Modelling the dynamic gas/particle partitioning process of semi-volatile organic compounds emitted from point sources: Quantitative analysis and impact assessment.

The deleterious impact of pollution point sources on the surrounding environment and human has long been a focal point of environmental research. When considering the local atmospheric dispersion of semi-volatile organic compounds (SVOCs) around the emission sites, it is essential to account the dynamic process for the gas/particle (G/P) partitioning, which involves the transition from an initial state to a steady state. In this study, we have developed a model that enables the prediction of the dynamic process for G/P partitioning of SVOCs, particularly considering the influence from emission. It is important to note that the dynamic processes of the concentrations of SVOCs in particle phase (CP) and in gas phase (CG) differ significantly. These differences arise due to the influence of two critical factors: particulate proportion of SVOCs in the emissions (ϕ0) and octanol-air partitioning coefficient (KOA). The validity of our model was assessed by comparing its predictions of the extremum value of the G/P partitioning quotient (KP) with the results obtained from the steady-state model. Remarkably, the characteristic time (tC), used to evaluate the timescale required for SVOCs to reach steady state, demonstrated different variations with KOA for CP and CG. Additionally, the values of tC were quite different for CP and CG, which were markedly influenced by ϕ0. For some SVOCs with high KOA values, it took approximately 35 h to reach steady state. Furthermore, it was found that the time to achieve 95 % of steady state (t95 ≈ 3tC) could reach approximately 105 h. This duration is sufficient for chemicals to disperse from their emission site to the surrounding areas. Therefore, it is crucial to consider the dynamic process of G/P partitioning in local atmospheric transport studies. Moreover, the influence of ϕ0 should be incorporated into future investigations examining the dynamic process of G/P partitioning.

Rehabilitation Assessment System for Stroke Patients Based on Fusion-Type Optoelectronic Plethysmography Device and Multi-Modality Fusion Model: Design and Validation.

This study aimed to propose a portable and intelligent rehabilitation evaluation system for digital stroke-patient rehabilitation assessment. Specifically, the study designed and developed a fusion device capable of emitting red, green, and infrared lights simultaneously for photoplethysmography (PPG) acquisition. Leveraging the different penetration depths and tissue reflection characteristics of these light wavelengths, the device can provide richer and more comprehensive physiological information. Furthermore, a Multi-Channel Convolutional Neural Network-Long Short-Term Memory-Attention (MCNN-LSTM-Attention) evaluation model was developed. This model, constructed based on multiple convolutional channels, facilitates the feature extraction and fusion of collected multi-modality data. Additionally, it incorporated an attention mechanism module capable of dynamically adjusting the importance weights of input information, thereby enhancing the accuracy of rehabilitation assessment. To validate the effectiveness of the proposed system, sixteen volunteers were recruited for clinical data collection and validation, comprising eight stroke patients and eight healthy subjects. Experimental results demonstrated the system's promising performance metrics (accuracy: 0.9125, precision: 0.8980, recall: 0.8970, F1 score: 0.8949, and loss function: 0.1261). This rehabilitation evaluation system holds the potential for stroke diagnosis and identification, laying a solid foundation for wearable-based stroke risk assessment and stroke rehabilitation assistance.

Insufficient epitope-specific T cell clones are responsible for impaired cellular immunity to inactivated SARS-CoV-2 vaccine in older adults.

Aging is a critical risk factor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine efficacy. The immune responses to inactivated vaccine for older adults, and the underlying mechanisms of potential differences to young adults, are still unclear. Here we show that neutralizing antibody production by older adults took a longer time to reach similar levels in young adults after inactivated SARS-CoV-2 vaccination. We screened SARS-CoV-2 variant strains for epitopes that stimulate specific CD8 T cell response, and older adults exhibited weaker CD8 T-cell-mediated responses to these epitopes. Comparison of lymphocyte transcriptomes from pre-vaccinated and post-vaccinated donors suggested that the older adults had impaired antigen processing and presentation capability. Single-cell sequencing revealed that older adults had less T cell clone expansion specific to SARS-CoV-2, likely due to inadequate immune receptor repertoire size and diversity. Our study provides mechanistic insights for weaker response to inactivated vaccine by older adults and suggests the need for further vaccination optimization for the old population.

