Compared with previous reports of controlled laboratory speech, the Voicing Effect was found to be substantially smaller in spontaneous speech, but still influenced by the expected range of phonetic factors. Dialects of English differed substantially from each other in the size of the Voicing Effect, whilst individual speakers varied little relative to their particular dialect. This study demonstrates the value of large-scale phonetic research as a means of developing our understanding of the structure of speech variability, and illustrates how large-scale studies, such as those carried out within SPADE, can be applied to other questions in phonetic and sociolinguistic research.Recent advances in access to spoken-language corpora and development of speech processing tools have made possible the performance of “large-scale” phonetic and sociolinguistic research. This study illustrates the usefulness of such a large-scale approach—using data from multiple corpora across a range of English dialects, collected, and analyzed with the SPADE project—to examine how the pre-consonantal Voicing Effect (longer vowels before voiced than voiceless obstruents, in e.g.,  For example, the deletion of word-final /t/ and /d/ segments  has been shown to vary across a wide range of dialects and speech communities  refers to vowels preceding voiced obstruents being consistently longer than their voiceless counterparts, such as the differences in beat-bead and mace-maze  how much does the VE vary across dialects and speakers? In addressing these questions, we hope to gain insight into a number of open issues, including the extent to which there is a single “English” VE or whether dialects differ in the magnitude of the effect, as well as the range of VE sizes across individual speakers of a given dialect.The pre-consonantal voicing effect  project , which aims to consider phonetic and phonological variation in British and North American English across time and space through the use of automated acoustic analysis of features across English dialects occurring in many corpora. The methodological and research goals of the SPADE project are exemplified through this study of the English VE, specifically by the use of multiple corpora of diverse sources and structures, and the use of linguistic and acoustic analysis via the Integrated Speech Corpus ANalysis (ISCAN) tool , where vowels preceding voiced fricatives and morpheme boundaries are lengthened, whilst all other contexts have short vowels Aitken, , and hen Evanini , using ilearned property of a given language, compared with an automatic consequence of low-level phonetic structure? Much of the discussion with respect to variation in VE has revolved around differences across languages  potentially avoids this problem; the specification of phonological categories—here, the voicing status of final obstruents—are expected be largely consistent within a language, meaning that language-internal variability may be driven by only differences in phonetic implementation.Whilst a large number of studies on the VE have provided useful information for its realization in English and other languages, there are still a range of outstanding questions that can be addressed through a large-scale cross-dialectal approach. To what extent is the VE a es Chen, , which mLittle is known about how English dialects may vary in their implementation of the VE, and so a range of possibilities exist for how dialects might compare. One possibility is that, with the exception of varieties with specific phonological rules interacting with the VE, dialects might cluster around a single “English” VE value, potentially of the size reported in the previous literature. Such a finding would support the previous approach in the literature, in terms of English compared to other languages, and suggest that dialects do not differ in how the final voicing contrast is phonetically implemented. Alternatively, dialects may differ gradiently from each other, and so may show a continuum of possible dialect-specific VE sizes. If dialects do differ in their VE size in this way, this would suggest that the previous literature on the VE in “English” accounts for just a fraction of the possible VE realizations across English, and would provide evidence that individual English dialects differ in their phonetic implementation of an otherwise “phonological” contrast Keating, , 1985.Similarly, little is known about how individual speakers vary in the VE, and what the overall distribution of speaker VE sizes is. Synchronic variability across speakers is one of the key inputs to sound change Ohala, , and alsThe Atlas of North American English, which is based around phonetic, not lexical, differences between geographic regions  tool was developed for use in this kind of cross-dialectal study in the context of the SPADE project. This section provides a brief overview of the ISCAN system: see McAuliffe et al.  to datasets which can be statistically analyzed. As the corpora differ in their formats—the phone labels used, organization of speaker data, etc.—modifying the acoustic analysis procedure for each different corpus format would be both labor and time-intensive, as well as increase the risk that the analysis itself differed across corpora. In order to standardize the acoustic analysis across corpora, the e et al. , 2019 animported into a graph database format, where each transcription file is minimally composed of word and phone boundaries , and these word-phone relationships are structurally-defined in the database . Importers have been developed for a range of standard automatic aligners, including all formats of corpora described in section 3. Corpora, represented in database format, can then be further enriched with additional structure, measurements, and linguistic information. For example, utterances can be defined as groups of words , syllables can be defined as a property between groups of adjacent phones. Once the database has been enriched with utterance and syllable information, speech rate (often defined as syllables per second within an utterance) can be calculated and included in the database. Similarly, information about words (such as frequency) or speakers  can be added to the corpus from metadata files. Once a corpus has been sufficiently enriched with linguistic and acoustic information, it is then possible to perform a query on the corpus at a given level of analysis. This level of analysis refers to the level of the hierarchy on which the resulting datafile should use as the main level of observation, for example individual phones, syllables, or utterances. Filters can be applied to a query to restrict it to the particular contexts of interest, for example, including only syllables occurring at the right edge of an utterance, or vowels followed by a specific subset of phone types . Finally, the resulting query can then be exported into a data format (currently CSV only) for further analysis.The process of deriving a dataset from raw corpus files consists of three major steps. In the first step, individual speech corpora (in the form of sets of audio-transcription pairs) are relative to their average speech rate  were created via forced alignment with a minimum duration of 10 ms and a time-step of 30 ms, any token with a vowel duration below 50 ms was excluded from further study, as is common in acoustic studies of vowel formants to exclude heavily reduced vowels , spontaneous speech taken from corpora is rarely balanced in this sense: some speakers speak more than others, have different conversations leading to some combinations of segments occurring infrequently relative to others, speakers manage properties of their speech (such as speech rate) for communicative purposes which are generally absent in laboratory studies. In trying to obtain an accurate estimate of the VE (or indeed any other linguistic property), the unbalanced nature of spontaneous speech motivates the need for a statistical approach where individual factors of interest  can be explored whilst controlling for the influence of other effects. This approach—the use of multiple regression to model corpus data—is now common in phonetics and sociolinguistic research , Bayesian models provide a range of possible sizes for each level . In a Bayesian model, all parameters (coefficients) in the model are assumed to have a prior distribution of possible values, reflecting which effect sizes are believed to be more or less likely, before examining the data itself. The output of a Bayesian model is a set of posterior distributions, which result from combining the priors and the likelihood of observing the data. Each model parameter has its own posterior distribution, which each represent the range of values for that parameter that is consistent with both the modeled data, conditioned on prior expectations about likely values, and the structure of the model itself. Bayesian models are well-suited to the task in this study, as they allow for flexible fitting of model parameters, and allow the complex random-effects structures which are often recommended for fitting statistically-conservative models  and this variability is of direct interest for our research questions. Bayesian mixed models resemble more traditional linear mixed-effects (LME) models approaches commonly used in linguistic and phonetic research, such as those performed with the brms , the lexical class of the word , both mean and local speech rates, and lexical frequency. To observe how compression of the vowel influences VE size, interactions between all of these factors with obstruent voicing were also included. The continuous predictors , were centered and divided by two standard deviations  and the manner of the obstruent would affect the size of the VE, correlation terms between the intercept and both the consonant voicing and manner predictors, as well as for the interaction between the voicing and manner predictors, were included for both dialects and speakers. Random intercepts were included for words and phoneme labels, also nested within dialects. The model was fit using 8,000 samples across 4 Markov chains (2000/2000 warmup/sample split per chain) and was fit with weakly informative “regularizing” priors ]; the other fixed effects parameters used Normal priors, with the exception of the obstruent voicing parameter which used a Normal priorbrms default prior of a half Student's t-distribution with 3 degrees of freedom and a scale parameter of 10. The correlations between group-level effects used the LKJ  structure of the model contained the complete set of model predictors for both dialects and speakers, nested within dialects. These terms capture two kinds of variability in the VE size: for each individual dialect, as well as the degree of variability across speakers—the nesting of speaker term inside dialects can be interpreted as capturing the variability in the size of the VE across speakers size of the effect  and the confidence in the effect's predicted direction. The strength of evidence for an effect is distinct from the strength of the effect itself: to value the strength of evidence for an effect, we follow the recommendations of Nicenboim and Vasishth . Evaluating the strength of an effect is determined with respect to effect sizes previously reported for laboratory  in spontaneous speech, and (2) across English dialects and individual speakers. The results are reported for each effect in terms of the median value