Deep Learning Model for Predicting Proliferative Hepatocellular Carcinoma Using Dynamic Contrast-Enhanced MRI: Implications for Early Recurrence Prediction Following Radical Resection.

RATIONALE AND OBJECTIVES: The proliferative nature of hepatocellular carcinoma (HCC) is closely related to early recurrence following radical resection. This study develops and validates a deep learning (DL) prediction model to distinguish between proliferative and non-proliferative HCCs using dynamic contrast-enhanced MRI (DCE-MRI), aiming to refine preoperative assessments and optimize treatment strategies by assessing early recurrence risk. MATERIALS AND METHODS: In this retrospective study, 355 HCC patients from two Chinese medical centers (April 2018-February 2023) who underwent radical resection were included. Patient data were collected from medical records, imaging databases, and pathology reports. The cohort was divided into a training set (n = 251), an internal test set (n = 62), and external test sets (n = 42). A DL model was developed using DCE-MRI images of primary tumors. Clinical and radiological models were generated from their respective features, and fusion strategies were employed for combined model development. The discriminative abilities of the clinical, radiological, DL, and combined models were extensively analyzed. The performances of these models were evaluated against pathological diagnoses, with independent and fusion DL-based models validated for clinical utility in predicting early recurrence. RESULTS: The DL model, using DCE-MRI, outperformed clinical and radiological feature-based models in predicting proliferative HCC. The area under the curve (AUC) for the DL model was 0.98, 0.89, and 0.83 in the training, internal validation, and external validation sets, respectively. The AUCs for the combined DL and clinical feature models were 0.99, 0.86, and 0.83 in these sets, while the AUCs for the combined DL, clinical, and radiological model were 0.99, 0.87, and 0.8, respectively. Among models predicting early recurrence, the DL plus clinical features model showed superior performance. CONCLUSION: The DL-based DCE-MRI model demonstrated robust performance in predicting proliferative HCC and stratifying patient risk for early postoperative recurrence. As a non-invasive tool, it shows promise in enhancing decision-making for individualized HCC management strategies.

The responses of CO2 emission to nitrogen application and earthworm addition in the soybean cropland.

The effects of nitrogen application or earthworms on soil respiration in the Huang-Huai-Hai Plain of China have received increasing attention. However, the response of soil carbon dioxide (CO2) emission to nitrogen application and earthworm addition is still unclear. A field experiment with nitrogen application frequency and earthworm addition was conducted in the Huang-Huai-Hai Plain. Results showed nitrogen application frequency had a significant effect on soil respiration, but neither earthworms nor their interaction with nitrogen application frequency were significant. Low-frequency nitrogen application (NL) significantly increased soil respiration by 25%, while high-frequency nitrogen application (NH), earthworm addition (E), earthworm and high-frequency nitrogen application (E*NH), and earthworm and low-frequency nitrogen application (E*NL) also increased soil respiration by 21%, 21%, 12%, and 11%, respectively. The main reason for the rise in soil respiration was alterations in the bacterial richness and keystone taxa (Myxococcales). The NH resulted in higher soil nitrogen levels compared to NL, but NL had the highest bacterial richness. The abundance of Corynebacteriales and Gammaproteobacteria were positively connected with the CO2 emissions, while Myxococcales, Thermoleophilia, and Verrucomicrobia were negatively correlated. Our findings indicate the ecological importance of bacterial communities in regulating the carbon cycle in the Huang-Huai-Hai Plain.

Seasonal patterns of nonstructural carbohydrate storage and mobilization in two tree species with distinct life-history traits.

