Salivary Distinctiveness and Modifications in Males with Diabetes and Behçet's Disease

Diagnostic value of isolated plasma biomarkers and its combination in neurodegenerative dementias: A multicenter cohort study

BACKGROUND

Plasma amyloid-β (Aβ), phosphorylated tau-181 (p-tau181), neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) potentially aid in the diagnosis of neurodegenerative dementias. We aim to conduct a comprehensive comparison between different biomarkers and their combination, which is lacking, in a multicenter Chinese dementia cohort consisting of Alzheimer's disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP).

METHODS

We enrolled 92 demented patients [64 AD, 16 FTD, and 12 PSP with dementia] and 20 healthy controls (HC). Their plasma Αβ, p-tau181, NfL, and GFAP were detected by highly sensitive-single molecule immunoassays. Αβ pathology in patients was measured by cerebrospinal fluid or/and amyloid positron emission tomography.

RESULTS

All plasma biomarkers tested were significantly altered in dementia patients compared with HC, especially Aβ42/Aβ40 and NfL showed significant performance in distinguishing AD from HC. A combination of plasma Aβ42/Aβ40, p-tau181, NfL, and GFAP could discriminate FTD or PSP well from HC and was able to distinguish AD and non-AD (FTD/PSP).

CONCLUSIONS

Our results confirmed the diagnostic performance of individual plasma biomarkers Aβ42/Aβ40, p-tau181, NfL, and GFAP in Chinese dementia patients and noted that a combination of these biomarkers may be more accurate in identifying FTD/PSP patients and distinguishing AD from non-AD dementia.

The impact of dietary supplements on blood pressure in older adults: A network meta-analysis of randomized controlled trials

Purpose

The prevalence of hypertension (HTN) increases with age and there is a need for effective, evidence-based treatments for HTN among older adults. The objective of this study was to perform a network meta-analysis to evaluate the effectiveness of different forms of nutritional supplementation on reducing blood pressure in older adults.

Methods

A systematic review using PubMed and Clinical Key was performed to identify randomized controlled trials (RCTs) evaluating the effects of dietary supplements on blood pressure in adults older than 65 years of age. Network meta-analysis (NMA) was used to compare and rank the effects of different supplements on systolic (sBP), diastolic (dBP), and mean (mBP) blood pressure. Supplements were ranked according to P score. Meta-regressions were conducted to examine whether treatment effects were moderated by baseline BP and supplementation duration.

Findings

We identified 144 relevant studies in the literature, twelve of which met criteria for inclusion in NMA. The included studies were published between 2003 and 2022. In reducing sBP, docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), inorganic nitrates, tart cherry juice, and vitamin D supplementation were more effective than placebo, and the effect of tart cherry juice outranked that of vitamin D, vitamin E, and vitamin K2. In reducing dBP, inorganic nitrates, DHA and EPA, protein, resveratrol, and vitamin D supplementation were more effective than placebo, and the effect of resveratrol outranked that of tart cherry juice, vitamin D, vitamin E, and vitamin K2. However, the effects of tart cherry juice on sBP and resveratrol on dPB were smaller than the pooled effect of placebo, and none of the pairwise differences between the effects of examined supplements were statistically significant. Caution is needed when interpreting these results given concerns about the risk of bias assessed in seven of the twelve studies included in this analysis.

Saliva biomarkers in oral disease

Saliva is a versatile biofluid that contains a wide variety of biomarkers reflecting both physiologic and pathophysiologic states. Saliva collection is noninvasive and highly applicable for tests requiring serial sampling. Furthermore, advances in test accuracy, sensitivity and precision for saliva has improved diagnostic performance as well as the identification of novel markers especially in oral disease processes. These include dental caries, periodontitis, oral squamous cell carcinoma (OSCC) and Sjögren's syndrome (SS). Numerous growth factors, enzymes, interleukins and cytokines have been identified and are the subject of much research investigation. This review highlights current procedures for successful determination of saliva biomarkers including preanalytical factors associated with sampling, storage and pretreatment as well as subsequent analysis. Moreover, it provides an overview of the diagnostic applications of these salivary biomarkers in common oral diseases.

