Standardized Management of Sickle Cell Disease Patients and the Effects on Care Utilization and Costs.

An individualized management program for patients with sickle cell disease (SCD) was created to reduce health care utilization and cost. The program was implemented to standardize the management of patients with SCD. SCD encounters from January 2010 to December 2020 were reviewed for analysis. Preintervention utilization of inpatient, emergency room, and outpatient settings was compared to postintervention. There were 7114 encounters analyzed. Outpatient encounters increased from 36.5% to 70.9%; inpatient encounters decreased from 38.6% to 20.3%; and emergency department visits decreased from 20.3% to 8.8%. The number of high inpatient utilizers decreased 8.4% and the number of individuals who received any emergency care decreased 11.9%. When comparing average charges per time period, the median charge per encounter decreased by $1838 postintervention compared to preintervention. This newly implemented SCD program demonstrated success through shifting the care of the SCD patient to the outpatient setting rather than the emergency department or inpatient hospitalizations.

A deep learning-guided automated workflow in LipidOz for detailed characterization of fungal fatty acid unsaturation by ozonolysis.

Understanding fungal lipid biology and metabolism is critical for antifungal target discovery as lipids play central roles in cellular processes. Nuances in lipid structural differences can significantly impact their functions, making it necessary to characterize lipids in detail to understand their roles in these complex systems. In particular, lipid double bond (DB) locations are an important component of lipid structure that can only be determined using a few specialized analytical techniques. Ozone-induced dissociation mass spectrometry (OzID-MS) is one such technique that uses ozone to break lipid DBs, producing pairs of characteristic fragments that allow the determination of DB positions. In this work, we apply OzID-MS and LipidOz software to analyze the complex lipids of Saccharomyces cerevisiae yeast strains transformed with different fatty acid desaturases from Histoplasma capsulatum to determine the specific unsaturated lipids produced. The automated data analysis in LipidOz made the determination of DB positions from this large dataset more practical, but manual verification for all targets was still time-consuming. The DL model reduces manual involvement in data analysis, but since it was trained using mammalian lipid extracts, the prediction accuracy on yeast-derived data was reduced. We addressed both shortcomings by retraining the DL model to act as a pre-filter to prioritize targets for automated analysis, providing confident manually verified results but requiring less computational time and manual effort. Our workflow resulted in the determination of detailed DB positions and enzymatic specificity.

Introducing 'identification probability' for automated and transferable assessment of metabolite identification confidence in metabolomics and related studies.

Methods for assessing compound identification confidence in metabolomics and related studies have been debated and actively researched for the past two decades. The earliest effort in 2007 focused primarily on mass spectrometry and nuclear magnetic resonance spectroscopy and resulted in four recommended levels of metabolite identification confidence - the Metabolite Standards Initiative (MSI) Levels. In 2014, the original MSI Levels were expanded to five levels (including two sublevels) to facilitate communication of compound identification confidence in high resolution mass spectrometry studies. Further refinement in identification levels have occurred, for example to accommodate use of ion mobility spectrometry in metabolomics workflows, and alternate approaches to communicate compound identification confidence also have been developed based on identification points schema. However, neither qualitative levels of identification confidence nor quantitative scoring systems address the degree of ambiguity in compound identifications in context of the chemical space being considered, are easily automated, or are transferable between analytical platforms. In this perspective, we propose that the metabolomics and related communities consider identification probability as an approach for automated and transferable assessment of compound identification and ambiguity in metabolomics and related studies. Identification probability is defined simply as 1/N, where N is the number of compounds in a reference library or chemical space that match to an experimentally measured molecule within user-defined measurement precision(s), for example mass measurement or retention time accuracy, etc. We demonstrate the utility of identification probability in an in silico analysis of multi-property reference libraries constructed from the Human Metabolome Database and computational property predictions, provide guidance to the community in transparent implementation of the concept, and invite the community to further evaluate this concept in parallel with their current preferred methods for assessing metabolite identification confidence.

A Systematic Review of Clinical Trials Comparing Radiation Therapy Versus Radical Prostatectomy in Prostate Cancer.

