Exploring the impact of high-altitude de-acclimatization on renal function: The roles of oxidative and endoplasmic reticulum stress in rat models.

BACKGROUND: High-altitude de-acclimatization (HADA) significantly impacts physiological functions when individuals acclimatize to high altitudes return to lower altitudes. This study investigates HADA's effects on renal function and structure in rats, focusing on oxidative and endoplasmic reticulum stress as potential mechanisms of renal injury. OBJECTIVE: To elucidate the pathophysiological mechanisms of renal damage in HADA and evaluate the efficacy of antioxidants Vitamin C (Vit C) and tauroursodeoxycholic acid (TUDCA) in mitigating these effects. METHODS: 88 male Sprague-Dawley rats were randomly divided into a control group, a high-altitude (HA) group, a high-altitude de-acclimatization (HADA) group, and a treatment group. The control group was housed in a sea level environment (500 m), while the HA, HADA, and treatment groups were placed in a simulated high-altitude chamber (5000 m) for 90 days. After this period, the HA group completed the modeling phase; the HADA group was further subdivided into four subgroups, each continuing to be housed in a sea level environment for 3, 7, 14, and 30 days, respectively. The treatment group was split into the Vit C group, the TUDCA group, and two placebo groups, receiving medication for 3 consecutive days, once daily upon return to the sea level. The Vit C group received 100 mg/kg Vit C solution via intravenous injection, the TUDCA group received 250 mg/kg TUDCA solution via intraperitoneal injection, and the placebo groups received an equivalent volume of saline similarly. Serum, urine, and kidney tissues were collected immediately after the modeling phase. Renal function and oxidative stress levels were assessed using biochemical and ELISA methods. Renal histopathology was observed with H&E, Masson's trichrome, PAS, and PASM staining. Transmission electron microscopy was used to examine the ultrastructure of glomeruli and filtration barrier. TUNEL staining assessed cortical apoptosis in the kidneys. Metabolomics was employed for differential metabolite screening and pathway enrichment analysis. RESULTS: Compared to the control and HA groups, the HADA 3-day group (HADA-3D) exhibited elevated renal function indicators, significant pathological damage, observable ultrastructural alterations including endoplasmic reticulum expansion and apoptosis. TUNEL-positive cells significantly increased, indicating heightened oxidative stress levels. Various differential metabolites were enriched in pathways related to oxidative and endoplasmic reticulum stress. Early intervention with Vit C and TUDCA markedly alleviated renal injury in HADA rats, significantly reducing the number of apoptotic cells, mitigating endoplasmic reticulum stress, and substantially lowering oxidative stress levels. CONCLUSION: This study elucidates the pivotal roles of oxidative and endoplasmic reticulum stress in the early-stage renal injury in rats undergoing HADA. Early intervention with the Vit C and TUDCA significantly mitigates renal damage caused by HADA. These findings provide insights into the pathophysiological mechanisms of HADA and suggest potential therapeutic strategies for its future management.

Investigating the nexus of metabolic syndrome, serum uric acid, and dementia risk: a prospective cohort study.

BACKGROUND: The global dementia prevalence is surging, necessitating research into contributing factors. We aimed to investigate the association between metabolic syndrome (MetS), its components, serum uric acid (SUA) levels, and dementia risk. METHODS: Our prospective study comprised 466,788 participants without pre-existing MetS from the UK Biobank. We confirmed dementia diagnoses based on the ICD-10 criteria (F00-03). To evaluate the dementia risk concerning MetS, its components, and SUA levels, we applied Cox proportional hazards models, while adjusting for demographic factors. RESULTS: Over a median follow-up of 12.7 years, we identified 6845 dementia cases. Individuals with MetS had a 25% higher risk of all-cause dementia (hazard ratio [HR] = 1.25, 95% confidence interval [CI] = 1.19-1.31). The risk increased with the number of MetS components including central obesity, dyslipidemia for high-density lipoprotein (HDL) cholesterol, hypertension, hyperglycemia, and dyslipidemia for triglycerides. Particularly for those with all five components (HR = 1.76, 95% CI = 1.51-2.04). Dyslipidemia for HDL cholesterol, hypertension, hyperglycemia, and dyslipidemia for triglycerides were independently associated with elevated dementia risk (p < 0.01). MetS was further linked to an increased risk of all-cause dementia (11%) and vascular dementia (VD, 50%) among individuals with SUA levels exceeding 400 µmol/L (all-cause dementia: HR = 1.11, 95% CI = 1.02-1.21; VD: HR = 1.50, 95% CI = 1.28-1.77). CONCLUSIONS: Our study provides robust evidence supporting the association between MetS, its components, and dementia risk. These findings emphasize the importance of considering MetS and SUA levels in assessing dementia risk, offering valuable insights for prevention and management strategies.

