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Abstract Objective White matter hyperintensities (WMH) on brain MRI images are the most common feature of cerebral small vessel disease (CSVD). Studies have yielded divergent findings on the modifiable risk factors for WMH and WMH’s impact on cognitive decline. Mounting evidence suggests sex differences in WMH burden and subsequent effects on cognition. Thus, we aimed to identify sex-specific modifiable risk factors for WMH. We then explored whether there were sex-specific associations of WMH to longitudinal clinical dementia outcomes. Methods Participants aged 49–89 years were recruited at memory clinics and underwent a T2-weighted fluid-attenuated inversion recovery (FLAIR) 3T MRI scan to measure WMH volume. Participants were then recruited for two additional follow-up visits, 1–2 years apart, where clinical dementia rating sum of boxes (CDR-SB) scores were measured. We first explored which known modifiable risk factors for WMH were significant when tested for a sex-interaction effect. We additionally tested which risk factors were significant when stratified by sex. We then tested to see whether WMH is longitudinally associated with clinical dementia that is sex-specific. Results The study utilized data from 713 participants (241 males, 472 females) with a mean age of 72.3 years and 72.8 years for males and females, respectively. 57.3% and 59.5% of participants were diagnosed with mild cognitive impairment (MCI) for males and females, respectively. 40.7% and 39.4% were diagnosed with dementia for males and females, respectively. Of the 713 participants, 181 participants had CDR-SB scores available for three longitudinal time points. Compared to males, females showed stronger association of age to WMH volume. Type 2 Diabetes was associated with greater WMH burden in females but not males. Finally, baseline WMH burden was associated with worse clinical dementia outcomes longitudinally in females but not in males. Discussion Older females have an accelerated increase in cerebrovascular burden as they age, and subsequently are more vulnerable to clinical dementia decline due to CSVD. Additionally, females are more susceptible to the cerebrovascular consequences of diabetes. These findings emphasize the importance of considering sex when examining the consequences of CSVD. Future research should explore the underlying mechanisms driving these sex differences and personalized prevention and treatment strategies. Clinical trial registration The BICWALZS is registered in the Korean National Clinical Trial Registry (Clinical Research Information Service; identifier, KCT0003391). Registration Date 2018/12/14.

Abstract In this study, we address the persistent challenge of providing adequate oxygen to transplanted cells by introducing a respiratoid biosystem. Central to our strategy is the chloroplast-transit-peptide (CTP), crucial for optimal oxygenation. Through conjugation of CTP with alginate, we achieve stabilization of chloroplast structure. Strategically anchored to the outer chloroplast membrane, CTP not only ensures structural integrity but also upregulates key photosynthesis-associated genes. This biosystem demonstrates exceptional efficacy in spontaneously generating oxygen, particularly under hypoxic conditions (~1% pO2). In an application, pancreatic islets encapsulated within the respiratoid biosystem and intraperitoneally implanted in diabetic mice maintain normal glucose levels effectively. Insulin secretion persists for 100 days post-xenotransplantation without the need for immunosuppressant administration, highlighting the reliance on the respiratoid biosystem’s oxygen supply and structural stability. Our study demonstrates the respiratoid biosystem as a platform in tissue engineering, offering a nature-inspired solution to the critical challenge of spontaneous oxygen supply.

Abstract The role of torso computed tomography (CT) in evaluating body composition has been unexplored. This study assessed the potential of low-dose torso CT from positron emission tomography (PET)/CT for analyzing body composition and its relation to muscle strength. We retrospectively recruited 384 healthy Korean adults (231 men, 153 women) who underwent torso 18F-FDG PET/CT, bioelectrical impedance analysis (BIA), and muscle strength tests (handgrip strength [HGS] and knee extension strength [KES]). CT images were segmented into three compartments: torso volumetric, abdominal volumetric, and abdominal areal. Muscle amounts from each compartment were indexed to height (m2). BIA and HGS served as reference standards, with correlation coefficients (r) calculated. Torso muscle volumetric index (TorsoMVI) had the strongest correlations with BIA-derived values (r = 0.80 for men; r = 0.73 for women), surpassing those from the abdominal compartments. TorsoMVI was also correlated significantly with HGS (r = 0.39, p

Abstract Background Serum bone turnover markers offer limited insight into metabolic activity at the individual vertebra level in osteoporosis. This study introduces a novel image-derived bone turnover marker for individual vertebrae to address this limitation, utilizing volumetric density-adjusted quantitative bone single-photon emission computed tomography/computed tomography (SPECT/CT) with [99mTc]Tc-DPD. This retrospective study included 177 lumbar vertebrae from 55 postmenopausal South Korean women. The mean standardized uptake value (SUVmean, g/cm3) and volumetric bone mineral density (vBMD, mg/cm3) were determined within a 2-cm³ volume of interest in the trabecular portion of each vertebra using quantitative SPECT and CT. The density-adjusted mean standardized uptake value (dSUVmean) was calculated by dividing the SUVmean by the vBMD and multiplying by 1,000. Results SUVmean correlated positively with vBMD (r = 0.60, p

Abstract The mass production of high-quality graphene is required for industrial application as a future electronic material. However, the chemical vapor deposition (CVD) systems previously studied for graphene production face bottlenecks in terms of quality, speed, and reproducibility. Herein, we report a novel conveyor CVD system that enables rapid graphene synthesis using liquid precursors. Pristine and nitrogen-doped graphene samples of a size comparable to a smartphone (15 cm × 5 cm) are successfully synthesized at temperatures of 900, 950, and 1000 °C using butane and pyridine, respectively. Raman spectroscopy allows optimization of the rapid-synthesis conditions to achieve uniformity and high quality. By conducting compositional analysis via X-ray photoelectron spectroscopy as well as electrical characterization, it is confirmed that graphene synthesis and nitrogen doping degree can be adjusted by varying the synthesis conditions. Testing the corresponding graphene samples as gas-sensor channels for NH3 and NO2 and evaluating their response characteristics show that the gas sensors exhibit polar characteristics in terms of gas adsorption and desorption depending on the type of gas, with contrasting characteristics depending on the presence or absence of nitrogen doping; nitrogen-doped graphene exhibits superior gas-sensing sensitivity and response speed compared with pristine graphene.

Abstract Digital positron emission tomography/computed tomography (PET/CT) has shown enhanced sensitivity and spatial resolution compared with analog PET/CT. The present study compared the diagnostic performance of digital and analog PET/CT with [68Ga]Ga-PSMA-11 in prostate cancer patients who experienced biochemical recurrence (BCR) after prostatectomy. Forty prostate cancer patients who experienced BCR, defined as serum prostate-specific antigen (PSA) concentrations exceeding 0.2 ng/mL after prostatectomy, were prospectively recruited. These patients were stratified into three groups based on their serum PSA levels. [68Ga]Ga-PSMA-11 was injected into each patient, and images were acquired using both analog and digital PET/CT scanners. Analog and digital PET/CT showed comparable lesion detection rate (71.8% vs. 74.4%), sensitivity (85.0% vs. 90.0%), and positive predictive value (PPV, 100.0% vs. 100.0%). However, digital PET/CT detected more lesions (139 vs. 111) and had higher maximum standardized uptake values (SUVmax, 14.3 vs. 10.3) and higher kappa index (0.657 vs. 0.502) than analog PET/CT, regardless of serum PSA levels. On both analog and digital PET/CT, lesion detection rates and interrater agreement increased with increasing serum PSA levels. Compared with analog PET/CT, digital PET/CT detected more lesions with a higher SUVmax and better interrater agreement in prostate cancer patients who experienced BCR after prostatectomy.

