Three-Dimensional Printing of Lignocellulose Structures: Improving Mechanical Properties and Shape Fidelity.

Additive manufacturing of nanocellulose (NC) materials is an emergent technological domain that facilitates the fabrication of complex and environment-friendly structures that mitigate greenhouse gas emissions. However, printing high concentrations of NC into intricate structures encounters substantial challenges due to inadequate adhesion between the printed layers attributed to a high cellulose solid content, resulting in low shape fidelity and mechanical properties. Therefore, to address these challenges, this paper reports lignin (LG) blending, a nanofiller, in high-content NC (>25 wt % solid content) paste to improve the layer adhesion of three-dimensional (3D) printed structures. The printed structures are dried in a clean room condition followed by postcuring. The optimized lignocellulose (0.5LG-NC) paste showed high structural shape fidelity, remarkable flexural strength, and moduli of 102.93 ± 0.96 MPa and 9.05 ± 0.07 GPa. Furthermore, the volumetric shrinkage behavior in box-like 3D printed structures with optimized LG-NC paste shows low standard deviations, demonstrating the repeatability of the printed structures. The study can be adapted for high-performance engineering and biomedical applications to manufacture high mechanical strength environment-friendly structures.

The impact of genre-based instruction on Saudi university students' English writing performance and motivation: a mixed-method study.

Despite the important role motivation plays in students' writing learning and development, not much attention has been given to experimenting particular instructional techniques for developing students' writing motivation. One of the least researched teaching techniques in writing motivation studies is genre-based instruction. In this study, we examined the impact of genre-based instruction on 21 Saudi university students' English argumentative and classification essay writing performance and their writing motivation dimensions (writing apprehension, anxiety, self-efficacy and self-concept). Drawing upon the quasi-experimental research design and non-random sampling technique, we used genre-based instruction with a representative intact class of English-as-a-foreign-language (EFL) writing students at a Saudi university. To examine the potential impact of the treatment, we collected pre- and post-instruction data, along with data gathered through an open-ended questionnaire. The results showed that genre-based instruction has contributed significantly to improving the students' writing performance and also their writing motivation dimensions. These positive gains varied from one writing quality aspect and motivational variable to another. The students' answers to the open-ended questionnaire also showed the positive writing learning and motivation improvements they experienced. It is generally concluded that developing students' language and rhetorical awareness and text composition performance seems to be a prerequisite for improving their writing motivation levels. The paper ends with discussing the implications of the results.

Alzheimer's disease and drug delivery across the blood-brain barrier: approaches and challenges.

Alzheimer's disease (AD) is a diverse disease with a complex pathophysiology. The presence of extracellular ß-amyloid deposition as neuritic plaques and intracellular accumulation of hyper-phosphorylated tau as neurofibrillary tangles remain the core neuropathologic criteria for diagnosing Alzheimer's disease. Nonetheless, several recent basic discoveries have revealed significant pathogenic roles for other essential cellular and molecular processes. Previously, there were not so many disease-modifying medications (DMT) available as drug distribution through the blood-brain barrier (BBB) is difficult due to its nature, especially drugs of polypeptides nature and proteins. Recently FDA has approved lecanemab as DMT for its proven efficacy. It is also complicated to deliver drugs for diseases like epilepsy or any brain tumor due to the limitations of the BBB. After the advancements in the drug delivery system, different techniques are used to transport the medication across the BBB. Other methods are used, like enhancement of brain blood vessel fluidity by liposomes, infusion of hyperosmotic solutions, and local intracerebral implants, but these are invasive approaches. Non-invasive approaches include the formulation of nanoparticles and their coating with polymers. This review article emphasizes all the above-mentioned techniques, procedures, and challenges to transporting medicines across the BBB. It summarizes the most recent literature dealing with drug delivery across the BBB.

Transgenic expression of artificial microRNA targeting soybean mosaic virus P1 gene confers virus resistance in plant.

