Relevant Markers Research Articles

Characterizing the Links Between Systemic Sclerosis and Breast Cancer.

Systemic sclerosis (SSc) is a complex, autoimmune connective tissue disease that affects multiple organs in the body, culminating in a variance of severity and a reduced quality of life. Breast cancer (BC) also affects patients with SSc, and these two conditions affect a similar demographic. With this systematic review, we aim to characterize the links between SSc and BC. Characterizing possible links between SSc and breast malignancies is important for advancing the understanding of SSc management and comorbidities. In this systematic meta-analysis, a comprehensive literature search was conducted in PubMed using relevant keywords and MeSH terms. The inclusion criteria included an English-language retrospective analysis that characterized patients with SSc with or without BC. Two independent reviewers assessed the study's eligibility based on predetermined criteria. Data extraction included patient antibody measurements, demographics (age and gender), family history, social behaviors (alcohol use and smoking history), concurrent condition treatments, and adverse effects following treatment. Thirteen articles were identified in the literature with relevant data on SSc and BC patients. Studies encompassed research about SSc patients with or without BC and relevant risk factors being measured. SSc was found to have a link to antibodies widely associated with cancer. Adverse treatment outcomes and concurrent conditions of BC were found when patients had a family history of SSc, BC, or an alcohol or smoking history. Our results suggest that the presence of antinuclear antibodies, anti-centromere antibodies, or anti-topoisomerase antibodies in SSc patients is correlated with BC. Out of the three antibodies, ATA seemed to be found more commonly in patients with SSc and malignancy across the studies. This systematic review discusses the link between SSc and BC through patients with relevant clinical markers, medical histories, and treatments. However, further research is necessary to advance the linkage between SSc and BC and determine whether management of one condition may prevent or alleviate the other.

Exploratory study of PD-1 inhibitors for recurrent meningioma.

26 Background: Meningiomas are the most common primary intracranial tumor. Some patients still have poorly controlled conditions after multiple surgeries and radiotherapies. More effective treatment methods are urgently needed. Previous studies have suggested that meningioma may shape an inhibitory tumor immune microenvironment and achieve immune escape by expressing programmed cell death ligand 1 (PD-L1) and other factors. Immune checkpoint inhibitors (ICIs) such as PD-1 inhibitors have shown promising efficacy in cases, but large-sample studies are needed to confirm these findings. Methods: Recurrent meningioma patients were included and treated with PD-1 inhibitors until tumor progression or intolerance occurred. The efficacy evaluation of enrolled patients used the Response Assessment in Neuro-Oncology (RANO) criteria. The primary endpoint was progression-free survival at 6 months (PFS-6), and secondary endpoints were progression-free survival at 12 months (PFS-12) and overall survival (OS). Adverse events were also recorded. Regular imaging follow-ups were conducted, and clinical characteristics were collected for survival analysis. Peripheral blood lymphocyte subsets and cytokines were detected before and after treatment, and tumor paraffin sections were used for immunohistochemical detection of relevant molecular markers. Results: A total of 35 recurrent meningioma patients (10 grade I, 14 grade II, 11 grade III) were included. Among all grades of patients, the median PFS was 9 months, PFS-6 was 63.6%, and PFS-12 was 47.6%. In grade I patients, the median PFS was 14 months, PFS-6 was 83%, and PFS-12 was 67%. In grade II/III patients, the median PFS was 9 months, PFS-6 was 58.9%, and PFS-12 was 42%. Among all grades of meningioma patients, PFS was significantly correlated with Ki-67 index (P = 0.021) and tumor progression times (P = 0.019). In grade II/III meningioma patients, PFS was only correlated with tumor progression times (P = 0.012). Twenty-five patients had stable disease, and seven patients had disease progression, with no patient achieving partial or complete remission. There was no significant correlation between tumor mutation burden (TMB) and PFS. Further immunohistochemical analysis of tumor tissues in three recurrent high-grade patients revealed varying degrees of increase in local CD3+, CD4+, CD8+ and PD-1+ T lymphocytes after treatment compared to baseline. Conclusions: Our study suggests that PD-1 inhibitors may prolong PFS in recurrent meningioma patients (especially high-grade) with good drug safety, warranting further exploration. Recurrent meningiomas have an immunosuppressive tumor microenvironment, and PD-1 inhibitors may improve the immune status of tumor microenvironments. Clinical trial information: NCT04728568 .

