Category: Nevin Manimala

J Neuroimmunol. 2021 Jul 1;358:577653. doi: 10.1016/j.jneuroim.2021.577653. Online ahead of print.

ABSTRACT

BACKGROUND: Aseptic meningitis can be caused by autoimmune diseases, such as lupus and sarcoidosis. Aseptic meningitis with leptomeningeal enhancement can be the initial presentation of a neuroinflammatory syndrome associated with antibodies to myelin oligodendrocyte glycoprotein (MOG-abs). MOG-abs is a serum biomarker for MOG-associated disorder (MOG-AD), an acquired demyelinating syndrome that includes features of neuromyelitis optica, multiple sclerosis, optic neuritis, and acute disseminated encephalomyelitis. The purpose of this study is to review cases of aseptic meningitis and leptomeningeal enhancement associated with MOG-abs.

METHODS: Systematic review using PubMed, Embase, Ovid MEDLINE, Web of Science Core Collection, and Google Scholar up to December 2020 was performed. Cases of MOG-AD were included if they met the following criteria: 1) Initial clinical presentation of aseptic meningitis; 2) positive leptomeningeal enhancement and 3) MOG-Ab seropositivity. Descriptive statistics were used. This analysis was limited to the cases available in the literature.

RESULTS: 11 total cases of aseptic meningitis and leptomeningeal enhancement in setting of MOG-ab were identified. Demyelinating type T2 lesions were also present at time of presentation in 6/11; however, 5/11 of patients had leptomeningeal enhancement alone without demyelinating lesions. All 5 patients required immunotherapy for improvement, including one patient with symptoms for 28 days, with 4/5 receiving steroids and 1/5 receiving intravenous immunoglobulin (IVIG).

CONCLUSIONS: Aseptic meningitis with leptomeningeal enhancement can be the initial presenting symptom of MOG-AD. MOG-ab testing should be considered in a patient presenting with aseptic meningitis and leptomeningeal enhancement of unknown etiology.

PMID:34229204 | DOI:10.1016/j.jneuroim.2021.577653

J Clin Virol. 2021 Jun 27;141:104904. doi: 10.1016/j.jcv.2021.104904. Online ahead of print.

ABSTRACT

BACKGROUND: Most COVID-19 patients experience non-severe illness. The presence of SARS-CoV-2 antibodies suggest possible protection against re-infections in prior SARS-CoV-2 infected individuals.

OBJECTIVES: The aims of this prospective observational study were to longitudinally assess the antibody response during the first 4-6 months after polymerase chain reaction (PCR) confirmed SARS-CoV-2 infection, and to study the diagnostic performance of four different enzyme-linked immunosorbent assays (ELISAs) and a surrogate virus neutralization test (sVNT) in symptomatic healthcare workers (HCWs) with non-severe COVID-19.

STUDY DESIGN: HCWs in a teaching hospital were included between March 8 and June 15, 2020, when they had a PCR-confirmed SARS-CoV-2 infection in the past 3 months. The performances of four ELISAs (Wantai, Bio-Rad Platelia, BioTrading Immy clarus, and Euroimmun) were evaluated in serum samples obtained at the moment of study inclusion and subsequently at 1, 2 and 3 months thereafter. Furthermore, in the last available serum sample sVNT by GenScript was performed.

RESULTS: 309 samples from 80 positive HCWs were included of whom 70 (88%) were SARS-CoV-2 seropositive. The detection rates of SARS-CoV-2 antibodies by the different ELISAs were heterogenous ranging from 64% for the Euroimmun ELISA to 88% for the Wantai ELISA. The Wantai ELISA had the highest and almost perfect agreement with sVNT (96%, Cohen’s kappa 0.83).

CONCLUSION: SARS-CoV-2 (neutralizing) antibodies were detectable in most symptomatic individuals with non-severe COVID-19. The presence of antibodies remained stable up to six months after initial infection. There is large variability in diagnostic test performance between ELISA tests.

PMID:34229209 | DOI:10.1016/j.jcv.2021.104904

Clin Nutr. 2021 Jun 9;40(7):4535-4536. doi: 10.1016/j.clnu.2021.05.022. Online ahead of print.

