Common Pattern Research Articles

Developing radiology diagnostic tools for pulmonary fibrosis using machine learning methods

BackgroundAccurate and prompt diagnosis of the different patterns for pulmonary fibrosis is essential for patient management. However, accurate diagnosis of the specific pattern is challenging due to overlapping radiographic characteristics. Materials and methodsWe conducted a retrospective chart review utilizing two machine learning methods, classification and regression tree and Bayesian additive regression tree, to select the most important radiographic features for diagnosing the three most common fibrosis patterns and created an online diagnostic app for convenient implementation. ResultsFour hundred patients (median age of 67 with inter quartile range 58–73; 200 males) were included in the study. Peripheral distribution, homogeneity, lower lobe predominance and mosaic attenuation of fibrosis are the four most important features identified. Bayesian additive regression tree demonstrates better performance than classification and regression tree in diagnosis prediction and provides the predicted probability of each diagnosis with uncertainty intervals for each combination of features. ConclusionThe model and app built with Bayesian additive regression tree can be used as an effective tool in assisting radiologists in the diagnostic process of pulmonary fibrosis pattern recognition.

Impact of computer users on cyber defense strategies

AbstractCybersecurity research often focuses primarily or exclusively on the interactions between the attacker, trying to exploit the computer system, and the defender, trying to protect it. However, including the computer users is important because the users’ requirements are the reason the computer system exists.An extension of the Petri net formalism, Petri Nets with Players, Strategies, and Costs (PNPSC) was used to model cyberattacks described in the MITRE Common Attack Pattern Enumeration and Classification database. PNPSC models include the attacker, defender, and computer user as “players” attempting to achieve competing goals. Each player can observe the current marking of a subset of the PNPSC net's places and change the stochastic firing rates of a subset of the net's transitions in order to achieve their goals. A mapping between the markings of a player's observable places and the desired firing rates of player's controllable transitions is the player's strategy.A reinforcement learning algorithm was integrated with PNPSC models of three cyberattack patterns to learn strategies for the defender in simulations both with and without a representation of the computer user. A simulation experiment showed that the defender's reward was lower and the defender's learned strategy was different when the user was represented. A second simulation experiment and statistical analysis confirmed that the differences were not due simply to randomness. With the user represented, the system defender must balance security against usability. This research provides a more complete cyberattack model and shows that user models are important in future cybersecurity simulation.

Comparison of Bone Bruise Pattern Epidemiology between Anterior Cruciate Ligament Rupture and Patellar Dislocation Patients-Implications of Injury Mechanism.

Different bone bruise patterns observed using magnetic resonance imaging (MRI) after non-contact anterior cruciate ligament (ACL) rupture and lateral patellar dislocation may indicate different knee injury mechanisms. In this study, 77 ACL ruptures and 77 patellar dislocations in knee MR images taken from patients with bone bruises at our institution between August 2020 and March 2022 were selected and analyzed. In order to determine typical bone bruising patterns following by ACL rupture and patellar dislocation, sagittal- and transverse-plane images were used to determine bone bruise locations in the directions of medial-lateral and superior-inferior with MR images. The presence, intensity, and location of the bone bruises in specific areas of the femur and tibial after ACL rupture and patellar dislocation were recorded. Relative bone bruise patterns after ACL rupture and patellar dislocation were classified. The results showed that there were four kinds of bone bruise patterns (1-, 2-, 3-, and 4- bone bruises) after ACL rupture. The most common two patterns after ACL rupture were 3- bone bruises (including the lateral femoral condyle and both the lateral-medial tibial plateau, LF + BT; both the lateral-medial femoral condyle and the lateral tibial plateau, BF + LT; and the medial femoral condyle and both the medial and lateral tibial plateau, MF + BT) followed by 4- bone bruises (both the lateral-medial femoral condyle and the tibial plateau, BF + BT), 2- bone bruises (the lateral femoral condyle and tibial plateau, LF + LT; the medial femoral condyle and the lateral tibial plateau, MF + LT; the lateral femoral condyle and the medial tibial plateau, LF + MT; the medial femoral condyle and the tibial plateau, MF + MT; both the lateral-medial tibial plateau, 0 + BT), and 1- bone bruise (only the lateral tibial plateau, 0 + LT). There was only a 1- bone bruise (the latera femoral condyle and medial patella bone bruise) for patellar dislocation, and the most common pattern of patellar dislocation was in the inferior medial patella and the lateral anterior inferior femur. The results suggested that bone bruise patterns after ACL rupture and patellar dislocation are completely different. There were four kinds of bone bruise patterns after non-contact ACL rupture, while there was only one kind of bone bruise pattern after patellar dislocation in patients, which was in the inferior medial patella and lateral anterior inferior femur.

