Dynamic Economic Scheduling with Self-Adaptive Uncertainty in Distribution Network Based on Deep Reinforcement Learning

Traditional optimal scheduling methods are limited to accurate physical models and parameter settings, which aredifficult to adapt to the uncertainty of source and load, and there are problems such as the inability to make dynamicdecisions continuously. This paper proposed a dynamic economic scheduling method for distribution networksbased on deep reinforcement learning. Firstly, the economic scheduling model of the new energy distributionnetwork is established considering the action characteristics of micro-gas turbines, and the dynamic schedulingmodel based on deep reinforcement learning is constructed for the new energy distribution network system with ahigh proportion of new energy, and the Markov decision process of the model is defined. Secondly, Second, for thechanging characteristics of source-load uncertainty, agents are trained interactively with the distributed networkin a data-driven manner. Then, through the proximal policy optimization algorithm, agents adaptively learn thescheduling strategy and realize the dynamic scheduling decision of the new energy distribution network system.Finally, the feasibility and superiority of the proposed method are verified by an improved IEEE 33-node simulationsystem.

Formal Modeling of Self-Adaptive Resource Scheduling in Cloud

A self-adaptive resource provisioning on demand is a critical factor in cloud computing.The selection of accurate amount of resources at run time is not easy due to dynamic nature of requests.Therefore,a self-adaptive strategy of resources is required to deal with dynamic nature of requests based on run time change in workload.In this paper we proposed a Cloud-based Adaptive Resource Scheduling Strategy(CARSS)Framework that formally addresses these issues and is more expressive than traditional approaches.The decision making in CARSS is based on more than one factors.TheMAPE-K based framework determines the state of the resources based on their current utilization.Timed-Arc Petri Net(TAPN)is used to model system formally and behaviour is expressed in TCTL,while TAPAAL model checker verifies the underline properties of the system.

Self-adaptive bulk/surface engineering of Bi_(x)O_(y)Br_(z) towards enhanced photocatalysis:Current status and future challenges

The bulk/surface states of semiconductor photocatalysts are imperative parameters to maneuver their performance by significantly affecting the key processes of photocatalysis including light absorption,separation of charge carrier,and surface site reaction.Recent years have witnessed the encouraging progress of self-adaptive bulk/surface engineered Bi_(x)O_(y)Br_(z) for photocatalytic applications spanning various fields.However,despite the maturity of current research,the interaction between the bulk/surface state and the performance of Bi_(x)O_(y)Br_(z) has not yet been fully understood and highlighted.In this regard,a timely tutorial overview is quite urgent to summarize the most recent key progress and outline developing obstacles in this exciting area.Herein,the structural characteristics and fundamental principles of Bi_(x)O_(y)Br_(z)for driving photocatalytic reaction as well as related key issues are firstly reviewed.Then,we for the first time summarized different self-adaptive engineering processes over Bi_(x)O_(y)Br_(z)followed by a classification of the generation approaches towards diverse Bi_(x)O_(y)Br_(z)materials.The features of different strategies,the up-to-date characterization techniques to detect bulk/surface states,and the effect of bulk/surface states on improving the photoactivity of Bi_(x)O_(y)Br_(z)in expanded applications are further discussed.Finally,the present research status,challenges,and future research opportunities of self-adaptive bulk/surface engineered Bi_(x)O_(y)Br_(z)are prospected.It is anticipated that this critical review can trigger deeper investigations and attract upcoming innovative ideas on the rational design of Bi_(x)O_(y)Br_(z)-based photocatalysts.

