Functional Outcomes After Transanal Total Mesorectal Excision (taTME) for Rectal Cancer: Results from the Phase II North American Multicenter Prospective Observational Trial.

OBJECTIVE: To investigate fecal incontinence and defecatory, urinary, and sexual functional outcomes after taTME. SUMMARY BACKGROUND DATA: Proctectomy for rectal cancer may result in alterations in defecatory, urinary, and sexual function that persist beyond 12 months. The recent multicenter Phase II taTME trial demonstrated the safety of taTME in patients with stage I-III tumors. METHODS: Prospectively registered self-reported questionnaires were collected from 100 taTME patients. Fecal continence (FIQL, Wexner), defecatory function (COREFO), urinary function (IPSS), and sexual function (FSFI-female, IIEF-male) were assessed preoperatively (PQ), 3-4 months post-ileostomy closure (FQ1), and 12-18 months post-taTME (FQ2). RESULTS: Among 83 patients who responded at all three time points, FIQL, Wexner, and COREFO significantly worsened post-ileostomy closure. Between FQ1 and FQ2, FIQL lifestyle and coping, Wexner, and COREFO incontinence, social impact, frequency, and need for medication significantly improved, while FIQL depression and embarrassment did not change. IPSS did not change relative to preoperative scores. For females, FSFI declined for desire, orgasm, and satisfaction between PQ and FQ1, and did not improve between FQ1 and FQ2. In males, IIEF declined with no change between FQ1 and FQ2. CONCLUSIONS: Although taTME resulted in initial decline in defecatory function and fecal continence, most functional domains improved by 12 months after ileostomy closure, without returning to preoperative status. Urinary function was preserved while sexual function declined without improvement by 18 months post-taTME. Our results address patient expectations and inform shared decision-making regarding taTME.

Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial.

OBJECTIVES: Machine learning algorithms can outperform older methods in predicting clinical deterioration, but rigorous prospective data on their real-world efficacy are limited. We hypothesized that real-time machine learning generated alerts sent directly to front-line providers would reduce escalations. DESIGN: Single-center prospective pragmatic nonrandomized clustered clinical trial. SETTING: Academic tertiary care medical center. PATIENTS: Adult patients admitted to four medical-surgical units. Assignment to intervention or control arms was determined by initial unit admission. INTERVENTIONS: Real-time alerts stratified according to predicted likelihood of deterioration sent either to the primary team or directly to the rapid response team (RRT). Clinical care and interventions were at the providers' discretion. For the control units, alerts were generated but not sent, and standard RRT activation criteria were used. MEASUREMENTS AND MAIN RESULTS: The primary outcome was the rate of escalation per 1000 patient bed days. Secondary outcomes included the frequency of orders for fluids, medications, and diagnostic tests, and combined in-hospital and 30-day mortality. Propensity score modeling with stabilized inverse probability of treatment weight (IPTW) was used to account for differences between groups. Data from 2740 patients enrolled between July 2019 and March 2020 were analyzed (1488 intervention, 1252 control). Average age was 66.3 years and 1428 participants (52%) were female. The rate of escalation was 12.3 vs. 11.3 per 1000 patient bed days (difference, 1.0; 95% CI, -2.8 to 4.7) and IPTW adjusted incidence rate ratio 1.43 (95% CI, 1.16-1.78; p < 0.001). Patients in the intervention group were more likely to receive cardiovascular medication orders (16.1% vs. 11.3%; 4.7%; 95% CI, 2.1-7.4%) and IPTW adjusted relative risk (RR) (1.74; 95% CI, 1.39-2.18; p < 0.001). Combined in-hospital and 30-day-mortality was lower in the intervention group (7% vs. 9.3%; -2.4%; 95% CI, -4.5% to -0.2%) and IPTW adjusted RR (0.76; 95% CI, 0.58-0.99; p = 0.045). CONCLUSIONS: Real-time machine learning alerts do not reduce the rate of escalation but may reduce mortality.

Malnutrition risk assessment using a machine learning-based screening tool: A multicentre retrospective cohort.

