APOE) genotype testing, and amyloid PET. Among the potential predictors, verbal and visual memory tests, medial temporal lobe atrophy, APOE genotype, and age showed significant differences between the Aβ-positive and Aβ-negative groups and were combined to make a model for predicting amyloid PET positivity with the area under the curve (AUC) of 0.856. Based on the best model, we developed the new predictive scale comprising integers, which had an optimal cutoff score ≥ 3. The new predictive scale was validated in another cohort of 98 participants and showed a good performance with AUC of 0.835. This new predictive scale with accessible variables may be useful for predicting Aβ positivity in aMCI patients in clinical practice.The presence of amyloid-β (Aβ) deposition is considered important in patients with amnestic mild cognitive impairment (aMCI), since they can progress to Alzheimer’s disease dementia. Amyloid positron emission tomography (PET) has been used for detecting Aβ deposition, but its high cost is a significant barrier for clinical usage. Therefore, we aimed to develop a new predictive scale for amyloid PET positivity using easily accessible tools. Overall, 161 aMCI patients were recruited from six memory clinics and underwent neuropsychological tests, brain magnetic resonance imaging (MRI), apolipoprotein E ( Mild cognitive impairment (MCI) has been considered as a transitional state between normal aging and dementia . Since tAD is neuropathologically diagnosed based on the deposition of amyloid-β (Aβ) plaques and pathologic tau proteins . As the Although these AD confirmatory diagnostic modalities have been used as enrollment criteria for research, their application in primary care clinical settings is still difficult. CSF testing is an invasive test that the patients may be reluctant to undergo. Amyloid PET scans have the issue of high cost, availability of PET scanners, and radiation exposure ,9. Thus,Although several longitudinal studies have developed models for predicting the conversion of MCI to AD dementia, AD was estimated clinically, not pathologically ,11,12,13APOE) epsilon 4 (ε4) allele  PiB) or 18F-florbetaben ([18F] FBB). Nine subjects underwent [11C] PiB PET (Siemens) and 138 subjects underwent [18F] FBB PET  scans. The standard uptake value ratio (SUVR) was obtained for [11C] PiB images to determine amyloid PET positivity [18F] FBB PET was evaluated visually by a trained nuclear medicine specialist in each center using brain amyloid plaque load (BAPL) score.All participants underwent one of the following two amyloid PET tests: sitivity . [18F] FFor the validation cohort, 98 aMCI subjects were recruited from the Inha University hospital in South Korea. The inclusion criteria of the validation cohort were the same as those of the original group. To validate the new predictive scale of amyloid PET positivity, the scale was applied to the validation cohort set. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performance. Area under the curve (AUC) value, sensitivity, and specificity were calculated at the optimal cutoff score of the newly developed scale.In this cross-sectional study, Student’s t-test was used to analyze the continuous variables, while the chi-square test was used for the dichotomous variables. Based on the results of the comparison between Aβ+ and Aβ− subjects, potential predictors were selected. Pearson’s correlation analysis was conducted to determine the association between the potential predictors as well as to exclude the correlates.APOE-ε4 carrier, a score of 1 was given, while if the subject was an APOE-ε4 noncarrier, a score of 0 was given.The selected significant continuous variables were converted to categorical variables to maximize their utility in clinical practice. Since the two groups of Aβ+ and Aβ− subjects were divided based on the average age of 70 years, 1 point was given to those aged 70 or older and 0 point to those under the age of 70. For SNSB, subjects with higher than −1.0 SD were scored as 0, while subjects with lower than −1.0 SD were scored as 1. The presence of MTA was determined and scored as 1 if MTA aVRS was ≥2. If the subject was an Univariate logistic regression analysis was applied to predict amyloid PET positivity with each potential predictor. Subsequently, these predictors were combined to develop several models using multivariate logistic regression analysis. The ROC curves for all models were analyzed to assess their predictive ability for amyloid PET positivity. The model with the highest AUC value was selected as the most appropriate model for predicting amyloid PET positivity. To detect multicollinearity between the predictors in the model, variance inflation factor (VIF) statistics were calculated. The calibration of each prediction model was assessed using the Hosmer–Lemeshow goodness-of-fit test.The most appropriate model could generate a new predictive scale based on the regression β coefficients from the multivariate logistic regression analysis. The β coefficients values were adjusted to the nearest integer to develop a simple integer-based modeling scale. ROC curves were constructed to determine the diagnostic ability of the scale. The optimal cutoff score of the scale was calculated using the Youden’s index.p < 0.05.For statistical analysis, Statistical Package for the Social Sciences was used . Statistical significance was defined as a probability value of APOE-ε4 carriers (43.5%). A total of 78 participants (48.4%) showed Aβ positivity in amyloid PET.The average age of the 161 subjects was 69.88 ± 7.23 years (mean ± SD). Of the subjects, 90 (55.9%) were women and 71 (44.1%) were men; also, the subjects consisted of 70 p = 0.034), but not in sex (p = 0.086) and education (p = 0.685) between the Aβ+ and Aβ− groups. However, there were no significant differences in the cardiovascular risk factors, such as hypertension, diabetes mellitus, hyperlipidemia, and heart disease, as well as stroke and cancer.APOE genotypes of the subjects according to the amyloid status. Among neuropsychological tests, Aβ+ subjects showed significantly lower z-scores of SVLT-DR, RCFT-DR, and K-BNT than Aβ− subjects . Compared to the Aβ− group, the Aβ+ group was more likely to have both verbal and visual memory impairments rather than either visual or verbal memory alone (p < 0.001). The K-MMSE score of the Aβ+ group was lower than that of the Aβ− group (p < 0.001). Aβ+ subjects had higher global CDR and CDR-SB scores than Aβ− subjects . Aβ+ subjects had lower MTA aVRS than Aβ− subjects (p < 0.001). The proportion of APOE-ε4 carriers among Aβ+ subjects was significantly higher than that among Aβ− subjects (p < 0.001).APOE genotype, and age. Correlation analysis of the variables demonstrated that K-MMSE had a correlation with SVLT-DR (p < 0.001), RCFT-DR (p < 0.001), K-BNT (p = 0.030), global CDR (p < 0.001), and CDR-SB (p < 0.001). Global CDR and CDR-SB also showed significant correlation with SVLT-DR, RCFT-DR, K-BNT, and K-MMSE. Thus, K-MMSE, global CDR, and CDR-SB were excluded when constructing the models.Potential predictors that showed significant differences between the Aβ+ and Aβ−groups were extracted, including SVLT-DR, RCFT-DR, K-BNT, K-MMSE, global CDR, CDR-SB, MTA aVRS, APOE-ε4 carriers , and age (odds ratio (OR) 2.340, 95% CI 1.207–4.538) were associated with amyloid PET positivity. However, K-BNT (p = 0.207) did not demonstrate significance in the univariate analysis. Since all aMCI patients subjects already had either impaired visual or verbal memory, the aOR of both aMCI with both visual and verbal memory impairment was calculated and compared to single aMCI with only visual or verbal memory impairment .APOE genotype were included in the multivariate analyses after adjustment for age. These predictors were combined to develop the following models:Model 1: included age, both aMCI.Model 2: included age, both aMCI, MTA aVRS.APOE genotype.Model 3: included age, both aMCI, APOE genotype.Model 4: included age, both aMCI, MTA aVRS, Both aMCI with both visual and verbal memory impairment, MTA aVRS, and Multivariate analyses showed that predictors in all models had significant ORs .APOE-ε4 carrier . VIF values of all variables were <4 , indicating that there was no multicollinearity among the predictors. The Hosmer−Lemeshow test for model 4 verified that the model fitted well with the data .APOE-ε4 carrier, based on the value of the β coefficients. In the scale, a higher score had a higher probability of Aβ positivity (score range: 0–5).To develop a new predictive scale based on a simple integer scoring system, the regression β coefficients generated from the multivariable analysis of model 4 were simplified. The β coefficients were divided by the β coefficient of MTA aVRS, which was the lowest at 0.981 among all predictors. They were rounded to the nearest integer for the scoring system. ROC curve analysis  shows thAmong the 98 aMCI patients subjects in the validation cohort, 34 (34.7%) were amyloid PET positive. APOE genotype, and the neurodegenerative marker of MTA VRS. As the prevalence of MCI due to AD increases, this practical scale will be valuable for recognizing Aβ positivity in the prodromal stage.Our study developed a new predictive scale for detecting amyloid PET positivity with easily accessible variables in aMCI subjects. To our knowledge, this is the first predictive scale consisting of integers to identify Aβ+ aMCI subjects by using a combination of the neuropsychological memory domain, This predictive scale has the following distinctive strong points. Firstly, the scale can be applied quickly and cost-effectively in clinical practice where amyloid PET evaluation is difficult to access as amyloid PET is a costly and uncommonly used equipment. Several studies have attempted to predict amyloid PET positivity in aMCI participants. These studies required advanced testing tools such as MRI volumetry ,36,37,38APOE genotype, cognitive status, and MTA [Few studies have attempted to detect Aβ positivity among aMCI subjects with commonly available variables. Kim et al. developed a nomogram for predicting Aβ+ aMCI . This no and MTA . HoweverSecondly, this new scale can predict amyloid PET positivity with high specificity in aMCI patients. In the present study, the specificity was high at 86.7% for the optimal cutoff value of the scale. This study was not intended to screen aMCI patients but to develop a scale for predicting Aβ positivity among those diagnosed as aMCI. It will be helpful not only for implementing clinical care but also in the research field. Studies on AD treatment drugs have not been successful, probably due to the difficulty recruiting Aβ+ aMCI patients. The proportion of Aβ+ patients among MCI patients is known to be only 40–60% ,45; the Third, all subjects underwent amyloid PET scans in this study. There have been several observational longitudinal studies on conversion from MCI to AD dementia, but the subjects were diagnosed clinically with probable AD dementia ,46,47,48APOE ε4 allele was found to be an essential factor for the development of Aβ positivity, in line with the results of previous studies [APOE genotype variable showed the highest aOR in univariate and multivariate analyses . Further study of the associations between the BAPL score and the scale score can be investigated. Finally, although memory impairment in MCI is the most distinguishing feature of Aβ positivity [Our study has the following limitations. First, when this predictive scale was validated, the specificity was not very high at 62.5%. It may be because the positive rate of amyloid PET in the validation cohort was 34.7%, which is less than the commonly known 40–60% among aMCI patients ,45. Neve studies ,65. A nusitivity ,66, Aβ pAPOE genotype were revealed as the critical predictors of Aβ positivity in subjects with aMCI, and (2) the new predictive scale comprising these factors can be easily applied in clinical practice.Despite these limitations, the advantages of this study are as follows: (1) both aMCI, MTA aVRS, and APOE ε4 allele are associated with Aβ load in the brain of aMCI patients. Integration of these predictors was used to develop a new predictive scale of integers to detect Aβ positivity in aMCI patients with a cutoff score of ≥3. The scale can be used conveniently to predict AD and prognosis of aMCI patients in clinical practice.This study shows that verbal and visual memory impairment, MTA, and the