A WSN Node Fault Diagnosis Model Based on BRB with Self-Adaptive Quality Factor

Wireless sensor networks (WSNs) operate in complex and harshenvironments;thus, node faults are inevitable. Therefore, fault diagnosis ofthe WSNs node is essential. Affected by the harsh working environment ofWSNs and wireless data transmission, the data collected by WSNs containnoisy data, leading to unreliable data among the data features extracted duringfault diagnosis. To reduce the influence of unreliable data features on faultdiagnosis accuracy, this paper proposes a belief rule base (BRB) with a selfadaptivequality factor (BRB-SAQF) fault diagnosis model. First, the datafeatures required for WSN node fault diagnosis are extracted. Second, thequality factors of input attributes are introduced and calculated. Third, themodel inference process with an attribute quality factor is designed. Fourth,the projection covariance matrix adaptation evolution strategy (P-CMA-ES)algorithm is used to optimize the model’s initial parameters. Finally, the effectivenessof the proposed model is verified by comparing the commonly usedfault diagnosis methods for WSN nodes with the BRB method consideringstatic attribute reliability (BRB-Sr). The experimental results show that BRBSAQFcan reduce the influence of unreliable data features. The self-adaptivequality factor calculation method is more reasonable and accurate than thestatic attribute reliability method.

Genetically modified pigs:Emerging animal models for hereditary hearing loss

Hereditary hearing loss(HHL),a genetic disorder that impairs auditory function,significantly affects quality of life and incurs substantial economic losses for society.To investigate the underlying causes of HHL and evaluate therapeutic outcomes,appropriate animal models are necessary.Pigs have been extensively used as valuable large animal models in biomedical research.In this review,we highlight the advantages of pig models in terms of ear anatomy,inner ear morphology,and electrophysiological characteristics,as well as recent advancements in the development of distinct genetically modified porcine models of hearing loss.Additionally,we discuss the prospects,challenges,and recommendations regarding the use pig models in HHL research.Overall,this review provides insights and perspectives for future studies on HHL using porcine models.

Hemoglobin loss method calculates blood loss during pancreaticoduodenectomy and predicts bleeding-related risk factors

BACKGROUND The common clinical method to evaluate blood loss during pancreaticoduoden-ectomy(PD)is visual inspection,but most scholars believe that this method is extremely subjective and inaccurate.Currently,there is no accurate,objective me-thod to evaluate the amount of blood loss in PD patients.We retrospectively analyzed the clinical data of 341 patients who underwent PD in Shandong Provincial Hospital from March 2017 to February 2019.According to different surgical methods,they were divided into an open PD(OPD)group and a laparoscopic PD(LPD)group.The differences and correlations between the in-traoperative estimation of blood loss(IEBL)obtained by visual inspection and the intraoperative calculation of blood loss(ICBL)obtained using the Hb loss method were analyzed.ICBL,IEBL and perioperative calculation of blood loss(PCBL)were compared between the two groups,and single-factor regression analysis was performed.RESULTS There was no statistically significant difference in the preoperative general patient information between the two groups(P>0.05).PD had an ICBL of 743.2(393.0,1173.1)mL and an IEBL of 100.0(50.0,300.0)mL(P<0.001).There was also a certain correlation between the two(r=0.312,P<0.001).Single-factor analysis of ICBL showed that a history of diabetes[95%confidence interval(CI):53.82-549.62;P=0.017]was an independent risk factor for ICBL.In addition,the single-factor analysis of PCBL showed that body mass index(BMI)(95%CI:0.62-76.75;P=0.046)and preoperative total bilirubin>200μmol/L(95%CI:7.09-644.26;P=0.045)were independent risk factors for PCBL.The ICBLs of the LPD group and OPD group were 767.7(435.4,1249.0)mL and 663.8(347.7,1138.2)mL,respectively(P>0.05).The IEBL of the LPD group 200.0(50.0,200.0)mL was slightly greater than that of the OPD group 100.0(50.0,300.0)mL(P>0.05).PCBL was greater in the LPD group than the OPD group[1061.6(612.3,1632.3)mL vs 806.1(375.9,1347.6)mL](P<0.05).CONCLUSION The ICBL in patients who underwent PD was greater than the IEBL,but there is a certain correlation between the two.The Hb loss method can be used to evaluate intraoperative blood loss.A history of diabetes,preoperative bilirubin>200μmol/L and high BMI increase the patient's risk of bleeding.