NO ABSTRACT

PMID:34229256 | DOI:10.1016/j.clnu.2021.05.022

Med Image Anal. 2021 Jun 8;72:102128. doi: 10.1016/j.media.2021.102128. Online ahead of print.

ABSTRACT

Tracking of particles in temporal fluorescence microscopy image sequences is of fundamental importance to quantify dynamic processes of intracellular structures as well as virus structures. We introduce a probabilistic deep learning approach for fluorescent particle tracking, which is based on a recurrent neural network that mimics classical Bayesian filtering. Compared to previous deep learning methods for particle tracking, our approach takes into account uncertainty, both aleatoric and epistemic uncertainty. Thus, information about the reliability of the computed trajectories is determined. Manual tuning of tracking parameters is not necessary and prior knowledge about the noise statistics is not required. Short and long-term temporal dependencies of individual object dynamics are exploited for state prediction, and assigned detections are used to update the predicted states. For correspondence finding, we introduce a neural network which computes assignment probabilities jointly across multiple detections as well as determines the probabilities of missing detections. Training requires only simulated data and therefore tedious manual annotation of ground truth is not needed. We performed a quantitative performance evaluation based on synthetic and real 2D as well as 3D fluorescence microscopy images. We used image data of the Particle Tracking Challenge as well as real time-lapse fluorescence microscopy images displaying virus structures and chromatin structures. It turned out that our approach yields state-of-the-art results or improves the tracking results compared to previous methods.

PMID:34229189 | DOI:10.1016/j.media.2021.102128

Med Image Anal. 2021 Jun 23;72:102145. doi: 10.1016/j.media.2021.102145. Online ahead of print.

ABSTRACT

PURPOSE: Artificial-intelligence population-based automated quantification of placental maturation and health from a rapid functional Magnetic Resonance scan. The placenta plays a crucial role for any successful human pregnancy. Deviations from the normal dynamic maturation throughout gestation are closely linked to major pregnancy complications. Antenatal assessment in-vivo using T2* relaxometry has shown great promise to inform management and possible interventions but clinical translation is hampered by time consuming manual segmentation and analysis techniques based on comparison against normative curves over gestation.

METHODS: This study proposes a fully automatic pipeline to predict the biological age and health of the placenta based on a free-breathing rapid (sub-30 second) T2* scan in two steps: Automatic segmentation using a U-Net and a Gaussian process regression model to characterize placental maturation and health. These are trained and evaluated on 108 3T MRI placental data sets, the evaluation included 20 high-risk pregnancies diagnosed with pre-eclampsia and/or fetal growth restriction. An independent cohort imaged at 1.5 T is used to assess the generalization of the training and evaluation pipeline.

RESULTS: Across low- and high-risk groups, automatic segmentation performs worse than inter-rater performance (mean Dice coefficients of 0.58 and 0.68, respectively) but is sufficient for estimating placental mean T2* (0.986 Pearson Correlation Coefficient). The placental health prediction achieves an excellent ability to differentiate cases of placental insufficiency between 27 and 33 weeks. High abnormality scores correlate with low birth weight, premature birth and histopathological findings. Retrospective application on a different cohort imaged at 1.5 T illustrates the ability for direct clinical translation.

CONCLUSION: The presented automatic pipeline facilitates a fast, robust and reliable prediction of placental maturation. It yields human-interpretable and verifiable intermediate results and quantifies uncertainties on the cohort-level and for individual predictions. The proposed machine-learning pipeline runs in close to real-time and, deployed in clinical settings, has the potential to become a cornerstone of diagnosis and intervention of placental insufficiency. APPLAUSE generalizes to an independent cohort imaged at 1.5 T, demonstrating robustness to different operational and clinical environments.

PMID:34229190 | DOI:10.1016/j.media.2021.102145

Eur J Obstet Gynecol Reprod Biol. 2021 Jun 20;263:198-204. doi: 10.1016/j.ejogrb.2021.06.022. Online ahead of print.

ABSTRACT

OBJECTIVE: The purpose of our study was to assess the knowledge and attitudes toward expanded carrier screening (ECS) between the medical staff and general population in China.

