Papillary Muscle Infarction by Cardiac MRI in Patients With Mitral Regurgitation.

BACKGROUND: Papillary muscle (PM) infarction (PMI) detected by cardiac magnetic resonance imaging (CMR) is associated with poor outcomes. Whether PM parameters provide more value for mitral regurgitation (MR) management currently remains unclear. Therefore, we examined the prognostic value of PMI using CMR in patients with MR. METHODS: Between March 2018 and July 2023, we retrospectively enrolled 397 patients with MR undergoing CMR. CMR was used to detect PMI qualitatively and quantitively. We also collected baseline clinical, echocardiography, and follow-up data. RESULTS: Of the 397 patients with MR (52.4 ± 13.9 years), 117 (29.5%) were assigned to the PMI group, with 280 (70.5%) in the non-PMI group. PMI was demonstrated more in the posteromedial PM (PM-PM, 98/117) than in the anterolateral PM (AL-PM, 45/117). Compared with patients without PMI, patients with PMI had a decreased AL-PM (41.5 ± 5.4 vs. 45.6 ± 5.3)/PM-PM diastolic length (35.0 ± 5.2 vs. 37.9 ± 4.0), PM-longitudinal strain (LS, 20.4 ± 6.1 vs. 24.9 ± 4.6), AL-PM-LS (19.7 ± 6.8 vs. 24.7 ± 5.6)/PM-PM-LS (21.2 ± 7.9 vs. 25.2 ± 6.0), and increased inter-PM distance (25.7 ± 8.0 vs. 22.7 ± 6.2, all p < 0.001). Multiple logistic regression analyses identified male sex (odds ratio [OR] = 3.65, 95% confidence interval = 1.881-7.081, p < 0.001) diabetes mellitus (OR/95% CI/p = 2.534/1.13-5.68/0.024), AL-PM diastolic length (OR/95% CI/p = 0.841/0.77-0.92/< 0.001), PM-PM diastolic length (OR/95% CI/p = 0.873/0.79-0.964/0.007), inter-PM distance (OR/95% CI/p = 1.087/1.028-1.15/0.003), AL-PM-LS (OR/95% CI/p = 0.892/0.843-0.94/< 0.001), and PM-PM-LS (OR/95% CI/p = 0.95/0.9-0.992/0.021) as independently associated with PMI. Over a 769 ± 367-day follow-up, 100 (25.2%) patients had arrhythmia. Cox regression analyses indicated that PMI (hazard ratio [HR]/95% CI/p = 1.644/1.062-2.547/0.026), AL-PM-LS (HR/95% CI/p = 0.937/0.903-0.973/0.001), and PM-PM-LS (HR/95% CI/p = 0.933/0.902-0.965/< 0.001) remained independently associated with MR. CONCLUSIONS: The CMR-derived PMI and LS parameters improve the evaluation of PM dysfunction, indicating a high risk for arrhythmia, and provide additive risk stratification for patients with MR.

The impact of REM sleep loss on human brain connectivity.

Brain function is vulnerable to the consequences of inadequate sleep, an adverse trend that is increasingly prevalent. The REM sleep phase has been implicated in coordinating various brain structures and is hypothesized to have potential links to brain variability. However, traditional imaging research have encountered challenges in attributing specific brain region activity to REM sleep, remained understudied at the whole-brain connectivity level. Through the spilt-night paradigm, distinct patterns of REM sleep phases were observed among the full-night sleep group (n = 36), the early-night deprivation group (n = 41), and the late-night deprivation group (n = 36). We employed connectome-based predictive modeling (CPM) to delineate the effects of REM sleep deprivation on the functional connectivity of the brain (REM connectome) during its resting state. The REM sleep-brain connectome was characterized by stronger connectivity within the default mode network (DMN) and between the DMN and visual networks, while fewer predictive edges were observed. Notably, connections such as those between the cingulo-opercular network (CON) and the auditory network, as well as between the subcortex and visual networks, also made significant contributions. These findings elucidate the neural signatures of REM sleep loss and reveal common connectivity patterns across individuals, validated at the group level.

Preparation and evaluation of germanium concentrate by ultrasonic purification of tannin germanium residue.

