DNA Framework-Guided Self-Limiting Aggregation for Highly Luminescent Metal Cluster Nanoaggregates.

The photoluminescent properties of atomically precise metal nanoclusters (MCs) have garnered significant attention in the fields of chemical sensing and biological imaging. However, the limited brightness of single-component nanoclusters hinders their practical applications, and the conventional ligand engineering approaches have proven insufficient in enhancing the emission efficiency of MCs. Here, we present a DNA framework-guided strategy to prepare highly luminescent metal cluster nanoaggregates. Our approach involves an amphiphilic DNA framework comprising a hydrophobic alkyl core and a rigid DNA framework shell, serving as a nucleation site and providing well-defined nanoconfinements for the self-limiting aggregation of MCs. Through this method, we successfully produced homogeneous MC nanoaggregates (10.1 ± 1.2 nm) with remarkable nanoscale precision. Notably, this strategy proves adaptable to various MCs, leading to a substantial enhancement in emission and quantum yield, up to 3011- and 87-fold, respectively. Furthermore, our investigation using total internal reflection fluorescence microscopy at the single-particle level uncovered a more uniform photon number distribution and higher photostability for MC nanoaggregates compared to template-free counterparts. This DNA-templating strategy introduces a conceptually innovative approach for studying the photoluminescent properties of aggregates with nanoscale precision and holds promise for constructing highly luminescent MC nanoparticles for diverse applications.

Clinical and Genetic Spectrum in a Large Cohort of Hereditary Spastic Paraplegia.

BACKGROUND: Next-generation sequencing-based molecular assessment has benefited the diagnosis of hereditary spastic paraplegia (HSP) subtypes. However, the clinical and genetic spectrum of HSP due to large fragment deletions/duplications has yet to be fully defined. OBJECTIVE: We aim to better characterize the clinical phenotypes and genetic features of HSP and to provide new thoughts on diagnosis. METHODS: Whole-exome sequencing (WES) was performed in patients with clinically suspected HSP, followed by multiple ligation-dependent probe amplification (MLPA) sequentially carried out for those with negative findings in known causative genes. Genotype-phenotype correlation analyses were conducted under specific genotypes. RESULTS: We made a genetic diagnosis in 60% (162/270) of patients, of whom 48.9% (132/270) had 24 various subtypes due to point mutations (SPG4/SPG11/SPG35/SPG7/SPG10/SPG5/SPG3A/SPG2/SPG76/SPG30/SPG6/SPG9A/SPG12/SPG15/SPG17/SPG18/SPG26/SPG49/SPG55/SPG56/SPG57/SPG62/SPG78/SPG80). Thirty patients were found to have causative rearrangements by MLPA (11.1%), among which SPG4 was the most prevalent (73.3%), followed by SPG3A (16.7%), SPG6 (3.3%), SPG7 (3.3%), and SPG11 (3.3%). Clinical analysis showed that some symptoms were often related to specific subtypes, and rearrangement-related SPG3A patients seemingly had later onset. We observed a presumptive anticipation among SPG4 and SPG3A families due to rearrangement. CONCLUSIONS: Based on the largest known Asian HSP cohort, including the largest subgroup of rearrangement-related pedigrees, we gain a comprehensive understanding of the clinical and genetic spectrum of HSP. We propose a diagnostic flowchart to sequentially detect the causative genes in practice. Large fragment mutations account for a considerable proportion of HSP, and thus, MLPA screening acts as a beneficial supplement to routine WES. © 2024 International Parkinson and Movement Disorder Society.

The Phenotypic and Genotypic Spectrum of CSF1R-Related Disorder in China.

