Association between personality traits and glycemic control after inpatient diabetes education

application/pdfAims The longitudinal effect of personality traits on glycemic control is unclear. This prospective observational study explored the relationship between personality traits and glycemic control in patients with uncontrolled diabetes after inpatient diabetes education. Methods Patients with diabetes mellitus （HbA1c ≥ 7.5%, measured by high-performance liquid chromatography） who received inpatient diabetes education were scored on the Big Five personality traits: neuroticism, extraversion, openness, agreeableness, and conscientiousness. Multiple linear analysis was used to determine whether any personality traits were independently associated with HbA1c on admission and HbA1c change from admission to 1, 3, and 6 months after discharge. Results One hundred seventeen participants （mean age 60.4 ± 14.5 years; 59.0% male） were enrolled. HbA1c values on admission and 1, 3, and 6 months after discharge were 10.2 ± 2.1%, 8.3 ± 1.4%, 7.6 ± 1.4%, and 7.7 ± 1.5%, respectively. Multiple linear analysis showed that no personality traits were associated with HbA1c on admission. Neuroticism was negatively associated with the HbA1c change from admission to 3 months （β = −0.192, P = 0.025） and 6 months after discharge （β = −0.164, P = 0.043）. Conclusions Neuroticism was associated with good long-term glycemic control after inpatient diabetes education

Impaired humoral immunity following COVID-19 vaccination in HTLV-1 carriers

Background Whether human T-lymphotropic virus type 1 (HTLV-1) carriers can develop sufficient humoral immunity after coronavirus disease 2019 (COVID-19) vaccination is unknown. Methods To investigate humoral immunity after COVID-19 vaccination in HTLV-1 carriers, a multicenter, prospective observational cohort study was conducted at five institutions in southwestern Japan, an endemic area for HTLV-1. HTLV-1 carriers and HTLV-1-negative controls were enrolled for this study from January to December 2022. During this period, the third dose of the COVID-19 vaccine was actively administered. HTLV-1 carriers were enrolled during outpatient visits, while HTLV-1-negative controls included health care workers and patients treated by participating institutions for diabetes, hypertension, or dyslipidemia. The main outcome was the effect of HTLV-1 infection on the plasma anti-COVID-19 spike IgG (IgG-S) titers after the third dose, assessed by multivariate linear regression with other clinical factors. Results We analyzed 181 cases (90 HTLV-1 carriers, 91 HTLV-1-negative controls) after receiving the third dose. HTLV-1 carriers were older (median age 67.0 vs. 45.0 years, p < 0.001) and more frequently had diabetes, hypertension, or dyslipidemia than did HTLV-1-negative controls (60.0% vs. 27.5%, p < 0.001). After the third dose, the IgG-S titers decreased over time in both carriers and controls. Multivariate linear regression in the entire cohort showed that time since the third dose, age, and HTLV-1 infection negatively influenced IgG-S titers. After adjusting for confounders such as age, or presence of diabetes, hypertension, or dyslipidemia between carriers and controls using the overlap weighting propensity score method, and performing weighted regression analysis in the entire cohort, both time since the third dose and HTLV-1 infection negatively influenced IgG-S titers. Conclusions The humoral immunity after the third vaccination dose is impaired in HTLV-1 carriers; thus, customized vaccination schedules may be necessary for them.Citation: Takuro Kameda, Atae Utsunomiya, Nobuaki Otsuka, Yoko Kubuki, Taisuke Uchida, Kotaro Shide, Ayako Kamiunten, Nobuaki Nakano, Masahito Tokunaga, Takayoshi Miyazono, Yoshikiyo Ito, Kentaro Yonekura, Toshiro Kawakita, Keiichi Akizuki, Yuki Tahira, Masayoshi Karasawa, Tomonori Hidaka, Ayaka Konagata, Norifumi Taniguchi, Yuma Nagatomo, Fumiko Kogo, Koichiro Shimizu, Hiroaki Ueno, Junzo Ishizaki, Naoya Takahashi, Yoshihiko Ikei, Michihiro Hidaka, Hideki Yamaguchi, Kazuya Shimoda, Impaired humoral immunity following COVID-19 vaccination in HTLV-1 carriers. BMC Infectious Diseases. 2024-01-17, 24(1), https://doi.org/10.1186/s12879-024-09001-

