Association of modifiable risk factors with progression to dementia in relation to amyloid and tau pathology.

BACKGROUND: Dementia preventive interventions targeting multiple modifiable risk factors are a promising approach. However, the impact of modifiable risk factors in the presence of beta-amyloid or phosphorylated-tau (p-tau) pathology is unclear. METHODS: The objective of the study was to examine the role of modifiable risk factors (vascular factors, depression, and smoking) in the progression to mild cognitive impairment (MCI) or dementia among 434 cognitively unimpaired (CU) and 611 individuals with MCI from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Vascular risk factors were summarized with the Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) score, dichotomized into higher versus lower risk. Depression and smoking (yes/no) were categorised according to medical history or current symptoms. Analyses were stratified by beta-amyloid negative (A-) and positive (A +), p-tau negative (T-) and positive (T +), or beta-amyloid and p-tau negative (A-T-) and positive (A + T +) biomarker status. Cox proportional hazard models were adjusted for age, sex, education, baseline MMSE score, baseline hippocampal volume and ApoE4 carrier status. RESULTS: Higher CAIDE score was associated with increased risk of progression to all-cause dementia in most MCI subgroups: adjusted hazard ratios (aHR) [95% CI] were 3.1 [1.43; 6.53] in the A- subgroup, 1.7 [1.20-2.27] in T + , 2.6 [1.06-6.59] in A-T-, and 1.6 [1.15-2.22] in the A + T + subgroup. Smoking (yes/no) was associated with increased dementia aHR in the A + MCI subgroup: 1.6 [1.07-2.34]. Depression increased dementia aHR in the T + MCI subgroup: 1.5 [1.06-2.02]. No significant associations were found in the CU biomarker subgroups. CONCLUSION: Addressing modifiable risk factors carries an important potential for reducing the risk of dementia even after the onset of Alzheimer's pathology. Knowledge of biomarker status can further optimize prevention strategies.

Effects of Acute Citrulline Malate Supplementation on CrossFit® Exercise Performance: A Randomized, Double-Blind, Placebo-Controlled, Cross-Over Study.

Given the increasing popularity of CrossFit® as a high-intensity functional training program and the potential benefits of citrulline malate (CM) in enhancing exercise performance through its role as a precursor to L-arginine and nitric oxide production, this study aimed to investigate the acute effects of CM supplementation on CrossFit® performance and cardiovascular function. Using a randomized, double-blind, placebo-controlled, cross-over design, 21 recreationally active participants (mean age 22.2 ± 2.6 years, mean body weight 75.9 ± 10.4 kg) with CrossFit® experience completed the "Cindy" workout under CM and placebo conditions. Participants consumed 4.4 g of CM or a placebo 60 min before the workout, and the performance was measured by the number of rounds completed. Secondary outcomes included heart rate response, time spent in different heart rate intensity zones, and post-exercise recovery time. The results indicated no significant difference in the number of rounds completed between the CM and placebo conditions (13.5 ± 5.2 vs. 13.8 ± 6.7 rounds, respectively; p = 0.587). However, the time spent in zone 4 (80-90% of HR max) was significantly increased in the CM condition (527 ± 395 s vs. 453 ± 334 s; p = 0.017), suggesting a potential benefit for aerobic capacity and anaerobic threshold. No significant differences in post-exercise recovery time were observed (6.6 ± 4.7 h vs. 6.9 ± 4.7 h; p = 0.475). This study highlights the need for further research with larger sample sizes, both genders, and different CM dosages to clarify these findings and better understand CM's role in enhancing athletic performance.

Disruption of sleep macro- and microstructure in Alzheimer's disease: overlaps between neuropsychology, neurophysiology, and neuroimaging.

