Throat microbiota drives alterations in pulmonary alveolar microbiota in patients with septic ARDS.

OBJECTIVES: The translocation of intestinal flora has been linked to the colonization of diverse and heavy lower respiratory flora in patients with septic ARDS, and is considered a critical prognostic factor for patients. METHODS: On the first and third days of ICU admission, BALF, throat swab, and anal swab were collected, resulting in a total of 288 samples. These samples were analyzed using 16S rRNA analysis and the traceability analysis of new generation technology. RESULTS: On the first day, among the top five microbiota species in abundance, four species were found to be identical in BALF and throat samples. Similarly, on the third day, three microbiota species were found to be identical in abundance in both BALF and throat samples. On the first day, 85.16% of microorganisms originated from the throat, 5.79% from the intestines, and 9.05% were unknown. On the third day, 83.52% of microorganisms came from the throat, 4.67% from the intestines, and 11.81% were unknown. Additionally, when regrouping the 46 patients, the results revealed a significant predominance of throat microorganisms in BALF on both the first and third day. Furthermore, as the disease progressed, the proportion of intestinal flora in BALF increased in patients with enterogenic ARDS. CONCLUSIONS: In patients with septic ARDS, the main source of lung microbiota is primarily from the throat. Furthermore, the dynamic trend of the microbiota on the first and third day is essentially consistent.It is important to note that the origin of the intestinal flora does not exclude the possibility of its origin from the throat.

Reduced Viral Shedding Time in High-Risk COVID-19 Patients Infected by Omicron and Treated with Paxlovid: A Real-World Study from China.

Introduction: The purpose of this study was to compare the viral shedding time in patients infected with the Omicron variant during Paxlovid therapy and conventional therapy and to analyze the effects of Paxlovid on patients infected with COVID-19. Methods: In this study, the demographic and clinical characteristics and laboratory data of 3159 patients infected with the SARS-CoV-2 Omicron variant treated at Jilin Province People's Hospital were collected and analyzed. A total of 362 patients received Paxlovid therapy, and 2797 patients received conventional therapy. After propensity score matching (PSM), 1086 patients were obtained. Results: The difference in platelet (PLT) count between the two groups was statistically significant but within the normal range (P < 0.05). CT value revealed that the nucleic acid test results became negative more quickly in the Paxlovid therapy group. Analysis of the Paxlovid therapy group showed that IgG and IgM levels were increased after Paxlovid therapy administration. Conclusion: The CT value of the Paxlovid therapy group became negative more quickly. This finding suggests that Paxlovid treatment after early diagnosis of the Omicron variant may achieve good therapeutic efficacy.

Combined metabolomic and proteomic analysis of sepsis related acute liver injury and its pathogenesis research.

BACKGROUND: Sepsis-induced acute liver injury is common in patients in intensive care units. However, the exact mechanism of this condition remains unclear. The purpose of this study was to investigate the roles and mechanisms of proteins and metabolites in the liver tissue of mice after sepsis and elucidate the molecular biological mechanisms of sepsis-related liver injury. METHODS: First, a lipopolysaccharide (LPS)-induced sepsis mouse model was established. Then, according to alanine aminotransferase (ALT) and aspartate aminotransferase (AST) detection in mouse serum and liver histopathological examination (HE) staining, the septic mice were divided into two groups: acute liver injury after sepsis and nonacute liver injury after sepsis. Metabolomics and proteomic analyses were performed on the liver tissues of the two groups of mice to identify significantly different metabolites and proteins. The metabolomics and proteomics results were further analysed to identify the biological indicators and pathogenesis related to the occurrence and development of sepsis-related acute liver injury at the protein and metabolite levels. RESULTS: A total of 14 differentially expressed proteins and 46 differentially expressed metabolites were identified. Recombinant Erythrocyte Membrane Protein Band 4.2 (Epb42) and adenosine diphosphate (ADP) may be the key proteins and metabolites responsible for sepsis-related acute liver injury, according to the correlation analysis of proteomics and metabolomics. The expression of the differential protein Epb42 was further verified by western blot (WB) detection. CONCLUSIONS: Our study suggests that the differential protein Epb42 may be key proteins causing sepsis-associated acute liver injury, providing new and valuable information on the possible mechanism of sepsis-associated acute liver injury.

