A natural single-guide RNA repurposes Cas9 to autoregulate CRISPR-Cas expression.

CRISPR-Cas systems provide prokaryotes with acquired immunity against viruses and plasmids, but how these systems are regulated to prevent autoimmunity is poorly understood. Here, we show that in the S. pyogenes CRISPR-Cas system, a long-form transactivating CRISPR RNA (tracr-L) folds into a natural single guide that directs Cas9 to transcriptionally repress its own promoter (Pcas). Further, we demonstrate that Pcas serves as a critical regulatory node. De-repression causes a dramatic 3,000-fold increase in immunization rates against viruses; however, heightened immunity comes at the cost of increased autoimmune toxicity. Using bioinformatic analyses, we provide evidence that tracrRNA-mediated autoregulation is widespread in type II-A CRISPR-Cas systems. Collectively, we unveil a new paradigm for the intrinsic regulation of CRISPR-Cas systems by natural single guides, which may facilitate the frequent horizontal transfer of these systems into new hosts that have not yet evolved their own regulatory strategies.

O-GlcNAc forces an α-synuclein amyloid strain with notably diminished seeding and pathology.

Amyloid-forming proteins such α-synuclein and tau, which are implicated in Alzheimer's and Parkinson's disease, can form different fibril structures or strains with distinct toxic properties, seeding activities and pathology. Understanding the determinants contributing to the formation of different amyloid features could open new avenues for developing disease-specific diagnostics and therapies. Here we report that O-GlcNAc modification of α-synuclein monomers results in the formation of amyloid fibril with distinct core structure, as revealed by cryogenic electron microscopy, and diminished seeding activity in seeding-based neuronal and rodent models of Parkinson's disease. Although the mechanisms underpinning the seeding neutralization activity of the O-GlcNAc-modified fibrils remain unclear, our in vitro mechanistic studies indicate that heat shock proteins interactions with O-GlcNAc fibril inhibit their seeding activity, suggesting that the O-GlcNAc modification may alter the interactome of the α-synuclein fibrils in ways that lead to reduce seeding activity in vivo. Our results show that posttranslational modifications, such as O-GlcNAc modification, of α-synuclein are key determinants of α-synuclein amyloid strains and pathogenicity.

"Helicase" Activity promoted through dynamic interactions between a ssDNA translocase and a diffusing SSB protein.

Replication protein A (RPA) is a eukaryotic single-stranded (ss) DNA-binding (SSB) protein that is essential for all aspects of genome maintenance. RPA binds ssDNA with high affinity but can also diffuse along ssDNA. By itself, RPA is capable of transiently disrupting short regions of duplex DNA by diffusing from a ssDNA that flanks the duplex DNA. Using single-molecule total internal reflection fluorescence and optical trapping combined with fluorescence approaches, we show that S. cerevisiae Pif1 can use its ATP-dependent 5' to 3' translocase activity to chemomechanically push a single human RPA (hRPA) heterotrimer directionally along ssDNA at rates comparable to those of Pif1 translocation alone. We further show that using its translocation activity, Pif1 can push hRPA from a ssDNA loading site into a duplex DNA causing stable disruption of at least 9 bp of duplex DNA. These results highlight the dynamic nature of hRPA enabling it to be readily reorganized even when bound tightly to ssDNA and demonstrate a mechanism by which directional DNA unwinding can be achieved through the combined action of a ssDNA translocase that pushes an SSB protein. These results highlight the two basic requirements for any processive DNA helicase: transient DNA base pair melting (supplied by hRPA) and ATP-dependent directional ssDNA translocation (supplied by Pif1) and that these functions can be unlinked by using two separate proteins.

Structure-based design of nanobodies that inhibit seeding of Alzheimer's patient-extracted tau fibrils.

