Predictive role of blood-based indicators in neuromyelitis optica spectrum disorders

IntroductionThis study aimed to assess the predictive role of blood markers in neuromyelitis optica spectrum disorders (NMOSD).MethodsData from patients with NMOSD, multiple sclerosis (MS), and healthy individuals were retrospectively collected in a 1:1:1 ratio. The expanded disability status scale (EDSS) score was used to assess the severity of the NMOSD upon admission. Receiver operating characteristic (ROC) curve analysis was used to distinguish NMOSD patients from healthy individuals, and active NMOSD from remitting NMOSD patients. Binary logistic regression analysis was used to evaluate risk factors that could be used to predict disease recurrence. Finally, Wilcoxon signed-rank test or matched-sample t-test was used to analyze the differences between the indicators in the remission and active phases in the same NMOSD patient.ResultsAmong the 54 NMOSD patients, neutrophil count, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) (platelet × NLR) were significantly higher than those of MS patients and healthy individuals and positively correlated with the EDSS score of NMOSD patients at admission. PLR can be used to simultaneously distinguish between NMOSD patients in the active and remission phase. Eleven (20.4%) of the 54 patients had recurrence within 12 months. We found that monocyte-to-lymphocyte ratio (MLR) (AUC = 0.76, cut-off value = 0.34) could effectively predict NMOSD recurrence. Binary logistic regression analysis showed that a higher MLR at first admission was the only risk factor for recurrence (p = 0.027; OR = 1.173; 95% CI = 1.018–1.351). In patients in the relapsing phase, no significant changes in monocyte and lymphocyte count was observed from the first admission, whereas patients in remission had significantly higher levels than when they were first admitted.ConclusionHigh PLR is a characteristic marker of active NMOSD, while high MLR is a risk factor for disease recurrence. These inexpensive indicators should be widely used in the diagnosis, prognosis, and judgment of treatment efficacy in NMOSD

Igg, Igm and Iga Antibodies against the Novel Polyprotein in Active Tuberculosis

Background The present study was aimed to evaluate whether IgG, IgM and IgA antibodies levels detected against a novel Mycobacterium tuberculosis polyprotein 38 F-64 F (with 38 F being the abbreviation for 38kD-ESAT6-CFP10 and 64 F for Mtb8.4-MPT64-TB16.3-Mtb8) are suitable for diagnosing active tuberculosis, and for monitoring the efficacy of chemotherapy on TB patients. Methods In this study, a total of 371 active TB patients without treatment were selected and categorized into S+/C+ group (n = 143), S-/C+ group (n = 106) or S-/C- group (n = 122). A series of serum samples were collected from 82 active TB patients who had undergone anti-TB chemotherapy for 0–6 months at one month interval. Humoral responses (IgG, IgM and IgA) were determined for the novel Mycobacterium tuberculosis polyprotein using indirect ELISA methods in all of serum samples. Results For S+/C+, S-/C+ and S-/C- active tuberculosis patients before anti-TB chemotherapy, the sensitivities of tests based on IgG were 65.7%, 46.2% and 52.5% respectively; the sensitivities based on IgM were 21.7%, 24.5% and 18.9%; and the sensitivities based on IgA were 25.2%, 17.9% and 23.8%. By combination of three isotypes, for all active tuberculosis patients, the test sensitivity increased to 70.4% with the specificity being 91.5%. After anti-TB chemotherapy, there were no significant differences between groups with different courses of anti-TB chemotherapy. Conclusions The novel Mycobacterium tuberculosis polyprotein 38 F-64 F represents potential antigen suitable for measuring IgG, IgM and IgA antibodies. However, the serodiagnostic test based on the 38 F-64 F polyprotein appears unsuitable for monitoring the efficacy of chemotherapy

A multiple-antigen detection assay for tuberculosis diagnosis based on broadly reactive polyclonal antibodies

Objective(s): Detection of circulating Mycobacterium tuberculosis (M. tuberculosis) antigens is promising in Tuberculosis (TB) diagnosis. However, not a single antigen marker has been found to be widely expressed in all TB patients. This study is aimed to prepare broadly reactive polyclonal antibodies targeting multiple antigen markers (multi-target antibodies) and evaluate their efficacies in TB diagnosis. Materials and Methods: A fusion gene consisting of 38kD, ESAT6, and CFP10 was constructed and overexpressed. The fusion polyprotein was used as an immunogen to elicit production of multi-target antibodies. Their reactivities were tested. Then, the multi-target antibodies and three corresponding antibodies elicited by each single antigen (mono-target antibodies) were evaluated with sandwich ELISA for detecting M. tuberculosis antigens. Their diagnostic efficacies for TB were also compared. Results: The polyprotein successfully elicited production of multi-target antibodies targeting 38kD, ESAT6, and CFP10 as analyzed by Western blotting. When used as coating antibodies, the multi-target antibodies were more efficient in capturing the three antigens than the corresponding mono-target antibodies. By testing clinical serum, the multi-target antibodies demonstrated significantly higher sensitivity for clinical TB diagnosis than all three mono-target antibodies. Conclusion: The multi-target antibodies allowed detecting multiple antigens simultaneously and significantly enhanced TB detection compared to routine mono-target antibodies. Our study may provide a promising strategy for TB diagnosis

