Propionate outperforms conventional acetate as electron donors for highly-sensitive electrochemical active biofilm sensors in water biotoxicity early-warning.

With the ability to generate in situ real-time electric signals, electrochemically active biofilm (EAB) sensors have attracted wide attention as a promising water biotoxicity early-warning device. Organic matters serving as the electron donors potentially affect the electric signal's output and the sensitivity of the EAB sensor. To explore the influence of organic matters on EAB sensor's performance, this study tested six different organic matters during the sensor's inoculation. Besides the acetate, a conventional and widely used organic matter, propionate and lactate were also found capable of starting up the sensor. Moreover, the propionate-fed (PF) sensor delivered the highest sensitivity, which are respectively 1.4 times and 2.8 times of acetate-fed (AF) sensor and lactate-fed (LF) sensor. Further analysis revealed that EAB of PF sensor had more vulnerable intracellular metabolism than the others, which manifested as the most severe energy metabolic suppression and reactive oxygen species attack. Regarding the microbial function, a two-component system that was deemed as an environment awareness system was found in the EAB of PF, which also contributed to its high sensitivity. Finally, PF sensor was tested in real water environment to deliver early-warning signals.

Revisiting the Transferability of Few-Shot Image Classification: A Frequency Spectrum Perspective.

Few-shot learning, especially few-shot image classification (FSIC), endeavors to recognize new categories using only a handful of labeled images by transferring knowledge from a model trained on base categories. Despite numerous efforts to address the challenge of deficient transferability caused by the distribution shift between the base and new classes, the fundamental principles remain a subject of debate. In this paper, we elucidate why a decline in performance occurs and what information is transferred during the testing phase, examining it from a frequency spectrum perspective. Specifically, we adopt causality on the frequency space for FSIC. With our causal assumption, non-causal frequencies (e.g., background knowledge) act as confounders between causal frequencies (e.g., object information) and predictions. Our experimental results reveal that different frequency components represent distinct semantics, and non-causal frequencies adversely affect transferability, resulting in suboptimal performance. Subsequently, we suggest a straightforward but potent approach, namely the Frequency Spectrum Mask (FRSM), to weight the frequency and mitigate the impact of non-causal frequencies. Extensive experiments demonstrate that the proposed FRSM method significantly enhanced the transferability of the FSIC model across nine testing datasets.

Continual Reinforcement Learning for Quadruped Robot Locomotion.

The ability to learn continuously is crucial for a robot to achieve a high level of intelligence and autonomy. In this paper, we consider continual reinforcement learning (RL) for quadruped robots, which includes the ability to continuously learn sub-sequential tasks (plasticity) and maintain performance on previous tasks (stability). The policy obtained by the proposed method enables robots to learn multiple tasks sequentially, while overcoming both catastrophic forgetting and loss of plasticity. At the same time, it achieves the above goals with as little modification to the original RL learning process as possible. The proposed method uses the Piggyback algorithm to select protected parameters for each task, and reinitializes the unused parameters to increase plasticity. Meanwhile, we encourage the policy network exploring by encouraging the entropy of the soft network of the policy network. Our experiments show that traditional continual learning algorithms cannot perform well on robot locomotion problems, and our algorithm is more stable and less disruptive to the RL training progress. Several robot locomotion experiments validate the effectiveness of our method.

Results of the phase IIa study to evaluate the efficacy and safety of rezivertinib (BPI-7711) for the first-line treatment of locally advanced or metastatic/recurrent NSCLC patients with EGFR mutation from a phase I/IIa study.

