Updated Version Research Articles

Impact of Pharmacist-Provided Education Using New Information Sheets on Activation in Patients Treated with Oral Antineoplastic Drugs (IMPACT-OAD Project).

Oral antineoplastic drugs (OADs) play an increasing role in the treatment of cancer. Patients must have a high degree of understanding and autonomy to manage the numerous adverse effects at home. In Quebec, recommendations have been made for oncology pharmacists to systematically counsel all patients who are starting an OAD. To measure the impact of education provided by oncology pharmacists on patient activation. In this prospective, single-centre, observational cohort study, patients starting an OAD received education from oncology pharmacists, who used the 2020 updated version of information sheets from the Groupe d'étude en oncologie du Québec (GEOQ, www.geoq.info). The Patient Activation Measure (PAM-13) questionnaire was used to measure patients' activation before and after the intervention. Of the 43 patients recruited in the intention-to-treat analysis, 41 were included in the modified intention-to-treat analysis. The mean difference between PAM-13 scores before and after the intervention was 2.30 (standard deviation [SD] 11.85) (p = 0.22) in the intention-to-treat analysis and 3.63 (SD 10.33) (p = 0.032) in the modified intention-to-treat analysis; these differences were less than the 5 points required for a result to be considered clinically meaningful. None of the effect-modifying variables for which data were collected had a significant impact on the degree of activation; however, a weak negative correlation was observed between the level of health literacy and the change in PAM-13 score. The study did not show a clinically meaningful change in patient activation following pharmacist-provided education, according to the updated GEOQ information sheets. Further studies are needed to evaluate these data in a larger population and to determine whether the impact of education persists beyond the first treatment cycle.

The Constant K and the Gaussian temporal evolution for COVID-19 & new wave of COVID -X

This paper is an invitation from the South Florida Journal of Development[1] for the republication of an original version published in reference (A - Balloni & Winter, 2020). This paper presents a slightly updated version of the original publication and includes "Recommendations2" concerns about a possible new wave of COVID-X in the section. This republication has been allowed by the IJONEST Journal and iLSET conference (A, B, C: Balloni, A. J. & Winter, R. (2020). The paper presents the Gaussian temporal evolution of Corona Virus, the temporal average constant Ktemporal average constant = Kt. The Kt and its standard deviation come from the 52 experimental Gaussian distribution analysis -histogram-. We have analyzed all histograms from 185 countries presented in the reference (Johns Hopkins, 2020), and we found 52 countries have a definite trend toward an experimental Gaussian profile. As a result, we found Kt = K52 countries = (35 ± 5) days - average & standard deviation-. Using an experimental Gaussian got in reference (Johns Hopkins, 2020), we also calculate the temporal evolution of the World, the constant Kworld. We found Kworld = Kw = (47 ± ½) days. Finally, up to April 20/2020, only 52 (C: Balloni, A. J. & Winter, R. (2020)) of 185 countries present trends toward an experimental Gaussian profile (Johns Hopkins, 2020). The main conclusion from this short communication is that the standard deviation found -Kt = (35 ± 5) days-is very low, which is very good. Therefore, we may conclude that the maximum spread of the Corona contamination should occur in "a maximum" of up to 40 days from the first registered contamination and, in the worst scenario, up to 30 days. Regarding the Brazil peak of contamination, on March 10/2020, we carried out A PREVISION, and in that time, we affirmed by reasoning that the peak in Brazil would be around 10-15 April/2020. We confirm this prevision, as presented in the ILSET/2020 Congress (C: Balloni, A. J. & Winter, R. (2020)). For our next prevision, the decrease from contamination must trend to zero within 30-40 days after the peak contamination, and we also confirm this prevision as presented in the ILSET/2020 Congress (C: Balloni, A. J. & Winter, R. (2020)). These are the most critical situations because the real zero takes a while to get null, and the contamination starts all over if no personal safety, such as social reclusion & mask protection use, are adopted. Finally, we have observed that the Kw has a shifting in the function of the time, and our finding explains this. The last section, "Recommendations, item 2," presents concerns about a possible new wave of COVID-X.