Effect of early serum phosphate disorder on in-hospital and 28-day mortality in sepsis patients: a retrospective study based on MIMIC-IV database.

BACKGROUND: This study aims to assess the influence of early serum phosphate fluctuation on the short-term prognosis of sepsis patients. METHODS: This retrospective study used the Medical Information Mart for Intensive Care IV database to analyze serum phosphate levels in sepsis patients within 3 days of ICU admission. According to the absolute value of delta serum phosphate (the maximum value minus the minimum value of serum phosphorus measured within three days), the patients were divided into four groups, 0-1.3, 1.4-2.0, 2.1-3.1, and ≥ 3.2 mg/dl. Meanwhile, the direction of delta serum phosphate was compared. With the serum phosphate change group of 0-1.3 mg/dl as the reference group, the relationship between delta serum phosphate and in-hospital mortality and 28-day mortality was analyzed by multivariate Logistics regression analysis. RESULTS: The study involved 1375 sepsis patients. Serum phosphate changes (0-1.3, 1.4-2.0, 2.1-3.1, and ≥ 3.2 mg/dl) correlated with in-hospital and 28-day mortality variations (p = 0.005, p = 0.008). Much higher serum phosphate fluctuation elevated in-hospital and 28-day mortality. Compared to the 0-1.3 mg/dl change group, adjusted odds ratios (OR) in other groups for in-hospital mortality were 1.25 (0.86-1.81), 1.28 (0.88-1.86), and 1.63 (1.10-2.43), and for 28-day mortality were 1.21 (0.86-1.72), 1.10 (0.77-1.57), and 1.49 (1.03-2.19). Under the trend of increasing serum phosphate, the ORs of in-hospital mortality and 28-day mortality in ≥ 3.2 mg/dl group were 2.52 and 2.01, respectively. CONCLUSION: In conclude, the delta serum phosphate ≥ 3.2 mg/dl was associated with in-hospital mortality and 28-day mortality in patients with sepsis.

Gut microbiota composition and changes in patients with sepsis: potential markers for predicting survival.

BACKGROUND: Sepsis can cause immune dysregulation and multiple organ failure in patients and eventually lead to death. The gut microbiota has demonstrated its precise therapeutic potential in the treatment of various diseases. This study aimed to discuss the structural changes of the gut microbiota in patients with sepsis and to analyze the differences in the gut microbiota of patients with different prognoses. METHODS: We conducted a multicenter study in which rectal swab specimens were collected on the first and third days of sepsis diagnosis. A total of 70 specimens were collected, and gut microbiota information was obtained by 16S rRNA analysis. RESULTS: The relative abundance of Enterococcus decreased in rectal swab specimens during the first three days of diagnosis in patients with sepsis, while the relative abundance of inflammation-associated Bacillus species such as Escherichia coli, Enterobacteriaceae, and Bacteroidetes increased. By comparing the differences in the flora of the survival group and the death group, we found that the abundance of Veillonella and Ruminococcus in the death group showed an increasing trend (p < 0.05), while the abundance of Prevotella_6 and Prevotella_sp_S4_BM14 was increased in surviving patients (p < 0.05). CONCLUSIONS: The Firmicutes/Bacteroidetes ratio, reflecting overall gut microbial composition, was significantly lower on day three of sepsis diagnosis. Changes in the abundance of specific gut microbiota may serve as prognostic markers in patients with sepsis.

Deep learning-based projection synthesis for low-dose cone-beam computed tomography imaging in image-guided radiotherapy.