BACKGROUND: Malnutrition is associated with increased morbidity, mortality, and healthcare costs. Early detection is important for timely intervention. This paper assesses the ability of a machine learning screening tool (MUST-Plus) implemented in registered dietitian (RD) workflow to identify malnourished patients early in the hospital stay and to improve the diagnosis and documentation rate of malnutrition. METHODS: This retrospective cohort study was conducted in a large, urban health system in New York City comprising six hospitals serving a diverse patient population. The study included all patients aged ≥ 18 years, who were not admitted for COVID-19 and had a length of stay of ≤ 30 days. RESULTS: Of the 7736 hospitalisations that met the inclusion criteria, 1947 (25.2%) were identified as being malnourished by MUST-Plus-assisted RD evaluations. The lag between admission and diagnosis improved with MUST-Plus implementation. The usability of the tool output by RDs exceeded 90%, showing good acceptance by users. When compared pre-/post-implementation, the rate of both diagnoses and documentation of malnutrition showed improvement. CONCLUSION: MUST-Plus, a machine learning-based screening tool, shows great promise as a malnutrition screening tool for hospitalised patients when used in conjunction with adequate RD staffing and training about the tool. It performed well across multiple measures and settings. Other health systems can use their electronic health record data to develop, test and implement similar machine learning-based processes to improve malnutrition screening and facilitate timely intervention.

MUST-Plus: A Machine Learning Classifier That Improves Malnutrition Screening in Acute Care Facilities.

OBJECTIVE: Malnutrition among hospital patients, a frequent, yet under-diagnosed problem is associated with adverse impact on patient outcome and health care costs. Development of highly accurate malnutrition screening tools is, therefore, essential for its timely detection, for providing nutritional care, and for addressing the concerns related to the suboptimal predictive value of the conventional screening tools, such as the Malnutrition Universal Screening Tool (MUST). We aimed to develop a machine learning (ML) based classifier (MUST-Plus) for more accurate prediction of malnutrition. METHOD: A retrospective cohort with inpatient data consisting of anthropometric, lab biochemistry, clinical data, and demographics from adult (≥ 18 years) admissions at a large tertiary health care system between January 2017 and July 2018 was used. The registered dietitian (RD) nutritional assessments were used as the gold standard outcome label. The cohort was randomly split (70:30) into training and test sets. A random forest model was trained using 10-fold cross-validation on training set, and its predictive performance on test set was compared to MUST. RESULTS: In all, 13.3% of admissions were associated with malnutrition in the test cohort. MUST-Plus provided 73.07% (95% confidence interval [CI]: 69.61%-76.33%) sensitivity, 76.89% (95% CI: 75.64%-78.11%) specificity, and 83.5% (95% CI: 82.0%-85.0%) area under the receiver operating curve (AUC). Compared to classic MUST, MUST-Plus demonstrated 30% higher sensitivity, 6% higher specificity, and 17% increased AUC. CONCLUSIONS: ML-based MUST-Plus provided superior performance in identifying malnutrition compared to the classic MUST. The tool can be used for improving the operational efficiency of RDs by timely referrals of high-risk patients.

[Experimental study on improvement of alcoholic liver disease by polysaccharides from Balanophora henryi through targeting miR-122a].

The aim of this paper was to investigate the effect of total polysaccharide from Balanophora henryi(TBP) on alcoholic liver disease(ALD) and explore the possible mechanism. C57 BL/6 N mice were randomly divided into 4 groups: pair-feeding group, alcohol-feeding model group, model+TBP group and TBP drug control group. The Gao-binge method was used to prepare the chronic ALD model, and at the same time, 400 mg·kg~(-1) TBP was given for interventional therapy. After feeding for 6 weeks, the serum, liver and colon tissues were collected for detection. As compared with the pair-feeding group, the model group mice showed obvious fatty degeneration and a large number of infiltration of inflammatory cells in the liver, with increased serum ALT and AST levels. After TBP intervention, histopathological changes in liver tissues were significantly improved, with decreased lipid deposition, closer arrangement of hepatocytes, lower expression level of inflammatory factors, and reduced activity of serum ALT and AST, indicating that TBP had a significant improvement effect on ALD. The observation of colonic tissues in mice showed that TBP effectively maintained the integrity of intestinal tissue structure of mice with ALD, enhanced the expression of tight junction protein occludin and reduced miR-122 a expression level. More importantly, TBP significantly reduced serum lipopolysaccharide(LPS) level in model mice. These results indicated that TBP may improve ALD by maintaining and enhancing intestinal barrier function. In vitro experiments showed that TBP significantly inhibited the expression level of miR-122 a in Caco-2 cells exposed to ethanol. Overexpression of miR-122 a in Caco-2 cells induced the inhibition of occludin protein production, and the addition of TBP significantly interfered with the effect. These results suggested that TBP could improve ALD by maintaining the stability of intestinal barrier function and reducing LPS content into the liver, and the mechanism may be partially related to inhibiting miR-122 a expression.