An explainable machine learning-based model to predict intensive care unit admission among patients with community-acquired pneumonia and connective tissue disease.

BACKGROUND: There is no individualized prediction model for intensive care unit (ICU) admission on patients with community-acquired pneumonia (CAP) and connective tissue disease (CTD) so far. In this study, we aimed to establish a machine learning-based model for predicting the need for ICU admission among those patients. METHODS: This was a retrospective study on patients admitted into a University Hospital in China between November 2008 and November 2021. Patients were included if they were diagnosed with CAP and CTD during admission and hospitalization. Data related to demographics, CTD types, comorbidities, vital signs and laboratory results during the first 24 h of hospitalization were collected. The baseline variables were screened to identify potential predictors via three methods, including univariate analysis, least absolute shrinkage and selection operator (Lasso) regression and Boruta algorithm. Nine supervised machine learning algorithms were used to build prediction models. We evaluated the performances of differentiation, calibration, and clinical utility of all models to determine the optimal model. The Shapley Additive Explanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) techniques were performed to interpret the optimal model. RESULTS: The included patients were randomly divided into the training set (1070 patients) and the testing set (459 patients) at a ratio of 70:30. The intersection results of three feature selection approaches yielded 16 predictors. The eXtreme gradient boosting (XGBoost) model achieved the highest area under the receiver operating characteristic curve (AUC) (0.941) and accuracy (0.913) among various models. The calibration curve and decision curve analysis (DCA) both suggested that the XGBoost model outperformed other models. The SHAP summary plots illustrated the top 6 features with the greatest importance, including higher N-terminal pro-B-type natriuretic peptide (NT-proBNP) and C-reactive protein (CRP), lower level of CD4 + T cell, lymphocyte and serum sodium, and positive serum (1,3)-ß-D-glucan test (G test). CONCLUSION: We successfully developed, evaluated and explained a machine learning-based model for predicting ICU admission in patients with CAP and CTD. The XGBoost model could be clinical referenced after external validation and improvement.

Characteristics of patients with recurrent retinoblastoma: a survival analysis.

BACKGROUND: Management guidelines and corresponding survival data for patients with recurrent retinoblastoma (RB) are lacking. This study aimed to summarize the clinical characteristics of patients with recurrent RB and analyze their survival outcomes. METHODS: We retrospectively analyzed 68 patients with recurrent RB who underwent treatment in our institution from January 2016 to December 2020. Patients were grouped according to location of recurrence: intraocular, orbital, and distant metastasis. RESULTS: The male:female ratio was 1.3:1 and the median age at recurrence was 37.5 months (range, 30.3-62.8). The number of patients in the intraocular recurrence, orbital recurrence, and metastasis groups was 13 (19.1%), 23 (33.8%), and 32 (47.1%), respectively. Thirty patients died, 36 were alive at last follow-up, and two were lost to follow-up. Eye enucleation was performed in 94.1% of patients. Five-year overall survival in patients with intraocular recurrence, orbital recurrence, and metastasis was 84.6%, 69.6%, and 31.3%, respectively (P = 0.001). Most deaths occurred within 2 years of recurrence. Presence of high-risk pathological factors, central nervous system invasion, and absence of combination therapy were independent predictors of worse 5-year overall survival. CONCLUSION: The rate of eye preservation in survivors of recurrent RB was very low. Although 5-year overall survival in patients who underwent treatment for intraocular and orbital recurrence was high, it was low in those with metastasis. RB patients may need lifelong follow-up for recurrence and secondary malignancy.

Prognostic value of GLIM-defined malnutrition in combination with hand-grip strength or gait speed for the prediction of postoperative outcomes in gastric cancer patients with cachexia.

