Cefiderocol.

Cefiderocol is a new siderophore cephalosporin with potent in vitro activity against gram-negative bacilli including Enterobacterales that produce all kinds of carbapenemases and non-fermenting Gram-negative with difficult-to-treat resistance. As a ß-lactam, its efficacy is optimized in extended-perfusion and requires dose adjustment in renal dysfunction and hyperclearance. Its efficacy has been validated in three clinical trials, one of them in the treatment of hospital-acquired pneumonia and ventilator-associated pneumonia. The clinical trial aimed at difficult-to-treat gram-negatives achieved the clinical and microbiological target, but the increase in mortality observed in the cefiderocol arm makes it necessary to demonstrate efficacy in real clinical practice. Cefiderocol is a good option among the new ß-lactams for the treatment of pneumonia caused by Gram-negative bacilli carbapenem-resistant.

Impact of patients' perception of COPD and treatment on adherence and health-related quality of life in real-world: Study in 53 community pharmacies.

BACKGROUND: Patient adherence to treatment in chronic obstructive pulmonary disease (COPD) is essential to optimize disease management. We aimed to assess the impact of patients' perception of their treatment and disease on adherence and Health-Related Quality of Life (HRQL) in patients attending a community pharmacy, where usually subjects have a better condition than those in clinical settings. METHODS: We performed a cross-sectional study of 318 patients with COPD in treatment with inhalers in the last 3 months from 53 community pharmacies. We assessed HRQL with St George's Respiratory Questionnaire (SGRQ). Persistence was assessed from the three previous refills and adherence through the Test of Adherence to Inhalers test. RESULTS: Persistence was achieved by 78.6% of the patients and 58.5% had good adherence. Patients having a multidose DPI and those with MDI showed a 2.8-fold and 4.1-fold increased association, respectively, with intermediate/poor adherence in comparison with those having a single dose DPI. Those patients who did not have knowledge about COPD (aOR 2.106, p = 0.006) and those who thought that the inhaler effectiveness was fair/poor (aOR 2.361, p = 0.006) were more likely to have intermediate/poor adherence. Overall SGRQ score was significantly worse in patients with intermediate/poor adherence (p = 0.036) and in those who thought the inhaler's effectiveness was fair/poor (p < 0.001). CONCLUSIONS: The type of inhaler and patients' knowledge and perceptions of their disease and treatment were associated with good adherence and higher HRQL. Clinicians should promote shared-decision making in the choice of inhaler depending on patients' individual abilities and beliefs.

Cross-predicting the dynamics of an optically injected single-mode semiconductor laser using reservoir computing.

In real-world dynamical systems, technical limitations may prevent complete access to their dynamical variables. Such a lack of information may cause significant problems, especially when monitoring or controlling the dynamics of the system is required or when decisions need to be taken based on the dynamical state of the system. Cross-predicting the missing data is, therefore, of considerable interest. Here, we use a machine learning algorithm based on reservoir computing to perform cross-prediction of unknown variables of a chaotic dynamical laser system. In particular, we chose a realistic model of an optically injected single-mode semiconductor laser. While the intensity of the laser can often be acquired easily, measuring the phase of the electric field and the carriers in real time, although possible, requires a more demanding experimental scheme. We demonstrate that the dynamics of two of the three dynamical variables describing the state of the laser can be reconstructed accurately from the knowledge of only one variable, if our algorithm has been trained beforehand with all three variables for a limited period of time. We analyze the accuracy of the method depending on the parameters of the laser system and the reservoir. Finally, we test the robustness of the cross-prediction method when adding noise to the time series. The suggested reservoir computing state observer might be used in many applications, including reconstructing time series, recovering lost time series data and testing data encryption security in cryptography based on chaotic synchronization of lasers.

Consistency properties of chaotic systems driven by time-delayed feedback.

Consistency refers to the property of an externally driven dynamical system to respond in similar ways to similar inputs. In a delay system, the delayed feedback can be considered as an external drive to the undelayed subsystem. We analyze the degree of consistency in a generic chaotic system with delayed feedback by means of the auxiliary system approach. In this scheme an identical copy of the nonlinear node is driven by exactly the same signal as the original, allowing us to verify complete consistency via complete synchronization. In the past, the phenomenon of synchronization in delay-coupled chaotic systems has been widely studied using correlation functions. Here, we analytically derive relationships between characteristic signatures of the correlation functions in such systems and unequivocally relate them to the degree of consistency. The analytical framework is illustrated and supported by numerical calculations of the logistic map with delayed feedback for different replica configurations. We further apply the formalism to time series from an experiment based on a semiconductor laser with a double fiber-optical feedback loop. The experiment constitutes a high-quality replica scheme for studying consistency of the delay-driven laser and confirms the general theoretical results.

