Method for predicting outcome of purulent lung disease caused by klebsiellapneumoniae
Genotyping the AQP4 rs1058424 polymorphism in patients with Klebsiella pneumoniae infections allows early identification of high-risk patients, enabling personalized treatment and prevention strategies to reduce mortality.
Patent Information
- Authority / Receiving Office
- RU · RU
- Patent Type
- Patents
- Current Assignee / Owner
- FEDERALNOE GOSUDARSTVENNOE BYUDZHETNOE NAUCHNOE UCHREZHDENIE FEDERALNYJ NAUCHNO KLINICHESKIJ TSENTR REANIMATOLOGII I REABILITOLOGII FNKTS RR
- Filing Date
- 2024-11-27
- Publication Date
- 2026-07-07
AI Technical Summary
Current methods for predicting the outcome of purulent lung diseases caused by Klebsiella pneumoniae, a highly antibiotic-resistant bacterium, are inadequate, particularly in identifying high-risk patients early enough to implement timely preventive and therapeutic measures.
The method involves genotyping the AQP4 rs1058424 single nucleotide polymorphism in patients upon admission to determine the AQP4 rs1058424 genotype, using the Sanger sequencing method to identify the presence of the minor T allele, which is associated with a favorable outcome, while the AA genotype indicates a high risk, allowing for early identification of high-risk patients.
This approach enables early division of patients into high-risk and low-risk groups for fatal outcomes, facilitating personalized preventive and therapeutic measures, reducing mortality from Klebsiella pneumoniae infections.
Smart Images

Figure 00000001
Abstract
Description
[0001] The invention relates to medicine, namely to clinical laboratory diagnostics using nucleic acids, and can be used to predict the outcome of purulent lung disease (PLD) caused by Klebsiella pneumoniae.
[0002] Relevance.
[0003] HCLs are severe pathological conditions characterized by inflammatory infiltration followed by destruction of lung tissue as a result of exposure to infectious agents. Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa are among the causative agents of a group of opportunistic bacteria collectively known as ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species). Most microorganisms in this group, with the exception of S. aureus, are Gram-negative bacteria that predominate in hospital-acquired infections (HAIs). These bacteria are included by the WHO in a "critical" group of pathogens resistant to antibiotics and posing a life-threatening threat to patients. Klebsiella pneumoniae primarily affects the lungs and genitourinary tract. This species is currently characterized by a high level of antibiotic resistance and high virulence.The most common form of pulmonary empyema is pleural empyema (PE), an inflammation of the pleural sheets accompanied by the formation of purulent exudate in the pleural cavity.
[0004] Early detection of biomarkers of the risk of adverse outcomes in HZL facilitates the personalization of timely preventive and therapeutic measures, preventing the spread of nosocomial infections and increasing the effectiveness of targeted therapy.
[0005] Technique level.
[0006] Klebsiella pneumoniae is known to exhibit resistance to β-lactam antibiotics, especially due to the expression of β-lactamases, the most important of which are cephalosporinases, extended-spectrum β-lactamases (ESBLs), and carbapenemases. The activity of these bacterial enzymes significantly increases the mortality of patients with pneumonia and its sequelae, which include HZL [Wang G., Zhao G., Chao X., Xie L., Wang H. The Characteristic of Virulence, Biofilm, and Antibiotic Resistance of Klebsiella pneumoniae. Int J Environ Res Public Health. 2020; 17(17):6278. Published 2020 Aug 28. doi:10.3390 / ijerph17176278].
[0007] A number of prognostic markers are currently known from the prior art that characterize the risk of an unfavorable outcome of pulmonary infections caused by various viruses and bacteria.
[0008] These include, in particular, a method for predicting acute metapneumonic nonspecific EP in patients with acute destructive pneumonia, which involves determining the amount of peptide-bound hydroxyproline in the patient's blood serum on the 1st or 2nd day from the start of treatment. An increase in its level to 82.44 μmol / L or higher predicts the development of acute metapneumonic nonspecific EP (RU 2282193). This method relates to predicting the development of EP in patients with pneumonia, in contrast to the claimed method, which predicts the outcome of EP. Thus, both methods are relevant to patients with different diagnoses - pneumonia (RU 2282193) or EP (the claimed method).
