Prognostic value of inflammatory nutritional scores in locally advanced esophageal squamous cell carcinoma patients undergoing neoadjuvant chemoimmunotherapy: a multicenter study in China.

Objective: This study investigates the prognostic significance of inflammatory nutritional scores in patients with locally advanced esophageal squamous cell carcinoma (LA-ESCC) undergoing neoadjuvant chemoimmunotherapy. Methods: A total of 190 LA-ESCC patients were recruited from three medical centers across China. Pre-treatment laboratory tests were utilized to calculate inflammatory nutritional scores. LASSO regression and multivariate logistic regression analyses were conducted to pinpoint predictors of pathological response. Kaplan-Meier and Cox regression analyses were employed to assess disease-free survival (DFS) prognostic factors. Results: The cohort comprised 154 males (81.05%) and 36 females (18.95%), with a median age of 61.4 years. Pathological complete response (pCR) was achieved in 17.38% of patients, while 44.78% attained major pathological response (MPR). LASSO and multivariate logistic regression analyses identified that hemoglobin, albumin, lymphocyte, and platelet (HALP) (P=0.02) as an independent predictors of MPR in LA-ESCC patients receiving neoadjuvant chemoimmunotherapy. Kaplan-Meier and log-rank tests indicated that patients with low HALP, MPR, ypT1-2, ypN0 and, ypTNM I stages had prolonged DFS (P < 0.05). Furthermore, univariate and multivariate Cox regression analyses underscored HALP (P = 0.019) and ypT (P = 0.029) as independent predictive factors for DFS in ESCC. Conclusion: Our study suggests that LA-ESCC patients with lower pre-treatment HALP scores exhibit improved pathological response and reduced recurrence rate. As a comprehensive index of inflammatory nutritional status, pre-treatment HALP may be a reliable prognostic marker in ESCC patients undergoing neoadjuvant chemoimmunotherapy.

Improved REBA: deep learning based rapid entire body risk assessment for prevention of musculoskeletal disorders.

Preventing work-related musculoskeletal disorders (WMSDs) is crucial in reducing their impact on individuals and society. However, the existing mainstream 2D image-based approach is insufficient in capturing the complex 3D movements and postures involved in many occupational tasks. To address this, an improved deep learning-based rapid entire body assessment (REBA) method has been proposed. The method takes working videos as input and automatically outputs the corresponding REBA score through 3D pose reconstruction. The proposed method achieves an average precision of 94.7% on real-world data, which is comparable to that of ergonomic experts. Furthermore, the method has the potential to be applied across a wide range of industries as it has demonstrated good generalisation in multiple scenarios. The proposed method offers a promising solution for automated and accurate risk assessment of WMSDs, with implications for various industries to ensure the safety and well-being of workers.

This paper proposes a deep learning-based improved rapid entire body assessment (REBA) method for assessing work-related musculoskeletal disorders (WMSDs) risks using 3D pose reconstruction from videos, achieving 94.7% precision, comparable to ergonomic experts, with potential applications across various industries.

Experience in treating children with ocular dyskinesia and hemifacial spasm secondary to pontine tumours adjacent to the fourth ventricle and systematic review.