Background: The imaging dose of cone-beam computed tomography (CBCT) in image-guided radiotherapy (IGRT) poses adverse effects on patient health. To improve the quality of sparse-view low-dose CBCT images, a projection synthesis convolutional neural network (SynCNN) model is proposed. Methods: Included in this retrospective, single-center study were 223 patients diagnosed with brain tumours from Beijing Cancer Hospital. The proposed SynCNN model estimated two pairs of orthogonally direction-separable spatial kernels to synthesize the missing projection in between the input neighboring sparse-view projections via local convolution operations. The SynCNN model was trained on 150 real patients to learn patterns for inter-view projection synthesis. CBCT data from 30 real patients were used to validate the SynCNN, while data from a phantom and 43 real patients were used to test the SynCNN externally. Sparse-view projection datasets with 1/2, 1/4, and 1/8 of the original sampling rate were simulated, and the corresponding full-view projection datasets were restored using the SynCNN model. The tomographic images were then reconstructed with the Feldkamp-Davis-Kress algorithm. The root-mean-square error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) metrics were measured in both the projection and image domains. Five experts were invited to grade the image quality blindly for 40 randomly selected evaluation groups with a four-level rubric, where a score greater than or equal to 2 was considered acceptable image quality. The running time of the SynCNN model was recorded. The SynCNN model was directly compared with the three other methods on 1/4 sparse-view reconstructions. Results: The phantom and patient studies showed that the missing projections were accurately synthesized. In the image domain, for the phantom study, compared with images reconstructed from sparse-view projections, images with SynCNN synthesis exhibited significantly improved qualities with decreased values in RMSE and increased values in PSNR and SSIM. For the patient study, between the results with and without the SynCNN synthesis, the averaged RMSE decreased by 3.4×10-4, 10.3×10-4, and 21.7×10-4, the averaged PSNR increased by 3.4, 6.6, and 9.4 dB, and the averaged SSIM increased by 5.2×10-2, 18.9×10-2 and 33.9×10-2, for the 1/2, 1/4, and 1/8 sparse-view reconstructions, respectively. In expert subjective evaluation, both the median scores and acceptance rates of the images with SynCNN synthesis were higher than those reconstructed from sparse-view projections. It took the model less than 0.01 s to synthesize an inter-view projection. Compared with the three other methods, the SynCNN model obtained the best scores in terms of the three metrics in both domains. Conclusions: The proposed SynCNN model effectively improves the quality of sparse-view CBCT images at a low time cost. With the SynCNN model, the CBCT imaging dose in IGRT could be reduced potentially.

Causal relationship between gut Prevotellaceae and risk of sepsis: a two-sample Mendelian randomization and clinical retrospective study in the framework of predictive, preventive, and personalized medicine.

Objective: Gut microbiota is closely related to sepsis. Recent studies have suggested that Prevotellaceae could be associated with intestinal inflammation; however, the causal relationship between Prevotellaceae and sepsis remains uncertain. From the perspective of predictive, preventive, and personalized medicine (PPPM), exploring the causal relationship between gut Prevotellaceae and sepsis could provide opportunity for targeted prevention and personalized treatment. Methods: The genome-wide association study (GWAS) summary-level data of Prevotellaceae (N = 7738) and sepsis were obtained from the Dutch Microbiome Project and the UK Biobank (sepsis, 1380 cases; 429,985 controls). MR analysis was conducted to estimate the associations between Prevotellaceae and sepsis risk. The 16S rRNA sequencing analysis was conducted to calculate the relative abundance of Prevotellaceae in sepsis patients to explore the relationship between Prevotellaceae relative abundance and the 28-day mortality. Results: Genetic liability to f__Prevotellaceae (OR, 1.91; CI, 1.35-2.71; p = 0.0003) was associated with a high risk of sepsis with inverse-variance weighted (IVW). The median Prevotellaceae relative abundance in non-survivors was significantly higher than in survivors (2.34% vs 0.17%, p < 0.001). Multivariate analysis confirmed that Prevotellaceae relative abundance (OR, 1.10; CI, 1.03-1.22; p = 0.027) was an independent factor of 28-day mortality in sepsis patients. ROC curve analysis indicated that Prevotellaceae relative abundance (AUC: 0.787, 95% CI: 0.671-0.902, p = 0.0003) could predict the prognosis of sepsis patients. Conclusion: Our results revealed that Prevotellaceae was causally associated with sepsis and affected the prognosis of sepsis patients. These findings may provide insights to clinicians on developing improved sepsis PPPM strategies. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-023-00340-6.