Alzheimer's disease (AD) is the leading cause of dementia, often associated with impaired sleep quality and disorganized sleep structure. This study aimed to characterize changes in sleep macrostructure and K-complex density in AD, in relation to neuropsychological performance and brain structural changes. We enrolled 30 AD and 30 healthy control participants, conducting neuropsychological exams, brain MRI, and one-night polysomnography. AD patients had significantly reduced total sleep time (TST), sleep efficiency, and relative durations of non-rapid eye movement (NREM) stages 2 (S2), 3 (S3), and rapid eye movement (REM) sleep (p < 0.01). K-complex (KC) density during the entire sleep period and S2 (p < 0.001) was significantly decreased in AD. We found strong correlations between global cognitive performance and relative S3 (p < 0.001; r = 0.86) and REM durations (p < 0.001; r = 0.87). TST and NREM stage 1 (S1) durations showed a moderate negative correlation with amygdaloid and hippocampal volumes (p < 0.02; r = 0.51-0.55), while S3 and REM sleep had a moderate positive correlation with cingulate cortex volume (p < 0.02; r = 0.45-0.61). KC density strongly correlated with global cognitive function (p < 0.001; r = 0.66) and the thickness of the anterior cingulate cortex (p < 0.05; r = 0.45-0.47). Our results indicate significant sleep organization changes in AD, paralleling cognitive decline. Decreased slow wave sleep and KCs are strongly associated with cingulate cortex atrophy. Since sleep changes are prominent in early AD, they may serve as prognostic markers or therapeutic targets.

Tuning the Solubility of Soluble Support Constructs in Liquid Phase Oligonucleotide Synthesis.

Solubility of the growing oligonucleotide-soluble support constructs in the liquid phase oligonucleotide synthesis (LPOS) is a critical parameter, which affects coupling efficiency, purity, and recovery of the growing oligonucleotides during the chain elongation. In the present study, oligonucleotides have been assembled on a 4-oxoheptanedioic acid (OHDA) linker-derived tetrapodal soluble support using 5'-O-(2-methoxyprop-2-yl)-protected 2'-deoxyribonucleotide phosphoroamidite building blocks with different nucleobase protecting groups [isobutyryl (Gua), 1-butylpyrrolidin-2-ylidene (Gua, Cyt), 2,4-dimethylbenzoyl (Ade, Cyt), and Bz (Thy)]. The solubility of the oligonucleotide-soluble support constructs (molecular mass varying between 3 and 10 kDa) as models of protected tetra-, octa-, dodeca-, hexadeca-, and eicosa-nucleotides was measured in different solvent systems and in potential antisolvents. By tuning the nucleobase protecting group scheme, the solubility can be improved in aprotic organic solvent systems, while the recovery of the constructs in the precipitation, used for the isolation and purification of the growing oligonucleotide intermediates in a protic antisolvent (2-propanol), remained near quantitative. The precipitation-based yield of the protected tetrapodal oligonucleotides varied from a quantitative to 90% yield. Overall yield (for di-: 95%, tri-: 79-96%, tetra-: 82-88%, and pentanucleotides: 68-75%) and purity of the LPOS were evaluated by RP HPLC and MS-spectroscopy of the released oligonucleotide aliquots. In addition, the orthogonality of the OHDA linker was applied to release authentic protected nucleotides from the soluble supports.

KCNQ1 suppression-replacement gene therapy in transgenic rabbits with type 1 long QT syndrome.

BACKGROUND AND AIMS: Type 1 long QT syndrome (LQT1) is caused by pathogenic variants in the KCNQ1-encoded Kv7.1 potassium channels, which pathologically prolong ventricular action potential duration (APD). Herein, the pathologic phenotype in transgenic LQT1 rabbits is rescued using a novel KCNQ1 suppression-replacement (SupRep) gene therapy. METHODS: KCNQ1-SupRep gene therapy was developed by combining into a single construct a KCNQ1 shRNA (suppression) and an shRNA-immune KCNQ1 cDNA (replacement), packaged into adeno-associated virus serotype 9, and delivered in vivo via an intra-aortic root injection (1E10 vg/kg). To ascertain the efficacy of SupRep, 12-lead electrocardiograms were assessed in adult LQT1 and wild-type (WT) rabbits and patch-clamp experiments were performed on isolated ventricular cardiomyocytes. RESULTS: KCNQ1-SupRep treatment of LQT1 rabbits resulted in significant shortening of the pathologically prolonged QT index (QTi) towards WT levels. Ventricular cardiomyocytes isolated from treated LQT1 rabbits demonstrated pronounced shortening of APD compared to LQT1 controls, leading to levels similar to WT (LQT1-UT vs. LQT1-SupRep, P < .0001, LQT1-SupRep vs. WT, P = ns). Under ß-adrenergic stimulation with isoproterenol, SupRep-treated rabbits demonstrated a WT-like physiological QTi and APD90 behaviour. CONCLUSIONS: This study provides the first animal-model, proof-of-concept gene therapy for correction of LQT1. In LQT1 rabbits, treatment with KCNQ1-SupRep gene therapy normalized the clinical QTi and cellular APD90 to near WT levels both at baseline and after isoproterenol. If similar QT/APD correction can be achieved with intravenous administration of KCNQ1-SupRep gene therapy in LQT1 rabbits, these encouraging data should compel continued development of this gene therapy for patients with LQT1.