Nonstructural carbohydrates (NSC) are essential for tree growth and adaptation, yet our understanding of the seasonal storage and mobilization dynamics of whole-tree NSC is still limited, especially when tree functional types are involved. Here, Quercus acutissima Carruth. and Pinus massoniana Lamb. with distinct life-history traits (i.e., a deciduous broadleaf species vs. an evergreen coniferous species) were studied to assess the size and seasonal fluctuations of organ and whole-tree NSC pools with a focus on comparing differences in carbon resource mobilization patterns between the two species. We sampled the organs (leaf, branch, stem, and root) of the target trees repeatedly over four seasons of the year. Then, NSC concentrations in each organ were paired with biomass estimates from the allometric model to generate whole-tree NSC pools. The seasonal dynamics of the whole-tree NSC of Q. acutissima and P. massoniana reached the peak in autumn and summer, respectively. The starch pools of the two species were supplemented in the growing season while the soluble sugar pools were the largest in the dormant season. Seasonal dynamics of organ-level NSC concentrations and pools were affected by organ type and tree species, with above-ground organs generally increasing during the growing season and P. massoniana roots decreasing during the growing season. In addition, the whole-tree NSC pools of P. massoniana were larger but Q. acutissima showed larger seasonal fluctuations, indicating that larger storage was not associated with more pronounced seasonal fluctuations. We also found that the branch and root were the most dynamic organs of Q. acutissima and P. massoniana, respectively, and were the major suppliers of NSC to support tree growth activities. These results provide fundamental insights into the dynamics and mobilization patterns of NSC at the whole-tree level, and have important implications for investigating environmental adaptions of different tree functional types.

Role of NADPH Oxidase 4 on Dry Eye Syndrome in Mice.

Objective: This study aims to investigate the effect of NADPH oxidase 4 (NOX4)-mediated inflammation on concanavalin A (ConA)-induced dry eye syndrome (DES) in mice. Methods: Thirty-six mice were randomly divided into Control, Model, no-load Control, and NOX4 interference group. Adenovirus was injected (10 µL) into the lacrimal glands of both eyes of mice in no-load Control group and NOX4 interference group. Four days after adenovirus injection, the Control group was injected with phosphate-buffered saline, and the other groups were injected with ConA (200 µg) in the lacrimal glands of mice to establish DES models. The tear secretion rate was estimated by phenol red thread test. Lissamine green eye staining was used to evaluate conjunctival damage. The corneal surface was observed by hematoxylin-eosin (HE) staining and scanning electron microscopy (SEM). The morphology and quantity of conjunctival epithelial cells and goblet cells were observed by Periodic acid-Schiff staining. The expression of NOX4, NOD-like receptor thermal protein domain-associated protein 3 (NLRP3), interleukin-1ß (IL-1ß), and mucin 5 subtype AC (MUC5AC) was detected by immunohistochemistry. Results: Compared with the Control group, the Model group showed a significant decrease in tear secretion and an upregulation in microscopic image score. The HE staining and SEM showed corneal and conjunctiva damage in the Model group. The protein expression of NOX4, NLRP3, and IL-1ß was upregulated, but MUC5AC was downregulated in the Model group. After interfering with NOX4, all these indicators were reversed. Conclusion: The pathological process of concanavalin A-induced DES appears to be related to NOX4.

Performance of Corvis ST Parameters Including Updated Stress-Strain Index in Differentiating Between Normal, Forme-Fruste, Subclinical, and Clinical Keratoconic Eyes.

PURPOSE: This study seeks to evaluate the ability of the updated stress strain index (SSIv2) and other Corvis ST biomechanical parameters in distinguishing between keratoconus at different disease stages and normal eyes. DESIGN: Diagnostic accuracy analysis to distinguish disease stages. METHODS: 1084 eyes were included and divided into groups of normal (199 eyes), forme fruste keratoconus (FFKC, 194 eyes), subclinical keratoconus (SKC, 113 eyes), mild clinical keratoconus (CKC-Ⅰ, 175 eyes), moderate clinical keratoconus (CKC-Ⅱ, 204 eyes), and severe clinical keratoconus (CKC-Ⅲ, 199 eyes). Each eye was subjected to a Corvis ST examination to determine the central corneal thickness (CCT), biomechanically corrected intraocular pressure (bIOP), SSIv2 (updated stress-strain index), and other 8 Corvis parameters including the stress-strain index (SSIv1), stiffness parameter at first applanation (SP-A1), first applanation time (A1T), Ambrósio relational thickness to the horizontal profile (ARTh), integrated inverse radius (IIR), maximum deformation amplitude (DAM), ratio between deformation amplitude at the apex and at 2 mm nasal and temporal (DARatio2), and Corvis biomechanical index (CBI). The sensitivity and specificity of these parameters in diagnosing keratoconus were analyzed through receiver operating characteristic curves. RESULTS: Before and after correction for CCT and bIOP, SSIv2 and ARTh were significantly higher and IIR and CBI were significantly lower in the normal group than in the FFKC group, SKC group and the 3 CKC groups (all P < .05). There were also significant correlations between the values of SSIv2, ARTh, IIR, CBI, and the CKC severity (all P < .05). AUC of SSIv2 was significantly higher than all other Corvis parameters in distinguishing normal eyes from FFKC, followed by IIR, ARTh and CBI. CONCLUSION: Corvis ST's updated stress-strain index, SSIv2, demonstrated superior performance in differentiating between normal and keratoconic corneas, and between corneas with different keratoconus stages. Similar, but less pronounced, performance was demonstrated by the IIR, ARTh and CBI.