Gut microbiota disruption during sepsis and the influence of innate metabolites on sepsis prognosis / Alteración de la microbiota intestinal durante la sepsis y influencia de los metabolitos innatos en el pronóstico de la sepsis

Sepsis causes high mortality in intensive care units. Although there have been many studies on the gut microbiota in patients with sepsis, the impact of sepsis on the gut microbiota has not been directly determined because the treatment of sepsis also affects the gut microbiota. Therefore, we designed this animal experiment to explore gut microbiota alterations during sepsis. Mice were divided into two groups, mice that survived less than 3 days and mice that survived more than 3 days. Fecal samples collected on the day of cecal ligation and puncture (CLP), as well as on the 3rd and 7th days after CLP, were subjected to microbial community analysis and nontargeted metabolomics analysis. The results showed significantly lower bacterial diversity in fecal samples after CLP. At the genus level, the fecal samples obtained on the 3rd and 7th days after CLP exhibited significantly increased relative abundances of Bacteroides, Helicobacter, etc., and significantly decreased relative abundances of Alloprevotella, Prevotella, etc. Innate metabolite levels were significantly different in mice that survived less than 3 days and mice that survived more than 3 days. In conclusion, CLP-induced sepsis in mice changes the structure of the gut microbiome, and innate metabolites affect the prognosis of septic mice.(AU)

Early gut microbiological changes and metabolomic changes in patients with sepsis: a preliminary study / Cambios microbiológicos intestinales tempranos y cambios metabólicos en pacientes con sepsis: un estudio preliminar

The gut microbiota is closely related to the development of sepsis. The aim of this study was to explore changes in the gut microbiota and gut metabolism, as well as potential relationships between the gut microbiota and environmental factors in the early stages of sepsis. Fecal samples were collected from 10 septic patients on the first and third days following diagnosis in this study. The results showed that in the early stages of sepsis, the gut microbiota is dominated by microorganisms that are tightly associated with inflammation, such as Escherichia-Shigella, Enterococcus, Enterobacteriaceae, and Streptococcus. On sepsis day 3 compared to day 1, there was a significant decrease in Lactobacillus and Bacteroides and a significant increase in Enterobacteriaceae, Streptococcus, and Parabacteroides. Culturomica_massiliensis, Prevotella_7 spp., Prevotellaceae, and Pediococcus showed significant differences in abundance on sepsis day 1, but not on sepsis day 3. Additionally, 2-keto-isovaleric acid 1 and 4-hydroxy-6-methyl-2-pyrone metabolites significantly increased on sepsis day 3 compared to day 1. Prevotella_7 spp. was positively correlated with phosphate and negatively correlated with 2-keto-isovaleric acid 1 and 3-hydroxypropionic acid 1, while Prevotella_9 spp. was positively correlated with sequential organ failure assessment score, procalcitonin and intensive care unit stay time. In conclusion, the gut microbiota and metabolites are altered during sepsis, with some beneficial microorganisms decreasing and some pathogenic microorganisms increasing. Furthermore, Prevotellaceae members may play different roles in the intestinal tract, with Prevotella_7 spp. potentially possessing beneficial health properties and Prevotella_9 spp. potentially playing a promoting role in sepsis.(AU)

A Straightforward Bifurcation Pattern-Based Fundus Image Registration Method.

