Low adoption of maize varieties bred to address the nutritional needs of the growing African population limits their impact. Aroma is essential in consumer preference, but has hitherto hardly been studied. We analysed the volatile organic compounds of flours and porridges of 22 maize varieties belonging to four nutritionally distinct groups, namely provitamin A maize, quality protein maize, yellow and white maize.m/z. Principal component analysis separated the varieties belonging to the four groups. With headspace solid‐phase microextraction gas chromatography–mass spectrometry (HS‐SPME GC–MS), 48 volatile compounds were identified in maize flour and 21 in maize porridge, including hexane, nonane, pentanoic acid, 1‐octen‐3‐ol, 1‐hexanol, hexanal, nonanal, 2‐pentylfuran and 2‐heptanone. Volatile compounds such as 1,2,4‐trimethyl benzene, associated with thermal degradation of carotenoids, increased in the porridge of yellow and provitamin A maize.Proton‐transfer‐reaction quadrupole ion time‐of‐flight mass spectrometry (PTR‐QiTOF‐MS) analysis generated 524 mass peaks ranging from 16.007 to 448.089 The results indicate that PTR‐QiTOF‐MS and HS‐SPME GC–MS combined with multivariate analysis are instrumental to study the volatile aroma compounds of different maize varieties. Several maize varieties have been bred to cater for the rising food demand  and nutritional deficiencies  in Africa.Volatile compounds of other cereals such as rice, wheat and recently millet have been widely studied.In the present study, PTR‐QiTOF‐MS was used for the first time on maize with the aim of identifying the volatile profile or fingerprint of different varieties and their porridges. We opted for porridges as these are the most common foods prepared from maize flour throughout Africa.Twenty‐two maize varieties were obtained from the International Institute of Tropical Agriculture (IITA), Nigeria, and the Centre de Recherches Agricoles, Benin (INRAB), Supporting Information, Table n‐hexane and pentane. All standards had purity higher than 99% and were purchased from Merck  and Actu‐All Chemicals .The following standards were used for identification of VOCs by GC–MS: C7‐C40 saturated alkanes , heptanoic acid, 2‐propanol, 2‐octanol, 1‐heptanol, acetaldehyde, limonene, 2‐mercaptoethanol, benzaldehyde, hexanal, 2‐butanol, ethanol, benzene, dimethyl sulfoxide, 1‐octanol, acetonitrile, 2‐propanol, + peak, m/z = 29.9974 and acetone, C3H7O+, m/z = 59.0497, to guarantee high mass accuracy throughout the analysis. The instrumental conditions for the proton transfer were: a drift voltage of 650 V, drift temperature of 60 °C, drift pressure of 3.80 mbar, and an E/N (electric field strength/particle density number) value of 120 Td (1 Td = 10−17 cm2 V−1 s−1). Sampling was at a flow rate of 50 mL min‐1. Every sample measurement started with flushing the PTR machine with ambient air of the bottle for 10 s as the blank. Then, the sample was measured for 40 s, followed by flushing for 10 s.Briefly, 3 g of maize sample in 250 mL glass bottle was agitated at 46 g for 30 min at 40 °C. The headspace of the sample was analysed by connecting the bottle to the inlet flow of the PTR‐QiTOF‐MS/MS 8000 instrument . The mass scale was calibrated using the peaks of recognized components, namely the NO−1 to 200 °C and then held at 200 °C for 5 min. The carrier gas was helium at a flow rate of 1 mL min−1.Samples were analysed using stabilwax DA capillary column (30 m × 0.25 mm ID × 0.25 μm) and SPME fibre assembly DVB/CAR/PDMS . Calibration of HS‐SPME GC–MS mass scale was regularly performed using perfluorotributylamine (PFTBA). Briefly, 2 g of the maize flour was put in a 10 mL glass vial, crimped, and incubated at 40 °C for 15 min. This was followed by 10 min of headspace absorption and another 10 min desorption in the GC. The oven temperature for SPME injection was 40 °C for 2 min, increased at 10 °C minThe raw PTR‐QiTOF‐MS data were processed using PTRwid.Chromeleon 7.2  was used to analyse the GC–MS data. The VOCs detected were identified by matching their mass peaks with the NIST spectral library database, the retention indexes according to literature and C7–C40 saturated alkanes retention index marker probe. When available, the MS identifications were confirmed by matching the GC retention times of the analytes with pure standards.post hoc test) were performed using IBM SPSS® software version 23 since the experimental groups had different sample sizes, unequal variances and the data were not normally distributed (Shapiro–Wilk test < 0.05).P < 0.05.Non‐parametric tests  served as a means of comparison between each sample and group. An example of the predominant mean mass peaks in the four groups is shown in Fig. m/z 33.030, 38.034, 51.044, 127.112 and 143.143 increased in all porridges. However, a compound having a mass of m/z 61.029 was lost in the porridge of all varieties, possibly due to high volatility, fast thermal degradation or hydrolysis in contact with hot water  generated 524 mass peaks in the range of es Table . The masm/z 54.034, 97.064, 98.068, 99.080, 100.044, 100.081, 112.047, 129.127 and 429.089. The yellow and PVA maize flours, which are closely related in terms of colour and carotenoid content, were shown to be significantly different in the measured mass, 84.185 and 256.780, respectively. A similar trend was observed in maize porridges wherein 43 masses significantly differentiated white maize and PVA maize flour  maize flours were significantly different Table . White mur Table . In contm/z 33.033, 42.034, 43.017, 45.033, 47.049, 49.011, 51.044, 59.050, 61.029 and 135.115. These masses, tentatively identified as methanol, acetonitrile, acetaldehyde, ethanol, methanethiol, acetone/propanal, acetic acid and terpene, respectively, have been associated with maize through conventional GC–MS analysis.et al.et al.As shown in Table m/z 33.033 and 51.044, which showed stability and a significant increase in all varieties except the QPM. The m/z 61.029 was abundant in maize flour but not present in the porridge. This compound could have been lost by thermal degradation and vaporization. Volatiles present in raw maize and below detection in cooked maize, are likely lost due to vaporization.m/z 49.011, methanethiol (otherwise known as methyl mercaptan), was generated during porridge preparation, possibly due to heat treatment and/or hydration processes. In combination with other VOCs, methanethiol is an important aroma contributor to cooked cereals, e.g. cooked rice.m/z 59.050 showed a significant difference  in the ten predominant masses in the four groups, while m/z 42.034 and 47.049 were significantly different in porridges at P‐values = 0.05 and 0.02, respectively (Table P < 0.05) but not dominant are shown in   Table . All sigversus PC2 are shown in Fig. The first two principal components (PCs) for maize flour explain 77.75% variance. All maize flour samples (except the PVA maize) are more spread out as compared to the maize porridge. The QPM varieties are located in between the other three groups, although the distribution is dispersed. Overlap is between the region of QPM and others, suggesting that the groups are more diverse in their volatile profiles. This is not strange because QPM varieties are usually developed from either the white or yellow maize. In fact, QPM P2) and (P4) located close to the yellow maize were identified as the yellowish 2000 EVDT Y STR QPM and 2009 TZE OR2 DT STR QPM, respectively The first two PCs for maize porridge explain 59.08% variance – much lower than for maize flour, see Fig. GC–MS is the conventional method for volatile analysis in food matrices due to its reliable compound identification and quantification. However, PTR‐MS equipment is rapid and sensitive but difficult for compound identification even with the advent of the new versions with TOF.et al.,et al.Figure et al.Comparing the four groups of maize, the release of volatiles was more prominent in variety P1 and A5, mainly caused by hexanal and 1,2,4‐trimethyl benzene (psi‐cumene), respectively. High concentrations of trimethyl benzene have been reported in barley, oat, rye and wheat.P > 0.05). Macku et al.The identified VOCs in the four maize groups  are shown in Tables et al.VOCs in the acid group are mainly responsible for cheesy, fatty, sour, vinegar, rancid, fruity and sweaty aroma.Alcohols are important contributors to the overall green, floral, fruity, grassy, and earthy aroma profile of maize.et al.−1 in water), signifying its important contribution to the overall aroma of maize. The proportion of hexanal was most prominent in PVA maize and QPM. Hexanal is commonly formed during cooking processes, thus the higher proportion in the porridge was to be expected. Hexanal can be generated by lipid breakdown (commonly oxidative degradation of linoleic acid) initiated by lipoxygenase.Aldehydes are very prominent in VOC composition of food and their flavour threshold level for human sensing is low, implying crucial contributions to aroma perception. Aldehydes mainly contribute green, grassy, soapy, citric and malty notes.Aromatic hydrocarbons (arene) and furans are interesting groups of VOCs in maize. In maize flour, the peak areas (%) were: white, 35.37 ± 4.67; yellow, 60.14 ± 37.56; QPM, 30.69 ± 8.4; PVA, 31.03 ± 9.8, see Fig. This is the first study on volatile compounds in maize using PTR‐QiTOF‐MS. Maize varieties from different groups were successfully grouped by PCA. With such sophisticated, highly sensitive and fast equipment, coupled with a statistical tool for multivariate analysis, the diversity in maize odour‐active compounds can be assessed as an input to improve sensory qualities of new varieties. HS‐SPME GC–MS was used to identify VOCs and this was also the first time the method was used on improved maize cultivars developed for the nutritional needs of the growing African population. The study identified differences in volatile composition of maize cultivars and their corresponding porridges. Results of this study can be the basis for further research of flavour threshold values and identification of the association between consumer perception and the inherent volatiles compounds. This will contribute to the understanding of consumer preferences for maize varieties in Africa and help breeders to build a data bank for volatiles that will enable the incorporation of aroma traits during variety selection and development. Breeding for aroma is a difficult task for maize breeders because aroma is yet to be properly understood and classified genetically, but our current research paves ways to generate information useful for further classification. Our results show that maize has a vast volatile variability that is still untapped: considering that aroma is a major contributor to taste and food crop acceptance, this research aspect requires further efforts. An investigation into methods to monitor off‐flavour during post‐harvest handling of the nutrient‐rich maize varieties is recommended. For instance, hexanal production is a good indicator of lipid oxidation and could be used to evaluate storage stability, especially in provitamin A biofortified maize.Table S1. Overview of the maize varieties (n = 22) used in this study.Click here for additional data file.Table S2. Supporting InformationClick here for additional data file.Table S3. Supporting InformationClick here for additional data file.


