HADS and SOMS-2 brief score evaluation can prevent unnecessary minimal invasive spine interventions - a prospective blinded observational clinical trial.

INTRODUCTION: To test the hypothesis, whether HADS/SOMS is practical in a spine surgery consultation setting and that patients with CLBP, but a high-risk of psychic comorbidities using above screenings will not improve after minimal-invasive spine interventions (MIS). METHODS: n = 150 completed HADS and SOMS prior to the acquisition of history and examination. Primary outcome was improvement by numeric rating scale (NRS), Pain disability index (PDI) and oswestry disability index (ODI) at baseline and 6 months after intervention. In case of sciatica due to disc herniation epidural neurolysis, for facet or SI-joint-syndrome, radiofrequency and for discogenic pain intradiscal electrothermal therapy (IDET) was performed. RESULTS: 6 months after interventions, pat. with a high-risk of anxiety or depression showed no clinically important improvements in NRS, PDI and ODI, whereas in the low-risk group all 3 parameters were significantly reduced. We found a statistically significant difference in the improvement of NRS (p < 0·05), PDI (p < 0·001), ODI (p < 0·001) between high- and low-risk HADS-anxiety and depression groups and in the improvement of NRS and PDI (p < 0·05) between high- and low-risk SOMS-2-subgroups. CONCLUSIONS: In this group of CLBP patients, the easy-to-administer HADS/SOMS reliably predicted outcome after MIS due to the detection of somatoform comorbidities. Thus, 30 out of 150 patients were invasively treated without improvement. This is alarming not only because of unnecessary MIS being performed on these individuals, but also because it represents an inefficient allocation of increasingly limited healthcare funds. LEVEL OF EVIDENCE: II.

Patient-reported bowel and bladder function is not adversely impacted by bariatric surgery.

INTRODUCTION: This study aims to assess the effect of bariatric surgery on patient-reported outcomes of bowel and bladder function. We hypothesized that bariatric surgery does not worsen bowel and bladder function. METHODS AND PROCEDURES: A retrospective review was conducted of a prospectively maintained surgical quality database. We included patients who underwent primary bariatric surgery at a single institution between 2012 and 2020, excluding revisional procedures. Patient-reported outcomes were assessed using Surgical Outcomes Measurement System (SOMS) bowel and bladder function questionnaires at time of pre-operative consult and routine post-operative follow-up visits through 2 years. Data were analyzed using a statistical mixed effects model. RESULTS: 573 patients (80.6% female) were identified with completed SOMS questionnaire data on bowel and bladder function. Of these, 370 (64.6%) underwent gastric bypass, 190 (33.2%) underwent sleeve gastrectomy, and 13 (2.3%) underwent either gastric banding or duodenal switch. Compared to pre-operative baseline scores, patients reported a transient worsening of bowel function at 2-weeks post-op (p = 0.009). However, by 3-months post-op, bowel function improved and was significantly better than baseline (p = 0.006); this improvement was sustained at every point through 2-year follow-up (p = 0.026). Bladder function scores improved immediately at 2-weeks post-op (p = 0.026) and showed sustained improvement through 1-year follow-up. On subgroup analysis, sleeve patients showed greater improvement in bowel function than bypass patients at 1-year (p = 0.031). Multivariable analysis showed significant improvement in bowel function associated with greater total body weight loss (TBWL) (p = 0.002). CONCLUSIONS: Bariatric surgery does not worsen patient-reported bowel or bladder function. In fact, there is overall improvement from pre-operative scores for both bowel and bladder function by 3-months post-op which is sustained through 2-year and 1-year follow-up, respectively. Most encouragingly, a greater TBWL is significantly associated with improved bowel function after bariatric surgery.

Computer-Aided Chemotaxonomy and Bioprospecting Study of Diterpenes of the Lamiaceae Family.

