H2O2/acid self-supplying double-layer electrospun nanofibers based on ZnO2 and Fe3O4 nanoparticles for efficient catalytic therapy of wound infection.

Catalytic therapy based on nanozymes is promising for the treatment of bacterial infections. However, its therapeutic efficacy is usually restricted by the limited amount of hydrogen peroxide and the weak acidic environment in infected tissues. To solve these issues, we prepared polyvinyl alcohol (PVA)-polyacrylic acid (PAA)-iron oxide (Fe3O4)/polyvinyl alcohol (PVA)-zinc peroxide (ZnO2) double-layer electrospun nanofibers (PPF/PZ NFs). In this design, PVA serves as the carrier for ZnO2 nanoparticles (NPs), Fe3O4 NPs, and PAA. The double-layer structure of nanofibers can spatially separate the PAA and ZnO2 to avoid their reaction with each other during preparation and storage, while in the wet wound bed, PVA can dissolve and PAA can provide H+ ions to promote the generation of hydrogen peroxide and subsequent conversion to hydroxyl radicals for bacteria killing. In vitro experimental results demonstrated that PPF/PZ NFs can reduce the methicillin-resistant Staphylococcus aureus by 3.1 log (99.92%). Moreover, PPF/PZ NFs can efficiently treat the bacterial infection in a mouse wound model and promote wound healing with negligible toxicity to animals, indicating their potential use as "plug-and-play" antibacterial wound dressings. This work provides a novel strategy for the construction of double-layer electrospun nanofibers as catalytic wound dressings with hydrogen peroxide/acid self-supplying properties for the efficient treatment of bacterial infections.

Nanodrug Delivery Systems in Antitumor Immunotherapy.

Cancer has become one of the most important factors threatening human health, and the global cancer burden has been increasing rapidly. Immunotherapy has become another clinical research hotspot after surgery, chemotherapy, and radiotherapy because of its high efficiency and tumor metastasis prevention. However, problems such as lower immune response rate and immune-related adverse reaction in the clinical application of immunotherapy need to be urgently solved. With the development of nanodrug delivery systems, various nanocarrier materials have been used in the research of antitumor immunotherapy with encouraging therapeutic results. In this review, we mainly summarized the combination of nanodrug delivery systems and immunotherapy from the following 4 aspects: (a) nanodrug delivery systems combined with cytokine therapy to improve cytokines delivery in vivo; (b) nanodrug delivery systems provided a suitable platform for the combination of immune checkpoint blockade therapy with other tumor treatments; (c) nanodrug delivery systems helped deliver antigens and adjuvants for tumor vaccines to enhance immune effects; and (d) nanodrug delivery systems improved tumor treatment efficiency and reduced toxicity for adoptive cell therapy. Nanomaterials chosen by researchers to construct nanodrug delivery systems and their function were also introduced in detail. Finally, we discussed the current challenges and future prospects in combining nanodrug delivery systems with immunotherapy.

Ultrasound-responsive gallium protoporphyrin and oxygen loaded perfluoropentane nanodroplets for effective sonodynamic therapy of implant infections.

Implant infections are severe complications in clinical treatment, which often accompany the formation of bacterial biofilms with high antibiotic resistance. Sonodynamic therapy (SDT) is an antibiotic-free method that can generate reactive oxygen species (ROS) to kill bacteria under ultrasound (US) treatment. However, the extracellular polymeric substances (EPS) barrier of bacterial biofilms and the hypoxic microenvironment significantly limit the antibiofilm activity of SDT. In this study, lipid-shelled perfluoropentane (PFP) nanodroplets loaded with gallium protoporphyrin IX (GaPPIX) and oxygen (O2) (LPGO NDs) were developed for the treatment of implant infections. Under US stimulation, LPGO NDs undergo the cavitation effect and disrupt the biofilm structure like bombs due to liquid-gas phase transition. Meanwhile, the LPGO NDs release O2 and GaPPIX upon US stimulation. The released O2 can alleviate the hypoxic microenvironment in the biofilm and enhance the ROS formation by GaPPIX for enhanced bacterial killing. In vivo experimental results demonstrate that the LPGO NDs can efficiently treat implant infections of methicillin-resistant Staphylococcus aureus (MRSA) in a mouse model by disrupting the biofilm structure, alleviating hypoxia, and enhancing bacterial killing by SDT. Therefore, this work provides a new multifunctional sonosensitizer to overcome the limitations of SDT for treating implant infections.

