Rapid detection of colored and colorless macro- and micro-plastics in complex environment via near-infrared spectroscopy and machine learning.

To better understand the migration behavior of plastic fragments in the environment, development of rapid non-destructive methods for in-situ identification and characterization of plastic fragments is necessary. However, most of the studies had focused only on colored plastic fragments, ignoring colorless plastic fragments and the effects of different environmental media (backgrounds), thus underestimating their abundance. To address this issue, the present study used near-infrared spectroscopy to compare the identification of colored and colorless plastic fragments based on partial least squares-discriminant analysis (PLS-DA), extreme gradient boost, support vector machine and random forest classifier. The effects of polymer color, type, thickness, and background on the plastic fragments classification were evaluated. PLS-DA presented the best and most stable outcome, with higher robustness and lower misclassification rate. All models frequently misinterpreted colorless plastic fragments and its background when the fragment thickness was less than 0.1mm. A two-stage modeling method, which first distinguishes the plastic types and then identifies colorless plastic fragments that had been misclassified as background, was proposed. The method presented an accuracy higher than 99% in different backgrounds. In summary, this study developed a novel method for rapid and synchronous identification of colored and colorless plastic fragments under complex environmental backgrounds.

Selective CO2 Photoreduction into CH4 Triggered by the Synergy between Oxygen Vacancy and Ru Substitution under Near-Infrared Light Irradiation.

Near-infrared (NIR) light powdered CO2 photoreduction reaction is generally restricted to the separation efficiency of photogenerated carriers and the supply of active hydrogen (*H). Herein, the study reports a retrofitting hydrogenated MoO3-x (H-MoO3-x) nanosheet photocatalysts with Ru single atom substitution (Ru@H-MoO3-x) fabricated by one-step solvothermal method. Experiments together with theoretical calculations demonstrate that the synergistic effect of Ru substitution and oxygen vacancy can not only inhibit the recombination of photogenerated carriers, but also facilitate the CO2 adsorption/activation as well as the supply of *H. Compared with H-MoO3-x, the Ru@H-MoO3-x exhibit more favorable formation of *CHO in the process of *CO conversion due to the fast *H generation on electron-rich Ru sites and transfer to *CO intermediates, leading to the preferential photoreduction of CO2 to CH4 with high selectivity. The optimized Ru@H-MoO3-x exhibits a superior CO2 photoreduction activity with CH4 evolution rate of 111.6 and 39.0 µmol gcatalyst -1 under full spectrum and NIR light irradiation, respectively, which is 8.8 and 15.0 times much higher than that of H-MoO3-x. This work provides an in-depth understanding at the atomic level on the design of NIR responsive photocatalyst for achieving the goal of carbon neutrality.

Clothing color effect as a target of the smallest scale climate change adaptation.

The purpose of this study is to understand a physical mechanism to determine the surface temperature of clothes in calm and fine conditions of outdoors. We observed surface temperatures of polo shirts of the same material and design but different colors. The shirts were placed in unshaded and well-ventilated outdoor, open spaces on sunny summer days. The maximum difference between dark green or black and white was more than 15 °C during calm, fine weather and was greatest when the solar radiation was strong. If the transmission of solar radiation energy through a shirt is ignored to calculate the absorption by the shirt, the difference in solar radiation absorption due to different colors is as much as 24% in the maximum, and if considered, we concluded that an absorption difference of 34% led to a temperature difference of 15℃. When we compared the brightness of the colors, we found that the albedo of both the visible and NIR bands explained why the red and green colors were so different with respect to the surface temperatures we observed. The reflection in the NIR bands was also an important determinant of the surface temperature. An additional experiment using masks showed that the temperature difference between white and black was almost eliminated at a wind speed of ~ 3 m/s. The color of clothing is therefore a target for small-scale adaptation to climate change.

Predicting in vivo therapeutic efficacy of CelTrac1000-labeled hair follicle epidermal neural crest stem cells in models of repairing rat facial nerve defects via second near-infrared fluorescence imaging.

