Multiple diffusion models for predicting pathologic response of esophageal squamous cell carcinoma to neoadjuvant chemotherapy.

BACKGROUND: To assess the feasibility and diagnostic performance of the fractional order calculus (FROC), continuous-time random-walk (CTRW), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), mono-exponential (MEM) and stretched exponential models (SEM) for predicting response to neoadjuvant chemotherapy (NACT) in patients with esophageal squamous cell carcinoma (ESCC). MATERIALS AND METHODS: This study prospectively included consecutive ESCC patients with baseline and follow up MR imaging and pathologically confirmed cT1-4aN + M0 or T3-4aN0M0 and underwent radical resection after neoadjuvant chemotherapy (NACT) between July 2019 and January 2023. Patients were divided into pCR (TRG 0) and non-pCR (TRG1 + 2 + 3) groups according to tumor regression grading (TRG). The Pre-, Post- and Delta-treatment models were built. 18 predictive models were generated according to different feature categories, based on six models by five-fold cross-validation. Areas under the curve (AUCs) of the models were compared by using DeLong method. RESULTS: Overall, 90 patients (71 men, 19 women; mean age, 64 years ± 6 [SD]) received NACT and underwent baseline and Post-NACT esophageal MRI, with 29 patients in the pCR group and 61 patients in the non-pCR group. Among 18 predictive models, The Pre-, Post-, and Delta-CTRW model showed good predictive efficacy (AUC = 0.722, 0.833 and 0.790). Additionally, the Post-FROC model (AUC = 0.907) also exhibited good diagnostic performance. CONCLUSIONS: Our study indicates that the CTRW model, along with the Post-FROC model, holds significant promise for the future of NACT efficacy prediction in ESCC patients.

Investigation of deformation behavior and strain-induced precipitations in Al-Zn-Mg-Cu alloys across a wide temperature range.

This study explores the hot deformation behavior of Al-Zn-Mg-Cu alloy through uniaxial hot compression (200 °C-450°C) using the Gleeble-1500. True stress-strain curves were corrected, and three models were established: the Arrhenius model, strain compensated (SC) Arrhenius model, and strain compensated recrystallization temperature (RT) segmentation-based (TS-SC) Arrhenius model. Comparative analysis revealed the limited predictive accuracy of the SC Arrhenius model, with a 25.12% average absolute relative error (AARE), while the TS-SC Arrhenius model exhibited a significantly improved to 9.901% AARE. Material parameter calculations displayed variations across the temperature range. The SC Arrhenius model, utilizing an average slope method for parameter computation, failed to consider temperature-induced disparities, limiting its predictive capability. Hot processing map, utilizing the Murty improved Dynamic Materials Model (DMM), indicated optimal conditions for stable forming of the Al-Zn-Mg-Cu alloy. Microstructural analysis revealed MgZn2 precipitation induced by hot deformation, with crystallographic defects enhancing nucleation rates and precipitate refinement.

Ischemic cardio-cerebrovascular disease and all-cause mortality in Chinese elderly patients: a propensity-score matching study.

BACKGROUND: Ischemic cardio-cerebrovascular disease is the leading cause of mortality worldwide. However, studies focusing on elderly and very elderly patients are scarce. Hence, our study aimed to characterize and investigate the long-term prognostic implications of ischemic cardio-cerebrovascular diseases in elderly Chinese patients. METHODS: This retrospective cohort study included 1026 patients aged ≥ 65 years who were categorized into the mono ischemic cardio-cerebrovascular disease (MICCD) (either coronary artery disease or ischemic stroke/transient ischemic attack) (n = 912) and the comorbidity of ischemic cardio-cerebrovascular disease (CICCD) (diagnosed with both coronary artery disease and ischemic stroke/transient ischemic attack at admission) (n = 114). The primary outcome was all-cause death. The mortality risk was evaluated using the Cox proportional hazards risk model with multiple adjustments by conventional and propensity-score-based approaches. RESULTS: Of the 2494 consecutive elderly patients admitted to the hospital, 1026 (median age 83 years [interquartile range]: 76.5-86.4; 94.4% men) met the inclusion criteria. Patients with CICCD consisted mostly of very elderly (79.2% vs. 66.1%, P < 0.001) individuals with a higher burden of comorbidities. Over a median follow-up of 10.4 years, 398 (38.8%) all-cause deaths were identified. Compared with the MICCD group, the CICCD group exhibited a higher adjusted hazard ratio (HR) (95% confidential interval, CI) of 1.71 (1.32-2.39) for long-term mortality after adjusting for potential confounders. The sensitivity analysis results remained robust. After inverse probability of treatment weighting (IPTW) modeling, the CICCD group displayed an even worse mortality risk (IPTW-adjusted HR: 2.07; 95% CI 1.47-2.90). In addition, anemia (adjusted HR: 1.48; 95% CI 1.16-1.89) and malnutrition (adjusted HR: 1.43; 95% CI 1.15-1.78) are also independent risk factors for all-cause mortality among elderly and very elderly patients. CONCLUSIONS: Our results thus suggest that elderly patients with ischemic cardio-cerebrovascular disease and anemia or malnutrition may have higher mortality, which may be predicted upon admission. These findings, however, warrant further investigation.

