Tag: pubmed

Proc Natl Acad Sci U S A. 2023 Dec 19;120(51):e2309034120. doi: 10.1073/pnas.2309034120. Epub 2023 Dec 11.

ABSTRACT

There is an urgent need for reliable data on the impacts of deforestation on tropical biodiversity. The city-state of Singapore has one of the most detailed biodiversity records in the tropics, dating back to the turn of the 19th century. In 1819, Singapore was almost entirely covered in primary forest, but this has since been largely cleared. We compiled more than 200 y of records for 10 major taxonomic groups in Singapore (>50,000 individual records; >3,000 species), and we estimated extinction rates using recently developed and novel statistical models that account for “dark extinctions,” i.e., extinctions of undiscovered species. The estimated overall extinction rate was 37% (95% CI [31 to 42%]). Extrapolating our Singapore observations to a future business-as-usual deforestation scenario for Southeast Asia suggests that 18% (95% CI [16 to 22%]) of species will be lost regionally by 2100. Our extinction estimates for Singapore and Southeast Asia are a factor of two lower than previous estimates that also attempted to account for dark extinctions. However, we caution that particular groups such as large mammals, forest-dependent birds, orchids, and butterflies are disproportionately vulnerable.

PMID:38079550 | DOI:10.1073/pnas.2309034120

ACS Synth Biol. 2023 Dec 11. doi: 10.1021/acssynbio.3c00504. Online ahead of print.

ABSTRACT

A universal biochemical signal for bacterial cell-cell communication could facilitate programming dynamic responses in diverse bacterial consortia. However, the classical quorum sensing paradigm is that Gram-negative and Gram-positive bacteria generally communicate via homoserine lactones (HSLs) or oligopeptide molecular signals, respectively, to elicit population responses. Here, we create synthetic HSL sensors for Gram-positive Bacillus subtilis 168 using allosteric LuxR-type regulators (RpaR, LuxR, RhlR, and CinR) and synthetic promoters. Promoters were combinatorially designed from different sequence elements (-35, -16, -10, and transcriptional start regions). We quantified the effects of these combinatorial promoters on sensor activity and determined how regulator expression affects its activation, achieving up to 293-fold activation. Using the statistical design of experiments, we identified significant effects of promoter regions and pairwise interactions on sensor activity, which helped to understand the sequence-function relationships for synthetic promoter design. We present the first known set of functional HSL sensors (≥20-fold dynamic range) in B. subtilis for four different HSL chemical signals: p-coumaroyl-HSL, 3-oxohexanoyl-HSL, n-butyryl-HSL, and n-(3-hydroxytetradecanoyl)-HSL. This set of synthetic HSL sensors for a Gram-positive bacterium can pave the way for designable interspecies communication within microbial consortia.

PMID:38079538 | DOI:10.1021/acssynbio.3c00504

PLoS One. 2023 Dec 11;18(12):e0295678. doi: 10.1371/journal.pone.0295678. eCollection 2023.

ABSTRACT

Large datasets with noisy labels and high dimensions have become increasingly prevalent in industry. These datasets often contain errors or inconsistencies in the assigned labels and introduce a vast number of predictive variables. Such issues frequently arise in real-world scenarios due to uncertainties or human errors during data collection and annotation processes. The presence of noisy labels and high dimensions can significantly impair the generalization ability and accuracy of trained models. To address the above issues, we introduce a simple-structured penalized γ-divergence model and a novel meta-gradient correction algorithm and establish the foundations of these two modules based on rigorous theoretical proofs. Finally, comprehensive experiments are conducted to validate their effectiveness in detecting noisy labels and mitigating the curse of dimensionality and suggest that our proposed model and algorithm can achieve promising outcomes. Moreover, we open-source our codes and distinctive datasets on GitHub (refer to https://github.com/DebtVC2022/Robust_Learning_with_MGC).

PMID:38079441 | DOI:10.1371/journal.pone.0295678

PLoS One. 2023 Dec 11;18(12):e0295761. doi: 10.1371/journal.pone.0295761. eCollection 2023.

ABSTRACT

BACKGROUND: Low back pain (LBP) is a highly prevalent condition that substantially impairs individuals’ physical functioning. This highlights the need for effective management strategies to improve patient outcomes. It is, therefore, crucial to have knowledge of physical functioning prognostic factors that can predict outcomes to facilitate the development of targeted treatment plans aiming to achieve better patient outcomes. There is no synthesis of evidence for physical functioning measures as prognostic factors in the LBP population. The objective of this systematic review is to synthesize evidence for physical measures of physical functioning as prognostic factors to predict outcomes in LBP.

