Risk factors for postoperative delirium in frail elderly patients undergoing on-pump cardiac surgery and development of a prediction model-a prospective observational study.

Background: To identify the risk factors for postoperative delirium (POD) after cardiac surgery in frail elderly patients and develop a receiver operating characteristic (ROC) prediction model to confirm the effectiveness. Methods: This was a prospective observational study, patients were assessed preoperatively according to the frailty index (FI) scale. Cerebral (SctO2) was assessed at different time points using near-infrared spectroscopy (NIRS). On the basis of the occurrence of POD within 7 days after surgery, patients were divided into POD and non-POD groups. Risk factors were analyzed using logistic regression analysis, while their predictive values were evaluated using the receiver operating characteristic curve analysis. Results: POD was significantly associated with frailty, lower preoperative MMSE scores, hyperlipidemia, diabetes, cerebrovascular disease, lower hemoglobin level, lower albumin level, longer operation time, longer CPB time, lower SctO2 at T5, and lower SctO2baseline (P < 0.05). SrtO2 and SmtO2 did not differ significantly between groups. FI, preoperative MMSE score, and operation time as independent risk factors (P < 0.05). Significant predictive value was demonstrated in all 3 variables (P < 0.001; respectively). Among them, high sensitivity and specificity were observed with the FI (cut-off value 0.27, sensitivity 75%, specificity 73.5%) and operation time (cut-off value 237.5, sensitivity 62.5%, specificity 78.6%). Conclusions: The FI, preoperative MMSE score, and operation time were independent risk factors for POD in elderly patients after cardiac surgery, with high predictive value observed with the FI and operation time. Cerebral oxygen saturation was associated with POD but was not an independent risk factor. Clinical Trial Registration: Chinese Clinical Trail Registry, No: chictr2200056038.

Prediction of protein content in paddy rice (Oryza sativa L.) combining near-infrared spectroscopy and deep-learning algorithm.

Rice is a staple crop in Asia, with more than 400 million tons consumed annually worldwide. The protein content of rice is a major determinant of its unique structural, physical, and nutritional properties. Chemical analysis, a traditional method for measuring rice's protein content, demands considerable manpower, time, and costs, including preprocessing such as removing the rice husk. Therefore, of the technology is needed to rapidly and nondestructively measure the protein content of paddy rice during harvest and storage stages. In this study, the nondestructive technique for predicting the protein content of rice with husks (paddy rice) was developed using near-infrared spectroscopy and deep learning techniques. The protein content prediction model based on partial least square regression, support vector regression, and deep neural network (DNN) were developed using the near-infrared spectrum in the range of 950 to 2200 nm. 1800 spectra of the paddy rice and 1200 spectra from the brown rice were obtained, and these were used for model development and performance evaluation of the developed model. Various spectral preprocessing techniques was applied. The DNN model showed the best results among three types of rice protein content prediction models. The optimal DNN model for paddy rice was the model with first-order derivative preprocessing and the accuracy was a coefficient of determination for prediction, Rp 2 = 0.972 and root mean squared error for prediction, RMSEP = 0.048%. The optimal DNN model for brown rice was the model applied first-order derivative preprocessing with Rp 2 = 0.987 and RMSEP = 0.033%. These results demonstrate the commercial feasibility of using near-infrared spectroscopy for the non-destructive prediction of protein content in both husked rice seeds and paddy rice.

Toward understanding ammonia capture in two amino-functionalized metal-organic frameworks using in-situ infrared spectroscopy and DFT calculation.

Two isostructural, three-dimensional, interpenetrated amino-functionalized Metal-Organic Frameworks (Co-2AIN-MOF and Cd-2AIN-MOF) based on 2-aminoisonicotinic acid (2AIN) were synthesized, structurally characterized and determined. Based on the PXRD analysis, the solvent exchange hardly changed their framework structure, and the samples fully activated by methanol can be achieved and examined by infrared spectroscopy. Due to the presence of the carbonyl group and free amino groups in the pore of the framework, the NH3 uptakes of Co-2AIN-MOF and Cd-2AIN-MOF are 11.70 and 13.81 mmol/g and at 1 bar, respectively. In-situ Infrared spectroscopy and DFT calculations revealed the different adsorption sites and processes between Co-2AIN-MOF and Cd-2AIN-MOF.

Disability Moderates Dual Task Walking Performance and Neural Efficiency in Older Adults With Multiple Sclerosis.

