Data providing a relationship between the anesthetic method and postoperative length of stay (PLOS) is limited. We aimed to investigate whether general anesthesia alone or combined with epidural anesthesia might affect perioperative risk factors and PLOS for patients undergoing radical resection of malignant esophageal tumors.The study retrospectively analyzed the clinical data of 680 patients who underwent a radical esophageal malignant tumor resection in a Chinese hospital from January 01, 2010, to December 31, 2020. The primary outcome measure was PLOS, and the secondary outcome was perioperative risk-related parameters that affect PLOS. The independent variable was the type of anesthesia: general anesthesia (GA) or combined epidural-general anesthesia (E-GA). The dependent variable was PLOS. We conducted univariate and multivariate logistic regression and propensity score matching to compare the relationships of GA and E-GA with PLOS and identify the perioperative risk factors for PLOS. In this cohort study, the confounders included sociodemographic data, preoperative chemotherapy, coexisting diseases, laboratory parameters, intraoperative variables, and postoperative complications.P = 0.094, 18.09 ± 9.71 days vs. 19.39 ± 10.75 days, P = 0.145). The significant risk factors for increased PLOS were lung infection : 1.54–5.52), anastomotic leakage , and surgical site infection  by multivariate regression analysis. Subgroup analysis revealed a stronger association between PLOS and vasoactive drug use, blood transfusions, and open esophagectomy. The results remained essentially the same (stable and reliable) after subgroup analysis.In all patients, the average PLOS was 19.85 ± 12.60 days. There was no significant difference in PLOS between the GA group and the E-GA group either before or after propensity score matching  and PLOS for patients undergoing radical esophageal malignant tumor resection, an association between PLOS and lung infection, anastomotic leakage, and surgical site infection was determined by multivariate regression analysis. A larger sample future study design may verify our results. Esophageal cancer (EC) is a concerning health threat in China, ranking sixth among new cancer cases in 2020, with approximately 320,000 new claims and the 4th highest mortality rate , 2. AddiThe incidence of EC in China is much higher than that in Western countries, with more than half of new annual cases of EC worldwide occurring in China . EC may General anesthesia (GA) and combined epidural-general anesthesia (E-GA) are two anesthesia types commonly used in radical resection of esophageal malignant tumor. However, previous findings regarding the relationship between anesthesia type and PLOS are mixed; studies either showed that anesthesia type might have an association with PLOS , 13 or sSpecifically, we explored the relationship between the two types of anesthesia and PLOS in patients undergoing radical resection of esophageal malignant tumor in China, after adjusting for other confounders.In this retrospective cohort study design, we aimed to investigate whether anesthesia type (GA/E-GA) during radical esophageal malignant tumor resection has any association with PLOS. The objective, the independent variable, was anesthesia type (GA/E-GA), and the dependent variable was PLOS. PLOS was defined as the total number of days from the day of surgery to discharge. GA was general anesthesia in the form of complete intravenous anesthesia (propofol + remifentanil) or intravenous and inhalation anesthesia (sevoflurane). E-GA was based on GA combined with thoracic epidural anesthesia. Thoracic epidural anesthesia was started after a sterile preparation and insertion of an epidural catheter at the thoracic level of T6 to T8 in every patient with the same anesthesia protocol of the hospital. The study protocol includes sterile preparation with betadine, the lateral position of the patient after GA induction, insertion of Thuoy needle Gouge number 18 with the use of appropriate technique and placement of an epidural catheter, and preparation and administration of the same epidural anesthetic solution). Data from participants who had received radical resection of esophageal malignant tumor were obtained from the Department of Anesthesiology of the First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong Province, China. To protect patient privacy, our data did not include identifiable participant data. Data were extracted from the hospital’s electronic medical records system. The hospital’s Institutional Review Board approved the study (NO.B-2021-249). Written informed consent was waived by the Medical Ethics Committee of the First Affiliated Hospital of Shantou University School of Medicine because our study did not involve individually identifiable data or determine the treatment of patients. This study complied with the Declaration of Helsinki and adhered to the applicable STROBE guidelines. We obtained the data of patients who underwent radical resection of esophageal malignant tumor from the clinical information system of the First Affiliated Hospital of Shantou University Medical College. We recorded anesthesia type as a categorical variable and divided it into GA or E-GA. The outcome variable (PLOS) was a continuous. In this study, the primary outcome measures was PLOS, and the secondary outcome was perioperative risk-related parameters that affect PLOS.The literature lacks a precise and clinically acceptable definition of prolonged length of stay (LOS). Some studies have used the 75th percentile as a cutoff for defining prolonged LOS, although it is arbitrary , 16. We The medical records of eligible patients were reviewed. We included the following confounders that are perioperative risk-related parameters as listed below: (1) sociodemographic data ; (2) preoperative chemotherapy; (3) coexisting disease , heart disease, or lung disease); (4) laboratory examination results , and levels of AST (aspartate transaminase), ALT , and Scr (serum creatinine)); (5) intraoperative associated variables , endotracheal tube type, continuous anesthesia , operation type , vasoactive drug use, blood transfusions, postoperative ICU admission, operation time, and blood loss); and (6) postoperative complications , or surgical site infection).2 < 60 mmHg); lung infection, with clinical symptoms of cough, productive cough, fever or chest tightness, leukocyte count > 10.0 × 109/L or < 4.0 × 109/L, and purulent secretions, and postoperative imaging of new or progressive development, persistent pulmonary invasive shadows, and consolidation; anastomotic leakage ; and surgical site infection .The determination of postoperative complications was based on the medical record system. These complications can be listed as follows; respiratory failure , Student’s t tests , or Mann–Whitney U tests (skewed distribution) to evaluate differences between the anesthesia (GA and E-GA) groups. To confirm the association between anesthesia type and PLOS, we conducted a sensitivity analysis using propensity score matching because anesthesia types differed significantly across baseline characteristics [Continuous variables with a normal distribution are expressed as the mean ± standard deviation (SD), continuous variables with a skewed distribution are expressed as the median , and categorical variables are expressed as a frequency or percentage. We used χeristics . The rateristics –20. We chttp://www.R-project.org, The R Foundation) and EmpowerStats . P values less than 0.05 (two-tailed) were considered statistically significant.Data analysis can be summarized into two steps. Step 1: Selection bias was avoided by using propensity score matching; subsequently, univariate and multivariate linear regression were used to explore the relationship between anesthesia type and PLOS (days) Table . Next, wn = 8), (2) combined operation at other sites than the esophagus (n = 10), (3) automatic discharge or postoperative death (n = 5), (4) canceled operations (n = 4), (5) postoperative pathological results showing nonesophageal cancer (n = 4), and (6) missing data (n = 2). The final number of cases was 647. The mean age of the 647 patients selected was 61.01 ± 8.16 years old; of these patients, 77.43% were men, 185 underwent GA, and the remaining 462 underwent E-GA.The study initially involved a total of 680 participants. Participants’ entry time and selection deadline were 2010-1-1 and 2020-12-30, respectively. The inclusion criteria were patients undergoing radical esophageal malignant tumor resection while receiving GE or E-GA from January 01, 2010 to December 31, 2020. Exclusion criteria were (1) an unplanned second surgery (P < 0.05). The following confounders exhibited higher rates in the GA group than in the E-GA group: preoperative chemotherapy, hypertension, heart disease, Scr levels, ASA III, single lumen intubation, CIIV, MIE, operation time, vasoactive drug use, and postoperative admission to the ICU (P < 0.05). Participants in the E-GA group had higher values for albumin and blood loss. They experienced more double-lumen intubation, TIVA, OE, and surgical site infections than the GA group (P < 0.05). For unbiased comparisons, propensity score matching was performed to minimize intergroup differences among some cofounders. After propensity score matching, 137 patients in the E-GA group were successfully matched with 137 patients in the GA group (P > 0.05), and the confounders were uniformly distributed between the two groups.The baseline characteristics of the selected participants are shown in Table P value < 0.1 in the univariate analysis were entered into a multivariate logistic regression model to identify risk factors for PLOS. Neither univariate nor multivariate analyses showed an association between anesthesia type and PLOS. The multivariate regression showed that lung infection , anastomotic leakage  and surgical site infection  were significant risk factors for PLOS.The results of the univariate analyses (after propensity score matching) are presented in Table 2. Variables with a P < 0.1 in the univariate analysis  on prolonged PLOS > 21 days) after propensity score matching. Variables with 1 days afP = 0.1841)As shown in Table As stratified variables, we selected categorical variables  and continuous variables  that