Bacteriotherapy in Chronic Fatigue Syndrome (Cfs) a Retrospective Review
Front Nutr. 2021; 8: 756177.
Oral Bacteriotherapy Reduces the Occurrence of Chronic Fatigue in COVID-xix Patients
Letizia Santinelli
iDepartment of Public Health and Infectious Diseases, Sapienza Academy of Rome, Rome, Italy
Luca Laghi
2Section of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
3Interdepartmental Middle for Agri-Food Industrial Enquiry, Academy of Bologna, Bologna, Italy
Giuseppe Pietro Innocenti
iDepartment of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italian republic
Claudia Pinacchio
oneDepartment of Public Wellness and Infectious Diseases, Sapienza University of Rome, Rome, Italy
Paolo Vassalini
1Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy
Luigi Celani
aneDepartment of Public Health and Infectious Diseases, Sapienza Academy of Rome, Rome, Italy
Alessandro Lazzaro
1Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy
Cristian Borrazzo
aneDepartment of Public Health and Infectious Diseases, Sapienza Academy of Rome, Rome, Italy
Massimiliano Marazzato
1Section of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy
Lorenzo Tarsitani
4Department of Man Neurosciences, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
Alexia E. Koukopoulos
4Section of Human Neurosciences, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
Claudio M. Mastroianni
iDepartment of Public Wellness and Infectious Diseases, Sapienza University of Rome, Rome, Italia
Gabriella d'Ettorre
1Department of Public Health and Infectious Diseases, Sapienza Academy of Rome, Rome, Italian republic
Giancarlo Ceccarelli
iDepartment of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy
Received 2021 Aug ten; Accepted 2021 Nov 29.
Abstract
Long COVID refers to patients with symptoms every bit fatigue, "brain fog," pain, suggesting the chronic involvement of the fundamental nervous system (CNS) in COVID-xix. The supplementation with probiotic (OB) would have a positive effect on metabolic homeostasis, negatively impacting the occurrence of symptoms related to the CNS after infirmary belch. On a total of 58 patients hospitalized for COVID-19, 24 (41.4%) received OB during hospitalization (OB+) while 34 (58.6%) taken only the standard treatment (OB–). Serum metabolomic profiling of patients has been performed at both hospital acceptance (T0) and belch (T1). Six months afterward discharge, fatigue perceived by participants was assessed by administrating the Fatigue Cess Scale. 70.7% of participants reported fatigue while 29.3% were negative for such condition. The OB+ group showed a significantly lower proportion of subjects reporting fatigue than the OB– one (p < 0.01). Furthermore, OB+ subjects were characterized past significantly increased concentrations of serum Arginine, Asparagine, Lactate reverse to lower levels of three-Hydroxyisobutirate than those not treated with probiotics. Our results strongly suggest that in COVID-xix, the assistants of probiotics during hospitalization may foreclose the evolution of chronic fatigue by impacting key metabolites involved in the utilization of glucose as well as in energy pathways.
Keywords: chronic fatigue, COVID-19, probiotics, metabolomics, FAS, Arginine, Asparagine, Lactate
Introduction
Since its inception, COVID-19 immediately proved to exist an ambitious respiratory syndrome capable of degenerating into pneumonia, ARDS (Astute Respiratory Distress Syndrome), multiorgan failure, and expiry. Eventually, the massive rise of new cases over time, highlighted the presence of mail service-SARS-CoV-2-chronic symptoms following the resolution of the disease's critical and infective phase. A distinctive characteristic of the "Long COVID" (i) is postal service-exertion malaise, worsening symptoms post-obit physical or mental exertion occurring inside 12–48 h of the effort and requiring an extended recovery menstruum (2–5). The clinical motion-picture show of the Long COVID patients reporting fatigue is similar to what was observed in individuals with myalgic encephalopathy/chronic fatigue syndrome (ME/CFS), e.g., several months of profound exhaustion, abysmal performance, and brusque-term memory problems.
All the current hypotheses, e.g., mitochondrial dysfunction, immune organisation dysregulation, nitric oxide dysmetabolism, hypothalamic–pituitary–adrenal disruption, and genetic predisposition, call into question the microbes' role in the intestines. Abdominal discomfort, nausea, diarrhea, and vomiting are clinically evident in nigh 50% of COVID-nineteen patients (half-dozen). These medical signs and symptoms are more frequent in the virus infected individuals with an altered microbiome due to pre-existing conditions such equally chronic diseases, inflammation, drug treatments, and age (seven). Levels of bacteria with probiotic properties [e.g., Lactobacillus and Bifidobacterium; (8)] and other beneficial symbionts are lower in hospitalized COVID-19 patients. By contrast, opportunistic pathogens (e.g., Streptococcus, Rothia, and Actinomyces) are higher (ix, 10). Notably, these changes may persist after respiratory symptoms resolution and usually correlate with COVID-19 severity (ten).
We have already demonstrated and published the benefits of oral bacteriotherapy for COVID-19 patients during the hospital stay quo advertisement vitam (eleven–fifteen). In this paper, we report the efficacy of our therapeutic approach quo advertisement valetudinem.
Materials and Methods
Participants
Nosotros conducted a retrospective observational written report at the Division of Infectious Diseases, Department of Public Health and Infectious Diseases, Umberto I Hospital of Sapienza University of Rome (Italy), including 58 patients hospitalized from March the 1st and Apr the 30th 2020 with confirmed COVID-19 and discharged to habitation intendance.
All the hospitalized patients received therapeutic regimens including one or more of the post-obit antimicrobial agents: hydroxychloroquine (200 mg twice a day for 7 days), azithromycin (500 mg once a 24-hour interval for v days), antiviral therapy including lopinavir–ritonavir (400/100 mg twice a 24-hour interval), or darunavir–cobicistat (800/150 mg one time a twenty-four hour period) for 14 days. Low molecular weight heparin was administered for prevention of deep vein thrombosis, as recommended at the time by the Italian Order of Infectious Diseases (16). Tocilizumab (viii mg/kg up to a maximum of 800 mg per dose with an interval of 12 h for two times) was administered in case of loftier serum IL-6 or of significant worsening of the respiratory picture in case of unavailability of IL-6 dosage. The information source for patient information analysis was derived from electronic medical records in the Hospital Electronic Data System. The variables considered for the written report included: (1) age, gender, access, and discharge engagement from the hospital, length of hospitalization, (2) cardiovascular (CV) disease. We used the Charlson score to predict the 1-year bloodshed for a patient with a range of comorbid conditions (17).