Examining network structure of impulsivity and depression in adolescents and young adults: A two-sample study.

BACKGROUND: Depression ranks as one of the top five contributors to ill health in youth, the most formative period in life. Extensive research has highlighted the significant role of impulsivity in understanding depression. However, there has been limited exploration into how each dimension of impulsivity uniquely affect depressive symptoms, especially across crucial developmental stages like adolescence and young adulthood. METHODS: This study investigates the unique relationships between impulsivity (assessed by the short UPPS-P scale) and depression (assessed by the Patient Health Questionnaire-9) via network analysis. We analysed data from a total of 2296 participants, comprising 858 adolescents aged 14-17 years and 1438 young adults aged 18-25 years, to estimate both a combined network and age-group specific networks. Key features of the networks, including their structure, global connectivity, and bridge nodes, were compared. RESULTS: The results indicated that age differentially impacts individual depression symptoms, both directly and indirectly, via impulsivity dimensions. The comparison test revealed consistent network structures between the two age groups, with several robust pathways, such as lack of perseverance to concentration difficulties, sensation seeking to suicidal ideation, and negative urgency to feelings of worthlessness. Negative urgency and lack of perseverance were identified as bridge nodes across the two networks. LIMITATIONS: The study employed a cross-sectional design, which limits the ability to estimate causal or temporal relationships. CONCLUSIONS: The current findings highlight the significance of tailoring intervention strategies to individual symptom profiles and assessing negative urgency and lack of perseverance as potential early targets for depression among youth.

Mental health problems of front-line medical staff in the early stage of public health emergencies.

In the face of the unprecedented public health crisis caused by the novel coronavirus pneumonia epidemic, front-line health workers are under enormous mental pressure. This paper aims to explore the mental health challenges faced by front-line health workers in the early stages of a public health emergency, such as stress, anxiety, and depression. At the same time, the factors that increase their mental stress are analyzed, and practical measures are put forward to prevent and manage mental health problems, aiming at improving the quality of medical treatment during public health emergencies. This paper has some reference value for people engaged in mental health prevention.

Imaging Transcriptomics of the Brain for Schizophrenia.

Schizophrenia is a severe mental disorder with a neurodevelopmental origin. Although schizophrenia results from changes in the brain, the underlying biological mechanisms are unknown. Transcriptomics studies quantitative expression changes or qualitative changes of all genes and isoforms, providing a more meaningful biological insight. Magnetic resonance imaging (MRI) techniques play roles in revealing brain structure and function. We give a narrative focused review on the current transcriptome combined with MRI studies related to schizophrenia and summarize the research methodology and content of these studies to identify the research commonalities as well as the implications for future research, in an attempt to provide new insights into the mechanism, clinical diagnosis, and treatments of schizophrenia.

Transcriptomic and neuroimaging data integration enhances machine learning classification of schizophrenia.

