Simulating short-term light responses of photosynthesis and water use efficiency in sweet sorghum under varying temperature and CO2 conditions.

Climate change, characterized by rising atmospheric CO2 levels and temperatures, poses significant challenges to global crop production. Sweet sorghum, a prominent C4 cereal extensively grown in arid areas, emerges as a promising candidate for sustainable bioenergy production. This study investigated the responses of photosynthesis and leaf-scale water use efficiency (WUE) to varying light intensity (I) in sweet sorghum under different temperature and CO2 conditions. Comparative analyses were conducted between the A n-I, g s-I, T r-I, WUEi-I, and WUEinst-I models proposed by Ye et al. and the widely utilized the non-rectangular hyperbolic (NRH) model for fitting light response curves. The Ye's models effectively replicated the light response curves of sweet sorghum, accurately capturing the diminishing intrinsic WUE (WUEi) and instantaneous WUE (WUEinst) trends with increasing I. The fitted maximum values of A n, g s, T r, WUEi, and WUEinst and their saturation light intensities closely matched observations, unlike the NRH model. Despite the NRH model demonstrating high R 2 values for A n-I, g s-I, and T r-I modelling, it returned the maximum values significantly deviating from observed values and failed to generate saturation light intensities. It also inadequately represented WUE responses to I, overestimating WUE. Across different leaf temperatures, A n, g s, and T r of sweet sorghum displayed comparable light response patterns. Elevated temperatures increased maximum A n, g s, and T r but consistently declined maximum WUEi and WUEinst. However, WUEinst declined more sharply due to the disproportionate transpiration increase over carbon assimilation. Critically, sweet sorghum A n saturated at current atmospheric CO2 levels, with no significant gains under 550 µmol mol-1. Instead, stomatal closure enhanced WUE under elevated CO2 by coordinated g s and T r reductions rather than improved carbon assimilation. Nonetheless, this response diminished under simultaneously high temperature, suggesting intricate interplay between CO2 and temperature in modulating plant responses. These findings provide valuable insights into photosynthetic dynamics of sweet sorghum, aiding predictions of yield and optimization of cultivation practices. Moreover, our methodology serves as a valuable reference for evaluating leaf photosynthesis and WUE dynamics in diverse plant species.

Self-assembling peptide hydrogel scaffold integrating stem cell-derived exosomes for infected bone defects.

Infected bone defect (IBD) is a great challenge in orthopedics, which involves in bone loss and infection. Here, a self-assembling hydrogel scaffold (named AMP-RAD/EXO), integrating antimicrobial peptides(AMPs), RADA16 and BMSCs exosomes with an innovative strategy, is developed and applied in IBD treatment for sustained antimicrobial ability, accelerating osteoblasts proliferation and promoting bone regeneration. AMPs present an excellent ability to inhibit infection, RADA16 is a self-assembling peptide hydrogel for AMPs delivery, and BMSCs exosomes can promote the bone regeneration. The prepared AMP-RAD/EXO exhibited a polyporous 3D structure for imbibition of BMSCs exosomes and migration of osteoblasts. In vitro studies indicate AMP-RAD/EXO can inhibit the growth of Staphylococcus aureus, accelerate the proliferation and migration of BMSCs. More importantly, in vivo results also prove that AMP-RAD/EXO exhibit an excellent effect on IBD treatment. Thus, the prepared AMP-RAD/EXO provides a multifunctional scaffold concept for bone tissue engineering technology.

Qualitative research on the cognition of breastfeeding knowledge in primiparas during pregnancy.