Automated Actuarial Data Analytics-Based Inflation Adjusted Frequency Severity Loss Reserving Model

In this paper, the Automated Actuarial Loss Reserving Model is developed and extended using machine learning. The traditional actuarial reserving techniques are no longer compatible with the increase in technological advancement currently at hand. As a result, the development of the alternative Artificial Intelligence Based Automated Actuarial Loss Reserving Methodology which captures diverse risk profiles for various policyholders through augmenting the Micro Finance services, Auto Insurance Services and Both Services lines of business on the same platform through the computation of the Comprehensive Automated Actuarial Loss Reserves (CAALR) has been implemented in this paper. The introduction of the four further types of actuarial loss reserves to those existing in the actuarial literature seems to significantly reduce lapse rates, reduce the reinsurance costs as well as expenses and outgo. As a matter of consequence, this helps to bring together a combination of new and existing policyholders in the insurance company. The frequency severity models have been extended in this paper using ten machine learning algorithms which ultimately leads to the derivation of the proposed machine learning-based actuarial loss reserving model which remarkably performed well when compared to the traditional chain ladder actuarial reserving method using simulated data.

In-situ interfacial passivation and self-adaptability synergistically stabilizing all-solid-state lithium metal batteries

The function of solid electrolytes and the composition of solid electrolyte interphase(SEI)are highly significant for inhibiting the growth of Li dendrites.Herein,we report an in-situ interfacial passivation combined with self-adaptability strategy to reinforce Li_(0.33)La_(0.557)TiO_(3)(LLTO)-based solid-state batteries.Specifically,a functional SEI enriched with LiF/Li_(3)PO_(4) is formed by in-situ electrochemical conversion,which is greatly beneficial to improving interface compatibility and enhancing ion transport.While the polarized dielectric BaTiO_(3)-polyamic acid(BTO-PAA,BP)film greatly improves the Li-ion transport kinetics and homogenizes the Li deposition.As expected,the resulting electrolyte offers considerable ionic conductivity at room temperature(4.3 x 10~(-4)S cm^(-1))and appreciable electrochemical decomposition voltage(5.23 V)after electrochemical passivation.For Li-LiFePO_(4) batteries,it shows a high specific capacity of 153 mA h g^(-1)at 0.2C after 100 cycles and a long-term durability of 115 mA h g^(-1)at 1.0 C after 800 cycles.Additionally,a stable Li plating/stripping can be achieved for more than 900 h at 0.5 mA cm^(-2).The stabilization mechanisms are elucidated by ex-situ XRD,ex-situ XPS,and ex-situ FTIR techniques,and the corresponding results reveal that the interfacial passivation combined with polarization effect is an effective strategy for improving the electrochemical performance.The present study provides a deeper insight into the dynamic adjustment of electrode-electrolyte interfacial for solid-state lithium batteries.

Numerical study of alpha particle loss with toroidal field ripple based on CFETR steady-state scenario

Effects of plasma equilibrium parameters on the alpha particle loss with the toroidal field ripple based on the CFETR steady-state scenario have been numerically investigated by the orbit-following code GYCAVA. It is found that alpha particle losses decrease and loss regions become narrower with the plasma current increasing or with the magnetic field decreasing. It is because the ripple stochastic transport and the ripple well loss of alpha particle are reduced with the safety factor decreasing. Decrease of the plasma density and temperature can reduce alpha particle losses due to enhancement of the slowing-down effect. The direction of the toroidal magnetic field can significantly affect heat loads induced by lost alpha particle. The vertical asymmetry of heat loads induced by the clockwise and counter-clockwise toroidal magnetic fields are due to the fact that the ripple distribution is asymmetric about the mid-plane, which can be explained by the typical orbits of alpha particle. The maximal heat load of alpha particle for the clockwise toroidal magnetic field is much smaller than that for the counter-clockwise one.