Case Report: CD19 CAR T-cell therapy following autologous stem cell transplantation: a successful treatment for R/R CD20-negative transformed follicular lymphoma with TP53 mutation.

Background: Follicular lymphoma (FL), a common indolent B-cell lymphoma, has the potential to transform into an aggressive lymphoma, such as diffuse large B-cell lymphoma (DLBCL). The outcome of patients with transformed follicular lymphoma (tFL) is poor, especially in patients with transformed lymphoma after chemotherapy and patients with progression within 24 months (POD24). Chimeric antigen receptor (CAR) T-cell therapy combined with autologous stem cell transplantation (ASCT) has promising antitumor efficacy. Case presentation: Here, we described a 39-year-old male patient who was initially diagnosed with FL that transformed into DLBCL with POD24, CD20 negativity, TP53 mutation, and a bulky mass after 3 lines of therapy, all of which were adverse prognostic factors. We applied a combination approach: CD19 CAR T-cell infusion following ASCT. Ibrutinib was administered continuously to enhance efficacy, DHAP was administered as a salvage chemotherapy, and ICE was administered as a bridging regimen. The patient underwent BEAM conditioning on days -7~ -1, a total of 3.8 × 106/kg CD34+ stem cells were infused on days 01~02, and a total of 108 CAR T cells (relmacabtagene autoleucel, relma-cel, JWCAR029) were infused on day 03. The patient experienced grade 2 cytokine release syndrome (CRS), manifesting as fever and hypotension according to institutional standards. There was no immune effector cell-associated neurotoxicity syndrome (ICANS) after CAR T-cell infusion. Finally, the patient achieved CMR at +1 month, which has been maintained without any other adverse effects. Conclusion: This case highlights the amazing efficacy of CD19 CAR T-cell therapy following ASCT for R/R tFL, thus providing new insight on therapeutic strategies for the future.

CAENet: Contrast adaptively enhanced network for medical image segmentation based on a differentiable pooling function.

Pixel differences between classes with low contrast in medical image semantic segmentation tasks often lead to confusion in category classification, posing a typical challenge for recognition of small targets. To address this challenge, we propose a Contrastive Adaptive Augmented Semantic Segmentation Network with a differentiable pooling function. Firstly, an Adaptive Contrast Augmentation module is constructed to automatically extract local high-frequency information, thereby enhancing image details and accentuating the differences between classes. Subsequently, the Frequency-Efficient Channel Attention mechanism is designed to select useful features in the encoding phase, where multifrequency information is employed to extract channel features. One-dimensional convolutional cross-channel interactions are adopted to reduce model complexity. Finally, a differentiable approximation of max pooling is introduced in order to replace standard max pooling, strengthening the connectivity between neurons and reducing information loss caused by downsampling. We evaluated the effectiveness of our proposed method through several ablation experiments and comparison experiments under homogeneous conditions. The experimental results demonstrate that our method competes favorably with other state-of-the-art networks on five medical image datasets, including four public medical image datasets and one clinical image dataset. It can be effectively applied to medical image segmentation.

Antipyretic and Anti-Inflammatory Effects of Rectal Administration of Reduning Injection in Feverish Rats Induced by Lipopolysaccharide.

