Hasil untuk "Neurology. Diseases of the nervous system"

Jaimie D Steinmetz, Katrin Seeher, N. Schiess et al.

Summary Background Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. Methods We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined. Findings Globally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer. Interpretation As the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed. Funding Bill & Melinda Gates Foundation.

Minghui Lu, Jiajun Wei, Qiang Cai

BackgroundThe optimal timing for tracheostomy in patients with intracerebral hemorrhage extending into the ventricles who require mechanical ventilation remains controversial, and there is a paucity of evidence to guide clinical practice. This study aimed to elucidate the impact of early vs. late tracheostomy on clinical outcomes and complications in this population, utilizing multivariable models to identify risk factors and define the potential beneficiary population.MethodsThis single-center retrospective cohort study consecutively enrolled 157 patients with severe spontaneous intracerebral hemorrhage extending into the ventricles requiring mechanical ventilation (GCS score ≤8) between January 2020 and December 2023. Based on the timing of tracheostomy, patients were classified into an early group (ET, ≤7 days after mechanical ventilation, n = 81) and a late group (LT, >7 days after mechanical ventilation, n = 76). Baseline characteristics, treatment measures, and outcome data were collected. Hematoma volumes in both the brain parenchyma and ventricles on admission CT scans were precisely quantified using 3D Slicer software. The primary outcome was the 6-month modified Rankin Scale (mRS) score. Secondary outcomes included the duration of mechanical ventilation, ICU length of stay (LOS), and the incidence of short-term complications [ventilator-associated pneumonia (VAP), new-onset arrhythmia, shock, and acute kidney injury (AKI)]. Multivariable logistic regression analysis was employed to identify independent risk factors for complications and to assess the protective effect of early tracheostomy.ResultsIn this cohort of 157 mechanically ventilated patients with severe intraventricular hemorrhage, baseline characteristics were well-balanced between Early (ET, n = 81) and Late Tracheostomy (LT, n = 76) groups. While 6-month functional outcomes (mRS) showed no significant difference (P = 0.360), the ET group demonstrated substantially shorter duration of mechanical ventilation (13 vs. 19 days, P < 0.001) and ICU stay (17 vs. 25 days, P < 0.001). ET was associated with significantly lower incidence of ventilator-associated pneumonia (28.40 vs. 48.68%, P = 0.009), new-onset arrhythmia (18.52 vs. 32.89%, P = 0.039), and shock requiring vasopressors (24.7 vs. 40.79%, P = 0.031). Multivariable analysis identified GCS score <6 (OR 3.588, P = 0.008) and Graeb score ≥8 (OR 8.735, P = 0.037) as independent risk factors for complications, while confirming early tracheostomy as an independent protective factor (aOR 0.306, P = 0.019) after adjustment for confounders.ConclusionIn this single-center retrospective cohort study, early tracheostomy was associated with shorter durations of mechanical ventilation and ICU stay, as well as a lower incidence of major complications, and demonstrates a favorable safety profile. Although it does not improve long-term neurological function, early tracheostomy serves as an independent protective factor. When combined with the identification of risk factors such as GCS <6 and Graeb score ≥8, it provides a basis for individualized treatment. These findings suggest an association that warrants further investigation in prospective studies.

S. Sisodiya, Medine I. Gulcebi, Francesco Fortunato et al.

Anthropogenic climate change is affecting people's health, including those with neurological and psychiatric diseases. Currently, making inferences about the effect of climate change on neurological and psychiatric diseases is challenging because of an overall sparsity of data, differing study methods, paucity of detail regarding disease subtypes, little consideration of the effect of individual and population genetics, and widely differing geographical locations with the potential for regional influences. However, evidence suggests that the incidence, prevalence, and severity of many nervous system conditions (eg, stroke, neurological infections, and some mental health disorders) can be affected by climate change. The data show broad and complex adverse effects, especially of temperature extremes to which people are unaccustomed and wide diurnal temperature fluctuations. Protective measures might be possible through local forecasting. Few studies project the future effects of climate change on brain health, hindering policy developments. Robust studies on the threats from changing climate for people who have, or are at risk of developing, disorders of the nervous system are urgently needed.

