite the awareness of this challenge, the difficulty of analyzing multi-molecular spectra is often underestimated, leading to unsubstantiated molecular interpretations. Here, we examine the prevalent overreliance on spectral band assignment and illuminate the pitfalls of correlating spectral signals to discrete molecular entities or physiological states without rigorous validation. Focusing on blood-based infrared spectroscopy, we provide examples illustrating how peak overlap among different substances, relative substance concentrations, and preprocessing steps can lead to erroneous interpretations. We advocate for a viewpoint shift towards a more careful understanding of complex spectra, which shall lead to either accepting their fingerprinting nature and leveraging machine learning analysis - or involving additional measurement modalities for robust molecular interpretations. Aiming to help translate and improve analytical practices within the field, we highlight the limitations of molecular interpretations and feature their viable applications.

SESAM-assisted Kerr-lens mode-locked Cr:ZnS laser

Mode-locking in Cr:ZnS/Se lasers typically rely on Kerr-lensing (KLM) or a semiconductor saturable absorber mirror (SESAM). The former allows generation of shorter pulses, but, unlike the latter, does not support self-starting mode-locking. Here, we combine the advantages of these two techniques and demonstrate the SESAM-assisted KLM Cr:ZnS laser. Our self-starting oscillator generates up to 1 W of average power with 54 fs pulses at a central wavelength of 2360 nm. We identify a general limitation for further pulse shortening in SESAM mode-locked Cr:ZnS/Se lasers, which is related to the finite operation bandwidth of the semiconductor absorbers. In our experiment, we fully exploit the potential of commercially available GaSb SESAMs and fill their entire reflection bands. Furthermore, we compare the performance of a SESAM-assisted KLM laser with a pure KLM oscillator producing broadband, yet not self-starting, 33 fs pulses with 780 mW power. We also show that the choice of saturable absorbers has a negligible impact on the laser intensity noise, which is exceptionally low with sub-0.005% integrated noise.

Sub-attosecond-precision optical-waveform stability measurements using electro-optic sampling

The generation of laser pulses with controlled optical waveforms, and their measurement, lie at the heart of both time-domain and frequency-domain precision metrology. Here, we obtain mid-infrared waves via intra-pulse difference-frequency generation (IPDFG) driven by 16-femtosecond near-infrared pulses, and characterise the jitter of sub-cycle fractions of these waves relative to the gate pulses using electro-optic sampling (EOS). We demonstrate sub-attosecond temporal jitter at individual zero-crossings and sub-0.1%-level relative amplitude fluctuations in the 10-kHz-0.625-MHz band. Chirping the nearly-octave-spanning mid-infrared pulses uncovers wavelength-dependent attosecond-scale waveform jitter. Our study validates EOS as a broadband (both in the radio-frequency and the optical domains), highly sensitive measurement technique for the jitter dynamics of optical waveforms. This sensitivity reveals outstanding stability of the waveforms obtained via IPDFG and EOS, directly benefiting precision measurements including linear and nonlinear (infrared) field-resolved spectroscopy. Furthermore, these results form the basis toward EOS-based active waveform stabilisation and sub-attosecond multi-oscillator synchronisation/delay tracking.

Mechanochemistry: Fundamental Principles and Applications

Mechanochemistry is an emerging research field at the interface of physics, mechanics, materials science, and chemistry. Complementary to traditional activation methods in chemistry, such as heat, electricity, and light, mechanochemistry focuses on the activation of chemical reactions by directly or indirectly applying mechanical forces. It has evolved as a powerful tool for controlling chemical reactions in solid state systems, sensing and responding to stresses in polymer materials, regulating interfacial adhesions, and stimulating biological processes. By combining theoretical approaches, simulations and experimental techniques, researchers have gained intricate insights into the mechanisms underlying mechanochemistry. In this review, the physical chemistry principles underpinning mechanochemistry are elucidated and a comprehensive overview of recent significant achievements in the discovery of mechanically responsive chemical processes is provided, with a particular emphasis on their applications in materials science. Additionally, The perspectives and insights into potential future directions for this exciting research field are offered.

Lightwave-electronic harmonic frequency mixing

Electronic frequency mixers are fundamental building blocks of electronic systems. Harmonic frequency mixing in particular enables broadband electromagnetic signal analysis across octaves of spectrum using a single local oscillator. However, conventional harmonic frequency mixers do not operate beyond hundreds of gigahertz to a few terahertz. If extended to the petahertz scale in a compact and scalable form, harmonic mixers would enable field-resolved optical signal analysis spanning octaves of spectra in a monolithic device without the need for frequency conversion using nonlinear crystals. Here, we demonstrate lightwave-electronic harmonic frequency mixing beyond 0.350 PHz using plasmonic nanoantennas. We demonstrate that the mixing process enables complete, field-resolved detection of spectral content far outside that of the local oscillator, greatly extending the range of detectable frequencies compared to conventional heterodyning techniques. Our work has important implications for applications where optical signals of interest exhibit coherent femtosecond-scale dynamics spanning multiple harmonics.