STUDY DESIGN: It was a survey-based cross-sectional study in Chinese. We provided an online survey for the general public nationwide. We classified the population into the medical staff and general population to evaluate the knowledge gap and provide a reference for ECS’s education programs. Except for obstetrician-gynecologists and nurses in the department of Obstetrics and Gynecology, other medical staff were not included in our study. A total of 1947 questionnaires were collected from July 11, 2020 to February 10, 2021. Two hundred and eighty-four questionnaires were excluded from further analysis. The remaining 1663 cases were incorporated into the final analysis. Data were analyzed using IBM SPSS Statistics 26. Comparisons between categorical variables were tested by the use of crosstabs and χ2 test.

RESULTS: The total awareness rates of the knowledge about monogenic diseases and ECS in the respondents were low, with 35.7%, 26.1%, 3.3%, 23.3%, 24.1%, 55.2%, and 23.4% for questions Q1-Q7, respectively. Medical staff had more knowledge than general population. Knowledge about monogenic diseases and ECS was positively correlated with educational level. Most respondents showed a positive attitude toward ECS: 54.4% thought ECS was necessary, and 80.5% wanted to know more about monogenic diseases.

CONCLUSION: Although the public had little knowledge about monogenic disease and ECS, most of them showed a positive attitude. Our cross-analysis showed that medical staff had more knowledge compared to general population. Pre-test education for ECS can be carried out by medical staff who are not qualified for genetic counseling. ECS training for medical staff, especially obstetrician-gynecologist and nurse in the department of Obstetrics and Gynecology, can reduce the workload of genetic counseling.

PMID:34229183 | DOI:10.1016/j.ejogrb.2021.06.022

Eur J Obstet Gynecol Reprod Biol. 2021 Jun 25;263:205-209. doi: 10.1016/j.ejogrb.2021.06.029. Online ahead of print.

ABSTRACT

OBJECTIVE: Women undergoing assisted reproductive treatment are usually concerned about the side effects caused by high doses of gonadotropin. A common inquiry of patients is concerning the weight gain as a consequence. The aim of this study was to evaluate if controlled ovarian stimulation increase the weight of women undergoing IVF treatment. Study design This retrospective cohort study included 734 women undergoing IVF treatment between January 2017 and May 2018 and had body weight measured on the day of ovarian stimulation starting (basal-weight) and on the hCG trigger day (hCG-weight). The difference of hCG-weight and basal-weight was calculated and correlated to number of oocytes retrieved and ovarian stimulation protocol. For 358 women, two international validated questionnaires to evaluate the anxiety and binge eating were applied at the end of ovarian stimulation and also associated to the body weight gain.

RESULTS: The basal-weight and hCG-weight were paired compared and demonstrate a statistically significant weight gain from basal to hCG-weight of a mean of 387.7 ± 720.4 g (p < 0.001). The weight gain had a positive correlation with the number of oocytes retrieved (Pearson correlation, r = 0.181; p < 0.001) but no correlation with the ovarian stimulation protocol. Regarding the questionnaires answered by patients, neither anxiety score (Pearson: r = -0,031; p = 0,561) nor binge eating score (Pearson: r = 0,069; p = 0,199) were correlated with weight gain from basal-weight to hCG- weight. However, patients who felt eating more during the treatment had a higher weight gain (p < 0.001) independently of the number of oocytes retrieved.

CONCLUSIONS: The weight gain is possibly a result from edema and is clinically irrelevant despite of the statistical significance and will probably be resolved in some days after oocytes retrieval. A small “weight gain” was observed and associated to the number of oocytes retrieved regardless of protocol and medication used in the ovarian stimulation.

PMID:34229184 | DOI:10.1016/j.ejogrb.2021.06.029

Ecotoxicol Environ Saf. 2021 Jun 30;222:112481. doi: 10.1016/j.ecoenv.2021.112481. Online ahead of print.