AIMS: To detect the therapeutic efficacy of CelTrac1000-labeled hair follicle epidermal neural crest stem cells (EPI-NCSCs) on repairing facial nerve defects by second near-infrared (NIR-II) fluorescence imaging. MATERIALS AND METHODS: Firstly, CelTrac1000-labeled EPI-NCSCs were microinjected into the acellular nerve allografts (ANAs) to bridge a 10-mm-long gap in the buccal branch of facial nerve in adult rats. Then, Celtrac1000-labeled EPI-NCSCs were detected by NIR-II fluorescence imaging system to visualize the behavior of the transplanted cells in vivo. Additionally, the effect of the transplanted EPI-NCSCs on repairing facial nerve defect was examined. KEY FINDINGS: Through 14 weeks of dynamic observation, the transplanted EPI-NCSCs survived in the ANAs in vivo after surgery. Meanwhile, the region of the NIR-II fluorescence signals was gradually limited to be consistent with the direction of the regenerative nerve segment. Furthermore, the results of functional and morphological analysis showed that the transplanted EPI-NCSCs could promote the recovery of facial paralysis and neural regeneration after injury. SIGNIFICANCE: Our research provides a novel way to track the transplanted cells in preclinical studies of cell therapy for facial paralysis, and demonstrates the therapeutic potential of EPI-NCSCs combined with ANAs in bridging rat facial nerve defects.

A lysosomal-targeted and viscosity-ultrasensitive near-infrared fluorescent probe for sensing viscosity in cells and a diabetic mice model.

Diabetes, as a metabolic disorder, has been implicated in organ dysfunction, often correlated with aberrant changes in viscosity. Lysosomal viscosity serves as an indicator of the lysosome's condition and activity, as it always varies synchronously with the change of lysosome's positioning, structure, and internal constituents. Diabetes, a condition within the metabolic disease category, has the potential to disrupt organ function due to irregular changes in viscosity. Therefore, early and precise diagnosis of diabetes is crucial for the prevention and management of diabetic conditions. Understanding the correlation between viscosity variations and lysosomal changes in vivo is vitally important for researching associated diseases. In this study, we developed Lyso-V, a near-infrared (NIR) fluorescent probe targeting lysosomes, with ultrasensitivity to viscosity changes. This probe, designed with a donor-π-bridge-acceptor (D-π-A) structure, exhibits a significant increase in NIR fluorescence intensity (approximately 690 times) when responding to viscosity, due to a twisted intramolecular charge transfer (TICT) mechanism. Furthermore, the probe designed specifically for lysosomes, enables the detection of changes in lysosomal viscosity as well as autophagy processes. Notably, through the application of this probe, we have detected an increased viscosity within the pathological model of the diabetic mouse. Moreover, Lyso-V was employed to measure the viscosity in diabetic mice. Owing to the multifaceted nature of the Lyso-V probe, it is anticipated to act as a practical and potent resource for deepening our understanding of the pathophysiological aspects of diabetes and aiding in its early detection.

A near-infrared fluorescent probe for differentiating cancer cells from normal cells and early diagnosis of liver cirrhosis.

BACKGROUND: Cirrhosis represents the terminal stage of liver disease progression and timely intervention in a diseased liver can enhance the likelihood of recovery. Viscosity, a crucial parameter of the cellular microenvironment, is intricately linked to the advancement of cirrhosis. However, viscosity monitoring still faces significant challenges in achieving non-invasive and rapid early diagnosis of cirrhosis. Near-infrared (NIR) fluorescence imaging has the advantages of high sensitivity, non-destructive detection, and ignoring background fluorescence interference, plays an important role in diagnosing and treating various biological diseases. Hence, monitoring cellular viscosity changes with NIR fluorescence probe holds great significance in the early diagnosis of cirrhosis. RESULTS: In this study, the NIR fluorescence probe based on the intramolecular charge transfer (TICT) mechanism was developed for imaging applications in mouse model of liver cirrhosis. A molecular rotor-type viscosity-responsive probe was synthesized by linking dioxanthracene groups via carbon-carbon double bonds. The probe demonstrated remarkable sensitivity, high selectivity and photostability, with its responsiveness to viscosity largely unaffected by factors such as polarity, pH, and interfering ions. The probe could effectively detect various drug-induced changes in cellular viscosity, enabling the differentiation between normal cells and cancerous cells. Furthermore, the enhanced tissue penetration capabilities of probe facilitated its successful application in mouse model of liver cirrhosis, allowing for the assessment of liver disease severity based on fluorescence intensity and providing a powerful tool for early diagnosis of cirrhosis. SIGNIFICANCE: A NIR viscosity-sensitive fluorescent probe was specifically designed to effectively monitor alterations in cellular and organ viscosity, which could advance the understanding of the biological characteristics of cancer and provide theoretical support for the early diagnosis of cirrhosis. Overall, this probe held immense potential in monitoring viscosity-related conditions, expanding the range of biomedical tools available.