with 95% credible intervals (CrIs), and the probability of that effect's direction. These values enable us to understand the Vasishth  and consLooking at how the overall VE size for all dialects is modulated by phonetic context, there is weak evidence that the manner of the following obstruent modulates VE size .Turning to dialectal variability in VE, we observe that the dialect variation in VE  how the VE is realized in spontaneous speech, and (2) how the VE varies across dialects and speakers. The VE in English is often considered to be substantially larger than in other languages Chen,  and claiIn this study, the overall VE in spontaneous speech was observed to have a maximum size of around 1.2—substantially smaller than the 1.5 commonly reported in laboratory studies  considered how the VE was modulated in spontaneous speech, averaging across dialects. To what extent dialects themselves differ in VE was the focus of the second research question. As shown in section 6.2, English was shown to exhibit a range of different VE sizes across individual dialects. The dialects with the smallest and largest VEs—Scottish Englishes and AAE, respectively—were expected to show these values given evidence of additional phonological rules governing vowel duration in these varieties Aitken, . Beyond Individual speakers are also shown to vary in the realization of the VE, though the extent of this variability is rather limited when compared to variability across dialects : that isBy using speech data from multiple sources and multiple dialects, it has been possible to investigate variability of a phonological feature across “English” overall, examine variability at the level of individual dialects and speakers, and reveal the extent of English-wide phonetic variability that was not previously apparent in studies of individual dialects and communities. In this sense, our “large-scale” approach, using consistent measures and controlling factors, enables us to understand the nature of dialectal variability in the English VE directly within the context of both other dialects and English as a whole.too much data to manually check and correct all durations, and so the best means of limiting these effects is through sensible filtering and modeling of the data. For example, segments with aligned durations of less than 50 ms were excluded, since accurately capturing the duration of a vowel this small could be difficult given the time resolution of the aligner. This decision could exaggerate the size of the VE estimation, as only the most reduced vowels have been removed from the data. Another property of forced alignment which impacts our study of VE is that aligners will only apply the phonological segment label to the segment, meaning that it is possible to only examine VE in terms of phonological voicing specification , as opposed to whether the segment itself was realized with phonetic voicing. For example, the realization of the stop as devoiced phonetic research, there are of course a number of limitations that should be kept in mind in studies of this kind. This study of the English VE predominantly uses data from automatic acoustic measurements, in turn calculated from forced aligned-segmented datasets. All forced-alignment tools have a minimum time resolution (often 10 ms), a minimum segment duration (often 30 ms), and there always exists the possibility of poor or inaccurate alignment. This is a necessary consequence of the volume of data used in this study: there is simply The recent increase in availability of spoken-language corpora, and development of speech and data processing tools have now made it easier to perform phonetic research at a “large-scale”—incorporating data from multiple different corpora, dialects, and speakers. This study applies this large-scale approach to investigate how the English Voicing Effect (VE) is realized in spontaneous speech, and the extent of its variability across individual dialects and speakers. Little has been known about how the VE varies across dialects bar a handful of studies of specific dialects Aitken, . EnglishThe datasets generated for this study are available on request to the corresponding author.JT extracted the data, performed the statistical analysis, and wrote the first draft of the manuscript. All authors contributed to the conception and design of the study. All authors contributed to manuscript revision, and 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.


Regardless of growing interest and awareness of the effect of energy poverty on mental health, studies on this linkage have mainly relied on unidimensional measures of energy poverty with much concentration on advanced economies. Employing a two-wave socioeconomic survey, we analyzed the impact of multidimensional energy poverty on mental health in Ghana. We found energy poverty to heighten the chances of being mentally unhealthy. Using prices of liquefied petroleum gas and electricity as instruments for multidimensional energy poverty, we found that a rise in energy deprivation is associated with a 0.562-, 1.494- and 1.867-fold increase in the odds of being mildly, moderately and severely depressed, respectively. Among the indicators of multidimensional energy poverty, a deprivation in household appliance ownership (refrigerator ownership), recorded the highest impact on the depression levels of household heads. We concluded by urging policymakers to adopt a holistic approach in solving issues of energy poverty where simultaneous attention is given to all the dimensions of energy poverty since they collectively have detrimental effects on mental health, especially in a developing country setting. The United Nations Sustainable Development Goal (SDG) seven (SDG 7) stresses “access to affordable, reliable, sustainable, and modern energy for all” . GloballNonetheless, there exists an inadequate understanding of the concept of energy poverty, particularly among decision-makers and politicians in SSA. Following Phoumin and Kimura , this stMost recent scholarly that view energy poverty from a multidimensional perspective, also look at its effect on numerous development indicators such as health, poverty, education and the environment. Among these indicators, the relevant and forthright impact of energy poverty on health has fueled several recent studies—particularly in developing economies ,11. DespEnergy deprivation in itself, is also is evidenced as an primary source of cumulative stress or anxiety . This isExamining the impact of multidimensional energy poverty on the mental health of individuals in developing country settings is invaluable to influencing policies. Studies that have examined this relationship have all relied heavily on unidimensional measures of energy poverty and have mostly focused on industrialized economies ,19,20,21The problems mentioned above lead to an essential question: To what extent does energy poverty matter? This study, attempts to answer this research question by examining the effect of multidimensional energy poverty on mental health in a developing country. We explicitly expand the existing studies by adopting Nussbaumer et al.’s  frameworUnlike previous studies ,19,20,21Compared to the rest of the continent, Ghana has one of the highest rates of access to electricity, but is unlikely to achieve its target of attaining universal modern energy access in 2020 . The cosThe remainder of the study is arranged as follows: a review of the literature is presented in Originally, the concept of energy poverty, as proposed by Lewis , was to The 10% cutoff as an income-based measure of energy poverty was introduced by Boardman . A houseAs an improvement to the 10% threshold approach, the low income high cost (LIHC) measure was suggested by Hills . This meThe indicators mentioned above of energy poverty are mostly suitable in advanced economies where issues of energy deprivation are primarily centered on affordability. The situation in developing countries is more complicated as matters of energy poverty hover around affordability and accessibility . This haSimilarly, Sher et al.  and OgwuThe broad range of developmental indicators affected by energy poverty has motivated existing research to measure energy poverty accurately. A summary of recent studies on the impact of energy poverty on health, environment, and the economy at large by Gonzalez-Eguino  concludeYet, despite this growing interest in mental health and energy poverty, relatively little is known about how energy deprivation influences mental wellbeing  in develGenerally, it can be observed that recent studies ,19,20,21Data from a two-wave socioeconomic panel household survey on Ghana by the Economic Growth Center (EGC), based at Yale University and Institute of Statistical, Social and Economic Research (ISSER) at the University of Ghana  was emplFor a score less than 20, the respondent is ranked to have low levels of depression;Between 20 and 24, the respondent is described to suffer from mild levels of depression;Between 25 and 29, the respondent is defined to be moderately depressed;For scores above 30, the respondent is described to be severely depressed.We used the Kessler psychological distress scale (K-10) to determine the mental health status of household heads . This meCapturing multiple dimensions of energy deprivation at the household level forms a significant contribution to this paper. To achieve this, we adopted Nussbaumer et al.  frameworMathematically, the dimensions of deprivation The summation of this weight is defined as e k=0.33 .In estimating a national household energy poverty index using the MEPI framework, the headcount ratio or incidence The study controlled for other attributes of the household that affects mental health theoretically and intuitively. These included the household head’s level of education, age, sex, body mass index (BMI), his/her health insurance status, monthly household expenditure, whether the household head smokes or not, place of residence and the region within which the household finds itself. A summary statistic of the variables employed for this study is presented in The following equation is estimated in this study:Due to the categorical nature of our dependent variable (Kessler-10 depression measure), we used the logistic regression technique in estimating equation 1. This technique is argued to have more accurate predictions of the outcome variable than the ordinary least square (OLS) technique, especially when the dependent variable is categorical . To be mA likely potential source of endogeneity for energy deprivation is the omission of a variable. This could render the coefficient of energy deprivation either to be biased upwards or downward. We solve this using an instrumental variable MLR-FE, where electricity and liquefied petroleum gas (LPG) prices are used as instruments for energy poverty. The rationale behind this approach is that a rise in prices of LPG and electricity is related to the increase in energy deprivation, which turns to increase one’s chances of being mentally depressed. Findings from Narayan and Smyth,  and Fan The propensity score matching (PSM) approach is also applied as an additional technique in addressing the endogeneity issue. This approach is often used in addressing problems of endogeneity in non-experimental surveys. It determines the average treatment effect (energy-deprived households in the case of this study) on our dependent variable (depression) ,58.The heights of