Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-treatment regression analysis: the unbalanced case

Under multi-treatment regression analysis, instead of a sample for each treatment of a linear model, there is a linear regression in the same variables. Then, instead of the action of the treatments on the sample mean values, the action on regression coefficients is studied. When data is unbalanced, the regression matrices differs between regressions. This problem is solved through the use of a block-wise diagonal covariance matrix in the ANOVA procedures. The methodology was then applied to data obtained from experiments of electrodialtic removal of 3 heavy metals from contaminated wood. First, polynomial regressions of the 4th and 3rd were fitted to each metal concentration in the electrolytes through time. Then the unbalanced case of multi-treatment regression analysis was applied aiming to choose the best treatment in jointly removing the 3 metals. Results pointed to the choice of treatment 1 as the most efficient.
Experience of the Sudanese doctors in surgery of conjoined twins

Abstract Surgical separation of conjoined twins remains one of the most unique and rewarding experiences in the field of pediatric surgery, bearing in mind that this decision is their best chance of survival. These are the first reported cases of successfully separating omphalopagus conjoined twins by the liver in Sudan. After an emergency cesarean section, 62-day-old term-conjoined twins were referred to our pediatric surgery center. Examination revealed well-appearing twins fused from the xiphoid to the umbilicus; imaging confirmed a fused liver with a separate portal and caval structures, necessitating surgical separation and closure, which was done successfully on subsequent hours with well tolerance and recovery discharged on day 21. The second case involved 21-day-old term-conjoined female twins who were fused from the xiphoid to the umbilicus and shared the same cord, as well as complete fusion of the liver with separate other vital organs. They were successfully separated and recovered well.
Bayesian versus diagnostic information in physician-patient communication: Effects of direction of statistical information and presentation of visualization

Background Communicating well with patients is a competence central to everyday clinical practice, and communicating statistical information, especially in Bayesian reasoning tasks, can be challenging. In Bayesian reasoning tasks, information can be communicated in two different ways (which we call directions of information): The direction of Bayesian information (e.g., proportion of people tested positive among those with the disease) and the direction of diagnostic information (e.g., the proportion of people having the disease among those tested positive). The purpose of this study was to analyze the impact of both the direction of the information presented and whether a visualization (frequency net) is presented with it on patient’s ability to quantify a positive predictive value. Material and methods 109 participants completed four different medical cases (2⨯2⨯4 design) that were presented in a video; a physician communicated frequencies using different directions of information (Bayesian information vs. diagnostic information). In half of the cases for each direction, participants were given a frequency net. After watching the video, participants stated a positive predictive value. Accuracy and speed of response were analyzed. Results Communicating with Bayesian information led to participant performance of only 10% (without frequency net) and 37% (with frequency net) accuracy. The tasks communicated with diagnostic information but without a frequency net were correctly solved by 72% of participants, but accuracy rate decreased to 61% when participants were given a frequency net. Participants with correct responses in the Bayesian information version without visualization took longest to complete the tasks (median of 106 seconds; median of 13.5, 14.0, and 14.5 seconds in other versions). Discussion Communicating with diagnostic information rather than Bayesian information helps patients to understand specific information better and more quickly. Patients’ understanding of the relevance of test results is strongly dependent on the way the information is presented.
Low skeletal muscle mass index and all-cause mortality risk in adults: A systematic review and meta-analysis of prospective cohort studies

Objective The relationship between low skeletal muscle mass index (SMI) and all-cause mortality risk in the general adults remains unclear. Our study was conducted to examine and quantify the associations between low SMI and all-cause mortality risks. Methods PubMed, Web of Science, and Cochrane Library for primary data sources and references to relevant publications retrieved until 1 April 2023. A random-effect model, subgroup analyses, meta-regression, sensitivity analysis, and publication bias were conducted using STATA 16.0. Results Sixteen prospective studies were included in the meta-analysis of low SMI and the risk of all-cause mortality. A total of 11696 deaths were ascertained among 81358 participants during the 3 to 14.4 years follow-up. The pooled RR of all-cause mortality risk was 1.57 (95% CI, 1.25 to 1.96, P < 0.001) across the lowest to the normal muscle mass category. The results of meta-regression showed that BMI (P = 0.086) might be sources of heterogeneity between studies. Subgroup analysis showed that low SMI was significantly associated with an increased risk of all-cause mortality in studies with a body mass index (BMI) between 18.5 to 25 (1.34, 95% CI, 1.24–1.45, P<0.001), 25 to 30 (1.91, 95% CI, 1.16–3.15, P = 0.011), and over 30 (2.58, 95% CI, 1.20–5.54 P = 0.015). Conclusions Low SMI was significantly associated with the increased risk of all-cause mortality, and the risk of all-cause mortality associated with low SMI was higher in adults with a higher BMI. Low SMI Prevention and treatment might be significant for reducing mortality risk and promoting healthy longevity.
Geographical specific association between lifestyles and multimorbidity among adults in China

