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In this paper, a CMOS wideband low-pass filter is proposed. In the wide band active filter design, the unit gain frequency (GBW) of OPAMP should be larger than GHz. The GBW of the proposed OPAMP is around 2.3 GHz. Additionally, the OPAMP with a complementary structure in signal and common mode feedback is proposed and has a wide operating voltage range at the input and output. The 1-dB gain compression point (P1dB) at the output is 4.9 dBm. A source follower is employed for driving 50 Ω output impedance without degrading the bandwidth and linearity of the filter. The power consumption is 27 mW from a 1-V supply voltage. The 3 dB bandwidth of the filter ranges from 330 MHz to 660 MHz with 3-bit cap tuning. This work is implemented in a 65-nm CMOS process, with a chip area of 0.18 mm2.

In this paper, an energy-efficient switching scheme with additional quarter-reference voltage sources in a successive approximation register (SAR) analog-to-digital converter (ADC) is proposed for a low power and small area device for frequency modulated continuous wave (FMCW) radar transceivers. Recently, state-of-the-art ADCs have adopted a configuration that also uses Vref/2 as the reference voltage of the ADCs to improve the switching energy of capacitive digital-to-analog converter (CDAC). The proposed switching configuration additionally uses Vref/4 and 3Vref/4 reference voltages as the reference voltage of CDAC. Compared to state-of-the-art configurations that use the additional reference voltage of Vref/2, the average switching energy, and the total capacitance of CDAC in the proposed configuration are reduced by about 87.5% and 50%, respectively. In this switching scheme, the CDAC output voltage gradually converges to Vref/2, like with conventional SAR ADCs, which minimizes the dynamic offset that deteriorates the linearity of the SAR ADC.

The Korean Society of Laryngology, Phoniatrics and Logopedics appointed a task force to establish clinical practice guidelines for the management of unilateral vocal fold paralysis (UVFP). These guidelines cover a comprehensive range of management-related factors, including the diagnosis and treatment of UVFP, and provide in-depth information based on current, up-to-date knowledge. Detailed evidence profiles are provided for each recommendation. The CORE databases, including OVID Medline, Embase, the Cochrane Library, and KoreaMed, were searched to identify all relevant papers, using a predefined search strategy. When insufficient evidence existed, expert opinions and Delphi questionnaires were used to fill the evidence gap. The committee developed 16 evidence-based recommendations in six categories: initial evaluation (R1–4), spontaneous recovery (R5), medical treatment (R6), surgical treatment (R7–14), voice therapy (R15), and aspiration prevention (R16). The goal of these guidelines is to assist general otolaryngologists and speech-language pathologists who are primarily responsible for treating patients with UVFP. These guidelines are also intended to facilitate understanding of the condition among other health-care providers, including primary care physicians, nurses, and policy-makers.

This paper examines the relationship of the leading financial assets, Bitcoin, Gold, and S&P 500 with GARCH-Dynamic Conditional Correlation (DCC), Nonlinear Asymmetric GARCH DCC (NA-DCC), Gaussian copula-based GARCH-DCC (GC-DCC), and Gaussian copula-based Nonlinear Asymmetric-DCC (GCNA-DCC). Under the high volatility financial situation such as the COVID-19 pandemic occurrence, there exist a computation difficulty to use the traditional DCC method to the selected cryptocurrencies. To solve this limitation, GC-DCC and GCNA-DCC are applied to investigate the time-varying relationship among Bitcoin, Gold, and S&P 500. In terms of log-likelihood, we show that GC-DCC and GCNA-DCC are better models than DCC and NA-DCC to show relationship of Bitcoin with Gold and S&P 500. We also consider the relationships among time-varying conditional correlation with Bitcoin volatility, and S&P 500 volatility by a Gaussian Copula Marginal Regression (GCMR) model. The empirical findings show that S&P 500 and Gold price are statistically significant to Bitcoin in terms of log-return and volatility.

