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•Cognitive training does not significantly improve objective biomarkers.•Identifying the most accurate measure and the most benefitting age group is crucial.•Proper randomization and less heterogeneity could lead to more convincing results.•Cognitive training’s efficacy shown in neuropsychology is not evident on biomarkers. Cognitive training is a widely recommended technique for cognitive decline and has been shown to improve cognitive functioning. However, the findings on its effect on objective biomarkers of cognitive impairment are highly ambiguous. This study therefore aims to clarify how cognitive training alters brain structure and physiology. A systematic search was conducted in three databases (MEDLINE, Embase, and CENTRAL) for eligible articles in November 2023. The search identified 6.134 articles from which 501 remained after title and abstract selection. Eight articles were identified that assessed the efficacy of cognitive training on objective parameters in non-demented adults. Mean differences (MD) and standardized mean differences (SMD of changes between pre- and post-training data were calculated using random-effects models. 4767 records remained after the removal of duplicates. The selection process ended with 40 eligible articles for qualitative and 8 for quantitative analysis. We did not identify enough articles for the analysis of PET, functional MRI and fluid-based parameters. No significant differences were found in fractional anisotropy (MD=0.01, 95 % Confidence interval (CI): -0.01; 0.04) or in hippocampal volume (SMD=0.03, 95 % CI: -0.01; 0.06). Heterogeneity was high in all analyses. Training groups showed no significant morphological or microstructural modifications compared to control conditions. The current results of objective markers are not powerful enough to recommend cognitive training as a preventive method. Future research should focus on proper randomization, elimination of baseline differences and use standardized techniques. The review was pre-registered with PROSPERO (ID: CRD42023485440).

Preoperative fasting is a worldwide routine even though the most recent Enhanced Recovery After Surgery (ERAS) Guidelines recommend preoperative carbohydrate loading instead of fasting, but with low quality of evidence. Our aim was to compare the effects of preoperative carbohydrate loading to fasting and placebo in patients undergoing elective major non-cardiac surgery under general anaesthesia. Our systematic search was conducted on 15th of October 2021 in five databases, Medline, Embase, Central, Web of Science and Scopus, and updated on November 12th, 2024. We included randomized controlled trials that compared the carbohydrate loading (CHO-group) with fasting or with placebo. Main outcomes were length of hospital stay (LOS), postoperative glucose levels on postoperative, postoperative insulin levels, and C-reactive protein (CRP) levels. Our search revealed 44 eligible articles for data extraction. LOS was shorter in the CHO group as compared to the No-CHO group (MD: − 0.56 [95% CI: − 1.10, − 0.02]). There were no clinically significant differences between the CHO and No-CHO groups regarding the postoperative glucose, insulin and CRP levels. This meta-analysis found that preoperative CHO-loading as compared to preoperative fasting or placebo shortened the length of hospital stay in patients undergoing major elective, non-cardiac surgery. Although several details are still to be unveiled, these data provide further support that preoperative carbohydrate loading could be beneficial in this patient population.

Schizophrenia is a lifelong mental disorder associated with cognitive dysfunctions. Comorbid metabolic dysregulations, such as diabetes and insulin resistance, may further deteriorate cognitive functions. It is therefore essential to investigate the effects of these metabolic disturbances on cognition in this population. A systematic review and meta-analysis following PRISMA guidelines was conducted using data from five databases: Medline, Embase, CENTRAL, Scopus, and Web of science. Of the 26 studies included, 9 were meta-analyzed with random effects model. The search was completed on November 23, 2023 and updated on April 2, 2025. We examined the cognitive functions of schizophrenia patients with and without diabetes or insulin resistance, using standardized mean differences (SMD) or mean differences (MD) as outcomes. The review section provides an overview of the literature on the relationship between glucose homeostasis and cognitive functions. The risk of bias was assessed using the QUIPS tool. There is a clear trend suggesting that diabetes exacerbates cognitive dysfunction in schizophrenia (global cognition: SMD=−0.26; P  = 0.1087; 95% CI, −0.59 to 0.08), particularly in domains such as reasoning (SMD=−0.40; P  = 0.0109, 95% CI −0.58 to -0.22) and processing speed (SMD=−0.43; P  = 0.0005, 95% CI −0.52 to −0.35). Conflicting results were observed in studies on insulin resistance (global cognition: SMD=–0.12; P  = 0.5890; 95% CI −0.91 to 0.68). Our findings suggest that glucose metabolism dysregulations might worsen cognitive dysfunctions in schizophrenia. However, further research is needed with larger samples and less heterogeneous studies to investigate if the effect is statistically significant. Addressing these metabolic issues could help improve cognitive and functional outcomes in schizophrenia patients.

