Miracle-dz/UniFAR-FTUs huggingface dataset:
Potential Biomarkers for Post-Stroke Cognitive Impairment: A Systematic Review and Meta-Analysis

Stroke is a primary debilitating disease in adults, occurring in 15 million individuals each year and causing high mortality and disability rates. The latest estimate revealed that stroke is currently the second leading cause of death worldwide. Post-stroke cognitive impairment (PSCI), one of the major complications after stroke, is frequently underdiagnosed. However, stroke has been reported to increase the risk of cognitive impairment by at least five to eight times. In recent decades, peripheral blood molecular biomarkers for stroke have emerged as diagnostic, prognostic, and therapeutic targets. In this study, we aimed to evaluate some blood-derived proteins for stroke, especially related to brain damage and cognitive impairments, by conducting a systematic review and meta-analysis and discussing the possibility of these proteins as biomarkers for PSCI. Articles published before 26 July 2021 were searched in PubMed, Embase, the Web of Science, and the Cochrane Library to identify all relevant studies reporting blood biomarkers in patients with stroke. Among 1820 articles, 40 were finally identified for this study. We meta-analyzed eight peripheral biomarker candidates: homocysteine (Hcy), high-density lipoprotein cholesterol (HDL-C), C-reactive protein (CRP), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglyceride (TG), uric acid, and glycated hemoglobin (HbA1c). The Hcy, CRP, TC, and LDL-C levels were significantly higher in patients with PSCI than in the non-PSCI group; however, the HDL-C, TG, uric acid, and HbA1c levels were not different between the two groups. Based on our findings, we suggest the Hcy, CRP, TC, and LDL-C as possible biomarkers in patients with post-stroke cognitive impairment. Thus, certain blood proteins could be suggested as effective biomarkers for PSCI.
Influenza-induced Tpl2 expression within alveolar epithelial cells is dispensable for host viral control and anti-viral immunity

Tumor progression locus 2 (Tpl2) is a serine/threonine kinase that regulates the expression of inflammatory mediators in response to Toll-like receptors (TLR) and cytokine receptors. Global ablation of Tpl2 leads to severe disease in response to influenza A virus (IAV) infection, characterized by respiratory distress, and studies in bone marrow chimeric mice implicated Tpl2 in non-hematopoietic cells. Lung epithelial cells are primary targets and replicative niches of influenza viruses; however, the specific regulation of antiviral responses by Tpl2 within lung epithelial cells has not been investigated. Herein, we show that Tpl2 is basally expressed in primary airway epithelial cells and that its expression increases in both type I and type II airway epithelial cells (AECI and AECII) in response to influenza infection. We used Nkx2.1-cre to drive Tpl2 deletion within pulmonary epithelial cells to delineate epithelial cell-specific functions of Tpl2 during influenza infection in mice. Although modest increases in morbidity and mortality were attributed to cre-dependent deletion in lung epithelial cells, no alterations in host cytokine production or lung pathology were observed. In vitro, Tpl2 inhibition within the type I airway epithelial cell line, LET1, as well as genetic ablation in primary airway epithelial cells did not alter cytokine production. Overall, these findings establish that Tpl2-dependent defects in cells other than AECs are primarily responsible for the morbidity and mortality seen in influenza-infected mice with global Tpl2 ablation.
Biasing Influence of ‘Mental Shortcuts’ on Diagnostic Decision-Making: Radiologists Can Overlook Breast Cancer in Mammograms When Prior Diagnostic Information Is Available

When making decisions under uncertainty, people in all walks of life, including highly trained medical professionals, tend to resort to using ‘mental shortcuts’, or heuristics. Anchoring-and-adjustment (AAA) is a well-known heuristic in which subjects reach a judgment by starting from an initial internal judgment (‘anchored position’) based on available external information (‘anchoring information’) and adjusting it until they are satisfied. We studied the effects of the AAA heuristic during diagnostic decision-making in mammography. We provided practicing radiologists (N = 27 across two studies) a random number that we told them was the estimate of a previous radiologist of the probability that a mammogram they were about to see was positive for breast cancer. We then showed them the actual mammogram. We found that the radiologists’ own estimates of cancer in the mammogram reflected the random information they were provided and ignored the actual evidence in the mammogram. However, when the heuristic information was not provided, the same radiologists detected breast cancer in the same set of mammograms highly accurately, indicating that the effect was solely attributable to the availability of heuristic information. Thus, the effects of the AAA heuristic can sometimes be so strong as to override the actual clinical evidence in diagnostic tasks.
Deep learning fetal ultrasound video model match human observers in biometric measurements

