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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Prevalence of erythromycin-resistant emm92 -type invasive group A streptococcal infections among injection drug users in West Virginia, United States, 2021–23

Abstract Background Increasing incidence of invasive group A Streptococcus (iGAS) disease has been reported in Europe and the USA over the past several years. Coupled with this are observations of higher rates of resistance to erythromycin and clindamycin. Objectives To characterize iGAS and pharyngitis isolates from West Virginia (WV), a US state outside of the national Active Bacteria Core surveillance purview, where risk factors associated with iGAS infections are prevalent. Methods Seventy-seven invasive group A Streptococcus isolates were collected from 67 unique patients at the J.W. Ruby Memorial Hospital Clinical Microbiology Laboratory in WV from 2021 to 2023. Invasive isolates and 20 unique pharyngitis isolates were tested for clindamycin and erythromycin susceptibility in the clinical laboratory. Patient demographic and clinical information was retrieved from patient electronic health records. Isolates were further characterized based on emm subtype and detection of MLSB resistance determinants. Results Twenty-six (39%) isolates were of a single emm92 type. All emm92 isolates were uniformly erythromycin/clindamycin resistant with inducible or constitutive MLSB resistance imparted by the plasmid-borne erm(T) gene. The majority of emm92 infections were associated with adult patients who reported IV drug use, whereas no pharyngitis infections were caused by an emm92 strain. Overall, 51 (76%) of the 67 iGAS isolates were determined to carry MLSB resistance. Conclusions Isolates of emm92 type (clonal subtype emm92.0) were associated with iGAS infections in adult IV drug users, but not with paediatric pharyngitis, and were uniformly resistant to erythromycin and clindamycin.

Powell, Lillie M.↗
DOE OSTI2025

Matrix Metalloproteinases as Candidate Antigenic Determinants for Anti‐Tumor Autoantibodies in Human Ovarian Cancer: A Post Hoc Analysis

Circulating antibodies in patients with cancer can facilitate the identification of accessible epitopes on autoantigens expressed by tumors. To identify previously unrecognized protein targets in ovarian cancer, we computationally assessed a heptapeptide consensus motif (VPELGHE, flanked by two cysteine residues yielding a cyclic nonapeptide under oxidizing conditions) previously discovered via phage display-based epitope mapping of autoantibodies in patients. Eight proteins associated with ovarian cancer encompass amino acid sequences similar to the consensus motif and were, therefore, considered as candidate native autoantigens. Among these candidate targets, however, matrix metalloproteinase 14 (MMP14) demonstrates gene expression that is both high and negatively correlated with survival in ovarian cancer patient cohorts. MMP14 protein levels are also stable in tumor versus non-tumor tissues. Moreover, the corresponding heptapeptide mimic in MMP14 occurs within an α-helical secondary structural element observed in its catalytic domain. These findings demonstrate that a subset of patient-derived autoantibodies may interact with a previously unknown antigenic epitope found in MMP14 and other MMPs, thereby providing opportunities for the development of new targeted agents.

Biochemistry & Molecular Biology↗
DOE OSTI2022

Analysis of implant loss risk factors after simultaneous guided bone regeneration: A retrospective study of 5404 dental implants

Abstract Purpose The purpose was to analyze the risk factors for implant loss after simultaneous guided bone regeneration (GBR). Materials and Methods Patients who underwent implant placement with simultaneous GBR between January 2011 and December 2018 were screened for this study. The cumulative survival rate (CSR) was calculated using the life table method. Log‐rank test and Kaplan–Meier survival estimates were used to identify potential risk factors for implant loss. The association between the investigated variables and implant loss was determined using hazard ratios (HRs) obtained from a multivariate Cox regression analysis. Results A total of 3973 patients with 5404 implants were included in this study. The CSRs of the implants at 1, 5, and 10 years were 99.6%, 98.9%, and 98.7%, respectively. Male patient (HR = 2.94, 95% CI: 1.41–6.14), periodontitis (HR = 4.26, 95% CI: 2.05–9.86), tissue‐level implants (HR = 3.02, 95% CI: 1.30–6.98), narrow implants (HR = 2.71, 95% CI: 1.12–6.57), and implant length ≤10 mm (HR = 2.91, 95% CI: 1.41–6.02) significantly increased the risk of implant loss ( p < 0.05). The risk of implant loss was significantly higher in the maxillary posterior region (HR = 2.26, 95% CI: 1.04–4.90) than in the maxillary anterior region ( p < 0.05). Compared to Straumann, Nobel (HR = 4.07, 95% CI: 1.75–9.44) and other implant systems (HR = 14.23, 95% CI: 4.32–46.85) showed a significantly higher risk of implant loss ( p < 0.05). Conclusion Male patient, periodontitis, maxillary posterior region, Nobel implant system, other implant systems, tissue‐level implants, narrow implants, and implant length ≤10 mm were considered risk factors for implant loss after simultaneous GBR.