BACKGROUND: Mobility and cognitive impairment are prevalent and co-occurring in older adults with multiple sclerosis (OAMS), yet there is limited research concerning the role of disability status in the cognitive control of gait among OAMS. OBJECTIVE: We investigated the levels of prefrontal cortex (PFC) activation, using oxygenated hemoglobin (HbO2), during cognitively-demanding tasks in OAMS with lower and higher disability using functional near-infrared spectroscopy (fNIRS) to: (1) identify PFC activation differences in single task walk and cognitively-demanding tasks in OAMS with different levels of disability; and (2) evaluate if disability may moderate practice-related changes in neural efficiency in OAMS. METHODS: We gathered data from OAMS with lower (n = 51, age = 65 ± 4 years) or higher disability (n = 48, age = 65 ± 5 years), using a cutoff of 3 or more, in the Patient Determined Disease Steps, for higher disability, under 3 different conditions (single-task walk, Single-Task-Alpha, and Dual-Task-Walk [DTW]) administered over 3 counterbalanced, repeated trials. RESULTS: OAMS who had a lower disability level exhibited decreased PFC activation levels during Single-Task-Walk (STW) and larger increases in PFC activation levels, when going from STW to a cognitively-demanding task, such as a DTW, than those with higher disability. OAMS with a lower disability level exhibited greater declines in PFC activation levels with additional within session practice than those with a higher disability level. CONCLUSIONS: These findings suggest that disability moderates brain adaptability to cognitively-demanding tasks and demonstrate the potential for fNIRS-derived outcome measures to complement neurorehabilitation outcomes.

Dose Response of Transcranial Photobiomodulation on Cognitive Efficiency in Healthy Older Adults: A Task-Related Functional Near-Infrared Spectroscopy Study.

Background: Alzheimer's disease has become increasingly prevalent among the older population, leading to significant social and economic burdens. Transcranial photobiomodulation (tPBM) has shown promise as a cognitive intervention for enhancing cognitive efficiency in healthy older adults, and individuals with mild cognitive impairment and Alzheimer's disease. However, determining the optimal tPBM dosage is crucial for ensuring effective and efficient intervention. Objective: This study aimed to compare the effects of different dosages in a single tPBM session on cognitive efficiency in healthy older adults. Methods: In this randomized controlled trial, 88 healthy older participants were assigned to either a single dose (irradiance = 30 mW/cm2, fluence = 10.8 J/cm2; n = 44) or a double dose (irradiance = 30 mW/cm2, fluence = 21.6 J/cm2; n = 44) tPBM session. Cognitive efficiency was assessed using functional near-infrared spectroscopy during a visual working memory span task. Results: The single dose group exhibited significantly greater cognitive efficiency enhancement, indicated by a more pronounced reduction in oxygenated hemoglobin during a challenging task level (span level 9) (p = 0.021, d = 0.50), and better working memory task performance (p = 0.045, d = 0.31). Furthermore, participants with better visuospatial abilities demonstrated greater improvement after a single dose (r = -0.42, p = 0.004). In contrast, participants with varying cognitive function did not exhibit additional benefits from a double dose (r = -0.22-0.15, p = 0.16-0.95). Conclusions: These findings suggest that higher tPBM dosages may not necessarily result in superior cognitive improvement in older adults.

Paleoradiological and scientific investigations of the screaming woman mummy from the area beneath Senmut's (1479-1458 BC) Theban tomb (TT71).

