Background: Pancreatic cancer is recognized as one of the most malignant tumors with poor prognosis. Recently, long noncoding RNAs (lncRNAs) are considered as a potential prognostic biomarker of PC. However, the concrete biological effect of lncRNAs in PC remains unmasked. Herein, we explored the mechanism of LINC00491 in PC.Methods: Quantitative real-time PCR (qRT-PCR) was administrated to detected the expression of LINC00491 in PC tissues and cell lines. Loss-of-function experiment in vitro and in vivo was carried out to figure out the biological effects of LINC00491 on PC carcinogenesis. Luciferase reporter assay, subcellular fractionation, western blotting, pull-down assay and RNA immunoprecipitation assay were further used to explore the mechanism of PC tumorigenesis of LINC00491.Results: An increase of LINC00491 was detected in PC cell lines and tissues. Silencing LINC00491 in vitro and in vivo subsequently hindered cell migration, invasion, proliferation and tumor growth, respectively. Further research confirmed a negative and a positive connection of LINC00491 with microRNA 188-5p (miR-188-5p) level and Zinc finger protein 91 (ZFP91), a target of miR-188-5p, respectively. qRT-PCR and western blotting found that miR-188-5p was upregulated while LINC00491 was downregulated, concomitant with ZFP91 decreasing in PC cells or node mouse tumors, which could be significantly restored by inhibiting miR-188-5p. Besides, overexpression of miR-188-5p partially restored the inhibitory effect of LINC00491 diminution on proliferation, migration, and invasion of PC cells.Conclusion: LINC00491 promotes PC proliferation, migration, invasion via the miR-188-5p/ZFP91 axis, suggesting LINC00491 could be a new therapeutic target for PC. Pancreatic cancer (PC) is the fourth leading fatal malignant solid tumor in the United States, which could contribute to thousands of cancer-related deaths around the world Long non‑coding RNAs (lncRNAs) which are initially recognized as the “noise” of genomic transcription are a group of evolutionarily conserved RNA transcripts with over 200 nucleotides in length Long intergenic non-coding RNA 491 (LINC00491) is a newly identified lncRNA located on human chromosome 5q21.1 In our study, we determined the expression and carcinogenic functions of LINC00491 in PC. LINC00491 aggravated pancreatic cancer progression by microRNA 188-5p (miR-188-5p)/Zinc finger protein 91 (ZFP91) axis, which may open up new avenues for the development of prevention and treatment of PC in the future.24 paired PC tissues and adjacent normal tissues used in our study were obtained with written informed consent acquired under the requirements of the Ethics Committee of the First Affiliated Hospital of Nanchang University. The inclusion and exclusion criterion are as follows: The patients recruited in our study were ranged from 18 to 75 years old who were diagnosed as primary pancreatic cancer without any radiotherapy and chemotherapy and with no distant and/or multiple metastasis.The cells used in our research such as normal human pancreatic ductal epithelial cells (HPDE), AsPC-1, BxPC-3, Capan-2, MIAPaCa-2, PANC-1 and SW1990 were purchased from the Chinese Academy of Sciences Cell Bank . The complete Dulbecco's Modified Eagle Medium (DMEM) contain 10% Fetal Bovine Serum (FBS) attained from Biological Industry  was utilized to cells culture.-ΔΔCq) method was used to calculate the results The total RNAs of PC tissues and cells were extracted with Trizol reagent . Subsequently, the PrimeScript RT Reagent Kit and the SYBR Premix Ex Taq purchased from TaKaRa company were further utilized to detect the specific molecular levels. GAPDH was used as an internal control. The experiment was repeated in triplicate and comparing the quantitative cycle . Additionally, the scrambled short-hairpin RNA (sh-RNA) and LINC00491 knockdown plasmid which could steadily suppress LINC00491 were also obtained from GenePharm company. The miR-188-5p mimics and inhibitor, and the matched control (inhibitor-Con and miR-Con) were attained from GenePharm . A 50-70% density of cells was required while transfecting the above reagents into cells via Lipofectamine 3000 (Invitrogen). Next, the cells were used for further experiments after 48h-culturement.3 cells were seeded into each well of 96-well plates overnight. Then 10 µl CCK-8 solution was added and cultured for 30 minutes, then the viabilities were measured for four consecutive days at 450 nm absorbance.The proliferation abilities of PC cells were evaluated by the Cell Counting Kit-8 purchased from Glpbio company. Average 2×10500 cells planted in 6-well plates were washed with PBS after a 12-day incubation. Subsequently 4% paraformaldehyde and crystal violet were applied to fix and stain the treated cells for 20 minutes, respectively. Then the colonies were counted and finally compared after being washed with running water.4 cells mixed in 200 µl serum-free medium, the lower chamber was full of 600 µl complete medium after filling with 60 µl Matrigel  for invasion assays and without for migration assays, respectively. After 48h-incubation, fixed with 4% paraformaldehyde and stained by crystal violet for separate 20 minutes, the cells were eventually photographed and recorded.The migration and invasion assay were carried out as described previously TM Kit (AM1921) purchased from Thermo Scientific company was employed to isolate nuclear and cytoplasmic RNAs as described previously 6 fresh cultured cells were washed once in PBS and placed on ice. Then the Cell Fractionation Buffer and Cell Disruption Buffer were used to split the sample for RNA isolation. The RNA isolation should be done at room temperature and the RNA extracted should be stored at -80 °C. qRT-PCR was utilized to evaluate the subcellular fractions. U6 (nucleus control) and β-actin (cytoplasm control) was set as a control.The PARIShttp://starbase.sysu.edu.cn/. Wild-type (wt) LINC00491 and mutant (mt) LINC00491 luciferase vectors were constructed in advanced. At a density of 60%, SW1990 cells were transiently transfected with miR-188-5p negative control or mimics together with LINC00491 wt or LINC00491 mt via Lipofectamine 3000 (Invitrogen) transfection. Then the cells were collected for luciferase activity analysis after 48-incubation.Firstly, the potential binding sites of miR-188-5p and LINC00491 were predicted by StarBase3.0 The assay was conducted with the Magna RIP™ RNA-Binding Protein Immunoprecipitation Kit (no. 17-700) purchased from Millipore company. SW1990 cells washed once with PBS were lysed in RIP lysis buffer which contained negative control IgG or Ago2 antibody magnetic beads. The complexes bound by magnetic beads were immobilized with magnet and washed off with wash buffer. After purification of RNA, qRT-PCR was then used to measure the expression of immunoprecipitated LINC00491.7 SW1990 cells were dissolved in 700 µl lysis buffer with Dynabeads  after 48h incubation according to the manufacturer's instruments. After being incubated on at 4 °C for 3 h, the beads were washed for 3 times and the retrieved supernatant was prepared for purification of RNAs. LINC00491 was quantified by qRT-PCR.Negative control and biotin-labelled miR-188-5p were transfected into SW1990 cells separately via Lipofectamine 3000. About 1×10Western blotting was conducted as described before 7) were injected into the axillary skin of nude mice from the corresponding groups, respectively. The tumor volume and weight of the two groups were measured every 7 days for four consecutive weeks. Additionally, the expression of LINC00491 and ZFP91 were also detected in the xenografts.12 five-week-old female nude mice achieved from the National Laboratory Animal Center  were divided into two groups randomly. The assay was conducted according to our previous study 2 test. Usually, p < 0.05 was considered statistically significant.All experiments involving in our research were repeated at least in triple. The data presented as mean ± SD was processed by SPSS software version 26.0 . The differences between groups were distinguished by Two-tailed Student's T-test or χqRT-PCR was performed to assess the level of LINC00491 in PC tissues and adjacent normal tissues. As shown in Figure To investigate the effect of LINC00491 in PC cell migration, invasion and proliferation, the loss-of-function assays were carried out followed by transfecting LINC00491 siRNA and scramble control into SW1990 and MIAPaCa-2  in vivo. SW1990 cells transfected with LINC00491 shRNA or negative control were injected subcutaneously into the armpits of nude mice. After 28 days, the mass tumors were obtained carefully from the mice models (Figure Nude mice xenograft tumor growth assay was further performed to explore LINC00491 effects s Figure A. Results Figure B and C. s Figure D. Moreovs Figure E and F. Recently, PC was considered to be one of the most dangerous cancers that was famous for its poor prognosis despite the use of multi-agent conventional chemotherapy To elucidate this point, the expression level of LINC00491 was evaluated in PC cell lines and tissues. As results showed, the LINC00491 was greatly increased in the cell lines especially in SW1990 and MIAPaCa-2 and PC tissues. Subsequently, loss-of-function studies proved that silencing LINC00491 could inhibit PC cells migration, invasion and proliferation and retard tumor growth. All the results above implied LINC00491 exerted an oncogenic role in the development of PC. To further explored whether LINC00491 can affect the process of PC by interacting with miRNA, we carried out subcellular fractionation assays, which was similar to the research made by Ye et al. It was widely acknowledged that miRNAs repressed protein synthesis by base-pairing to the mRNA 3'-UTR, which usually occurred post-transcriptionally in vivo and in vitro, respectively. LINC00491 can promote ZFP91 expression through its sponge miR-188-5p ability. Therefore, LINC00491 can be regarded to be a valuable prognostic biomarker for PC therapy in the future.To date, the concrete effects of LINC00491 and miR-188-5p are still controversial. In this study, we clarified the possibility of the potential mutual interaction between LINC00491 and miR-188-5p In summary, our study provides evidence that LINC00491 can increase ZFP91 expression through sponging miR-188-5p, thereby promoting PC progression. This emphasized the LINC00491/miR-188-5p/ZFP91 axis as one potential treatment strategy for PC.


