Existing literature on the impacts of adult illness on household labour supply and income in low- and middle-income countries shows that adverse health conditions significantly affect household labour supply, work participation and earnings. Most of the studies, however, are not equipped to distinguish between short- and long-term consequences of adult illness. We measured the impact of adult illness on household employment outcomes both in the short- and the long-run, using a unique longitudinal data set from rural India.We used two waves of India Human Development Survey (1993-94 and 2004-05) with a balanced panel of 10 726 households to assess short-run (in the year of the occurrence of adult illness) and long-run (after 11 years of the occurrence of adult illness) effects of major illness of adult household members aged 15-64 years on household employment outcomes, using multiple matching methods: nearest-neighbor matching and inverse probability weighting following propensity score matching, and coarsened exact matching to compare employment outcomes to a set of matched control households.Rural households affected by adult illness experienced declines in workforce participation rate by 1-3%, wage employment by 4-15 days, and wage-earnings by Indian Rupee (INR) 374 to INR 837 compared to the matched control households in the short-run. In response, adult non-sick members of the affected households increased their workforce participation sharply by 14-16% to compensate for shortfalls in the short-run. In the long-run, workforce participation rate of the affected households also declined by nearly 1-3%. The long-run declines in wage-days and wage-earnings were small and not always statistically significant across the methods. However, long-run workforce participation rate of non-sick adults were smaller (4-6%) compared to short-run, but still statistically significant.The long-term effects were smaller in absolute magnitude than those of the short-run. This suggests coping and adjustments by the affected households using this 11-year longer time-span in a manner that helps to ameliorate the immediate impacts of adult illness. Our study also reiterates the importance of improving financial access to health services as well as access to social security benefits for the illness-affected households in rural India both in the short- and long-run. There is a vast literature on the impacts of adult illness on household labour supply and income in low- and middle-income countries (LMICs). Studies have estimated the impacts of adult illness using both cross-sectional and longitudinal household surveys. Analyses based on cross-sectional data and short eg, 1-year) panels show that adverse health conditions significantly affect household labour supply, work participation and earnings, although the magnitudes of the effects vary greatly across studies -year pan. StudiesThe above findings on adverse earnings and employment effects of illness are not surprising given the heavy reliance of household members on informal employment in LMICs, with little access to social protection in the form of medical coverage, unemployment insurance and job protection. It is likely that a household member with a disease will experience lower work participation, with the household potentially experiencing increased work and labour force participation of (other) non-sick members to compensate for any financial shortfalls ,14,15. IMost of the existing studies, however, are not equipped to distinguish between short- and long-term consequences of adult illness, although a recent study from Chile showed that a severe illness  lowered employment and earnings both in the short-run (current year of illness) and 4 years after the original illness . The autIn this paper we focus on the impact of adult illness on household employment outcomes both in short-run (in the year of the occurrence of adult illness) and long-run (after 11 years of the occurrence of adult illness) using a unique longitudinal data set from India. This data set includes a rich set of variables on employment in India, including workforce participation, days spent working for wages, income from wages, cropped area and irrigated cropped area. Quite apart from our contribution to the international literature on the longer-term implications of adult illness, our paper also adds to the very limited literature that exists on the economic implications of adult illness in India, all of it focused on short-term impacts. These studies in India using cross-sectional surveys showed adult-illness reduce work participation and incomes of adult household members at different magnitude ,18-20.We used three matching methods: i) nearest-neighbor matching and ii) inverse probability weighting (IPW)  followinThe PSM procedure involves two steps . In the Balance checking of pre-treatment covariates is typically a key step in PSM methods . We compCEM is an alternative matching approach where households with adult illness and control households are exactly matched, but after ‘coarsening’ of the variables . For exaAnother method that lowers the risk of imbalance is IPW. As in the case of PSM, the first step in using IPW is the generation of propensity scores. The IPW method uses weights (based on the inverse of the propensity score) to create a synthetic sample such that the distribution of measured baseline covariates is independent of treatment assignment. Larger weights are assigned to “underrepresented” observations, and lower weight to “overrepresented” observations as indicated by propensity scores. A weighted regression (with the inverse of the propensity scores as weights) was used to generate estimates of the impact of adult illness under the IPW method.Matching methods such as PSM are nonparametric and typically require a common support restriction involving dropping treatment observations whose p score is higher than the maximum or less than the minimum pscore of the controls. The quality of the matches may thus be improved, but the cost is loss of observations, making PSM methods sensitive to common support. So, we explored the implication of the loss of observations due to imposing common support restrictions for our results. Relatedly, the thinness of overlap in propensity scores may also be a concern. To assess the resulting implications for employment outcomes, we estimated the impact of further restricting the common support region by dropping treatment and control households with the lowest density . In particular, we dropped between 1% to 10% of the households with the lowest density for propensity scores to assess the sensitivity of our results to assumptions about common support .Second, estimates from matching methods cannot be interpreted causally unless the so-called “conditional independence assumption” (CIA) is satisfied. In our case, CIA implies that conditional on the observed covariates using for matching, the distribution of treatment households is statistically independent of the potential household economic outcomes . Unfortunately, it is not possible to directly test the validity of this assumption; so, we adopted a strategy suggested in the literature to evaluate the robustness of our economic impact estimates based on PSM to violations of CIA. The strategy to assess the implications of a violation of the CIA requires assuming that CIA does not hold and the existence of a convenient unobserved binary variable (say U), so that if U were observed and included in the set of matching variables, CIA would, indeed, be satisfied . AlternaThird, we tried to address “variable selection” by dropping less relevant co-variates in propensity score that drive our treatment variable (adult illness). We assessed changes in our outcome estimates if the number of covariates are reduced. We did this under two additional scenarios – checking the robustness of our findings to a reduced number of covariates.Finally, we applied the following fixed effect (FE) regression in panel data analysis to examine current employment effects of adult illness (current illness) using a 2-wave panel data :Where,it – ῩiY change in current employment outcomesit – IllnessiIllnessacute illnessit – XiX dummy covariatesit – ϵiϵ error termθ FE coefficientit – ῩiY and it – IllnessiIllness. Thus we estimated the economic impacts of major illness in the current period (not the long-term impact of illness). As we are taking deviations from the mean, we are (in effect) also ruling out illnesses that show up for the individual household in both periods, that is chronic illnesses (because they are part of the mean). Thus, we ended up with is the impact of acute illnesses.Using FE we looked at changes over time over the same household, all we examined was “within”  variation. That is, the coefficient θ we estimated is primarily based on the covariance (correlation) between The main advantage of the FE method is that it removes bias introduced by heterogeneous individual characteristics. However, it is still possible that other sources of endogeneity remain. For example, illness in the previous period may affect economic outcomes in the previous period, and these economic outcomes in the past period may influence future economic opportunities.So, we estimated long-term employment effect of the lagged illness in following equation:Where,itYlong-term employment outcomes (wave 2)it–1Illness lagged illness (wave 1)it–1X all dummy covariates (wave 1)itIllnessmajor illness (wave 2)itϵ error termπ regression coefficientThis specification is well known to have endogeneity problems (apart of the standard heterogeneity across households). However, it is likely that the long time period between rounds (11 years) may have helped flush out “most” of the endogeneity. With this specification, and with only 2 rounds of data, this is essentially a regression model where we only used 2004-2005 outcomes (wave 2) and the lagged illness variable from 1993-1994 (wave 1) and all the X variables from 1993-1994 (wave 1).We used data from the Human Development Profile of India (HDPI) Survey and the India Human Development Survey (IHDS), both carried out by the National Council for Applied Economic Research (NCAER). The HDPI survey was implemented in 1993-94 and covered 33 230 rural households in 1765 villages and 195 districts across 16 states in India. The HDPI used a stratified three stage sampling design and its sampling frame included more than 95% of India’s rural population. The HDPI survey collected information on household and individual level socio-demographic and economic characteristics, such as age, sex, religion, whether scheduled caste or tribe, income and land ownership. The survey also collected detailed information on employment, earnings, health care utilization, indicators of health and educational status, and some categories of household expenditures.The IHDS was carried out in 2004-2005 as a follow-up to the HDPI and is a nationally representative, survey of 41 554 households in 1503 villages and 971 urban neighbourhoods located in 276 towns and cities across India. About 65% of the sample consisted of rural households, and IHDS collected data on household expenditures and incomes, along with household- and individual-level data on education, heath, employment, marriage, fertility, indicators of social capital, landownership, farming practices and crop diversity. In states where HDPI was conducted, re-contact details were available for 13 593 households for a follow-up in the 2004-2005 IHDS. The IHDS interviewed 10 791 households from HDPI as well as an additional 2290 households in 2004-2005, some of whose members were part of the set of 10 791 households in 1993-94. In effect, information was available for 13 081 households in 2004-2005, consisting of members of the initial set of 10 791 households. Hence, we constructed a balanced panel data set of 10 791 households combining HDPI (1993-94) and IHDS (2004-05). However, after merging IHDS with HDPI, only 10 726 households could be matched in this manner. For both HDPI and IHDS, the initial ethics approval was obtained from the Ethics Review Committee of the NCAER, New Delhi and the Institutional Review Board of the University of Maryland, College Park, USA. For this study, the Monash University Human Research Ethics Committee granted exemption from further ethical review (reference No.CF12/1442-2012000778).We constructed a dummy of adult illness as the treatment variable, with