Germanium (Ge) is a dispersed metal primarily recovered from secondary Ge-containing resources. The traditional treatment method is hindered by incomplete impurity removal, resulting in a low grade of tannin germanium residue (TGR) and Ge concentrate, high production costs, and significant hazardous waste. This study proposes a new technology involving ultrasonic pre-purification of TGR to enhance the quality of Ge concentrate prepared by roasting. Under optimal conditions (ultrasonic power 225 W, liquid-solid ratio 7:1, H2SO4 concentration 20 g/L, reaction time 30 min, and reaction temperature 40 °C), the removal efficiencies of impurities Zn, Mg, Fe, As, and S from purified tannin germanium residue (PTGR) increased by 4.2%, 4.2%, 17.4%, 8.7%, and 2.9% respectively. Moreover, the Ge content in PTGR increased from 2.9% to 4.1%. The mechanism of ultrasonic action indicated the ultrasonic energy reduced the particle size of the reactants from 67.698 µm to 31.768 µm, thereby accelerating impurity removal. Roasting ultrasonic-purified tannin germanium residue (U-PTGR) at 650 °C with 40 L/h air flow for 120 min produced Ge concentrate with a Ge grade of 33.26%, which is 6.11% higher than the regular method. Analysis using XRD and HRTEM, combined with crystallite size calculation, revealed that the Ge concentrate prepared by U-PTGR exhibited low sintering degree, good crystal properties, and high crystallinity. Implementing this technology could save enterprises approximately $57,412 annually in production costs. Additionally, it holds significant practical importance in reducing hazardous waste emissions and promoting the high-quality development of the Ge industry.

Robust Quantum Gates against Correlated Noise in Integrated Quantum Chips.

As quantum circuits become more integrated and complex, additional error sources that were previously insignificant start to emerge. Consequently, the fidelity of quantum gates benchmarked under pristine conditions falls short of predicting their performance in realistic circuits. To overcome this problem, we must improve their robustness against pertinent error models besides isolated fidelity. Here, we report the experimental realization of robust quantum gates in superconducting quantum circuits based on a geometric framework for diagnosing and correcting various gate errors. Using quantum process tomography and randomized benchmarking, we demonstrate robust single-qubit gates against quasistatic noise and spatially correlated noise in a broad range of strengths, which are common sources of coherent errors in large-scale quantum circuits. We also apply our method to nonstatic noises and to realize robust two-qubit gates. Our Letter provides a versatile toolbox for achieving noise-resilient complex quantum circuits.

WS2 ribbon arrays with defined chirality and coherent polarity.

One-dimensional transition metal dichalcogenides exhibiting an enhanced bulk photovoltaic effect have the potential to exceed the Shockley-Queisser limit efficiency in solar energy harvest within p-n junction architectures. However, the collective output of these prototype devices remains a challenge. We report on the synthesis of single-crystalline WS2 ribbon arrays with defined chirality and coherent polarity through an atomic manufacturing strategy. The chirality of WS2 ribbon was defined by substrate couplings into tunable armchair, zigzag, and chiral species, and the polarity direction was determined by the ribbon-precursor interfacial energy along a coherent direction. A single armchair ribbon showed strong bulk photovoltaic effect and the further integration of ~1000 aligned ribbons with coherent polarity enabled upscaling of the photocurrent.

Pharmacokinetics, Pharmacodynamics, Safety, and Tolerability of Stapokibart in Healthy Volunteers and Adult Subjects with Atopic Dermatitis.