Association of Novel Loci With Keratoconus Susceptibility in a Chinese Genome-Wide Association Study.

Purpose: Keratoconus (KC) is a progressive corneal disease that can lead to corneal blindness if not properly managed. The purpose of this study was to identify genetic associations with KC in China and to investigate whether these genetic variants are associated with corneal thickness and corneal curvature in KC cases. Methods: A genome-wide association study was conducted on 853 patients with KC and 6248 controls. The KC cases were genotyped with the Illumina Infinium Human Asian Screening Array BeadChip, and the controls were genotyped with the Illumina Infinium Human Global Screening Array BeadChip. Genetic associations with KC, as well as correlations between the positive variants and corneal parameters including central corneal thickness (CCT) and mean keratometry (Km), were compared using PLINK version 1.90. Results: Our present study identified four single-nucleotide polymorphisms (SNPs) within four risk loci (PTGER3: rs2300163, EYA1: rs1077435, ASS1: rs141365191, and CHTF8: rs3743680) associated with KC in Chinese patients that reached genome-wide significance. Among the identified SNPs with P < 1.00 × 10-4, seven SNPs (FOSL2-PLB1: rs12622211, RXRA-COL5A1: rs3118515, rs3132306, rs1536482, rs3118520, KAT6B: rs192187772, RAP2A-IPO5: rs41361245) were observed to be associated with CCT, and one SNP (USP13: rs6767552) was found to be associated with Km. Conclusions: In the first genome-wide association study of KC with a relatively large study population in China, we identified four SNPs in four risk loci associated with the disease. The findings enriched the understanding of genetic susceptibility to KC and provided new insights into the genetic etiology of the disease.

Metabolic Modulation-Mediated Antibiotic and Immune Activation for Treatment of Chronic Lung Infections.

The Pseudomonas aeruginosa biofilm in recalcitrant chronic lung infections not only develops high antimicrobial tolerance but also induces an aberrant host inflammatory response. The metabolic condition plays a vital role in both the antimicrobial susceptibility of bacteria and the inflammatory response of immune cells, thereby offering a potential therapeutic target. Herein, we described a metabolic modulation strategy by using ultrasound-responsive liposomal nanoparticles containing a sonosensitizer and a hypoxia-activated prodrug against biofilm-associated chronic lung infections. Under ultrasound stimulation, the sonosensitizer generates antibacterial reactive oxygen species by oxygen consumption. Subsequently, the oxygen consumption-mediated hypoxia not only induces the anaerobic metabolism of bacteria for antibiotic activation but also triggers the glycolysis pathway of immune cells for inflammatory activation. Such metabolic modulation strategy demonstrated efficient therapeutic efficacy for P. aeruginosa biofilm-induced chronic lung infections in mice models and provides a promising way for combating biofilm-associated chronic infections.

The Chinese keratoconus (CKC) cohort study.

The Chinese keratoconus (CKC) cohort study is a population-based longitudinal prospective cohort study in the Chinese population involving a clinical database and biobanks. This ongoing study focuses on the prevention of KC progression and is the first to involve the effect of gene‒environment interactions on KC progression. The CKC cohort is hospital-based and dynamic and was established in Zhengzhou, China; KC patients (n = 1114) from a large geographical area were enrolled from January 2019 to June 2023, with a mean age of 22.23 years (6‒57 years). Demographic details, socioeconomic characteristics, lifestyle, disease history, surgical history, family history, and visual and social function data are being collected using questionnaires. General physical examination, eye examination, biological specimen collection, and first-degree relative data were collected and analyzed in the present study. The primary focus of the present study was placed on gene, environment and the effect of gene‒environment interactions on KC progression. The follow-up of the CKC cohort study is expected to include data collection at 3 months, 6 months, and 1 year after the initial examination and then at the annual follow-up examinations. The first follow-up of the CKC cohort study was recorded. A total of 918 patients completed the follow-up by June 1, 2023, with a response rate of 82.40%. Aside from the younger age of patients who were followed up, no significant differences were found between patients who were followed up and patients who were not.