The accuracy of serum osmolarity calculation in small children

Background

Serum osmolality can be measured (Omeas) or calculated (Ocal). Many formulas for Ocal have been already published, but data regarding the most accurate equation in small babies is not available. Thus, we aim to compare Omeas and Ocal obtained by different formulas in newborns and small children.

Methods

The study included 280 serum samples taken from children, from the first day of life to 2 years (mean age 8.2 ± 7.6 months) treated in the University Children's Hospital in Krakow. The serum osmolality was measured by osmometer and calculated by 8 common formulas.

Results

The mean value of Omeas (2 8 5 .8 ± 5 .1 mOsm/kgH2O) was significantly different as compared to the mean values of Ocal (p< 0.01) for all formulas, except Ocal obtained by the formula: 1.86*(N a + K) +1.15*Glu + Urea + 14. According to Bland-Altman analysis, this formula showed the best performance for estimating osmolality. In children under 3 months of life Passing-Bablok regression indicated both systematic and proportional error for results obtained by each formula compared to the measured values.

Conclusions

To calculate osmolarity in children aged between 3 months and 2 years old the following equation: 1 .86*(N a + K) + 1.1 5*G lu+ U rea+ 14 might be used, whereas serum osmolality in children up to 3 month of life should be measured.

Caries-related salivary parameters and oral microbial flora in patients with type 1 diabetes: A meta-analysis

OBJECTIVES

This study aimed to conduct a meta-analysis by synthesising the outcomes of studies that investigated the relationship between type 1 diabetes (T1D) and salivary flow rate (SFR), salivary pH (SpH), salivary buffer capacity (SBC), streptococcus Mutans (SM), and lactobacillus (LB) counts.

MATERIAL AND METHODS

The PRISMA statement guide was followed for the meta-analysis. Electronic databases were searched, and study selection and data collection processes were performed. The risks of bias in individual studies and across studies were assessed. Mean differences (MD) and Odds Ratio (OR) were used to measure the effect estimates in the comparisons.

RESULTS

29 studies were included in the qualitative and quantitative syntheses. Significantly higher SFR (MD = -0.22, CI: -0.26, -0.18; p < 0.001) and SpH (MD = -0.59, CI: -0.81, -0.36; p < 0.001) were observed in the healthy individuals than T1D individuals. No significant difference was observed among groups in terms of SBC (MD = 0.10, CI: -0.46,0.66; p = 0.73). An increased odds ratio of SM counts were observed regarding the T1D (OR = 3.09, 95% CI: 1.16, 8.20; p = 0.02). No association was found between LB counts and T1D (OR = 2.15, 95% CI: 0.38, 11.98; p = 0.38).

CONCLUSIONS

Subjects with T1D have a significantly lesser SFR and SpH than healthy individuals. But no significant difference is available in terms of SBC. Lower SM counts were observed in individuals with T1D, while no association was observed regarding LB counts. The tendency to dental caries is more likely in subjects with T1D due to lower SFR, SpH, and higher SM.

Analysis of conventional and nonconventional forensic specimens in drug-facilitated sexual assault by liquid chromatography and tandem mass spectrometry

The incidence of drug-facilitated sexual assault (DFSA) has dramatically increased in the last decades. Forensic analytical scientists continuously seek new methods and specimens to prove the incidence of intoxication for the judiciary system. Factors influencing sample selection include the ease of obtaining the samples and the window of detection of the drugs, among others. Both conventional (blood, urine) and non-conventional specimens (hair, nails, fluids) have been proposed as suitable in DFSA cases. Reported sample treatments include a variety of liquid-liquid and solid-phase extraction as well as dilute-and-shoot procedures and microextraction techniques. Regarding analysis, liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) has emerged as the preferred confirmatory technique, due to its sensitivity, selectivity, and wide-scope applicability. In this review, we critically discuss the most common specimens and sample treatments/analysis procedures (related to LC-MS/MS) that have been reported during the last ten years. As a final goal, we intend to provide a critical overview and suggest analytical recommendations for the establishment of suitable analytical strategies in DFSA cases.

