Duration of Adjunctive Antidepressant Maintenance in Bipolar I Depression.

BACKGROUND: Antidepressants are used to treat acute depression in patients with bipolar I disorder, but their effect as maintenance treatment after the remission of depression has not been well studied. METHODS: We conducted a multisite, double-blind, randomized, placebo-controlled trial of maintenance of treatment with adjunctive escitalopram or bupropion XL as compared with discontinuation of antidepressant therapy in patients with bipolar I disorder who had recently had remission of a depressive episode. Patients were randomly assigned in a 1:1 ratio to continue treatment with antidepressants for 52 weeks after remission or to switch to placebo at 8 weeks. The primary outcome, assessed in a time-to-event analysis, was any mood episode, as defined by scores on scales measuring symptoms of hypomania or mania, depression, suicidality, and mood-episode severity; additional treatment or hospitalization for mood symptoms; or attempted or completed suicide. Key secondary outcomes included the time to an episode of mania or hypomania or depression. RESULTS: Of 209 patients with bipolar I disorder who participated in an open-label treatment phase, 150 who had remission of depression were enrolled in the double-blind phase in addition to 27 patients who were enrolled directly. A total of 90 patients were assigned to continue treatment with the prescribed antidepressant for 52 weeks (52-week group) and 87 were assigned to switch to placebo at 8 weeks (8-week group). The trial was stopped before full recruitment was reached owing to slow recruitment and funding limitations. At 52 weeks, 28 of the patients in the 52-week group (31%) and 40 in the 8-week group (46%) had a primary-outcome event. The hazard ratio for time to any mood episode in the 52-week group relative to the 8-week group was 0.68 (95% confidence interval [CI], 0.43 to 1.10; P = 0.12 by log-rank test). A total of 11 patients in the 52-week group (12%) as compared with 5 patients in the 8-week group (6%) had mania or hypomania (hazard ratio, 2.28; 95% CI, 0.86 to 6.08), and 15 patients (17%) as compared with 35 patients (40%) had recurrence of depression (hazard ratio, 0.43; 95% CI, 0.25 to 0.75). The incidence of adverse events was similar in the two groups. CONCLUSIONS: In a trial involving patients with bipolar I disorder and a recently remitted depressive episode, adjunctive treatment with escitalopram or bupropion XL that continued for 52 weeks did not show a significant benefit as compared with treatment for 8 weeks in preventing relapse of any mood episode. The trial was stopped early owing to slow recruitment and funding limitations. (Funded by the Canadian Institutes of Health Research; ClinicalTrials.gov number, NCT00958633.).

Replication Stress in Activated Human NK Cells Induces Sensitivity to Apoptosis.

NK cells are innate immune effectors that kill virally infected or malignant cells. NK cell deficiency (NKD) occurs when NK cell development or function is impaired and variants in MCM4, GINS1, MCM10, and GINS4 result in NKD. Although NK cells are strongly impacted by mutational deficiencies in helicase proteins, the mechanisms underlying this specific susceptibility are poorly understood. In this study, we induced replication stress in activated NK cells or T cells by chemical and genetic methods. We found that the CD56bright subset of NK cells accumulates more DNA damage and replication stress during activation than do CD56dim NK cells or T cells. Aphidicolin treatment increases apoptosis of CD56bright NK cells through increased pan-caspase expression and decreases perforin expression in surviving cells. These findings show that sensitivity to replication stress affects NK cell survival and function and contributes to NKD.

Unsupervised embedding of trajectories captures the latent structure of scientific migration.

Human migration and mobility drives major societal phenomena including epidemics, economies, innovation, and the diffusion of ideas. Although human mobility and migration have been heavily constrained by geographic distance throughout the history, advances, and globalization are making other factors such as language and culture increasingly more important. Advances in neural embedding models, originally designed for natural language, provide an opportunity to tame this complexity and open new avenues for the study of migration. Here, we demonstrate the ability of the model word2vec to encode nuanced relationships between discrete locations from migration trajectories, producing an accurate, dense, continuous, and meaningful vector-space representation. The resulting representation provides a functional distance between locations, as well as a "digital double" that can be distributed, re-used, and itself interrogated to understand the many dimensions of migration. We show that the unique power of word2vec to encode migration patterns stems from its mathematical equivalence with the gravity model of mobility. Focusing on the case of scientific migration, we apply word2vec to a database of three million migration trajectories of scientists derived from the affiliations listed on their publication records. Using techniques that leverage its semantic structure, we demonstrate that embeddings can learn the rich structure that underpins scientific migration, such as cultural, linguistic, and prestige relationships at multiple levels of granularity. Our results provide a theoretical foundation and methodological framework for using neural embeddings to represent and understand migration both within and beyond science.

