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Abstract Background Leukocyte Ig-like receptor B family 4 (LILRB4) as an immune checkpoint on myeloid cells is a potential target for tumor therapy. Extensive osteolytic bone lesion is the most characteristic feature of multiple myeloma. It is unclear whether ectopic LILRB4 on multiple myeloma regulates bone lesion. Methods The conditioned medium (CM) from LILRB4-WT and -KO cells was used to analyze the effects of LILRB4 on osteoclasts and osteoblasts. Xenograft, syngeneic and patient derived xenograft models were constructed, and micro-CT, H&E staining were used to observe the bone lesion. RNA-seq, cytokine array, qPCR, the activity of luciferase, Co-IP and western blotting were used to clarify the mechanism by which LILRB4 mediated bone damage in multiple myeloma. Results We comprehensively analyzed the expression of LILRB4 in various tumor tissue arrays, and found that LILRB4 was highly expressed in multiple myeloma samples. The patient’s imaging data showed that the higher the expression level of LILRB4, the more serious the bone lesion in patients with multiple myeloma. The conditioned medium from LILRB4-WT not -KO cells could significantly promote the differentiation and maturation of osteoclasts. Xenograft, syngeneic and patient derived xenograft models furtherly confirmed that LILRB4 could mediate bone lesion of multiple myeloma. Next, cytokine array was performed to identify the differentially expressed cytokines, and RELT was identified and regulated by LILRB4. The overexpression or exogenous RELT could regenerate the bone damage in LILRB4-KO cells in vitro and in vivo. The deletion of LILRB4, anti-LILRB4 alone or in combination with bortezomib could significantly delay the progression of bone lesion of multiple myeloma. Conclusions Our findings indicated that LILRB4 promoted the bone lesion by promoting the differentiation and mature of osteoclasts through secreting RELT, and blocking LILRB4 singling pathway could inhibit the bone lesion.

Active Pharmaceutical Ingredients-Ionic liquids (API-ILs) can increase drug solubility and bioavailability of solid drugs without changing the structure of drug molecules. In the present work, nonivamide (pelargonic acid vanillylamide, PAVA) was used as the active drug and choline (Ch) and citric acid (CA) were selected as the ions to prepare PAVA–based ionic liquid ([Ch][PAVA] and [PAVA]3 [CA]), respectively. The characterization and physical properties of [Ch][PAVA] and [PAVA]3 [CA], such as FT–IR spectra, 1H NMR spectra, thermal stability and hydrophilicity, were investigated. And the irritant effects of the PAVA–based ionic liquids were measured by the animal irritation experiment. [Ch][PAVA] has higher decomposition temperatures, better hydrophilicity and comparable irritant effects. The results show that the PAVA–based ILs synthesized in this study may potentially serve as a promising novel riot control agent.

Summary: Background: It is generally recognized that there is unequal mortality in childhood central nervous system (CNS) malignancy in the United States (US), but little is known about the trends and contributors of racial/ethnic disparities in death. We assessed the trends of racial/ethnic disparities in all-cause and cause-specific death, and the contributions of tumour, treatment and socioeconomic factors to this disparity. Methods: This registry-based cohort study included children (aged ≤19 years) diagnosed with malignant CNS tumours, using data from the US population-based cancer registry in the Surveillance, Epidemiology, and End Results (SEER) Program. The clinical outcomes were all-cause and cause-specific death for each racial/ethnic group (White, Black, Hispanic, non-Hispanic Asian/Pacific Islander [API], and non-Hispanic American Indian/Alaska Native [AI/AN] children). We quantified absolute disparities using absolute rate difference in 5-year cumulative incidence of death. Cox proportion risk models were used to estimate the relative racial/ethnic disparities, and the contribution of factors to disparities in death. Findings: In this study, data from 14,510 children with malignant CNS tumours (mean [SD] age, 8.5 [5.7]; 7988 [55.1%] male) were analysed. Overall, the cumulative incidence of death from CNS tumours across four racial/ethnic groups decreased from 2001 to 2020. Black patients had the highest risk of death from all causes and CNS tumours between 2001 and 2020, with adjusted hazard ratios (HR) of 1.52 (1.38–1.68) and 1.47 (1.31–1.64), respectively. The absolute disparity in all-cause death between Hispanic and White patients increased slightly (from 8.2 percentage points [ppt] to 9.4 ppt), and the relative disparity in death from CNS tumours increased from 1.33 (1.15–1.55) in 2001–2005 to 1.78 (1.44–2.20) in 2016–2020. The absolute disparities in death from CNS tumours between Black and White patients (from 11.8 ppt to 4.3 ppt) and between API and White patients (from 10.1 ppt to 5.1 ppt) decreased from 2001–2005 to 2011–2015. Interpretation: Race/ethnicity disparities in death from CNS tumours among childhood malignant CNS tumours had reduced from 2001 to 2020, and quantifying the contribution of factors to this disparity in death could provide a basis for decreasing mortality among racial/ethnic minority patients. Funding: Shenyang Young and Middle-aged Science and Technology Innovation Talent Support Program.

Abstract Vitamin D deficiency and insufficiency pose global public health challenges, yet research on serum vitamin D levels in the 0–17-year-old age group in southeastern China remains limited. This study aimed to fill this gap by investigating serum 25(OH)D levels in children in the region aged 0–17 years, contributing crucial data for understanding vitamin D nutritional status. Liquid chromatography‒mass spectrometry/mass spectrometry (LC‒MS/MS) technology was used. Vitamin D testing was integrated into routine diagnostic procedures for 11,116 children in Wujiang District, Suzhou City. Among the 0–17-year age group, comprising 6348 boys and 4768 girls, the prevalence of serum 25(OH)D deficiency and insufficiency was 21.4% and 31.0%, respectively. The median serum 25(OH)D concentration was 29.72 ng/mL (21.84–39.84 ng/mL) in boys compared to 28.48 ng/mL (20.65–39.23 ng/mL) in girls. Seasonal variations were observed, with median serum 25(OH)D concentrations of 29.02 ng/mL (20.73–39.72 ng/mL) in spring, 28.79 ng/mL (21.53–39.37 ng/mL) in summer, 30.12 ng/mL (22.00–39.70 ng/mL) in autumn, and 28.58 ng/mL (19.97–39.46 ng/mL) in winter. Statistically significant differences were noted in the serum 25(OH)D levels during autumn and winter. In conclusion, the rate of adequate vitamin D levels in local children was 47.5%, revealing a relatively high prevalence of vitamin D deficiency (21.4%) and insufficiency (31.0%), especially during the post-preschool period. Advocating for vitamin D supplementation in children is crucial for ensuring adequate vitamin D support.

In the realm of commercial rabbit farming, assessment of liveweight for each rabbit is crucial for production management. Traditional manual weighing methods are labor-intensive, time-consuming, and can induce stress and disease transmission. To solve this problem, this paper introduced a liveweight estimation method for rabbit utilizing near-infrared and depth image, including a segmentation stage and a weight estimation stage. Specifically, a dual-stream feature fusion mechanism was proposed to effectively integrate information from both near-infrared and depth imaging. The network was trained and validated on a dataset of 1,957 overhead images from 300 rabbits collected from a commercial farm, achieving superior performance with an R-Square (R2) of 0.95, Root Mean Square Error (RMSE) of 194.95 g, Mean Absolute Deviation (MAD) of 155.10 g, Mean Absolute Percentage Error (MAPE) of 4.08 %, and Mean Coefficient of Variation (MCV) of 3.03 %. Ablation experiments revealed that employing the proposed dual-stream feature fusion mechanism led to reductions of 52.87 g, 38.19 g, 1.01 %, and 0.75 % in RMSE, MAD, MAPE, and MCV, respectively, compared to not employing the mechanism. Compared to machine learning method, our proposed approach demonstrates superior performance in RMSE, MAD, MAPE, and MCV, achieving more accurate liveweight estimation for large-scale commercial farms.