Neurofilament light chain (NfL) is an attractive biomarker of diseaseactivity and progression in MS, but there is a lack in long-term prognosticdata.To test the long-term clinical and radiological prognostic value ofcerebrospinal fluid (CSF)-NfL among newly diagnosed patients with MS.Newly diagnosed MS patients where followed prospectively with baselineCSF-NfL and repeated MRI and clinical assessments for up to 10 years.Associations between baseline CSF-NfL and longitudinal MRI and clinicalassessments were found by Generalized Estimating Equations analysis.p = 0.009) and hippocampus (p = 0.001) asevaluated by MRI. Baseline volumes of thalamus , T1  and T2  lesions and baseline levels of CSF-NfL  significantly predictedEDSS worsening over 10 years. Baseline CSF-NfL gave a comparable predictionto the best MRI volumetric predictors.Forty-two participants were included. CSF-NfL at baseline was significantlyassociated with the rate of atrophy in globus pallidus(CSF-NfL predicted the clinical and radiological course of newly diagnosedpatients with MS over a 10-year period, underlining its prognostic role. Age of onset is about 30 years, and consequently large parts of patients’lives are affected by the disease. The lack of reliable biomarkers for long-termdisease prognosis, combined with a highly heterogeneous disease course, often makesit a life of uncertainty.Multiple sclerosis (MS) is the leading inflammatory disorder of the central nervoussystem (CNS) among young adults worldwide, with an escalating prevalence.4 However, thereare a number of potential limitations such as time delays from disease onset toimage examination, as well as logistics and examination costs. In addition, thelimited correlation between traditional MRI measurements and clinical disabilityimpedes the value of MRI as a surrogate marker for MS disease activity.6 Gadolinium accumulation withinthe CNS and potential toxicity, which has led to FDA warnings, should also be takeninto account.8 Theselimitations illustrate an unmet need in the handling of MS which has led to theimplementation of composite surveillance strategies, including both MRI and clinicalscorings for evaluating disease activity.At present, magnetic resonance imaging (MRI) is the biomarker of choice for diagnosisand follow-up in MS, and the current McDonald diagnostic criteria are heavily basedon MRI. We and others have previously shown that neurofilament light chainmeasurements in CSF (CSF-NfL) correlate well with clinical worsening ofdisability.13 In addition, both cross-sectional and longitudinal studiesreport associations of CSF-NfL with MRI activity in MS, but the number of studiesare limited, with relatively short follow-up.17Some of these challenges could be solved by implementing new and robust biomarkers.In particular, neurofilaments have emerged as an attractive biomarker of MS diseaseactivity. This group of biomarkers consist of polypeptides found in the cytoplasm ofneurons, which are released into the cerebrospinal fluid (CSF) and blood in numerousCNS diseases, including MS.In this prospective study, we aimed to evaluate the prognostic value of CSF-NfL amongnewly diagnosed MS-patients in terms of both clinical and radiological diseaseworsening over a 10-year follow-up.This study is part of a prospective population-based longitudinal cohort study ofpatients with newly diagnosed MS at two specialized centers in South-WesternNorway . In total, 108 patients received the diagnosis of MSaccording to the Poser criteria during 1998 to 2000. Of these, 42 patients withrelapsing remitting MS (RRMS) or secondary progressive MS (SPMS) were willing toundergo extended MRI examinations and a lumbar puncture, and were thus includedin this study. Upon recruitment, the patients provided written informed consentin study participation, and then underwent standardized clinical evaluationsincluding a full neurological examination and Expanded Disability Status Scale(EDSS) scoring. At the subsequent follow-up with MRI examination and clinicalscorings after five and 10 years, in total 37 and 25 patients, respectively,were included.3, for 3D T1-WI0.9  ×  0.9  ×  1.4 mm3, and for SE T10.9  ×  0.9  × 5.0 mm3 on the Siemens scanner. On the Philipsscanner the voxel size for (SE) PD/T2-WI was0.89  ×  0.89  ×  5.0 mm3, for 3D T1-WI0.89  ×  0.89  × 1.2 mm3, and for SE T10.89  ×  0.89  ×  5.0 mm3. Further details on the MRI protocolhave been described previously.MRI scans were performed at baseline and after 5, and 10 years of follow-up usingthe same standardized study protocol at both centers. Scans were performed usingthe same 1.5 T unit . The MRIprotocol consisted of dual spin echo (SE) PD/T2-WI, a three-dimensional (3D)T1-W1 and a SE T1-WI. The voxel size for (SE) PD/T2-WI was0.9  ×  0.9  ×  5.0 mm Normalised measures for whole brain volume, grey matter volume, whitematter volume, cortical volume and lateral ventricular volume were measuredusing SIENAX (v2.6) with lesion inpainted 3D-T1 images.All baseline and follow-up images for each subject were co-registered to itsbaseline SE T1 image using a 6° of freedom rigid-body model using FMRIB's LinearImage Registration Tool (FMRIB's FLIRT). All subsequent lesion analyses weredone using the co-registered images. T1 and T2 lesion volumes were calculatedusing a reliable semi-automated edge detection contouring/thresholding technique. Normalized subcortical deep grey matter volumes were estimated bymultiplying the estimated volumes from FIRST by the volumetric scaling factorfrom SIENAX.Absolute volumes of the subcortical grey matter structures were also derived fromusing MRIB's Integrated Registration and Segmentation Tool (FIRST v1.2), amodel-based segmentation and registration tool. Intra-assay coefficients of variation were below 15%, and inter-assaycoefficients of variation were below 10%.CSF was obtained at baseline by lumbar puncture using standardized procedures,aliquoted and kept frozen at −70°C. CSF samples had gone through one freeze-thawcycle before NfL concentrations were quantified using the commercially availablesensitive sandwich enzyme-linked immunosorbent assay (ELISA) kit fromUmanDiagnostics AB, according to the manufacturer’s kit instructions, described elsewhere.Means and standard deviations (SD) are presented for continuous variables thatwere normally distributed and medians and interquartile ranges (IQR) forvariables that were not. Counts and percentages are presented for categoricalvariables.We used linear regression to study the association between baselineCSF-NfL-levels and baseline MRI brain volumes. CSF-NfL was log transformed usingthe natural logarithm (after adding a constant 1), to reduce the potentialimpact of outlying values. T1 and T2 lesion volumes were right-skewed and werethus square root transformed to improve the symmetry of the residualdistributions. Results are presented as point estimates of effect (β) with 95%confidence intervals (CI) and with p-values from Wald tests, with and withoutadjustment for age at baseline, sex and disease duration. For increasedinterpretability, we calculated the expected difference in brain volumes betweenCSF-NfL values at the third vs. the first quartile for the statisticallysignificant results. For transformed outcomes, CI for this difference werepercentile intervals based on non-parametric bootstrap with 1000 resamples andwith predictions based on medium values or most frequent category for thecovariates.p-values for the interaction term and the main effect(interpretable as the predicted association between CSF-NfL and brain volume atbaseline). We also calculated the expected additional change in MRI brainvolumes per five years for CSF-NfL values at the third vs. the first quartile.The exchangeable working correlation structure was used throughout, and robust(sandwich) estimation of standard errors.Next, Generalized Estimating Equations (GEE) analysis was used to study theassociation between baseline CSF-NfL levels and longitudinal MRI brain volumes.All models contain time as a continuous explanatory variable as well as theinteraction between time and CSF-NfL to assess effect on slope of brain atrophy.Presented results include for each outcome β, 95% CI and WaldFinally, models for longitudinal measures of EDSS score were fitted using GEE,with individual baseline MRI brain volumes or CSF-NfL as predictors. The modelsand presentation are similar to the previous analyses. Additionally, for thesemodels we present the Corrected Quasi-likelihood under Independence ModelCriterion (QICC), which was used for comparison of models with differentpredictors.p < 0.01 ascut off for statistical significance. All analyses were performed in SPSSversion 23 , except the bootstrapping which wasperformed in R version 4.0.2 .Due to the large number of comparisons, we used Forty-two patients were included with a mean age at baseline of 41.9 years(interquartile range (IQR) 33.2, 50.0), and 29 (69%) of the participants werefemale. The median disease duration at baseline was 60 months .Thirty-five (83%) patients were categorized as RRMS at baseline and seven (17%)as SPMS. At the five-year follow-up 37 patients were still included and 25remained at the 10-year follow-up. The proportion with progressive diseaseincreased throughout the study. Only 17% were started on disease-modifyingtreatment (DMT) at baseline, which had increased to 68% at 10-year follow-up.p = 0.002), nucleus accumbens , and highersquare-rooted T1-  andT2-lesion volumes .. When comparing the thirdand the first quartile value of CSF-NfL concentrations (i.e. CSF-NfL 1.2 vs.0.1) we found an expected difference in thalamic volume of −1.42 cm3(95% CI −2.0 to 0.5 cm3); in nucleus accumbens volume−0.12 cm3 (−0.21 to −0.03 cm3); in T1 lesion volume of+3.8 cm3 (1.8 to 6.0 cm3); and in T2 lesion volume+8.5 cm3 (3.9 to 12.5 cm3).When adjusted for age at baseline, sex and disease duration, higher CSF-NfLconcentrations were significantly associated with lower MRI volumes of thalamus. Lowervop = 0.009) and hippocampus , for both of which higher CSF-NfLpredicted a higher rate of atrophy (3 (95% CI 0.03 to0.24 cm3) per five years, which amounted to 280% of the medianchange in globus pallidus volume from baseline to five years (Table S1). Theadditional loss of volume in hippocampus for the third compared to the firstquartile was 0.22 cm3 (95% CI 0.10 to 0.35 cm3), amountingto 275% of the median changes in the volume from baseline to five years.When adjusting for age at baseline, sex, and disease duration we foundsignificant CSF-NfL-dependent slopes for volumes of globus pallidus ,T1-lesions , T2-lesions, and baseline levelsof CSF-NfL  eachsignificantly predicted the rate of EDSS worsening over the 10-year follow-upperiod  between baseline CSF-NfL and futureloss of total deep grey matter and putamen. Patients with baseline CSF-NfL in thethird quartile compared to the first quartile had a volume loss of globus pallidusand hippocampus of 2.8 times higher than the median change of the whole studypopulation seen in the first five years. To our knowledge, this study is the firstto show an association between CSF-NfL and grey matter volumes in a long-termsetting. This observation has direct clinical implications, as deep grey matter losshas been associated with disability accumulation, and involvement of the hippocampushas been found to relate to several cognitive functions, including poor verbalmemory performance.29 CSF-NfL was not associated with future thalamic atrophy overthe 10 years of follow-up in our study. Previous studies have found thalamus atrophyto commence early in the disease course. This might play a role in the lack in association in our patients, as ourpatients already had a considerably long interval from disease onset todiagnosis.We also found significant associations between baseline CSF-NfL and future loss ofgrey matter volume structures of globus pallidus and hippocampus, as well as trend than sNfL. Consequently we find it meaningful to analyze for CSF-NfL at time ofdiagnoses despite the more readily available analysis for sNfL.We used ELISA technology to assess levels of CSF-NfL in this study. However todayeven more sensitive methods for detection of low concentration of NfL like the Simoatechnology has made it possible to also analyze blood for NfL (sNfL). In a smallstudy from 2016, there was a correlation between sNfL and white matter volume loss,but