MiR-1915-3p regulates megakaryocytic and erythroid differentiation by targeting SOCS4

BackgroundProper control of the lineage bias of megakaryocytic and erythroid progenitor cells (MEPs) is of significant importance, the disorder of which will lead to abnormalities in the number and function of platelets and erythrocytes. Unfortunately, the signaling pathways regulating MEP differentiation largely remain to be elucidated. This study aimed to analyze the role and the underlying molecular mechanism of miR-1915-3p in megakaryocytic and erythroid differentiation.MethodsWe utilized miRNA mimics and miRNA sponge to alter the expression of miR-1915-3p in megakaryocytic and/or erythroid potential cells; siRNA and overexpression plasmid to change the expression of SOCS4, a potential target of miR-1915-3p. The expression of relevant surface markers was detected by flow cytometry. We scanned for miR-1915-3p target genes by mRNA expression profiling and bioinformatic analysis, and confirmed the targeting by dual-luciferase reporter assay, western blot and gain- and lost-of-function studies. One-way ANOVA and t-test were used to analyze the statistical significance.ResultsIn this study, overexpression or knockdown of miR-1915-3p inhibited or promoted erythroid differentiation, respectively. Accordingly, we scanned for miR-1915-3p target genes and confirmed that SOCS4 is one of the direct targets of miR-1915-3p. An attentive examination of the endogenous expression of SOCS4 during megakaryocytic and erythroid differentiation suggested the involvement of SOCS4 in erythroid/megakaryocytic lineage determination. SOCS4 knockdown lessened erythroid surface markers expression, as well as improved megakaryocytic differentiation, similar to the effects of miR-1915-3p overexpression. While SOCS4 overexpression resulted in reversed effects. SOCS4 overexpression in miR-1915-3p upregulated cells rescued the effect of miR-1915-3p.ConclusionsmiR-1915-3p acts as a negative regulator of erythropoiesis, and positively in thrombopoiesis. SOCS4 is one of the key mediators of miR-1915-3p during the differentiation of MEPs.

Patient-derived bladder cancer organoids show stable transcript expression along cultivation.

Bladder cancer (BC) is a prevalent malignancy with high recurrence rates. Patient-derived bladder cancer organoids (BCO) pose as a promising approach in both, disease modeling and individualized treatment screening. The aim of this study was to investigate the transcriptomic plasticity in BCOs as a function of cultivation times to define ideal time periods for the applications envisioned. Tumor samples of three patients with pathologically confirmed non-muscle invasive and muscle-invasive bladder cancer were included in this study and expanded as BCOs. RNA expression was investigated at different time periods of cells in culture using differential gene expression for overall transcript expression and quantitative real-time PCR (qRT-PCR) for pathological relevant markers. Differential gene expression of the BCO lines was investigated across passages 1-4, in passages 5-9 and above 9, respectively. Analysis of the entire transcriptome of the respective BCO lines revealed consistent profiles without significant alterations throughout the cultivation and expansion procedure. Notably, key transcripts like TP53, PIK3CA, BRCA1, among others, exhibited stable expression levels in the quantitative RNA analysis during the cultivation period. The robust transcriptome during BCO cultivation advocates for the use of earlier passages of BCOs in personalized medicine providing a time-efficient drug screening option to accelerate the counseling of patients' treatment options. Higher passages of BCOs still hold the potential in topics demanding for expanded cell masses such as medical device development and others.

