Bilateral first rib fractures with multi-organ complications: A case report and literature review.

Background: Bilateral first rib fractures are rare. This article presented the diagnosis and treatment of a case of bilateral first rib fractures with multi-organ complications and discussed the injury mechanism. Case presentation: A 15-year-old girl fell off a motorcycle. She complained of right neck root pain and right upper limb weakness. The myodynamia of the right upper limb was grade 0, and the sensation disappeared below the level of the elbow joint. The computed tomography (CT) showed bilateral first rib fractures and transverse process fracture of the 6th cervical vertebra. Chest CT revealed a massive hemothorax in the right thoracic cavity, and head magnetic resonance imaging showed bilateral cerebellar infarction. Cervical computed tomography angiography (CTA) revealed a lumen occlusion at the origin of the right subclavian artery. The patient underwent an emergency thoracoscopy, and a re-examination of chest CT indicated that no obvious pleural effusion was found after the hemothorax was cleared. The patient underwent right subclavian arteriography and interventional endovascular thrombolysis, and the right subclavicular artery was patency postoperative. Bilateral first rib fractures and cerebellar infarction were treated conservatively. The brachial plexus injury did not show any signs of recovery after conservative treatment, and she was recommended to be transferred to a superior hospital for surgical treatment. Conclusions: The injury mechanism of bilateral first rib fractures with multi-organ complications was closely related to the initial factor of the right neck root colliding with a bulge on the ground. We believe that the fractures occur as a result of a combination including a high energy trauma from direct impact and a low-energy mechanism from violent muscle contraction caused by neck hyperextension. This case report was helpful for clinicians to understand bilateral first rib fractures and their complications.

A comprehensive epigenetic network can influence the occurrence of thyroid-associated ophthalmopathy by affecting immune and inflammatory response.

The primary objective of this study is to understand the regulatory role of epigenetics in thyroid-associated ophthalmopathy (TAO) using multi-omics sequencing data. We utilized tRFs sequencing data, DNA methylation sequencing data, and lncRNA/circRNA/mRNA sequencing data, as well as several RNA methylation target prediction websites, to analyze the regulatory effect of DNA methylation, non-coding RNA, and RNA methylation on TAO-associated genes. Through differential expression analysis, we identified 1019 differentially expressed genes, 985 differentially methylated genes, and 2601 non-coding RNA. Functional analysis showed that differentially expressed genes were mostly associated with the PI3K signaling pathway and the IL17 signaling pathway. Genes regulated by DNA epigenetic regulatory networks were mainly related to the Cytokine-cytokine receptor interaction pathway, whereas genes regulated by RNA epigenetic regulatory networks were primarily related to the T cell receptor signaling pathway. Finally, our integrated regulatory network analysis revealed that epigenetics mainly impacts the occurrence of TAO through its effects on key pathways such as cell killing, cytokine production, and immune response. In summary, this study is the first to reveal a new mechanism underlying the development of TAO and provides new directions for future TAO research.

Cadmium promoted LPS-induced inflammation through TLR4/IκBα/NFκ-B signaling by increasing ROS-mediated incomplete autophagy.

Cadmium (Cd) exposure is considered as non-infectious stressor to human and animal health. Recent studies suggest that the immunotoxicity of low dose Cd is not directly apparent, but disrupts the immune responses when infected with some bacteria or virus. But how Cd alters the adaptive immunity organ and cells remains unclear. In this study, we applied lipopolysaccharide (LPS, infectious stressor) to induced inflammation in spleen tissues and T cells, and investigated the effects after Cd exposure and the underlying mechanism. Cd exposure promoted LPS-induced the expressions of the inflammatory factors, induced abnormal initiation of autophagy, but blocked autophagic flux. The effects Cd exposure under LPS activation were reversed by the autophagy promoter Rapamycin. Under LPS activation conditions, Cd also induced oxidative stress by increasing the levels of reactive oxygen species (ROS) and malondialdehyde (MDA), and reducing total antioxidant capacity (T-AOC) activity. The increased superoxide dismutase (SOD) activity after Cd exposure might be a negative feedback or passive adaptive regulation of oxidative stress. Cd-increased autophagic flux inhibition and TNF-α expression were reversed by ROS scavenger α-tocopherol (TCP). Furthermore, under LPS activation condition, Cd promoted activation of toll-like receptor 4 (TLR4)/IκBα/NFκ-B signaling pathway and increased TLR4 protein stability, which were abolished by the pretreatment of Rapamycin. The present study confirmed that, by increasing ROS-mediated inhibiting autophagic degradation of TLR4, Cd promoted LPS-induced inflammation in spleen T cells. This study identified the mechanism of autophagy in Cd-aggravated immunotoxicity under infectious stress, which could arouse public attention to synergistic toxicity of Cd and bacterial or virus infection.

