Biomarker Characteristics Research Articles

TP53 Y220C mutations in colorectal carcinoma (CRC): A genomic landscape study.

239 Background: Inactivating genomic alteration (GA) of the TP53 tumor suppressor gene leads to inactivation of p53 protein and is currently the most frequently associated GA across all cancers. Colorectal cancer is a common and lethal subtype of cancer, in the top 5 for incidence, prevalence and cancer-related deaths worldwide. TP53 is the second most frequent GA identified in clinically advanced CRC. It has been postulated that GA in TP53 not only affects the molecular biology of malignant cells but also impacts the tumor microenvironment in CRC. This GA is currently untargetable by approved drugs however, recently a novel approach designed to revert to wild type functioning of TP53 inactivated by Y220C base substitution has gained significant clinical interest. Methods: 67,301 cases of clinically advanced CRC underwent hybrid capture based comprehensive genomic profiling to assess all classes of GA. Cases were sequenced to a mean coverage depth of 650X with microsatellite instability (MSI) status and tumor mutation burden (TMB) determined from the sequencing data and PD-L1 expression measured by immunohistochemistry using the DAKO tumor proportional staining system (low positive set at 1-49% staining and high positive set at ≥50% staining). Results: 422 (0.6%) of the CRC featured the TP53 Y220C GA (Y220C+). When compared with the CRC that were TP53 Y220C negative (Y220C-), the Y220C+ cases were of similar age, gender and number of GA per tumor. The Y220C- cases has significantly higher frequencies of MSI status (6.1% vs 2.2%; p=.0007) and TMB levels greater >10 mutations/Mb (8.7% vs 4.7%; p=.004). The Y220C+ featured lower frequencies of GA in PIK3CA (12.9% vs 18.6%; p=.002), BRAF (8.8% vs 10.1%; NS) and PTEN (7.4% vs 8.3%, NS) and a higher frequency of ERBB2 amplification (5.0% vs 2.7%; p=.004). GA in APC , KRAS , NRAS , BRCA2 , EGFR and MET were similar in both Y220C+ and Y220C- CRC. PD-L1 low expression was similarly infrequent (12.1% to 16.7% range) in both groups. Conclusions: The potentially targetable TP53 Y220C short variant mutation is uncommon in clinically advanced CRC but is associated with unique genomic and biomarker characteristics. Further research might elucidate subpopulations or CRC subtypes with a greater frequency of this mutation who might benefit from a novel targeted therapy. CRC TP53 Y220C+(422 Cases) CRC TP53 Y220C-(66,879 Cases) P Value Gender 41.2% F/ 58.8% M 44.4% F/55.6% M NS Median Age (range) 62 (23-89+) 61 (8-89+) NS GA/tumor 6.1 6.5 NS TP53 non-Y220C GA 16.1% 75.7% <.0001 PIK3CA 12.9% 18.6% .002 ERBB2 6.2% (5.0% amp) 5.1% (2.7% amp) .004 (amp) MSI High 2.2% 6.1% .0007 TMB > 10 mut/Mb 4.7% 8.7% .004 PD-L1 Low (1-49%TPS)/ PD-L1 High (>50% TPS) 16.7% (132 cases)/2.3% 12.1% (20,759 cases)/1.4% NS

Origin of Crude Oils in the Lower Yanchang Formation of Yan'an Area in Ordos Basin, China.

The clastic rocks of the Yanchang Formation in the Ordos Basin display poor physical properties but are rich in petroleum resources, exhibiting significant exploration potential. However, due to the existence of multiple sets of oil-bearing formations, hydrocarbon-generating formations, and a large longitudinal span, elucidating the correspondence between crude oil and source rocks is vital for further exploration. This study concentrates on the Lower Yanchang Formation of Triassic in the Yan'an area of the Ordos Basin, aiming to perform refined oil-source correlation. The findings indicate that the relative contents of diasteranes [DiaC27βα (20S + 20R), DiaC28βα (20S + 20R), and DiaC29βα (20S + 20R)] are instrumental in categorizing hydrocarbon sources. By examination of the biomarker characteristics of crude oils in the Lower Yanchang Formation, it is detected that there are variations in hydrocarbon source contributions across the Wuqi, Shunning, and Xihekou areas and among different formations. In conclusion, the oils within the lower assembly in the study area primarily originate from a composite source, which includes Chang-7 black mudstone in the center of the lake basin, Chang-9 black mudstone in the Wuqi region, and Chang-9 dark mudstone in other areas. The Chang-7 dark mudstone in other areas plays a minor role in the lower assembly crude oil genesis, while the Chang-10 dark mudstone has a negligible influence on the lower assembly oil source of the Yanchang Formation.