INTRODUCTION: Stapokibart, a novel humanized anti-interleukin (IL)-4 receptor alpha monoclonal antibody, inhibits the signaling of IL-4 and IL-13, which are key drivers of type 2 inflammation in atopic dermatitis (AD). This study aimed to assess the safety, tolerability, pharmacokinetics (PK), and pharmacodynamics (PD) of stapokibart in a randomized, double-blind, placebo-controlled single ascending dose (SAD) study and a multiple ascending dose (MAD) study. METHODS: The SAD study enrolled 33 healthy male adults aged 18-65 years at a single center. The MAD study enrolled 39 patients with moderate-to-severe AD aged 18-70 years at seven centers. Enrolled subjects were randomized to subcutaneous (SC) doses of stapokibart (75-600 mg) or placebo. Serum thymus and activation-regulated chemokine (TARC) and total immunoglobulin E (IgE) were measured as PD biomarkers for stapokibart. RESULTS: Similar PK characteristics were observed in healthy volunteers and subjects with AD after the initial administration. Stapokibart exhibited non-linear pharmacokinetics in both types of subjects. Following single doses, the mean maximum serum concentration (Cmax) ranged from 5.3 to 63.0 µg/mL, median Tmax ranged from 3.0 to 7.0 days, mean terminal half-life (t1/2z) ranged from 2.39 to 7.43 days, and mean apparent volume (Vz/F) ranged from 3.64 to 6.73 L in healthy subjects. The mean AUC accumulation ratio was 2.29 in subjects with AD after three doses of stapokibart 300 mg administered every 2 weeks. The median serum total IgE and TARC levels on day 43 decreased from baseline by 14.9-25.2% and 48.6-77.0%, respectively, among subjects with AD receiving three doses of stapokibart. No subjects developed grade ≥ 3 adverse events (AEs) or serious AEs or discontinued the study because of AEs. The incidence of AEs was similar between stapokibart and placebo groups. CONCLUSION: Stapokibart showed favorable pharmacokinetics, pharmacodynamics, safety, and tolerability in the SAD and MAD studies. Based on these results, phase II and phase III trials of stapokibart have been performed in subjects with moderate-to-severe AD. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT06161090 (29 November, 2023), NCT04893941 (15 May, 2021).

Room-Temperature Band-Aligned Infrared Heterostructures for Integrable Sensing and Communication.

The demand for miniaturized and integrated multifunctional devices drives the progression of high-performance infrared photodetectors for diverse applications, including remote sensing, air defense, and communications, among others. Nonetheless, infrared photodetectors that rely solely on single low-dimensional materials often face challenges due to the limited absorption cross-section and suboptimal carrier mobility, which can impair sensitivity and prolong response times. Here, through experimental validation is demonstrated, precise control over energy band alignment in a type-II van der Waals heterojunction, comprising vertically stacked 2D Ta2NiSe5 and the topological insulator Bi2Se3, where the configuration enables polarization-sensitive, wide-spectral-range photodetection. Experimental evaluations at room temperature reveal that the device exhibits a self-powered responsivity of 0.48 A·W-1, a specific directivity of 3.8 × 1011 cm·Hz1/2·W-1, a response time of 151 µs, and a polarization ratio of 2.83. The stable and rapid photoresponse of the device underpins the utility in infrared-coded communication and dual-channel imaging, showing the substantial potential of the detector. These findings articulate a systematic approach to developing miniaturized, multifunctional room-temperature infrared detectors with superior performance metrics and enhanced capabilities for multi-information acquisition.

Autonomous Stabilization of Fock States in an Oscillator against Multiphoton Losses.

Fock states with a well-defined number of photons in an oscillator have shown a wide range of applications in quantum information science. Nonetheless, their usefulness has been marred by single and multiphoton losses due to unavoidable environment-induced dissipation. Though several dissipation engineering methods have been developed to counteract the leading single-photon-loss error, averting multiple-photon losses remains elusive. Here, we experimentally demonstrate a dissipation engineering method that autonomously stabilizes multiphoton Fock states against losses of multiple photons using a cascaded selective photon-addition operation in a superconducting quantum circuit. Through measuring the photon-number populations and Wigner tomography of the oscillator states, we observe a prolonged preservation of nonclassical Wigner negativities for the stabilized Fock states |N⟩ with N=1, 2, 3 for a duration of about 10 ms. Furthermore, the dissipation engineering method demonstrated here also facilitates the implementation of a nonunitary operation for resetting a binomially encoded logical qubit. These results highlight potential applications in error-correctable quantum information processing against multiple-photon-loss errors.

Robust Domain Adaptive Object Detection With Unified Multi-Granularity Alignment.