BACKGROUND: Rezivertinib (BPI-7711) is a novel third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI). This phase IIa study was part of a phase I/IIa study (NCT03386955), aimed to evaluate the efficacy and safety of rezivertinib as the first-line treatment for patients with locally advanced or metastatic/recurrent EGFR mutated non-small cell lung cancer (NSCLC). METHODS: Patients received the first-line treatment of 180 mg rezivertinib orally once daily until disease progression, unacceptable toxicity, or withdrawal of consent. The primary endpoint was the objective response rate (ORR) assessed by blinded independent central review (BICR). Secondary endpoints included disease control rate (DCR), duration of response (DoR), progression-free survival (PFS), overall survival (OS), and safety. RESULTS: From Jun 12, 2019, to Oct 17, 2019, 43 patients were enrolled. At the data cutoff date on Dec 23, 2021, the ORR by BICR was 83.7% (95% CI: 69.3-93.2%). The median DoR was 19.3 (95% CI: 15.8-25.0) months. The median PFS by BICR was 20.7 (95% CI: 13.8-24.8) months and 22.0 (95% CI: 16.8-26.3) months by investigators. Data on OS was immature. Totally, 40 (93.0%) patients had at least one treatment-related adverse event while 4 (9.3%) of them were grade ≥ 3. CONCLUSIONS: Rezivertinib (BPI-7711) showed promising efficacy and a favorable safety profile for the treatment among the locally advanced or metastatic/recurrent NSCLC patients with EGFR mutation in the first-line setting. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03386955.

Quorum-sensing gene regulates hormetic effects induced by sulfonamides in Comamonadaceae.

IMPORTANCE: Antibiotics can induce dose-dependent hormetic effects on bacterial cell proliferation, i.e., low-dose stimulation and high-dose inhibition. However, the underlying molecular basis has yet to be clarified. Here, we showed that sulfonamides play dual roles as a weapon and signal against Comamonas testosteroni that can modulate cell physiology and phenotype. Subsequently, through investigating the hormesis mechanism, we proposed a comprehensive regulatory pathway for the hormetic effects of Comamonas testosteroni low-level sulfonamides and determined the generality of the observed regulatory model in the Comamonadaceae family. Considering the prevalence of Comamonadaceae in human guts and environmental ecosystems, we provide critical insights into the health and ecological effects of antibiotics.

Electricity-Driven Microbial Metabolism of Carbon and Nitrogen: A Waste-to-Resource Solution.

Electricity-driven microbial metabolism relies on the extracellular electron transfer (EET) process between microbes and electrodes and provides promise for resource recovery from wastewater and industrial discharges. Over the past decades, tremendous efforts have been dedicated to designing electrocatalysts and microbes, as well as hybrid systems to push this approach toward industrial adoption. This paper summarizes these advances in order to facilitate a better understanding of electricity-driven microbial metabolism as a sustainable waste-to-resource solution. Quantitative comparisons of microbial electrosynthesis and abiotic electrosynthesis are made, and the strategy of electrocatalyst-assisted microbial electrosynthesis is critically discussed. Nitrogen recovery processes including microbial electrochemical N2 fixation, electrocatalytic N2 reduction, dissimilatory nitrate reduction to ammonium (DNRA), and abiotic electrochemical nitrate reduction to ammonia (Abio-NRA) are systematically reviewed. Furthermore, the synchronous metabolism of carbon and nitrogen using hybrid inorganic-biological systems is discussed, including advanced physicochemical, microbial, and electrochemical characterizations involved in this field. Finally, perspectives for future trends are presented. The paper provides valuable insights on the potential contribution of electricity-driven microbial valorization of waste carbon and nitrogen toward a green and sustainable society.

CHARACTERIZATION OF MACULAR NEOVASCULARIZATION IN BIETTI CRYSTALLINE DYSTROPHY USING MULTIMODAL IMAGING MODALITIES.

PURPOSE: To characterize the clinical features of macular neovascularization (MNV) secondary to Bietti crystalline dystrophy. METHODS: The imaging data of 157 eyes in 79 patients with Bietti crystalline dystrophy were retrospectively reviewed. 12 individuals (19 eyes) were found to have MNVs. Multimodal retinal imaging was used to evaluate the features of MNVs and the primary chorioretinopathy. RESULTS: The MNV lesions were shown as typical type 2 MNVs with subretinal hyperreflective material (SHRM), and usually detected along the borders of the retinal pigment epithelium/choriocapillaris dropout. The active MNVs were noted in earlier stages of Bietti crystalline dystrophy, while the activity was observed to be reduced in advanced cases. On spectral domain optical coherence tomography, the outer retinal structures were demonstrated to be partially preserved above the SHRMs compared with the extensive atrophy contiguously. Fibrotic scaring of the MNVs was commonly observed and arteriolarization was usually shown within the scars. CONCLUSION: MNV was demonstrated to be a common complication secondary to Bietti crystalline dystrophy. The lesions were typical type 2 MNV of varied activities possibly associated with the degrees of the primary degeneration. Choriocapillaris hypoperfusion may participate in MNV development.

