Concurrent Patterns Research Articles

Abstract TP348: Overload of efferocytic cargoes in lysosome shifts microglia/macrophages towards pro-inflammatory phenotype through activating STING after stroke.

Objective: Incomplete clearance of cell debris in stroke lesion contributes to post-stroke cognitive impairment. Microglia and infiltrated macrophages are the major scavenger of debris in stroke lesion. However, as stroke progresses, their phagocytic capacity is impaired, while secretion of pro-inflammatory factors was enhanced. This study aims to identify the mechanisms driving the phenotypic shift after excessive phagocytosis. Methods: Brain cells from 8-12 week-old male C57BL/6J mice were collected for single-cell RNA sequencing at 1, 5, and 14 days after transient middle cerebral artery occlusion (tMCAO), as well as from sham-operated control group. Key transcription factors mediating the phenotypic changes of microglia and macrophages were identified through bioinformatics analysis, and further validated in vivo and in vitro using immunofluorescence staining, flow cytometry, and Western blot. Additionally, tMCAO models were treated with the key factor inhibitor to evaluate microglia and macrophage phenotypic shifts and the progression of stroke. Results: Through single-cell RNA sequencing analysis, we identified a concurrent activation pattern between the stimulator of interferon genes (STING) mediated Type I interferon signaling and the pro-inflammatory phenotype of microglia/macrophages. In the first 5 days after stroke, microglia and macrophages displayed an inflammatory-resolving phenotype with enhanced phagocytic activity, but from days 5 to 14, they transitioned to a pro-inflammatory phenotype with sustained upregulation of STING-mediated Type I interferon pathway molecules. We validated the phenomenon observed in bioinformatics using tMCAO models. In vitro and in vivo, we found that continuous phagocytosis by macrophages and microglia led to STING activation, triggering Type I interferon signaling and driving the phenotypic shift towards a pro-inflammatory state. Treatment with STING inhibitor H-151 reversed these detrimental shifts.. Conclusions: These findings suggest that continuous post-stroke phagocytosis by macrophages and microglia led to the activation of STING, thereby triggering type I interferon signaling and driving the phenotypic shift towards a pro-inflammatory state. STING inhibition may serve as a therapeutic strategy for mitigating neuroinflammatory responses following stroke.

P1278 The use of pain and sedative medications among individuals with a diagnosis of Inflammatory Bowel Disease

Abstract Background Individuals with inflammatory bowel disease (IBD) frequently experience pain, poor sleep and anxiety even when disease activity is well controlled. A nationwide UK study showed that 42% individuals with IBD want help with pain and 56% want help with fatigue.(1) Unfortunately, pharmacological management of these symptoms is often inadequate and frequently associated with significant side effects, particularly when pain medications and sedatives are prescribed chronically or concurrently. Despite the risks, there is a lack of evidence regarding the trend in use of these medications in European IBD populations. Methods An extract of over 80,000 individuals with IBD was obtained from the general practice database "Clinical Practice Research Datalink" (CPRD) including details of prescriptions, diagnoses and demographics. Data from 1st January 2010 to 31st December 2019 was analysed to assess prescribing trends for opioids, gabapentinoids, benzodiazepines, and Z-drugs. We examined overall, chronic, and concurrent prescribing patterns. Chronic prescribing was defined as continuous use of opioids for more than 3 months, or Z-drugs and benzodiazepines for more than 4 weeks, in accordance with national guidelines.(2–4) Concurrent prescribing, assessed in 2-year intervals, was defined as overlapping prescriptions of opioids, gabapentinoids, Z-drugs, or benzodiazepines. Data were analysed using Stata 18 and R. Results Over the study period, the annual prevalence of gabapentinoids, and Z-drug use increased (2.5% to 5.5% and 3.3% to 3.4% respectively) while strong opioid (9.2%-8.5%), weak opioid (12.1%-9.9%) and benzodiazepine use (6.1%-5.6%) decreased (see Figure 1). The annual prevalence of chronically prescribed medications in 2019 were 2.5% strong opioids, 3.4% weak opioids, 2.4% benzodiazepines and 1.8% Z-drugs. Over 1 in 5 gabapentinoid prescriptions were concurrent with another pain or sedative medication; 17% with strong opioids, 6% benzodiazepines and 4% Z-drugs, while 18% of strong opioids, 18% Z-drugs and 18% benzodiazepines were concurrently prescribed with another pain medication or sedative (see Table 1). Conclusion Overall, prescribing rates of pain medications and sedatives in individuals with IBD remain concerning. While opioid use has dropped and sedative use is stable, gabapentinoid use has increased, and all are often co-prescribed. Chronic prescribing of these medications provides no clear benefit and poses significant risks. Future efforts should prioritise reducing chronic and concurrent prescribing of pain and sedative medications