the dummy taking the value 1 if a household experienced a major illness  of a member aged 15-64 years in the year preceding the 1993-94 HDPI survey.To account for observable confounders in the relationship between adult illness and employment outcomes, we used the following household characteristics from 1993-94 survey to construct propensity scores (for the PSM method) and for matching households under the CEM method:These included socio-demographic characteristics, living conditions and characteristics of the head of the household.Socio-demographic characteristics included were: (a) a dummy equal to 1 if household size was less than the average rural household size based on the Census of India 2001 , 0 otherwise; (b) dummy for cultivable land ownership ; (c) 15 state dummies ; (d) a dummy for major religion ; and (e) a dummy for caste or tribal status . Indicators of living conditions were: (a) type of house ; (b) the number of rooms in the house ; (c) separate kitchen in the house ; (d) type of cooking stove ; (e) electricity supply ; (f) toilet ; (g) improved toilets  and; (h) improved drinking water sources  .Characteristics of the household head that were included: (a) age ; (b) sex ; and (c) indicator of educational attainment .We constructed a measure of days absent from work per adult by dividing the total number of days absent from work by the number of all working age adult members (15-64 years) of the household.Adult individuals aged 15-64 years were considered to be working if they were engaged in one or more gainful activities during the year preceding the two surveys – whether working on household farms or businesses, or for wages or salaries. We constructed household-level adult workforce participation rate by dividing the total number of adult workers by the number of all working age adult members (15-64 years) of the household. Similarly, we constructed a household-level adult workforce participation rate for non-sick adults aged 15-64 years.The number of days spent working for wages per adult (15-64 years) in the previous year was constructed by dividing the total wage-days by the number of adults of the household to assess household employment other than participating in work on the family farm.We constructed a measure of household wage-income per adult by dividing all wage-incomes by the number of adult (15-64 years) household members . We inflA measure of per capita cropped area  in bighaWe examined employment outcomes of adult illness-affected households by subgroups of socioeconomic status, particularly (a) scheduled caste and tribe (SC/ST), two groups that are considered historically deprived in India, vs non-SC/ST households, and (b) households having cultivable land, vs households without cultivable land. To assess group-specific differences in employment outcomes, we estimated linear probability models, using ordinary least square (OLS) regressions on a data set consisting only of matched households based on nearest-neighbour matching and CEM. For IPW, we run OLS regression on the unmatched data (with propensity scores) but using the inverse of the propensity scores as the sampling weight. The outcomes were the Y variable, with the X variables being an indicator for whether a household was affected by adult illness, an indicator for the specific sub-groups of interest  and the product (interaction) of the indicators for the household with adult illness and sub-group. The coefficient of the interaction term was used to assess sub-group differences.The summary statistics of treatment households, unmatched control households and matched control households with nearest-neighbour matching (using propensity scores) are presented in Online Supplementary Document(Online Supplementary Document).Adult illness increased household out-of-pocket (OOP) health expenditure per adult (15-64 years) for the treatment households by 835-997 Indian Rupee (INR) in the year they occurred but the effect was smaller (98-115 INR) after 11 years of adult illness compared to matched controls. Analogously, hospitalized days for the treatment households increased by 5 days per adult (15-64 years) in the year of adult illness but after 11 years hospitalized days per adult in treatment households were statistically indistinguishable from that for matched controls (these results are not presented in the table). These results show that major illness is associated with increased hospitalization and household OOP spending in the short-run.Our results also show that work participation rates of non-sick adults (15-64 years) rose sharply in the short-run by 14-16% (83% for the treated vs 68% for the matched control households under nearest-neighbour matching). After11 years, these effects were smaller (4-6%), but still statistically significant. Our subgroup results by SC/ST status are presented in Our second subgroup results by cultivable land ownership status are presented in Online Supplementary Document(Online Supplementary Document) show that trimming of the sample of adult illness-affected households with low density propensity scores does not influence our findings on the magnitude of the estimated impacts or the overall conclusions in the PSM analysis.We re-estimated household employment and earnings impacts under alternative “trimming” assumptions, ranging from dropping 1% to 10% of total treatment households that had propensity scores with a low density in the empirical distribution. The results of this analysis, which are summarized in Appendix Table A1 in Online Supplementary Document(Online Supplementary Document)) suggest that an unobserved confounder with a distribution similar to that of U  does not overturn our main findings. The smaller the selection and outcome effects associated with U, the closer the simulated average treatment effect on the treated (ATT) estimates to our base ATT estimates reported in Although we cannot directly test for the CIA, our simulation results for the nearest-neighbour PSM (in Table SA2 in Online Supplementary Document(Online Supplementary Document), respectively.Our robustness check for “variable selection” under two additional scenarios –our findings to a reduced number of covariates  did not fundamentally change our original results on the employment impacts of adult illness. Dropping co-variates have just increased our total matched control sample sizes, but sample of matched treatment remained same. The results are presented in Tables SA3 and SA4 in Online Supplementary Document(Online Supplementary Document).Finally, applying FE regression in panel data analysis to examine current employment effects of adult illness and long-term employment effects of lagged illness using regression also did not change our original results from matching methods. The results are presented in the column 2 and 3, respectively, of Table SA5 in We present evidence that rural Indian households, when faced with an adult illness, experience negative impacts on labour supply and wage-incomes in the short-run. These include a lowering of adult workforce participation rate, wage-days per adult and a lower wage-incomes from work. Our results also show that the affected households try to compensate for the declines in labour supply and incomes in the short-run by increasing work participation of non-sick adult household members. Our findings are consistent with previous literature. For example, Gertler and Gruber showed that in Indonesia, in response to the illness of head of households, the labour supply of other family members signiﬁcantly increased . BerloffOur sub-group analyses show socioeconomically deprived groups such as households belonging to SC/ST experience a greater loss in wage-days and wage-incomes than their non-SC/ST counterparts. We also find that landless households that are more dependent on selling labour services tend to experience a larger decline in workforce participation because of adult illness compared to the households with land ownership. Analogously, the households with land ownership experienced consistently higher declines in both per capita cropped area and per capita irrigated cropped area.We cannot entirely reject the hypothesis that adult illness has no long-run effects on household employment and earning outcomes in rural India. It is true that in most cases, we find the magnitude of the employment and earnings effects to be much lower in the long-run than in the short-run and sometimes the results are statistically insignificant. This suggests coping and adjustments by the affected households using this 11-year longer time-span in a manner that helps to ameliorate the short-term impacts of adult illness. This may be through informal support systems at the community level and households’ own responses to mitigate the adverse economic impacts of adult illness in the long-run. For example, if the households have access to micro credit, or sources of informal credit, they may be able to better protect their non-medical consumption and future economic vulnerability ,35. IntrThere are limitations to our analysis. In the construction of the treatment variable, we excluded child illness assuming child illness has no direct impact on household labour supply. However, child illness requires care and support from the adult household members and this can negatively influence adult employment outcomes as well. Neglecting child illness can contribute to underestimation of the impacts of household employment outcomes. Our analysis also does not control for adult illness that households may have experienced over an 11-year period because the survey did not collect any information on major illnesses that may have occurred in the interim. While our sensitivity analyses sought to address confounding due to such events, it is possible  that our estimates do not adequately address this concern. We also could not adequately investigate the factors driving long-term impacts, as we lacked data on informal and formal credit markets and support systems in the survey. Nonetheless, our examination of “variable selection” and application of alternative methods such as FE regression in panel data analysis and regression of lagged illness on long-term employment outcomes confirm our original findings from the three matching methods.Our analysis points to the importance of improving financial access to health services. Specifically, our work suggests that major health expenses and possible loss of a breadwinner can lead to intra-household adjustments in labour supply and income losses, some of which may persist even over a decade. Increased workforce participation by non-sick members, particularly by children may have adverse implications for human capital formation in the household such as educational attainment, and this is partially reflected in some of our findings on increase in workforce participation among children. It is also likely that efforts to fund health care expenses arising from adult illness may be inefficient, both because members whose skills are less remunerative may be forced to participate in the workforce. The risk of income losses following an adult illness also depends on access to social security benefits such as income protection against disability and sickness, unemployment benefits. These are frequently missing in LMICs such as India, except the small minority involved in formal sector work and primarily in urban areas. Thus a second policy implication of our work is the need to focus on social security for rural and other informal sector workers in LMICs.We conclude that the rural households remarkably decrease their labour supply and incomes in the short-run as a result of adult illness. The affected households also loss their labour supply and incomes in the long-run. But the long-term impacts of adult-illness on households were smaller in absolute magnitude than those of the short-run. This indicates coping and adjustments by the affected households using longer time-span after the incidence of adult-illness. Our study suggests improving financial access to health services as well as financial risk protection from major illness for the affected households. We also emphasize the importance of access to social security benefits for the illness-affected households. Finally, we call to activate effective health and social policies in rural India so that no household suffers undue financial hardship as a result of illnesses both in the short- and long-run.


