Depression remains underdiagnosed in non- and minimally speaking (NMS) autistic adults, despite caregiver concerns suggesting high rates of mood-related difficulties, as such this study evaluates the validity, reliability, and feasibility of three established caregiver-report depression measures (Anxiety, Depression, and Mood Scale-ADAMS; Glasgow Depression Scale-Caregiver Supplement-GDS-CS; Mood, Interest, and Pleasure Questionnaire-MIPQ) with 160 caregivers of NMS autistic adults. Participants completed surveys, and a subset engaged in cognitive interviews to assess content validity and usability. Psychometric analyses included confirmatory factor analyses, internal consistency estimation, and exploratory cut-off scores based on parent-reported concern about depression. Results indicated that the GDS-CS had the strongest support, showing acceptable model fit, fair reliability, and high caregiver acceptability. The ADAMS also demonstrated strong psychometric properties and feasibility, with the added benefit of capturing related symptoms such as anxiety. The MIPQ, while designed for individuals with limited language, showed poor model fit and lower caregiver usability. Findings support the use of the GDS-CS and ADAMS as promising tools for screening depression in NMS autistic adults and highlight the need for further validation and tailored mental health assessment approaches for this underserved population.Lay AbstractSome autistic people do not use speech to communicate, even when they become adults. These individuals are called minimally speaking (or nonspeaking; NMS). Many parents think their NMS autistic adult children may be depressed, but few have a diagnosis from a doctor. One reason for this is that most ways doctors check for depression ask about feelings using spoken words. This does not work well for people who do not speak. This study asked 160 parents of minimally speaking autistic adults to fill out three surveys that may help identify depression. The surveys were the ADAMS, the GDS-CS, and the MIPQ. The parents answered questions about how their adult children behave, how often certain things happen, and whether they think their child is depressed. Some parents also talked in interviews about how easy or hard the surveys were to understand and complete. The results showed that two of the surveys, the ADAMS and the GDS-CS, worked pretty well and were quick to fill out. Parents said the GDS-CS was the easiest to understand. The third survey, the MIPQ, was harder for parents to use and did not work as well. This study shows that it is possible to screen for depression in autistic adults who do not speak by asking caregivers the right kinds of questions. It also shows that more research is needed to make sure these tools work for everyone. Doctors and caregivers can use these tools to find people who may be feeling depressed and need more help. This is an important step toward making sure all autistic adults, including those who don't speak, get the mental health care they need.

There is an urgent need to better understand the pathophysiology of primary graft dysfunction (PGD) to develop point-of-care methods predicting those at risk. We utilized a multiplex multivariable approach to define cytokines, chemokines, and growth factors in patient-matched biospecimens to identify factors predictive of PGD. Biospecimens were collected from patients undergoing bilateral lung transplantation (LTx) from three sites: donor lung perfusate, post-transplant bronchoalveolar lavage (BAL) fluid (2h), and plasma (2h, 24h, 72h, and 1 and 2 wks). A 71-multiplex panel was performed on each. Cross-validated logistic regression (LR) and random forest (RF) models determined whether analytes from each site, alone or combined with clinical data, discriminated PGD grade 0 (n = 9) vs. 3 (n = 8). BAL fluid at 2h was most predictive of PGD (LR, 0.825; RF, 0.919), followed by multi-timepoint plasma (LR, 0.841; RF, 0.653), then perfusate (LR, 0.565; RF, 0.448). Combined clinical, BAL, and plasma data yielded the strongest performance (LR, 1.000; RF, 1.000). BAL collected 2h post-transplant showed the strongest discriminatory signal for severe PGD in this exploratory cohort. This integrative approach identified IL-1RA, BCA-1, and Fractalkine as hypothesis-generating candidate biomarkers that warrant validation in larger independent studies.

