Persistent sciatic artery (PSA) is an extremely rare condition that is present in around 0.05% of the population and is commonly associated with many complications. The management is conservative or through surgical intervention and depends on the type of complication. The case presented is of a 40-year-old man who complained of persistent pain in the buttock region. On radiology, bilateral PSAs were observed exiting through the infra-pyriformis compartment of the greater sciatic foramen accompanying the sciatic nerve. The femoral artery and the external iliac artery are small in caliber. In this case report, we discuss the underlying embryology that might have led to the persistence of this vessel with illustrations and the abnormal radiological pattern of this anomaly. Increased awareness of PSA can improve patient care and prevent potentially hazardous complications during hip and renal transplant surgery. Persistent sciatic artery (PSA) is an extremely rare vascular anomaly resulting from a lack of regression of an embryonal artery to the lower extremity. It is present in around 0.05% of the population, and only around 49 cases have been published in the world literature since 1832 [This anomaly should be kept in mind in the clinical assessment of a pulsatile gluteal mass as it presents potentially hazardous complications during hip and renal transplant surgery . In thisA 40-year-old man underwent a CT angiogram (CTA) investigation due to a six-month history of pain in the buttock region, which showed bilateral arteries exiting through the infra-pyriformis compartment of the greater sciatic foramen accompanying the sciatic nerve. The axial CTA images taken at levels of ischial tuberosity Figure  and uppePSA, especially the bilateral variant, is a very rare congenital vascular anomaly due to the abnormal developmental process of the axial limb vasculature. Knowledge of the embryological patterning of the lower limb vessels, which involves vasculogenesis, angiogenesis, sprouting, and resorption, is essential for understanding the persistence of the sciatic artery. The major arteries of the body wall and limbs are derived from the intersegmental arteries. Around 30 or more pairs arise serially at each segmental level and run between the somites . In the A literature search revealed that PSAs are classified into five types according to the Pillet-Gauffre classification. Type 1 represents complete PSA with normal SFA, type 2 represents complete PSA with incompletely developed SFA, and type 3 represents incomplete PSA with the persistence of proximal SFA. Type 4 represents complete development of SFA but the axial artery (represents the sciatic artery) is persistent at the lower part. Type 5 is a mix of the above . The axiAs seen in the radiological images, these arteries are located superficially and need to be further evaluated as they tend to result in pathologic vascular complications such as aneurysm formation. Symptoms such as lower limb pain, claudication, cold lower extremities, black toes, neurological deficits (sensory and motor), and pain along sciatic nerve distribution are some of the clinical presenting signs and symptoms of this anomaly. A minority of patients also present with a palpable popliteal pulse in the absence of femoral pulse (Cowie’s sign) . This anThe management of these types of cases is variable depending on the pathology as well as the classification type. While types 1 and 2 are typically treated medically, arteries in the other types are prone to embolism and aneurysm formation and are treated by interventional radiologists with coil embolization .PSA is an extremely rare condition and is commonly associated with many complications. In this case, bilateral PSAs were observed exiting through the infra-pyriformis compartment of the greater sciatic foramen accompanying the sciatic nerve. The management is dependent on the type of complication. As the patient in our case presented with pain in the gluteal region, and the CT failed to reveal any aneurysm or embolism, he was managed conservatively with pain control medications.


The evolution of next-generation sequencing has revolutionized genomic studies to generate more data at a cheaper cost. These are divided into short- and long-read sequencing technologies, depending on the length of reads generated during sequencing runs. Long-read sequencing also called third-generation sequencing emerged commercially through the instruments released by Pacific Biosciences and Oxford Nanopore Technologies, although relying on different sequencing chemistries, with the first one being more accurate both platforms can generate ultra-long sequence reads. Long-read sequencing is capable of entirely spanning previously established genomic identification regions or potentially small whole genomes, drastically improving the accuracy of the identification of pathogens directly from clinical samples. Long-read sequencing may also provide additional important clinical information, such as antimicrobial resistance profiles and epidemiological data from a single sequencing run. While initial applications of long-read sequencing in clinical diagnosis showed that it could be a promising diagnostic technique, it also has highlighted the need for further optimization. In this review, we show the potential long-read sequencing has in clinical diagnosis of fungal infections and discuss the pros and cons of its implementation.Identification of the causative infectious agent is essential in the management of infectious diseases, with the ideal diagnostic method being rapid, accurate, and informative, while remaining cost-effective. Traditional diagnostic techniques rely on culturing and cell propagation to isolate and identify the causative pathogen. These techniques are limited by the ability and the time required to grow or propagate an agent  Starting factor .Fusarium, Aspergillus, and Scedosporium actor 1α . The higactor 1α  and the actor 1α .Sequencing technologies have recently rapidly advanced. The early NGS technologies were classified as second-generation sequencing technologies and achieved increased sequencing throughput after the amplification of thousands of DNA templates and the simultaneous sequencing of the resulting DNA fragments, saving time, and decreasing costs . The mosThe introduction of sequence-based identification methods improved the speed and accuracy of fungal diagnostics and the rapid advancements of sequencing technologies enables the identification of fungi in complex samples.Metabarcoding/metagenomic sequencing is a method in which nucleic acid (DNA or RNA) of all organisms in a sample is extracted and sequenced using NGS techniques. The generated sequences are then used to identify organisms present in the sample. It was first mentioned in 1998 , when ittargeted amplicon sequencing (metabarcoding) and (ii) shotgun metagenomics. While the amplicon sequencing is based on the amplification of well-characterized genetic regions, shotgun metagenomics attempts to sequence the entire genetic content in a sample. The detailed differences between the two approaches have been previously discussed elsewhere (There are two main approaches which can be used to characterize the microbiome of a specific sample: (i) lsewhere .Targeted amplicon sequencing (metabarcoding) enables the direct identification of multiple species simultaneously from any environmental or clinical sample without culturing. It has been extensively used in microbiome studies and its biggest advantage over shotgun sequencing is the low amount of microbial DNA needed for identification and targeted enrichment of the sequence of interest. It is based on the amplification of specific taxonomic genetic regions (barcodes), such as the 16S ribosomal RNA (rRNA) gene cluster for bacteria  are unable to span the full length of the established barcodes, the entire ITS1/2 region . In addishotgun metagenomic sequencing allows for a higher resolution, as it sequences most parts of the genomes of every organism present in the sample. This feature enables the technology not only to identify the organism, but also to characterize their extended profiles, such as antimicrobial resistance, genetic subtypes, and virulence. It involves extraction of nucleic acid (DNA or RNA) from primary specimens , and sputum, tissue), fragmentation of the obtained DNA or RNA extracts, library preparation, in-depth sequencing, and subsequent data analysis. Shotgun metagenomics is significantly more expensive (depending on the sequencing depth) and computationally more extensive than amplicon sequencing. Another challenge is the overwhelming amount of host or background DNA compared to the microbial DNA. Many methods have been developed for enriching microbial DNA to combat this for both environmental and clinical samples, see below. Additionally, in cases of non-sterile patient samples or co-infections, genomic material from multiple microbial species may prove difficult to assign correctly to the particular species present . As previously discussed, culturing greatly limits the detection of causative pathogens, as not all pathogens can be grown in a laboratory setting and it also greatly delays the timing of accurate identification . In addi dataset .The quantity and quality of data generated from metagenomic studies is reliant upon the NGS technology used and as such the advantages and disadvantages must be considered. The characteristics of the main technologies used for the identification of fungal pathogens are summarized inThird-generation sequencing technologies are characterized by the generation of ultra-long-reads and offer a number of advantages over short-read sequencing. Long-read sequencing routinely generates reads over 10 kb . CurrentPacific Biosciences (PacBio) released the first commercial long-read sequencer in 2011 and continue to maintain and release improved sequencing instruments . The basPacBio currently have three sequencers on the market, the Sequel System, the Sequel II system, and the Sequel IIe system, released in October 2020 . The newde novo assemblies for genomes up to 2GB of a single sample and full length 16S region sequences for 192 samples for strain level identification . Additionally, the sample sites were bronchiolar lavage and induced sputum samples which are non-sterile sites and so multiple other fungal species were identified alongside the known causative pathogen. Notably, Paracoccidioides spp. were identified within the sample. However, this indicates a clear false positive, as Paracoccidioides spp. are geographically restricted to the tropical areas of Latin America, which did not align with the patient’s travel history. This indicated that fungal diagnosis solely based off metagenomic sequencing using ONT has currently a number of limiting factors, including the low host:pathogen ratio, lack of comprehensive reference sequence databases, and the lack of appropriate bioinformatic tool, which need to be overcome before it can be applied in a routine diagnostic setting  DNA in the sample, which may shadow the detection of pathogen DNA. One possible solution would be to increase the proportion of pathogen DNA in comparison with host DNA within the sample. This may be achieved through the depletion of human DNA in the clinical sample, which still is suboptimal even though there are several commercial kits and laboratory protocols for this purpose available .An alternative to this would be to increase the abundance of pathogen DNA, which can be achieved through amplification of important genomic regions, such as in metabarcoding studies, or amplification of overlapping DNA regions as done in viral whole-genome sequencing . An imprAnother way to enrich pathogen DNA and deplete host DNA is the application of adaptive sequencing with nanopore sequencers. DNA molecules are selected for by identifying unwanted sequences and reversing the voltage across the membrane, thereby stopping sequencing. Bioinformatic tools have been developed to implement adaptive sequencing for the selection of specific chromosomes and the depletion of bacterial genomes to enrich the remaining species in a metagenomic population . For diaThe major appeal of long-read sequencing in a shotgun approach is the vast genomic information that can be gained from the data generated. In metagenomic studies, genomic information from throughout the genome is generated; however, there is a lack of reference genomes for most of the pathogenic fungal species  and as sThe basis for accurate genomic-based identification is the availability of high-quality, curated reference whole-genome databases. It has been demonstrated that inaccurate reference sequences have caused miss-mapping of the generated sequence reads leading to clear misidentification that potentially causes confusion surrounding diagnosis in clinical practice . In addiFusarium solani species complex. A previous study examined four loci of these species and proposed the change in nomenclature of the F. solani species complex to be placed in the Neocosmospora genus  fungal species would greatly increase the discriminatory