Amid all participants, a group of 24 subjects received oral bacteriotherapy (OB) during the entire hospitalization menses (T1) [median: 23 days (IQR: 19–38 days)] (OB+). Another group of 34 individuals (OB–) was not supplement with oral bacteriotherapy [median hospitalization flow: 21 days (IQR: 18–26 days)]. Patients admitted to the ward received supplementation with oral bacteriotherapy, in addition to the best available therapy, in case of intestinal symptoms (11). Known or suspected allergy or intolerance to oral bacteriotherapy conception was considered a contraindication to the prescription of supplementation.
The commercial oral bacteriotherapy conception (SLAB51; currently sold under the brand Sivomixx800®, Ormendes, Switzerland) was composed of Streptococcus thermophilus DSM 32245®, Bifidobacterium lactis DSM 32246®, Bifidobacterium lactis DSM 32247®, Lactobacillus acidophilus DSM 32241®, Lactobacillus helveticus DSM 32242®, Lactobacillus paracasei DSM 32243®, Lactobacillus plantarum DSM 32244®, and Lactobacillus brevis DSM 27961®. The conception was administered in three equal doses per mean solar day for a total of 2,400 billion bacteria per day.
Nosotros applied the post-obit exclusion criteria: clinically axiomatic cognitive impairment and inadequate knowledge of the Italian language, history of or current diseases of the small-scale or large intestine, any current or previous systemic malignancy, and pregnancy. Nasopharyngeal swabs and blood samples were collected at hospital admission (T0) and earlier discharge (T1) from all SARS-CoV-two-positive patients. Six months afterward belch, all patients were also contacted by phone by trained clinical raters, and Fatigue Assessment Scale (FAS) questionnaire was administered.
The Ethical Committee of the Sapienza University of Rome approved the study (num. Rif. 109/2020). All study participants gave written informed consent.
RT-qPCR Detection of SARS-CoV-2 RNA
Viral RNA was extracted from nasopharyngeal swabs using Versant SP 1.0 Kit (Siemens Healthcare Diagnostics), as previously described (18). Briefly, ten μl of extracted RNA was reverse-transcribed and simultaneously amplified by a real-time RT-PCR system (RealStar SARS-CoV-two RT-PCR, Altona Diagnostics), targeting Due east and S viral genes.
Fatigue Assessment Scale (FAS)
Vi months later on hospital discharge, participants were contacted by telephone by trained clinical raters, and completed the Fatigue Assessment Calibration test, a 10 items questionnaire used to assess perceived fatigue (nineteen). FAS is validated for patient affected by rheumatological disease (xx), sarcoidosis, (21) but as well for full general population (xx). It has been already used in COVID-19 patients to evaluate fatigue in post-COVID setting (22, 23). Of the ten questions, 5 assess concrete fatigue (questions 1–ii, 4–five, and 10) and 5 mental fatigue (questions 3 and 6–9). Responses are on a 5-point Likert scale (from i = never to 5 = always). The FAS full score ranges from 10 to 50, with college score indicating more fatigue. Full scores beneath 22 indicate "non-fatigued" persons, scores higher or equal to 22 bespeak "fatigued" patients, and scores higher or equal to 35 indicate extreme fatigue.
Serum Metabolome Analysis
For metabolomics investigation by Proton Nuclear Magnetic Resonance (1H-NMR), a standard solution was prepared with three-(trimethylsilyl)-propionic-two,2,3,3-d4 acrid (TSP) sodium common salt, 10 mM, and sodium azide, 2 mM, in D2O, set at pH 7.00 with a ane-Chiliad phosphate buffer.
Whole blood was left to stand for thirty′ at 20°C earlier beingness centrifuged at 3,000 rpm for xv′ at 4°C for serum isolation, within 2 h after withdrawal. The samples were then stored at −80°C prior to investigation. Each thawed aliquot was centrifuged at 18,630 g for 10 min at four°C degrees; 0.7 mL of supernatant were added to 0.1 mL of the standard solution and centrifuge once more. 1H-NMR spectra were recorded at 298 K with an AVANCE III spectrometer (Bruker, Milan, Italia) operating at a frequency of 600.13 MHz. The signal due to the residual hydrogen deuterium oxide was suppressed by presaturation, whereas broad signals from slowly tumbling molecules were removed by including a Carr–Purcell–Meiboom–Gill filter (24) to a gratuitous induction decay sequence. The filter was made up past a railroad train of 400 echoes separated by 800 μs, for a total time of 328 ms. Each spectrum was acquired past summing up 256 transients using 32 Chiliad data points over a 7211.54 Hz spectra (for an acquisition time of 2.27 south). The recycle filibuster was prepare to 8 s, considering the longitudinal relaxation time of the protons under investigation. Spectra were adapted for stage and baseline in Topspin ver. 3.5 (Bruker, Milan, Italy).
Signals were assigned by comparison their chemic shift and multiplicity with the Human Metabolome Database (25) and Chenomx software library (Chenomx Inc., Edmonton, Canada, ver. 10). Any other further processing was performed in R computational language (www.r-project.org). Moreover, molecules' quantification was performed in the kickoff sample acquired by employing an external standard, while the spectra from the other samples were adjusted toward the first past probabilistic quotient normalization (26). Integration of the signals was performed for each molecule by means of rectangular integration.
Statistical Analysis
The statistical analyses were performed using GraphPad Prism software, version five.0 (GraphPad Software Inc., La Jolla, California, USA) and Statistical package for social science (SPSS software), version 22 (IBM SPSS, Chicago, III). The continuous information were presented equally means with Standard Difference (±SD), and medians with Interquartile Range (IQR: 25–75%), and the presence of statistically significant differences between groups were assessed by the Pupil's t-test or Mann–Whitney U-test. The dichotomous variables were described as uncomplicated frequencies (n) and percentages (%) and and so compared past the Fisher's verbal test or χ2-test for the two groups.
Metabolic concentration differences between SARS-CoV-2-infected patients receiving or not oral bacteriotherapy formulation were analyzed using the Isle of mann–Whitney U-exam. The Wilcoxon signed-rank test for paired samples was used to evaluate Metabolic concentration differences between T0 and T7 in OB+ and in OB– patients. A point-biserial Pearson's correlation was calculated to assess the correlation between oral bacteriotherapy supplementation and serum metabolites concentration. A p < 0.05 was considered statistically significant.