BACKGROUND: Cancer cachexia is associated with impaired functional and nutritional status and worse clinical outcomes. Global Leadership Initiative in Malnutrition (GLIM) consensus recommended the application of GLIM criteria to diagnose malnutrition in patients with cachexia. However, few previous study has applied the GLIM criteria in patients with cancer cachexia. METHODS: From July 2014 to May 2019, patients who were diagnosed with cancer cachexia and underwent radical gastrectomy for gastric cancer were included in this study. Malnutrition was diagnosed using the GLIM criteria. Skeletal muscle index was measured using abdominal computed tomography (CT) images at the third lumbar vertebra (L3) level. Hand-grip strength and 6-meters gait speed were measured before surgery. RESULTS: A total of 356 patients with cancer cachexia were included in the present study, in which 269 (75.56%) were identified as having malnutrition based on the GLIM criteria. GLIM-defined malnutrition alone did not show significant association with short-term postoperative outcomes, including complications, costs or length of postoperative hospital stays. The combination of low hand-grip strength or low gait speed with GLIM-defined malnutrition led to a significant predictive value for these outcomes. Moreover, low hand-grip strength plus GLIM-defined malnutrition was independently associated with postoperative complications (OR 1.912, 95% CI 1.151-3.178, P = 0.012). GLIM-defined malnutrition was an independent predictive factor for worse OS (HR 2.310, 95% CI 1.421-3.754, P = 0.001) and DFS (HR 1.815, 95% CI 1.186-2.779, P = 0.006) after surgery. The addition of low hand-grip strength or low gait speed to GLIM-defined malnutrition did not increase its predictive value for survival. CONCLUSION: GLIM-defined malnutrition predicted worse long-term survival in gastric cancer patients with cachexia. Gait speed and hand-grip strength added prognostic value to GLIM-defined malnutrition for the prediction of short-term postoperative outcomes, which could be incorporated into preoperative assessment protocols in patients with cancer cachexia.

Prognostic value of the Naples prognostic score in patients with intrahepatic cholangiocarcinoma after hepatectomy.

BACKGROUND: The Naples Prognostic Score (NPS), integrating inflammatory and nutritional biomarkers, has been reported to be associated with the prognosis of various malignancies, but there is no report on intrahepatic cholangiocarcinoma (ICC). This study aimed to explore the prognostic value of NPS in patients with ICC. METHODS: Patients with ICC after hepatectomy were collected, and divided into three groups. The prognosis factors were determined by Cox regression analysis. Predictive efficacy was evaluated by the time-dependent receiver operating characteristic (ROC) curves. RESULTS: A total of 174 patients were included (Group 1: 33 (19.0%) patients; Group 2: 83 (47.7%) patients; and Group 3: 58 (33.3%) patients). The baseline characteristics showed the higher the NPS, the higher the proportion of patients with cirrhosis and Child-Pugh B, and more advanced tumors. The Kaplan-Meier curves reflect higher NPS were associated with poor survival. Multivariable analysis showed NPS was an independent risk factor of overall survival (NPS group 2 vs. 1: HR = 1.671, 95% CI: 1.022-3.027, p = 0.009; NPS group 3 vs. 1: HR = 2.208, 95% CI: 1.259-4.780, p = 0.007) and recurrence-free survival (NPS group 2 vs. 1: HR = 1.506, 95% CI: 1.184-3.498, p = 0.010; NPS group 3 vs. 1: HR = 2.141, 95% CI: 2.519-4.087, P = 0.001). The time ROC indicated NPS was superior to other models in predicting prognosis. CONCLUSIONS: NPS is a simple and effective tool for predicting the long-term survival of patients with ICC after hepatectomy. Patients with high NPS require close follow-up, and improving NPS may prolong the survival time.

Remarkable Toughening of Plastic with Monodispersed Nano-CaCO3: From Theoretical Predictions to Experimental Validation.

The structure-property relationship of poly(vinyl chloride) (PVC)/CaCO3 nanocomposites is investigated by all-atom molecular dynamics (MD) simulations. MD simulation results indicate that the dispersity of nanofillers, interfacial bonding, and chain mobility are imperative factors to improve the mechanical performance of nanocomposites, especially toughness. The tensile behavior and dissipated work of the PVC/CaCO3 model demonstrate that 12 wt % CaCO3 modified with oleate anion and dodecylbenzenesulfonate can impart high toughness to PVC due to its good dispersion, favorable interface interaction, and weak migration of PVC chains. Under the guidance of MD simulation, we experimentally prepared a transparent PVC/CaCO3 nanocomposite with good mechanical properties by in situ polymerization of monodispersed CaCO3 in vinyl chloride monomers. Interestingly, experimental tests indicate that the optimum toughness of a nanocomposite (a 368% increase in the elongation at break and 204% improvement of the impact strength) can be indeed realized by adding 12 wt % CaCO3 modified with oleic acid and dodecylbenzenesulfonic acid, which is remarkably consistent with the MD simulation prediction. In short, this work provides a proof-of-concept of using MD simulation to guide the experimental synthesis of PVC/CaCO3 nanocomposites, which can be considered as an example to develop other functional nanocomposites.