Shen, Xiaoting↗
DOE OSTI2021

Implementation of rapid diagnostics assays for detection of histoplasmosis and cryptococcosis in central american people living with HIV

Abstract Objectives Histoplasmosis and cryptococcosis are important public health problems in people living with HIV (PLHIV) in Central America. Conventional laboratory assays, based on microscopy and culture, are not optimal for the diagnosis of either disease. However, antigen (Ag) assays are rapid and highly accurate for the diagnosis of these infections. Methods Laboratory surveillance of PLHIV was carried out in four hospitals in Panama, Honduras and Nicaragua, between 2015 and 2019. Detection of Histoplasma antigens in urine was performed by enzyme immunoassay (EIA), and Cryptococcus antigen detection in sera and cerebrospinal fluid specimens was performed by lateral flow assay (LFA). Results A total of 4,453 PLHIV with clinical suspicion of histoplasmosis ( n = 1,343) or cryptococcosis ( n = 3,110; 2,721 sera and 389 CSF) were tested. Of 1,343 patients suspected of having histoplasmosis, 269 (20%) were Histoplasma Ag positive. Of 3,110 patients tested using the Cryptococcus Ag assay, 329 (11%) were positive. Honduras reported the highest positivity rates (32% for Histoplasma Ag, and 16% for Cryptococcus Ag); Panama reported the largest number of patients testing positive using the Histoplasma Ag assay ( n = 201); and Nicaragua reported the largest number of patients testing positive using the Cryptococcus Ag assay ( n = 170). Conclusion Here, we show how the implementation of rapid diagnostics assays impacted case detection and was useful for the care of people with advanced HIV. Rapid and accurate diagnosis could reduce mortality associated with histoplasmosis and cryptococcosis in PLHIV.

Caceres, Diego H.↗
DOE OSTI2025

Microbial vitamin biosynthesis links gut microbiota dynamics to chemotherapy toxicity

ABSTRACT Dose-limiting toxicities pose a major barrier to cancer treatment. While preclinical studies show that the gut microbiota influences and is influenced by anticancer drugs, data from patients paired with careful side effect monitoring remains limited. Here, we investigate capecitabine (CAP)-microbiome interactions through longitudinal metagenomic sequencing of stool from 56 advanced colorectal cancer patients. CAP significantly altered the gut microbiome, enriching for menaquinol (vitamin K2) biosynthesis genes. Transposon library screens, targeted gene deletions, and media supplementation revealed that menaquinol biosynthesis protectsEscherichia colifrom drug toxicity. Stool menaquinol gene and metabolite levels were associated with decreased peripheral sensory neuropathy. Machine learning models trained in this cohort predicted toxicities in an independent cohort. Taken together, these results suggest treatment-associated increases in microbial vitamin biosynthesis serve a chemoprotective role for bacterial and host cells. Further, our findings provide a foundation for in-depth mechanistic dissection, human intervention studies, and extension to other cancer treatments. IMPORTANCE Side effects are common during the treatment of cancer. The trillions of microbes found within the human gut are sensitive to anticancer drugs, but the effects of treatment-induced shifts in gut microbes for side effects remain poorly understood. We profiled gut microbes in colorectal cancer patients treated with capecitabine and carefully monitored side effects. We observed a marked expansion in genes for producing vitamin K2 (menaquinone). Vitamin K2 rescued gut bacterial growth and was associated with decreased side effects in patients. We then used information about gut microbes to develop a predictive model of drug toxicity that was validated in an independent cohort. These results suggest that treatment-associated increases in bacterial vitamin production protect both bacteria and host cells from drug toxicity, providing new opportunities for intervention and motivating the need to better understand how dietary intake and bacterial production of micronutrients like vitamin K2 influence cancer treatment outcomes.