Fundus image registration is crucial in eye disease examination, as it enables the alignment of overlapping fundus images, facilitating a comprehensive assessment of conditions like diabetic retinopathy, where a single image's limited field of view might be insufficient. By combining multiple images, the field of view for retinal analysis is extended, and resolution is enhanced through super-resolution imaging. Moreover, this method facilitates patient follow-up through longitudinal studies. This paper proposes a straightforward method for fundus image registration based on bifurcations, which serve as prominent landmarks. The approach aims to establish a baseline for fundus image registration using these landmarks as feature points, addressing the current challenge of validation in this field. The proposed approach involves the use of a robust vascular tree segmentation method to detect feature points within a specified range. The method involves coarse vessel segmentation to analyze patterns in the skeleton of the segmentation foreground, followed by feature description based on the generation of a histogram of oriented gradients and determination of image relation through a transformation matrix. Image blending produces a seamless registered image. Evaluation on the FIRE dataset using registration error as the key parameter for accuracy demonstrates the method's effectiveness. The results show the superior performance of the proposed method compared to other techniques using vessel-based feature extraction or partially based on SURF, achieving an area under the curve of 0.526 for the entire FIRE dataset.

Investigation on the proton range uncertainty with spectral CT-based virtual monoenergetic images.

OBJECTIVE: The stopping power ratio (SPR) prediction error will contribute to the range uncertainty of proton therapy. Spectral CT is promising in reducing the uncertainty in SPR estimation. The purpose of this research is to determine the optimal energy pairs of SPR prediction for each tissue and to evaluate the dose distribution and range difference between the spectral CT with the optimal energy pairs method and the single energy CT (SECT) method. METHODS: A new method was proposed based on image segmentation to calculate the proton dose with spectral CT images for the head and body phantom. CT number of each organ region were converted to SPR with the optimal energy pairs of each organ. The CT images were segmented into different organ parts with thresholding method. Virtual monoenergetic (VM) images from 70 keV to 140 keV were investigated to determine the optimal energy pairs for each organ based on Gammex 1467 phantom. The beam data of Shanghai Advanced Proton Therapy facility (SAPT) was employed in matRad (an open-source software for radiation treatment planning) for the dose calculation. RESULTS: The optimal energy pairs were obtained for each tissue. The dose distribution of two tumor sites (brain and lung) were calculated with the aforementioned optimal energy pairs. The maximum dose deviation between spectral CT and SECT at the target region was 2.57% and 0.84% for the lung tumor and brain tumor respectively. The range difference between spectral and SECT was significant with 1.8411 mm for the lung tumor. γ passing rate was 85.95% and 95.49% for the lung tumor and brain tumor with the criterion 2%/2 mm. CONCLUSIONS: This work presents a way to determine the optimal energy pairs for each organ and to calculate the dose distribution based on the more accurate SPR prediction.

Highly Reliable Textile-Type Memristor by Designing Aligned Nanochannels.

Information-processing devices are the core components of modern electronics. Integrating them into textiles is the indispensable demand for electronic textiles to form close-loop functional systems. Memristors with crossbar configuration are regarded as promising building blocks to design woven information-processing devices that seamlessly unify with textiles. However, the memristors always suffer from severe temporal and spatial variations due to the random growth of conductive filaments during filamentary switching processes. Here, inspired by the ion nanochannels across synaptic membranes, a highly reliable textile-type memristor made of Pt/CuZnS memristive fiber with aligned nanochannels, showing small set voltage variation (<5.6%) under ultralow set voltage (≈0.089 V), high on/off ratio (≈106 ), and low power consumption (0.1 nW), is reported. Experimental evidence indicate that nanochannels with abundant active S defects can anchor silver ions and confine their migrations to form orderly and efficient conductive filaments. Such memristive performances enable the resultant textile-type memristor array to have high device-to-device uniformity and process complex physiological data like brainwave signals with high recognition accuracy (95%). The textile-type memristor arrays are mechanically durable to withstand hundreds of bending and sliding deformations, and seamlessly unified with sensing, power-supplying, and displaying textiles/fibers to form all-textile integrated electronic systems for new generation human-machine interactions.