deprivation on the chosen dimensions grounded on the threshold of multidimensional energy poverty during the study period are discussed in this section. The findings presented in Access to electricity also witnessed improvements within the five-year period. Precisely, the proportion of households who were not connected to the grid decreased by 16%. Investments made in thermal and hydropower plants to augment the existing production is attributable to this decline . FurtherA further analysis of the MEPI by regions is presented in Compared to the reference group , it can be observed from To be able to establish causality between energy poverty and depression, we presented a two-stage instrumental variable MLR-FE of the effect of MEPI on depression to deal with the endogeneity issue in Confirming our prior expectations, we find prices of electricity and LPG to be positively related to energy poverty from the first-stage model. Thus, a rise in the price of electricity and LPG increases energy deprivation. Consistent with the results in Considering the impact of the respective indicators of energy poverty on depression, our results revealed that household heads who did not own a refrigerator were more susceptible to depression, followed by those who lacked access to electricity, mobile phone ownership, modern cooking fuel and indoor air pollution. The depression levels of household heads who did not own a refrigerator were about 1.218 higher than their counterparts who had one, at a 1% significance level. Individuals who are deprived of refrigerators are noted to experience frequent food spoilage, which, in turn, increase their depression levels . In anotAt a 1% significance level, the depression levels of respondents who were deprived of electricity were about 1.803 greater than their counterparts who had access. The lack of electricity access limits the activities people can enjoy. Recreational and relaxation activities such as watching TV or playing video games while enjoying the cool breeze from an air-conditioner or standing fan is cut off. This is noted to stimulate the anxiety levels of people . InsteadTo the best of our knowledge, this is the first study of its kind in a sub-Saharan African nation like Ghana, that empirically investigates the effect of multidimensional energy poverty on mental health. The findings suggest a decline in energy deprivation for the understudied period. MEPI reduced from 0.497 in 2010 to 0.338 in 2015. This implies that MEPI reduced by 16% between 2010 and 2015 and that about 34% of households in Ghana were multidimensionally energy-poor in 2015. Furthermore, a large proportion of households were found to continuously use biomass for cooking and heating than the other indicators of MEPI. This is indicative that addressing problems concerning traditional sources and the use of fuel can substantially reduce energy poverty in Ghana. In addition, the decomposition of the MEPI by regions showed that households in Northern Ghana experienced a high prevalence of energy poverty. Consistent with previous studies ,19,20,21To reduce energy poverty and improve mental health, policymakers must consider a holistic approach in solving energy poverty where simultaneous attention is given to all of the dimensions of the MEPI;Although interventions such as the LPG program that sought to supply households with cookstoves and LPG cylinders have been implemented, the ability of beneficiaries to financially and sustainably use LPG cylinders and stoves continues to be a significant constraint ,67. TherGranting that the MEPI has reduced across all the ten regions of Ghana in the understudied period, there is still a high prevalence of it in the three Northern regions. A great deal of political weightiness is brought to the floor by this particular finding, as it tends to serve as a guide to politicians in targeting regions with of higher incidence of energy poverty;As energy poverty has been observed to deteriorate the mental health of respondents in this study. Policies makers must consider the role of access to clean, affordable and reliable energy play in mental health policies;Aside from concentrating on electricity access and modern fuel usage as means in reducing energy poverty, attention should be given to the end usage of energy (refrigerator and mobile phone ownership) as they play a vital role in the mental health status of people. We advocate for subsidies on these energy services for vulnerable groups.Indicators such as the number of people living in the same household and its surface (in square-meter) have direct effects both on energy poverty and mental wellbeing, but due to data unavailability, they were not included in the analysis. Thus, future studies could look at this dimension.


There is substantial confusion about and overlap between health and social care services labeled as “subacute,” “intermediate care” and those labeled as “reablement.” In this article, we have used “convalescent.”3 The convalescent care facilities model is defined as a transitional form of care provided after a hospital stay but before going home. Convalescent care provides a home-like environment during post-surgery recovery, injury recovery, and can even be used as a transitional form of care following stroke or a lengthy illness. Previously, such services were mainly used for diseases, such as strokes, as well as accidents that the patient required convalescent services, and their effectiveness have been proven.4 The rapid outbreak of coronavirus disease (COVID-19) in Iran paved the way for the establishment of convalescent centers because one of the issues related to the break of the coronavirus transmission chain is that patients should not return home immediately after recovery and discharge from the hospital and instead they need intermediate places to recover completely from COVID 19 and reduce any chance of transmitting the disease. The health care system in Iran consists of 4 levels: the first level, which includes health houses and health posts; the second level, which consists of comprehensive health centers and clinics; the third level, which includes public hospitals; and the fourth level, which consists of specialty and subspecialty hospitals.5 In epidemics, another level of services is designed and operated, the convalescent centers, which is placed between the second and third levels of the service delivery system. Convalescent centers are an integral part of the service delivery system in Iran, which do not require advanced hospital facilities, and their responsibility is to admit suspected patients infected with disease from an epidemic or to admit patients who do not need specialized hospital services.Policy-makers, health care providers, and the public are interested in getting services in the right place because providing services in the wrong place will have negative consequences for access, cost, and quality. The use of alternative care levels is one of the indicators of performance management and accountability to patients who do not require acute and long-term careDue to the increasing number of patients with COVID-19 in Iran who are discharged from the hospitals to continue their additional and supplementary treatment and care at home but do not have adequate isolation space or a way to take care of themselves, establishing a temporary place such as convalescent centers for these patients and providing necessary services and training for them is an appropriate strategy. In Iran, convalescent centers were set up by military organizations, municipalities, non-governmental organizations, and the public themselves, and almost no government facilities were used to establish them. However, addressing the technical issues related to setting up, equipping, and monitoring the centers was the responsibility of medical universities. The physical space in these centers for hospital beds per bed is at least 5 meters. The health care team for every 50 beds includes 1 nurse, 2 practical nurses, 1 service personnel, and 1 guard; and the required equipment includes an emergency trolley and Cardiopulmonary and Cerebral Resuscitation equipment. At least 14 days after the onset of early symptoms, patients should be isolated in the convalescent centers.In one of the military health care organizations, a 1000-bed convalescent center was established within 48 hours in the organization’s multi-story car park. Nurses and nursing students worked in shifts and in on-call form to organize the health care teams of this convalescent center. The Islamic Republic of Iran Army established a 2000-bed convalescent center in less than 24 hours at the Tehran International Exhibition Center. Moreover, the Iran Mall, one of the biggest shopping malls in the world, established a convalescent center with 3000 beds in 5 working days, so that in the first stage, 50 intensive care unit beds and 150 beds equipped with oxygen therapy equipment were used. This center was equipped with the latest and most up-to-date medical facilities and became a care center for COVID-19 patients. The establishment of these convalescent centers has gradually expanded to other cities in Iran.3 The convalescent center is a good opportunity for the cooperation of volunteer forces in the epidemic. The executive plan for the use of volunteers in the convalescent centers can compensate for the care workers, and the expert forces and staff in the hospitals can focus on providing services to the more acute patients. The health care system and the National Corona Committee should use tools to identify capacity to increase the standard convalescent beds and to securely transfer patient information. The use of Skype and other applications for secure virtual calls should be increased to ensure that the physician’s or health care advice is followed. Convalescent care audits, including scrutinizing the daily infection controls, nursing services, and the transparent reporting process of personal care plans for patients in the convalescent center, mental health measures, and finally additional activities such as providing balanced and delicious meals and physiotherapy services are all key indicators in the operation of a convalescent center during the COVID-19 epidemic.Convalescent service providers should comply with professional standards for providing services to the patients. Due to the high risk of being infected with COVID-19 in the convalescent centers, it is recommended to observe the minimum social distance (6 feet) requirement in the arrangement of beds. The separation of clean and infected spaces and design of safe traffic routes are essential. Removing face-to-face contact with family members and prohibiting group activities increase the recovery time for socially isolated patients. One of the topics that should be considered in convalescence is appropriate leveling and space creation, which includes the spaces for COVID-19-suspected patients, the spaces for patients in good condition, and the spaces for people who have had physical contact with the patients. These spaces have not been considered in some convalescent centers, which are not based on epidemiological models of the needs assessment. The double stress of fear of re-infection leads to behavioral problems. Delirium caused by hypoxia, one of the important clinical features of COVID-19, can complicate the dementia. Therefore, in the convalescent centers, a protocol on how to provide mental health services should be developed.


