Development and prospect of near-infrared spectroscopy-assisted schizophrenia diagnosis based on bibliometrics

In this editorial,we comment on the recent article by Fei et al exploring the field of near-infrared spectroscopy(NIRS)research in schizophrenia from a bibliometrics perspective.In recent years,NIRS has shown unique advantages in the auxiliary diagnosis of schizophrenia,and the introduction of bibliometrics has provided a macro perspective for research in this field.Despite the opportunities brought about by these technological developments,remaining challenges require multidi-sciplinary approach to devise a reliable and accurate diagnosis system for schizo-phrenia.Nonetheless,NIRS-assisted technology is expected to contribute to the division of methods for early intervention and treatment of schizophrenia.

Outlier Detection in Near Infra-Red Spectra with Self-Organizing Map

A new method to detect multiple outliers in multivariate data is proposed. It is a combination of minimum subsets, resampling and self-organizing map (SOM) algorithm introduced by Kohonen,which provides a robust way with neural network. In this method, the number and organization of the neurons are selected by the characteristics of the spectra, e.g., the spectra data are often changed linearly with the concentration of the components and are often measured repeatedly, etc. So the spatial distribution of the neurons can be arranged by this characteristic. With this method, all the outliers in the spectra can be detected, which cannot be solved by the traditional method, and the speed of computation is higher than that of the traditional neural network method. The results of the simulation and the experiment show that this method is simple, effective, intuitionistic and all the outliers in the spectra can be detected in a short time. It is useful when associated with the regression model in the near infra-red research.

Near infra-red light treatment of Alzheimer's disease

Alzheimers disease(AD)is a chronic neurodegenerative disease.The symptoms include memoryand spatial learning dificulties,language disorders,and loss of motivation,which get worse overtime,eventually ending in death.No ffective treatments are available for AD,currently.Currenttreatments only attenuate symptoms temporarily and are associated with severe side ffects.Nearinfra-red(NIR)light has been studied for a long time.We investigated the effect of NIR on ADusing a transgenic mouse model,which was obtained by co-injecting two vectors carrying ADmutations in amyloid precursor protein(APP)and presenilin-i(PSEN1)into C57BL/6J mice.The irradiation equipment consisted of an accommodating box and an LED array.The wave-length of NIR light emitted from LED was between 1040 nm and 1090 nm.The power densitydelivered at the level of the mice was approximately 15 mW/cm^(2),Firstly,we treated the micewith NIR for 40 days,Then,the irradiation was suspended for 28 days.Finally,another 15 daystreatment was brought to mice.We conducted Morris water maze and immunofluorescenceanalysis to evaluate the effects of treatment.Immunofuorescence analysis was based on mea-suring the quantity of plaques in mouse brain slices,Our results show that NIR light improvesmemory and spatial learning ability and reduces plaques moderately.NIR light represents apotential treatment for AD.

Laser spectroscopy imaging technique coupled withnanomaterials for cancer diagnosis: A review

Laser spectroscopic imaging techniques have received tremendous attention in the-eld of cancer diagnosis due to their high sensitivity,high temporal resolution,and short acquisition time.However,the limited tissue penetration of the laser is still a challenge for the in vivo diagnosis of deep-seated lesions.Nanomaterials have been universally integrated with spectroscopic imaging techniques for deeper cancer diagnosis in vivo.The components,morphology,and sizes of nanomaterials are delicately designed,which could realize cancer diagnosis in vivo or in situ.Considering the enhanced signal emitting from the nanomaterials,we emphasized their combination with spectroscopic imaging techniques for cancer diagnosis,like the surface-enhanced Raman scattering(SERS),photoacoustic,fluorescence,and laser-induced breakdown spectroscopy(LIBS).Applications ofthe above spectroscopic techniques offer new prospectsfor cancer diagnosis.

