In Vivo Corneal Biomechanical Response to Three Different Laser Corneal Refractive Surgeries.

PURPOSE: To compare the effects of three common refractive surgeries on corneal biomechanics. METHODS: Two hundred seven patients who had refractive surgery were included in this study, of whom 65 received transepithelial photorefractive keratectomy (tPRK), 73 received femtosecond laser-assisted laser in situ keratomileusis (FSLASIK), and 69 received small incision lenticule extraction (SMILE). Each patient had biomechanical measurements using the Corvis ST (Oculus Optikgeräte GmbH) preoperatively and at 3 and 6 months postoperatively. The measurements included five parameters expected to be associated with corneal biomechanics: deformation amplitude ratio at 2 mm (DAR2), integrated inverse radius (IIR), stiffness parameter at first applanation (SP-A1), highest concavity time (HCT), and the updated stress-strain index (SSIv2). The variations in these parameters postoperatively among the three surgeries, and their relationship with corneal thickness (CCT) and intraocular pressure measured by the Dynamic Contour Tonometer (DCT-IOP) were analyzed. RESULTS: SP-A1 decreased significantly from preoperatively to 3 months postoperatively in all three groups, whereas DAR2 and IIR increased significantly, all indicating stiffness losses. Between 3 and 6 months postoperatively, the results were inconsistent, with DAR2 decreasing (indicating stiffness increases) and IIR increasing (denoting stiffness decreases) in the FS-LASIK and SMILE groups. The decrease in SSIv2 (the only measure of corneal material stiffness) postoperatively was comparatively less pronounced at both 3 and 6 months postoperatively. On the other hand, HCT remained generally stable after all three surgeries. Unlike DAR2, IIR, and SP-A1, the changes postoperatively in stiffness parameters HCT and SSIv2 were independent of the corresponding changes in both DCT-IOP and CCT. CONCLUSIONS: Among the stiffness parameters considered, SSIv2 was not correlated with CCT or DCT-IOP, and holds promise for representing the corneal material stiffness and how it remains largely unaffected by refractive surgeries. Overall, FS-LASIK had the most significant impact on corneal stiffness, followed by SMILE, and finally tPRK. [J Refract Surg. 2024;40(5):e344-e352.].

Relationship Learning From Multisource Images via Spatial-Spectral Perception Network.

Advances in multisource remote sensing have allowed for the development of more comprehensive observation. The adoption of deep convolutional neural networks (CNN) naturally includes spatial-spectral information, which has achieved promising performance in multisource data classification. However, challenges are still found with the extraction of spatial distribution and spectrum relationships, which eventually limit the classification performance. To solve the issue, a spatial-spectral perception network (S2PNet) is proposed to extract the advantages of different data sources and the cross information between data sources in a targeted manner. Specifically, the spatial perception network is developed to build the spatial distribution relationship from high-resolution images, while the spectral perception network extracts the spectrum relationship from spectral images. For perceiving cross information, a memory unit is utilized to store the features from different data sources in succession. In addition, the distance loss and reconstruction loss are introduced to keep the feature integrity, and the cross-entropy loss ensures that features can distinguish different classes. The comprehensive experiments are conducted on several datasets to validate the superiority of the proposed algorithm. The proposed S2PNet outperforms the considered classifiers with an average improvement of +0.77%, +5.62%, +1.58%, and +1.79% for overall accuracy values.

An investigation of methods to enhance adhesion of conductive layer and dielectric substrate for additive manufacturing of electronics.

Additive manufacturing of conductive layers on a dielectric substrate has garnered significant interest due to its promise to produce printed electronics efficiently and its capability to print on curved substrates. A considerable challenge encountered is the conductive layer's potential peeling due to inadequate adhesion with the dielectric substrate, which compromises the durability and functionality of the electronics. This study strives to facilitate the binding force through dielectric substrate surface modification using concentrated sulfuric acid and ultraviolet (UV) laser treatment. First, polyetheretherketone (PEEK) and nanoparticle silver ink were employed as the studied material. Second, the surface treatment of PEEK substrates was conducted across six levels of sulfuric acid exposure time and eight levels of UV laser scanning velocity. Then, responses such as surface morphology, roughness, elemental composition, chemical bonding characteristics, water contact angle, and surface free energy (SFE) were assessed to understand the effects of these treatments. Finally, the nanoparticle silver ink layer was deposited on the PEEK surface, and the adhesion force measured using a pull-off adhesion tester. Results unveiled a binding force of 0.37 MPa on unmodified surface, which escalated to 1.99 MPa with sulfuric acid treatment and 2.21 MPa with UV laser treatment. Additionally, cross-approach treatment investigations revealed that application sequence significantly impacts results, increasing binding force to 2.77 MPa. The analysis further delves into the influence mechanism of the surface modification on the binding force, elucidating that UV laser and sulfuric acid surface treatment methods hold substantial promise for enhancing the binding force between heterogeneous materials in the additive manufacturing of electronics.

