Extramedullary relapsed acute lymphoblastic leukemia presenting as asymptomatic acute kidney injury after hematopoietic stem cell transplantation

Acute kidney injury (AKI) is a common complication in children with hematological malignancies. Although AKI due to infiltration of tumor cells in children is rare, it negatively impacts treatment outcomes and increases the risk of mortality. We introduce a case of a child with acute lymphoblastic leukemia (ALL) who experienced kidney relapse resulting in asymptomatic AKI after remission from treatment, to remind clinicians not to overlook the primary disease in clinical judgment. In cases of unexplained AKI, kidney biopsy should be performed when feasible to get an accurate diagnosis and scientific treatment. In brief, children with leukemia who have achieved remission after treatment still need regular monitoring of urine routine and kidney function.

The Evaluation of Generative AI Should Include Repetition to Assess Stability

The increasing interest in the potential applications of generative artificial intelligence (AI) models like ChatGPT in health care has prompted numerous studies to explore its performance in various medical contexts. However, evaluating ChatGPT poses unique challenges due to the inherent randomness in its responses. Unlike traditional AI models, ChatGPT generates different responses for the same input, making it imperative to assess its stability through repetition. This commentary highlights the importance of including repetition in the evaluation of ChatGPT to ensure the reliability of conclusions drawn from its performance. Similar to biological experiments, which often require multiple repetitions for validity, we argue that assessing generative AI models like ChatGPT demands a similar approach. Failure to acknowledge the impact of repetition can lead to biased conclusions and undermine the credibility of research findings. We urge researchers to incorporate appropriate repetition in their studies from the outset and transparently report their methods to enhance the robustness and reproducibility of findings in this rapidly evolving field.

Widespread reductions in cortical thickness following ketamine abuse

BACKGROUND

Esketamine is a version of ketamine that has been approved for treatment-resistant depression, but our previous studies showed a link between non-medical use of ketamine and brain structural and functional alterations, including dorsal prefrontal grey matter reduction among chronic ketamine users. In this study, we sought to determine cortical thickness abnormalities following long-term, non-medical use of ketamine.

METHODS

We acquired structural brain images for patients with ketamine use disorder and drug-free healthy controls. We used FreeSurfer software to measure cortical thickness for 68 brain regions. We compared cortical thickness between the 2 groups using analysis of covariance with covariates of age, gender, educational level, smoking, drinking, and whole-brain mean cortical thickness.

RESULTS

We included images from 95 patients with ketamine use disorder and 169 controls. Compared with healthy controls, patients with ketamine use disorder had widespread decreased cortical thickness, with the most extensive reductions in the frontal (including the dorsolateral prefrontal cortex) and parietal (including the precuneus) lobes. Increased cortical thickness was not observed among ketamine users relative to comparison participants. Estimated total lifetime ketamine consumption was correlated with reductions in the right inferior parietal and the right rostral middle frontal cortical thickness.

LIMITATIONS

We conducted a retrospective cross-sectional study, but longitudinal studies are needed to further validate decreased cortical thickness after nonmedical use of ketamine.

CONCLUSION

This study provided evidence that, compared with healthy controls, chronic ketamine users have widespread reductions in cortical thickness. Our study underscores the importance of the long-term effects of ketamine on brain structure and serves as a reference for the antidepressant use of ketamine.

ChatGPT's ability to generate realistic experimental images poses a new challenge to academic integrity

The rapid advancements in large language models (LLMs) such as ChatGPT have raised concerns about their potential impact on academic integrity. While initial concerns focused on ChatGPT's writing capabilities, recent updates have integrated DALL-E 3's image generation features, extending the risks to visual evidence in biomedical research. Our tests revealed ChatGPT's nearly barrier-free image generation feature can be used to generate experimental result images, such as blood smears, Western Blot, immunofluorescence and so on. Although the current ability of ChatGPT to generate experimental images is limited, the risk of misuse is evident. This development underscores the need for immediate action. We suggest that AI providers restrict the generation of experimental image, develop tools to detect AI-generated images, and consider adding "invisible watermarks" to the generated images. By implementing these measures, we can better ensure the responsible use of AI technology in academic research and maintain the integrity of scientific evidence.