Functional near-infrared spectroscopy in non-invasive neuromodulation

Non-invasive cerebral neuromodulation technologies are essential for the reorganization of cerebral neural networks,which have been widely applied in the field of central neurological diseases,such as stroke,Parkinson’s disease,and mental disorders.Although significant advances have been made in neuromodulation technologies,the identification of optimal neurostimulation paramete rs including the co rtical target,duration,and inhibition or excitation pattern is still limited due to the lack of guidance for neural circuits.Moreove r,the neural mechanism unde rlying neuromodulation for improved behavioral performance remains poorly understood.Recently,advancements in neuroimaging have provided insight into neuromodulation techniques.Functional near-infrared spectroscopy,as a novel non-invasive optical brain imaging method,can detect brain activity by measuring cerebral hemodynamics with the advantages of portability,high motion tole rance,and anti-electromagnetic interference.Coupling functional near-infra red spectroscopy with neuromodulation technologies offe rs an opportunity to monitor the cortical response,provide realtime feedbac k,and establish a closed-loop strategy integrating evaluation,feedbac k,and intervention for neurostimulation,which provides a theoretical basis for development of individualized precise neuro rehabilitation.We aimed to summarize the advantages of functional near-infra red spectroscopy and provide an ove rview of the current research on functional near-infrared spectroscopy in transcranial magnetic stimulation,transcranial electrical stimulation,neurofeedback,and braincomputer interfaces.Furthermore,the future perspectives and directions for the application of functional near-infrared spectroscopy in neuromodulation are summarized.In conclusion,functional near-infrared spectroscopy combined with neuromodulation may promote the optimization of central pellral reorganization to achieve better functional recovery form central nervous system diseases.

Near-infrared spectroscopy in schizophrenia:A bibliometric perspective

BACKGROUND Compared with current methods used to assess schizophrenia,near-infrared spectroscopy(NIRS)has the advantages of providing noninvasive and real-time monitoring of functional activities of the brain and providing direct and objective assessment information.AIM To explore the research field of NIRS in schizophrenia from the perspective of bibliometrics.METHODS The Web of Science Core Collection was used as the search tool,and the last search date was April 21,2024.Bibliometric indicators,such as the numbers of publications and citations,were recorded.Bibliometrix and VOS viewer were used for visualization analysis.RESULTS A total of 355 articles from 105 journals were included in the analysis.The overall trend of the number of research publications increased.Schizophrenia Research was identified as an influential journal in the field.Kasai K was one of the most influential and productive authors in this area of research.The University of Tokyo and Japan had the highest scientific output for an institution and a country,respectively.The top ten keywords were“schizophrenia”,“activation”,“near-infrared spectroscopy”,“verbal fluency task”,“cortex”,“brain,performance”,“workingmemory”,“brain activation”,and“prefrontal cortex”.CONCLUSION Our study reveals the evolution of knowledge and emerging trends in the field of NIRS in schizophrenia.the research focus is shifting from underlying disease characteristics to more in-depth studies of brain function and physiological mechanisms.

Infra-red Thermal Imaging of the Inner Canthus: Correlates with the Temperature of the Injured Human Brain

Introduction: Infra-red (IR) thermometry is a safe and valid method to determine internal and surface temperature in human subjects. Under conditions of brain damage (head injury or stroke) knowledge of changes in the temperature of intracranial tissue is justified because of the vulnerability of neurons to accelerated damage at temperatures at the upper end of the febrile range. Aim: To determine the temperature at the inner canthus (IC) of the eye as a potential surrogate for brain temperature. Methods: Invasive monitoring of deep brain structures, lateral ventricle and deep white matter. IR temperature readings obtained at right and left IC. Results: ?Strong correlations were evident between R and L IC and brain. Close, as well as poor, agreement between?? sites was shown in some patients and at some times. For right hemispheric lesions four had a better correlation between TbrV and TRIC when compared to TLIC.? When the correlation between TbrV and TLIC was better compared to TbrV and TRIC, four had a predominant right hemispheric lesion. Conclusions: Improved techniques for IR thermal imaging accuracy at the bedside has the potential to improve temperature measurement agreement. The predominant lesion side may have a bearing on maximum ipsilateral IC temperature Further studies are ongoing in this pilot study population.

Breast Thermography: A 20-Year Retrospective Review of Infra-Red Breast Thermal Imaging in New Zealand and Its Potential Role in Breast Health Management

Cases are presented to reveal how modern computerised infra-red thermal imaging has the potential to assist in early breast cancer detection. The history of thermography and some recent controversies surrounding mammography are discussed. Examples of thermal imaging combined with naturopathic interventions are described. Since 2002, more than 8000 women in New Zealand have chosen to include thermal imaging as a part of their breast health management. Breast thermal imaging combined with relevant health advice, resulted in a perceived worthwhile benefit to patients in managing overall health.