power of long-read sequencing in clinical diagnosis.It is predicted that with the implementation of a reliable and accurate whole-genome reference database, the accuracy of fungal identification will dramatically improve . The prira genus . HoweverFusarium . As suchThis highlights that global efforts are urgently needed to improve the relevant reference genome databases (FungiDB and GenBank) as well as the antifungal resistance database MARDyCurrently, there is a wide variety of bioinformatics tools for the analysis of long-read sequences . Some suFor use in a clinical setting, a simple bioinformatics workflow would be necessary for practical implementation into routine diagnosis as it would be best to avoid requiring highly specialized personnel for analysis. A study comparing the ability of different bioinformatics tools to identify a wide array of pathogens from long-read sequencing dataset would be necessary to determine the most suitable bioinformatics tools.Homo sapiens reads and reads assigned the causative pathogen. However, if any contamination was to occur and reads were assigned to multiple microbes, this would complicate identification of the causative pathogen. This issue is magnified when patient samples are taken from non-sterile sites. Sequencing results will have reads assigned to multiple microbes and although it would be intuitive to assume the microbe with the highest abundance would be the causative pathogen, this is not always the case as has been observed in H. sapiens reads also complicates data interpretation as percentages of reads assigned to microorganisms is comparatively small. However, if bioinformatics tools were designed to remove host reads, microorganism abundance can be more easily compared and may further illuminate the causative pathogen.Data interpretation is a major issue in metagenomics and metabarcoding analysis. Both methods generate large amounts of data and for the purpose of clinical diagnosis, the interpretation can be complex. When samples are taken from sterile sites, the expected sequencing results would consist of predominantly The introduction of long-read sequencers from PacBio and ONT has allowed sequencing of genetic material in a way previously not possible. The first applications of long-read sequencing to identify agents of infectious disease has demonstrated its potential in clinical diagnosis.The current state of DNA extraction technologies, the lack of comprehensive reference databases, and simple bioinformation pipelines requires further development before long-read sequencers can be implemented in routine diagnosis. Additionally, the identification of multiple microbes within a clinical specimen may not directly lead to a specific diagnosis, but in conjunction with the patient’s presentation and further testing should seriously be considered as a way to achieve a fast and reliable diagnosis. Further advancements in the clinical diagnostic metagenomics workflow must be made to make its implementation in routine clinical diagnostic feasible. With the rapid decline of sequencing costs and the exponential improvement in sequencing capabilities, long-read sequencing is an important new technology which may eventually reduce the impact of pathogenic fungi on human health, by drastically reducing the turnaround time for diagnosis, supporting better treatment choices, reducing morbidity and mortality, and massively reduce associated healthcare costs, through its use in clinical diagnosis.WM, LI, and BS conceived the review. WM coordinated and supervised the review. MH, LI, YH, BS, and WM wrote and corrected the manuscript. All authors contributed to the article and approved the submitted version.This study was supported by a National Health and Medical Research Council of Australia (NH&MRC) grant (no. APP1121936) to WM.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The mean value of MPLZC results in the non-focal group are significantly higher than those in the focal group for scales above 1 (p < 0.05). The result indicates that the non-focal EEG signals are more complex. MPLZC feature sets are used for the least squares support vector machine (LS-SVM) classifier to classify into the focal and non-focal EEG signals. Our experimental results confirmed the usefulness of the MPLZC method for distinguishing focal and non-focal EEG signals with a classification accuracy of 86%.This paper analyses the complexity of electroencephalogram (EEG) signals in different temporal scales for the analysis and classification of focal and non-focal EEG signals. Futures from an original multiscale permutation Lempel–Ziv complexity measure (MPLZC) were obtained. MPLZC measure combines a multiscale structure, ordinal analysis, and permutation Lempel–Ziv complexity for quantifying the dynamic changes of an electroencephalogram (EEG). We also show the dependency of MPLZC on several straight-forward signal processing concepts, which appear in biomedical EEG activity via a set of synthetic signals. The main material of the study consists of EEG signals, which were obtained from the Bern-Barcelona EEG database. The signals were divided into two groups: focal EEG signals ( Electroencephalography (EEG) is a non-invasive procedure to measure the bioelectric activity of the brain. The analysis of EEG signals contributes to a better understanding of brain functions and malfunctions. Electroencephalographic signals from epilepsy patients are of interest to researchers in particular.Epilepsy is one of the most common chronic neurological diseases, characterized by recurrent seizures that can be single or complex in nature and are manifested by disturbances in consciousness, behavior, perception, movement, or sensation. According to WHO data , over 50The diagnosis of epilepsy patients sometimes requires EEG recording directly from the brain surface or from deeper brain structures . IntracrNonlinear analysis of EEG signals includes many measures that allow for extraction of useful information from dynamical systems. There are many methods of detecting dynamic changes in physiological systems; some complexity indexes in particular, such as Lempel–Ziv complexity , permutaRelated researches have indicated that LZC  is powerThe purpose of the research presented in this article is to evaluate MPLZC measure in identification of focal signals.The structure of the paper is organized as follows: The Python language, an interpreted high-level performance programming language, was used for the analysis of the synthetic signals and EEG signals.Gaussian noiseIn this subsection, the simulated signals used to evaluate the MPLZC measure in terms of classical signal-processing concept  are described. Some of them have been used to evaluate the Lempel–Ziv complexity measure , auto-muWhite Gaussian noise is a random signal having equal intensity at different frequencies, giving it a constant power spectral density variance a.Pink noise, or te noise   [In the present work, we used Bern-Barcelona EEG database (ch 2021)  to verifThe Lempel–Ziv complexity measure can characterize the degree of order or disorder and development of spatiotemporal patterns . The sigsequence ,17. The Step 1: Transform the signal into a finite sequence Step 2: Let Step 3: Connect Step 4: The rule if Step 5: The permutation Lempel–Ziv complexity measure combines the permutation scheme and Lempel–Ziv complexity . In the MPLZC combine two topics. First, a coarse-graining procedure is applied to the original time series n-dimensional space (n-the number of features). The transformation is made in such a way that after it is made in the new space, objects are separable by means of a hyperplane . The hyperplane can be found using the least squares support vector machine (LS-SVM). The main element of the transformation is the selection of the kernel function responsible for mapping the points to the new space. The SVM algorithm works very well in practical applications, such as biomedical data analysis.The support vector machine (SVM) algorithm can be used for both classification and regression . The SVMSEN), specificity (SPF), and accuracy (ACC). The mathematical expressions of the classification parameters are presented as follows [LS-SVM classification was applied to confirm the usefulness of the obtained twenty MPLZC features. Scikit-Learn tool  implemen follows ,37,38:, which indicates that non-focal signals are more complex/irregular. The permutation Lempel–Ziv measures increase for all scales. Standard deviation values for both groups are large, but the non-focal group shows higher values of them, as can be seen in the Permutation Lempel–Ziv complexity was evaluated for 20 scale factors with the dimension m = 4. Mann–Whitney rank test  was used to find significant differences between the groups, and results were considered statistically significant for Comparing the signals shown in The result of the SVM classification is presented in The evolution of computational techniques has enabled the development of non-linear methods of analysis. These methods are derived from chaos theory and are often used in the study of complex biological systems. Chaos means some kind of disorder/irregularity in which there are both deterministic and stochastic elements. Lempel–Ziv complexity measure borrowed its useful approach for estimating randomness of finite symbolic sequence from chaos theory. Higher LZ values indicate the presence of new sequence patterns and thus a more complex dynamic behavior. The Lempel–Ziv measure shows the rate at which new patterns appear with respect to the underlying system regardless of whether the system is deterministic or stochastic.The study of dynamic systems in medicine characterized by high sensitivity to initial conditions suggests that the human body shows the highest degree of complexity. Living organisms are affected by changing internal and external factors. In order to maintain an actively changing body balance, it needs regulatory mechanisms (homeodynamics) based, inter alia, on the feedback loop. These dynamic systems, in a healthy person, contain oscillations of physiological parameters in acceptable ranges. The normal EEG signal consists of disorganized fluctuations, but during epileptic seizure, the EEG signals are more rhythmic. The change of such states is reflected by complexity. The LZ algorithm describes the EEG signal in the time domain, but there are studies showing the sensitivity of the method to changing the power spectrum and amplitude distribution in the time domain. Therefore, it seems justified to use LZ in the analysis of EEG signals. The Lempel–Ziv measure is based on the procedure of converting a signal into a binary signal using differently determined threshold values . Unfortunately, during such conversion, information from the original signal is lost. The study  showed tMPLZC values for noisy signals are higher than for periodic signals. As the length of the analyzed signal increases, the variability of the results (the standard deviation) decreases. The results were more stable. For both constant and amplitude-modulated chirp signal, the MPLZC values were increased along the windowing signal until the highest values were reached. The transitions between the windows were quite smooth. The analysis showed that there were no significant differences in slow change in amplitude. In the case of a quasi-periodic synthetic signal, the MPLZC values generally increased in successive time windows. For a scale factor of 1, the amount of noise power was not recognizable from the PLZC values because they were saturated. However, given the higher scale factors, the importance of the multiscale concept can be seen. Different noise power levels saturated a different number of temporal scales. For coloured noise, MPLZC was sensitive to signal bandwidth changes with increasing bandwidth. The analysis in AR(1) process showed that a part of the signal with wider spectra has higher values. Mix process showed that values of MPLZC decrease from randomness to periodic oscillations.By using the MPLZC measure, the EEG signal analysis is focused on the possibility of differentiation of focal from non-focal signals. Lower PLZC values of focal signals suggest that the arrangement of brain EEG signals increases during focal epilepsy. This is consistent with the general hypothesis that reduction in the permutation Lempel–Ziv complexity of biological signals is associated with disease . MoreoveRelated studies have indicated that complexity indexes are powerful in analyzing focal versus non-focal signals within the Bern-Barcelona EEG database . The preThis is the first study to introduce a new methodology of complex systems analysis;The features obtained from MPLZC analysis allow for distinguishing two classes of EEG signals;We used only one measure, so it can be useful in building a real system supporting identification of a epileptogenic activity in an area of the brain.The main highlights of this study are as follows:In the feature, the proposed solution should be applied with reconstructed source-space data from surface EEG, EMG (electromyography), or EHG (electrohysterography).