BACKGROUND: Colony-stimulating factor 1 receptor (CSF1R)-related disorder (CRD) is a rare autosomal dominant disease. The clinical and genetic characteristics of Chinese patients have not been elucidated. OBJECTIVE: The objective of the study is to clarify the core features and influence factors of CRD patients in China. METHODS: Clinical and genetic-related data of CRD patients in China were collected. Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Sundal MRI Severity Score were evaluated. Whole exome sequencing was used to analyze the CSF1R mutation status. Patients were compared between different sexes, mutation types, or mutation locations. RESULTS: A total of 103 patients were included, with a male-to-female ratio of 1:1.51. The average age of onset was (40.75 ± 8.58). Cognitive impairment (85.1%, 86/101) and parkinsonism (76.2%, 77/101) were the main clinical symptoms. The most common imaging feature was bilateral asymmetric white matter changes (100.0%). A total of 66 CSF1R gene mutants (22 novel mutations) were found, and 15 of 92 probands carried c.2381 T > C/p.I794T (16.30%). The MMSE and MoCA scores (17.0 [9.0], 11.90 ± 7.16) of female patients were significantly lower than those of male patients (23.0 [10.0], 16.36 ± 7.89), and the white matter severity score (20.19 ± 8.47) of female patients was significantly higher than that of male patients (16.00 ± 7.62). There is no statistical difference in age of onset between male and female patients. CONCLUSIONS: The core manifestations of Chinese CRD patients are progressive cognitive decline, parkinsonism, and bilateral asymmetric white matter changes. Compared to men, women have more severe cognitive impairment and imaging changes. c.2381 T > C/p.I794T is a hotspot mutation in Chinese patients. © 2024 International Parkinson and Movement Disorder Society.

Intracardiac metastasis of gestational choriocarcinoma: a case report and literature review.

INTRODUCTION: Gestational trophoblastic neoplasia (GTN) with intracardiac metastasis is rare, and here we reported a patient with intracardiac metastasis of high-risk and refractory gestational choriocarcinoma and reviewed relevant literatures. CASE PRESENTATION: A 37-year-old woman presented with vaginal bleeding and high level of ß-human chorionic gonadotropin (ß-hCG) at 199,060 (mIU/mL). It was clinically diagnosed with gestational choriocarcinoma. The patient initially received eight cycles of chemotherapy but unsatisfactory response was observed, and the level of ß-hCG still ranged between 5000 and 10,000. Then there was found intracardiac masses in the right atrium (2.6*1.7 cm), anterior chordae tendineae of the tricuspid valve (1.4*0.7 cm) and the right ventricle (4.1*2.9 cm) by ultrasonic cardiogram (UCG). PET/CT highly suspected the intracardiac metastasis of choriocarcinoma (SUVmax = 9.3) and no disease was found in the lung and pelvis. The patient undertook complete intracardiac masses resection. The pathology confirmed the intracardiac metastasis of disease. After a week of operation, the UCG found a 5.4*4.2 cm mass in the right atrium again. Considering the poor prognosis, the patient received palliative care and eventually died of disease progression. CONCLUSION: Intracardiac metastasis of GTN is an aggressive sign of disease. Patients can benefit from chemotherapy and surgery. Future investigation of PD-1 immunotherapy combines with chemotherapy are expected to improve the prognosis in this group of patients.

Autologous Transplantation Tooth Guide Design Based on Deep Learning.

BACKGROUND: Autologous tooth transplantation requires precise surgical guide design, involving manual tracing of donor tooth contours based on patient cone-beam computed tomography (CBCT) scans. While manual corrections are time-consuming and prone to human errors, deep learning-based approaches show promise in reducing labor and time costs while minimizing errors. However, the application of deep learning techniques in this particular field is yet to be investigated. PURPOSE: We aimed to assess the feasibility of replacing the traditional design pipeline with a deep learning-enabled autologous tooth transplantation guide design pipeline. STUDY DESIGN, SETTING, SAMPLE: This retrospective cross-sectional study used 79 CBCT images collected at the Guangzhou Medical University Hospital between October 2022 and March 2023. Following preprocessing, a total of 5,070 region of interest images were extracted from 79 CBCT images. PREDICTOR VARIABLE: Autologous tooth transplantation guide design pipelines, either based on traditional manual design or deep learning-based design. MAIN OUTCOME VARIABLE: The main outcome variable was the error between the reconstructed model and the gold standard benchmark. We used the third molar extracted clinically as the gold standard and leveraged it as the benchmark for evaluating our reconstructed models from different design pipelines. Both trueness and accuracy were used to evaluate this error. Trueness was assessed using the root mean square (RMS), and accuracy was measured using the standard deviation. The secondary outcome variable was the pipeline efficiency, assessed based on the time cost. Time cost refers to the amount of time required to acquire the third molar model using the pipeline. ANALYSES: Data were analyzed using the Kruskal-Wallis test. Statistical significance was set at P < .05. RESULTS: In the surface matching comparison for different reconstructed models, the deep learning group achieved the lowest RMS value (0.335 ± 0.066 mm). There were no significant differences in RMS values between manual design by a senior doctor and deep learning-based design (P = .688), and the standard deviation values did not differ among the 3 groups (P = .103). The deep learning-based design pipeline (0.017 ± 0.001 minutes) provided a faster assessment compared to the manual design pipeline by both senior (19.676 ± 2.386 minutes) and junior doctors (30.613 ± 6.571 minutes) (P < .001). CONCLUSIONS AND RELEVANCE: The deep learning-based automatic pipeline exhibited similar performance in surgical guide design for autogenous tooth transplantation compared to manual design by senior doctors, and it minimized time costs.

