QTL Mapping Using RIL Population.

Genetic maps are an excellent tool for the analysis of important traits, the development of which is the result of the combined expression of several genes, enabling the genomic localization of the factors determining them. Such features, characterized by a normal distribution of values, are referred to as quantitative or polygenic. The analysis of their genetic background using a chromosome map is called the mapping of quantitative traits loci (QTL). QTL analysis is a statistical method of determining the genetic association of phenotypic data (trait measurements) with genotypic data (DNA markers assigned to linkage groups).There are numerous tools developed for QTL mapping. This chapter introduces Windows QTL Cartographer with Composite Interval Mapping (CIM) method, which estimates the QTL position by combining interval mapping with multiple regression. The genotypic and phenotypic data used in the exemplary QTL mapping procedure were obtained for the recombinant inbred line (RIL) population of rye. Plant height, assessed in three seasons, was the exemplary trait under study.

Yoga for Migraine Prevention: An Ancient Practice with Evidence for Current Use.

PURPOSE OF REVIEW: The objective of this study is to review the recent literature on yoga for migraine prevention either as adjuvant or standalone therapy. Yoga is one of the most widely used complementary and integrative medicine (CIM) therapies; clinicians should be familiar with yoga practice so that they can best advise interested patients. It is also important to assess study design and types of yoga offered. Using PubMed and Litmaps, research published from 2018 to 2023 addressing yoga and migraine was assessed. RECENT FINDINGS: Two systematic reviews and six studies have recently been published on yoga as adjunctive migraine preventive treatment. There is class III evidence and a grade B recommendation for yoga as an adjunct migraine preventive treatment. Yoga has been shown to reduce headache frequency, disability, and likely also pain intensity and self-efficacy. Two studies (one in children and one in adults) suggested that yoga as standalone migraine preventive treatment reduces pain intensity, disability, and perceived stress. More research is needed on the long-term efficacy (including change in monthly migraine days specifically in addition to headache frequency) and adherence to yoga practice for the prevention of migraine. In addition, to our knowledge, there is no study evaluating yoga practice in the prodromal or headache phase of migraine as acute treatment.

RoBétArmé Project: Human-robot collaborative construction system for shotcrete digitization and automation through advanced perception, cognition, mobility and additive manufacturing skills.

The importance of construction automation has grown worldwide, aiming to deliver new machineries for the automation of roads, tunnels, bridges, buildings and earth-work construction. This need is mainly driven by (i) the shortage and rising costs of skilled workers, (ii) the tremendous increased needs for new infrastructures to serve the daily activities and (iii) the immense demand for maintenance of ageing infrastructure. Shotcrete (sprayed concrete) is increasingly becoming popular technology among contractors and builders, as its application is extremely economical and flexible as the growth in construction repairs in developed countries demand excessive automation of concrete placement. Even if shotcrete technology is heavily mechanized, the actual application is still performed manually at a large extend. RoBétArméEuropean project targets the Construction 4.0 transformation of the construction with shotcrete with the adoption of breakthrough technologies such as sensors, augmented reality systems, high-performance computing, additive manufacturing, advanced materials, autonomous robots and simulation systems, technologies that have already been studied and applied so far in Industry 4.0. The paper at hand showcases the development of a novel robotic system with advanced perception, cognition and digitization capabilities for the automation of all phases of shotcrete application. In particular, the challenges and barriers in shotcrete automation are presented and the RoBétArmésuggested solutions are outlined. We introduce a basic conceptual architecture of the system to be developed and we demonstrate the four application scenarios on which the system is designated to operate.

The RoBétArmé European project targets the Construction 4.0 transformation of the construction with shotcrete with the adoption of breakthrough technologies such as sensors, augmented reality systems, high-performance computing, additive manufacturing, advanced materials, autonomous robots and simulation systems, technologies that have already been studied and applied so far in Industry 4.0. This paper showcases a case study on which novel robotic systems will be developed for the automation of shotecrete application. The outcomes of this research can be widely used in other application technologies related to the construction domain.

Biological activities, identification, method development, and validation for analysis of polyphenolic compounds in Nymphaea rubra flowers and leaves by UHPLC-Q-cIM-TOF-MS and UHPLC-TQ-MS.

