Dynamics and Impacts of Human-Algorithm Consensus in Logistics Scheduling: Evidence from A Field Experiment

Algorithms are being implemented to aid human decision-making and most studies on human-algorithm interactions focus on how to improve human-algorithm cooperation. However, excessive reliance on algorithms in decision-making may hinder the complementary value of humans and algorithms. There is a lack of empirical evidence on the impacts of human-algorithm consensus in collaborative decision-making. To address this gap, this paper reports a large-scale field experiment conducted by one of China\u27s largest logistics firms in the context of route scheduling. The experiment involved assigning routes to either a treatment group, where algorithms and human operators collaborated in decision-making, or a control group, where human operators made decisions independently. We plan to collect data to evaluate the effects of algorithm implementation and to analyze the patterns and effects of human-algorithm consensus in a long-term cooperation. Our study aims to contribute to the literature on human-algorithm interactions in operational decisions

Combining NMR and LC/MS Using Backward Variable Elimination: Metabolomics Analysis of Colorectal Cancer, Polyps, and Healthy Controls

Both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) play important roles in metabolomics. The complementary features of NMR and MS make their combination very attractive; however, currently the vast majority of metabolomics studies use either NMR or MS separately, and variable selection that combines NMR and MS for biomarker identification and statistical modeling is still not well developed. In this study focused on methodology, we developed a backward variable elimination partial least-squares discriminant analysis algorithm embedded with Monte Carlo cross validation (MCCV-BVE-PLSDA), to combine NMR and targeted liquid chromatography (LC)/MS data. Using the metabolomics analysis of serum for the detection of colorectal cancer (CRC) and polyps as an example, we demonstrate that variable selection is vitally important in combining NMR and MS data. The combined approach was better than using NMR or LC/MS data alone in providing significantly improved predictive accuracy in all the pairwise comparisons among CRC, polyps, and healthy controls. Using this approach, we selected a subset of metabolites responsible for the improved separation for each pairwise comparison, and we achieved a comprehensive profile of altered metabolite levels, including those in glycolysis, the TCA cycle, amino acid metabolism, and other pathways that were related to CRC and polyps. MCCV-BVE-PLSDA is straightforward, easy to implement, and highly useful for studying the contribution of each individual variable to multivariate statistical models. On the basis of these results, we recommend using an appropriate variable selection step, such as MCCV-BVE-PLSDA, when analyzing data from multiple analytical platforms to obtain improved statistical performance and a more accurate biological interpretation, especially for biomarker discovery. Importantly, the approach described here is relatively universal and can be easily expanded for combination with other analytical technologies

Icariside II Ameliorates Cognitive Impairments Induced by Chronic Cerebral Hypoperfusion by Inhibiting the Amyloidogenic Pathway: Involvement of BDNF/TrkB/CREB Signaling and Up-Regulation of PPARα and PPARγ in Rats

Chronic cerebral hypoperfusion (CCH) is regarded as a high-risk factor for cognitive decline of vascular dementia (VD) as it is conducive to induce beta-amyloid (Aβ) aggregation. Icariside II (ICS II), a plant-derived flavonoid compound, has showed neuroprotective effect on animal models of Alzheimer’s disease (AD) by decreasing Aβ levels. Here, we assessed the effect of ICS II on CCH-induced cognitive deficits and Aβ levels in rats, and the possible underlying mechanisms were also explored. It was disclosed that CCH induced by bilateral common carotid artery occlusion (BCCAO) caused cognitive deficits, neuronal injury and increase of Aβ1-40 and Aβ1-42 levels in the rat hippocampus, while oral administration of ICS II for 28 days abolished the above deficits in the hippocampus of BCCAO rats. Meanwhile, ICS II significantly decreased the expression of beta-amyloid precursor protein (APP) and β-site amyloid precursor protein cleavage enzyme 1 (BACE1), as well as increased the expression of a disintegrin and metalloproteinase domain 10 (ADAM10) and insulin-degrading enzyme (IDE). ICS II also activated peroxisome proliferator-activated receptor (PPAR)α and PPARγ, enhanced the expression of brain-derived neurotrophic factor (BDNF), tyrosine receptor kinase B (TrkB), levels of Akt and cAMP response element binding protein (CREB) phosphorylation. Together, these findings suggested that ICS II attenuates CCH-induced cognitive deficits by inhibiting the amyloidogenic pathway via involvement of BDNF/TrkB/CREB signaling and up-regulation of PPARα and PPARγ in rats

Altered metabolite levels and correlations in patients with colorectal cancer and polyps detected using seemingly unrelated regression analysis