not grey matter loss over a median follow-up of 3.6 years.As this study only examined patients at three different time points it is ofimportance that these visits were carried out during a clinically stable timeperiod, and not examined during a relapse. In total eight patients were included inthe study that had an attack within the last two months prior to the baseline visit,as well as one patient with an attack around three months prior to the five-yearfollow-up. However, we did not observe any significant differences between thegroups. This study further strengthens the use of CSF-NfL as a prognostic biomarkerfor clinical and radiological disease worsening in newly diagnosed MS. Although theresults from the statistical models used in this paper must be interpreted on agroup level, there is now increasing evidence that assessing patients at time ofdiagnosis for CSF-NfL will provide an indication of future disease burden up to 10years in advance. This further allows for a better stratification of diseaseseverity, and thus a more personalized approach in choosing treatment for MS.We have previously shown correlation between baseline CSF-NfL and worsening ofdisability defined by EDSS after five years of follow-upClick here for additional data file.Supplemental material, sj-docx-1-mso-10.1177_20552173211060337 for CSFneurofilament light chain predicts 10-year clinical and radiologic worsening inmultiple sclerosis by Alok Bhan, Cecilie Jacobsen, Ingvild Dalen, NielsBergsland, Robert Zivadinov, Guido Alves, Kjell-Morten Myhr and Elisabeth Farbuin Multiple Sclerosis Journal – Experimental, Translational and ClinicalClick here for additional data file.Supplemental material, sj-doc-2-mso-10.1177_20552173211060337 for CSFneurofilament light chain predicts 10-year clinical and radiologic worsening inmultiple sclerosis by Alok Bhan, Cecilie Jacobsen, Ingvild Dalen, NielsBergsland, Robert Zivadinov, Guido Alves, Kjell-Morten Myhr and Elisabeth Farbuin Multiple Sclerosis Journal – Experimental, Translational and Clinical


Evidence of the health and environmental harms of red meat is growing, yet little is known about which harms may be most impactful to include in meat reduction messages. This study examined which harms consumers are most aware of and which most discourage them from wanting to eat red meat.Within-subjects randomised experiment. Participants responded to questions about their awareness of, and perceived discouragement in response to, eight health and eight environmental harms of red meat presented in random order. Discouragement was assessed on a 1-to-5 Likert-type scale.Online survey.544 US parents.P < 0·05).A minority of participants reported awareness that red meat contributes to health harms (ranging from 8 % awareness for prostate cancer to 28 % for heart disease) or environmental harms (ranging from 13 % for water shortages and deforestation to 22 % for climate change). Among specific harms, heart disease elicited the most discouragement (mean = 2·82 out of 5), followed by early death (mean = 2·79) and plants and animals going extinct (mean = 2·75), though most harms elicited similar discouragement . In multivariable analyses, participants who were younger, identified as Black, identified as politically liberal, had higher general perceptions that red meat is bad for health and had higher usual red meat consumption reported being more discouraged from wanting to eat red meat in response to health and environmental harms (all Messages about a variety of health and environmental harms of red meat could inform consumers and motivate reductions in red meat consumption. Further, red meat is a major contributor to environmental harms such as greenhouse gas emissions,9–13, air and water pollution,9, biodiversity loss,14 and deforestation,15. Reducing red meat consumption is therefore an important strategy for reducing chronic disease risk and mitigating environmental damage.High consumption of meat, particularly red and processed meat, increases risk of CVD, diabetes and some cancers. More than half of Americans say they are willing to eat less red meat. Yet red meat consumption is projected to increase over the next decade, perhaps in part because many Americans are unaware of the health and environmental harms of red meat,19. Given this willingness to change, coupled with lack of awareness about red meat’s impacts, educating consumers about the harms of red meat could reduce red meat consumption.Despite growing recognition of the health and environmental harms of red meat, American adults consume an average of 284 g/week (about 0·6 pounds) of unprocessed red meat alone (i.e. not including processed red meats such as bacon), nearly three times the maximum level recommended for optimising human and planetary health,21, alcohol consumption and sugary drink consumption–25. Similarly, a recent systematic review found that providing information about the health effects of meat consumption is an effective strategy for reducing intentions to eat meat as well as meat consumption. Emerging literature also suggests the promise of communicating about products’ environmental harms as a strategy for changing consumer behaviour. For example, a randomised experiment with undergraduate students in the UK found that sending students 2 weeks of daily messages about the environmental effects of meat production reduced students’ red and processed meat consumption compared with a no-message control group. What remains unknown is which specific health and environmental harms hold the most promise for motivating consumers to reduce their red meat intake. Identifying the specific harms that most discourage red meat intake is important because messaging campaigns may not be able to communicate about all harms (e.g. due to space constraints), and because prior studies of tobacco and sugary drink messages suggest advantages to shorter, simpler messages–32. Also unknown is whether consumers’ reactions to health and environmental harms of red meat vary by demographic characteristics, information that could help to tailor messages to specific groups.A growing body of research has shown that communicating about a products’ health harms, for example, through product warning labels and mass media campaigns, is an effective strategy for reducing unhealthy behaviours including cigarette smoking. Parents of young children (i.e. under age five) are especially important, given that dietary habits in early childhood affect diet and health later in childhood and into adolescence,35. Moreover, US parents are nearly 40 % less likely than non-parents to have reduced their red meat intake compared with 3 years ago, suggesting red meat reduction campaigns may be especially beneficial for this group. Thus, the specific objectives of this study were to examine which health and environmental harms of red meat parents are aware of and which are most likely to discourage red meat consumption. Additionally, to provide insight on populations that might respond more strongly to messages about red meat’s harms, we examined demographic predictors of awareness of health and environmental harms and of the extent to which these harms discouraged participants from wanting to consume red meat.To inform communication efforts, we examined consumers’ responses to health and environmental harms of red meat in an experiment with US parents of young children. Parents are a critical group to study in dietary communication interventions because their behaviours influence both their own health and the dietary habits of their childrenhttps://aspredicted.org/q5e9b.pdf). The only deviations from this plan were that we corrected for multiple comparisons using Bonferroni’s method rather than Tukey’s method because Tukey’s method cannot be applied to mixed models, and that we conducted two unplanned exploratory analyses, examining: (1) predictors of awareness of health and environmental harms and (2) predictors of harm-induced discouragement separately for health v. environmental harms.Prior to data collection, we pre-registered the sample size, hypotheses and analysis plan .,37 and general perceptions that red meat is bad for health and for the environment . Next, they responded to questions about their awareness of, and discouragement in response to, specific health and environmental harms of red meat. The order of presentation of health and environmental harms was randomised such that half of participants answered questions about health harms first and half answered questions about environmental harms first.A flow of survey questions is shown in Fig. –40, ‘Before today, had you ever heard that eating red meat can contribute to the following harms?’ Then, we listed the eight health or eight environmental harms, displayed in random order. Participants could also select ‘I haven’t heard of red meat contributing to any of these harms before;’ this option was always displayed last.We assessed awareness of harms using a select-all-that-apply question adapted from previous studies–40, ‘How much does knowing that eating red meat contributes to these harms discourage you from wanting to eat red meat?’ We assessed perceived discouragement because meta-analytic evidence indicates that perceived message effectiveness is predictive of actual message effectiveness. Participants rated perceived discouragement in response to each harm on a 5-point scale, from ‘Not at all’ (coded as 1) to ‘Very much’ (coded as 5).Next, we assessed the extent to which each harm discouraged participants from wanting to eat red meat using an item adapted from previous studies,43, weight gain–45, heart disease,46, stroke,48, colon cancer,49,50, prostate cancer, stomach cancer and early death,51. The eight environmental harms were climate change,15, more greenhouse gases,9–12, water shortages,11,52, water pollution, air pollution, plants and animals going extinct,14, clearing of forests,15 and worse land quality,15,53. All participants rated their awareness and discouragement for each of the eight health harms and each of the eight environmental harms. Within each type of harm , specific harms were presented in random order.We selected harms to present based on recent literature linking red meat production and consumption with health and environmental harms Table . The eig1.Finally, the survey assessed standard demographics. Survey measures appear in online supplementary material, Supplemental Exhibit First, we calculated the proportion of participants who reported they were aware of each harm and the mean discouragement ratings for each harm. We also calculated the proportion of participants who were aware of at least one harm, and the mean number of harms for which participants indicated awareness, both overall and separately for health and environmental harms. Next, we assessed whether likelihood of reporting awareness of harms was higher for health compared with environmental harms using mixed effects logistic regression, regressing awareness (coded as 0/1 for each harm) on an indicator variable for whether the harm was a health or environmental harm. These models treated the intercept as random to account for repeated measures within participants.v. environmental harms.To shed light on the populations who were most aware of red meat’s harms, analyses also examined demographic predictors of the total number of harms for which participants indicated awareness . These analyses used negative binomial regression with robust standard errors. We regressed the total number of harms for which participants indicated awareness on the following potential predictors: age, gender, race/ethnicity, educational attainment, income, political leaning and usual red meat consumption. We also used this approach to examine predictors of awareness separately for health harms z-tests to conduct pairwise comparisons of predicted mean discouragement for each harm, applying Bonferroni’s method to adjust for multiple comparisons. These comparisons allowed us to determine which of the harms (if any) were more discouraging than the others while adjusting for repeated measures within participants.Next, analyses assessed whether health or environmental harms were more effective at discouraging participants from wanting to eat red meat. These analyses used a linear mixed model, regressing harm-induced discouragement ratings on an indicator variable for