EPAT: a user-friendly MATLAB toolbox for EEG/ERP data processing and analysis.

Background: At the intersection of neural monitoring and decoding, event-related potential (ERP) based on electroencephalography (EEG) has opened a window into intrinsic brain function. The stability of ERP makes it frequently employed in the field of neuroscience. However, project-specific custom code, tracking of user-defined parameters, and the large diversity of commercial tools have limited clinical application. Methods: We introduce an open-source, user-friendly, and reproducible MATLAB toolbox named EPAT that includes a variety of algorithms for EEG data preprocessing. It provides EEGLAB-based template pipelines for advanced multi-processing of EEG, magnetoencephalography, and polysomnogram data. Participants evaluated EEGLAB and EPAT across 14 indicators, with satisfaction ratings analyzed using the Wilcoxon signed-rank test or paired t-test based on distribution normality. Results: EPAT eases EEG signal browsing and preprocessing, EEG power spectrum analysis, independent component analysis, time-frequency analysis, ERP waveform drawing, and topological analysis of scalp voltage. A user-friendly graphical user interface allows clinicians and researchers with no programming background to use EPAT. Conclusion: This article describes the architecture, functionalities, and workflow of the toolbox. The release of EPAT will help advance EEG methodology and its application to clinical translational studies.

Investigating quantitative approach for microalgal biomass using deep convolutional neural networks and image recognition.

The effective monitoring of microalgae cultivation is crucial for optimizing their energy utilization efficiency. In this paper, a quantitative analysis method, using microalgae images based on two convolutional neural networks, EfficientNet (EFF) and residual network (RES), is proposed. Suspension samples prepared from two types of dried microalgae powders, Rhodophyta (RH) and Spirulina (SP), were used to mimic real microalgae cultivation settings. The method's prediction accuracy of the algae concentration ranges from 0.94 to 0.99. RH, with a distinctively pronounced red-green-blue value shift, achieves a higher prediction accuracy than SP. The prediction results of the two algorithms were significantly superior to those of a linear regression. Additionally, RES outperforms EFF in terms of its generalization ability and robustness, which is attributable to its distinct residual block architecture. The RES provides a viable approach for the image-based quantitative analysis.

Rotenone-induced PINK1/Parkin-mediated mitophagy: establishing a silkworm model for Parkinson's disease potential.

Parkinson's disease (PD), ranking as the second most prevalent neurodegenerative disorder globally, presents a pressing need for innovative animal models to deepen our understanding of its pathophysiology and explore potential therapeutic interventions. The development of such animal models plays a pivotal role in unraveling the complexities of PD and investigating promising treatment avenues. In this study, we employed transcriptome sequencing on BmN cells treated with 1 µg/ml rotenone, aiming to elucidate the underlying toxicological mechanisms. The investigation brought to light a significant reduction in mitochondrial membrane potential induced by rotenone, subsequently triggering mitophagy. Notably, the PTEN induced putative kinase 1 (PINK1)/Parkin pathway emerged as a key player in the cascade leading to rotenone-induced mitophagy. Furthermore, our exploration extended to silkworms exposed to 50 µg/ml rotenone, revealing distinctive motor dysfunction as well as inhibition of Tyrosine hydroxylase (TH) gene expression. These observed effects not only contribute valuable insights into the impact and intricate mechanisms of rotenone exposure on mitophagy but also provide robust scientific evidence supporting the utilization of rotenone in establishing a PD model in the silkworm. This comprehensive investigation not only enriches our understanding of the toxicological pathways triggered by rotenone but also highlights the potential of silkworms as a valuable model organism for PD research.

Potential Strategy to Control the Organic Components of Condensable Particulate Matter: A Critical Review.