A Novel Methodology for Performance Evaluation in Advanced Quality Control

Current global conditions and challenges in industrial manufacturing, marked by dynamism, competition, and the need for responsible resource management, have increased the demand for sustainable manufacturing practices. The integration of Industry 4.0 and the recent development of Industry 5.0 have added dynamism, which has generated profound implications for quality control and process monitoring, focusing mainly on recognising control patterns within the manufacturing environment. This study introduces a novel methodology for evaluating the performance of pattern classification models used in advanced quality control. Our approach incorporates robust performance metrics, early detection, window size, network hyperparameters, and concurrent patterns within a simulated monitoring environment. Unlike previous research, our evaluation methodology addresses the sensitivity of classification models to various factors, emphasising the critical balance between early detection and minimising false alarms. The findings reveal that window size significantly impacts the model’s sensitivity to pattern changes, highlighting that measuring early detection alone is impractical in real-world applications. Furthermore, optimal hyperparameter selection enhances the model’s practical applicability.

Computing ecosystem risk hotspots: A mediterranean case study

In ecosystem management, risk assessment quantifies the probability and impact of events and informs on intervention priorities. Analytical models for risk assessment quantify the impact of natural and anthropogenic stressors on ecosystems. Traditional approaches evaluate single stressors, whereas complex models assess cumulative impacts of frequently interacting stressors and offer better accuracy at the expense of low cross-area re-applicability and long implementation times.We introduce a versatile, re-usable, and semi-automated workflow designed for big data-driven ecosystem risk assessment, utilizing spatiotemporal data from open repositories. It allows for a flexible definition of the stressors on which the risk under analysis depends. By applying cluster analysis, the workflow identifies different patterns of stressor concurrency, while statistical analysis highlights clusters of stressors likely linked to elevated risk. Ultimately, it generates geospatial risk maps and identifies spatial risk hotspots. The workflow methodology is independent of the geographical area of the application.As a case study, we present risk assessments for the Mediterranean Sea, a region with intense anthropogenic pressures and significant climatic vulnerabilities. We used over 1.1 million open data from 2017 to 2021 and projections to 2050 under the RCP8.5 scenario (a high greenhouse gas emission scenario) at a 0.5°spatial resolution. Data included environmental, oceanographic, biodiversity variables, and manifest and hidden fishing effort distributions. Our workflow identified different types of high-risk hotspots, highlighting different concurrencies of habitat loss, overfishing, hidden fishing, and climate change stressors. High-risk hotspots concentrated in the Western Mediterranean, the Tyrrhenian Sea, the Adriatic Sea, the Strait of Sicily, the Aegean Sea, and eastern Turkey. Our results agreed with an alternative Fuzzy C-means-based method (with a 90% to 96% overlap over the years) and a Bayesian regression model (∼80% overlap).Our Mediterranean risk maps can facilitate the development of management and monitoring strategies, supporting the sustainable development and resilience of coastal zones, and can act as prior knowledge for ecosystem models and spatial plans.

Emotion coupling across socialization contexts in adolescence: Differences in parent-child and peer interactions.

