PD-1 blockade immunotherapy as a successful rescue treatment for disseminated adenovirus infection after allogeneic hematopoietic stem cell transplantation.

Disseminated adenovirus infection is a complication with a relatively high mortality rate among patients undergoing hematopoietic stem cell transplantation. The low efficacy and poor availability of current treatment options are of major concern. Programmed cell death 1 (PD-1) blockade has been used to treat several chronic viral infections. Herein, we report a case of disseminated adenovirus infection in the early posttransplant period. The patient was diagnosed with diffuse large B-cell lymphoma at first and underwent 8 cycles of chemotherapy, including rituximab. She was subsequently diagnosed with acute myeloid leukemia and received haploidentical transplantation. She was diagnosed with Epstein‒Barr virus (EBV)-positive posttransplant lymphoproliferative disorder (PTLD) 2 months after the transplant, and 3 doses of rituximab were administered. The patient was diagnosed with disseminated adenovirus infection with upper respiratory tract, gastrointestinal tract and blood involved at 3 months after transplantation. She was first treated with a reduction in immunosuppression, cidofovir and ribavirin. Then, the patient received salvage treatment with the PD-1 inhibitor sintilimab (200 mg) after achieving no response to conventional therapy. The adenovirus was cleared 3 weeks later, and concomitant EBV was also cleared. Although the patient developed graft-versus-host disease of the liver after the administration of the PD-1 inhibitor, she was cured with steroid-free therapy. Therefore, PD-1 blockade immunotherapy can be considered a promising treatment option for patients with disseminated adenovirus infection after transplantation, with fully weighing the hazards of infection and the side effects of this therapy.

Superdurable Full-Life Superhydrophobic Composite Block.

Superhydrophobic materials are attractive for industrial development but plagued by poor mechanical stability. Herein, a superdurable full-life superhydrophobic composite block is designed and fabricated by embedding near-zero contractive superhydrophobic silica aerogel into a rigid iron-nickel foam structured similarly to a regular dodecahedron. The synergistic protection afforded by these materials ensures superrobust mechanical stability for the composite block, which features a high compressive strength of up to ≈7.4 MPa, and ultralow Taber abrasion of down to ≈0.567 mm after withstanding 50 000 cycles, and highly efficient water harvesting capability of up to ≈3114.3 mg min-1 cm-2 at a supercooling degree of 40 K. This robust material system provides a novel strategy to design superhydrophobic materials capable of withstanding extreme conditions, including high temperature, humidity, pressure, and abrasion.

Functionalized DNA Origami-Enabled Detection of Biomarkers.

Biomarkers are crucial physiological and pathological indicators in the host. Over the years, numerous detection methods have been developed for biomarkers, given their significant potential in various biological and biomedical applications. Among these, the detection system based on functionalized DNA origami has emerged as a promising approach due to its precise control over sensing modules, enabling sensitive, specific, and programmable biomarker detection. We summarize the advancements in biomarker detection using functionalized DNA origami, focusing on strategies for DNA origami functionalization, mechanisms of biomarker recognition, and applications in disease diagnosis and monitoring. These applications are organized into sections based on the type of biomarkers-nucleic acids, proteins, small molecules, and ions-and concludes with a discussion on the advantages and challenges associated with using functionalized DNA origami systems for biomarker detection.

Inorganic Composition Modulation of Solid Electrolyte Interphase for Fast Charging Lithium Metal Batteries.

The solid electrolyte interphase (SEI) with lithium fluoride (LiF) is critical to the performance of lithium metal batteries (LMBs) due to its high stability and mechanical properties. However, the low Li ion conductivity of LiF impedes the rapid diffusion of Li ions in the SEI, which leads to localized Li ion oversaturation dendritic deposition and hinders the practical applications of LMBs at high-current regions (>3 C). To address this issue, a fluorophosphated SEI rich with fast ion-diffusing inorganic grain boundaries (LiF/Li3P) is introduced. By utilizing a sol electrolyte that contains highly dispersed porous LiF nanoparticles modified with phosphorus-containing functional groups, a fluorophosphated SEI is constructed and the presence of electrochemically active Li within these fast ion-diffusing grain boundaries (GBs-Li) that are non-nucleated is demonstrated, ensuring the stability of the Li || NCM811 cell for over 1000 cycles at fast-charging rates of 5 C (11 mA cm-2). Additionally, a practical, long cycling, and intrinsically safe LMB pouch cell with high energy density (400 Wh kg-1) is fabricated. The work reveals how SEI components and structure design can enable fast-charging LMBs.

