Abstract
BACKGROUND
Increasing prevalence of metastatic disease has been accompanied by increasing rates of surgical intervention. Current tools have poor to fair predictive performance for ...intermediate (90-d) and long-term (1-yr) mortality.
OBJECTIVE
To develop predictive algorithms for spinal metastatic disease at these time points and to provide patient-specific explanations of the predictions generated by these algorithms.
METHODS
Retrospective review was conducted at 2 large academic medical centers to identify patients undergoing initial operative management for spinal metastatic disease between January 2000 and December 2016. Five models (penalized logistic regression, random forest, stochastic gradient boosting, neural network, and support vector machine) were developed to predict 90-d and 1-yr mortality.
RESULTS
Overall, 732 patients were identified with 90-d and 1-yr mortality rates of 181 (25.1%) and 385 (54.3%), respectively. The stochastic gradient boosting algorithm had the best performance for 90-d mortality and 1-yr mortality. On global variable importance assessment, albumin, primary tumor histology, and performance status were the 3 most important predictors of 90-d mortality. The final models were incorporated into an open access web application able to provide predictions as well as patient-specific explanations of the results generated by the algorithms. The application can be found at https://sorg-apps.shinyapps.io/spinemetssurvival/
CONCLUSION
Preoperative estimation of 90-d and 1-yr mortality was achieved with assessment of more flexible modeling techniques such as machine learning. Integration of these models into applications and patient-centered explanations of predictions represent opportunities for incorporation into healthcare systems as decision tools in the future.
Abstract
BACKGROUND
Preoperative prognostication of short-term postoperative mortality in patients with spinal metastatic disease can improve shared decision making around end-of-life care.
OBJECTIVE
...To (1) develop machine learning algorithms for prediction of short-term mortality and (2) deploy these models in an open access web application.
METHODS
The American College of Surgeons, National Surgical Quality Improvement Program was used to identify patients that underwent operative intervention for metastatic disease. Four machine learning algorithms were developed, and the algorithm with the best performance across discrimination, calibration, and overall performance was integrated into an open access web application.
RESULTS
The 30-d mortality for the 1790 patients undergoing surgery for spinal metastatic disease was 8.49%. Preoperative factors used for prognostication were albumin, functional status, white blood cell count, hematocrit, alkaline phosphatase, spinal location (cervical, thoracic, lumbosacral), and severity of comorbid systemic disease (American Society of Anesthesiologist Class). In this population, machine learning algorithms developed to predict 30-d mortality performed well on discrimination (c-statistic), calibration (assessed by calibration slope and intercept), Brier score, and decision analysis. An open access web application was developed for the best performing model and this web application can be found here: https://sorg-apps.shinyapps.io/spinemets/.
CONCLUSION
Machine learning algorithms are promising for prediction of postoperative outcomes in spinal oncology and these algorithms can be integrated into clinically useful decision tools. As the volume of data in oncology continues to grow, creation of learning systems and deployment of these systems as accessible tools may significantly enhance prognostication and management.
Abstract
We study the tidal interaction of galaxies in the Eridanus supergroup, using H
i
data from the pre-pilot survey of the Widefield ASKAP
L
-band Legacy All-sky Blind surveY. We obtain optical ...photometric measurements and quantify the strength of tidal perturbation using a tidal parameter
S
sum
. For low-mass galaxies of
M
*
≲ 10
9
M
⊙
, we find a dependence of decreasing H
i
to optical disk size ratio with increasing
S
sum
, but no dependence of H
i
spectral line asymmetry with
S
sum
. This is consistent with the behavior expected under tidal stripping. We confirm that the color profile shape and color gradient depend on the stellar mass, but there is an additional correlation of low-mass galaxies having their color gradients within 2
R
50
increasing with higher
S
sum
. For these low-mass galaxies, the dependence of color gradients on
S
sum
is driven by the color becoming progressively redder in the inner disk when tidal perturbations are stronger. For high-mass galaxies, there is no dependence of color gradients on
S
sum
, and we find a marginal reddening throughout the disks with increasing
S
sum
. Our result highlights tidal interaction as an important environmental effect in producing the faint end of the star formation suppressed sequence in galaxy groups.
Aim
This study aimed to investigate the association between Twitter exposure and the number of citations for coloproctology articles.