OBJECTIVE: To investigate the treatment plan and prognosis of children with ocular dyskinesia and hemifacial spasm secondary to pontine tumours adjacent to the fourth ventricle. METHODS: In this retrospective study, the clinical information of 10 consecutively collected children with ocular dyskinesia and hemifacial spasm secondary to pontine tumours adjacent to the fourth ventricle was analyzed. All 10 children underwent pontine tumour resection through a trans-cerebellomedullary fissure approach; 4 children underwent preoperative diffusion tensor imaging scans to determine the relationship between the tumour and facial nerve nucleus, and the other 6 children underwent intraoperative deep electroencephalography (EEG) tumour monitoring, in which the tumour electrical discharge activity of the tumour was recorded. A voxel distribution map was established to describe the distribution of the tumour location, and patient prognosis was evaluated through clinical and imaging follow-up. RESULTS: All 10 children achieved total tumour resection; 9 tumours were pathologically suggested to be ganglioglioma (WHO grade I), and 1 was a hamartoma. The symptoms of the original ocular dyskinesia and hemifacial spasm disappeared immediately after the operation. The children were followed up for 4-75 months, and none of the symptoms recurred; four cases with preoperative diffusion tensor imaging showed that the tumour was close to the facial nerve. Four in six intraoperative electrophysiological monitoring showed that the tumour had electrical discharge behaviour, and the tumour distribution map indicates a high density of tumour presence in the facial nerve nucleus and the nucleus of the abducens nerve. CONCLUSIONS: In paediatric patients, the facial symptoms are related to the location and abnormal electrical discharge of the tumour. There is no significant correlation between ocular dyskinesia and the location of the tumour. Conventional antiepileptic therapy for this disease is ineffective, and early surgical intervention for total tumour resection can achieve a clinical curative effect.

Comparison of efficacy and safety between neoadjuvant chemotherapy and neoadjuvant immune checkpoint inhibitors combined with chemotherapy for locally advanced esophageal squamous cell carcinoma: a systematic review and meta-analysis.

BACKGROUND: The application of neoadjuvant immune checkpoint inhibitors combined with chemotherapy (NICT) in treating locally advanced oesophageal squamous cell carcinoma (ESCC) is a subject of considerable research interest. In light of this, we undertook a comprehensive meta-analysis aiming to compare the efficacy and safety of this novel approach with conventional neoadjuvant chemotherapy (NCT) in the management of ESCC. METHODS: A systematic search was conducted in PubMed, Embase, Cochrane Library, and Web of Science to gather relevant literature on the efficacy and safety of NICT compared to conventional NCT in locally advanced ESCC published before June 2023. Effect indicators, including odds ratios (ORs) with associated 95% CIs, were employed to evaluate the safety and efficacy outcomes. The risk of bias was assessed using the Cochrane bias risk assessment tool, and s ubgroup analysis and sensitivity analysis were conducted to investigate the findings further. RESULTS: A total of nine studies qualified for the meta-analysis, all of which investigated the efficacy and safety of NICT compared to conventional NCT. The pooled rates of pathologic complete response and major pathologic response in the NICT group were significantly higher compared to the NCT group, with values of 26.9% versus 8.3% ( P <0.00001) and 48.1% versus 24.6% ( P <0.00001), respectively. The ORs for achieving pathologic complete response and major pathologic response were 4.24 (95% CI, 2.84-6.32, I 2 =14%) and 3.30 (95% CI, 2.31-4.71, I 2 =0%), respectively, indicating a significant advantage for the NICT group. Regarding safety outcomes, the pooled incidences of treatment-related adverse events and serious adverse events in the NICT group were 64.4% and 11.5%, respectively, compared to 73.8% and 9.3% in the NCT group. However, there were no significant differences observed between the two groups in terms of treatment-related adverse events (OR=0.67, 95% CI, 0.29-1.54, P =0.35, I 2 =58%) or serious adverse events (OR=1.28, 95% CI, 0.69-2.36, P =0.43, I 2 =0%). Furthermore, no significant differences were found between the NICT and NCT groups regarding R0 resection rates, anastomotic leakage, pulmonary infection, and postoperative hoarseness. CONCLUSIONS: Neoadjuvant immune checkpoint inhibitors combined with chemotherapy demonstrate efficacy and safety in treating resectable oesophageal squamous cell carcinoma. Nevertheless, additional randomized trials are required to confirm the optimal treatment regimen.

Insights into the structures and properties of dyes in the Fenton catalytic process for treating wastewater effluent.