Differential diagnosis of Crohn’s disease and intestinal tuberculosis based on ATR-FTIR spectroscopy combined with machine learning

BACKGROUND Crohn’s disease(CD)is often misdiagnosed as intestinal tuberculosis(ITB).However,the treatment and prognosis of these two diseases are dramatically different.Therefore,it is important to develop a method to identify CD and ITB with high accuracy,specificity,and speed.AIM To develop a method to identify CD and ITB with high accuracy,specificity,and speed.METHODS A total of 72 paraffin wax-embedded tissue sections were pathologically and clinically diagnosed as CD or ITB.Paraffin wax-embedded tissue sections were attached to a metal coating and measured using attenuated total reflectance fourier transform infrared spectroscopy at mid-infrared wavelengths combined with XGBoost for differential diagnosis.RESULTS The results showed that the paraffin wax-embedded specimens of CD and ITB were significantly different in their spectral signals at 1074 cm^(-1) and 1234 cm^(-1) bands,and the differential diagnosis model based on spectral characteristics combined with machine learning showed accuracy,specificity,and sensitivity of 91.84%,92.59%,and 90.90%,respectively,for the differential diagnosis of CD and ITB.CONCLUSION Information on the mid-infrared region can reveal the different histological components of CD and ITB at the molecular level,and spectral analysis combined with machine learning to establish a diagnostic model is expected to become a new method for the differential diagnosis of CD and ITB.

A rened analytical model for reconstruction problems in diuse reectance spectroscopy

A rened analytical model of spatially resolved diffuse reectance with small source-detector separations(SDSs)for the in vivo skin studies is proposed.Compared to the conventional model developed by Farrell et al.,it accounts for the limited acceptance angle of the detectorber.The rened model is validated in the wide range of optical parameters by Monte Carlo simulations of skin diffuse reectance at SDSs of units of mm.Cases of uniform dermis and two-layered epidermis-dermis structures are studied.Higher accuracy of the rened model compared to the conventional one is demonstrated in the separate,constraint-free reconstruction of absorption and reduced scattering spectra of uniform dermis from the Monte Carlo simulated data.In the case of epidermis-dermis geometry,the recovered values of reduced scattering in dermis are overestimated and the recovered values of absorption are underestimated for both analytical models.Presumably,in the presence of a thin mismatched topical layer,only the effective attenuation coe±cient of the bottom layer can be accurately recovered using a diffusion theorybased analytical model while separate reconstruction of absorption and reduced scattering fails due to the inapplicability of the method of images.These-ndings require implementation of more sophisticated models of light transfer in inhomogeneous media in the recovery algorithms.

Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.

In situ infrared, Raman and X-ray spectroscopy for the mechanistic understanding of hydrogen evolution reaction

Hydrogen production by water reduction reactions has received considerable attention because hydrogen is considered a clean-energy carrier,key for a sustainable energy future.Computational methods have been widely used to study the reaction mechanism of the hydrogen evolution reaction(HER),but the calculation results need to be supported by experimental results and direct evidence to confirm the mechanistic insights.In this review,we discuss the fundamental principles of the in situ spectroscopic strategy and a theoretical model for a mechanistic understanding of the HER.In addition,we investigate recent studies by in situ Fourier transform infrared(FTIR),Raman spectroscopy,and X-ray absorption spectroscopy(XAS) and cover new findings that occur at the catalyst-electrolyte interface during HER.These spectroscopic strategies provide practical ways to elucidate catalyst phase,reaction intermediate,catalyst-electrolyte interface,intermediate binding energy,metal valency state,and coordination environment during HER.

Near Infrared Spectroscopy (NIRS) Model-Based Prediction for Protein Content in Cowpea

Cowpea (Vigna unguiculata L. Walp) is a multi-purpose legume with high quality protein for human consumption and livestock. The objective of this work was to develop near-infrared spectroscopy (NIRS) prediction models to estimate protein content in cowpea. A total of 116 cowpea breeding lines with a wide range of protein contents (19.28 % to 32.04%) were selected to build the model using whole seed and ground seed samples. Partial least-squares discriminant analysis (PLS-DA) regression technique with different pre-treatments (derivatives, standard normal variate, and multiplicative scatter correction) were carried out to develop the protein prediction model. Results showed: 1) spectral plots of both the whole seed and ground seed showed higher spectral scatter at higher wavelengths (>1450 nm), 2) data pre-processing affects prediction accuracy for bot whole seed and ground seed samples, 3) prediction using ground seed samples (0.64 R2 0.85) is better than the whole seed (0.33 R2 0.78), and 4) the data pre-processing second derivative with standard normal variate has the best prediction (R2_whole seed = 0.78, R2_ground seed = 0.85). The results will be of interest in cowpea breeding programs aimed at improving total seed protein content.