Early gut microbiological changes and metabolomic changes in patients with sepsis: a preliminary study.

The gut microbiota is closely related to the development of sepsis. The aim of this study was to explore changes in the gut microbiota and gut metabolism, as well as potential relationships between the gut microbiota and environmental factors in the early stages of sepsis. Fecal samples were collected from 10 septic patients on the first and third days following diagnosis in this study. The results showed that in the early stages of sepsis, the gut microbiota is dominated by microorganisms that are tightly associated with inflammation, such as Escherichia-Shigella, Enterococcus, Enterobacteriaceae, and Streptococcus. On sepsis day 3 compared to day 1, there was a significant decrease in Lactobacillus and Bacteroides and a significant increase in Enterobacteriaceae, Streptococcus, and Parabacteroides. Culturomica_massiliensis, Prevotella_7 spp., Prevotellaceae, and Pediococcus showed significant differences in abundance on sepsis day 1, but not on sepsis day 3. Additionally, 2-keto-isovaleric acid 1 and 4-hydroxy-6-methyl-2-pyrone metabolites significantly increased on sepsis day 3 compared to day 1. Prevotella_7 spp. was positively correlated with phosphate and negatively correlated with 2-keto-isovaleric acid 1 and 3-hydroxypropionic acid 1, while Prevotella_9 spp. was positively correlated with sequential organ failure assessment score, procalcitonin and intensive care unit stay time. In conclusion, the gut microbiota and metabolites are altered during sepsis, with some beneficial microorganisms decreasing and some pathogenic microorganisms increasing. Furthermore, Prevotellaceae members may play different roles in the intestinal tract, with Prevotella_7 spp. potentially possessing beneficial health properties and Prevotella_9 spp. potentially playing a promoting role in sepsis.

Coco-Attention for Tumor Segmentation in Weakly Paired Multimodal MRI Images.

Multimodal magnetic resonance imaging (MRI) contains complementary information in anatomical and functional images that help the accurate diagnosis and treatment evaluation of lung cancers. However, effectively exploiting the complementary information in chest MRI images remains challenging due to the lack of rigorous registration. In this paper, a novel method is proposed that can effectively exploit the complementary information in weakly paired images for accurate tumor segmentation, namely coco-attention mechanism. Coco-attention module consists of two parts: the multi-modal co-attention (MultiCo-attn) and the multi-level coordinate attention (MultiCord-attn). The former aims to obtain tumor-aware deep features for accurate tumor localization, and the latter aims to highlight tumor area for more precise segmentation. Specifically, the MultiCo-attn extracts complementary information from multimodal high-dimensional semantic features using a bidirectional algorithm to generate attention maps focused on tumor region, and then uses the attention maps to enhance the feature representations. The MultiCord-attn leverages multi-level feature information to highlight tumor regions by adjusting the weight of each point in the feature. We evaluate the proposed method on lung tumor segmentation with a clinical dataset of 90 chest MRI scans of non-small cell lung cancer (NSCLC). The results show that the proposed method is effective for tumor segmentation in weakly paired images and achieves significant improvement (p < 0.005) over several commonly used multimodal segmentation methods. Furthermore, the ablation experiment results confirm the effectiveness and interpretability of the proposed coco-attention module.

A Circular Total Focusing Method With Eccentricity Correction and Intensity Compensation for Endoscopic Ultrasound Imaging of Dual-Layered Media.