Ethics of research

Ethics of research

Concept of dementia (Nisy ā n) in Unani system of medicine and scientific validation of an important Unani pharmacopoeial preparation 'Majoon Vaj' for its management: a review.

This review focused on the concept of dementia in the Unani system of medicine and comprehensive, updated information on Majoon Vaj about the phytochemistry, nootropic, CNS activities and provide insights into potential opportunities for future research. The classical literature on Majoon Vaj for its anti-dementic properties, and therapeutic uses were gathered from nearly thirteen classical Unani books including Unani Pharmacopoeia. The information of pharmacognosy, phytochemical and pharmacological activities of Majoon Vaj and its ingredient was collected by browsing the Internet (PubMed, ScienceDirect, Wiley online library, Google Scholar, ResearchGate). The relevant primary sources were probed, analysed, and included in this review. The keywords used to browse were Majoon Vaj, Dementia, Nootropic, Acorus calamus, Piper nigram, Zingiber officinalis, Nigella sativa, Carum carvi, Plumbago zeylanica, and β-asarone. Relevant Sources were gathered up to July 2021, and the chemical structures were drawn using ACD/ChemSketch software. The species name and synonyms were checked with WFO (2021): World Flora online (http://www.worldfloraonline.org) an updated version of 'The Plant List.' Majoon Vaj contains an excess of bioactive compounds e.g., alkaloids, phenols, flavonoids, tannins, diterpenes, coumarins, carbohydrates, and fixed oils and its ingredients possess broad pharmacological properties, including cognitive-enhancing, neuroprotective, anti-inflammatory, antioxidant and antimicrobial properties. The literature of Unani medicine is quite rich in discussing the pathophysiological basis of memory disorders. It argues that memory, retention, and retrieval are regulated by a complex process involving various faculties. Majoon Vaj seems to have great potential for therapeutic applications in the treatment of dementia and thus encourage more preclinical and clinical trials in this field.

A reliable optimization framework for parameter identification of single‐diode solar photovoltaic model using weighted velocity‐guided grey wolf optimization algorithm and Lambert‐W function

AbstractIn estimating the parameters of the five unknown parameters Single‐Diode Model (SDM) of the solar photovoltaic (PV) model, a non‐linear equation for the PV cell current is typically utilized. Then, the error between the estimated current and measured current is computed using the objective function called Root‐Mean‐Square‐Error (RMSE). In order to compute the PV cell current in SDM, an iterative method built on the Lambert‐W function is presented in this study. Along with the Lamber‐W function, an optimization algorithm called Weighted Velocity‐Guided Grey Wolf Optimizer (WVGGWO) is used to identify the unknown lumped parameters of SDM of the cell and the module. The proposed WVGGWO is an updated version of the original Grey Wolf Optimizer (GWO). The position update of the GWO has been modified, and the weightage has been provided for the wolf hierarchy. Additionally, by emphasizing the lengthening of each leading wolf's steps towards the others in the earlier search while emphasizing the shortening of the steps while reaching the later iterations, WVGGWO improves both the exploration and exploitation of the original GWO. Four case studies are considered for testing the validity of the proposed algorithm along with the Lambert‐W function. The performance of the proposed approach is compared with seven other well‐known algorithms. The results demonstrate that the suggested approach produces better outcomes than many optimization algorithms.

Version 1.3-BANSHEE—A MATLAB toolbox for Non-Parametric Bayesian Networks

This update (version 1.3) of our contribution BANSHEE—A MATLAB toolbox for Non-Parametric Bayesian Networks provides functional updates. Additions to the software package include quantifying fully parametric Bayesian Networks, drawing a user-defined sample size number of (un)conditional samples, sample-based conditioning sampling, and choosing different sample sizes for the model-validation tests based on the Hellinger distance. The use of the t copula in the Cramér–Von Mises test is also added. New detailed examples demonstrating the new features available are also provided.