Investigation on Binding between Cations and Amides using UV Raman Spectroscopy

The interaction of proteins with salt ions plays an important role in life activities.We used butyramide as a model molecule to investigate the interaction of protein backbones with cations.The experiment was performed in an aqueous solution of metal chloride using UV Raman spectroscopy.It was found that well-hydrated metal cations(Ca^(2+),Mg^(2+))tend to bind to C=O in the amide bond,resulting in redistribution of the amide I band peaks.Specifically,the peak intensity ratio of 1655 cm^(-1)to 1610 cm^(-1)increases significantly with increasing concentrations.However,this phenomenon is not obviously observed in NaCl solution.Furthermore,we studied the effect of salt ions on the water structures.The addition of Ca^(2+)and Mg^(2+)is beneficial to the enhancement of the water signal at the 3400 cm^(-1)position,while the Na^(+)at the same concentration is not obvious.The results have shown that the interaction between cations and amides satisfies the following order:Ca^(2+)>Mg^(2+)>Na^(+),which conforms to the Hofmeister series.

A dual-route optical emission spectroscopy diagnostic with wide spectral range and high wavelength resolution on HL-2A tokamak

A dual-route optical emission spectroscopy(D-OES)diagnostic is newly developed to monitor the optical emission from the X-point plasma region on the HL-2 A tokamak.This diagnostic is composed of an imaging system,a beam-splitting system for dual-route measurements,fiber bundles,a spectrometer system,and a control and acquisition system.One route is used to obtain wide-spectral-range spectra,and the other route is used to acquire high-wavelengthresolution line shapes.The spectral resolution of the wide-range spectrometers is 0.8 nm with a coverage of 800 nm(@200-1000 nm).The spectral resolution of the high-resolution spectrometer is 0.01 nm with a coverage of 6 nm(@200-660 nm).The spatial resolution of each route of D-OES is about 4 cm with 11 channels.The temporal resolution is 16 ms at maximum in the single-channel mode.Wide-range spectra(containing Balmer series and a Fulcher band)and highly resolved Ha line shapes are obtained by D-OES in the hydrogen glow discharge in the lab.D-OES measurements are carried out in the high-density deuterium experiments of HL-2A.The electron density n_(e)and deuterium temperature T_(D) in the X-point multifaceted asymmetric radiation from the edge(MARFE)region are derived simultaneously by fitting the measured D_(a) shape.The density n_(e)is observed to increase from~8.7×10^(18)m^(-3)to~7.8×10^(19)m^(-3),and the temperature T_(D)drops from~14.4 eV to~2.3 eV after the onset of MARFE in the discharge#38260.

Visualizing the electronic structure of kagome magnet LuMn_(6)Sn_(6) by angle-resolved photoemission spectroscopy

Searching for the dispersionless flat band(FB)in quantum materials,especially in topological systems,becomes an interesting topic.The kagome lattice is an ideal platform for such exploration because the FB can be naturally induced by the underlying destructive interference.Nevertheless,the magnetic kagome system that hosts the FB close to the Fermi level(EF)is exceptionally rare.Here,we study the electronic structure of a kagome magnet LuMn_(6)Sn_(6) by combining angleresolved photoemission spectroscopy and density functional theory calculations.The observed Fermi-surface topology and overall band dispersions are similar to previous studies of the XMn_(6)Sn_(6)(X=Dy,Tb,Gd,Y)family of compounds.We clearly observe two kagome-derived FBs extending through the entire Brillouin zone,and one of them is located just below EF.The photon-energy-dependent measurements reveal that these FBs are nearly dispersionless along the kz direction as well,supporting the quasi-two-dimensional character of such FBs.Our results complement the XMn_(6)Sn_(6) family and demonstrate the robustness of the FB features across this family.