A notable level of apprehension exists over the adverse impacts of dye pollution on aquatic ecosystems and human well-being. The primary objective of this research is to assess the effectiveness of Fenton catalytic reactions in degrading 14 different commercial azo dyes (both single and double) present in aqueous solutions. The investigation focused on the function of dye structures, using a combination of experimental data and examination of theoretical factors. Dye degradation process was carried out at pH 3, and the concentrations of Fe2+ (10-4 mol/L), H2 O2 (2 × 10-3 mol/L), and dye (0.05 g/L). The findings revealed that dyes with a larger molecular weight were more effective at degrading (D%), with the overall degradation efficiency varying from 0% to 94%. Functional groups played an important role in degradation efficiency; for example, dyes with higher aromatic rings led to less D%, while a higher number of sulfonic, methyl, and nitro groups was responsible for better D%. Notably, the presence of OH groups in the backbone of dyes (AB 24, ABE 113, and MB 9) formed the Fe complex during the catalytic process, and the D% was minimal. On the other hand, theoretical quantum calculations such as the greater the JCLogP, highest occupied molecular orbital, and Dipole moment value, the higher the degradation efficiency. And dyes with low lowest unoccupied molecular orbital tended to have a better degradation efficiency. To some extent, UV-Vis spectral analysis was investigated to determine the degradation pathway, and the pseudo-second-order kinetic model fitted better in the degradation process. The overall experimental and theoretical findings suggested that dye degradation efficiency by the Fenton process is structure-dependent. PRACTITIONER POINTS: Insights into the role of azo dye structures-properties on degradation efficiency. Higher molecular weight and sulfonic groups containing dyes showed better degradation efficiency. Hydroxyl groups play the formation of the Fe complex during the degradation process. Higher values of HOMO and lower values of LUMO enhanced degradation efficiency. The pseudo-second-order (PSO) kinetic model obeyed the Fenton process.

Experimental Study on Double-Joint Soft Actuator and Its Dexterous Hand.

In this paper, we propose a pneumatic double-joint soft actuator based on fiber winding and build a dexterous hand with 11 degrees of freedom. Firstly, soft actuator structural design is carried out according to the actuator driving principle and gives the specific manufacturing process. Then, an experimental analysis of the bending performance of a single soft actuator, including bending angle, speed, and force magnitude, is carried out by building a pneumatic control experimental platform. Finally, a series of dexterous robotic hand-grasping experiments is conducted. Different grasping methods are used to catch the objects and measure the objects' change in height, length, and rotation angle during the experiment. The results show that the proposed soft actuator is more consistent with the bending rule of human fingers, and that the gestures of the dexterous hand are more imaginable and flexible when grasping objects. The soft actuator can carry out horizontal and vertical movements, and rotation of the object in the dexterous hand, thus achieving better human-computer interaction.

Nomogram-based prediction model for survival of COVID-19 patients: A clinical study.

The study aim to construct an effective model for predicting the survival period of COVID-19 patients. METHODS: Clinical data of 386 COVID-19 patients were collected from December 2022 to January 2023. The patients were randomly divided into training and validation cohorts in a 7:3 ratio. LASSO regression and multivariate Cox regression analyses were used to identify prognostic factors, and a nomogram was constructed. Nomogram was evaluated using decision curve analysis, receiver operating characteristic curve, consistency index (c-index), and calibration curve. RESULTS: 86 patients (22.3%) died. A new nomogram for predicting the survival was established based on age, resting oxygen saturation, Blood urea nitrogen (BUN), c-reactive protein-to-albumin ratio (CAR), and pneumonia visual score. The decision curve indicated high clinical applicability. The nomogram c-indexes in the training and validation cohorts were 0.846 and 0.81, respectively. The area under the curves (AUCs) for the 15-day and 30-day survival probabilities were 0.906 and 0.869 in the training cohort, and 0.851 and 0.843 in the validation cohort. The calibration curves demonstrated consistency between predicted and actual survival probabilities. CONCLUSIONS: Our nomogram has the capacity to assist clinical practitioners in estimating the survival rate of COVID-19 patients, thereby facilitating more optimal management strategies and therapeutic interventions with substantial clinical applicability.

Characterization and comparative transcriptomic analysis of skeletal muscle in female Pekin duck and Hanzhong Ma duck during different growth stages using RNA-seq.