PESSA: A web tool for pathway enrichment score-based survival analysis in cancer

The activation levels of biologically significant gene sets are emerging tumor molecular markers and play an irreplaceable role in the tumor research field; however, web-based tools for prognostic analyses using it as a tumor molecular marker remain scarce. We developed a web-based tool PESSA for survival analysis using gene set activation levels. All data analyses were implemented via R. Activation levels of The Molecular Signatures Database (MSigDB) gene sets were assessed using the single sample gene set enrichment analysis (ssGSEA) method based on data from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), The European Genome-phenome Archive (EGA) and supplementary tables of articles. PESSA was used to perform median and optimal cut-off dichotomous grouping of ssGSEA scores for each dataset, relying on the survival and survminer packages for survival analysis and visualisation. PESSA is an open-access web tool for visualizing the results of tumor prognostic analyses using gene set activation levels. A total of 238 datasets from the GEO, TCGA, EGA, and supplementary tables of articles; covering 51 cancer types and 13 survival outcome types; and 13,434 tumor-related gene sets are obtained from MSigDB for pre-grouping. Users can obtain the results, including Kaplan-Meier analyses based on the median and optimal cut-off values and accompanying visualization plots and the Cox regression analyses of dichotomous and continuous variables, by selecting the gene set markers of interest. PESSA (https://smuonco.shinyapps.io/PESSA/ OR http://robinl-lab.com/PESSA) is a large-scale web-based tumor survival analysis tool covering a large amount of data that creatively uses predefined gene set activation levels as molecular markers of tumors.

Risk factors for Pneumocystis jirovecii pneumonia after kidney transplantation: A systematic review and meta-analysis

BACKGROUND AND OBJECTIVE

Pneumocystis jirovecii pneumonia (PJP), an opportunistic infection, often leads to an increase in hospitalization time and mortality rates in kidney transplant (KT) recipients. However, the risk factors associated with PJP in KT recipients remain debatable. Therefore, we conducted this meta-analysis to identify risk factors for PJP, which could potentially help to reduce PJP incidence and improve outcome of KT recipients.

METHODS

We systematically retrieved relevant studies in PubMed, EMBASE, and the Cochrane Library up to November 2023. Pooled odds ratios (ORs) or mean differences (MDs) and the corresponding 95% confidence intervals (CIs) were calculated to assess the impact of potential risk factors on the occurrence of PJP.

RESULTS

27 studies including 42383 KT recipients were included. In this meta-analysis, age at transplantation (MD = 3.48; 95% CI = .56-6.41; p = .02), cytomegalovirus (CMV) infection (OR = 4.00; 95% CI = 2.53-6.32; p = .001), BK viremia (OR = 3.38; 95% CI = 1.70-6.71; p = .001), acute rejection (OR = 3.66; 95% CI = 2.44-5.49; p = .001), ABO-incompatibility (OR = 2.51; 95% CI = 1.57-4.01; p = .001), estimated glomerular filtration rate (eGFR) (MD = -14.52; 95% CI = -25.37- (-3.67); p = .009), lymphocyte count (MD = -.54; 95% CI = -.92- (-.16); p = .006) and anti-PJP prophylaxis (OR = .53; 95% CI = .28-.98; p = .04) were significantly associated with PJP occurrence.

CONCLUSION

Our findings suggest that transplantation age greater than 50 years old, CMV infection, BK viremia, acute rejection, ABO-incompatibility, decreased eGFR and lymphopenia were risk factors for PJP.

Efficacy of targeted therapy in patients with non-small cell lung cancer harboring very rare mutations in EGFR exon 18

Background

Somatic mutations in epidermal growth factor receptor (EGFR) exon 18 are classified as uncommon or rare mutations in non-small cell lung cancer (NSCLC), in this context, other than G719X or E709X exon 18 mutations are even more rare and heterogeneous. In such scenario, first line treatment options are still debated. The aim of this study was to investigate the response of NSCLC patients harboring very rare exon 18 mutations to EGFR tyrosine kinase inhibitors (EGFR-TKIs).

Methods

This retrospective descriptive study included 105 patients with NSCLC harboring mutations in EGFR exon 18 diagnosed at West China Hospital. The clinical response to EGFR-TKIs was evaluated according to different classifications of mutations in 45 NSCLC patients: 39 harboring G719X or E709X mutations and 6 harboring very rare mutations in EGFR exon 18.