EEG connectivity and network analyses predict outcome in patients with disorders of consciousness - A systematic review and meta-analysis.

Outcome prediction in prolonged disorders of consciousness (DOC) remains challenging. This can result in either inappropriate withdrawal of treatment or unnecessary prolongation of treatment. Electroencephalography (EEG) is a cheap, portable, and non-invasive device with various opportunities for complex signal analysis. Computational EEG measures, such as EEG connectivity and network metrics, might be ideal candidates for the investigation of DOC, but their capacity in prognostication is still undisclosed. We conducted a meta-analysis aiming to compare the prognostic power of the widely used clinical scale, Coma Recovery Scale-Revised - CRS-R and EEG connectivity and network metrics. We found that the prognostic power of the CRS-R scale was moderate (AUC: 0.67 (0.60-0.75)), but EEG connectivity and network metrics predicted outcome with significantly (p = 0.0071) higher accuracy (AUC:0.78 (0.70-0.86)). We also estimated the prognostic capacity of EEG spectral power, which was not significantly (p = 0.3943) inferior to that of the EEG connectivity and graph-theory measures (AUC:0.75 (0.70-0.80)). Multivariate automated outcome prediction tools seemed to outperform clinical and EEG markers.

Excitation/inhibition imbalance in schizophrenia: a meta-analysis of inhibitory and excitatory TMS-EMG paradigms.

Cortical excitation-inhibition (E/I) imbalance is a potential model for the pathophysiology of schizophrenia. Previous research using transcranial magnetic stimulation (TMS) and electromyography (EMG) has suggested inhibitory deficits in schizophrenia. In this meta-analysis we assessed the reliability and clinical potential of TMS-EMG paradigms in schizophrenia following the methodological recommendations of the PRISMA guideline and the Cochrane Handbook. The search was conducted in three databases in November 2022. Included articles reported Short-Interval Intracortical Inhibition (SICI), Intracortical Facilitation (ICF), Long-Interval Intracortical Inhibition (LICI) and Cortical Silent Period (CSP) in patients with schizophrenia and healthy controls. Meta-analyses were conducted using a random-effects model. Subgroup analysis and meta-regressions were used to assess heterogeneity. Results of 36 studies revealed a robust inhibitory deficit in schizophrenia with a significant decrease in SICI (Cohen's d: 0.62). A trend-level association was found between SICI and antipsychotic medication. Our findings support the E/I imbalance hypothesis in schizophrenia and suggest that SICI may be a potential pathophysiological characteristic of the disorder.

Low Functional network integrity in cognitively unimpaired and MCI subjects with depressive symptoms: results from a multi-center fMRI study.

