Enhancing precision medicine: a nomogram for predicting platinum resistance in epithelial ovarian cancer.

BACKGROUND: This study aimed to develop a novel nomogram that can accurately estimate platinum resistance to enhance precision medicine in epithelial ovarian cancer(EOC). METHODS: EOC patients who received primary therapy at the General Hospital of Ningxia Medical University between January 31, 2019, and June 30, 2021 were included. The LASSO analysis was utilized to screen the variables which contained clinical features and platinum-resistance gene immunohistochemistry scores. A nomogram was created after the logistic regression analysis to develop the prediction model. The consistency index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to assess the nomogram's performance. RESULTS: The logistic regression analysis created a prediction model based on 11 factors filtered down by LASSO regression. As predictors, the immunohistochemical scores of CXLC1, CXCL2, IL6, ABCC1, LRP, BCL2, vascular tumor thrombus, ascites cancer cells, maximum tumor diameter, neoadjuvant chemotherapy, and HE4 were employed. The C-index of the nomogram was found to be 0.975. The nomogram's specificity is 95.35% and its sensitivity, with a cut-off value of 165.6, is 92.59%, as seen by the ROC curve. After the nomogram was externally validated in the test cohort, the coincidence rate was determined to be 84%, and the ROC curve indicated that the nomogram's AUC was 0.949. CONCLUSION: A nomogram containing clinical characteristics and platinum gene IHC scores was developed and validated to predict the risk of EOC platinum resistance.

Related Clinical Factors of Platinum-Based Chemotherapy Resistance in Patients with Epithelial Ovarian Cancer.

OBJECTIVE: Ovarian cancer is the second most common malignancy in women, but it is a fatal gynecological tumor. Although it has a standard treatment regimen, resistance to chemotherapy makes patients more prone to early recurrence, leading to poor survival rates. Therefore, this study investigated factors related to platinum resistance through a complete analysis of clinical data. DESIGN: Clinical data of patients with ovarian cancer were collected, and the patients were categorized into platinum-sensitive and platinum-resistant groups. By comparing the differences in clinical data between the groups, the key factors affecting platinum resistance were analyzed. PARTICIPANTS/MATERIALS, SETTING, METHODS: We collected the clinical data of patients with epithelial ovarian cancer (EOC) who were admitted to the Department of Oncology of the General Hospital of Ningxia Medical University between January 1, 2019, and December 31, 2020. We conducted univariate and multivariate analyses and evaluated overall survival and progression-free survival using the Kaplan-Meier method. RESULTS: We enrolled 161 patients with EOC, of whom 124 demonstrated platinum sensitivity and 37 demonstrated platinum resistance after the initial platinum-based chemotherapy. Univariate analyses revealed that the International Federation of Gynecology and Obstetrics (FIGO) stage, neoadjuvant chemotherapy, and Fagotti score were associated with an increased risk of platinum resistance for the first recurrence. In multivariate logistic regression analysis, only Fagotti score and neoadjuvant chemotherapy were associated with an increased risk of platinum resistance (odds ratio: 0.372 and 0.328, 95% confidence interval: 0.160-0.863 and 0.141-0.762, p = 0.021 and 0.010, respectively). LIMITATIONS: The sample size of this study was relatively small because of nonstandard treatment of some patients, the absence of clinical data, and failure of follow-up. CONCLUSIONS: Patients with EOC exhibiting platinum resistance had a very poor prognosis. The Fagotti score and neoadjuvant chemotherapy appeared to increase the risk of platinum resistance at first recurrence.

Automatic retinoblastoma screening and surveillance using deep learning.