Application value of indocyanine green fluorescence imaging in guiding sentinel lymph node biopsy diagnosis of gastric cancer: Meta-analysis.

BACKGROUND: Gastric cancer is a common malignant tumor of the digestive system worldwide, and its early diagnosis is crucial to improve the survival rate of patients. Indocyanine green fluorescence imaging (ICG-FI), as a new imaging technology, has shown potential application prospects in oncology surgery. The meta-analysis to study the application value of ICG-FI in the diagnosis of gastric cancer sentinel lymph node biopsy is helpful to comprehensively evaluate the clinical effect of this technology and provide more reliable guidance for clinical practice. AIM: To assess the diagnostic efficacy of optical imaging in conjunction with indocyanine green (ICG)-guided sentinel lymph node (SLN) biopsy for gastric cancer. METHODS: Electronic databases such as PubMed, Embase, Medline, Web of Science, and the Cochrane Library were searched for prospective diagnostic tests of optical imaging combined with ICG-guided SLN biopsy. Stata 12.0 software was used for analysis by combining the "bivariable mixed effect model" with the "midas" command. The true positive value, false positive value, false negative value, true negative value, and other information from the included literature were extracted. A literature quality assessment map was drawn to describe the overall quality of the included literature. A forest plot was used for heterogeneity analysis, and P < 0.01 was considered to indicate statistical significance. A funnel plot was used to assess publication bias, and P < 0.1 was considered to indicate statistical significance. The summary receiver operating characteristic (SROC) curve was used to calculate the area under the curve (AUC) to determine the diagnostic accuracy. If there was interstudy heterogeneity (I 2 > 50%), meta-regression analysis and subgroup analysis were performed. RESULTS: Optical imaging involves two methods: Near-infrared (NIR) imaging and fluorescence imaging. A combination of optical imaging and ICG-guided SLN biopsy was useful for diagnosis. The positive likelihood ratio was 30.39 (95%CI: 0.92-1.00), the sensitivity was 0.95 (95%CI: 0.82-0.99), and the specificity was 1.00 (95%CI: 0.92-1.00). The negative likelihood ratio was 0.05 (95%CI: 0.01-0.20), the diagnostic odds ratio was 225.54 (95%CI: 88.81-572.77), and the SROC AUC was 1.00 (95%CI: The crucial values were sensitivity = 0.95 (95%CI: 0.82-0.99) and specificity = 1.00 (95%CI: 0.92-1.00). The Deeks method revealed that the "diagnostic odds ratio" funnel plot of SLN biopsy for gastric cancer was significantly asymmetrical (P = 0.01), suggesting significant publication bias. Further meta-subgroup analysis revealed that, compared with fluorescence imaging, NIR imaging had greater sensitivity (0.98 vs 0.73). Compared with optical imaging immediately after ICG injection, optical imaging after 20 minutes obtained greater sensitivity (0.98 vs 0.70). Compared with that of patients with an average SLN detection number < 4, the sensitivity of patients with a SLN detection number ≥ 4 was greater (0.96 vs 0.68). Compared with hematoxylin-eosin (HE) staining, immunohistochemical (+ HE) staining showed greater sensitivity (0.99 vs 0.84). Compared with subserous injection of ICG, submucosal injection achieved greater sensitivity (0.98 vs 0.40). Compared with 5 g/L ICG, 0.5 and 0.05 g/L ICG had greater sensitivity (0.98 vs 0.83), and cT1 stage had greater sensitivity (0.96 vs 0.72) than cT2 to cT3 clinical stage. Compared with that of patients ≤ 26, the sensitivity of patients > 26 was greater (0.96 vs 0.65). Compared with the literature published before 2010, the sensitivity of the literature published after 2010 was greater (0.97 vs 0.81), and the differences were statistically significant (all P < 0.05). CONCLUSION: For the diagnosis of stomach cancer, optical imaging in conjunction with ICG-guided SLN biopsy is a therapeutically viable approach, especially for early gastric cancer. The concentration of ICG used in the SLN biopsy of gastric cancer may be too high. Moreover, NIR imaging is better than fluorescence imaging and may obtain higher sensitivity.