An estimated 70% of critically ill patients receive antibiotics, most frequently beta-lactams. The pharmacokinetic properties of these substances in this patient population are poorly predictable. Therapeutic drug monitoring (TDM) is helpful in making personalized decisions in this field, but its overall impact as a clinical decision-supporting tool is debated. We aimed to evaluate the clinical implications of adjusting beta-lactam dosages based on TDM in the critically ill population by performing a systematic review and meta-analysis of available investigations. Randomized controlled trials and observational studies were retrieved by searching three major databases. The intervention group received TDM-guided beta-lactam treatment, that is, at least one dose reconsideration based on the result of the measurement of drug concentrations, while TDM-unadjusted dosing was employed in the comparison group. The outcomes were evaluated using forest plots with random-effects modeling and subgroup analysis. Eight eligible studies were identified, including 1044 patients in total. TDM-guided beta-lactam treatment was associated with improved clinical cure from infection [odds ratio (OR): 2.22 (95% confidence interval (CI): 1.78–2.76)] and microbiological eradication [OR: 1.72 (CI: 1.05–2.80)], as well as a lower probability of treatment failure [OR: 0.47 (CI: 0.36–0.62)], but the heterogeneity of studies was remarkably high, especially in terms of mortality (70%). The risk of bias was moderate. While the TDM-guided administration of beta-lactams to critically ill patients has a favorable impact, standardized study designs and larger sample sizes are required for developing evidence-based protocols in this field.

Background Inertial measurement units (IMUs) offer a portable, affordable alternative to optical motion capture (OMC) systems for gait analysis. This systematic review and meta-analysis evaluated the concurrent validity of IMUs against gold-standard systems (OMC and force plates) for the lower-limb sagittal plane range of motion (RoM) during walking. We also summarized evidence on estimating vertical and anterior–posterior ground reaction forces (GRFs). Methods PubMed, Embase, Web of Science, and Cochrane Central were searched on December 10, 2023 and updated on August 26, 2025. We included studies of ambulatory human participants where IMUs were compared with optical motion capture or force plates for sagittal plane RoM or on estimating vertical and anterior–posterior GRFs. Both observational and randomized designs were eligible. Two reviewers independently screened, extracted data, and assessed study quality (QUADAS-2). Pooled root mean square error (RMSE) values were calculated using random-effects meta-analysis for RoM and GRFs. Results 27 studies met inclusion criteria; 22 were included in meta-analysis. IMUs showed concurrent validity (RMSE) within the commonly cited threshold ≤ 5° for ankle (RMSE = 4.62°, 95% CI 3.34–5.90) and knee (RMSE = 4.60°, 95% CI 3.60–5.60) sagittal plane RoM, especially during overground walking. Hip concurrent validity was borderline (RMSE = 5.79°, 95% CI 4.39–7.19), with errors amplified on treadmills. Variability (I 2  = 90–96%) reflected differences in hardware, placement, calibration, and processing. Estimates of GRFs, particularly vertical (RMSE = 8.37%BW; 95% CI 5.14–11.61) and anterior–posterior components (RMSE = 5.50%BW; 95% CI 2.90–8.09), were less consistent. Conclusion IMUs provide acceptable concurrent validity (RMSE ≤ 5°) for ankle and knee sagittal plane RoM during walking. Concurrent validity decreases for the hip and treadmill conditions. Standardized calibration, sensor placement, and processing protocols are essential for reliable clinical use, and until further validation, IMUs should be considered complementary rather than stand-alone tools.

COVID-19 is a disease in which early prognosis of severity is critical for desired patient outcomes and for the management of limited resources like intensive care unit beds and ventilation equipment. Many prognostic statistical tools have been developed for the prediction of disease severity, but it is still unclear which ones should be used in practice. We aim to guide clinicians in choosing the best available tools to make optimal decisions and assess their role in resource management and assess what can be learned from the COVID-19 scenario for development of prediction models in similar medical applications. Using the five major medical databases: MEDLINE (via PubMed), Embase, Cochrane Library (CENTRAL), Cochrane COVID-19 Study Register, and Scopus, we conducted a comprehensive systematic review of prediction tools between 2020 January and 2023 April for hospitalized COVID-19 patients. We identified both the relevant confounding factors of tool performance using the MetaForest algorithm and the best tools—comparing linear, machine learning, and deep learning methods—with mixed-effects meta-regression models. The risk of bias was evaluated using the PROBAST tool. Our systematic search identified eligible 27,312 studies, out of which 290 were eligible for data extraction, reporting on 430 independent evaluations of severity prediction tools with ~ 2.8 million patients. Neural Network-based tools have the highest performance with a pooled AUC of 0.893 (0.748–1.000), 0.752 (0.614–0.853) sensitivity, 0.914 (0.849–0.952) specificity, using clinical, laboratory, and imaging data. The relevant confounders of performance are the geographic region of patients, the rate of severe cases, and the use of C-Reactive Protein as input data. 88% of studies have a high risk of bias, mostly because of deficiencies in the data analysis. All investigated tools in use aid decision-making for COVID-19 severity prediction, but Machine Learning tools, specifically Neural Networks clearly outperform other methods, especially in cases when the basic characteristics of severe and non-severe patient groups are similar, and without the need for more data. When highly specific biomarkers are not available—such as in the case of COVID-19—practitioners should abandon general clinical severity scores and turn to disease specific Machine Learning tools.