Four Decades of Trends and Drivers of Global Surface Ocean Acidification

AbstractThe oceans are acidifying in response to the oceanic uptake of anthropogenic carbon dioxide (CO2) from the atmosphere, yet the global‐scale progression of this acidification has been poorly documented so far by observations. Here, we fill this gap and use an updated version of the in situ and satellite observation‐based product OceanSODA‐ETHZ to determine the trends and drivers of the surface ocean aragonite saturation state (Ωar) and pH = –log([H+]) (total scale) over the last four decades (1982–2021). In the global mean, Ωar and pH declined at rates of −0.071 ± 0.006 decade−1 and −0.0166 ± 0.0010 decade−1, respectively, with the errors of the trends largely reflecting the uncertainties in the reconstructed pH and Ωar fields. These global mean trends are driven primarily by the increase in surface ocean concentration of dissolved inorganic carbon (DIC) in response to the uptake of anthropogenic CO2, but moderated by changes in natural DIC. Surface warming enhances the decrease in pH, accounting for ∼15% of the global trend. The long‐term trends vary substantially across regions and also differ distinctly between pH and Ωar. The highest trends in pH are found in the high latitudes, while Ωar decreases the fastest in the low latitudes. These regional differences are primarily a consequence of regional differences in the ability of the surface ocean to take up and buffer the anthropogenic CO2. Substantial El Niño‐driven interannual variability is superimposed on these trends, with Ωar showing greater variability than pH, resulting in substantially longer time of emergence for Ωar.

Corrigendum to “Iron complexes of [2 + 2] and [6 + 6] Schiff-base macrocycles derived from 2,2′-oxydianiline and their applications” [Inorg. Chem. Commun. 139 (2022) 109376

• The correct formula of 3 is [Fe 2 (L 2 H 4 )][FeBr 3 OFeBr 3 ] 2 ‧8MeCN. • The revised CIF has been deposited with the CSD • An updated version of the supplementary information file is provided.

Evaluation Criteria for Psychosomatic Practice

To diagnose and treat somatic disorders while considering psychosocial factors, medical and psychological practices require a comprehensive and operationalized list of criteria. The Evaluation Criteria for Psychosomatic Practice (ECPP) has been developed to address this need. It builds upon the updated version of the Diagnostic Criteria for Psychosomatic Research (DCPR) by incorporating significant psychodynamic factors and restructuring its framework to better cater to the practical demands of clinical assessment, diagnosis, treatment planning, and outcome monitoring. It offers four axes for clinical evaluation that can be used together or separately, depending on the needs of diagnostic process, treatment, informing the patient, or research: psychosomatic symptoms and complaints, risk factors related to personality structure, triggers, and secondary risk factors. By utilizing the ECPP’s four axes, clinicians can gain a deeper understanding of how psychosocial factors impact the clinical picture and dynamics of somatic disorders and then effectively communicate this knowledge to patients, improving compliance and collaboration in treatment. Additionally, the ECPP’s framework allows for a balance of psychological, physical, and social treatment interventions that can be tailored to the specific needs of the patient, ultimately leading to better treatment outcomes.

Distributional Censored and Uncensored Validation Testing under a Modified Test Statistic with Risk Analysis and Assessment

This paper introduces and studies a unique probability distribution. The maximum likelihood estimation, the ordinary least squares, the weighted least squares, and the Anderson–Darling estimation methods all take into account a number of financial risk indicators, including the value-at-risk, tail-value-at-risk, tail variance, tail mean-variance, and mean excess loss function. These four approaches were used in a simulation study and an application to insurance claims data for the actuarial evaluation. The well-known Nikulin–Rao–Robson statistic is taken into consideration for distributional validation under the whole set of data. Three complete actual datasets and a simulation study are used to evaluate the Nikulin–Rao–Robson test statistic. An updated version of the Nikulin–Rao–Robson statistic is taken into consideration for censored distributional validation. Three censored actual datasets and a thorough simulation analysis are used to evaluate the novel Nikulin–Rao–Robson test statistic.