RNA silencing is an innate immune mechanism of plants against invasion by viral pathogens. Artificial microRNA (amiRNA) can be engineered to specifically induce RNA silencing against viruses in transgenic plants and has great potential for disease control. Here, we describe the development and application of amiRNA-based technology to induce resistance to soybean mosaic virus (SMV), a plant virus with a positive-sense single-stranded RNA genome. We have shown that the amiRNA targeting the SMV P1 coding region has the highest antiviral activity than those targeting other SMV genes in a transient amiRNA expression assay. We transformed the gene encoding the P1-targeting amiRNA and obtained stable transgenic Nicotiana benthamiana lines (amiR-P1-3-1-2-1 and amiR-P1-4-1-2-1). Our results have demonstrated the efficient suppression of SMV infection in the P1-targeting amiRNA transgenic plants in an expression level-dependent manner. In particular, the amiR-P1-3-1-2-1 transgenic plant showed high expression of amiR-P1 and low SMV accumulation after being challenged with SMV. Thus, a transgenic approach utilizing the amiRNA technology appears to be effective in generating resistance to SMV.

Advances in the Optimization of Fe Nanoparticles: Unlocking Antifungal Properties for Biomedical Applications.

In recent years, nanotechnology has achieved a remarkable status in shaping the future of biological applications, especially in combating fungal diseases. Owing to excellence in nanotechnology, iron nanoparticles (Fe NPs) have gained enormous attention in recent years. In this review, we have provided a comprehensive overview of Fe NPs covering key synthesis approaches and underlying working principles, the factors that influence their properties, essential characterization techniques, and the optimization of their antifungal potential. In addition, the diverse kinds of Fe NP delivery platforms that command highly effective release, with fewer toxic effects on patients, are of great significance in the medical field. The issues of biocompatibility, toxicity profiles, and applications of optimized Fe NPs in the field of biomedicine have also been described because these are the most significant factors determining their inclusion in clinical use. Besides this, the difficulties and regulations that exist in the transition from laboratory to experimental clinical studies (toxicity, specific standards, and safety concerns) of Fe NPs-based antifungal agents have been also summarized.

Smart integration of cold plasma stream and surface discharge with ns laser ablation for composite nanomaterial.

In this paper, smart integration of cold dielectric barrier discharge (DBD) plasma in various geometrical arrangements with laser ablation at atmospheric pressure for nanomaterial was described. A composite Co:ZnO target was ablated in an airflow by a nanosecond (ns) laser (wavelength: 1064 nm, pulse duration: 30 ns) using fluence of 5 J-cm-2 at a repetition rate of 10 Hz. The nanomaterial produced under vertical and oblique plasma streams, surface discharge and gas flow, were compared. Utilization surface discharge markedly improved the material adhesion by altering surface intrinsic behavior, inducing anticipated surface energy activation, chemical changes, and the formation of a densely packed solid structure. Under all conditions, the material consistently retained its crystalline nature, elemental composition, and ultraviolet emission characteristics. These preliminary findings hold promise for additional research, suggesting avenues for making complex materials in a flexible environment. Such new advancements could facilitate applications in the biomedical, catalysis, pharmaceutical, and surgical device domains.

Identification of Novel and Recurrent Variants in BTD, GBE1, AGL and ASL Genes in Families with Metabolic Disorders in Saudi Arabia.