Attention pyramid pooling network for artificial diagnosis on pulmonary nodules.

The development of automated tools using advanced technologies like deep learning holds great promise for improving the accuracy of lung nodule classification in computed tomography (CT) imaging, ultimately reducing lung cancer mortality rates. However, lung nodules can be difficult to detect and classify, from CT images since different imaging modalities may provide varying levels of detail and clarity. Besides, the existing convolutional neural network may struggle to detect nodules that are small or located in difficult-to-detect regions of the lung. Therefore, the attention pyramid pooling network (APPN) is proposed to identify and classify lung nodules. First, a strong feature extractor, named vgg16, is used to obtain features from CT images. Then, the attention primary pyramid module is proposed by combining the attention mechanism and pyramid pooling module, which allows for the fusion of features at different scales and focuses on the most important features for nodule classification. Finally, we use the gated spatial memory technique to decode the general features, which is able to extract more accurate features for classifying lung nodules. The experimental results on the LIDC-IDRI dataset show that the APPN can achieve highly accurate and effective for classifying lung nodules, with sensitivity of 87.59%, specificity of 90.46%, accuracy of 88.47%, positive predictive value of 95.41%, negative predictive value of 76.29% and area under receiver operating characteristic curve of 0.914.

Two-dimensional ternary chalcogenide nanodots with spatially controlled catalytic activity for bacteria infected wound treatment.

Nanozymes hold great prospects for bacteria-infected wound management, yet the spatial control of their catalytic activity in infected area and normal tissues remains mired by the heterogeneity of tissue microenvironment. Here, we develop a novel two-dimensional ternary chalcogenide nanodots (Cu2MoS4, CMS NDs) with renal clearable ability and controlled catalytic activity for bacteria-infected wound treatment. The two-dimensional CMS NDs (∼4 nm) are prepared by a simple microwave-assisted chemical synthetic route. Our results show that CMS NDs not only have peroxidase-like activity in a pH-dependent manner (pH < 5.5). Based on the generation of hydroxyl radical (OH) by adding H2O2, CMS NDs show > 2 log bacterial inactivation for both Gram-positive methicillin-resistant Staphylococcus aureus (MRSA) and Gram-negative Escherichia coli (E. coli) under the acidic condition. Moreover, CMS NDs show good biocompatibility and can be excreted by the kidney in mice. In vivo results display that CMS NDs show good therapeutic effect against bacteria infected wound in the presence of H2O2, but no damage for normal tissues. Taken together, this work provides a renal clearable two-dimensional nanozyme with spatially controlled catalytic activity for the treatment of wounds and bacterial infections on the skin surface.

Machine learning analysis with the comprehensive index of corneal tomographic and biomechanical parameters in detecting pediatric subclinical keratoconus.