We present a patient with SARS‐CoV‐2 infection, with an unexpected presence of lymphocytosis. Examination of blood film revealed mature small lymphocytes associated with high percentage of smudge cells (63%). A peripheral flow cyometry evidenced a CD5 negative CLL. A high percentage of smudge cells is associated with CLL diagnosis and has an important prognostic value: better survival and prolonged time to first treatment. It is a useful index in developing countries with low access to molecular testing. During hospitalization lymphocytosis diminished to 6390/mm3, but persisted. In this scenario, a direct visualization of blood film was performed and small mature lymphocytes with scant cytoplasm were noted , CD23(high), CD200(high), and CD43(dim), and was negative for CD5, CD79b, and cell‐surface light chain expression. A diagnosis of CD5‐negative early‐stage CLL was made. Total immunoglobulins were in normal range and after 7 days of hospital care, the patient continued to recover.A 55‐year‐old man with a previous history of hypertension presented with myalgia, fever, dyspnea, and mild hypoxemia. A chest X‐ray evidenced a typical pattern of COVID‐19, and a positive PCR confirmed SARS‐CoV‐2 infection. Laboratory workup showed mild leukocytosis  suggested CLL with moderate specificity , 3, 4. I0% suggesarly CLL .


We aimed at quantifying the load of water, sodium and chloride due to different fluid indications in our pediatric intensive care unit (PICU). We were particularly interested in the role of fluid Critically ill children aged ≤3 years and invasively ventilated for ≥48 h between 2016 and 2019 in a single tertiary center PICU were retrospectively enrolled. Need for renal replacement therapy, plasmapheresis or parenteral nutrition constituted exclusion criteria. Quantity, quality and indication of fluids administered intravenously or enterally, urinary output and fluid balance were recorded for the first 48 h following intubation. Concentrations of sodium and chloride provided by the manufacturers were used to compute the electrolyte load.creep (34%) and maintenance (24%) fluids. Patients received 14.4 ± 4.8 mEq/kg/day of sodium and 13.6 ± 4.7 mEq/kg/day of chloride, respectively. The majority of sodium and chloride derived from fluid creep (56 and 58%). Daily fluid balance was 417 ± 221 ml (64 ± 30 ml/kg/day) and was associated with total sodium intake .Forty-three patients (median 7 months (IQR 3–15)) were enrolled. Patients received 1004 ± 284 ml of water daily (153 ± 36 ml/kg/day), mainly due to enteral (39%), creep is quantitatively the most relevant fluid in the PICU and future research efforts should address this topic in order to reduce the inadvertent water and electrolyte burden and improve the quality of care of critically ill children.Critically ill children are exposed, especially in the acute phase, to extremely high loads of water, sodium and chloride, possibly contributing to edema development. Fluid  Water is the main constituent of the human body. Indeed, 60–70% of the body weight of an adult is made of water and the percentage rises up to 75–80% when dealing with infants and young children –3. Due tIntravenous fluid therapy is therefore a cornerstone of pediatric critical care medicine and the prescription of intravenous fluids needs to be approached as any other pharmacological treatment, i.e., intravenous fluids have clear indications, contraindications and possible side effects . Classic1) Fluid resuscitation, i.e. rapid infusion of parenteral fluids in order to correct an acute intravascular fluid deficit ; 2) fluicreep [In addition, a substantial and frequently neglected water and electrolyte amount is administered to patients as a vehicle for intravenous drugs , to provide patency of indwelling vascular catheters and to flush venous lines after blood withdrawal or drug administration –13. Thiscreep , in analcreep .creep [Isotonic saline, i.e. NaCl 0.9%, which is constituted of 154 mEq of sodium and 154 mEq of chloride per Liter, is the classical fluid creep . Besidescreep –20, NaClcreep . Furthercreep . It is cThe aim of the present retrospective study is to describe the current clinical practice regarding fluid therapy in the pediatric intensive care unit (PICU) of a tertiary Italian referral hospital, quantify the load of water, sodium and chloride due to different fluid indications and assess the association between sodium intake and water balance.This retrospective, single center study was approved by the institutional review board of our hospital (decision number 502/2019). The need for informed consent was waived owing to the retrospective nature of the study.All patients admitted to the 5-bed tertiary PICU of the Fondazione IRCCS Ca′ Granda – Ospedale Maggiore Policlinico, Milan between January 2016 and the end of May 2019 were screened for eligibility. The inclusion criteria were age ≤ 3 years and ≥ 48 h of continuative invasive mechanical ventilation. Exclusion criteria included patients < 28 days, patients who received renal replacement therapy, plasmapheresis and parental nutrition. Patients were studied for 48 h starting from the time of intubation or PICU admission if the endotracheal tube was already in place.2), and ratio of arterial partial pressure of oxygen to FiO2 (P/F ratio).Clinical data were extracted from the patient data management system of our PICU . Demographic data included age, gender, body weight, height, presence and type of comorbidities. The cause of PICU admission was categorized in 4 classes: respiratory failure, sepsis/septic shock, neurological disease and post-operative. Several variables were extracted from the digital records in order to describe the severity of patients’ clinical condition. These included the use of vasopressors and/or inotropes , rescue respiratory strategies (high frequency oscillatory ventilation (HFOV), prone position) and worst values of the 48-h study period for positive end-expiratory pressure (or mean airway pressure in case of HFOV), fraction of inspired oxygen , to provide patency of indwelling vascular catheters and to flush venous lines after blood withdrawal or drug administration.According to the medical records, each fluid administered was assigned to a fluid indication : fluid rDaily forms included also urinary output and a simplified daily fluid balance, calculated by subtracting total urinary output from the total input of parenteral and enteral water. Finally, the percentage of water, sodium and chloride administered with each indication were computed.P-value lower than 0.05 was considered as statistically significant.All data were tested for homogeneity of variance and normality of distribution using the Shapiro-Wilk test. Normally distributed data were expressed as mean ± standard deviation, while non-normally distributed data were reported as median and interquartile range. Pearson’s correlation was used to assess the association between sodium intake and cumulative water balance. Analysis was performed with SAS 9.4  and Sigma Plot 12.0 . A Fifty-four patients fulfilled the inclusion criteria, 11 presented exclusion criteria, leaving 43 patients for the analysis  and fluid maintenance . The quantitative role of fluid boluses/fluid resuscitation was minor (1.7%) and quantitatively similar to blood components (1.5%).Acetated Ringer’s was the preferred choice for both fluid resuscitation 88 ± 33%) and fluid maintenance (88 ± 26%). The other employed intravenous fluid for these purposes was NaCl 0.9%, which was also the only type of fluid used for fluid 3% and flFluids administered as a vehicle for intravenous drugs constituted 76 ± 12% of fluid creep, while fluids administered to provide patency of catheters and for flushes constituted the remaining 24 ± 12% of fluid creep. Among intravenously administered drugs, sedatives and antibiotics where the two major sources of fluid creep .The daily dose of sodium was 97 ± 42 mEq (14.4 ± 4.8 mEq/kg/day). Fluid creep represented the major source of sodium , followed by maintenance fluids (32.8%), enteral feed (6.9%), fluid resuscitation (2.3%) and blood components (2.2%) (Table The daily dose of chloride was 92 ± 40 mEq (13.6 ± 4.7 mEq/kg/day), slightly lower than sodium. Fluid creep represented the major source of chloride , followed by maintenance fluids (29.9%), enteral feed (8%), fluid resuscitation (2.1%) and blood components (1.7%). Figure 2 = 0.49, p < 0.0001) with cumulative fluid balance.Patients had an average daily urinary output of 602 ± 242 ml, i.e. 92 ± 32 ml/kg per day. Given the total fluid input  the strong association between total sodium input and positive fluid balance.We studied a population of young (≤3 years), severely ill, mechanically ventilated children during the first 48 h of the acute phase. The main findings of our study are (i) the overall extremely high water, sodium and chloride load, (ii) the predominant role of fluid creep, accounting for 34% of water input, followed by fluid maintenance. As already pointed out by other authors [creep, it is not surprising that this category of fluids represented the major source of sodium  as NaCl 0.9% was used for this purpose.The total chloride load was slightly lower than sodium (13.6 ± 4.7 mEq/kg/day). The prevalent use of acetated Ringer’s as maintenance fluid explains this finding. Indeed, acetated Ringer’s has a sodium and chloride concentration of 132 and 110 mEq/L, respectively. Consequently, the chloride load deriving from this source is slightly lower than the corresponding sodium load. On the contrary, sodium and chloride load deriving from fluid creep in particular, might contribute to the development of hyperchloremia, with the related side effects [creep. When analyzing the two major components of fluid creep, we found that the majority (76%) was due to the dilution of intravenous drugs, while the remaining part (24%) was due to the use of fluids to guarantee catheters’ patency.The high chloride burden due to fluid therapy in general, and fluid  effects . Hyperch effects , 20, alt effects , 27, pot effects . Further effects , 30. Ind effects . This is effects . InteresThe cultural awareness regarding intravenous fluids is certainly increasing –35 and cIndeed, there is strong consensus regarding the tonicity of fluids for resuscitation and replacement, i.e., in this context isotonic, possibly balanced fluids should be preferred. On the contrary, there is a great debate regarding the appropriate tonicity of maintenance fluids –39. Manycreep. Indeed, these fluids have been neglected for a very long time and only recently, the research interest in the topic is increasing [creep can account up to 50% of daily parenteral fluid administration and a similar percentage of total daily sodium load