Background: Schizophrenia is a polygenic disorder associated with changes in brain structure and function. Integrating macroscale brain features with microscale genetic data may provide a more complete overview of the disease etiology and may serve as potential diagnostic markers for schizophrenia. Objective: We aim to systematically evaluate the impact of multi-scale neuroimaging and transcriptomic data fusion in schizophrenia classification models. Methods: We collected brain imaging data and blood RNA sequencing data from 43 patients with schizophrenia and 60 age- and gender-matched healthy controls, and we extracted multi-omics features of macroscale brain morphology, brain structural and functional connectivity, and gene transcription of schizophrenia risk genes. Multi-scale data fusion was performed using a machine learning integration framework, together with several conventional machine learning methods and neural networks for patient classification. Results: We found that multi-omics data fusion in conventional machine learning models achieved the highest accuracy (AUC ~0.76-0.92) in contrast to the single-modality models, with AUC improvements of 8.88 to 22.64%. Similar findings were observed for the neural network, showing an increase of 16.57% for the multimodal classification model (accuracy 71.43%) compared to the single-modal average. In addition, we identified several brain regions in the left posterior cingulate and right frontal pole that made a major contribution to disease classification. Conclusion: We provide empirical evidence for the increased accuracy achieved by imaging genetic data integration in schizophrenia classification. Multi-scale data fusion holds promise for enhancing diagnostic precision, facilitating early detection and personalizing treatment regimens in schizophrenia.

'Dumpling suture method' versus traditional suture method of protective loop ileostomy in laparoscopic anterior rectal resection with specimen extraction through stoma incision: a retrospective comparative cohort study.

BACKGROUND: A diverting loop ileostomy (DLI) is performed in laparoscopic anterior rectal resection (LAR) surgery at high risk of anastomotic fistula. Minimally invasive surgery promotes postoperative recovery and cosmetics. To reduce abdominal trauma, specimen extraction through stoma incision (EXSI) is usually performed to avoid auxiliary abdominal incision with enlarged stomal incision. The traditional suture method (TSM) reduces the incision size by suturing the ends of the enlarged incision, leading to peristomal incisions and a higher risk of stomal complications. The study aimed to introduce the dumpling suture method (DSM) of PLI and compare this new method with TSM. MATERIALS AND METHODS: The authors propose a novel stoma suture technique, which utilized a method of skin folding suture to reduce the enlarged incision size. A retrospective analysis was conducted on 71 consecutive patients with rectal cancer who underwent LAR-DLI with EXSI, and the intraoperative details and postoperative outcomes of the two groups were measured. RESULTS: The DSM group showed a lower stomal complication rate (10.3 vs. 35.7%, P=0.016) than that of the TSM group. The scores of DET (Discoloration, Erosion, Tissue overgrowth), stomal pain, quality of life were all significantly lower in DSM group than in TSM group. In multivariate analysis, DSM was an independent protective factor for stoma-related complications. Operative time, time to first flatus, defecation and eat, nonstomal related postoperative complications were similar in both groups. CONCLUSION: DSM utilizes a method of skin folding suture to reduce the enlarged incision size, which is safe and effective in reducing the incidence of peristomal skin infections and stomal complications. This procedure offers a novel suturing approach for loop ileostomy with enlarged incision, effectively reducing the postoperative trauma and incidence of stomal complications.

Defective mutations in STAY-GREEN 1, PHYTOENE SYNTHASE 1, and MYB12 genes lead to formation of green ripe fruit in tomato.

Modern tomatoes produce colorful mature fruits, but many wild tomato ancestors form green or gray green ripe fruits. Here, tomato cultivar 'Lvbaoshi' (LBS) that produces green ripe fruits was found to contain three recessive loci responsible for fruit development. The colorless peel of LBS fruits was caused by a 603 bp deletion in the promoter of SlMYB12. The candidate genes of the remaining two loci were identified as STAY-GREEN 1 (SlSGR1) and PHYTOENE SYNTHASE 1 (SlPSY1). SGR1 and PSY1 co-suppression by RNAi converted the pink fruits into green ripe fruits in transgenic plants. An amino acid change in PSY1 and a deletion in the promoter of SGR1 were also identified in several wild tomatoes bearing green or gray ripe fruits. Overexpression of PSY1 from green ripe fruit wild tomatoes in LBS plants could only partially rescue the green ripe fruit phenotype of LBS, and transgenic lines expressing ProSGR1::SGR1 from Solanum pennellii also failed to convert purple-flesh into red-flesh fruits. This work uncovers a novel regulatory mechanism by which SlMYB12, SlPSY1, and SlSGR1 control fruit color in cultivated and some wild tomato species.