Analysis of Changes of Ang-2 and TNF-α Levels in Patients with AMI Complicated with Pulmonary Infection and Drug Resistance of Infectious Pathogens.

Objective: This study aimed to investigate the changes in angiopoietin-2 and tumor necrosis factor α levels in patients with acute myocardial infarction complicated with pulmonary infection. Methods: Retrospective selection was conducted on 61 patients with acute myocardial infarction complicated with pulmonary infection and 122 patients with simple acute myocardial infarction. A comparison was made between the two groups regarding general information and serum myocs. The distribution and drug resistance of pathogenic bacteria were also explored. Results: The study showed significant differences in the duration of alcohol consumption, the proportion of diabetes mellitus, and levels of certain markers (serum cardiac troponin T, creatine kinase isoenzyme, myoglobin, angiopoietin-2, tumor necrosis factor α) between the two groups (P < .05). Logistic regression analysis identified elevated levels of serum angiopoietin-2 and tumor necrosis factor α, along with diabetes mellitus, as independent risk factors for acute myocardial infarction complicated with pulmonary infection (P < .05). Pearson correlation analysis demonstrated a positive correlation between serum angiopoietin-2 and tumor necrosis factor α levels and CPI scores in patients (P < .05). ROC curve analysis indicated that combined diagnosis of serum angiopoietin-2 and tumor necrosis factor α had an AUC of 0.867, with a sensitivity of 85.25% and specificity of 77.87% for detecting acute myocardial infarction complicated with pulmonary infection. Among the sputum culture specimens, gram-negative bacteria accounted for 55.34%, gram-positive bacteria for 39.81%, and fungi for 4.85%. Gram-negative bacteria like Klebsiella pneumoniae and Escherichia coli showed high resistance to various antibiotics, while gram-positive bacteria like Streptococcus pneumoniae and Staphylococcus aureus had relatively low resistance to specific antibiotics. Conclusion: Gram-negative bacteria were the main pathogens and exhibited resistance to several antibiotics. Increased levels of angiopoietin-2 and tumor necrosis factor α were observed. Early detection of these markers can assist in the clinical diagnosis and guide the appropriate use of antibiotics.

Self-Biased Magneto-Electric Antenna for Very-Low-Frequency Communications: Exploiting Magnetization Grading and Asymmetric Structure-Induced Resonance.

VLF magneto-electric (ME) antennas have gained attention for their compact size and high radiation efficiency in lossy conductive environments. However, the need for a large DC magnetic field bias presents challenges for miniaturization, limiting portability. This study introduces a self-biased ME antenna with an asymmetric design using two magneto materials, inducing a magnetization grading effect that reduces the resonant frequency during bending. Operating principles are explored, and performance parameters, including the radiation mechanism, intensity and driving power, are experimentally assessed. Leveraging its excellent direct and converse magneto-electric effect, the antenna proves adept at serving as both a transmitter and a receiver. The results indicate that, at 2.09 mW and a frequency of 24.47 kHz, the antenna has the potential to achieve a 2.44 pT magnetic flux density at a 3 m distance. A custom modulation-demodulation circuit is employed, applying 2ASK and 2PSK to validate communication capability at baseband signals of 10 Hz and 100 Hz. This approach offers a practical strategy for the lightweight and compact design of VLF communication systems.

Monomeric CXCL12-Engineered Adipose-Derived Stem Cells Transplantation for the Treatment of Ischemic Stroke.