Raquel Norel, Michele Merler, Pavitra Modi

Patients with rare neurological diseases report cognitive symptoms -"brain fog"- invisible to traditional tests. We propose continuous neurocognitive monitoring via smartphone speech analysis integrated with Relational Graph Transformer (RELGT) architectures. Proof-of-concept in phenylketonuria (PKU) shows speech-derived "Proficiency in Verbal Discourse" correlates with blood phenylalanine (p = -0.50, p < 0.005) but not standard cognitive tests (all |r| < 0.35). RELGT could overcome information bottlenecks in heterogeneous medical data (speech, labs, assessments), enabling predictive alerts weeks before decompensation. Key challenges: multi-disease validation, clinical workflow integration, equitable multilingual deployment. Success would transform episodic neurology into continuous personalized monitoring for millions globally.

Felix Menne, Felix Dörr, Julia Schräder et al.

Abstract Background Psychiatry faces a challenge due to the lack of objective biomarkers, as current assessments are based on subjective evaluations. Automated speech analysis shows promise in detecting symptom severity in depressed patients. This project aimed to identify discriminating speech features between patients with major depressive disorder (MDD) and healthy controls (HCs) by examining associations with symptom severity measures. Methods Forty-four MDD patients from the Psychiatry Department, University Hospital Aachen, Germany and fifty-two HCs were recruited. Participants described positive and negative life events, which were recorded for analysis. The Beck Depression Inventory (BDI-II) and the Hamilton Rating Scale for Depression gauged depression severity. Transcribed audio recordings underwent feature extraction, including acoustics, speech rate, and content. Machine learning models including speech features and neuropsychological assessments, were used to differentiate between the MDD patients and HCs. Results Acoustic variables such as pitch and loudness differed significantly between the MDD patients and HCs (effect sizes 𝜼2 between 0.183 and 0.3, p < 0.001). Furthermore, variables pertaining to temporality, lexical richness, and speech sentiment displayed moderate to high effect sizes (𝜼2 between 0.062 and 0.143, p < 0.02). A support vector machine (SVM) model based on 10 acoustic features showed a high performance (AUC = 0.93) in differentiating between HCs and patients with MDD, comparable to an SVM based on the BDI-II (AUC = 0.99, p = 0.01). Conclusions This study identified robust speech features associated with MDD. A machine learning model based on speech features yielded similar results to an established pen-and-paper depression assessment. In the future, these findings may shape voice-based biomarkers, enhancing clinical diagnosis and MDD monitoring.

Md Fahim Anjum, Arturo I. Espinoza, Rachel C. Cole et al.

Abstract Cognitive dysfunction is common in Parkinson’s disease (PD). We developed and evaluated an EEG-based biomarker to index cognitive functions in PD from a few minutes of resting-state EEG. We hypothesized that synchronous changes in EEG across the power spectrum can measure cognition. We optimized a data-driven algorithm to efficiently capture these changes and index cognitive function in 100 PD and 49 control participants. We compared our EEG-based cognitive index with the Montreal cognitive assessment (MoCA) and cognitive tests across different domains from National Institutes of Health (NIH) Toolbox using cross-validations, regression models, and randomization tests. Finally, we externally validated our approach on 32 PD participants. We observed cognition-related changes in EEG over multiple spectral rhythms. Utilizing only 8 best-performing electrodes, our proposed index strongly correlated with cognition (MoCA: rho = 0.68, p value < 0.001; NIH-Toolbox cognitive tests: rho ≥ 0.56, p value < 0.001) outperforming traditional spectral markers (rho = −0.30–0.37). The index showed a strong fit in regression models (R 2 = 0.46) with MoCA, yielded 80% accuracy in detecting cognitive impairment, and was effective in both PD and control participants. Notably, our approach was equally effective (rho = 0.68, p value < 0.001; MoCA) in out-of-sample testing. In summary, we introduced a computationally efficient data-driven approach for cross-domain cognition indexing using fewer than 10 EEG electrodes, potentially compatible with dynamic therapies like closed-loop neurostimulation. These results will inform next-generation neurophysiological biomarkers for monitoring cognition in PD and other neurological diseases.

Moez Dawood, Ben Heavner, Marsha M. Wheeler et al.