Standardized Electric-Field-Resolved Molecular Fingerprinting

Field-resolved infrared spectroscopy (FRS) of impulsively excited molecular vibrations can surpass the sensitivity of conventional time-integrating spectroscopies, owing to a temporal separation of the molecular signal from the noisy excitation. However, the resonant response carrying the molecular signal of interest depends on both the amplitude and phase of the excitation, which can vary over time and across different instruments. To date, this has compromised the accuracy with which FRS measurements could be compared, which is a crucial factor for practical applications. Here, we utilize a data processing procedure that overcomes this shortcoming while preserving the sensitivity of FRS. We validate the approach for aqueous solutions of molecules. The employed approach is compatible with established processing and evaluation methods for the analysis of infrared spectra and can be applied to existing spectra from databases, facilitating the spread of FRS to new molecular analytical applications.

Background-free mid-infrared absorption spectroscopy using sub-cycle pulses

We have demonstrated highly sensitive single-shot based background-free mid-infrared (MIR) absorption spectroscopy using sub-cycle MIR pulses generated through filamentation. The MIR pulse transmitted through a sample was upconverted with a fast rising and long tailing gate pulse through four-wave difference frequency generation in a silicon membrane. By recording the upconverted spectrum of the free induction decay alone, we successfully measured the absorption spectrum as a positive signal in the wavenumber range from 500 to 4500 cm-1, which covers both the fingerprint and functional group regions. We obtained an absorption spectrum of ∼50 mM of aqueous glucose, which is not detectable with a standard Fourier transform infrared spectrometer.

Plasma infrared fingerprinting with machine learning enables single-measurement multi-phenotype health screening

Infrared spectroscopy is a powerful technique for probing the molecular profiles of complex biofluids, offering a promising avenue for high-throughput in vitro diagnostics. While several studies showcased its potential in detecting health conditions, a large-scale analysis of a naturally heterogeneous potential patient population has not been attempted. Using a population-based cohort, here we analyze 5,184 blood plasma samples from 3,169 individuals using Fourier transform infrared (FTIR) spectroscopy. Applying a multi-task classification to distinguish between dyslipidemia, hypertension, prediabetes, type 2 diabetes, and healthy states, we find that the approach can accurately single out healthy individuals and characterize chronic multimorbid states. We further identify the capacity to forecast the development of metabolic syndrome years in advance of onset. Dataset-independent testing confirms the robustness of infrared signatures against variations in sample handling, storage time, and measurement regimes. This study provides the framework that establishes infrared molecular fingerprinting as an efficient modality for populational health diagnostics.

From Genotype to Phenotype: Raman Spectroscopy and Machine Learning for Label-Free Single-Cell Analysis

Raman spectroscopy has made significant progress in biosensing and clinical research. Here, we describe how surface-enhanced Raman spectroscopy (SERS) assisted with machine learning (ML) can expand its capabilities to enable interpretable insights into the transcriptome, proteome, and metabolome at the single-cell level. We first review how advances in nanophotonics-including plasmonics, metamaterials, and metasurfaces-enhance Raman scattering for rapid, strong label-free spectroscopy. We then discuss ML approaches for precise and interpretable spectral analysis, including neural networks, perturbation and gradient algorithms, and transfer learning. We provide illustrative examples of single-cell Raman phenotyping using nanophotonics and ML, including bacterial antibiotic susceptibility predictions, stem cell expression profiles, cancer diagnostics, and immunotherapy efficacy and toxicity predictions. Lastly, we discuss exciting prospects for the future of single-cell Raman spectroscopy, including Raman instrumentation, self-driving laboratories, Raman data banks, and machine learning for uncovering biological insights.

Background-free correlation spectroscopy using an infrared mode-locked laser

The recent advances in infrared laser technology are expanding the capabilities and applications of vibrational spectroscopy. A promising approach utilizing broadband infrared mode-locked lasers is background-free (BF) absorption spectroscopy. This method captures the free-induction decay (FID) of excited molecules while suppressing the background light. It is unique in that the signal strength increases with input optical power but eventually struggles with detector noise when targeting fewer molecules. In this paper, we present a novel method of multiplexed background-free spectroscopy using a spectral mask whose transmittance has a strong correlation with the absorption spectrum of a target molecule. We successfully demonstrate an order of magnitude increase in the sensitivity due to multiplexing as well as a high molecular contrast due to the spectral correlation. The presented results indicate the promising potential of the method for sensitive and selective detection of trace molecules.

Optical-parametric-amplification-enhanced background-free spectroscopy

Traditional absorption spectroscopy has a fundamental difficulty in resolving small absorbance from a strong background due to the instability of laser sources. Existing background-free methods in broadband vibrational spectroscopy help to alleviate this problem but face challenges in realizing either low extinction ratios or time-resolved field measurements. Here, we introduce optical-parametric-amplification-enhanced background-free spectroscopy, in which the excitation background is first suppressed by an interferometer, and then the free-induction decay that carries molecular signatures is selectively amplified. We show that this method can improve the limit of detection in linear interferometry by order(s) of magnitude without requiring lower extinction ratios or a time-resolved measurement, which can benefit sensing applications in detecting trace species.

