Standard Platform Research Articles

Tightness of the conical implant-abutment interface

Dental implant-based structures actively interact with the oral cavity and are subject to various factors. Local changes in the microflora near the implant can cause inflammation and affect its viability, as well as in the tooth. Improperly manufactured construction can also serve as a factor in the development of dysbiosis. The purpose of our study is to explore the permeability of the conical joint of the implant with an abutment of various types of manufacture under the influence of masticatory load. The tightness of the conical joint is studied on MIS C1 implants, a standard platform. The control group of the study consists of standard transgingival abutments. As an experimental group were used: milled, cast, and obtained by laser sintering. Modelling of oral cavity conditions was studied in a simulation complex. After 3000 masticating cycles the implant shafts were explored. When examining the inner surface of implants on which standard and milled abutments are fixed, the presence of methylene blue was not detected. A study of the implants shafts on which abutments were fixed, obtained by casting and laser sintering, showed the permeability of these compounds through the implant-abutment interface. Use of original elements in the system ensures a hermetic implant-abutment connection. In complex clinical cases for treatment and rehabilitation of patients, the manufacture of structures with individual abutments is required. The best result is achieved using abutments made by milling.

Optimization and Application of Comprehensive Environmental-Economic Evaluation Indicator System in Sustainable Development Policies of Chinese Manufacturing Industry

This paper focuses on optimizing the comprehensive environmental-economic evaluation index system to enhance the sustainable development policy of China’s manufacturing industry. The current indicator system, while useful, has notable shortcomings that limit its effectiveness. To address these issues, the paper proposes the inclusion of crucial indicators such as green productivity, carbon footprint, and water footprint, which are essential for providing a more holistic evaluation. These additions aim to capture better the environmental impacts and resource efficiency within the manufacturing sector. The paper also discusses the challenges in data acquisition, emphasizing the need for a standardized national environmental data platform. Such a platform would facilitate the collection of accurate, reliable, and accessible data, thereby improving the precision of evaluations. To further refine the assessment process, dynamic evaluation models, like the system dynamics model, are introduced. These models are designed to provide a more nuanced understanding of the environmental impacts over time, allowing for more responsive and adaptive policy-making. The optimized indicator system is expected to have significant applications in policy formulation, enterprise management, and social oversight. By providing a scientific basis for decision-making, it will play a critical role in advancing the sustainable development of China’s manufacturing industry, ensuring that environmental considerations are fully integrated into economic planning and industrial practices.

Validation, implementation and quality control of a Torque Teno Virus qPCR in a multinational clinical trial

BackgroundImmunosuppressive medication after organ transplantation is usually dosed through therapeutic drug monitoring. Trough levels of antirejection medication however, do not adequately predict rejection or infections. The TTVguideIT trial is a multinational clinical trial evaluating the safety of Torque Teno Virus (TTV) load assessed by qPCR, as an alternative to trough level tacrolimus dosing. MethodsPrior to, and during the clinical trial, the inter-and intra-laboratory variability, accuracy, and precision of the TTV R-GENE® assay was evaluated through analysis of internal quality control (IQC), external quality assessment (EQA) and linearity panels performed by the thirteen participating clinical virology laboratories, each using their standard testing platforms. ResultsIQC samples with a target of 4 log10 copies/mL (cp/mL) were tested by the participating laboratories 130 times during the implementation phase and 987 times during the trial phase. They showed excellent accuracy, with an inter-laboratory standard deviation (SD) of 0.17 log10 cp/mL, and an intra-laboratory SD of 0.03 to 0.20 log10 cp/mL during the implementation phase, and an inter-laboratory SD of 0.19 log10 cp/mL, and an intra-laboratory SD 0.07 to 0.18 log10 cp/mL during the trial phase. Three EQA panels and three linearity panels showed similarly small variability during implementation as well as within the trial phase. ConclusionThis data shows that TTV load measurement can be standardized for use in a multinational clinical trial. By using IQC, LP and EQA samples, the quality and integrity of the assay can be compared between laboratories and precise and accurate results can be generated.

Freestanding Germanium Photonic Crystal Waveguide for a Highly Sensitive and Compact Mid-Infrared On-Chip Gas Sensor.

