Miracle-dz/UniFAR-FTUs huggingface dataset:
Combination of Pharmacokinetic and Pathogen Susceptibility Information To Optimize Meropenem Treatment of Gram-Negative Infections in Critically Ill Patients

Meropenem is one of the most frequently used antibiotics to treat life-threatening infections in critically ill patients. This study aimed to develop a meropenem dosing algorithm for the treatment of Gram-negative infections based on intensive care unit (ICU)-specific resistance data. Antimicrobial susceptibility testing of Gram-negative bacteria obtained from critically ill patients was carried out from 2016 to 2020 at a tertiary care hospital. ABSTRACT Meropenem is one of the most frequently used antibiotics to treat life-threatening infections in critically ill patients. This study aimed to develop a meropenem dosing algorithm for the treatment of Gram-negative infections based on intensive care unit (ICU)-specific resistance data. Antimicrobial susceptibility testing of Gram-negative bacteria obtained from critically ill patients was carried out from 2016 to 2020 at a tertiary care hospital. Based on the observed MIC distribution, stochastic simulations (n = 1,000) of an evaluated pharmacokinetic meropenem model, and a defined pharmacokinetic/pharmacodynamic target (100%T>4×MIC while minimum concentrations were <44.5 mg/L), dosing recommendations for patients with varying renal function were derived. Pathogen-specific MIC distributions were used to calculate the cumulative fraction of response (CFR), and the overall MIC distribution was used to calculate the local pathogen-independent mean fraction of response (LPIFR) for the investigated dosing regimens. A CFR/LPIFR of >90% was considered adequate. The observed MIC distribution significantly differed from the EUCAST database. Based on the 6,520 MIC values included, a three-level dosing algorithm was developed. If the pathogen causing the infection is unknown (level 1), known (level 2), known to be neither Pseudomonas aeruginosa nor Acinetobacter baumannii, or classified as susceptible (level 3), a continuous infusion of 1.5 g daily reached sufficient target attainment independent of renal function. In all other cases, dosing needs to be adjusted based on renal function. ICU-specific susceptibility data should be assessed regularly and integrated into dosing decisions. The presented workflow may serve as a blueprint for other antimicrobial settings.
Balancing normalcy and safety: health-related needs in patients with a ventricular assist device within their home environment.

AIMS Ventricular assist device (VAD) implantation has become a well-established treatment strategy for patients suffering from advanced heart failure. Ventricular assist device treatment attempts to ameliorate the symptom burden but may create new challenges in patients' lives. Lacking are insights into perceived challenges and health-related needs of patients with VAD within their home environment. Our study aimed to explore the perceived health-related needs of patients living with a VAD in their home environment. METHODS AND RESULTS We used a qualitative approach based on a hermeneutic, directed content analysis design. Telephone-based interviews were conducted with 10 patients with VAD from a single cardiology centre in Germany. Data collection and analyses were carried out using content-structuring content analyses. Normalcy and safety were identified as overarching themes: participants expressed a need to balance daily activities between striving for normalcy and maintaining safety. Underlying necessities reflecting this balance were categorized as functional, social, and mental health-related needs. Learning by doing, social-, and peer support were described as relevant requisites. Fulfilling these health-related needs could aid patients living with VAD in achieving the sense of normalcy and safety they seek. CONCLUSION Balancing health-related needs with striving for normalcy and safety, emerged as a new core concept for patients with VAD. Thus, being cognizant of this balance when caring for these patients, could facilitate coping after VAD implantation through increasing acceptance of limitations to daily functions by enhancing individual safety. A supportive social environment, including peer support, becomes vital in self-management programs preparing patients with VAD for their home environment.
Neurofilament light chain as a biological marker for amyotrophic lateral sclerosis: a meta-analysis study

