Despite the fact that health facilities in Ethiopia are being built closer to communities in all regions, the proportion of home deliveries remains high, and there are no studies being conducted to identify low birth weight (LBW) and premature newborn babies using simple, best, alternative, and appropriate anthropometric measurement in the study area. The objective of the present study was to find the simple, best, and alternative anthropometric measurement and identified its cut-off points for detecting LBW and premature newborn babies. A health facility-based cross-sectional study was conducted in the Dire Dawa city administration, Eastern Ethiopia. The study included 385 women who gave birth in health facility. To evaluate the overall accuracy of the anthropometric measurements, a non-parametric receiver operating characteristic curve was used. Chest circumference (AUC = 0⋅95) with 29⋅4 cm and mean upper arm circumference (AUC = 0⋅93) with 7⋅9 cm proved to be the best anthropometric diagnostic measure for LBW and gestational age, respectively. Also, both anthropometric measuring tools are achieved the highest correlation (r = 0⋅62) for LBW and gestational age. Foot length had a higher sensitivity (94⋅8 %) in detecting LBW than other measurements, with a higher negative predictive value (NPV) (98⋅4 %) and a higher positive predictive value (PPV) (54⋅8 %). Chest circumference and mid-upper arm circumference were found to be better surrogate measurements for identifying LBW and premature babies in need of special care. More research is needed to identify better diagnostic interventions in situations like the study area, which has limited resources and a high proportion of home deliveries.

UNASSIGNED: Osteosarcoma is most prevalently found primary malignant bone tumors, with primary metastatic patients accounting for approximately 25% of all osteosarcoma patients, yet their 5-year OS remains below 30%. Bilirubin plays a key role in oxidative stress-associated events, including malignancies, making the regulation of its serum levels a potential anti-tumor strategy. Herein, we investigated the association of osteosarcoma prognosis with serum levels of TBIL, IBIL and DBIL, and further explored the mechanisms by which bilirubin affects tumor invasion and migration.
UNASSIGNED: ROC curve was plotted to assess survival conditions based on the determined optimal cut-off values and the AUC. Then, Kaplan-Meier curves, along with Cox proportional hazards model, was applied for survival analysis. Inhibitory function of IBIL on the malignant properties of osteosarcoma cells was examined using the qRT-PCR, transwell assays, western blotting, and flow cytometry.
UNASSIGNED: We found that, versus osteosarcoma patients with pre-operative higher IBIL (>8.9 μmol/L), those with low IBIL (≤8.9 μmol/L) had shorter OS and PFS. As indicated by the Cox proportional hazards model, pre-operative IBIL functioned as an independent prognostic factor for OS and PFS in total and gender-stratified osteosarcoma patients (P < 0.05 for all). In vitro experiments further confirmed that IBIL inhibits PI3K/AKT phosphorylation and downregulates MMP-2 expression via reducing intracellular ROS, thereby decreasing the invasion of osteosarcoma cells.
UNASSIGNED: IBIL may serve as an independent prognostic predictor for osteosarcoma patients. IBIL impairs invasion of osteosarcoma cells through repressing the PI3K/AKT/MMP-2 pathway by suppressing intracellular ROS, thus inhibiting its metastatic potential.

Strategies to minimize immune-suppressive medications after liver transplantation are limited by allograft rejection. Biopsy of liver is the current standard of care in diagnosing rejection. However, it adds to physical and economic burden to the patient and has diagnostic limitations. In this review, we aim to highlight the different biomarkers to predict and diagnose acute rejection. We also aim to explore recent advances in molecular diagnostics to improve the diagnostic yield of liver biopsies.

UNASSIGNED: Manually identifying geographic atrophy (GA) presence and location on OCT volume scans can be challenging and time consuming. This study developed a deep learning model simultaneously (1) to perform automated detection of GA presence or absence from OCT volume scans and (2) to provide interpretability by demonstrating which regions of which B-scans show GA.
UNASSIGNED: Med-XAI-Net, an interpretable deep learning model was developed to detect GA presence or absence from OCT volume scans using only volume scan labels, as well as to interpret the most relevant B-scans and B-scan regions.
UNASSIGNED: One thousand two hundred eighty-four OCT volume scans (each containing 100 B-scans) from 311 participants, including 321 volumes with GA and 963 volumes without GA.
UNASSIGNED: Med-XAI-Net simulates the human diagnostic process by using a region-attention module to locate the most relevant region in each B-scan, followed by an image-attention module to select the most relevant B-scans for classifying GA presence or absence in each OCT volume scan. Med-XAI-Net was trained and tested (80% and 20% participants, respectively) using gold standard volume scan labels from human expert graders.
UNASSIGNED: Accuracy, area under the receiver operating characteristic (ROC) curve, F1 score, sensitivity, and specificity.
UNASSIGNED: In the detection of GA presence or absence, Med-XAI-Net obtained superior performance (91.5%, 93.5%, 82.3%, 82.8%, and 94.6% on accuracy, area under the ROC curve, F1 score, sensitivity, and specificity, respectively) to that of 2 other state-of-the-art deep learning methods. The performance of ophthalmologists grading only the 5 B-scans selected by Med-XAI-Net as most relevant (95.7%, 95.4%, 91.2%, and 100%, respectively) was almost identical to that of ophthalmologists grading all volume scans (96.0%, 95.7%, 91.8%, and 100%, respectively). Even grading only 1 region in 1 B-scan, the ophthalmologists demonstrated moderately high performance (89.0%, 87.4%, 77.6%, and 100%, respectively).
UNASSIGNED: Despite using ground truth labels during training at the volume scan level only, Med-XAI-Net was effective in locating GA in B-scans and selecting relevant B-scans within each volume scan for GA diagnosis. These results illustrate the strengths of Med-XAI-Net in interpreting which regions and B-scans contribute to GA detection in the volume scan.

