Observations of the effectiveness, dosage, and prognosis of intensity-modulated radiation therapy under ultrasonic guidance for cervical cancer patients.

BACKGROUND: Volumetric modulated arc therapy (VMAT) guided by ultrasound is a novel radiation therapy technique that facilitates the delineation of the tumor target area under image guidance, enhancing the precision of radiation therapy and maximizing the protection of surrounding tissues. OBJECTIVE: The objective of this paper is to investigate the effectiveness of VMAT under ultrasonic guidance for cervical cancer patients and its impact on radiotherapy dosage and prognosis. METHODS: A retrospective analysis encompassed 128 instances of cervical cancer patients who were admitted to our medical facility between April 2019 and April 2021. The patients were categorized into an observation cohort and a control cohort, depending on variations in treatment modalities post-admission. The control group underwent conventional radiotherapy, whereas the observation group received VMAT guided by ultrasound. Clinical efficacy, average radiation dosages (in the radiotherapy target area, rectum, and bladder), radiotherapy-related toxicities during treatment, and one-year survival rates were compared between the two groups. Additionally, variances in pre- and post-treatment serum levels of squamous cell carcinoma antigen (SCC-Ag), carcinoembryonic antigen (CEA), and carbohydrate antigen 724 (CA724) were subjected to assessment. RESULTS: When compared to the control group (64.52%), the observation cohort's comprehensive effectiveness rate was considerably greater (80.30%). The observation group saw lower average radiation exposures and a reduction in the post-treatment concentrations of CEA, SCC-Ag, and CA724. The overall incidence of adverse effects from radiation treatment also declined. The observation group had a greater one-year survival rate (90.48%) than the control group (73.33%). When comparing the observation cohort to the control group, Kaplan-Meier survival analysis showed a significantly higher one-year survival rate (Log-Rank = 6.530, P= 0.011). CONCLUSION: VMAT guided by ultrasound for patients with cervical cancer demonstrates promising short- and long-term treatment outcomes. It also leads to improvements in serum CEA, SCC-Ag, and CA724 levels, as well as reductions in the average radiation dosages to the radiotherapy target area, rectum, and bladder. This approach warrants attention from clinicians in clinical practice.

Dermal FOXO3 activity in response to Wnt/ß-catenin signaling is required for feather follicle development of goose embryos (Anser cygnoides).

Feather is an important economic trait of poultry, and growth and development state of feathers plays an important role in the economic value of poultry. Dermal fibroblasts are required for structural integrity of the skin and for feather follicle development. How FOXO3 affects feather follicle development as skin tissues change during goose embryo (Anser cygnoides) development and growth is not well understood. Here, we demonstrate that in vitro culture of single feathers and skin tissue results in changes in feather morphological structure by adding drugs to the culture medium that affect FOXO3 expression. We used feather follicles to show that during growth, the root location of feathers, the dermis layer, affects cell proliferation and apoptosis and regulates the expression of major genes in the Wingless-types/beta-catenin (Wnt/ß-catenin) signaling pathway through the activity of FOXO3 in dermal fibroblasts. Feathers and dorsal skin tissues develop the correct structure, but feather length and width and feather follicle diameter change significantly (p < 0.05) without significant changes in feather follicle density (p > 0.05). Transfected dermal fibroblasts also showed that FOXO3 affected the formation and development of feather follicles in the embryonic stage by regulating the Wnt/ß-catenin signaling pathway. Therefore, this study reveals the critical role of dermal fibroblast-FOXO3-induced Wnt/ß-catenin signaling in promoting the formation and development of embryonic feather follicles.

Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches.

Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically developing (TD) peers are visible to the eye, but quantifications of those differences outside of the gait laboratory have been elusive. In this work, we measured vertical, mediolateral, and anteroposterior acceleration using a waist-worn iPhone accelerometer during ambulation across a typical range of velocities. Fifteen TD and fifteen DMD children from 3 to 16 years of age underwent eight walking/running activities, including five 25 m walk/run speed-calibration tests at a slow walk to running speeds (SC-L1 to SC-L5), a 6-min walk test (6MWT), a 100 m fast walk/jog/run (100MRW), and a free walk (FW). For clinical anchoring purposes, participants completed a Northstar Ambulatory Assessment (NSAA). We extracted temporospatial gait clinical features (CFs) and applied multiple machine learning (ML) approaches to differentiate between DMD and TD children using extracted temporospatial gait CFs and raw data. Extracted temporospatial gait CFs showed reduced step length and a greater mediolateral component of total power (TP) consistent with shorter strides and Trendelenberg-like gait commonly observed in DMD. ML approaches using temporospatial gait CFs and raw data varied in effectiveness at differentiating between DMD and TD controls at different speeds, with an accuracy of up to 100%. We demonstrate that by using ML with accelerometer data from a consumer-grade smartphone, we can capture DMD-associated gait characteristics in toddlers to teens.

A primer on the use of machine learning to distil knowledge from data in biological psychiatry.

Applications of machine learning in the biomedical sciences are growing rapidly. This growth has been spurred by diverse cross-institutional and interdisciplinary collaborations, public availability of large datasets, an increase in the accessibility of analytic routines, and the availability of powerful computing resources. With this increased access and exposure to machine learning comes a responsibility for education and a deeper understanding of its bases and bounds, borne equally by data scientists seeking to ply their analytic wares in medical research and by biomedical scientists seeking to harness such methods to glean knowledge from data. This article provides an accessible and critical review of machine learning for a biomedically informed audience, as well as its applications in psychiatry. The review covers definitions and expositions of commonly used machine learning methods, and historical trends of their use in psychiatry. We also provide a set of standards, namely Guidelines for REporting Machine Learning Investigations in Neuropsychiatry (GREMLIN), for designing and reporting studies that use machine learning as a primary data-analysis approach. Lastly, we propose the establishment of the Machine Learning in Psychiatry (MLPsych) Consortium, enumerate its objectives, and identify areas of opportunity for future applications of machine learning in biological psychiatry. This review serves as a cautiously optimistic primer on machine learning for those on the precipice as they prepare to dive into the field, either as methodological practitioners or well-informed consumers.

Genetic susceptibility modifies the association of long-term air pollution exposure on Parkinson's disease.

Inconsistent findings exist regarding the potential association between polluted air and Parkinson's disease (PD), with unclear insights into the role of inherited sensitivity. This study sought to explore the potential link between various air pollutants and PD risk, investigating whether genetic susceptibility modulates these associations. The population-based study involved 312,009 initially PD-free participants with complete genotyping data. Annual mean concentrations of PM2.5, PM10, NO2, and NOx were estimated, and a polygenic risk score (PRS) was computed to assess individual genetic risks for PD. Cox proportional risk models were employed to calculate hazard ratios (HR) and 95% confidence intervals (CI) for the associations between ambient air pollutants, genetic risk, and incident PD. Over a median 12.07-year follow-up, 2356 PD cases (0.76%) were observed. Compared to the lowest quartile of air pollution, the highest quartiles of NO2 and PM10 pollution showed HRs and 95% CIs of 1.247 (1.089-1.427) and 1.201 (1.052-1.373) for PD incidence, respectively. Each 10 µg/m3 increase in NO2 and PM10 yielded elevated HRs and 95% CIs for PD of 1.089 (1.026-1.155) and 1.363 (1.043-1.782), respectively. Individuals with significant genetic and PM10 exposure risks had the highest PD development risk (HR: 2.748, 95% CI: 2.145-3.520). Similarly, those with substantial genetic and NO2 exposure risks were over twice as likely to develop PD compared to minimal-risk counterparts (HR: 2.414, 95% CI: 1.912-3.048). Findings suggest that exposure to air contaminants heightens PD risk, particularly in individuals genetically predisposed to high susceptibility.