in critically ill children admitted to the PICU, we can firmly state that they are conceptually as important as, and quantitatively even more important than resuscitation, replacement and maintenance fluids. Indeed, in a recent before-and-after study performed in a single center adult ICU, Bihari and colleagues demonstrated that the sodium burden and positive fluid balance deriving from fluid creep can be safely reduced by switching from an isotonic solution, such as NaCl 0.9%, to a hypotonic solution, such as 5% glucose [Finally, it is not surprising that, at the time of writing, no indication exists regarding fluid creasing , 43, 44. glucose . This imOther possible strategies to reduce the water, sodium and chloride burden of intravenous fluids would be to favor, whenever possible, the enteral route for drug administration; to concentrate as much as possible parenteral drugs; to review, on a daily basis, the indications of intravenous fluids, i.e. to adopt strategies of fluid stewardship  and to aThere were several limitations to our study. First, the study was retrospective in nature and data derived from only 43 patients of the same PICU. Consequently, the small number of patients hampers the generalizability of our findings. The extensive use of non-invasive ventilation in our PICU and the established tendency to intubate and ventilate invasively patients only as last resort, might in part explain the limited number of included patients. Second, we had no data on urinary sodium and chloride excretion. It was thus impossible to assess sodium and chloride balance. Third, we did not consider the sodium content of antibiotics, which can be significant . Finallycreep is quantitatively the most relevant fluid in the PICU and future research and clinical efforts should address this topic in order to improve the quality of care of critically ill children.In conclusion, our study described the clinical practice regarding fluid administration in critically ill, mechanically ventilated patients under 3 years of age, treated at our PICU. We had established protocols in our unit for drug dilution, not necessarily employing the maximal possible concentration. Furthermore, we did not have local protocols to reduce the inadvertent amount of fluids deriving from crystalloids used to guarantee the patency of catheters. As a result, our current clinical approaches and habits unequivocally lead to an inadvertent and excessive water, sodium and chloride load, which might contribute to the development of edema and significantly impact on patients’ outcomes. Fluid


Anti‐inflammatory and immune‐modulatory therapies have been proposed for the treatment of COVID‐19 and its most serious complications. Among others, the use of mesenchymal stromal cells (MSCs) is under investigation given their well‐documented anti‐inflammatory and immunomodulatory properties. However, some critical issues regarding the possibility that MSCs could be infected by the virus have been raised. Angiotensin‐converting enzyme 2 (ACE2) and type II transmembrane serine protease (TMPRSS2) are the main host cell factors for the severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2), entry, but so far it is unclear if human MSCs do or do not express these two proteins. To elucidate these important aspects, we evaluated if human MSCs from both fetal and adult tissues constitutively express ACE2 and TMPRSS2 and, most importantly, if they can be infected by SARS‐CoV‐2. We evaluated human MSCs derived from amnios, cord blood, cord tissue, adipose tissue, and bone marrow. ACE2 and TMPRSS2 were expressed by the SARS‐CoV‐2‐permissive human pulmonary Calu‐3 cell line but not by all the MSCs tested. MSCs were then exposed to SARS‐CoV‐2 wild strain without evidence of cytopathic effect. Moreover, we also excluded that the MSCs could be infected without showing lytic effects since their conditioned medium after SARS‐CoV‐2 exposure did not contain viral particles. Our data, demonstrating that MSCs derived from different human tissues are not permissive to SARS‐CoV‐2 infection, support the safety of MSCs as potential therapy for COVID‐19. SARS‐CoV‐2 enters into host cells through ACE2 and TMPRSS2. Mesenchymal stromal cells (MSCs) derived from amnios (A), cord blood (CB), cord tissue (CT), adipose tissue (AT) and bone marrow (BM) do not express these proteins, as demonstrated by RT‐qPCR, western blot, ELISA and immunofuorescence. They are not infected by either spike pseudovirus, or by SARS‐CoV‐2 wild strain. Human mesenchymal stromal cells (hMSCs) are currently under investigation for the treatment of COVID‐19. However, the potential safety profile of hMSCs in this context has never been defined since none has described if they express ACE2 and TMPRSS2, the main host cell factors for SARS‐CoV‐2 entry, and if they can be infected by SARS‐CoV‐2. This study provides the first evidence that ACE2 and TMPRSS2 are not expressed in hMSCs derived from both adult and fetal human tissues and, most importantly, that hMSCs are not permissive to SARS‐CoV‐2 infection. These results support the safety of MSCs as potential therapy for COVID‐19.1ClinicalTrials.gov. However, infusion of MSCs in the presence of active viraemia has raised some critical issues regarding the possibility that the virus may infect MSCs, causing not only lack of efficacy but also possible deleterious effects.In December 2019, an outbreak caused by a novel coronavirus, later named SARS‐CoV‐2, occurred in China and rapidly spread throughout several other countries, becoming pandemic.Angiotensin‐converting enzyme 2 (ACE2) is the main host cell receptor for SARS‐CoV‐2 entry, and the virus uses the host cell transmembrane serine protease II (TMPRSS2) for Spike envelope protein priming.Accordingly, the aim of the present work was to evaluate whether human MSCs from various sources express ACE2 and TMPRSS2 and, most importantly, if they are permissive to SARS‐CoV‐2 infection.2An expanded method section is available as 2.1www.lgcstandards-atcc.org).The MSC lines were previously isolated from amniotic membrane of human placenta, cord blood, cord tissue, bone marrow, and adipose tissue, expanded and characterized.2.2SARS‐CoV‐2 spike pseudotyped retroviral particles were produced by cotransfection of 293T cells (ThermoFisher) with these following three plasmids: a replication‐deficient retroviral vector FCQ pMM2‐eGFP expressing the green fluorescent protein (GFP)2.350/mL) of a previously titrated SARS‐CoV‐2 wild strain, isolated from an infected patient. The virus was incubated for 1 hour and then removed; the medium was changed every 3 days. Cells were scored every other day and for 1 week using a light microscope to detect the appearance of cell rounding, detachment, degeneration, and/or syncytium formation, called hereafter cytopathic effect (CPE). To verify if the cells tested can be infected and allow SARS‐CoV‐2 replication even in the absence of CPE, at day 7 from infection, supernatants from each MSC, Calu‐3, and VERO E6 culture were collected and inoculated into VERO E6. CPE occurrence was monitored for 1 week.MSCs, Calu‐3, and VERO E6 were infected with 100 μL (100 TCID2.4http://www.graphpad.com). P values less than .05 were considered statistically significant.All results are reported as mean ± SD and the data were analyzed with a one‐way or two‐way analysis of variance followed by Bonferroni all pair‐wise multiple comparison test using the InStat software , cord blood  or cord tissue , and human adult MSCs derived from bone marrow  or adipose tissue . The lung epithelial cell line Calu‐3, which expresses high levels of both ACE2 and TMPRSS2 and is permissive to SARS‐CoV‐2 infection and nonlytic replication,To substantiate the absence of ACE2 and TMPRSS2 in fetal and adult MSCs, we transduced both A‐MSCs and BM‐MSCs, as representative cell populations, with a replication‐defective, GFP‐tagged, pseudotyped retrovirus bearing the SARS‐CoV‐2 spike envelope protein. This pseudovirus does not go through a lytic replication and does not induce CPE, but it shares the same host cell factors for viral entry with the authentic SARS‐CoV‐2. As expected, Calu‐3 were infected by the spike‐pseudotyped virus and turned green, confirming that the assay properly worked (Figure To exclude that SARS‐CoV‐2 can infect MSCs through other host factors/receptors, we infected fetal and adult human MSCs of different origin with a SARS‐CoV‐2 wild strain under two different conditions: as adherent monolayer or cellular suspension Figure . All MSC4The recent emergence of the COVID‐19 pandemic and the absence of specific and validated therapeutic agents against this disease, prompted the search for new therapies able to hamper the strong immune reaction and the life‐threatening complications occurring in the most severe cases. The inflammatory nature of COVID‐19 points toward a solid rationale for the use of MSCs. Indeed, current understanding of MSC mechanisms of action is that most of their beneficial effects in repair from injury occur through secretion of cytoprotective, repair‐promoting, and immunoregulatory factors.Stem cells are generally resistant to viral agentsUsing a variety of assays, we unequivocally demonstrated that human MSCs do express neither ACE2 nor TMPRSS2. Most importantly, using a direct infection assay, our study provides the first evidence that human MSCs derived from fetal and adult tissues are not permissive to SARS‐CoV‐2 infection.5Our data demonstrating that MSCs derived from different human tissues are resistant to SARS‐CoV‐2 infection are important to support the use of MSCs as a possible useful tool to down‐modulate the immune hyper‐activation in COVID‐19 patients, and to contrast the pro‐fibrotic mechanisms that lead to the severe long‐term pulmonary sequelae increasingly observed in patients recovering from acute infection.F.B. declared consultant/advisory role with Humabs, Biotest, Shire, DiaSorin, MSD Qiagen; research funding from AB Analitica, NTP, Qiagen, Elitechgroup, and DiaSorin. The other authors declared no potential conflicts of interest.M.A.A.: conception and design, collection and assembly of data, data analysis and interpretation, manuscript writing, financial support, final approval of manuscript; M.M., E.P.: conception and design, collection and assembly of data, data analysis and interpretation, manuscript writing; F. Bastaroli, S.C., C.V., E.L., G.N.: collection and assembly of data, data analysis and interpretation; I.C., J.B., F. Baldanti, M.Z., P.C.: financial support and final approval of manuscript; M.G.: conception and design, financial support, data analysis and interpretation, manuscript writing, final approval of manuscript.AppendixS1. Supporting InformationClick here for additional data file.