Personalized multifactorial risk assessment in neoadjuvant-treated breast carcinoma

Abstract Purpose Due to biological heterogeneity of breast carcinoma, predicting the individual response to neoadjuvant treatment (NAT) is complex. Consequently, there are no comprehensive, generally accepted practices to guide post-treatment follow-up. We present clinical and histopathological criteria to advance the prediction of disease outcome in NA-treated breast cancer. Methods A retrospective consecutive cohort of 257 NA-treated Finnish breast cancer patients with up to 13-year follow-up and the corresponding tissue samples of pre- and post-NAT breast and metastatic specimen were evaluated for prognostic impacts. All relevant clinical and biomarker characteristics potentially correlated with tumor response to NAT, course of disease, or outcome of breast cancer were included in the statistical analyses. Results The results highlight the intensified characterization of distinguished prognostic factors and previously overlooked histological features, e.g., mitotic and apoptotic activity. Particularly, decreased PR indicated 3.8-fold (CI 1.9–7.4, p = 0.0001) mortality risk, and a > 10.5-year shorter survival for the majority, > 75% of patients (Q1). Clinically applicable prognostic factors both preceding and following NAT were identified and compiled into heat maps to quantify mortality and recurrence risks. Combinations of risk factors for aggressive disease were exemplified as an interactive tool (bcnatreccalc.utu.fi) to illustrate the spectrum of disease outcomes. Conclusion The results emphasize the value of comprehensive evaluation of conventional patient and biomarker characteristics, especially concerning re-assessment of biomarkers, risk-adapted surveillance, and personalized treatment strategies. Future personalized NA-treatment strategies might benefit from models combining risk-adapted surveillance data and post-NAT re-assessed biomarkers.

Classifying cognitive impairment based on FDG-PET and combined T1-MRI and rs-fMRI: An ADNI study.

Mild cognitive impairment (MCI) refers to a memory impairment among non-demented adults. It is a condition that increases the risk of dementia, notably due to Alzheimer's disease (AD). MCI is heterogeneous and there is a need for novel diagnostic approaches. Fluorodeoxyglucose positron emission tomography (FDG-PET) imaging provides robust AD biomarker characteristics, while anatomical and functional magnetic resonance imaging (MRI) offer complementary information. Classify MCI and cognitively normal (CN) adults using FDG-PET images; predict individuals with MCI that convert to AD dementia; determine if MRI can achieve comparable performance to FDG-PET classification. Four ADNI cohorts were created. Cohort 1: 805 participants (MCI n = 455; CN n = 350) that underwent FDG-PET. FDG-PET images were inputs to a one-channel 3-dimensional (3D) DenseNet deep learning model. Cohort 2: 348 participants (MCI n = 174; CN n = 174) with MRI and functional MRI. Cohort 3: overlapping cases from cohorts 1 and 2 (MCI n = 70; CN n = 70). Cohort 4: 336 participants (MCI-converters n = 168; MCI-stable n = 168) with FDG-PET from cohort 1. The one/two-channel models' inputs were T1-weighted MRI and/or amplitude of low-frequency fluctuations images, with classification metrics evaluated through 10-fold cross-validation. The FDG-PET model achieved 88.02%±3.82 accuracy for MCI versus CN classification, with 88.70%±4.70 sensitivity and 87.14%±5.03 specificity. Neither MRI model outperformed the FDG-PET model, as the highest MRI-based accuracy was 76.86%±1.95. The FDG-PET model achieved 63.23%±4.68 accuracy in classifying MCI-converters versus MCI-stable. FDG-PET images produced the highest accuracy in classifying MCI versus CN. While MRI-based approaches were inferior to FDG-PET, multi-contrast MRI still offers value for neurodegeneration classification.

