bluuebunny/crossref_metadata_2025 huggingface dataset:
A time-motion study of community health workers delivering community-based primary health care in Neno District, Malawi
Authors: Aron Moses Banda , Ndambo Myness Kasanda , Munyaneza Fabien , Mulwafu Manuel , Makungwa Henry , Nhlema Basimenye , Connolly Emilia
Published: June 2023

Introduction

Community health workers (CHWs) are vital resources in delivering community-based primary health care, especially in low-and-middle-income countries (LMIC). However, few studies have investigated detailed time and task assessments of CHW's work. We conducted a time-motion study to evaluate CHWs' time on health conditions and specific tasks in Neno District, Malawi.

Methods

We conducted a descriptive quantitative study utilizing a time observation tracker to capture time spent by CHWs on focused health conditions and tasks performed during household visits. We observed 64 CHWs between 29 June and 20 August 2020. We computed counts and median to describe CHW distribution, visit type, and time spent per health condition and task. We utilized Mood’s median test to compare the median time spent at a household during monthly visits with the program design standard time. We used pairwise median test to test differences in median time duration for health conditions and assigned tasks.

Results

We observed 660 CHW visits from 64 CHWs, with 95.2% (n = 628) of the visits as monthly household visits. The median time for a monthly household visit was 34 min, statistically less than the program design time of 60 min (p < 0.001). While the CHW program focused on eight disease areas, pretesting with the observation tool showed that CHWs were engaged in additional health areas like COVID-19. Of the 3043 health area touches by CHWs observed, COVID-19, tuberculosis, and non-communicable diseases (NCDs) had the highest touches (19.3%, 17.6%, and 16.6%, respectively). The median time spent on sexually transmitted infections (STIs) and NCDs was statistically higher than in other health areas (p < 0.05). Of 3813 tasks completed by CHWs, 1640 (43%) were on health education and promotion. A significant difference was observed in the median time spent on health education, promotion, and screening compared to other tasks (p < 0.05).

Conclusion

This study demonstrates that CHWs spend the most time on health education, promotion, and screening per programmatic objectives but, overall, less time than program design. CHWs deliver care for a broader range of health conditions than the programmatic design indicates. Future studies should examine associations between time spent and quality of care delivery.
Ambient RNAs removal of cortex-specific snRNA-seq reveals Apoe+ microglia/macrophage after deeper cerebral hypoperfusion in mice
Authors: Zhang Yuan , Tan Jinyun , Yang Kai , Fan Weijian , Yu Bo , Shi Weihao
Published: June 2023

Background

Ambient RNAs contamination in single-nuclei RNA sequencing (snRNA-seq) is a challenging problem, but the consequences of ambient RNAs contamination of damaged and/or diseased tissues are poorly understood. Cognitive impairments and white/gray matter injuries are characteristic of deeper cerebral hypoperfusion mouse models induced by bilateral carotid artery stenosis (BCAS), but the molecular mechanisms still need to be further explored. More importantly, the BCAS mice can also offer an excellent model to examine the signatures of ambient RNAs contamination in damaged tissues when performing snRNA-seq.

Methods

After the sham and BCAS mice were established, cortex-specific single-nuclei libraries were constructed. Single-nuclei transcriptomes were described informatically by the R package Seurat, and ambient RNA markers of were identified in each library. Then, after removing ambient RNAs in each sample using the in silico approaches, the combination of CellBender and subcluster cleaning, single-nuclei transcriptomes were reconstructed. Next, the comparison of ambient RNA contamination was performed using irGSEA analysis before and after the in silico approaches. Finally, further bioinformatic analyses were performed.

Results

The ambient RNAs are more predominant in the BCAS group than the sham group. The contamination mainly originated from damaged neuronal nuclei, but could be reduced largely using the in silico approaches. The integrative analysis of cortex-specific snRNA-seq data and the published bulk transcriptome revealed that microglia and other immune cells were the primary effectors. In the sequential microglia/immune subgroups analysis, the subgroup of Apoe+ MG/Mac (microglia/macrophages) was identified. Interestingly, this subgroup mainly participated in the pathways of lipid metabolism, associated with the phagocytosis of cell debris.

Conclusions

Taken together, our current study unravels the features of ambient RNAs in snRNA-seq datasets under diseased conditions, and the in silico approaches can effectively eliminate the incorrected cell annotation and following misleading analysis. In the future, snRNA-seq data analysis should be carefully revisited, and ambient RNAs removal needs to be taken into consideration, especially for those diseased tissues. To our best knowledge, our study also offers the first cortex-specific snRNA-seq data of deeper cerebral hypoperfusion, which provides with novel therapeutic targets.
Preoperative chemoradiation-induced hematological toxicity and related vertebral dosimetry evaluations in patients with locally advanced gastric cancer: data from a phase III clinical trial
Authors: Wang Ji-jin , Shao Han , Zhang Li , Jing Ming , Xu Wen-jing , Sun Heng-wen , Zhou Zhi-wei , Zhang Yu-jing
Published: June 2023

Background

To explore the hematological toxicity (HT) induced by neoadjuvant chemoradiotherapy (nCRT) compared with neoadjuvant chemotherapy (nCT) and to identify the appropriate vertebral body (VB) dosimetric parameters for predicting HT in patients with locally advanced gastric cancer (GC).

