OBJECTIVE: This study was conducted to evaluate the effects of plasma treatment of sandblasted and acid-etched (SLA) titanium implants on surface cleansing and osseointegration in a beagle model.
METHODS: For morphological analysis and XPS analysis, scanning electron microscope and x-ray photoelectron spectroscopy were used to analyze the surface topography and chemical compositions of implant before and after plasma treatment. For this animal experiment, twelve SLA titanium implants were divided into two groups: a control group (untreated implants) and a plasma group (implants treated with plasma). Each group was randomly located in the mandibular bone of the beagle dog (n = 6). After 8 weeks, the beagle dogs were sacrificed, and volumetric analysis and histometric analysis were performed within the region of interest.
RESULTS: In morphological analysis, plasma treatment did not alter the implant surface topography or cause any physical damage. In XPS analysis, the atomic percentage of carbon at the inspection point before the plasma treatment was 34.09%. After the plasma treatment, it was reduced to 18.74%, indicating a 45% reduction in carbon. In volumetric analysis and histometric analysis, the plasma group exhibited relatively higher mean values for new bone volume (NBV), bone to implant contact (BIC), and inter-thread bone density (ITBD) compared to the control group. However, there was no significant difference between the two groups (P > .05).
CONCLUSIONS: Within the limits of this study, plasma treatment effectively eliminated hydrocarbons without changing the implant surface.

Mefenamic acid, renowned for its analgesic properties, stands as a reliable choice for alleviating mild to moderate pain. However, its versatility extends beyond pain relief, with ongoing research unveiling its promising therapeutic potential across diverse domains. A straightforward, environmentally friendly, and sensitive spectrofluorometric technique has been developed for the precise quantification of the analgesic medication, mefenamic acid. This method relies on the immediate reduction of fluorescence emitted by a probe upon interaction with varying concentrations of the drug. The fluorescent probe utilized, N-phenyl-1-naphthylamine (NPNA), was synthesized in a single step, and the fluorescence intensities were measured at 480 nm using synchronous fluorescence spectroscopy with a wavelength difference of 200 nm. Temperature variations and lifetime studies indicated that the quenching process was static. The calibration curve exhibited linearity within the concentration range of 0.50-9.00 μg/mL, with a detection limit of 60.00 ng/mL. Various experimental parameters affecting the quenching process were meticulously examined and optimized. The proposed technique was successfully applied to determine mefenamic acid in pharmaceutical formulations, plasma, and urine, yielding excellent recoveries ranging from 98% to 100.5%. The greenness of the developed method was evaluated using three metrics: the Analytical Eco-scale, AGREE, and the Green Analytical Procedure Index.

Celiac Disease (CD) is a primary malabsorption syndrome resulting from the interplay of genetic, immune, and dietary factors. CD negatively impacts daily activities and may lead to conditions such as osteoporosis, malignancies in the small intestine, ulcerative jejunitis, and enteritis, ultimately causing severe malnutrition. Therefore, an effective and rapid differentiation between healthy individuals and those with celiac disease is crucial for early diagnosis and treatment. This study utilizes Raman spectroscopy combined with deep learning models to achieve a non-invasive, rapid, and accurate diagnostic method for celiac disease and healthy controls. A total of 59 plasma samples, comprising 29 celiac disease cases and 30 healthy controls, were collected for experimental purposes. Convolutional Neural Network (CNN), Multi-Scale Convolutional Neural Network (MCNN), Residual Network (ResNet), and Deep Residual Shrinkage Network (DRSN) classification models were employed. The accuracy rates for these models were found to be 86.67%, 90.76%, 86.67% and 95.00%, respectively. Comparative validation results revealed that the DRSN model exhibited the best performance, with an AUC value and accuracy of 97.60% and 95%, respectively. This confirms the superiority of Raman spectroscopy combined with deep learning in the diagnosis of celiac disease.

OBJECTIVE: Quantifying the contribution of individual coagulation factors to haemostasis may aid our understanding of the haemostatic function in patients with rare coagulation deficiencies (RCDs) and the exploration of suitable treatments.
METHODS: Reconstituted blood prepared from specific coagulation factor-deficient plasma (factor [F]II; prothrombin, FV, FVII, FVIII, FIX, FX, FXI or FXII) and red blood cell/platelet products were used to simulate the whole blood of patients with RCD. We prepared in vitro treatment models for patients with prothrombin deficiency using coagulation factor agents and fresh frozen plasma. Haemostatic function was measured using a microchip flow chamber system at 600 s-1.
RESULTS: The haemostatic function was low, especially in blood samples reconstituted with prothrombin- and FX-deficient plasma. In a plasma transfusion model of prothrombin deficiency, haemostatic function recovered after 10% replacement with normal plasma and reached a plateau at ≧60% replacement. A treatment model of prothrombin deficiency with prothrombin complex concentrates revealed dose-dependent therapeutic effects in the range of 0-50 IU/kg.
CONCLUSIONS: Microchip flow chamber system-based quantification of haemostatic function using reconstituted blood could predict haemostasis and therapeutic effects of treatments in patients with prothrombin deficiency.