Results

Among 105 patients, 84% (88/105) harbored rare mutations in EGFR exon 18, including G719X and E709X mutations. The remaining 16% (17/105) had very rare mutations in EGFR exon 18, including E709_710delinsX and G724S. For the subsequent efficacy analysis of EGFR-TKI in 45 NSCLC patients, patients harboring very rare mutations achieved a favorable disease control rate (DCR) of 100% and had a median progression-free survival (PFS) of 17.2 months, which was not significantly different compared to patients harboring G719X or E709X (P=0.59).

Conclusions

EGFR-TKIs showed great efficacy in terms of responses and survival in patients harboring exon 18 EGFR rare mutations. This may justify the use of targeted therapies as a potential treatment strategy for these patients.

Immune checkpoint inhibitor plus chemotherapy as first-line treatment for non-small cell lung cancer with malignant pleural effusion: a retrospective multicenter study

BACKGROUND

Immune checkpoint inhibitors (ICI) combined with chemotherapy are efficacious for treating advanced non-small cell lung cancer (NSCLC); however, the effectiveness of this approach in the malignant pleural effusion (MPE) population is unclear. This study evaluated ICI plus chemotherapy in NSCLC patients with MPE.

METHODS

Patients from 3 centers in China with NSCLC and MPE who received ICI plus chemotherapy (ICI Plus Chemo) or chemotherapy alone (Chemo) between December 2014 and June 2023 were enrolled. Clinical outcomes and adverse events (AEs) were compared.

RESULTS

Of 155 eligible patients, the median age was 61.0 years old. Males and never-smokers accounted for 73.5% and 39.4%, respectively. Fifty-seven and 98 patients received ICI Plus Chemo or Chemo, respectively. With a median study follow-up of 10.8 months, progression-free survival (PFS) was significantly longer with ICI Plus Chemo than with Chemo (median PFS: 7.4 versus 5.7 months; HR = 0.594 [95% CI: 0.403-0.874], P = 0.008). Median overall survival (OS) did not differ between groups (ICI Plus Chemo: 34.2 versus Chemo: 28.3 months; HR = 0.746 [95% CI: 0.420-1.325], P = 0.317). The most common grade 3 or worse AEs included decreased neutrophil count (3 [5.3%] patients in the ICI Plus Chemo group vs. 5 [5.1%] patients in the Chemo group) and decreased hemoglobin (3 [5.3%] versus 10 [10.2%]).

CONCLUSIONS

In patients with untreated NSCLC with MPE, ICI plus chemotherapy resulted in significantly longer PFS than chemotherapy and had a manageable tolerability profile, but the effect on OS may be limited.

Measuring Protein-Ligand Binding by Hyperpolarized Ultrafast NMR

Protein-ligand interactions can be detected by observing changes in the transverse relaxation rates of the ligand upon binding. The ultrafast NMR technique, which correlates the chemical shift with the transverse relaxation rate, allows for the simultaneous acquisition of R2 for carbon spins at different positions. In combination with dissolution dynamic nuclear polarization (D-DNP), where the signal intensity is enhanced by thousands of times, the R2 values of several carbon signals from unlabeled benzylamine are observable within a single scan. The hyperpolarized ultrafast chemical shift-R2 correlated experiment separates chemical shift encoding from the readout phase in the NMR pulse sequence, which allows it to beat the fundamental limit on the spectral resolution otherwise imposed by the sampling theorem. Applications enabled by the ability to measure multiple relaxation rates in a single scan include the study of structural properties of protein-ligand interactions.

Experimental Study on the Explosion Parameters of n-Decane Aerosol under Saturated Vapor Pressure

This research aims to conduct a comprehensive investigation and analysis of the effects of particle size and concentration on crucial explosion parameters in n-decane aerosols. Two sets of n-decane aerosols with different concentrations were initially measured, with Sauter mean diameters of 22 and 38 μm, respectively. These measurements served as the foundation for understanding the impact of the particle size on explosion parameters. Subsequently, experiments were performed on n-decane aerosols with various concentrations, utilizing an ignition energy of 40.32 J. The analysis focused on critical explosion parameters including the lower flammability limit, explosion pressure, explosion temperature, and flame propagation delay time. Through thorough examination of the data obtained from these experiments, the research elucidated the relationship between n-decane concentration, particle size, and these explosion parameters.