Introduction: The Screaming Mummy of Cairo Egyptian-Museum Store, is an anonymous woman with a wide-open mouth coded as CIT8, discovered beneath Theban Tomb 71 (TT71) which is the burial site of Senmut's relatives, the architect of 18th-Dynasty Queen Hatschepsut (1479-1458 BC). The study aims to evaluate if combining computed tomography (CT) with scientific investigations and archeological data of the Screaming Mummy CIT8 will reveal information about its physical appearance, health, cause of death, and mummification. Methods: We CT-scanned the mummy and created reconstructed images. Scanning-Electron-Microscope (SEM), Fourier-Transform-Infrared-Spectroscopy (FTIR), and X-ray-Diffraction-Analysis (XRD) were used to investigate mummy skin, hair, and wig samples. We compared our findings to previous data. Results: Computed tomography estimated the age of death to be 48.1 years ±14.6 based on the pubic symphyseal surface. CT detected mild-to-moderate teeth attrition, and joints degeneration. The desiccated brain and viscera remained in situ. FTIR revealed the wig is formed of midrib date palm that shows in CT as spiral low density fibers. The wig fibers are partially coated with a thick substance that is inspected as black consolidation and identified as crystalline by XRD, comparable to material found in an ancient wig-making workshop. FTIR showed that the skin, hair, and wig samples were treated with imported juniper resin had anti-bacterial and insecticidal properties. The skin and wig samples contained frankincense, and the hair sample contained henna. Discussion: Combining the advantages of paleoradiology to the scientific investigations, provided enhanced comprehension of the mummy CIT8 and ancient Egyptian wig structure and material. CT scanning non-invasively showed the mummy's inner and exterior morphology, and estimated the age of death as 48 years. CT evaluated the mummification technique based on retained viscera and absence of embalming packs. The scientific tests revealed expensive imported embalming materials, contradicting the traditional belief that the non-removal of the viscera implied poor mummification, resulting in careless embalmers sealing the mouth. The widely opened mouth could be a result of facial expression of suffering before death, fixed by cadaveric spasm. The study also explores how rigor mortis, tissue decomposition, burial techniques, and postmortem alterations may contribute to a mummy's screaming appearance.

Do selectivity filter carbonyls in K+ channels flip away from the pore? Two-dimensional infrared spectroscopy study.

Molecular dynamics simulations revealed that the carbonyls of the Val residue in the conserved selectivity filter sequence TVGTG of potassium ion channels can flip away from the pore to form hydrogen bonds with the network of water molecules residing behind the selectivity filter. Such a configuration has been proposed to be relevant for C-type inactivation. Experimentally, X-ray crystallography of the KcsA channel admits the possibility that the Val carbonyls can flip, but it cannot decisively confirm the existence of such a configuration. In this study, we combined molecular dynamics simulations and line shape theory to design two-dimensional infrared spectroscopy experiments that can corroborate the existence of the selectivity filter configuration with flipped Val carbonyls. This ability to distinguish between flipped and unflipped carbonyls is based on the varying strength of the electric field inside and outside the pore, which is directly linked to carbonyl stretching frequencies that can be resolved using infrared spectroscopy.

Visual effects on tactile stimulation and its perception: A pilot study using near-infrared spectroscopy.

In rubber hand illusion, visual information affects tactile information, whereas in the mirror box illusion, visual information has the opposite effect. However, its underlying mechanisms are not fully understood. As one of the reasons, non-invasive neuroimaging techniques, such as functional magnetic resonance, positron emission tomography, and electroencephalography, often fail to detect complex and fragile responses in the sensory-motor cortex. Using near-infrared spectroscopy (NIRS), we examined neural activity during tactile tracing on a sine-shaped acrylic board to investigate the effects of (1) visual information and (2) the spatial frequency of the sine shape on brain activity. We used spatial frequencies of 2-3 and 20-30 Hz as low- and high-tactile stimuli, respectively. Two types of experiments, with and without an acrylic board, were conducted. Participants performed the tracing tasks with their index finger at 1 Hz of temporal frequency of a 200 mm length of the acrylic board as main tasks and only space moving without touching as a control task. We show effect of visual information on neural activation, including not only activation intensity but also activation patterns.•Testing of mutual effects of vision and haptics.•Testing of sensory-motor paradox using NIRS.•A high NIRS sensitivity to stimulus-induced hemodynamic change.

Early identification of the nosocomial spread of vancomycin-resistant Enterococcus faecium by Fourier-transform infrared spectroscopy and performance comparison with PFGE and WGS.

