Dithiocarbonate-Protected Au25 Nanorods of a Chiral D5 Configuration and NIR-II Phosphorescence.

Innovative surface-protecting ligands are in constant demand due to their crucial role in shaping the configuration, property, and application of gold nanoclusters. Here, the unprecedented O-ethyl dithiocarbonate (DTX)-stabilized atomically precise gold nanoclusters, [Au25(PPh3)10(DTX)5Cl2]2+ (Au25DTX-Cl) and [Au25(PPh3)10(DTX)5Br2]2+ (Au25DTX-Br), were synthesized and structurally characterized. The introduction of bidentate DTX ligands not only endowed the gold nanocluster with unique staggered Au25 nanorod configurations but also generated the symmetry breaking from the D5d geometry of the Au25 kernels to the chiral D5 configuration of the Au25 molecules. The chirality of Au25 nanorods was notably revealed through single-crystal X-ray diffraction, and chiral separation was induced by employing chiral DTX ligands. The staggered configurations of Au25 nanorods, as opposed to eclipsed ones, were responsible for the large red shift in the emission wavelengths, giving rise to a promising near-infrared II (NIR-II, >1000 nm) phosphorescence. Furthermore, their performances in photocatalytic sulfide oxidation and electrocatalytic hydrogen evolution reactions have been examined, and it has been demonstrated that the outstanding catalytic activity of gold nanoclusters is highly related to their stability.

A direct observation of up-converted room-temperature phosphorescence in an anti-Kasha dopant-matrix system.

It is common sense that emission maxima of phosphorescence spectra (λP) are longer than those of fluorescence spectra (λF). Here we report a serendipitous finding of up-converted room-temperature phosphorescence (RTP) with λP < λF and phosphorescence lifetime > 0.1 s upon doping benzophenone-containing difluoroboron ß-diketonate (BPBF2) into phenyl benzoate matrices. The up-converted RTP is originated from BPBF2's Tn (n ≥ 2) states which show typical 3n-π* characters from benzophenone moieties. Detailed studies reveal that, upon intersystem crossing from BPBF2's S1 states of charge transfer characters, the resultant T1 and Tn states build T1-to-Tn equilibrium. Because of their 3n-π* characters, the Tn states possess large phosphorescence rates that can strongly compete RTP(T1) to directly emit RTP(Tn) which violates Kasha's rule. The direct observation of up-converted RTP provides deep understanding of triplet excited state dynamics and opens an intriguing pathway to devise visible-light-excitable deep-blue afterglow emitters, as well as stimuli-responsive afterglow materials.

Benzophenone-containing phosphors with an unprecedented long lifetime of 1.8 s under ambient conditions.

It is well-known that benzophenone has a short phosphorescence lifetime of around 1 ms even at 77 K. Here we report a benzophenone-containing emitter with an unprecedented long phosphorescence lifetime of 1.8 s under ambient conditions, which can be attributed to its T1 state of localized excitation nature as revealed by detailed studies.

A deep learning approach to the diagnosis of atelectasis and attic retraction pocket in otitis media with effusion using otoscopic images.

BACKGROUND: This study aimed to develop and validate a deep learning (DL) model to identify atelectasis and attic retraction pocket in cases of otitis media with effusion (OME) using multi-center otoscopic images. METHOD: A total of 6393 OME otoscopic images from three centers were used to develop and validate a DL model for detecting atelectasis and attic retraction pocket. A threefold random cross-validation procedure was adopted to divide the dataset into training validation sets on a patient level. A team of otologists was assigned to diagnose and characterize atelectasis and attic retraction pocket in otoscopic images. Receiver operating characteristic (ROC) curves, including area under the ROC curve (AUC), accuracy, sensitivity, and specificity were used to assess the performance of the DL model. Class Activation Mapping (CAM) illustrated the discriminative regions in the otoscopic images. RESULTS: Among all OME otoscopic images, 3564 (55.74%) were identified with attic retraction pocket, and 2460 (38.48%) with atelectasis. The diagnostic DL model of attic retraction pocket and atelectasis achieved a threefold cross-validation accuracy of 89% and 79%, AUC of 0.89 and 0.87, a sensitivity of 0.93 and 0.71, and a specificity of 0.62 and 0.84, respectively. Larger and deeper cases of atelectasis and attic retraction pocket showed greater weight, based on the red color depicted in the heat map of CAM. CONCLUSION: The DL algorithm could be employed to identify atelectasis and attic retraction pocket in otoscopic images of OME, and as a tool to assist in the accurate diagnosis of OME.

[Predictive value of strobovideolaryngoscopy, acoustic and aerodynamic measures in the prognosis of temporally unilateral vocal fold paralysis after thyroidectomy].