Lamiaceae is one of the largest families of angiosperms and is classified into 12 subfamilies that are composed of 295 genera and 7775 species. It presents a variety of secondary metabolites such as diterpenes that are commonly found in their species, and some of them are known to be chemotaxonomic markers. The aim of this work was to construct a database of diterpenes and to use it to perform a chemotaxonomic analysis among the subfamilies of Lamiaceae, using molecular descriptors and self-organizing maps (SOMs). The 4115 different diterpenes corresponding to 6386 botanical occurrences, which are distributed in eight subfamilies, 66 genera, 639 different species and 4880 geographical locations, were added to SistematX. Molecular descriptors of diterpenes and their respective botanical occurrences were used to generate the SOMs. In all obtained maps, a match rate higher than 80% was observed, demonstrating a separation of the Lamiaceae subfamilies, corroborating with the morphological and molecular data proposed by Li et al. Therefore, through this chemotaxonomic study, we can predict the localization of a diterpene in a subfamily and assist in the search for secondary metabolites with specific structural characteristics, such as compounds with potential biological activity.

Quality of life after laparoscopic totally extraperitoneal repair of an asymptomatic inguinal hernia.

BACKGROUND: When considering an asymptomatic inguinal hernia, surgeons must weigh the risks of watchful waiting against the risk of operative complications. Laparoscopy offers the benefit of reduced postoperative pain, which, for appropriate surgical candidates, may strengthen the case for repair. This study compares general and disease-specific quality of life following totally extraperitoneal (TEP) laparoscopic inguinal hernia repair (LIHR) of asymptomatic and symptomatic hernias. METHODS: We summarize prospective data from 387 patients who underwent TEP LIHR between 2009 and 2015 by four surgeons at a single institution. Asymptomatic individuals were identified by pain scores of zero at preoperative clinic visits. Validated quality of life (QOL) measurements were administered preoperatively and at 3 weeks, 6 months, and 1-year postop. Comparisons were made using Chi-square test, t test, or Mann-Whitney U test. Changes over time were assessed using longitudinal mixed effects models. RESULTS: A cohort of 79 asymptomatic cases were compared to 308 symptomatic individuals. The asymptomatic cohort had larger median hernia defects (2.5 vs 2 cm, p < 0.01), was older (mean 63.0 vs 58.9 years, p = 0.03), included fewer indirect hernias (57.7 vs 74.9%, p < 0.01), took pain medication for fewer days (mean 1.2 ± 1.5 vs 2.2 ± 3.0 days, p = 0.02), returned to baseline activities of daily living earlier (median 3 vs 5 days, p < 0.01), and reported decreased postoperative pain (p = 0.02). There was no significant difference in general QOL. There was one recurrence in the asymptomatic group and were two in the symptomatic cohort. CONCLUSIONS: Asymptomatic individuals undergoing TEP LIHR reported less postoperative pain, returned to baseline activities, and discontinued pain medication sooner than symptomatic patients. These results are encouraging and may inform patient-centered discussions about asymptomatic hernia repair.

Comparative genomics and transcriptomics of Pichia pastoris.

BACKGROUND: Pichia pastoris has emerged as an important alternative host for producing recombinant biopharmaceuticals, owing to its high cultivation density, low host cell protein burden, and the development of strains with humanized glycosylation. Despite its demonstrated utility, relatively little strain engineering has been performed to improve Pichia, due in part to the limited number and inconsistent frameworks of reported genomes and transcriptomes. Furthermore, the co-mingling of genomic, transcriptomic and fermentation data collected about Komagataella pastoris and Komagataella phaffii, the two strains co-branded as Pichia, has generated confusion about host performance for these genetically distinct species. Generation of comparative high-quality genomes and transcriptomes will enable meaningful comparisons between the organisms, and potentially inform distinct biotechnological utilies for each species. RESULTS: Here, we present a comprehensive and standardized comparative analysis of the genomic features of the three most commonly used strains comprising the tradename Pichia: K. pastoris wild-type, K. phaffii wild-type, and K. phaffii GS115. We used a combination of long-read (PacBio) and short-read (Illumina) sequencing technologies to achieve over 1000X coverage of each genome. Construction of individual genomes was then performed using as few as seven individual contigs to create gap-free assemblies. We found substantial syntenic rearrangements between the species and characterized a linear plasmid present in K. phaffii. Comparative analyses between K. phaffii genomes enabled the characterization of the mutational landscape of the GS115 strain. We identified and examined 35 non-synonomous coding mutations present in GS115, many of which are likely to impact strain performance. Additionally, we investigated transcriptomic profiles of gene expression for both species during cultivation on various carbon sources. We observed that the most highly transcribed genes in both organisms were consistently highly expressed in all three carbon sources examined. We also observed selective expression of certain genes in each carbon source, including many sequences not previously reported as promoters for expression of heterologous proteins in yeasts. CONCLUSIONS: Our studies establish a foundation for understanding critical relationships between genome structure, cultivation conditions and gene expression. The resources we report here will inform and facilitate rational, organism-wide strain engineering for improved utility as a host for protein production.