Method
Original articles from journals using Twitter between June ...2015 and May 2016 were evaluated for the following characteristics: publishing journal; article subject; study design; nationality, speciality and affiliation of the author(s); and reference on Twitter. Citation data for these articles were retrieved from Google Scholar (https://scholar.google.com) in January 2018. We performed a univariate analysis using these data followed by a multivariate, logistic regression analysis to search for factors associated with a high citation level, which was defined as accrual of more than five citations.
Results
Out of six coloproctology journals listed on the InCites JCR database, three (Diseases of the Colon & Rectum, Colorectal Disease and Techniques in Coloproctology) used Twitter, where 200 (49.5%) out of a total of 404 articles had been featured. Citation rates of articles that featured on Twitter were significantly higher than those that did not (11.4 ± 9.2 vs 4.1 ± 3.1, P < 0.001). In multivariate analysis, Twitter exposure (OR 8.6, P = 0.001), European Union nationality (OR 2.4, P = 0.004), Colorectal Disease journal (OR 3.3, P = 0.005) and systematic review articles (OR 3.4, P = 0.009) were associated with higher citation levels.
Conclusion
Article exposure on Twitter was strongly associated with a high citation level. Medical communities should encourage journals as well as physicians to actively utilize social media to expedite the spread of new ideas and ultimately benefit medical society as a whole.
Aim
Preoperative factors predictive of permanent stoma creation were investigated in a long‐term follow‐up of patients with mid or low rectal cancer.
Method
We included patients who underwent radical ...resection for mid or low rectal cancer with available data for preoperative anal function measured by manometry and Faecal Incontinence Severity Index questionnaire between January 2005 and December 2015 in three tertiary referral hospitals. A permanent stoma was defined as a stoma present until the patient’s last follow‐up visit or death. Preoperative factors that predicted permanent stoma creation were analysed.
Results
Over a median follow‐up of 57.4 months (range 12–143 months), a permanent stoma was created in 144/577 (25.0%) patients, including 89 (15.4%) who underwent abdominoperineal resection, one (0.2%) who underwent Hartmann’s operation without reversal, 15 (2.6%) with a diverting ileostomy at the time of initial sphincter‐preserving surgery without undergoing stoma reversal, and 39 (6.8%) who underwent permanent ileostomy formation after sphincter‐preserving surgery. Patients with permanent stoma creation had a shorter tumour distance from the anal verge (P < 0.001), larger tumour size (P = 0.020) and higher preoperative Faecal Incontinence Severity Index score (P = 0.020). On multivariable analysis, tumour distance from the anal verge predicted permanent stoma formation (relative risk 0.53 per centimetre increase; 95% confidence interval 0.46–0.60; P < 0.001) but preoperative anal function did not.
Conclusion
Tumour distance from the anal verge was the only preoperative determinant of permanent stoma creation in rectal cancer patients. These data may help mid and low rectal cancer patients understand the need for permanent stoma.
Recent studies have suggested potential roles of the microbiome in cervicovaginal diseases. However, there has been no report on the cervical microbiome in cervical intraepithelial neoplasia (CIN). ...We aimed to identify the cervical microbiota of Korean women and assess the association between the cervical microbiota and CIN, and to determine the combined effect of the microbiota and human papillomavirus (HPV) on the risk of CIN. The cervical microbiota of 70 women with CIN and 50 control women was analysed using pyrosequencing based on the 16S rRNA gene. The associations between specific microbial patterns or abundance of specific microbiota and CIN risk were assessed using multivariate logistic regression, and the relative excess risk due to interaction (RERI) and the synergy index (S) were calculated. The phyla Firmicutes, Actinobacteria, Bacteroidetes, Proteobacteria, Tenericutes, Fusobacteria and TM7 were predominant in the microbiota and four distinct community types were observed in all women. A high score of the pattern characterized by predominance of Atopobium vaginae, Gardnerella vaginalis and Lactobacillus iners with a minority of Lactobacillus crispatus had a higher CIN risk (OR 5.80, 95% CI 1.73‒19.4) and abundance of A. vaginae had a higher CIN risk (OR 6.63, 95% CI 1.61‒27.2). The synergistic effect of a high score of this microbial pattern and oncogenic HPV was observed (OR 34.1, 95% CI 4.95‒284.5; RERI/S, 15.9/1.93). A predominance of A. vaginae, G. vaginalis and L. iners with a concomitant paucity of L. crispatus in the cervical microbiota was associated with CIN risk, suggesting that bacterial dysbiosis and its combination with oncogenic HPV may be a risk factor for cervical neoplasia.