INTRODUCTION: Nymphaea rubra belongs to the Nymphaea family and is regarded as a vegetable used in traditional medicine to cure several ailments. These species are rich in phenolic acid, flavonoids, and hydrolysable tannin. OBJECTIVE: This study aimed to assess the biological activities of Nymphaea rubra flowers (NRF) and leaves (NRL) by identifying and quantifying their polyphenolic compounds using ultra-performance liquid chromatography coupled to quadrupole cyclic ion mobility time-of-flight mass spectrometry (UHPLC-Q-cIM-TOF-MS) and triple quadrupole mass spectrometry (UHPLC-TQ-MS). METHODOLOGY: NRF and NRL powder was extracted with methanol and fractionated using hexane, ethylacetate, and water. Antioxidant and α-glucosidase, and tyrosinase enzyme inhibitory activities were evaluated. The polyphenolic components of NRF and NRL were identified and quantified using UHPLC-Q-cIM-TOF-MS and UHPLC-TQ-MS. The method was validated using linearity, precision, accuracy, limit of detection (LOD), and lower limit of quantification (LLOQ). RESULTS: Bioactive substances and antioxidants were highest in the ethylacetate fraction of flowers and leaves. Principal component analysis showed how solvent and plant components affect N. rubra's bioactivity and bioactive compound extraction. A total of 67 compounds were identified, and among them 21 significant polyphenols were quantified. Each calibration curve had R2 > 0.998. The LOD and LLOQ varied from 0.007 to 0.09 µg/mL and from 0.01 to 0.1 µg/mL, respectively. NRF contained a significant amount of gallic acid (10.1 mg/g), while NRL contained abundant pentagalloylglucose (2.8 mg/g). CONCLUSION: The developed method is simple, rapid, and selective for the identification and quantification of bioactive molecules. These findings provide a scientific basis for N. rubra's well-documented biological effects.

Validation of the Diagnostic Accuracy Levels of International Classification of Diseases, 10th Revision Codes for Diabetic Ketoacidosis: A Multicentre, Cross-sectional Study of Adults.

OBJECTIVES: International Classification of Diseases (ICD) codes are commonly used to identify cases of diabetic ketoacidosis (DKA) in health services research, but they have not been validated. Our aim in this study was to assess the accuracy of ICD, 10th revision (ICD-10) diagnosis codes for DKA. METHODS: We conducted a multicentre, cross-sectional study using data from 5 hospitals in Ontario, Canada. Each hospitalization event has a single most responsible diagnosis code. We identified all hospitalizations assigned diagnosis codes for DKA. A true case of DKA was defined using laboratory values (serum bicarbonate ≤18 mmol/L, arterial pH ≤7.3, anion gap ≥14 mEq/L, and presence of ketones in urine or blood). Chart review was conducted to validate DKA if laboratory values were missing or the diagnosis of DKA was unclear. Outcome measures included positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity of ICD-10 codes in patients with laboratory-defined DKA. RESULTS: We identified 316,517 hospitalizations. Among these, 312,948 did not have an ICD-10 diagnosis code for DKA and 3,569 had an ICD-10 diagnosis code for DKA. Using a combination of laboratory and chart review, we identified that the overall PPV was 67.0%, the NPV was 99.7%, specificity was 99.6%, and sensitivity was 74.9%. When we restricted our analysis to hospitalizations in which DKA was the most responsible discharge diagnosis (n=3,374 [94.5%]), the test characteristics were PPV 69.8%, NPV 99.7%, specificity 99.7%, and sensitivity 71.9%. CONCLUSION: ICD-10 codes can identify patients with DKA among those admitted to general internal medicine.

Cation-independent mannose 6-phosphate receptor: From roles and functions to targeted therapies.

The cation-independent mannose 6-phosphate receptor (CI-M6PR) is a ubiquitous transmembrane receptor whose main intracellular role is to direct enzymes carrying mannose 6-phosphate moieties to lysosomal compartments. Recently, the small membrane-bound portion of this receptor has appeared to be implicated in numerous pathophysiological processes. This review presents an overview of the main ligand partners and the roles of CI-M6PR in lysosomal storage diseases, neurology, immunology and cancer fields. Moreover, this membrane receptor has already been noted for its strong potential in therapeutic applications thanks to its cellular internalization activity and its ability to address pathogenic factors to lysosomes for degradation. A number of therapeutic delivery approaches using CI-M6PR, in particular with enzymes, antibodies or nanoparticles, are currently being proposed.

Bridging upstream and downstream for improved adenovirus 5 bioprocess.