[Analysis of clinical characteristics and molecular genetics in eighteen patients with 1q21.1 microdeletion syndrome].

OBJECTIVE: To explore the clinical characteristics of 1q21.1 microdeletion by using single nucleotide polymorphism microarrays (SNP array). METHODS: Eighteen cases of 1q21.1 microdeletion syndrome diagnosed at the Longgang District Maternal and Child Health Care Hospital of Shenzhen City from June 2017 to December 2022 were selected as the study subjects. Clinical data of the patients were collected. Results of chromosomal karyotyping and SNP assay were retrospectively analyzed. RESULTS: Among the 18 cases with 1q21.1 microdeletions, 13 had a deletion between BP3 and BP4, 4 had a deletion between BP1/BP2 and BP4, whilst 1 had a proximal 1q21.1 deletion (between BP2 and BP3) involving the Thrombocytopenia-absent radius (TAR) region. The deletions had spanned from 360 kb to 3.9 Mb, which encompassed the GJA5, GJA8, CHD1L, RBM8AB and other morbid genes. In three families, the proband child has inherited the same 1q21.1 microdeletion from their parents, whose clinical phenotype was normal or slightly abnormal. The clinical phenotypes of 1q21.1 microdeletion had included cognitive or behavioral deficits in 9 cases (9/18, 50.0%), growth retardation in 8 cases (8/18, 44.4%), craniofacial deformities in 7 cases (7/18, 38.8%), cardiovascular malformations in 5 cases (5/18, 27.8%), and microcephaly in 3 cases (3/18, 16.7%). CONCLUSION: 1q21.1 microdeletion syndrome has incomplete penetrance and varied expression such as intellectual impairment, growth and development delay, and microcephaly, with a wide range of non-specific phenotypes.

Optimal response to tislelizumab plus chemotherapy in metastatic triple-negative breast cancer: a case report and literature review.

Metastatic triple-negative breast cancer (mTNBC) has the worst prognosis among breast cancer subtypes. Immune checkpoint inhibitors (ICIs) plus chemotherapy have promising survival benefits. Herein, we report a 51-year-old woman whose metastatic lesions were diagnosed as triple-negative subtype and who received tislelizumab plus eribulin treatment and achieved excellent efficacy. To our knowledge, this study is the first attempt to present tislelizumab in combination with eribulin for mTNBC treatment. New treatments resulting in prolonged survival and durable clinical responses would benefit mTNBC patients. Then, we summarize the possible influencing factors of the interaction between tislelizumab and eribulin.

Native T1-mapping as a predictor of progressive renal function decline in chronic kidney disease patients.

BACKGROUND: To investigate the potential of Native T1-mapping in predicting the prognosis of patients with chronic kidney disease (CKD). METHODS: We enrolled 119 CKD patients as the study subjects and included 20 healthy volunteers as the control group, with follow-up extending until October 2022. Out of these patients, 63 underwent kidney biopsy measurements, and these patients were categorized into high (25-50%), low (< 25%), and no renal interstitial fibrosis (IF) (0%) groups. The study's endpoint event was the initiation of renal replacement therapy, kidney transplantation, or an increase of over 30% in serum creatinine levels. Cox regression analysis determined factors influencing unfavorable kidney outcomes. We employed Kaplan-Meier analysis to contrast kidney survival rates between the high and low T1 groups. Additionally, receiver-operating characteristic (ROC) curve analysis assessed the predictive accuracy of Native T1-mapping for kidney endpoint events. RESULTS: T1 values across varying fibrosis degree groups showed statistical significance (F = 4.772, P < 0.05). Multivariate Cox regression pinpointed 24-h urine protein, cystatin C(CysC), hemoglobin(Hb), and T1 as factors tied to the emergence of kidney endpoint events. Kaplan-Meier survival analysis revealed a markedly higher likelihood of kidney endpoint events in the high T1 group compared to the low T1 value group (P < 0.001). The ROC curves for variables (CysC, T1, Hb) tied to kidney endpoint events demonstrated area under the curves(AUCs) of 0.83 (95%CI: 0.75-0.91) for CysC, 0.77 (95%CI: 0.68-0.86) for T1, and 0.73 (95%CI: 0.63-0.83) for Hb. Combining these variables elevated the AUC to 0.88 (95%CI: 0.81-0.94). CONCLUSION: Native T1-mapping holds promise in facilitating more precise and earlier detection of CKD patients most at risk for end-stage renal disease.