Spinocerebellar ataxia is a hereditary neurodegenerative disease characterized by changes in balance, locomotion and motor coordination. Stem cell therapies are currently being investigated as an alternative to delay the evolution of the disease, and some experimental studies have investigated the effect of stem cell treatment on spinocerebellar ataxia.The aim of this review was to investigate whether the application of stem cells produced an effect on functional recovery in individuals with spinocerebellar ataxia.The studies included in this review investigated the efficacy and safety of a protocol for the application of mesenchymal stem cells extracted from umbilical cord and adipose tissue. Two studies used intrathecal route for application and one study used intravenous route.Studies have shown clinical improvement in the scores of the ICARS , ADL , BBS  and SARA , but lacked statistical significance.There was low evidence for recommending stem cell therapy in individuals with spinocerebellar ataxia, and no statistical difference was observed for improving functional recovery of patients. Further studies are needed with different designs, largest sample sizes and placebo control, to fully understand anticipated outcomes of cellular therapy for spinocerebellar ataxia. The term ataxia is used to describe a neurodegenerative disease with heterogeneous genotypic and phenotypic characteristics . SpinoceThere is a wide variety of clinical manifestations in SCA, such as chances in muscle tone, inadequate motor coordination, poor postural control, including changes in locomotion, dysarthria, progressive ophthalmoplegia, extrapyramidal signs including dystonia, stiffness and/or bradykinesia, and changes in the lower motor neuron, with fasciculations, amyotrophy, decreased sensitivity, eyelid retraction, weight loss, sleep disorders and fatigue , 6. ThusMany treatments have been considered to reduce the impact of the SCA on functionality, as well as to delay the degeneration of the cerebellum. Among the therapeutic options, multipotent mesenchymal stem cells have been considered in this population due to their immunomodulatory and regenerative properties . These cStem cell-based therapies represent a new therapeutic strategy for SCA , 11. In In addition, neurotransplants have been performed in several models with mutant mice using different cell types and techniques to stop or delay the degeneration of Purkinje cells and restore normal cerebellar architecture . These pCochrane Handbook for Intervention Reviews ..22].We planned to assess publication bias through the visual inspection of funnel plots for each outcome for which we identified 10 or more eligible studies; however, we were not able to do so because there were an insufficient number of studies to conduct this assessment.2statistic and the p-value for the chi square test of heterogeneity provided by Review Manager. In addition, Review Manager (RevMan)  was used for all analyses. Due to the small number of studies that were identified, sensitivity tests  were not performed and subgroups were not applied.All outcomes as continuous variables were analyzed. The results were presented as mean of differences (MD) along with 95% confidence intervals, using fixed-effects models. The unit of analysis was each participant recruited for review. The variability in results across studies was checked by using the IWe identified a total of 143 studies . After screening the titles and then the abstracts, we obtained full-text articles for the 27 studies that were potentially eligible for inclusion in the review. We excluded 24 studies because they were considered observational studies. This left 3 clinical trials –21 for aThe main characteristics of the three selected studies are showed in the Table The interventions, results and GRADE for each selected study are showed in the Table For the random sequence generation, all studies demonstrated high risk of bias: Dongmei et al. 2011)  is a non11  is a The risk of bias of the included studies is shown in Table p = 0.08) between the stem cell groups in the baseline and follow-up in both studies.The meta-analysis was performed with two studies due to the variability of the outcomes. The included studies in the meta-analysis were: Dongmei et al. 2011) , who inj11 , who Based on the results of the meta-analysis we observed that there are no statistically significant differences in the ICARS scale score before and after the application of stem cells in SCA considering the two included studies. The ICARS was developed by Trouillas et al. (2011)  and compBecause they are not randomized clinical trials, there is no concealment of allocation or blinding of participants or evaluators and even if there is a report on outcome evaluators, justification of loss and exclusion of participants and availability of protocols, following the criteria of the GRADE system, there is a low evidence recommendation for the use of stem cell protocol in spinocerebellar ataxia. In the studies included in this review, there were heterogeneous study designs and small sample size, which can be explained by the fact that it is a rare disease, leading to a low number of participants, thus influencing the results of the meta-analysis. If there are studies with different designs than the studies included in this review, such as randomization, blinding, among others; the recommendation for evidence will be higher.Through this systematic review, we can observe the clinical efficacy and safety of treatments involving individuals with spinocerebellar ataxia who have undergone stem cell treatments, as well as other types of ataxia, such as multiple systems atrophy-cerebellar type. In all studies, research participants had no major side effects.Among the various sources for stem cell extraction, two studies used cells from umbilical cord , 20 and Interestingly, when we evaluated the studies separately, we can see that there were improvements in the motor parameters of individuals with spinocerebellar ataxia undergoing stem cell therapy, but when evaluated in the meta-analysis, the result was influenced by the small sample size and the high variability of the outcomes. Furthermore, knowing the age variability presented in the included studies and the difference in the cell sources used for each procedure, some questions remain unanswered for future work. What is the difference in the effectiveness of stem cell treatment in individuals with spinocerebellar ataxia at different ages? Are the results similar in younger and older people? Stem cells extracted from which source have the best effects? Does variability in isolation of cells affect outcomes? Which cells are more efficient, autologous or allogeneic?Strengths of our review include a comprehensive search; assessment of eligibility, risk of bias, and data abstraction independently and in duplicate; assessment of risk of bias that included a sensitivity analysis addressing loss to follow-up; and use of the GRADE approach for rating the certainty of evidence for each outcome. Furthermore, there were no language restrictions, and translations of non-English trials were obtained whenever possible. The primary limitation of our review is the low certainty consequent to study limitations. We identified a small number of RCTs with a modest number of participants resulting in wide confidence intervals. The total number of participants was relatively very low due to the small sample sizes of individual trials, which led to downgrading the quality of evidence in some instances because underpowered trials are likely to have a greater degree of imprecision. Moreover, selection bias and unblinding were substantial. Another limitation of this review was having an insufficient number of included studies to allow for the complete statistical analysis that we had planned. We were not able to assess publication bias because there were fewer than 10 eligible studies addressing the same outcome in a meta-analysis.Low-quality evidence shows that steam cell therapy is more efficacious for functional recovery after SCA measured by ICARS. Future trials should adhere to CONSORT guidelines to ensure clarity and reproducibility in the reporting of methods. There are no specific systematic reviews on stem cell treatments for patients with spinocerebellar ataxia, demonstrating the importance of this review, in order to achieve a greater understanding by researchers, health professionals and patients on the subject. This review can assist future research, as it brings together important data regarding the target audience, type of cells used, form of application, evaluation criteria, among others. There is a need for more research related to this therapy with careful designs, such as randomized, blind or double-blind clinical trials with a larger sample size and less risk of bias.There was low evidence for recommending stem cell therapy in individuals with spinocerebellar ataxia, and no statistical difference was observed for improving functional recovery of patients. In addition, it should be taken into account that the studies included in this review present risks of bias and methodological flaws, and therefore, it is recommended to develop clinical trials of larger sample size and lower risk of bias so that future conclusions can be based on more robust searches.