Adenoviruses are well-known viral vectors that have been previously used in gene therapy and as a vaccine-delivery vehicle for humans and animals. During the COVID-19 pandemic, it gained renewed attention, but at the same time, it raised concerns due to side effects observed with some of the resulting vaccines administered to patients. It has been indicated that these side effects might be attributed to impurities present in the final product. Therefore, constant enhancement of the vaccine purity and further improvement of impurity detection methods are needed. In this work, we showcase an example of industry-relevant adenovirus bioprocess optimization. Our data show the effect of upstream parameters on the bioburden introduced to the downstream process. We provide an example of process optimization using a combination of the PATfix analytical method, ddPCR, infectivity, total DNA, and total protein analyses to optimize cell density, multiplicity of infection, and length of production. Additionally, we provide data illustrating the robustness of the convective interaction media quaternary amine monolithic chromatography step. This anion exchange strategy was shown to remove over 99% of protein and DNA impurities, including those unable to be addressed by tangential flow filtration, while maintaining high adenovirus recoveries.

[ICD-11: New revision and impact of this classification in psychiatry]. / CIM-11 (OMS) : nouvelle révision et impact de la classification onusienne en psychiatrie.

OBJECTIVES: After more than 20 years of work, the World Health Organization's efforts have culminated in the adoption of the 11th revision of the International Classification of Diseases (ICD-11). The process has been guided by the principles of global applicability, scientific validity, and clinical utility. The update of the chapter on mental, behavioral, and neurodevelopmental disorders (MBND) within the ICD-11 has generated widespread interest worldwide. This has raised various questions about the status of mental disorder nosology, changes to diagnostic guidelines, and the potential implications for clinical practice. METHODS: We conducted a narrative analysis of the literature in four different languages to track the various stages of the ICD-11 revision and to highlight the major changes. We searched databases such as PubMed, EMBASE, MEDLINE, and Google Scholar, and consulted the official websites of the WHO, APA, and UNICEF. A total of 79 articles from 40 different editorials and websites were analyzed and included in this study. RESULTS: The new chapters on mental disorders in the ICD-11 include 21 groups, as opposed to the 11 in the ICD-10. The changes aim to align the diagnoses with those of the DSM-5 and introduce a new chapter structure, new diagnostic categories, modifications to diagnostic criteria, and advancements in dimensionality. For the first time in the history of the ICD, sleep and wakefulness disorders, as well as disorders related to sexual health, have been addressed in separate chapters of the international classification. Four new diagnoses have been added: complex post-traumatic stress disorder (PTSD), gaming disorder, prolonged grief disorder, and compulsive sexual behavior which replaces "excessive sexual activity" in the ICD-10. Moreover, the ICD-11 revision has brought about a fundamental change in the clinical conceptualization of addictive behaviors, introducing a distinction between substance use disorders and addictive behaviors. The criteria for many existing conditions have been revised, particularly those related to bipolar disorders, eating disorders, and gender identity disorders. CONCLUSIONS: The revision process for mental, behavioral, and neurodevelopmental disorders in the ICD-11 has witnessed unprecedented participation in the history of mental disorder classification. These changes could have a significant impact on clinical practice in psychiatry. However, it is crucial to examine the advantages and limitations of this new classification compared to previous versions.

Clozapine-induced myocarditis and subsequent rechallenge: a narrative literature review and case report.

Clozapine is an antipsychotic medication that has been proven effective for the management of treatment-resistant schizophrenia (TRS). For some patients, it is the only medication that can improve disease burden and quality of life. Clozapine comes with various potentially serious adverse effects which may dissuade physicians from prescribing it despite its well-documented efficacy. One of these adverse effects is clozapine-induced myocarditis (CIM). Due to these risks, patients who undergo a clozapine rechallenge after CIM require close monitoring. Myocardial damage can be reversible if CIM is promptly identified, and clozapine is discontinued appropriately. The gold-standard for diagnosing myocarditis is an endomyocardial biopsy but there are no clear recommendations for how to use less invasive screening assessments to monitor for CIM during a clozapine rechallenge. This review article aims to increase awareness of CIM and provide guidance on monitoring and management. The accompanying case report presents a proposed strategy, including biomarkers that were used to identify inflammation and cardiac injury which guided the treatment of an adolescent patient who had a successful clozapine rechallenge. Further research is necessary to validate the proposed monitoring protocol and to further advance guidance for clinicians.