Rare diseases are collectively common, affecting approximately one in twenty individuals worldwide. In recent years, rapid progress has been made in rare disease diagnostics due to advances in DNA sequencing, development of new computational and experimental approaches to prioritize genes and genetic variants, and increased global exchange of clinical and genetic data. However, more than half of individuals suspected to have a rare disease lack a genetic diagnosis. The Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) Consortium was initiated to study thousands of challenging rare disease cases and families and apply, standardize, and evaluate emerging genomics technologies and analytics to accelerate their adoption in clinical practice. Further, all data generated, currently representing ~7500 individuals from ~3000 families, is rapidly made available to researchers worldwide via the Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) to catalyze global efforts to develop approaches for genetic diagnoses in rare diseases (https://gregorconsortium.org/data). The majority of these families have undergone prior clinical genetic testing but remained unsolved, with most being exome-negative. Here, we describe the collaborative research framework, datasets, and discoveries comprising GREGoR that will provide foundational resources and substrates for the future of rare disease genomics.

Snehasis Banerjee, Sayan Paul, Ruddradev Roychoudhury et al.

This article presents Teledrive, a telepresence robotic system with embodied AI features that empowers an operator to navigate the telerobot in any unknown remote place with minimal human intervention. We conceive Teledrive in the context of democratizing remote care-giving for elderly citizens as well as for isolated patients, affected by contagious diseases. In particular, this paper focuses on the problem of navigating to a rough target area (like bedroom or kitchen) rather than pre-specified point destinations. This ushers in a unique AreaGoal based navigation feature, which has not been explored in depth in the contemporary solutions. Further, we describe an edge computing-based software system built on a WebRTC-based communication framework to realize the aforementioned scheme through an easy-to-use speech-based human-robot interaction. Moreover, to enhance the ease of operation for the remote caregiver, we incorporate a person following feature, whereby a robot follows a person on the move in its premises as directed by the operator. Moreover, the system presented is loosely coupled with specific robot hardware, unlike the existing solutions. We have evaluated the efficacy of the proposed system through baseline experiments, user study, and real-life deployment.

Ari Rappoport

Migraine (MGR) ranks first among diseases in terms of years of lost healthy life in young adult and adult women. Currently, there is no theory of MGR. This paper presents a complete theory of migraine that explains its etiology, symptoms, pathology, and treatment. Migraine involves partially saturated (usually chronically high) sympathetic nervous system (SNS) activity, mainly due to higher sensitivity of the metabolic sensors that recruit it. MGR headache occurs when SNS activity is desensitized or excessive, resulting in hyperexcitability of baroreceptors, oxidative stress, and activation of pain pathways via TRPV1 channels and CGRP. The theory is supported by overwhelming evidence, and explains the properties of current MGR treatments.

Jie Yang, Feifei Jiang, Ming Yang et al.

S. Bhagavati

Remarkable discoveries over the last two decades have elucidated the autoimmune basis of several, previously poorly understood, neurological disorders. Autoimmune disorders of the nervous system may affect any part of the nervous system, including the brain and spinal cord (central nervous system, CNS) and also the peripheral nerves, neuromuscular junction and skeletal muscle (peripheral nervous system, PNS). This comprehensive overview of this rapidly evolving field presents the factors which may trigger breakdown of self-tolerance and development of autoimmune disease in some individuals. Then the pathophysiological basis and clinical features of autoimmune diseases of the nervous system are outlined, with an emphasis on the features which are important to recognize for accurate clinical diagnosis. Finally the latest therapies for autoimmune CNS and PNS disorders and their mechanisms of action and the most promising research avenues for targeted immunotherapy are discussed.

Michael M.H. Yang, MD, MSc, MBiotech, Jay Riva-Cambrin, MD, MSc, Jonathan Cunningham, MD, MSc et al.