BACKGROUND: In view of the lack of attention and predictability in postpartum breastfeeding in primiparas, health education on breastfeeding during pregnancy should be carried out to publicize the benefits of breastfeeding. OBJECTIVE: To investigate how well the primiparas during pregnancy are known of breastfeeding knowledge, and to provide a basis for developing health education measures for them. METHODS: With the adoption of the objective sampling method and the principle of saturation, 10 primiparas in the obstetrics outpatient department of the Hunan Provincial People's Hospital were selected as the study participants. Semi-structured in-depth interviews combined with the observation method were used for data collection. The interview data were analyzed and the theme was refined by Colaizzi's seven-step method. RESULTS: The results of the four themes of the cognition of breastfeeding knowledge among primiparas were as follows: Lack of knowledge and curiosity about breastfeeding in some women, lack of access to correct breastfeeding knowledge, insufficient support from family members for postpartum breastfeeding, and lack of approach to solve problems during breastfeeding among primiparas. CONCLUSION: Due to the current problems of the cognition of breastfeeding knowledge in primiparas, it was imperative to build a health education model suitable for primiparas to improve this knowledge.

Application of Perioperative Pain Management in the Perioperative Nursing of Labia Minora Plasty and its Effect on the Rehabilitation of Patients.

Objective: The objective of this study is to investigate effective pain management strategies for women undergoing labiaplasty surgery. By focusing on pain relief, patient rehabilitation, and satisfaction improvement, we aim to enhance the overall patient experience and outcomes of this common gynecological plastic surgery. Methods: A total of 126 individuals diagnosed with labia minora hypertrophy and who underwent plastic surgery on their labia minora within the period of July 2020 to July 2023 were chosen as the participants for this study. They were divided into an observation group and a comparison group, each consisting of 63 cases, based on the different nursing methods. The comparison group was treated with routine perioperative nursing after labia minora surgery, and the observation group was treated with perioperative pain nursing management based on the comparison group. Postoperative pain score, comfort score, incision healing time, first urination time, night Pittsburgh Sleep Quality Index (PSQI) score, complications, and satisfaction were compared between the two groups. All data were established in an Excel database, and statistical analysis was performed using SPSS26.0. Statistical methods used include descriptive analysis, t tests, and Chi-square tests. Results: The mean incision healing time of the observation group was 3.90±0.61 days, and that of the control group was 3.62±0.64 days. The mean incision healing time of the observation group was significantly different from that of the control group (P < .05). VRS scores and PSQI scores were significantly lower in both groups 1 week aftercare compared with 1 day before care, indicating improvements in pain and sleep quality. The improvement degree of VRS score and PSQI score in the observation group was significantly different (P < .05). The number of incision infections, hematoma, flap necrosis, skin scar, delayed healing, and total complication rate were 3 in the observation group and 11 in the comparison group, indicating that the complication rate in the observation group was significantly lower than that in the comparison group. The comparison difference was statistically significant (P < .05). Through the Chi-square test, the nursing satisfaction and perineal aesthetic effect satisfaction of the observation group were significantly higher than those of the comparison group, and the difference was statistically significant (P < .05). Conclusions: The implementation of perioperative pain nursing management has been shown to effectively alleviate pain in patients diagnosed with labia minora hypertrophy. This approach not only enhances treatment comfort but also significantly reduces the occurrence of postoperative complications. Additionally, it accelerates the healing process of incisions, improves the quality of incision healing, and enhances patient satisfaction with both the aesthetic outcome of the perineal area and the quality of nursing care provided.

Dietary Provision, GLIM-Defined Malnutrition and Their Association with Clinical Outcome: Results from the First Decade of nutritionDay in China.

Malnutrition is a common and serious issue that worsens patient outcomes. The effects of dietary provision on the clinical outcomes of patients of different nutritional status needs to be verified. This study aimed to identify dietary provision in patients with eaten quantities of meal consumption and investigate the effects of dietary provision and different nutritional statuses defined by the GLIM criteria on clinical outcomes based on data from the nutritionDay surveys in China. A total of 5821 adult in-patients from 2010 to 2020 were included in this study's descriptive and Cox regression analyses. Rehabilitation and home discharge of 30-day outcomes were considered a good outcome. The prevalence of malnutrition defined by the GLIM criteria was 22.8%. On nutritionDay, 51.8% of all patients received dietary provisions, including hospital food and a special diet. In multivariable models adjusting for other variables, the patients receiving dietary provision had a nearly 1.5 higher chance of a good 30-day outcome than those who did not. Malnourished patients receiving dietary provision had a 1.58 (95% CI [1.36-1.83], p < 0.001) higher chance of having a good 30-day outcome and had a shortened length of hospital stay after nutritionDay (median: 7 days, 95% CI [6-8]) compared to those not receiving dietary provision (median: 11 days, 95% CI [10-13]). These results highlight the potential impacts of the dietary provision and nutritional status of in-patients on follow-up outcomes and provide knowledge on implementing targeted nutrition care.