The relationship between lifestyles and multimorbidity is well established, but previous studies have often neglected the role of spatial heterogeneity. Thus, this study is the first to explore this association in Chinese adults from a spatial perspective using a geographically weighted logistic regression (GWLR) model and describe the geographical characteristics across different regions. According to 2018 China Health and Retirement Longitudinal Study (CHARLS) database, a total of 7101 subjects were finally included, with 124 prefecture-level administrative regions in China. Non-spatial and GWLR model were used for analysis, and gender stratification analysis was also performed. Data were visualized through ArcGIS 10.7. The results showed that a total prevalence of approximately 5.13% of multimorbidity, and among participants with multimorbidity, the separate prevalence of hypertension, diabetes or high blood sugar, heart disease, and stroke were 4.45%, 2.32%, 3.02%, and 1.41%, respectively. The GWLR model indicated that current (OR: 1.202–1.220) and former smokers (OR: 1.168–1.206) may be important risk factors for multimorbidity in adults, especially in north and west among male. Past drinkers (OR: 1.233–1.240), especially in eastern China, contribute to the development of the multimorbidity in men but not in women. Vigorous-intensity activities (OR: 0.761–0.799) were negatively associated with multimorbidity in the west, with no gender difference. Depression (OR: 1.266–1.293) appeared to increase the risk for multimorbidity, with the weakest effects in central China and no gender difference. There was an interaction between light activities and gender (P = 0.024). The prevalence of multimorbidity differed across various areas of the province. The role of geographical variations in lifestyles and multimorbidity may provide valuable information for developing site-specific intervention strategies.
Determinants of joint stiffness and jumping height during drop jump

The present study aimed to examine the effects of muscle‐tendon mechanical properties and electromyographic activity on joint stiffness and jumping height and to explore the determinants of joint stiffness and jumping height. Twenty‐nine males performed unilateral drop jumps at three drop heights (10, 20, and 30 cm) using only the ankle joint on the sledge apparatus. Ankle joint stiffness, jumping height, and electromyographic activity of the plantar flexor muscles were measured during drop jumps. Active muscle stiffness of the medial gastrocnemius muscle was calculated according to changes in the estimated muscle force and fascicle length during fast stretching at five different angular velocities (100, 200, 300, 500, and 600 deg s−1) after submaximal isometric contractions. Tendon stiffness and elastic energy were measured during ramp and ballistic contractions. Active muscle stiffness was significantly correlated with joint stiffness, except for a few conditions. Tendon stiffness measured during ramp and ballistic contractions was not significantly correlated with joint stiffness. The ratios of electromyographic activity before landing and during the eccentric phase to that during the concentric phase were significantly correlated with joint stiffness. In addition, jumping heights at 10 and 20 cm (except for 30 cm) drop heights were strongly associated with the tendon elastic energy, whereas no other measured variables showed significant correlations with jumping heights. These results suggested that (1) joint stiffness is determined by active muscle stiffness and electromyographic activity patterns during jumping, and (2) jumping height is determined by tendon elastic energy.
Genetic control of N-glycosylation of human blood plasma proteins

Glycosylation is an important protein modification, which influences the physical and chemical properties as well as biological function of these proteins. Large-scale population studies have shown that the levels of various plasma protein N-glycans are associated with many multifactorial human diseases. Observed associations between protein glycosylation levels and human diseases have led to the conclusion that N-glycans can be considered a potential source of biomarkers and therapeutic targets. Although biochemical pathways of glycosylation are well studied, the understanding of the mechanisms underlying general and tissue-specific regulation of these biochemical reactions in vivo is limited. This complicates both the interpretation of the observed associations between protein glycosylation levels and human diseases, and the development of glycan-based biomarkers and therapeutics. By the beginning of the 2010s, high-throughput methods of N-glycome profiling had become available, allowing research into the genetic control of N-glycosylation using quantitative genetics methods, including genome-wide association studies (GWAS). Application of these methods has made it possible to find previously unknown regulators of N-glycosylation and expanded the understanding of the role of N-glycans in the control of multifactorial diseases and human complex traits. The present review considers the current knowledge of the genetic control of variability in the levels of N-glycosylation of plasma proteins in human populations. It briefly describes the most popular physical-chemical methods of N-glycome profiling and the databases that contain genes involved in the biosynthesis of N-glycans. It also reviews the results of studies of environmental and genetic factors contributing to the variability of N-glycans as well as the mapping results of the genomic loci of N-glycans by GWAS. The results of functional in vitro and in silico studies are described. The review summarizes the current progress in human glycogenomics and suggests possible directions for further research.
An analysis of Chinese nursing electronic medical records to predict violence in psychiatric inpatients using text mining and machine learning techniques