Characteristics of cerebrospinal fluid biomarkers/ imaging findings in patient with amyloid‐negative dementia ∼second report∼

Characteristics of cerebrospinal fluid biomarkers/ imaging findings in patient with amyloid‐negative dementia ∼second report∼

Machine learning-based prediction of sarcopenia in community-dwelling middle-aged and older adults: findings from the CHARLS.

Sarcopenia is a prominent issue among aging populations and associated with poor health outcomes. This study aimed to examine the predictive value of questionnaire and biomarker data for sarcopenia, and to further develop a user-friendly calculator for community-dwelling middle-aged and older adults. We used two waves (2011 and 2013) of the China Health and Retirement Longitudinal Study (CHARLS) to predict sarcopenia, defined by the Asian Working Group for Sarcopenia 2019 criteria. We restricted the analytical sample to adults aged 45 or above (N = 2934). Five machine learning models were used to construct Q-based (only questionnaire variables), Bio-based (only biomarker variables), and combined (questionnaire plus biomarker variables) models. Area under the receiver operating characteristic curve (AUROC) was used for performance assessment. Temporal external validation was performed based on two datasets from CHARLS. Important predictors were identified by Shapley values and coefficients. Extreme gradient boosting (XGBoost), considering both questionnaire and biomarker characteristics, emerged as the optimal model, and its AUROC was 0.759 (95% CI: 0.747-0.771) at a decision threshold of 0.20 on the test set. Models also performed well on the external datasets. We found that cognitive function was the most important predictor in both Q-based and combined models, and blood urea nitrogen was the most important predictor in the Bio-based model. Other key predictors included education, haematocrit, total cholesterol, drinking, number of chronic diseases, and instrumental activities of daily living score. Our findings offer a potential for early screening and targeted prevention of sarcopenia among middle-aged and older adults in the community setting.

Identification of DAGLA as an autoantibody target in cerebellar ataxia

BackgroundWe aimed to investigate the clinical, imaging and fluid biomarker characteristics in patients with antidiacylglycerol lipase alpha (DAGLA)-autoantibody-associated cerebellitis.MethodsSerum and cerebrospinal fliud (CSF) samples from four index patients were subjected...

Salivary microbiome and biomarker characteristics of diabetics with periodontitis.

To examine the characteristics of the salivary microbiome in Type 2 diabetes mellitus (T2DM) patients with or without periodontitis. Periodontitis has been identified as clear sequelae of T2DM. This chronic oral disease also impacts the management of the clinical features of diabetes. The oral microbiome characteristics in T2DM with and without periodontitis, as well as the response of this oral microbiome to nonsurgical therapy have not been well described. Knowledge of key oral biological features could help address the observed poorer clinical presentation of T2DM patients. The oral microbiome in saliva of adult cohorts periodontally healthy/non-diabetic (non-periodontitis; NP; n=31), T2DM without periodontitis (DWoP; n=32), and T2DM with periodontitis (DWP; n=29) were characterized by microbial molecular analysis using V3-V4 sequencing and Luminex or ELISA techniques for salivary host analytes. Phyla distribution showed DWP with significantly lower levels of Firmicutes and Actinobacteria and higher levels of Fusobacteria and Spirochetes compared to the healthier groups. Approximately 10% of the detected microbial species showed significant differences in frequency and level of colonization among the DWP, DWoP, and NP samples. A subset of bacteria were significantly correlated with clinical disease features, as well as a specific repertoire of salivary analytes, in particular matrix metalloproteinase (MMP)8/MMP9, interleukin-1ß, B-cell activating factor, and resistin differed between the groups and were related to specific taxa. Principal component analysis that identified a majority of the DWP subjects microbiome was unique based upon an array of 27 taxa out of up to 255 detected in the saliva samples. T2DM patients with periodontitis show unique oral microbiome and salivary analyte composition compared to diabetics or non-diabetic persons without periodontitis. Specific members of the oral microbiome relate directly to the clinical disease features and/or salivary biomolecules in T2DM individuals.

