Exploring the Path of Shantytown Renewal Based on the Theory of Environment-behavior Studies: A Case Study of the Northwest Area of Saihantala in Baotou City

The application of environment-behavior studies plays an important role in studying the renewal of shantytowns.One of the most humane ways of renewal is designing and constructing the necessary urban spatial environment from the perspective of human daily behavior.Most of the shantytown renovation projects currently carried out in China are mainly focused on demolition and reconstruction,which not only incurs high costs but also damages the original social structure and economic model.During the process of shantytown renewal,it should improve the urban landscape,living environment,and life quality of residents,and ensure the daily life of shantytown residents without increasing their economic burden,and preserve the traces of urban development.In order to achieve this goal,it should explore the renewal strategies of shantytowns from the perspective of environment-behavior studies through behavior maps,on-site research,and literature review.Updating and design from a human perspective often achieve faster and better development;the renewal of shantytowns should be a bottom-up approach and start from a grassroots perspective,completing the renovation design through the composition of the population and behavioral patterns.

Epidemiological and clinical features,treatment status,and economic burden of traumatic spinal cord injury in China:a hospital-based retrospective study

Traumatic spinal cord injury is potentially catastrophic and can lead to permanent disability or even death.China has the largest population of patients with traumatic spinal cord injury.Previous studies of traumatic spinal cord injury in China have mostly been regional in scope;national-level studies have been rare.To the best of our knowledge,no national-level study of treatment status and economic burden has been performed.This retrospective study aimed to examine the epidemiological and clinical features,treatment status,and economic burden of traumatic spinal cord injury in China at the national level.We included 13,465 traumatic spinal cord injury patients who were injured between January 2013 and December 2018 and treated in 30 hospitals in 11 provinces/municipalities representing all geographical divisions of China.Patient epidemiological and clinical features,treatment status,and total and daily costs were recorded.Trends in the percentage of traumatic spinal cord injuries among all hospitalized patients and among patients hospitalized in the orthopedic department and cost of care were assessed by annual percentage change using the Joinpoint Regression Program.The percentage of traumatic spinal cord injuries among all hospitalized patients and among patients hospitalized in the orthopedic department did not significantly change overall(annual percentage change,-0.5%and 2.1%,respectively).A total of 10,053(74.7%)patients underwent surgery.Only 2.8%of patients who underwent surgery did so within 24 hours of injury.A total of 2005(14.9%)patients were treated with high-dose(≥500 mg)methylprednisolone sodium succinate/methylprednisolone(MPSS/MP);615(4.6%)received it within 8 hours.The total cost for acute traumatic spinal cord injury decreased over the study period(-4.7%),while daily cost did not significantly change(1.0%increase).Our findings indicate that public health initiatives should aim at improving hospitals’ability to complete early surgery within 24 hours,which is associated with improved sensorimotor recovery,increasing the awareness rate of clinical guidelines related to high-dose MPSS/MP to reduce the use of the treatment with insufficient evidence.

Causal associations between gastroesophageal reflux disease and essential hypertension: A bidirectional Mendelian randomization study

BACKGROUND Clinical studies have reported that patients with gastroesophageal reflux disease(GERD)have a higher prevalence of hypertension.AIM To performed a bidirectional Mendelian randomization(MR)analysis to investi-gate the causal link between GERD and essential hypertension.METHODS Eligible single nucleotide polymorphisms(SNPs)were selected,and weighted median,inverse variance weighted(IVW)as well as MR egger(MR-Egger)re-gression were used to examine the potential causal association between GERD and hypertension.The MR-Pleiotropy RESidual Sum and Outlier analysis was used to detect and attempt to reduce horizontal pleiotropy by removing outliers SNPs.The MR-Egger intercept test,Cochran’s Q test and“leave-one-out”sen-sitivity analysis were performed to evaluate the horizontal pleiotropy,heterogen-eities,and stability of single instrumental variable.RESULTS IVW analysis exhibited an increased risk of hypertension(OR=1.46,95%CI:1.33-1.59,P=2.14E-16)in GERD patients.And the same result was obtained in replication practice(OR=1.002,95%CI:1.0008-1.003,P=0.000498).Meanwhile,the IVW analysis showed an increased risk of systolic blood pressure(β=0.78,95%CI:0.11-1.44,P=0.021)and hypertensive heart disease(OR=1.68,95%CI:1.36-2.08,P=0.0000016)in GERD patients.Moreover,we found an decreased risk of Barrett's esophagus(OR=0.91,95%CI:0.83-0.99,P=0.043)in essential hypertension patients.CONCLUSION We found that GERD would increase the risk of essential hypertension,which provided a novel prevent and therapeutic perspectives of essential hypertension.