Despite much effort, antibody therapies for Alzheimer's disease (AD) have shown limited efficacy. Challenges to the rational design of effective antibodies include the difficulty of achieving specific affinity to critical targets, poor expression, and antibody aggregation caused by buried charges and unstructured loops. To overcome these challenges, we grafted previously determined sequences of fibril-capping amyloid inhibitors onto a camel heavy chain antibody scaffold. These sequences were designed to cap fibrils of tau, known to form the neurofibrillary tangles of AD, thereby preventing fibril elongation. The nanobodies grafted with capping inhibitors blocked tau aggregation in biosensor cells seeded with postmortem brain extracts from AD and progressive supranuclear palsy (PSP) patients. The tau capping nanobody inhibitors also blocked seeding by recombinant tau oligomers. Another challenge to the design of effective antibodies is their poor blood-brain barrier (BBB) penetration. In this study, we also designed a bispecific nanobody composed of a nanobody that targets a receptor on the BBB and a tau capping nanobody inhibitor, conjoined by a flexible linker. We provide evidence that the bispecific nanobody improved BBB penetration over the tau capping inhibitor alone after intravenous administration in mice. Our results suggest that the design of synthetic antibodies that target sequences that drive protein aggregation may be a promising approach to inhibit the prion-like seeding of tau and other proteins involved in AD and related proteinopathies.

Cryo-EM structure of RNA-induced tau fibrils reveals a small C-terminal core that may nucleate fibril formation.

In neurodegenerative diseases including Alzheimer's and amyotrophic lateral sclerosis, proteins that bind RNA are found in aggregated forms in autopsied brains. Evidence suggests that RNA aids nucleation of these pathological aggregates; however, the mechanism has not been investigated at the level of atomic structure. Here, we present the 3.4-Å resolution structure of fibrils of full-length recombinant tau protein in the presence of RNA, determined by electron cryomicroscopy (cryo-EM). The structure reveals the familiar in-register cross-ß amyloid scaffold but with a small fibril core spanning residues Glu391 to Ala426, a region disordered in the fuzzy coat in all previously studied tau polymorphs. RNA is bound on the fibril surface to the positively charged residues Arg406 and His407 and runs parallel to the fibril axis. The fibrils dissolve when RNase is added, showing that RNA is necessary for fibril integrity. While this structure cannot exist simultaneously with the tau fibril structures extracted from patients' brains, it could conceivably account for the nucleating effects of RNA cofactors followed by remodeling as fibrils mature.

Mycobacterium tuberculosis DNA repair helicase UvrD1 is activated by redox-dependent dimerization via a 2B domain cysteine.

Mycobacterium tuberculosis (Mtb) causes tuberculosis and, during infection, is exposed to reactive oxygen species and reactive nitrogen intermediates from the host immune response that can cause DNA damage. UvrD-like proteins are involved in DNA repair and replication and belong to the SF1 family of DNA helicases that use ATP hydrolysis to catalyze DNA unwinding. In Mtb, there are two UvrD-like enzymes, where UvrD1 is most closely related to other family members. Previous studies have suggested that UvrD1 is exclusively monomeric; however, it is well known that Escherichia coli UvrD and other UvrD family members exhibit monomer-dimer equilibria and unwind as dimers in the absence of accessory factors. Here, we reconcile these incongruent studies by showing that Mtb UvrD1 exists in monomer, dimer, and higher-order oligomeric forms, where dimerization is regulated by redox potential. We identify a 2B domain cysteine, conserved in many Actinobacteria, that underlies this effect. We also show that UvrD1 DNA-unwinding activity correlates specifically with the dimer population and is thus titrated directly via increasing positive (i.e., oxidative) redox potential. Consistent with the regulatory role of the 2B domain and the dimerization-based activation of DNA unwinding in UvrD family helicases, these results suggest that UvrD1 is activated under oxidizing conditions when it may be needed to respond to DNA damage during infection.

An efficient hybrid deep learning architecture for predicting short antimicrobial peptides.