Development and validation of an ensemble machine-learning model for predicting early mortality among patients with bone metastases of hepatocellular carcinoma.

Purpose: Using an ensemble machine learning technique that incorporates the results of multiple machine learning algorithms, the study's objective is to build a reliable model to predict the early mortality among hepatocellular carcinoma (HCC) patients with bone metastases. Methods: We extracted a cohort of 124,770 patients with a diagnosis of hepatocellular carcinoma from the Surveillance, Epidemiology, and End Results (SEER) program and enrolled a cohort of 1897 patients who were diagnosed as having bone metastases. Patients with a survival time of 3 months or less were considered to have had early death. To compare patients with and without early mortality, subgroup analysis was used. Patients were randomly divided into two groups: a training cohort (n = 1509, 80%) and an internal testing cohort (n = 388, 20%). In the training cohort, five machine learning techniques were employed to train and optimize models for predicting early mortality, and an ensemble machine learning technique was used to generate risk probability in a way of soft voting, and it was able to combine the results from the multiply machine learning algorithms. The study employed both internal and external validations, and the key performance indicators included the area under the receiver operating characteristic curve (AUROC), Brier score, and calibration curve. Patients from two tertiary hospitals were chosen as the external testing cohorts (n = 98). Feature importance and reclassification were both operated in the study. Results: The early mortality was 55.5% (1052/1897). Eleven clinical characteristics were included as input features of machine learning models: sex (p = 0.019), marital status (p = 0.004), tumor stage (p = 0.025), node stage (p = 0.001), fibrosis score (p = 0.040), AFP level (p = 0.032), tumor size (p = 0.001), lung metastases (p < 0.001), cancer-directed surgery (p < 0.001), radiation (p < 0.001), and chemotherapy (p < 0.001). Application of the ensemble model in the internal testing population yielded an AUROC of 0.779 (95% confidence interval [CI]: 0.727-0.820), which was the largest AUROC among all models. Additionally, the ensemble model (0.191) outperformed the other five machine learning models in terms of Brier score. In terms of decision curves, the ensemble model also showed favorable clinical usefulness. External validation showed similar results; with an AUROC of 0.764 and Brier score of 0.195, the prediction performance was further improved after revision of the model. Feature importance demonstrated that the top three most crucial features were chemotherapy, radiation, and lung metastases based on the ensemble model. Reclassification of patients revealed a substantial difference in the two risk groups' actual probabilities of early mortality (74.38% vs. 31.35%, p < 0.001). Patients in the high-risk group had significantly shorter survival time than patients in the low-risk group (p < 0.001), according to the Kaplan-Meier survival curve. Conclusions: The ensemble machine learning model exhibits promising prediction performance for early mortality among HCC patients with bone metastases. With the aid of routinely accessible clinical characteristics, this model can be a trustworthy prognostic tool to predict the early death of those patients and facilitate clinical decision-making.

MiR-181a-5p promotes osteogenesis by targeting BMP3.

High-throughput microRNA (miRNA) sequencing of osteoporosis was analyzed from the Gene Expression Omnibus (GEO) database to investigate specific microRNAs that control osteogenesis. MiR-181a-5p was differentially expressed among healthy subjects and those with osteoporosis. Inhibitors and mimics were transfected into cells to modulate miR-181a-5p levels to examine the role in MC3T3-E1 functions. Alkaline phosphatase (ALP) staining and Alizarin Red S (ARS) staining were used for morphological detection, and proteins of ALP and Runt-related transcription factor 2 (RUNX2), as osteogenesis markers, were detected. During the osteogenic differentiation of MC3T3-E1, the transcription level of miR-181a-5p was significantly increased. The inhibition of miR-181a-5p suppressed MC3T3-E1 osteogenic differentiation, whereas its overexpression functioned oppositely. Consistently, the miR-181a-5p antagomir aggravated osteoporosis in old mice. Additionally, we predicted potential target genes via TargetScan and miRDB and identified bone morphogenetic protein 3 (BMP3) as the target gene. Moreover, the reduced expression of miR-181a-5p was validated in our hospitalized osteoporotic patients. These findings have substantial implications for the strategies targeting miR-181a-5p to prevent osteoporosis and potential related fractures.