Rapid activity prediction of HIV-1 integrase inhibitors: harnessing docking energetic components for empirical scoring by chemometric and artificial neural network approaches.

Improving performance of scoring functions for drug docking simulations is a challenging task in the modern discovery pipeline. Among various ways to enhance the efficiency of scoring function, tuning of energetic component approach is an attractive option that provides better predictions. Herein we present the first development of rapid and simple tuning models for predicting and scoring inhibitory activity of investigated ligands docked into catalytic core domain structures of HIV-1 integrase (IN) enzyme. We developed the models using all energetic terms obtained from flexible ligand-rigid receptor dockings by AutoDock4, followed by a data analysis using either partial least squares (PLS) or self-organizing maps (SOMs). The models were established using 66 and 64 ligands of mercaptobenzenesulfonamides for the PLS-based and the SOMs-based inhibitory activity predictions, respectively. The models were then evaluated for their predictability quality using closely related test compounds, as well as five different unrelated inhibitor test sets. Weighting constants for each energy term were also optimized, thus customizing the scoring function for this specific target protein. Root-mean-square error (RMSE) values between the predicted and the experimental inhibitory activities were determined to be <1 (i.e. within a magnitude of a single log scale of actual IC50 values). Hence, we propose that, as a pre-functional assay screening step, AutoDock4 docking in combination with these subsequent rapid weighted energy tuning methods via PLS and SOMs analyses is a viable approach to predict the potential inhibitory activity and to discriminate among small drug-like molecules to target a specific protein of interest.

Sunken oil mats: A biomarker-based investigation.

Sunken oil mats (SOMs) pose a significant threat to marine ecosystems, yet their long-term fate and weathering processes remain poorly understood. This study investigates the degradation of biomarkers in a SOM sample collected from the Brazilian coast following the long-lasting 2019 oil spill. The SOM clearly distinguished from spilt oil and were attributed to tanker-washing residues. Analysis of its sections revealed a consistent depletion pattern, associated with losses of volatile and photooxidation-sensitive compounds, even in the most preserved inner fractions, this suggests weathering of the oil prior SOM formation. While biodegradation was minor, photooxidation revealed a significant weathering factor, especially for aromatic compounds as indicated by preferential degradation of highly-alkylated tricyclic aromatic sulfur heterocycles, and specific methylpyrenes and benzofluorenes. This study underscore the complex interplay of weathering processes shaping the fate of SOMs and the importance of biomarker-based diagnosis in assessing the origin and ecological impacts of long-lasting oil spills.

The degenerate coding of psychometric profiles through functional connectivity archetypes.