Objective. This work investigates the use of deep convolutional neural networks (CNN) to automatically perform measurements of fetal body parts, including head circumference, biparietal diameter, abdominal circumference and femur length, and to estimate gestational age and fetal weight using fetal ultrasound videos. Approach. We developed a novel multi-task CNN-based spatio-temporal fetal US feature extraction and standard plane detection algorithm (called FUVAI) and evaluated the method on 50 freehand fetal US video scans. We compared FUVAI fetal biometric measurements with measurements made by five experienced sonographers at two time points separated by at least two weeks. Intra- and inter-observer variabilities were estimated. Main results. We found that automated fetal biometric measurements obtained by FUVAI were comparable to the measurements performed by experienced sonographers The observed differences in measurement values were within the range of inter- and intra-observer variability. Moreover, analysis has shown that these differences were not statistically significant when comparing any individual medical expert to our model. Significance. We argue that FUVAI has the potential to assist sonographers who perform fetal biometric measurements in clinical settings by providing them with suggestions regarding the best measuring frames, along with automated measurements. Moreover, FUVAI is able perform these tasks in just a few seconds, which is a huge difference compared to the average of six minutes taken by sonographers. This is significant, given the shortage of medical experts capable of interpreting fetal ultrasound images in numerous countries.
Fewer daily steps are associated with greater cartilage oligomeric matrix protein response to loading post‐ACL reconstruction

Aberrant joint loading contributes to the development of posttraumatic knee osteoarthritis (PTOA) following anterior cruciate ligament reconstruction (ACLR); yet little is known about the association between joint loading due to daily walking and cartilage health post‐ACLR. Accelerometer‐based measures of daily steps and cadence (i.e., rate of steps/min) provide information regarding daily walking in a real‐world setting. The purpose of this study was to determine the association between changes in serum cartilage oligomeric matrix protein (COMP; %∆COMP), a mechanosensitive biomarker that is associated with osteoarthritis progression, following a standardized walking protocol and daily walking in individuals with ACLR and uninjured controls. Daily walking was assessed over 7 days using an accelerometer worn on the right hip in 31 individuals with ACLR and 21 controls and quantified as mean steps/day and time spent in ≥100 steps/min. Serum COMP was measured before and following a 3000‐step walking protocol at a preferred speed. %∆COMP was calculated as a change in COMP relative to the prewalking value. Linear regressions were used to examine associations between daily walking and %∆COMP after adjusting for preferred speed. Fewer daily steps (ΔR2 = 0.18, p = 0.02) and fewer minutes spent in ≥100 steps/min (ΔR2 = 0.16, p = 0.03) were associated with greater %∆COMP following walking in individuals with ACLR; no statistically significant associations existed in controls (daily steps: ΔR2 = 0.03, p = 0.47; time ≥100 steps/min: ΔR2 < 0.01, p = 0.81). Clinical significance: Individuals with ACLR who engage in less daily walking undergo greater %ΔCOMP, which may represent greater cartilage degradation or turnover in response to walking.
Biomechanical Characteristics of the Knee Joint during Gait in Obese versus Normal Subjects