Results
Written report Population
A full of 58 SARS-CoV-2-infected patients were enrolled in the study. Demographic and clinical characteristics of the whole population at the hospital admission (T0) are reported in Tabular array 1. During hospitalization, 79.three% (46/58) of the patients received supplemental oxygen therapy, 88% (51/58) of cases were treated with hydroxychloroquine, 31% (18/58) with azithromycin, 48.3% (28/58) with anti-IL-half-dozen agent (Tocilizumab) and 29.3% (17/58) were treated with antiviral therapy.
Table one
Demographic and clinical characteristic of study population at T0.
| Parameters | Median (IQR 25–75%) | n (%) |
|---|---|---|
| Gender. Male | – | 37 (64) |
| Historic period (years) | 63 (56–70) | – |
| White blood cells (mmc) | 5,625 (4072.5–seven,105) | |
| Lymphocytes (mmc) | 805 (640–one,200) | – |
| Lymphocytes (%) | 16 (10.5–23.43) | – |
| Glucose (mg/dL) | 102 (88.25–128.5) | |
| C-reactive protein (mg/Fifty) | 62,340 (17,505–i,77,600) | – |
| Length of hospitalization (days) | 22 (eighteen–27) | – |
| CHARLSON alphabetize | 3 (1–4) | – |
| ICU hospitalization | – | nine (fifteen%) |
SD, Standard deviation; IQR, Interquartile range; ICU, Intensive care unit.
Oral Bacteriotherapy (T0–T1)
Among all patients recruited (n = 58), 24 (41.4%) received oral bacteriotherapy during the hospitalization period [median: 23 days (IQR: 19–38 days)] while 34 (58.6%) were treated with simply pharmacological handling [median: 23 days (IQR: xix–38 days)]. Specifically, 70.8% (17/24) of the OB+ patients had received supplemental oxygen therapy, 87.v% (21/24) hydroxychloroquine, 25% (6/24) azithromycin, 50% (12/24) an anti-IL-6 amanuensis (Tocilizumab), and 29.2% (7/24) antiviral therapy. Amongst the OB– group, 85.3% (29/34) of the individuals had received supplemental oxygen therapy, 88.2% (xxx/34) hydroxychloroquine, 35.3% (12/34) azithromycin, 47% (16/34) an anti-IL-6 agent (Tocilizumab), and 29.4% (ten/34) antiviral therapy. Therefore, no statistically significant differences were determined between the OB+ and OB– groups with respect to all clinical characteristics and therapeutic regimens. The characteristics of the ii groups are shown in Table two.
Table ii
Demographic and clinical characteristic of OB– and OB+ SARS-CoV-two-infected patients.
| Parameters | OB– ( n = 34) | OB+ ( due north = 24) | p-value | ||
|---|---|---|---|---|---|
| Median (IQR 25–75%) | Number (%) | Median (IQR 25–75%) | Number (%) | ||
| Gender. Male person/Female | – | 23 (68)/11 (32) | – | fourteen (58)/10 (42) | 0.86–0.66 |
| Historic period | 62 (52–63) | 64 (56–69) | – | 0.47 | |
| White claret cells (mmc) | v,870 (4,390–7,105) | – | five,300 (3,615–7042.5) | – | 0.56 |
| Lymphocytes (mmc) | 805 (642.v–1137.5) | – | 810 (620–1,220) | – | 0.86 |
| Lymphocytes (%) | 14.half dozen (nine.viii–20.1) | – | 17.4 (10.eight–25.9) | – | 0.84 |
| Glucose (mg/dL) | 106 (89.75–120.3) | 99.v (85–142.8) | 0.92 | ||
| C-reactive protein (mg/Fifty) | fourscore,480 (24,545–ii,02,000) | – | 57,120 (14,760–one,29,815) | – | 0.23 |
| Length of hospitalization (days) | 20.5 (18–26) | – | 22.five (nineteen.3–37.5) | – | 0.9 |
| CHARLSON index | 2 (1–4) | – | 3 (1–v) | – | 0.35 |
| ICU hospitalization | – | 7 (21) | – | 2 (8.3) | 0.19 |
Considering that fatigue has been recently described as i of the listed symptoms of post-COVID-19 (1, 22, 23), at 6 months (T6) later hospital belch all SARS-CoV-2-infected patients underwent the FAS questionnaire. Out of the 58 patients, 41 (70.7%) reported fatigue [FAS median (IQR) 32(26–36)], while 17 (29.three%) individuals displayed a FAS score below 22 [FAS median (IQR) 20(17–xx)] (fatigued FAS vs. not fatigued FAS: p < 0.01). At infirmary belch, no meaning differences in demographic and clinical variables were adamant betwixt subjects found fatigued and not fatigued at T6 (Table 3).
Table 3
Demographic and clinical characteristic of drawn and not fatigued SARS-CoV-two-infected patients.
| Parameters | Not fatigued (No. 17) | Fatigued (No. 41) | p-value | ||
|---|---|---|---|---|---|
| Median (IQR 25–75%) | Number (%) | Median (IQR 25–75%) | Number (%) | ||
| Gender, Male/Female | – | 10 (59)/seven (41) | – | 27 (66)/14 (34) | 0.629 |
| Age | 62 (51–64) | – | 66 (59–70) | – | – |
| White blood cells (mmc) | five,230 (iii,980–6,800) | – | 5,900 (4,290–7,120) | – | 0.490 |
| Lymphocytes (mmc) | 800 (690–ane,200) | – | 810 (600–1,200) | – | 0.875 |
| Lymphocytes (%) | 17.3 (13.4–25.9) | – | 14.6 (9.6–21.1) | – | 0.678 |
| Glucose (mg/dL) | 101 (85–126) | – | 110 (89–129) | – | 0.480 |
| C-reactive protein (mg/L) | 22,080 (14,040–1,22,520) | – | 68,040 (21,360–ane,77,960) | – | 0.555 |
| Length of hospitalization (days) | 25 (20–43) | – | 21 (18–26) | – | 0.030 |
| CHARLSON index | two (1–four) | – | 3 (1–four) | – | 0.095 |
| ICU hospitalization | – | 1 (half-dozen) | – | 8 (20) | 0.111 |
SD, Standard divergence; IQR, Interquartile range; ICU, Intensive intendance unit of measurement. The bold values point statistic pregnant values.