The vacuolar H+-adenosine triphosphatase (ATPase) subunit V0C (ATP6V0C), a proton-conducting, pore-forming subunit of vacuolar ATPase, maintains pH homeostasis and induces organelle acidification. The intracellular and extracellular pH of cancer cells affects their growth; however, the role of ATP6V0C in highly invasive esophageal cancer cells (ECCs) remains unclear. In this study, we examined the role of ATP6V0C in glucose metabolism in ECCs. The ATP6V0C depletion attenuated ECC proliferation, invasion, and suppressed glucose metabolism, as indicated by reduced glucose uptake and decreased lactate and adenosine triphosphate (ATP) production in cells. Consistent with this, expression of glycolytic enzyme and the extracellular acidification rate (ECAR) were also decreased by ATP6V0C knockdown. Mechanistically, ATP6V0C interacted with pyruvate kinase isoform M2 (PKM2), a key regulator of glycolysis in ECCs. The ATP6V0C depletion reduced PKM2 phosphorylation at tyrosine residue 105 (Tyr105), leading to inhibition of nuclear translocation of PKM2. In addition, ATP6V0C was recruited at hypoxia response element (HRE) sites in the lactate dehydrogenase A (LDHA) gene for glycolysis. Thus, our data suggest that ATP6V0C enhances aerobic glycolysis and motility in ECCs.

In current business management, knowledge is considered to be a strategic resource that can strengthen an organization’s competitiveness. Today, under the process of continuous globalization, almost all companies are rapidly exposed to global competition regardless of their scale or type of business. However, multinational management is very complicated and uncertain and it is hard for multinationals to effectively coordinate and manage their global value chains. In light of this, the utility of multinational management based on knowledge is increased. The present study examines multinational firms’ knowledge management systems, knowledge creation processes and global supply chain performance and attempts to reveal any significant linkages between these latent variables. For this research interest, we proposed 18 items to measure four types of knowledge creation processes (SECI) designed by Nonaka (1994) and revised by authors considering the global business environment, in particular involving the global supply chain management concept. Utilizing the confirmed SECI model, 128 sample companies were classified into four groups according to the levels of their knowledge creation processes. The empirical results of this study reveal important linkages between a multinational firm’s knowledge management system and knowledge creation process, as well as between its knowledge creation process and global supply chain management performance. In particular, the current work suggests that the creation and conversion of tacit knowledge as well as explicit knowledge can be effectively supported by information and communication technology.

Prostate cancer gene 3 (PCA3) is a non-coding gene specifically overexpressed in prostate cancer (PCa) that has great potential as a clinical biomarker for predicting prostate biopsy outcome. However, genetic determinants of PCA3 expression level remain unknown. To investigate the association between genetic variants and PCA3 mRNA level, a genome-wide association study was conducted in 1371 men of European descent in the REduction by DUtasteride of prostate Cancer Events trial. First-voided urine specimens containing prostate cells were obtained after digital rectal examination. The PROGENSA PCA3 assay was used to determine PCA3 score in the urinary samples. A linear regression model was used to detect the associations between (single nucleotide polymorphisms) SNPs and PCA3 score under an additive genetic model, adjusting for age and population stratification. Two SNPs, rs10993994 in β-microseminoprotein at 10q11.23 and rs10424878 in kallikrein-related peptidase 2 at 19q13.33, were associated with PCA3 score at genome-wide significance level (P = 1.22 x 10-9 and 1.06 x 10-8, respectively). Men carrying the rs10993994 “T” allele or rs10424878 “A” allele had higher PCA3 score compared with men carrying rs10993994 “C” allele or rs10424878 “G” allele (β = 1.25 and 1.24, respectively). This is the first comprehensive search for genetic determinants of PCA3 score. The novel loci identified may provide insight into the molecular mechanisms of PCA3 expression as a potential marker of PCa.

BACKGROUND: Percentage of free-to-total prostate-specific antigen (%fPSA) is an independent predictor of risk for prostate cancer among men with modestly elevated level of total PSA (tPSA) in blood. Physiological and pathological factors have been shown to influence the %fPSA value and diagnostic accuracy. MATERIALS/METHODS: To evaluate genetic determinants of %fPSA, we conducted a genome-wide association study of serum %fPSA by genotyping 642,584 single nucleotide polymorphisms (SNPs) in 3192 men of European ancestry, each with a tPSA level of 2.5 to 10 ng/ml, that were recruited in the REduction by DUtasteride of Prostate Cancer Events study. Single nucleotide polymorphisms (SNPs) with P

KCNQ channels are critical determinants of neuronal excitability, thus emerging as a novel target of anti-epileptic drugs. To date, the mechanisms of KCNQ channel modulation have been mostly characterized to be inhibitory via Gq-coupled receptors, Ca2+/CaM, and protein kinase C. Here we demonstrate that methylation of KCNQ by protein arginine methyltransferase 1 (Prmt1) positively regulates KCNQ channel activity, thereby preventing neuronal hyperexcitability. Prmt1+/- mice exhibit epileptic seizures. Methylation of KCNQ2 channels at 4 arginine residues by Prmt1 enhances PIP2 binding, and Prmt1 depletion lowers PIP2 affinity of KCNQ2 channels and thereby the channel activities. Consistently, exogenous PIP2 addition to Prmt1+/- neurons restores KCNQ currents and neuronal excitability to the WT level. Collectively, we propose that Prmt1-dependent facilitation of KCNQ-PIP2 interaction underlies the positive regulation of KCNQ activity by arginine methylation, which may serve as a key target for prevention of neuronal hyperexcitability and seizures.