Nanoparticles as a novel key driver for the isolation and detection of circulating tumour cells

Circulating tumour cells (CTCs), derived from primary tumours, play a pivotal role in cancer metastasis by migrating into the peripheral bloodstream. These cells are paramount in clinical research, serving as early diagnostic markers for metastatic cancer. Analysing CTC counts and their biomarker characteristics can provide invaluable insights into tumour identification, profiling, and metastatic capabilities. However, the rarity and diverse nature of CTCs in the bloodstream present significant challenges to their isolation and detection, especially in the initial stages of metastasis. Recent advancements in nanotechnology have led to the development of innovative CTC separation and detection methods. This review focuses on applying nanoparticles, nanomaterials, and microfluidic platforms to simplify the isolation and detection of CTCs. The infusion of nanotechnology in this field marks a crucial turning point, enabling the necessary progress to advance CTC research.

Ethnic differences in the prevalence of amyloid positivity and cognitive trajectories.

We investigated the prevalence of amyloid beta (Aβ) positivity (+) and cognitive trajectories in Koreans and non-Hispanic Whites (NHWs). We included 5121 Koreans from multiple centers across South Korea and 929 NHWs from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Participants underwent Aβ positron emission tomography and were categorized into cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia stages. Age, sex, education, and apolipoprotein E. genotype were adjusted using multivariable logistic regression and stabilized inverse probability of treatment weights based on the propensity scores to mitigate imbalances in these variables. The prevalence of Aβ+ was lower in CU Koreans than in CU NHWs (adjusted odds ratio 0.60). Aβ+ Koreans showed a faster cognitive decline than Aβ+ NHWs in the CU (B=-0.314, p=.004) and MCI stages (B=-0.385, p<.001). Ethnic characteristics of Aβ biomarkers should be considered in research and clinical application of Aβ-targeted therapies in diverse populations. Koreans have a lower prevalence of Aβ positivity compared to NHWs in the CU stage. The effects of Alzheimer's risk factors on Aβ positivity differ between Koreans and NHWs. Aβ-positive (Aβ+) Koreans show faster cognitive decline than Aβ+ NHWs in the CU and MCI stages.

Clinical Characteristics of Charcot-Marie-Tooth Disease Type 4J.

Charcot-Marie-Tooth disease type 4J (CMT4J) is caused by autosomal recessive variants in the Factor-Induced Gene 4 (FIG4) gene. Recent preclinical work has demonstrated the feasibility of adeno-associated virus serotype 9-FIG4 gene therapy. This study aimed to further characterize the CMT4J phenotype and evaluate feasibility of validated CMT-related outcome measures for future clinical trials. This cross-sectional study enrolled children and adults with genetically confirmed CMT4J, with 2 documented disease-causing variants in the FIG4 gene. Patients were recruited through the Inherited Neuropathy Consortium network. Disease severity was assessed using standardized CMT-specific outcome measures and exploratory biomarkers including muscle MRI fat fraction, electrophysiology, and neurofilament light chain levels. Descriptive statistics and correlation analyses were conducted to explore relationships between variables. We recruited a total of 19 patients, including 14 pediatric patients (mean age 10.9 ± 3.9 years) and 5 adults (mean age 40.0 ± 13.9 years). The most frequent symptoms were gross motor delay and distal more than proximal muscle weakness, which were observed in 14 of 19 patients. The most common non-neuromuscular symptoms were cognitive and respiratory deficits, each seen in 8 of 19 patients. We denoted asymmetric weakness in 2 patients and nonuniform slowing of conduction velocities in 6 patients. Charcot-Marie-Tooth Disease Pediatric Scale (CMTPedS), Pediatric Quality of Life Inventory, and Vineland Adaptive Behavior Scale scores were affected in most patients. We observed a significant positive correlation between neurofilament light chain levels and CMTPedS, but the study was underpowered to observe a correlation between CMTPedS and MRI fat fraction. We obtained baseline clinical and biomarker data in a broad cohort with CMT4J in pediatric and adult patients. Motor delay, muscle weakness, and respiratory and cognitive difficulties were the most common clinical manifestations of CMT4J. Many patients had nerve conduction studies with nonuniform slowing, and 2 had an asymmetric pattern of muscle weakness. We observed that the neurofilament light chain levels correlated with the CMTPedS in the pediatric population. This study showed feasibility of clinical outcomes including CMTPedS in assessment of disease severity in the pediatric patient population and provided baseline characteristics of exploratory biomarkers, neurofilament light chain levels, and muscle MRI fat fraction. The coronavirus disease 2019 pandemic affected some of the visits, resulting in a reduced number of some of the assessments.