Cathepsin V is a human lysosomal cysteine peptidase with specific functions during pathological processes and is as such a promising therapeutic target. Peptidase inhibitors represent powerful pharmacological tools for regulating excessive proteolytic activity in various diseases. Cathepsin V is highly related to cathepsin L but differs in tissue distribution, binding site morphology, substrate specificity, and function. To validate its therapeutic potential and extend the number of potent and selective cathepsin V inhibitors, we used virtual high-throughput screening of commercially available compound libraries followed by an evaluation of kinetic properties to identify novel potent and selective cathepsin V inhibitors. We identified the ureido methylpiperidine carboxylate derivative, compound 7, as a reversible, selective, and potent inhibitor of cathepsin V. It also exhibited the most preferable characteristics for further evaluation with in vitro functional assays that simulate the processes in which cathepsin V is known to play an important role. Compound 7 exerted significant effects on cell proliferation, elastin degradation, and immune cell cytotoxicity. The latter was increased because compound 7 impaired conversion of immunosuppressive factor cystatin F to its active monomeric form. Taken together, our results present novel potent inhibitors of cathepsin V and provide new hit compounds for detailed development and optimization. Further, we demonstrate that cathepsin V is a potential target for new approaches to cancer therapy.

UNASSIGNED: To establish cutoff scores for the Activity Measure for Post-Acute Care \"6-Clicks\" standardized Basic Mobility scores (sBMSs) for predicting discharge destination after acute care hospitalization for diagnostic subgroups within an acute care population and to evaluate the need for a second score to improve predictive ability.
UNASSIGNED: Retrospective, observational design.
UNASSIGNED: Major medical center in metropolitan area.
UNASSIGNED: Electronic medical records of 1696 adult patients (>18 years) admitted to acute care from January to October 2018. Records were stratified by orthopedic, cardiac, pulmonary, stroke, and other neurological diagnoses (N=1696). Interventions: None.
UNASSIGNED: Physical therapists scored patients\' sBMSs after referral for physical therapy and prior to discharge. Receiver operating characteristic curves delineated sBMS cutoff scores distinguishing various pairings of home, home with services, inpatient rehabilitation, or skilled nursing facility discharges. First and second sBMSs were compared with percentage change of the area under the curve and inferential statistics.
UNASSIGNED: Home vs institution cutoff score was 42.88 for combined sample, pulmonary and neurological cases. The cutoff score for orthopedic diagnoses score was 41.46. Cardiac and stroke model quality invalidated cutoff scores. Home without services vs skilled nursing discharges and home with services vs skilled nursing discharges were predicted with varying cutoff scores per diagnosis. sBMS cutoff scores collected closer to discharge were either the same or higher than first cutoffs, with varying effects on predictive ability.
UNASSIGNED: sBMSs can help decide institution vs home discharge and finer distinctions among discharge settings for some diagnostic groups. A single sBMS may provide sufficient assistance with discharge destination decisions but timing of scoring and diagnostic group may influence cutoff score selection.

