Journal of Translational Medicine

Skeletal muscle regeneration is a cardinal feature of muscle pathologies and is crucial for post-exercise recovery and traumatic sports injuries. Regeneration of damaged muscle in humans is a prolonged process and is accompanied by pain and physical dysfunction, highlighting the unmet need for effective interventions to accelerate the regenerative process. Through cellular and preclinical models, we have previously identified nicotinamide (NAM) and pyridoxine (PN) as potent stimulators of Muscle Stem Cells (MuSCs). Herein we investigated if a combination of NAM and PN could enhance MuSC activity and improve muscle regeneration in healthy volunteers during recovery from eccentric contractions. MethodsThis randomized, double-blind, placebo-controlled trial enrolled male participants aged 18-50 years supplemented daily with 714mg NAM and 19mg PN (NAM/PN) or placebo for 8 days following unilateral eccentric muscle contractions using Neuromuscular Electrical Stimulation (NMES). MuSC was quantified by immunohistofluorescence on vastus lateralis muscle biopsies. Results39 out of 43 enrolled participants completed the study. Supplementation of NAM/PN was well tolerated and increased blood concentrations of NAM and PN vitamers. The NMES protocol caused myofiber necrosis and triggered a strong MuSC response. After 8 days, the number of Pax7, MyoD, and myogenin positive cells per damaged fiber was significantly higher in NAM/PN vs placebo groups (+29-67%). NAM/PN also increased the proportion of regenerating fibers re-expressing embryonic myosin (+37%). ConclusionDaily oral NAM/PN supplementation following eccentric muscle damaging contractions enhances MuSC activity and accelerates muscle regeneration. These findings provide new possibilities for targeted therapeutic interventions in muscle repair. Trial registrationNCT04874662 One Sentence SummaryMuscle regeneration is enhanced by nicotinamide and pyridoxine supplementation, accelerating recovery and offering therapeutic potential.

ObjectiveMouse Patient-Derived Xenograft (PDX) models are essential tools for evaluating experimental therapeutics. Baylor College of Medicine (BCM) established a PDX Core to provide technical support and infrastructure for PDX-based research. To manage PDX collections effectively, de-identified patient clinical and omics data, as well as PDX-related information and omics data, must be curated and stored. Data must then be analyzed and visualized for each case. To enhance PDX collection management and data dissemination, the BCM Biomedical Informatics Core created the BCM PDX Portal (https://pdxportal.research.bcm.edu/). Materials and MethodsPatient clinical data are abstracted from medical records for each PDX and stored in a central database. Annotations are reviewed by a clinician and de-identified. PDX development method and biomarker expression are annotated. DNAseq, RNAseq, and proteomics data are processed through standardized pipelines and stored. PDX gene expression (mRNA/protein), copy number alterations, and mutations can be searched in combination with clinical markers to identify models potentially useful as a PDX cohort. ResultsPDX collection management and PDX selection of models for drug evaluation are facilitated using the PDX Portal. DiscussionTo improve the translational effectiveness of PDX models, it is beneficial to use a tool that captures and displays multiple features of the patient clinical and molecular data. Selection of models for studies should be representative of the patient cohort from which they originated. ConclusionThe BCM PDX Portal is a highly effective PDX collection management tool allowing data access in a visual, intuitive manner thereby enhancing the utility of PDX collections.

Image-based machine learning holds great promise for facilitating clinical care, however the datasets often used for model training differ from the interventional clinical trial-based findings frequently used to inform treatment guidelines. Here, we draw on longitudinal imaging of psoriasis patients undergoing treatment in the Ultima 2 clinical trial (NCT02684357), including 2,700 body images with psoriasis area severity index (PASI) annotations by uniformly trained dermatologists. An image-processing workflow integrating clinical photos of multiple body regions into one model pipeline was developed, which we refer to as the One-Step PASI framework due to its simultaneous body detection, lesion detection, and lesion severity classification. Group-stratified cross-validation was performed with 145 deep convolutional neural network models combined in an ensemble learning architecture. The highest-performing model demonstrated a mean absolute error of 3.3, Lins concordance correlation coefficient of 0.86, and Pearson correlation coefficient of 0.90 across a wide range of PASI scores comprising disease classifications of clear skin, mild, and moderate-to-severe disease. Within-person, time-series analysis of model performance demonstrated that PASI predictions closely tracked the trajectory of physician scores from severe to clear skin without systematically over or underestimating PASI scores or percent changes from baseline. This study demonstrates the potential of image processing and deep learning to translate otherwise inaccessible clinical trial data into accurate, extensible machine learning models to assess therapeutic efficacy.