This study aimed to explore the antipyretic and anti-inflammatory effects of rectal administration of Reduning injection in feverish rats induced by lipopolysaccharide (LPS), and observe the temperature changes and inflammatory indexes. The selected rats were randomly divided into 6 groups, with 10 rats in each group, named as normal empty group, model group, intravenous group (2 mL/kg), low-dose enema group (1 mL/kg), middle-dose enema group (2 mL/kg), and high-dose enema group (4 mL/kg). The hourly temperature variations in rats injected with LPS in the abdomen were recorded. Five hours later, blood samples from the abdominal aorta were collected to monitor immunoglobulin M (IgM), immunoglobulin A (IgA), interleukin (IL)-6, and tumor necrosis factor (TNF)-α. At 5 hours, the fever peak induced by LPS appeared, and obvious antipyretic effects were observed; the effect was optimal in the medium dose enema group at 4 hours (p < 0.05); the IgM value in the enema groups, the intravenous group, and normal empty group was significantly lower than that in the model group; the IgA value in each group was higher than that in the model group, but there was no statistical significance (p > 0.05); values of IL-6 and TNF-α in each group were lower than those in the model group, and the difference was statistically significant except for the high-dose enema group (p > 0.05). Low-dose and medium-dose rectal administration of Reduning injection have inhibitory effects on IL-6, TNF-α, and IgM in feverish rats induced by LPS, but there is no obvious difference compared to intravenous administration and it could achieve an anti-inflammatory effect. There is a possibility of enhancing IgA immunity with rectal administration, but there is no obvious difference compared to intravenous administration, and rectal administration has no significant effect on mucosal immunity.

SHCBP1 contributes to the proliferation and self­renewal of cervical cancer cells and activation of the NF­κB signaling pathway through EIF5A.

Cervical cancer (CC) is the most common human papillomavirus-related disease. Continuous activation of the NF-κB signaling pathway has been observed in CC. SHC binding and spindle associated 1 (SHCBP1) contributes to tumorigenesis and activation of the NF-κB pathway in multiple cancer types, while its function in CC remains unclear. In the present study, three Gene Expression Omnibus datasets were used to identify differentially expressed genes (DEGs) in CC. Loss- and gain-of-function experiments were performed using stable SHCBP1-silenced and SHCBP1-overexpressing CC cells. To further explore the molecular mechanism of SHCBP1 in CC, small interfering RNA targeting eukaryotic translation initiation factor 5A (EIF5A) was transfected into stable SHCBP1-overexpressing CC cells. The results demonstrated that SHCBP1 was an upregulated DEG in CC tissues compared with healthy control cervical tissues. Functional experiments revealed the pro-proliferative and pro-stemness role of SHCBP1 in CC cells (CaSki and SiHa cells), in vitro. Furthermore, the NF-κB signaling pathway in CC cells was activated by SHCBP1. Increases in cell proliferation, stemness and activation of NF-κB, induced by SHCBP1 overexpression in CC cells, were reversed by EIF5A knockdown. Taken together, the results indicated that SHCBP1 serves an important role in regulation of CC cell proliferation, self-renewal and activation of NF-κB via EIF5A. The present study demonstrated a potential molecular mechanism underlying the progression of CC.

A Light-Programmed Rewritable Lattice-Mediated Multistate Memory for High-Density Data Storage.

Mainstream non-volatile memory (NVM) devices based on floating gate structures or phase-change/ferroelectric materials face inherent limitations that compromise their suitability for long-term data storage. To address this challenge, a novel memory device based on light-programmed lattice engineering of thin rhenium disulfide (ReS2 ) flakes is proposed. By inducing sulfur vacancies in the ReS2 channel through light illumination, the device's electrical conductivity is modified accordingly and multiple conductance states for data storage therefore are generated. The device exhibits more than 128 distinct states with linearly increasing conductance, corresponding to a sevenfold increase in storage density. Through further optimization to achieve atomic-level precision in defect creation, it is possible to achieve even higher storage densities. These states are extremely stable in vacuum or inert ambient showing long retention of >10 years, while they can be erased upon exposure to the air. The ReS2 memory device can maintain its stability over multiple program-erase operation cycles and shows superior wavelength discrimination capability for incident light in the range of 405-785 nm. This device represents a significant contribution to NVM technology by offering the ability to store information in multistate memory and enabling filter-free color image recorder applications.

SIAP: an intelligent algorithm for multiple prescription pattern recognition based on weighted similarity distances.