Investigating and Quantifying Molecular Complexity Using Assembly Theory and Spectroscopy

Current approaches to evaluate molecular complexity use algorithmic complexity, rooted in computer science, and thus are not experimentally measurable. Directly evaluating molecular complexity could be used to study directed vs undirected processes in the creation of molecules, with potential applications in drug discovery, the origin of life, and artificial life. Assembly theory has been developed to quantify the complexity of a molecule by finding the shortest path to construct the molecule from building blocks, revealing its molecular assembly index (MA). In this study, we present an approach to rapidly infer the MA of molecules from spectroscopic measurements. We demonstrate that the MA can be experimentally measured by using three independent techniques: nuclear magnetic resonance (NMR), tandem mass spectrometry (MS/MS), and infrared spectroscopy (IR). By identifying and analyzing the number of absorbances in IR spectra, carbon resonances in NMR, or molecular fragments in tandem MS, the MA of an unknown molecule can be reliably estimated. This represents the first experimentally quantifiable approach to determining molecular assembly. This paves the way to use experimental techniques to explore the evolution of complex molecules as well as a unique marker of where an evolutionary process has been operating.

Direct Assembly of Bioactive Nanoparticles Constructed from Polyphenol-Nanoengineered Albumin

Albumin nanoparticles are widely used in biomedicine due to their safety, low immunogenicity, and prolonged circulation. However, incorporating therapeutic molecules into these carriers faces challenges due to limited binding sites, restricting drug conjugation efficiency. We introduce a universal nanocarrier platform (X-UNP) using polyphenol-based engineering to incorporate phenolic moieties into albumin nanoparticles. Integration of catechol or galloyl groups significantly enhances drug binding and broadens the drug conjugation possibilities. Our study presents a library of X-UNP nanoparticles with improved drug-loading efficiency, achieving up to 96% across 10 clinically used drugs, surpassing conventional methods. Notably, ibuprofen-UNP nanoparticles exhibit a 5-fold increase in half-life compared with free ibuprofen, enhancing in vivo analgesic and anti-inflammatory effectiveness. This research establishes a versatile platform for protein-based nanosized materials accommodating various therapeutic agents in biotechnological applications.

High-power 100 W Kerr-lens mode-locked ring-cavity femtosecond Yb:YAG thin-disk oscillator

High-power femtosecond pulses delivered at a high-repetition rate will aid machining throughput and improve signal-to-noise ratios for sensitive measurements. Here we demonstrate a Kerr-lens mode-locked femtosecond Yb:YAG ring-cavity thin-disk oscillator with a multi-pass scheme for the laser beam. With four passes through the thin disk, 175-fs pulses were delivered from the oscillator at an average power of 71.5 W and a repetition rate of 65.3 MHz. The corresponding intra-cavity peak power of 110 MW is ample for intra-cavity nonlinear conversion into more exotic wavelength ranges. With six passes, the average output power reached 101.3 W. To the best of our knowledge, this is the highest average output power of any mode-locked ring laser. These results confirm the viability of using multi-pass configuration on a thin-disk ring oscillator for high-throughput femtosecond applications.

Ultra-phase-stable infrared light source at the watt level

Ultrashort pulses at infrared wavelengths are advantageous when studying light-matter interaction. For the spectral region around 2 µm, multi-stage parametric amplification is the most common method to reach higher pulse energies. Yet it has been a key challenge for such systems to deliver waveform-stable pulses without active stabilization and synchronization systems. Here, we present a different approach for the generation of infrared pulses centered at 1.8 µm with watt-level average power utilizing only a single nonlinear crystal. Our laser system relies on a well-established Yb:YAG thin-disk technology at 1.03 µm wavelength combined with a hybrid two-stage broadening scheme. We show the high-power downconversion process via intra-pulse difference frequency generation, which leads to excellent passive stability of the carrier envelope phase below 20 mrad-comparable to modern oscillators. It also provides simple control over the central wavelength within a broad spectral range. The developed infrared source is employed to generate a multi-octave continuum from 500 nm to 2.5 µm opening the path toward sub-cycle pulse synthesis with extreme waveform stability.

Terahertz Photons Inhibit Cancer Cells Long Term by Suppressing Nano Telomerase Activity

Telomeres are nanoscale DNA-protein complexes to protect and stabilize chromosomes. The reexpression of telomerase in cancer cells is a key determinant crucial for the infinite proliferation and long-term survival of most cancer cells. However, the use of telomerase inhibitors for cancer treatment may cause problems such as poor specificity, drug resistance, and cytotoxicity. Here, we discovered a nondrug and noninvasive terahertz modulation strategy capable of the long-term suppression of cancer cells by inhibiting telomerase activity. First, we found that an optimized frequency of 33 THz photon irradiation effectively inhibited the telomerase activity by molecular dynamics simulation and frequency filtering experiments. Moreover, in vitro experiments showed that telomerase activity in 4T1 and MCF-7 cells significantly decreased by 77% and 80% respectively, after 21 days of regular 33 THz irradiation. Furthermore, two kinds of cells were found to undergo aging, apoptosis, and DNA double-strand breaks caused by telomere crisis, which seriously affected the survival of cancer cells. In addition, the tumorigenicity of 4T1 cells irradiated with 33 THz waves for 21 days in in vivo mice decreased by 70%. In summary, this study demonstrates the potential application of THz modulation in nano therapy for cancer.