Knee osteoarthritis (OA) is a growing source of pain and disability. Obesity is the most important avoidable risk factor underlying knee OA. The processes by which obesity impacts osteoarthritis are of tremendous interest to osteoarthritis researchers and physicians, where the joint mechanical load is one of the pathways generally thought to cause or intensify the disease process. In the current work, we developed a hybrid framework that simultaneously incorporates a detailed finite element model of the knee joint within a musculoskeletal model to compute lower extremity muscle forces and knee joint stresses in normal-weight (N) and obese (OB) subjects during the stance phase gait. This model accounts for the synergy between the active musculature and passive structures. In comparing OB subjects and normal ones, forces significantly increased in all muscle groups at most instances of stance. Mainly, much higher activation was computed with lateral hamstrings and medial gastrocnemius. Cartilage contact average pressure was mostly supported by the medial plateau and increased by 22%, with a larger portion of the load transmitted via menisci. This medial compartment experienced larger relative movement and cartilage stresses in the normal subjects and continued to do so with a higher level in the obese subjects. Finally, the developed bioengineering frame and the examined parameters during this investigation might be useful clinically in evaluating the initiation and propagation of knee OA.
Performance analysis of data mining algorithms for diagnosing COVID-19

BACKGROUND: An outbreak of atypical pneumonia termed COVID-19 has widely spread all over the world since the beginning of 2020. In this regard, designing a prediction system for the early detection of COVID-19 is a critical issue in mitigating virus spread. In this study, we have applied selected machine learning techniques to select the best predictive models based on their performance. MATERIALS AND METHODS: The data of 435 suspicious cases with COVID-19 which were recorded from the Imam Khomeini Hospital database between May 9, 2020 and December 20, 2020, have been taken into consideration. The Chi-square method was used to determine the most important features in diagnosing the COVID-19; eight selected data mining algorithms including multilayer perceptron (MLP), J-48, Bayesian Net (Bayes Net), logistic regression, K-star, random forest, Ada-boost, and sequential minimal optimization (SMO) were applied in data mining. Finally, the most appropriate diagnostic model for COVID-19 was obtained based on comparing the performance of the selected algorithms. RESULTS: As the result of using the Chi-square method, 21 variables were identified as the most important diagnostic criteria in COVID-19. The results of evaluating the eight selected data mining algorithms showed that the J-48 with true-positive rate = 0.85, false-positive rate = 0.173, precision = 0.85, recall = 0.85, F-score = 0.85, Matthews Correlation Coefficient = 0.68, and area under the receiver operator characteristics = 0.68, respectively, had the higher performance than the other algorithms. CONCLUSION: The results of evaluating the performance criteria showed that the J-48 can be considered as a suitable computational prediction model for diagnosing COVID-19 disease.
Clinical Indications to Germectomy in Pediatric Dentistry: A Systematic Review

Germectomy is a procedure often required in patients at developmental age. It is defined as the surgical removal of the third molar at a very specific stage of development. The aim of this study was to systematically analyze the literature in terms of clinical indications for germectomy in patients at developmental age. Literature searches were performed using PubMed, Google Scholar, Cochrane Library and Scopus from 1952 to 30 June 2021. The study protocol was registered after the screening stage (PROSPERO CRD42021262949). The search strategy identified 3829 articles: 167 from PubMed, 2860 from Google Scholar, 799 from Cochrane Library and 3 from Scopus. Finally, eight full-text papers were included into the qualitative analysis. Based on the included studies, clinical indications for germectomy were mainly related to orthodontic causes, infectious and cariogenic causes and prophylaxis. Based on these results, it is not possible to present evidence-based clinical indications for germectomy in patients at developmental age. Clinical trials on this subject focused specifically on patients at developmental age are awaited.
Thrombocytopenia in COVID-19 and vaccine-induced thrombotic thrombocytopenia

