Enhanced NSAIDs Solubility in Drug-Drug Formulations with Ciprofloxacin.

Drug-drug salts are a kind of pharmaceutical multicomponent solid in which the two co-existing components are active pharmaceutical ingredients (APIs) in their ionized forms. This novel approach has attracted great interest in the pharmaceutical industry since it not only allows concomitant formulations but also has proved potential to improve the pharmacokinetics of the involved APIs. This is especially interesting for those APIs that have relevant dose-dependent secondary effects, such as non-steroidal anti-inflammatory drugs (NSAIDs). In this work, six multidrug salts involving six different NSAIDs and the antibiotic ciprofloxacin are reported. The novel solids were synthesized using mechanochemical methods and comprehensively characterized in the solid state. Moreover, solubility and stability studies, as well as bacterial inhibition assays, were performed. Our results suggest that our drug-drug formulations enhanced the solubility of NSAIDs without affecting the antibiotic efficacy.

Two Compensation Strategies for Optimal Estimation in Sensor Networks with Random Matrices, Time-Correlated Noises, Deception Attacks and Packet Losses.

Due to its great importance in several applied and theoretical fields, the signal estimation problem in multisensor systems has grown into a significant research area. Networked systems are known to suffer random flaws, which, if not appropriately addressed, can deteriorate the performance of the estimators substantially. Thus, the development of estimation algorithms accounting for these random phenomena has received a lot of research attention. In this paper, the centralized fusion linear estimation problem is discussed under the assumption that the sensor measurements are affected by random parameter matrices, perturbed by time-correlated additive noises, exposed to random deception attacks and subject to random packet dropouts during transmission. A covariance-based methodology and two compensation strategies based on measurement prediction are used to design recursive filtering and fixed-point smoothing algorithms. The measurement differencing method-typically used to deal with the measurement noise time-correlation-is unsuccessful for these kinds of systems with packet losses because some sensor measurements are randomly lost and, consequently, cannot be processed. Therefore, we adopt an alternative approach based on the direct estimation of the measurement noises and the innovation technique. The two proposed compensation scenarios are contrasted through a simulation example, in which the effect of the different uncertainties on the estimation accuracy is also evaluated.

A Two-Phase Distributed Filtering Algorithm for Networked Uncertain Systems with Fading Measurements under Deception Attacks.

In this paper, the distributed filtering problem is addressed for a class of discrete-time stochastic systems over a sensor network with a given topology, susceptible to suffering deception attacks, launched by potential adversaries, which can randomly succeed or not with a known success probability, which is not necessarily the same for the different sensors. The system model integrates some random imperfections and features that are frequently found in real networked environments, namely: (1) fading measurements; (2) multiplicative noises in both the state and measurement equations; and (3) sensor additive noises cross-correlated with each other and with the process noise. According to the network communication scheme, besides its own local measurements, each sensor receives the measured outputs from its adjacent nodes. Based on such measurements, a recursive algorithm is designed to obtain the least-squares linear filter of the state. Thereafter, each sensor receives the filtering estimators previously obtained by its adjacent nodes, and these estimators are all fused to obtain the desired distributed filter as the minimum mean squared error matrix-weighted linear combination of them. The theoretical results are illustrated by a simulation example, where the efficiency of the developed distributed estimation strategy is discussed in terms of the error variances.

Relationship between skin and urine colonization and surgical site infection in the proximal femur fracture: a prospective study.

PURPOSE: Antibiotic prophylaxis is routinely used in the surgical management of proximal femur fractures. The role of bacterial colonization of the skin and urine in the development of deep surgical site infections (SSI) is yet to be elucidated. This study aimed to evaluate the role of previous skin and urine colonization in the development of deep SSI after a proximal femoral fracture surgery. METHODS: We conducted a prospective observational study in 326 patients > 64 years old, who were scheduled to surgery. Cultures from skin samples of the surgical site and from urine were performed prior to the procedure, and cefazoline was administered as prophylaxis. RESULTS: Skin microbiota was isolated in 233 (71.5%) cases; 8 (2.5%) samples were positive for other bacteria, and 85 (26%) were negative. Of 236 urine samples, 168 were negative or contaminated (71.2%), and 68 (28.8%) were positive, being 58/236 for Enterobacterales (24.6%). Acute deep SSI were diagnosed in nine out of 326 patients (2.7%), and two (22%) were infected by Gram-negative bacilli. Of the 9 cases, normal skin microbiota was isolated in 7 (78%), and the remaining two were negative. Seven cases had negative or contaminated urine cultures, and the one with E. coli did not correlate with SSI bacteria. CONCLUSION: In our elderly hip fracture population, most patients harbored normal skin microbiota, and Enterobacterales urine cultures were positive in one-quarter of cases. There was no relationship between skin colonization, urine culture, and deep SSI. We therefore do not believe that our patients would benefit from modifying the current antibiotic prophylaxis.

