Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness of the DROP training for military behavioral health providers targeting therapeutic alliance and premature dropout

Abstract Premature discontinuation from behavioral health treatment is a major problem reducing effectiveness of care in military populations. A training was developed and delivered to 622 behavioral health providers across 15 sites within the Army behavioral healthcare system. The training taught two techniques to foster treatment engagement: (1) Progress Informed Treatment, consisting of reviewing symptom assessments and outcome measures, and (2) assessment and discussion of the treatment alliance via a paper survey given near the end of each session. Eighty-five percent of providers indicated the training was useful and 89% of providers incorporated a technique into their practice. Dropout before the fourth session was significantly reduced in the six months following training, from 72.5% to 67.1% in Service Members (SM; X 2(1, N=9127) = 39.58, p < . 001). In both the pre and post-training periods, providers working at the Master’s level, SM aged 17 or 46 or older, and clients receiving a mood, PTSD, anxiety, adjustment, substance or childhood/adolescent psychiatric diagnosis experienced significantly less dropout, while SM aged 18–21 had significantly more dropout. This training is a feasible and available option to increase treatment engagement and improve treatment outcomes for service members.
Lexicogrammatical skills in 2-year-old children with and without repaired cleft palate

ABSTRACT The purpose of the current research was to compare the lexical–grammatical skills of two-year-old children with and without repaired cleft palate (CP), accounting for the effect of variables such as vocabulary size at 18 months of age, maternal education level, and gender. Participants included 52 children with CP and 25 typically developing (TD) children. The CDI-WS was employed to measure vocabulary and grammatical skills. Significant differences were observed between the CP and TD groups with respect to the number of words, word forms (irregular nouns and verbs), word endings (overuse of plural (-s) and past tense (-ed) markers), the mean number of morphemes in their three longest utterances (M3L), and sentence complexity. In addition, compared to TD children, significantly smaller proportions of children with CP were observed to use words to talk about past and future events or use words to talk about an absent object. The difference between the CP and TD groups in terms of the size of vocabulary at 24 months of age remained statistically significant in the multivariable model. Among all predictors, the size of vocabulary at 18 months of age was identified as the most robust precursor of lexical and grammatical skills at 24 months of age. Gender was identified as a predictor of the M3L measure as an index for syntactic ability.
Spravato oder die Frage: „Wie viel darf ein Antidepressivum kosten?“

pressivum auf den Markt kam. Große Hoffnungen ruhen daher auf (Es)Ketamin. Ketamin – eine aufgrund der Wirkmechanismen pharmakologisch interessante Substanz – konnte seine Wirkung im klinischen Alltag als i. v. Infusion in der Dosierung 0,5mg/kg KG (off-label) wie auch in einer Reihe offener Studien und RCTs zeigen, in Einzelfällen mit oft beeindruckenden Effekten. Die Kosten für eine Ketamin-i. v. -Behandlung inkl. Überwachung lagen bei etwa 200 Euro. Mit Spannung wurde daher die Zulassung von (Es)Ketamin in einer einfacheren Applikationsform erwartet. Diese erfolgte für Esketamin Nasenspray (Spravato) 2019 in den USA und im EWR, seit Frühjahr 2021 ist Spravato nun zum Einsatz im stationären Bereich unter Beachtung besonderer Sicherheitsvorkehrungen verfügbar. Spravato kann auf Antrag des Krankenhauses als sog. „Neue Untersuchungsund Behandlungsmethode“ (NUB) abgerechnet werden – außerbudgetär, zeitlich befristet und fallbezogen/sachgerecht (was letztendlich aber erst in den Verhandlungen der Vertragsparteien vor Ort mit dem Krankenhaus festgelegt wird und somit ein wirtschaftliches Risiko für die Kliniken darstellt). Seit 01.03. 2021 läuft das AMNOG-Verfahren der frühen Nutzungsbewertung, der Beschluss des G-BA soll am 19.08. 2021 erfolgen. Der vom Hersteller aktuell festgesetzte Preis für Spravato in Deutschland: 345 Euro pro Nasenspray (28mg), Mindestabnahme 24 Nasensprays (entsprechend 8280 Euro für 4 Behandlungswochen).
Polycationic adamantane-based dendrons form nanorods in complex with plasmid DNA