More and more attention has been paid to condensable particulate matter (CPM) since its emissions have surpassed that of filterable particulate matter (FPM) with the large-scale application of ultralow-emission reform. CPM is a gaseous material in the flue stack but instantly turns into particles after leaving the stack. It is composed of inorganic and organic components. Organic components are an important part of CPM, and they are an irritant, teratogenic, and carcinogenic, which triggers photochemical smog, urban haze, and acid deposition. CPM organic components can aggravate air pollution and climate change; therefore, consideration should be given to them. Based on existing methods for removing atmospheric organic pollutants and combined with the characteristics of CPM organic components, we provide a critical overview from the aspects of (i) fundamental cognition of CPM, (ii) common methods to control CPM organic components, and (iii) catalytic oxidation of CPM organic components. As one of the most encouraging methods, catalytic oxidation is discussed in detail, especially in combination with selective catalytic reduction (SCR) technology, to meet the growing demands for multipollutant control (MPC). We believe that this review is inspiring for a fuller understanding and deeper exploration of promising approaches to control CPM organic components.

Eco-evolutionary evidence for the global diversity pattern of Cycas (Cycadaceae).

The evolution of the latitudinal diversity gradient (LDG), characterized by a peak in diversity toward the tropics, has captured significant attention in evolutionary biology and ecology. However, the inverse LDG (i-LDG) mechanism, wherein species richness increases toward the poles, remains inadequately explored. Cycads are among one of the oldest lineages of extant seed plants and have undergone extensive diversification in the tropics. Intriguingly, the extant cycad abundance exhibits an i-LDG pattern, and the underlying causes for this phenomenon remain largely elusive. Here, using 1,843 nuclear genes from a nearly complete sampling, we conducted comprehensive phylogenomic analyses to establish a robust species-level phylogeny for Cycas, the largest genus within cycads. We then reconstructed the spatial-temporal dynamics and integrated global environmental data to evaluate the roles of species ages, diversification rates, contemporary environment, and conservatism to ancestral niches in shaping the i-LDG pattern. We found Cycas experienced decreased diversification rates, coupled with the cooling temperature since its origin in the Eocene from continental Asia. Different regions have distinctively contributed to the formation of i-LDG for Cycas, with the northern hemisphere acting as evolutionary museums and the southern hemisphere serving as cradles. Moreover, water-related climate variables, specifically precipitation seasonality and potential evapotranspiration, were identified as paramount factors constraining Cycas species richness in the rainforest biome near the equator. Notably, the adherence to ancestral monsoonal climates emerges as a critical factor in sustaining the diversity pattern. This study underscores the imperative of integrating both evolutionary and ecological approaches to comprehensively unravel the mechanisms underpinning global biodiversity patterns.

A novel digital intermediate frequency module for hyperspectral microwave radiometers based on the parallel fast Fourier transform algorithm.

Microwave radiometers, possessing all-day and all-weather operational capabilities, are extensively utilized in the exploration of planetary atmospheres and surfaces. The potential of the hyperspectral detection technology to enhance the precision and resolution of microwave radiometer detection has made it a crucial research focus. This paper introduces an intermediate frequency (IF) module for hyperspectral microwave radiometers. The IF module is constructed with two 6.4 gigabit samples per second sampling-rate analog-to-digital converter (ADC) chips and a Xilinx Virtex-7 field programmable gate array. By implementing a parallel fast Fourier transform algorithm and a pipeline architecture, the IF module can efficiently process all ADC sampling data in real-time, generating 512 channels of output for each ADC. The test results, including linearity, sensitivity, and flatness, are presented and thoroughly analyzed for the IF module. Furthermore, the module is interfaced with the radio frequency front-end of the microwave radiometer to measure hot and cold calibration sources and assess its sensitivity. When combined with a suitable front-end receiver, the IF module can form a radiometer system suitable for various applications of microwave remote sensing.

An integrated transcriptomics and network pharmacology approach to explore the mechanism of Wang-Bi tablet against SAPHO syndrome.