Tuberculous trochanteric bursitis is rare. We report on a 48-year-old man with a huge gravitational abscess in the thigh secondary to tuberculosis of the trochanteric bursa.

In utero injection of a retroviral vector into the embryonic telencephalon aided by ultrasound backscatter microscopy permits introduction of a gene of interest at an early stage of development. In this study, we compared the tissue distribution of gene expression in adult mice injected with retroviral vectors at different embryonic ages in utero. Following ultrasound image-guided gene delivery (UIGD) into the embryonic telencephalon, adult mice were subjected to whole-body luciferase imaging and immunohistochemical analysis at 6 weeks and 1 year postinjection. Luciferase activity was observed in a wide range of tissues in animals injected at embryonic age 9.5 (E9.5), whereas animals injected at E10.5 showed brain-localized reporter gene expression. These results suggest that mouse embryonic brain creates a closed and impermeable structure around E10. Therefore, by injecting a transgene before or after E10, transgene expression can be manipulated to be local or systemic. Our results also provide information that widens the applicability of UIGD beyond neuroscience studies.

Complement C3 and C4 play key roles in the main physiological activities of complement system, and their deficiencies or over-expression are associated with many clinical infectious or immunity diseases. A two-stage genome-wide association study (GWAS) was performed for serum levels of C3 and C4. The first stage was conducted in 1,999 healthy Chinese men, and the second stage was performed in an additional 1,496 subjects. We identified two SNPs, rs3753394 in CFH gene and rs3745567 in C3 gene, that are significantly associated with serum C3 levels at a genome-wide significance level (P = 7.33 × 10(-11) and P = 1.83 × 10(-9), respectively). For C4, one large genomic region on chromosome 6p21.3 is significantly associated with serum C4 levels. Two SNPs (rs1052693 and rs11575839) were located in the MHC class I area that include HLA-A, HLA-C, and HLA-B genes. Two SNPs (rs2075799 and rs2857009) were located 5' and 3' of C4 gene. The other four SNPs, rs2071278, rs3763317, rs9276606, and rs241428, were located in the MHC class II region that includes HLA-DRA, HLA-DRB, and HLA-DQB genes. The combined P-values for those eight SNPs ranged from 3.19 × 10(-22) to 5.62 × 10(-97). HBsAg-positive subjects have significantly lower C3 and C4 protein concentrations compared with HBsAg-negative subjects (P

The p53 tumor suppressor function can be compromised in many tumors by the cellular antagonist HDM2 and human papillomavirus oncogene E6 that induce p53 degradation. Restoration of p53 activity has strong therapeutic potential. Here, we identified TSC-22 as a novel p53-interacting protein and show its novel function as a positive regulator of p53. We found that TSC-22 level was significantly down-regulated in cervical cancer tissues. Moreover, over-expression of TSC-22 was sufficient to inhibit cell proliferation, promote cellular apoptosis in cervical cancer cells and suppress growth of xenograft tumors in mice. Expression of also TSC-22 enhanced the protein level of p53 by protecting it from poly-ubiquitination. When bound to the motif between amino acids 100 and 200 of p53, TSC-22 inhibited the HDM2- and E6-mediated p53 poly-ubiquitination and degradation. Consequently, ectopic over-expression of TSC-22 activated the function of p53, followed by increased expression of p21(Waf1/Cip1) and PUMA in human cervical cancer cell lines. Interestingly, TSC-22 did not affect the interaction between p53 and HDM2. Knock-down of TSC-22 by small interfering RNA clearly enhanced the poly-ubiquitination of p53, leading to the degradation of p53. These results suggest that TSC-22 acts as a tumor suppressor by safeguarding p53 from poly-ubiquitination mediated-degradation.