Cross-domain attention-guided generative data augmentation for medical image analysis with limited data

Data augmentation is widely applied to medical image analysis tasks in limited datasets with imbalanced classes and insufficient annotations. However, traditional augmentation techniques cannot supply extra information, making the performance of diagnosis unsatisfactory. GAN-based generative methods have thus been proposed to obtain additional useful information to realize more effective data augmentation; but existing generative data augmentation techniques mainly encounter two problems: (i) Current generative data augmentation lacks of the capability in using cross-domain differential information to extend limited datasets. (ii) The existing generative methods cannot provide effective supervised information in medical image segmentation tasks. To solve these problems, we propose an attention-guided cross-domain tumor image generation model (CDA-GAN) with an information enhancement strategy. The CDA-GAN can generate diverse samples to expand the scale of datasets, improving the performance of medical image diagnosis and treatment tasks. In particular, we incorporate channel attention into a CycleGAN-based cross-domain generation network that captures inter-domain information and generates positive or negative samples of brain tumors. In addition, we propose a semi-supervised spatial attention strategy to guide spatial information of features at the pixel level in tumor generation. Furthermore, we add spectral normalization to prevent the discriminator from mode collapse and stabilize the training procedure. Finally, to resolve an inapplicability problem in the segmentation task, we further propose an application strategy of using this data augmentation model to achieve more accurate medical image segmentation with limited data. Experimental studies on two public brain tumor datasets (BraTS and TCIA) show that the proposed CDA-GAN model greatly outperforms the state-of-the-art generative data augmentation in both practical medical image classification tasks and segmentation tasks; e.g. CDA-GAN is 0.50%, 1.72%, 2.05%, and 0.21% better than the best SOTA baseline in terms of ACC, AUC, Recall, and F1, respectively, in the classification task of BraTS, while its improvements w.r.t. the best SOTA baseline in terms of Dice, Sens, HD95, and mIOU, in the segmentation task of TCIA are 2.50%, 0.90%, 14.96%, and 4.18%, respectively.

Workplace violence inflicted by patients or their family members/visitors and its relationship with suicidal ideation among undergraduate medical students during clinical training in China

BACKGROUND

Workplace violence in healthcare settings is a significant public concern that profoundly impacts healthcare workers. However, there is a dearth of knowledge regarding the prevalence of workplace violence and its correlation with suicidal ideation among undergraduate medical students in China during their clinical training. The objective of this study was to evaluate the prevalence of workplace violence inflicted by patients or their family members/visitors and to assess its association with suicidal ideation among undergraduate medical students.

METHOD

The snowballing sampling technique was used to recruit Chinese medical students. A question designed by the research team was used to ask medical students about their encounters with workplace violence. Students' basic demographic information and mental distresses (learning burnout, depression symptoms, anxiety symptoms, alcohol abuse/dependence, excessive daytime sleepiness and history of mental disorders) were also assessed. As appropriate, the data were analysed using descriptive statistics, chi-square tests, independent-sample t-tests and multiple logistic regression.

RESULTS

Out of the 1402 undergraduate medical students who participated, 493 (35.2%) reported having experienced workplace violence inflicted by patients or their family members/visitors, of which 394 (28.1%) were verbal abuse, 14 (1.0%) were physical aggression, and 85 (6.1%) were suffered from both verbal abuse and physical aggression. Furthermore, students exposed to workplace violence were more likely to report suicidal ideation and had a higher prevalence of learning burnout, depression symptoms, anxiety symptoms, alcohol abuse/dependence and excessive daytime sleepiness. Depression symptoms, history of mental disorders, learning burnout and having a partner were significantly associated with suicidal ideation in this population.

CONCLUSION

The prevalence of workplace violence inflicted by patients or their family members/visitors was high among undergraduate medical students in China. This may be associated with their mental distress and suicidal ideation. Consequently, it is crucial to strengthen workplace safety measures and promptly implement interventions to mitigate the potentially serious consequences.