Background and Objectives: Inherited metabolic disorders (IMDs) are a group of genetic disorders characterized by defects in enzymes or transport proteins involved in metabolic processes. These defects result in an abnormal accumulation of metabolites and thus interfere with the body's metabolism. A variety of IMDs exist and differential diagnosis is often challenging. Our objective was to gain insight into the genetic basis of IMDs and the correlations between specific genetic mutations and clinical presentations in patients admitted at various hospitals in the Madinah region of the Kingdom of Saudi Arabia. Material and Methods: Whole exome sequencing (WES) has emerged as a powerful tool for diagnosing IMDs and allows for the identification of disease-causing genetic mutations in individuals suspected of IMDs. This ensures accurate diagnosis and appropriate management. WES was performed in four families with multiple individuals showing clinical presentation of IMDs. Validation of the variants identified through WES was conducted using Sanger sequencing. Furthermore, various computational analyses were employed to uncover the disease gene co-expression and metabolic pathways. Results: Exome variant data analysis revealed missense variants in the BTD (c.1270G > C), ASL (c.1300G > T), GBE1 (c.985T > G) and AGL (c.113C > G) genes. Mutations in these genes are known to cause IMDs. Conclusions: Thus, our data showed that exome sequencing, in conjunction with clinical and biochemical characteristics and pathological hallmarks, could deliver an accurate and high-throughput outcome for the diagnosis and sub-typing of IMDs. Overall, our findings emphasize that the integration of WES with clinical and pathological information has the potential to improve the diagnosis and understanding of IMDs and related disorders, ultimately benefiting patients and the medical community.

Unconventional Reservoir Characterization of Patala Formation, Upper Indus Basin, Pakistan.

Unconventional hydrocarbon exploration is needed in the current oil and gas crisis scenario. Therefore, the development of conditions for unconventional hydrocarbon exploration is needed. In the Upper Indus Basin (UIB), Pakistan, the Patala Formation is one of the potential candidates for this unconventional exploration. It is a proven source rock at the regional level in the Kohat-Potwar sub-basin of UIB. This study aims to evaluate the shale gas potential of the rock in the Minwal-Joyamair area of the sub-basin. Developing a shale rock physics model is important for exploring and developing shale reservoirs due to the difference between unconventional shale and conventional sand reservoirs. These differences include mineral types, mineral characteristics, matrix pores, and fluid properties. To achieve the study's objectives, an integrated strategy provides for evaluating rock physics parameters, petrophysics, and geochemical analyses. This integrated approach indicates that the Patala Formation is a good potential reservoir for shale gas exploration. The Formation has a significant thickness (around 40-50 m), higher total organic carbon content (02-10%), higher brittleness index (0.44-0.56), and relatively shallow depth (2136-3223 m). These research findings suggested that the presence of organic and quartz-rich lithofacies can be considered as highly favorable "sweet spots" for shale-gas exploration in the UIB, Pakistan. Through proper understanding of the spatial and temporal distribution of these "sweet spots", shale-gas exploration can be developed as an effective strategy to exploit shale gas.

Bioinspired mp20 mimicking uricase in ZIF-8: Metal ion dependent for controllable activity.

Mini protein mimicking uricase (mp20) has shown significant potential as a replacement for natural enzymes in the development of uric acid biosensors. However, the design of mp20 has resulted to an inactive form of peptide, causing of loss their catalytic activity. Herein, this paper delineates the impact of various metal cofactors on the catalytic activity of mp20. The metal ion-binding site prediction and docking (MIB) web server was employed to identify the metal ion binding sites and their affinities towards mp20 residues. Among the tested metal ions, Cu2+ displayed the highest docking score, indicating its preference for interaction with Thr16 and Asp17 residues of mp20. To assess the catalytic activity of mp20 in the presence of metal ions, uric acid assays was monitored using a colorimetric method. The presence of Cu2+ in the assays promotes the activation of mp20, resulting in a color change based on quinoid production. Furthermore, the encapsulation of the mp20 within zeolitic imidazolate framework-8 (ZIF-8) notably improved the stability of the biomolecule. In comparison to the naked mp20, the encapsulated ZIFs biocomposite (mp20@ZIF-8) demonstrates superior stability, selectivity and sensitivity. ZIF's porous shells provides excellent protection, broad detection (3-100 µM) with a low limit (4.4 µM), and optimal function across pH (3.4-11.4) and temperature (20-100°C) ranges. Cost-effective and stable mp20@ZIF-8 surpasses native uricase, marking a significant biosensor technology breakthrough. This integration of metal cofactor optimization and robust encapsulation sets new standards for biosensing applications.