The announcement of the COVID-19 pandemic by the World Health Organisation in March 2020 and the spread of coronavirus in most parts of the world, including Iraq, have posed severe challenges to the management of cancer patients both psychologically and logistically. Special experts at Hiwa Cancer Hospital, Iraq, took serious action aimed to decrease and prevent the spread of the virus among cancer patients while maintaining standard treatment protocols through compiling expert consensus, focusing on the prevention of COVID-19 and cancer patient management. Following the worldwide spread of COVID-19, especially in neighbouring countries, experts at Hiwa Cancer Hospital in Iraq made some strategic decisions to decrease and prevent COVID-19 spread in cancer patients since this population group is prone to viral and bacterial infection more than the normal population due to immunocompromised status following active treatment and frequent visits to the hospital.Hiwa Cancer Hospital is located in Sulaymaniyah city in the northeast of Iraq and southeast of Kurdistan. The city houses a population of 800,000 people as of 2016. Hiwa Cancer Hospital was built by the government sector and supported by both government and charitable donations. It is the only cancer hospital in Sulaymaniyah city. The hospital has 170 inpatient and 50 outpatient beds and yearly receives around 1,600–2,000 new adult haematology and oncology cases. About 100% of all patients are accepted for cancer management completely free of charge, irrespective of race or nationality.At the beginning of the crisis, in late March 2020, there was a curfew all over the country. It was difficult for the patients to reach hospitals and seek medical care. The admission of new cancer patients was suspended along with prolonging neoadjuvant chemotherapy, stopping seeing follow-up cases and doing screening programs with delaying elective surgeries—this continued until late May. As time went by, we understood more that this problem is not a short duration crisis, and it is not logical to deprive patients from life-saving treatment. It was expected that there will be a gush of new cancer cases after the curfew is over, unfortunately, that is exactly what happened from late May when the government started to loosen the curfew and lockdown measures. As we all know, delaying diagnoses and treatment of new cancer cases will lead to their presentation at a more advanced stage which then leads to the reduced benefit of treatment and poor survival.In order to continue cancer management according to the available facilities and based on the evidence available in the literature and guidelines –4, we fo(1) Decrease transmission of COVID-19The best way to continue standard medical and surgical care is through decreasing transmission of the virus and increasing protection through:Screening for COVID-19; anyone entering the hospital campus, whether they are a staff member, patient, patient’s companion or patient admitted in the ward, has to undergo initial screening by well-educated staff to triage suspicious cases.The first part of screening includes searching for symptoms associated with COVID-19 infection including fever, breathlessness and cough. The second part includes doing a SARS-cov2 PCR test for all those with:Personal respiratory symptomsOne or more family member with respiratory symptoms in the past 14 daysHistory of residence or travel to a community with a high rate of COVID-19-positive cases in the past 14 daysHistory of exposure to a COVID-19-positive case in the past 14 daysIn case of the positive result, the case will be isolated immediately and reported to a superior department in the hospital, and later on, the person will be referred to any COVID-19 dedicated hospital for further assessment and management.Personal protection: any person entering the hospital campus from the patient to their companion or hospital staff should be dealt with as an infected person to minimize the spread of the virus. Any person inside the hospital should wear surgical mask, gloves and surgical gown, keeping to required physical distancing and frequent hand washing. Special attention must be paid to high-risk patients .Sanitise the hospital more frequently than routine hospital guidelines, and environmental ventilation, frequent disinfection of equipment and management of medical waste are measures believed to decrease nosocomial infection .Inpatient management: family visitors are strictly restricted, only one companion is allowed to stay with the patient and the patient and the companion must undergo daily screening. Meal delivery from outside the hospital is severely restricted, and the meals are prepared by specialized staff within the hospital and delivered by a nurse. When a patient is discharged, the room is sanitized and disinfected before admission of another patientHospital staff training: arranging awareness training programs for all hospital staff to educate them on COVID-19 and its symptoms with preventive measures every other day with training on the appropriate use of PPE (b) Telephone call: to detect the positive cases of COVID-19 in the early stage, and the hospital set up a hot telephone line to:Register any cancer patient with COVID-19 symptoms, and in case of any suspicion of COVID-19, they will be contacted in order to get a sample from them. For positive RT-PCR test, all cancer treatments  must be stopped temporarily, and the case has to be referred to specialized COVID-19 centres immediately. Although there is no accepted guideline for safe initiation or re-initiation of cancer treatment after COVID-19 infection, we started to re-challenge with anticancer therapy when the symptoms of COVID-19 have resolved for at least 48 hours, and the patient is at least 14 days from the onset of COVID-19 symptoms (or 14 days since specimen collection date if asymptomatic), or two negative PCR tests for COVID-19 collected at ≥24-hour interval  looks to be a better option rather than postponing treatment, which may harm the patient and be of higher economic burden on the hospital and government , 7. We rA special clinic was organized for phone consultation and psychological support. From this clinic, all patients were called and informed about this facility with an overwhelmingly positive response, providing all psychological support and answering any question or queries the patients have, and for them to feel safe while they are home, instructions were given about not coming to the hospital except in certain situations and specific indications to avoid unnecessary trips to the hospital, while palliative care and management of acute severe complications of cancer and relief of severe distress were maintained, providing adequate supply for pain management drugs at home .The strategies and measures that we are following are local and are not unique and have many deficiencies. There are no courier services in the country, and the patients have to buy any necessary medication from outside the hospital; this was one of the main problems that we faced since, most of the times, the patient could not buy the necessary medications and had to visit the hospital due to economic issues. The country is an oil-dependent country, and an economic crisis was another negative impact of COVID-19. There were difficulties in retaining hospital employees and many lost their jobs, and the resultant limited number of healthcare staff disabled the facility of the administration of chemotherapeutic drugs at home and home care for patients who had advanced and end-stage disease.During the COVID-19 pandemic, we have to be flexible, patient and cautious, to share the experiences from different cancer centres around the world, to endorse best interim anticancer treatment regimens and be able to provide the best care for the patients until we reach a state that emergency measures put in place to address the COVID-19 pandemic are no longer necessary. It is highly recommended to have a virtual multidisciplinary team in place for decision-making, and each patient must be considered on an individual basis. In case of the modification of systemic anticancer treatment, using fewer immunosuppressive protocols, shifting from the intravenous route to oral or subcutaneous route to reduce visits and decreasing the frequency of immunotherapy protocols, it may be reasonable to postpone regular follow-up visits of patients not on active cancer treatment or to conduct those appointments via telemedicine.The authors declare that no competing financial interests exist.This research was supported by Hiwa Cancer Hospital, Ministry of Health/Kurdistan Regional Government, Iraq.