[0009] A known method for predicting the development of acute PE in victims with blunt closed chest trauma involves measuring the amount of peptide-bound hydroxyproline in the blood serum 12 hours after the injury. An increase in this level to 109.92 μmol / L or higher, i.e., 12 times or higher than the norm, is considered a predictor of acute PE (RU 2350965). This method predicts the risk of developing PE after trauma, unlike the claimed method, which predicts the outcome of PE that has already developed. Therefore, the risk calculations apply to different patient groups: post-traumatic patients (RU 2350965) and patients diagnosed with PE (the claimed method).
[0010] A known method for predicting the course of EP and pyopneumothorax includes determining the procoagulant activity of monocytes in the patient's blood plasma, and the proteolytic activity of leukocytes and procoagulant activity of macrophages in the pleural exudate, with high or normal leukocyte activity in the exudate. A favorable course of the disease is predicted in the presence of procoagulant activity of macrophages, as well as in the case of a decrease in the proteolytic activity of leukocytes, a multidirectional effect of macrophages on the coagulation activity of plasma, and in the absence of procoagulant activity in monocytes. An unfavorable course of the disease is predicted in the presence of a decrease in the proteolytic activity of leukocytes, the presence of anticoagulant activity in macrophages, and procoagulant activity in monocytes (RU 2043636).This method predicts an unfavorable or favorable course of EP, in contrast to the claimed method, which proposes a prognostic marker for an unfavorable outcome of EP, with the help of which it is possible to determine the possibility of an unfavorable outcome of EP at the earliest possible time - on the day of hospitalization.
[0011] A method for predicting the unfavorable course of acute, limited purulent-inflammatory diseases of the lungs and pleura of microbial etiology is known. This method for predicting the course of purulent-inflammatory diseases of the lungs and pleura involves isolating pathogens, classifying them, and determining their anti-lysozyme and anti-complement activity (RU 2237248). These research methods take several days, which delays the possibility of prognosis, unlike the proposed method, which allows for the identification of a high risk of fatal outcome from epidemiologically induced pneumonia on the first day of hospitalization.
[0012] A method for predicting Klebsiella pneumoniae colonization in patients undergoing allogeneic hematopoietic stem cell transplantation is known. A model for predicting Klebsiella pneumoniae colonization, a method for its construction and application (CN 117174320). This known method allows for predicting the formation of Klebsiella pneumoniae colonies in patients undergoing hematopoietic stem cell transplantation. This development is relevant, but, unlike the claimed method, it provides a prognosis for a completely different group of patients.
[0013] Thus, clinically validated prognostic biomarkers for a homogeneous cohort of patients, namely patients with purulent infection caused by gram-negative pathogens of nosocomial infections, are currently unknown to the authors of the claimed method.
[0014] Disclosure of invention.
[0015] Gram-negative bacteria Klebsiella pneumoniae are known to exhibit resistance to β-lactam antibiotics, especially due to the expression of β-lactamases, the most important of which are cephalosporinases, extended-spectrum β-lactamases (ESBLs), and carbapenemases. The activity of these bacterial enzymes significantly increases the mortality of patients with pneumonia and its severe sequelae, which include HZL [Wang G., Zhao G., Chao X., Xie L., Wang H. The Characteristic of Virulence, Biofilm, and Antibiotic Resistance of Klebsiella pneumoniae. Int J Environ Res Public Health. 2020; 17(17):6278.. doi:10.3390 / ijerph17176278].
[0016] The essence of the claimed method is that the characteristics of the patient's genome, namely the single nucleotide polymorphism of the AQP4 gene, encoding a protein that transports water into the cells of the vascular walls, participates in the control of the migration of immune system cells and contributes to the formation and duration of edema in the perivascular region, is a source of early, informative biomarkers of a high risk of death in patients with severe complications of pneumonia - EP.
[0017] The authors of the proposed method empirically established that carriage of the minor T allele (AT and TT genotypes) of rs1058424 AQP4 is associated with a favorable prognosis in patients with HZL diagnosed with nosocomial infections caused by the gram-negative bacteria Klebsiella pneumoniae. If a nosocomial infection caused by Klebsiella pneumoniae and the AA genotype of AQP4 rs1058424 are detected, the patient with HZL is considered to be at high risk for an unfavorable outcome of the infectious process.