Large-scale mechanism hypothesis and research prospects of cognitive impairment in schizophrenia based on magnetic resonance imaging.

Cognitive impairments in schizophrenia are pivotal clinical issues that need to be solved urgently. However, the mechanism remains unknown. It has been suggested that cognitive impairments in schizophrenia are associated with connectome damage, and are especially relevant to the disrupted hub nodes in the frontal and parietal lobes. Activating the dorsolateral prefrontal cortex (DLPFC) via repetitive transcranial magnetic stimulation (rTMS) could result in improved cognition. Based on several previous magnetic resonance imaging (MRI) studies on schizophrenia, we found that the first-episode patients showed connectome damage, as well as abnormal activation and connectivity of the DLPFC and inferior parietal lobule (IPL). Accordingly, we proposed that DLPFC-IPL pathway destruction might mediate connectome damage of cognitive impairments in schizophrenia. In the meantime, with the help of multimodal MRI and noninvasive neuromodulation tool, we may not only validate the hypothesis, but also find IPL as the potential intervention target for cognitive impairments in schizophrenia.

AMBRA1 promotes intestinal inflammation by antagonizing PP4R1/PP4c mediated IKK dephosphorylation in an autophagy-independent manner.

IκB kinase (IKK) complex is central regulators of the NF-κB pathway, and dysregulation of IKK phosphorylation leads to hyperactivation of proinflammatory response in various chronic inflammatory diseases, including inflammatory bowel disease (IBD). However, the dynamic modulation of IKK phosphorylation and dephosphorylation in intestinal inflammation remains uncharacterized. Here, we found that autophagy/beclin-1 regulator 1 (AMBRA1) was highly expressed in inflamed colons in a colitis mouse model and in clinical IBD samples. Importantly, AMBRA1 deletion significantly decreased proinflammatory cytokine expression and enhanced the therapeutic effect of infliximab on intestinal inflammation. Mechanistically, the N-term F1 domain of AMBRA1 was required for AMBRA1 to competitively interact with protein phosphatase 4 regulatory subunit 1 (PP4R1) and catalytic protein phosphatase 4 (PP4c) to suppress their interactions with IKK, promote the dissociation of the PP4R1/PP4c complex, and antagonize the dephosphorylation activity of this complex towards the IKK complex. In response to TNF-α stimulation, IKKα phosphorylates AMBRA1 at S1043 to stabilize AMBRA1 expression by impairing its binding to Cullin4A (CUL4A) to decrease its CUL4A-mediated K48-linked ubiquitination. Overall, our study identifies an autophagy-independent function of AMBRA1 as a positive modulator of IKK phosphorylation to promote intestinal inflammation, thus providing a new targeted therapeutic strategy for patients with refractory IBD.

Targeting suicidal ideation in major depressive disorder with MRI-navigated Stanford accelerated intelligent neuromodulation therapy.

High suicide risk represents a serious problem in patients with major depressive disorder (MDD), yet treatment options that could safely and rapidly ameliorate suicidal ideation remain elusive. Here, we tested the feasibility and preliminary efficacy of the Stanford Accelerated Intelligent Neuromodulation Therapy (SAINT) in reducing suicidal ideation in patients with MDD. Thirty-two MDD patients with moderate to severe suicidal ideation participated in the current study. Suicidal ideation and depression symptoms were assessed before and after 5 days of open-label SAINT. The neural pathways supporting rapid-acting antidepressant and suicide prevention effects were identified with dynamic causal modelling based on resting-state functional magnetic resonance imaging. We found that 5 days of SAINT effectively alleviated suicidal ideation in patients with MDD with a high response rate of 65.63%. Moreover, the response rates achieved 78.13% and 90.63% with 2 weeks and 4 weeks after SAINT, respectively. In addition, we found that the suicide prevention effects of SAINT were associated with the effective connectivity involving the insula and hippocampus, while the antidepressant effects were related to connections of the subgenual anterior cingulate cortex (sgACC). These results show that SAINT is a rapid-acting and effective way to reduce suicidal ideation. Our findings further suggest that distinct neural mechanisms may contribute to the rapid-acting effects on the relief of suicidal ideation and depression, respectively.

