Streptococcus pneumoniae (Spn) is the most common etiology of bacterial pneumonia, which is one of the leading causes of death in children and the elderly worldwide. During non-lethal infections with Spn, immune cells accumulate in the lungs and protect against reinfection with more lethal strains, this protection is termed heterotypic immunity. Lymphocyte populations such as resident memory T cells and resident memory B cells are known to be crucial for heterotypic immunity, but their diversity remains understudied. Here, we aimed to elucidate resident lymphocyte heterogeneity in the lungs after recovery from pneumococcal pneumonia, and their contributions to heterotypic immune protection. We developed a comprehensive immunophenotyping panel for full-spectrum flow cytometry (FSFC) to identify novel subsets of lymphocytes and combined it with an unbiased analysis approach. With this tool we discovered that murine lungs were enriched for unexpected subsets of resident lymphocytes, and we defined CD73 as a potential lymphocyte residence marker. We discovered a novel subset of CD4+ T cells defined by the phenotype CD11a+CD69+GL7+, which corresponded to a significant proportion of lung CD4+ TRM cells. Initial analyses demonstrated GL7+ T cells resembled CD4+ TRM cells. Functional studies revealed that unlike GL7- TRM subsets that were mostly RORT+, GL7+ TRM cells were also Gata-3+ and/or T-bet+ could secrete type 2 or type 1 cytokines, suggesting they were poised to be TH2 or TH1-like in function. This study emphasizes the use of a multiparameter panel for FSFC as tool to identify novel lymphocyte subsets. We conclude that the environment of pneumonia-recovered lungs contains heterogeneous subsets of resident lymphocytes, including GL7+ TRM cells. We propose these subsets may contribute to lung immunity in unique ways and may be important players in serotype-independent protection to pneumococcal pneumonia. / 2024-01-23T00:00:00Z

No description available.

No description available.

<p> A linear state space model (LSSM) of cardiovascular regulation in ten normal human volunteers is developed using instantaneous lung volume (IL V), heart rate (HR.), pulse pressure (PP) and mean arterial blood pressure (MBP) time series. Closed-loop transfer functions are computed and physiologically interpreted and the sensitivity of the transfer functions is assessed by comparison of supine and standing experimental results. The zeros ofthe transfer functions are used to infer the causality relationship between HR and PP. Results (1) In the supine condition, changes in ILV cause changes in HR within 0.5 s, followed shortly (0.3 -0.5 s) by changes in PP and finally changes in MBP 1 -2 slater. (2) When standing, changes in MBP occur concurrent with changes in PP. (3) MBP changes are dominated by blood pooling effects when standing. ( 4) Group delay is less affected than the magnitude by the physiological differences between the supine and standing conditions. (5) The relationship between HR and PP is neither completely causal nor anti-causal, but rather a combination of the two. (6) The minimum system delays are coincident with breathing frequencies between 0.2 -0.4 Hz. Conclusions Closed-loop LSSM and transfer function analysis may be used to infer the time delays and causality of the closed-loop system response. The classical model of RSA generation is supported by the LS SM results. </p> / Thesis / Master of Engineering (MEngr)

Diss. (sammanfattning) Stockholm : Karol. inst., 2004. / Härtill 4 uppsatser.

The aim of this thesis is a data transfer protocol implementation for a mobile control unit for transporting lungs. Apart from this thesis the data transfer protocol is used in AlveoPic project. The introductory part is focused on an anatomical and physiological background of a human respiratory system. Consequently it describes the i-Lung module and the mobile circulation module (MCM). It deals with the healthcare informatics interoperability standards with an emphasis to the ISO/IEEE 11073 standard. The subsequent part is represented by MCM’s simulator realization and design of a monitoring application. The final part aims at an analysis of the test cases for a monitoring application’s and a protocol framework’s control.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第25189号 / 医博第5075号 / 新制||医||1072(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 平井 豊博, 教授 江木 盛時, 教授 後藤 慎平 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

