HLA-DRB1 locus. Blood samples collected sequentially post-transplantation from a cohort of lung recipients were used to obtain proof-of-principle for the validity of the assay, correlating results with transbronchial biopsies and lung capacity tests. The results revealed an increase in dd-cfDNA during the first 2 weeks after transplantation related to ischemia-reperfusion injury . In the absence of complications, donor DNA levels stabilized, while increasing again during acute rejection episodes . Respiratory tract infections were also involved in the release of dd-cfDNA , with a positive correlation with C-reactive protein levels. Overall, the dd-cfDNA percentages were inversely correlated with the lung function values measured by spirometry. These results confirm the value of dd-cfDNA determination during post-transplant follow-up to monitor acute rejection in lung recipients, achieved using a rapid and inexpensive approach based on the HLA mismatch between donor and recipient.Despite advances in immunosuppression therapy, acute rejection remains the leading cause of graft dysfunction in lung transplant recipients. Donor-derived cell-free DNA is increasingly being considered as a valuable biomarker of acute rejection in several solid organ transplants. We present a technically improved molecular method based on digital PCR that targets the mismatch between the recipient and donor at the   Affecting almost one patient in three between discharge and 1-year follow up, acute rejection (AR) represents one of the most common causes of allograft dysfunction after lung transplantation -4. In coBronchoscopy with associated transbronchial lung biopsy (TBB) and cytology are typically used to monitor acute cellular rejection (ACR), whereas analysis of donor-specific antibodies (DSA) in recipients’ sera detects antibody-mediated rejection (AMR). However, even if both techniques are currently the “gold standard” in rejection monitoring, they can be poorly informative. First, TBB is invasive with possible complications, whereas DSA only detects anti-HLA antibodies, limiting their clinical impact and stressing the need for additional tools in post-transplant monitoring , 9-11.Donor-derived cell-free DNA (dd-cfDNA) has recently been proposed as a biomarker for graft injury . DNA is Donor DNA can be distinguished from the recipient DNA by using single nucleotide polymorphisms (SNPs). The most sensitive techniques are based on the simultaneous evaluation of dozens of SNPs using next-generation sequencing (NGS), guaranteeing high accuracy , 14, 21.HLA-DRB1 locus, which is routinely analyzed before transplantation. The assay, which is based on a droplet digital PCR technique, is more rapid, technically easier, and significantly less expensive than NGS-based analysis of dozens of SNPs. The results obtained in a cohort of heart-transplanted patients show that this assay is effective in identifying patients undergoing rejection, with 64.2% sensitivity and 70.8% specificity  and used for analysis.This study was approved by the Ethics Committee of Città della Salute e della Scienza University Hospital of Turin . The enrolled patients underwent lung transplantation from 1 July 2019, to 31 March 2021, and provided written informed consent. Exclusion criteria were refusal or inability to provide informed consent, any form of substance abuse, psychiatric disorders, or conditions that could complicate communication between the investigator and the patient. Patient data were anonymized using an alphanumeric ID and all sensitive information was conserved on the RedCap online platform . Donor HLA loci were assessed by real-time PCR using a LinkSeq HLA typing kit . Donor and recipient pairs sharing the same ex vivo lung perfusion (EVLP) prior to transplantation, performed according to the Toronto technique  requiring mechanical ventilation and/or extracorporeal lung support with extracorporeal membrane oxygenation (ECMO) . The graechnique . Lungs fechnique . Lung trAll patients were admitted to a dedicated intensive care unit ICU, allowing controlled ventilator weaning. Primary graft dysfunction (PGD), defined according to the International Society of Heart and Lung Transplantation (ISHLT) guidelines , was evahttp://www.progettoeccellenzateseo.unito.it/) until further processing. Cell-free DNA (cfDNA) was extracted from 1 ml of plasma using MagMAX Cell free DNA isolation kit  and stored at −20°C until analysis.Plasma samples were collected using PAXgene Blood ccfDNA tubes . Blood samples were collected weekly during hospitalization following transplantation, and then every time the patients underwent medical examinations or transbronchial biopsies. A total of 372 plasma samples were obtained from 30 patients . Plasma was separated by centrifugation  and stored at −80°C in the Teseo Biobank of the Department of Medical Sciences of University of Turin  designed to target the HLA-DRB1 gene. A list of the available probes is reported in Two nanograms of cfDNA was amplified using Sso PreAmp Assays  to enrich the number of Surveillance lung allograft bronchoscopy and TBBs were performed at 4, 8, 12- and 18-month post-transplant. In addition, bronchoscopy and TBB were performed whenever there was clinical suspicion of rejection or pulmonary infection. The Working Formulation of the ISHLT criteria  was applSixty serum samples were collected at the time of liquid biopsy during posttransplant management. Sera were assessed for DSA by Luminex using commercially available SAB kits , and the results were expressed as mean fluorescence intensity . All the patients were DSA-negative at the time of transplantation. In addition, all patients had a negative cross-match, as determined by flow cytometry  testing of sera for the presence of IgG and IgM antibodies against donor T and B lymphocytes isolated from peripheral blood samples.p-values lower than 0.05 were considered as statistically significant. The correlation between two continuous variables was analyzed using the nonparametric Spearman test. Receiver operating characteristic (ROC) curves were calculated using the Wilson-Braun method. All statistical analyses were performed using GraphPad Prism version8.0.2.Dd-cfDNA quantification is reported as mean ± standard deviation (SD). Differences between mean values in each group were compared using the Mann-Whitney nonparametric test, since data resulted to be not normally distributed using the Shapiro Wilk test. HLA-DRB1 FAM probes have been assessed previously assessed  and quantified using the FAM-only probe method described before  or combined transplant recipients . During the first 2 weeks after transplantation, dd-cfDNA peaked , in line with previous results, demonstrating organ damage due to ischemia-reperfusion . The mean dd-cfDNA percentages obtained at all times differed significantly between monopulmonary, bipulmonary, and combined transplant recipients, reflecting the number of donor cells present in the recipient . In facterfusion . In patip < 0.0001, p = 0.03), whereas A2 rejection caused a stronger increase  scored positive for cellular rejection. Nine biopsies were classified as minimal grade (indicated as A1) and 11 as mild grade  and Klebsiella pneumoniae , while Cytomegalovirus  was the most common. Dd-cfDNA levels significantly increased during infectious episodes compared to stable conditions, with a slightly stronger increase observed during viral  and mixed infections  with C-reactive protein (CRP) blood levels, as determined by studying dd-cfDNA levels in 104 samples from 28 patients and collected close to CRP measurements during infection episodes , viruses in 23 (76.7%), and fungi in 11 (36.7%) cases, with specimens from eight patients (26.7%) showing mixed contamination . Among tepisodes . One timr = −0.26, p = 0.0054).Lung transplant function was assessed using spirometry. FEV1 was quantified using recipient characteristics for the normative equation and considered a respiratory function measure. A total of 114 liquid biopsies were collected close to the spirometry tests, and dd-cfDNA quantification was correlated with relative FEV1 percentages. As shown in p < 0.0001, Receiver operating characteristic (ROC) analysis was performed to assess the performance of this method. The area under the curve (AUC) was 0.87,  were fully matched at the HLA-DRB1 locus. These donor-recipient pairs were excluded from our assay, as there would be no genetic differences to monitor. However, it should be noted that if HLA-DRB1 is matched, rejection occurs less frequently, and survival rates are higher (HLA-DRB1 alleles and showed that it could identify rejection episodes in a cohort of heart-transplanted patients (Donor DNA can be distinguished from the recipient’s exploitation of any type of genetic polymorphism spread across the genetic code. e higher -40(Supple higher . We prevpatients . The curCompared to NGS, droplet digital PCR is more rapid, with results available 24 h after blood draw, feasible, and significantly cheaper. Using our optimized method, the cost of reagents for a single reaction is in the range of 80 euros, which is comparable to that of the Luminex assay for DSA monitoring , 23, 41.The mean donor DNA percentages showed a clear correlation with the amount of donor tissue transplanted; bilateral transplant samples showed values approximately double those of single-lung transplants. Moreover, samples from patients who received more than one organ presented a significantly higher amount of dd-cfDNA, reflecting the higher number of donor cells inside the recipient. All samples collected in the first 2 weeks after transplantation demonstrated high levels of dd-cfDNA, consistent with ischemia-reperfusion injury and in line with previous data reported in the literature , 17, 33.Donor DNA kinetics exhibited low percentages in samples collected from patients in stable conditions , whereasMorphological and immunohistochemical evaluations did not report evidence of AMR in any TBB collected during the follow-up period, even though seven recipients developed DSA. Although we observed a significant difference between DSA-positive samples and stable conditions, the reduced number of samples do not allow any speculation about the value of dd-cfDNA as a biomarker of AMR.Remarkably, dd-cfDNA also increased in the presence of infection, in keeping with the notion that it is a marker of graft damage, independent of the cause . TherefoIn conclusion, we present an improved molecular method to monitor lung-transplant outcomes that allows rapid rejection identification through dd-cfDNA quantification at high costs. Larger clinical studies are needed to determine the best way to integrate this biomarker in the routine post-transplant management of lung transplant recipients to improve graft survival and patients’ quality of life.