Nonviral vectors such as cationic dendrimers and dendrons are demonstrating great properties for their use as gene delivery systems. A good carrier has to efficiently bind and protect the genetic material, but many of the newly developed vectors already fail at this initial step. A continuous and rational design of novel molecular structures is therefore beneficial to this field. Here we report the study of the complexation between different polycationic adamantane-based dendrons, called HYDRAmers, with a model plasmid DNA (pDNA). The role of the dendron generation, the cationic periphery and the functionalization at the focal point on the binding has been thoroughly evaluated. We discovered how appropriate chemical modifications could improve efficiently the complexation to get HYDRAplexes with very good pDNA binding and protecting properties. Despite these favorable characteristics, the unexpected morphology of the complexes forming long nanorods can explain the relatively low transfection performance. Both the reported literature data that guided us for the design of the HYDRAmers and the lessons learned from this work should broadly inform for future development of well-defined gene carriers. Our results also strongly encourage to proceed on the study of the polycationic adamantane-based dendrons for alternative therapies like gene silencing.
Norcantharidin counteracts acquired everolimus resistance in renal cell carcinoma by dual inhibition of mammalian target of rapamycin complex 1 and complex 2 pathways in Vitro

Everolimus, an oral mammalian target of rapamycin complex 1 (mTORC1) inhibitor, presents a therapeutic option in metastatic renal cell carcinoma (RCC) patients who were intolerant to, or previously failed, immune- and vascular endothelial growth factor-targeted therapies. However, the onset of drug resistance limits its clinical use. One possible mechanism underpinning the resistance is that inhibiting mTORC1 by everolimus results in mTORC2-dependent activation of v-Akt murine thymoma viral oncogene (AKT) and upregulation of hypoxia-inducible transcription factors (HIF). Norcantharidin (NCTD) is a demethylated derivative of cantharidin with antitumor properties which is an active ingredient of the traditional Chinese medicine Mylabris. In this study, everolimus-resistant RCC cells (786-O-R) obtained by chronic everolimus treatment revealed higher level of HIF2α and over-activated mTORC2 pathway and NCTD inhibits cell proliferation in both everolimus-resistant and -sensitive RCC cells by arresting cell cycle in G0/G1 phase and reducing cell cycle-related proteins of C-Myc and cyclin D. Furthermore, NCTD shows synergistic anticancer effects combined with everolimus in everolimus-resistant 786-O-R cells. Mechanically, NCTD repressed both mTORC1 and mTORC2 signaling pathways as well as downstream molecular signaling pathways, such as p-4EBP1, p-AKT, HIF1α and HIF2α. Our findings provide sound evidence that combination of NCTD and everolimus is a potential therapeutic strategy for treating RCC and overcoming everolimus resistance by dual inhibition of mTORC1 and mTORC2.
A geometry-guided deep learning technique for CBCT reconstruction

Purpose. Although deep learning (DL) technique has been successfully used for computed tomography (CT) reconstruction, its implementation on cone-beam CT (CBCT) reconstruction is extremely challenging due to memory limitations. In this study, a novel DL technique is developed to resolve the memory issue, and its feasibility is demonstrated for CBCT reconstruction from sparsely sampled projection data. Methods. The novel geometry-guided deep learning (GDL) technique is composed of a GDL reconstruction module and a post-processing module. The GDL reconstruction module learns and performs projection-to-image domain transformation by replacing the traditional single fully connected layer with an array of small fully connected layers in the network architecture based on the projection geometry. The DL post-processing module further improves image quality after reconstruction. We demonstrated the feasibility and advantage of the model by comparing ground truth CBCT with CBCT images reconstructed using (1) GDL reconstruction module only, (2) GDL reconstruction module with DL post-processing module, (3) Feldkamp, Davis, and Kress (FDK) only, (4) FDK with DL post-processing module, (5) ray-tracing only, and (6) ray-tracing with DL post-processing module. The differences are quantified by peak-signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and root-mean-square error (RMSE). Results. CBCT images reconstructed with GDL show improvements in quantitative scores of PSNR, SSIM, and RMSE. Reconstruction time per image for all reconstruction methods are comparable. Compared to current DL methods using large fully connected layers, the estimated memory requirement using GDL is four orders of magnitude less, making DL CBCT reconstruction feasible. Conclusion. With much lower memory requirement compared to other existing networks, the GDL technique is demonstrated to be the first DL technique that can rapidly and accurately reconstruct CBCT images from sparsely sampled data.
Solubility of CaHPO4 · 2H2O and Formation of Ion Pairs in the System Ca(OH)2- H3PO4 - H2O at 37.5 °C.