The field of biosensing is rapidly developing, and the number of novel sensor architectures and different sensing elements is growing fast. One of the most important features of all biosensors is their very high selectivity stemming from the use of bioreceptor recognition elements. The typical calibration of a biosensor requires simple univariate regression to relate a response value with an analyte concentration. Nevertheless, dealing with complex real-world sample matrices may sometimes lead to undesired interference effects from various components. This is where chemometric tools can do a good job in extracting relevant information, improving selectivity, circumventing a non-linearity in a response. This brief review aims to discuss the motivation for the application of chemometric tools in biosensing and provide some examples of such applications from the recent literature. Biosensors combine bioreceptor recognition with various physicochemical transduction principles, such as amperometry, voltammetry, potentiometry, different optical techniques, etc. . Figure The most important feature of biosensors in comparison to chemical sensors is the possibility to achieve extreme selectivity with the appropriate bioreceptor for the analyte of interest. The wide variety of bioreceptors  and techniques for their immobilization allows the creation of highly sensitive biosensors for a broad range of analytes.One of the first and probably the most widely used example of an enzyme biosensor is a device for glucose detection . Such deThe creation of the first enzyme-based glucose biosensor by Clark and Lyons in 1962 initiated the development of the entire field of biosensors. Since then, enzymes remain the most popular bioreceptor type for the detection of glucose and other analytes.Due to the high selectivity of biorecognition elements, the calibration of a biosensor typically does not require using some sophisticated mathematical tools, and ordinary univariate regression can be employed to relate the response of the sensor with the analyte concentration. At the same time, when trying to resolve complex mixtures of several structurally similar analytes in real matrices, various interferences may occur, leading to the increase in analytical errors. The first possible option to circumvent this is to design more advanced and selective recognition elements and sensing platforms; however, this way typically requires significant investments of time and effort. Another option is to use more sophisticated data processing techniques that would still allow the construction of reliable calibration models, even with non-ideally selective sensor responses. As “math is cheaper than physics,” this option appears to be more attractive, and it builds a solid motivation for the application of advanced multivariate mathematical modeling tools in biosensing. This latter research field  represents a rapidly developing part of modern chemical science. The application of chemometric tools in biosensing can provide several benefits: (1) the use of experimental design methodology can significantly reduce the cost of sensor composition optimization; (2) the application of multivariate data visualization tools, such as principal component analysis (PCA), can provide useful insights into the experimental data; (3) multivariate regression methods, including partial least squares regression (PLS) and artificial neural networks (ANN), allow for the effective handling of non-ideal analytical signals impacted by non-linearities, interferences, measurement noise.Moreover, the use of chemometrics gave birth to the so-called “bioelectronic tongues”—arrays of biosensors  where seThe purpose of this review is to give the basic ideas about the benefits that one may get using chemometrics in biosensor research and to promote a wider application of chemometric tools in biosensing. In no way, the authors aim to embrace the whole body of literature available on the topic, but they try to provide some convincing examples instead. The paper is organized as follows: first, we will introduce several typical chemometric tools explaining their prerequisites and outcomes using examples from literature; then we will review the common examples from different fields like environmental monitoring, food, and beverage analysis, biomedical applications; finally, the view of the authors on the perspectives and future trends in chemometric processing of biosensor data will be provided.univariate calibration approaches where biosensor response in each sample is characterized by a single number , chemometrics is dealing with multivariate data. In this case, the response of biosensor  is given by the set of numbers . In the latter case, each measured sample can be represented as a point in a multidimensional space with dimensionality defined by the number of values in the registered response. The basic method of chemometrics is principal component analysis (PCA), which is primarily aimed at the convenient visualization of multivariate data and finding specific patterns therein [Let us now briefly introduce several of the most popular chemometric tools employed in biosensing. At first, it is crucial to understand the data structure required for chemometric processing. Unlike with conventional  therein . PCA is  therein , where by = b0 + bx the method seeks the coefficients b for the equation y = b0 + b1x1 + b2x2 + … + ixib that will convert the response values  into the analyte concentration y. Once these coefficients are found —one can employ them for calculating y values in new samples. It must be noted that PLS, in general, allows for relating the sensor signal with any meaningful parameter y characterizing the sample (not necessarily a concentration), like, e.g., its toxicity, or intensity of particular taste descriptor in terms of the human sensory panel. There are different mathematical ways of calculating b coefficients, and the PLS algorithm finds them in the projection space similar to that of PCA with the only difference that PLS components are drawn in the direction of maximal variance in response space, which is correlated with the variance in calibration values of y. This is a very powerful feature of PLS, allowing extracting useful chemical information from noisy, overlapped, or otherwise distorted analytical signals. The results of PLS modeling are often presented as a “measured vs. predicted” plot indicating reference values of the modeled parameter on the x-axis and the values predicted from the model on the y-axis. An ideal case of complete correspondence between the two, this will be a straight line originating from the center of the coordinate system and having the slope of 45°. The RMSEP—root-mean-square error of prediction—is normally applied to judge the predictive performance of the model:i,ref,y and i,predy are y values for the ith sample obtained from the reference method and the model correspondingly, and n is the number of samples. The RMSEP has the units of the modeled parameter and should always be reported together with the range of the modeled parameter to assess practical applicability.In this way, PCA can be applied to study the ability of individual sensors and multisensor arrays in distinguishing between different types of complex samples. While PCA is purely a visualization tool and suits solely for the exploratory data analysis, many chemometric tools allow numerical predictions of sample quality parameters. The most popular one is probably partial least squares regression (PLS) . This is7 by less than 5.6% in all types of samples.A typical example of PLS application in biosensing can be found in the study by Raud and Kikas , where bAnother powerful and popular data processing tool in chemometrics is the methodology of artificial neural networks (ANNs), the group of methods capable of handling both classification and numerical prediction tasks . The basx1, x2, …, nx). The number of input neurons corresponds to the dimensionality of the initial dataset, e.g., if the initial spectrum was recorded as the absorbance at 100 different wavelengths, then the number of input neurons will be set to 100. The second layer of a neural network is called the hidden layer, where the elements a1, a2…ma are related to the input layer neurons via certain mathematical functions, F, which are called activation functions. These activation functions can be both linear and nonlinear, e.g., exponential, sigmoidal, sinusoidal, etc., and that makes ANN a highly adaptable approach. All the hidden layer neurons are connected to the output layer, where the number of neurons is equal to the number of modeled parameters Y in the initial dataset. So, if the ANN is created to predict the octane number in the petrol sample based on its near infra-red (NIR) spectrum, the output layer will have only one neuron with the predicted octane numbers. The goal of neural network training is to find an optimal number of hidden layer neurons m and the optimal activation functions F and G between layers to minimize the error of prediction for the parameter of interest.The input layer neurons obtain as input the initial analytical data: spectral intensities, parameters of chromatographical peaks, responses of single chemical sensors —one of the first methods historically developed for the classification of multivariate data. It is widely employed for the construction of classification models to distinguish samples from different classes based on biosensor response. The algorithm is based on the search of hyperplane in the variable space, which will separate the classes. In case of only two variables, this hyperplane is a straight line. In case of three variables, this will be an ordinary three-dimensional plane. LDA is a probabilistic method estimating probability density functions in a multivariate way. These functions are similar to the well-known normal distribution and they can be described by the similar multivariate analogues of means and variances. Thus, LDA is based on the assumption about the normality of sample distribution in the classes and the assumption about similar variance in the classes. When the samples under analysis are plotted in the variable space, one can calculate the decision boundary based on the equiprobabilistic hyperellipsoids defined from Mahalanobis distances (Euclidean distances corrected for intercorrelation between the variables) of the samples from the class centroids—this will be given by the points of intersection of such ellipsoids belonging to the different classes. The sample in question will belong to the particular class depending on its location regarding the decision boundary.It must be pointed out that many other chemometric tools can be applied for the processing of biosensing data; however, the three methods described above are the most common ones, and, in this review, we will limit the detailed discussion to PCA, PLS, and ANN only. The readers interested in a more comprehensive overview of the available chemometric tools and methods are referred to the specialized books . This seIt is also important to mention that most of the popular chemometric algorithms are absolutely universal tools for processing any type of multivariate data, regardless of their nature. Thus, different algorithms can be applied to the same