Background The prevalence of violence in acute psychiatric wards is a critical concern. According to a meta-analysis investigating violence in psychiatric inpatient units, researchers estimated that approximately 17% of inpatients commit one or more acts of violence during their stay. Inpatient violence negatively affects health-care providers and patients and may contribute to high staff turnover. Therefore, predicting which psychiatric inpatients will commit violence is of considerable clinical significance. Objective The present study aimed to estimate the violence rate for psychiatric inpatients and establish a predictive model for violence in psychiatric inpatients. Methods We collected the structured and unstructured data from Chinese nursing electronic medical records (EMRs) for the violence prediction. The data was obtained from the psychiatry department of a regional hospital in southern Taiwan, covering the period between January 2008 and December 2018. Several text mining and machine learning techniques were employed to analyze the data. Results The results demonstrated that the rate of violence in psychiatric inpatients is 19.7%. The patients with violence in psychiatric wards were generally younger, had a more violent history, and were more likely to be unmarried. Furthermore, our study supported the feasibility of predicting aggressive incidents in psychiatric wards by using nursing EMRs and the proposed method can be incorporated into routine clinical practice to enable early prediction of inpatient violence. Conclusions Our findings may provide clinicians with a new basis for judgment of the risk of violence in psychiatric wards.
Fifty-five years in sleep research: contributions, experiences, and progress

© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Submitted for publication: February 10, 2023; Revised: March 10, 2023 Living Legends in Sleep Research
Quantitative intravital imaging for real-time monitoring of pancreatic tumor cell hypoxia and stroma in an orthotopic mouse model

Pancreatic cancer is a lethal disease with few successful treatment options. Recent evidence demonstrates that tumor hypoxia promotes pancreatic tumor invasion, metastasis, and therapy resistance. However, little is known about the complex relationship between hypoxia and the pancreatic tumor microenvironment (TME). In this study, we developed a novel intravital fluorescence microscopy platform with an orthotopic mouse model of pancreatic cancer to study tumor cell hypoxia within the TME in vivo, at cellular resolution, over time. Using a fluorescent BxPC3-DsRed tumor cell line with a hypoxia-response element (HRE)/green fluorescent protein (GFP) reporter, we showed that HRE/GFP is a reliable biomarker of pancreatic tumor hypoxia, responding dynamically and reversibly to changing oxygen concentrations within the TME. We also characterized the spatial relationships between tumor hypoxia, microvasculature, and tumor-associated collagen structures using in vivo second harmonic generation microscopy. This quantitative multimodal imaging platform enables the unprecedented study of hypoxia within the pancreatic TME in vivo.
Isoform specific knockdown of the ETS transcription factor Pointed in Drosophila S2 cells

Alternate splicing of the pointed ( pnt ) gene locus produces two major isoforms, PntP1 and PntP2. Understanding their individual contributions to key developmental processes and identification of their genome-wide transcriptional targets has been hampered by a number of factors including their essential roles during embryonic development, and co-expression in several tissues. siRNAs were designed to target isoform-specific exons that code for the unique N-terminal region of either PntP1 or PntP2. The efficacy and specificity of the siRNAs were examined by co-transfection of isoform specific siRNAs with plasmids encoding epitope tagged PntP1 or PntP2 in Drosophila S2 cells. All P1-specific siRNAs were demonstrated to knockdown PntP1 protein level to greater than 95%, while having nominal impact on PntP2 level. Similarly, PntP2 siRNAs while ineffective at eliminating PntP1, were shown to reduce PntP2 protein level by 87-99%.
Does the Cambridge classification alone predict the possibility to perform echocardiographic examination in lateral recumbency in dogs affected by brachycephalic obstructive airways syndrome?