A machine learning-Based model to predict early death among bone metastatic breast cancer patients: A large cohort of 16,189 patients.

Purpose: This study aims to develop a prediction model to categorize the risk of early death among breast cancer patients with bone metastases using machine learning models. Methods: This study examined 16,189 bone metastatic breast cancer patients between 2010 and 2019 from a large oncological database in the United States. The patients were divided into two groups at random in a 90:10 ratio. The majority of patients (n = 14,582, 90%) were served as the training group to train and optimize prediction models, whereas patients in the validation group (n = 1,607, 10%) were utilized to validate the prediction models. Four models were introduced in the study: the logistic regression model, gradient boosting tree model, decision tree model, and random forest model. Results: Early death accounted for 17.4% of all included patients. Multivariate analysis demonstrated that older age; a separated, divorced, or widowed marital status; nonmetropolitan counties; brain metastasis; liver metastasis; lung metastasis; and histologic type of unspecified neoplasms were significantly associated with more early death, whereas a lower grade, a positive estrogen receptor (ER) status, cancer-directed surgery, radiation, and chemotherapy were significantly the protective factors. For the purpose of developing prediction models, the 12 variables were used. Among all the four models, the gradient boosting tree had the greatest AUC [0.829, 95% confident interval (CI): 0.802-0.856], and the random forest (0.828, 95% CI: 0.801-0.855) and logistic regression (0.819, 95% CI: 0.791-0.847) models came in second and third, respectively. The discrimination slopes for the three models were 0.258, 0.223, and 0.240, respectively, and the corresponding accuracy rates were 0.801, 0.770, and 0.762, respectively. The Brier score of gradient boosting tree was the lowest (0.109), followed by the random forest (0.111) and logistic regression (0.112) models. Risk stratification showed that patients in the high-risk group (46.31%) had a greater six-fold chance of early death than those in the low-risk group (7.50%). Conclusion: The gradient boosting tree model demonstrates promising performance with favorable discrimination and calibration in the study, and this model can stratify the risk probability of early death among bone metastatic breast cancer patients.

A novel nomogram to stratify quality of life among advanced cancer patients with spinal metastatic disease after examining demographics, dietary habits, therapeutic interventions, and mental health status.

BACKGROUND: It would be very helpful to stratify patients and direct patient selection if risk factors for quality of life were identified in a particular population. Nonetheless, it is still challenging to forecast the health-related quality of life among individuals with spinal metastases. The goal of this study was to stratify patient's populations for whom the assessment of quality of life should be encouraged by developing and validating a nomogram to predict the quality of life among advanced cancer patients with spine metastases. METHODS: This study prospectively analyzed 208 advanced cancer patients with spine metastases, and collected their general characteristics, food preferences, addictions, comorbidities, therapeutic strategies, and mental health status. The functional assessment of cancer therapy-general (FACT-G) and hospital anxiety and depression scale (HADS) were used to assess quality of life and mental health, respectively. The complete cohort of patients was randomly divided into two groups: a training set and a validation set. Patients from the training set were conducted to train and develop a nomogram, while patients in the validation set were performed to internally validate the nomogram. The nomogram contained significant variables discovered using the least absolute shrinkage and selection operator (LASSO) approach in conjunction with 10-fold cross-validation. The nomogram's predictive ability was assessed utilizing discrimination, calibration, and clinical usefulness. Internal validation was also completed using the bootstrap method after applying 500 iterations of procedures. A web calculator was also developed to promote clinical practice. RESULTS: Advance cancer patients with spinal metastases had an extremely low quality of life, as indicated by the average FACT-G score of just 60.32 ± 20.41. According to the LASSO and 10-fold cross-validation, Eastern Cooperative Oncology Group (ECOG) score, having an uncompleted life goal, preference for eating vegetables, chemotherapy, anxiety status, and depression status were selected as nomogram predictors. In the training set, the area under the receiver operating characteristic curve (AUROC) was 0.90 (95% CI: 0.84-0.96), while in the validation set, it was 0.85 (95% CI: 0.78-0.93). They were 0.50 (95% CI: 0.41-0.58) and 0.44 (95% CI: 0.33-0.56), respectively, for the discrimination slopes. The nomogram had favorable capacity to calibrate and was clinically useful, according to the calibration curve and decision curve analysis. When compared to patients in the low-risk group, patients in the high-risk group were above four times more likely to experience a poor quality of life (82.18% vs. 21.50%, P < 0.001). In comparison to patients in the low-risk group, patients in the high-risk group also exhibited significant higher levels of anxiety and depression. The webpage for the web calculator was https://starshiny.shinyapps.io/DynNomapp-lys/ . CONCLUSIONS: This study suggests a nomogram that can be applied as a practical clinical tool to forecast and categorize the quality of life among patients with spine metastases. Additionally, patients with poor quality of life experience more severe anxiety and depression. Effective interventions should be carried out as soon as possible, especially for patients in the high-risk group, to improve their quality of life and mental health condition.