[0018] The method for predicting the outcome of HZL includes: collecting venous blood upon admission to the city clinical hospital and determining the genotypes of AQP4 rs1058424. As a genotyping method, different methods for determining single nucleotide substitutions existing in medicine can be used, including the most well-known sequencing method - [Podnar JW, Pantano L., Zeller MJ, Rolling FW, Zhang Y., Alekseyev YO, Niece J., Deiderick H., Fan J., Xuei X., Kieleczawa J., Levine SS, Herbert ZT, Adams M. Cross-Site Evaluation of Commercial Sanger Sequencing Chemistries. J Biomol Tech. 2020 Sep; 31(3):88-93. doi: 10.7171 / jbt.20-3103-002; Slatko BE, Kieleczawa J., Ju J., Gardner AF, Hendrickson CL, Ausubel FM "First generation" automated DNA sequencing technology. Curr Protoc Mol Biol. 2011 Oct;Chapter 7:Unit7.2. doi: 10.1002 / 0471142727.mb0702s96; Sanger Sequencing. Chapter 5 - Genetic Testing Techniques. Editors: Nathaniel H. Robin, Meagan B.Farmer, Pediatric Cancer Genetics, Elsevier, 2018, Pages 47-64, ISBN 9780323485555, https: / / doi.org / 10.1016 / B978-0-323-48555-5.00005-3].
[0019] Thus, in established infection with gram-negative bacteria, the presence of the minor allele T of AQP4 rs1058424 in patients with HZL is a factor for a favorable outcome, whereas the homozygous AA variant provides a high risk of an unfavorable outcome of the infectious process.
[0020] In case of multidrug-resistant pathogen, the proposed method will help to justify the physician's decision regarding the use of preventive measures, personalization of intensive monitoring of the infectious process and personalization of treatment for patients at high risk of an adverse outcome using alternative high-tech methods (genodiagnostics of pathogens, phage therapy, etc.).
[0021] The technical (therapeutic) result of the claimed method is that, based on the determination of the AQP4 rs1058424 genotype for patients with HZL and identified gram-negative bacteria, it becomes possible to fairly early divide hospitalized patients with purulent infection into high-risk and low-risk groups for a fatal outcome.
[0022] The authors of the proposed method conducted a clinical examination of 214 patients diagnosed with the most common HZL, EP, in whom the infectious agents were identified. All patients were genotyped for variants of the AQP4 rs1058424 single nucleotide substitution.
[0023] In the cohort of patients with HZL examined by the authors of the claimed method, the main pathogens of infections were: Streptococcus viridans (30%) Streptococcus pneumonia (16%) Klebsiella pneumonia (15%) Pseudomonas aeruginos (11%).
[0024] During clinical studies, the authors identified a specific pathogen that may be associated with a prognosis for the outcome of the infection. Analysis of a cohort of patients revealed that the subgroup of patients with detected Klebsiella pneumoniae made the main contribution to mortality (89%) in patients with Gram-negative bacteria. When analyzing subgroups separately based on the presence of Klebsiella pneumoniae, the association remained significant for some patients with detected Klebsiella pneumoniae (P=0.018, logrank test, HR=7.6, 96% CI: 2.8-20.2, n=45). For the remaining patients with Gram-negative bacteria in whom Klebsiella pneumoniae was not detected, no difference in survival was found depending on the AQP4 rs1058424 genotypes, although all carriers of minor genotypes (AQP4 TA, TT) survived (P=0.51, logrank test, n=24). Thus, carriage of the minor T allele of AQP4 rs1058424 was found to protect against an unfavorable outcome of EP caused by Klebsiella pneumoniae.
[0025] The distribution of AQP4 rs1058424 genotypes in the examined sample of patients with EP was: AA - 71%, AT - 26%, TT - 3%; this distribution was consistent with the Hardy-Weinberg law (p = 0.67, χ 2= 0.15, allele frequencies A - 84%, T - 16%). For patients with fistula (fistula) complication of EP (a more severe form of EP) and without fistula complication, a similar distribution pattern of genotypes was found: 29%, T / T - 2% (p = 0.69, χ 2= 0D6), and AA - 74%, AT 23% T / T - 3% (p=0.37, χ 2 =0.80) (EP with fistula and without fistula, respectively).
