Diffusion and activation of n-type dopants in germanium

The diffusion and activation of $n$-type impurities (P and As) implanted into $p$-type Ge(100) substrates were examined under various dose and annealing conditions. The secondary ion mass spectrometry profiles of chemical concentrations indicated the existence of a sufficiently high number of impurities with increasing implanted doses. However, spreading resistance probe profiles of electrical concentrations showed electrical concentration saturation in spite of increasing doses and indicated poor activation of As relative to P in Ge. The relationships between the chemical and electrical concentrations of P in Ge and Si were calculated, taking into account the effect of incomplete ionization. The results indicated that the activation of P was almost the same in Ge and Si. The activation ratios obtained experimentally were similar to the calculated values, implying insufficient degeneration of Ge. The profiles of P in Ge substrates with and without damage generated by Ge ion implantation were compared, and it was clarified that the damage that may compensate the activated $n$-type dopants has no relationship with the activation of P in Ge.Comment: 6 pages, 4 figure

Pancreatic colonization of fungi in the development of severe acute pancreatitis

Acute pancreatitis is a common emergent disorder, a significant population of which develops the life-threatening condition, called severe acute pancreatitis (SAP). It is generally accepted that bacterial infection is associated with the development and persistence of SAP. In addition to bacterial infection, recent clinical studies disclosed a high incidence of fungal infection in patients with SAP. Moreover, SAP patients with fungal infection exhibit a higher mortality rate than those without infection. Although these clinical studies support pathogenic roles played by fungal infection in SAP, beneficial effects of prophylactic anti-fungal therapy on SAP have not been proved. Here we summarize recent clinical findings as to the relationship between fungal infection and the development of SAP. In addition, we discuss molecular mechanisms accounting for the development of SAP in the presence of fungal infection

Bispectral index-guided propofol sedation during endoscopic ultrasonography

Background/Aims Bispectral index (BIS) monitors process and display electroencephalographic data are used to assess the depth of anesthesia. This study retrospectively evaluated the usefulness of BIS monitoring during endoscopic ultrasonography (EUS). Methods This study included 725 consecutive patients who underwent EUS under sedation with propofol. BIS monitoring was used in 364 patients and was not used in 361. The following parameters were evaluated: (1) median dose of propofol; (2) respiratory and circulatory depression; (3) occurrence of body movements; (4) awakening score >8 at the time; and (5) awakening score 2 hours after leaving the endoscopy room. Results The BIS group received a significantly lower median dose of propofol than the non-BIS group (159.2 mg vs. 167.5 mg; p=0.015) in all age groups. For patients aged ≥75 years, the reduction in heart rate was significantly lower in the BIS group than in the non-BIS group (1.2% vs. 9.1%; p=0.023). Moreover, the occurrence of body movements was markedly lower in the BIS group than in the non-BIS group (8.5% vs. 39.4%; p<0.001). Conclusions During EUS examination, BIS monitoring is useful for maintaining a constant depth of anesthesia, especially in patients 75 years of age or older

Amelioration of Acute Kidney Injury in Lipopolysaccharide-Induced Systemic Inflammatory Response Syndrome by an Aldose Reductase Inhibitor, Fidarestat

Systemic inflammatory response syndrome is a fatal disease because of multiple organ failure. Acute kidney injury is a serious complication of systemic inflammatory response syndrome and its genesis is still unclear posing a difficulty for an effective treatment. Aldose reductase (AR) inhibitor is recently found to suppress lipopolysaccharide (LPS)-induced cardiac failure and its lethality. We studied the effects of AR inhibitor on LPS-induced acute kidney injury and its mechanism.Mice were injected with LPS and the effects of AR inhibitor (Fidarestat 32 mg/kg) before or after LPS injection were examined for the mortality, severity of renal failure and kidney pathology. Serum concentrations of cytokines (interleukin-1β, interleukin-6, monocyte chemotactic protein-1 and tumor necrosis factor-α) and their mRNA expressions in the lung, liver, spleen and kidney were measured. We also evaluated polyol metabolites in the kidney.Mortality rate within 72 hours was significantly less in LPS-injected mice treated with AR inhibitor both before (29%) and after LPS injection (40%) than untreated mice (90%). LPS-injected mice showed marked increases in blood urea nitrogen, creatinine and cytokines, and AR inhibitor treatment suppressed the changes. LPS-induced acute kidney injury was associated with vacuolar degeneration and apoptosis of renal tubular cells as well as infiltration of neutrophils and macrophages. With improvement of such pathological findings, AR inhibitor treatment suppressed the elevation of cytokine mRNA levels in multiple organs and renal sorbitol accumulation.AR inhibitor treatment ameliorated LPS-induced acute kidney injury, resulting in the lowered mortality

The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force

「コロナ制圧タスクフォース」COVID-19患者由来の血液細胞における遺伝子発現の網羅的解析 --重症度に応じた遺伝子発現の変化には、ヒトゲノム配列の個人差が影響する--. 京都大学プレスリリース. 2022-08-23.Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection

DOCK2 is involved in the host genetics and biology of severe COVID-19

「コロナ制圧タスクフォース」COVID-19疾患感受性遺伝子DOCK2の重症化機序を解明 --アジア最大のバイオレポジトリーでCOVID-19の治療標的を発見--. 京都大学プレスリリース. 2022-08-10.Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge. Here we conducted a genome-wide association study (GWAS) involving 2, 393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3, 289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target

Classifying Microscopic Images of Reactive Lymphocytosis Using Two-Step Tandem AI Models

The practical applications of automatic recognition and categorization technology for next-generation systems are desired in the clinical laboratory. We approached the identification of reactive lymphocytosis using artificial intelligence (AI) technology and studied its clinical usefulness for blood smear screening. This study created one- and two-step AI models for the identification of reactive lymphocytosis. The ResNet-101 model was applied for deep learning. The original image set for supervised AI training consisted of 5765 typical nucleated blood cell images. The subjects for clinical assessment were 25 healthy cases, 25 erythroblast cases, and 25 reactive lymphocytosis cases. The total accuracy (mean ± standard deviation) of the one- and two-step models were 0.971 ± 0.047 and 0.977 ± 0.024 in healthy, 0.938 ± 0.040 and 0.978 ± 0.018 in erythroblast, and 0.856 ± 0.056 and 0.863 ± 0.069 in reactive lymphocytosis cases, respectively. The two-step AI model showed a sensitivity of 0.960 and a specificity of 1.000 between healthy and reactive lymphocytosis cases. As our two-step tandem AI model showed high performance for identifying reactive lymphocytosis in blood smear screening, we plan to apply this method to the development of AI models to differentiate reactive and neoplastic lymphocytosis