Introduction: Degeneracy in the brain-behavior code refers to the brain's ability to utilize different neural configurations to support similar functions, reflecting its adaptability and robustness. This study aims to explore degeneracy by investigating the non-linear associations between psychometric profiles and resting-state functional connectivity (RSFC). Methods: The study analyzed RSFC data from 500 subjects to uncover the underlying neural configurations associated with various psychometric outcomes. Self-organized maps (SOM), a type of unsupervised machine learning algorithm, were employed to cluster the RSFC data. And identify distinct archetypal connectivity profiles characterized by unique within- and between-network connectivity patterns. Results: The clustering analysis using SOM revealed several distinct archetypal connectivity profiles within the RSFC data. Each archetype exhibited unique connectivity patterns that correlated with various cognitive, physical, and socioemotional outcomes. Notably, the interaction between different SOM dimensions was significantly associated with specific psychometric profiles. Discussion: This study underscores the complexity of brain-behavior interactions and the brain's capacity for degeneracy, where different neural configurations can lead to similar behavioral outcomes. These findings highlight the existence of multiple brain architectures capable of producing similar behavioral outcomes, illustrating the concept of neural degeneracy, and advance our understanding of neural degeneracy and its implications for cognitive and emotional health.

Representative Residential Property Model-Soft Computing Solution.

Residential properties are a major component of the environment and economy and a key element for the quality of human life. Faced with disruptive ideological and technological changes in the world, real estate analysis has also become a key research problem for many academic centers and private institutions. Due to the complex nature of properties, they are one of the most difficult and troublesome subjects of analysis. Given the rapid advancements in competitive automated analytical models, the problem of data representative sample selection may prove to be a very wide-reaching subject. The aim of this paper was the assessment of the particular soft computing methods' (e.g., Self-Organizing Maps, Rough Set Theory) usefulness for selecting a representative property model. The obtained results confirm that the use of these methods leads to the creation of a model that enables a more reality-based view of the uncertainty and imprecise residential environment.

"Psychological characteristics of functional respiratory disorders in children and adolescents-Pilot study".

BACKGROUND: Aim of our prospective, multicenter, nonrandomized study was to identify characteristic features and similarities of patients with functional respiratory disorders regarding socio-familial and behavioral aspects, in comparison with controls in a cross-sectional analysis using standardized psychological questionnaires. Furthermore, we investigated the longitudinal outcome of symptoms, effects of primary interventions and the stability of psychological traits 6 months after diagnosis and primary intervention. METHODS: Initially, 106 patients (68 females, 27 males) and 58 controls (33 females, 25 males) were recruited for the study. Mean age was 12.6 years in patients and 11.9 years in controls. RESULTS: The child behavior checklist (CBCL) showed significantly increased scores for anxious/depressed (p = 0.002) and schizoid/obsessive (p = 0.001) behavior in patients. A trend was evident for internalizing behavior (p = 0.009) and for a higher total score (p = 0.008). In the self-assessment youth self-report (YSR), there was a trend towards higher values for anxious/depressed behavior in patients (p = 0.06) and towards more externalizing behavior (p = 0.029) in the control group. After 6 months, 31% of the patients were free of symptoms, 42% had improved. For themselves, parents reported a decreased burden from 56% to 23% (p < 0.001) and decreased impairment from 57% to 30% (p < 0.008). For their children, parents reported a decrease from 45% to 16% (p < 0.0001) and from 74% to 37% (p < 0.0001), respectively. A longitudinal comparison from T1 to T2 showed no statistically significant changes in all three psychological questionnaires (CBCL, YSR, and SOMS-KJ). CONCLUSIONS: In summary, we show that patients with functional respiratory disorders differ from healthy subjects, with internalizing behavior being a characteristic trait. The outcome in terms of symptoms, perceived psycho-familial burden and impairment after 6 months is encouraging. However, we are aware that our preliminary data offer thought-provoking impulses rather than firm findings.

ICU admission and mortality classifiers for COVID-19 patients based on subgroups of dynamically associated profiles across multiple timepoints.