Duck is an economically important poultry, and there is currently a major focus on improving its meat quality through breeding. There are wide variations in the growth regulation mechanisms of different duck breeds, that fundamental research on skeletal muscle growth is essential for understanding the regulation of unknown genes. The study aimed to broaden the understanding the duck skeletal muscle development and thereby to improve the performance of domestic ducks. In this study, RNA-seq data from skeletal muscles (breast muscle and leg muscle) of Pekin duck and Hanzhong Ma duck sampled at d 17, 21, and 27 of embryo (E17d, E21d, and E27d), as well as at 6-mo-old following birth (M6), to investigate and compare the mRNA temporal expression profiles and associated pathways that regulate skeletal myogenesis of different duck breeds. There were 331 to 1,440 annotated differentially expressed genes (DEGs) in breast muscle and 380 to 1,790 annotated DEGs in leg muscle from different databases between 2 duck breeds. Gene ontology (GO) enrichment in skeletal muscles indicated that these DEGs were mainly involved in biosynthetic process, developmental process, regulation of protein metabolic process and regulation of gene expression. KEGG analysis in skeletal muscles showed that a total of 41 DEGs were mapped to 7 KEGG pathways, including ECM-receptor interaction, focal adhesion, carbon metabolism, regulation of actin cytoskeleton, calcium signaling pathway, biosynthesis of amino acids and PPAR signaling pathway. The differential expression of 8 selected DEGs was verified by qRT-PCR, and the results were consistent with RNA-seq data. The identified DEGs, such as SDC, SPP1, PAK1, MYL9, PGK1, NOS1, PHGDH, TNNT2, FN1, and AQP4, were specially highlighted, indicating their associations with muscle development in the Pekin duck and Hanzhong Ma duck. This study provides a basis for revealing the differences in skeletal muscle development between Pekin duck and Hanzhong Ma duck.

Tuning the surface functionality of polyethylene glycol-modified graphene oxide/chitosan composite for efficient removal of dye.

There has been a lot of attention on water pollution by dyes in recent years because of their serious toxicological implications on human health and the environment. Therefore, the current study presented a novel polyethylene glycol-functionalized graphene oxide/chitosan composite (PEG-GO/CS) to remove dyes from aqueous solutions. Several characterization techniques, such as SEM, TEM, FTIR, TGA/DTG, XRD, and XPS, were employed to correlate the structure-property relationship between the adsorption performance and PEG-GO/CS composites. Taguchi's (L25) approach was used to optimize the batch adsorption process variables [pH, contact time, adsorbent dose, and initial concentration of methyl orange (MO)] for maximal adsorption capacity. pH = 2, contact time = 90 min, adsorbent dose = 10 mg/10 mL, and MO initial concentration = 200 mg/L were found to be optimal. The material has a maximum adsorption capacity of 271 mg/g for MO at room temperature. With the greatest R2 = 0.8930 values, the Langmuir isotherm model was shown to be the most appropriate. Compared to the pseudo-first-order model (R2 = 0.9685), the pseudo-second-order model (R2 = 0.9707) better fits the kinetic data. Electrostatic interactions were the dominant mechanism underlying MO sorption onto the PEG/GO-CS composite. The as-synthesized composite was reusable for up to three adsorption cycles. Thus, the PEG/GO-CS composite fabricated through a simple procedure may remove MO and other similar organic dyes in real contaminated water.

Optimization and prediction of the cotton fabric dyeing process using Taguchi design-integrated machine learning approach.

The typical textile dyeing process calls for a wide range of operational parameters, and it has always been difficult to pinpoint which of these qualities is the most important in dyeing performance. Consequently, this research used a combined design of experiments and machine learning prediction models' method to offer a sustainable and beneficial reactive cotton fabric dyeing process. To be more precise, we built a least square support vector regression (LSSVR) model based on Taguchi's statistical orthogonal design (L27) to predict exhaustion percentage (E%), fixation rate (F%), and total fixation efficiency (T%) and color strength (K/S) in the reactive cotton dyeing process. The model's prediction accuracy was assessed using many measures, including root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R2). Principal component regression (PCR), partial least square regression (PLSR), and fuzzy modelling were some of the other types of regression models used to compare results. Our findings reveal that the LSSVR model greatly outperformed competing models in predicting the E%, F%, T%, and K/S. This is shown by the LSSVR model's much smaller RMSE and MAE values. Overall, it provided the highest possible R2 values, which reached 0.9819.