A balanced intake of macronutrients-protein, carbohydrate and fat-is essential for the well-being of organisms. An adequate calorific intake but with insufficient protein consumption can lead to ...several ailments, including kwashiorkor
. Taste receptors (T1R1-T1R3)
can detect amino acids in the environment, and cellular sensors (Gcn2 and Tor)
monitor the levels of amino acids in the cell. When deprived of dietary protein, animals select a food source that contains a greater proportion of protein or essential amino acids (EAAs)
. This suggests that food selection is geared towards achieving the target amount of a particular macronutrient with assistance of the EAA-specific hunger-driven response, which is poorly understood. Here we show in Drosophila that a microbiome-gut-brain axis detects a deficit of EAAs and stimulates a compensatory appetite for EAAs. We found that the neuropeptide CNMamide (CNMa)
was highly induced in enterocytes of the anterior midgut during protein deprivation. Silencing of the CNMa-CNMa receptor axis blocked the EAA-specific hunger-driven response in deprived flies. Furthermore, gnotobiotic flies bearing an EAA-producing symbiotic microbiome exhibited a reduced appetite for EAAs. By contrast, gnotobiotic flies with a mutant microbiome that did not produce leucine or other EAAs showed higher expression of CNMa and a greater compensatory appetite for EAAs. We propose that gut enterocytes sense the levels of diet- and microbiome-derived EAAs and communicate the EAA-deprived condition to the brain through CNMa.
Nutrient sensors allow animals to identify foods rich in specific nutrients. The Drosophila nutrient sensor, diuretic hormone 44 (DH44) neurons, helps the fly to detect nutritive sugar. This sensor ...becomes operational during starvation; however, the mechanisms by which DH44 neurons or other nutrient sensors are regulated remain unclear. Here, we identified two satiety signals that inhibit DH44 neurons: (1) Piezo-mediated stomach/crop stretch after food ingestion and (2) Neuromedin/Hugin neurosecretory neurons in the ventral nerve cord (VNC) activated by an increase in the internal glucose level. A subset of Piezo+ neurons that express DH44 neuropeptide project to the crop. We found that DH44 neuronal activity and food intake were stimulated following a knockdown of piezo in DH44 neurons or silencing of Hugin neurons in the VNC, even in fed flies. Together, we propose that these two qualitatively distinct peripheral signals work in concert to regulate the DH44 nutrient sensor during the fed state.
Display omitted
•Drosophila DH44 neurons respond to the nutritional value of sugar only when starved•During the fed state, two peripheral signals inhibit the activity of DH44 neurons•Piezo channels in the crop respond to food-induced mechanical stretch•HuginTS neurons respond to heightened sugar levels in the internal reserve
Oh et al. identified two distinct satiety signals that inhibit the Drosophila nutrient sensor, DH44 neurons, through the gut-brain axis during fed state. Gastric mechanosensation mediated by Piezo channels in the crop and peptidergic sugar-sensing HuginTS neurons in the ventral nerve cord inhibit glucose-induced response of DH44 neurons to suppress sugar overconsumption.
•P-type (Bi,Sb)2Te3 compounds were fabricated with the ball-milled powders.•Finer grain sizes were confirmed in the samples after long milling time.•Thermoelectric properties were largely dependent ...on milling time.•The carrier concentration was changed with the milling time.•ZT=1.14 at 323K was achieved for the samples with the optimized milling time.
P-type (Bi,Sb)2Te3 compounds were fabricated with high energy ball-milled powder and their thermoelectric properties were investigated as a function of the ball milling time. The fine grain sizes were confirmed with the X-ray analysis and the microscopy images in the samples fabricated with powders from long ball milling time. The values of the lattice thermal conductivity of the samples at high temperature show smaller values for long milling time (>24h) than those for short time, resulted from the finer grain sizes of the samples. As well as the microstructural change, the Seebeck coefficient and the electrical resistivity of the compounds were significantly altered with the ball milling time. The carrier concentration was dramatically increased in the samples after 24h milling, which was attributed to the formation of the antisite defects introduced by the accumulated thermal energy. The formation of antisite defects may be also promoted by the unintentional Fe doping from jars and balls. The highest value of ZT=1.14 was achieved at 323K for the samples with 10h. The temperature where the value of ZT was maximized and the values of ZT was varied with the ball milling time, which implies that the ball milling time should be carefully optimized for the suitable application of this compounds.
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