A significantly higher proportion of subjects positive for fatigue has been observed in the OB– group compared to those additionally treated with SLAB51 (OB– vs. OB+, 91% (31/34) vs. 41.7% (x/24); p < 0.01). The drawn patients who had received SLAB51 reported significantly lower FAS scores than those not treated with the probiotic formula [median (IQR), OB+, 24 (22.5–26) vs. OB–, 34 (31.5–38); p = 0.02]. Interestingly, the proportion of subjects presenting farthermost fatigue was significantly college amongst the OB– group than in the OB+ one [OB– vs. OB+, 29.4 (10/34) vs. 4.two (ane/24); p = 0.047].
Metabolomic Contour of SARS-CoV-ii Infected Patients
Since CFS has been previously associated to altered metabolic signature (27), we performed metabolomic profiling of the serum collected from our patients at T0 and T1 to evaluate modification in the concentration of key metabolites.
Before handling, the OB– and the OB+ groups were comparable with respect to all serum metabolites considered. Significantly increases in the levels of Arginine, Asparagine, and Lactate opposite to a significantly decrease in the levels of 3-Hydroxyisobutirate accept been determined in SARS-CoV-two-infected patients afterward the SLAB51 treatment (Figure 1). Conversely, no significant modification in the concentration of the same serum metabolites were observed for the OB– grouping (Effigy 1).
(A–D) Serum Arginine, Asparagine, Lactate, and iii-Hydroxyisobutirate concentration in SARS-CoV-ii infected patients receiving and non receiving oral bacteriotherapy handling at T0 and T1. (A) Comparison of Arginine serum concentration at T0 and T1 between SARS-CoV-2 infected patients treated or non treated with OB. (B) Comparison of Asparagine serum concentration at T0 and T1 between SARS-CoV-2 infected patients treated or not treated with OB. (C) Comparison of Lactate serum concentration at T0 and T1 betwixt SARS-CoV-2 infected patients treated or not treated with OB. (D) Comparing of 3-Hydroxyisobutirate serum concentration at T0 and T1 betwixt SARS-CoV-2 infected patients treated or not treated with OB. Data were analyzed using the Mann–Whitney U-test and the Wilcoxon signed-rank test for paired samples. *Statistically significant.
Sub Analysis of Patients Enrolled Not Admitted to Intensive Care Unit
In social club to minimize the possible biases between the two groups, nosotros also evaluated our information afterward removing the patients hospitalized in ICU from both groups (OB– and OB+). Obtained results were as follows: the grouping administered with probiotics was characterized by a significantly lower prevalence of drawn subjects with respect to the one not taking oral bacteriotherapy [OB– vs. OB+; 24(70.58%) vs. 9(37.five%), p = 0.0003]. The grouping administered with probiotics was characterized by significantly lower FAS score values than the one non taking oral bacteriotherapy [OB– vs. OB+; median (IQR), 33(31–34.five) vs. 24 (26–22), p = 0.007]. For what concerns the metabolic variables no changes has been observed respect to what reported in the manuscript except for Arginine for which no meaning differences has been determined betwixt the OB– and the OB+ one at T1 (come across Supplementary Effigy ane).
Mail service-hoc Power Assay
Finally, we performed a post-hoc power analysis relative to all endpoint we reported in the manuscript as significantly different. The results of our assay, reported every bit Supplementary Table 1, show that for most considered variables the power of the used statistical methods is more than 50% with most of the major endpoints showing >ninety% retained power.
Discussion
An accepted definition of post-COVID-xix fatigue is a "decrease in concrete and/or mental operation that results from changes in central, psychological, and/or peripheral factors due to the COVID-nineteen illness" (28). The prevalence of fatigue has been reported in up to fifty% of mail service-COVID-xix patients (6).
Without evidence of organ damage, these individuals feel tired and unwilling to perform current tasks even later on many months from the immigration of the infection. To date, at that place is no specific tool available to appraise fatigue in COVID-19 subjects. Therefore, we used the Fatigue Cess Scale (FAS), which is convenient for patients to complete and is not time-consuming. Physicians have used FAS for monitoring patients with sarcoidosis and idiopathic pulmonary fibrosis (19–23). We have evaluated the patients half-dozen months from belch.
All enrolled subjects were acutely and severely ill at admission to the ER (Emergency Room) (Tabular array 1). Equally per our internal protocol (11) 34 (58.half-dozen%) patients had standard treatment, and 24 (41.4%) also supplementation with the loftier potency probiotic blend SLAB51. Patients remained hospitalized until clinical resolution (SO2 ≥94%) or testing negative for COVID-19. At belch, all the patients had similar non-detectable blood levels of serotonin, dopamine, or acetylcholine (Effigy i). They had been hospitalized and isolated for a long time, and therefore and therefore they appeared psychologically relieved due to discharge.
Six months later on release from the hospital, no patient showed abnormal lung office tests or Thentwo beneath 94%. We could not appraise the office of family environment, economical atmospheric condition, and other feelings during their half-dozen months stay at dwelling with their families. Still, none of the patients referred to the use of antidepressants, sedatives, or sleeping pills earlier the FAS exam. A significantly lower proportion of subjects experimenting CFS has been determined in the group additionally administered with SLAB51 with respect to that taking only standard pharmacological therapy. Notably, the group administered with SLAB51 presented likewise a significantly lower percentages of subjects with extreme fatigue, compared to the grouping not taking probiotics.
Patients with symptoms as fatigue, "brain fog," pain, breathlessness, and orthostatic intolerance (29) are more and more than frequent and suggest chronic interest of the central nervous system (CNS) (30). New findings testify that detectable levels of the virus in COVID-19 in the brains are depression and do not correlate with histopathological changes (31). The observed microglial activation, microglial nodules, and neuronal phagocytosis upshot from systemic inflammation, probably in synergy with hypoxia and ischemia (32, 33). As detected by 18F-fluorodeoxyglucose positron emission tomography (FDG-PET), which measures brain glucose metabolism, the hypometabolism of the frontal lobe may exist involved in fatigue in patients with COVID-nineteen (34). Undeniably, in subjects with post-COVID-nineteen fatigue, the metabolic homeostasis is disturbed (35, 36).
The metabolomic profile of the 2 groups was similar at infirmary admission. At T1, increased serum levels of arginine, asparagine, lactate, and decreased levels of 3-Hydroxyisobutyrate were found in OB+ treated subjects (n = 24). The same parameters did not change amid OB– patients at T1.