The solubility isotherm for CaHPO4 · 2H2O (DCPD) in the three-component system Ca(OH)2 - H3PO4 - H2O was determined in the pH range 3.5 to 6.8 by leaching a thermostated column of DCPD with dilute phosphoric acid solutions. In confirmatory experiments, equilibrium was approached both from super- and under-saturation by shaking DCPD with appropriate solutions. The calculated ionic activity product (Ca++) × ( HPO 4 = ), appeared to be a parabolic function of pH with a minimum near pH 5.0. The pH dependence of the ionic product could be accounted for by considering the ion pairs [CaHPO4]° and [CaH2PO4]+ as semi-empirical parameters. Under the condition of saturation with respect to DCPD, the activity of the pair [CaHPO4]° must be a constant. The activity of the species [CaH2PO4]+ was shown to vary directly with hydrogen ion activity. The activities of the two ion pairs were adjusted to give a set of pH-independent ionic activity products with a mean of 2.19±0.011 × 10-7. The stability constants for [CaHPO4]° and [CaH2PO4]+ are 5.88±0.031 × 102 and 7.49 ±0.039, respectively. Experiments were conducted to study the hydrolysis of DCPD to more basic calcium phosphates and the kinetics of these transformations is discussed. The significance of the ion pairs in human serum is considered.
Differences in physical performance between Olympic and non-Olympic female rugby sevens players.

BACKGROUND This study compared the physical performance of National female rugby sevens players selected or not selected to form the Brazilian National Olympic team. METHODS Thirty women rugby sevens players from the Brazilian National team (15 Olympic and 15 non-Olympic) participated in this study. Tests were performed on consecutive days, in the following order: day 1) standing long jump (SLJ); squat and countermovement jumps (SJ and CMJ); and one-repetition maximum test in the bench-press, prone-row, and parallel squat exercises; day 2) 40-m linear sprint; Pro-agility and L-drill change of direction tests; and Yo-Yo intermittent recovery test level 1 (IR1). The differences between groups in all variables examined were analyzed using the independent t test and effect sizes (ES). RESULTS Greater jump performances were noticed for the Olympic players in all jump tests compared to the non-Olympics (ES = 0.95, 1.05, and 0.93, for SLJ, SJ, and CMJ, respectively; P< 0.05). Olympics revealed shorter sprint times than non-Olympics in 40-m distance (ES = 0.88; P< 0.05). Higher one-repetition maximum in the bench-press and Yo-Yo IR1 distance were also observed for the Olympics in comparison to non-Olympic players (ES = 0.65 and 0.93, respectively; P< 0.05). CONCLUSIONS Lower-body power, upper-body strength, maximal sprint velocity and aerobic fitness were found to be important for distinguishing between Olympic and non-Olympic female rugby sevens players. Coaches and practitioners should prioritize the development of these physical qualities in these team-sport athletes.
Predicting miRNA-Disease Associations via Combining Probability Matrix Feature Decomposition With Neighbor Learning

Predicting the associations of miRNAs and diseases may uncover the causation of various diseases. Many methods are emerging to tackle the sparse and unbalanced disease related miRNA prediction. Here, we propose a Probabilistic matrix decomposition combined with neighbor learning to identify MiRNA-Disease Associations utilizing heterogeneous data(PMDA). First, we build similarity networks for diseases and miRNAs, respectively, by integrating semantic information and functional interactions. Second, we construct a neighbor learning model in which the neighbor information of individual miRNA or disease is utilized to enhance the association relationship to tackle the spare problem. Third, we predict the potential association between miRNAs and diseases via probability matrix decomposition. The experimental results show that PMDA is superior to other five methods in sparse and unbalanced data. The case study shows that the new miRNA-disease interactions predicted by the PMDA are effective and the performance of the PMDA is superior to other methods.
Reverse translation approach generates a signature of penetrating fibrosis in Crohn’s disease that is associated with anti-TNF response