Adipose-derived stem cells (ASCs) possess therapeutic potential for ischemic brain injury, and the chemokine CXCL12 has been shown to enhance their functional properties. However, the cumulative effects of ASCs when combined with various structures of CXCL12 on ischemic stroke and its underlying molecular mechanisms remain unclear. In this study, we genetically engineered mouse adipose-derived ASCs with CXCL12 variants and transplanted them to the infarct region in a mice transient middle cerebral artery occlusion (tMCAO) model of stroke. We subsequently compared the post-ischemic stroke efficacy of ASC-mCXCL12 with ASC-dCXCL12, ASC-wtCXCL12, and unmodified ASCs. Neurobehavior recovery was assessed using modified neurological severity scores, the hanging wire test, and the elevated body swing test. Changes at the tissue level were evaluated through cresyl violet and immunofluorescent staining, while molecular level alterations were examined via Western blot and real-time PCR. The results of the modified neurological severity score and cresyl violet staining indicated that both ASC-mCXCL12 and ASC-dCXCL12 treatment enhanced neurobehavioral recovery and mitigated brain atrophy at the third and fifth weeks post-tMCAO. Additionally, we observed that ASC-mCXCL12 and ASC-dCXCL12 promoted angiogenesis and neurogenesis, accompanied by an increased expression of bFGF and VEGF in the peri-infarct area of the brain. Notably, in the third week after tMCAO, the ASC-mCXCL12 exhibited superior outcomes compared to ASC-dCXCL12. However, when treated with the CXCR4 antagonist AMD3100, the beneficial effects of ASC-mCXCL12 were reversed. The AMD3100-treated group demonstrated worsened neurological function, aggravated edema volume, and brain atrophy. This outcome is likely attributed to the interaction of monomeric CXCL12 with CXCR4, which regulates the recruitment of bFGF and VEGF. This study introduces an innovative approach to enhance the therapeutic potential of ASCs in treating ischemic stroke by genetically engineering them with the monomeric structure of CXCL12.

Drug-target interaction prediction based on spatial consistency constraint and graph convolutional autoencoder.

BACKGROUND: Drug-target interaction (DTI) prediction plays an important role in drug discovery and repositioning. However, most of the computational methods used for identifying relevant DTIs do not consider the invariance of the nearest neighbour relationships between drugs or targets. In other words, they do not take into account the invariance of the topological relationships between nodes during representation learning. It may limit the performance of the DTI prediction methods. RESULTS: Here, we propose a novel graph convolutional autoencoder-based model, named SDGAE, to predict DTIs. As the graph convolutional network cannot handle isolated nodes in a network, a pre-processing step was applied to reduce the number of isolated nodes in the heterogeneous network and facilitate effective exploitation of the graph convolutional network. By maintaining the graph structure during representation learning, the nearest neighbour relationships between nodes in the embedding space remained as close as possible to the original space. CONCLUSIONS: Overall, we demonstrated that SDGAE can automatically learn more informative and robust feature vectors of drugs and targets, thus exhibiting significantly improved predictive accuracy for DTIs.

Repeat-Enhancing Featured Ion-Guided Stoichiometry for Identification and Quantification of Direct Infusion Proteome.

The direct infusion-shotgun proteome analysis (DI-SPA) alongside data-independent acquisition mass spectrometry achieved fast proteome identification and quantification without chromatographic separation. However, robust peptide identification and quantification (label and label-free) for the DI-SPA data is still insufficient. We find that in the absence of chromatography, the identification of DI-SPA can be boosted by extending acquisition cycles repeatedly and maximizing the utilization of the featured repetition characteristics, combined with the machine learning-based automatic peptide scoring strategy. Here, we present the repeat-enhancing featured ion-guided stoichiometry (RE-FIGS), a complete and compact solution to (repeated) DI-SPA data. Using our strategy, the peptide identification can be improved above 30% with high reproducibility (70.0%). Notably, the label-free quantification of repeated DI-SPA can be successfully obtained with high accuracy (mean median error, 0.108) and high reproducibility (median error, 0.001). We believe our RE-FIGS method could boost the broad application of the (repeated) DI-SPA method and offer a new choice for proteomic analysis.

Spastic paraplegia type 76 due to novel CAPN1 mutations: three case reports with literature review.