We experienced two cases of dipeptidyl peptidase‐4 (DPP‐4) inhibitor‐associated bullous pemphigoid (BP) showing an unfavorable course despite its discontinuation. Clinicians should carefully monitor the course of DPP‐4 inhibitor‐associated BP even after withdrawal of DPP‐4 inhibitor therapy, especially in very elderly patients. We experienced two cases of dipeptidyl peptidase‐4 (DPP‐4) inhibitor‐associated bullous pemphigoid (BP) showing an unfavorable course despite its discontinuation. Clinicians should carefully monitor the course of DPP‐4 inhibitor‐associated BP even after withdrawal of DPP‐4 inhibitor therapy, especially in very elderly patients. Therefore, clinicians should pay close attention to the clinical course of DPP‐4 inhibitor‐associated BP, even after withdrawal of these drugs.Bullous pemphigoid (BP) is a bullous autoimmune skin disease that is characterized by autoantibodies targeting BP180 and BP230, which are two hemidesmosomal proteins localized at the epidermal‐dermal junction.However, we experienced two cases of BP associated with DPP‐4 inhibitor therapy showing unfavorable outcomes despite immediate discontinuation of the relevant drugs. Here, we report a total of three cases of DPP‐4 inhibitor‐associated BP in patients with type 2 diabetes, summarizing their characteristics and the clinical course of BP after discontinuation of DPP‐4 inhibitors. Patients provided informed consent for publication of these cases.2Case 1: An 82‐year‐old woman with a long history of type 2 diabetes started to take linagliptin (5 mg/d) in addition to the combination of basal insulin and a glinide. Nine months later, linagliptin was switched to teneligliptin (20 mg/d) at a different hospital. After a further six months, she presented with pruritic erythema on the trunk and limbs, followed by development of blisters on the left arm  and cyclosporine (150 mg/d) was initiated, while teneligliptin was discontinued because it was suspected to be the cause of BP. However, her skin lesions did not improve and serum anti‐BP 180 antibody increased to 10 000 U/mL on January 10, 2017. Intravenous steroid pulse therapy was commenced, as well as administration of intravenous immunoglobulin (IVIG) and plasmapheresis on several occasions. Subsequently, her skin lesions improved and anti‐BP180 antibody decreased to 109 U/mL on March 13, 2017. However, her symptoms showed repeated exacerbation after discharge from hospital. Therefore, the patient was readmitted and received intravenous steroid pulse therapy, IVIG, and plasmapheresis, but her skin lesions did not respond. After multiple courses of intravenous steroid pulse therapy followed by a high dose of oral glucocorticoid, HbA1c was increased to 8.4%. After that, she had a fall and developed confusion. Emergency head computed tomography revealed new bleeding into an existing chronic subdural hematoma Figure . The patCase 2: An 89‐year‐old woman with long‐standing type 2 diabetes started treatment with sitagliptin (50 mg/d), which was switched to vildagliptin (100 mg/d) at a different hospital. Three years after initiation of vildagliptin therapy, she presented with erythema and small tense blisters on her limbs and trunks. She visited a local dermatology clinic and was referred to the department of dermatology at our university hospital. On examination, she had tense bullae and erythema on her chest and limbs Figure , along wCase 3: A 67‐year‐old man with type 2 diabetes commenced treatment with alogliptin (12.5 mg/d). The dose of alogliptin was subsequently increased to 25 mg/d and metformin (500 mg/d) was added. After 3.5 years, he developed generalized blisters on his skin and intraorally. He presented to the department of dermatology at our university hospital. On examination, several areas of edematous erythema without blistering were found on his thigh and in the oral cavity Figure . Histolo3BP is an autoimmune disease that causes bullae, erosions, and erythema on the skin and mucosal surfaces. It is characterized by autoantibodies targeting hemidesmosomal proteins BP180 and BP230 involved in adhesion at the epidermal‐dermal junction.We experienced 3 patients with type 2 diabetes who presented BP after treatment with DPP‐4 inhibitors. We confirmed our three cases developed BP as an adverse effect of DPP‐4 inhibitor based on Naranjo scale . However, it cannot be denied that amlodipine may be associated with development of BP in Case 1 and 2, because amlodipine is known to be a risk of drug‐induced BP.Izumi et al reported that DPP‐4 inhibitor‐associated BP featured less prominent erythema clinically and showed little evidence of histological inflammation with scanty infiltration of eosinophils into the skin, suggesting it was an atypical form of noninflammatory BP.Benzaquen et al reported that discontinuation of DPP‐4 inhibitor therapy had a favorable impact on the outcome of BP in 19 patients with diabetes, because 95% of them achieved clinical remission after stopping DPP‐4 inhibitors and receiving first‐line treatment for BP.In Case 1, skin lesions showed multiple relapses despite discontinuation of DPP‐4 inhibitor therapy and initiation of treatment for BP. She received intravenous steroid pulse therapy, IVIG, and plasmapheresis in hospital on several occasions. Eventually, she died after a fall, probably from cerebral herniation associated with a subdural hematoma. In Case 2, symptoms of BP were improved by treatment with oral prednisolone and cyclosporine, but the patient died after deterioration of her general condition. She may have died of lung metastasis from primary colon cancer, although the possibility that opportunistic pulmonary infection was associated with her death cannot be excluded. It was recently reported that control of BP and relapse of this condition did not differ between patients who stopped or continued treatment with DPP‐4 inhibitors.The mechanisms responsible for BP associated with DPP‐4 inhibitor therapy remain to be determined. DPP‐4 (CD26) is highly expressed by T cells, especially CD4+ T cells. It is possible that inhibition of DPP‐4 may be associated with development of autoimmune skin diseases, because autoreactive T cells are involved in the pathogenesis of BP.In conclusion, we experienced 3 patients with type 2 diabetes who developed DPP‐4 inhibitor‐associated BP. Despite prompt discontinuation of DPP‐4 inhibitor therapy and initiation of first‐line treatment for BP, the outcome was unfavorable in two patients. Accordingly, clinicians should carefully monitor the course of DPP‐4 inhibitor‐associated BP even after withdrawal of DPP‐4 inhibitor therapy, especially in very elderly patients.None declared.YS: treated the patient and drafted the manuscript. TI: wrote the manuscript. EO, SS, and SH: treated the patients. TJ, IU, and KI: reviewed the manuscript. YA: wrote the manuscript. All authors read and approved the final manuscript.


Identifying individuals at risk of developing Parkinson's disease (PD) is critical to define target populations for future neuroprotective trials.The objective of this study was to apply the PREDICT‐PD algorithm of risk indicators for PD in a prospective community‐based study (the Bruneck study), representative of the general elderly population.PREDICT‐PD risk scores were calculated based on risk factor assessments obtained at baseline . Cases of incident PD were identified at 5‐year and 10‐year follow‐ups. Participants with PD or secondary parkinsonism at baseline were excluded (n = 35). We analyzed the association of log‐transformed risk scores with the presence of well‐established markers as surrogates for PD risk at baseline and with incident PD at follow‐up.P = 0.001) after 5 years and of 1.95  after 10 years of follow‐up per doubling of risk scores. In addition, higher PREDICT‐PD scores were significantly correlated with established PD risk markers  and significantly associated with higher probability for prodromal PD according to the Movement Disorder Society research criteria at baseline.A total of 20 participants with incident PD were identified during follow‐up (11 after 5 years and 9 after 10 years). Baseline PREDICT‐PD risk scores were associated with incident PD with odds ratios of 2.09 (95% confidence interval, 1.35–3.25; Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.The PREDICT‐PD score was associated with an increased risk for incident PD in our sample and may represent a useful first screening step in future algorithms aiming to identify cases of prodromal PD. © 2020 The Authors.  The diagnosis of Parkinson's disease (PD) is preceded by a prodromal phaseA number of risk factors and prodromal symptoms of PD have been identified,The PREDICT‐PD study algorithm is based on a comprehensive meta‐analysis of early nonmotor features and risk factors.The simple, questionnaire‐based approach of the PREDICT‐PD algorithm would make an attractive tool for future population‐based risk screening, Therefore, we assessed the association of the PREDICT‐PD algorithm with incident PD in the longitudinal Bruneck study cohort, a sample of the general elderly population, during an overall follow‐up period of 10 years.Assessments were carried out in the Bruneck study, a prospective population‐based study on cardiovascular and neurological diseases initiated in 1990.In 2005, 574 participants (aged 55–94 years) underwent a standardized interview and neurological examination including the Unified PD Rating Scale motor section (UPDRS Part III). Medical history, medication, and family history with a focus on movement disorders and possible causes for secondary parkinsonism were recorded. Assessments were performed by 2 neurologists with special expertise in the field of movement disorders.Follow‐up examinations took place in 2010 after a median of 5.0 years  and in 2016 after a median of 10.4 years . Assessments followed a similar protocol as in 2005 and were performed by 2 neurologists blinded to baseline risk markers. Incident PD cases were identified as per UK PD Society Brain Bank criteria.For a detailed flowchart of the study population including deceased participants and differences of participants according to follow‐up status, see Supplementary Figure Following factors for the calculation of the PREDICT‐PD algorithm were available: age, sex, smoking status, coffee use, hypertension, use of nonsteroidal anti‐inflammatory drugs, calcium channel blockers, beta blockers, alcohol consumption, constipation, depression and/or anxiety, known history of head injury, and a first‐degree relative with history of PD Table . ApplicaThe following established risk markers A detailed description of the ascertainment of all markers and respective cut‐offs is available in the Supplementary Methods.U test. Significance levels for binary data were assessed with the chi‐square test. Cross‐sectional correlation analysis between log2‐transformed risk scores (expressed as odds) and established PD risk markers at baseline was performed using the Spearman rank test. The predictive value of the risk scores for cases of incident PD at follow‐up was examined using binary logistic regression analysis for the PREDICT‐PD log odds, and the results are given in odds