Exploring the impact of gut microbiota on liver health in mice and patients with Wilson disease.

BACKGROUND AND AIMS: Distinctive gut microbial profiles have been observed between patients with Wilson disease (WD) and healthy individuals. Despite this, the exact relationship and influence of gut microbiota on the advancement of WD-related liver damage remain ambiguous. This research seeks to clarify the gut microbiota characteristics in both human patients and mouse models of WD, as well as their impact on liver injury. METHODS: Gut microbial features in healthy individuals, patients with WD, healthy mice and mice with early- and late-stage WD were analysed using 16S rRNA gene sequencing. Additionally, WD-afflicted mice underwent treatment with either an antibiotic cocktail (with normal saline as a control) or healthy microbiota (using disease microbiota as a control). The study assessed gut microbiota composition, hepatic transcriptome profiles, liver copper concentrations and hepatic pathological injuries. RESULTS: Patients with hepatic WD and mice with WD-related liver injury displayed altered gut microbiota composition, notably with a significant reduction in Lactobacillus abundance. Additionally, the abundances of several gut genera, including Lactobacillus, Veillonella and Eubacterium coprostanoligenes, showed significant correlations with the severity of liver injury in patients with WD. In WD mice, antibiotic treatment or transplantation of healthy microbiota altered the gut microbial structure, increased Lactobacillus abundance and modified the hepatic transcriptional profile. These interventions resulted in reduced hepatic copper concentration and alleviation of WD-related liver injury. CONCLUSIONS: Individuals and mice with pronounced WD-related liver injury exhibited shifts in gut microbial composition. Regulating gut microbiota through healthy microbiota transplantation emerges as a promising therapeutic approach for treating WD-related liver injury.

TRIM25-mediated XRCC1 ubiquitination accelerates atherosclerosis by inducing macrophage M1 polarization and programmed death.

BACKGROUND: Macrophage-mediated cleaning up of dead cells is a crucial determinant in reducing coronary artery inflammation and maintaining vascular homeostasis. However, this process also leads to programmed death of macrophages. So far, the role of macrophage death in the progression of atherosclerosis remains controversial. Also, the underlying mechanism by which transcriptional regulation and reprogramming triggered by macrophage death pathways lead to changes in vascular inflammation and remodeling are still largely unknown. TRIM25-mediated RIG-I signaling plays a key role in regulation of macrophages fate, however the role of TRIM25 in macrophage death-mediated atherosclerotic progression remains unclear. This study aims to investigate the relationship between TRIM25 and macrophage death in atherosclerosis. METHODS: A total of 34 blood samples of patients with coronary stent implantation, including chronic total occlusion (CTO) leisions (n = 14) or with more than 50% stenosis of a coronary artery but without CTO leisions (n = 20), were collected, and the serum level of TRIM25 was detected by ELISA. Apoe-/- mice with or without TRIM25 gene deletion were fed with the high-fat diet (HFD) for 12 weeks and the plaque areas, necrotic core size, aortic fibrosis and inflammation were investigated. TRIM25 wild-type and deficient macrophages were isolated, cultured and stimulated with ox-LDL, RNA-seq, real-time PCR, western blot and FACS experiments were used to screen and validate signaling pathways caused by TRIM25 deletion. RESULTS: Downregulation of TRIM25 was observed in circulating blood of CTO patients and also in HFD-induced mouse aortas. After HFD for 12 weeks, TRIM25-/-ApoeE-/- mice developed smaller atherosclerotic plaques, less inflammation, lower collagen content and aortic fibrosis compared with TRIM25+/+ApoeE-/- mice. By RNA-seq and KEGG enrichment analysis, we revealed that deletion of TRIM25 mainly affected pyroptosis and necroptosis pathways in ox-LDL-induced macrophages, and the expressions of PARP1 and RIPK3, were significantly decreased in TRIM25 deficient macrophages. Overexpression of TRIM25 promoted M1 polarization and necroptosis of macrophages, while inhibition of PARP1 reversed this process. Further, we observed that XRCC1, a repairer of DNA damage, was significantly upregulated in TRIM25 deficient macrophages, inhibiting PARP1 activity and PARP1-mediated pro-inflammatory change, M1 polarization and necroptosis of macrophages. By contrast, TRIM25 overexpression mediated ubiquitination of XRCC1, and the inhibition of XRCC1 released PARP1, and activated macrophage M1 polarization and necroptosis, which accelerated aortic inflammation and atherosclerotic plaque progression. CONCLUSIONS: Our study has uncovered a crucial role of the TRIM25-XRCC1Ub-PARP1-RIPK3 axis in regulating macrophage death during atherosclerosis, and we highlight the potential therapeutic significance of macrophage reprogramming regulation in preventing the development of atherosclerosis.