whether the harm was a health or environmental harm, treating the intercept as random. We then assessed the extent to which each specific harm elicited discouragement using a linear mixed model with indicator variables for each of the sixteen harms (excluding one as the referent), again treating the intercept as random. We used v. environmental harms.To examine which population groups reported more discouragement in response to health and environmental harms of red meat, we also examined demographic predictors of average discouragement from wanting to eat red meat. First, we averaged discouragement ratings across all sixteen harms. We then used ordinary least squares linear regression to assess predictors of average discouragement. These analyses assessed the same demographic predictors as for awareness and additionally examined general perceptions that red meat is bad for health and for the environment. Exploratory analyses used the same approach to examine predictors of average harm-induced discouragement separately for health harms Analyses were conducted in 2021 using Stata MP version 16.1 (StataCorp LLC).sd 8·0) years (range: 19–80). About two-thirds were White (69 %), 18 % were Latino(a), 8 % were another race/ethnicity and 5 % were Black .For each of the sixteen harms, fewer than one-third of participants indicated awareness that red meat contributed to that harm Table . About oP = 0·029, Table P = 0·023). Likewise, those who identified as politically moderate  or conservative  reported awareness of fewer harms than those who identified as liberal. Participants who identified as Black reported awareness of more harms than those identifying as White , but identifying as Latino(a) or as another race/ethnicity (compared with identifying as White) was not associated with awareness. Higher educational attainment and higher income were generally associated with being aware of more harms. Usual red meat consumption was not associated with being aware of more health and environmental harms of red meat .In multivariate analyses examining predictors of the number of harms for which participants reported awareness, participants aged 26–34 years reported awareness of about 0·3 fewer harms of red meat compared with those aged 18–25 years . In analyses of awareness of environmental harms only, being age 26–34 years (compared with 18–25), identifying as female  and identifying as politically conservative  were associated with awareness of fewer harms . Higher education, higher income and higher usual red meat consumption were associated with awareness of more of the environmental harms of red meat.In analyses of awareness of health harms only, participants who identified as Black (compared with White) and those who had higher educational attainment reported awareness of a greater number of health harms. By contrast, participants who identified as politically moderate  reported awareness of fewer harms . Harms with higher awareness generally elicited higher discouragement , and heart disease was more discouraging than both prostate cancer  and worsening land quality .In mixed effects regressions of harm-induced discouragement, health harms elicited slightly more discouragement than environmental harms, but the magnitude of the difference was small (mean discouragement 2·73 P = 0·019). Those who identified as politically moderate  or conservative  were less discouraged by the health and environmental harms of red meat than those who identified as politically liberal. Participants who reported higher general perceptions that red meat is bad for health also reported higher average discouragement . By contrast, general perceptions that red meat is bad for the environment were not associated with average discouragement . Finally, participants who reported higher usual red meat consumption reported higher average discouragement . Gender, education, income and other race/ethnicities (i.e. Latino(a) and other race/ethnicity) were not associated with average discouragement . The pattern of results was similar when examining harm-induced discouragement separately for health v. environmental harms .In multivariate analyses examining predictors of average discouragement ratings, older participants generally reported lower discouragement than younger participants Table . Particiany of the sixteen harms examined. These results suggest a major opportunity to educate consumers and motivate positive behaviour change. Expectancy disconfirmation theory posits that when consumers receive negative information about a product that conflicts with their prior expectations (e.g. being informed about the harms of red meat when they had previously not known these harms), their attitudes towards the product will become more negative–56. This theory would suggest that correcting consumers’ misperceptions about the health and environment risks of red meat could motivate them to reduce their red meat consumption. In line with this prediction, one study found that warning messages about the health harms of sugary drinks led to larger changes in parents’ attitudes and purchase intentions when the messages were displayed on beverages parents had perceived as healthier compared with beverages parents already understood to be unhealthy.Results of this study suggest that messages describing the health and environmental harms of red meat could be a promising strategy for discouraging red meat consumption among US parents of young children. The majority of respondents were not yet aware of the specific health and environmental harms of red meat assessed in this study, and one-third were not aware of Regression analyses revealed that participants who were 26–34 years old (compared with 18–25 years), identified as female  and identified as politically moderate or conservative  reported awareness of fewer harms of red meat. By contrast, participants who identified as Black (compared with White) and those with higher educational attainment and higher income reported being aware of more harms. These results suggest that it may be beneficial to tailor awareness-raising campaigns to particular groups with lower awareness, such as parents who identify as female, are politically moderate or conservative or have lower educational attainment or income. However, given that the majority of participants were unaware that red meat contributes to the health and environmental harms assessed in this study, educational efforts are likely to benefit parents from all demographic groups..Participants’ usual red meat consumption was not related to their awareness of red meat’s health harms, but higher red meat consumption did predict higher awareness of the environmental harms of red meat. The reason for this association is unclear. One explanation is that higher red meat consumers are more likely to pay attention to information about the environmental consequences of red meat consumption because this information is particularly relevant to them, but have not yet acted on their awareness by reducing their red meat consumption. Regardless of the explanation, this finding highlights that interventions would likely benefit from incorporating a variety of strategies to reduce red meat consumption, including increasing the accessibility, availability and attractiveness of non-meat options–61. Younger adults also reported higher discouragement in response to health harms than older adults. This pattern of results differs somewhat from prior research finding that younger adults were less likely than older adults to report health reasons for not eating meat. Our results could potentially reflect a growing openness among young adults towards reducing their red meat consumption or consuming a plant-forward diet, regardless of the precise motivation for making dietary changes. Participants who reported higher red meat consumption also reported higher discouragement in response to health and environmental harms of red meat. This finding is encouraging, as it suggests that messages about the harms of red meat might have the greatest impact on those who stand to benefit the most from reducing their red meat intake. Additionally, participants who had stronger general perceptions that red meat is bad for health reported being more discouraged, on average, in response the specific health and environmental harms examined in this study. By contrast, general perceptions that red meat is bad for the environment were not associated with average discouragement ratings. These findings might suggest that strengthening the public’s general perception that red meat is bad for health could increase the public’s receptivity to messages about specific health or environmental harms. However, the observed associations between participants’ characteristics and their average discouragement ratings should be interpreted with caution because we cannot rule out the possibility that some demographic groups  might respond more strongly to any type of message presented in an online survey, even messages not about red meat. Studies that experimentally compare red meat messages to control messages are needed to establish whether characteristics like age, meat consumption, and general perceptions about red meat influence the effectiveness of red meat reduction messages on consumer behaviour.Several participant characteristics predicted higher discouragement from wanting to eat red meat in response to health and environmental harms. For example, consumers aged 18–25 years reported higher discouragement in response to environmental harms of red meat compared with those aged 26–34 and 35–44 years, perhaps because young adults have stronger interest in environmental sustainability and greater concern about climate change than older adults,21, alcohol and sugary drinks–25 have been shown to generate small but meaningful reductions in purchases and consumption of these products, suggesting that communicating about the harms of red meat could help curb red meat intake. We found that both health and environmental harms elicited similar levels of perceived discouragement. Likewise, a variety of health and environmental harms were similarly discouraging to consumers. These results suggest that message developers have many promising options for topics to address in meat reduction messages. The limited differences in mean discouragement observed between the specific harms also suggest that communication campaigns could easily rotate among these harms, a strategy that could help prevent messages from becoming ‘stale’ and losing efficacy over time.Communication interventions such as product warnings and mass media campaigns that describe the health harms of cigarettes,65,66, future research should confirm our findings with non-parents and with a wider range of ages. Additionally, although we did not query whether participants were vegetarian or vegan, about 13 % of our sample reported eating red meat less than 1 time per week during the past 30 d. Future studies may wish to examine awareness and discouragement specifically among non-vegans/vegetarians or among high red meat consumers, for whom messages may be most relevant. Another limitation is that we did not assess whether some consumers believe that red meat is beneficial for specific health and environmental outcomes; understanding whether these beliefs are widespread, and who is most likely to hold these beliefs, could help inform messaging campaigns. Additionally, this study focused on health and environmental harms because these are two of the key reasons that US adults report as motivating them to change their diet or reduce their meat consumption,67. However, consumers might also be motivated by other harms of red meat production. For example, a recent meta-analysis suggested that interventions appealing to animal welfare  hold promise for reducing meat purchases and consumption. We also did not assess other potentially important aspects of message design, such as message framing–71. Finally, while perceived message effectiveness is predictive of behaviour change, we did not assess behavioural outcomes. Future studies should experimentally evaluate the extent to which messages describing different types of harms of red meat reduce red meat purchases and consumption.The strengths of this study include the comprehensive set of health and environmental harms tested and the experimental comparison of how much each harm motivated participants to reduce their red meat consumption. Limitations include the use of a convenience sample of parents and the relatively young age distribution of the sample. Although prior studies indicate that online convenience samples can provide similar experimental results as probability samples. Our study suggests that communication interventions describing how red meat consumption affects both human and planetary health hold promise for informing US consumers and motivating reductions in red meat consumption.Reducing meat consumption is critical for mitigating climate change and reducing chronic disease burden