Snowmelt Flood Mapping and Land Surface Short-Term Dynamics Assessment in a “Before-During-After” Scenario Based on Radar and Optical Satellite Imagery: Case Study Around the Lewisville Lake (Dallas/Fort Worth Metropolitan, Texas, USA)

The main goal of this study has been to map flood and assess land surface short-term dynamics in relation with snowy weather. The two recent snowfall events, which happened in, February 14th and 15th, of year 2021, and February 3rd and 4th, of year 2022, were chosen. A pre-analysis correlation was assumed between, the snow events, recurrency of floods, and changes in the land surface characteristics (i.e., wetness, energy, temperature), in a “Before-During-After” scenario. Active and passive microwave satellites data such as, Sentinel-1 synthetic aperture radar (SAR), Sentinel-2 multispectral instrument (MSI) and Landsat-9 Operation Land Imager-2/Thermal Infrared Sensors-2 (OLI-2/TIRS-2), as well as cloud databased global models for water and urban layers were used. The first step of processing was thresholding of SAR image, at 0.25 cutoff, based on bimodal histogram distribution, followed by the change analysis. The following processing consisted in the images transformation, by computing the tasseled cap transformation wetness (TCTw) and the surface albedo on MSI image. In addition, the land surface temperature (LST) was modeled from OLI-2/TIRS-2 image. Then, a 5th order polynomial regression was computed, between TCTw as dependent variable and, albedo and LST as independent variables. As a first result, an area of 5.6 km2 has been mapped as recurrently flooded from the two years assessment. The other output highlighted a constant increase of wetness (TCTw), considered most influential on land surface dynamics, comparatively to energy exchange (albedo) and temperature (LST). The “After” event dependency between the three indicators was highest, with a correlation coefficient, R2 = 0.682, confirming the persistence of wetness after-snowmelt. Validation over topographic layers confirmed that, recurrently flooded areas are mostly distributed on, lowest valley depth points, farthest distances from channel network (i.e., from perennial waters), and lowest relative slope position areas. Whereas, 88.9% of the validation sampling were confirmed in the laboratory, and 86.7% of urban validation points were assessed as recurrently flooded when combining pre-/post-field-work campaign.

Recent progresses in the development of tubular segmented-in-series solid oxide fuel cells:Experimental and numerical study

Solid oxide fuel cells(SOFCs)have attracted a great deal of interest because they have the highest efficiency without using any noble metal as catalysts among all the fuel cell technologies.However,traditional SOFCs suffer from having a higher volume,current leakage,complex connections,and difficulty in gas sealing.To solve these problems,Rolls-Royce has fabricated a simple design by stacking cells in series on an insulating porous support,resulting in the tubular segmented-in-series solid oxide fuel cells(SIS-SOFCs),which achieved higher output voltage.This work systematically reviews recent advances in the structures,preparation methods,perform-ances,and stability of tubular SIS-SOFCs in experimental and numerical studies.Finally,the challenges and future development of tubular SIS-SOFCs are also discussed.The findings of this work can help guide the direction and inspire innovation of future development in this field.

Short-Term Memory Capacity across Time and Language Estimated from Ancient and Modern Literary Texts. Study-Case: New Testament Translations

We study the short-term memory capacity of ancient readers of the original New Testament written in Greek, of its translations to Latin and to modern languages. To model it, we consider the number of words between any two contiguous interpunctions Ip, because this parameter can model how the human mind memorizes “chunks” of information. Since IP can be calculated for any alphabetical text, we can perform experiments—otherwise impossible— with ancient readers by studying the literary works they used to read. The “experiments” compare the IP of texts of a language/translation to those of another language/translation by measuring the minimum average probability of finding joint readers (those who can read both texts because of similar short-term memory capacity) and by defining an “overlap index”. We also define the population of universal readers, people who can read any New Testament text in any language. Future work is vast, with many research tracks, because alphabetical literatures are very large and allow many experiments, such as comparing authors, translations or even texts written by artificial intelligence tools.