Deciphering male influence in gynogenetic Pengze crucian carp (Carassius auratus var. pengsenensis): insights from Nanopore sequencing of structural variations.

In this study, we investigate gynogenetic reproduction in Pengze Crucian Carp (Carassius auratus var. pengsenensis) using third-generation Nanopore sequencing to uncover structural variations (SVs) in offspring. Our objective was to understand the role of male genetic material in gynogenesis by examining the genomes of both parents and their offspring. We discovered a notable number of male-specific structural variations (MSSVs): 1,195 to 1,709 MSSVs in homologous offspring, accounting for approximately 0.52%-0.60% of their detected SVs, and 236 to 350 MSSVs in heterologous offspring, making up about 0.10%-0.13%. These results highlight the significant influence of male genetic material on the genetic composition of offspring, particularly in homologous pairs, challenging the traditional view of asexual reproduction. The gene annotation of MSSVs revealed their presence in critical gene regions, indicating potential functional impacts. Specifically, we found 5 MSSVs in the exonic regions of protein-coding genes in homologous offspring, suggesting possible direct effects on protein structure and function. Validation of an MSSV in the exonic region of the polyunsaturated fatty acid 5-lipoxygenase gene confirmed male genetic material transmission in some offspring. This study underscores the importance of further research on the genetic diversity and gynogenesis mechanisms, providing valuable insights for reproductive biology, aquaculture, and fostering innovation in biological research and aquaculture practices.

Intense emission at 605†nm from Pr3+-doped fluorotellurite glass fibers.

Pr3+-doped fluorotellurite glass fibers (PDFTFs) were fabricated by using a rod-in-tube method. By using a 976/1400 nm dual-wavelength upconversion pump technique, an intense emission at 605 nm was obtained from a 6 cm long PDFTF, which was attributed to the transition 1D2 → 3H4 of Pr3+ ions. With an increase in power of the 1400 nm laser from ∼34 to ∼136 mW, the spectral bandwidth of the 605 nm emission decreased and the intensity of the 605 nm emission increased monotonically, indicating the generation of 605 nm amplified spontaneous emission (ASE). To the best of our knowledge, this is the first report of 605 nm ASE in PDFTFs. Our results showed that PDFTFs had the potential for constructing red fiber lasers and amplifiers.

Widely tunable S-band ring-cavity Tm3+-doped fluorotellurite fiber laser.

Tm3+-doped fluorotellurite fibers (TDFTFs) are fabricated by using a rod-in-tube method. A 2.1 m long TDFTF is used as the gain medium, in which both ends of the TDFTF are connected to a short piece of a silica fiber by direct fusion splicing. By inserting the above TDFTF and a tunable optical bandpass filter into a ring cavity and employing a 1400/1570 nm dual-wavelength pumping technique, tunable lasing from 1460 to 1526 nm is obtained, which almost covers the whole S-band. To the best of our knowledge, this is the first report of tunable Tm3+-doped fiber laser with a tunable range almost covering the whole S-band. Furthermore, by removing the tunable optical bandpass filter from the ring cavity, free-running multi-wavelength lasers at 1500 and 1901 nm are achieved. Our results show that TDFTFs are promising gain media for constructing S-band fiber lasers.

Comparison efficacy and safety of acupuncture and moxibustion therapies in breast cancer-related lymphedema: A systematic review and network meta-analysis.