Mediterranean spotted fever in the elderly: a prospective cohort study.

The objective of this study is to evaluate the characteristics and outcome of elderly patients with Mediterranean spotted fever (MSF). This study was a prospective observational cohort study of all adult cases with confirmed MSF treated in a teaching hospital (1984-2015) to compare the characteristics of elderly patients (> 65 years) with younger adults. We identified 263 adult patients with MSF, and 53 (20.2%) were elderly. Severe MSF was more frequent in the elderly (26.4% vs. 10.5%; p = 0.002). Gastrointestinal symptoms, impaired consciousness, lung infiltrate, oedema, acute hearing loss, raised alanine transaminase, hyponatremia, and thrombocytopenia occurred more frequently in elderly patients, and arthromyalgia occurred less frequently. Most patients were treated with a single-day doxycycline regimen (two oral doses of 200 mg for 1 day). All patients recovered uneventfully. Fever disappeared 2.55 ± 1.16 days after treatment initiation in elderly patients, and the remaining symptoms disappeared after 3.65 ± 1.42 days. These figures were similar to non-elderly patients. Severe MSF was more frequent in elderly patients. Some clinical manifestations occurred with different frequencies in the elderly compared with younger patients. Single-day doxycycline therapy is an effective and well-tolerated treatment for MSF in elderly patients.

Covariance-Based Estimation for Clustered Sensor Networks Subject to Random Deception Attacks.

In this paper, a cluster-based approach is used to address the distributed fusion estimation problem (filtering and fixed-point smoothing) for discrete-time stochastic signals in the presence of random deception attacks. At each sampling time, measured outputs of the signal are provided by a networked system, whose sensors are grouped into clusters. Each cluster is connected to a local processor which gathers the measured outputs of its sensors and, in turn, the local processors of all clusters are connected with a global fusion center. The proposed cluster-based fusion estimation structure involves two stages. First, every single sensor in a cluster transmits its observations to the corresponding local processor, where least-squares local estimators are designed by an innovation approach. During this transmission, deception attacks to the sensor measurements may be randomly launched by an adversary, with known probabilities of success that may be different at each sensor. In the second stage, the local estimators are sent to the fusion center, where they are combined to generate the proposed fusion estimators. The covariance-based design of the distributed fusion filtering and fixed-point smoothing algorithms does not require full knowledge of the signal evolution model, but only the first and second order moments of the processes involved in the observation model. Simulations are provided to illustrate the theoretical results and analyze the effect of the attack success probability on the estimation performance.

Prospective Cohort Study of Single-Day Doxycycline Therapy for Mediterranean Spotted Fever.

The objective of this study is to evaluate the results of single-day doxycycline therapy for Mediterranean spotted fever (MSF). This is a prospective cohort study of cases with confirmed MSF treated with the single-day doxycycline regimen in a teaching hospital from 1990 to 2015. Patients received two oral doses of 200 mg of doxycycline for 1 day. The outcomes evaluated were the time interval between the start of treatment and apyrexia, the time interval between the start of treatment and disappearance of other symptoms, and the adverse reactions to treatment and death. The study included 158 subjects, 18 of whom (11.4%) had a severe form of MSF and 31 (19.6%) were >65 years. The interval between onset of symptoms and start of treatment was 4.31 ± 1.54 days. All patients recovered uneventfully. Fever disappeared 2.55 ± 1.14 days after the start of treatment. The remaining symptoms (headache, arthromyalgia) disappeared 3.63 ± 1.35 days after the start of treatment. Only one patient had a delay in reaching apyrexia (8 days). The fever disappeared somewhat later in severe cases (median, 3 days; interquartile range [IQR], 2 to 4 days) than in nonsevere cases (median, 2 days; IQR, 2 to 3 days). Likewise, the remaining symptoms disappeared later in severe cases (median, 5 days; IQR, 4 to 6 days) than in nonsevere cases (median, 3 days; IQR, 3 to 4 days). The outcome was similar in both elderly and nonelderly patients. Eight patients had mild adverse effects possibly related to treatment. The results of the study confirm that single-day doxycycline therapy is an effective and well-tolerated treatment for MSF, including elderly patients and severe cases.