Recognition of the inducible, secretory small protein OsSSP1 by the membrane receptor OsSSR1 and the co-receptor OsBAK1 confers rice resistance to the blast fungus.

The plant apoplast, which serves as the frontline battleground for long-term host-pathogen interactions, harbors a wealth of disease resistance resources. However, the identification of the disease resistance proteins in the apoplast is relatively lacking. In this study, we identified and characterized the rice secretory protein OsSSP1 (Oryza sativa secretory small protein 1). OsSSP1 can be secreted into the plant apoplast, and either in vitro treatment of recombinant OsSSP1 or overexpression of OsSSP1 in rice could trigger plant immune response. The expression of OsSSP1 is suppressed significantly during Magnaporthe oryzae infection in the susceptible rice variety Taibei 309, and OsSSP1-overexpressing lines all show strong resistance to M. oryzae. Combining the knockout and overexpression results, we found that OsSSP1 positively regulates plant immunity in response to fungal infection. Moreover, the recognition and immune response triggered by OsSSP1 depend on an uncharacterized transmembrane OsSSR1 (secretory small protein receptor 1) and the key co-receptor OsBAK1, since most of the induced immune response and resistance are lost in the absence of OsSSR1 or OsBAK1. Intriguingly, the OsSSP1 protein is relatively stable and can still induce plant resistance after 1 week of storage in the open environment, and exogenous OsSSP1 treatment for a 2-week period did not affect rice yield. Collectively, our study reveals that OsSSP1 can be secreted into the apoplast and percepted by OsSSR1 and OsBAK1 during fungal infection, thereby triggering the immune response to enhance plant resistance to M. oryzae. These findings provide novel resources and potential strategies for crop breeding and disease control.

Effects of anthocyanidins on the conformational transition of Aß(1-42) peptide: Insights from molecular docking and molecular dynamics simulations.

Recent evidence from in vitro and in vivo studies has shown that anthocyanins and anthocyanidins can reduce and inhibit the amyloid beta (Aß) species, one of the hallmarks of Alzheimer's disease (AD). However, their inhibition mechanisms on Aß species at molecular details remain elusive. Therefore, in the present study, molecular modelling methods were employed to investigate their inhibitory mechanisms on Aß(1-42) peptide. The results highlighted that anthocyanidins effectively inhibited the conformational transitions of helices into beta-sheet (ß-sheet) conformation within Aß(1-42) peptide by two different mechanisms: 1) the obstruction of two terminals from coming into contact due to the binding of anthocyanidins with residues of N- and second hydrophobic core (SHC)-C-terminals, and 2) the prevention of the folding process due to the binding of anthocyanidin with the central polar (Asp23 and Lys28) and native helix (Asp23, Lys28, and Leu34) residues. These new findings on the inhibition of ß-sheet formation by targeting both N- and SHC-C-terminals, and the long-established target, D23-K28 salt bridge residues, not with the conventional central hydrophobic core (CHC) as reported in the literature, might aid in designing more potent inhibitors for AD treatment.

Exposure to Imidacloprid under variable conditions disturbs the muscle fatty acid profile of a fresh water non target fish: Labeo rohita.