BACKGROUND: Retinoblastoma is the most common intraocular malignancy in childhood. With the advanced management strategy, the globe salvage and overall survival have significantly improved, which proposes subsequent challenges regarding long-term surveillance and offspring screening. This study aimed to apply a deep learning algorithm to reduce the burden of follow-up and offspring screening. METHODS: This cohort study includes retinoblastoma patients who visited Beijing Tongren Hospital from March 2018 to January 2022 for deep learning algorism development. Clinical-suspected and treated retinoblastoma patients from February 2022 to June 2022 were prospectively collected for prospective validation. Images from the posterior pole and peripheral retina were collected, and reference standards were made according to the consensus of the multidisciplinary management team. A deep learning algorithm was trained to identify "normal fundus", "stable retinoblastoma" in which specific treatment is not required, and "active retinoblastoma" in which specific treatment is required. The performance of each classifier included sensitivity, specificity, accuracy, and cost-utility. RESULTS: A total of 36,623 images were included for developing the Deep Learning Assistant for Retinoblastoma Monitoring (DLA-RB) algorithm. In internal fivefold cross-validation, DLA-RB achieved an area under curve (AUC) of 0.998 (95% confidence interval [CI] 0.986-1.000) in distinguishing normal fundus and active retinoblastoma, and 0.940 (95% CI 0.851-0.996) in distinguishing stable and active retinoblastoma. From February 2022 to June 2022, 139 eyes of 103 patients were prospectively collected. In identifying active retinoblastoma tumours from all clinical-suspected patients and active retinoblastoma from all treated retinoblastoma patients, the AUC of DLA-RB reached 0.991 (95% CI 0.970-1.000), and 0.962 (95% CI 0.915-1.000), respectively. The combination between ophthalmologists and DLA-RB significantly improved the accuracy of competent ophthalmologists and residents regarding both binary tasks. Cost-utility analysis revealed DLA-RB-based diagnosis mode is cost-effective in both retinoblastoma diagnosis and active retinoblastoma identification. CONCLUSIONS: DLA-RB achieved high accuracy and sensitivity in identifying active retinoblastoma from the normal and stable retinoblastoma fundus. It can be used to surveil the activity of retinoblastoma during follow-up and screen high-risk offspring. Compared with referral procedures to ophthalmologic centres, DLA-RB-based screening and surveillance is cost-effective and can be incorporated within telemedicine programs. CLINICAL TRIAL REGISTRATION: This study was registered on ClinicalTrials.gov (NCT05308043).

Design, methodology, and preliminary results of the non-human primates eye study.

PURPOSE: To describe the normative profile of ophthalmic parameters in a healthy cynomolgus monkey colony, and to identify the characteristic of the spontaneous ocular disease non-human primates (NHP) models. METHODS: The NHP eye study was a cross-sectional on-site ocular examination with about 1,000 macaques held in Guangdong Province, southeastern China. The NHPs (Macaca fascicularis, cynomolgus) in this study included middle-aged individuals with a high prevalence of the ocular disease. The NHP eye study (NHPES) performed the information including systematic data and ocular data. Ocular examination included measurement of intraocular pressure (IOP), anterior segment- optical coherence tomography (OCT), slit-lamp examination, fundus photography, autorefraction, electroretinography, etc. Ocular diseases included measurement of refractive error, anisometropia, cataract, pterygium, etc. RESULTS: A total of 1148 subjects were included and completed the ocular examination. The average age was 16.4 ± 4.93 years. Compared to the male participants, the females in the NHPES had shorter axial length and the mean Average retinal nerve fiber layer (RNFL) thickness (except for the nasal quadrants). The mean IOP, anterior chamber depth, lens thickness, axial length, central corneal thickness, choroid thickness and other parameters were similar in each group. CONCLUSION: The NHPES is a unique and high-quality study, this is the first large macaque monkey cohort study focusing on ocular assessment along with comprehensive evaluation. Results from the NHPES will provide important information about the normal range of ophthalmic measurements in NHP.

Effect of Exogenous Plant Growth Regulators and Rejuvenation Measures on the Endogenous Hormone and Enzyme Activity Responses of Acer mono Maxim in Cuttage Rooting.