were transformed into categorical variables. We then observed the differences in effect size for these variables Table .P = 0.0346), operation type (P = 0.0346) and vasoactive drug use (P = 0.002). The remaining variables showed no significant differences.We found significantly different interactions for blood transfusion , although there was no significant difference in rates of postoperative respiratory complications [Postoperative complications are independently associated with decreased survival due to cancer recurrence , and prelization . Epiduralization . A meta-lization . The twoications . Lung inications .n = 3,515) was comparable to conventional OE  in terms of short-term, with thoracic esophageal cancer patients who underwent esophagectomy at 864 hospitals  in Japan [The wound length and pain in OE were greater than those in MIE. The advantage of MIE were no need for rib fractures, the ambulation early after surgery, less intraoperative blood loss, and lower total complication rates compared with OE –44. Howein Japan . To compin Japan  providedVasoactive drugs were administered at the discretion of the anesthesiologist without a standard protocol due to there is no widely accepted definition of intraoperative hypotension. Intraoperative hypotension is associated with increased 30-day operative mortality in Noncardiac Surgery , 50. TheOur study has the following advantages: (1) relatively large sample size for a single center study compared to a similar previous study; (2) strict statistical adjustment to minimize the residual confounders that observational studies are susceptible to; (3) handling independent variables as both continuous variables and categorical variables, which can reduce the contingency in the data analysis and enhance the robustness of the results; and (4) the use of effect modifier factor analysis to better utilize the data to draw stable conclusions in different subgroupsHowever, our study also has some limitations: (1) retrospective analysis performed in a single institution, which limits generalizability; (2) no postoperative care or early surgical rehabilitation; (3) patient-controlled intravenous analgesia in the GA group and patient-controlled epidural analgesia in the E-GA group, without unification of the postoperative analgesia; (4) lack of severity classification of postoperative complications; and (5) lack of identification of contraindications for epidurals in the GA groupAlthough there is no significant association between the type of anesthesia(GA or E-GA) and PLOS for patients undergoing radical esophageal malignant tumor resection, an association between PLOS and lung infection, anastomotic leakage, and surgical site infection was determined by multivariate regression analysis. A larger sample future study design may verify our results


Escherichia coli (UPEC) is one of the most common causes of urinary tract infections. Here, we report for the first time the whole-genome sequencing (WGS) and analysis of four extended-spectrum β-lactamase (ESBL), UPEC sequence type (ST) 127 isolates that were recovered from patients in five hospitals in Armenia from January to August of 2019. A phylogenetic comparison revealed that our isolates were closely related to each other by their core and accessory genomes, despite having been isolated from different regions and hospitals in Armenia. We identified unique genes in our isolates and in a closely related isolate recovered in France. The unique genes  were identified in three separate genomic regions that were adjacent to prophage genes, including one region containing the TonB-dependent iron siderophore receptor gene ireA, which was only found in 5 other ST127 isolates from the European Nucleotide Archive (ENA). We further identified that these isolates possessed unique virulence and metabolic genes and harbored antibiotic resistance genes, including the ESBL genes blaCTX-M-3 (n = 3), blaCTX-M-236 (n = 1), and blaTEM-1 (n = 1), in addition to a quinolone resistance protein gene qnrD1 (n = 1), which was absent in the ST127 isolates obtained from the ENA. Moreover, a plasmid replicon gene IncI2 (n = 1) was unique to ARM88 of the Armenian isolates. Our findings demonstrate that at the time of this study, E. coli ST127 was a cause of urinary tract infections in patients in different regions of Armenia, with a possibility of cross-country transmission between Armenia and France.Uropathogenic IMPORTANCE Whole-genome sequencing studies of pathogens causing infectious diseases are seriously lacking in Armenia, hampering global efforts to track, trace and contain infectious disease outbreaks. In this study, we report for the first-time the whole-genome sequencing and analysis of ESBL UPEC ST127 isolates recovered from hospitalized patients in Armenia and compare them with other E. coli ST127 retrieved from the ENA. We found close genetic similarities of the Armenian isolates, indicating that E. coli ST127 was potentially a dominant lineage causing urinary tract infections in Armenia. Furthermore, we identified unique genes that were horizontally acquired in the clusters of Armenian and French isolates that were absent in other ST127 isolates obtained from the ENA. Our findings highlight a possible cross-country transmission between Armenia and France and the idea that the implementation of WGS surveillance could contribute to global efforts in tackling antibiotic resistance, as bacteria carrying antimicrobial resistance (AMR) genes do not recognize borders. Escherichia coli is one of the most common causes of urinary tract infections (UTI), and it is estimated to affect about 150 million people, globally (E. coli (UPEC) pathotype is the primary cause of urinary tract infections and is a part of the broader pathotype designated extraintestinal pathogenic E. coli (ExPEC), which is known to cause infections in the bloodstream and in other nonintestinal sites (E. coli (NMEC), sepsis-associated E. coli (SEPEC), and avian pathogenic E. coli (APEC)  . One of  (APEC) 57. The ac (APEC) 5–10. Thes(APEC) 5–. An exam(APEC) 5–. Over thglobally –15. Howelobally –, 17.E. coli. Previously, we reported the occurrence of diverse MRSA genotypes (E. coli ST127 recovered from multiple sources (available at the European Nucleotide Archive [ENA]), and identify the mode of horizontal transfer of the unique genes found only in the Armenian isolates.Our understanding of UPEC infections has greatly improved due to the abilities of whole-genome sequencing (WGS) analyses to trace the sources and transmission routes of infections as well as to identify genes involved in virulence and antibiotic resistance for the implementation of improved infection control practices , 18–20. 18–enotypes  and provenotypes . In thisE. coli isolates (Table S3) belonged to ST127 (n = 1), 6 (n = 1), and 5 (n = 2) of the antibiotics tested. All four isolates were resistant to the cephalosporin antibiotics cefepime and ceftazidime as well as the aminopenicillins antibiotic ampicillin. In addition, 3 isolates  were resistant to the β-lactam antibiotic amoxicillin-clavulanic acid, and 2 isolates (ARM64 and ARM66) had intermediate resistance to the β-lactam antibiotic piperacillin-tazobactam. One isolate (ARM88) was resistant to the aminoglycoside antibiotic amikacin and the fluoroquinolone antibiotics norfloxacin and levofloxacin (ARM75). One isolate had an intermediate resistance to the carbapenem antibiotic imipenem (ARM66). All four isolates were sensitive to the β-lactam antibiotic meropenem and were also sensitive to chloramphenicol.4 out of the 12 sequenced to ST127  and wereE. coli ST127 in this study were aligned against 168 E. coli ST127 genomes that were obtained from the ENA archive and were previously recovered from 15 countries and 11 different animal sources and belonged to 3 different serotypes  . Moreover, all of the Armenian ST127 isolates were phylogenetically closely related to a French isolate (DABGLY01) that was recovered from a patient (urine sample) in 2015.The short reads of four of the [n = 8]) . A maxim[n = 8]) . All of E. coli ST127 isolates (excluding the EC536 isolate due to the lack of its date of isolation) was constructed using BEAST to determine the inferred date of divergence of the Armenian isolates and the French isolate (DABGLY01) obtained from the ENA archive to other ST127 isolates . The inferred divergence date of these isolates to their closest phylogenetically related isolate (the UK isolate DABBWT01 recovered from blood) was 1966 (date CI: 1956 to 1977). The most recent divergence date that was shared by both the Armenian isolates and the French isolate was 2000 (date CI: 1995 to 2006), and the most recent divergence date between ARM75 and the closely phylogenetically related French isolate DABGLY01 was 2005 (date CI: 2000 to 2009).A maximum clade credibility (MCC) time-calibrated phylogeny tree of 171 isolates . The ST1E. coli ST127 isolates that we analyzed, of which 41 were ubiquities , which was not present in any of the other ST127 isolates. In addition, they also carried the TonB-dependent iron siderophore receptor gene ireA, which was also found in five other ST127 isolates recovered from a dog (AATKBA01), a cat (AATMZD02), and human urine and fecal swabs . However, these isolates did not show any phylogenetic or geographical relationship to each other.All four of the isolates in this study and a phylogenetically closely related French isolate DABGLY01 (<25 SNP difference between the Armenian isolates and the French isolate within the core genomes) harbored the hemolysin E gene , lactate utilization protein operon (lutABC), peptide ABC transporter substrate-binding protein, transposase insD for insertion element IS2, Inovirus Gp2 family protein, and endonuclease restriction system operon (hsdMSR). We identified that 12 of these genes were located within the same locus, next to a prophage integrase intA gene, including the lutABC operon gene and the oppA gene. In addition, two genes that were located near the ireA gene and were unique to the Armenian and DABGLY01 isolates are InsD and the Inovirus Gp2 family protein gene. Moreover, we found one additional uncharacterized gene that was unique to the Armenian isolates adjacent to the hlyE virulent gene.Using Scoary, we identified 16 genes that were unique to all of