METHODS: The protocol is registered in the International Prospective Register of Systematic Reviews and reported in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P). Prospective longitudinal observational studies investigating potential physical prognostic factors in LBP and/or low back-related leg pain population will be included, with no restriction on outcome. Searches will be performed in MEDLINE, EMBASE, Scopus, CINAHL databases, grey literature search using Open Grey System and ProQuest Dissertations and Theses, hand-searching journals, and reference lists of included studies. Two independent reviewers will evaluate the eligibility of studies, extract data, assess risk of bias and quality of evidence. Risk of bias will be assessed using the Quality in Prognostic Studies (QUIPS) tool. Adequacy of clinical, methodological, and statistical homogeneity among included studies will decide quantitative (meta-analysis) or qualitative analysis (narrative synthesis) focused on prognostic factors and strength of association with outcomes. Quality of cumulative evidence will be evaluated using a modified Grading of Recommendations Assessment, Development, and Evaluation (GRADE).

DISCUSSION: Information about prognostic factors can be used to predict outcomes in LBP. Accurate outcome prediction is essential for identifying high-risk patients that allows targeted allocation of healthcare resources, ultimately reducing the healthcare burden.

REGISTRATION: PROSPERO, CRD42023406796.

PMID:38079434 | DOI:10.1371/journal.pone.0295761

JMIR Hum Factors. 2023 Dec 11;10:e52088. doi: 10.2196/52088.

ABSTRACT

BACKGROUND: The digital app SWEPPE (sustainable worker, a digital support for persons with chronic pain and their employers) was developed to improve the support of people with chronic pain in their return-to-work process after sick leave and includes functions such as the action plan, daily self-rating, self-monitoring graphs, the coach, the library, and shared information with the employer.

OBJECTIVE: This study aims to describe the use of the smartphone app SWEPPE among people with chronic pain who have participated in an interdisciplinary pain rehabilitation program.

METHODS: This is a case study including 16 people participating in a feasibility study. The analyses were based on user data collected for 3 months. Quantitative data regarding used functions were analyzed with descriptive statistics, and qualitative data of identified needs of support from the employer were grouped into 8 categories.

RESULTS: Self-monitoring was used by all participants (median 26, IQR 8-87 daily registrations). A total of 11 (N=16, 69%) participants set a work-related goal and performed weekly evaluations of goal fulfillment and ratings of their work ability. In total, 9 (56%) participants shared information with their employer and 2 contacted the coach. A total of 15 (94%) participants identified a total of 51 support interventions from their employer. Support to adapt to work assignments and support to adapt to work posture were the 2 biggest categories. The most common type of support identified by 53% (8/15) of the participants was the opportunity to take breaks and short rests.

CONCLUSIONS: Participants used multiple SWEPPE functions, such as daily self-registration, goal setting, self-monitoring, and employer support identification. This shows the flexible nature of SWEPPE, enabling individuals to select functions that align with their needs. Additional research is required to investigate the extended use of SWEPPE and how employers use shared employee information.

PMID:38079212 | DOI:10.2196/52088

JMIR Form Res. 2023 Dec 11;7:e49179. doi: 10.2196/49179.

ABSTRACT

BACKGROUND: The prevention of oral health diseases is a key public health issue and a major challenge for racial and ethnic minority groups, who often face barriers in accessing dental care. Daily toothbrushing is an important self-care behavior necessary for sustaining good oral health, yet engagement in regular brushing remains a challenge. Identifying strategies to promote engagement in regular oral self-care behaviors among populations at risk of poor oral health is critical.

OBJECTIVE: The formative research described here focused on creating messages for a digital oral self-care intervention targeting a racially and ethnically diverse population. Theoretically grounded strategies (reciprocity, reciprocity-by-proxy, and curiosity) were used to promote engagement in 3 aspects: oral self-care behaviors, an oral care smartphone app, and digital messages. A web-based participatory co-design approach was used to develop messages that are resource efficient, appealing, and novel; this approach involved dental experts, individuals from the general population, and individuals from the target population-dental patients from predominantly low-income racial and ethnic minority groups. Given that many individuals from racially and ethnically diverse populations face anonymity and confidentiality concerns when participating in research, we used an approach to message development that aimed to mitigate these concerns.