Methods

In the phase III study, 302 patients with GC from an ongoing multi-center randomized clinical trial (NCT 01815853) were included. Patients from two major centers were grouped into training and external validation cohorts. The nCT group received three cycles of XELOX chemotherapy, while the nCRT received the same dose-reduced chemotherapy plus 45 Gy radiotherapy. The complete blood counts at baseline, during neoadjuvant treatment, and in the preoperative period were compared between the nCT and nCRT groups. The VB was retrospectively contoured and the dose-volume parameters were extracted in the nCRT group. Patients’ clinical characteristics, VB dosimetric parameters, and HTs were statistically analyzed. Instances of HT were graded according to the Common Terminology Criteria for Adverse Events v5.0 (CTCAE v5.0). The receiver operating characteristic (ROC) curves were generated to identify the optimal cut-off points for dosimetric variables and verify the prediction efficiency of the dosimetric index in both training and external validation cohorts.

Results

In the training cohort, 27.4% Grade 3 + HTs were noted in the nCRT group and 16.2% in the nCT group (P = 0.042). A similar result was exhibited in the validation cohort, with 35.0% Grade 3 + HTs in the nCRT group and 13.2% in the nCT group (P = 0.025). The multivariate analysis of the training cohort revealed that V5 was associated with Grade 3 + leukopenia (P = 0.000), Grade 3 + thrombocytopenia (P = 0.001), and Grade 3 + total HTs (P = 0.042). The Spearman correlation analysis identified a significant correlation of V5 with the white blood cell nadir (P = 0.0001) and platelet nadir (P = 0.0002). The ROC curve identified the optimal cut-off points for V5 and showed that V5 < 88.75% could indicate a decreased risk of Grade 3 + leukopenia, thrombocytopenia, and total HTs in the training as well as the external validation cohorts.

Conclusions

Compared with nCT, nCRT could increase the risk of Grade 3 + HT in patients with locally advanced GC. Dose constraints of V5 < 88.75% in irradiated VB could reduce the incidence of Grade 3 + HT.
Rewiring innate and adaptive immunity with TLR9 agonist to treat osteosarcoma
Authors: Cascini Caterina , Ratti Chiara , Botti Laura , Parma Beatrice , Cancila Valeria , Salvaggio Adriana , Meazza Cristina , Tripodo Claudio , Colombo Mario P. , Chiodoni Claudia
Published: June 2023

Background

Osteosarcoma (OS) is the most common primary bone tumor in children and adolescent. Surgery and multidrug chemotherapy are the standard of treatment achieving 60–70% of event-free survival for localized disease at diagnosis. However, for metastatic disease, the prognosis is dismal. Exploiting immune system activation in the setting of such unfavorable mesenchymal tumors represents a new therapeutic challenge.

Methods

In immune competent OS mouse models bearing two contralateral lesions, we tested the efficacy of intralesional administration of a TLR9 agonist against the treated and not treated contralateral lesion evaluating abscopal effect. Multiparametric flow cytometry was used to evaluate changes of the tumor immune microenviroment. Experiments in immune-deficient mice allowed the investigation of the role of adaptive T cells in TLR9 agonist effects, while T cell receptor sequencing was used to assess the expansion of specific T cell clones.

Results

TLR9 agonist strongly impaired the growth of locally-treated tumors and its therapeutic effect also extended to the contralateral, untreated lesion. Multiparametric flow cytometry showed conspicuous changes in the immune landscape of the OS immune microenvironment upon TLR9 engagement, involving a reduction in M2-like macrophages, paralleled by increased infiltration of dendritic cells and activated CD8 T cells in both lesions. Remarkably, CD8 T cells were needed for the induction of the abscopal effect, whereas they were not strictly necessary for halting the growth of the treated lesion. T cell receptor (TCR) sequencing of tumor infiltrating CD8 T cells showed the expansion of specific TCR clones in the treated tumors and, remarkably, their selected representation in the contralateral untreated lesions, providing the first evidence of the rewiring of tumor-associated T cell clonal architectures.

Conclusions

Overall these data indicate that the TLR9 agonist acts as an in situ anti-tumor vaccine, activating an innate immune response sufficient to suppress local tumor growth while inducing a systemic adaptive immunity with selective expansion of CD8 T cell clones, which are needed for the abscopal effect.

Graphical Abstract
Allogenic mesenchymal stromal cells and their extracellular vesicles in COVID-19 induced ARDS: a randomized controlled trial
Authors: Zarrabi Morteza , Shahrbaf Mohammad Amin , Nouri Masoumeh , Shekari Faezeh , Hosseini Seyedeh-Esmat , Hashemian Seyed-Mohammad Reza , Aliannejad Rasoul , Jamaati Hamidreza , Khavandgar Naghmeh , Alemi Hediyeh , Madani Hoda , Nazari Abdoreza , Amini Azadeh , Hassani Seyedeh Nafiseh , Abbasi Fatemeh , Jarooghi Neda , Fallah Nasrin , Taghiyar Leila , Ganjibakhsh Meysam , Hajizadeh-Saffar Ensiyeh , Vosough Massoud , Baharvand Hossein
Published: June 2023

Background and aims

The main causes of death in patients with severe Coronavirus disease-2019 (COVID-19) are acute respiratory distress syndrome (ARDS) and multiorgan failure caused by a severe inflammatory cascade. Novel treatment strategies, such as stem-cell-based therapy and their derivatives can be used to relieve inflammation in these cases. In this study, we aimed to evaluate the safety and efficacy of therapy using mesenchymal stromal cells (MSCs) and their derived extracellular vesicles in COVID-19 patients.