Abstract Suicide is a growing public health problem around the world. The most important risk factor for suicide is underlying psychiatric illness, especially depression. Detailed classification of suicide in patients with depression can greatly enhance personalized suicide control efforts. This study used unstructured psychiatric charts and brain magnetic resonance imaging (MRI) records from a psychiatric outpatient clinic to develop a machine learning-based suicidal thought classification model. The study included 152 patients with new depressive episodes for development and 58 patients from a geographically different hospital for validation. We developed an eXtreme Gradient Boosting (XGBoost)-based classification models according to the combined types of data: independent components-map weightings from brain T1-weighted MRI and topic probabilities from clinical notes. Specifically, we used 5 psychiatric symptom topics and 5 brain networks for models. Anxiety and somatic symptoms topics were significantly more common in the suicidal group, and there were group differences in the default mode and cortical midline networks. The clinical symptoms plus structural brain patterns model had the highest area under the receiver operating characteristic curve (0.794) versus the clinical notes only and brain MRI only models (0.748 and 0.738, respectively). The results were consistent across performance metrics and external validation. Our findings suggest that focusing on personalized neuroimaging and natural language processing variables improves evaluation of suicidal thoughts.

Purpose: Patients with lower urinary tract symptoms (LUTS) often experience comorbid depression and anxiety, yet the mechanisms underlying this association remain incompletely understood. This prospective study aimed to investigate the relationship between depression, anxiety, and LUTS in men. Materials and methods: A prospective study was conducted with 350 male patients who underwent urologic examinations at our institution from January 2021 to December 2021. Of these, 131 patients meeting the inclusion criteria were included. Various questionnaires, including the International Prostate Symptom Score (IPSS) and the Hospital Anxiety and Depression Scale (HADS), as well as LUTS examinations (prostate-specific antigen test, transrectal ultrasonography, and urine flowmetry), were administered. Results: Among the 350 patients, 131 were included in the analysis, with an average age of 58.0 ± 13.69 years. The total IPSS was 18.0 ± 8.69, with the average voiding symptom score at 8.7 ± 5.19 and the average storage symptom score at 6.0 ± 3.27. Both anxiety and depression were found to be correlated with LUTS (P

Abstract Background Ahmed valve implantation demonstrated an increasing proportion in glaucoma surgery, but predicting the successful maintenance of target intraocular pressure remains a challenging task. This study aimed to evaluate the performance of machine learning (ML) in predicting surgical outcomes after Ahmed valve implantation and to assess potential risk factors associated with surgical failure to contribute to improving the success rate. Methods This study used preoperative data of patients who underwent Ahmed valve implantation from 2017 to 2021 at Ajou University Hospital. These datasets included demographic and ophthalmic parameters (dataset A), systemic medical records excluding psychiatric records (dataset B), and psychiatric medications (dataset C). Logistic regression, extreme gradient boosting (XGBoost), and support vector machines were first evaluated using only dataset A. The algorithm with the best performance was selected based on the area under the receiver operating characteristics curve (AUROC). Finally, three additional prediction models were developed using the best performance algorithm, incorporating combinations of multiple datasets to predict surgical outcomes at 1 year. Results Among 153 eyes of 133 patients, 131 (85.6%) and 22 (14.4%) eyes were categorized as the success and failure groups, respectively. The XGBoost was shown as the best-performance model with an AUROC value of 0.684, using only dataset A. The final three further prediction models were developed based on the combination of multiple datasets using the XGBoost model. All datasets combinations demonstrated the best performances in terms of AUROC (dataset A + B: 0.782; A + C: 0.773; A + B + C: 0.801). Furthermore, advancing age was a risk factor associated with a higher surgical failure incidence. Conclusions ML provides some predictive value in predicting the outcomes of Ahmed valve implantation at 1 year. ML evaluation revealed advancing age as a common risk factor for surgical failure.

Obesity triggers inflammatory responses in the microenvironment of white adipose tissue, resulting in chronic systemic inflammation and the subsequent development of non-communicable diseases, including type 2 diabetes, coronary heart disease, and breast cancer. Current therapy approaches for obesity-induced non-communicable diseases persist in prioritizing symptom remission while frequently overlooking the criticality of targeting and alleviating inflammation at its source. Accordingly, this review highlights the importance of the microenvironment of obese white adipose tissue and the promising potential of employing immunotherapy to target it as an effective therapeutic approach for non-communicable diseases induced by obesity. Additionally, this review discusses the challenges and offers perspective about the immunotherapy targeting the microenvironment of obese white adipose tissue.

Abstract Background The association between antihypertensive medication and schizophrenia has received increasing attention; however, evidence of the impact of antihypertensive medication on subsequent schizophrenia based on large-scale observational studies is limited. We aimed to compare the schizophrenia risk in large claims-based US and Korea cohort of patients with hypertension using angiotensin-converting enzyme (ACE) inhibitors versus those using angiotensin receptor blockers (ARBs) or thiazide diuretics. Methods Adults aged 18 years who were newly diagnosed with hypertension and received ACE inhibitors, ARBs, or thiazide diuretics as first-line antihypertensive medications were included. The study population was sub-grouped based on age (> 45 years). The comparison groups were matched using a large-scale propensity score (PS)-matching algorithm. The primary endpoint was incidence of schizophrenia. Results 5,907,522; 2,923,423; and 1,971,549 patients used ACE inhibitors, ARBs, and thiazide diuretics, respectively. After PS matching, the risk of schizophrenia was not significantly different among the groups (ACE inhibitor vs. ARB: summary hazard ratio [HR] 1.15 [95% confidence interval, CI, 0.99–1.33]; ACE inhibitor vs. thiazide diuretics: summary HR 0.91 [95% CI, 0.78–1.07]). In the older subgroup, there was no significant difference between ACE inhibitors and thiazide diuretics (summary HR, 0.91 [95% CI, 0.71–1.16]). The risk for schizophrenia was significantly higher in the ACE inhibitor group than in the ARB group (summary HR, 1.23 [95% CI, 1.05–1.43]). Conclusions The risk of schizophrenia was not significantly different between the ACE inhibitor vs. ARB and ACE inhibitor vs. thiazide diuretic groups. Further investigations are needed to determine the risk of schizophrenia associated with antihypertensive drugs, especially in people aged > 45 years.

Background Perioperative adverse cardiac events (PACE), a composite of myocardial infarction, coronary revascularization, congestive heart failure, arrhythmic attack, acute pulmonary embolism, cardiac arrest, and stroke during 30-day postoperative period, is associated with long-term mortality, but with limited clinical evidence. We compared long-term mortality with PACE using data from nationwide multicenter electronic health records. Methods Data from 7 hospitals, converted to Observational Medical Outcomes Partnership Common Data Model, were used. We extracted records of 277,787 adult patients over 18 years old undergoing non-cardiac surgery for the first time at the hospital and had medical records for more than 180 days before surgery. We performed propensity score matching and then an aggregated meta‑analysis. Results After 1:4 propensity score matching, 7,970 patients with PACE and 28,807 patients without PACE were matched. The meta‑analysis showed that PACE was associated with higher one-year mortality risk (hazard ratio [HR]: 1.33, 95% CI [1.10, 1.60], P = 0.005) and higher three-year mortality (HR: 1.18, 95% CI [1.01, 1.38], P = 0.038). In subgroup analysis, the risk of one-year mortality by PACE became greater with higher-risk surgical procedures (HR: 1.20, 95% CI [1.04, 1.39], P = 0.020 for low-risk surgery; HR: 1.69, 95% CI [1.45, 1.96], P < 0.001 for intermediate-risk; and HR: 2.38, 95% CI [1.47, 3.86], P = 0.034 for high-risk). Conclusions A nationwide multicenter study showed that PACE was significantly associated with increased one-year mortality. This association was stronger in high-risk surgery, older, male, and chronic kidney disease subgroups. Further studies to improve mortality associated with PACE are needed.