Short-length antimicrobial peptides (AMPs) have been demonstrated to have intensified antimicrobial activities against a wide spectrum of microbes. Therefore, exploration of novel and promising short AMPs is highly essential in developing various types of antimicrobial drugs or treatments. In addition to experimental approaches, computational methods have been developed to improve screening efficiency. Although existing computational methods have achieved satisfactory performance, there is still much room for model improvement. In this study, we proposed iAMP-DL, an efficient hybrid deep learning architecture, for predicting short AMPs. The model was constructed using two well-known deep learning architectures: the long short-term memory architecture and convolutional neural networks. To fairly assess the performance of the model, we compared our model with existing state-of-the-art methods using the same independent test set. Our comparative analysis shows that iAMP-DL outperformed other methods. Furthermore, to assess the robustness and stability of our model, the experiments were repeated 10 times to observe the variation in prediction efficiency. The results demonstrate that iAMP-DL is an effective, robust, and stable framework for detecting promising short AMPs. Another comparative study of different negative data sampling methods also confirms the effectiveness of our method and demonstrates that it can also be used to develop a robust model for predicting AMPs in general. The proposed framework was also deployed as an online web server with a user-friendly interface to support the research community in identifying short AMPs.

Physical activity across midlife and health-related quality of life in Australian women: A target trial emulation using a longitudinal cohort.

BACKGROUND: There is little long-term causal evidence on the effect of physical activity on health-related quality of life. This study aimed to examine the associations between longitudinal patterns of physical activity over 15 years and health-related quality of life in both the physical and mental health domains, in a cohort of middle-aged Australian women. METHODS AND FINDINGS: We used data collected at 3-year intervals (1998 to 2019) from 11,336 participants in the Australian Longitudinal Study on Women's Health (ALSWH) (1946 to 1951 birth cohort). Primary outcomes were the physical (PCS) and mental health component summary (MCS) scores (range from 0 to 100; higher scores indicate higher perceived physical/mental health) from the SF-36 in 2019 (when women aged 68 to 73 years). Using target trial emulation to imitate a randomized controlled trial (RCT), we tested 2 interventions: (1) meeting the World Health Organization (WHO) physical activity guidelines consistently throughout the 15-year "exposure period" (2001 to 2016; when women aged 50-55 to 65-70 years; physical activity assessed every 3 years); and (2) not meeting the guidelines at the beginning of the exposure period but starting to first meet the guidelines at age 55, 60, or 65; against the control of not meeting the guidelines throughout the exposure period. Analysis controlled for confounding using marginal structural models which were adjusted for sociodemographic and health variables and conditions. Consistent adherence to guidelines during the exposure period (PCS: 46.93 [99.5% confidence interval [CI]: 46.32, 47.54]) and first starting to meet the guidelines at age 55 (PCS: 46.96 [99.5% CI: 45.53, 48.40]) were associated with three-point higher PCS (mean score difference: 3.0 [99.5% CI: 1.8, 4.1] and 3.0 [99.5% CI:1.2, 4.8]) than consistent non-adherence (PCS: 43.90 [99.5% CI: 42.79, 45.01]). We found a similar pattern for most SF-36 subscales but no significant effects of the interventions on MCS. The main limitations of the study were that it may not account for all underlying health conditions and/or other unmeasured or insufficiently measured confounders, the use of self-reported physical activity and that findings may not be generalizable to all mid-age women. CONCLUSIONS: Results from the emulated RCT suggest women should be active throughout mid-age, ideally increasing activity levels to meet the guidelines by age 55, to gain the most benefits for physical health in later life.

Telehealth Initiation of Buprenorphine for Opioid Use Disorder: Patient Characteristics and Outcomes.