Evaluation of a Nondepleted Plasma Multiprotein-Based Model for Discriminating Psychiatric Disorders Using Multiple Reaction Monitoring-Mass Spectrometry: Proof-of-Concept Study.

Psychiatric evaluation relies on subjective symptoms and behavioral observation, which sometimes leads to misdiagnosis. Despite previous efforts to utilize plasma proteins as objective markers, the depletion method is time-consuming. Therefore, this study aimed to enhance previous quantification methods and construct objective discriminative models for major psychiatric disorders using nondepleted plasma. Multiple reaction monitoring-mass spectrometry (MRM-MS) assays for quantifying 453 peptides in nondepleted plasma from 132 individuals [35 major depressive disorder (MDD), 47 bipolar disorder (BD), 23 schizophrenia (SCZ) patients, and 27 healthy controls (HC)] were developed. Pairwise discriminative models for MDD, BD, and SCZ, and a discriminative model between patients and HC were constructed by machine learning approaches. In addition, the proteins from nondepleted plasma-based discriminative models were compared with previously developed depleted plasma-based discriminative models. Discriminative models for MDD versus BD, BD versus SCZ, MDD versus SCZ, and patients versus HC were constructed with 11 to 13 proteins and showed reasonable performances (AUROC = 0.890-0.955). Most of the shared proteins between nondepleted and depleted plasma models had consistent directions of expression levels and were associated with neural signaling, inflammatory, and lipid metabolism pathways. These results suggest that multiprotein markers from nondepleted plasma have a potential role in psychiatric evaluation.

Targeting Mycobacterium tuberculosis response to environmental cues for the development of effective antitubercular drugs.

Sensing and response to environmental cues, such as pH and chloride (Cl-), is critical in enabling Mycobacterium tuberculosis (Mtb) colonization of its host. Utilizing a fluorescent reporter Mtb strain in a chemical screen, we have identified compounds that dysregulate Mtb response to high Cl- levels, with a subset of the hits also inhibiting Mtb growth in host macrophages. Structure-activity relationship studies on the hit compound "C6," or 2-(4-((2-(ethylthio)pyrimidin-5-yl)methyl)piperazin-1-yl)benzo[d]oxazole, demonstrated a correlation between compound perturbation of Mtb Cl- response and inhibition of bacterial growth in macrophages. C6 accumulated in both bacterial and host cells, and inhibited Mtb growth in cholesterol media, but not in rich media. Subsequent examination of the Cl- response of Mtb revealed an intriguing link with bacterial growth in cholesterol, with increased transcription of several Cl--responsive genes in the simultaneous presence of cholesterol and high external Cl- concentration, versus transcript levels observed during exposure to high external Cl- concentration alone. Strikingly, oral administration of C6 was able to inhibit Mtb growth in vivo in a C3HeB/FeJ murine infection model. Our work illustrates how Mtb response to environmental cues can intersect with its metabolism and be exploited in antitubercular drug discovery.

The effects of long-pulsed alexandrite laser therapy on facial redness and skin microbiota compositions in rosacea: A prospective, multicentre, single-arm clinical trial.