Probing Blood Plasma Protein Glycosylation with Infrared Spectroscopy

The health state of an individual is closely linked to the glycosylation patterns of his or her blood plasma proteins. However, obtaining this information requires cost- and time-efficient analytical methods. We put forward infrared spectroscopy, which allows label-free analysis of protein glycosylation but so far has only been applied to analysis of individual proteins. Although spectral information does not directly provide the molecular structure of the glycans, it is sensitive to changes therein and covers all types of glycosidic linkages. Combining single-step ion exchange chromatography with infrared spectroscopy, we developed a workflow that enables the separation and analysis of major protein classes in blood plasma. Our results demonstrate that infrared spectroscopy can identify different patterns and global levels of glycosylation of intact plasma proteins. To showcase the strengths and limitations of the proposed approach, we compare the glycoforms of human and bovine alpha-1-acid glycoproteins, which exhibit highly variable global levels of glycosylation. To independently evaluate our conclusions, the glycan moieties of human alpha-1-acid glycoprotein were further analyzed using an established glycomics workflow. Importantly, the chromatographic separation of blood plasma improves the detection of aberrant glycoforms of a given protein as compared to infrared spectroscopy of bulk plasma. The presented approach allows a time-efficient comparison of glycosylation patterns of multiple plasma proteins, opening new avenues for biomedical probing.

Artificial Intelligence-based Amide-II Infrared Spectroscopy Simulation for Monitoring Protein Hydrogen Bonding Dynamics

The structurally sensitive amide II infrared (IR) bands of proteins provide valuable information about the hydrogen bonding of protein secondary structures, which is crucial for understanding protein dynamics and associated functions. However, deciphering protein structures from experimental amide II spectra relies on time-consuming quantum chemical calculations on tens of thousands of representative configurations in solvent water. Currently, the accurate simulation of amide II spectra for whole proteins remains a challenge. Here, we present a machine learning (ML)-based protocol designed to efficiently simulate the amide II IR spectra of various proteins with an accuracy comparable to experimental results. This protocol stands out as a cost-effective and efficient alternative for studying protein dynamics, including the identification of secondary structures and monitoring the dynamics of protein hydrogen bonding under different pH conditions and during protein folding process. Our method provides a valuable tool in the field of protein research, focusing on the study of dynamic properties of proteins, especially those related to hydrogen bonding, using amide II IR spectroscopy.

Infrared Spectroscopy for Rapid Triage of Cancer Using Blood Derivatives: A Reality Check

Infrared (IR) spectroscopy of serum/plasma represents an alluring molecular diagnostic tool, especially for cancer, as it can provide a molecular fingerprint of clinical samples based on vibrational modes of chemical bonds. However, despite the superior performance, the routine adoption of this technique for clinical settings has remained elusive. This is due to the potential confounding factors that are often overlooked and pose a significant barrier to clinical translation. In this Perspective, we summarize the concerns associated with various confounding factors, such as fluid sampling, optical effects, hemolysis, abnormal cardiovascular and/or hepatic functions, infections, alcoholism, diet style, age, and gender of a patient or normal control cohort, and improper selection of numerical methods that ultimately would lead to improper spectral diagnosis. We also propose some precautionary measures to overcome the challenges associated with these confounding factors.

Antimicrobial susceptibility testing using infrared attenuated total reflection (IR-ATR) spectroscopy to monitor metabolic activity

Fast and accurate detection of antimicrobial resistance in pathogens remains a challenge, and with the increase in antimicrobial resistance due to mis- and overuse of antibiotics, it has become an urgent public health problem. We demonstrate how infrared attenuated total reflection (IR-ATR) can be used as a simple method for assessment of bacterial susceptibility to antibiotics. This is achieved by monitoring the metabolic activities of bacterial cells via nutrient consumption and using this as an indicator of bacterial viability. Principal component analysis of the obtained spectra provides a tool for fast and simple discrimination of antimicrobial resistance in the acquired data. We demonstrate this concept using four bacterial strains and four different antibiotics, showing that the change in glucose concentration in the growth medium after 2 h, as monitored by IR-ATR, can be used as a spectroscopic diagnostic technique, to reduce detection time and to improve quality in the assessment of antimicrobial resistance in pathogens.

Photoinduced force microscopy as a novel method for the study of microbial nanostructures

A detailed comparison of the capabilities of electron microscopy and nano-infrared (IR) microscopy for imaging microbial nanostructures has been carried out for the first time. The surface sensitivity, chemical specificity, and non-destructive nature of spectroscopic mapping is shown to offer significant advantages over transmission electron microscopy (TEM) for the study of biological samples. As well as yielding important topographical information, the distribution of amides, lipids, and carbohydrates across cross-sections of bacterial (Escherichia coli, Staphylococcus aureus) and fungal (Candida albicans) cells was demonstrated using PiFM. The unique information derived from this new mode of spectroscopic mapping of the surface chemistry and biology of microbial cell walls and membranes, may provide new insights into fungal/bacterial cell function as well as having potential use in determining mechanisms of antimicrobial resistance, especially those targeting the cell wall.