People spontaneously adjust their emotions to others when they interact. This temporal coupling of emotions is an adaptive process facilitating social bonding. The present study examined differences in coupling patterns during parent-child versus peer interactions in adolescence, a developmental period marked by evolving parent-child dynamics and bond formation with peers. Because adolescents prioritize peer bonding while gradually asserting their autonomy from parental influence, we hypothesized that peer dyads showed stronger coupling than parent-adolescent dyads. Adolescents (age 16) with diverse ethnic backgrounds (N = 615; 50.2% female; 46.8% European American, 31.2% African American, 5.0% Hispanic, 3.0% Asian or Pacific Islander, 2.0% Native American, and 12.0% multiple ethnic backgrounds) participated in two videotaped interaction tasks: one with a parent and one with a self-nominated peer. Parent and peer interactions included discussions on positive and negative topics. Both dyad members' emotions were coded in real time. Cross-recurrence quantification analyses and growth-curve modeling revealed concurrent emotion coupling patterns, with peer dyads showing stronger coupling than parent-adolescent dyads. Moreover, peer dyads showed the most pronounced coupling patterns when they discussed personal problems, while parent-adolescent dyads showed the most pronounced coupling patterns when they discussed the planning of a fun activity. Our findings emphasize the importance of microlevel emotion dynamics in understanding larger scale developmental shifts in relationships during adolescence. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

On-line recognition of mixture control chart patterns using hybrid CNN and LSTM for auto-correlated processes

Statistical process control (SPC), designed to detect and identify process disturbances, is an effective quality control method for ensuring process stability. Owing to the growing automation of the industry, the manufacturing process can be autocorrelated. Engineer process control (EPC) is typically used to address autocorrelation. However, process disturbances can be offset by feedback compensation, making control chart patterns (CCPs) difficult to identify. Most studies on control chart pattern recognition (CCPR) techniques are based on a single abnormal control chart pattern (CCP). However, a mixture of CCPs can occur during real-world manufacturing processes. With the development of intelligent manufacturing systems, early detection of abnormal concurrent CCPs has become an important issue. In this study, a hybrid model combining a convolutional neural network (CNN) and long short-term memory (LSTM) in an online detection system was used to recognize the concurrent CCPR problem in SPC-EPC processes. The results showed that the average accuracy of the deep learning CNN-LSTM method was 99.83%, which was significantly better than that of the machine learning method. In addition, the running time of the CNN-LSTM model was shortened. In a comparison of online monitoring between the deep learning method and the machine learning method, the CNN-LSTM model for an online monitoring system identified abnormal concurrent patterns faster. Therefore, the proposed CNN-LSTM online monitoring scheme can be applied confidently and successfully to identify mixture CCPs in an SPC-EPC process.

Thyroid Lesion with a Novel Concurrent ETV6-NTRK3 Translocation and DICER1 Mutation

Abstract Introduction/Objective Understanding of the behavior of thyroid tumors expand as the basis of their classification gradually move from morphologic to molecular/genetic. The use of molecular methods in detecting mutations in fine needle aspiration (FNA) specimens further helped in tailoring patient management. Here, we describe a case of a thyroid lesion which was diagnosed with atypia of undetermined significance (AUS) on FNA and discovered to have an unreported concurrent mutation pattern. Methods/Case Report The patient is a 26 year-old female with long standing history of prominent anterior neck mass. New onset of neck pain prompted sonographic analysis which revealed a 1.1 cm hypoechoic left thyroid nodule with microcalcification. FNA was done, and was signed out as AUS which initiated molecular genetic testing. The lesion was found to have both ETV6/NTRK3 translocation and DICER1 p.P375R mutation. Existing literature on NTRK3 rearrangements in thyroid tumors confer a >95% risk of malignancy. It is commonly associated with BRAF-negative papillary thyroid carcinomas (PTC) with both in BRAF-like behavior in terms of nodal metastases and extrathyroidal extension. On the other hand, there are no existing literature specifying the malignancy risk of the exact DICER1 mutation identified since it has been linked to follicular neoplasms in general. Furthermore, isolated DICER1 mutations in the thyroid showed RAS-like behavior. Subsequent resection of the thyroid revealed that the tumor is morphologically a PTC, with lymphovascular invasion. Results (if a Case Study enter NA) NA Conclusion Molecular testing in thyroid lesions with morphologically indeterminable features on FNA significantly aided in prognostication of patients and prediction of malignancy risk. In this case with a previously unreported combination of mutations, existing literature helped in describing the probable behavior of the patient’s tumor. Thus, the researchers emphasize the importance of databases of identified mutations in tumors and their associated characteristics such as The Cancer Genomic Atlas (TCGA) and The Catalogue of Somatic Mutations in Cancer (COSMIC).