Hybrid Reinforced Medical Report Generation With M-Linear Attention and Repetition Penalty

To reduce doctors' workload, deep-learning-based automatic medical report generation has recently attracted more and more research efforts, where deep convolutional neural networks (CNNs) are employed to encode the input images, and recurrent neural networks (RNNs) are used to decode the visual features into medical reports automatically. However, these state-of-the-art methods mainly suffer from three shortcomings: 1) incomprehensive optimization; 2) low-order and unidimensional attention; and 3) repeated generation. In this article, we propose a hybrid reinforced medical report generation method with m-linear attention and repetition penalty mechanism (HReMRG-MR) to overcome these problems. Specifically, a hybrid reward with different weights is employed to remedy the limitations of single-metric-based rewards, and a local optimal weight search algorithm is proposed to significantly reduce the complexity of searching the weights of the rewards from exponential to linear. Furthermore, we use m-linear attention modules to learn multidimensional high-order feature interactions and to achieve multimodal reasoning, while a new repetition penalty is proposed to apply penalties to repeated terms adaptively during the model's training process. Extensive experimental studies on two public benchmark datasets show that HReMRG-MR greatly outperforms the state-of-the-art baselines in terms of all metrics. The effectiveness and necessity of all components in HReMRG-MR are also proved by ablation studies. Additional experiments are further conducted and the results demonstrate that our proposed local optimal weight search algorithm can significantly reduce the search time while maintaining superior medical report generation performances.

A New Method for Discovering Plant Biostimulants

Structurally well-defined compounds have advantages for quality control in plant biostimulant production and application processes. Humic acid (HA) is a biostimulant that significantly affects plant growth, and soil-dwelling Protaetia brevitarsis larva (PBLs) can rapidly convert agricultural waste into HA. In this study, we use PBLs as a model to investigate HA formation and screen for structurally well-defined HA-related plant biostimulant compounds. Dephasing magic angle spinning nuclear magnetic resonance (13C DD-MAS NMR) analysis indicated HA structural changes during PBL digestion; metabolic profiling detected seven HA-related aromatic ring-containing compounds. A total of six compounds that significantly stimulate plant growth were identified through plant experiments, and all six compounds demonstrate the ability to enhance seed germination. It is noteworthy that piperic acid exhibits a remarkable promotion of root growth in plants, a finding reported for the first time in this study. Thus, this study not only provides insights into the insect-mediated transformation of HA but also illustrates a new method for discovering structurally well-defined plant biostimulant compounds.

A novel pathogenic variant c.262delA in PBX1 causing oligomeganephronia identified using whole-exome sequencing and a literature review

Oligomeganephronia (OMN) is a rare congenital renal hypoplasia reported more often in children than in adults. The diagnosis of OMN relies on renal biopsy and exhibits a significant reduction in the number of glomeruli and pronounced glomerular hypertrophy. Here, we report the case of an 8-year-old boy with recurrent proteinuria and abnormal external ears. A renal biopsy revealed large and rare glomeruli. The histological findings confirmed the diagnosis of OMN. Whole-exome sequencing of the patient revealed a new pathogenic variant in PBX1 (hg19, NM_002585, c.262delA, p.Thr88Glnfs*3). The PBX1 gene encodes a transcription factor whose pathogenic variants can result in congenital renal and urinary system anomalies, with or without hearing loss, abnormal ears, and developmental retardation (CAKUTED). This is the first report to detect PBX1 pathogenic variants in children with OMN, a novel phenotype of human PBX1 pathogenic variants. We performed functional prediction analyses of deletions in the corresponding structural domains. We summarized 27 cases of PBX1 single pathogenic variants reported between 2003 and 2023 in terms of truncating and missense pathogenic variants, which can deepen our understanding of the PBX1 structural domain and expand our knowledge of the PBX1 genotype and phenotype.

