Water-Solubilization of P(V) and Sb(V) Porphyrins and Their Photobiological Application

Porphyrins have been widely utilized as biochemical and biological functional chromophores which can operate under visible-light irradiation. Water-soluble porphyrins have been used as the drug for photodynamic therapy (PDT) and photodynamic inactivation (PDI). Although usual water-solubilization of porphyrins has been achieved by an introduction of an ionic group such as ammonium, pyridinium, sulfonate, phosphonium, or carboxyl to porphyrin ring, we proposed the preparation of water-soluble P and Sb porphyrins by modification of axial ligands. Alkyl (type A), ethylenedioxy (type E), pyridinium (type P), and glucosyl groups (type G) were introduced to axial ligands of Sb and P porphyrins to achieve water-solubilization of Sb porphyrin and P porphyrins. Here, we review their water-soluble P and Sb porphyrins from the standpoints of preparation, bioaffinity, and photosensitized inactivation

Levetiracetam improves symptoms of multiple chemical sensitivity : Case report

Multiple chemical sensitivity (MCS) is a disorder of unknown etiology with no effective treatment. Many clinicians accept that a diagnosis of somatic symptoms disorder (SSD) is an appropriate diagnostic category for MCS. We found that administration of levetiracetam improved recurrent symptoms of MCS in a patient. A 23-year-old female presented with recurrent multiple symptoms of musculoskeletal, airway or mucous membrane, heart/chest-related, gastrointestinal, cognitive, affective, neuromuscular, head-related, and skinrelated induced by exposure to diesel or gas engine exhaust, tobacco smoke, insecticide, gasoline, paint or paint thinner, cleaning products, fragrances, tar or asphalt, nail polish or hairspray, and new furnishings. Gastrointestinal, cognitive, and skin-related symptoms were precipitated by some food additives. She suffered partial seizures from the age of 17 years, and was diagnosed with right parietal lobe epilepsy. Administration of levetiracetam (250 mg/day) eliminated her MCS symptoms. Levetiracetam reduces the release of presynaptic neurotransmitter including glutamate by binding to presynaptic vesicle protein. A recent study established the presence of glutamatergic overactivation in somatization disorder, a form of SSD. Our case may indicate that a subset of patients with SSD have glutamatergic overactivation, which levetiracetam can normalize

Parental satisfaction and seizure outcome after corpus callosotomy in patients with infantile or early childhood onset epilepsy

AbstractPurposeTo elucidate the benefit of corpus callosotmy in terms of parental satisfaction and seizure outcome.MethodThis study included 16 consecutive patients with infantile or early childhood onset epilepsy who underwent total corpus callosotomy for alleviation of seizures. Questionnaires were sent anonymously to the parents asking about relative changes in seizures and about parental satisfaction for the post-operative outcome.ResultsThe improvements in frequency, intensity, and duration of seizures were correlated with the level of satisfaction (Spearman's rank-order correlation coefficient, ρ=0.87, 0.93, and 0.75, respectively). The highest level of satisfaction was only seen in patients who achieved freedom from all seizures or drop attacks.ConclusionComplete seizure freedom and freedom from drop attacks are important goals of corpus callosotomy for parental satisfaction. These factors should be considered in assessing post-operative outcome after corpus callosotomy

Ongoing EEG artifact correction using blind source separation

Objective: Analysis of the electroencephalogram (EEG) for epileptic spike and seizure detection or brain-computer interfaces can be severely hampered by the presence of artifacts. The aim of this study is to describe and evaluate a fast automatic algorithm for ongoing correction of artifacts in continuous EEG recordings, which can be applied offline and online. Methods: The automatic algorithm for ongoing correction of artifacts is based on fast blind source separation. It uses a sliding window technique with overlapping epochs and features in the spatial, temporal and frequency domain to detect and correct ocular, cardiac, muscle and powerline artifacts. Results: The approach was validated in an independent evaluation study on publicly available continuous EEG data with 2035 marked artifacts. Validation confirmed that 88% of the artifacts could be removed successfully (ocular: 81%, cardiac: 84%, muscle: 98%, powerline: 100%). It outperformed state-of-the-art algorithms both in terms of artifact reduction rates and computation time. Conclusions: Fast ongoing artifact correction successfully removed a good proportion of artifacts, while preserving most of the EEG signals. Significance: The presented algorithm may be useful for ongoing correction of artifacts, e.g., in online systems for epileptic spike and seizure detection or brain-computer interfaces.Comment: 16 pages, 4 figures, 3 table