The Labour Share, Government Expenditure and Income Inequality of Post-Soviet Countries

This study analyses the influence of economic growth on inequality, concentrating on the role of governments as mediators. The period studied is from 2000 to 2020, encompassing 11 post-Soviet countries. The primary estimation method used is the two-stage least squares for panel data. Despite the differences in the economic and political systems at the current development stage, the post-Soviet countries share a common pattern in terms of the relationship between economic growth, the labour income share and the level of inequality, which we first show in this article. Government expenditure has the potential to reduce inequality. However, its effectiveness depends largely on government efficiency and the development of democratic institutions. Despite the increase in government spending on education, more is needed to reduce income inequality. Increased economic performance, productivity, and high-quality state institutions are necessary for this change.

A Rare Cell State Underpins Diverse Mechanisms of Adaptive Resistance to CAR T-Cell Therapy in B-Cell Acute Lymphoblastic Leukemia

The most common pattern of treatment failure of B-cell acute lymphoblastic leukemia (B-ALL) following CD19-targeting chimeric antigen receptor T cell therapy (CAR T), is a measurable residual disease (MRD) negative response followed by relapse. Whilst in a fraction of patients relapse is associated with loss of function mutations &/or deletions of the CD19 locus, a significant proportion of patients relapse with CD19+ disease. We hypothesised that this arises from a rare CAR T tolerant persister population that is able to survive the strong therapeutic pressure and seed relapse. To address this, we investigated the clonal origin and transcriptional dynamics of “CAR T tolerant persister cells” via time resolved clonal tracing of the progeny of individual B-ALL clones, using expressed molecular barcodes in an immunocompetent mouse model of CD19 targeting CAR T. We demonstrate that relapse is a pre-determined fate of rare B-ALL clones, which each adopt diverse, yet clone-specific, transcriptional phenotypes at relapse. Moreover, each diverse relapse phenotype appears to be underpinned by a shared, rare “origin of relapse” cell state that is common to all relapse-fated clones. Our immunocompetent mouse model of murine CAR T cells targeting CD19 (ID3-h41bb-3z) on a syngeneic, BCR::ABL1(p190) driven B-ALL recapitulates the clinical scenario of MRD-negative remission followed by CD19+ relapse. We labelled B-ALL cells with SPLINTR (Fennell & Vassiliadis et al. Nature 2022), a lentiviral lineage tracing reagent comprising expressed molecular barcodes that are read out by single cell RNA sequencing (scRNAseq), to allow dynamic profiling of the clonal origin and transcriptome of individual B-ALL clones over time, across multiple therapeutic timepoints including pre-treatment, remission and relapse. Tumour initiating frequency in this model of B-ALL is high with 23% of transplanted clones able to establish fulminant B-ALL. Only 0.7% of clones, however, were able to persist following CAR-T pressure and seed relapse. In fact, >99% of post-CAR T relapsed disease was comprised by just 3 (0.3%) individual clones and in one mouse disease relapse was driven entirely a single clone. Remarkably, we found that the same clones were able to drive relapse in multiple mice, consistent with a the presence of pre-determined, heritable cell-intrinsic properties capable of causing relapse following CAR T. To further study this phenomenon, we performed scRNAseq on these murine B-ALL samples to examine the transcriptional profiles of these rare, relapse fated clones prior to and following CAR T. Whilst prior to therapy, relapse fated clones were transcriptionally identical to the CAR T sensitive clones, following CAR T we observed that relapse fated clones adopted distinct transcriptional profiles compared to their transcriptome in the absence of therapeutic pressure, suggesting transcriptional adaptation underpins their ability to survive therapy. We noted that each resistant clone had a unique adaptive response and consequent transcriptional signature. Remarkably however, the adaptive response of each clone in different mice was essentially identical, indicative of strong, conserved clone-intrinsic mechanisms of adaptation. Although each CAR T resistant clone adopted disparate transcriptional states in the bulk ALL, we identified a single rare cell state (~1% of the bulk B-ALL) that was shared between all clones, highly suggestive of a common point of origin from which transcriptional adaptation arises. This rare cell state demonstrates metabolic hallmarks of therapy resistance and a distinct developmental transcriptional profile most analogous to the recently characterised preBCR-dependant stage of normal B cell development, raising the prospect that these cells represent an “origin of relapse” cell state. Preliminary data suggests that this rare cell state may also be conserved in human Ph+ B-ALL. In summary, by modelling CD19+ B-ALL relapse following MRD negative remission after CAR T, we have identified a rare cell state that our analysis suggests serves as a common and necessary point from which a transcriptionally diverse range of B-ALL phenotypes can arise and be maintained. We have demonstrated that relapse following CAR T emerges due to clone-specific transcriptional differences from this rare cell state, a phenomenon which may extend to a diverse range of therapies in B-ALL.