Spastic paraplegia type 76 (SPG76) is a subtype of hereditary spastic paraplegia (HSP) caused by calpain-1 (CAPN1) mutations. Our study described the phenotypic and genetic characteristics of three families with spastic ataxia due to various CAPN1 mutations and further explored the pathogenesis of the two novel mutations. The three patients were 48, 39, and 48 years old, respectively. Patients 1 and 3 were from consanguineous families, while patient 2 was sporadic. Physical examination showed hypertonia, hyperreflexia, and Babinski signs in the lower limbs. Patients 2 and 3 additionally had dysarthria and depression. CAPN1 mutations were identified by whole-exome sequencing, followed by Sanger sequencing and co-segregation analysis within the family. Functional examination of the newly identified mutations was further explored. Two homozygous mutations were detected in patient 1 (c.213dupG, p.D72Gfs*95) and patient 3 (c.1729+1G>A) with HSP, respectively. Patient 2 had compound heterozygous mutations c.853C>T (p.R285X) and c.1324G>A (p.G442S). Western blotting revealed the p.D72Gfs*95 with a smaller molecular weight than WT and p.G442S. In vitro, the wild-type calpain-1 is mostly located in the cytoplasm and colocalized with tubulin by immunostaining. However, p.D72Gfs*95 and p.G442S abnormally formed intracellular aggregation, with little colocalization with tubulin. In this study, we identified three cases with SPG76, due to four various CAPN1 mutations, presenting lower limb spasticity and ataxia, with or without bulbar involvement and emotional disorder. Among these, c.213dupG and c.1324G>A are first identified in this paper. The genotype-phenotype correlation of the SPG76 cases reported worldwide was further summarized.

De novo myeloid sarcoma mimicking gynecological tumors: a retrospective case series of eight patients.

OBJECTIVE: To describe myeloid sarcoma (MS) that mimic gynecological tumors and provide guidelines for improving the diagnosis and treatment of patients. METHODS: This case series study retrospectively analyzed the clinicopathological characteristics and oncological outcomes of female patients who were histologically diagnosed with MS after initially presenting with reproductive-system tumors at the Peking Union Medical College Hospital between January 2000 and March 2022. RESULTS: There were eight cases in which MS mimicked cervical cancer, ovarian cancer, or hysteromyoma. Six patients had isolated MS, and the other two had acute myeloid leukemia (AML)-M2. The average age was 39.00 ± 14.26. They each sought advice from a gynecological oncologist at the initial visit, complaining of irregular bleeding (3/8), low abdominal pain (3/8), dysmenorrhea (1/8), or an accidentally found mass (1/8). CT/MRI exams revealed that the average tumor size reached 5.65 ± 2.35 cm, with 50% of the tumors being larger than 8 cm. The final diagnoses were confirmed by biopsy (2/8) or postoperative pathology (6/8); the most frequent positive immunohistochemical markers were Ki-67 (60-90%), MPO (100%), LCA (62.5%), CD43 (62.5%), CD117 (62.5%), CD99 (50%), vimentin (37.5%), and lysozyme (25%). MLL/AF9 gene fusions and CEBPA, JAK2, NRAS, and FLT3-TKD mutations were found in the patients. Six (75%) of the patients showed a complete response after upfront treatment using chemotherapy + surgery and experienced no recurrence during follow-up. The overall survival (OS) rate was 72.9%, and the 5-year OS rate was 72.9% (95%CI: 0.4056-1.000). The median OS was 26 months (range: 3-82). CONCLUSION: For patients with isolated MS, treatment by chemotherapy and surgery are radical procedure, and initial treatment using chemotherapy alone should be considered for MS with synchronous intramedullary AML. Poor response to chemotherapy, short interval to leukemia occurrence, and heavy tumor burden (> 10 cm) could indicate a poor prognosis for patients with MS.

A Membrane Tension-Responsive Mechanosensitive DNA Nanomachine.

Membrane curvature reflects physical forces operating on the lipid membrane, which plays important roles in cellular processes. Here, we design a mechanosensitive DNA (MSD) nanomachine that mimics natural mechanosensitive PIEZO channels to convert the membrane tension changes of lipid vesicles with different sizes into fluorescence signals in real time. The MSD nanomachine consists of an archetypical six-helix-bundle DNA nanopore, cholesterol-based membrane anchors, and a solvatochromic fluorophore, spiropyran (SP). We find that the DNA nanopore effectively amplifies subtle variations of the membrane tension, which effectively induces the isomerization of weakly emissive SP into highly emissive merocyanine isomers for visualizing membrane tension changes. By measuring the membrane tension via the fluorescence of MSD nanomachine, we establish the correlation between the membrane tension and the curvature that follows the Young-Laplace equation. This DNA nanotechnology-enabled strategy opens new routes to studying membrane mechanics in physiological and pathological settings.

TreeQNet: a webserver for Treatment evaluation with Quantified Network.