Background: Keratoconus (KC) occurs at puberty but diagnosis is focused on adults. The early diagnosis of pediatric KC can prevent its progression and improve the quality of life of patients. This study aimed to evaluate the ability of corneal tomographic and biomechanical variables through machine learning analysis to detect subclinical keratoconus (SKC) in a pediatric population. Methods: Fifty-two KC, 52 SKC, and 52 control pediatric eyes matched by age and gender were recruited in a case-control study. The corneal tomographic and biomechanical parameters were measured by professionals. A linear mixed-effects test was used to compare the differences among the three groups and a least significant difference analysis was used to conduct pairwise comparisons. The receiver operating characteristic (ROC) curve and the Delong test were used to evaluate diagnostic ability. Variables were used in a multivariate logistic regression in the machine learning analysis, using a stepwise variable selection to decrease overfitting, and comprehensive indices for detecting pediatric SKC eyes were produced in each step. Results: PE, BAD-D, and TBI had the highest area under the curve (AUC) values in identifying pediatric KC eyes, and the corresponding cutoff values were 12 µm, 2.48, and 0.6, respectively. For discriminating SKC eyes, the highest AUC (95% CI) was found in SP A1 with a value of 0.84 (0.765, 0.915), and BAD-D was the best parameter among the corneal tomographic parameters with an AUC (95% CI) value of 0.817 (0.729, 0.886). Three models were generated in the machine learning analysis, and Model 3 (y = 0.400*PE + 1.982* DA ratio max [2 mm]-0.072 * SP A1-3.245) had the highest AUC (95% CI) value, with 90.4% sensitivity and 76.9% specificity, and the cutoff value providing the best Youden index was 0.19. Conclusion: The criteria of parameters for diagnosing pediatric KC and SKC eyes were inconsistent with the adult population. Combined corneal tomographic and biomechanical parameters could enhance the early diagnosis of young patients and improve the inadequate representation of pediatric KC research.

Mitochondrial DNA heteroplasmy analysis in keratoconus patients from China.

Background: Mitochondrial DNA (mtDNA) variants have been implicated in keratoconus (KC). The present study aimed to characterize the mtDNA heteroplasmy profile in KC and explore the association of mitochondrial heteroplasmic levels with KC. Methods: Mitochondrial sequencing of peripheral blood samples and corneal tomography were conducted in 300 KC cases and 300 matched controls. The number of heteroplasmic and homoplasmic variants was calculated across the mitochondrial genome. Spearman's correlation was used to analyze the correlation between the number of heteroplasmic variants and age. The association of mtDNA heteroplasmic level with KC was analyzed by logistic regression analysis. Moreover, the relationship between mitochondrial heteroplasmic levels and clinical parameters was determined by linear regression analysis. Results: The distribution of mtDNA heteroplasmic variants showed the highest number of heteroplasmic variants in the non-coding region, while the COX3 gene exhibited the highest number in protein-coding genes. Comparisons of the number of heteroplasmic and homoplasmic non-synonymous variants in protein-coding genes revealed no significant differences between KC cases and controls (all p > 0.05). In addition, the number of heteroplasmic variants was positively associated with age in all subjects (r = 0.085, p = 0.037). The logistic regression analyses indicated that the heteroplasmic levels of m.16180_16181delAA was associated with KC (p < 0.005). Linear regression analyses demonstrated that the heteroplasmic levels of m.16180_16181delAA and m.302A>C were not correlated with thinnest corneal thickness (TCT), steep keratometry (Ks), and flat keratometry (Kf) (all p > 0.05) in KC cases and controls separately. Conclusion: The current study characterized the mtDNA heteroplasmy profile in KC, and revealed that the heteroplasmic levels of m.16180_16181delAA were associated with KC.

Eye Rubbing in Chinese Patients With Keratoconus: A Multicenter Analysis.

PURPOSE: To investigate the eye rubbing habits of Chinese patients with keratoconus. METHODS: This study was carried out from 2018 to June 2022 at Shandong Eye Hospital, Qingdao Eye Hospital, and Henan Eye Hospital. The study compared the number of patients who rubbed their eyes between medical records and second time questionnaires, eye rubbing of patients with myopia and patients with keratoconus, and disease severity between patients with keratoconus. A questionnaire survey of ophthalmologists was conducted to determine their degree of awareness that eye rubbing is a risk factor for keratoconus. RESULTS: The study assessed 799 patients with keratoconus and 798 control patients, and 97 ophthalmologists. The average proportion of patients with keratoconus who rubbed their eyes was 31.0% in the medical records with an increasing trend related to the increase in ophthalmologists' awareness, 66.6% after the second follow-up, and 25.4% among patients with myopia. After multivariate analysis, the following variables showed significant results: eye rubbing frequency more than 10 times/day (odds ratio [OR], 9.168; P < .001); rubbing with knuckles (OR, 9.804; P = .001); and prone sleep position (OR, 12.427; P < .001). The proportion of patients who rubbed their eyes with stage IV keratoconus was 71.9%, 18.9% higher than those with stage I, 4.8% higher than stage II, and 17.8% higher than stage III. CONCLUSIONS: The proportion of Chinese patients with keratoconus who rubbed their eyes was relatively high. The main reasons for the low proportions reported were lack of attention. Clinical attention should be paid to eye rubbing in patients with keratoconus who should be educated to avoid it. [J Refract Surg. 2023;39(10):712-718.].