Insights into the mechanism of L-malic acid on drip loss of chicken meat under commercial conditions

Background A deterioration in the meat quality of broilers has attracted much more attention in recent years.L-malic acid(MA)is evidenced to decrease meat drip loss in broilers,but the underlying molecular mechanisms are still unclear.It’s also not sure whether the outputs obtained under experimental conditions can be obtained in a com-mercial condition.Here,we investigated the effects and mechanisms of dietary MA supplementation on chicken meat drip loss at large-scale rearing.Results Results showed that the growth performance and drip loss were improved by MA supplementation.Meat metabolome revealed that L-2-aminoadipic acid,β-aminoisobutyric acid,eicosapentaenoic acid,and nicotinamide,as well as amino acid metabolism pathways connected to the improvements of meat quality by MA addition.The transcriptome analysis further indicated that the effect of MA on drip loss was also related to the proper immune response,evidenced by the enhanced B cell receptor signaling pathway,NF-κB signaling pathway,TNF signaling pathway,and IL-17 signaling pathway.Conclusions We provided evidence that MA decreased chicken meat drip loss under commercial conditions.Metabolome and transcriptome revealed a comprehensive understanding of the underlying mechanisms.Together,MA could be used as a promising dietary supplement for enhancing the water-holding capacity of chicken meat.

Machine learning for carbonate formation drilling: Mud loss prediction using seismic attributes and mud loss records

Due to the complexity and variability of carbonate formation leakage zones, lost circulation prediction and control is one of the major challenges of carbonate drilling. It raises well-control risks and production expenses. This research utilizes the H oilfield as an example, employs seismic features to analyze mud loss prediction, and produces a complete set of pre-drilling mud loss prediction solutions. Firstly, 16seismic attributes are calculated based on the post-stack seismic data, and the mud loss rate per unit footage is specified. The sample set is constructed by extracting each attribute from the seismic trace surrounding 15 typical wells, with a ratio of 8:2 between the training set and the test set. With the calibration results for mud loss rate per unit footage, the nonlinear mapping relationship between seismic attributes and mud loss rate per unit size is established using the mixed density network model.Then, the influence of the number of sub-Gausses and the uncertainty coefficient on the model's prediction is evaluated. Finally, the model is used in conjunction with downhole drilling conditions to assess the risk of mud loss in various layers and along the wellbore trajectory. The study demonstrates that the mean relative errors of the model for training data and test data are 6.9% and 7.5%, respectively, and that R2is 90% and 88%, respectively, for training data and test data. The accuracy and efficacy of mud loss prediction may be greatly enhanced by combining 16 seismic attributes with the mud loss rate per unit footage and applying machine learning methods. The mud loss prediction model based on the MDN model can not only predict the mud loss rate but also objectively evaluate the prediction based on the quality of the data and the model.

An Improved Solov2 Based on Attention Mechanism and Weighted Loss Function for Electrical Equipment Instance Segmentation

The current existing problem of deep learning framework for the detection and segmentation of electrical equipment is dominantly related to low precision.Because of the reliable,safe and easy-to-operate technology provided by deep learning-based video surveillance for unmanned inspection of electrical equipment,this paper uses the bottleneck attention module(BAM)attention mechanism to improve the Solov2 model and proposes a new electrical equipment segmentation mode.Firstly,the BAM attention mechanism is integrated into the feature extraction network to adaptively learn the correlation between feature channels,thereby improving the expression ability of the feature map;secondly,the weighted sum of CrossEntropy Loss and Dice loss is designed as the mask loss to improve the segmentation accuracy and robustness of the model;finally,the non-maximal suppression(NMS)algorithm to better handle the overlap problem in instance segmentation.Experimental results show that the proposed method achieves an average segmentation accuracy of mAP of 80.4% on three types of electrical equipment datasets,including transformers,insulators and voltage transformers,which improve the detection accuracy by more than 5.7% compared with the original Solov2 model.The segmentation model proposed can provide a focusing technical means for the intelligent management of power systems.

Navigating Silence: A Comprehensive Review of Parental Roles in the Rehabilitation of Children with Hearing Loss

This narrative literature review delves into the multifaceted realm of parental involvement in the rehabilitation of children with permanent hearing loss. While existing research has made strides in elucidating parental roles in this context, critical gaps persist, necessitating a comprehensive exploration to inform future endeavors. Our review synthesizes a wide array of studies, identifying these gaps and emphasizing the significance of addressing them. Themes emerging from the literature include the varying degrees of parental engagement, the impact of cultural and socio-economic factors, and the challenges faced by families navigating rehabilitation processes. The synthesis of this literature not only highlights the current state of knowledge but also provides a roadmap for future research efforts. By addressing these gaps, we aim to contribute to a more nuanced understanding of parental involvement in the rehabilitation of children with permanent hearing loss, ultimately fostering improved support systems and holistic care for affected families.