Score Dynamics: Scaling Molecular Dynamics with Picoseconds Time Steps via Conditional Diffusion Model.

We propose score dynamics (SD), a general framework for learning accelerated evolution operators with large timesteps from molecular dynamics (MD) simulations. SD is centered around scores or derivatives of the transition log-probability with respect to the dynamical degrees of freedom. The latter play the same role as force fields in MD but are used in denoising diffusion probability models to generate discrete transitions of the dynamical variables in an SD time step, which can be orders of magnitude larger than a typical MD time step. In this work, we construct graph neural network-based SD models of realistic molecular systems that are evolved with 10 ps timesteps. We demonstrate the efficacy of SD with case studies of the alanine dipeptide and short alkanes in aqueous solution. Both equilibrium predictions derived from the stationary distributions of the conditional probability and kinetic predictions for the transition rates and transition paths are in good agreement with MD. Our current SD implementation is about 2 orders of magnitude faster than the MD counterpart for the systems studied in this work. Open challenges and possible future remedies to improve SD are also discussed.

A Study of the Adsorption Properties of Individual Atoms on the Graphene Surface: Density Functional Theory Calculations Assisted by Machine Learning Techniques.

In this research, the adsorption performance of individual atoms on the surface of monolayer graphene surface was systematically investigated using machine learning methods to accelerate density functional theory. The adsorption behaviors of over thirty different atoms on the graphene surface were computationally analyzed. The adsorption energy and distance were extracted as the research targets, and the basic information of atoms (such as atomic radius, ionic radius, etc.) were used as the feature values to establish the dataset. Through feature engineering selection, the corresponding input feature values for the input-output relationship were determined. By comparing different models on the dataset using five-fold cross-validation, the mathematical model that best fits the dataset was identified. The optimal model was further fine-tuned by adjusting of the best mathematical ML model. Subsequently, we verified the accuracy of the established machine learning model. Finally, the precision of the machine learning model forecasts was verified by the method of comparing and contrasting machine learning results with density functional theory. The results suggest that elements such as Zr, Ti, Sc, and Si possess some potential in controlling the interfacial reaction of graphene/aluminum composites. By using machine learning to accelerate first-principles calculations, we have further expanded our choice of research methods and accelerated the pace of studying element-graphene interactions.

Aldo-keto reductase-7A2 protects against atorvastatin-induced hepatotoxicity via Nrf2 activation.

Atorvastatin (ATO), as a cholesterol-lowering drug, was the world's best-selling drug in the early 2000s. However, ATO overdose-induced liver or muscle injury is a threat to many patients, which restricts its application. Previous studies suggest that ATO overdose is accompanied with ROS accumulation and increased lipid peroxidation, which are the leading causes of ATO-induced liver damage. This study is, therefore, carried out to investigate the roles of anti-oxidant pathways and enzymes in protection against ATO-induced hepatotoxicity. Here we show that in ATO-challenged HepG2 cells, the expression levels of transcription factor NFE2L2/Nrf2 (nuclear factor erythroid 2 p45-related factor 2) are significantly upregulated. When Nrf2 is pharmacologically inhibited or genetically inactivated, ATO-induced cytotoxicity is significantly aggravated. Aldo-keto reductase-7A (AKR7A) enzymes, transcriptionally regulated by Nrf2, are important for bioactivation and biodetoxification. Here, we reveal that in response to ATO exposure, mRNA levels of human AKR7A2 are significantly upregulated in HepG2 cells. Furthermore, knockdown of AKR7A2 exacerbates ATO-induced hepatotoxicity, suggesting that AKR7A2 is essential for cellular adaptive response to ATO-induced cell damage. In addition, overexpression of AKR7A2 in HepG2 cells can significantly mitigate ATO-induced cytotoxicity and this process is Nrf2-dependent. Taken together, these findings indicate that Nrf2-mediated AKR7A2 is responsive to high concentrations of ATO and contributes to protection against ATO-induced hepatotoxicity, making it a good candidate for mitigating ATO-induced side effects.