As such we propose an automated diagnostic technique using a variant of deep neural networks language models (DNNLM) on the verbal utterances of affected individuals. Motivated by the success of DNNLM on natural language tasks, we propose a combination of deep neural network and deep language models (D2NNLM) for classifying the disease. Results on the DementiaBank language transcript clinical dataset show that D2NNLM sufficiently learned several linguistic biomarkers in the form of higher order  Early diagnosis of Mild Cognitive Impairment due to Alzheimer’s disease (MCI) and Alzheimer-type dementia (AD-type dementia) is currently a challenge  2]. Mor. Mor2]. As opposed to the ad hoc use of neuropsychological examinations, linguistic ability captured from verbal utterances could be a good indication of Mild Cognitive Impairments due to AD-type dementia (MCI) and AD-type dementia . The pren-grams. The ordinary DNNLM uses lower order n-gram N-dimensional sparse vectors as discrete feature representations to train the neural network with multiple hidden layers 21] to dee Models .i giving its history, hj, thus P(wj = i|hj). We present the details of the output layer and the language model probability as follows:Vij denotes the weights between the hidden layers and the output layer, ki represents the biases of the output layer and the pi computes the language model probability for every ith output neuron.Note that since the DNNLM follows the NNLM architecture, other hidden layers with the same hyperbolic tangent non-linear activation functions are added to make the network deeper. The output layer uses a softmax function to simultaneously compute the language model probability of each word n-gram vocabulary space that was used in the original DNNLM and also use a decomposition technique to reduce the sparse feature space to a lower dimensional feature space in order to minimize the generalization error 19]. Usinmilar to  and [19]ror (SE) .p <0.001, CI: 0.355-1.000) and a statistically significant AUC of 0.83 on the AD-type dementia dataset . Similarly, D2NNLM-4n has a statistically significant AUC of 0.74 on the MCI dataset  and a statistically significant AUC of 0.79 on the AD-type dementia dataset . The performance improvement over DNNLM is consistent with the percentage errors reported in Tables Tables In comparison to the word alignment technique proposed in , our modA limitation of this study could be the limited size of the datasets, which is often a challenge in clinical research. We believe that an increase in the data sample is likely to improve the performance of our proposed models for classifying MCI and AD-type dementia from the healthy controls.n-gram features in this study are limited to the description of the Cookie-Theft picture in the DementiaBank clinical dataset. This is understandable since the objects within the picture dictate the specific n-grams within the language space of the MCI, AD-type dementia, and control individuals. Unless a picture with similar objects in the Cookie-Theft picture is used for collecting the speech transcript, the use of any other pictures of different objects is likely to generate a different set of n-grams.It is worth mentioning that the use of higher order n-gram vocabulary spaces. Experimental results show that the models predict MCI and AD-type dementia with less percentage error, perplexity, and statistically significant AUC on sparse clinical datasets. As part of our future work, we anticipate that our model has the potential to predict conversion from MCI to AD-type dementia [We have proposed the combination of deep neural network and deep language models to predict MCI and AD-type dementia from sparse clinical language datasets. We learned deep language models using higher order dementia . We also


There are very few clinical or prognostic studies on the role of SRT (Stereotactic Radiation Therapy) in the continuum of care of metastatic colorectal cancer (mCRC) patients.Criteria In Solid Tumors). FDG-PET (FluoroDeoxyGlucose - Positron Emission Tomography) was done before and after SRT; metabolic responses were evaluated by using the EORTC (European Organization for Research and Treatment of Cancer) criteria. The Kaplan-Meier product limit method was applied to graph Overall Survival (OS) and Progression-Free Survival (PFS).Patients affected by oligo-mCRC were treated with SRT before or after front-line standard treatments. SRT was delivered according to a risk-adapted protocol. Total body CT (Computed Tomography) scan was done before therapy and every three months thereafter. The radiologic responses to therapy were evaluated by RECIST  correlated with the local control (p<0.001) and two-years survival (p=0.003). At univariate analysis, localization of primary tumor, site of metastases, KRAS (Kirsten RAt Sarcoma) oncogene mutational status, response to first-line chemotherapy, response to SRT and number of treated lesions predicted both PFS and OS.Forty-seven patients were included. Twenty-one patients had disease limited to lungs, 9 to lung and liver, 7 only to liver, 10 to multiple sites. The median prescription SRT dose was 60 Gy per organ in 3 fractions . The reduction of delta SUVmax (maximum This real practice experience suggests that further studies are needed to analyze the promising role of SRT in the multidisciplinary management of mCRC. Colorectal cancer is the third most common cancer worldwide. Despite progresses in the screening allowing for early diagnosis and definitive surgical removing of the localized tumors, about 30% of patients presents with advanced disease involving liver in more than 50% of cases . Other oIn last years, the management of advanced disease has been enriched of integrated strategies including SRT (Stereotactic Radiation Therapy). The administration of SRT demonstrated, particularly in oligo-metastatic disease, to be a safe and effective option . A definMany factors prompt the integration of SRT in the multidisciplinary therapeutic management of mCRC: i) the radiosensitivity of colorectal cancer, ii) the reduced toxicity  with the intriguing possibility of concomitant therapies, iii) the potential to induce immune system modulation with regression of tumor deposits in non-irradiated regions , iv) the increasing availability of the technique. Several studies suggested a significant survival increase versus historical controls in patients bearing lung metastases with two-years survivals ranging from 67.7 % to 77.0% and medians surpassing 30 months . The mosHere we report the outcome of 47 patients treated from 2007 to 2012 with SRT for mCRC; the majority of patients had oligo-metastatic disease. In half of the cases the disease involved multiple sites .Patients, diseases and treatment characteristics are shown in Table per patient at first-line SRT treatment. Most of patients had technically resectable oligo-metastatic disease (29 patients); however, they refused surgery  or had comorbidities (13 patients)  contraindicating metastasectomies or aggressive front-line chemotherapies . The SRT treatment was well tolerated; only three patients experienced persistent cough for 20 to 40 days after the last irradiation.In Table Treatments are depicted in details in Table max correlated with the local control of disease  and survival at two years (p=0.003). Interestingly, although not significant (p=0.0512) for the low numbers included, patients who received a first-line chemotherapy including bevacizumab (anti-VEGF) before SRT were more prone to respond to SRT compared to patients treated with chemotherapy only. There were no significant correlations between delta SUVmax and timing of chemotherapy (before or after SRT), response to first-line treatment, and sites of disease (Table vs ii) SRT after front-line chemotherapy. In fact, in the second group, responses to SRT could be influenced by the previous exposition of neoplastic cells to chemotherapy. There were no significant differences in terms of FDG-PET responses to SRT between different sites into the two groups; however, most of CMR and PMR according to EORTC criteria were observed in lung-limited disease patientsIn our series, all patients performed FDG-PET before and after the first administration of SRT. Figure se Table . Given tse Table  and 5b. One of the most important characteristic of our series is the mature follow-up (median follow-up: 48.8 months); forty-five events were registered, only two patients are still alive at the time of last follow-up May, 16 2017). The median PFS of the entire series was 16 months; median OS 44.0 months. Figure 017. The Agolli et al. of 36 months [Patients with mCRC may present with an oligo-metastatic disease with neoplastic lesions approachable with local treatments. In last years, many studies have been published reporting results of SRT in the treatment of oligo-mCRC –23. They6 months . In our 6 months . Interes6 months –24 consihttps://clinicaltrials.gov/). The intent of these studies is to take advantage from the immune-modulating properties of SRT in synergism with immunotherapeutic drugs to improve the anti-tumor effects.The more positive outcome of our study could be attributable to the introduction of new therapies  in the context of a continuum of care strategy. However, many patients had comorbidities excluding the administration of standard or continuous chemotherapies. A possible speculative explanation of significantly better results can rely also on different lines of SRT (re-irradiations) reinforcing the abscopal effect of radiotherapy which consists on the local induction of tumor antigens and the release of cytokines stimulating in turn the innate and adaptive immunity . HoweverInterestingly, some patients presented with poly-metastatic multi-organs disease and received a standard first-line chemotherapy as front-line therapy; in these cases, SRT was administered in “residual” disease. These patients are more similar to mCRC patients with more aggressive and widely metastatic tumors. They did not receive systemic therapy after SRT until progression. The univariate analysis showed a worse prognosis compared to patients with only lung or liver involvement; however, they had a median survival of 34 months which is superior to the survival described in last generation randomized trials , 32. LacThe neoplastic lesions responded to SRT independently from i) the primary or metastatic site, ii) the administration of upfront