Injectable Ozone-Rich Nanocomposite Hydrogel Loaded with D-Mannose for Anti-Inflammatory and Cartilage Protection in Osteoarthritis Treatment.

Osteoarthritis (OA) is a dynamic condition characterized by cartilage damage and synovial inflammation. Ozone (O3 ) shows potential therapeutic effects owing to its anti-inflammatory properties; however, its high reactivity and short half-life substantially limit its effectiveness in OA treatment. In this study, an ozone-rich thermosensitive nanocomposite hydrogel loaded with D-mannose is developed for OA treatment. Briefly, O3 is encapsulated in nanoparticles (NPs) composed of perfluorotributylamine and fluorinated hyaluronic acid to improve its stability. Next, D-mannose is conjugated with α-amino of the hydroxypropyl chitin (HPCH) via Schiff base to prepare MHPCH. These nanoparticles are encapsulated in MHPCH to produce O3 NPs@MHPCH. In vitro cell experiments demonstrate that the O3 NPs@MHPCH treatment significantly reduced VEGF and inflammation levels, accompanied by a decrease in inflammatory factors such as IL-1ß, IL-6, TNF-α, and iNOS. Furthermore, O3 NPs@MHPCH promotes the expression of collagen II and aggrecan and stimulates chondrocyte proliferation. Additionally, in vivo studies show that O3 NPs@MHPCH significantly alleviated OA by reducing synovial inflammation, cartilage destruction, and subchondral bone remodeling. O3 NPs@MHPCH offers a promising option for improving the efficacy of O3 therapy and reducing the risk of synovial inflammation and cartilage degeneration in OA.

Regulating Anionic Redox via Mg Substitution in Mn-Rich Layered Oxide Cathodes Enabling High Electrochemical Stability for Sodium-Ion Batteries.

With the limited resources and high cost of lithium-ion batteries (LIBs) and the ever-increasing market demands, sodium-ion batteries (SIBs) gain much interest due to their economical sustainability, and similar chemistry and manufacturing processes to LIBs. As cathodes play a vital role in determining the energy density of SIBs, Mn-based layered oxides are promising cathodes due to their low cost, environmental friendliness, and high theoretical capacity. However, the main challenge is structural instability upon cycling at high voltage. Herein, Mg is introduced into the P2-type Na0.62 Ni0.25 Mn0.75 O2 cathode to enhance electrochemical stability. By combining electrochemical testing and material characterizations, it is found that substituting 10 mol% Mg can effectively alleviate the P2-O2 phase transition, Jahn-Teller distortion, and irreversible oxygen redox. Moreover, structural integrity is greatly improved. These lead to enhanced electrochemical performances. With the optimized sample, a remarkable capacity retention of 92% in the half cell after 100 cycles and 95% in the full cell after 170 cycles can be achieved. Altogether, this work provides an alternative way to stabilize P2-type Mn-based layer oxide cathodes, which in turn, put forward the development of this material for the next-generation SIBs.

Aberrant SUMO2/3 modification of RUNX1 upon SENP1 inhibition is linked to the development of diabetic retinopathy in mice.

Our previous report established that RUNX family transcription factor 1 (RUNX1) promotes proliferation of mouse retinal microvascular endothelial cells (mRMECs) and exacerbates diabetic retinopathy (DR). However, the mechanism behind the upregulation of RUNX1 remains unclear. This study aims to investigate the possible correlation between histone SUMOylation and RUNX1 in DR, as well as the involved molecules. A mouse model of diabetes was induced by streptozotocin (STZ). These mice had increased retinal thickness and elevated production of inflammatory cytokines. Additionally, they showed elevated levels of SUMO1 and SUMO2/3, but reduced levels of SUMO specific peptidase 1 (SENP1) in retinal tissues. Co-immunoprecipitation and Western blot assays revealed that the RUNX1 protein was primarily modified by SUMO2/3, and SENP1 inhibited SUMO2/3 modification, thereby reducing RUNX1 expression. Overexpression of SENP1 alleviated symptoms in mice and alleviated inflammation. In vitro experiments demonstrated that the SENP1 overexpression suppressed the proliferation, migration, and angiogenesis of high-glucose-induced mRMECs. However, further overexpression of RUNX1 counteracted the alleviating effects of SENP1 both in vivo and in vitro. In conclusion, this study demonstrates that the downregulation of SENP1 in DR leads to SUMO2/3-dependent activation of RUNX1. This activation promotes proliferation of mRMECs and exacerbates DR symptoms in mice.