Domain adaptive detection aims to improve the generalization of detectors on target domain. To reduce discrepancy in feature distributions between two domains, recent approaches achieve domain adaption through feature alignment in different granularities via adversarial learning. However, they neglect the relationship between multiple granularities and different features in alignment, degrading detection. Addressing this, we introduce a unified multi-granularity alignment (MGA)-based detection framework for domain-invariant feature learning. The key is to encode the dependencies across different granularities including pixel-, instance-, and category-levels simultaneously to align two domains. Specifically, based on pixel-level features, we first develop an omni-scale gated fusion (OSGF) module to aggregate discriminative representations of instances with scale-aware convolutions, leading to robust multi-scale detection. Besides, we introduce multi-granularity discriminators to identify where, either source or target domains, different granularities of samples come from. Note that, MGA not only leverages instance discriminability in different categories but also exploits category consistency between two domains for detection. Furthermore, we present an adaptive exponential moving average (AEMA) strategy that explores model assessments for model update to improve pseudo labels and alleviate local misalignment problem, boosting detection robustness. Extensive experiments on multiple domain adaption scenarios validate the superiority of MGA over other approaches on FCOS and Faster R-CNN detectors. Code will be released at https://github.com/tiankongzhang/MGA.

Mechanism of Germanium Adsorption by Iron Hydroxide Colloids during the Leaching Process of Secondary Zinc Oxide.

In the leaching process of secondary zinc oxide, there is a problem of germanium loss caused by the colloidal adsorption of germanium by iron hydroxide (Fe(OH)3) formed by Fe3+ hydrolysis. In response to this, this article elucidates the hydrolysis conditions of Fe3+ and the adsorption mechanism of the Fe(OH)3 colloid on germanium through theoretical analysis and simulation of the adsorption process. The coexistence of Fe3+ and H2GeO3 requires high acidity conditions (pH < 1.53 at 25 °C). The adsorption of germanium by the Fe(OH)3 colloid is a spontaneous exothermic entropy reduction process, which conforms to a pseudo-second-order kinetic model and includes three stages: fast, slow, and equilibrium. In addition, the adsorption process can be fitted by the Langmuir isotherm adsorption model, mainly consisting of monolayer and chemical adsorption. The Fe(OH)3 colloid has a great adsorption capacity for germanium at 328 K, and the equilibrium adsorption capacity is 261.15 mg/g in 40 min. During leaching, the adsorption of germanium by Fe(OH)3 colloids can be inhibited by increasing the reaction temperature, controlling the pH value of the solution system, and suppressing the formation of Fe3+ at the source. This study provides direction for how to suppress the adsorption of germanium by Fe(OH)3 colloids during the leaching process of secondary zinc oxide, which is of great significance for improving the germanium leaching efficiency and fully utilizing limited germanium resources.

Coronary artery segmentation in CCTA images based on multi-scale feature learning.

BACKGROUND: Coronary artery segmentation is a prerequisite in computer-aided diagnosis of Coronary Artery Disease (CAD). However, segmentation of coronary arteries in Coronary Computed Tomography Angiography (CCTA) images faces several challenges. The current segmentation approaches are unable to effectively address these challenges and existing problems such as the need for manual interaction or low segmentation accuracy. OBJECTIVE: A Multi-scale Feature Learning and Rectification (MFLR) network is proposed to tackle the challenges and achieve automatic and accurate segmentation of coronary arteries. METHODS: The MFLR network introduces a multi-scale feature extraction module in the encoder to effectively capture contextual information under different receptive fields. In the decoder, a feature correction and fusion module is proposed, which employs high-level features containing multi-scale information to correct and guide low-level features, achieving fusion between the two-level features to further improve segmentation performance. RESULTS: The MFLR network achieved the best performance on the dice similarity coefficient, Jaccard index, Recall, F1-score, and 95% Hausdorff distance, for both in-house and public datasets. CONCLUSION: Experimental results demonstrate the superiority and good generalization ability of the MFLR approach. This study contributes to the accurate diagnosis and treatment of CAD, and it also informs other segmentation applications in medicine.

Preparation of Wheat Straw Hot-Pressed Board through Coupled Dilute Acid Pretreatment and Surface Modification.