62 Prognostic biomarker development using deep learning and spatial proteomics in papillary renal cell carcinoma

Abstract Background Papillary renal cell carcinoma (pRCC) is a prevalent but understudied kidney cancer pathology, constituting 15-20% of cases. While many patients achieve curative therapy using nephrectomy, others go on to develop progressive, metastatic disease with poor overall prognosis. In order to improve the current standards of care for pRCC patients, it is critical to identify new methods to identify high-risk patients likely to require more intense and risk-modulated follow-up. Our goals in this project are two-fold: (1) to identify prognostic patient clusters based on spatial architecture of tumor tissue, and (2) to identify a minimal subset of markers to accurately predict the defined clusters for clinical translation. Methods A tissue microarray of 100 pRCC patients was assayed using multiplex immunofluorescence with a 31-antibody panel with immune- and cancer-related proteins. We have developed novel algorithms to identify spatial neighborhoods and features. These features are then used to identify unsupervised clusters of patients. This new approach to classifying patients allows for a more specific and comprehensive description of each patient tumor’s spatial composition and association with diverse clinical outcomes. Next, we developed attention-based deep learning models capable of predicting these spatially-defined clusters directly from the underlying immunofluorescence images and subsequently profiled these for interpretability by retraining based on individual channels. We assessed each model iteratively on a validation set and a held-out test set for final model selection. We focussed on developing an accurate model with the minimal number of channels to enable development of a cost-efficient biomarker assay for the clinic. Results We performed a systematic analysis of the cellular and spatial phenotypes for each patient in our cohort and identified six (6) major spatial clusters. These clusters are based on the spatial neighborhood composition of the tumors (Fig 1A) and describe the composite effects of cell-cell interactions within a patient tumor. We identified one cluster in particular (cluster #6, mainly associated with spatial interaction of CD163+ macrophages) with a significantly worse prognosis than the other clusters. Using our advanced deep learning models, we have been able to achieve excellent validation accuracy in predicting a variety of clinical phenotypes and spatial features, including patient clusters and histological grade. We wished to then reduce the set of required features and began our efforts in predicting tumor vs. normal based on individual immunofluorescence channels and identified 6 channels with >75% individual predictive accuracy (Fig. 1B). Compositing all 6 markers further improves our accuracy to 90%. This success paves the way for exciting future prospects as we work to extend these efforts to identify a minimal clinically-applicable subset of protein markers. Conclusions The combination of computational spatial proteomics and deep learning models has the potential to identify new biomarkers specific to the spatial organization of patient tumors. We have identified a particular patient cluster with multiple associations with CD163+ macrophages demonstrating poor prognosis; selecting these patients may allow for tailored and more informed patient care. We are also working to enhance our deep learning models to circumvent the need for stepwise spatial analysis and, instead, allow for direct-from-image assessment of patients for particular spatial features indicative of various prognostic indicators. Our identified set of 6 markers serves as a basis for further refinements as we work to identify a minimal set of relevant markers able to predict various clinical outcomes from immunofluorescence imaging, offering a promising new avenue in the field of cancer pathology and biomarker development. DOD CDMRP Funding: yes

Early automated classification of neonatal hypoxic-ischemic encephalopathy − An aid to the decision to use therapeutic hypothermia

ObjectiveThe study aimed to address the challenge of early assessment of neonatal hypoxic-ischemic encephalopathy (HIE) severity to identify candidates for therapeutic hypothermia (TH). The objective was to develop an automated classification model for neonatal EEGs, enabling accurate HIE severity assessment 24/7. MethodsEEGs recorded within 6 h of life after perinatal anoxia were visually graded into 3 severity groups (HIE French Classification) and quantified using 6 qEEG markers measuring amplitude, continuity and frequency content. Machine learning models were developed on a dataset of 90 EEGs and validated on an independent dataset of 60 EEGs. ResultsThe selected model achieved an overall accuracy of 80.6% in the development phase and 80% in the validation phase. Notably, the model accurately identified 28 out of 30 children for whom TH was indicated after visual EEG analysis, with only 2 cases (moderate EEG abnormalities) not recommended for cooling. ConclusionsThe combination of clinically relevant qEEG markers led to the development of an effective automated EEG classification model, particularly suited for the post-anoxic latency phase. This model successfully discriminated neonates requiring TH. SignificanceThe proposed model has potential as a bedside clinical decision support tool for TH.

Multiparametric identification of putative senescent cells in skeletal muscle via mass cytometry.

Senescence is an irreversible arrest of the cell cycle that can be characterized by markers of senescence such as p16, p21, and KI-67. The characterization of different senescence-associated phenotypes requires selection of the most relevant senescence markers to define reliable cytometric methodologies. Mass cytometry (a.k.a. Cytometry by time of flight, CyTOF) can monitor up to 40 different cell markers at the single-cell level and has the potential to integrate multiple senescence and other phenotypic markers to identify senescent cells within a complex tissue such as skeletal muscle, with greater accuracy and scalability than traditional bulk measurements and flow cytometry-based measurements. This article introduces an analysis framework for detecting putative senescent cells based on clustering, outlier detection, and Boolean logic for outliers. Results show that the pipeline can identify putative senescent cells in skeletal muscle with well-established markers such as p21 and potential markers such as GAPDH. It was also found that heterogeneity of putative senescent cells in skeletal muscle can partly be explained by their cell type. Additionally, autophagy-related proteins ATG4A, LRRK2, and GLB1 were identified as important proteins in predicting the putative senescent population, providing insights into the association between autophagy and senescence. It was observed that sex did not affect the proportion of putative senescent cells among total cells. However, age did have an effect, with a higher proportion observed in fibro/adipogenic progenitors (FAPs), satellite cells, M1 and M2 macrophages from old mice. Moreover, putative senescent cells from muscle of old and young mice show different expression levels of senescence-related proteins, with putative senescent cells of old mice having higher levels of p21 and GAPDH, whereas putative senescent cells of young mice had higher levels of IL-6. Overall, the analysis framework prioritizes multiple senescence-associated proteins to characterize putative senescent cells sourced from tissue made of different cell types.