Targeting the macrophage immunocheckpoint: a novel insight into solid tumor immunotherapy.

Tumor immunotherapy, which targets immune checkpoints, presents a promising strategy for the treatment of various cancer types. However, current clinical data indicate challenges in its application to solid tumors. Recent studies have revealed a significant correlation between the degree of immune response in immunotherapy and the tumor microenvironment, particularly with regard to tumor-infiltrating immune cells. Among these immune cells, macrophages, a critical component, are playing an increasingly vital role in tumor immunotherapy. This review focuses on elucidating the role of macrophages within solid tumors and provides an overview of the progress in immunotherapy approaches centered around modulating macrophage responses through various immune factors. Video Abstract.

Facile preparation of high-performance plywood adhesive from gelatinized corn starch crosslinked with ammonium dihydrogen phosphate.

A flame retardant high-performance gelatinized starch (GS)-ammonium dihydrogen phosphate (ADP) wood adhesive, named GS-ADP adhesive was prepared by condensation of GS and ADP under acidic condition. The preparation process of GS-ADP adhesive is very simple by mixing and stirring GS and ADP evenly at room temperature. The results revealed that the GS-ADP adhesive has good storage stability and water resistance, and its wet shear strength is much higher than that of phenolic resin (PF) adhesive. Markedly, the cone calorimeter test results show that G-ADP adhesive has good flame retardancy, and the plywood based on GS-ADP adhesive has good flame retardancy. Meanwhile, it can be seen from dynamic mechanical analysis (DMA) and thermogravimetric analysis (TGA) that GS-ADP has excellent modulus of elasticity (MOE), high glass transition temperature (Tg) and good thermal stability. The findings suggest that GS-ADP could be a viable substitute for PF resin in structural wood fabrication.

Entropy-Mediated Stable Structural Evolution of Prussian White Cathodes for Long-Life Na-Ion Batteries.

The high-entropy approach is applied to monoclinic Prussian White (PW) Na-ion cathodes to address the issue of unfavorable multilevel phase transitions upon electrochemical cycling, leading to poor stability and capacity decay. A series of Mn-based samples with up to six metal species sharing the N-coordinated positions was synthesized. The material of composition Na1.65 Mn0.4 Fe0.12 Ni0.12 Cu0.12 Co0.12 Cd0.12 [Fe(CN)6 ]0.92 □0.08 ⋅ 1.09H2 O was found to exhibit superior cyclability over medium/low-entropy and conventional single-metal PWs. We also report, to our knowledge for the first time, that a high-symmetry crystal structure may be advantageous for high-entropy PWs during battery operation. Computational comparisons of the formation enthalpy demonstrate that the compositionally less complex materials are prone to phase transitions, which negatively affect cycling performance. Based on data from complementary characterization techniques, an intrinsic mechanism for the stability improvement of the disordered PW structure upon Na+ insertion/extraction is proposed, namely the dual effect of suppression of phase transitions and mitigation of gas evolution.

Mangiferin alleviates renal inflammatory injury in spontaneously hypertensive rats by inhibiting MCP-1/CCR2 signaling pathway.