We previously reported that immunoglobulin superfamily member 9 (IGSF9) as a tumor specific immune checkpoint promoted the tumor immune escape, however, as an adhesion molecule, whether IGSF9 promotes tumor invasion and metastasis has not been reported. Here, the full length, the intracellular domain (ID) not extracellular domain (ECD) of IGSF9 could alter tumor cell morphology from a flat and polygonal shape to elongated strips, suggesting that IGSF9 signal pathway has the potential to mediate epithelial-to-mesenchymal transition (EMT). Real-time PCR and western blotting also showed that the mesenchymal markers were significantly up-regulated, and the epithelial markers were significantly down-regulated in IGSF9 and IGSF9-ID groups. Meanwhile, immunofluorescence showed that β-catenin was clearly translocated into the nucleus in IGSF9 and IGSF9-ID groups. The in vitro and in vivo data showed that IGSF9, IGSF9-ID and ECD could promote tumor invasion and metastasis. Mechanistically, IGSF9-ID could recruit GSK-3β to result in the accumulation and nuclear translocation of β-catenin to trigger EMT. Anti-IGSF9 could significantly inhibit the invasion and metastasis, and IGSF9 is an effective candidate for lung cancer therapy.

AbstractBackground Although ERAS Program had some advantages in laparoscopic distal gastrectomy (LDG), its efficacy and safety remained unclear. We conducted a systematic review and meta-analysis to assess the efficacy and safety of the ERAS group and the traditional care (TC) group in LDG.Methods Multiple databases were retrieved from 1 January 2000 to 30 April 2023. The risk ratio (RR), standardized mean difference (SMD) and their 95% confidence interval (CI) were used to estimate the results.Results Our meta-analysis contained 17 randomized controlled trials (RCTs) studies, which comprised 1468 patients. Regarding efficacy, the ERAS group had significantly shorter postoperative time to first flatus (SMD = −1.29 [95% CI: −1.68, −0.90]), shorter time to first defecation (SMD = −1.26 [95% CI: −1.90, −0.61]), shorter hospital stays (SMD = −0.99 [95% CI: −1.34, −0.63]), and lower hospitalization costs (SMD = −1.17 [95% CI: −1.86, −0.48]) compared to the TC group. Furthermore, in the ERAS group, C-reactive protein levels were lower on postoperative days 1, 3 or 4, and 7; albumin levels were higher on postoperative days 3 or 4 and 7; and interleukin-6 levels were lower on postoperative days 1 and 3. Regarding safety, the overall postoperative complication rate was lower in the ERAS group (RR: 0.76 [95% CI: 0.60, 0.97]), but there was no significant difference in the individual postoperative complication rate. Other indicators were also not statistically significant.Conclusion The combination of ERAS Program with laparoscopy surgery was safe and effective for the perioperative management of patients with distal gastric cancer.

Effective early pregnancy diagnosis is crucial for commercial rabbit breeding. Early pregnancy diagnosis enables the implementation of staged feeding for pregnant does, effectively preventing excessive weight gain and reducing the high mortality rates of kits during the birthing stage. This not only enhances production efficiency but also ensures the health and well-being of the breeding rabbits. The study introduces a method and device, the Rabbit Pregnancy Identification Device (RAPID), for detecting rabbit pregnancies using matrix optical sensing. RAPID comprises eight sensor modules and a central host unit. Each sensor module is equipped with three LEDs emitting light at wavelengths of 660 nm, 850 nm, and 940 nm, along with two photodiodes for data collection. A mobile application was developed to enable flexible control of the device. Signal-to-noise ratio tests were conducted to evaluate the stability of data collection by the device across varying light intensities. The experimental results reveal a direct correlation between light intensity levels and the signal-to-noise ratio of collected data. Notably, under a light intensity level of 4, RAPID achieves a signal-to-noise ratio ranging from 42 to 45 dB, satisfying the necessary criteria for data collection. Different classification models were trained using sample data from 216 does across various batches, and their generalization capabilities were evaluated. The experimental findings indicate that the optimal time for RAPID to diagnose the pregnancy status of does is on the 14th day after insemination, achieving an accuracy of 86.63 % and a recall of 80.49 %. Moreover, the model exhibits a degree of generalization, achieving an accuracy of 78.36 % when classifying another batch of sample data. RAPID achieves an accuracy of 97.25 % for pregnancy diagnosis of older does, which is 7.44 % higher than that of younger does; the accuracy rate for pregnancy diagnosis of does with sparse hair is 86.92 %, which is 4.78 % higher than that of does with dense hair. By comparing the effectiveness of using data from 8 sensor modules and data from a single sensor module for pregnancy diagnosis of different batches of does, it was found that the former exhibits more stable generalization capability in doe pregnancy detection.

In this study, corn starch was used as the raw material, and modified starch was prepared using a method combining plasma-activated water and ultrasound treatment (PUL). This method was compared with treatments using plasma-activated water (PAW) and ultrasound (UL) alone. The structure, thermal, physicochemical, pasting, and functional properties of the native and treated starches were evaluated. The results indicated that PAW and UL treatments did not alter the shape of the starch granules but caused some surface damage. The PUL treatment increased the starch gelatinization temperature and enthalpy (from 11.22 J/g to 13.13 J/g), as well as its relative crystallinity (increased by 0.51 %), gel hardness (increased by 16.19 %) compared to untreated starch, without inducing a crystalline transition. The PUL treatment resulted in a whitening of the samples. The dual treatment enhanced the thermal stability of the starch paste, which can be attributed to the synergistic effect between PAW and ultrasound (PAW can modify the starch structure at a molecular level, while ultrasound can further disrupt the granule weak crystalline structures, leading to improved thermal properties). Furthermore, FTIR results suggested significant changes in the functional groups related to the water-binding capacity of starch, and the order of the double-helical structure was disrupted. The findings of this study suggest that PUL treatment is a promising new green modification technique for improving the starch structure and enhancing starch properties. However, further research is needed to tailor the approach based on the specific properties of the raw material.

Abstract Background The incidence of breast cancer among Chinese women has gradually increased in recent years. This study aims to analyze the situation of breast cancer screening programs in China and compare the cancer detection rates (CDRs), early-stage cancer detection rates (ECDRs), and the proportions of early-stage cancer among different programs. Methods We conducted a systematic review and meta-analysis of studies in multiple literature databases. Studies that were published between January 1, 2010 and June 30, 2023 were retrieved. A random effects model was employed to pool the single group rate, and subgroup analyses were carried out based on screening model, time, process, age, population, and follow-up method. Results A total of 35 studies, including 47 databases, satisfied the inclusion criteria. Compared with opportunistic screening, the CDR (1.32‰, 95% CI: 1.10‰–1.56‰) and the ECDR (0.82‰, 95% CI: 0.66‰–0.99‰) were lower for population screening, but the proportion of early-stage breast cancer (80.17%, 95% CI: 71.40%–87.83%) was higher. In subgroup analysis, the CDR of population screening was higher in the urban group (2.28‰, 95% CI: 1.70‰–2.94‰), in the breast ultrasonography (BUS) in parallel with mammography (MAM) group (3.29‰, 95% CI: 2.48‰–4.21‰), and in the second screening follow-up group (2.47‰, 95% CI: 1.64‰–3.47‰), and the proportion of early-stage breast cancer was 85.70% (95% CI: 68.73%–97.29%), 88.18% (95% CI: 84.53%–91.46%), and 90.05% (95% CI: 84.07%–94.95%), respectively. Conclusion There were significant differences between opportunistic and population screening programs. The results of these population screening studies were influenced by the screening process, age, population, and follow-up method. In the future, China should carry out more high-quality and systematic population-based screening programs to improve screening coverage and service.

Abstract Background Central nervous system (CNS) tumors are the most common solid tumors in children and the leading cause of cancer-related death in the latter. Currently, the incidence rate exceeds that of leukemia and ranks first in the incidence of malignant tumors in children. Methods The epidemiological data on childhood CNS tumors were collected from the Chinese Cancer Registry Annual Report. The annual percent change (APC) of incidence and mortality-rate changes were estimated via Joinpoint regression. Due to a lack of pertinent data, we performed a system review on the clinical-pathological characteristics in Chinese publications. Results There was no significant increase in the incidence rate (APC: -0.1, 95% CI: -1.5 to 1.3), but there was a significant increase in the mortality rate (APC: 1.8, 95% CI: 0.3 to 3.4) for childhood CNS tumors. In the subgroup analysis, there were significant increases in both the incidence and mortality rates in rural areas (APC in the incidence: 6.2, 95% CI: 2.4 to 10.2; APC in mortality: 4.4, 95% CI: 0.4 to 8.4). The most common location and type of childhood CNS were, respectively, the cerebral hemisphere (25.5%, 95% CI: 21.7% to 29.4%) and astrocytomas (26.8%, 95% CI: 23.9% to 29.6%). Conclusions The epidemiological trends, and the relevant prediction, highlighted the need to pay continual attention to childhood CNS tumors, and the clinicopathology evinced its own distinctive characteristics. Timely detection and effective treatment must be further promoted regarding childhood CNS tumors with a view to decreasing the disease burden, especially in rural areas.