Cytomegalovirus (CMV) is a prevalent herpesvirus that remains typically asymptomatic in immunocompetent individuals but can cause severe, potentially life-threatening disease in immunocompromised patients. This study assessed the impact of CMV-associated lower respiratory tract infections (LRTIs), diagnosed by polymerase chain reaction (PCR) testing of bronchoalveolar lavage fluid (BALF), focusing on coinfections and clinical outcomes. Between 2009 and 2017, a total of 2666 visits involving 1301 immunocompromised patients with suspected LRTI who underwent diagnostic bronchoalveolar lavage (BAL) were analyzed. The primary outcomes included CMV detection in BAL and resulting treatment modifications. Among these, 235 BALFs from 157 patients tested positive for CMV. Among these CMV-positive cases, immunosuppression was classified as hematological conditions (n = 88), solid organ transplantation (n = 70), or other causes of immunosuppression (n = 77). Overall, 59 cases exhibited isolated CMV infection, which was associated with a higher percentage of macrophages in BALF, compared to cases with CMV and coinfection [75.5%, 95% confidence interval (CI): 44.0-85.0 vs. 37.5%, 95% CI: 11.5%-67.0%, p = 0.008]. A total of 176 cases demonstrated CMV and coinfection, which were associated with neutrophilia in BALF (49.5%, 95% CI: 15.5-82.5; vs. CMV-monoinfection: 7.5%, 95% CI:2-36, p = 0.002). BAL findings prompted treatment modifications in 61.7% (n = 145) of all CMV-positive cases. The 30-day mortality rate was 13.6%, with a significantly elevated hazard ratio for those with CMV-positive BAL diagnosis (unadjusted HR 2.85, 95% CI: 1.86-4.36). Cases with a CMV infection exhibited a significantly higher probability of requiring hospitalization compared to CMV-negative cases, (OR 1.39, 95% CI: 1.03-1.87, p = 0.030). Immunocompromised patients have an increased risk of CMV infection, and the presence of CMV does not exclude a coinfection with other respiratory viruses, bacteria, or fungi. CMV detection in BALF was associated with higher hospitalization rates and mortality. Preventive and preemptive antiviral strategies are crucial, especially given the adverse impact of coinfections.

The α-hydroxyketone motif is a key structural element in many pharmaceuticals and serves as a versatile intermediate in the synthesis of fine chemicals and natural products. Benzaldehyde lyase (BAL), a thiamine diphosphate (ThDP)-dependent enzyme, has emerged as a prominent biocatalyst for the synthesis of α-hydroxyketones. In recent years, significant research efforts have focused on the engineering and discovery of BAL mutants with unique or enhanced properties. In this chapter, we first review the engineering and applications of BALs in α-hydroxyketone synthesis. Next, we outline strategies to engineer BALs for improved activity and chemoselectivity. Subsequently, molecular dynamics studies have elucidated the structural basis for improved catalytic performance. Finally, we detail general procedures for synthesizing α-hydroxymethyl ketones and for developing a one-pot concurrent reaction coupling BALs with carbonyl reductases. These biocatalytic processes offer efficient routes for the synthesis of α-hydroxymethyl ketones and chiral 1,2-diols.

Intestinal parasitic infections (IPIs) remain a critical global public health concern, particularly for epidemiological surveillance in resource-limited tropical regions. Standard laboratory diagnostics heavily rely on the manual microscopic examination of stool samples, a process that is notoriously time-consuming, labor-intensive, and highly dependent on the scarce availability of experienced parasitologists. To alleviate medical workloads and enhance community-wide screening efficiency, reliable, automated diagnostic tools are urgently needed. From an epidemiological control perspective, such tools should not only improve image-level classification but also support scalable screening, case triage, and prioritization of specimens requiring confirmatory testing in routine surveillance programs. However, most existing frameworks operate as end-to-end "black boxes" that rely solely on pixel-level data, significantly lacking the clinical explainability and morphological reasoning required for high-stakes medical decisions. To address this critical limitation, this study introduces an innovative hybrid framework that integrates deep learning algorithms with expert morphological domain knowledge to classify seven commonly encountered intestinal protozoan cysts (Entamoeba histolytica (E. histolytica), Giardia lamblia, Entamoeba coli, Endolimax nana, Entamoeba hartmanni (E. hartmanni), Iodamoeba bütschlii, and Blastocystis sp.). Utilizing a comprehensive dataset of 3143 microscopic images, the system first deploys a Mask R-CNN model to accurately detect and segment intracystic nuclei. Subsequently, a rule-based decision engine classifies the cysts by extracting key morphological attributes, including cyst shape, size boundaries, and exact nuclear configurations. The proposed framework demonstrated high diagnostic efficiency, achieving an exceptional processing speed of 0.04 s per image, making it highly scalable for high-throughput population screening. The system achieved a robust overall classification accuracy of 84.8%. While conventional light microscopy often struggles to differentiate E. hartmanni from E. histolytica due to profound structural similarities, our framework successfully resolves this taxonomic ambiguity from an epidemiological perspective. When E. histolytica and E. hartmanni were grouped into a single complex category to address this intrinsic limitation of microscopy-based methods, the overall system accuracy improved to 87.8%. This knowledge-driven AI framework provides a cost-effective, interpretable, and high-throughput screening and decision-support tool to support active disease surveillance, specimen triage, and infectious disease control programs in endemic areas.