The treatment landscape for localized and regional prostate cancer includes active surveillance, radiation therapy (RT), and radical prostatectomy (RP). Population-based studies comparing RP to radiation reveal conflicting results due to methodological flaws. This systematic review and pooled analysis of studies aim to compare cause-specific survival (CSS), overall survival (OS), disease-free survival (DFS) and toxicity outcomes, comparing RP to RT in the management of prostate cancer. This systematic review search included the PubMed, Embase, and Cochrane libraries according to the PRISMA statement with the inception of each database up to June 24, 2023. Randomized phase 2 or 3 clinical trials that compared RP to RT in prostate cancer were included. The forest plot for the Odds ratio (OR) was plotted using the Mantel-Haenszel method, and the Z test was used to assess significance. A fixed effects model was used for meta-analysis. The search yielded seven completed randomized clinical trials and four ongoing trials. The majority of complete trials had low to intermediate-risk patient populations. OR for OS was 1.00 with 95% CI, 0.71-1.41 (P-value: 0.98), CSS OR was 0.99 with 95% CI, 0.45-2.18 (P-value 0.11), OR for DFS was 1.26 with 95% CI, 0.89-1.78 (P-value 0.19) when comparing RP to RT. The rate of distant metastatic disease was 2.3% in the RP versus 2.9% in the RT at 10 years. The rate of second malignant neoplasms was 4.5% in the RP compared to 4.2% in the RT arm at 10 years. RP caused more urinary symptoms, with a predominance of the need for urinary pads and a higher incidence of sexual dysfunction, and RT caused a higher incidence of bowel symptoms, such as blood in stools and fecal incontinence. This study provides evidence that the treatment-related outcomes are similar in patients with low to intermediate-risk prostate cancer when comparing RP to RT. Multidisciplinary treatment approaches and factoring patients' values and preferences should form the cornerstone of the ideal treatment option for each patient with localized prostate cancer. Patients with prostate cancer have an equal chance of being cancer-free and alive at 10 years with either RP or RT. In terms of side effects, RP causes more urine leakage and loss of erections, whereas RT tends to cause more bowel side effects, such as blood in stools and fecal leakage.

Evaluation of a Reference-Free Collision Cross Section Calibration Strategy for Proteomics Using SLIM-Based High-Resolution Ion Mobility Spectrometry-Mass Spectrometry.

Ion mobility spectrometry (IMS) is a gas-phase analytical technique that separates ions with different sizes and shapes and is compatible with mass spectrometry (MS) to provide an additional separation dimension. The rapid nature of the IMS separation combined with the high sensitivity of MS-based detection and the ability to derive structural information on analytes in the form of the property collision cross section (CCS) makes IMS particularly well-suited for characterizing complex samples in -omics applications. In such applications, the quality of CCS from IMS measurements is critical to confident annotation of the detected components in the complex -omics samples. However, most IMS instrumentation in mainstream use requires calibration to calculate CCS from measured arrival times, with the most notable exception being drift tube IMS measurements using multifield methods. The strategy for calibrating CCS values, particularly selection of appropriate calibrants, has important implications for CCS accuracy, reproducibility, and transferability between laboratories. The conventional approach to CCS calibration involves explicitly defining calibrants ahead of data acquisition and crucially relies upon availability of reference CCS values. In this work, we present a novel reference-free approach to CCS calibration which leverages trends among putatively identified features and computational CCS prediction to conduct calibrations post-data acquisition and without relying on explicitly defined calibrants. We demonstrated the utility of this reference-free CCS calibration strategy for proteomics application using high-resolution structures for lossless ion manipulations (SLIM)-based IMS-MS. We first validated the accuracy of CCS values using a set of synthetic peptides and then demonstrated using a complex peptide sample from cell lysate.

Anti-aquaporin-4 immunoglobulin G/anti-myelin oligodendrocyte glycoprotein immunoglobulin G double-positive paraneoplastic neurological syndrome in a patient with triple-negative breast cancer.