UNASSIGNED: To assess clinical and immunological benefits of passive immunization using convalescent plasma therapy (CPT) we performed sub-group analyses on a completed randomised control trial (RCT) on CPT in severe COVID-19.
UNASSIGNED: A series of subclass analyses were performed on the previously published outcome data and accompanying clinical metadata from a completed RCT (Clinical Trial Registry of India, No. CTRI/2020/05/025209).
UNASSIGNED: The subclass analyses were performed on the outcome data and accompanying clinical metadata from a completed randomized control trial. Data on the plasma abundance of a large panel of cytokines from the same cohort of patients were also utilised to characterize the heterogeneity of the putative anti-inflammatory function of convalescent plasma (CP) in addition to passively providing neutralizing antibodies.
UNASSIGNED: While across all age-groups primary clinical outcomes were not significantly different in the RCT, significant immediate mitigation of hypoxia, reduction in hospital stay as well as significant survival benefit were registered in younger (<67 years in our cohort) severe COVID-19 patients with ARDS on receiving CPT. In addition to neutralizing antibody content of convalescent plasma, its anti-inflammatory proteome on attenuation of systemic cytokine deluge, significantly contributed to the clinical benefits of CPT.
UNASSIGNED: The sub-group analyses revealed that clinical benefit of CPT in severe COVID-19 is linked to the anti-inflammatory protein content of CP, apart from the anti-SARS-CoV-2 neutralizing antibody content.

UNASSIGNED: The microscopic tumor extension before, during or after radiochemotherapy (RCHT) and its correlation with the tumor microenvironment (TME) are presently unknown. This information is, however, crucial in the era of image-guided, adaptive high-precision photon or particle therapy.
UNASSIGNED: In this pilot study, we analyzed formalin-fixed paraffin-embedded (FFPE) tumor resection specimen from patients with histologically confirmed squamous cell carcinoma (SCC; n = 10) or adenocarcinoma (A; n = 10) of the esophagus, having undergone neoadjuvant radiochemotherapy followed by resection (NRCHT + R) or resection (R)]. FFPE tissue sections were analyzed by immunohistochemistry regarding tumor hypoxia (HIF-1α), proliferation (Ki67), immune status (PD1), cancer cell stemness (CXCR4), and p53 mutation status. Marker expression in HIF-1α subvolumes was part of a sub-analysis. Statistical analyses were performed using one-sided Mann-Whitney tests and Bland-Altman analysis.
UNASSIGNED: In both SCC and AC patients, the overall percentages of positive tumor cells among the five TME markers, namely HIF-1α, Ki67, p53, CXCR4 and PD1 after NRCHT were lower than in the R cohort. However, only PD1 in SCC and Ki67 in AC showed significant association (Ki67: p = 0.03, PD1: p = 0.02). In the sub-analysis of hypoxic subvolumes among the AC patients, the percentage of positive tumor cells within hypoxic regions were statistically significantly lower in the NRCHT than in the R cohort across all the markers except for PD1.
UNASSIGNED: In this pilot study, we showed changes in the TME induced by NRCHT in both SCC and AC. These findings will be correlated with microscopic tumor extension measurements in a subsequent cohort of patients.

Post-translational modifications (PTMs) are closely linked to numerous diseases, playing a significant role in regulating protein structures, activities, and functions. Therefore, the identification of PTMs is crucial for understanding the mechanisms of cell biology and diseases therapy. Compared to traditional machine learning methods, the deep learning approaches for PTM prediction provide accurate and rapid screening, guiding the downstream wet experiments to leverage the screened information for focused studies. In this paper, we reviewed the recent works in deep learning to identify phosphorylation, acetylation, ubiquitination, and other PTM types. In addition, we summarized PTM databases and discussed future directions with critical insights.

UNASSIGNED: Development of sepsis is a major contributor to poor outcomes after liver transplant. The neutrophil-lymphocyte ratio (NLR) is an easily calculable inflammatory biomarker. We aim to utilize NLR to diagnose and predict the onset of sepsis in patients undergoing living donor liver transplants (LDLT).
UNASSIGNED: Analysis of the perioperative course of 314 consecutive adult patients who underwent elective ABO compatible LDLT was done. Patients were divided into two cohorts; those who developed sepsis and a control group. Sepsis was defined by the combination of SIRS and clinical/radiological suspicion of infection. NLR was calculated by dividing the percentage of neutrophils by the percentage of lymphocytes in peripheral blood.
UNASSIGNED: ostoperatively, 127 out of 314 patients (40.5%) having at least one episode of sepsis were included in the septic cohort and were compared to the 187 (59.5%) patients in the control group. Demographic and baseline characteristics, including NLR (13.74 ± 0.99 vs. 12.65 ± 0.57, P = 0.294) were comparable preoperatively. The NLR of the septic cohort was significantly higher than the control cohort (15.01 ± 1.67 vs. 9.98 ± 0.63, P = 0.001) 3 days prior to sepsis and remained significantly higher till the day of sepsis. The area under the cover was maximum for NLR 1 day prior to the development of sepsis (r = 0.707) with a sensitivity, specificity, positive predictive value, and negative predictive value of 62.4%, 62.2%, 51.4%, and 72.0%, respectively, at a cutoff of 8.5.
UNASSIGNED: NLR is a useful tool in diagnosing and pre-empting development of sepsis in LDLT.