Prenatal diagnosis, pregnancy determination and follow up of sex chromosome aneuploidy screened by non-invasive prenatal testing from 122 453 unselected singleton pregnancies: A retrospective analysis of 7-year experience.

The phenotype of SCA patients are diversities, make prenatal counseling and parental decision-making following the prenatal diagnosis of SCA more complicated and challenging. NIPT has higher sensitivity and specificity in screening trisomy 21 syndrome, but the effectiveness of NIPT in detecting SCA is still controversial. This study is a large-scale retrospective cohort of positive SCA screened from unselected singleton pregnancies by non-invasive prenatal testing (NIPT) from a single prenatal center of a tertiary hospital. Clinical information, indications, diagnostic results, ultrasound findings, pregnancy determinations, and follow-up were reviewed and analyzed. 596 cases of SCA positive were screened out of 122 453, giving a positive detection rate of 0.49%. 510 cases (85.6%) conducted with amniocentesis to detect fetal chromosome, of which 236 were confirmed as true positive of SCA with PPV of 46.3% (236/510). Of the 236 cases confirmed as true positive SCA, 114 cases (48.3%)chose to terminate the pregnancy (93.0%, 65.3%, 15.4% and 10.9% for 45,X, 47,XXY, 47,XXX and 47,XYY, respectively), 122 cases (51.7%) elected to continue the pregnancy. In conclusions, NIPT as a first-tier routine method for screening autosomal aneuploidies, also could play an important role in screening SCA. Low-risk pregnant women are the main indication for the detection of SCA as NIPT test provides to non-selective population. For 47,XXX and 47,XYY with mild phenotype, couples would like to continue the pregnancy. But for 45,X and 47,XXY, parents apt to terminate pregnancy no matter ultrasound abnormalities were found or not.

Cryo-EM structures of the plant plastid-encoded RNA polymerase.

Chloroplasts are green plastids in the cytoplasm of eukaryotic algae and plants responsible for photosynthesis. The plastid-encoded RNA polymerase (PEP) plays an essential role during chloroplast biogenesis from proplastids and functions as the predominant RNA polymerase in mature chloroplasts. The PEP-centered transcription apparatus comprises a bacterial-origin PEP core and more than a dozen eukaryotic-origin PEP-associated proteins (PAPs) encoded in the nucleus. Here, we determined the cryo-EM structures of Nicotiana tabacum (tobacco) PEP-PAP apoenzyme and PEP-PAP transcription elongation complexes at near-atomic resolutions. Our data show the PEP core adopts a typical fold as bacterial RNAP. Fifteen PAPs bind at the periphery of the PEP core, facilitate assembling the PEP-PAP supercomplex, protect the complex from oxidation damage, and likely couple gene transcription with RNA processing. Our results report the high-resolution architecture of the chloroplast transcription apparatus and provide the structural basis for the mechanistic and functional study of transcription regulation in chloroplasts.

Role of C/EBP Homologous Protein in Vascular Stenosis After Carotid Artery Injury.