Materials and methods

COVID-19 patients with ARDS were included in this study and allocated into two study and control groups using block randomization. While all patients received recommended treatment based on guidelines from the national advisory committee for COVID-19 pandemic, the two intervention groups received two consecutive injections of MSCs (100 × 106cells) or one dose of MSCs (100 × 106cells) followed by one dose of MSC-derived extracellular vesicles (EVs). Patients were assessed for safety and efficacy by evaluating clinical symptoms, laboratory parameters, and inflammatory markers at baseline and 48 h after the second intervention.

Results

A total number of 43 patients (the MSC alone group = 11, MSC plus EV group = 8, and control group = 24) were included in the final analysis. Mortality was reported in three patients in the MSC alone group (RR: 0.49; 95% CI 0.14–1.11;P = 0.08); zero patient in the MSC plus EV group (RR: 0.08; 95% CI 0.005–1.26;P = 0.07) and eight patients in the control group. MSC infusion was associated with a decrease in inflammatory cytokines such as IL-6 (P = 0.015), TNF-α (P = 0.034), IFN-γ (P = 0.024), and CRP (P = 0.041).

Conclusion

MSCs and their extracellular vesicles can significantly reduce the serum levels of inflammatory markers in COVID-19 patients, with no serious adverse events.

Trial registrationIRCT, IRCT registration number: IRCT20200217046526N2. Registered 13th April 2020,http://www.irct.ir/trial/47073.
The microbiota of pregnant women with SARS-CoV-2 and their infants
Authors: Leftwich Heidi K. , Vargas-Robles Daniela , Rojas-Correa Mayra , Yap Yan Rou , Bhattarai Shakti , Ward Doyle V. , Fujimori Gavin , Forconi Catherine S. , Yeboah Tracy , Carter Acara , Kastrinakis Alyssa , Asirwatham Alison M. , Bucci Vanni , Moormann Ann M. , Maldonado-Contreras Ana
Published: June 2023

Background

Infants receive their first bacteria from their birthing parent. This newly acquired microbiome plays a pivotal role in developing a robust immune system, the cornerstone of long-term health.

Results

We demonstrated that the gut, vaginal, and oral microbial diversity of pregnant women with SARS-CoV-2 infection is reduced, and women with early infections exhibit a different vaginal microbiota composition at the time of delivery compared to their healthy control counterparts. Accordingly, a low relative abundance of twoStreptococcussequence variants (SV) was predictive of infants born to pregnant women with SARS-CoV-2 infection.

Conclusions

Our data suggest that SARS-CoV-2 infections during pregnancy, particularly early infections, are associated with lasting changes in the microbiome of pregnant women, compromising the initial microbial seed of their infant. Our results highlight the importance of further exploring the impact of SARS-CoV-2 on the infant’s microbiome-dependent immune programming.
Properties of multi-GNSS uncalibrated phase delays with considering satellite systems, receiver types, and network scales
Authors: Zeng Ping , Zhang Zhetao , Wen Yuanlan , He Xiufeng , He Lina , Li Muzi , Chen Wu
Published: June 2023

The Wide-Lane (WL) and Narrow-Lane (NL) Uncalibrated Phase Delays (UPDs) are the prerequisites in the traditional Precise Point Positioning (PPP) Ambiguity Resolution (AR). As the generation mechanism of various biases becomes more complex, we systematically studied the impact factors of four satellite systems WL and NL UPDs from the perspective of parameter estimation. Approximately 100 stations in a global network are used to generate the UPDs. The results of different satellite systems show that the estimation method, update frequency, and solution mode need to be treated differently. Two regional networks with different receiver types, JAVAD, and Trimble, are also adopted. The results indicate that the receiver-dependent bias has an influence on UPD estimation. Also, the hardware delays can inhibit the satellite-side UPDs if these receiver-specific errors are not fully deployed or even misused. Furthermore, the temporal stability and residual distribution of NL UPDs are significantly enhanced by utilizing a regional network, with the improvements by over 68% and 40%, respectively. It demonstrates that different network scales exhibit the different implication of unmodeled errors, and the unmodeled errors cannot be ignored and must be handled in UPD estimation.
Using the Precision Lasso for gene selection in diffuse large B cell lymphoma cancer
Authors: Pourhamidi Rashed , Moslemi Azam
Published: June 2023

Background

Gene selection from gene expression profiles is the appropriate tool for diagnosing and predicting cancers. The aim of this study is to perform a Precision Lasso regression model on gene expression of diffuse large B cell lymphoma patients and to find marker genes related to DLBCL.

Methods

In the present case–control study, the dataset included 180 gene expressions from 14 healthy individuals and 17 DLBCL patients. The marker genes were selected by fitting Ridge, Lasso, Elastic Net, and Precision Lasso regression models.

Results

Based on our findings, the Precision Lasso, the Ridge, the Elastic Net, and the Lasso models choose the most marker genes, respectively. In addition, the top 20 genes are based on models compared with the results of clinical studies. The Precision Lasso and the Ridge models selected the most common genes with the clinical results, respectively.