BACKGROUND: Rosacea is a chronic skin disorder characterised by abnormal neurovasculature and inflammation in the central region of the face. The efficacy of pulsed-dye laser and intense pulsed light treatments for rosacea have been demonstrated in several clinical trials. However, there is currently no research on the efficacy of long-pulsed alexandrite laser (LPAL) therapy alone for rosacea-related facial redness and its effect on skin microbiota. AIM: To evaluate the efficacy of LPAL therapy on facial redness in rosacea and assess changes in skin microbiota composition. METHODS: Subjects with rosacea (n = 21, mean age: 39.2 ± 11.3 years) were recruited from two medical institutions and received monthly LPAL treatments (Clarity II™, Lutronic Corp.) for 3 months. At each visit, clinical photographs were taken, and erythema was measured using a spectrometer. At the initial and final visits, the Dermatology Life Quality Index (DLQI) and Skin Sensitivity Questionnaire (SSQ) were evaluated. Skin swabs were obtained at the initial and final visit, and facial microbiome composition was analysed using 16S rRNA amplicon sequencing. RESULTS: After three LPAL treatment sessions, the average facial erythema index, measured using Mexameter® decreased significantly from 360.0 ± 96.7 at baseline to 312.0 ± 94.5 at the final visit (p < .05). The DLQI and SSQ showed significant improvement of symptoms. Skin microbiome diversity and relative abundance were altered significantly, particularly in the genera Clostridium, Lawsonella, Bacteroides, and Lactobacillus. CONCLUSIONS: LPAL therapy alone showed favourable efficacy for the treatment of facial redness in rosacea, with some impacts on the skin microbiota composition.

Whole-Section Landscape Analysis of Molecular Subtypes in Curatively Resected Small Cell Lung Cancer: Clinicopathologic Features and Prognostic Significance.

Despite the recognition of various molecular subtypes in small cell lung cancer (SCLC), most information has been derived from tissue microarrays or biopsy samples. Using whole sections of curatively resected SCLCs, we aimed to elucidate the clinicopathologic relevance and prognostic significance of the molecular subtypes. Whole-section immunohistochemistry was conducted for 73 resected SCLC samples using antibodies representative of molecular subtypes: ASCL1 (SCLC-A), NEUROD1 (SCLC-N), POU2F3 (SCLC-P), and YAP1. Furthermore, multiplexed immunofluorescence was performed to evaluate the spatial relationship of YAP1 expression with other markers. The molecular subtype was correlated with clinical and histomorphologic features, and its prognostic role was explored in this cohort and validated in a previously published surgical cohort. Overall, the molecular subtypes were SCLC-A (54.8%), SCLC-N (31.5%), SCLC-P (6.8%), and SCLC-TN (triple negative, 6.8%). We found significant enrichment of SCLC-N (48.0%; P = .004) among combined SCLCs. Although a distinct subtype with high YAP1 expression was not found, YAP1 expression was reciprocal with ASCL1/NEUROD1 at the cellular level within tumors and was increased in areas with non-small cell-like morphology. Furthermore, the YAP1-positive SCLCs showed significantly increased recurrence at mediastinal lymph nodes (P = .047) and are an independent poor prognostic factor after surgery (adjusted hazard ratio, 2.87; 95% CI, 1.20-6.86; P = .017). The poor prognostic impact of YAP1 was also validated in the external surgical cohort. Our whole-section analysis in resected SCLCs reveals the highly heterogeneous nature of the molecular subtype and its clinicopathologic relevance. Although YAP1 is not a subtype delineator, YAP1 relates to the phenotypic plasticity of SCLC and may serve as a poor prognostic factor in resected SCLC.

Prediction of impending mood episode recurrence using real-time digital phenotypes in major depression and bipolar disorders in South Korea: a prospective nationwide cohort study.

BACKGROUND: Mood disorders require consistent management of symptoms to prevent recurrences of mood episodes. Circadian rhythm (CR) disruption is a key symptom of mood disorders to be proactively managed to prevent mood episode recurrences. This study aims to predict impending mood episodes recurrences using digital phenotypes related to CR obtained from wearable devices and smartphones. METHODS: The study is a multicenter, nationwide, prospective, observational study with major depressive disorder, bipolar disorder I, and bipolar II disorder. A total of 495 patients were recruited from eight hospitals in South Korea. Patients were followed up for an average of 279.7 days (a total sample of 75 506 days) with wearable devices and smartphones and with clinical interviews conducted every 3 months. Algorithms predicting impending mood episodes were developed with machine learning. Algorithm-predicted mood episodes were then compared to those identified through face-to-face clinical interviews incorporating ecological momentary assessments of daily mood and energy. RESULTS: Two hundred seventy mood episodes recurred in 135 subjects during the follow-up period. The prediction accuracies for impending major depressive episodes, manic episodes, and hypomanic episodes for the next 3 days were 90.1, 92.6, and 93.0%, with the area under the curve values of 0.937, 0.957, and 0.963, respectively. CONCLUSIONS: We predicted the onset of mood episode recurrences exclusively using digital phenotypes. Specifically, phenotypes indicating CR misalignment contributed the most to the prediction of episodes recurrences. Our findings suggest that monitoring of CR using digital devices can be useful in preventing and treating mood disorders.