Understanding the correlation between energy-state mismatching and open-circuit voltage loss in bulk heterojunction solar cells

Photoinduced intermolecular charge transfer(PICT)determines the voltage loss in bulk heterojunction(BHJ)organic photovoltaics(OPVs),and this voltage loss can be minimized by inducing efficient PICT,which requires energy-state matching between the donor and acceptor at the BHJ interfaces.Thus,both geometrically and energetically accessible delocalized state matching at the hot energy level is crucial for achieving efficient PICT.In this study,an effective method for quantifying the hot state matching of OPVs was developed.The degree of energy-state matching between the electron donor and acceptor at BHJ interfaces was quantified using a mismatching factor(MF)calculated from the modified optical density of the BHJ.Furthermore,the correlation between the open-circuit voltage(Voc)of the OPV device and energy-state matching at the BHJ interface was investigated using the calculated MF.The OPVs with small absolute MF values exhibited high Voc values.This result clearly indicates that the energy-state matching between the donor and acceptor is crucial for achieving a high Voc in OPVs.Because the MF indicates the degree of energy-state matching,which is a critical factor for suppressing energy loss,it can be used to estimate the Voc loss in OPVs.

A Loss-model-based Efficiency Optimization Control Method for Induction Traction System of High-speed Train under Emergency Self-propelled Mode

Increasing attention has been paid to the efficiency improvement of the induction traction system of high-speed trains due to the high demand for energy saving. In emergency self-propelled mode, however, the dc-link voltage and the traction power of the motor are significantly reduced, resulting in decreased traction efficiency due to the low load and low speed operations. Aiming to tackle this problem, a novel efficiency improved control method is introduced to the emergency mode of high-speed train traction system in this paper. In the proposed method, a total loss model of induction motor considering the behaviors of both iron and copper loss is established. An improved iterative algorithm with decreased computational burden is then introduced, resulting in a fast solving of the optimal flux reference for loss minimization at each control period. In addition, considering the parameter variation problem due to the low load and low speed operations, a parameter estimation method is integrated to improve the controller's robustness. The effectiveness of the proposed method on efficiency improvement at low voltage and low load conditions is demonstrated by simulated and experimental results.

Modified intratympanic steroid therapy for sudden sensorineural hearing loss via tympanic tube and gelfoam as a salvage treatment

Background: Sudden sensorineural hearing loss(SSNHL) is a prevalent emergency in ear, nose, and throat practice. Previous studies have demonstrated that intratympanic steroid therapy(IST) can serve as a salvage treatment for SSNHL after the failure of systemic steroid therapy(SST).Objective: This study aimed to analyze the efficacy of modified IST involving the insertion of a tympanic tube and gelfoam as a salvage treatment for patients with SSNHL, and to explore its associated factors.Methods: Totally, 74 patients who were aged 22–81 years with SSNHL were enrolled and allocated to either the control group(n = 25) or the treatment group(n = 49) based on their treatment modalities. All patients received SST lasting for at least 7 days. Subsequently, patients in the treatment group, after SST failure, underwent IST twice a week for 2–6 weeks, while the control group did not. Efficacy was assessed by the improvement in pure tone average at the affected frequency at the beginning and end of IST.Results: Hearing improvement in all patients after IST in the treatment group was 9.71 ± 14.84 dB, with significant improvement at affected frequencies(250-8000 Hz) compared with the control group(P < 0.05). The findings indicated the duration from the onset of SSNHL to the beginning of IST as an independent factor for pure tone average improvement after treatment(P = 0.002), whereas age, duration of SST, and time of IST were not(P > 0.05).Conclusion: The modified IST was demonstrated to be a safe and effective method as a salvage treatment for SSNHL. This study explored the efficacy of a modified IST approach, incorporating the utilization of tympanic tubes and gelfoam as key components. The findings underscore the advantages of gelfoam as a strategic drug carrier placed in the round window niche. By minimizing drug loss, extending action time, and increasing perilymph concentration, gelfoam enhances the therapeutic impact of IST, contributing to improved hearing outcomes in patients with SSNHL.