BACKGROUND: The COVID-19 pandemic exacerbated access barriers for patients with opioid use disorder. Telehealth presents an opportunity to improve access, treatment quality, and patient outcomes. OBJECTIVE: To determine patient characteristics associated with initiating buprenorphine treatment via telehealth and to examine how telehealth initiation is associated with access, treatment quality, and health outcomes. DESIGN AND PARTICIPANTS: This cross-sectional study used deidentified insurance claims to identify opioid use disorder adult patients initiating buprenorphine treatment between March 1, 2020, and November 30, 2021. Multivariable logistic regression assessed determinants of telehealth initiation. Propensity score matching addressed observed differences between in-person and telehealth initiators. MAIN MEASURES: Treatment quality outcomes included initiation within 14 days of diagnosis, engagement (at least 2 opioid use disorder-related visits), and any buprenorphine refill during the study period. Health outcomes included opioid overdose and opioid use disorder-related emergency department and inpatient visits. KEY RESULTS: We identified 23,565 adult buprenorphine initiators, including 3314 (14.1%) patients using telehealth. Younger patients (OR 0.91 to 0.77), females (OR 1.18), South (OR 1.63) and Midwest (OR 1.27) regions, rural area (OR 1.12), and higher-income (OR 1.16) neighborhood residents were more likely to use telehealth. Telehealth patients were more likely than in-person patients (54.5% vs. 48.4%; adjusted odds ratio (AOR), 1.29; 95% CI, 1.19-1.40) to stay engaged with opioid use disorder treatment, and more likely to refill buprenorphine during the study period (83.6% vs. 79.0%, AOR 1.37; 95% CI, 1.23-1.52). Telehealth initiation of buprenorphine was associated with 36% lower overdose rate than in-person initiation (adjusted incidence rate ratio 0.64; 95% CI, 0.45-0.94). The two groups evidenced no significant differences in opioid use disorder-related ED visit and hospitalization. CONCLUSIONS: Our findings suggest that telehealth-initiated buprenorphine treatment is associated with reduced opioid overdose rate and improved patient engagement. Our findings strengthen the case for extending telehealth exemptions and prescribing flexibilities for treatment.

Relationship of Hoarding and Depression Symptoms in Older Adults.

Hoarding disorder (HD) is a debilitating neuropsychiatric condition that affects 2%-6% of the population and increases in incidence with age. Major depressive disorder (MDD) co-occurs with HD in approximately 50% of cases and leads to increased functional impairment and disability. However, only one study to date has examined the rate and trajectory of hoarding symptoms in older individuals with a lifetime history of MDD, including those with current active depression (late-life depression; LLD). We therefore sought to characterize this potentially distinct phenotype. We determined the incidence of HD in two separate cohorts of participants with LLD (n = 73) or lifetime history of MDD (n = 580) and examined the reliability and stability of hoarding symptoms using the Saving Inventory-Revised (SI-R) and Hoarding Rating Scale-Self Report (HRS), as well as the co-variance of hoarding and depression scores over time. HD was present in 12% to 33% of participants with MDD, with higher rates found in those with active depressive symptoms. Hoarding severity was stable across timepoints in both samples (all correlations >0.75), and fewer than 30% of participants in each sample experienced significant changes in severity between any two timepoints. Change in depression symptoms over time did not co-vary with change in hoarding symptoms. These findings indicate that hoarding is a more common comorbidity in LLD than previously suggested, and should be considered in screening and management of LLD. Future studies should further characterize the interaction of these conditions and their impact on outcomes, particularly functional impairment in this vulnerable population.

Injecting drug use increases the risk of death in HIV patients on antiretroviral therapy in Vietnam.

The Human Immunodeficiency Virus (HIV) epidemic remains a major public health issue worldwide. In Vietnam, the HIV epidemic is essentially driven by people who inject drugs (PWID). This study aims to compare mortality and loss to follow-up (LTFU) between PWID and other patients. From June 2017 to April 2018, HIV-infected adults were enrolled in a prospective cohort from time of ART initiation in six provinces of North Vietnam. The end date was July 2020. Mortality and LTFU were described using competing-risk survival models. Factors associated with mortality and with LTFU were identified using Cox models with a competing-risk approach. Of the 578 participants, 261 (45.2%) were PWID and almost exclusively male. 49 patients died, corresponding to a mortality rate (95% confidence interval (CI)) of 3.7 (2.8-4.9) per 100 person-months, and 79 were lost to follow-up, corresponding to a rate (95% CI) of 6.0 (4.8-7.4) per 100 person-months. PWID were at higher risk of death but not of LTFU. Overall, LTFU was high in both groups. Latecomers to clinical visits were more at risk of both death and LTFU. Therefore, this should be a warning to clinical teams and preventive actions taken in these patients.Trial registration: ClinicalTrials.gov identifier: NCT03249493..