Background: Surface electromyography (sEMG) based robot-assisted rehabilitation systems have been adopted for chronic stroke survivors to regain upper limb motor function. However, the evaluation of rehabilitation effects during robot-assisted intervention relies on traditional manual assessments. This study aimed to develop a novel sEMG data-driven model for automated assessment.Method: A data-driven model based on a three-layer backpropagation neural network (BPNN) was constructed to map sEMG data to two widely used clinical scales, i.e., the Fugl–Meyer Assessment (FMA) and the Modified Ashworth Scale (MAS). Twenty-nine stroke participants were recruited in a 20-session sEMG-driven robot-assisted upper limb rehabilitation, which consisted of hand reaching and withdrawing tasks. The sEMG signals from four muscles in the paretic upper limbs, i.e., biceps brachii (BIC), triceps brachii (TRI), flexor digitorum (FD), and extensor digitorum (ED), were recorded before and after the intervention. Meanwhile, the corresponding clinical scales of FMA and MAS were measured manually by a blinded assessor. The sEMG features including Mean Absolute Value (MAV), Zero Crossing (ZC), Slope Sign Change (SSC), Root Mean Square (RMS), and Wavelength (WL) were adopted as the inputs to the data-driven model. The mapped clinical scores from the data-driven model were compared with the manual scores by Pearson correlation.Results: The BPNN, with 15 nodes in the hidden layer and sEMG features, i.e., MAV, ZC, SSC, and RMS, as the inputs to the model, was established to achieve the best mapping performance with significant correlations , according to the FMA. Significant correlations were also obtained between the mapped and manual FMA subscores, i.e., FMA-wrist/hand and FMA-shoulder/elbow, before and after the intervention . Significant correlations (P < 0.001) between the mapped and manual scores of MASs were achieved, with the correlation coefficients r = 0.91 at the fingers, 0.88 at the wrist, and 0.91 at the elbow after the intervention.Conclusion: An sEMG data-driven BPNN model was successfully developed. It could evaluate upper limb motor functions in chronic stroke and have potential application in automated assessment in post-stroke rehabilitation, once validated with large sample sizes.Clinical Trial Registration:www.ClinicalTrials.gov, identifier: NCT02117089. Stroke is one of the leading causes of upper limb disability and affects about 15 million individuals worldwide annually  , 29 hemiplegic participants with chronic stroke were recruited from local districts according to the following inclusion criteria: (1) ages ranging from 18 to 78 years, (2) at least 6 months after the diagnosis of a singular and unilateral brain lesion due to stroke, (3) able to extend the metacarpophalangeal and interphalangeal joints of the fingers to 170° passively, (4) MAS ≤ 3 for spasticity at the finger, wrist, and elbow joints during extension, (5) moderate to severe motor impairments in the affected upper limb as assessed by the FMA (15 < FMA < 45), (6) without cognition impairments as assessed by the Mini-Mental State Examination (MMSE) > 21  took less time to perform the evaluation task after receiving the intervention, while some participants did not improve the speed of movements.After the removal of the pauses in the evaluation, the average duration of the sEMG trials was 30.92 s , with a minimum of 9.8 s and a maximum of 51.8 s. The reason for the relatively large variation in the signal lengths was that some participants . The sEMG signals were subjected to the investigation of the mapping relationship with (1) the FMA subscores of the shoulder/elbow (FMA-SE) and the wrist/hand (FMA-WH), and (2) MASs for the elbow, wrist, and finger joints. For the mapping to MAS scores, the sEMG signals were further low-pass filtered (4th-order Butterworth filter) with different cutoff frequencies of 80, 150, 200, 300, 400, and 500 Hz. This was done in order to evaluate the mapping performance with an effective frequency domain, which would capture the features mainly related to slow involuntary contractures in a spastic muscle after stroke  sEMG feature extraction, (2) setup of the BPNN model, (3) configuration of the hidden layer, and (4) sEMG feature selection.Abstracted features of sEMG signals in the time domain have been adopted for the recognition of dynamic myo-activities , as follows:MAV is calculated by taking the average of the absolute value of sEMG signals ZC is the number of times that the amplitude value of sEMG signals crosses the zero axis, formulated as:SSC measures the number of times the sign changes in the slope of the sEMG signals, as follows:WL is the cumulative measure of the length of the signal, given as:The five features extracted from the segmented sEMG signals of the target muscles formed the input vectors to the BPNN whose output would be the mapped scores.A three-layer, i.e., one input layer, one hidden layer, and one output layer, BPNN was established as the data-driven model to investigate the mapping relationship between the extracted sEMG features and the clinical scales .k represented the kth sEMG epoch from the four muscles, and m. The projection for the mapping from the feature vectors to the output clinical scales can be described byThe essence of BPNN was to minimize the error of the network outputs with the derivatives of the error function . Then, the BPNN models with 10, 15, 20, 30, 40, 50, 100, 150, and 200 nodes in the hidden layer were trained by the 80% sEMG epochs and the corresponding FMA-WH and FMA-SE manual scores, both pre- and post-intervention sessions. The models were fed with the remaining 20% sEMG epochs during the testing stage, whose outputs were assessed for correlation performance with the manual scores in the testing set. FMA was employed in the model configuration because it was the primary outcome of the sEMG-driven robot-assisted intervention in this work. r, between the FMA scores and the mapped scores obtained using the BPNN model with different numbers of nodes in the hidden layer. A three-layer BPNN with 15 nodes in the hidden layer was used in this study, yielding strong correlations above 0.9 for both FMA-SE and FMA-WH  is the sEMG envelope signal obtained after normalization with respect to the maximal value of the muscle in the session, and T is the length of the signal trial. A decrease in the sEMG amplitude measured by the activation level of a muscle after rehabilitation could indicate the release of muscular spasticity  is the overlapping activity of sEMG linear envelopes for muscles i and j, and T is the length of the signal. An increase in the CI value represented increased co-contraction of a muscle pair (broadened overlapping area), and a decrease in the CI value indicated decreased co-contraction of a muscle pair (reduced overlapping area), i.e., better co-ordination , while the MASs did not. The comparisons between pre- and post-intervention sessions of the FMAs and MASs were evaluated by the paired t-test and Wilcoxon test, respectively. The level of statistical significance was set at 0.05, and significance levels at 0.01 and 0.001 were also indicated in the Results section.The normalized sEMG parameters , and the correlation coefficients decreased with the number of hidden nodes exceeding or less than 15. r = 0.93 for FMA-SE and r = 0.92 for FMA-WH, P < 0.001, was observed in the combination of MAV, SSC, RMS, and ZC. All feature combinations produced significant correlations (P < 0.01) between the mapped and the manual FMA subscores, and the minimum r was 0.54  when using only WL as the input feature. As the number of features in a combination increased, the correlation between the mapped and the manual FMA subscores was also enhanced. However, the combination of all five features led to a decrement of 0.3 and an increment of 0.1 on the correlation coefficient between the mapped and the manual FMA-SE and FMA-WH scores, respectively, compared to the maximum coefficient achieved by the combination of MAV, SSC, RMS, and ZC.r = 0.92 for FMA-SE, and r = 0.93 for FMA-WH, P < 0.001). The mapped FMA-SE scores ranged from 6.65 to 32.80 when the manual scores ranged from 5 to 30; the mapped FMA-WH scores ranged from 2.57 to 17.25 when the manual scores ranged from 2 to 20. The mapped scores were closer to the manual ones when the manual FMA-SE and FMA-WH scores were 11–24 and 2–9, respectively, than within other manual FMA-SE and FMA-WH score distributions. r = 0.93, P < 0.001) and FMA-WH scores . The mapped FMA-SE scores ranged from 12.84 to 39 when the manual scores ranged from 10 to 41; the mapped FMA-WH scores ranged from 6.22 to 21 when the manual scores ranged from 5 to 22. The mapped scores were the closest to the manual ones for manual FMA-SE and FMA-WH scores between 15–24 and 9–15 points, respectively. For both the pre- and post-intervention datasets, the correlation between the mapped FMA subscores and the manual scores were numerically high.P < 0.001) and 0.58 for FMA-WH (P < 0.001), respectively. The mapped FMA-SE and FMA-WH scores ranged from 13.37 to 35.85 and from 6.67 to 22.87, respectively. The distributions of manual scores were the same as those in P < 0.05). The correlation coefficient increased with increasing lowpass cutoff frequency and reached a maximum of 0.92 (P < 0.001) when the cutoff frequency was 200 Hz. The correlation decreased when the cutoff frequency was greater than 200 Hz. P < 0.001, MAS-elbow), 0.88 , and 0.91 . For the post-intervention dataset, the correlations between the mapped and manual scores were 0.92 , 0.80 , and 0.90 . The correlation coefficient between the mapped and the manual MAS-wrist scores observed in the pre-intervention data was larger than that of the post-intervention data. For the pre-intervention dataset, the distances between the mapped and manual MAS scores exceeded 0.5 when the manual MASs were graded at 0 and 3. For the post-intervention data, the distances between the mapped and manual MAS scores exceeded 0.5 when the manual MASs were graded at 0, 2, and 3.t-test, P < 0.05) muscles, and the activation levels of the BIC and FD muscles before the intervention were higher than those after the intervention. There were significant differences in the CI of the FD-BIC, FD-TRI, and BIC-TRI muscle pairs  before and after the interventions. The CI values detected before the intervention were higher than those after the interventions. No significant difference was observed in the sEMG parameters of other target muscles and muscle pairs. t-test, P < 0.05), and MAS scores, i.e., MAS-elbow, MAS-wrist, and MAS-finger , were observed between the pre- and post-intervention sessions. The pre-intervention FMA-WH and FMA-SE scores were lower than the post-intervention scores. The MAS-elbow, MAS-wrist, and MAS-finger scores before the intervention were higher than those obtained after the intervention. The differences in clinical scales before and after intervention are shown in r > 0.9, This study developed an sEMG data-driven BPNN model for mapping sEMG signals to two clinical scales, FMA subscores (FMA-SE and FMA-WH) and MAS, that have been widely adopted in clinical practices in post-stroke rehabilitation. The model was optimized by changing the number of the nodes in the hidden layer of the BPNN and the input feature vectors. The mapped FMA subscores and MAS scores generated by the data-driven model were strongly correlated with the manual scores r > 0.9, , 4, 7  in the hidden layer were evaluated. All models yielded high  and MU-firing-related features (ZC and SSC), which demonstrates that both the magnitude and MU firing information of the sEMG signals are essential for mapping