Evidence suggests that depressive symptomatology is a consequence of network dysfunction rather than lesion pathology. We studied whole-brain functional connectivity using a Minimum Spanning Tree as a graph-theoretical approach. Furthermore, we examined functional connectivity in the Default Mode Network, the Frontolimbic Network (FLN), the Salience Network, and the Cognitive Control Network. All 183 elderly subjects underwent a comprehensive neuropsychological evaluation and a 3 Tesla brain MRI scan. To assess the potential presence of depressive symptoms, the 13-item version of the Beck Depression Inventory (BDI) or the Geriatric Depression Scale (GDS) was utilized. Participants were assigned into three groups based on their cognitive status: amnestic mild cognitive impairment (MCI), non-amnestic MCI, and healthy controls. Regarding affective symptoms, subjects were categorized into depressed and non-depressed groups. An increased mean eccentricity and network diameter were found in patients with depressive symptoms relative to non-depressed ones, and both measures showed correlations with depressive symptom severity. In patients with depressive symptoms, a functional hypoconnectivity was detected between the Anterior Cingulate Cortex (ACC) and the right amygdala in the FLN, which impairment correlated with depressive symptom severity. While no structural difference was found in subjects with depressive symptoms, the volume of the hippocampus and the thickness of the precuneus and the entorhinal cortex were decreased in subjects with MCI, especially in amnestic MCI. The increase in eccentricity and diameter indicates a more path-like functional network configuration that may lead to an impaired functional integration in depression, a possible cause of depressive symptomatology in the elderly.

Study protocol of the Hungarian Longitudinal Study of Healthy Brain Aging (HuBA).

Background and purpose:

Neuro­cog­nitive aging and the associated brain diseases impose a major social and economic burden. Therefore, substantial efforts have been put into revealing the lifestyle, the neurobiological and the genetic underpinnings of healthy neurocognitive aging. However, these studies take place almost exclusively in a limited number of highly-developed countries. Thus, it is an important open question to what extent their findings may generalize to neurocognitive aging in other, not yet investigated regions. The purpose of the Hungarian Longitudinal Study of Healthy Brain Aging (HuBA) is to collect multi-modal longitudinal data on healthy neurocognitive aging to address the data gap in this field in Central and Eastern Europe.

We adapted the Australian Ima­ging, Biomarkers and Lifestyle (AIBL) study of aging study protocol to local circumstances and collected demographic, lifestyle, men­tal and physical health, medication and medical history related information as well as re­cor­ded a series of magnetic resonance imaging (MRI) data. In addition, participants were al­so offered to participate in the collection of blood samples to assess circulating in­flam­matory biomarkers as well as a sleep study aimed at evaluating the general sleep quality based on multi-day collection of subjective sleep questionnaires and whole-night elec­troencephalographic (EEG) data.

Baseline data collection has al­ready been accomplished for more than a hundred participants and data collection in the se­cond
session is on the way. The collected data might reveal specific local trends or could also indicate the generalizability of previous findings. Moreover, as the HuBA protocol al­so offers a sleep study designed for tho­rough characterization of participants’ sleep quality and related factors, our extended multi-modal dataset might provide a base for incorporating these measures into healthy and clinical aging research. 

Besides its straightforward na­tional benefits in terms of health ex­pen­di­ture, we hope that this Hungarian initiative could provide results valid for the whole Cent­ral and Eastern European region and could also promote aging and Alzheimer’s disease research in these countries.

Epilepsy and epileptiform activity in late-onset Alzheimer disease: clinical and pathophysiological advances, gaps and conundrums.

A growing body of evidence has demonstrated a link between Alzheimer disease (AD) and epilepsy. Late-onset epilepsy and epileptiform activity can precede cognitive deterioration in AD by years, and its presence has been shown to predict a faster disease course. In animal models of AD, amyloid and tau pathology are linked to cortical network hyperexcitability that precedes the first signs of memory decline. Thus, detection of epileptiform activity in AD has substantial clinical importance as a potential novel modifiable risk factor for dementia. In this Review, we summarize the epidemiological evidence for the complex bidirectional relationship between AD and epilepsy, examine the effect of epileptiform activity and seizures on cognition in people with AD, and discuss the precision medicine treatment strategies based on the latest research in human and animal models. Finally, we outline some of the unresolved questions of the field that should be addressed by rigorous research, including whether particular clinicopathological subtypes of AD have a stronger association with epilepsy, and the sequence of events between epileptiform activity and amyloid and tau pathology.

Lifestyle and behavioural changes in older adults during the Covid-19 pandemic are associated with subjective cognitive complaints.