HLA-B*27 and Ankylosing Spondylitis: 50 Years of Insights and Discoveries

PURPOSE OF REVIEW

To commemorate the 50th anniversary of the groundbreaking discovery of a remarkably strong association between HLA-B*27 and ankylosing spondylitis (AS).

RECENT FINDINGS

In addition to HLA-B*27, more than 116 other recognized genetic risk variants have been identified, while epigenetic factors largely remain unexplored in this context. Among patients with AS who carry the HLA-B*27 gene, clonally expanded CD8 + T cells can be found in their bloodstream and within inflamed tissues. Moreover, the α and β chain motifs of these T-cell receptors demonstrate a distinct affinity for certain self- and microbial-derived peptides, leading to an autoimmune response that ultimately results in the onset of the disease. These distinctive peptide-binding and presentation characteristics are a hallmark of the disease-associated HLA-B*27:05 subtype but are absent in HLA-B*27:09, a subtype not associated with the disease, differing by only a single amino acid. This discovery represents a significant advancement in unraveling the 50-year-old puzzle of how HLA-B*27 contributes to the development of AS. These findings will significantly accelerate the process of identifying peptides, both self- and microbial-derived, that instigate autoimmunity. This, in return, will pave the way for the development of more accurate and effective targeted treatments. Moreover, the discovery of improved biomarkers, in conjunction with the emerging technology of electric field molecular fingerprinting, has the potential to greatly bolster early diagnosis capabilities. A very recently published groundbreak paper underscores the remarkable effectiveness of targeting and eliminating disease-causing T cells in a HLA-B*27 patients with AS. This pivotal advancement not only signifies a paradigm shift but also bolsters the potential for preventing the disease in individuals carrying high-risk genetic variants.

Transmission infrared micro-spectroscopic study of individual human hair

Significance

Understanding the optical transmission property of human hair, especially in the infrared regime, is vital in physical, clinical, and biomedical research. However, the majority of infrared spectroscopy on human hair is performed in the reflection mode, which only probes the absorptance of the surface layer.

Aim

The direct transmission spectrum of individual hair without horizontal cut offers a rapid and non-destructive test of the hair cortex but is less investigated experimentally due to the small size and strong absorption of the hair.

Approach

In this work, we conduct a transmission infrared micro-spectroscopic study on individual human hair with the help of Fourier-transform infrared microscope experimentally. Its high spatial resolution of infrared micro-spectroscopy further allows the comparison among different regions of hair. The geometry effect of the internal hair structure is also quantified using the finite-element simulation, which supports the experimental results.

Results

By utilizing direct measurements of the transmission spectrum using a Fourier-transform infrared microscope, the human hair is found to display prominent band filtering behavior. In a case study of adult-onset Still's disease, the corresponding infrared transmission exhibits systematic variations of spectral weight as the disease evolves.

Conclusions

Our work implies that the variation of spectral weight may relate to the disordered microscopic structure variation of the hair cortex during an inflammatory attack. Our work reveals the potential of hair infrared transmission spectrum in tracing the variation of hair cortex retrospectively.

Lichen Biodiversity and Near-Infrared Metabolomic Fingerprint as Diagnostic and Prognostic Complementary Tools for Biomonitoring: A Case Study in the Eastern Iberian Peninsula

In the 1990s, a sampling network for the biomonitoring of forests using epiphytic lichen diversity was established in the eastern Iberian Peninsula. This area registered air pollution impacts by winds from the Andorra thermal power plant, as well as from photo-oxidants and nitrogen depositions from local and long-distance transport. In 1997, an assessment of the state of lichen communities was carried out by calculating the Index of Atmospheric Purity. In addition, visible symptoms of morphological injury were recorded in nine macrolichens pre-selected by the speed of symptom evolution and their wide distribution in the territory. The thermal power plant has been closed and inactive since 2020. During 2022, almost 25 years later, seven stations of this previously established biomonitoring were revaluated. To compare the results obtained in 1997 and 2022, the same methodology was used, and data from air quality stations were included. We tested if, by integrating innovative methodologies (NIRS) into biomonitoring tools, it is possible to render an integrated response. The results displayed a general decrease in biodiversity in several of the sampling plots and a generalised increase in damage symptoms in the target lichen species studied in 1997, which seem to be the consequence of a multifactorial response.