Objective:To investigate the strobovideolaryngoscopy, acoustic and aerodynamic characteristics of transient unilateral vocal ford paralysis（UVFP） after thyroidectomy. Methods:A retrospective analysis was made of 11 patients with temporary UVFP after thyroidectomy who were treated in Department of Otolaryngology and Head and Neck Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University from January 2013 to March 2021; 8 patients with permanent UVFP after thyroidectomy during the same period were included as a control group. The differences in baseline strobovideolaryngoscopy, acoustic and aerodynamic measures were compared between the two groups. Results:The tones of patients with temporary UVFP after thyroidectomy were all normal, and the proportions of abnormal vocal fords（vocal ford bowing, atrophy, and shortening）, ventricular adduction and glottic insufficiency were significantly lower than those of permanent UVFP patients; arytenoid cartilage stability and height mismatch of vocal ford tended to be better than permanent UVFP. The maximal phonation time（MPT） in patients with temporary UVFP was （8.5±4.1） s, which was significantly longer than （3.9±2.1） s in patients with permanent UVFP; fundamental frequency, mean airflow（MeAF） and mean subglottic pressure（SGP） were better in temporary UVFP than those in patients with permanent UVFP, but the difference did not reach statistical significance. Conclusion:None and mild glottic insufficiency, normal tone, ventricular adduction, and vocal ford appearances without vocal fold bowing, atrophy, and shortening, can be served as the predictors for the early recovery of vocal ford movement in temporary UVFP after thyroidectomy. The MPT less than 4 s, and MeAF, and SGP remarkably increased is the predictor of poor prognosis for vocal ford recovery.

Boosting Organic Afterglow Performance via a Two-Component Design Strategy Extracted from Macromolecular Self-Assembly.

Because intersystem crossing and phosphorescence decay are spin-forbidden in organic systems, it is challenging to obtain high-performance organic afterglow materials. Inspired by two-component design strategy from macromolecular self-assembly, here we report the utilization of synthetic polymers to control the excited state properties of difluoroboron ß-diketonate (BF2bdk) and deuterated BF2bdk compounds for the fabrication of room-temperature organic afterglow materials. The polymer component can interact with BF2bdk excited states by dipole-dipole interactions, lower BF2bdk S1 levels with insignificant effect on T1 levels, reduce ΔEST, and thus enhance intersystem crossing of BF2bdk excited states. The polymer component can also suppress intramolecular motion of BF2bdk triplets and protect BF2bdk triplets from oxygen quenching. The obtained BF2bdk-polymer afterglow materials exhibit emission lifetimes up to 2.2 s and high photoluminescence quantum yields under ambient conditions, display excellent processability and flexibility, and can function as efficient donors for excited state energy transfer to construct red afterglow materials.

A Deep Learning Approach to Predict Conductive Hearing Loss in Patients With Otitis Media With Effusion Using Otoscopic Images.

Importance: Otitis media with effusion (OME) is one of the most common causes of acquired conductive hearing loss (CHL). Persistent hearing loss is associated with poor childhood speech and language development and other adverse consequence. However, to obtain accurate and reliable hearing thresholds largely requires a high degree of cooperation from the patients. Objective: To predict CHL from otoscopic images using deep learning (DL) techniques and a logistic regression model based on tympanic membrane features. Design, Setting, and Participants: A retrospective diagnostic/prognostic study was conducted using 2790 otoscopic images obtained from multiple centers between January 2015 and November 2020. Participants were aged between 4 and 89 years. Of 1239 participants, there were 209 ears from children and adolescents (aged 4-18 years [16.87%]), 804 ears from adults (aged 18-60 years [64.89%]), and 226 ears from older people (aged >60 years, [18.24%]). Overall, 679 ears (54.8%) were from men. The 2790 otoscopic images were randomly assigned into a training set (2232 [80%]), and validation set (558 [20%]). The DL model was developed to predict an average air-bone gap greater than 10 dB. A logistic regression model was also developed based on otoscopic features. Main Outcomes and Measures: The performance of the DL model in predicting CHL was measured using the area under the receiver operating curve (AUC), accuracy, and F1 score (a measure of the quality of a classifier, which is the harmonic mean of precision and recall; a higher F1 score means better performance). In addition, these evaluation parameters were compared to results obtained from the logistic regression model and predictions made by three otologists. Results: The performance of the DL model in predicting CHL showed the AUC of 0.74, accuracy of 81%, and F1 score of 0.89. This was better than the results from the logistic regression model (ie, AUC of 0.60, accuracy of 76%, and F1 score of 0.82), and much improved on the performance of the 3 otologists; accuracy of 16%, 30%, 39%, and F1 scores of 0.09, 0.18, and 0.25, respectively. Furthermore, the DL model took 2.5 seconds to predict from 205 otoscopic images, whereas the 3 otologists spent 633 seconds, 645 seconds, and 692 seconds, respectively. Conclusions and Relevance: The model in this diagnostic/prognostic study provided greater accuracy in prediction of CHL in ears with OME than those obtained from the logistic regression model and otologists. This indicates great potential for the use of artificial intelligence tools to facilitate CHL evaluation when CHL is unable to be measured.