Surgical Options for Appropriate Length of J-Pouch Construction for Better Outcomes and Long-term Quality of Life in Patients with Ulcerative Colitis after Ileal Pouch-Anal Anastomosis.

Background/Aims: Total proctocolectomy with ileal pouch-anal anastomosis (IPAA) is widely accepted as a radical surgery for refractory ulcerative colitis (UC). Definite results on the appropriate pouch length for an evaluation of the risk-to-benefit ratio regarding technical complications and long-term quality of life (QOL) are still scarce. Methods: Data on UC patients who underwent IPAA from 2008 to 2022 in four well-established pouch centers affiliated to China UC Pouch Center Union were collected. Results: A total of 208 patients with a median follow-up time of 6.0 years (interquartile range, 2.3 to 9.0 years) were enrolled. The median lengths of the patients' short and long pouches were 14.0 cm (interquartile range, 14.0 to 15.0 cm) and 22.0 cm (interquartile range, 20.0 to 24.0 cm), respectively. Patients with a short J pouch configuration were less likely to achieve significantly improved long-term QOL (p=0.015) and were prone to develop late postoperative complications (p=0.042), such as increased defecation frequency (p=0.003) and pouchitis (p=0.035). A short ileal pouch was an independent risk factor for the development of late postoperative complications (odds ratio, 3.100; 95% confidence interval, 1.519 to 6.329; p=0.002) and impaired longterm QOL improvement (odds ratio, 2.221; 95% confidence interval, 1.218 to 4.050, p=0.009). Conclusions: The length of the J pouch was associated with the improvement in long-term QOL and the development of late post-IPAA complications. A long J pouch configuration could be a considerable surgical option for pouch construction.

Spatiotemporal reconstruction of global ocean surface pCO2 based on optimized random forest.

The partial pressure of ocean surface CO2 (pCO2) plays an important role in quantifying the carbon budget and assessing ocean acidification. For such a vast and complex ocean system as the global ocean, most current research practices tend to study the ocean into regions. In order to reveal the overall characteristics of the global ocean and avoid mutual influence between zones, a holistic research method was used to detect the correlation of twelve predictive factors, including chlorophyll concentration (Chlor_a), diffuse attenuation coefficient at 490 nm (Kd_490), density ocean mixed layer thickness (Mlotst), eastward velocity (East), northward velocity (North), salinity (Sal), temperature (Temp), dissolved iron (Fe), dissolved silicate (Si), nitrate (NO3), potential of hydrogen (pH), phosphate (PO4), at the global ocean scale. Based on measured data from the Global Surface pCO2 (LDEO) database, combined with National Aeronautics and Space Administration (NASA) Ocean Color satellite data and Copernicus Ocean reanalysis data, an improved optimized random forest (ORF) method is proposed for the overall reconstruction of global ocean surface pCO2, and compared with various machine learning methods. The results indicate that the ORF method is the most accurate in overall modeling at the global ocean scale (mean absolute error of 6.27µatm, root mean square error of 15.34µatm, R2 of 0.92). Based on independent observations from the LDEO dataset and time series observation stations, the ORF model was further validated, and the global ocean surface pCO2 distribution map of 0.25° × 0.25° for 2010 to 2019 was reconstructed, which is of significance for the global ocean carbon cycle and carbon assessment.

Overweight and obesity determined by body mass index criteria for Asian populations adversely affect assisted reproductive outcomes among Chinese women with polycystic ovary syndrome.