ratios (ORs) and 95% CIs. Log2‐transformation was used following the example of the original PREDICT‐PD cohort in order to render results comparable and allow better interpretation of risk estimates. Statistical analysis was performed using SPSS version 24 for Windows . The significance level was set at a 2‐sided P value of ≤0.05.As nonnormal distributions for continuous quantitative variables were shown throughout, group comparisons were performed with the Mann‐Whitney rs = −0.186, P < 0.001), RBD Screening Questionnaire scores , and UPDRS Part III scores   after 5 years and of 1.95  after 10 years of follow‐up per the doubling of risk scores. The results remained significant even when using risk scores without age and sex , a direct comparison of HRs is difficult.In this study, we applied the PREDICT‐PD algorithm, a simple questionnaire‐based screening tool aiming to identify participants with increased PD risk in a longitudinal sample of the general elderly population. The PREDICT‐PD study first employed the algorithm in an online cohort with follow‐ups for future PD diagnosis over 3 years, where it predicted incident PD with a HR of 4.39 and correlated with established markers of PD.In our sample, we found a significant association of higher risk scores at baseline with a future diagnosis of PD with an OR of 2.09 after 5 and 1.95 after 10 years of follow‐up. These results survived even after omitting age and sex from the score, which is encouraging in light of the ambiguous results in the Rotterdam study. In addition, risk scores significantly correlated with established PD risk markers  and were associated with higher posttest probability for prodromal PD as per MDS research criteria at baseline. It should be noted that our data do not allow calculation of HR, as the exact time of conversion was unknown because of the 5‐year follow‐up intervals. However, OR and HR can be comparable at a low incidence rate,Distribution of the various risk markers and early nonmotor features as well as age and sex were mostly comparable with the original cohort studied by Noyce and colleagues.An interesting detail concerns the prediction differences for converters identified after the first as compared with the second 5‐year interval. The OR for this second group was slightly lower at 1.50 and not statistically significant. This observation could point to a declining predictive accuracy of the model over time and is in line with the fact that different prodromal nonmotor and motor manifestations occur at different time intervals prior to the onset of motor symptoms.The PREDICT‐PD score was developed as an online tool only including items that can be assessed remotely and therefore does not require in‐person examinations. It did not include the established and stronger “intermediate” markers shown to clearly associate to a substantially increased PD riskOur study has limitations. The small incidence of case numbers leads to wide confidence intervals and may also contribute to differences observed in risk estimates of the first versus the second 5‐year follow‐up interval. Despite the fact that established criteria for a PD diagnosis were applied by movement disorders specialists, misdiagnosis cannot be excluded. The long follow‐up of 10 years in an unselected population‐based sample represents a strength of our study as does the in‐person assessments by movement disorder specialists blinded to the baseline results, adding to the validity of this analysis. Although our results support the usefulness of the PREDICT‐PD algorithm as a possible screening tool for prodromal PD, large (online) studies will be needed to finally determine its value.(1) Research Project: A. Conception, B. Designing the Bruneck Study, C. Obtaining Funding, D. Organization, E. Acquisition of Data; (2) Statistical Analysis: A. Design, B. Execution, C. Interpretation; (3) Manuscript: A. Drafting of the Manuscript, B. Revisions.K.M.: 2A, 2B, 2C, 3A, 3BP.M.: 1A, 1B, 1C, 1D, 1E, 2A, 2C, 3A, 3BF.T.: 2C, 3BH.S.: 1E, 3BA.G.: 1B, 1E, 3BA.D.: 1E, 3BP.W.: 2C, 3BS.K.: 1B, 1C, 1D, 1E, 2C, 3BJ.W.: 1B, 1C, 1D, 1E, 3BG.R.: 1E, 3BA.J.N.: 1A, 2C, 3BA.S.: 1A, 2C, 3BW.P.: 1A, 1C, 2C, 3BK.S.: 1A, 1B, 1E, 2A, 2C, 3BA.J.N. reports a salary from Barts Health NHS Trust and from the Barts Charity to support the Preventive Neurology Unit at the Wolfson Institute of Preventive Medicine, QMUL; grants from Parkinson's UK, the Leonard Wolfson Experimental Neurology Centre, the UCL Movement Disorders Centre, and the Virginia Kieley Benefaction; and honoraria/consultancy fees from Britannia Pharmaceuticals, Global Kinetics Corporation, Profile Pharmaceuticals, Bial Pharmaceuticals, Biogen, and F. Hoffmann‐La Roche. A.S. reports research funding or support from University College London, National Institute of Health, National Institute for Health Research ULCH Biomedical Research Centre, the International Parkinson and Movement Disorder Society, the European Commission, Parkinson's UK, Royal Free Hospital charity, GE Healthcare, and the Economic and Social Research Council; honoraria for consultancy from Biogen, Roche, Bial, GE Healthcare; license fee payments from the University College London for the MSA‐QoL, PSP‐QoL, and PQolCarers; and royalties from Oxford University Press. K.S. reports grants from Oesterreichische Nationalbank, FWF Austrian Science Fund, Michael J, Fox Foundation, and International Parkinson and Movement Disorders Society and consultancy and lecture fees from Boehringer‐Ingelheim, UCB, Lundbeck, AOP Orphan Pharmaceuticals AG, Roche, and Teva. W.P. reports consultancy and lecture fees in relation to clinical drug programs from AbbVie, AstraZeneca, BIAL, Biogen, Cynapsus, Britannia, Grünenthal, Intec, Ipsen, Lundbeck, Merz Pharmaceuticals, Novartis, Neuroderm, Orion Pharma, Prexton, Teva, UCB, and Zambon and royalties from Thieme, Wiley Blackwell, Oxford University Press, and Cambridge University Press. All other authors have nothing to report.AppendixS1: Supporting InformationClick here for additional data file.


Healthy aging is associated with changes in cognitive performance and functional brain organization. In fact, cross‐sectional studies imply lower modularity and significant heterogeneity in modular architecture across older subjects. Here, we used a longitudinal dataset consisting of four occasions of resting‐state‐fMRI and cognitive testing (spanning 4 years) in 150 healthy older adults. We applied a graph‐theoretic analysis to investigate the time‐evolving modular structure of the whole‐brain network, by maximizing the multilayer modularity across four time points. Global flexibility, which reflects the tendency of brain nodes to switch between modules across time, was significantly higher in healthy elderly than in a temporal null model. Further, global flexibility, as well as network‐specific flexibility of the default mode, frontoparietal control, and somatomotor networks, were significantly associated with age at baseline. These results indicate that older age is related to higher variability in modular organization. The temporal metrics were not associated with simultaneous changes in processing speed or learning performance in the context of memory encoding. Finally, this approach provides global indices for longitudinal change across a given time span and it may contribute to uncovering patterns of modular variability in healthy and clinical aging populations. In this research paper, we used a longitudinal dataset consisting of four occasions of resting‐state‐fMRI and cognitive testing (spanning 4 years) in 150 healthy older adults. We applied a graph‐theoretic analysis to investigate the time‐evolving modular structure of the whole‐brain network, by maximizing the multilayer modularity across four time points. Network flexibility, which reflects the tendency of brain nodes to switch between modules across time, was significantly higher in older adults than in a null model and with increasing age, indicating that older age is related to increased variability in modular organization. PreviouImportantly, the architecture of these subnetworks has been shown to undergo important developmental and aging‐related changes  decreases while, between‐network connectivity  increases, resulting in less modular, “dedifferentiated” brains in older age  processing speed and (b) learning performance in the context of memory encoding. These two cognitive domains were chosen as they have been found to be particularly vulnerable to aging effects . At each measurement occasion, participants completed an extensive battery of neuropsychological and psychometric cognitive tests and underwent brain imaging. The brain imaging session was conducted in close temporal proximity to the behavioral assessments . Inclusion criteria for study participation at baseline were age ≥64, right‐handedness, fluent German language proficiency, a score of ≥26 on the Mini Mental State Examination  data were taken from the Longitudinal Healthy Aging Brain Database Project —an ongoing project conducted at the University of Zurich , of which 86.7%  had complete data for rs‐fMRI.For the present analysis, we only included participants with complete rs‐fMRI data (four measurement occasions). This was necessary because four temporal windows enable a more reliable maximization of the multilayer modularity function. At 4‐year follow‐up, the dataset still comprised 74.6% of the baseline sample  with respect to baseline and averaged across subtests to calculate the domain‐average composite scores.All participants completed a neuropsychological test battery assessing multiple cognitive domains at each measurement occasion. For the present analysis, data from the domains “processing speed” and “learning/memory encoding” were used. Individual scores were standardized to T scores (Processing speed was assessed using four psychometric paper‐pencil tests: (a) the number of correct responses across two test parts of the Identical Pictures Test  number of correctly reproduced abstract designs at first five trials of the DCS figural memory test . Two hundred and twenty‐five multislice T2*‐weighted volumes were retrieved with a gradient echo‐planar sequence using transverse slice orientation .MRI scans were acquired at the University Hospital of Zurich on a Philips Ingenia 3T scanner . T1‐weighted (T1w) structural images were acquired using a gradient echo sequence  , used to build the network, were selected from the atlas of Schaefer and colleagues  defined as the kil × kjl/2ml, where m is the average edge weight in the matrix, gil gives the community assignment of node i in layer l, and gjr gives the community assignment of node j in layer r. The γ is the structural resolution parameter which defines the weight of intralayer connections and thus the number of obtained modules, while ω is the temporal resolution parameter which sets the weight of the interlayer edges that link each node i to itself across layers. When the value of γ is small, the maximization of Q produces relatively large communities, while large values result in more communities with smaller number of nodes. Given that the value of ω defines the consistency of multilayer