Multitask Learning on Graph Convolutional Residual Neural Networks for Screening of Multitarget Anticancer Compounds.

Recently, various modern experimental screening pipelines and assays have been developed to find promising anticancer drug candidates. However, it is time-consuming and almost infeasible to screen an immense number of compounds for anticancer activity via experimental approaches. To partially address this issue, several computational advances have been proposed. In this study, we present iACP-GCR, a model based on multitask learning on graph convolutional residual neural networks with two types of shortcut connections, to identify multitarget anticancer compounds. In our architecture, the graph convolutional residual neural networks are shared by all the prediction tasks before being separately customized. The NCI-60 data set, one of the most reliable and well-known sources of experimentally verified compounds, was used to develop our model. From that data set, we collected and refined data about compounds screened across nine cancer types (panels), including breast, central nervous system, colon, leukemia, nonsmall cell lung, melanoma, ovarian, prostate, and renal, for model training and evaluation. The model performance evaluated on an independent test set shows that iACP-GCR surpasses the three advanced computational methods for multitask learning. The integration of two shortcut connection types in the shared networks also improves the prediction efficiency. We also deployed the model as a public web server to assist the research community in screening potential anticancer compounds.

Predicting Cardiotoxicity of Molecules Using Attention-Based Graph Neural Networks.

In drug discovery, the search for new and effective medications is often hindered by concerns about toxicity. Numerous promising molecules fail to pass the later phases of drug development due to strict toxicity assessments. This challenge significantly increases the cost, time, and human effort needed to discover new therapeutic molecules. Additionally, a considerable number of drugs already on the market have been withdrawn or re-evaluated because of their unwanted side effects. Among the various types of toxicity, drug-induced heart damage is a severe adverse effect commonly associated with several medications, especially those used in cancer treatments. Although a number of computational approaches have been proposed to identify the cardiotoxicity of molecules, the performance and interpretability of the existing approaches are limited. In our study, we proposed a more effective computational framework to predict the cardiotoxicity of molecules using an attention-based graph neural network. Experimental results indicated that the proposed framework outperformed the other methods. The stability of the model was also confirmed by our experiments. To assist researchers in evaluating the cardiotoxicity of molecules, we have developed an easy-to-use online web server that incorporates our model.

Low HBV knowledge is associated with low HBV vaccination uptake in general adult population despite incentivization of HBV vaccination.

BACKGROUND: Hepatitis B virus (HBV) vaccination in Vietnamese adults remains low and unequally distributed. We conducted a study on HBV-naïve adults living in Ho Chi Minh City, Viet Nam, to determine barriers associated with HBV vaccination uptake after removing the financial barrier by providing free coupons for HBV vaccination. METHODS: After being screened for HBsAg, anti-HBs, and anti-HBc, 284 HBV-naïve study participants aged 18 and over (i.e., negative for HBsAg, anti-HBs, and anti-HBc total) were provided free 3-dose HBV vaccine coupons. Next, study participants' receipt of 1st, 2nd, and 3rd doses of HBV vaccine was documented at a pre-specified study healthcare facility, where HBV vaccines were distributed at no cost to the participants. Upon study entry, participants answered questionnaires on sociodemographics, knowledge of HBV and HBV vaccination, and related social and behavioral factors. The proportions of three doses of HBV vaccine uptake and their confidence intervals were analyzed. Associations of HBV vaccine initiation with exposures at study entry were evaluated using modified Poisson regression. RESULTS: 98.9% (281 of 284) of study participants had complete data and were included in the analysis. The proportion of participants obtaining the 1st, 2nd, and 3rd doses of HBV vaccine was 11.7% (95% Confidence Interval [95% CI] 8.0-15.5%), 10.7% (95%CI 7.1-14.3%), and 8.9% (95%CI 5.6-12.2%), respectively. On the other hand, participants were more likely to initiate the 1st dose if they had adequate knowledge of transmission (adjusted relative risk [aRR] = 2.58, 95% CI 1.12-5.92), adequate knowledge of severity (aRR = 6.75, 95%CI 3.38-13.48), and annual health-checking seeking behavior (aRR = 2.04, 95%CI 1.07-3.87). CONCLUSION: We documented a low HBV vaccination uptake despite incentivization. However, increased vaccine initiation was associated with better HBV knowledge and annual health check-up adherence. When considering expanding HBV vaccination to the general adult population, we should appreciate that HBV knowledge is an independent predictor of vaccine uptake.