performance. In addition, the performance of the models improved as the number of features in a combination increased. However, instead of the full combination of all five features, the combination of MAV, SSC, RMS, and ZC without WL produced the highest correlation coefficient between the mapped and manual scores, suggesting that WL might be a redundant feature that weakened mapping performance. Furthermore, WL alone yielded the poorest performance (r = 0.54) among all the combinations, also indicating that WL was not an effective feature for mapping the sEMG signals to the clinical scales of FMA. Therefore, in this work, the combination of MAV, SSC, RMS, and ZC was selected as the input vector for the BPNN. This optimized feature combination was consistent with a previous study of feature reduction and selection for sEMG signal classification  served as the input vectors to the BPNN model . All fear > 0.90) were observed between the mapped and manual FMA subscores, i.e., the FMA-SE and FMA-WH, before and after the intervention  hindered the model's effective generalization, i.e., recognizing completely new inputs, compared to those achieved this in the literatures usually with larger sample sizes   The limited sample size of the recruited subjects n = 2 hinderedThis study presented an sEMG data-driven BPNN model for mapping sEMG data in bare hand daily tasks to two widely used clinical scales, the FMA and the MAS. The combination of four features of sEMG  as the input vector into the BPNN model optimized the mapping accuracy. The high correlations between the mapped scores and the manual MAS and FMA subscores suggested that the sEMG data-driven BPNN model could evaluate upper limb motor functions based on sEMG signals. The results demonstrated the potential application in automated assessment without close professional operation, or supervision, by a clinician as in the evaluation of FMA and MAS for chronic stroke, once the external generalization of the model could be validated with large sample sizes.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.The studies involving human participants were reviewed and approved by Human Subjects Ethics Committee of Hong Kong Polytechnic University (HSEARS20130306005-04 and CRE-2013.283-T). The patients/participants provided their written informed consent to participate in this study.FY contributed to the construction of the data-driven BPNN model, data analysis, and manuscript drafting. BY contributed to the manuscript drafting. CN and YX contributed to the robotic-hand-assisted training experiment and data collection. XH and FC conceived of the study and coordinated the whole project, including the experiment design, model construction, and manuscript drafting. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The early diagnosis of leptomeningeal disease is a challenge because it is asymptomatic in the early stages. Consequently, it is important to identify a panel of biomarkers to help in its diagnosis and/or prognosis. For this purpose, we explored a multipronged proteomics approach in cerebrospinal fluid (CSF) to determine a potential panel of biomarkers. Thus, a systematic and exhaustive characterization of more than 300 CSF samples was performed by an integrated approach by Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) and functional proteomics analysis to establish protein profiles, which were useful for developing a panel of biomarkers validated by in silico approaches. In the present work, leptomeningeal disease, a very destructive form of systemic cancer, was characterized from several proteomics points of view. This pathology involves the invasion of the leptomeninges by malignant tumor cells. The tumor spreads to the central nervous system through the cerebrospinal fluid (CSF) and has a very grim prognosis; the average life expectancy of patients who suffer it does not exceed 3 months. The early diagnosis of leptomeningeal disease is a challenge because, in most of the cases, it is an asymptomatic pathology. When the symptoms are clear, the disease is already in the very advanced stages and life expectancy is low. Consequently, there is a pressing need to determine useful CSF proteins to help in the diagnosis and/or prognosis of this disease. For this purpose, a systematic and exhaustive proteomics characterization of CSF by multipronged proteomics approaches was performed to determine different protein profiles as potential biomarkers. Proteins such as PTPRC, SERPINC1, sCD44, sCD14, ANPEP, SPP1, FCGR1A, C9, sCD19, and sCD34, among others, and their functional analysis, reveals that most of them are linked to the pathology and are not detected on normal CSF. Finally, a panel of biomarkers was verified by a prediction model for leptomeningeal disease, showing new insights into the research for potential biomarkers that are easy to translate into the clinic for the diagnosis of this devastating disease. The leptomeninges are the two innermost membranes (arachnoid and pia matter) lining the brain and spinal cord. The cerebrospinal fluid (CSF) flows in between these membranes. Cancer cells may travel to the leptomeninges from other parts of the body via blood vessels or spread directly from the bones of the spine . LeptomeLM usually presents in patients with widely disseminated and progressive systemic cancer (>70%), but it can present after a disease-free interval 20%) and even be the first manifestation of cancer (5–10%), occasionally in the absence of other evidence of a systemic disease . The inc0% and evCurrently, the diagnosis and/or confirmation of LM is based on the detection of cancer cells by cytology (as gold standard) in CSF or by conventional flow cytometry immunophenotyping, together with the evaluation of neurological symptoms and imaging . HoweverFurthermore, CSF is considered as an excellent source for biomarkers in neuro-oncology diseases because it is in close contact with the nervous system ,21. The There is a pressing need for an accessible panel of biomarkers allowing for the rapid detection of LM in patients ,24. In cThere are multiple strategies for the identification of biomarkers in biological fluids, including those described by Philipp E. Geyer et al. (2017) , such asHerein, a discovery phase, with a limited number of well-characterized CSF samples (n = 12) corresponding to patients with CNS infiltration (+LM) and negative patients without infiltration (−LM), was performed by Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) in order to decipher differential protein profiles. Afterwards, a verification phase (n = 226) was performed by customized protein microarrays (266 antibodies (Abs) targeting 258 proteins) in order to define the intra- and inter-individual variability. This was followed by a validation or confirmation phase (based on affinity proteomics)  with the main goal of evaluating the sensitivity, specificity and accuracy of the potential biomarkers for the diagnosis and prognosis of LM.Subsequently, using multiple proteomics tools, differential protein profiles are obtained from a cohort (large enough) to reflect the prevalence and heterogeneity of patients in this pathology of interest. Furthermore, a potential panel of biomarkers was predicted in silico by selecting the most relevant proteins for each group of study. Overall, in this study, by the systematic and exhaustive characterization of the CSF (>300 samples) based on multipronged proteomics approaches, a potential panel of proteins with a discrimination capacity for diagnosis/prognosis, such as PTPRC, SERPINC1, sCD44, sCD14, ANPEP, SPP1, FCGR1A, C9, sCD34 and sCD19, among others, was formed.CSF was collected by National DNA Bank-Carlos III from the University of Salamanca, Spain, according to the recommended consensus protocol for CSF collection and Biobanking (in accordance with the Helsinki Declaration of 1975). The participants provided their written informed consent for research. These samples came from patients with B- and T-cell lymphomas; and B- or T-cell or myeloid leukemias, classified into two main groups of study, lymphoma and leukemia. Clinical characteristics of the CSF samples used in this study are shown in Normal CSF samples (1 mL) were provided by Lee Biosolutions . All of them were from donors which were negative for meningitis and other neurological diseases/disorders. Each sample was constituted as a pool from ≥3 donors. All the donors gave their written informed consent, and the supplier reported that the local institutional ethical committee approved the clinical protocol.A pool of 20 CSF samples was used for multiple purposes: (i) Evaluation of protein detection of high-abundant proteins in CSF; (ii) Evaluation of effect of CSF-stabilizing reagents on protein detection; and (iii) Determination of differential protein profiles in CSF +/− LM or +/− infiltration. In the g for 30 min at 4 °C. The supernatants were then completely evaporated to dryness in a vacuum concentrator centrifuge without heating, in order to remove ACN. The lyophilized acetonitrile soluble proteins were reconstituted in 25 μL of 2× Laemmli sample buffer in preparation for SDS-PAGE under denaturing conditions. (ii) Protein Depletion by Affinity Resins: briefly, an aliquot of 50 µL of pooled CSF was depleted following the detailed instructions described by the manufacturer . The supernatants and eluted proteins were then completely evaporated to dryness in a vacuum concentrator centrifuge without heating, to remove ACN. The lyophilized proteins were reconstituted in 25 μL of 2× Laemmli sample buffer and prepared for SDS-PAGE under denaturing conditions.Abundant proteins in human proximal fluids affected the accuracy of protein identification by LC-MS/MS, and this is a key point for CSF analysis, because it has a low protein content compared to other human proximal fluids . Hence, different strategies for protein depletion were assayed to evaluate their effect on protein identification from CSF samples by conventional LC-MS/MS. (i) Protein Depletion by organic solvent extraction: depletion was performed by following the method previously described by Fernandez et al., 2011, and Larssen et al., 2014 ,31. Briew/v) Coomassie Brilliant Blue solution. Polyacrylamide gels were then digitized with a gel reader and stored at 4 °C in an aqueous solution containing 1% (v/v) acetic acid until analysis.A total of 20 μg of total protein were run on 4–20% polyacrylamide precast Ready Gels  under reducing conditions. Gels were stained in a 0.5% (v/v) of 50 mM ammonium bicarbonate-acetonitrile. Next, dehydrated plugs with acetonitrile were treated with 10 mM dithiothreitol in 50 mM ammonium bicarbonate at 56 °C for 45 min and, subsequently, alkylated with 55 mM iodoacetamide in 50 mM ammonium bicarbonate at room temperature in the dark for 30 min. Protein digestion was stopped by addition of formic acid, and desalting was carried out by using C18-stage tips columns [m/z 400 to 1600 with 30,000 resolutions at m/z 400 with a lock mass option enabled for the 445.120025 ions [m/z precursor isolation width and wideband activation. The maximum injection time was 1000 and 50 ms for survey and MS/MS scans, respectively, and AGC was 1 × 106 for MS and 5 × 103 for MS/MS scans. Dynamic exclusion was enabled for 90 s.Each gel lane was manually cut in three fragments and digested with sequencing-grade trypsin , following the method described by Shevchenko et al., 1996, with slight modifications . Briefly columns . The sam025 ions . The 20 To biotinylate the samples, 10 μL of CSF  was mixed with 7.3 μL of 1 × PBS and 0.7 μL of NHSPEG4-biotin from a stock solution of 100 μg/μL N-hydroxysuccinimide ester- polyethylene glycol-biotin (NHS-PEG4-biotin)  in dimethyl sulfoxide (DMSO)  . After iv/v) propyl-methyl dimethoxysilane (MANAE)  as described by Gonzalez-Gonzalez M. et al. [®Printer Marathon vs. 1.4; Roslin, UK) with 12 identical subarrays, 99.91 µm of spot diameter; distance between spot was 0.4 mm horizontally and 0.2 mm vertically  targeting 258 proteins  (v/v) in a 47% (v/v) glycerol solution, according to ArrayJet®Printer Marathon specifications  (ii) Controls: NHS-PEG4-biotin (0.39 mg/mL) was prepared as a positive control. Spotting buffers +/− cross-linkers, in the absence of Abs, and BSA (0.6 mg/L to 3.66 mg/mL range) were prepared as negative controls [® Fluorescence Microarray Reader  at 532 