chemotherapy, iii) chemosensitivity of the tumor . Interestingly, the administration of bevacizumab before irradiation was slightly associated with the metabolic response (p=0.0512). Although not significant, this could be related to the effect of bevacizumab on tumor vasculature with reduction in microvessel density producing an increase of tumor oxygenation and perfusion; these phenomena are associated with increased sensitivity to radiation therapy in tumor models , 34.KRAS mutational status was not associated with response to SRT, but predicted PFS and OS at univariate analysis. The best prognostic profile in this study was represented by left sided, KRAS wild-type, lung-limited tumor. The presence of these three conditions were strongly associated with survival compared to other prognostic combinations  and with response to SRT and chemotherapy (data not shown).One of the major limitation of our study consists on the heterogeneity of patient cohort with regard to systemic treatment protocols, radiotherapy regimens (doses and timing with chemotherapy) and Kras status that, in absence of a comparator (no SRT), makes interpretation of the findings as predominantly descriptive and exploratory. However, the increasing availability of SRT along with the shorter treatment duration, the high precision and the high sparing of surrounding normal tissues, make this technique a valid option in the treatment of oligo-mCRC; in left-sided, KRAS wild-type, lung-limited tumors it could be a valid alternative to surgery. Furthermore, our experience suggests that SRT could contribute to obtain a long-term disease control also when multiple organs are involved; prospective and larger studies are needed to confirm these data.Criteria In Solid Tumors). Patients with target metastatic lesions restaged at the Radiology Unit were considered for response evaluation. Complete response (CR) was defined as complete disappearance of all detectable evidence of disease on total body computed tomography. Partial response (PR) was defined as at least a 30% decrease in the sum of diameters of target lesions. Stable disease (SD) was defined as everything between 30% decrease and 20% growth of tumor size. Progressive disease (PD) was defined as at least a 20% increase in the sum of diameters of target lesions. Toxicity was graded with the Common Toxicity Criteria for Adverse Events (CTCAE) v3.0. Local control was defined from last day of SRT to local relapse within the irradiated site. RECIST was only used to assess response to chemotherapy.Patients were treated at the Department of Abdominal Medical Oncology of the National Cancer Institute  from 2007 to 2012. Only two patients of the present cohort did not undergo to primary tumor resection because it was asymptomatic. All primary tumors were routinely characterized for KRAS (Kirsten RAt Sarcoma) oncogene mutational status. Six patients were stage III at diagnosis but they presented distant metastases three months after surgery at the first follow-up (synchronous metastases). Sequential standard treatments with chemotherapy  and/or biologic therapies  were administered. The choice of chemotherapy regimen was based on patient's performance status, extent of disease, comorbidities, previous treatments and individual preferences. Informed consent from each patient was sought. Total body computed tomography (CT) scan and CEA (CarcinoEmbryonic Antigen) monitoring were done every three months. The response to therapy was evaluated by RECIST  and after 60 days from SRT treatment (SUV2) were compared and the change was expressed as the percentage of SUV reduction (ΔSUV = (SUV1−SUV2)/SUV1×100).FDG-PET (FluoroDeoxyGlucose-Positron Emission Tomography) responses were evaluated by using the European Organization for Research and Treatment of Cancer (EORTC) criteria , 36. In per organ smaller than 7 cm or in patients who refused surgery or had comorbidities contraindicating surgery or chemotherapy. The presence of metastatic abdominal lymphnodes (until 3) did not excluded SRT. However, the indication to perform SRT was discussed in a multidisciplinary context. Notably, in few cases the transition from poly- to oligo-metastatic disease was obtained after chemotherapy; these patients were re-evaluated for SRT.Our policy was to propose SRT in patients with one to six lesions in the lungs, one to three lesions into the liver, with a cumulative maximum tumor diameter SRT was delivered according to a risk-adapted protocol; doses and fractionations were based on the size and location of the tumor . Treatment was delivered on alternate days regardless of the dose-fractionation regimen. A 4-D CT simulation scan was acquired for all patients. Respiratory gating was considered in cases where motion was > 7 mm in any direction. The gross tumor volume (GTV) was defined as the visible tumor on CT and PET imaging, and an internal GTV encompassed the GTV from all phases of respiration. A planning target volume (PTV) margin of 5 mm was used. The prescription point was approximately the 80% isodose line surrounding the PTV, with the requirement that 95% of the PTV was covered by 100% of the prescription dose. FDG-PET was performed before SRT and after 60 days from the treatment end.® 9.3.7.0 and Excel software.Results of this study are predominantly descriptive and exploratory. Associations between responses to chemotherapy, SRT and clinical and pathologic variables  were evaluated by χ 2 test. P < 0.05 was considered statistically significant. Progression-free survival (PFS) was defined as the time elapsed from front-line treatment start to progression of the cancer as it occurred first; overall survival (OS) was defined as the time elapsed from the diagnosis to death from any cause. The Kaplan-Meier product limit method was applied to graph OS and PFS. Survival was measured from diagnosis in order to avoid generation of prognostic subgroups related to different treatments start times. Univariate analysis was done with the log-rank test. No attempt was done to perform multivariate analysis because of small number of cases. Statistical analysis was performed using the MedCalc


Regeneration Rosetta. Using either built-in or user-provided lists of genes in one of dozens of supported organisms, our web application facilitates the (1) visualization of clustered temporal expression trends; (2) identification of proximal and distal regions of accessible chromatin to expedite downstream motif analysis; and (3) description of enriched functional gene ontology categories. By enabling a straightforward interrogation of these rich data without extensive bioinformatic expertise, Regeneration Rosetta is broadly useful for both a deep investigation of time-dependent regulation during regeneration in zebrafish and hypothesis generation in other organisms.Time-course high-throughput assays of gene expression and enhancer usage in zebrafish provide a valuable characterization of the dynamic mechanisms governing gene regulatory programs during CNS axon regeneration. To facilitate the exploration and functional interpretation of a set of fully-processed data on regeneration-associated temporal transcription networks, we have created an interactive web application called  Axon degeneration accompanying central nervous system (CNS) injury or disease leads to a permanent loss of function in human patients. This is largely due to an inability of mammals to reinitiate axon growth in adult CNS neurons . In contTranscriptional changes have long been correlated with the intrinsic capacity for regenerative axon growth . In ordeRegeneration Rosetta, as a means to explore, visualize, and functionally interpret regeneration-associated gene expression and chromatin accessibility. Using either built-in lists of differentially expressed (DE) genes from These data on regeneration-associated temporal transcription networks in zebrafish represent a rich source of information with wide potential use and insight for the broader regeneration community. To this end, we provide fully processed data from Regeneration Rosetta app represents a new paradigm to facilitate data sharing and re-use in the field of regeneration. This type of data sharing directly promotes the National Institutes of Health guidelines for ensuring rigor and reproducibility in pre-clinical research . As large-scale genomic data become more common, tools that allow rapid querying and exploration of fully processed data  will be critical in accelerating advances in the regeneration field.The n = 3 at each time point). For the RNA-seq data, we tested differential expression with respect to the initial time point (0 dpi), controlling the false discovery rate at 5%. For the ATAC-seq data, sequences were aligned . A proximal peaklet was then defined as one that overlaps the TSS and/or is within ±1kb of the TSS, while a distal peaklet was defined as one within ±100kb of the TSS but not proximal. Users can optionally remove exonic peaklets from these lists, defined as those within 50bp of exonic regions but not overlapping a TSS. To identify genes that are proximal or distal to a given set of accessible chromatin , users may choose to include all genes or only a subset of those identified to be DE at a particular time point.For peaklets identified as proximal or distal to the query set of genes, a FASTA file of sequences and BED file of genomic coordinates may be downloaded by the user for further analysis; in addition, a CSV file providing the potentially many-to-many correspondences of proximal and distal peaklets to genes may also be downloaded.Regeneration Rosetta app. These include the lists of DE genes  compared to 0 dpi, as well as pre-identified clusters with expression patterns roughly corresponding to established events in the regeneration process . Users may also employ the Regeneration Rosetta app to explore gene sets for one of 68 species , or Z-scores of these measures are produced using Regeneration Rosetta performs on-the-fly functional enrichment analyses of GO terms for Biological Processes (BP), Cellular Components (CC), and Molecular Function (MF) for a given gene set using topGO with the weight01 algorithm, Fisher test statistic, and gene universe defined as the set of expressed transcripts from Regeneration Rosetta would typically make use of lists of regeneration-related genes from one of the supported organisms to understand their behavior in the gene expression and chromatin accessibility data of