The cuttage rooting method for Acer species is difficult to achieve a good efficacy as trees maintain good characteristics at the rejuvenation stage, thus improving the rooting of Acer species. The addition of exogenous hormones and rejuvenation can improve the rooting effect of cuttings; however, the specific regulatory mechanism is still unclear. Here, Acer mono Maxim rejuvenation and non-rejuvenation cuttings were used as test subjects, to investigate the effects of exogenous hormones on the activities of endogenous hormones and antioxidant enzymes in the rooting process of young cuttings. The results showed that exogenous growth-regulating substances significantly improved the rooting rate of A. mono. Exogenous hormones naphthylacetic acid (NAA) + indolebutyric acid (IBA) increased the initial levels of the endogenous hormones, indoleacetic acid (IAA) and abscisic acid (ABA), and the enzyme activities of peroxidase (POD) and polyphenol oxidase (PPO). Rejuvenation treatment prolonged the time of increase in ABA content and indoleacetic acid oxidase (IAAO) activity at the root primordium induction stage, while increasing trans-zeatin riboside (ZR) content and decreasing POD enzyme activity in cuttings. These results demonstrate that A. mono cuttings can achieve the purpose of improving the rooting rate by adding the exogenous hormone (NAA + IBA), which is closely related to the changes of endogenous hormone content and enzyme activity, and these changes of A. mono rejuvenation cuttings are different from non-rejuvenation cuttings.

Advances in Polyoxometalates as Electron Mediators for Photocatalytic Dye Degradation.

The increasing concerns over the environment and the growing demand for sustainable water treatment technologies have sparked substantial interest in the field of photocatalytic dye removal. Polyoxometalates (POMs), known for their intricate metal-oxygen anion clusters, have received considerable attention due to their versatile structures, compositions, and efficient facilitation of photo-induced electron transfers. This paper provides an overview of the ongoing research progress in the realm of photocatalytic dye degradation utilizing POMs and their derivatives. The details encompass the compositions of catalysts, catalytic efficacy, and light absorption propensities, and the photocatalytic mechanisms inherent to POM-based materials for dye degradation are exhaustively expounded upon. This review not only contributes to a better understanding of the potential of POM-based materials in photocatalytic dye degradation, but also presents the advancements and future prospects in this domain of environmental remediation.

[A Health Education Program for Home Emergency Management of Acute Complications of Diabetes in the Elderly].

Objective To establish a health education program for home emergency management of acute complications of diabetes in the elderly.Methods The program was drafted by literature review and panel discussion.The final draft was formed after two rounds of correspondence from 13 experts.Results The recovery rate of the two rounds of expert correspondence was 100%,and the expert authority coefficient was 0.98.The Kendall's harmony coefficients of the two rounds of correspondence were 0.263 and 0.212 respectively(both P<0.001).The established health education program included indicators of three categories:early stage of acute complications of diabetes at home(understanding the inducing factors),emergency warning(quick and early identification in case of emergency),and emergency treatment at home.Conclusion The contents of the health education program are systematic and reliable and meet the needs of health education for home emergency management of the elderly with diabetes.

Discovery of new inhibitors against both NF-κB and osteoclastogenesis from in-house library with α, ß-unsaturated-enone fragment.

The α,ß-unsaturated-enone contained natural products have been reported showing NF-κB inhibition effect. It is well known that NF-κB inhibitors can also be used to inhibit osteoclastogenesis. In a continual discovery new agents for anti-osteoclastogenesis, 8 different type compounds with α,ß-unsaturated-enone fragments from our in-house library were evaluated for NF-κB inhibition and anti-osteoclastogenesis. Experimental results indicated five compounds exhibited inhibition of NF-κB signal pathway. Among them, one compound ((E)-2-(4-fluorobenzylidene)-3,4-dihydronaphthalen-1(2H)-one, 6a) simultaneously inhibits both osteoclastogenesis and NF-κB signal pathway. Furthermore, 12 compounds with similar scaffold with 6a were tested for anti-osteoclastogenesis. As a result, 9 compounds inhibited both NF-κB and osteoclastogenesis. Among them, compound 6b is the most potent inhibitor against NF-κB (IC50 = 2.09 µM) and osteoclast differentiation (IC50 = 0.86 µM). Further studies show that compound 6b blocks the phosphorylation of both p65 and IκBα, and suppresses NF-κB targeted gene expression without interfering MAPKs and PI3K/Akt signal transduction pathways. This study demonstrates that we can identify promising synthesized compounds with new scaffolds as therapeutic solutions against osteoclastogenesis inspired by the privileged fragment derived from natural leads.