Short-Term Household Load Forecasting Based on Attention Mechanism and CNN-ICPSO-LSTM

Accurate load forecasting forms a crucial foundation for implementing household demand response plans andoptimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations,a single prediction model is hard to capture temporal features effectively, resulting in diminished predictionaccuracy. In this study, a hybrid deep learning framework that integrates attention mechanism, convolution neuralnetwork (CNN), improved chaotic particle swarm optimization (ICPSO), and long short-term memory (LSTM), isproposed for short-term household load forecasting. Firstly, the CNN model is employed to extract features fromthe original data, enhancing the quality of data features. Subsequently, the moving average method is used for datapreprocessing, followed by the application of the LSTM network to predict the processed data. Moreover, the ICPSOalgorithm is introduced to optimize the parameters of LSTM, aimed at boosting the model’s running speed andaccuracy. Finally, the attention mechanism is employed to optimize the output value of LSTM, effectively addressinginformation loss in LSTM induced by lengthy sequences and further elevating prediction accuracy. According tothe numerical analysis, the accuracy and effectiveness of the proposed hybrid model have been verified. It canexplore data features adeptly, achieving superior prediction accuracy compared to other forecasting methods forthe household load exhibiting significant fluctuations across different seasons.

A Time Series Short-Term Prediction Method Based on Multi-Granularity Event Matching and Alignment

Accurate forecasting of time series is crucial across various domains.Many prediction tasks rely on effectively segmenting,matching,and time series data alignment.For instance,regardless of time series with the same granularity,segmenting them into different granularity events can effectively mitigate the impact of varying time scales on prediction accuracy.However,these events of varying granularity frequently intersect with each other,which may possess unequal durations.Even minor differences can result in significant errors when matching time series with future trends.Besides,directly using matched events but unaligned events as state vectors in machine learning-based prediction models can lead to insufficient prediction accuracy.Therefore,this paper proposes a short-term forecasting method for time series based on a multi-granularity event,MGE-SP(multi-granularity event-based short-termprediction).First,amethodological framework for MGE-SP established guides the implementation steps.The framework consists of three key steps,including multi-granularity event matching based on the LTF(latest time first)strategy,multi-granularity event alignment using a piecewise aggregate approximation based on the compression ratio,and a short-term prediction model based on XGBoost.The data from a nationwide online car-hailing service in China ensures the method’s reliability.The average RMSE(root mean square error)and MAE(mean absolute error)of the proposed method are 3.204 and 2.360,lower than the respective values of 4.056 and 3.101 obtained using theARIMA(autoregressive integratedmoving average)method,as well as the values of 4.278 and 2.994 obtained using k-means-SVR(support vector regression)method.The other experiment is conducted on stock data froma public data set.The proposed method achieved an average RMSE and MAE of 0.836 and 0.696,lower than the respective values of 1.019 and 0.844 obtained using the ARIMA method,as well as the values of 1.350 and 1.172 obtained using the k-means-SVR method.

Pharmacodynamic Study of Parallel Groups Comparing the Effect of Rivaroxaban 20 Mg (Laboratorios Leti, S.A.V.) vs Rivaroxaban 20 Mg (Bayer Laboratories) on Prothrombin Time

Background: The prevalence of both atrial fibrillation (FA) and diabetes mellitus (DM) is increasing and they often occur together and constitute a high risk of thrombosis. Rivaroxaban is a Factor Xa inhibitor with a rapid onset and disappearance of action after oral administration;it acts by inhibiting the active form of the coagulation factor. In order to reflect the effect of the action of Rivaroxaban, we used the prothrombin time (PT);however, it′s not the most accurate, but it is the one available in our community. Methods: This was a prospective, randomized, analyst-blinded, parallel group clinical study to verify the efficacy of Rivaroxaban Leti 20 mg (RL) (12 volunteers vs Rivaroxaban Bayer 20 mg (RB) (13 volunteers). The variables were determination of PT and Partial Thromboplastin Time (aPTT) at baseline and at 24, 48 and 72 hours after administering a daily dose of 20 mg for three days. The determination was carried out with the IDG method (Integrated Diagnostics Group Sanzay Corporation) with an International Sensitivity Index (ISI) of 1.17 PT and aPTT were taken before the first dose, and then, every day during the next 3 days, three hours after the ingestion of their daily dose at 7 am. Results: The 25 healthy volunteers were similar in age, BMI, and SBP/DBP level with a greater number of men in the Bayer group. The efficacy of rivaroxaban was similar in both groups with prolongation of PTT to the 2nd day of treatment with PT, and percentage changes from baseline (14.46 ± 0.97 for RB vs 14.17 ± 0.94 RL p: 0.45), PTT results and percentage changes from the base (RB: 34 ± 4.53 RL: 33.46 ± 2.82). The safety of rivaroxaban was good in both groups with no serious adverse events. The equivalence in the logarithmically transformed PT result (ln) on day two, Mean and CI (90%) 99.2 (94.4-104) and 100 (99.5-100.8);neither the means nor the 90% confidence intervals of the PT variable transformed logarithmically to ensure its normality, were far from the 80%-125% allowed for declaration of similarity. Conclusion: The test formulation Rivaroxaban Asarap? 20 mg, manufactured by Leti Laboratories, is interchangeable or bioequivalent in clinical and laboratory response to the reference formulation Xarelto? manufactured by Bayer Laboratories.