The Early Cretaceous Sembar Formation, Southern Indus Basin, Pakistan: Biomarkers and Trace Element Distributions to Investigate the Sedimentary Palaeoenvironment and Organic Matter Input.

The Early Cretaceous clay-rich facies of the Sembar Formation represent the most significantly occurring organic-rich sediments in the Southern Indus Basin of Pakistan. In this study, detailed geochemical research of total organic carbon, biomarker, mineralogy and trace elemental compositions, together with kerogen microscopic analysis, were carried out and used to understand the organic matter input and the dispositional environmental setting of the organic-rich Sembar shale. The Sembar shales have high organic matter, as indicated by the total organic carbon (TOC) content of up to 2.31 wt %. These shales contain a high abundance of liptinites (i.e., alginite and bituminite), with significant reactive vitrinite maceral, reflecting a mixed-organic matter with a high contribution of marine-derived input. The biomarker distributions evidence the finding of mainly marine organic matter. The biomarker characteristics such as Pr/Ph, Pr/n-C17, Ph/n-C18, and tricyclic terpane ratios together with C27-C29 regular sterane distributions show that the source of organic matter was primarily marine-derived from mainly phytoplankton algae, along with amounts of land plant input, and accumulated under a low oxygenated environment. The Sembar shale facies are characterized by high Mo trace element content and high V/Ni and Mo/TOC ratios, suggesting anoxic and nonsulfidic environmental conditions during time deposition. The geochemical proxies such as the Sr/Ba ratio and gammacerane/C30 hopane (G/C30) index suggest that the Sembar shale facies were deposited in a relatively low moderate stratified water column. The higher gallium (Ga) than rubidium (Rb), with high Ga/Rb ratios, indicates a high abundance of the kaolinite mineral, thereby deducing the subaerial weathering during the warm and humid climatic conditions. In this case, these warm and humid climatic conditions cause an influx of masses of nutrients, which could be attributed to increasing marine primary bioproductivity. These large masses of nutrients into the photic zone are also attributed to the presence of the upwelling system during the deposition time. Therefore, such conditions of bioproductivity and preservation of organic matter (OM) resulted in the accumulation of organic carbon in the shale facies of the Early Cretaceous Sembar Formation.

Study of the relationship among biomarkers, cell and tissue of glioma through Raman spectroscopy

Glioma is the most common brain tumors with high mortality and recurrence rates. Currently, the diagnosis methods for glioma are mainly based on tissue level, cellular level and biomarker level. In this paper, the characteristics of biomarkers (γ-aminobutyric acid and matrix mtalloproteinses-2), U87MG glioma cell and tissue were studied based on Raman spectroscopy, respectively. The results showed that the γ-aminobutyric acid concentration exhibited a linear relation with the intensity of characteristic peaks in 800–1600 cm−1 region, whereas the spectral baseline increased with the increasing of sample concentration in 200–700 cm−1 region. The Raman characteristics of matrix mtalloproteinses-2 in 20–1800 cm−1 region was investigated. Especially, it is demonstrated that the matrix mtalloproteinses-2 showed sixteen low-wavenumber Raman peaks in the range of 20–300 cm−1. Moreover, the U87MG glioma cell showed seven different Raman characteristic peaks in 600–1800 cm−1 region. Compared with the normal tissue, the Raman intensity of tumor tissue showed apparent intensity differences in 300–1800 cm−1, where the intensity changes of these Raman peaks were related to the reducing of the lipid metabolic pathways, and increase of the RNA in tumor tissue region. Furthermore, it is found that the Raman spectra of U87MG glioma cell and tumor tissue had corresponding peaks in the Raman spectra of the liquid γ-aminobutyric acid and matrix mtalloproteinses-2. It is suggested that the γ-aminobutyric acid and matrix mtalloproteinses-2 contributed to the formation and growth of glioma cell and tissue. Thus, Raman spectroscopy not only can diagnose glioma at the biomarkers, cellular and tissue level, but also analyze the relationship among the three. Furthermore, the results provided a physical marker for the detection of glioma in clinically.