Early detection of disseminating vancomycin-resistant Enterococcus faecium (VREfm) in ICU wards is crucial for outbreak identification and the implementation of prompt infection control measures. Genotypic methods like pulsed-field gel electrophoresis (PFGE) and whole-genome sequencing (WGS) are costly and time-consuming, hindering rapid response due to batch dependency. Fourier-transform infrared spectroscopy (FT-IR) offers the potential for real-time outbreak detection and reliable strain typing. We utilized FT-IR to identify clonal VREfm dissemination and compared its performance to PFGE and WGS. Between February through October 2023, an unusually high number of VREfm were recovered at a tertiary hospital in Barcelona. Isolates were examined for antimicrobial susceptibility, carriage of vanA/vanB genes and clonality was also studied using FT-IR, PFGE, and WGS. Routine FT-IR inspections revealed recurring VREfm clustering during the outbreak's initial weeks. In total, 104 isolates were recovered from 75 patients and from multiple wards. However, only one isolate was recovered from an environmental sample, suggesting the absence of environmental reservoirs. An ST80 vancomycin-resistant (vanA) E. faecium strain was the main strain responsible for the outbreak, although a few additional VREfm strains were also identified, all belonging to CC17. PFGE and cgMLST (WGS) yielded identical clustering results to FT-IR, and WGS confirmed vanA/vanB gene carriage in all VREfm isolates. Infection control measures led to a rapid decline in VREfm isolates, with no isolates detected in November. FT-IR spectroscopy offers rapid turnaround times, sensitivity, and reproducibility, comparable to standard typing methods. It proved as an effective tool for monitoring VREfm dissemination and early outbreak detection.

An integrated and rapid evaluation of Curcumae Radix from different botanical origins based on chemical components, antiplatelet aggregation effect and Fourier transform near-infrared spectroscopy.

Curcumae Radix (CR) is a widely used traditional Chinese medicine with significant pharmaceutical importance, including enhancing blood circulation and addressing blood stasis. This study aims to establish an integrated and rapid quality assessment method for CR from various botanical origins, based on chemical components, antiplatelet aggregation effects, and Fourier transform near-infrared (FT-NIR) spectroscopy combined with multivariate algorithms. Firstly, ultra-performance liquid chromatography-photodiode array (UPLC-PDA) combined with chemometric analyses was used to examine variations in the chemical profiles of CR. Secondly, the activation effect on blood circulation of CR was assessed using an in vitro antiplatelet aggregation assay. The studies revealed significant variations in chemical profiles and antiplatelet aggregation effects among CR samples from different botanical origins, with constituents such as germacrone, ß-elemene, bisdemethoxycurcumin, demethoxycurcumin, and curcumin showing a positive correlation with antiplatelet aggregation biopotency. Thirdly, FT-NIR spectroscopy was integrated with various machine learning algorithms, including Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), Logistic Regression (LR), Support Vector Machine (SVM), and Subspace K-Nearest Neighbors (Subspace KNN), to classify CR samples from four distinct sources. The result showed that FT-NIR combined with KNN and SVM classification algorithms after SNV and MSC preprocessing successfully distinguished CR samples from four plant sources with an accuracy of 100%. Finally, Quantitative models for active constituents and antiplatelet aggregation bioactivity were developed by optimizing the partial least squares (PLS) model with interval combination optimization (ICO) and competitive adaptive reweighted sampling (CARS) techniques. The CARS-PLS model achieved the best predictive performance across all five components. The coefficient of determination (R2p) and root mean square error (RMSEP) in the independent test sets were 0.9708 and 0.2098, 0.8744 and 0.2065, 0.9511 and 0.0034, 0.9803 and 0.0066, 0.9567 and 0.0172 for germacrone, ß-elemene, bisdemethoxycurcumin, demethoxycurcumin and curcumin, respectively. The ICO-PLS model demonstrated superior predictive capabilities for antiplatelet aggregation biotency, achieving an R2p of 0.9010, and an RMSEP of 0.5370. This study provides a valuable reference for the quality evaluation of CR in a more rapid and comprehensive manner.

Evaluation of serum mid-infrared spectroscopy as new prognostic marker for first-line bevacizumab-based chemotherapy in metastatic colorectal cancer.

BACKGROUND AND AIMS: Bevacizumab-based chemotherapy is a recommended first-line treatment for metastatic colorectal cancer (mCRC). Robust biomarkers with clinical practice applicability have not been identified for patients with this treatment. We aimed to evaluate the prognostic yield of serum mid-infrared spectroscopy (MIRS) on patients receiving first-line bevacizumab-based chemotherapy for mCRC. METHODS: We conducted an ancillary analysis from a multicentre prospective study (NCT00489697). All baseline serums were screened by attenuated total reflection method. Principal component analysis and unsupervised k-mean partitioning methods were performed blinded to all patients' data. Endpoints were progression-free survival (PFS) and overall survival (OS). RESULTS: From the 108 included patients, MIRS discriminated two prognostic groups. First group patients had significantly lower body mass index (p = 0.026) and albumin levels (p < 0.001), and higher levels of angiogenic markers, lactate dehydrogenase and carcinoembryonic antigen (p < 0.001). In univariate analysis, their OS and PFS were shorter with respective medians: 17.6 vs 27.9 months (p = 0.02) and 8.7 vs 11.3 months (p = 0.03). In multivariate analysis, PFS was significantly shorter (HR = 1.74, p = 0.025) with a similar trend for OS (HR = 1.69, p = 0.061). CONCLUSION: By metabolomic fingerprinting, MIRS proves to be a promising prognostic tool for patients receiving first-line bevacizumab-based chemotherapy for mCRC.