OBJECTIVE: Although several acupuncture and moxibustion therapies have been tested in managing breast cancer-related lymphedema (BCRL), there is little consensus regarding the best options for treating this condition. This systematic review and network meta-analysis compared the efficacy of various acupuncture and/or moxibustion therapies for BCRL. METHODS: Seven databases and two clinical registration centers were searched from their inception to December 1st, 2023. The Cochrane Collaboration risk-of-bias assessment tool evaluated the quality of included RCTs. A pairwise meta-analysis was performed in STATA 16.0, while a network meta-analysis was performed in R 4.2.2. RESULTS: 18 studies were included in this analysis. Our results showed that acupuncture and moxibustion methods had great advantages in improving BCRL of patients with breast cancer. In particular, needle-warming moxibustion (NWM) could be the optimal acupuncture and moxibustion method for improving clinical effectiveness and reducing the degree of swelling of affected limbs. CONCLUSION: Our findings suggest that NWM has great potential in treating BCRL. It may reduce arm circumference, lower swelling levels, and improve clinical effectiveness. Nevertheless, more multi-center, high-quality, and large sample RCTs will be needed in the future.

Extraction and In Vitro Skincare Effect Assessment of Polysaccharides Extract from the Roots of Abelmoschus manihot (L.).

Obtaining high-added value compounds from agricultural waste receives increasing attention, as it can both improve resource utilization efficiency and reduce waste generation. In this study, polysaccharides are extracted from the discarded roots of Abelmoschus manihot (L.) by the high-efficiency ultrasound-assisted extraction (UAE). The optimized condition was determined as solid-liquid ratio SL ratio = 1:20, temperature T = 30 °C and time T = 40 min, achieving an extraction yield of 13.41%. Composition analysis revealed that glucose (Glc, 44.65%), rhamnose (Rha, 26.30%), galacturonic acid (GalA, 12.50%) and galactose (Gal, 9.86%) are the major monosaccharides of the extract. The extract showed a low degree of esterification (DE) value of 40.95%, and its Fourier-transform infrared (FT-IR) spectrum exhibited several characteristic peaks of polysaccharides. Inspired by the wide cosmetic applications of polysaccharides, the skincare effect of the extract was evaluated via the moisture retention, total phenolic content (TPC) quantification, 2,2-Diphenyl-1-picrylhydrazyl (DPPH)-free radical scavenging activity, anti-hyaluronidase and anti-elastase activity experiments. The extract solutions demonstrated a 48 h moisture retention rate of 10.75%, which is superior to that of commercially available moisturizer hyaluronic acid (HA). Moreover, both the TPC value of 16.16 mg GAE/g (dw) and DPPH-free radical scavenging activity of 89.20% at the concentration of 2 mg/mL indicated the strong anti-oxidant properties of the extract. Furthermore, the anti-hyaluronidase activity and moderate anti-elastase activity were determined as 72.16% and 42.02%, respectively. In general, in vitro skincare effect experiments suggest moisturizing, anti-oxidant, anti-radical and anti-aging activities of the A. manihot root extract, indicating its potential applications in the cosmetic industry.

Integrating UPLC-QTOF-MS/MS and UPLC-DAD to evaluate the influence of sulfur-fumigated Paeoniae Radix Alba on the overall quality of three Si-Wu-Tang formulations.

INTRODUCTION: Sulfur-fumigation of Paeoniae Radix Alba (PRA) could induce the chemical transformation of its bioactive component paeoniflorin into a sulfur-containing derivative paeoniflorin sulfite, and thus alter the quality, bioactivities, pharmacokinetics, and toxicities of PRA. However, how sulfur-fumigated PRA (S-PRA) affects the quality of PRA-containing complex preparations has not been intensively evaluated. OBJECTIVES: We intend to evaluate the influence of S-PRA on the overall quality of three kinds of Si-Wu-Tang (SWT) formulations, i.e., decoction (SWT-D), granule (SWT-G), and mixture (SWT-M). MATERIAL AND METHODS: An UPLC-DAD multi-components quantification method was used to compare the transfer rates of paeoniflorin sulfite and other 10 bioactive components between S-PRA-containing and NS-PRA-containing SWT formulations. An UPLC-QTOF-MS/MS-based target metabolomics approach was applied to explore the differential sulfur-containing derivatives in S-PRA-containing SWT formulations. RESULTS: The transfer rates of paeoniflorin sulfite in three S-PRA-containing SWT formulations were all higher than 100%. Moreover, S-PRA also increased the transfer rate of 5-hydroxymethylfurfural, 1,2,3,4,6-O-pentagalloylglucose, whereas decreased that of paeoniflorin, albiflorin, and ferulic acid in three SWT formulations. Six pinane monoterpene glucoside sulfites originally identified in S-PRA, were also detectable in three S-PRA-containing SWT formulations. In addition, seven phenolic acid sulfites including (3Z)-6-sulfite-ligustilide, (3E)-6-sulfite-ligustilide, 6,8-disulfite-ligustilide, ferulic acid sulfite, neochlorogenic acid sulfite, chlorogenic acid sulfite, and angelicide sulfite (or isomer) were newly identified in these three S-PRA-containing formulations. CONCLUSION: S-PRA could differentially affect the transfer rate of paeoniflorin sulfite and other bioactive components during the preparation of three SWT formulations and subsequently the overall quality thereof.