METHODS: Messages were initially developed with feedback from dental experts and Amazon Mechanical Turk workers. Dental patients were then recruited for 2 facilitator-mediated group webinar sessions held over Zoom (Zoom Video Communications; session 1: n=13; session 2: n=7), in which they provided both quantitative ratings and qualitative feedback on the messages. Participants interacted with the facilitator through Zoom polls and a chat window that was anonymous to other participants. Participants did not directly interact with each other, and the facilitator mediated sessions by verbally asking for message feedback and sharing key suggestions with the group for additional feedback. This approach plausibly enhanced participant anonymity and confidentiality during the sessions.

RESULTS: Participants rated messages highly in terms of liking (overall rating: mean 2.63, SD 0.58; reciprocity: mean 2.65, SD 0.52; reciprocity-by-proxy: mean 2.58, SD 0.53; curiosity involving interactive oral health questions and answers: mean 2.45, SD 0.69; curiosity involving tailored brushing feedback: mean 2.77, SD 0.48) on a scale ranging from 1 (do not like it) to 3 (like it). Qualitative feedback indicated that the participants preferred messages that were straightforward, enthusiastic, conversational, relatable, and authentic.

CONCLUSIONS: This formative research has the potential to guide the design of messages for future digital health behavioral interventions targeting individuals from diverse racial and ethnic populations. Insights emphasize the importance of identifying key stimuli and tasks that require engagement, gathering multiple perspectives during message development, and using new approaches for collecting both quantitative and qualitative data while mitigating anonymity and confidentiality concerns.

PMID:38079204 | DOI:10.2196/49179

JMIR Form Res. 2023 Dec 11;7:e50579. doi: 10.2196/50579.

ABSTRACT

BACKGROUND: Medication adherence is vital in the treatment of patients with chronic illness who require long-term medication therapies to maintain optimal health. Medication adherence, a complex and widespread problem, has been difficult to solve. Additionally, lower-income, medically underserved communities have been found to have higher rates of inadequate adherence to oral medications. Even so, this population has been underrepresented in studies using mobile medication adherence app interventions. Federally qualified health centers provide care for medically underserved populations, defined as communities and populations where there is a demonstrable unmet need for health services. These centers have been reporting an increase in a more complex chronic disease population. Including medically underserved individuals in mobile health studies provides opportunities to support this disproportionately affected group, work toward reducing health disparities in access to health care, and understand barriers to mobile health uptake.

OBJECTIVE: The aim of this preliminary efficacy study was to evaluate the effects and feasibility of a commercially available medication adherence app, Medisafe, in a medically underserved adult population with various chronic illnesses seeking care in a federally qualified health center.

METHODS: Participants in this single-arm pre-post intervention preliminary efficacy study (N=10) completed a baseline survey, used the app for 2 weeks, and completed an end-of-study survey. The primary outcome measures were medication adherence and medication self-efficacy. Feedback on the use of the app was also gathered.

RESULTS: A statistically significant median increase of 8 points on the self-efficacy for adherence to medications scale was observed (P=.03, Cohen d=0.69). Though not significant, the adherence to refills and medications scale demonstrated a median change of 2.5 points in the direction of increased medication adherence (P=.21, Cohen d=0.41). Feedback about the app was positive.

CONCLUSIONS: Use of the Medisafe app is a viable option to improve medication self-efficacy and medication adherence in medically underserved patients in an outpatient setting with a variety of chronic illnesses.

PMID:38079192 | DOI:10.2196/50579

Nord J Psychiatry. 2023 Dec 11:1-9. doi: 10.1080/08039488.2023.2289915. Online ahead of print.

ABSTRACT

AIMS: To examine the association between pulse width and HRQoL measured within one week after electroconvulsive therapy (ECT) and at six-month follow-up in patients with unipolar or bipolar depression.

METHODS: This was an observational register study using data from the Swedish National Quality Registry for ECT (2011-2019). Inclusion criteria were: age ≥18 years; index treatment for unipolar/bipolar depression; unilateral electrode placement; information on pulse width; EQ-5D measurements before and after ECT. Multiple linear regressions were performed to investigate the association between pulse width (<0.5 ms; 0.5 ms; >0.5 ms) and HRQoL (EQ-5D-3L index; EQ VAS) one week after ECT (primary outcome) and six months after ECT (secondary outcome).