Beijing Children's Hospital guidelines on the design and conduction of the first standardized database for medulloblastoma.

Medulloblastoma (MB) is one of the most common malignant childhood brain tumors (WHO grade IV). Its high degree of malignancy leads to an unsatisfactory prognosis, requiring more precise and personalized treatment in the near future. Multi-omics and artificial intelligence have been playing a significant role in precise medical research, but their implementation needs a large amount of clinical information and biomaterials. For these reasons, it is urgent for current MB researchers to establish a large sample-size database of MB that contains complete clinical data and sufficient biomaterials such as blood, cerebrospinal fluid (CSF), cancer tissue, and urine. Unfortunately, there are few biobanks of pediatric central nervous system (CNS) tumors throughout the world for limited specimens, scarce funds, different standards collecting methods and et cl. Even though, China falls behind western countries in this area. The present research set up a standard workflow to construct the Beijing Children's Hospital Medulloblastoma (BCH-MB) biobank. Clinical data from children with MB and for collecting and storing biomaterials, along with regular follow-up has been collected and recorded in this database. In the future, the BCH-MB biobank could make it possible to validate the promising biomarkers already identified, discover unrevealed MB biomarkers, develop novel therapies, and establish personalized prognostic models for children with MB upon the support of its sufficient data and biomaterials, laying the foundation for individualized therapies of children with MB.

Electrospun nanofiber membrane diameter prediction using a combined response surface methodology and machine learning approach.

Despite the widespread interest in electrospinning technology, very few simulation studies have been conducted. Thus, the current research produced a system for providing a sustainable and effective electrospinning process by combining the design of experiments with machine learning prediction models. Specifically, in order to estimate the diameter of the electrospun nanofiber membrane, we developed a locally weighted kernel partial least squares regression (LW-KPLSR) model based on a response surface methodology (RSM). The accuracy of the model's predictions was evaluated based on its root mean square error (RMSE), its mean absolute error (MAE), and its coefficient of determination (R2). In addition to principal component regression (PCR), locally weighted partial least squares regression (LW-PLSR), partial least square regression (PLSR), and least square support vector regression model (LSSVR), some of the other types of regression models used to verify and compare the results were fuzzy modelling and least square support vector regression model (LSSVR). According to the results of our research, the LW-KPLSR model performed far better than other competing models when attempting to forecast the membrane's diameter. This is made clear by the much lower RMSE and MAE values of the LW-KPLSR model. In addition, it offered the highest R2 values that could be achieved, reaching 0.9989.

Microbial Fuel Cell Construction Features and Application for Sustainable Wastewater Treatment.

A microbial fuel cell (MFC) is a system that can generate electricity by harnessing microorganisms' metabolic activity. MFCs can be used in wastewater treatment plants since they can convert the organic matter in wastewater into electricity while also removing pollutants. The microorganisms in the anode electrode oxidize the organic matter, breaking down pollutants and generating electrons that flow through an electrical circuit to the cathode compartment. This process also generates clean water as a byproduct, which can be reused or released back into the environment. MFCs offer a more energy-efficient alternative to traditional wastewater treatment plants, as they can generate electricity from the organic matter in wastewater, offsetting the energy needs of the treatment plants. The energy requirements of conventional wastewater treatment plants can add to the overall cost of the treatment process and contribute to greenhouse gas emissions. MFCs in wastewater treatment plants can increase sustainability in wastewater treatment processes by increasing energy efficiency and reducing operational cost and greenhouse gas emissions. However, the build-up to the commercial-scale still needs a lot of study, as MFC research is still in its early stages. This study thoroughly describes the principles underlying MFCs, including their fundamental structure and types, construction materials and membrane, working mechanism, and significant process elements influencing their effectiveness in the workplace. The application of this technology in sustainable wastewater treatment, as well as the challenges involved in its widespread adoption, are discussed in this study.