Role of dynamical injection locking and characteristic pulse events for low frequency fluctuations in semiconductor lasers.

We investigate the dynamics of semiconductor lasers subject to time-delayed optical feedback from the perspective of dynamical self-injection locking. Based on the Lang-Kobayashi model, we perform an analysis of the well-known Low Frequency Fluctuations (LFFs) in the frequency-intensity plane. Moreover, we investigate a recently found dynamical regime of fragmented LFFs by means of a locking-range analysis, spectral comparison and precursor pulse identification. We show that LFF dynamics can be explained by dynamical optical injection locking due to the delayed optical feedback. Moreover, the fragmented LFFs occur due to a re-injection locking induced by a particular optical pulse structure in the chaotic feedback dynamics. This is corroborated by experiments with a semiconductor laser experiencing delayed feedback from an optical fiber loop. The dynamical nature of the feedback injection results in an eventual loss, but also possible regaining, of the locking, explaining the recently observed phenomenon of fragmented LFFs.

A Unified Framework for Reservoir Computing and Extreme Learning Machines based on a Single Time-delayed Neuron.

In this paper we present a unified framework for extreme learning machines and reservoir computing (echo state networks), which can be physically implemented using a single nonlinear neuron subject to delayed feedback. The reservoir is built within the delay-line, employing a number of "virtual" neurons. These virtual neurons receive random projections from the input layer containing the information to be processed. One key advantage of this approach is that it can be implemented efficiently in hardware. We show that the reservoir computing implementation, in this case optoelectronic, is also capable to realize extreme learning machines, demonstrating the unified framework for both schemes in software as well as in hardware.

Experimental Phase-Space Tomography of Semiconductor Laser Dynamics.

We perform phase-space tomography of semiconductor laser dynamics by simultaneous experimental determination of optical intensity, frequency, and population inversion with high temporal resolution. We apply this technique to a laser with delayed feedback, serving as prominent example for high-dimensional chaotic dynamics and as model system for fundamental investigations of complex systems. Our approach allows us to explore so far unidentified trajectories in phase space and identify the underlying physical mechanism.

Optoelectronic reservoir computing: tackling noise-induced performance degradation.

We present improved strategies to perform photonic information processing using an optoelectronic oscillator with delayed feedback. In particular, we study, via numerical simulations and experiments, the influence of a finite signal-to-noise ratio on the computing performance. We illustrate that the performance degradation induced by noise can be compensated for via multi-level pre-processing masks.

Distinguishing chaotic and stochastic dynamics from time series by using a multiscale symbolic approach.

In this paper we introduce a multiscale symbolic information-theory approach for discriminating nonlinear deterministic and stochastic dynamics from time series associated with complex systems. More precisely, we show that the multiscale complexity-entropy causality plane is a useful representation space to identify the range of scales at which deterministic or noisy behaviors dominate the system's dynamics. Numerical simulations obtained from the well-known and widely used Mackey-Glass oscillator operating in a high-dimensional chaotic regime were used as test beds. The effect of an increased amount of observational white noise was carefully examined. The results obtained were contrasted with those derived from correlated stochastic processes and continuous stochastic limit cycles. Finally, several experimental and natural time series were analyzed in order to show the applicability of this scale-dependent symbolic approach in practical situations.

Impact of liposomal amphotericin B on renal function in critically ill patients with renal function impairment.