ABSTRACT

Due to the COVID-19 outbreak, the Chinese government implemented nationwide traffic restrictions and self-quarantine measures from January 23 to April 8 (in Wuhan), 2020. We estimated how these measures impacted ambient air pollution and the subsequent consequences on health and the health-related economy in 367 Chinese cities. A random forests modeling was used to predict the business-as-usual air pollution concentrations in 2020, after adjusting for the impact of long-term trend and weather conditions. We calculated changes in mortality attributable to reductions in air pollution in early 2020 and health-related economic benefits based on the value of statistical life (VSL). Compared with the business-as-usual scenario, we estimated 1239 (95% CI: 844-1578) PM_2.5-related deaths were avoided, as were 2777 (95% CI: 1565-3995) PM₁₀-related deaths, 1587 (95% CI: 98-3104) CO-related deaths, 4711 (95% CI: 3649-5781) NO₂-related deaths, 215 (95% CI: 116-314) O₃-related deaths, and 1088 (95% CI: 774-1421) SO₂-related deaths. Based on the reduction in deaths, economic benefits for in PM_2.5, PM₁₀, CO, NO₂, O₃, and SO₂ were 1.22, 2.60, 1.36, 4.05, 0.20, and 0.95 billion USD, respectively. Our findings demonstrate the substantial benefits in human health and health-related costs due to improved urban air quality during the COVID lockdown period in China in early 2020.

PMID:34229169 | DOI:10.1016/j.ecoenv.2021.112481

J Mech Behav Biomed Mater. 2021 Jun 29;122:104666. doi: 10.1016/j.jmbbm.2021.104666. Online ahead of print.

ABSTRACT

Teeth are the hardest part of the human body. Cracking of human teeth under compression progresses by avalanches emitting acoustic noise. Acoustic emission (AE) spectroscopy reveals that tooth avalanches are statistically fully compatible with predictions of mean field (MF) theory. Avalanche energies collapse into a power law distributed which is stable over more than five decades with an energy exponent ε = 1.4. Acoustic amplitudes (exponent ~τ), durations (~α), correlations between amplitudes and energies (~x), and correlations between amplitude and duration (~χ) follow equally power laws with MF values of all exponents. The exponents correlation: τ-1 = x(ε-1) = (α-1)/χ is confirmed. Crack propagation bifurcates and shows the hallmarks of avalanches where main cracks nucleate secondary cracks.

PMID:34229170 | DOI:10.1016/j.jmbbm.2021.104666

Forensic Sci Int. 2021 Jun 24;325:110883. doi: 10.1016/j.forsciint.2021.110883. Online ahead of print.

ABSTRACT

In post-mortem investigations of fatal intoxication, it is challenging to determine which drug(s) were responsible for the death, and which drugs did not. This study aims to provide post-mortem femoral blood drug levels in lethal intoxication and in post-mortem control cases, where the cause of death was other than intoxication. The reference values could assist in the interpretation of toxicological results in the routine casework. To this end, all post-mortem toxicological results in femoral blood from 2011 to 2017 in Western Switzerland were considered. A full autopsy with systematic toxicological analysis (STA) was conducted in all cases. Results take into account the cause of death classified into one of four categories (as published by Druid and colleagues): I) certified intoxication by one substance alone, IIa) certified intoxication by more than one substance, IIb) certified other causes of death with incapacitation due to drugs, and III) certified other causes of death without incapacitation due to drugs. This study includes 1 990 post-mortem cases where femoral blood was analysed. The material comprised 619 women (31%) and 1 371 men (69%) with a median age of 50 years. The concentrations of the 32 most frequently recorded substances as well as alcohol are discussed. These include 6 opioids and opiates, 3 antidepressants, 6 neuroleptics and hypnotics, 1 barbiturate, 11 benzodiazepines (and related drugs), 2 amphetamine-type stimulants, cocaine, paracetamol, and tetrahydrocannabinol (THC). The most common substances that caused intoxication alone were morphine, methadone, ethanol, tramadol, and cocaine. The post-mortem concentration ranges for all substance are categorized as I, IIa, IIb, or III. Statistical post-mortem reference concentrations for drugs are discussed and compared with previously published concentrations. This study shows that recording and classifying cases is time-consuming, but it is rewarding in a long-term perspective to achieve a more reliable information about fatal and non-fatal blood concentrations.

PMID:34229141 | DOI:10.1016/j.forsciint.2021.110883