Core-level spectroscopy of the photodissociation process of BrCN molecule

Fewest-switches surfacing hopping(FSSH) simulations have been performed with the high-level multi-reference electronic structure method to explore the coupled electronic and nuclear dynamics upon photoexcitation of cyanogen bromide(BrCN). The potential energy surfaces(PES) of BrCN are charted as functions of the Jacobi coordinates(R, θ). An indepth examination of the FSSH trajectories reveals the temporal dynamics of the molecule and the population changes of the lowest twelve states during BrCN's photodissociation process, which presents a rich tapestry of dynamical information.Furthermore, the carbon K-edge x-ray absorption spectroscopy(XAS) is calculated with multi-reference inner-shell spectral simulations. The rotation of the CN fragment and the elongation of the C–Br bond are found to be the reason for the peak shifting in the XAS. Our findings offer a nuanced interpretation for inner-shell probe investigations of BrCN, setting the stage for a deeper understanding of the photodissociation process of cyanogen halides molecules.

Negligible normal fluid in superconducting state of heavily overdoped Bi_(2)Sr_(2)CaCu_(2)O_(8+δ) detected by ultra-low temperature angle-resolved photoemission spectroscopy

In high temperature cuprate superconductors,it was found that the superfluid density decreases with the increase of hole doping.One natural question is whether there exists normal fluid in the superconducting state in the overdoped region.In this paper,we have carried out high-resolution ultra-low temperature laser-based angle-resolved photoemission measurements on a heavily overdoped Bi2212 sample with a T_(c) of 48 K.We find that this heavily overdoped Bi2212 remains in the strong coupling regime with 2Δ_(0)/(k_(B)T_(c))=5.8.The single-particle scattering rate is very small along the nodal direction(~5 meV) and increases as the momentum moves from the nodal to the antinodal regions.A hard superconducting gap opening is observed near the antinodal region with the spectral weight at the Fermi level fully suppressed to zero.The normal fluid is found to be negligibly small in the superconducting state of this heavily overdoped Bi2212.These results provide key information to understand the high T_(c) mechanism in the cuprate superconductors.

Research on batch multielement rapid quantitative analysis based on the standard curve-assisted calibration-free laserinduced breakdown spectroscopy method

This study proposes a batch rapid quantitative analysis method for multiple elements by combining the advantages of standard curve(SC)and calibration-free laser-induced breakdown spectroscopy(CF-LIBS)technology to achieve synchronous,rapid,and accurate measurement of elements in a large number of samples,namely,SC-assisted CF-LIBS.Al alloy standard samples,divided into calibration and test samples,were applied to validate the proposed method.SC was built based on the characteristic line of Pb and Cr in the calibration sample,and the contents of Pb and Cr in the test sample were calculated with relative errors of 6%and 4%,respectively.SC built using Cr with multiple characteristic lines yielded better calculation results.The relative contents of ten elements in the test sample were calculated using CF-LIBS.Subsequently,the SC-assisted CF-LIBS was executed,with the majority of the calculation relative errors falling within the range of 2%-5%.Finally,the Al and Na contents of the Al alloy were predicted.The results demonstrate that it effectively enables the rapid and accurate quantitative analysis of multiple elements after a single-element SC analysis of the tested samples.Furthermore,this quantitative analysis method was successfully applied to soil and Astragalus samples,realizing an accurate calculation of the contents of multiple elements.Thus,it is important to advance the LIBS quantitative analysis and its related applications.

Estimating the yield stress of soft materials via laser-induced breakdown spectroscopy

Taking three typical soft samples prepared respectively by loose packings of 77-,95-,and 109-μm copper grains as examples,we perform an experiment to investigate the energy-dependent laser-induced breakdown spectroscopy(LIBS)of soft materials.We discovered a reversal phenomenon in the trend of energy dependence of plasma emission intensity:increasing initially and then decreasing separated by a well-defined critical energy.The trend reversal is attributed to the laser-induced recoil pressure at the critical energy just matching the sample's yield strength.As a result,a one-to-one correspondence can be well established between the samples'yield stress and the critical energy that is easily obtainable from LIBS measurements.This allows us to propose an innovative method for estimating the yield stress of soft materials via LIBS with attractive advantages including in-situ remote detection,real-time data collection,and minimal destructive to sample.