Conclusions

The performance of the Precision Lasso model in selecting related genes could be considered more acceptable rather than other models.
Flexural behaviour of recycled reinforced concrete beams strengthened/ repaired with CFRP laminates
Authors: Hemida Ola Adel Ramadan , Abdalla Hany Ahmed , Fouad Hala Emad Elden
Published: June 2023

This research deals with the flexural performance of reinforced concrete beams which contain Recycled Concrete Aggregates (RCA) and were strengthened by Carbon Fiber Reinforced Polymers (CFRP). For this purpose, seven Reinforced Concrete (RC) beams were manufactured using RCA as a replacement of Normal Coarse aggregates (NCA) with percentages of (0%, 25%, 50%, and 100%). The cross-section of all beams was 150 × 300 mm and 2100 mm overall length and with loaded span of 1800 mm. Firstly four beams (group A) with different RCA ratios were loaded in a four-point loading configuration until failure. Secondly three beams (group B) were loaded to 30% of its ultimate load after that group B beams were strengthened using CFRP laminates on the lower face of the beams to be strengthened to resist flexural stress. Crack pattern, initial cracking load, ultimate load, mid-span deflection, and strain in main reinforcement were monitored. The results show that increasing RCA ratios generally leads to decreasing in the ultimate loads, for RCA ratios of 25%, 50% and 100% the decrease in beams ultimate load was with ratios 4.8%, 25.5% and 26.8%, respectively compared to control beam (0% RCA). The preloaded beams that were repaired with CFRP laminates have higher ultimate loads than beams without CFRP laminates and lower mid span deflection at maximum load (for instance repaired beam with 50% RCA ratio with CFRP laminate has shown higher ultimate load with 56.6% and less deflection with 36.9% compared to its corresponding unstrengthen beam).
Forge ahead in acquisition and model building via full-waveform inversion: Gulf of Mexico case study
Authors: Vigh Denes , Cheng Xin , Xu James , Jiao Kun
Published: June 2023

Full-waveform inversion (FWI) has proven itself an essential tool for velocity model building using seismic data. In recent years, the geophysical community has made substantial progress in developing FWI to overcome some long-standing limitations, such as handling cycle skipping, better using reflection energy, including more physics in the inversion algorithms, and increasing inverted frequencies to achieve higher resolution. FWI does not only target the larger and midscale model updates, more and more FWI examples were presented with increased resolution which allows for extraction of FWI derived reflectivity. Interrogating the FWI kernel with given geology and acquisition geometry can provide critical information on how the acquisition design should be optimized to provide FWI a better opportunity to update the velocity model at target depth, especially in the deep part of the model. When the acquisition geometry is different in terms of offsets, azimuthal coverage, and the minimum frequency in the recording, it can be analyzed to design workflows to enable FWI to optimally update the model parameters. Obviously, recent ocean-bottom node acquisitions that record long offsets, full azimuth, and low frequencies have made FWI shine in the seismic industry. Modifying and reshaping a complex salt geometry is one of the ultimate goals of FWI. In addition to the salt boundary being an issue, there is a potential cycle-skipping problem associated with uncertainties of large salt bodies missing or misplaced even though the frequencies used to start FWI are becoming lower due to the advancement in seismic acquisition and FWI algorithms. Furthermore, if the FWI-predicted data are simulated with an acoustic engine, it could pose amplitude and phase discrepancies at high-velocity contrast interfaces. Elastic FWI alone has been proposed as a means of overcoming these challenges associated with salt and regions with high-velocity contrast. We determine the FWI progress of the past few decades with the latest examples from different acquisition geometries.
SLKNet: An attention-based deep-learning framework for downhole distributed acoustic sensing data denoising
Authors: Yang Liuqing , Fomel Sergey , Wang Shoudong , Chen Xiaohong , Chen Yunfeng , Chen Yangkang
Published: June 2023

Distributed acoustic sensing (DAS) is a novel and fast-developing seismic acquisition technology, which enjoys many advantages compared with traditional geophones. However, DAS data often suffer from severe and diverse types of noise with varying amplitudes, resulting in a low signal-to-noise ratio (S/N) and making the extraction of hidden signals a challenging task. Therefore, exploring a high-efficiency and high-generalization denoising method is crucial for improving the S/N of DAS data and subsequent processing. We develop a dense connection network with the kernel-wise attention mechanism to denoise complex and diverse noise (e.g., high-amplitude erratic, high-frequency, random, and horizontal noise) on real DAS data sets. We use an integrated denoising framework that is suitable for attenuating DAS noise to generate labels for network training. Our network consists of five types of blocks, i.e., convolutional, dense, transition down, transition up, and selective kernel blocks (SKB). In particular, the SKB is used to fuse multiscale features by weighting, thereby improving denoising accuracy. The computational efficiency and denoising performance are further augmented by using a patching method to segment the DAS data and generate many small-scale patches. Our network is trained on a small DAS data set and tested on the synthetic and field data from vastly different geographic areas. The comparisons of our network with three state-of-the-art deep-learning-based benchmark models demonstrate more robust performance and superior signal extraction ability.
Novel Immunotherapeutics: Perspectives on Checkpoints, Bispecifics, and Vaccines in Development
Authors: Kreidieh Firas Y. , Tawbi Hussein A. , Alexaki Aikaterini , Borghaei Hossein , Kandalaft Lana E.
Published: June 2023