Astragalus Polysaccharide Protect against Cadmium-Induced Cytotoxicity through the MDA5/NF-κB Pathway in Chicken Peripheral Blood Lymphocytes.

Cadmium (Cd) is a known environmental pollutant that is associated with inflammation, oxidative stress, and cell apoptosis. Astragalus polysaccharide (APS) is a major component of Astragalus membranaceus, a vital qi-reinforcing herb medicine with favorable immuneregulation properties. To study the effect of APS on the inhibition of the cadmium-induced injury of peripheral blood lymphocytes (PBLs) in chickens through the MDA5/NF-κB signaling pathway, PLBs acquired from 15-day-old chickens were divided into control group, Cd group, APS + Cd group, anti-MDA5 mAb + Cd group, BAY 11-7082 (a nuclear factor kappa-light chain-enhancer of activated B cells [NF-κB] inhibitor) +Cd group, APS group, anti-MDA5 mAb group, and BAY 11-7082 group. The transcription levels of melanoma differentiation-associated gene 5 (MDA5), interferon promoter-stimulating factor 1 (IPS-1), NF-κB, and inflammatory factors tumor necrosis factor (TNF)-α, interleukin (IL)-1ß, and IL-6 were measured by quantitative real-time PCR. MDA5 protein expression was measured by western blotting. Levels of malondialdehyde (MDA), glutathione peroxidase (GSH-Px), and superoxide dismutase (SOD) were measured by corresponding antioxidant kit. The morphological change of PBLs was measured by transmission electron microscopy. The results showed that Cd significantly increased the expression of MDA5, IPS-1, NF-κB, and their downstream cytokines, IL-1ß and TNF-α, IL-6 in PLBs. In addition, a high level of MDA was observed in the Cd treatment group; the activities of GSH-Px and SOD were significantly lower in the Cd treatment group than those in controls (p < 0.05). Ultrastructural changes of PBLs showed that Cd promoted autophagy, apoptosis, and necrosis in PBLs. However, APS can efficiently improve Cd-induced cell damage by decreasing the activation of the MDA5 signaling pathway. The effect is consistent with that of anti-MDA5 mAb or/and BAY. The results indicated that APS inhibited Cd-induced cytotoxicity through the regulation of MDA5/NF-κB signaling.

Identification of a G-protein coupled receptor-related gene signature through bioinformatics analysis to construct a risk model for ovarian cancer prognosis.

BACKGROUND: Ovarian cancer (OV) is a common malignant tumor of the female reproductive system with a 5-year survival rate of ∼30 %. Inefficient early diagnosis and prognosis leads to poor survival in most patients. G protein-coupled receptors (GPCRs, the largest family of human cell surface receptors) are associated with OV. We aimed to identify GPCR-related gene (GPCRRG) signatures and develop a novel model to predict OV prognosis. METHOD: We downloaded data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Prognostic GPCRRGs were screened using least absolute shrinkage and selection operator (LASSO) Cox regression analysis, and a prognostic model was constructed. The predictive ability of the model was evaluated by Kaplan-Meier (K-M) survival analysis. The levels of GPCRRGs were examined in normal and OV cell lines using quantitative reverse-Etranscription polymerase chain reaction. The immunological characteristics of the high- and low-risk groups were analyzed using single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT. RESULTS: Based on the risks scores, 17 GPCRRGs were associated with OV prognosis. CXCR4, GPR34, LGR6, LPAR3, and RGS2 were significantly expressed in three OV datasets and enabled accurate OV diagnosis. K-M analysis of the prognostic model showed that it could differentiate high- and low-risk patients, which correspond to poorer and better prognoses, respectively. GPCRRG expression was correlated with immune infiltration rates. CONCLUSIONS: Our prognostic model elaborates on the roles of GPCRRGs in OV and provides a new tool for prognosis and immune response prediction in patients with OV.

[Prediction Model of Groundwater Sulphate Based on Combined Multi-source Spatio-temporal Data].