Empirical Analysis of Forest Penalizing Attribute and Its Enhanced Variations for Android Malware Detection

As a result of the rapid advancement of mobile and internet technology, a plethora of new mobile security risks has recently emerged. Many techniques have been developed to address the risks associated with Android malware. The most extensively used method for identifying Android malware is signature-based detection. The drawback of this method, however, is that it is unable to detect unknown malware. As a consequence of this problem, machine learning (ML) methods for detecting and classifying malware applications were developed. The goal of conventional ML approaches is to improve classification accuracy. However, owing to imbalanced real-world datasets, the traditional classification algorithms perform poorly in detecting malicious apps. As a result, in this study, we developed a meta-learning approach based on the forest penalizing attribute (FPA) classification algorithm for detecting malware applications. In other words, with this research, we investigated how to improve Android malware detection by applying empirical analysis of FPA and its enhanced variants (Cas_FPA and RoF_FPA). The proposed FPA and its enhanced variants were tested using the Malgenome and Drebin Android malware datasets, which contain features gathered from both static and dynamic Android malware analysis. Furthermore, the findings obtained using the proposed technique were compared with baseline classifiers and existing malware detection methods to validate their effectiveness in detecting malware application families. Based on the findings, FPA outperforms the baseline classifiers and existing ML-based Android malware detection models in dealing with the unbalanced family categorization of Android malware apps, with an accuracy of 98.94% and an area under curve (AUC) value of 0.999. Hence, further development and deployment of FPA-based meta-learners for Android malware detection and other cybersecurity threats is recommended.

Improving the phishing website detection using empirical analysis of Function Tree and its variants

The phishing attack is one of the most complex threats that have put internet users and legitimate web resource owners at risk. The recent rise in the number of phishing attacks has instilled distrust in legitimate internet users, making them feel less safe even in the presence of powerful antivirus apps. Reports of a rise in financial damages as a result of phishing website attacks have caused grave concern. Several methods, including blacklists and machine learning-based models, have been proposed to combat phishing website attacks. The blacklist anti-phishing method has been faulted for failure to detect new phishing URLs due to its reliance on compiled blacklisted phishing URLs. Many ML methods for detecting phishing websites have been reported with relatively low detection accuracy and high false alarm. Hence, this research proposed a Functional Tree (FT) based meta-learning models for detecting phishing websites. That is, this study investigated improving the phishing website detection using empirical analysis of FT and its variants. The proposed models outperformed baseline classifiers, meta-learners and hybrid models that are used for phishing websites detection in existing studies. Besides, the proposed FT based meta-learners are effective for detecting legitimate and phishing websites with accuracy as high as 98.51% and a false positive rate as low as 0.015. Hence, the deployment and adoption of FT and its meta-learner variants for phishing website detection and applicable cybersecurity attacks are recommended.

Size-dependent light scattering of CoOOH nanoflakes for convenient and sensitive detection of alkaline phosphatase in human serum

As a natural enzyme, alkaline phosphatase (ALP) plays an essential role in clinicopathological examinations and biomedical research, and is capable of hydrolyzing the phosphate group of l-ascorbic acid-2-phosphate (AAP) to yield l-ascorbic acid (L-AA). L-AA reduced cobalt oxyhydroxide (CoOOH) nanoflakes to Co²⁺ , leading to a smaller size and weaker light scattering, which could be monitored by electron microscopic images and optical spectra. The indirect detection of ALP was achieved by the reduced light scattering signal of CoOOH nanoflakes. Under optimal conditions, the decrease in scattering intensity was proportional to the ALP concentration over the range 0.1-160 U/L and the detection limit was 0.034 U/L (3σ/k). Compared with other assays, this proposed light scattering method was more convenient and economic for ALP sensing. The method was successfully applied to ALP analysis in human serum samples, and was similar to the results obtained by commercial kits.