PSIP1 promotes gefitinib resistance in lung adenocarcinoma by inducing the expression of WASF3 and its downstream ITGB3/AKT signaling.

Gefitinib (GR), a representative drug of epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), is a key pillar in the treatment of lung adenocarcinoma (LUAD), but drug resistance is universal. Identifying the potential factors of drug resistance to GR is essential to treat patients with EGFR mutant LUAD. The GR-resistant LUAD cells were established and confirmed by MTT assay. The effects of PC4 and SRSF1 interacting protein 1 (PSIP1) on GR-resistant cell proliferation and apoptosis in vitro and in vivo were detected by colony formation, flow cytometry, tumor-bearing animal model, immunohistochemistry, and TUNEL staining. Western blotting and qPCR were used to determine the expression of relevant markers. The effect of PSIP1 on the promoter region of Wiskott-Aldrich syndrome protein family member 3 (WASF3) was detected by the dual-luciferase assay. The interaction between PSIP1 and RNA polymerase II was evaluated using ChIP-qPCR and Co-IP assays. PSIP1 was highly enriched in GR-resistant LUAD cells. Downregulation of PSIP1 expression significantly inhibited the proliferation of LUAD-resistant cells and promoted apoptosis. WASF3 was shown to have similar effects as PSIP1 in promoting drug resistance in LUAD cells. PSIP1 promoted the transcriptional activity of WASF3, which was achieved by increasing RNA polymerase II recruitment on the WASF3 promoter. Furthermore, PSIP1 positively regulated the expression of the pro-EGFR-TKI resistance factor integrin subunit beta 3 (ITGB3). Our work suggests that PSIP1 promotes resistance to GR in LUAD cells by inducing the expression of WASF3 and its downstream regulator ITGB3.

Exhausted Lag-3+ CD4+ T cells are increased in pediatric Inflammatory Bowel Disease.

T cells are one of the main drivers of inflammatory bowel diseases (IBD). Infliximab (IFX) is used in the treatment of IBD as an anti-inflammatory drug to induce remission by neutralizing TNFα. We determined the individual chemokine/homing receptor and cytokine profile in pediatric IBD patients before and during IFX therapy to identify predictive biomarkers for therapy success. Peripheral blood CD4+ cells from pediatric patients with IBD were immunomagnetically isolated and either directly analyzed by FACS for cell distribution and chemokine/homing receptor expression or evaluated for cytokine production after in-vitro-stimulation. 21 responders (RS) and 21 non-responders (NRS) were recruited. Before IFX therapy, flow cytometry revealed decreased percentages of naïve conventional T cells in pediatric IBD patients. The proportions of CD62-L+ T cells were decreased in both CD and UC therapy responders. The cytokine profile of T cells was highly altered in IBD patients compared to healthy controls (HC). During IFX therapy, the frequencies of conventional memory and regulatory memory T cells expanded in both cohorts. IFX response was marked by a decrease of α4β7+ and IFNγ+ memory T cells in both CD and UC. In contrast, frequencies of Lag-3+ T cells proved to be significantly increased in NRS. These observations were irrespective of the underlying disease. T cells of pediatric IBD patients display an activated and rather Th1/Th17 shifted phenotype The increased expression of the checkpoint molecule Lag-3 on T cells of NRS resembles a more exhausted phenotype than in RS and HC which appeared to be a relevant predictive marker for therapy failure.