BACKGROUND: Obesity is a common feature in women with polycystic ovary syndrome (PCOS) and is associated with multiple adverse reproductive outcomes. However, the impact of overweight and obesity on reproductive outcomes of women with PCOS who underwent in vitro fertilization-embryo transfer (IVF-ET) is currently controversial and appropriate body mass index (BMI) levels differ across ethnic groups. METHODS: This was a retrospective study including 1066 women with PCOS receiving IVF treatment at our institution between January 2018 and June 2021, among whom 960 underwent their first fresh or frozen embryo transfer. Participants were categorized according to BMI cut-off values proposed by the World Health Organization for Asian populations: normal weight (BMI < 23 kg/m2), overweight (BMI: 23-24.9 kg/m2), and obesity (BMI ≥ 25 kg/m2). The effect of BMI on clinical and embryological outcomes was evaluated by descriptive statistics and logistic regression models with confounders adjusted. The dose-response relationship between BMI as a continuous variable and IVF outcomes is also explored. INTERVENTIONS: no RESULTS: Increasing BMI was associated with significantly lower numbers of total oocytes retrieved, metaphase II oocytes, two pronuclear (2PN) zygotes, and good-quality embryos among women with PCOS. Patients with PCOS with a BMI ≥ 23 kg/m2 had significantly lower live birth rates (41.9% vs. 49.1%; adjusted odds ratio [aOR], 0.75; 95% confidence interval [CI], 0.57-0.97) and implantation rates (35.8% vs. 43.9%; aOR, 0.76; 95% CI, 0.61-0.93) than those with normal BMI. Moreover, BMI showed a non-linear relationship (p for nonlinearity <0.001) with the number of 2PN zygotes with the curve becoming steeper as BMI surpassed 22.4 kg/m2. CONCLUSIONS: Patients with PCOS with a BMI ≥ 23 kg/m2 have lower live birth rates than those with a BMI < 23 kg/m2. Defining obesity and overweight with ethnicity-specific BMI cut-offs may help to improve IVF outcomes among PCOS patients.

EARLY FLOWERING is a dominant gain-of-function allele of FANTASTIC FOUR 1/2c that promotes early flowering in tomato.

Flowering time, an important factor in plant adaptability and genetic improvement, is regulated by various genes in tomato (Solanum lycopersicum). In this study, we characterized a tomato mutant, EARLY FLOWERING (EF), that developed flowers much earlier than its parental control. EF is a dominant gain-of-function allele with a T-DNA inserted 139 bp downstream of the stop codon of FANTASTIC FOUR 1/2c (FAF1/2c). The transcript of SlFAF1/2c was at elevated levels in the EF mutant. Overexpressing SlFAF1/2c in tomato plants phenocopied the early flowering trait of the EF mutant. Knocking out SlFAF1/2c in the EF mutant reverted the early flowering phenotype of the mutant to the normal flowering time of the wild-type tomato plants. SlFAF1/2c promoted the floral transition by shortening the vegetative phase rather than by reducing the number of leaves produced before the emergence of the first inflorescence. The COP9 signalosome subunit 5B (CSN5B) was shown to interact with FAF1/2c, and knocking out CSN5B led to an early flowering phenotype in tomato. Interestingly, FAF1/2c was found to reduce the accumulation of the CSN5B protein by reducing its protein stability. These findings imply that FAF1/2c regulates flowering time in tomato by reducing the accumulation and stability of CSN5B, which influences the expression of SINGLE FLOWER TRUSS (SFT), JOINTLESS (J) and UNIFLORA (UF). Thus, a new allele of SlFAF1/2c was discovered and found to regulate flowering time in tomato.

Exploring myometrial microenvironment changes at the single-cell level from nonpregnant to term pregnant states.

The microenvironment and cell populations within the myometrium play crucial roles in maintaining uterine structural integrity and protecting the fetus during pregnancy. However, the specific changes occurring at the single-cell level in the human myometrium between nonpregnant (NP) and term pregnant (TP) states remain unexplored. In this study, we used single-cell RNA sequencing (scRNA-Seq) and spatial transcriptomics (ST) to construct a transcriptomic atlas of individual cells in the myometrium of NP and TP women. Integrated analysis of scRNA-Seq and ST data revealed spatially distinct transcriptional characteristics and examined cell-to-cell communication patterns based on ligand-receptor interactions. We identified and categorized 87,845 high-quality individual cells into 12 populations from scRNA-Seq data of 12 human myometrium tissues. Our findings demonstrated alterations in the proportions of five subpopulations of smooth muscle cells in TP. Moreover, an increase in monocytic cells, particularly M2 macrophages, was observed in TP myometrium samples, suggesting their involvement in the anti-inflammatory response. This study provides unprecedented single-cell resolution of the NP and TP myometrium, offering new insights into myometrial remodeling during pregnancy.NEW & NOTEWORTHY Using single-cell RNA sequencing and spatial transcriptomics, the myometrium was examined at the single-cell level during pregnancy. We identified spatially distinct cell populations and observed alterations in smooth muscle cells and increased M2 macrophages in term pregnant women. These findings offer unprecedented insights into myometrial remodeling and the anti-inflammatory response during pregnancy. The study advances our understanding of pregnancy-related myometrial changes.