Microbiology↗
DOE OSTI2022

Effect of vaccination on the case fatality rate for COVID-19 infections 2020–2021: multivariate modelling of data from the US Department of Veterans Affairs

Objectives: To evaluate the benefits of vaccination on the case fatality rate (CFR) for COVID-19 infections. Design, setting and participants: The US Department of Veterans Affairs has 130 medical centres. We created multivariate models from these data—339 772 patients with COVID-19—as of 30 September 2021. Outcome measures: The primary outcome for all models was death within 60 days of the diagnosis. Logistic regression was used to derive adjusted ORs for vaccination and infection with Delta versus earlier variants. Models were adjusted for confounding factors, including demographics, comorbidity indices and novel parameters representing prior diagnoses, vital signs/baseline laboratory tests and outpatient treatments. Patients with a Delta infection were divided into eight cohorts based on the time from vaccination to diagnosis. A common model was used to estimate the odds of death associated with vaccination for each cohort relative to that of unvaccinated patients. Results: 9.1% of subjects were vaccinated. 21.5% had the Delta variant. 18 120 patients (5.33%) died within 60 days of their diagnoses. The adjusted OR for a Delta infection was 1.87±0.05, which corresponds to a relative risk (RR) of 1.78. The overall adjusted OR for prior vaccination was 0.280±0.011 corresponding to an RR of 0.291. Raw CFR rose steadily after 10–14 weeks. The OR for vaccination remained stable for 10–34 weeks. Conclusions: Our CFR model controls for the severity of confounding factors and priority of vaccination, rather than solely using the presence of comorbidities. Our results confirm that Delta was more lethal than earlier variants and that vaccination is an effective means of preventing death. After adjusting for major selection biases, we found no evidence that the benefits of vaccination on CFR declined over 34 weeks. We suggest that this model can be used to evaluate vaccines designed for emerging variants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Altered Regional Homogeneity and Functional Connectivity during Microlesion Period after Deep Brain Stimulation in Parkinson’s Disease

Background. Patients with Parkinson’s disease (PD) undergoing deep brain electrode implantation experience a temporary improvement in motor symptoms before the electrical stimulation begins. We usually call this the microlesion effect (MLE), but the mechanism behind it is not clear. Purpose. This study aimed to assess the alterations in brain functions at the regional and whole-brain levels, using regional homogeneity (ReHo) and functional connectivity (FC), during the postoperative microlesion period after deep brain stimulation (DBS) in PD patients. Method. Resting-state functional MRI data were collected from 27 PD patients before and after the first day of DBS and 12 healthy controls (HCs) in this study. The ReHo in combination with FC analysis was used to investigate the alterations of regional brain activity in all the subjects. Results. There were increased ReHo in the basal ganglia-thalamocortical circuit (left supplementary motor area and bilateral paracentral lobule), whereas decreased ReHo in the default mode network (DMN) (left angular gyrus, bilateral precuneus), prefrontal cortex (bilateral middle frontal gyrus), and the cerebello-thalamocortical (CTC) circuit (Cerebellum_crus2/1_L) after DBS. In addition, we also found abnormal FC in the lingual gyrus, cerebellum, and DMN. Conclusion. Microlesion of the thalamus caused by electrode implantation can alter the activity of the basal ganglia-thalamocortical circuit, prefrontal cortex, DMN, and CTC circuit and induce abnormal FC in the lingual gyrus, cerebellum, prefrontal cortex, and DMN among PD patients. The findings of this study contribute to the understanding of the mechanism of MLE.