COVID-19 contact tracking based on person reidentification and geospatial data.

Efficient contact tracing is a crucial step in preventing the spread of COVID-19. However, the current methods rely heavily on manual investigation and truthful reporting by high-risk individuals. Mobile applications and Bluetooth-based contact tracing methods have also been adopted, but privacy concerns and reliance on personal data have limited their effectiveness. To address these challenges, in this paper, a geospatial big data method that combines person reidentification and geospatial information for contact tracing is proposed. The proposed real-time person reidentification model can identify individuals across multiple surveillance cameras, and the surveillance data is fused with geographic information and mapped onto a 3D geospatial model to track movement trajectories. After real-world verification, the proposed method achieves a first accuracy rate of 91.56%, a first-five accuracy rate of 97.70%, and a mean average precision of 78.03% with an inference speed of 13 ms per image. Importantly, the proposed method does not rely on personal information, mobile phones, or wearable devices, avoiding the limitations of existing contact tracing schemes and providing significant implications for public health in the post-COVID-19 era.

Presurgical MRI-Based Radiomics Models for Predicting Cerebellar Mutism Syndrome in Children With Posterior Fossa Tumors.

BACKGROUND: Current studies have indicated that tumoral morphologic features are associated with cerebellar mutism syndrome (CMS), but the radiomics application in CMS is scarce. PURPOSE: To develop a model for CMS discrimination based on multiparametric MRI radiomics in patients with posterior fossa tumors. STUDY TYPE: Retrospective. POPULATION: A total of 218 patients (males 132, females 86) with posterior fossa tumors, 169 of which were included in the MRI radiomics analysis. The MRI radiomics study cohort (169) was split into training (119) and testing (50) sets with a ratio of 7:3. FIELD/SEQUENCE: All the MRI were acquired under 1.5/3.0 T scanners. T2-weighted image (T2W), T1-weighted (T1W), fluid attenuated inversion recovery (FLAIR), diffusion-weighted imaging (DWI). ASSESSMENT: Apparent diffusion coefficient (ADC) maps were generated from DWI. Each MRI dataset generated 1561 radiomics characteristics. Feature selection was performed with univariable logistic analysis, correlation analysis, and least absolute shrinkage and selection operator (LASSO) penalized logistic regression. Significant clinical features were selected with multivariable logistic analysis and used to constructed the clinical model. Radiomics models (based on T1W, T2W, FLAIR, DWI, ADC) were constructed with selected radiomics features. The mix model was based on the multiparametric MRI radiomics features. STATISTICAL TEST: Multivariable logistic analysis was utilized during clinical features selection. Models' performance was evaluated using the area under the receiver operating characteristic (AUC) curve. Interobserver variability was assessed using Cohen's kappa. Significant threshold was set as P < 0.05. RESULTS: Sex (aOR = 3.72), tumor location (aOR = 2.81), hydrocephalus (aOR = 2.14), and tumor texture (aOR = 5.08) were significant features in the multivariable analysis and were used to construct the clinical model (AUC = 0.79); totally, 33 radiomics features were selected to construct radiomics models (AUC = 0.63-0.93). Seven of the 33 radiomics features were selected for the mix model (AUC = 0.93). DATA CONCLUSION: Multiparametric MRI radiomics may be better at predicting CMS than single-parameter MRI models and clinical model. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: 2.

Long-term postoperative quality of life in childhood survivors with cerebellar mutism syndrome.