Objective: The price of pharmaceuticals is important from the economic and industrial perspectives but as well as patients’ access to treatment. This study aimed to analyze the variables affecting the prices of new drugs in South Korea’s pricing system.Methods: Data on 192 new drugs listed in South Korea from 2012 to 2022 were collected from the official website of the Health Insurance Review and Assessment Service. The independent variables included drugs for severe diseases, alternatives, number of patients, number of advanced 7 countries listed, budget impact, and listing period. The dependent variables included annual treatment cost and the price ratio to the advanced 7 country’s average adjusted price. Descriptive statistics of variables, linear correlations between quantitative independent and dependent variables, and associations between independent and dependent variables were analyzed.Results: The mean annual treatment cost and price ratio to the advanced 7 country’s average adjusted price were higher for drugs for severe diseases and those with no alternatives. Annual treatment cost and price ratio to the advanced 7 country’s average adjusted price were negatively correlated with the number of patients and positively correlated with the number of advanced 7 countries listed. Annual treatment cost was affected by the variables drugs for severe diseases, alternatives, number of patients, number of advanced 7 countries listed, and budget impact. The price ratio to the advanced 7 country’s average adjusted price was affected by drugs for severe diseases, alternatives, and the number of patients.Conclusion: This study revealed the effect of different variables on the prices of new drugs in South Korea, allowing for the development of a more effective assessment system to evaluate the prices of new drugs while ensuring profitability for pharmaceutical companies, sustainability of public insurance, and accessibility to drugs by patients.

Abstract This work reports the fabrication of a large‐sized hydrogel sheet with enhanced mechanical and adhesive properties. The fabrication involves the introduction of carboxymethyl‐modified cellulose nanofibers (m‐CNFs) and solid silica nanoparticles (SSNs) as physical cross‐linkers into acrylic acid monomer (AA), followed by bar coating and photopolymerization. The addition of the nanomaterials to the monomer solution renders it viscous, enabling the fabrication of A4‐sized hydrogel sheets with uniform thickness and enhanced mechanical and adhesive properties. Interestingly, the combined incorporation of both the nanomaterials generates a synergistic effect to improve the properties much more, which results from the hierarchical rupture of the multiple hydrogen‐bonded interactions among the poly(acrylic acid) (PAA) matrix, m‐CNFs, and SSNs. Under optimal conditions, the hydrogel sheet incorporated with the dual crosslinkers exhibits a sevenfold higher toughness and a sixfold increased peel strength than plain PAA, together with good biocompatibility. Furthermore, when mesoporous silica nanoparticles (MSNs) with active agent loading into their pores are incorporated instead of SSNs, the active agent can be released from the hydrogel sheet in a sustained or temperature‐sensitive manner, indicating that the system is potentially applicable to transdermal drug delivery system with no additional adhesive.

Abstract Background Glioblastoma is a highly malignant brain tumor associated with poor prognosis. Conventional therapeutic approaches have limitations due to their toxic effects on normal tissue and the development of tumor cell resistance. This study aimed to explore alternative mechanisms for glioblastoma treatment by targeting angiogenesis. Methods The study investigated the anti-angiogenic properties of heparin in glioblastoma treatment. To overcome the limitations of heparin, a heparin-taurocholate conjugate (LHT7) was synthesized by conjugating heparin to taurocholic acid. The study utilized the U87MG human glioblastoma cell line and human umbilical vein endothelial cells (HUVEC) as experimental models. Cell viability assays and sprouting assays were performed to assess the effects of LHT7. Additionally, phosphorylation of angiogenesis-related proteins, such as phospho-ERK and phospho-VEGFR2, was measured. The anti-angiogenic effects of LHT7 were further evaluated using a glioblastoma orthotopic mouse model. Results Treatment with LHT7 resulted in a dose-dependent reduction in cell viability in U87MG human glioblastoma cells. The sprouting of HUVEC cells was significantly decreased upon LHT7 treatment. Furthermore, LHT7 treatment led to a decrease in the phosphorylation of angiogenesis-related proteins, including phospho-ERK and phospho-VEGFR2. In the glioblastoma orthotopic mouse model, LHT7 exhibited anti-angiogenic effects, supporting its potential as a therapeutic agent. Conclusions The conjugation of heparin and taurocholic acid to create LHT7 offers several advantages over conventional therapeutic approaches for glioblastoma. LHT7 demonstrated anti-angiogenic properties, as evidenced by the reduction in cell viability and inhibition of endothelial cell sprouting. Moreover, LHT7 modulated the phosphorylation of angiogenesis-related proteins. These findings suggest that LHT7 holds promise as a medication for glioblastoma treatment, offering potential implications for improving patient outcomes. Graphical Abstract

Abstract Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder of childhood. Although it requires timely detection and intervention, existing continuous performance tests (CPTs) have limited efficacy. Research suggests that eye movement could offer important diagnostic information for ADHD. This study aimed to compare the performance of eye-tracking with that of CPTs, both alone and in combination, and to evaluate the effect of medication on eye movement and CPT outcomes. We recruited participants into an ADHD group and a healthy control group between July 2021 and March 2022 from among children aged 6–10 years (n = 30 per group). The integration of eye-tracking with CPTs produced higher values for the area under the receiver operating characteristic (AUC, 0.889) compared with using CPTs only (AUC, 0.769) for identifying patients with ADHD. The use of eye-tracking alone showed higher performance compare with the use of CPTs alone (AUC of EYE: 0.856, AUC of CPT: 0.769, p = 0.029). Follow-up analysis revealed that most eye-tracking and CPT indicators improved significantly after taking an ADHD medication. The use of eye movement scales could be used to differentiate children with ADHD, with the possibility that integrating eye movement scales and CPTs could improve diagnostic precision.

Abstract To resolve the problem of target specificity and light transmission to deep-seated tissues in photodynamic therapy (PDT), we report a cancer cell-targeted photosensitizer using photoprotein-conjugated upconversion nanoparticles (UCNPs) with high target specificity and efficient light transmission to deep tissues. Core-shell UCNPs with low internal energy back transfer were conjugated with recombinant proteins that consists of a photosensitizer (KillerRed; KR) and a cancer cell-targeted lead peptide (LP). Under near infrared (NIR)-irradiating condition, the UCNP-KR-LP generated superoxide anion radicals as reactive oxygen species via NIR-to-green light conversion and exhibited excellent specificity to target cancer cells through receptor-mediated cell adhesion. Consequently, this photosensitizing process facilitated rapid cell death in cancer cell lines (MCF-7, MDA-MB-231, and U-87MG) overexpressing integrin beta 1 (ITGB1) receptors but not in a cell line (SK-BR-3) with reduced ITGB1 expression and a non-invasive normal breast cell line (MCF-10A). In contrast to green light irradiation, NIR light irradiation exhibited significant PDT efficacy in cancer cells located beneath porcine skin tissues up to a depth of 10 mm, as well as in vivo tumor xenograft mouse models. This finding suggests that the designed nanocomposite is useful for sensing and targeting various deep-seated tumors.