Transcriptomic without Clinical Response to Menin Inhibition As a Mechanism of Upfront Resistance in Samples from Mutliply Relapsed Patients with KMT2A-Rearranged Leukemia

Inhibitors of the Menin-KMT2A interaction are emerging as promising agents for the treatment of KMT2A-rearranged ( KMT2A-r) acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). Menin is required for the recruitment of the KMT2A-fusion to a subset of its target genes. Early phase clinical trials have shown highly encouraging results in patients with relapsed and refractory leukemias with KMT2A rearrangements and NPM1 mutations. In a recently reported early phase clinical trial evaluating the Menin inhibitor revumenib, about 50% of patients failed to show a clinical response despite robust downregulation of known Menin:KMT2A target genes, suggesting on target activity of the drug. This was the most common pattern of upfront resistance. We sought to understand upfront resistance (in contrast to the reported induced resistance via MEN1 mutations) in patient derived xenograft models. To this end, we evaluated the efficacy of Menin-inhibition in KMT2A-r leukemias with high-risk features: high-risk KMT2A fusion partners in AML ( MLLT10, MLLT4), infant ALL, and serial samples from patients with multiply relapsed ALL. We found that AML samples with high-risk fusion partners banked at initial diagnosis were sensitive to Menin-inhibition in xenografts. In contrast, three highly pretreated samples from patients with KMT2A-AFF1 ALL showed only a slight, or no decrease in latentcy in the Menin-inhibitor arm. Interestingly, Menin inhibition showed excellent in vivo efficacy against leukemia samples obtained from the same three patients earlier in their disease course. Therefore, prior chemotherapy (+/- immunotherapy) selects for Menin-inhibitor resistant cells without prior exposure to Menin inhibitor. Transcriptomic analysis (RNA-Seq) documents sustained on-target efficacy of the Menin inhibitor on a transcriptional level in resistant cells. None of the samples contained a MEN1 mutation at any time point. Targeted panel sequencing at initial diagnosis and relapse documented clonal evolution and the emergence of multiple co-mutations (particularly RAS pathway mutations and TP53 mutations), however, all co-mutations tested failed to induce resistance as a single alteration. It is possible that the cooperation of multiple emerging mutations (rather than a single mutation) is sufficient to drive AML in a KMT2A-fusion independent manner, thus mediating Menin resistance. A transcriptomic response (i.e. downregulation of KMT2A-fusion target genes) without a clinical response was the most common pattern of upfront resistance in the recently reported phase I/II clinical trial of the Menin inhibitor revumenib. We conclude that it will be critical to use Menin-inhibitors upfront or in early lines of therapy before substantial clonal evolution has occurred.

Sleep patterns according to genetically determined ethnicity in the population of São Paulo, Brazil

Sleep is a behavior expressed differently for each individual. However, studies have shown that some ethnic groups express common sleep patterns, which can be observed in different ethnic groups. Previous studies have shown the existence of sleep disparities in populations of different ethnicities. Most of these studies have considered self-reported ethnicity and assessed sleep subjectively. Therefore, the aim of this study was to evaluate sleep disparities in different ethnic groups based on an analysis of genetic ancestry and the use of objective sleep evaluation. To do this, we used data from the São Paulo Epidemiologic Sleep Study (EPISONO), which was undertaken in Brazil, a country that is known for its ethnic/racial diversity. All individuals completed a series of questionnaires, underwent full polysomnography and had their blood collected for DNA extraction. After genotyping and identifying samples with high-quality DNA suitable for genetic analysis, 31 ancestry-informative markers (AIMs) were selected. These markers exhibited substantial allelic frequency differences, enabling the characterization of the three primary founding populations of modern Brazil - Europeans, West-Africans, and Native Americans. Through this analysis, the genetic contribution of each of these ancestral groups was identified in respect of each participant. Based on this, a latent class cluster analysis (LCCA) was performed to define the three clusters that best classified the sample according to ethnic group: African (n = 255), Caucasian (n = 668) and Native American (n = 83). Applying the adjusted model for the confounding variables (age, socio-economic class and sex), statistically significant differences in sleep variables between ethnicities were found. Africans had higher sleep latency compared to the other groups (β = 4.46, CI = 1.18 to 7.74 and β = 7.83, CI = 3.50 to 12.15), while Caucasians had longer total sleep time (β = −16.47, CI = −29.94 to −2.99) and better sleep efficiency (β = −2.19, CI = −4.35 to −0.02) compared to Africans. Regarding the respiratory arousals index (β = −1.11, IC = −2.07 to −0.16) and periodic leg movements index (β = −7.48, CI = −12.08 to −2.88), both were higher among Caucasians compared to Africans. We were able to conclude that genetic ancestry might modulate sleep structure and the occurrence of sleep disorders.