In 2020, the global spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection  has led to pandemic health issues with significant changes in individual and community practices. Preterm birth could be one of the risks in pregnant mothers who are infected by the SARS-CoV-2. Preterm births contribute upto 10% of all births and incur significant impact on the child health and cost to the health care system. However, the association of city lockdown during COVID-19 pandemic with the rate of preterm births is unclear. In a cohort study, we examined the association of city lockdown during the COVID-19 pandemic with the births at different gestations in three different cities. Compared with the pre-pandemic epoch, the associative relationships ranged from a decrease in all births, all births across all preterm gestations and to preterm births in moderately and late preterm gestations. We concluded that there were variable associative relationships of city lockdown during COVID-19 pandemic with preterm births. This could be related to the differences in health, societal and cultural factors, which will inspire further studies in this area. In 2020, the global spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection  has led to pandemic health issues with significant changes in individual and community practices. Masking, hygienic practices and city lockdown are advocated to different extents in various jurisdictions. Preterm birth could be one of the risks in pregnant mothers who are infected by the SARS-CoV-2  categorized into different groups according to the range of preterm gestation  of Edmonton and Calgary in Alberta, Canada and Shenzhen in China. We also examined the rates of stillbirths during these epochs. We further compared the rates of preterm births at different gestational groups and stillbirths (defined as births at ≥20 weeks gestation and/or ≥500g) during pre-pandemic and pandemic epochs using the z-test . Odds ratios and 95% confidence interval were also calculated.Following institutional approval for a COVID-19 audit project, we accessed the database collected by the provincial and municipal epidemiological programs of Alberta Perinatal Health Program and Shenzhen Pregnancy Outcome Program. We studied the rates of preterm births . The increase in stillbirths in Calgary was modest.Regarding the rates of stillbirths in Calgary, Edmonton and Shenzhen, we did not find any significant differences during the pre-pandemic and pandemic epochs (16/2969 and 23/2628; 31/3085 and 29/2970; 21/13776 and 20/11727; Up to date, there are few reports that investigated the association between adverse birth outcomes and city lockdown during the COVID-19 pandemic period. Matheson et al. recently reported low rates of preterm births during the COVID-19 lockdown in Melbourne, Australia . They obOur findings showed a variable associative relationship of city lockdown with preterm births depending on the societal-cultural and gestational age in different jurisdictions. Hederman et al. suggested that elements of the lockdown including reduced infection load and reduced physical activity might possibly be beneficial for reducing extreme preterm births and potentially reducing infant mortality . InteresIn the last year, many reports and systematic reviews have been published to examine the association between COVID-19 in pregnant women and the maternal and neonatal outcomes. Papapanou et al. analyzed 39 reviews and, after accounting for quality of studies, reported increased rates of cesarean sections and preterm birth rates, with iatrogenic reasons potentially involved . FurtherPreterm birth occurs at ~10% of births worldwide and is associated with significant mortality, acute morbidity and long-term neurodevelopmental and neurobehavioral consequences. Razzaque et al. advocated the importance of antenatal care visits for maternal and fetal health with regular consultation with a health professional throughout the pregnancy for mothers with SARS-CoV-2 infection . We fullOur study is limited by the retrospective review of epidemiological databases with an one-time snap-shot observation. We have challenges and should be cautious in the interpretation of aggregated data which have significant ecological fallacy and confounding bias of individual data . Of noteOur interesting findings are preliminary and needed to be confirmed with the data from other jurisdictions. The causes of variations in the rate of preterm births between different regions are yet to be determined. Responses to the lockdown restrictions, air pollution levels, social safety network for pregnant women and government measures to relieve financial stress on families are potential factors. Understanding the relationship between lockdown and preterm births may help develop policies to prevent and reduce preterm births.The original contributions generated for the study are included in the article/P-YC conceptualized and designed the study, collected and analyzed the data, drafted the initial manuscript, and reviewed and revised the manuscript. BA and CY conceptualized the study, collected the data, and critically reviewed the manuscript for important intellectual content. 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.


Pinus tabuliformis) during 2017–2019 at three sites in semi-arid China. We compared the dynamics of xylem formation under a drought event, testing the hypothesis that drought affects the process of cell enlargement and thus induces the production of IADF. Wood microcores collected weekly from April to October were used for anatomical analyses to estimate the timings of cambial activity, and the phases of enlargement, wall thickening, and lignification of the xylem. The first cells started enlargement from late April to early May. The last latewood cells completed differentiation in mid-September. Trees produced IADF in 2018. During that year, a drought in June limited cell production in the cambium, only 36% of the xylem cells being formed in IADF trees, compared to 68% in normal tree rings. IADF cells enlarged under drought in early July and started wall thickening during the rainfall events of late July. The drought restricted cell enlargement and affected wall thickening, resulting in narrow cells with wide walls. Cambium and cell enlargement recovered from the abundant rainfall, producing a new layer with large earlywood tracheids. IADF is a specific adaptation of trees to cope with water deficit events occurring during xylem formation. Our findings confirmed the hypothesis that the June-July drought induces latewood-like IADFs by limiting the process of cell enlargement in the xylem. Our finding suggests a higher occurrence of IADF in trees of arid and semi-arid climates of continental Asia if the changes to monsoon flows result in more frequent drought events during the earlywood formation in June.Intra-annual density fluctuation (IADF) is a structural modification of the tree ring in response to fluctuations in the weather. The expected changes in monsoon flow would lead to heterogeneous moisture conditions during the growing season and increase the occurrence of IADF in trees of the arid ecosystems of continental Asia. To reveal the timings and physiological mechanisms behind IADF formation, we monitored cambial activity and wood formation in Chinese pine ( E-IADFs), or earlywood-like cells with larger lumina and thinner walls in latewood intra-annual density fluctuation  is a structural modification of the tree ring involving an abrupt change in wood density , produciL-IADFs; . Large tL-IADFs; . IADF reL-IADFs; . The morL-IADFs; .L-IADFs occurring after the summer drought, at the beginning of the autumnal rainfall  in three sites located in the semi-arid region lying between the East Asian monsoon zone and the arid region of Northwestern China and investigated the dynamics of xylogenesis and IADF formation. The objective of this study was to (i) assess the phenology of IADF and (ii) investigate the climatic drivers of IADF production. We tested the hypothesis that summer drought affects the process of cell enlargement and thus induces IADF.In this study, we collected samples in Chinese pine (Pinus tabuliformis) is one of the dominant tree species growing at the northwestern boundary of its distribution. The long-term climate recorded by the national weather stations during 1951–2019 showed similar mean annual temperature between the two regions, with 9.7 and 10°C in Helan and Hasi, respectively . Trees at Hasi were bigger, i.e., larger and taller, and older than those at the other two sites . The youThree automated weather stations were installed at each site to measure air temperature and precipitation every 30min, and daily means were calculated from the half-an-hour time series. To quantify drought severity, the standardized precipitation evapotranspiration index (SPEI) was calculated according to the Hargreaves equation, as a monthly difference between precipitation and potential evapotranspiration, using “SPEI” package  in R envWood samples were collected in 2017–2019 weekly, at breast height (1.3m above ground), from April to September, the main growing season of Chinese pine  using a We recorded the proportion of trees with IADFs in all sampling trees in each site and year; we compared difference in monthly air temperature, precipitation, and SPEI using mixed models to assess which factor affected IADFs occurrence. Year and site were considered as random effects in the model. To identify the timings of IADFs formation, the number of cells in earlywood, IADFs, and latewood were counted and reported in the form of proportion. Tracheids were classified as earlywood or latewood according to the Mork’s formula, which classifies all cells with lumen areas of less than twice the thickness of a double cell wall as latewood . The cumY(t) is the cumulative proportion of cells at time t; A is the upper asymptote parameter; β is the x-axis placement parameter; and k is the rate of change parameter. The cumulative proportion of mature cells, mature cell and wall thickening cells, and total xylem cells represented the timings when the cells produced by the cambium underwent enlargement and wall thickening  in a semi-arid region of northwest China and found that IADF cells were produced under a prolonged summer drought and differentiate during the precipitation deficit in June and abundant rainfall in July and August. These findings suggest that summer drought triggers cell enlargement and affects IADF formation, which allowed us to accept our initial hypothesis.Earlywood intra-annual density fluctuation is a response to a drought event occurring during the growing season, mainly in the summer , 2015. ILatewood-like IADF cells enlarged during the drought event, although some of them completed enlargement at the beginning of the abundant rainfall (DOY 190–210). IADF cells started wall thickening when the precipitations had started again (DOY 200) and matured before mid-August. A significant decrease in the number of cambial and enlarging cells at the end of the drought was also observed, suggesting that drought inhibited cambial division and thus limited cell differentiation. Water availability is the primary climatic factor limiting stem growth in dry and warm regions . ProlongIADF cells started secondary wall formation during the rainfall period, producing thick cell walls. It is suggested that wall thickness is encoded during the previous phase of cell enlargement . It is wIADF formation is a specific adaptation under summer drought. This modification in the xylem structure protects the trees from irreversible damage by xylem cavitation and vessel embolism at the cost of the reduction of water transfer efficiency . The phyThe rainfall of mid-July improved growing conditions and reactivated cambial activity and cell enlargement. In other words, once water availability is sufficient, xylogenesis recovers the expected activities of cell division and differentiation. During cell enlargement, the vacuoles loaded with sugars increase the turgor pressure and attract water inside the cells, then producing the large earlywood tracheids . This meSabina przewalskii in semi-arid northwestern China , and a State Scholarship Fund provided by the China Scholarship Council (202004910757).