Head and neck cancer (HNC) and its treatment often negatively impact swallowing function. The aim was to investigate the course of patient-reported swallowing problems from diagnosis to 3, 6, 12, and 24 months after treatment, in relation to demographic, clinical, and lifestyle factors.Data were used of the Netherlands Quality of Life and Biomedical Cohort Study in head and neck cancer research (NET-QUBIC). The primary outcome measures were the subscales of the Swallowing Quality of Life Questionnaire (SWAL-QOL). Linear mixed-effects models (LMM) were conducted to investigate changes over time and associations with patient, clinical, and lifestyle parameters as assessed at baseline.Data were available of 603 patients. There was a significant change over time on all subscales. Before treatment, 53% of patients reported swallowing problems. This number increased to 70% at M3 and decreased to 59% at M6, 50% at M12, and 48% at M24. Swallowing problems  were more pronounced in the case of female, current smoking, weight loss prior to treatment, and stage III or IV tumor, and were more prevalent at 3 to 6 months after treatment. Especially patients with an oropharynx and oral cavity tumor, and patients receiving (C)RT following surgery or CRT only showed a longer eating duration after treatment, which did not return to baseline levels.Half of the patients with HNC report swallowing problems before treatment. Eating duration was associated with sex, smoking, weight loss, tumor site and stage, and treatment modality, and was more pronounced 3 to 6 months after treatment. Head and neck cancer (HNC) is the seventh most common cancer worldwide, accounting for an estimated 650,000 new cases and 350,000 deaths every year . HNC is n = 2458) provided a survey at baseline, and 4 and 12 months post-baseline [To evaluate patient-reported outcomes (PROs) regarding dysphagia, several tools are available such as the swallowing subscale of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-H&N35), the M.D. Anderson Dysphagia Inventory (MDADI) , 18, andbaseline . This stbaseline .Unlike the EORTC QLQ-H&N35 questionnaire , the SWAL-QOL questionnaire includes multiple subscales to assess swallowing-related quality of life. Multiple studies assessed swallowing as measured with the SWAL-QOL, either as prospective cohort study to investigate swallowing differences over time , 20–24 oTo reduce the risk for persistent patient-reported swallowing problems after treatment for HNC, it is important to identify factors associated with these swallowing problems. Information can be provided about possible problems that may occur after treatment and the possibility of rehabilitation during and after treatment can be discussed. This will lead to a better evaluation of possible treatment options and more patient-centered care. As mentioned, previous research about the SWAL-QOL mainly focused on one type of treatment modality, or one type of tumor site , 29. In The primary aim of this study was to investigate the course over time in the first 2 years after HNC diagnosis of various aspects of patient-reported swallowing problems as measured with the SWAL-QOL. The secondary aim was to identify demographic, clinical, and lifestyle factors associated with patient-reported swallowing problems in patients with HNC.Data were used of 739 patients with HNC participating in the prospective NETherlands Quality of Life and Biomedical Cohort study in HNC cancer (NET-QUBIC), of which details were published previously , 33. RecThe primary outcome measure was the 47-item Swallowing Quality of life Questionnaire (SWAL-QOL) . This quBaseline characteristics about age, sex, ACE-27 comorbidity score , TNM7 clDescriptive statistics were used to describe the study population. Differences between the total NET-QUBIC population and patients that filled in the SWAL-QOL were tested using ANOVA to assess differences in age, and chi-square tests were run to test for differences in sex, tumor site, tumor stage, primary treatment, alcohol consumption, smoking, comorbidity, and weight loss.2 laser, surgery with post-operative (C)RT), tumor stage consisted of 4 levels  [p < 0.10 level were removed, beginning with the interactions. A hierarchical structure was maintained, meaning that if an interaction was included in the model, the main effects were also represented in the model. Risk factors were reported as estimated unstandardized regression coefficients with 95% confidence intervals (CI) and p-values.Linear mixed models (LMM) were used to assess if demographic, clinical, and lifestyle factors influenced changes over time of the total score and all subscales of the SWAL-QOL. Akaike’s Information Criterion (AIC) was used to select the most appropriate covariance structure to fit the data . To accoanyN3M0) , sex conp-values < 0.05 for the descriptive statistics and < 0.10 for the linear mixed-effects model were considered statistically significant.The coefficients of the significant covariates, together with the value of the intercept of the mixed model analysis, were combined into a formula for the estimated SWAL-QOL subscale. The intercept is the value of the estimated SWAL-QOL subscale in which all coefficients remain zero. Addition of the coefficients will lead to an increase or decrease of the estimated SWAL-QOL subscale. This formula can be used to estimate the QOL of patients during the follow-up period. For each time point, the formula was filled with average variable values for significant coefficients, as calculated by a restricted maximum likelihood approach. All analyses were performed using Statistical Package for the Social Sciences (SPSS) version 25 . Among the 739 patients participating in the NET-QUBIC research, 603 patients filled in the questionnaire at least once during the 2-year follow-up and were included in the LMM analyses. At baseline, 553 patients completed the SWAL-QOL questionnaire, 516 at 3 months, 464 at 6 months, 427 at 12 months, and 374 at 24 months , after which these scores returned to baseline at 6 months after treatment and beyond Fig. . There w2 laser treatment  showed no decline after treatment.The factors alcohol, comorbidity, HPV status, age, and the interaction between timing of assessment and tumor stage were not associated with eating duration and were therefore removed from the model. The factors sex, smoking, weight loss, tumor site, treatment, tumor stage, and timing of assessment were associated with a worse eating duration Table . The eatThe LMM analyses revealed that the total score and the subscales “general burden,” “food selection,” “eating desire,” “fear of eating,” “mental health,” “social functioning,” and “symptoms” scored worse when the patient was a smoker at baseline, had more comorbidities at baseline, and received CRT or surgery followed by (C)RT. In addition, receiving CRT or surgery followed by (C)RT led to more deterioration shortly after treatment. Having a more advanced tumor stage (stages III and IV) also resulted in a worse outcome for the total score and subscales “general burden,” “food selection,” “eating desire,” “fear of eating,” “mental health,” and “symptoms.” Having a tumor in the oral cavity led to worse outcomes on the total score and subscales “general burden,” “food selection,” “eating desire,” “mental health,” “social functioning,” and “symptoms.” Losing weight before treatment resulted in a worse outcome on the total score and subscales “general burden,” “social functioning,” and “symptoms.” Patients with a higher age showed a worse outcome on the subscales “food selection” and “eating desire.” Drinking alcohol regularly led to less problems on the subscales “mental health” and “social functioning.”n = 603) identified factors associated with worse swallowing as measured with the SWAL-QOL in patients with HNC and all treatment modalities. In this study, it was shown that patient-reported problems with swallowing increased from baseline to 3 months after treatment, and slowly decreased from 6 months onwards with return to baseline levels at 2 years after treatment in patients with HNC. Based on the SWAL-QOL cut-off score of ≥ 14, which indicates swallowing problems in daily life, 53% of patients had problems before treatment, which increased to 70% at 3 months after treatment and decreased to 59% at 6 months after treatment, 50% at 12 months after treatment, and 48% at 24 months after treatment. After treatment, the subscale eating duration showed the most problems and did not return to baseline. Therefore, this subscale was used in a LMM to identify factors associated with a worse eating duration, to indicate which patients could benefit from preventive strategies and rehabilitation during and after treatment. Eating duration was associated with sex, smoking, weight loss, tumor site, treatment, tumor stage, and timing of assessment. In addition, the interactions of timing of assessment with tumor site and treatment modality were significant, indicating that the course over time differed for different tumor sites and different treatment modalities.This large 2-year prospective cohort study (n = 52) found a deviant score in 79% of patients, which is higher than the 70% found in this research at 3 months after treatment. One explanation could be that almost 60% of the patients in that study were treated with 3D conformal RT, in which salivary glands were not spared. After 2005, IMRT was introduced, enabling a significant reduction of dose to the salivary glands [n = 111, mean age = 56 years, 44% male) showed that mean scores of all subscales were between 3.7  and 10.4 (fear of eating) [Based on a cut-off score on the total SWAL-QOL score of ≥ 14 points , a previy glands . Since ty glands . Another eating) . Althougn = 2458) as measured with the EORTC QLQ-H&N35, and found that multi-modality treatment, oropharynx tumors, age, sex, living alone, low socio-economic status, and smoking were outcome predictors [n = 529), and showed in their multivariate analysis that T3-T4 HNC tumors, bilateral irradiation, weight loss, oropharynx tumors, accelerated RT, and concomitant CRT were related to a worse outcome [n = 587) from 2016 found the following factors to be associated with less HNC symptoms: older age, higher education, private insurance, no current tobacco use, alcohol use, no comorbidities, early stage cancer, and no current feeding tube [n = 52) investigating tumor site and RT technique in a multivariable regression analysis found that only tumor site was significantly associated with total SWAL-QOL score [n = 110) in patients receiving RT or CRT found that advanced tumors, patients receiving CRT, use of a nasogastric tube, tracheotomy, and continuation of smoking and drinking alcohol decreased QOL [A prospective cohort study from 2021 investigated factors associated with swallowing and social eating . A limitation of this study was the fact that only 374 patients filled in the questionnaire 2 years after treatment [The strengths of this study were the prospective study design, the large number of patients, and the use of the LMM checklist with recommendations for reporting multilevel data and analyses . Becausereatment , 33. Thereatment . TherefoPatients with HNC reported an increase in swallowing problems from baseline to 3 months after treatment, and a slow decrease from 6 months onwards with return to baseline level at 12 and 24 months. The subscale eating duration of the SWAL-QOL showed the most problems after treatment. A longer eating duration was associated with female sex, smoking and weight loss at time of diagnosis, having tumor stage III or IV, and being 3 to 6 months after treatment. Especially patients with an oropharynx and oral cavity tumor showed a persistent increase in eating duration. In addition, patients receiving (C)RT following surgery and patients receiving CRT only showed the worst decline in outcomes, which did not return to baseline levels after treatment.