Loss of heterozygosity for chromosomes 16q in Wilms tumors predicts outcomes:A meta-analysis

BACKGROUND The research findings suggest that the prognosis of children with Wilms tumor(WT)is affected by various factors.Some scholars have indicated that loss of heterozygosity(LOH)on chromosome 16q is associated with a poor prognosis in patients with WT.AIM To further elucidate this relationship,we conducted a meta-analysis.METHODS This meta-analysis was registered in INPLASY(INPLASY2023100060).We systematically searched databases including Embase,PubMed,Web of Science,Cochrane,and Google Scholar up to May 31,2020,for randomized trials reporting any intrapartum fetal surveillance approach.The meta-analysis was performed within a frequentist framework,and the quality and network inconsistency of trials were assessed.Odds ratios and 95%CIs were calculated to report the relationship between event-free survival and 16q LOH in patients with WT.RESULTS Eleven cohort studies were included in this meta-analysis to estimate the relationship between event-free survival and 16q LOH in patients with WT(I^(2)=25%,P<0.001).As expected,16q LOH can serve as an effective predictor of eventfree survival in patients with WT(risk ratio=1.95,95%CI:1.52–2.49,P<0.001).CONCLUSION In pediatric patients with WT,there exists a partial correlation between 16q LOH and an unfavorable treatment prognosis.Clinical detection of 16q chromosome LOH warrants increased attention to the patient’s prognosis.

Weight regain after intragastric balloon for pre-surgical weight loss

BACKGROUND Over one-third of Americans carry the diagnosis of obesity,many also with obesity-related comorbidities.This can place patients at increased risk of operative and postoperative complications.The intragastric balloon has been shown to aid in minor weight loss,however its weight recidivism in patients requiring short interval weight loss has not been well studied.AIM To evaluate weight loss,ability to undergo successful elective surgery after intragastric balloon placement,and weight management after balloon removal.METHODS This study is a retrospective review of patients in a single academic institution undergoing intragastric balloon placement from 2019-2023 to aid in weight loss prior to undergoing elective surgery.Clinical outcomes including weight loss,duration of balloon placement,successful elective surgery,weight regain postballoon and post-procedure complications were assessed.Exclusion criteria included those with balloon in place at time of study.RESULTS Thirty-three patients completed intragastric balloon therapy from 2019-2023 as a bridge to elective surgery.All patients were required to participate in a 12-month weight management program to be eligible for balloon therapy.Elective surgeries included incisional hernia repair,umbilical hernia repair,inguinal hernia repair,and knee and hip replacements.The average age at placement was 53 years±11 years,majority(91%)were male.The average duration of intragastric balloon therapy was 186 days±41 days.The average weight loss was 14.0 kg±7.4 kg and with an average percent excess body weight loss of 30.0%(7.9%-73.6%).Over half of the patients(52.0%)achieved the goal of 30-50 lbs(14-22 kg)weight loss.Twenty-one patients(64%)underwent their intended elective surgery,2 patients(6%)deferred surgery due to symptom relief with weight loss alone.Twenty-one of the patients(64%)have documented weights in 3 months after balloon removal,in these patients the majority(76%)gained weight after balloon removed.In patients with weight regain at 3 months,they averaged 5.8 kg after balloon removal in the first 3 months,this averaged 58.4%weight regain of the initial weight lost.CONCLUSION Intragastric balloon placement is an option for short-term weight management,as a bridge to elective surgery in patients with body mass index(BMI)>35.Patients lost an average of 14 kg with the balloon,allowing two-thirds of patients to undergo elective surgery at a healthy BMI.However,most patients regained an average of 58%of the original weight lost after balloon removal.The intragastric balloon successfully serves as a tool for rapid weight loss,though patients must be educated on the risks including weight regain.