Background: To investigate the long-term quality of life (QoL) of children with cerebellar mutism syndrome (CMS) and explore the risk factors for a low QoL. Procedure: This cross-sectional study investigated children who underwent posterior fossa surgery using an online Pediatric Quality of Life Inventory questionnaire. CMS and non-CMS patients were included to identify QoL predictors. Results: Sixty-nine patients were included (male, 62.3%), 22 of whom had CMS. The mean follow-up time was 45.2 months. Children with CMS had a significantly lower mean QoL score (65.3 vs. 83.7, p < 0.001) and subdomain mean scores (physical; 57.8 vs. 85.3, p < 0.001; social: 69.5 vs. 85.1, p = 0.001; academic: p = 0.001) than those without CMS, except for the emotional domain (78.0 vs. 83.7, p = 0.062). Multivariable analysis revealed that CMS (coefficient = -14.748.61, p = 0.043), chemotherapy (coefficient = -7.629.82, p = 0.013), ventriculoperitoneal (VP) shunt placement (coefficient = -10.14, p = 0.024), and older age at surgery (coefficient = -1.1830, p = 0.007) were independent predictors of low total QoL scores. Physical scores were independently associated with CMS (coefficient = -27.4815.31, p = 0.005), VP shunt placement (coefficient = -12.86, p = 0.025), and radiotherapy (coefficient = -13.62, p = 0.007). Emotional score was negatively associated with age at surgery (coefficient = -1.92, p = 0.0337) and chemotherapy (coefficient = -9.11, p = 0.003). Social scores were negatively associated with male sex (coefficient = -13.68, p = 0.001) and VP shunt placement (coefficient = -1.36, p = 0.005), whereas academic scores were negatively correlated with chemotherapy (coefficient = -17.45, p < 0.001) and age at surgery (coefficient = -1.92, p = 0.002). Extent of resection (coefficient = 13.16, p = 0.021) was a good predictor of higher academic scores. Conclusion: CMS results in long-term neurological and neuropsychological deficits, negatively affecting QoL, and warranting early rehabilitation.

Effect of a family-involvement combined aerobic and resistance exercise protocol on cancer-related fatigue in patients with breast cancer during postoperative chemotherapy: study protocol for a quasi-randomised controlled trial.

INTRODUCTION: Cancer-related fatigue (CRF) is one of the most common and debilitating side effects experienced by patients with breast cancer (BC) during postoperative chemotherapy. Family-involvement combined aerobic and resistance exercise has been introduced as a promising non-pharmacological intervention for CRF symptom relief and improving patients' muscle strength, exercise completion, family intimacy and adaptability and quality of life. However, evidence for the practice of home participation in combined aerobic and resistance exercise for the management of CRF in patients with BC is lacking. METHODS AND ANALYSIS: We present a protocol for a quasi-randomised controlled trial involving an 8-week intervention. Seventy patients with BC will be recruited from a tertiary care centre in China. Participants from the first oncology department will be assigned to the family-involvement combined aerobic and resistance exercise group (n=28), while participants from the second oncology department will be assigned to the control group that will receive standard exercise guidance (n=28). The primary outcome will be the Piper Fatigue Scale-Revised (R-PFS) score. The secondary outcomes will include muscle strength, exercise completion, family intimacy and adaptability and quality of life, which will be evaluated by the stand-up and sit-down chair test, grip test, exercise completion rate, Family Adaptability and Cohesion Scale, Second Edition-Chinese Version (FACESⅡ-CV) and Functional Assessment of Cancer Therapy -Breast (FACT-B) scale. Analysis of covariance will be applied for comparisons between groups, and paired t-tests will be used for comparison of data before and after exercise within a group. ETHICS AND DISSEMINATION: This study has been approved by the Ethics Committee of the First Affiliated Hospital of Dalian Medical University (PJ-KS-KY-2021-288). The results of this study will be published via peer-reviewed publications and presentations at conferences. TRAIL REGISTRATION NUMBER: ChiCTR2200055793.

The Advancement in Membrane Bioreactor (MBR) Technology toward Sustainable Industrial Wastewater Management.