Simultaneous determination of total homocysteine, methionine, methylmalonic acid and 2-methylcitric acid in dried blood spots by ultra-performance liquid chromatography–tandem mass spectrometry

Homocysteine, methionine, methylmalonic acid and 2-methylcitric acid are clinically relevant markers in the methionine, propionate, and cobalamin metabolism. This study aimed to develop and validate an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for simultaneously determining total homocysteine, methionine, methylmalonic acid and 2-methylcitric acid in dried blood spots. Three 3.2 mm discs were punched from each calibrator, quality control, and sample dried blood spot into a 96-well U-plate. Each sample was spiked with internal standards and extracted. Then the supernatant was transferred to another 96-well U-plate. After nitrogen drying, the dried residues were reconstituted, centrifuged, and the resulting supernatant was transferred to another 96-well plate for analysis. The method was performed using UPLC-MS/MS within 3 min, validated according to guidance documents, and applied to 72 samples from confirmed patients with methionine, propionate, and cobalamin metabolism disorders. The UPLC-MS/MS method provided satisfactory separation of the four analytes. The R2 values were ≥ 0.9937 for all analytes. The recoveries ranged from 94.17 to 114.29 %, and the coefficients of variation for intraday and interday precision were 0.19 % to 5.23 % and 1.02 % to 6.89 %, respectively. No significant carry-over was detected for the four analytes, and most of confirmed samples exhibited biomarker patterns characteristic of the relevant disorders. A simple and fast UPLC-MS/MS method was successfully developed, validated, and applied to clinical samples for the simultaneous determination of total homocysteine, methionine, methylmalonic acid, and 2-methylcitric acid in dried blood spots.

Correlates and predictors of sarcopenia among men with metastatic castrate-resistant prostate cancer.

Sarcopenia is a predictor of clinical outcomes in men with metastatic castrate-resistant prostate cancer (mCRPC); however, correlates and predictors of sarcopenia are poorly understood in this population. The aim of this study was to examine correlates and predictors of sarcopenia in men with mCRPC prior to treatment. A secondary analysis of an observational study was performed. Participants were receiving care for mCRPC at the Princess Margaret Cancer Centre. Sarcopenia was assessed prior to treatment and was defined as the combination of low grip strength (<35.5 kg), low gait speed (<0.8 m/s), and computed tomography-derived low muscle mass or density. Participants' sociodemographic and clinical characteristics, comorbidity information, and clinically relevant blood markers were collected prior to treatment and were used to identify correlates and predictors of sarcopenia through Spearman correlations and multivariable logistic regression, respectively. In total, 110 men had complete data on sarcopenia measures and were included in the analysis. Sarcopenia was identified in 30 (27.3%) participants. Pre-treatment sarcopenia was moderately correlated with dependence in one or more instrumental activities of daily living (IADLs) (r=0.412), Vulnerable Elders Survey-13 (r=0.404), and a lower hemoglobin (r=0.407 per 10 g/L decrease). In adjusted logistic regression, dependence in one or more IADLs (odds ratio [OR] 4.37, 95% confidence interval [CI] 1.37-13.86, p=0.012), and a 10 g/L decrease in hemoglobin (OR 1.70, 95% CI 1.13-2.57, p=0.012) were significantly associated with sarcopenia. In settings where assessment of sarcopenia is not feasible, evaluation of IADLs and hemoglobin may be used to identify high-risk patients that can benefit from supportive care strategies aiming to improve muscle mass and function.

Torque Teno Virus: A Promising Biomarker in Kidney Transplant Recipients.

Torque Teno Virus (TTV) is a ubiquitous component of the human virome, not associated with any disease. As its load increases when the immune system is compromised, such as in kidney transplant (KT) recipients, TTV load monitoring has been proposed as a method to assess immunosuppression. In this prospective study, TTV load was measured in plasma and urine samples from 42 KT recipients, immediately before KT and in the first 150 days after it. Data obtained suggest that TTV could be a relevant marker for evaluating immune status and could be used as a guide to predict the onset of infectious complications in the follow-up of KT recipients. Since we observed no differences considering distance from transplantation, while we found a changing trend in days before viral infections, we suggest to consider changes over time in the same subjects, irrespective of time distance from transplantation.