A prediction model of abnormal acid reflux in gastroesophageal reflux disease.

BACKGROUND AND AIM: The measurement of esophageal acid exposure time (AET) using combined multichannel intraluminal impedance-pH (MII-pH) tests is the gold standard for diagnosing gastroesophageal reflux disease (GERD). However, this catheter-based 24-h test can cause considerable patient discomfort. Our aim is to identify factors affecting AET and to develop a scoring model for predicting AET abnormalities before conducting the MII-pH test. METHODS: Of the 366 patients who underwent MII-pH test at two facilities in Japan and Vietnam, 255 patients who also had esophagogastroduodenoscopy and high-resolution manometry were included in this study. Logistic regression analysis was conducted using risk factors for AET > 6% identified from a derivation cohort (n = 109). A scoring system predicting AET > 6% was then constructed and externally validated with a separate cohort (n = 146). RESULTS: Three variables were derived from the prediction model: male gender, Hill grades III-IV, and weak mean distal contractile integrals. Based on these scores, patients were classified into low (0 point), intermediate (1-3 points), and high (4 points) risk groups. The probabilities of having an AET > 6% were 6%, 34%, and 100% for these groups, respectively. A score of < 1 excluded patients with abnormal AET, with a negative predictive value of 93.8% in the derivation cohort and 80.0% in the validation cohort. CONCLUSIONS: We derived and externally validated a prediction model for abnormal AET. This system could assist in guiding the appropriate treatment strategies for GERD.

Development and validation of algorithms for identifying lines of therapy in multiple myeloma using real-world data.

Aim: To validate algorithms based on electronic health data to identify composition of lines of therapy (LOT) in multiple myeloma (MM). Materials & methods: This study used available electronic health data for selected adults within Henry Ford Health (Michigan, USA) newly diagnosed with MM in 2006-2017. Algorithm performance in this population was verified via chart review. As with prior oncology studies, good performance was defined as positive predictive value (PPV) ≥75%. Results: Accuracy for identifying LOT1 (N = 133) was 85.0%. For the most frequent regimens, accuracy was 92.5-97.7%, PPV 80.6-93.8%, sensitivity 88.2-89.3% and specificity 94.3-99.1%. Algorithm performance decreased in subsequent LOTs, with decreasing sample sizes. Only 19.5% of patients received maintenance therapy during LOT1. Accuracy for identifying maintenance therapy was 85.7%; PPV for the most common maintenance therapy was 73.3%. Conclusion: Algorithms performed well in identifying LOT1 - especially more commonly used regimens - and slightly less well in identifying maintenance therapy therein.

Electronic health data helps us understand treatment in the 'real world'. The data has great value in cancer if we can identify the drugs patients get. Yet this is hard in multiple myeloma (MM), where treatment is complex. Algorithms (set of decision rules) to identify drugs can help here. We tested an existing algorithm for identifying 'lines of therapy' (LOT) given to patients with MM. Each LOT included one or more drugs for MM. We also developed and tested a new algorithm for 'maintenance therapy'. This is a treatment given to help maintain the response to the main MM treatment. We tested how well the algorithms identified MM treatments in electronic health data. This data came from Henry Ford Health, a healthcare system in Michigan, USA. Treatments were confirmed by cancer specialists who reviewed medical charts. The LOT algorithm was good at finding the first LOT patients. The maintenance algorithm did a fair job of identifying the most used therapy. Our algorithms could help researchers study the real-world treatment of MM.