Cybersecurity Technology Foresight: 2040 Scenarios for Turkey

Foresight is a methodical and comprehensive approach that prioritizes investment and research in order to shape the future and implement future strategies. Cybersecurity, one of the most important elements of Industry 4.0, is to protect information and communication systems against cyber attacks and to ensure the availability, confi-dentiality and integrity of these systems and the data therein. This study aims to make a theoretical and practical contribution to foresight and cybersecurity studies by summarizing the updated version of the methods and outputs used in the doctoral thesis titled “Technology Foresight and Modeling: Turkish Cybersecurity Foresight 2040”, con-ducted at Middle East Technical University (METU) in 2019. As a result of the study, Turkey's national cybersecurity technology foresight was given with different scenarios; Turkey's strengths, weaknesses, opportunities and threats in terms of cybersecurity were determined; a cybersecurity technology taxonomy which is officially accepted by the Presidency of Defense Industries was created; the cybersecurity status of the universities and companies in Turkey has been determined; and concrete policy recommendations based on foresight outputs have been put forward. The study is the most comprehensive cybersecurity foresight in Turkey in terms of topics covered and participants, which comprises nearly 150 experts from government, military, academia, and the private sector. Overall, the study provides important insights into the current state of cybersecurity in Turkey and makes recommendations for the future. Its wide range of stakeholders and comprehensive analysis make it a valuable resource for understanding the complex landscape of cybersecurity in the country.

The Outcomes of Allogenic Bone Marrow Transplantation for BThalassemia Major Patients: Single-Centre Experience

Objectives: The Primary objective of this study is to assess the outcome of Allogenic Bone Marrow Transplantation for B- Thalassemia Major (B-TM) Patients at KFSHD, also to compare our local results with international outcomes, and to identify the complications of this modality of treatment in our cohort. Design: This is a retrospective descriptive study. It includes all patients’ less16 year transfusion-dependent, b-TM patients who underwent matched-related donor (MRD) allogeneic stem cell transplantation at KFSHD, pediatric hematology/ oncology department between January 2013 and December 2020. Total number of cohort is 21 patients. Methods: After obtaining the IRB approval, all the data and information were retrieved from the patients’ hard and electronic medical records and then computerized using a Microsoft Excel sheet. Computerized data exported to (SPSS) program updated version 24 (IBM Corp., Armonk, NY, USA) which was used for analysis of the data. Results: The results of the 21 patients with b-TM who underwent MRD allogenic BMT at KFSHD highlighted the role of MRD/BMT as curative therapy of b-TM with no increase in transplantation-related complications when compared with similar results. In our study, SOS rate was found to be 33.3%, GVHD was 23.8% but non-invasive infections were 76.2%, which is high but not influential. The overall survival (OS) was 90.5% and the disease-free survival (DFS) was 95.2%. Conclusion: Because of the perfect, promising figures of survival for stem cell transplantation in b-thalassemia major (b-TM) patients during the last decades and the noticeable improvement in the quality of their life after that, and since our study showed similar good comparable outcome and survival rates with other international centers, we strongly recommend early transplantation for b-TM if a suitable donor is available in an experienced BMT center. The overall survival (OS) was 90.5% and the disease-free survival (DFS) was 95.2%, which are comparable outcomes with other international similar centers.

Two components of the forensic assessment process and severity of nonlife-threatening local musculoskeletal injuries: a review of the article “Controversial issues of the use of medical criteria ‘persistent loss of general working capacity’ in determining the severity of harm caused to human health”

In the article, the doctrine of denying a forensic medical assessment of the severity of local injuries of the musculoskeletal system, which are not life-threatening, is considered from a critical position, based on an interdisciplinary approach, without considering the influence of medical care. The article shows the inconsistency, still present among some forensic physicians, of the opinion that determining the severity of harm to health by causing nonlife-threatening injuries without the fact of a determined outcome is allegedly expressed in violation of the basic provisions of the Criminal Code of the Russian Federation. In the context of the topic, the author reasonably points to the two-component essence of the definition of clause 6.11, 194th order of the Ministry of Health and Social Development of Russia of 2008, dated April 24, 2008, N 194n On approval of medical criteria for determining the severity of harm caused to human health. The fundamental explanatory provisions of the conceptual construction of the wording of clause 6.11 are provided in criminal law and medical relations. The author showed that there were no inconsistencies between these components. The presence of a list of medical criteria for harm to health of a similar direction, as in the existing paragraph 6.11, demonstrates the objective need in the updated version of the draft order of the Ministry of Health of Russia On approval of the procedure for determining the severity of harm caused to human health.