Phosphorus depletion is exacerbated by increasing nitrogen loading in the Bohai sea.

Phosphorus (P) is an essential nutrient for algal growth in nearshore ecosystems. In recent years, there has been a shift in nutrient dynamics in nearshore areas, leading to an exacerbation of P limitation, although the underlying mechanisms remain unclear. This study analyzed the P species and budget in the Bohai Sea (BS) from 2011 to 2020, aiming to explore the intrinsic mechanisms of P limitation in the BS. The results show that the main external source of P in the BS was river transport (89%), and the primary fate of P was burial (96%) into the sediment. Due to excessive nitrogen (N) input and biological processes in the BS, the P budget in the BS is unbalanced, resulting in an increase in the N/P ratio, particularly in nearshore areas. Nearshore areas typically have lower concentrations of dissolved inorganic P (DIP) in the water and higher concentrations of reactive P (Reac-P) in the sediments. This pattern is particularly evident in Bohai Bay and the northwest nearshore region, where harmful algal blooms occur frequently. To cope with enhanced P limitation, the biologically driven P regeneration and cycling processes within the BS are accelerated. From 2011 to 2020, the concentration of DIP in the BS during autumn increased, while the content of Reac-P in sediments slightly decreased. Historical data indicate that P depletion in the BS is intensifying and expanding, primarily due to N enrichment and algal production. N enrichment alters the structure and composition of primary production, potentially exacerbating P depletion in the BS. Excessive N may have significant impacts on the P pool, potentially influencing the stability of future coastal ecosystems.

Rational design of 2D Janus P3m1 M2N3 (M = Cu, Zr, and Hf) and their surface-functionalized derivatives: ferromagnetic, piezoelectric, and photocatalytic properties.

In this study, first-principles calculations were employed to rationally design two-dimensional (2D) Janus transition metal nitrides of P3m1 M2N3 phases, where M is a d-block element (Sc-Zn, Y-Cd, Hf-Hg). Among the 29 examined 2D M2N3, three 2D phases, namely P3m1 Cu2N3, Zr2N3, and Hf2N3, exhibit excellent thermodynamic, dynamic, mechanical, and thermal stabilities. These novel Janus 2D materials exhibit ferromagnetic metallic and half-metallic behavior. The related 2D Janus surface-functionalized derivatives, Cu2N3H, Cu2N3F, Cu2N3Cl, Zr2N3H, Hf2N3H, and Hf2N3F, are all dynamically stable. The 2D Janus P3m1 phases of Zr2N3H, Hf2N3H, and Hf2N3F, all with M in the +IV oxidation state, act as semiconductors in the visible region, with energy band gaps of 2.26-2.70 eV at the HSE06 level of theory. On the other hand, the 2D Janus P3m1 Cu2N3X phases (where X = H, F, and Cl) are ferromagnetic half-metals. Additionally, it has been unveiled that there are high hole mobilities (∼6 × 103 cm2 V-1 s-1) derived from the moderate deformation potential and effective mass in the 2D Janus P3m1 Zr2N3H, Hf2N3H, and Hf2N3F phases. Uniaxial strain engineering has demonstrated the outstanding in-plane piezoelectric properties of 2D Janus P3m1 Zr2N3H, Hf2N3H, and Hf2N3F with high d11 values (∼99.91 pm V-1). Furthermore, the desirable band-edge alignments and high anisotropic carrier mobilities of 2D Janus P3m1 Zr2N3H, Hf2N3H, and Hf2N3F phases indicate their potential as visible light-driven photocatalysts for water splitting reactions on different facets. These properties render 2D Janus P3m1 Zr2N3H, Hf2N3H, and Hf2N3F phases promising for use in optoelectronics, piezoelectric sensing, and photocatalysis applications.