Effects of brain tissue section processing and storage time on gene expression

The pre-processing of samples is important factors that affect the results of the RNA-sequencing (RNA-seq) data. However, the effects of frozen sections storage conditions on the integrity of RNA and sequencing results haven't been reported. The study of frozen section protection schemes can provide reliable experimental results for single-cell and spatial transcriptome sequencing. In this study, RNA was isolated to be studied for RNA from brain section at different temperatures (RT: room temperature, -20 °C) and storage time (0 h, 2 h, 4 h, 8 h, 12 h, 16 h, 24 h, 7day, 3week, 6month). The stability of reference genes was validated using reverse transcription quantitative real-time polymerase chain reaction (qRT-PCR). The results showed that the storage at room temperature significantly affected RNA integrity number (RIN), and the RIN value was lower with the prolongation of storage, while the storage at -20 °C exerted less effect on the RIN value. Cresyl violet staining for brain tissue sections had little effect on RNA integrity. 1925, 899 and 3390 differential expression genes (DEGs) were screened at 2 h, 4 h and 8 h at room temperature, respectively. A total of 892, 478 and 619 genes were shown to be differentially expressed at -20 °C for 7d, 3w and 6 m, respectively. Among them, the expression of glycoprotein m6a (Gpm6a), calmodulin 1 (Calm1), calmodulin 1 (Calm2), thymosin, beta 4, X chromosome (Tmsb4x), ribosomal protein S21 (Rps21) and so on were correlated with RNA quality. According to the expression stability of 4 reference genes (Actb: beta-actin; Gapdh: glyceraldehyde-3-phosphate dehydrogenase; 18S: 18S ribosomal; Hprt1: hypoxanthine phosphoribosyltransferase 1), 18S is the most stable reference gene in the brain. In conclusion, the storage temperature and time of frozen sections have significant effects on RNA integrity and sequencing results. But there are still some genes that are stable and not affected by worsening of overall RNA integrity ie the decrease of RIN value. In addition, 1% cresyl violet staining can protect RNA.

Secretome Analysis of Inductive Signals for BM-MSC Transdifferentiation into Salivary Gland Progenitors

Severe dry mouth in patients with Sjögren's Syndrome, or radiation therapy for patients with head and neck cancer, significantly compromises their oral health and quality of life. The current clinical management of xerostomia is limited to palliative care as there are no clinically-proven treatments available. Previously, our studies demonstrated that mouse bone marrow-derived mesenchymal stem cells (mMSCs) can differentiate into salivary progenitors when co-cultured with primary salivary epithelial cells. Transcription factors that were upregulated in co-cultured mMSCs were identified concomitantly with morphological changes and the expression of acinar cell markers, such as α-amylase (AMY1), muscarinic-type-3-receptor(M3R), aquaporin-5(AQP5), and a ductal cell marker known as cytokeratin 19(CK19). In the present study, we further explored inductive molecules in the conditioned media that led to mMSC reprogramming by high-throughput liquid chromatography with tandem mass spectrometry and systems biology. Our approach identified ten differentially expressed proteins based on their putative roles in salivary gland embryogenesis and development. Additionally, systems biology analysis revealed six candidate proteins, namely insulin-like growth factor binding protein-7 (IGFBP7), cysteine-rich, angiogenetic inducer, 61(CYR61), agrin(AGRN), laminin, beta 2 (LAMB2), follistatin-like 1(FSTL1), and fibronectin 1(FN1), for their potential contribution to mMSC transdifferentiation during co-culture. To our knowledge, our study is the first in the field to identify soluble inductive molecules that drive mMSC into salivary progenitors, which crosses lineage boundaries.