The production of wheat straw waste board materials encounters challenges, including inadequate inherent adhesiveness and the utilization of environmentally harmful adhesives. Employing a hot-pressed method for converting wheat straw into board materials represents a positive stride towards the resourceful utilization of agricultural wastes. This study primarily focuses on examining the influence of hot-pressing process conditions on the mechanical properties of wheat straw board materials pretreated with dilute acid. Additionally, it assesses the necessity of dilute acid treatment and optimizes the hot-pressing conditions to achieve optimal results at 15 MPa, 2 h, and 160 °C. Furthermore, a comprehensive process is developed for preparing wheat straw hot-pressed board materials by combining dilute acid pretreatment with surface modification treatments, such as glutaraldehyde, citric acid, and rosin. Finally, a thorough characterization of the mechanical properties of the prepared board materials is conducted. The results indicate a substantial improvement in tensile strength across all modified wheat straw board materials compared to untreated ones. Notably, boards treated with glutaraldehyde exhibited the most significant enhancement, achieving a tensile strength of 463 kPa, bending strength of 833 kPa, and a water absorption rate of 14.14%. This study demonstrates that combining dilute acid pretreatment with surface modification treatments effectively enhances the performance of wheat straw board materials, offering a sustainable alternative to traditional wood-based board materials.

Predicting who has delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage using machine learning approach: a multicenter, retrospective cohort study.

BACKGROUND: Early prediction of delayed cerebral ischemia (DCI) is critical to improving the prognosis of aneurysmal subarachnoid hemorrhage (aSAH). Machine learning (ML) algorithms can learn from intricate information unbiasedly and facilitate the early identification of clinical outcomes. This study aimed to construct and compare the ability of different ML models to predict DCI after aSAH. Then, we identified and analyzed the essential risk of DCI occurrence by preoperative clinical scores and postoperative laboratory test results. METHODS: This was a multicenter, retrospective cohort study. A total of 1039 post-operation patients with aSAH were finally included from three hospitals in China. The training group contained 919 patients, and the test group comprised 120 patients. We used five popular machine-learning algorithms to construct the models. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, precision, and f1 score were used to evaluate and compare the five models. Finally, we performed a Shapley Additive exPlanations analysis for the model with the best performance and significance analysis for each feature. RESULTS: A total of 239 patients with aSAH (23.003%) developed DCI after the operation. Our results showed that in the test cohort, Random Forest (RF) had an AUC of 0.79, which was better than other models. The five most important features for predicting DCI in the RF model were the admitted modified Rankin Scale, D-Dimer, intracranial parenchymal hematoma, neutrophil/lymphocyte ratio, and Fisher score. Interestingly, clamping or embolization for the aneurysm treatment was the fourth button-down risk factor in the ML model. CONCLUSIONS: In this multicenter study, we compared five ML methods, among which RF performed the best in DCI prediction. In addition, the essential risks were identified to help clinicians monitor the patients at high risk for DCI more precisely and facilitate timely intervention.

Two {CuI[P4Mo6]2}-Based Coordination Polymers Incorporating In Situ Converted Tetrapyridyl Ligands for Trace Analysis of Nitrofuran Antibiotics.

Nitrofurans are important synthetic broad-spectrum antibacterial drugs with the basic structure of 5-nitrofuran. Due to their toxicity, it is essential to develop a sensitive sensor with strong anti-interference capabilities for their detection. In this work, two {P4Mo6O31}12--based compounds, [H4(HPTTP)]2{CuI[Mo12O24(OH)6(PO4)3(HPO4)(H2PO4)4]}·xH2O (x = 13 for (1), 7 for (2); HPTTP = 4,4',4″,4‴-(1H-pyrrole-2,3,4,5-tetrayl)tetrapyridine), exhibiting similar coordination but distinct stacking modes. Both compounds were synthesized and used for the electrochemical detection of nitrofuran antibiotics. The tetrapyridine-based ligand was generated in situ during assembly, and its potential mechanism was discussed. Composite electrode materials, formed by mixing graphite powder with compounds 1-2 and physically grinding them, proved to be highly effective in the electrochemical trace detection of furazolidone (FZD) and furaltadone hydrochloride (FTD·HCl) under optimal conditions. Besides, the possible electrochemical detection mechanisms of two nitro-antibiotics were studied.

Predicting major adverse cardiovascular events within 3 years by optimization of radiomics model derived from pericoronary adipose tissue on coronary computed tomography angiography: a case-control study.