Encephalopathy of prematurity (EoP) affects approximately 30% of infants born < 32 weeks gestation and is highly associated with inflammation in the foetus. Here we evaluated the efficacy of montelukast, a cysteinyl leukotriene receptor antagonist widely used to treat asthma in children, to ameliorate peripheral and central inflammation, and subsequent grey matter neuropathology and behaviour deficits in a mouse model of EoP. Male CD-1 mice were treated with intraperitoneal (i.p.) saline or interleukin-1beta  from postnatal day (P)1–5 ± concomitant montelukast (1–30 mg/kg). Saline or montelukast treatment was continued for a further 5 days post-injury. Assessment of systemic and central inflammation and short-term neuropathology was performed from 4 h following treatment through to P10. Behavioural testing, MRI and neuropathological assessments were made on a second cohort of animals from P36 to 54. Montelukast was found to attenuate both peripheral and central inflammation, reducing the expression of pro-inflammatory molecules  in the brain. Inflammation induced a reduction in parvalbumin-positive interneuron density in the cortex, which was normalised with high-dose montelukast. The lowest effective dose, 3 mg/kg, was able to improve anxiety and spatial learning deficits in this model of inflammatory injury, and alterations in cortical mean diffusivity were not present in animals that received this dose of montelukast. Repurposed montelukast administered early after preterm birth may, therefore, improve grey matter development and outcome in EoP.The online version contains supplementary material available at 10.1186/s12974-022-02625-5. Preterm birth occurs in 11% of live births worldwide , with 30Whilst white matter (WM) injury has been the historical focus of preterm brain injury studies, there is increasing evidence of the importance for grey matter (GM) injury in this condition . NeuropaThe underlying causes of EoP are multifactorial and most likely interlinked, with intrauterine growth restriction –23, inflThe cysteinyl leukotrienes (CysLTs) are a family of highly potent pro-inflammatory mediators, derived from arachidonic acid via the 5-lipoxygenase pathway. They have been associated with a range of neuroinflammatory diseases including cerebral ischaemia , 40, AlzMontelukast is an attractive candidate for repurposing; it is currently utilised as an asthma medication; it has a good safety profile and is approved for administration to infants from 6 months of age. In addition, studies have shown that it is safe and that there are predictable changes in its pharmacokinetics in 0- to 6-month-old infants , 61. HerA model of preterm brain injury was used in this study, whereby exposure to systemic inflammation from postnatal day 1 (P1) to P5 induces diffuse WM injury , 34, 52 n = 3–9 per group, specific numbers for each experiment detailed in results and figure legends), or histological analysis (n = 3–6) at 0.5, 1, 4, 8 and 24 h, as well as at P2, P5 and P10. Twelve animals per group (2/litter) were used for behaviour testing (P36–54), after which tissue was collected at P54 for MRI and histological analysis. Animals from these litters not used for behavioural studies (2–4 per litter) were used at P40 for histological analysis of brain tissue. Animal numbers were based on power calculations  using previous data from this model [CD-1 time-mated females were purchased from Charles River and were singly housed in individually ventilated SPF cages under standard diurnal lighting conditions (12 h) with ad libitum access to food and water. Consistent with the previous studies using this model, only male pups were used due to a sex bias in this model whereby females do not display myelin deficits . Therefois model , 33.n = 1), the remaining were frozen until use. For the assessment of systemic inflammation, fresh liver was collected and immersed in TRIzol reagent (ThermoFisher) for RNA extraction. Brains were then dissected for mass spectroscopy (fresh frozen), RNA extraction (TRIzol), protein extraction (protein extraction buffer) or for histology following paraformaldehyde perfusion . Fixed samples were processed to paraffin wax prior to coronal sectioning at 5 μm thickness, using the Leica RM2245 Microtome .Prior to tissue collection animals were terminally anaesthetised with pentobarbital . Blood samples were collected by cardiac puncture using a 25 g needle, for the assessment of plasma drug and cytokine levels. Following collection, blood samples were centrifuged for 5 min at 4000 rpm and the plasma removed. Heavily haemolysed plasma samples were discarded (©) as per manufacturer’s instructions. qRT-PCR was completed with 200 ng of RNA, using TaqMan RNA-to-CT1-Step Kit (Applied Biosystems), with a StepOnePlus Real-Time PCR system (Applied Biosystems). Relative quantification of expression was determined by the 2−ΔΔct method, normalised to the expression of the housekeeping gene GAPDH, as previously described [RNA was extracted from liver and brain samples using RNeasy Mini Kit . Initial experiments were performed to optimise the mass spectroscopy parameters  to dete4, LTD4 and LTE4, collectively) was determined for each sample using a competitive ELISA assay, in duplicate and at two dilutions, following manufacturer’s instructions .Protein concentration in the brain was quantified with BCA assay (ThermoFisher). The concentration of cysteinyl leukotrienes (LTCLycopersicon esculentum (tomato) lectin . Biotinylated secondary antibodies  were used, followed by HRP  and DAB prior to imaging and analysis.Immunostaining was performed using an avidin–biotin–peroxidase (ABP) method, with 3,3′-diaminobenzidine (DAB) for visualisation. Sections were incubated overnight (4 °C) in one of the following primary antibodies, diluted in 1% NHS block: Goat anti-serum albumin , rabbit anti-parvalbumin , mouse anti-MBP , mouse-anti-CNPase , mouse anti-ICAM-1 , goat anti-GFAP  and For assessment of general tissue structure, sections underwent staining with haematoxylin and eosin (H&E).Micrographs of immunohistochemically stained tissue sections were acquired using a light microscope  with bright and fluorescent light capacity, CCD colour video camera , and equipped with a motorised stage (MicroBrightfield Inc.).Stereo Investigator software  or ImageJ (NIH), following semi-automated or manual tools as previously described [All histological image analysis was performed blinded to treatment group using escribed , 68, 69.2. At P10, arborisation was assessed using an ImageJ classifier to detect parvalbumin-positive arbours within the region of parvalbumin-positive cell. Arbour density was determined relative to total cell number. At P40, when arbours were more clearly delineated, Image J was used to specifically identify arbours attached to immune-reactive cell bodies, and the number and area of identified arbours was assessed. Parvalbumin-positive puncta, indicating synapses from parvalbumin neurons [For parvalbumin-positive interneurons, cell counts were performed manually throughout the hippocampus or from a region of interest (ROI) from the sensory (barrel) cortex , 33, 51, neurons , that cob-values of 1000, 4000 and 8000 s/mm2, respectively; an isotropic voxel size of 100 µm with a field of view of 12.8 × 12.8 mm2, echo time (TE) = 40.8 ms, and repetition time (TR) = 1000 ms; 13 reference images with b = 0 s/mm2 were acquired . Total acquisition time was 88 h per subject. Of the 35 scans acquired, five were excluded following visual quality check , due to artefacts produced from air bubbles and/or excessive vibration during the scan. Pre-processing was performed to correct eddy-current, and B1 bias using FSL [b = 4000 s/mm2 shell data using FSL [http://mig.cs.ucl.ac.uk/index.php?n=Tutorial.NODDImatlab; [py), stratum radiatum (CAsr) and stratum lacunosum moleculare (CAslm) of the CA1 region as well as the dentate gyrus (DG), and white matter ROIs were placed in the corpus callosum (CC), left and right external capsules (EC) and the anterior commissure (AC). Median DTI and NODDI metrics for each ROI were calculated for each subject in native space, and mean values compared between treatment groups.Ex vivo MRI was performed after PFA perfusion-fixation of tissue, followed by immersion fixation at 4 °C and PBS washing . Diffusising FSL  and MRtrsing FSL . Diffusising FSL  and FA aImatlab; ). A popuImatlab; , and ROIA series of behavioural tests were performed to determine whether montelukast was able to alleviate the behaviour deficits observed with this model of preterm brain injury. Three cohorts of animals were tested, with 4 animals per treatment group (2 per litter) in each cohort. Behavioural testing was spread over a 2-week period, with no more than one behavioural test completed each day, after which the animal was returned to their home cage. In all cases the experimenter was blinded to treatment and animals were tested in a pseudo-randomised order, counterbalanced between each behavioural test, and steps taken to ensure testing was performed in a clean, olfactory neutral environment. Data were recorded and analysed with EthoVision tracking software (Noldus) .General locomotor activity and baseline anxiety were tested with the open field paradigm, which measures the conflict between a rodent’s exploratory behaviour and aversion to open, exposed areas . Time spA light–dark box test was used to measure anxiety, based on the conflict between rodents’ exploratory behaviour and aversion to open and brightly lit areas , 79. ForThe Morris water maze (MWM) was performed to assess spatial learning , 81. Anip < 0.05 and reported as statistically significant based on injury or treatment effect, as well as after multiple comparison correction for specific comparisons. Quantitative data are expressed as mean ± standard error of the mean (SEM).All statistical analyses were completed with GraphPad Prism 7 software using one- or two-way analysis of variance (ANOVA), as appropriate. Post hoc testing was performed either to compare every mean with every other mean (Tukey’s test), selected pairs of means (Sidak’s test) or every mean to a control mean (Dunnett’s tests) depending on experimental design. Results were considered significant at p < 0.001, p = 0.034 after post hoc test for TNF: SAL vs IL1). At this time point, the increased expression of IL-1β and TNF persisted in animals receiving both montelukast and IL-1β . However, the expression of IL-6 was significantly ameliorated by montelukast , with expression levels comparable to saline and montelukast controls. By 24 h, the hepatic inflammatory response was substantially reduced, with no significant increase in inflammatory gene expression found in the IL-1β treated animals .In this inflammatory model of preterm brain injury, IL-1β was injected intraperitoneally in male CD-1 mice to provoke a systemic inflammatory response. This in turn induces central inflammation, and the associated structural deficits in the brain , 33. To p < 0.001; SAL vs IL1 p < 0.001, p = 0.016 and p = 0.050 for IL-1β, IL-6 and TNF, respectively; and IL1 vs IL + MO p = 0.002, p = 0.018 and p = 0.042 after post hoc test; Fig. p = 0.047; TNF: 1.01 ± 0.06 SAL vs 1.91 ± 0.42 IL1, p = 0.020). Montelukast significantly decreased expression of TNF , IL-6 (6.36 ± 1.74), and TNF (5.47 ± 1.50) were significantly elevated at 4 h compared with saline-treated controls; this elevation was completely ameliorated by high-dose montelukast . At both ages, the IL–MO group was not significantly different from either the SAL or IL1 group .Next, we sought to identify the lowest effective dose in this inflammatory model of preterm brain injury. As a marker of central inflammation, relative gene expression of IL-6 in the