Predictive value of red blood cell distribution width and hematocrit for short-term outcomes and prognosis in colorectal cancer patients undergoing radical surgery

BACKGROUND Previous studies have reported that low hematocrit levels indicate poor survival in patients with ovarian cancer and cervical cancer,the prognostic value of hematocrit for colorectal cancer(CRC)patients has not been determined.The prognostic value of red blood cell distribution width(RDW)for CRC patients was controversial.AIM To investigate the impact of RDW and hematocrit on the short-term outcomes and long-term prognosis of CRC patients who underwent radical surgery.METHODS Patients who were diagnosed with CRC and underwent radical CRC resection between January 2011 and January 2020 at a single clinical center were included.The short-term outcomes,overall survival(OS)and disease-free survival(DFS)were compared among the different groups.Cox analysis was also conducted to identify independent risk factors for OS and DFS.RESULTS There were 4258 CRC patients who underwent radical surgery included in our study.A total of 1573 patients were in the lower RDW group and 2685 patients were in the higher RDW group.There were 2166 and 2092 patients in the higher hematocrit group and lower hematocrit group,respectively.Patients in the higher RDW group had more intraoperative blood loss(P<0.01)and more overall complications(P<0.01)than did those in the lower RDW group.Similarly,patients in the lower hematocrit group had more intraoperative blood loss(P=0.012),longer hospital stay(P=0.016)and overall complications(P<0.01)than did those in the higher hematocrit group.The higher RDW group had a worse OS and DFS than did the lower RDW group for tumor node metastasis(TNM)stage I(OS,P<0.05;DFS,P=0.001)and stage II(OS,P=0.004;DFS,P=0.01)than the lower RDW group;the lower hematocrit group had worse OS and DFS for TNM stage II(OS,P<0.05;DFS,P=0.001)and stage III(OS,P=0.001;DFS,P=0.001)than did the higher hematocrit group.Preoperative hematocrit was an independent risk factor for OS[P=0.017,hazard ratio(HR)=1.256,95%confidence interval(CI):1.041-1.515]and DFS(P=0.035,HR=1.194,95%CI:1.013-1.408).CONCLUSION A higher preoperative RDW and lower hematocrit were associated with more postoperative complications.However,only hematocrit was an independent risk factor for OS and DFS in CRC patients who underwent radical surgery,while RDW was not.

Dyslipidemia in Adults with Type 2 Diabetes in a Rural Community in Ganadougou, Mali: A Cross-Sectional Study

Dyslipidemia is a disorder where abnormally lipid concentrations circulate in the bloodstream. The disorder is common in type 2 diabetics (T2D) and is linked with T2D comorbidities, particularly cardiovascular disease. Dyslipidemia in T2D is typically characterized by elevated plasma triglyceride and low high-density lipoprotein cholesterol (HDL-C) levels. There is a significant gap in the literature regarding dyslipidemia in rural parts of Africa, where lipid profiles may not be captured through routine surveillance. This study aimed to characterize the prevalence and demo-graphic profile of dyslipidemia in T2D in the rural community of Ganadougou, Mali. We performed a cross-sectional study of 104 subjects with T2D in Ganadougou between November 2021 and March 2022. Demographic and lipid profiles were collected through cross-sectional surveys and serological analyses. The overall prevalence of dyslipidemia in T2D patients was 87.5% (91/104), which did not differ by sex (P = .368). High low-density lipoprotein cholesterol (LDL-C) was the most common lipid abnormality (78.9%, [82/104]). Dyslipidemia was associated with age and hypertension status (P = .013 and.036, respectively). High total and high LDL-C parameters were significantly associated with hypertension (P = .029 and .006, respectively). In low-resource settings such as rural Mali, there is a critical need to improve infrastructure for routine dyslipidemia screening to guide its prevention and intervention approaches. The high rates of dyslipidemia observed in Gandadougou, consistent with concomitant increases in cardiovascular diseases in Africa suggest that lipid profile assessments should be incorporated into routine medical care for T2D patients in African rural settings.