Plasma ß2-microglobulin and cerebrospinal fluid biomarkers of Alzheimer's disease pathology in cognitively intact older adults: the CABLE study.

BACKGROUND: Previous studies have suggested a correlation between elevated levels of ß2-microglobulin (B2M) and cognitive impairment. However, the existing evidence is insufficient to establish a conclusive relationship. This study aims to analyze the link of plasma B2M to cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers and cognition. METHODS: To track the dynamics of plasma B2M in preclinical AD, 846 cognitively healthy individuals in the Chinese Alzheimer's Biomarker and LifestylE (CABLE) cohort were divided into four groups (suspected non-AD pathology [SNAP], 2, 1, 0) according to the NIA-AA criteria. Multiple linear regression models were employed to examine the plasma B2M's relationship with cognitive and CSF AD biomarkers. Causal mediation analysis was conducted through 10,000 bootstrapped iterations to explore the mediating effect of AD pathology on cognition. RESULTS: We found that the levels of plasma B2M were increased in stages 1 (P = 0.0007) and 2 (P < 0.0001), in contrast to stage 0. In total participants, higher levels of B2M were associated with worse cognitive performance (P = 0.006 for MMSE; P = 0.012 for MoCA). Moreover, a higher level of B2M was associated with decreases in Aß1-42 (P < 0.001) and Aß1-42/Aß1-40 (P = 0.015) as well as increases in T-tau/Aß1-42 (P < 0.001) and P-tau/Aß1-42 (P < 0.001). The subgroup analysis found B2M correlated with Aß1-42 in non-APOE ε4 individuals (P < 0.001) but not in APOE ε4 carriers. Additionally, the link between B2M and cognition was partially mediated by Aß pathology (percentage: 8.6 to 19.3%), whereas tau pathology did not mediate this effect. CONCLUSIONS: This study demonstrated the association of plasma B2M with CSF AD biomarkers as well as a possible important role of Aß pathology in the association between B2M and cognitive impairment, particularly in cognitively normal individuals. The results indicated that B2M could be a potential biomarker for preclinical AD and might have varied functions throughout various stages of preclinical AD progression.

Differences between ante mortem Alzheimer's disease biomarkers in predicting neuropathology at autopsy.

INTRODUCTION: This study aimed to assess whether biomarkers related to amyloid, tau, and neurodegeneration can accurately predict Alzheimer's disease (AD) neuropathology at autopsy in early and late clinical stages. METHODS: We included 100 participants who had ante mortem biomarker measurements and underwent post mortem neuropathological examination. Based on ante mortem clinical diagnosis, participants were divided into non-dementia and dementia, as early or late clinical stages. RESULTS: Amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) amyloid beta (Aß)42/phosphorylated tau (p-tau)181 showed excellent performance in differentiating autopsy-confirmed AD and predicting the risk of neuropathological changes in early and late clinical stages. However, CSF Aß42 performed better in the early clinical stage, while CSF p-tau181, CSF t-tau, and plasma p-tau181 performed better in the late clinical stage. DISCUSSION: Our findings provide important clinical information that, if using PET, CSF, and plasma biomarkers to detect AD pathology, researchers must consider their differential performances at different clinical stages of AD. HIGHLIGHTS: Amyloid PET and CSF Aß42/p-tau181 were the most promising candidate biomarkers for predicting AD pathology. CSF Aß42 can serve as a candidate predictive biomarker in the early clinical stage of AD. CSF p-tau181, CSF t-tau, and plasma p-tau181 can serve as candidate predictive biomarkers in the late clinical stage of AD. Combining APOE ε4 genotypes can significantly improve the predictive accuracy of AD-related biomarkers for AD pathology.