Background: Approximately 30% to 64% of patients experience inadequate pain control following spine surgery. The Calgary postoperative pain after spine surgery (CAPPS) score was developed to identify this subset of patients. The impact of preoperative insomnia on postoperative pain control is unknown. This study aimed to investigate the relationship between preoperative insomnia and poor pain control after spine surgery, as well as improve the predictive accuracy of the CAPPS score. Methods: A prospective cohort study was conducted in patients undergoing elective spine surgery. Poor pain control was defined as a mean numeric rating scale pain score >4 at rest within the first 24-hours after surgery. Patients were evaluated using the CAPPS score, which included 7 prognostic factors. A multivariable logistic regression model was used to examine the association between preoperative insomnia severity index (ISI) and poor pain control, adjusting for the CAPPS score. The Modified CAPPS score was derived from this model. Results: Of 219 patients, 49.7% experienced poorly controlled pain. Prevalence of clinical insomnia (ISI≥15) was 26.9%. Preoperative ISI was independently associated with poor pain control (odds ratio [OR] 1.09, [95%CI=1.03–1.16], p=.004), after adjusting for the CAPPS score (OR 1.61, [95%CI=1.38–1.89], p<.001). The model exhibited good discrimination (c-statistics 0.80, [95%CI=0.74–0.86]) and calibration (Hosmer-Lemeshow chi-square=8.95, p=.35). The Modified CAPPS score also demonstrated good discrimination (c-statistic 0.78, [95%CI=0.72–0.84]) and calibration (Hosmer-Lemeshow chi-square=2.92, p=.57). Low-, high-, and extreme-risk groups stratified by the Modified CAPPS score had 17.3%, 49.1%, and 80.7% predicted probability of experiencing inadequate pain control compared to 32.0%, 64.0%, and 85.1% in the CAPPS score. Conclusions: Preoperative insomnia is prevalent and is a modifiable risk factor for poor pain control following spine surgery. Early identification and management of preoperative insomnia may lead to improved postoperative pain outcomes. Future external validation is needed to confirm the accuracy of the Modified CAPPS score.

Andrii Voshchepynets, Oleksiy Agapitov, Lynn Wilson et al.

We present the results of processing the effects of the powerful Gamma Ray Burst GRB221009A captured by the charged particle detectors (electrostatic analyzers and solid-state detectors) onboard spacecraft at different points in the heliosphere on October 9, 2022. To follow the GRB221009A propagation through the heliosphere we used the electron and proton flux measurements from solar missions Solar Orbiter and STEREO-A; Earth magnetosphere and the solar wind missions THEMIS and Wind; meteorological satellites POES15, POES19, MetOp3; and MAVEN - a NASA mission orbiting Mars. GRB221009A had a structure of four bursts: less intense Pulse 1 - the triggering impulse - was detected by gamma-ray observatories at 131659 UT (near the Earth); the most intense Pulses 2 and 3 were detected on board all the spacecraft from the list, and Pulse 4 detected in more than 500 s after Pulse 1. Due to their different scientific objectives, the spacecraft, which data was used in this study, were separated by more than 1 AU (Solar Orbiter and MAVEN). This enabled tracking GRB221009A as it was propagating across the heliosphere. STEREO-A was the first to register Pulse 2 and 3 of the GRB, almost 100 seconds before their detection by spacecraft in the vicinity of Earth. MAVEN detected GRB221009A Pulses 2, 3, and 4 at the orbit of Mars about 237 seconds after their detection near Earth. By processing the time delays observed we show that the source location of the GRB221009A was at RA 288.5 degrees, Dec 18.5 degrees (J2000) with an error cone of 2 degrees

M. Jha, B. Morrison

&NA; The brain is, by weight, only 2% the volume of the body and yet it consumes about 20% of the total glucose, suggesting that the energy requirements of the brain are high and that glucose is the primary energy source for the nervous system. Due to this dependence on glucose, brain physiology critically depends on the tight regulation of glucose transport and its metabolism. Glucose transporters ensure efficient glucose uptake by neural cells and contribute to the physiology and pathology of the nervous system. Despite this, a growing body of evidence demonstrates that for the maintenance of several neuronal functions, lactate, rather than glucose, is the preferred energy metabolite in the nervous system. Monocarboxylate transporters play a crucial role in providing metabolic support to axons by functioning as the principal transporters for lactate in the nervous system. Monocarboxylate transporters are also critical for axonal myelination and regeneration. Most importantly, recent studies have demonstrated the central role of glial cells in brain energy metabolism. A close and regulated metabolic conversation between neurons and both astrocytes and oligodendroglia in the central nervous system, or Schwann cells in the peripheral nervous system, has recently been shown to be an important determinant of the metabolism and function of the nervous system. This article reviews the current understanding of the long existing controversies regarding energy substrate and utilization in the nervous system and discusses the role of metabolic transporters in health and diseases of the nervous system. HighlightsGlucose, lactate and acetate are used as metabolic fuels in the nervous systemFunction of energy metabolites dependent on expression of specific metabolic transportersBrain glucose transporters are primarily expressed in blood vessels and gliaMonocarboxylate transporters support axon function in the brain and nerve regeneration in the peripheral nervous systemDisruption of glucose or monocarboxylate transporters leads to cellular dysfunction and neurologic disease