Use of long short-term memory network (LSTM) in the reconstruction of missing water level data in the River Seine

ABSTRACT This paper aims to fill in the missing time series of hourly surface water levels of some stations installed along the River Seine, using the long short-term memory (LSTM) algorithm. In our study, only the water level data from the same station, containing many missing parts, were used as input and output variables, in contrast to other works where several features are available to take advantage of e.g. other station data/physical variables. A sensitive analysis is presented on both the network properties and how the input and output data are reentered to better determine the appropriate strategy. Numerous scenarios are presented, each an updated version of the previous one. Ultimately, the final version of the model can impute missing values of up to one year of hourly data with great flexibility (one-year Root-Mean-Square Error (RMSE) = 0.14 m) regardless of the location of the missing gaps in the series or their size.

Treatment Algorithm for Patients With Gastric Adenocarcinoma: Austrian Consensus on Systemic Therapy - An Update.

Over the last decade, therapeutic options for patients with gastric cancer have improved significantly. However, despite these recent advances, mortality is still substantial. Surgery and chemotherapy represent the cornerstones of patient management. Immune checkpoint inhibitors as well as targeted treatments such as HER2-directed therapies and antiangiogenic agents contribute to improved patient prognosis. Herein, we present the updated version of an Austrian consensus on the systemic treatment of patients with gastric adenocarcinoma and adenocarcinoma of the lower gastroesophageal junction, including those with human epidermal growth receptor 2 (HER2) overexpression, microsatellite instability, programmed death-ligand 1 (PD-L1)-positive disease, and claudin 18.2 positivity. The consensus considers the curative setting as well as first-line and later-line systemic treatment options in advanced disease. For HER2-positive disease, HER2 testing is discussed in addition to a review of first-line and later-line therapies. Potential future therapies are also listed, with a focus on targeted [e.g., fibroblast growth factor receptor 2 (FGRF2)-directed] treatments that might provide a further step forward in the management of patients with gastric cancer.

P-122 Evaluation of an updated artificial intelligence embryo viability model on implantation and miscarriage