A high body mass index strengthens the association between the time of eye rubbing and keratoconus in a Chinese population: a case control study.

BACKGROUND: Although body mass index (BMI) and eye rubbing are linked to an increased risk of keratoconus (KC), the interactive effect of eye rubbing and BMI on KC is largely unknown. This study aimed to evaluate the independent and interactive effects of BMI and eye rubbing on KC and to further explore the role of environmental factors on the occurrence of KC. METHODS: A total of 621 individuals (291 KC patients and 330 control individuals) were enrolled in this hospital­based study on KC patients in Central China after individuals missing BMI data were excluded. BMI was calculated as weight in kilograms divided by the square of height in meters. Data on eye rubbing was recorded through face-to-face interviews. Generalized linear regression models were used to analyze associations among BMI, eye rubbing and KC. Interaction plots were used to describe the interactive effects of BMI and eye rubbing on KC. RESULTS: The ß and 95% confidence interval (CI) were 0.923 (0.112, 1.733) (p = 0.026) and 3.356 (1.953, 4.759) (p < 0.001), respectively, for the effect of each 10 kg/m2 increase in BMI and each 1 min increase in eye rubbing on KC. The interaction of BMI and eye rubbing were positively correlated with KC (p < 0.001). CONCLUSION: These findings suggested that a high BMI aggravated the negative effect of eye rubbing on KC, implying that individuals with a high BMI may be more susceptible to exposure to eye rubbing, which is related to an increased risk of KC.

Maternal Supplementary Tapioca Polysaccharide Iron Improves the Growth Performance of Piglets by Regulating the Active Components of Colostrum and Cord Blood.

The purpose of this study was to investigate the effect of maternal supplementation with TpFe (tapioca polysaccharide iron) on reproductive performance, colostrum composition, cord blood active components of sows, and growth performance of their nursing piglets. Sixty healthy Duroc × Landrace × Yorkshire sows were randomly assigned to three groups at day 85 of gestation. The experimental diets included a basal diet supplemented with 100 mg/kg FeSO4·H2O (CON group), the basal diet supplemented with 50 mg/kg TpFe (TpFe50 group), and the basal diet supplemented with 100 mg/kg TpFe (TpFe100 group), as calculated by Fe content. The experiment lasted from day 85 of gestation to the end of weaning (day 21 of lactation). Results showed that maternal supplementation with 100 mg/kg TpFe improved (p < 0.05) feed intake during lactation, live births, and birth weight of the litter (alive) and increased (p < 0.05) colostrum IgM (immunoglobulin m), IgA (immunoglobulin A), as well as the IgG levels, while it decreased (p < 0.05) the urea nitrogen and somatic cell count of sows. Moreover, sows in the TpFe100 group had higher (p < 0.05) serum iron levels and IgG. Additionally, maternal supplementation with 100 mg/kg TpFe increased (p < 0.05) iron level, total antioxidant capacity (T-AOC), glutathione peroxidase (GSH-px), catalase (CAT), IgG, red blood cells (RBC), and hemoglobin (Hb) of cord blood, similar with the iron content, T-AOC, GSH-px, IgG, RBC, Hb, hematocrit (HCT), and mean corpuscular volume (MCV) of weaned piglet blood. The diarrhea and mortality rates among the nursing piglets were decreased (p < 0.05), while the average weight at day 21 of age was increased (p < 0.05) in the TpFe100 group. Serum PRL (prolactin) levels of sows exhibited a positive correlation (p < 0.05) with live births. Suckling piglet diarrhea was positively correlated with colostrum urea nitrogen level but negatively correlated with colostrum IgM, IgG, and cord blood Hb content (p < 0.05). The mortality of suckling piglets was negatively correlated with serum iron content and IgM in colostrum, GSH-px, and IgG in cord serum of sows (p < 0.05). The average weight of weaning piglets was positively (p < 0.05) related to colostrum IgM and IgG levels, as well as cord serum RBC counts of sows on day 21. In conclusion, maternal supplementation with TpFe can improve the active components of colostrum and umbilical cord blood and improve the growth performance of suckling piglets.