Rifampin Resistance in Staphylococci after Rifaximin Intake for Surgical Prophylaxis in Elective Colorectal Surgery.

The aim of our study was to determine whether rifampin resistance emerges in human skin staphylococci after oral intake of rifaximin for surgical prophylaxis. Rifampin-resistant staphylococci appeared on the skin of 32 out of 74 patients (43.2%) two weeks after prophylactic treatment with rifaximin. In all cases, the resistant strains were coagulase-negative staphylococci. The resistance completely reverted after three months. This study shows the emergence of transient resistance to rifampin after rifaximin intake.

Centralized Fusion Approach to the Estimation Problem with Multi-Packet Processing under Uncertainty in Outputs and Transmissions.

This paper is concerned with the least-squares linear centralized estimation problem in multi-sensor network systems from measured outputs with uncertainties modeled by random parameter matrices. These measurements are transmitted to a central processor over different communication channels, and owing to the unreliability of the network, random one-step delays and packet dropouts are assumed to occur during the transmissions. In order to avoid network congestion, at each sampling time, each sensor's data packet is transmitted just once, but due to the uncertainty of the transmissions, the processing center may receive either one packet, two packets, or nothing. Different white sequences of Bernoulli random variables are introduced to describe the observations used to update the estimators at each sampling time. To address the centralized estimation problem, augmented observation vectors are defined by accumulating the raw measurements from the different sensors, and when the current measurement of a sensor does not arrive on time, the corresponding component of the augmented measured output predictor is used as compensation in the estimator design. Through an innovation approach, centralized fusion estimators, including predictors, filters, and smoothers are obtained by recursive algorithms without requiring the signal evolution model. A numerical example is presented to show how uncertain systems with state-dependent multiplicative noise can be covered by the proposed model and how the estimation accuracy is influenced by both sensor uncertainties and transmission failures.

Optimal Fusion Estimation with Multi-Step Random Delays and Losses in Transmission.

This paper is concerned with the optimal fusion estimation problem in networked stochastic systems with bounded random delays and packet dropouts, which unavoidably occur during the data transmission in the network. The measured outputs from each sensor are perturbed by random parameter matrices and white additive noises, which are cross-correlated between the different sensors. Least-squares fusion linear estimators including filter, predictor and fixed-point smoother, as well as the corresponding estimation error covariance matrices are designed via the innovation analysis approach. The proposed recursive algorithms depend on the delay probabilities at each sampling time, but do not to need to know if a particular measurement is delayed or not. Moreover, the knowledge of the signal evolution model is not required, as the algorithms need only the first and second order moments of the processes involved. Some of the practical situations covered by the proposed system model with random parameter matrices are analyzed and the influence of the delays in the estimation accuracy are examined in a numerical example.

Networked Fusion Filtering from Outputs with Stochastic Uncertainties and Correlated Random Transmission Delays.

This paper is concerned with the distributed and centralized fusion filtering problems in sensor networked systems with random one-step delays in transmissions. The delays are described by Bernoulli variables correlated at consecutive sampling times, with different characteristics at each sensor. The measured outputs are subject to uncertainties modeled by random parameter matrices, thus providing a unified framework to describe a wide variety of network-induced phenomena; moreover, the additive noises are assumed to be one-step autocorrelated and cross-correlated. Under these conditions, without requiring the knowledge of the signal evolution model, but using only the first and second order moments of the processes involved in the observation model, recursive algorithms for the optimal linear distributed and centralized filters under the least-squares criterion are derived by an innovation approach. Firstly, local estimators based on the measurements received from each sensor are obtained and, after that, the distributed fusion filter is generated as the least-squares matrix-weighted linear combination of the local estimators. Also, a recursive algorithm for the optimal linear centralized filter is proposed. In order to compare the estimators performance, recursive formulas for the error covariance matrices are derived in all the algorithms. The effects of the delays in the filters accuracy are analyzed in a numerical example which also illustrates how some usual network-induced uncertainties can be dealt with using the current observation model described by random matrices.