A novel approach to risk exposure and epigenetics—the use of multidimensional context to gain insights into the early origins of cardiometabolic and neurocognitive health

BackgroundEach mother–child dyad represents a unique combination of genetic and environmental factors. This constellation of variables impacts the expression of countless genes. Numerous studies have uncovered changes in DNA methylation (DNAm), a form of epigenetic regulation, in offspring related to maternal risk factors. How these changes work together to link maternal-child risks to childhood cardiometabolic and neurocognitive traits remains unknown. This question is a key research priority as such traits predispose to future non-communicable diseases (NCDs). We propose viewing risk and the genome through a multidimensional lens to identify common DNAm patterns shared among diverse risk profiles.MethodsWe identified multifactorial Maternal Risk Profiles (MRPs) generated from population-based data (n = 15,454, Avon Longitudinal Study of Parents and Children (ALSPAC)). Using cord blood HumanMethylation450 BeadChip data, we identified genome-wide patterns of DNAm that co-vary with these MRPs. We tested the prospective relation of these DNAm patterns (n = 914) to future outcomes using decision tree analysis. We then tested the reproducibility of these patterns in (1) DNAm data at age 7 and 17 years within the same cohort (n = 973 and 974, respectively) and (2) cord DNAm in an independent cohort, the Generation R Study (n = 686).ResultsWe identified twenty MRP-related DNAm patterns at birth in ALSPAC. Four were prospectively related to cardiometabolic and/or neurocognitive childhood outcomes. These patterns were replicated in DNAm data from blood collected at later ages. Three of these patterns were externally validated in cord DNAm data in Generation R. Compared to previous literature, DNAm patterns exhibited novel spatial distribution across the genome that intersects with chromatin functional and tissue-specific signatures.ConclusionsTo our knowledge, we are the first to leverage multifactorial population-wide data to detect patterns of variability in DNAm. This context-based approach decreases biases stemming from overreliance on specific samples or variables. We discovered molecular patterns demonstrating prospective and replicable relations to complex traits. Moreover, results suggest that patterns harbour a genome-wide organisation specific to chromatin regulation and target tissues. These preliminary findings warrant further investigation to better reflect the reality of human context in molecular studies of NCDs.Graphical

Food co-consumption network as a new approach to dietary pattern in non-alcoholic fatty liver disease

Dietary patterns strongly correlate with non-alcoholic fatty liver disease (NAFLD), which is a leading cause of chronic liver disease in developed societies. In this study, we introduce a new definition, the co-consumption network (CCN), which depicts the common consumption patterns of food groups through network analysis. We then examine the relationship between dietary patterns and NAFLD by analyzing this network. We selected 1500 individuals living in Tehran, Iran, cross-sectionally. They completed a food frequency questionnaire and underwent scanning via the FibroScan for liver stiffness, using the CAP score. The food items were categorized into 40 food groups. We reconstructed the CCN using the Spearman correlation-based connection. We then created healthy and unhealthy clusters using the label propagation algorithm. Participants were assigned to two clusters using the hypergeometric distribution. Finally, we classified participants into two healthy NAFLD networks, and reconstructed the gender and disease differential CCNs. We found that the sweet food group was the hub of the proposed CCN, with the largest cliques of size 5 associated with the unhealthy cluster. The unhealthy module members had a significantly higher CAP score (253.7 ± 47.8) compared to the healthy module members (218.0 ± 46.4) (P < 0.001). The disease differential CCN showed that in the case of NAFLD, processed meat had been co-consumed with mayonnaise and soft drinks, in contrast to the healthy participants, who had co-consumed fruits with green leafy and yellow vegetables. The CCN is a powerful method for presenting food groups, their consumption quantity, and their interactions efficiently. Moreover, it facilitates the examination of the relationship between dietary patterns and NAFLD.