Over the past decade, the advent of molecular techniques and deeper understanding of the tumor microenvironment (TME) have enabled the development of a multitude of immunotherapy targets and approaches. Despite the revolutionary advancement in immunotherapy, treatment resistance remains a challenge leading to decreased response rate in a significant proportion of patients. As such, there has recently been an evolving focus to enhance efficacy, durability, and toxicity profiles of immunotherapy. Although immune checkpoint inhibitors have revolutionized cancer treatment with many already-approved antibodies and several others in the pipeline, bispecific antibodies build on their success in an attempt to deliver an even more potent immune response against tumor cells. On the other hand, vaccines comprise the oldest and most versatile form of immunotherapy. Peptide and nucleic acid vaccines are relatively simple to manufacture compared with oncolytic virus–based vaccines, whereas the dendritic cell vaccines are the most complex, requiring autologous cell culture. Nevertheless, a crucial question in the development of cancer vaccines is the choice of antigen whereby shared and patient-private antigen approaches are currently being pursued. There is hope that cancer vaccines will join the repertoire of successful novel immunotherapeutics in the market. Better insights into the impact of immunotherapy on effector T cells and other immune cell populations in the TME shall be a major priority across the immune-oncology discipline and can help identify predictive biomarkers to evaluate response to treatment and identify patients who would most likely benefit from immunotherapy.
Receptor-Based Pharmacophore Modelling of a series of ligands used as inhibitors of the SARS-CoV-2 virus by complementary theoretical approaches, molecular docking, and reactivity descriptors.
Authors: Morales-Bayuelo Alejandro , Sánchez-Márquez Jesús
Published: June 2023

Background: A coronavirus identified in 2019, SARS-CoV-2, has caused a pandemic of respiratory illness, called COVID-19. Most people with COVID-19 experience mild to moderate symptoms and recover without the need for special treatments. The SARS‑CoV‑2 RNA‑dependent RNA polymerase (RdRp) plays a crucial role in the viral life cycle. The active site of the RdRp is a very accessible region, so targeting this region to study the inhibition of viral replication may be an effective therapeutic approach. For this reason, this study has selected and analysed a series of ligands used as SARS-CoV-2 virus inhibitors, namely: the Zidovudine, Tromantadine, Pyramidine, Oseltamivir, Hydroxychoroquine, Cobicistat, Doravirine (Pifeltro), Dolutegravir, Boceprevir, Indinavir, Truvada, Trizivir, Trifluridine, Sofosbuvir  and Zalcitabine.

Methods: These ligands were analyzed using molecular docking, Receptor-Based Pharmacophore Modelling. On the other hand, these outcomes were supported with chemical reactivity indices defined within a conceptual density functional theory framework.

Results: The results show the conformations with the highest root-mean-square deviation (RMSD), have π-π stacking interaction with residue LEU141, GLN189, GLU166 and GLY143, HIE41, among others. Also was development an electrostatic potential comparison using the global and local reactivity indices.

Conclusions: These studies allow the identification of the main stabilizing interactions using the crystal structure of SARS‑CoV‑2 RNA‑dependent RNA polymerase. In this order of ideas, this study provides new insights into these ligands that can be used in the design of new COVID-19 treatments. The studies allowed us to find an explanation supported in the Density Functional Theory about the chemical reactivity and the stabilization in the active site of the ligands.
Predicting multi-vascular diseases in patients with coronary artery disease
Authors: Adiarto Suko , Nurachman Luthfian Aby , Dewangga Raditya , Indriani Suci , Taofan Taofan , Alkatiri Amir Aziz , Firman Doni , Santoso Anwar
Published: June 2023

Background: Because of its systemic nature, the occurrence of atherosclerosis in the coronary arteries can also indicate a risk for other vascular diseases.  However, screening program targeted for all patients with coronary artery disease (CAD) is highly ineffective and no studies have assessed the risk factors for developing multi-vascular diseases in general. This study constructed a predictive model and scoring system to enable targeted screening for multi-vascular diseases in CAD patients.

Methods: This cross-sectional study includes patients with CAD, as diagnosed during coronary angiography or percutaneous coronary intervention from March 2021 to December 2021. Coronary artery stenosis (CAS) and abdominal aortic aneurysm (AAA) were diagnosed using Doppler ultrasound while peripheral artery disease (PAD) was diagnosed based on ABI score. Multivariate logistic regression was conducted to construct the predictive model and risk scores. Validation was conducted using ROC analysis and Hosmer-Lemeshow test.

Results: Multivariate analysis showed that ages of >60 years (OR [95% CI] = 1.579 [1.153-2.164]), diabetes mellitus (OR = 1.412 [1.036-1.924]), cerebrovascular disease (OR = 3.656 [2.326-5.747]), and CAD3VD (OR = 1.960 [1.250-3.073]) increased the odds for multi-vascular disease. The model demonstrated good predictive capability (AUC = 0.659) and was well-calibrated (Hosmer-Lemeshow p = 0.379). Targeted screening for high-risk patients reduced the number needed to screen (NNS) from 6 in the general population to 3 and has a high specificity of 96.5%

Conclusions: Targeted screening using clinical risk scores was able to decrease NNS with good predictive capability and high specificity
Prognostic role of C-reactive protein-to-albumin ratio in acute pancreatitis: a systematic review and meta-analysis
Authors: Mariadi I Ketut , Somayana Gde , Shalim Christina Permata , Sindhughosa Dwijo Anargha , Daniella Dian , Purwanta Made Lady Adelaida
Published: June 2023

Background: Acute pancreatitis (AP) is a common disorder and although most of the cases are mild, the mortality risk is high when it comes to severe AP. It is therefore important to determine the severity of AP as early as possible. This review aimed to determine the prognostic value of C-reactive protein-to-albumin ratio (CRP/alb ratio) in patients with AP.