Integrating fNIRS and machine learning: shedding light on Parkinson's disease detection.

The purpose of this research is to introduce an approach to assist the diagnosis of Parkinson's disease (PD) by classifying functional near-infrared spectroscopy (fNIRS) studies as PD positive or negative. fNIRS is a non-invasive optical signal modality that conveys the brain's hemodynamic response, specifically changes in blood oxygenation in the cerebral cortex; and its potential as a tool to assist PD detection deserves to be explored since it is non-invasive and cost-effective as opposed to other neuroimaging modalities. Besides the integration of fNIRS and machine learning, a contribution of this work is that various approaches were implemented and tested to find the implementation that achieves the highest performance. All the implementations used a logistic regression model for classification. A set of 792 temporal and spectral features were extracted from each participant's fNIRS study. In the two best performing implementations, an ensemble of feature-ranking techniques was used to select a reduced feature subset, which was subsequently reduced with a genetic algorithm. Achieving optimal detection performance, our approach reached 100 % accuracy, precision, and recall, with an F1 score and area under the curve (AUC) of 1, using 14 features. This significantly advances PD diagnosis, highlighting the potential of integrating fNIRS and machine learning for non-invasive PD detection.

Effect of Inspiratory Muscle-Loaded Exercise Training on Ventilatory Response and Intercostal Muscle Deoxygenation During Incremental Cycling Exercise.

Purpose: This study evaluated the effects of exercise training (ET) and inspiratory muscle-loaded exercise training (IMLET) on ventilatory response and intercostal muscle deoxygenation levels during incremental cycling exercise. Methods: Twenty-one male participants were randomly divided into IMLET (n = 10) or ET (n = 11) groups. All participants underwent a 4-week cycling exercise training at 60% peak oxygen uptake. IMLET loaded 50% of maximal inspiratory pressure (PImax). Respiratory muscle strength test, respiratory muscle endurance test (RMET), resting hypoxic ventilatory responsiveness (HVR) test, and incremental cycling test were performed pre- and post-training. Results: The extent of improvement in the PImax was significantly greater in the IMLET group (24%) than in the ET group (8%) (p = .018), and an extended RMET time was observed in the IMLET group (p < .001). Minute ventilation (V˙E) during exercise was unchanged in both groups before and after training, but tidal volume during exercise increased in the IMLET group. The increase in the exercise intensity threshold for muscle deoxygenation was similar in both groups (p < .001). HVR remained unchanged in both groups post-training. The exercise duration for the incremental exercise until reaching fatigue increased by 7.9% after ET and 6.9% after IMLET (p < .001). Conclusion: The 4-week IMLET improved respiratory muscle strength and endurance but did not alter HVR. Respiratory muscle deoxygenation was alleviated by exercise training, with a limited impact of inspiratory load training.

Broadband sensitized near-infrared emission in Eu2+-Nd3+ co-doped BaAl2O4 as a potential spectral modulator for silicon solar cells.