We report a rare case of paraneoplastic neurological syndrome with dual seropositivity of anti-aquaporin-4 and myelin oligodendrocyte glycoprotein antibodies in a 40 year-old woman with metastatic triple-negative breast cancer. She received multiple lines of anti-neoplastic treatment, including immunotherapy with pembrolizumab, as well as cytotoxic chemotherapy. Paraneoplastic meningoencephalomyelitis developed 2 years after diagnosis of breast cancer and 1 year after discontinuation of immunotherapy with pembrolizumab. She first developed longitudinally extending transverse myelitis followed by left optic neuritis and meningoencephalitis with new enhancing lesions in the brain and spinal leptomeninges. Cerebrospinal fluid analysis during both episodes showed normal glucose and protein, and elevated white blood cell count. Cytology was negative for malignancy. Cerebrospinal fluid was positive for neuromyelitis optica immunoglobulin G antibody anti-aquaporin-4, and autoimmune myelopathy panel was positive for myelin oligodendrocyte glycoprotein antibody. The patient had significant clinical and radiographic improvement after completion of five cycles of plasmapheresis followed by intravenous immunoglobulin. She did not have recurrence of paraneoplastic syndrome with maintenance rituximab every 6 months and daily low-dose prednisone. She succumbed to progressive systemic metastatic disease 4.5 years after her breast cancer diagnosis. This case shows that these antibodies can occur concurrently and cause clinical features, such as both neuromyelitis optica spectrum disorder and myelin oligodendrocyte glycoprotein antibody disease, in a patient with a singular type of cancer. We highlight the importance of testing for paraneoplastic etiology in cancer patients with radiographic menigoencephalomyelitis or meningitis with atypical symptoms of meningeal carcinomatosis and/or cerebrospinal fluid profile negative for leptomeningeal carcinomatosis.

Development and Application of a Multidimensional Database for the Detection of Quaternary Ammonium Compounds and Their Phase I Hepatic Metabolites in Humans.

The COVID-19 pandemic has led to significantly increased human exposure to the widely used disinfectants quaternary ammonium compounds (QACs). Xenobiotic metabolism serves a critical role in the clearance of environmental molecules, yet limited data are available on the routes of QAC metabolism or metabolite levels in humans. To address this gap and to advance QAC biomonitoring capabilities, we analyzed 19 commonly used QACs and their phase I metabolites by liquid chromatography-ion mobility-tandem mass spectrometry (LC-IM-MS/MS). In vitro generation of QAC metabolites by human liver microsomes produced a series of oxidized metabolites, with metabolism generally occurring on the alkyl chain group, as supported by MS/MS fragmentation. Discernible trends were observed in the gas-phase IM behavior of QAC metabolites, which, despite their increased mass, displayed smaller collision cross-section (CCS) values than those of their respective parent compounds. We then constructed a multidimensional reference SQLite database consisting of m/z, CCS, retention time (rt), and MS/MS spectra for 19 parent QACs and 81 QAC metabolites. Using this database, we confidently identified 13 parent QACs and 35 metabolites in de-identified human fecal samples. This is the first study to integrate in vitro metabolite biosynthesis with LC-IM-MS/MS for the simultaneous monitoring of parent QACs and their metabolites in humans.

Evaluating outcomes and toxicities for a newly implemented MRI-based brachytherapy program for cervical cancer.

OBJECTIVE: We report an updated analysis of the outcomes and toxicities of MRI-based brachytherapy for locally advanced cervical cancer from a U.S. academic center. METHODS: A retrospective review was performed on patients treated with MRI-based brachytherapy for cervical cancer. EBRT was standardly 45 Gy in 25 fractions with weekly cisplatin. MRI was performed with the brachytherapy applicator in situ. Dose specification was most commonly 7 Gy for 4 fractions with optimization aim of D90 HR-CTV EQD2 of 85-95 Gyα/ß=10 Gy in 2 implants each delivering 2 fractions. RESULTS: Ninety-eight patients were included with median follow up of 24.5 months (IQR 11.9-39.8). Stage IIIA-IVB accounted for 31.6% of cases. Dosimetry results include median GTV D98 of 101.0 Gy (IQR 93.3-118.8) and HR-CTV D90 of 89 Gy (IQR 86.1-90.6). Median D2cc bladder, rectum, sigmoid, and bowel doses were 82.1 Gy (IQR 75.9-88.0), 65.9 Gy (IQR 59.6-71.2), 65.1 Gy (IQR 57.7-69.6), and 55 Gy (IQR 48.9-60.9). Chronic grade 3+ toxicities were seen in the bladder (8.2%), rectosigmoid (4.1%), and vagina (1.0%). Three-year LC, PFS, and OS were estimated to be 84%, 61.7%, and 76.1%, respectively. CONCLUSION: MRI-based brachytherapy demonstrates excellent local control and acceptable rates of high-grade morbidity. These results are possible in our population with relatively large volume primary tumors and extensive local disease.