The accurate prediction of spatial variation trends in groundwater SO42- is of great significance for improving groundwater quality and regional groundwater management level. The multi-source spatio-temporal data such as land cover data, soil parameter data, digital elevation data, and groundwater pH value in the plain area of the Yarkant River Basin in 2011, 2014, 2017, and 2020 were used as characteristic variables to analyze their correlation with groundwater SO42- concentration. To enhance the prediction accuracy, the Bayesian optimization algorithm (BOA) was used to optimize the random forest regression (RFR). Based on the BOA-RFR model, the importance of the characteristic variables was analyzed, the prediction accuracy of the model was evaluated, and the groundwater SO42- prediction map was generated. The results showed that pH value, ground elevation (GE), and percentage of bare land (BAR) in the contribution area were important parameters influencing groundwater hydrochemical composition, which were significantly negatively correlated with groundwater SO42- concentration, and the importance of impact factors for predicting groundwater SO42- concentration exceeded 25 %. The geostatistical interpolation method was used as an auxiliary tool for the predictive modeling of spatial distribution. After adding auxiliary samples, the R2 of groundwater SO42- concentration prediction of the BOA-RFR model was greater than 0.96, and the maximum values of RMSE and MAE were reduced by 4.7 % and 23.8 %, respectively, compared with the minimum values of the model with fewer samples. The SO42- concentration prediction map showed that high SO42- groundwater was enriched in the northeast of the plain area of the Yarkand River Basin, an area that was expanding.

A novel pH-sensitive hemi-cyanine containing tetrahydropyridine ring near-infrared fluorescence probe with lysosome-targeting ability.

In recent years, hemi-cyanine dyes have been widely used as biological probes due to their red-light emission characteristics and high fluorescence quantum yield. In this study, we synthesized a novel hemi-cyanine dye containing a tetrahydropyridine ring. A lysosomal target was introduced into its structure to create a new pH-sensitive near-infrared fluorescent probe that successfully targeted lysosomes. The results showed that when the probe solution was excited at the absorption wavelength of 650 nm, its fluorescence emission wavelength was about 700 nm, and the peak intensity changed with different pH values in a wide range. Therefore, this probe enabled non-invasive detection of changes in the acidic environment of lysosomes in living organisms and showed good imaging capabilities. Moreover, the probe displays high sensitivity and good stability. The theoretical calculation of a probe structure has also been completed to discuss the relationship between structure and property.

Survival benefit of adjuvant chemotherapy after resection of Stage I lung adenocarcinoma containing micropapillary components.

BACKGROUND: The usefulness of postoperative adjuvant chemotherapy (ACT) for patients with stage I lung adenocarcinoma with micropapillary (MIP) components remains unclear. We analyzed whether postoperative ACT could reduce recurrence in patients with stage I lung adenocarcinoma with MIP components, thereby improving their overall survival (OS) and disease-free survival (DFS). METHODS: Data for patients with pathologically confirmed stage I lung adenocarcinoma with MIP components from January 2012 to December 2018 were retrospectively analyzed. OS and DFS were analyzed in groups and subgroups. RESULTS: Overall, 259 patients were enrolled. Patients who received ACT in stage IA showed significantly better survival than did those with no-adjuvant chemotherapy (NACT); (5-year OS 89.4% vs. 73.6%, p < 0.001; 5-year DFS 87.2% vs. 66.0%, p = 0.008). A difference was also observed for in-stage IB patients (5-year OS 82.0% vs. 51.8%, p = 0.001; 5-year DFS 76.0% vs. 41.11 %, p = 0.004). In subgroup analysis based on the proportion of MIP components, patients with 1%-5% MIP components had a significantly better prognosis in the ACT group than in the NACT group (5-year OS 82.4% vs. 66.0%, p = 0.005; 5-year DFS 76.5% vs. 49.1%, p = 0.032). A similar difference was observed for patients with MIP ≥5% (5-year OS 80.7% vs. 47.8%, p = 0.009; 5-year DFS 73.11% vs. 43.5%, p = 0.007). CONCLUSION: Among patients with stage I lung adenocarcinoma with MIP components, those who received ACT showed significant survival benefits compared to those without ACT. Patients with lung adenocarcinoma with MIP components could benefit from ACT when the MIP was ≥1%.