[Observation on the efficacy of different targets low-frequency repetitive transcranial magnetic stimulation for the treatment of tremor-dominant subtypes of Parkinson's disease]

Objective: To analyze the efficacy of different targets low-frequency repetitive transcranial magnetic stimulation (rTMS) for the treatment of tremor Parkinson's disease(PD). Method: A total of 82 patients with primary PD who were admitted to the Department of Neurology, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from April 1, 2020 to March 31, 2021 were prospectively collected. According to the clinical characteristics of major movement disorders, 82 patients with tremor type (TD) were selected to enroll.The patients were randomly divided into 3 groups at a 1∶1∶1 ratio according to the randomized coding sequence of the trial: the primary motor cortex (M1) group with 26 cases, the cerebellum group with 26 cases and the dual-site (M1, cerebellum) group with 30 cases. All patients were treated with 1 Hz low-frequency stimulation of the corresponding target once a day for 5 days a week for 2 weeks, a total of 10 times; The dosage remained unchanged during the treatment for all groups. Before and after 2 weeks' treatment, the patients were assessed with the Unified PD Rating Scale (UPDRS) and PD Quality of Life Questionnaire-39 (PDQ-39) without medication. Cortical excitability, namely transcranial magnetic stimulation motor evoked potential (TMS-MEP), [including resting motor threshold (rMT) and active motor threshold (aMT) examinations], timed up and go (TUG) and electromyographic tremor were conducted. Result: There were 82 patients, 39 males and 43 females, with an average age of (67±8) years. Before the treatment, there was no statistically significant difference in the evaluation indicators among the three groups (all P>0.05). After the treatment, the differences of the UPDRS-Ⅲ score [(38.9±2.5) vs (29.2±3.6) ], UPDRS tremor score [(23.7±2.1) vs (14.6±3.1) ], TUG time [(44.8±3.1) s vs (33.7±4.1) s], tremor amplitude [(480±126) μV vs (276±94) μV], PDQ-39 score [(51±13) vs (45±13) ], rMT [(36±17)% vs (43±13)%], and aMT [(26±16)% vs (31±12)%] were statistically significant (all P<0.01) from those before the treatment. There was no statistical difference in the above factors between the M1 group and cerebellum group (all P>0.05). There was no statistically significant difference in tremor peak frequency among the three groups before and after the treatment (all P>0.05). Conclusions: Dual-site low-frequency rTMS can improve PD tremor, while M1 or cerebellar low-frequency rTMS does not significantly improve PD tremor. Its mechanism may be to improve PD tremor symptoms by regulating cortical excitability.

Gender differences in alcohol abuse/dependence among medical undergraduates during the post-COVID‑19 pandemic period (October 20, 2020-April 5, 2021) in China

BACKGROUND

This study aimed to assess the prevalence and the gender-specific risk factors of alcohol abuse/dependence among medical undergraduates during the post-COVID‑19 pandemic period in China.

METHOD

The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) was used to identify respondents with alcohol abuse/dependence. A questionnaire on basic demographics and mental distresses (learning burnout, depression symptoms, anxiety symptoms, excessive daytime sleepiness, and history of mental disorders) was used. The logistic regression model was used to explore the associations between the above characteristics and alcohol abuse/dependence.

RESULTS

A total of 3,412 medical undergraduates were included in the analysis. Males showed a higher prevalence of alcohol abuse/dependence than females (16.6% vs 7.4%, p < 0.001). Alcohol abuse/dependence was associated with learning burnout (OR: 2.168, p < 0.001) and having a partner (OR: 1.788 p = 0.001) among female medical undergraduates. Among male medical undergraduates, excessive daytime sleepiness (OR: 1.788 p = 0.001) and older age (OR: 1.788, p = 0.001) were independently associated with alcohol abuse/dependence.

CONCLUSION

Alcohol abuse/dependence was common among medical undergraduates during the post-COVID‑19 pandemic period. Substantial gender differences in the prevalence and risk factors of alcohol abuse/dependence were found among medical undergraduates in this study, which highlighted the need for timely gender-specific screening and interventions. However, the cross-sectional design adopted in this study has limited the examination of causality, thus further longitudinal studies are warranted.

Measurement of oesophageal hiatus surface area by multiplanar reconstruction of MDCT: relationship with lower oesophageal sphincter pressure and acid reflux

AIM

To evaluate the relationship between oesophageal hiatus surface area (OHSA) and gastro-oesophageal reflux disease (GERD).

MATERIALS AND METHODS

Patients who underwent 24-h pH monitoring, oesophageal high-resolution manometry, and upper abdominal contrast-enhanced multidetector computed tomography (MDCT) during 2014-2021 were enrolled. Patients with a hiatus hernia (HH) on MDCT or who had a history of gastro-oesophageal surgery were excluded. Multiplanar reconstruction (MPR) of the MDCT image was used for the measurement of OHSA. Correlations of OHSA with acid exposure time (AET) and lower oesophageal sphincter (LOS) pressure of all patients were analysed.