modules, large values relative to intralayer edges result in communities that are more similar to one another across layers. We set these parameters to frequently used default values of γ = 1, ω = 1 .Thus, to investigate the changes in network organization across time, the multilayer modularity was optimized  structure, we calculated the node promiscuity  communities, we calculated the Node cohesion strength and node disjointedness quantify the node changes based on mutual versus independent changes, respectively .The calculation of global flexibility, cohesion strength, and disjointedness was implemented with code from the Network Community Toolbox . Hence, we ensure that the community structure we calculate is not random but instead captures the modular organization of functional connectivity. This null model, similar to the configuration model for static graphs, was constructed by randomly rewiring edges occurring at the same point .Further, we computed a Therefore, we computed 50 null models  for each subject's multilayer functional matrix and then optimized the multilayer modularity quality function 100 times on each of these null model networks.t test implemented in R .The real networks were compared to null networks using Welch's two‐sample p‐values was adjusted to p < .05/n, where n represents the number of multilayer measures that were compared between the observed and null networks.The significance level of index of effect size using an R‐based package lsr (v. 0.5), and interpreted it as follows: d ≥ 0.2 was considered a “small” effect size, d ≥ 0.5 represented a “medium” effect size and d ≥ 0.8 a “large” effect size , in which the outcome was a particular multilayer measure and the predictor was age at baseline (grand‐mean‐centered variable). Gender  and education  were entered as nuisance covariates into the model, as previous studies have related these variables to brain's functional network organization  multilayer measures .η2) were calculated using the lmSupport package (v. 2.9.13) in R (v. 3.5.2). The significance level of p‐values was adjusted to p < .05/n, where n represent the number of models tested.The effect sizes . In addition, partial correlation analysis was conducted to test the relationship between these metrics while controlling for the effects of age at baseline using the ppcor (v. 1.1) package in R.In addition, to investigate the relationship between the metrics, Pearson's correlation analysis was used to calculate the association between the modularity index (Q), global recruitment, and global flexibility. The analysis was performed using an R‐based package called sjPlot (v. 2.6.1) and ggplot (v. 2‐3.0.0) packages in R.The results were visualized using 2.9.2lme4 package (v.1.1‐18‐1) in R (v. 3.5.2); Bates, Mächler, Bolker, & Walker, We performed linear mixed effects (LME) analysis  in R (v. 3.5.2); Kuznetsova, Brockhoff, & Christensen, p‐values was adjusted to .05/n, where n represents the number of cognitive domains.Linear mixed models were fit by maximum likelihood and the p‐values were obtained from the t‐statistic using Satterthwaites's approximation to the denominator degrees of freedom (ggplot (v. 2‐3.0.0) package in R.The results were visualized using the 2.9.3psycho (v. 0.4.0.)) between the individual rate of change in cognition and the multilayer measures  which summarize network properties across time. In addition, partial correlation analysis was done to test the brain‐cognition relationship while controlling for the effects of age at baseline using the ppcor (v. 1.1) package in R.To investigate the “change–change” brain‐cognition association, we performed Pearson's correlation analysis (R‐based package ggplot (v. 2‐3.0.0) package in R.The individual rate of change in cognitive performance, defined as the subject‐specific slope of the regression line between time and the cognitive scores, was derived from the LME models described in the previous section  = 71.5, p < .0001, d = 8.26)  = 59.2, p < .0001, d = 6.84), and global promiscuity (t(298) = 69.6, p < .0001, d = 8.04), were significantly higher than in the temporal null model suggesting that the functional brain displayed more change than expected in a temporal null network  = 52.7, p < .0001, d = 6.09) was significantly higher than in the temporal null model, suggesting that the observed functional networks had a greater range of community dynamics in comparison to the null network  = −17.7, p < .0001, d = 2.05) was significantly lower than in the null model, suggesting that the change in community structure was driven by subgroups of nodes switching communities (indicated by a higher cohesion strength) instead of individual nodes switching independently of other nodes .All statistically significant effects survived multiple comparison corrections  = −.64, 95% CI , p < .0001), implying that more segregated networks are also more resistant to change, and thus exhibit lower variability across a given time span  = −.64, 95% CI , p < .0001), suggesting that flexibility is related to nodes not being consistently assigned to the same module across time  = −.62, 95% CI , p < .0001), and recruitment and flexibility (r(148) = −.63, 95% CI , p < .0001) remained significant after controlling for age at baseline.In addition, partial correlation analysis was conducted to test the relationship between modularity, recruitment and flexibility while controlling for the effects of age at baseline. The association between modularity and flexibility , suggesting that there were no age differences in the number of networks the nodes switch between  or disjointedness  and age at baseline, implying that the extent of mutual or independent changes in community structure , was not linked to age at baseline.We did not observe any significant association between the global cohesion strength , suggesting a lower probability of a given region to be grouped in the same community as other regions of its own community across time in older age .Importantly, the associations between age at baseline and flexibility survived multiple comparison correction  can be found in Supplementary Figure ω (interlayer coupling parameter). Higher values of ω increase the similarity of layers across time thus reducing variance in temporal modular structure uniformly across subjects. However, it is also possible that age‐related flexibility changes manifest scale‐specific patterns, as suggested elsewhere  calculated with other values of multilayer parameters ; FPCN ; and SM  was higher with older age, suggesting that older subjects have higher flexibility in these networks .Of all of the tested models, only the association between age and DMN flexibility survived multiple comparison correction  with older age  and SM  was lower with higher age .All statistically significant effects survived multiple comparison corrections  and learning/memory encoding . Older age was associated with lower performance in both domains , suggesting that older participants had a more significant decline in processing speed across the 4‐year time interval.First, we performed LME analysis to investigate longitudinal change in cognitive functioning . In addition, there was a significant retest effect on processing speed , but not on learning/memory encoding .Also, participants with better education had higher scores in learning/memory encoding (p < .05 corrected for two domains).All statistically significant effects (except the interaction effect on processing speed) survived multiple comparison corrections (r(148) = −.03, 95% CI , p = .74). This was also true for the association between learning/memory encoding and global flexibility (r(146) = −.008, 95% CI , p = .92).Next, we conducted Pearson's correlation analysis to assess the association between flexibility and change in cognitive performance. We did not find a significant relationship between change in processing speed and global flexibility  and change in processing speed or learning/memory encoding .4In the present study, we investigated the temporal change of the brain's modular structure in healthy aging. We applied the multilayer model, which resulted in several measures summarizing the characteristics of longitudinal network reconfiguration in healthy elderly.We showed significantly higher variability and a greater range of modular “dynamics” over the course of 4 years in older subjects' functional networks in comparison to temporal null networks. Further, flexibility was significantly associated with age at baseline, with older participants having higher global and network‐specific flexibility, particularly evident in the FPCN, DMN, and SVAN.We also observed a decrease in the global network recruitment with older age, indicating community structure reorganization in which some brain regions are inconsistently assigned to their modules across different time points. This was most evident for the DMN which had lower time‐dependent self‐recruitment in older participants.Over the same 4‐year time interval, we observed a significant decrease in processing speed and learning/memory encoding , we explored changes in the functional segregation of resting state networks across time  in order to maximize the overall number of temporal layers. Selective exclusion of subjects with incomplete data might introduce some bias into this type of analysis, although there was no selective attrition in our sample. As a consequence, the future research should explore different strategies for handling missing data in the context of multilayer modularity.Finally, although multilayer metrics present a convenient method for summarizing change information across time points, this “summarization” might also obscure different rates of change existing between specific time windows, which could be more easily explored within a different statistical framework.5This study, for the first time, illustrates substantial functional network reconfiguration in healthy aging across a 4‐year time interval. In particular, the whole brain network flexibility, which reflects the tendency of brain nodes to switch between modules was significantly higher in healthy elderly than in a temporal null model and with increasing age. The modular temporal variability was not related to simultaneous changes in cognitive performance, however, further studies should include more cognitive domains or investigate lagged changes to better understand the temporal implication of the multilayer modular reconfiguration. Finally, this approach provides simple intuitive indices for overall longitudinal changes across a desired time span and it can be useful for uncovering patterns of modular variability in healthy and clinical aging populations.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.Susan Mérillat, Franziskus Liem, and Lutz Jäncke contributed to the design, set‐up, maintenance, and support of the Longitudinal Healthy Aging Brain (LHAB) database. Brigitta Malagurski performed the data analysis and wrote the first draft of the manuscript. All authors discussed the results, contributed to manuscript revision, read, and approved the submitted version.AppendixS1 Supporting Information.Click here for additional data file.