Epidemiology and risk factors for infections due to AmpC ß-lactamase-producing Escherichia coli.

OBJECTIVES: To describe the prevalence and risk factors for infection due to AmpC ß-lactamase-producing Escherichia coli (AmpC-EC). METHODS: For the prevalence study, all clinical isolates of E. coli with reduced susceptibility to third-generation cephalosporins were prospectively included from June 2010 to November 2011. For risk factor analysis, a case-control study was conducted. Cases were patients with an infection due to AmpC-EC. Controls were patients infected with cephalosporin-susceptible E. coli, matched 1 : 2. Detection of blaAmpC genes was done with a multiplex AmpC-PCR, and hyperproduction of E. coli chromosomal blaAmpC by quantitative RT-PCR. Alteration of the blaAmpC promoter was studied by PCR and sequencing. RESULTS: We identified 243 (1.1%) AmpC-EC strains out of 21 563 clinical isolates. Three cases with strains carrying ESBLs, 18 strains that were considered due to colonization and 8 cases lost to clinical follow-up were excluded. Finally, 214 cases were included in the analysis. Ninety-one cases (42.5%) and 269 (62.8%) controls were strictly community acquired (P < 0.001). Thirty-five (16.3%) cases and 186 controls (43.5%) did not have any identifiable risk factor (P < 0.001). Among cases, 158 (73.8%) were found to harbour an acquired AmpC (73.4% CMY-2). Previous use of fluoroquinolones [OR 2.6 (95% CI 1.12-3.36); P = 0.008] was independently associated with AmpC-EC in the multivariate analysis. CONCLUSIONS: Prevalence of AmpC in E. coli remains low in our area. Plasmid acquisition (CMY type) represents the main mechanism of AmpC production. A high proportion of community-acquired isolates and patients with no identifiable risk factors were found. Previous use of fluoroquinolones was identified as a risk factor.

Intrinsic acid-base properties of a hexa-2'-deoxynucleoside pentaphosphate, d(ApGpGpCpCpT): neighboring effects and isomeric equilibria.

The intrinsic acid-base properties of the hexa-2'-deoxynucleoside pentaphosphate, d(ApGpGpCpCpT) [=(A1∙G2∙G3∙C4∙C5∙T6)=(HNPP)5⁻] have been determined by ¹H NMR shift experiments. The pKa values of the individual sites of the adenosine (A), guanosine (G), cytidine (C), and thymidine (T) residues were measured in water under single-strand conditions (i.e., 10% D2O, 47 °C, I=0.1 M, NaClO4). These results quantify the release of H⁺ from the two (N7)H⁺ (G∙G), the two (N3)H⁺ (C∙C), and the (N1)H⁺ (A) units, as well as from the two (N1)H (G∙G) and the (N3)H (T) sites. Based on measurements with 2'-deoxynucleosides at 25 °C and 47 °C, they were transferred to pKa values valid in water at 25 °C and I=0.1 M. Intramolecular stacks between the nucleobases A1 and G2 as well as most likely also between G2 and G3 are formed. For HNPP three pKa clusters occur, that is those encompassing the pKa values of 2.44, 2.97, and 3.71 of G2(N7)H⁺, G3(N7)H⁺, and A1(N1)H⁺, respectively, with overlapping buffer regions. The tautomer populations were estimated, giving for the release of a single proton from five-fold protonated H5(HNPP)(±) , the tautomers (G2)N7, (G3)N7, and (A1)N1 with formation degrees of about 74, 22, and 4%, respectively. Tautomer distributions reveal pathways for proton-donating as well as for proton-accepting reactions both being expected to be fast and to occur practically at no "cost". The eight pKa values for H5(HNPP)(±) are compared with data for nucleosides and nucleotides, revealing that the nucleoside residues are in part affected very differently by their neighbors. In addition, the intrinsic acidity constants for the RNA derivative r(A1∙G2∙G3∙C4∙C5∙U6), where U=uridine, were calculated. Finally, the effect of metal ions on the pKa values of nucleobase sites is briefly discussed because in this way deprotonation reactions can easily be shifted to the physiological pH range.