Objective: Hypertension is a low-grade inflammation state of the disease and was easily complicated by kidneys' inflammatory response. Mangiferin (MGF), a pharmacologically active compound in various plants including Mangifera indica, has a strong anti-inflammatory activity. However, the effects of MGF on renal inflammatory injury in spontaneously hypertensive rats (SHRs) remain unclear. The purpose of this study was to investigate the protective effects and mechanisms of MGF on renal inflammatory injury in SHRs. Methods: MGF was used in SHRs at the doses of 10, 20, 40 mg/kg/d for 8 weeks consecutively. The blood and urine were collected for assessment of renal function. Renal tissues were collected for histological, immunohistochemistry, ELISA, Western blot and real time reverse transcription PCR (RT-PCR) analysis. Results: The results showed that the levels of interleukin 6 (IL-6), tumor necrosis factor-α (TNF-α), monocyte chemoattractant protein-1 (MCP-1) and recombinant chemokine C-C-Motif receptor 2 (CCR2) were increased in SHRs, meanwhile, the level of IL-10 was decreased in SHR. Treatment of MGF inhibited the expression of IL-6, TNF-α, MCP-1 and CCR2, and promoted the expression of IL-10. Furthermore, the content of blood urea nitrogen (BUN) and serum uric acid (SUA) was significantly increased in the model group, and treatment of MGF had no obvious effects on these parameters at all dose levels. Conclusion: Our study proved that the kidneys of SHRs had significant inflammatory injury, and MGF had the protective effects on renal inflammatory injury in SHRs; The protective mechanism may be mediated partly by the MCP-1/CCR2 signaling pathway. Thus, it is a potential new drug for the treatment of hypertension.

Dual blockade of CD47 and CD24 signaling using a novel bispecific antibody fusion protein enhances macrophage immunotherapy.

CD47 and its receptor signal regulatory protein α (SIRPα) act as a dominant antiphagocytic, "don't eat me" signal. Recent studies reveal CD24 as a novel target for cancer immunotherapy by macrophages in ovarian cancer and breast cancer. However, whether simultaneous blockade of CD47 and CD24 by a bispecific antibody may result in a potential synergy is still unclear. In the present study, we for the first time designed and developed a bispecific antibody fusion protein, PPAB001 for cotargeting CD47 and CD24. Data demonstrate that simultaneous blockade of CD47/SIRPα and CD24/Siglec-10 signaling by PPAB001 potently promoted macrophage phagocytosis of tumor cells. Compared to single CD47 or CD24 targeting agents, PPAB001 was more effective in inhibiting tumor growth in both mouse 4T-1 syngeneic and human SK-OV-3 xenogeneic tumor models. Mechanistically, we found that PPAB001 therapy markedly increased the proportion of tumor-infiltrating macrophages and upregulated interleukin-6 and tumor necrosis factor-α levels that were representative macrophage inflammatory cytokines. Notably, an increased ratio of M1/M2 in tumor-infiltrating macrophages in the mice treated with PPAB001 suggested that the dual blockade may promote the transition of macrophages from M2 to M1. Taken together, our data supported the development of PPAB001 as a novel immunotherapeutic in the treatment of CD47 and CD24 double-positive cancers.

Identification and verification of three autophagy-related genes as potential biomarkers for the diagnosis of psoriasis.

Psoriasis vulgaris is the most common form of the four clinical types. However, early diagnosis of psoriasis vulgaris is difficult due to the lack of effective biomarkers. The aim of this study was to screen potential biomarkers for the diagnosis of psoriasis. In our study, we downloaded the original data from GSE30999 and GSE41664, and the autophagy-related genes list from human autophagy database to identify differentially expressed autophagy-related genes (DERAGs) by R software. Then Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed for DERAGs. DERAGs were validated by the other four databases (GSE13355, GSE14905, GSE6710, and GSE55201) to screen biomarkers with high diagnostic value for the early diagnosis of psoriasis vulgaris. Finally, DERAGs were verified in our clinical blood samples by ELISA. A total of 12 DERAGs were identified between 123 paired non-lesional and lesional skin samples from patients with psoriasis vulgaris. GO and KEGG enrichment analysis indicated the TORC2 complex was more enriched and the NOD-like receptor signaling pathway was mostly enriched. Three autophagy-related genes (BIRC5, NAMPT and BCL2) were identified through bioinformatics analysis and verified by ELISA in clinical blood samples. And these genes showed high diagnostic value for the early diagnosis of psoriasis vulgaris. We identified three autophagy-related genes (BIRC5, NAMPT and BCL2) with high diagnostic value for the early diagnosis of psoriasis vulgaris through bioinformatics analysis and clinical samples. Therefore, we proposed that BIRC5, NAMPT and BCL2 may be as potential biomarkers for the early diagnosis of psoriasis vulgaris. In addition, BIRC5, NAMPT and BCL2 may affect the development of psoriasis by regulating autophagy.