Sleep duration and risk of cardio-cerebrovascular disease: A dose-response meta-analysis of cohort studies comprising 3.8 million participants.

Background: The effect of extreme sleep duration on the risk of cardiovascular and cerebrovascular diseases (CCDs) remains debatable. The pathology of CCDs is consistent in some respects (e.g., vascular factors), suggesting that there may be an overlapping range of sleep duration associated with a low risk of both diseases We aimed to quantify the dose-response relationship between sleep duration and CCDs. Study objective: To explore whether there is an optimal sleep duration (SD) in reducing the risk of CCDs. Methods: PubMed and EMBASE were searched until June 24, 2022 to include cohort studies that investigated the longitudinal relationships of SD with incident CCDs, including stroke and coronary heart disease (CHD). The robusterror meta-regression model (REMR model) was conducted to depict the dose-response relationships based on multivariate-adjusted risk estimates. Results: A total of 71 cohorts with 3.8 million participants were included for meta-analysis, including 57 for cardiovascular diseases (CVD) and 29 for cerebrovascular disease. A significant U-shaped relationship was revealed of nighttime sleep duration with either cardiovascular or cerebrovascular disease. The nighttime sleep duration associated with a lower risk of CVD was situated within 4.3-10.3 h, with the risk hitting bottom at roughly 7.5 h per night (p non-linearity < 0.0001). Sleep duration associated with a lower risk of cerebrovascular diseases ranges from 5 to 9.7 h per night, with the inflection at 7.5 h per night (p non-linearity = 0.05). Similar non-linear relationship exited in daily sleep duration and CCDs. Other subgroup analyses showed non-linear relationships close to the above results. Conclusion: Rational sleep duration (7.5 h/night) is associated with a reduced risk of cardio-cerebrovascular disease for adults.

Polygenic resilience scores capture protective genetic effects for Alzheimer's disease.

Polygenic risk scores (PRSs) can boost risk prediction in late-onset Alzheimer's disease (LOAD) beyond apolipoprotein E (APOE) but have not been leveraged to identify genetic resilience factors. Here, we sought to identify resilience-conferring common genetic variants in (1) unaffected individuals having high PRSs for LOAD, and (2) unaffected APOE-ε4 carriers also having high PRSs for LOAD. We used genome-wide association study (GWAS) to contrast "resilient" unaffected individuals at the highest genetic risk for LOAD with LOAD cases at comparable risk. From GWAS results, we constructed polygenic resilience scores to aggregate the addictive contributions of risk-orthogonal common variants that promote resilience to LOAD. Replication of resilience scores was undertaken in eight independent studies. We successfully replicated two polygenic resilience scores that reduce genetic risk penetrance for LOAD. We also showed that polygenic resilience scores positively correlate with polygenic risk scores in unaffected individuals, perhaps aiding in staving off disease. Our findings align with the hypothesis that a combination of risk-independent common variants mediates resilience to LOAD by moderating genetic disease risk.

Association of peripheral immunity with cognition, neuroimaging, and Alzheimer's pathology.