LPS induced significant changes in the expression of 2844 genes, affecting 179 pathways related to mitochondrial dysfunction, defective oxidative phosphorylation, nitric oxide (NO) and reactive oxygen species (ROS) accumulation, nuclear factor, erythroid 2 like 2 (Nrf2), Toll‐like receptors (TLRs), and tumor necrosis factor α receptor (TNFR)‐mediated processes in wild‐type mice. The disruption of CypD reduced LPS‐induced alterations in gene expression and pathways involving TNFRs and TLRs, in addition to improving survival and attenuating oxidative liver damage and the related NO‐ and ROS‐producing pathways. CypD deficiency diminished the suppressive effect of LPS on mitochondrial function, nuclear‐ and mitochondrial‐encoded genes, and mitochondrial DNA (mtDNA) quantity, which could be critical in improving survival. Our data propose that CypD‐dependent mPT is an amplifier in inflammatory reprogramming and promotes disease progression. The mortality in human sepsis and shock is associated with mitochondrial dysfunction. Prevention of mPT by CypD disruption reduces inflammatory reprogramming, mitochondrial dysfunction, and lethality; therefore, CypD can be a novel drug target in endotoxic shock and related inflammatory diseases.Microorganisms or LPS (lipopolysaccharide), an outer membrane component of Gram‐negative bacteria, can induce a systemic inflammatory response that leads to sepsis, multiple organ dysfunction, and mortality. Here, we investigated the role of cyclophilin D (CypD)‐dependent mitochondrial permeability transition (mPT) in the immunosuppressive phase of LPS‐induced endotoxic shock. The liver plays an important role in immunity and organ dysfunction; therefore, we used liver RNA sequencing (RNA‐seq) data, Ingenuity Disruption of CypD prevents mPT and attenuates LPS‐induced complex changes, resulting in the maintenance of stable mitochondrial structure and reduced ROS‐related signaling. The effects of CypD disruption were reduction of LPS‐induced reprogramming and protection of mitochondria and OXPHOS complexes, which have an important effect on mouse survival. CypD‐dependent mPT inhibition may be a novel drug target for inflammatory diseases. In the ++ induced mPT and reduces ROS production and cell death /[(length bp*660 g·mol−1 *109 ng·g−1)]. β2m and mito12SrRNA PCR products were diluted containing 109 copies per µl of the DNA standard stock solution (SSS). Each SSS was diluted in tenfold for 2–8 log. PCR was performed from each sample to determine the correlation between the Ct and copy number . 2nd part: Absolute quantification. The template DNA was used for qPCR to determine the amount of mtDNA and nuclear DNA in the sample. Determination of Ct value gives back the concentration (or copy number) by the calibration curve. Template DNA and SSS DNA have run parallel way. 3rd part: Mt/Nuclear DNA ratio is given by dividing the average of copy number of Mt samples, and the average of the copy number of the nuclear DNA.The method is based on the Ajaz’s publication . Briefly® ‐Resistant AEC, # 30015.K, Histopathology Ltd., Budapest, Hungary) and counterstained with hematoxylin.Immunohistochemistry was performed on tissue sections. The sections were probed with antibodies indicated in the figures and listed in the materials and methods section for 1 h at room temperature. Secondary antibodies  were applied for 30 min at room temperature. Sections were incubated with 3‐amino‐9‐ethylcarbazol  and 0.5% phosphatase inhibitor cocktail , pH 7.4). The cell homogenate was sonicated, and the protein concentration was determined with protein assay kit  based on Bradford’s method according to the manufacturer’s description. The cell lysate was diluted in Laemmli buffer, boiled for five minutes and centrifuged , and the clear supernatant was used for further investigations. Tissue extracts were separated with SDS/PAGE with protein loads of 20 µg/lane and transferred onto nitrocellulose membrane. The membranes were blocked with 5% nonfat dried‐milk proteins in TBS and 0.1% Tween, incubated with the primary antibody at 4 °C overnight at a dilution of 1:1000. The secondary antibody was horseradish peroxidase‐conjugated goat anti‐rabbit IgG . Peroxidase labeling was visualized with the ECL Western blotting detection system . Quantification of band intensities of the blots was performed in imagej software .Ten mg of frozen tissue was homogenized with ultra turrax and Potter homogenizer in 150 µL lysis buffer  Statistics program for Windows, v21.0. Graphs were plotted with GraphPad Prism 6 software  or in Microsoft Excel 2016. Quantitative data are presented as the mean ± SEM. The significance of difference between sets of data was determined by independent samples t‐test or by one‐way analysis of variance (ANOVA) following Bonferroni or LSD post hoc test; a P value of less than 0.05 was considered significant.Statistical evaluations were performed using the The authors declare no conflict of interest.BV, FG, and BS supervised the project, designed and performed experiments, and wrote the paper. CA and NK performed Q‐RT‐PCR. FF and PBJ performed the in vivo studies the histological and western blot experiments. KE, EB, ZH, and IN performed the gene expression analysis, statistical evaluations, and data interpretation. LT provided and screened mouse lines.Fig S1. Heat maps demonstrating expression levels of individual genes among the study groups, (n=5).Click here for additional data file.Fig S2. Read coverage patterns derived from RNA‐seq experiments in mice liver tissue.Click here for additional data file.Fig S3. Effect of CypD disruption on the LPS induced differential expression of nuclear DNA encoded genes of oxidative phosphorylation.Click here for additional data file.Table S1. LPS induced significant enrichment of DEGs in WT mice liver tissue in canonical pathways analyzed by IPA. ‐lg > 1.3.Click here for additional data file.Table S2. LPS induced significant enrichment of DEGs in CypD‐/‐ mice liver tissue in canonical pathways analyzed by IPA. ‐lg > 1.3.Click here for additional data file.Table S3. List of DEGs in the CypD‐/‐+LPS vs WT+LPS comparison in canonical pathways analyzed by IPA. ‐lg > 1.3.Click here for additional data file.


Programmed death‐ligand 1 (PD‐L1) is one of the immune checkpoint proteins, and plays an important role in the progression and microenvironment of cancer. PD‐L1 expression has been associated with poor survival in many cancers. Several studies have also shown an association between PD‐L1 expression and the prognosis of patients with thymic epithelial tumors (TETs). In this study, we systematically evaluated the prognostic and clinicopathological roles of PD‐L1 expression in TETs.We searched the literature through PubMed, Embase and Cochrane library and chose the eligible studies, and subsequently performed a meta‐analysis to evaluate the prognostic and clinicopathological roles of PD‐L1 expression in TETs.P = 0.046) in TETs. PD‐L1 expression was significantly associated with male gender  and higher Masaoka stage .Six of the 75 articles found in the literature were selected. PD‐L1 expression was significantly related to unfavorable overall survival (hazard ratio 1.52, 95% confidence interval [CI]: 1.01–2.30, PD‐L1 expression was correlated with unfavorable prognosis in TETs, indicating PD‐L1 expression could help determine the prognosis of TET patients. Thymic epithelial tumors (TETs), including thymoma and thymic carcinoma (TC), are rare malignant tumors that show various morphologic appearances and clinical symptoms.Programmed death‐ligand 1 (PD‐L1) is one of the immune checkpoint proteins, and plays important roles in the progression and microenvironment of the cancer.PD‐L1 expression has been associated with poor survival in many cancers, including lung, pancreatic, esophageal, breast, ovarian, bladder, renal cancers and hematologic malignancies.Therefore, we performed a comprehensive meta‐analysis to explore the prognostic and clinicopathological roles of PD‐L1 expression in TETs.We searched the literature through PubMed, Embase and Cochrane library and chose eligible studies to include in the analysis. The search was conducted until 1 May 2020 using the following keywords: PD‐L1 or programmed death‐ligand 1; and thymic carcinoma or thymic epithelial tumor; and prognostic or predict or prognosis; or survival or outcome. This was accompanied by a manual search.The analysis included studies satisfying the following conditions: (i) A study showing the correlation of PD‐L1 expression with prognosis in human TETs; and (ii) hazard ratio (HR) with 95% confidence interval (CI) was reported. Articles with inaccurate data, together with conference abstracts and reviews were excluded from the analysis.We collected basic information reviewing the included articles. Two authors collected basic information individually and reached an agreement if there were any differences in the results. We evaluated the quality of the included articles using the Newcastle‐Ottawa Scale (NOS). The quality assessment was also conducted separately by two authors, and if there were any differences in the results, an agreement was reached.2 value was used to determine the degree of heterogeneity among the included studies. We also performed a funnel plot with filled method and Egger test to reveal the publication bias. Sensitivity analysis was performed to confirm the consistency of the pooled results. A P‐value <0.05 was considered as statistically significant.We conducted a meta‐analysis using StataSE12 . ISix studies of the 75 articles found in the literature were selected Fig  The basiet al.et al.et al.et al.et al.The analysis of the association between PD‐L1 expression and overall survival (OS) included four studies with 555 TET patients. Hakiri 2 = 24.5%, P = 0.258). The pooled HR was 1.52 , implying there was a relationship between PD‐L1 expression and unfavorable OS in TETs . Additionally, we conducted subgroup analyses according to tumor type (thymoma vs. TC) and sample size (fewer than 100 vs. more than 100). The results showed that the relationship between PD‐L1 expression and poor OS was still significant in the group with thymoma   Table . No sign3) Table .et al.et al.et al.et al.et al.The analysis of the association between PD‐L1 expression and disease‐free survival (DFS) or progression‐free survival (PFS) included four studies with 375 TET patients. Hakiri 2 = 0.0%, P = 0.771). The pooled HR was 1.36   Fig .P = 0.017) and higher Masaoka stage , but not with age, tumor size and grade, and myasthenia gravis ; and for DFS (P = 0.234)  with two studies filled in for OS, and the result was unchanged for DFS   Fig . Thus, a074) Fig .et al.et al.In the sensitivity analyses, the study by Wei PD‐L1 is a T cell coinhibitory receptor with a unique biologic function.PD‐L1 is selectively expressed on various cancer and inflammatory cells within the tumor microenvironment.Here, a meta‐analysis was performed for a systematic understanding of the relationship between PD‐L1 expression and prognosis in TETs.P = 0.046), suggesting an association between PD‐L1 expression with unfavorable OS in TETs. Nevertheless, in the subgroup analysis, the results were only statistically significant for thymoma , and not for TC.In the analysis of the association between PD‐L1 expression and OS, the results revealed a close correlation between PD‐L1 expression and OS .With respect to the association between PD‐L1 expression and DFS, the results of the analysis suggested a link between PD‐L1 expression and DFS, but were not statistically significant  and higher Masaoka stage .In addition, PD‐L1 expression was significantly related to male gender (OR 1.55, 95% CI: 1.08–2.22, Despite various efforts, this study had some limitations. First, there were not many studies related to PD‐L1 expression and prognosis, so the number of studies included in our analysis was small. In particular, the fact that it contains very few cases of TC and the failure to fully consider that TC is a separate disease in terms of natural prognosis and treatment especially chemotherapy is considered a major limitation of our research. Second, all the studies included, except one, were published in Asia, which was also a limitation of our study. Finally, the cutoff value of PD‐L1 expression varied slightly from study to study, so this might have affected our results. Since there is no gold standard for cutoff value of PD‐L1 expression so far and each PD‐L1 assay applies a different automated staining system, detection system, and cutoff value to determine PD‐L1 expression, it seems reasonable that studies with various cutoff values of PD‐L1 expression are reported.In conclusion, PD‐L1 expression was related to poor prognosis and higher stage in TETs. The results indicated that PD‐L1 expression could help determine the prognosis of TET patients.No authors report any conflict of interest.