Methods: We performed a systematic search on the electronic databases PubMed, Cochrane Library, and Google Scholar up to January 2023. Studies reporting CRP/alb ratio on admission and its association with severity or mortality in AP patients were included. We calculated pooled mean difference (MD) and their 95% confidence intervals (CI) using a random-effects model. Quality assessment of the included studies was appraised using a Newcastle–Ottawa scale.

Results: A total of six studies comprising 2244 patients were included in this meta-analysis. Severe AP had higher CRP/alb ratio on admission than mild-moderate AP (pooled MD: 3.59; 95% CI: 2.51-4.68; p<0.00001). CRP/alb ratio was also significantly higher on non-survivor AP patients compared to survivor AP patients (pooled MD: 2.12; 95% CI: 0.43-3.8; p < 0.01).

Conclusion: High CRP/alb ratio can be used as an early predictor of poor prognosis in patients with AP.
Does food biodiversity protect against malnutrition and favour the resilience to climate change-related events in Amazon Indigenous communities? A protocol for a mixed methods study
Authors: Zavaleta-Cortijo Carol , Cade Janet , Ford James , Greenwood Darren C. , Carcamo Cesar , Silvera-Ccallo Rosa , Fernandez-Neyra Connie , Lancha-Rucoba Guillermo , Pizango-Tangoa Manuel , Pizango-Inuma Rogelia , Chanchari-Huiñapi Junior , Velez-Quevedo Jorge , Inuma-Tangoa Nerita , Antazu Teresita , Miranda-Cuadros Marianella , Aparco Juan Pablo , Aro-Guardia Pedro , Verastegui Manuela , Morales-Ancajima Valeria , Bressan Tiana , Miranda J. Jaime
Published: June 2023

Background: Undernutrition is projected to be a major consequence of climate change. Biodiversity could enhance climate change resilience by improving nutritional outcomes and providing healthy food resources during and/or after climate-related events. For Indigenous populations who currently base their diet on local biodiversity, rapid climate changes may affect their ability to produce, access or gather food and consequently impact their nutritional status. There is a knowledge gap regarding whether nutritional status among Indigenous populations is better among those who consume a diet with greater biodiversity than those who have a diet with low biodiversity.

Objective: This study aims to investigate the role of food biodiversity (FBD) in nutritional resilience to extreme flooding events of Shawi Amazon Indigenous adults living in Peruvian communities that have experienced extreme floods in the past five years.

Methods: This study will use a mixed-method sequential explanatory design. The quantitative component includes a cross-sectional survey to assess the association between food biodiversity (FBD) and the prevalence of anaemia in adults aged 15 to 60 years old (n=365). Anaemia will be evaluated using blood hemoglobin and serum ferritin. FBD will be measured with a food frequency questionnaire and a 24-hour dietary recall. Soil-transmitted helminth infections, malaria, and inflammatory biomarkers will also be evaluated. Qualitative component will include a community-based participatory approach to investigate the role of FBD in the responses to extreme floods. Male (n=14) and female (n=14) participants, previously identified in the quantitative phase with high and low levels of FBD, will be invited to participate in a Photovoice activity and semi-structured interviews. A analytical framework for climate change resilience will be used to integrate the data.

Discussion: Findings will be integrated to identify features of diet quality to suggest nutritional interventions that are resilient to changing climatic conditions in the Amazon and respect Indigenous views.
Association between fatty liver disease and hearing impairment in Korean adults: a retrospective cross-sectional study
Authors: Jung Da Jung
Published: June 2023

Background: We hypothesized that fatty liver disease (FLD) is associated with a high prevalence of hearing loss (HL) owing to metabolic disturbances. This study aimed to evaluate the association between FLD and HL in a large sample of the Korean population.Methods: We used a dataset of adults who underwent routine voluntary health checkups (n=21,316). Fatty liver index (FLI) was calculated using Bedogni’s equation. The patients were divided into two groups: the non-FLD (NFLD) group (n=18,518, FLI <60) and the FLD group (n=2,798, FLI ≥60). Hearing thresholds were measured using an automatic audiometer. The average hearing threshold (AHT) was calculated as the pure-tone average at four frequencies (0.5, 1, 2, and 3 kHz). HL was defined as an AHT of >40 dB.Results: HL was observed in 1,370 (7.4%) and 238 patients (8.5%) in the NFLD and FLD groups, respectively (p=0.041). Compared with the NFLD group, the odds ratio for HL in the FLD group was 1.16 (p=0.040) and 1.46 (p<0.001) in univariate and multivariate logistic regression analyses, respectively. Linear regression analyses revealed that FLI was positively associated with AHT in both univariate and multivariate analyses. Analyses using a propensity score-matched cohort showed trends similar to those using the total cohort.Conclusion: FLD and FLI were associated with poor hearing thresholds and HL. Therefore, active monitoring of hearing impairment in patients with FLD may be helpful for early diagnosis and treatment of HL in the general population.
Grounding drones in political ecology: understanding the complexities and power relations of drone use in conservation
Authors: Bersaglio Brock , Enns Charis , Goldman Mara , Lunstrum Libby , Millner Naomi
Published: June 2023