BackgroundCongenital insensitivity to pain with anhidrosis (CIPA, OMIM #256800), also known as hereditary sensory and autonomic neuropathy type Ⅳ (HSAN-IV), is a rare autosomal recessive disorder characterized by recurrent episodic fevers, anhidrosis, insensitivity to noxious stimuli, self-mutilating behavior and intellectual disability. CIPA can be caused by the variants in NTRK1 gene, which encodes a high-affinity tyrosine kinase receptor for nerve growth factor. To ascertain the hereditary cause of a patient with CIPA accompanied by the additional symptoms of mild growth retardation, prone to fracture, underdeveloped nails of fingers and toes, irregular tooth alignment, enamel hypoplasia, postoperative wound healing difficulty, hand and limb deformity, and dislocation of hip joint, whole exome sequencing was used and revealed a compound heterozygous variant in NTRK1.MethodsDNA was extracted from peripheral blood samples of pediatric patients and their parents, and subjected to comprehensive analysis using whole-exome sequencing (WES), followed by verification of variant sites in the NTRK1 gene through Sanger sequencing. To elucidate the functional impact of the newly discovered variants, an in vitro experimental system was established. Splicing analysis was conducted using PCR and Sanger sequencing, while expression levels were assessed through qPCR and Western blot techniques.ResultsOne hotspot variant c.851-33T>A(ClinVar ID: 21308) and a novel variant c.850 + 5G>A(ClinVar ID:3069176) was inherited from her father and mother, respectively, identified in the affected individuals. The c.850 + 5G>A variant in NTRK1 resulted in two forms of aberrant mRNA splicing: 13bp deletion (c.838_850del13, p. Val280Ser fs180) and 25bp deletion (826_850del25, p. Val276Ser fs180) in exon 7, both leading to a translational termination at a premature stop codon and forming a C-terminal truncated protein. The expression of two abnormal splicing isoforms was decreased both in the level of mRNA and protein.ConclusionIn conclusion, this study elucidated the genetic cause of a patient with CIPA and identified a novel variant c.850 + 5G>A in NTRK1, which broadened the and enriched the NTRK1 mutation spectrum.

Abstract Background To study the value of shear wave elasticity and shear wave dispersion imaging to evaluate the viscoelasticity of renal parenchyma in children with glomerular diseases. Methods Forty-three children with glomerular diseases were prospectively evaluated by shear wave elasticity (SWE) and shear wave dispersion imaging (SWD); 43 healthy volunteers served as the control group. The shear wave velocities (SWV) and the dispersion slopes were measured at the upper, middle, and lower poles of both kidneys. The analysis of mean SWV and mean dispersion slope in control and patient groups was used to further evaluate the value of SWE and SWD in the viscoelasticity of renal parenchyma in children with glomerular disease. Results The mean SWV in children with glomerular disease was higher than that in the healthy control group (1.61 ± 0.09 m/s vs. 1.43 ± 0.07 m/s, p

Abstract Ileocolic intussusception is one of the common acute abdomens in children and is first diagnosed urgently using ultrasound. Manual diagnosis requires extensive experience and skill, and identifying surgical indications in assessing the disease severity is more challenging. We aimed to develop a real-time lesion visualization deep-learning pipeline to solve this problem. This multicenter retrospective-prospective study used 14,085 images in 8736 consecutive patients (median age, eight months) with ileocolic intussusception who underwent ultrasound at six hospitals to train, validate, and test the deep-learning pipeline. Subsequently, the algorithm was validated in an internal image test set and an external video dataset. Furthermore, the performances of junior, intermediate, senior, and junior sonographers with AI-assistance were prospectively compared in 242 volunteers using the DeLong test. This tool recognized 1,086 images with three ileocolic intussusception signs with an average of the area under the receiver operating characteristic curve (average-AUC) of 0.972. It diagnosed 184 patients with no intussusception, nonsurgical intussusception, and surgical intussusception in 184 ultrasound videos with an average-AUC of 0.956. In the prospective pilot study using 242 volunteers, junior sonographers’ performances were significantly improved with AI-assistance (average-AUC: 0.966 vs. 0.857, P

Abstract Visual landmarks influence spatial cognition and behavior, but their influence on visual codes for action is poorly understood. Here, we test landmark influence on the visual response to saccade targets recorded from 312 frontal and 256 supplementary eye field neurons in rhesus macaques. Visual response fields are characterized by recording neural responses to various target-landmark combinations, and then we test against several candidate spatial models. Overall, frontal/supplementary eye fields response fields preferentially code either saccade targets (40%/40%) or landmarks (30%/4.5%) in gaze fixation-centered coordinates, but most cells show multiplexed target-landmark coding within intermediate reference frames (between fixation-centered and landmark-centered). Further, these coding schemes interact: neurons with near-equal target and landmark coding show the biggest shift from fixation-centered toward landmark-centered target coding. These data show that landmark information is preserved and influences target coding in prefrontal visual responses, likely to stabilize movement goals in the presence of noisy egocentric signals.

In large-scale poultry farming, real-time online measurement of egg weight and shape parameters remains a challenge. To address this, we developed FEgg3D, a non-contact dynamic measuring device based on a self-designed laser scanner. The device employed a subset of the point cloud generated to predict the shape parameters and weight of eggs using machine learning algorithms. Different colors and sizes of eggs on various backgrounds were scanned using FEgg3D mounted on a gantry system. Our results demonstrated the following: (1) The Support Vector Regression (SVR) model was optimal for major axis length estimation, with an R2 of 0.932 using six laser lines and eight points per line. (2) The Gaussian Process Regression (GPR) model excelled in minor axis length estimation, achieving an R2 of 0.974 with six laser lines and 16 points per line. (3) SVR was optimal for volume estimation, attaining an R2 of 0.962 with six laser lines and 16 points per line. (4) GPR showed superior performance in weight prediction, with an R2 of 0.964 using five laser lines and 16 points per line. Including density features significantly improved accuracy to an R2 of 0.978. This approach paves the way for advanced online egg measurement in commercial settings.

Using the discrete element method to simulate the interaction between growing media and machinery is an effective method to design seedling machinery and improve the precision of facility horticultural operations. In order to further improve the accuracy of the study on the interaction between seedling block-forming machines and growing media, the growing media used in the production of seedling nursery blocks was taken as the research object, and the Plackett–Burman screening test and Box–Behnken test were conducted based on the discrete element method using the EEPA model to conduct the calibration of discrete element parameters of the growing media. Optimization was conducted with an actual repose angle as the target value, and the optimal combination is as follows: the interparticle collision-recovery coefficient is 0.5066, the collision-recovery coefficient between particles and the geometric model is 0.714, the interparticle dynamic-friction coefficient is 0.381, and the tangential stiffness factor is 0.375. Finally, the soil uniaxial closed compression test was conducted with optimized calibration parameters. The relative error between the maximum axial load on the punch and the measured value in the simulation process was 4.23%, which verified the accuracy and reliability of parameter calibration of the growing media and provided support for the simulation of growing media and optimization of seedling nursery block-forming machine.