brain was measured 4 h post-injury Fig. E. Resultp = 0.007), and was not significantly different from the control, despite remaining 2.5-fold higher than the saline only group  and significantly different from the injury group (p < 0.001). As such, 3 mg/kg was determined as the lowest dose completely effective at reducing central inflammation.Montelukast significantly reduced IL-6 expression in a dose-dependent manner; administration of the 1 mg/kg dose reduced expression significantly compared to the injury group  interneurons at P10. The high dose of montelukast was used to determine the maximum capacity for montelukast to protect from short-term cellular injury. The density of PV+ interneurons were significantly decreased in the barrel cortex in IL-1β-treated animals (85 ± 4 cells/mm2) compared to saline controls . While there was a change in cell number, no alterations in the arborisation of the existing PV+ interneurons were detected , in addition to a significant difference between treatment groups (p = 0.018). Following post hoc analysis assessing effect between treatment groups, a significant decrease in FA was found between the saline group and the group treated with IL-1β and montelukast .We performed a diffusion MRI and neuropathological assessment of the cortical GM to determine any long-term structural effects of postnatal inflammation and low-dose 3 mg/kg) montelukast as a potential therapy. Assessment of FA  and treatment group  and was the only difference statistically significant after post hoc testing. MD in IL + MO was not significantly different from SAL or IL animals. Orientation dispersion index (ODI) and neurite density index (NDI) showed median values per group inversely proportional to those calculated for FA and MD, respectively , with a reduction of fibres in the radial direction. This was normalised with montelukast . As with the open field test, there were no general changes in locomotion that could have confounded this finding  and latency (p = 0.001) to platform, and increase in velocity  over the multiple trials and days of the experiment . Animals treated with montelukast showed improved learning; with increasing trials, there were significant decreases in the distance travelled and latency to reach the platform  at a rate comparable to the saline group , whMontelukast was successful at ameliorating the established central and, to a lesser degree, peripheral pro-inflammatory response. It is still unclear how inflammation is specifically signalled from the peripheral to the central compartment of the body in this perinatal injury model, and whether montelukast exerts its effects directly on the brain. There were small but significant increases in the expression of CysLTR1, the receptor target for montelukast, and CysLT concentrations in the brain following systemic inflammation that suggest montelukast could have its actions centrally, should it be able to access the receptors. Age and brain region-specific alterations in blood–brain barrier permeability have previously been reported in models of perinatal brain injury , 89, 90,Injury to cortical parvalbumin interneurons has previously been described in this model , a cell Similarly, an increased MD in the cortex in the inflammatory-injury group was not detected with montelukast treatment. Interestingly, a decrease in FA was observed only with a combination of inflammatory injury and montelukast treatment, compared to saline-treated controls. Assessments of normal early human , 97 and Montelukast was able to protect from inflammation-induced behavioural deficits in a mouse model of EoP. Improvements in anxiety and spatial learning were evident, which coexisted with the normalisation of parvalbumin interneurons early in development, and long-term organisation of cortical myelinated fibres as well as absence of the inflammation-induced increase in MD. Collectively, these findings suggest that GM injury may play a greater role in EoP than previously appreciated. Certainly, deficits in parvalbumin interneurons have been associated with these specific behaviour changes , 100. InWork remains to determine the clinical situations in which this preventative approach is most appropriate, as some of the inflammatory drive may start prior to birth. Our hypothesis suggests that preventing inflammatory signalling from the periphery to the brain can limit down stream injury but does require therapeutic targeting of this inflammatory response early in the disease process. This can be tested in our preclinical mouse model and should be considered for meaningful evaluation of montelukast’s potential in future clinical trials. Of note, this preventative/ameliorative action was not seen on the early white matter injury, suggesting either an increased susceptibility of myelin to inflammatory injury that was not completely ameliorated or an interaction between montelukast and the developing oligodendrocytes that warrants further investigation. While this hypothesised mechanism is of scientific interest, and will be investigated, the key finding of ameliorated neuropathology is clearly evidence of the potential utility of this therapeutic approach. Future studies should also consider the broader beneficial potential of montelukast of other inflammation-associated pathologies in the preterm infant .In conclusion, this study has demonstrated the importance of GM injury in EoP and that montelukast is a safe, repurposable drug. Montelukast is an effective treatment at reducing central inflammation, normalising parvalbumin interneuron numbers, and behavioural deficits associated with EoP in an inflammatory model of preterm brain injury. We therefore propose that montelukast has potential as a novel therapy for preterm brain injury.Additional file 1: Figure S1. Effect of montelukast on CysLTR1 and CysLT in the brain. Figure S2. IL-1β induces vascular inflammation, but not BBB breakdown. Figure S3. No improvement of white matter damage is evident following montelukast treatment in this model. Figure S4. No hippocampal damage evident in this model. Figure S5. Inflammation and/or montelukast treatment does not induce motor deficits.


G are reportedfor interfaces between nitride metals and group IV  and group III–V  materials.Group IV and group III–V semiconductors have systematic differencesin vibrational properties. Similarly, HfN and TiN are also vibrationallydistinct from each other. Therefore, comparing G ofinterfaces formed from these materials provides a systematic testof how vibrational similarity between two materials affects interfacialtransport. For HfN interfaces, we observe conductances between 140and 300 MW m–2 K–1, whereas conductancesbetween 200 and 800 MW m–2 K–1 are observed for TiN interfaces. TiN forms exceptionally conductiveinterfaces with GaN, AlN, and diamond, that is, G > 400 MW m–2 K–1. Surprisingly,interfaces formed between vibrationally similar and dissimilar materialsare similarly conductive. Thus, vibrational similarity between twomaterials is not a necessary requirement for high G. Instead, the time-domain thermoreflectance experiment (TDTR) data,an analysis of bulk vibrational properties, and transmission electronmicroscopy (TEM) suggest that G depends on two othermaterial properties, namely, the bulk phonon properties of the vibrationallysofter of the two materials and the interfacial structure. To determinehow G depends on interfacial structure, TDTR andTEM measurements were conducted on a series of TiN/AlN samples preparedin different ways. Interfacial disorder at a TiN/AlN interface addsa thermal resistance equivalent to ∼1 nm of amorphous material.Our findings improve fundamental understanding of what material propertiesare most important for thermally conductive interfaces. They alsoprovide benchmarks for the thermal conductance of interfaces withwide band gap semiconductors.The goal of this study is to determine how bulk vibrationalpropertiesand interfacial structure affect thermal transport at interfaces inwide band gap semiconductor systems. Time-domain thermoreflectancemeasurements of thermal conductance  Due to betterthermal performance, SiC devices have aided in the development ofgreen technologies such as electric vehicles5 and wind turbines.6 Wide band gap materialsalso offer advantages for high-frequency telecommunications electronics.8 The high critical field of GaN allows high-frequency GaN electronicsto outperform RF devices consisting of small band gap materials.7 Further gains in performance of high-power andhigh-frequency electronics require semiconductor materials with evenwider band gaps than SiC or GaN.8 Therefore,there is an urgent need to understand the materials physics of ultra-wideband gap materials such as AlN, Ga2O3, cubicBN, and diamond.8 The focus of this studyis to advance fundamental understanding of interfacial heat transferin wide and ultra-wide band gap material systems.Devices made from wide band gap semiconductorscan outperform theirsilicon-based counterparts.9 Thermally resistive interfacesalso hinder device reliability.10 The effectof interfaces on thermal transport is characterized by the interfacialthermal conductance per unit area G. The conductance G relates the heat current at the interface, J, to the temperature drop, ΔT, at the interface, J = −GΔT.Decades of research have firmly established the phenomenology of G in small band gap material systems, for example, Si.11 However, an experimental understanding of G in wide and ultra-wide band gap materials is emergingonly now.14Understandingthe physics of interfacial thermal transport is criticalbecause thermally resistive interfaces limit the maximum power beforedevice failure.15 Ga2O3,14 SiC,15 and diamond systems.17 Research has also shown that interfacial chemical reactions canlead to larger G,18 while a fewnanometers of crystalline disorder at the interface leads to lower G.15 Despite these advances,important gaps in the fundamental understanding of G remain. These include the effect on G of: (i) vibrationalsimilarity of the materials forming the interface; (ii) complex unitcells; and (iii) interfacial structure. A fundamental understandingof vibrational similarity and complex unit cells is particularly importantfor high-power electronic applications. Candidate device heterostructuresfor high power applications often involve heterostructures composedof vibrationally dissimilar materials, for example, AlGaN/GaN/diamond.19 Other device heterostructures involve materialswith complex unit cells, such as β-Ga2O3 or 4H-SiC.8Recent studies have shown that strong chemicalbonds are a pre-requisitefor conductive interfaces in GaN,G that occur because of changes in interfacialbonding strength or interfacial chemical reactions.Nitride metals areamong the most vibrationally stiff metals. Theirvibrational stiffness allows one to study the upper limits to theinterface conductance of wide and ultra-wide band gap materials. Here,we report time-domain thermoreflectance (TDTR) measurements of theinterface conductance between nitride metals and group IV materials:diamond, SiC, Si, and Ge. We also measure transport between nitridemetals and group III–V crystals: AlN, GaN, and cubic BN. Thegroup IV and group III–V materials have systematic differencesin acoustic properties; see 2/Arenvironment using an AJA Orion Series sputtering system. Because oxygenhas a detrimental effect on the transport properties of nitride metals,we took several steps to reduce oxygen content in the chamber priorto deposition. To reduce the pressure of the sputtering chamber below3 × 10–7 Torr, it was baked at approximately100 °C for at least 12 h prior to deposition. Prior to deposition,titanium was sputtered as an oxygen getter material for 10 min. Thebase pressure