PURPOSEIdentifying reliable predictors of immunotherapeutic response in melanoma remains an outstanding challenge. Existing transcriptomic and proteomic profiling methods for the tumor-immune microenvironment (TIME) are costly and may not faithfully capture modifications actively impacting tumor behavior. Here, we present a non-destructive, single-cell approach combining Raman spectroscopy and machine learning (ML) that enables rapid cell profiling and therapeutic response prediction. METHODSWe analyzed single-cell Raman spectra of mouse and human melanoma cell lines alongside nine melanoma patient-derived samples with known resistance profiles to targeted and immunotherapeutic inhibitors bemcentinib, cabozantinib, dabrafenib, nivolumab, and a combination of nivolumab and relatlimab. We assessed cell phenotyping classification and treatment resistance using random forests and feature importance analysis. For patient samples, we constructed a two-stage evaluation workflow to determine clinical drug resistance through aggregated single-cell predictions and identified corresponding highly variant spectral signatures using computational methods adapted from single-cell RNA sequencing methods. RESULTSIn cell lines, our approach achieved >96% differentiation accuracy across tumor microenvironment cell types and induced functional phenotypes. Persistent (drug-resistant) cells formed subclusters based on genetic mutations rather than sample origin, with Raman signatures reflecting biochemical changes relevant to therapeutic pathways. For patient samples, our workflow correctly inferred resistance likelihoods for 30 of 33 clinically-relevant patient-drug combinations (91% accuracy). CONCLUSIONSingle-cell Raman spectroscopy combined with machine learning offers a scalable, prognostic platform to predict therapeutic resistance likelihood, with further potential to advance clinical, multi-omic biomarker efforts for melanoma. Our approach may improve first-and second-line therapy selection assessments for precision medicine by providing rapid, non-destructive prediction of therapeutic response based on cellular spectral profiles. Context SummaryO_ST_ABSKey objectiveC_ST_ABSCan label-free, single-cell Raman spectroscopy and machine learning approach accurately profile melanoma cell states and therapeutic resistance likelihood to targeted and immunotherapeutic agents? Knowledge generatedRaman spectroscopy with machine learning differentiated tumor microenvironment cell types and functional phenotypes with >96% accuracy in cell lines. When applied to patient-derived metastatic melanoma samples, the approach correctly inferred patient response to a panel of targeted and immunotherapeutic inhibitors with 91% accuracy (30 of 33 cases). High-likelihood persistent and sensitive cells across diverse patients exhibited recurrent spectral features. RelevanceSingle-cell Raman-based profiling supports functional-diagnostic assessment or resistance likelihood and may contribute to improved therapeutic selection and precision oncology strategies for melanoma patients.

ObjectivesWe investigated whether palmar cooling alters inflammatory responses following a single session of high-intensity eccentric exercise. We hypothesized that palmar cooling during rest intervals would attenuate maladaptive inflammatory responses while preserving beneficial immune adaptations necessary for muscle repair and recovery. MethodsIn this randomized interventional study, 20 healthy adults were matched by sex and one-repetition maximum (1RM) for bicep curls. Participants performed 10 sets at 70% 1RM, receiving either palmar cooling at 14{o}C or a thermoneutral control at 30{o}C during 3-minute inter-set rest periods. Whole blood was collected at baseline, immediately post-exercise, and on post-exercise days 1, 2, and 4 for comprehensive immune profiling with mass cytometry. Blood lactate and pain scores were also recorded. ResultsExercise induced broad immunosuppression that was significantly attenuated in the palmar cooling group by 2 days post-exercise (AUC=0.79, p=0.03). The cooled group had decreased immunosuppressive activity and increased inflammatory innate immune mechanisms in the cooled group. Palmar cooling also significantly reduced lactate levels compared to controls (p=0.024). ConclusionPalmar cooling at 14{o}C during rest intervals effectively modulated the immune response to high-intensity exercise and reduced lactate accumulation. These findings suggest palmar cooling may serve as a promising intervention to mitigate exercise-induced immunosuppression and support recovery. Trial identifierNCT07215338 (retrospectively registered). Summary BoxO_ST_ABSWhat is already known on this topicC_ST_ABSHigh intensity eccentric exercise contributes to physiological heat stress which induces significant immune alterations that can lead to a transient period of immunosuppression and increased incidence of respiratory tract infections. What this study addsPalmar cooling resulted in cell-type-specific alterations in innate and adaptive immune cell signaling activity, particularly decreasing immunosuppressive cell responses while enhancing inflammatory innate immune mechanisms implicated in pathogen defense. How this study might affect research, practice or policyPalmar cooling may serve as an effective intervention for managing exercise-induced immunosuppression and supporting recovery in athletes. Integration of palmar cooling techniques into athletic training regimens and rehabilitation protocols can ultimately enhance exercise performance and reduce the adverse effects associated with high-intensity exercise.