BACKGROUND: SAPHO syndrome is recognized as a rare entity with damage to skin and bones due to inflammation. Currently, the treatment for SAPHO syndrome is still a challenge in clinical practice. In this study, an integrated transcriptomics and network pharmacology approach was applied to explore the therapeutic effect and mechanism of Wang-Bi tablet (WBT) on SAPHO syndrome. METHODS: The main components of WBT and their targets, as well as the targets of SAPHO syndrome, were collected from databases. Network visualization was performed using Cytoscape software. The GO and KEGG enrichment analysis was executed by David dataset. Then, the molecular mechanism of WBT improving SAPHO syndrome was validated by transcriptomics of peripheral blood neutrophils in SAPHO syndrome. Finally, the above results were validated by molecular docking. RESULTS: The Network Pharmacology results showed there are 152 core targets for WBT treatment on SAPHO syndrome. RNA-seq data showed 442 differentially expressed genes (DEGs) in peripheral blood neutrophils of SAPHO patients. Intriguingly, NIK/NF-kappaB-, MyD88-dependent toll-like receptor-, and MAPK pathway were included in the enrichment results of network pharmacology and RNA-seq. Moreover, we verified that the core components of WBT have good affinity with the core targets of NIK/NF-kappaB-, MyD88-dependent toll-like receptor-, and MAPK pathway by molecular docking. CONCLUSIONS: This study illustrated that the possible mechanisms of WBT against SAPHO syndrome may be related to NIK/NF-kappaB-, MyD88-dependent toll-like receptor-, and MAPK pathway, and further experiments are needed to prove these predictions.

From ferroptosis to cuproptosis, and calcicoptosis, to find more novel metals-mediated distinct form of regulated cell death.

Regulated cell death (RCD), also known as programmed cell death (PCD), plays a critical role in various biological processes, such as tissue injury/repair, development, and homeostasis. Dysregulation of RCD pathways can lead to the development of many human diseases, such as cancer, neurodegenerative disorders, and cardiovascular diseases. Maintaining proper metal ion homeostasis is critical for human health. However, imbalances in metal levels within cells can result in cytotoxicity and cell death, leading to a variety of diseases and health problems. In recent years, new types of metal overload-induced cell death have been identified, including ferroptosis, cuproptosis, and calcicoptosis. This has prompted us to examine the three defined metal-dependent cell death types, and discuss other metals-induced ferroptosis, cuproptosis, and disrupted Ca2+ homeostasis, as well as the roles of Zn2+ in metals' homeostasis and related RCD. We have reviewed the connection between metals-induced RCD and various diseases, as well as the underlying mechanisms. We believe that further research in this area will lead to the discovery of novel types of metal-dependent RCD, a better understanding of the underlying mechanisms, and the development of new therapeutic strategies for human diseases.

Recycling selectable markers via Cre/loxP system for constructing Komagataella phaffii strains co-expressing multiple proteins.

OBJECTIVE: A convenient strategy was developed to recycle selectable markers using Cre/loxP system for constructing Komagataella phaffii strains co-expressing multiple proteins. RESULTS: A plasmid in this strategy was generated from pPICZαA with integration of lox71-Sh ble-lox66. Firstly, the plasmid was inserted with one target protein gene and then transformed into K. phaffii KM71. Secondly, the auxiliary plasmid pPICZαA/cre/his4 containing CRE recombinase gene was further chromosomally inserted to Sh ble gene therein. Finally, methanol induction was conducted to produce CRE for Cre/loxP-mediated recombination, and consequently, the sequence between lox71 and lox66 was deleted, leading to recycling of ZeoR and His- markers. Then the resulted strain expressing the one target protein was used as the host to which another target protein gene could be inserted by the same procedures. CONCLUSIONS: With easy manipulation, the method was effective in recycling of the selectable markers, and consequently two protein genes were sequential integrated chromosomally and successfully co-expressed in the yeast.

Data pyramid structure for optimizing EUS-based GISTs diagnosis in multi-center analysis with missing label.

This study introduces the Data Pyramid Structure (DPS) to address data sparsity and missing labels in medical image analysis. The DPS optimizes multi-task learning and enables sustainable expansion of multi-center data analysis. Specifically, It facilitates attribute prediction and malignant tumor diagnosis tasks by implementing a segmentation and aggregation strategy on data with absent attribute labels. To leverage multi-center data, we propose the Unified Ensemble Learning Framework (UELF) and the Unified Federated Learning Framework (UFLF), which incorporate strategies for data transfer and incremental learning in scenarios with missing labels. The proposed method was evaluated on a challenging EUS patient dataset from five centers, achieving promising diagnostic performance. The average accuracy was 0.984 with an AUC of 0.927 for multi-center analysis, surpassing state-of-the-art approaches. The interpretability of the predictions further highlights the potential clinical relevance of our method.

TikTok video as a health education source of information on heart failure in China: a content analysis.