Structural consequences of the N7 and C8 translocation on the metal binding behavior of adenine.

7-Deaza-8-aza-adenine, namely 4-aminopyrazolo[3,4-d]pyrimidine (H4app), is a bioisoster of adenine (Hade) resulting from the translocation of N7 and C8 atoms on the purine moiety. With the aim of studying the influence of this translocation on the metal binding abilities of H4app, we have prepared and structurally characterized two ternary copper(II) complexes having H4app and one N-benzyl-iminodiacetate chelator (MEBIDA or FBIDA, with a methyl or fluoro group in para- of the benzyl aromatic ring): [Cu(2)(MEBIDA)(2)(µ(2)-N1,N8-H4app)(H(2)O)(2)]·4H(2)O (1) and [Cu(4)(FBIDA)(4)(µ(2)-N8,N9-H4app)(2)(H(2)O)]·3.5H(2)O (2). Furthermore, thermal, spectral, and magnetic properties have been also investigated. In 1, H(N9)4app is disordered over two equally pondered positions and the µ(2)-N1,N8 coordination mode is assisted by N6-H···O and N9-H···O intramolecular interactions, respectively. The acyclic nonlinear molecular topology of 2 is strongly influenced by two intramolecular H-bonding interactions (O-H···O-carboxylate) involving the apical aqua ligand of a terminal Cu(II) atom. Thus, both compounds have in common the Cu-N8 bond. In order to better understand our limited structural information, DFT calculations for the individual tautomers of H4app as well as mononuclear Cu(II) model systems have been carried out. According to previous results, we conclude that H(N9)4app is the most stable tautomer followed by H(N8)4app. When N9 and N8 are metalated, then the tautomer H(N1)4app can come into play as observed in compound 2. Likewise, the findings concerning compound 1 suggest that the formation of a Cu-N1 bond in H4app results was favored compared to neutral adenine, for which only one case has been reported with such coordination despite the large variety of related Cu(II)-Hade described in the literature.

Host genetic variants associated with susceptibility and severity of pneumococcal pneumonia in adult patients.

BACKGROUND: Pneumococcal community-acquired pneumonia (P-CAP) is a major cause of morbidity and hospitalization. Several host genetics factors influencing risk of pneumococcal disease have been identified, with less information about its association with P-CAP. The aim of the study was to assess the influence of single nucleotide polymorphisms (SNP) within key genes involved in the innate immune response on the susceptibility to P-CAP and to study whether these polymorphic variants were associated with the severity and outcome of the episodes in a cohort of adult Caucasian patients. METHODS: Seventeen SNPs from 7 genes (IL-R1, IL-4, IL-10, IL-12B, NFKBIA, NFKBIE, NFKBIZ) were analyzed. For susceptibility, a case-control study including a cohort of 57 adult with P-CAP, and 280 ethnically matched controls was performed. Genetic influence on clinical severity and outcome was evaluated in a prospective observational study including all consecutive adult P-CAP patients from November 2015 to May 2017. RESULTS: The NFKBIA polymorphism rs696 and a haplotype combination were associated with susceptibility to P-CAP (OR = 0.62, p = 0.005 and OR = 0.63, p = 0.008, respectively). The SNP IL4 rs2227284 was associated with severe P-CAP (OR = 2.17, p = 0.04). IL-R1 (rs3917267) and IL-10 (rs3024509) variants were related with respiratory failure (OR = 3.31, p = 0.001 and OR = 0.18, p = 0.003, respectively) as well as several haplotype combinations in NFKBIA, NFKBIZ, IL-R1 and IL-10 (p = 0,02, p = 0,01, p = 0,001, p = 0,03, respectively). CURB-65 values were associated with the IL-10 rs3024509 variant (beta = - 0.4, p = 0.04), and with haplotype combinations of NFKBIZ and IL-10 (p = 0.05, p = 0.04, respectively). Genetic variants in IL-10 (rs3024509) and in IL-12B (rs730691) were associated with PSI values (beta = - 0.54, p = 0.01, and beta = - 0.28, p = 0.04, respectively), as were allelic combinations in IL-R1 (p = 0.02) and IL-10 (p = 0.01). Finally, several polymorphisms in the IL-R1 gene (rs13020778, rs2160227, & rs3917267) were associated with the time elapsed until clinical stability (beta = - 0.83, p = 0.03; beta = - 1, p = 0.02 and beta = 1.07, p = 0.008, respectively). CONCLUSIONS: A genetic variant in NFKBIA was associated with susceptibility to P-CAP in adult Caucasian patients and genetic variants from key cytokines of the innate immune response (Il-4, IL-10, IL-R1 and IL-12B) and NF-κB inhibitors were associated with different phenotypes of severe P-CAP. If validated, these SNPs may help to identify people at risk of P-CAP or severe P-CAP on which preventive measures could be applied.