B-082 Clinical Investigation of Rods and Rings Pattern in Anti-Nuclear Antibody Test in Korean Patients

Abstract Background In the mid-2000s, a novel pattern in antinuclear antibody (ANA) testing was reported. Indirect immunofluorescence assays on HEp-2 cells, conducted with sera from patients with Hepatitis C virus (HCV) infection, revealed cytoplasmic structures in the form of rods and rings (RR). These structures typically displayed rod lengths of 3-10μm and ring diameters of 2-5μm. Inosine monophosphate dehydrogenase (IMPDH) was identified as the primary component of the RR structures. Research on the administration of interferon/ribavirin (IFN/RBV) showed that ribavirin, an IMPDH inhibitor, induced RR formation in over 95% of cells. Additionally, RR patterns were reported in patients receiving other IMPDH inhibitors such as mycophenolic acid and azathioprine. While cytidine triphosphate synthase 1 (CTPS1) was suggested to be associated with RR structures, there were no reported cases in patients. Interestingly, patients receiving methotrexate, which does not directly inhibit IMPDH but hinders GTP biosynthesis, also exhibited RR structures. To explore the clinical implications of specimens showing RR patterns, a study was conducted to investigate the actual clinical scenarios associated with these findings. Methods This is a retrospective study conducted at a single center, covering the period from January 2022 to December 2023, focusing on the results of ANA testing. The ANA tests were performed using HEp-2 cells (FLUORO HEPANA TEST, MBL, Nagoya, Japan) on slides manufactured with AP 16 IF Plus (das, Palombara Sabina, RM, Italy). ANA results were obtained through qualitative testing, ranging from 1+ to 4+, or quantitative testing based on dilutions ranging from 1:40 to 1:640, depending on clinical requirements. Results Out of the 7,648 ANA test results, the RR pattern was observed in 40 cases (0.5%). Among these, 2.5% had a history of HCV infection with IFN/RBV treatment, and an additional 2.5% had concurrent use of IMPDH inhibitors. There were no reported cases of medication history related to the synthetic pathway of nucleic acids, including CTPS1. Cases where RR patterns coexisted with autoimmune diseases accounted for 35%, infections for 25%, and other inflammatory conditions for 22.5%. RR patterns reported with an intensity of 3+ or at dilutions of 1:160 or higher constituted 27.5%. Among cases displaying strong fluorescence, 45% were associated with infections, 18% with autoimmune conditions, and another 18% with unexplained inflammatory causes. In the overall sample, elevated CRP or ESR was noted in 54.5% of cases with infections, autoimmune diseases, or other inflammatory conditions. Among samples with intense intensity, 55.5% showed elevated CRP or ESR when inflammatory conditions were present. Conclusions The majority of cases exhibiting the RR pattern showed no history of exposure to IMPDH inhibitors or drugs affecting the nucleic acid synthetic pathway. A high proportion of cases clinically diagnosed with inflammation showed a concurrent RR pattern, with only approximately half of them demonstrating elevated CRP or ESR levels. This study suggests the possibility of identifying inflammatory responses not captured by conventional acute inflammation markers through the RR pattern observed in ANA testing.

Concurrent control chart pattern recognition in manufacturing processes based on zero-shot learning

In real industrial settings, collecting and labeling concurrent abnormal control chart pattern (CCP) samples are challenging, thereby hindering the effectiveness of current CCP recognition (CCPR) methods. This paper introduces zero-shot learning into quality control, proposing an intelligent model for recognizing zero-shot concurrent CCPs (C-CCPs). A multiscale ordinal pattern (OP) feature considering data sequential relationship is proposed. Drawing from expert knowledge, an attribute description space (ADS) is established to infer from single CCPs to C-CCPs. An ADS is embedded between features and labels, and the attribute classifier associates the features and attributes of CCPs. Experimental results demonstrate an accuracy of 98.73 % for 11 unseen C-CCPs and an overall accuracy of 98.89 % for all 19 CCPs, without C-CCP samples in training. Compared with other features, the multiscale OP feature has the best recognition effect on unseen C-CCPs.

Perinatal arterial ischemic stroke diagnosed in infants receiving therapeutic hypothermia for hypoxic-ischemic encephalopathy.