Present endoscopic ultrasound (EUS) imaging methods for circular array (CA) suffer from the nonuniform spatial resolution in the imaging of a dual-layered media, such as the tubes' immersion EUS inspection. The problem is mainly attributed to the restricted focus and beam de-focusing at the interface. In this article, a circular total focusing method (CTFM) is proposed, which leverages the concept of the conventional total focusing method (TFM) and makes three vital improvements to overcome the challenges. First, to obtain the accurate time-of-flight (TOF) in the dual-layered media, a fourth-order equation of Snell's law is built and solved in polar coordinate system. Second, a fast geometric approximation method is derived to correct the TOF distortion caused by the transducer's eccentricity. Third, the intensity compensation is applied to flatten the imaging intensity at different positions by considering the directivity of element, transmission at interface, and divergence in media. The CTFM is validated on a tube's immersion EUS using a 10 MHz CA with 128 elements. Experimental results demonstrate that the proposed CTFM outperforms existing imaging methods. The lateral and axial resolutions are 0.71 and 0.30 mm, which are 27.5% and 33.3% higher than those of the classic delay-and-sum (DAS) method. The CTFM image shows high and uniform signal-to-noise ratio (SNR) which is 33.6% higher than that of DAS images. The CTFM provides a novel EUS imaging modality which can be applied in both medical and nondestructive testing domains.

Gut microbiota disruption during sepsis and the influence of innate metabolites on sepsis prognosis.

Sepsis causes high mortality in intensive care units. Although there have been many studies on the gut microbiota in patients with sepsis, the impact of sepsis on the gut microbiota has not been directly determined because the treatment of sepsis also affects the gut microbiota. Therefore, we designed this animal experiment to explore gut microbiota alterations during sepsis. Mice were divided into two groups, mice that survived less than 3 days and mice that survived more than 3 days. Fecal samples collected on the day of cecal ligation and puncture (CLP), as well as on the 3rd and 7th days after CLP, were subjected to microbial community analysis and nontargeted metabolomics analysis. The results showed significantly lower bacterial diversity in fecal samples after CLP. At the genus level, the fecal samples obtained on the 3rd and 7th days after CLP exhibited significantly increased relative abundances of Bacteroides, Helicobacter, etc., and significantly decreased relative abundances of Alloprevotella, Prevotella, etc. Innate metabolite levels were significantly different in mice that survived less than 3 days and mice that survived more than 3 days. In conclusion, CLP-induced sepsis in mice changes the structure of the gut microbiome, and innate metabolites affect the prognosis of septic mice.

End-to-End QA with Polymer Gel Dosimeter for Photon Beam Radiation Therapy.

With the complexity and high demands on quality assurance (QA) of photon beam radiation therapy, end-to-end (E2E) QA is necessary to validate the entire treatment workflow from pre-treatment imaging to beam delivery. A polymer gel dosimeter is a promising tool for three-dimensional (3D) dose distribution measurement. The purpose of this study is to design a fast "one delivery" polymethyl methacrylate (PMMA) phantom with a polymer gel dosimeter for the E2E QA test of the photon beam. The one delivery phantom is composed of ten calibration cuvettes for the calibration curve measurement, two 10 cm gel dosimeter inserts for the dose distribution measurement, and three 5.5 cm gel dosimeters for the square field measurement. The one delivery phantom holder is comparable in size and shape to that of a human thorax and abdomen. In addition, an anthropomorphic head phantom was employed to measure the patient-specific dose distribution of a VMAT plan. The E2E dosimetry was verified by undertaking the whole RT procedure (immobilization, CT simulation, treatment planning, phantom set-up, imaged-guided registration, and beam delivery). The calibration curve, field size, and patient-specific dose were measured with a polymer gel dosimeter. The positioning error can be mitigated with the one-delivery PMMA phantom holder. The delivered dose measured with a polymer gel dosimeter was compared with the planned dose. The gamma passing rate is 86.64% with the MAGAT-f gel dosimeter. The results ascertain the feasibility of the one delivery phantom with a polymer gel dosimeter for a photon beam in E2E QA. The QA time can be reduced with the designed one delivery phantom.

New insights into mechanisms of berberine in alleviating reproductive disorders of polycystic ovary syndrome: Anti-inflammatory properties.