Abstract Aim: The aim of the present metanalysis is to evaluate blood and CSF Neurofilament light chain (NfL) concentrations in ALS patients, compared to healthy controls, ALS mimic disorders (ALSmd) and other neurological diseases (OND), and to evaluate their diagnostic yield against ALSmd. Methods: Search engines were systematically investigated for relevant studies. A random effect model was applied to estimate the pooled standard mean difference in NfL levels between ALS and controls and a bivariate mixed-effects model was applied to estimate their diagnostic accuracy on blood and CSF. Results and conclusions: NfL CSF levels were higher in ALS compared with all other control groups. On blood, NfL levels were significantly higher in ALS patients compared with healthy controls and ALSmd. In a subgroup analysis, the use of SIMOA yielded to a better differentiation between ALS and controls on blood, compared with ELISA. Studies performed on CSF (AUC = 0.90) yielded to better diagnostic performances compared with those conducted on blood (AUC = 0.78). Further prospective investigations are needed to determine a diagnostic cutoff, exploitable in clinical practice.
Behavioral and Self-reported Data Collected From Smartphones for the Assessment of Depressive and Manic Symptoms in Patients With Bipolar Disorder: Prospective Observational Study

Background Smartphones allow for real-time monitoring of patients’ behavioral activities in a naturalistic setting. These data are suggested as markers for the mental state of patients with bipolar disorder (BD). Objective We assessed the relations between data collected from smartphones and the clinically rated depressive and manic symptoms together with the corresponding affective states in patients with BD. Methods BDmon, a dedicated mobile app, was developed and installed on patients’ smartphones to automatically collect the statistics about their phone calls and text messages as well as their self-assessments of sleep and mood. The final sample for the numerical analyses consisted of 51 eligible patients who participated in at least two psychiatric assessments and used the BDmon app (mean participation time, 208 [SD 132] days). In total, 196 psychiatric assessments were performed using the Hamilton Depression Rating Scale and the Young Mania Rating Scale. Generalized linear mixed-effects models were applied to quantify the strength of the relation between the daily statistics on the behavioral data collected automatically from smartphones and the affective symptoms and mood states in patients with BD. Results Objective behavioral data collected from smartphones were found to be related with the BD states as follows: (1) depressed patients tended to make phone calls less frequently than euthymic patients (β=−.064, P=.01); (2) the number of incoming answered calls during depression was lower than that during euthymia (β=−.15, P=.01) and, concurrently, missed incoming calls were more frequent and increased as depressive symptoms intensified (β=4.431, P<.001; β=4.861, P<.001, respectively); (3) the fraction of outgoing calls was higher in manic states (β=2.73, P=.03); (4) the fraction of missed calls was higher in manic/mixed states as compared to that in the euthymic state (β=3.53, P=.01) and positively correlated to the severity of symptoms (β=2.991, P=.02); (5) the variability of the duration of the outgoing calls was higher in manic/mixed states (β=.0012, P=.045) and positively correlated to the severity of symptoms (β=.0017, P=.02); and (6) the number and length of the sent text messages was higher in manic/mixed states as compared to that in the euthymic state (β=.031, P=.01; β=.015, P=.01; respectively) and positively correlated to the severity of manic symptoms (β=.116, P<.001; β=.022, P<.001; respectively). We also observed that self-assessment of mood was lower in depressive (β=−1.452, P<.001) and higher in manic states (β=.509, P<.001). Conclusions Smartphone-based behavioral parameters are valid markers for assessing the severity of affective symptoms and discriminating between mood states in patients with BD. This technology opens a way toward early detection of worsening of the mental state and thereby increases the patient’s chance of improving in the course of the illness.
Left ventricular systolic dysfunction predicted by artificial intelligence using the electrocardiogram in Chagas disease patients–The SaMi-Trop cohort

