Ecological investigations of giant Phaeocystis colonies in Viet Nam: I. Cell abundance and elemental composition.

Phaeocystis globosa is an important bloom-forming marine phytoplankton species that often accumulates to large levels in temperate and tropical waters and has significant impacts on food webs and biogeochemical cycles. It can form "giant" colonies that reach 3 cm in diameter. Microscopic observations, colony elemental composition, and pigment composition were analyzed to assess the characteristics of colonies as a function of colony size. Particulate organic carbon (POC) per unit surface area, colonial cell density, and chlorophyll a per unit surface area all increased with colony size, in contrast to results from temperate waters. Cellular chl a averaged 0.85 pg chl · cell-1. Colonies had both photosynthetic and protective pigments, with fucoxanthin being the dominant accessory pigment. Based on chl a and pigment levels, it appears colonies were acclimated to relatively low irradiances, likely due to their life cycle and the extremely turbulent environment in which they grew. Mucous carbon ranged from 16.2% to 79.2% of the total POC, and mucous carbon per unit surface area increased with colony size, suggesting that the mucous envelope did not thin as the colony grew. Based on elemental composition, nitrogen did not appear to limit growth, but phosphorus:carbon ratios were similar to those of P-limited cultures. Giant colonies represent an extreme response to the environment, but they do not appear to have greatly different characteristics than other tropical strains.

Long-term associations of PM1 versus PM2.5 and PM10 with asthma and asthma-related respiratory symptoms in the middle-aged and elderly population.

Background: Few studies have compared the associations between long-term exposures to particulate matters (aerodynamic diameter ≤1, ≤2.5 and ≤10 µm: PM1, PM2.5 and PM10, respectively) and asthma and asthma-related respiratory symptoms. The objective of the present study was to compare the strength of the aforementioned associations in middle-aged and elderly adults. Methods: We calculated the mean 722-day personal exposure estimates of PM1, PM2.5 and PM10 at 1 km×1 km spatial resolution between 2013 and 2019 at individual levels from China High Air Pollutants (CHAP) datasets. Using logistic regression models, we presented the associations as odds ratios and 95% confidence intervals, for each interquartile range (IQR) increase in PM1/PM2.5/PM10 concentration. Asthma denoted a self-reported history of physician-diagnosed asthma or wheezing in the preceding 12 months. Results: We included 7371 participants in COPD surveillance from Guangdong, China. Each IQR increase in PM1, PM2.5 and PM10 was associated with a greater odds (OR (95% CI)) of asthma (PM1: 1.22 (1.02-1.45); PM2.5: 1.24 (1.04-1.48); PM10: 1.30 (1.07-1.57)), wheeze (PM1: 1.27 (1.11-1.44); PM2.5: 1.30 (1.14-1.48); PM10: 1.34 (1.17-1.55)), persistent cough (PM1: 1.33 (1.06-1.66); PM2.5: 1.36 (1.09-1.71); PM10: 1.31 (1.02-1.68)) and dyspnoea (PM1: 2.10 (1.84-2.41); PM2.5: 2.17 (1.90-2.48); PM10: 2.29 (1.96-2.66)). Sensitivity analysis results were robust after excluding individuals with a family history of allergy. Associations of PM1, PM2.5 and PM10 with asthma and asthma-related respiratory symptoms were slightly stronger in males. Conclusion: Long-term exposure to PM is associated with increased risks of asthma and asthma-related respiratory symptoms.

Effects of starting one lung ventilation and applying individualized PEEP right after patients are placed in lateral decubitus position on intraoperative oxygenation for patients undergoing thoracoscopic pulmonary lobectomy: study protocol for a randomized controlled trial.