Objective Fibrosis is a common feature of Crohn’s disease (CD) which can involve the mesenteric fat. However, the molecular signature of this process remains unclear. Our goal was to define the transcriptional signature of mesenteric fibrosis in CD subjects and to model mesenteric fibrosis in mice to improve our understanding of CD pathogenesis. Design We performed histological and transcriptional analysis of fibrosis in CD samples. We modelled a CD-like fibrosis phenotype by performing repeated colonic biopsies in mice and analysed the model by histology, type I collagen-targeted positron emission tomography (PET) and global gene expression. We generated a gene set list of essential features of mesenteric fibrosis and compared it to mucosal biopsy datasets from inflammatory bowel disease patients to identify a refined gene set that correlated with clinical outcomes. Results Mesenteric fibrosis in CD was interconnected to areas of fibrosis in all layers of the intestine, defined as penetrating fibrosis. We found a transcriptional signature of differentially expressed genes enriched in areas of the mesenteric fat of CD subjects with high levels of fibrosis. Mice subjected to repeated colonic biopsies showed penetrating fibrosis as shown by histology, PET imaging and transcriptional analysis. Finally, we composed a composite 24-gene set list that was linked to inflammatory fibroblasts and correlated with treatment response. Conclusion We linked histopathological and molecular features of CD penetrating fibrosis to a mouse model of repeated biopsy injuries. This experimental system provides an innovative approach for functional investigations of underlying profibrotic mechanisms and therapeutic concepts in CD.
Development of Gas–Liquid Flow Regimes Identification Using a Noninvasive Ultrasonic Sensor, Belt-Shape Features, and Convolutional Neural Network in an S-Shaped Riser

The problem of classifying gas–liquid two-phase flow regimes from ultrasonic signals is considered. A new method, belt-shaped features (BSFs), is proposed for performing feature extraction on the preprocessed data. A convolutional neural network (CNN/ConvNet)-based classifier is then applied to categorize into one of the four flow regimes: 1) annular; 2) churn; 3) slug; or 4) bubbly. The proposed ConvNet classifier includes multiple stages of convolution and pooling layers, which both decrease the dimension and learn the classification features. Using experimental data collected from an industrial-scale multiphase flow facility, the proposed ConvNet classifier achieved 97.40%, 94.57%, and 94.94% accuracy, respectively, for the training set, testing set, and validation set. These results demonstrate the applicability of the BSF features and the ConvNet classifier for flow regime classification in industrial applications.
Good glycemic control at puberty in boys with type 1 diabetes is important for final height

Poor glycemic control in children with type 1 diabetes (T1D) may hinder sexual development and the associated growth spurt. This study aims to identify factors that may affect the timing of puberty, total pubertal growth (TPG), and final height (F‐Ht) in boys with T1D.
The Effects of Continuous Usage of a Diabetes Management App on Glycemic Control in Real-world Clinical Practice: Retrospective Analysis

Background The efficacy of digital technology in improving diabetes management has typically been demonstrated through studies such as randomized controlled trials, which have reported a steeper reduction in hemoglobin A1c (HbA1c) values for patients who adopted a digital solution. However, evidence from real-world clinical practice is still limited. Objective This study aimed to evaluate the effectiveness of digital interventions by tracking HbA1c improvements over 1 year in real-world clinical settings. Methods Patients used the Health2Sync mobile app to track self-measured outcomes and communicate with health care professionals (HCPs). HCPs used the web-based Patient Management Platform to monitor patient data, view test results from clinical laboratories, and communicate with patients. Patients who have been onboarded for at least 13 months and have consecutive HbA1c findings for 5 quarters were included in the analysis. They were then stratified into 3 groups (high, mid, and low retention) based on their level of use of Health2Sync in the first 6 months of onboarding. A mixed model was built to compare the slopes of the rate of reduction in HbA1c among the groups. In addition, these patients’ retention on the app from the seventh to the 12th month was verified through multiple comparisons. Results A sample of 2036 users was included in the analysis. With the mixed model coefficient estimates, we found that app users had significant HbA1c percentage reductions as the passed quarter count increased (t=–9.869; P<.001), and that effectiveness increased in the high (t=–5.173) and mid retention (t=–6.620) groups as the interaction effects were significantly negative compared to that in the low retention group (P<.001) in the passed quarter count. The low retention group also had the highest average HbA1c value at the end of 13 months (high: 7.01%, SD 1.02%; mid: 6.99%, SD 1.00%; low: 7.17%, SD 1.14%) (Bonferroni correction: high vs low, P=.07; mid vs low, P=.02; high vs mid, P>.99). The level of use of the app remained consistent in the seventh to the 12th month after onboarding (high: 5.23 [SD 1.37] months, mid: 2.43 [SD 1.68] months, low: 0.41 [SD 0.97] months) (P<.001). Conclusions Our analysis shows that continuous usage of the diabetes management app is associated with better glycemic control in real-world clinical practice. Further studies are required to reveal the efficacy for specific diabetes types and to observe effects beyond 1 year.
Specific survival nomograms based on SEER database for small intestine adenocarcinoma.