Is it true that negative emotions cause more utilitarian judgements? from the influence of emotion and cognition.

ABSTRACTThe affect-as-information (AAI) model proposes that emotions influence the accessibility and value of information (Avramova & Inbar, 2013). Furthermore, according to the dual-process model of moral judgement, emotions and cognition influence moral judgement (Greene, 2007; Greene et al., 2001, 2008); however, there is no direct evidence of a causal chain to support this model's proposition. By using a 3 (emotions: positive vs. neutral vs. negative) × 2 (primed rule: save lives vs. do not kill) between-participants design, we examined two hypotheses in two experiments: supraliminal (Experiment 1) and subliminal (Experiment 2) priming. Our results partially supported the AAI model and confirmed that emotions and cognition independently influence moral judgement. Specifically, the positive emotions group made more utilitarian decisions after being primed with the "save lives" rule and more deontological decisions after being primed with the do not kill rule. However, priming did not affect moral judgement in the negative emotion condition. Further, irrespective of whether priming was done, the negative emotion group mostly made utilitarian decisions. Accordingly, we propose a dynamic dual-process model of moral judgement, that can help clarify how emotion and cognition influence moral judgement.

Structural Health Monitoring in Long-Span Steel Structures Based on the BeiDou Navigation Satellite System.

The BeiDou navigation satellite system (BDS) provides precise positioning, navigation, and timing (PNT) services in the Asia-Pacific Region, but the BDS-based structural health monitoring (SHM) approach (SHM) is rarely studied, especially in civil engineering. Moreover, how BDS can be applied to complete the tasks of SHM in a real project is also not fully investigated, especially working in conjunction with other techniques. This study aims to propose a BDS-based approach for SHM in civil engineering. The performance of the proposed approach is investigated through a case study-the Tianhan Grand Theater (TGT). A specific Tianhan system corresponding to BDS is proposed to complete the SHM tasks of TGT. Based on the collected data, the trusses with maximum displacement and stress are found by BDS to evaluate structural health in the construction stage. The results show that the maximum displacement and stress have certain safety reserves and meet the requirements of the specifications and regulations. Thus, BDS can satisfactorily complete the tasks of SHM for Long-span steel structures. This study gives a clear view to engineers and researchers that how to apply BDS in structural construction and provides a valuable real case for evaluating the performance of BDS in SHM.

Super-fast Charging Biohybrid Batteries through a Power-to-formate-to-bioelectricity Process by Combining Microbial Electrochemistry and CO2 Electrolysis.

Extensive study on renewable energy storage has been sparked by the growing worries regarding global warming. In this study, incorporating the latest advancements in microbial electrochemistry and electrochemical CO2 reduction, a super-fast charging biohybrid battery was introduced by using pure formic acid as an energy carrier. CO2 electrolyser with a slim-catholyte layer and a solid electrolyte layer was built, which made it possible to use affordable anion exchange membranes and electrocatalysts that are readily accessible. The biohybrid battery only required a 3-minute charging to accomplish an astounding 25-hour discharging phase. In the power-to-formate-to-bioelectricity process, bioconversion played a vital role in restricting both the overall Faradaic efficiency and Energy efficiency. The CO2 electrolyser was able to operate continuously for an impressive total duration of 164 hours under Gas Stand-By model, by storing N2 gas in the extraction chamber during stand-by periods. Additionally, the electric signal generated during the discharging phase was utilized for monitoring water biotoxicity. Functional genes related to formate metabolism were identified in the bioanode and electrochemically active bacteria were discovered. On the other hand, Paracoccus was predominantly found in the used air cathode. These results advance our current knowledge of exploiting biohybrid technology.

A novel nonparametric computational strategy for identifying differential methylation regions.