Rajeev Sharma, Ashish Bindra, Kapil Dev Soni

Nasal bridge is a common site suffering personal protective equipment-induced skin damages over face among first-line health care workers in this coronavirus disease 2019 pandemic. We hereby report folliculitis as a complication following regular use of N95 respirator and goggles, unreported in literature till now.

Rumeysa Eda Kanık Tezcan, Özden Yalçınkaya Alkar

Fibromyalgia is a musculoskeletal pain syndrome characterized with the presence of sensitive points and widespread chronic pain and restricts one's daily life activities and decreases the quality of life. The etiology of fibromyalgia is unclear, but there are numerous hypotheses regarding the emergence and progression of the disease. Among these, the biopsychosocial model offers a holistic framework in which biological, psychological and social mechanisms play a role in the development of fibromyalgia. Since the etiology of the disease is not yet understood, effective methods for its treatment have not been found, thus, interventions aim to reduce the effect of fibromyalgia and increase psychological and physiological functionality. This article aims to examine the psyhcological intervention areas and methods for fibromyalgia patients. In the literature, it is concluded that pain avoidance beliefs and behaviors, self-efficacy, physical activity, sleep quality, self-compassion, emotional skills, coping strategies, personality, comorbid psychopathology are the factors related with the emergence of the disease, severity of pain, and adherence to treatment in fibromyalgia patients. In this context, Cognitive-Behavioral Therapy (CBT), physical exercises, sleep management Acceptance and Commitment Therapy (ACT), compassion focused psychotherapies, mindfulness based psychotherapies, emotion expression and emotion regulation techniques, and biofeedback are recommended as effective methods which can be included in the treatment plans of fibromyalgia patients. Moreover, considering the psychosocial factors in the assessment processes was essential to establish individualized treatment plans. In addition, the importance of multidisciplinary approaches in the treatment processes of fibromyalgia has been discussed within the framework of the biopsychosocial model.

Sisi Shen, Zaiquan Dong, Qi Zhang et al.

Background: Emotional disorder is an important indicator for assessing the quality of life (QOL) of people with epilepsy (PWE). Depression, somatic symptom disorder (SSD) and anxiety are among the most frequently occurring mental disorders and overlap with each other. Objectives: This study examines the overlap of these three emotional disorders and their effects separately and in combination on the QOL of PWE. Design: Cross-sectional study. Data Sources and Methods: Adults attending our epilepsy clinic between 1 July 2020 and 1 May 2022 were consecutively enrolled. They were screened for depression, SSD, and anxiety by structured interviews, and demographic, epilepsy-related and QOL indicators were collected. Multivariate analysis, propensity score matching (PSM) and stratified analysis were used to explore the effects of their respective and combined effects on QOL. Results: Among the 749 patients, 189 patients (25%) were diagnosed with depression, 183 patients (24%) were diagnosed with SSD, and 157 patients (21%) were diagnosed with anxiety. The frequency of occurrence of each emotional disorder together with other emotional disorders was higher than the frequency of occurrence of an emotional disorder alone. Depression, SSD, and anxiety all had an independent effect on QOL of PWE ( p  < 0.001). Depression had the greatest effect, followed by SSD, and then anxiety ( β : multivariate analysis, −11.0 versus –7.8 versus –6.5; PSM, −14.7 versus –9.4 versus –6.8). The QOL of PWE decreased more significantly with the increasing number of comorbid emotional disorders ( β : –12.1 versus –20.7 versus –23.0). Conclusion: It is necessary to screen for three emotional disorders, that is, depression, SSD, and anxiety, in PWE. Attention should be paid to people with multiple comorbid emotional disorders.