BACKGROUND: Personalized therapy has been at the forefront of cancer care, making cancer treatment more effective. Since cancer patients respond individually to drug therapy, predicting the sensitivity of each patient to specific drugs is very helpful to apply therapeutic agents. Traditional methods focus on node (molecular) information but ignore relevant interactions among different nodes, which has very limited application in complex situations, such as cancer drug responses in real clinical practice. RESULTS: Treatment evaluation with Quantified Network (TreeQNet) is a webserver which could predict sensitivity to drugs for patients through the innovative use of proteomic and phosphoproteomic network from tumor tissues. CONCLUSION: TreeQNet service: http://bioinfo.ustc.edu.cn/ . TreeQNet source code: https://github.com/Really00/treeqnet-web-front/ .

TMEM151A Variants Cause Paroxysmal Kinesigenic Dyskinesia: A Large-Sample Study.

BACKGROUND: Paroxysmal kinesigenic dyskinesia (PKD) is the most common type of paroxysmal dyskinesias. Only one-third of PKD patients are attributed to proline-rich transmembrane protein 2 (PRRT2) mutations. OBJECTIVE: We aimed to explore the potential causative gene for PKD. METHODS: A cohort of 196 PRRT2-negative PKD probands were enrolled for whole-exome sequencing (WES). Gene Ranking, Identification and Prediction Tool, a method of case-control analysis, was applied to identify the candidate genes. Another 325 PRRT2-negative PKD probands were subsequently screened with Sanger sequencing. RESULTS: Transmembrane Protein 151 (TMEM151A) variants were mainly clustered in PKD patients compared with the control groups. 24 heterozygous variants were detected in 25 of 521 probands (frequency = 4.80%), including 18 missense and 6 nonsense mutations. In 29 patients with TMEM151A variants, the ratio of male to female was 2.63:1 and the mean age of onset was 12.93 ± 3.15 years. Compared with PRRT2 mutation carriers, TMEM151A-related PKD were more common in sporadic PKD patients with pure phenotype. There was no significant difference in types of attack and treatment outcome between TMEM151A-positive and PRRT2-positive groups. CONCLUSIONS: We consolidated mutations in TMEM151A causing PKD with the aid of case-control analysis of a large-scale WES data, which broadens the genotypic spectrum of PKD. TMEM151A-related PKD were more common in sporadic cases and tended to present as pure phenotype with a late onset. Extensive functional studies are needed to enhance our understanding of the pathogenesis of TMEM151A-related PKD. © 2021 International Parkinson and Movement Disorder Society.

Role of puerarin in pathological cardiac remodeling: A review.

Pathological cardiac remodeling normally involves changes in structure, function, and energy metabolism of the heart induced by cardiac injury or load, terminally leading to heart failure. Cardiac remodeling plays an essential role in the progression of cardiovascular disease, thus increasingly identified as an important therapeutic target for heart failure of all pathogenesis. Puerarin, as a natural isoflavone mainly from Pueraria lobata （Willd.）Ohwi, has been developed as injections, eye drops, microemulsions, etc., and is widely used in the clinical treatment of cardiovascular diseases in eastern Asia countries. In recent years, a growing number of studies have shown that puerarin significantly inhibits myocardial hypertrophic growth, myocyte death, fetal gene expression, fibroblast proliferation and activation, improves energy metabolism, promotes post-infarction angiogenesis, and suppresses inflammation and oxidative stress, consequently attenuating or preventing cardiac remodeling in response to multiple stimuli ( e.g., pressure overload, MIRI, MI, Iso, and Ang II stimulation). This review summarized the roles and underlying molecular mechanisms of puerarin in cardiac remodeling induced by diverse etiologies, aiming to help develop novel therapeutic strategies to prevent or reverse pathological ventricular remodeling.

Lipid metabolism-related gene prognostic index (LMRGPI) reveals distinct prognosis and treatment patterns for patients with early-stage pulmonary adenocarcinoma.