BackgroundThe hepatocellular carcinoma is one of the leading causes of cancer-related mortality and is characterized by high heterogeneity and subsequently adaptation by developing resistance to current treatments. In this scenario the application of individualized models is crucial to understand the potential of approved therapies. Recently, we established a series of individual cell lines derived from patients who developed HCC on different entities, serving as a platform for individual approaches. In this study, we classified the LC4 cells derived from the center region of a HCC with underlying HIV-HCV co-infection, by using deep analysis on the pathway regulation level. MethodsWe employed DEG analysis, followed by pathway analysis to characterize the preservation level of the LC4 cells and the level of adoption. Next, we classify the model, by employing healthy donor samples, commonly used HCC cell lines and global RNAseq data sets. ResultsWe showed that the LC4 cells reflect significant characteristics of the parental region, including the replication of the immuno-suppressive and the proliferative milieu. The LC4 cells exhibit a metabolic reprogramming characterized by the downregulation of drug-metabolizing CYP enzymes compared to healthy individuals, indicating a transition to alternate metabolic pathways. Moreover, we identified common Biomarkers in the parental tissue, global datasets and the LC4 cells. ConclusionWe showed that the LC4 cell line is applicable as an individual model for pre-clinical testing of treatment regimens in HCC driven research.

Background and AimsPrimary liver cancer, predominantly hepatocellular carcinoma (HCC), has limited therapeutic options. While mutation-derived neoantigen vaccine holds promise, its success is hindered by low antigen availability. This study explores transcriptome-derived neoantigens (neoantigen-encoding tumor-specific transcripts, neoTSTs) in HCC, characterizing their features, generation mechanisms, and therapeutic potential. Approach and ResultsWe analyzed RNA-seq data from 1,013 liver cancer patients and constructed a multi-layered reference dataset. Using a customized pipeline, we identified an average of 60 neoTSTs per patient, significantly surpassing mutation-derived neoantigens (neoMuts). NeoTSTs exhibited higher population frequencies, with 73.1% providing multiple epitopes, and were validated through mass spectrometry and HLA transgenic mouse models. Mechanistically, neoTSTs were generated via retained introns, transposable element activation, HNF4A-regulated alternative promoters, and de novo transmembrane domain (TMD) generation. Single-cell analysis revealed neoTSTs cover >75% of tumor cells and identified antigen-presenting cancer-associated fibroblasts (apCAFs) that enriched in immunotherapy responders and amplified CD4 T-cell responses via MHC-II presentation. In murine HCC models, neoTST vaccination outperformed neoMuts, inducing dual MHC-I/II activation and significant tumor growth inhibition. ConclusionsNeoTSTs represent a superior neoantigen source in HCC, compensating for the limitations of mutation-derived targets. Their abundance, sharedness, and dual MHC pathway activation highlight their potential for personalized immunotherapy, particularly in low-TMB tumors. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=178 SRC="FIGDIR/small/692877v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@1bedfedorg.highwire.dtl.DTLVardef@5f6c95org.highwire.dtl.DTLVardef@d1deb5org.highwire.dtl.DTLVardef@743e85_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundThe Neutrophil to lymphocyte ratio (NLR) has emerged as a pivotal biomarker in the fields of inflammation and immunity research. NLR, calculated from routine blood counts, reflects the balance between neutrophil-driven innate immunity and lymphocyte-mediated adaptive responses. In recent decades, a growing body of research has underscored the application of this field across diverse medical disciplines, including oncology, cardiology, immunology, and other areas of medicine. However, there is a paucity of comprehensive studies that objectively map the evolving landscape, hotspots, and research frontiers of global NLR studies. MethodsA comprehensive search was conducted using the Web of Science Core Collection to identify articles and reviews related to NLR from 2004 to 2023. A robust bibliometric approach was employed, utilizing tools such as VOSviewer, CiteSpace, and Bibliometrix (R-tool for R Studio). Analyses were focused on publication outputs, country/institutional collaborations, journal and author productivity, and keyword co-occurrence. This approach provides both quantitative and qualitative perspectives on the NLR field. ResultsThe bibliometric review under consideration included a total of 14,877 publications, which indicates a marked upward trend in annual publications. The United States and China contributed the most papers and maintained leading positions in international collaborations and citation influence. A close examination of the most prolific journals in the field, including Frontiers in Oncology, Medicine, and PLOS One, has revealed their role as pivotal dissemination outlets. A comprehensive analysis of the literature revealed that keywords pertaining to oncology, immunotherapy, inflammation, prognosis, and clinical outcome exhibited a marked prevalence in research themes related to NLR. Of particular note is the escalating convergence of these themes with those concerning cancer immunotherapy, cardiovascular risk, and systemic inflammatory response syndromes. Co-citation and cluster analyses revealed an increasing connection between research on the nucleotide-binding leucine-rich repeat (NLR) proteins and emerging fields, including tumor immunology, metabolic disease, and personalized medicine. Network mapping revealed an increase in intercontinental collaborations and identified key researchers who are influencing the discipline. ConclusionsThis is the inaugural bibliometric and visual analysis to methodically map the global research landscape of neutrophil-to-lymphocyte ratio. The study reveals a thriving and multidisciplinary research landscape, with significant concentrations in oncology and immunology, as well as noteworthy advancements into emerging domains such as immunotherapy and precision medicine. By unveiling collaboration patterns, identifying leading contributors, and examining keyword trends, this work offers indispensable guidance for scholars seeking to identify impactful research topics and establish strategic partnerships. These insights not only illuminate the current status of NLR research but also forecast its promising directions, inviting further exploration and cross-disciplinary innovation in the years ahead.