the function , includihlyE gene found in the Armenian isolates was located within the active prophage region (ireA gene region (lutABCP/hsdMSR operons gene region (ireA gene and to the lutABC and hsdMSR operons that are adjacent to the prophage integrase gene intA and near tRNA-phe), we hypothesize that a possible horizontal transfer of genes could have occurred in these regions via prophages.To determine the origin of the horizontal gene transfer of these unique genes found in the Armenian isolates, we looked for insertion via transposable elements, such as integrated and conjugated plasmids within the chromosome and phage insertions. Using the MOB-suite software package to reconstruct plasmids from WGS data, we determined that all of these genes were chromosomal and were not plasmid-borne. Further, using ICEfinder, we determined that these unique genes did not belong to integrative and conjugative elements (ICEs). Using Prophage hunter, we identified that the e region , with the region  and the e region  were notireA virulent gene was present in other E. coli ST127 isolates, but the adjacent incD and the Inovirus Gp2 protein, which were unique to the Armenian and DABGLY01 isolates, were absent. To investigate further, we conducted a comparative analysis of the ireA gene loci of all of the E. coli ST127 isolates. The main difference in the ireA gene loci was that all of the isolates recovered in our study and DABGLY01 harbored two additional insertion sequence transposases instead of a hypothetical protein gene. In addition, the Inovirus Gp2 protein family gene found in the ireA locus shared 87.24% protein similarity . We found that each unique genomic region had 100% homology with E. coli isolates belonging to other sequence types. In addition, the ireA (Table S5) and hlyE (Table S6) gene regions had 100% homology with those found in E. coli ST761 and ST93 isolates recovered from pig feces in Canada and chicken meat in South Korea, respectively. For the lutABC/hsdMS genomic region (Table S7), we found multiple E. coli isolates from the ENA archive that had 100% homology with the Armenian ST127 isolates that were sequence types ST1485, ST40, ST117, ST1266, ST95, and ST117, isolated from China, Japan, the United States of America, France, Switzerland, and the United Kingdom and from mammalian, avian, human, and wastewater sources. However, we did not find isolates with ≥99.99% homology that contained all three genomic regions; instead, we detected multiple isolates that harbored the ireA and hlyA genomic region and the ireA and lutABC/hsdMSR genomic region. However, all three genomic regions were identified in various isolates belonging to the ST117 sequence type.To determine whether the unique genes and genomic regions detected in the Armenian  and French (DABGLY01) isolates were also present in other E. coli ST127 isolates were compared to 168 WGS data sets of E. coli ST127 isolates obtained from the ENA archive. In total, we identified 120 different antimicrobial genes/mutations within the resistome of these isolates  that have been reported previously. In addition, a plasmid-mediated quinolone resistance protein gene qnrD1 was unique to the ARM88 isolate recovered in this study.All four of the isolates that were recovered in this study possessed various degrees of antibiotic resistance genes/mutations, including 1 isolate (ARM64) possessing 59 antibiotic resistance genes/mutations, 1 isolate (ARM88) possessing 57 antibiotic resistance genes/mutations, and 2 isolates (ARM66 and ARM75) possessing 56 antibiotic resistance genes mutations. These numbers are greater than the average number of antibiotic resistance genes, compared to the n = 17), TEM (n = 48), and OXA-1 (n = 3). The most common CTX gene was blaCTX-M-3 (n = 16), which was also found in 3 of the Armenian isolates , blaCTX-M-15 (n = 15), blaCTX-M-211 (n = 6), blaCTX-M-55 (n = 4), blaCTX-M-216 and blaCTX-M-236 (n = 2), which was found in one of the Armenian isolates (ARM64), and blaCTX-M-14 (n = 2). The most common TEM gene was blaTEM-1 (n = 45), which was also found in ARM64, blaTEM-196 (n = 4), blaTEM-112 (n = 2), blaTEM-160 (n = 1), blaTEM-234 (n = 1), blaTEM-34 (n = 1), and blaTEM-91 (n = 1). In addition, the carbapenem-resistance genes blaNMD-1 (n = 1) and blaIPM-4 (n = 1) were detected in one of each of the E. coli ST127 isolates. However, they were detected only in those obtained from the ENA archive. We also found the antibiotic resistance genes/mutations, which were found in nearly all of the E. coli ST127 isolates from the ENA archive and in the all of the Armenian E. coli ST127 isolates, including the multidrug efflux mdtE, mdtF, the gadW and gadX, the pmr phosphoethanolamine transferase gene eptA , the elfamycin antibiotic resistance EF-Tu mutation (169 of the 172 E. coli ST127 isolates) and the tetracycline efflux pump genes tet(B) and tetR (32 of the 172 E. coli ST127 isolates). In addition, the aminoglycoside acetyltransferase gene AAC(3)-IId was identified in ARM64 (3 of the 172 E. coli ST127 isolates).60 out of the 172 (34.88%) ST127 isolates, and all 4 of the Armenian isolates that were recovered in this study, possessed genes that encode ESBL, including but not limited to: CTX . 36 different plasmid replicons were identified, of which IncFIB (AP001918) 1 was the most common (n = 74), followed by Col156_1 (n = 71) and IncFII (n = 48) (n = 2), followed by 5 (n = 6), 4 (n = 17), 3 (n = 48), 2 (n = 20), and 1 (n = 31). The ARM64 isolates harbored 3 plasmid replicons, including IncFII_1 (found in 8.14% of the ST127 isolates), IncI1_1_Alpha (found in 5.23% of the ST127 isolates), and IncX1 (found in 4.07% of the ST127 isolates). Moreover, ARM66 harbored one plasmid replicon, IncI2_1, that was unique to it. Overall, we found that isolates, based on the hierarchy cluster heat map of their plasmid replicons, do not group with their BAP cluster groups. We did not detect any known plasmid replicon for the ARM75 and ARM88 isolates, despite MOB-suite identifying part of the genome sequence as plasmid-associated.A plasmid replicon was identified in 72% (124/172) of the d IncFII  1_pUTI89(n = 48) . The greE. coli ST127 retrieved from the ENA (recovered from multiple sources), and identify the mode of horizontal transfer of the unique genes found only in the Armenian isolates. Interestingly, all of the Armenian E. coli ST127 isolates were identified as UPEC ESBL and belonged to the same genetic lineage. Despite these isolates being recovered from patients in five different hospitals, their inferred divergence date of the most recent common ancestor was around 2000 (95% CI of the date: 1995 to 2006). The close genetic similarities of the Armenian isolates indicated that ST127 was potentially a dominant lineage in causing urinary tract infections in Armenia at the time of this study (January to September of 2019). In addition, we found that a French UPEC ESBL isolate was the only other isolate from the ENA archive that was part of the same genetic lineage and shared the most recent common ancestor with the Armenian isolates. Furthermore, we identified unique genes that were near known prophage genes in both the Armenian and French isolate clusters, which suggested that these genes were horizontally transferred via a prophage. These unique genes and the associated genomic regions were novel to the ST127 lineage but were present in other E. coli sequence types that were recovered from different human (including human urine samples) and animal sources. However, none of these isolates were shown to harbor all three genomic regions, suggesting a unique combination of genes that is only found in the Armenian and French UPEC ST127 isolate clusters. As there is a large Armenian community in France with relevant family links in Armenia, it seems plausible that the E. coli ST127 was transmitted between countries.Studies investigating the potential of the DNA sequencing of pathogens that cause infectious diseases are seriously lacking in Armenia, hampering global efforts to track, trace, and contain infectious disease outbreaks. In this study, we report for the first-time a whole-genome analysis of ESBL UPEC ST127 isolates recovered from hospitalized patients in Armenia, compare them with other E. coli ST127 lineage was the pore-forming toxin hemolysin E gene hlyE . Hemolysin E has been identified across different species, including Salmonella typhi and Shigella flexneri, with a hemolytic action toward mammalian cells in anaerobic conditions . However, scientific evidence obtained under laboratory conditions has shown that Stx2-phages can also infect ExPEC isolates, although no evidence has ever been speculated of the prophage inserting the Shiga toxin gene into ExPEC isolates  and other unique genes as being adjacent to prophage genes in the bacterial chromosome. For example, we identified another gene that had homology to an Inovirus Gp2 family protein that was unique to our isolates as well as the IS3 family transposase IS2 near the TonB-dependent siderophore receptor gene an urine . The ire genomes . We alsoreA gene , 39.intA and the tRNA-phe gene. Downstream of these genes were the unique genes to the Armenian and French cluster, including a peptide ABC transporter substrate-binding protein, the lactate utilization protein operon lutABC , and the endonuclease restriction modification operon hsdMSR. To our knowledge, there have been no reports of the involvement of these genes in UPEC growth and survival in the urinary tract. Nonetheless, we can hypothesize that the peptide ABC transporter substrate-binding protein gene, lutABC operon, and lutP permease, may have a role in utilizing lactate as an energy source, along with other metabolites found in the urine; however, further studies are required . Intriguingly, we found 46 antibiotic resistance determinants that were ubiquitous in all of the E. coli ST127 isolates that were studied, which coincides with an analysis by Goldstone and Smith (2017) that described 50 antibiotic resistance genes, which may play a role in providing basal-level resistance toward a diverse number of antimicrobial compounds, as being part of the core resistome (≥95% of the isolates)  . Howeversolates)  also poiisolates , 55.E. coli ST127 isolates, except in one phylogenetically closely related UPEC