Background: Lipid metabolism plays a pivotal role in cancer progression and metastasis. This study aimed to investigate the prognostic value of lipid metabolism-related genes (LMRGs) in early-stage lung adenocarcinoma (LUAD) and develop a lipid metabolism-related gene prognostic index (LMRGPI) to predict their overall survival (OS) and treatment response. Methods: A total of 774 early-stage LUAD patients were identified from The Cancer Genome Atlas (TCGA, 403 patients) database and Gene Expression Omnibus (GEO, 371 patients) database. The non-negative Matrix Factorization (NMF) algorithm was used to identify different population subtypes based on LMRGs. The Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate Cox regression analyses were used to develop the LMRGPI, with receiver operating characteristic (ROC) curves and concordance index being used to evaluate its performance. The characteristics of mutation landscape, enriched pathways, tumor microenvironment (TME), and treatment response between different LMRGPI groups were also investigated. Results: We identified two population subtypes based on LMRGs in the TCGA-LUAD cohort, with distinct prognosis, TME, and immune status being observed. LMRGPI was developed based on the expression levels of six LMRGs, including ANGPTL4, NPAS2, SLCO1B3, ACOXL, ALOX15, and B3GALNT1. Higher LMRGPI was correlated with poor OS both in TCGA and GSE68465 cohorts. Two nomograms were established to predict the survival probability of early-stage LUAD, with higher consistencies being observed between the predicted and actual OS. Higher LMRGPI was significantly correlated with more frequent TP53 mutation, higher tumor mutation burden (TMB), and up-regulation of CD274. Besides, patients with higher LMRGPI presented unremarkable responses for gefitinib, erlotinib, cisplatin, and vinorelbine, while they tend to have a favorable response for immune checkpoint inhibitors (ICIs). The opposite results were observed in the low-LMRGPI group. Conclusions: We comprehensively investigated the prognostic value of LMRGs in early-stage LUAD. Given its good prognostic ability, LMRGPI could serve as a promising biomarker to predict the OS and treatment response of these patients.

Progress of targeted and immunotherapy for hepatocellular carcinoma and the application of next-generation sequencing.

Hepatocellular carcinoma (HCC), leading cancer worldwide, has a high degree of genetic heterogeneity; next-generation sequencing (NGS) technology has contributed significantly to the discovery of driving genes as well as high-frequency mutations in HCC. The detection of gene alterations may allow us to predict prognosis and adverse drug reactions for individuals, paving the way for personalized medicine in HCC patients. In this review, we summarized the common systemic therapy regimens for HCC and the predictive efficacy of genetic biomarkers on the prognosis of patients under these treatments. Finally, we put forward a future perspective on the potential of NGS technology for the guidance of targeted therapy and immunotherapy in HCC.

Uneven paths: Soft Policy's benefits to recovery in Louisiana Parishes after Hurricanes Katrina and Rita.

Factors driving community recovery trajectories after disaster are not well understood. We assess why some communities show stronger recoveries from disaster than others, examining the role of four policy toolkits that U.S. county governments frequently adopt to recover from disaster. Using mixed methods, we examine the cases of Hurricanes Katrina and Rita with a novel dataset of recovery policies adopted within each Louisiana parish following the disasters. We typologize recovery strategies and analyze policy adoption patterns after crises. To compare which policy toolkit leads to the best recovery outcomes, we use synthetic control experiments on the 20 parishes hit by Hurricanes Katrina and Rita between August and September 2005, tracking net income inflow and net in-migration measures from 1997 to 2018 over 1408 parish-year observations, paired with qualitative case studies of parish policies and recovery outcomes. On average, soft and local recovery policies focused on community policies and feedback helped parishes stem the flow of finances away from the disaster-zone, as did infrastructural 'hard' policies, to a degree. in comparison, state policies focused on top-down planning experienced weaker recovery. Evidence shows that soft and local policy toolkits can accelerate recovery and that governments seeking to rebuild infrastructure should invest in locally-engaged community development in order to attain better overall recovery.

DNA-Encoded Gold-Gold Wettability for Programmable Plasmonic Engineering.

Controlling the deposition and diffusion of adsorbed atoms (adatoms) on the surface of a solid material is vital for engineering the shape and function of nanocrystals. Here, we report the use of single-stranded DNA (oligo-adenine, oligo-A) to encode the wettability of gold seeds by homogeneous gold adatoms to synthesize highly tunable plasmonic nanostructures. We find that the oligo-A attachment transforms the nanocrystal growth mode from the classical Frank-van der Merwe to the Volmer-Weber island growth. Finely tuning the oligo-A density can continuously change the gold-gold contact angle (θ) from 35.1±3.6° to 125.3±8.0°. We further demonstrate the versatility of this strategy for engineering nanoparticles with different curvature and dimensions. With this unconventional growth mode, we synthesize a sub-nanometer plasmonic cavity with a geometrical singularity when θ>90°. Superfocusing of light in this nanocavity produces a near-infrared intraparticle plasmonic coupling, which paves the way to surface engineering of single-particle plasmonic devices.