The study aims to explore the fluctuating expression of C/EBP Homologous Protein (CHOP) following rat carotid artery injury and its central role in vascular stenosis. Using in vivo rat carotid artery injury models and in vitro ischemia and hypoxia cell models employing human aortic endothelial cells (HAECs) and vascular smooth muscle cells (T/G HA-VSMCs), a comprehensive investigative framework was established. Histological analysis confirmed intimal hyperplasia in rat models. CHOP expression in vascular tissues was assessed using Western blot and immunohistochemical staining, and its presence in HAECs and T/G HA-VSMCs was determined through RT-PCR and Western blot. The study evaluated HAEC apoptosis, inflammatory cytokine secretion, cell proliferation, and T/G HA-VSMCs migration through Western blot, ELISA, CCK8, and Transwell migration assays. The rat carotid artery injury model revealed substantial fibrous plaque formation and vascular stenosis, resulting in an increased intimal area and plaque-to-lumen area ratio. Notably, CHOP is markedly elevated in vessels of the carotid artery injury model compared to normal vessels. Atorvastatin effectively mitigated vascular stenosis and suppresses CHOP protein expression. In HAECs, ischemia and hypoxia-induced CHOP upregulation, along with heightened TNFα, IL-6, caspase3, and caspase8 levels, while reducing cell proliferation. Atorvastatin demonstrated a dose-dependent suppression of CHOP expression in HAECs. Downregulation of CHOP or atorvastatin treatment led to reduced IL-6 and TNFα secretion, coupled with augmented cell proliferation. Similarly, ischemia and hypoxia conditions increased CHOP expression in T/G HA-VSMCs, which was concentration-dependently inhibited by atorvastatin. Furthermore, significantly increased MMP-9 and MMP-2 concentrations in the cell culture supernatant correlated with enhanced T/G HA-VSMCs migration. However, interventions targeting CHOP downregulation and atorvastatin usage curtailed MMP-9 and MMP-2 secretion and suppressed cell migration. In conclusion, CHOP plays a crucial role in endothelial injury, proliferation, and VSMCs migration during carotid artery injury, serving as a pivotal regulator in post-injury fibrous plaque formation and vascular remodeling. Statins emerge as protectors of endothelial cells, restraining VSMCs migration by modulating CHOP expression.

A deep-learning model for intracranial aneurysm detection on CT angiography images in China: a stepwise, multicentre, early-stage clinical validation study.

BACKGROUND: Artificial intelligence (AI) models in real-world implementation are scarce. Our study aimed to develop a CT angiography (CTA)-based AI model for intracranial aneurysm detection, assess how it helps clinicians improve diagnostic performance, and validate its application in real-world clinical implementation. METHODS: We developed a deep-learning model using 16 546 head and neck CTA examination images from 14 517 patients at eight Chinese hospitals. Using an adapted, stepwise implementation and evaluation, 120 certified clinicians from 15 geographically different hospitals were recruited. Initially, the AI model was externally validated with images of 900 digital subtraction angiography-verified CTA cases (examinations) and compared with the performance of 24 clinicians who each viewed 300 of these cases (stage 1). Next, as a further external validation a multi-reader multi-case study enrolled 48 clinicians to individually review 298 digital subtraction angiography-verified CTA cases (stage 2). The clinicians reviewed each CTA examination twice (ie, with and without the AI model), separated by a 4-week washout period. Then, a randomised open-label comparison study enrolled 48 clinicians to assess the acceptance and performance of this AI model (stage 3). Finally, the model was prospectively deployed and validated in 1562 real-world clinical CTA cases. FINDINGS: The AI model in the internal dataset achieved a patient-level diagnostic sensitivity of 0·957 (95% CI 0·939-0·971) and a higher patient-level diagnostic sensitivity than clinicians (0·943 [0·921-0·961] vs 0·658 [0·644-0·672]; p<0·0001) in the external dataset. In the multi-reader multi-case study, the AI-assisted strategy improved clinicians' diagnostic performance both on a per-patient basis (the area under the receiver operating characteristic curves [AUCs]; 0·795 [0·761-0·830] without AI vs 0·878 [0·850-0·906] with AI; p<0·0001) and a per-aneurysm basis (the area under the weighted alternative free-response receiver operating characteristic curves; 0·765 [0·732-0·799] vs 0·865 [0·839-0·891]; p<0·0001). Reading time decreased with the aid of the AI model (87·5 s vs 82·7 s, p<0·0001). In the randomised open-label comparison study, clinicians in the AI-assisted group had a high acceptance of the AI model (92·6% adoption rate), and a higher AUC when compared with the control group (0·858 [95% CI 0·850-0·866] vs 0·789 [0·780-0·799]; p<0·0001). In the prospective study, the AI model had a 0·51% (8/1570) error rate due to poor-quality CTA images and recognition failure. The model had a high negative predictive value of 0·998 (0·994-1·000) and significantly improved the diagnostic performance of clinicians; AUC improved from 0·787 (95% CI 0·766-0·808) to 0·909 (0·894-0·923; p<0·0001) and patient-level sensitivity improved from 0·590 (0·511-0·666) to 0·825 (0·759-0·880; p<0·0001). INTERPRETATION: This AI model demonstrated strong clinical potential for intracranial aneurysm detection with improved clinician diagnostic performance, high acceptance, and practical implementation in real-world clinical cases. FUNDING: National Natural Science Foundation of China. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Effects of collagen-based coating with chitosan and ε-polylysine on sensory, texture, and biochemical changes of refrigerated Nemipterus virgatus fillets.