The coronavirus disease 2019 (COVID-19) which is caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is consistently causing profound wounds in the global healthcare system due to its increased transmissibility. Currently, there is an urgent unmet need to identify the underlying dynamic associations among COVID-19 patients and distinguish patient subgroups with common clinical profiles towards the development of robust classifiers for ICU admission and mortality. To address this need, we propose a four step pipeline which: (i) enhances the quality of multiple timeseries clinical data through an automated data curation workflow, (ii) deploys Dynamic Bayesian Networks (DBNs) for the detection of features with increased connectivity based on dynamic association analysis across multiple points, (iii) utilizes Self Organizing Maps (SOMs) and trajectory analysis for the early identification of COVID-19 patients with common clinical profiles, and (iv) trains robust multiple additive regression trees (MART) for ICU admission and mortality classification based on the extracted homogeneous clusters, to identify risk factors and biomarkers for disease progression. The contribution of the extracted clusters and the dynamically associated clinical data improved the classification performance for ICU admission to sensitivity 0.83 and specificity 0.83, and for mortality to sensitivity 0.74 and specificity 0.76. Additional information was included to enhance the performance of the classifiers yielding an increase by 4% in sensitivity and specificity for mortality. According to the risk factor analysis, the number of lymphocytes, SatO2, PO2/FiO2, and O2 supply type were highlighted as risk factors for ICU admission and the percentage of neutrophils and lymphocytes, PO2/FiO2, LDH, and ALP for mortality, among others. To our knowledge, this is the first study that combines dynamic modeling with clustering analysis to identify homogeneous groups of COVID-19 patients towards the development of robust classifiers for ICU admission and mortality.

Bio-inspired CO2 reduction reaction catalysis using soft-oxometalates.

The enzyme, Formate Dehydrogenase, is biological catalyst responsible for the hydrogenation of carbon dioxide to formic acid. The present research has discovered CO2 reduction activities and their application using certain metal containing (Mo- or W-)/ NAD + -linked Formate Dehydrogenases. However, the enzyme must be immobilized for easy separation, increased stability and reusability. The shortcomings associated with conventional immobilization method include leaching, mass transfer limitation and low activity. We here present a perspective, wherein, we assess the efficacy of soft-oxometalates and macrocycles as a promising alternative to Formate Dehydrogenase immobilization. The mechanistic pathway and stability of Formate Dehydrogenase from different sources are discussed and compared with their tailored 'chemical counterparts' soft-oxometalates and macrocycles based systems such as {Mo132}, {Mo154}, {MoV9}, Co and Mn based Corroles. The structure, properties and mechanism of CO2 reduction by different Soft-oxometalates and metal based macrocycles were found to be synonymous with that of metal based Formate Dehydrogenase. We comprehensively summarize different reported approaches to valorize CO2 to C1 and C2 products such as photochemical, electrochemical and systems chemistry to showcase our efforts in the ongoing pursuit of CO2 valorization, inspired by the workings of such enzymes, alongside the efforts of several other leading groups. The revelatory insights in the perspective could be used not only for developing bio-inspired CO2 Reduction Reaction but also constructing artificial cell automata for artificial life like system.

A computational workflow for the detection of candidate diagnostic biomarkers of Kawasaki disease using time-series gene expression data.

Unlike autoimmune diseases, there is no known constitutive and disease-defining biomarker for systemic autoinflammatory diseases (SAIDs). Kawasaki disease (KD) is one of the "undiagnosed" types of SAIDs whose pathogenic mechanism and gene mutation still remain unknown. To address this issue, we have developed a sequential computational workflow which clusters KD patients with similar gene expression profiles across the three different KD phases (Acute, Subacute and Convalescent) and utilizes the resulting clustermap to detect prominent genes that can be used as diagnostic biomarkers for KD. Self-Organizing Maps (SOMs) were employed to cluster patients with similar gene expressions across the three phases through inter-phase and intra-phase clustering. Then, false discovery rate (FDR)-based feature selection was applied to detect genes that significantly deviate across the per-phase clusters. Our results revealed five genes as candidate biomarkers for KD diagnosis, namely, the HLA-DQB1, HLA-DRA, ZBTB48, TNFRSF13C, and CASD1. To our knowledge, these five genes are reported for the first time in the literature. The impact of the discovered genes for KD diagnosis against the known ones was demonstrated by training boosting ensembles (AdaBoost and XGBoost) for KD classification on common platform and cross-platform datasets. The classifiers which were trained on the proposed genes from the common platform data yielded an average increase by 4.40% in accuracy, 5.52% in sensitivity, and 3.57% in specificity than the known genes in the Acute and Subacute phases, followed by a notable increase by 2.30% in accuracy, 2.20% in sensitivity, and 4.70% in specificity in the cross-platform analysis.