BACKGROUND: For patients receiving one lung ventilation in thoracic surgery, numerous studies have proved the superiority of lung protective ventilation of low tidal volume combined with recruitment maneuvers (RM) and individualized PEEP. However, RM may lead to overinflation which aggravates lung injury and intrapulmonary shunt. According to CT results, atelectasis usually forms in gravity dependent lung regions, regardless of body position. So, during anesthesia induction in supine position, atelectasis usually forms in the dorsal parts of lungs, however, when patients are turned into lateral decubitus position, collapsed lung tissue in the dorsal parts would reexpand, while atelectasis would slowly reappear in the lower flank of the lung. We hypothesize that applying sufficient PEEP without RM before the formation of atelectasis in the lower flank of the lung may beas effective to prevent atelectasis and thus improve oxygenation as applying PEEP with RM. METHODS: A total of 84 patients scheduled for elective pulmonary lobe resection necessitating one lung ventilation will be recruited and randomized totwo parallel groups. For all patients, one lung ventilation is initiated the right after patients are turned into lateral decubitus position. For patients in the study group, individualized PEEP titration is started the moment one lung ventilation is started, while patients in the control group will receive a recruitment maneuver followed by individualized PEEP titration after initiation of one lung ventilation. The primary endpoint will be oxygenation index measured at T4. Secondary endpoints will include intrapulmonary shunt, respiratory mechanics, PPCs, and hemodynamic indicators. DISCUSSION: Numerous previous studies compared the effects of individualized PEEP applied alone with that applied in combination with RM on oxygenation index, PPCs, intrapulmonary shunt and respiratory mechanics after atelectasis was formed in patients receiving one lung ventilation during thoracoscopic surgery. In this study, we will apply individualized PEEP before the formation of atelectasis while not performing RM in patients allocated to the study group, and then we're going to observe its effects on the aspects mentioned above. The results of this trial will provide a ventilation strategy that may be conductive to improving intraoperative oxygenation and avoiding the detrimental effects of RM for patients receiving one lung ventilation. TRIAL REGISTRATION: www.Chictr.org.cn ChiCTR2400080682. Registered on February 5, 2024.

A new artificial intelligence system for both stomach and small bowel capsule endoscopy.

BACKGROUND AND AIMS: Despite the benefits of artificial intelligence (AI) in small bowel (SB) capsule endoscopy (CE) image reading, information on its application in the stomach and SB CE is lacking. METHODS: In this multicenter, retrospective diagnostic study, gastric imaging data were added to the deep learning (DL)-based SmartScan (SS), which has been described previously. A total of 1,069 magnetically controlled gastrointestinal (GI) CE examinations (comprising 2,672,542 gastric images) were used in the training phase for recognizing gastric pathologies, producing a new AI algorithm named SS Plus. 342 fully automated, magnetically controlled CE (FAMCE) examinations were included in the validation phase. The performance of both senior and junior endoscopists with both the SS Plus-Assisted Reading (SSP-AR) and conventional reading (CR) modes was assessed. RESULTS: SS Plus was designed to recognize 5 types of gastric lesions and 17 types of SB lesions. SS Plus reduced the number of CE images required for review to 873.90 (1000) (median, IQR 814.50-1,000) versus 44,322.73 (42,393) (median, IQR 31,722.75-54,971.25) for CR. Furthermore, with SSP-AR, endoscopists took 9.54 min (8.51) (median, IQR 6.05-13.13) to complete the CE video reading. In the 342 CE videos, SS Plus identified 411 gastric and 422 SB lesions, whereas 400 gastric and 368 intestinal lesions were detected with CR. Moreover, junior endoscopists remarkably improved their CE image reading ability with SSP-AR. CONCLUSIONS: Our study shows that the newly upgraded DL-based algorithm SS Plus can detect GI lesions and help improve the diagnostic performance of junior endoscopists in interpreting CE videos.

Telehealth With Comprehensive Live-Fed Real-World Data as a Patient Care Platform for Lung Cancer: Implementation and Evaluation Study.