The use of protein biomarkers in blood for clinical settings is limited by the cost and accessibility of traditional venipuncture sampling. The dried blood spot (DBS) technique offers a less invasive and more accessible alternative. However, protein stability in DBS has not been well evaluated. Herein, we deployed a quantitative LC-MS/MS system to construct proteomic atlases of whole blood, DBSs, plasma, and blood cells. Approximately 4% of detected proteins\' abundance was significantly altered during blood drying into blood spots, with overwhelming disturbances in cytoplasmic fraction. We also reported a novel finding suggesting a decrease in the level of membrane/cytoskeletal proteins (SLC4A1, RHAG, DSC1, DSP, and JUP) and an increase in the level of proteins (ATG3, SEC14L4, and NRBP1) related to intracellular trafficking. Furthermore, we identified 19 temporally dynamic proteins in DBS samples stored at room temperature for up to 6 months. There were three declined cytoskeleton-related proteins (RDX, SH3BGRL3, and MYH9) and four elevated proteins (XPO7, RAN, SLC2A1, and SLC29A1) involved in cytoplasmic transport as representatives. The instability was governed predominantly by hydrophilic proteins and enhanced significantly with an increasing storage time. Our analyses provide comprehensive knowledge of both short- and long-term storage stability of DBS proteins, forming the foundation for the widespread use of DBS in clinical proteomics and other analytical applications.

Synthesis and secretion of bile acids (BA) is a key physiological function of the liver. In pathological conditions like portosystemic shunt, hepatic insufficiency, hepatitis, or cirrhosis BA metabolism and secretion are disturbed. Quantification of total serum BA is an established diagnostic method to assess the general liver function and allows early detection of abnormalities, liver disease progression and guidance of treatment decisions. To date, data on comparative BA profiles in dogs are limited. However, BA profiles might be even better diagnostic parameters than total BA concentrations. On this background, the present study analyzed and compared individual BA profiles in serum, plasma, urine, and feces of 10 healthy pups and 40 adult healthy dogs using ultra-high performance liquid chromatography coupled to electrospray ionization mass spectrometry. Sample preparation was performed by solid-phase extraction for serum, plasma, and urine samples or by protein precipitation with methanol for the feces samples. For each dog, 22 different BA, including unconjugated BA and their glycine and taurine conjugates, were analyzed. In general, there was a great interindividual variation for the concentrations of single BA, mostly exemplified by the fact that cholic acid (CA) was by far the most prominent BA in blood and urine samples of some of the dogs (adults and pups), while in others, CA was under the detection limit. There were no significant age-related differences in the BA profiles, but pups showed generally lower absolute BA concentrations in serum, plasma, and urine. Taurine-conjugated BA were predominant in the serum and plasma of both pups (68%) and adults (74-75%), while unconjugated BA were predominant in the urine and feces of pups (64 and 95%, respectively) and adults (68 and 99%, respectively). The primary BA chenodeoxycholic acid and taurocholic acid and the secondary BA deoxycholic acid and lithocholic acid were the most robust analytes for potential diagnostic purpose. In conclusion, this study reports simultaneous BA profiling in dog serum, plasma, urine, and feces and provides valuable diagnostic data for subsequent clinical studies in dogs with different kinds of liver diseases.

BACKGROUND: Vervets are non-human primates that share high genetic homology with humans and develop amyloid beta (Aβ) pathology with aging. We expand current knowledge by examining Aβ pathology, aging, cognition, and biomarker proteomics.
METHODS: Amyloid immunoreactivity in the frontal cortex and temporal cortex/hippocampal regions from archived vervet brain samples ranging from young adulthood to old age was quantified. We also obtained cognitive scores, plasma samples, and cerebrospinal fluid (CSF) samples in additional animals. Plasma and CSF proteins were quantified with platforms utilizing human antibodies.
RESULTS: We found age-related increases in Aβ deposition in both brain regions. Bioinformatic analyses assessed associations between biomarkers and age, sex, cognition, and CSF Aβ levels, revealing changes in proteins related to immune-related inflammation, metabolism, and cellular processes.
CONCLUSIONS: Vervets are an effective model of aging and early-stage Alzheimer\'s disease, and we provide translational biomarker data that both align with previous results in humans and provide a basis for future investigations.
CONCLUSIONS: We found changes in immune and metabolic plasma biomarkers associated with age and cognition. Cerebrospinal fluid (CSF) biomarkers revealed changes in cell signaling indicative of adaptative processes. TNFRSF19 (TROY) and Artemin co-localize with Alzheimer\'s disease pathology. Vervets are a relevant model for translational studies of early-stage Alzheimer\'s disease.