OBJECTIVE: To assess the tolerability of liposomal amphotericin B (L-AmB) in critically ill patients with elevated serum creatinine concentrations (Cr) (> 1.5 mg/dL) at starting L-AmB therapy. METHODS: Retrospective, multicenter, comparative study of two cohorts of critically ill patients treated with L-AmB during 3 or more days, the difference between them was the level of Cr at the beginning of treatment. A cutoff value of Cr of 1.5 mg/dL was established. Patients undergoing extrarenal depuration procedures before or 48 hours after starting L-AmB were excluded. The primary endpoint was the difference between Cr values at the end of treatment as compared with Cr at starting L-AmB. Secondary endpoints were treatment-related withdrawals, need of extrarenal depuration techniques, and treatment-related severe adverse events. Demographic data, underlying illness, indication of L-AmB therapy, concomitant risk factors of nephrotoxicity, and vital status at ICU and hospital discharge were recorded. RESULTS: A total of 122 patients admitted to 26 ICUs (16 with Cr > 1.5 g/dL; 106 with normal Cr levels) were recruited. Main reasons for the use of L-AmB in both groups were the broad spectrum of the drug and the presence of hemodynamic instability. L-AmB was administered as first-line treatment in 68.8% of patients with elevated Cr and in 52.8% with normal Cr. The APACHE II score on ICU admission was 25 in patients with elevated Cr and 17 in those with normal Cr values (p < 0.001). Duration of treatment with L-AmB was 16 and 12 days in patients with elevate and normal Cr values, respectively, with a mean dose of 3.5 vs 3.9 mg/kg/day. The use of concomitant nephrotoxic drugs, mortality rate, and ICU and hospital length of stay were similar in both cohorts. In patients with renal function impairment at the initiation of L-AmB treatment, an absolute decrease of Cf-Ci of 1.08 mg/dL was observed (P < 0.001). A decrease of Cr levels to normal limits was observed in 50% of the patients; in 37.5% of patients there was a decrease but normal levels were not achieved, whereas a Cr increased occurred in only one (6.25%) patient. None of the patients required withdrawal of L-AmB or use of extrarenal depuration procedures. Treatment-related severe adverse events were not reported. CONCLUSIONS: In critically ill patients with impaired renal function, the impact of L-AmB on renal function was minimal. L-AmB can be used for the treatment of fungal infections in critically ill patients independently of renal function at the initiation of treatment.

Zero-lag synchronization and bubbling in delay-coupled lasers.

We show experimentally that two semiconductor lasers mutually coupled via a passive relay fiber loop exhibit chaos synchronization at zero lag, and study how this synchronized regime is lost as the lasers' pump currents are increased. We characterize the synchronization properties of the system with high temporal resolution in two different chaotic regimes, namely, low-frequency fluctuations and coherence collapse, identifying significant differences between them. In particular, a marked decrease in synchronization quality develops as the lasers enter the coherence collapse regime. Our high-resolution measurements allow us to establish that synchronization loss is associated with bubbling events, the frequency of which increases with increasing pump current.

Photonic information processing beyond Turing: an optoelectronic implementation of reservoir computing.

Many information processing challenges are difficult to solve with traditional Turing or von Neumann approaches. Implementing unconventional computational methods is therefore essential and optics provides promising opportunities. Here we experimentally demonstrate optical information processing using a nonlinear optoelectronic oscillator subject to delayed feedback. We implement a neuro-inspired concept, called Reservoir Computing, proven to possess universal computational capabilities. We particularly exploit the transient response of a complex dynamical system to an input data stream. We employ spoken digit recognition and time series prediction tasks as benchmarks, achieving competitive processing figures of merit.

Desorption of two organophosphorous pesticides from soil with wastewater and surfactant solutions.

A batch test was used to evaluate the extent of desorption of diazinon and dimethoate, preadsorbed on a calcareous agricultural soil, representative of the Mediterranean area. Urban wastewater from a secondary treatment and seven surfactant solutions, at concentrations ranging from 0.75 mg L(-1) to 10 gL(-1), were used. The surfactants assayed were cationic (hexadecyl trimethyl ammonium bromide (HD)), anionic (sodium dodecyl sulfate (SDS), Aerosol 22 (A22) and Biopower (BP)), and nonionic (Tween 80 (TW), Triton X 100 (TX) and Glucopon 600 (G600)). Desorption of dimethoate was either not affected or only slightly by the nonionic and anionic surfactants tested, while desorption of diazinon from the soil was only enhanced by A22, BP and TW. This desorption increase correlated significantly with the surfactant concentration of the solution used for desorption and with the concurrent increase in the supernatant of the dissolved organic carbon, in particular that originating from the surfactant. This parameter did not vary with the use of SDS, G600 and TX. The cationic surfactant HD was retained on the soil surface, as confirmed by an increase in soil organic carbon, resulting in a fall in desorption rate for both pesticides. Comparing treatment by wastewater with control water, there was no difference in desorption rate for either pesticide. Mixed TW/anionic surfactant solutions either did not modify or slightly increased desorption of both pesticides in comparison with individual surfactant solutions.