HYPNOINDUCTORS OF THE EFFECTIVE FORMULA OF POSITIVATION IN SOCIAL ADVERTISING DISCOURSE

The article is devoted to influential elements of social advertising discourse, where Milton-model inductions are arranged, which is proposed to be nominated as hypnoinducers. The purpose of the study was to identify actual hypnoinducers of the influential formula of positivity in social advertising discourse. The object of intelligence research is Ukrainian advertising megadiscourse, the subject is suggestive markers of Ukrainian social advertising discourse. General scientific methods contributed to the delineation of specific features of social advertising discourse, various types of hypnoinducers (descriptive method); identification of the components of a communicative suggestion and combining them into a whole (methods of analysis and synthesis); concretization of general conclusions (method of induction); construction of formula models of advertising influence (modeling method). Special linguistic — the study of the semantic load and functional features of linguistic components of social advertising discourse (contextualinterpretive and component analysis) and the communicative nature of advertising suggestogens (elements of discursive analysis). The methodological base of the latest scientific directions (suggestive linguistics and neurolinguistic programming) made it possible to differentiate and systematize relevant markers (hypnoinducers) of advertising suggestion (methods of meta- and Milton-model identification and suggestive qualification, which are distinguished by R. Bandler, J. Grinder, M. Erikson, T. Yu. Kovalevska. The formulas of vectors of emotional orientation of influence are presented: positivity, negation and change of vector (in commercial, political and social advertising discourses), where special attention is paid to the formula of positivity realized in social advertising discourse. Relevant hypnoinducers, which are fixed in the above formula. In particular, hypnoinducers of complex syntactic structure + lexical-semantic hypnoinductors ("point" markers) and actually lexical-semantic hypnoinducers are singled out. Truisms can act as hypnoinducers of complex syntactic structure; pattern break; "reading thoughts" complicated by other hypnoinducers, and quotations, or "quotes" of an established and transformed structure, which, in turn, often act as separate hypnoinducers without the support of lexical and semantic markers. Elements of the inverse metamodel of the processes of omission (nominalization, nonspecific vocabulary) and generalization (universal quantifiers, modal operators of necessity) act as lexical-semantic hypnoinducers. The characteristic feature is the presence of affectives as super (powerful) hypnoinducers, the presence of ergonomics varies, and predicates are not clearly represented. Prospects for research development: in-depth analysis and systematization of current hypnoinducers in various genres of advertising discourse, which will expand the spectrum of the most effective influential dominants.

Melanoma progression and prognostic models drawn from single-cell, spatial maps of benign and malignant tumors.

Melanoma clinical outcomes emerge from incompletely understood genetic mechanisms operating within the tumor and its microenvironment. Here, we used single-cell RNA-based spatial molecular imaging (RNA-SMI) in patient-derived archival tumors to reveal clinically relevant markers of malignancy progression and prognosis. We examined spatial gene expression of 203,472 cells inside benign and malignant melanocytic neoplasms, including melanocytic nevi and primary invasive and metastatic melanomas. Algorithmic cell clustering paired with intratumoral comparative two-dimensional analyses visualized synergistic, spatial gene signatures linking cellular proliferation, metabolism, and malignancy, validated by protein expression. Metastatic niches included up-regulation of CDK2 and FABP5, which independently predicted poor clinical outcome in 473 patients with melanoma via Cox regression analysis. More generally, our work demonstrates a framework for applying single-cell RNA-SMI technology toward identifying gene regulatory landscapes pertinent to cancer progression and patient survival.

DNA methylation profiles of cancer-related fatigue associated with markers of inflammation and immunometabolism.

Cancer patients are commonly affected by fatigue. Herein, we sought to examine epigenetic modifications (i.e., DNA methylation) related to fatigue in peripheral blood among patients during and after treatment for head and neck cancer (HNC). Further, we determined whether these modifications were associated with gene expression and inflammatory protein markers, which we have previously linked to fatigue in HNC. This prospective, longitudinal study enrolled eligible patients with data collected at pre-radiotherapy, end of radiotherapy, and six months and one-year post-radiotherapy. Fatigue data were reported by patients using the Multidimensional Fatigue Inventory (MFI)-20. DNA methylation (Illumina MethylationEPIC) and gene expression (Applied Biosystems Clariom S) arrays and assays for seven inflammatory markers (R&D Systems multiplex) were performed. Mixed models and enrichment analyses were applied to establish the associations. A total of 386 methylation loci were associated with fatigue among 145 patients (False Discovery Rate [FDR] < 0.05). Enrichment analyses showed the involvement of genes related to immune and inflammatory responses, insulin and lipid metabolism, neuropsychological disorders, and tumors. We further identified 16 methylation-gene expression pairs (FDR < 0.05), which were linked to immune and inflammatory responses and lipid metabolism. Ninety-one percent (351) of the 386 methylation loci were also significantly associated with inflammatory markers (e.g., interleukin 6, c-reactive protein; FDR < 0.05), which further mediated the association between methylation and fatigue (FDR < 0.05). These data suggest that epigenetic modifications associated with inflammation and immunometabolism, in conjunction with relevant gene expression and protein markers, are potential targets for treating fatigue in HNC patients. The findings also merit future prospective studies in other cancer populations as well as interventional investigations.