Manipulation of Triplet Excited States in Two-Component Systems for High-Performance Organic Afterglow Materials.

The past several years have witnessed the tremendous development of novel chemical structures, new design strategies and intriguing applications in the field of room-temperature phosphorescence (RTP) and organic afterglow materials. This Review article focuses on recent advancements of high-performance organic afterglow materials obtained by two-component design strategies such as a dopant-matrix, donor-acceptor, sensitization, and energy-transfer strategies. Based on some cutting-edge studies, organic afterglow efficiency has been largely improved, exceeding 90 % in several cases. Organic afterglow durations reach tens of seconds in phosphorescence systems and hours in donor-acceptor systems. Organic afterglow brightness outcompetes some inorganic afterglow materials in the first several seconds after ceasing excitation source. Organic afterglow colors cover the whole visible regions and extend to near-infrared regions with respectful afterglow efficiency. On the basis of these achievements, researchers demonstrate promising applications of organic afterglow materials in diverse fields, which has also been reviewed.

Investigating the use of a two-stage attention-aware convolutional neural network for the automated diagnosis of otitis media from tympanic membrane images: a prediction model development and validation study.

OBJECTIVES: This study investigated the usefulness and performance of a two-stage attention-aware convolutional neural network (CNN) for the automated diagnosis of otitis media from tympanic membrane (TM) images. DESIGN: A classification model development and validation study in ears with otitis media based on otoscopic TM images. Two commonly used CNNs were trained and evaluated on the dataset. On the basis of a Class Activation Map (CAM), a two-stage classification pipeline was developed to improve accuracy and reliability, and simulate an expert reading the TM images. SETTING AND PARTICIPANTS: This is a retrospective study using otoendoscopic images obtained from the Department of Otorhinolaryngology in China. A dataset was generated with 6066 otoscopic images from 2022 participants comprising four kinds of TM images, that is, normal eardrum, otitis media with effusion (OME) and two stages of chronic suppurative otitis media (CSOM). RESULTS: The proposed method achieved an overall accuracy of 93.4% using ResNet50 as the backbone network in a threefold cross-validation. The F1 Score of classification for normal images was 94.3%, and 96.8% for OME. There was a small difference between the active and inactive status of CSOM, achieving 91.7% and 82.4% F1 scores, respectively. The results demonstrate a classification performance equivalent to the diagnosis level of an associate professor in otolaryngology. CONCLUSIONS: CNNs provide a useful and effective tool for the automated classification of TM images. In addition, having a weakly supervised method such as CAM can help the network focus on discriminative parts of the image and improve performance with a relatively small database. This two-stage method is beneficial to improve the accuracy of diagnosis of otitis media for junior otolaryngologists and physicians in other disciplines.

[Study on Simultaneous Mercury and Lead Detection in Water Samples with PGNAA-XRF].

Prompt gamma neutron activation analysis (PGNAA) technology is used in heavy metals measurement. It is found that the detection accuracy of lead (Pb) is impacted heavily by mercury (Hg), because of thermal neutron cross section of mercury is much bigger than lead. In this paper, a new combined detection method was proposed to improve the lead measurement accuracy in situ environmental water rejects analysis by PGNAA-XRF. Thus, a combined measurement facility was developed to analyze the mercury and lead in water simultaneously. The geometry of set-up is determined by a series of simulations with the MCNP code to improve the detection efficiency of the prompt gamma-ray intensity (Iγ) and characteristic X-ray fluorescence intensity (IX) of element. The ideal sample height and cavity are 33 and 16 cm, respectively. The influence of the relationship between Iγ, IX and different concentration (ｃi) of Hg and Pb was researched by MCNP calculations, respectively. The simulation results showed that there were good linear relationships between Iγ, IX and ｃi, respectively. The empirical formula of combined detection method was proposed based on the above calculations. The limits of detection for Hg and Pb with the combined measurement instrument were 3.89 and 4.80 mg·kg-1, respectively. It is a significant increase in performance of the mercury and lead detection simultaneously.

[Fungus culture of the ear discharge and therapeutic effects in 60 outpatients with otitis externa].

OBJECTIVE: To assess the diagnosis and therapeutic effects for fungal otitis externa by clinical symptoms, endoscopic findings, and fungus culture of the ear discharge. METHOD: Sixty outpatients diagnosed with otitis externa were enrolled in the study. All patients were treated with a thorough debridement of the ear and one antifungal medication regimens (compound resorcinol solution) in case of a positive fungus culture. One subgroup of patients treated with daub glycerol during 2 weeks of follow-up. RESULT: Positive cultures were found in 42 cases. The efficacy was observed in all patients even in those who received only ear endoscopy. CONCLUSION: Fungal otitis externa could be easily diagnosed by ear endoscopy. A thorough debridement of the ear and utility of compound resorcinol solution is an easy and effective approach for treatment of fungal otitis externa.