Luo, Bei↗
DOE OSTI2023

COVID-19 Outcomes by Cancer Status, Site, Treatment, and Vaccination

Background: Studies have shown an increased risk of severe SARS-CoV-2–related (COVID-19) disease outcome and mortality for patients with cancer, but it is not well understood whether associations vary by cancer site, cancer treatment, and vaccination status. Methods: Using electronic health record data from an academic medical center, we identified a retrospective cohort of 260,757 individuals tested for or diagnosed with COVID-19 from March 10, 2020, to August 1, 2022. Of these, 52,019 tested positive for COVID-19 of whom 13,752 had a cancer diagnosis. We conducted Firth-corrected logistic regression to assess the association between cancer status, site, treatment, vaccination, and four COVID-19 outcomes: hospitalization, intensive care unit admission, mortality, and a composite “severe COVID” outcome. Results: Cancer diagnosis was significantly associated with higher rates of severe COVID, hospitalization, and mortality. These associations were driven by patients whose most recent initial cancer diagnosis was within the past 3 years. Chemotherapy receipt, colorectal cancer, hematologic malignancies, kidney cancer, and lung cancer were significantly associated with higher rates of worse COVID-19 outcomes. Vaccinations were significantly associated with lower rates of worse COVID-19 outcomes regardless of cancer status. Conclusions: Patients with colorectal cancer, hematologic malignancies, kidney cancer, or lung cancer or who receive chemotherapy for treatment should be cautious because of their increased risk of worse COVID-19 outcomes, even after vaccination. Impact: Additional COVID-19 precautions are warranted for people with certain cancer types and treatments. Further, significant benefit from vaccination is noted for both cancer and cancer-free patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Novel Anti-LY6G6D/CD3 T-Cell–Dependent Bispecific Antibody for the Treatment of Colorectal Cancer

Abstract New therapeutics and combination regimens have led to marked clinical improvements for the treatment of a subset of colorectal cancer. Immune checkpoint inhibitors have shown clinical efficacy in patients with mismatch-repair–deficient or microsatellite instability–high (MSI-H) metastatic colorectal cancer (mCRC). However, patients with microsatellite-stable (MSS) or low levels of microsatellite instable (MSI-L) colorectal cancer have not benefited from these immune modulators, and the survival outcome remains poor for the majority of patients diagnosed with mCRC. In this article, we describe the discovery of a novel T-cell–dependent bispecific antibody (TDB) targeting tumor-associated antigen LY6G6D, LY6G6D-TDB, for the treatment of colorectal cancer. RNAseq analysis showed that LY6G6D was differentially expressed in colorectal cancer with high prevalence in MSS and MSI-L subsets, whereas LY6G6D expression in normal tissues was limited. IHC confirmed the elevated expression of LY6G6D in primary and metastatic colorectal tumors, whereas minimal or no expression was observed in most normal tissue samples. The optimized LY6G6D-TDB, which targets a membrane-proximal epitope of LY6G6D and binds to CD3 with high affinity, exhibits potent antitumor activity both in vitro and in vivo. In vitro functional assays show that LY6G6D-TDB–mediated T-cell activation and cytotoxicity are conditional and target dependent. In mouse xenograft tumor models, LY6G6D-TDB demonstrates antitumor efficacy as a single agent against established colorectal tumors, and enhanced efficacy can be achieved when LY6G6D-TDB is combined with PD-1 blockade. Our studies provide evidence for the therapeutic potential of LY6G6D-TDB as an effective treatment option for patients with colorectal cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Single reader between-cases AUC estimator with nested data

The area under the receiver operating characteristic curve (AUC) is widely used in evaluating diagnostic performance for many clinical tasks. It is still challenging to evaluate the reading performance of distinguishing between positive and negative regions of interest (ROIs) in the nested-data problem, where multiple ROIs are nested within the cases. To address this issue, we identify two kinds of AUC estimators, within-cases AUC and between-cases AUC. We focus on the between-cases AUC estimator, since our main research interest is in patient-level diagnostic performance rather than location-level performance (the ability to separate ROIs with and without disease within each patient). Another reason is that as the case number increases, the number of between-cases paired ROIs is much larger than the number of within-cases ROIs. We provide estimators for the variance of the between-cases AUC and for the covariance when there are two readers. We derive and prove the above estimators’ theoretical values based on a simulation model and characterize their behavior using Monte Carlo simulation results. We also provide a real-data example. Moreover, we connect the distribution-based simulation model with the simulation model based on the linear mixed-effect model, which helps better understand the sources of variation in the simulated dataset.