Phase-Modulated Waveform Design for Extended Target Detection in the Presence of Clutter

The problem to be addressed in this paper is a phase-modulated waveform design for the detection of extended targets contaminated by signal-dependent noise (clutter) and additive noise in practical radar systems. An optimal waveform design method that leads to the energy spectral density (ESD) of signal under the maximum signal-to-clutter-and-noise ratio (SCNR) criterion is introduced first. In order to make full use of the transmission power, a novel phase-iterative algorithm is then proposed for designing the phase-modulated waveform with a constant envelope, whose ESD matches the optimal one. This method is proven to be able to achieve a small SCNR loss by minimizing the mean-square spectral distance between the optimal waveform and the designed waveform. The results of extensive simulations demonstrate that our approach provides less than 1 dB SCNR loss when the signal duration is greater than 1 μs, and outperforms the stationary phase method and other phase-modulated waveform design methods

DOA Estimation of Coherent Signals on Coprime Arrays Exploiting Fourth-Order Cumulants

This paper considers the problem of direction-of-arrival (DOA) estimation of coherent signals on passive coprime arrays, where we resort to the fourth-order cumulants of the received signal to explore more information. A fourth-order cumulant matrix (FCM) is introduced for the coprime array. The special structure of the FCM is combined with the array configuration to resolve the coherent signals. Since each sparse array of a coprime array is uniform, a series of overlapping identical subarrays can be extracted. Using this property, we propose a generalized spatial smoothing scheme applied to the FCM. From the smoothed FCM, the DOAs of both the coherent and independent signals can be successfully estimated on the pseudo-spectrum generated by the fourth-order MUSIC algorithm. To overcome the problem of occasional false peaks appearing on the pseudo-spectrum, we use a supplementary sparse array whose inter-sensor spacing is coprime to that of either existing sparse array. From the combined spectrum aided by the supplementary sensors, the false peaks are removed while the true peaks remain. The effectiveness of the proposed methods is demonstrated by simulation examples

A Low-Power Area-Efficient Precision Scalable Multiplier with an Input Vector Systolic Structure

In this paper, a small-area low-power 64-bit integer multiplier is presented, which is suitable for portable devices or wireless applications. To save the area cost and power consumption, an input vector systolic (IVS) structure is proposed based on four 16-bit radix-8 Booth multipliers and a data input scheme is proposed to reduce the number of signal transitions. This structure is similar to a systolic array in matrix multiply units of a Convolutional Neural Network (CNN), but it reduces the number of processing elements by 3/4 concerning the same vector systolic accelerator in reference. The comparison results prove that the IVS multiplier reduces at least 61.9% of the area and 45.18% of the power over its counterparts. To increase the hardware resource utilization, a Transverse Carry Array (TCA) structure for Partial Products Accumulation (PPA) was designed by replacing the 32-bit adders with 3/17-bit adders in the 16-bit multipliers. The experiment results show that the optimization could lead to at least a 6.32% and 13.65% reduction in power consumption and area cost, respectively, compared to the standard 16-bit radix-8 Booth multiplier. In the end, the precise scale of the proposed IVS multiplier is discussed. Benefiting from the modular design, the IVS multiplier can be configured to support sixteen different kinds of multiplications at a step of 16 bits [16b, 32b, 48b, 64b] × [16b, 32b, 48b, 64b]

A Low-Power Area-Efficient Precision Scalable Multiplier with an Input Vector Systolic Structure

In this paper, a small-area low-power 64-bit integer multiplier is presented, which is suitable for portable devices or wireless applications. To save the area cost and power consumption, an input vector systolic (IVS) structure is proposed based on four 16-bit radix-8 Booth multipliers and a data input scheme is proposed to reduce the number of signal transitions. This structure is similar to a systolic array in matrix multiply units of a Convolutional Neural Network (CNN), but it reduces the number of processing elements by 3/4 concerning the same vector systolic accelerator in reference. The comparison results prove that the IVS multiplier reduces at least 61.9% of the area and 45.18% of the power over its counterparts. To increase the hardware resource utilization, a Transverse Carry Array (TCA) structure for Partial Products Accumulation (PPA) was designed by replacing the 32-bit adders with 3/17-bit adders in the 16-bit multipliers. The experiment results show that the optimization could lead to at least a 6.32% and 13.65% reduction in power consumption and area cost, respectively, compared to the standard 16-bit radix-8 Booth multiplier. In the end, the precise scale of the proposed IVS multiplier is discussed. Benefiting from the modular design, the IVS multiplier can be configured to support sixteen different kinds of multiplications at a step of 16 bits [16b, 32b, 48b, 64b] × [16b, 32b, 48b, 64b]