Abstract Aims Population-wide restrictions during the COVID-19 pandemic may create barriers to mental health diagnosis. This study aims to examine changes in the number of incident cases and the incidence rates of mental health diagnoses during the COVID-19 pandemic. Methods By using electronic health records from France, Germany, Italy, South Korea and the UK and claims data from the US, this study conducted interrupted time-series analyses to compare the monthly incident cases and the incidence of depressive disorders, anxiety disorders, alcohol misuse or dependence, substance misuse or dependence, bipolar disorders, personality disorders and psychoses diagnoses before (January 2017 to February 2020) and after (April 2020 to the latest available date of each database [up to November 2021]) the introduction of COVID-related restrictions. Results A total of 629,712,954 individuals were enrolled across nine databases. Following the introduction of restrictions, an immediate decline was observed in the number of incident cases of all mental health diagnoses in the US (rate ratios (RRs) ranged from 0.005 to 0.677) and in the incidence of all conditions in France, Germany, Italy and the US (RRs ranged from 0.002 to 0.422). In the UK, significant reductions were only observed in common mental illnesses. The number of incident cases and the incidence began to return to or exceed pre-pandemic levels in most countries from mid-2020 through 2021. Conclusions Healthcare providers should be prepared to deliver service adaptations to mitigate burdens directly or indirectly caused by delays in the diagnosis and treatment of mental health conditions.

Abstract Background High-mobility group box-1 (HMGB1) released from the tumor microenvironment plays a pivotal role in the tumor progression. HMGB1 serves as a damaged-associated molecular pattern (DAMP) that induces tumor angiogenesis and its development. Glycyrrhizin (GL) is an effective intracellular antagonist of tumor released HMGB1, but its pharmacokinetics (PK) and delivery to tumor site is deficient. To address this shortcoming, we developed lactoferrin-glycyrrhizin (Lf-GL) conjugate. Methods Biomolecular interaction between Lf-GL and HMGB1 was evaluated by surface plasmon resonance (SPR) binding affinity assay. Inhibition of tumor angiogenesis and development by Lf-GL attenuating HMGB1 action in the tumor microenvironment was comprehensively evaluated through in vitro, ex vivo, and in vivo. Pharmacokinetic study and anti-tumor effects of Lf-GL were investigated in orthotopic glioblastoma mice model. Results Lf-GL interacts with lactoferrin receptor (LfR) expressed on BBB and GBM, therefore, efficiently inhibits HMGB1 in both the cytoplasmic and extracellular regions of tumors. Regarding the tumor microenvironment, Lf-GL inhibits angiogenesis and tumor growth by blocking HMGB1 released from necrotic tumors and preventing recruitment of vascular endothelial cells. In addition, Lf-GL improved the PK properties of GL approximately tenfold in the GBM mouse model and reduced tumor growth by 32%. Concurrently, various biomarkers for tumor were radically diminished. Conclusion Collectively, our study demonstrates a close association between HMGB1 and tumor progression, suggesting Lf-GL as a potential strategy for coping with DAMP-related tumor microenvironment. Graphical Abstract HMGB1 is a tumor-promoting DAMP in the tumor microenvironment. The high binding capability of Lf-GL to HMGB1 inhibits tumor progression cascade such as tumor angiogenesis, development, and metastasis. Lf-GL targets GBM through interaction with LfR and allows to arrest HMGB1 released from the tumor microenvironment. Therefore, Lf-GL can be a GBM treatment by modulating HMGB1 activity.

Abstract Owing to the strong absorption of water in the near-infrared (NIR) region near 1.0 μm, this wavelength is considered unsuitable as an imaging and analytical signal in biological environments. However, 1.0 μm NIR can be converted into heat and used as a local water-molecular heating strategy for the photothermal therapy of biological tissues. Herein, we describe a Nd-Yb co-doped nanomaterial (water-heating nanoparticles (NPs)) as strong 1.0 μm emissive NPs to target the absorption band of water. Furthermore, introducing Tm ions into the water-heating NPs improve the NIR lifetime, enabling the development of a NIR imaging-guided water-heating probe (water-heating NIR NPs). In the glioblastoma multiforme male mouse model, tumor-targeted water-heating NIR NPs reduce the tumor volume by 78.9% in the presence of high-resolution intracranial NIR long-lifetime imaging. Hence, water-heating NIR NPs can be used as a promising nanomaterial for imaging and photothermal ablation in deep-tissue-bearing tumor therapy.

Abstract Background Postoperative delirium is a common complication that is distressing. This study aimed to demonstrate a prediction model for delirium. Methods Among 203,374undergoing non-cardiac surgery between January 2011 and June 2019 at Samsung Medical Center, 2,865 (1.4%) were diagnosed with postoperative delirium. After comparing performances of machine learning algorithms, we chose variables for a prediction model based on an extreme gradient boosting algorithm. Using the top five variables, we generated a prediction model for delirium and conducted an external validation. The Kaplan–Meier and Cox survival analyses were used to analyse the difference of delirium occurrence in patients classified as a prediction model. Results The top five variables selected for the postoperative delirium prediction model were age, operation duration, physical status classification, male sex, and surgical risk. An optimal probability threshold in this model was estimated to be 0.02. The area under the receiver operating characteristic (AUROC) curve was 0.870 with a 95% confidence interval of 0.855–0.885, and the sensitivity and specificity of the model were 0.76 and 0.84, respectively. In an external validation, the AUROC was 0.867 (0.845–0.877). In the survival analysis, delirium occurred more frequently in the group of patients predicted as delirium using an internal validation dataset (p

IntroductionDeep sternal wound infection (DSWI) is a serious complication that may occur after median sternotomy, with potentially devastating consequences. By reporting our case and analyzing the existing literature, this article aimed to provide a thorough understanding of the role of negative-pressure wound therapy (NPWT) and the importance of flap choice in managing DSWI accompanied by severe heart injury and high hemodynamic risk.Case descriptionA 60-year-old woman with severe aortic stenosis, aortic valve regurgitation, and heart failure underwent redo sternotomy, which resulted in an intraoperative right ventricle injury. She required extracorporeal membrane oxygenation support because of low blood pressure and subsequently developed complications, including surgical site hematoma, wound dehiscence, and fat necrosis. She was referred for wound closure, where a significant 10 × 20-cm soft tissue defect in the anterior chest wall was observed. A pedicled vertical rectus abdominis myocutaneous flap addressed the soft tissue defect. The wound showed remarkable improvement at the 8-month follow-up visit.ConclusionsDSWI management is a complex and multifaceted challenge. NPWT, when combined with appropriate surgical strategies, including wound debridement and flap selection, may promote successful wound healing. This case report highlights the successful management of a complex DSWI using a multidisciplinary approach, including debridement, appropriate antibiotic therapy, and free-flap reconstruction, which resulted in favorable outcomes.