BACKGROUND Small intestine cancers, as an extremely rare tumor type, account only for 3% of all gastrointestinal tumors. Small intestine adenocarcinoma (SIA), representing approximately one-third of all small bowel cancers, has received relatively little attention, both in research efforts and clinical cognizance. Owing to anatomical proximity and rarity, small bowel adenocarcinomas are frequently grouped with colorectal adenocarcinomas. Therefore, a large SIA patient cohort is needed to develop and validate new nomogram prognostic models specific to SIA patients. METHODS Patients diagnosed with SIA between 2004 and 2016 were extracted from the Surveillance, Epidemiology, and Final Results (SEER) database. All patients were randomly assigned to the training cohort and the validation cohort (2:1). The basic clinical information, detailed pathological staging, and treatment information of the patients were included in the analysis. Nomograms were shaped following the evaluations of the Cox regression model and verified using the decision curve analysis (DCA), time-dependent receiver operating characteristic (ROC) curves, concordance index (C-index), and calibration curves. RESULTS The entire group comprised 6,947 patients with small intestine adenocarcinoma. According to the results of the multivariate Cox regression analysis, ten variables, including marital status, age, pathological grade, tumor location, T (tumor), N (nodes), M (metastasis) stage, surgery, chemotherapy, and regional nodes examined (RNE), were independent predictors of both of overall survival (OS) and cancer-specific survival (CSS). All significant variables were used to create the nomograms for OS and CSS. Various methods verified the reliability of the nomograms. The C-indexes of the OS and CSS nomogram were 0.756 (95% CI, 0.748-0.764) and 0.771 (95% CI, 0.761-0.781) in the training cohort and 0.748 (95% CI, 0.736-0.760) and 0.767 (95% CI, 0.752-0.781) in the validation cohort. The calibration curve showed good agreement between the nomogram prediction and actual survival. DCA indicated a clear net benefit of these new forecasting models. CONCLUSIONS This study built and verified nomograms to predict OS and CSS for rare SIA, which appear to be excellent tools to augment the clinically available evidence to facilitate the discussion between SIA patients and clinicians regarding therapeutic choice.
Following Metal-to-Ligand Charge-Transfer Dynamics with Ligand and Spin Specificity Using Femtosecond Resonant Inelastic X-ray Scattering at the Nitrogen K-Edge

We demonstrate for the case of photoexcited [Ru(2,2′-bipyridine)3]2+ how femtosecond resonant inelastic X-ray scattering (RIXS) at the ligand K-edge allows one to uniquely probe changes in the valence electronic structure following a metal-to-ligand charge-transfer (MLCT) excitation. Metal–ligand hybridization is probed by nitrogen-1s resonances providing information on both the electron-accepting ligand in the MLCT state and the hole density of the metal center. By comparing to spectrum calculations based on density functional theory, we are able to distinguish the electronic structure of the electron-accepting ligand and the other ligands and determine a temporal upper limit of (250 ± 40) fs for electron localization following the charge-transfer excitation. The spin of the localized electron is deduced from the selection rules of the RIXS process establishing new experimental capabilities for probing transient charge and spin densities.