BACKGROUND: Telehealth has emerged as a popular channel for providing outpatient services in many countries. However, the majority of telehealth systems focus on operational functions and offer only a sectional patient journey at most. Experiences with incorporating longitudinal real-world medical record data into telehealth are valuable but have not been widely shared. The feasibility and usability of such a telehealth platform, with comprehensive, real-world data via a live feed, for cancer patient care are yet to be studied. OBJECTIVE: The primary purpose of this study is to understand the feasibility and usability of cancer patient care using a telehealth platform with longitudinal, real-world data via a live feed as a supplement to hospital electronic medical record systems specifically from physician's perspective. METHODS: A telehealth platform was constructed and launched for both physicians and patients. Real-world data were collected and curated using a comprehensive data model. Physician activities on the platform were recorded as system logs and analyzed. In February 2023, a survey was conducted among the platform's registered physicians to assess the specific areas of patient care and to quantify their before and after experiences, including the number of patients managed, time spent, dropout rate, visit rate, and follow-up data. Descriptive and inferential statistical analyses were performed on the data sets. RESULTS: Over a period of 15 months, 16,035 unique users (13,888 patients, 1539 friends and family members, and 174 physician groups with 608 individuals) registered on the platform. More than 382,000 messages including text, reminders, and pictures were generated by physicians when communicating with patients. The survey was completed by 78 group leaders (45% of the 174 physician groups). Of the participants, 84% (65.6/78; SD 8.7) reported a positive experience, with efficient communication, remote supervision, quicker response to questions, adverse event prevention, more complete follow-up data, patient risk reduction, cross-organization collaboration, and a reduction in in-person visits. The majority of the participants (59/78, 76% to 76/78, 97.4%) estimated improvements in time spent, number of patients managed, the drop-off rate, and access to medical history, with the average ranging from 57% to 105%. When compared with prior platforms, responses from physicians indicated better experiences in terms of time spent, the drop-off rate, and medical history, while the number of patients managed did not significantly change. CONCLUSIONS: This study suggests that a telehealth platform, equipped with comprehensive, real-world data via a live feed, is feasible and effective for cancer patient care. It enhances inpatient management by improving time efficiencies, reducing drop-off rates, and providing easy access to medical history. Moreover, it fosters a positive experience in physician-patient interactions.

Cross-site validation of lung cancer diagnosis by electronic nose with deep learning: a multicenter prospective study.

BACKGROUND: Although electronic nose (eNose) has been intensively investigated for diagnosing lung cancer, cross-site validation remains a major obstacle to be overcome and no studies have yet been performed. METHODS: Patients with lung cancer, as well as healthy control and diseased control groups, were prospectively recruited from two referral centers between 2019 and 2022. Deep learning models for detecting lung cancer with eNose breathprint were developed using training cohort from one site and then tested on cohort from the other site. Semi-Supervised Domain-Generalized (Semi-DG) Augmentation (SDA) and Noise-Shift Augmentation (NSA) methods with or without fine-tuning was applied to improve performance. RESULTS: In this study, 231 participants were enrolled, comprising a training/validation cohort of 168 individuals (90 with lung cancer, 16 healthy controls, and 62 diseased controls) and a test cohort of 63 individuals (28 with lung cancer, 10 healthy controls, and 25 diseased controls). The model has satisfactory results in the validation cohort from the same hospital while directly applying the trained model to the test cohort yielded suboptimal results (AUC, 0.61, 95% CI: 0.47─0.76). The performance improved after applying data augmentation methods in the training cohort (SDA, AUC: 0.89 [0.81─0.97]; NSA, AUC:0.90 [0.89─1.00]). Additionally, after applying fine-tuning methods, the performance further improved (SDA plus fine-tuning, AUC:0.95 [0.89─1.00]; NSA plus fine-tuning, AUC:0.95 [0.90─1.00]). CONCLUSION: Our study revealed that deep learning models developed for eNose breathprint can achieve cross-site validation with data augmentation and fine-tuning. Accordingly, eNose breathprints emerge as a convenient, non-invasive, and potentially generalizable solution for lung cancer detection. CLINICAL TRIAL REGISTRATION: This study is not a clinical trial and was therefore not registered.

Effectiveness and safety of vedolizumab and infliximab in biologic-naïve patients with moderate-to-severe ulcerative colitis: A multicenter, retrospective cohort study.