Production of Molecular Iodine via a Redox Reaction between Iodate and Organic Compounds in Ice.

The abiotic mechanism of molecular iodine (I2) production from iodate (IO3-) remains largely unknown. Here, we demonstrate the production of I2 in the presence of IO3- and organic compounds in ice. When the solution containing IO3- (100 µM) and furfuryl alcohol (100 µM) at pH 3.0 was frozen at -20 °C, 13.1 µM of I2 was produced with complete degradation of furfuryl alcohol after 20 min. However, there was little change in the IO3- and furfuryl alcohol concentrations in water at 25 °C. The production of I2 in ice is due to the freeze concentration effect, which induces the accumulation of IO3-, furfuryl alcohol, and protons in the ice grain boundaries. This behavior facilitated the production of I2 via a redox reaction between IO3- and organic compounds. The production of I2 increased with increasing furfuryl alcohol concentration and decreasing pH. However, freezing temperature had a minor effect on the maximum production of I2. The production of I2 is highly dependent on the type of organic compounds. It was higher for organic compounds with higher electron-donating properties. This study suggests a new mechanism for I2 production, which is helpful for predicting precisely the atmospheric I2 budget in cold regions.

Recent trends in radiotherapy use for major cancers in Korea.

BACKGROUND: Although the trend in radiotherapy in all cancer patients has been studied, changes in radiotherapy modalities for specific cancer types have not been reported. This study aimed to analyze radiotherapy patterns for major cancers in Korea in recent years. MATERIALS AND METHODS: We collected data from claims and reimbursement records of the Health and Insurance Review and Assessment Service from 2017 to 2020, according to initial diagnostic codes. The radiotherapy modalities for major cancers, such as lung, stomach, colorectal, breast and liver cancer, were analyzed. The radiotherapy modalities consisted of two-dimensional radiotherapy, three-dimensional conformal radiotherapy, intensity-modulated radiotherapy, proton radiotherapy and stereotactic body radiotherapy. RESULTS: Overall, from 2017 to 2020, the use of two-dimensional radiotherapy and three-dimensional conformal radiotherapy decreased, and intensity-modulated radiotherapy increased. In 2017, three-dimensional conformal radiotherapy accounted for approximately half of the radiotherapy in patients for lung and colorectal cancer, which was replaced by intensity-modulated radiotherapy in 2020. In 2020, stereotactic body radiotherapy also accounted for a large proportion of radiotherapy used in liver cancer cases. Intensity-modulated radiotherapy was most used, followed by three-dimensional conformal radiotherapy and two-dimensional radiotherapy for breast cancer in 2020. Among major cancers, radiotherapy utilization for breast cancer is the highest. Compared with other cancers, the number of patients receiving radiotherapy for stomach cancer was low. CONCLUSION: The number of patients receiving radiotherapy for major cancers has increased. The use of advanced forms of radiotherapy, such as intensity-modulated radiotherapy, is rapidly increasing for major cancers. The rate of radiotherapy utilization was higher in major cancer patients than in all cancer patients.

Evidence from internet search data shows information-seeking responses to news of local COVID-19 cases.

The COVID-19 outbreak is a global pandemic with community circulation in many countries, including the United States, with confirmed cases in all states. The course of this pandemic will be shaped by how governments enact timely policies and disseminate information and by how the public reacts to policies and information. Here, we examine information-seeking responses to the first COVID-19 case public announcement in a state. Using an event study framework for all US states, we show that such news increases collective attention to the crisis right away. However, the elevated level of attention is short-lived, even though the initial announcements are followed by increasingly strong policy measures. Specifically, searches for "coronavirus" increased by about 36% (95% CI: 27 to 44%) on the day immediately after the first case announcement but decreased back to the baseline level in less than a week or two. We find that people respond to the first report of COVID-19 in their state by immediately seeking information about COVID-19, as measured by searches for coronavirus, coronavirus symptoms, and hand sanitizer. On the other hand, searches for information regarding community-level policies (e.g., quarantine, school closures, testing) or personal health strategies (e.g., masks, grocery delivery, over-the-counter medications) do not appear to be immediately triggered by first reports. These results are representative of the study period being relatively early in the epidemic, and more-elaborate policy responses were not yet part of the public discourse. Further analysis should track evolving patterns of responses to subsequent flows of public information.