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Topological matter has now become a very broad field in frontier of condensed-matter physics and beyond. Initial study of quantum matter started about four decades ago when the quantum Hall effect was discovered. A quantum Hall state is characterized by a Chern number, which leads to the observed quantized transverse conductance in a 2D electron system under perpendicular high magnetic fields. Explosive development of the present topic of quantum matter was largely due to the theoretical work of Charles Kane and Gene Mele, and Shoucheng Zhang and their collaborators, who proposed topological insulators with time-reversal symmetry and predicted materials. The concept of topological matter with time-reversal symmetry may be traced back to a toy model studied earlier by Duncan Haldane. In the past 12 years, we have witnessed remarkable development in the field, thanks to the theoretical predictions and experimental discoveries in various types of topological matter.In a personal interview on this special topic, Xiao-Gang Wen at MIT—a pioneer and chief architect of a new concept of ‘topological order’—examines its significance. Topological order describes quantum entanglement well beyond Landau's phase transition. Wen emphasizes the difference and close relation between the topological insulator and the topological order, and introduces the notion of symmetry-protected topology. In Wen's view, topological order may also describe the internal structure of empty space, hence making the world out of it. According to Jain's composite, fermion theory—a quantum-entangled fractional quantum Hall state of electrons—can be viewed as an integer quantum Hall effect of composite fermions without long-range entanglement. Therefore, I would expect a deep connection between the quantum entanglement and composite fermions.The article by Ning Hao and Jiangping Hu is the first comprehensive review on the concept, models, materials and experiments on the topological states of iron-based superconductors. Topological states in iron-based superconductors are of great interest for the realization of Majorana modes at relatively high temperatures. This special topic includes several perspective articles. One of the important developments in topological matter is the observations of strong evidence of a Majorana zero mode inside corresponding superconducting vortices. Lingyuan Kong and Hong Ding report Majorana modes in iron-based superconductors. Yi Zhou examines theoretically spin-selective Andreev reflection of the Majorana zero modes, which was observed by the Jinfeng Jia group in 2016. In another perspective paper, Jian Wang discusses the observed tip-induced superconductivity in topological semimetal. Ke He and Qi-Kun Xue, who discovered the quantum anomalous Hall effect together with their collaborators in 2013, show an interesting perspective of quantum anomalous Hall hetero-structures. Chen Fang finds an automatic search for topological materials and his team have predicted non-trivial band topology in over 8000 materials, hence a large class of topological materials has been cataloged. Joel Moore reviews the optical properties of Weyl semimetals including TaAs and related compounds. Haizhou Lu proposes a 3D quantum Hall effect in topological semimetal and discusses the experimental findings and remaining questions on this. Yan Zhou outlines the intriguing physics and new spintronic device concept inmagnetic skyrmions.This special topic only covers a small portion of the recent development in topological matter—a field expanding rapidly. I expect the field to continue to grow for years to come. The new challenges will be in understanding and predicting topological matter with strong interactions and in topological materials with great applications. China has been very active, with a number of major contributions in the field, including the discovery of the quantum anomalous Hall effect, the observations of Majorana zero modes inside superconducting topological vortices, and the theoretical predictions and experimental realization of topological materials such as the 3D topological insulators and Weyl semimetals. I fully expect continuous activities in this field from China and the world. Finally, I wish to thank all the authors, reviewers and editorial staff for their substantial support in the preparation of this special topic.


Behavioral and psychological symptoms of dementia (BPSD) are taxing for both the person with dementia (PWD) and their family caregivers. Yet, little is known about how BPSD fluctuates throughout the day  and how caregivers perceive BPSD at different times of the day. Using 8-day daily diary data from 173 family caregivers whose relatives were using Adult Day Services (ADS), this study investigated temporal patterns of BPSD and caregivers’ stress responses to BPSD throughout the day. Overall, the number of BPSD was highest in the evening, and caregivers’ stress reactivity to BPSD increased throughout the phases of the day . However, caregivers showed lower reactivity to BPSD in the mornings and at night on days when the PWD used ADS. Our findings about fluctuations of (caregiver reactions to) BPSD throughout the day suggest target windows for just-in-time adaptive intervention.


Allosteric drugshave been attracting increasing interest overthe past few years. In this context, it is common practice to usehigh-throughput screening for the discovery of non-natural allostericdrugs. While the discovery stage is supported by a growing amountof biological information and increasing computing power, major challengesstill remain in selecting allosteric ligands and predicting theireffect on the target protein’s function. Indeed, allostericcompounds can act both as inhibitors and activators of biologicalresponses. Computational approaches to the problem have focused onvariations on the theme of molecular docking coupled to moleculardynamics with the aim of recovering information on the (long-range)modulation typical of allosteric proteins. Here, wepresent a protocolthat combines docking-based screening, information on the conformationaldynamics of the protein, and machine learning (ML) to classify ligandsof the molecular chaperon Hsp90 as activators or inhibitors. To thisend, we develop a classifier of activation/inhibition of Hsp90 allostericligands that is trained on data from a panel of ensemble docking results.The data set for this study is built from a database of 133 knownHsp90 ligands.Three different ML methods are compared withthe best-performingalgorithm, achieving an average balanced accuracy of 0.90  in correctly separating inhibitors from activators.A comparison with a direct classification of the chemical propertiesof ligands suggests that the ML prediction is not dependent on thesimilarity among the molecular structures but recovers hidden similaritiesin functional effects of different ligands.2 In particular,improved target identification can shed light on biomolecules whoseperturbation via small-molecule binding results in a functional response,transforming a disease phenotype into a normal one. The extraordinarycomplexity of biochemical networks in healthy and disease conditions4 and the costs associated with drug discovery are however hamperingthe advent of this new era of therapeutics, as shown by the relativelylow numbers of new drugs approved in the past few years.6 Most drug discovery efforts aim at targeting the active sites ofenzymes or the orthosteric sites of regulatory proteins. Because ofthe evolutionary and structural conservation of such sites acrossthe proteome, issues related to selectivity, off-target effects, anddevelopment of drug resistance have started to appear.The improved knowledgeof gene organization coupled with the advancesin gene editing and structural analysis methods can potentially starta whole new era in drug discovery.10 Allosteric ligands bind to sites that are generally distinct anddistal from the classic orthosteric ones. In doing so, they can perturbthe target not only by inhibition but also through modulation or activationof specific functions. This represents an advantage in terms of fundamentaland applicative perspectives. In fundamental research, chemical modulators(effectors) can be used to direct signaling pathways and whole cellstoward desired functional states, representing important tools forunderstanding the roles of specific biomolecules in complex biochemicalnetworks.12 In biomedical applications, since they targetsites that are generally less evolutionarily conserved, allostericligands can be highly selective, even among different members of thesame protein family,13 providing new opportunitiesfor therapeutic discovery.In thiscontext, allosteric ligands have recently emerged as aviable complement or alternative to active-site directed molecules,with novel potential as drug candidates or chemical tools.To date, most  allostericligands/drugs have beendiscovered using high-throughput screening. The ever growing amountof sequences and structural information combined with the increasesin computing power and the improvement of predictive algorithms arestarting to facilitate the discovery of allosteric modulators, butmajor challenges remain to develop approaches focused on rationaldrug design.15 Efficient screening of large libraries of compounds is achievedby the use of approximate scoring functions and simplified strategiesfor conformational sampling.16 Typically,a static model of the target structure is used. However, recentlythe influence of protein dynamics on the recognition process has beenmore accurately modeled using ensemble strategies.22 These strategies involve the docking of a molecular ligand librariesover an ensemble of selected geometries of the protein, creating amore realistic representation of the ligand bound to the differentexpected conformations of the target. The use of an ensemble of conformationsreduces the dependence of the docking results on the target structure.23 Ensembles can be extracted from unbiased molecularsimulations of apo structures24 and moreoften by sampling of protein conformations from holo structures containingfirst-generation ligands.25 Under the assumptionof conformational selection, a set of different ensembles representingdifferent binding states would have selective preferential bindingfor different ligands. On the basis of this hypothesis, previous studieshave used “a panel of ensembles” for virtual screening,26 whereby a vector of binding affinities againstthe panel is used to generate a specific fingerprint for each ligand.Computational