An Open Dataset of Annotated Metaphase Cell Images for Chromosome Identification.

Chromosomes are a principal target of clinical cytogenetic studies. While chromosomal analysis is an integral part of prenatal care, the conventional manual identification of chromosomes in images is time-consuming and costly. This study developed a chromosome detector that uses deep learning and that achieved an accuracy of 98.88% in chromosomal identification. Specifically, we compiled and made available a large and publicly accessible database containing chromosome images and annotations for training chromosome detectors. The database contains five thousand 24 chromosome class annotations and 2,000 single chromosome annotations. This database also contains examples of chromosome variations. Our database provides a reference for researchers in this field and may help expedite the development of clinical applications.

Anti-fatigue activity of dripped spent hens chicken essence in ICR mice.

OBJECTIVE: Chicken essence and branched chain amino acid (BCAA) supplementation has been recognized to significantly relieve fatigue. To obtain chicken essence with high amounts of BCAA, spent hens herein was used to prepare dripped chicken essence (SCE) and compared with commercial dripped chicken essence (CCE) for in vivo anti-fatigue effect. METHODS: To determine the effect on anti-fatigue by dripped chicken essence, the exhaustive swimming was performed. Thirty-two 7-week ICR mice were divided into four groups, which included the control group (CG), CCE, SCE-1X and SCE-2X. The mice were given daily oral administration (0.012 mL/g body weight/d). The fatigue index analysis was conducted weekly. RESULTS: The results showed that SCE had a higher BCAA level as expected, and mice treated with dripped chicken essence (CCE and SCE) could significantly improve exercise performance. The lower blood lactate level, blood urea nitrogen level and creatine phosphokinase activity were found in the supplement of SCE group compared with the CCE group, which suggested that the SCE possessed strong anti-fatigue ability. This could possibly be due to the higher content of BCAA. CONCLUSION: In this study, SCE promoted recovery from physical fatigue in mice and elevated endurance ability. Among them, the double dose (SCE-2X) showed the strongest anti-fatigue ability. Taken together, spent chickens could be a good source of chicken essence to improve the effect of anti-fatigue.

A comparative study of acute heat tolerance and meat quality in three chicken breeds.

In order to breed a strain that has heat tolerance and meat productivity, the commercial red-feathered Taiwan native chickens were male (F group), and heat stress resistant strain Taiwan native chickens (Taishu-9, bred by the Taiwan Livestock Research Institute) were female (TR9 group) to hybridize to generate offspring (F9 group). Three breeds of birds (male) were conducted to compare acute heat stress and meat quality. At 12 weeks of age, TR9 group showed the significantly lowest activity of plasma creatine kinase upon acute heat stress which indicated heat stress resistant in TR9 group as expected. In addition, only limited thermoregulation was obtained in F9 group, while F group exhibited almost no acute heat stress tolerance ability. After slaughtered at 16 weeks of age, the F group revealed poor meat quality in breast meat as pale, soft, and exudative (PSE)-like muscle samples according to CIE L* and pH value. The F9 group was an offspring of TR9 group with heat tolerance, but it only demonstrated limitation of heat resistance. However, the improve meat quality was obtained in F9 group compared to F group, and that may be contributed from better anti-stress as like as TR9 group during slaughtering process.

Using Machine Learning to Predict ICU Transfer in Hospitalized COVID-19 Patients.