Purpose: Chemoradiotherapy (CRT) for human papillomavirus-related oropharyngeal cancer (HPV+ OPC) causes substantial treatment-related toxicity, with well-known adverse effects on quality of life (QoL), weight loss, and self-reported physical functioning. However, its impact on objectively measured cardiorespiratory fitness is unknown. This study examined changes in cardiorespiratory fitness, body composition, grip strength, and patient-reported outcomes in patients with HPV+ OPC undergoing CRT. Methods: We invited 20 patients with HPV+ OPC scheduled for CRT (age: 61.2 {+/-} 7.1 years, female: n=4) to complete assessments at three timepoints: pre-CRT (baseline), 2-weeks post-CRT, and 8-weeks post-CRT. Cardiorespiratory fitness was assessed using a maximal incremental cardiopulmonary exercise test (CPET). Body composition was estimated using segmental bioelectrical impedance analysis. QoL was assessed using the EORTC QLQ-C30 and QLQ-H&N43, and physical activity was self-reported using the International Physical Activity Questionnaire-Short Form. The primary outcome was change in oxygen consumption at the anaerobic threshold ([V]O2 at AT) measured during CPET; an objective, effort-independent marker of cardiorespiratory fitness. Results: Mean [V]O2 at AT declined from 16.0 {+/-} 3.8 ml/kg/min at baseline to 12.0 {+/-} 3.4 ml/kg/min at 2-weeks post-CRT (adjusted mean change: -4.2, 95% CI: -5.4 to -3.0 ml/kg/min) and remained low at 8-weeks post-CRT. Peak oxygen consumption ([V]O2peak: -7.4, -9.3 to -5.4 ml/kg/min), body mass (-8.5, -10.7 to -6.2 kg), fat-free mass (-6.4, -7.7 to -5.0 kg), grip strength (-4.1, -7.2 to -0.99 kg), global health status (-26.9, -39.2 to -14.6 points), fatigue (49.8, 33.7 to 65.8 points), and several disease-specific symptoms were also adversely affected at 2-weeks post-CRT and remained impaired at 8 weeks. Conclusion: This is the first study to estimate the impact of CRT on cardiopulmonary fitness in patients with HPV+ OPC. Cardiorespiratory fitness declined by ~25% following CRT and remained reduced at 8-weeks. Targeted interventions to mitigate these adverse physiological effects warrants further investigation.

BackgroundFibrosis in most organs has proven to be an critical factor related to high risk of morbidity and mortality, but an adequate assessment of fibrosis severity is still challenging. This study tried to evaluate fibrosis severity through a fibrosis transcriptional signature. MethodsA fibrosis transcriptional signature was developed through an integrated analysis of multiple expression profiling datasets of human organs with fibrosis-related diseases. A fibrosis severity score for each sample was the calculated through gene set variation analysis (GSVA), and its role in evaluating fibrosis severity was then analyzed. ResultsTen expression profiling datasets of human tissues with organ failure were integrated with robust rank aggregation method, and a fibrosis severity score consisting of 149 genes. Most of those included genes were involved in fibrogenic pathways. GSEA analysis revealed that fibrosis transcriptional signature was significantly enriched in the fibrogenic tissues. Additionally, we found that fibrosis transcriptional signature could effectively differentiate fibrosis tissues and non-fibrosis tissues. ConclusionThis study developed an useful fibrosis transcriptional signature involved in fibrosis-related diseases. This fibrosis transcriptional signature is helpful in precisely evaluating the fibrosis severity in common organs at the transcriptional level.

BackgroundBased on our previous study, we have identified ZNF180, a zinc finger protein, as a pro-tumorigenic regulator in primary melanoma and a marker for poor prognosis. Herein, we report that ZNF180-regulated pathway, hence ZNF180-regulome, underlies resistance towards immune checkpoint inhibitions (ICIs). MethodsTo investigate regulatory roles of ZNF180 to confer these immune suppressive phenotypes, we performed ZNF180 knock-down in melanoma cells in vitro with different genetic backgrounds, namely A375 (BRAF-mutant) and SKMEL147 (NRAS-mutant) cells, and performed RNA- and ATAC-sequencing. We performed integrative analysis of RNA- and ATAC-sequencing data with publicly available sequencing data from ICI-treated cohorts to construct comprehensive model of ZNF180-regulome and its impacts on immune microenvironment. Further, we performed ZNF180 silencing in immune competent Yumm1.7 murine model to confirm the changes in immune microenvironments. ResultsZNF180-regulome was predictive of ICI responses in independent bulk sequencing cohorts, and ZNF180+ tumors persisted after the therapy with immune-suppressive features such as MHC-I loss and CD155 expressions, the primary ligand to TIGIT inhibitory receptor. Further, ZNF180 silencing revealed its regulations on AP-1 transcription factors to drive melanoma reprogramming towards de-differentiated MITFlowAXLhigh cells, an established melanoma subtypes associated with recurrence and ICI resistance. In tandem, we observed that ZNF180+ tumor neighborhood significantly excluded with CD4 T-cells in metastatic tumor, and its silencing in immune competent murine model increased CD4 helper T-cell infiltrations with significant tumor regression in vivo. ConclusionCollectively, these results indicate ZNF180 is a tumor intrinsic regulator of melanoma plasticity to drive de-differentiated phenotypes with immune-suppressive features including loss of immunogenicity, T-cell inhibitory signals through TIGIT/CD155 checkpoint and exclusion of CD4 helper T-cells. As ZNF180-regulome manifests in non-metastatic melanoma in contrast to the current focus of standard-of-care ICI on the metastatic disease, these results establish ZNF180-regulome as a biomarker and novel therapeutic avenue for early-stage, non-metastatic melanoma to intervene ICI resistance.