Health Care Sciences & Services↗
DOE OSTI2022

In search of autophagy biomarkers in breast cancer: Receptor status and drug agnostic transcriptional changes during autophagy flux in cell lines

Autophagy drives drug resistance and drug-induced cancer cell cytotoxicity. Targeting the autophagy process could greatly improve chemotherapy outcomes. The discovery of specific inhibitors or activators has been hindered by challenges with reliably measuring autophagy levels in a clinical setting. We investigated drug-induced autophagy in breast cancer cell lines with differing ER/PR/Her2 receptor status by exposing them to known but divergent autophagy inducers each with a unique molecular target, tamoxifen, trastuzumab, bortezomib or rapamycin. Differential gene expression analysis from total RNA extracted during the earliest sign of autophagy flux showed both cell- and drug-specific changes. We analyzed the list of differentially expressed genes to find a common, cell- and drug-agnostic autophagy signature. Twelve mRNAs were significantly modulated by all the drugs and 11 were orthogonally verified with Q-RT-PCR (Klhl24, Hbp1, Crebrf, Ypel2, Fbxo32, Gdf15, Cdc25a, Ddit4, Psat1, Cd22, Ypel3). The drug agnostic mRNA signature was similarly induced by a mitochondrially targeted agent, MitoQ. In-silico analysis on the KM-plotter cancer database showed that the levels of these mRNAs are detectable in human samples and associated with breast cancer prognosis outcomes of Relapse-Free Survival in all patients (RSF), Overall Survival in all patients (OS), and Relapse-Free Survival in ER + Patients (RSF ER + ). High levels of Klhl24, Hbp1, Crebrf, Ypel2, CD22 and Ypel3 were correlated with better outcomes, whereas lower levels of Gdf15, Cdc25a, Ddit4 and Psat1 were associated with better prognosis in breast cancer patients. This gene signature uncovers candidate autophagy biomarkers that could be tested during preclinical and clinical studies to monitor the autophagy process.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Longitudinal analysis of host protein serum signatures of treatment and recovery in pulmonary tuberculosis

A better understanding of treatment progression and recovery in pulmonary tuberculosis (TB) infectious disease is crucial. This study analyzed longitudinal serum samples from pulmonary TB patients undergoing interventional treatment to identify surrogate markers for TB-related outcomes. Serum that was collected at baseline and 8, 17, 26, and 52 weeks from 30 TB patients experiencing durable cure were evaluated and compared using a sensitive LC-MS/MS proteomic platform for the detection and quantification of differential host protein signatures relative to timepoint. The global proteome signature was analyzed for statistical differences across the time course and between disease severity and treatment groups. A total of 676 proteins showed differential expression in the serum over these timepoints relative to baseline. Comparisons to understand serum protein dynamics at 8 weeks, treatment endpoints at 17 and 26 weeks, and post-treatment at 52 weeks were performed. The largest protein abundance changes were observed at 8 weeks as the initial effects of antibiotic treatment strongly impacted inflammatory and immune modulated responses. However, the largest number of proteome changes was observed at the end of treatment time points 17 and 26 weeks respectively. Post-treatment 52-week results showed an abatement of differential proteome signatures from end of treatment, though interestingly those proteins uniquely significant at post-treatment were almost exclusively downregulated. Patients were additionally stratified based upon disease severity and compared across all timepoints, identifying 461 discriminating proteome signatures. These proteome signatures collapsed into discrete expression profiles with distinct pathways across immune activation and signaling, hemostasis, and metabolism annotations. Insulin-like growth factor (IGF) and Integrin signaling maintained a severity signature through 52 weeks, implying an intrinsic disease severity signature well into the post-treatment timeframe. Previous proteome studies have primarily focused on the 8-week timepoint in relation to culture conversion status. While this study confirms previous observations, it also highlights some differences. The inclusion of additional end of treatment and post-treatment time points offers a more comprehensive assessment of treatment progression within the serum proteome. Examining the expression dynamics at these later time periods will help in the investigation of relapse patients and has provided indicative markers of response and recovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Facility Location Optimization Model for COVID-19 Resources