BACKGROUND: DNA methylation has long been known as an epigenetic gene silencing mechanism. For a motivating example, the methylomes of cancer and non-cancer cells show a number of methylation differences, indicating that certain features characteristics of cancer cells may be related to methylation characteristics. Robust methods for detecting differentially methylated regions (DMRs) could help scientists narrow down genome regions and even find biologically important regions. Although some statistical methods were developed for detecting DMR, there is no default or strongest method. Fisher's exact test is direct, but not suitable for data with multiple replications, while regression-based methods usually come with a large number of assumptions. More complicated methods have been proposed, but those methods are often difficult to interpret. RESULTS: In this paper, we propose a three-step nonparametric kernel smoothing method that is both flexible and straightforward to implement and interpret. The proposed method relies on local quadratic fitting to find the set of equilibrium points (points at which the first derivative is 0) and the corresponding set of confidence windows. Potential regions are further refined using biological criteria, and finally selected based on a Bonferroni adjusted t-test cutoff. Using a comparison of three senescent and three proliferating cell lines to illustrate our method, we were able to identify a total of 1077 DMRs on chromosome 21. CONCLUSIONS: We proposed a completely nonparametric, statistically straightforward, and interpretable method for detecting differentially methylated regions. Compared with existing methods, the non-reliance on model assumptions and the straightforward nature of our method makes it one competitive alternative to the existing statistical methods for defining DMRs.

On-treatment blood TMB as predictors for camrelizumab plus chemotherapy in advanced lung squamous cell carcinoma: biomarker analysis of a phase III trial.

BACKGROUND: Camrelizumab plus chemotherapy significantly prolonged progression-free survival (PFS) and overall survival (OS) compared to chemotherapy alone as first-line treatment in advanced lung squamous cell carcinoma (LUSC) in the phase III trial (CameL-sq), which has become an option of standard-of-cares for Chinese patients with advanced LUSC. However, the predictive biomarkers remain unknown. METHODS: Tumor tissue samples at baseline, and peripheral blood samples at baseline (pretreatment) and after two cycles of treatment (on-treatment) were prospectively collected from 270 LUSC patients from the CameL-sq study. Blood tumor mutation burden (bTMB) and its dynamics were analyzed to explore their predictive values. RESULTS: Pretreatment bTMB was not associated with objective response, PFS and OS in camrelizumab or placebo plus chemotherapy groups. Low on-treatment bTMB was associated with significantly better objective response (73.8% vs 27.8%, P < 0.001), PFS (median, 9.1 vs 4.1 months; P < 0.001) and OS (median, not reached vs 8.0 months; P < 0.001) in camrelizumab plus chemotherapy group whereas it did not correlate with objective response and PFS in chemotherapy alone group. Importantly, on-treatment bTMB level could discriminate patients of initially radiological stable disease who would long-term benefit from camrelizumab plus chemotherapy (low vs high, median OS, 18.2 vs 7.8 months; P = 0.001). Combing on-treatment bTMB and its dynamics improved the ability for predicting the efficacy of camrelizumab plus chemotherapy. CONCLUSION: On-treatment bTMB together with its dynamics could serve as a predictive biomarker for camrelizumab plus chemotherapy in patients with advanced LUSC. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03668496.

Anlotinib Monotherapy for Refractory Metastatic Colorectal Cancer: A Double-Blinded, Placebo-Controlled, Randomized Phase III Trial (ALTER0703).