Fatty acid desaturase 1 (FADS1) is a cancer marker for patient survival and a potential novel target for precision cancer treatment.

Fatty Acid Desaturase-1 (FADS1) or delta 5 desaturase (D5D) is a rate-limiting enzyme involved in the biosynthesis of long-chain polyunsaturated fatty acids (LC-PUFAs), i.e., arachidonic acid (ARA) and eicosapentaenoic (EPA). These LC-PUFAs and their metabolites play essential and broad roles in cancer cell proliferation, metastasis, and tumor microenvironment. However, the role of FADS1 in cancers remains incompletely understood. Utilizing The Cancer Genome Atlas (TCGA) database, we explored the role of FADS1 across different cancer types using multiple bioinformatics and statistical tools. Moreover, we studied the impact of a FADS1 inhibitor (D5D-IN-326) on proliferation of multiple cancer cell lines. We identified that FADS1 gene is a predictor for cancer survival in multiple cancer types. Compared to normal tissue, the mRNA expression of FADS1 is significantly increased in primary tumors while even higher in metastatic and recurrent tumors. Mechanistically, pathway analysis demonstrated that FADS1 is associated with cholesterol biosynthesis and cell cycle control genes. Interestingly, FADS1 expression is higher when TP53 is mutated. Tumors with increased FADS1 expression also demonstrated an increased signatures of fibroblasts and macrophages infiltration among most cancer types. Our in vitro assays showed that D5D-IN-326 significantly inhibited cell proliferation of kidney, colon, breast, and lung cancer cell lines in a dose-dependent manner. Lastly, single nucleotide polymorphisms (SNPs) which are well-established expression quantitative trait loci (eQTLs) for FADS1 in normal human tissues are also significantly correlated with FADS1 expression in tumors of multiple tissue types, potentially serving as a marker to stratify cancer patients with high/low FADS1 expression in their tumor tissue. Our study suggests that FADS1 plays multiple roles in cancer biology and is potentially a novel target for precision cancer treatment.

[Impacts of long-term different fertilization managements on soil acid hydrolysable organic nitrogen fractions in double-cropping rice field]. / é•¿æœŸä¸åŒæ–½è‚¥æ¨¡å¼å¯¹åŒå­£ç¨»ç”°åœŸå£¤é ¸è§£æœ‰æœºæ°®ç»„åˆ†çš„å½±å“.