La clozapine est une médication antipsychotique qui s'est révélée efficace pour la prise en charge de la schizophrénie résistante au traitement (SRT). Pour certains patients, c'est le seul médicament qui peut améliorer le fardeau de la maladie et la qualité de vie. La clozapine s'accompagne de divers effets secondaires potentiellement sérieux qui peuvent empêcher les médecins de la prescrire, malgré son efficacité bien documentée. L'un de ces effets indésirables est la myocardite induite par la clozapine (MIC). En raison de ces risques, les patients qui subissent une nouvelle provocation à la clozapine après une MIC demandent une surveillance étroite. Les lésions myocardiques peuvent être réversibles si la MIC est rapidement identifiée et que la clozapine est interrompue de façon appropriée. La référence en matière de diagnostic de myocardite est une biopsie endomyocardique mais il n'y a pas de recommandations nettes sur la façon d'utiliser des évaluations de dépistage moins invasives pour surveiller la MIC durant une nouvelle provocation à la clozapine. Le présent article de revue vise à accroître la connaissance de la MIC et à offrir un guide de la surveillance et de la gestion. Le rapport de cas ci-joint présente une stratégie proposée, notamment des biomarqueurs qui ont servi à identifier l'inflammation et la blessure cardiaque qui a guidé le traitement d'un patient adolescent ayant subi une provocation à la clozapine réussie. Il faut plus de recherche pour valider le protocole de surveillance proposé et faire avancer le guide pour les cliniciens.

Design Strategies of 40 nm Split-Gate NOR Flash Memory Device for Low-Power Compute-in-Memory Applications.

The existing von Neumann architecture for artificial intelligence (AI) computations suffers from excessive power consumption and memory bottlenecks. As an alternative, compute-in-memory (CIM) technology has been emerging. Among various CIM device candidates, split-gate NOR flash offers advantages such as a high density and low on-state current, enabling low-power operation, and benefiting from a high level of technological maturity. To achieve high energy efficiency and high accuracy in CIM inference chips, it is necessary to optimize device design by targeting low power consumption at the device level and surpassing baseline accuracy at the system level. In split-gate NOR flash, significant factors that can cause CIM inference accuracy drop are the device conductance variation, caused by floating gate charge variation, and a low on-off current ratio. Conductance variation generally has a trade-off relationship with the on-current, which greatly affects CIM dynamic power consumption. In this paper, we propose strategies for designing optimal devices by adjusting oxide thickness and other structural parameters. As a result of setting Tox,FG to 13.4 nm, TIPO to 4.6 nm and setting other parameters to optimal points, the design achieves erase on-current below 2 µA, program on-current below 10 pA, and off-current below 1 pA, while maintaining an inference accuracy of over 92%.

Uncovering the Resistance Mechanisms in Extended-Drug-Resistant Pseudomonas aeruginosa Clinical Isolates: Insights from Gene Expression and Phenotypic Tests.

(1) Background: The purpose of the study was to describe the activity of mex efflux pumps in Multidrug-Resistant (MDR) clinical isolates of Pseudomonas aeruginosa and to compare the carbapenem-resistance identification tests with PCR; (2) Methods: Sixty MDR P. aeruginosa were analyzed for detection of carbapenemase by disk diffusion inhibitory method, carbapenem inactivation method and Modified Hodge Test. Endpoint PCR was used to detect 7 carbapenemase genes (blaKPC, blaOXA48-like, blaNDM, blaGES-2, blaSPM, blaIMP, blaVIM) and mcr-1 for colistin resistance. The expression of mexA, mexB, mexC, mexE and mexX genes corresponding to the four main efflux pumps was also evaluated; (3) Results: From the tested strains, 71.66% presented at least one carbapenemase gene, with blaGES-2 as the most occurring gene (63.3%). Compared with the PCR, the accuracy of phenotypic tests did not exceed 25% for P. aeruginosa. The efflux pump genes were present in all strains except one. In 85% of the isolates, an overactivity of mexA, mexB and mostly mexC was detected. Previous treatment with ceftriaxone increased the activity of mexC by more than 160 times; (4) Conclusions: In our MDR P. aeruginosa clinical isolates, the carbapenem resistance is not accurately detected by phenotypic tests, due to the overexpression of mex efflux pumps and in a lesser amount, due to carbapenemase production.

FinFET 6T-SRAM All-Digital Compute-in-Memory for Artificial Intelligence Applications: An Overview and Analysis.