Cinobufotalin prevents bone loss induced by ovariectomy in mice through the BMPs/SMAD and Wnt/β-catenin signaling pathways

Background:Osteoporosis is a chronic bone disease characterized by bone loss and decreased bone strength.However,current anti-resorptive drugs carry a risk of various complications.The deep learning-based efficacy prediction system(DLEPS)is a forecasting tool that can effectively compete in drug screening and prediction based on gene expression changes.This study aimed to explore the protective effect and potential mechanisms of cinobufotalin(CB),a traditional Chinese medicine(TCM),on bone loss.Methods:DLEPS was employed for screening anti-osteoporotic agents according to gene profile changes in primary osteoporosis.Micro-CT,histological and morphological analysis were applied for the bone protective detection of CB,and the osteogenic differentiation/function in human bone marrow mesenchymal stem cells(hBMMSCs)were also investigated.The underlying mechanism was verified using qRT-PCR,Western blot(WB),immunofluorescence(IF),etc.Results:A safe concentration(0.25mg/kg in vivo,0.05μM in vitro)of CB could effectively preserve bone mass in estrogen deficiency-induced bone loss and promote osteogenic differentiation/function of hBMMSCs.Both BMPs/SMAD and Wnt/β-catenin signaling pathways participated in CB-induced osteogenic differentiation,further regulating the expression of osteogenesis-associated factors,and ultimately promoting osteogenesis.Conclusion:Our study demonstrated that CB could significantly reverse estrogen deficiency-induced bone loss,further promoting osteogenic differentiation/function of hBMMSCs,with BMPs/SMAD and Wnt/β-catenin signaling pathways involved.

Systemic Inflammation Response Index and weight loss as prognostic factors in metastatic pancreatic cancer: A concept study from the PANTHEIA-SEOM trial

BACKGROUND The prognostic value of the Systemic Inflammation Response Index(SIRI)in advanced pancreatic cancer is recognized,but its correlation with patients´nutritional status and outcomes remains unexplored.AIM To study the prognostic significance of SIRI and weight loss in metastatic pancreatic cancer.METHODS The PANTHEIA-Spanish Society of Medical Oncology(SEOM)study is a multicentric(16 Spanish hospitals),observational,longitudinal,non-interventional initiative,promoted by the SEOM Real World-Evidence work group.This pilot study sought to analyze the association between weight loss and inflammatory status as defined by SIRI.The cohort stems from a proof-of-concept pilot study conducted at one of the coordinating centers.Patients with pathologically confirmed metastatic pancreatic adenocarcinoma,treated from January 2020 to January 2023,were included.The index was calculated using the product of neutrophil and monocyte counts,divided by lymphocyte counts,obtained within 15 days before initiation chemotherapy.This study evaluated associations between overall survival(OS),SIRI and weight loss.RESULTS A total of 50 patients were included.66%of these patients were male and the median age was 66 years.Metastasis sites:36%liver,12%peritoneal carcinomatosis,10%lung,and 42%multiple locations.Regarding the first line palliative chemotherapy treatments:50%received gemcitabine plus nab-paclitaxel;28%,modified fluorouracil,leucovorin,irinotecan and oxaliplatin,and 16%were administered gemcitabine.42%had a weight loss>5%in the three months(mo)preceding diagnosis.21 patients with a SIRI≥2.3×10^(3)/L exhibited a trend towards a lower median OS compared to those with a SIRI<2.3×10^(3)/L(4 vs 18 mo;P<0.000).Among 21 patients with>5%weight loss before diagnosis,the median OS was 6 mo,in contrast to 19 mo for those who did not experience such weight loss(P=0.003).Patients with a weight loss>5%showed higher SIRI levels.This difference was statistically significant(P<0.000).For patients with a SIRI<2.3×10^(3)/L,those who did not lose>5%of their weight had an OS of 20 mo,compared to 11 mo for those who did(P<0.001).No association was found between carbohydrate antigen 19-9 levels≥1000 U/mL and weight loss.CONCLUSION A higher SIRI was correlated with decreased survival rates in patients with metastatic pancreatic cancer and associated with weight loss.An elevated SIRI is suggested as a predictor of survival,emphasizing the need for prospective validation in the upcoming PANTHEIA-SEOM study.