Introduction: Metabolomics technologies enable the identification of putative biomarkers for numerous diseases; however, the influence of confounding factors on metabolite levels poses a major challenge in moving forward with such metabolites for pre-clinical or clinical applications. Objectives: To address this challenge, we analyzed metabolomics data from a colorectal cancer (CRC) study, and used seemingly unrelated regression (SUR) to account for the effects of confounding factors including gender, BMI, age, alcohol use, and smoking. Methods: A SUR model based on 113 serum metabolites quantified using targeted mass spectrometry, identified 20 metabolites that differentiated CRC patients (n = 36), patients with polyp (n = 39), and healthy subjects (n = 83). Models built using different groups of biologically related metabolites achieved improved differentiation and were significant for 26 out of 29 groups. Furthermore, the networks of correlated metabolites constructed for all groups of metabolites using the ParCorA algorithm, before or after application of the SUR model, showed significant alterations for CRC and polyp patients relative to healthy controls. Results: The results showed that demographic covariates, such as gender, BMI, BMI2, and smoking status, exhibit significant confounding effects on metabolite levels, which can be modeled effectively. Conclusion: These results not only provide new insights into addressing the major issue of confounding effects in metabolomics analysis, but also shed light on issues related to establishing reliable biomarkers and the biological connections between them in a complex disease

Targeted serum metabolite profiling and sequential metabolite ratio analysis for colorectal cancer progression monitoring

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide and a major cause of human morbidity and mortality. In addition to early detection, close monitoring of disease progression in CRC can be critical for patient prognosis and treatment decisions. Efforts have been made to develop new methods for improved early detection and patient monitoring; however, research focused on CRC surveillance for treatment response and disease recurrence using metabolomics has yet to be reported. In this proof of concept study, we applied a targeted liquid chromatography tandem mass spectrometry (LC-MS/MS) metabolic profiling approach focused on sequential metabolite ratio analysis of serial serum samples to monitor disease progression from 20 CRC patients. The use of serial samples reduces patient to patient metabolic variability. A partial least squares-discriminant analysis (PLS-DA) model using a panel of five metabolites (succinate, N2, N2-dimethylguanosine, adenine, citraconic acid, and 1-methylguanosine) was established, and excellent model performance (sensitivity = 0.83, specificity = 0.94, area under the receiver operator characteristic curve (AUROC) = 0.91 was obtained, which is superior to the traditional CRC monitoring marker carcinoembryonic antigen (sensitivity = 0.75, specificity = 0.76, AUROC = 0.80). Monte Carlo cross validation was applied, and the robustness of our model was clearly observed by the separation of true classification models from the random permutation models. Our results suggest the potential utility of metabolic profiling for CRC disease monitoring

Toxicity Study of VOSO4 Using NMR-based Metabonomics

NMR-Based metabonomics combined with clinical biochemical analysis and histopathological examination was applied to investigate the toxicity effects of vanadyl sulfate with insulin-like activity in male Wistar rats. Male Wistar rats were administrated with VOSO4 at doses of 15 and 45 mg/kg body weight by intragastric administration for 16 d. Urine and serum samples were collected and analyzed by H-1 NMR experiment. Multivariate analyses were employed to identify the characteristic metabolites for the toxicity effects of vanadyl sulfate. Then the metabolic networks of these characteristic metabolites were built up using TICL (a web Tool for automatic Interpretation of Compound List). The relationship between the characteristic metabolites and the main matebolic pathways perturbed were analyzed and discussed. The differences of metabolic profiles were examined among high-dose (45 mg/kg), low-dose (15 mg/kg) of VOSO4 and control groups. Compared to the control group, increased levels of lactate, creatinine and taurine in serum and increased excretion of trymethylamine-N-2-oxide, creatinine, taurine and glycine in urine were found in both high- and low-dose groups which showed an obvious dose-dependent relationship. On the other hand, the concentration of acetate and succinate were decreased in both serum and urine samples of dosed groups. These results indicate that VOSO4 have disturbed the carbohydrate metabolism, lipid metabolism and gut microflora and the high-dosage of VOSO4 may cause liver and kidney injury

IL-2 Inhibition of Th17 Generation Rather Than Induction of Treg Cells Is Impaired in Primary Sjögren’s Syndrome Patients