Risk factors associated with inappropriate empirical antimicrobial treatment in bloodstream infections. A cohort study.

Introduction: Bloodstream infections (BSI) are a major cause of mortality all over the world. Inappropriate empirical antimicrobial treatment (i-EAT) impact on mortality has been largely reported. However, information on related factors for the election of i-EAT in the treatment of BSI in adults is lacking. The aim of the study was the identification of risk-factors associated with the use of i-EAT in BSI. Methods: A retrospective, observational cohort study, from a prospective database was conducted in a 400-bed acute-care teaching hospital including all BSI episodes in adult patients between January and December 2018. The main outcome variable was EAT appropriation. Multivariate analysis using logistic regression was performed. Results: 599 BSI episodes were included, 146 (24%) received i-EAT. Male gender, nosocomial and healthcare-associated acquisition of infection, a high Charlson Comorbidity Index (CCI) score and the isolation of multidrug resistant (MDR) microorganisms were more frequent in the i-EAT group. Adequation to local guidelines' recommendations on EAT resulted in 91% of appropriate empirical antimicrobial treatment (a-EAT). Patients receiving i-EAT presented higher mortality rates at day 14 and 30 when compared to patients with a-EAT (14% vs. 6%, p = 0.002 and 22% vs. 9%, p < 0.001 respectively). In the multivariate analysis, a CCI score ≥3 (OR 1.90 (95% CI 1.16-3.12) p = 0.01) and the isolation of a multidrug resistant (MDR) microorganism (OR 3.79 (95% CI 2.28-6.30), p < 0.001) were found as independent risk factors for i-EAT. In contrast, female gender (OR 0.59 (95% CI 0.35-0.98), p = 0.04), a correct identification of clinical syndrome prior to antibiotics administration (OR 0.26 (95% CI 0.16-0.44), p < 0.001) and adherence to local guidelines (OR 0.22 (95% CI 0.13-0.38), p < 0.001) were identified as protective factors against i-EAT. Conclusion: One quarter of BSI episodes received i-EAT. Some of the i-EAT related factors were unmodifiable (male gender, CCI score ≥3 and isolation of a MDR microorganism) but others (incorrect identification of clinical syndrome before starting EAT or the use of local guidelines for EAT) could be addressed to optimize the use of antimicrobials.

Evaluation of Plasma Lipocalin-2 as a Predictor of Etiology and Severity in Adult Patients with Community-Acquired Pneumonia.

The aim of this study was to evaluate the diagnostic performance of plasma Lipocalin-2 (LCN2) concentration in adult patients with community-acquired pneumonia (CAP) to determine its etiology, severity and prognosis. A prospective observational study involving adults with CAP from November 2015 to May 2017 was conducted. Plasma LCN2 concentration was measured upon admission by a modified enzyme immunoassay coupled with chemiluminescence (Architect, Abbott Laboratories). The diagnostic performance of LCN2, C-reactive protein (CRP) and white blood cell to predict bacterial CAP was assessed. A total of 130 patients with CAP were included: 71 (54.6%) bacterial CAP, 42 (32.3%) unknown origin CAP and 17 (13.1%) viral CAP. LCN2 was higher in bacterial CAP than in non-bacterial CAP (122.0 vs. 89.7 ng/mL, respectively) (p = 0.03) with a limited ability to distinguish bacterial and non-bacterial CAP (AUROC: 0.62 [95% CI 0.52-0.72]). The LCN2 cutoff ≥ 204 ng/mL predicted the presence of pneumococcal bacteremia with an AUROC of 0.74 (sensitivity 70%, specificity 79.1%). Regarding severity, as defined by CURB-65 and PSI scores, there was a significant linear trend in the mean concentration of LCN2, exhibiting a shift from the low-risk to the intermediate-risk and high-risk group (p < 0.001 and 0.001, respectively). LCN2 concentration was associated with severity in adult patients with CAP. However, its utility as a biomarker to discriminate viral and bacterial etiology in CAP is limited.