Artificial intelligence (AI) has revolutionized present-day life through automation and independent decision-making capabilities. For AI hardware implementations, the 6T-SRAM cell is a suitable candidate due to its performance edge over its counterparts. However, modern AI hardware such as neural networks (NNs) access off-chip data quite often, degrading the overall system performance. Compute-in-memory (CIM) reduces off-chip data access transactions. One CIM approach is based on the mixed-signal domain, but it suffers from limited bit precision and signal margin issues. An alternate emerging approach uses the all-digital signal domain that provides better signal margins and bit precision; however, it will be at the expense of hardware overhead. We have analyzed digital signal domain CIM silicon-verified 6T-SRAM CIM solutions, after classifying them as SRAM-based accelerators, i.e., near-memory computing (NMC), and custom SRAM-based CIM, i.e., in-memory-computing (IMC). We have focused on multiply and accumulate (MAC) as the most frequent operation in convolution neural networks (CNNs) and compared state-of-the-art implementations. Neural networks with low weight precision, i.e., <12b, show lower accuracy but higher power efficiency. An input precision of 8b achieves implementation requirements. The maximum performance reported is 7.49 TOPS at 330 MHz, while custom SRAM-based performance has shown a maximum of 5.6 GOPS at 100 MHz. The second part of this article analyzes the FinFET 6T-SRAM as one of the critical components in determining overall performance of an AI computing system. We have investigated the FinFET 6T-SRAM cell performance and limitations as dictated by the FinFET technology-specific parameters, such as sizing, threshold voltage (Vth), supply voltage (VDD), and process and environmental variations. The HD FinFET 6T-SRAM cell shows 32% lower read access time and 1.09 times better leakage power as compared with the HC cell configuration. The minimum achievable supply voltage is 600 mV without utilization of any read- or write-assist scheme for all cell configurations, while temperature variations show noise margin deviation of up to 22% of the nominal values.

Critical illness-associated weakness and related motor disorders.

Weakness of limb and respiratory muscles that occurs in the course of critical illness has become an increasingly common and serious complication of adult and pediatric intensive care unit patients and a cause of prolonged ventilatory support, morbidity, and prolonged hospitalization. Two motor disorders that occur singly or together, namely critical illness polyneuropathy and critical illness myopathy, cause weakness of limb and of breathing muscles, making it difficult to be weaned from ventilatory support, commencing rehabilitation, and extending the length of stay in the intensive care unit, with higher rates of morbidity and mortality. Recovery can take weeks or months and in severe cases, and may be incomplete or absent. Recent findings suggest an improved prognosis of critical illness myopathy compared to polyneuropathy. Prevention and treatment are therefore very important. Its management requires an integrated team approach commencing with neurologic consultation, creatine kinase (CK) measurement, detailed electrodiagnostic, respiratory and neuroimaging studies, and potentially muscle biopsy to elucidate the etiopathogenesis of the weakness in the peripheral and/or central nervous system, for which there may be a variety of causes. These tenets of care are being applied to new cases and survivors of the coronavirus-2 disease pandemic of 2019. This chapter provides an update to the understanding and approach to critical illness motor disorders.

Simulation of a Fully Digital Computing-in-Memory for Non-Volatile Memory for Artificial Intelligence Edge Applications.

In recent years, digital computing in memory (CIM) has been an efficient and high-performance solution in artificial intelligence (AI) edge inference. Nevertheless, digital CIM based on non-volatile memory (NVM) is less discussed for the sophisticated intrinsic physical and electrical behavior of non-volatile devices. In this paper, we propose a fully digital non-volatile CIM (DNV-CIM) macro with compressed coding look-up table (LUT) multiplier (CCLUTM) using the 40 nm technology, which is highly compatible with the standard commodity NOR Flash memory. We also provide a continuous accumulation scheme for machine learning applications. When applied to a modified ResNet18 network trained under the CIFAR-10 dataset, the simulations indicate that the proposed CCLUTM-based DNV-CIM can achieve a peak energy efficiency of 75.18 TOPS/W with 4-bit multiplication and accumulation (MAC) operations.

Proteus mirabilis - analysis of a concealed source of carbapenemases and development of a diagnostic algorithm for detection.