Coordination of pinna, petiole, and root anatomical traits in 24 tropical-subtropical fern species.

Ferns are primitive vascular plants with diverse morphologies and structures. Plant anatomical traits and their linkages can reflect adaptation to the environment; however, these remain are still poorly understood in ferns. The main objective of this study was to explore whether there was structural coordination among and within organs in fern species. We measured 16 hydraulically related anatomical traits of pinnae, petioles, and roots of 24 representative fern species from the tropical and subtropical forest understory and analyzed trait correlation networks. In addition, we examined phylogenetic signals for the anatomical traits and analyzed co-evolutionary relationships. These results indicated that stomatal density and all petiole anatomical traits exhibited significant phylogenetic signals. Evolutionary correlations were observed between the tracheid diameter and wall thickness of the petiole and between the water transport capacity of the petiole and stomatal density. Conversely, anatomical traits of roots (e.g., root diameter) showed no phylogenetic signals and were not significantly correlated with those of the pinnae and petioles, indicating a lack of structural coordination between the below- and above-ground organs. Unlike angiosperms, vein density is unrelated to stomatal density or pinna thickness in ferns. As root diameter decreased, the cortex-to-stele diameter ratio decreased significantly (enhanced water absorption) in angiosperms but remained unchanged in ferns. These differences lead to different responses of ferns to climate change and improve our knowledge of the water adaptation strategies of ferns.

Collaborative analysis for drug discovery by federated learning on non-IID data.

With the increasing availability of large-scale QSAR (Quantitative Structure-Activity Relationship) datasets, collaborative analysis has become a promising approach for drug discovery. Traditional centralized analysis which typically concentrates data on a central server for training faces challenges such as data privacy and security. Distributed analysis such as federated learning offers a solution by enabling collaborative model training without sharing raw data. However, it may fail when the training data in the local devices are non-independent and identically distributed (non-IID). In this paper, we propose a novel framework for collaborative drug discovery using federated learning on non-IID datasets. We address the difficulty of training on non-IID data by globally sharing a small subset of data among all institutions. Our framework allows multiple institutions to jointly train a robust predictive model while preserving the privacy of their individual data. We leverage the federated learning paradigm to distribute the model training process across local devices, eliminating the need for data exchange. The experimental results on 15 benchmark datasets demonstrate that the proposed method achieves competitive predictive accuracy to centralized analysis while respecting data privacy. Moreover, our framework offers benefits such as reduced data transmission and enhanced scalability, making it suitable for large-scale collaborative drug discovery efforts.

Identification of ARF genes in Juglans Sigillata Dode and analysis of their expression patterns under drought stress.

BACKGROUND: Auxin response factor (ARF), a transcription factors that controls the expression of genes responsive to auxin, plays a key role in the regulation of plant growth and development. Analyses aimed at identifying ARF family genes and characterizing their functions in Juglans sigillata Dode are lacking. METHODS AND RESULTS: We used bioinformatic approaches to identify members of the J. sigillata ARF gene family and analyze their evolutionary relationships, collinearity, cis-acting elements, and tissue-specific expression patterns. The expression patterns of ARF gene family members under natural drought conditions were also analyzed. The J. sigillata ARF gene family contained 31 members, which were unevenly distributed across 16 chromosomes. We constructed a phylogenetic tree of JsARF genes and other plant ARF genes. Cis-acting elements in the promoters of JsARF were predicted. JsARF28 showed higher expressions in both the roots and leaves. A heat map of the transcriptome data of the cluster analysis under drought stress indicated that JsARF3/9/11/17/20/26 are responsive to drought. The expression of the 11 ARF genes varied under PEG treatment and JsARF18 and JsARF20 were significantly up-regulated. CONCLUSIONS: The interactions between abiotic stresses and plant hormones are supported by our cumulative data, which also offers a theoretical groundwork for comprehending the ARF mechanism and drought resistance in J. sigillata.

Sex-differential cognitive performance on MCCB of youth with BD-II depression.