I-II mixed fracture characterization of hot mix asphalt under tensile test using notched semi-circular specimens

I-II mixed mode fracture is a common fracture pattern of asphalt pavement under the coupled tension and shearing loads. To address the roles of reclaimed asphalt pavement (RAP) and loading effect, this study proposed a novel test method to characterize the I-II mixed fracture toughness of two types of asphalt mixture. Within the novel tensile test, direct tension load could be applied on the bottom of the notched semi-circular specimens at −10 °C. I-II mixed fracture could be generated by varying the notch angle. Fracture parameters, including the stress intensity factors of mode I and mode II fracture (KIC and KIIC) and the T stress were obtained for specimens with five notch angles, including 0∘, 15∘, 30∘, 45∘ and 60∘, respectively. Results indicated that from 0∘ to 30∘, pure mode I to pure mode II fracture could be generated. Under the same loading rate, compared to mixture A, mixture B presented superior fracture toughness in terms of mode I and mode II stress intensity factors (KI and KII), which was attributed to the fact that the inclusion of RAP in mixture A deteriorated the fracture resistance. Loading rate played positive effect on the fracture toughness. From 1 mm/min to 5 mm/min, the improvements of KIC were 52% and 33% for mixture A and B, respectively. For KIIC, the increase of loading rate enhanced the pure mode II fracture resistance by 30% and 20% for mixture A and B, respectively. Several fracture criteria were adopted for the fracture prediction. Comparison was performed between the test data and the predictions. It was found that compared to MTS criterion, the inclusion of T stress in GMTS criterion made the prediction closer to the test data. Compared to GMTS and GEMTS criteria, GEMTS criterion could provide better estimates for I-II mixed mode, indicating considering the effect of fracture mode on the critical distance (rc) could make the prediction with a higher reliability.

Assessment of mental workload across cognitive tasks using a passive brain-computer interface based on mean negative theta-band amplitudes.

Brain-computer interfaces (BCI) can provide real-time and continuous assessments of mental workload in different scenarios, which can subsequently be used to optimize human-computer interaction. However, assessment of mental workload is complicated by the task-dependent nature of the underlying neural signals. Thus, classifiers trained on data from one task do not generalize well to other tasks. Previous attempts at classifying mental workload across different cognitive tasks have therefore only been partially successful. Here we introduce a novel algorithm to extract frontal theta oscillations from electroencephalographic (EEG) recordings of brain activity and show that it can be used to detect mental workload across different cognitive tasks. We use a published data set that investigated subject dependent task transfer, based on Filter Bank Common Spatial Patterns. After testing, our approach enables a binary classification of mental workload with performances of 92.00 and 92.35%, respectively for either low or high workload vs. an initial no workload condition, with significantly better results than those of the previous approach. It, nevertheless, does not perform beyond chance level when comparing high vs. low workload conditions. Also, when an independent component analysis was done first with the data (and before any additional preprocessing procedure), even though we achieved more stable classification results above chance level across all tasks, it did not perform better than the previous approach. These mixed results illustrate that while the proposed algorithm cannot replace previous general-purpose classification methods, it may outperform state-of-the-art algorithms in specific (workload) comparisons.

Characterization of human pluripotent stem cell differentiation by single-cell dual-omics analyses

Invivo differentiation of human pluripotent stem cells (hPSCs) has unique advantages, such as multilineage differentiation, angiogenesis, and close cell-cell interactions. To systematically investigate multilineage differentiation mechanisms of hPSCs, we constructed the invivo hPSC differentiation landscape containing 239,670 cells using teratoma models. We identified 43 cell types, inferred 18 cell differentiation trajectories, and characterized common and specific gene regulation patterns during hPSC differentiation at both transcriptional and epigenetic levels. Additionally, we developed the developmental single-cell Basic Local Alignment Search Tool (dscBLAST), an R-based cell identification tool, to simplify the identification processes of developmental cells. Using dscBLAST, we aligned cells in multiple differentiation models to normally developing cells to further understand their differentiation states. Overall, our study offers new insights into stem cell differentiation and human embryonic development; dscBLAST shows favorable cell identification performance, providing a powerful identification tool for developmental cells.

Unveiling individuals’ financial behavior patterns: The Polish-Ukrainian case study in the pre-war period

The study investigates the financial behavior of Ukrainians residing in Ukraine and Poland, aiming to identify patterns for the development of customized financial literacy programs. Additionally, it assesses Ukrainians’ preparedness, within their behavioral patterns, for global crises leading to financial shocks. During January-February 2022, a survey method was used to collect data from randomly chosen two groups of representatives of Ukrainians in Poland (N1 = 280) and Ukraine (N2 = 341). Data were proceeded with SPSS. Common patterns were revealed for both Ukraine and Poland, which are based on traditions and personal beliefs: disciplined cash flows controlling of personal budget and forming reserves for different types of crises; concentration on short-term plans and avoiding long-term ones; lack of trust to financial institutions for saving money. Among distinguished patterns are the following: In Poland, Ukrainians are more responsible and attentive to consumer loans, regularly receive and pay bills. In Poland, the investment portfolio of Ukrainians has a more diverse set of instruments. Online financial services are preferable in Poland. The study helps to identify if financially Ukrainians were ready to resist the russian war in Ukraine. Almost 30% of Ukrainians in Ukraine and 25% in Poland had only reserve for the period 1-3 months. In both countries, they claim they are ready to cover sources of covering unforeseen expenses from their reserves (more than 50% of respondents). AcknowledgmentsThe authors would like to express their gratitude to the Kirkland Scholarship Program, the Leaders of Change Foundation, the Polish American Freedom Foundation, the University of Wroclaw and personally to Marek Wróblewski, Professor at the University of Wroclaw, Associate of Ukrainian banks, and to those who helped to disseminate information about the survey, including the Foundation Ukraine, as well as to the respondents and all those who expressed interest in the results.