To clarify the impacts of long-term different fertilization modes on the soil acid hydrolysable organic nitrogen and its components in the double-cropping rice field of southern China, a long-term (36-year) location field experiment was used as a platform to systematically analyze the variations of soil acid hydrolysable organic nitrogen and its components (amino acid nitrogen, amino sugar nitrogen, ammonium nitrogen, unidentified hydrolysable nitrogen) at 0-10 cm and 10-20 cm soil layers under four fertilization treatments, including chemical fertilizer alone (CF), rice straw and chemical fertilizer (RF), 30% organic manure and 70% chemical fertilizer (OM), and control (CK). The relationships of soil acid hydrolysable organic nitrogen content and soil total nitrogen, soil organic carbon content were also analyzed. The results showed that compared with CK, OM and RF treatments significantly increased the contents of total nitrogen, available nitrogen, and organic carbon at both soil layers. The contents of soil acid hydrolysable organic nitrogen at 0-10 cm and 10-20 cm layers of OM, RF and CF treatments were 10.7%-42.6% and 12.2% -51.5% higher than that of CK, respectively. Compared with CF and CK treatments, OM and RF treatments significantly increased the contents of amino acid nitrogen, ammonium nitrogen, unidentified hydrolysable nitrogen and amino sugar nitrogen contents atboth soil layers. The soil acid hydrolysable organic nitrogen and non-hydrolysable nitrogen contents at 0-10 cm and 10-20 cm paddy soils under different fertilization treatments decreased in an order of OM>RF>CF>CK. The contents of soil amino acid nitrogen, ammonium nitrogen, amino sugar nitrogen and non-hydrolysable nitrogen at 0-10 cm soil layer of each fertilization treatment were higher than those at 10-20 cm soil layer. In addition, the contents of soil acid hydrolyzed organic nitrogen were positively correated with the contents of soil total nitrogen and soil organic carbon. In conclusion, RF and OM treatments were beneficial to increase organic nitrogen content at 0-10 and 10-20 cm soil layers of double cropping paddy fields, with postive consequences on nitrogen supply capacity and soil fertility.

[A new hexenol glycoside from Buddleja officinalis].

The chemical constituents of the flower buds of Buddleja officinalis were investigated in this study. Eight compounds were isolated from the water extract of B. officinalis by column chromatography, and their structures were elucidated on the basis of physicochemical properties and spectral data. These compounds were identified as(Z)-hex-3-en-1-ol-1-O-ß-D-glucopyranosyl-(1→2)-[ß-D-xylcopyranosyl-(1→6)]-ß-D-glucopyranoside(1), ebracteatoside B(2), jasmonic acid-11-O-ß-D-glucopyranoside(3), 6-hydroxyluteolin-7-O-ß-D-glucopyranoside(4), luteolin-7-O-galacturonide(5), vicenin-2(6), decaffeoylverbascoside(7), and 6-O-(E)-feruloyl-D-glucopyranoside(8). Compound 1 is a new 3-hexenol glycoside. Compounds 2, 3, and 6 were isolated from Buddleja genus for the first time, and compounds 4 and 5 were isolated from this plant for the first time.

Exposure to a mixture of legacy, alternative, and replacement per- and polyfluoroalkyl substances (PFAS) results in sex-dependent modulation of cholesterol metabolism and liver injury.

BACKGROUND: Epidemiological studies have shown Per- and polyfluoroalkyl substances (PFAS) to be associated with diseases of dysregulated lipid and sterol homeostasis such as steatosis and cardiometabolic disorders. However, the majority of mechanistic studies rely on single chemical exposures instead of identifying mechanisms related to the toxicity of PFAS mixtures. OBJECTIVES: The goal of the current study is to investigate mechanisms linking exposure to a PFAS mixture with alterations in lipid metabolism, including increased circulating cholesterol and bile acids. METHODS: Male and female wild-type C57BL/6J mice were fed an atherogenic diet used in previous studies of pollutant-accelerated atherosclerosis and exposed to water containing a mixture of 5 PFAS representing legacy, replacement, and alternative subtypes (i.e., PFOA, PFOS, PFNA, PFHxS, and GenX), each at a concentration of 2 mg/L, for 12 weeks. Changes at the transcriptome and metabolome level were determined by RNA-seq and high-resolution mass spectrometry, respectively. RESULTS: We observed increased circulating cholesterol, sterol metabolites, and bile acids due to PFAS exposure, with some sexual dimorphic effects. PFAS exposure increased hepatic injury, demonstrated by increased liver weight, hepatic inflammation, and plasma alanine aminotransferase levels. Females displayed increased lobular and portal inflammation compared to the male PFAS-exposed mice. Hepatic transcriptomics analysis revealed PFAS exposure modulated multiple metabolic pathways, including those related to sterols, bile acids, and acyl carnitines, with multiple sex-specific differences observed. Finally, we show that hepatic and circulating levels of PFOA were increased in exposed females compared to males, but this sexual dimorphism was not the same for other PFAS examined. DISCUSSION: Exposure of mice to a mixture of PFAS results in PFAS-mediated modulation of cholesterol levels, possibly through disruption of enterohepatic circulation.