approaches to the problem have focusedon variationson the theme of molecular docking. Binding affinities predicted bydocking simulations are routinely used in virtual screening to estimaterelative ligand rankings and to inform further steps in lead identification.29 and they have been effectively used in the enhancementof structural-based virtual screening and scoring.31 ML methods are mostly data-driven, and their performance is oftendependent on the size and quality of the data set. To this end, theymay present limited transferability, and care is required in reportingresults and the scope of applicability.This type of data has high dimensionality both in the chemicaland conformational space and is best suited for analysis using MLmethods, which have been increasingly adopted in drug discovery studies.Indeed, they contributed to the improvement of performance in virtualscreening studies32 Indeed, a major limitation in docking simulations is the lack ofinformation on the functional consequences of the allosteric bindingevent. While relative binding affinities and geometries can be reproducedclose to experimental accuracy, there is no predictive score to discriminateinhibitors from activators, agonists from antagonists or partial agonists.33 Experimental assays typically report on theorthosteric function, in most cases by direct measurement of a relevantbiochemical parameter that involves the active/orthosteric site. Thismay not necessarily reflect the affinity of binding at the allostericsite.36 In most cases, binding is only one aspect of an intricateinterplay of structural and dynamic factors that emerges from thecross-talk between the allosteric ligand and the protein and definefunctional responses. As a consequence, the derivation of structure–activityrelationships (SARs) for allosteric ligands is typically much morecomplex than for orthosteric ones.The combination of MLwith molecular simulations can dramaticallyadvance the process of selection of allosteric ligands with a desiredimpact on the function of the target.This unmet challenge callsfor new approaches that integrate informationon binding, conformational dynamics, and biological activity becausethe desired readout of the binding event is a change of functionalstate in the protein that is not directly or easily modeled by singledocking calculations.42 Proteins of the Hsp90 family  are homodimers with two chains consistingof three globular domains, the N-terminal (NTD), middle (M), and C-terminal(CTD). The functions of the chaperone are regulated by ATP hydrolysisin the NTD, where ATP processing is coupled to Hsp90 conformationalreorganization and consequent client remodelling . This data set was usedto train and test the predictive model. The protein conformationalensembles for docking were generated by atomistic molecular dynamicssimulations in explicit water of Hsp90 in complex with three differentligands: one activator (CC26) and two inhibitors (ND2 and Novobiocin).First, a panel of structural ensembles is generatedby clusteranalysis of conformations from molecular dynamics simulations of representativeholo structures, in which Hsp90 is bound to ATP in the N-terminaldomain and to an allosteric effector in the allosteric site. Thena library of allosteric compounds is docked against the Hsp90 structuralpanel. Finally, a predictive model for functional classification ofthe allosteric ligands is trained taking into account the structural,dynamic, and energetic properties of the resulting complexes. Fromthe literature, we collected 133 compounds with known activity againstHsp90, comprising 49 inhibitors and 84 activators ; the backbone atoms of middle domain (Clust-M); thebackbone atoms of N-terminal and middle domains (Clust-NM), and thebackbone atoms of middle and C-terminal domains (Clust-MC). In additionto these domain-based frameworks, a cluster analysis of the allostericsite was performed, where the ligand binding site was defined as theensemble of residues that are within 1 nm of any bound allostericligand in at least 75% of all visited structures collected in themetatrajectory. This latter criterion was used to consider the mostrelevant local interactions between residues in and around the bindingpocket and the ligand. It is worth underlining here that, during MD,the spectrum of contacts dynamically evolves.Next, the representativestructures from the three most populatedclusters for each of the four domain-based ensembles were selectedas a target for docking experiments. The total number of structuresin the three most populated clusters always account for at least 45%of the metatrajectory. In addition, the two main representative structuresresulting from the allosteric-site based clustering were added. Twostructures were enough to recapitulate more than 95% of the structuralvariability observed in the pocket.Cluster analysis of themolecular dynamics metatrajectory yieldeda total of 14 representative protein structures for the followingstep of docking. This collection was generated to capture the propensityof Hsp90 to populate conformations potentially endowed with differentfunctional properties. After docking the ligand library to each ofthe selected representative structures, three measures were calculatedfor every resulting complex: the docking score of the best pose forevery representative structure; the root-mean-square (RMS) of thedocking score for the 10 best poses; and finally, the RMSD on theatomic positions of the first 10 poses, reporting on the structuraladaptation within the pocket. Ten poses per ligand were selected asa compromise to provide a tractable and easy to visualize number ofconfigurations, while capturing positional adaptation of the moleculesto a changing binding site. A total of 42 features was thus used forML prediction.The underlining hypothesis of our study is thatfeatures describingthe docking results of a ligand against a panel of distinct conformationalensembles can be used as “dynamic fingerprints” of itsfunctional effect on the protein. We tested this hypothesis underthree assumptions: (1) the separation of activators and inhibitorscannot be directly detected in the feature space by cluster analysis;(2) the separation of activators and inhibitors requires modelinga complex relationship by supervised learning; and (3) the separationcannot be trivially obtained by use of small molecule fingerprintsin the absence of information on the protein structure and dynamics.Supplementary Figure 3). This suggests that a model basedon the combination of these features is required to discriminate betweenthe two classes. The first step is to test if the separation of thetwo groups of ligands can be directly detected with an unsupervisedlearning approach.None of the features described above can independently be usedas a classifier and directly separate inhibitors from activators.This is evident from the distribution of values for every single featureagainst the two known ligand classes: in all the cases, the pair ofper-class distributions overlap  can be detected. Two different algorithmswere used: k-means and agglomerative hierarchical clustering. Thetarget cluster numbers could be set to 2, but we adopted an unbiasedapproach and explored values between 2 and 6. The ability to correctlyseparate ligand classes in the clusters was estimated by cluster purity,which has values between 0 (when the class labels are completely mixedin the clusters) and 1 (clusters composed by only one class). Bothalgorithms have similar purity values; in particular, when 2 clustersare considered, the purity is low ,and with more clusters, the purity increases, remaining below 0.80. The increased purity is due to the reduced size of clustersthat helps adapt to the class separation. Yet, the value in the caseof 2 clusters reveals that is difficult to detect a segmentation ofthe compounds in the functional classes directly by cluster analysis.This suggest that it is not possible to automatically partition thespace of the data to identify inhibitors and activators. A model trainedon properties from the different binding conformations is thereforeneeded.In this framework, a classification model was builtusing supervisedlearning. The model is trained to predict class labels describingthe functional effect of the ligand .Three widely used algorithms were compared: Logistic Regression (LR)as a baseline, Support Vector Machine (SVM), and Random Forest (RF).The performances of the three methods was compared after trainingand testing using the holdout method, where the data set is randomlysplit in training set and test set with the proportion of 70% and30% respectively. The performance in prediction is reported in LR and SVM show similarperformances while RF has poorer performance.Nevertheless, all three methods show a better classification powercompared with the cluster segmentation. A 10-fold cross-validationwithout shuffling was performed to exclude any bias due to the simpleholdout split and to further compare the methods. This approach alsohighlighted possible variability across the data sets and facilitatedinterpreting the performance with more insight on the chemical featuresof the molecules (see below).Supplementary Figure 4).SVM shows the best performancewith an average balanced accuracyof 0.90, compared with 0.87 (LR) and 0.79 (RF). In Supplementary Figure 5), and therefore, no feature was detected as dominant.Finally, the possibledominance of one type of ensemble feature in the prediction was assessed by selectivelyexcluding each feature in turn and repeated cross-validation. In eachcase the variation in the average performance was not statically significant. It may be possibleto qualitatively cluster these molecules with respect to shared scaffolds:in our case, this results in eight different groups . The comparisonwas broken down by chemical groups to explore how the two approachesperform on different subclasses of ligands. In The best result obtained by ECFP fingerprint on two clusters wascompared with the best ML predictive model obtained by SVM  for yeast Hsp90were downloaded from the Protein Databank. Initial poses for liganddocking were derived from previously published models.www.schrodinger.com): Bond orders and atomic charges were assigned, and the hydrogenswere added. Protonation states were evaluated on acid and basic enzymes,and hydrogen bonds were optimized. The protein was then minimizedwith a Cutoff of 0.3 with respect to starting configuration. The Glide60 software was used for molecular docking: theputative binding site was mapped on a grid with dimensions of 48 A,enclosing box, and 28 A, inner box. Calculations with a fixed receptorand flexible ligand were made with standard precision (SP) modalitywith OPLS3e Force Field. No additional changes to default settingswere made. Fingerprint similarities were computed with the Canvasprogram of the Schrodinger Suite, and the typing scheme is atom distinguishedby functional type with no scaling in 32 bit.All systems were prepared using the Maestro Software Suite fromSchrodinger  for optimization. The SVM models were trainedusing a linear kernel and all other settings were set to default values.The RF models were trained with an increased number of trees (1000)compared with default, and the best split at decision points was selectedby minimization of Gini impurity.In-house scripts for cluster analysis and supervisedlearning predictionwere developed in Python using scikit-learn functions.