First Report of Phytophthora ramorum Causing a Leafspot on Loropetalum chinense, Chinese Fringe Flower in California.

Chinese fringe flower is a popular landscape plant in California for its red evergreen foliage and its showy red flowers in the spring. In April 2007, a sample was submitted to the California Department of Food and Agriculture diagnostic laboratory from Sacramento County as part of an inspection of a nursery for Phytophthora ramorum. A sample was taken from Loropetalum chinense because the inspector noticed very small spots and defoliation in the crop, even though P. ramorum was not detected in previous samples sent to the lab with similar symptoms. Six 5-mm2 pieces of the leaves were placed on CMA-PARP (1) medium as part of our standard nursery screening, even though no lesions were seen. An organism with coralloid coenocytic hyphae, chlamydospores, and ellipsoidal semi-papillate sporangia matching the description of P. ramorum (2) grew into a snowflake-shaped colony from two pieces. On closer inspection of the leaves, small green lesions of approximately 3 to 5 mm wide were visible, especially when the leaves were backlit. For sporangial production, a 6-mm plug was transferred from the colony margin of the isolate onto V8 juice agar (V8). Sporangia, produced on V8 plugs incubated in dH20 for 2 days, were from 41 to 61 × 23 to 32 µm (48.7 × 29.3 µm average) with a length to breadth ratio from 1.3 to 2.0 (average 1.7). Chlamydospores on CMA-PARP were 36.7 to 60.1 µm (49.1 µm diameter average). From 2008 to 2011, similar symptoms were found on L. chinense from Contra Costa, San Joaquin, and Los Angeles Counties. The same organism was isolated from these infected plants. To confirm pathogenicity on L. chinense, five nursery-grown plants in 3.78-L pots were inoculated with three isolates each. Plants were inoculated with 6-mm plugs taken from the margin of a 7- to 10-day old culture grown on V8. Plant leaves were wounded with a sterile pushpin and two colonized plugs were covered with a freezer tube cap filled with sterile dH2O and attached to the underside of the leaves with a sterile pin-curl clip (4). Inoculated plants were sprayed with water, covered with plastic bags, and incubated for 2 days, when bags and plugs were removed. Four leaves per isolate were inoculated on each plant and four leaves per plant were treated similarly with uncolonized V8 plugs as a control. Plants were incubated for 12 to 14 days at 18°C (16-h photoperiod) when lesions were visible and some of the leaves began to abscise. P. ramorum grew from each lesion produced on inoculated leaves and no Phytophthora spp. grew from the control leaves when isolated onto CMA-PARP. Inoculations were repeated with similar results. The internal transcribed spacer region (ITS) of rDNA was amplified and sequenced from the isolates using ITS1 and ITS4 primers as described by White et al. (3). BLAST analysis of the sequenced amplicons (GenBank JQ361743 through JQ361745) showed 100% identity with the ITS sequence of P. ramorum (GenBank AY594198). P. ramorum is a quarantine pathogen with many hosts (2,4). Leaf spots on L. chinense caused by P. ramorum are inconspicuous and missing this disease during nursery inspections could lead to unintended spread to neighboring host plants. References: (1) S. N. Jeffers and S. B. Martin. Plant Dis. 70:1038, 1986. (2) S. Werres et al. Mycol. Res. 105:1155, 2001. (3) T. J. White et al. Page 315 in: PCR Protocols. A Guide to Methods and Applications. Academic Press, San Diego, CA, 1990. (4) L. E. Yakabe et al. Plant Dis. 93:883, 2009.

First Report of Leaf Spot Caused by Phytophthora taxon Pgchlamydo on Evergreen Nursery Stock in California.