isolate from France. Further whole-genome sequencing surveillance is necessary to better understand the molecular epidemiology of the Armenian isolates and the roles of some of these genes as well as to determine whether ST127 is the dominate lineage causing urinary tract infections in Armenia. Such surveillance studies will contribute to global efforts to tackle antibiotic resistance, as bacteria carrying AMR genes do not recognize borders.The main limitation of this study is its small sample size; however, this is the first genomic analysis of ESBL UPEC ST127 isolates recovered from patients in Armenia. These isolates were recovered from different hospitals in different regions of Armenia but belonged to the same genetic lineage and share a recent common ancestor. In addition, all of the isolates shared virulence and metabolic genes that were acquired via horizontal transfer and were not found in other E. coli isolates were received from the medical microbiology laboratories of 5 hospitals in Armenia between January and August of 2019. All isolates were recovered from urine specimens of hospitalized patients. The isolates were identified as E. coli using matrix-assisted laser desorption ionization-time of flight mass spectroscopy (MALDI-TOF-MS), as described previously , piperacillin-tazobactam (30/6 mg), amoxicillin and clavulanic acid (20/10 mg), ceftazidime (10 mg), cefepime (30 mg), norfloxacin (10 mg), levofloxacin (5 mg), amikacin (30 mg), imipenem (10 mg), meropenem (10 mg), and chloramphenicol (30 mg) , using a disk diffusion method, according to the European Committee on Antimicrobial Susceptibility Testing protocol . The antE. coli isolates were whole-genome sequenced using an Illumina HiSeq platform. However, for the purposes of this study, WGS analyses were conducted for only 4 isolates belonging to ST127. Genomic DNA was extracted using a TIANamp Bacteria DNA Kit  and the paired-end sequencing libraries were constructed using Nextera XT DNA Sample Preparation Kits or a TruSeq DNA HT Sample Prep Kit , following the manufacturers’ instructions.All of the de novo assembled using SPAdes  were obtained from the ENA database (accessed January 2022). The selection criteria of the isolates included the date and source of isolation and the country of origin. To select only the ST127 genomes among the 12 E. coli isolates recovered in this study and those retrieved from the ENA database, we screened the draft E. coli genomes using mlst  with the Achtman typing scheme from pubMLST (accessed January 2022).To conduct a comparative genomic analysis of the E. coli ST127 isolates, we first aligned all of the isolates against the reference E. coli ST127 genome EC536 (accession no. NC_008253.1) using the Parsnps alignment software from the Harvest suite (https://github.com/tseemann/snp-dists).To construct a core SNP maximum-likelihood (ML) phylogenetic tree of the st suite . Then, rst suite . To selest suite , 62. Finst suite . The SNPhttp://tree.bio.ed.ac.uk/software/figtree/).A Bayesian dated maximum clade credibility (MCC) tree was reconstructed using BEAST v1.10.4 . A GTR eE. coli ST127 isolates were annotated using Prokka (https://github.com/tseemann/abricate) in conjunction with the VirulenceFinder and Virulence Factor Database combined for virulence detection and the PlasmidFinder database for the identification of plasmid replicons (accessed January 2022) (–The genomes of the g Prokka . Virulenry 2022) –68. Antiy 2022) –. The isoy 2022) –.E. coli ST127 isolates was constructed using Roary with the BLASTP percentage identify cutoff set to 90% (E. coli ST127 groups were identified using Scoary (The pangenome combining both the Armenian and ENA t to 90% . Unique g Scoary . Unique g Scoary . The geng Scoary .E. coli isolates via a sequence similarity search using NCBI blast against the ENA sequence archive (The MOB-suite was used to reconstruct plasmid sequences from draft genomes to determine whether unique genes were plasmid-borne . Integra archive .https://cran.r-project.org/web/packages/pheatmap/index.html).The grouping of isolates into subclusters within the SNP core whole-genome alignment was conducted using the hierarchical clustering R package “RhierBAPS” . In addiPRJEB51925. Individual sequence file accession numbers are included in Table S2.The short-read data were deposited in the ENA under the study


Coffea liberica Bull ex Hiern 1876) has a high resistance to leaf rust, a devasting disease caused by Hemileia vastatrix. However, there are few reports on the systematic position and phylogenetic relationship of C. liberica at the chloroplast (cp) genome level. Thus, we successfully assembled its cp genome. The full length is 154,799 bp with a GC content of 37.48%. We have further annotated the cp genome and predicted 85 protein-coding genes together with 8 rRNAs and 37 tRNAs. Furthermore, a large single copy region (LSC), a small single copy region (SSC), an inverted repeat region a (IRa) and an inverted repeat region b (IRb) are identified with lengths of 84,868 bp, 18,121 bp, 25,905 bp and 25,905 bp, respectively. The phylogenetic tree indicates that C. liberica is closely related to C. canephora, which is consistent with a previous result obtained from genotyping‐by‐sequencing.Coffee is one of the most popular beverages around the world. As one of the best-known coffee species, Liberian coffee ( Coffea arabica L.), Robusta (C. canephora L. Linden) and Liberian coffees (C. liberica Bull ex Hiern 1876)  genome level. The cp genome could provide reliable evidence of the evolution and origin of plant species, such as Solanaceae  and used for DNA extraction. The specimen has been preserved in the Herbarium of the Dehong Tropical Agriculture Research Institute of Yunnan  under the voucher number DTARI-cl202101. The fresh leaves were rapidly soaked in liquid nitrogen and broken into powder for total DNA extraction by using the CTAB method (Doyle and Doyle C. liberica contained 154,799 bp with a GC content of 37.48%, which was deposited in GenBank under the accession number MW970411. We selected the GeSeq and CPGAVAS2 software to annotate the cp genome and predicted 85 protein-coding genes together with 8 rRNAs and 37 tRNAs (Tillich et al. Young leaves of Myxopyrum hainanense, Mitreola yangchunensis, Hoya carnosa and Calotropis procera (Amenu et al. C. liberica is closely related to C. canephora (Coffea genus.We selected 46 cp genome sequences to conduct the phylogenetic analysis. There are 42 species in Rubiaceae and four other species as outgroup, comprising anephora , which ianephora . This st


Leptospira, presenting complex and dynamic epidemiology. To determine the genetic variability and its phylogenetic relationship of Leptospira spp isolates from three sources in Iquitos (Peruvian Amazon) from 2002 to 2013, seven MLST genes were analyzed to obtain the Sequence Type (ST) and these sequences were concatenated for phylogenetic analysis. The genetic relationship between STs was determined with the goeBURST algorithm and genetic diversity was determined using DnaSP. Of 51 isolates, 48 were pathogenic belonging to five different species: Leptospira interrogans Nascimento 2004, Leptospira santarosai Feil 2004, Leptospira noguchii Haake 2021, Leptospira borgpetersenii Levett 2021, and Leptospira kirschneri Levett 2021. Of 20 STs identified, 60% corresponded to new genotypes circulating only in Peru. The genotypes ST17, ST37, and ST301 were recorded in rodents and humans. A high intraspecific genetic diversity was demonstrated in L. noguchi. The goeBURST analysis revealed three clonal complexes (CCs) and 16 singletons. The STs were found to show high genetic variability and phylogenetic and goeBURST analysis determined that the genotypes found did not form specific groups according to the source of infection or origin, which confirms the zoonotic potential of these STs in an area highly endemic for leptospirosis.Leptospirosis is a zoonotic disease caused by the genus  Leptospira [Leptospira [Leptospirosis is a zoonotic disease caused by pathogenic species of ptospira ,2. The wptospira . The higptospira ,4. In Peptospira  being muptospira , 7..In humans, leptospirosis has a very wide spectrum of clinical manifestations ranging from mild flu-like symptoms to serious complications such as Weil's disease and Hemorrhagic Pulmonary Syndrome (HPS), with a 40% fatality rate . This diLeptospira genus is classified in more than 300 serovars based on the structural heterogeneity of the O antigen lipopolysaccharide (LPS) detected by the Cross-agglutinin absorption test (CAAT) [Multilocus Sequence Typing (MLST), and comparative genomics, have been used to identify 22 species of the genus Leptospira. Species are classified into three phylogenetic groups: 10 pathogenic, 5 intermediate, and 7 saprophytic, correlated also with the virulence of the bacterium [The t (CAAT)  and 25 st (CAAT) . Differeacterium . Currentacterium .Leptospira variants is a technique based on PCR and followed by sequencing, to assign and characterize alleles present in different target genes and share the information between different laboratories through a database (https://pubmlst.org/organisms/leptospira-spp). Thus, several reports mention the use of MLST for molecular typing in genotypes or SequenceType (STs) [single locus variants, SLV), in two alleles , or three alleles . Likewise, the STs not assigned to any CC are called singletons, that is, STs differentiated by 4 or more alleles [MLST for the characterization of pe (STs) –16. Likepe (STs) , the genpe (STs) . This lape (STs) . CCs are alleles .Leptospira and Bartonella species in rodents from the southern Peruvian Amazon has been reported based on 16S metagenomic analysis [Leptospira from isolates and in biological samples of Iquitos using 16S rRNA gene analysis [In Peru, several studies have been carried out for the molecular identification of leptospirosis, thus, the prevalence of analysis . Other sanalysis .L. interrogans [Leptospira liceraceae suggesting a history of horizontal gene transfer (HGT) [Leptospira spp isolates in Peru is based on the serological test of MAT. Although this method allows typifying serogroups/serovars, it does not discriminate species [Leptospira has been detected [rfb loci, gene cluster associated with the biosynthesis of LPS from