Both perinatal arterial ischemic stroke (PAIS) and hypoxic-ischemic encephalopathy (HIE) can present with neonatal encephalopathy. We hypothesized that among infants undergoing therapeutic hypothermia, presence of PAIS is associated with a higher risk of seizures and a lower risk of persistent encephalopathy after rewarming. We studied 473 infants with moderate or severe HIE enrolled in the HEAL Trial who received a brain MRI. We defined PAIS as focal ischemic infarct(s) within an arterial distribution, and HIE pattern of brain injury as central gray, peripheral watershed, or global injury. We compared the risk of seizures (clinically suspected or electrographic), and of an abnormal 5-day Sarnat exam, in infants with and without PAIS. PAIS was diagnosed in 21(4%) infants, most of whom (16/21, 76%) also had concurrent HIE pattern of brain injury. Infants with PAIS were more likely to have seizures (RR 2.4, CI 2.8-3.3) and persistent moderate or severe encephalopathy on 5-day Sarnat exam (RR 2.5, 95% CI 1.9-3.4). Among infants undergoing therapeutic hypothermia, PAIS typically occurs with concurrent HIE pattern brain injury. The higher rate of encephalopathy after rewarming in infants with PAIS may be due to the frequent co-existence of PAIS and HIE patterns of injury.

Blood methylation pattern reflects epigenetic remodelling in adipose tissue after bariatric surgery

Studies on DNA methylation following bariatric surgery have primarily focused on blood cells, while it is unclear to which extend it may reflect DNA methylation profiles in specific metabolically relevant organs such as adipose tissue. Here, we investigated whether adipose tissue depots specific methylation changes after bariatric surgery are mirrored in blood. Using Illumina 850K EPIC technology, we analysed genome-wide DNA methylation in paired blood, subcutaneous and omental visceral AT (SAT/OVAT) samples from nine individuals (N=6 female) with severe obesity pre- and post-surgery. The numbers and effect sizes of differentially methylated regions (DMRs) post-bariatric surgery were more pronounced in AT (SAT: 12,865 DMRs from-11.5 to 10.8%; OVAT: 14,632 DMRs from-13.7 to 12.8%) than in blood (9267 DMRs from-8.8 to 7.7%). Cross-tissue DMRs implicated immune-related genes. Among them, 49regions could be validated with similar methylation changes in blood from independent individuals. Fourteen DMRs correlated with differentially expressed genes in AT post bariatric surgery, including downregulation of PIK3AP1 in both SAT and OVAT. DNA methylation age acceleration was significantly higher in AT compared to blood, but remained unaffected after surgery. Concurrent methylation pattern changes in blood and AT, particularly in immune-related genes, suggest blood DNA methylation mirrors AT's inflammatory state post-bariatric surgery. The funding sources are listed in the Acknowledgments section.

Learning multi-graph structure for Temporal Knowledge Graph reasoning

Temporal Knowledge Graph (TKG) reasoning aiming at forecasting future events based on historical snapshots distributed over timestamps. Referred to as extrapolation in numerous studies, this aspect of research in KG has garnered significant attention in recent years. Owing to its extreme versatility and variation in spatial and temporal correlations, TKG reasoning presents a challenging task, demanding efficient capture of concurrent structures and evolutional interactions among facts. While existing methods have made strides in this direction, they still fall short of harnessing the diverse forms of intrinsic expressive semantics of TKGs, which encompass entity correlations across multiple timestamps and periodicity of temporal information. This limitation constrains their ability to thoroughly reflect historical dependencies and future trends. In response to these drawbacks, this paper proposes an innovative reasoning approach that focuses on Learning Multi-graph Structure (LMS). Concretely, it comprises three distinct modules concentrating on multiple aspects of graph structure knowledge within TKGs, including concurrent and evolutional patterns along timestamps, query-specific correlations across timestamps, and semantic dependencies of timestamps, which capture TKG features from various perspectives. Besides, LMS incorporates an adaptive gate for merging entity representations both along and across timestamps effectively. Moreover, it integrates timestamp semantics into graph attention calculations and time-aware decoders, in order to impose temporal constraints on events and narrow down prediction scopes with historical statistics. Extensive experimental results on five event-based benchmark datasets demonstrate that LMS outperforms state-of-the-art extrapolation models, indicating the superiority of modeling a multi-graph perspective for TKG reasoning.