BACKGROUND: Recent evidences have shown sex-differential cognitive deficits in bipolar disorder (BD) and differences in cognitions across BD subtypes. However, the sex-specific effect on cognitive impairment in BD subtype II (BD-II) remains obscure. The aim of the current study was to examine whether cognitive deficits differ by gender in youth with BD-II depression. METHOD: This cross-sectional study recruited 125 unmedicated youths with BD-II depression and 140 age-, sex-, and education-matched healthy controls (HCs). The Chinese version of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) was used to assess cognitive functions. Mood state was assessed using the 24-item Hamilton Depression Rating Scale (24-HDRS) and the Young Mania Rating Scale (YMRS). Multivariate analysis of covariance (MANCOVA) was conducted. RESULT: ​Compared with HCs, patients with BD-II depression had lower scores on MCCB composite and its seven cognitive domains (all p < 0.001). After controlling for age and education, MANCOVA revealed significant gender-by-group interaction on attention/vigilance (F = 6.224, df = 1, p = 0.013), verbal learning (F = 9.847, df = 1, p = 0.002), visual learning (F = 4.242, df = 1, p = 0.040), and composite (F = 8.819, df = 1, p = 0.003). Post hoc analyses suggested that males performed worse in the above-mentioned MCCB tests than females in BD-II depression. CONCLUSION: Our study demonstrated generalized cognitive deficits in unmedicated youths with BD-II depression. Male patients performed more serious cognitive impairment on attention/vigilance, verbal learning, and visual learning compared to female patients.

Epidemiology and Clinical Characteristics of Pediatric Sepsis in PICUs in Southwest China: A Prospective Multicenter Study.

OBJECTIVES: To describe the epidemiological characteristics of pediatric sepsis in Southwest China PICUs. DESIGN: A prospective, multicenter, and observational study. SETTING: Twelve PICUs in Southwest China. PATIENTS: The patients admitted to the PICU from April 1, 2022, to March 31, 2023. The age ranged from 28 days to 18 years. All patients met the criteria of severe sepsis or septic shock. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of the 31 PICUs invited to participate, 12 PICUs (capacity of 292 beds) enrolled patients in the study. During the study period, 11,238 children were admitted to the participating PICUs, 367 (3.3%) of whom met the diagnosis of severe sepsis or septic shock. The most prevalent sites of infection were the respiratory system (55%) and the digestive system (15%). The primary treatments administered to these patients included antibiotics (100%), albumin (61.3%), invasive mechanical ventilation (58.7%), glucocorticoids (55.6%), blood products (51%), gammaglobulin (51%), and vasoactive medications (46.6%). Sepsis-related mortality in the PICU was 11.2% (41/367). Nearly half of the sepsis deaths occurred within the first 3 days of PICU admission (22/41, 53.7%). The mortality rate of septic shock (32/167, 19.2%) was significantly higher than that of severe sepsis (9/200, 4.5%; p < 0.001). The outcomes of a multivariate logistic regression analysis suggested that a higher pediatric Sequential Organ Failure Assessment score, and the use of invasive mechanical ventilation and vasoactive medications were independently associated with PICU mortality in children with sepsis. CONCLUSIONS: This report updates the epidemiological data of pediatric sepsis in PICUs in Southwest China. Sepsis is still a life-threatening disease in children.

Clinical profile analysis and nomogram for predicting in-hospital mortality among elderly severe community-acquired pneumonia patients: a retrospective cohort study.

BACKGROUND: Severe community-acquired pneumonia is one of the most lethal forms of CAP with high mortality. For rapid and accurate decisions, we developed a mortality prediction model specifically tailored for elderly SCAP patients. METHODS: The retrospective study included 2365 elderly patients. To construct and validate the nomogram, we randomly divided the patients into training and testing cohorts in a 70% versus 30% ratio. The primary outcome was in-hospital mortality. Univariate and multivariate logistic regression analyses were used in the training cohort to identify independent risk factors. The robustness of this model was assessed using the C index, ROC and AUC. DCA was employed to evaluate the predictive accuracy of the model. RESULTS: Six factors were used as independent risk factors for in-hospital mortality to construct the prediction model, including age, the use of vasopressor, chronic renal disease, neutrophil, platelet, and BUN. The C index was 0.743 (95% CI 0.719-0.768) in the training cohort and 0.731 (95% CI 0.694-0.768) in the testing cohort. The ROC curves and AUC for the training cohort and testing cohort (AUC = 0.742 vs. 0.728) indicated a robust discrimination. And the calibration plots showed a consistency between the prediction model probabilities and observed probabilities. Then, the DCA demonstrated great clinical practicality. CONCLUSIONS: The nomogram incorporated six risk factors, including age, the use of vasopressor, chronic renal disease, neutrophil, platelet and BUN, which had great predictive accuracy and robustness, while also demonstrating clinical practicality at ICU admission.