Attributing individual deaths to extreme heat events (EHE) in Canada and elsewhere is important for understanding the risk factors, protective interventions, and burden of mortality associated with climate change. However, there is currently no single mechanism for identifying individual deaths due to EHE and different agencies have taken different approaches, including (1) vital statistics coding based on medical certificates of death, (2) probabilistic methods, and (3) enhanced surveillance. The 2018 EHE in Montréal provides an excellent case study to compare EHE deaths identified by these different approaches. There were 353 deaths recorded in the vital statistics data over an 8-day period, of which 102 were potentially attributed to the EHE by at least one approach and 251 were not attributed by any approach. Only nine of the 102 deaths were attributed to the EHE by all three approaches, 23 were attributed by two approaches, and 70 were attributed by only one approach. Given that there were approximately 50 excess deaths during the EHE, it remains unclear exactly which of the total 353 deaths should be attributed to the extreme temperatures. These results highlight the need for a more systematic and cooperative approach to EHE mortality in Canada, which will continue to increase as the climate changes. For example, the 2009 EHE in greater Vancouver was associated with approximately 110 excess deaths over a 7-day period  code J09.X2. In comparison, only one of the 411 deaths during the EHE was directly attributed the ICD-10 code X30, indicating exposure to excessive natural heat. As such, we estimate that approximately 110 people died because of the EHE, but we cannot identify the specific individuals. National vital statistics data indicate that an average of only 16 deaths per year are coded as X30  are often referenced as a Attributing individual deaths to EHE is important for three reasons. First, it is difficult to narrow down the specific risk factors for hot weather mortality when retrospective analyses also include many expected deaths over the EHE period. We generally know that social isolation, economic status, lack of greenspace, age, comorbidities, and some drugs are associated with increased risk, but more refined data would lead to more specific conclusions  developed a statistical approach to separate excess deaths from expected deaths, which is described in detail elsewhere , population density, neighbourhood deprivation, and surrounding residential greenness  developed an enhanced surveillance protocol for identifying deaths attributable to extreme temperatures . Together, these methods identified a total of 102 individual deaths that may have been attributable to the EHE. However, only 32 of the deaths were identified by more than one approach while 70 were identified by a single approach  were compared with the unattributed 251 deaths (10.8% at home), which is a hallmark of EHE mortality  sent a reminder to clinicians that any death with extreme heat as a possible contributor should be reported for investigation. Soon after the event, the BCCDC estimated 740 excess deaths during the EHE (Henderson et al., More generally, Environment and Climate Change Canada provides hot weather notifications across the country. Such notifications could be used to trigger regional public health reminders for clinicians and coroners to consider the role of high temperatures in any deaths they attend. If heat may have been a causal or contributing factor, noting it on the certificate of death creates the opportunity for future review and appropriate attribution. A death simply cannot be coded as X30 or T67 by vital statistics agencies unless this information is included on the certificate of death they receive. Coroners, clinicians, public health, vital statistics, and other agencies could then work together after the event to review specific cases, especially those where the role of heat is less clear. This type of systematic and cooperative approach would facilitate improved understanding of EHE and the burden of mortality, risk factors, and potentially effective interventions in Canada.


SUPERMAN (SUP) gene was described in Arabidopsis thaliana over 30 years ago. SUP was classified as a cadastral gene required to maintain the boundaries between reproductive organs, thus controlling stamen and carpel number in flowers. We summarize the information on the characterization of SUP orthologs in plant species other than Arabidopsis, focusing on the findings for the MtSUP, the ortholog in the legume Medicago truncatula. M. truncatula has been widely used as a model system to study the distinctive developmental traits of this family of plants, such as the existence of compound inflorescence and complex floral development. MtSUP participates in the complex genetic network controlling these developmental processes in legumes, sharing conserved functions with SUP. However, transcriptional divergence between SUP and MtSUP provided context-specific novel functions for a SUPERMAN ortholog in a legume species. MtSUP controls the number of flowers per inflorescence and the number of petals, stamens and carpels regulating the determinacy of ephemeral meristems that are unique in legumes. Results obtained in M. truncatula provided new insights to the knowledge of compound inflorescence and flower development in legumes. Since legumes are valuable crop species worldwide, with high nutritional value and important roles in sustainable agriculture and food security, new information on the genetic control of their compound inflorescence and floral development could be used for plant breeding.The  SUPERMAN (SUP) gene was assigned , petals (W2), stamens (W3) and carpel/s (W4), . The numassigned .SUP is a transcriptional repressor, extensively studied in Arabidopsis thaliana, that encodes a plant-specific EPF-like protein with one Cys2-His2 zinc finger DNA binding domain and a C-terminus EAR-like (DLELRL) motif (SUP at the boundary between W3 and W4 (sup-1 mutant (APETALA3 (AP3) and PISTILLATA (PI) expression closer to the centre of the floral meristem   at the early stages of flower development.L) motif . The spe3 and W4  led to i1 mutant  was initmeristem . Initial(flo-10) . Howeverunctions . SUP is SUP is required for the correct timing to turn off WUSCHEL (WUS) from the floral meristem centre (FMC), thus controlling the floral meristem termination. WUS activity is required for the stem cell division at the floral meristem centre, a prolonged expression of WUS would lead to a delayed floral meristem termination, and more floral organs could be produced. However, SUP and WUS do not show an overlapping spatial expression and, in sup mutants, WUS expression is prolonged . By contrast, the increased number of stamens and carpels in the sup-5 mutant  differentiates a secondary inflorescence meristem (I2). The existence of the I2 is linked to the compound inflorescence development and is a distinctive feature compared to Arabidopsis, which produces a unique inflorescence meristem (IM) before differentiating the floral meristem (FM) (VEGETATIVE1 (VEG1) in Pisum sativum and MtFRUITFULLc (MtFULc) in M. truncatula  and MtAPETALA1 (MtAP1) or MtPROLIFERATING INFLORESCENCE MERISTEM (MtPIM), respectively (M. truncatula (Most legumes show complex raceme inflorescences with more than one branching. In the model legume tem (FM) . The I2 uncatula . It has L family . The perL family . In the ectively . Their suncatula .M. truncatula  gene was described as the SUP ortholog in rice  allele  or plants with complex inflorescence  could help to understand SUP-like genes implications in the development of higher order meristems (i.e. I2). Alternatively, they could show the emergence of new functions for transcription factors when they are expressed in species with different architectures. Recently, the SINGLE FLOWER (SFL) gene, a MYB transcription factor expressed in the I2, was shown to perform a similar role to MtSUP in chickpea (SUP-like genes in other crops should be studied to determine their possible roles in inflorescence development.The functional study of chickpea . Multiflchickpea . Howeverchickpea . In lineER, AR and LC wrote the manuscript and RH, CG-M and JB contributed with valuable comments during the manuscript writing. All authors contributed to the article and approved the submitted version.