Cystic echinococcosis (CE) is a chronic zoonotic infection caused by Echinococcus granulosus that most commonly affects the liver and lungs. In disseminated disease, the combination of bilateral pulmonary nodules, cavitary consolidation, mediastinal lymphadenopathy, and hepatic lesions can closely mimic metastatic malignancy on cross-sectional imaging and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT). This case highlights disseminated CE mimicking pulmonary embolism (PE) and metastatic malignancy. This is a case of a previously healthy 27-year-old woman who presented with acute dyspnea, pleuritic chest pain, fever, and productive cough and was referred for suspected PE; however, CT pulmonary angiography ruled out PE and revealed bilateral pulmonary nodules, cavitary right middle lobe consolidation, mediastinal lymphadenopathy, and multiple hepatic lesions initially interpreted as metastatic malignancy. FDG PET/CT showed intensely hypermetabolic pulmonary and mediastinal disease (SUVmax (maximum standardized uptake value), 15.6), while the hepatic lesions were isometabolic, suggesting a separate etiology. Liver MRI showed well-defined cystic lesions across multiple hepatic segments consistent with hydatid cysts, and Echinococcus serology was positive (titer, 1:640). Bronchoalveolar lavage (BAL) was negative for malignancy and alternative infections. She was treated with albendazole 400 mg twice daily, and five-week follow-up CT showed cavitary transformation of pulmonary nodules consistent with treatment-related cyst degeneration. Disseminated CE can mimic both PE and metastatic malignancy. In patients from endemic regions, discordant FDG PRT/CT findings - hypermetabolic pulmonary lesions with isometabolic hepatic cysts - should prompt consideration of CE. A multidisciplinary approach integrating multimodal imaging and serology is essential for accurate diagnosis and to avoid unnecessary invasive procedures.

Background: The study goal was to assess the association between mortality and renal impairment markers in the nutritionDay ICU cohort, incorporating creatinine, urine volume, and renal replacement therapy (RRT) while adjusting for ICU- and patient-level factors. Methods: During nutritionDay, participating ICUs worldwide prospectively documented all patients treated on a predefined study day in November. Renal impairment markers included creatinine and urine volume at ICU admission and RRT status on nutritionDay. ICU-level factors included world region, calendar year and time of assessment. Patient-level factors included sex, age, BMI, disease severity, and underlying disease leading to ICU admission. Sixty-day hospital mortality and use of RRT on nutritionDay were assessed in multivariable logistic regressions including all ICU- and patient-level factors. Results: The post hoc analysis included 23,485 adult ICU patients from 1855 ICU-year units in 60 countries from 2007 to 2024, with analytic sample sizes of 23,485 for RRT, 18,245 for mortality, 21,054 for creatinine, and 20,753 for urine volume. Mean age was 61.4 (SD 17.0) years. Mean SAPS 2 at ICU admission was 39.8 (SD 17.7) points. Renal replacement therapy was associated with approximately twice the observed mortality. Severity of illness remained a major determinant of mortality after removing age and urine volume from SAPS 2. RRT use was similar up to 70 years but declined thereafter. Creatinine increased with age and BMI, while urine volume progressively declined with age. The reason for ICU dependency was associated with mortality, RRT use, creatinine, and urine volume. Conclusions: RRT, age and severity of illness were strongly associated with mortality in this large ICU cohort. The reason for ICU dependency, reflecting the underlying disease, was substantially associated with mortality, RRT use, creatinine, and urine volume.