Numerous studies demonstrate racial and ethnic differences in end-of-life (EOL) care, including place of death and hospice use. Experiencing discrimination in healthcare is often cited in the literature as a potent source explaining the pathways of the racial and ethnic disparities in EOL care. However, none of the studies have tested its mediating effects on racial and ethnic disparities in EOL care. The study examines if the effects of race and ethnicity on place of death and hospice use are mediated by perceived healthcare discrimination. This is a secondary analysis of 2008-2014 data from the nationally representative Health and Retirement Study, including oversampling of Blacks and Hispanics. Samples included 1,446 decedents aged 65 or older who completed an exit interview by proxy. Perceived healthcare discrimination was measured by a self-report of receiving poorer service or treatment than other people from doctors or hospitals. In multivariate analyses, Blacks were more likely to die at hospitals  than Whites. Those who experienced discriminatory healthcare were more likely to die at hospitals than those who never experienced discriminatory healthcare . However, the Karlson-Home-Breen (KHB) method showed no significant mediating effects of perceived healthcare discrimination on racial and ethnic disparities in place of death. Race and ethnicity did not affect hospice use. Although there is no mediating effect of healthcare discrimination on racial and ethnic disparities in EOL care, its direct impact is observed. The research contributes to evidence on the significant role of discrimination in healthcare choices.


The use of electronic cigarettes (ECIGs) has become popular in recent years. The popularity can be attributed to any number of reasons ranging from harm reduction  to availability of a myriad of palatable flavors. Regardless of the reasons for this surge in popularity, ECIG use has become a public health concern. Less is known about vaping  and its effects on human health as compared to conventional smoking. Furthermore, what is known remains inconclusive due to the lack of experimental standardization. To better understand how ECIG-generated aerosol interacts with biological systems, and consequently, how it affects human health, it is imperative that the physical characteristics and chemical composition of the inhaled aerosol be investigated in a standardized manner. Of particular interest is the overall effect the addition of nicotine and/or flavors to the ECIG-liquids (E-liquids) have on human health. Hence, the objective of this Research Topic is to bring forward a collection of research articles assessing the potential impact the physical and chemical nature of E-liquids and ECIG-generated aerosols have on human health. The result of this effort is a collection of 12 papers authored by 43 researchers, globally. This collection consists of three reviews, eight original research articles and one commentary, each addressing specific issues associated with the physical and chemical characteristics of E-liquids and ECIG-generated aerosols and how they potentially impact human health. Below is a brief description of the works presented in this E-book.Farsalinos and Gillman present a systematic review of 32 studies evaluating the production of carbonyl emissions from various ECIG devices. Since carbonyl emissions represent a significant health hazard, the authors emphasize the importance of using realistic vaping conditions in the determination of aerosolized carbonyl levels. In their mini review, Sosnowski and Odziomek, discuss the effects of inhalation patterns and particle size distribution of ECIG-generated aerosol as important factors to consider when assessing interactions of aerosols with the respiratory system. In the final review of this Research Topic, Kaur et al. evaluate the characteristics, composition and toxicological effects associated with tobacco and menthol/mint flavored E-liquids. Additionally, the flavor prevalence among ECIG users is reported.Cunningham et al. quantified 97 aerosol constituents, 84 smoke compounds, 19 flavor compounds and evaluated five newer generation ECIG devices. The authors performed comparative chemical analyses of ECIG vapor and cigarette smoke and concluded that vaping ECIGs offer significantly lower toxicant exposure than smoking cigarettes. Palazzolo et al. determined the presence of trace metals in E-Liquid, in ECIG-generated aerosol and in cigarette smoke. While the presence of all trace metals was comparable and extremely low for both E-Liquid and in its generated aerosol (much lower than in cigarette smoke), only nickel, a known carcinogen, was found to have a higher level in the aerosol as compared to E-liquid. This indicates that the ECIG device is the source of the nickel and raises questions as to the potential detriment of continued use of ECIG devices which contain nickel In another study, Palazzolo et al. investigated the effects of ECIG-generated aerosol on the mucociliary clearance of ex vivo bullfrog palates (Rana catesbiana). It was determined that the palates exposed to aerosol display a modest decrease in mucociliary clearance due to aerosol sedimentation on the surface of the palate. This is unlike palates exposed to cigarette smoke where the mucociliary clearance ceased entirely due to loss of cilia. Cobb et al. investigated the effects ECIG-generated aerosol in a nematode (Caenorhabditis elegans) as an assessment of stress-induced cellular damage in an intact whole organism. Expression of metallothionein, which served as an index of oxidative stress, was significantly increased after exposure to cigarette smoke but remained unaffected after exposure to unflavored ECIG-generated aerosol.Four of the original manuscripts directly compared ECIG-generated aerosol with conventional cigarette smoke. in vitro, in a variety of cell lines or in various colonies of oral commensal bacteria. Muthumalage et al. reported that two monocytic cell lines exhibited inflammatory and oxidative responses when exposed to common flavored E-liquid (without nicotine), thus highlighting the potential pulmonary toxicity and tissue damage these flavored E-liquids can induce. In another study, Lucus et al. exposed pulmonary fibroblasts to an E-liquid containing a mixture of flavors (with nicotine) and found the E-liquid to induce inflammation and senescence and hinder normal wound healing repair processes. In their brief report, Leigh and Goniewicz measured cytotoxicity of bronchial epithelial cells exposed to aerosols generated from cannabidiol and non-cannabidiol containing ECIGs (with and without flavor additives). Their findings show different flavors produced different cytotoxic effects and that ECIGs containing cannabidiol induced more cytotoxicity than non-cannabidiol ECIGs. Fischman et al. investigated the effects of flavored and unflavored E-liquids (with nicotine) and their aerosols on the growth of four common oral commensal streptococci. The results indicate that flavored E-liquids hinder the normal growth of these bacteria more than unflavored E-liquids. Since commensal streptococci are crucial to the development of a healthy dental plaque, any disruption in the growth of these microbes could lead to periodontal disease and a host of other health-related issues.The remaining four original manuscripts investigated the effects of E-liquids and/or ECIG-generated aerosols, with and without flavors and in the presence or absence of nicotine. These studies were all conducted Caruso et al. offer a critical assessment of the work presented by Muthumalage et al. (see description above). While the results of the assessed study (as they relate to the in vitro monocytic cell lines) are not in dispute, the translation of these results into clinically relevant scenarios is questioned. The authors of this commentary stress the use of realistic standardized methodology to adequately assess the impact ECIG-generated aerosols may have on human health under normal conditions.The studies contained within this Research Topic address a wide array of important topics concerning the physical characteristics and chemical composition of inhaled ECIG-generated aerosol, but, clearly, further investigation is required to completely unravel the physiological effects attributed to ECIG aerosol. Hopefully, the contributions to this Research Topic will stimulate further discussion and research linking the effects of inhaled aerosol with overall human health. Finally, an expression of heartfelt appreciation and gratitude must go to the authors, editors, and reviewers involved with this project for their dedication and the countless hours spent ensuring the successful completion of this Research Topic. Their diligent efforts have greatly improved the final product.DP conceived the Research Topic, recruited authors for article submissions and edited the Editorial.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Normal tissue’s morbidity continues to limit the increase in the therapeutic index in radiation therapy. This study explores the potential advantages of combining proton arc therapy and proton minibeam radiation therapy, which have already individually shown a significant normal tissue’s sparing. This alliance aims to integrate the benefits of those techniques in a single approach.