Plasma-activated water (PAW) contains multiple active species that alter the structure of myofibrillar protein (MP) to enhance their gel properties. This work investigated the impact of PAW on the oxidation of cysteine in MP by label-free quantitative proteomics. PAW treatment caused the oxidation of 8241 cysteine sites on 2815 proteins, and structural proteins such as nebulin, myosin XVIIIB, myosin XVIIIA, and myosin heavy chain were susceptible to oxidation by PAW. Bioinformatics analysis, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, subcellular localization, and STRING analysis, indicated that these proteins with differential oxidation sites were mainly derived from the cytoplasm and membrane, and were involved in multiple GO terms and KEGG pathways. This is one of the first reports of the redox proteomic changes induced by PAW treatment, and the results are useful for understanding the possible mechanism of PAW-induced oxidation of MP.

Tumor derived Extracellular vesicles (EVs) in circulating system may contain tumor-specific markers, and EV detection in body fluids could become an important tool for early tumor diagnosis, prognosis assessment. Meningiomas are the most common benign intracranial tumors, few studies have revealed specific protein markers for meningiomas from patients\' body fluids. In this study, using proximity labeling technology and non-tumor patient plasma as a control, we detected protein levels of EVs in plasma samples from meningioma patients before and after surgery. Through bioinformatics analysis, we discovered that the levels of EV count and protein count in meningioma patients were significantly higher than those in healthy controls, and were significantly decreased postoperatively. Among EV proteins in meningioma patients, the levels of MUC1, SIGLEC11, E-Cadherin, KIT, and TASCTD2 were found not only significantly elevated than those in healthy controls, but also significantly decreased after tumor resection. Moreover, using publicly available GEO databases, we verified that the mRNA level of MUC1, SIGLEC11, and CDH1 in meningiomas were significantly higher in comparison with normal dura mater tissues. Additionally, by analyzing human meningioma specimens collected in this study, we validated the protein levels of MUC1 and SIGLEC11 were significantly increased in WHO grade 2 meningiomas and were positively correlated with tumor proliferation levels. This study indicates that meningiomas secret EV proteins into circulating system, which may serve as specific markers for diagnosis, malignancy predicting and tumor recurrent assessment.

Cancer detection is challenging, especially in patients with unspecific cancer symptoms. Biomarkers could identify patients at high risk of cancer. Prior studies indicate that neutrophil extracellular traps (NETs) are associated with cancer, but also with autoimmune and infectious diseases. The objective of this prospective study was to investigate markers associated with NET formation (nucleosomal citrullinated histone 3 [H3Cit-DNA], cell free DNA [cfDNA] and neutrophil elastase [NE]), and c-reactive protein (CRP) in patients with unspecific cancer symptoms, such as fatigue, weight loss or radiological sign of malignancy without an apparent primary tumor, referred to the Diagnostic Center at Danderyd Hospital in Sweden. Blood samples were drawn on admission, before cancer diagnosis. Out of 475 patients, 160 (34%) were diagnosed with cancer, 56 (12%) with autoimmune disease, 32 (7%) with infectious disease, 71 (15%) with other diseases and 156 (33%) received no diagnosis. H3Cit-DNA, cfDNA, NE and CRP were significantly higher in patients with cancer compared to patients without cancer (p < 0.0001, p < 0.0001, p = 0.004, and p = 0.0002 respectively). H3Cit-DNA, but not cfDNA, NE or CRP, was significantly elevated in patients with cancer compared to patients with autoimmune disease (p = 0.0001). H3Cit-DNA, cfDNA, NE or CRP did not differ between cancer and infectious disease. In conclusion, H3Cit-DNA is elevated in patients diagnosed with cancer compared to non-cancer patients with the same symptomatology. Further studies should evaluate if H3Cit-DNA could aid in selecting patients that would benefit the most from a rapid cancer diagnostic work-up.