Abstract Background Methylphenidate (MPH) is the most frequently prescribed medication for the treatment of attention deficit hyperactivity disorder (ADHD). However, the safety of its long-term use remain unclear. In particular, real-world evidence of long-term MPH treatment regarding the risk of depression, conduct disorders, and psychotic disorders in children and adolescents is needed. This study aimed to compare the risks of depression, conduct disorder, and psychotic disorder between long- and short-term MPH treatments in children and adolescents. Methods This population-based cohort study used a nationwide claims database of all patients with ADHD in South Korea. Patients aged less than 18 years who were prescribed MPH were included in the study. Long- and short-term MPH were defined as > 1 year, and

BackgroundMood disorder has emerged as a serious concern for public health; in particular, bipolar disorder has a less favorable prognosis than depression. Although prompt recognition of depression conversion to bipolar disorder is needed, early prediction is challenging due to overlapping symptoms. Recently, there have been attempts to develop a prediction model by using federated learning. Federated learning in medical fields is a method for training multi-institutional machine learning models without patient-level data sharing. ObjectiveThis study aims to develop and validate a federated, differentially private multi-institutional bipolar transition prediction model. MethodsThis retrospective study enrolled patients diagnosed with the first depressive episode at 5 tertiary hospitals in South Korea. We developed models for predicting bipolar transition by using data from 17,631 patients in 4 institutions. Further, we used data from 4541 patients for external validation from 1 institution. We created standardized pipelines to extract large-scale clinical features from the 4 institutions without any code modification. Moreover, we performed feature selection in a federated environment for computational efficiency and applied differential privacy to gradient updates. Finally, we compared the federated and the 4 local models developed with each hospital's data on internal and external validation data sets. ResultsIn the internal data set, 279 out of 17,631 patients showed bipolar disorder transition. In the external data set, 39 out of 4541 patients showed bipolar disorder transition. The average performance of the federated model in the internal test (area under the curve [AUC] 0.726) and external validation (AUC 0.719) data sets was higher than that of the other locally developed models (AUC 0.642-0.707 and AUC 0.642-0.699, respectively). In the federated model, classifications were driven by several predictors such as the Charlson index (low scores were associated with bipolar transition, which may be due to younger age), severe depression, anxiolytics, young age, and visiting months (the bipolar transition was associated with seasonality, especially during the spring and summer months). ConclusionsWe developed and validated a differentially private federated model by using distributed multi-institutional psychiatric data with standardized pipelines in a real-world environment. The federated model performed better than models using local data only.

Two-dimensional (2D) vertical van der Waals heterostructures (vdWHs) show great potential across various applications. However, synthesizing large-scale structures poses challenges owing to the intricate growth parameters, forming unexpected hybrid film structures. Thus, precision in synthesis and thorough structural analysis are essential aspects. In this study, we successfully synthesized large-scale structured 2D transition metal dichalcogenides (TMDs) via chemical vapor deposition using metal oxide (WO3 and MoO3) thin films and a diluted H2S precursor, individual MoS2, WS2 films and various MoS2/WS2 hybrid films (Type I: MoxW1−xS2 alloy; Type II: MoS2/WS2 vdWH; Type III: MoS2 dots/WS2). Structural analyses, including optical microscopy, Raman spectroscopy, transmission electron microscopy (TEM) with energy-dispersive X-ray spectroscopy, and cross-sectional imaging revealed that the A1g and E2g modes of WS2 and MoS2 were sensitive to structural variations, enabling hybrid structure differentiation. Type II showed minimal changes in the MoS2′s A1g mode, while Types I and III exhibited a ~2.8 cm−1 blue shift. Furthermore, the A1g mode of WS2 in Type I displayed a 1.4 cm−1 red shift. These variations agreed with the TEM-observed microstructural features, demonstrating strain effects on the MoS2–WS2 interfaces. Our study provides insights into the structural features of diverse hybrid TMD materials, facilitating their differentiation through Raman spectroscopy.

This study encoded the complete mitochondrial genomic sequence of the little ringed plover Charadrius dubius. The mitochondrial genome has a total length of 16,864 bp, consisting of 13 protein-coding genes, 22 tRNA genes, two rRNA genes, and a control region. The nucleotide composition was 23.8% T, 31.6% A, 30.8% C, and 13.8% G. This study provides the basic information on the mitogenome of C. dubius and supports the understanding of mitogenomic information and its phylogenetic relationship within Charadriiformes.

Abstract Anti-dementia medications are widely prescribed to patients with Alzheimer’s dementia (AD) in South Korea. This study investigated the pattern of medical management in newly diagnosed patients with AD using a standardized data format—the Observational Medical Outcome Partnership Common Data Model from five hospitals. We examined the anti-dementia treatment patterns from datasets that comprise > 5 million patients during 2009–2019. The medication utility information was analyzed with respect to treatment trends and persistence across 11 years. Among the 8653 patients with newly diagnosed AD, donepezil was the most commonly prescribed anti-dementia medication (4218; 48.75%), followed by memantine (1565; 18.09%), rivastigmine (1777; 8.98%), and galantamine (494; 5.71%). The rising prescription trend during observation period was found only with donepezil. The treatment pathways for the three cholinesterase inhibitors combined with N-methyl-d-aspartate receptor antagonist were different according to the drugs (19.6%; donepezil; 28.1%; rivastigmine, and 17.2%; galantamine). A 12-month persistence analysis showed values of approximately 50% for donepezil and memantine and approximately 40% for rivastigmine and galantamine. There were differences in the prescribing pattern and persistence among anti-dementia medications from database using the Observational Medical Outcome Partnership Common Data Model on the Federated E-health Big Data for Evidence Renovation Network platform in Korea.

Orally absorbable gold nanoparticles (AuNP) having cancer ablation therapy is strongly demanded to treat glioblastoma multiforme (GBM) for patients with its highest incidence rate. Here, we develop a milk protein lactoferrin-conjugated AuNP for its oral absorption and targeting to the GBM through the interaction between lactoferrin (Lf) and lactoferrin receptor (LfR) that is highly expressed in the intestine, blood-brain barrier and GBM. For stability and long circulation of AuNP, glutathione and polyethylene glycol (PEG) is introduced, which is called to Lf-PEG-AuNP. When Lf-PEG-AuNP are orally administered to orthotopic GBM-bearing mice, 11-fold and 8-fold higher concentrations of AuNP are measured in bloodstreams and GBM in the brain, respectively, compared with unconjugated-AuNP. Therefore, orally administered Lf-PEG-AuNP exhibit an outstanding temperature rise in GBM by irradiating laser and significantly reduce tumor volume. Collectively, we suggest that the Lf-PEG-AuNP can fundamentally target GBM in the brain through oral absorption, and that its efficient photothermal therapy is possible.

Abstract Background The outcome of phototherapy, including photothermal therapy (PTT) and photodynamic therapy (PDT) for glioblastoma multiforme (GBM), is disappointing due to insufficient photoconversion efficiency and low targeting rate. The development of phototherapeutic agents that target GBM and generate high heat and potent ROS is important to overcome the weak anti-tumor effect. Results In this study, nanoconjugates composed of gold nanoparticles (AuNPs) and photosensitizers (PSs) were prepared by disulfide conjugation between Chlorin e6 (Ce6) and glutathione coated-AuNP. The maximum heat dissipation of the nanoconjugate was 64.5 ± 4.5 °C. Moreover, the proximate conjugation of Ce6 on the AuNP surface resulted in plasmonic crossover between Ce6 and AuNP. This improves the intrinsic ROS generating capability of Ce6 by 1.6-fold compared to that of unmodified-Ce6. This process is called generation of metal-enhanced reactive oxygen species (MERos). PEGylated-lactoferrin (Lf-PEG) was incorporated onto the AuNP surface for both oral absorption and GBM targeting of the nanoconjugate (denoted as Ce6-AuNP-Lf). In this study, we explored the mechanism by which Ce6-AuNP-Lf interacts with LfR at the intestinal and blood brain barrier (BBB) and penetrates these barriers with high efficiency. In the orthotopic GBM mice model, the oral bioavailability and GBM targeting amount of Ce6-AuNP-Lf significantly improved to 7.3 ± 1.2% and 11.8 ± 2.1 μg/kg, respectively. The order of laser irradiation, such as applying PDT first and then PTT, was significant for the treatment outcome due to the plasmonic advantages provided by AuNPs to enhance ROS generation capability. As a result, GBM-phototherapy after oral administration of Ce6-AuNP-Lf exhibited an outstanding anti-tumor effect due to GBM targeting and enhanced photoconversion efficiency. Conclusions The designed nanoconjugates greatly improved ROS generation by plasmonic crossover between AuNPs and Ce6, enabling sufficient PDT for GBM as well as PTT. In addition, efficient GBM targeting through oral administration was possible by conjugating Lf to the nanoconjugate. These results suggest that Ce6-AuNP-Lf is a potent GBM phototherapeutic nanoconjugate that can be orally administered. Graphical Abstract