In order to evaluate the effects of chitosan, ε-polylysine, and collagen on the preservation properties of refrigerated Nemipterus virgatus, samples were tested with different treatments for 10 days, namely chitosan, ε-polylysine and collagen (CH + ε-PL + CA), chitosan and ε-polylysine (CH + ε-PL), chitosan and collagen (CH + CA), ε-polylysine and collagen (ε-PL + CA), and the uncoated sample (CK). The results demonstrated that the bio-coating exhibited better preservation effects. The CH + ε-PL + CA, CH + ε-PL, CH + CA, ε-PL + CA treatments could significantly inhibit bacterial growth and retard the increase of total volatile base nitrogen (TVB-N), 2-thiobarbituric acid (TBA), K-value, and total viable counts (TVC) in N. virgatus fillets. The pH of all samples decreased and reached its lowest value on day 6, then increased significantly at the end of the experiment (p < .05). Water-holding capacity (WHC) of all the groups decreased continuously throughout storage, and CK reached 66.03% on day 6, which is significantly lower than CH + ε-PL + CA, CH + ε-PL, CH + CA, and ε-PL + CA (p < .05). On the contrary, the sensory scores of CH + ε-PL + CA, CH + ε-PL, CH + CA, and ε-PL + CA were significantly higher than the control, and the score of CH + ε-PL + CA (p < .05) was the best among all the groups. In terms of texture, CH + PL + CA also showed less cell shrinkage and tighter muscle fiber arrangement compared to other treatments. To sum up, the CH + PL + CA bio-coating proved to be a promising method for maintaining the storage quality of N. virgatus under refrigerated storage conditions.

Magnesium Transporter MgtA revealed as a Dimeric P-type ATPase.

Magnesium (Mg2+) uptake systems are present in all domains of life given the vital role of this ion. Bacteria acquire Mg2+ via conserved Mg2+ channels and transporters. The transporters are required for growth when Mg2+ is limiting or during bacterial pathogenesis, but, despite their significance, there are no known structures for these transporters. Here we report the first structure of the Mg2+ transporter MgtA solved by single particle cryo-electron microscopy (cryo-EM). Using mild membrane extraction, we obtained high resolution structures of both a homodimeric form (2.9 Å), the first for a P-type ATPase, and a monomeric form (3.6 Å). Each monomer unit of MgtA displays a structural architecture that is similar to other P-type ATPases with a transmembrane domain and two soluble domains. The dimer interface consists of contacts between residues in adjacent soluble nucleotide binding and phosphotransfer regions of the haloacid dehalogenase (HAD) domain. We suggest oligomerization is a conserved structural feature of the diverse family of P-type ATPase transporters. The ATP binding site and conformational dynamics upon nucleotide binding to MgtA were characterized using a combination of cryo-EM, molecular dynamics simulations, hydrogen-deuterium exchange mass spectrometry, and mutagenesis. Our structure also revealed a Mg2+ ion in the transmembrane segments, which, when combined with sequence conservation and mutagenesis studies, allowed us to propose a model for Mg2+ transport across the lipid bilayer. Finally, our work revealed the N-terminal domain structure and cytoplasmic Mg2+ binding sites, which have implications for related P-type ATPases defective in human disease.