OBJECTIVES: We conducted this multicenter, retrospective cohort study aiming to evaluate the effectiveness and safety of vedolizumab (VDZ) and infliximab (IFX) in biologic-naïve patients with moderate-to-severe ulcerative colitis (UC). METHODS: Biologic-naïve patients with moderate-to-severe UC who were treated with IFX or VDZ for at least 14 weeks at three tertiary hospitals in southwest China between January 2021 and January 2023 were retrospectively included. Efficacy of the biologics was evaluated based on the steroid-free clinical remission rate, clinical remission rate, and mucosal healing rate at Weeks 14 and 52. Adverse events related to biologic use were recorded. RESULTS: Altogether 122 biologic-naïve patients with moderate-to-severe UC were included. No marked differences in the steroid-free clinical remission rate and clinical remission rate were observed between the two groups at Week 14 or Week 52 (P > 0.05). The VDZ group exhibited a higher mucosal healing rate at Week 14 compared to the IFX group (33.3% vs 16.9%, P = 0.036), while that at Week 52 did not differ between the two groups (65.6% vs 47.1%, P = 0.098). There was no statistically significant difference in the rate of adverse events between the two groups (P = 0.071). CONCLUSION: VDZ and IFX showed comparable clinical efficacy and safety profiles and can be used as viable first-line therapeutic options for biologic-naïve patients with moderate-to-severe UC.

Sputum bacterial microbiota signature as a surrogate for predicting disease progression of nontuberculous mycobacterial lung disease.

OBJECTIVES: Predicting progression of nontuberculous mycobacterial lung disease (NTM-LD) remains challenging. This study evaluated whether sputum bacterial microbiome diversity can be the biomarker and provide novel insights into related phenotypes and treatment timing. METHODS: We analyzed 126 sputum microbiomes of 126 patients with newly diagnosed NTM-LD due to Mycobacterium avium complex, M. abscessus complex, and M. kansasii between May 2020 and December 2021. Patients were followed for 2 years to determine their disease progression status. We identified consistently representative genera that differentiated the progressor and nonprogressor by using six methodologies. These genera were used to construct a prediction model using random forest with 5-fold cross validation. RESULTS: Disease progression occurred in 49 (38.6%) patients. Compared with nonprogressors, α-diversity was lower in the progressors. Significant compositional differences existed in the ß-diversity between groups (p=0.001). The prediction model for NTM-LD progression constructed using seven genera (Burkholderia, Pseudomonas, Sphingomonas, Candidatus Saccharibacteria, Phocaeicola, Pelomonas, and Phascolarctobacterium) with significantly differential abundance achieved an area under curve of 0.871. CONCLUSIONS: Identification of the composition of sputum bacterial microbiome facilitates prediction of the course of NTM-LD, and maybe used to develop precision treatment involving modulating the respiratory microbiome composition to ameliorate NTM-LD.

USP9X-mediated REV1 deubiquitination promotes lung cancer radioresistance via the action of REV1 as a Rad18 molecular scaffold for cystathionine γ-lyase.

BACKGROUND: Radioresistance is a key clinical constraint on the efficacy of radiotherapy in lung cancer patients. REV1 DNA directed polymerase (REV1) plays an important role in repairing DNA damage and maintaining genomic stability. However, its role in the resistance to radiotherapy in lung cancer is not clear. This study aims to clarify the role of REV1 in lung cancer radioresistance, identify the intrinsic mechanisms involved, and provide a theoretical basis for the clinical translation of this new target for lung cancer treatment. METHODS: The effect of targeting REV1 on the radiosensitivity was verified by in vivo and in vitro experiments. RNA sequencing (RNA-seq) combined with nontargeted metabolomics analysis was used to explore the downstream targets of REV1. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to quantify the content of specific amino acids. The coimmunoprecipitation (co-IP) and GST pull-down assays were used to validate the interaction between proteins. A ubiquitination library screening system was constructed to investigate the regulatory proteins upstream of REV1. RESULTS: Targeting REV1 could enhance the radiosensitivity in vivo, while this effect was not obvious in vitro. RNA sequencing combined with nontargeted metabolomics revealed that the difference result was related to metabolism, and that the expression of glycine, serine, and threonine (Gly/Ser/Thr) metabolism signaling pathways was downregulated following REV1 knockdown. LC-MS/MS demonstrated that REV1 knockdown results in reduced levels of these three amino acids and that cystathionine γ-lyase (CTH) was the key to its function. REV1 enhances the interaction of CTH with the E3 ubiquitin ligase Rad18 and promotes ubiquitination degradation of CTH by Rad18. Screening of the ubiquitination compound library revealed that the ubiquitin-specific peptidase 9 X-linked (USP9X) is the upstream regulatory protein of REV1 by the ubiquitin-proteasome system, which remodels the intracellular Gly/Ser/Thr metabolism. CONCLUSION: USP9X mediates the deubiquitination of REV1, and aberrantly expressed REV1 acts as a scaffolding protein to assist Rad18 in interacting with CTH, promoting the ubiquitination and degradation of CTH and inducing remodeling of the Gly/Ser/Thr metabolism, which leads to radioresistance. A novel inhibitor of REV1, JH-RE-06, was shown to enhance lung cancer cell radiosensitivity, with good prospects for clinical translation.