Subjective cognitive complaints (SCC) is a self-reported experience of persistently impaired cognitive functions which could be the earliest red flag of neurocognitive disorders. The COVID-19 pandemic and related restriction measures changed the lifestyle and behaviour of older adults. The aim of this study was to assess the relation of these changes and SCC status in Hungary. This cross-sectional study analysed the data of 359 elderly Hungarians who filled out the WW-FINGERS-SARS-CoV2 survey. A quarter of the respondents (n:88) reported SCC in connection with the pandemic. We compared sociodemographic features, health status, lifestyle, and social life parameters between subjects with reported SCC and without. To eliminate the potential interrelation across group differences, stepwise logistic regression was applied. Participants with SCC showed the following characteristics, compared to individuals without: (1) they were older; (2) they were more likely to be women; (3) they had a higher number of chronic disorders; (4) showed more prominent impairment in physical mobility; (5) had worse sleep quality; (6) spent less time with family; and (7) used internet more frequently during the pandemic (all p's < 0.001). Logistic regression highlighted that only two parameters were related to SCC status independently, the physical mobility (ability to walk 500 m without difficulties; OR = 1.186; p < 0.001; 95%CI = 1.101, 1.270) and changes in time spent with grandchildren (OR = 1.04; p = 0.015; 95%CI = 1.008, 1.073). Our study draws attention to the importance of physical mobility and quality time with family as key factors in the cognitive well-being of elderly people.

Effect of postpartum drenching on plasma parameters of cows at a large-scale dairy farm.

The aim of the present study was to explore the influence of postpartum drenching with a feed additive on the plasma concentration of biochemical parameters while factoring in prepartum rumination times (RT). One hundred and sixty-one cows were fitted with a Ruminact© HR-Tag approximately 5 days before calving. Drenching and control groups were established based on calving dates. Animals in the drenched group were treated three times (Day 1/day of calving/, Day 2, and Day 3 postpartum) using a feed additive containing calcium propionate, magnesium sulphate, yeast, potassium chloride and sodium chloride mixed in approximately 25 L of lukewarm tap water. Blood samples were collected on Days 1, 2, 3, 7 and 12. Cows with below the average RT were categorised as "low rumination" and those above it as "high rumination" animals. Drenching decreased the plasma concentrations of total protein, urea and creatinine and increased the levels of alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT) and chloride. Low rumination time prepartum resulted in higher concentrations of beta-hydroxybutyrate, total protein and activities of alkaline phosphatase and GGT, while it decreased the activity of ALT and the concentrations of calcium, magnesium, sodium and potassium. The day of lactation had an effect on all parameters except for potassium.

Ability of ChatGPT to generate competent radiology reports for distal radius fracture by use of RSNA template items and integrated AO classifier.

The amount of acquired radiology imaging studies grows worldwide at a rapid pace. Novel information technology tools for radiologists promise an increase of reporting quality and as well quantity at the same time. Automated text report drafting is one branch of this development. We defined for the present study in total 9 cases of distal radius fracture. Command files structured according to a template of the Radiological Society of North America (RSNA) and to Arbeitsgemeinschaft Osteosynthese (AO) classifiers were given as input to the natural language processing tool ChatGPT. ChatGPT was tasked with drafting an appropriate radiology report. A parameter study (n = 5 iterations) was performed. An overall high appraisal of ChatGPT radiology report quality was obtained in a score card based assessment. ChatGPT demonstrates the capability to adjust output files in response to minor changes in input command files. Existing shortcomings were found in technical terminology and medical interpretation of findings. Text drafting tools might well support work of radiologists in the future. They would allow a radiologist to focus time on the observation of image details and patient pathology. ChatGPT can be considered a substantial step forward towards that aim.

Comparison of the diagnostic accuracy of resting-state fMRI driven machine learning algorithms in the detection of mild cognitive impairment.