A Computer Software Program for Specifying Water Sampling Sites using Lan

departmental bulletin pape

Observation of B± → pp̅K±

journal articl

New Solvents for Cellulose. II. Ethylenediamine/Thiocyanate Salt System

The ethylenediamine/thiocyanate salt system was found to be a new solvent for cellulose. The solubility, dissolution behavior, solution properties, and cellulose recovered from the solutions were investigated. The dissolution took place at room temperature, and the maximum solubility achieved was 16％ (w/w) for cellulose of DP210 in the ethylenediamine/sodium thiocyanate 54/46 (w/w).The dependence of cellulose solubility on DP is also described. Tracing the dissolution behavior of the cellulose by CP/MAS ^CNMR measurements revealed the polymorphic conversion of cellulose l to III to amorphous structure during the dissolution process. The cellulose dissolved was stable for 30 days storage at room temperature. Microscopic observations and steady-shear viscosity measurements of the solutions indicated mesophase formation of cellulose in the ethylenediamine/sodium thiocyanate system. This anisotrpoic phase appeared from ca.10％ (w/w) cellulose with DP210 and greatly depended on the cellulose concentrations. Coagulation studies disclosed that cellulose II and amorphous cellulose were recovered from the cellulose/ethylenediamine/thiocyanate salt solutions when water and alcohol were used as a coagulant, respectively. It was suggested that this solvent system has high potential for cellulosic fiber and film formations.application/pdfjournal articl

Normalized metagenome comparison of 3000 m-deep Mediterranean Km3 and Pacific ALOHA water column.

<p>For normalization, a total of 6,853 sequences (size of the smallest library compared, ALOHA 130 m) from each library were randomly selected and compared. A, Neighbour joining analysis of fosmid-end sequences in Km3 and different depths in ALOHA. Temperature, salinity, and the total number of sequences available for each library are shown on the right; Jackknife values, at nodes. B, Normalized MUMmer plots showing the number of maximal unique matches (MUMs) shared by the 3000 m deep Km3 and the different ALOHA metagenomic libraries. MUMs are distributed as a function of their identity (ordinates) and the type of COG to which they belong (abscises). Average identity values are indicated for each pair of libraries compared. The number of MUMs having more that 80% identity are given to the right of each panel.</p

Comparison of COG distribution of fosmid-ends in Km3 and ALOHA water column.

<p>Fosmid-ends were classified according to the COG database both Km3 and ALOHA <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0000914#pone.0000914-DeLong2" target="_blank">[14]</a> datasets were analyzed (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0000914#s4" target="_blank">methods</a>).</p

ALOHA and Km3 oceanographic data.

<p>Values shown are those from the same CTD casts as the samples (DeLong <i>et al.</i> 2006 and this work). *Archival data are from ALOHA HOT-DOGS© database (<a href="http://hahana.soest.hawaii.edu/hot/hot-dogs/" target="_blank">http://hahana.soest.hawaii.edu/hot/hot-dogs/</a>) or in the case of Km3 from the ICES oceanographic database (<a href="http://www.ices.dk/ocean" target="_blank">http://www.ices.dk/ocean</a>) and correspond to several datasets collected at the depth and approximate location (less than 50 NM away) as the samples. Values in parentheses are the average value±standard deviation. Abbreviations are Temp, Temperature; Chl, chlorophyll; DOC, dissolved organic carbon; DIP, dissolved inorganic phosphate; N+N, nitrate plus nitrite; SLCA, silicate; HPP, heterotrophic picoplankton (DAPI counts); POC, particulate organic carbon.</p

Distribution of Km3 fosmid-ends in KEGG categories.

<p>A, Detailed KEGG categories. B, Major KEGG categories and classification by type of substrate of Km3 fosmid-ends identified as transporters. * Other transporters.</p

Prokaryotic taxa identified in Km3 3,000 m-deep plankton inferred from fosmid-ends and 16S rRNA detection in environmental and metagenomic libraries.

<p>Relative abundances of PCR-amplified 16S rRNA genes in environmental libraries are from Ref.4. For bacteria in the Km3 metagenomic library (central panel), only 16S rRNA genes whose adjacent ITS can be distinguished in size from that of <i>E. coli</i> were detected.</p