The Regeneration Rosetta interactive web app was built in R using the Shiny and flexdashboard packages. In addition to the other software packages already cited above, it makes use of the data.table and RSQLite R packages for fast data manipulation, DT for rendering HTML tables using JavaScript, readxl for parsing data from Excel spreadsheets, dplyr for data manipulation, and tokenizers to convert user-provided gene IDs into tokens. The Regeneration Rosetta R/Shiny app is available at http://ls-shiny-prod.uwm.edu/rosetta/. A FAQ page is available directly on the app website. Source code for the Regeneration Rosetta is available from GitHub: https://github.com/andreamrau/rosetta. The processed data used within the app are directly located in https://github.com/andreamrau/rosetta/tree/master/data; scripts used to process the raw data from https://github.com/andreamrau/OpticRegen_2019. Archived source code at the time of publication can be found at https://doi.org/10.5281/zenodo.2658771. The Regeneration Rosetta app was developed under a GPL-3 software license. Supplemental material available at figshare: https://doi.org/10.25387/g3.8856227.The Regeneration Rosetta, we input a list of 125 genes with cholesterol-related GO terms obtained from the Mouse Genome Informatics (MGI) database  in Regeneration Rosetta, AME motif analysis , were also enriched for SREBF2 motifs; SREBF1 is a transcription factor related to SREBF2 that is known to regulate genes involved in fatty acid synthesis and lipid homeostasis  of SREBF2, a known cholesterol master-regulatory transcription factor , we identified 734 (brain) and 846  differentially expressed genes, where 483 were shared between the three data sets  and 53  DE transcription factor encoding genes that were differential in the zebrafish optic nerve regeneration data . Assessing the combined list of DE transcription factors, we found that 25 transcripts corresponding to 21 transcription factor encoding genes are shared among CNS neuron responses to axonal injury in the lamprey spinal cord and brain, and zebrafish optic nerve  provide a useful a framework for sharing results and data. The Regeneration Rosetta app will be widely useful, both for further investigation and interpretation of the data from The


Several studies emphasized the potential of single and multiple transcranial random noise stimulation (tRNS) sessions to interfere with auditory cortical activity and to reduce tinnitus loudness. It was the objective of the present study to evaluate the use of high-frequency (hf) tRNS in a one-arm pilot study in patients with chronic tinnitus. Therefore, 30 patients received 10 sessions of high frequency tRNS  over the bilateral temporal cortex. All patients had received rTMS treatment for their tinnitus at least 3 months before tRNS. Primary outcome was treatment response (tinnitus questionnaire reduction of ≥5 points). The trial was registered at clinicaltrials.gov (NCT01965028). Eight patients (27%) responded to tRNS. Exactly the same number of patients had responded before to rTMS, but there were only two “double responders” for both treatments. None of the secondary outcomes  was significant when results were corrected for multiple comparisons. tRNS treatment was accompanied by tolerable side effects but resulted in temporal increases in tinnitus loudness in 20% of the cases (2 drop-outs). Our trial showed that hf-tRNS is feasible for daily treatment in chronic tinnitus. However, summarizing low treatment response, increase of tinnitus loudness in 20% of patients and missing of any significant secondary outcome, the use of hf-tRNS as a general treatment for chronic tinnitus cannot be recommended at this stage. Differences in treatment responders between tRNS and rTMS highlight the need for individualized treatment procedures. Technically, tRNS represents a special form of transcranial alternating current stimulation (tACS) with the current alternating at random normally distributed frequencies. tRNS is typically applied as low frequency tRNS , high frequency tRNS  or as whole frequency tRNS . tRNS has demonstrated more pronounced effects on motor cortex excitability than other non-invasive brain stimulation techniques such as anodal transcranial direct current stimulation (tDCS) or intermittent theta burst TMS  (iTBS)2. Even short-term tRNS of 4 minutes was shown to modulate the blood oxygen level dependent (BOLD) signal in the human motor cortex3. Its putative mechanism of action is the enhancement of neuronal noise and the decrease of hypersynchronicity4. It was hypothesized that the main mechanism of tRNS action was based on repeated subthreshold stimulations, which might prevent homeostasis of the system and potentiate task-related neural activity5.Transcranial random noise stimulation (tRNS) is a non-invasive brain stimulation method using varying alternating currents to interfere with oscillatory brain activity6, schizophrenia7, neuropathic pain8, and fibromyalgia9. It has been shown to modulate pain perception in multiple sclerosis10. hf- tRNS has also been found to be able to enhance mathematical ability speed11 and perceptual learning5. In a case report the successful treatment of a patient suffering from “Red Ear Syndrome” by high-frequency tRNS was registered12. The “Red Ear Syndrome” contains a symptom complex of auricular erythema, attack-like local pain and tinnitus perception13.tRNS has been proposed as a treatment option for major depression14.In patients with tinnitus, the effects of single sessions of tDCS, tACS and low-frequency tRNS of the auditory cortex were compared regarding tinnitus loudness and the tinnitus-related distress after stimulation of the auditory cortex. A direct comparison of three non-invasive stimulation methods applied to the bilateral auditory cortex in 111 tinnitus patients demonstrated that the transient suppressive effect on tinnitus loudness and tinnitus related distress was larger after tRNS compared to tDCS and tACS. Both tDCS and tACS induced small and non-significant effects on tinnitus perceptions, suggesting lf-tRNS as a superior brain stimulation method for tinnitus suppression15. The differential effects of high- and low-frequency tRNS targeting the auditory cortex were investigated by Joos et al.16 in 154 chronic tinnitus patients. A total of 119 patients was treated with lf-tRNS, 19 with hf-tRNS and 16 with wf-tRNS. The effects were evaluated applying numeric rating scales for loudness and distress for the states pre- and post-stimulation. This study showed a significant reduction in tinnitus loudness for both lf-tRNS and hf-tRNS as well as reduced tinnitus-related distress with lf-tRNS. However, hf-tRNS resulted in a more pronounced reduction of loudness and distress in pure tone tinnitus than in narrow band noise tinnitus16. This is in line with results derived from motor-cortex tRNS applications indicating a higher effectiveness for hf-tRNS1.A recent proof-of-concept study provides evidence on an added value of bilateral temporal lf-tRNS treatment following bifrontal tDCS in 40 patients reporting chronic tinnitus4 indicating that previously described mechanisms of actions derived from motor-cortical areas could potentially be transferred to the auditory cortex. Van Doren et al. applied EEG measures to examine tRNS induced changes in resting state activity and auditory steady state responses (ASSRs). 1000 Hz carrier frequency tones with amplitudes modulated at 20 Hz and 40 Hz applied in randomized order were applied as stimuli. Fourteen healthy subjects took part in this placebo-controlled randomized design study; each of the participants received 20 min of tRNS applied over the auditory cortices with 2 mA. The study resulted in significant increases regarding the ASSR in response to 40 Hz frequency modulated tone and non-significant trends towards an increase in mean theta band power and variability of the theta band power for the resting state data. Although the authors interpreted their results of tRNS induced increased excitability of the auditory cortex in line with tRNS effects on motor cortex excitability, it should not be concealed that stimulation parameters used in this study significantly differ from the “conventional” study protocols targeting motor cortical areas with regard to higher stimulation intensities and longer stimulation periods4.Moreover, a sham-controlled trial demonstrated that resting state and steady state activity of the auditory cortex were lowered by hf-tRNS in a sample of healthy controlsIn sum, single studies highlight the capability of different types of tRNS among tES techniques to modulate tinnitus loudness and distress effectively. Here we aimed to investigate the effects of multiple sessions of hf-tRNS in a one-arm pilot study in patients with chronic tinnitus who had already received repetitive transcranial magnetic stimulation.17; total score); tinnitus laterality: one purely right-sided, seven purely left-sided, 22 with tinnitus in both ears or within head; tinnitus duration: 96.0 ± 73.7 months).We included 30 patients with chronic tinnitus : 20.1 ± 12.5 dB HL; tinnitus distress: 45.8 ± 19.3 [range: 9–80] tinnitus questionnaire (TQ4. Patients were treated for 10 consecutive working days beginning with Monday and pausing at weekend.Patients were stimulated with 2 mA (0 off-set) over the bilateral temporal cortex for 20 minutes . The cathode was always applied to the left hemisphere and the anode to the right hemisphere with the inferior center of the electrode over the EEG position T7/T8. The long side of the electrodes was oriented in anterior-posterior direction. We used hf-tRNS (100–640 Hz) applied by a NeuroConn  DC-Stimulator Plus device for ten days. Stimulation procedures were similar to earlier published data in healthy controlsStudy visits were done in the hospital, included measurement of tinnitus characteristics and questionnaires, and took place at baseline (treatment day 1), week2 (treatment day 10/end of treatment), follow-up visits were conducted in week4 and 12 .All patients had previously received a rTMS treatment series 22.6 ± 27.1 months (range 3–108 months) before enrolment in the tRNS study. However, the main focus of the study was the investigation of tRNS in tinnitus in a sample of patients pre-treated with rTMS. However, it was not pre-specified that rTMS has to be standardized with respect to the rTMS protocol and the time difference between both treatments. The