the Leptospira cell wall [Leptospira plays an important role in understanding the distribution, transmission, and pathogenicity of this disease [Genomic plasticity is known to occur in this genus, thus a genomic island of ∼ 54 kb and a large inversion in chromosome I were reported in the differentiation between the genomes of the Lai and Copenhageni serovars in errogans . Also, ser (HGT) . So, it er (HGT) . However species  in addit species , 9. Due detected . It is pell wall . Geneticell wall . In part disease .Leptospira spp isolates, from different sources and geographic areas of the Peruvian Amazon of Iquitos (a hyperendemic zone for leptospirosis) from 2002 to 2013. Thus, in addition to the MAT test, we evaluated the MLST scheme composed of 7 loci (housekeeping genes): pntA (NAD (P) transhydrogenase alpha subunit), SucA (Component 2-oxoglutarate dehydrogenase-decarboxylase), pfkB (Ribokinasa), tpiA (Triosephosphate isomerase), mreA (Protein rodA (Rod Shape-Determining protein rodA), glmU (UDP-N-acetylglucosamina pyrophosphorylase) and the caiB that encodes Acyl-CoA transferase III/carnitine dehydratase. The new genetic variants identified in this study (and not detected with MAT) were registered in the leptospira database, contributing to the knowledge of new variants of Peruvian leptospires strains throughout the world.In this sense, the present study sought to determine the genetic variability and its phylogenetic relationship of n = 300) Leptospira isolations were obtained from humans and rodents of different geographical areas from Iquitos city (Peruvian Amazon). The samples were collected between 2002 and 2013 as part of the Peruvian surveillance program for Leptospirosis and as part of a large project called “Dynamic of Leptospirosis Transmission in Maynas-Loreto province 2010–2014,” approved by the Ethics Committee of the National Institute of Health (code: 2-01-05-10-06). Leptospira spp isolates (n = 51) with their complete epidemiological information and stored in the biobank of the National Reference Laboratory for Bacterial Zoonoses (NRLBZ) (Three hundred ( (NRLBZ) .Ellinghausen-McCullough-Johnson-Harris (EMJH), at 28°C, for 6 to 8 weeks. Bacterial growth (up to the log phase) and contamination were observed using a dark field microscope  at 40X magnification. The isolates with the absence of contamination and a concentration of 1–2 x 108 leptospires/mL (counted in a Petroff Hausser Chamber) were selected to perform the serological and molecular analyzes.The reactivation of the isolates was carried out using the liquid medium L. interrogans, L. kirschneri, L. noguchii, L. weilii, L. borgpetersenii, and L. santarosai) provided by the Center for Disease Control and Prevention (CDC-USA) were included for the standardization and evaluation of MLST.Additionally, six reference strains of pathogenic leptospires , Autumnalis , Ballum , Bataviae (Bataviae), Canicola (Canicola), Celledoni (Celledoni), Cynopteri, (Cynopteri), Djasiman (Djasiman), Grippotyphosa (Grippotyphosa), Icterohaemorrhagiae (Cophenageni/Mankarso/Icterohaemorrhagiae), Javanica (Javanica), Mini (Georgia) Panama (Panama), Pomona (Pomona), Pyrogenes (Pyrogenes), Sejroe (Wolffi and Hardjo), Shermani (Shermani), Tarassovi (Tarassovi). The serogroups mentioned corresponded to the group of pathogens. The serogroup Iquitos  belonged to the intermediate group and Semaranga (Patoc) corresponds to the group of saprophytes. The serogroup was assigned according to the antiserum that produced an agglutination titer ≥800 .NotI restriction enzyme for 2 hours at 37°C. Salmonella serotype Braenderup H9812 was digested with 50 U XbaI for use as a standard marker. The agarose blocks containing the digested DNA were placed in the wells of the 1% agarose gel (SeaKem Gold) in 0.5X TBE buffer. The run was carried out using the CHEF MAPPER equipment (Bio-Rad Laboratories) for 18 h at 14°C with recirculating 0.5X TBE buffer and under the following conditions: Initial time of 2.16 s, final time of 35.07 s, an angle of 120° and voltage gradient of 6 V/cm. Gels were stained with ethidium bromide (1 ug/mL) for 20 min and documented with Gel-Doc 2000 (Bio-Rad). The images of the gels were analyzed using the GelCompar II program. Dendrograms were created using UPGMA clustering analysis based on band similarity coefficient with optimization of 1.4% and position tolerance of 1.4%. The database with the PFGE profiles of the 65 reference strains of Leptospira spp. was used as a search library for the comparison and identification of serovars of the isolates studied. It was compared with the results obtained by Galloway and Levett for the reference strains [The PFGE methodology and analysis were done according to Rivera et al. Reference . Briefly strains .housekeeping genes was performed according to the protocol described by Boonsilp (2013) [μL of reaction, with final concentrations of 1.5–3.5 mM of MgCl2, 0.2 μM–0.6 μM of each primer, 200 μM of dNTP , 1.25 U of Taq DNA polymerase (Invitrogen), and approximately 50 ng of template DNA. The thermal cycling conditions used were, an initial denaturation of 95°C for 2 min, followed by 30 cycles of 95°C for 10 s, 46°C for 15 s and 72°C for 30 s, and a final extension of 72°C for 7 min. The amplified products were evaluated by electrophoresis in 2% agarose gels; products with expected sizes were purified and sequenced for both strands. Sequencing was performed using the same primers from previous PCR, with the BigDye Terminator v3.1 kit (Applied Biosystems), on an ABI 3500XL genetic analyzer (Applied Biosystems). The obtained chromatograms were analyzed using SeqScape v2 program, for editing and exporting the consensus sequence for each allele of the 7 loci.DNA extraction was done using GeneJET Genomic DNA Purification Kit (Thermo Fisher Scientific) for Gram-negative bacteria, following the manufacturer's instructions. The amplification of the internal fragments of seven p (2013) , with sl#1 of Leptospira database (https://pubmlst.org/organisms/leptospira-spp), were obtained, concatenated for each locus, and aligned with those obtained in this study.The sequences of the seven MLST genes obtained from 48 isolates identified as pathogenic leptospires, were concatenated (3111 bp) with the Sequence Matrix v8 program . Additio#1 was assigned a numerical code. Subsequently, the allele combinations of the 7 loci were assigned an allelic profile (known as ST), in the following gene order: caiB-glmU-mreA-pfkB-pntA-sucA-tpiA. In case of noncoincidence with the database, sequences were verified and sent to the curator of the Leptospira MLST database, so new alleles and new STs were assigned, correlative to the existing ones.Each allele identified from each sample for each of the seven genes that make up the MLST scheme n = 48) were aligned with other 308 concatenated reference sequences obtained from the MLST database, of seven species of the genus Leptospira . The multiple sequence alignment was performed with the Clustal X2 algorithm [X program [For species identification, the concatenated sequences , and 8 STs of reference strains of From the concatenated sequences 3111 bp), diversity indices were calculated such as the number of polymorphic sites (S), haplotype diversity (Hd), number of haplotypes (H), and nucleotide diversity (Pi) using the DnaSP program v6 [11 bp, dihttps://www.phyloviz.net/goeburst/) [The clustering of STs into clonal complexes (CCs) was done with the goeBURST algorithm, using the PHYLOViZ Online software (eburst/) , 18. TheLeptospira spp characterized by MAT, the most predominant serogroup 25.49% (13/51) was Icterohaemorrhagiae with the serovars: Icterohaemorrhagiae/Copenhageni was the most predominant, followed by the serogroup Sejroe (Hardjo/Wolffi) with 11.76% (6/51). Other serogroups were registered but to a lesser extent. Likewise, 25.49% (13/51) of the isolates could not be characterized by MAT, so they were designated as “Not defined” , and one from rodents identified as Semaranga (Patoc); belonging to the intermediate and saprophytic groups, respectively  The species L. interrogans (n = 28) was made up of four serovars: serovar Icterohaemorrhagiae/Copenhageni (n = 22) that also agree with MAT results in 12 samples; the serovar Canicola (n = 5) that mostly agree with MAT; one serovar as unknown (n = 1) but identified as serogroup Bataviae by MAT. (2) The species L. santarosai (n = 14) is associated with serovars that could not be defined by PFGE and different serogroups by MAT. (3) The species L. noguchii (n = 2) was associated with the serovar Proechimys. (4) The species L. licerasiae (n = 2) was associated with the serovar Varillal , therefore they were not considered for this study. In addition, the ML tree showed that isolates from different distribution areas were discriminated in 5 clades, with high bootstrap values (100%). The isolates were identified as: L. interrogans (n = 21), L. santarosai (n = 17), L.noguchii (n = 8), L. borgpetersenii (n = 1) and L. kirschneri (n = 1) (Of 51 Peruvian isolates of  (n = 1) .glmU gene , 14 alleles for the pntA gene (three new), 13 alleles for the sucA gene (two new), 11 for the tpiA gene (two new), 16 for the pfkB gene (three new), 11 for the mreA gene (two new) and 10 alleles for the caiB gene . The distribution of each sample by locus is shown . We registered between 10 and 16 alleles per locus. 