Rapidly evolving drone technologies are taking the conservation sector by storm. Although the technical and applied conservation literature tends to frame drones as autonomous, neutral technologies, we argue that neither drones nor their implications can be adequately understood unless they are grounded, conceptually and methodologically, in the context of broader societal structures that shape how drones and the data they produce are used. This article introduces the value of a political ecology framework to an interdisciplinary audience of biophysical and social scientists interested in the multiple possibilities and complications associated with conservation drones. Political ecology provides the tools for studying and critically engaging with drone use in conversation in ways that are politically engaged and attuned to power relations – historic and present, local and global – in a more-than-human world. In making this argument, we point to four conceptual tools in political ecology that offer a framework for unveiling the power relations and structures that surround drones in different contexts: political economy, territoriality, knowledge and expertise, and more-than-human relations. Using empirics from our work across Latin America (Colombia and Guatemala), Africa (Kenya, Tanzania, South Africa and Mozambique), and North America (the US and Canada), we illustrate the salience of this framework and demonstrate why evaluating what drones do in and for conservation requires first understanding the complex set of power relations that shape their use.
Influence of NaCl concentration on the optical scattering properties of water-based aerosols
Authors: Pattyn Christian A. , Zenker Jake P. , Redman Brian J. , van der Laan John D. , Sanchez Andres L. , Westlake Karl , Patel Lekha , Bentz Brian Z. , Wright Jeremy B.
Published: June 2023

We present the characterization of several atmospheric aerosol analogs
in a tabletop chamber and an analysis of how the concentration of NaCl
present in these aerosols influences their bulk optical properties.
Atmospheric aerosols (e.g., fog and haze) degrade optical signal via
light–aerosol interactions causing scattering and absorption, which
can be described by Mie theory. This attenuation is a function of the
size distribution and number concentration of droplets in the light
path. These properties are influenced by ambient conditions and the
droplet’s composition, as described by Köhler theory. It is therefore
possible to tune the wavelength-dependent bulk optical properties of
an aerosol by controlling droplet composition. We present
experimentation wherein we generated multiple microphysically and
optically distinct atmospheric aerosol analogs using salt water
solutions with varying concentrations of NaCl. The results demonstrate
that changing the NaCl concentration has a clear and predictable
impact on the microphysical and optical properties of the aerosol.
Semi-supervised OCT lesion segmentation via transformation-consistent with uncertainty and self-deep supervision
Authors: Shen Hailan , Yang Qiao , Chen Zailiang , Ye Ziyu , Dai Peishan , Duan Xuanchu
Published: June 2023

Optical coherence tomography (OCT) is a non-invasive, high-resolution ocular imaging technique with important implications for the diagnosis and management of retinal diseases. Automatic segmentation of lesions in OCT images is critical for assessing disease progression and treatment outcomes. However, existing methods for lesion segmentation require numerous pixel-wise annotations, which are difficult and time-consuming to obtain. To address this challenge, we propose a novel framework for semi-supervised OCT lesion segmentation, termed transformation-consistent with uncertainty and self-deep supervision (TCUS). To address the issue of lesion area blurring in OCT images and unreliable predictions from the teacher network for unlabeled images, an uncertainty-guided transformation-consistent strategy is proposed. Transformation-consistent is used to enhance the unsupervised regularization effect. The student network gradually learns from meaningful and reliable targets by utilizing the uncertainty information from the teacher network, to alleviate the performance degradation caused by potential errors in the teacher network’s prediction results. Additionally, self-deep supervision is used to acquire multi-scale information from labeled and unlabeled OCT images, enabling accurate segmentation of lesions of various sizes and shapes. Self-deep supervision significantly improves the accuracy of lesion segmentation in terms of the Dice coefficient. Experimental results on two OCT datasets demonstrate that the proposed TCUS outperforms state-of-the-art semi-supervised segmentation methods.
Principle and strategy of using probabilistic shaping in a flexible coherent passive optical network without optical amplifiers
Authors: Xing Sizhe , Li Guoqiang , Yan An , Shen Wangwei , Li Zhongya , Wang Jiaye , Shi Jianyang , He Zhixue , Chi Nan , Zhang Junwen
Published: June 2023

The coherent passive optical network (CPON) has received a great deal of attention in recent years due to its superior receiver sensitivity and extended power budget for 100G and beyond. In order to fully utilize the channel capacity and achieve adaptive rate adjustment in a flexible coherent passive optical network (FLCS-CPON), constellation-shaping techniques, such as probabilistic shaping (PS), have been introduced. Unlike long-distance transmission networks, which are subject to average power constraint when optical amplifiers are utilized, commercial passive optical network systems are generally subject to peak power constraint, as no optical amplifiers are used. This difference makes the classical probabilistic-shaping (CPS) technology less efficient in CPON systems without optical amplifiers. In this study, the use cases of PS in a flexible coherent access network, including nonlinear-penalty-dominant and noise-dominated regions, are thoroughly explored. By fixing the modulation order and utilizing CPS and reversed probabilistic shaping with a fixed modulation format, a hybrid PS-based FLCS-CPON without optical amplifiers is demonstrated, achieving a peak rate of 200G and a high dynamic range boost of up to 72% from 16 to 27.5 dB in upstream burst-mode-based PS-16 quadrature amplitude modulation. Over the entire dynamic range, the net data rate varies from 168 to 85 Gbps with a power budget of 37 dB, and a dynamic range and net-rate product improvement of 55% is achieved.
Kerker-type positional disorder immune metasurfaces
Authors: Song Hao , Hong Binbin , Wang Neng , Ping Wang Guo
Published: June 2023