(1) Background: Proton Arc Therapy and Proton Minibeam Radiation Therapy are two novel therapeutic approaches with the potential to lower the normal tissue complication probability, widening the therapeutic window for radioresistant tumors. While the benefits of both modalities have been individually evaluated, their combination and its potential advantages are being assessed in this proof-of-concept study for the first time. (2) Methods: Monte Carlo simulations were employed to evaluate the dose and LET distributions in brain tumor irradiations. (3) Results: a net reduction in the dose to normal tissues (up to 90%), and the preservation of the spatial fractionation of the dose were achieved for all configurations evaluated. Additionally, Proton Minibeam Arc Therapy (pMBAT) reduces the volumes exposed to high-dose and high-LET values at expense of increased low-dose and intermediate-LET values. (4) Conclusions: pMBAT enhances the individual benefits of proton minibeams while keeping those of conventional proton arc therapy. These results might facilitate the path towards patients’ treatments since lower peak doses in normal tissues would be needed than in the case of a single array of proton minibeams. In recent decades, radiation therapy (RT) has profited from numerous technological advances allowing a very high dose conformation to the tumor along with significant dose reduction to surrounding normal tissues. Examples include techniques such as Intensity Modulated Radiation Therapy (IMRT)  or VolumCharged particles, such as protons, further increase the tissue sparing-potential with respect to X-rays thanks to their more favorable depth dose deposition . DespiteTo diminish the side effects and achieve a high therapeutic index for current difficult-to-treat cases, new approaches have been proposed. This is the case of Proton Arc Therapy (PAT)  and ProtPAT is considered one of the future promising evolutions in proton therapy dose delivery . Proton Another approach to diminish normal tissue’s toxicity is proton minibeam radiation therapy (pMBRT) . pMBRT iThis work highlights the potential advantages of combining these two approaches, PAT and pMBRT, in order to improve the treatment of radioresistant tumors, as these techniques can be very complementary . This combined delivery method will be referred to as Proton Minibeam Arc Therapy (pMBAT) hereafter. In this work, the potential increase in normal tissue sparing of pMBAT while maintaining the characteristic pattern of peaks and valleys of pMBRT was evaluated. In addition, the impact of the several main parameters in the treatment planning process on the possible reduction in dose to normal tissues of pMBAT was assessed. To the best of our knowledge, this is the first evaluation of pMBAT.Dose distributions of all treatment cases were computed by means of Monte Carlo (MC) simulations. The simulation code TOPAS (TOolkit for Particle Simulation v3.5 based on Geant4.10.7) was employed . The penThe physics list, which defines the physical processes involved in the simulation , was buiThe calculations were performed using fully anonymized computer tomography images of a patient from the ICPO patient database see . All proWe compared three types of treatment plans: (i) a single-array pMBRT treatment; (ii) different pMBAT treatments, and (iii) a PAT plan. At the same average dose to the tumor, the reduction in normal tissue doses , and maintenance of the spatial modulation of the dose in the normal tissues were considered as figures of merit. To evaluate the possible dose reduction in pMBAT with respect to pMBRT and PAT, depth dose curves both in the peak and valley regions and dose volume histograms (DVH) were computed. To assess the preservation of the spatial fractionation, the peak-to-valley dose ratio (PVDR) in the pMBAT and pMBRT scenarios was also computed. Finally, LET distributions were studied to give an overview of the possibilities of biological optimization with these techniques.In order to evaluate the dosimetric parameters of our irradiation types, a virtual 2 cm-diameter planning target volume (PTV) was positioned in the centre of the patient’s brain, as in previous works ,29.The spot configuration of all the treatment plans presented hereafter was created by the ECLIPSE treatment planning system  using the Nonlinear Universal Proton Optimized algorithm (NUPO) (v.15.6.05) with pencil beam scanning algorithm and delivery.To simulate the single-array pMBRT irradiations, a 65 mm-thick multi-slit brass collimator, optimized for proton minibeam generation , was utiTo simulate the PAT treatments, an arc was made up of a discrete number of fields separated by a constant angle. The PAT plan was composed of up to 13 equally spaced fields forming a 180° arc around the parietal region of the patient’s head see .To create the pMBAT treatment, a collimator as previously described was added to the PAT plan detailed in the previous section. Thus, the pMBAT plan was composed of up to 13 equally spaced minibeam arrays. To preserve the spatial fractionation along all of the arc, the rotation of the gantry was carried out around the axis perpendicular to the slits. The influence of different parameters  distances and PTV size) on the pMBAT dose distributions was evaluated. In this section, the comparative evaluation of the doses deposited on both normal tissues and tumor by pMBRT, PAT and pMBAT, as well as on the influence of the different parameters on the performance of pMBAT, are reported. In addition, we present a comparison of the LET distributions between pMBRT and pMBAT. If not otherwise stated, the pMBAT calculations correspond to case 1 .d distributions of pMBRT and pMBAT treatments. pMBAT reduces the hot spots and the normal tissue volumes receiving high LET values at expenses of a higher volume receiving intermediate-LET values, as compared to pMBRT. Mean LETd values in the PTV and the normal tissue are similar in the three scenarios within their statistical uncertainty . To the best of our knowledge, this is the first evaluation of combining proton minibeams with PAT, a promising proton therapy technique.The potential for integrating PAT into the clinic is currently very high. Indeed, the first prototype of spot-scanning arc treatment (SPArc) delivery was performed on a clinical proton beam therapy machine . PAT haspMBRT is a novel experimental technique that has proven to significantly widen the therapeutic window for brain tumors in small animal experiments ,21,33. TIn this work, we showed that pMBAT further increases the individual benefits of PAT and pMBRT. pMBAT has proven to maintain the spatial fractionation of the dose in the normal tissues. Thereby, the normal tissue preservation of pMBRT is expected to add up to the benefits of dose reduction in PAT ,11,12,32pMBAT also results in lower valley doses as compared with PAT. This constitutes a potential advantage. In micro and minibeam radiation therapy, valley doses are considered to be the most relevant parameter and seem to have a proportional relation with normal tissue tolerances . MoreoveIn this proof-of-concept study, we also have shown that independently of the pMBAT plan configuration , the dose to normal tissues is reduced as compared to pMBRT. Further evaluations considering more complex geometries and tumor types are needed to assess in depth the benefits of pMBAT. Finally, pMBAT could be implemented using technologies and protocols similar to those already implemented at our institution for pre-clinical trials in pMBRT .This manuscript presents the proof-of-concept of a new treatment modality, called Proton Minibeam Arc Therapy (pMBAT). This study demonstrated that pMBAT not only maintains but significantly increases the individual benefits of pMBRT and PAT for normal tissue sparing. The same level of spatial modulation of the dose in normal tissues, as in single-array pMBRT irradiations, along with up to 90% reduction in both peak and valley doses may be achieved. pMBAT also reduces the high-dose and -LET normal tissue volumes as compared to pMBRT. These results can facilitate the translation of pMBRT to patients’ treatments by enabling with the use of lower peak doses than those used in the single array studies and further dose escalation in the tumor.


Schamberg disease is a type of pigmented purpuric dermatosis (PPD), which is a benign cutaneous capillaritis characterized by macules and patches most commonly found on the lower extremities. Rutoside and ascorbic acid have been shown in previous cases to be efficacious in the treatment of PPD lesions due to their free radical scavenging effect on capillaries. We present the case of a 19-year-old woman with Schamberg disease who achieved complete clearance of lesions within four months of daily rutoside and ascorbic acid treatment. The goal of this case report is to further demonstrate the effectiveness of this treatment and to call for investigation of its use as a standard of care in PPD. Schamberg disease, the most common type of pigmented purpuric dermatosis (PPD), is a capillaritis characterized by reddish-brown macules and patches, most commonly distributed on the lower legs, but may appear on other parts of the body -3. PPD uA 19-year-old woman presented with a two-week history of a progressive, asymptomatic rash on the bilateral legs, arms, and abdomen. Physical examination consisted of non-blanching erythematous and brown papules and macules that were most apparent on the lower extremities Figure .At the 1.5-month follow-up, the patient endorsed some improvement of her lesions with the 10-day taper of prednisone. However, her lesions quickly recurred soon after. At that time, she was initiated on oral ascorbic acid 500 mg twice daily and oral rutoside 50 mg twice daily. After three months of treatment, there was significant improvement in the patient’s lesions with complete lesion clearance at four months Figure .Few studies have tested the efficacy of rutoside and ascorbic acid in the treatment of PPD. A 1999 pilot study demonstrated that among three patients with variable duration of disease courses, full remission was achieved within four weeks of treatment, and remission was maintained at three months post-treatment . AnotherThe effectiveness of these treatments is related to both the hypothesized pathogenesis of PPD and the effect these agents have on cutaneous vasculature. PPD is thought to be due in part to the fragility of cutaneous blood vessels . A contrCurrent standard treatment for Schamberg disease includes topical steroids for those with pruritus, avoiding or discontinuing possible triggers , and the use of compression stockings for vessel support . HoweverThe lack of any known severe side effects of rutoside and ascorbic acid for the treatment of PPD further supports its transition to standard of care. Studies suggest a linear correlation between time to response to treatment and disease duration. Our patient achieved significant improvement after approximately 12 weeks of treatment. Continued research, including randomized, controlled, clinical trials, would be justified to further demonstrate the efficacy of this treatment regimen. Exploration of different doses can help optimize treatment for the fastest and most effective treatment of PPD.