rationale was to be able to estimate differences in the efficacy of both treatments. Tinnitus distress for the patients was comparable between the baseline visit of the rTMS and the tRNS treatment . Detailed rTMS treatment parameters differed between patients due to the participation in different rTMS studies in our center. We contrasted both types of treatment (tRNS vs. rTMS). For an overview of demographics and rTMS study parameters see supplementary information.17 of five points or more according to Adamchic et al.18 from baseline to week 12. The Tinnitus Questionnaire (TQ) was initially developed by Hallam et al.19 and has been translated and adapted by Goebel and Hiller in 199417. This instrument differentiates between emotional and cognitive distress, auditory perceptual difficulties and self-experienced intrusiveness produced by the tinnitus. Broadly accepted as an outcome measure in clinical studies on chronic tinnitus, the TQ can be employed both for comparative studies in different tinnitus-related institutions and for the evaluation of the relative effects of different treatment approaches.17Treatment response (primary outcome) was defined as reduction in the tinnitus questionnaire et al.20, numeric rating scales for tinnitus loudness, discomfort, annoyance, ignorability and unpleasantness , and WHO Quality of Life questionnaire (WHOQOL-BREF)21 over the course of the trial. Data were assessed according to international standards23 and registered in a tinnitus database following ICH-GCP-regulations24. Secondary outcome variables were used for direct contrast between baseline and final to see if tRNS has treatment effects. Analyses of variance with the dependent variables TQ, MDI, numeric ratings, and quality of life and with the independent factors time (visits) and treatment  were used to see if there is a difference of tRNS with respect to pre-treatment with rTMS. All results from statistical analyses of secondary outcomes were also calculated with corrections for multiple comparisons by using Bonferroni corrections. All data are displayed as mean ± standard deviation if not otherwise labelled. Significance threshold was set to 5%. We conducted a per-protocol analysis (n = 26). Missing data were replaced with last-observation-carried-forward method.To investigate possible association of treatment response between tRNS and rTMS we calculated a Chi-Square-test. Secondary outcomes were changes in TQ, Major Depression Inventory (MDI) by Bech hf-tRNS is a relatively new type of brain stimulation in daily treatment. Therefore, further objectives were the assessment of adverse events and safety information by the application of standardized questionnaires at all visits. Data were available for 18 patients who answered on a 10-point numeric scale (1 (not) to 10 (extreme)) the occurrence of side effects. Cognitive effects were tested with measures of tonic and phasic alertness, working memory and divided attention as elicited by the Test of Attentional Performance . Cognitive data were available for 23 patients.25 and registered in an established tinnitus database following ICH-GCP-regulations23. The trial was registered on clinicaltrials.gov  and approved by the local ethics committee of the University Hospital Regensburg (13-101-0143). All participants gave written informed consent after a comprehensive explanation of the study procedures. All methods were performed in accordance with the relevant guidelines and regulations.Data were assessed according to international standardsSix patients perceived temporal increases in tinnitus loudness  and two patients reported headaches (one drop-out). One patient did not finish the treatment due to personal reasons . Reported adverse effects were the perception of mild to extreme pain (17% out of 18 patients), tingling (72%), burning (28%), tiredness (56%), nervousness (22%), concentration problems (39%), visual problems (11%), headaches (39%), itching (39%), dizziness (11%), lightnings (6%) and sounds (28%) during or after the stimulation. 44% reported sleeping problems. In general 17% rated the stimulation as unpleasant. One patient presented high ratings of all side effects. With respect to cognitive effects of the stimulation, quantitative analyses of norm T scores showed mean numeric increases over the course of the trial . For detailed information with respect to kind of rTMS treatment and response to rTMS and tRNS see supplementary information. Most of the rTMS treatments included prefrontal and temporal/temporoparietal stimulation and indicated no specific association of treatment response and kind of treatment. This study was not designed as study to investigate the additive effects of rTMS treatment and tRNS treatment. rTMS treatment serves as control condition for statistical reasons but was not Contrasts from baseline to final visit for tRNS treatment resulted in significant decreases for tinnitus annoyance, unpleasantness and depressivity Table . Analyse1. Accordingly, no erythema or burning skin lesion were observed in our study. In our clinical cohort no significant effects on cognitive functioning were detected assuming tRNS of the bilateral temporal cortex as a safe procedure even if applied on a repetitive basis of 10 sessions. Decreases in performance by one standard deviation in single cases did not exceed the number of increases of performance by one standard deviation. Nonetheless, single cases with amelioration TAP-scores suggest that hf-tRNS may have potential to improve cognitive functioning under certain conditions. Even if we have no systematic or obvious deterioration in cognitive functions, further detailed investigations seem to be required.Treatment of chronic tinnitus with hf-tRNS is easily applicable, showed tolerable side effects, but resulted in temporal increases in tinnitus loudness in 20% of the cases leading to two drop-outs. One advantage over rTMS is that tRNS is not associated with pulsed local aversive sensations inherent to TMS stimulation. During tRNS patients report either constant slight tingling or no local sensations at all. As tRNS provides a balanced current stimulation it is considered even safer than tDCS, which induces a polarizing stimulation possibly leading to skin lesions under certain conditions26.tRNS treatment was detected to be effective in 31% of the patients who completed the treatment indicated by clinical response defined by an at least 5 point reduction in the TQ (the response rate in the intention-to-treat population was 27%). This response rate was comparable to rTMS efficacy in earlier trials of our center27. However, in predictor analyses concerning brain stimulation methods in chronic tinnitus, no impact of hearing level on clinical outcome could be detected so far28.A potential objection of the present study might be the missing measurement of individual hearing loss, as this is well known and broadly accepted as a central risk factor for the development of chronic tinnitusNotably, treatment response to rTMS in our study sample did not predict treatment response to tRNS. Please note, that it was not the intention of the present study to investigate the additive effects of rTMS treatment and tRNS treatment . In addition to these arguments related to study design, potential carry-over effects cannot reliably and totally be ruled out although the authors consider them as unlikely in the view of the long (minimum 3 months) wash-out periods between the two courses of brain stimulation techniques. The exact time spans are proved in detail for each participant in a table in supplementary information. The authors suggest not to over-interpret the comparing analyses between rTMS and tRNS treatment. However, they feel that it may indeed serve as a helpful tool to estimate the potential of hf-tRNS treatment in a naturalistic setting of a variety of differential brain stimulation techniques targeting chronic tinnitus perceptions.29. However, it has to be stated that in the presented study we did not evaluate possible immediate effects of single-sessions of tRNS in our patients. These issues will have to be addressed in upcoming studies.Only two “double responders” according to the criterion mentioned above were detected in our study cohort. This observation might favor an individualized treatment approach. For brain stimulation techniques, such an approach could be realized by utilizing single test sessions as predictors for daily treatment. Such attempts have already been suggested in rTMS applications for different stimulation targets and parameters providing innovative treatment strategies in chronic tinnitus4. However, we would strongly suggest not to over-interpret this result as it might be purely attributable to multiple testing. In line with this argumentation we abstain from over-interpretation of the physical quality of life findings. No other secondary outcome over the course of the treatment was significant. In sum, for the whole group we could not demonstrate efficacy of hf-tRNS for treatment of chronic tinnitus.Specific changes in tinnitus unpleasantness after tRNS in contrast to rTMS might be explained by the stimulation of more medial temporal areas such as posterior insula or hippocampus as a summation effect of electric currents in border regions linking different types of tissues16. In sum, most tRNS studies in tinnitus used lf-tRNS and showed efficacy. One direct comparison of hf- and lf-rRNS turned out that lf-tRNS might be superior to hf-tRNS with respect to tinnitus distress16. Both interventions were similar effective with respect to tinnitus loudness. Hf-tRNS turned out to be more effective for pure-tone in contrast to noise-like tinnitus. Although there is evidence from steady state EEG data and auditory evoked potentials that tRNS effect to the auditory might parallel the effects in motor-cortical areas4, the optimal frequency spectrum for stimulation of the auditory cortex in tinnitus patients remains a matter of debate.A factor of uncertainty is the use of hf-tRNS (100–640 Hz) as there is evidence for efficacy of lf-tRNS in chronic tinnitusAnother limitation of our study is the fact, that all patients had already absolved one rTMS treatment series introducing a possible selection bias. However, the fact that positive response to rTMS treatment did not predict response in the present tRNS-based study suggests different underlying mechanisms of both stimulation techniques. The authors are well aware of the fact that unspecific effects cannot be reliably ruled out. Nevertheless, the fact that all patients already participated in a neurostimulation treatment study before, makes it rather improbable that the observed effects are purely unspecific effects, as unspecific effects of rTMS and tRNS should resemble each other. In addition, an optimal design would have included a placebo group/condition. For ethical reasons, we decided to use a real-life application using a within-subjects design with the factor of different conditions.Taken together, our pilot study provides evidence for the feasibility of high-frequency tRNS in the treatment of chronic tinnitus and demonstrated an identical low response rate compared to transcranial magnetic stimulation in a study cohort which was treated almost two years after the first neurostimulation treatment attempt with rTMS. In sum, the trial was negative as no secondary outcome measure was significant including TQ (the basis for the definition of treatment response). As the subgroup of patients who responded to hf-tRNS differed from rTMS responders, the results advocate to further focus on individualized treatment approaches.table 2