Unreliable networks with random parameter matrices and time-correlated noises: distributed estimation under deception attacks.

This paper examines the distributed filtering and fixed-point smoothing problems for networked systems, considering random parameter matrices, time-correlated additive noises and random deception attacks. The proposed distributed estimation algorithms consist of two stages: the first stage creates intermediate estimators based on local and adjacent node measurements, while the second stage combines the intermediate estimators from neighboring sensors using least-squares matrix-weighted linear combinations. The major contributions and challenges lie in simultaneously considering various network-induced phenomena and providing a unified framework for systems with incomplete information. The algorithms are designed without specific structure assumptions and use a covariance-based estimation technique, which does not require knowledge of the evolution model of the signal being estimated. A numerical experiment demonstrates the applicability and effectiveness of the proposed algorithms, highlighting the impact of observation uncertainties and deception attacks on estimation accuracy.

Improvement of pneumococcal pneumonia diagnosis using quantitative real-time PCR targeting lytA in adult patients: a prospective cohort study.

OBJECTIVES: The aim of the study was to assess the performance of real-time PCR targeting the lytA gene (rtPCR-lytA) in plasma, urine and nasopharyngeal (NP) samples for the diagnosis of pneumococcal community-acquired pneumonia (P-CAP). METHODS: Prospective observational study including all consecutive adults with CAP from November 2015 to May 2017. P-CAP was defined if pneumococcus was identified using conventional methods (CM) and/or a positive rtPCR-lytA was detected in blood, urine or NP samples (NP cut-off ≥8000 copies/mL). Diagnostic performance of each test was calculated. RESULTS: A total of 133 individuals with CAP were included. Of these, P-CAP was diagnosed in 62 (46.6%). The proportion of P-CAP diagnosed by rtPCR-lytA methods was significantly higher than that diagnosed by CM (87.1% versus 59.7%, p 0.005). The rtPCR-lytA identified Streptococcus pneumoniae in 25 patients (40.3% of all individuals with P-CAP) whose diagnosis would have been missed by CM. NP-rtPCR-lytA allowed diagnosis of 62.3% of P-CAP. A nasopharyngeal colonization density ≥2351 copies/mL predicted P-CAP diagnosis (area under the curve = 0.82, sensitivity 83.3%, specificity 80.9%). There was a positive correlation between increasing bacterial load in blood and CURB-65 score (Spearman correlation coefficient r = 0.4, p 0.001), pneumonia severity index (r = 0.3, p 0.02) and time to clinical stability (r = 0.33, p 0.01). Median bacterial load in blood was higher in P-CAP patients with bacteraemia (0.65 × 103 versus 0 × 103 copies/mL, p 0.002), intensive care unit admission (0.68 × 103 versus 0 × 103 copies/mL, p 0.04) or mechanical ventilation (7.45 × 103 versus 0 × 103 copies/mL, p 0.04). CONCLUSIONS: The use of rtPCR-lytA methods significantly increased the diagnosis of P-CAP compared with CM. Nasopharyngeal swabs rtPCR-lytA detection, with an accurate cut-off value, was the most promising among molecular methods for the diagnosis of P-CAP.

Chelating ligand conformation driving the hypoxanthine metal binding patterns.

The X-ray diffraction structural results of 23 ternary compounds, type M(II)(iminodiacetate-like)(hypoxanthine) [M = Co, Ni, Cu, or Zn], show that the iminodiacetate moiety conformation (mer-NO(2) or fac-NO(2)) is able to drive the M-hypoxanthine binding patterns displaying the M-N9 or M-N3 bond, cooperating with a N9-H···O intramolecular interaction, respectively.