ObjectiveTo investigate the role of IL-2 in the balance of Th17 and Tregs and elucidate the underlying mechanisms of enhanced Th17 differentiation in primary Sjögren’s syndrome (pSS) patients.MethodsThis study involved 31 pSS patients, 7 Sicca patients, and 31 healthy subjects. Th17 and Treg cells were determined by flow cytometry, and IL-17A was detected by immunohistochemistry. IL-2 and IL-6 levels were assessed by ELISA and qPCR. p-STAT5 and p-STAT3 in salivary glands (SGs) were evaluated by immunohistochemistry and flow cytometry. The binding of STAT5 and STAT3 to the Il17a gene locus was measured by chromatin immunoprecipitation.ResultsWe found that the percentage of Th17 cells was increased in the periphery and SG of pSS patients when compared with healthy subjects, but the Treg cells was unchanged. Meanwhile, the IL-2 level was reduced, and the IL-6 and IL-17A level was increased in the plasma of pSS patients. The ratio of IL-2 and IL-6 level was also decreased and IL-2 level was negatively correlated with the level of IL-17A. The expression of Il6 and Il17a mRNA was significantly increased, whereas Foxp3, Tgfb1, Tnfa, and Ifng mRNA were comparable. Furthermore, the level of STAT5 phosphorylation (p-STAT5) was reduced and p-STAT3 was enhanced in the SGs and in peripheral CD4+ T cells of pSS patients. In vitro IL-2 treatment-induced STAT5 competed with STAT3 binding in human Il17a locus, leading to decreased Th17 differentiation, which was associated with the reduced transcription activation marker H3K4me3.ConclusionOur findings demonstrated a Treg-independent upregulation of Th17 generation in pSS, which is likely due to a lack of IL-2-mediated suppression of Th17 differentiation. This study identified a novel mechanism of IL-2-mediated immune suppression in pSS

Correction: Symptom improvement in children with autism spectrum disorder following bumetanide administration is associated with decreased GABA/glutamate ratios.

An important detail was omitted in the Method of the original Article, I.E, The CARS and other evaluations were conducted 'blind' to condition (Bumetanide or no treatment) by experienced clinicians. This has now been updated in the HTML and PDF versions of this Article

Correction: Symptom improvement in children with autism spectrum disorder following bumetanide administration is associated with decreased GABA/glutamate ratios

An important detail was omitted in the Method of the original Article, I.E, The CARS and other evaluations were conducted ‘blind' to condition (Bumetanide or no treatment) by experienced clinicians. This has now been updated in the HTML and PDF versions of this Article

Symptom improvement in children with autism spectrum disorder following bumetanide administration is associated with decreased GABA/glutamate ratios

Funder: Shanghai Municipal Commission of Health and Family Planning Shanghai Shenkang Hospital Development Center Shanghai Municipal Education Commission National Natural Science Foundation of China Shanghai Committee of Science and Technology Xinhua Hospital of Shanghai Jiao Tong University School of Medicine Guangdong Key Project in "Development of new tools for diagnosis and treatment of Autism "Funder: Shanghai Municipal Commission of Health and Family Planning Shanghai Municipal Education Commission National Natural Science Foundation of China the National Key Research and Development Program of China ZJ LabFunder: National Human Genetic Resources Sharing Service Platform 111 Project ZJ LabFunder: National Natural Science Foundation of China ZJ LabAbstract: Bumetanide has been reported to alter synaptic excitation–inhibition (E-I) balance by potentiating the action of γ-aminobutyric acid (GABA), thereby attenuating the severity of autism spectrum disorder (ASD) in animal models. However, clinical evidence of its efficacy in young patients with ASD is limited. This was investigated in the present clinical trial of 83 patients, randomised to the bumetanide group (bumetanide treatment, 0.5 mg twice daily) or the control group (no bumetanide treatment). Primary [Children Autism Rating Scale (CARS)], secondary [Clinical Global Impressions (CGI)], and exploratory [inhibitory (γ-aminobutyric acid, GABA) and excitatory (glutamate, Glx) neurotransmitter concentrations measured in the insular cortex (IC) and visual cortex (VC) by magnetic resonance spectroscopy (MRS)] outcome measures were evaluated at baseline and at the 3-month follow-up. Side effects were monitored throughout the treatment course. Compared with the control group, the bumetanide group showed significant reduction in symptom severity, as indicated by both total CARS score and number of items assigned a score ≥ 3. The improvement in clinical symptoms was confirmed by CGI. GABA/Glx ratio in both the IC and VC decreased more rapidly over the 3-month period in the bumetanide group than that in the control group. This decrease in the IC was associated with the symptom improvement in the bumetanide group. Our study confirmed the clinical efficacy of bumetanide on alleviating the core symptoms of ASD in young children and it is the first demonstration that the improvement is associated with reduction in GABA/Glx ratios. This study suggests that the GABA/Glx ratio measured by MRS may provide a neuroimaging biomarker for assessing treatment efficacy for bumetanide