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry.

Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.

Thoracic Reirradiation with Stereotactic Body Radiation Therapy (SBRT) for Recurrent Advanced Non-Small Cell Lung Cancer (NSCLC).

PURPOSE: Non-small cell lung cancer (NSCLC) local control remains suboptimal with rates around 75%. Stereotactic body radiation therapy (SBRT) is an option for isolated local recurrences of small-volume recurrences. This study investigates the safety and efficacy of 60 Gy in 8 fractions in large-volume local recurrences. METHODS AND MATERIALS: We conducted a retrospective chart review of patients treated with salvage SBRT for NSCLC lung parenchymal recurrence between July 2013 and February 2020. Reirradiation prescribed dose was 60 Gy in 8 fractions using the SBRT technique. The primary endpoint was local control at most recent follow-up or death. Secondary endpoints included overall survival, disease-free interval, cancer-specific survival, and treatment related toxicities. RESULTS: Seven patients met inclusion criteria. Median follow up time was 38 months (18.1-72.4). Median age was 67 years (63-80). Median time to reirradiation was 18.2 months (7.3-28.6). Retreatment median ITV was 57.9 cc (15.8-344.6), and PTV median was 113.6 cc (38.3-506.9). Local control was maintained in 4 of 7 patients (57.1%). Two of the 7 patients (28.6%) remained alive. Median disease-free interval was 22.5 months (11-65). Three of 7 patients (42.9%) had grade 2 toxicities. One patient (14.3%) had a grade 3 rib/chest wall toxicity with concurrent disease recurrence invading the chest wall. CONCLUSION: This study reports that SBRT of 60 Gy in 8 fractions was delivered safely and effectively to large volume recurrent NSCLC previously treated with radiation therapy. The disease-free interval of nearly 2 years is meaningful for patients' quality of life and duration of time off systemic therapy.

Prevalence of trauma history and symptoms in patients who have received vaginal brachytherapy as part of their endometrial cancer treatment.

OBJECTIVE: Vaginal brachytherapy (VBT) is an essential component of curative intent treatment for many patients with endometrial cancer. The prevalence of trauma history in this population is unknown and important to understand considering VBT requires patients to have an instrument vaginally inserted while in the vulnerable lithotomy position. We aim to identify patients treated with intracavitary VBT and collect survey data to assess trauma endpoints. METHODS: We retrospectively identified patients with endometrial cancer who underwent intracavitary VBT at our institution between 01/2017 and 08/2022. Patients were mailed and/or electronically mailed a survey that included demographics, psychosocial background, and validated trauma surveys to be filled out as they relate to their trauma experiences prior to VBT and again considering any trauma symptomatology related to VBT. Electronic medical record review was performed. Descriptive statistics as well as multivariate analysis were performed. RESULTS: 206 patients met inclusion criteria, 66 (32.1%) of whom returned the survey and were included for analysis. Thirty-two percent of patients self-reported a personal history of any prior mental health diagnosis. Eighty-eight percent of patients screened positive for a history of trauma exposure, 23% endorsed symptoms of PTSD related to their VBT experience, and 5% screened positive for a likely PTSD diagnosis from VBT. CONCLUSION: A majority of included patients had a history of trauma exposure prior to VBT. In a subset of patients, VBT re-induced trauma and was considered to be an independent traumatic event. This study highlights the importance of practicing trauma informed care, particularly in this patient population.