Integrated phenotypic, transcriptomics and metabolomics: growth status and metabolite accumulation pattern of medicinal materials at different harvest periods of Astragalus Membranaceus Mongholicus.

BACKGROUND: Astragalus membranaceus var. mongholicus (Astragalus), acknowledged as a pivotal "One Root of Medicine and Food", boasts dual applications in both culinary and medicinal domains. The growth and metabolite accumulation of medicinal roots during the harvest period is intricately regulated by a transcriptional regulatory network. One key challenge is to accurately pinpoint the harvest date during the transition from conventional yield content of medicinal materials to high and to identify the core regulators governing such a critical transition. To solve this problem, we performed a correlation analysis of phenotypic, transcriptome, and metabolome dynamics during the harvesting of Astragalus roots. RESULTS: First, our analysis identified stage-specific expression patterns for a significant proportion of the Astragalus root genes and unraveled the chronology of events that happen at the early and later stages of root harvest. Then, the results showed that different root developmental stages can be depicted by co-expressed genes of Astragalus. Moreover, we identified the key components and transcriptional regulation processes that determine root development during harvest. Furthermore, through correlating phenotypes, transcriptomes, and metabolomes at different harvesting periods, period D (Nov.6) was identified as the critical period of yield and flavonoid content increase, which is consistent with morphological and metabolic changes. In particular, we identified a flavonoid biosynthesis metabolite, isoliquiritigenin, as a core regulator of the synthesis of associated secondary metabolites in Astragalus. Further analyses and experiments showed that HMGCR, 4CL, CHS, and SQLE, along with its associated differentially expressed genes, induced conversion of metabolism processes, including the biosynthesis of isoflavones and triterpenoid saponins substances, thus leading to the transition to higher medicinal materials yield and active ingredient content. CONCLUSIONS: The findings of this work will clarify the differences in the biosynthetic mechanism of astragaloside IV and calycosin 7-O-ß-D-glucopyranoside accumulation between the four harvesting periods, which will guide the harvesting and production of Astragalus.

Molecular Dynamics Simulation on Solidification Microstructure and Tensile Properties of Cu/SiC Composites.

The shape of ceramic particles is one of the factors affecting the properties of metal matrix composites. Exploring the mechanism of ceramic particles affecting the cooling mechanical behavior and microstructure of composites provides a simulation basis for the design of high-performance composites. In this study, molecular dynamics methods are used for investigating the microstructure evolution mechanism in Cu/SiC composites containing SiC particles of different shapes during the rapid solidification process and evaluating the mechanical properties after cooling. The results show that the spherical SiC composites demonstrate the highest degree of local ordering after cooling. The more ordered the formation is of face-centered-cubic and hexagonal-close-packed structures, the better the crystallization is of the final composite and the less the number of stacking faults. Finally, the results of uniaxial tensile in three different directions after solidification showed that the composite containing spherical SiC particles demonstrated the best mechanical properties. The findings of this study provide a reference for understanding the preparation of Cu/SiC composites with different shapes of SiC particles as well as their microstructure and mechanical properties and provide a new idea for the experimental and theoretical research of Cu/SiC metal matrix composites.

Classification of Benign-Malignant Thyroid Nodules Based on Hyperspectral Technology.