Real-time motion artifact suppression using convolution neural networks with penalty in fNIRS.

Introduction: Removing motion artifacts (MAs) from functional near-infrared spectroscopy (fNIRS) signals is crucial in practical applications, but a standard procedure is not available yet. Artificial neural networks have found applications in diverse domains, such as voice and image processing, while their utility in signal processing remains limited. Method: In this work, we introduce an innovative neural network-based approach for online fNIRS signals processing, tailored to individual subjects and requiring minimal prior experimental data. Specifically, this approach employs one-dimensional convolutional neural networks with a penalty network (1DCNNwP), incorporating a moving window and an input data augmentation procedure. In the training process, the neural network is fed with simulated data derived from the balloon model for simulation validation and semi-simulated data for experimental validation, respectively. Results: Visual validation underscores 1DCNNwP's capacity to effectively suppress MAs. Quantitative analysis reveals a remarkable improvement in signal-to-noise ratio by over 11.08 dB, surpassing the existing methods, including the spline-interpolation, wavelet-based, temporal derivative distribution repair with a 1 s moving window, and spline Savitzky-Goaly methods. Contrast-to-noise ratio (CNR) analysis further demonstrated 1DCNNwP's ability to restore or enhance CNRs for motionless signals. In the experiments of eight subjects, our method significantly outperformed the other approaches (except offline TDDR, t < -3.82, p < 0.01). With an average signal processing time of 0.53 ms per sample, 1DCNNwP exhibited strong potential for real-time fNIRS data processing. Discussion: This novel univariate approach for fNIRS signal processing presents a promising avenue that requires minimal prior experimental data and adapts seamlessly to varying experimental paradigms.

Intermittent theta-burst stimulation in aphasia caused by right side cerebral lesions after stroke: A case report with 2-year follow-up.

Background and objectives: This case report investigates the application of intermittent Theta-Burst Stimulation (iTBS) in aphasia rehabilitation following a right hemisphere stroke. Case presentation: A 52-year-old Chinese male with Broca's aphasia post-stroke was treated with iTBS. His progress was evaluated using Functional Near-Infrared Spectroscopy (fNIRS) and behavioral assessments. Significant language function improvement was noted, with fNIRS showing increased activation in right hemisphere language-related cortical areas and altered functional connectivity patterns. Conclusion: The findings indicate that iTBS is effective in facilitating language recovery in right hemisphere stroke-induced aphasia, highlighting the importance of personalized neurorehabilitation strategies. Despite focusing on a single case, the study contributes to understanding neural plasticity mechanisms in right hemisphere stroke-induced aphasia.

Monitoring lung and cerebral oxygenation using near-infrared spectroscopy in preterm infants during kangaroo mother care.

Lung function has never been assessed during kangaroo mother care (KMC) in preterm infants. We measured lung (rSO2L) and cerebral (rSO2C) oxygenation by near-infrared spectroscopy (NIRS) in infants born at less than 32 weeks of gestation or weighing ≤ 1500 g during KMC. rSO2L, rSO2C, and pulmonary (FOEL) and cerebral (FOEC) tissue oxygen extraction fraction were measured in 20 preterm infants before, during, and after a 2-h period of KMC at a mean postnatal age of 36 ± 21 days of life. We found that rSO2L, rSO2C, FOEL, and FOEC did not change in our patients. After 120 min of KMC, rSO2L was lower (71.3 ± 1.4 vs. 76.7 ± 4.6%; P = 0.012) in infants with BPD (n = 6; 30%) than in infants without BPD (n = 14 = 60%), while FOEL was higher (0.26 ± 0.02 vs. 0.20 ± 0.05; P = 0.012).Conclusion: Cerebral and lung oxygenation did not change in preterm infants during KMC. A transient decrease in lung oxygenation was offset by the increase in oxygen extraction, but these changes were clinically insignificant. These results confirm the safety of KMC in preterm infants who are in stable clinical conditions. What is Known • Kangaroo mother care (KMC) is widely used to improve the care of preterm newborns since it improves their outcome. • KMC is safe as patients' vital parameters, are not negatively affected, but lung function has never been directly assessed. What is New • Cerebral and lung oxygenation measured by near-infrared spectroscopy did not change during KMC. • A transient decrease in lung oxygenation compensated for by the increase in oxygen extraction occurred only in infants with BPD, but these changes were clinically insignificant.