Strain-induced ferroelectric polarization reversal without undergoing geometric inversion in blue SiSe monolayer.

Ferroelectricity in two-dimensional (2D) systems generally arises from phonons and has been widely investigated. On the contrary, electronic ferroelectricity in 2D systems has been rarely studied. Using first-principles calculations, the ferroelectric behavior of the buckled blue SiSe monolayer under strain are explored. It is found that the direction of the out-of-plane ferroelectric polarization can be reversed by applying an in-plane strain. And such polarization switching is realized without undergoing geometric inversion. Besides, the strain-triggered polarization reversal emerges in both biaxial and uniaxial strain cases, indicating it is an intrinsic feature of such a system. Further analysis shows that the polarization switching is the result of the reversal of the magnitudes of the positive and negative charge center vectors. And the variation of buckling is found to play an important role, which results in the switch. Moreover, a non-monotonic variation of band gap with strain is revealed. Our findings throws light on the investigation of novel electronic ferroelectric systems.

Protocol for quantitative evaluation of misfolded protein degradation using Agrobacterium-mediated expression system in Nicotiana benthamiana.

Cellular protein homeostasis is maintained by the disposal of aggregated misfolded proteins. Here, we present a protocol for investigating the involvement of the proteins of interest in misfolded protein degradation via Agrobacterium-mediated transient expression in Nicotiana benthamiana. We describe in detail the steps of misfolded protein design, transient protein expression in N. benthamiana, subsequent total protein extraction, and quantification of misfolded proteins through western blotting. This generalizable system can be used for misfolded proteins derived from various plants or microbes. For complete details on the use and execution of this protocol, please refer to Ai et al.1.

A study on expression recognition based on improved mobilenetV2 network.

This paper proposes an improved strategy for the MobileNetV2 neural network(I-MobileNetV2) in response to problems such as large parameter quantities in existing deep convolutional neural networks and the shortcomings of the lightweight neural network MobileNetV2 such as easy loss of feature information, poor real-time performance, and low accuracy rate in facial emotion recognition tasks. The network inherits the characteristics of MobilenetV2 depthwise separated convolution, signifying a reduction in computational load while maintaining a lightweight profile. It utilizes a reverse fusion mechanism to retain negative features, which makes the information less likely to be lost. The SELU activation function is used to replace the RELU6 activation function to avoid gradient vanishing. Meanwhile, to improve the feature recognition capability, the channel attention mechanism (Squeeze-and-Excitation Networks (SE-Net)) is integrated into the MobilenetV2 network. Experiments conducted on the facial expression datasets FER2013 and CK + showed that the proposed network model achieved facial expression recognition accuracies of 68.62% and 95.96%, improving upon the MobileNetV2 model by 0.72% and 6.14% respectively, and the parameter count decreased by 83.8%. These results empirically verify the effectiveness of the improvements made to the network model.

Bayesian inference of structured latent spaces from neural population activity with the orthogonal stochastic linear mixing model.