Cancer treatment during nationwide lockdown due to the COVID-19 pandemic has posed several challenges in the delivery of cancer care and carries tremendous potential sequel of impoverishing the households. This study aims to examine the economic distress faced by breast cancer patients receiving treatment at Tata Memorial Center (TMC) Mumbai, India during the nationwide lockdown initiated in March 2020 following the outbreak of COVID-19. A total of 138 non-metastatic breast cancer patients who were accrued in this study at TMC before imposing of lockdown, and their treatment was impacted because of the COVID-19 outbreak, were interviewed. Telephonic interviews were conducted using a structured schedule which contained information on household and demographic characteristics of the patients, knowledge about COVID-19, their daily expenditure for treatment, difficulties faced during lockdown and how they met expenditures. Descriptive statistics and logistic regression were used in the analyses. The average monthly expenditure of cancer patients had increased by 32% during the COVID-19 period while the mean monthly household income was reduced by a quarter. More than two-thirds of the patients had no income during the lockdown. More than half of the patients met their expenditure by borrowing money, 30% of the patients used their savings, 28% got charity and 25% used household income. About 81% of the patients had reported shortage of money, 32% reported shortage of food and 28% reported shortage of medicine. The distress financing was significantly higher among patients receiving treatment in Mumbai compared to those receiving treatment at their native cities (67% vs. 46%), patients under 40 years of age, illiterate, currently married, Muslim and staying at a rented house. The incremental expenditure coupled with reduced or no income due to the closure of economic activities in the country imposed severe financial stress on breast cancer patients.  Cancer has become the leading cause of death among non-communicable diseases in at least half of the countries worldwide. Cancer accounted for 233.5 million Disability Adjusted Life Years (DALYs) in 2017 Among all cancer related DALYs 97% was attributed to Years of Life Lost (YLL) and 3% was attributed to Years of Live with Disability (YLD) . Of the 18.1 million cancers diagnosed globally in 2018, about 2.1 million were of breast cancer. Breast cancer is the leading type of cancer in 80% of the countries and the leading cause of cancer mortality in the majority of the countries .The incidence and mortality from cancer is increasing globally and is compounded by the population growth, population ageing and changing lifestyle . Besides, deteriorating health and psychological stress, cancer patients and their caregivers undergo economic distress and often catastrophic health spending due to the high cost of treatment and lack of financial protection . Access to affordable cancer care is the biggest challenge for developing economies like India . About 79% of Indian households face catastrophic health expenditure due to cancer and 46% of the expenses for cancer treatment is met through distress financing . Mean out-of-pocket payment (OOP) on hospitalization is highest for cancer and the cost of cancer inpatient care in a private facilities is at least three times higher than public facility . Among all types of cancer, breast cancer accounts for 14% of total cases with an age-standardized mortality rate of 61.4%. Breast cancer is the most common cancer in India accounting for 14% of new cases in both gender and 27.7% cases among females . It ranks first in cancer mortality accounting for 11.1% of all cancer deaths in contrast to the 6.6% global estimates . Since December 2019, the world has witnessed a massive outbreak of COVID-19 that has become a global pandemic in a span of three months. The disease was triggered by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated in Wuhan province of China. The fatality rate is very high for the elderly, people with co-morbidities, lung cancer, males and patients undergoing immunosuppressive chemotherapy for cancer treatment . The COVID-19 pandemic posed numerous challenges in cancer treatment as management of covid-19 gained priority over cancer care due to limited medical resources . The Asian National Cancer Centers Alliance (ANCCA) recently published the results of a survey conducted on the nuances of cancer care during COVID times within Asian countries and highlighted the role of various regional leadership strategies in safeguarding the health of staff and patients. . At the household level, the impact of COVID-19 is multilayered; loss of household income, temporary or permanent closure of business and loss of productivity .Patients with breast cancer receive multimodality treatment which comprises of breast surgery, systemic therapy in the form of chemotherapy, hormone therapy or targeted therapy and radiotherapy. This entails a prolonged duration of treatment which generally takes six months but can be delayed subject to the availability of facilities, financial background and waiting lists at public hospitals. The cancer treatment centers in India are very limited. Most of these centers are either located in metropolises or the capital city of the states thereby mandating patients to travel long distances for treatment. While cancer affects the rich and poor, the economic burden of cancer is very high for the poor and middle-class families. The recent COVID-19 pandemic has worsened the situation for patients suffering from cancer; the pandemic and the nationwide lockdown has now made them more vulnerable . Though studies have examined the impact of altered treatment protocols and severity of the disease among cancer patients, no attempt has been made to understand the economic hardship of cancer patients who are undergoing treatment during the COVID-19 pandemic. In this context, the main objective of this study is to examine the economic distress of breast cancer patients undergoing treatment at Tata Memorial Center, Mumbai during the COVID-19 pandemic and lockdown. Study populationThis study has been conducted by Tata Memorial Center (TMC) in collaboration with International Institute for Population Sciences (IIPS), Mumbai. A team of oncologists, health economists, statisticians, demographers and social workers designed and executed the study. This paper is based on 138 non-metastatic breast cancer patients who were accrued in this study at TMC before lockdown and continued their treatment during lockdown. A structured questionnaire was prepared and telephonic interviews were conducted. The questionnaire covered household, demographic and socio-economic characteristics including income and detailed record of the direct and indirect health expenditure of each visit to the hospital as well as inpatient care. This paper is derived from a project on economic impact of breast cancer patients that received approval from the institutional ethics committee and is registered on the Clinical Trial Registry of India (CTRI/2019/07/020142). All participants gave written informed consent for the study. Outcome variablesThe primary outcome variables of interest are expenditure and income in pre COVID-19 and during the COVID-19 period and the extent of distress financing. Patients were asked about their daily expenditure on food, of cancer patients undergoing treatment at TMC accommodation, medicine, transport and others along with household income. Daily expenditure on food was defined as the expenditure incurred by patients and the accompanying persons on food during the treatment at lockdown period; accommodation cost was defined as the daily cost of renting rooms for the patients who came from their native places; medicine cost contained expenditure at the hospital for surgery, chemotherapy, radiotherapy, consumable medicines, investigation cost, registration and admission charges; cost incurred to reach hospital from current address has been captured under transport cost. Monthly expenditure includes the expenditure of the patients and consumption the accompanying person(s) at the place of treatment and it does not include expenditure of other household members at their permanent residence. Pre COVID-19 and COVID-19 period were demarcated by the day of starting of nationwide lockdown (before 24th March 2020 as pre COVID-19 and 24th March onwards as COVID-19) due to the virus outbreak. A patient was said to be incurring distress financing if she reported borrowing money from their friends or relatives to meet treatment and other expenditures. Statistical analysisDescriptive statistics and logistic regression were used in the analyses. The distress financing variable has coded 1 if the patient met her expenditure through distress financing and 0 otherwise. The statistical analysis was done using STATA 13.Strategy to manage financial condition during the COVID-19 pandemic among the patients are shown in Since the third week of March 2020, India has witnessed a nationwide complete lockdown due to the outbreak of COVID-19. Breast cancer patients of TMC, Mumbai has faced a double burden of economic hardship during the pandemic; one is due to the high catastrophic expenditure associated with cancer treatment and the other is due to financial instability resulting from lockdown. The salient findings of the study are as follow: First, more than two-thirds of the patients at TMC had come from outside of the state and 68% of the patients had no income during the lockdown which triggered the vulnerability of the patients. Second, the monthly expenditure of the patients had increased by about one-third of the pre-pandemic expenditure. On the other hand, income had reduced by three-fourths. General patients had the highest increment of expenditure followed by non-chargeable patients. However, the expenditure of private patients had reduced. Third, the daily expenditure was met mainly by borrowing from friends or relatives. About 61% of the patients had borrowed money from friends and relatives. This was even larger for the patients with no schooling (76.4%) and patients belong to the second tertile (80%). Fourth, the likelihood of incurring distress financing was higher among general patients and patients who came from outside of the state. Fifth, more than half of the breast cancer patients reported that it was difficult to overcome the current situation of pandemic and almost all of them had fear of contracting the virus. Here we have some possible explanations for our findings. Most of the patients were from outside of the state, and this is one of the reasons for bearing a higher cost of daily expenditure on food, accommodation and transport. The daily wage and lack of job security in informal sectors resulted in a loss of income during the lockdown which was evident in 68% of the households with cancer patients in our study cohort. General patients had suffered more as they had to bear the cost of the treatment which was higher than their current ability to pay. They receive lesser subsidy than non-chargeable patients which resulted in higher expenses. Patients who cannot afford to pay rents while undergoing treatments at TMC, generally search for some religious places where they can stay by paying a minimum amount or sometimes the service is provided free. Despite this there was a sub-group which suffered more economic hardship and medicine accounted for the major share in their expenditure. The increment of the monthly expenditure was almost even across all subgroups but with some exceptions. For instance, the expenditure of private patients had decreased as most of them (19 patients out of 25) had been transferred to their native places for treatment. On the other hand, patients who stayed at religious places, their expenditure was lowest in pre COVID-19 period but during COVID-19 period, the expenditure had increased to just below the average monthly expenditure. This explains the doubling of expenditure and subsequently the economic hardship faced by those patients. The cost of transport accounted a significant increase in expenditure. As public transport was completely shut down, patients had to take cabs with higher rental prices than the pre COVID period. The increment in expenditure coupled with reduced or no income due to the closure of economic activities in the country had left needy patients with no options other than borrowing money from friends or relatives. The distress financing adds another burden to the patient’s family apart from higher out-of-pocket expenditure and zero income. India is one of the worst hit nations from the coronavirus and currently ranked second in total number of infected populations. Mumbai is among the worst hit metro cities accounts 4% of the total COVID-19 positive cases in the country. It has led to the modification of treatment protocols to balance the spread of COVID-19 among patients and health care workers and cancer cure. During the pandemic, accessing treatment facilities was dramatically affected mainly due to the travel restrictions and also due to the operational restrictions at treatment facilities. The importance of digital infrastructure in health care delivery has been felt significantly . Till March 2020, there was no law of providing digital consults to the patients but after the lockdown, the Indian Ministry of Health allowed to provide the full potential of technology in health care delivery . Telemedicine is one of the ways forward to the current shortage of health care delivery. For cancer patients, telemedicine can be one of the major preventive strategies to keep them safe and out of fear. Although this does not replace in-person visits, it is the most beneficial substitute amid the shutdown of public transport . Patients who were receiving treatment in their native cities were those patients who were provided teleconsultation to help them continue the treatment so that undue delay in treatment and its adverse impact is averted. India’s expenditure on health care is one of the lowest. Recently, the Government of India has introduced an ambitious health policy that will cover annual health care cost up to ₹ 500,000 per family. This is the “world’s largest health care initiative” that is expected to cover 500 million poorest in the country. However, following such economic hardship faced by households with cancer patients, especially in the time of the pandemic, there needs to be more clarity from policies to finance such high-cost disease. The policies need to prioritize the optimal treatment of cancer patients as well as protect the households from financial catastrophe. The findings of the study are based on a small sample size of 138 patients and may be difficult to generalize. However, important insights on the economic hardship of breast cancer patients during lockdown have come out from this study.COVID-19 outbreak around the world has impacted the health care delivery system badly. Cancer patients have suffered the most due to their higher cost of treatment and loss of household income resulting from complete lockdown. Policies should prioritize coverage of the treatment cost as well as safe guarding the livelihood. Providing cancer care through digital infrastructure could be one of the ways forward to the current situation.Authorship contributions TW and SKM conceptualized the study, research design, drafted and edited the manuscript. SS analyzed the data and drafted the manuscript. RW collected the data. PR and SK contributed to data analysis and statistical review. RS VP and SG critically reviewed the manuscript.