Abundance considerations for modeling yield of rapeseed at the flowering stage.

Introduction: To stabilize the edible oil market, it is necessary to determine the oil yield in advance, so the accurate and fast technology of estimating rapeseed yield is of great significance in agricultural production activities. Due to the long flowering time of rapeseed and the characteristics of petal color that are obviously different from other crops, the flowering period can be carefully considered in crop classification and yield estimation. Methods: A field experiment was conducted to obtain the unmanned aerial vehicle (UAV) multispectral images. Field measurements consisted of the reflectance of flowers, leaves, and soils at the flowering stage and rapeseed yield at physiological maturity. Moreover, GF-1 and Sentinel-2 satellite images were collected to compare the applicability of yield estimation methods. The abundance of different organs of rapeseed was extracted by the spectral mixture analysis (SMA) technology, which was multiplied by vegetation indices (VIs) respectively to estimate the yield. Results: For the UAV-scale, the product of VIs and leaf abundance (AbdLF) was closely related to rapeseed yield, which was better than the VIs models for yield estimation, with the coefficient of determination (R2) above 0.78. The yield estimation models of the product of normalized difference yellowness index (NDYI), enhanced vegetation index (EVI) and AbdLF had the highest accuracy, with the coefficients of variation (CVs) below 10%. For the satellite scale, most of the estimation models of the product of VIs and rapeseed AbdLF were also improved compared with the VIs models. The yield estimation models of the product of AbdLF and renormalized difference VI (RDVI) and EVI (RDVI×AbdLF and EVI×AbdLF) had the steady improvement, with CVs below 13.1%. Furthermore, the yield estimation models of the product of AbdLF and normalized difference VI (NDVI), visible atmospherically resistant index (VARI), RDVI, and EVI had consistent performance at both UAV and satellite scales. Discussion: The results showed that considering SMA could improve the limitation of using only VIs to retrieve rapeseed yield at the flowering stage. Our results indicate that the abundance of rapeseed leaves can be a potential indicator of yield prediction during the flowering stage.

A diagnostic classification of lung nodules using multiple-scale residual network.

Computed tomography (CT) scans have been shown to be an effective way of improving diagnostic efficacy and reducing lung cancer mortality. However, distinguishing benign from malignant nodules in CT imaging remains challenging. This study aims to develop a multiple-scale residual network (MResNet) to automatically and precisely extract the general feature of lung nodules, and classify lung nodules based on deep learning. The MResNet aggregates the advantages of residual units and pyramid pooling module (PPM) to learn key features and extract the general feature for lung nodule classification. Specially, the MResNet uses the ResNet as a backbone network to learn contextual information and discriminate feature representation. Meanwhile, the PPM is used to fuse features under four different scales, including the coarse scale and the fine-grained scale to obtain more general lung features of the CT image. MResNet had an accuracy of 99.12%, a sensitivity of 98.64%, a specificity of 97.87%, a positive predictive value (PPV) of 99.92%, and a negative predictive value (NPV) of 97.87% in the training set. Additionally, its area under the receiver operating characteristic curve (AUC) was 0.9998 (0.99976-0.99991). MResNet's accuracy, sensitivity, specificity, PPV, NPV, and AUC in the testing set were 85.23%, 92.79%, 72.89%, 84.56%, 86.34%, and 0.9275 (0.91662-0.93833), respectively. The developed MResNet performed exceptionally well in estimating the malignancy risk of pulmonary nodules found on CT. The model has the potential to provide reliable and reproducible malignancy risk scores for clinicians and radiologists, thereby optimizing lung cancer screening management.