Abstract Study question Is the implantation and miscarriage prediction performance of the iDAScore model v2.0 increased as compared to the original v1.0 model? Summary answer The predictive performance is better for iDAScore v2.0 than for v1.0 on both implantation and miscarriage, although the differences did not reach statistical significance. What is known already In recent years, several artificial intelligence (AI) models for the prediction of embryo implantation based on image or time-lapse data have been published and validated in various ways. Some of these models are commercial products while others are more of an academic nature. The long-term benefit of AI models in clinical practice relies on their use in clinical routine and that the models are continuously monitored and updated. The iDAScore time-lapse model has been available from Vitrolife since 2021 and several external validations of iDAScore v1.0 have been published. An updated version (iDAScore v2.0) has recently been released. Study design, size, duration This was an observational retrospective study with data collected during the years 2019 to 2022 from one Danish clinic from fresh single embryo transfers performed on day 5. Blastocysts were selected for transfer by experienced embryologists based on morphology (Gardner score). Within the study period, we included all 849 embryos for which we had information on hCG test results, implantation (fetal heartbeat (FH) detected by ultrasound) and live birth (LB). Participants/materials, setting, methods Embryos were cultured in an EmbryoScope+ incubator (Vitrolife A/S). Time-lapse images were automatically captured throughout the incubation period. We used the original time-lapse images to calculate scores for iDAScore v1.0 and v2.0 retrospectively. For each version, the predictive performance for miscarriage (early pregnancy loss and clinical miscarriage), FH and LB prediction was expressed in terms of area under the ROC curve (AUC). Differences in performance between versions were assessed in paired comparisons of the AUCs. Main results and the role of chance The median age of the transfer recipients was 34 years. One third of the blastocysts was derived from ICSI and the remaining from standard IVF cycles. Among all transferred blastocysts, the hCG rate was 58.0% (492/849), the FH rate was 46.5% (395/849), the LB rate was 42.4% (360/849), and the overall miscarriage rate from hCG to live birth was 26.8% (132/492).The overall AUC for FH prediction was 0.652 (0.616 to 0.689) for iDAScore v2.0 compared to 0.632 (0.595 to 0.669) for v1.0. Similarly, the AUC for LB prediction was 0.644 (95% CI: 0.607 to 0.681) for iDAScore v2.0 compared to 0.626 (95% CI: 0.588 to 0.663) for iDAScore v1.0. However, these differences were not statistically significant (P-values: 0.12 for FH and 0.17 for LB) in paired comparisons.For miscarriage, we found an increase in AUC from v1.0 (0.574; 95% CI: 0.514 to 0.633) to v2.0 (0.592; 95% CI: 0.534 to 0.649), P-value: 0.40. Limitations, reasons for caution This study only includes data from a single clinic. Patient characteristics and procedures followed might not be representative for other clinics. The data is limited to blastocysts that were chosen for transfer by morphology from trained embryologists. Furthermore, the limited sample size does not provide statistically significant differences in performance. Wider implications of the findings It is important that predictive models are constantly updated and improved. Updated versions should take into account a larger database as well as potential new methodologies that evolve in the rapidly developing AI field. This study shows that the iDAScore model update seems to represent an actual performance increase. Trial registration number 1-16-02-277-22

Quantification of methane emissions in Hamburg using a network of FTIR spectrometers and an inverse modeling approach

Abstract. Methane (CH4) is a potent greenhouse gas, and anthropogenic CH4 emissions contribute significantly to global warming. In this study, the CH4 emissions of the second most populated city in Germany, Hamburg, were quantified with measurements from four solar-viewing Fourier transform infrared (FTIR) spectrometers, mobile in situ measurements, and an inversion framework. For source type attribution, an isotope ratio mass spectrometer was deployed in the city. The urban district hosts an extensive industrial and port area in the south as well as a large conglomerate of residential areas north of the Elbe River. For emission modeling, the TNO GHGco (Netherlands Organisation for Applied Scientific Research greenhouse gas and co-emitted species emission database) inventory was used as a prior for the inversion. In order to improve the inventory, two approaches were followed: (1) the addition of a large natural CH4 source, the Elbe River, which was previously not included in the inventory, and (2) mobile measurements were carried out to update the spatial distribution of emissions in the TNO GHGco gridded inventory and derive two updated versions of the inventory. The addition of the river emissions improved model performance, whereas the correction of the spatial distribution with mobile measurements did not have a significant effect on the total emission estimates for the campaign period. A comparison of the updated inventories with emission estimates from a Gaussian plume model (GPM) showed that the updated versions of the inventory match the GPM emissions estimates well in several cases, revealing the potential of mobile measurements to update the spatial distribution of emission inventories. The mobile measurement survey also revealed a large and, at the time of the study, unknown point source of thermogenic origin with a magnitude of 7.9 ± 5.3 kg h−1 located in a refinery. The isotopic measurements show strong indications that there is a large biogenic CH4 source in Hamburg that produced repeated enhancements of over 1 ppm which correlated with the rising tide of the river estuary. The CH4 emissions (anthropogenic and natural) of the city of Hamburg were quantified as 1600 ± 920 kg h−1, 900 ± 510 kg h−1 of which is of anthropogenic origin. This study reveals that mobile street-level measurements may miss the majority of total methane emissions, potentially due to sources located within buildings, including stoves and boilers operating on natural gas. Similarly, the CH4 enhancements recorded during the mobile survey from large-area sources, such as the Alster lakes, were too small to generate GPM emission estimates with confidence, but they could nevertheless influence the emission estimates based on total column measurements.