In response to anticipated resource shortfalls related to the treatment and testing of COVID-19, many communities are planning to build additional facilities to increase capacity. These facilities include field hospitals, testing centers, mobile manufacturing units, and distribution centers. In many cases, these facilities are intended to be temporary and are designed to meet an immediate need. When deciding where to place new facilities many factors need to be considered, including the feasibility of potential locations, existing resource availability, anticipated demand, and accessibility between patients and the new facility. In this project, a facility location optimization model was developed to integrate these key pieces of information to help decision makers identify the best place, or places, to build a facility to meet anticipated resource demands. The facility location optimization model uses the location of existing resources and the anticipated resource demand at each location to minimize the distance a patient must travel to get to the resource they need. The optimization formulation is presented below. The model was designed to operate at the county scale, where patients are grouped per county. This assumption can be modified to integrate other scales or include individual patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Filter Adapters for BI-PAP and CPAP Equipment

Researchers at Los Alamos National Laboratory are researching and designing technology intended to help reduce the exposure of patients and medical staff to pathogens, such as SARS-CoV-2, while providing medical staff the dexterity and flexible work conditions necessary to conduct routine and complex patient care on infected patients. This investigative technology would potentially enable hospitals to adapt, utilize, and repurpose existing Bilevel Positive Airway Pressure (BiPAP) or Continuous Positive Airway Pressure (C-PAP) equipment in the fight against COVID-19, which would potentially save hospitals significant money, reduce exposure to staff and patients, and increase the supply of critically needed devices at a time when supplies are scarce in the market place. A provisional patent has been filed on the technology and we are seeking a commercialization partner to license and further develop the product for commercial purposes, including processing the device through the FDA emergency use authorization or clearance process. One hospital system has indicated that upon FDA authorization or clearance, it would have interest in the product.

42 ENGINEERING↗
DOE OSTI2020

Air Evacuation Bridge

Researchers at Los Alamos National Laboratory are researching and designing technology intended to help reduce the exposure of patients and medical staff to pathogens, such as SARS-CoV-2 while providing medical staff the dexterity and flexible work conditions necessary to conduct routine and complex patient care on infected patients. This investigative technology would potentially enable hospitals to adapt, utilize, and re-purpose existing and otherwise infrequently used equipment in the fight against COVID-19, thereby saving hospitals significant money, reducing exposure to staff and patients, and increasing the supply of critically needed devices at a time when supplies are scarce in the market place. A provisional patent has been filed on the technology and we are seeking a commercialization partner to license and further develop the product for commercial purposes, including processing the device through the FDA authorization or clearance process. Once FDA has cleared the product, at least one hospital system has expressed interest in the experimental test components for use in their hospitals.

42 ENGINEERING↗
DOE OSTI2020

COVID-19 biomarkers based on respiratory microbiome content

COVID-19 patient care management would greatly benefit from new tools that enable accurate assessment of disease severity and stage, potentially enabling a personalized medicine approach. Detection of the SARS-CoV-2 virus itself, or even quantitation of viral loads, is not sufficient for accurate assessment of disease state beyond diagnosis of infection [eg, doi:10.1093/cid/ciaa344]. Levels of usual suspect protein biomarkers associated with host response to infection [eg, C-reactive protein (CRP); cytokines like IL-6, TNF-alpha, and IL-10; complement proteins like C3a and C5a], and of individual blood cell types (eg, leukocytes, lymphocytes, and subsets thereof), show limited correlation with disease severity and stage, with high patient-to-patient and study-to-study variability [eg, doi:10.1093/cid/ciaa248]. High-dimensional panels of biomarkers should have greater predictive power and resilience to unavoidable sources of variability; however, their assembly from proteins and cell types is extremely difficult, due to technical limitations in analyte measurement, especially with regard to starting material requirements and detection sensitivity. Host response profiling through Next Generation Sequencing (NGS) of gene expression patterns (ie, RNA-Seq) is a promising approach, but at the time of this project there were only two publicly available datasets of relevance [doi:10.1093/cid/ciaa203, doi:10.1080/22221751.2020.1747363], and close inspection of them revealed that each had at least one major flaw that severely undermined its value in supporting robust analysis of host response to SARS-CoV- 2 infection. However, the first of these studies [doi:10.1093/cid/ciaa203] fortuitously collected NGS data not only from host cells, but also from bacteria present in bronchoalveolar lavage fluid (BALF) recovered from COVID-19 patients; and because the respiratory microbiome (in terms of bacterial species content) is far less complex than the human transcriptome, the NGS data collected were sufficient to provide coverage depth supporting robust analysis. Surprisingly, the authors of the study did not carry out a detailed analysis of these data and their potential for revealing important new information about COVID-19. Therefore, we carried out a meta-analysis of the dataset as a first step in evaluating the potential for profiling of respiratory microbiome dynamics as a means of accurately assessing COVID-19 disease state.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A randomised sham-controlled study evaluating rTMS analgesic efficacy for postherpetic neuralgia