BackgroundThe emergence of immune checkpoint inhibitors (ICIs) has transformed the treatment landscape of metastatic melanoma. However, despite its success, reliable biomarkers for predicting primary resistance are not available in clinical practice. This study seeks to identify predictors of primary resistance based on novel gene expression signatures using pre-treatment multidimensional profiling in melanoma patients. MethodsThe transcriptomic profile of the tumor microenvironment was analyzed using tissue samples from 46 metastatic cutaneous melanoma patients collected prior to the initiation of ICIs therapy. A primary resistance predictive model was trained with the Discovery FFPE RNA-seq sub-cohort and validated using an independent external cohort of 54 samples. Additionally, liquid biopsy samples from peripheral blood mononuclear cells were analyzed in 8 patients using single-cell RNA sequencing (scRNA-seq) and in 46 patients using flow cytometry to characterize the distribution and abundance of the different immune cell populations. ResultsWe identified an 82-gene transcriptomic signature composed of tumor- and immune-related genes that stratifies metastatic cutaneous melanoma patients based on primary resistance to ICIs, with key markers including CXCL13, WDR63, MZB1, FDCSP, IGKC and GRIK3. This signature was enriched for pathways related to B cell activation and immune cell communication and achieved an AUC of 0.814 in predictive modeling. Immune deconvolution guided by scRNA-seq revealed four immune cell subsets (Plasma cells, Pre-B cells, Memory CD4 T cells, and Naive CD4 T cells) as prognostic indicators of resistance. Some of these subpopulations were validated by flow cytometry before and after treatment. ConclusionsWe propose a transcriptomic biomarker signature that accurately predicts primary resistance to ICIs in metastatic cutaneous melanoma. Through the integration of immune deconvolution with circulating immune cell profiles, we derived an ImmuneSignature linked to patient survival. By combining these approaches, we provide a framework for enhancing the prediction of immunotherapy outcomes and offer a novel strategy for identifying therapeutic targets to overcome resistance. Our findings lead to more effective and personalized immunotherapy guidance.

IntroductionNon-alcoholic steatohepatitis (NASH) is characterized by excessive accumulation of fat, accompanied by inflammation and liver injury. NASH can lead to chronic conditions like fibrosis and cirrhosis, and has an elevated risk of progressing to hepatocellular carcinoma (HCC). Currently there are no FDA-approved drugs for the treatment of NASH. ObjectivesOur discovery of Uttroside B (Utt-B), a phytosaponin isolated from Solanum nigrum Linn., which exhibits remarkable anti-HCC potential, has gained global recognition and is currently a US-FDA-designated orphan drug against HCC. The present study highlights Utt-B as an anti-NASH molecule, by utilizing a High-Fat-Diet murine model, and as an inhibitor to the progression of NASH to HCC, using a streptozotocin-induced steatohepatitis-derived HCC animal model, thereby warranting its further validation as a propitious candidate drug molecule against NASH and NASH-induced HCC. MethodsHigh fat diet-induced NASH and streptozotocin-induced steatohepatitis-derived HCC were developed in C57BL/6 mice. Utt-B was administered intraperitoneally. q-PCR, immunoblotting and staining techniques such as Haematoxylin and eosin, Oil Red O, Sirius Red and Massons Trichrome, were performed to assess the therapeutic potency of Utt-B against NASH. Nanostring n-Counter analysis was conducted to verify the anti-fibrotic potential of Utt-B in NASH-induced HCC mouse model. ResultsUtt-B ameliorates the pathological features such as, steatosis, hepatocyte ballooning and inflammation associated with NASH. Utt-B up-regulates the expression of autophagy markers ATG7, Beclin-1 and LC-III and down-regulates the expression of -SMA, the indicator protein for the activation of hepatic stellate cells. Utt-B hinders the development of fibrosis and halts the progression of NASH to HCC in NASH-induced HCC mouse model. ConclusionOur investigation reveals that Utt-B effectively alleviates NASH and abrogates its progression to HCC. As no treatment options are currently available against NASH, our findings are very relevant and strengthen the prospect of developing Utt-B as a potent drug for the treatment of NASH and NASH-induced HCC. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/622394v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1d637dcorg.highwire.dtl.DTLVardef@ed6b34org.highwire.dtl.DTLVardef@1195acaorg.highwire.dtl.DTLVardef@197b072_HPS_FORMAT_FIGEXP M_FIG C_FIG