Economy of Pakistan is heavily dependent upon agriculture and extensive use of pesticide is quiet common to enhance the crop yield. Imidacloprid is among the first choice pesticides in Pakistan and it has been reported that through run off along with water it ends up in water bodies affecting non target aquatic fauna. Through the present investigation, we are reporting the effects of Imidacloprid on the fatty acids composition of a non-target, commercially important carp: Labeo rohita. Fish were exposed to sub lethal concentration of Imidacloprid (120 mgL1) for 2, 4 and 8 days (short term) as well as for 16, 32 and 64 days (long term experimental conditions). Pesticide untreated controls were also maintained for each treatment. Following the specific Imidacloprid exposure, fatty acid composition (%) was determined in the muscle of all experimental groups by using gas chromatography. Fish exposed to Imidacloprid for 8 days had reduced Palmitic acid (p = 0.02) and elevated muscle Arachidic acid (p < 0.001) than control group. Labeo rohita exposed to the pesticide for 32 days had elevated muscle Oleic (p = 0.02) and Linoleic acid (p = 0.02) while fish exposed to Imidacloprid to 64 days had reduced muscle Palmitic (p = 0.04) and Oleic acid (p = 0.03). In conclusion, we are reporting that the exposure to sub lethal concentration of Imidacloprid disturb the muscle fatty acid composition of Labeo rohita that may affect its food quality. The effects were more pronounced under long term experimental conditions and were probably due to potentiating lipid peroxidation and disturbed fish metabolism upon Imidacloprid exposure.

Comparative catalytic reduction and degradation with biodegradable sodium alginate based nanocomposite: Zinc oxide/N-doped carbon nitride/sodium alginate.

Sodium alginate (SA) is a biodegradable macromolecule which is used to synthesize nanocomposites and their further use as catalysis. Zinc oxide (ZnO) and nitrogen doped carbon nitride (ND-C3N4) nanoparticles are prepared using solvothermal and hydrothermal methods, respectively. ZnO/ND-C3N4/SA nanocomposites are successfully synthesized by employing in-situ polymerization. The presence of essential functional groups is confirmed by Fourier transform infrared (FTIR) spectroscopic analysis. Controlled spherical morphology for ZnO nanoparticles, with an average diameter of ∼52 nm, is shown by Scanning electron microscopic (SEM) analysis, while rice-like grain structure with an average grain size ∼62 nm is exhibited by ND-C3N4 nanoparticles. The presence of required elements is confirmed by Energy dispersive X-ray spectroscopic (EDX) analysis. The crystalline nature of nanocomposites is verified by X-ray diffraction spectroscopic (XRD) analysis. The investigation of the catalytic efficiency for degradation and reduction of various organic dyes is carried out on nanoparticles and nanocomposites. Thorough examination and comparison of parameters, such as apparent rate constant (kapp), reduction time, percentage reduction, reduced concentration and half-life, are conducted for all substrates. The nanocomposites show greater efficiency than nanoparticles in both reactions: catalytic reduction and catalytic degradation.

The impact of diabetes mellitus on the emergence of multi-drug resistant tuberculosis and treatment failure in TB-diabetes comorbid patients: a systematic review and meta-analysis.

Background: The existence of Type 2 Diabetes Mellitus (DM) in tuberculosis (TB) patients is very dangerous for the health of patients. One of the major concerns is the emergence of MDR-TB in such patients. It is suspected that the development of MDR-TB further worsens the treatment outcomes of TB such as treatment failure and thus, causes disease progression. Aim: To investigate the impact of DM on the Emergence of MDR-TB and Treatment Failure in TB-DM comorbid patients. Methodology: The PubMed database was systematically searched until April 03, 2022 (date last searched). Thirty studies met the inclusion criteria and were included in this study after a proper selection process. Results: Tuberculosis-Diabetes Mellitus patients were at higher risk to develop MDR-TB as compared to TB-non-DM patients (HR 0.81, 95% CI: 0.60-0.96, p < 0.001). Heterogeneity observed among included studies was moderate (I2 = 38%). No significant change was observed in the results after sub-group analysis by study design (HR 0.81, 95% CI: 0.61-0.96, p < 0.000). In the case of treatment failure, TB-DM patients were at higher risk to experience treatment failure rates as compared to TB-non-DM patients (HR 0.46, 95% CI: 0.27-0.67, p < 0.001). Conclusion: The results showed that DM had a significant impact on the emergence of MDR-TB in TB-diabetes comorbid patients as compared to TB-non-DM patients. DM enhanced the risk of TB treatment failure rates in TB-diabetes patients as compared to TB-non-DM patients. Our study highlights the need for earlier screening of MDR-TB, thorough MDR-TB monitoring, and designing proper and effective treatment strategies to prevent disease progression.