The Social Contagion Potential of Pro-Vaccine Messages on Black Twitter.

Black Americans in the US not only suffered from disproportionately high hospitalization and death rates throughout the pandemic but also from the consequences of low COVID-19 vaccination rates. This pattern of disparity is linked to distrust of public health systems that originates from a history of medical atrocities committed against Black people. For that reason, mitigation of race-based inequity in COVID-19 impacts might find more success in grassroots information contagion than official public health campaigns. While Black Twitter is well-positioned as a conduit for such information contagion, little is known about message characteristics that would afford it. Here, we tested the impact of four different message frames (personalization, interactive, fear appeal, neutral) on the social contagion potential of bi-modal social media messages promoting COVID-19 vaccinations and finding personalized messages to be the most shareable. Wary of recommending personalization as the blueprint for setting a social contagion health campaign in motion, we probed further to understand the influence of individual-level variables on the communicability of personalized messages. Subsequently, regression models and focus group data were consulted, revealing that thinking styles, vaccine confidence levels, and attitudes toward social media were significant factors of influence on the contagion potential of personalized messages. We discussed the implications of these results for health campaigns.

Acoustic Analysis of Speech for Screening for Suicide Risk: Machine Learning Classifiers for Between- and Within-Person Evaluation of Suicidality.

BACKGROUND: Assessing a patient's suicide risk is challenging for health professionals because it depends on voluntary disclosure by the patient and often has limited resources. The application of novel machine learning approaches to determine suicide risk has clinical utility. OBJECTIVE: This study aimed to investigate cross-sectional and longitudinal approaches to assess suicidality based on acoustic voice features of psychiatric patients using artificial intelligence. METHODS: We collected 348 voice recordings during clinical interviews of 104 patients diagnosed with mood disorders at baseline and 2, 4, 8, and 12 months after recruitment. Suicidality was assessed using the Beck Scale for Suicidal Ideation and suicidal behavior using the Columbia Suicide Severity Rating Scale. The acoustic features of the voice, including temporal, formal, and spectral features, were extracted from the recordings. A between-person classification model that examines the vocal characteristics of individuals cross sectionally to detect individuals at high risk for suicide and a within-person classification model that detects considerable worsening of suicidality based on changes in acoustic features within an individual were developed and compared. Internal validation was performed using 10-fold cross validation of audio data from baseline to 2-month and external validation was performed using data from 2 to 4 months. RESULTS: A combined set of 12 acoustic features and 3 demographic variables (age, sex, and past suicide attempts) were included in the single-layer artificial neural network for the between-person classification model. Furthermore, 13 acoustic features were included in the extreme gradient boosting machine learning algorithm for the within-person model. The between-person classifier was able to detect high suicidality with 69% accuracy (sensitivity 74%, specificity 62%, area under the receiver operating characteristic curve 0.62), whereas the within-person model was able to predict worsening suicidality over 2 months with 79% accuracy (sensitivity 68%, specificity 84%, area under receiver operating characteristic curve 0.67). The second model showed 62% accuracy in predicting increased suicidality in external sets. CONCLUSIONS: Within-person analysis using changes in acoustic features within an individual is a promising approach to detect increased suicidality. Automated analysis of voice can be used to support the real-time assessment of suicide risk in primary care or telemedicine.

Nanozyme based colorimetric detection of biogenic gaseous H2S using Ag@Au core/shell nanoplates with peroxidase-like activity.

A highly sensitive and facile colorimetric assay is introduced for detecting biogenic gaseous H2S using peroxidase (POD)-like catalytic activity of silver core/gold shell nanoplates (Ag@Au NPls). H2S can react with Ag@Au NPls to form Ag2S or Au2S on their surface, which can reduce POD-like activity of Ag@Au NPls and consequently decrease the absorbance at 650 nm due to oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) in the presence of hydrogen peroxide (H2O2). For in situ and multiple detection of H2S, we utilized a microplate cover with 24 polydimethylsiloxane inner wells where Ag@Au NPls reacted with H2S gas followed by treatment with TMB/H2O2. As a result, the change in absorbance at 650 nm showed a linear relationship with the H2S concentration in the range 0.33 to 2.96 µM (0.36 absorbance/µM H2S in PBS, R2 = 0.994) with a limit of detection of 263 nM and a relative standard deviation of 4.4%. Finally, this assay could detect H2S released from Eikenella corrodens, used as a model bacterium, in a short time (20 min) or at a low number of bacteria (1 × 104 colony forming units/mL). Therefore, this assay is expected to be applied for the study of H2S signaling in bacterial physiology, as well as measure H2S production released from other oral bacteria that cause halitosis and oral diseases, leading to the subsequent diagnosis.