A Longitudinal Study of the Use and Effects of Fall-Risk-Increasing Drugs in Residential Aged Care

ObjectivesFall-risk-increasing drugs (FRIDs)—psychotropics and cardiovascular disease (CVD) drugs—may elevate the risk of falling, with strong evidence observed in psychotropic FRIDs, whereas findings from cardiovascular disease (CVD) FRIDs remain inconclusive. Existing studies on FRIDs and falls are often hampered by methodologic limitations. Leveraging longitudinal observational data, we aimed to determine the long-term patterns of FRID use and their association with falls in residential aged care (RAC) homes. DesignA retrospective longitudinal cohort study. Setting and ParticipantsA total of 4207 permanent residents newly admitted to 27 RAC homes in Sydney, Australia. MethodThe outcomes were incidence of all and injurious falls. We measured exposure to each FRID over 60 months using the Proportion of Days Covered (PDC) metric. We used group-based multitrajectory modeling to determine concurrent usage patterns of psychotropics and CVD FRIDs and applied negative binomial regression to assess their associations with the outcomes. ResultsA total of 83.6% (n = 3516) and 77.3% (n = 3254) residents used psychotropic and CVD FRIDs, respectively. The PDC values ranged from 67.3% (opioids) to 86.9% (antidepressants) for specific psychotropics and 79.0% (α-adrenoceptor antagonists) to 89.6% (β blockers) for CVD FRIDs. We identified 4 groups: group 1, low psychotropics–low CVDs use (16.7%, n = 701); group 2, low psychotropics–high CVDs (25.0%, n = 1054); group 3, high psychotropics–high CVDs (41.0%, n = 1723); and group 4, high psychotropics–low CVDs (17.3%, n = 729). Group 4 had a significantly higher rate of falls than the other groups for both outcomes, including relative to group 3, in which exposure to both FRID classes was high. Conclusions and ImplicationsOur findings reveal concerningly high FRID use in RAC homes and highlight a critical difference in the impact of the 2 major FRID classes on falls. Psychotropics were strongly associated with falls, whereas the studied CVD FRIDs did not elevate risk of falling.

Senolytic effects of exercise in human muscles require acute inflammation.

Higher intensity exercise, despite causing more tissue damage, improved aging conditions. We previously observed decreased p16INK4a mRNA in human skeletal muscle after high-intensity interval exercise (HIIE), with no change following equivalent work in moderate-intensity continuous exercise. This raises the question of whether the observed senolytic effect of exercise is mediated by inflammation, an immune response induced by muscle damage. In this study, inflammation was blocked using a multiple dose of ibuprofen (total dose: 1200 mg), a commonly consumed nonsteroidal anti-inflammatory drug (NSAID), in a placebo-controlled, counterbalanced crossover trial. Twelve men aged 20-26 consumed ibuprofen or placebo before and after HIIE at 120% maximum aerobic power. Multiple muscle biopsies were taken for tissue analysis before and after HIIE. p16INK4a+ cells were located surrounding myofibers in muscle tissues. The maximum decrease in p16INK4a mRNA levels within muscle tissues occurred at 3 h post-exercise (-82%, p < 0.01), gradually recovering over the next 3-24 h. A concurrent reduction pattern in CD11b mRNA (-87%, p < 0.01) was also found within the same time frame. Ibuprofen treatment attenuated the post-exercise reduction in both p16INK4a mRNA and CD11b mRNA. The strong correlation (r = 0.88, p < 0.01) between p16INK4a mRNA and CD11b mRNA in muscle tissues suggests a connection between the markers of tissue aging and pro-inflammatory myeloid differentiation. In conclusion, our results suggest that the senolytic effect of high-intensity exercise on human skeletal muscle is mediated by acute inflammation.