Calcium l-Malate and d-Tartarate Frameworks as Adjuvants for the Sustainable Delivery of a Fungicide.

Agrichemical adjuvants that combine a highly selective, efficient, and active mode of operation are critically needed to realize a more sustainable approach to their usage. Herein, we report the synthesis and full characterization of two new metal-organic frameworks (MOFs), termed UPMOF-1 and UPMOF-2, that were constructed from eco-friendly Ca2+ ions and naturally occurring, low-molecular weight plant acids, l-malic and d-tartaric acid, respectively. Upon structural elucidation of both MOFs, a widely used fungicide, hexaconazole (Hex), was loaded on the structures, reaching binding affinities of -5.0 and -3.5 kcal mol-1 and loading capacities of 63% and 62% for Hex@UPMOF-1 and Hex@UPMOF-2, respectively, as a result of the formation of stable host-guest interactions. Given the framework chemistry of the MOFs and their predisposition to disassembly under relevant agricultural conditions, the sustained release kinetics were determined to show nearly quantitative release (98% and 95% for Hex@UPMOF-1 and Hex@UPMOF-2, respectively) after >500 h, a release profile drastically different than the control (>80% release in 24 h), from which the high efficiency of these new systems was established. To confirm their high selectivity and activity, in vitro and in vivo studies were performed to illustrate the abilities of Hex@UPMOF-1 and Hex@UPMOF-2 to combat the known aggressive pathogen Ganoderma boninense that causes basal stem rot disease in oil palm. Accordingly, at an extremely low concentration of 0.05 µg mL-1, both Hex@UPMOF-1 and Hex@UPMOF-2 were demonstrated to completely inhibit (100%) G. boninense growth, and during a 26 week in vivo nursery trial, the progression of basal stem rot infection was completely halted upon treatment with Hex@UPMOF-1 and Hex@UPMOF-2 and seedling growth was accelerated given the additional nutrients supplied via the disassembly of the MOFs. This study represents a significant step forward in the design of adjuvants to support the environmentally responsible use of agrichemical crop protection.

NEWSPAPER-REPORTING ON SUICIDES DURING THE COVID-19 LOCKDOWN IN PAKISTAN: A CONTENT ANALYSIS.

BACKGROUND: Suicide is a social relevant issue and a leading cause of deaths in the world; it has been reported that COVID-19 has significantly increased the rate of suicide worldwide. This study aimed to review media reporting on suicide cases occurred in Pakistan during the COVID-19 lockdown. SUBJECTS AND METHODS: A content analysis has been performed considering the electronic version of the daily Kawish newspaper reporting suicide cases from March to August 2020 in Pakistan. RESULTS: A total of 213 news regarding suicide in Pakistan during the lockdown period were identified. Suicide committers reported age ranging 19-30 years old, and the majority of them were males (74%). Suicide methods ranged as following: harmful practices (79%) > hanging (37%) > self-poisoning (28%). Factors associated to the risk of suicide were: familial discords (36%), poverty (21%) and joblessness (14%). CONCLUSION: Findings of this study have shown that pandemic lockdown in Pakistan have increased the number of factors, such as family issues, unemployment and poverty, leading to suicide especially in young males. The report of suicides may have an impact on the public general opinion and a responsible news-reporting is needed by press agencies and media.

Factors Influencing Despair, Self-blame, and Acceptance Among Parents of Children with Autism Spectrum Disorder (ASD): A Malaysian Perspective.