Six months subsequently, when the FAS test was administered, the group additionally administered with SLAB51 presented a significantly lower prevalence of chronic fatigue as compared to patients treated with merely the pharmacological therapy. At T1, the subjects treated with SLAB51 had significantly higher levels of arginine as compared to baseline and to the OB– group at T1. Although this observation needs to be confirmed past investigating larger number of samples, our results strongly suggest that the arginine levels/variations might plant an early predictive mark of chronic fatigue when COVID-19 patients are discharged from the hospital. Nosotros hypothesize that the higher levels of arginine observed in patients treated with SLAB51 at belch may underlie the improve physical and psychiatric conditions observed later on 6 months, compared to subjects treated only with standard therapy.
In this context, arginine is essential in the regulation of growth hormone, glucagon, insulin, and for the synthesis of DNA, RNA, polyamines, and creatine, a molecule produced in the liver to regenerate ATP post-obit muscle contraction (37, 38). Low concentrations of arginine have been consistently associated with fatigue in its chronic and reversible forms. Mizuno et al. plant that plasma concentration of arginine, together with other branched-concatenation amino acids, was low in salubrious subjects after mentally fatiguing activities (39). In addition, Camic et al. found that the administration of arginine was able to delay the onset of neuromuscular fatigue (40). Co-ordinate to Chen et al. this could be related to the arginine ability to remove the NH3 in excess by increasing nitric oxide biosynthesis or urea cycle (41).
It is also interesting to bespeak out the design of 3-Hydroxyisobutyrate that decreases in subjects treated with SLAB51 (OB+) only remains unmodified in those not treated with oral bacteriotherapy (OB–). 3-Hydroxyisobutyrate in conditions of energy deficiency is a source of nourishment for the middle, encephalon, and muscles. It has been recently published that ketone bodies are unbalanced in subjects with COVID-19 and that their persistence at high levels in the blood was associated with a poor prognosis (42–44). In the OB– group, the unmodified levels of 3-Hydroxyisobutyrate suggest steady country compensatory mechanisms for contradistinct glucose utilization or insulin resistance. The treatment with SLAB51 might take lowered three-Hydroxyisobutyrate in the OB+ grouping by modifying arginine and asparagine levels that regulate glucagon and insulin and consequently improved glucose utilization and energy metabolism. Asparagine in the body is a critical support in energy production and is essential for nervous tissue, particularly brain evolution and function (45–47). In addition, information technology can increase the synthesis of glucagon, the hormone that antagonizes insulin, which causes an increase in blood glucose. Low levels of asparagine may indicate poor metabolism or synthesis of aspartic acrid, resulting in the disability to synthesize and excrete urea accordingly. The inability to excrete urea can outcome in the formation of toxic nitrogen-containing metabolites, which tin cause a diverseness of symptoms, such as depression, irritability, headaches, defoliation, or, in more extreme cases, psychosis. Decreased arginine and asparagine levels are present in the plasma during acute pulmonary inflammatory exacerbations (48).
The lactate increment observed just in OB+ subjects should be framed in the context of energy metabolism utilization. We practice not think that the difference observed at T1 results from a different muscle action in our patients. The OB+ and OB– subjects had been bedridden for weeks and discharged without any motor rehabilitation. Therefore, in our opinion, the observed variation depends on the modification of the intestinal flora induced by SLAB51. Information technology is well-known that appropriate intestinal fermentation is associated with improved concrete and able-bodied performance (49). An increase in lactate levels in OB+ subjects could exist an additional energy source for the brain, every bit suggested by its use every bit a neuroprotectant in encephalon trauma (fifty).
The observational nature of the study, as well as the lack of appropriate command, randomization, and blinding should be assumed as major limitations for this study; taking into account all those aspects, the authors consider the results suggestive for generating hypothesis that will demand farther confirmatory studies, but currently incomplete to depict firm conclusions.
Conclusion
In conclusion, a growing body of show suggests that dysbiosis and modification of metabolic processes due to the imbalance of the abdominal flora, observed in patients infected by SARS-CoV-two, may play a key role in determining the severity of the COVID-xix, including neuropsychological, psychiatric and long-term disorders (51–55). Given the pregnant impact of SARS-CoV-2 on host'due south microbiota and the electric current lack of constructive therapeutic options, a possible part of oral bacteriotherapy has been hypothesized, as complementary therapeutic strategy to fight the pathophysiological changes due to SARS-CoV-two and the COVID-19 related damages (eleven–15, 56–62).
We believe that, in addition to what has been previously reported regarding survival and the risk of being intubated (eleven), the administration of SLAB51 during hospitalization may touch on the subject's functioning months subsequently. Even because all the limitations of the present written report, some of the evidence can be underlined: (a) subjects infected by the virus, if treated with SLAB51, have a lower incidence of chronic fatigue; (b) the administration of bacteriotherapy induces metabolic changes for a improve utilization of glucose and energy pathways. Yet, these findings need to exist confirmed past more in-depth analysis and replicated in further studies.
Data Availability Argument
The raw data supporting the conclusions of this article will be made available past the authors, without undue reservation.
Ideals Statement
The studies involving human participants were reviewed and canonical by Ideals Committee of Policlinico Umberto I—Sapienza Academy (blessing number: Rif. 109/2020). The patients/participants provided their written informed consent to participate in this study.
Author Contributions
Gd'E and GC: conceptualization and validation. LS, LL, GI, CP, and GC: methodology. LS, GI, CP, PV, AL, and CB: formal analysis. LS, LL, GI, CP, LC, LT, and AK: investigation. LS, LL, GI, CP, LC, and MM: data curation. LS, GI, CP, PV, MM, Gd'E, and GC: writing—original draft preparation. LS and Gd'E: writing—review and editing. CM, Gd'East, and GC: visualization. Gd'Eastward: supervision, project administration, and funding conquering. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported in office by grants of Sapienza University of Rome (Progetti di Ateneo 2018 Due north.801/2019).
Disharmonize of Interest
The authors declare that the enquiry was conducted in the absenteeism of whatever commercial or financial relationships that could exist construed as a potential conflict of interest.
Publisher'south Notation
All claims expressed in this article are solely those of the authors and do not necessarily stand for 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 past its manufacturer, is not guaranteed or endorsed by the publisher.
Acknowledgments
Authors wish to thank Prof. Claudio De Simone for contributing to the rationale of the study and suggesting the dosage of administered oral bacteriotherapy.