Background Left ventricular systolic dysfunction (LVSD) in Chagas disease (ChD) is relatively common and its treatment using low-cost drugs can improve symptoms and reduce mortality. Recently, an artificial intelligence (AI)-enabled ECG algorithm showed excellent accuracy to detect LVSD in a general population, but its accuracy in ChD has not been tested. Objective To analyze the ability of AI to recognize LVSD in patients with ChD, defined as a left ventricular ejection fraction determined by the Echocardiogram ≤ 40%. Methodology/principal findings This is a cross-sectional study of ECG obtained from a large cohort of patients with ChD named São Paulo-Minas Gerais Tropical Medicine Research Center (SaMi-Trop) Study. The digital ECGs of the participants were submitted to the analysis of the trained machine to detect LVSD. The diagnostic performance of the AI-enabled ECG to detect LVSD was tested using an echocardiogram as the gold standard to detect LVSD, defined as an ejection fraction <40%. The model was enriched with NT-proBNP plasma levels, male sex, and QRS ≥ 120ms. Among the 1,304 participants of this study, 67% were women, median age of 60; there were 93 (7.1%) individuals with LVSD. Most patients had major ECG abnormalities (59.5%). The AI algorithm identified LVSD among ChD patients with an odds ratio of 63.3 (95% CI 32.3–128.9), a sensitivity of 73%, a specificity of 83%, an overall accuracy of 83%, and a negative predictive value of 97%; the AUC was 0.839. The model adjusted for the male sex and QRS ≥ 120ms improved the AUC to 0.859. The model adjusted for the male sex and elevated NT-proBNP had a higher accuracy of 0.89 and an AUC of 0.874. Conclusion The AI analysis of the ECG of Chagas disease patients can be transformed into a powerful tool for the recognition of LVSD.
Radiographic Assessment of the Feline Temporomandibular Joint with Oblique Projections: A Preliminary Ex Vivo Study

Radiographic assessment of the temporomandibular joint in the domestic cat using conventional radiographic views can be challenging due to superimposition of overlying structures and the complex anatomy of the skull. The use of computed tomography, magnetic resonance imaging, and cone beam computed tomography to assess the temporomandibular joint in the cat has increased, but these modalities are not always available in general veterinary practices. Conventional radiography is still commonly used for first line assessment of the temporomandibular joint. The aim of this preliminary study was to determine optimal angle of obliquity of lateroventral-laterodorsal and laterorostral-laterocaudal (nose up lateral oblique) oblique radiographic views in the assessment of the temporomandibular joints in five feline mesaticephalic dry skulls. Visibility of the mandibular head, mandibular fossa, retroarticular process, and temporomandibular joint space were evaluated and scored by two veterinary radiologists. The results of this study identified that the dependent temporomandibular joint anatomy was best seen on the latero-10°-ventral-laterodorsal, latero-15°-ventral-laterodorsal, and latero-20°-ventral-laterodorsal, oblique views, and opposite lateral oblique views at these angulations may be helpful in characterization of this anatomy in clinical patients. The results also indicate that the laterorostral-laterocaudal (nose up lateral oblique) oblique view did not allow adequate discrimination of all TMJ anatomy at any angle, and is not recommended.
The effects of atorvastatin on emotional processing, reward learning, verbal memory and inflammation in healthy volunteers: An experimental medicine study

Background: Growing evidence from clinical trials and epidemiological studies suggests that statins can have clinically significant antidepressant effects, potentially related to anti-inflammatory action on several neurobiological structures. However, the underlying neuropsychological mechanisms of these effects remain unexplored. Aims: In this experimental medicine trial, we investigated the 7-day effects of the lipophilic statin, atorvastatin on a battery of neuropsychological tests and inflammation in healthy volunteers. Methods: Fifty healthy volunteers were randomised to either 7 days of atorvastatin 20 mg or placebo in a double-blind design. Participants were assessed with psychological questionnaires and a battery of well-validated behavioural tasks assessing emotional processing, which is sensitive to putative antidepressant effects, reward learning and verbal memory, as well as the inflammatory marker, C-reactive protein. Results: Compared to placebo, 7-day atorvastatin increased the recognition (p = 0.006), discriminability (p = 0.03) and misclassifications (p = 0.04) of fearful facial expression, independently from subjective states of mood and anxiety, and C-reactive protein levels. Otherwise, atorvastatin did not significantly affect any other psychological and behavioural measure, nor peripheral C-reactive protein. Conclusions: Our results reveal for the first time the early influence of atorvastatin on emotional cognition by increasing the processing of anxiety-related stimuli (i.e. increased recognition, discriminability and misclassifications of fearful facial expression) in healthy volunteers, in the absence of more general effects on negative affective bias. Further studies exploring the effects of statins in depressed patients, especially with raised inflammatory markers, may clarify this finding and inform future clinical trials.
Uniform iron oxide nanoparticles reduce the required amount of polyethylenimine in the gene delivery to mesenchymal stem cells