Higher HRR (≥1)  was independently associated with the CNS co-infection after adjusting for covariates. No significant nonlinear association was found between the HRR and CNS co-infection in the multivariate spline regression (p > 0.05) and a positive relationship was found between the HRR and CNS co-infection when the HRR was ≥0.78. Higher HRR was associated with an increased risk of CNS co-infection in HIV-1-positive patients. The relationship between the HRR and CNS co-infection may be related to the BBB disturbance and warrants further investigation with a large, longitudinal cohort.Cerebrospinal fluid (CSF) human immunodeficiency virus-1 (HIV-1) ribonucleic acid (RNA) at higher levels than in plasma has been observed in HIV-1-positive patients and defined as CSF/plasma discordance or CSF escape. Discordance is particularly seen in untreated patients with antiretroviral agents. Quantitative data regarding its association with blood–brain barrier (BBB) damage and intracranial co-infection with other pathogens are limited. Therefore, we used the CSF to plasma HIV-1 RNA ratio (HRR) to determine its relation to central nervous system (CNS) co-infection in HIV-1-positive treatment-naïve individuals. We retrospectively recruited the subjects with HIV-1-positive and potential neurological deficits. A lumbar puncture was performed before the antiretroviral therapy. The paired CSF/plasma HIV-1 RNA samples were analyzed. Univariate and multivariate logistic regression models and multiple spine regression analyses were performed to assess the association between the HRR and CNS co-infection. A total of 195 patients with 78% males (median age: 49 years) were included in this study, of whom 98 (50.2%) had CNS co-infection with other pathogens. The receiver-operating characteristic curve analysis showed that the optimal cutoff value for the HRR to predict the CNS co-infection was 1.00. Higher HRR (≥1) was significantly associated with tuberculous meningitis (OR 6.50, 95% CI 2.08–20.25,  The central nervous system (CNS) is vulnerable to be affected in patients with positive-human immunodeficiency virus-1 (HIV-1) ,3. The HGenerally, the integrity of the BBB maintains the viral load, and thus HIV-1 RNA, in plasma higher than CSF . HoweverA proportion of HIV-1-positive treatment-naive patients (HPTNPs) shows neurological symptoms. HIV-1 could attack the immune cells and frequently compromise the integrity of the BBB. The BBB impairment is common in HIV-1-positive patients, which increases the risk of opportunistic co-infection in the central nervous system, such as tuberculous meningitis and cryptococcal meningitis ,17,18. TThe CSF/plasma ratio of HIV-1-RNA (HRR) of >1 was labeled as a discordance in a few previous studies, but little is known about the effects of the HRR on the AIDS complicated with the CNS co-infection . TherefoThis is a cross-sectional study which retrospectively collected data of HIV-1 infected patients who met the diagnostic criteria and admitted to the Chongqing public health medical center from January 2020 to June 2020 for this study. The HIV-1-positive diagnosis was in accordance with the European AIDS Clinical Society (EACS) Guidelines 2020 . All theThe detailed clinical data such as demographic information, laboratory tests results, and different types of CNS co-infection were collected for analysis.HIV-1 RNA detection: 10 mL of venous blood was collected using an EDTA anticoagulant tube, centrifuged to separate the plasma, and then frozen to −80 ℃ in an ultra-freezer. The plasma HIV-1-RNA level was quantitatively detected using an automatic real-time fluorescence quantitative detector . The lowest detection down-line value was 20 copies/mL.The CD4+T lymphocyte detection: A 2 mL venous blood was collected by using an EDTA anticoagulant tube, and the number of CD4+T cells in the samples was analyzed by using a Trucount absolute counting tube in a flow cytometer . The cells in the CSF were counted and classified using SYSMEX XE-4000 . The CSF protein and glucose were detected using colorimetry, and the CSF chloride was detected using the direct electrode method. All tests are carried out in the Chongqing public health medical center clinical laboratory.Tuberculous meningitis: (i) The CSF with lymphocytic pleocytosis, low glucose, and elevated protein; (ii) the brain CT/MRI showing enhancement of the meninges and the periphery with the tuberculoma lesions; (iii) the culture or CSF smear or CSF-PCR; (iv) the successful response by a specific treatment. The diagnosis complied with (iii) or any two of the other three criteria.Toxoplasma meningitis should have been consistent at the same time: (i) progressive neurological deficits; (ii) contrast-enhancing mass lesion(s) on the CT/MRI; (iii) successful response within 2 weeks of the specific treatment.Cryptococcal meningitis needed to meet any one of these criteria: (i) visualizing the fungus in the CSF using India ink; (ii) detecting the cryptococcal antigen by the latex agglutination assay in the CSF; (iii) positive CSF culture for C. neoformans.6/L; CSF protein of ≥500 mg/L; (v) CSF TPPA positive.Diagnosis of neurosyphilis should have been consistent at the same time: (i) epidemiological history; (ii) clinical manifestations; (iii) positive serum TPPA; (iv) CSF leukocyte count of ≥20 × 10Viral encephalitis included CMV  and JC virus (JCV). Diagnosis of CMV encephalitis via clinical appearance, positive PCR in CSF, and other pathology was excluded. Diagnosis of Progressive Multifocal Leukoencephalopathy, which is caused by JCV, depends on the evidence of JCV-deoxyribonucleic acid (JCV-DNA) in CSF and compatible clinical-radiological picture.Multiple co-infections referred to the combination of more than two types of co-infectionDetection of co-infectious pathogens mentioned in our manuscript by Next-Generation Sequencing (NGS) testing.The CNS co-infection was identified from the discharge medical records. Diagnosis criteria were as follows ,26,27:TuThe continuous variables were tested for normality at first. The mean ± standard deviation were used to describe the continuous variables with the normal distribution. The median with the interquartile range was used to describe variables with non-normal distribution. The percentages were used to describe the categorical variables. The chi-square test and the Mann–Whitney U test were performed for the comparisons of variables between different subgroups as appropriate.p < 0.1 in the univariate analysis were considered to be included in the multivariate logistic regression models. The odds ratios (ORs), as well as the corresponding 95% confidence interval (CI) values, were reported. The restricted cubic splines were used to examine the shape of the association between the X and Y with three knots .The receiver operating characteristics (ROC) curve analysis was used to identify the optimal cut-off value for the continuous HRR to predict the ratio of the CSF/plasma. Then, the HRR was dichotomized in accordance with its optimal cutoff value and tested using a multivariate logistic regression model. The univariate and multivariate logistic regression models were adopted to examine the association between the HRR and the CNS co-infection group. The variables with the p-values less than 0.05 were considered as a significant difference.All the analyses were performed with the SPSS 19.0  and Stata 15.0  software. The A total of 195  HPTNPs were included in this study, of whom 98 (50.2%) were identified as having CNS co-infection. Among the patients with CNS co-infection, 30 (30.6%) manifested tuberculous meningitis (TBM), 18 (18.3%) manifested cryptococcus meningitis (CM), 14 (14.2%) manifested viral encephalitis (VE), 11 (11.2%) exhibited toxoplasma meningitis (TM), 6 (6.1%) showed neurosyphilis (NS), and 19 (19.3%) showed multiple co-infection (MI).p < 0.001).The baseline characteristics are presented in p < 0.001] ; < 0.001] . The HRRp = 0.001), tuberculous meningitis , cryptococcus meningitis , and multiple co-infection .p = 0.032), higher HIV-1 RNA in CSF , and lower CD4+ cell count  were significantly associated with increased risk of CNS co-infection. Furthermore, we adopted HRR levels in the model as continuous data after potential confounders were adjusted in p > 0.05), suggesting a linear relationship between the HRR and CNS co-infection. In addition, a positive relationship was found between the HRR and CNS co-infection when the HRR was ≥0.78.In our cohort, we provided preliminary evidence about the relationship between HRR and CNS co-infection in HIV-1 positive treatment-naïve patients. Due to the different research objectives, the definitions of discordance/escape have yielded inconclusive standards . Rawson Investigating the mechanisms and risk factors associated with CSF/plasma HIV-1 discordance is useful for choosing an appropriate systemic intervention. This study contributes to the emerging literature and provides further evidence that higher HRR was independently associated with an increased risk of CNS co-infection in HPTNPs. Although there have been several previous studies about discordance, they often described the poor patient prognosis. Anderson AM revealed that high CSF HIV-1 RNA was correlated with active CNS viral replication in the HIV-1-associated neurocognitive disorder (HAND) ,32. DravIn addition to the higher HRR being associated with the CNS co-infection, we also observed that the higher absolute value of the HIV-1 RNA in the CSF and low CD4+ cell counts were also associated with the CNS co-infection in the HIV-1-infected patients; the result is consistent with another study . At the The present study had several limitations. First, we did not measure the dynamic changes of the HRR before and after the ART. Whether the reduced HRR is associated with CNS co-infection improvement needs further investigation. Second, although we adjusted the cases with CNS co-infection, due to the small sample size, we could not conduct the subgroup multivariate analyses. Third, due to the cross-sectional design, we could not assess the causation. Further longitudinal studies are needed to assess its effect for long-term outcomes. To the best of our knowledge, our study is one of the reports of a large number of neuro-symptomatic CSF/plasma HIV-1 discordance cases. Larger sample size and longitudinal follow-up are needed to further clarify the value of the HRR in the clinical diagnosis and treatment.