With the widespread application of tagging materials, existing chemical tagging materials exhibit limitations in stability and detection under field conditions. This study introduces a novel magnetic detection scheme. Hydrophilic material-modified Fe3O4 nanoparticles (COOH-PEG@Fe3O4 NPs) were synthesized using the co-precipitation technique. The content of Fe3O4 nanoparticles in the magnetic tagging liquid can reach up to 10 wt% and remain stable in an aqueous phase system for seven days. This research details the preparation process, the characterization methods (IR, 1HNMR, EDX, XRD, SEM, TEM, VSM, DLS), and the performance effects of the materials in magnetic tagging. Experimental results indicate that COOH-PEG@Fe3O4 NPs exhibit high remanence intensity (Br = 1.75 emu/g) and considerable stability, making it possible to quickly detect tagged liquids in the field using portable flux meters and optical pump magnetometers. This study provides new insights into the design and application of magnetic tagging materials, making it particularly suitable for long-term tagging and convenient detection in field scenarios.

In future smart cities, automatic landscape design can be viewed as a promising intelligent application to reduce the reliance on expert labors. As it is a kind of visual sensing activity, it is expected to develop a robust interaction platform with strong ability of visual information fusion. To deal with this issue, this paper integrates vision computing, and designs an automatic landscape design system in smart cities. The whole design framework can be attributed as three aspects of works: function analysis, structure design and implementation. Among, the visual information processing runs through the three aspects. Then, the generation process of landscape design is simulated in detail via a systematic case study. To prove the significance of visual information processing in our proposal, this article uses a model analysis method to compare the effects of traditional data processing technology and visual data processing technology. The analysis results show that vision computing technology provides technical support for landscape design. We also carry out some performance testing towards the designed automatic landscape design system, and evaluation results are demonstrated via visualization format. The designed automatic system is a proper prototype that can be developed to realistic engineering systems by some following completion.

Objectives. We aimed to develop a new calculation model for calcium requirements in dialysis patients following parathyroidectomy. Methods. A total of 98 patients with secondary hyperparathyroidism receiving parathyroidectomy from January 2014 to January 2022 were enrolled in this study. Among these patients, 78 were randomly selected for construction of the calcium requirement calculation model, and the remaining 20 patients were selected for model validation. The calcium requirement model estimated the total calcium supplementation for 1 week after surgery using variables with significant relationships in the derivation group by stepwise multiple linear regression analysis. Bias, precision, and accuracy were measured in the validation group to determine the performance of the model. Results. The model was as follows: calcium requirement for 1 week after surgery=33.798–8.929×immediate postoperative calcium+0.190×C-reactive protein–0.125×age+0.002×preoperative intact parathyroid hormone+0.003×preoperative alkaline phosphatase (R2=0.8). The model was successfully validated. Conclusion. We generated a novel model to guide calcium supplementation. This model can assist in stabilizing the serum calcium levels of patients during the early postoperative period. Furthermore, it contributes to the individualized and precise treatment of hypocalcemia in patients following parathyroidectomy.

Abstract Background Depression is a prevalent mental health disorder with a complex etiology and substantial public health implications. Early identification of individuals at risk for depression is crucial for effective intervention and prevention efforts. This study aimed to develop a predictive model for depression by integrating demographic factors (age, race, marital status, income), lifestyle factors (sleep duration, physical activity), and physiological measures (hypertension, blood lead levels). A key objective was to explore the role of physical activity and blood lead levels as predictors of current depression risk. Methods Data were extracted from the 2007–2014 National Health and Nutrition Examination Survey (NHANES). We applied a logistic regression analysis to these data to assess the predictive value of the above eight factors for depression to create the predictive model. Results The predictive model had bootstrap-corrected c-indexes of 0.68 (95% CI, 0.67–0.70) and 0.66 (95% CI, 0.64–0.68) for the training and validation cohorts, respectively, and well-calibrated curves. As the risk of depression increased, the proportion of participants with 1.76 ~ 68.90 µg/L blood lead gradually increased, and the proportion of participants with 0.05 ~ 0.66 µg/L blood lead gradually decreased. In addition, the proportion of sedentary participants increased as the risk of depression increased. Conclusions This study developed a depression risk assessment model that incorporates physical activity and blood lead factors. This model is a promising tool for screening, assessing, and treating depression in the general population. However, because the corrected c-indices of the predictive model have not yet reached an acceptable threshold of 0.70, caution should be exercised when drawing conclusions. Further research is required to improve the performance of this model.

Abstract Background The purpose of this paper was to systematically evaluate the application value of artificial intelligence in predicting mortality among COVID-19 patients. Methods The PubMed, Embase, Web of Science, CNKI, Wanfang, China Biomedical Literature, and VIP databases were systematically searched from inception to October 2022 to identify studies that evaluated the predictive effects of artificial intelligence on mortality among COVID-19 patients. The retrieved literature was screened according to the inclusion and exclusion criteria. The quality of the included studies was assessed using the QUADAS-2 tools. Statistical analysis of the included studies was performed using Review Manager 5.3, Stata 16.0, and Meta-DiSc 1.4 statistical software. This meta-analysis was registered in PROSPERO (CRD42022315158). Findings Of 2193 studies, 23 studies involving a total of 25 AI models met the inclusion criteria. Among them, 18 studies explicitly mentioned training and test sets, and 5 studies did not explicitly mention grouping. In the training set, the pooled sensitivity was 0.93 [0.87, 0.96], the pooled specificity was 0.94 [0.87, 0.97], and the area under the ROC curve was 0.98 [0.96, 0.99]. In the validation set, the pooled sensitivity was 0.84 [0.78, 0.88], the pooled specificity was 0.89 [0.85, 0.92], and the area under the ROC curve was 0.93 [1.00, 0.00]. In the subgroup analysis, the areas under the summary receiver operating characteristic (SROC) curves of the artificial intelligence models KNN, SVM, ANN, RF and XGBoost were 0.98, 0.98, 0.94, 0.92, and 0.91, respectively. The Deeks funnel plot indicated that there was no significant publication bias in this study (P > 0.05). Interpretation Artificial intelligence models have high accuracy in predicting mortality among COVID-19 patients and have high prognostic value. Among them, the KNN, SVM, ANN, RF, XGBoost, and other models have the highest levels of accuracy.

Abstract Duct-dependent congenital heart diseases (CHDs) are a serious form of CHD with a low detection rate, especially in underdeveloped countries and areas. Although existing studies have developed models for fetal heart structure identification, there is a lack of comprehensive evaluation of the long axis of the aorta. In this study, a total of 6698 images and 48 videos are collected to develop and test a two-stage deep transfer learning model named DDCHD-DenseNet for screening critical duct-dependent CHDs. The model achieves a sensitivity of 0.973, 0.843, 0.769, and 0.759, and a specificity of 0.985, 0.967, 0.956, and 0.759, respectively, on the four multicenter test sets. It is expected to be employed as a potential automatic screening tool for hierarchical care and computer-aided diagnosis. Our two-stage strategy effectively improves the robustness of the model and can be extended to screen for other fetal heart development defects.

Developing a meniscus substitute mimicking the anisotropic mechanics (higher circumferential tensile modulus and lower compressive modulus) of native tissue remains a great challenge. In this work, based on the pendant group structure-dependent H-bonding strengthening mechanism, two kinds of amide-based H-bonding crosslinked hydrogels with distinct mechanical behaviors, that is, the flexible poly(N-acryloyl glycinamide) (PNAGA) and the ultra-stiff poly(N-acryloylsemicarbazide) (PNASC) hydrogels are employed to construct the biomimetic meniscus substitute. To this end, a gel microparticle-based self-thickening strategy is first proposed to fabricate PNASC (GMP-PNASC) high-modulus hydrogels skeleton by extrusion printing technology in mimicking the collagen fibers in native meniscus to resist the circumferential tensile stress. Then, the PNAGA hydrogel is infused into the PNASC skeleton to replicate the proteoglycan, providing a lower compressive modulus. By regulating the structural features at the interior and peripheral regions, the GMP-PNASC/PNAGA hydrogel meniscus scaffold with the higher tensile modulus (87.28 ± 6.06 MPa) and lower compressive modulus (2.11 ± 0.28 MPa) can be constructed. In vivo outcome at 12 weeks post-implantation of rabbit's medial meniscectomy model confirms the effects of GMP-PNASC/PNAGA meniscus scaffold on alleviating the wear of articular cartilage and ameliorating the development of osteoarthritis (OA).