Objectives To evaluate if the functional grading system (Cambridge classification) of brachycephalic obstructive airways syndrome (BOAS) and the temperament score can be useful tools in predicting the feasibility of echocardiographic examination in lateral recumbency. The hypothesis is that the temperament of the dog, rather than the severity of BOAS alone, can exacerbate respiratory symptoms (dyspnea, stertor, stridor and/or cyanosis) during lateral containment. Methods Prospective cross-sectional study. Twenty-nine French Bulldogs were included and classified according to the Cambridge classification for the BOAS and to the Maddern score for the temperament. Receiver operating characteristic analysis was used to evaluate the sensitivity (Se) and specificity (Sp) of the Cambridge classification, of the temperament score and their sum to predict the feasibility of the echocardiography in lateral recumbency without dyspnea/cyanosis. Results 8 females (27.59%) and 21 (72.41%) males French Bulldogs of 3 years (IQR25-75 1–4), and 12.45 kg (IQR25-7511.5–13.25) were included. The Cambridge classification alone was not predictive for the possibility of performing the echocardiography in lateral recumbency, unlike temperament score and the sum of the two classification indices. The diagnostic accuracy of Cambridge classification (AUC 0.81, Se 50%, Sp 100%), temperament score (AUC 0.73, Se 75%, Sp 69%), and their sum (AUC 0.83, Se 75%, Sp 85%) cut-offs was moderate for each score. Clinical significance The dog’s temperament, and therefore its susceptibility to stress, rather than the severity of BOAS (Cambridge classification) alone, is a good predictor of the possibility of performing the echocardiographic examination in standing instead of lateral recumbency.
Action Planning for Building Program Sustainability: Results from a Group-Randomized Trial

Background: Public health programs are charged with implementing evidence-based interventions to support public health improvement, however, to achieve long term population based benefit these interventions must be sustained. Empirical evidence suggests that program sustainability can be improved through training and technical assistance, but few resources are available to support public health programs in building capacity for sustainability. Methods: This study sought to build capacity for sustainability among state tobacco control programs through a multiyear, group-randomized trial that developed, tested, and evaluated a novel Program Sustainability Action Planning Model and Training Curricula. Using Kolb’s experiential learning theory, we developed this action-oriented training model to address the program-related domains proven to impact capacity for sustainability as outlined in the Program Sustainability Framework. We evaluated the intervention using a longitudinal mixed-effects model using Program Sustainability Assessment (PSAT) scores from three time points. The main predictors in our model included group (control vs intervention) and type of dosage (active and passive). Covariates included state level American Lung Association score (proxy for tobacco control policy environment) and percent of CDC-recommended funding (proxy for program resources). Results: Twenty-three of the 24 state tobacco control programs were included in the analyses: 11 received the training intervention and 12 were control. Results of the longitudinal mixed-effects linear regression model, where the annual PSAT score was the outcome, showed that states in the intervention condition reported significantly higher PSAT scores. The effects for CDC-recommended funding and American Lung Association smoke-free scores (proxy for policy environment) were small but statistically significant. Conclusion: This study found that the Program Sustainability Action Planning Model and Training Curricula was effective in building capacity for sustainability. The training was most beneficial for programs that had made less policy progress than others, implying that tailored training may be most appropriate for programs possibly struggling to make progress. Finally, while funding had a small, statistically significant effect in our model, it virtually made no difference for the average program in our study. This suggests that other factors may be more or equally important as the level of funding a program receives. Trial registration: NCT03598114, Registered on July 26, 2018 (clnicaltrials.gov/NCT03598114)
AKT inhibition interferes with the expression of immune checkpoint proteins and increases NK-induced killing of HL60-AML cells

ABSTRACT Objective To determine the role of the AKT pathway in the regulating of natural Killer-induced apoptosis of acute myeloid leukemia cells and to characterize the associated molecular mechanisms. Methods BALB/c nude mice were injected with HL60 cells to induce a xenogenic model of subcutaneous leukemic tumors. Mice were treated with perifosine, and their spleens were analyzed using biometry, histopathology, and immunohistochemistry. Gene expression analysis in leukemia cells was performed by real-time PCR. Protein analysis of leukemia and natural Killer cells was performed by flow cytometry. AKT inhibition in HL60 cells, followed by co-culture with natural Killer cells was performed to assess cytotoxicity. Apoptosis rate was quantified using flow cytometry. Results Perifosine treatment caused a reduction in leukemic infiltration in the spleens of BALB/c nude mice. In vitro , AKT inhibition reduced HL60 resistance to natural Killer-induced apoptosis. AKT inhibition suppressed the immune checkpoint proteins PD-L1, galectin-9, and CD122 in HL60 cells, but did not change the expression of their co-receptors PD1, Tim3, and CD96 on the natural Killer cell surface. In addition, the death receptors DR4, TNFR1, and FAS were overexpressed by AKT inhibition, thus increasing the susceptibility of HL60 cells to the extrinsic pathway of apoptosis. Conclusion The AKT pathway is involved in resistance to natural Killer-induced apoptosis in HL60 cells by regulating the expression of immune suppressor receptors. These findings highlight the importance of AKT in contributing to immune evasion mechanisms in acute myeloid leukemia and suggests the potential of AKT inhibition as an adjunct to immunotherapy.