Retinol-binding protein 4 (RBP4) has been implicated in insulin resistance in rodents and humans with obesity and T2DM, making it a potential biomarker for the early diagnosis of T2DM. However, diagnostic tools for low-level detection of RBP4 are still lagging behind. Therefore, there is an urgent need for the development of T2DM diagnostics that are rapid, cost-effective and that can be used at the point-of-care (POC). Recently, nano-enabled biosensors integrating highly selective optical detection techniques and specificity of aptamers have been widely developed for the rapid detection of various targets. This study reports on the development of a rapid gold nanoparticles (AuNPs)-based aptasensor for the detection of RBP4. The retinol-binding protein aptamer (RBP-A) is adsorbed on the surface of the AuNPs through van der Waals and hydrophobic interactions, stabilizing the AuNPs against sodium chloride (NaCl)-induced aggregation. Upon the addition of RBP4, the RBP-A binds to RBP4 and detaches from the surface of the AuNPs, leaving the AuNPs unprotected. Addition of NaCl causes aggregation of AuNPs, leading to a visible colour change of the AuNPs solution from ruby red to purple/blue. The test result was available within 5 min and the assay had a limit of detection of 90.76 ± 2.81 nM. This study demonstrates the successful development of a simple yet effective, specific, and colorimetric rapid assay for RBP4 detection.  Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease with debilitating effects on human health. It is a growing epidemic, that affects over 536.6 million adults worldwide . If undiRetinol-binding protein 4 (RBP4), an adipokine responsible for obesity-induced insulin resistance, has been identified as one of the reliable biomarkers for the early diagnosis of T2DM ,6,7,8,9.The detection of RBP4 is usually performed through different biotechnological assays, such as enzyme-linked immunosorbent assay (ELISA) and Western blot ,11,12, wLee et al. reported on the development of the first RBP-aptamer (RBP-A) and its application in a surface plasmon resonance (SPR) biosensor for the detection of RBP4 in serum. The SPR biosensor specifically detected RBP4 and had a limit of detection of 75 nM (1.58 µg/mL), which is sufficiently sensitive to probe for RBP4 in the serum of people who are at risk of developing T2DM . For insColorimetric assays have been extensively used for the rapid detection of various diseases due to their simplicity, quick response, and high sensitivity ,29,30,314·3H2O), sodium chloride (NaCl), and sodium citrate were purchased from Sigma-Aldrich . Purified Milli-Q water was used in all experiments . All the chemicals were of analytical grade.Retinol-binding protein aptamer (RBP-A) 5′-ATA CCA GCT TAT TCA ATT ACA GTA GTG AGG GGT CC GTC GTG GGG TAG TTG GGT CGT GGA GAT AGT AAG TGC AAT CT-3′ , was synv/v) HNO3: HCl), then thoroughly washed with distilled water (dH2O) and dried overnight at 70 °C in an oven. AuNPs were prepared via the reduction of HAuCl4·3H2O using sodium citrate as described by Stiolica et al. [2 20 field-emission gun (FEG) HRTEM  operated in bright field mode at an accelerating voltage of 200 kV.All glassware used for the preparation of AuNPs was first immersed thoroughly in aqua regia . The samples were incubated at 25 °C for 5 min and observed for colour change. The UV–vis spectra were measured using a plate reader, and the absorbance ratios (A650/A520) were calculated to determine the aggregation percentage of the AuNPs [AuNPs are highly reactive and aggregate easily in the presence of salts; therefore, it is important to monitor the salt-induced AuNPs aggregation percentage for the development of a colorimetric aptasensor ,45,46. The AuNPs . The exp2O. Then, 25 μL of different concentrations of RBP4  were added into the aptasensor, mixed thoroughly, and incubated for another 5 min at 25 °C, and observed for colour change This was followed by the addition of 6 μL of 1 M NaCl solution  and incubation at 25 °C for 5 min. The UV–vis spectra were measured using a plate reader and the absorbance ratios (A650/A520) were calculated to determine the aggregation percentage of the AuNPs. The experiment was performed in triplicate and the average absorbance ratios were calculated and used to plot the linear curve.For the detection of RBP4, 600 μL of 50 nM RBP-A and 1.08 mL of AuNPs were added to a 2 mL tube, mixed well, and incubated overnight at 25 °C. Subsequently, 50 μL of the aptasensor was added into the 96-well microtiter plate containing 25 µL of dH2O. Then, 25 μL of 250 nM RBP4, A2MG, leptin and BSA were added into the aptasensor, mixed thoroughly, and incubated for another 5 min at 25 °C and observed for colour change. This was followed by the addition of 6 μL of 1 M NaCl solution  and incubation at 25 °C for 5 min. A water sample was used as a blank. The UV–vis spectra were measured using a plate reader and the absorbance ratios (A650/A520) were calculated to determine the aggregation percentage of the AuNPs. The experiment was performed in triplicate and the average absorbance ratios were calculated and used to plot bar graphs.To evaluate the specificity of the RBP-A-aptasensor, 50 μL of the aptasensor was added into the 96-well microtiter plate, containing 25 µL of dHAuNPs-based aptasensors have been widely applied in the detection of various targets including chemical compounds, proteins, pesticides, toxins, and viruses ,48,49,50The synthesized AuNPs had an SPR peak at 519 nm a, indicaThe principles of the AuNPs-based RBP-A-aptasensor for the detection of RBP4 is illustrated in The compatibility of the AuNPs-based RBP-A-aptasensor for the detection of RBP4 was validated using four techniques: UV–vis spectroscopy, TEM, ζ- potential, and FTIR. As shown in The ζ- potential was also measured to monitor the changes on the AuNPs’ surface during the development of the aptasensor and when the aptasensor was incubated with RBP4 c. AuNPs −1. The peak at 3305.81 cm−1 is attributed to the stretching vibration of OH and NH2. The peaks at 1400.82 cm−1 and 1638.55 cm−1 are attributed to the carboxylate symmetric and asymmetric stretching bonds of the carboxylate group (COO−) in citrate ions [−1 is attributed to the S-H group on the AuNPs [−1) were observed in RBP-A-AuNPs conjugate spectra which were absent in the spectrum for the AuNPs. The peak at 1064.23 cm−1 is attributed to the symmetric C=O stretching band of the phosphate backbone and the peak at 723.88 cm−1 is attributed to the C–H out of plane base vibration of the RBP-A [−1. This peak was also visible in the AuNPs, further supporting the assertion that RBP-A was bound to RBP4 and detached from the AuNPs.Finally, FTIR (PerkinElmer Spectrum One FTIR spectrophotometer) analysis was carried out to monitor elemental changes to the AuNPs during the development of the aptasensor and when the aptasensor was incubated with RBP4 d. The FTate ions , respecthe AuNPs , furtherhe RBP-A , indicat+ and Cl− ions destroyed the ionic environment and led to the aggregation of AuNPs in the absence of aptamers [The flocculation assay was used to determine the stability of the AuNPs-based RBP-A-aptasensor in the presence of different concentrations of NaCl. From aptamers . In contThe sensitivity of the AuNPs-based RBP-A-aptasensor for the detection of RBP4, under the optimized experimental conditions (50 nM RBP-A and 60 mM NaCl), was assessed by incubation with different concentrations of RBP4 and by calculating the absorbance ratios (A650/A520) to evaluate the aggregation of the AuNPs. Over the years, there has been a greater focus on the development of colorimetric aptasensors due to their simplicity, which is based on the visual detection of a test result. However, they frequently have sensitivity and reproducibility issues; thus, the reproducibility of the RBP-A-aptasensor was evaluated. The assay was performed in triplicate (at a concentration of 250 nM), on three separate days. As shown in The specificity of the developed RBP-A-aptasensor for the detection of RBP4 was evaluated against two diabetes-related biomarkers (A2MG and leptin) and one serum-abundant protein (BSA). The proteins (at a concentration of 250 nM) were individually incubated with the RBP-A-aptasensor, and the absorbance ratios of A620/A520 were calculated . A waterSince the identification of RBP-A in 2008 by Lee et al. , there hThe incubation time of the aptasensor with RBP4 was also evaluated. This was carried out by incubating RBP4 (at a concentration of 250 nM) with the aptasensor for different time periods (0–30 min), followed by the UV–vis measurements and calculation of the absorbance ratios (A620/A520) to determine the degree of aggregation of the AuNPs . The resIn this study, a label-free colorimetric aptasensor for the detection of RBP4 using ssDNA aptamer and unmodified AuNPs was successfully developed. The assay is based on colour change from ruby red to blue/purple due to the binding of RBP-A to RBP4, which leaves AuNPs exposed to the phenomenon of salt-induced AuNP aggregation. The assay was sensitive, with an LOD of 90.76 ± 2.81 nM. Further development using clinical samples on non-diabetic and diabetic patients is required to assess the utility of the aptasensor for the early detection of T2DM.