The highly heterogeneous symptomatology and unpredictable progress of COVID-19 triggered unprecedented intensive biomedical research and a number of clinical research projects. Although the pathophysiology of the disease is being progressively clarified, its complexity remains vast. Moreover, some extremely infrequent cases of thrombotic thrombocytopenia following vaccination against SARS-CoV-2 infection have been observed. The present study aimed to map the signaling pathways of thrombocytopenia implicated in COVID-19, as well as in vaccine-induced thrombotic thrombocytopenia (VITT). The biomedical literature database, MEDLINE/PubMed, was thoroughly searched using artificial intelligence techniques for the semantic relations among the top 50 similar words (>0.9) implicated in COVID-19-mediated human infection or VITT. Additionally, STRING, a database of primary and predicted associations among genes and proteins (collected from diverse resources, such as documented pathway knowledge, high-throughput experimental studies, cross-species extrapolated information, automated text mining results, computationally predicted interactions, etc.), was employed, with the confidence threshold set at 0.7. In addition, two interactomes were constructed: i) A network including 119 and 56 nodes relevant to COVID-19 and thrombocytopenia, respectively; and ii) a second network containing 60 nodes relevant to VITT. Although thrombocytopenia is a dominant morbidity in both entities, three nodes were observed that corresponded to genes (AURKA, CD46 and CD19) expressed only in VITT, whilst ADAM10, CDC20, SHC1 and STXBP2 are silenced in VITT, but are commonly expressed in both COVID-19 and thrombocytopenia. The calculated average node degree was immense (11.9 in COVID-19 and 6.43 in VITT), illustrating the complexity of COVID-19 and VITT pathologies and confirming the importance of cytokines, as well as of pathways activated following hypoxic events. In addition, PYCARD, NLP3 and P2RX7 are key potential therapeutic targets for all three morbid entities, meriting further research. This interactome was based on wild-type genes, revealing the predisposition of the body to hypoxia-induced thrombosis, leading to the acute COVID-19 phenotype, the 'long-COVID syndrome', and/or VITT. Thus, common nodes appear to be key players in illness prevention, progression and treatment.
Differences in peripheral immune system gene expression in frontotemporal degeneration

Supplemental Digital Content is available in the text Abstract The peripheral immune system has a key pathophysiologic role in Frontotemporal degeneration (FTD). We sought a comprehensive transcriptome-wide evaluation of gene expression alterations unique to the peripheral immune system in FTD compared to healthy controls and amyotrophic lateral sclerosis.Nineteen subjects with FTD with 19 matched healthy controls and 9 subjects with amyotrophic lateral sclerosis underwent isolation of peripheral blood mononuclear cells (PBMCs) which then underwent bulk ribonucleic acid sequencing. There was increased expression in genes associated with CD19+ B-cells, CD4+ T-cells, and CD8+ T-cells in FTD participants compared to healthy controls. In contrast, there was decreased expression in CD33+ myeloid cells, CD14+ monocytes, BDCA4+ dendritic cells, and CD56+ natural killer cells in FTD and healthy controls. Additionally, there was decreased expression is seen in associated with 2 molecular processes: autophagy with phagosomes and lysosomes, and protein processing/export. Significantly downregulated in PBMCs of FTD subjects were genes involved in antigen processing and presentation as well as lysosomal lumen formation compared to healthy control PBMCs. Our findings that the immune signature based on gene expression in PBMCs of FTD participants favors adaptive immune cells compared to innate immune cells. And decreased expression in genes associated with phagosomes and lysosomes in PBMCs of FTD participants compared to healthy controls.
HMGB1-Mediated Activation of the Inflammatory-Reparative Response Following Myocardial Infarction

Different cell types belonging to the innate and adaptive immune system play mutually non-exclusive roles during the different phases of the inflammatory-reparative response that occurs following myocardial infarction. A timely and finely regulation of their action is fundamental for the process to properly proceed. The high-mobility group box 1 (HMGB1), a highly conserved nuclear protein that in the extracellular space can act as a damage-associated molecular pattern (DAMP) involved in a large variety of different processes, such as inflammation, migration, invasion, proliferation, differentiation, and tissue regeneration, has recently emerged as a possible regulator of the activity of different immune cell types in the distinct phases of the inflammatory reparative process. Moreover, by activating endogenous stem cells, inducing endothelial cells, and by modulating cardiac fibroblast activity, HMGB1 could represent a master regulator of the inflammatory and reparative responses following MI. In this review, we will provide an overview of cellular effectors involved in these processes and how HMGB1 intervenes in regulating each of them. Moreover, we will summarize HMGB1 roles in regulating other cell types that are involved in the different phases of the inflammatory-reparative response, discussing how its redox status could affect its activity.
Assessing Genotoxicity of Ten Different Engineered Nanomaterials by the Novel Semi-Automated FADU Assay and the Alkaline Comet Assay