Nature-Inspired Gelatin-Based Adhesive Hydrogel: A Rapid and User-Friendly Solution for Hemostatic Applications.

Conventional hemostatic agents face challenges in achieving rapid hemostasis and effective tissue repair due to limited hemostatic scenarios, suboptimal efficacy, and inadequate adhesion to wet tissues. Drawing inspiration from nature-sourced materials, a gelatin-based adhesive hydrogel (AOT)  is designed, easily prepared and quick to form, driven by Schiff base and multiple hydrogen bonds for applications in arterial and liver bleeding models. AOT exhibits exceptional adhesion to wet tissues (48.67 ± 0.16 kPa) and displays superior hemostatic properties with reduced blood loss and hemostatic time compared to other hydrogels and conventional hemostatic materials. Moreover, AOT exhibits good biocompatibility and biodegradability. In summary, this easily prepared adhesive hydrogel has the potential to supplant traditional hemostatic agents, offering a novel approach to achieve swift sealing of hemostasis and facilitate wound healing and repair in broader application scenarios, owing to its unique advantages.

Research on eco-efficiency measurement, spatiotemporal analysis and prosperity warning based on the three-stage chain network SBM and MS-DDFM.

This paper studies the changes of ecological efficiency (eco-efficiency) boom in China. Firstly, based on the improvement of the three-stage slack-based model (SBM), a hybrid chain network model is used to clarify the internal development structure of eco-efficiency. Then, Taking eco-efficiency as the benchmark indicator, the boom warning indicators are screened by comprehensively considering the correlation analysis of time difference, Kullback-Leibler (K-L) information and peak valley correspondence method. The Markov regime switching dynamic dual factor model (MS-DDFM) is used to fit the leading indicators and consistent indicators in the field of eco-efficiency prosperity. The empirical results show that the sub-efficiencies of the three-stage are not consistent, and most of the years with high efficiency in the second stage. In addition, there are differences and fluctuations of the eco-efficiency in different regions. The value of the eco-efficiency in eastern region is larger than average value of China, while the result is just the opposite for the central and western regions. In general, the eco-efficiency of China is in a prosperous state of operation.

The predictive value of radiomics-based machine learning for peritoneal metastasis in gastric cancer patients: a systematic review and meta-analysis.

Background: For patients with gastric cancer (GC), effective preoperative identification of peritoneal metastasis (PM) remains a severe challenge in clinical practice. Regrettably, effective early identification tools are still lacking up to now. With the popularization and application of radiomics method in tumor management, some researchers try to introduce it into the early identification of PM in patients with GC. However, due to the complexity of radiomics, the value of radiomics method in the early identification of PM in GC patients remains controversial. Therefore, this systematic review was conducted to explore the feasibility of radiomics in the early identification of PM in GC patients. Methods: PubMed, Cochrane, Embase and the Web of Science were comprehensively and systematically searched up to 25 July, 2022 (CRD42022350512). The quality of the included studies was assessed using the radiomics quality score (RQS). To discuss the superiority in diagnostic accuracy of radiomics-based machine learning, a subgroup analysis was performed by machine learning (ML) based on clinical features, radiomics features, and radiomics + clinical features. Results: Finally, 11 eligible original studies covering 78 models were included in this systematic review. According to the meta-analysis, the radiomics + clinical features model had a c-index of 0.919 (95% CI: 0.871-0.969), pooled sensitivity and specificity of 0.90 (0.83-0.94) and 0.87 (0.78-0.92), respectively, in the training set, and a c- index of 0.910 (95% CI: 0.886-0.934), pooled sensitivity and specificity of 0.78 (0.71-0.84) and 0.83 (0.74-0.89), respectively, in the validation set. Conclusions: The ML methods based on radiomics + clinical features had satisfactory accuracy for the early diagnosis of PM in GC patients, and can be used as an auxiliary diagnostic tool for clinicians. However, the lack of guidelines for the proper operation of radiomics has led to the diversification of radiomics methods, which seems to limit the development of radiomics. Even so, the clinical application value of radiomics cannot be ignored. The standardization of radiomics research is required in the future for the wider application of radiomics by developing intelligent tools of radiomics. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=350512, identifier CRD42022350512.