The performance of mid-infrared (MIR) on-chip gas sensors, operating via laser absorption spectroscopy, hinges critically on light-matter interaction dynamics, significantly influenced by external confinement and the effective light path length. Conventional on-chip sensors, however, face challenges in achieving the required limit of detection for highly sensitive applications, primarily due to their intrinsically short effective light path. Furthermore, these sensors are limited in their spectral range coverage within the MIR spectrum by the constraints of standard silicon-based platforms. To overcome these limitations, our research presents a novel approach to fabricate a freestanding germanium (Ge) photonic crystal waveguide (PCW) on a germanium-on-insulator (Ge-OI) platform, utilizing yttrium oxide (Y2O3) as the buried oxide layer. This device leverages the broad transparent windows of Ge and Y2O3, broadening the spectral coverage across the MIR range. The introduction of the PCW and its slow light effect significantly elevate external confinement and light-matter interactions, enabling a notable reduction in waveguide length, which traditionally limits on-chip configurations. The freestanding structure not only expands the sensing region and enhances external confinement but also prevents the emergence of leaky modes within the PCW. As a result, our compact sensor achieves an exceptionally low LoD of 7.56 ppm for carbon dioxide (CO2) sensing at the operational wavelength of 4.23 μm, with a compact waveguide length of only 800 μm.

Planetary health in action: developing a heatwave vulnerability tool for primary care.

Heatwaves are becoming longer and more frequent. Despite the availability of open environmental data, little is operable and formatted for primary care use. Create a user-friendly online mapping tool to assess the vulnerability of communities to heatwaves for use by primary care practitioners. This study questioned what knowledge needed to be deployed, who needed to participate and how the knowledge should be shared. A participatory action-research project based on knowledge mobilization in France as part of the Green Data for Health Challenge. Knowledge was summarized on the factors most affecting heatwave vulnerability in a collaborative process, enabling a consensus on data variables and mobilised content for the online tool. Purposive sampling included primary care stakeholders with Regional Health Agencies (ARS), Public Health France, and data scientists. Nineteen participants participated in ten co-construction workshops, a brainstorming carousel strategy and five weekly co-design meetings between December 2022 and June 2023. The heatwave vulnerability variable was constructed using surface temperature, social deprivation, vegetation coverage, and presence of air conditioning equipment. Identified experts mobilized data on the national composite indicator at the communal level for heatwave morbidity. There is no standard platform for sharing environmental data in France. This co-creation study offers a new approach to incorporating environmental data on heatwaves into primary care consultations. We demonstrate the importance of knowledge mobilisation in primary care to bridge the research-practice gap. Integrating primary care records with environmental data may promote broader applications for planetary health research.

Establishing a rabbit model with massive supraspinatus tendon defect for investigating scaffold-assisted tendon repair

BackgroundShoulder pain and disability from rotator cuff tears remain challenging clinical problem despite advancements in surgical techniques and materials. To advance our understanding of injury progression and develop effective therapeutics using tissue engineering and regenerative medicine approaches, it is crucial to develop and utilize animal models that closely resemble the anatomy and display the pathophysiology of the human rotator cuff. Among various animal models, the rabbit shoulder defect model is particularly favored due to its similarity to human rotator cuff pathology. However, a standardized protocol for creating a massive rotator cuff defect in the rabbits is not well defined. Therefore, the objective of our study was to establish a robust and reproducible model of a rotator cuff defect to evaluate the regenerative efficacy of scaffolds.ResultsIn our study, we successfully developed a rabbit model with a massive supraspinatus tendon defect that closely resembles the common rotator cuff injuries observed in humans. This defect involved a complete transection of the tendon, spanning 10 mm in length and encompassing its full thickness and width. To ensure stable scaffolding, we employed an innovative bridging suture technique that utilized a modified Mason-Allen suture as a structural support. Moreover, to assess the therapeutic effectiveness of the model, we utilized different scaffolds, including a bovine tendon extracellular matrix (ECM) scaffold and a commercial acellular dermal matrix (ADM) scaffold. Throughout the observation period, no scaffold damage was observed. Notably, comprehensive histological analysis demonstrated that the regenerative tissue in the tendon ECM scaffold group exhibited an organized and aligned fiber structure, indicating tendon-like tissue regeneration while the tissue in the ADM group showed comparatively less organization.ConclusionsThis study presents a comprehensive description of the implemented procedures for the development of a highly reproducible animal model that induces massive segmental defects in rotator cuff tendons. This protocol can be universally implemented with alternative scaffolds to investigate extensive tendon defects and evaluate the efficacy of regenerative treatments. The application of our animal model offers a standardized and reproducible platform, enabling researchers to systematically evaluate, compare, and optimize scaffold designs. This approach holds significant importance in advancing the development of tissue engineering strategies for effectively repairing extensive tendon defects.