Abstract Background The menopause transition is a vulnerable period that can be associated with changes in mood and cognition. The present study aimed to investigate whether a symptomatic menopausal transition increases the risks of depression, anxiety, and sleep disorders. Methods This population-based, retrospective cohort study analysed data from five electronic health record databases in South Korea. Women aged 45–64 years with and without symptomatic menopausal transition were matched 1:1 using propensity-score matching. Subgroup analyses were conducted according to age and use of hormone replacement therapy (HRT). A primary analysis of 5-year follow-up data was conducted, and an intention-to-treat analysis was performed to identify different risk windows over 5 or 10 years. The primary outcome was first-time diagnosis of depression, anxiety, and sleep disorder. We used Cox proportional hazard models and a meta-analysis to calculate the summary hazard ratio (HR) estimates across the databases. Results Propensity-score matching resulted in a sample of 17,098 women. Summary HRs for depression (2.10; 95% confidence interval [CI] 1.63–2.71), anxiety (1.64; 95% CI 1.01–2.66), and sleep disorders (1.47; 95% CI 1.16–1.88) were higher in the symptomatic menopausal transition group. In the subgroup analysis, the use of HRT was associated with an increased risk of depression (2.21; 95% CI 1.07–4.55) and sleep disorders (2.51; 95% CI 1.25–5.04) when compared with non-use of HRT. Conclusions Our findings suggest that women with symptomatic menopausal transition exhibit an increased risk of developing depression, anxiety, and sleep disorders. Therefore, women experiencing a symptomatic menopausal transition should be monitored closely so that interventions can be applied early.

Abstract Background Predicting the course of depression is necessary for personalized treatment. Impaired glucose metabolism (IGM) was introduced as a promising depression biomarker, but no consensus was made. This study aimed to predict IGM at the time of depression diagnosis and examine the relationship between long-term prognosis and predicted results. Methods Clinical data were extracted from four electronic health records in South Korea. The study population included patients with depression, and the outcome was IGM within 1 year. One database was used to develop the model using three algorithms. External validation was performed using the best algorithm across the three databases. The area under the curve (AUC) was calculated to determine the model’s performance. Kaplan–Meier and Cox survival analyses of the risk of hospitalization for depression as the long-term outcome were performed. A meta-analysis of the long-term outcome was performed across the four databases. Results A prediction model was developed using the data of 3,668 people, with an AUC of 0.781 with least absolute shrinkage and selection operator (LASSO) logistic regression. In the external validation, the AUCs were 0.643, 0.610, and 0.515. Through the predicted results, survival analysis and meta-analysis were performed; the hazard ratios of risk of hospitalization for depression in patients predicted to have IGM was 1.20 (95% confidence interval [CI] 1.02–1.41, p = 0.027) at a 3-year follow-up. Conclusions We developed prediction models for IGM occurrence within a year. The predicted results were related to the long-term prognosis of depression, presenting as a promising IGM biomarker related to the prognosis of depression.

Abstract Many patients with bipolar disorder (BD) are initially misdiagnosed with major depressive disorder (MDD) and are treated with antidepressants, whose potential iatrogenic effects are widely discussed. It is unknown whether MDD is a comorbidity of BD or its earlier stage, and no consensus exists on individual conversion predictors, delaying BD’s timely recognition and treatment. We aimed to build a predictive model of MDD to BD conversion and to validate it across a multi-national network of patient databases using the standardization afforded by the Observational Medical Outcomes Partnership (OMOP) common data model. Five “training” US databases were retrospectively analyzed: IBM MarketScan CCAE, MDCR, MDCD, Optum EHR, and Optum Claims. Cyclops regularized logistic regression models were developed on one-year MDD-BD conversion with all standard covariates from the HADES PatientLevelPrediction package. Time-to-conversion Kaplan-Meier analysis was performed up to a decade after MDD, stratified by model-estimated risk. External validation of the final prediction model was performed across 9 patient record databases within the Observational Health Data Sciences and Informatics (OHDSI) network internationally. The model’s area under the curve (AUC) varied 0.633–0.745 (µ = 0.689) across the five US training databases. Nine variables predicted one-year MDD-BD transition. Factors that increased risk were: younger age, severe depression, psychosis, anxiety, substance misuse, self-harm thoughts/actions, and prior mental disorder. AUCs of the validation datasets ranged 0.570–0.785 (µ = 0.664). An assessment algorithm was built for MDD to BD conversion that allows distinguishing as much as 100-fold risk differences among patients and validates well across multiple international data sources.

Abstract Background Superparamagnetic iron oxide (SPIO) nanoparticles have been widely used in several biomedical engineering in vivo. Although various surface modifications have been made to these non-biodegradable nanoparticles to make them more biocompatible, their toxic potential still remains a major concern. Method In this study, we newly developed unfractionated heparin (UFH)-coated and low molecular weight heparin (LMWH)-coated SPIO nanoparticles through surface modification engineering, which was compared with commercially available dextran-coated SPIO nanoparticles. Their toxicity such as cytotoxicity, single cell gel electrophoresis (SCGE) comet assay, intracellular reactive oxygen species (ROS) content and cellular apoptosis was evaluated to hepatic HepG2 and renal HK-2 cells. Results When UFH-, LMWH- or dextran-coated SPIO nanoparticles were applied, they did not affect the viability of HepG2 cell. However, HK-2 cells were more sensitive to dextran-coated SPIO nanoparticles than others. In genotoxicity assay using SCGE comet, DNA tail moment values in the groups treated with dextran- and LMWH-coated SPIO nanoparticles significantly increased. However, UFH-coated SPIO nanoparticles was only significantly lowing DNA tail moment value. In addition, UFH-coated SPIO nanoparticles had lower cytotoxicity in HepG2 and HK-2 cells compared to dextran-coated SPIO nanoparticles, especially in terms of apoptosis and intracellular ROS production. Conclusions Collectively, it is possible that UFH- coated SPIO nanoparticles can be used as alternative negative contrast agents.

Tip-enhanced nano-spectroscopy suffers from inconsistent signal and difficulty in polarization-resolved measurement. Here, the authors present adaptive tip-enhanced nano-spectroscopy, which enables the additional signal enhancement and near-field polarization control via dynamic wavefront shaping.