Background: Heart failure (HF) is a complex and life-threatening syndrome associated with significant morbidity and mortality. While TikTok has gained popularity as a social media platform for sharing HF-related information, the quality of such content on TikTok remains unexplored. Methods: A cross-sectional analysis was conducted on TikTok videos related to HF in China. The sources of the videos were identified and analyzed. The content comprehensiveness of the videos was evaluated using six questions that covered definition, signs and symptoms, risk factors, evaluation, management, and outcomes. The reliability and quality of the videos were assessed using three standardized evaluation instruments: DISCERN, JAMA benchmarks, and the Global Quality Scale. Additionally, the correlation between video quality and video characteristics was further investigated. Results: Among the video sources, 92.2% were attributed to health professionals, while news agencies and non-profit organizations accounted for 5.7% and 2.1%, respectively. The content comprehensiveness score for the videos was 3.36 (SD 3.56), with news agencies receiving the highest scores of 4.06 (SD 3.31). The median DISCERN, JAMA, and GQS scores for all 141 videos were 26.50 (IQR 25.00-28.750), 2.00 (IQR 2.00-2.00), and 2.00 (IQR 2.00-2.00), respectively. Videos from health professionals had significantly higher JAMA scores compared to those from non-profit organizations (P < 0.01). Correlation analysis between video quality and video characteristics showed positive correlations between content comprehensiveness scores and video duration (r = 0.420, P < 0.001), number of comments (r = 0.195, P < 0.05), and number of shares (r = 0.174, P < 0.05). GQS scores were negatively or positively correlated with the number of days since upload (r = -0.212, P < 0.05) and video duration (r = 0.442, P < 0.001). Conclusion: The overall quality of the videos was found to be unsatisfactory, with variations in quality scores observed across different video sources. Content comprehensiveness was inadequate, the reliability and quality of the information presented in the videos was questionable. As TikTok continues to grow as a platform for health information, it is essential to prioritize accuracy and reliability to enhance patients' self-care abilities and promote public health.

RAD-sequencing improves the genetic characterization of a threatened tree peony (Paeonia ludlowii) endemic to China: Implications for conservation.

Compared with traditional genetic markers, genomic approaches have proved valuable to the conservation of endangered species. Paeonia ludlowii having rarely and pure yellow flowers, is one of the world's most famous tree peonies. However, only several wild populations remain in the Yarlung Zangbo Valley (Nyingchi and Shannan regions, Xizang) in China due to increasing anthropogenic impact on the natural habitats. We used genome-wide single nucleotide polymorphisms to elucidate the spatial pattern of genetic variation, population structure and demographic history of P. ludlowii from the fragmented region comprising the entire range of this species, aiming to provide a basis for conserving the genetic resources of this species. Unlike genetic uniformity among populations revealed in previous studies, we found low but varied levels of intra-population genetic diversity, in which lower genetic diversity was detected in the population in Shannan region compared to those in Nyingzhi region. These spatial patterns may be likely associated with different population sizes caused by micro-environment differences in these two regions. Additionally, low genetic differentiation among populations (Fst = 0.0037) were detected at the species level. This line of evidence, combined with the result of significant genetic differentiation between the two closest populations and lack of isolation by distance, suggested that shared ancestry among now remnant populations rather than contemporary genetic connectivity resulted in subtle population structure. Demographic inference suggested that P. ludlowii probably experienced a temporal history of sharp population decline during the period of Last Glacial Maximum, and a subsequent bottleneck event resulting from prehistoric human activities on the Qinghai-Tibet Plateau. All these events, together with current habitat fragment and excavation might contribute to the endangered status of P. ludlowii. Our study improved the genetic characterization of the endangered tree peony (P. ludlowii) in China, and these genetic inferences should be considered when making different in situ and ex situ conservation actions for P. ludlowii in this evolutionary hotspot region.

A pan-cancer analysis revealing the role of LFNG, MFNG and RFNG in tumor prognosis and microenvironment.