nm emission wavelength. The array images were analyzed by GenePix® Pro 4.0 software  . All of  others)  were re-controls . All thecontrols . Then, esoftware . In all biotin 0. mg/mL wasoftware , by a quwww.proteinatlas.org, accessed on 8 March 2017, and 2 commercially available) (v/v) in dilution buffer . In total, 10 µL CSF and 6.7µL dilution buffer were pre-mixed and biotinylated, as described above, resulting in a 1:1 (v/v) final dilution of the samples. Blank wells (no sample) and pools were also included in the assay as technical replicates. After biotin-labelling, samples were further diluted 1:8 (v/v) in an assay reaction buffer (0.1% (w/v) casein, 0.5% (w/v) polyvinylalcohol, and 0.8% (w/v) polyvinylpyrrolidone in PBS 0.05% Tween 20 with 10% (v/v) rabbit IgG), transferred to a 384-well plate, and incubated overnight with the array. Sample read-out was performed by a FlexMap 3D system . Data analysis was rerun after the inclusion of the new clinical information. A background adjustment was performed per sample and antibody by (i) subtraction of the empty bead intensity signal  from the intensity signal detected for each single antibody in each sample, followed by (ii) the subtraction of the blank wells’ average intensity of each antibody in each sample well.Customized Beads Suspension Microarrays (Affinity Proteomics) were developed, targeting 89 proteins   as previIn this study, 12 CSF samples were analyzed by LC-MS/MS; 7 of which taken from patients with CNS infiltration (+LM), and the remaining 5 from the patients without infiltration (−LM). Using R interface , a one vAdditionally, two different restriction levels were applied, filtering the results: Universal-full detected protein set- and Unique-75-strictly detected protein set, which included all detected proteins with two or more unique peptides present in more than 75% of the samples of the same subgroup. For each variable studied, the number of common and exclusive proteins between all of the groups  was calculated.All raw files were converted to mgf using Proteowizard . Data fiGene Ontology (GO) Term Enrichment Analysis  and Pathway Enrichment Analysis  and 96 of them did not have infiltration (−LM) and were given a specific diagnosis that differentiated between malignant hemopathy and solid tumor.p < 0.001; H0: equal groups; H1: different groups).Using R interface based on the standardized data, a bioinformatics strategy was established in order to identify possible diagnostic CSF proteins that differentiated between the different groups of study, thus reducing the possible number of potential biomarkers by Bonferroni multiple testing correction and Wilcoxon test  and 196 were from patients without infiltration (−LM), with a specific diagnosis that differentiated between malignant hemopathy and solid tumor.p < 0.001; H0: equal groups; H1: different groups).As above, using R interface based on the standardized data, a bioinformatics strategy was established to identify proteins in CSF that allowed for the distinction between the different groups of interest, and thus reduced the possible number of potential biomarkers by Bonferroni multiple testing correction and Wilcoxon test   classifiFirstly, a limited number of well-defined CSF samples (n = 12) were characterized by LC-MS/MS as described in the Materials and Methods section . As CSF Regarding the protein depletion of high-abundant proteins in CSF, the side-by-side comparison of the conventional chromatography procedure with solvent  precipitation  and non-depleted  CSF at the first glance, did not yield huge differences in protein distribution; but, as expected, the relative protein abundance was altered, similar to small proteins (11–25 kDa) between the groups, and most of albumin seems to be removed in D-CSF. Regarding protein identification by both depletion strategies, 159 proteins were commonly and uniquely identified (≥2 unique peptides) . When th2+, extracellular matrix organization, complement cascade and its regulation, degradation of extracellular matrix, scavenging of heme from plasma and amyloids. Identified proteins in TM− have predominant functions associated with extracellular matrix organization and degradation, platelet degranulation and Ca2+ activation , which could affect the determination of protein profiles by LC-MS/MS. Accordingly, the number of identified proteins in CSF with TM (TM+) was 297 (non-redundant proteins) in comparison to 268 in CSF without TM (TM−) . In summtivation .Bearing in mind the effect on the CSF processing, a differential profile between CSF +/− LM can be established, which might be directly linked to the presence of tumoral cells in CSF. Here, 221 proteins were commonly determined, by LC-MS/MS, in CSF +/− LM, from 405 identified proteins in CSF-LM and 268 detected proteins in CSF + LM ; whereasConsidering the differential protein profiles observed by LC-MS/MS, a customized protein microarray, containing 266 Abs targeting 258 proteins. were used to screen 226 CSF +/− LM samples, as reported in p < 0.001; Test Wilcoxon; H0: CSF + LM and CSF-LM are equal; H1: CSF + LM and CSF-LM are different)  that discriminated between the analyzed CSF samples was investigated. To this end, as a starting point, LM +/− CSF were compared, and approximately 234 proteins showed significant differences (fferent) . In Figufferent) .Furthermore, it is interesting to note that differences in protein profiles are also observed within the group, CSF + LM, according to the primary tumor  . In the Bearing in mind the results and with the main goal to confirm them, 367 CSF +/− LM samples were analyzed by Beads Suspension Microarrays (targeting 89 proteins with 129 Abs) see . Therefore, a systematic comparison between groups of samples was performed as previously described, starting with CSF from patients with a pathology in comparison with CSF from healthy donors . Here, mIn a similar manner, protein profiles are different between CSF + LM in lymphoma and healthy donors , and betIn this screening, the protein distribution comparison within CSF + LM hemopathological groups, lymphoma versus leukemia , yieldedFrom the multipronged proteomics characterization , a robusConsequently, the ranking of proteins in each group of the study to perform the best separation on sensitivity and selectivity, in order to discriminate between CSF + LM and CSF-LM samples under the conditions described, was employed . To thisThe content of the proposed panel for CSF +/− LM is NCAM1, sCD34, ITGB1, sCD3, SERPINA4, MMP1, GSTP1, among others, which displayed an AUC (area under the curve) >90%, with a sensitivity and specificity of 100% by protein arrays and sensitivity of >75% and >91% specificity by affinity proteomics a. In theThe content of the proposed panel for CSF +/− LM (lymphoma) is PTPRC, SERPINC1, sCD44, sCD14, ANPEP, SPP1, FCGR1A, C9, sCD34, sCD19, CCND2, C1QB, NCAM1, TP53, PIM1; which displayed AUC 76.3% with a sensitivity of >81% and specificity of >62% for the protein arrays; meanwhile, AUC was >81% with a sensitivity of >71% and specificity of >73% by affinity proteomics , whereasLM is a devastating complication of malignancy that is characterized by the spread of cancer to the CNS and the formation of secondary tumors within the leptomeninges. Early detection of the disease and the early initiation of treatment remain essential to slow neurological deterioration . As prevThe critical need to identify therapeutic targets and potential biomarkers is reflected in previous proteomic studies of LM patients, where complement component 3 (C3) protein expression in primary tumors was found to correlate with disease relapse . In a siAnother proteomics study, reported by Smalley et al., analyzed 45 CSF samples from 16 melanoma LM patients by mass spectrometry and RNA sequencing, showing that CSF from most LM patients was highly enriched in pathways involved in damage mediated by protease, IGF-mediated signaling and innate immunity. Furthermore, there was a significant activation of the PI3K/AKT pathway, integrin, TNFR2, TGF-β, B-cell activation and oxidative stress that correlated with development of BRAF inhibitor resistance, leptomeningeal progression and poor survival ; or evenIn this study, a pipeline for biomarker discovery and validation  for LM fIn CSF, a large dynamic range between the most abundant proteins  and a very low number of abundant proteins in the detection range of ng/L exist, since high-abundant protein depletion is critical in CSF because of the expected low amount of proteins present. Therefore, a compromise with a high number of proteins identified and one-step depletion strategy was made, which allowed for the deciphering of relative, differential, quantitative protein profiles in the CSF +/− LM, included in this study. From this characterization, a total of 408 proteins were detected, which were considered as the starting point for the protein content in further screenings. From a functional point of view, most of the proteins were related to an acute inflammatory response, complement cascade, extracellular matrix organization, regulation chemotaxis, endothelial cell proliferation and its regulation, among others. Therefore, after a thorough analysis of protein function and relative abundance, 258 proteins, that are uniquely expressed in immune cells, as well as proteins related with onco-hemopathies, humoral responses (innate and adaptive), neurological tissues and endothelial cells, were selected. Then, a customized protein array was designed and developed to perform the screening of 226 CSF +/− LM (in a homogenous groups distributions) in order to define a potential panel of protein biomarkers from a differential protein profile obtained by high-throughput immunoassays. Starting from 258 proteins, after this screening, the number of proteins that could accurately distinguish between two tested groups was reduced to 51. Moreover, this screening by protein microarrays is simplified because it does not require pretreatment for sample processing and allows protein determination in a large dynamic range. Additionally, the functional analysis of these 51 proteins revealed that most of them are linked to the pathology.Therefore, the integration of diverse proteomics techniques shows great complementarity and compatibility, which means that the obtained results could be confirmed easily and translated faster into the clinic.Furthermore, 367 CSF +/− LM were screened by affinity proteomics . A potential panel of biomarkers, based on PTPRC, SERPINC1, sCD44, sCD14, ANPEP, SPP1, FCGR1A, C9, sCD34, sCD19, CCND2, C1QB, NCAM1, TP53 and PIM1, was confirmed in a different cohort of CSF +/− LM, observing a sensitivity and specificity of 85% and 71%, respectively. This selection of proteins displayed a similar ROC by protein array screening, which could be considered as an asset. The resultant potential panel of protein biomarkers is in agreement with a previous study by Iole Cordone et al. . In thatAside from this, it seems quite critical to continue searching for the best options to study CSF for the rapid, accurate and facile diagnosis LM, as these results show novel insights into the research for biomarkers with an easy translation for the diagnosis of this devastating disease; they might be compatible with other diagnostic strategies already successfully reported . Hence, a new hallmark in LM diagnosis could be opened from the multipronged diagnostic methodologies to stratify patients.These results suggest that differential protein profiles in CSF could be a unique source for biomarkers that would help in the diagnosis, prognosis, and monitoring of the evolution of leptomeningeal disease. Furthermore, protein microarrays can be considered as a useful methodological approach for the validation and confirmation of a potential panel of biomarkers, mainly because of their inherent capacity for obtaining fast, qualitative and quantitative information. In this study, a set of potential biomarkers were identified, validated and confirmed as a result of the systematic integration of multipronged proteomics approaches. In addition, this panel of biomarkers allows for the discrimination between CSF +/− LM with a high sensitivity and specificity, which might be considered as an asset for the usefulness of multipronged proteomics approaches for deciphering biomarkers in translational biomedical research.