BACKGROUND: Neuroinflammation has been considered to be a driving force of Alzheimer's disease. However, the association between peripheral immunity and AD has been rarely investigated. METHODS: Separate regression analyses were conducted to explore the associations among peripheral immune markers and cognition, neuroimaging, and AD pathology. Causal mediation analyses were used to investigate whether the associations with cognition were mediated by AD pathology. RESULTS: A total of 1107 participants (43.9% female, mean age of 73.2 years) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were included. Regression analyses indicated that elevated neutrophils (NEU) count and neutrophil-lymphocyte ratio (NLR) were associated with lower levels of global cognition, memory function (MEM), and executive function (EF), and reduced brain metabolism by 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET) as well as greater ventricular volume. An elevated NLR was associated with a lower level of ß-amyloid (Aß) and a higher level of total tau (T-tau) in cerebrospinal fluid (CSF), smaller hippocampal volume (HV), and lesser entorhinal cortex (EC) thickness. On the contrary, an elevated level of lymphocytes (LYM) was associated with a higher level of Aß and a lower level of T-tau in CSF, better cognition, and less atrophy of brain regions (ventricular volume, HV, and EC thickness). The associations of LYM and NLR with cognition were mediated by Aß and T-tau pathology (proportion: 18%~64%; p < 0.05). CONCLUSIONS: We revealed that two types of peripheral immune cells (NEU and LYM) and the ratio of these two cell types (NLR) had associations with cognition, neuroimaging, and AD pathology. The associations might be mediated by Aß and tau pathology.

New insights into denitrification and phosphorus removal with degradation of polycyclic aromatic hydrocarbons in two-sludge system.

Polycyclic aromatic hydrocarbons (PAHs) have led to failure of waste water treatment plant operations. In this study, a two-sludge system was used to solve this problem of simultaneously removing phosphorus, nitrogen, and PAHs. The results showed that increasing the maximum PAHs concentration to 15 mg/L did not have any negative effect on the removal rates of total nitrogen (79.68%) and chemical oxygen demand (75.94%); however, the phosphorus removal efficiency decreased to 61.16%. The system exhibited a stronger degradation ability for phenanthrene. Thauera, Hydrogenophaga, and Hyphomicrobium were enriched, which resulted in good denitrification, and contributed to PAHs removal. PAHs mixture promoted PAHs functional genes but restrained denitrification functional genes. However, single naphthalene enhanced denitrification functional genes, which confirmed the feasibility of denitrification coupled with PAHs degradation. In conclusion, for the removal of pollutants from sewage treatment, nitrogen and phosphorus removal coupled with PAHs could be maintained by selecting a two-sludge system.

Distribution of antibiotic resistance genes and their association with bacteria and viruses in decentralized sewage treatment facilities.

The distribution of antibiotic resistance genes (ARGs) has been intensively studied in large-scale wastewater treatment plants and livestock sources. However, small-scale decentralized sewage treatment facilities must also be explored due to their possible direct exposure to residents. In this study, six wastewater treatment facilities in developed rural areas in eastern China were investigated to understand their risks of spreading ARGs. Using metagenomics and network analysis tools, ARGs and bacterial and viral communities were identified in the influent (INF) and effluent (EFF) samples. The dominant ARGs belonged to the bacitracin class, which are different from most of municipal wastewater treatment plants (WWTPs). The dominant hosts of ARGs are Acidovorax in bacterial communities and Prymnesiovirus in viral communities. Furthermore, a positive relationship was found between ARGs and phages. The ARGs significantly correlated with phages were all hosted by specific genera of bacteria, indicating that phages had contributed to the ARG's proliferation in sewage treatment facilities. Paying significant concern on the possible enhanced risks caused by bacteria, viruses and their related ARGs in decentralized sewage treatment facilities is necessary. ELECTRONIC SUPPLEMENTARY MATERIAL: Supplementary material is available in the online version of this article at 10.1007/s11783-021-1469-4 and is accessible for authorized users.

Evaluating the Accuracy of Breast Cancer and Molecular Subtype Diagnosis by Ultrasound Image Deep Learning Model.