PURPOSE: Accepting and adapting to the child's diagnosis of Autism Spectrum Disorder (ASD) can be challenging for parents. We aimed to assess domains of parental adjustment namely despair, self-blame, and acceptance among parents whose children were diagnosed with ASD. METHODS: A cross-sectional study was conducted among 111 parents of children with autism who attended Child and Adolescent Psychiatry Unit (CAPU), in a university teaching hospital in Kuala Lumpur, Malaysia. Sociodemographic profiles of both parents and children were gathered. Parental adjustment focusing on parental self-blame, despair and acceptance were assessed using self-reported questionnaires namely Adjustment to the Diagnosis of Autism (ADA). RESULTS: Higher level of despair was associated with parents who have medical illness (ß = 0.214, p = 0.016) and children who received antipsychotic medications (ß = 0.329, p < 0.001). Parents with tertiary education (ß = -0.207, p = 0.023) and those with autistic child attended school (ß = -0.200, p = 0.037) have lower level of despair. Parents with medical illness (ß = 0.245, p = 0.008), child receiving antipsychotic medications (ß = 0.251, p = 0.005), Chinese ethnicity (ß = 0.185, p = 0.04), and child's gender (ß = 0.283, p = 0.003) were significantly associated with higher level of self-blame. Lower acceptance was found among Chinese parents (ß = -0.264, p = 0.005) while married parents had higher acceptance levels (ß = 0.215, p = 0.022). CONCLUSION: Parental adjustment involving domains of despair, self-blame, and acceptance were significantly associated with ethnicity of parents, educational level, parents' marital status and medical illness, as well as the ASD children's schooling status and type of medications used.

Membership inference attack on differentially private block coordinate descent.

The extraordinary success of deep learning is made possible due to the availability of crowd-sourced large-scale training datasets. Mostly, these datasets contain personal and confidential information, thus, have great potential of being misused, raising privacy concerns. Consequently, privacy-preserving deep learning has become a primary research interest nowadays. One of the prominent approaches adopted to prevent the leakage of sensitive information about the training data is by implementing differential privacy during training for their differentially private training, which aims to preserve the privacy of deep learning models. Though these models are claimed to be a safeguard against privacy attacks targeting sensitive information, however, least amount of work is found in the literature to practically evaluate their capability by performing a sophisticated attack model on them. Recently, DP-BCD is proposed as an alternative to state-of-the-art DP-SGD, to preserve the privacy of deep-learning models, having low privacy cost and fast convergence speed with highly accurate prediction results. To check its practical capability, in this article, we analytically evaluate the impact of a sophisticated privacy attack called the membership inference attack against it in both black box as well as white box settings. More precisely, we inspect how much information can be inferred from a differentially private deep model's training data. We evaluate our experiments on benchmark datasets using AUC, attacker advantage, precision, recall, and F1-score performance metrics. The experimental results exhibit that DP-BCD keeps its promise to preserve privacy against strong adversaries while providing acceptable model utility compared to state-of-the-art techniques.

Interpersonal psychotherapy for traumatic grief following a loss due to COVID-19: a case report.

Interpersonal psychotherapy (IPT) is a highly regarded evidence-based psychotherapy that aims to alleviate the suffering of clients and improve their interpersonal functioning. Research has demonstrated the effectiveness of IPT in depressive, bipolar and eating disorders. IPT also focuses on grief and loss as a problem area to help clients address and process their grief symptoms, leading them to reach a phase of finding meaning. However, traumatic grief which is characterized by someone who has both symptoms of trauma and grief can further complicate treatment. As for Posttraumatic Stress Disorder (PTSD), IPT can be a choice of treatment by addressing perceived isolation and emotional dysregulation through mobilizing adequate social support. This case study highlights the efficacy of IPT in treating complicated grief with traumatic experiences caused by the loss of a loved one during the COVID-19 pandemic, without undergoing exposure-based therapy. The treatment course consisted of 12 sessions scheduled twice weekly, and the client received antidepressant medication augmented with antipsychotic medication. After undergoing IPT, the client experienced an improvement in symptoms, gradual recovery of functional disability, and more meaningful interpersonal relationships. The case study presented provides evidence to suggest that IPT is a promising treatment approach for individuals struggling with trauma related to grief.