The near-infrared (NIR) down-conversion process for broadband sensitization has been studied in Eu2+-Nd3+ co-doped BaAl2O4. This material has a broad absorption band of 200-480 nm and can convert photons in the visible region into NIR photons. The NIR emission at 1064 nm, attributed to the Nd3+:4F3/2 → 4I11/2 transition, matches the bandgap of Si, allowing Si solar cells to utilize the solar spectrum better. The energy transfer (ET) process between Eu2+ and Nd3+ was demonstrated using photoluminescence spectra and luminescence decay curves, and Eu2+ may transfer energy to Nd3+ through the cooperative energy transfer (CET) to achieve the down-conversion process. The energy transfer efficiency (ETE) and theoretical quantum efficiency (QE) were 68.61% and 156.34%, respectively, when 4 mol% Nd3+ was introduced. The results indicate that BaAl2O4:Eu2+-Nd3+ can serve as a potential modulator of the solar spectrum and is expected to be applied to Si solar cells.

Near-Infrared Emissive Super Penetrating Conjugated Polymer Dots for Intratumoral Imaging in 3D Tumor Spheroid Models.

This study describes the formation of single-chain polymer dots (Pdots) via ultrasonic emulsification of nonionic donor-acceptor-donor type (D-A-D) alkoxy thiophene-benzobisthiadiazole-based conjugated polymers (Poly BT) with amphiphilic cetyltrimethylammonium bromide (CTAB). The methodology yields Pdots with a high cationic surface charge (+56.5 mV ± 9.5) and average hydrodynamic radius of 12 nm. Optical characterization reveals that these Pdots emit near-infrared (NIR) light at a maximum wavelength of 860 nm owing to their conjugated polymer backbone consisting of D-A-D monomers. Both colloidal and optical properties of these Pdots make them promising fluorescence emissive probes for bioimaging applications. The significant advantage of positively charged Pdots is demonstrated in diffusion-limited mediums such as tissues, utilizing human epithelial breast adenocarcinoma, ATCC HTB-22 (MCF-7), human bone marrow neuroblastoma, ATCC CRL-2266 (SH-SY5Y), and rat adrenal gland pheochromocytoma, CRL-1721 (PC-12) tumor spheroid models. Fluorescence microscopy analysis of tumor spheroids from MCF-7, SH-SY5Y, and PC-12 cell lines reveals the intensity profile of Pdots, confirming extensive penetration into the central regions of the models. Moreover, a comparison with mitochondria staining dye reveals an overlap between the regions stained by Pdots and the dye in all three tumor spheroid models. These results suggest that single-chain D-A-D type Pdots, cationized via CTAB, exhibit long-range mean free path of penetration (≈1 µm) in dense mediums and tumors.

Effect of transbronchial or intravenous administration of indocyanine green on resection margins during near-infrared-guided segmentectomy: a review.

For early-stage non-small cell lung cancer, surgical resection remains the best treatment option. Currently, sublobar resection, including segmentectomy, is recommended in these cases, as it provides a better quality of life with the same oncological outcomes; however, is requires adequate resection margins. Accurate preoperative planning and proper identification of the intersegmental planes during thoracic surgery are crucial for ensuring precise surgical management and adequate resection margins. Three dimensional computed tomography reconstruction and near-infrared-guided intersegmental plane identification can greatly facilitate the surgical procedures. Three-dimensional computed tomography reconstruction can simulate both the resection and resection margins. Indocyanine green is one of the most frequently used and affordable fluorophores. There are two ways to identify the intersegmental planes using indocyanine green: intravenous and transbronchial administration. Intravenous application is simple; however, its effectiveness may be affected by underlying lung disease, and it requires the isolation of segmental structures before administration. Transbronchial use requires appropriate bronchoscopic skills and preoperative planning; however, it also allows for delineation deep in the parenchyma and can be used for complex segmentectomies. Both methods can be used to ensure adequate resection margins and, therefore, achieve the correct oncological radicality of the surgical procedure. Here, we summarise these applications and provide an overview of their different possibilities.

Application of adaptive chaotic dung beetle optimization algorithm to near-infrared spectral model transfer.