Fracture risk prediction in old Chinese people-a narrative review.

With aging, the burden of osteoporotic fracture (OF) increases substantially, while China is expected to carry the greatest part in the future. The risk of fracture varies greatly across racial groups and geographic regions, and systematically organized evidence on the potential predictors for fracture risk is needed for Chinese. This review briefly introduces the epidemiology of OF and expands on the predictors and predictive tools for the risk of OF, as well as the challenges for their potential translation in the old Chinese population. There are regional differences of fracture incidence among China. The fracture incidences in Hong Kong and Taiwan have decreased in recent years, while it is still increasing in mainland China. Although the application of dual-energy X-ray absorptiometry (DXA) is limited among old Chinese in the mainland, bone mineral density (BMD) by DXA has a predictive value similar to that worldwide. Other non-DXA modalities, especially heel QUS, are helpful in assessing bone health. The fracture risk assessment tool (FRAX) has a good discrimination ability for OFs, especially the FRAX with BMD. And some clinical factors have added value to FRAX, which has been verified in old Chinese. In addition, although the application of the osteoporosis self-assessment tool for Asians (OSTA) in Chinese needs further validation, it may help identify high-risk populations in areas with limited resources. Moreover, the translation use of the muscle quality and genetic or serum biomarkers in fracture prediction needs further works. More applicable and targeted fracture risk predictors and tools are still needed for the old Chinese population.

Multicomponent cyclization with azides to synthesize N-heterocycles.

Heterocyclic compounds, both naturally derived and synthetically produced, constitute a wide variety of biologically active and industrially important compounds. The synthesis and application of heterocyclic compounds have garnered significant attention and experienced rapid growth in recent decades. Organic azides, due to their unique properties and distinctive reactivity, have become a convenient chemical tool for achieving a wide range of heterocycles such as triazoles and tetrazoles. Importantly, the field of multicomponent reaction (MCR) chemistry provides a convergent approach to access various N-heterocyclic scaffolds, offering novelty, diversity, and complexity. However, the exploration of MCR pathways to N-heterocyclic compounds remains incomplete. Here, we review the use of multicomponent reactions for the preparation of N-heterocycles. A wide range of reactions based on azides for the synthesis of various types of N-heterocyclic systems have been developed.

Bioinspired Natural Shellac Dressing for Rapid Wound Sealing and Healing.

Developing safe and effective wound dressings that address the complexities of wound healing is an ongoing goal in biomaterials research. Inspired by the shield used to protect lac insects, we have designed and developed a type of bioactive shellac-based wound dressing in this paper. The dressing exhibited a high adhesion energy of 146.6 J·m-2 in porcine skin and showed a reversible binding due to its pH sensitivity. Meanwhile, a novel "shellac-like" compound, n-octacosanol gallate ester, has been synthesized and added to the dressing to improve its antibacterial and blood coagulation properties. The novel shellac-based dressing could be sprayed to form a sticky film within 70 s for rapid hemostasis and wound sealing, which could be conveniently applied to various wounds on extensible body parts. In addition, the shellac-based dressing can actively promote the healing of a full-thickness wound in the skin of mice. We also used molecular dynamics simulations to investigate the interactions between the shellac molecule and the phospholipid bilayer and attempted to show that the shellac molecule was beneficial for wound healing. This work provides a novel and practical bioinspired wound dressing with significant properties, facile preparation, and ease of use, which is an interesting alternative to its traditional counterparts.