BACKGROUND: Clinical practices have demonstrated that disease treatment can be very complex. Patients with chronic diseases often suffer from more than one disease. Complex diseases are often treated with a variety of drugs, including both primary and auxiliary treatments. This complexity and multidimensionality increase the difficulty of extracting knowledge from clinical data. METHODS: In this study, we proposed a subgroup identification algorithm for complex prescriptions (SIAP). We applied the SIAP algorithm to identify the importance level of each drug in complex prescriptions. The algorithm quickly classified and determined valid prescription combinations for patients. The algorithm was validated through classification matching of classical prescriptions in traditional Chinese medicine. We collected 376 formulas and their compositions from a formulary to construct a database of standard prescriptions. We also collected 1438 herbal prescriptions from clinical data for automated prescription identification. The prescriptions were divided into training and test sets. Finally, the parameters of the two sub-algorithms of SIAP and SIAP-All, as well as those of the combination algorithm SIAP + All, were optimized on the training set. A comparison analysis was performed against the baseline intersection set rate (ISR) algorithm. The algorithm for this study was implemented with Python 3.6. RESULTS: The SIAP-All and SIAP + All algorithms outperformed the benchmark ISR algorithm in terms of accuracy, recall, and F1 value. The F1 values were 0.7568 for SIAP-All and 0.7799 for SIAP + All, showing improvements of 8.73% and 11.04% over the existing ISR algorithm, respectively. CONCLUSION: We developed an algorithm, SIAP, to automatically match sub-prescriptions of complex drugs with corresponding standard or classic prescriptions. The matching algorithm weights the drugs in the prescription according to their importance level. The results of this study can help to classify and analyse the drug compositions of complex prescriptions.

Mapping the core concepts of physiology across Australian university curricula.

Core concepts in physiology, designed by physiology educators to promote improved learning and teaching, have existed for over a decade. This study aimed to investigate the extent to which a set of 15 core concepts of physiology (developed by Michael and McFarland, U.S.-based educators) are reflected in the learning outcomes (LOs) of units (subjects) comprising physiology curricula in Australian universities. From publicly accessible online information, we identified 17 Australian universities that offered a physiology major for undergraduate degree students and downloaded 788 LOs from the 166 units that comprised the majors. Each LO was blindly mapped against the 15 core concepts by 8 physiology educators from 3 Australian universities. Additionally, text-matching software was employed to match keywords and phrases (identified as descriptors of the 15 core concepts) against the LOs. The frequency of individual words and two-word phrases for each core concept was calculated and ranked. There was variability in rating LOs for the same university among academic mappers; nevertheless, many of the 15 core concepts did not appear to be adequately covered in the LOs. Two core concepts most matched manually were in the top three most mapped by the software. These were, from most common, structure/function and interdependence. Our findings suggest a lack of alignment of LOs with the core concepts across Australian physiology curricula. This highlights the need for Australia-wide agreement on a set of core concepts in physiology as the first step in collaboratively improving assessment and learning and teaching practice in physiology.NEW & NOTEWORTHY This is the first time an existing set of core concepts for physiology, developed by Michael and McFarland (U.S.-based educators), have been mapped against unit (subject) learning outcomes across physiology curricula in Australian universities to gauge uptake and the need for agreement on a set of core concepts in the Australian higher education context.

Effects of Variation in Tamarix chinensis Plantations on Soil Microbial Community Composition in the Middle Yellow River Floodplain.

Floodplains have important ecological and hydrological functions in terrestrial ecosystems, experience severe soil erosion, and are vulnerable to losing soil fertility. Tamarix chinensis Lour. plantation is the main vegetation restoration measure for maintaining soil quality in floodplains. Soil microorganisms are essential for driving biogeochemical cycling processes. However, the effects of sampling location and shrub patch size on soil microbial community composition remain unclear. In this study, we characterized changes in microbial structure, as well as the factors driving them, in inside- and outside-canopy soils of three patch sizes (small, medium, large) of T. chinensis plants in the middle Yellow River floodplain. Compared with the outside-canopy soils, inside-canopy had higher microbial phospholipid fatty acids (PLFAs), including fungi, bacteria, Gram-positive bacteria (GP), Gram-negative bacteria (GN), and arbuscular mycorrhizal fungi. The ratio of fungi to bacteria and GP to GN gradually decreased as shrub patch size increased. Differences between inside-canopy and outside-canopy soils in soil nutrients (organic matter, total nitrogen, and available phosphorus) and soil salt content increased by 59.73%, 40.75%, 34.41%, and 110.08% from small to large shrub patch size. Changes in microbial community composition were mainly driven by variation in soil organic matter, which accounted for 61.90% of the variation in inside-canopy soils. Resource islands could alter microbial community structure, and this effect was stronger when shrub patch size was large. The results indicated that T. chinensis plantations enhanced the soil nutrient contents (organic matter, total nitrogen, and available phosphorus) and elevated soil microbial biomass and changed microbial community composition; T. chinensis plantations might thus provide a suitable approach for restoring degraded floodplain ecosystems.