OBJECTIVES: To analyse carbapenemases in Proteus mirabilis and assess the performance of carbapenemase detection assays. METHODS: Eighty-one clinical P. mirabilis isolates with high-level resistance at least to ampicillin (>32 mg/L) or previous detection of carbapenemases were selected and investigated by three susceptibility testing methods (microdilution, automated susceptibility testing, and disk diffusion), six phenotypic carbapenemase assays (CARBA NP, modified carbapenemase inactivation method [CIM], modified zinc-supplemented CIM, simplified CIM, faropenem, and carbapenem-containing agar), two immunochromatographic assays, and whole-genome sequencing. RESULTS: Carbapenemases were detected in 43 of 81 isolates (OXA-48-like [n = 13]; OXA-23 [n = 12]; OXA-58 [n = 12]; New Delhi metallo-ß-lactamase (NDM) [n = 2]; Verona integron-encoded metallo-ß-lactamase (VIM) [n = 2]; Imipenemase (IMP) [n = 1]; Klebsiella pneumoniae carbapenemase (KPC) [n = 1]). Carbapenemase-producing Proteus were frequently susceptible to ertapenem (26/43; 60%), meropenem (28/43; 65%), ceftazidime (33/43; 77%), and some even to piperacillin-tazobactam (9/43; 21%). Sensitivity/specificity of phenotypic tests were 30% (CI: 17-46%)/89% (CI: 75-97%) for CARBA NP, 74% (CI: 60-85%)/82% (CI: 67-91%) for faropenem, 91% (CI: 78-97%)/82% (CI: 66-92%) for simplified CIM, and 93% (CI: 81-99%)/100% (CI: 91-100%) for modified zinc-supplemented CIM. An algorithm for improved detection was developed, which demonstrated sensitivity/specificity of 100% (CI: 92-100%)/100% (CI: 91-100%) on the 81 isolates, and 100% (CI: 29-100%)/100% (CI: 96-100%) in a prospective analysis of additional 91 isolates. Interestingly, several OXA-23-producing isolates belonged to the same clonal lineage reported previously from France. DISCUSSION: Current susceptibility testing methods and phenotypic tests frequently fail to detect carbapenemases in P. mirabilis, which could result in inadequate antibiotic treatment. In addition, the non-inclusion of blaOXA-23/OXA-58 in many molecular carbapenemase assays further impedes their detection. Therefore, the prevalence of carbapenemases in P. mirabilis is likely underestimated. With the herein proposed algorithm, carbapenemase-producing Proteus can be easily identified.

Post-Traumatic Stress Disorder/Developmental Trauma Disorder/Complex Post-Traumatic Stress Disorder and Complementary and Integrative Medicine/Functional Medicine.

Response to PTSD treatments differ based on the age the abuse occurred, the type of abuse, and the chronicity of the abuse. Even when modifications to treatment are made based on the developmental age when the abuse occurred, therapies may be insufficient. In addition, when diagnostic criteria are modified to identify more children, some children continue to escape detection. Developmental Trauma Disorder, (akin to the RDoC), may be more suitable to identify epigenetic and inflammatory effects of early abuse that may be responsible for the nonresponsive to treatment. Complementary and Integrative Medicine interventions (meditation, EFT, EMDR, PUFAs, etc.) may reverse these effects.

Prevalence of carbapenemases in Enterobacterales from urine specimens in an university hospital in Istanbul, Turkey.

We aimed to investigate the prevalence of carbapenemases in Enterobacterales strains isolated from urine specimens between July 2019 and July 2020.CIM and modified CIM tests were applied as well as detection of blaOXA-48, blaNDM, blaVIM, blaKPC and blaIMP genes was performed by multiplex PCR.One hundred fifty of 3,242 Enterobacterales strains were found to be carbapenem resistant and 46 were included in the study. Forty five (98%) of the 46 strains included in the study were Klebsiella spp. and one (2%) of them was Escherichia coli. Susceptibility to ceftazidime-avibactam, amikacin and gentamicin was 97%, 11% and 9%, respectively. Forty three (94%) isolates were found positive at 2 and 4 h with CIM test. Forty four (97%) strains were found positive at 4 h and 43 (94%) strains were found positive at 2 h with modified CIM test.While blaOXA-48, blaNDM and blaOXA-48 with blaNDM association were found in Klebsiella spp. isolates in 55%, 27% and 11%, respectively, blaVIM, blaKPC, blaIMP were not found. Only blaOXA-48 and blaNDM-1 were detected in the E. coli strain.None of the investigated genes were detected in three Klebsiella strains but with whole genome analysis the combination of blaOXA-534, blaCMY-99 and blaKPC-3 was found in the first strain, blaOXA-370 in the second strain and no resistance gene was found in the third strain.Ceftazidime-avibactam was found to be active against 97% of strains, and the most common resistance genes were blaOXA-48 and blaNDM-1. Previously undetected resistance genes have been identified in our country.