13 alleles were identified for the pfkB, pntA, and caiB, respectively), therefore for these isolates it was not possible to define ST due to their incomplete allelic profile, but its identification was carried out up to the species level. These sequences were also excluded from the analysis for the identification of CCs and genetic diversity.Of the 48 isolates analyzed, three of them  were not possible to determine the loci sequences (L. noguchii (Hd = 0.933 ± 0.122) and L. santarosai (Hd = 0.908 ± 0.063). Likewise, L. santarosai presented slightly more polymorphic sites (4.4%) compared to L. noguchii (4.27%) (High intraspecific genetic diversity was observed in  (4.27%) .L. interrogans (I.1), L. noguchii (I.2), and L. kirschneri (I.3); while group II consisted of two subgroups formed by the species L. borgpetersenii (II.1), and L. santarosai (II.2) (The phylogenetic relationships between the 20 genotypes (STs) of the 45 pathogenic leptospires species found in the present study, showed differentiation into two groups, which partially coincided with the identified serogroups. Group I was formed by three subgroups integrated by i (II.2) .Leptospira MLST database (312 STs) allowed for establishing 3 clonal complexes: CC17, CC37, and CC310 and 16 singletons  and ST321 (new). The CC310 of L. santarosai was composed of genotypes ST310 and ST322, both STs determined only for Peru, and each one represented by a Leptospira isolates. The CC310 complex is SLV-type CCs that are linked only by two genotypes  were identified as “new” and circulating only in the Peruvian Amazon, while the other 6 known singletons  have also been reported in other countries according to the MLST database .Leptospira spp were detected in this study, by MLST, circulating in the Peruvian Amazon. This is the first MLST molecular typing study (based on 7 housekeeping genes) carried out in Peru, from isolates of pathogenic leptospires from different sources and geographic areas of Iquitos city, collected over 11 years (2002–2013). Iquitos, located in the Peruvian Amazon, is considered a hyperendemic zone for leptospirosis [New genetic variants of spirosis , 20. LocLeptospira spp were also evaluated by PFGE. Of these, only 37 results are concordant between both methods  of the total analyzed, and concordant with two serogroups: Icterohaemorrhagiae and canicola defined by MAT and PFGE. Several reports mention that L. interrogans is widely distributed in the world and is associated with several outbreaks of leptospirosis in animals, including humans. In China, this species has been the most predominant for 50 years, with 90.83% (109/120) [L. interrogans serovar Autumnalis and ST34 [Of the five species identified (by ML), 109/120) . Likewisand ST34 .L. noguchii (Hd = 0.933 ± 0.122) followed by L. santarosai (Hd = 0.908 ± 0.063) (H = 0.96 ± 0.223) was observed for L. noguchii [L. santarosai as the most interesting species with high intraspecific diversity (Hd = 0.942 ± 0.034) [In general, a high genetic diversity (Hd = 0.867 ± 0.041) was registered in the total of isolates identified in this study, showing the highest intraspecific genetic diversity in ± 0.063) . Similar Hd = 0.9 ± 0.122 ± 0.034) , 33. HowIs important to mention that a high percentage  of registered genotypes (STs) were considered “new,” apparently circulating only in Peru. It should be noted that the STs were found in different sources of isolation; and that 12 of the new STs were derived from new alleles at various loci, while the new ST309 was generated by a different combination of alleles already known and present in various STs . This evidence highlights the potential of the MLST to explore the transmission and circulation of genotypes between reservoirs and humans, both during outbreaks and in epidemiological studies , 32.Rattus spp are an important source of transmission of leptospirosis. The genotype ST17 is known to be virulent to its hosts and is generally part of a zoonotic transmission cycle, involving humans, rats, and dogs [L. interrogans species, forming two different clusters with high statistical support, being the most frequent and closely related, since they share a recent common ancestor  in humans and rodents, which reaffirms the fact that reservoirs of the genus and dogs , 16, 32.and dogs , 36, andand dogs , as respancestor .L. noguchii were registered as news and found so far only in Peru. In addition, a close phylogenetic relationship was not observed between its members, being ST320 the most ancestral and all of them grouped in a cluster with high statistical support. The presence of ST301 in two isolates, one from humans (collected in 2003) and the other from rodents (from 2013), would reflect the occurrence of the circulation of the same genotype over time and in different sources. Similarly, other genotypes have been described with the capacity to infect a wide variety of domestic animal hosts, as well as rats and bats, at the same time. Also, serious clinical cases have been reported in humans in Brazil [Also, something to highlight is that all the genotypes  identified in the isolates of n Brazil .L. kirshneri species from a 2012 human sample, could not be characterized by MAT and PFGE . However, there are other different genotypes reported within L. kirschneri in different geographical areas, such as the genotype ST117 isolated from domestic animals (cattle and horses), ST100 isolated from rodents [The genotype ST298, characterized in the  rodents , ST110 f rodents . All theL. interrogans genome are related to the high rate of transmission through water, which does not occur with L. borgpetersenii due to a genetic decay process restricted to survival within the host, decreasing its transmissibility [L. borgpetersenii by MLST, but as L interrogans by PFGE, in one rodent isolate (L_110)  could not be characterized by serology, so they were determined as “not defined” by MAT . ST322 also presents allele 47 at the sucA loci that were also found in other STs  (The characterization of leptospires using MLST scheme enotypes . This gr or DLVs . The goe or DLVs . The STsd ST322) .sucA pathogenic and pfkB genes, observed in isolates of pathogenic leptospires in Argentina, variants that could generate new alleles and therefore new STs, as is the case of the new STN1(35); (3) evidence of HGT in Leptospira generating the appearance of an allelic profile that seems to arise from the combination between two other STs, as happened in the case of STN2 found in an MLST study for Leptospira in Argentina. Its profile was not made up of new alleles, but consisted of a new combination of alleles already known present in ST58  and ST17 (pfkB and mre A) [sucA and pfkB loci in six isolates of leptospires described in an MLST study in India, where they classified it as distantly related (DR) strains, assuming that they could be related to the supposed HGT that can occur between leptospires species [# 2 for Leptospira in which it contains the genes of scheme # 1  and which have shown high levels of genetic recombination and HGT for strains of the genus Leptospira [These findings could be associated with previously described situations, such as (1) the appearance of a high number of polymorphisms in a gene that could be considered evidence of the existence of recombination in a bacteria population ; (2) the new STN1; (3) evi species . On the ptospira .A limitation of the study was associated with the laboriousness and its slight complexity in the processing of the MLST method, in addition to requiring contamination-free isolates of leptospires and a good microbial concentration. However, there is also the possibility of optimizing the MLST directly from clinical samples or having other technologies. Thus, for example, the application of NGS technologies would allow us to expand the genetic variability studies of Leptospira more quickly and efficiently, as well as offer advantages when working with a larger number of samples from different isolation sources and geographical areas.Leptospira, being the first work of its type carried out in Peru. The determination of genotypes of Leptospira spp by MLST, of rodents as a source of transmission of leptospirosis in a hyperendemic area and its association with severe clinical cases, is of great relevance and utility for the molecular epidemiology of this pathogen. Indeed, these contributions will make it possible to suggest adequate measures regarding the rodent control strategy for reducing the transmission of the disease from animals to humans.The identification of new genotypes given in this study, together with all the epidemiological information, has contributed to the increase of records in MLST database of


Participants were ≥65 years without a diagnosis of dementia and presented for primary elective hip or knee arthroplasty. Plasma samples collected pre- and postoperatively were grouped as either control  or delirium . Widespread changes in plasma metabolite levels occurred following surgery. The only metabolites significantly differing between corresponding control and delirium samples were ornithine and spermine. In delirium cases, ornithine was 17.6% higher preoperatively, and spermine was 12.0% higher postoperatively. Changes were not associated with various perioperative factors. In binary logistic regression modeling, these two metabolites did not confer a significantly increased risk of delirium. These findings support the hypothesis that disturbed polyamine metabolism is an underlying factor in delirium that warrants further investigation.The mechanisms underlying the occurrence of postoperative delirium development are unclear and measurement of plasma metabolites may improve understanding of its causes. Participants ( Delirium is a clinical syndrome characterized by disturbances in attention, awareness, and cognition . DeliriuMass spectrometry methods for profiling metabolites have been used extensively to investigate disease processes and discover novel disease biomarkers ,12. Key Only a small number of studies to date have explored changes in metabolites associated with delirium. Previous work from our group has shown arginine metabolism is altered preoperatively in CSF from delirium patients . Other sParticipants were sampled from an observational cohort study, the methods for which are published . In brien = 28, aged: 76.2 ± 5.7) and age and sex-matched controls  underwent metabolomic analysis [Plasma samples from participants developing delirium , years in education, Charlson Comorbidity Index (CCI), estimated IQ, Bristol activities of daily living scale (BALD) score, Vertical Visual Analog Pain Scores, and American Society Anesthesiologists (ASA) physical status ,26,27. NPerioperative anesthetic and surgical data were collected and considered as potential confounders as below. Data available included: premedications; duration of surgery; intraoperative blood loss; intraoperative intravenous fluid volumes administered; use of peripheral nerve block/plexus blockade; general anesthetic and intraoperative sedation; perioperative analgesics and antiemetics; intraoperative tachycardia and/or hypotension; prophylactic antibiotics administered.Venous blood was sampled from fasted participants into lithium heparin bottles preoperatively