Optimal dose of fenfluramine in adjuvant treatment of drug-resistant epilepsy: evidence from randomized controlled trials

ObjectiveSeveral clinical trials have suggested that fenfluramine (FFA) is effective for the treatment of epilepsy in Dravet syndrome (DS) and Lennox–Gastaut syndrome (LGS). However, the exploration of its optimal target dose is ongoing. This study aimed to summarize the best evidence to inform this clinical issue.Materials and methodsWe searched PubMed, Embase (via Ovid), and Web of Science for relevant literature published before December 1st, 2023. Randomized, double-blind, placebo-controlled studies that evaluated the efficacy, safety, and tolerability of FFA in DS and LGS were identified and meta-analysis was performed according to doses. The study was registered with PROSPERO (CRD42023392454).ResultsSix hundred and twelve patients from four randomized controlled trials were enrolled. The results demonstrated that FFA at 0.2, 0.4, or 0.7 mg/kg/d showed significantly greater efficacy compared to placebo in terms of at least 50% reduction (p < 0.001, p < 0.001, p < 0.001) and at least 75% reduction (p < 0.001, p = 0.007, p < 0.001) in monthly seizure frequency from baseline. Moreover, significantly more patients receiving FFA than placebo were rated as much improved or very much improved in CGI-I by both caregivers/parents and investigators (p < 0.001). The most common treatment-emergent adverse events were decreased appetite, diarrhea, fatigue, and weight loss, with no valvular heart disease or pulmonary hypertension observed in any participant. For dose comparison, 0.7 mg/kg/d group presented higher efficacy on at least 75% reduction in seizure (p = 0.006) but not on at least 50% reduction. Weight loss (p = 0.002), decreased appetite (p = 0.04), and all-cause withdrawal (p = 0.036) were more common in 0.7 mg/kg/d group than 0.2 mg/kg/d. There was no statistical difference in other safety parameters between these two groups.ConclusionThe higher range of the licensed dose achieves the optimal balance between efficacy, safety, and tolerability in patients with DS and LGS.Clinical trial registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023392454

Safety and efficacy of rapid withdrawal of anti-seizure medication during long-term video-EEG monitoring

ObjectiveAnti-seizure medications (ASMs) are often withdrawn during long-term video-EEG monitoring (LTM) to allow pre-surgical evaluation. Herein, we evaluated the safety and efficacy of ultra-rapid withdrawal (URW) and rapid withdrawal (RW) of ASMs in an epilepsy monitoring unit (EMU).MethodsThis retrospective study examined all consecutive patients admitted to our EMU between May 2021 and October 2022. Patients were classified into the URW and RW groups according to the way ASMs were withdrawn. We compared the efficacy and safety of the procedures used in the groups in terms of duration of LTM, latency to the first seizure, and incidence of focal to bilateral tonic–clonic seizures (FBTCS), seizure clusters (SC), and status epilepticus (SE).ResultsOverall, 110 patients (38 women) were included. The mean age of patients at the time of LTM was 29 years. All medications were stopped on admission for monitoring in the URW group (n = 75), while in the RW group (n = 35) ASMs were withdrawn within 1 day. In both groups, the duration of LTM was approximately 3 days: URW group (2.9 ± 0.5 days) and RW group (3.1 ± 0.8 days). The latency to the first seizure was significantly different between the two groups; however, there were no differences between the two groups in terms of the distribution of FBTCS, SC, or SE, number of seizures, and the requirement for intravenous rescue medication was low.ConclusionThe rapid withdrawal of ASMs to provoke seizures during monitoring for pre-surgical evaluation following the URW protocol was as effective and safe as with RW. Ultra-rapid ASM withdrawal has the benefits of reducing LTM duration and shortening the time to first seizure compared to rapid medication tapering

The impact of type 2 diabetes and its management on the prognosis of patients with severe COVID‐19