Controlling for log KYNA/KYN, log ANTH was elevated in VFD-reared subjects versus controls. CSF log KYNA/KYN obtained post-RSP was positively correlated with mean social affiliation scores during RSP, specifically in VFD. ELS is associated with a reduced neuroprotective and increased neurotoxic pathway products. That the two contrasting processes are paradoxically correlated following ELS suggests a cross-talk between two opposing KP enzymatic systems.Early life stress (ELS) precedes alterations to neuro-immune activation, which may mediate an increased risk for stress-related psychiatric disorders, potentially through alterations of central kynurenine pathway (KP) metabolites, the latter being relatively unexplored. We hypothesized that ELS in a non-human primate model would lead to a reduction of neuroprotective and increases of neurotoxic KP metabolites. Twelve adult female bonnet macaques reared under conditions of maternal variable foraging demand (VFD) were compared to 27 age- and weight-matched non-VFD-exposed female controls. Baseline behavioral observations of social affiliation were taken over a 12-week period followed by the first cerebrospinal fluid (CSF) sample. Subjects were then either exposed to a 12-week repeated separation paradigm (RSP) or assigned to a “no-RSP” condition followed by a second CSF. We used high-performance liquid chromatography for kynurenine (KYN), tryptophan, 5-hydroxyindoleacetic acid, kynurenic acid (KYNA), and anthranilic acid (ANTH) as a proxy for quinolinic acid determination. At baseline, social affiliation scores were reduced in VFD-reared versus control subjects. CSF log KYNA and log KYNA/KYN ratio were lower in VFD-reared versus control subjects. CSF log KYNA/KYN was positively correlated with CSF log ANTH in VFD only ( The role of pathogenic neuro-immune activation is increasingly recognized in serious psychiatric disorders such as major depression, bipolar disorder, and schizophrenia . During Childhood adversity may represent an independent, yet potentially preventable, risk factor for altered neuro-immune activation that persists into adulthood . DysfuncNeuro-immune-mediated alterations of the KP catabolites have been of growing interest as a) acute KP activation may theoretically rapidly deplete tryptophan resources necessary for serotonin biosynthesis ; b) via QUIN concentrations, the final metabolite of the neuroexcitatory arm of the KP, are elevated in the lumbar cerebrospinal fluid (CSF) of MDD patients who attempted suicide in comparison to patients with MDD without suicidality . KYNA, bELS inevitably exerts epigenetic modifications that may exhibit persistent phenotypic effects across emotional development . The conIn this study, we seek to develop an understanding of psycho-neuro-immune development as pertains to kynurenine metabolism. The neurodevelopmental trajectory of KP metabolism and its modulation by early life experience are of clear translational significance. We hypothesized that ELS would be associated with significant alterations in key KP metabolites that suggest persistently elevated brain neurotoxicity and reduced neuroprotection. Further, we sought to demonstrate that these KP metabolite alterations would relate to behavioral profiles reflective of affective distress.1.Twelve adult variable foraging demand (VFD)-reared female subjects were studied. In order to provide an age- and weight-matched control, 27 non-VFD reared subjects were studied as a comparison see . As can For the VFD-rearing exposure, as previously described , mothersn = 12) that had been stabilized for at least 2 months , blinded to the rearing group. For 20 successive 30-s observation cycles, the presence or absence of social affiliative behaviors was identified for each animal within the social group. Thirty-second intervals were digitally timed using a tone delivered by headphones so that the tone could only be heard by the observer. Instances of hugging, grooming, receiving grooming, passive contact, and proximity were tallied and later summed to yield an overall affiliation score for each session. For the majority of subjects, a full 36 behavioral observation sessions were completed over a 12-week baseline period, generally on Mondays, Wednesdays, and Fridays . A similar number of behavioral observations were available for the RSP . The data is presented as the mean score/session collapsed over a 2-week block.Baseline behavioral observations were conducted over a 12-week period (data on 6 weeks are available) that preceded exposure or no-exposure to a repeated separation paradigm (RSP) protocol of 12 weeks (data are available on 10 weeks), during which behavioral observations identical to the baseline period were conducted. All observation sessions were conducted at the same general time of day (from 10 am to 1 pm) to control for any potential diurnal rhythms in social behavior. The behavioral ratings were conducted by a trained technician  was administered. Sedation of subjects was achieved in less than 5 min after exiting the carrying cage. Cisternal CSF sampling was performed immediately following sedation. CSF samples were then placed in Gant tubes and stored in a −70°C freezer. As part of the IACUC protocol, there is an option of administering analgesics in the event any of the animal subjects were experiencing pain or discomfort following the CSF draw. The procedure has been very well tolerated, and the subjects do not appear to experience pain or discomfort even when observed after the anesthetic and analgesic effects of ketamine have worn off.Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to analyze the extraction of CSF samples, using the method described by the Clinical Laboratory and Standards Institute . The samTM was used for analysis of all data. Outliers, which were defined as data points three deviations outside a mean that included both rearing groups, were to be excluded from the analyses. T-tests were performed to test for baseline characteristics. All kynurenine metabolites and their ratios were log-transformed to protect against non-homogeneity of variance. Non-parametric testing was used when appropriate. Generalized linear models were used to test for VFD rearing effects when using covariates. Factorial ANOVAs were used in the general liner model (GLM), generating an interactive term included in the overall model, specifically when comparing correlations between rearing groups. Significance was set at p ≤ 0.05, two-tailed.Age and weight of animals were matched and not used as covariates. Statistica 12.0 by StatSoftThe two groups were closely matched for age and weight and were not significantly different from each other .N = 12 vs non-VFD mean ± SD: 85.34 ± 4.75, N = 25; F1,34 = 6.01, p = 0.019).Affiliation scores combined the last two of the three 2-week baseline periods and used the first baseline period as covariate. There was an overall effect for group . There were no significant group effects for logged CSF tryptophan, kynurenine 5-HIAA, or anthranilic acid. Data related to ratios are presented below.Log KYNA was significantly lower in VFD-reared subjects versus non-VFD controls at baseline  , indicating that when controlling for log KYNA/KYN ratio, VFD exhibited elevations of log ANTH  in comparison to non-VFD . There was a significant effect for log KYNA/KYN ratio prediction of log ANTH  in a positive direction, when rearing groups are combined. There was, however, a marked VFD∗log KYNA/KYN interactive effect  reflective of a positive correlation between log KYNA/KYN and log ANTH in VFD  in comparison to non-VFD-reared controls   . To put  of 0.42 , where a∗RSP interactive effect  consistent with the view that CSF log KYNA/KYN ratio is reduced in VFD irrespective of whether subjects were exposed to the RSP or not. Although no overall effect of the RSP on CSF log KYNA/KYN was evident , a significant effect of VFD∗RSP interactive effect for CSF log KYNA/KYN was observed  (see N = 5 versus RSP: 3.01 (2.57 to 3.45), N = 17; post hoc least square difference (LSD); p < 0.025]. By comparison, VFD subjects exposed to RSP exhibit increases in CSF log KYNA/KYN in comparison to VFD with no RSP exposure . CSF log KYNA/KYN ratio of VFD subjects exposed to RSP was not distinguishable from non-VFD exposed to RSP  see . Non-VFD RSP see . A scatt RSP see .∗RSP interactive term, CSF log KYNA/KYN taken from the second CSF tap . However, only in the VFD subjects did CSF log KYNA/KYN ratio positively predict social affiliative behavior, whereas in non-VFD, this relationship was not evident . For example, in r = 0.82, N = 12, p = 0.007) in comparison to the corresponding correlation in the non-VFD subjects . = A repeated-measures∗VFD∗log KYNA/KYN three-way interactive effect  was observed .In order to control for the effects of RSP in relation to CSF log KYNA/KYN ratio and affiliative behavior, we entered the following variables into the GLM: VFD grouping, VFDrved see . Univarivior see . The mea∗CSF log KYNA/KYN∗repeated separation paradigm. This term was in fact significant . Post hoc Pearson’s correlations revealed that there was indeed a significant positive relationship between CSF log KYNA/KYN and mean social affiliation scores for the RSP-exposed subjects  versus RSP non-exposed subjects , supporting the view that the effects were due to the RSP-exposed subjects. There was no significant relationship between the mean baseline scores of social affiliation and CSF log KYNA/KYN derived from the second draw , indicating that this relationship in RSP-exposed subjects was not due to a pre-existing relationship evident prior to RSP exposure.It remained unclear whether the post-RSP CSF log KYNA/KYN correlation to social affiliative behaviors was indeed dependent on exposure to the repeated separation paradigm as only four of the 12 VFD subjects were in fact exposed to the RSP. We therefore conducted a GLM in which we used as the repeated measure the mean of the baseline three 2-week blocks and then the mean of the five RSP social affiliative behavior 2-week block tallies, categorical variable was whether there was exposure to the RSP paradigm, and CSF log KYNA/KYN derived from the second CSF draw served as the continuous variable. In addition, we used a factorial design that generated a three-way interactive term of repeated measuresThe social affiliative behavioral response to the repeated separation paradigm is covered in r = 0.82) is present—uniquely evident in VFD-reared subjects—and is suggestive of a synchronized activity between the neurotoxic and neuroprotective arms of the KP following ELS. The effect size of the VFD-specific synchronization exceeds a large effect size by a factor of three  matrix. The current study leverages a paradigm of ELS   and an aLimitations of the study include the examination of only female subjects. It is of note that human plasma KYNA levels are reduced in females and particularly women on oral contraceptives . It is upositively correlated specifically in VFD subjects. That these two opposing systems are positively correlated specifically in VFD implies persistent and coordinated cross-talk between the KAT and KMO enzyme systems. Only in VFD does exposure to the repeated separation paradigm reveal a novel relationship between social affiliation and kynurenine metabolites serving neuroprotection. Future studies are needed to establish the presence of perturbed inflammatory status in conjunction with KP metabolite alterations —a model which may serve as an invaluable opportunity for evaluation and development of novel therapeutic options.In summary, ELS is associated with persistent reductions in KP metabolites integral to the neuroprotective arm, such as KYNA, and increases of KP metabolites within the neuroprotective arm, such as ANTH. The collective findings suggest that developmental alterations in neuro-immune activity may extend to the KP in adulthood and may be behaviorally evident in changes of social affiliative behavior. Of note, the underactive neuroprotective arm and overactive neurotoxic arm evident in the current study are paradoxically The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The animal study was reviewed and approved by SUNY Downstate, Institutional Animal Care and Use Committee.SAS and JDC drafted manuscript, interpreted data, and critically revised manuscript through submission and acceptance. JDC completed analysis of data. RG, AR, JT, SF, and TP assisted with acquisition of data and made significant contributions to finalizing of manuscript.RG was employed by company Firstox Laboratories. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.