Precise planning based on 3D-printed dry-laboratory models can reduce perioperative complications of laparoscopic surgery for complex hepatobiliary diseases: a preoperative cohort study.

BACKGROUND & AIMS: Complications after laparoscopic liver resection (LLR) are important factors affecting the prognosis of patients, especially for complex hepatobiliary diseases. The present study aimed to evaluate the value of a three-dimensional (3D) printed dry-laboratory model in the precise planning of LLR for complex hepatobiliary diseases. METHODS: Patients with complex hepatobiliary diseases who underwent LLR were preoperatively enrolled, and divided into two groups according to whether using a 3D-printed dry-laboratory model (3D vs. control group). Clinical variables were assessed and complications were graded by the Clavien-Dindo classification. The Comprehensive Complication Index (CCI) scores were calculated and compared for each patient. Multivariable analysis was performed to determine the risk factors of postoperative complications. RESULTS: Sixty-two patients with complex hepatobiliary diseases underwent the precise planning of LLR. Among them, thirty-one patients acquired the guidance of a 3D-printed dry-laboratory model, and others were only guided by traditional enhanced CT or MRI. The results showed no significant differences between the two groups in baseline characters. However, compared to the control group, the 3D group had a lower incidence of intraoperative blood loss, as well as postoperative 30-day and major complications, especially bile leakage (all P < 0.05). The median score on the CCI was 20.9 (range 8.7-51.8) in the control group and 8.7 (range 8.7-43.4) in the 3D group (mean difference, -12.2, P = 0.004). Multivariable analysis showed the 3D model was an independent protective factor in decreasing postoperative complications. Subgroup analysis also showed that a 3D model could decrease postoperative complications, especially for bile leakage in patients with intrahepatic cholelithiasis. CONCLUSION: The 3D-printed models can help reduce postoperative complications. The 3D-printed models should be recommended for patients with complex hepatobiliary diseases undergoing precise planning LLR.

Analysis of the effect on costochondral graft for TMJ ankylosis with jaw deformities in pediatrics.

OBJECTIVES: To evaluate the effects of costochondral grafting (CCG) used for temporomandibular joint ankylosis (TMJA) in growing patients. MATERIALS AND METHODS: Pediatric patients with TMJA treated by CCG from 2010.5 to 2021.7 were included in the study. CT scans were performed before and after operations with at least 1 year follow-up. The height of the mandibular ramus, menton deviation or retraction, osteotomy gap, etc. were measured by ProPlan CMF1.4 software. CCG growth, resorption, and relapse were evaluated and analyzed with influencing factors such as age, ostectomy gap, etc. by generalized estimating equation. RESULTS: There were 24 patients (29 joints) with an average age of 6.30 ± 3.13 years in the study. After operation, the mandibular ramus was elongated by 5.97 ± 3.53 mm. Mandibular deviation or retrusion was corrected by 4.82 ± 2.84 mm and 3.76 ± 2.97 mm respectively. After a mean follow-up of 38.91 ± 29.20 months, 58.62% CCG grew (4.18 ± 7.70 mm), 20.69% absorbed (2.23 ± 1.16 mm), and 20.69% re-ankylosed. The re-ankylosis was negatively correlated with the osteotomy gap (OR:0.348,0.172-0.702 95%CI, critical value = 6.10 mm). CCG resorption was positively correlated with the distance of CCG ramus elongation (OR:3.353,1.173-9.586 95%CI, critical value = 7.40 mm). CONCLUSIONS: An adequate osteotomy gap and CCG ramus elongation distance are the key factors for successful treatment of TMJA with jaw deformities in growing patients. CLINICAL RELEVANCE: TMJA affects mouth opening and jaw development in pediatric patients. The most common autogenous bone graft for pediatric patients is CCG due to its growth potential, convenient access and easy contouring. Also, it can simultaneously reconstruct the TMJ and improve jaw deformity by lengthening the mandibular ramus. But the growth of CCG is unpredictable. In this study, we explored several factors that may affect the absorption and re-ankylosis of CCG, expecting to provide several suggestions to improve future CCG treatment.