The brain produces diverse functions, from perceiving sounds to producing arm reaches, through the collective activity of populations of many neurons. Determining if and how the features of these exogenous variables (e.g., sound frequency, reach angle) are reflected in population neural activity is important for understanding how the brain operates. Often, high-dimensional neural population activity is confined to low-dimensional latent spaces. However, many current methods fail to extract latent spaces that are clearly structured by exogenous variables. This has contributed to a debate about whether or not brains should be thought of as dynamical systems or representational systems. Here, we developed a new latent process Bayesian regression framework, the orthogonal stochastic linear mixing model (OSLMM) which introduces an orthogonality constraint amongst time-varying mixture coefficients, and provide Markov chain Monte Carlo inference procedures. We demonstrate superior performance of OSLMM on latent trajectory recovery in synthetic experiments and show superior computational efficiency and prediction performance on several real-world benchmark data sets. We primarily focus on demonstrating the utility of OSLMM in two neural data sets: µECoG recordings from rat auditory cortex during presentation of pure tones and multi-single unit recordings form monkey motor cortex during complex arm reaching. We show that OSLMM achieves superior or comparable predictive accuracy of neural data and decoding of external variables (e.g., reach velocity). Most importantly, in both experimental contexts, we demonstrate that OSLMM latent trajectories directly reflect features of the sounds and reaches, demonstrating that neural dynamics are structured by neural representations. Together, these results demonstrate that OSLMM will be useful for the analysis of diverse, large-scale biological time-series datasets.

Prevalence of depressive symptoms in patients with advanced schistosomiasis in China: A systematic review and meta-analysis.

BACKGROUND: Advanced schistosomiasis is the most serious outcome of infection and has a negative impact on both physical fitness and mental health of patients, the latter of which has long been overlooked. Therefore, we performed this systematic review and meta-analysis to estimate the overall prevalence of depressive symptoms, one of the most common mental problems, in patients with advanced schistosomiasis in China. METHODS: Six electronic databases were searched for studies reporting the prevalence of depressive symptoms in the targeted patients. Assessments were pooled using a fixed- or random-effects model based on heterogeneity test. Subgroup analyses were further performed and differences between/among groups were examined using the chi-squared test. The protocol had previously been registered in PROSPERO (CRD42023406708). RESULTS: A total of 11 studies with 1,673 participants were included. The pooled prevalence of depressive symptoms in advanced schistosomiasis in China was 62.01% (95% CI: 51.30% - 72.72%), with a significant heterogeneity among studies. Depressive symptoms were more prevalent in patients with complications and more than half of the patients suffered a mild- or moderate-level of depression. No publication bias was found, and sensitivity analysis showed a stable result. CONCLUSIONS: The overall prevalence of depressive symptoms in advanced schistosomiasis in China was high enough to warrant psychotherapeutic interventions, especially for patients with complications. This would greatly prevent or/and reduce depression and improve their quality of life.

Computer-Vision-Based Sensing Technologies for Livestock Body Dimension Measurement: A Survey.

Livestock's live body dimensions are a pivotal indicator of economic output. Manual measurement is labor-intensive and time-consuming, often eliciting stress responses in the livestock. With the advancement of computer technology, the techniques for livestock live body dimension measurement have progressed rapidly, yielding significant research achievements. This paper presents a comprehensive review of the recent advancements in livestock live body dimension measurement, emphasizing the crucial role of computer-vision-based sensors. The discussion covers three main aspects: sensing data acquisition, sensing data processing, and sensing data analysis. The common techniques and measurement procedures in, and the current research status of, live body dimension measurement are introduced, along with a comparative analysis of their respective merits and drawbacks. Livestock data acquisition is the initial phase of live body dimension measurement, where sensors are employed as data collection equipment to obtain information conducive to precise measurements. Subsequently, the acquired data undergo processing, leveraging techniques such as 3D vision technology, computer graphics, image processing, and deep learning to calculate the measurements accurately. Lastly, this paper addresses the existing challenges within the domain of livestock live body dimension measurement in the livestock industry, highlighting the potential contributions of computer-vision-based sensors. Moreover, it predicts the potential development trends in the realm of high-throughput live body dimension measurement techniques for livestock.

Single-cell and multi-omics analyses highlight cancer-associated fibroblasts-induced immune evasion and epithelial mesenchymal transition for smoking bladder cancer.