Shuganning injection, a traditional Chinese patent medicine, induces ferroptosis and suppresses tumor growth in triple-negative breast cancer cells.

BACKGROUND: Triple-negative breast cancer (TNBC), lacking targeted therapies currently, is susceptible to ferroptosis, a recently defined form of cell death. PURPOSE: To evaluate the anticancer activity of Shuganning injection (SGNI), a traditional Chinese patent medicine, on TNBC cells; To elucidate the mechanism of SGNI induced ferroptosis. METHODS: The anticancer activity of SGNI was examined via in vitro cell proliferation assays and in vivo xenograft growth assay. Ferroptosis was determined by flow-cytometric analysis of lipid ROS, labile iron pool measurement, and propidium iodide exclusion assay. The dependency on heme oxygenase 1 (HO-1) of SGNI induced ferroptosis was confirmed by genetic knockdown and pharmacological inhibition of the protein. RESULTS: SGNI selectively inhibited the proliferation of TNBC cells compared to non-TNBC breast cancer cells and normal cells. The cell death induced by SGNI in TNBC cells showed distinct morphology from apoptosis and could not be rescued by the pan-caspase inhibitor Z-VAD(OMe)-FMK. On the other hand, SGNI induced cell death was blocked by the lipid ROS scavengers ferrostatin-1 and liproxstatin-1, the acyl-CoA synthetase long chain family member 4 inhibitor rosiglitazone, and the iron chelators 1,10-phenanthroline and deferoxamine. These data indicated that SGNI induced a ferroptotic cell death of TNBC cells. Mechanistically, SGNI induced ferroptosis was dependent on HO-1, which promotes intracellular labile iron pool accumulation, and was alleviated by HO-1 knockdown and inhibition by tin protoporphyrin IX. In line with the in vitro data, SGNI significantly inhibited the xenograft growth of TNBC cell line MD-MB-231 in nude mice. CONCLUSION: Collectively, our study elaborates on a promising regimen for TNBC treatment through induction of ferroptosis by SGNI, a traditional Chinese patent medicine currently available in the clinic, which merits further investigation.

Autophagy inhibitors increase the susceptibility of KRAS-mutant human colorectal cancer cells to a combined treatment of 2-deoxy-D-glucose and lovastatin.

RAS-driven colorectal cancer relies on glucose metabolism to support uncontrolled growth. However, monotherapy with glycolysis inhibitors like 2-deoxy-D-glucose causes limited effectiveness. Recent studies suggest that anti-tumor effects of glycolysis inhibition could be improved by combination treatment with inhibitors of oxidative phosphorylation. In this study we investigated the effect of a combination of 2-deoxy-D-glucose with lovastatin (a known inhibitor of mevalonate pathway and oxidative phosphorylation) on growth of KRAS-mutant human colorectal cancer cell lines HCT116 and LoVo. A combination of lovastatin (>3.75 µM) and 2-deoxy-D-glucose (>1.25 mM) synergistically reduced cell viability, arrested cells in the G2/M phase, and induced apoptosis. The combined treatment also reduced cellular oxygen consumption and extracellular acidification rate, resulting in decreased production of ATP and lower steady-state ATP levels. Energy depletion markedly activated AMPK, inhibited mTOR and RAS signaling pathways, eventually inducing autophagy, the cellular pro-survival process under metabolic stress, whereas inhibition of autophagy by chloroquine (6.25 µM) enhanced the cytotoxic effect of the combination of lovastatin and 2-deoxy-D-glucose. These in vitro experiment results were reproduced in a nude mouse xenograft model of HCT116 cells. Our findings suggest that concurrently targeting glycolysis, oxidative phosphorylation, and autophagy may be a promising regimen for the management of RAS-driven colorectal cancers.