Abstract Tumor-induced osteomalacia (TIO) is an uncommon paraneoplastic syndrome presenting with sustained hypophosphatemia. Treatment of choice is removal of the tumor causing the TIO, but identification of the culprit tumor by routine imaging is challenging. This study aimed to assess the usefulness of somatostatin receptor imaging, called 68Ga-DOTATOC PET/CT, in the management of patients with TIO. Twelve patients who were suspected of having TIO underwent 68Ga-DOTATOC PET/CT. Lesion detectability and maximum standardized uptake value (SUVmax) were determined and retrospectively compared with the clinical/imaging surveillance and histopathologic diagnosis. The median duration of suspected TIO with hypophosphatemia was 7.8 years (range 2.1–21.0). Conventional radiologic and/or nuclear medicine images failed to identify the culprit tumors. However, 68Ga-DOTATOC PET/CT scans showed that 8 of the 12 patients had positive lesions, suggesting the presence of focal culprit tumors. The SUVmax of positive tumors was 1.9–45.7 (median: 11.5). Six skeletal lesions and two extra-skeletal lesions were identified. Seven of the lesions were pathologically confirmed as potential culprits of TIO. Hypophosphatemia was resolved in five patients who underwent lesion excision. The 68Ga-DOTATOC PET/CT is a useful whole-body imaging modality for the detection of causative tumors in patients with suspected TIO.

BackgroundIdentifying patients at a high risk of psychosis relapse is crucial for early interventions. A relevant psychiatric clinical context is often recorded in clinical notes; however, the utilization of unstructured data remains limited. This study aimed to develop psychosis-relapse prediction models using various types of clinical notes and structured data.MethodsClinical data were extracted from the electronic health records of the Ajou University Medical Center in South Korea. The study population included patients with psychotic disorders, and outcome was psychosis relapse within 1 year. Using only structured data, we developed an initial prediction model, then three natural language processing (NLP)-enriched models using three types of clinical notes (psychological tests, admission notes, and initial nursing assessment) and one complete model. Latent Dirichlet Allocation was used to cluster the clinical context into similar topics. All models applied the least absolute shrinkage and selection operator logistic regression algorithm. We also performed an external validation using another hospital database.ResultsA total of 330 patients were included, and 62 (18.8%) experienced psychosis relapse. Six predictors were used in the initial model and 10 additional topics from Latent Dirichlet Allocation processing were added in the enriched models. The model derived from all notes showed the highest value of the area under the receiver operating characteristic (AUROC = 0.946) in the internal validation, followed by models based on the psychological test notes, admission notes, initial nursing assessments, and structured data only (0.902, 0.855, 0.798, and 0.784, respectively). The external validation was performed using only the initial nursing assessment note, and the AUROC was 0.616.ConclusionsWe developed prediction models for psychosis relapse using the NLP-enrichment method. Models using clinical notes were more effective than models using only structured data, suggesting the importance of unstructured data in psychosis prediction.

Abstract Background In a pilot study, we found that feces transplantation from elderly individuals to mice significantly caused cognitive impairment. Paenalcaligenes hominis and Escherichia coli are increasingly detected in the feces of elderly adults and aged mice. Therefore, we isolated Paenalcaligenes hominis and Escherichia coli from the feces of elderly individuals and aged mice and examined their effects on the occurrence of age-related degenerative cognitive impairment and colonic inflammation in mice. Results The transplantation of feces collected from elderly people and aged mice caused significantly more severe cognitive impairment in transplanted young mice than those from young adults and mice. Oral gavage of Paenalcaligenes hominis caused strong cognitive impairment and colitis in specific pathogen-free (SPF) and germ-free mice. Escherichia coli also induced cognitive impairment and colitis in SPF mice. Oral gavage of Paenalcaligenes hominis, its extracellular vesicles (EVs), and/or lipopolysaccharide caused cognitive impairment and colitis in mice. However, celiac vagotomy significantly inhibited the occurrence of cognitive impairment, but not colitis, in mice exposed to Paenalcaligenes hominis or its EVs, whereas its lipopolysaccharide or Escherichia coli had no such effects. Vagotomy also inhibited the infiltration of EVs into the hippocampus. Conclusions Paenalcaligenes hominis, particularly its EVs, can cause cognitive function-impaired disorders, such as Alzheimer’s disease, and its EVs may penetrate the brain through the blood as well as the vagus nerve. Video Abstract

Abstract Background To compare the diagnostic sensitivity of [18F]fluoroestradiol ([18F]FES) and [18F]fluorodeoxyglucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) for breast cancer recurrence in patients with estrogen receptor (ER)-positive primary breast cancer. Methods Our database of consecutive patients enrolled in a previous prospective cohort study to assess [18F]FES PET/CT was reviewed to identify eligible patients who had ER-positive primary breast cancer with suspected first recurrence at presentation and who underwent [18F]FDG PET/CT. The sensitivity of qualitative [18F]FES and [18F]FDG PET/CT interpretations was assessed, comparing them with histological diagnoses. Results Of the 46 enrolled patients, 45 were confirmed as having recurrent breast cancer, while one was diagnosed with chronic granulomatous inflammation. Forty (89%) patients were ER-positive, four (9%) were ER-negative, and one (2%) patient did not undergo an ER assay. The sensitivity of [18F]FES PET/CT was 71.1% (32/45, 95% CI, 55.7–83.6), while that of [18F]FDG PET/CT was 80.0% (36/45, 95% CI, 65.4–90.4) with a threshold of positive interpretation, and 93.3% (42/45, 95% CI, 81.7–98.6) when a threshold of equivocal was used. There was no significant difference in sensitivity between [18F]FES and [18F]FDG PET/CT (P = 0.48) with a threshold of positive [18F]FDG uptake, but the sensitivity of [18F]FDG was significantly higher than [18F]FES (P = 0.013) with a threshold of equivocal [18F]FDG uptake. One patient with a benign lesion showed negative [18F]FES but positive [18F]FDG uptake. Conclusions The restaging of patients who had ER-positive primary breast cancer and present with recurrent disease may include [18F]FES PET/CT as an initial test when standard imaging studies are equivocal or suspicious.

Cancer is the leading cause of death after cardiovascular disease. Despite significant advances in cancer research over the past few decades, it is almost impossible to cure end-stage cancer patients and bring them to remission. Adverse effects of chemotherapy are mainly caused by the accumulation of chemotherapeutic agents in normal tissues, and drug resistance hinders the potential therapeutic effects and curing of this disease. New drug formulations need to be developed to overcome these problems and increase the therapeutic index of chemotherapeutics. As a chemotherapeutic delivery platform, three-dimensional (3D) scaffolds are an up-and-coming option because they can respond to biological factors, modify their properties accordingly, and promote site-specific chemotherapeutic deliveries in a sustainable and controlled release manner. This review paper focuses on the features and applications of the variety of 3D scaffold-based nano-delivery systems that could be used to improve local cancer therapy by selectively delivering chemotherapeutics to the target sites in future.