Elucidating the impact of bacterial lipases, human serum albumin, and FASII inhibition on the utilization of exogenous fatty acids by Staphylococcus aureus.

IMPORTANCE: Incorporation of host-derived exogenous fatty acids (eFAs), particularly unsaturated fatty acids (UFAs), by Staphylococcus aureus could affect the bacterial membrane fluidity and susceptibility to antimicrobials. In this work, we found that glycerol ester hydrolase (Geh) is the primary lipase hydrolyzing cholesteryl esters and, to a lesser extent, triglycerides and that human serum albumin (HSA) could serve as a buffer of eFAs, where low levels of HSA facilitate the utilization of eFAs but high levels of HSA inhibit it. The fact that the type II fatty acid synthesis (FASII) inhibitor, AFN-1252, leads to an increase in UFA content even in the absence of eFA suggests that membrane property modulation is part of its mechanism of action. Thus, Geh and/or the FASII system look to be promising targets to enhance S. aureus killing in a host environment by restricting eFA utilization or modulating membrane properties, respectively.

MRI-guided Real-time Online Gated Stereotactic Body Radiation Therapy for Liver Tumors.

BACKGROUND: Liver tumors are commonly encountered in oncology. The study aimed to assess the impact of magnetic resonance imaging (MRI)-guided stereotactic body radiation therapy (SBRT) (MRgSBRT) on disease-related outcomes and the toxicity profile. METHODS: Patients who received MRgSBRT from 2019 to 2021 for primary and metastatic liver tumors were included in this analysis. The protocol for treatment simulation included Gadoxetate disodium injection followed by a single-dimensional post-exhale MRI (0.35-T MRI linear accelerator) and computed tomography simulation. The patient demographics and treatment-related outcomes were assessed. The time-to-event curves were analyzed for freedom from local progression (FFLP) and overall survival (OS). RESULTS: A total of 35 patients were eligible for analysis with a median age of 70 years (range 25 to 95). The median follow-up was 19.4 months (range 1 to 37 mo). The one-year OS was 77.7%, with an estimated 3 years of 47.9%. Patients with the locally controlled disease had a better median OS of 27.8 months (95% CI [23.8-31.6]) compared with 13.5 months (95% CI [5.6-21.3], P =0.007) in patients with local disease progression. The 1-year FFLP was 95.6%, and 3-year estimated FFLP was 87.1%. Patients who received a radiation dose of biologically equivalent dose≥100 Gy had FFLP of 30.9 months (95% CI [28.7-33.1]) compared with 13.3 months (95% CI [5.3-21.3], P =0.004) in patients who received <100 Gy biologically equivalent dose. CONCLUSION: MRI-guided SBRT provides optimal local control, associated with improved OS in a heavily morbid, pretreated older cohort of patients with reasonable safety profiles.

High-throughput analysis of lipidomic phenotypes of methicillin-resistant Staphylococcus aureus by coupling in situ 96-well cultivation and HILIC-ion mobility-mass spectrometry.

Antimicrobial resistance is a major threat to human health as resistant pathogens spread globally, and the development of new antimicrobials is slow. Since many antimicrobials function by targeting cell wall and membrane components, high-throughput lipidomics for bacterial phenotyping is of high interest for researchers to unveil lipid-mediated pathways when dealing with a large number of lab-selected or clinical strains. However, current practice for lipidomic analysis requires the cultivation of bacteria on a large scale, which does not replicate the growth conditions for high-throughput bioassays that are normally carried out in 96-well plates, such as susceptibility tests, growth curve measurements, and biofilm quantitation. Analysis of bacteria grown under the same condition as other bioassays would better inform the differences in susceptibility and other biological metrics. In this work, a high-throughput method for cultivation and lipidomic analysis of antimicrobial-resistant bacteria was developed for standard 96-well plates exemplified by methicillin-resistant Staphylococcus aureus (MRSA). By combining a 30-mm liquid chromatography (LC) column with ion mobility (IM) separation, elution time could be dramatically shortened to 3.6 min for a single LC run without losing major lipid features. Peak capacity was largely rescued by the addition of the IM dimension. Through multi-linear calibration, the deviation of retention time can be limited to within 5%, making database-based automatic lipid identification feasible. This high-throughput method was further validated by characterizing the lipidomic phenotypes of antimicrobial-resistant mutants derived from the MRSA strain, W308, grown in a 96-well plate.