A new transfer approach was proposed to share calibration models of the hexamethylenetetramine-acetic acid solution for studying hexamethylenetetramine concentration values across different near-infrared (NIR) spectrometers. This approach combines Savitzky-Golay first derivative (S_G_1) and orthogonal signal correction (OSC) preprocessing, along with feature variable optimization using an adaptive chaotic dung beetle optimization (ACDBO) algorithm. The ACDBO algorithm employs tent chaotic mapping and a nonlinear decreasing strategy, enhancing the balance between global and local search capabilities and increasing population diversity to address limitations observed in traditional dung beetle optimization (DBO). Validated using the CEC-2017 benchmark functions, the ACDBO algorithm demonstrated superior convergence speed, accuracy, and stability. In the context of a partial least squares (PLS) regression model for transferring hexamethylenetetramine-acetic acid solutions using NIR spectroscopy, the ACDBO algorithm excelled over alternative methods such as uninformative variable elimination, competitive adaptive reweighted sampling, cuckoo search, grey wolf optimizer, differential evolution, and DBO in efficiency, accuracy of feature variable selection, and enhancement of model predictive performance. The algorithm attained outstanding metrics, including a determination coefficient for the calibration set (Rc2) of 0.99999, a root mean square error for the calibration set (RMSEC) of 0.00195%, a determination coefficient for the validation set (Rv2) of 0.99643, a root mean squared error for the validation set (RMSEV) of 0.03818%, residual predictive deviation (RPD) of 16.72574. Compared to existing OSC, slope and bias correction (S/B), direct standardization (DS), and piecewise direct standardization (PDS) model transfer methods, the novel strategy enhances the accuracy and robustness of model predictions. It eliminates irrelevant background information about the hexamethylenetetramine concentration, thereby minimizing the spectral discrepancies across different instruments. As a result, this approach yields a determination coefficient for the prediction set (Rp2) of 0.96228, a root mean squared error for the prediction set (RMSEP) of 0.12462%, and a relative error rate (RER) of 17.62331, respectively. These figures closely follow those obtained using DS and PDS, which recorded Rp2, RMSEP, and RER values of 0.97505, 0.10135%, 21.67030, and 0.98311, 0.08339%, 26.33552, respectively. Unlike conventional methods such as OSC, S/B, DS, and PDS, this novel approach does not require the analysis of identical samples across different instruments. This characteristic significantly broadens its applicability for model transfer, which is particularly beneficial for transferring specific measurement samples.

Synthesis of non-modified near-infrared carbon dots for hypochlorite detection and cell membrane imaging.

Devising carbon dots with long wavelength emission (red light or near infrared), high selectivity and good bio-compatibility is critical in fluorescence detection and imaging, but achieving this goal remains a great challenge. Herein, near-infrared emissive carbon dots (NIR-CDs) with obvious emission characteristic of 653 nm were synthesized through hydrothermally treatment of toluidine bule and gallic acid. Noticeably, the NIR-CDs exhibited excellent selectivity and sensitivity to hypochlorite (ClO-), and the limit of detection is as low as 42.7 nM. The selective recognition reaction between ClO- and the surface functional groups of NIR-CDs inhibits the fluorescence from NIR-CDs. The quenching mechanism was confirmed by fluorescence lifetime decays, FT-IR spectroscopy and UV-vis absorption spectra. More remarkably, the NIR-CDs have rich hydrophilic groups showed lower cytotoxicity, excellent bio-compatibility and specific cell membrane localization ability. The established spectrofluorometric method based on NIR-CDs has been used to determination of ClO- level in tap water sample, the recoveries were 97.7 %-103.3 %. In addition, the NIR-CDs also has been successfully applied for the imaging of cell membrane. The study provides a novel idea for developing NIR ClO- probe as well as cell membrane localization probe based on CDs, which present bright prospects in real water samples monitoring and cell membrane imaging.

Convolutional neural networks can detect orthostatic hypotension in Parkinson's disease using resting-state functional near-infrared spectroscopy data.