[0026] Statistical processing of the results confirmed the diagnostic significance of the identified prognostic genetic marker using genotyping of the AQP4 rs1058424 variant in patients with HZL, namely: the presence of the minor T allele of AQP4 rs1058424 (genotypes TA, TT) predicted a favorable outcome of HZL in the presence of gram-negative bacteria.
[0027] For all patients with HZL, the presence of minor genotypes of AQP4 rs1058424 TA, TT was associated with a favorable prognosis (P=0.012, logrank test, HR=9.7, 96% CI: 3.9-24.2, n=214). For some patients with detected gram-negative bacteria, the association remained significant (P=0.018, logrank test, HR=8.4, 96% CI: 3.3-21.7, n=69). For the remaining patients in whom gram-negative bacteria were not detected, but gram-positive bacteria and fungi were isolated, or, despite the tests performed, the pathogens were not identified, no difference in survival was found depending on the AQP4 rs1058424 genotypes (P=0.43, logrank test, n=145).
[0028] The method is carried out as follows.
[0029] The method for predicting the outcome of hepatitis C includes: venous blood sampling upon admission to the city hospital and determination of the AQP4 rs1058424 genotype. Various methods for determining single nucleotide substitutions existing in medicine can be used as a genotyping method, including the most well-known sequencing method – the Sanger method.
[0030] To isolate genomic DNA, 200 μl of whole blood is used, then a PCR product of 823 nucleotides in length is obtained using primers:
[0031]
[0032] Next, the resulting PCR fragment is sequenced using the Sanger method. The PCR products are purified using an enzyme mixture. The reaction is carried out using a primer.
[0033] Capillary electrophoresis and genotyping analysis are then performed on patients. If a nosocomial infection caused by Klebsiella pneumoniae and the AA AQP4 rs1058424 genotype are detected, the patient is considered to be at high risk of death.
[0034] Thus, early detection of biomarkers of adverse outcomes in HZL facilitates the personalization of timely preventive and therapeutic measures, preventing the spread of nosocomial infections and increasing the effectiveness of targeted therapy. Clinical examples.
[0035] Case Study #1. Patient M., 69, was admitted to the City Clinical Hospital with a primary diagnosis of pleural empyema without a fistula. On the first day of hospitalization, pleural drainage was performed. Microbiological testing revealed Klebsiella pneumoniae and the AA genotype of AQP4 rs1058424. Due to disease progression, he was transferred to the intensive care unit on the third day. Despite treatment, he died 10 days later.
[0036] Case Study #2. Patient R., 59, was treated for community-acquired pneumonia and then transferred to the specialized thoracic department of the City Clinical Hospital with a diagnosis of pleural empyema with a fistula. On the first day of hospitalization, pleural drainage and bronchial block were performed, and video-assisted thoracoscopic sanitation of the pleural cavity was performed on the fourth day of hospitalization. Microbiological testing revealed Klebsiella pneumoniae and the AQP4 rs1058424 AA genotype. Despite the treatment, due to disease progression, the patient was transferred to the intensive care unit (ICU) after 9 days. He died after 7 days in the ICU.
[0037] Case Study #3. Patient E., 68, was treated for a primary diagnosis of novel coronavirus infection and was then admitted to the City Clinical Hospital's thoracic department with a diagnosis of epidemiologically significant pulmonary embolism with a fistula. On the first day of hospitalization, video-assisted thoracoscopic debridement, pleural drainage, and bronchial blockade were performed. Microbiological testing revealed Klebsiella pneumoniae, Pseudomonas aeruginosa, and the AQP4 rs 1058427 AT genotype. On the fifth day, the patient was transferred to the intensive care unit (ICU). On the seventh day, he was transferred from the ICU back to the thoracic department and discharged two weeks later with a SOFA score of 1.
[0038] Case Study #4. Patient K., 54, was undergoing treatment for a primary diagnosis of novel coronavirus infection and was then admitted to the specialized thoracic department of the City Clinical Hospital with a diagnosis of EP with a fistula. The patient's genotype was AQP4 rs1058424 AT, and Klebsiella pneumoniae was isolated. On the third day of hospitalization, the patient was transferred to the intensive care unit (ICU). The following procedures were performed: pleural drainage, bronchial block, and negative pressure wound therapy. After 39 days, he was transferred from the ICU and discharged from the City Clinical Hospital 11 days later with a SOFA score of 2.