Elucidating the Impact of Bacterial Lipases, Human Serum Albumin, and FASII Inhibition on the Utilization of Exogenous Fatty Acids by Staphylococcus aureus.

Staphylococcus aureus only synthesizes straight-chain or branched-chain saturated fatty acids (SCFAs or BCFAs) via the type II fatty acid synthesis (FASII) pathway, but as a highly adaptive pathogen, S. aureus can also utilize host-derived exogenous fatty acids (eFAs), including SCFAs and unsaturated fatty acids (UFAs). S. aureus secretes three lipases, Geh, sal1, and SAUSA300_0641, which could perform the function of releasing fatty acids from host lipids. Once released, the FAs are phosphorylated by the fatty acid kinase, FakA, and incorporated into the bacterial lipids. In this study, we determined the substrate specificity of S. aureus secreted lipases, the effect of human serum albumin (HSA) on eFA incorporation, and the effect of FASII inhibitor, AFN-1252, on eFA incorporation using comprehensive lipidomics. When grown with major donors of fatty acids, cholesteryl esters (CEs) and triglycerides (TGs), Geh was found to be the primary lipase responsible for hydrolyzing CEs, but other lipases could compensate for the function of Geh in hydrolyzing TGs. Lipidomics showed that eFAs were incorporated into all major S. aureus lipid classes and that fatty acid-containing HSA can serve as a source of eFAs. Furthermore, S. aureus grown with UFAs displayed decreased membrane fluidity and increased production of reactive oxygen species (ROS). Exposure to AFN-1252 enhanced UFAs in the bacterial membrane, even without a source of eFAs, indicating a FASII pathway modification. Thus, the incorporation of eFAs alters the S. aureus lipidome, membrane fluidity, and ROS formation, which could affect host-pathogen interactions and susceptibility to membrane-targeting antimicrobials.

mzapy: An Open-Source Python Library Enabling Efficient Extraction and Processing of Ion Mobility Spectrometry-Mass Spectrometry Data in the MZA File Format.

Analysis of ion mobility spectrometry (IMS) data has been challenging and limited the full utility of these measurements. Unlike liquid chromatography-mass spectrometry, where a plethora of tools with well-established algorithms exist, the incorporation of the additional IMS dimension requires upgrading existing computational pipelines and developing new algorithms to fully exploit the advantages of the technology. We have recently reported MZA, a new and simple mass spectrometry data structure based on the broadly supported HDF5 format and created to facilitate software development. While this format is inherently supportive of application development, the availability of core libraries in popular programming languages with standard mass spectrometry utilities will facilitate fast software development and broader adoption of the format. To this end, we present a Python package, mzapy, for efficient extraction and processing of mass spectrometry data in the MZA format, especially for complex data containing ion mobility spectrometry dimension. In addition to raw data extraction, mzapy contains supporting utilities enabling tasks including calibration, signal processing, peak finding, and generating plots. Being implemented in pure Python and having minimal and largely standardized dependencies makes mzapy uniquely suited to application development in the multiomics domain. The mzapy package is free and open-source, includes comprehensive documentation, and is structured to support future extension to meet the evolving needs of the MS community. The software source code is freely available at https://github.com/PNNL-m-q/mzapy.

Evaluating Software Tools for Lipid Identification from Ion Mobility Spectrometry-Mass Spectrometry Lipidomics Data.