Abstract Alkylnitriles play important roles in many fields because of their unique electronic properties and structural characteristics. Incorporating cyanoalkyl with characteristic spectroscopy and reactivity properties into amino acids and peptides is of special interest for potential imaging and therapeutic purposes. Here, we report a copper-catalyzed asymmetric cyanoalkylation of C(sp3)-H. In the reactions, glycine derivatives can effectively couple with various cycloalkanone oxime esters with high enantioselectivities, and the reaction can be applied to the late-stage modification of peptides with good yields and excellent stereoselectivities, which is useful for modern peptide synthesis and drug discovery. The mechanistic studies show that the in situ formed copper complex by the coordination of glycine derivatives and chiral phosphine Cu catalyst can not only mediate the single electronic reduction of cycloalkanone oxime ester but also control the stereoselectivity of the cyanoalkylation reaction.

Obesity is associated with chronic inflammation in the central nervous system (CNS), and neuroinflammation has been shown to have detrimental effects on mood and cognition. The growth hormone secretagogue receptor (GHSR), the biologically relevant receptor of the orexigenic hormone ghrelin, is primarily expressed in the brain. Our previous study showed that neuronal GHSR deletion prevents high-fat diet-induced obesity (DIO). Here, we investigated the effect of neuronal GHSR deletion on emotional and cognitive functions in DIO. The neuron-specific GHSR-deficient mice exhibited reduced depression and improved spatial memory compared to littermate controls under DIO. We further examined the cortex and hippocampus, the major regions regulating cognitive and emotional behaviors, and found that the neuronal deletion of GHSR reduced DIO-induced neuroinflammation by suppressing proinflammatory chemokines/cytokines and decreasing microglial activation. Furthermore, our data showed that neuronal GHSR deletion suppresses neuroinflammation by downregulating AMPK-autophagy signaling in neurons. In conclusion, our data reveal that neuronal GHSR inhibition protects against DIO-induced depressive-like behavior and spatial cognitive dysfunction, at least in part, through AMPK-autophagy signaling-mediated neuroinflammation.

In this study, classic thin-layer drying models such as the Page model, Verma model, and Two-term model were used to fit the thin-layer drying data of feed. Based on this, a novel thin-layer drying model for pelleted feed (modified Verma model) was proposed. The results indicate that the new model is the optimal choice for describing the drying kinetics of pelleted feed for growing pig and calf. The drying rate of pelleted feed is linearly correlated with the feed moisture content. The effective water diffusion coefficient for pelleted feed of growing pig and calf ranges from 1.86 × 10−10 to 2.75 × 10−9 m2/s and 3.32 × 10−10 to 3.87 × 10−9 m2/s, respectively. The activation energy (Ea) for moisture diffusion in both types of feed is 26.42 kJ/mol and 25.86 kJ/mol, respectively. By establishing predictive models for model parameters based on air temperature and air velocity variables, the new model demonstrates extrapolation capability, wide applicability, and practical value. This work lays the foundation for developing a similarly characterized deep-bed cooling drying model for pelleted feed.

AbstractObjectives The outcome of balloon-based atherosclerosis thermoplasty is closely related to the temperature/stress distribution during the treatment. For precise prediction of a required thermal lesion in the heterogeneous and thin atherosclerotic vessel, a numerical model incorporating heat-induced tissue expansion or shrinkage and the strain caused by balloon dilation is necessary.Methods A fully coupled thermal-electrical-structural new model was established. The model features a heterogeneous structure including eccentric plaque, healthy artery and surrounding tissue. Tissue expansion/shrinkage and hyperelasticity material model were taken into consideration. Different heating strategies and plaque mechanical properties were investigated. The temperature distribution was compared with the traditional thermal-electrical coupled model. The possibility of thermoplasty treatment using balloons with different sizes was also explored.Results The temperature, the electrical intensity and the stress during the thermoplasty were obtained. Lower stress was found in the heating region where tissue shrinkage occurred. The ablation depth was predicted to be ∼0.42 mm larger without coupling the biomechanical influence. The mechanical properties and input condition significantly affect the temperature and stress distribution considering the small dimensions of the tissue. Besides, with a 12.5% reduction of balloon diameter, the largest Von Mises stress decreases by 25.4%.Conclusions It is confirmed that a coupled thermal-electrical-structural model is needed for precise temperature prediction in the balloon-based thermoplasty of the heterogeneous and thin tissue. The model presented may help with future development of optimized treatment planning considering both ablation depth and minimum stress.

Abstract Background Interspecific hybridization plays vital roles in enriching animal diversity, while male hybrid sterility (MHS) of the offspring commonly suffered from spermatogenic arrest constitutes the postzygotic reproductive isolation. Cattle-yak, the hybrid offspring of cattle (Bos taurus) and yak (Bos grunniens) can serve as an ideal MHS animal model. Although meiotic arrest was found to contribute to MHS of cattle-yak, yet the cellular characteristics and developmental potentials of male germline cell in pubertal cattle-yak remain to be systematically investigated. Results Single-cell RNA-seq analysis of germline and niche cell types in pubertal testis of cattle-yak and yak indicated that dynamic gene expression of developmental germ cells was terminated at late primary spermatocyte (meiotic arrest) and abnormal components of niche cell in pubertal cattle-yak. Further in vitro proliferation and differentially expressed gene (DEG) analysis of specific type of cells revealed that undifferentiated spermatogonia of cattle-yak exhibited defects in viability and proliferation/differentiation potentials. Conclusion Comparative scRNA-seq and in vitro proliferation analysis of testicular cells indicated that not only meiotic arrest contributed to MHS of cattle-yak. Spermatogenic arrest of cattle-yak may originate from the differentiation stage of undifferentiated spermatogonia and niche cells of cattle-yak may provide an adverse microenvironment for spermatogenesis.

Objective To investigate the pain catastrophising in patients with breast cancer during postoperative chemotherapy.Methods Objective sampling method was used to select patients with breast cancer who underwent breast surgery and received chemotherapy in a third-class hospital of Wuhan from October to December 2022 through semi-structured interview. The interview data were sorted out and analysed by content analysis method.Results A total of 11 patients were interviewed and five categories were summarised: (1) Physical memory of pain; (2) the special meaning of time; (3) disease treatment and prognosis; (4) interpersonal communication and coping; (5) personal behaviour and growth.Conclusion Patients with breast cancer have adverse pain experience during postoperative chemotherapy. The evaluation and screening of psychological variables such as pain catastrophising should be strengthened to provide new ideas for pain management.

BackgroundProgrammed cell death protein 1 (PD-1) receptor has two ligands,programmed death-ligand 1 (PD-L1) and PD-L2. When compared with PD-L1, PD-L2 has not received much attention, and its role remains unclear.MethodsThe expression profiles of pdcd1lg2 (PD-L2-encoding gene) mRNA and PD-L2 protein were analyzed using TCGA, ICGC, and HPA databases. Kaplan-Meier and Cox regression analyses were used to assess the prognostic significance of PD-L2. We used GSEA, Spearman’s correlation analysis and PPI network to explore the biological functions of PD-L2. PD-L2-associated immune cell infiltration was evaluated using the ESTIMATE algorithm and TIMER 2.0. The expressions of PD-L2 in tumor-associated macrophages (TAMs) in human colon cancer samples, and in mice in an immunocompetent syngeneic setting were verified using scRNA-seq datasets, multiplex immunofluorescence staining, and flow cytometry. After fluorescence-activated cell sorting, flow cytometry and qRT-PCR and transwell and colony formation assays were used to evaluate the phenotype and functions of PD-L2+TAMs. Immune checkpoint inhibitors (ICIs) therapy prediction analysis was performed using TIDE and TISMO. Last, a series of targeted small-molecule drugs with promising therapeutic effects were predicted using the GSCA platform.ResultsPD-L2 was expressed in all the common human cancer types and deteriorated outcomes in multiple cancers. PPI network and Spearman’s correlation analysis revealed that PD-L2 was closely associated with many immune molecules. Moreover, both GSEA results of KEGG pathways and GSEA results for Reactome analysis indicated that PD-L2 expression played an important role in cancer immune response. Further analysis showed that PD-L2 expression was strongly associated with the infiltration of immune cells in tumor tissue in almost all cancer types, among which macrophages were the most positively associated with PD-L2 in colon cancer. According to the results mentioned above, we verified the expression of PD-L2 in TAMs in colon cancer and found that PD-L2+TAMs population was not static. Additionally, PD-L2+TAMs exhibited protumor M2 phenotype and increased the migration, invasion, and proliferative capacity of colon cancer cells. Furthermore, PD-L2 had a substantial predictive value for ICIs therapy cohorts.ConclusionPD-L2 in the TME, especially expressed on TAMs, could be applied as a potential therapeutic target.