Ultrafast Yb:YAG laser oscillator with gigahertz repetition rate

We present a SESAM modelocked Yb:YAG solid-state laser providing low-noise narrowband pulses with a pulse duration of 606 fs at a 1.09-GHz repetition rate, delivering up to 2.5 W of average output power. This laser provides access to a new parameter space that could previously not be reached by solid-state lasers and, to the best of our knowledge, is the first modelocked solid-state Yb:YAG laser in the gigahertz regime. This is achieved by introducing a single additional intracavity element, specifically a nonlinear birefringent YVO4 crystal, for soliton formation, polarization selection, and cavity intensity clamping. The isotropic pump absorption in Yb:YAG allows for stable and low-noise operation with multimode fiber pumping. This laser is ideally suited as a seed source for many commercial high-power Yb-doped amplification systems operating at a center wavelength around 1.03 µm. The laser exhibits a high power per comb line of 5.0 mW which also makes it interesting for applications in frequency comb spectroscopy, especially if it is used to pump an optical parametric oscillator. We measure a relative intensity noise (RIN) of 0.03%, integrated from 1 Hz to 10 MHz. Furthermore, we show that the laser timing jitter for noise frequencies >2 kHz is fully explained by a power-dependent shift in the center wavelength of 0.38 nm/W due to the quasi-three-level laser gain material. The narrow gain bandwidth of Yb:YAG reduces this contribution to noise in comparison to other SESAM modelocked Yb-doped lasers.

Coherent Subcycle Optical Shock from a Superluminal Plasma Wake

We propose exploiting the superluminal plasma wake for coherent Cherenkov radiation by injecting a relativistic electron beam (REB) into a plasma with a slowly varying density up-ramp. Using three-dimensional particle-in-cell and far-field time-domain radiation simulations, we show that an isolated subcycle pulse is coherently emitted towards the Cherenkov angle by bubble-sheath electrons successively at the rear of the REB-induced superluminal plasma wake. A theoretical model based on a superluminal current dipole has been developed to interpret such coherent radiation, and agrees well with the simulation results. This radiation has ultrashort attosecond-scale duration and high intensity, and exhibits excellent directionality with ultralow angular divergence and stable carrier envelope phase. Its intensity increases with the square of the propagation length and its central frequency can be easily tuned over a wide range, from the far infrared to the ultraviolet.

Continuous-Spectrum-Polarization Recombinant Optical Encryption with a Dielectric Metasurface

The Jones matrix, with eight degrees of freedom (DoFs), provides a general mathematical framework for the multifunctional design of metasurfaces. Theoretically, the maximum eight DoFs can be further extended in the spectrum dimension to endow unique encryption capabilities. However, the topology and intrinsic spectral responses of meta-atoms constrains the continuous engineering of polarization evolution over wavelength dimension. In this work, a forward evolution strategy to quickly establish the mapping relationships between the solutions of the dispersion Jones matrix and the spectral responses of meta-atoms is reported. Based on the eigenvector transformation method, arbitrary conjugate polarization channels over the continuous-spectrum dimension are successfully reconstructed. As a proof-of-concept, a silicon metadevice is demonstrated for optical information encryption transmission. Remarkably, the arbitrary combination forms of polarization and wavelength dimension increase the information capacity (210 ), and the measured polarization contrasts of the conjugate polarization conversion are >94% in the entire wavelength range (3-4 µm). It is believed that the proposed approach will benefit secure optical and quantum information technologies.

In-line synthesis of multi-octave phase-stable infrared light

Parametric downconversion driven by modern, high-power sources of 10-fs-scale near-infrared pulses, in particular intrapulse difference-frequency generation (IPDFG), affords combinations of properties desirable for molecular vibrational spectroscopy in the mid-infrared range: broad spectral coverage, high brilliance, and spatial and temporal coherence. Yet, unifying these in a robust and compact radiation source has remained a key challenge. Here, we address this need by employing IPDFG in a multi-crystal in-line geometry, driven by the 100-W-level, 10.6-fs pulses of a 10.6-MHz-repetition-rate, nonlinearly post-compressed Yb:YAG thin-disk oscillator. Polarization tailoring of the driving pulses using a bichromatic waveplate is followed by a sequence of two crystals, LiIO₃ and LiGaS₂, resulting in the simultaneous coverage of the 800-cm^-1-to-3000-cm^-1 spectral range (at -30-dB intensity) with 130 mW of average power. We demonstrate that optical-phase coherence is maintained in this in-line geometry, in theory and experiment, the latter employing ultra-broadband electro-optic sampling. These results pave the way toward coherent spectroscopy schemes like field-resolved and frequency-comb spectroscopy, as well as nonlinear, ultrafast spectroscopy and optical-waveform synthesis across the entire infrared molecular fingerprint region.

FTIR study on the CO interactions of benzeneacetamide in solution

The main attention of present work is to study how benzeneacetamide interacts with other molecules in organic solvents. The frequencies of CO groups in 18 solvents were obtained by using infrared spectroscopy. The empirical parameters of the solvents as the acceptor number (AN), the van der Waals interaction parameters (S_VW) and the linear solvation energy relationships (LSER) were correlated with the frequencies of carbonyl stretching vibration (ν(CO)) of benzeneacetamide to estimate the contributions in intermolecular interactions. The results showed that solvent effects on the frequencies of CO stretching vibrations of benzeneacetamide were obvious. Self-association of alkanol leads to enhancement of O-H⋯O=C hydrogen bond strength and red-shift of the ν(CO) peak. The ν(CO) of benzeneacetamide is more vulnerable to the acidity of the hydrogen bond donor of the solvent. This research contributes to a thorough understanding of the molecular interactions and microstructures in the liquid mixtures.