Background: Breast ultrasound is the first choice for breast tumor diagnosis in China, but the Breast Imaging Reporting and Data System (BI-RADS) categorization routinely used in the clinic often leads to unnecessary biopsy. Radiologists have no ability to predict molecular subtypes with important pathological information that can guide clinical treatment. Materials and Methods: This retrospective study collected breast ultrasound images from two hospitals and formed training, test and external test sets after strict selection, which included 2,822, 707, and 210 ultrasound images, respectively. An optimized deep learning model (DLM) was constructed with the training set, and the performance was verified in both the test set and the external test set. Diagnostic results were compared with the BI-RADS categorization determined by radiologists. We divided breast cancer into different molecular subtypes according to hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression. The ability to predict molecular subtypes using the DLM was confirmed in the test set. Results: In the test set, with pathological results as the gold standard, the accuracy, sensitivity and specificity were 85.6, 98.7, and 63.1%, respectively, according to the BI-RADS categorization. The same set achieved an accuracy, sensitivity, and specificity of 89.7, 91.3, and 86.9%, respectively, when using the DLM. For the test set, the area under the curve (AUC) was 0.96. For the external test set, the AUC was 0.90. The diagnostic accuracy was 92.86% with the DLM in BI-RADS 4a patients. Approximately 70.76% of the cases were judged as benign tumors. Unnecessary biopsy was theoretically reduced by 67.86%. However, the false negative rate was 10.4%. A good prediction effect was shown for the molecular subtypes of breast cancer with the DLM. The AUC were 0.864, 0.811, and 0.837 for the triple-negative subtype, HER2 (+) subtype and HR (+) subtype predictions, respectively. Conclusion: This study showed that the DLM was highly accurate in recognizing breast tumors from ultrasound images. Thus, the DLM can greatly reduce the incidence of unnecessary biopsy, especially for patients with BI-RADS 4a. In addition, the predictive ability of this model for molecular subtypes was satisfactory,which has specific clinical application value.

Laurionite Competes with 2D Ruddlesden-Popper Perovskites During the Saturation Recrystallization Process.

The room-temperature saturation recrystallization (RTSR) method has been extensively used to prepare all-inorganic lead halide perovskite (e.g., CsPbBr3) nanocrystals. Here, we revealed that the composition of the products prepared by the seemingly simple RTSR method could be extremely complex under different experimental parameters. The pH value of the solution and the protonation tendency of the amines influenced by the amounts and types of introduced amines, oleic acid, and water from the environment determined the composition of the final products. PbBr2, 2D Ruddlesden-Popper perovskites (RPPs) formed by perovskite layers separated by intercalating cations, and laurionite Pb(OH)Br would form under acidic, mildly acidic, and alkaline conditions, respectively. Based on the understanding of the formation mechanism, Pb(OH)Br microparticles with well-defined morphologies were prepared, which could be transformed into highly luminescent CH3NH3PbBr3 with the morphology unchanged. The protonated amine behaves as an intercalating layer during the formation of 2D RPPs. Phenylethylamine (PEA) was proven to be an appropriate amine to prepare pure RPP microplates because of its weaker alkalinity compared to aliphatic amines. The prepared (PEA)2PbBr4 RPP microplates showed strong deep-blue light emission with a PL peak at 415 nm, which could be fine-tuned by changing amines. This study proved the complex reaction pathways of the seemingly simple RTSR method and extended the RTSR method into the fabrication of 2D RPPs and laurionite with promising applications in optoelectronic devices.

Pneumocystis jiroveci pneumonia, Nocardia brasiliensis, and Mycobacterium tuberculosis co-infection in a myasthenia gravis patient: A case report.