Stochastic reconstruction of geological reservoir models based on a concurrent multi-stage U-Net generative adversarial network

For complex geological reservoir modeling, some numerical-simulation-based methods, such as traditional multiple-point statistics (MPS), cannot extract nonstationary patterns of training images (TIs) effectively. CPU-intensive calculations require that variables information only be stored in RAM instead of other storage mediums to avoid huge time consumption if many simulations are performed successively. Generative Adversarial Network (GAN) modeling methods are able to overcome these issues, but when the training datasets are limited, mode collapse easily occurs. Meanwhile, fixed receptive fields might cause the problem that the corresponding reconstruction cannot take local features and global features of the TIs into account simultaneously. Therefore, we propose the Concurrent Multi-Stage U-Net GAN (Con-MSUGAN) based on a single TI. The pyramid structure is used for spatial pattern multi-scale representation in Con-MSUGAN, which can capture the corresponding feature information of TIs under different scales. Meanwhile, concurrent training patterns can make network parameters in adjacent stages correlated with each other to accelerate network convergence speed, thereby realizing stochastic multi-scale reconstructions. Stationary channel and nonstationary delta facies TIs were used to verify the performance of Con-MSUGAN. Results show that simulation of different datasets using this method are more similar in terms of spatial variance, connectivity degree and facies type frequency distribution to the original TIs. Meanwhile, muti-dimensional-scaling (MDS) plots show small discrepancies between simulation results and the corresponding TI. It indicates that Con-MSUGAN can overcome the problem that complex spatial patterns are hard to reproduce. In addition, saved network parameters can be reused. A variety of equiprobability simulation results can be obtained rapidly, thereby realizing stochastic reconstruction of geological reservoir models.

Role of short term Video EEG monitoring and MRI in refractory Epilepsy

Introduction: Inpatient video EEG monitoring is widely used for the diagnosis, seizure classification and pre surgical evaluation of patients with epilepsy. Only few studies have highlighted the role of short term video EEG in the diagnosis of paroxysmal events. The present study was undertaken to identify the role of short term video EEG in refractory epilepsy. Materials &amp; Methods: Forty patients, attending neurology outpatient department in our institution, during the study period, fulfilling the criteria for refractory epilepsy were included. Short term video EEG and MRI Brain were done for all of them. Outcomes measured were 1) Video recording of epileptic seizures with concurrent ictal pattern or psychogenic non epileptic seizure. 2) Identification of new interictal epileptiform discharges, which were not there in the previous routine EEG. 3) Observation of congruency between EEG and MRI Brain. Results: Clinical events were recorded in 12.5% of patients - 7.5% had epileptic seizures and 5% had psychogenic non epileptic seizures recorded. Short term video EEG was abnormal in 70% of the patients, whereas previous routine EEG was abnormal in only 30% and these observations were statistically significant. Short term video EEG was useful in diagnostic classification in 70% of the cases. MRI Brain was abnormal in 35% and among them, 30% had lateralized epiletiform discharges and the congruency between them is not statistically significant. Conclusions: Short term video EEG monitoring could be an initial investigation to sort our more frequent seizure group and proceed to long term VEEG if short term VEEG is inconclusive.

Latent Class Groups of Concurrent Substance Use Among Adolescents in an Urban Community: Correlates With Mental Health, Access to Drugs and Alcohol, and Risk Perception.

Concurrent substance use among adolescents has been associated with an increase in physical and mental health problems. These outcomes tend to be exacerbated among adolescents of color in underserved urban settings. The purpose of this study was to understand alcohol and concurrent drug use patterns among adolescents in an underserved urban community to provide targeted prevention and treatment recommendations. This study examined data among adolescents in an underserved urban community (N = 1789; 56.90% female; 70.86% Hispanic/Latino/a; meanage = 15.96 ± 1.56). Using latent class analysis (LCA) and multinomial logistic regression modeling, analyses identified independent correlates of latent class membership. Five latent classes (LC) were identified including LC group 1: Predominant alcohol use and limited to no concurrent-drug use (n = 213; 11.9%); LC group 2: Concurrent drug and alcohol use including methamphetamine, marijuana and synthetic marijuana use, and alcohol use (n = 74; 4.2%); LC group 3: Concurrent drug and alcohol use, with no marijuana use (n = 204; 11.39%); LC group 4: High Concurrent drug use and alcohol use (n = 204; 11.40%); and LC group 5: Concurrent drug use without alcohol use (n = 1101; 61.52%). Significant between group differences were noted between latent class groups and sociodemographic characteristics. Multinomial logistic regression models identified the associations between sociodemographic characteristics and corollary clinical features of substance use on latent class groupings of alcohol and concurrent drug use. Understanding concurrent substance use LC groups among adolescents is essential to providing targeted interventions and treatment programs, as well as early intervention programs that may help reduce substance use during adolescence.