RESULTS

Seventy-eight patients were included in the study. OHSA was much less in the AET <4% group than in the AET >6% group (1.61 ± 0.42 versus 2.09 ± 0.55 cm2, p<0.001). Correlation analysis reveals that OHSA correlated positively with AET (correlation coefficient = 0.47, p<0.001). Receiver operating characteristic (ROC) curve analysis reveals that OHSA can significantly distinguish patients in different groups divided by AET (area under the ROC curve [AUC] = 0.76, 95% confidence interval [CI]: 0.63-0.90). OHSA was not related to LOS pressure (correlation coefficient = -0.268, p=0.051). There was no difference in OHSA between the low LOS pressure group and the normal LOS pressure group (1.84 ± 0.61 versus 1.74 ± 0.50 cm2, p=0.52).

CONCLUSIONS

OHSA significantly correlated with AET but has no relationship with LOS pressure. It may be an independent risk factor of GERD.

Value of peripheral blood circulating tumor cell detection in the diagnosis of thoracic diseases and the prediction of severity

Circulating tumor cell (CTC) detection, as a noninvasive liquid biopsy method, has been used in the diagnosis, prognostic indication, and monitoring of a variety of cancers. In this study, we aimed to investigate whether CTC detection could be used in the early diagnosis and prediction of severity of thoracic diseases. We enrolled 168 thoracic disease patients, all of whom underwent pathological biopsy. Carcinoembryonic antigen (CEA) and neuron-specific enolase (NSE) measurement was also performed in 146 patients. There were 131 cases of malignant thoracic diseases and 37 cases of benign lesions. We detected CTCs in a 5 ml peripheral blood sample with the CTCBiopsy® system and analyzed the value of CTC count for predicting disease severity. Of 131 patients with a diagnosis of thoracic malignancy, CTCs were found in blood samples from 122 patients. However, only 2 out of 37 patients with benign thoracic disease had no detectable CTCs. There was no significant correlation between CTC count and benign and malignant lesions (P = 0.986). However, among 131 patients who had been diagnosed with malignant lesions, 33 had lymph node metastasis or distant metastasis. The presence of CTCs was significantly correlated with metastasis (P = 0.016 OR = 1.14). The area under the receiver operating characteristic (ROC) curve was 0.625 (95% confidence interval (CI), 0.519 to 0.730 P = 0.032). In addition, with stage IA1 as the cutoff, all patients were further divided into an early-stage group and a late-stage group. CTC count was significantly correlated with disease progression (P = 0.031 OR = 1.11), with an area under the curve (AUC) of 0.599 (95% CI, 0.506-0.692 P = 0.47). The sensitivity and specificity of CTC detection for the diagnosis of disease stage were 72.3% and 45.5%, respectively. In addition, the cutoff of 2.5 CTCs was the same when predicting disease metastasis and staging. Furthermore, the combination of CTC count, demographic characteristics and tumor markers had better predictive significance for disease staging. CTC count can effectively indicate the stages and metastasis of thoracic diseases, but it cannot differentiate benign and malignant diseases.

Potential benefits and risks of solar photovoltaic power plants on arid and semi-arid ecosystems: an assessment of soil microbial and plant communities

Exponential increase in photovoltaic installations arouses concerns regarding the impacts of large-scale solar power plants on dryland ecosystems. While the effects of photovoltaic panels on soil moisture content and plant biomass in arid ecosystems have been recognized, little is known about their influence on soil microbial communities. Here, we employed a combination of quantitative PCR, high-throughput sequencing, and soil property analysis to investigate the responses of soil microbial communities to solar panel installation. We also report on the responses of plant communities within the same solar farm. Our findings showed that soil microbial communities responded differently to the shading and precipitation-alternation effects of the photovoltaic panels in an arid ecosystem. By redirecting rainwater to the lower side, photovoltaic panels stimulated vegetation biomass and soil total organic carbon content in the middle and in front of the panels, positively contributing to carbon storage. The shade provided by the panels promoted the co-occurrence of soil microbes but inhibited the abundance of 16S rRNA gene in the soil. Increase in precipitation reduced 18S rRNA gene abundance, whereas decrease in precipitation led to decline in plant aboveground biomass, soil prokaryotic community alpha diversity, and dehydrogenase activity under the panels. These findings highlight the crucial role of precipitation in maintaining plant and soil microbial diversities in dryland ecosystems and are essential for estimating the potential risks of large-scale solar power plants on local and global climate change in the long term.