RESEARCH ON THE STANDARDIZATION AND VISUALIZATION PLATFORM FOR MONITORING AND TESTING DATA OF METRO CIVIL FACILITIES BASED ON BIG DATA

Introduction: With consideration for extensive standardized detection and monitoring data, multi-source data fusion analysis and comparison were implemented at cross-project and inter-regional levels to provide robust data support for the full life-cycle management of metro civil facilities. The purpose of the study was to integrate detection and monitoring data on metro bridges and tunnel structures and address the significant data isolation issue in existing systems and various units. Based on big data and Internet of Things technology, this paper investigates the standardized format of uploading, storage, processing, sharing, and other types of managing detection and monitoring data on metro bridges and tunnel structures. Additionally, a third-party data standardization and visualization platform for bridges and tunnel structures was developed, ensuring integration of detection and monitoring data fusion. In the course of the study, the following methods were used: theoretical analysis and software system development. As a result, the practicability and feasibility of the platform were verified through practical applications.

Investigation and Analysis of the Contribution of Chinese Electric Vehicle Social Organizations’ Standardization Innovation to Intelligent Optimization Research and Development Investment

Intelligent design has been the direction pursued by international electric vehicle (EV) research and development (R&D) teams in recent years. This paper analyzes the problems of unsustainable development in the current product design of EVs in China, such as high R&D investment, high innovation risks, and low R&D input–output ratios. It explores the issues related to intelligent design, R&D investment, car prices, and safety in the field of EVs in China, and it proposes the concept of optimizing intelligence to optimize the design investment of EVs in China. On the basis of the development situation and the existing problems of social organization standards that gather innovative technologies for EVs, this paper used data from the national social organization standard information platform as the research object and analyzed important data, such as the quantity of the information of relevant social organizations and professional fields of social organization standards, through mathematical methods. The article proposes an optimization design scheme for EV products in China, combining intelligence and practicality from the perspective of the optimizing intelligent design, and it models the construction of EV optimization design. The quantitative relationship between the two schemes before and after optimization design is compared in terms of cost savings in intelligent design, the improvement of social benefits, and the enhancement of EV cost performance. The comparative study found that intelligent optimization design reduced the R&D cost of EVs by 45.24%, and the social benefits of R&D investment increased by 29.51%.

HiExM: high-throughput expansion microscopy enables scalable super-resolution imaging.

Expansion microscopy (ExM) enables nanoscale imaging using a standard confocal microscope through the physical, isotropic expansion of fixed immunolabeled specimens. ExM is widely employed to image proteins, nucleic acids, and lipid membranes in single cells; however, current methods limit the number of samples that can be processed simultaneously. We developed High-throughput Expansion Microscopy (HiExM), a robust platform that enables expansion microscopy of cells cultured in a standard 96-well plate. Our method enables ~4.2x expansion of cells within individual wells, across multiple wells, and between plates. We also demonstrate that HiExM can be combined with high-throughput confocal imaging platforms to greatly improve the ease and scalability of image acquisition. As an example, we analyzed the effects of doxorubicin, a known cardiotoxic agent, on human cardiomyocytes (CMs) as measured by Hoechst signal across the nucleus. We show a dose dependent effect on nuclear DNA that is not observed in unexpanded CMs, suggesting that HiExM improves the detection of cellular phenotypes in response to drug treatment. Our method broadens the application of ExM as a tool for scalable super-resolution imaging in biological research applications.

Comparison of a Fully Automated Platform and an Established ELISA for the Quantification of Neurofilament Light Chain in Patients With Cognitive Decline.

Enzyme-linked immunosorbent assay (ELISA) is the most-used method for neurofilament light chain (NfL) quantification in cerebrospinal fluid (CSF). Recently, fully automated immunoassays for NfL measurement in CSF and blood have allowed high reproducibility among laboratories, making NfLs suitable for routine use in clinical practice. In this study, we compared the Uman Diagnostics NF-light ELISA with the fully automated platform Lumipulse. We enrolled 60 patients with cognitive decline, including Alzheimer disease (AD). CSF NfL levels were measured by a NF-light ELISA kit (UmanDiagnostics), and chemiluminescent enzyme immunoassay (CLEIA) on the Lumipulse G1200 platform (Fujirebio Diagnostics). Serum NfLs levels were measured by CLEIA on the Lumipulse G1200. We found a significant, very strong correlation [Spearman rho = 0.94 (0.90-0.96)] between CLEIA and ELISA in CSF, and a significant moderate correlation between CSF and serum with both analytical methods [CLEIA vs serum CLEIA 0.41 (0.16-0.61); ELISA vs serum CLEIA 0.40 (0.15-0.60)]. It is worth noting that CSF CLEIA measurements were approximately 136.12 times higher than the serum measurements. Our findings show a robust correlation between ELISA Uman Diagnostic and the standardized Lumipulse G1200 platform for CSF NfL measurements.