BackgroundCoronavirus disease 2019 (COVID-19) infection is associated with troponin elevation, which is associated with increased mortality. However, it is not clear if troponin elevation is independently linked to increased mortality in COVID-19 patients. Although there is considerable literature on risk factors for mortality in COVID-19-associated myocardial injury, the Global Registry of Acute Coronary Events (GRACE), Thrombolysis in Myocardial Infarction (TIMI), and Sequential Organ Failure Assessment (SOFA) scores have not been studied in COVID-19-related myocardial injury. This data is important in risk-stratifying COVID-19 myocardial injury patients.MethodologyOf the 1,500 COVID-19 patients admitted to our hospitals, 217 patients who had troponin levels measured were included. Key variables were collected manually, and univariate and multivariate cox regression analysis was done to determine the predictors of mortality in COVID-19-associated myocardial injury. The differences in clinical profiles and outcomes of COVID-19 patients with and without troponin elevation were compared.ResultsMortality was 26.5% in the normal troponin group and 54.6% in the elevated troponin group. Patients with elevated troponins had increased frequency of hypotension (p = 0.01), oxygen support (p < 0.01), low absolute lymphocyte (p < 0.01), elevated blood urea nitrogen (p < 0.01), higher C-reactive protein (p < 0.01), higher D-dimer (p < 0.01), higher lactic acid (p < 0.01), and higher Quick SOFA (qSOFA), SOFA, TIMI, and GRACE . On univariate cox regression, troponin elevation (hazard ratio (HR) = 1.85, 95% confidence interval (CI) = 1.18-2.88, p < 0.01), TIMI score >3 , and GRACE score >140  were highly associated with mortality, whereas cardiovascular disease  and cardiovascular risk factors  were not. After adjusting for age, use of a non-rebreather or high-flow nasal cannula, hemoglobin <8.5 g/dL, suspected or confirmed source of infection, and qSOFA and SOFA scores  were independently associated with mortality, whereas troponin , TIMI score  and GRACE scores  were not associated with mortality.ConclusionsOur study shows that troponin, GRACE score, and TIMI score are not independent predictors of mortality in COVID-19 myocardial injury. This may be because troponin elevation in COVID-19 patients may be related to demand ischemia rather than acute coronary syndrome-related. This was shown by the association of troponin with a higher degree of systemic inflammation and end-organ dysfunction. Therefore, we recommend SOFA scores in risk-stratifying COVID-19 patients with myocardial injury. Coronavirus disease 2019 (COVID-19) is a pandemic caused by a novel strain of coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Several studies have shown that myocardial injury is commonly seen in COVID-19 and is associated with a worse prognosis . SeveralHowever, studies have reported conflicting data on whether troponin is independently associated with mortality -9. The GThis article was previously presented as a meeting abstract at the 2021 AHA Annual Scientific Meeting on November 8, 2021.The electronic medical records of adult patients who were symptomatic for COVID-19 and tested positive for COVID-19 (SARS-CoV-2 reverse transcription polymerase chain reaction positive) from two centers from March 1, 2020, to December 31, 2020, were reviewed. A high-sensitivity troponin-I assay was used to divide patients into two categories. Patients who had troponin levels more than the upper limit of normal (troponin >ULN) were compared with patients who had troponin levels less than the upper limit of normal (troponin <ULN). The upper limit of normal corresponds to the 99th percentile of normal values for troponin. Demographics, clinical features, comorbidities, confounding factors for elevated troponin, vital signs, physical examination findings, laboratory values, troponin trends, electrocardiogram (EKG) changes, COVID-19 treatment, and special scores were collected on the day of troponin elevation. Some laboratory variables such as D-dimer, C-reactive protein (CRP), ferritin, and lactate dehydrogenase (LDH) were collected within seven days of the troponin test as they were not available on the day of troponin elevation. Data were extracted manually by trained investigators through standardized data collection manual. The institutional review board (IRB) of the appropriate institutions approved the study. The IRB waived informed consent due to the retrospective nature of the study.Statistical analysisContinuous data were reported as the median and interquartile range, and categorical data were reported as counts and percentages. Wilcoxon rank-sum test was used to analyze continuous data. The chi-square test was used to analyze categorical data. Survival analysis was done with the length of stay as the time variable and death or discharge from the hospital as right censoring. Survival graphs were reported as Kaplan-Meier survivor function with the log-rank test. We compared the clinical profiles, laboratory values, and special scores among patients who had troponin levels more than the upper limit of normal (troponin >ULN) with patients who had troponin levels less than the upper limit of normal (troponin <ULN). We initially ran a univariate cox regression to determine the predictors of mortality with elevated troponin. Variables that were significant in univariate analysis were incorporated in multivariate cox regression. We ran four separate models for troponin, TIMI score, GRACE score, and SOFA score to determine if these variables independently predicted mortality. Kaplan-Meier survival graphs were plotted for key variables with the log-rank test. Any variable with missing data of 10% or less was not included in the analysis. A p-value of less than or equal to 0.05 was considered significant. All data were analyzed with Stata Statistical Software: Release 17 .Clinical features and comorbiditiesAfter screening 1,500 COVID-19 patients, 217 patients who had troponin levels measured during any time of the hospital stay were included. Out of the 217 patients, 85 had elevated troponin, and 132 had normal troponin. Most patients had troponin levels measured during the first week of COVID-19 illness . The mean age was 63 (IQR = 50-77) years in the normal troponin group and 79 (IQR = 63-85) years in the elevated troponin group, and the difference was statistically significant (p < 0.01). Cardiovascular diseases (p < 0.01) were associated with elevated troponin but not cardiovascular risk factors (p = 0.887). Patients with elevated troponins also had an increased likelihood of having a mean arterial pressure <65 mmHg (p = 0.01), increased respiratory rate (p = 0.04), increased oxygen support (p < 0.01), and rales on physical examination (p < 0.01) (Appendices).Laboratory valuesPatients with elevated troponin levels had lower absolute lymphocytes (p < 0.01), lower albumin (p < 0.01), higher blood urea nitrogen (p < 0.01), higher creatinine (p < 0.01), higher aspartate aminotransferase (p < 0.01), higher total bilirubin (p < 0.01), higher CRP (p < 0.01), lower LDH (p = 0.01), higher D-dimer (p < 0.01), and higher lactic acid (p < 0.01). Serial troponins were not available for 20% of patients. However, a delta change of 30% (positive or negative change) was more prevalent in patients with elevated troponin (p < 0.01). EKG changes such as tachyarrhythmia (p < 0.01), ST elevation (p < 0.01), ST depression (p = 0.01), and left ventricular hypertrophy (p = 0.02) were more prevalent in patients with elevated troponins (Appendices).Hospital course and outcomesIn-hospital complications such as atrial fibrillation with rapid ventricular response rates (p < 0.01), congestive heart failure (p < 0.01), chronic obstructive pulmonary disease exacerbation (p < 0.01), intensive care unit (ICU) admission (p < 0.01), suspected or confirmed source of a bacterial infection (p < 0.01), intubation (p = 0.01), vasopressor use (p < 0.01), and death (p < 0.01) were more common in patients with elevated troponin. Higher Systemic Inflammatory Response System (SIRS), Quick SOFA (qSOFA), SOFA, TIMI, and GRACE scores were highly associated with elevated troponin levels (p < 0.01) (Appendices).Survival analysisMortality was 26.5% in the normal troponin group and 54.6% in the elevated troponin group. Patients were categorized into three groups: troponin <ULN, troponin 1-3 times ULN, and troponin >3 ULN. The mortality in each group was 23.6%, 55.2%, and 59.6%, respectively. In unadjusted Cox regression, age , cardiomyopathy , and chronic kidney disease  were statistically significant for mortality. Vitals signs such as heart rate >100 , respiratory rate , and the use of a non-rebreather or high-flow nasal cannula  were associated with mortality. Among the laboratory values, hemoglobin <8.5 g/dL , anion gap >12 , serum albumin <3.1 g/dL , blood urea nitrogen (BUN) , tachyarrhythmia , and troponin elevation more than the upper limit of normal  were associated with mortality  and corticosteroids  were associated with lower mortality. The presence of a confirmed or suspected bacterial infection  and ICU stay  were associated with increased mortality. The presence of systemic inflammatory response syndrome features , qSOFA score >1 , SOFA >4 , TIMI score >3 , GRACE >140  were all highly associated with mortality. The Kaplan-Meier survival curves plotted for troponin, GRACE, TIMI, and SOFA scores were significant based on the log-rank test  and cardiovascular risk factors  were not associated with mortality. We created four separate multivariate Cox regression models for troponin, GRACE score, and TIMI score while adjusting for age, non-rebreather or high-flow nasal cannula, hemoglobin <8.5 g/dL, suspected or confirmed source of infection, and SOFA score. Troponin elevation , TIMI score , and GRACE score  were not independently associated with mortality. SOFA score  was strongly associated with mortality in all models (Tables Similar to prior literature, patients with troponin elevation were older and more likely to have cardiovascular diseases such as coronary artery disease, heart failure, cardiomyopathy, stroke, and atrial fibrillation. Patients with elevated troponin also had a higher prevalence of cardiovascular risk factors such as hypertension, diabetes, dyslipidemia, smoking history, chronic kidney disease, and hemodialysis or continuous renal replacement therapy ,4-6,10. There is conflict in current data on whether cardiovascular diseases and cardiovascular risk factors are independently associated with mortality -9. In ouIt is important to distinguish type 1 from type 2 myocardial injury in COVID-19 patients as management is different . Type 1 2/FiO2 ratio, mechanical ventilation, thrombocytopenia, Glasgow Coma Scale score, mean arterial pressure, use of vasopressors, and creatinine and bilirubin levels [The SOFA score is the gold standard for predicting sepsis mortality . The SOFn levels . This enn levels ,14. The In our study, SOFA scores were independently associated with mortality in COVID-19-related myocardial injury, whereas GRACE and TIMI scores were not independently associated with mortality. This is likely due to the possibility of most patients having type 2 myocardial injury in COVID-19. Although we did not perform cardiac catheterization, it can be safely inferred that troponin elevation in COVID-19 was mainly due to demand ischemia from sepsis rather than acute coronary thrombosis in our cohort. In such patients, management should focus on treating COVID-19 sepsis, not myocardial injury. Patients with low SOFA scores and a higher degree of troponin elevation may have a true type 1 myocardial injury, and these patients may need early catheterization and management for acute coronary syndrome. However, we need more studies comparing type 1 and 2 myocardial injury to make this inference. Limitations of our study include a dual-center design, a small sample size, and the lack of cardiac catheterization data. Our study is one of the few studies which has evaluated the role of GRACE, SOFA, and TIMI scores in COVID-19-associated myocardial injury.Our study shows that the SOFA score independently predicts mortality, whereas troponin, GRACE, and TIMI scores do not independently predict mortality in COVID-19-associated myocardial injury. This association suggests the possibility of a preponderance of type 2 myocardial injury in COVID-19 instead of type 1 myocardial injury. Troponin is a cardiac enzyme, and it can be elevated in a variety of disorders, especially severe sepsis. Patients with elevated troponin had higher crude mortality rates. However, after adjusting for markers of sepsis, troponin elevation was not independently associated with elevated mortality. Therefore, we recommend the SOFA score in risk-stratifying COVID-19 patients. The role of the SOFA score in differentiating COVID-19-associated type 1 and 2 myocardial injury is an area of future research.