of the chamber was further reduced by circulating liquidnitrogen through coils within the chamber.Nitride metal films were depositedusing reactive DC magnetron sputtering in a mixed N20Prior to depositionof the nitride metal, the substrates were subjected to heat and plasmatreatments. Substrates were heated to ≈450 °C for 20 minin order to vaporize hydrocarbons or other physisorbed molecules presenton the surface. The heating temperature of the substrates is onlyapproximate because the temperature was measured at the heating sourcerather than the sample stage. Then, the substrates were RF sputter-etchedat 3.5 mTorr and 35 W for 5 min in an effort to increase the strengthof interfacial bonds between the nitride metal and substrate. BriefRF sputter etching has been shown previously to change interfacialbonding and enhance interfacial thermal transport at diamond surfaces.2/Ar partial pressureswere selected through an iterative process that used refs  scans of the TiN surface morphologyare shown, as well as Raman spectra from the TiN and HfN films.The deposition temperatures and Nsed refs  and 22)2/Ar part2O3 and MgO). TiNand HfN were also deposited on Si with (100) orientation and SiO2/Si with (100) orientation wafers from University Wafers ascontrol samples. The (0001) 4H-SiC substrate, (0001) 6H-SiC substrate,(100) Ge substrate, (0001) GaN film on sapphire, and (100) 3C-SiCfilm on Si were purchased from MTI Corporation. Cubic BN crystalswere purchased from Hyperion Materials & Technologies, Inc.The TiN and HfN films were deposited on group IV crystals, group III–V crystals , and oxide crystals on a 1 cm2c-plane sapphire substrate.Nb and Ti were supplied using an e-beam evaporator, with flux measuredand controlled using an electron impact emission spectroscopy (EIES)system. The Nb2N film was grown at a substrate temperatureof 1150 °C, with an active nitrogen flux that exceeded the Nbflux. Growth at these temperatures is found to yield single crystalβ-Nb2N films, with the c-axis alignedto the sapphire c-axis. The AlN film was grown bynucleating the film growth with an active nitrogen flux, which exceedsthe aluminum flux, which was discovered to be necessary to preventreaction of any excess aluminum with the underlying Nb2N. This nucleation was approximately 100 nm in thickness and is grownat 725 °C. The remaining AlN growth is completed at 825 °Cwith an aluminum flux greater than the active nitrogen flux, suchthat aluminum droplets accumulate on the sample surface, which isa well-known growth condition to yield high crystal quality and lowroughness AlN grown by MBE.23 Prior togrowth of the TiN layer, all accumulated aluminum droplets are thermallydesorbed by heating the substrate to 1000 °C, a temperature thatgives rapid evaporation of liquid Al. The TiN was then grown at asubstrate temperature of 1000 °C. The TiN was grown under nitrogen-richconditions at a growth rate of approximately 2.3 nm/min.In addition to sputter-deposited TiN/AlN samples prepared as describedabove, we studied a TiN/AlN interface prepared via MBE. The growthof TiN on AlN films was performed in a Veeco GENxplor system witha base pressure less than 1 × 102O3, MgO, and GaN substratesto be between 0.2 and 2 nm. Raman spectra were performed on HfN andTiN on Si and MgO substrates in the backscattering configuration using633 nm (red) laser excitation wavelength with a cutoff frequency of110 cm–1. The Raman spectra are consistent withstoichiometric growth of TiN on both Si and MgO substrates (see Supporting Information). The electrical resistivityof all nitride films was measured with the four-point probe method.Typical resistivity values for the TiN and HfN films were 30–70μΩcm but varied with substrate (see Supporting Information). TEM provided measurements of filmthickness and interfacial structure. Samples suitable for observationin cross section by TEM were prepared using a dual-beam Helios G5UXsystem. Observations were made using a Phillips-FEI CM200 FEG-TEMoperated at 200 kV and an image-corrected FEI Titan 80-300 operatedat 300 kV.To characterize samples aftersynthesis, we did transmission electron microscopy (TEM), atomic forcemicroscopy, Raman spectroscopy, and electrical resistivity measurements.Atomic force microscopy revealed surface roughness of diamond, CVDAlN, polycrystal AlN, Al24 The pump beam heatsup the metal transducer, for example, TiN or HfN metal, resultingin transient evolution of the surface temperature. A time-delayedprobe pulse measures the fluctuation of the sample’s reflectancecaused by the change in surface temperature. The wavelength of thelaser in these experiments is centered at 783 nm, and the pump beamis modulated at 10.7 MHz. The intensity of the reflected probe beamis measured using a silicon photodetector. Optical filters are usedto prevent the reflected pump beam from reaching the detector. Thephotodiode is connected to an RF lock-in amplifier, which measuresin-phase and out-of-phase voltages as a function of delay time. Theratio of the in- and out-of-phase temperature response to pump heatingis then determined. Further details on the experimental setup canbe found elsewhere.25TDTR is an optical pump/probetechnique used to measure thermal transport properties in thin filmsand at interfaces.24 The thermal model uses thethermal conductivity, heat capacity, and the thickness of each layeras inputs and predicts the corresponding temperature response. Unknownthermal properties are adjusted until the predictions of the thermalmodel agree with the experimental data. Literature values for theheat capacities of TiN, HfN, and all the substrates were used as inputsfor the model. The metal thicknesses and thermal conductivity werefixed as described in Supporting Information. The interfacial thermal conductance and substrate thermal conductivitywere treated as fit parameters. 2 K, respectively.ExperimentalTDTR signals are compared to the predictions of a thermal model, whichis a 3D analytical solution to the heat diffusion equation for a multilayerstructure.–2 K–1; see –2 K–1. To quantify differences in the vibrational properties in the semiconductorsstudied, Gmax was calculated for eachgroup IV and III–V material. Gmax of a material .Irrespective of the vibrational properties of the substrate,all studied HfN interfaces have comparable heat-carrying abilities.The interface conductance of HfN and the group IV semiconductors rangesbetween 140 and 200 MW min refs  and 27)–2 K–1; s diamond 3a despitG between TiN and group IV materialsand group III–V materials plotted as a function of Gmax of the substrate. For the TiN/group IV semiconductors,a weak positive correlation is observed between G and Gmax. An increase in G from ≈200 ± 20 MW m–2 K–1 for TiN/Ge to ≈500 ± 50 MW m–2 K–1 for TiN/diamond is observed. Alternatively, for groupIII–IV materials, there is no significant correlation between G and the vibrational properties of the substrate, thatis, G and Gmax. G for TiN/group III–V nitrides ranges from 300 to500 MW m–2 K–1.In contrast to HfN, TiN forms highly conductiveinterfaces withthe wide and ultra-wide band gap semiconductors. For example, G of ≈550 ± 100 MW m–2 K–1 was observed between TiN and a high-purity element-sixELSC grade {100} diamond. A similar value was measured for G of ≈500 ± 40/90 MW m–2 K–1 between TiN and a lower-grade element-six {100} CVDdiamond substrate. Finally, a third TiN/diamond sample was preparedafter wet-etch removal of the original TiN layer on the lower-gradeelement-six diamond. To remove the TiN film, the sample was dippedin HF for ∼10 s; the sample was then dipped in a mixture of4:1 KOH/H2O2 at 70 °C, for approximately10 min until the TiN had been etched. Diamond is notoriously resistantto wet chemical etching.29 Nevertheless,the TiN on wet-etched diamond had the lowest G of≈320 ± 30 MW m–2 K–1. The extra thermal resistance at the TiN/wet-etched diamond interfacewas equivalent to resistance from ∼1 nm of amorphous carbonwith a thermal conductivity of 1 W m–1 K–1.To evaluateand confirm the reproducibility of the interface conductancevalues for several material systems, as reported in G for TiN/MgO ≈ 550 ± 50MW m–2 K–1, HfN/MgO ≈ 200± 20 MW m–2 K–1, TiN/Al2O3 ≈ 350 ± 50 MW m–2 K–1, and HfN/Al2O3 ≈140 ± 20 MW m–2 K–1.In addition to the group III–V and group IV substrates,conductance between the nitride metals and sapphire and MgO was alsomeasured. The G reported in G. Many prior experimental studies have reached the opposite conclusionand reported that vibrational similarity between two materials isan important governor of thermal interface conductance.32 60GPa,28 and ZnO/GaN.36 Alternatively,some of the lowest reported values for G are forinterfaces between vibrationally dissimilar materials, for example,Pb/diamond,33 Au/Ga2O3,37 and Al/graphene.38 By compiling the results of a number of experimental studies,Giri and Hopkins32 and Koh et al.39 pointed out a positive correlation between theratio of elastic moduli of the constituent materials and the thermalboundary conductance. A number of experimental studies have explainedexperimentally observed trends for G in metal/insulatorsystems as a consequence of vibrational overlap between the metaland insulator.37Prior conclusions that vibrational similarity is animportant determinerof G. Many prior experimental studies report how G of various metal/insulator systems vary as the metal is changed.38 Changing the metal alters not only how vibrationally similar themetal and insulator are but also interfacial bonding18 and the phonon irradiance of the metal.28 The strength of interfacial bonds between a metal and a substratevaries, and weak interfacial bonds lead to low G.26 The current study tries to minimize such effects by focusing oniso-valent material systems. Another difference between the currentstudy and prior work is that the data set in G is affectedby changes to vibrational properties of both the metal and substrate.This makes it easier to distinguish between how changes in bulk vibrationalproperties effect phonon irradiance33 versusenergy transmission. We discuss the issue of phonon irradiance versusenergy transmission in more detail in a later section focused on transportphysics analysis.There are key differences in the design of the current experimentalstudy and prior work. Some of these differences make the current dataset a more direct test of the effect of vibrational similarity on G between nitride metals and 3C-SiC, 4H-SiC,and 6H-SiC was measured. All three polytypes of SiC consist of covalentlybonded Si and C atoms as building blocks, and they differ from eachother only in stacking sequence. The 3C-SiC polytype has a cubic crystallattice structure with 4 atoms in the conventional unit cell, while4H-SiC and 6H-SiC have hexagonal lattice structures, with 8 and 12atoms in the conventional unit cell, respectively. For both HfN andTiN, the measured interface conductances of 4H-SiC, 6H-SiC, and 3C-SiCare comparable. For TiN, G for TiN on SiC-6H andSiC-4H lie in the range 250–350 MW m–2 K–1, and G for TiN SiC-3C is ≈230± 30 MW m–2 K–1. For HfN,we observe that G for HfN/SiC-3C and HfN/SiC-6H arein the range of 170–230 MW m–2 K–1, and G for HfN/SiC-4H is ≈140 ± 20MW m–2 K–1. These results indicatethat increasing cell complexity of the SiC polytypes does not havea significant effect on G.Unit cell complexity can affect the vibrational structure of a material.With an increase in the number of atoms per unit cell, more phononmodes are in optical phonon branches, which tend to have lower groupvelocities. To evaluate how unit cell complexity affects interfacialtransport, G. To our knowledge, ref (G. In ref (G of Pton YIG.40 Both YIG (20 atoms pre unit cell)and 6H-SiC (12 atoms per unit cell) have large basis unit cells. However,the 