Unidirectional and highly dispersive grating emitters for silicon photonic beam steerers.

Grating emitters are the key component used in silicon photonic beam steerers to create light emission and allow dispersion-based steering. Conventional grating emitters are inefficient due to bidirectional emission, and their angular dispersion is only on the order of 0.1°/nm. In this paper, we develop unidirectional grating emitters by choosing a top cladding material with a refraction index higher than that of the bottom cladding. The refractive index difference allows the phase-matching condition to be satisfied only for the upward diffraction. We demonstrate experimentally grating emitters with a directionality of 83% and an angular dispersion of 0.79°/nm. These grating emitters have a simple device structure compatible with the standard silicon photonic platform.

MBCN: A novel reference database for Effcient Metagenomic analysis of human gut microbiome

Metagenomic shotgun sequencing data can identify microbes and their proportions. But metagenomic shotgun data profiling results obtained from multiple projects using different reference databases are difficult to compare and apply meta-analysis. Our work aims to create a novel collection of human gut prokaryotic genomes, named Microbiome Collection Navigator (MBCN). 2379 human gut metagenomic samples are screened, and 16,785 metagenome-assembled genomes (MAGs) are assembled using a standardized pipeline. In addition, MAGs are combined with the representative genomes from public prokaryotic genomes collections to cluster, and pan-genomes for each cluster's genomes are constructed to build Kraken2 and Bracken databases. The databases built by MBCN are more comprehensive and accurate for profiling metagenomic reads comparing with other collections on simulated reads and virtual bio-projects. We profile 1082 human gut metagenomic samples with MBCN database and organize profiles and metadata on the web program. Meanwhile, using MBCN as a reference database, we also develop a unified, standardized, and systematic metagenomic analysis pipeline and platform, named MicrobiotaCN (http://www.microbiota.cn) and common statistical and visualization tools for microbiome research are integrated into the web program. Taken together, MBCN and MicrobiotaCN can be a valuable resource and a powerful tool that allows researchers to perform metagenomic analysis by a unified pipeline efficiently.

A systematic review of blockchain for energy applications

The increasing penetration of distributed energy resources and the growing electrification of end-use consumption complicate energy management. Current strategies, which rely on centralized systems for peer-to-peer interactions, face issues of scalability, security, traceability, single points of failure, and privacy. Blockchain, with its decentralized nature, offers immutability, transparency, automation, and scalability as potential solutions. However, practical implementation remains challenging. This study systematically reviews 156 studies published since 2021 using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to explore these limitations. Results highlight that selecting the appropriate blockchain platform and consensus mechanism is crucial. Observations show that 42% of studies proposing new consensus methods and 46% developing new platforms or using simulations struggle with practical implementation. In contrast, leveraging existing standard blockchain platforms and consensus mechanisms enhances practicality and scalability. Additionally, seamless interoperability with Internet of Things (IoT) remains a significant challenge due to the high costs associated with the few platforms that offer this feature. Standardization of blockchain methodology, interoperability, performance measurement, and governance remains a major issue despite several parallel efforts by multiple stakeholders, including blockchain platform providers. Consolidation of these efforts into a common framework, together with the utilization of existing blockchain components, is key to resolving current limitations and fostering wider adoption. Among the various blockchain components suited for different applications, this study provides key criteria for selection, guiding the development of practical and scalable blockchain-based energy applications.

Accurate Prediction of Rat Acute Oral Toxicity and Reference Dose for Thousands of Polycyclic Aromatic Hydrocarbon Derivatives Based on Chemometric QSAR and Machine Learning.