The advancement in water treatment technology has revolutionized the progress of membrane bioreactor (MBR) technology in the modern era. The large space requirement, low efficiency, and high cost of the traditional activated sludge process have given the necessary space for the MBR system to come into action. The conventional activated sludge (CAS) process and tertiary filtration can be replaced by immersed and side-stream MBR. This article outlines the historical advancement of the MBR process in the treatment of industrial and municipal wastewaters. The structural features and design parameters of MBR, e.g., membrane surface properties, permeate flux, retention time, pH, alkalinity, temperature, cleaning frequency, etc., highly influence the efficiency of the MBR process. The submerged MBR can handle lower permeate flux (requires less power), whereas the side-stream MBR can handle higher permeate flux (requires more power). However, MBR has some operational issues with conventional water treatment technologies. The quality of sludge, equipment requirements, and fouling are major drawbacks of the MBR process. This review paper also deals with the approach to address these constraints. However, given the energy limitations, climatic changes, and resource depletion, conventional wastewater treatment systems face significant obstacles. When compared with CAS, MBR has better permeate quality, simpler operational management, and a reduced footprint requirement. Thus, for sustainable water treatment, MBR can be an efficient tool.

Epidemiological characteristics, clinical presentations, and prognoses of pediatric brain tumors: Experiences of national center for children's health.

Background: We aimed to describe the epidemiological characteristics, clinical presentations, and prognoses in a national health center for children. Methods: From January 2015 to December 2020, 484 patients aged 0-16 years, who were diagnosed with brain tumors and received neurosurgery treatment, were enrolled in the study. Pathology was based on the World Health Organization 2021 nervous system tumor classification, and tumor behaviors were classified according to the International Classification of Diseases for Oncology, third edition. Results: Among the 484 patients with brain tumors, the median age at diagnosis was 4.62 [2.19, 8.17] years (benign tumors 4.07 [1.64, 7.13] vs. malignant tumors 5.36 [2.78, 8.84], p=0.008). The overall male-to-female ratio was 1.33:1(benign 1.09:1 vs. malignant 1.62:1, p=0.029). Nausea, vomiting, and headache were the most frequent initial symptoms. The three most frequent tumor types were embryonal tumors (ET, 22.8%), circumscribed astrocytic gliomas (20.0%), and pediatric-type diffuse gliomas (11.0%). The most common tumor locations were the cerebellum and fourth ventricle (38.67%), the sellar region (22.9%) and ventricles (10.6%). Males took up a higher proportion than females in choroid plexus tumors (63.6%), ET (61.1%), ependymal tumors (68.6%), and germ cell tumors (GCTs, 78.1%). Patients were followed for 1 to 82 months. The overall 5-year survival rate was 77.5%, with survival rates of 91.0% for benign tumors and 64.6% for malignant tumors. Conclusion: Brain tumors presented particularly sex-, age-, and regional-dependent epidemiological characteristics. Our results were consistent with previous reports and might reflect the real epidemiological status in China.

Sustainable fashion: Design of the experiment assisted machine learning for the environmental-friendly resin finishing of cotton fabric.

Given the carcinogenic properties of formaldehyde-based chemicals, an alternative method for resin-finishing cotton textiles is urgently needed. Therefore, the primary objective of this study is to introduce a sustainable resin-finishing process for cotton fabric via an industrial procedure. For this purpose, Bluesign® approved a formaldehyde-free Knittex RCT® resin was used, and the process parameters were designed and optimized according to the Taguchi L27 method. XRD analysis confirmed the crosslinking formation between resin and neighboring molecules of cotton fabric, as no change in the cellulose crystallization phase. Several machine learning models were built in a sequence to predict the crease recovery angle (CRA), tearing strength (TE) and whiteness index (WI). Assessment of modelling was evaluated through the use of various metrics such as root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R2). Results were compared to those from other regression models, such as principal component regression (PCR), partial least squares regression (PLSR), and fuzzy modelling. Based on the results of our research, the LSSVR model predicted the CRA, TE, and WI with substantially more accuracy than other models, as shown by the fact that its RMSE and MAE values were significantly lower. In addition, it offered the greatest possible R2 values, reaching up to 0.9627.