6H-SiC unit cell is significantly less complex than YIG. The differencebetween 3C-SiC versus 4H-SiC versus 6H-SiC crystals involve minordifferences in stacking sequence of atomic planes along the c-axis. Therefore, Si and C atoms are likely to have localbonding environments similar to Si and C atoms with different basispositions.To date, there havebeen few studies of how unit cell complexity affects dge, ref  is the o. In ref , AngelesG depends on interfacial structure,a series of different TiN/AlN samples were prepared. We then studiedinterfacial transport between (1) sputtered TiN films and CVD-grownepilayers of AlN on sapphire, (2) sputtered TiN films and polycrystallineceramic AlN, and (3) MBE-grown TiN film on an MBE-grown AlN layer.For the sputtered TiN deposited on CVD-grown AlN samples, the effectof AlN surface treatments prior to TiN deposition was also explored.To determine how G as a functionof substrate roughness are shown in A total of six TiN/AlN samples were studied. Details of the samplesand the associated surface treatments prior to TiN deposition arereported in –2 K–1 for all three surface treatments. G for TiN on CVD AlN from DOWA is ∼400 ± 50/20MW m–2 K–1. Therefore, we concludethat the surface treatment of the substrate does not affect the conductanceof reactively sputtered TiN/AlN samples. Rather, it appears that reactivesputtering of the TiN introduces some intrinsic interfacial disorderindependent of surface treatments or AlN surface morphology. The interfaceconductance for TiN on polycrystalline ceramic AlN ∼700 ±50 MW m–2 K–1 is higher than the G for the sputtered TiN on CVD AlN epilayers. AFM showedaverage grain sizes of 5 nm for polycrystalline AlN. To test if grainmorphology affects the TDTR response of the sample, measurements weredone with a laser spot size of 1.6 nm. Small spot size measurementsyielded nearly identical results for G as large spotsize measurements. Finally, the G for the TiN/AlN/NbN/sapphiresample grown by molecular beam epitaxy is the highest at ∼800MW m–2 K–1.The lowest conductance was observed for TiN sputterdeposited onthe CVD-grown AlN epilayers. The reactive DC-sputtered TiN on CVDAlN from Kyma Technologies is ∼450 ± 50 MW mSupporting Information.Cross-sectionaltransmission electron micrographs were used tobetter understand the differences in interface morphology betweenthe sputtered and MBE-grown TiN samples. TEM images were collectedon three TiN/AlN samples. These include the MBE-grown sample, theas-received sample, and the RF-etched TiN on AlN samples. G from∼800 to ∼450 MW m–2 K–1. In relative terms, the differences in conductance observed forthe various TiN/AlN samples are large. However, in absolute terms,the differences in conductance are relatively small because all studiedTiN/AlN interfaces have a high conductance. The sputtered TiN interfaceshave an “extra” thermal resistance of only 0.75 m2 K/GW in comparison to the MBE sample, which is equivalentto ∼0.75 nm of an amorphous material with a thermal conductivityof 1 W m–1 K–1.Increasing disorder at the interface between thetwo materialscorresponds to a significant reduction of G. Blank andWeber41 showed that G reducesfrom ∼270 to ∼150 MW m–2 K–1 with an increase in interdiffusion of Si across the interface forTi/Si systems. Mu et al.42 showed thatreducing disorder by eliminating a 3 nm amorphous layer at the GaN/SiCinterface leads to an increase in G from 170 m–2 K–1 to ∼230 MW m–2 K–1. Similarly, Sakata et al.43 showed that recrystallization of a 5 nm amorphous layerat a Si/Si interface increases G from ∼130m–2 K–1 to ∼570 MW m–2 K–1. A GaN/diamond interface havinggood contact was shown by Yates et al.44 to have higher G (∼160 MW m–2 K–1) as compared to a GaN/diamond interface withvoids (G ∼ 125 MW m–2 K–1). Finally, in addition to experimental evidence,theoretical models also concluded that increase in disorder at theinterface reduces G.45The conclusiondrawn from TDTR data and analysis of TEM micrographsin our study is in accord with the existing body of knowledge. A majorityof experimental studies have concluded that increase in disorder atthe interface leads to a reduction in 51 This wisdom is premised on the assumption that interfacial heatcurrents are carried by phonons with vibrational frequencies thatare natural to both crystals. This need for materials to be vibrationallysimilar to form thermally conductive interfaces poses a special challengefor ultra-wide band gap semiconductor devices. Ultra-wide band gapsemiconductors such as AlN, c-BN, and diamond consist of light elementsand possess strong interatomic bonds. As a result, these semiconductorshave phonon frequencies much higher than most other materials.Conventional wisdom in thenanoscale heat-transfer community is that vibrational similarity betweentwo materials effects G.G between HfN and TiN and groupIV and III–V semiconductors show that vibrational similaritybetween two materials is not required for thermally conductive interfaces.For example, TiN (ΘD ≈ 600 K) is not vibrationallysimilar to cubic BN (ΘD ≈ 1700 K) or diamond(ΘD ≈ 2200 K). Not only does vibrationallysimilarity not appear to be required to form conductive interfaces,but dissimilarity is also not a significant impediment to interfacialheat currents. The interface formed between HfN and diamond (ΘD ∼ 300 K) is just as conductive as the interface formedbetween HfN and Ge (ΘD ∼ 360 K) or HfN andGaN (ΘD ∼ 600 K).The results for G and bulkvibrational properties more quantitatively, kinetic gas theory canbe considered. Kinetic gas theory for transport predicts that theinterfacial conductance depends on the bulk vibrational propertiesand the probability that phonons will transmit on the interface.52g(ω)dω describesthe phonon irradiance per Kelvin for phonons at frequency ω,and α(ω) is the frequency-dependent interfacial transmissionprobability of the phonons. The phonon irradiance function g(ω) depends on the density of states D(ω),the temperature derivative of the phonon occupation function dn/dT, the phonon energy ℏω,and the average group velocity of phonons of frequency ω inthe direction perpendicular to the interface ⟨vz⟩. In an isotropic material,⟨vz⟩ equals vz/2.To evaluate the relationshipbetween G isthe experimentally measured interface conductance between two materials,for example, G = 500 MW m–2 K–1 for TiN/diamond. Gmax is the maximum conductance for the interfaces, as calculated in Gmax for an interfaceis limited by whichever of the two materials is vibrationally softer.For example, in the case of TiN/diamond, Gmax = 1200 MW m–2 K–1 = {Gmax}TiN.Theoretical models,such as the acoustic and diffuse mismatch model,assume that α(ω) depends on the vibrational similarityof the two materials forming the interface. If all the energy frommaterial 1 impinging on the interface is carried by phonons with frequenciesthat atoms of material 2 do not naturally oscillate at, then α(ω)is expected to be small or zero. With this in mind, we define twoterms that allow us to quantify what the experimental data in We define vibrationalsimilarity as the inner product of the phononirradiance functions of the two materialsHere, material “1” isthe nitride metal and material“2” is the substrate.Supporting Information). For simplicity, it is assumed that heat currents are carried byacoustic branches and optic modes are neglected.Physically, η describesthe similarity in the spectral distributionof the phonon irradiance per Kelvin of the two materials. The valueof η approaches unity if heat in both materials is carried byphonons with similar frequencies and approaches zero if heat is carriedby phonons of different frequencies. η is evaluated for eachmaterial system studied by assuming an isotropic quadratic dispersionrelationship 62), 10 td in ref  is consiG onvibrational similarityof the materials forming the interface, complexity of unit cells,and interfacial structure has been studied by depositing TiN and HfNon group IV and group III–V crystals. G forHfN on group IV and III–V materials ranged from 140 to 300MW m–2 K–1, whereas G for TiN on group IV and III–V materials ranged from 200 to800 MW m–2 K–1. There was no evidencethat G depended on whether the materials formingthe interface were vibrationally similar. Instead, it was found that G depended on the vibrational properties of the vibrationallysoft material as well as the interfacial structure. This study establisheswhat material properties govern thermal transport at interfaces withwide- and ultra-wide band gap materials. These fundamental findingsshould be useful in ongoing efforts to optimize thermal transportin high power electronic devices.The dependence of


To analyze the changes of gene expression at different timepoints after spinal cord injury (SCI) with tenth segment thoracic injury.Two SCI models, the complete paraplegia (H) and Allen’s strike (D) methods were applied to induce SCI in rats, and transcriptome sequencing was performed 1, 3, 7, 14, 56, and 70 days after SCI, respectively. Principal component analysis, differentially expressed gene analysis, and hierarchical clustering analysis were applied to analyze the differentially expressed genes (DEGs). Gene Ontology GO enrichment analysis, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and Gene Set Enrichment Analysis revealed the pathway of gene enrichment.There were 1,907, 3,120, 3,728, 978, 2,319, and 3,798 DEGs in the complete paraplegia group and 2,380, 878, 1,543, 6,040, 1,945, and 3,850 DEGs in the Allen’s strike method group and after SCI at 1, 3, 7, 14, 56, and 70 days, respectively. The transcriptome contours of D1, H1, D3, and H14 were clustered with C; the H56, D56, H70, and D70 transcriptome contours were similar and clustered together. H3, D7, and H7 were clustered together, and D14 was clustered separately. The transcriptome differences of the two SCI models were mainly concentrated during the first 2 weeks after SCI. The DEGs after SCI in the complete paraplegia group were more concentrated. Most of the early transcriptional regulation stabilized within 2 weeks after injury.There were DEGs between the two SCI models. Through the gene changes and pathway enrichment of the entire time period after SCI, the molecular mechanism of SCI repair was revealed in depth, which provided a reference for SCI treatment in the future. Spinal cord injury (SCI) is a destructive neurological and pathological state that causes major motor, sensory, and autonomic dysfunctions, often with lifelong consequences –3. AccorCurrently, many studies are also committed to developing neuroprotective and nerve regeneration therapies to promote neuronal recovery. Although this treatment has achieved varying degrees of success, the outcome remains uncertain due to the complex healing mechanisms involved. Therefore, a more intensive investigation of the mechanism and molecular events of SCI and its secondary damage is a significant approach to developing SCI treatment plans , 12. NorThe ultimate goal of SCI research is to develop and provide effective repair and treatment strategies for clinical development . PreviouTherefore, the use of RNA-seq (RNA-sequencing) technology to efficiently analyze the sequence of events during and after injury in different injury models enables a comprehensive understanding of the mechanism of SCI and its secondary injury, thereby providing data for the further study of the molecular mechanism of SCI, and providing strategies for the recovery and treatment of neurological function after severe central nervous system injury in the future. The results of the present study provided a novel insight into the mechanisms underlying SCI.A total of 39 specific-pathogen-free 8-week-old adult female Sprague–Dawley rats weighing 200–220 g were purchased from the Shanghai SLAC Laboratory Animal Co. Ltd. . Animal care in the surgical procedures and post-operation were in accordance with the Regulations for the Administration of Affairs Concerning Experimental Animals and Guidelines and Policies for Rodent Survival Surgery provided by the Animal Care and Use Committees of Ningxia Medical University General Hospital.The 39 adult female rats were randomly assigned to a control group  and one of two SCI groups: complete paraplegia  and Allen's strike  groups. The SCI models were established after 3 days of adaptive feeding. The mice were anesthetized by intraperitoneal injection of 4% chloral hydrate. The surgical area was shaved and disinfected with 70% ethanol and betadine. A 5 cm long incision was made centered on T10, the spinous processes and lamina of the thoracic area (T9–T11) were separated and exposed, the spinous processes and lamina were removed, the spinal cord was fully exposed, and an incomplete cross-cut was made with ophthalmic scissors or scalpel for the group H. In the group D, a 5 g hammer was fixed at a height of 16 cm in a smashing device and was allowed to fall freely to impact the T9–T11 spinal cord tissue . All ratRats were euthanized 1, 3, 7, 14, 56, and 70 days after injury, and a 2 cm wound tissue sample was taken from the injury site for RNA analysis. Total RNA was extracted with TRIzol reagent  . RNA intP < 0.05 was defined as differentially expressed [FPKM (Fragments Per Kilobase Million) were considered to estimate the gene expression level . DESeq2 xpressed . In addihttp://www.genome.jp/kegg/) of DEGs were implemented using the clusterProfiler R package, in which gene length bias was corrected. P < 0.05 were considered significantly enriched by DEGs.Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG)  is a pre-defined gene set that can show a significant consistent difference between two biological states. The genes were ranked according to the degree of differential expression in the two samples, and then the predefined gene set was tested to determine whether they were enriched at the top or bottom of the list. GSEA can distinguish between subtle expression changes. We used the local version of the GSEA analysis tool For the high quality assessment of sequencing data, 39 cDNA libraries were established, including the group C, complete paraplegia group , and Allen's strike method group . RNA-Seq produced 39,435,984–52,386,642 raw reads for each sample. After filtering out the low-quality reads, there were 38,663,500–50,797,750 clean reads, with the Q20 97.46–98.58% and the Q30 92.76–95.66%. To identify the source of variation within the original data and evaluate the difference between groups and the duplication of samples within groups, PCA  was conducted. As shown in Fig. RPKM and DESeq were used to analyze the gene expression level and differential expression profiles, respectively. The results are shown in Fig. Heat map and hierarchical clustering were used to determine the gene expression patterns in the rat transcriptome at different times after SCI in different SCI models. Genes with similar expression patterns may have similar functions or may participate in the same metabolic process or cellular pathway. In this study, FPKM was applied for hierarchical cluster analysis of transcriptome abundance, with the results shown in Fig. Compared with the control group, the number of GO terms significantly enriched by upregulated and downregulated DEGs is shown in Fig. Compared with the control group, the number of KEGG terms significantly enriched by upregulated and downregulated DEGs is shown in Fig. To further investigate the changes of the transcriptome level after SCI, we analyzed the gene set enrichment of the complete paraplegia and Allen’s strike groups across all timepoints after SCI to investigate the transcriptome changes caused by SCI. Figure In recent years, research has focused on analyzing the complex pathological process and molecular mechanism of SCI to determine the impact of microenvironmental changes on SCI repair . CurrentThe results of the present study showed that the two SCI methods were quite different within 1–14 days, whereas they were relatively similar at 56 and 70 days. The difference between samples in the complete paraplegia group gradually increased with time, reached a peak at 7 days after SCI, while there was little difference between samples in this group at 14, 56, and 70 days after SCI. The Allen’s strike method group displayed considerable changes immediately on the first day after SCI, while D3 was closer to group C, but D7 and D14 were far away from group C, and was thus quite different from group C. Consistent with the complete paraplegia group, there was little difference between 56 and 70 days after SCI, and H56, H70, D56, and D70 were also gathered together. Consistent results were found in the heat map and hierarchical clustering, with D1, H1, D3, and H14 clustered with C; H56, D56, H70, and D70 transcriptome contours were similar and clustered together. H3, D7, and H7 were clustered together, whereas D14 was clustered separately. The transcriptome difference between the two SCI models was the largest on days and 14 after SCI.Siebert et al.  demonstrAt 56 and 70 day post-injury, the transcriptome characteristics of the two SCI models were relatively similar, while the relevant differential genes that were significantly enriched were in “glial cell development”, “epithelial cell proliferation”, “urogenital system development”, “gliogenesis”, “glial cell differentiation”, “regulation of angiogenesis”, “renal system development”, “glomerulus development”, “nephron development”, and other signal pathways related to glial production and renal development.Through KEGG enrichment analysis of differential genes, we found that the Allen’s strike group was the most enriched in KEGG pathway terms on day 14 after SCI, with upregulated differential genes enriched in 95 KEGG pathway terms and downregulated differential genes enriched in 70 KEGG pathway terms. Upregulated KEGG pathways included “ECM-receptor interaction”, “NOD-like receptor signaling pathway”, “cytokine-cytokine receptor interaction”, “NF-kappa B signaling pathway”, “lysosome”, “osteoclast differentiation”, “protein digestion and absorption”, “Th17 cell differentiation”, “adipocytokine signaling pathway”, and “PI3K-Akt signaling pathway”. Downregulated KEGG pathways included “dopaminergic synapse”, “neuroactive ligand-receptor interaction”, “cAMP signaling pathway”, “insulin secretion”, “aldosterone synthesis and secretion”, “biosynthesis of amino acids”, “GABAergic synapse”, “GnRH secretion”, “inflammatory mediator regulation of TRP channels”, and “oocyte meiosis”. In contrast, in the complete paraplegia group, the upregulated differential genes were not enriched in any KEGG terms at 14 days after SCI, while there were three downregulated KEGG terms, which were “Cell cycle”, “Oocyte meiosis”, and “Progesterone-mediated oocyte maturation”. “Oocyte meiosis” was downregulated in both groups at 14 days after SCI. Previous studies have shown that the key activities that drive the process of meiosis are maturation-promoting factor, cyclin B, and a heterodimer of cell division cycle 2 kinase , 34.Through the overlapping gene sets of the two SCI models, we can understand the common molecular characteristics of SCI. “L17 Signaling Pathway (RNO04657)”, “selenocompound metabolism (RNO00450)”, “non-small cell lung cancer (RNO05223)”, “melanoma (RNO05218)”, “bladder cancer (RNO05219)”, “EGFR tyrosine kinase inhibitor resistance (RNO01521)”,”adipocytokine signaling pathway (RNO04920)”, “sphingolipid signaling pathway (RNO04071)”, “MAPK signaling pathway (RNO04010)”, “estrogen signaling pathway (RNO04915)”, and “RAS signaling pathway (RNO04014)” were upregulated while “steroid hormone biosynthesis (RNO00140)”, and “oocyte meiosis (RNO04114)” were downregulated at 1 day post-injury. “lysine degradation (RNO00310)”, “renin angiotensin system (RNO04614)”, and “AMPK signaling pathway (RNO04152)” were upregulated and there was no overlapping downregulated gene set between the two SCI models at 3 day post-injury. “basal transcription factors (RNO03022)”, “ribosome biogenesis in eukaryotes (RNO03008)”, “RNA degradation (RNO03018)”, and “mRNA surveillance pathway (RNO03015)” were upregulated, whereas “steroid biosynthesis (RNO00100)” and “serotonergic synapse (RNO04726)” were downregulated at 7 day post-injury. “primary bile acid biosynthesis (RNO00120)”, “drug metabolism cytochrome P450 (RNO00982)”, “insulin resistance (RNO04931)”, “lysine degradation (RNO00310)”, and “chemical carcinogenesis (RNO05204)” were upregulated, whereas there was no overlapping downregulated gene set between the two SCI models at 14 day post-injury. “Starch and sucrose metabolism (RNO00500)” was upregulated and “steroid biosynthesis (RNO00100)” and “snare interactions in vesicular transport (RNO04130)” were downregulated at 56 day post-injury. “Lysine degradation (RNO00310)”, “circadian rhythm (RNO04710)”, “Phenylalanine metabolism (RNO00360)”, “longevity regulating pathway multiple species (RNO04213)”, “ABC transporters (RNO02010)”, “tyrosine metabolism (RNO00350)”, “AMPK signaling pathway (RNO04152)”, “renin secretion (RNO04924)”, and “purine metabolism (RNO00230)” were upregulated, whereas “fat digestion and absorption (RNO04975)” was downregulated at 70 day post-injury.In summary, through RNA-seq technology and bioinformatics analysis, it was found that the transcriptomes of the two SCI models were different, and the differences were concentrated in the first 2 weeks after the SCI occurred. The main molecular events after SCI in the complete paraplegia group were more concentrated in the week after injury, reaching a peak on day 7. The major molecular events after SCI in the Allen’s strike group occurred immediately, but they were adjusted on the third day, and the duration was relatively long of up to 14 days. This study analyzed the changes in gene expression levels of different SCI models at different timepoints, investigated signal pathways enriched by different genes, elucidated molecular changes after SCI and SCI repair pathways, and further clarified the mechanism of SCI at the level of gene expression changes. Most early transcription events appear to be stabilized within 2 weeks after the injury, such that the overall change in the average gene expression was no longer obvious, and the expression level remained relatively stable. The downregulation of “Fat digestion and absorption” at 70 days after injury may be closely associated with the formation of glial scars after SCI. On the other hand, comparing and analyzing the difference in gene expression between complete paraplegia group and Allen’s group provides a reference for explaining the entire molecular process of SCI as well as a novel direction for spinal cord injury treatment.The transcriptomes of the two SCI models were different, and these differences were mainly concentrated in the first 2 weeks after the SCI. In the complete paraplegia group, the main molecular events after SCI were more concentrated during the first week after the injury, reaching a peak on day 7. Major molecular events after SCI in the Allen’s strike group lasted for a relatively long time, up 14 days. This study found that most of the early transcription events appeared to be stabilized within 2 weeks after injury, and the down-regulation of “fat digestion and absorption” at 70 days after injury may be closely associated with the formation of glial scars after SCI. These studies may provide some meaningful insights into the differences of targeted treatment strategies by explaining the entire molecular process after SCI.