RESULTS: The sample included 5,046 patients with unipolar (82%) or bipolar (18%) depression. At first ECT session, 741 patients (14.7%) had pulse width <0.5 ms, 3,639 (72.1%) had 0.5 ms, and 666 (13.2%) had >0.5 ms. There were no statistically significant associations between pulse width and HRQoL one week after ECT. In the subsample of patients with an EQ-5D index recorded six months after ECT (n = 730), patients receiving 0.5 ms had significantly lower HRQoL (-0.089) compared to <0.5 ms, after adjusting for demographic and clinical characteristics (p = .011). The corresponding analysis for EQ VAS did not show any statistically significant associations.

CONCLUSION: No robust associations were observed between pulse width and HRQoL after ECT. On average, significant improvements in HRQoL were observed one week and six months after ECT for patients with unipolar or bipolar disease, independent of the pulse width received.

PMID:38079191 | DOI:10.1080/08039488.2023.2289915

Tissue Eng Regen Med. 2023 Dec 11. doi: 10.1007/s13770-023-00612-2. Online ahead of print.

ABSTRACT

BACKGROUND: Collagen is a key component of connective tissue and has been frequently used in the fabrication of medical devices for tissue regeneration. Human-originated collagen is particularly appealing due to its low immune response as an allograft biomaterial compared to xenografts and its ability to accelerate the regeneration process. Ethically and economically, adipose tissues available from liposuction clinics are a good resource to obtain human collagen. However, studies are still scarce on the extraction and characterization of human collagen, which originates from adipose tissue. The aim of this study is to establish a novel and simple method to extract collagen from human adipose tissue, characterize the collagen, and compare it with commercial-grade porcine collagen for tissue engineering applications.

METHODS: We developed a method to extract the collagen from human adipose tissue under quasi-Good Manufacturing Practice (GMP) conditions, including freezing the tissue, blood removal, and ethanol-based purification. Various techniques, including protein quantification, decellularization assessment, SDS-PAGE, FTIR, and CD spectroscopy analysis, were used for characterization. Amino acid composition was compared with commercial collagen. Biocompatibility and cell proliferation tests were performed, and in vitro tests using collagen sponge scaffolds were conducted with statistical analysis.

RESULTS: Our results showed that this human adipose-derived collagen was equivalent in quality to commercially available porcine collagen. In vitro testing demonstrated high cell attachment and the promotion of cell proliferation.

CONCLUSION: In conclusion, we developed a simple and novel method to extract and characterize collagen and extracellular matrix from human adipose tissue, offering a potential alternative to animal-derived collagen for xeno-free tissue engineering applications.

PMID:38079100 | DOI:10.1007/s13770-023-00612-2

Clin Transl Oncol. 2023 Dec 11. doi: 10.1007/s12094-023-03355-7. Online ahead of print.

ABSTRACT

BACKGROUND: The use of additional treatment after surgery for stage IIIC endometrial cancer (EC) according to the Federation of Gynecology and Obstetrics (FIGO) is still a topic of discussion. This meta-analysis examined the effects of sandwich treatment and sequential treatment on the survival of individuals diagnosed with stage IIIC EC.

METHODS: We examined the literature from various databases regarding the overall survival (OS) and adverse effects of the two additional therapies following surgery in individuals diagnosed with stage IIIC EC. Revman 5.4.1 was utilized to combine hazard ratios (HR) and their corresponding 95% confidence intervals (95% CI) for OS and toxicities.

RESULTS: The findings comprised of five retrospective investigations involving a combined total of 800 individuals. The patients who underwent sandwich treatment did not demonstrate a notable improvement in survival rates over a period of 3 years. Upon eliminating the impact of extensive samples, it was discovered that sandwich therapy exhibited a superior 5-year overall survival compared to patients receiving sequential therapy. The effectiveness of sandwich therapy was superior to sequential therapy in terms of a 3-year OS for non-endometrioid histology, although the outcome did not reach statistical significance. The toxicities of both treatments were similar.

CONCLUSIONS: In terms of long-term survival, sandwich therapy was found to be more advantageous than sequential therapy for patients with stage IIIC EC, with no significant disparity observed in the 3-year OS and toxicities between the two treatments. Sandwich therapy exhibited a tendency towards improved effectiveness in patients with histology other than endometrioid.

PMID:38079088 | DOI:10.1007/s12094-023-03355-7