Improving the prediction ability of a human-machine interface (HMI) is critical to accomplish a bio-inspired or model-based control strategy for rehabilitation interventions, which are of increased interest to assist limb function post neurological injuries. A fundamental role of the HMI is to accurately predict human intent by mapping signals from a mechanical sensor or surface electromyography (sEMG) sensor. These sensors are limited to measuring the resulting limb force or movement or the neural signal evoking the force. As the intermediate mapping in the HMI also depends on muscle contractility, a motivation exists to include architectural features of the muscle as surrogates of dynamic muscle movement, thus further improving the HMI’s prediction accuracy.The purpose of this study is to investigate a non-invasive sEMG and ultrasound (US) imaging-driven Hill-type neuromuscular model (HNM) for net ankle joint plantarflexion moment prediction. We hypothesize that the fusion of signals from sEMG and US imaging results in a more accurate net plantarflexion moment prediction than sole sEMG or US imaging.Ten young non-disabled participants walked on a treadmill at speeds of 0.50, 0.75, 1.00, 1.25, and 1.50 m/s. The proposed HNM consists of two muscle-tendon units. The muscle activation for each unit was calculated as a weighted summation of the normalized sEMG signal and normalized muscle thickness signal from US imaging. The HNM calibration was performed under both single-speed mode and inter-speed mode, and then the calibrated HNM was validated across all walking speeds.On average, the normalized moment prediction root mean square error was reduced by 14.58 % (The proposed sEMG-US imaging-driven HNM can significantly improve the net plantarflexion moment prediction accuracy across multiple walking speeds. The findings imply that the proposed HNM can be potentially used in bio-inspired control strategies for rehabilitative devices due to its superior prediction.The online version contains supplementary material available at 10.1186/s12984-022-01061-z. Locomotion mobility accounts for a dominant part of human activities of daily living, like moving around the home and community, going to work or school, doing errands, visiting friends, etc. The human lower extremity plays an essential role in achieving locomotion mobility. The human ankle plantarflexors generate a large burst of “push-off” mechanical power during the late stance phase of walking, enabling forward and upward acceleration of the body’s center of mass. Due to neurological disorders or injuries like spinal cord injury, stroke, and multiple sclerosis, the weakened function or dysfunction of plantarflexors is likely to cause a dramatic decrease in the “push-off” power. Consequently, these mobility disorders impair walking function and cause poor energy economy , as wellModern neurorehabilitation devices, such as powered ankle exoskeletons –5, soft Surface electromyography (sEMG) measures electrical potentials during asynchronous muscle neurons firings, and its amplitude and frequency positively relate to muscle activation levels. Therefore, sEMG-derived signals can be used in a Hill-type neuromuscular model (HNM) or to train a machine learning approach (model-free) to predict volitional joint moment , 18 and Motivation also exists to use a dual-modal approach that combines the measurement from sEMG and US imaging. Potentially sEMG signals and US imaging provide complementary information, and the combination between them may (1) mitigate any cross-talking effect from neighboring sEMG signals and (2) lower US imaging-derived features’ drift due to the accumulated errors from cyclic joint movement. Our recent studies have shown the advantages of using the dual-modal approach over uni-modal bio-signals (sEMG or US imaging) for ankle joint moment/motion prediction under isometric/dynamic dorsiflexion studies , 25, 27 In this study, we investigated a dual-modal approach that takes both processed sEMG and MT from US imaging as inputs to a modified HNM, named sEMG-US imaging-driven HNM, to predict net ankle joint plantarflexion moment during the walking stance phase across multiple speeds. We hypothesize that (1) the proposed HNM will achieve a better net plantarflexion moment prediction accuracy than sEMG-driven and US imaging-driven HNMs, (2) the net plantarflexion moment prediction performance is more robust if data collected from multiple speeds are included in HNMs’ calibration procedure.In previous US imaging studies, visualized architectural features, such as PA and FL, require high-resolution US imaging, which can be significantly affected by a US transducer placement site on the muscle. To mitigate the requirement of high-resolution US imaging, US imaging-derived signals such as echogenicity , 36, 37,Below, we propose a modified sEMG-US imaging-driven HNM to directly build a relationship between the joint net PF moment and sEMG-US imaging-derived surrogate signals of both LGS and SOL muscles. There are three sub-models involved in the HNM: (a) sEMG-US imaging-derived weighted muscle activation model, (b) muscle-tendon unit geometry model, and (c) muscle contraction dynamic model.The neural activation at fined as 1\documenh muscle , and theA nonlinear relationship between neural activation given as 3\documenAccording to the reported results in –43, the sults in , there iBy introducing an allocation gain between the sEMG- and US imaging-derived muscle activations, the synthesized/weighted muscle activation levels for LGS or SOL muscle, O, the proximal and distal osteotendinous junction points of each each muscle-tendon unit (MTU) near the knee joint and heel as gait2392) was linearly scaled to each participant in OpenSim version 4.1 O, the pre change , 48, \do work in , 50 has From the preliminary results of plantarflexors’ US imaging in , it is vrding to , the nonfined in , \documeIn the sEMG-US imaging-driven HNM, the individual moment component produced by each muscle, found in , 32, 52.The study was approved by the Institutional Review Board (IRB) at North Carolina State University (IRB number: 20602). Ten young participants  without any neuromuscular or orthopedic disorders, were recruited in this study. Every participant got familiar with the experimental procedures and signed an informed consent form before participation.Figure UltraTrack [sEMG signals were band-pass filtered with the bandwidth between 20 Hz and 450 Hz, and then full-wave rectified and low-pass filtered with a cut-off frequency of 6 Hz. The resulting linear envelopes were normalized to the peak processed sEMG values obtained from all sets of dynamic gait trials with different speeds. The US radio frequency data were converted to B-mode images through beamforming and logarithmic compression, and then a commercial US imaging processing toolbox traTrack  was applBefore data collection, participants practiced dynamic walking steadily with all sensing devices attached to the lower extremities on the treadmill for at least 30 s for each speed. The duration of each walking trial was set as 2 min, and data from the middle 20 s were collected for analysis. In the current study, there were five different walking speeds, 0.50 m/s, 0.75 m/s, 1.00 m/s, 1.25 m/s, and 1.50 m/s, and the order was selected randomly for each participant. The participants were provided with at least 2 min for rest between two successive dynamic walking trials to avoid muscle fatigue.j, j, and N represents the length of the data used for the calibration.To determine the values for a set of parameters, including the shape factor terature . The sumentclass1pt{minimaterature . Except It should be noted that the HNM calibration is subjective, and for each participant, the calibration procedure was repeated for both single-speed modes and inter-speed mode. In the current study, single-speed modes are defined as the HNM calibration only with data collected from one single speed (five single-speed modes here), while the inter-speed mode is defined as the HNM calibration with all data collected from five different speeds (one inter-speed mode here). In HNM calibration, collected data, including ankle joint’s kinematics, kinetics, sEMG signals, and US imaging from the stance phase of 10 steady gait cycles, were used to minimize the objective function in . For theRMSE), RMSE normalized to individual peak net PF moment  of net plantarflexion moment generation during treadmill walking at the same speed is different, which would affect the prediction RMSE directly. Therefore, the direct RMSE values comparison among subjects is likely to introduce high deviations. An effective way to reduce the subjective variation of the prediction RMSE is to