Proteomic analysis of peripheral blood mononuclear cells in first episode psychosis – Protein and peptide-centered approaches to elucidate potential diagnostic biomarkers

Diagnosing patients suffering from psychotic disorders is far from being achieved with molecular support, despite all the efforts to study these disorders from different perspectives. Characterizing the proteome of easily obtainable blood specimens, such as the peripheral blood mononuclear cells (PBMCs), has particular interest in biomarker discovery and generating pathophysiological knowledge. This approach has been explored in psychiatry, and while generating valuable information, it has not translated into meaningful biomarker discovery. In this project, we report the proof-of-concept of a methodology that aims to explore further information obtained with classical proteomics approaches that is easily overlooked. PBMC samples from first-episode psychosis and control subjects were subjected to a SWATH-MS approach, and the classical protein relative quantification was performed, where 389 proteins were found to be important to distinguish the two groups. Individual analysis of the quantified peptides was also performed, highlighting peptides of unchanged proteins that were significantly altered. With the combination of protein- and peptide-centered proteomics approaches, it is possible to highlight that information about proteoforms, namely regulation at the peptide level possibly due to post-translational modifications, is routinely overlooked and that its diagnostic potential should be further explored. SignificanceOur exploratory findings highlight the potential of MS-based proteomics strategies, combining protein- and peptide-centered approaches, to aid clinical decision-making in first-episode psychosis, helping to establish early biomarkers for schizophrenia and other psychotic disorders. Particularly, the less popular peptide-centered approach allows the identification/measurement of overlooked modulated peptides that may have potential biomarker characteristics. The application in parallel of protein- and peptide-centered strategies is transversal to research of other diseases, potentially allowing a more comprehensive characterization of the metabolic/pathophysiological alterations related to a specific disease.

Clinical and Biomarker Characteristic of Lymphoma Patients in Hasan Sadikin Lymphoma Registry.

No specific data have been systematically collected regarding lymphoma patient characteristics, while non-Hodgkin lymphoma (NHL) is identified as the 7th most common cancer and Hodgkin lymphoma (HL) is the 28th. Inflammation plays an important role in the pathogenesis and progression of lymphoma. Malnutrition is an adverse prognostic factor in lymphoma. Systemic Inflammatory Index (SII), Prognostic Nutritional Index (PNI), and Advanced Lung Cancer Inflammation Index (ALI) were biomarkers depicting inflammation and nutritional status. This study aims to describe the clinical and biomarker characteristics of both HL and NHL patients. This descriptive study used a cross-sectional design, and data were collected from Hasan Sadikin Hospital lymphoma registry from January 2020 to November 2023. Demographic, staging, and histopathological data were extracted. Three biomarkers were evaluated. Survival curves were drawn using Kaplan-Meier curve analysis, and the log rank test was used for comparison of survival between early and advanced stage. A total of 271 patients were recruited as participants, and the majority (80.5%) had NHL, with diffuse large B-cell lymphoma (DLBCL) being the most common histopathological type (50.5%). Early disease was observed in two-thirds of patients, and low-risk International Prognostic Index (IPI) score was the most common prognostic score found (95%). SII was slightly higher in early compared to advanced stages. Treatment response was evaluated from 101 patients, and complete response was observed in 44.5%. Two-year overall survival (OS) was 93.1%, with median survival 22.7 (95% CI 21.9-23.5) months. In early stage, the median survival was slightly longer than in advanced stage [23.0 (95% CI 22.2-23.8) vs 21.6 (95% CI 19.3-23.8) months, P=0.09]. Hodgkin lymphoma and DLBCL had similar clinical and biomarker characteristics. There were slight differences between the three biomarkers SII, ALI, and PNI based on the disease stage. Almost all patients still survived at 2-year follow-up.

