ObjectiveThe widespread adoption of portable fundus cameras for primary care and community screening is hindered by limitations in current autofocus(AF) technologies. Image-based methods relying on sharpness evaluation require iterative searches, resulting in slow convergence, while projection-based techniques are susceptible to optical artifacts and calibration errors. To address these challenges, this study introduces a novel AF system based on direct wavefront sensing, designed to deliver simultaneous high speed, high precision, and operational robustness within the compact form factor essential for portable ophthalmic devices. MethodsOur approach fundamentally reimagines the AF process by directly measuring the ocular wavefront aberration. We developed a custom portable fundus camera integrating a miniaturized Shack-Hartmann wavefront sensor (SHWS) into the optical path. An 850 nm laser diode projects a point source onto the retina via oblique illumination to minimize corneal reflections. Light scattered from this spot carries the eye’s refractive error through the imaging optics and is directed to the SHWS, positioned at a plane optically conjugate to the primary color CMOS imaging sensor. A microlens array within the SHWS samples the incident wavefront, generating a pattern of focal spots on a CCD. Real-time centroid analysis of these spots provides a map of local wavefront slopes. These measurements are processed through a singular value decomposition (SVD) algorithm to fit a Zernike polynomial basis set, enabling real-time reconstruction of the wavefront phase. The defocus component (S) is extracted from the second-order Zernike coefficients, providing a direct, quantitative measure of the refractive error in diopters. This value serves as a precise error signal in a closed-loop control system, which commands a voice-coil actuated focusing lens to its null position in a single, deterministic step, eliminating the need for iterative search algorithms. ResultsComprehensive evaluation demonstrated the system’s high performance. Testing on a calibrated model eye (OEMI-7) established a highly linear relationship between the computed defocus S and the focusing lens position across a ±20 Diopter (D) compensation range, achievable within a 5 mm mechanical travel. The system achieved a focusing precision of 0.08 D, corresponding to an 18-fold improvement over a conventional projection spot-size method tested under identical conditions. The total focus acquisition time, encompassing wavefront measurement, computation, and lens actuation, averaged under 0.5 s. Clinical validation with 25 human volunteers (50 eyes, refractive range -15 D to +10 D) confirmed practical efficacy. The wavefront-sensing AF succeeded in 92% of attempts with a mean time of 0.5 s, substantially outperforming a projection-based benchmark which achieved only a 32% success rate with an average time of 4.25 s. The system provided instantaneous directional guidance and maintained stability during minor ocular movements. Objective assessment of image quality, via amplitude contrast of retinal vasculature, showed consistent and significant enhancement following AF correction across the entire tested diopter range. ConclusionThis work successfully implements and validates a direct wavefront-sensing autofocus paradigm for portable fundus cameras. By directly quantifying and compensating for the optical defocus aberration, this method bypasses the fundamental limitations of image-processing and projection-based techniques, enabling rapid, precise, and deterministic diopter compensation. The developed system delivers an exceptional combination of a wide operational range (±20 D), high accuracy (0.08 D), fast convergence (0.5 s), and a compact physical footprint. This technology provides a practical and high-performance focusing solution capable of enhancing the reliability, throughput, and diagnostic utility of portable retinal imaging in large-scale screening applications. Future efforts will be directed towards system cost optimization and performance adaptation for diverse ocular conditions.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Five saponins were isolated from the kernels of Momordica cochinchinensis, by macroporous resin, silica gel, ODS column chromatography, and semi preparative HPLC. Based on MS and NMR analysis, combining with alkaline hydrolysis and acid hydrolysis, their structures were identified as: gypsogenin-3-O-{β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonosyl}-28-O-β-D-xylopyranosyl (1→3)-[β-D-xylopyranosyl (1→4)]-α-L-rhamnopyranosyl (1→2)-β-D-fucopyranoside (1), quillaic acid-3-O-{β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonosyl}-28-O-β-D-xylopyranosyl (1→3)-[β-D-xylopyranosyl (1→4)]-α-L-rhamnopyranosyl (1→2)-β-D-fucopyranoside (2), gypsogenin-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside sodium (3), quillaic acid-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside sodium (4), 18α-quillaic acid-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside (5). Compounds 1-5 were new compounds, and named as mubezhisides A, B, C, D, E, respectively. They all could obviously inhibited the growth of Candida albicans, C. parapsilosis, and C. tropicalis.