Estimation of the relationship between meteorological factors and measles using spatiotemporal Bayesian model in Shandong Province, China

BACKGROUND

Measles-containing vaccine (MCV) has been effective in controlling the spread of measles. Some countries have declared measles elimination. But recently years, the number of cases worldwide has increased, posing a challenge to the global goal of measles eradication. This study estimated the relationship between meteorological factors and measles using spatiotemporal Bayesian model, aiming to provide scientific evidence for public health policy to eliminate measles.

METHODS

Descriptive statistical analysis was performed on monthly data of measles and meteorological variables in 136 counties of Shandong Province from 2009 to 2017. Spatiotemporal Bayesian model was used to estimate the effects of meteorological factors on measles, and to evaluate measles risk areas at county level. Case population was divided into multiple subgroups according to gender, age and occupation. The effects of meteorological factors on measles in subgroups were compared.

RESULTS

Specific meteorological conditions increased the risk of measles, including lower relative humidity, temperature, and atmospheric pressure; higher wind velocity, sunshine duration, and diurnal temperature variation. Taking lowest value (Q1) as reference, RR (95%CI) for higher temperatures (Q2-Q4) were 0.79 (0.69-0.91), 0.54 (0.44-0.65), and 0.48 (0.38-0.61), respectively; RR (95%CI) for higher relative humidity (Q2-Q4) were 0.76 (0.66-0.88), 0.56 (0.47-0.67), and 0.49 (0.38-0.63), respectively; RR (95%CI) for higher wind velocity (Q2-Q4) were 1.43 (1.25-1.64), 1.85 (1.57-2.18), 2.00 (1.59-2.52), respectively. 22 medium-to-high risk counties were identified, mainly in northwestern, southwestern and central Shandong Province. The trend was basically same in the effects of meteorological factors on measles in subgroups, but the magnitude of the effects was different.

CONCLUSIONS

Meteorological factors have an important impact on measles. It is crucial to integrate these factors into public health policies for measles prevention and control in China.

Observation of a Strongly Isospin-Mixed Doublet in ^{26}Si via β-Delayed Two-Proton Decay of ^{26}P

β decay of proton-rich nuclei plays an important role in exploring isospin mixing. The β decay of ^{26}P at the proton drip line is studied using double-sided silicon strip detectors operating in conjunction with high-purity germanium detectors. The T=2 isobaric analog state (IAS) at 13 055 keV and two new high-lying states at 13 380 and 11 912 keV in ^{26}Si are unambiguously identified through β-delayed two-proton emission (β2p). Angular correlations of two protons emitted from ^{26}Si excited states populated by ^{26}P β decay are measured, which suggests that the two protons are emitted mainly sequentially. We report the first observation of a strongly isospin-mixed doublet that deexcites mainly via two-proton decay. The isospin mixing matrix element between the ^{26}Si IAS and the nearby 13 380-keV state is determined to be 130(21) keV, and this result represents the strongest mixing, highest excitation energy, and largest level spacing of a doublet ever observed in β-decay experiments.

Challenges of COPD Patients during the COVID-19 Pandemic

Coronavirus disease 2019 (COVID-19) is a severe systemic infection that is a major threat to healthcare systems worldwide. According to studies, chronic obstructive pulmonary disease (COPD) patients with COVID-19 usually have a high risk of developing severe symptoms and fatality, but limited research has addressed the poor condition of COPD patients during the pandemic. This review focuses on the underlying risk factors including innate immune dysfunction, angiotensin converting enzyme 2 (ACE2) expression, smoking status, precocious differentiation of T lymphocytes and immunosenescence in COPD patients which might account for their poor outcomes during the COVID-19 crisis. Furthermore, we highlight the role of aging of the immune system, which may be the culprit of COVID-19. In brief, we list the challenges of COPD patients in this national pandemic, aiming to provide immune-related considerations to support critical processes in COPD patients during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and inspire immune therapy for these patients.