Background Although type 2 diabetes mellitus (T2DM) patients with coronavirus disease 2019 (COVID‐19) develop a more severe condition compared to those without diabetes, the mechanisms for this are unknown. Moreover, the impact of treatment with antihyperglycemic drugs and glucocorticoids is unclear. Methods From 1584 COVID‐19 patients, 364 severe/critical COVID‐19 patients with clinical outcome were enrolled for the final analysis, and patients without preexisting T2DM but elevated glucose levels were excluded. Epidemiological data were obtained and clinical status evaluation carried out to assess the impact of T2DM and its management on clinical outcomes. Results Of 364 enrolled severe COVID‐19 inpatients, 114 (31.3%) had a history of T2DM. Twenty‐seven (23.7%) T2DM patients died, who had more severe inflammation, coagulation activation, myocardia injury, hepatic injury, and kidney injury compared with non‐DM patients. In severe COVID‐19 patients with T2DM, we demonstrated a higher risk of all‐cause fatality with glucocorticoid treatment (adjusted hazard ratio [HR], 3.61; 95% CI, 1.14‐11.46; P = .029) and severe hyperglycemia (fasting plasma glucose ≥11.1 mmol/L; adjusted HR, 11.86; 95% CI, 1.21‐116.44; P = .034). Conclusions T2DM status aggravated the clinical condition of COVID‐19 patients and increased their critical illness risk. Poor fasting blood glucose (≥ 11.1 mmol/L) and glucocorticoid treatment are associated with poor prognosis for T2DM patients with severe COVID‐19

Agarose-resolvable InDel markers based on whole genome re-sequencing in cucumber

Insertion and Deletion (InDel) are common features in genomes and are associated with genetic variation. The whole-genome re-sequencing data from two parents (X1 and X2) of the elite cucumber (Cucumis sativus) hybrid variety Lvmei No.1 was used for genome-wide InDel polymorphisms analysis. Obtained sequence reads were mapped to the genome reference sequence of Chinese fresh market type inbred line ‘9930’ and gaps conforming to InDel were pinpointed. Further, the level of cross-parents polymorphism among five pairs of cucumber breeding parents and their corresponding hybrid varieties were used for evaluating hybrid seeds purity test efficiency of InDel markers. A panel of 48 cucumber breeding lines was utilized for PCR amplification versatility and phylogenetic analysis of these markers. In total, 10,470 candidate InDel markers were identified for X1 and X2. Among these, 385 markers with more than 30 nucleotide difference were arbitrary chosen. These markers were selected for experimental resolvability through electrophoresis on an Agarose gel. Two hundred and eleven (211) accounting for 54.81% of markers could be validated as single and clear polymorphic pattern while 174 (45.19%) showed unclear or monomorphic genetic bands between X1 and X2. Cross-parents polymorphism evaluation recorded 68 (32.23%) of these markers, which were designated as cross-parents transferable (CPT) InDel markers. Interestingly, the marker InDel114 presented experimental transferability between cucumber and melon. A panel of 48 cucumber breeding lines including parents of Lvmei No. 1 subjected to PCR amplification versatility using CPT InDel markers successfully clustered them into fruit and common cucumber varieties based on phylogenetic analysis. It is worth noting that 16 of these markers were predominately associated to enzymatic activities in cucumber. These agarose-based InDel markers could constitute a valuable resource for hybrid seeds purity testing, germplasm classification and marker-assisted breeding in cucumber

From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities

Multi-modal Large Language Models (MLLMs) have shown impressive abilities in generating reasonable responses with respect to multi-modal contents. However, there is still a wide gap between the performance of recent MLLM-based applications and the expectation of the broad public, even though the most powerful OpenAI's GPT-4 and Google's Gemini have been deployed. This paper strives to enhance understanding of the gap through the lens of a qualitative study on the generalizability, trustworthiness, and causal reasoning capabilities of recent proprietary and open-source MLLMs across four modalities: ie, text, code, image, and video, ultimately aiming to improve the transparency of MLLMs. We believe these properties are several representative factors that define the reliability of MLLMs, in supporting various downstream applications. To be specific, we evaluate the closed-source GPT-4 and Gemini and 6 open-source LLMs and MLLMs. Overall we evaluate 230 manually designed cases, where the qualitative results are then summarized into 12 scores (ie, 4 modalities times 3 properties). In total, we uncover 14 empirical findings that are useful to understand the capabilities and limitations of both proprietary and open-source MLLMs, towards more reliable downstream multi-modal applications

Search for the Rare Decays J/Psi --> Ds- e+ nu_e, J/Psi --> D- e+ nu_e, and J/Psi --> D0bar e+ e-

We report on a search for the decays J/Psi --> Ds- e+ nu_e + c.c., J/Psi --> D- e+ nu_e + c.c., and J/Psi --> D0bar e+ e- + c.c. in a sample of 5.8 * 10^7 J/Psi events collected with the BESII detector at the BEPC. No excess of signal above background is observed, and 90% confidence level upper limits on the branching fractions are set: B(J/Psi --> Ds- e+ nu_e + c.c.)<4.8*10^-5, B(J/Psi --> D- e+ nu_e + c.c.) D0bar e+ e- + c.c.)<1.1*10^-5Comment: 10 pages, 4 figure