Objective:To screen the risk factors for non-complete procedural success of transvenous lead extraction(TLE),and to establish a prediction model based on the results and evaluate its predictive efficacy.Methods:A total of 1 029 patients who underwent TLE in Peking University People's Hospital from January 2014 to December 2020 were enrolled and divided into training set(n=720)and validation set(n=309)using the random number method.There were no statistically significant differences among the variables in the training set and the validation set.The training set was divided into the complete procedural success(CPS)group(n=664)and the non-CPS group(n=56).Univariate analysis was employed to screen the relevant indicators of non-CPS,followed by binary logistic regression analysis to identify the independent risk factors of non-CPS.Subsequently,a predictive model and nomogram were constructed.The receiver operating characteristic(ROC)curve analysis was applied to evaluate the ability of the model to distinguish non-CPS from TLE patients in the training set and validation set.The Hosmer-Lemeshow goodness-of-fit test was used to assess the consistency between the predicted risk and the actual risk of the model.Results:Univariate analysis showed that the relevant variables with P<0.1 including the age at the first implantation of the lead,the number of leads extracted,the oldest dwell time of lead extracted,the presence of abandoned leads,non-manual traction for lead extracted,the number of extracted leads>3,bilateral lead implantation,and the indications for TLE.The binary logistic regression analysis revealed that the presence of abandoned leads(OR=2.252,95%CI:1.111-4.564,P=0.024),the oldest dwell time of the extracted leads(OR=1.009,95%CI:1.005-1.012,P<0.001),and the number of extracted leads>3(OR=3.177,95%CI:1.306-7.733,P=0.011)were independent risk factors for non-CPS of TLE.ROC curve analysis revealed that the area under the ROC curve(AUC)of the training set was 0.80(95%CI:0.75-0.85,P<0.001).The AUC of the validation set was 0.81(95%CI:0.72-0.90,P<0.001).The Hosmer-Lemeshow goodness-of-fit test indicated that the P values of both the training set(P=0.089)and the validation set(P=0.136)were greater than 0.05.Conclusions:The presence of abandoned leads,the oldest dwell time of lead extracted,and the number of extracted leads>3 are independent risk factors for non-CPS in patients undergoing TLE.The nomogram model based on the above factors has satisfactory predictive ability.

Clear aligner treatment is a novel technique in current orthodontic practice. Distinct from traditional fixed orthodontic appliances, clear aligners have different material features and biomechanical characteristics and treatment efficiencies, presenting new clinical challenges. Therefore, a comprehensive and systematic description of the key clinical aspects of clear aligner treatment is essential to enhance treatment efficacy and facilitate the advancement and wide adoption of this new technique. This expert consensus discusses case selection and grading of treatment difficulty, principle of clear aligner therapy, clinical procedures and potential complications, which are crucial to the clinical success of clear aligner treatment.