Application of roadside air purifiers in urban street canyons: A pilot-scale study in Hong Kong.

The implementation of roadside air purifiers has emerged as an effective active control measure to alleviate air pollution in urban street canyons. However, technical questions raised under real conditions remain challenging. In this study, we conducted a pilot-scale investigation involving seven units of self-designed roadside air purifiers in an urban street canyon in Hong Kong. The air cleaning effects were quantified with an air quality sensor network after rigorous quality control. The removal efficiencies of Nitrogen dioxide (NO2), Fine suspended particulates (PM2.5), Carbon monoxide (CO), and Nitric oxide (NO) were determined by comparing with simultaneously measured ambient concentrations, with hourly average efficiencies of 14.0 %-16.9 %, 3.5-10.0 %, 11.9 %-18.7 %, and 19.2 %-44.9 %, respectively. Generally, the purification effects presented variations depending on the ambient pollutants' levels. Higher ambient concentrations of NO2, PM2.5, CO correlated with increased purification effects, while NO presented the opposite trend. The influence of interval distance combined with spatial distribution indicated the operation of purifiers will induce local NO2 attenuation even at an interval distance of four meters. Statistical analysis delivered evidence the air cleaning ability exhibited optimal performance when relative humidity level is ranged from 70 % to 90 %, aligning with the prevailing conditions in Hong Kong. Additionally, improved purification effects were observed at the downwind direction, and their performance was enhanced when the wind speed exceeded 2.5 m/s. Moreover, we estimated the operational lifetime of the air purifiers to be approximately 130 days, offering crucial information regarding the filter replacement cycle. This work serves as a pioneering case study, showcasing the feasibility and deployment considerations of roadside air purifiers in effectively controlling air pollution in urban environments.

Dopaminergic-related Anatomical Pattern of Dorsal Striatum in Schizophrenia.

Striatal dopaminergic overactivity was hypothesized as the core pathophysiology of schizophrenia. However, morphological alterations of striatum in schizophrenia remains exclusive, largely because brain regional heterogeneity limited traditional group-mean based approach. Leveraging third-party brain maps of neurotransmitter and cognition behaviours, we developed a pattern-based representation feature score (ReFS) to investigate structural spatial pattern variation in schizophrenia. Structural ReFS of subcortical regions, particularly the striatum, were linked to schizophrenia diagnosis, symptom severity, and genetic susceptibility. Dopaminergic-ReFS of striatum was increased in schizophrenia patients and reliably reproduced across 13 datasets. The pattern-based ReFS effectively captured the shared genetic pathways underlying both schizophrenia and striatum. The results provide convergent, multimodal suggest the central role of striatal spatial patterns in schizophrenia psychopathologies and and open new avenues to develop individualized treatments for psychotic disorders.

A new method for predicting SIRS after percutaneous transhepatic gallbladder drainage.

The occurrence of systemic inflammatory response after percutaneous transhepatic gallbladder drainage brings great risks to patients and is one of the challenges faced by clinicians. Therefore, it is of great significance to find a suitable prediction method for clinicians to intervene early and reduce the transformation of serious complications. Easy-to-obtain and objectively measured clinical features were screened, and logistic regression was used to construct a prediction model. The predictive ability of the model was evaluated by using the receiver operating characteristic curve and the decision curve in the validation set and the training set, respectively. Nine clinical features (CRP, Fever, DBIL, Obstruction, Bile properties, PCT, Length, Width, and Volume factor) were used to construct the prediction model, and the validation results showed that the prediction model had good performance in the training set (AUC = 0.83) and the validation set (AUC = 0.81). The decision curve also showed that the predictive ability of the model incorporating nine clinical features is better than that of a single clinical feature. The model we constructed can accurately predict the occurrence of SIRS, which can guide clinicians to take treatment measures and avoid the deterioration of complications.