The results showed that SCN− at 1818.00 mg L−1 in the influent decreased to 0.68 mg L−1 after flowing through the two-stage activated sludge units. Raman spectroscopy was used to study the changes of relevant functional groups, finding that SCN− was degraded in the COS pathway. Based on 16S rRNA high-throughput sequencing technology, the microbial diversity in this system was analyzed, and the results indicated that Thiobacillus played a major role in degrading SCN−, of which the abundance in these two activated sludge units was 32.05% and 20.37%, respectively. The results further revealed the biological removal mechanism of SCN− in gold mine tailings wastewater.As one of the inorganic pollutants with the highest concentration in the waste water of gold tailings using biohydrometallurgy, thiocyanate (SCN −) was degraded in COS pathway, and the removal rate was 99.94%. The Thiobacillus played an important role.Thiocyanate (SCN No matter which chemical or biological treatment is adopted, the conversion of SCN− in aerobic conditions needs a lot of oxidants, which is costly and may produce intermediate product CN−, thus increasing the toxicity of wastewater.7,8 As an economic and environmental-friendly method, biohydrometallurgy is attracting more and more attention. Considering that SCN− consists of S, C and N, which are all necessary elements for the growth of the living beings, it can provide a carbon source, nitrogen source and sulfur source for microorganisms under aerobic conditions, and generate such metabolites as SO42−, CO2, and NH4+.9 Hence, high-load SCN− in the wastewater can be biodegraded efficiently under the condition that dissolved oxygen and hydraulic retention time (HRT) are sufficient.China is rich in gold resources, most of which have been developed completely, with the rest hard to mine. In view of this, economical, efficient and environmentally-friendly biohydrometallurgy is explored across the world. However, when minerals are oxidized by microorganisms, sulfides or thiosulfates can react with cyanide to form a large number of sulfur cyanates  at the concentration of 2500 mg L−1 thiocyanate at pH 6.0 and 37 °C. Different from physical and chemical treatment, biological treatment does not need a large number of oxidants and thus gradually becomes the research hotspot in respect of sulfur-containing cyanide wastewater treatment.Biological treatment of SCN−) in the gold mine tailings wastewater. Meanwhile, the functional groups in this system is analyzed to decode the degradation pathway of SCN−, and 16S rRNA high-throughput sequencing technology is also employed to analyze the microbial diversity in the system and further to explore the related biodegradation mechanism of SCN−.As a mature biological treatment process, activated sludge process plays an irreplaceable role in wastewater treatment. The large surface area and sugar layer of the activated sludge can quickly absorb pollutants in sewage, and effectively biodegrade pollutants relying on the relevant functional microorganisms. Hence, in this paper, a two-stage activated sludge biological treatment process is applied into the effective biodegradation of high-concentration thiocyanate , NH4+–N by Nessler's reagent spectrophotometry (HJ 535-2009), TOC by NPOC (non purged organic carbon) in combustion oxidation non dispersive infrared absorption (HT 501-2009), SCN− by Isonicotinic acid pyrazolone spectrophotometry (GB/T13897-92), and total mercury by cold atomic absorption spectrophotometry (HJ 597-2011).The pH value was analyzed by HACH portable multi parameter digital analyzer, COD by rapid digestion spectrophotometry (HJ/T 399-2007), NO2.4−1; and this process lasted 10 s and was repeated 4 times, in order to obtain a relatively smooth spectrum ranging form 100 cm−1 to 4000 cm−1. In addition, every spectrum sample was repeatedly collected three times to improve the accuracy. All the spectra were collected in a dark room at the laboratory temperature (23 °C) and pressure (0.1 MPa). Original 8.0 software was used for data analysis.The water samples were frozen at −20 °C and then dried to powder. Then, a proper amount of powder was taken to the center of quartz slide for spectral integration using confocal micro Raman spectrometer , with excitation light source being 632.8 nm He–Ne laser, excitation wavelength 532.08 nm, and grating 1800 L mm2.5−1 dNTPs 2 μL, forward primer (5 μM) and reverse primer (5 μM) 0.8 μL, FastPfu polymer 0.4 μL, BSA 0.2 μL, and template DNA 10 ng, then, adding ddH2O to 20 μL, as well as ABI GeneAmp® 9700 PCR amplification instrument, with the reaction parameters: pre denaturation at 95 °C for 3 min, denaturation temperature at 95 °C for 30 s, annealing temperature at 55 °C for 30 s, extension temperature at 72 °C for 45 s, in 72 cycles, and extension at 72 °C for 10 min. After amplification, PCR product sample of 3 L were loaded and assayed by 2% agarose gel electrophoresis. After that, an Illumina platform library was constructed, and then the data obtained were analyzed for biological information, including OTU clustering, species annotation and classification, community composition and others.Microorganisms in the two units were collected and frozen at −20 °C, and then sent to Shanghai Meiji for 16S rRNA high-throughput sequencing. An universal bacterial primer: 338F (5′-ACTCCTACGGGAGGCAGCAG-3′), was used to amplify V3–V5. Microbial DNA was extracted for PCR amplification and product purification pre-experiment. Passing the pre-experiment, the formal experiment could be initiated, using TransGen AP221-02: TransStart Fastpfu DNA Polymerase, 20 μL reaction system: 5 × FastPfu buffer 4 μL, 2.5 mmol L33.1− wastewater was treated by two-stage activated sludge biological treatment process, in the stable period, water quality of the influent and effluent was shown in − decreased from 1818.00 mg L−1 to 1.01 mg L−1 and the removal rate reached 99.94% after the flowing through the primary unit, and then, the total removal rate of SCN− increased to 99.96% after the secondary unit, which was consistent with the removal rate of COD (85.89%) and the reduction rate of TOC in water (93.89%). As a main source of COD in gold wastewater, decreases of SCN− concentration can lead to COD decrease.High-concentration SCN2−–N and NO3−–N in the wastewater reached 93.6% and 95.79%, respectively and only NH4+–N exhibited an upward trend from 99.21 mg L−1 to 318 mg L−1, suggesting NH4+–N was an intermediate product from SCN− degradation which further led to the accumulation of NH4+–N due to a lack of electron acceptors in the system. Theoretically, 100 mg SCN− can release 24 mg NH4+–N, about 10% of which can be transformed into biomass by microorganism as nitrogen source, and the rest enter into the water body in a form of NH4+, resulting in the increase of NH4+–N concentration in water.12 On the other hand, Huang et al. found that the nitrification of NH4+-N was inhibited due to the existence of SCN−.14After the treatment in the primary unit, the removal rate of NO− conversion path.Formula 4+–N in the wastewater decreased by 26 mg L−1, but NO3−–N increased by 29.55 mg L−1, showing nitrification occurred in this secondary unit. Moreover, it was found that mercury in this unit reduced from 47.79 ng mL−1 to 1.47 ng mL−1 with the removal efficiency high up to 96.92%, suggesting this system had a favorable condition to remove mercury.Then, after flowing through the secondary unit, NH3.2−. One was COS pathway. Under the action of thiocyanate hydrolase, the nitrogen carbon bond in SCN− hydrolyzed to COS and NH3, where the C–S bond was broken into CO2 and H2S, and H2S oxidized to SO42−. The other was CNO pathway. The sulfur carbon bond in SCN− was broken and hydrolyzed to cyanate (CNO−) and HS−, where CNO− was hydrolyzed into NH3 and CO2 by cyanate hydrolysis enzyme, and S2− was further oxidized to sulfide and SO42−.9The results showed that there were two pathways to degrade SCN15The COS pathway:−1 in the regulating tank, specifically speaking, 634 cm−1 and 757 cm−1, respectively. In the primary unit, there was only one vibration at 636 cm−1, and in the secondary unit, there was only one vibration at 627 cm−1, with the vibration frequency less than that in the regulating tank and the primary unit. At the same time, the CN stretching vibration frequency of M–S–CN, a metal thiocyanate salt located at 2160–2040 cm−1, also appears in the water of the regulating tank.20,21 Tian et al. reported that the S-and N-combined thiocyanate showed C–N stretching vibration in the range of 2050–2165 cm−1, that is to say, this peak belongs to CN stretching vibration, and the absorption band in the secondary activated sludge unit is the weakest, indicating that the C–S bond and CN bond fracture of SCN− (electronic formula is NC–S−) mainly occur in the primary activated sludge unit. The CS stretching vibration peak at 1200–1020 cm−1 only appeared in the regulating tank and the primary effluent, and disappeared in the secondary effluent, indicating that the CS bond fracture of OCS mainly occurred in the secondary unit.22 In Minogue's report, the Raman spectral frequencies of 981 cm−1 and 451 cm−1 belong to the vibration of SO42−. The vibration frequency (about 460 cm−1) caused by the symmetric angle change of SO42− from the regulating tank to the primary effluent changed slightly, but then weakened to the lowest extent in the secondary effluent; however, the S–O symmetric stretching vibration peak (about 980 cm−1) of SO42− was very strong at the beginning, and then weakened gradually from the regulating tank to the primary effluent and then to the secondary effluent, indicating that H2S can be further oxidized into SO42− both in the primary and secondary units. Accordingly, Raman spectrum analysis indicated that biodegradation of SCN− belonged to COS pathway, where the N–C bond and S–C bond in SCN− was hydrolyzed into COS and NH3 in the primary unit; then the C–S bond in COS was broken into CO2 and H2S mainly in the secondary unit; and finally, H2S was further oxidized into SO42−.It can be seen from the analysis of three groups of data by comparing the Raman spectrogram  and Rama3.3−, and OTU clustering was carried out for non-repetitive sequences (excluding single sequences) according to 97% similarity by calculating common diversity indexes  in coking wastewater.27,28The dominant family-level bacteria of the two samples were Hydrophillaceae, Chitinophagaceae and Trueperaceae, with the similar relative abundance . RelativThiobacillus (32.05% and 20.37%), Truepera (15.58% and 19.96%), Chitinophagaceae (13.45% and 14.02%), and Dokdonella (7.95% and 10.94%). Oxidation–reduction sulfide or elemental sulfur of Thiobacillus was sulfuric acid, and as a specific autotrophic bacterum using chemical energy, Thiobacillus could effectively degrade SCN−, during which SCN− would generate metabolites such as NH3, NO2− and S2−.29As shown in Thiobacillus, a SCN− degrading bacterium isolated from coking wastewater treatment plant, belonged to COS degradation pathway,30 while Pseudomonas Putida and Pseudomonas stutzeri, separated from gold smelting wastewater polluted soil, belonged to CNO degradation pathway.31Thiobacillus was the dominant strain in this experiment, suggesting the degradation of SCN− belonged to COS degradation pathway,30 consistent with the afore results of Raman spectrum analysis.The results showed that thiocyanate can be degraded in two pathways: et al. put forward that COS can generate CO2 and H2S through C–S bond fracture,32 and H2S can further oxidize to generate SO42−, where the resulting energy can also facilitate the growth of microorganisms. Stratford et al. and Arakawa et al. extracted thiocyanate hydrolase from the isolated strain and identified that thiocyanate hydrolase was an inducible enzyme.33,34 Huddy et al. proved that Thiobacillus was the dominant bacteria to degrade SCN− in ASTER™ biological treatment system using gene clone library analysis.35 In addition, the anammox bacteria Candidatus Campbell bacteria was detected, but its abundance was very small, about 0.17%, so it exerted a poor effect on the removal of NH4+–N.Moreover, results of this experiment can reaffirm some of other researches. For example, Kelly Thiobacillus became the dominant bacteria, and oxidized sulfur to sulfate, causing the pH value of the system decreased. However, nitrifying bacteria prefer a relatively weak alkaline environment. Kim et al. also studied that nitrifying bacteria in aerobic sludge cannot be detected due to the inhibition of toxic compounds.36 Hence, nitrifying bacteria were not dominant in this experimental condition.The sequencing results showed that the nitrifying bacteria and nitrobacteria were not the dominant, and were excluded in the community Heatmap diagram . What's 4− gold tailing wastewater was treated in a two-stage serial activated sludge process, where SCN− of 1818 mg L−1 was reduced to 0.68 mg L−1, with the degradation efficiency high up to 99.96%. In addition, the removal efficiency of COD, TN and Hg reached 85.89%, 85.51% and 96.92%, respectively. Meanwhile, according to Raman spectrum analysis of the functional groups' changes, SCN− was transformed and degraded in the same COS pathway as thiocyanate was biodegraded. Analysis of 16S rRNA high-throughput sequencing identified. Thiobacillus was the dominant bacteria to degrade SCN−, with the abundance of 32.05% and 20.37% respectively in the two-stage activated sludge units.In this research, high-concentration SCNThe authors declare that there are no conflicts to declare.