Neurological disorders such as Parkinson's disease (PD) often adversely affect the vascular system, leading to alterations in blood flow patterns. Functional near-infrared spectroscopy (fNIRS) is used to monitor hemodynamic changes via signal measurement. This study investigated the potential of using resting-state fNIRS data through a convolutional neural network (CNN) to evaluate PD with orthostatic hypotension. The CNN demonstrated significant efficacy in analyzing fNIRS data, and it outperformed the other machine learning methods. The results indicate that judicious input data selection can enhance accuracy by over 85%, while including the correlation matrix as an input further improves the accuracy to more than 90%. This study underscores the promising role of CNN-based fNIRS data analysis in the diagnosis and management of the PD. This approach enhances diagnostic accuracy, particularly in resting-state conditions, and can reduce the discomfort and risks associated with current diagnostic methods, such as the head-up tilt test.

Effect of near-infrared spectroscopy on postoperative delirium in cardiac surgery with cardiopulmonary bypass: a systematic review and meta-analysis.

Background: Postoperative delirium (POD) is a common anesthetic side effect in cardiac surgery. However, the role of oxygen saturation monitoring in reducing postoperative delirium has been controversial. Therefore, this meta-analysis aimed to analyze whether NIRS monitoring during cardiac surgery under cardiopulmonary bypass could reduce the incidence of postoperative delirium. Methods: PubMed, Web of Science, Cochrane Library, Embase and China National Knowledge Infrastructure (CNKI) databases were systematically searched using the related keywords for randomized-controlled trials (RCTs) published from their inception to March 16, 2024. This review was conducted by the Preferred Reporting Project and Meta-Analysis Statement (PRISMA) guidelines for systematic review. The primary outcome was postoperative delirium, and the second outcomes included the length of ICU stay, the incidence of kidney-related adverse outcomes, and the incidence of cardiac-related adverse outcomes. Results: The incidence of postoperative delirium could be reduced under the guidance of near-infrared spectroscopy monitoring (OR, 0.657; 95% CI, 0.447-0.965; P = 0.032; I2 = 0%). However, there were no significant differences in the length of ICU stay (SMD, 0.005 days; 95% CI, -0.135-0.146; P = 0.940; I2 = 39.3%), the incidence of kidney-related adverse outcomes (OR, 0.761; 95% CI, 0.386-1.500; P = 0.430; I2 = 0%), and the incidence of the cardiac-related adverse outcomes (OR, 1.165; 95% CI, 0.556-2.442; P = 0.686; I2 = 0%) between the two groups. Conclusion: Near-infrared spectroscopy monitoring in cardiac surgery with cardiopulmonary bypass helps reduce postoperative delirium in patients. Systematic Review Registration: PROSPERO, identifier, CRD42023482675.

A satellite-derived dataset on vegetation phenology across Central Asia from 2001 to 2023.

Satellite-observed land surface phenology (LSP) data have helped us better understand terrestrial ecosystem dynamics at large scales. However, uncertainties remain in comprehending LSP variations in Central Asian drylands. In this article, an LSP dataset covering Central Asia (45-100°E, 33-57°N) is introduced. This LSP dataset was produced based on Moderate Resolution Imaging Spectroradiometer (MODIS) 0.05-degree daily reflectance and land cover data. The phenological dynamics of drylands were tracked using the seasonal profiles of near-infrared reflectance of vegetation (NIRv). NIRv time series processing involved the following steps: identifying low-quality observations, smoothing the NIRv time series, and retrieving LSP metrics. In the smoothing step, a median filter was first applied to reduce spikes, after which the stationary wavelet transform (SWT) was used to smooth the NIRv time series. The SWT was performed using the Biorthogonal 1.1 wavelet at a decomposition level of 5. Seven LSP metrics were provided in this dataset, and they were categorized into the following three groups: (1) timing of key phenological events, (2) NIRv values essential for the detection of the phenological events throughout the growing season, and (3) NIRv value linked to vegetation growth state during the growing season. This LSP dataset is useful for investigating dryland ecosystem dynamics in response to climate variations and human activities across Central Asia.