As part of the Phytophthora ramorum testing program from 2005 through 2007, a Phytophthora sp. was isolated on PARP-CMA medium (4) at the CDFA lab in Sacramento, CA, from the margin of necrotic spots and tissue suffering from dieback on Arctostaphylos sp. (manzanita), Camellia spp., Laurus nobilis (bay), Buxus sempervirens (boxwood), Rhododendron sp., Arbutus unedo (strawberry tree), and Sequoia sempervirens (coast redwood). Isolates were collected from Shasta, Contra Costa, San Diego, Solano, Santa Cruz, Alameda, Sacramento, San Joaquin, Monterey, and Los Angeles Counties. Isolates from A. unedo tissue on PARP medium produced apapillate, obovate sporangia 25 to 80 × 15 to 40 µm (48.0 × 26.9 µm average) and a few isolates produced intercalary and terminal chlamydospores at 22°C (30 to 46 µm diameter, 38.9 µm average). The internal transcribed spacer region (ITS) of rDNA was amplified from four isolates using ITS1 and ITS4 primers as described by White et al. (3) and the amplicons sequenced (GenBank Accession Nos. JQ307188 through JQ307191). BLAST analysis of the amplicons showed 99 to 100% identity with the ITS sequence of Phytophthora taxon Pgchlamydo from forest streams in Oregon (GenBank Accession No. HM004224) (1). Pathogenicity tests were performed on B. sempervirens, C. sasanqua, L. nobilis, and A. unedo. Five plants of each species were inoculated with 6-mm plugs taken from the margin of a 7- to 10-day-old culture grown on V8 juice agar. Plant leaves were wounded with a sterile pushpin and two agar plugs were covered with a freezer tube cap filled with sterile dH2O and clipped to the underside of the leaves with a sterile pin-curl clip (4). Inoculated plants were sprayed with water, covered with plastic bags, and incubated for 2 days, when bags and plugs were removed. Five leaves of each isolate plus five control plugs using V8 juice agar alone were inoculated on each plant. Plants were incubated for 12 days at 18°C (16-h photoperiod). Lesions formed on all inoculated plants, ranging in size from approx. 1 mm on B. sempervirens to 9.2 × 10.9 mm average on A. unedo. The lesions on A. unedo grew into and caused the mid-vein to blacken. The lesion sizes on camellia and bay were larger than those formed on B. sempervirens and smaller than those formed on A. unedo, with most lesions surrounded by a dark ring. Phytophthora taxon Pgchlamydo is associated with leaf lesions on rhododendron and dieback of yew in Minnesota (2). To our knowledge, this is the first report of Phytophthora taxon Pgchlamydo causing disease in camellia, bay, strawberry tree, and boxwood in California. Phytophthora taxon Pgchlamydo causes damage that is indistinguishable from the quarantine pest, P. ramorum (4). References: (1) P. W. Reeser et al. Mycologia 103:22, 2011. (2) B. W. Schwingle and R. A. Blanchette. Plant Dis. 92:642, 2008. (3) T. J. White et al. PCR Protocols: A Guide to Methods and Applications. M. A. Innis et al., eds., Academic Press, San Diego, 1990. (4) L. E. Yakabe et al. Plant Dis. 93:883, 2009.

Information processing using a single dynamical node as complex system.

Novel methods for information processing are highly desired in our information-driven society. Inspired by the brain's ability to process information, the recently introduced paradigm known as 'reservoir computing' shows that complex networks can efficiently perform computation. Here we introduce a novel architecture that reduces the usually required large number of elements to a single nonlinear node with delayed feedback. Through an electronic implementation, we experimentally and numerically demonstrate excellent performance in a speech recognition benchmark. Complementary numerical studies also show excellent performance for a time series prediction benchmark. These results prove that delay-dynamical systems, even in their simplest manifestation, can perform efficient information processing. This finding paves the way to feasible and resource-efficient technological implementations of reservoir computing.

Permutation-information-theory approach to unveil delay dynamics from time-series analysis.

In this paper an approach to identify delay phenomena from time series is developed. We show that it is possible to perform a reliable time delay identification by using quantifiers derived from information theory, more precisely, permutation entropy and permutation statistical complexity. These quantifiers show clear extrema when the embedding delay τ of the symbolic reconstruction matches the characteristic time delay τ(S) of the system. Numerical data originating from a time delay system based on the well-known Mackey-Glass equations operating in the chaotic regime were used as test beds. We show that our method is straightforward to apply and robust to additive observational and dynamical noise. Moreover, we find that the identification of the time delay is even more efficient in a noise environment. Our permutation approach is also able to recover the time delay in systems with low feedback rate or high nonlinearity.