In recent years, the incidence of thyroid cancer has rapidly increased. To address the issue of the inefficient diagnosis of thyroid cancer during surgery, we propose a rapid method for the diagnosis of benign and malignant thyroid nodules based on hyperspectral technology. Firstly, using our self-developed thyroid nodule hyperspectral acquisition system, data for a large number of diverse thyroid nodule samples were obtained, providing a foundation for subsequent diagnosis. Secondly, to better meet clinical practical needs, we address the current situation of medical hyperspectral image classification research being mainly focused on pixel-based region segmentation, by proposing a method for nodule classification as benign or malignant based on thyroid nodule hyperspectral data blocks. Using 3D CNN and VGG16 networks as a basis, we designed a neural network algorithm (V3Dnet) for classification based on three-dimensional hyperspectral data blocks. In the case of a dataset with a block size of 50 × 50 × 196, the classification accuracy for benign and malignant samples reaches 84.63%. We also investigated the impact of data block size on the classification performance and constructed a classification model that includes thyroid nodule sample acquisition, hyperspectral data preprocessing, and an algorithm for thyroid nodule classification as benign and malignant based on hyperspectral data blocks. The proposed model for thyroid nodule classification is expected to be applied in thyroid surgery, thereby improving surgical accuracy and providing strong support for scientific research in related fields.

Transcriptome and Metabolome Analysis of Rice Cultivar CBB23 after Inoculation by Xanthomonas oryzae pv. oryzae Strains AH28 and PXO99A.

Bacterial leaf blight (BLB), among the most serious diseases in rice production, is caused by Xanthomonas oryzae pv. oryzae (Xoo). Xa23, the broadest resistance gene against BLB in rice, is widely used in rice breeding. In this study, the rice variety CBB23 carrying the Xa23 resistance gene was inoculated with AH28 and PXO99A to identify differentially expressed genes (DEGs) associated with the resistance. Transcriptome sequencing of the infected leaves showed 7997 DEGs between the two strains at different time points, most of which were up-regulated, including cloned rice anti-blight, peroxidase, pathology-related, protein kinase, glucosidase, and other coding genes, as well as genes related to lignin synthesis, salicylic acid, jasmonic acid, and secondary metabolites. Additionally, the DEGs included 40 cloned, five NBS-LRR, nine SWEET family, and seven phenylalanine aminolyase genes, and 431 transcription factors were differentially expressed, the majority of which belonged to the WRKY, NAC, AP2/ERF, bHLH, and MYB families. Metabolomics analysis showed that a large amount of alkaloid and terpenoid metabolite content decreased significantly after inoculation with AH28 compared with inoculation with PXO99A, while the content of amino acids and their derivatives significantly increased. This study is helpful in further discovering the pathogenic mechanism of AH28 and PXO99A in CBB23 rice and provides a theoretical basis for cloning and molecular mechanism research related to BLB resistance in rice.

A Personalized Collaborative Filtering Recommendation System Based on Bi-Graph Embedding and Causal Reasoning.

The integration of graph embedding technology and collaborative filtering algorithms has shown promise in enhancing the performance of recommendation systems. However, existing integrated recommendation algorithms often suffer from feature bias and lack effectiveness in personalized user recommendation. For instance, users' historical interactions with a certain class of items may inaccurately lead to recommendations of all items within that class, resulting in feature bias. Moreover, accommodating changes in user interests over time poses a significant challenge. This study introduces a novel recommendation model, RCKFM, which addresses these shortcomings by leveraging the CoFM model, TransR graph embedding model, backdoor tuning of causal inference, KL divergence, and the factorization machine model. RCKFM focuses on improving graph embedding technology, adjusting feature bias in embedding models, and achieving personalized recommendations. Specifically, it employs the TransR graph embedding model to handle various relationship types effectively, mitigates feature bias using causal inference techniques, and predicts changes in user interests through KL divergence, thereby enhancing the accuracy of personalized recommendations. Experimental evaluations conducted on publicly available datasets, including "MovieLens-1M" and "Douban dataset" from Kaggle, demonstrate the superior performance of the RCKFM model. The results indicate a significant improvement of between 3.17% and 6.81% in key indicators such as precision, recall, normalized discount cumulative gain, and hit rate in the top-10 recommendation tasks. These findings underscore the efficacy and potential impact of the proposed RCKFM model in advancing recommendation systems.

Diagnosis of Forme Fruste Keratoconus Using Corvis ST Sequences with Digital Image Correlation and Machine Learning.