Role of FDG PET/CT in definitive and presumed autoimmune encephalitis.

F-18 Fluorodeoxyglucose PET/CT (FDG-PET) is emerging as a useful imaging adjunct to MRI in the initial diagnostic evaluation of autoimmune encephalitis (AIE)-though presently it is not included in the diagnostic criteria. In this prospective study we enrolled a total of 52 patients with clinically diagnosed and treated AIE. MRI evaluation was done in each case along with CSF and EEG where feasible. FDG-PET was done for all and images were interpreted visually and using SPM. The mean age group of patients included was 38.5 ± 22.6 years with 31 females and 21 males. 23 antibody-positive cases underwent PET, the most common antibody detected was anti-NMDAR type followed by anti-LGI 1. Most common metabolic pattern in NMDARE was hypermetabolism in basal ganglia and hypometabolism in parieto-occipital cortices and ovarian teratoma was detected in two of these patients on whole-body PET. A metabolic pattern consistent with AIE was demonstrated in 22/29 (75.8%) antibody-negative patients with hypermetabolism in basal ganglia and mesial temporal cortices. The overall sensitivity of FDG PET was 86% (45/52). MRI abnormalities were detected in 22/52 (42%) cases, 10/23 antibody positive and 12/29 antibody negative cases. PET was positive in 23/30 (76%) MRI negative cases. Sensitivity of FDG PET for supporting a diagnosis of AIE was higher compared to MRI in both antibody-positive (definitive) and antibody-negative (presumed) AIE. Specific metabolic patterns can be demonstrated on FDG PET in AIE, prompting an early diagnosis so that timely treatment can be instituted.

Enhancing the clinical diagnosis of the acute and subacute phases of autoimmune encephalitis and predicting the risk factors: the potential advantages of 18F-FDG PET/CT

Background2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography (18F-FDG PET) could help evaluate metabolic abnormalities by semi-quantitative measurement to identify autoimmune encephalitis (AE). Few studies have been conducted to analyze the prognostic factors of AE. The study aimed to explore the values of diagnosis and treatment evaluation by 18F-FDG PET and preliminarily discussed the potential value in predicting the prognosis of AE patients.MethodsAE patients underwent 18F-FDG PET/CT and magnetic resonance imaging (MRI). There were two steps to analyse 18F-FDG PET imaging data. The first step was visual assessment. The second step was to analyse 18F-FDG PET parameters using Scenium software (Siemens Molecular Imaging Ltd). The mean standardized uptake value (SUVmean) and maximum standardized uptake value (SUVmax) of brain relative regional metabolism (BRRM) were quantified in the case and control groups according to the anatomical automatic labeling (AAL) partition. The main statistical method was the Kruskal–Wallis test. Finally, the simple linear regression method was used to analyse the relationships between 18F-FDG PET parameters and the modified Rankin Scale (mRS) scores before and after treatment.ResultsThe results on 18F-FDG PET showed that visual assessment abnormalities were in the mesial temporal lobe (MTL) (70.8%), (mainly infringing on the hippocampus and amygdala), basal ganglia (62.5%), frontal lobes (37.5%), occipital lobes (29.2%), and parietal lobes (12.5%). The positive rate of abnormalities on 18F-FDG PET was more sensitive than that on MRI (95.5% vs 32.2%, p = 0.001). The number of lesions on PET was positively correlated with the mRS scores before and after treatment, and the correlation before treatment was more significant. Before treatment, the SUVmean of the left occipital lobe was the most remarkable (SUVmean, R2 = 0.082, p > 0.05) factor associated with the mRS score, and the correlation was negative. With regard to prognosis, the SUVmax of the MTL was the most notable (R2 = 0.1471, p > 0.05) factor associated with the mRS score after treatment, and the correlation was positive.Conclusions18F-FDG PET could be more sensitive and informative than MRI in the early phases of AE. The common pattern of AE was high MTL metabolism on 18F-FDG PET, which was associated with hypometabolism of the occipital lobe, and the number of lesions on PET before treatment may be significant factors in assessing disease severity. The SUVmax of MTL hypermetabolism may serve as a prognostic biomarker in AE.