BACKGROUND: Prostate-specific antigen (PSA) screening is growing in popularity in China, but its impact on biopsy characteristics and outcomes are poorly understood. OBJECTIVE: Our objective was to characterize prostate biopsy outcomes and trends in Chinese men over a 10-year period, since the increasing use of PSA tests. METHODS: All men (n = 1,650) who underwent prostate biopsy for PCa at Huashan Hospital, Shanghai, China from 2003-2011 were evaluated. Demographic and clinical information was collected for each patient, including age, digital rectal examination (DRE), transrectal ultrasound (prostate volume and nodule), total prostate-specific antigen (tPSA) levels and free PSA ratio (fPSA/tPSA) prior to biopsy. Prostate biopsy was performed using six cores before October 2007 or ten cores thereafter. Logistic regression and multivariate analysis were used to evaluate our data. RESULTS: The overall positive rate of prostate biopsy for PCa was 47% and the rate decreased significantly over the years from 74% in 2003 to 33% in 2011 (P-trend = 0.004). Age at diagnosis was slightly increased (P-trend = 0.04) while fPSA/tPSA was significantly decreased (P-trend = 1.11×10-5). A statistically significant trend was not observed for tPSA levels, prostate volume, or proportion of positive nodule. The model including multiple demographic and clinical variables (i.e., age, DRE, tPSA, fPSA/tPSA and transrectal ultrasound results) (AUC = 0.93) statistically outperformed models that included only PSA (AUC = 0.85) or fPSA/tPSA (AUC = 0.66) to predict PCa risks (P

Many differentially methylated genes have been identified in prostate cancer (PCa), primarily using candidate gene-based assays. Recently, several global DNA methylation profiles have been reported in PCa, however, each of these has weaknesses in terms of ability to observe global DNA methylation alterations in PCa. We hypothesize that there remains unidentified aberrant DNA methylation in PCa, which may be identified using higher resolution assay methods. We used the newly developed Illumina HumanMethylation450 BeadChip in PCa (n = 19) and adjacent normal tissues (n = 4) and combined these with gene expression data for identifying new DNA methylation that may have functional consequences in PCa development and progression. We also confirmed our methylation results in an independent data set. Two aberrant DNA methylation genes were validated among an additional 56 PCa samples and 55 adjacent normal tissues. A total 28,735 CpG sites showed significant differences in DNA methylation (FDR adjusted P

Purpose. To compare treatment outcomes after closing wedge osteotomy and plate fixation for cubitus varus deformity undertaken with or without medialisation of the distal fragment. Methods. Records of 21 men and 16 women aged 20 to 34 years who underwent closing wedge osteotomy and plate fixation for cubitus varus deformity with (n=21) or without (n=16) medialisation of the distal fragment were reviewed. A daily alternate flexion-extension splinting was applied for one week for early restoration of full range of motion. The carrying angle and range of motion of the elbow were measured. Results. All patients regained the normal carrying angle and range of motion; none had loss of fixation or limitation in range of motion exceeding 10°. Outcomes were excellent in 23 patients and good in 9. A small bony prominence over the lateral condylar region (‘lazy S’ deformity) was noted in group-1 but not group-2 patients. Conclusion. Closing wedge supracondylar osteotomy with medialisation of the distal fragment was an effective treatment for cubitus varus deformity and minimised the risk of ‘lazy S’ deformity.

Consistent segmentation of CT scans in COVID-19 patients across multiple time points is important to accurately evaluate disease progression and therapeutic response. In medical domains, previous interactive segmentation studies have been mainly conducted on data from a single time point. However, the valuable segmentation information from previous time points is often underutilized in assisting the segmentation of a patient’s follow-up scans. Moreover, fully automatic segmentation techniques frequently produce results that would need further refinement for clinical applicability. In this study, we propose a novel single-network model for interactive segmentation that fully leverages all available past information to refine the segmentation of follow-up scans. In the first segmentation round, our model takes concatenated slices of 3D volumes from two-time points (target and reference), employing the segmentation results from the reference time point as a guide for segmenting the target scan. Subsequent refinement rounds incorporate user feedback in the form of scribbles that rectify the segmentation, in addition to incorporating the previous segmentation results of the target scan. This iterative process ensures the preservation of segmentation information from prior refinement rounds. Experimental results obtained from our in-house multiclass longitudinal COVID-19 dataset demonstrate the effectiveness of the proposed method compared to its static counterpart, thus providing valuable assistance in localizing COVID-19 infections in patients’ follow-up scans.