Higher or lower? Interpersonal behavioral and neural synchronization of movement imitation in autistic children.

How well autistic children can imitate movements and how their brain activity synchronizes with the person they are imitating have been understudied. The current study adopted functional near-infrared spectroscopy (fNIRS) hyperscanning and employed a task involving real interactions involving meaningful and meaningless movement imitation to explore the fundamental nature of imitation as a dynamic and interactive process. Experiment 1 explored meaningful and meaningless gesture imitation. The results revealed that autistic children exhibited lower imitation accuracy and behavioral synchrony than non-autistic children when imitating both meaningful and meaningless gestures. Specifically, compared to non-autistic children, autistic children displayed significantly higher interpersonal neural synchronization (INS) in the right inferior parietal lobule (r-IPL) (channel 12) when imitating meaningful gestures but lower INS when imitating meaningless gestures. Experiment 2 further investigated the imitation of four types of meaningless movements (orofacial movements, transitive movements, limb movements, and gestures). The results revealed that across all four movement types, autistic children exhibited significantly lower imitation accuracy, behavioral synchrony, and INS in the r-IPL (channel 12) than non-autistic children. This study is the first to identify INS as a biomarker of movement imitation difficulties in autistic individuals. Furthermore, an intra- and interindividual imitation mechanism model was proposed to explain the underlying causes of movement imitation difficulties in autistic individuals.

Key charged residues influence the amyloidogenic propensity of the helix-1 region of serum amyloid A.

Increased plasma levels of serum amyloid A (SAA), an acute-phase protein that is secreted in response to inflammation, may lead to the accumulation of amyloid in various organs thereby obstructing their functions. Severe cases can lead to a systemic disorder called AA amyloidosis. Previous studies suggest that the N-terminal helix is the most amyloidogenic region of SAA. Moreover, computational studies implicated a significant role for Arg-1 and the residue-specific interactions formed during the fibrillization process. With a focus on the N-terminal region of helix-1, SAA1-13, mutational analysis was employed to interrogate the roles of the amino acid residues, Arg-1, Ser-5, Glu-9, and Asp-12. The truncated SAA1-13 fragment was systematically modified by substituting the key residues with alanine or uncharged but structurally similar amino acids. We monitored the changes in the amyloidogenic propensities, associated conformational markers, and morphology of the amyloids resulting from the mutation of SAA1-13. Mutating out Arg-1 resulted in much reduced aggregation propensity and a lack of detectable ß-structures alluding to the importance of salt-bridge interactions involving Arg-1. Our data revealed that by systematically mutating the key amino acid residues, we can modulate the amyloidogenic propensity and alter the time-dependent conformational variation of the peptide. When the behaviors of each mutant peptide were analyzed, they provided evidence consistent with the aggregation pathway predicted by MD simulation studies. Here, we detail the important temporal molecular interactions formed by Arg-1 with Ser-5, Glu-9, and Asp-12 and discuss its mechanistic implications on the self-assembly of the helix-1 region of SAA.

Rapid measurement of soluble xylo-oligomers using near-infrared spectroscopy (NIRS) and multivariate statistics: calibration model development and practical approaches to model optimization.