The effect of rhythmic movement on physical and cognitive functions among cognitively healthy older adults: A systematic review and meta-analysis.

OBJECTIVE: To explore the effects of rhythmic movement interventions on the physical and cognitive functions among cognitively healthy older adults. METHODS: We searched PubMed, Web of Science, Cochrane Library, EMBASE, CNKI, CBM, Wanfang Data, and VIP databases from inception to March 30, 2022. The inclusion criteria were: ① randomized controlled trials (RCTs); ② older adults (aged ≥ 60 years) without cognitive impairments or neurological or neurodegenerative diseases; ③ intervention: rhythmic movement (rhythmic exercise or physical activities performed to music); ④ outcomes: physical or cognitive function. Overall, 44 RCTs across 20 countries (n = 2752 participants) were included. RESULTS: An association was found between rhythmic movement and improved physical function (mobility, cardiopulmonary endurance, muscle strength, flexibility, and balance), global cognitive function, and quality of life (QOL). The physical function outcomes suggested additional significant benefits when using control groups with no exercise than when using control groups with exercise. No significant improvement was found in executive function. CONCLUSION: Regular rhythmic movement likely improves physical function, global cognitive function, and QOL in healthy older adults. The effect of rhythmic movement on the physical function in older adults is similar to that of routine exercise. Further studies on cognitive function of healthy older adults using larger samples of populations with more balanced sex ratios with long-term follow-up are particularly encouraged.

Programmed cell death 1 pathway inhibitors improve the overall survival of small cell lung cancer patients with brain metastases.

PURPOSE: The objective of this study was to evaluate the safety and efficacy of immune checkpoint inhibitors in small cell lung cancer patients with brain metastases. METHODS: We retrospectively reviewed the records of small cell lung cancer patients with brain metastases treated with chemotherapy and radiotherapy for brain metastases with or without immune checkpoint inhibitors at our institution from January 2019 to January 2021. Patients were divided into two groups. In Group A, patients received chemotherapy and radiotherapy for brain metastases. In Group B, patients received chemotherapy, radiotherapy for brain metastases and at least four cycles of immunotherapy. Overall survival and intracranial progression-free survival were assessed using Kaplan-Meier estimates and Cox regression models. RESULTS: A total of 282 patients were enrolled in our study. At the end of the study (May 12, 2021), the median overall survival was 13.3 months among 218 patients in Group A and 33.4 months among 64 patients in Group B (hazards ratio [HR] 0.320, 95% confidence interval [CI], 0.189-0.545, P < 0.001). Both univariate and multivariate analyses suggested that two factors were significantly correlated with overall survival: the inclusion of immunotherapy in the regimen and the presence of extracranial metastases. The median intracranial progression-free survival was 6.93 months in Group A and 10.73 months in Group B (HR = 0.540, 95% CI, 0.346-0.841, P = 0.006). The intracranial objective response rate of Group B was greater than that of Group A, but the intracranial disease control rate was similar between the groups. CONCLUSION: Immunotherapy plus chemotherapy and radiotherapy for brain metastases showed promising efficacy for small cell lung cancer patients with brain metastases.

Predicting rice diseases using advanced technologies at different scales: present status and future perspectives.

The past few years have witnessed significant progress in emerging disease detection techniques for accurately and rapidly tracking rice diseases and predicting potential solutions. In this review we focus on image processing techniques using machine learning (ML) and deep learning (DL) models related to multi-scale rice diseases. Furthermore, we summarize applications of different detection techniques, including genomic, physiological, and biochemical approaches. In addition, we also present the state-of-the-art in contemporary optical sensing applications of pathogen-plant interaction phenotypes. This review serves as a valuable resource for researchers seeking effective solutions to address the challenges of high-throughput data and model recognition for early detection of issues affecting rice crops through ML and DL models.