Development of an epileptic seizure prediction algorithm using R–R intervals with self-attentive autoencoder

Epilepsy is a neurological disorder that may affect the autonomic nervous system (ANS) from 15 to 20 min before seizure onset, and disturbances of ANS affect R–R intervals (RRI) on an electrocardiogram (ECG). This study aims to develop a machine learning algorithm for predicting focal epileptic seizures by monitoring R–R interval (RRI) data in real time. The developed algorithm adopts a self-attentive autoencoder (SA-AE), which is a neural network for time-series data. The results of applying the developed seizure prediction algorithm to clinical data demonstrated that it functioned well in most patients; however, false positives (FPs) occurred in specific participants. In a future work, we will investigate the causes of FPs and optimize the developing seizure prediction algorithm to further improve performance using newly added clinical data

Decline in subarachnoid haemorrhage volumes associated with the first wave of the COVID-19 pandemic

BACKGROUND: During the COVID-19 pandemic, decreased volumes of stroke admissions and mechanical thrombectomy were reported. The study\u27s objective was to examine whether subarachnoid haemorrhage (SAH) hospitalisations and ruptured aneurysm coiling interventions demonstrated similar declines. METHODS: We conducted a cross-sectional, retrospective, observational study across 6 continents, 37 countries and 140 comprehensive stroke centres. Patients with the diagnosis of SAH, aneurysmal SAH, ruptured aneurysm coiling interventions and COVID-19 were identified by prospective aneurysm databases or by International Classification of Diseases, 10th Revision, codes. The 3-month cumulative volume, monthly volumes for SAH hospitalisations and ruptured aneurysm coiling procedures were compared for the period before (1 year and immediately before) and during the pandemic, defined as 1 March-31 May 2020. The prior 1-year control period (1 March-31 May 2019) was obtained to account for seasonal variation. FINDINGS: There was a significant decline in SAH hospitalisations, with 2044 admissions in the 3 months immediately before and 1585 admissions during the pandemic, representing a relative decline of 22.5% (95% CI -24.3% to -20.7%, p\u3c0.0001). Embolisation of ruptured aneurysms declined with 1170-1035 procedures, respectively, representing an 11.5% (95%CI -13.5% to -9.8%, p=0.002) relative drop. Subgroup analysis was noted for aneurysmal SAH hospitalisation decline from 834 to 626 hospitalisations, a 24.9% relative decline (95% CI -28.0% to -22.1%, p\u3c0.0001). A relative increase in ruptured aneurysm coiling was noted in low coiling volume hospitals of 41.1% (95% CI 32.3% to 50.6%, p=0.008) despite a decrease in SAH admissions in this tertile. INTERPRETATION: There was a relative decrease in the volume of SAH hospitalisations, aneurysmal SAH hospitalisations and ruptured aneurysm embolisations during the COVID-19 pandemic. These findings in SAH are consistent with a decrease in other emergencies, such as stroke and myocardial infarction

Global Carbon Budget 2023

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based f CO2 products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements, and Earth system models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2022, EFOS increased by 0.9 % relative to 2021, with fossil emissions at 9.9 ± 0.5 Gt C yr−1 (10.2 ± 0.5 Gt C yr−1 when the cement carbonation sink is not included), and ELUC was 1.2 ± 0.7 Gt C yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 11.1 ± 0.8 Gt C yr−1 (40.7±3.2 Gt CO2 yr−1). Also, for 2022, GATM was 4.6±0.2 Gt C yr−1 (2.18±0.1 ppm yr−1; ppm denotes parts per million), SOCEAN was 2.8 ± 0.4 Gt C yr−1, and SLAND was 3.8 ± 0.8 Gt C yr−1, with a BIM of −0.1 Gt C yr−1 (i.e. total estimated sources marginally too low or sinks marginally too high). The global atmospheric CO2 concentration averaged over 2022 reached 417.1 ± 0.1 ppm. Preliminary data for 2023 suggest an increase in EFOS relative to 2022 of +1.1 % (0.0 % to 2.1 %) globally and atmospheric CO2 concentration reaching 419.3 ppm, 51 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean of and trend in the components of the global carbon budget are consistently estimated over the period 1959–2022, with a near-zero overall budget imbalance, although discrepancies of up to around 1 Gt C yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows the following: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living-data update documents changes in methods and data sets applied to this most recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2023 (Friedlingstein et al., 2023)