RBM15-Mediated m6A Modification of K17 Affects Keratinocytes Response to IL-17A Stimulation in Psoriasis.

OBJECTIVE: Psoriasis is characterized by excessive proliferation and abnormal differentiation of epidermal keratinocytes. This study aimed to reveal the function and mechanism of a N6-methyladenosine (m6A) methyltransferase RNA-binding motif protein 15 (RBM15) in IL-17A-induced keratinocytes. METHODS: A immortalized keratinocyte cell line HaCaT was used to undergo the IL-17A stimulation. The mRNA levels were detected by qRT-PCR, whereas the protein levels were measured by western blotting. The change of keratinocytes proliferation was determined using CCK8 and EdU assays, and the inflammation factors (IL-8 and TNF-α) in keratinocytes were analyzed by qRT-PCR. The m6A modification of Keratin 17 (K17) was confirmed by MeRIP and mRNA stability assays. RESULTS: The levels of RBM15 and K17 in skin samples from patients with psoriasis and IL-17A-induced keratinocytes were upregulated, and showed the positive correlation. Silencing RBM15 suppressed viability, proliferation, and inflammation of keratinocytes that were enhanced by IL-17A stimulation. Moreover, RBM15 knockdown reduced the stability of K17 mRNA via m6A modification method. Since K17 is modified by RBM15, its overexpression relieved the effects of RBM15 knockdown on keratinocytes under IL-17A stimulation. CONCLUSION: This study revealed that RBM15 knockdown suppressed proliferation and inflammation by mediating m6A modification of K17 to reduce K17 stability in IL-17A-induced keratinocytes. Our findings may provide novel idea for improving the treatment of psoriasis.

ATNet: A Defect Detection Framework for X-ray Images of DIP Chip Lead Bonding.

In order to improve the production quality and qualification rate of chips, X-ray nondestructive imaging technology has been widely used in the detection of chip defects, which represents an important part of the quality inspection of products after packaging. However, the current traditional defect detection algorithm cannot meet the demands of high accuracy, fast speed, and real-time chip defect detection in industrial production. Therefore, this paper proposes a new multi-scale feature fusion module (ATSPPF) based on convolutional neural networks, which can more fully extract semantic information at different scales. In addition, based on this module, we design a deep learning model (ATNet) for detecting lead defects in chips. The experimental results show that at 8.2 giga floating point operations (GFLOPs) and 146 frames per second (FPS), mAP0.5 and mAP0.5-0.95 can achieve an average accuracy of 99.4% and 69.3%, respectively, while the detection speed is faster than the baseline yolov5s by nearly 50%.

Dataset for developing optimal headway-based bus dispatching strategy during epidemic outbreaks.

This article presents the data utilized in a study focused on identifying an optimal bus dispatching strategy in light of epidemic impacts. The study specifically examines the Xi'an Xiaozhai central business district (CBD) street network, which consists of 33 major signalized intersections and 112 bus stops associated with 12 bus routes. The dataset includes details of intersection and bus stop geospatial data, street segment and intersection design, intersection signal timing plans, bus route operational properties such as dispatching frequencies, fleet sizes, loading bay capacities, and bus-specific parameters. It also encompasses data on passenger boarding and alighting counts, as well as travelers' origin and destination (O-D) locations, routes, and departure times during three time periods: 10:00-11:00 PM, 1:00-2:00 PM, and 7:00-8:00 PM on Monday, June 7, 2021. These times represent off-peak (10:00 PM-1:00 AM the next day), adjacent-to-peak (9:00-11:00 AM, 1:00-4:00 PM, and 8:00-10:00 PM), and peak (7:00-9:00 AM, 11:00 AM-1:00 PM, and 4:00-8:00 PM) periods, respectively. Data collection involves searching government and organizational records, utilizing Alibaba Cloud's Amap platform, conducting onsite measurements, and performing a field survey. The dataset is a valuable resource for studying the integrated operations of various urban mass transit services, including buses, bus rapid transit (BRT), and fixed guideway transit, under both normal and epidemic-affected travel conditions. Additionally, it can be used to investigate multimodal integrated urban passenger services offered by automobiles, transit, ridesharing, and active transportation modes.