Cationic polyethylenimine (PEI) is regarded as the ‘golden standard’ of non-viral gene vectors. However, the superiority of PEI with high positive charge density also induces its major drawback of cytotoxicity, which restricts its application for an effective and safe gene delivery to stem cells. To redress this shortcoming, herein, a magnetic gene complex containing uniform iron oxide nanoparticles (UIONPs), plasmid DNA, and free PEI is prepared through electrostatic interactions for the gene delivery to bone marrow-derived mesenchymal stem cells (BM-MSCs). Results show that UIONPs dramatically promote the gene delivery to BM-MSCs using the assistance of magnetic force. In addition, decreasing the free PEI nitrogen to DNA phosphate (N/P) ratio from 10 to 6 has little adverse impact on the transgene expression levels (over 300 times than that of PEI alone at the N/P ratio of 6) and significantly reduces the cytotoxicity to BM-MSCs. Further investigations confirmed that the decrease of free PEI has little influence on the cellular uptake after applying external magnetic forces, but that the reduced positive charge density decreases the cytotoxicity. The present study demonstrates that magnetic gene delivery not only contributes to the enhanced gene expression but also helps to reduce the required amount of PEI, providing a potential strategy for an efficient and safe gene delivery to stem cells.
Aircraft flight parameter estimation using acoustical Lloyd's mirror effect

A model is developed for the acoustical Lloyd's mirror effect observed in the output time-frequency distribution of a microphone located near the ground during the transit of a jet aircraft. The feasibility of using this effect for flight parameter estimation is assessed by a simple Cramer-Rao lower bound analysis. The nonlinear least-squares method and the generalized Hough transform method are formulated for flight parameter estimation. The performances of both methods are evaluated and compared using real acoustic data.
Language Recovery after Brain Injury: A Structural Network Control Theory Study

Aphasia recovery after stroke depends on the condition of the remaining, extralesional brain network. Network control theory (NCT) provides a unique, quantitative approach to assess the interaction between brain networks. In this longitudinal, large-scale, whole-brain connectome study, we evaluated whether controllability measures of language-related regions are associated with treated aphasia recovery. Using probabilistic tractography and controlling for the effects of structural lesions, we reconstructed whole-brain diffusion tensor imaging (DTI) connectomes from 68 individuals (20 female, 48 male) with chronic poststroke aphasia who completed a three-week language therapy. Applying principles of NCT, we computed regional (1) average and (2) modal controllability, which decode the ability of a region to (1) spread control input through the brain network and (2) to facilitate brain state transitions. We tested the relationship between pretreatment controllability measures of 20 language-related left hemisphere regions and improvements in naming six months after language therapy using multiple linear regressions and a parsimonious elastic net regression model with cross-validation. Regional controllability of the inferior frontal gyrus (IFG) pars opercularis, pars orbitalis, and the anterior insula were associated with treatment outcomes independently of baseline aphasia severity, lesion volume, age, education, and network size. Modal controllability of the IFG pars opercularis was the strongest predictor of treated aphasia recovery with cross-validation and outperformed traditional graph theory, lesion load, and demographic measures. Regional NCT measures can reflect the status of the residual language network and its interaction with the remaining brain network, being able to predict language recovery after aphasia treatment. SIGNIFICANCE STATEMENT Predicting and understanding language recovery after brain injury remains a challenging, albeit a fundamental aspect of human neurology and neuroscience. In this study, we applied network control theory (NCT) to fully harness the concept of brain networks as dynamic systems and to evaluate their interaction. We studied 68 stroke survivors with aphasia who underwent imaging and longitudinal behavioral assessments coupled with language therapy. We found that the controllability of the inferior frontal regional network significantly predicted recovery in language production six months after treatment. Importantly, controllability outperformed traditional demographic, lesion, and graph-theoretical measures. Our findings shed light on the neurobiological basis of human language and can be translated into personalized rehabilitation approaches.
"Model-based approaches in biomechanical movements: From the assessment to the interpretation in clinical use."