Sedimentary environment shift and organic matter enrichment mechanism in response to volcanic ash influence: A case study of the Permian Lucaogou Formation, Santanghu Basin, NW China

The second member of the Lucaogou Formation (P2l2) in the Tiaohu and Malang Sags of the Santanghu Basin (study area) underwent periodic volcanic activity and frequent lithological changes. This study comprehensively analyzed the organic geochemistry, mineral composition, organic matter (OM) types, volcanic cycle, and palaeoenvironment of shale in the study area. Techniques such as total organic carbon (TOC), rock pyrolysis (Rock-Eval), organic petrology, scanning electron microscopy (SEM) with energy-dispersive spectrum (EDS) analysis, X-ray diffraction (XRD), trace elements, and saturated hydrocarbon gas chromatography and mass spectrometry (GC–MS) were employed. The findings suggest that limited terrigenous input during the sedimentary period of the P2l2 led to the deposition of a distinctive mixture of volcanic ash (felsic) and carbonate (dolomite and calcite), with a low average clay mineral content of 6%. The P2l2 shale emerged as a high-quality source rock, predominantly composed of type I and II kerogens, with moderate OM maturity. The deposition environment was characterized by hot and arid conditions, high salinity, and intensive reducibility, which was favorable for algae development and conducive to OM preservation. Notably, two lamalginite types, labeled as lamalginite “A” and lamalginite “B,” were identified. Lamalginite “B”-rich shales were deposited in a hotter and drier climate compared to lamalginite “A”-rich shales. Lamalginite “B”- rich shale inexhibited high levels of C28 regular sterane and β-carotenes, distinguishing it from lamalginite “A”-rich shale. A comprehensive analysis involving organic petrology, SEM, sedimentary environment, and biomarker characteristics suggests that lamalginite “B” may be a salt-tolerant green alga, while lamalginite “A” may be a cyanobacterium. Finally, an OM enrichment model for the P2l2 shale was established.

Serum Biomarker Signatures of Choroid Plexus Volume Changes in Multiple Sclerosis.

Increased choroid plexus (CP) volume has been recently implicated as a potential predictor of worse multiple sclerosis (MS) outcomes. The biomarker signature of CP changes in MS are currently unknown. To determine the blood-based biomarker characteristics of the cross-sectional and longitudinal MRI-based CP changes in a heterogeneous group of people with MS (pwMS), a total of 202 pwMS (148 pwRRMS and 54 pwPMS) underwent MRI examination at baseline and at a 5-year follow-up. The CP was automatically segmented and subsequently refined manually in order to obtain a normalized CP volume. Serum samples were collected at both timepoints, and the concentration of 21 protein measures relevant to MS pathophysiology were determined using the Olink™ platform. Age-, sex-, and BMI-adjusted linear regression models explored the cross-sectional and longitudinal relationships between MRI CP outcomes and blood-based biomarkers. At baseline, there were no significant proteomic predictors of CP volume, while at follow-up, greater CP volume was significantly associated with higher neurofilament light chain levels, NfL (standardized β = 0.373, p = 0.001), and lower osteopontin levels (standardized β = -0.23, p = 0.02). Higher baseline GFAP and lower FLRT2 levels were associated with future 5-year CP % volume expansion (standardized β = 0.277, p = 0.004 and standardized β = -0.226, p = 0.014, respectively). The CP volume in pwMS is associated with inflammatory blood-based biomarkers of neuronal injury (neurofilament light chain; NfL) and glial activation such as GFAP, osteopontin, and FLRT2. The expansion of the CP may play a central role in chronic and compartmentalized inflammation and may be driven by glial changes.