Time series anomaly detection is a task that determines whether an unseen signal is normal or abnormal, and it is a crucial function in various real-world applications. Typical approach is to learn normal data representation using generative models, like Generative Adversarial Network (GAN), to discriminate between normal and abnormal signals. Recently, a few studies actively adopt Transformer to model time series data, but there is no pure Transformer-based GAN framework for time series anomaly detection. As a pioneer work, we propose a new pure Transformer-based GAN framework, called AnoFormer, and its effective training strategy for better representation learning. Specifically, we improve the detection ability of our model by introducing two-step masking strategies. The first step is Random masking: we design a random mask pool to hide parts of the signal randomly. This allows our model to learn the representation of normal data. The second step is Exclusive and Entropy-based Re-masking: we propose a novel refinement step to provide feedback to accurately model the exclusive and uncertain parts in the first step. We empirically demonstrate the effectiveness of re-masking step that generates more normal-like signals robustly. Extensive experiments on various datasets show that AnoFormer significantly outperforms the state-of-the-art methods in time series anomaly detection.

Quantitative assessment of the abdominal region from CT scans requires the accurate delineation of abdominal organs. Therefore, automatic abdominal image segmentation has been the subject of intensive research for the past two decades. Recently, deep learning-based methods have resulted in state-of-the-art performance for the 3D abdominal CT segmentation. However, the complex characterization of abdominal organs with weak boundaries prevents the deep learning methods from accurate segmentation. Specifically, the voxels on the boundary of organs are more vulnerable to misprediction due to the highly-varying intensities. This paper proposes a method for improved abdominal image segmentation by leveraging organ-boundary prediction as a complementary task. We train 3D encoder-decoder networks to simultaneously segment the abdominal organs and their boundaries via multi-task learning. We explore two network topologies based on the extent of weights shared between the two tasks within a unified multi-task framework. In the first topology, the whole-organ prediction task and the boundary detection task share all the layers in the network except for the last task-specific layers. The second topology employs a single shared encoder but two separate task-specific decoders. The effectiveness of utilizing the organs’ boundary information for abdominal multi-organ segmentation is evaluated on two publically available abdominal CT datasets: Pancreas-CT and the BTCV dataset. The improvements shown in segmentation results reveal the advantage of the multi-task training that forces the network to pay attention to ambiguous boundaries of organs. A maximum relative improvement of 3.5% and 3.6% is observed in Mean Dice Score for Pancreas-CT and BTCV datasets, respectively.

Collecting large-labeled data is an expensive and challenging issue for training deep neural networks. To address this issue, active learning is recently studied where the active learner provides informative samples for labeling. Diversity-based sampling algorithms are commonly used for representation-based active learning. In this paper, a new diversity-based sampling is introduced for semi-supervised active learning. To select more informative data at the initial stage, we devise a diversity-based initial dataset selection method by using self-supervised representation. We further propose a new active learning query strategy, which exploits both consistency and diversity. Comparative experiments show that the proposed method can outperform other active learning approaches on two public datasets.

Multimodal emotion recognition has gained much traction in the field of affective computing, human–computer interaction (HCI), artificial intelligence (AI), and user experience (UX). There is growing demand to automate analysis of user emotion towards HCI, AI, and UX evaluation applications for providing affective services. Emotions are increasingly being used, obtained through the videos, audio, text or physiological signals. This has led to process emotions from multiple modalities, usually combined through ensemble-based systems with static weights. Due to numerous limitations like missing modality data, inter-class variations, and intra-class similarities, an effective weighting scheme is thus required to improve the aforementioned discrimination between modalities. This article takes into account the importance of difference between multiple modalities and assigns dynamic weights to them by adapting a more efficient combination process with the application of generalized mixture (GM) functions. Therefore, we present a hybrid multimodal emotion recognition (H-MMER) framework using multi-view learning approach for unimodal emotion recognition and introducing multimodal feature fusion level, and decision level fusion using GM functions. In an experimental study, we evaluated the ability of our proposed framework to model a set of four different emotional states (Happiness, Neutral, Sadness, and Anger) and found that most of them can be modeled well with significantly high accuracy using GM functions. The experiment shows that the proposed framework can model emotional states with an average accuracy of 98.19% and indicates significant gain in terms of performance in contrast to traditional approaches. The overall evaluation results indicate that we can identify emotional states with high accuracy and increase the robustness of an emotion classification system required for UX measurement.