BackgroundSuicide has emerged as a serious concern for public health; however, only few studies have revealed the differences between major psychiatric disorders and suicide. Recent studies have attempted to quantify research domain criteria (RDoC) into numeric scores to systematically use them in computerized methods. The RDoC scores were used to reveal the characteristics of suicide and its association with major psychiatric disorders. ObjectiveWe intended to investigate the differences in the dimensional psychopathology among hospitalized suicidal patients and the association between the dimensional psychopathology of psychiatric disorders and length of hospital stay. MethodsThis retrospective study enrolled hospitalized suicidal patients diagnosed with major psychiatric disorders (depression, schizophrenia, and bipolar disorder) between January 2010 and December 2020 at a tertiary hospital in South Korea. The RDoC scores were calculated using the patients’ admission notes. To measure the differences between psychiatric disorder cohorts, analysis of variance and the Cochran Q test were conducted and post hoc analysis for RDoC domains was performed with the independent two-sample t test. A linear regression model was used to analyze the association between the RDoC scores and sociodemographic features and comorbidity index. To estimate the association between the RDoC scores and length of hospital stay, multiple logistic regression models were applied to each psychiatric disorder group. ResultsWe retrieved 732 admissions for 571 patients (465 with depression, 73 with schizophrenia, and 33 with bipolar disorder). We found significant differences in the dimensional psychopathology according to the psychiatric disorders. The patient group with depression showed the highest negative RDoC domain scores. In the cognitive and social RDoC domains, the groups with schizophrenia and bipolar disorder scored higher than the group with depression. In the arousal RDoC domain, the depression and bipolar disorder groups scored higher than the group with schizophrenia. We identified significant associations between the RDoC scores and length of stay for the depression and bipolar disorder groups. The odds ratios (ORs) of the length of stay were increased because of the higher negative RDoC domain scores in the group with depression (OR 1.058, 95% CI 1.006-1.114) and decreased by higher arousal RDoC domain scores in the group with bipolar disorder (OR 0.537, 95% CI 0.285-0.815). ConclusionsThis study showed the association between the dimensional psychopathology of major psychiatric disorders related to suicide and the length of hospital stay and identified differences in the dimensional psychopathology of major psychiatric disorders. This may provide new perspectives for understanding suicidal patients.

Over the past decades, graphene has attracted much attention from the scientific community due to its broad applications in the optoelectronics industries [1]. Owing to graphene's high transmission and high electrical conductivity, diverse functional materials/graphene hybridized heterostructures and interfaces are under extensive investigation to satisfy the increasing interest in the need for bendable, flexible and high performance optoelectronic devices [2]. Due to the good atomic lattice structure of graphene, varying heterostructures have been formed by depositing different functional materials directly on graphene [3–5].We fabricated a vertical photovoltaic type G/PbS/Ti device by making use of the Ti/PbS Schottky junction and discussed the photocurrent transient characteristics. Lead sulfide (PbS) was deposited directly on large area CVD (Chemical vapor deposition) graphene by CBD (Chemical bath deposition). Temperature dependent photocurrent spectra of our G/PbS/Ti photovoltaic devices were measured by a Fourier transformed infrared (FTIR) set-up.In this paper, we present the experimental procedures and the raw experimental data for the direct chemical deposition of PbS on CVD-graphene for high performance photovoltaic infrared photo-detectors. The manuscript is already available [6].

The current treatment for malignant brain tumors includes surgical resection, radiotherapy, and chemotherapy. Nevertheless, the survival rate for patients with glioblastoma multiforme (GBM) with a high grade of malignancy is less than one year. From a clinical point of view, effective treatment of GBM is limited by several challenges. First, the anatomical complexity of the brain influences the extent of resection because a fine balance must be struck between maximal removal of malignant tissue and minimal surgical risk. Second, the central nervous system has a distinct microenvironment that is protected by the blood–brain barrier, restricting systemically delivered drugs from accessing the brain. Additionally, GBM is characterized by high intra-tumor and inter-tumor heterogeneity at cellular and histological levels. This peculiarity of GBM-constituent tissues induces different responses to therapeutic agents, leading to failure of targeted therapies. Unlike surgical resection and radiotherapy, photodynamic therapy (PDT) can treat micro-invasive areas while protecting sensitive brain regions. PDT involves photoactivation of photosensitizers (PSs) that are selectively incorporated into tumor cells. Photo-irradiation activates the PS by transfer of energy, resulting in production of reactive oxygen species to induce cell death. Clinical outcomes of PDT-treated GBM can be advanced in terms of nanomedicine. This review discusses clinical PDT applications of nanomedicine for the treatment of GBM.

Spin ice materials are defined by ice rules, local constraints that lead to frustrated interactions and macroscopic numbers of degenerate configurations. Here the authors show that the ice rule in colloidal ice is emergent, limited to certain geometries, and demonstrate how it can break down under changes of the lattice structure.

The prevalence of type 2 diabetes (T2D) is increasing worldwide. Patients with T2D suffer from various diabetes-related complications. Since there are many patients with T2D that cannot be controlled by previously developed drugs, it has been necessary to develop new drugs, one of which is a glucagon-like peptide-1 (GLP-1) based therapy. GLP-1 has been shown to ameliorate diabetes-related conditions by augmenting pancreatic β-cell insulin secretion and having the low risk of causing hypoglycemia. Because of a very short half-life of GLP-1, many researches have been focused on the development of GLP-1 receptor (GLP-1R) agonists with long half-lives such as exenatide and dulaglutide. Now GLP-1R agonists have a variety of dosing-cycle forms to meet the needs of various patients. In this article, we review the physiological features of GLP-1, the effects of GLP-1 on T2D, the features of several GLP-1R agonists, and the therapeutic effect on T2D.

Background: Knowledge on microclimate conditions under artificial shades in a ginseng field would facilitate climate-aware management of ginseng production. Methods: Weather data were measured under the shade and outside the shade at two fields located in Gochang-gun and Jeongeup-si, Korea, in 2011 and 2012 seasons to assess temperature and humidity conditions under the shade. An empirical approach was developed and validated for the estimation of leaf wetness duration (LWD) using weather measurements outside the shade as inputs to the model. Results: Air temperature and relative humidity were similar between under the shade and outside the shade. For example, temperature conditions favorable for ginseng growth, e.g., between 8°C and 27°C, occurred slightly less frequently in hours during night times under the shade (91%) than outside (92%). Humidity conditions favorable for development of a foliar disease, e.g., relative humidity > 70%, occurred slightly more frequently under the shade (84%) than outside (82%). Effectiveness of correction schemes to an empirical LWD model differed by rainfall conditions for the estimation of LWD under the shade using weather measurements outside the shade as inputs to the model. During dew eligible days, a correction scheme to an empirical LWD model was slightly effective (10%) in reducing estimation errors under the shade. However, another correction approach during rainfall eligible days reduced errors of LWD estimation by 17%. Conclusion: Weather measurements outside the shade and LWD estimates derived from these measurements would be useful as inputs for decision support systems to predict ginseng growth and disease development.

The solution-processed deposition of metal-oxide semiconducting materials enables the fabrication of large-area and low-cost electronic devices by using printing technologies. Additionally, the simple patterning process of these types of materials become an important issue, as it can simplify the cost and process of fabricating electronics such as thin-film transistors (TFTs). In this study, using the electrohydrodynamic (EHD) jet printing technique, we fabricated directly patterned zinc-tin-oxide (ZTO) semiconductors as the active layers of TFTs. The straight lines of ZTO semiconductors were successfully drawn using a highly soluble and homogeneous solution that comprises zinc acrylate and tin-chloride precursors. Besides, we found the optimum condition for the fabrication of ZTO oxide layers by analyzing the thermal effect in processing. Using the optimized condition, the resulting devices exhibited satisfactory TFT characteristics with conventional electrodes and conducting materials. Furthermore, these metal-oxide TFTs were successfully applied to complementary inverter with conventional p-type organic semiconductor-based TFT, showing high quality of voltage transfer characteristics. Thus, these printed ZTO TFT results demonstrated that solution processable metal-oxide transistors are promising for the realization of a more sustainable and printable next-generation industrial technology.