Lizel Göranson, Olof Svensson, Olof Svensson et al.

BackgroundWhich type of information experts use to make decisions regarding legal insanity within forensic psychiatric investigations (FPI) is relatively unknown, both in general and when considering variations due to case context. It is important to explore this area to be able to counteract the effects of various kinds of cognitive bias.MethodThe aim was to explore whether FPI expert groups differed regarding case-specific as well as general use of information types required to make decisions on severe mental disorder (SMD). Three FPI case vignettes were presented to three professional groups involved in FPIs in Sweden (n = 41): forensic psychiatrists (n = 15), psychologists (n = 15), and social workers (n = 11). The participants reported which types of information they required to reach conclusions regarding SMD in each case. They also reported which types of information they had used within general FPI praxis during the previous year and the information types’ perceived usefulness.ResultsThe expert groups differed somewhat regarding what type of information they required for the cases (e.g., results from cognitive testing), but some information was required in all cases (e.g., client’s self-report). Regarding the preliminary assessment of SMD in the three cases, minor differences were found. Within the general FPI praxis, experts reported using several information types, while the general perceived usefulness of these sources varied.DiscussionThe professional groups relied partly on a “core” of information sources, but some case-specific adaptations were found. The professional groups’ inclination to suspect SMD also varied somewhat. This indicates a need to explore the potential consequences of these similarities and differences.

Wending Mai, Yifan Chen

We propose a system to visualize the chirality of the protein in brains, which would be helpful to diagnose early neurological degenerative diseases in vivo. These neurological degenerative diseases often occur along with some mark proteins. By nanoparticle instilling and metamaterial technique, the chiral effect of the mark proteins is assumed to be manifest in microwave regime. Therefore, by detecting the transmission of cross-polarization, we could detect the chirality that rotates the microwave polarization angle. We developed a numerical method to simulate the electromagnetic response upon chiral (bi-isotropic) material. Then a numerical experiment was conduct with a numerical head phantom. A map of cross-polarized transmission magnitude can be reached by sweeping the antenna pair. The imaging results matches well with the distribution of chiral materials. It suggests that the proposed method would be capable of in vivo imaging of neurological degenerative disease using microwaves.

G. Nandakumar, N. Ryde, M. Montelius et al.

Phosphorus (P) is considered to be one of the key elements for life, making it an important element to look for in the abundance analysis of spectra of stellar systems. Yet, there exists only a handful of spectroscopic studies to estimate the P abundances and investigate its trend across a range of metallicities. We have observed full HK band spectra at a spectral resolving power of R=45,000 with IGRINS instrument. Abundances are determined using SME in combination with 1D MARCS stellar atmosphere models. The investigated sample of stars have reliable stellar parameters estimated using optical FIES spectra (GILD; Jönsson et al. in prep.). In order to determine the P abundances from the 16482.92 Angstrom P line, we take special care of the CO($ν=7-4$) blend. We determine the C, N, O abundances from atomic carbon and a range of non-blended molecular lines (CO, CN, OH) which are aplenty in the H band region of K giant stars, assuring an appropriate modelling of the blending CO($ν=7-4$) line. We present [P/Fe] vs [Fe/H] trend for 38 K giant stars in the metallicity range of -1.2 dex $<$ [Fe/H] $<$ 0.4 dex. We find that our trend matches well with the compiled literature sample of prominently dwarf stars and limited number of giant stars. Our trend is found to be higher by $\sim$ 0.05 - 0.1 dex compared to the theoretical chemical evolution trend in Cescutti et al. 2012 resulting from core collapse supernova (type II) of massive stars with the P yields from Kobayashi et al. (2006) arbitrarily increased by a factor of 2.75. Thus the enhancement factor might need to be $\sim$ 0.05 - 0.1 dex higher to match our trend. We also find an empirically determined primary behaviour for phosphorus. Furthermore, the phosphorus abundance is found to be elevated by $\sim$ 0.6 - 0.9 dex in two metal poor s-enriched stars compared to the theoretical chemical evolution trend.