Type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) share several common pathophysiological features. Rare variants of triggering receptor expressed on myeloid cells 2 (TREM2) increase the risk of developing AD, suggesting the involvement of TREM2 and innate immunity in AD development. It is still unknown whether TREM2 is related to cognitive impairment in T2DM. Here, we investigated the effects of the hippocampal overexpression of TREM2 on cognitive in long-term high-fat diet (HFD)-fed mice. Male C57BL/6J mice were maintained on HFD for 50 weeks. TREM2 was overexpressed in the hippocampus 36 weeks after HFD feeding using adeno-associated virus vector (AAV)-mediated gene delivery. The results showed that the HFD feeding induced rapid and persistent weight gain, glucose intolerance and significant impairments in learning and memory. Compared with AAV-con, AAV-TREM2 significantly ameliorated cognitive impairment without altering body weight and glucose homeostasis in HFD mice. The overexpression of TREM2 upregulated the synaptic proteins spinophilin, PSD95 and synaptophysin, suggesting the improvement in synaptic transmission. Dendritic complexity and spine density in the CA1 region were rescued after TREM2 overexpression. Furthermore, TREM2 markedly increased the number of iba-1/Arg-1-positive microglia in the hippocampus, suppressed neuroinflammation and microglial activation. In sum, hippocampal TREM2 plays an important role in improving HFD-induced cognitive dysfunction and promoting microglial polarization towards the M2 anti-inflammatory phenotype. Our study also suggests that TREM2 might be a novel target for the intervention of obesity/diabetes-associated cognitive decline.

Abstract Background Once malignancy tumors were diagnosed, the determination of tissue origin and tumor type is critical for clinical management. Although the significant advance in imaging techniques and histopathological approaches, the diagnosis remains challenging in patients with metastatic and poorly differentiated or undifferentiated tumors. Gene expression profiling has been demonstrated the ability to classify multiple tumor types. The present study aims to assess the performance of a 90-gene expression test for tumor classification (i.e. the determination of tumor tissue of origin) in real clinical settings. Methods Formalin-fixed paraffin-embedded samples and associated clinicopathologic information were collected from three cancer centers between January 2016 and January 2021. A total of 1417 specimens that met quality control criteria (RNA quality, tumor cell content ≥ 60% and so on) were analyzed by the 90-gene expression test to identify the tumor tissue of origin. The performance was evaluated by comparing the test results with histopathological diagnosis. Results The 1417 samples represent 21 main tumor types classified by common tissue origins and anatomic sites. Overall, the 90-gene expression test reached an accuracy of 94.4% (1338/1417, 95% CI: 0.93 to 0.96). Among different tumor types, sensitivities were ranged from 74.2% (head&neck tumor) to 100% (adrenal carcinoma, mesothelioma, and prostate cancer). Sensitivities for the most prevalent cancers of lung, breast, colorectum, and gastroesophagus are 95.0%, 98.4%, 93.9%, and 90.6%, respectively. Moreover, specificities for all 21 tumor types are greater than 99%. Conclusions These findings showed robust performance of the 90-gene expression test for identifying the tumor tissue of origin and support the use of molecular testing as an adjunct to tumor classification, especially to those poorly differentiated or undifferentiated tumors in clinical practice.

We present a fully integrated cryogenic controller for electrostatically controlled quantum dots (QDs) implemented in a commercial 22-nm fully depleted silicon-on-insulator CMOS process and operating in a quantum regime. The QDs are realized in local well areas of transistors separated by tunnel barriers controlled by voltages applied to gate terminals. The QD arrays (QDA) are co-located with the control circuitry inside each quantum experiment cell, with a total of 28 of such cells comprising this system-on-chip (SoC). The QDA structure is controlled by small capacitive digital-to-analog converters (CDACs) and its quantum state is measured by a single-electron detector. The SoC operates at a cryogenic temperature of 3.4K. The occupied area of each QDA is $0.7 \times 0.4\mu \text{m}^2$ , while each QD occupies only $20 \times 80 \text{nm}^2$ . The low power and miniaturized area of these circuits are an important step on the way for integration of a large quantum core with millions of QDs, required for practical quantum computers. The performance and functionality of the CDAC are validated in a loop-back mode with the detector sensing the CDAC-compelled electron tunneling from the quantum point contact (QPC) node into the quantum structure. The position of the injected charge inside the QDA is intended to be controlled through the CDAC codes and programmable pulse width. Quantum effects are shown by an experimental characterization of charge injection and quantization into the QDA consisting of three coupled QDs. The charge can be transferred to a QD and sensed at the QPC, and this process is controlled by the relevant voltages and CDACs.

Many patients with genetic syndromes have special facial features, which boast significant potential value for clinical diagnosis. Deep learning and computer vision technology can be employed to diagnose genetic diseases by analyzing facial features of patients. As a matter of fact, the application of deep learning technology in the area of genetic diseases is confined owing to the difficulties of patient data acquisition. This study develops BioFace, a deep learning framework that can recognize multiple genetic diseases facial attributes based on limited datasets. BioFace is a deep neural network architecture designed premised on Resnet. To increase the weight of effective features and weaken the weight of invalid or unobvious features during extraction of facial features, we add Squeeze-and-Excitation (SE) blocks in the network. In combination with this network architecture, we designed a cross-loss training method based on transfer learning. This method can transfer the ability learned from the task of face identification to the task of recognition of genetic diseases facial attribute, and improve the inter-class distance of different genetic diseases and the intra-class distance of similar genetic diseases simultaneously. These render it possible for deep learning to be applied to recognition of multiple genetic diseases facial attribute with very small amount of data. In this research, we tested 10 syndromes with our framework and the Top-1 accuracy was 93.5%, which is the state-of-the-art in multiple genetic syndromes recognition research. In practical clinical applications, our framework and methods can be extended to the disease identification of more small datasets, potentially offering valuable assistance for the auxiliary clinical application of genetic diagnosis and other related genetic research.

Ferroptosis is an iron-dependent programmed cell death characterized by reactive oxygen species-induced lipid peroxidation and resultant membrane damage. Recent research has elucidated the mechanism of ferroptosis and investigated the relationship between ferroptosis and various diseases, including degenerative diseases, cancer, and inflammation. Ferroptosis is associated with inflammation-related intestinal diseases such as colitis and colitis-associated cancer. New insights into the role of ferroptosis in the pathogenesis of inflammation-related gut diseases have suggested novel therapeutic targets. In this review, we summarize current information on the molecular mechanisms of ferroptosis and describe its emerging role and therapeutic potential in inflammation-related intestinal diseases.

A large amount of rabbit manure is produced with the development of the rabbit industry, which will cause environmental pollution without proper treatment. Rabbit manure compost may be suitable for seedling cultivation, considering its low moisture, low heavy metal, high lignocellulose, and good fertilizer effect. In this study, a pre-proportioning test of growing media was conducted to optimize the ratio of perlite and vermiculite with peat/rabbit manure compost according to their physicochemical properties. Then, based on the results of the first proportioning optimization, the mixing ratio of rabbit manure compost and peat was further optimized using a bioassay. In this bioassay, salt-tolerant calendula (Calendula officinalis L.) and salt-intolerant cucumber (Cucumis sativus L.) were selected as test plants. The seedling effects (e.g., seedling emergence percentage, plant growth parameters, plant biomass, and nutrient effects) were evaluated. It was shown in the results that the rabbit manure compound growing media could be used for the seedlings, and suitable seedling performance was obtained with the increase of the total porosity (5.0%–61.2%), organic matter content (8.3%–39.9%), and nutrient elements from the rabbit manure compost. From the perspective of seedling emergence, there was no significant difference between rabbit manure compound media and peat treatment, in which the highest emergence percentages were >90%. At the same time, the nutrient performance of plant aboveground was significantly increased in rabbit manure compound growing media compared to peat treatment. In particular, the contents of P and Mg were increased by 31%–141.4% and 80.4%–107.8% for calendula and by 82.6%–117.4% and 35.1%–67.6% for cucumber, respectively. It was indicated in the two-step optimization that the rabbit manure compost proportion of 30%–50% (that is, 60%–100% instead of peat) was more suitable. Additionally, the greenhouse gas emission could be reduced by using rabbit manure compost replacing peat, and the greenhouse gas emission reduction potential would be 3.65 × 105–4.06 × 108 kg CO2-equivalent/year in China, which has important ecological significance.