OBJECTIVES: Approximately 20-30% of patients with COVID-19 require hospitalization, and 5-12% may require critical care in an intensive care unit (ICU). A rapid surge in cases of severe COVID-19 will lead to a corresponding surge in demand for ICU care. Because of constraints on resources, frontline healthcare workers may be unable to provide the frequent monitoring and assessment required for all patients at high risk of clinical deterioration. We developed a machine learning-based risk prioritization tool that predicts ICU transfer within 24 h, seeking to facilitate efficient use of care providers' efforts and help hospitals plan their flow of operations. METHODS: A retrospective cohort was comprised of non-ICU COVID-19 admissions at a large acute care health system between 26 February and 18 April 2020. Time series data, including vital signs, nursing assessments, laboratory data, and electrocardiograms, were used as input variables for training a random forest (RF) model. The cohort was randomly split (70:30) into training and test sets. The RF model was trained using 10-fold cross-validation on the training set, and its predictive performance on the test set was then evaluated. RESULTS: The cohort consisted of 1987 unique patients diagnosed with COVID-19 and admitted to non-ICU units of the hospital. The median time to ICU transfer was 2.45 days from the time of admission. Compared to actual admissions, the tool had 72.8% (95% CI: 63.2-81.1%) sensitivity, 76.3% (95% CI: 74.7-77.9%) specificity, 76.2% (95% CI: 74.6-77.7%) accuracy, and 79.9% (95% CI: 75.2-84.6%) area under the receiver operating characteristics curve. CONCLUSIONS: A ML-based prediction model can be used as a screening tool to identify patients at risk of imminent ICU transfer within 24 h. This tool could improve the management of hospital resources and patient-throughput planning, thus delivering more effective care to patients hospitalized with COVID-19.

Effects of porcine brain hydrolysate on impairment of cognitive learning ability in amyloid ß(1-40) -infused rats.

This study assessed whether administering porcine brain hydrolysate (PBH) ameliorates the impairment of spatial cognition learning ability in amyloid ß (Aß)-infused rats. PBH was prepared using organic solvents (i.e., acetone and ethanol). Enzyme hydrolysates were derived from these PBH and the sequence of the Aß peptide for infusion was selected. The results indicated the PBH, in particular EP (porcine brain extract with ethanol and protease N), demonstrated the potentials to reduce damage of neurodegenerative disorders in vitro and in vivo. The principal findings of this study indicate that PBH has prolyl endopeptidase inhibitory activity in vitro. Moreover, administering EP to Aß(1-40)-infused rats significantly improves their performance on reference, spatial performance, and working memory tests during water maze tasks; concurrent proportional decreases are also observed in malondialdehyde levels, acetylcholinesterase (AChE) activity, and Aß accumulation levels in brain tissues. The PBH was suggested to ameliorate learning deficits associated with Alzheimer's disease by inhibition of lipid peroxidation in the brain of Aß infused rat.

The in vitro antioxidant properties of alcalase hydrolysate prepared from silkie fowl (Gallus gallus) blood protein.

Two types of proteins including blood plasma protein and blood cell protein were isolated from silkie fowl (Gallus gallus) blood and hydrolyzed using alcalase for 0, 2, 4 and 6 h. The blood plasma protein hydrolysate (BPH) and blood cell protein hydrolysate (BCH) were analyzed for pH value, peptide content and antioxidative properties. The significantly higher peptide contents were observed in BPH than that of BCH, which showed that blood plasma protein was more suitable to hydrolysis by alcalase than blood cell protein. Both BPH and BCH showed strong 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical-scavenging activity and Fe(2+) chelating ability. BPH at 4 h of hydrolysis (BPH4) demonstrated significantly higher antioxidant capacity than those treated by alcalase in most of the assays. The BPH4 was separated using ultra-filtration and assessment of the fractions and indicated that low molecular weight of peptides (< 3 kDa) possessed greater DPPH scavenging activity, Fe(2+) chelating ability and inhibitory activity of lipid peroxidation. These results show that BPH has the potential to be ingredients in the food industry as a replacement of synthetic antioxidants.