take the normalization to a subjective characteristic, like the body mass and peak net plantarflexion moment as we selected. The relationship between The validation procedures comprised three tests to assess the sEMG-US imaging-driven, sEMG-driven, and US imaging-driven HNMs’ calibration and prediction abilities of the net ankle joint PF moment during the stance phase. In each type of HNM test, the root mean square error  a weighted muscle activation model component, (2) a muscle-tendon unit geometry model component, and (3) a muscle dynamic contraction model component. This study also investigated the effects of HNM categories  and calibration speed modes (single-speed modes and inter-speed mode) on the net PF moment prediction performance during the walking stance phase. The ID-calculated net PF moment worked as the benchmark in both calibration and prediction. The results support our hypothesis that compared to sEMG-driven and US imaging-driven HNMs, the sEMG-US imaging-driven HNM accurately predicts the net PF moment. Further, the HNMs, when calibrated with the inter-speed mode, robustly predict the net PF moment.The evaluation of the proposed HNMs’ calibration and prediction performance was based on three criteria: orted in , the resThe superior net PF torque prediction of the sEMG-US imaging-driven HNM can be mainly due to the reason that the fused signals capture complementary mechanical and neural aspects of the muscle contraction . informaAs a preliminary study of the sEMG-US imaging-driven HNM for walking on a treadmill across multiple speeds, the results are promising and can help overcome the challenges of joint motion intent detection in volitional control of assistive devices. However, there are still some limitations in the current study. First of all, only a few US imaging-derived parameters, MT from both LGS and SOL, measured muscle activation levels indirectly . Other US-derived parameters, like FL and PA , 27, 35,In this preliminary study, although the combination of US imaging and sEMG data in the model improved the prediction of the ankle moment, it was unknown if the prediction was better only because in this combination the solution space was higher by adding parameters in the optimization problem. To address this ambiguity, we have conducted additional model calibration and prediction procedures for comparison, where the time sequence of the US imaging-derived muscle activation was replaced by a randomly generated signal between 0 and 1. In this way, we could reproduce the same solution space just like the proposed sEMG-US imaging-driven HNM, so we would be able to investigate if the prediction benefits still exist or not. We took a representative participant as an example, and present the calibration performance and prediction performance by using five different HNMs, as shown in the Additional file The key point to implement the proposed sEMG-US imaging-driven HNM is to find the allocation gain Another limitation of the current study is that we only considered the agonist LGS and SOL muscles to predict the ankle joint net PF moment, and the effects of the MGS and TA muscles were not considered. Although in the experiments we collected the sEMG signals from LGS, MGS, SOL, and TA muscles, ultrasound imaging data was collected from the LGS and SOL muscles only. Therefore, the fusion results were only based on these two muscles. The main reasons that we did not consider the effects from the MGS and TA muscles are 1) existing evidence suggests that sEMG signals from LGS and MGS are comparable , and sim existingRMSE, normalized to peak net PF moment/body mass, was significantly reduced when using the sEMG-US imaging-driven HNM, compared to sEMG-driven and US imaging-driven HNMs. The results also showed that the calibrated HNMs with the inter-speed mode were more robust for net PF moment prediction at different speed scenarios than HNMs with single-speed modes. The improved net ankle joint PF moment prediction during the dynamic walking tasks at different speeds could potentially lead to improved volitional control of assistive devices with more advanced and intelligent algorithms.This paper investigated the feasibility of an sEMG-US imaging-driven HNM to predict net ankle joint PF moment during the stance phase across multiple walking speeds. The results showed that on average, the net PF moment prediction Additional file 1: Table S1. Participants’ anthropometric characteristics and peak net PF moment during treadmill walking at each speed. Table S2. HNMs prediction performance under single-speed modes and inter-speed mode on Sub01. (RMSE unit: Nm). Table S3. HNMs prediction performance under single-speed modes and inter-speed mode on Sub02. (RMSE unit: Nm). Table S4. HNMs prediction performance under single-speed modes and inter-speed mode on Sub03. (RMSE unit: Nm). Table S5. HNMs prediction performance under single-speed modes and inter-speed mode on Sub04. (RMSE unit: Nm). Table S6. HNMs prediction performance under single-speed modes and inter-speed mode on Sub05. (RMSE unit: Nm). Figure S1. Right ankle joint kinematics and kinetics results from Participant Sub01. Figure S2. Right ankle joint kinematics and kinetics results from Participant Sub02. Figure S3. Right ankle joint kinematics and kinetics results from Participant Sub03. Figure S4. Right ankle joint kinematics and kinetics results from Participant Sub04. Figure S5. Right ankle joint kinematics and kinetics results from Participant Sub05. Figure S6. sEMG raw data and processed data from both LGS and SOL muscles during 20 seconds walking experiments on Participant Sub01. Figure S7. sEMG raw data and processed data from both LGS and SOL muscles during 20 seconds walking experiments on Participant Sub02. Figure S8. sEMG raw data and processed data from both LGS and SOL muscles during 20 seconds walking experiments on Participant Sub03. Figure S9. sEMG raw data and processed data from both LGS and SOL muscles during 20 seconds walking experiments on Participant Sub04. Figure S10. sEMG raw data and processed data from both LGS and SOL muscles during 20 seconds walking experiments on Participant Sub05. Figure S11. US imaging-derived MT and processed sEMG signals during the walking stance phase from Sub01. Figure S12. US imaging-derived MT and processed sEMG signals during the walking stance phase from Sub02. Figure S13. US imaging-derived MT and processed sEMG signals during the walking stance phase from Sub03. Figure S14. US imaging-derived MT and processed sEMG signals during the walking stance phase from Sub04. Figure S15. US imaging-derived MT and processed sEMG signals during the walking stance phase from Sub05. Figure S16. The Ultratrack toolbox interface with US imaging-derived MT tracking procedures and results without key-frame correction on Participant Sub07 walking at 1.00 m/s. Figure S17.The Ultratrack toolbox interface with US imaging-derived MT tracking procedures and results with key-frame correction on Participant Sub07 walking at 1.00 m/s. Figure S18. Exampled calibration and prediction performance on Participant Sub01 by using five HNM categories. The blue, red, orange, purple, and green bars represent the results by using the sEMG-, US imaging-, sEMG-US imaging-, random signal (RS)-, and sEMG-RS-driven HNMs under both single-speed modes and inter-speed mode. (a) Calibration RMSE and prediction RMSE values under different speed modes. (b) Calibration R-square and prediction R-square values under different speed modes. Figure S19. Exampled results of the ankle joint net moment and processed sEMG signals from LGS, MGS, SOL, and TA muscles throughout the recorded walking duration. Data are collected during the treadmill walking experiments on Sub01, where muscle activation levels from LGS and MGS muscles are comparable, and the activation level of the TA muscle is relatively small during the walking stance phase. (a) Walking speed at 0.5 m/s. (b) Walking speed at 0.75 m/s.Additional file 2. The LGS and SOL muscles' thickness tracking results from sequential US images on Participant Sub01 during treadmill walking at 0.50 m/s.Additional file 3. The LGS and SOL muscles' thickness tracking results from sequential US images on Participant Sub01 during treadmill walking at 0.75 m/s.Additional file 4. The LGS and SOL muscles' thickness tracking results from sequential US images on Participant Sub01 during treadmill walking at 1.00 m/s.Additional file 5. The LGS and SOL muscles' thickness tracking results from sequential US images on Participant Sub01 during treadmill walking at 1.25 m/s.Additional file 6. The LGS and SOL muscles' thickness tracking results from sequential US images on Participant Sub01 during treadmill walking at 1.50 m/s.