Polycystic ovary syndrome (PCOS) is a complex reproductive disorder that seriously harms female reproductive health and decreases quality of life. Although spontaneous or assisted ovulation occurs, women with PCOS suffer from poor-quality oocytes and embryos and lower fertilization and final pregnancy rates. Therefore, it is urgent to identify new pathological mechanisms and discover the underlying therapeutic targets for reproductive disorders associated with PCOS. Berberine, one of the famous traditional Chinese medicines, has been shown to improve ovulation and live birth rates in women with PCOS. The effects of berberine on insulin resistance and abnormal glucose and lipid metabolism for restoring the reproductive health of women with PCOS are well recognized and have been widely studied, but much less attention has been given to its anti-inflammatory properties. Chronic low-grade inflammation is the unifying feature of PCOS and may contribute to reproductive disorders in PCOS. Berberine can modulate the inflammatory state of the ovaries and uterus in PCOS. The anti-inflammatory properties of berberine may provide new insight into the mechanisms by which berberine alleviates reproductive disorders associated with PCOS. Here, we summarized the most recent insights into the anti-inflammatory properties of berberine in PCOS reproductive disorders to inspire researchers to pursue new study directions involving berberine.

Registration on DCE-MRI images via multi-domain image-to-image translation.

Registration of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is challenging as rapid intensity changes caused by a contrast agent lead to large registration errors. To address this problem, we propose a novel multi-domain image-to-image translation (MDIT) network based on image disentangling for separating motion from contrast changes before registration. In particular, the DCE images are disentangled into a domain-invariant content space (motion) and a domain-specific attribute space (contrast changes). The disentangled representations are then used to generate images, where the contrast changes have been removed from the motion. After that the resulting deformations can be directly derived from the generated images using an FFD registration. The method is tested on 10 lung DCE-MRI cases. The proposed method reaches an average root mean squared error of 0.3 ± 0.41 and the separation time is about 2.4 s for each case. Results show that the proposed method improves the registration efficiency without losing the registration accuracy compared with several state-of-the-art registration methods.

Analysis of metabolic disturbances attributable to sepsis-induced myocardial dysfunction using metabolomics and transcriptomics techniques.

Background: Sepsis-induced myocardial dysfunction (SIMD) is the most common and severe sepsis-related organ dysfunction. We aimed to investigate the metabolic changes occurring in the hearts of patients suffering from SIMD. Methods: An animal SIMD model was constructed by injecting lipopolysaccharide (LPS) into mice intraperitoneally. Metabolites and transcripts present in the cardiac tissues of mice in the experimental and control groups were extracted, and the samples were studied following the untargeted metabolomics-transcriptomics high-throughput sequencing method. SIMD-related metabolites were screened following univariate and multi-dimensional analyses methods. Additionally, differential analysis of gene expression was performed using the DESeq package. Finally, metabolites and their associated transcripts were mapped to the relevant metabolic pathways after extracting transcripts corresponding to relevant enzymes. The process was conducted based on the metabolite information present in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results: One hundred and eighteen significant differentially expressed metabolites (DEMs) (58 under the cationic mode and 60 under the anionic mode) were identified by studying the SIMD and control groups. Additionally, 3,081 significantly differentially expressed genes (DEGs) (1,364 were down-regulated and 1717 were up-regulated DEGs) were identified in the transcriptomes. The comparison was made between the two groups. The metabolomics-transcriptomics combination analysis of metabolites and their associated transcripts helped identify five metabolites (d-mannose, d-glucosamine 6-phosphate, maltose, alpha-linolenic acid, and adenosine 5'-diphosphate). Moreover, irregular and unusual events were observed during the processes of mannose metabolism, amino sugar metabolism, starch metabolism, unsaturated fatty acid biosynthesis, platelet activation, and purine metabolism. The AMP-activated protein kinase (AMPK) signaling pathways were also accompanied by aberrant events. Conclusion: Severe metabolic disturbances occur in the cardiac tissues of model mice with SIMD. This can potentially help in developing the SIMD treatment methods.