C*-BODIPYs: Exploring a New Strategy to Transfer Chirality towards BODIPY Chiroptics†.

C*-BODIPYs, that is, boron dipyrromethenes (BODIPYs) which have chiral carbons attached directly to the boron center, are introduced for the first time. These novel chiral BODIPYs mean a new strategy for the chiral perturbation of the inherently achiral BODIPY chromophore that is directed to enable chiroptical properties. Their preparation is very simple and only implies the complexation of a dipyrrin with an enantiopure dialkylborane having boron bonded to chiral carbons.

Summers with low Arctic sea ice linked to persistence of spring atmospheric circulation patterns.

The declining trend of Arctic September sea ice constitutes a significant change in the Arctic climate system. Large year-to-year variations are superimposed on this sea-ice trend, with the largest variability observed in the eastern Arctic Ocean. Knowledge of the processes important for this variability may lead to an improved understanding of seasonal and long-term changes. Previous studies suggest that transport of heat and moisture into the Arctic during spring enhances downward surface longwave radiation, thereby controlling the annual melt onset, setting the stage for the September ice minimum. In agreement with these studies, we find that years with a low September sea-ice concentration (SIC) are characterized by more persistent periods in spring with enhanced energy flux to the surface in forms of net longwave radiation plus turbulent fluxes, compared to years with a high SIC. Two main atmospheric circulation patterns related to these episodes are identified: one resembles the so-called Arctic dipole anomaly that promotes transport of heat and moisture from the North Pacific, whereas the other is characterized by negative geopotential height anomalies over the Arctic, favoring cyclonic flow from Siberia and the Kara Sea into the eastern Arctic Ocean. However, differences between years with low and high September SIC appear not to be due to different spring circulation patterns; instead it is the persistence and intensity of processes associated with these patterns that distinguish the two groups of anomalous years: Years with low September SIC feature episodes that are consistently stronger and more persistent than years with high SIC.

Redox Reaction Triggered Nanomotors Based on Soft-Oxometalates With High and Sustained Motility.

The recent interest in self-propulsion raises an immediate challenge in facile and single-step synthesis of active particles. Here, we address this challenge and synthesize soft oxometalate nanomotors that translate ballistically in water using the energy released in a redox reaction of hydrazine fuel with the soft-oxometalates. Our motors reach a maximum speed of 370 body lengths per second and remain motile over a period of approximately 3 days. We report measurements of the speed of a single motor as a function of the concentration of hydrazine. It is also possible to induce a transition from single-particle translation to collective motility with biomimetic bands simply by tuning the loading of the fuel. We rationalize the results from a physicochemical hydrodynamic theory. Our nanomotors may also be used for transport of catalytic materials in harsh chemical environments that would otherwise passivate the active catalyst.

Psychometric Properties of the Persian Version of Screening for Somatic Symptom Disorders-7(SOMS-7).