Experience of Autologous Immunotherapy for Non-Small Cell Lung Cancer Using Zoledronate-Actived Gammadelta T Cells.

BACKGROUND: Several nations around the world have utilized autologous immune enhancement therapy in the treatment of cancer, with initial positive outcomes. This study describes our experience with autologous gamma delta T cell immunotherapy for the treatment of non-small cell lung cancer patients in Vietnam, a developing nation. METHODS: Five patients with non-small cell lung cancer at stages III - IV were enrolled in the study. Each patient received six infusions of autologous γδT cells, separated by two weeks. Before, during, at the end of treatment, and three and six months after treatment, a comprehensive evaluation of clinical, laboratory, quality of life, and adverse events related to the method was conducted. RESULTS: At the time of culture seeding, the total number of cells ranged from 2.9 to 18.2 x 106, with γδT cells ranging in number from 10.7 to 19.6 x 104. On day 14 of the culture, the number of γδT cells ranged from 3.1 to 8.3 x 108. Regarding the safety of therapy in a total of 30 infusions, two (fever), one (myalgia), and one (joint pain) were graded as 1 by CTCAE criteria. After the course, no toxicity was observed in the hematopoietic system, kidney function, or liver function. Evaluation of the patient's response in accordance with the RECIST 1.1 criteria: 20% of patients (one patient) had partial response disease, and 80% of patients (four patients) had stable disease at the end of treatment. During the follow-up period of the study, three patients were still alive, and the disease remained stable. The patient's quality of life improved after treatment in most functional measures (activity, cognitive, and social), but physical and emotional scores decreased slightly. Two patients' fatigue symptoms increased, but after six months of treatment, the average value dropped from 25.3 to 8.3. Dyspnea symptoms decreased gradually from 33.3 at the start of treatment to 8.3 six months later. CONCLUSIONS: The initial results we obtained regarding the efficacy and safety of autologous γδT cell immunotherapy for patients with non-small cell lung cancer are extremely encouraging and comparable to those of previous studies.

[Kids Lung Registry and Child-EU Project - Progress in Rare and Interstitial Lung Diseases in Childhood Through Collaboration]. / Kinderlungenregister (chILD-EU) ­ Zusammenarbeit führt zu Fortschritten bei den seltenen und interstitiellen Lungenerkrankungen.

BACKGROUND: Progress in rare and interstitial lung disease in childhood can most usefully be achieved through systematic, registry-based collection. QUESTION AND METHODS: What are the practicalities and benefits of participating in the pediatric lung registry/chILD-EU project? We report our clinical experiences. RESULTS: Pediatricians and pediatric pulmonologists identify children with rare lung diseases. These are reported to the Kid's Lung Register after parental consent. Clinical data, imaging, and blood are sent to the registry. Genetic analysis can be arranged if desired. With completeness of the data, a peer-review process by pediatric radiology, possibly lung pathology, clinical and possibly genetic experts takes place in an interdisciplinary conference. A working diagnosis is established and communicated to the responsible physician via the registry and, if necessary, further discussed in case-related discussions. Assistance in entering the data is provided by the registry. Follow-ups are performed annually, and all registered physicians are invited to regular, web-based case discussions. Significant questions are answered in scientific projects and jointly published (>110 publications to date). CONCLUSIONS: Due to voluntary additional work of all participants beyond clinical routine, more than 1000 children with rare lung diseases have been included in the registry with biobank to date. A deeper understanding of the clinical courses of large cohorts of rare diseases and the initial description of new entities contributes to better care for these children.