Tobacco carcinogens are recognized as critical hazard factors for bladder tumorigenesis, affecting the prognosis of patients through aromatic amines components. However, the specific function of tobacco carcinogens and systematic assessment models in the prognosis of bladder cancer remains poorly elucidated. We retrieved bladder cancer specific tobacco carcinogens-related genes from Comparative Toxicogenomic Database, our Nanjing Bladder Cancer cohort and TCGA database. Gene×Gene interaction method was utilized to establish a prognostic signature. Integrative assessment of immunogenomics, tumor microenvironments and single-cell RNA-sequencing were performed to illustrate the internal relations of key events from different levels. Finally, we comprehensively identified 33 essential tobacco carcinogens-related genes to construct a novel prognostic signature, and found that high-risk patients were characterized by significantly worse overall survival (HR=2.25; Plog-rank < 0.01). Single-cell RNA-sequencing and multi-omics analysis demonstrated that cancer-associated fibroblasts mediated the crosstalk between epithelial-mesenchymal transition progression and immune evasion. Moreover, an adverse outcome pathway framework was established to facilitate our understanding to the tobacco carcinogens-triggered bladder tumorigenesis. Our study systematically provided immune microenvironmental alternations for smoking-induced adverse survival outcomes in bladder cancer. These findings facilitated the integrative multi-omics insights into risk assessment and toxic mechanisms of tobacco carcinogens.

Quantifying the contribution of smear-negative, culture-positive pulmonary tuberculosis to nosocomial transmission.

BACKGROUND: Despite current guidelines for tuberculosis (TB) control in health care settings, which focused on smear-positive cases, prevention of nosocomial TB transmission continues to be a challenge. Here, we report the results of the first hospital-wide prospective study applying interferon-gamma release assay to investigate the role of smear-negative, culture-positive index cases in nosocomial TB transmission. METHODS: We prospectively identified cases of culture-confirmed smear-negative pulmonary TB receiving aerosol-generating procedures (AGPs) and cases of culture-confirmed smear-positive pulmonary TB admitted at a medical center. Nosocomial transmission was evaluated by screening their close contacts for latent TB infection (LTBI) using an interferon-gamma release assay. RESULTS: A total of 93 smear-negative index receiving AGP and 122 smear-positive index were enrolled. Among them, 13 (14.0%) and 43 (35.2%) index cases, respectively, had secondary cases of LTBI (P < .001). Sputum smear negativity (adjusted odds ratio: 0.20 [0.08-0.48]) and AGP (sputum suction; adjusted odds ratio: 3.48 [1.34-9.05]) are independent factors of transmission. A similar proportion in the close contacts of the 2 index groups had LTBI (17 [15.3%] and 63 [16.0%], respectively), and the former index group contributed to 21.3% of the nosocomial transmission. CONCLUSIONS: Smear-negative, culture-positive index cases receiving AGPs could be as infectious as smear-positive index cases. Hospital TB control policy should also focus on the former group.

Effects of occupational exposure to dust, gas, vapor and fumes on chronic bronchitis and lung function.

Background: Chronic obstructive pulmonary disease (COPD) is one of the leading causes of mortality worldwide, and therefore the identification of the modifiable risk factors [such as exposure to vapors, gases, dust and fumes (VGDF)] for accelerate disease progression has important significance. Methods: We conducted COPD surveillance in six cities of southern China between 2014 and 2019. We recorded the diagnosis of chronic bronchitis, respiratory symptoms, occupational exposure to VGDF and other covariates by using a structured questionnaire. Logistic regression and multivariate linear regression model were adopted for analysis. We performed sensitivity analyses based on two methods of propensity score (PS) methods to evaluate the robustness of our results. Results: A total of 7,418 participants were included. Cough [odds ratios (ORs): 1.60, 95% confidence interval (CI): 1.22 to 2.08] and phlegm (OR: 1.49, 95% CI: 1.19 to 1.85) correlated significantly with exposure to dust. There was an increased risk of cough (OR: 1.53, 95% CI: 1.11 to 2.07) for occupational exposure to gas/vapor/fume. Dual exposure to dust and gas/vapor/fume was associated with a significantly increased risk of chronic bronchitis (OR: 1.74, 95% CI: 1.20 to 2.52), cough (OR: 1.43, 95% CI: 1.15 to 1.79) and phlegm (OR: 1.49, 95% CI: 1.24 to 1.79). In 5,249 participants with complete data of spirometry, gas/vapor/fume was associated with a decreased ratio of forced expiratory volume in one second and forced vital capacity (FEV1/FVC) (ß: -1.05, 95% CI: -1.85 to -0.26) and maximal mid-expiratory flow (MMEF) (ß: -0.15, 95% CI: -0.23 to -0.07). Dual exposure to dust and gas/vapor/fume was significantly associated with decreased FEV1/FVC (ß: -0.74, 95% CI: -1.28 to -0.20) and MMEF (ß: -0.06, 95% CI: -0.12 to -0.01). Results of sensitivity analysis were not materially changed. Conclusions: VGDF exposure is associated with chronic bronchitis, respiratory symptoms and decreased lung function, suggesting that VGDF contributes to the pathogenesis and progression of COPD.