Analyzing Citramalic Acid Enantiomers in Apples and Commercial Fruit Juice by Liquid Chromatography-Tandem Mass Spectrometry with Pre-Column Derivatization.

Optically active citramalic acid (CMA) is naturally present as an acidic taste component in fruits, such as apples. The absolute configuration of CMA in such fruits was investigated by high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) following pre-column derivatization with a chiral reagent, benzyl 5-(2-aminoethyl)-3-methyl-4-oxoimidazolidine-1-carboxylate. The developed LC-MS/MS method successfully separated the enantiomers of CMA using an octadecylsilica column with a resolution and separation factor of 2.19 and 1.09, respectively. Consequently, the R-form of CMA was detected in the peel and fruit of three kinds of apple at concentrations in the 1.24-37.8 and 0.138-1.033 mg/wet 100 g ranges, respectively. In addition, R- CMA was present in commercial apple juice, whereas no quantity was detected in commercial blueberry, perilla, or Japanese apricot juice.

Performance estimation for the memristor-based computing-in-memory implementation of extremely factorized network for real-time and low-power semantic segmentation.

Nowadays many semantic segmentation algorithms have achieved satisfactory accuracy on von Neumann platforms (e.g., GPU), but the speed and energy consumption have not meet the high requirements of certain edge applications like autonomous driving. To tackle this issue, it is of necessity to design an efficient lightweight semantic segmentation algorithm and then implement it on emerging hardware platforms with high speed and energy efficiency. Here, we first propose an extremely factorized network (EFNet) which can learn multi-scale context information while preserving rich spatial information with reduced model complexity. Experimental results on the Cityscapes dataset show that EFNet achieves an accuracy of 68.0% mean intersection over union (mIoU) with only 0.18M parameters, at a speed of 99 frames per second (FPS) on a single RTX 3090 GPU. Then, to further improve the speed and energy efficiency, we design a memristor-based computing-in-memory (CIM) accelerator for the hardware implementation of EFNet. It is shown by the simulation in DNN+NeuroSim V2.0 that the memristor-based CIM accelerator is ∼63× (∼4.6×) smaller in area, at most ∼9.2× (∼1000×) faster, and ∼470× (∼2400×) more energy-efficient than the RTX 3090 GPU (the Jetson Nano embedded development board), although its accuracy slightly decreases by 1.7% mIoU. Therefore, the memristor-based CIM accelerator has great potential to be deployed at the edge to implement lightweight semantic segmentation models like EFNet. This study showcases an algorithm-hardware co-design to realize real-time and low-power semantic segmentation at the edge.

Case report: Personalized adapted motor activity in a COVID-19 patient complicated by critical illness polyneuropathy and myopathy.

Background: COVID-19 may require hospitalization in an intensive care unit (ICU) and is often associated with the onset of critical illness polyneuropathy (CIP) and critical illness myopathy (CIM). Due to the spread of the disease around the world, the identification of new rehabilitation strategies for patients facing this sequence of events is of increasing importance. Case presentation: We report the clinical presentation and the beneficial effects of a prolonged, supervised adapted motor activity (AMA) program in a highly deconditioned 61-year-old male COVID-19 patient discharged from the ICU and complicated by residual CIP and CIM. The program included aerobic, strength, gait, and balance training (1 h, 2 sessions per week). Measures: Pulmonary (spirometry), metabolic (indirect calorimetry and bioimpedance), and neuromuscular functions (electromyography) were evaluated at baseline and after 1 year of training. Results: Relative to baseline, an amelioration of several spirometric parameters such as vital capacity (VC, +40%), total lung capacity (TLC, +25%), and forced expiratory volume in 1 s (FEV1, +28%) was appreciable. Metabolic parameters such as body water (60%-46%), phase angle (3.6°-5.9°), and respiratory quotient (0.92-0.8) returned to the physiological range. Electromyographic parameters were substantially unchanged. The overall amelioration in clinical parameters resulted in a significant improvement of patient autonomy and the quality of life. Conclusion: Our results highlight the importance of AMA for counteracting respiratory, metabolic, and functional but not neuromuscular impairments in COVID-19 patients with residual CIM and CIP.