Non-contact resonant ultrasound spectroscopy (NC-RUS) has been proven as a reliable technique for the dynamic determination of leaf water status. It has been already tested in more than 50 plant species. In parallel, relative water content (RWC) is highly used in the ecophysiological field to describe the degree of water saturation in plant leaves. Obtaining RWC implies a cumbersome and destructive process that can introduce artefacts and cannot be determined instantaneously.Viburnum tinus leaf samples with Pearson’s correlations between 0.92 and 0.84.Here, we present a method for the estimation of RWC in plant leaves from non-contact resonant ultrasound spectroscopy (NC-RUS) data. This technique enables to collect transmission coefficient in a [0.15–1.6] MHz frequency range from plant leaves in a non-invasive, non-destructive and rapid way. Two different approaches for the proposed method are evaluated: convolutional neural networks (CNN) and random forest (RF). While CNN takes the entire ultrasonic spectra acquired from the leaves, RF only uses four relevant parameters resulted from the transmission coefficient data. Both methods were tested successfully in This study showed that the combination of NC-RUS technique with deep learning algorithms is a robust tool for the instantaneous, accurate and non-destructive determination of RWC in plant leaves. Most common methods to asses plant water status, through the measurement of either relative water content or water potential –4, are dTLP) obtained using the NC-RUS technique did not show any significant difference compared to those obtained using p–v curves approximation  has been proven as a non-destructive, non-invasive and rapid method for the dynamic determination of leaf water status . NC-RUS ion Fig. b. In parTLP requires of a whole set of RWC values for its computation.All these physical parameters obtained from ultrasonic measurements can provide critical information about the leaf properties and their relation with the leaf water status, specifically with the relative water content (RWC) . RWC is This work represents a step forward in the instantaneous estimation of RWC in a non-invasive, non-destructive and rapid way. The proposed approach uses NC-RUS measurements and apply advanced machine learning regression and especially deep-learning method to infer RWC value from one single measurement. Deep convolutional neural networks (CNN)  is the mTable Additional file Figure Viburnum tinus leaves.The proposed technique for an instantaneous estimation of RWC through non-invasive and non-destructive ultrasonic measurements combined with machine learning approaches has been proved successfully in In general, transmission coefficient spectra obtained using the NC-RUS technique are able to monitor changes in the water status of leaves connected or detached to the plant rapidly without direct contact. In this work, we combined this ultrasonic technique with two different machine-learning algorithms in order to translate that information directly into a well-known and widely used parameter as RWC. Our main aim is to obtain RWC instantaneously, avoiding the normalization process and hence the need of previously knowing the fresh and dried mass of the sample under study.V. tinus leaves covering different hydration states were used in this work, comprised of NC-RUS transmission coefficient spectra and their corresponding RWC values measured experimentally. Sixty-three percent of the measurements corresponded to RWC values in the range of 1 to 0.88 , while the rest (37%) are distributed between 0.88 and 0.52 (below TLP). Although we had enough data points to achieve good correlation models throughout the whole RWC range  contained information enough about the water status of the leaf to train and estimate its RWC value. This assumption was successfully revealed on the RF results, whose correlation is slightly below the one performed using CNN. The main advantage of the RF-based approach is that the frequency range of the ultrasonic transmission coefficient needed is narrower and thus the measurement only require one pair of ultrasonic sensors.We proposed herein a new tool to estimate instantaneously RWC from ultrasonic measurements using NC-RUS technique in a non-destructive and non-invasive way applying two different machine-learning algorithms (CNN and RF) previously trained with experimental data coming from leaves within the same species and location. Although both algorithms excelled in performance, we consider that RF resulted more convenient since is able to predict RWC values using only one pair of ultrasonic transducers centered at the same working frequency. This might be translated into a faster, easier and cheaper application in the field.Further work on collecting RWC-ultrasonic experimental data from different species or same species at different locations must be done in order to evaluate the suitability of applying transfer-learning methods, which can lead to a big improvement on the scalability of this technique.Altogether, NC-RUS and the proposed RWC estimation method have the potential of becoming a rapid and robust tool to measure the hydration state of plants, which may provide a breakthrough in the irrigation scheduling of agriculture systems.Viburnum tinus leaves were collected from The Royal Botanical Garden of Madrid  steadily during 18 months. The easy availability of V. tinus leaves throughout the year and the high accuracy of NC-RUS measurements in this species, promoted its selection as plant material for this study. In the early morning, branches were collected, rapidly introduced in plastic containers with water in order to ensure a water–vapor saturated atmosphere and carried to the laboratory. Once in the lab, shoots were re-cut under water to avoid embolism and kept immersed (avoiding the wetting of leaves) for 24 h at 4 °C to ensure full leaf hydration  were used in this work.Additionally, we also extracted four parameters whose relevance is known from previous works. They are: the maximum value of the magnitude of the transmission coefficient, the phase and the frequency at which this maximum is located and the bandwidth of the first resonance peak  .Measurements were grouped by leaf, forming 31 groups with variable amount of data representing different NC-RUS measurements at several time points  obtained from the same leaf. A leave-one-out cross-validation (CV) strategy using these groups was followed to train and evaluate a model for the prediction of RWC values from NC-RUS measurements. Therefore, in each round of the cross-validation procedure, measurements coming from 30 leaves were used for training purposes, and the evaluation was performed over all measurements from the leaf that is left. We named this strategy as leaf-one-out CV (leafOO-CV). It represents a realistic practical scenario where a RWC-prediction model would be used to estimate the RWC of a completely new leaf that was never used for training that model.A deep learning approach using one-dimensional (1D) convolutional neural networks (CNN) was used to create a regression model able to predict RWC from magnitude and phase NC-RUS spectral data, with the objective of fully using all the NC-RUS available information, and also exploiting the non-independent relationship that exist between signals measured in nearby frequencies Fig. . AdditioThe architecture of the CNN comprised a total of 18 layers, including 3 1D-convolutional layers using  kernels with sizes , respectively, and 3 fully connected layers with  nodes, respectively, as depicted in Fig. The more traditional RF machine-learning approach that we tested bagged an ensemble of 400 regression trees using bootstrap samples. We used sampling with replacement, half of the number of variables for each decision split, and a minimum number of 3 observations per tree leaf .The imbalanced learning problem, caused by the huge dominance of RWC values close to 1 in our dataset, limited the proper construction of regression models able to generalize estimations in the whole range of possible RWC measurements . In ordePrediction of RWC values were performed at each leafOO-CV round in samples corresponding to the leaf that was left from training, using the correspondent CNN and RF regression models. To evaluate the goodness of RWC estimations, root mean square errors (RMSE) were calculated. A global RMSE, together with the Pearson’s linear correlation coefficient (R), were reported using final RWC-predictions of all samples from the 31 testing leaves. Additionally, we also extracted RMSE and R values obtained after grouping and computing the mean of predictions for the seven interpolated versions of NC-RUS measurements .Additional file 1: Figure S1. Statistical analyses. a) Boxplots comparing interpolation methods for prediction of RWC values with CNN (left) and RF (right) approaches. Prediction errors obtained with each approach are not statistically different when using data preprocessed with different interpolation methods (repeated measures ANOVA with both Bonferroni and Tukey-Kramer multiple comparison tests). b) Boxplot displaying RMSE values computed individually on each leaf confirm the superior performance of CNN method for estimation of RWC values .