The Hepatic Nerves Regulated Inflammatory Effect in the Process of Liver Injury: Is Nerve the Key Treating Target for Liver Inflammation?

Liver injury is a common pathological basis for various liver diseases. Chronic liver injury is often an important initiating factor in liver fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Currently, hepatitis A and E infections are the most common causes of acute liver injury worldwide, whereas drug toxicity (paracetamol overdose) in the USA and part of Western Europe. In recent years, chronic liver injury has become a common disease that harms human health. Meanwhile, the main causes of chronic liver injury are viral hepatitis (B, C) and long-term alcohol consumption worldwide. During the process of liver injury, massive inflammatory cytokines are stimulated by these hazardous factors, leading to a systemic inflammatory response syndrome, followed by a compensatory anti-inflammatory response, which causes immune cell dysfunction and sepsis, subsequent multi-organ failure. Cytokine release and immune cell infiltration-mediated aseptic inflammation are the most important features of the pathobiology of liver failure. From this perspective, diminishing the onset and progression of liver inflammation is of clinical importance in the treatment of liver injury. Although many studies have hinted at the critical role of nerves in regulating inflammation, there largely remains undetermined how hepatic nerves mediate immune inflammation and how the inflammatory factors released by these nerves are involved in the process of liver injury. Therefore, the purpose of this article is to summarize previous studies in the field related to hepatic nerve and inflammation as well as future perspectives on the aforementioned questions. Our findings were presented in three aspects: types of nerve distribution in the liver, how these nerves regulate immunity, and the role of liver nerves in hepatitis and liver failure.

Accuracy of tomographic and biomechanical parameters in detecting unilateral post-LASIK keratoectasia and fellow eyes.

Background: Patients with unilateral post-LASIK keratectasia (KE) have clinical ectasia in one eye but not in the fellow eye. As serious complications, these cases are rarely reported but are worth investigating. This study aimed to explore the characteristics of unilateral KE and the accuracy of corneal tomographic and biomechanical parameters to detect KE and distinguish fellow eyes from control eyes. Methods: The study analyzed 23 KE eyes, 23 KE fellow eyes, and 48 normal eyes from age- and sex-matched patients who had undergone LASIK. The Kruskal-Wallis test and further paired comparisons were performed to compare the clinical measurements of the three groups. The receiver operating characteristic curve was used to evaluate the ability to distinguish KE and fellow eyes from the control eyes. Binary logistic regression with the forward stepwise method was performed to produce a combined index, and the DeLong test was used to compare the discriminability difference of the parameters. Results: Males accounted for 69.6% of patients with unilateral KE. The duration between corneal surgery and the onset of ectasia ranged from 4 months to 18 years, with a median time of 10 years. The KE fellow eye had a higher posterior evaluation (PE) value than the control eyes (5 vs. 2, p = 0.035). Diagnostic tests showed that PE, posterior radius of curvature (3 mm), anterior evaluation (FE), and Corvis biomechanical index-laser vision correction (CBI-LVC) were sensitive indicators for distinguishing KE in the control eyes. The ability of PE to detect the KE fellow eye from the control eye was 0.745 (0.628 and 0.841), with 73.91% sensitivity and 68.75% specificity at a cut-off value of 3. The ability of a combined index, constructed using PE and FE, to distinguish fellow eyes of KE from controls was 0.831 (0.723 and 0.909), which was higher than that of PE and FE individually (p < 0.05). Conclusion: The fellow eyes of patients with unilateral KE had significantly higher PE values than control eyes, and a combination of PE and FE enhanced this differentiation in a Chinese population. More attention should be paid to the long-term follow-up of patients after LASIK and to be wary of the occurrence of early KE.