Humans ; Consensus ; Orthodontic Appliance Design ; Orthodontic Appliances, Removable ; Tooth Movement Techniques/methods* ; Malocclusion/therapy* ; Orthodontics, Corrective/instrumentation*

OBJECTIVE: To investigate the role and mechanism of the cyclic guanosine monophosphate-adenosine monophosphate synthase/stimulator of interferon gene (cGAS/STING) pathway in oleic acid-induced acute lung injury (ALI) in mice. METHODS: Male wild-type C57BL/6J mice were randomly divided into five groups (each n = 10): normal control group, ALI model group, and 5, 50, 500 μg/kg inhibitor pretreatment groups. The ALI model was established by tail vein injection of oleic acid (7 mL/kg), while the normal control group received no intervention. The inhibitor pretreatment groups were intraperitoneally injected with the corresponding doses of cGAS inhibitor RU.521 respectively 1 hour before modeling. At 24 hours post-modeling, blood was collected, and mice were sacrificed. Lung tissue pathological changes were observed under light microscopy after hematoxylin-eosin (HE) staining, and pathological scores were assessed. Western blotting was used to detect the protein expressions of cGAS, STING, phosphorylated TANK-binding kinase 1 (p-TBK1), phosphorylated interferon regulatory factor 3 (p-IRF3), and phosphorylated nuclear factor-κB p65 (p-NF-κB p65) in lung tissue. Immunohistochemistry was performed to observe STING and p-NF-κB positive expressions in lung tissue. Serum interferon-β (IFN-β) levels were measured by enzyme-linked immunosorbent assay (ELISA). RESULTS: Compared with the normal control group, the ALI model group exhibited significant focal alveolar thickening, intra-alveolar hemorrhage, pulmonary capillary congestion, and neutrophil infiltration in the pulmonary interstitium and alveoli, along with markedly increased pathological scores (10.33±0.58 vs. 1.33±0.58, P < 0.05). Protein expressions of cGAS, STING, p-TBK1, p-IRF3, and p-NF-κB p65 in lung tissue significantly increased [cGAS protein (cGAS/β-actin): 1.24±0.02 vs. 0.56±0.02, STING protein (STING/β-actin): 1.27±0.01 vs. 0.55±0.01, p-TBK1 protin (p-TBK1/β-actin): 1.34±0.03 vs. 0.22±0.01, p-IRF3 protein (p-IRF3/β-actin): 1.23±0.02 vs. 0.36±0.01, p-NF-κB p65 protein (p-NF-κB p65/β-actin): 1.30±0.02 vs. 0.53±0.02, all P < 0.05], positive expressions of STING and p-NF-κB in lung tissue were significantly elevated [STING (A value): 0.51±0.03 vs. 0.30±0.07, p-NF-κB (A value): 0.57±0.05 vs. 0.31±0.03, both P < 0.05], and serum IFN-β levels were also significantly higher (ng/L: 256.02±3.84 vs. 64.15±1.17, P < 0.05). The cGAS inhibitor pretreatment groups showed restored alveolar structural integrity, reduced inflammatory cell infiltration, and decreased hemorrhage area, along with dose-dependent lower pathological scores as well as the protein expressions of cGAS, STING, p-TBK1, p-IRF3 and p-NF-κB p65 in lung tissue, with significant differences between the 500 μg/kg inhibitor group and ALI model group [pathological score: 2.67±0.58 vs. 10.33±0.58, cGAS protein (cGAS/β-actin): 0.56±0.03 vs. 1.24±0.02, STING protein (STING/β-actin): 0.67±0.03 vs. 1.27±0.01, p-TBK1 protein (p-TBK1/β-actin): 0.28±0.01 vs. 1.34±0.03, p-IRF3 protein (p-IRF3/β-actin): 0.32±0.01 vs. 1.23±0.02, p-NF-κB p65 protein (p-NF-κB p65/β-actin): 0.63±0.01 vs. 1.30±0.02, all P < 0.05]. Compared with the ALI model group, positive expressions of STING and p-NF-κB in lung tissue were significantly reduced in the 500 μg/kg inhibitor group [STING (A value): 0.40±0.01 vs. 0.51±0.03, p-NF-κB (A value): 0.43±0.02 vs. 0.57±0.05, both P < 0.05], and serum IFN-β levels were also markedly reduced (ng/L: 150.03±6.19 vs. 256.02±3.84, P < 0.05). CONCLUSIONS The cGAS/STING pathway is activated in oleic acid-induced ALI, leading to exacerbated inflammatory responses and increased lung damage. RU.521 can inhibit cGAS, thereby down-regulating the expression of pathway proteins and cytokines, and providing protection to lung tissue.