Multiple Pattern Synthesis in Four-Dimensional Antenna Arrays Using the Quasi-Newton Memetic Optimization Method

The evolution in wireless radio communication systems has fueled the development of array antenna designs toward the direction of inventive, economical, and outcome-driven solutions. This article explored unorthodox techniques for designing array antennas for multiple radiation pattern synthesis by eradicating the required attenuators and phase shifters. An economical alternate design model is proposed with “Time-modulated” antennas capable of scanning and steering the beam electronically. “Time” is employed as a four-dimensional antenna parameter, and hence, the “Time-modulated” antennas are referred to as four-dimensional (4D) antennas. The idea is conceptualized by controlling high-speed switches attached to the antennas in a periodic way to produce the desirable excitation and phase tapering. So, the requirement of costly phase shifters and attenuators is eliminated. This work expanded the idea of “Time-modulation” for synthesizing multiple radiating beams such as monopulse, scanned beams, and shaped beams for multifunction radar systems. An appropriate switch sequence is designed to produce a concurrent sum-difference pattern for monopulse radars. Simultaneous scanning patterns and shaped flat-top patterns are also proposed for multifunction radars. To achieve the goals, two sets of 4D linear arrays are designed and the modulation parameters switch ON time and periods are optimized with a quasi-Newton memetic GA (Genetic algorithm). All the optimal outcomes are reported and also compared with other counterpart outcomes to show the efficacies of the “Time-modulation” concept for the said applications.

Multi-region calcium imaging in freely behaving mice with ultra-compact head-mounted fluorescence microscopes.

To investigate the circuit-level neural mechanisms of behavior, simultaneous imaging of neuronal activity in multiple cortical and subcortical regions is highly desired. Miniature head-mounted microscopes offer the capability of calcium imaging in freely behaving animals. However, implanting multiple microscopes on a mouse brain remains challenging due to space constraints and the cumbersome weight of the equipment. Here, we present TINIscope, a Tightly Integrated Neuronal Imaging microscope optimized for electronic and opto-mechanical design. With its compact and lightweight design of 0.43g, TINIscope enables unprecedented simultaneous imaging of behavior-relevant activity in up to four brain regions in mice. Proof-of-concept experiments with TINIscope recorded over 1000 neurons in four hippocampal subregions and revealed concurrent activity patterns spanning across these regions. Moreover, we explored potential multi-modal experimental designs by integrating additional modules for optogenetics, electrical stimulation or local field potential recordings. Overall, TINIscope represents a timely and indispensable tool for studying the brain-wide interregional coordination that underlies unrestrained behaviors.

Timing of Spinal Surgery in Polytrauma: The Relevance of Injury Severity, Injury Level and Associated Injuries.

Retrospective database analysis. Polytraumatized patients with spinal injuries require tailor-made treatment plans. Severity of both spinal and concomitant injuries determine timing of spinal surgery. Aim of this study was to evaluate the role of spinal injury localization, severity and concurrent injury patterns on timing of surgery and subsequent outcome. The TraumaRegister DGU® was utilized and patients, aged ≥16years, with an Injury Severity Score (ISS) ≥16 and diagnosed with relevant spinal injuries (abbreviated injury scale, AIS ≥ 3) were selected. Concurrent spinal and non-spinal injuries were analysed and the relation between injury severity, concurrent injury patterns and timing of spinal surgery was determined. 12.596 patients with a mean age of 50.8years were included. 7.2% of patients had relevant multisegmental spinal injuries. Furthermore, 50% of patients with spine injuries AIS ≥3 had a more severe non-spinal injury to another body part. ICU and hospital stay were superior in patients treated within 48hrs for lumbar and thoracic spinal injuries. In cervical injuries early intervention (<48hrs) was associated with increased mortality rates (9.7 vs 6.3%). The current multicentre study demonstrates that polytrauma patients frequently sustain multiple spinal injuries, and those with an index spine injury may therefore benefit from standardized whole-spine imaging. Moreover, timing of surgical spinal surgery and outcome appear to depend on the severity of concomitant injuries and spinal injury localization. Future prospective studies are needed to identify trauma characteristics that are associated with improved outcome upon early or late spinal surgery.