Estimation of Rice Aboveground Biomass by UAV Imagery with Photosynthetic Accumulation Models.

The effective and accurate aboveground biomass (AGB) estimation facilitates evaluating crop growth and site-specific crop management. Considering that rice accumulates AGB mainly through green leaf photosynthesis, we proposed the photosynthetic accumulation model (PAM) and its simplified version and compared them for estimating AGB. These methods estimate the AGB of various rice cultivars throughout the growing season by integrating vegetation index (VI) and canopy height based on images acquired by unmanned aerial vehicles (UAV). The results indicated that the correlation of VI and AGB was weak for the whole growing season of rice and the accuracy of the height model was also limited for the whole growing season. In comparison with the NDVI-based rice AGB estimation model in 2019 data (R2 = 0.03, RMSE = 603.33 g/m2) and canopy height (R2 = 0.79, RMSE = 283.33 g/m2), the PAM calculated by NDVI and canopy height could provide a better estimate of AGB of rice (R2 = 0.95, RMSE = 136.81 g/m2). Then, based on the time-series analysis of the accumulative model, a simplified photosynthetic accumulation model (SPAM) was proposed that only needs limited observations to achieve R2 above 0.8. The PAM and SPAM models built by using 2 years of samples successfully predicted the third year of samples and also demonstrated the robustness and generalization ability of the models. In conclusion, these methods can be easily and efficiently applied to the UAV estimation of rice AGB over the entire growing season, which has great potential to serve for large-scale field management and also for breeding.

Discussion on the need for correction during isotopic analysis of nitrogen by the denitrifier method.

The nitrogen and oxygen isotopes of NO3 - are effectively used to trace the main nitrogen sources and migration processes in the atmosphere, water and soil. NO3 - can be converted into N2O by the bacterial denitrification method, which is an advanced method with high sensitivity. However, due to the existence of a small but inevitable blank during the whole experimental process, the N isotopic signal of N2O produced by denitrification superimposes on that of the N blank. Currently, the standard curve correction method is used to correct measured nitrogen isotope results to mitigate blank interference. It has been reported that high variability of the nitrogen isotope results have been produced by the denitrifier method by conducting an interlaboratory comparison of denitrifier methods and other methods on standards and environmental samples, and to reduce this problem, the nitrogen isotope calibration process with a standard curve is examined in depth in this paper, which uses PreCon-GC-IRMS to determine the nitrogen isotopes in N2O. We demonstrate for the first time that reliable results can be obtained without correction for samples with nitrogen isotope composition ranging from -9.9 to 19.5‰, which covers the natural sample range. This study establishes the double test approach for the bacterial denitrification method, ensuring the accuracy and long-term stability of different batches of nitrogen isotope results.

Bioinformatics analysis of key candidate genes and pathways in Chinese patients with keratoconus.

Keratoconus (KC) is a multifactorial disease in which genetic factors played important roles in its pathogenesis. The purpose of the current study was to identify the key candidate genes and pathways in Chinese patients with KC through bioinformatics analysis. Totally, we identified 71 candidate genes by analyzing the results of whole exome sequencing on 51 Chinese patients with KC, combining with previous reports on differential expression at transcription and protein levels in KC. Gene enrichment analysis with GeneCodis demonstrated that two significantly enriched terms including 21 genes in biological process (BP) were detected, and six significantly enriched terms containing 14 genes in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were discovered. The STRING was utilized to construct the protein-protein interaction (PPI) network of identified genes. The result showed that a PPI network consisted of 14 nodes with 14 edges was constructed, and two gene modules were obtained. Eight hub genes (LAMB3, LAMA3, LAMA1, ITGA6, ITGA3, COL6A3, COL6A2, and COL6A1) were identified as key candidate genes for KC by cytoHubba in Cytoscape. Functional enrichment analysis with ClueGO and CluePedia indicated that the ECM-receptor interaction was the key pathway accounted for KC. The findings might provide novel insights on the genetic basis of KC.