In situ Gels for Periodontitis: An Overview

ABSTRACTA successful approach for periodontitis treatment isin situgel administration, which delivers medication to the site of infection in a controlled and continuous manner. Researchers used components such as zein, borneol, piperine, and curcumin to create a formulation. The formulations demonstrated antimicrobial effects and were designed to target the inflammatory condition associated with dysbiosis in periodontitis. Polymers such as gellan gum, alginic acid, xyloglucan, pectin, chitosan, poly (D Lactic acid), poly (DL-lactide co glycolide), and polycaprolactone are commonly used polymers to prepare the In situ gel formulation , which enables prolonged medication and Controlled release. In the presence of ions, alginic acid gels are biocompatible. Whereas pectin gels are used in the presence of calcium ions, xyloglucan gels are used in response to temperature fluctuations. To increase the efficacy of the treatment, the studies sought to enhance gel characteristics such as gelation temperature, thickness, and drug release rate. The improved formulations showed anti-inflammatory solid effects and efficient drug delivery for periodontal conditions by significantly reducing pocket depth, plaque, and gum inflammation. The direct application ofin situgels offers targeted delivery, few side effects, and self-administration; the review focuses on the benefits, advantages, and disadvantages ofin situgel administration for periodontitis, as well as the characteristics of tooth physiology, preparation techniques, and polymers and biomarkers used. Assessments ofin situgels: To significantly improve periodontitis treatment, future research should focus on clinical studies to contribute substantially to periodontitis treatment.

Biomarkers for subclinical bovine mastitis: a high throughput TMT-based proteomic investigation.

Mastitis represents the biggest threat to the health and productivity of dairy cows, leading to substantial economic losses in milk production. It manifests in two forms: clinical mastitis, easily diagnosed by visible symptoms, and subclinical mastitis (SCM), which lacks overt clinical signs. SCM's elusive nature often results in it going undetected, thus facilitating the spread of the disease-causing agent due to lack of treatment. Finding a reliable biomarker for early SCM would reduce the possibility of mastitis spreading in the herd, reduce the need for antibiotic use and ultimately reduce milk losses for producers. Utilizing state-of-the-art proteomics techniques, 138 milk samples from dairy cows in continental Croatia underwent analysis. These samples were categorized into four groups based on the Zagreb Mastitis Test (ZMT) and microbiological analysis: lowSCC- (n = 20), lowSCC + (n = 20), medSCC + (n = 79), and highSCC + (n = 19). A total of 386 proteins were identified and quantified, with 76 proteins showing significant differential abundances among the groups. Many of these proteins are linked to the innate immune system, as well as neutrophil and platelet degranulation processes. Through fold changes observed between groups, 15 proteins exhibiting biomarker characteristics for subclinical mastitis (SCM) were identified. Among these, five proteins-cathelicidins (-1, -4, and -7), lactoferrin, and haptoglobin-showed particular promise.

Biomarker conversion from primary breast cancer to synchronous axillary lymph node metastasis and neoadjuvant therapy response: a single-center analysis

PurposeThe biomarker characteristics of breast cancer plays an important role in predicting treatment sensitivity. The aim of the present study was to compare immunohistochemical profiles (ER, PR, HER2, and Ki67) between the primary tumor and synchronous axillary lymph node metastasis and investigate the subsequent effects on neoadjuvant therapy response.MethodsA total of 358 patients with pathologically confirmed synchronous axillary lymph node metastasis at first diagnosis and treated by neoadjuvant therapy at Peking University First Hospital from January 1, 2013 to December 31, 2022 were included in this retrospective study. Clinicopathologic data, especially receptor status in primary and metastatic foci, was collected for each case.ResultsChange of ER, PR, HER2, and Ki67 expression was observed in 5.9%, 8.7%, 12.6%, and 17.3% of patients, respectively. HR discordance was observed more frequently when the ER status (p = 0.023) or PR status (p = 0.010) of primary tumor was negative, while HER2 discordance seemed to be more frequent when the HER2 status of primary tumor was HER2-0 or HER2-low (p < 0.001). Patients with loss of HR-positivity (positive to negative) responded to neoadjuvant chemotherapy better compared to those with stable positive HR expression (50% vs. 11.1%, p = 0.0017). A significantly decrease in pCR rate was observed in patients with unstable HER2 status, but not in the HER2-0/HER2-low subgroup.ConclusionReceptor discordance between primary tumor and synchronous axillary LNM appears to already exist before any anti-tumor therapy. This instability has limited clinical impact on the choice of neoadjuvant therapy at current stage, but further investigation is warranted with the incremental application of endocrine drugs and ADCs in neoadjuvant therapy.