Effectiveness of a Smartphone-Based Stress Management Program for Depression in Hospital Nurses During COVID-19 in Vietnam and Thailand: 2-Arm Parallel-Group Randomized Controlled Trial.

BACKGROUND: During the COVID-19 pandemic, health care professionals experienced high levels of depression. However, extant research has not highlighted effective internet-based psychological interventions to improve the mental health in this population during the pandemic. It remains unclear whether self-guided, internet-based cognitive behavioral therapy (iCBT) programs are effective in improving the mental health of health care workers during the COVID-19 pandemic. OBJECTIVE: The aim of this study was to evaluate the effectiveness of a smartphone-based iCBT stress management program for reducing the depression experienced by nurses in Vietnam and Thailand. METHODS: From March to April 2022, a 2-arm, parallel-group randomized controlled trial was implemented. One arm offered a 7-week self-guided iCBT program, and the other offered treatment as usual as a control arm. Full-time nurses were recruited from 6 hospitals: 2 hospitals in Vietnam and 4 hospitals in Thailand. The primary outcome of this program was the severity of depression measured by the Depression Anxiety Stress Scale-21 items. Follow-up surveys were conducted to measure the change in depression severity at 3 months (July-August 2022) and at 6 months (October-November 2022) after baseline. Mixed modeling for repeated measures was used to test the effects of the intervention compared with the control for the follow-up. RESULTS: A total of 1203 nurses were included in this study: 602 in the intervention group and 601 in the control group. The follow-up rate at 3 and 6 months ranged from 85.7% (515/601) to 87.5% (527/602). The completion rate for the program was 68.1% (410/602). The group difference in depression was significant at the 3-month follow-up (coefficient=-0.92, 95% CI -1.66 to -0.18; P=.02) and nonsignificant at the 6-month follow-up (coefficient=-0.33, 95% CI -1.11 to 0.45; P=.41). The estimated effect sizes were -0.15 and -0.06 at the 3- and 6-month follow-ups, respectively. CONCLUSIONS: Our study shows that the smartphone-based iCBT program was effective in reducing depression at the 3-month follow-up among hospital nurses in Vietnam and Thailand during the COVID-19 pandemic. However, the effect size was small, and therefore, these results may not be clinically meaningful. TRIAL REGISTRATION: UMIN Clinical Trials Registry UMIN000044145; https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000050128. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.20944/preprints202303.0450.v1.

The influence of attributes on community preferences regarding antibiotic treatment: evidence from a discrete choice model.

Antibiotic resistance (AR) rates in Vietnam are among the highest in Asia, and recent infections due to multi-drug resistance in the country have caused thousands of deaths each year. This study investigated a Vietnamese community's preferences for antibiotic treatment and its knowledge and attitudes regarding antibiotics. A discrete choice experiment-based survey was developed and administered to the population of interest. The respondents were given sociodemographic-, knowledge- and attitude-related items and 17 pairs of choice tasks. Two hypothetical options were included in each choice task. Latent class analysis was conducted to determine the differences among the respondents' preferences. Among 1,014 respondents, 805 (79.4%) gave valid questionnaires. A three-latent-class model with four covariates (age, healthcare-related education or career, occupation, and attitude classifications) was used in the analysis. All five attributes significantly influenced the respondents' decisions. The majority, including young employed respondents with non-healthcare-related work or education, found treatment failure more important. Older respondents who had healthcare-related education/careers and/or appropriate antibiotic use- and antibiotics resistance-related attitudes, regarded contribution to antibiotic resistance as an important attribute in selecting antibiotic treatments. Unemployed individuals with correct knowledge identified the cost of antibiotic treatment as the most essential decision-making factor. Findings suggest minimal antibiotic impact on resistance; only 7.83% view it as amajor concern. The respondents exhibited substantial preference heterogeneity, and the general Vietnamese public had poor knowledge of and attitudes toward antibiotic use and antibiotic resistance. This study emphasizes the need for individual responsibility for antibiotic resistance and appropriate antibiotic use.