Animals ; Acute Lung Injury/chemically induced* ; Male ; Nucleotidyltransferases/metabolism* ; Mice ; Signal Transduction ; Mice, Inbred C57BL ; Membrane Proteins/metabolism* ; Oleic Acid/adverse effects* ; Transcription Factor RelA/metabolism* ; Lung/pathology* ; Interferon Regulatory Factor-3/metabolism* ; Disease Models, Animal

Objective To investigate the factors influencing the occurrence of coma in patients with acute basilar artery occlusion(BAO)and the favorable prognosis in the coma patients after receiving mechanical thrombectomy(MT).Methods The clinical data and imaging materials of 102 patients with acute BAO,who received MT at the First Affiliated Hospital of Soochow University of China from January 2016 to April 2024,were retrospectively analyzed.According to whether the patient had a coma or not on admission,the patients were divided into non-coma group and coma group.The clinical data and imaging findings were compared between the two groups.Multivariate logistic regression analysis was performed to identify the factors influencing the occurrence of coma.The modified Rankin scale(mRS)score was used to evaluate 90-day clinical prognosis.The patients of coma group were further divided into favorable prognosis subgroup(mRS:0-3 points)and poor prognosis subgroup(mRS:4-6 points).Baseline date and surgical data were compared between the two subgroups,and multivariate logistic regression analysis was conducted to identify the factors associated with a favorable prognosis in coma patients after receiving mechanical thrombectomy.Results Of the 102 patients with acute BAO,54 were in unconscious state on admission(coma group)and 48 were in conscious state(non-coma group)on admission.Multivariate logistic regression analysis revealed that coexisting cardiovascular diseases with severe cardiac insufficiency or moderate to severe coronary artery stenosis(P=0.009)and low BATMAN score(P＜0.001)were the independent risk factors for the occurrence of coma in acute BAO patients.Among the 54 unconscious patients who received MT treatment,favorable prognosis was obtained in 13 and poor prognosis was seen in 41.Multivariate logistic regression analysis indicated that high BATMAN score(P=0.017)was the independent influencing factor for favorable prognosis in acute BAO patients with coma after receiving MT therapy.Conclusion Acute BAO patients having coexisting cardiovascular diseases with severe cardiac insufficiency or moderate to severe coronary artery stenosis or having low BATMAN score are more likely to develop coma.Acute BAO patients with coma having high BATMAN score are more likely to obtain a favorable prognosis after receiving MT therapy.

Objective:To evaluate the relationship between transverse sinus stenosis (TSS) and cerebral blood flow in normal adults based on four-dimensional flow (4D Flow) MRI.Methods:The study was a cross-sectional study. Totally 81 normal volunteers who underwent magnetic resonance venography (MRV) and 4D Flow MRI were prospectively enrolled at Beijing Friendship Hospital, Capital Medical University from January 2020 to December 2022. Based on MRV evaluation of transverse sinus dysplasia, the volunteers were divided into a dysplasia group (26 cases) and a non-dysplasia group (55 cases); The area of the stenosis and the normal transverse sinus at the distal end were measured. The degree of TSS and the bilateral average transverse sinus stenosis (BA-TSS) were calculated. TSS was determined using TSS levels of 1/3, 1/2, and 2/3 as thresholds, and was divided into three groups: no TSS group, unilateral TSS group, and bilateral TSS group, with 28, 39, and 14 cases, 37, 37, and 7 cases, and 43, 36, and 2 cases, respectively. Based on 4D Flow MRI, the blood flow of the internal carotid artery, vertebral artery, superior sagittal sinus, straight sinus, and transverse sinus distal and proximal ends were measured. The cerebral blood flow (bilateral internal carotid artery blood flow+bilateral vertebral artery blood flow), venous sinus return blood flow 1 (superior sagittal sinus blood flow+straight sinus blood flow), return blood flow 2 (sum of bilateral transverse sinus distal end blood flow), return blood flow 3 (sum of bilateral transverse sinus proximal end blood flow), and the ratio