[0039] Thus, by determining the AQP4 rs1058424 genotype in patients with HZL, it becomes possible to identify those at high risk of an adverse outcome in the event of infection with gram-negative bacteria of the Klebsiella pneumoniae species on the first day of hospitalization. Such information, depending on the prevalence of nosocomial infections caused by Klebsiella pneumoniae in a given healthcare facility, may be useful for strengthening personalized anti-epidemic measures for at-risk patients, for prescribing personalized treatment, including prioritizing surgical procedures and prescribing phage therapy, and for justifying the intensity of infectious process monitoring using gene diagnostics of the nosocomial pathogen.
[0040] --->
[0041] <?xml version="1.0" encoding="ISO-8859-1"?>
[0042] <!DOCTYPE ST26SequenceListing SYSTEM "ST26SequenceListing_V1_3.dtd"
[0043] PUBLIC "- / / WIPO / / DTD Sequence Listing 1.3 / / EN">
[0044] <st26sequencelisting productiondate="2026-02-11"
[0045] softwareversion="2.3.0" softwarename="WIPO Sequence" filename="ФНКЦ
[0046] РР, Писарев Владимир Митрофанович.xml" dtdversion="V1_3">
[0047] <applicationidentification>
[0048] <ipofficecode>RU< / ipofficecode>
[0049] <applicationnumbertext> RU MPK C12N7 / 00< / applicationnumbertext>
[0050] <filingdate> 2024-11-27< / filingdate>
[0051] < / applicationidentification>
[0052] <applicantfilereference> RU MPK C12N7 / 00< / applicantfilereference>
[0053] <earliestpriorityapplicationidentification>
[0054] <ipofficecode> RU< / ipofficecode>
[0055] <applicationnumbertext> RU MPK C12N7 / 00< / applicationnumbertext>
[0056] <filingdate> 2024-11-27< / filingdate>
[0057] < / earliestpriorityapplicationidentification>
[0058] <applicantname languagecode="ru">Pisarev Vladimir Mitrofanovich,
[0059] Federal State Budgetary Scientific Institution "Federal
[0060] Research and Clinical Center for Resuscitation and Rehabilitation, Federal Scientific and Clinical Center
[0061] RR< / applicantname>
[0062] <applicantnamelatin>Vladimir Pisarev
[0063] Mitrofanovich< / applicantnamelatin>
[0064] <inventiontitle languagecode="ru">"A method for predicting the outcome of purulent
[0065] Lung disease caused by Klebsiella pneumoniae" Application No.
[0066] 2024135483 / 10(078684). Application filing date: 27.11.2024. Applicant
[0067] Federal State Budgetary Scientific Institution "Federal
[0068] Scientific and Clinical Center for Resuscitation and Rehabilitation" (FSCC RR),
[0069] RU IPC C12N7 / 00 (2006.01)< / inventiontitle>
[0070] <sequencetotalquantity> 3< / sequencetotalquantity>
[0071] <sequencedata sequenceidnumber="1">
[0072] <insdseq>
[0073] <INSDSeq_length> 823< / INSDSeq_length>
[0074] <INSDSeq_moltype> DNA< / INSDSeq_moltype>
[0075] <INSDSeq_division> PAT< / INSDSeq_division>
[0076] <INSDSeq_feature-table>
[0077] <insdfeature>
[0078] <INSDFeature_key>source< / INSDFeature_key>
[0079] <INSDFeature_location>1..823< / INSDFeature_location>
[0080] <INSDFeature_quals>
[0081] <insdqualifier>
[0082] <INSDQualifier_name>mol_type< / INSDQualifier_name>
[0083] <INSDQualifier_value>genomic DNA< / INSDQualifier_value>
[0084] < / insdqualifier>
[0085] <insdqualifier id="q2">