Acute oral toxicity is currently not available for most polycyclic aromatic hydrocarbons (PAHs), especially their derivatives, because it is cost-prohibitive to experimentally determine all of them. Here, quantitative structure-activity relationship (QSAR) models using machine learning (ML) for predicting the toxicity of PAH derivatives were developed, based on oral toxicity data points of 788 individual substances of rats. Both the individual ML algorithm gradient boosting regression trees (GBRT) and the stacking ML algorithm (extreme gradient boosting + GBRT + random forest regression) provided the best prediction results with satisfactory determination coefficients for both cross-validation and the test set. It was found that those PAH derivatives with fewer polar hydrogens, more large-sized atoms, more branches, and lower polarizability have higher toxicity. Software based on the optimal ML-QSAR model was successfully developed to expand the application potential of the developed model, obtaining reliable prediction of pLD50 values and reference doses for 6893 external PAH derivatives. Among these chemicals, 472 were identified as moderately or highly toxic; 10 out of them had clear environment detection or use records. The findings provide valuable insights into the toxicity of PAHs and their derivatives, offering a standard platform for effectively evaluating chemical toxicity using ML-QSAR models.

A standardized image processing and data quality platform for rodent fMRI

Functional magnetic resonance imaging in rodents holds great potential for advancing our understanding of brain networks. Unlike the human community, there remains no standardized resource in rodents for image processing, analysis and quality control, posing significant reproducibility limitations. Our software platform, Rodent Automated Bold Improvement of EPI Sequences, is a pipeline designed to address these limitations for preprocessing, quality control, and confound correction, along with best practices for reproducibility and transparency. We demonstrate the robustness of the preprocessing workflow by validating performance across multiple acquisition sites and both mouse and rat data. Building upon a thorough investigation into data quality metrics across acquisition sites, we introduce guidelines for the quality control of network analysis and offer recommendations for addressing issues. Taken together, this software platform will allow the emerging community to adopt reproducible practices and foster progress in translational neuroscience.

Towards interworking of matter and oneM2M: Design and implementation of a matter–oneM2M Interworking Proxy Entity

The new smart home protocol, Matter, has garnered worldwide attention for its ability to tackle the most significant obstacle to fully unlock the potential of smart homes: interoperability. The increasing support for Matter among numerous vendors in their products is having a noticeable impact on interoperability at the device level. This work expands the reach of Matter to the IoT platform level by integrating it with an open and standardized platform, oneM2M. One of the key strengths of oneM2M is its ability to provide an open, common, and flexible interface at the platform level, facilitating seamless interconnection across various domains. This integration pave the way to provide Matter’s smart homes user with advanced intelligence services, including AI/ML applications, and emerging concepts like the metaverse. The proposed Interworking Proxy Entity (IPE) for Matter has been successfully implemented, and multiple scenarios have been tested using both commercial and experimental Matter devices within the oneM2M ACME and Mobius platforms. The results demonstrate seamless integration of Matter devices into the oneM2M platform, enabling other applications to interact with them solely through oneM2M standard interfaces. Additionally, the IPE proves to be practical for real-world applications with negligible overhead, offering mutual benefits for both Matter and oneM2M ecosystems.

Introducing biosimilar competition for cell and gene therapy products.

This article provides an early analysis of the potential for creating future biosimilar competition for cell and gene therapies (CGTs) to lower prices and improve patient access, building on a unique set of interviews with relevant experts. Our discussion addressed regulatory, manufacturing, intellectual property, and market size challenges. Due to CGTs' complexity, meeting the regulatory requirement of 'high similarity with no clinically meaningful differences' will be difficult. Gene therapies are likely better candidates for biosimilar development than cell therapies. Biosimilarity should be met when gene therapy biosimilars contain the same genetic sequence as a reference product, and the variability in the vector meets the high similarity standard. Manufacturing challenges, including the lack of standardized platforms, high production costs, and complexity, pose significant obstacles. It may also be important to demonstrate biosimilarity within the manufacturing process. Intellectual property barriers, specifically patenting, trade secrecy, and regulatory exclusivity, could hinder biosimilars' ability to gain market share, although recent Supreme Court decisions limiting the breadth of patent claims could ease barriers to future CGT competition, including from biosimilars. Finally, inadequate market sizes might create hurdles, especially for curative treatments, as patient pools shrink following treatment by the reference CGT.

Rehabilitation Using Implants with Sloped Platform Edge vs. Standard Platform with Guided Bone Regeneration: A Randomized Control Clinical Trial.