Predicting diabetic kidney disease for type 2 diabetes mellitus by machine learning in the real world: a multicenter retrospective study.

Objective: Diabetic kidney disease (DKD) has been reported as a main microvascular complication of diabetes mellitus. Although renal biopsy is capable of distinguishing DKD from Non Diabetic kidney disease(NDKD), no gold standard has been validated to assess the development of DKD.This study aimed to build an auxiliary diagnosis model for type 2 Diabetic kidney disease (T2DKD) based on machine learning algorithms. Methods: Clinical data on 3624 individuals with type 2 diabetes (T2DM) was gathered from January 1, 2019 to December 31, 2019 using a multi-center retrospective database. The data fell into a training set and a validation set at random at a ratio of 8:2. To identify critical clinical variables, the absolute shrinkage and selection operator with the lowest number was employed. Fifteen machine learning models were built to support the diagnosis of T2DKD, and the optimal model was selected in accordance with the area under the receiver operating characteristic curve (AUC) and accuracy. The model was improved with the use of Bayesian Optimization methods. The Shapley Additive explanations (SHAP) approach was used to illustrate prediction findings. Results: DKD was diagnosed in 1856 (51.2 percent) of the 3624 individuals within the final cohort. As revealed by the SHAP findings, the Categorical Boosting (CatBoost) model achieved the optimal performance 1in the prediction of the risk of T2DKD, with an AUC of 0.86 based on the top 38 characteristics. The SHAP findings suggested that a simplified CatBoost model with an AUC of 0.84 was built in accordance with the top 12 characteristics. The more basic model features consisted of systolic blood pressure (SBP), creatinine (CREA), length of stay (LOS), thrombin time (TT), Age, prothrombin time (PT), platelet large cell ratio (P-LCR), albumin (ALB), glucose (GLU), fibrinogen (FIB-C), red blood cell distribution width-standard deviation (RDW-SD), as well as hemoglobin A1C(HbA1C). Conclusion: A machine learning-based model for the prediction of the risk of developing T2DKD was built, and its effectiveness was verified. The CatBoost model can contribute to the diagnosis of T2DKD. Clinicians could gain more insights into the outcomes if the ML model is made interpretable.

Optical multiple-image authentication based on computational ghost imaging and hybrid non-convex second-order total variation.

An optical security method for multiple-image authentication is proposed based on computational ghost imaging and hybrid non-convex second-order total variation. Firstly, each original image to be authenticated is encoded to the sparse information using computational ghost imaging, where illumination patterns are generated based on Hadamard matrix. In the same time, the cover image is divided into four sub-images with wavelet transform. Secondly, one of sub-images with low-frequency coefficients is decomposed using singular value decomposition (SVD), and all sparse data are embedded into the diagonal matrix with the help of binary masks. To enhance the security, the generalized Arnold transform is used to scramble the modified diagonal matrix. After using SVD again, the marked cover image carrying the information of multiple original images is obtained using the inverse wavelet transform. In the authentication process, the quality of each reconstructed image can be greatly improved based on hybrid non-convex second-order total variation. Even at a very low sampling ratio (i.e., 6%), the existence of original images can be efficiently verified using the nonlinear correlation maps. To our knowledge, it is first to embed sparse data into the high-frequency sub-image using two cascaded SVDs, which can guarantee high robustness against the Gaussian filter and sharpen filter. The optical experiments demonstrate the feasibility of the proposed mechanism, which can provide an effective alternative for the multiple-image authentication.