3-Hydroxyflavone inhibits human osteosarcoma U2OS and 143B cells metastasis by affecting EMT and repressing u-PA/MMP-2 via FAK-Src to MEK/ERK and RhoA/MLC2 pathways and reduces 143B tumor growth in vivo.

Many natural flavonoids have cytostatic and apoptotic properties; however, we little know whether the effect of synthetic 3-hydroxyflavone on metastasis and tumor growth of human osteosarcoma. Here, we tested the hypothesis that 3-hydroxyflavone suppresses human osteosarcoma cells metastasis and tumor growth. 3-hydroxyflavone, up to 50 µM without cytotoxicity, inhibited U2OS and 143B cells motility, invasiveness and migration by reducing matrix metalloproteinase (MMP)-2 and urokinase-type plasminogen activator (u-PA) and also impaired cell adhesion to gelatin. 3-hydroxyflavone significantly reduced p-focal adhesion kinase (FAK) Tyr397, p-FAK Tyr925, p-steroid receptor coactivator (Src), p-mitogen/extracellular signal-regulated kinase (MEK)1/2, p-myosin light chain (MLC)2 Ser19, epithelial cell adhesion molecule, Ras homolog gene family (Rho)A and fibronectin expressions. 3-hydroxyflavone also affected the epithelial-mesenchymal transition (EMT) by down-regulating expressions of Vimentin and α-catenin with activation of the transcription factor Slug. In nude mice xenograft model and tail vein injection model showed that 3-hydroxyflavone reduced 143B tumor growth and lung metastasis. 3-hydroxyflavone possesses the anti-metastatic activity of U2OS and 143B cells by affecting EMT and repressing u-PA/MMP-2 via FAK-Src to MEK/ERK and RhoA/MLC2 pathways and suppresses 143B tumor growth in vivo. This may lead to clinical trials of osteosarcoma chemotherapy to confirm the promising result in the future.

Determination of angiotensin-I converting enzyme inhibitory peptides in chicken leg bone protein hydrolysate with alcalase.

This study aims to identify peptides with angiotensin-I converting enzyme (ACE) inhibitory activity in hydrolysate from chicken leg bone protein hydrolyzed with alcalase for 4 h (A4H). The hydrolysate has demonstrated potent in vitro ACE inhibitory activity, and has been shown to attenuate the development of hypertension and cardiovascular hypertrophy in spontaneously hypertensive rats (SHR). A4H is competitive for ACE and was separated using high-performance liquid chromatography (HPLC) with a gel filtration column (Superdex Peptide HR 10/30). The results show that A4H is a mixed non-competitive inhibitor. Eighteen fractions were detected after separation of A4H, and most of them showed ACE inhibitory activity. Five fractions with strong ACE inhibitory activities (above 50%) were labeled from A to E. In addition, there were 10 peptides, consisting of 5-10 amino acid residues that were identified from fraction D that exhibited the strongest ACE inhibitory activity. Three of the identified peptides corresponded to peptides derived from collagen type I and chicken muscular protein. It is revealed that A4H has several peptides that possess ACE inhibitory activities.

Study on bioactive compounds of in vitro cultured Calculus Suis and natural Calculus Bovis.

The purpose of the study was to investigate bioactive compounds of in vitro cultured Calculus Suis and natural Calculus Bovis obtained as valuable by-products from animals used for meat production. The results showed that the components of natural Calculus Bovis were rich in bilirubin and biliverdin and had higher content of essential amino acids. The major amino acids of in vitro cultured Calculus Suis were identified as glycine, alanine, glutamic acid and aspartic acid, and those for natural Calculus Bovis were found to be glutamic acid, aspartic acid, proline, and arginine. The methionine and cysteine contents of precursors for glutathione in natural Calculus Bovis were significantly higher than those of in vitro cultured Calculus Suis. The mineral contents of zinc, iron and manganese of natural Calculus Bovis were significantly higher than those of in vitro cultured Calculus Suis. The major bile acids in both products were cholic acid and dehydrocholic acid, respectively. The chenodeoxycholic and ursodeoxycholic acid content of in vitro cultured Calculus Suis was significantly higher than that of natural Calculus Bovis.