BACKGROUND: Treatment options for refractory metastatic colorectal cancer (mCRC) were limited. Anlotinib is a novel multitarget tyrosine kinase inhibitor. ALTER0703 study was conducted to assess efficacy and safety of anlotinib for patients with refractory mCRC. MATERIALS AND METHODS: This was a multicenter, double-blinded, placebo-controlled, randomized phase III trial involving 33 hospitals in China. Patients had taken at least two lines of therapies were 2:1 randomized to receive oral anlotinib (12 mg/day; days 1-14; 21 days per cycle) or placebo, plus best supportive care. Randomization was stratified by previous VEGF-targeting treatments and time from diagnosis to metastases. The primary endpoint was overall survival (OS). The secondary endpoints were progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR), quality of life (QoL), and safety. RESULTS: A total of 419 patients (anlotinib: 282; placebo: 137) were treated from December 2014 to August 2016. The median PFS was improved in anlotinib group (4.1 months; 95% confidence interval [CI], 3.4-4.5) over placebo group (1.5 months; 95% CI, 1.4-1.5), with a hazard ratio (HR) of 0.34 (95% CI, 0.27-0.43; p < .0001). However, median OS was similar between two groups (8.6 months; 95% CI, 7.8-9.7 vs. 7.2 months; 95% CI, 6.2-8.8; HR, 1.02; p = .870). Improvements of ORR and DCR were observed in anlotinib over placebo. The most common grade ≥ 3 anlotinib related adverse events were hypertension (20.92%), increased γ-GT (7.09%), and hand-foot skin reaction (6.38%). CONCLUSION: Anlotinib was tolerated in Chinese patients with refractory mCRC. Although OS did not reach significant difference, anlotinib still provided clinical benefits by substantially prolonged PFS in these patients. IMPLICATIONS FOR PRACTICE: In this randomized clinical trial that included 419 patients with refractory metastatic colorectal cancer, substantial prolonged in progression-free survival was noted in patients who received anlotinib compared with those given placebo. Improvements on objective response rate and disease control rate was also observed in anlotinib group. However, overall survival was similar between the two groups. In a word, in third-line or above treatment of Chinese patients with refractory metastatic colorectal cancer, anlotinib provided clinical benefit by significantly prolonged progression-free survival.

A novel method of high-purity extracellular vesicle enrichment from microliter-scale human serum for proteomic analysis.

We have developed a rapid, low-cost, and simple separation strategy to separate extracellular vesicles (EVs) from a small amount of serum (i.e.,<100 µL) with minimal contamination by serum proteins and lipoprotein particles to meet the high purity requirement for EV proteome analysis. EVs were separated by a novel polyester capillary channel polymer (PET C-CP) fiber phase/hydrophobic interaction chromatography (HIC) method which is rapid and can process small size samples. The collected EV fractions were subjected to a post-column cleanup protocol using a centrifugal filter to perform buffer exchange and eliminate potential coeluting non-EV proteins while minimizing EV sample loss. Downstream characterization demonstrated that our current strategy can separate EVs with the anticipated exosome-like particle size distribution and high yield (∼1 × 1011 EV particles per mL of serum) in approximately 15 min. Proteome profiling of the EVs reveals that a group of genuine EV components were identified that have significantly less high-abundance blood proteins and lipoprotein particle contamination in comparison to traditional separation methods. The use of this methodology appears to address the major challenges facing EV separation for proteomics analysis. In addition, the EV post-column cleanup protocol proposed in the current work has the potential to be combined with other separation methods, such as ultracentrifugation (UC), to further purify the separated EV samples.

Recovery trajectories and community resilience of biofilms in receiving rivers after wastewater treatment plant upgrade.

Wastewater treatment plant (WWTP) upgrades can reduce both nutrient and micropollutant emissions into receiving rivers, thus modifying the composition and function of biological communities. However, how microbial communities vary and whether they can be restored to levels found in less-polluted rivers remains uncertain. Aquatic biofilms are sensitive to environmental change and respond rapidly to bottom-up pressure. Thus, we used 12 flumes configured in three experimental treatments to mimic the dynamic processes of biofilm microbial communities occurring in a wastewater-receiving river following WWTP upgrade, with rivers containing two levels of nutrients and micropollutants used as references. We compared the biofilm microbial biomass, carbon source utilization, and community composition among the three "blocks". Results showed that the metabolic patterns of the carbon sources and composition of the biofilm bacterial communities in the flumes mimicking a receiving river with WWTP upgrade recovered over time to those mimicking a less-disturbed river. The restoration of potential carboxylic acid-consuming denitrifying bacteria (i.e., Zoogloea, Comamonas, Dechloromonas, and Acinetobacter) likely played a significant role in this process. Combining quantitative analysis of the denitrification genes nirS and nosZ, we confirmed that the denitrification function of the river biofilms recovered after WWTP upgrade, consistent with our previous field investigation.

Individualized diagnosis of major depressive disorder via multivariate pattern analysis of thalamic sMRI features.