Mild cognitive impairment (MCI) is a potential therapeutic window in the prevention of dementia; however, automated detection of early cognitive deterioration is an unresolved issue. The aim of our study was to compare various classification approaches to differentiate MCI patients from healthy controls, based on rs-fMRI data, using machine learning (ML) algorithms. Own dataset (from two centers) and ADNI database were used during the analysis. Three fMRI parameters were applied in five feature selection algorithms: local correlation, intrinsic connectivity, and fractional amplitude of low frequency fluctuations. Support vector machine (SVM) and random forest (RF) methods were applied for classification. We achieved a relatively wide range of 78-87% accuracy for the various feature selection methods with SVM combining the three rs-fMRI parameters. In the ADNI datasets case we can also see even 90% accuracy scores. RF provided a more harmonized result among the feature selection algorithms in both datasets with 80-84% accuracy for our local and 74-82% for the ADNI database. Despite some lower performance metrics of some algorithms, most of the results were positive and could be seen in two unrelated datasets which increase the validity of our methods. Our results highlight the potential of ML-based fMRI applications for automated diagnostic techniques to recognize MCI patients.

[Care of dementia in the general practice]. / A dementia ellátása a háziorvosi gyakorlatban.

Treating and caring for people with dementia is a complex task, which can be achieved through cooperation between primary and specialist healthcare, social care and specialist care services. General practitioners are key players in the prevention, screening, treatment and care of dementia. Our aim was to present the general practitioner's aspects of modern dementia care through different levels of prevention. Educating patients to lead a healthy lifestyle and optimising their cardiovascular status reduces the risk of developing dementia. Emphasis was placed on early screening and referral to a specialist, and the importance of timely, individualised therapy for modern care. General practitioner's care of patients with dementia includes monitoring the progression of the disease as well as co-morbidities so that the quality of life of both the patients and their family can be improved by reducing complications. Family doctors also have an important role to support family members who care for the patient. In addition to presenting the current possibilities in Hungary, we reviewed the international literature and national guidelines, which must be followed continuously to ensure quality patient care. Orv Hetil. 2023; 164(32): 1263-1270.

Stereo-Controlled Liquid Phase Synthesis of Phosphorothioate Oligonucleotides on a Soluble Support.

5'-O-(2-Methoxyisopropyl) (MIP)-protected 2'-deoxynucleosides as chiral P(V)-building blocks, based on the limonene-derived oxathiaphospholane sulfide, were synthesized and used for the assembly of di-, tri-, and tetranucleotide phosphorothioates on a tetrapodal pentaerythritol-derived soluble support. The synthesis cycle consisted of two reactions and two precipitations: (1) the coupling under basic conditions, followed by neutralization and precipitation and (2) an acid catalyzed 5'-O-deacetalization, followed by neutralization and precipitation. The simple P(V) chemistry together with the facile 5'-O-MIP deprotection proved efficient in the liquid phase oligonucleotide synthesis (LPOS). Ammonolysis released nearly homogeneous Rp or Sp phosphorothioate diastereomers in ca. 80% yield/synthesis cycle.

Comparative evaluation of Duragen® and skim milk extenders to enhance ram semen quality and fertility: A promising alternative in ovine artificial insemination.

This study aimed to investigate the effectiveness of Duragen® and skimmed milk (SM) extenders on the quality parameters, bacterial load and fertilization ability of stored ram semen. A total of 50 ejaculates from Sardi rams (n = 5) aged 2.5-3 years, were collected and stored in Duragen® and SM at 15°C. The motilities and velocity parameters generated by the CASA system were then evaluated at 0, 8 and 24 h of storage. Afterward, bacterial loads of sperm extended in Duragen® and SM were determined at 0, 5 and 24 h of incubation. In addition, ewes (n = 100) aged 2 years, have been chosen in the same herd. The selected ewes were then synchronized and inseminated using semen extended in Duragen® and SM and stored for 5 h at 15°C. The results revealed that total and progressive motilities, straight velocity (VSL), straightness (SRT), lateral head displacement (ALH) and beat cross frequency (BCF) were not affected by the extender type after 24 h of storage (p > .05). However, curvilinear velocity (VCL), velocity average path (VAP), linearity (LIN) and wobble (WOB) showed higher values in Duragen® compared with SM extender after 24 h of storage (p < .05). Bacterial loads were observed mainly in sperm stored in SM at 5 h (183 UFC/mL) and at 24 h (357 UFC/mL) of incubation. However, the only case showing a bacterial load in Duragen® is when the storage time attains 24 h (199 UFC/mL). Concerning fertility, sperm diluted in both extenders resulting in high fertility rates which reaches 66% and 73% for Duragen® and SM, respectively, with no statistical difference (p > .05). In summary, Duragen® extender decreased bacterial load in stored semen and maintained high ram sperm quality and fertility. These findings suggest that Duragen® extender could be used as SM alternative in ovine artificial insemination (OAI).