Understanding the genetics underlying the heritable subphenotypes of sickle cell anemia, specific to each population, would be prognostically useful and could inform personalized therapeutics.The objective of this study was to describe the genetic modulators of sickle cell disease in a cohort of pediatric patients followed up in Mayotte.st2007 and December 31st2017, in children younger than 18 years.This retrospective cohort study analyzed clinical and biological data, collected between January1We included 185 children with 72% SS, 16% Sβ0-thalassemia and 12% Sβ + thalassemia. The average age was 9.5 years; 10% of patients were lost to follow up. The Bantu haplotype was associated with an increase in hospitalizations and transfusions. The alpha-thalassemic mutation was associated with a decrease of hemolysis biological parameters , and a decrease of cerebral vasculopathy. The Single Nucleotide Polymorphisms BCL11A rs4671393, BCL11A rs11886868, BCL11A rs1427407 and HMIP rs9399137 were associated with the group of children with HbF > 10%. Patients with HbF > 10% presented a significant risk of early onset of cerebral vasculopathy.The most remarkable result of our study was the association of SNPs with clinically relevant phenotypic groups. BCL11A rs4671393, BCL11A rs11886868, BCL11A rs1427407 and HMIP rs9399137 were correlated with HbF > 10%, a group that has a higher risk of cerebral vasculopathy and should be oriented towards the hemolytic sub-phenotype. SCD is characterized by abnormally shaped, adhesive red blood cells (RBCs) that interact with white blood cells (WBCs) and the endothelium, leading to chronic hemolysis, vasculopathy and a prothrombotic state [Sickle cell disease (SCD) refers to a group of autosomal recessive genetic disorders characterized by the synthesis of an abnormal hemoglobin: sickle hemoglobin S , Cameroon, Senegal and Arab-Indian [Coinheritance of alpha thalassemia trait and SCD is known to decrease the SCD severity. Indeed, alphathalassemia modulates SCD by reducing the intracellular concentration of HbS, which in turn reduces the HbS-polymer induced cellular damage. By the basis of this mechanism, there will be a reduction in hemolysis, stroke, silent infarction, transcranial doppler (TCD) velocity, and acute chest syndrome . The βS-b-Indian . Many aub-Indian , 11.Other genetic polymorphisms with an established influence on the SCD phenotype have been identified, including, HbF modifiers , uridine-diphosphoglucuronate glucuronosyltransferase (UGT1A1) promoter polymorphisms, and Glucose-6-phosphate dehydrogenase (G6PD) deficiency –14.Additional candidate genes associated with subphenotypes of SCD have been described . ClinicaMayotte is a French territory in the southern hemisphere, between the African continent and Madagascar and in the middle of the Indian Ocean. Its proximity to the Comoros, less than 70 km away, allows a massive immigration from the other islands of the archipelago to that country . The avaThis retrospective cohort study was performed using data collected from the medicalized information system program (MISP) of the Center for SCD of the Mamouzou General Hospital in Mayotte. The clinical and biological data collected for this project followed the recommended standard of care of SCD, by the French authority (Haute Autorité de Santé).Patients with SCA or S/beta-thalassemia, younger than 18 years in 2017, were seen every 3 months . A specific appointment was scheduled for annual review (during which the TCDwas carried out). These patients were prospectively included in the database between 2007 and 2017, after obtaining a statement of patient’s non opposition, as required by French regulations. For 50% of them, SCD has been diagnosed by universal neonatal screening . The othst 2007 and December 31st 2017, were considered for the analysis. The patients were in a stable state when these biological data were taken. For each patient, the following data were collected: age, gender, hemoglobin type, alpha and beta globin genotype, beta globin haplotype, basal HbF level, basal Hb level, glucose-6-phosphate-dehydrogenase (G6PD) status, UGT1A1 gene mutations status, single nucleotide polymorphism (SNP). SNP was genotyped using Single-Tube Fluorescent Bidirectional polymerase chain reaction (PCR). The other variables included severity and number of prior acute or chronic sickle cell specific complications , neurologic events, severe infections, acute anemia, cholelithiasis), use of opioids for painful events, hydroxyurea treatment, number of RBCs transfusions (or RBCs exchange), and number of hospitalizations. These data, from the computerized medical record, were transferred in 2017 to an anonymized database for analysis.Clinical and biological data, collected between January1The VOC is apainful complication of SCD . We onlyst2017, because of their high HbF level. Children lost tofollow-up for more than 3 years were also excluded.Were excluded from this study infants under 1 year of age on December31P values < 0·05 were considered statistically significant. All acute clinical events, correctlyrecorded in the medical files from birth (or the beginning of follow-up) to the date of the final evaluation were included in the analyses. Kaplan-Meyer curves and log-rank test were performed for generating survey curves. We performed a ROC curve for HbF, which allows to distinguish two groups (HbF < 10% versus HbF > 10%).The database was anonymised before analysis. The Statistical Package for the Social Sciences (SPSS) statistical software, version 13.0  was used for statistical analysis. The data were described as number and percentages for categorical variables and mean ± standard deviation (SD) or median (range) for continuous variables. Independent Student’st- test was used to compare continuous variables between groups , andchi-square test (or Fisher exact test) for categorical data. Multivariable logistic regression was used to examine the association between each of the variables and the sickle subphenotype with adjustment for age and sex. All patients or legal representatives (for the children included in the study) gavewritten informed consent to participate in this research. The study cohort was approved by the Mamoudzou Hospital Ethical committeeand the database was declared at the Commission NationaleInformatiqueetLibertés .0-thalassemia and 12% with Hb/Sβ+ thalassemia. The mean age was 9.5 years, with ranges from 19 months to 18 years. 15.3% of the children met the definition criteria of cerebral vasculopathy. There were missing data for 22 of included patients.Ten percent of patients from the Center were lost to follow up Fig. . One hunIn our study, homozygous sickle cell patients had significantly lower mean hemoglobin and hematocrit levels than Sβ0 and then Sβ + patients. On the clinical level, SCA was significantly associated with ACS, bacterial infections, cholelithiasis, hospitalizations and more frequent transfusions Table .Table 1Having at least one Bantu allele concerned almost all of our study population. The patients with Bantu / Bantu haplotype had significantly lower hematocrit, higher MCV and MCHC. They were hospitalized andtransfusedmore often Table .Table 2Fifty percent of the patients had a alpha-3.7 mutation of at least one alpha gene. The absence of this alpha-thalassemic mutation was significantly associated with cerebral vasculopathy and more frequent RBC transfusions  did not allow statistical analysis.The low number of patients with the UGTA1 mutation (p = 0.002), less transfused (p = 0.025), had less VOC / year (p = 0.039), but they had more cerebral vasculopathy (p = 0.023) than those with < 10% HbF. Homozygous Bantu patients in the HbF group < 10% had less cholelithiasis (p = 0.021). Patients in both groups, when they carried one or two Benin haplotypes, were less hospitalized (p = 0.002), had less VOC per year (p = 0.039) and their 1st VOC occurred less early (p = 0.03) than those that did not have any Benin haplotypes. Only the patients heterozygous for Benin haplotypes had a significant high HbF level (p = 0.04). Patients who do not carry a Benin allele were more transfused (p = 0.018) than those who did. The alpha-thalassemic mutation was associated with an increase in hemoglobin level in patients at risk of vasculopathy (p = 0.023), and an increased leukocyte rate (p = 0.001). Children in the group with an alpha mutation were hospitalized less often (p = 0.004) and were less likely to have cholelithiasis (p = 0.041) than other children. Children in the < 10% HbF group who carried an alpha mutation received fewer transfusions than those > 10% (p = 0.048). Multivariate analysis (Table p = 0.051) and BCL11A rs11886868 (p = 0.06). BCL11A rs4671393 (p = 0.2) and HMIP rs9399137 (p = 0.24) were not independently associated with the phenotypic groups. A concordance chi-2 test found preferential associations between some SNPs , and more infections (p = 0.045) than those without. Regarding patient management, TCD was performed more often (p = 0.026), iron chelatorsand transfusion were prescribed more often .Patients with G6PD mutation had a greater MCV , affecting up to 30% of children with the disease. Despite the relative frequency of stroke in SCA, few predictors of this risk have been described –40. ThusInvestigation of genetic variants has identified several genes as principal influencers of HbF regulation. In our study, the alleles BCL11A rs1427407, HMIP rs4895441 and HMIP rs9399137 were significantly associated with an increase in HbF. In the literature, these SNPs are indeed strongly associated with HbF. BCL11A rs1427407 was the SNP with the highest correlation withHbF in a Genome wide association study (GWAS) performed in Tanzania . The mecThe most remarkable result of our study was the association of SNPs with the phenotypic groups that we aimed to determine. BCL11A rs4671393, BCL11A rs11886868, BCL11A rs1427407 and HMIP rs9399137 were correlated with the HbF group> 10%, which presents a higher risk of cerebral vasculopathy and would be oriented towards the hemolytic sub-phenotype. BCL11A rs1427407 was the most strongly associated in our population, which corresponds to its strong correlation with HbF found in the Tanzanian GWAS . HMIP rsThe alpha-thalassemic mutation was associated with a decrease of hemolysis biological parameters , and less cerebral vasculopathy. In the literature, it is also associated with fewer vascular complications , 58, 59.Our determination of the sickle cell sub-phenotypes from the HbF level didnot yield the expected result, although some trends have emerged. Difficulties in monitoring the Mahoran pediatric patients lead to poor control of environmental prognostic factors such as lifestyle, therapeutic education of the patient, screening and early management, and regular monitoring. This may have impacted some results of our study. However, we relied on the fact that environmental factors do not appear to affect the type of expression of the disease . The numOur study allowed a description of the Mahoran pediatric population, reflecting the need to continue to improve monitoring clinical data continuously. In our cohort, the SNPs BCL11A rs4671393, BCL11A rs11886868, BCL11A rs1427407 and HMIP rs9399137 were associated with the group of children with HbF > 10%, and which seemed to present a high risk of occurrence of cerebral vasculopathy. This link was not found independently for each SNP. Beta-globin haplotypes and alpha-thalassemic mutations might also influence the clinical expression of the disease, but the multivariate analysis did not find any independent genotypic marker.