ObjectiveTo determine if psychophysiologic symptom relief therapy (PSRT) will reduce symptom burden in patients suffering from post-acute sequelae of COVID-19 (PASC) who had mild/moderate acute COVID-19 disease without objective evidence of organ injury. Patients and MethodsTwenty-three adults under the age of 60 with PASC for at least 12 weeks following COVID-19 infection were enrolled in an interventional cohort study conducted via virtual platform between May 18, 2021 and August 7, 2022. Participants received PSRT during a 13 week (approximately 44 hour) course. Participants were administered validated questionnaires at baseline and at 4, 8, and 13 weeks. The primary outcome was change in somatic symptoms from baseline, measured using the Somatic Symptom Scale-8 (SSS-8). ResultsThe median duration of symptoms prior to joining the study was 267 days (IQR: 144, 460). The mean SSS-8 score of the cohort decreased from baseline by 8.5 (95% CI: 5.7-11.4), 9.4 (95% CI: 6.9-11.9), and 10.9 (95% CI: 8.3-13.5) at 4, 8, and 13 weeks respectively (all p<0.001). Participants also experienced statistically significant improvements across secondary outcomes including changes in dyspnea, fatigue, and pain (all p<0.001). ConclusionPSRT may effectively decrease symptom burden in patients suffering from PASC without evidence of organ injury. The study was registered on clinicaltrials.gov (NCT 04854772).

BackgroundThe polymerized type I collagen (PTIC) is a {gamma}-irradiated mixture of pepsinized porcine type I collagen and polyvinylpyrrolidone (PVP). It has immunomodulatory properties. However, the receptor and signaling pathway through which it exerts its therapeutic effects has not yet been identified. AimTo evaluate LAIR-1 as a potential receptor for PTIC and the signaling pathway evoked by ligand-receptor binding. MethodsLAIR-1 binding assay was performed by incubating various concentrations of recombinant human LAIR-1 with native type I collagen or PTIC. Macrophages M1- derived from THP-1 cells were cultured with 2-10% PTIC for 24 h. Cell lysates from THP- 1, monocytes-like cells (MLCs), M1, M1+IFN-{gamma}, M1+LPS, and 2 or 10% PTIC treated M1 were analyzed by western blot for the transcription factors NF-{kappa}B (p65), p38, STAT-1, and pSTAT-1. Cytokines, Th1 cells, and M1/M2 macrophages were analyzed by luminometry and flow cytometry from blood samples of symptomatic COVID-19 outpatients on treatment with intramuscular administration of PTIC. ResultsPTIC binds LAIR-1 with a similar affinity to native collagen. This binding decreases STAT-1 signaling IFN-{gamma}-induced and IL-1{beta} expression in M1 macrophages by down-regulating STAT-1 phosphorylation. Moreover, intramuscular PTIC treatment of symptomatic COVID-19 outpatients decreased at statistically significant levels the percentage of M1 macrophages and cytokines (IP-10, MIF, eotaxin, IL-8, IL-1RA, and M- CSF) associated with STAT-1 transcription factor and increased M2 macrophages and Th1 cells. The downregulation of inflammatory mediators was related to better oxygen saturation and decreased dyspnea, chest pain, cough, and chronic fatigue syndrome in the acute phase of infection and the long term. ConclusionPTIC is an agonist of LAIR-1 and down-regulates STAT-1 phosphorylation. PTIC could be relevant for treating STAT-1-mediated inflammatory diseases, including COVID-19 and long COVID

BackgroundMyocarditis has emerged as a rare but lethal Immune checkpoint inhibitor (ICI)-associated toxicity. However, the exact mechanism for ICI related myocarditis remains underexplored; and the specific therapeutic targets is still lacking. In this study, we used scRNA-seq to characterize the transcriptomic profiles of single cells from the peripheral blood mononuclear cell (PBMC) of ICI related myocarditis during fulminant myocarditis and disease recovery. MethodsPBMC samples were taken from the patient during fulminant ICI related myocarditis and after disease remission. Cells were isolated from blood samples by density gradient centrifugation over Ficoll-Paque. Single-cell RNA sequencing with 10X genomics was performed. Subpopulation determination, functional analysis, single-cell trajectory and cell-cell interaction analysis were carried out afterwards. ResultsWe presented the altered landscape of immune cells and differential genes in ICI related myocarditis during the disease activity and remission using scRNA-seq. Substantial immune cell composition and intercellular communication were found to be altered. Monocyte, NK cell as well as B cell subpopulations contributed to the regulation of innate immunity and inflammation in ICI related myocarditis. T cell subpopulations highly expressed genes associated with PD-1 inhibitor resistance and hyper-progressor. At last, the intercellular communication in ICI related myocarditis was significantly dysregulated. ConclusionBy identifying altered pathways and highlighting a catalog of marker genes, this study has revealed the diversity of cellular populations in ICI related myocarditis, marked by their distinct transcriptional profiles and biological functions. Our investigation would shed light on the pathophysiological mechanism and potential therapeutic targets of ICI related myocarditis in continuous exploration.