Longitudinal analysis of a disease is an important issue to understand its progression and design prognosis and early diagnostic tools. From the longitudinal images where data is collected from multiple time points, both the spatial structural information and the longitudinal variations are captured. The temporal dynamics are more informative than static observations of the symptoms, particularly for neurodegenerative diseases such as Alzheimer’s disease, whose progression spans over the years with early subtle changes. In this paper, we propose a new generative framework to predict the lesion progression over time. Our method first encodes images into the structural and longitudinal state vectors, where interpolation or extrapolation of feature vectors in the time axis can be performed for the manipulation of these feature vectors. These processed feature vectors can be decoded into image space to predict the image at the time point which we are interested in. During the training, we force the model to encode longitudinal changes into longitudinal state features and capture the structural information in a separate vector. Moreover, we introduce a personalized memory for the online update scheme, which adapts the model to the target subject, which helps the model preserve fine details of brain image structures in each subject. Experimental results on the public longitudinal brain magnetic resonance imaging dataset show the effectiveness of the proposed method.

(1) Background: The Chief Executive Officer’s (CEO’s) message on a hospital’s homepage on the Internet contains various components, such as the hospital’s future vision, promises to customers, availability of upgraded services and public activities. This statement usually includes non-financial information as well as financial information about the corporate entity owning/operating the hospital. In addition, it provides useful information about not only the company’s goals and vision, but also firm performance targets and strategies for the future. This study aims to investigate associations between the CEO’s message and the financial status of the institution. We used the balanced scorecard framework to analyze what content on the hospital’s homepage is related to the hospital’s various financial ratios. (2) Methods: We adopted a text-mining method to extract significantly repeated keywords from the CEO’s message on the hospital’s website. Then, we classified these keywords using a balanced scorecard approach. To examine the relationship between keywords in the CEO’s message and the hospital’s financial ratios, a t-test was conducted for the difference in the term frequency divided by inverse document frequency (TF-IDF) mean of the home page contents and its relationship with the views of the balanced scorecard framework. (3) Results: According to our empirical results on 65 samples collected from local hospitals, there are some significant relationships between the qualitative content of the hospital’s homepage and the quantitative financial ratios that indicate profitability, activity, leverage, liquidity, and accumulating reserves for proper business purposes. (4) Conclusions: The introduction section of a homepage is the part most accessible to customers, containing the aims and ideals of the hospital and reflecting the institution’s values and visions. In addition, in the coverage of financial status, the organization can either emphasize financial strength or focus on other areas to divert attention from any weakness shown in the financial information. This study reminds us of the importance of the hospital website’s disclosure, and what can be inferred from the financial status of the hospital. It also highlights the need for reconciliation and harmony between the quantitative data, financial statements, and qualitative data in the CEO’s message. (5) Implications: To the best of our knowledge, this paper is the first research attempting to investigate the relationship between text on the hospital’s homepage and the hospital’s financial ratios using text-mining techniques and the balanced scorecard framework. Hospitals play a crucial role in a country’s welfare and healthcare industry. Nevertheless, in many countries, hospital organizations tend to remain a source of critical fiscal deficits due to ineffective and sloppy management. We expect that the result of this paper can provide hospital managers with useful information to address that situation.

ObjectivesVerbal communication depends on a good function of voice and speech organs. Some of the voice characteristics of deaf people differ considerably from those of speakers with normal hearing. After cochlear implantation (CI), auditory control of voice production is possible and the quality of the voice is improved. CI improves quality of voice, speech and hearing with deafness. The aim of our study was to investigate the relationship between acoustic analysis before CI and the speech intelligibility before and after CI.MethodsTwelve prelingually deafened children implanted unilaterally at the age of 3.4-9 years were included in the study. For all of the children an acoustic analysis of the Slovene vowel 'a' was performed before CI. The fundamental frequency (F0), jitter, shimmer and noise-to-harmonic ratio (NHR) were studied before the implantation. For all of the children the speech intelligibility was performed before and 12 months after CI. Preoperative hearing was divided on existing residual hearing. The results of the acoustic analyses and speech intelligibility before and after CI were compared for preoperative hearing. The results of the speech intelligibility were compared for the age of operation and preoperative acoustic analysis (F0, jitter, shimmer, NHR).ResultsPreoperative hearing had no influence on preoperative voice analysis. The children with residual hearing had a high grade of speech intelligibility before and after CI. The preoperative shimmer had positive correlation with postoperative 12 month speech intelligibility (r=0.618, P=0.032). The preoperative jitter had positive correlation with postoperative 12 month speech intelligibility, but was not statistically significant (r=0.479, P=0.116).ConclusionShimmer on preoperative voice analyses had influence on speech intelligibility after CI.