The initial stage of a lung examination involves the segmentation of a CT image, a process that has been put under a lot of pressure with the high demand for chest scans and accurate segmentations. Current automatic segmentation algorithms are either non-robust for different datasets, not easily accessible, or time-consuming. Furthermore, classification of lung diseases such as IPF and NSIP is a difficult task often requiring decision-making between pathologists, radiologists and clinicians to make an accurate prognosis.  Therefore, this thesis aims to create two algorithms easily accessible through a common medical software, 3D Slicer, with simple user interfaces for more efficient lung analysis. The first one is a fully automatic segmentation algorithm with a manual adjustment option. It is robust and developed on a diverse dataset, demonstrating a high accuracy with a median Dice score of0,967. The second one is a lung vessel tree morphometry algorithm which computes various parameters correlated to the vessel tree and its structure, providing insight into morphological changes. It shows great usability but has certain limitations, making it not entirely finished for clinical research but acts as an excellent starting point for a future project. The segmentation algorithm was developed using classical image processing techniques making it comprehensible. The distinctive feature of this algorithm is the entropy map used, enabling an effective way in distinguishing between the fibrotic regions of the lungs with surrounding soft tissue and therefore increasing its applicability on lungs with various diseases. The lung vessel tree morphometry algorithm utilized a segmentation of the lung vessels to organize them into a tree-like structure. The structure was divided into branches where each branch was used to calculate different parameters such as its level within the tree hierarchy, the length of the branch and more. These parameters were displayed and color-coded for further analysis. The obtained result underscores the substantial potential and importance of these developed algorithms for clinical research by providing user-friendly, robust and reliable methods. / Det inledande skedet av en lungundersökning involverar segmenteringen av en CT-bild, en process som har satts under mycket press på grund utav den höga efterfrågan på bröstskanningar och noggrann segmentering. Aktuella automatiska segmenteringsalgoritmer är antingen icke-robusta för olika dataset, ej lättillgängliga eller tidskrävande. Dessutom är klassificering av lungsjukdomar som IPF och NSIP en svår uppgift som ofta kräver beslutsfattande mellan patologer, radiologer och kliniker för att göra en korrekt prognos. Därför syftar denna rapport till att skapa två lättillgängliga algoritmer genom en ofta användmedicinsk programvara, 3D Slicer, bestående utav enkla användargränssnitt för en effektivare analys av lungorna. Den första är en helautomatisk segmenteringsalgoritm med ett manuellt justeringsalternativ. Den är robust och utvecklad på ett mångsidigt dataset som har demonstrerat en hög noggrannhet med en median Dice-score på 0,967. Den andra är en morfometri algoritm för lungkärlsträd som beräknar olika parametrar korrelerade till kärlträdet och dess struktur, vilket ger insikt i morfologiska förändringar. Den visar stor användbarhet men innehåller begränsningar, vilket gör den ej helt färdig för klinisk forskning utan fungerar som en utmärkt utgångspunkt för framtida arbete. Segmenteringsalgoritmen utvecklades med hjälp av klassiska bildbehandlingsmetoder vilket gör den mer lättförstådd. Det utmärkande för denna algoritm är entropikartan som används, vilket möjliggör ett effektivt sätt att skilja mellan de fibrotiska regionerna i lungorna med omgivande mjukdelar, detta gör den mer användbar på lungor med olika sjukdomar. Algoritmen för lungkärlsträdets morfometri använde en segmentering av lungkärlen för att sedanorganiseras i en trädliknande struktur. Strukturen var uppdelad i grenar där varje gren användes för att beräkna olika parametrar såsom dess nivå inom trädhierarkin, grenens längd med mera. Dessutom uppvisades dessa parametrar och färgkodades för vidare analys. Det erhållna resultatet understryker den substantiella potential och betydelse som dessa utvecklade algoritmer kommer att ha i klinisk forskning genom att tillhandahålla användarvänliga, robusta och pålitliga metoder