Distinct response patterns of plants and soil microorganisms to agronomic practices and seasonal variation in a floodplain ecosystem.

Introduction: Climate change and anthropogenic activities are the greatest threats to floodplain ecosystems. A growing body of literature shows that floodplain ecosystems have experienced increased chemical fertilizer and pesticide loads, which will disturb the above and belowground ecosystems. However, we lack knowledge regarding the effects of such human activities on the vegetation and soil microbiomes in these ecosystems. Methods: In the present study, plant functional traits and Illumina Mi-Seq sequencing were to assess the impact of nitrogen fertilizer and glyphosate addition on the structure and function of the vegetation and soil microbiomes (bacteria, fungi, and protists) in a floodplain ecosystem, and to assess the influence of seasonal variation. Results: We identified distinct response mechanisms of plant and microbial communities to the addition of nitrogen fertilizer and glyphosate, and seasonal variation. Nitrogen fertilizer and glyphosate significantly affected plant diversity, aboveground and underground biomass, and C and N content and significantly changed the leaf area and plant stature of dominant plants. However, the addition of nitrogen fertilizer and glyphosate did not significantly affect the diversity and structure of bacterial, fungal, and protist communities. The application of nitrogen fertilizer could improve the negative effects of glyphosate on the functional traits of plant communities. The seasonal variation of floodplain has significantly changed the soil's physical, chemical, and biological properties. Our results showed that compared with that in summer, the soil ecosystem multifunctionality of the floodplain ecosystem in autumn was significantly lower. Seasonal variation had a significant effect on plant diversity and functional traits. Moreover, seasonal variation significantly affected the community compositions, diversity, and structure of bacteria, fungi, and protists. Seasonal variation had a stronger impact on fungal community assembly than on that of bacteria and protists. In summer, the assembly of the fungal community was dominated by a deterministic process, while in autumn, it is dominated by a stochastic process. In addition, the negative association among bacteria, fungi, and protists has been strengthened in autumn and formed a more robust network to cope with external changes. Discussion: These results extended our understanding of the ecological patterns of soil microbiomes in floodplain ecosystems and provided support for enhancing the ecological barrier function and the service potential of floodplain ecosystems.

Early detection of depression using a conversational AI bot: A non-clinical trial.

BACKGROUND: Artificial intelligence (AI) has gained momentum in behavioural health interventions in recent years. However, a limited number of studies use or apply such methodologies in the early detection of depression. A large population needing psychological-intervention is left unidentified due to barriers such as cost, location, stigma and a global shortage of health workers. Therefore, it is essential to develop a mass screening integrative approach that can identify people with depression at its early stage to avoid a potential crisis. OBJECTIVES: This study aims to understand the feasibility and efficacy of using AI-enabled chatbots in the early detection of depression. METHODS: We use Dialogflow as a conversation interface to build a Depression Analysisn (DEPRA) chatbot. A structured and authoritative early detection depression interview guide, which contains 27 questions combining the structured interview guide for the Hamilton Depression Scale (SIGH-D) and the inventory of depressive symptomatology (IDS-C), underpins the design of the conversation flow. To attain better accuracy and a wide variety of responses, we train Dialogflow with the utterances collected from a focus group of 10 people. The occupation of the focus group members included academics and HDR candidates who are conscious, vigilant and have a clear understanding of the questions. In addition, DEPRA is integrated with a social media platform to provide practical access to all the participants. For the non-clinical trial, we recruited 50 participants aged between 18 and 80 from across Australia. To evaluate the practicability and performance of DEPRA, we also asked participants to submit a user satisfaction survey at the end of the conversation. RESULTS: A sample of 50 participants, with an average age of 34.7 years, completed this non-clinical trial. More than half of the participants (54%) are male and the major ethnicities are Asian (63%), Middle Eastern (25%), and others 12%. The first group comprises professional academic staff and HDR candidates, the second and third groups comprise relatives, friends, and volunteers who were recruited via social media promotions. DEPRA uses two scientific scoring systems, QIDS-SR and IDS-SR to verify the results of early depression detection. As the results indicate, both scoring systems return a similar outcome with slight variations for different depression levels. According to IDS-SR, 30% of participants were healthy, 14% mild, 22% moderate, 14% severe, and 20% very severe. QIDS-SR suggests 32% were healthy, 18% mild, 10% moderate, 18% severe, and 22% very severe. Furthermore, the overall satisfaction rate of using DEPRA was 79% indicating that the participants had a high rate of user satisfaction and engagement. CONCLUSION: DEPRA shows promises as a feasible option for developing a mass screening integrated approach for early detection of depression. Although the chatbot is not intended to replace the functionality of mental health professionals, it does show promise as a means of assisting with automation and concealed communication with verified scoring systems.