BACKGROUND: Coronary inflammation induces changes in pericoronary adipose tissue (PCAT) can be detected by coronary computed tomography angiography (CCTA). Our aim was to investigate whether different PCAT radiomics model based on CCTA could improve the prediction of major adverse cardiovascular events (MACE) within 3 years. METHODS: This retrospective study included 141 consecutive patients with MACE and matched to patients with non-MACE (n = 141). Patients were randomly assigned into training and test datasets at a ratio of 8:2. After the robust radiomics features were selected by using the Spearman correlation analysis and the least absolute shrinkage and selection operator, radiomics models were built based on different machine learning algorithms. The clinical model was then calculated according to independent clinical risk factors. Finally, an overall model was established using the radiomics features and the clinical factors. Performance of the models was evaluated for discrimination degree, calibration degree, and clinical usefulness. RESULTS: The diagnostic performance of the PCAT model was superior to that of the RCA-model, LAD-model, and LCX-model alone, with AUCs of 0.723, 0.675, 0.664, and 0.623, respectively. The overall model showed superior diagnostic performance than that of the PCAT-model and Cli-model, with AUCs of 0.797, 0.723, and 0.706, respectively. Calibration curve showed good fitness of the overall model, and decision curve analyze demonstrated that the model provides greater clinical benefit. CONCLUSION: The CCTA-based PCAT radiomics features of three major coronary arteries have the potential to be used as a predictor for MACE. The overall model incorporating the radiomics features and clinical factors offered significantly higher discrimination ability for MACE than using radiomics or clinical factors alone.

Evaporating crystallization effect of ammonium sulfate at atmospheric pressure under the action of ultrasound.

Ultrasound enhanced evaporating crystallization has been proposed to solve the problems of low crystallization yield and uneven particle size in the evaporating crystallization process of ammonium sulfate solution at atmospheric pressure. The effects of key operating parameters, including the ultrasound power, stirring speed, pH value, and ultrasound time, on the yield of ammonium sulfate product and the duration of solid-liquid transformation time are studied. The results show that the ultrasound crystallization can increase the ammonium sulfate yield by 52.9 %, reduce the solid-liquid transformation time of ammonium sulfate by 10 %, and obtain ammonium sulfate products with higher crystallinity and more uniform particle size. Ultrasound promotes the crystallization of ammonium sulfate by enhancing the transfer of heat in the solution and reducing the supersolubility of the ammonium sulfate solution from 937.5 g/L to 833.33 g/L. This study provides experimental justification for the use of ultrasound in atmospheric evaporative crystallization.

Synaptotagmins family affect glucose transport in retinal pigment epithelial cells through their ubiquitination-mediated degradation and glucose transporter-1 regulation.

BACKGROUND: Synaptotagmins (SYTs) are a family of 17 membrane transporters that function as calcium ion sensors during the release of Ca2+-dependent neurotransmitters and hormones. However, few studies have reported whether members of the SYT family play a role in glucose uptake in diabetic retinopathy (DR) through Ca2+/glucose transporter-1 (GLUT1) and the possible regulatory mechanism of SYTs. AIM: To elucidate the role of the SYT family in the regulation of glucose transport in retinal pigment epithelial cells and explore its potential as a therapeutic target for the clinical management of DR. METHODS: DR was induced by streptozotocin in C57BL/6J mice and by high glucose medium in human retinal pigment epithelial cells (ARPE-19). Bioinformatics analysis, reverse transcriptase-polymerase chain reaction, Western blot, flow cytometry, ELISA, HE staining, and TUNEL staining were used for analysis. RESULTS: Six differentially expressed proteins (SYT2, SYT3, SYT4, SYT7, SYT11, and SYT13) were found between the DR and control groups, and SYT4 was highly expressed. Hyperglycemia induces SYT4 overexpression, manipulates Ca2+ influx to induce GLUT1 fusion with the plasma membrane, promotes abnormal expression of the glucose transporter GLUT1 and excessive glucose uptake, induces ARPE-19 cell apoptosis, and promotes DR progression. Parkin deficiency inhibits the proteasomal degradation of SYT4 in DR, resulting in SYT4 accumulation and enhanced GLUT1 fusion with the plasma membrane, and these effects were blocked by oe-Parkin treatment. Moreover, dysregulation of the myelin transcription factor 1 (Myt1)-induced transcription of SYT4 in DR further activated the SYT4-mediated stimulus-secretion coupling process, and this process was inhibited in the oe-MYT1-treated group. CONCLUSION: Our study reveals the key role of SYT4 in regulating glucose transport in retinal pigment epithelial cells during the pathogenesis of DR and the underlying mechanism and suggests potential therapeutic targets for clinical DR.