at the time of anesthetic administration and postoperatively on Day 1. Samples were transported to the laboratory on wet ice within 12 h of collection, where they were centrifuged at 4 °C at 3750 rpm for 10 min and 500 mL aliquots of the supernatant pipetted  into 1.5 mL polypropylene tubes  and stored at −80 °C.Quantitative mass spectrometry-based metabolomic profiling was carried out by the Biocrates Absolute IDQ p180 . All plasma samples were prepared according to the manufacturer’s instructions and analyzed on a triple-quadrupole mass spectrometer . Metabolites (amino acids and biogenic amines) were derivatized using phenylisothiocyanate (PITC) in the presence of isotopically labeled internal standards, separated using a UPLC  system with a reverse-phase column  and quantified using a triple-quadrupole mass spectrometer  operating in the multiple reaction monitoring (MRM) mode. All the remaining metabolites  were quantified using the same mass spectrometer without column separation by the flow injection analysis (FIA) operating in MRM mode. Metabolite concentrations were calculated and expressed as micromole (μM). The mean of the coefficient of variation (CV) for the 184 metabolites in repeated quality controls was 0.12, and 85% of the metabolites had a CV of <0.15. Following these analyses, 138 metabolites were selected above limit of detection (LOD) values.g for 5 min with no brake and 500 mcl aliquots of the supernatant pipetted  into 1.5 mL polypropylene tubes  and stored at −80 °C. Spinal anesthesia was carried out, fasting, in the sitting or lateral positions using 25-gauge  Whitacre-type spinal needles with graduated metal introducers (Vygon). Once CSF was obtained, a 5 mL syringe  was attached to the spinal needle, and up to 5 mL of CSF was withdrawn by the anesthetist. The CSF was immediately transferred to a 30 mL sterile polypropylene universal container (Unisurge), which was placed on wet ice in an insulated container. All samples were transported to the laboratory within 12 h of collection. CSF samples were centrifuged at 4 °C at 3000 rpm/1811× CSF samples were transported to the Leonard Wolfson Biomarker Laboratory, University College London on dry ice. There, CSF Aβ42, t-tau, and p-tau concentrations were measured by a single, trained, technician, blinded to the clinical data, using the INNOTEST β-amyloid (1–42), hTau Ag, and Phospho-tau (181 P) ELISA kits, respectively , run on a FLUO star Omega BMG LABTECH instrument (chemiluminescent plate reader) according to the manufacturer’s protocols. Samples were thawed at 21 °C in an air-conditioned lab and vortexed before use. CSF biomarker values were determined using Omega software  and a 4-parameter curve fit. Intra- and interassay CVs, respectively, were 2.0% and 3.9% for Aβ42, 3.3% and 8.1% for T-tau, and 1.6% and 5.1% for P-tau. Longitudinal stability in the measurements is further monitored in the laboratory by participation in the Alzheimer’s Association Quality Control program.MetaboAnalyst software  was used for the data analysis. Data were normalized to the median and autoscaled before using PLS-DA scores and VIP scores. A normality test was carried out by SPSS . To compare the difference between pre and post-op metabolites, the paired Student’s t-test for parametric data and the Wilcoxon Mann-Whitney test for nonparametric data were performed. False discovery rates  were calculated based on Benjamini–Hochberg to determine if metabolites were statistically different between the two groups . For multiple comparisons on metabolites over 4 groups , a one-way ANOVA test for parametric data and Kruskal–Wallis test for nonparametric data were conducted. PLS-DA was carried out to highlight significant metabolites, which explain the maximum amount of variation between the groups. A VIP plot was created to identify the top 15 metabolites responsible for the observed separation between groups. t-test, χ2 analysis, and Mann-Whitney U test to compare the difference between control and delirium groups. To investigate whether perioperative changes in metabolites could be due to perioperative factors, correlation analyses were undertaken between perioperative variables and % change of metabolites, and the q-value from Benjamini–Hochberg was confirmed.Binary logistic regression was carried out to investigate risk factors for delirium. Statistical tests that we used were independent Baseline characteristics of the selected participants with and without delirium are displayed in Changes related to surgery: A total of 121 metabolites out of 138 significantly differed between pre-op and post-op samples  clearly differentiated pre-op and post-op plasma samples . Seven metabolites were commonly influential in both models , and their characteristics are shown in p-value, 0.005; adjusted results: odds ratio for delirium, 0.994; 95% (CI), 0.989–0.999; p-value, 0.027). Estimated IQ and MMSE show a significant difference for p-value in unadjusted results , 0.872–0.999; p-value, 0.047; MMSE: odd ratio for delirium, 0.711; 95% (CI), 0.528–0.958; p-value, 0.025). Neither spermine nor ornithine reached statistical significance. Although, the adjusted result for spermine was just outside the p-value threshold , 0.997–1.076; p-value, 0.071).To investigate potential predictor variables for delirium, binary logistic regression analysis was undertaken. Univariate analyses of perioperative variables between delirium and control groups are displayed in In this investigation, plasma from a nested case–control cohort of postoperative delirium underwent broad metabolite profiling and showed two metabolites, spermine and ornithine, were significantly elevated in delirium cases. The physiological context for the observations was either hip or knee arthroplasty, and the surgical procedures had an overriding impact on the plasma metabolome. The occurrence of delirium influenced the overall metabolome to a minor extent, and furthermore, those changes linked to delirium appear to be highly specific. In blood samples taken preoperatively, ornithine was almost 17.6% higher in persons prone to delirium. Furthermore, a metabolically related metabolite, spermine, was almost 12.0% higher postoperatively in cases of delirium.The fact that ornithine differed preoperatively, before the ensuing metabolic turbulence of surgery, indicates a possibility that this metabolite is a prognostic biomarker and/or risk factor for delirium. Although logistic regression modeling did not determine ornithine to confer additional risk in this nested cohort, sampling of larger cohorts is needed to definitively determine this risk. Ornithine overall was lowered by the surgical insult, but then this was also the case for the vast majority  of measured metabolites. This postsurgical lowering was only significant in delirium cases and not in controls, which is intriguing since ornithine is a precursor for polyamine formation, which includes spermine . Postoperative spermine was also not determined to be a significant risk factor here, but the odds ratio had a p-value of 0.07, indicating that with increased statistical power it possibly could be. The delirium-specific rise in spermine following surgery raises the question of whether the activity of the rate-limiting enzyme, ornithine decarboxylase (ODC) is augmented in individuals prone to delirium. The translation and activity of ODC are regulated by various factors, which include changes in polyamine concentrations . ODC conThere is a neurological context for the dysregulation of polyamines. Most pertinently, we have recently demonstrated using preoperatively collected cerebrospinal fluid (CSF) from this same cohort that spermidine, putrescine, and glutamine were significantly higher in delirium patients compared with controls . It shoup = 0.027). Aβ is a pathological feature of AD, and CSF Aβ is used for specific diagnosis of AD. Lower CSF Aβ42 normally signifies greater aggregation of Aβ in amyloid plaques in the brain [The aggregation of Aβ and phosphorylated tau protein are considered hallmarks of AD. The present investigation did not find evidence of CSF t-tau or p-tau associated with delirium; however, the data from the entire cohort did find a relationship , so the he brain . This sthe brain ,42. Furthe brain . It is nhe brain .The delirium and control groups in this case–control study were matched only for age and sex and differed in a number of other significant ways. Despite the relatively small sample size of this nested case–control study, which will have limited the statistical power, there are a number of key strengths to this investigation. Firstly, the collection of preoperative and postoperative blood samples is relatively unique; secondly, the detailed clinical characterization and measurement of CSF biomarkers; thirdly, the collection of perioperative information helps exclude potential confounding from the surgical and anesthetic procedures; and finally, the acquisition of annotated and quantitative metabolomic data provides a relatively broad understanding of the impact on metabolism. There are also some minor limitations. The nested case–control used available blood samples from participants matched only for age and sex who did and did not develop delirium following elective arthroplasty. A very small number of participants lacked perioperative variable data . The scaIn summary, metabolomic approaches are providing new insights underlying delirium occurrence, allowing new hypotheses to be formed. Once again, the findings here indicate that polyamine metabolism either contributes to the development of delirium or is a part of underlying neurodegeneration or vulnerability. Clearly, a comprehensive and focused examination of the entire arginine–ornithine biochemical pathway is now warranted. This should include the measurement of metabolites from various tissue compartments involved in the urea cycle, polyamine biosynthesis (including their acetylated forms), as well as interconnecting metabolites such as agmatine and glutamine. The most logical way forward should be to establish a bespoke targeted quantitative LC-MS/MS methodology for measuring all the metabolites in the wider biochemical pathway. Then, this methodology could be applied to samples acquired from a range of different postoperative delirium cohorts.