BACKGROUND: Magnetic resonance imaging (MRI) studies have found thalamic abnormalities in major depressive disorder (MDD). Although there are significant differences in the structure and function of the thalamus between MDD patients and healthy controls (HCs) at the group level, it is not clear whether the structural and functional features of the thalamus are suitable for use as diagnostic prediction aids at the individual level. Here, we were to test the predictive value of gray matter density (GMD), gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and fractional amplitude of low-frequency fluctuations (fALFF) in the thalamus using multivariate pattern analysis (MVPA). METHODS: Seventy-four MDD patients and 44 HC subjects were recruited. The Gaussian process classifier (GPC) was trained to separate MDD patients from HCs, Gaussian process regression (GPR) was trained to predict depression scores, and Multiple Kernel Learning (MKL) was applied to explore the contribution of each subregion of the thalamus. RESULTS: The primary findings were as follows: [1] The balanced accuracy of the GPC trained with thalamic GMD was 96.59% (P < 0.001). The accuracy of the GPC trained with thalamic GMV was 93.18% (P < 0.001). The correlation between Hamilton Depression Scale (HAMD) score targets and predictions in the GPR trained with GMD was 0.90 (P < 0.001, r2 = 0.82), and in the GPR trained with GMV, the correlation between HAMD score targets and predictions was 0.89 (P < 0.001, r2 = 0.79). [2] The models trained with ALFF and fALFF in the thalamus failed to discriminate MDD patients from HC participants. [3] The MKL model showed that the left lateral prefrontal thalamus, the right caudal temporal thalamus, and the right sensory thalamus contribute more to the diagnostic classification. CONCLUSIONS: The results suggested that GMD and GMV, but not functional indicators of the thalamus, have good potential for the individualized diagnosis of MDD. Furthermore, the thalamus shows the heterogeneity in the structural features of thalamic subregions for predicting MDD. To our knowledge, this is the first study to focus on the thalamus for the prediction of MDD using machine learning methods at the individual level.

Diversity of Viruses Infecting Eukaryotic Algae.

Algae are photosynthetic organisms that drive aquatic ecosystems, e.g. fuelling food webs or forming harmful blooms. The discovery of viruses that infect eukaryotic algae has raised many questions about their influence on aquatic primary production and their role in algal ecology and evolution. Although the full extent of algal virus diversity is still being discovered, this review summarizes current knowledge of this topic. Where possible, formal taxonomic classifications are referenced from the International Committee on Taxonomy of Viruses (ICTV); since the pace of virus discovery has far surpassed the rate of formal classification, however, numerous unclassified viruses are discussed along with their classified relatives. In total, we recognized 61 distinct algal virus taxa with highly variable morphologies that include dsDNA, ssDNA, dsRNA, and ssRNA genomes ranging from approximately 4.4 to 560 kb, with virion sizes from approximately 20 to 210nm in diameter. These viruses infect a broad range of algae and, although there are a few exceptions, they are generally lytic and highly species or strain specific. Dedicated research efforts have led to the appreciation of algal viruses as diverse, dynamic, and ecologically important members of the biosphere, and future investigations will continue to reveal the full extent of their diversity and impact.

Factors associated with diagnostic delay in recurrent TB.

BACKGROUND: Recurrent tuberculosis (TB) contributes to the burden of TB. The study was designed to explore the time of diagnostic delay and risk of delay in patients with recurrent TB in China. METHODS: A total of 13,334 patients with new and recurrent TB registered in Yulin a city in China were included. The Kaplan-Meier survival curve was employed to estimate the median delay time. The mixed-effects survival model was used to identify the correlates associated with diagnostic delay. The outcome of interest in the model was"being diagnosed". RESULTS: We found that 6.5% of cases with TB were attributed to recurrence. The median delay time of recurrent TB cases (73 days) was more than twice as long as that of new TB (35 days). Individuals with recurrent TB had a higher risk of diagnostic delay than new TB (HR, 0.5, 95%CI, 0.5-0.6). Factors associated with diagnostic delay differed between new TB and recurrent TB cases. Immigrants (HR, 0.5, 95%CI, 0.3-0.9), cases notified by way of recommendation (HR, 0.6, 95%CI, 0.4-0.9) and diagnosed at TB dispensary (HR, 0.4, 95%CI, 0.3-0.6) were associated with a higher risk of a longer delay for recurrent TB cases. CONCLUSIONS: The proportion of TB cases attributed to recurrence was high. Patients with recurrent TB had a longer delay time and a higher risk of diagnostic delay. Further interventions to improve diagnostic delay should focus on screening for TB in immigrants, improving public health services at the lowest healthcare level and update of TB diagnosis and management model.