Short-term efficacy of microwave ablation in the treatment of liver cancer and its effect on immune function

BACKGROUND Hepatectomy is the first choice for treating liver cancer.However,inflammatory factors,released in response to pain stimulation,may suppress perioperative immune function and affect the prognosis of patients undergoing hepatectomies.AIM To determine the short-term efficacy of microwave ablation in the treatment of liver cancer and its effect on immune function.METHODS Clinical data from patients with liver cancer admitted to Suzhou Ninth People’s Hospital from January 2020 to December 2023 were retrospectively analyzed.Thirty-five patients underwent laparoscopic hepatectomy for liver cancer(liver cancer resection group)and 35 patients underwent medical image-guided microwave ablation(liver cancer ablation group).The short-term efficacy,complications,liver function,and immune function indices before and after treatment were compared between the two groups.RESULTS One month after treatment,19 patients experienced complete remission(CR),8 patients experienced partial remission(PR),6 patients experienced stable disease(SD),and 2 patients experienced disease progression(PD)in the liver cancer resection group.In the liver cancer ablation group,21 patients experienced CR,9 patients experienced PR,3 patients experienced SD,and 2 patients experienced PD.No significant differences in efficacy and complications were detected between the liver cancer ablation and liver cancer resection groups(P>0.05).After treatment,total bilirubin(41.24±7.35 vs 49.18±8.64μmol/L,P<0.001),alanine aminotransferase(30.85±6.23 vs 42.32±7.56 U/L,P<0.001),CD4+(43.95±5.72 vs 35.27±5.56,P<0.001),CD8+(20.38±3.91 vs 22.75±4.62,P<0.001),and CD4+/CD8+(2.16±0.39 vs 1.55±0.32,P<0.001)were significantly different between the liver cancer ablation and liver cancer resection groups.CONCLUSION The short-term efficacy and safety of microwave ablation and laparoscopic surgery for the treatment of liver cancer are similar,but liver function recovers quickly after microwave ablation,and microwave ablation may enhance immune function.

Ganoderma lucidum:a comprehensive review of phytochemistry,efficacy,safety and clinical study

Ganoderma lucidum,one of the most well-known edible fungi,is believed to be very beneficial for longevity and vitality.A long usage history suggests that G.lucidum has various clinical therapeutic effects.And experimental studies have confirmed that G.lucidum has multiple pharmacological effects,including antitumor,anti-microbial,anti-HIV protease,and antidiabetic activity and so on.With the deepening of research,more than 300 compounds have been isolated from G.lucidum.There is an increasing population of G.lucidum-based products,and its international development is expanding.Currently,G.lucidum has drawn much attention to its chemical composition,therapeutic effect,clinical value,and safety.This paper provides a comprehensive review of these aspects to enhance the global promotion of G.lucidum.

An Enhanced Ensemble-Based Long Short-Term Memory Approach for Traffic Volume Prediction

With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service quality.Traffic volume is an influential parameter for planning and operating traffic structures.This study proposed an improved ensemble-based deep learning method to solve traffic volume prediction problems.A set of optimal hyperparameters is also applied for the suggested approach to improve the performance of the learning process.The fusion of these methodologies aims to harness ensemble empirical mode decomposition’s capacity to discern complex traffic patterns and long short-term memory’s proficiency in learning temporal relationships.Firstly,a dataset for automatic vehicle identification is obtained and utilized in the preprocessing stage of the ensemble empirical mode decomposition model.The second aspect involves predicting traffic volume using the long short-term memory algorithm.Next,the study employs a trial-and-error approach to select a set of optimal hyperparameters,including the lookback window,the number of neurons in the hidden layers,and the gradient descent optimization.Finally,the fusion of the obtained results leads to a final traffic volume prediction.The experimental results show that the proposed method outperforms other benchmarks regarding various evaluation measures,including mean absolute error,root mean squared error,mean absolute percentage error,and R-squared.The achieved R-squared value reaches an impressive 98%,while the other evaluation indices surpass the competing.These findings highlight the accuracy of traffic pattern prediction.Consequently,this offers promising prospects for enhancing transportation management systems and urban infrastructure planning.