BackgroundQuantitative contrast-enhanced ultrasonography parameters are affected by various factors. We evaluated corrected quantitative contrast enhanced ultrasonography in differentiating benign adnexal tumors from malignant tumors.MethodsPatients with adnexal masses who underwent conventional and contrast-enhanced ultrasonography were included. Contrast-enhanced ultrasonography parameters such as base intensity, arrival time, peak intensity, time to peak intensity, ascending slope, and descending slope were measured. Corrected (time to peak intensity − arrival time) mass/(time to peak intensity − arrival time) uterus and (peak intensity − base intensity) mass/(peak intensity − base intensity) uterus were calculated. Lesions were confirmed by pathologic examination of surgical specimens.ResultsThis study included 31 patients with 35 adnexal lesions including 20 (57.10%) benign and 15 (42.90%) malignant lesions. The corrected contrast-enhanced ultrasonography quantitative parameters in lesions were statistically different between malignant and benign groups (P

Titanium dioxide (TiO2) has emerged as a viable choice for several biological and environmental applications because of its high efficiency, cheap cost, and high photostability. In pursuit of this purpose, the research of its many forms has been influenced by these unique aspects. The development of novel TiO2-based hybrid materials with enhanced photocatalytically induced anticancer activity has gained tremendous attention. Here, we have developed a novel photocatalytic material (TiO2–Ag NPs@-CD) by decorating ultrasmall silver nanoparticles (Ag NPs) with per-6-thio-β-cyclodextrin (SH-β-CD) on TiO2 NPs. TiO2–Ag NPs@-CD were characterized by employing various characterization techniques and evaluated for their anticancer activity against HeLa cancer cells using an MTT assay. The biocompatibility of the designed nanoparticles was determined on two normal cell lines, namely, 3T3 and human mesenchymal stem cells (hMSCs). The results show that the TiO2–Ag NPs@-CD induced superior cytotoxic effects on HeLa cancer cells at a concentration of 64 μg/ml. Live-dead staining and oxidative stress investigations demonstrated that cell membrane disintegration and ROS-induced oxidative stress generated by TiO2-Ag NPs@-CD inside HeLa cancer cells are the contributing factors to their exceptional anti-cancer performance. Moreover, TiO2-Ag NPs@-CD exhibited good biocompatibility with 3T3 and hMSCs. These results indicated that the combination of all three components—a silver core, SH-β-CD ligands, and TiO2 nanoparticles—produced a synergistic anticancer effect. Hence, the TiO2-Ag NPs@-CD is a promising material that can be employed for different biological applications.

In large-scale laying hen farming, timely detection of dead chickens helps prevent cross-infection, disease transmission, and economic loss. Dead chicken detection is still performed manually and is one of the major labor costs on commercial farms. This study proposed a new method for dead chicken detection using multi-source images and deep learning and evaluated the detection performance with different source images. We first introduced a pixel-level image registration method that used depth information to project the near-infrared (NIR) and depth image into the coordinate of the thermal infrared (TIR) image, resulting in registered images. Then, the registered single-source (TIR, NIR, depth), dual-source (TIR-NIR, TIR-depth, NIR-depth), and multi-source (TIR-NIR-depth) images were separately used to train dead chicken detecting models with object detection networks, including YOLOv8n, Deformable DETR, Cascade R-CNN, and TOOD. The results showed that, at an IoU (Intersection over Union) threshold of 0.5, the performance of these models was not entirely the same. Among them, the model using the NIR-depth image and Deformable DETR achieved the best performance, with an average precision (AP) of 99.7% (IoU = 0.5) and a recall of 99.0% (IoU = 0.5). While the IoU threshold increased, we found the following: The model with the NIR image achieved the best performance among models with single-source images, with an AP of 74.4% (IoU = 0.5:0.95) in Deformable DETR. The performance with dual-source images was higher than that with single-source images. The model with the TIR-NIR or NIR-depth image outperformed the model with the TIR-depth image, achieving an AP of 76.3% (IoU = 0.5:0.95) and 75.9% (IoU = 0.5:0.95) in Deformable DETR, respectively. The model with the multi-source image also achieved higher performance than that with single-source images. However, there was no significant improvement compared to the model with the TIR-NIR or NIR-depth image, and the AP of the model with multi-source image was 76.7% (IoU = 0.5:0.95) in Deformable DETR. By analyzing the detection performance with different source images, this study provided a reference for selecting and using multi-source images for detecting dead laying hens on commercial farms.

PurposeFew studies have evaluated hyponatremia management in children with bacterial meningitis (BM). Thus, we aimed to describe variations in clinical practice, the effectiveness of sodium management, and adverse outcomes in children with BM and hyponatremia.MethodsThis retrospective cross-sectional study conducted at a tertiary institution analyzed participants' demographic, clinical, and sodium-altering treatment data. The sodium trigger for treatment was defined as pretreatment sodium level, with response and overcorrection defined as increments of ≥5 and >10 mmol/L after 24 h, respectively.ResultsThis study enrolled 364 children with BM (age:

BackgroundDespite the effectiveness of chemotherapy and targeted therapy for colorectal cancer, drug resistance drives therapy failure and tumor relapse. Increasing evidence has suggested that cancer cells can enter a reversible drug-tolerant persister state to survive chemotherapy or targeted agents. However, the traits and treatable vulnerabilities of anti-colorectal cancer drug-tolerant persister cells is not yet known.MethodsIn this study, we established 5-fluorouracil and AZ628-tolerant persister cell models in two colorectal cancer cell lines, namely HCT116 and SW620, and revealed the characteristics of colorectal cancer persister cells by cell viability assay and flow cytometry. We investigated the efficacy and mechanism of ferroptosis inducers RSL3 and FIN56 on persister cells, which are glutathione peroxidase 4 inhibitors. In the xenograft mouse model, we further evaluated the inhibitory effect of RSL3 on tumor regrowth.ResultsColorectal cancer persister cells, which were enriched in the residual cancer cell population, exhibited reduced drug sensitivity, were largely quiescent and expressed high levels of stem cell-related genes and mesenchymal markers but not epithelial markers. The persister cells were more sensitive and underwent ferroptosis induced by glutathione peroxidase 4 inhibitors. Mechanistically, glutathione peroxidase 4 and ferrous iron, which are pivotal ferroptosis regulators, were upregulated in residual cells or tumors, and were hence potential therapeutic targets of persister cells. In the xenograft model, we confirmed that inhibition of glutathione peroxidase 4 restrained tumor regrowth after discontinuation of anti-cancer drug treatment. Moreover, biopsies obtained from patients with colorectal cancer undergoing neoadjuvant chemoradiotherapy revealed upregulated glutathione peroxidase 4 and ferritin heavy chain 1. High glutathione peroxidase 4 expression correlates with a worse prognosis in colorectal cancer patients.ConclusionsOur work reveals that the upregulated glutathione peroxidase 4 and ferrous iron in anti-colorectal cancer drug-tolerant persister cells were potential therapeutic targets. Glutathione peroxidase 4 inhibition combined with chemotherapy or targeted therapy may be a promising therapy for colorectal cancer.

Abstract Background ATP1A2 gene mutation has been indicated to cause alternating hemiplegia of childhood (AHC); however, limited evidence supports this relationship so far. Case presentation We reported two Chinese patients with de novo ATP1A2 variants (c.970G>A and c.889G>A). Both patients presented with episodes of alternating hemiplegia, seizures and mild developmental delay. Brain magnetic resonance imaging revealed abnormal signals in both patients. Conclusions The new genetic evidence we reported here strengthened the gene–disease relationship, and the gene curation level between ATP1A2 and AHC became “Moderate” following the ClinGen Standard Operation Procedure. Consequently, the two variants can be reclassified as likely pathogenic.