Assessing the financial stability of Warsaw-listed transport and logistics firms

Purpose. The primary objective of this paper is to evaluate the financial security of transport and logistics companies listed on the Warsaw Stock Exchange. Methodology. The research employs various financial security indicators such as liquidity, capital coverage of assets, working capital, and others. The study focuses on 11 companies in the transport and logistics sector listed on the Warsaw Stock Exchange in the third quarter of 2023. Results. The findings reveal that companies in the transport and logistics sector are highly diverse and challenging to compare on non-financial security aspects. Average data do not reflect the real situation in the sector, and individual companies significantly influence average results. The importance of maintaining an optimal structure of assets and capital for ensuring financial security is also highlighted. Theoretical contribution. This paper contributes to financial security in the transport and logistics sector by analysing companies listed on the Warsaw Stock Exchange. It offers a new perspective on the financial stability of these companies and the factors influencing it. Practical implications. The research calls for caution when assessing the financial security of enterprises in the transport and logistics sector. It also suggests expanding the research group and checking whether the entire sector has any common patterns regarding financial security. This could provide valuable insights for companies in the sector and policymakers.

Exploring the burden of mixed dyslipidemia in patients with type 2 diabetes mellitus: A cross-sectional study in Kashmir, India.

Diabetes-related dyslipidemia is a multifaceted, complicated disorder characterized by an abnormal lipid profile in individuals with diabetes. The incidence of different types of dyslipidemia, however, was not a focus of prior investigations. The patients were characterized into three categories of dyslipidemia. Different patterns of dyslipidemia were combined into single dyslipidemia (7 patterns), mixed dyslipidemia (16 patterns), and triple dyslipidemia (4 patterns). In this cross-sectional study, 586 people suffering from type 2 diabetes mellitus (T2DM) were included. We assessed the serum lipid profile and used log (TG/HDL-C) to determine the atherogenic index of plasma (AIP). Dyslipidemia was examined as a categorical variable, and the findings were presented as percentages and numbers. To compare categorical variables, we either utilized Fisher exact tests or Chi square tests. The study comprised of 586 T2DM patients, with 310 (52.9%) women and 276 (47.1%) men. Women have significantly higher hypertension (33.6%) as compared to men (23.2%). 18.94% (111) of patients were having coronary artery disease (CAD) history consisting of 12.28% (72) females and 6.66% (39) males, a difference which is statistically significant. 98.12% of total individuals had as a minimum of one lipid abnormality. 4.61% (27) of study subjects were having isolated dyslipidemia and 93.51% (548) had dual or triple pattern of dyslipidemia (mixed dyslipidemia). High AIP >0.24 (94.8%) was the most predominant trend of dyslipidemia. The dual combination of AIP (>0.24) and HDL (<50 mg/dL in Females and <40 mg/dL in Males) was found to be the most common pattern of mixed dyslipidemia (68.08%). The most prevalent trend of isolated dyslipidemia was found to be high AIP (>0.24), In patients with CAD history. Among the mixed dyslipidemia, the common pattern of dyslipidemia (71.17%) was the dual combination of high AIP (>0.24) and low HDL (<50 mg/dL women and <40 mg/dL males). The triple combination of TG (≥200 mg/dL) and HDL (<40 and <50 mg/dL) and LDL (≥100 mg/dL) was only found in females. In conclusion, dyslipidemia is highly prevalent in T2DM patients, with mixed dyslipidemia being the most common type observed in the community of Kashmir valley, India. High AIP was the most prevalent pattern in the current investigation.

Early Graft Tear As a Major Risk Factor for the Clinical Failure of Lateral Meniscal Allograft Transplantation