References
2. Identifier NCT02669212. Myalgic Encephalomyelitis Chronic Fatigue at the National Institutes of Wellness. Bethesda, MD: National Library of Medicine (U.s.) (2017). [Google Scholar]
three. Newberry FW, Hsieh SY, Wileman T, Carding SR. Does the microbiome and virome contribute to myalgic encephalomyelitis/chronic fatigue syndrome? Clin Sci. (2018) 132:523–42. 10.1042/CS20171330 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
4. Prins JB, van der Meer JW, Bleijenberg Chiliad. Chronic fatigue syndrome. Lancet. (2006) 367:346–55. 10.1016/S0140-6736(06)68073-ii [PubMed] [CrossRef] [Google Scholar]
5. Pall ML, Satterlee JD. Elevated nitric oxide/peroxynitrite mechanism for the common etiology of multiple chemical sensitivity, chronic fatigue syndrome, and posttraumatic stress disorder. Ann North Y Acad Sci. (2001) 933:323–9. 10.1111/j.1749-6632.2001.tb05836.x [PubMed] [CrossRef] [Google Scholar]
6. Pan L, Mu M, Yang P, Sunday Y, Wang R, Yan J, et al. . Clinical characteristics of COVID-nineteen patients with digestive symptoms in Hubei, China: a descriptive, cross-sectional, multicenter study. Am J Gastroenterol. (2020) 115:766–73. x.14309/ajg.0000000000000620 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
vii. Viana SD, Nunes S, Reis F. ACE2 imbalance equally a cardinal player for the poor outcomes in COVID-xix patients with age-related comorbidities - role of gut microbiota dysbiosis. Ageing Res Rev. (2020) 62:101123. x.1016/j.arr.2020.101123 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
viii. Xu Z, Shi L, Wang Y, Zhang J, Huang L, Zhang C, et al. . Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med. (2020) viii:420–2. x.1016/S2213-2600(20)30076-Ten [PMC free article] [PubMed] [CrossRef] [Google Scholar]
9. Gu S, Chen Y, Wu Z, Chen Y, Gao H, Lv L, et al. . Alterations of the gut microbiota in patients with coronavirus affliction 2019 or H1N1 influenza. Clin Infect Dis. (2020) 71:2669–78. 10.1093/cid/ciaa709 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
x. Zuo T, Zhang F, Lui GCY, Yeoh YK, Li AYL, Zhan H, et al. . Alterations in gut microbiota of patients with COVID-19 during time of hospitalization. Gastroenterology. (2020) 159:944–55.e8. ten.1053/j.gastro.2020.05.048 [PMC free commodity] [PubMed] [CrossRef] [Google Scholar]
11. Ceccarelli 1000, Borrazzo C, Pinacchio C, Santinelli L, Innocenti GP, Cavallari EN, et al. . Oral bacteriotherapy in patients with COVID-nineteen: a retrospective cohort report. Front end Nutr. (2021) 7:613928. 10.3389/fnut.2020.613928 [PMC gratis commodity] [PubMed] [CrossRef] [Google Scholar]
12. Ceccarelli G, Scagnolari C, Pugliese F, Mastroianni CM, d'Ettorre G. Probiotics and COVID-19. Lancet Gastroenterol Hepatol. (2020) 5:721–2. 10.1016/S2468-1253(twenty)30196-5 [PMC free commodity] [PubMed] [CrossRef] [Google Scholar]
13. d'Ettorre M, Ceccarelli Thousand, Marazzato Thousand, Campagna G, Pinacchio C, Alessandri F, et al. . Challenges in the direction of SARS-CoV2 infection: the office of oral bacteriotherapy as complementary therapeutic strategy to avoid the progression of COVID-19. Front Med. (2020) 7:389. 10.3389/fmed.2020.00389 [PMC complimentary article] [PubMed] [CrossRef] [Google Scholar]
14. Araimo F, Imperiale C, Tordiglione P, Ceccarelli G, Borrazzo C, Alessandri F, et al. . Ozone as adjuvant support in the treatment of COVID-19: a preliminary report of probiozovid trial. J Med Virol. (2021) 93:2210–20. ten.1002/jmv.26636 [PubMed] [CrossRef] [Google Scholar]
15. Marazzato M, Ceccarelli K, d'Ettorre G. Dysbiosis in SARS-CoV-2-infected patients. Gastroenterology. (2021) 160:2195. 10.1053/j.gastro.2020.12.056 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
17. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. (1987) 40:373–83. x.1016/0021-9681(87)90171-eight [PubMed] [CrossRef] [Google Scholar]
xviii. d'Ettorre Chiliad, Recchia G, Ridolfi M, Siccardi G, Pinacchio C, Innocenti GP, et al. . Analysis of type I IFN response and T cell activation in astringent COVID-nineteen/HIV-one coinfection: a instance report. Medicine. (2020) 99:e21803. 10.1097/MD.0000000000021803 [PMC gratis article] [PubMed] [CrossRef] [Google Scholar]
19. Michielsen HJ, De Vries J, Van Heck GLJ. Psychometric qualities of a brief self-rated fatigue measure: the Fatigue Cess Scale. Psychosom Res. (2003) 54:345–52. x.1016/S0022-3999(02)00392-6 [PubMed] [CrossRef] [Google Scholar]
20. Garcia RJ, Francis L, Dawood 1000, Lai ZW, Faraone SV, Perl A. Attention deficit and hyperactivity disorder scores are elevated and respond to N-acetylcysteine treatment in patients with systemic lupus erythematosus. Arthritis Rheum. (2013) 65:1313–eight. 10.1002/art.37893 [PMC complimentary article] [PubMed] [CrossRef] [Google Scholar]
21. de Kleijn WP, De Vries J, Wijnen PA, Drent Chiliad. Minimal (clinically) important differences for the Fatigue Cess Scale in sarcoidosis. Respir Med. (2011) 105:1388–95. 10.1016/j.rmed.2011.05.004 [PubMed] [CrossRef] [Google Scholar]
22. Morgul E, Bener A, Atak M, Akyel Southward, Aktaş Due south, Bhugra D, et al. . COVID-19 pandemic and psychological fatigue in Turkey. Int J Soc Psychiatry. (2020) 67:128–35. 10.1177/0020764020941889 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
23. El Sayed Southward, Shokry D, Gomaa SM. Post-COVID-19 fatigue and anhedonia: a cross-exclusive study and their correlation to mail-recovery menstruum. Neuropsychopharmacol Rep. (2021) 41:50–5. x.1002/npr2.12154 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