NEOVASCULAR COMPLICATIONS FROM CYTOMEGALOVIRUS NECROTIZING RETINOPATHY IN PATIENTS AFTER HAPLOIDENTICAL HEMATOPOIETIC STEM CELL TRANSPLANTATION.

PURPOSE: To report the incidence and clinical features of neovascular complications from cytomegalovirus (CMV) necrotizing retinopathy in patients after haploidentical hematopoietic stem cell transplantation. METHODS: Thirty-nine patients (58 eyes) of CMV necrotizing retinopathy after haploidentical hematopoietic stem cell transplantation in our institute between January 2018 and June 2020 were retrospectively reviewed, and cases that developed neovascular complications during follow-up were identified and described. RESULTS: Two (2 eyes) cases that developed neovascular glaucoma from CMV necrotizing retinopathy were identified. Both of them manifested as granular peripheral retinitis, panretinal occlusive vasculitis, and some degree of intraocular inflammation, which were consistent with chronic retinal necrosis. Insidious progression of isolated immune-mediated occlusive vasculitis that could only be observed on fundus fluorescein angiography without active retinitis or intraocular inflammation was recognized to be the cause in one of two cases. CONCLUSION: Neovascular glaucoma developed in 5.1%/cases and 3.4%/eyes complicated by CMV chronic retinal necrosis and vasculitis in patients after haploidentical hematopoietic stem cell transplantation, which warrants the needs for long-term follow-up. Immune-mediated CMV vasculitis could be an isolated manifestation in patients with a minimal immune deviation and may only be found on fundus fluorescein angiography, which emphasizes the importance of fundus fluorescein angiography on a regular basis during follow-up.

Continuous High-Dose (6 mg) vs. Low-Dose (3 mg) Intravitreal Ganciclovir for Cytomegalovirus Retinitis After Haploidentical Hematopoietic Stem Cell Transplantation: A Randomized Controlled Study.

Purpose: To evaluate the safety and efficacy of continuous high-dose (6 mg) intravitreal ganciclovir injections (IVG) for cytomegalovirus (CMV) retinitis (CMVR) after haploidentical hematopoietic stem cell transplantation (Haplo-HSCT), and to explore factors that may influence the treatment procedure. Design: Prospective, randomized, single-blinded, positive-controlled, interventional, comparative study. Methods: A total of 22 patients with CMVR (32 eyes) were randomized to either high-dose group (IVG 6 mg weekly) or low-dose group (IVG 3 mg given twice weekly for 2 weeks as induction phase and weekly thereafter as maintenance phase). Patients who were recorded any positive CMV DNAemia or other active CMV diseases and needed systemic anti-CMV treatment during the study period were excluded. The vision outcome, variables of the treatment procedure, and incidence of complication and CMVR recurrence were analyzed and compared. Logistic regression was applied to determine the factors that may have an impact on the treatment process at baseline. Results: Compared to the low-dose group, the high-dose group resulted in a median of two less intravitreal injections (4 vs. 6 times, respectively, P = 0.016), while the rate of vision stability or improvement (81.2 vs. 87.5%), the incidence of complication (6.2 vs. 18.8%), and CMVR recurrence (12.5% vs. 6.2%) were similar (all P > 0.05). No drug-related toxicity was observed. Initial aqueous CMV-DNA load (OR: 6.872, 95% CI: 1.335-35.377, P = 0.021) and extension of lesion (OR: 0.942, 95% CI: 0.897 to .991, P = 0.020), but not dosing regimen (P = 0.162), were predictors of the treatment duration. Conclusions: Continuous high-dose regimen was well tolerated and resulted in less intravitreal injections, with similar vision outcomes and safety profiles. The clinical course of CMVR after Haplo-HSCT was determined by its own nature at baseline and could not be modified by treatment protocols under consistent immune background.

High expression of HOXA5 is associated with poor prognosis in acute myeloid leukemia.