P-449 Association of corpus luteum activity in early pregnancy and live birth after assisted reproductive technology (ART) and intrauterine insemination (IUI)

Abstract Study question What is the incidence of low corpus luteum activity in early pregnancy, and how are endogenous progesterone levels and live birth achievement associated? Summary answer Frequently occurring low corpus luteum activity (progesterone-level) in early pregnancy after ART and IUI strongly predicts pregnancy demise, though not independent of trophoblast activity (hCG-level). What is known already Ovarian stimulation and human chorion gonadotropine (hCG) administration may induce a luteal phase defect via negative feedback on the hypothalamic-pituitary-ovarian (HPO) axis. Luteal phase support (LPS) is routinely administered with bio-identical progesterone or oral dydrogesterone (DYD). DYD has high oral availability, minimal interaction with the pituitary gland, and no cross-reactivity in enzyme-linked immunosorbent assay (ELISA) with progesterone. Therefore, utilizing DYD as LPS in IVF/ICSI or ovulatory IUI cycles provides a unique perspective to assess endocrine luteal activity. While various studies explored progesterone and hCG post-IVF or IUI, none focused solely on the corpus luteum’s sole endocrine function and its outcomes. Study design, size, duration This single-center, retrospective study (with institutional review board approval) investigated hCG and progesterone serum levels after IVF/ICSI cycles or IUI cycles supported with DYD as the sole LPS. The study aims to assess their predictive value, individually and in combination, for sustaining pregnancy. Data from 189 IVF/ICSI and 198 IUI early pregnancies, respectively, with positive hCG test between January 2017 and June 2022, was extracted from the patient management system at the University Fertility Center. Participants/materials, setting, methods Included were only first IVF/ICSI and IUI treatment-cycles with serum hCG value ≥ limit of detection (0.6 IU/l) between days 9 and 16 after fresh embryo transfer or IUI, respectively. Additionally to hCG, endogenous progesterone was determined and the relationship between these and pregnancy maintenance was investigated using logistic regression analysis. Inclusion criteria encompassed hCG-triggered cycles using DYD as the sole LPS, administered at 30 and 20 mg daily for IVF/ICSI and IUI therapy, respectively. Main results and the role of chance The 10th, 25th, 50th and 75th quantiles of serum progesterone are at 0.28, 3.75, 33.0 and 98.7 µg/l in IVF/ICSI cycles and 0.48, 2.70, 18.40 and 26.6 µg/l in IUI cycles. Women in the first quartile of progesterone levels had nearly exclusively pregnancy demise: live birth rate 3/47 (7%, 95% confidence interval (CI) 1-19%) and 0/47 (0%, 95% CI 0-7.5%) in IVF/ICSI and IUI cycles, respectively. In both IVF/ICSI and IUI, progesterone and hCG were highly correlated (correlation coefficient 0.83 in both cases). Accordingly, the association of serum hCG levels with live birth achievement was similar in quartile analyses. Using receiver operating characteristic (ROC) curves and Youden’s indices, the optimal cut-off values for predicting live birth were determined as follows: 16.49 µg/l (89 % sensitivity (SN) and 59 % specificity (SP)) for IVF/ICSI and 15.89 µg/l (90 % SN and 70 % SP) for IUI therapy. Logarithmic regression analysis also revealed a significant correlation between progesterone levels and live birth in IVF/ICSI and IUI therapy, with a p-value of &amp;lt; 0.001. Limitations, reasons for caution Low progesterone in early pregnancy may be a consequence or a cause for pregnancy demise. DYD, like any other progesterone for LPS, might adversely impact corpus luteum formation and maintenance through HPO axis interaction, especially in mono-ovulatory cycles or in older women with inherently higher risk of luteal phase defect. Wider implications of the findings Ovarian stimulation and hCG-administration may induce a luteal phase defect with insufficient luteal activity in early pregnancy, even up to luteolysis, with potential consequences for pregnancy maintenance and maternal/fetal health. Future treatment protocols may require exploring an optimal luteotropic state at pregnancy’s outset, necessitating the establishment of relevant markers. Trial registration number not applicable

Immune markers of severe acute pancreatitis.