Objective: Somatic symptoms are one of the most prevalent complaints in both psychiatric and general population, and validated scales are required to assess these problems. The present study was conducted to determine psychometric properties of the Persian version of Screening for Somatic Symptom Disorders-7(SOMS-7) in an Iranian population. Method : This was a multi centric comprehensive study conducted in Psychosomatic Research Center of Isfahan University of Medical Sciences in collaboration with Department of Clinical Psychology of Philipp University of Marburg, Germany. This part of the study includes 100 patients with anxiety/mood disorders and 291 healthy individuals. All participants completed the Patient Health Questionnaire (PHQ-15) and Screening for Somatic symptom disorders 7(SOMS-7). Data were analyzed by Pearson and Spearman correlation coefficient, factor analysis, independent t test, and discriminant analysis using SPSS-20 software. Results: Reliability coefficient based on Cronbach's alpha was 0.92 and 0.94 (clinical vs. healthy sample). Validity index of the SOMS according to correlation between factor 1 and 2 with PHQ somatic subscale was. 51 and. 59, respectively. Score of 15.5 as cut-off point was accompanied with sensitivity of 77% and specificity of 66%. Factor analysis extracted 2 factors in patients and 4 factors in healthy population. Conclusion: Findings of this study indicated that the Persian version of SOMS-7 has appropriate reliability and validity for the assessment of somatic symptoms disorder and evaluation of treatment effects in these patients.

RD-Metabolizer: an integrated and reaction types extensive approach to predict metabolic sites and metabolites of drug-like molecules.

BACKGROUND: Experimental approaches for determining the metabolic properties of the drug candidates are usually expensive, time-consuming and labor intensive. There is a great deal of interest in developing computational methods to accurately and efficiently predict the metabolic decomposition of drug-like molecules, which can provide decisive support and guidance for experimentalists. RESULTS: Here, we developed an integrated, low false positive and reaction types extensive metabolism prediction approach called RD-Metabolizer (Reaction Database-based Metabolizer). RD-Metabolizer firstly employed the detailed reaction SMARTS patterns to encode different metabolism reaction types with the aim of covering larger chemical reaction space. 2D fingerprint similarity calculation model was built to calculate the metabolic probability of each site in a molecule. RDKit was utilized to act on pre-written reaction SMARTS patterns to correct the metabolic ranking of each site in a molecule generated by the 2D fingerprint similarity calculation model as well as generate corresponding structures of metabolites, thus helping to reduce the false positive metabolites. Two test sets were adopted to evaluate the performance of RD-Metabolizer in predicting SOMs and structures of metabolites. The results indicated that RD-Metabolizer was better than or at least as good as several widely used SOMs prediction methods. Besides, the number of false positive metabolites was obviously reduced compared with MetaPrint2D-React. CONCLUSIONS: The accuracy and efficiency of RD-Metabolizer was further illustrated by a metabolism prediction case of AZD9291, which is a mutant-selective EGFR inhibitor. RD-Metabolizer will serve as a useful toolkit for the early metabolic properties assessment of drug-like molecules at the preclinical stage of drug discovery. Graphical abstract A visual example of the metabolic site and the corresponding metabolite of Chloroquine predicted by RD-Metabolizer.

The German Validation Study of the Surgical Intensive Care Unit Optimal Mobility Score.

PURPOSE: Immobilization of critically ill patients leads to muscle weakness, which translates to increased costs of care and long-term functional disability. We tested the validity of a German Surgical Intensive Care Unit (ICU) Optimal Mobilization Score (SOMS) in 2 different cohorts (neurocritical and nonneurocritical care patients). MATERIALS AND METHODS: Physical therapists estimated the patients' mobilization capacity by using the German version of the SOMS the morning after admission. We tested the prognostic value of the prediction for ICU and hospital length of stay (LOS) as well as for mortality, and built a model to account for other known predictors of these outcomes in the 2 cohorts. RESULTS: A total of 128 patients were included in the analysis, 48 of these were neurocritical care patients. The SOMS predicted mortality and ICU and hospital LOS. Neurocritical care patients stayed significantly longer in the ICU (median 12 vs 4 days, P < .001) and in the hospital (25 vs 17 days, P = .02). The SOMS predicted ICU and hospital LOS. It predicted mortality only in nonneurocritical patients. CONCLUSIONS: The German SOMS assessed by physical therapists on the day after ICU admission predicts ICU and hospital LOS, and mortality. Our data suggest that the association between early mobilization and mortality is more complex in neurocritical care patients.