Background/Objectives: The C-reactive protein-albumin-lymphocyte (CALLY) index integrates systemic inflammation, nutritional status, and host immunity. We evaluated its association with postoperative pathological axillary nodal status and its incremental discrimination beyond routinely recorded preoperative clinical factors. Methods: This retrospective single-center diagnostic-accuracy study screened 380 patients evaluated between July 2019 and January 2026. The primary cohort included 247 unilateral M0 patients undergoing upfront surgery; 80 neoadjuvant-treated M0 patients were analyzed separately. CALLY was calculated from laboratory values obtained within 7 days before surgery. Associations and discrimination were assessed using logistic regression, Firth penalized logistic regression when clinical nodal status caused separation, paired bootstrap AUC comparisons, restricted cubic splines, and prespecified sensitivity analyses for BMI and available inflammatory/comorbidity covariates. Results: In the primary cohort, 75 patients (30.4%) were pN-positive. Median CALLY was 2.629 in pN-positive and 3.586 in pN0 patients (p = 0.058), and standalone discrimination was weak (AUC = 0.576; 95% CI, 0.496-0.651). In the age- and cT-adjusted model, the OR per CALLY doubling was 0.89 (95% CI, 0.72-1.10; p = 0.271). Preoperative cN status nearly separated the outcome; in a Firth model including age, cT, cN, and CALLY, the CALLY OR was 0.78 (profile 95% CI, 0.51-1.21; p = 0.250). Adding CALLY to age, cT, and cN changed the AUC from 0.988 to 0.988 (ΔAUC = -0.0001; 95% CI, -0.0013 to 0.0041; p = 0.551). No nonlinearity was detected (p = 0.352), and BMI/confounder sensitivities were concordant. Secondary neoadjuvant and observed-burden analyses remained exploratory and imprecise. Conclusions: In this single-center upfront-surgery cohort, preoperative CALLY was not independently associated with postoperative axillary nodal positivity and provided no convincing incremental discrimination beyond the available clinical assessment. The data do not support using CALLY alone for axillary staging or surgical decisions; limited high-burden event counts preclude a definitive exclusion of smaller associations.

The rise of multidrug-resistant (MDR) pathogens presents a major challenge to food safety, particularly in preservation approaches. Lactic acid bacteria (LAB) gain probiotic recognition by effectively controlling MDR pathogens using antimicrobial substances (AMSs) and bacteriocin-like inhibitory substances (BLISs). The study evaluated the probiotic properties and AMS production potential of five LAB strains: Lactiplantibacillus plantarum NBRC 3070 (LP), Lactobacillus acidophilus ATCC 4356 (LA), Lacticaseibacillus casei ATCC 393 (LC), Lacticaseibacillus rhamnosus GG ATCC 53103 (LGG), and Bifidobacterium animalis subsp. lactis ATCC 27673 (BAL). AMS was extracted from neutralized and concentrated cell-free supernatant and tested for antimicrobial activities against common foodborne pathogens using minimum inhibitory concentrations (MICs). All LAB strains showed antagonistic activity, with LP demonstrating the most substantial antagonism. Four strains are resistant to multiple antibiotics but remain susceptible to azithromycin and tetracycline, while LP is resistant to all tested antibiotics. LP and LC demonstrated the highest probiotic potential based on cell surface hydrophobicity and aggregation abilities. Optimal AMS activity (85.36%-91.29%) occurred between 24 and 36 h at 37°C or 28-48 h at 30°C. LGG exhibited the highest AMS activity with the lowest MIC against Salmonella enterica serovar Typhimurium. Enzyme sensitivity confirmed the peptide nature of BLIS produced by BLIS from LP, LA, LC, and LGG. In conclusion, LAB strains demonstrated significant probiotic traits and the ability to produce AMS, especially BLIS, from four strains, with LP and LC showing the most potential. These findings support their application as natural biopreservation against MDR pathogens; however, further validation in the food system is required.