To investigate the relationship between paraspinal lean muscle mass and adjacent vertebral compression fracture (AVCF) after percutaneous kyphoplasty (PKP) for osteoporotic vertebral compression fracture (OVCF).The data of 272 patients who underwent two consecutive single-level PKP in our hospital from January 2017 to December 2019 were collected. 42 patients who met the inclusion and exclusion criteria were selected as AVCF group, and 42 propensity score-matched patients were selected as control group. There were 10 males and 32 females in each group; the ages were 75.55 ± 5.76 years and 75.60 ± 5.87 years, respectively. All patients underwent preoperative lumbar MRI. The total cross-sectional area (CSA), functional cross-sectional area (FCSA), cross-sectional area of vertebra index (CSA-VI), functional cross-sectional area of vertebra index (FCSA-VI) of the multifidus (MF), erector spinae (ES), psoas (PS), and paravertebral muscles (PVM) were measured. Other related parameters included preoperative bone mineral density (BMD), kyphotic angle (KA), anterior-to-posterior body height ratio (AP ratio), vertebral height restoration, and cement leakage into the disc. Logistic regression analysis was performed to find independent risk factors for AVCF using the parameters that were statistically significant in univariate analysis.p = 0.026). Logistic regression analysis showed that PVM with lower FCSA-VI at L4 level  and lower BMD  were independent risk factors for AVCF after PKP.At L3 and L4 levels, the mean CSA, FCSA, and FCSA-VI of MF, ES, PVM and PS were significantly lower in the AVCF group. DeLong test indicated that the AUC of ES (0.806 vs. 0.900) and PVM (0.861 vs. 0.941) of FCSA-VI at L4 level were significantly greater than L3 level. In the AVCF group, patients had a significantly lower BMD (93.55 ± 14.99 HU vs. 106.31 ± 10.95 HU), a greater preoperative KA (16.02° ± 17.36° vs. 12.87° ± 6.58°), and a greater vertebral height restoration rate (20.4% ± 8.1% vs. 16.4% ± 10.0%, Low paraspinal lean muscle mass is an independent risk factor for AVCF after PKP. Surgeons should pay attention to evaluate the status of paraspinal muscle preoperatively. Postoperative reasonable nutrition, standardized anti-osteoporosis treatment, and back muscle exercise could reduce the incidence of AVCF. With prolonged life expectancy, the increase of the aging population imposes a burden on the healthcare system. Osteoporosis is considered a main feature of the aging process, and osteoporotic compression fractures (OVCFs) have become a major cause of back pain, reduced daily activities, and increased bedridden time . PercutaSarcopenia is another age-related change in body composition that is defined as a progressive decline in muscle mass and strength . Spinal A close relationship between sarcopenia and osteoporosis has been conclusively reported , 7. MuscPrevious studies have reported that osteoporosis is a predictor of AVCFs , 11. DueAlthough previous studies have reported various predictors of AVCFs, data related to paraspinal muscle factors is scarce –15. ConsFrom January 2017 to December 2019, 312 consecutive patients who underwent single-level kyphoplasty twice at our hospital were recruited for this retrospective study. The inclusion criteria were as follows: (i) age from 65 to 85 years old; (ii) available preoperative radiography, computed tomography (CT), and MRI; (iii) acute or subacute single-level OVCFs treated with kyphoplasty; (iv) diagnosed with osteoporosis by T-score ≤ −2.5 measured on dual-energy x-ray absorptiometry (DXA) or Hounsfield unit (HU) values of L5 ≤ 110 HU measured on sagittal reconstruction CT images ; (v) antA total of 272 patients were eligible in our study, and 42 patients who met the inclusion and exclusion criteria were selected as the adjacent vertebral compression fracture (AVCF) group. A control group of 42 propensity score-matched patients who underwent kyphoplasty for single-level OVCFs without further adjacent vertebral fractures were selected. Each patient in the AVCF group was matched with a patient in the control group based on age, sex, BMI, and treatment level of the first kyphoplasty .There were no significant differences in age, sex, BMI, or the initial treatment level between the AVCF group and the control group. The demographic and clinical characteristics of the patients are summarized in Preoperative lumbar spine MRI was performed. The slicing plane was parallel to the vertebral endplates. Axial T2-weighted MR images obtained at the L3 and L4 lower endplate levels were exported as DICOM data and analyzed using ImageJ software . To evaluate the muscle mass and strength, the total cross-sectional area (CSA) and functional cross-sectional area (FCSA) of the multifidus (MF), erector spinae (ES), psoas (PS), and paravertebral muscle (PVM), which indicated the combination of MF and ES, were measured using the method reported by Xie et al  17). Th. Th17). To decrease bias caused by the stature of the patients, we also evaluated the standardized muscle mass using the muscle-vertebra index (-VI) . The val. was used to measure the KA  was obtained by measuring the HU values of L5 on sagittal reconstruction CT images  16). Pa. Pa16). e the KA . The vere the KA .t tests and Pearson chi-square tests, respectively.The continuous data falling in a normal distribution are presented as the mean ± standard deviation. Continuous and categorical data were compared between the AVCF group and the control group by using independent-sample ROC curves were constructed using the CSA, FCSA, CSA-VI, and FCSA-VI of each muscle. The area under the curve (AUC) of each MRI parameter was calculated, and the DeLong test was applied to compare the AUC of each MRI parameter between the L3 and L4 level.p < 0.05.To minimize the effects of the confounders in multivariate analysis, the most effective predictor among the MRI parameters was selected based on the AUC results. Then, this parameter and other possible factors with significant differences in the univariate analysis were analyzed in binary logistic regression to determine independent predictors for the development of AVCFs. SPSS for Mac 25.0  and MedCalc for Win 19.1.3  were used for all the statistical analyses. Differences were considered statistically significant when The mean CSA and FCSA of the MF, ES, PVM, and PS were significantly smaller in the AVCF group than in the control group at the L3 and L4 levels .p > 0.05). However, the FCSA-VI of MF, ES, PVM, and PS on L3 and L4 were significantly smaller in the AVCF group than in the control group  and PVM  was significantly greater at the L4 level. The detailed results of the DeLong test are presented in ROC curve analysis was performed to identify the most effective predictor of AVCFs among the various MRI parameters. Based on the results of the DeLong test, there were no significant differences in the AUCs of CSA, FCSA, and CSA-VI of each muscle between the L3 and L4 levels. However, the AUC of FCSA-VI of ES , a greater AUC was observed for the FCSA-VI of PVM. The AUC of this MRI parameter was 0.941 (p < 0.001), and the cutoff value was 119.55. When this cutoff value was used for predicting the development of AVCFs, the sensitivity and specificity were 90.5% and 90.5%, respectively. Therefore, the FCSA-VI of PVM on L4 was selected as a potential predictor of AVCFs and was analyzed with the other possible factors in binary logistic regression.The performance of the FCSA-VI of ES and PVM on the L4 level is demonstrated in p < 0.001), a greater preoperative KA , and a greater vertebral height restoration rate .The results of univariate analysis of other possible factors are shown in p < 0.001) and lower BMD  remained as independent predictors for AVCFs . For patients with spinal sarcopenia preoperatively, low paraspinal lean muscle mass and strength might cause reduced daily activities and mobility, which could impact the effect of anti-osteoporotic therapy after kyphoplasty. The continuous loss of cancellous bone increased the risk of refractures, especially in the vertebra adjacent to the cemented vertebra. Consequently, patients with low paraspinal lean muscle might remain susceptible to decreased bone density and AVCFs.Previous studies reported that osteoporosis was the most important risk factor for AVCFs , 11. In rcopenia . PearsonGreater preoperative KA was also observed in patients with AVCFs, although this factor was not identified as an independent predictor in the current study. We believe that the more severe imbalance in the sagittal plane could be attributed to paraspinal muscle weakness. Numerous studies have reported that poor sagittal alignment is associated with spinal sarcopenia . Weak MFThis study revealed that low paraspinal lean muscle mass was an effective independent predictor of AVCFs after kyphoplasty. The evaluation of muscle mass by MRI is recommended as a routine procedure before kyphoplasty to predict potential AVCFs. In addition to anti-osteoporotic therapy, the prevention and treatment of muscle mass loss are also crucial. Hence, a combination of nutritional guidance and resistance exercise focused on back muscles should be encouraged before and after surgery . ExercisSeveral limitations should be noted in this study. First, only the CSA or FCSA measured by MRI was involved in evaluating the paraspinal muscle. The HU values obtained by CT scan could also be used to evaluate the the density of paraspinal muscle. Second, we did not consider the muscle function or muscle strength, which is an important component in spinal mechanics. In future prospective studies, muscle strength and daily activities would be definitely assessed according to the guidance from the Asian Working Group for Sarcopenia . Third, This study confirmed that the low lumbar paraspinal lean muscle mass on L4 was an independent predictor of AVCFs in patients with OVCFs treated by PKP. Lower BMD was also a factor affecting AVCFs. For patients with spinal sarcopenia, surgeons should pay attention to pre- and postoperative nutritional guidance, anti-osteoporotic therapy, and back muscle exercises to minimize the risk of new AVCFs.