A Novel Oral GyrB/ParE Dual Binding Inhibitor Effective against Multidrug-Resistant Neisseria gonorrhoeae and Other High-Threat Pathogens.

Drug-resistant Neisseria gonorrhoeae is a serious global health concern. New drugs are needed that can overcome existing drug resistance and limit the development of new resistances. Here, we describe the small molecule tricyclic pyrimidoindole JSF-2414 [8-(6-fluoro-8-(methylamino)-2-((2-methylpyrimidin-5-yl)oxy)-9H-pyrimido[4,5-b]indol-4-yl)-2-oxa-8-azaspiro[4.5]decan-3-yl)methanol], which was developed to target both ATP-binding regions of DNA gyrase (GyrB) and topoisomerase (ParE). JSF-2414 displays potent activity against N. gonorrhoeae, including drug-resistant strains. A phosphate pro-drug, JSF-2659, was developed to facilitate oral dosing. In two different animal models of Neisseria gonorrhoeae vaginal infection, JSF-2659 was highly efficacious in reducing microbial burdens to the limit of detection. The parent molecule also showed potent in vitro activity against high-threat Gram-positive organisms, and JSF-2659 was shown in a deep tissue model of vancomycin-resistant Staphylococcus aureus (VRSA) and a model of Clostridioides difficile-induced colitis to be highly efficacious and protective. JSF-2659 is a novel preclinical drug candidate against high-threat multidrug resistant organisms with low potential to develop new resistance.

Frozen Hydrogen Peroxide and Nitrite Solution: The Acceleration of Benzoic Acid Oxidation via the Decreased pH in Ice.

We investigated benzoic acid oxidation via the reaction of hydrogen peroxide (H2O2) and nitrite (NO2-). The oxidation of benzoic acid by reactive nitrous acid (HONO) was negligible, and the reactivity of the H2O2/NO2- system decreased with a decrease in temperature under aqueous conditions. However, freezing markedly accelerated the chemical reaction. Based on Raman microscope measurements, concentrated species were confirmed in certain regions of the ice. We proposed that the change in nitrite speciation (accordingly, a decrease in the pH below pKa), derived from the freezing concentration effect, was the reason for the accelerated reactions. The oxidation characteristics of the system were monitored under varying conditions, such as initial pH, dosage ratio, benzoic acid concentration, and reaction with various benzene derivatives. The ultrahigh-performance liquid chromatography/electrospray ionization/mass spectrometry (UHPLC/ESI/MS) measurement showed that peroxynitrous acid (HOONO)-mediated oxidation generated hydroxylated and nitrated byproducts. Additionally, decarboxylated products were detected, indicating direct electron transfer from the organic compounds to HOONO. As freezing is a global phenomenon, and H2O2 and NO2- are ubiquitous in the environment, the transformation of aromatic compounds with H2O2/NO2- in cold environments must be considered in environmental chemistry.

Development of an integrated fatigue measurement system for construction workers: a feasibility study.