Introduction Biomechanical models are mainly used to analyse and interpret human movements. Physiological gait can be considered as a 2D movement which is cyclic and highly reproducible. The kinematics can be measured and correlated to the bone-joint and neuromuscular functions. When measuring external forces, the kinetics of the movements can be calculated on the basis of models and visualized (1). In contrast, upper extremity movements are 3D and completely different from being restricted, repeatable or cyclic as compared to gait, and they are more complex since the joints and the multitude of muscles imply a high number of degrees of freedom. Pathological changes induce additional complications in both, gait and upper extremity movements, regarding measurement and interpretation. A proposal for how to proceed in measurements, e. g. where to place the markers and how to calculate joint angles, will be discussed which results in the description of the joint movements of wrist, elbow, shoulder and sterno-clavicular joint (2). Biomechanical analyses in clinical daily routine are subjected to the extreme pressure of time during diagnosis and control of therapeutic progress. The decisions on the degree of pathology and restoration towards physiological ranges are essential but frequently may be based on a restricted accuracy of the analysis. 2. Methods: Upper extremity analysis The analysis of the upper extremities starts on a common methodological platform with gait analysis. A proposal of a marker-based measurement procedure for upper-extremity motions is reported (2,3). The kinematic model describes what is to be measured for the upper extremities based on the rigid segment approach in which each segment is assigned to one bone. By means of rigidly interconnected marker triplets the motions of each segment in all 6 degrees of freedom are assessed based on a 6-camera system. The model is made up of nine segments: the hands, the forearms, the upper-arms, the collarbones and the thorax. The joints in the model (wrist, elbow, shoulder and sterno- clavicular joint) are assumed to be ideal ball-and-socket joints. Additional markers are used to define joint co-ordinate systems which are aligned to the anatomical axes of each joint. These additional markers only used during an extra static trial, because skin
Development of a genome‐wide 200K SNP array and its application for high‐density genetic mapping and origin analysis of Camellia sinensis

Tea is one of the most popular drinks in the world. It is a self-incompatible plant species, and self-incompatibility greatly contributes to its high genetic diversity. Cultivated tea plants mainly include Camellia sinensis var. assamica (CSA) and Camellia sinensis var. sinensis (CSS). The former is characterized by large leaves, cold sensitive phenotype, an arborous or semiarborous habit, whereas CSS has smaller leaves, cold tolerance and a shrub or semishrub growth habit.
A Nonresponse Adjustment Strategy using Modeling in the Canadian Labour Force Survey

Despite good sampling design and surveyors’ best efforts to avoid nonresponse, it is an inevitable part of survey sampling. To offset the effects of nonresponse, reweighting of respondents is done to take into account the nonresponding part of the sample. The current reweighting method in the Canadian Labour Force Survey (LFS) creates nonresponse adjustment classes based on design variables and calculates a nonresponse adjustment factor within each class. Our approach uses logistic regression modeling to form nonresponse adjustment classes (see for reference Little 1986, Eltinge and Yansaneh 1997, and Haziza and al. 2001). We model the sampled dwellings using contact information, such as the number of attempts to contact a sampling unit and time of the attempt, along with the design information. The results show significant improvement over the current method used in the LFS, in terms of several diagnostics. We have also investigated the effect of separately modeling the probability of being contacted and the probability of response given a contact. With this approach, the final response probability is obtained as the product of the probabilities resulting from the two models. We have used different diagnostics to evaluate if this approach performs better than the more traditional one.