problem and various types of biosensor responses can be treated with the same algorithm.There are numerous examples of biosensors and sensor arrays proposed for environmental monitoring. In 2007, the array of enzymatic amperometric biosensors based on three types of acetylcholinesterase was introduced to measure the concentrations of dichlorvos and carbofuran in water. The chronoamperometric response of three AChE biosensors was measured in 22 samples of two pesticide solutions with random concentrations, and the percentage of inhibition was calculated for each of the three enzymes. Τhe training subset comprised 16 points, and the test subset had 6. For each enzyme, residual enzyme activities at nine different incubation times (1–15 min) in each pesticide mixture were recorded, resulting in 594 residual activity values as the input information for the ANN. The output layer was defined a priori: it had two neurons, one for each pesticide concentration (dichlorvos and carbofuran). The pesticide concentrations ranged from 0.029 to 1.56 nM for dichlorvos and 0.071 to 8.3 nM for carbofuran. ANNs were used to build a model and predict sensor responses to the simultaneous presence of the two pesticides in mixtures. The predicted values were in accordance with the spectroscopic reference data .r > 0.988) on the external test set. Another approach to determine phenolic contaminants (hydroquinone and guaiacol) in water was recently proposed by Mendes and coworkers [R2 > 0.99 and low relative error (1.3 to 4.4%) using cyclic voltammograms with 220 variables as the input data.The same research group also presented the simple methodology for the simultaneous detection of several phenolic compounds  using the amperometric enzyme biosensor based on polyphenol oxidase . The optoworkers . The tyrMost of the biosensors employed for the water quality determination are based on the amperometric transduction principle. The range of analytes of interest includes pesticides, phenolic compounds, heavy metal ions, and other non-specific pollutants. Some papers also aim to quantify both the biochemical and chemical oxygen demand  based on the combination of biosensors data and chemometric processing. It is important to mention that this type of quantification of integral quality parameters is only possible with sensor arrays and chemometric modeling as there is no way to construct a single sensor responding to the variety of chemicals responsible, e.g., COD. As can be seen from the examples above, chemometric processing can be applied both for handling the responses of individual biosensors and for responses of biosensor arrays. The most popular bioreceptors for ecological monitoring are enzymes as they allow a rather straightforward determination of harmful contaminants, such as phenols and pesticides.Another area where a lot of examples of chemometric processing of biosensor data are available is food chemistry. Biosensors based on various transduction principles are employed to analyze food and beverages, and data processing and modeling methods include Principle Component Analysis, Artificial Neural Networks, MCR-ALS, Partial Least Squares, etc.For a deeper understanding of biosensor applications in different areas of edible media analysis, more specific reviews are recommended ,35,36,37In the field of safety analysis, there exist numerous examples of biosensors developed for the determination of pesticides, herbicides, fungicides, heavy metals, and other toxic and harmful compounds in food to ensure its safety and compliance with standards and regulations. Similar approaches employing single biosensors and biosensor arrays are for the gustatory qualities’ analysis and detection of adulterations in food and beverages.As can be seen from Another field of use for biosensors is various biomedical studies: it is rather convenient to study different proteins in living organisms, tissues, and biofluids using the biorecognition principle that allows for high selectivity and specificity to the analyte. However, not only highly selective biosensors are developed; biosensor arrays with cross-selectivity are also widely employed to quantify single analytes, classes of analytes, and integral sample characteristics . This teA lot of biosensors developed for the biochemical and medical purposes are built for the recognition and quantification of various proteins: enzymes, kinases, cytokines, antibodies, etc. Recently, the approach to determine the activity of extracellular signal-regulated kinase (ERK) was suggested . This tyOne more example of the fluorescent SOX-peptides biosensing array to quantify mitogen-activated protein kinases activity was introduced by Zamora-Olivares D. et al. . The obtd-galactopyranoside and amplifying the response. The fluorescent responses were analyzed with LDA and classified by the Mahalanobis distances of unknown samples to the centroid of the respective protein clusters in the canonical score plot, resulting in 92% accuracy of classification.Miranda O. R. et al. proposed an enzyme-nanoparticle sensor array for the identification of proteins in human urine samples at the nanomolar level . The senDe M. et al. described a method for protein sensing in human serum samples with a biosensor based on the conjugates of nanoparticles with the green fluorescent protein (GFP) . FluoresAnother approach to protein classification in human urine was suggested by Motiei L. et al.: an array of cross-reactive optical biosensors was developed based on oligonucleotides, modified with fluorophores and protein-binding groups to identify different glutathione S-transferases . LDA wasAnother important type of analytes suitable for the biosensing in biochemistry are cells of different types: from bacteria to human tissues. A magnetoresistive biosensor was introduced for the BCG mycobacteria detection for the express diagnostics of tuberculosis . The minAn interesting approach to the cell type differentiation was suggested by Bajaj A. and coworkers : gold naOne more option for cell identification based on the optical cross-reactive biosensor array was presented by Tomita S. et al. . The senApart from proteins and whole cells as the substances for biosensing and chemometric processing, other analytes include lipids, nucleotides, neurotransmitters, and pharmaceutical substances. For example, an enzymatic biosensor based on a set of three deoxynucleoside kinases was proposed to monitor the nucleoside analogs in human plasma . A BayesAnother interesting approach was suggested for the quantification of glycerides and their regio- and stereoselective identification . The senA multielectrode array was suggested for the voltammetric quantification of neurotransmitters dopamine and norepinephrine in biological fluids in situ, i.e., without any pretreatment steps . The eleChemometric methods not only are useful in terms of processing the existing data but also for planning the experiments and rationally designing new sensors. One example of the experimental design is the attempt to evaluate how much the experimental design influences the prediction ability of a chemometric model . The nonBotryosphaeria rhodina, namely laccase and botryosphaeran. A factorial design was used to optimize the operational parameters of the sensor and the most suitable pH for the measurements. The optimized biosensor is able to quantify the chlorogenic acid in coffee samples resulting in statistically similar values to those obtained by HPLC at the 95% confidence level.Another paper  describeThe chemometrics-assisted approach to the design of the bioreceptors for the new sensors is widely used in the development of new molecularly imprinted polymers (MIPs) . MIPs arThe chemometric-based approach to MIP design and synthesis seems to be an excellent opportunity to overcome this disadvantage; therefore, it has already been demonstrated on a number of different templates. It is based on statistical analysis and allows using the experimental data for MIP design. For example, Muzyka et al.  demonstrOther examples of rational MIP synthesis design include the two-factor experimental design for the (–)-ephedrine imprinted polymer , optimizOnly a few examples of the structure–property/activity relationships modeling in biosensors development exist. Thus, there was an attempt to describe the antigen–antibody interaction kinetics in the sensor chips , or the We believe that further research in the application of chemometric methods to biosensor data will be focused on several main topics. The employment of chemometric algorithms may help in the mass-production of biosensors to improve their interbatch reproducibility. This can be achieved by using the methods of multivariate calibration transfer between two non-identical sets of sensors. These non-identical sensors will produce different responses’ values in the same sample, thus invalidating the calibration and implying the necessity of frequent measurements in calibration solutions. Since standardization at the physical level is not always possible due to the natural variability in raw materials, the application of mathematical methods appears to be an attractive option in this respect. This also relates to the long-term stability of biosensor response in applications requiring continuous measurements—the chemometric algorithms are available to eliminate long-term response drifts of sensors and sensor arrays ,80.Another important issue with chemometrics relates to the fact that at the moment, only a few reports are addressing the development of formal analytical figures of merit like sensitivity, selectivity, detection limits for sensors and sensor arrays employing multivariate calibration ,82. ThisWith the active development of various machine learning tools intended both for solving classification and regression problems, one can also predict their adoption in the field of biosensing; however, thorough precautions must be taken against a careless implementation of all newly developed mathematical tools just because they are new. Quite often, the choice of the optimal method is very task specific, and the understanding of all pros and cons is needed for the responsible application of mathematical tools in biosensing.Although it may seem unnecessary at first glance due to the high selectivity of bioreceptors, the application of chemometric methods can provide significant improvements for the analytical performance of biosensors. In particular, the following advantages can be achieved: better precision in the resolution of complex analyte mixtures, better tolerance of sensor response towards interferences, and a possibility of quantifying complex integral sample quality parameters depending on many various (bio) chemical components. As part of the discussed applications of chemometric tools to biosensor data in environmental monitoring, food, and beverage analysis, biomedical problems reveal the high potential of this approach for further development of biosensing. The discussed applications of chemometric tools to biosensor data in environmental monitoring, food, and beverage analysis, biomedical problems reveal the high potential of this approach for further development of biosensing. We believe that future research in this area will bring a whole variety of new exciting opportunities for using biosensors.