The purpose of this study was to evaluate the vertical bone loss after using different techniques: sloped implants or standard implants with guided bone regeneration. Patients with tooth gap and horizontal bone deficiency were randomly allocated to the test group (implants with sloped platform-SLP) and control group (standard design implants with guided bone regeneration-GBR). The primary outcome was bone loss (6 months after finishing the prosthetic treatment). Secondary outcomes included the following: patient-reported outcome measures (PROMs), post-operative edema, keratinized mucosa width, and pink aesthetic score (PES). The average bone loss at 6 months was 0.23 ± 0.15 mm and 1.03 ± 0.37 mm in the SLP and GBR groups, respectively. The SLP group was characterized by lower pain intensity the first 7 days (p < 0.001), lower post-operative edema (p < 0.001), lower consumption of NSAIDs on days 1, 3, 5, and 7 (p = 0.002, <0.001, <0.001, and 0.008), and lower total OHIP-14 (p = 0.047) on day 7. The keratinized mucosa width was 3.7 (3.4-4.0) mm and 2 (1.4-2.0) mm in the SLP and GBR groups, respectively. The preservation of the mesial, distal papillae, and the level of soft tissue correspondence were significantly higher in the SLP group (p = 0.003, 0.038, <0.001). In the SLP group, more natural color and better texture of soft tissues were found (p = 0.048, p = 0.041). The use of implants with a sloped platform resulted in superior outcomes compared to the standard-design implants with GBR.

A peak enhancement of frequency response of waveguide integrated silicon-based germanium avalanche photodetector

Avalanche photodetectors (APDs) featuring an avalanche multiplication region are vital for reaching high sensitivity and responsivity in optical transceivers. Waveguide-coupled Ge-on-Si separate absorption, charge, and multiplication (SACM) APDs are popular due to their straightforward fabrication process, low optical propagation loss, and high detection sensitivity in optical communications. This paper introduces a lateral SACM Ge-on-Si APD on a silicon-on-insulator (SOI) wafer, featuring a 10 μm-long, 0.5 μm-wide Ge layer at 1310 nm on a standard 8-inch silicon photonics platform. The dark current measures approximately 38.6 μA at −21 V, indicating a breakdown voltage greater than −21 V for the device. The APDs exhibit a unit-gain responsivity of 0.5 A/W at −10 V. At −15 V, their responsivity reaches 2.98 and 2.91 A/W with input powers of −10 and −25 dBm, respectively. The device's 3-dB bandwidth is 15 GHz with an input power of −15 dBm and a gain is 11.68. Experimental results show a peak in impedance at high bias voltages, attributed to inductor and capacitor (LC) circuit resonance, enhancing frequency response. Furthermore, 20 Gbps eye diagrams at −21 V and −9 dBm input power reveal signal to noise ratio (SNRs) of 5.30. This lateral SACM APD, compatible with the stand complementary metal oxide semiconductor (CMOS) process, shows that utilizing the peaking effect at low optical power increases bandwidth.

Chroma: A MATLAB package and open-source platform for biomarker data processing and automatic index calculations

The molecular ratio indices of biological markers (biomarkers), such as the Carbon Preference Index (CPI) or Paq, are frequently used as proxies for paleoclimatic and palaeoecological conditions. These indices are regularly extracted from the relative abundances of target molecules detected by a Gas Chromatography analyzer with a Flame Ionization Detector (GC-FID). Despite their use in biogeochemical studies for over a half-century, it remains common procedure to quantify the abundance of individual compounds by manual integration of chromatogram peaks (i.e., interpret baselines visually and characterize peaks by hand), which is time consuming and can lead to inconsistent results. Here, we introduce a new MATLAB package (Chroma) for the automatic detection and integration of standard-referenced biomarker abundances and the calculation of a variety of established hydrocarbon indices commonly reported in the published literature. The algorithm identifies the detector response timing of specific target peaks in a sample chromatogram by cross-referencing to a standard (e.g., Mix-A6, Schimmelmann, Indiana University Bloomington), then calculates the peak areas for an approximation of molecular abundance. This new toolkit for automatic and rapid integration of GC-acquired data provides a consistent and reproducible approach for the calculation of hydrocarbon indices and offers a standardized inter-laboratory platform for data comparisons and exchange. We validate the utility of the Chroma package with the chromatograms of plant wax n-alkanes, a widely used proxy for ecology and hydrology, from six stratigraphic sections in the Tibetan Plateau. Chroma is an effective tool for efficient data processing and will continuously evolve to accommodate extended uses in related areas of biomarker research beyond n-alkanes.