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PURPOSE@#. The aim of this study was to evaluate the reliability of implant stability measuring devices depending on the location of the implant and the position of the patient. @*MATERIALS AND METHODS@#. Six implants were installed in different dentate sextants of six artificial bone models. Implant stability was measured in three conditions of the bone model (without mounting on a phantom head, mounted on a phantom head in supine position, and mounted on a phantom head in upright position). A resonance frequency analysis device (Osstell) and two damping capacity analysis devices (Periotest and Anycheck) were used to measure implant stability. The values measured outside the phantom head were treated as controls, and the values inside the phantom head were compared using an independent t-test. @*RESULTS@#. Osstell showed different results in two of the six divisions in both the supine and upright positions compared to outside of the mouth (P < .05). Periotest showed different results in all six parts in the supine position and in five parts in the upright position compared to outside of the mouth (P < .05). While Anycheck showed different results in five areas in the supine position compared to outside of the mouth, it showed different results in only one area in the upright position (P < .05). @*CONCLUSION@#. In the difficult implant position for the operator to access, the implant stability measuring devices show less reliability. The accessibility of implant is greatly affected in the order of Osstell, Anycheck, and Periotest. [J Adv Prosthodont 2023;15:126-35]
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Objective@#To explore the differences of sensory manifestations between ASD children and typical development children, and to clarify the characteristics of sensory abnormalities in ASD and their relationship with various clinical symptoms, so as to provide scientific basis for early identification and specific intervention.@*Methods@#A total of 265 ASD children who received rehabilitation training in autism rehabilitation institutions in Heilongjiang Province were collected as the case group, and 223 typical development children in ordinary kindergartens and schools in Harbin were taken as the control group. Short Sensory Profile (SSP) was used to evaluate the difference of children s sensory perception level between the two groups, and Social Response Scale (SRS) and Autism Behavior Checklist (ABC) were used to evaluate the severity of symptoms including social disorder of autistic children. The correlation between SSP scores in ASD group and clinical scales was analyzed.@*Results@#The comparison of SSP scores between the two groups found that the median scores of all sensory dimensions in ASD group (tactile=33, taste/smell=18, motion sensitivity=13, Low response/sensation seeking=28, auditory filtering=19, low strength=22, visual/auditory=20) were lower than those of the healthy control group( Z =-2.73,-4.36,-3.17,-5.09,-11.00,-10.45,-3.43, P <0.05). The abnormal rate of multisensory score in children in ASD group was 55.1%, and that in control group was 21.2%, with significant difference( χ 2=57.15, P <0.05). Correlation analysis showed that SSP score in ASD group was negatively correlated with all dimensions of SRS, nonverbal communication, and social function of ADI-R scale, ADOS communication and social interaction, and total scores of ABC and CARS( P < 0.05 ).@*Conclusion@#Children with ASD have atypical sensory experiences, especially in auditory filtering dimension, and the level of atypical sensation is related to the severity of clinical symptoms of autism. In the future clinical diagnosis, treatment and research, it is necessary to strengthen the ability to recognize the sensory symptoms of children with ASD, so as to realize the early diagnosis and intervention.
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Objective@#To identify the functional connectivity characteristics of insula, sensory and social related brain regions in boys with autism spectrum disorder(ASD), to explore the central nervous basis of sensory abnormality affecting core symptoms in boys with ASD.@*Methods@#Resting state functional magnetic resonance imaging (rs fMRI) data were collected from 34 boys with ASD and 29 typical development boys (TD group). Based on functional connectivity analysis, the sensory related brain regions, insula, and social related brain regions were taken as regions of interest to calculate the functional connectivity (FC) level between the regions of interest, the differences between the two groups were compared and the results were corrected by FDR. The Autism Diagnostic Observation Schedule (ADOS), Childhood Autism Rating Scale (CARS) and Autism Spectrum Quotient-Children s Version (AQ-Child) were used to assess the core phenotypes of boys with ASD.@*Results@#Compared with the TD group, the levels of FC between tactile brain regions and insula, olfactory brain regions and insula, auditory brain regions and insula in boys with ASD group were significantly increased. The level of FC between the insula and bilateral amygdala，insula and the medial prefrontal cortex(mPFC) were significantly increased( P <0.05).Pearson correlation analysis showed that the level of FC between auditory brain region(BA42)and left insula in ASD group was negatively correlated with the scores of communication subscale of ADOS( r =-0.44)，social interaction subscale of ADOS( r =-0.43), communication & social interaction subscale of ADOS( r =-0.49),attention to details subscale of AQ-Child( r =-0.41). The level of FC between the right insula and right amygdala was positively correlated with the attention switch subscale of AQ-Child( r =0.38), the level of FC between right insula and mPFC was positively correlated with the scores of repetitive behavior subscale of ADOS( r =0.48), the attention switch subscale of AQ-Child( r =0.49), total scale subscale of AQ-Child( r =0.41), total scale of CARS( r =0.41)( P < 0.05 ).@*Conclusion@#The levels of FC between insula and sensory related, social related brain regions are abnormal in children with ASD, which have significant correlations with clinical symptoms. In depth studies can be conducted to explore underlying neutral mechanisms.
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@#Abstract: Objective To investigate the distribution and drug resistance characteristics of pathogenic bacteria in patients with neutropenic acute leukemia (AL) and bloodstream infections (BSI). Methods The clinical data of 258 neutropenic acute leukemia patients with bloodstream infections, who admitted to Shengjing Hospital of China Medical University from January 2016 to December 2021, were collected and analyzed for pathogenic bacteria and drug resistance. Results A total of 268 strains of pathogenic bacteria were isolated from 258 patients, including 180 strains of gram-negative bacteria (67.16%), 61 strains of gram-positive bacteria (22.76%), and 27 strains of fungi (10.07%). Gram-negative bacteria were mainly Klebsiella pneumoniae (53/268, 19.78%), Escherichia coli (49/268, 18.28%) and Pseudomonas aeruginosa (41/268, 15.30%). Gram-positive bacteria were mainly coagulase negative Staphylococcus (31/268, 11.57%) and Staphylococcus aureus(17/268, 6.34%). The main fungi were Candida tropicalis (25/268, 9.33%). Escherichia coli (33/268, 12.31%) was the most common pathogen isolated from acute myeloid leukemia (AML), followed by Pseudomonas aeruginosa (25/268, 9.33%), coagulase-negative Staphylococcus (18/268, 6.72%) and Candida tropicalis (18/268, 6.72%). Klebsiella pneumoniae (35/268, 13.06%) was the most common pathogen isolated from acute lymphoblastic leukemia (ALL),followed by Pseudomonas aeruginosa (15/268, 5.60%) and Escherichia coli (14/268, 5.22%). The resistance of Gram-negative bacteria to piperacillin/tazobactam, cefoperazone/sulbactam, imipenem, meropenem, ertapenem, amikacin, cefoxitin, amoxicillin/clavulanic acid was low. Gram-positive bacteria were sensitive to linezolid and vancomycin. Candida was sensitive to flucytosine, amphotericin B and itraconazole. Conclusions In patients with granulosa after AL chemotherapy combined with BSI, the pathogenic bacteria isolated from AML are diverse, and the pathogenic bacteria isolated from ALL are mainly gram-negative bacteria. Pathogenic bacteria have different degrees of drug resistance to commonly used antibacterial drugs, so it is important to strengthen the monitoring of the distribution of pathogenic bacteria and the change of drug resistance and rational use of antibacterial drugs to minimize the death of patients.