IntroductionLow-dose computed tomography (LDCT) lung cancer screening has significantly enhanced early detection and patient survival rates in the population at risk. Current screening methods, that primarily rely on LDCT imaging, will very likely benefit from molecular biomarkers to achieve a more comprehensive, accurate, personalized and non-invasive risk assessment leveraging multimodal tools. We present a novel open access multimodal (imaging, proteomics and demographic) dataset designed to provide an available research resource on LDCT-based early lung cancer detection. The dataset includes annotated screening LDCT scans and plasma proteomics generated by proximity extension assay (Olink) platform. MethodsThe dataset integrates data from control screened individuals without nodules or with benign nodules, and LDCT-diagnosed lung cancer individuals, matched by sex, age and time between image and sample collection. Both radiological and molecular signatures were collected within a six month window, providing detailed insights into disease progression. Nodules were considered as lung cancer cases if biopsy-confirmed lung cancer was diagnosed within 5 years after imaging, enabling the study of longitudinal biomarker evolution and its correlation with imaging findings. To complement the dataset, clinical and demographic data are also available in open access, providing a detailed overview of patient characteristics. The informed consent signed by the participants allows for unrestricted open access for requests directy or indirectly related to lung cancer research. ResultsThe dataset consists of annotated screening LDCT scans and plasma proteomics data measured with most of the Olink Target 96 platforms (1078 individual proteins across 12 panels focused on a specific area of disease or biology) for a total of 211 screening participants. There are 67 lung cancer patients, 68 matched controls with benign pulmonary nodules, 71 matched controls without nodules and 5 surgically excised false positive lesions. Experiments were performed to assess the technical quality and provide a proof-of-concept of usability of the dataset, showing the alignment with findings from previous published studies. ConclusionThis comprehensive dataset aims to facilitate research towards the development of personalized multimodal artificial intelligence models. We also aim to support the investigation of the relationship between imaging and molecular data, paving the way for more accurate understanding of early lung cancer biology. Finally, our open access dataset may help to develop or validate individualized risk prediction models that could significantly advance early lung cancer detection and intervention strategies.

ObjectiveThe proteolytic cleavage of membrane-bound proteins, ectodomain shedding, functionally expands the reservoire of proteins/peptides available for endocrine crosstalk, and metabolic regulation. However, the functional understanding of secreted proteoforms, including whether they act synergistically or antagonistically with their membrane precursors, is often unknown. We aimed to develop a novel viral vector based gene delivery platform enabling characterization of both membrane-bound and soluble proteoforms in adipocytes, independent of endogenous shedding. ResultsWe describe a novel platform, termed EctoShed, achieves expression of proteoforms of amine oxidase copper-containing 3 (AOC3) in adipocytes by capitalising on both the established lentiviral (LV) and AAV gene delivery systems, expressing full length or a soluble AOC3 mimic (m-sAOC3) isoforms. In vitro transduction of primary white adipocytes induced significant expression of both isoforms, retaining AOC3 enzymatic activity. In vivo delivery to inguinal white adipose tissue enabled depot-specific AOC3 expression and increased abundance of m-sAOC3 in the serum. Mice expressing m-sAOC3 exhibited reduced fat mass and fasting glucose levels. ConclusionEctoShed represents a versatile tool to dissect the functional roles of soluble proteoforms shed from adipocytes, enabling in vitro and in vivo applications in cardiometabolic health and disease.