Volatile organic compounds (VOCs) and essential oils of conifers are widely used in the pharmaceutical industry. This work aimed to analyze the VOCs of 30 conifer species representing the Pinaceae and Cupressaceae families. Samples were collected from arboreta in Hungary, and their chemical composition was determined by gas chromatography (SPME-GC/MS); then, chemometric analyses were performed using multivariate methods to identify characteristic VOCs of conifers. Here, we present results for monoterpene and sesquiterpene profiles of the examined conifer samples. The most abundant compounds detected were α-pinene, bornyl acetate, limonene, β-pinene, β-caryophyllene, β-myrcene, δ-3-carene, and β-phellandrene. The results showed that the following volatiles were characteristic of the conifer groups: sabinene (RRT=6.0) for the cupressoid group (which includes the Cupressaceae species), longifolene (RRT=15.0) and β-pinene (RRT=6.1) were characteristic of the pinoid group (including Picea , Pinus , and Pseudotsuga species), and camphene (RRT=5.5) and bornyl acetate (RRT=12.6) were characteristic of the abietoid group (including Abies , Cedrus , and Tsuga species). Our results on VOCs in the Pinaceae and Cupressaceae families contribute to the elucidation of biodiversity patterns of conifer species and, in addition, may support the industrial application of terpenes.

Background Measurement of beta-amyloid (Aβ) and phosphorylated tau (p-tau) levels offers the potential for early detection of neurocognitive impairment. Still, the probability of developing a clinical syndrome in the presence of these protein changes (A+ and T+) remains unclear. By performing a systematic review and meta-analysis, we investigated the risk of mild cognitive impairment (MCI) or dementia in the non-demented population with A+ and A- alone and in combination with T+ and T- as confirmed by PET or cerebrospinal fluid examination. Methods A systematic search of prospective and retrospective studies investigating the association of Aβ and p-tau with cognitive decline was performed in three databases (MEDLINE via PubMed, EMBASE, and CENTRAL) on January 9, 2024. The risk of bias was assessed using the Cochrane QUIPS tool. Odds ratios (OR) and Hazard Ratios (HR) were pooled using a random-effects model. The effect of neurodegeneration was not studied due to its non-specific nature. Results A total of 18,162 records were found, and at the end of the selection process, data from 36 cohorts were pooled ( n = 7,793). Compared to the unexposed group, the odds ratio (OR) for conversion to dementia in A+ MCI patients was 5.18 [95% CI 3.93; 6.81]. In A+ CU subjects, the OR for conversion to MCI or dementia was 5.79 [95% CI 2.88; 11.64]. Cerebrospinal fluid Aβ42 or Aβ42/40 analysis and amyloid PET imaging showed consistent results. The OR for conversion in A+T+ MCI subjects (11.60 [95% CI 7.96; 16.91]) was significantly higher than in A+T- subjects (2.73 [95% CI 1.65; 4.52]). The OR for A-T+ MCI subjects was non-significant (1.47 [95% CI 0.55; 3.92]). CU subjects with A+T+ status had a significantly higher OR for conversion (13.46 [95% CI 3.69; 49.11]) than A+T- subjects (2.04 [95% CI 0.70; 5.97]). Meta-regression showed that the ORs for Aβ exposure decreased with age in MCI. (beta = -0.04 [95% CI -0.03 to -0.083]). Conclusions Identifying Aβ-positive individuals, irrespective of the measurement technique employed (CSF or PET), enables the detection of the most at-risk population before disease onset, or at least at a mild stage. The inclusion of tau status in addition to Aβ, especially in A+T+ cases, further refines the risk assessment. Notably, the higher odds ratio associated with Aβ decreases with age. Trial registration The study was registered in PROSPERO (ID: CRD42021288100).

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.

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.