AttMOT: Improving Multiple-Object Tracking by Introducing Auxiliary Pedestrian Attributes.

Multiobject tracking (MOT) is a fundamental problem in computer vision with numerous applications, such as intelligent surveillance and automated driving. Despite the significant progress made in MOT, pedestrian attributes, such as gender, hairstyle, body shape, and clothing features, which contain rich and high-level information, have been less explored. To address this gap, we propose a simple, effective, and generic method to predict pedestrian attributes to support general reidentification (Re-ID) embedding. We first introduce attribute multi-object tracking (AttMOT), a large, highly enriched synthetic dataset for pedestrian tracking, containing over 80k frames and six million pedestrian identity switches (IDs) with different times, weather conditions, and scenarios. To the best of authors' knowledge, AttMOT is the first MOT dataset with semantic attributes. Subsequently, we explore different approaches to fuse Re-ID embedding and pedestrian attributes, including attention mechanisms, which we hope will stimulate the development of attribute-assisted MOT. The proposed method attribute-assisted method (AAM) demonstrates its effectiveness and generality on several representative pedestrian MOT benchmarks, including MOT17 and MOT20, through experiments on the AttMOT dataset. When applied to the state-of-the-art trackers, AAM achieves consistent improvements in multi-object tracking accuracy (MOTA), higher order tracking accuracy (HOTA), association accuracy (AssA), IDs, and IDF1 scores. For instance, on MOT17, the proposed method yields a + 1.1 MOTA, + 1.7 HOTA, and + 1.8 IDF1 improvement when used with FairMOT. To further encourage related research, we release the data and code at https://github.com/HengLan/AttMOT.

Deciphering Authentic Nociceptive Thalamic Responses in Rats.

The thalamus and its cortical connections play a pivotal role in pain information processing, yet the exploration of its electrophysiological responses to nociceptive stimuli has been limited. Here, in 2 experiments we recorded neural responses to nociceptive laser stimuli in the thalamic (ventral posterior lateral nucleus and medial dorsal nucleus) and cortical regions (primary somatosensory cortex [S1] and anterior cingulate cortex) within the lateral and medial pain pathways. We found remarkable similarities in laser-evoked brain responses that encoded pain intensity within thalamic and cortical regions. Contrary to the expected temporal sequence of ascending information flow, the recorded thalamic response (N1) was temporally later than its cortical counterparts, suggesting that it may not be a genuine thalamus-generated response. Importantly, we also identified a distinctive component in the thalamus, i.e., the early negativity (EN) occurring around 100 ms after the onset of nociceptive stimuli. This EN component represents an authentic nociceptive thalamic response and closely synchronizes with the directional information flow from the thalamus to the cortex. These findings underscore the importance of isolating genuine thalamic neural responses, thereby contributing to a more comprehensive understanding of the thalamic function in pain processing. Additionally, these findings hold potential clinical implications, particularly in the advancement of closed-loop neuromodulation treatments for neurological diseases targeting this vital brain region.

Application of ultrasonic-enhanced active seed crystals in the removal of sodium oxalate from alumina refinery waste liquor.

When organic matter, especially sodium oxalate (Na2C2O4), accumulates to a certain extent, it will seriously affect the alumina production process in the refinery and therefore urgently needs to be removed. This work attempts to illuminate the benefits of ultrasonic intensification of the crystallization process of Na2C2O4, taking the alumina refinery waste liquor, i.e., flat plate washing liquor, as a case study. The effects of different operating parameters (seed crystal addition amount, caustic soda concentration, reaction time, ultrasonic power) on the crystallization behavior and yield are discussed, and it is found that ultrasonic can increase the Na2C2O4 removal rate to 70.4%. The addition of ultrasonic promotes the morphological evolution of Na2C2O4 and is of great significance to the optimization of the components of the precipitated Na2C2O4. Specifically, the proportion of Na2C2O4 in the crystallized product reaches 64% with conventional conditions, while it reaches 77% with ultrasonic conditions. Therefore, ultrasonic can greatly reduce the alkali loss caused by the crystallization process of Na2C2O4 in flat plate washing liquor, which has great economic benefits.