Context Postherpetic neuralgia (PHN) is a refractory neuropathic pain condition in which new treatment options are being developed. Repetitive transcranial magnetic stimulation (rTMS) may have the potential to reduce pain sensations in patients with postherpetic neuralgia. Objectives This study investigated the efficacy on postherpetic neuralgia by stimulating two potential targets, the motor cortex (M1) and the dorsolateral prefrontal cortex (DLPFC). Methods This is a double-blind, randomised, sham-controlled study. Potential participants were recruited from Hangzhou First People’s Hospital. Patients were randomly assigned to either the M1, DLPFC or Sham group. Patients received ten daily sessions of 10-Hz rTMS in 2 consecutive weeks. The primary outcome measure was visual analogue scale (VAS) assessed at baseline, first week of treatment (week 1), post-treatment (week 2), 1-week (week 4), 1-month (week 6) and 3-month (week 14) follow-up. Results Of sixty patients enrolled, 51 received treatment and completed all outcome assessments. M1 stimulation resulted in a larger analgesia during and after treatment compared to the Sham (week 2 – week 14, p < 0.005), as well as to the DLPFC stimulation (week 1 – week 14, p < 0.05). In addition to pain, sleep disturbance was significantly improved and relieved by targeting either the M1 or the DLPFC (M1: week 4 – week 14, p < 0.01; DLPFC: week 4 – week 14, p < 0.01). Moreover, pain sensations following M1 stimulation uniquely predicted improvement in sleep quality. Conclusion M1 rTMS is superior to DLPFC stimulation in treating PHN with excellent pain response and long-term analgesia. Meanwhile, M1 and DLPFC stimulation were equally effective in improving sleep quality in PHN. Clinical trial registration https://www.chictr.org.cn/ , identifier ChiCTR2100051963.

Wang, Huan↗
DOE OSTI2024

Towards verifiable cancer digital twins: tissue level modeling protocol for precision medicine

Cancer exhibits substantial heterogeneity, manifesting as distinct morphological and molecular variations across tumors, which frequently undermines the efficacy of conventional oncological treatments. Developments in multiomics and sequencing technologies have paved the way for unraveling this heterogeneity. Nevertheless, the complexity of the data gathered from these methods cannot be fully interpreted through multimodal data analysis alone. Mathematical modeling plays a crucial role in delineating the underlying mechanisms to explain sources of heterogeneity using patient-specific data. Intra-tumoral diversity necessitates the development of precision oncology therapies utilizing multiphysics, multiscale mathematical models for cancer. This review discusses recent advancements in computational methodologies for precision oncology, highlighting the potential of cancer digital twins to enhance patient-specific decision-making in clinical settings. We review computational efforts in building patient-informed cellular and tissue-level models for cancer and propose a computational framework that utilizes agent-based modeling as an effective conduit to integrate cancer systems models that encode signaling at the cellular scale with digital twin models that predict tissue-level response in a tumor microenvironment customized to patient information. Furthermore, we discuss machine learning approaches to building surrogates for these complex mathematical models. These surrogates can potentially be used to conduct sensitivity analysis, verification, validation, and uncertainty quantification, which is especially important for tumor studies due to their dynamic nature.

60 APPLIED LIFE SCIENCES↗