Mental health and insomnia problems in healthcare workers after the COVID-19 pandemic:A multicenter cross-sectional study

BACKGROUND Healthcare workers(HCWs)are at increased risk of contracting coronavirus disease 2019(COVID-19)as well as worsening mental health problems and insomnia.These problems can persist for a long period,even after the pandemic.However,less is known about this topic.AIM To analyze mental health,insomnia problems,and their influencing factors in HCWs after the COVID-19 pandemic.METHODS This multicenter cross-sectional,hospital-based study was conducted from June 1,2023 to June 30,2023,which was a half-year after the end of the COVID-19 emergency.Region-stratified population-based cluster sampling was applied at the provincial level for Chinese HCWs.Symptoms such as anxiety,depression,and insomnia were evaluated by the Generalized Anxiety Disorder-7,Patient Health Questionnaire-9,and Insomnia Severity Index.Factors influencing the symptoms were identified by multivariable logistic regression.RESULTS A total of 2000 participants were invited,for a response rate of 70.6%.A total of 1412 HCWs[618(43.8%)doctors,583(41.3%)nurses and 211(14.9%)nonfrontline],254(18.0%),231(16.4%),and 289(20.5%)had symptoms of anxiety,depression,and insomnia,respectively;severe symptoms were found in 58(4.1%),49(3.5%),and 111(7.9%)of the participants.Nurses,female sex,and hospitalization for COVID-19 were risk factors for anxiety,depression,and insomnia symptoms;moreover,death from family or friends was a risk factor for insomnia symptoms.During the COVID-19 outbreak,most[1086(76.9%)]of the participating HCWs received psychological interventions,while nearly all[994(70.4%)]of them had received public psychological education.Only 102(7.2%)of the HCWs received individual counseling from COVID-19.CONCLUSION Although the mental health and sleep problems of HCWs were relieved after the COVID-19 pandemic,they still faced challenges and greater risks than did the general population.Identifying risk factors would help in providing targeted interventions.In addition,although a major proportion of HCWs have received public psychological education,individual interventions are still insufficient.

A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.

Development and validation of a circulating tumor DNA-based optimization-prediction model for short-term postoperative recurrence of endometrial cancer

BACKGROUND Endometrial cancer(EC)is a common gynecological malignancy that typically requires prompt surgical intervention;however,the advantage of surgical management is limited by the high postoperative recurrence rates and adverse outcomes.Previous studies have highlighted the prognostic potential of circulating tumor DNA(ctDNA)monitoring for minimal residual disease in patients with EC.AIM To develop and validate an optimized ctDNA-based model for predicting shortterm postoperative EC recurrence.METHODS We retrospectively analyzed 294 EC patients treated surgically from 2015-2019 to devise a short-term recurrence prediction model,which was validated on 143 EC patients operated between 2020 and 2021.Prognostic factors were identified using univariate Cox,Lasso,and multivariate Cox regressions.A nomogram was created to predict the 1,1.5,and 2-year recurrence-free survival(RFS).Model performance was assessed via receiver operating characteristic(ROC),calibration,and decision curve analyses(DCA),leading to a recurrence risk stratification system.RESULTS Based on the regression analysis and the nomogram created,patients with postoperative ctDNA-negativity,postoperative carcinoembryonic antigen 125(CA125)levels of<19 U/mL,and grade G1 tumors had improved RFS after surgery.The nomogram’s efficacy for recurrence prediction was confirmed through ROC analysis,calibration curves,and DCA methods,highlighting its high accuracy and clinical utility.Furthermore,using the nomogram,the patients were successfully classified into three risk subgroups.CONCLUSION The nomogram accurately predicted RFS after EC surgery at 1,1.5,and 2 years.This model will help clinicians personalize treatments,stratify risks,and enhance clinical outcomes for patients with EC.