Acute pancreatitis is a common acute inflammatory disorder of the pancreas, and its incidence has been increasing worldwide. Approximately 10% of acute pancreatitis progresses to severe acute pancreatitis (SAP), which carries significant morbidity and mortality. Disordered immune response to pancreatic injury is regarded as a key event that mediates systemic injury in SAP. In this article, we review recent developments in immune biomarkers of SAP and future directions for research. Given the importance of the NLRP3-inflammasome pathway in mediating systemic inflammatory response syndrome and systemic injury, recent studies have investigated associations of SAP with systemic levels of activators of NLRP3, such as the damage associated molecular patterns (DAMPs) for the first time in human SAP. For example, circulating levels of histones, mitochondrial DNAs, and cell free DNAs have been associated with SAP. A panel of mechanistically relevant immune markers (e.g., panel of Angiopoeitin-2, hepatocyte growth factor, interleukin-8 (IL-8), resistin and sTNF-α R1) carried higher predictive accuracies than existing clinical scores and individual immune markers. Of the cytokines with established relevance to SAP pathogenesis, phase 2 trials of immunotherapies, including tumor necrosis factor (TNF)-alpha inhibition and stimulation of IL-10 production, are underway to determine if altering the immunologic response can reduce the severity of acute pancreatitis (AP). Circulating systemic levels of various DAMPs and a panel of immune markers that possibly reflect activities of different pathways that drive SAP appear promising as predictive biomarkers for SAP. But larger multicenter studies are needed for external validation. Studies investigating immune cellular pathways driving SAP using immunophenotyping techniques are scarce. Interdisciplinary efforts are also needed to bring some of the promising biomarkers to the bedside for validation and testing for clinical utility. Studies investigating the role of and characterization of altered gut-lymph and gut-microbiota in severe AP are needed.

Spatial Deconvolution of Cell Types and Cell States at Scale Utilizing TACIT.

Identifying cell types and states remains a time-consuming, error-prone challenge for spatial biology. While deep learning is increasingly used, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in health and disease. To address this, we developed TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data. TACIT uses unbiased thresholding to distinguish positive cells from background, focusing on relevant markers to identify ambiguous cells in multiomic assays. Using five datasets (5,000,000-cells; 51-cell types) from three niches (brain, intestine, gland), TACIT outperformed existing unsupervised methods in accuracy and scalability. Integrating TACIT-identified cell types with a novel Shiny app revealed new phenotypes in two inflammatory gland diseases. Finally, using combined spatial transcriptomics and proteomics, we discovered under- and overrepresented immune cell types and states in regions of interest, suggesting multimodality is essential for translating spatial biology to clinical applications.

Fusing 1H NMR and Raman experimental data for the improvement of wine recognition models

The present study proposes the development of new wine recognition models based on Artificial Intelligence (AI) applied to the mid-level data fusion of 1H NMR and Raman data. In this regard, a supervised machine learning method, namely Support Vector Machines (SVMs), was applied for classifying wine samples with respect to the cultivar, vintage, and geographical origin. Because the association between the two data sources generated an input space with a high dimensionality, a feature selection algorithm was employed to identify the most relevant discriminant markers for each wine classification criterion, before SVM modeling. The proposed data processing strategy allowed the classification of the wine sample set with accuracies up to 100% in both cross-validation and on an independent test set and highlighted the efficiency of 1H NMR and Raman data fusion as opposed to the use of a single-source data for differentiating wine concerning the cultivar and vintage.

Immunohistochemistry for Assessing Toxicity and Mechanism of Action of Anticancer Drugs During Preclinical Trials. Part II. Cell Death, Vasculogenesis and Angiogenesis

About 120 chemical compounds are registered in Russia as anticancer drugs, and screening and investigation of novel therapies remain an urgent task for specialists in pathophysiology, pharmacology and oncology. Among them, treatments targeting neovascularisation and regulated cell death of atypical cells within the malignant tumours are of utmost importance. Hence, development of novel anti-cancer drugs must include testing of their pro-apoptotic and anti-angiogenic activity. Here we review the markers of angiogenesis and regulated cell death during the tumor development and the respective immunohistochemical applications for preclinical trials. Here we discuss relevant molecular markers for studying primary cell death subroutines which can be targeted by anticancer agents. The most sensitive and specific immunohistochemical markers of programmed cell death are tumor necrosis factor alpha (TNF-α) for necrosis and anti-cellular apoptosis susceptibility/CSE1L, Bcl-2, and apoptotic protease activating factor-1 (APAF1) for apoptosis. Primary markers of angiogenesis include vascular endothelial growth factor A (VEGF-A), hypoxia-inducible factor 1-alpha (HIF-1α), and platelet-derived growth factor (PDGF). Analysis of tumour blood supply, metastasis and apoptosis has both theoretical and practical significance with direct implications for the pharmaceutical industry.