of return blood flow to cerebral blood flow were calculated. Independent sample t-test was used to compare the differences between the group with and without transverse sinus dysplasia; Single factor analysis of variance was used to compare the differences between the TSS free group, unilateral TSS group, and bilateral TSS group. Based on single factor linear regression, the relationships between BA-TSS and blood flow parameters were analyzed.Results:There was no statistically significant difference in various blood flow parameters between the group with and without transverse sinus dysplasia (all P>0.05). When using 1/3, 1/2, and 2/3 as thresholds, there was no statistically significant difference in various blood flow parameters between the non TSS group, unilateral TSS group, and bilateral TSS group (all P>0.05). BA-TSS was linearly positively correlated with cerebral blood flow (β=0.986, 95% CI 0.108-1.865, P=0.028), but not linearly correlated with return blood flow 1, 2, and 3 (all P>0.05). The degree of BA-TSS was linearly negatively correlated with return blood flow 1/cerebral blood flow (β=-0.001, 95% CI -0.002-0, P=0.009) and return blood flow 2/cerebral blood flow (β=-0.001, 95% CI -0.002-0, P=0.018), but not with return blood flow 3/cerebral blood flow ( P=0.076). Conclusion:The BA-TSS degree in normal adults is positively correlated with cerebral blood inflow and negatively correlated with the proportion of venous sinus outflow.

Objective To develop a value evaluation index system for health management and logistics positions in pub-lic hospitals,providing a research tool for future performance evaluations and salary reform.Methods Literature review,focus group interviews,and the point-factor method were employed to establish an initial index pool.A public hospital in Guangzhou was selected as a case study.Delphi expert consultation was then utilized to refine and finalize the indicators for the evaluation system.Results For the two rounds of Delphi expert consultation,the response rates were 87.5％and 100.0％,with the expert authority coefficient of 0.812.The Kendall's W coordination coefficients were 0.796 and 0.624 for the first round,and 0.747 and 0.918 for the second,(all＜0.001).The coefficients of variation ranged from 0.157 to 0.265 for the first round and from 0.108 to 0.230 for the second round.Experts provided four suggestions,leading to the removal of one secondary indicator and modifications to the definitions of three others.Finally,the evaluation system consists of 4 primary indicators and 12 secondary indicators.Conclusion This system can provide a research tool and reference for the follow-up performance evaluation,improve the salary reform of public hospitals,and promote the high-quality development of public hospitals.

Medical therapy and surgical intervention are the two primary approaches for treating myocardial bridge.However,there remains controversy regarding the use of coronary artery bypass grafting(CABG)and myocardial bridge unroofing.Here,we report a case of myocardial infarction following CABG in a patient with a myocardial bridge.The patient was admitted to Lanzhou First Peopie's Hospital with persistent chest pain,chest tightness,and shortness of breath lasting 2 hours.Physical examination revealed no significant abnormalities.Electrocardiography(ECG)indicated extensive anterior wall myocardial infarction.Laboratory findings showed myoglobin levels of 140.1 ng/ml and troponin Ⅰ levels of 2.59 ng/ml,with no other significant abnormalities.The initial diagnosis was acute extensive anterior wall myocardial infarction.Emergency coronary angiography revealed a myocardial bridge in the mid-segment of the left anterior descending artery(LAD).Emergency CABG using the left internal mammary artery to the LAD was performed,leading to symptomatic improvement,and the patient was discharged in stable condition.However,the patient experienced a recurrent myocardial infarction seven years post-surgery and received secondary preventive medical therapy.The patient is currently under ongoing follow-up care.CABG is an effective treatment for myocardial bridge.However,based on the case reported in this study,we recommend careful evaluation of whether a patient may benefit from CABG.