The growth ofβphase in Mg-Gd-Y-Ni alloy by experimental and first-principles study

The paper reports on the atomic investigation aboutβphase in Mg_(96)Gd_(2)Y_(1)Ni_(1) alloy by using the first-principles study and the high-angle annular dark-field scanning transmission electron microscope(HAADF-STEM)corrected by atomic Cs.By using HAADF-STEM,the rectangularβphases were observed in the underage and peak aging stages in Mg_(96)Gd_(2)Y_(1)Ni_(1) alloy.Theβphase could be precipitated from the previously precipitatedβphase,and theβphase grew in steps when it was precipitated.A special transition structure of three atomic layer thicknesses was first observed at the edge of theβphase and the structure of this interface is probably as theβ/Mg_(1) interface for the analysis of thermodynamic characterization and electronic characterization.Theβ'phase and theβ_(H) structure were precipitated only at the edge of the length directions of theβphase.Theβ'phase continues to grow into aβphase directly without the formation ofβ_(1) phase,resulting in an increase in the length of theβphase,which is discovered for the first time.

Pharmacokinetics and Bioequivalence of Dienogest in Healthy Bangladeshi Female Volunteers: An Open-Label, Single-Dose, Randomized, Two-Way Crossover Study

Background: Dienogest is a potential treatment for pelvic pain associated with endometriosis, a condition of significant concern in gynaecology. The current study was conducted as a crossover-randomized bioequivalence assessment of two oral Dienogest 2 mg formulations, aiming to provide valuable insights for healthcare professionals and researchers in this field. Objective: The primary aim of this research was to evaluate and compare the pharmacokinetic characteristics of Dienogest 2 mg tablets. Dinogest (Dienogest 2 mg) tablets, manufactured by Nuvista Pharma Limited in Bangladesh, and Visanne (Dienogest 2 mg) tablets, manufactured by Bayer Pharma in Germany, were the test and reference formulations, respectively. Materials and Method: The study was an open-label, balanced, randomized, two treatments, two sequences, two periods, two-way crossover, laboratory blind, single oral dose bioequivalence study conducted in healthy adult females under fasting conditions. The study was carried out on 13 healthy, non-pregnant female subjects, and all the subjects completed both study periods with a 15-day washout in between. Randomization was used to assign the test and reference formulations to the subjects. Following each oral administration, a series of blood samples were obtained at different time intervals from pre-dose to 72 hours post-dose and analyzed for Dienogest concentrations using a validated bio-analytical method. A standard non-compartmental model was used to analyze the pharmacokinetic parameters. The primary pharmacokinetic parameters were peak plasma drug concentration (Cmax), the area under the plasma concentration-time curve from time zero to time t (AUC0–t), and AUC from t = 0 to infinity (AUC0–∞). The other PK parameters included time to reach Cmax (Tmax), terminal elimination rate constant (Kel), and half-life (t1/2). Result: The ratios and 90% CI for the geometric mean test/reference were 95.53% (86.70% - 105.26%) for Cmax, 101.75% (95.42% - 108.49%) for AUC0−t, and 101.54% (95.59%% - 107.87%) for AUC0−∞. The formulations were bioequivalent since the 90% CIs for the geometric mean test/reference ratios were 80% to 125%, according to the predetermined range of US Food and Drug Administration (FDA) requirements. Conclusion: This single-dose investigation shows that the Dienogest test and reference formulations exhibited a rate and degree of absorption that met the regulatory requirements for bioequivalence.

Integrating Transformer and Bidirectional Long Short-Term Memory for Intelligent Breast Cancer Detection from Histopathology Biopsy Images

Breast cancer is a significant threat to the global population,affecting not only women but also a threat to the entire population.With recent advancements in digital pathology,Eosin and hematoxylin images provide enhanced clarity in examiningmicroscopic features of breast tissues based on their staining properties.Early cancer detection facilitates the quickening of the therapeutic process,thereby increasing survival rates.The analysis made by medical professionals,especially pathologists,is time-consuming and challenging,and there arises a need for automated breast cancer detection systems.The upcoming artificial intelligence platforms,especially deep learning models,play an important role in image diagnosis and prediction.Initially,the histopathology biopsy images are taken from standard data sources.Further,the gathered images are given as input to the Multi-Scale Dilated Vision Transformer,where the essential features are acquired.Subsequently,the features are subjected to the Bidirectional Long Short-Term Memory(Bi-LSTM)for classifying the breast cancer disorder.The efficacy of the model is evaluated using divergent metrics.When compared with other methods,the proposed work reveals that it offers impressive results for detection.