Posterior Segment Air Injection-Assisted Descemet Membrane Endothelial Keratoplasty in Pseudophakic and Vitrectomized Eyes.

PURPOSE: This study aimed to present a novel technique for Descemet membrane endothelial keratoplasty (DMEK) in pseudophakic and vitrectomized eyes. METHODS: The sterile air was injected into the posterior eye segment (anterior vitreous cavity) as a barrier to prevent the fluid of the vitreous cavity flowing into the anterior chamber, levitating the iris-lens diaphragm to flatten the anterior chamber during the surgery. This approach assists in the unfolding of the donor endothelial graft, helping to perform DMEK surgery on patients with a posterior intraocular lens (IOL) and vitrectomy. RESULTS: Four cases presented with corneal endothelial decompensation (pseudophakic bullous keratopathy) with previous IOL implantation and vitrectomy underwent DMEK with this technique. The Descemet endothelial graft unfolding time after air injection was 68.75 ± 8.96 seconds. No graft displacement occurred during the surgery. The uncorrected and corrected distance visual acuities were improved in 3 of 4 patients. The corneas were transparent, and there was no graft detachment observed postoperatively in all 4 patients. CONCLUSIONS: The posterior eye segment air injection can reduce the difficulty of unfolding the DMEK graft in patients after IOL implantation and vitrectomy and the potential intraoperative and postoperative complications, allowing for easy performance of DMEK surgery on pseudophakic and vitrectomized eyes for corneal endothelial dysfunction.

Clipping decreases plant cover, litter mass, and water infiltration rate in soil across six plant community sites in a semiarid grassland.

Water infiltration in the soil is a crucial hydrological function in the land water cycle, especially in the semiarid region where water is relatively scarce. The semiarid grassland in Northern China represents the regional vegetation in the vast area of Eurasian continent and is sensitive to land use change. However, no clear patterns exist regarding the comprehensive examination of water infiltration in relation to clipping across six plant community sites. This study aimed to test the effect of clipping and plant community sites, which were dominated by Agropyron cristatum, Stipa krylovii, Leymus chinensis, Potentilla tanacetifolia, Artemisia frigida, or Lespedeza davurica, on the water infiltration rate in the semiarid grassland. Clipping significantly decreased the water initial, steady, and average infiltration rates by 39.13, 4.36, and 12.46 mm h-1, respectively, across the six plant community sites. Clipping-induced changes in the average infiltration rate positively correlated with the changes in the plant cover (r = 0.60, P < 0.01), litter mass (r = 0.53, P < 0.01), forb functional group ratio (r = 0.46, P = 0.03), and total porosity (r = 0.49, P = 0.02), and negatively with water-holding capacity (r = -0.45, P = 0.03). Further, the water infiltration rate significantly differed among the six plant community sites. The L.davurica site had the highest water initial infiltration rate with a value of 137.63 ± 17.76 mm h-1, while the L. chinensis site had the lowest rate with a value of 74.08 ± 5.26 mm h-1. Principal component analysis showed that the total porosity, litter mass, plant cover, and forb functional group ratio were the main factors affecting water infiltration rates in the control grassland. Overall, our findings suggested that local governments and herders should implement unclipping as a potential sustainable management for improving hydrological function in the semiarid grassland.

A novel NGS-based diagnostic algorithm for classifying multifocal lung adenocarcinomas in pN0M0 patients.