[0086] <INSDQualifier_name>organism< / INSDQualifier_name>
[0087] <INSDQualifier_value>Homo sapiens< / INSDQualifier_value>
[0088] < / insdqualifier>
[0089] < / INSDFeature_quals>
[0090] < / insdfeature>
[0091] < / INSDSeq_feature-table>
[0092] <INSDSeq_sequence> ccgtgtgtcaagatttggttaagtcttgcctgacagaactcaaagacacgtc
[0093] tatcagcttattccttctctactggaatattggtatagtcaattcttatttgaatatttattctattaaa
[0094] ctgagtttaacaatggcaaaatacagtatgtcacagtcatgcacattcaagagagaaaatataacaagtt
[0095] cttttatgagcaatcccttatgcatagactaccttggcaaaagagcattagcaagtgtcactgctcatca
[0096] gttacttccttccatttatatcacaaatacccaagtttcaattctaacttcatttcatggtatttcttcc
[0097] tcctcaatgcccaaggtaatgtgggactaaagcccagaaatttgaaaaaatattcagaaatccttccca
[0098] aatcataagggcacctattgagattcaagacaagcagactcgtaaaatcttgtagaggcagaggcaaagt
[0099] tatcatcatacaaaaatcacaaacaaaaaaggagatctgtattcgggtatcaaacggttgatctgttttca
[0100] gtgcacaccctcaaatgcaccacaccagttttacgatctaagcttttaacccctttaccactttgcttat
[0101] ttttaaaaaatttattggcaaaactggggattttgtttgtaactttggttatctatatttaaacattagc
[0102] tgagacatatttttgataacaagaacttagctagttgagtcctggctttttgttgattattaagctgtgt
[0103] tcactctagaaggtgtaaaggccctgtcccaatctctgctctctcacttctcgtgacatttgttgataat
[0104] c< / INSDSeq_sequence>
[0105] < / insdseq>
[0106] < / sequencedata>
[0107] <sequencedata sequenceidnumber="2">
[0108] <insdseq>
[0109] <INSDSeq_length> 19< / INSDSeq_length>
[0110] <INSDSeq_moltype> DNA< / INSDSeq_moltype>
[0111] <INSDSeq_division> PAT< / INSDSeq_division>
[0112] <INSDSeq_feature-table>
[0113] <insdfeature>
[0114] <INSDFeature_key>source< / INSDFeature_key>
[0115] <INSDFeature_location>1..19< / INSDFeature_location>
[0116] <INSDFeature_quals>
[0117] <insdqualifier>
[0118] <INSDQualifier_name>mol_type< / INSDQualifier_name>
[0119] <INSDQualifier_value>other DNA< / INSDQualifier_value>
[0120] < / insdqualifier>
[0121] <insdqualifier id="q4">
[0122] <INSDQualifier_name>organism< / INSDQualifier_name>
[0123] <INSDQualifier_value>Homo sapiens< / INSDQualifier_value>
[0124] < / insdqualifier>
[0125] < / INSDFeature_quals>
[0126] < / insdfeature>
[0127] < / INSDSeq_feature-table>
[0128] <INSDSeq_sequence> ccgtgtgtcaagatttggt< / INSDSeq_sequence>
[0129] < / insdseq>
[0130] < / sequencedata>
[0131] <sequencedata sequenceidnumber="3">
[0132] <insdseq>
[0133] <INSDSeq_length>22< / INSDSeq_length>
[0134] <INSDSeq_moltype>DNA< / INSDSeq_moltype>
[0135] <INSDSeq_division>PAT< / INSDSeq_division>
[0136] <INSDSeq_feature-table>
[0137] <insdfeature>
[0138] <INSDFeature_key>source< / INSDFeature_key>
[0139] <INSDFeature_location>1..22< / INSDFeature_location>
[0140] <INSDFeature_quals>
[0141] <insdqualifier>
[0142] <INSDQualifier_name>mol_type< / INSDQualifier_name>
[0143] <INSDQualifier_value>other DNA< / INSDQualifier_value>
[0144] < / insdqualifier>
[0145] <insdqualifier id="q6">
[0146] <INSDQualifier_name>organism< / INSDQualifier_name>
[0147] <INSDQualifier_value>Homo sapiens< / INSDQualifier_value>
[0148] < / insdqualifier>
[0149] < / INSDFeature_quals>
[0150] < / insdfeature>
[0151] < / INSDSeq_feature-table>
[0152] <INSDSeq_sequence>gattatcaacaaatgtcacgag< / INSDSeq_sequence>
[0153] < / insdseq>
[0154] < / sequencedata>
[0155] < / st26sequencelisting>
[0156] <---