PURPOSE: This study aimed to employ the incremental digital image correlation (DIC) method to obtain displacement and strain field data of the cornea from Corvis ST (CVS) sequences and access the performance of embedding these biomechanical data with machine learning models to distinguish forme fruste keratoconus (FFKC) from normal corneas. METHODS: 100 subjects were categorized into normal (N = 50) and FFKC (N = 50) groups. Image sequences depicting the horizontal cross-section of the human cornea under air puff were captured using the Corvis ST tonometer. The high-speed evolution of full-field corneal displacement, strain, velocity, and strain rate was reconstructed utilizing the incremental DIC approach. Maximum (max-) and average (ave-) values of full-field displacement V, shear strain γxy, velocity VR, and shear strain rate γxyR were determined over time, generating eight evolution curves denoting max-V, max-γxy, max-VR, max-γxyR, ave-V, ave-γxy, ave-VR, and ave-γxyR, respectively. These evolution data were inputted into two machine learning (ML) models, specifically Naïve Bayes (NB) and Random Forest (RF) models, which were subsequently employed to construct a voting classifier. The performance of the models in diagnosing FFKC from normal corneas was compared to existing CVS parameters. RESULTS: The Normal group and the FFKC group each included 50 eyes. The FFKC group did not differ from healthy controls for age (p = 0.26) and gender (p = 0.36) at baseline, but they had significantly lower bIOP (p < 0.001) and thinner central cornea thickness (CCT) (p < 0.001). The results demonstrated that the proposed voting ensemble model yielded the highest performance with an AUC of 1.00, followed by the RF model with an AUC of 0.99. Radius and A2 Time emerged as the best-performing CVS parameters with AUC values of 0.948 and 0.938, respectively. Nonetheless, no existing Corvis ST parameters outperformed the ML models. A progressive enhancement in performance of the ML models was observed with incremental time points during the corneal deformation. CONCLUSION: This study represents the first instance where displacement and strain data following incremental DIC analysis of Corvis ST images were integrated with machine learning models to effectively differentiate FFKC corneas from normal ones, achieving superior accuracy compared to existing CVS parameters. Considering biomechanical responses of the inner cornea and their temporal pattern changes may significantly improve the early detection of keratoconus.

Characteristics and phylogenetic analysis of the complete chloroplast genome of Cornus hongkongensis Hemsl. 1888 (Cornaceae).

Cornus hongkongensis Hemsl. 1888, native to Hong Kong, belongs to the subgenus Syncarpea within the Cornus genus of the Cornaceae family. The complete chloroplast genome of C. hongkongensis spans 156,954 bp, comprising four subregions: a large single-copy region (86,290 bp), a small single-copy region (18,394 bp), and a pair of inverted repeats (26,135 bp). Within the chloroplast genome of C. hongkongensis, we identified 113 unique genes, including 80 protein-encoding genes, four ribosomal RNA (rRNA) genes, and 30 transfer RNA (tRNA) genes. Phylogenetic analysis based on the complete chloroplast genome of 30 related taxa of the Cornus genus indicates that C. hongkongensis has not formed a monophyletic lineage. Analyses of sequence divergence found three intergenic regions including rps19-rpl22, ccsA-ndhD, and atpH-atpI, exhibiting a high degree of variations. The first chloroplast genome of C. hongkongensis was reported in this work contributes to the enrichment of genomic data for the genus Cornus.

Drug-Target Binding Affinity Prediction in a Continuous Latent Space Using Variational Autoencoders.

Accurate prediction of Drug-Target binding Affinity (DTA) is a daunting yet pivotal task in the sphere of drug discovery. Over the years, a plethora of deep learning-based DTA models have emerged, rendering promising results in predicting the binding affinities between drugs and their target proteins. However, in contrast to the conventional approach of modeling binding affinity in vector spaces, we propose a more nuanced modeling process in a continuous space to account for the diversity of input samples. Initially, the drug is encoded using the Simplified Molecular Input Line Entry System (SMILES), while the target sequences are characterized via a pretrained language model. Subsequently, highly correlative information is extracted utilizing residual gated convolutional neural networks. In a departure from existing deep learning-based models, our model learns the hidden representations of the drugs and targets jointly. Instead of employing two vectors, our hidden representations consist of two Gaussian distributions. To validate the effectiveness of our proposal, we conducted evaluations on commonly utilized benchmark datasets. The experimental outcomes corroborated that our method surpasses the state-of-the-art vectorial representation methods in terms of performance. This approach, therefore, offers potential enhancements in the precision of DTA predictions, potentially contributing to more efficient drug discovery processes.