Background: Graft tears are often observed on magnetic resonance imaging after lateral meniscal allograft transplantation (MAT). Their characteristics, such as the location and configuration, are likely to be different depending on the timing of the injury. However, the clinical relevance of early and late graft tears has not been investigated. Hypothesis: (1) Both early and late graft tears would be associated with the clinical failure of lateral MAT, and (2) an early graft tear (ET) would lead to worse outcomes than a late graft tear (LT) or an intact graft. Study Design: Cohort study; Level of evidence, 3. Methods: A total of 261 patients who had undergone lateral MAT between March 2000 and June 2019 were retrospectively reviewed. The graft tear was investigated using magnetic resonance imaging, which was performed routinely during the first postoperative year and every 2 years thereafter. The patients were classified according to the timing of the graft tear: no graft tear (NT) group, ET (≤1 year after surgery) group, and LT (>1 year after surgery) group. Clinical failure was defined as (1) reoperations including arthroplasty, realignment osteotomy, revision MAT, and meniscectomy (>50% of the graft or to the zone of the meniscocapsular junction) or (2) a Lysholm score of <65. Risk factors for a low survival rate were investigated using Cox regression analysis. A comparison of the Lysholm scores for each group was also performed. Results: There were 24 (9.2%) patients who had clinical failure at a mean follow-up of 7.5 ± 4.3 years. The overall survival rate at 5 years was 92.8% (95% CI, 91.1%-94.5%). A graft tear was noted in 80 patients: 23 patients in the ET group and 57 patients in the LT group. The most common tear pattern was a meniscocapsular tear in the ET group and a complex tear in the LT group. The hazard ratios for clinical failure in the ET and LT groups were 30.7 (95% CI, 9.4-76.4; P < .001) and 4.0 (95% CI, 1.3-12.9; P = .013), respectively. The Lysholm score of the ET group (82.7 ± 14.8) was significantly lower than that of the other 2 groups (NT: 87.6 ± 11.7; LT: 90.7 ± 9.0; P = .024). Conclusion: An ET was a major risk factor for the clinical failure of lateral MAT. An LT was associated with a lower survival rate. An ET was also associated with worse clinical outcomes.

Ancient allopatry and ecological divergence act together to promote plant diversity in mountainous regions: evidence from comparative phylogeography of two genera in the Sino-Himalayan region

BackgroundHow geographical isolation and ecological divergence act together to promote plant diversity in mountainous regions remains largely unknown. In this study, we chose two genera comprising a small number of species distributed in the Sino-Himalayan region, Megacodon (Gentianaceae) and Beesia (Ranunculaceae), which both exhibit a fragmented distribution pattern and are found across a wide range of elevations. By summarizing their common patterns of speciation and/or divergence processes, we aim to understand how environmental changes accelerated lineage diversification in the Sino-Himalayan region through ancient allopatry and ecological divergence.ResultsUsing ddRAD-seq, chloroplast genome sequences, and specific molecular markers, we studied the phylogenetic relationships, population structure, and historical biogeography of Beesia and Megacodon. Both genera began to diverge from the late Miocene onwards, with ancient allopatry at lower elevations formed narrow-range species or relict populations. Mantel tests between genetic distance and climatic, elevational, or geographic distance revealed an isolation-by-distance pattern in Beesia and Megacodon stylophorus. Megacodon showed two clades occupying entirely different altitudinal ranges, whereas Beesia calthifolia exhibited a genetic divergence pattern along an elevation gradient. Furthermore, we conducted morphological measurements on Beesia calthifolia and found that different elevational groups had distinct leaf shapes.ConclusionsThe regional disjunctions of plant groups in the Sino-Himalayan region are drastic and closely related to several biogeographic boundaries. As a consequence of major geological and climate change, ecological divergence when different elevations are colonized often happens simultaneously within plant groups. Although habitat fragmentation and parapatric ecological divergence each spur speciation to different extents, a combined effect of these two factors is a common phenomenon in the Sino-Himalayan region.

Viral interactions with host factors (TIM-1, TAM -receptors, Glut-1) are related to the disruption of glucose and ascorbate transport and homeostasis, causing the haemorrhagic manifestations of viral haemorrhagic fevers.

The haemorrhagic features of viral haemorrhagic fevers may be caused by common patterns of metabolic disturbances of the glucose and ascorbate homeostasis. Haemorrhages and vasculature disfunctions are a clinical feature not only of viral haemorrhagic fevers, but also in scurvy, diabetes and thrombotic microangiopathic haemolytic anaemia. Interestingly, the expression of glucose and ascorbate transporter Glut-1 on the erythrocyte membrane is associated with the inability to synthesize ascorbate and is restricted to that very species that are susceptible to filoviruses (primates, humans and fruit bats). Glut-1 may play a pivotal role in haemorrhagic fever pathogenesis. TIM-1 and TAM receptors have been recognized to enhance entry of Ebola, Lassa and Dengue viruses and viral interferences with TIM-1 could disturb its function, disturbing the expression of Glut-1.In those species not able to synthesize ascorbate and expressing Glut-1 on erythrocytes virus could interact with Glut-1 or other functionally related protein, and the influx of glucose into the cells would be severely impaired. As a consequence, transient hyperglycemia and a marked oxidative stress coupled with the high levels of glucose in plasma would be established, and then promote the activation of NF–κB transcription, exacerbating a pro-inflammatory response mediated by cytokines and chemokines: The inability to synthesize ascorbate is an Achilles Heel when trying to counteract the oxidative stress.