The purpose of this thesis was to evaluate and compare the peripheral dose associated with VMAT lung SABR treatments for 10X, 6X, and 10X-FFF beams. Flattening Filter Free (FFF) radiotherapy photon beams exhibit high dose rates as compared to standard flattened photon beams. The high dose rates available with FFF beams make them ideal for high dose treatments, such as Volumetric Modulated Arc Therapy (VMAT)-delivery lung Stereotactic Ablative Radiotherapy (SABR), where treatment delivery is longer than that of standard treatments. They are also known to show reductions in treatment head scatter, multi-leaf collimator (MLC) transmission and treatment head leakage radiation, compared to flattened beams. The use of FFF beams for VMAT lung SABR has been shown to significantly reduce treatment delivery time, while maintaining plan quality and accuracy. Another potential advantage of the use of FFF beams for VMAT lung SABR is the reduction in peripheral (out-of-field) dose, due mainly to the reduction in head scatter and treatment head leakage. The peripheral doses delivered by VMAT Lung SABR treatments using 10X-FFF, 10X and 6X were investigated for the Varian TrueBeam medical linear accelerator. There were three components to this investigation; (1) Ion chamber measurement of peripheral dose for static open, static MLC and dynamic MLC fields, (2) Validation of Monte Carlo, Acuros XB and AAA algorithms for peripheral dose prediction, and (3) Evaluation of peripheral doses for VMAT lung SABR treatments using the validated Monte Carlo model. Measurements of out-of field doses for static open, static MLC and dynamic MLC fields showed that 10X-FFF delivered peripheral doses in the range of 30% to 50%, 3% to 40% and 5% to 20% lower than the peripheral doses for flattened beams. Dose calculation algorithm validation showed that AAA and Acuros XB significantly under predicted the dose in the peripheral region. Monte Carlo was found to be the most accurate dose calculation algorithm for peripheral dose prediction. The VMAT lung SABR dose distributions were calculated for both static gantry delivery and arc delivery using the validated Monte Carlo model. For static gantry Monte Carlo simulation, 10X-FFF was found to show a reduction in peripheral dose in the range of 7% to 21% and 7% to 17% when compared to 6X and 10X. For arc delivery Monte Carlo simulation, 10X-FFF was found to deliver a statistically significant reduction in mean peripheral dose compared to 6X in four of the six cases, and was not found to deliver a statistically significant reduction in mean peripheral dose compared to 10X in any of the six cases. For this type of VMAT lung SABR treatment, 10X-FFF offers a reduction in peripheral dose over 6X. In terms of the benefits of using 10X-FFF for this type of treatment, the reduction in peripheral dose is added to the already-established reduction in treatment times. / Graduate / 0756 / 0574

BACKGROUND: Carfilzomib (CFZ) is a proteasome inhibitor that selectively and irreversibly binds to its target and has been approved in the US for treatment of relapsed and refractory multiple myeloma. Phase 1B studies of CFZ reported signals of clinical activity in solid tumors, including small cell lung cancer (SCLC). The aim of this study was to investigate the activity of CFZ in lung cancer models. METHODS: A diverse panel of human lung cancer cell lines and a SHP77 small cell lung cancer xenograft model were used to investigate the anti-tumor activity of CFZ. RESULTS: CFZ treatment inhibited both the constitutive proteasome and the immunoproteasome in lung cancer cell lines. CFZ had marked anti-proliferative activity in A549, H1993, H520, H460, and H1299 non-small cell lung cancer (NSCLC) cell lines, with IC₅₀ values after 96 hour exposure from <1.0 nM to 36 nM. CFZ had more variable effects in the SHP77 and DMS114 SCLC cell lines, with IC₅₀ values at 96 hours from <1 nM to 203 nM. Western blot analysis of CFZ-treated H1993 and SHP77 cells showed cleavage of poly ADP ribose polymerase (PARP) and caspase-3, indicative of apoptosis, and induction of microtubule-associated protein-1 light chain-3B (LC3B), indicative of autophagy. In SHP77 flank xenograft tumors, CFZ monotherapy inhibited tumor growth and prolonged survival, while no additive or synergistic anti-tumor efficacy was observed for CFZ + cisplatin (CDDP). CONCLUSIONS: CFZ demonstrated anti-proliferative activity in lung cancer cell lines in vitro and resulted in a significant survival advantage in mice with SHP77 SCLC xenografts, supporting further pre-clinical and clinical investigations of CFZ in NSCLC and SCLC.