The abducens nucleus (nVI) contains several functional cell groups: motoneurons of the singly-innervated twitch muscle fibers (SIF) and those of the multiply-innervated muscle fibers (MIF) of the lateral rectus muscle (LR), internuclear neurons (INTs) projecting to the contralateral oculomotor nucleus (nIII) and paramedian tract-neurons (PMT) that receive input from premotor neurons of the oculomotor system and project to the floccular region. In monkey, these cell populations can be delineated by their chemical signature. For correlative clinico-pathological studies the identification of the homologous cell groups in the human nVI are required. In this study, we plotted the distribution of these populations in monkey nVI by combined tract-tracing and immunohistochemical staining facilitating the identification of homologous cell groups in man. Paraffin sections of two Rhesus monkeys fixed with 4% paraformaldhehyde and immunostained with antibodies directed against choline acetyltransferase (ChAT) as marker enzyme for cholinergic neurons and chondroitin sulfate proteoglycan (CSPG) to detect perineuronal nets (PNs) revealed four neuron populations in nVI with different chemical signatures: ChAT-positive and CSPG-positive SIF motoneurons, ChAT-positive, but CSPG-negative MIF motoneurons, and ChAT-negative neurons with prominent PNs that were considered as INTs. This was confirmed by combined immunofluorescence labeling of cholera toxin subunit B (CTB) or wheat germ agglutinin (WGA) and ChAT or CSPG in nVI sections from cases with tracer injections into nIII. In the rostral part of nVI and at its medial border, populations of ChAT-negative groups with weak CSPG-staining, but with strong acetylcholinesterase (AChE) activity, were identified as PMT cell groups by correlating them with the location of anterograde tracer labeling from INTs in nIII. Applying ChAT- and CSPG-immunostaining as well as AChE staining to human brainstem sections four neuron groups with the same chemical signature as those in monkey could be identified in and around the nVI in human. In conclusion, the distribution of nVI neuron populations was identified in human based on findings in monkey utilizing their markers for cholinergic neurons and their different ensheathment by PNs of the extracellular matrix. Recording and anatomical tract-tracing studies in vertebrates revealed that the abducens nucleus (nVI) contains several functional cell groups  whose axons travel up within the contralateral medial longitudinal fascicle (MLF) to target the medial rectus (MR) motoneurons in the contralateral nIII -based perineuronal nets (PNs). As SIF-motoneurons, INTs are ensheathed by PNs, but they are not cholinergic and therefore choline acetyltransferase (ChAT)-immunonegative  directed against the whole enzyme isolated from human placenta, which is identical to the brain enzyme  a mouse monoclonal antibody  directed against a brain CSPG core protein, obtained with feline spinal cord fixed gray matter as immunogen; and (2) a polyclonal rabbit antiserum  raised against CSPG purified from bovine nasal cartilage and digested with chondroitinase ABC. It recognizes the antigenic determinants present on the sulfated glucuronic acid-As a further CSPG marker, a monoclonal antibody raised against purified human articular cartilage aggrecan (ACAN) was used. The applied liquid tissue culture supernatant was obtained from Acris  was detected with a polyclonal goat antibody .Polyclonal goat anti-choleragenoid  was used to detect the tracer cholera toxin subunit B (CTB) provided by the same manufacturer. Tracing and detection method of CTB has been successfully applied in numerous previous studies  were obtained 24 h after death through the Reference Center for Neurodegenerative Disorders of the Ludwig-Maximilians Universität, one case (H4) 8 h after death from the Department of Forensic Medicine , pH 7.4, containing 0.3% Triton X-100 (NDS-TBS-T) for 1 h at room temperature. Subsequently, the sections were processed with a mixture of goat anti-ChAT  and rabbit anti-CTB  in NDS-TBS-T for 48 h at 4°C. After three washes in 0.1 M TBS, the sections were treated with a mixture of Cy3-conjugated donkey anti-rabbit IgG  and Alexa Fluor 488-tagged donkey anti-goat IgG  for 2 h at room temperature. Sections of case M3 were incubated in NDS-TBS-T and then processed with a mixture of goat anti-WGA (1:250 in NDS-TBS-T) and mouse anti-ACAN (1:75). After three washes in 0.1 M TBS, the sections were incubated with a mixture of Alexa Fluor 488-conjugated donkey anti-goat IgG  and Cy3- conjugated donkey anti-mouse IgG . After a short rinse in distilled water sections were dried and coverslipped with permanent aqueous mounting medium  and stored in the dark at 4°C.For single immunoperoxidase staining for either CTB, ChAT or CSPG selected brainstem sections were processed free-floating with polyclonal goat antibodies directed against either CTB  or ChAT  or with rabbit anti-CSPG  for 48 h at 4°C. All markers were visualized by binding of biotinylated donkey-anti-goat IgG  or biotinylated donkey anti-rabbit IgG  followed by extravidin-peroxidase  and diaminobenzidine (DAB) as chromogen to yield a brown color.2O2 in TBS for 30 min, were rinsed again, and preincubated with NDS-TBS-T for 1 h at room temperature. The sections were then processed with a mixture of goat anti-ChAT  and rabbit anti-CSPG  in NDS-TBS-T for 16 h at room temperature. After washing in 0.1 M TBS, the sections were incubated in a mixture of biotinylated donkey anti-goat IgG  and donkey anti-rabbit IgG (1:100 Dianova) in TBS containing 2% bovine serum albumin (TBS-BSA) for 1 h. For the detection of ChAT, the sections were incubated with preformed streptavidin/biotinyl-peroxidase complexes for 1 h according to Härtig et al.  for 1 h. After two rinses with TBS and one wash in 0.05 M Tris-buffer, pH 7.6, the sections were stained with 0.05% DAB and 0.015% H2O2 as chromogen for 10–15 min resulting in a brown staining of PNs. The sections were extensively washed with TBS, briefly, with distilled water, air-dried and coverslipped with Entellan in toluene .Series of paraffin sections from monkey (M1) and human  were processed for the concomitant detection of ChAT-positive neurons and CSPG-containing PNs as described previously  equipped with appropriate filters for red fluorescent Cy3 (N2.1) and green fluorescent Cy2 or Alexa 488 (I3). Photographs of brightfield and fluorescence preparations were taken with a digital camera  mounted on the microscope . The images were captured on a computer with Pixera Viewfinder software (Klughammer) and processed with Photoshop 7.0 software . The sharpness, contrast and brightness were adjusted to reflect the appearance of the labeling seen through the microscope. All pictures were arranged and labeled with drawing software .Paraffin sections of monkey and human nVI stained for ChAT and CSPG were imaged using a slide scanner  equipped with a plan Apochromate objective (×20). The digitized images were viewed on a computer with the free software Panoramic Viewer . Different neuron populations were plotted on zoomed images using a counter plugin (3DHistech). The images were taken as template for the reconstructions using drawing software . This software was used to arrange and label the figure plates.Ntot = 545; Figures The simultaneous detection of CSPG and ChAT in monkey paraffin sections revealed that the vast majority of cholinergic neurons within nVI is associated with prominent CSPG-immunoreactive PNs enwrapping somata and proximal dendrites (47%; At more rostral planes another PMT cell group, the rostral cap of nVI, is outlined by anterograde labeling Figures . NotablyIn human, the nVI was found on transverse sections at the pontine-medullary junction stretching between the planes of the oral end of the facial nucleus caudally and the caudal end of the motor trigeminal nucleus rostrally (Büttner-Ennever and Horn, Ntot = 387; Figures As in monkey, the nVI was highlighted by its content of CSPG-immunopositive PNs Figures , brown aPlotting on four transversal planes through the human nVI revealed that cholinergic neurons lacking PNs were preferentially located at the ventromedial aspect of nVI Figures , whereasThe close inspection of the nVI vicinity in AChE-stained sections revealed the putative homologous PMT cell groups in human. At planes through the rostral nVI neuronal cell bridges between neurons medial to the exiting NVI to the midline were seen with diffuse CSPG-labeling Figures  and AChEUtilizing the chemical signature of motoneurons and INTs in monkey, four functional cell groups were distinguished in and around the nVI: motoneurons of MIFs and SIFs innervating the LR, as well as INTs and PMT cell groups. Accordingly, the homologous cell groups of MIF- and SIF-motoneurons and INTs were identified in human—based on the histochemical properties found in rhesus monkey. Similarly, the putative PMT cell groups associated with nVI in human were localized.In accordance with former studies the present work revealed two populations of cholinergic neurons in and around the nVI in monkey and man (Eberhorn et al., Based on previous tract-tracing studies the ChAT-positive neurons with PNs are considered as motoneurons targeting twitch muscle fibers via single en plaque endplates in the LR (Büttner-Ennever et al., The ChAT-positive neurons without PNs may represent the motoneurons of MIFs and most probably include the cell bodies of palisade endings targeting the myotendinous junction of all EOMs (Lienbacher et al., Not much is known about the location of the motoneurons of the orbital layer, which does not insert into the sclera of the eye bulb but into collagen of the pulleys and thereby alters the functional origin of the muscle, which determines its pulling direction (Demer et al., In cat, early electron microscopic studies applying AChE staining had already demonstrated that motoneurons differ from INTs by their histochemistry. AChE staining was found associated with the endoplasmic reticulum, the soma-dendritic and axonal surface of motoneurons, but was absent from INTs (Spencer and Baker, In cat, more than 80% of the INTs but no motoneurons express the calcium-binding protein calretinin (de la Cruz et al., The presence of motoneurons and INTs is a constant feature in vertebrates throughout the evolution and provides the neuroanatomical basis for conjugate horizontal eye movements, but their location varies between species. While birds and teleosts show a high degree of segregation of INTs and motoneurons (Labandeira-Garcia et al., According to data on PMT neurons from Büttner-Ennever et al. , anterogvice versa (Armstrong et al., The observation of Rodella et al. , who fouvia their connections to the cerebellum (Dean and Porrill, Putative PMT neurons around nVI exhibit a burst-tonic firing (Nakao et al., PNs appear to play a role in different functions, which include synaptic stabilization during development, control of plasticity, ion homeostasis and neuroprotection (Soleman et al., post mortem cases of ALS. The cytoarchitectural boundaries of the rostral nVI enclose the PMT neurons as another functional cell group that project to the flocculus and may contribute to the cerebellar control of gaze holding (Dean and Porrill, In conclusion, within the nVI of monkey and man, the well-known LR motoneurons and INTs can be easily delineated from each other by their different neurotransmitters. The motoneurons of singly-innervated twitch muscle fibers and multiply-innervated non-twitch muscle fibers subserving different tasks in oculomotor control can be identified by their present or lacking ensheathment by PNs. This allows for a specific analysis of different motoneuron types in AHorn, AHorng and NB contributed conception and design of the study. AHorng, AM, NB and WH created the data. AHorn and WH wrote the first draft of the manuscript. All authors contributed to manuscript revision, read and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.