24. Meiboom Southward, Gill D. Modified spin echo method for measuring nuclear relaxation times. Rev Sci Instrum. (1958) 29:668–91. 10.1063/one.1716296 [CrossRef] [Google Scholar]
25. Wishart DS, Tzur D, Knox C, Eisner R, Guo AC, Young N, et al. . HMDB: the human being metabolome database. Nucleic Acids Res. (2007) 35:D521–6. 10.1093/nar/gkl923 [PMC gratis article] [PubMed] [CrossRef] [Google Scholar]
26. Dieterle F, Ross A, Schlotterbeck M, Senn H. Probabilistic caliber normalization as robust method to account for dilution of complex biological mixtures. Application in 1H NMR metabonomics. Anal Chem. (2006) 78:4281–90. x.1021/ac051632c [PubMed] [CrossRef] [Google Scholar]
27. Naviaux RK, Naviaux JC, Li 1000, Bright AT, Alaynick WA, Wang 50, et al. . Metabolic features of chronic fatigue syndrome. Proc Natl Acad Sci USA. (2016) 113:E5472–fourscore. 10.1073/pnas.1607571113 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
28. Rudroff T, Fietsam Ac, Deters JR, Bryant AD, Kamholz J. Post-COVID-xix fatigue: potential contributing factors. Brain Sci. (2020) 10:1012. 10.3390/brainsci10121012 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
29. Carfì A, Bernabei R, Landi F, Gemelli Against COVID-nineteen Post-Acute Care Written report Group. Persistent symptoms in patients after acute COVID-xix. JAMA. (2020) 324:603–five. 10.1001/jama.2020.12603 [PMC gratis article] [PubMed] [CrossRef] [Google Scholar]
30. Dani M, Dirksen A, Taraborrelli P, Torocastro M, Panagopoulos D, Sutton R, et al. . Autonomic dysfunction in "long COVID:" rationale, physiology and management strategies. Clin Med. (2021) 21:e63–seven. 10.7861/clinmed.2020-0896 [PMC costless article] [PubMed] [CrossRef] [Google Scholar]
31. Solomon IH, Normandin E, Bhattacharyya S, Mukerji SS, Keller K, Ali AS, et al. . Neuropathological features of covid-19. N Engl J Med. (2020) 383:989–92. 10.1056/NEJMc2019373 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
32. Al-Dalahmah O, Thakur KT, Nordvig Equally, Prust ML, Roth Westward, Lignelli A, et al. . Neuronophagia and microglial nodules in a SARS-CoV-ii patient with cerebellar hemorrhage. Acta Neuropathol Commun. (2020) eight:147. x.1186/s40478-020-01024-2 [PMC gratuitous article] [PubMed] [CrossRef] [Google Scholar]
33. Butler CA, Popescu Equally, Kitchener EJA, Allendorf DH, Puigdellívol M, Dark-brown GC. Microglial phagocytosis of neurons in neurodegeneration, and its regulation. J Neurochem. (2021) 158:621–39. 10.1111/jnc.15327 [PubMed] [CrossRef] [Google Scholar]
34. Delorme C, Paccoud O, Kas A, Hesters A, Bombois Southward, Shambrook P, et al. . COVID-xix-related encephalopathy: a instance series with encephalon FDG-positron-emission tomography/computed tomography findings. Eur J Neurol. (2020) 27:2651–7. 10.1111/ene.14478 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
35. Carod-Artal FJ. Post-COVID-19 syndrome: epidemiology, diagnostic criteria and pathogenic mechanisms involved. Rev Neurol. (2021) 72:384–96. English, Spanish. 10.33588/rn.7211.2021230 [PubMed] [CrossRef] [Google Scholar]
36. Tsoukalas D, Sarandi E, Georgaki South. The snapshot of metabolic health in evaluating micronutrient status, the risk of infection and clinical outcome of COVID-19. Clin Nutr ESPEN. (2021) 44:173–87. x.1016/j.clnesp.2021.06.011 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
37. Oh HS, Oh SK, Lee JS, Wu C, Lee SJ. Effects of l-arginine on growth hormone and insulin-similar growth factor 1. Food Sci Biotechnol. (2017) 26:1749–54. 10.1007/s10068-017-0236-6 [PMC free commodity] [PubMed] [CrossRef] [Google Scholar]
38. Gardner DG, Shoback D . Greenspan's Basic and Clinical Endocrinology. 10th ed. New York, NY: McGraw-Loma Educational activity; (2018). [Google Scholar]
39. Mizuno Chiliad, Tanaka M, Nozaki South, Yamaguti K, Mizuma H, Sasabe T, et al. . Mental fatigue-induced decrease in levels of several plasma amino acids. J Neural Transm. (2007) 114:555–61. 10.1007/s00702-006-0608-1 [PubMed] [CrossRef] [Google Scholar]
xl. Camic CL, Housh TJ, Zuniga JM, Hendrix CR, Mielke K, Johnson Become, et al. . Effects of arginine-based supplements on the physical working capacity at the fatigue threshold. J Strength Cond Res. (2010) 24:1306–12. ten.1519/JSC.0b013e3181d68816 [PubMed] [CrossRef] [Google Scholar]
41. Chen IF, Wu HJ, Chen CY, Chou KM, Chang CK. Branched-concatenation amino acids, arginine, citrulline alleviate central fatigue after 3 simulated matches in taekwondo athletes: a randomized controlled trial. J Int Soc Sports Nutr. (2016) 13:28. 10.1186/s12970-016-0140-0 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
42. Shi X, Li 10, Li D, Li Y, Song Y, Deng Q, et al. . Hydroxybutyrate activates the NF-κB signaling pathway to promote the expression of pro-inflammatory factors in calf hepatocytes. Cell Physiol Biochem. (2014) 33:920–32. 10.1159/000358664 [PubMed] [CrossRef] [Google Scholar]
43. Li J, Wang X, Chen J, Zuo X, Zhang H, Deng A. COVID-19 infection may cause ketosis and ketoacidosis. Diabetes Obes Metab. (2020) 22:1935–41. 10.1111/dom.14057 [PMC costless article] [PubMed] [CrossRef] [Google Scholar]
44. Baranovicova E, Bobcakova A, Vysehradsky R, Dankova Z, Halasova E, Nosal 5, et al. . The ability to normalise free energy metabolism in avant-garde COVID-19 disease seems to be 1 of the cardinal factors determining the disease progression—a metabolomic NMR report on blood plasma. Appl Sci. (2021) xi:4231. ten.3390/app11094231 [CrossRef] [Google Scholar]