Expert Consensus on the Diagnosis and Treatment of NRG1/2 Gene Fusion Solid Tumors.

The fusion genes NRG1 and NRG2 , members of the epidermal growth factor (EGF) receptor family, have emerged as key drivers in cancer. Upon fusion, NRG1 retains its EGF-like active domain, binds to the ERBB ligand family, and triggers intracellular signaling cascades, promoting uncontrolled cell proliferation. The incidence of NRG1 gene fusion varies across cancer types, with lung cancer being the most prevalent at 0.19 to 0.27%. CD74 and SLC3A2 are the most frequently observed fusion partners. RNA-based next-generation sequencing is the primary method for detecting NRG1 and NRG2 gene fusions, whereas pERBB3 immunohistochemistry can serve as a rapid prescreening tool for identifying NRG1 -positive patients. Currently, there are no approved targeted drugs for NRG1 and NRG2 . Common treatment approaches involve pan-ERBB inhibitors, small molecule inhibitors targeting ERBB2 or ERBB3, and monoclonal antibodies. Given the current landscape of NRG1 and NRG2 in solid tumors, a consensus among diagnostic and treatment experts is proposed, and clinical trials hold promise for benefiting more patients with NRG1 and NRG2 gene fusion solid tumors.

Deep Learning-based Diagnosis of Pulmonary Tuberculosis on Chest X-ray in the Emergency Department: A Retrospective Study.

Prompt and correct detection of pulmonary tuberculosis (PTB) is critical in preventing its spread. We aimed to develop a deep learning-based algorithm for detecting PTB on chest X-ray (CXRs) in the emergency department. This retrospective study included 3498 CXRs acquired from the National Taiwan University Hospital (NTUH). The images were chronologically split into a training dataset, NTUH-1519 (images acquired during the years 2015 to 2019; n = 2144), and a testing dataset, NTUH-20 (images acquired during the year 2020; n = 1354). Public databases, including the NIH ChestX-ray14 dataset (model training; 112,120 images), Montgomery County (model testing; 138 images), and Shenzhen (model testing; 662 images), were also used in model development. EfficientNetV2 was the basic architecture of the algorithm. Images from ChestX-ray14 were employed for pseudo-labelling to perform semi-supervised learning. The algorithm demonstrated excellent performance in detecting PTB (area under the receiver operating characteristic curve [AUC] 0.878, 95% confidence interval [CI] 0.854-0.900) in NTUH-20. The algorithm showed significantly better performance in posterior-anterior (PA) CXR (AUC 0.940, 95% CI 0.912-0.965, p-value < 0.001) compared with anterior-posterior (AUC 0.782, 95% CI 0.644-0.897) or portable anterior-posterior (AUC 0.869, 95% CI 0.814-0.918) CXR. The algorithm accurately detected cases of bacteriologically confirmed PTB (AUC 0.854, 95% CI 0.823-0.883). Finally, the algorithm tested favourably in Montgomery County (AUC 0.838, 95% CI 0.765-0.904) and Shenzhen (AUC 0.806, 95% CI 0.771-0.839). A deep learning-based algorithm could detect PTB on CXR with excellent performance, which may help shorten the interval between detection and airborne isolation for patients with PTB.