West Nile virus infections in Hungary: Epidemiological update and phylogenetic analysis of the Hungarian virus strains between 2015 and 2022.

Following the introduction of the West Nile virus (WNV) into Hungary in 2004, it has shortly become one of the most important human arbovirus infections, with a gradually increasing number of cases. The study aimed to summarize the current epidemiological situation in Hungary and sequence the WNV PCR-positive clinical specimens and virus isolates by next-generation whole genome sequencing (NGS) to obtain a detailed phylogenetic analysis of the circulating virus strains. Whole blood and urine samples from confirmed WNV-infected patients and WNV isolates were investigated by reverse transcription PCR assays. Genome sequencing was carried out by Sanger-method, followed by NGS on the Illumina MiSeq platform. Altogether 499 human infections were diagnosed between 2004 and 2022. A particularly remarkable increase in human WNV infections was observed in 2018, while the number of reported cases significantly decreased during the COVID-19 pandemic. Between 2015 and 2022, 15 WNV isolates, and 10 PCR-positive clinical specimens were investigated by NGS. Phylogenetic analysis revealed that the major European WNV lineage 2 clades, namely the Eastern European (or Russian) and the Central European (or Hungarian) clades, are presented in Hungary. Strains of the Balkan and other European clusters within the Central European clade are co-circulating in the country, following a characteristic geographical distribution. In Hungary, the presence and co-circulation of multiple lineage 2 WNV strains could be identified in the last few years. Therefore, in light of the 2018 WNV outbreak, sequence-based typing of the currently circulating strains could highly support outbreak investigations.

Deep Learning-Based Prediction of Right Ventricular Ejection Fraction Using 2D Echocardiograms.

BACKGROUND: Evidence has shown the independent prognostic value of right ventricular (RV) function, even in patients with left-sided heart disease. The most widely used imaging technique to measure RV function is echocardiography; however, conventional 2-dimensional (2D) echocardiographic assessment is unable to leverage the same clinical information that 3-dimensional (3D) echocardiography-derived right ventricular ejection fraction (RVEF) can provide. OBJECTIVES: The authors aimed to implement a deep learning (DL)-based tool to estimate RVEF from 2D echocardiographic videos. In addition, they benchmarked the tool's performance against human expert reading and evaluated the prognostic power of the predicted RVEF values. METHODS: The authors retrospectively identified 831 patients with RVEF measured by 3D echocardiography. All 2D apical 4-chamber view echocardiographic videos of these patients were retrieved (n = 3,583), and each subject was assigned to either the training or the internal validation set (80:20 ratio). Using the videos, several spatiotemporal convolutional neural networks were trained to predict RVEF. The 3 best-performing networks were combined into an ensemble model, which was further evaluated in an external data set containing 1,493 videos of 365 patients with a median follow-up time of 1.9 years. RESULTS: The ensemble model predicted RVEF with a mean absolute error of 4.57 percentage points in the internal and 5.54 percentage points in the external validation set. In the latter, the model identified RV dysfunction (defined as RVEF <45%) with an accuracy of 78.4%, which was comparable to an expert reader's visual assessment (77.0%; P = 0.678). The DL-predicted RVEF values were associated with major adverse cardiac events independent of age, sex, and left ventricular systolic function (HR: 0.924 [95% CI: 0.862-0.990]; P = 0.025). CONCLUSIONS: Using 2D echocardiographic videos alone, the proposed DL-based tool can accurately assess RV function, with similar diagnostic and prognostic power as 3D imaging.