Simultaneous standard total joint prosthesis reconstruction with SSRO and Le Fort I osteotomy in the treatment of unilateral temporomandibular joint ankylosis with jaw deformity: a case cohort study.

OBJECTIVE: Unilateral temporomandibular joint ankylosis with jaw deformity (UTMJAJD) may require simultaneous total joint prosthesis (TJP) reconstruction, sagittal split ramus (SSRO), and Le Fort I osteotomies. The purpose of this study was to evaluate outcomes in patients treated with these procedures. METHODS: Patients diagnosed UTMJAJD between 2016 and 2018 were selected for the study. Mandible-first procedure was performed after ankylosis release with TJP on the ankylosed side and SSRO on the contralateral side. Le Fort I osteotomy with and without genioplasty was lastly performed. Maximal incisor opening (MIO), facial symmetry, and jaw and condyle stability were compared before, after operation, and during follow-ups. RESULTS: Seven patients were included in the study. Their average chin deviation was 9.5 ± 4.2 mm, and maxillary cant was 5.1 ± 3.0°. After operation, jaw deformity significantly improved, with chin deviation corrected 7.6 ± 4.1 mm (p = 0.015) and advanced 5.9 ± 2.5 mm (p = 0.006). After an average follow-up of 26.6 ± 17.1 months, MIO significantly increased from 11.4 ± 9.3 to 35.7 ± 2.6 mm (p = 0.000). The occlusion was stable with no significant positional or rotational changes of the jaw (p > 0.05). There was no obvious condylar resorption during follow-ups. CONCLUSION: Simultaneous TJP reconstruction, SSRO, and Le Fort I osteotomy are reliable and effective methods for the treatment of UTMJAJD.

Deep recognition of rice disease images: how many training samples do we really need?

BACKGROUND: With the rapid development of deep learning, the recognition of rice disease images using deep neural networks has become a hot research topic. However, most previous studies only focus on the modification of deep learning models, while lacking research to systematically and scientifically explore the impact of different data sizes on the image recognition task for rice diseases. In this study, a functional model was developed to predict the relationship between the size of dataset and the accuracy rate of model recognition. RESULTS: Training VGG16 deep learning models with different quantities of images of rice blast-diseased leaves and healthy rice leaves, it was found that the test accuracy of the resulting models could be well fitted with an exponential model (A = 0.9965 - e(-0.0603×I50-1.6693)). Experimental results showed that with an increase of image quantity, the recognition accuracy of deep learning models would show a rapid increase at first. Yet when the image quantity increases beyond a certain threshold, the accuracy of image classification would not improve much, and the marginal benefit would be reduced. This trend remained similar when the composition of the dataset was changed, no matter whether (i) the disease class was changed, (ii) the number of classes was increased or (iii) the image data were augmented. CONCLUSIONS: This study provided a scientific basis for the impact of data size on the accuracy of rice disease image recognition, and may also serve as a reference for researchers for database construction. © 2024 Society of Chemical Industry.

Evaluating the surface water pollution risk of mineral resource exploitation via an improved approach: a case study in Liaoning Province, Northeastern China.

Pollution from mineral exploitation is an important risk factor affecting surface water environment in mineral regions. It is urgent to construct a simple and accurate model to assess the surface water pollution risk from mineral exploitation in the regional scale. Thus, taking a mining province namely Liaoning in northeastern China as the study area, we proposed a framework to simulate the transport process of pollutants from mineral exploitation points to the surrounding surface water based on the "source-sink" theory. In our framework, we adopted the regional growth method (RGM) to extract the potential polluted water area as the certain "sink" considering the influence of the topography, and then applied Minimum Cumulative Resistance (MCR) model to assess the surface water pollution risk from mineral exploitation. The results revealed that: (1) 9.5% of the water areas were located at the potential impact area of MEPs. (2) The total value of resistance surface in Liaoning is relatively low, and gradually decreased from west to east. (3) MEPs in Liaoning had a high risk and seriously threatened the surface water environment, among 2125 MEPs, 733 MEPs (32.99%) were assessed as extremely high risk level, and about 35% of the MEPs were distributed within 10KM buffer zone of surface water. (4) Water pollution risk of MEPs in Dalian, Tieling, Fuxin and Dandong need to be emphasized. (5) Compared to previous studies, we considered the topographical influence before applying MCR model directly, so the results of water pollution risk were more reliable. This study provides a methodological support and scientific reference for the water environment protection and regional sustainable development.