The unambiguous identification of lipids is a critical component of lipidomics studies and greatly impacts the interpretation and significance of analyses as well as the ultimate biological understandings derived from measurements. The level of structural detail that is available for lipid identifications is largely determined by the analytical platform being used. Mass spectrometry (MS) coupled with liquid chromatography (LC) is the predominant combination of analytical techniques used for lipidomics studies, and these methods can provide fairly detailed lipid identification. More recently, ion mobility spectrometry (IMS) has begun to see greater adoption in lipidomics studies thanks to the additional dimension of separation that it provides and the added structural information that can support lipid identification. At present, relatively few software tools are available for IMS-MS lipidomics data analysis, which reflects the still limited adoption of IMS as well as the limited software support. This fact is even more pronounced for isomer identifications, such as the determination of double bond positions or integration with MS-based imaging. In this review, we survey the landscape of software tools that are available for the analysis of IMS-MS-based lipidomics data and we evaluate lipid identifications produced by these tools using open-access data sourced from the peer-reviewed lipidomics literature.

LipidOz enables automated elucidation of lipid carbon-carbon double bond positions from ozone-induced dissociation mass spectrometry data.

Lipids play essential roles in many biological processes and disease pathology, but unambiguous identification of lipids is complicated by the presence of multiple isomeric species differing by fatty acyl chain length, stereospecifically numbered (sn) position, and position/stereochemistry of double bonds. Conventional liquid chromatography-mass spectrometry (LC-MS/MS) analyses enable the determination of fatty acyl chain lengths (and in some cases sn position) and number of double bonds, but not carbon-carbon double bond positions. Ozone-induced dissociation (OzID) is a gas-phase oxidation reaction that produces characteristic fragments from lipids containing double bonds. OzID can be incorporated into ion mobility spectrometry (IMS)-MS instruments for the structural characterization of lipids, including additional isomer separation and confident assignment of double bond positions. The complexity and repetitive nature of OzID data analysis and lack of software tool support have limited the application of OzID for routine lipidomics studies. Here, we present an open-source Python tool, LipidOz, for the automated determination of lipid double bond positions from OzID-IMS-MS data, which employs a combination of traditional automation and deep learning approaches. Our results demonstrate the ability of LipidOz to robustly assign double bond positions for lipid standard mixtures and complex lipid extracts, enabling practical application of OzID for future lipidomics.

MZA: A Data Conversion Tool to Facilitate Software Development and Artificial Intelligence Research in Multidimensional Mass Spectrometry.

Modern mass spectrometry-based workflows employing hybrid instrumentation and orthogonal separations collect multidimensional data, potentially allowing deeper understanding in omics studies through adoption of artificial intelligence methods. However, the large volume of these rich spectra challenges existing data storage and access technologies, therefore precluding informatics advancements. We present MZA (pronounced m-za), the mass-to-charge (m/z) generic data storage and access tool designed to facilitate software development and artificial intelligence research in multidimensional mass spectrometry measurements. Composed of a data conversion tool and a simple file structure based on the HDF5 format, MZA provides easy, cross-platform and cross-programming language access to raw MS-data, enabling fast development of new tools in data science programming languages such as Python and R. The software executable, example MS-data and example Python and R scripts are freely available at https://github.com/PNNL-m-q/mza.

Spatiotemporal scaling changes in gait in a progressive model of Parkinson's disease.

Objective: Gait dysfunction is one of the most difficult motor signs to treat in patients with Parkinson's disease (PD). Understanding its pathophysiology and developing more effective therapies for parkinsonian gait dysfunction will require preclinical studies that can quantitatively and objectively assess the spatial and temporal features of gait. Design: We developed a novel system for measuring volitional, naturalistic gait patterns in non-human primates, and then applied the approach to characterize the progression of parkinsonian gait dysfunction across a sequence of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) treatments that allowed for intrasubject comparisons across mild, moderate, and severe stages. Results: Parkinsonian gait dysfunction was characterized across treatment levels by a slower stride speed, increased time in both the stance and swing phase of the stride cycle, and decreased cadence that progressively worsened with overall parkinsonian severity. In contrast, decreased stride length occurred most notably in the moderate to severe parkinsonian state. Conclusion: The results suggest that mild parkinsonism in the primate model of PD starts with temporal gait deficits, whereas spatial gait deficits manifest after reaching a more severe parkinsonian state overall. This study provides important context for preclinical studies in non-human primates studying the neurophysiology of and treatments for parkinsonian gait.