The classification of multifocal lung adenocarcinomas (MLAs), including multiple primary lung adenocarcinomas (MPLAs) and intrapulmonary metastases (IPMs), has great clinical significance in staging and treatment determination. However, the application of molecular approaches in pN0M0 MLA diagnosis has not been well investigated. Here, we performed next-generation sequencing (NGS) analysis in 45 pN0M0 MLA patients (101 lesion pairs) who were initially diagnosed as having MPLA by comprehensive histologic assessment (CHA). Five additional patients with intrathoracic metastases were used as positive controls, while 197 patients with unifocal lung adenocarcinomas (425 random lesion pairs) were used as negative controls. By utilizing a predefined NGS criterion, all IPMs in the positive control group could be accurately classified, whereas 13 lesion pairs (3.1%) in the negative control cohort were misdiagnosed as IPMs. Additionally, 14 IPM lesion pairs were diagnosed in the study group, with at least 7 misdiagnoses. We thus developed a refined algorithm, incorporating both NGS and histologic results, that could correctly diagnose all the known MPLAs and IPMs. In particular, all IPMs identified by the refined algorithm were diagnosed to be IPMs or suspected IPMs by CHA reassessment. The refined algorithm-diagnosed MPLAs patients also had significantly better progression-free survival than the refined algorithm-diagnosed IPMs (p < 0.0001), which is superior to conventional NGS or CHA diagnoses. Overall, we developed an NGS-based algorithm that could accurately distinguish IPMs from MPLAs in MLA patients. Our results demonstrate a promising clinical utility of NGS to complement traditional CHA-based MLA diagnosis and help determine patient staging and treatment.

Determination of biological exposure limit of damage in red blood cells caused by exposure to polycyclic aromatic hydrocarbons using benchmark dose method in general population / 公共卫生与预防医学

Objective To explore the biological exposure limit of blood system damage caused by long-term exposure to polycyclic aromatic hydrocarbons (PAHs) in non-occupational population by using the benchmark dose method, and to provide relevant reference for further improving the assessment of PAHs-induced health damage effects. Methods Adult residents living in downwind direction of a coke-oven plant in Shanxi Province were selected as the research subjects, and the information collected from baseline was used as the control. The metabolites of PAHs in urine were used as exposure biomarker, and the abnormal rate of red blood cell index was used as response biomarker. The relationship between urinary OH-PAHs and the erythrocyte damage rate was analyzed, and the benchmark dose (BMD) and the lower confidence limitation for the benchmark dose (BMDL) were calculated using Bayesian dose-optimizing software. Results The urinary PAH metabolites were mainly naphthalene and fluorene. The detection concentrations of 2-OHFlu and 1-OHPhe in the final year were higher than those in the baseline (P<0.05). With the increase of exposure years, the abnormal rate of red blood cells in the final year was higher than that in the baseline (P<0.05). In addition, the abnormal rate of red blood cells increased with the increase of the concentrations of five metabolites of PAHs in urine, and the chi-square trend test was significant (P<0.05). The benchmark dose (BMD) of OH-PAHs was 0.67 μmol/mol Cr, 0.82 μmol/mol Cr, 1.40 μmol/mol Cr and 0.78 μmol/mol Cr, respectively. The BMD of 2-OHNap in people with barbecue diet habits was 0.23 μmol/mol Cr. The BMD of 2-OHNap in people without barbecue diet habits was 1.44 μmol/mol Cr. Conclusion There is a dose-response relationship between the concentration of PAHs metabolites in urine and the damage of red blood cells. Long-term exposure to PAHs can lead to hematological damage. It is suggested that targeted public health interventions should be formulated to reduce the exposure of the general population to PAHs.

Differential responses of the seed germination of three functional groups to low temperature and darkness in a typical steppe, Northern China.

Seed germination is a key stage in the life history of plants, which has a crucial effect on plant community structure. Climate change has substantially altered the surface soil temperature and light availability, which can affect seed germination. However, whether the seed germination of different functional groups is affected by the interactions of light and temperature remains unclear. Under laboratory conditions, we examined the effects of low temperature and darkness, as well as their interaction, on the seed germination of 16 species belonging to three plant functional groups (annual and biennials, perennial grasses, and perennial forbs) in a typical steppe, Northern China. We found that low temperature had a significant negative effect on seed germination of all species. Low temperature significantly decreased the final germination percentage and germinative force of the three plant functional groups, and the germination duration of perennial grasses. Darkness significantly decreased the germinative force of perennial forbs and total seeds, and the germination duration of perennial grasses. The interactive effects of light and temperature on the seed final germination percentage and germinative force of perennial grass indicated that darkness strengthened the inhibitory effect of low temperature on the seed germination of the grass functional group. Our study indicate that the seed germination of different plant functional groups varied greatly in response to changing environmental conditions. Our results suggest that future climate change could alter the regeneration and species composition of plant communities through changing seed germination.