BACKGROUND: HOXA5 is considered as an oncogene in many tumors. This study in- vestigated the HOXA5 expression in Chinese acute myeloid leukemia (AML) patients and evaluated the predictive significance of HOXA5 with a single-center retrospective study. METHODS: We investigated the expression pattern and prognostic value of HOXA5 in patients with AML through by using a series of databases and various datasets, including the ONCOMINE, TCGA, and STRING datasets. The bone marrow samples of 53 newly diagnosed AML patients (non-M3 subtype) and 19 benign individuals were collected in our center. HOXA5 mRNA expression levels were detected by real-time qPCR, HOXA5 protein expression levels were detected by Western Blot. Clinical data was obtained from inpatient medical records. RESULTS: Two microarrays in Oncomine showed that the expression level of HOXA5 was significantly upregulated in AML. Our data revealed that AML patients had higher HOXA5 mRNA and protein expression levels than the controls (P < 0.001). The blast percentage in bone marrow of HOXA5 high-expression group was higher that of HOXA5 low-expression group (P < 0.05). Higher expression level of HOXA5 revealed a worse OS in AML (P < 0.05). CONCLUSION: Our findings suggested that HOXA5 might have the potential ability to act as a diagnostic biomarker and potential therapeutic target for AML.

Ventilator for the management of patients with severe pneumonia: A protocol of systematic review.

BACKGROUND: This study will assess the efficacy and safety of ventilator for the management of severe pneumonia (SP). METHODS: This study will search the following electronic databases in MEDLINE, EMBASE, Web of Science, PsycINFO, Cochrane Library, CNKI, and Scopus from the beginning to present without language restrictions. Two authors will screen all records according to the eligibility criteria; assess study quality; and extract all essential data from eligible studies. If sufficient studies are included, we will pool the extracted data and carry out meta-analysis. RESULTS: This study will summarize published studies to assess the efficacy and safety of ventilator for patients with SP. CONCLUSION: The results of this study may supply a genuine understanding of perspective from a scientific basis on ventilator for the management of patients with SP.

Arthroscopic capsular release for the treatment of post-stroke frozen shoulder: A protocol for systematic review.

BACKGROUND: This study will assess the efficacy and safety of arthroscopic capsular release (ACR) for the treatment of post-stroke frozen shoulder (PSFS). METHODS: We will carry out a systematic study of randomized controlled trials that assess the efficacy and safety of ACR for PSFS. We will search all potential records for any eligible trials from selected electronic databases (MEDLINE, EMBASE, Cochrane Library, Web of Science, Chinese Biomedical Literature Database, WANGFANG, and China National Knowledge Infrastructure) and grey literature sources from inception to the present. Two authors will independently perform study selection, data extraction, and study quality assessment. Any disagreement will be solved by a third author via consultation. Statistical analysis will be carried out by RevMan 5.3 software. RESULTS: This study will comprehensively summarize current eligible studies to systematically assess the efficacy and safety of ACR for PSFS. CONCLUSION: This study will provide evidence to determine whether ACR is an effective management for patients with PSFS.

Efficacy of shoulder arthroscopic surgery for the treatment of rotator cuff injury: A protocol of systematic review and meta-analysis.

BACKGROUND: This study will investigate the efficacy and safety of shoulder arthroscopic surgery (SAS) for patients with rotator cuff injury (RCI). METHODS: We will systematically search for randomized controlled trials in the electronic databases of PUBMED, EMBASE, Cochrane Library, CINAHL, PsycINFO, Web of Science, Allied and Complementary Medicine Database, Chinese Biomedical Literature Database, and China National Knowledge Infrastructure. All above databases will be searched from their beginning to March 1, 2020 without language restrictions. Two reviewers will independently scan retrieved records, evaluate study quality and extract data. If possible, we will synthesize the data and conduct a meta-analysis by RevMan 5.3 software. RESULTS: This systematic review will summarize the most recent evidence to explore the efficacy and safety of SAS for patients with RCI. CONCLUSION: The findings of this study will help to provide a genuine understanding of perspective from a scientific basis on the efficacy and safety of SAS for patients with RCI. PROSPERO REGISTRATION NUMBER: PROSPERO CRD42020170009.