Metasurfaces that can operate without a strictly periodic arrangement of meta-atoms are highly desirable for practical optical micro-nano devices. In this paper, we propose two kinds of Kerker-type metasurfaces that exhibit immunity to positional disorder. These metasurfaces consist of two distinct core-shell cylinders that satisfy the first and second Kerker conditions, respectively. Despite significant positional disorder perturbations of the meta-atoms, the metasurfaces can maintain excellent performance comparable to periodic ones, including total transmission and magnetic mirror responses. This positional disorder immunity arises from the unidirectional forward or backward scattering of a single core-shell cylinder, which results in minimal lateral scattering coupling between neighboring cylinders, thereby having little impact on multiple scattering in either the forward or backward direction. In contrast, the response of positional disorder non-Kerker-type metasurfaces decreases significantly. Our findings present a new approach for designing robust metasurfaces and expanding the applications of metasurfaces in sensing and communications within complex practical scenarios.
Improved phase-locking of laser arrays by pump shaping
Authors: Gadasi Sagie , Bernstein Eran , Pando Amit , Friesem Asher , Davidson Nir
Published: June 2023

We introduce a method to enhance the phase-locking quality and duration of an end-pumped laser array by precisely shaping its pump beam to overlap with the array. Shaping the pump beam results in a significant improvement in lasing efficiency and reduces the pump power required to reach the lasing threshold compared to a typical uniform pumping configuration. Our approach involves shaping a highly incoherent laser beam by addressing smaller segments of the beam with higher local spatial coherence. We demonstrate a remarkable increase in the laser array output brightness by up to a factor of 10, accompanied by a substantial extension in the phase-locking duration.
Computational imaging and occluded objects perception method based on polarization camera array
Authors: Pu Xiankun , Wang Xin , Shi Lei , Ma Yiming , Wei Chongfeng , Gao Xinjian , Gao Jun
Published: June 2023

Traditional optical imaging relies on light intensity information from light reflected or transmitted by an object, while polarization imaging utilizes polarization information of light. Camera array imaging is a potent computational imaging technique that enables computational imaging at any depth. However, conventional imaging methods mainly focus on removing occlusions in the foreground and targeting, with limited attention to imaging and analyzing polarization characteristics at specific depths. Conventional camera arrays cannot be used for polarization layered computational imaging. Thus, to study polarization layered imaging at various depths, we devised a flexible polarization camera array system and proposed a depth-parallax relationship model to achieve computational imaging of polarization arrays and polarization information reconstruction under varying conditions and depths. A series of experiments were conducted under diverse occlusion environments. We analyzed the distinctive characteristics of the imaging results obtained from the polarization array, employing a range of array distribution methods, materials, occlusion density, and depths. Our research successfully achieved computational imaging that incorporates a layered perception of objects. Finally, we evaluated the object region’s polarization information using the gray level co-occurrence matrix feature method.
Multievent localization for loop-based Sagnac sensing system using machine learning
Authors: Ali Jameel , Almaiman Ahmed , Ragheb Amr M. , Esmail Maged A. , Almohimmah Esam M. , Alshebeili Saleh A.
Published: June 2023

In optical sensing applications such as pipeline monitoring and intrusion detection systems, accurate localization of the event is crucial for timely and effective response. This paper experimentally demonstrates multievent localization for long perimeter monitoring using a Sagnac interferometer loop sensor and machine learning techniques. The proposed method considers the multievent localization problem as a multilabel multiclassification problem by dividing the optical fiber into 250 segments. A deep neural network (DNN) model is used to predict the likelihood of event occurrence in each segment and accurately locate the events. The sensing loop comprises 106.245 km of single-mode fiber, equivalent to ∼50 km of effective sensing distance. The training dataset is constructed in simulation using VPItransmissionMaker, and the proposed machine learning model’s complexity is reduced by using discrete cosine transform (DCT). The designed DNN is tested for event localization in both simulation and experiment. The simulation results show that the proposed model achieves an accuracy of 99% in predicting the location of one event within one segment error, an accuracy of 95% in predicting the location of one event out of the two within one segment error, and an accuracy of 78% in predicting the location of the two events within one segment error. The experimental results validate the simulation ones, demonstrating the proposed model’s effectiveness in accurately localizing events with high precision. In addition, the paper includes a discussion on extending the proposed model to sense more than two events simultaneously.
Tunable, coherent optical comb source via on-chip bidirectional coupling
Authors: McCarthy John , O’Sullivan Diarmuid , Shayesteh Maryam , Dernaika Mohamad , Peters Frank H. , Kelleher Bryan
Published: June 2023

A tunable comb source is demonstrated through gain switching on a three-sectioned photonic integrated circuit (PIC). The PIC consists of two mutually coupled lasers connected by a passive waveguide. One of these is a tunable, two-section, single mode laser. The second laser is a simple Fabry–Perot cavity laser which can be phase-locked with the single mode laser via bidirectional coupling. Frequency combs are produced by gain switching the Fabry–Perot laser by applying a high-power radio frequency signal. Combs are generated with line spacings ranging from 3.5 to 8 GHz. The on-chip bidirectional coupling causes the comb to also be generated in the two-section device. Despite the lack of on-chip optical isolation between the lasers, the resulting combs are stable. Numerical simulations using a delay-differential model reproduce the results and reveal the important role played by the short delay times inherent to on-chip integration in this stability.