Trend in risk of delay in diagnosis of new pulmonary tuberculosis in Northwest China from 2008 to 2017.

BACKGROUND: With great changes over the past 10 years in China, especially the rapid economic development, population mobility, urbanization and aging, dynamic change on risk of delay, to our knowledge, has not been well studied in China. The study was to explore risk of delay in diagnosis of new pulmonary tuberculosis (PTB) and dynamic changes in risk of delay in Northwest China. METHODS: From January 1, 2008 to December 31, 2017, a total of 13,603 people with new PTB registered in Yulin city of Shaanxi province were included. The median delay time was estimated by Kaplan-Meier survival curve. Time delay curves of year-, gender-year-, age-year- and smear-year specific were examined using log-rank test. Two-level mixed-effects survival model was used to calculate the hazard ratio (HR) and 95% confidence interval (95%CI) for factors associated with diagnostic delay. Time delay was defined as time interval between the onset of PTB symptoms and being diagnosed. The outcome variable of interest was defined as "being diagnosed" in survival analysis. RESULTS: The 10-year delay time was 33 days (Interquartile Range, 16-65). Annual median delay time gradually decreased from 60 days to 33 days during the past 10 years. The probability that individuals were diagnosed since onset of PTB symptoms increased by 1.29 times in 2017 when compared to 2008. Female (Hazard Ratio (HR), 95%CI, 0.95(0.91-0.99)), age>45 years (HR, 95%CI, 0.87(0.82-0.93)) and smear positive (HR, 95%CI, 0.86(0.78-0.95)) were associated with increased risk of diagnostic delay over 10-year timespan. However, Age>45 years and smear positive showed trend to be protective factors in the past 5 years. CONCLUSIONS: Time and risk of delay in diagnosis of new PTB had declined over the past 10 years. However, more attentions should be paid to the fact that female still suffered from higher risk of diagnostic delay. We noted a potential reversal in traditional risk factors such as age>45 and smear positive. Those dynamic changes deserved further attention.

Predictive value of spectral-domain optical coherence tomography features in assessment of visual prognosis in eyes with acute welding arc maculopathy.

OBJECTIVE: To observe spectral-domain optical coherence tomography (SD-OCT) features and to determine whether baseline OCT features can be used as predictors of visual acuity outcome in eyes with acute welding arc maculopathy. METHODS: This retrospective study enrolled twenty-two eyes of eleven subjects with acute welding arc maculopathy. All subjects were evaluated by SD-OCT at baseline and final visit. The involved parameters included best-corrected visual acuity (BCVA), central macular thickness (CMT), the length of ellipsoid zone (EZ) defects, the greatest linear dimension (GLD) of outer retinal lesions, EZ reflectivity and relative EZ reflectivity (defined as the ratio of EZ reflectivity to retinal pigment epithelium reflectivity on OCT). RESULTS: Acute welding arc maculopathy was presented as abnormal hyperreflectivity, hyporeflectivity and defects of outer retinal layer in fovea on OCT. Compared with baseline, BCVA improved significantly accompanied by decreased GLD of outer retinal lesions and the length of EZ defects at final visit (P = 0.0004, P < 0.0001 and P < 0.0001, respectively). No significant changes were shown on CMT (P = 0.248). In multivariate regression analysis, final BCVA was associated with baseline BCVA and the length of EZ defects (P = 0.012 and P = 0.045, respectively). However, EZ reflectivity and relative EZ reflectivity were not associated with final BCVA (P > 0.05). CONCLUSION: In conclusion, SD-OCT images clearly reveal morphological changes in outer retinal layer in acute welding arc maculopathy. The baseline BCVA and length of EZ defects are the strongest predictors of final BCVA.