The rapid advancement in vaccine development represents a critical milestone that will help humanity tackle the COVID-19 pandemic. However, the success of these efforts is not guaranteed, as it relies on the outcomes of national and international vaccination strategies. In this article, we highlight some of the challenges that Romania will face and propose a set of solutions to overcome them. With this in mind, we discuss issues such as the infrastructure of vaccine storage and delivery, the deployment and administration of immunisations, and the public acceptance of vaccines. The ways in which Romanian society will respond to a national COVID-19 vaccination campaign will be contingent on appropriate and timely actions. As many of the problems encountered in Romania are not unique, the proposed recommendations could be adapted and implemented in other countries that face similar issues, thereby informing better practices in the management of the COVID-19 pandemic. The COVID-19 pandemic has generated unprecedented efforts in the development of potential vaccines against its causative agent, SARS-CoV-2 . Prior to the COVID-19 pandemic, RENV required all childhood immunisations to be recorded by medical personnel, thus having the prerequisite attributes to serve as a useful tool in any national vaccination campaign . Indeed,One of the recurrent topics worldwide concerned the question of who will be the first beneficiaries of COVID-19 immunizations .Uncontrolled distribution and reports of individuals “jumping the queue” have the potential to generate mistrust and cause public unrest. Indeed, there are numerous instances of this phenomenon occurring throughout the Romanian healthcare system, as waiting lists are vulnerable to corruption . As suchPublic outreach concerning immunization is critical for the success of a national COVID-19 vaccination campaign due to several issues . For exawww.vaccinare-covid.gov.ro) which provided accessible information, including other verified national and international resources , in the sense that some people may wish to be immunized, but would not disclose that in polls or surveys . This phThroughout the COVID-19 pandemic, containing the spread of misinformation was perhaps at least as difficult as controlling new infections. Indeed, Romania is no exception to this phenomenon, and there are numerous instances where public health efforts were hindered by false information. For example, during the early stages of the pandemic, returning members of the Romanian diaspora were vilified on various social media platforms . SimilarSocial media need not be detrimental to the prevention and control of infectious diseases. Indeed, if its potential can be harnessed efficiently, public health interventions may gain significant advantages. Fortunately, such is the case with vaccination in Romania, where social media platforms have become an important vector for the delivery of accurate scientific information. For example, Romania has the largest Facebook group in the world that provides parents with vaccination advice directly from primary-care physicians , 17. WitLastly, the success of any immunization campaign depends on the sociocultural and historical factors that characterize the region(s) of the concerned populations. Important contributions to national public health campaigns can be offered by non-governmental entities, as was demonstrated in the course of the COVID-19 pandemic. One of the most illustrative examples in Romania concerns the Romanian Orthodox Church, which contributed both by providing significant human and material resources and by reinforcing the messages that were communicated by public health authorities . This waad-hoc vaccination campaigns which were not based on a solid framework did not achieve their desired goals. Such is the case with the 2008–2009 HPV vaccination campaign, which had a staggeringly low success rate (2.57%) without facing the many difficulties associated with the COVID-19 pandemic (In Romania, by the end of December 2020, there have been more than half a million documented SARS-CoV-2 infections, with the real numbers likely far exceeding this figure due to insufficient testing (pandemic .As the Romanian healthcare system is under immense pressure, an evidence-based strategy drawing on implementation science is the most effective means of delivering such a task . A succePublic health actions in Romania must be taken based on the lessons learned from successful vaccination campaigns in other countries of the EU and around the world. The available scientific knowledge concerning the implementation of good practices should serve as a basis for thorough planning and informed choices with regards to country-specific issues.COVID-19 testing must continue, and the national testing capacity must be increased for accurate data to inform the vaccination campaign. Currently, Romania's testing strategy offers a limited insight into the number of daily infections. A better understanding of the incidence rate coupled with cross-sectional studies of seroprevalence will inform strategies which could be tailored to specific regions of the country.Potential issues concerning the logistics of transport and storage need to be addressed in a centralized approach, and current impediments to the delivery infrastructure need to be identified and tackled. The involvement of military personnel in this process may overcome most of these challenges.The present infrastructure and information network concerning immunizations needs to be continuously developed to meet the demands of COVID-19 vaccination. Some of the resources available presently have the potential to be adapted for future requirements, and the feasibility of such actions will need to be carefully evaluated.The locations and stakeholders involved in immunization need to be clearly defined. Moreover, the Romanian public needs to be informed about the responsibilities of each concerned party throughout the vaccine implementation process.The identification and immunization of the priority groups should be explained and done appropriately. At the same time, equitable access to vaccination must be guaranteed, and constant communication concerning this aspect will be required during the COVID-19 immunization campaign in Romania.The transparency of both decision-making and implementation coupled with efficient communication will be crucial for a national vaccination strategy to succeed and for people to accept immunizations.Mechanisms to report potential side-effects or other issues concerning immunization need to be carefully defined and communicated in a clear and transparent manner.An elaborate and evidence-based vaccine awareness campaign must be carried out as soon as possible to tackle both general vaccine hesitancy and any potential mistrust concerning the provisioning of healthcare services. Moreover, classical awareness and educational campaigns will be insufficient if not brought together through an optimally devised delivery strategy that can be tailored to different at-risk categories of the population.Raising awareness and managing misinformation must be carried out on all channels of communication in Romania, with social media being of particular importance. With this in mind, the involvement of various influencers on these platforms will be key. At the same time, communication experts, psychologists, and sociologists should be approached to tailor the messaging strategy to various age and risk groups, according to national or local behavioral patterns.The support of influential figures and non-governmental institutions and organizations is required to facilitate an increase in the public understanding and acceptance of vaccines.A unifying legislative framework about vaccination is necessary to define the duties and responsibilities of all stakeholders involved in immunization. This will not only provide a basis for any national vaccination strategy, but will also ensure that all potential concerns are addressed in a clear and transparent manner.Together, these recommendations will create an efficient and sustainable vaccine implementation framework which will serve as a basis for tackling the current challenges posed by the COVID-19 pandemic in Romania.In this article, we have described some of the main issues concerning the COVID-19 vaccination campaign in Romania. We also highlighted mechanisms through which many of these difficulties can be overcome, provided certain criteria are satisfied and actions are taken in a timely manner. Although most of the challenges that we presented in this article are country-specific, the proposed solutions could be adapted in order to inform similar public health policy development in other EU member states and beyond.The original contributions presented in the study are included in the article and further inquiries can be directed to the corresponding author.SD, OC, and OG wrote the main text of the manuscript. SD coordinated the academic initiative which resulted in the drafting of this article. OC and OG contributed equally to the work. RC, GDi, GDu, VG, and EP provided very insightful suggestions and assistance throughout the drafting of the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.