45. Kang P, Liu Y, Zhu H, Zhang J, Shi H, Li Due south, et al. . The effect of dietary asparagine supplementation on free energy metabolism in liver of weaning pigs when challenged with lipopolysaccharide. Asian Australas J Anim Sci. (2018). 31:548–55. 10.5713/ajas.17.0426 [PMC free commodity] [PubMed] [CrossRef] [Google Scholar]
46. Marquezi ML, Roschel HA, dos Santa Costa A, Sawada LA, Lancha AH Jr. Effect of aspartate and asparagine supplementation on fatigue determinants in intense practise. Int J Sport Nutr Exerc Metab. (2003) 13:65–75. x.1123/ijsnem.thirteen.one.65 [PubMed] [CrossRef] [Google Scholar]
47. Ruzzo EK, Capo-Chichi JM, Ben-Zeev B, Chitayat D, Mao H, Pappas AL, et al. . Deficiency of asparagine synthetase causes congenital microcephaly and a progressive grade of encephalopathy. Neuron. (2013) eighty:429–41. 10.1016/j.neuron.2013.08.013 [PMC free commodity] [PubMed] [CrossRef] [Google Scholar]
48. Inoue S, Ikeda H. Differences in plasma amino acrid levels in patients with and without bacterial infection during the early on stage of astute exacerbation of COPD. Int J Chron Obstruct Pulmon Dis. (2019) fourteen:575–83. 10.2147/COPD.S188422 [PMC gratuitous article] [PubMed] [CrossRef] [Google Scholar]
49. Mohr AE, Jäger R, Carpenter KC, et al. . The athletic gut microbiota. J Int Soc Sports Nutr. (2020). 17:24. 10.1186/s12970-020-00353-w [PMC free article] [PubMed] [CrossRef] [Google Scholar]
l. Buscemi L, Blochet C, Toll Chiliad, Magistretti PJ, Lei H, Hirt L. Extended preclinical investigation of lactate for neuroprotection after ischemic stroke. Clin Transl Neurosci. (2020) iv:2514183X20904571. x.1177/2514183X20904571 [CrossRef] [Google Scholar]
51. Papoff P, Ceccarelli Thousand, d'Ettorre Yard, Cerasaro C, Caresta E, Midulla F, et al. . Gut microbial translocation in critically sick children and effects of supplementation with pre- and pro biotics. Int J Microbiol. (2012) 2012:151393. 10.1155/2012/151393 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
52. Oliva A, Miele MC, Di Timoteo F, De Angelis Thousand, Mauro Five, Aronica R, et al. . Persistent systemic microbial translocation and abdominal impairment during coronavirus disease-19. Front end Immunol. (2021) 12:708149. x.3389/fimmu.2021.708149 [PMC gratuitous article] [PubMed] [CrossRef] [Google Scholar]
53. Spagnolello O, Pinacchio C, Santinelli L, Vassalini P, Innocenti GP, De Girolamo Thou, et al. . Targeting microbiome: an culling strategy for fighting SARS-CoV-ii infection. Chemotherapy. (2021) 66:24–32. ten.1159/000515344 [PMC gratis article] [PubMed] [CrossRef] [Google Scholar]
54. Tarsitani 50, Vassalini P, Koukopoulos A, Borrazzo C, Alessi F, Di Nicolantonio C, et al. . Post-traumatic stress disorder among COVID-19 survivors at iii-month follow-up after hospital discharge. J Gen Intern Med. (2021) 36:1702–7. 10.1007/s11606-021-06731-7 [PMC free commodity] [PubMed] [CrossRef] [Google Scholar]
55. d'Ettorre 1000, Ceccarelli Chiliad, Santinelli L, Vassalini P, Innocenti GP, Alessandri F, et al. . Post-traumatic stress symptoms in healthcare workers dealing with the COVID-19 pandemic: a systematic review. Int J Environ Res Public Health. (2021) 18:601. 10.3390/ijerph18020601 [PMC gratis article] [PubMed] [CrossRef] [Google Scholar]
56. Ceccarelli Grand, Alessandri F, Oliva A, Borrazzo C, Dell'Isola S, Ialungo AM, et al. . The role of teicoplanin in the treatment of SARS-CoV-ii infection: a retrospective study in critically ill COVID-19 patients (Tei-COVID report). J Med Virol. (2021) 93:4319–25. x.1002/jmv.26925 [PMC gratis article] [PubMed] [CrossRef] [Google Scholar]
57. Violi F, Ceccarelli Grand, Cangemi R, Alessandri F, D'Ettorre G, Oliva A, et al. . Hypoalbuminemia, coagulopathy, and vascular disease in COVID-nineteen. Circ Res. (2020) 127:400–1. 10.1161/CIRCRESAHA.120.317173 [PubMed] [CrossRef] [Google Scholar]
58. Ceccarelli Grand, Alessandri F, d'Ettorre Thou, Borrazzo C, Spagnolello O, Oliva A, et al. . Is teicoplanin a complementary treatment pick for COVID-nineteen? The question remains. Int J Antimicrob Agents. (2020). 56:106029. ten.1016/j.ijantimicag.2020.106029 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
59. Giovanetti M, Cella East, Benedetti F, Rife Magalis B, Fonseca V, Fabris Southward, et al. . SARS-CoV-2 shifting manual dynamics and subconscious reservoirs potentially limit efficacy of public health interventions in Italy. Commun Biol. (2021) 4:489. 10.1038/s42003-021-02025-0 [PMC gratis commodity] [PubMed] [CrossRef] [Google Scholar]
threescore. Zella D, Giovanetti M, Cella E, Borsetti A, Ciotti Grand, Ceccarelli Thou, et al. . The importance of genomic analysis in cracking the coronavirus pandemic. Expert Rev Mol Diagn. (2021) 21:547–62. ten.1080/14737159.2021.1917998 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
61. Cella E, Benedetti F, Fabris S, Borsetti A, Pezzuto A, Ciotti M, et al. . SARS-CoV-2 lineages and sub-lineages circulating worldwide: a dynamic overview. Chemotherapy. (2021) 66:iii–7. 10.1159/000515340 [PMC free commodity] [PubMed] [CrossRef] [Google Scholar]
62. Giovanetti M, Benedetti F, Campisi K, Ciccozzi A, Fabris S, Ceccarelli Chiliad, et al. . Evolution patterns of SARS-CoV-2: snapshot on its genome variants. Biochem Biophys Res Commun. (2021) 538:88–91. x.1016/j.bbrc.2020.ten.102 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
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