Detectability of hemodynamic oscillations in cerebral cortex through functional near-infrared spectroscopy: a simulation study.

Significance: We explore the feasibility of using time-domain (TD) and continuous-wave (CW) functional near-infrared spectroscopy (fNIRS) to monitor brain hemodynamic oscillations during resting-state activity in humans, a phenomenon that is of increasing interest in the scientific and medical community and appears to be crucial to advancing the understanding of both healthy and pathological brain functioning. Aim: Our general object is to maximize fNIRS sensitivity to brain resting-state oscillations. More specifically, we aim to define comprehensive guidelines for optimizing main operational parameters in fNIRS measurements [average photon count rate, measurement length, sampling frequency, and source-detector distance (SSD)]. In addition, we compare TD and CW fNIRS performance for the detection and localization of oscillations. Approach: A series of synthetic TD and CW fNIRS signals were generated by exploiting the solution of the diffusion equation for two different geometries of the probed medium: a homogeneous medium and a bilayer medium. Known and periodical perturbations of the concentrations of oxy- and deoxy-hemoglobin were imposed in the medium, determining changes in its optical properties. The homogeneous slab model was used to determine the effect of multiple measurement parameters on fNIRS sensitivity to oscillatory phenomena, and the bilayer model was used to evaluate and compare the abilities of TD and CW fNIRS in detecting and isolating oscillations occurring at different depths. For TD fNIRS, two approaches to enhance depth-selectivity were evaluated: first, a time-windowing of the photon distribution of time-of-flight was performed, and then, the time-dependent mean partial pathlength (TMPP) method was used to retrieve the hemoglobin concentrations in the medium. Results: In the homogeneous medium case, the sensitivity of TD and CW fNIRS to periodical perturbations of the optical properties increases proportionally with the average photon count rate, the measurement length, and the sampling frequency and approximatively with the square of the SSD. In the bilayer medium case, the time-windowing method can detect and correctly localize the presence of oscillatory components in the TD fNIRS signal, even in the presence of very low photon count rates. The TMPP method demonstrates how to correctly retrieve the periodical variation of hemoglobin at different depths from the TD fNIRS signal acquired at a single SSD. For CW fNIRS, measurements taken at typical SSDs used for short-separation channel regression show notable sensitivity to oscillations occurring in the deep layer, challenging the assumptions underlying this correction method when the focus is on analyzing oscillatory phenomena. Conclusions: We demonstrated that the TD fNIRS technique allows for the detection and depth-localization of periodical fluctuations of the hemoglobin concentrations within the probed medium using an acquisition at a single SSD, offering an alternative to multi-distance CW fNIRS setups. Moreover, we offered some valuable guidelines that can assist researchers in defining optimal experimental protocols for fNIRS studies.

Visualization of cecal tumor by near-infrared laparoscopy and intraoperative colonoscopy.

BACKGROUND: In laparoscopic colorectal surgery, accurate localization of a tumor is essential for ensuring an adequate ablative margin. Therefore, a new method, near-infrared laparoscopy combined with intraoperative colonoscopy, was developed for visualizing the contour of a cecal tumor from outside of the bowel. The method was used after it was verified on a model that employed a silicone tube. CASE PRESENTATION: The patient was a 77-year-old man with a cecal tumor near the appendiceal orifice. Laparoscopy was used to clamp of the terminal ileum, and a colonoscope was then inserted through the anus to the cecum. The laparoscope in the normal light mode could not be used to identify the cecal tumor. However, a laparoscope in the near-infrared ray mode could clearly visualize the contour of the cecal tumor from outside of the bowel, and the tumor could be safely resected by a stapler. The histopathological diagnosis of the resected specimen was adenocarcinoma with an invasion depth of M and a clear negative margin. CONCLUSIONS: This is the first report of the laparoscopic detection of the contour of a cecal tumor from outside the bowel. This technique is useful and safe for contouring tumors in laparoscopic colorectal surgery and can be used in various surgeries that combine endoscopy and laparoscopy.