RATIONALE: Myasthenia gravis (MG) is an autoimmune disorder of the neuromuscular junctions that leads to fluctuating weakness and disabling fatigability. Due to difficulty in breathing caused by weakness of the respiratory muscles, patients with MG are more susceptible to pneumonia and other respiratory infections. As many patients with MG are given immunosuppressive therapy, this makes them more prone to infections. However, coinfection with 3 pathogens is very rare. PATIENT CONCERNS: Here, we report the case of a 41-year-old gentleman with MG who was receiving long-term steroid therapy. He presented with a cough with pale brown expectoration that occurred without obvious inducement, severe pain in the scapula, as well as swelling and weakness of both legs. Despite undergoing treatment, but his symptoms did not improve, prompting two additional hospital admissions over a period of several months. DIAGNOSIS: Bronchoscopy and bronchoalveolar lavage (BAL) were performed, revealing the presence of Pneumocystis jirovecii , Nocardia brasiliensis, and Mycobacterium tuberculosis (MTB). N brasiliensis was identified by positive modified acid-fast Kinyoun staining as well as a positive colony culture identified by matrix-assisted laser desorption ionization-time of flight mass spectrometry from the BAL sample. MTB was confirmed using GeneXpert, and due to the limitations of the culture conditions, methenamine silver stain was used to confirm Pneumocystis jirovecii. Next-generation sequencing (NGS) assay of the BAL samples also confirmed these pathogens. INTERVENTIONS: The patient was transferred to a designated tuberculosis hospital and received anti-infective and anti-TB treatment. OUTCOMES: During treatment at the designated hospital, the patient developed gastrointestinal bleeding and impaired liver function. One month later, he developed multiple organ failure, consolidation of the left lower lung, and pan-drug resistant bacteremia. He refused further treatment and was discharged. CONCLUSION: In conclusion, physicians should be aware of the predisposition of MG patients to co-infections, especially patients with metabolic disorders, to avoid inadequate treatment and poor patient outcomes. Due to the limitations of culture conditions, NGS should be considered as a new technique for identifying pathogens.

Ultrastable Laurionite Spontaneously Encapsulates Reduced-dimensional Lead Halide Perovskites.

Reduced dimensional lead halide perovskites (RDPs) have attracted great research interest in diverse optical and optoelectronic fields. However, their poor stability is one of the most challenging obstacles prohibiting them from practical applications. Here, we reveal that ultrastable laurionite-type Pb(OH)Br can spontaneously encapsulate the RDPs in their formation solution without introducing any additional chemicals, forming RDP@Pb(OH)Br core-shell microparticles. Interestingly, the number of the perovskite layers within the RDPs can be conveniently and precisely controlled by varying the amount of CsBr introduced into the reaction solution. A single RDP@Pb(OH)Br core-shell microparticle composed of RDP nanocrystals with different numbers of perovskite layers can be also prepared, showing different colors under different light excitations. More interestingly, barcoded RDP@Pb(OH)Br microparticles with different parts emitting different lights can also be prepared. The morphology of the emitting microstructures can be conveniently manipulated. The RDP@Pb(OH)Br microparticles demonstrate outstanding environmental, chemical, thermal, and optical stability, as well as strong resistance to anion exchange processes. This study not only deepens our understanding of the reaction processes in the extensively used saturation recrystallization method but also points out that it is highly possible to dramatically improve the performance of the optoelectronic devices through manipulating the spontaneous formation process of Pb(OH)Br.

New Aspects of Ultrasound-Mediated Targeted Delivery and Therapy for Cancer.

Ultrasound-mediated targeted delivery (UMTD), a novel delivery modality of therapeutic materials based on ultrasound, shows great potential in biomedical applications. By coupling ultrasound contrast agents with therapeutic materials, UMTD combines the advantages of ultrasound imaging and carrier, which benefit deep tissue penetration and high concentration aggregation. In this paper we introduced recent advances in ultrasound contrast agents and applications in tumor therapy. Ultrasound contrast agents were categorized by their functions, mainly including thermosensitive, pH-sensitive and photosensitive ultrasound contrast agents. The various applications of UMTD in tumor treatment were summarized as follows: drug therapy, transfection of anti-oncogene, RNA interference, vaccine immunotherapy, monoclonal antibody immunotherapy, adoptive cellular immunotherapy, cytokine immunotherapy, and so on. In the end, we elaborated on the current challenges and provided perspectives of UMTD for clinical applications.