BACKGROUND: Fringe is a glycosyltransferase involved in tumor occurrence and metastasis. However, a comprehensive analysis of the Fringe family members lunatic fringe (LFNG), manic fringe (MFNG), radical fringe (RFNG) in human cancers is lacking. METHODS: In this study, we performed a pan-cancer analysis of Fringe family members in 33 cancer types with transcriptomic, genomic, methylation data from The Cancer Genome Atlas (TCGA) project. The correlation between Fringe family member expression and patient overall survival, copy number variation, methylation, Gene Ontology enrichment, and tumor-infiltrating lymphocytes (TILs) was investigated by using multiple databases, such as cBioPortal, Human Protein Atlas, GeneCards, STRING, MSigDB, TISIDB, and TIMER2. In vitro experiments and immunohistochemical assays were performed to validate our findings. RESULTS: High expression levels of LFNG, MFNG, RFNG were closely associated with poor overall survival in multiple cancers, particularly in pancreatic adenocarcinoma (PAAD), uveal melanoma (UVM), and brain lower-grade glioma (LGG). Copy number variation analysis revealed that diploid and gain mutations of LFNG was significantly increased in PAAD and stomach adenocarcinoma (STAD), and significantly associated with the methylation levels in promoter regions. Significant differential genes between high and low expression groups of these Fringe family members were found to be consistently enriched in immune response and T cell activation pathway, extracellular matrix adhesion pathway, RNA splicing and ion transport pathways. Correlation between the abundance of tumor-infiltrating lymphocytes (TILs) and LFNG, MFNG, and RFNG expression showed that high LFNG expression was associated with lower TIL levels, particularly in PAAD. In vitro experiment by using pancreatic cancer PANC1 cells showed that LFNG overexpression promoted cell proliferation and invasion. Immunohistochemical assay in 90 PAAD patients verified the expression level of LFNG and its relationship with the prognosis. CONCLUSIONS: Our study provides a relatively comprehensive understanding of the expression, mutation, copy number, promoter methylation level changes along with prognosis values of LFNG, MFNG, and RFNG in different tumors. High LFNG expression may serve as a poor prognosis molecular marker for PAAD.

Driving Intention Recognition of Surrounding Vehicles Based on a Time-Sequenced Weights Hidden Markov Model for Autonomous Driving.

Accurate perception, especially situational awareness, is central to the evolution of autonomous driving. This necessitates understanding both the traffic conditions and driving intentions of surrounding vehicles. Given the unobservable nature of driving intentions, the hidden Markov model (HMM) has emerged as a popular tool for intention recognition, owing to its ability to relate observable and hidden variables. However, HMM does not account for the inconsistencies present in time series data, which are crucial for intention recognition. Specifically, HMM overlooks the fact that recent observations offer more reliable insights into a vehicle's driving intention. To address the aforementioned limitations, we introduce a time-sequenced weights hidden Markov model (TSWHMM). This model amplifies the significance of recent observations in recognition by integrating a discount factor during the observation sequence probability computation, making it more aligned with practical requirements. Regarding the model's input, in addition to easily accessible states of a target vehicle, such as lateral speed and heading angle, we also introduced lane hazard factors that reflect collision risks to capture the traffic environment information surrounding the vehicle. Experiments on the HighD dataset show that TSWHMM achieves recognition accuracies of 94.9% and 93.4% for left and right lane changes, surpassing both HMM and recurrent neural networks (RNN). Moreover, TSWHMM recognizes lane-changing intentions earlier than its counterparts. In tests involving more complex roundabout scenarios, TSWHMM achieves an accuracy of 87.3% and can recognize vehicles' intentions to exit the roundabout 2.09 s in advance.

Single-Molecule Methane Sensing Using Palladium-Functionalized nIR Fluorescent Single-Walled Carbon Nanotubes.

There has been considerable interest in detecting atmospheric and process-associated methane (CH4) at low concentrations due to its potency as a greenhouse gas. Nanosensor technology, particularly fluorescent single-walled carbon nanotube (SWCNT) arrays, is promising for such applications because of their chemical sensitivities at single-molecule detection limits. However, the methodologies for connecting the stochastic molecular fluctuations from gas impingement on such sensors require further development. In this work, we synthesize Pd-conjugated ss(GT)15-DNA-wrapped SWCNTas near-infrared (nIR) fluorescent, single-molecule sensors of CH4. The complexes are characterized using X-ray photoelectron spectroscopy (XPS) and spectrophotometry, demonstrating spectral changes between the Pd2+ and Pd0 oxidation states. The nIR fluctuations generated upon exposure from 8 to 26 ppb of CH4 were separated into high- and low-frequency components. Aggregating the low-frequency components for an array of sensors showed the most consistent levels of detection with a limit of 0.7 ppb. These results advance the hardware and computational methods necessary to apply this approach to the challenge of environmental methane sensing.