Efficacy and safety of local ablative therapy for patients with NSCLC and coexisting interstitial lung disease.

BACKGROUND: The effective therapeutic approach is still an unmet need for patients diagnosed with both lung cancer and interstitial lung disease (ILD). This is primarily due to the possible risk of ILD exacerbation caused by surgery or radiotherapy. The current study aimed to investigate the efficacy and safety of local ablative therapy (LAT) for this specific population. METHODS: Consecutive patients with non-small cell lung cancer (NSCLC) and ILD who received LAT between January 2018 and August 2022 were enrolled, and propensity score matching (PSM) was utilized to match the non-ILD group. The primary endpoint was recurrence-free survival (RFS), and secondary endpoints included overall survival (OS), adverse events (AEs) and hospital length of stay (HLOS). RESULTS: The PSM algorithm yielded matched pairs in the ILD group (n = 25) and non-ILD group (n = 72) at a ratio of 1:3. There were no statistically significant differences in RFS (median 16.4 vs. 18 months; HR = 1.452, p = 0.259) and OS (median: not reached vs. 47.9 months; HR = 1.096, p = 0.884) between the two groups. Meanwhile, no acute exacerbation of ILD was observed in the ILD group. However, the incidence of pneumothorax, especially pneumothorax requiring chest tube drainage, was significantly higher (36.0% vs. 11.2%, p = 0.005) among patients with NSCLC and co-existing ILD, which resulted in longer HLOS (p = 0.045). CONCLUSION: Although ILD was associated with a higher incidence of pneumothorax, the efficacy of LAT for NSCLC patients with ILD was comparable to those without ILD, suggesting that LAT might be a reliable and effective treatment option for this population, particularly in the early stage.

Can pluripotent/multipotent stem cells reverse Parkinson's disease progression?

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by continuous and selective degeneration or death of dopamine neurons in the midbrain, leading to dysfunction of the nigrostriatal neural circuits. Current clinical treatments for PD include drug treatment and surgery, which provide short-term relief of symptoms but are associated with many side effects and cannot reverse the progression of PD. Pluripotent/multipotent stem cells possess a self-renewal capacity and the potential to differentiate into dopaminergic neurons. Transplantation of pluripotent/multipotent stem cells or dopaminergic neurons derived from these cells is a promising strategy for the complete repair of damaged neural circuits in PD. This article reviews and summarizes the current preclinical/clinical treatments for PD, their efficacies, and the advantages/disadvantages of various stem cells, including pluripotent and multipotent stem cells, to provide a detailed overview of how these cells can be applied in the treatment of PD, as well as the challenges and bottlenecks that need to be overcome in future translational studies.

An advanced machine learning method for simultaneous breast cancer risk prediction and risk ranking in Chinese population: A prospective cohort and modeling study.

BACKGROUND: Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk among Chinese women and to simultaneously rank potential non-experimental risk factors. METHODS: The Breast Cancer Cohort Study in Chinese Women, a large ongoing prospective dynamic cohort study, includes 122,058 women aged 25-70 years from the eastern part of China. We developed multiple machine-learning risk prediction models using parametric models (penalized logistic regression, bootstrap, and ensemble learning), which were the short-term ensemble penalized logistic regression (EPLR) risk prediction model and the ensemble penalized long-term (EPLT) risk prediction model to estimate BC risk. The models were assessed based on calibration and discrimination, and following this assessment, they were externally validated in new study participants from 2017 to 2020. RESULTS: The AUC values of the short-term EPLR risk prediction model were 0.800 for the internal validation and 0.751 for the external validation set. For the long-term EPLT risk prediction model, the area under the receiver operating characteristic curve was 0.692 and 0.760 in internal and external validations, respectively. The net reclassification improvement index of the EPLT relative to the Gail and the Han Chinese Breast Cancer Prediction Model (HCBCP) models for external validation was 0.193 and 0.233, respectively, indicating that the EPLT model has higher classification accuracy. CONCLUSIONS: We developed the EPLR and EPLT models to screen populations with a high risk of developing BC. These can serve as useful tools to aid in risk-stratified screening and BC prevention.