Background and aimsMetabolic reprogramming represents as a pivotal hallmark for cancer, but TCA cycle in tumorigenesis and progression has long been neglected. Solute carrier (SLC) transporters mediate the transport of TCA cycle intermediates across membrane, but their functions in cancer pathogenesis remains unclear. Approaches & ResultsUsing integrated analysis of solute carrier (SLC) transporters for TCA cycle intermediates, we found that SLC13A2 was consistently downregulated in hepatocellular carcinoma (HCC) cells and liver tissues from human patients and heterogeneous mouse models. Adeno-associated virus (AAV)-transduced liver-specific knockout or overexpression of SLC13A2 promoted or ameliorated HCC progression in the primary mouse model, demonstrating that SLC13A2 served as a protective factor during HCC pathogenesis. SLC13A2 inhibited HCC cell proliferation by decreasing mitochondrial function via suppressed oxygen consumption and ATP production. Combined with metabolic flux analysis, we found that SLC13A2 imported citrate, which secreted acetyl-CoA as a precursor for the acetylation of pyruvate kinase muscle isozyme M2 (PKM2), which led to its protein degradation. Decreased activity of pyruvate kinase depleted pyruvate for the TCA cycle, thus inhibiting amino acid synthesis and nucleotide metabolism. Additionally, a decrease in nuclear PKM2 protein transduced to reprogrammed gene transcription for cell proliferation and metabolism which is required for tumor growth. ConclusionsThis study revealed that citrate transported by SLC13A2 acts as a signal to disrupt metabolic homeostasis for tumor growth and suggests potential drug targets for HCC therapy. graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC="FIGDIR/small/591017v2_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@80c95eorg.highwire.dtl.DTLVardef@124750corg.highwire.dtl.DTLVardef@809ab4org.highwire.dtl.DTLVardef@12cbe74_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundTranscutaneous cervical vagus nerve stimulation (tcVNS) is a non-invasive neuromodulation that can influence autonomic function and emotional regulation by activating vagal pathways. Similarly, slow breathing exercises and aromatherapy are likewise known to enhance parasympathetic activity and reduce stress. However, the combined effects of multimodal sensory neuromodulation (e.g., combining electrical, mechanical respiratory, and olfactory stimuli) on autonomic nervous system activity, emotional stress, and prefrontal cortical activation remain underexplored. Further research is needed to clarify its potential benefits for stress regulation. ObjectiveWe investigated the effects of tcVNS, breathing training, and aroma inhalation--individually and combined--on heart rate variability (HRV), self-reported emotional stress, and prefrontal cortex (PFC) activation measured by functional near-infrared spectroscopy (fNIRS). MethodsTwenty-three healthy adult participants underwent four conditions in a within-subject design: (1) Resting (baseline control, 5 minutes), (2) tcVNS stimulation (a custom-built transcutaneous cervical vagus nerve stimulator developed in-house at 25 Hz, 15 minutes) alone, (3) breathing + aroma (deep breathing exercise with calming aroma inhalation, 5 minutes) without tcVNS, and (4) combined tcVNS + breathing + aroma (15 minutes). Each condition lasted the specified duration, during which HRV indices (SDNN, RMSSD, pNN50, Poincare SD1 and SD2, LF/HF ratio, approximate entropy (ApEn), and short-term fractal 1) were measured from PPG recordings, and changes in PFC oxyhemoglobin concentration were monitored with NIRSIT Quest (OBELAB, Seoul, South Korea) fNIRS system. Participants rated their emotional stress (state anxiety) after each condition. Statistical analyses used repeated-measures ANOVA and paired t-tests (with false discovery rate correction) to compare conditions. ResultsBoth tcVNS and breathing+aroma conditions produced significant increases in HRV compared to resting baseline, and the combined tcVNS+breathing+aroma yielded the largest HRV enhancements. For example, SDNN (heart period variability) increased from 76.5{+/-}15.2 ms at rest to 109.5{+/-}18.7 ms with tcVNS (p=0.041, q=0.049) and to 121.1{+/-}20.3 ms with breathing+aroma (p<0.001, q=0.000), while the combined stimulation raised SDNN to 157.6{+/-}25.4 ms (p<0.001, q=0.001). Similar patterns were found in RMSSD, pNN50, SD1, and SD2, indicating augmented vagal tone. The combined condition significantly exceeded tcVNS-alone for these HRV metrics (all q<0.01). ApEn of HRV increased with tcVNS (from 1.05{+/-}0.10 to 1.23{+/-}0.14, p=0.006) and combined stimulation (q=0.052 vs. baseline), suggesting greater complexity under vagal stimulation, whereas breathing+aroma alone did not change ApEn. Self-reported emotional stress significantly decreased after all interventions, with the largest reduction in the combined tcVNS+breathing+aroma condition. Participants reported lower anxiety and worry, both remaining significant after FDR correction (q = .042). Additional reductions were observed in tension, restlessness, low mood, and stress reactivity (uncorrected p < .05), indicating a broad alleviation of negative affect consistent with the physiological findings. fNIRS revealed that breathing+aroma elicited increased PFC oxygenation bilaterally (mean {Delta}oxy-Hb +0.11 {micro}M, p<0.01 vs. rest), and combined stimulation produced an even larger PFC oxy-Hb increase (+0.19 {micro}M, p<0.001). tcVNS alone caused a mild PFC activation (+0.05 {micro}M, n.s.). PFC activation in the combined condition was significantly greater than in tcVNS alone and in breathing+aroma alone (p<0.05). ConclusionsMultimodal stimulation combining tcVNS with breathing and aroma yielded synergistic benefits, evidenced by robust increases in vagally mediated HRV, lower emotional stress, and heightened PFC activity. These findings suggest that engaging both peripheral and central pathways through combined neuromodulatory and behavioral interventions can potentiate autonomic regulation and stress reduction beyond what single modalities achieve. This novel approach highlights a promising, non-pharmacological strategy for enhancing stress resilience and emotional well-being via coordinated autonomic and prefrontal modulation.