BACKGROUND: Construction workers working in physically and mentally challenging environments experience high levels of occupational fatigue, which is the primary cause of industrial accidents and illnesses. Therefore, it is very important to measure fatigue in real time to manage the safety and health of construction workers. This study presents a novel approach for simultaneously measuring the subjective and objective fatigue of construction workers using ecological momentary assessment (EMA) and smartwatches. Due to the complexity and diversity of construction site environments, it is necessary to examine whether data collection using smartwatches is suitable in actual construction sites. This study aims to examine the feasibility of the integrated fatigue measurement method. METHODS: This study comprised two phases: (1) development of an integrated fatigue measurement system for construction workers, and (2) a validation study to evaluate the method's feasibility based on sensor data acquisition, EMA compliance, and feedback from construction workers in the field (N = 80). Three days of biometric data were collected through sensors embedded in the smartwatches for objective fatigue measurement, including heart rate, accelerometer, and gyroscope data. Two types of self-reported data regarding each worker's fatigue were collected through a researcher-developed EMA application. The acceptability and usability of this system were examined based on the researchers' observations and unstructured interviews. RESULTS: Based on the standardized self-report questionnaire scores, participants were classified into high (n = 35, 43.75%) and low (n = 45, 56.25%) fatigue groups for comparison. The quantitative outcomes did not show a statistically significant difference between the two fatigue groups. Both groups experienced positive emotions and were able to recognize their health condition at the time of self-reporting, but stated that responding to this measurement system could be burdensome. CONCLUSIONS: This feasibility study provides a unique understanding of the applications of EMA and smartwatches for safety management in the construction workforce. The developed measurement system shows potential for monitoring fatigue based on the real-time collection of relevant data. It is expected that by expanding this integrated system through further research and onsite application, the health and safety of construction workers can be improved.

Learning curve for minimally invasive transforaminal lumbar interbody fusion: a systematic review.

PURPOSE: Minimally invasive transforaminal lumbar interbody fusion (MI-TLIF) is commonly used to treat degenerative lumbar spinal disorders. It facilitates a full-scale spinal decompression and interbody fusion with minimal neural retraction using the tubular retractor system. Despite the benefits of surgical efficiency and minimalism, this technique requires a long learning curve. There is currently no consensus on the learning curve characteristics and proper training methods for MI-TLIF. Thus, this systematic review aimed to discuss the cutoff point at which technical proficiency is achieved and ways to enhance the learning process. METHODS: Major databases, including PubMed, Embase, and Cochrane Library, were searched for learning curve studies that have evaluated the clinical outcome and learning progress of MI-TLIF using quantitative data. The qualities of the selected studies were assessed using the Newcastle‒Ottawa scale. The plateau points in the "learning curve" were analyzed according to various outcome measures. RESULTS: Nine full-text articles, representing 753 cases, were included from 9743 screened studies. The most commonly used outcome measures were the operative time, followed by the complication rate. The mean cutoff point for the operative time was 31.33 ± 11.98 (range 13‒45) cases. CONCLUSION: The plateau point in the learning curve for MI-TLIF may differ according to the outcome measures used. Most studies have demonstrated the learning progress based on simple task efficiency, rather than patient outcomes. Moreover, the learning rate may be affected by the patients' and technical conditions. Therefore, great care is required in interpreting the learning curve and cutoff point for MI-TLIF proficiency.

Percutaneous endoscopic lumbar foraminotomy: how I do it.

BACKGROUND: Percutaneous endoscopic lumbar foraminotomy (PELF) is a good alternative for foraminal stenosis. The steep learning curve and lack of a practical manual can make this technique challenging. METHOD: We describe a step-by-step technique based on the literature review and our experience in actual practice: (1) posterolateral foraminal landing, (2) bony unroofing of the superior articular process, and (3) full-scale soft tissue decompression. Technical tips for preventing complications are also discussed. CONCLUSION: PELF may be effective and minimally invasive. Standardized surgical techniques are essential for clinical success.

Simple and Sensitive Detection of Bacterial Hydrogen Sulfide Production Using a Paper-Based Colorimetric Assay.

Hydrogen sulfide (H2S) is known to participate in bacteria-induced inflammatory response in periodontal diseases. Therefore, it is necessary to quantify H2S produced by oral bacteria for diagnosis and treatment of oral diseases including halitosis and periodontal disease. In this study, we introduce a paper-based colorimetric assay for detecting bacterial H2S utilizing silver/Nafion/polyvinylpyrrolidone membrane and a 96-well microplate. This H2S-sensing paper showed a good sensitivity (8.27 blue channel intensity/µM H2S, R2 = 0.9996), which was higher than that of lead acetate paper (6.05 blue channel intensity/µM H2S, R2 = 0.9959). We analyzed the difference in H2S concentration released from four kinds of oral bacteria (Eikenella corrodens, Streptococcus sobrinus, Streptococcus mutans, and Lactobacillus casei). Finally, the H2S level in Eikenella corrodens while varying the concentration of cysteine and treatment time was quantified. This paper-based colorimetric assay can be utilized as a simple and effective tool for in vitro screening of H2S-producing ability of many bacteria as well as salivary H2S analysis.