Nonlinear pulse compression to sub-two-cycle, 1.3 mJ pulses at 1.9 μm wavelength with 132 W average power

We report the nonlinear pulse compression of a high-power, thulium-doped fiber laser system using a gas-filled hollow-core fiber. The sub-two cycle source delivers 1.3 mJ pulse energy with 80 GW peak power at a central wavelength of 1.87 μm and an average power of 132 W. This is, so far, to the best of our knowledge, the highest average power of a few-cycle laser source reported in the short-wave infrared region. Given its unique combination of high pulse energy and high average power, this laser source is an excellent driver for nonlinear frequency conversion, toward terahertz, mid-infrared, and soft X-ray spectral regions.

Passively CEP stable sub-2-cycle source in the mid-infrared by adiabatic difference frequency generation

We report on the generation of a passive carrier-envelope phase (CEP) stable 1.7-cycle pulse in the mid-infrared by adiabatic difference frequency generation. With sole material-based compression, we achieve a sub-2-cycle 16-fs pulse at a center wavelength of 2.7 µm and measured a CEP stability of <190 mrad root mean square. The CEP stabilization performance of an adiabatic downconversion process is characterized for the first time, to the best of our knowledge.

Upconversion time-stretch infrared spectroscopy

High-speed measurement confronts the extreme speed limit when the signal becomes comparable to the noise level. In the context of broadband mid-infrared spectroscopy, state-of-the-art ultrafast Fourier-transform infrared spectrometers, in particular dual-comb spectrometers, have improved the measurement rate up to a few MSpectra s-1, which is limited by the signal-to-noise ratio. Time-stretch infrared spectroscopy, an emerging ultrafast frequency-swept mid-infrared spectroscopy technique, has shown a record-high rate of 80 MSpectra s-1 with an intrinsically higher signal-to-noise ratio than Fourier-transform spectroscopy by more than the square-root of the number of spectral elements. However, it can measure no more than ~30 spectral elements with a low resolution of several cm-1. Here, we significantly increase the measurable number of spectral elements to more than 1000 by incorporating a nonlinear upconversion process. The one-to-one mapping of a broadband spectrum from the mid-infrared to the near-infrared telecommunication region enables low-loss time-stretching with a single-mode optical fiber and low-noise signal detection with a high-bandwidth photoreceiver. We demonstrate high-resolution mid-infrared spectroscopy of gas-phase methane molecules with a high resolution of 0.017 cm-1. This unprecedentedly high-speed vibrational spectroscopy technique would satisfy various unmet needs in experimental molecular science, e.g., measuring ultrafast dynamics of irreversible phenomena, statistically analyzing a large amount of heterogeneous spectral data, or taking broadband hyperspectral images at a high frame rate.

Designing broadband dispersive mirrors in the mid-infrared spectral range: a theoretical study

The study reports practically important and interesting results on designing dispersive mirrors (DMs) operating in the mid-infrared spectral range from 3 to 18 µm. The admissible domains of the most important design specifications, the mirror bandwidth and group delay variation, were constructed. Estimations of the required total coating thickness, thickness of the thickest layer, and expected number of layers are obtained. The results are confirmed by an analysis of several hundreds of DM design solutions.

Mid-infrared cross-comb spectroscopy

Dual-comb spectroscopy has been proven beneficial in molecular characterization but remains challenging in the mid-infrared region due to difficulties in sources and efficient photodetection. Here we introduce cross-comb spectroscopy, in which a mid-infrared comb is upconverted via sum-frequency generation with a near-infrared comb of a shifted repetition rate and then interfered with a spectral extension of the near-infrared comb. We measure CO2 absorption around 4.25 µm with a 1-µm photodetector, exhibiting a 233-cm-1 instantaneous bandwidth, 28000 comb lines, a single-shot signal-to-noise ratio of 167 and a figure of merit of 2.4 × 106 Hz1/2. We show that cross-comb spectroscopy can have superior signal-to-noise ratio, sensitivity, dynamic range, and detection efficiency compared to other dual-comb-based methods and mitigate the limits of the excitation background and detector saturation. This approach offers an adaptable and powerful spectroscopic method outside the well-developed near-IR region and opens new avenues to high-performance frequency-comb-based sensing with wavelength flexibility.

Z-DNA and Z-RNA: Methods-Past and Future

A quote attributed to Yogi Berra makes the observation that "It's tough to make predictions, especially about the future," highlighting the difficulties posed to an author writing a manuscript like the present. The history of Z-DNA shows that earlier postulates about its biology have failed the test of time, both those from proponents who were wildly enthusiastic in enunciating roles that till this day still remain elusive to experimental validation and those from skeptics within the larger community who considered the field a folly, presumably because of the limitations in the methods available at that time. If anything, the biological roles we now know for Z-DNA and Z-RNA were not anticipated by anyone, even when those early predictions are interpreted in the most favorable way possible. The breakthroughs in the field were made using a combination of methods, especially those based on human and mouse genetic approaches informed by the biochemical and biophysical characterization of the Zα family of proteins. The first success was with the p150 Zα isoform of ADAR1 (adenosine deaminase RNA specific), with insights into the functions of ZBP1 (Z-DNA-binding protein 1) following soon after from the cell death community. Just as the replacement of mechanical clocks by more accurate designs changed expectations about navigation, the discovery of the roles assigned by nature to alternative conformations like Z-DNA has forever altered our view of how the genome operates. These recent advances have been driven by better methodology and by better analytical approaches. This article will briefly describe the methods that were key to these discoveries and highlight areas where new method development is likely to further advance our knowledge.