PEGylation, glycosylation, polysialylation, or conjugation with immunoglobulins or albumins have successfully increased G-CSFs’ half-lives. Pegfilgrastim (Neulasta) has been successfully approved and marketed for the treatment of patients with neutropenia. The rapidly expanding market for G-CSFs has increased demand for G-CSF biosimilars. Therefore, the importance of this review is to highlight the principle, elimination’s route, half-life, clearance, safety, benefits, and limitations of different strategies and techniques used to increase the half-life of biotherapeutic G-CSFs. Understanding these strategies will allow for a new treatment with more competitive manufacturing and lower unit costs compared with that of Neulasta.Over the last 20 years, granulocyte colony-stimulating factors (G-CSFs) have become the major therapeutic option for the treatment of patients with neutropenia. Most of the current G-CSFs require daily injections, which are inconvenient and expensive for patients. Increased understanding of G-CSFs’ structure, expression, and mechanism of clearance has been very instrumental in the development of new generations of long-acting G-CSFs with improved efficacy. Several approaches to reducing G-CSF clearance  Most of the current G-CSFs require daily injections, which are inconvenient and expensive.Different strategies have been used to overcome the short half-life of the first-generation rhG-CSFs.Understanding of G-CSF structure, expression, and mechanism of action on neutrophils may contribute to development of safe long-acting G-CSF therapies for patients with neutropenia.1®) was the first recombinant human granulocyte colony-stimulating factor (rhG-CSF) used for hematopoietic progenitor cell (HPC) mobilization. Filgrastim is a non-glycosylated G-CSF form produced in E. coli. It has a molecular weight of approximately 18.8 kDa and contains a methionine group at its N-terminus. It was the first G-CSF medicine approved by the United States Food and Drug Administration (US FDA) for treating neutropenia for various indications  receptor (FcRn) recycling through fusing several proteins with Fc portion of albumin or immunoglobulin –16 Tab. This ar22.1®) is another PEGylated form of second-generation rhG-CSF, and it is the only long-acting (once weekly) G-CSF that has been approved by the FDA (Conjugation with polyethylene glycol (PEG), known as PEGylation, was first described in the 1970s by both Abuchowski and Davis, who discovered that PEGylation process may increase the longevity of different proteins and improve their immunological properties, such as albumin and bovine liver catalase . Consequ the FDA Figure 1 the FDA , 45.2.1.1A single 20-kDa PEG molecule is covalently bound to the recombinant N-terminal methionine (r-met) residue of rhG-CSF Neupogen (Filgrastim) Figure 12.1.1.1via glomular filtration, making neutrophil-mediated clearance the primary route of elimination   , 65.N-linked glycans, O-linked glycans, glycosam inoglycans, phosphorylated glycans, and formation of glycosylphosphatidylinositol anchors to peptide backbones as well as residues of C-mannosylation-tryptophan  of serine (Ser), threonine (Thr), or tyrosine (Tyr) residues within a protein  catalyzes the transfer of the GalNAc moiety of uridine diphosphate to the hydroxyl of Ser or Thr  residue attaches to the amide group of an asparagine residue. It occurs in consensus sequences Asn-X-Ser/Thr, where X indicates any residue except proline (Pro)  , fucose (Fuc), sialic acid (NeuAc), linked by different α- or β-glycosidic linkages (recognized as a complex type) (In ne (Pro) . N-glycoysteine) . N-glycoeticulum Figure 2 content . The bioex type) , 75.N-linked glycan terminal site contains sialic acid , characterized by a diverse group of nine carbon-containing carbohydrates with a negatively charged carboxylate (C1), and has been shown to be critical in maintaining the half-life of several glycoproteins in the bloodstream , where either an tive FSH , 88.via a flexible (Gly4Ser)n linker including different glycosylation sites to form a tandem [G-CSF contains two glycosylation motifs (G-CSF2NAT): G-CSF4NAT and G-CSF8NAT] and their respective controls . Using Western blot, the preclinical study demonstrated an increase in the molecular weight of isolated glycosylated G-CSF tandems compared with controls  to the gylation Figure 4gylation , 89. Lipgylation –92. Lipegylation . Althoug2.2.2.1.1Lipegfilgrastim has two different clearance pathways: a linear pathway involving proteolytic enzyme degradation and a non-linear pathway involving neutrophil-mediated clearance . HoweverIn studies on the safety of lipegfilgrastim in dogs and rats, a single subcutaneous dose of 10 mg/kg was well tolerated. Similarly, an intravenous dose of 250 mcg/kg was well effective and tolerated in the renal excretion of rats. In a study of 139 patients, adverse events related to lipegfilgrastim occurred in 55 (39.5%) patients; bone pain and back pain were the most common .2.2.2.1.2vs. 27.2 h, respectively). In a randomized, double-blind, phase III trial, it was determined that lipegfilgrastim was non-inferior to pegfilgrastim in terms of the duration of severe neutropenia in patients with breast cancer . Although it can directly protect the body from infections by activating its antigen binding site, IgG immune functions are mostly mediated through receptors and proteins expressed by special cell subsets that bind to a region of IgG called Fc. The neonatal FcRn belongs to a large family of Fc gamma (γ) receptors (FcγRs) and has become increasingly important on binding IgGs and albumin. FcRn is known as a recycling receptor and has been shown to bind and maintain IgGs and albumin in the blood circulation and to bidirectionally transport both ligand molecules through polarized cellular barriers .In general, FcRn can attach to albumin and IgGs at the cell membrane in a pH-dependent way. Because of the presence of histidines in albumin and IgGs, the imidazole group of histidine protonates at a pH of 6.0 and binds to the FcRn receptor. The FcRn–IgG or FcRn–albumin complex interaction is then internalized and absorbed through the cell membrane, protecting albumin or IgGs from lysosomal degradation –101. The3.1Human serum albumin (HSA) is the main protein produced in the liver and serves a variety of physiological functions, including bilirubin, fatty acids, ion transport, and regulation of colloid blood pressure control. Because albumin is a massive protein , it can be used to conjugate with multiple recombinant proteins to prolong their half-lives. Consequently, these conjugated proteins will eventually acquire a molecular weight that is too large and challenging for the kidney to filter, extending the residency time of plasma proteins in the blood circulation , 105.Later, the importance of carboxy-terminal domain III human serum albumin (HAS) was recognized and genetically merged with the N-terminus of rhG-CSF. As a result, pharmacokinetic and pharmacodynamic experiments revealed a longer circulating half-life and a high number of white blood cells (WBC) counts in neutropenic mice when compared with rhG-CSF .3.2via disulfide linkages. Both chains have two regions: the antigen-binding fragment (Fab), an antibody’s head portion, is essential for detecting immunogenicity, whereas the Fc, an antibody’s tail component that interacts with a cell surface receptor, is crucial to maintaining IgG circulation  and CH (CH1-Hinge-CH2-CH3) domains (IgG immunoglobulin is composed of two fragment domains: Fc (Hinge-CH2-CH3) and CH (CH1-Hinge-CH2-CH3). The Hinge domain connects the Fc and Fab areas and allows for more flexibility, and it has been reported that various biotherapeutic proteins can be linked  domains . IgG fus domains , 35.in vivo, without affecting G-CSF bioactivity in vitro (The carboxy-terminus of rhG-CSF has been fused to the amino termini of the Fc (Hinge-CH2-CH3) and CH (CH1-Hinge-CH2-CH3) domains of human IgG4 and IgG1 immunoglobulins, which are connected by a 7–amino acid flexible linker (Ser-Gly-Gly-Ser-Gly-Gly-Ser) Figure 6in vitro , 35.3.2.1via a PEG linker to increase G-CSF half-life (Eflapegrastim (Rolvedon), a novel long-acting rhG-CSF, is created by fusing the rhG-CSF to the Fc fragment of human IgG4 alf-life , 107. Thalf-life Figure 7alf-life . Preclinalf-life , 109. Phalf-life , 38. A ralf-life , 110. In3.2.1.1Eflapegrastim is not detectable in the urine after subcutaneous dose administration . In patiLeukocytosis and bone pain may result from an eflapegrastim overdose. In this case, patients must be monitored for these adverse effects, and general supportive measures should be taken as required (FDA-approved drug products).3.2.1.2A study in rat models showed that eflapegrastim improved clinical benefit and was associated with higher bone marrow and serum concentrations than pegfilgrastim, which resulted in a significantly shorter duration of neutropenia when administered 24 h after chemotherapy compared with pegfilgrastim . Leukocy4All the long-acting G-CSFs in development rely on pegylation, glycopegylation, conjugation to IgG fragments, or serum human albumin Table 1.All authors contributed equally to this publication. Conception and design: AT and KFA. Drafting: ATA and KFA. All authors contributed to the article and approved the submitted version.