Increased engineered nanomaterial (ENM) production and incorporation in consumer and biomedical products has raised concerns about the potential adverse effects. The DNA damaging capacity is of particular importance since damaged genetic material can lead to carcinogenesis. Consequently, reliable and robust in vitro studies assessing ENM genotoxicity are of great value. We utilized two complementary assays based on different measurement principles: (1) comet assay and (2) FADU (fluorimetric detection of alkaline DNA unwinding) assay. Assessing cell viability ruled out false-positive results due to DNA fragmentation during cell death. Potential structure–activity relationships of 10 ENMs were investigated: three silica nanoparticles (SiO2-NP) with varying degrees of porosity, titanium dioxide (TiO2-NP), polystyrene (PS-NP), zinc oxide (ZnO-NP), gold (Au-NP), graphene oxide (GO) and two multi-walled carbon nanotubes (MWNT). SiO2-NPs, TiO2-NP and GO were neither cytotoxic nor genotoxic to Jurkat E6-I cells. Quantitative interference corrections derived from GO results can make the FADU assay a promising screening tool for a variety of ENMs. MWNT merely induced cytotoxicity, while dose- and time-dependent cytotoxicity of PS-NP was accompanied by DNA fragmentation. Hence, PS-NP served to benchmark threshold levels of cytotoxicity at which DNA fragmentation was expected. Considering all controls revealed the true genotoxicity for Au-NP and ZnO-NP at early time points.
Compared the Microbiota Profiles between Samples from Bronchoalveolar Lavage and Endotracheal Aspirates in Severe Pneumonia: A Real-World Experience

Lower respiratory tract sampling from endotracheal aspirate (EA) and bronchoalveolar lavage (BAL) are both common methods to identify pathogens in severe pneumonia. However, the difference between these two methods in microbiota profiles remains unclear. We compared the microbiota profiles of pairwise EA and BAL samples in ICU patients with respiratory failure due to severe pneumonia. We prospectively enrolled 50 ICU patients with new onset of pneumonia requiring mechanical ventilation. EA and BAL were performed on the first ICU day, and samples were analyzed for microbial community composition via 16S rRNA metagenomic sequencing. Pathogens were identified in culture medium from BAL samples in 21 (42%) out of 50 patients. No difference was observed in the antibiotic prescription pattern, ICU mortality, or hospital mortality between BAL-positive and BAL-negative patients. The microbiota profiles in the EA and BAL samples are similar with respect to diversity, microbial composition, and microbial community correlations. The antibiotic treatment regimen was rarely changed based on the BAL findings. The samples from BAL did not provide more information than EA in the microbiota profiles. We suggest that EA is more useful than BAL for microbiome identification in mechanically ventilated patients.
Distinction between Antimicrobial Resistance and Putative Virulence Genes Characterization in Plesiomonas shigelloides Isolated from Different Sources

Plesiomonas shigelloides are gram-negative, thermotolerant, motile, and pleomorphic microorganisms that are only distantly related to those of the Enterobacteriaceae and Vibrionaceae families. One of the most common sources of P. shigelloides contamination is human stool, but it may also be found in a wide range of other animals, plants, and aquatic habitats. Antimicrobial resistance in P. shigelloides from seawater and shellfish was investigated, and pathogenicity involved genes were characterized as part of this study. Out of 384 samples of shellfish, 5.7% included P. shigelloides. The presence of P. shigelloides was also discovered in 5% of the seawater sampled. The antimicrobial resistance of 23 P. shigelloides isolates derived from those samples was investigated. All isolates were sensitive to nalidixic acid, carbenicillin, cephalothin, erythromycin, kanamycin, tetracycline, and ciprofloxacin in the study. Several strains isolated from diseased shellfish were tested for virulence in shellfish by intraperitoneal injections. The LD50 values ranged from 12 × 108 to 3 × 1012 cfu/shellfish. When looking for possible virulence factors that may play a significant role in bacterial infection in the current study, we found that all of these genes were present in these strains. These include genes such as elastase, lipase, flagellin, enterotoxin, and DNases. According to these findings, shellfish may serve as a reservoir for multi-resistant P. shigelloides and help spread virulence genes across the environment.