Ultra-broadband all-optical sampling of optical waveforms

Optical-field sampling techniques provide direct access to the electric field of visible and near-infrared light. The existing methods achieve the necessary bandwidth using highly nonlinear light-matter interaction that involves ionization of atoms or generation of charge carriers in solids. We demonstrate an alternative, all-optical approach for measuring electric fields of broadband laser pulses, which offers an advantage in terms of sensitivity and signal-to-noise ratio and extends the detection bandwidth of optical methods to the petahertzdomain.

Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract Cancers

Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) of liquid biofluids enables the probing of biomolecular markers for disease diagnosis, characterized as a time and cost-effective approach. It remains poorly understood for fast and deep diagnosis of digestive tract cancers (DTC) to detect abundant changes and select specific markers in a broad spectrum of molecular species. Here, we present a diagnostic protocol of DTC in which the in-situ blood-based ATR-FTIR spectroscopic data mining pathway was designed for the identification of DTC triages in 252 blood serum samples, divided into the following groups: liver cancer (LC), gastric cancer (GC), colorectal cancer (CC), and their different three stages respectively. The infrared molecular fingerprints (IMFs) of DTC were measured and used to build a 2-dimensional second derivative spectrum (2D-SD-IR) feature dataset for classification, including absorbance and wavenumber shifts of FTIR vibration peaks. By comparison, the Partial Least-Squares Discriminant Analysis (PLS-DA) and backpropagation (BP) neural networks are suitable to differentiate DTCs and pathological stages with a high sensitivity and specificity of 100% and averaged more than 95%. Furthermore, the measured IMF data was mutually validated via clinical blood biochemistry testing, which indicated that the proposed 2D-SD-IR-based machine learning protocol greatly improved DTC classification performance.

Investigation of bactericidal effect of a mid-infrared free electron laser on Escherichia coli

The rapid increase in the number of bacteria that are resistant to many commonly used antimicrobial agents and their global spread have become a major problem worldwide. In particular, for periodontal disease, which is a localized infection, there is a growing need for treatment methods that do not primarily involve antimicrobial agents, and antimicrobial photodynamic therapy (aPDT) is attracting attention. In this study, the bactericidal effects of a mid-infrared free electron laser (MIR-FEL) on E. coli were investigated as a basic study to examine the applicability of MIR-FELs, which can selectively excite molecular vibrations due to their wavelength tunability, to aPDT. The optimal irradiation wavelengths to be examined in this study were determined from the infrared spectrum of the bacteria, which was obtained using Fourier transform infrared spectroscopy. Five irradiation wavelengths (6.62, 6.88, 7.14, 8.09 and 9.26 µm) were selected from the FT-IR spectrum, and we found that the bactericidal effects at a wavelength of 6.62 µm were markedly stronger than those observed at the other wavelengths. At this wavelength corresponding to the Amide II band, the bacterial survival rate decreased significantly as the irradiation time increased. On the contrary, irradiation of a neodymium-doped yttrium aluminum garnet (Nd: YAG) laser at 1.06 µm exhibited no distinct bactericidal effect. No morphological changes were observed after MIR-FEL irradiation, suggesting that a bacterial organelle molecule may be the target of MIR-FEL irradiation, but the exact target was not identified. Furthermore, the temperature change induced in the culture medium by the laser irradiation was ± 1.5 °C at room temperature. These results suggest that the bactericidal effects of MIR-FEL are derived from photochemical reactions involving infrared photons, since E. coli is usually killed by heating it to 75 °C for 1 min or longer.

Broadband background-free vibrational spectroscopy using a mode-locked Cr:ZnS laser

We demonstrate high-sensitivity vibrational absorption spectroscopy in the 2-micron wavelength range by using a mode-locked Cr:ZnS laser. Interferometric subtraction and multichannel detection across the broad laser spectrum realize simultaneous background-free detection of multiple vibrational modes over a spectral span of >380 cm^-1. Importantly, we achieve detection of small absorbance on the order of 10^-4, which is well below the detection limit of conventional absorption spectroscopy set by the detector dynamic range. The results indicate the promising potential of the background-free method for ultrasensitive and rapid detection of trace gases and chemicals.

Second and third-order dispersion compensating mirror pairs for the spectral range from 1.2-3.2µm

We demonstrate the design, production, characterization and application of two dispersive complementary mirror pairs compensating second- and third-order dispersion, respectively. Both mirror pairs operate in the spectral range from 1.2-3.2µm. This is an unprecedented bandwidth of over 1.4 octaves which can drive further improvements in Cr:ZnS, Cr:ZnSe and other laser systems with a central wavelength around 2µm. The first pair provides a constant group delay dispersion of -100fs², while the second one enables the compensation of the third-order dispersion that is introduced by a TiO₂ crystal.