Abstract Intestinal epithelium serves as the first barrier against the infections and injuries that mediate colonic inflammation. Colorectal cancer is often accompanied with chronic inflammation. Differed from its well-known oncogenic role in many malignancies, we present here that Golgi membrane protein 1 (GOLM1, also referred to as GP73) suppresses colorectal tumorigenesis via maintenance of intestinal epithelial barrier. GOLM1 deficiency in mice conferred susceptibility to mucosal inflammation and colitis-induced epithelial damage, which consequently promoted colon cancer. Mechanistically, depletion of GOLM1 in intestinal epithelial cells (IECs) led to aberrant Notch activation that interfered with IEC differentiation, maturation, and lineage commitment in mice. Pharmacological inhibition of Notch pathway alleviated epithelial lesions and restrained pro-tumorigenic inflammation in GOLM1-deficient mice. Therefore, GOLM1 maintains IEC homeostasis and protects against colitis and colon tumorigenesis by modulating the equilibrium of Notch signaling pathway.

Lily Fusarium wilt disease caused by Fusarium spp. spreads rapidly and is highly destructive, leading to a severe reduction in yield. In this study, lily (Lilium brownii var. viridulum) bulbs were irrigated after planting with suspensions of two Bacillus strains that effectively control lily Fusarium wilt disease to assess their effects on the rhizosphere soil properties and microbial community. A high-throughput sequencing of microorganisms in the rhizosphere soil was performed and the soil physicochemical properties were measured. The FunGuild and Tax4Fun tools were used for a functional profile prediction. The results showed that Bacillus amyloliquefaciens BF1 and B. subtilis Y37 controlled lily Fusarium wilt disease with control efficacies of 58.74% and 68.93%, respectively, and effectively colonized the rhizosphere soil. BF1 and Y37 increased the bacterial diversity and richness of the rhizosphere soil and improved the physicochemical properties of the soil, thereby favoring the proliferation of beneficial microbes. The relative abundance of beneficial bacteria was increased and that of pathogenic bacteria was decreased. Bacillus abundance in the rhizosphere was positively correlated with most soil physicochemical properties, whereas Fusarium abundance was negatively correlated with most physicochemical properties. Functional prediction revealed that irrigation with BF1 and Y37 significantly upregulated glycolysis/gluconeogenesis among metabolism and absorption pathways. This study provides insights into the mechanism by which two Bacillus strains with antifungal activity, BF1 and Y37, antagonize plant pathogenic fungi and lays the foundation for their effective application as biocontrol agents.

Automated body weight (BW) estimation is an important indicator to reflect the automation level of breeding, which can effectively reduce the damage to animals in the breeding process. In order to manage meat rabbits accurately, reduce the frequency of manual intervention, and improve the intelligent of meat rabbit breeding, this study constructed a meat rabbit weight estimation system to replace manual weighing. The system consists of a meat rabbit image acquisition robot and a weight estimation model. The robot stops at each cage in turn and takes a top view of the rabbit through an RGB camera. The images from the robot are automatically processed in the weight estimation model, which consists of the meat rabbit segmentation network based on improved Mask RCNN and the BW fitting network. Attention mechanism, PointRend algorithm, and improved activation function are proposed to improve the performance of Mask RCNN. Six morphological parameters (relative projected area, contour perimeter, body length, body width, skeleton length, and curvature) are extracted from the obtained mask, and are sent into the BW fitting network based on SVR-SSA-BPNN. The experiment shows that the system achieves a 4.3% relative error and 172.7 g average absolute error in BW estimation for 441 rabbits, while the meat rabbit segmentation network achieves a 99.1% mean average precision (mAP) and a 98.7% mean pixel accuracy (MPA). The system provides technical support for automatic BW estimation of meat rabbits in commercial breeding, which is helpful to promote precision breeding.

BackgroundsUsing the self-reported questionnaire to assess the levels of physical activity (PA) and sedentary behavior (SB) has been a widely recognized method in public health and epidemiology research fields. The selected items of the Health Behavior in School-aged (HBSC) Survey Questionnaire have been used globally for measurements and assessments in PA and SB of children and adolescents. However, there are no comprehensive and critical reviews to assess the quality of studies on reliability and validity of selected items for PA and SB measurement and assessment derived from the HBSC. Thus, this review aimed to critically assess the quality of those studies and summary evidence for future recommendations.MethodsA systematic review protocol was used to search potentially eligible studies on assessing reliability and validity of PA and SB measures of the HBSC questionnaire. electronically academic databases were used. The information on the reliability and validity of the PA and SB measures were extracted and evaluated with well-recognized criteria or assessment tools.ResultsAfter a literature search, six studies were included in this review. The reliability of PA measures of the HBSC questionnaire showed a moderate agreement while the reliability of SB measures showed a great variation across the different items in the different subgroups. The validity of the PA measures had acceptable performance, whereas no studies assess the validity of the SB measures. The included studies all had quality weaknesses on reliability or validity analysis.ConclusionsThe PA and SB measures of the HBSC questionnaires were reliable in assessing PA and SB among adolescents. However, a little evidence showed that PA measures are partially valid in assessing PA, but no evidence confirmed the validity of SB measures. The included studies all had methodological weaknesses in examining the reliability and validity of the PA and SB measures, which should be addressed in the future. Further studies are encouraged to use a more standardized study design to examine the reliability and validity of the PA and SB measures in more young populations.

Single tracks of Inconel 718 were manufactured by selective laser melting (SLM) under the same volumetric energy density (VED), but via various scanning speed and laser power, with the aim of discerning the influence of the melting mode of molten pools on their solidification behavior, microstructure and nano-hardness. For this purpose, the geometric appearance of each Inconel 718 single track was firstly investigated. The results indicate that the molten pool geometries are significantly different despite melting under the same VED condition; the typical melting modes of molten pools, including the keyhole and conduction modes, can be obtained. The solidified microstructures of both modes evolve from cellular at the bottom to cellular dendrites at the top; but the dendrites are more developed under the keyhole mode. In addition, the grains of both modes follow the epitaxial columnar crystal growth pattern along the boundary of molten pool. The preferential growth direction of grains under the conduction mode is closer to the direction, but the grains orientation of the keyhole mode tends to be and direction. Moreover, in comparison with the conduction mode, the average nano-hardness for different regions of molten pools corresponding to the keyhole mode is slightly higher.

Abstract Background Restenosis remains a challenge in the treatment of atherosclerosis due to damage to the endothelial layer and induced proliferation of smooth muscle cells. A novel radiofrequency (RF) heating strategy was proposed to selectively ablate atherosclerosis plaque and to thermally inhibit the proliferation of smooth muscle cells while keeping the endothelial cells intact. Methods To realize the proposed strategy, a new radiofrequency balloon catheter, consisting of three ports, a three-channel tube, a balloon and an electrode patch, was designed. To evaluate the feasibility of this new design, a phantom experiment with thermocouples measuring temperatures with different voltages applied to the electrodes was conducted. A numerical model was established to obtain the 3D temperature distribution. The heating ability was also evaluated in ex vivo diseased artery samples. Results The experimental results showed that the highest temperature could be achieved in a distance from the surface of the balloon as designed. The temperature differences between the highest temperature at 0.78 mm and those of the surface reached 9.87 °C, 12.55 °C and 16.00 °C under applied 15 V, 17.5 V and 20 V heating, respectively. In the circumferential direction, the heating region (above 50 °C) spread from the middle of the two electrodes. The numerical results showed that the cooling effect counteracted the electrical energy deposition in the region close to the electrodes. The thermal lesion could be directed to cover the diseased media away from the catheter surface. The ex vivo heating experiment also confirmed the selective heating ability of the device. The temperature at the targeted site quickly reached the set value. The temperature of the external surface was higher than the inner wall surface temperature of the diseased artery lumen. Conclusion Both the experimental and numerical results demonstrated the feasibility of the newly designed RF balloon catheter. The proposed RF microelectrodes heating together with the cooling water convection can realize the desired heating in the deeper site of the blood vessel wall while sparing the thin layer of the endothelium.