BACKGROUND: Rapid monitoring of biomass conversion processes using techniques such as near-infrared (NIR) spectroscopy can be substantially quicker and less labor-, resource-, and energy-intensive than conventional measurement techniques such as gas or liquid chromatography (GC or LC) due to the lack of solvents and preparation methods, as well as removing the need to transfer samples to an external lab for analytical evaluation. The purpose of this study was to determine the feasibility of rapid monitoring of a biomass conversion process using NIR spectroscopy combined with multivariate statistical modeling, and to examine the impact of (1) subsetting the samples in the original dataset by process location and (2) reducing the spectral range used in the calibration model on model performance. RESULTS: We develop multivariate calibration models for the concentrations of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids at multiple points in a biomass conversion process which produces and then purifies XOS compounds from sugar cane bagasse. A single model using samples from multiple locations in the process stream showed acceptable performance as measured by standard statistical measures. However, compared to the single model, we show that separate models built by segregating the calibration samples according to process location show improved performance. We also show that combining an understanding of the sample spectra with simple multivariate analysis tools can result in a calibration model with a substantially smaller spectral range that provides essentially equal performance to the full-range model. CONCLUSIONS: We demonstrate that real-time monitoring of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids concentration at multiple points in a process stream using NIR spectroscopy coupled with multivariate statistics is feasible. Segregation of sample populations by process location improves model performance. Models using a reduced spectral range containing the most relevant spectral signatures show very similar performance to the full-range model, reinforcing the importance of performing robust exploratory data analysis before beginning multivariate modeling.

Development and evaluation of portable NIR technology for the identification and quantification of Australian illicit drugs.

The efficient and accurate analysis of illicit drugs remains a constant challenge in Australia given the high volume of drugs trafficked into and around the country. Portable drug testing technologies facilitate the decentralisation of the forensic laboratory and enable analytical data to be acted upon more efficiently. Near-infrared (NIR) spectroscopy combined with chemometric modelling (machine learning algorithms) has been highlighted as a portable drug testing technology that is rapid and accurate. However, its effectiveness depends upon a database of chemically relevant specimens that are representative of the market. There are chemical differences between drugs in different countries that need to be incorporated into the database to ensure accurate chemometric model prediction. This study aimed to optimise and assess the implementation of NIR spectroscopy combined with machine learning models to rapidly identify and quantify illicit drugs within an Australian context. The MicroNIR (Viavi Solutions Inc.) was used to scan 608 illicit drug specimens seized by the Australian Federal Police comprising of mainly crystalline methamphetamine hydrochloride (HCl), cocaine HCl, and heroin HCl. A number of other traditional drugs, new psychoactive substances and adulterants were also scanned to assess selectivity. The 3673 NIR scans were compared to the identity and quantification values obtained from a reference laboratory in order to assess the proficiency of the chemometric models. The identification of crystalline methamphetamine HCl, cocaine HCl, and heroin HCl specimens was highly accurate, with accuracy rates of 98.4 %, 97.5 %, and 99.2 %, respectively. The sensitivity of these three drugs was more varied with heroin HCl identification being the least sensitive (methamphetamine = 96.6 %, cocaine = 93.5 % and heroin = 91.3 %). For these three drugs, the NIR technology provided accurate quantification, with 99 % of values falling within the relative uncertainty of ±15 %. The MicroNIR with NIRLAB infrastructure has demonstrated to provide accurate results in real-time with clear operational applications. There is potential to improve informed decision-making, safety, efficiency and effectiveness of frontline and proactive policing within Australia.

Characteristic brain functional activation and connectivity during actual and imaginary right-handed grasp.

We used 34-channel functional near infrared spectroscopy to investigate and compare changes in oxyhemoglobin concentration of brain networks in bilateral prefrontal cortex, sensorimotor cortex, and occipital lobe of 22 right-handed healthy adults during executive right-handed grasp (motor execution task) and imagined right-handed grasp (motor imagery task). Then calculated lateral index and functional contribution degree, and measured functional connectivity strength between the regions of interest. In the motor executive block task, there was a significant increase in oxyhemoglobin concentration in regions of interest except for right occipital lobe (P<0.05), while in the motor imagery task, all left regions of interest's oxyhemoglobin concentration increased significantly (P<0.05). Except the prefrontal cortex in motor executive task, the left side of the brain was dominant. Left sensorimotor cortex played a major role in these two tasks, followed by right sensorimotor cortex. Among all functional contribution degree, left sensorimotor cortex, right sensorimotor cortex and left occipital lobe ranked top three during these tasks. In continuous acquisition tasks, functional connectivity on during motor imagery task was stronger than that during motor executive task. Brain functions during two tasks of right-hand grasping movement were partially consistent. However, the excitability of brain during motor imagery was lower, and it was more dependent on the participation of left prefrontal cortex, and its synchronous activity of the whole brain was stronger. The trend of functional contribution degree was basically consistent with oxyhemoglobin concentration and lateral index, and can be used as a novel index to evaluate brain function. [ChiCTR2200063792 (2022-09-16)].