Machine learning techniques for electroencephalogram based brain-computer interface: A systematic literature review

Brain-computer interface systems with Electroencephalogram (EEG), especially those use motor-imagery (MI) signals, have demonstrated the ability to control electromechanical devices with promising results. EEG being easy to record and non-invasive makes it a good choice for BCI systems. MI-based BCI systems compute neuronal activity and decipher these electrical impulses into gestures or effects, aiming to enable the person to communicate with their surroundings. This study summarises techniques of EEG signal processing used in the recent decade. This research paper presents an exhaustive survey on four aspects of EEG signals in BCI systems: signal acquisition, signal pre-processing, feature extraction, and classification. The most prominent time-frequency technique, wavelet transform (WT), and its updated version, wavelet packet transform (WPT), is primarily used in EEG-BCI systems for feature extraction. The development of artificial intelligence technology motivated researchers to classify motor imagery signals for BCI systems using machine learning (ML) and deep learning (DL) techniques. This literature survey paper explores more than 220 research papers related to ML and DL approaches to classify EEG signals for BCI systems. In order to identify prospective research areas for future investigation, present challenges are carefully considered, and suggestions are also provided for appropriate feature extraction and classification techniques. The authors expect that the investigation presented in this paper will help researchers to find accurate feature extraction, ML, and DL methods and these techniques will be supportive in devising an effective EEG-BCI system.

Identification of further variation at the lipooligosaccharide outer core locus in Acinetobacter baumannii genomes and extension of the OCL reference sequence database for Kaptive.

The outer core locus (OCL) that includes genes for the synthesis of the variable outer core region of the lipooligosaccharide (LOS) is one of the key epidemiological markers used for tracing the spread of Acinetobacter baumannii, a bacterial pathogen of global concern. In this study, we screened 12 476 publicly available A. baumannii genome assemblies for novel OCL sequences, detecting six new OCL types that were designated OCL17-OCL22. These were compiled with previously characterized OCL sequences to create an updated version of the A. baumannii OCL reference database, providing a total of 22 OCL reference sequences for use with the bioinformatics tool Kaptive. Use of this database against the 12 476 downloaded assemblies found OCL1 to be the most common locus, present in 73.6 % of sequenced genomes assigned by Kaptive with a match confidence score of good or above. OCL1 was most common amongst isolates belonging to sequence types (STs) ST1, ST2, ST3 and ST78, all of which are over-represented clonal lineages. The highest level of diversity in OCL types was found in ST2, with eight different OCLs identified. The updated OCL reference database is available for download from GitHub (https://github.com/klebgenomics/Kaptive; under version v. 2.0.5), and has been integrated for use on Kaptive-Web (https://kaptive-web.erc.monash.edu/) and PathogenWatch (https://pathogen.watch/), enhancing current methods for A. baumannii strain identification, classification and surveillance.

Are We There Yet?

Problem, research strategy, and findings In 2020, Berke and Conroy demonstrated that plan policies did not promote sustainability principles strongly or in a balanced fashion. Has this changed in the intervening years? We conducted a longitudinal analysis of the policies in the updated versions of the plans in Berke and Conroy using their coding framework, comparing scores with the original plans. We found that most of the updated plans from the original study locations have an overarching sustainability vision, though this did not result in consistently higher sustainability scores. Although there were no significant differences in the strength with which sustainability principles were promoted in the updated plans, there were descriptive shifts in the promoted principles. In the updated plans, we found the same imbalance in principles promoted by present policies as in the original plans, making policy integration between principles a key consideration. The progress of policy adoption to promote sustainability principles may be slow; therefore, as more communities frame their comprehensive plans around sustainability, longitudinal studies are required to continue to track the effects of the progress. Takeaway for practice Sustainability scores for comprehensive plans have not significantly changed from 20 years ago, though more are focused on the concept of sustainability as an overarching vision. Evaluating scores over time provides insight into the nature of progress in supporting that vision.